Experimental demonstration and pan-structurome prediction of climate-associated riboSNitches in Arabidopsis

Author:

Ferrero-Serrano Ángel,Sylvia Megan M.,Forstmeier Peter C.,Olson Andrew J.,Ware Doreen,Bevilacqua Philip C.,Assmann Sarah M.ORCID

Abstract

AbstractBackgroundGenome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or “riboSNitches.”ResultsWe experimentally demonstrate the presence of riboSNitches in transcripts of twoArabidopsisgenes,ZINC RIBBON 3(ZR3) andCOTTON GOLGI-RELATED 3(CGR3), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbredArabidopsisaccessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation.ConclusionWe functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term “conditional riboSNitch.” We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additionalArabidopsisgenomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation.

Publisher

Springer Science and Business Media LLC

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