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Yoo D, Rhie A, Hebbar P, Antonacci F, Logsdon GA, Solar SJ, Antipov D, Pickett BD, Safonova Y, Montinaro F, Luo Y, Malukiewicz J, Storer JM, Lin J, Sequeira AN, Mangan RJ, Hickey G, Monfort Anez G, Balachandran P, Bankevich A, Beck CR, Biddanda A, Borchers M, Bouffard GG, Brannan E, Brooks SY, Carbone L, Carrel L, Chan AP, Crawford J, Diekhans M, Engelbrecht E, Feschotte C, Formenti G, Garcia GH, de Gennaro L, Gilbert D, Green RE, Guarracino A, Gupta I, Haddad D, Han J, Harris RS, Hartley GA, Harvey WT, Hiller M, Hoekzema K, Houck ML, Jeong H, Kamali K, Kellis M, Kille B, Lee C, Lee Y, Lees W, Lewis AP, Li Q, Loftus M, Loh YHE, Loucks H, Ma J, Mao Y, Martinez JFI, Masterson P, McCoy RC, McGrath B, McKinney S, Meyer BS, Miga KH, Mohanty SK, Munson KM, Pal K, Pennell M, Pevzner PA, Porubsky D, Potapova T, Ringeling FR, Rocha JL, Ryder OA, Sacco S, Saha S, Sasaki T, Schatz MC, Schork NJ, Shanks C, Smeds L, Son DR, Steiner C, Sweeten AP, Tassia MG, Thibaud-Nissen F, Torres-González E, Trivedi M, Wei W, Wertz J, Yang M, Zhang P, Zhang S, Zhang Y, Zhang Z, et alYoo D, Rhie A, Hebbar P, Antonacci F, Logsdon GA, Solar SJ, Antipov D, Pickett BD, Safonova Y, Montinaro F, Luo Y, Malukiewicz J, Storer JM, Lin J, Sequeira AN, Mangan RJ, Hickey G, Monfort Anez G, Balachandran P, Bankevich A, Beck CR, Biddanda A, Borchers M, Bouffard GG, Brannan E, Brooks SY, Carbone L, Carrel L, Chan AP, Crawford J, Diekhans M, Engelbrecht E, Feschotte C, Formenti G, Garcia GH, de Gennaro L, Gilbert D, Green RE, Guarracino A, Gupta I, Haddad D, Han J, Harris RS, Hartley GA, Harvey WT, Hiller M, Hoekzema K, Houck ML, Jeong H, Kamali K, Kellis M, Kille B, Lee C, Lee Y, Lees W, Lewis AP, Li Q, Loftus M, Loh YHE, Loucks H, Ma J, Mao Y, Martinez JFI, Masterson P, McCoy RC, McGrath B, McKinney S, Meyer BS, Miga KH, Mohanty SK, Munson KM, Pal K, Pennell M, Pevzner PA, Porubsky D, Potapova T, Ringeling FR, Rocha JL, Ryder OA, Sacco S, Saha S, Sasaki T, Schatz MC, Schork NJ, Shanks C, Smeds L, Son DR, Steiner C, Sweeten AP, Tassia MG, Thibaud-Nissen F, Torres-González E, Trivedi M, Wei W, Wertz J, Yang M, Zhang P, Zhang S, Zhang Y, Zhang Z, Zhao SA, Zhu Y, Jarvis ED, Gerton JL, Rivas-González I, Paten B, Szpiech ZA, Huber CD, Lenz TL, Konkel MK, Yi SV, Canzar S, Watson CT, Sudmant PH, Molloy E, Garrison E, Lowe CB, Ventura M, O'Neill RJ, Koren S, Makova KD, Phillippy AM, Eichler EE. Complete sequencing of ape genomes. Nature 2025; 641:401-418. [PMID: 40205052 PMCID: PMC12058530 DOI: 10.1038/s41586-025-08816-3] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2024] [Accepted: 02/19/2025] [Indexed: 04/11/2025]
Abstract
The most dynamic and repetitive regions of great ape genomes have traditionally been excluded from comparative studies1-3. Consequently, our understanding of the evolution of our species is incomplete. Here we present haplotype-resolved reference genomes and comparative analyses of six ape species: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan and siamang. We achieve chromosome-level contiguity with substantial sequence accuracy (<1 error in 2.7 megabases) and completely sequence 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, to provide in-depth evolutionary insights. Comparative analyses enabled investigations of the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference genome. Such regions include newly minted gene families in lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes and subterminal heterochromatin. This resource serves as a comprehensive baseline for future evolutionary studies of humans and our closest living ape relatives.
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Affiliation(s)
- DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Prajna Hebbar
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Francesca Antonacci
- Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, Italy
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven J Solar
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dmitry Antipov
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Brandon D Pickett
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yana Safonova
- Computer Science and Engineering Department, Huck Institutes of Life Sciences, Pennsylvania State University, State College, PA, USA
| | - Francesco Montinaro
- Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, Italy
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yanting Luo
- Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC, USA
| | - Joanna Malukiewicz
- Research Unit for Evolutionary Immunogenomics, Department of Biology, University of Hamburg, Hamburg, Germany
- German Primate Center, Primate Genetics Laboratory, Goettingen, Germany
| | - Jessica M Storer
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
| | - Jiadong Lin
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Riley J Mangan
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Genetics Training Program, Harvard Medical School, Boston, MA, USA
| | - Glenn Hickey
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | | | - Anton Bankevich
- Computer Science and Engineering Department, Huck Institutes of Life Sciences, Pennsylvania State University, State College, PA, USA
| | - Christine R Beck
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, USA
| | - Arjun Biddanda
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | | | - Gerard G Bouffard
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Emry Brannan
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Shelise Y Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lucia Carbone
- Department of Medicine, KCVI, Oregon Health Sciences University, Portland, OR, USA
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA
| | - Laura Carrel
- PSU Medical School, Penn State University School of Medicine, Hershey, PA, USA
| | - Agnes P Chan
- The Translational Genomics Research Institute, City of Hope National Medical Center, Phoenix, AZ, USA
| | - Juyun Crawford
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Eric Engelbrecht
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, USA
| | - Cedric Feschotte
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | - Giulio Formenti
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Gage H Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Luciana de Gennaro
- Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, Italy
| | - David Gilbert
- San Diego Biomedical Research Institute, San Diego, CA, USA
| | - Richard E Green
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Ishaan Gupta
- Department of Computer Science and Engineering, University of California, San Diego, San Diego, CA, USA
| | - Diana Haddad
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Junmin Han
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Robert S Harris
- Department of Biology, Penn State University, University Park, PA, USA
| | | | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Michael Hiller
- LOEWE Centre for Translational Biodiversity Genomics, Frankfurt, Germany
- Senckenberg Research Institute, Frankfurt, Germany
- Institute of Cell Biology and Neuroscience, Faculty of Biosciences, Goethe University Frankfurt, Frankfurt, Germany
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kaivan Kamali
- Department of Biology, Penn State University, University Park, PA, USA
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bryce Kille
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Chul Lee
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA
| | - Youngho Lee
- Laboratory of Bioinformatics and Population Genetics, Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - William Lees
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, USA
- Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Qiuhui Li
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Mark Loftus
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC, USA
- Center for Human Genetics, Clemson University, Greenwood, SC, USA
| | - Yong Hwee Eddie Loh
- Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Hailey Loucks
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Jian Ma
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Yafei Mao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- Center for Genomic Research, International Institutes of Medicine, Fourth Affiliated Hospital, Zhejiang University, Yiwu, China
- Shanghai Jiao Tong University Chongqing Research Institute, Chongqing, China
| | - Juan F I Martinez
- Computer Science and Engineering Department, Huck Institutes of Life Sciences, Pennsylvania State University, State College, PA, USA
| | - Patrick Masterson
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Barbara McGrath
- Department of Biology, Penn State University, University Park, PA, USA
| | - Sean McKinney
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Britta S Meyer
- Research Unit for Evolutionary Immunogenomics, Department of Biology, University of Hamburg, Hamburg, Germany
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Saswat K Mohanty
- Department of Biology, Penn State University, University Park, PA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Karol Pal
- Department of Biology, Penn State University, University Park, PA, USA
| | - Matt Pennell
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Pavel A Pevzner
- Department of Computer Science and Engineering, University of California, San Diego, San Diego, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Francisca R Ringeling
- Faculty of Informatics and Data Science, University of Regensburg, Regensburg, Germany
| | - Joana L Rocha
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, USA
| | | | - Samuel Sacco
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Swati Saha
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, USA
| | - Takayo Sasaki
- San Diego Biomedical Research Institute, San Diego, CA, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Nicholas J Schork
- The Translational Genomics Research Institute, City of Hope National Medical Center, Phoenix, AZ, USA
| | - Cole Shanks
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Linnéa Smeds
- Department of Biology, Penn State University, University Park, PA, USA
| | - Dongmin R Son
- Department of Ecology, Evolution and Marine Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA
| | | | - Alexander P Sweeten
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael G Tassia
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | | | - Mihir Trivedi
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Wenjie Wei
- School of Life Sciences, Westlake University, Hangzhou, China
- National Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Julie Wertz
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Muyu Yang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Panpan Zhang
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yang Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Zhenmiao Zhang
- Department of Computer Science and Engineering, University of California, San Diego, San Diego, CA, USA
| | - Sarah A Zhao
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yixin Zhu
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Erich D Jarvis
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | | | - Iker Rivas-González
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Zachary A Szpiech
- Department of Biology, Penn State University, University Park, PA, USA
| | - Christian D Huber
- Department of Biology, Penn State University, University Park, PA, USA
| | - Tobias L Lenz
- Research Unit for Evolutionary Immunogenomics, Department of Biology, University of Hamburg, Hamburg, Germany
| | - Miriam K Konkel
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC, USA
- Center for Human Genetics, Clemson University, Greenwood, SC, USA
| | - Soojin V Yi
- Department of Ecology, Evolution and Marine Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA
- Department of Molecular, Cellular and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Stefan Canzar
- Faculty of Informatics and Data Science, University of Regensburg, Regensburg, Germany
| | - Corey T Watson
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, USA
| | - Peter H Sudmant
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Erin Molloy
- Department of Computer Science, University of Maryland, College Park, MD, USA
| | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Craig B Lowe
- Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC, USA
| | - Mario Ventura
- Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, Italy
| | - Rachel J O'Neill
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Sergey Koren
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kateryna D Makova
- Department of Biology, Penn State University, University Park, PA, USA.
| | - Adam M Phillippy
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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2
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Zhang ZE, Kim A, Suboc N, Mancuso N, Gazal S. Efficient count-based models improve power and robustness for large-scale single-cell eQTL mapping. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.01.18.25320755. [PMID: 40093202 PMCID: PMC11908335 DOI: 10.1101/2025.01.18.25320755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 03/19/2025]
Abstract
Population-scale single-cell transcriptomic technologies (scRNA-seq) enable characterizing variant effects on gene regulation at the cellular level (e.g., single-cell eQTLs; sc-eQTLs). However, existing sc-eQTL mapping approaches are either not designed for analyzing sparse counts in scRNA-seq data or can become intractable in extremely large datasets. Here, we propose jaxQTL, a flexible and efficient sc-eQTL mapping framework using highly efficient count-based models given pseudobulk data. Using extensive simulations, we demonstrated that jaxQTL with a negative binomial model outperformed other models in identifying sc-eQTLs, while maintaining a calibrated type I error. We applied jaxQTL across 14 cell types of OneK1K scRNA-seq data (N=982), and identified 11-16% more eGenes compared with existing approaches, primarily driven by jaxQTL ability to identify lowly expressed eGenes. We observed that fine-mapped sc-eQTLs were further from transcription starting site (TSS) than fine-mapped eQTLs identified in all cells (bulk-eQTLs; P=1x10-4) and more enriched in cell-type-specific enhancers (P=3x10-10), suggesting that sc-eQTLs improve our ability to identify distal eQTLs that are missed in bulk tissues. Overall, the genetic effect of fine-mapped sc-eQTLs were largely shared across cell types, with cell-type-specificity increasing with distance to TSS. Lastly, we observed that sc-eQTLs explain more SNP-heritability (h2 ) than bulk-eQTLs (9.90 ± 0.88% vs. 6.10 ± 0.76% when meta-analyzed across 16 blood and immune-related traits), improving but not closing the missing link between GWAS and eQTLs. As an example, we highlight that sc-eQTLs in T cells (unlike bulk-eQTLs) can successfully nominate IL6ST as a candidate gene for rheumatoid arthritis. Overall, jaxQTL provides an efficient and powerful approach using count-based models to identify missing disease-associated eQTLs.
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Affiliation(s)
- Zixuan Eleanor Zhang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Artem Kim
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Noah Suboc
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
- Department of Quantitative and Computational Biology, University of Southern California
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California
| | - Steven Gazal
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
- Department of Quantitative and Computational Biology, University of Southern California
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California
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Dishuck PC, Munson KM, Lewis AP, Dougherty ML, Underwood JG, Harvey WT, Hsieh P, Pastinen T, Eichler EE. Structural variation, selection, and diversification of the NPIP gene family from the human pangenome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.04.636496. [PMID: 39975192 PMCID: PMC11838601 DOI: 10.1101/2025.02.04.636496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
The NPIP (nuclear pore interacting protein) gene family has expanded to high copy number in humans and African apes where it has been subject to an excess of amino acid replacement consistent with positive selection (1). Due to the limitations of short-read sequencing, NPIP human genetic diversity has been poorly understood. Using highly accurate assemblies generated from long-read sequencing as part of the human pangenome, we completely characterize 169 human haplotypes (4,665 NPIP paralogs and alleles). Of the 28 NPIP paralogs, just three (NPIPB2, B11, and B14) are fixed at a single copy, and only a single locus, B2, shows no structural variation. Four NPIP paralogs map to large segmental duplication blocks that mediate polymorphic inversions (355 kbp-1.6 Mbp) corresponding to microdeletions associated with developmental delay and autism. Haplotype-based tests of positive selection and selective sweeps identify two paralogs, B9 and B15, within the top percentile for both tests. Using full-length cDNA data from 101 tissue/cell types, we construct paralog-specific gene models and show that 56% (31/55 most abundant isoforms) have not been previously described in RefSeq. We define six distinct translation start sites and other protein structural features that distinguish paralogs, including a variable number tandem repeat that encodes a beta helix of variable size that emerged ~3.1 million years ago in human evolution. Among the 28 NPIP paralogs, we identify distinct tissue and developmental patterns of expression with only a few maintaining the ancestral testis-enriched expression. A subset of paralogs (NPIPA1, A5, A6-9, B3-5, and B12/B13) show increased brain expression. Our results suggest ongoing positive selection in the human population and rapid diversification of NPIP gene models.
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Affiliation(s)
- Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P. Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Max L. Dougherty
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Present address: Tisch Cancer Institute, Division of Hematology and Medical Oncology, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jason G. Underwood
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Pacific Biosciences (PacBio) of California, Incorporated, Menlo Park, CA, USA
| | - William T. Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genetics, Cell Biology, and Development, Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
| | - Tomi Pastinen
- Genomic Medicine Center, Department of Pediatrics, Children’s Mercy Kansas City, Kansas City, KS, USA
- UMKC School of Medicine, University of Missouri, Kansas City, Kansas City, KS, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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Singh S, Khan S, Shahid M, Sardar M, Hassan MI, Islam A. Targeting tau in Alzheimer's and beyond: Insights into pathology and therapeutic strategies. Ageing Res Rev 2025; 104:102639. [PMID: 39674375 DOI: 10.1016/j.arr.2024.102639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2024] [Revised: 12/04/2024] [Accepted: 12/08/2024] [Indexed: 12/16/2024]
Abstract
Tauopathies encompass a group of approximately 20 neurodegenerative diseases characterized by the accumulation of the microtubule-associated protein tau in brain neurons. The pathogenesis of intracellular neurofibrillary tangles, a hallmark of tauopathies, is initiated by hyperphosphorylated tau protein isoforms that cause neuronal death and lead to diseases like Alzheimer's, Parkinson's disease, frontotemporal dementia, and other complex neurodegenerative diseases. Current applications of tau biomarkers, including imaging, cerebrospinal fluid, and blood-based assays, assist in the evaluation and diagnosis of tauopathies. Emerging research is providing various potential strategies to prevent cellular toxicity caused by tau aggregation such as: 1) suppressing toxic tau aggregation, 2) preventing post-translational modifications of tau, 3) stabilizing microtubules and 4) designing tau-directed immunogens. This review aims to discuss the role of tau in tauopathies along with neuropathological features of the different tauopathies and the new developments in treating tau aggregation with the therapeutics for treating and possibly preventing tauopathies.
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Affiliation(s)
- Sunidhi Singh
- Department of Biosciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Sumaiya Khan
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Mohammad Shahid
- Department of Basic Medical Sciences, College of Medicine, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
| | - Meryam Sardar
- Department of Biosciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Md Imtaiyaz Hassan
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Asimul Islam
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India.
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5
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Jeong H, Dishuck PC, Yoo D, Harvey WT, Munson KM, Lewis AP, Kordosky J, Garcia GH, Human Genome Structural Variation Consortium (HGSVC), Yilmaz F, Hallast P, Lee C, Pastinen T, Eichler EE. Structural polymorphism and diversity of human segmental duplications. Nat Genet 2025; 57:390-401. [PMID: 39779957 PMCID: PMC11821543 DOI: 10.1038/s41588-024-02051-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 12/04/2024] [Indexed: 01/11/2025]
Abstract
Segmental duplications (SDs) contribute significantly to human disease, evolution and diversity but have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies (from 85 samples representing 38 Africans and 47 non-Africans) in which the majority of autosomal SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms and sex chromosomes, we identify 173.2 Mb of duplicated sequence (47.4 Mb not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable, with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy numbers than non-African samples. Comparison to a resource of 563 million full-length isoform sequencing reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.
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Affiliation(s)
- Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Altos Labs, San Diego, CA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Tomi Pastinen
- Children's Mercy Hospital and University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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6
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Shimada MK, Nishida T. Haplotype-Based Approach Represents Locus Specificity in the Genomic Diversification Process in Humans ( Homo sapiens). Genes (Basel) 2024; 15:1554. [PMID: 39766821 PMCID: PMC11675571 DOI: 10.3390/genes15121554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Revised: 11/23/2024] [Accepted: 11/25/2024] [Indexed: 01/11/2025] Open
Abstract
BACKGROUND/OBJECTIVES Recent progress in evolutionary genomics on human (Homo sapiens) populations has revealed complex demographic events and genomic changes. These include population expansion with complicated migration, substantial population structure, and ancient introgression from other hominins, as well as human characteristics selections. Nevertheless, the genomic regions in which such evolutionary events took place have remained unclear. METHODS Here, we focused on eight loci containing the haplotypes that were previously presented as atypical for the mutation pattern in sequence and/or geographic distribution pattern with the model of recent African origin, which constitute two major clusters: African only, and global. This was the consensus model before information regarding introgression from Neanderthal (Homo neanderthalensis) was available. We compared diversity in identical datasets of the modern human population genome, with the 1000 Genomes project among them. RESULTS/CONCLUSIONS This study identified representative genomic regions that show traces of various demographic events and genomic changes that modern humans have undergone by categorizing the relationships in sequence similarity and in worldwide geographic distribution among haplotypes.
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Affiliation(s)
- Makoto K. Shimada
- Center for Medical Science, Fujita Health University, Toyoake 470-1192, Aichi, Japan
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7
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Jamsandekar M, Ferreira MS, Pettersson ME, Farrell ED, Davis BW, Andersson L. The origin and maintenance of supergenes contributing to ecological adaptation in Atlantic herring. Nat Commun 2024; 15:9136. [PMID: 39443489 PMCID: PMC11499932 DOI: 10.1038/s41467-024-53079-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 09/26/2024] [Indexed: 10/25/2024] Open
Abstract
Chromosomal inversions are associated with local adaptation in many species. However, questions regarding how they are formed, maintained and impact various other evolutionary processes remain elusive. Here, using a large genomic dataset of long-read and short-read sequencing, we ask these questions in one of the most abundant vertebrates on Earth, the Atlantic herring. This species has four megabase-sized inversions associated with ecological adaptation that correlate with water temperature. The S and N inversion alleles at these four loci dominate in the southern and northern parts, respectively, of the species distribution in the North Atlantic Ocean. By determining breakpoint coordinates of the four inversions and the structural variations surrounding them, we hypothesize that these inversions are formed by ectopic recombination between duplicated sequences immediately outside of the inversions. We show that these are old inversions (>1 MY), albeit formed after the split between the Atlantic herring and its sister species, the Pacific herring. There is evidence for extensive gene flux between inversion alleles at all four loci. The large Ne of herring combined with the common occurrence of opposite homozygotes across the species distribution has allowed effective purifying selection to prevent the accumulation of genetic load and repeats within the inversions.
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Affiliation(s)
- Minal Jamsandekar
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, USA
| | - Mafalda S Ferreira
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Mats E Pettersson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | | | - Brian W Davis
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, USA
| | - Leif Andersson
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, USA.
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
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8
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Yoo D, Rhie A, Hebbar P, Antonacci F, Logsdon GA, Solar SJ, Antipov D, Pickett BD, Safonova Y, Montinaro F, Luo Y, Malukiewicz J, Storer JM, Lin J, Sequeira AN, Mangan RJ, Hickey G, Anez GM, Balachandran P, Bankevich A, Beck CR, Biddanda A, Borchers M, Bouffard GG, Brannan E, Brooks SY, Carbone L, Carrel L, Chan AP, Crawford J, Diekhans M, Engelbrecht E, Feschotte C, Formenti G, Garcia GH, de Gennaro L, Gilbert D, Green RE, Guarracino A, Gupta I, Haddad D, Han J, Harris RS, Hartley GA, Harvey WT, Hiller M, Hoekzema K, Houck ML, Jeong H, Kamali K, Kellis M, Kille B, Lee C, Lee Y, Lees W, Lewis AP, Li Q, Loftus M, Loh YHE, Loucks H, Ma J, Mao Y, Martinez JFI, Masterson P, McCoy RC, McGrath B, McKinney S, Meyer BS, Miga KH, Mohanty SK, Munson KM, Pal K, Pennell M, Pevzner PA, Porubsky D, Potapova T, Ringeling FR, Roha JL, Ryder OA, Sacco S, Saha S, Sasaki T, Schatz MC, Schork NJ, Shanks C, Smeds L, Son DR, Steiner C, Sweeten AP, Tassia MG, Thibaud-Nissen F, Torres-González E, Trivedi M, Wei W, Wertz J, Yang M, Zhang P, Zhang S, Zhang Y, Zhang Z, et alYoo D, Rhie A, Hebbar P, Antonacci F, Logsdon GA, Solar SJ, Antipov D, Pickett BD, Safonova Y, Montinaro F, Luo Y, Malukiewicz J, Storer JM, Lin J, Sequeira AN, Mangan RJ, Hickey G, Anez GM, Balachandran P, Bankevich A, Beck CR, Biddanda A, Borchers M, Bouffard GG, Brannan E, Brooks SY, Carbone L, Carrel L, Chan AP, Crawford J, Diekhans M, Engelbrecht E, Feschotte C, Formenti G, Garcia GH, de Gennaro L, Gilbert D, Green RE, Guarracino A, Gupta I, Haddad D, Han J, Harris RS, Hartley GA, Harvey WT, Hiller M, Hoekzema K, Houck ML, Jeong H, Kamali K, Kellis M, Kille B, Lee C, Lee Y, Lees W, Lewis AP, Li Q, Loftus M, Loh YHE, Loucks H, Ma J, Mao Y, Martinez JFI, Masterson P, McCoy RC, McGrath B, McKinney S, Meyer BS, Miga KH, Mohanty SK, Munson KM, Pal K, Pennell M, Pevzner PA, Porubsky D, Potapova T, Ringeling FR, Roha JL, Ryder OA, Sacco S, Saha S, Sasaki T, Schatz MC, Schork NJ, Shanks C, Smeds L, Son DR, Steiner C, Sweeten AP, Tassia MG, Thibaud-Nissen F, Torres-González E, Trivedi M, Wei W, Wertz J, Yang M, Zhang P, Zhang S, Zhang Y, Zhang Z, Zhao SA, Zhu Y, Jarvis ED, Gerton JL, Rivas-González I, Paten B, Szpiech ZA, Huber CD, Lenz TL, Konkel MK, Yi SV, Canzar S, Watson CT, Sudmant PH, Molloy E, Garrison E, Lowe CB, Ventura M, O’Neill RJ, Koren S, Makova KD, Phillippy AM, Eichler EE. Complete sequencing of ape genomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.31.605654. [PMID: 39131277 PMCID: PMC11312596 DOI: 10.1101/2024.07.31.605654] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
We present haplotype-resolved reference genomes and comparative analyses of six ape species, namely: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan, and siamang. We achieve chromosome-level contiguity with unparalleled sequence accuracy (<1 error in 500,000 base pairs), completely sequencing 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, providing more in-depth evolutionary insights. Comparative analyses, including human, allow us to investigate the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference. This includes newly minted gene families within lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes, and subterminal heterochromatin. This resource should serve as a definitive baseline for all future evolutionary studies of humans and our closest living ape relatives.
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Affiliation(s)
- DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Prajna Hebbar
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | - Francesca Antonacci
- Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, 70124, Italy
| | - Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19103, USA
| | - Steven J. Solar
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Dmitry Antipov
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Brandon D. Pickett
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Yana Safonova
- Computer Science and Engineering Department, Huck Institutes of Life Sciences, Pennsylvania State University, State College, PA 16801, USA
| | - Francesco Montinaro
- Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, 70124, Italy
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yanting Luo
- Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Joanna Malukiewicz
- Research Unit for Evolutionary Immunogenomics, Department of Biology, University of Hamburg, 20146 Hamburg, Germany
| | - Jessica M. Storer
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269, USA
| | - Jiadong Lin
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Abigail N. Sequeira
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Riley J. Mangan
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Genetics Training Program, Harvard Medical School, Boston, MA 02115, USA
| | - Glenn Hickey
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | | | | | - Anton Bankevich
- Computer Science and Engineering Department, Huck Institutes of Life Sciences, Pennsylvania State University, State College, PA 16801, USA
| | - Christine R. Beck
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269, USA
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, USA
| | - Arjun Biddanda
- Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Matthew Borchers
- Stowers Institute for Medical Research, Kansas City, MO 64110, USA
| | - Gerard G. Bouffard
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Emry Brannan
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Shelise Y. Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lucia Carbone
- Department of Medicine, KCVI, Oregon Health Sciences University, Portland, OR, USA
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA
| | - Laura Carrel
- PSU Medical School, Penn State University School of Medicine, Hershey, PA, USA
| | - Agnes P. Chan
- The Translational Genomics Research Institute, a part of the City of Hope National Medical Center, Phoenix, AZ, USA
| | - Juyun Crawford
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | - Eric Engelbrecht
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, USA
| | - Cedric Feschotte
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Giulio Formenti
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY 10021, USA
| | - Gage H. Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Luciana de Gennaro
- Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, 70124, Italy
| | - David Gilbert
- San Diego Biomedical Research Institute, San Diego, CA, USA
| | | | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Ishaan Gupta
- Department of Computer Science and Engineering, University of California San Diego, CA, USA
| | - Diana Haddad
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Junmin Han
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Robert S. Harris
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269, USA
| | - William T. Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Michael Hiller
- LOEWE Centre for Translational Biodiversity Genomics, Senckenberg Research Institute, Goethe University, Frankfurt, Germany
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marlys L. Houck
- San Diego Zoo Wildlife Alliance, Escondido, CA, 92027-7000, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Kaivan Kamali
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Bryce Kille
- Department of Computer Science, Rice University, Houston, TX 77005, USA
| | - Chul Lee
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA
| | - Youngho Lee
- Laboratory of bioinformatics and population genetics, Interdisciplinary program in bioinformatics, Seoul National University, Republic of Korea
| | - William Lees
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, USA
- Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel
| | - Alexandra P. Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Qiuhui Li
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mark Loftus
- Department of Genetics & Biochemistry, Clemson University, Clemson, SC, USA
- Center for Human Genetics, Clemson University, Greenwood, SC, USA
| | - Yong Hwee Eddie Loh
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Hailey Loucks
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | - Jian Ma
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, PA, USA
| | - Yafei Mao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- Center for Genomic Research, International Institutes of Medicine, Fourth Affiliated Hospital, Zhejiang University, Yiwu, Zhejiang, China
- Shanghai Jiao Tong University Chongqing Research Institute, Chongqing, China
| | - Juan F. I. Martinez
- Computer Science and Engineering Department, Huck Institutes of Life Sciences, Pennsylvania State University, State College, PA 16801, USA
| | - Patrick Masterson
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Barbara McGrath
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Sean McKinney
- Stowers Institute for Medical Research, Kansas City, MO 64110, USA
| | - Britta S. Meyer
- Research Unit for Evolutionary Immunogenomics, Department of Biology, University of Hamburg, 20146 Hamburg, Germany
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | - Saswat K. Mohanty
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Karol Pal
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Matt Pennell
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California San Diego, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO 64110, USA
| | - Francisca R. Ringeling
- Faculty of Informatics and Data Science, University of Regensburg, 93053 Regensburg, Germany
| | - Joana L. Roha
- Department of Integrative Biology, University of California, Berkeley, Berkeley, USA
| | - Oliver A. Ryder
- San Diego Zoo Wildlife Alliance, Escondido, CA, 92027-7000, USA
| | - Samuel Sacco
- University of California Santa Cruz, Santa Cruz, CA, USA
| | - Swati Saha
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, USA
| | - Takayo Sasaki
- San Diego Biomedical Research Institute, San Diego, CA, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Nicholas J. Schork
- The Translational Genomics Research Institute, a part of the City of Hope National Medical Center, Phoenix, AZ, USA
| | - Cole Shanks
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | - Linnéa Smeds
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Dongmin R. Son
- Department of Ecology, Evolution and Marine Biology, Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Cynthia Steiner
- San Diego Zoo Wildlife Alliance, Escondido, CA, 92027-7000, USA
| | - Alexander P. Sweeten
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Michael G. Tassia
- Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | | | - Mihir Trivedi
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Wenjie Wei
- School of Life Sciences, Westlake University, Hangzhou 310024, China
- National Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, 430070, Wuhan, China
| | - Julie Wertz
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Muyu Yang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, PA, USA
| | - Panpan Zhang
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yang Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, PA, USA
| | - Zhenmiao Zhang
- Department of Computer Science and Engineering, University of California San Diego, CA, USA
| | - Sarah A. Zhao
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yixin Zhu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Erich D. Jarvis
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | | | - Iker Rivas-González
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | - Zachary A. Szpiech
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Christian D. Huber
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Tobias L. Lenz
- Research Unit for Evolutionary Immunogenomics, Department of Biology, University of Hamburg, 20146 Hamburg, Germany
| | - Miriam K. Konkel
- Department of Genetics & Biochemistry, Clemson University, Clemson, SC, USA
- Center for Human Genetics, Clemson University, Greenwood, SC, USA
| | - Soojin V. Yi
- Department of Ecology, Evolution and Marine Biology, Department of Molecular, Cellular and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Stefan Canzar
- Faculty of Informatics and Data Science, University of Regensburg, 93053 Regensburg, Germany
| | - Corey T. Watson
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, USA
| | - Peter H. Sudmant
- Department of Integrative Biology, University of California, Berkeley, Berkeley, USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, USA
| | - Erin Molloy
- Department of Computer Science, University of Maryland, College Park, MD 20742, USA
| | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Craig B. Lowe
- Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Mario Ventura
- Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, 70124, Italy
| | - Rachel J. O’Neill
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269, USA
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, USA
- Departments of Molecular and Cell Biology, UConn Storrs, CT, USA
| | - Sergey Koren
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kateryna D. Makova
- Department of Biology, Penn State University, University Park, PA 16802, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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9
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Porubsky D, Guitart X, Yoo D, Dishuck PC, Harvey WT, Eichler EE. SVbyEye: A visual tool to characterize structural variation among whole-genome assemblies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.11.612418. [PMID: 39345373 PMCID: PMC11429710 DOI: 10.1101/2024.09.11.612418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Motivation We are now in the era of being able to routinely generate highly contiguous (near telomere-to-telomere) genome assemblies of human and nonhuman species. Complex structural variation and regions of rapid evolutionary turnover are being discovered for the first time. Thus, efficient and informative visualization tools are needed to evaluate and directly observe structural differences between two or more genomes. Results We developed SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex structural variants in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Xavi Guitart
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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10
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Messaoudi M, Pakstis AJ, Ezzaher T, Boussetta S, Ben Ammar Elgaaied A, Kidd KK, Cherni L. Genetic diversity of North African populations in the 17q21 genomic region. Mamm Genome 2024; 35:445-460. [PMID: 38965090 DOI: 10.1007/s00335-024-10051-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 06/28/2024] [Indexed: 07/06/2024]
Abstract
The demographic history of human populations in North Africa has been characterized by complex migration processes that have determined the current genetic structure of these populations. We examined the autosomal markers of eight sampled populations in northern Africa (Tunisia and Libya) to explore their genetic structure and to place them in a global context. We genotyped a set of 30 autosomal single-nucleotide polymorphisms (SNPs) extending 9.5 Mb and encompassing the 17q21 inversion region. Our data include 403 individuals from Tunisia and Libya. To put our populations in the global context, we analyzed our data in comparison with other populations, including those of the 1000 Genomes Project. To evaluate the data, we conducted genetic diversity, principal component, STRUCTURE, and haplotype analyses. The analysis of genetic composition revealed the genetic heterogeneity of North African populations. The principal component and STRUCTURE analyses converged and revealed the intermediate position of North Africans between Europeans and Asians. Haplotypic analysis demonstrated that the normal (H1) and inverted (H2) polymorphisms in the chromosome 17q21 region occur in North Africa at frequencies similar to those found in European and Southwest Asian populations. The results highlight the complex demographic history of North Africa, reflecting the influence of genetic flow from Europe and the Near East that dates to the prehistoric period. These gene flows added to demographic factors (inbreeding, endogamy), natural factors (topography, Sahara), and cultural factors that play a role in the emergence of the diverse and heterogeneous genetic structures of North African populations. This study contributes to a better understanding of the complex structure of North African populations.
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Affiliation(s)
- Mohsen Messaoudi
- Laboratory of Genetics, Immunology and Human Pathologies, Faculty of Sciences of Tunis, University of Tunis El Manar, 2092, Tunis, Tunisia.
| | - Andrew J Pakstis
- Department of Genetics, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Takwa Ezzaher
- Laboratory of Genetics, Immunology and Human Pathologies, Faculty of Sciences of Tunis, University of Tunis El Manar, 2092, Tunis, Tunisia
| | - Sami Boussetta
- Laboratory of Genetics, Immunology and Human Pathologies, Faculty of Sciences of Tunis, University of Tunis El Manar, 2092, Tunis, Tunisia
| | - Amel Ben Ammar Elgaaied
- Laboratory of Genetics, Immunology and Human Pathologies, Faculty of Sciences of Tunis, University of Tunis El Manar, 2092, Tunis, Tunisia
| | - Kenneth K Kidd
- Department of Genetics, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Lotfi Cherni
- Laboratory of Genetics, Immunology and Human Pathologies, Faculty of Sciences of Tunis, University of Tunis El Manar, 2092, Tunis, Tunisia
- Higher Institute of Biotechnology of Monastir, Monastir University, 5000, Monastir, Tunisia
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11
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Ressler HW, Humphrey J, Vialle RA, Babrowicz B, Kandoi S, Raj T, Dickson DW, Ertekin-Taner N, Crary JF, Farrell K. MAPT haplotype-associated transcriptomic changes in progressive supranuclear palsy. Acta Neuropathol Commun 2024; 12:135. [PMID: 39154163 PMCID: PMC11330133 DOI: 10.1186/s40478-024-01839-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 07/28/2024] [Indexed: 08/19/2024] Open
Abstract
Progressive supranuclear palsy (PSP) is a neurodegenerative movement and cognitive disorder characterized by abnormal accumulation of the microtubule-associated protein tau in the brain. Biochemically, inclusions in PSP are enriched for tau proteoforms with four microtubule-binding domain repeats (4R), an isoform that arises from alternative tau pre-mRNA splicing. While preferential aggregation and reduced degradation of 4R tau protein is thought to play a role in inclusion formation and toxicity, an alternative hypothesis is that altered expression of tau mRNA isoforms plays a causal role. This stems from the observation that PSP is associated with common variation in the tau gene (MAPT) at the 17q21.31 locus which contains low copy number repeats flanking a large recurrent genomic inversion. The complex genomic structural changes at the locus give rise to two dominant haplotypes, termed H1 and H2, that have the potential to markedly influence gene expression. Here, we explored haplotype-dependent differences in gene expression using a bulk RNA-seq dataset derived from human post-mortem brain tissue from PSP (n = 84) and controls (n = 77) using a rigorous computational pipeline, including alternative pre-mRNA splicing. We found 3579 differentially expressed genes in the temporal cortex and 10,011 in the cerebellum. We also found 7214 differential splicing events in the temporal cortex and 18,802 in the cerebellum. In the cerebellum, total tau mRNA levels and the proportion of transcripts encoding 4R tau were significantly increased in PSP compared to controls. In the temporal cortex, the proportion of reads that expressed 4R tau was increased in cases compared to controls. 4R tau mRNA levels were significantly associated with the H1 haplotype in the temporal cortex. Further, we observed a marked haplotype-dependent difference in KANSL1 expression that was strongly associated with H1 in both brain regions. These findings support the hypothesis that sporadic PSP is associated with haplotype-dependent increases in 4R tau mRNA that might play a causal role in this disorder.
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Affiliation(s)
- Hadley W Ressler
- Department of Pathology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jack Humphrey
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ricardo A Vialle
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bergan Babrowicz
- Department of Pathology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shrishtee Kandoi
- Department of Pathology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Towfique Raj
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | | | - John F Crary
- Department of Pathology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA.
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Kurt Farrell
- Department of Pathology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA.
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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12
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Recinos Y, Bao S, Wang X, Phillips BL, Yeh YT, Weyn-Vanhentenryck SM, Swanson MS, Zhang C. Lineage-specific splicing regulation of MAPT gene in the primate brain. CELL GENOMICS 2024; 4:100563. [PMID: 38772368 PMCID: PMC11228892 DOI: 10.1016/j.xgen.2024.100563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 01/22/2024] [Accepted: 04/23/2024] [Indexed: 05/23/2024]
Abstract
Divergence of precursor messenger RNA (pre-mRNA) alternative splicing (AS) is widespread in mammals, including primates, but the underlying mechanisms and functional impact are poorly understood. Here, we modeled cassette exon inclusion in primate brains as a quantitative trait and identified 1,170 (∼3%) exons with lineage-specific splicing shifts under stabilizing selection. Among them, microtubule-associated protein tau (MAPT) exons 2 and 10 underwent anticorrelated, two-step evolutionary shifts in the catarrhine and hominoid lineages, leading to their present inclusion levels in humans. The developmental-stage-specific divergence of exon 10 splicing, whose dysregulation can cause frontotemporal lobar degeneration (FTLD), is mediated by divergent distal intronic MBNL-binding sites. Competitive binding of these sites by CRISPR-dCas13d/gRNAs effectively reduces exon 10 inclusion, potentially providing a therapeutically compatible approach to modulate tau isoform expression. Our data suggest adaptation of MAPT function and, more generally, a role for AS in the evolutionary expansion of the primate brain.
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Affiliation(s)
- Yocelyn Recinos
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Suying Bao
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Xiaojian Wang
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Brittany L Phillips
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Yow-Tyng Yeh
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Sebastien M Weyn-Vanhentenryck
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Maurice S Swanson
- Department of Molecular Genetics and Microbiology, University of Florida, College of Medicine, Gainesville, FL 32610, USA; Center for NeuroGenetics and the Genetics Institute, University of Florida, College of Medicine, Gainesville, FL 32610, USA
| | - Chaolin Zhang
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA.
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13
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Jeong H, Dishuck PC, Yoo D, Harvey WT, Munson KM, Lewis AP, Kordosky J, Garcia GH, Human Genome Structural Variation Consortium (HGSVC), Yilmaz F, Hallast P, Lee C, Pastinen T, Eichler EE. Structural polymorphism and diversity of human segmental duplications. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.04.597452. [PMID: 38895457 PMCID: PMC11185583 DOI: 10.1101/2024.06.04.597452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Segmental duplications (SDs) contribute significantly to human disease, evolution, and diversity yet have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies where the majority of SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms, we identify 173.2 Mbp of duplicated sequence (47.4 Mbp not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy number when compared to non-African samples. A comparison to a resource of 563 million full-length Iso-Seq reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.
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Affiliation(s)
- Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Altos Labs, San Diego, CA, USA
| | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T. Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P. Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H. Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Tomi Pastinen
- Children’s Mercy Hospital and University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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14
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Mansueto A, Good DJ. Conservation of a Chromosome 8 Inversion and Exon Mutations Confirm Common Gulonolactone Oxidase Gene Evolution Among Primates, Including H. Neanderthalensis. J Mol Evol 2024; 92:266-277. [PMID: 38683367 PMCID: PMC11169010 DOI: 10.1007/s00239-024-10165-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 03/20/2024] [Indexed: 05/01/2024]
Abstract
Ascorbic acid functions as an antioxidant and facilitates other biochemical processes such as collagen triple helix formation, and iron uptake by cells. Animals which endogenously produce ascorbic acid have a functional gulonolactone oxidase gene (GULO); however, humans have a GULO pseudogene (GULOP) and depend on dietary ascorbic acid. In this study, the conservation of GULOP sequences in the primate haplorhini suborder were investigated and compared to the GULO sequences belonging to the primates strepsirrhini suborder. Phylogenetic analysis suggested that the conserved GULOP exons in the haplorhini primates experienced a high rate of mutations following the haplorhini/strepsirrhini divergence. This high mutation rate has decreased during the evolution of the haplorhini primates. Additionally, indels of the haplorhini GULOP sequences were conserved across the suborder. A separate analysis for GULO sequences and well-conserved GULOP sequences focusing on placental mammals identified an in-frame GULO sequence in the Brazilian guinea pig, and a potential GULOP sequence in the pika. Similar to haplorhini primates, the guinea pig and lagomorph species have experienced a high substitution rate when compared to the mammals used in this study. A shared synteny to examine the conservation of local genes near GULO/GULOP identified a conserved inversion around the GULO/GULOP locus between the haplorhini and strepsirrhini primates. Fischer's exact test did not support an association between GULOP and the chromosomal inversion. Mauve alignment showed that the inversion of the length of the syntenic block that the GULO/GULOP genes belonged to was variable. However, there were frequent rearrangements around ~ 2 million base pairs adjacent to GULOP involving the KIF13B and MSRA genes. These data may suggest that genes acquiring deleterious mutations in the coding sequence may respond to these deleterious mutations with rapid substitution rates.
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Affiliation(s)
- Alexander Mansueto
- Department of Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, VA, USA
- Department of Biological Sciences, Vanderbilt University, Nashvile, TN, USA
| | - Deborah J Good
- Department of Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, VA, USA.
- Department of Human Nutrition, Foods, and Exercise, Virginia Tech, 1981 Kraft Drive (0913), ILSB Room 1020, Blacksburg, VA, 24060, USA.
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15
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Pedicone C, Weitzman SA, Renton AE, Goate AM. Unraveling the complex role of MAPT-containing H1 and H2 haplotypes in neurodegenerative diseases. Mol Neurodegener 2024; 19:43. [PMID: 38812061 PMCID: PMC11138017 DOI: 10.1186/s13024-024-00731-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 05/11/2024] [Indexed: 05/31/2024] Open
Abstract
A ~ 1 Mb inversion polymorphism exists within the 17q21.31 locus of the human genome as direct (H1) and inverted (H2) haplotype clades. This inversion region demonstrates high linkage disequilibrium, but the frequency of each haplotype differs across ancestries. While the H1 haplotype exists in all populations and shows a normal pattern of genetic variability and recombination, the H2 haplotype is enriched in European ancestry populations, is less frequent in African ancestry populations, and nearly absent in East Asian ancestry populations. H1 is a known risk factor for several neurodegenerative diseases, and has been associated with many other traits, suggesting its importance in cellular phenotypes of the brain and entire body. Conversely, H2 is protective for these diseases, but is associated with predisposition to recurrent microdeletion syndromes and neurodevelopmental disorders such as autism. Many single nucleotide variants and copy number variants define H1/H2 haplotypes and sub-haplotypes, but identifying the causal variant(s) for specific diseases and phenotypes is complex due to the extended linkage equilibrium. In this review, we assess the current knowledge of this inversion region regarding genomic structure, gene expression, cellular phenotypes, and disease association. We discuss recent discoveries and challenges, evaluate gaps in knowledge, and highlight the importance of understanding the effect of the 17q21.31 haplotypes to promote advances in precision medicine and drug discovery for several diseases.
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Affiliation(s)
- Chiara Pedicone
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sarah A Weitzman
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alan E Renton
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison M Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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16
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Fröhlich A, Pfaff AL, Middlehurst B, Hughes LS, Bubb VJ, Quinn JP, Koks S. Deciphering the role of a SINE-VNTR-Alu retrotransposon polymorphism as a biomarker of Parkinson's disease progression. Sci Rep 2024; 14:10932. [PMID: 38740892 DOI: 10.1038/s41598-024-61753-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 05/09/2024] [Indexed: 05/16/2024] Open
Abstract
SINE-VNTR-Alu (SVA) retrotransposons are transposable elements which represent a source of genetic variation. We previously demonstrated that the presence/absence of a human-specific SVA, termed SVA_67, correlated with the progression of Parkinson's disease (PD). In the present study, we demonstrate that SVA_67 acts as expression quantitative trait loci, thereby exhibiting a strong regulatory effect across the genome using whole genome and transcriptomic data from the Parkinson's progression markers initiative cohort. We further show that SVA_67 is polymorphic for its variable number tandem repeat domain which correlates with both regulatory properties in a luciferase reporter gene assay in vitro and differential expression of multiple genes in vivo. Additionally, this variation's utility as a biomarker is reflected in a correlation with a number of PD progression markers. These experiments highlight the plethora of transcriptomic and phenotypic changes associated with SVA_67 polymorphism which should be considered when investigating the missing heritability of neurodegenerative diseases.
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Affiliation(s)
- Alexander Fröhlich
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- Perron Institute for Neurological and Translational Science, Perth, WA, Australia
| | - Abigail L Pfaff
- Perron Institute for Neurological and Translational Science, Perth, WA, Australia
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA, Australia
| | - Ben Middlehurst
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Lauren S Hughes
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Vivien J Bubb
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - John P Quinn
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
| | - Sulev Koks
- Perron Institute for Neurological and Translational Science, Perth, WA, Australia.
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA, Australia.
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17
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Li W, Li JY. Overlaps and divergences between tauopathies and synucleinopathies: a duet of neurodegeneration. Transl Neurodegener 2024; 13:16. [PMID: 38528629 DOI: 10.1186/s40035-024-00407-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 02/28/2024] [Indexed: 03/27/2024] Open
Abstract
Proteinopathy, defined as the abnormal accumulation of proteins that eventually leads to cell death, is one of the most significant pathological features of neurodegenerative diseases. Tauopathies, represented by Alzheimer's disease (AD), and synucleinopathies, represented by Parkinson's disease (PD), show similarities in multiple aspects. AD manifests extrapyramidal symptoms while dementia is also a major sign of advanced PD. We and other researchers have sequentially shown the cross-seeding phenomenon of α-synuclein (α-syn) and tau, reinforcing pathologies between synucleinopathies and tauopathies. The highly overlapping clinical and pathological features imply shared pathogenic mechanisms between the two groups of disease. The diagnostic and therapeutic strategies seemingly appropriate for one distinct neurodegenerative disease may also apply to a broader spectrum. Therefore, a clear understanding of the overlaps and divergences between tauopathy and synucleinopathy is critical for unraveling the nature of the complicated associations among neurodegenerative diseases. In this review, we discuss the shared and diverse characteristics of tauopathies and synucleinopathies from aspects of genetic causes, clinical manifestations, pathological progression and potential common therapeutic approaches targeting the pathology, in the aim to provide a timely update for setting the scheme of disease classification and provide novel insights into the therapeutic development for neurodegenerative diseases.
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Affiliation(s)
- Wen Li
- Health Sciences Institute, Key Laboratory of Major Chronic Diseases of Nervous System of Liaoning Province, China Medical University, Shenyang, 110122, China
| | - Jia-Yi Li
- Health Sciences Institute, Key Laboratory of Major Chronic Diseases of Nervous System of Liaoning Province, China Medical University, Shenyang, 110122, China.
- Neural Plasticity and Repair Unit, Department of Experimental Medical Science, Wallenberg Neuroscience Center, Lund University, BMC A10, 22184, Lund, Sweden.
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18
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Porubsky D, Eichler EE. A 25-year odyssey of genomic technology advances and structural variant discovery. Cell 2024; 187:1024-1037. [PMID: 38290514 PMCID: PMC10932897 DOI: 10.1016/j.cell.2024.01.002] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 02/01/2024]
Abstract
This perspective focuses on advances in genome technology over the last 25 years and their impact on germline variant discovery within the field of human genetics. The field has witnessed tremendous technological advances from microarrays to short-read sequencing and now long-read sequencing. Each technology has provided genome-wide access to different classes of human genetic variation. We are now on the verge of comprehensive variant detection of all forms of variation for the first time with a single assay. We predict that this transition will further transform our understanding of human health and biology and, more importantly, provide novel insights into the dynamic mutational processes shaping our genomes.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.
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19
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Gokuladhas S, Fadason T, Farrow S, Cooper A, O'Sullivan JM. Discovering genetic mechanisms underlying the co-occurrence of Parkinson's disease and non-motor traits. NPJ Parkinsons Dis 2024; 10:27. [PMID: 38263313 PMCID: PMC10805842 DOI: 10.1038/s41531-024-00638-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/09/2024] [Indexed: 01/25/2024] Open
Abstract
Understanding the biological mechanisms that underlie the non-motor symptoms of Parkinson's disease (PD) requires comprehensive frameworks that unravel the complex interplay of genetic risk factors. Here, we used a disease-agnostic brain cortex gene regulatory network integrated with Mendelian Randomization analyses that identified 19 genes whose changes in expression were causally linked to PD. We further used the network to identify genes that are regulated by PD-associated genome-wide association study (GWAS) SNPs. Extended protein interaction networks derived from PD-risk genes and PD-associated SNPs identified convergent impacts on biological pathways and phenotypes, connecting PD with established co-occurring traits, including non-motor symptoms. These findings hold promise for therapeutic development. In conclusion, while distinct sets of genes likely influence PD risk and outcomes, the existence of genes in common and intersecting pathways associated with other traits suggests that they may contribute to both increased PD risk and symptom heterogeneity observed in people with Parkinson's.
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Affiliation(s)
- Sreemol Gokuladhas
- The Liggins Institute, University of Auckland, Auckland, 1023, New Zealand
| | - Tayaza Fadason
- The Liggins Institute, University of Auckland, Auckland, 1023, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, 1010, New Zealand
| | - Sophie Farrow
- The Liggins Institute, University of Auckland, Auckland, 1023, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, 1010, New Zealand
| | - Antony Cooper
- St Vincent's Clinical School, UNSW Sydney, Sydney, NSW, Australia
- Australian Parkinson's Mission, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Justin M O'Sullivan
- The Liggins Institute, University of Auckland, Auckland, 1023, New Zealand.
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, 1010, New Zealand.
- Australian Parkinson's Mission, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK.
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
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Fröhlich A, Hughes LS, Middlehurst B, Pfaff AL, Bubb VJ, Koks S, Quinn JP. CRISPR deletion of a SINE-VNTR- Alu (SVA_67) retrotransposon demonstrates its ability to differentially modulate gene expression at the MAPT locus. Front Neurol 2023; 14:1273036. [PMID: 37840928 PMCID: PMC10570551 DOI: 10.3389/fneur.2023.1273036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 09/13/2023] [Indexed: 10/17/2023] Open
Abstract
Background SINE-VNTR-Alu (SVA) retrotransposons are hominid-specific elements which have been shown to play important roles in processes such as chromatin structure remodelling and regulation of gene expression demonstrating that these repetitive elements exert regulatory functions. We have previously shown that the presence or absence of a specific SVA element, termed SVA_67, was associated with differential expression of several genes at the MAPT locus, a locus associated with Parkinson's Disease (PD) and frontotemporal dementia. However, we were not able to demonstrate that causation of differential gene expression was directed by the SVA due to lack of functional validation. Methods We performed CRISPR to delete SVA_67 in the HEK293 cell line. Quantification of target gene expression was performed using qPCR to assess the effects on expression in response to the deletion of SVA_67. Differences between CRISPR edit and control cell lines were analysed using two-tailed t-test with a minimum 95% confidence interval to determine statistical significance. Results In this study, we provide data highlighting the SVA-specific effect on differential gene expression. We demonstrate that the hemizygous deletion of the endogenous SVA_67 in CRISPR edited cell lines was associated with differential expression of several genes at the MAPT locus associated with neurodegenerative diseases including KANSL1, MAPT and LRRC37A. Discussion This data is consistent with our previous bioinformatic work of differential gene expression analysis using transcriptomic data from the Parkinson's Progression Markers Initiative (PPMI) cohort. As SVAs have regulatory influences on gene expression, and insertion polymorphisms contribute to interpersonal differences in expression patterns, these results highlight the potential contribution of these elements to complex diseases with potentially many genetic components, such as PD.
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Affiliation(s)
- Alexander Fröhlich
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- Perron Institute for Neurological and Translational Science, Perth, WA, Australia
| | - Lauren S. Hughes
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Ben Middlehurst
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Abigail L. Pfaff
- Perron Institute for Neurological and Translational Science, Perth, WA, Australia
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA, Australia
| | - Vivien J. Bubb
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Sulev Koks
- Perron Institute for Neurological and Translational Science, Perth, WA, Australia
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA, Australia
| | - John P. Quinn
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
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21
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Kelly K, Lewis PA, Plun-Favreau H, Manzoni C. Protein network analysis links the NSL complex to Parkinson's disease via mitochondrial and nuclear biology. Mol Omics 2023; 19:668-679. [PMID: 37427757 DOI: 10.1039/d2mo00325b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Whilst the majority of Parkinson's Disease (PD) cases are sporadic, much of our understanding of the pathophysiological basis of the disease can be traced back to the study of rare, monogenic forms of PD. In the past decade, the availability of genome-wide association studies (GWAS) has facilitated a shift in focus, toward identifying common risk variants conferring increased risk of developing PD across the population. A recent mitophagy screening assay of GWAS candidates has functionally implicated the non-specific lethal (NSL) complex in the regulation of PINK1-mitophagy. Here, a bioinformatics approach has been taken to investigate the proteome of the NSL complex, to unpick its relevance to PD pathogenesis. The NSL interactome has been built, using 3 online tools: PINOT, HIPPIE and MIST, to mine curated, literature-derived protein-protein interaction (PPI) data. We built (i) the 'mitochondrial' NSL interactome exploring its relevance to PD genetics and (ii) the PD-oriented NSL interactome to uncover biological pathways underpinning the NSL/PD association. In this study, we find the mitochondrial NSL interactome to be significantly enriched for the protein products of PD-associated genes, including the Mendelian PD genes LRRK2 and VPS35. In addition, we find nuclear processes to be amongst those most significantly enriched within the PD-associated NSL interactome. These findings strengthen the role of the NSL complex in sporadic and familial PD, mediated by both its mitochondrial and nuclear functions.
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Affiliation(s)
- Katie Kelly
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Patrick A Lewis
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
- Royal Veterinary College, University of London, Royal College Street, Camden, NW1 0TU, UK
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Helene Plun-Favreau
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Claudia Manzoni
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- UCL School of Pharmacy, Brunswick Square, London, WC1N 1AX, UK.
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22
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Wang H, Makowski C, Zhang Y, Qi A, Kaufmann T, Smeland OB, Fiecas M, Yang J, Visscher PM, Chen CH. Chromosomal inversion polymorphisms shape human brain morphology. Cell Rep 2023; 42:112896. [PMID: 37505983 PMCID: PMC10508191 DOI: 10.1016/j.celrep.2023.112896] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/27/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
The impact of chromosomal inversions on human brain morphology remains underexplored. We studied 35 common inversions classified from genotypes of 33,018 adults with European ancestry. The inversions at 2p22.3, 16p11.2, and 17q21.31 reach genome-wide significance, followed by 8p23.1 and 6p21.33, in their association with cortical and subcortical morphology. The 17q21.31, 8p23.1, and 16p11.2 regions comprise the LRRC37, OR7E, and NPIP duplicated gene families. We find the 17q21.31 MAPT inversion region, known for harboring neurological risk, to be the most salient locus among common variants for shaping and patterning the cortex. Overall, we observe the inverted orientations decreasing brain size, with the exception that the 2p22.3 inversion is associated with increased subcortical volume and the 8p23.1 inversion is associated with increased motor cortex. These significant inversions are in the genomic hotspots of neuropsychiatric loci. Our findings are generalizable to 3,472 children and demonstrate inversions as essential genetic variation to understand human brain phenotypes.
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Affiliation(s)
- Hao Wang
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA
| | - Carolina Makowski
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA
| | - Yanxiao Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Anna Qi
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA
| | - Tobias Kaufmann
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, 72076 Tübingen, Germany; Norwegian Centre for Mental Disorders Research, Oslo University Hospital and University of Oslo, 0450 Oslo, Norway
| | - Olav B Smeland
- Norwegian Centre for Mental Disorders Research, Oslo University Hospital and University of Oslo, 0450 Oslo, Norway
| | - Mark Fiecas
- Division of Biostatistics, University of Minnesota School of Public Health, Minneapolis, MN 55455, USA
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Chi-Hua Chen
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA.
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23
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Soto DC, Uribe-Salazar JM, Shew CJ, Sekar A, McGinty S, Dennis MY. Genomic structural variation: A complex but important driver of human evolution. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2023; 181 Suppl 76:118-144. [PMID: 36794631 PMCID: PMC10329998 DOI: 10.1002/ajpa.24713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 01/21/2023] [Accepted: 02/05/2023] [Indexed: 02/17/2023]
Abstract
Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.
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Affiliation(s)
- Daniela C. Soto
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - José M. Uribe-Salazar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Aarthi Sekar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Sean McGinty
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
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24
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Laufer VA, Glover TW, Wilson TE. Applications of advanced technologies for detecting genomic structural variation. MUTATION RESEARCH. REVIEWS IN MUTATION RESEARCH 2023; 792:108475. [PMID: 37931775 PMCID: PMC10792551 DOI: 10.1016/j.mrrev.2023.108475] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 09/07/2023] [Accepted: 11/02/2023] [Indexed: 11/08/2023]
Abstract
Chromosomal structural variation (SV) encompasses a heterogenous class of genetic variants that exerts strong influences on human health and disease. Despite their importance, many structural variants (SVs) have remained poorly characterized at even a basic level, a discrepancy predicated upon the technical limitations of prior genomic assays. However, recent advances in genomic technology can identify and localize SVs accurately, opening new questions regarding SV risk factors and their impacts in humans. Here, we first define and classify human SVs and their generative mechanisms, highlighting characteristics leveraged by various SV assays. We next examine the first-ever gapless assembly of the human genome and the technical process of assembling it, which required third-generation sequencing technologies to resolve structurally complex loci. The new portions of that "telomere-to-telomere" and subsequent pangenome assemblies highlight aspects of SV biology likely to develop in the near-term. We consider the strengths and limitations of the most promising new SV technologies and when they or longstanding approaches are best suited to meeting salient goals in the study of human SV in population-scale genomics research, clinical, and public health contexts. It is a watershed time in our understanding of human SV when new approaches are expected to fundamentally change genomic applications.
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Affiliation(s)
- Vincent A Laufer
- Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
| | - Thomas W Glover
- Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
| | - Thomas E Wilson
- Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
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25
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Porubsky D, Harvey WT, Rozanski AN, Ebler J, Höps W, Ashraf H, Hasenfeld P, Paten B, Sanders AD, Marschall T, Korbel JO, Eichler EE. Inversion polymorphism in a complete human genome assembly. Genome Biol 2023; 24:100. [PMID: 37122002 PMCID: PMC10150506 DOI: 10.1186/s13059-023-02919-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/31/2023] [Indexed: 05/02/2023] Open
Abstract
The telomere-to-telomere (T2T) complete human reference has significantly improved our ability to characterize genome structural variation. To understand its impact on inversion polymorphisms, we remapped data from 41 genomes against the T2T reference genome and compared it to the GRCh38 reference. We find a ~ 21% increase in sensitivity improving mapping of 63 inversions on the T2T reference. We identify 26 misorientations within GRCh38 and show that the T2T reference is three times more likely to represent the correct orientation of the major human allele. Analysis of 10 additional samples reveals novel rare inversions at chromosomes 15q25.2, 16p11.2, 16q22.1-23.1, and 22q11.21.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Allison N Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Jana Ebler
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Wolfram Höps
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117, Heidelberg, Germany
| | - Hufsah Ashraf
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117, Heidelberg, Germany
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Helmholtz Association, 10115, Berlin, Germany
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
- Charité-Universitätsmedizin, 10117, Berlin, Germany
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Moorenstraße 5, 40225, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117, Heidelberg, Germany
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, 98195, USA.
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26
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Senkevich K, Bandres-Ciga S, Cisterna-García A, Yu E, Bustos BI, Krohn L, Lubbe SJ, Botía JA, the International Parkinson’s Disease Genomics Consortium (IPDGC), Gan-Or Z. Genome-wide association study stratified by MAPT haplotypes identifies potential novel loci in Parkinson's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.14.23288478. [PMID: 37292720 PMCID: PMC10246147 DOI: 10.1101/2023.04.14.23288478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Objective To identify genetic factors that may modify the effects of the MAPT locus in Parkinson's disease (PD). Methods We used data from the International Parkinson's Disease Genomics Consortium (IPDGC) and the UK biobank (UKBB). We stratified the IPDGC cohort for carriers of the H1/H1 genotype (PD patients n=8,492 and controls n=6,765) and carriers of the H2 haplotype (with either H1/H2 or H2/H2 genotypes, patients n=4,779 and controls n=4,849) to perform genome-wide association studies (GWASs). Then, we performed replication analyses in the UKBB data. To study the association of rare variants in the new nominated genes, we performed burden analyses in two cohorts (Accelerating Medicines Partnership - Parkinson Disease and UKBB) with a total sample size PD patients n=2,943 and controls n=18,486. Results We identified a novel locus associated with PD among MAPT H1/H1 carriers near EMP1 (rs56312722, OR=0.88, 95%CI= 0.84-0.92, p= 1.80E-08), and a novel locus associated with PD among MAPT H2 carriers near VANGL1 (rs11590278, OR=1.69 95%CI=1.40-2.03, p=2.72E-08). Similar analysis of the UKBB data did not replicate these results and rs11590278 near VANGL1 did have similar effect size and direction in carriers of H2 haplotype, albeit not statistically significant (OR= 1.32, 95%CI= 0.94-1.86, p=0.17). Rare EMP1 variants with high CADD scores were associated with PD in the MAPT H2 stratified analysis (p=9.46E-05), mainly driven by the p.V11G variant. Interpretation We identified several loci potentially associated with PD stratified by MAPT haplotype and larger replication studies are required to confirm these associations.
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Affiliation(s)
- Konstantin Senkevich
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montréal, QC, Canada
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada, Canada
| | - Sara Bandres-Ciga
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International LLC, Washington DC, USA
| | - Alejandro Cisterna-García
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | - Eric Yu
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Bernabe I. Bustos
- Ken and Ruth Davee Department of Neurology, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA
- Simpson Querrey Center for Neurogenetics, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA
| | - Lynne Krohn
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Steven J. Lubbe
- Ken and Ruth Davee Department of Neurology, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA
- Simpson Querrey Center for Neurogenetics, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA
| | - Juan A. Botía
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | | | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montréal, QC, Canada
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
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27
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Kosuthova K, Solc R. Inversions on human chromosomes. Am J Med Genet A 2023; 191:672-683. [PMID: 36495134 DOI: 10.1002/ajmg.a.63063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/13/2022] [Accepted: 11/17/2022] [Indexed: 12/14/2022]
Abstract
Human chromosome inversions are types of balanced structural variations, making them difficult to analyze. Thanks to PEM (paired-end sequencing and mapping), there has been tremendous progress in studying inversions. Inversions play an important role as an evolutionary factor, contributing to the formation of gonosomes, speciation of chimpanzees and humans, and inv17q21.3 or inv8p23.1 exhibit the features of natural selection. Both inversions have been related to pathogenic phenotype by directly affecting a gene structure (e.g., inv5p15.1q14.1), regulating gene expression (e.g., inv7q21.3q35) and by predisposing to other secondary arrangements (e.g., inv7q11.23). A polymorphism of human inversions is documented by the InvFEST database (a database that stores information about clinical predictions, validations, frequency of inversions, etc.), but only a small fraction of these inversions is validated, and a detailed analysis is complicated by the frequent location of breakpoints within regions of repetitive sequences.
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Affiliation(s)
- Klara Kosuthova
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
| | - Roman Solc
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
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28
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Wang H, Wang LS, Schellenberg G, Lee WP. The role of structural variations in Alzheimer's disease and other neurodegenerative diseases. Front Aging Neurosci 2023; 14:1073905. [PMID: 36846102 PMCID: PMC9944073 DOI: 10.3389/fnagi.2022.1073905] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/31/2022] [Indexed: 02/10/2023] Open
Abstract
Dozens of single nucleotide polymorphisms (SNPs) related to Alzheimer's disease (AD) have been discovered by large scale genome-wide association studies (GWASs). However, only a small portion of the genetic component of AD can be explained by SNPs observed from GWAS. Structural variation (SV) can be a major contributor to the missing heritability of AD; while SV in AD remains largely unexplored as the accurate detection of SVs from the widely used array-based and short-read technology are still far from perfect. Here, we briefly summarized the strengths and weaknesses of available SV detection methods. We reviewed the current landscape of SV analysis in AD and SVs that have been found associated with AD. Particularly, the importance of currently less explored SVs, including insertions, inversions, short tandem repeats, and transposable elements in neurodegenerative diseases were highlighted.
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Affiliation(s)
- Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Gerard Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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29
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Soutar MPM, Melandri D, O’Callaghan B, Annuario E, Monaghan AE, Welsh NJ, D’Sa K, Guelfi S, Zhang D, Pittman A, Trabzuni D, Verboven AHA, Pan KS, Kia DA, Bictash M, Gandhi S, Houlden H, Cookson MR, Kasri NN, Wood NW, Singleton AB, Hardy J, Whiting PJ, Blauwendraat C, Whitworth AJ, Manzoni C, Ryten M, Lewis PA, Plun-Favreau H. Regulation of mitophagy by the NSL complex underlies genetic risk for Parkinson's disease at 16q11.2 and MAPT H1 loci. Brain 2022; 145:4349-4367. [PMID: 36074904 PMCID: PMC9762952 DOI: 10.1093/brain/awac325] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 07/08/2022] [Accepted: 08/12/2022] [Indexed: 02/02/2023] Open
Abstract
Parkinson's disease is a common incurable neurodegenerative disease. The identification of genetic variants via genome-wide association studies has considerably advanced our understanding of the Parkinson's disease genetic risk. Understanding the functional significance of the risk loci is now a critical step towards translating these genetic advances into an enhanced biological understanding of the disease. Impaired mitophagy is a key causative pathway in familial Parkinson's disease, but its relevance to idiopathic Parkinson's disease is unclear. We used a mitophagy screening assay to evaluate the functional significance of risk genes identified through genome-wide association studies. We identified two new regulators of PINK1-dependent mitophagy initiation, KAT8 and KANSL1, previously shown to modulate lysine acetylation. These findings suggest PINK1-mitophagy is a contributing factor to idiopathic Parkinson's disease. KANSL1 is located on chromosome 17q21 where the risk associated gene has long been considered to be MAPT. While our data do not exclude a possible association between the MAPT gene and Parkinson's disease, they provide strong evidence that KANSL1 plays a crucial role in the disease. Finally, these results enrich our understanding of physiological events regulating mitophagy and establish a novel pathway for drug targeting in neurodegeneration.
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Affiliation(s)
- Marc P M Soutar
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Daniela Melandri
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Benjamin O’Callaghan
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Emily Annuario
- Department of Basic and Clinical Neuroscience, King’s College, London, UK
| | - Amy E Monaghan
- UCL Alzheimer’s Research UK, Drug Discovery Institute, London, UK
- UCL Dementia Research Institute, London, UK
| | - Natalie J Welsh
- MRC Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
| | - Karishma D’Sa
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Francis Crick Institute, London, UK
| | - Sebastian Guelfi
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
| | - David Zhang
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Alan Pittman
- Genetics Research Centre, Molecular and Clinical Sciences, St Georges University, London, UK
| | - Daniah Trabzuni
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Anouk H A Verboven
- Department of Human Genetics, Radboudumc, Donders Institute for Brain, Cognition and Behaviour, 6500 HB Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboudumc, Donders Institute for Brain, Cognition and Behaviour, 6500 HB Nijmegen, The Netherlands
| | - Kylie S Pan
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Demis A Kia
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London, UK
| | - Magda Bictash
- UCL Alzheimer’s Research UK, Drug Discovery Institute, London, UK
- UCL Dementia Research Institute, London, UK
| | - Sonia Gandhi
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Francis Crick Institute, London, UK
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London, UK
| | - Henry Houlden
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Mark R Cookson
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Nael Nadif Kasri
- Department of Human Genetics, Radboudumc, Donders Institute for Brain, Cognition and Behaviour, 6500 HB Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboudumc, Donders Institute for Brain, Cognition and Behaviour, 6500 HB Nijmegen, The Netherlands
| | - Nicholas W Wood
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London, UK
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - John Hardy
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- UCL Dementia Research Institute, London, UK
| | - Paul J Whiting
- UCL Alzheimer’s Research UK, Drug Discovery Institute, London, UK
- UCL Dementia Research Institute, London, UK
| | - Cornelis Blauwendraat
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | | | - Claudia Manzoni
- Department of Pharmacology, UCL School of Pharmacy, London, UK
| | - Mina Ryten
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Patrick A Lewis
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Department of Comparative Biomedical Sciences, Royal Veterinary College, LondonUK
| | - Hélène Plun-Favreau
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
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30
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Salzberg LI, Martos AAR, Lombardi L, Jermiin LS, Blanco A, Byrne KP, Wolfe KH. A widespread inversion polymorphism conserved among Saccharomyces species is caused by recurrent homogenization of a sporulation gene family. PLoS Genet 2022; 18:e1010525. [PMID: 36441813 PMCID: PMC9731477 DOI: 10.1371/journal.pgen.1010525] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 12/08/2022] [Accepted: 11/12/2022] [Indexed: 11/29/2022] Open
Abstract
Saccharomyces genomes are highly collinear and show relatively little structural variation, both within and between species of this yeast genus. We investigated the only common inversion polymorphism known in S. cerevisiae, which affects a 24-kb 'flip/flop' region containing 15 genes near the centromere of chromosome XIV. The region exists in two orientations, called reference (REF) and inverted (INV). Meiotic recombination in this region is suppressed in crosses between REF and INV orientation strains such as the BY x RM cross. We find that the inversion polymorphism is at least 17 million years old because it is conserved across the genus Saccharomyces. However, the REF and INV isomers are not ancient alleles but are continually being re-created by re-inversion of the region within each species. Inversion occurs due to continual homogenization of two almost identical 4-kb sequences that form an inverted repeat (IR) at the ends of the flip/flop region. The IR consists of two pairs of genes that are specifically and strongly expressed during the late stages of sporulation. We show that one of these gene pairs, YNL018C/YNL034W, codes for a protein that is essential for spore formation. YNL018C and YNL034W are the founder members of a gene family, Centroid, whose members in other Saccharomycetaceae species evolve fast, duplicate frequently, and are preferentially located close to centromeres. We tested the hypothesis that Centroid genes are a meiotic drive system, but found no support for this idea.
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Affiliation(s)
- Letal I. Salzberg
- Conway Institute, University College Dublin, Dublin, Ireland
- School of Medicine, University College Dublin, Dublin, Ireland
| | - Alexandre A. R. Martos
- Conway Institute, University College Dublin, Dublin, Ireland
- School of Medicine, University College Dublin, Dublin, Ireland
| | - Lisa Lombardi
- Conway Institute, University College Dublin, Dublin, Ireland
- School of Biomolecular and Biomedical Science, University College Dublin, Dublin, Ireland
| | - Lars S. Jermiin
- School of Medicine, University College Dublin, Dublin, Ireland
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
- Earth Institute, University College Dublin, Dublin, Ireland
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Alfonso Blanco
- Conway Institute, University College Dublin, Dublin, Ireland
| | - Kevin P. Byrne
- Conway Institute, University College Dublin, Dublin, Ireland
- School of Medicine, University College Dublin, Dublin, Ireland
| | - Kenneth H. Wolfe
- Conway Institute, University College Dublin, Dublin, Ireland
- School of Medicine, University College Dublin, Dublin, Ireland
- * E-mail:
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31
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Harerimana NV, Goate AM, Bowles KR. The influence of 17q21.31 and APOE genetic ancestry on neurodegenerative disease risk. Front Aging Neurosci 2022; 14:1021918. [PMID: 36337698 PMCID: PMC9632173 DOI: 10.3389/fnagi.2022.1021918] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 09/26/2022] [Indexed: 09/08/2024] Open
Abstract
Advances in genomic research over the last two decades have greatly enhanced our knowledge concerning the genetic landscape and pathophysiological processes involved in multiple neurodegenerative diseases. However, current insights arise almost exclusively from studies on individuals of European ancestry. Despite this, studies have revealed that genetic variation differentially impacts risk for, and clinical presentation of neurodegenerative disease in non-European populations, conveying the importance of ancestry in predicting disease risk and understanding the biological mechanisms contributing to neurodegeneration. We review the genetic influence of two important disease-associated loci, 17q21.31 (the "MAPT locus") and APOE, to neurodegenerative disease risk in non-European populations, touching on global population differences and evolutionary genetics by ancestry that may underlie some of these differences. We conclude there is a need to increase representation of non-European ancestry individuals in genome-wide association studies (GWAS) and biomarker analyses in order to help resolve existing disparities in understanding risk for, diagnosis of, and treatment for neurodegenerative diseases in diverse populations.
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Affiliation(s)
- Nadia V. Harerimana
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Alison M. Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Kathryn R. Bowles
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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32
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Partanen JJ, Häppölä P, Zhou W, Lehisto AA, Ainola M, Sutinen E, Allen RJ, Stockwell AD, Leavy OC, Oldham JM, Guillen-Guio B, Cox NJ, Hirbo JB, Schwartz DA, Fingerlin TE, Flores C, Noth I, Yaspan BL, Jenkins RG, Wain LV, Ripatti S, Pirinen M, International IPF Genetics Consortium, Global Biobank Meta-Analysis Initiative (GBMI), Laitinen T, Kaarteenaho R, Myllärniemi M, Daly MJ, Koskela JT. Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics. CELL GENOMICS 2022; 2:100181. [PMID: 36777997 PMCID: PMC9903787 DOI: 10.1016/j.xgen.2022.100181] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 05/24/2022] [Accepted: 09/07/2022] [Indexed: 04/12/2023]
Abstract
The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor-the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.
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Affiliation(s)
- Juulia J. Partanen
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Paavo Häppölä
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Arto A. Lehisto
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Mari Ainola
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
| | - Eva Sutinen
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
| | - Richard J. Allen
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Olivia C. Leavy
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Justin M. Oldham
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of California, Davis, Sacramento, CA, USA
| | | | - Nancy J. Cox
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jibril B. Hirbo
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Tasha E. Fingerlin
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
| | - Carlos Flores
- Research Unit, Hospital Universitario Ntra. Sra. de Candelaria, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- Faculty of Health Sciences, University of Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
| | - Imre Noth
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, VA, USA
| | | | - R. Gisli Jenkins
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton and Harefield Hospitals, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Louise V. Wain
- Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Samuli Ripatti
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - International IPF Genetics Consortium
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
- Department of Health Sciences, University of Leicester, Leicester, UK
- Human Genetics, Genentech, South San Francisco, CA, USA
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of California, Davis, Sacramento, CA, USA
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, University of Colorado, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
- Research Unit, Hospital Universitario Ntra. Sra. de Candelaria, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- Faculty of Health Sciences, University of Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, VA, USA
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton and Harefield Hospitals, Guy's and St Thomas' NHS Foundation Trust, London, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
- Administration Center, Tampere University Hospital and University of Tampere, Tampere, Finland
- Research Unit of Internal Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Global Biobank Meta-Analysis Initiative (GBMI)
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
- Department of Health Sciences, University of Leicester, Leicester, UK
- Human Genetics, Genentech, South San Francisco, CA, USA
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of California, Davis, Sacramento, CA, USA
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, University of Colorado, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
- Research Unit, Hospital Universitario Ntra. Sra. de Candelaria, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- Faculty of Health Sciences, University of Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, VA, USA
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton and Harefield Hospitals, Guy's and St Thomas' NHS Foundation Trust, London, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
- Administration Center, Tampere University Hospital and University of Tampere, Tampere, Finland
- Research Unit of Internal Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Tarja Laitinen
- Administration Center, Tampere University Hospital and University of Tampere, Tampere, Finland
| | - Riitta Kaarteenaho
- Research Unit of Internal Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Marjukka Myllärniemi
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
| | - Mark J. Daly
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jukka T. Koskela
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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33
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Campoy E, Puig M, Yakymenko I, Lerga-Jaso J, Cáceres M. Genomic architecture and functional effects of potential human inversion supergenes. Philos Trans R Soc Lond B Biol Sci 2022; 377:20210209. [PMID: 35694745 PMCID: PMC9189494 DOI: 10.1098/rstb.2021.0209] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Supergenes are involved in adaptation in multiple organisms, but they are little known in humans. Genomic inversions are the most common mechanism of supergene generation and maintenance. Here, we review the information about two large inversions that are the best examples of potential human supergenes. In addition, we do an integrative analysis of the newest data to understand better their functional effects and underlying genetic changes. We have found that the highly divergent haplotypes of the 17q21.31 inversion of approximately 1.5 Mb have multiple phenotypic associations, with consistent effects in brain-related traits, red and white blood cells, lung function, male and female characteristics and disease risk. By combining gene expression and nucleotide variation data, we also analysed the molecular differences between haplotypes, including gene duplications, amino acid substitutions and regulatory changes, and identify CRHR1, KANLS1 and MAPT as good candidates to be responsible for these phenotypes. The situation is more complex for the 8p23.1 inversion, where there is no clear genetic differentiation. However, the inversion is associated with several related phenotypes and gene expression differences that could be linked to haplotypes specific of one orientation. Our work, therefore, contributes to the characterization of both exceptional variants and illustrates the important role of inversions. This article is part of the theme issue 'Genomic architecture of supergenes: causes and evolutionary consequences'.
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Affiliation(s)
- Elena Campoy
- Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Bellaterra (Barcelona), Spain
| | - Marta Puig
- Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Bellaterra (Barcelona), Spain.,Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, Bellaterra (Barcelona), Spain
| | - Illya Yakymenko
- Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Bellaterra (Barcelona), Spain
| | - Jon Lerga-Jaso
- Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Bellaterra (Barcelona), Spain
| | - Mario Cáceres
- Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Bellaterra (Barcelona), Spain.,ICREA, Barcelona, Spain
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34
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Bowles KR, Pugh DA, Liu Y, Patel T, Renton AE, Bandres-Ciga S, Gan-Or Z, Heutink P, Siitonen A, Bertelsen S, Cherry JD, Karch CM, Frucht SJ, Kopell BH, Peter I, Park YJ, International Parkinson’s Disease Genomics Consortium (IPDGC), Charney A, Raj T, Crary JF, Goate AM. 17q21.31 sub-haplotypes underlying H1-associated risk for Parkinson's disease are associated with LRRC37A/2 expression in astrocytes. Mol Neurodegener 2022; 17:48. [PMID: 35841044 PMCID: PMC9284779 DOI: 10.1186/s13024-022-00551-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 06/21/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Parkinson's disease (PD) is genetically associated with the H1 haplotype of the MAPT 17q.21.31 locus, although the causal gene and variants underlying this association have not been identified. METHODS To better understand the genetic contribution of this region to PD and to identify novel mechanisms conferring risk for the disease, we fine-mapped the 17q21.31 locus by constructing discrete haplotype blocks from genetic data. We used digital PCR to assess copy number variation associated with PD-associated blocks, and used human brain postmortem RNA-seq data to identify candidate genes that were then further investigated using in vitro models and human brain tissue. RESULTS We identified three novel H1 sub-haplotype blocks across the 17q21.31 locus associated with PD risk. Protective sub-haplotypes were associated with increased LRRC37A/2 copy number and expression in human brain tissue. We found that LRRC37A/2 is a membrane-associated protein that plays a role in cellular migration, chemotaxis and astroglial inflammation. In human substantia nigra, LRRC37A/2 was primarily expressed in astrocytes, interacted directly with soluble α-synuclein, and co-localized with Lewy bodies in PD brain tissue. CONCLUSION These data indicate that a novel candidate gene, LRRC37A/2, contributes to the association between the 17q21.31 locus and PD via its interaction with α-synuclein and its effects on astrocytic function and inflammatory response. These data are the first to associate the genetic association at the 17q21.31 locus with PD pathology, and highlight the importance of variation at the 17q21.31 locus in the regulation of multiple genes other than MAPT and KANSL1, as well as its relevance to non-neuronal cell types.
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Affiliation(s)
- Kathryn R. Bowles
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Derian A. Pugh
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Yiyuan Liu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Tulsi Patel
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Alan E. Renton
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Sara Bandres-Ciga
- Laboratory of Neurogenetics, National Institute On Aging, National Institutes of Health, Bethesda, MD USA
| | - Ziv Gan-Or
- Department of Human Genetics, McGill University, Montréal, Québec Canada
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montréal, Québec Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec Canada
| | - Peter Heutink
- Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Ari Siitonen
- Institute of Clinical Medicine, Department of Neurology, University of Oulu, Oulu, Finland
- Department of Neurology and Medical Research Center, Oulu University Hospital, Oulu, Finland
| | - Sarah Bertelsen
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Jonathan D. Cherry
- Alzheimer’s Disease and CTE Center, Boston University, Boston University School of Medicine, Boston, MA USA
- Department of Neurology, Boston University School of Medicine, Boston, MA USA
- VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA USA
| | - Celeste M. Karch
- Department of Psychiatry, Washington University in St Louis, St. Louis, MO USA
| | - Steven J. Frucht
- Department of Neurology, Fresco Institute for Parkinson’s and Movement Disorders, New York University Langone, New York, NY USA
| | - Brian H. Kopell
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Center for Neuromodulation, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Inga Peter
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Y. J. Park
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | | | - Alexander Charney
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Towfique Raj
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - John F. Crary
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - A. M. Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY USA
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Porubsky D, Höps W, Ashraf H, Hsieh P, Rodriguez-Martin B, Yilmaz F, Ebler J, Hallast P, Maria Maggiolini FA, Harvey WT, Henning B, Audano PA, Gordon DS, Ebert P, Hasenfeld P, Benito E, Zhu Q, Lee C, Antonacci F, Steinrücken M, Beck CR, Sanders AD, Marschall T, Eichler EE, Korbel JO. Recurrent inversion polymorphisms in humans associate with genetic instability and genomic disorders. Cell 2022; 185:1986-2005.e26. [PMID: 35525246 PMCID: PMC9563103 DOI: 10.1016/j.cell.2022.04.017] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/14/2022] [Accepted: 04/08/2022] [Indexed: 12/13/2022]
Abstract
Unlike copy number variants (CNVs), inversions remain an underexplored genetic variation class. By integrating multiple genomic technologies, we discover 729 inversions in 41 human genomes. Approximately 85% of inversions <2 kbp form by twin-priming during L1 retrotransposition; 80% of the larger inversions are balanced and affect twice as many nucleotides as CNVs. Balanced inversions show an excess of common variants, and 72% are flanked by segmental duplications (SDs) or retrotransposons. Since flanking repeats promote non-allelic homologous recombination, we developed complementary approaches to identify recurrent inversion formation. We describe 40 recurrent inversions encompassing 0.6% of the genome, showing inversion rates up to 2.7 × 10-4 per locus per generation. Recurrent inversions exhibit a sex-chromosomal bias and co-localize with genomic disorder critical regions. We propose that inversion recurrence results in an elevated number of heterozygous carriers and structural SD diversity, which increases mutability in the population and predisposes specific haplotypes to disease-causing CNVs.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Wolfram Höps
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Hufsah Ashraf
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, 40225 Düsseldorf, Germany
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Bernardo Rodriguez-Martin
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Jana Ebler
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, 40225 Düsseldorf, Germany
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Flavia Angela Maria Maggiolini
- Department of Biology, University of Bari "Aldo Moro", 70125 Bari, Italy; Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria-Centro di Ricerca Viticoltura ed Enologia (CREA-VE), Via Casamassima 148, 70010 Turi, Italy
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Barbara Henning
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter A Audano
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - David S Gordon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Peter Ebert
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, 40225 Düsseldorf, Germany
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Eva Benito
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | | | - Matthias Steinrücken
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA; Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Christine R Beck
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA; The University of Connecticut Health Center, 400 Farmington Rd., Farmington, CT 06032, USA
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany; Charité-Universitätsmedizin, Berlin, Berlin, Germany
| | - Tobias Marschall
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, 40225 Düsseldorf, Germany.
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
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36
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Lanciano S, Cristofari G. Flip-flop genomics: Charting inversions in the human population. Cell 2022; 185:1811-1813. [DOI: 10.1016/j.cell.2022.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 04/30/2022] [Accepted: 05/02/2022] [Indexed: 11/29/2022]
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37
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Fray S, Achouri-Rassas AA, Hadj Fredj S, Messaoud T, Belal S. Association between H2 haplotype of microtubule associated protein tau gene (deletion / insertion) with Alzheimer Disease in Tunisian patients. Neurol Res 2022; 44:814-818. [PMID: 35348036 DOI: 10.1080/01616412.2022.2056338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
It is widely recognized that Alzheimer's disease (AD) is the main cause of dementia in the elderly. AD is typically characterized by the extraneuronal plaque made up essentially of the amyloid β peptide and intraneuronal tangles of hyperphosphorylated microtubule-associated Tau protein. This study investigates the possible interaction between AD and the deletion/insertion polymorphism in intron 9 of the Tau gene haplotype and APOE state in a Tunisian AD cases population (n = 85) and control (n = 91). The H2/H2 genotype was higher in the AD group as compared to the controls (22.4% vs. 7.8%). The frequency of H2 allele is higher in the patients group, and the difference of allele frequency is statistically significant between the two groups (χ2 = 12.220, p < 0.05). H2 allele is correlated with the female gender within the patient group (χ2 = 7.649, p = 0.006) Tau H2 haplotype can be identified as a risk factor of AD in the studied Tunisian population and was associated to female gender. There is no significant correlation between the frequency of Tau gene ins/del polymorphism and cognitive profile distribution in the patient group (p > 0.05).
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Affiliation(s)
- Saloua Fray
- Faculty of Medicine of Tunis, Tunis El Manar University, Tunis, Tunisia.,Department of Neurology, Charles Nicolle Hospital, Tunis, Tunisia.,Children Hospital, Biochemistry and Molecular Biology Laboratory, Tunis, Tunisia
| | - Afef Achouri Achouri-Rassas
- Department of Neurology, Charles Nicolle Hospital, Tunis, Tunisia.,Neurosciences Project, Faculty of Medicine of Tunis, Tunis El Manar University, Tunis, Tunisia
| | - Sondes Hadj Fredj
- Children Hospital, Biochemistry and Molecular Biology Laboratory, Tunis, Tunisia
| | - Taieb Messaoud
- Children Hospital, Biochemistry and Molecular Biology Laboratory, Tunis, Tunisia
| | - Samir Belal
- Faculty of Medicine of Tunis, Tunis El Manar University, Tunis, Tunisia.,Department of Neurology, National Institute Mongi Ben Hmida of Neurology, Tunis, Tunisia.,Molecular Neurobiology and Neuropathology Research laboratory, Faculty of Medicine of Tunis, Tunis El Manar University, Tunis, Tunisia
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38
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Fröhlich A, Pfaff AL, Bubb VJ, Koks S, Quinn JP. Characterisation of the Function of a SINE-VNTR-Alu Retrotransposon to Modulate Isoform Expression at the MAPT Locus. Front Mol Neurosci 2022; 15:815695. [PMID: 35370538 PMCID: PMC8965460 DOI: 10.3389/fnmol.2022.815695] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 02/10/2022] [Indexed: 11/30/2022] Open
Abstract
SINE-VNTR-Alu retrotransposons represent one class of transposable elements which contribute to the regulation and evolution of the primate genome and have the potential to be involved in genetic instability and disease progression. However, these polymorphic elements have not been extensively analysed when addressing the missing heritability of neurodegenerative diseases, including Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). SVA_67, a retrotransposon insertion polymorphism, is located in a 1.8 Mb region of high linkage disequilibrium, called the MAPT locus, which is known to contribute to increased risk of developing PD, frontotemporal dementia and other tauopathies. To investigate the role of SVA_67 in directing differential gene expression at this locus, we characterised the impact of SVA_67 allele dosage on isoform expression of several genes in the MAPT locus using the datasets from both the Parkinson’s Progression Markers Initiative and New York Genome Center Consortium Target ALS cohort. The Parkinson’s data was from gene expression in the blood and the ALS data from a variety of CNS regions and allowed us to demonstrate that SVA_67 presence or absence correlated with both isoform- and tissue-specific expression of multiple genes at this locus. This study highlights the importance of addressing SVA polymorphism in disease genetics to gain insight into a better understanding of the role of these regulatory domains to a variety of neurodegenerative diseases.
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Affiliation(s)
- Alexander Fröhlich
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- *Correspondence: Alexander Fröhlich,
| | - Abigail L. Pfaff
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA, Australia
- Perron Institute for Neurological and Translational Science, Perth, WA, Australia
| | - Vivien J. Bubb
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Sulev Koks
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA, Australia
- Perron Institute for Neurological and Translational Science, Perth, WA, Australia
| | - John P. Quinn
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
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Makowski C, van der Meer D, Dong W, Wang H, Wu Y, Zou J, Liu C, Rosenthal SB, Hagler DJ, Fan CC, Kremen WS, Andreassen OA, Jernigan TL, Dale AM, Zhang K, Visscher PM, Yang J, Chen CH. Discovery of genomic loci of the human cerebral cortex using genetically informed brain atlases. Science 2022; 375:522-528. [PMID: 35113692 DOI: 10.1126/science.abe8457] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
To determine the impact of genetic variants on the brain, we used genetically informed brain atlases in genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136 children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post hoc combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk. Opposing gradations of decreased surface area and increased thickness were associated with common inversion polymorphisms. Inferior frontal regions, encompassing Broca's area, which is important for speech, were enriched for human-specific genomic elements. Thus, a mixed genetic landscape of conserved and human-specific features is concordant with brain hierarchy and morphogenetic gradients.
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Affiliation(s)
- Carolina Makowski
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Weixiu Dong
- Department of Bioengineering, University of California, San Diego, CA, USA
| | - Hao Wang
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - Yan Wu
- Department of Bioengineering, University of California, San Diego, CA, USA
| | - Jingjing Zou
- Division of Biostatistics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, CA, USA
| | - Cin Liu
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - Sara B Rosenthal
- Center for Computational Biology and Bioinformatics, University of California, San Diego, CA, USA
| | - Donald J Hagler
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - Chun Chieh Fan
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - William S Kremen
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California, San Diego, CA, USA
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Terry L Jernigan
- Center for Human Development, University of California, San Diego, CA, USA
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA.,Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kun Zhang
- Department of Bioengineering, University of California, San Diego, CA, USA
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.,School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
| | - Chi-Hua Chen
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
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40
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Abstract
Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI but does not manifest as clinical stroke, is highly prevalent in the general population, particularly with increasing age. Advances in technologies and collaborative work have led to substantial progress in the identification of common genetic variants that are associated with cSVD-related stroke (ischaemic and haemorrhagic) and MRI-defined covert cSVD. In this Review, we provide an overview of collaborative studies - mostly genome-wide association studies (GWAS) - that have identified >50 independent genetic loci associated with the risk of cSVD. We describe how these associations have provided novel insights into the biological mechanisms involved in cSVD, revealed patterns of shared genetic variation across cSVD traits, and shed new light on the continuum between rare, monogenic and common, multifactorial cSVD. We consider how GWAS summary statistics have been leveraged for Mendelian randomization studies to explore causal pathways in cSVD and provide genetic evidence for drug effects, and how the combination of findings from GWAS with gene expression resources and drug target databases has enabled identification of putative causal genes and provided proof-of-concept for drug repositioning potential. We also discuss opportunities for polygenic risk prediction, multi-ancestry approaches and integration with other omics data.
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41
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Valentini S, Gandolfi F, Carolo M, Dalfovo D, Pozza L, Romanel A. OUP accepted manuscript. Nucleic Acids Res 2022; 50:1335-1350. [PMID: 35061909 PMCID: PMC8860573 DOI: 10.1093/nar/gkac024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/03/2022] [Accepted: 01/07/2022] [Indexed: 11/21/2022] Open
Abstract
In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants’ interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants’ functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact.
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Affiliation(s)
- Samuel Valentini
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Francesco Gandolfi
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Mattia Carolo
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Davide Dalfovo
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Lara Pozza
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Alessandro Romanel
- To whom correspondence should be addressed. Tel: +39 0461 285217; Fax: +39 0461 283937;
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42
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Leveille E, Ross OA, Gan-Or Z. Tau and MAPT genetics in tauopathies and synucleinopathies. Parkinsonism Relat Disord 2021; 90:142-154. [PMID: 34593302 PMCID: PMC9310195 DOI: 10.1016/j.parkreldis.2021.09.008] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/25/2021] [Accepted: 09/09/2021] [Indexed: 10/20/2022]
Abstract
MAPT encodes the microtubule-associated protein tau, which is the main component of neurofibrillary tangles (NFTs) and found in other protein aggregates. These aggregates are among the pathological hallmarks of primary tauopathies such as frontotemporal dementia (FTD). Abnormal tau can also be observed in secondary tauopathies such as Alzheimer's disease (AD) and synucleinopathies such as Parkinson's disease (PD). On top of pathological findings, genetic data also links MAPT to these disorders. MAPT variations are a cause or risk factors for many tauopathies and synucleinopathies and are associated with certain clinical and pathological features in affected individuals. In addition to clinical, pathological, and genetic overlap, evidence also suggests that tau and alpha-synuclein may interact on the molecular level, and thus might collaborate in the neurodegenerative process. Understanding the role of MAPT variations in tauopathies and synucleinopathies is therefore essential to elucidate the role of tau in the pathogenesis and phenotype of those disorders, and ultimately to develop targeted therapies. In this review, we describe the role of MAPT genetic variations in tauopathies and synucleinopathies, several genotype-phenotype and pathological features, and discuss their implications for the classification and treatment of those disorders.
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Affiliation(s)
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA; Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-hospital), McGill University, Montréal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada; Department of Human Genetics, McGill University, Montréal, QC, Canada.
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43
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Mosley TJ, Johnston HR, Cutler DJ, Zwick ME, Mulle JG. Sex-specific recombination patterns predict parent of origin for recurrent genomic disorders. BMC Med Genomics 2021; 14:154. [PMID: 34107974 PMCID: PMC8190997 DOI: 10.1186/s12920-021-00999-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 06/02/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Structural rearrangements of the genome, which generally occur during meiosis and result in large-scale (> 1 kb) copy number variants (CNV; deletions or duplications ≥ 1 kb), underlie genomic disorders. Recurrent pathogenic CNVs harbor similar breakpoints in multiple unrelated individuals and are primarily formed via non-allelic homologous recombination (NAHR). Several pathogenic NAHR-mediated recurrent CNV loci demonstrate biases for parental origin of de novo CNVs. However, the mechanism underlying these biases is not well understood. METHODS We performed a systematic, comprehensive literature search to curate parent of origin data for multiple pathogenic CNV loci. Using a regression framework, we assessed the relationship between parental CNV origin and the male to female recombination rate ratio. RESULTS We demonstrate significant association between sex-specific differences in meiotic recombination and parental origin biases at these loci (p = 1.07 × 10-14). CONCLUSIONS Our results suggest that parental origin of CNVs is largely influenced by sex-specific recombination rates and highlight the need to consider these differences when investigating mechanisms that cause structural variation.
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Affiliation(s)
- Trenell J Mosley
- Graduate Program in Genetics and Molecular Biology, Laney Graduate School, Emory University, 201 Dowman Drive, Atlanta, GA, 30322, USA
- Department of Human Genetics, Emory University School of Medicine, 615 Michael Street, Whitehead Building Suite 300, Atlanta, GA, 30322, USA
| | - H Richard Johnston
- Department of Human Genetics, Emory University School of Medicine, 615 Michael Street, Whitehead Building Suite 300, Atlanta, GA, 30322, USA
- Emory Integrated Computational Core, Emory University, 101 Woodruff Circle, Atlanta, GA, 30322, USA
| | - David J Cutler
- Department of Human Genetics, Emory University School of Medicine, 615 Michael Street, Whitehead Building Suite 300, Atlanta, GA, 30322, USA
| | - Michael E Zwick
- Department of Human Genetics, Emory University School of Medicine, 615 Michael Street, Whitehead Building Suite 300, Atlanta, GA, 30322, USA
- Department of Pediatrics, Emory University School of Medicine, 2015 Uppergate Drive, Atlanta, GA, 30322, USA
| | - Jennifer G Mulle
- Department of Human Genetics, Emory University School of Medicine, 615 Michael Street, Whitehead Building Suite 300, Atlanta, GA, 30322, USA.
- Department of Epidemiology, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA, 30322, USA.
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44
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D’Antonio M, The COVID-19 Host Genetics Initiative, Arthur TD, Nguyen JP, Matsui H, D’Antonio-Chronowska A, Frazer KA. Insights into genetic factors contributing to variability in SARS-CoV-2 susceptibility and COVID-19 disease severity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.05.10.21256423. [PMID: 34013287 PMCID: PMC8132261 DOI: 10.1101/2021.05.10.21256423] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we applied colocalization to compare summary statistics for 16 GWASs from the COVID-19 Host Genetics Initiative to investigate similarities and differences in their genetic signals. We identified 9 loci associated with susceptibility (one with two independent GWAS signals; one with an ethnicity-specific signal), 14 associated with severity (one with two independent GWAS signals; two with ethnicity-specific signals) and one harboring two discrepant GWAS signals (one for susceptibility; one for severity). Utilizing colocalization we also identified 45 GTEx tissues that had eQTL(s) for 18 genes strongly associated with GWAS signals in eleven loci (1-4 genes per locus). Some of these genes showed tissue-specific altered expression and others showed altered expression in up to 41 different tissue types. Our study provides insights into the complex molecular mechanisms underlying inherited predispositions to COVID-19-disease phenotypes.
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Affiliation(s)
- Matteo D’Antonio
- Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA
| | | | - Timothy D. Arthur
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Jennifer P. Nguyen
- Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Hiroko Matsui
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | | | - Kelly A. Frazer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA
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Ebert P, Audano PA, Zhu Q, Rodriguez-Martin B, Porubsky D, Bonder MJ, Sulovari A, Ebler J, Zhou W, Serra Mari R, Yilmaz F, Zhao X, Hsieh P, Lee J, Kumar S, Lin J, Rausch T, Chen Y, Ren J, Santamarina M, Höps W, Ashraf H, Chuang NT, Yang X, Munson KM, Lewis AP, Fairley S, Tallon LJ, Clarke WE, Basile AO, Byrska-Bishop M, Corvelo A, Evani US, Lu TY, Chaisson MJP, Chen J, Li C, Brand H, Wenger AM, Ghareghani M, Harvey WT, Raeder B, Hasenfeld P, Regier AA, Abel HJ, Hall IM, Flicek P, Stegle O, Gerstein MB, Tubio JMC, Mu Z, Li YI, Shi X, Hastie AR, Ye K, Chong Z, Sanders AD, Zody MC, Talkowski ME, Mills RE, Devine SE, Lee C, Korbel JO, Marschall T, Eichler EE. Haplotype-resolved diverse human genomes and integrated analysis of structural variation. Science 2021; 372:eabf7117. [PMID: 33632895 PMCID: PMC8026704 DOI: 10.1126/science.abf7117] [Citation(s) in RCA: 403] [Impact Index Per Article: 100.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 02/09/2021] [Indexed: 12/14/2022]
Abstract
Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.
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Affiliation(s)
- Peter Ebert
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Bernardo Rodriguez-Martin
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Marc Jan Bonder
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Jana Ebler
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Weichen Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA
| | - Rebecca Serra Mari
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Xuefang Zhao
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Joyce Lee
- Bionano Genomics, San Diego, CA 92121, USA
| | - Sushant Kumar
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 and 437, 266 Whitney Avenue, New Haven, CT 06520, USA
| | - Jiadong Lin
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
| | - Tobias Rausch
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Yu Chen
- Department of Genetics and Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Jingwen Ren
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Martin Santamarina
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Department of Zoology, Genetics, and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Wolfram Höps
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Hufsah Ashraf
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Nelson T Chuang
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | - Xiaofei Yang
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Susan Fairley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Luke J Tallon
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | | | | | | | | | | | - Tsung-Yu Lu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Junjie Chen
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | - Chong Li
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Aaron M Wenger
- Pacific Biosciences of California, Menlo Park, CA 94025, USA
| | - Maryam Ghareghani
- Max Planck Institute for Informatics, Saarland Informatics Campus E1.4, 66123 Saarbrücken, Germany
- Saarbrücken Graduate School of Computer Science, Saarland University, Saarland Informatics Campus E1.3, 66123 Saarbrücken, Germany
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Benjamin Raeder
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Allison A Regier
- Department of Medicine, Washington University, St. Louis, MO 63108, USA
| | - Haley J Abel
- Department of Medicine, Washington University, St. Louis, MO 63108, USA
| | - Ira M Hall
- Department of Genetics, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Oliver Stegle
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 and 437, 266 Whitney Avenue, New Haven, CT 06520, USA
| | - Jose M C Tubio
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Department of Zoology, Genetics, and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Zepeng Mu
- Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL 60637, USA
| | - Yang I Li
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Xinghua Shi
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | | | - Kai Ye
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
- Department of Human Genetics, University of Michigan, 1241 E. Catherine Street, Ann Arbor, MI 48109, USA
| | - Zechen Chong
- Department of Genetics and Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Ashley D Sanders
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | | | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ryan E Mills
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA
- Department of Human Genetics, University of Michigan, 1241 E. Catherine Street, Ann Arbor, MI 48109, USA
| | - Scott E Devine
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.
- Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
- Department of Graduate Studies-Life Sciences, Ewha Womans University, Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750, South Korea
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany.
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Tobias Marschall
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany.
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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Transcript Variants of Genes Involved in Neurodegeneration Are Differentially Regulated by the APOE and MAPT Haplotypes. Genes (Basel) 2021; 12:genes12030423. [PMID: 33804213 PMCID: PMC7999745 DOI: 10.3390/genes12030423] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 03/01/2021] [Accepted: 03/10/2021] [Indexed: 12/17/2022] Open
Abstract
Genetic variations at the Apolipoprotein E (ApoE) and microtubule-associated protein tau (MAPT) loci have been implicated in multiple neurogenerative diseases, but their exact molecular mechanisms are unclear. In this study, we performed transcript level linear modelling using the blood whole transcriptome data and genotypes of the 570 subjects in the Parkinson’s Progression Markers Initiative (PPMI) cohort. ApoE, MAPT haplotypes and two SNPs at the SNCA locus (rs356181, rs3910105) were used to detect expression quantitative trait loci eQTLs associated with the transcriptome and differential usage of transcript isoforms. As a result, we identified 151 genes associated with the genotypic variations, 29 cis and 122 trans eQTL positions. Profound effect with genome-wide significance of ApoE e4 haplotype on the expression of TOMM40 transcripts was identified. This finding potentially explains in part the frequently established genetic association with the APOE e4 haplotypes in neurodegenerative diseases. Moreover, MAPT haplotypes had significant differential impact on 23 transcripts from the 17q21.31 and 17q24.1 loci. MAPT haplotypes had also the largest up-regulating (256) and the largest down-regulating (−178) effect sizes measured as β values on two different transcripts from the same gene (LRRC37A2). Intronic SNP in the SNCA gene, rs3910105, differentially induced expression of three SNCA isoforms. In conclusion, this study established clear association between well-known haplotypic variance and transcript specific regulation in the blood. APOE e4 and MAPT H1/H2 haplotypic variants are associated with the expression of several genes related to the neurodegeneration.
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47
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Browning SR, Browning BL. Probabilistic Estimation of Identity by Descent Segment Endpoints and Detection of Recent Selection. Am J Hum Genet 2020; 107:895-910. [PMID: 33053335 PMCID: PMC7553009 DOI: 10.1016/j.ajhg.2020.09.010] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 09/25/2020] [Indexed: 12/18/2022] Open
Abstract
Most methods for fast detection of identity by descent (IBD) segments report identity by state segments without any quantification of the uncertainty in the endpoints and lengths of the IBD segments. We present a method for determining the posterior probability distribution of IBD segment endpoints. Our approach accounts for genotype errors, recent mutations, and gene conversions which disrupt DNA sequence identity within IBD segments, and it can be applied to large cohorts with whole-genome sequence or SNP array data. We find that our method's estimates of uncertainty are well calibrated for homogeneous samples. We quantify endpoint uncertainty for 77.7 billion IBD segments from 408,883 individuals of white British ancestry in the UK Biobank, and we use these IBD segments to find regions showing evidence of recent natural selection. We show that many spurious selection signals are eliminated by the use of unbiased estimates of IBD segment endpoints and a pedigree-based genetic map. Eleven of the twelve regions with the greatest evidence for recent selection in our scan have been identified as selected in previous analyses using different approaches. Our computationally efficient method for quantifying IBD segment endpoint uncertainty is implemented in the open source ibd-ends software package.
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Affiliation(s)
- Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
| | - Brian L Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
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48
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Corces MR, Shcherbina A, Kundu S, Gloudemans MJ, Frésard L, Granja JM, Louie BH, Eulalio T, Shams S, Bagdatli ST, Mumbach MR, Liu B, Montine KS, Greenleaf WJ, Kundaje A, Montgomery SB, Chang HY, Montine TJ. Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer's and Parkinson's diseases. Nat Genet 2020; 52:1158-1168. [PMID: 33106633 PMCID: PMC7606627 DOI: 10.1038/s41588-020-00721-x] [Citation(s) in RCA: 238] [Impact Index Per Article: 47.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 09/18/2020] [Indexed: 02/06/2023]
Abstract
Genome-wide association studies of neurological diseases have identified thousands of variants associated with disease phenotypes. However, most of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional SNPs for Alzheimer's and Parkinson's diseases, nominating target genes and cell types for previously orphaned loci from genome-wide association studies. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) Parkinson's disease risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease.
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Affiliation(s)
- M Ryan Corces
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Anna Shcherbina
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Soumya Kundu
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Michael J Gloudemans
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Laure Frésard
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Jeffrey M Granja
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Program in Biophysics, Stanford University, Stanford, CA, USA
| | - Bryan H Louie
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Tiffany Eulalio
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Shadi Shams
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - S Tansu Bagdatli
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Maxwell R Mumbach
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Boxiang Liu
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Baidu Research, Sunnyvale, CA, USA
| | - Kathleen S Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - William J Greenleaf
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Stephen B Montgomery
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
| | - Thomas J Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
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Single-cell strand sequencing of a macaque genome reveals multiple nested inversions and breakpoint reuse during primate evolution. Genome Res 2020; 30:1680-1693. [PMID: 33093070 PMCID: PMC7605249 DOI: 10.1101/gr.265322.120] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 09/02/2020] [Indexed: 12/14/2022]
Abstract
Rhesus macaque is an Old World monkey that shared a common ancestor with human ∼25 Myr ago and is an important animal model for human disease studies. A deep understanding of its genetics is therefore required for both biomedical and evolutionary studies. Among structural variants, inversions represent a driving force in speciation and play an important role in disease predisposition. Here we generated a genome-wide map of inversions between human and macaque, combining single-cell strand sequencing with cytogenetics. We identified 375 total inversions between 859 bp and 92 Mbp, increasing by eightfold the number of previously reported inversions. Among these, 19 inversions flanked by segmental duplications overlap with recurrent copy number variants associated with neurocognitive disorders. Evolutionary analyses show that in 17 out of 19 cases, the Hominidae orientation of these disease-associated regions is always derived. This suggests that duplicated sequences likely played a fundamental role in generating inversions in humans and great apes, creating architectures that nowadays predispose these regions to disease-associated genetic instability. Finally, we identified 861 genes mapping at 156 inversions breakpoints, with some showing evidence of differential expression in human and macaque cell lines, thus highlighting candidates that might have contributed to the evolution of species-specific features. This study depicts the most accurate fine-scale map of inversions between human and macaque using a two-pronged integrative approach, such as single-cell strand sequencing and cytogenetics, and represents a valuable resource toward understanding of the biology and evolution of primate species.
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50
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Refining Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Genetic Loci by Integrating Summary Data From Genome-wide Association, Gene Expression, and DNA Methylation Studies. Biol Psychiatry 2020; 88:470-479. [PMID: 32684367 DOI: 10.1016/j.biopsych.2020.05.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 04/09/2020] [Accepted: 05/02/2020] [Indexed: 01/15/2023]
Abstract
BACKGROUND Recent genome-wide association studies (GWASs) identified the first genetic loci associated with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The next step is to use these results to increase our understanding of the biological mechanisms involved. Most of the identified variants likely influence gene regulation. The aim of the current study is to shed light on the mechanisms underlying the genetic signals and prioritize genes by integrating GWAS results with gene expression and DNA methylation (DNAm) levels. METHODS We applied summary-data-based Mendelian randomization to integrate ADHD and ASD GWAS data with fetal brain expression and methylation quantitative trait loci, given the early onset of these disorders. We also analyzed expression and methylation quantitative trait loci datasets of adult brain and blood, as these provide increased statistical power. We subsequently used summary-data-based Mendelian randomization to investigate if the same variant influences both DNAm and gene expression levels. RESULTS We identified multiple gene expression and DNAm levels in fetal brain at chromosomes 1 and 17 that were associated with ADHD and ASD, respectively, through pleiotropy at shared genetic variants. The analyses in brain and blood showed additional associated gene expression and DNAm levels at the same and additional loci, likely because of increased statistical power. Several of the associated genes have not been identified in ADHD and ASD GWASs before. CONCLUSIONS Our findings identified the genetic variants associated with ADHD and ASD that likely act through gene regulation. This facilitates prioritization of candidate genes for functional follow-up studies.
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