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

• Recent advances in next generation sequencing technology have facilitated the assembly of very large molecular phylogenetic datasets.
• These phylogenomic datasets have unprecedented power to resolve insect phylogeny.
• There are many techniques available now to identify and remove systematic bias from these datasets.
• Advances in high-performance computing and more realistic models of molecular evolution will enable even greater accuracy in phylogenetic reconstruction.

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.