Evolving best practices for transcriptome-wide association studies accelerate discovery of gene-phenotype links.

IF 8.3 2区 生物学 Q1 PLANT SCIENCES Current opinion in plant biology Pub Date : 2024-12-02 DOI:10.1016/j.pbi.2024.102670
J Vladimir Torres-Rodríguez, Delin Li, James C Schnable
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引用次数: 0

Abstract

Transcriptome-wide association studies (TWAS) complement genome-wide association studies (GWAS) by using gene expression data to link specific genes to phenotypes. This review examines 37 TWAS studies across eight plant species, evaluating the impact of methodological choices on outcomes using maize and soybean datasets. Large sample sizes and synchronized sample collection for gene expression measurement appear to significantly increase power for discovering gene-phenotype linkages, while matching tissue, stage, and environment may matter much less than previously believed, making it feasible to reuse large and well-collected expression datasets across multiple studies. The development of statistical approaches and computational tools specifically optimized for plant TWAS data will ultimately be needed, but further potential remains to adapt advances developed in GWAS to TWAS contexts.

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来源期刊
Current opinion in plant biology
Current opinion in plant biology 生物-植物科学
CiteScore
16.30
自引率
3.20%
发文量
131
审稿时长
6-12 weeks
期刊介绍: Current Opinion in Plant Biology builds on Elsevier's reputation for excellence in scientific publishing and long-standing commitment to communicating high quality reproducible research. It is part of the Current Opinion and Research (CO+RE) suite of journals. All CO+RE journals leverage the Current Opinion legacy - of editorial excellence, high-impact, and global reach - to ensure they are a widely read resource that is integral to scientists' workflow.
期刊最新文献
Editorial overview: Spatial and temporal regulation of molecular and cell biological process across biological scales. Editorial overview: Physiology and metabolism 2024. Evolving best practices for transcriptome-wide association studies accelerate discovery of gene-phenotype links. Editorial Board Contents
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