Unknown

Dataset Information

0

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder.


ABSTRACT: Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

SUBMITTER: Werling DM 

PROVIDER: S-EPMC5961723 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder.

Werling Donna M DM   Brand Harrison H   An Joon-Yong JY   Stone Matthew R MR   Zhu Lingxue L   Glessner Joseph T JT   Collins Ryan L RL   Dong Shan S   Layer Ryan M RM   Markenscoff-Papadimitriou Eirene E   Farrell Andrew A   Schwartz Grace B GB   Wang Harold Z HZ   Currall Benjamin B BB   Zhao Xuefang X   Dea Jeanselle J   Duhn Clif C   Erdman Carolyn A CA   Gilson Michael C MC   Yadav Rachita R   Handsaker Robert E RE   Kashin Seva S   Klei Lambertus L   Mandell Jeffrey D JD   Nowakowski Tomasz J TJ   Liu Yuwen Y   Pochareddy Sirisha S   Smith Louw L   Walker Michael F MF   Waterman Matthew J MJ   He Xin X   Kriegstein Arnold R AR   Rubenstein John L JL   Sestan Nenad N   McCarroll Steven A SA   Neale Benjamin M BM   Coon Hilary H   Willsey A Jeremy AJ   Buxbaum Joseph D JD   Daly Mark J MJ   State Matthew W MW   Quinlan Aaron R AR   Marth Gabor T GT   Roeder Kathryn K   Devlin Bernie B   Talkowski Michael E ME   Sanders Stephan J SJ  

Nature genetics 20180426 5


Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 51  ...[more]

Similar Datasets

2020-09-09 | GSE157658 | GEO
2021-09-10 | GSE119791 | GEO
| S-EPMC6900387 | biostudies-literature
| S-EPMC5555838 | biostudies-literature
| S-EPMC3791269 | biostudies-literature
| S-EPMC4318517 | biostudies-other
| S-EPMC5875374 | biostudies-literature
2018-02-27 | GSE111176 | GEO
| S-EPMC4819764 | biostudies-literature
| S-EPMC8900942 | biostudies-literature