Transcriptome-wide association studies: recent advances in methods, applications and available databases

Jialin Mai; Mingming Lu; Qianwen Gao; Jingyao Zeng; Jingfa Xiao

doi:10.1038/s42003-023-05279-y

Transcriptome-wide association studies: recent advances in methods, applications and available databases

Commun Biol. 2023 Sep 1;6(1):899. doi: 10.1038/s42003-023-05279-y.

Authors

Jialin Mai^#^{1

2

3}, Mingming Lu^#^{1

2

3}, Qianwen Gao^{1

2

3}, Jingyao Zeng^{4

5}, Jingfa Xiao^{6

7

8}

Affiliations

¹ National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
² CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
³ University of Chinese Academy of Sciences, Beijing, 100049, China.
⁴ National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China. zengjy@big.ac.cn.
⁵ CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China. zengjy@big.ac.cn.
⁶ National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China. xiaojingfa@big.ac.cn.
⁷ CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China. xiaojingfa@big.ac.cn.
⁸ University of Chinese Academy of Sciences, Beijing, 100049, China. xiaojingfa@big.ac.cn.

^# Contributed equally.

Abstract

Genome-wide association study has identified fruitful variants impacting heritable traits. Nevertheless, identifying critical genes underlying those significant variants has been a great task. Transcriptome-wide association study (TWAS) is an instrumental post-analysis to detect significant gene-trait associations focusing on modeling transcription-level regulations, which has made numerous progresses in recent years. Leveraging from expression quantitative loci (eQTL) regulation information, TWAS has advantages in detecting functioning genes regulated by disease-associated variants, thus providing insight into mechanisms of diseases and other phenotypes. Considering its vast potential, this review article comprehensively summarizes TWAS, including the methodology, applications and available resources.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Databases, Factual
Fruit
Genome-Wide Association Study*
Phenotype
Transcriptome*