Predicting transcriptional responses to cold stress across plant species
Author(s) -
Xiaoxi Meng,
Zhikai Liang,
Xiuru Dai,
Yang Zhang,
Samira Mahboub,
Daniel W. Ngu,
Rebecca Roston,
James C. Schnable
Publication year - 2021
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2026330118
Subject(s) - biology , gene , plant species , cold stress , computational biology , genome , gene expression , genetics , evolutionary biology , ecology
Significance The same gene is often regulated differently in response to stress in even closely related plant species. Directly measuring stress-responsive gene expression can be financially and logistically challenging in nonmodel species. Here, we show that models trained using data on which genes respond to cold in one species can predict which genes will respond to cold in related species, even when the training and target species vary in their degree of tolerance to cold. The prediction models we used require only genomic sequence and gene models. As a result, data from well-studied model species may be used to predict which genes will respond to stress in less-studied species with sequenced genomes.
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