FarmGTEx TWAS-server: An Interactive Web Server for Customized TWAS Analysis
Transcriptome-wide association study (TWAS) is a powerful approach for investigating the molecular mechanisms linking genetic loci to complex phenotypes. However, the complexity of the TWAS analytical pipeline, including the construction of gene expression reference panels, gene expression prediction, and association analysis using data from genome-wide association studies (GWASs), poses challenges for genetic studies in many species. In this study, we provide the Farm Animal Genotype-Tissue Expression (FarmGTEx) TWAS-server, an interactive and user-friendly multispecies platform designed to streamline the translation of genetic findings across tissues and species. The server incorporates gene expression data from 49 human tissues (838 individuals), 34 pig tissues (5457 individuals), and 23 cattle tissues (4889 individuals), providing prediction models for 38,180 human genes, 21,037 pig genes, and 17,942 cattle genes. It supports genotype-based gene expression prediction, GWAS summary statistics imputation, customizable TWAS analysis, functional annotation, and result visualization. Additionally, we provide 479,203, 1208, and 657 tissue-gene-trait associations for 1129 human traits, 41 cattle traits, and 11 pig traits, respectively. Utilizing the TWAS-server, we validated the association of the ABCD4 gene with pig teat number. Furthermore, we identified that pig backfat thickness may share genetic similarities with human diastolic blood pressure, sarcoidosis (Löfgren syndrome), and body mass index. The FarmGTEx TWAS-server offers a comprehensive and accessible platform for researchers to perform TWAS analyses across tissues and species. It is freely available at https://twas.farmgtex.org, with regular updates planned as the FarmGTEx project expands to include more species.
Authors
- Qing Lin (ORCID: https://orcid.org/0000-0002-8416-9748)
- Lingzhao Fang (ORCID: https://orcid.org/0000-0003-1103-3679)
- Zhonghao Bai (ORCID: https://orcid.org/0009-0005-8697-1813)
- Shuli Liu (ORCID: https://orcid.org/0000-0002-5170-5313)
- Jinyan Teng (ORCID: https://orcid.org/0000-0002-3046-1452)
- Zhenyang Zhang
- Bingjie Li (ORCID: https://orcid.org/0000-0002-8528-1889)
- Yahui Gao (ORCID: https://orcid.org/0000-0003-0602-4823)
- Zhe Zhang (ORCID: https://orcid.org/0000-0001-5320-3125)
- Zitao Chen (ORCID: https://orcid.org/0000-0001-6213-0810)
- Jun Wu (ORCID: https://orcid.org/0000-0001-5537-6804)
Institutions
- South China Agricultural University (CN)
- University of Maryland, Baltimore (US)
- Agricultural Research Service (US)
- Zhejiang Sci-Tech University (CN)
- Roslin Institute (GB)
- Aarhus University (DK)
- Scotland's Rural College (GB)
- Westlake University (CN)
- Ministry of Agriculture (EE)
- Beltsville Agricultural Research Center (US)
- Quality Research (US)
- Ministry of Agriculture and Rural Affairs (CN)
- University of Maryland, College Park (US)
- Zhejiang University (CN)
Publication Details
- Journal
- Genomics Proteomics & Bioinformatics
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1093/gpbjnl/qzaf006
- Citations
- 9
- Primary Topic
- Molecular Biology Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 7.25
Funders
- National Natural Science Foundation of China
- Zhejiang University
- Directorate for Biological Sciences
- Biotechnology and Biological Sciences Research Council