Mitochondrial evolution in the Demospongiae (Porifera): Phylogeny, divergence time, and genome biology.

The sponge class Demospongiae is the most speciose and morphologically diverse in the phylum Porifera, and the species within it are vital components of a range of ecosystems worldwide. Despite their ubiquity, a number of recalcitrant problems still remain to be solved regarding their phylogenetic inter-relationships, the timing of their appearance, and their mitochondrial biology, the latter of which is only beginning to be investigated. Here we generated 14 new demosponge mitochondrial genomes which, alongside previously published mitochondrial resources, were used to address these issues. In addition to phylogenomic analysis, we have used syntenic data and analysis of coding regions to forge a framework for understanding the inter-relationships between Demospongiae sub-classes and orders. We have also leveraged our new resources to study the mitochondrial biology of these clades in terms of codon usage, optimisation and gene expression, to understand how these vital cellular components may have contributed to the success of the Porifera. Our results strongly support a sister relationship between Keratosa and (Verongimorpha + Heteroscleromorpha), contradicting previous studies using nuclear markers. Our study includes one species of Clionaida, and show for the first time support for a grouping of Suberitida+(Clionaida+(Tethyida + Poecilosclerida). The findings of our phylogenetic analyses are supported by in-depth examination of structural and coding-level evidence from our mitochondrial data. A time-calibrated phylogeny estimated the origin of Demospongiae in the Cambrian (~529 Mya), and suggests that most demosponge order crown-groups emerged in the Mesozoic. This work therefore provides a robust basis for considering demosponge phylogenetic relationships, as well as essential mitochondrial data for understanding the biological basis for their success and diversity.

Phylogenomics: Is less more when using large-scale datasets?

Phylogenetic studies have traditionally placed the simple Xenoacoelomorph worms as the sister group of all other animals with bilateral body symmetry. A new study shows that misidentification of orthologous genes might have been the source of at least some support for this placement.

Resolving tricky nodes in the tree of life through amino acid recoding.

Genomic data allowed a detailed resolution of the Tree of Life, but "tricky nodes" such as the root of the animals remain unresolved. Genome-scale datasets are heterogeneous as genes and species are exposed to different pressures, and this can negatively impacts phylogenetic accuracy. We use simulated genomic-scale datasets and show that recoding amino acid data improves accuracy when the model does not account for the compositional heterogeneity of the amino acid alignment. We apply our findings to three datasets addressing the root of the animal tree, where the debate centers on whether sponges (Porifera) or comb jellies (Ctenophora) represent the sister of all other animals. We show that results from empirical data follow predictions from simulations and suggest that, at the least in phylogenies inferred from amino acid sequences, a placement of the ctenophores as sister to all the other animals is best explained as a tree reconstruction artifact.

Trimitomics: An efficient pipeline for mitochondrial assembly from transcriptomic reads in nonmodel species.

Mitochondrial resources are of known utility to many fields of phylogenetic, population and molecular biology. Their combination of faster and slower-evolving regions and high copy number enables them to be used in many situations where other loci are unsuitable, with degraded samples and after recent speciation events.The advent of next-generation sequencing technologies (and notably the Illumina platform) has led to an explosion in the number of samples that can be studied at transcriptomic level, at relatively low cost. Here we describe a robust pipeline for the recovery of mitochondrial genomes from these RNA-sequencing resources. This pipeline can be used on sequencing of a variety of depths, and reliably recovers the protein coding and ribosomal gene complements of mitochondria from almost any transcriptomic sequencing experiment. The complete sequence of the mitochondrial genome can also be recovered when sequencing is performed in sufficient depth. We show the efficacy of our pipeline using data from eight nonmodel invertebrates of six disparate phyla. Interestingly, among our poriferan data, where microbiological symbionts are known empirically to make mitochondrial assembly difficult, this pipeline proved especially useful. Our pipeline will allow the recovery of mitochondrial data from a variety of previously sequenced samples, and add an additional angle of enquiry to future RNA-sequencing efforts, simplifying the process of mitochondrial genome assembly for even the most recalcitrant clades and adding these data to the scientific record for a range of future uses.