期刊
PLANT COMMUNICATIONS
卷 3, 期 4, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.xplc.2022.100323
关键词
gene expression; comparative transcriptomics; gene function; co-expression; differential expression; databases
资金
- Singapore Ministry of Education [MOE2018-T2-2-053]
- Singapore Food Agency [SFS_RND_SUFP_001_05]
This review describes how we can gain new knowledge from gene expression data and study plant evolution through comparative analysis. The gene expression data have great value, as they can be re-analyzed by others to answer questions beyond the scope of the original study.
There are now more than 300 000 RNA sequencing samples available, stemming from thousands of experiments capturing gene expression in organs, tissues, developmental stages, and experimental treatments for hundreds of plant species. The expression data have great value, as they can be re-analyzed by others to ask and answer questions that go beyond the aims of the study that generated the data. Because gene expression provides essential clues to where and when a gene is active, the data provide powerful tools for predicting gene function, and comparative analyses allow us to study plant evolution from a new perspective. This review describes how we can gain new knowledge from gene expression profiles, expression specificities, co-expression networks, differential gene expression, and experiment correlation. We also introduce and demonstrate databases that provide user-friendly access to these tools.
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