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Exploring Phylogenetic Relationships and Divergence Times of Bioluminescent Species Using Genomic and Transcriptomic Data.
Amaral, Danilo T; Romeiro-Brito, Monique; Bonatelli, Isabel A S.
Affiliation
  • Amaral DT; Departamento de Biologia, Centro de Ciências Humanas e Biológicas, Universidade Federal de São Carlos (UFSCar), Sorocaba, Brazil. danilo.trabuco@gmail.com.
  • Romeiro-Brito M; Programa de Pós Graduação em Biologia Comparada, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo (USP), Ribeirão Preto, Brazil. danilo.trabuco@gmail.com.
  • Bonatelli IAS; Departamento de Biologia, Centro de Ciências Humanas e Biológicas, Universidade Federal de São Carlos (UFSCar), Sorocaba, Brazil.
Methods Mol Biol ; 2525: 409-423, 2022.
Article in En | MEDLINE | ID: mdl-35836087
Next-generation sequencing (NGS) has dominated the scene of genomics and evolutionary biology as a great amount of genomic data have been accumulated for a diverse set of species. At the same time, phylogenetic approaches and programs are in development to allow better use of such large-size datasets. Phylogenomics appears as a promising field to accommodate and explore all the information of NGS data in phylogenetic methods, being an important approach to investigate the evolution of bioluminescence in different organisms. To guarantee accurate results in phylogenomic studies, it is mandatory to correctly identify orthologous genes in phylogenetic reconstruction. Here, we show a simplified step-by-step framework to perform phylogenetic analysis along with divergence time estimation, beginning with an orthologous search. As empirical data, we exemplify transcriptome sequences of six species of the Elateroidea superfamily (Coleoptera). We introduce several bioinformatics tools for handling genomic data, especially those available in the software OrthoFinder, IQTREE, BEAST2, and TreePL.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Coleoptera / Transcriptome Limits: Animals Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Document type: Article Affiliation country: Brazil Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Coleoptera / Transcriptome Limits: Animals Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Document type: Article Affiliation country: Brazil Country of publication: United States