Department of Biology, Pennsylvania State University, University Park, State College, PA, 16802, USA.
Department of Biochemistry, Microbiology, and Molecular Biology, Pennsylvania State University, University Park, State College, PA, 16802, USA.
Genome Biol. 2022 Apr 19;23(1):101. doi: 10.1186/s13059-022-02656-4.
Genome-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."
We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genes, ZINC RIBBON 3 (ZR3) and COTTON 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 inbred Arabidopsis accessions. 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.
We 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 additional Arabidopsis genomes 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.
全基因组关联研究（GWAS）旨在将表型变化与基因型变异相关联。转录后，单核苷酸变体（SNVs）可能会改变 mRNA 结构，从而对转录本稳定性、大分子相互作用和翻译产生潜在影响。然而，尚未评估植物基因组中是否存在这些改变结构的多态性或“核糖开关”。
我们通过实验证明了两个拟南芥基因 ZINC RIBBON 3（ZR3）和 COTTON GOLGI-RELATED 3（CGR3）转录本中存在核糖开关，这两个基因与自然环境中的大陆性和温度变化有关。这些核糖开关也与它们各自转录本丰度的差异有关，这表明它们在调节基因表达以适应当地气候条件方面发挥作用。然后，我们在 879 个自然近交系拟南芥品系的 mRNA 中转录组范围内计算预测了核糖开关。我们描述了这些品系中 SNP/核糖开关之间的相关性与它们当地环境的 434 个气候描述符之间的关系，这表明这些变体在局部适应中发挥作用。我们将这些信息整合到 CLIMtools V2.0 中，并提供了一个新的网络资源 T-CLIM，该资源揭示了转录本丰度变化与当地环境变化之间的关联。
我们对两个植物核糖开关进行了功能验证，并首次证明了核糖开关依赖温度的条件性，将其命名为“条件性核糖开关”。我们提供了植物中核糖开关的全基因组预测。我们用核糖开关信息和 1868 个额外的拟南芥基因组和 269 个额外的气候条件扩展了我们之前的 CLIMtools 网络资源，这将极大地促进自然遗传变异、其表型后果及其在局部适应中的作用的计算研究。
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