Periodic Reporting for period 1 - PLEVOCON (Pleiotropy and Evolutionary Constraint)
Periodo di rendicontazione: 2018-06-01 al 2020-05-31
Pleiotropy, or the influence of a single locus on multiple traits, is thought to be an important mechanism of evolutionary constraint and could be an important deterministic factor during adaptive evolution. Theoretical models and work in quantitative genetics has long suggest that pleiotropy strongly impacts the probability that a given locus will be used in adaptation. Despite these theoretical predictions, we have lacked explicit tests of how pleiotropy contributes to evolutionary predictability. The overarching goal of this project was to test whether pleiotropy is a source of evolutionary constraint that underlies the predictability of evolutionary responses. Specifically, we sought to identify the genomic loci associated with repeated divergence between stickleback adapted to different habitats and test whether pleiotropy levels explained the repeated use of the same loci during adaptation. Illumina sequence data from multiple independent ecotype pairs of threespine stickleback were analyzed to estimate the genome-wide patterns of genetic divergence. We found that a large portion of the genome was evolving in a repeatable manner among independently derived population pairs of stickleback. Furthermore, ecologically relevant traits mapped to these repeatedly diverged genomic regions, and ecological similarity was an important predictor of the magnitude of parallel evolution. Using two proxies for pleiotropy, gene connectivity and number of traits with mapped QTL, we estimated the relationship between the level of pleiotropy and probability of parallel evolution. We found that parallel genomic regions contained genes with significantly more pleiotropy than uniquely evolving (non-parallel) regions. The increased mean pleiotropy of parallel windows could not be explained by other genomic factors, as there was no significant difference in mean gene count, mutation or recombination rates between parallel and non-parallel windows. Interestingly, although non-parallel windows contained genes that were on average less connected and influencing fewer mapped traits than parallel windows, these windows also tended to contain the gene that were the most pleiotropic. Taken together, our findings are consistent with the idea that low or intermediate levels of pleiotropy may be beneficial for adaptation, and that it is only at high levels that pleiotropy becomes constraining. These findings may help to inform our expectations about the genetic architecture of rapid evolutionary responses in nature or in agricultural and medical settings.
We used a referenced based bioinformatics pipeline to analyze next-generation sequence data and characterize the magnitude of parallel genomic divergence in stream-lake, benthic-limnetic and marine-freshwater threespine stickleback. We were able to identify the genomic regions evolving in concert among independently derived pairs. Genome-wide association mapping and correlation analyses were run to associate the genomic regions found to exhibit a signature of parallel evolution with key morphological traits and ecological factors. We were able to determine which ecological forces were factors were important in shaping genome-wide patterns of parallel evolution. Using pleiotropic metrics, estimated as part of the project, we were able to test whether the level of pleiotropy differs between parallel and non-parallel genomic regions. Counter to our a priori prediction based on theory, we found that parallel genomic regions contained genes with significantly more pleiotropy. Our findings are consistent with the idea that low or intermediate levels of pleiotropy may be beneficial for adaptation, and that it is only at high levels that pleiotropy becomes constraining. The results are reported in two publications (Rennison et al. 2019 Phil. Trans. Roy. Soc.B 374: 20180241 and Rennison et al., 2019 American Naturalist In Press) and a third publication is in Review at Proceedings of the National Academy of Sciences. The findings were further communicated at scientific conferences, through social media and on the project website.
Our study added valuable insight into the relationship between pleiotropy and the probability of adaptive evolution. This finding may help to inform our expectations about the genetic architecture of rapid evolutionary responses. This will be of value to stakeholders involved in conservation efforts and agricultural breeding and also in clinical settings where the evolution of antibiotic resistance is being considered.