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Chemparathy A, Le Guen Y, Chen S, Lee EG, Leong L, Gorzynski JE, Jensen TD, Ferrasse A, Xu G, Xiang H, Belloy ME, Kasireddy N, Peña-Tauber A, Williams K, Stewart I, Talozzi L, Wingo TS, Lah JJ, Jayadev S, Hales CM, Peskind E, Child DD, Roeber S, Keene CD, Cong L, Ashley EA, Yu CE, Greicius MD. APOE loss-of-function variants: Compatible with longevity and associated with resistance to Alzheimer's disease pathology. Neuron 2024; 112:1110-1116.e5. [PMID: 38301647 PMCID: PMC10994769 DOI: 10.1016/j.neuron.2024.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 10/31/2023] [Accepted: 01/08/2024] [Indexed: 02/03/2024]
Abstract
The ε4 allele of apolipoprotein E (APOE) is the strongest genetic risk factor for sporadic Alzheimer's disease (AD). Knockdown of ε4 may provide a therapeutic strategy for AD, but the effect of APOE loss of function (LoF) on AD pathogenesis is unknown. We searched for APOE LoF variants in a large cohort of controls and patients with AD and identified seven heterozygote carriers of APOE LoF variants. Five carriers were controls (aged 71-90 years), one carrier was affected by progressive supranuclear palsy, and one carrier was affected by AD with an unremarkable age at onset of 75 years. Two APOE ε3/ε4 controls carried a stop-gain affecting ε4: one was cognitively normal at 90 years and had no neuritic plaques at autopsy; the other was cognitively healthy at 79 years, and lumbar puncture at 76 years showed normal levels of amyloid. These results suggest that ε4 drives AD risk through the gain of abnormal function and support ε4 knockdown as a viable therapeutic option.
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Affiliation(s)
- Augustine Chemparathy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA; Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Sunny Chen
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | - Eun-Gyung Lee
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | - Lesley Leong
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | - John E Gorzynski
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Tanner D Jensen
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Alexis Ferrasse
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Guangxue Xu
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Hong Xiang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael E Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Nandita Kasireddy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Andrés Peña-Tauber
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Kennedy Williams
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Ilaria Stewart
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Lia Talozzi
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Thomas S Wingo
- Emory University School of Medicine, Atlanta, GA, USA; Goizueta Alzheimer's Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - James J Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Suman Jayadev
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - Chadwick M Hales
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA; Department of Neurology, University of Washington, Seattle, WA, USA
| | - Elaine Peskind
- Veterans Affairs Northwest Network Mental Illness Research, Education, and Clinical Center, Veteran Affairs Puget Sound Health Care System, Seattle, WA, USA; Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Daniel D Child
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA
| | - Sigrun Roeber
- Center for Neuropathology and Prion Research, Faculty of Medicine, LMU Munich, Munich, Germany
| | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA
| | - Le Cong
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Euan A Ashley
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA; Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, USA; Division of Cardiology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Chang-En Yu
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA; Department of Medicine, University of Washington, Seattle, WA, USA
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
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Jensen TD, Ni B, Reuter CM, Gorzynski JE, Fazal S, Bonner D, Ungar RA, Goddard PC, Raja A, Ashley EA, Bernstein JA, Zuchner S, Greicius MD, Montgomery SB, Schatz MC, Wheeler MT, Battle A. Integration of transcriptomics and long-read genomics prioritizes structural variants in rare disease. medRxiv 2024:2024.03.22.24304565. [PMID: 38585781 PMCID: PMC10996727 DOI: 10.1101/2024.03.22.24304565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Rare structural variants (SVs) - insertions, deletions, and complex rearrangements - can cause Mendelian disease, yet they remain difficult to accurately detect and interpret. We sequenced and analyzed Oxford Nanopore long-read genomes of 68 individuals from the Undiagnosed Disease Network (UDN) with no previously identified diagnostic mutations from short-read sequencing. Using our optimized SV detection pipelines and 571 control long-read genomes, we detected 716 long-read rare (MAF < 0.01) SV alleles per genome on average, achieving a 2.4x increase from short-reads. To characterize the functional effects of rare SVs, we assessed their relationship with gene expression from blood or fibroblasts from the same individuals, and found that rare SVs overlapping enhancers were enriched (LOR = 0.46) near expression outliers. We also evaluated tandem repeat expansions (TREs) and found 14 rare TREs per genome; notably these TREs were also enriched near overexpression outliers. To prioritize candidate functional SVs, we developed Watershed-SV, a probabilistic model that integrates expression data with SV-specific genomic annotations, which significantly outperforms baseline models that don't incorporate expression data. Watershed-SV identified a median of eight high-confidence functional SVs per UDN genome. Notably, this included compound heterozygous deletions in FAM177A1 shared by two siblings, which were likely causal for a rare neurodevelopmental disorder. Our observations demonstrate the promise of integrating long-read sequencing with gene expression towards improving the prioritization of functional SVs and TREs in rare disease patients.
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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 2024:2024.03.05.24303792. [PMID: 38496498 PMCID: PMC10942501 DOI: 10.1101/2024.03.05.24303792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Ungar RA, Goddard PC, Jensen TD, Degalez F, Smith KS, Jin CA, Bonner DE, Bernstein JA, Wheeler MT, Montgomery SB. Impact of genome build on RNA-seq interpretation and diagnostics. medRxiv 2024:2024.01.11.24301165. [PMID: 38260490 PMCID: PMC10802764 DOI: 10.1101/2024.01.11.24301165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network (UDN) and Genomics Research to Elucidate the Genetics of Rare Disease (GREGoR) Consortium. We identified 2,800 genes with build-dependent quantification across six routinely-collected biospecimens, including 1,391 protein-coding genes and 341 known rare disease genes. We further observed multiple genes that only have detectable expression in a subset of genome builds. Finally, we characterized how genome build impacts the detection of outlier transcriptomic events. Combined, we provide a database of genes impacted by build choice, and recommend that transcriptomics-guided analyses and diagnoses are cross-referenced with these data for robustness.
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Affiliation(s)
- Rachel A. Ungar
- Department of Genetics, School of Medicine, Stanford University
- Department of Pathology, School of Medicine, Stanford University
| | - Pagé C. Goddard
- Department of Genetics, School of Medicine, Stanford University
- Department of Pathology, School of Medicine, Stanford University
| | - Tanner D. Jensen
- Department of Genetics, School of Medicine, Stanford University
- Department of Pathology, School of Medicine, Stanford University
| | | | - Kevin S. Smith
- Department of Pathology, School of Medicine, Stanford University
| | | | | | - Devon E. Bonner
- Department of Pediatrics, School of Medicine, Stanford University
- Stanford Center for Undiagnosed Diseases, Stanford University
| | | | - Matthew T. Wheeler
- Department of Cardiovascular Medicine, School of Medicine, Stanford University
| | - Stephen B. Montgomery
- Department of Genetics, School of Medicine, Stanford University
- Department of Pathology, School of Medicine, Stanford University
- Department of Biomedical Data Science, Stanford University
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5
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Gorzynski JE, Goenka SD, Shafin K, Jensen TD, Fisk DG, Grove ME, Spiteri E, Pesout T, Monlong J, Bernstein JA, Ceresnak S, Chang PC, Christle JW, Chubb H, Dunn K, Garalde DR, Guillory J, Ruzhnikov MR, Wright C, Wusthoff CJ, Xiong K, Hollander SA, Berry GJ, Jain M, Sedlazeck FJ, Carroll A, Paten B, Ashley EA. Ultra-Rapid Nanopore Whole Genome Genetic Diagnosis of Dilated Cardiomyopathy in an Adolescent With Cardiogenic Shock. Circ Genom Precis Med 2022; 15:e003591. [DOI: 10.1161/circgen.121.003591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- John E. Gorzynski
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Sneha D. Goenka
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Kishwar Shafin
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.)
| | - Tanner D. Jensen
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | | | | | - Elizabeth Spiteri
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Trevor Pesout
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.)
| | - Jean Monlong
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.)
| | - Jonathan A. Bernstein
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Scott Ceresnak
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | | | - Jeffrey W. Christle
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Henry Chubb
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Kyla Dunn
- Stanford Children’s Health, Palo Alto, CA (K.D.)
| | | | - Joseph Guillory
- Oxford Nanopore Technologies, United Kingdom (D.R.G., J.G., C.W.)
| | - Maura R.Z. Ruzhnikov
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Chris Wright
- Oxford Nanopore Technologies, United Kingdom (D.R.G., J.G., C.W.)
| | - Courtney J. Wusthoff
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Katherine Xiong
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Seth A. Hollander
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Gerald J. Berry
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
| | - Miten Jain
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.)
| | | | | | - Benedict Paten
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.)
| | - Euan A. Ashley
- Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.)
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Goenka SD, Gorzynski JE, Shafin K, Fisk DG, Pesout T, Jensen TD, Monlong J, Chang PC, Baid G, Bernstein JA, Christle JW, Dalton KP, Garalde DR, Grove ME, Guillory J, Kolesnikov A, Nattestad M, Ruzhnikov MRZ, Samadi M, Sethia A, Spiteri E, Wright CJ, Xiong K, Zhu T, Jain M, Sedlazeck FJ, Carroll A, Paten B, Ashley EA. Accelerated identification of disease-causing variants with ultra-rapid nanopore genome sequencing. Nat Biotechnol 2022; 40:1035-1041. [PMID: 35347328 PMCID: PMC9287171 DOI: 10.1038/s41587-022-01221-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 01/13/2022] [Indexed: 12/23/2022]
Abstract
Whole-genome sequencing (WGS) can identify variants that cause genetic disease, but the time required for sequencing and analysis has been a barrier to its use in acutely ill patients. In the present study, we develop an approach for ultra-rapid nanopore WGS that combines an optimized sample preparation protocol, distributing sequencing over 48 flow cells, near real-time base calling and alignment, accelerated variant calling and fast variant filtration for efficient manual review. Application to two example clinical cases identified a candidate variant in <8 h from sample preparation to variant identification. We show that this framework provides accurate variant calls and efficient prioritization, and accelerates diagnostic clinical genome sequencing twofold compared with previous approaches. A streamlined sequencing process enables identification of disease-causing variants in the clinic within 8 hours.
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Affiliation(s)
| | | | | | | | - Trevor Pesout
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | | | - Jean Monlong
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Tong Zhu
- NVIDIA Corporation, Santa Clara, CA, USA
| | - Miten Jain
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
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Cadiz MP, Jensen TD, Sens JP, Zhu K, Song WM, Zhang B, Ebbert M, Chang R, Fryer JD. Culture shock: microglial heterogeneity, activation, and disrupted single-cell microglial networks in vitro. Mol Neurodegener 2022; 17:26. [PMID: 35346293 PMCID: PMC8962153 DOI: 10.1186/s13024-022-00531-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 03/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Microglia, the resident immune cells of the brain, play a critical role in numerous diseases, but are a minority cell type and difficult to genetically manipulate in vivo with viral vectors and other approaches. Primary cultures allow a more controlled setting to investigate these cells, but morphological and transcriptional changes upon removal from their normal brain environment raise many caveats from in vitro studies. METHODS To investigate whether cultured microglia recapitulate in vivo microglial signatures, we used single-cell RNA sequencing (scRNAseq) to compare microglia freshly isolated from the brain to primary microglial cultures. We performed cell population discovery, differential expression analysis, and gene co-expression module analysis to compare signatures between in vitro and in vivo microglia. We constructed causal predictive network models of transcriptional regulators from the scRNAseq data and identified a set of potential key drivers of the cultured phenotype. To validate this network analysis, we knocked down two of these key drivers, C1qc and Prdx1, in primary cultured microglia and quantified changes in microglial activation markers. RESULTS We found that, although often assumed to be a relatively homogenous population of cells in culture, in vitro microglia are a highly heterogeneous population consisting of distinct subpopulations of cells with transcriptional profiles reminiscent of macrophages and monocytes, and are marked by transcriptional programs active in neurodegeneration and other disease states. We found that microglia in vitro presented transcriptional activation of a set of "culture shock genes" not found in freshly isolated microglia, characterized by strong upregulation of disease-associated genes including Apoe, Lyz2, and Spp1, and downregulation of homeostatic microglial markers, including Cx3cr1, P2ry12, and Tmem119. Finally, we found that cultured microglia prominently alter their transcriptional machinery modulated by key drivers from the homeostatic to activated phenotype. Knockdown of one of these drivers, C1qc, resulted in downregulation of microglial activation genes Lpl, Lyz2, and Ccl4. CONCLUSIONS Overall, our data suggest that when removed from their in vivo home environment, microglia suffer a severe case of "culture shock", drastically modulating their transcriptional regulatory network state from homeostatic to activated through upregulation of modules of culture-specific genes. Consequently, cultured microglia behave as a disparate cell type that does not recapitulate the homeostatic signatures of microglia in vivo. Finally, our predictive network model discovered potential key drivers that may convert activated microglia back to their homeostatic state, allowing for more accurate representation of in vivo states in culture. Knockdown of key driver C1qc partially attenuated microglial activation in vitro, despite C1qc being only weakly upregulated in culture. This suggests that even genes that are not strongly differentially expressed across treatments or preparations may drive downstream transcriptional changes in culture.
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Affiliation(s)
- Mika P Cadiz
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA.,Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Tanner D Jensen
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Jonathon P Sens
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA.,Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Kuixi Zhu
- Department of Neurology, University of Arizona, Tucson, AZ, 85721, USA
| | - Won-Min Song
- Department of Genetics & Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Bin Zhang
- Department of Genetics & Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Mark Ebbert
- Sanders-Brown Center on Aging, Biomedical Informatics, and Department of Neuroscience, University of Kentucky, Lexington, KY, 40536, USA
| | - Rui Chang
- Department of Neurology, University of Arizona, Tucson, AZ, 85721, USA.
| | - John D Fryer
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA. .,Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA.
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8
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Olney KC, Todd KT, Pallegar PN, Jensen TD, Cadiz MP, Gibson KA, Barnett JH, de Ávila C, Bouchal SM, Rabichow BE, Ding Z, Wojtas AM, Wilson MA, Fryer JD. Widespread choroid plexus contamination in sampling and profiling of brain tissue. Mol Psychiatry 2022; 27:1839-1847. [PMID: 34983929 PMCID: PMC9095494 DOI: 10.1038/s41380-021-01416-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/01/2021] [Accepted: 11/29/2021] [Indexed: 11/08/2022]
Abstract
The choroid plexus, a tissue responsible for producing cerebrospinal fluid, is found predominantly in the lateral and fourth ventricles of the brain. This highly vascularized and ciliated tissue is made up of specialized epithelial cells and capillary networks surrounded by connective tissue. Given the complex structure of the choroid plexus, this can potentially result in contamination during routine tissue dissection. Bulk and single-cell RNA sequencing studies, as well as genome-wide in situ hybridization experiments (Allen Brain Atlas), have identified several canonical markers of choroid plexus such as Ttr, Folr1, and Prlr. We used the Ttr gene as a marker to query the Gene Expression Omnibus database for transcriptome studies of brain tissue and identified at least some level of likely choroid contamination in numerous studies that could have potentially confounded data analysis and interpretation. We also analyzed transcriptomic datasets from human samples from Allen Brain Atlas and the Genotype-Tissue Expression (GTEx) database and found abundant choroid contamination, with regions in closer proximity to choroid more likely to be impacted such as hippocampus, cervical spinal cord, substantia nigra, hypothalamus, and amygdala. In addition, analysis of both the Allen Brain Atlas and GTEx datasets for differentially expressed genes between likely "high contamination" and "low contamination" groups revealed a clear enrichment of choroid plexus marker genes and gene ontology pathways characteristic of these ciliated choroid cells. Inclusion of these contaminated samples could result in biological misinterpretation or simply add to the statistical noise and mask true effects. We cannot assert that Ttr or other genes/proteins queried in targeted assays are artifacts from choroid contamination as some of these differentials may be due to true biological effects. However, for studies that have an unequal distribution of choroid contamination among groups, investigators may wish to remove contaminated samples from analyses or incorporate choroid marker gene expression into their statistical modeling. In addition, we suggest that a simple RT-qPCR or western blot for choroid markers would mitigate unintended choroid contamination for any experiment, but particularly for samples intended for more costly omic profiling. This study highlights an unexpected problem for neuroscientists, but it is also quite possible that unintended contamination of adjacent structures occurs during dissections for other tissues but has not been widely recognized.
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Affiliation(s)
- Kimberly C Olney
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, 85282, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, 85282, USA
| | - Kennedi T Todd
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Praveen N Pallegar
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Mayo Clinic MD/PhD Training Program, Scottsdale, AZ, 85259, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Tanner D Jensen
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Mika P Cadiz
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Katelin A Gibson
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Joseph H Barnett
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Mayo Clinic MD/PhD Training Program, Scottsdale, AZ, 85259, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Camila de Ávila
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Samantha M Bouchal
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Mayo Clinic MD/PhD Training Program, Scottsdale, AZ, 85259, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Benjamin E Rabichow
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Zonghui Ding
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | | | - Melissa A Wilson
- School of Life Sciences, Arizona State University, Tempe, AZ, 85282, USA
- The Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ, 85282, USA
| | - John D Fryer
- Department of Neuroscience, Mayo Clinic, Scottsdale, AZ, 85259, USA.
- Mayo Clinic MD/PhD Training Program, Scottsdale, AZ, 85259, USA.
- Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA.
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9
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Gorzynski JE, Goenka SD, Shafin K, Jensen TD, Fisk DG, Grove ME, Spiteri E, Pesout T, Monlong J, Baid G, Bernstein JA, Ceresnak S, Chang PC, Christle JW, Chubb H, Dalton KP, Dunn K, Garalde DR, Guillory J, Knowles JW, Kolesnikov A, Ma M, Moscarello T, Nattestad M, Perez M, Ruzhnikov MRZ, Samadi M, Setia A, Wright C, Wusthoff CJ, Xiong K, Zhu T, Jain M, Sedlazeck FJ, Carroll A, Paten B, Ashley EA. Ultrarapid Nanopore Genome Sequencing in a Critical Care Setting. N Engl J Med 2022; 386:700-702. [PMID: 35020984 DOI: 10.1056/nejmc2112090] [Citation(s) in RCA: 83] [Impact Index Per Article: 41.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
| | | | - Kishwar Shafin
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA
| | | | | | | | | | - Trevor Pesout
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA
| | - Jean Monlong
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA
| | | | | | | | | | | | | | | | - Kyla Dunn
- Stanford Children's Health, Palo Alto, CA
| | | | | | | | | | | | | | | | | | | | | | | | - Chris Wright
- Oxford Nanopore Technologies, Oxford, United Kingdom
| | | | | | | | - Miten Jain
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA
| | | | | | - Benedict Paten
- University of California at Santa Cruz Genomics Institute, Santa Cruz, CA
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10
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Wojtas AM, Carlomagno Y, Sens JP, Kang SS, Jensen TD, Kurti A, Baker KE, Berry TJ, Phillips VR, Castanedes MC, Awan A, DeTure M, De Castro CHF, Librero AL, Yue M, Daughrity L, Jansen-West KR, Cook CN, Dickson DW, Petrucelli L, Fryer JD. Clusterin ameliorates tau pathology in vivo by inhibiting fibril formation. Acta Neuropathol Commun 2020; 8:210. [PMID: 33261653 PMCID: PMC7708249 DOI: 10.1186/s40478-020-01079-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 11/11/2020] [Indexed: 11/10/2022] Open
Abstract
The molecular chaperone Clusterin (CLU) impacts the amyloid pathway in Alzheimer's disease (AD) but its role in tau pathology is unknown. We observed CLU co-localization with tau aggregates in AD and primary tauopathies and CLU levels were upregulated in response to tau accumulation. To further elucidate the effect of CLU on tau pathology, we utilized a gene delivery approach in CLU knock-out (CLU KO) mice to drive expression of tau bearing the P301L mutation. We found that loss of CLU was associated with exacerbated tau pathology and anxiety-like behaviors in our mouse model of tauopathy. Additionally, we found that CLU dramatically inhibited tau fibrilization using an in vitro assay. Together, these results demonstrate that CLU plays a major role in both amyloid and tau pathologies in AD.
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Affiliation(s)
- Aleksandra M Wojtas
- Department of Neuroscience, Mayo Clinic, Collaborative Research Building CR03-010 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Yari Carlomagno
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Jonathon P Sens
- Department of Neuroscience, Mayo Clinic, Collaborative Research Building CR03-010 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Silvia S Kang
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Tanner D Jensen
- Department of Neuroscience, Mayo Clinic, Collaborative Research Building CR03-010 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
| | - Aishe Kurti
- Department of Neuroscience, Mayo Clinic, Collaborative Research Building CR03-010 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
| | - Kelsey E Baker
- Department of Neuroscience, Mayo Clinic, Collaborative Research Building CR03-010 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
| | - Taylor J Berry
- Department of Neuroscience, Mayo Clinic, Collaborative Research Building CR03-010 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
| | | | | | - Ayesha Awan
- Department of Neuroscience, Mayo Clinic, Collaborative Research Building CR03-010 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
| | - Michael DeTure
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
| | | | - Ariston L Librero
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Mei Yue
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Lillian Daughrity
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
| | | | - Casey N Cook
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - Leonard Petrucelli
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA
| | - John D Fryer
- Department of Neuroscience, Mayo Clinic, Collaborative Research Building CR03-010 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA.
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, 85259, USA.
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11
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Ebbert MTW, Jensen TD, Jansen-West K, Sens JP, Reddy JS, Ridge PG, Kauwe JSK, Belzil V, Pregent L, Carrasquillo MM, Keene D, Larson E, Crane P, Asmann YW, Ertekin-Taner N, Younkin SG, Ross OA, Rademakers R, Petrucelli L, Fryer JD. Systematic analysis of dark and camouflaged genes reveals disease-relevant genes hiding in plain sight. Genome Biol 2019; 20:97. [PMID: 31104630 PMCID: PMC6526621 DOI: 10.1186/s13059-019-1707-2] [Citation(s) in RCA: 93] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 05/06/2019] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND The human genome contains "dark" gene regions that cannot be adequately assembled or aligned using standard short-read sequencing technologies, preventing researchers from identifying mutations within these gene regions that may be relevant to human disease. Here, we identify regions with few mappable reads that we call dark by depth, and others that have ambiguous alignment, called camouflaged. We assess how well long-read or linked-read technologies resolve these regions. RESULTS Based on standard whole-genome Illumina sequencing data, we identify 36,794 dark regions in 6054 gene bodies from pathways important to human health, development, and reproduction. Of these gene bodies, 8.7% are completely dark and 35.2% are ≥ 5% dark. We identify dark regions that are present in protein-coding exons across 748 genes. Linked-read or long-read sequencing technologies from 10x Genomics, PacBio, and Oxford Nanopore Technologies reduce dark protein-coding regions to approximately 50.5%, 35.6%, and 9.6%, respectively. We present an algorithm to resolve most camouflaged regions and apply it to the Alzheimer's Disease Sequencing Project. We rescue a rare ten-nucleotide frameshift deletion in CR1, a top Alzheimer's disease gene, found in disease cases but not in controls. CONCLUSIONS While we could not formally assess the association of the CR1 frameshift mutation with Alzheimer's disease due to insufficient sample-size, we believe it merits investigating in a larger cohort. There remain thousands of potentially important genomic regions overlooked by short-read sequencing that are largely resolved by long-read technologies.
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Affiliation(s)
- Mark T. W. Ebbert
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
- Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL 32224 USA
| | - Tanner D. Jensen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
| | | | - Jonathon P. Sens
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
| | - Joseph S. Reddy
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
| | - Perry G. Ridge
- Department of Biology, Brigham Young University, Provo, UT 84602 USA
| | - John S. K. Kauwe
- Department of Biology, Brigham Young University, Provo, UT 84602 USA
| | - Veronique Belzil
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
| | - Luc Pregent
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
| | | | - Dirk Keene
- Department of Pathology, University of Washington, Seattle, WA 98195 USA
| | - Eric Larson
- Department of Medicine, University of Washington, Seattle, WA 98195 USA
| | - Paul Crane
- Department of Medicine, University of Washington, Seattle, WA 98195 USA
| | - Yan W. Asmann
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL 32224 USA
| | - Nilufer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
- Department of Neurology, Mayo Clinic, Jacksonville, FL 32224 USA
| | | | - Owen A. Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
| | - Leonard Petrucelli
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
- Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL 32224 USA
| | - John D. Fryer
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224 USA
- Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL 32224 USA
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12
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Li J, Zhang X, Jensen TD, Wang K, Kølvraa S, Bolund L. Chromosomal imbalances mapped by array-based comparative genomic hybridization in an integrated approach to combat breast cancer in Denmark. Breast Cancer Res 2005. [PMCID: PMC4233588 DOI: 10.1186/bcr1167] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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13
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Bolt G, Jensen TD, Gottschalck E, Arctander P, Appel MJ, Buckland R, Blixenkrone-Møller M. Genetic diversity of the attachment (H) protein gene of current field isolates of canine distemper virus. J Gen Virol 1997; 78 ( Pt 2):367-72. [PMID: 9018059 DOI: 10.1099/0022-1317-78-2-367] [Citation(s) in RCA: 94] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
To characterize the variability of recent field isolates of canine distemper virus (CDV) from different hosts and geographical areas, we conducted nucleotide sequence analysis of the gene encoding the haemagglutinin (H), the attachment protein of this virus. Pronounced differences between field isolates were revealed in comparison to the Convac and Onderstepoort vaccine strains. The diversity of CDV appeared to exceed that determined for measles virus. Phylogenetic analysis also separated the field isolates of CDV from the vaccine strains and provided evidence for the existence of different contemporary genotypes of CDV. Isolates from a Greenlandic sledge dog and a Siberian seal formed a distinct lineage. The remaining isolates formed a group. This group contained two European isolates from mink and ferret, a single lineage comprising three European dog isolates, and another separate lineage of North American isolates from dog, javelina, raccoon and captive leopards.
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Affiliation(s)
- G Bolt
- Department of Veterinary Microbiology, The Royal Veterinary and Agricultural University, Frederiksberg C, Denmark
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14
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Abstract
DMV, dolphin morbillivirus, a paramyxovirus of uncertain origin recently emerged in Mediterranean dolphins. This study presents the complete nucleotide sequence of the hemagglutinin (H) gene including the gene boundaries. The single open reading frame of the DMV H gene encodes a protein of 604 residues which exhibits overall sequence characteristics similar to the H genes of other morbilliviruses. When compared to its closest homologues, measles virus (MV) and rinderpest virus (RPV), DMV has, respectively, 44 and 46% of amino acid residues in identical positions. The primary sequence of the DMV H protein is markedly less conserved than that of the fusion protein. The comparative data at the genomic level correspond with cross-neutralization studies with different morbilliviruses. Retrospective serogical studies dating back to 1983 indicate DMV-like infections in whales of the eastern Atlantic. The presented data support and extend previous studies suggesting that this novel morbillivirus is one of the phylogenetically oldest morbilliviruses known to circulate today. The relationship of DMV and established morbilliviruses to the newly emerged candidate morbillivirus infecting horse and man is discussed.
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Affiliation(s)
- M Blixenkrone-Møller
- Laboratory of Virology and Immunology, Royal Veterinary and Agricultural University, Frederiksberg, Denmark
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15
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Abstract
Pancreastatin, a 49-amino acid peptide with a COOH-terminal glycine amide, was originally isolated from porcine pancreas, but pancreastatin immunoreactivity has been found in several neuroendocrine tissues. There are strong indications that pancreastatin is derived from chromogranin A, since the amino acid sequence 240-288 in porcine chromogranin A corresponds to pancreastatin flanked by typical signals for proteolytic processing. We have studied the effect of electric stimulation of the nervous supply to perfused porcine pancreas, antrum, nonantral stomach, and small intestine on the release of immunoreactive pancreastatin, and we characterized the molecular nature of the secreted immunoreactivity by using a radioimmunoassay specific for the COOH-terminal glycine amide of porcine pancreastatin in combination with chromatography. In all tissues nerve stimulation significantly increased the release of immunoreactive pancreastatin. The secreted immunoreactive pancreastatin was heterogeneous, consisting of pancreastatin itself, a COOH-terminal pancreastatin fragment, and NH2-terminally extended pancreastatin forms. Pancreastatin predominated in the perfusate from pancreas and antrum, whereas mainly NH2-terminally extended molecular forms were secreted from the antrectomized stomach and small intestine. The different molecular forms of pancreastatin were secreted from the perfused organs in the same molar ratio as they occur in extracts of the corresponding tissues. Thus, pancreastatin and other chromogranin A-derived peptides in organ-specific proportions regularly accompany the secretion of the peptide hormones from the gastrointestinal tissues on appropriate stimulation.
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Affiliation(s)
- T D Jensen
- Dept. of Clinical Chemistry, Bispebjerg Hospital, Denmark
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16
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Abstract
Pancreastatin is a 49 amino acid peptide with a C-terminal glycine amide originally isolated from porcine pancreas. There are strong indications that pancreastatin is derived from chromogranin A, since the amino acid sequence 240-288 in porcine chromogranin A contains pancreastatin flanked by typical signals for proteolytic processing. Several molecular forms of immunoreactive pancreastatin have been reported to be present in porcine adrenal medulla, but no information on the secretion of the peptides is available. We studied stimuli for the release of immunoreactive pancreastatin from adrenal glands as well as the molecular nature of the released immunoreactivity using isolated, perfused, porcine adrenal glands with intact splanchnic nerve supply and a radioimmunoassay specific for the C-terminal glycine amide of porcine pancreastatin in combination with chromatography. Stimulation of the splanchnic nerves greatly enhanced the release of immunoreactive pancreastatin by a mechanism that seems to involve cholinergic nicotinic transmission. The pancreastatin immunoreactivity was due to large amounts of a N-terminally extended pancreastatin form, possibly corresponding to the chromogranin A(1-288) fragment and small amounts of pancreastatin and a C-terminal pancreastatin fragment. Adrenal extracts also contained unprocessed chromogranin A. We conclude that in the porcine adrenals at least 25% of chromogranin A is processed to smaller molecular forms with the pancreastatin sequence forming their C-terminus. These forms appear to be released in parallel with the catecholamines.
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Affiliation(s)
- T D Jensen
- Department of Clinical Chemistry, Bispebjerg Hospital, Copenhagen, Denmark
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17
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Abstract
Calcium-dependent binding of C-reactive protein (CRP) to Aspergillus fumigatus was determined by enzyme-linked immunosorbent assay. A homogenate of young hyphae was fractionated by hydrophobic interaction chromatography followed by gel filtration. High CRP-binding activity was found in a fraction of mol. wt c. 500,000 which was characterised by strong binding to the hydrophobic column. Three fractions of less conspicuous CRP-binding activity were identified (c. 500 000, 150 000 and 150 000-50 000 mol. wt respectively). In these four fractions, phosphorylcholine was detected by an anti-phosphorylcholine mouse hybridoma antibody. Some CRP-binding activity in fractions with low affinity for the hydrophobic column did not correspond closely with the presence of phosphorylcholine. It is suggested that C-reactive substance in A. fumigatus is heterogeneous. The C-reactive substances did not correspond with fractions containing major antigens (470 000 and 250 000 mol. wt respectively) which elicit a strong immune response in man.
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