PT  - JOURNAL ARTICLE
AU  - Donna M. Werling
AU  - Harrison Brand
AU  - Joon-Yong An
AU  - Matthew R. Stone
AU  - Joseph T. Glessner
AU  - Lingxue Zhu
AU  - Ryan L. Collins
AU  - Shan Dong
AU  - Ryan M. Layer
AU  - Eirene Markenscoff-Papadimitriou
AU  - Andrew Farrell
AU  - Grace B. Schwartz
AU  - Benjamin B. Currall
AU  - Jeanselle Dea
AU  - Clif Duhn
AU  - Carolyn Erdman
AU  - Michael Gilson
AU  - Robert E. Handsaker
AU  - Seva Kashin
AU  - Lambertus Klei
AU  - Jeffrey D. Mandell
AU  - Tomasz J. Nowakowski
AU  - Yuwen Liu
AU  - Sirisha Pochareddy
AU  - Louw Smith
AU  - Michael F. Walker
AU  - Harold Z. Wang
AU  - Mathew J. Waterman
AU  - Xin He
AU  - Arnold R. Kriegstein
AU  - John L. Rubenstein
AU  - Nenad Sestan
AU  - Steven A. McCarroll
AU  - Ben M. Neale
AU  - Hilary Coon
AU  - A. Jeremy Willsey
AU  - Joseph D. Buxbaum
AU  - Mark J. Daly
AU  - Matthew W. State
AU  - Aaron Quinlan
AU  - Gabor T. Marth
AU  - Kathryn Roeder
AU  - Bernie Devlin
AU  - Michael E. Talkowski
AU  - Stephan J. Sanders
TI  - Limited contribution of rare, noncoding variation to autism spectrum disorder from sequencing of 2,076 genomes in quartet families
AID  - 10.1101/127043
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 127043
4099  - http://biorxiv.org/content/early/2017/04/13/127043.short
4100  - http://biorxiv.org/content/early/2017/04/13/127043.full
AB  - Genomic studies to date in autism spectrum disorder (ASD) have largely focused on newly arising mutations that disrupt protein coding sequence and strongly influence risk. We evaluate the contribution of noncoding regulatory variation across the size and frequency spectrum through whole genome sequencing of 519 ASD cases, their unaffected sibling controls, and parents. Cases carry a small excess of de novo (1.02-fold) noncoding variants, which is not significant after correcting for paternal age. Assessing 51,801 regulatory classes, no category is significantly associated with ASD after correction for multiple testing. The strongest signals are observed in coding regions, including structural variation not detected by previous technologies and missense variation. While rare noncoding variation likely contributes to risk in neurodevelopmental disorders, no category of variation has impact equivalent to loss-of-function mutations. Average effect sizes are likely to be smaller than that for coding variation, requiring substantially larger samples to quantify this risk.