Splicing QTL analysis focusing on coding sequences reveals mechanisms for disease susceptibility loci

Kensuke Yamaguchi, Kazuyoshi Ishigaki, Akari Suzuki, Yumi Tsuchida, Haruka Tsuchiya, Shuji Sumitomo, Yasuo Nagafuchi, Fuyuki Miya, Tatsuhiko Tsunoda, Hirofumi Shoda, Keishi Fujio, Kazuhiko Yamamoto and Yuta Kochi ()
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Kensuke Yamaguchi: Tokyo Medical and Dental University
Kazuyoshi Ishigaki: RIKEN Center for Integrative Medical Sciences
Akari Suzuki: RIKEN Center for Integrative Medical Sciences
Yumi Tsuchida: The University of Tokyo
Haruka Tsuchiya: The University of Tokyo
Shuji Sumitomo: The University of Tokyo
Yasuo Nagafuchi: The University of Tokyo
Fuyuki Miya: Keio University School of Medicine
Tatsuhiko Tsunoda: The University of Tokyo
Hirofumi Shoda: The University of Tokyo
Keishi Fujio: The University of Tokyo
Kazuhiko Yamamoto: RIKEN Center for Integrative Medical Sciences
Yuta Kochi: Tokyo Medical and Dental University

Nature Communications, 2022, vol. 13, issue 1, 1-13

Abstract: Abstract Splicing quantitative trait loci (sQTLs) are one of the major causal mechanisms in genome-wide association study (GWAS) loci, but their role in disease pathogenesis is poorly understood. One reason is the complexity of alternative splicing events producing many unknown isoforms. Here, we propose two approaches, namely integration and selection, for this complexity by focusing on protein-structure of isoforms. First, we integrate isoforms with the same coding sequence (CDS) and identify 369-601 integrated-isoform ratio QTLs (i2-rQTLs), which altered protein-structure, in six immune subsets. Second, we select CDS incomplete isoforms annotated in GENCODE and identify 175-337 isoform-ratio QTL (i-rQTL). By comprehensive long-read capture RNA-sequencing among these incomplete isoforms, we reveal 29 full-length isoforms with unannotated CDSs associated with GWAS traits. Furthermore, we show that disease-causal sQTL genes can be identified by evaluating their trans-eQTL effects. Our approaches highlight the understudied role of protein-altering sQTLs and are broadly applicable to other tissues and diseases.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32358-1

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DOI: 10.1038/s41467-022-32358-1

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