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Evolutionary Bioinformatics

Phylotranscriptomic Analysis Based on Coalescence was Less Influenced by the Evolving Rates and the Number of Genes: A Case Study in Ericales

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Evolutionary Bioinformatics 2015:Suppl. 1 81-91

Original Research

Published on 18 Jan 2016

DOI: 10.4137/EBO.S22448


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Abstract

Advances in high-throughput sequencing have generated a vast amount of transcriptomic data that are being increasingly used in phylogenetic reconstruction. However, processing the vast datasets for a huge number of genes and even identifying optimal analytical methodology are challenging. Through de novo sequenced and retrieved data from public databases, we identified 221 orthologous protein-coding genes to reconstruct the phylogeny of Ericales, an order characterized by rapid ancient radiation. Seven species representing different families in Ericales were used as in-groups. Both concatenation and coalescence methods yielded the same well-supported topology as previous studies, with only two nodes conflicting with previously reported relationships. The results revealed that a partitioning strategy could improve the traditional concatenation methodology. Rapidly evolving genes negatively affected the concatenation analysis, while slowly evolving genes slightly affected the coalescence analysis. The coalescence methods usually accommodated rate heterogeneity better and required fewer genes to yield well-supported topologies than the concatenation methods with both real and simulated data.



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