Whole-genome analysis reveals the contribution of non-coding de novo transposon insertions to autism spectrum disorder

Abstract Background Retrotransposons have been implicated as causes of Mendelian disease, but their role in autism spectrum disorder (ASD) has not been systematically defined, because they are only called with adequate sensitivity from whole genome sequencing (WGS) data and a large enough cohort for...

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Autores principales: Rebeca Borges-Monroy, Chong Chu, Caroline Dias, Jaejoon Choi, Soohyun Lee, Yue Gao, Taehwan Shin, Peter J. Park, Christopher A. Walsh, Eunjung Alice Lee
Formato: article
Lenguaje:EN
Publicado: BMC 2021
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Acceso en línea:https://doaj.org/article/8f9cee324ba7466e90e75f9ca6ee92f3
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Sumario:Abstract Background Retrotransposons have been implicated as causes of Mendelian disease, but their role in autism spectrum disorder (ASD) has not been systematically defined, because they are only called with adequate sensitivity from whole genome sequencing (WGS) data and a large enough cohort for this analysis has only recently become available. Results We analyzed WGS data from a cohort of 2288 ASD families from the Simons Simplex Collection by establishing a scalable computational pipeline for retrotransposon insertion detection. We report 86,154 polymorphic retrotransposon insertions—including > 60% not previously reported—and 158 de novo retrotransposition events. The overall burden of de novo events was similar between ASD individuals and unaffected siblings, with 1 de novo insertion per 29, 117, and 206 births for Alu, L1, and SVA respectively, and 1 de novo insertion per 21 births total. However, ASD cases showed more de novo L1 insertions than expected in ASD genes. Additionally, we observed exonic insertions in loss-of-function intolerant genes, including a likely pathogenic exonic insertion in CSDE1, only in ASD individuals. Conclusions These findings suggest a modest, but important, impact of intronic and exonic retrotransposon insertions in ASD, show the importance of WGS for their analysis, and highlight the utility of specific bioinformatic tools for high-throughput detection of retrotransposon insertions.