Department of Biology, Indiana University, Bloomington, IN.
Department of Mathematics, Western University, London, ON, Canada.
Mol Biol Evol. 2023 May 2;40(5). doi: 10.1093/molbev/msad106.
Despite the increasing abundance of whole transcriptome data, few methods are available to analyze global gene expression across phylogenies. Here, we present a new software package (Computational Analysis of Gene Expression Evolution [CAGEE]) for inferring patterns of increases and decreases in gene expression across a phylogenetic tree, as well as the rate at which these changes occur. In contrast to previous methods that treat each gene independently, CAGEE can calculate genome-wide rates of gene expression, along with ancestral states for each gene. The statistical approach developed here makes it possible to infer lineage-specific shifts in rates of evolution across the genome, in addition to possible differences in rates among multiple tissues sampled from the same species. We demonstrate the accuracy and robustness of our method on simulated data and apply it to a data set of ovule gene expression collected from multiple self-compatible and self-incompatible species in the genus Solanum to test hypotheses about the evolutionary forces acting during mating system shifts. These comparisons allow us to highlight the power of CAGEE, demonstrating its utility for use in any empirical system and for the analysis of most morphological traits. Our software is available at https://github.com/hahnlab/CAGEE/.
尽管全转录组数据越来越丰富，但可用的方法很少能够分析跨进化枝系的全局基因表达。在这里，我们介绍了一种新的软件包（基因表达进化的计算分析 [CAGEE]），用于推断基因表达在系统发育树上增加和减少的模式，以及这些变化发生的速度。与以前的独立处理每个基因的方法不同，CAGEE 可以计算全基因组的基因表达率，以及每个基因的祖先状态。这里开发的统计方法使得推断跨基因组的进化速率的谱系特异性变化成为可能，除了在同一物种中从多个组织采样的速率之间可能存在差异之外。我们在模拟数据上验证了我们方法的准确性和稳健性，并将其应用于从茄属的多个自交亲和和自交不亲和物种中收集的胚珠基因表达数据集，以检验关于在交配系统转变过程中起作用的进化力量的假设。这些比较使我们能够突出 CAGEE 的优势，证明其在任何经验系统中的实用性以及对大多数形态特征的分析。我们的软件可在 https://github.com/hahnlab/CAGEE/ 获得。
