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Detalle de: The landscape of expression and alternative splicing variation across human traits

Title The landscape of expression and alternative splicing variation across human traits
Abstract

Understanding the consequences of individual transcriptome variation is fundamental to deciphering human biology and disease. We implement a statistical framework to quantify the contributions of 21 individual traits as drivers of gene expression and alternative splicing variation across 46 human tissues and 781 individuals from the Genotype-Tissue Expression project. We demonstrate that ancestry, sex, age, and BMI make additive and tissue-specific contributions to expression variability, whereas interactions are rare. Variation in splicing is dominated by ancestry and is under genetic control in most tissues, with ribosomal proteins showing a strong enrichment of tissue-shared splicing events. Our analyses reveal a systemic contribution of types 1 and 2 diabetes to tissue transcriptome variation with the strongest signal in the nerve, where histopathology image analysis identifies novel genes related to diabetic neuropathy. Our multi-tissue and multi-trait approach provides an extensive characterization of the main drivers of human transcriptome variation in health and disease.

Apa Reference García-Pérez, R., Ramirez, J.M., Ripoll-Cladellas, A., Chazarra-Gil, R., Oliveros, W., Soldatkina, O., Bosio, M., Rognon, P.J., Capella-Gutierrez, S., Calvo, M., Reverter, F., Guigó, R., Aguet, F., Ferreira, P.G., Ardlie, K.G. & Melé, M. (2023). The landscape of expression and alternative splicing variation across human traits. Cell Genomics, 3(1), 100244. 10.1016/j.xgen.2022.100244
Doi 10.1016/j.xgen.2022.100244
Publication Date Jan 2023
Publication Type Article
Researcher Salvador Capella
Ontology Transcriptomics, Expression Profiling, Statistical Methods for Biology, Image analysis
Research Groups
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