bioRxivMolecular BiologyPreprint
Overexpression of barley heat stress transcription factor HvHsfA6a provide thermotolerance by thermopriming
Reeku Chaudhary, Suchi BaliyaniD, Parul SirohiiD, Sweta SinghiD, Sumit Kumar MishraiD, Mohan Singh RajkumariD, Shashank Sagar SainiiD, Hugo GermainiD, Debabrata SircariD, Harsh ChauhaniD
Abstract
Adverse impacts of climate change, including high temperature on cereal crop production, have been evidenced globally. In plants, heat shock factors (HSFs) are crucial components of heat stress associated rescue mechanisms and are also required for normal biological processes. Here, we functionally characterized a highly heat stress responsive HvHSFA6a in barley by developing constitutively overexpressing transgenic lines. These transgenic lines showed heat tolerant phenotype via improved photosynthesis, antioxidants and upregulation of HSPs and metabolites involved in stress amelioration and keeping thermomemory as compared to wild type plants. Global transcriptomics and ChIP sequencing revealed that HvHSFA6a orchestrates the expression of several genes through direct binding with other HSFs containing consensus HSE in their promoter regions. A GC-MS based metabolomics analysis also revealed the alterations in key metabolic processes such as carbohydrate metabolism, citric acid cycle, amino acids and secondary metabolism. Higher accumulation of key metabolites such as sucrose, galactinol, shikimate and ascorbate has been observed under both control and heat stress in transgenic lines as compared to wild type plants. Taken together, the results suggest that overexpression of HvHsfA6a prime the plants for heat stress conditions by alteration in gene expression and metabolic status. HighlightPriming is a mechanism by which plants respond to various abiotic and biotic stresses. Through multi omics approach we found that barley HsfA6a provide thermotolernce in transgenic plants through priming effect on transcriptome and metabolome.
- assay: proteomics
- assay: metabolomics
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 6
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