Author
Listed:
- Lide Han
(Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
Vanderbilt Genetics Institute, Vanderbilt University Medical Center)
- Xuefang Zhao
(Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology (M.I.T.)
Center for Genomic Medicine, Massachusetts General Hospital
Department of Neurology, Massachusetts General Hospital and Harvard Medical School)
- Mary Lauren Benton
(Vanderbilt Genetics Institute, Vanderbilt University Medical Center
Department of Biomedical Informatics, Vanderbilt University Medical Center)
- Thaneer Perumal
(Sage Bionetworks)
- Ryan L. Collins
(Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology (M.I.T.)
Center for Genomic Medicine, Massachusetts General Hospital
Division of Medical Sciences, Harvard Medical School)
- Gabriel E. Hoffman
(Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai
Icahn Institute for Data Science and Genomic Sciences, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai)
- Jessica S. Johnson
(Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai)
- Laura Sloofman
(Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai)
- Harold Z. Wang
(Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology (M.I.T.)
Center for Genomic Medicine, Massachusetts General Hospital)
- Matthew R. Stone
(Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology (M.I.T.)
Center for Genomic Medicine, Massachusetts General Hospital)
- Kristen J. Brennand
(Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai)
- Harrison Brand
(Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology (M.I.T.)
Center for Genomic Medicine, Massachusetts General Hospital
Department of Neurology, Massachusetts General Hospital and Harvard Medical School)
- Solveig K. Sieberts
(Sage Bionetworks)
- Stefano Marenco
(Human Brain Collection Core, Intramural Research Program, NIMH, National Institutes of Health)
- Mette A. Peters
(Sage Bionetworks)
- Barbara K. Lipska
(Human Brain Collection Core, Intramural Research Program, NIMH, National Institutes of Health)
- Panos Roussos
(Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai
Icahn Institute for Data Science and Genomic Sciences, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
Friedman Brain Institute, Icahn School of Medicine at Mount Sinai
Psychiatry, JJ Peters VA Medical Center)
- John A. Capra
(Vanderbilt Genetics Institute, Vanderbilt University Medical Center
Department of Biomedical Informatics, Vanderbilt University Medical Center
Department of Biological Sciences, Vanderbilt University)
- Michael Talkowski
(Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology (M.I.T.)
Center for Genomic Medicine, Massachusetts General Hospital
Department of Neurology, Massachusetts General Hospital and Harvard Medical School
Division of Medical Sciences, Harvard Medical School)
- Douglas M. Ruderfer
(Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
Vanderbilt Genetics Institute, Vanderbilt University Medical Center
Department of Biomedical Informatics, Vanderbilt University Medical Center
Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center)
Abstract
Structural variants (SVs) contribute to many disorders, yet, functionally annotating them remains a major challenge. Here, we integrate SVs with RNA-sequencing from human post-mortem brains to quantify their dosage and regulatory effects. We show that genic and regulatory SVs exist at significantly lower frequencies than intergenic SVs. Functional impact of copy number variants (CNVs) stems from both the proportion of genic and regulatory content altered and loss-of-function intolerance of the gene. We train a linear model to predict expression effects of rare CNVs and use it to annotate regulatory disruption of CNVs from 14,891 independent genome-sequenced individuals. Pathogenic deletions implicated in neurodevelopmental disorders show significantly more extreme regulatory disruption scores and if rank ordered would be prioritized higher than using frequency or length alone. This work shows the deleteriousness of regulatory SVs, particularly those altering CTCF sites and provides a simple approach for functionally annotating the regulatory consequences of CNVs.
Suggested Citation
Lide Han & Xuefang Zhao & Mary Lauren Benton & Thaneer Perumal & Ryan L. Collins & Gabriel E. Hoffman & Jessica S. Johnson & Laura Sloofman & Harold Z. Wang & Matthew R. Stone & Kristen J. Brennand & , 2020.
"Functional annotation of rare structural variation in the human brain,"
Nature Communications, Nature, vol. 11(1), pages 1-13, December.
Handle:
RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16736-1
DOI: 10.1038/s41467-020-16736-1
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