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bioRxiv · 10.1101/2021.11.02.466997

Novel insights into the cold resistance of Hevea brasiliensis through coexpression networks

Abstract

BackgroundHevea brasiliensis is the main global source of natural rubber. Due to fungal disease pressure in hot, humid regions, rubber plantations have been moved to drier "escape areas" with lower temperatures. In order to analyze gene expression regulation during cold exposure, we studied young GT1 and RRIM 600 rubber tree clones with different cold tolerance strategies. ResultsAlongside traditional differential expression approaches, an RNA-seq gene coexpression network (GCN) was developed with 27,220 genes grouped into 205 gene clusters. The GCN related most rubber tree cold stress molecular responses to 31 clusters across three GCN modules: a downregulated group with 16 clusters and two upregulated groups with twelve and three clusters. The hub genes of the cold-responsive modules were also identified and analyzed. We observed that the general response to short-term cold exposure involves complex regulation of the jasmonic acid (JA) stress response and programmed cell death (PCD), upregulation of ethylene-responsive genes, and relaxation of florigen gene inhibition. As a result, we identified single DEGs and gained insights into the mechanisms involved in the response to cold stress in young rubber trees. ConclusionsOur findings may represent the species genetic stress responses developed during the course of evolution, since the examined varieties were genotypes selected during the early years of rubber tree domestication. Understanding the cold response mechanisms in H. brasiliensis could improve breeding strategies for this crop, which has a narrow genetic base, is being impacted by climate change and is the only source for large-scale rubber production.

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BibTeXRIS

Silva, C. C., Bajay, S. K., Aono, A. H., Francisco, F. R., Junior, R. B., de Souza, A. P., Mantello, C. C., Vicentini dos Santos, R.. 2021-11-04. Novel insights into the cold resistance of Hevea brasiliensis through coexpression networks. https://doi.org/10.1101/2021.11.02.466997

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