Data from: The population genomics of sunflowers and genomic determinants of protein evolution revealed by RNAseq

Few studies have investigated the causes of evolutionary rate variation among plant nuclear genes, especially in recently diverged species still capable of hybridizing in the wild. The recent advent of Next Generation Sequencing (NGS) permits investigation of genome wide rates of protein evolution and the role of selection in generating and maintaining divergence. Here, we use individual whole-transcriptome sequencing (RNAseq) to refine our understanding of the population genomics of a wild species of sunflowers (Helianthus spp.) and the factors that affect rates of protein evolution. We aligned 35 GB of transcriptome sequencing data and identified 433,257 polymorphic sites (SNPs) in a reference transcriptome comprising 16,312 genes. Using SNP markers, we identified strong population clustering largely corresponding to the three species analyzed here (Helianthus annuus, H. petiolaris, H. debilis), with one distinct early generation hybrid. Then, we calculated the proportions of adaptive substitution fixed by selection (alpha) and identified gene ontology categories with elevated values of alpha. The “response to biotic stimulus” category had the highest mean alpha across the three interspecific comparisons, implying that natural selection imposed by other organisms plays an important role in driving protein evolution in wild sunflowers. Finally, we examined the relationship between protein evolution (dN/dS ratio) and several genomic factors predicted to co-vary with protein evolution (gene expression level, divergence and specificity, genetic divergence [FST], and nucleotide diversity [pi]). We find that variation in rates of protein divergence was correlated with gene expression level and specificity, consistent with results from a broad range of taxa and timescales. This would in turn imply that these factors govern protein evolution both at a microevolutionary and macroevolutionary timescale. Our results contribute to a general understanding of the determinants of rates of protein evolution and the impact of selection on patterns of polymorphism and divergence.目前针对植物核基因进化速率差异成因的研究尚少，针对仍可在野外发生杂交的近缘分化物种的相关研究尤为匮乏。下一代测序（Next Generation Sequencing, NGS）技术的新近问世，使得研究者得以开展全基因组范围的蛋白质进化速率研究，并解析自然选择在产生并维持物种分化中的作用。本研究通过单样本全转录组测序（RNAseq），深化对野生向日葵属（Helianthus spp.）物种的群体基因组学认知，并解析影响蛋白质进化速率的各类因素。我们共比对得到35GB的转录组测序数据，并在包含16312个基因的参考转录组中鉴定出433257个单核苷酸多态性（Single Nucleotide Polymorphism, SNPs）位点。基于SNP分子标记，我们鉴定出清晰的群体聚类结果，其与本次研究涉及的三个物种（Helianthus annuus、H. petiolaris、H. debilis）基本对应，仅包含一个明确的早期世代杂交个体。随后，我们计算了由选择固定的适应性替换比例（α），并鉴定出α值显著升高的基因本体（Gene Ontology, GO）功能类别。在三次种间比较中，“生物胁迫响应”功能类别的平均α值最高，这表明其他生物施加的自然选择在驱动野生向日葵的蛋白质进化过程中发挥了重要作用。最后，我们探究了蛋白质进化（dN/dS比值）与若干被预测与蛋白质进化存在共变关系的基因组特征之间的关联，这些特征包括基因表达水平、分化程度与表达特异性、遗传分化系数（Fixation Index, FST）以及核苷酸多样性（π）。我们发现蛋白质分化速率的差异与基因表达水平及表达特异性显著相关，这一结果与多个类群及不同时间尺度下的相关研究结论一致。这进一步表明，上述因素在微观进化与宏观进化的时间尺度上共同调控蛋白质进化过程。本研究结果有助于我们更全面地理解蛋白质进化速率的决定因素，以及自然选择对多态性与分化模式的影响。