Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States of America.
New York Genome Center, New York, NY, United States of America.
PLoS One. 2024 Mar 13;19(3):e0291960. doi: 10.1371/journal.pone.0291960. eCollection 2024.
Common variants affecting mRNA splicing are typically identified though splicing quantitative trait locus (sQTL) mapping and have been shown to be enriched for GWAS signals by a similar degree to eQTLs. However, the specific splicing changes induced by these variants have been difficult to characterize, making it more complicated to analyze the effect size and direction of sQTLs, and to determine downstream splicing effects on protein structure. In this study, we catalogue sQTLs using exon percent spliced in (PSI) scores as a quantitative phenotype. PSI is an interpretable metric for identifying exon skipping events and has some advantages over other methods for quantifying splicing from short read RNA sequencing. In our set of sQTL variants, we find evidence of selective effects based on splicing effect size and effect direction, as well as exon symmetry. Additionally, we utilize AlphaFold2 to predict changes in protein structure associated with sQTLs overlapping GWAS traits, highlighting a potential new use-case for this technology for interpreting genetic effects on traits and disorders.
常见的影响 mRNA 剪接的变异通常是通过剪接数量性状基因座 (sQTL) 映射来识别的,并且已经通过类似的程度来显示与 eQTL 一样富集 GWAS 信号。然而,这些变体引起的具体剪接变化很难描述,这使得分析 sQTL 的效应大小和方向,以及确定对蛋白质结构的下游剪接效应更加复杂。在这项研究中,我们使用外显子百分比拼接 (PSI) 分数作为定量表型来编目 sQTL。PSI 是一种用于识别外显子跳跃事件的可解释指标,并且在从短读 RNA 测序定量剪接方面具有优于其他方法的优势。在我们的 sQTL 变体集中,我们发现了基于剪接效应大小和效应方向以及外显子对称性的选择效应的证据。此外,我们利用 AlphaFold2 预测与 GWAS 特征重叠的 sQTL 相关的蛋白质结构变化,突出了该技术在解释遗传对特征和疾病的影响方面的潜在新用途。