Background: Gene regulatory variation has been proposed to play an important role in the adaptation of plants to environmental stress. In the central highlands of Mexico, farmer selection has generated a unique group of maize landraces adapted to the challenges of the highland niche. In this study, gene expression in Mexican highland maize and a reference maize breeding line were compared to identify evidence of regulatory variation in stress-related genes. It was hypothesised that local adaptation in Mexican highland maize would be associated with a transcriptional signature observable even under benign conditions.
Methods: Allele specific expression analysis was performed using the seedling-leaf transcriptome of an F individual generated from the cross between the highland adapted Mexican landrace Palomero Toluqueño and the reference line B73, grown under benign conditions. Results were compared with a published dataset describing the transcriptional response of B73 seedlings to cold, heat, salt and UV treatments.
Results: A total of 2,386 genes were identified to show allele specific expression. Of these, 277 showed an expression difference between Palomero Toluqueño and B73 alleles under benign conditions that anticipated the response of B73 cold, heat, salt and/or UV treatments, and, as such, were considered to display a prior stress response. Prior stress response candidates included genes associated with plant hormone signaling and a number of transcription factors. Construction of a gene co-expression network revealed further signaling and stress-related genes to be among the potential targets of the transcription factors candidates.
Discussion: Prior activation of responses may represent the best strategy when stresses are severe but predictable. Expression differences observed here between Palomero Toluqueño and B73 alleles indicate the presence of -acting regulatory variation linked to stress-related genes in Palomero Toluqueño. Considered alongside gene annotation and population data, allele specific expression analysis of plants grown under benign conditions provides an attractive strategy to identify functional variation potentially linked to local adaptation.
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http://dx.doi.org/10.7717/peerj.3737 | DOI Listing |
Nature
January 2025
Program of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA.
Transcriptional regulation, which involves a complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate to unseen cell types and conditions. Here we introduce GET (general expression transformer), an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types.
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Department of Systems Biology, Columbia University, New York, NY, USA.
Transcriptional regulation, involving the complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate in unseen cell types and conditions. Here, we introduce GET, an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types.
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