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. 2023 Nov 20;10(1):813.
doi: 10.1038/s41597-023-02645-7.

Genomic data resources of the Brain Somatic Mosaicism Network for neuropsychiatric diseases

Collaborators, Affiliations

Genomic data resources of the Brain Somatic Mosaicism Network for neuropsychiatric diseases

McKinzie A Garrison et al. Sci Data. .

Abstract

Somatic mosaicism is defined as an occurrence of two or more populations of cells having genomic sequences differing at given loci in an individual who is derived from a single zygote. It is a characteristic of multicellular organisms that plays a crucial role in normal development and disease. To study the nature and extent of somatic mosaicism in autism spectrum disorder, bipolar disorder, focal cortical dysplasia, schizophrenia, and Tourette syndrome, a multi-institutional consortium called the Brain Somatic Mosaicism Network (BSMN) was formed through the National Institute of Mental Health (NIMH). In addition to genomic data of affected and neurotypical brains, the BSMN also developed and validated a best practices somatic single nucleotide variant calling workflow through the analysis of reference brain tissue. These resources, which include >400 terabytes of data from 1087 subjects, are now available to the research community via the NIMH Data Archive (NDA) and are described here.

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Conflict of interest statement

JVM is an inventor on patent US6150160, is a paid consultant for Gilead Sciences, and serves on the scientific advisory board of Tessera Therapeutics Inc., where he is paid as a consultant and has equity options. He has also recently served on the American Society of Human Genetics Board of Directors. CAW is a paid consultant to Third Rock Ventures and Flagship Pioneering, and is on the Clinical Advisory Board of Maze Therapeutics. DRW is on the Scientific Advisory Boards of Sage Therapeutics and Pasithea Therapeutics. The other authors do not declare competing interests. This article was prepared while MAP was employed at Sage Bionetworks. The opinions expressed in this article are the author’s own and do not reflect the view of the National Institute on Aging, the National Institutes of Health, the Department of Health and Human Services, or the United States government.

Figures

Fig. 1
Fig. 1
Heterozygous and homozygous (a) SNP and (b) indel counts in targeted exonic regions. Data represents uniformly processed WES data of cohorts from the University of San Diego (NDA ID 2968), University of Michigan (NDA ID 2966), and Kennedy Krieger Institute (KKI; NDA ID 2964). Phenotype for each cohort is marked at the bottom of the figure in a rugchart.
Fig. 2
Fig. 2
Heterozygous and homozygous (a) SNP and (b) indel counts in the uniformly processed WGS data in the cohorts from Mount Sinai School of Medicine (MSSM; NDA ID 2965), University of San Diego (UCSD; NDA ID 2968), Yale University (NDA ID 2961), Harvard University (NDA ID 2962), and the Lieber Institute for Brain Development (LIBD; NDA ID 2967). Phenotype is marked at the bottom in a rugchart. Some samples with possible contamination are labeled.
Fig. 3
Fig. 3
Variant allele frequencies (VAFs) for heterozygous SNPs were obtained for each sample using GATK HaplotypeCaller with ploidy 2. Two example distributions are shown here for samples LIBD01 and LIBD104 (collection 2967). The distribution is shifted from 50% and does not appear normally distributed for LIBD104 suggesting contamination of the sequenced sample with unrelated DNA.
Fig. 4
Fig. 4
Ratios of heterozygous and homozygous indels to SNPs across all cohorts for all uniformly processed WGS data.
Fig. 5
Fig. 5
Quality of RNA-seq data. (a) Postmortem interval (PMI) of affected (n = 38) and control (n = 42) individuals in the two Yale cohorts (collections 2960 and 2961), which were the only cohorts with such a data type. Differences were not statistically significant (p > 0.05). (b) RIN values of ASD-affected (n = 63 ASD, n = 23 suspected ASD samples) and control (n = 73 neurotypical control samples) RNA-seq samples from Yale cohort 2960.

References

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