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Keene JC, Mietzsch U, Natarajan N. Hypotonia in the Neonatal Intensive Care Unit. Clin Perinatol 2025; 52:407-419. [PMID: 40350219 DOI: 10.1016/j.clp.2025.02.013] [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] [Indexed: 05/14/2025]
Abstract
Hypotonia is a common presenting symptom in the neonatal intensive care unit (NICU). Hypotonia can be a manifestation of an underlying systemic illness, a primary nervous system disease, or a peripheral nervous system disease. Examination and history can suggest specific causes, but rapid and accurate diagnosis remains challenging due to the broad spectrum of causes. Options for disease-targeted therapies have increased the importance of early diagnosis. This article focuses on the evaluation and diagnostic approach of the hypotonic newborn in the NICU, with an emphasis on rapid identification of treatable conditions and updated recommendations on the utilization of genetic testing.
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Affiliation(s)
- Jennifer C Keene
- Division of Pediatric Neurology, Department of Pediatrics, Primary Children's Hospital, University of Utah, 81 North Mario Capecchi Drive, Salt Lake City, UT 84113, USA.
| | - Ulrike Mietzsch
- Division of Neonatology, Department of Pediatrics, University of Washington School of Medicine, Seattle Children's Hospital, 4800 Sandpoint Way Northeast, Mailstop FA 2.113, Seattle, WA 98105, USA
| | - Niranjana Natarajan
- Division of Child Neurology, Department of Neurology, University of Washington School of Medicine, 4800 Sandpoint Way Northeast, MB.7.420, Seattle, WA 98105, USA
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2
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Eisfeldt J, Ek M, Nordenskjöld M, Lindstrand A. Toward clinical long-read genome sequencing for rare diseases. Nat Genet 2025:10.1038/s41588-025-02160-y. [PMID: 40335760 DOI: 10.1038/s41588-025-02160-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2024] [Accepted: 03/11/2025] [Indexed: 05/09/2025]
Abstract
Genetic diagnostics is driven by technological advances, forming a tight interface between research, clinic and industry, which enables rapid implementation of new technologies. Short-read genome and exome sequencing, the current state of the art in clinical genetics, can detect a broad spectrum of genetic variants across the genome. However, despite these advancements, more than half of individuals with rare diseases remain undiagnosed after genomic investigations. Long-read whole-genome sequencing (LR-WGS) is a promising technology that identifies previously difficult-to-detect variants while also enabling phasing and methylation analysis and has the potential of generating complete personal assemblies. To pave the way for clinical use of LR-WGS, the clinical genomic community must establish standardized protocols and quality parameters while also developing innovative tools for data analysis and interpretation. In this Perspective, we explore the key challenges and benefits in integrating LR-WGS into routine clinical diagnostics.
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Affiliation(s)
- Jesper Eisfeldt
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
- Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Marlene Ek
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
| | - Magnus Nordenskjöld
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden.
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3
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Mahmoud M, Agustinho DP, Sedlazeck FJ. A Hitchhiker's Guide to long-read genomic analysis. Genome Res 2025; 35:545-558. [PMID: 40228901 PMCID: PMC12047252 DOI: 10.1101/gr.279975.124] [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] [Indexed: 04/16/2025]
Abstract
Over the past decade, long-read sequencing has evolved into a pivotal technology for uncovering the hidden and complex regions of the genome. Significant cost efficiency, scalability, and accuracy advancements have driven this evolution. Concurrently, novel analytical methods have emerged to harness the full potential of long reads. These advancements have enabled milestones such as the first fully completed human genome, enhanced identification and understanding of complex genomic variants, and deeper insights into the interplay between epigenetics and genomic variation. This mini-review provides a comprehensive overview of the latest developments in long-read DNA sequencing analysis, encompassing reference-based and de novo assembly approaches. We explore the entire workflow, from initial data processing to variant calling and annotation, focusing on how these methods improve our ability to interpret a wide array of genomic variants. Additionally, we discuss the current challenges, limitations, and future directions in the field, offering a detailed examination of the state-of-the-art bioinformatics methods for long-read sequencing.
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Affiliation(s)
- Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Daniel P Agustinho
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA;
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
- Department of Computer Science, Rice University, Houston, Texas 77005, USA
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4
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Hiatt L, Weisburd B, Dolzhenko E, Rubinetti V, Avvaru AK, VanNoy GE, Kurtas NE, Rehm HL, Quinlan AR, Dashnow H. STRchive: a dynamic resource detailing population-level and locus-specific insights at tandem repeat disease loci. Genome Med 2025; 17:29. [PMID: 40140942 PMCID: PMC11938676 DOI: 10.1186/s13073-025-01454-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2024] [Accepted: 03/11/2025] [Indexed: 03/28/2025] Open
Abstract
Approximately 8% of the human genome consists of repetitive elements called tandem repeats (TRs): short tandem repeats (STRs) of 1-6 bp motifs and variable number tandem repeats (VNTRs) of 7 + bp motifs. TR variants contribute to several dozen monogenic diseases but remain understudied and enigmatic. It remains comparatively challenging to interpret the clinical significance of TR variants, particularly relative to single nucleotide variants. We present STRchive ( http://strchive.org/ ), a dynamic resource consolidating information on TR disease loci from the research literature, up-to-date clinical resources, and large-scale genomic databases, streamlining TR variant interpretation at disease-associated loci.
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Affiliation(s)
- Laurel Hiatt
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Ben Weisburd
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Vincent Rubinetti
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Akshay K Avvaru
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Grace E VanNoy
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ambry Genetics, Aliso Viejo, CA, USA
| | - Nehir Edibe Kurtas
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Heidi L Rehm
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Aaron R Quinlan
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Harriet Dashnow
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA.
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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5
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Davenport ML, Swanson MS. RNA gain-of-function mechanisms in short tandem repeat diseases. RNA (NEW YORK, N.Y.) 2025; 31:349-358. [PMID: 39725460 PMCID: PMC11874975 DOI: 10.1261/rna.080277.124] [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: 09/30/2024] [Accepted: 12/23/2024] [Indexed: 12/28/2024]
Abstract
As adaptors, catalysts, guides, messengers, scaffolds, and structural components, RNAs perform an impressive array of cellular regulatory functions often by recruiting RNA-binding proteins (RBPs) to form ribonucleoprotein complexes (RNPs). While this RNA-RBP interaction network allows precise RNP assembly and the subsequent structural dynamics required for normal functions, RNA motif mutations may trigger the formation of aberrant RNP structures that lead to cell dysfunction and disease. Here, we provide our perspective on one type of RNA motif mutation, RNA gain-of-function mutations associated with the abnormal expansion of short tandem repeats (STRs) that underlie multiple developmental and degenerative diseases. We first discuss our current understanding of normal polymorphic STR functions in RNA processing and localization followed by an assessment of the pathogenic roles of STR expansions in the neuromuscular disease myotonic dystrophy. We also highlight ongoing questions and controversies focused on STR-based insights into the regulation of nuclear RNA processing and export as well as the relevance of the RNA gain-of-function pathomechanism for other STR expansion disorders in both coding and noncoding genes.
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Affiliation(s)
- Mackenzie L Davenport
- Department of Molecular Genetics and Microbiology, Center for NeuroGenetics and the Genetics Institute, University of Florida, Gainesville, Florida 32610, USA
| | - Maurice S Swanson
- Department of Molecular Genetics and Microbiology, Center for NeuroGenetics and the Genetics Institute, University of Florida, Gainesville, Florida 32610, USA
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6
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Liu J, Yu S, Lü P, Gong X, Sun M, Tang M. De novo assembly and characterization of the complete mitochondrial genome of Phellodendron amurense reveals three repeat-mediated recombination. Gene 2025; 935:149031. [PMID: 39461576 DOI: 10.1016/j.gene.2024.149031] [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: 07/19/2024] [Revised: 10/18/2024] [Accepted: 10/21/2024] [Indexed: 10/29/2024]
Abstract
Phellodendron amurense Rupr., a rare herb renowned for its medicinal and ecological significance, has remained genetically unexplored at the mitochondrial level until now. This study presents the first-ever systematic assembly and annotation of the complete mitochondrial genome of P. amurense, achieved through a hybrid strategy combining Illumina and Nanopore sequencing data. The mitochondrial genome spans 566,285 bp with a GC content of 45.51 %, structured into two circular molecules. Our comprehensive analysis identified 32 protein-coding genes (PCGs), 33 tRNA genes, and 3 rRNA genes, alongside 181 simple sequence repeats, 19 tandem repeats, and 310 dispersed repeats. Notably, multiple genome conformations were predicted due to repeat-mediated homologous recombination. Additionally, we assembled the chloroplast genome, identifying 21 mitochondrial plastid sequences that provide insights into organelle genome interactions. A total of 380 RNA-editing sites within the mitochondrial PCGs were predicted, enhancing our understanding of gene regulation and function. Phylogenetic analysis using mitochondrial PCGs from 30 species revealed evolutionary relationships, confirming the homology between P. amurense and Citrus species. This foundational study offers a valuable genetic resource for the Rutaceae family, facilitating further research into genetic evolution and molecular diversity in plant mitochondrial genomes.
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Affiliation(s)
- Junlin Liu
- School of Life Sciences, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Shaoshuai Yu
- Department of Pharmacy, Affiliated People's Hospital of Jiangsu University, Zhenjiang 212001, Jiangsu, China
| | - Peng Lü
- School of Life Sciences, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Xun Gong
- Department of Rheumatology & Immunology, Affiliated Hospital of Jiangsu University, Zhenjiang 212001, Jiangsu, China
| | - Mengmeng Sun
- Changchun University of Chinese Medicine, Changchun 130117, Jilin, China
| | - Min Tang
- School of Life Sciences, Jiangsu University, Zhenjiang 212013, Jiangsu, China.
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7
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Veiko NN, Ershova ES, Kondratyeva EI, Porokhovnik LN, Zinchenko RA, Melyanovskaya YL, Krasovskiy SA, Vasilyeva TP, Kostyuk GP, Zakharova NV, Kostyuk SV. Copy Number Variations of Human Ribosomal Genes in Health and Disease: Role and Causes. FRONT BIOSCI-LANDMRK 2025; 30:25765. [PMID: 40018927 DOI: 10.31083/fbl25765] [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: 07/19/2024] [Revised: 09/10/2024] [Accepted: 11/18/2024] [Indexed: 03/01/2025]
Abstract
BACKGROUND A number of association studies have linked ribosomal DNA gene copy number (rDNA CN) to aging and pathology. Data from these studies are contradictory and depend on the quantitative method. METHODS The hybridization technique was used for rDNA quantification in human cells. We determined the rDNA CN from healthy controls (HCs) and patients with schizophrenia (SZ) or cystic fibrosis (CF) (total number of subjects N = 1124). For the first time, rDNA CN was quantified in 105 long livers (90-101 years old). In addition, we conducted a joint analysis of the data obtained in this work and previously published by our group (total, N = 3264). RESULTS We found increased rDNA CN in the SZ group (534 ± 108, N = 1489) and CF group (567 ± 100, N = 322) and reduced rDNA CN in patients with mild cognitive impairment (330 ± 60, N = 93) compared with the HC group (422 ± 104, N = 1360). For the SZ, CF, and HC groups, there was a decreased range of rDNA CN variation in older age subgroups compared to child subgroups. For 311 patients with SZ or CF, rDNA CN was determined two or three times, with an interval of months to several years. Only 1.2% of patients demonstrated a decrease in rDNA CN over time. We did not find significant rDNA CN variation in eight different organs of the same patient or in cells of the same fibroblast population. CONCLUSIONS The results suggest that rDNA CN is a relatively stable quantitative genetic trait statistically associated with some diseases, which however, can change in rare cases under conditions of chronic oxidative stress. We believe that age- and disease-related differences between the groups in mean rDNA CN and its variance are caused by the biased elimination of carriers of marginal (predominantly low) rDNA CN values.
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Affiliation(s)
- Natalia N Veiko
- Laboratory of Molecular Biology, Research Centre of Medical Genetics, 115478 Moscow, Russia
| | - Elizaveta S Ershova
- Laboratory of Molecular Biology, Research Centre of Medical Genetics, 115478 Moscow, Russia
| | - Elena I Kondratyeva
- Laboratory of Molecular Biology, Research Centre of Medical Genetics, 115478 Moscow, Russia
| | - Lev N Porokhovnik
- Laboratory of Molecular Biology, Research Centre of Medical Genetics, 115478 Moscow, Russia
| | - Rena A Zinchenko
- Laboratory of Molecular Biology, Research Centre of Medical Genetics, 115478 Moscow, Russia
| | - Yuliya L Melyanovskaya
- Laboratory of Molecular Biology, Research Centre of Medical Genetics, 115478 Moscow, Russia
| | - Stanislav A Krasovskiy
- Laboratory of Molecular Biology, Research Centre of Medical Genetics, 115478 Moscow, Russia
| | - Tatiana P Vasilyeva
- Department of Public Health, National Research Institute of Public Health n.a. N.А. Semashko, 105064 Moscow, Russia
| | - George P Kostyuk
- Research Department, N. A. Alexeev Clinical Psychiatric Hospital №1, 115447 Moscow, Russia
| | - Natalia V Zakharova
- Research Department, N. A. Alexeev Clinical Psychiatric Hospital №1, 115447 Moscow, Russia
| | - Svetlana V Kostyuk
- Laboratory of Molecular Biology, Research Centre of Medical Genetics, 115478 Moscow, Russia
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8
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Van Deynze K, Mumm C, Maltby CJ, Switzenberg JA, Todd P, Boyle AP. Enhanced detection and genotyping of disease-associated tandem repeats using HMMSTR and targeted long-read sequencing. Nucleic Acids Res 2025; 53:gkae1202. [PMID: 39676678 PMCID: PMC11754662 DOI: 10.1093/nar/gkae1202] [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: 05/01/2024] [Revised: 10/16/2024] [Accepted: 11/19/2024] [Indexed: 12/17/2024] Open
Abstract
Tandem repeat sequences comprise approximately 8% of the human genome and are linked to more than 50 neurodegenerative disorders. Accurate characterization of disease-associated repeat loci remains resource intensive and often lacks high resolution genotype calls. We introduce a multiplexed, targeted nanopore sequencing panel and HMMSTR, a sequence-based tandem repeat copy number caller which outperforms current signal- and sequence-based callers relative to two assemblies and we show it performs with high accuracy in heterozygous regions and at low read coverage. The flexible panel allows us to capture disease associated regions at an average coverage of >150x. Using these tools, we successfully characterize known or suspected repeat expansions in patient derived samples. In these samples, we also identify unexpected expanded alleles at tandem repeat loci not previously associated with the underlying diagnosis. This genotyping approach for tandem repeat expansions is scalable, simple, flexible and accurate, offering significant potential for diagnostic applications and investigation of expansion co-occurrence in neurodegenerative disorders.
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Affiliation(s)
- Kinsey Van Deynze
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Camille Mumm
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Connor J Maltby
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jessica A Switzenberg
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Peter K Todd
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA
- Ann Arbor Veterans Administration Healthcare, Ann Arbor, MI 48105, USA
| | - Alan P Boyle
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
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9
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Zhang S, Song Q, Zhang P, Wang X, Guo R, Li Y, Liu S, Yan X, Zhang J, Niu Y, Shi Y, Song T, Xu T, He S. Genome-wide investigation of VNTR motif polymorphisms in 8,222 genomes: Implications for biological regulation and human traits. CELL GENOMICS 2024; 4:100699. [PMID: 39609246 DOI: 10.1016/j.xgen.2024.100699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 08/31/2024] [Accepted: 11/01/2024] [Indexed: 11/30/2024]
Abstract
Variable number tandem repeat (VNTR) is a pervasive and highly mutable genetic feature that varies in both length and repeat sequence. Despite the well-studied copy-number variants, the functional impacts of repeat motif polymorphisms remain unknown. Here, we present the largest genome-wide VNTR polymorphism map to date, with over 2.5 million VNTR length polymorphisms (VNTR-LPs) and over 11 million VNTR motif polymorphisms (VNTR-MPs) detected in 8,222 high-coverage genomes. Leveraging the large-scale NyuWa cohort, we identified 2,982,456 (31.8%) NyuWa-specific VNTR-MPs, of which 95.3% were rare. Moreover, we found 1,937 out of 38,685 VNTRs that were associated with gene expression through VNTR-MPs in lymphoblastoid cell lines. Specifically, we clarified that the expansion of a likely causal motif could upregulate gene expression by improving the binding concentration of PU.1. We also explored the potential impacts of VNTR polymorphisms on phenotypic differentiation and disease susceptibility. This study expands our knowledge of VNTR-MPs and their functional implications.
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Affiliation(s)
- Sijia Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Department of Scientific Research, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Qiao Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Peng Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaona Wang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Rong Guo
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanyan Li
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuai Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaoyu Yan
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Jingjing Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yiwei Niu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yirong Shi
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tingrui Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Xu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China.
| | - Shunmin He
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
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10
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Gustafson JA, Gibson SB, Damaraju N, Zalusky MPG, Hoekzema K, Twesigomwe D, Yang L, Snead AA, Richmond PA, De Coster W, Olson ND, Guarracino A, Li Q, Miller AL, Goffena J, Anderson ZB, Storz SHR, Ward SA, Sinha M, Gonzaga-Jauregui C, Clarke WE, Basile AO, Corvelo A, Reeves C, Helland A, Musunuri RL, Revsine M, Patterson KE, Paschal CR, Zakarian C, Goodwin S, Jensen TD, Robb E, McCombie WR, Sedlazeck FJ, Zook JM, Montgomery SB, Garrison E, Kolmogorov M, Schatz MC, McLaughlin RN, Dashnow H, Zody MC, Loose M, Jain M, Eichler EE, Miller DE. High-coverage nanopore sequencing of samples from the 1000 Genomes Project to build a comprehensive catalog of human genetic variation. Genome Res 2024; 34:2061-2073. [PMID: 39358015 DOI: 10.1101/gr.279273.124] [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: 03/04/2024] [Accepted: 09/16/2024] [Indexed: 10/04/2024]
Abstract
Fewer than half of individuals with a suspected Mendelian or monogenic condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control data sets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project (1KGP) Oxford Nanopore Technologies Sequencing Consortium aims to generate LRS data from at least 800 of the 1KGP samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37× and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.
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Affiliation(s)
- Jonas A Gustafson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, Washington 98195, USA
| | - Sophia B Gibson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Nikhita Damaraju
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
- Institute for Public Health Genetics, University of Washington, Seattle, Washington 98195, USA
| | - Miranda P G Zalusky
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - David Twesigomwe
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South Africa
| | - Lei Yang
- Pacific Northwest Research Institute, Seattle, Washington 98122, USA
| | - Anthony A Snead
- Department of Biology, New York University, New York, New York 10003, USA
| | | | - Wouter De Coster
- Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp 2650, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp 2000, Belgium
| | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA
- Human Technopole, Milan 20157, Italy
| | - Qiuhui Li
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Angela L Miller
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
| | - Joy Goffena
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
| | - Zachary B Anderson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
| | - Sophie H R Storz
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
| | - Sydney A Ward
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
| | - Maisha Sinha
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
| | - Claudia Gonzaga-Jauregui
- International Laboratory for Human Genome Research, Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Mexico City 76230, Mexico
| | - Wayne E Clarke
- New York Genome Center, New York, New York 10013, USA
- Outlier Informatics Inc., Saskatoon, Saskatchewan S7H 1L4, Canada
| | - Anna O Basile
- New York Genome Center, New York, New York 10013, USA
| | - André Corvelo
- New York Genome Center, New York, New York 10013, USA
| | | | | | | | - Mahler Revsine
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Karynne E Patterson
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Cate R Paschal
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington 98195, USA
- Department of Laboratories, Seattle Children's Hospital, Seattle, Washington 98195, USA
| | - Christina Zakarian
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Sara Goodwin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Tanner D Jensen
- Department of Genetics, Stanford University, Stanford, California 94305, USA
| | - Esther Robb
- Department of Computer Science, Stanford University, Stanford, California 94305, USA
| | | | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
- Department of Computer Science, Rice University, Houston, Texas 77251, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | | | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA
| | - Mikhail Kolmogorov
- Cancer Data Science Laboratory, National Cancer Institute, NIH, Bethesda, Maryland 20892, USA
| | | | - Richard N McLaughlin
- Molecular and Cellular Biology Program, University of Washington, Seattle, Washington 98195, USA
- Pacific Northwest Research Institute, Seattle, Washington 98122, USA
| | - Harriet Dashnow
- Department of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, Colorado 80045, USA
| | - Michael C Zody
- International Laboratory for Human Genome Research, Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Mexico City 76230, Mexico
| | - Matt Loose
- Deep Seq, School of Life Sciences, University of Nottingham, Nottingham NG7 2TQ, UK
| | - Miten Jain
- Department of Bioengineering, Northeastern University, Boston, Massachusetts 02115, USA
- Department of Physics, Northeastern University, Boston, Massachusetts 02115, USA
- Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts 02115, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, Washington 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, USA
| | - Danny E Miller
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA;
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington 98195, USA
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, Washington 98195, USA
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11
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van der Sanden B, Neveling K, Pang AWC, Shukor S, Gallagher MD, Burke SL, Kamsteeg EJ, Hastie A, Hoischen A. Optical Genome Mapping for Applications in Repeat Expansion Disorders. Curr Protoc 2024; 4:e1094. [PMID: 38966883 DOI: 10.1002/cpz1.1094] [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] [Indexed: 07/06/2024]
Abstract
Short tandem repeat (STR) expansions are associated with more than 60 genetic disorders. The size and stability of these expansions correlate with the severity and age of onset of the disease. Therefore, being able to accurately detect the absolute length of STRs is important. Current diagnostic assays include laborious lab experiments, including repeat-primed PCR and Southern blotting, that still cannot precisely determine the exact length of very long repeat expansions. Optical genome mapping (OGM) is a cost-effective and easy-to-use alternative to traditional cytogenetic techniques and allows the comprehensive detection of chromosomal aberrations and structural variants >500 bp in length, including insertions, deletions, duplications, inversions, translocations, and copy number variants. Here, we provide methodological guidance for preparing samples and performing OGM as well as running the analysis pipelines and using the specific repeat expansion workflows to determine the exact repeat length of repeat expansions expanded beyond 500 bp. Together these protocols provide all details needed to analyze the length and stability of any repeat expansion with an expected repeat size difference from the expected wild-type allele of >500 bp. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Genomic ultra-high-molecular-weight DNA isolation, labeling, and staining Basic Protocol 2: Data generation and genome mapping using the Bionano Saphyr® System Basic Protocol 3: Manual De Novo Assembly workflow Basic Protocol 4: Local guided assembly workflow Basic Protocol 5: EnFocus Fragile X workflow Basic Protocol 6: Molecule distance script workflow.
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Affiliation(s)
- Bart van der Sanden
- Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Kornelia Neveling
- Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Syukri Shukor
- Bionano Genomics Clinical and Scientific Affairs, San Diego, California
| | | | - Stephanie L Burke
- Bionano Genomics Clinical and Scientific Affairs, San Diego, California
| | - Erik-Jan Kamsteeg
- Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Alex Hastie
- Bionano Genomics Clinical and Scientific Affairs, San Diego, California
| | - Alexander Hoischen
- Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Internal Medicine, Radboud Expertise Center for Immunodeficiency and Autoinflammation and Radboud Center for Infectious Disease (RCI), Radboud University Medical Center, Nijmegen, the Netherlands
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12
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Hiatt L, Weisburd B, Dolzhenko E, VanNoy GE, Kurtas EN, Rehm HL, Quinlan A, Dashnow H. STRchive: a dynamic resource detailing population-level and locus-specific insights at tandem repeat disease loci. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.21.24307682. [PMID: 38826469 PMCID: PMC11142282 DOI: 10.1101/2024.05.21.24307682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Approximately 3% of the human genome consists of repetitive elements called tandem repeats (TRs), which include short tandem repeats (STRs) of 1-6bp motifs and variable number tandem repeats (VNTRs) of 7+bp motifs. TR variants contribute to several dozen mono- and polygenic diseases but remain understudied and "enigmatic," particularly relative to single nucleotide variants. It remains comparatively challenging to interpret the clinical significance of TR variants. Although existing resources provide portions of necessary data for interpretation at disease-associated loci, it is currently difficult or impossible to efficiently invoke the additional details critical to proper interpretation, such as motif pathogenicity, disease penetrance, and age of onset distributions. It is also often unclear how to apply population information to analyses. We present STRchive (S-T-archive, http://strchive.org/ ), a dynamic resource consolidating information on TR disease loci in humans from research literature, up-to-date clinical resources, and large-scale genomic databases, with the goal of streamlining TR variant interpretation at disease-associated loci. We apply STRchive -including pathogenic thresholds, motif classification, and clinical phenotypes-to a gnomAD cohort of ∼18.5k individuals genotyped at 60 disease-associated loci. Through detailed literature curation, we demonstrate that the majority of TR diseases affect children despite being thought of as adult diseases. Additionally, we show that pathogenic genotypes can be found within gnomAD which do not necessarily overlap with known disease prevalence, and leverage STRchive to interpret locus-specific findings therein. We apply a diagnostic blueprint empowered by STRchive to relevant clinical vignettes, highlighting possible pitfalls in TR variant interpretation. As a living resource, STRchive is maintained by experts, takes community contributions, and will evolve as understanding of TR diseases progresses.
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13
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Van Deynze K, Mumm C, Maltby CJ, Switzenberg JA, Todd PK, Boyle AP. Enhanced Detection and Genotyping of Disease-Associated Tandem Repeats Using HMMSTR and Targeted Long-Read Sequencing. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.01.24306681. [PMID: 38746091 PMCID: PMC11092683 DOI: 10.1101/2024.05.01.24306681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Tandem repeat sequences comprise approximately 8% of the human genome and are linked to more than 50 neurodegenerative disorders. Accurate characterization of disease-associated repeat loci remains resource intensive and often lacks high resolution genotype calls. We introduce a multiplexed, targeted nanopore sequencing panel and HMMSTR, a sequence-based tandem repeat copy number caller. HMMSTR outperforms current signal- and sequence-based callers relative to two assemblies and we show it performs with high accuracy in heterozygous regions and at low read coverage. The flexible panel allows us to capture disease associated regions at an average coverage of >150x. Using these tools, we successfully characterize known or suspected repeat expansions in patient derived samples. In these samples we also identify unexpected expanded alleles at tandem repeat loci not previously associated with the underlying diagnosis. This genotyping approach for tandem repeat expansions is scalable, simple, flexible, and accurate, offering significant potential for diagnostic applications and investigation of expansion co-occurrence in neurodegenerative disorders. Abstract Figure
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14
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Leitão E, Schröder C, Depienne C. Identification and characterization of repeat expansions in neurological disorders: Methodologies, tools, and strategies. Rev Neurol (Paris) 2024; 180:383-392. [PMID: 38594146 DOI: 10.1016/j.neurol.2024.03.005] [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: 03/08/2024] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 04/11/2024]
Abstract
Tandem repeats are a common, highly polymorphic class of variation in human genomes. Their expansion beyond a pathogenic threshold is a process that contributes to a wide range of neurological and neuromuscular genetic disorders, of which over 60 have been identified to date. The last few years have seen a resurgence in repeat expansion discovery propelled by technological advancements, enabling the identification of over 20 novel repeat expansion disorders. These expansions can occur in coding or non-coding regions of genes, resulting in a range of pathogenic mechanisms. In this article, we review strategies, tools and methods that can be used for efficient detection and characterization of known repeat expansions and identification of new expansion disorders. Features that can be used to prioritize repeat expansions include anticipation, which is characterized by increased severity or earlier onset of symptoms across generations, and founder effects, which contribute to higher prevalence rates in certain populations. Classical technologies such as Southern blotting, repeat-primed polymerase chain reaction (PCR) and long-range PCR can still be used to detect known repeat expansions, although they usually have significant limitations linked to the absence of sequence context. Targeted sequencing of known expansions using either long-range PCR or CRISPR-Cas9 enrichment combined with long-read sequencing or adaptive nanopore sampling are usually better but more expensive alternatives. The development of new bioinformatics tools applied to short-read genome data can now be used to detect repeat expansions either in a targeted manner or at the genome-wide level. In addition, technological advances, particularly long-read technologies such as optical genome mapping (Bionano Genomics), Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) HiFi sequencing, offer promising avenues for the detection of repeat expansions. Despite challenges in specific DNA extraction requirements, computation resources needed and data interpretation, these technologies have an immense potential to advance our understanding of repeat expansion disorders and improve diagnostic accuracy.
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Affiliation(s)
- E Leitão
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - C Schröder
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - C Depienne
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany.
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15
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Gustafson JA, Gibson SB, Damaraju N, Zalusky MPG, Hoekzema K, Twesigomwe D, Yang L, Snead AA, Richmond PA, De Coster W, Olson ND, Guarracino A, Li Q, Miller AL, Goffena J, Anderson Z, Storz SHR, Ward SA, Sinha M, Gonzaga-Jauregui C, Clarke WE, Basile AO, Corvelo A, Reeves C, Helland A, Musunuri RL, Revsine M, Patterson KE, Paschal CR, Zakarian C, Goodwin S, Jensen TD, Robb E, McCombie WR, Sedlazeck FJ, Zook JM, Montgomery SB, Garrison E, Kolmogorov M, Schatz MC, McLaughlin RN, Dashnow H, Zody MC, Loose M, Jain M, Eichler EE, Miller DE. Nanopore sequencing of 1000 Genomes Project samples to build a comprehensive catalog of human genetic variation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.05.24303792. [PMID: 38496498 PMCID: PMC10942501 DOI: 10.1101/2024.03.05.24303792] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Less than half of individuals with a suspected Mendelian condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control datasets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project ONT Sequencing Consortium aims to generate LRS data from at least 800 of the 1000 Genomes Project samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37x and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.
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Affiliation(s)
- Jonas A. Gustafson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
| | - Sophia B. Gibson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Nikhita Damaraju
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Miranda PG Zalusky
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - David Twesigomwe
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Lei Yang
- Pacific Northwest Research Institute, Seattle, WA, USA
| | | | | | - Wouter De Coster
- Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Nathan D. Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
- Human Technopole, Milan, Italy
| | - Qiuhui Li
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Angela L. Miller
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Joy Goffena
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Zachery Anderson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Sophie HR Storz
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Sydney A. Ward
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Maisha Sinha
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Claudia Gonzaga-Jauregui
- International Laboratory for Human Genome Research, Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México
| | - Wayne E. Clarke
- New York Genome Center, New York, NY, USA
- Outlier Informatics Inc., Saskatoon, SK, Canada
| | | | | | | | | | | | - Mahler Revsine
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | | | - Cate R. Paschal
- Department of Laboratories, Seattle Children’s Hospital, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Christina Zakarian
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Sara Goodwin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Esther Robb
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | | | | | | | | | - Fritz J. Sedlazeck
- Human Genome Sequencing Center Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Mikhail Kolmogorov
- Cancer Data Science Laboratory, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Richard N. McLaughlin
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
- Pacific Northwest Research Institute, Seattle, WA, USA
| | - Harriet Dashnow
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
| | | | - Matt Loose
- Deep Seq, School of Life Sciences, University of Nottingham, Nottingham, England
| | - Miten Jain
- Department of Bioengineering, Department of Physics, Khoury College of Computer Sciences, Northeastern University, Boston, MA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Danny E. Miller
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
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16
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Hannan AJ. Expanding horizons of tandem repeats in biology and medicine: Why 'genomic dark matter' matters. Emerg Top Life Sci 2023; 7:ETLS20230075. [PMID: 38088823 PMCID: PMC10754335 DOI: 10.1042/etls20230075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/27/2023] [Accepted: 11/27/2023] [Indexed: 12/30/2023]
Abstract
Approximately half of the human genome includes repetitive sequences, and these DNA sequences (as well as their transcribed repetitive RNA and translated amino-acid repeat sequences) are known as the repeatome. Within this repeatome there are a couple of million tandem repeats, dispersed throughout the genome. These tandem repeats have been estimated to constitute ∼8% of the entire human genome. These tandem repeats can be located throughout exons, introns and intergenic regions, thus potentially affecting the structure and function of tandemly repetitive DNA, RNA and protein sequences. Over more than three decades, more than 60 monogenic human disorders have been found to be caused by tandem-repeat mutations. These monogenic tandem-repeat disorders include Huntington's disease, a variety of ataxias, amyotrophic lateral sclerosis and frontotemporal dementia, as well as many other neurodegenerative diseases. Furthermore, tandem-repeat disorders can include fragile X syndrome, related fragile X disorders, as well as other neurological and psychiatric disorders. However, these monogenic tandem-repeat disorders, which were discovered via their dominant or recessive modes of inheritance, may represent the 'tip of the iceberg' with respect to tandem-repeat contributions to human disorders. A previous proposal that tandem repeats may contribute to the 'missing heritability' of various common polygenic human disorders has recently been supported by a variety of new evidence. This includes genome-wide studies that associate tandem-repeat mutations with autism, schizophrenia, Parkinson's disease and various types of cancers. In this article, I will discuss how tandem-repeat mutations and polymorphisms could contribute to a wide range of common disorders, along with some of the many major challenges of tandem-repeat biology and medicine. Finally, I will discuss the potential of tandem repeats to be therapeutically targeted, so as to prevent and treat an expanding range of human disorders.
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Affiliation(s)
- Anthony J Hannan
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3010, Australia
- Department of Anatomy and Physiology, University of Melbourne, Parkville, Victoria 3010, Australia
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