Evolutionary rates provide genomic insights into convergent and lineage-specific evolution in carnivorous plants
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Abstract
Carnivorous plants (CPs) are striking examples of convergent evolution across ecological, morphological, and molecular scales, making them ideal systems for investigating genomic adaptation to extreme environments. While genomic studies have shown that gene family expansion and functional recruitment underlie key carnivorous traits, the effects of these transitions on rates of sequence evolution remain incompletely understood. Here, we present a comparative framework to examine evolutionary rate shifts across 30 carnivorous and non-carnivorous eudicots in over 12,000 gene families. Analyzing branch-lengths and evolutionary rate covariation (ERC), we detect both lineage-specific and convergent acceleration in CPs for genes associated with stress response, stimulus signaling, and light perception. Accelerated genes often belong to expanded families and show relaxation of purifying selection pressure. Despite the limited number of specific genes or gene families showing convergent acceleration across CP lineages, we find strong convergence at the functional level. Distinct sets of accelerated genes in each CP lineage are enriched for similar functional pathways, particularly light and hormone responses. ERC network analysis identifies a stress- and stimulus-responsive gene community with lineage-specific acceleration in Sarraceniaceae species and moderate acceleration in other CP lineages. Hub genes in this network are also co-expressed in a distantly related non-CP model system, suggesting repeated co-option of an ancestral regulatory module for carnivorous functions. Together, our results show that convergent genomic rate accelerations in CPs primarily involve functionally equivalent or similar but lineage-distinct genes, shaped by gene duplication, relaxed selection, and co-option of stress-response networks.
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Convergent acceleration of genes involved in stimulus and stress responses
Have you considered using a formal test of evolutionary convergence in evolutionary rates, such as those implemented by RERconverge (https://github.com/nclark-lab/RERconverge; https://doi.org/10.1093/bioinformatics/btz468)? It seems like the tests implemented in this (or related) software would provide robust evidence for this line of questioning.
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