Nature GeneticsGenetic & Genomic MedicinePeer-reviewed journal article
Long-read RNA-seq atlas of novel microglia isoforms elucidates disease-associated genetic regulation of splicing
Jack HumphreyiD, Erica Brophy, Roman KosoyiD, Biao ZengiD, Elena CocciaiD, Daniele MatteiiD, Ashvin RaviiD, Tatsuhiko NaitoiD, Anastasia G. EfthymiouiD, Elisa NavarroiD, Claudia De SanctisiD, Victoria Flores Almazan, Benjamin Z. MulleriD, Gijsje J. L. SnijdersiD, Amanda AllaniD, Alexandra MünchiD, Reta Birhanu KitataiD, Steven P. KleopoulosiD, Stathis ArgyriouiD, Periklis MalakatesiD, Konstantina PsychogyiouiD, Zhiping ShaoiD, Nancy J. FrancoeuriD, Chia‐Feng TsaiiD, Marina A. GritsenkoiD, , Towfique RajiD
Abstract
Microglia, the innate immune cells of the central nervous system, have been genetically implicated in multiple neurodegenerative diseases. We previously mapped the genetic regulation of gene expression and mRNA splicing in human microglia, identifying several loci where common genetic variants in microglia-specific regulatory elements explain disease risk loci identified by GWAS. However, identifying genetic effects on splicing has been challenging due to the use of short sequencing reads to identify causal isoforms. Here we present the isoform-centric microglia genomic atlas (isoMiGA) which leverages the power of long-read RNA-seq to identify 35,879 novel microglia isoforms. We show that the novel microglia isoforms are involved in stimulation response and brain region specificity. We then quantified the expression of both known and novel isoforms in a multi-ethnic meta-analysis of 555 human microglia short-read RNA-seq samples from 391 donors, the largest to date, and found associations with genetic risk loci in Alzheimers disease and Parkinsons disease. We nominate several loci that may act through complex changes in isoform and splice site usage.
- organism: human
- assay: long-read sequencing
- assay: bulk RNA-seq
- research focus: differential expression
- approach: experimental assay
- Citations
- 34
- FWCI
- 10.16
- Field percentile
- top 1%
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