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      Power, resolution and bias: recent advances in insect phylogeny driven by the genomic revolution

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      Current Opinion in Insect Science
      Elsevier BV

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          Abstract

          Our understanding on the phylogenetic relationships of insects has been revolutionised in the last decade by the proliferation of next generation sequencing technologies (NGS). NGS has allowed insect systematists to assemble very large molecular datasets that include both model and non-model organisms. Such datasets often include a large proportion of the total number of protein coding sequences available for phylogenetic comparison. We review some early entomological phylogenomic studies that employ a range of different data sampling protocols and analyses strategies, illustrating a fundamental renaissance in our understanding of insect evolution all driven by the genomic revolution. The analysis of phylogenomic datasets is challenging because of their size and complexity, and it is obvious that the increasing size alone does not ensure that phylogenetic signal overcomes systematic biases in the data. Biases can be due to various factors such as the method of data generation and assembly, or intrinsic biological feature of the data per se, such as similarities due to saturation or compositional heterogeneity. Such biases often cause violations in the underlying assumptions of phylogenetic models. We review some of the bioinformatics tools available and being developed to detect and minimise systematic biases in phylogenomic datasets. Phylogenomic-scale data coupled with sophisticated analyses will revolutionise our understanding of insect functional genomics. This will illuminate the relationship between the vast range of insect phenotypic diversity and underlying genetic diversity. In combination with rapidly developing methods to estimate divergence times, these analyses will also provide a compelling view of the rates and patterns of lineagenesis (birth of lineages) over the half billion years of insect evolution.

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          Ultraconserved elements anchor thousands of genetic markers spanning multiple evolutionary timescales.

          Although massively parallel sequencing has facilitated large-scale DNA sequencing, comparisons among distantly related species rely upon small portions of the genome that are easily aligned. Methods are needed to efficiently obtain comparable DNA fragments prior to massively parallel sequencing, particularly for biologists working with non-model organisms. We introduce a new class of molecular marker, anchored by ultraconserved genomic elements (UCEs), that universally enable target enrichment and sequencing of thousands of orthologous loci across species separated by hundreds of millions of years of evolution. Our analyses here focus on use of UCE markers in Amniota because UCEs and phylogenetic relationships are well-known in some amniotes. We perform an in silico experiment to demonstrate that sequence flanking 2030 UCEs contains information sufficient to enable unambiguous recovery of the established primate phylogeny. We extend this experiment by performing an in vitro enrichment of 2386 UCE-anchored loci from nine, non-model avian species. We then use alignments of 854 of these loci to unambiguously recover the established evolutionary relationships within and among three ancient bird lineages. Because many organismal lineages have UCEs, this type of genetic marker and the analytical framework we outline can be applied across the tree of life, potentially reshaping our understanding of phylogeny at many taxonomic levels.
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            Applications of next-generation sequencing to phylogeography and phylogenetics.

            This is a time of unprecedented transition in DNA sequencing technologies. Next-generation sequencing (NGS) clearly holds promise for fast and cost-effective generation of multilocus sequence data for phylogeography and phylogenetics. However, the focus on non-model organisms, in addition to uncertainty about which sample preparation methods and analyses are appropriate for different research questions and evolutionary timescales, have contributed to a lag in the application of NGS to these fields. Here, we outline some of the major obstacles specific to the application of NGS to phylogeography and phylogenetics, including the focus on non-model organisms, the necessity of obtaining orthologous loci in a cost-effective manner, and the predominate use of gene trees in these fields. We describe the most promising methods of sample preparation that address these challenges. Methods that reduce the genome by restriction digest and manual size selection are most appropriate for studies at the intraspecific level, whereas methods that target specific genomic regions (i.e., target enrichment or sequence capture) have wider applicability from the population level to deep-level phylogenomics. Additionally, we give an overview of how to analyze NGS data to arrive at data sets applicable to the standard toolkit of phylogeography and phylogenetics, including initial data processing to alignment and genotype calling (both SNPs and loci involving many SNPs). Even though whole-genome sequencing is likely to become affordable rather soon, because phylogeography and phylogenetics rely on analysis of hundreds of individuals in many cases, methods that reduce the genome to a subset of loci should remain more cost-effective for some time to come. Copyright © 2011 Elsevier Inc. All rights reserved.
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              High-Throughput Genomic Data in Systematics and Phylogenetics

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                Author and article information

                Journal
                Current Opinion in Insect Science
                Current Opinion in Insect Science
                Elsevier BV
                22145745
                February 2016
                February 2016
                : 13
                :
                : 16-23
                Article
                10.1016/j.cois.2015.10.007
                27436549
                a2554bb8-5fe4-460a-ab80-d9f36482df14
                © 2016
                History

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