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Using population-scale transcriptomic and genomic data to map 3′ UTR alternative polyadenylation quantitative trait loci

  • Xudong Zou
  • , Ruofan Ding
  • , Wenyan Chen
  • , Gao Wang
  • , Shumin Cheng
  • , Qin Wang
  • , Wei Li
  • , Lei Li
  • Shenzhen Bay Laboratory
  • Columbia University
  • University of California

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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).

Original languageEnglish
Article number101566
JournalSTAR Protocols
Volume3
Issue number3
DOIs
StatePublished - 16 Sep 2022
Externally publishedYes

Keywords

  • Bioinformatics
  • Genetics
  • Genomics
  • Sequence analysis

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