Dornburg A, Townsend JP, Wang Z. Maximizing Power in Phylogenetics and Phylogenomics: A Perspective Illuminated by Fungal Big Data.
ADVANCES IN GENETICS 2017;
100:1-47. [PMID:
29153398 DOI:
10.1016/bs.adgen.2017.09.007]
[Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Since its original inception over 150 years ago by Darwin, we have made tremendous progress toward the reconstruction of the Tree of Life. In particular, the transition from analyzing datasets comprised of small numbers of loci to those comprised of hundreds of loci, if not entire genomes, has aided in resolving some of the most vexing of evolutionary problems while giving us a new perspective on biodiversity. Correspondingly, phylogenetic trees have taken a central role in fields that span ecology, conservation, and medicine. However, the rise of big data has also presented phylogenomicists with a new set of challenges to experimental design, quantitative analyses, and computation. The sequencing of a number of very first genomes presented significant challenges to phylogenetic inference, leading fungal phylogenomicists to begin addressing pitfalls and postulating solutions to the issues that arise from genome-scale analyses relevant to any lineage across the Tree of Life. Here we highlight insights from fungal phylogenomics for topics including systematics and species delimitation, ecological and phenotypic diversification, and biogeography while providing an overview of progress made on the reconstruction of the fungal Tree of Life. Finally, we provide a review of considerations to phylogenomic experimental design for robust tree inference. We hope that this special issue of Advances in Genetics not only excites the continued progress of fungal evolutionary biology but also motivates the interdisciplinary development of new theory and methods designed to maximize the power of genomic scale data in phylogenetic analyses.
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