Novel model-based clustering reveals ecologically differentiated bacterial genomes across a large climate gradient
Year: 2021
Type: dataset
Abstract: Here, you will find the main datasets used for analyses in: "Novel model-based clustering reveals ecologically differentiated bacterial genomes across a large climate gradient" If you use any of this resource material, please cite: Simonsen, A. K., Barrett, L. G., Thrall, P. H., & Prober, S. M. (2019). Novel model-based clustering reveals ecologically differentiated bacterial genomes across a large climate gradient. Ecology Letters. doi: 10.1111/ele.13389 https://onlinelibrary.wiley.com/doi/abs/10.1111/ele.13389 For further inquiries, please contact me [email protected] Abstract: A pervasive challenge in microbial ecology is understanding the genetic level where ecological units can be differentiated. Ecological differentiation often occurs at fine genomic levels, yet it is unclear how to utilize ecological information to define ecotypes given the breadth of environmental variation among microbial taxa. Here, we present an analytical framework that infers clusters along genome-based microbial phylogenies according to shared environmental responses. The advantage of our approach is the ability to identify genomic clusters that best fit complex environmental information, whilst characterising cluster niches through model predictions. We apply our method to determine climate-associated ecotypes in populations of nitrogen-fixing symbionts using whole genomes, explicitly sampled to detect climate differentiation across a heterogeneous landscape. Although soil and plant-host characteristics strongly influence distribution patterns of inferred ecotypes, our flexible statistical method enabled us to identify climate-associated genomic clusters using environmental data, providing solid support for ecological specialization in soil symbionts.
Source: Figshare
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4394295340