bioRxivGeneticsPreprint
Whole-genome analysis of de novo and polymorphic retrotransposon insertions in Autism Spectrum Disorder
Rebeca Borges-MonroyiD, Chong ChuiD, Caroline DiasiD, Jaejoon ChoiiD, Soohyun LeeiD, Yue Gao, Taehwan ShiniD, Peter J. ParkiD, Christopher A. WalshiD, Eunjung Alice LeeiD
Abstract
Retrotransposons are dynamic forces in evolutionary genomics and have been implicated as causes of Mendelian disease and hereditary cancer, but their role in Autism Spectrum Disorder (ASD) has never been systematically defined. Here, we report 86,154 polymorphic retrotransposon insertions including >60% not previously reported and 158 de novo retrotransposition events identified in whole genome sequencing (WGS) data of 2,288 families with ASD from the Simons Simplex Collection (SSC). As expected, the overall burden of de novo events was similar between ASD individuals and unaffected siblings, with 1 de novo insertion per 29, 104, and 192 births for Alu, L1, and SVA respectively, and 1 de novo insertion per 20 births total, while the location of transposon insertions differed between ASD and unaffected individuals. ASD cases showed more de novo L1 insertions than expected in ASD genes, and we also found de novo intronic retrotransposition events in known syndromic ASD genes in affected individuals but not in controls. Additionally, we observed exonic insertions in genes with a high probability of being loss-of-function intolerant, including a likely causative exonic insertion in CSDE1, only in ASD individuals. Although de novo retrotransposition occurs less frequently than single nucleotide and copy number variants, these findings suggest a modest, but important, impact of intronic and exonic retrotransposition mutations in ASD and highlight the utility of developing specific bioinformatic tools for high-throughput detection of transposable element insertions.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 4
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