Using population-scale transcriptomic and genomic data to map 3' UTR alternative polyadenylation quantitative trait loci
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Published on: March 3, 2015
Xudong Zou1, Ruofan Ding1, Wenyan Chen1
1Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.
Abstract:
3' UTR alternative polyadenylation (APA) quantitative trait loci (3'aQTL) can explain approximately 16.1% of trait-associated non-coding variants and is largely distinct from other molecular QTLs. Here, we describe a bioinformatic protocol for identifying 3'aQTLs through standard RNA-seq and matched genomic data. This protocol allows users to analyze dynamic APA events, identify common genetic variants associated with differential 3' UTR usage, and predict the potential causal variants that affect APA. For complete details on the use and execution of this protocol, please refer to Li et al. (2021).

