SwePub - search: WFRF:(Minaeva Mariia)

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1.	Einson, Jonah, et al. (author) The impact of genetically controlled splicing on exon inclusion and protein structure 2024 In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 19:3 March Journal article (peer-reviewed)abstract 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.

Einson, Jonah, et al. (author)
The impact of genetically controlled splicing on exon inclusion and protein structure
2024
In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 19:3 March
Journal article (peer-reviewed)abstract
- 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.

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