Structural variants (SVs), defined as any genomic rearrangements of 50 or more bp, are an important source of genetic diversity and have been linked to many diseases. Here, we report 170,996 SVs which were constructed using 1,760 short-read whole genomes from aging and Alzheimer’s disease subjects. We quantified the impact of cis-acting SVs on several molecular traits (SV-xQTL) including histone modification, gene expression, mRNA splicing, and protein abundance in post-mortem brain tissues. Our study provides a comprehensive view of the mechanisms linking structural variation to gene regulation and provides a valuable resource for understanding the functional impact of SVs in the aged human brain.

Ricardo A. Vialle, PhD
Icahn School of Medicine at Mount Sinai

Katia de Paiva Lopes, PhD
Icahn School of Medicine at Mount Sinai

David A. Bennett, MD
Rush University

John F. Crary, MD, PhD
Icahn School of Medicine at Mount Sinai

Towfique Raj, PhD
Icahn School of Medicine at Mount Sinai

This work was supported by grants from the US National Institutes of Health (NIH NIA U01 AG06888001, NIA R01-AG054005, NIA R56-AG055824, and NIA R01-AG054008).

Acknowledgment statement for any data distributed by NIAGADS:

Data for this study were prepared, archived, and distributed by the National Institute on Aging Alzheimer's Disease Data Storage Site (NIAGADS) at the University of Pennsylvania (U24-AG041689), funded by the National Institute on Aging.

For investigators using Integrating whole-genome sequencing with multi-omic data reveals the impact of structural variants on gene regulation in the human brain - Vialle et al. 2022 data:

We thank the participants of AMP-AD cohorts for their essential contributions and gift to these projects. ROSMAP study data were provided by the Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago. Data collection was supported through funding by National Institute on Aging (NIA) grants P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, U01AG61356, and the Illinois Department of Public Health. Mayo RNA-seq study data were provided by the following sources: the Mayo Clinic Alzheimer's Disease Genetic Studies, led by Dr. Nilufer Ertekin-Taner and Dr. Steven G. Younkin, Mayo Clinic, Jacksonville, Florida, using samples from the Mayo Clinic Study of Aging, the Mayo Clinic Alzheimer's Disease Research Center, and the Mayo Clinic Brain Bank. Data collection was supported through funding by NIA grants P50 AG016574, R01 AG032990, U01 AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, and R01 AG003949; National Institute of Neurological Disorders and Stroke (NINDS) grant R01 NS080820; the CurePSP Foundation; and support from Mayo Foundation. Study data include samples collected through the Sun Health Research Institute Brain and Body Donation Program of Sun City, Arizona. The Brain and Body Donation Program is supported by the National Institute of Neurological Disorders and Stroke (U24 NS072026, National Brain and Tissue Resource for Parkinson's Disease and Related Disorders), the NIA (P30 AG19610, Arizona Alzheimer's Disease Core Center), the Arizona Department of Health Services (contract 211002, Arizona Alzheimer's Research Center), the Arizona Biomedical Research Commission (contracts 4001, 0011, 05-901, and 1001 to the Arizona Parkinson's Disease Consortium), and the Michael J. Fox Foundation for Parkinson's Research. Mount Sinai Brain Bank (MSBB) data were generated from post-mortem brain tissue collected through the Mount Sinai VA Medical Center Brain Bank and were provided by Dr. Eric Schadt of the Mount Sinai School of Medicine through funding from NIA grant U01AG046170. The authors thank Dr. Bin Zhang and Dr. Erming Wang for assistance with data sharing, and members of the Raj and Crary labs for their feedback on the manuscript. We thank Jack Humphrey for his insightful comments and suggestions during this work. This work was supported in part through the computational and data resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. We thank the Mount Sinai Technology Development core for help and support with performing long-read sequencing. The research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD026880.

  • Vialle RA, de Paiva Lopes K, Bennett DA, Crary JF, Raj T. Integrating whole-genome sequencing with multi-omic data reveals the impact of structural variants on gene regulation in the human brain. Nat Neurosci. 2022 Apr. doi: 10.1038/s41593-022-01031-7 PubMed link