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Tysall, E. E.

Publications and source records attributed to Tysall, E. E..

3 recordsLinked to original sources

Comparative genomic analyses of trans-ithmanian reef fishes reveals different molecular targets of environmental adaptation in different families.

The extent to which selection acts upon the same molecular targets when faced with the same environmental changes has important implications for our understanding of the repeatability and predictability of evolutionary processes. Replicated natural experiments are well positioned to provide insight, however often these involve closely related species or populations of the same species. Given that the similarity of genetic background makes the same molecular change more likely, it is essential to evaluate the extent to which molecular parallelism occurs in more distantly related species. The rise of the Isthmus of Panama presents an ideal natural experiment to investigate the prevalence of parallel molecular changes in distantly related lineages exposed to the same environmental regimes of temperature, salinity and primary productivity in the two newly formed oceans. Here, we generate high-quality reference genomes for two replicate pairs of geminate reef fishes, one in the family Pomacentridae and one in the Serranidae. Comparative analyses of positive selection in protein-coding genes and of gene family evolution revealed multiple signals of potentially adaptive divergence between geminate species in response to environmental regime. Common targets of selection between families included MAPK signalling (MAP3K10), solute transport (SLC46A2) and reproduction (ZPL3L), as well as expansions in immune and MAPK related gene families. Overall, however, we found minimal evidence of parallelism between families either at the gene level or when considering higher functional categories. Our findings suggest that phylogenetic constraints may limit the levels of molecular parallelism in distant lineages even when faced with comparable selective pressures. Significance StatementUnderstanding the extent to which species exposed to similar environmental conditions may adapt using similar genetic solutions has important implications for our understanding of evolutionary processes and how we may expect species to adapt in the future. However, systems where multiple, independent lineages are faced with the same shift in conditions are rare. The rise of the Isthmus of Panama provides a unique, natural experiment where multiple marine species have been divided and exposed to radically different environmental conditions. Here, we generate genomes for separated species in two distantly related families of reef fishes and compare genome-wide patterns of divergence. Our analyses identified signals of selection in protein-coding genes and shifts in gene family size consistent with adaptation to the distinct environments, however the specific genes and pathways involved predominantly differed between the families, revealing that, even under shared selective pressures, molecular mechanisms may differ across more distant lineages.

evolutionary biology↗

tidygenclust: Clustering for Population Genetics in R

BackgroundPopulation structure analysis is crucial for evolutionary research and medical genomics. Clustering methods, broadly categorized as model-based (e.g. ADMIXTURE) or non-model-based (e.g. SCOPE), differ in their methodology and computational efficiency. Recently, fastmixture, a model-based approach, has improved scalability and performance, while replicate alignment tools, such as Clumppling, extend previous methods by also aligning the modes across K values. However, all the existing tools are standalone and generate numerous untracked text files, as well as offering limited plot customisability. ResultsWe introduce an R package, tidygenclust, which brings the functionalities of the original ADMIXTURE, fastmixture and Clumppling software into R, enabling a streamlined and integrated workflow. By integrating with tidypopgen, a package designed to handle large SNP datasets, these new tools maintain metadata, simplify data handling, and produce results as customisable ggplot2 objects for flexible visualisation. ConclusionsThe R package tidygenclust advances population genetic analysis by combining computational efficiency with reproducible workflows and user-friendly plotting. The source code and instructions can be accessed on https://github.com/EvolEcolGroup/tidygenclust.

bioinformatics↗

tidypopgen: Tidy Population Genetics in R

As genome-wide data has become increasingly available, software libraries for their analysis have proliferated. While new tools for downstream analyses are constantly emerging, existing workflows are hindered by inefficiencies. Switching between coding languages and object types in the early stages of pipelines wastes researchers time, impedes reproducibility, and creates opportunity for error. To confront these obstacles, we introduce tidypopgen, a comprehensive R package for population genetic analysis of biallelic SNP data. Genotype data can be read, filtered, and analysed within a single environment, without the need for prior data cleaning or setup with other software. tidypopgens gen_tibble object structure makes analysis efficient and intuitive, while standardised tidy grammar makes data manipulation clear. Functionality within tidypopgen supports cleaning and merging datasets, basic descriptive statistics, multivariate analysis, clustering algorithms, and F-statistics, as well as integrating with existing tools for population genetic analyses in R. We use the Human Genome Diversity Project SNP dataset (Li et al., 2008) to show that a basic population genetic workflow can be executed in under 25 lines of code in a single environment using one file set, without the need to write superfluous outputs or change directories. By supporting data assembly through to data analysis, tidypopgen significantly streamlines workflows without compromising speed or functionality.

bioinformatics↗