Dataset Information

Phylogenomic Insights into Mouse Evolution Using a Pseudoreference Approach.

ABSTRACT: Comparative genomic studies are now possible across a broad range of evolutionary timescales, but the generation and analysis of genomic data across many different species still present a number of challenges. The most sophisticated genotyping and down-stream analytical frameworks are still predominantly based on comparisons to high-quality reference genomes. However, established genomic resources are often limited within a given group of species, necessitating comparisons to divergent reference genomes that could restrict or bias comparisons across a phylogenetic sample. Here, we develop a scalable pseudoreference approach to iteratively incorporate sample-specific variation into a genome reference and reduce the effects of systematic mapping bias in downstream analyses. To characterize this framework, we used targeted capture to sequence whole exomes (?54 Mbp) in 12 lineages (ten species) of mice spanning the Mus radiation. We generated whole exome pseudoreferences for all species and show that this iterative reference-based approach improved basic genomic analyses that depend on mapping accuracy while preserving the associated annotations of the mouse reference genome. We then use these pseudoreferences to resolve evolutionary relationships among these lineages while accounting for phylogenetic discordance across the genome, contributing an important resource for comparative studies in the mouse system. We also describe patterns of genomic introgression among lineages and compare our results to previous studies. Our general approach can be applied to whole or partitioned genomic data and is easily portable to any system with sufficient genomic resources, providing a useful framework for phylogenomic studies in mice and other taxa.

SUBMITTER: Sarver BA

PROVIDER: S-EPMC5381554 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Phylogenomic Insights into Mouse Evolution Using a Pseudoreference Approach.

Sarver Brice A J BA Keeble Sara S Cosart Ted T Tucker Priscilla K PK Dean Matthew D MD Good Jeffrey M JM

Genome biology and evolution 20170301 3

Comparative genomic studies are now possible across a broad range of evolutionary timescales, but the generation and analysis of genomic data across many different species still present a number of challenges. The most sophisticated genotyping and down-stream analytical frameworks are still predominantly based on comparisons to high-quality reference genomes. However, established genomic resources are often limited within a given group of species, necessitating comparisons to divergent reference ...[more]

PMID: 28338821

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Project description:BACKGROUND: Recent phylogenomic analyses have revolutionized our view of eukaryote evolution by revealing unexpected relationships between and within the eukaryotic supergroups. However, for several groups of uncultivable protists, only the ribosomal RNA genes and a handful of proteins are available, often leading to unresolved evolutionary relationships. A striking example concerns the supergroup Rhizaria, which comprises several groups of uncultivable free-living protists such as radiolarians, foraminiferans and gromiids, as well as the parasitic plasmodiophorids and haplosporids. Thus far, the relationships within this supergroup have been inferred almost exclusively from rRNA, actin, and polyubiquitin genes, and remain poorly resolved. To address this, we have generated large Expressed Sequence Tag (EST) datasets for 5 species of Rhizaria belonging to 3 important groups: Acantharea (Astrolonche sp., Phyllostaurus sp.), Phytomyxea (Spongospora subterranea, Plasmodiophora brassicae) and Gromiida (Gromia sphaerica). RESULTS: 167 genes were selected for phylogenetic analyses based on the representation of at least one rhizarian species for each gene. Concatenation of these genes produced a supermatrix composed of 36,735 amino acid positions, including 10 rhizarians, 9 stramenopiles, and 9 alveolates. Phylogenomic analyses of this large dataset revealed a strongly supported clade grouping Foraminifera and Acantharea. The position of this clade within Rhizaria was sensitive to the method employed and the taxon sampling: Maximum Likelihood (ML) and Bayesian analyses using empirical model of evolution favoured an early divergence, whereas the CAT model and ML analyses with fast-evolving sites or the foraminiferan species Reticulomyxa filosa removed suggested a derived position, closely related to Gromia and Phytomyxea. In contrast to what has been previously reported, our analyses also uncovered the presence of the rhizarian-specific polyubiquitin insertion in Acantharea. Finally, this work reveals another possible rhizarian signature in the 60S ribosomal protein L10a. CONCLUSIONS: Our study provides new insights into the evolution of Rhizaria based on phylogenomic analyses of ESTs from three groups of previously under-sampled protists. It was enabled through the application of a recently developed method of transcriptome analysis, requiring very small amount of starting material. Our study illustrates the potential of this method to elucidate the early evolution of eukaryotes by providing large amount of data for uncultivable free-living and parasitic protists.

Dataset Information

Phylogenomic Insights into Mouse Evolution Using a Pseudoreference Approach.

Publications

Phylogenomic Insights into Mouse Evolution Using a Pseudoreference Approach.

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