Placental mammals comprise three principal clades: Afrotheria (e.g., elephants and tenrecs), Xenarthra (e.g., armadillos and sloths), and Boreoeutheria (all other placental mammals), the relationships among which are the subject of controversy and a touchstone for debate on the limits of phylogenetic inference. Previous analyses have found support for all three hypotheses, leading some to conclude that this phylogenetic problem might be impossible to resolve due to the compounded effects of incomplete lineage sorting (ILS) and a rapid radiation. Here we show, using a genome scale nucleotide data set, microRNAs, and the reanalysis of the three largest previously published amino acid data sets, that the root of Placentalia lies between Atlantogenata and Boreoeutheria. Although we found evidence for ILS in early placental evolution, we are able to reject previous conclusions that the placental root is a hard polytomy that cannot be resolved. Reanalyses of previous data sets recover Atlantogenata + Boreoeutheria and show that contradictory results are a consequence of poorly fitting evolutionary models; instead, when the evolutionary process is better-modeled, all data sets converge on Atlantogenata. Our Bayesian molecular clock analysis estimates that marsupials diverged from placentals 157–170 Ma, crown Placentalia diverged 86–100 Ma, and crown Atlantogenata diverged 84–97 Ma. Our results are compatible with placental diversification being driven by dispersal rather than vicariance mechanisms, postdating early phases in the protracted opening of the Atlantic Ocean.

The most important mechanism in the regulation of transcription is the binding of a transcription factor (TF) to a DNA sequence called the TF binding site (TFBS). Most binding sites are short and degenerate, which makes predictions based on their primary sequence alone somewhat unreliable. We present a new web tool that implements a flexible and extensible algorithm for predicting TFBS. The algorithm makes use of both direct (the sequence) and several indirect readout features of protein–DNA complexes (biophysical properties such as bendability or the solvent-excluded surface of the DNA). This algorithm significantly outperforms state-of-the-art approaches for in silico identification of TFBS. Users can submit FASTA sequences for analysis in the PhysBinder integrative algorithm and choose from >60 different TF-binding models. The results of this analysis can be used to plan and steer wet-lab experiments. The PhysBinder web tool is freely available at http://bioit.dmbr.ugent.be/physbinder/index.php.

There are numerous phylogenetic reconstruction methods and models available-but which should you use and why? Important considerations in phylogenetic analyses include data quality, structure, signal, alignment length and sampling. If poorly modelled, variation in rates of change across proteins and across lineages can lead to incorrect phylogeny reconstruction which can then lead to downstream misinterpretation of the underlying data. The risk of choosing and applying an inappropriate model can be reduced with some critical yet straightforward steps outlined in this paper. We use the question of the position of the root of placental mammals as our working example to illustrate the topological impact of model misspecification. Using this case study we focus on using models in a Bayesian framework and we outline the steps involved in identifying and assessing better fitting models for specific datasets.

Gene fusion occurs when two or more individual genes with independent open reading frames becoming juxtaposed under the same open reading frame creating a new fused gene. A small number of gene fusions described in detail have been associated with novel functions, for example, the hominid-specific PIPSL gene, TNFSF12, and the TWE-PRIL gene family. We use Sequence Similarity Networks and species level comparisons of great ape genomes to identify 45 new genes that have emerged by transcriptional readthrough, that is, transcription-derived gene fusion. For 35 of these putative gene fusions, we have been able to assess available RNAseq data to determine whether there are reads that map to each breakpoint. A total of 29 of the putative gene fusions had annotated transcripts (9/29 of which are human-specific). We carried out RT-qPCR in a range of human tissues (placenta, lung, liver, brain, and testes) and found that 23 of the putative gene fusion events were expressed in at least one tissue. Examining the available ribosome foot-printing data, we find evidence for translation of three of the fused genes in human. Finally, we find enrichment for transcription-derived gene fusions in regions of known segmental duplication in human. Together, our results implicate chromosomal structural variation brought about by segmental duplication with the emergence of novel transcripts and translated protein products.