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DOI | 10.1073/pnas.2026330118 |
Predicting transcriptional responses to cold stress across plant species | |
Meng X.; Liang Z.; Dai X.; Zhang Y.; Mahboub S.; Ngu D.W.; Roston R.L.; Schnable J.C. | |
发表日期 | 2021 |
ISSN | 00278424 |
卷号 | 118期号:10 |
英文摘要 | Although genome-sequence assemblies are available for a growing number of plant species, gene-expression responses to stimuli have been cataloged for only a subset of these species. Many genes show altered transcription patterns in response to abiotic stresses. However, orthologous genes in related species often exhibit different responses to a given stress. Accordingly, data on the regulation of gene expression in one species are not reliable predictors of orthologous gene responses in a related species. Here, we trained a supervised classification model to identify genes that transcriptionally respond to cold stress. A model trained with only features calculated directly from genome assemblies exhibited only modest decreases in performance relative to models trained by using genomic, chromatin, and evolution/diversity features. Models trained with data from one species successfully predicted which genes would respond to cold stress in other related species. Cross-species predictions remained accurate when training was performed in cold-sensitive species and predictions were performed in cold-tolerant species and vice versa. Models trained with data on gene expression in multiple species provided at least equivalent performance to models trained and tested in a single species and outperformed single-species models in cross-species prediction. These results suggest that classifiers trained on stress data from well-studied species may suffice for predicting gene-expression patterns in related, less-studied species with sequenced genomes. © 2021 National Academy of Sciences. All rights reserved. |
英文关键词 | Cold stress; Comparative genomics; Machine learning; Transcriptional regulation |
语种 | 英语 |
scopus关键词 | article; chromatin; classifier; cold stress; comparative genomics; genetic transcription; human; prediction |
来源期刊 | Proceedings of the National Academy of Sciences of the United States of America |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/180326 |
作者单位 | Center for Plant Science Innovation, University of Nebraska–Lincoln, Lincoln, NE 68588, United States; Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68588, United States; State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai’an, 273100, China; Department of Biochemistry, University of Nebraska–Lincoln, Lincoln, NE 68588, United States |
推荐引用方式 GB/T 7714 | Meng X.,Liang Z.,Dai X.,et al. Predicting transcriptional responses to cold stress across plant species[J],2021,118(10). |
APA | Meng X..,Liang Z..,Dai X..,Zhang Y..,Mahboub S..,...&Schnable J.C..(2021).Predicting transcriptional responses to cold stress across plant species.Proceedings of the National Academy of Sciences of the United States of America,118(10). |
MLA | Meng X.,et al."Predicting transcriptional responses to cold stress across plant species".Proceedings of the National Academy of Sciences of the United States of America 118.10(2021). |
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