Understanding phylogenetic relationships in Cladobranchia (Mollusca, Heterobranchia, Nudibranchia) using RNA-seq dataтезисы доклада

Дата последнего поиска статьи во внешних источниках: 28 февраля 2020 г.

Работа с тезисами доклада

[1] Understanding phylogenetic relationships in cladobranchia (mollusca, heterobranchia, nudibranchia) using rna-seq data / D. Karmeinski, J. Goodheart, T. Korshunova et al. // 20th Annual Meeting of the Society for Biological Systematics (GfBS). — Society for Biological Systematics Munich, 2019. — P. 18–18. The species–rich taxon Cladobranchia, which is sister to Anthobranchia in the exclusively marine group of Nudibranchia (Gastropoda, Heterobranchia), currently comprises approximately 98 genera from 22 families. Despite attempts to shed light on the evolution of Cladobranchia, the phylogenetic position of most families within the group is still subject to debate. While past efforts of gaining a better understanding of their relationships using approaches with barcoding genes did not result in phylogenies with satisfactory resolution, the first phylogenies using transcriptomic multi–gene approaches only covered a limited number of species omitting many families whose positions are still uncertain. To take further steps towards overcoming this problem we sequenced the transcriptomes of 21 species of heterobranch sea slugs and combined our data with raw reads from 40 species of Heterobranchia available from public databases. In order to obtain a high number of genes suitable for phylogenetic analyses, we assembled the raw reads using six different transcriptome assembly tools. For each species we identified the best assembly using a variety of descriptive parameters. We then searched the assemblies for orthologous genes that are presumed to be single–copy in molluscs and combined them in a phylogenetic analysis using a supermatrix approach. Our preliminary results expand the knowledge about the evolution of Cladobranchia by increasing the number of taxa examined in a transcriptomic multi–gene approach.

Публикация в формате сохранить в файл сохранить в файл сохранить в файл сохранить в файл сохранить в файл сохранить в файл скрыть