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09 01, 2023;6 (1): 899.

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

Jialin Mai, Mingming Lu, Qianwen Gao, Jingyao Zeng, Jingfa Xiao
Author Information
  1. Jialin Mai: National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
  2. Mingming Lu: National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
  3. Qianwen Gao: National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
  4. Jingyao Zeng: 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. ORCID
  5. Jingfa Xiao: 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. ORCID
PMID: 37658226 DOI: 10.1038/s42003-023-05279-y

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.

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MeSH Term

Genome-Wide Association Study
Transcriptome
Databases, Factual
Fruit
Phenotype
Journal Article Review Research Support, Non-U.S. Gov't

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