Lower Statistical Support with Larger Data Sets: Insights from the Ochrophyta Radiation.

It is commonly assumed that increasing the number of characters has the potential to resolve evolutionary radiations. Here, we studied photosynthetic stramenopiles (Ochrophyta) using alignments of heterogeneous origin mitochondrion, plastid, and nucleus. Surprisingly while statistical support for the relationships between the six major Ochrophyta lineages increases when comparing the mitochondrion (6,762 sites) and plastid (21,692 sites) trees, it decreases in the nuclear (209,105 sites) tree. Statistical support is not simply related to the data set size but also to the quantity of phylogenetic signal available at each position and our ability to extract it. Here, we show that this ability for current phylogenetic methods is limited, because conflicting results were obtained when varying taxon sampling. Even though the use of a better fitting model improved signal extraction and reduced the observed conflicts, the plastid data set provided higher statistical support for the ochrophyte radiation than the larger nucleus data set. We propose that the higher support observed in the plastid tree is due to an acceleration of the evolutionary rate in one short deep internal branch, implying that more phylogenetic signal per position is available to resolve the Ochrophyta radiation in the plastid than in the nuclear data set. Our work therefore suggests that, in order to resolve radiations, beyond the obvious use of data sets with more positions, we need to continue developing models of sequence evolution that better extract the phylogenetic signal and design methods to search for genes/characters that contain more signal specifically for short internal branches.

A cnidarian parasite of salmon (Myxozoa: Henneguya) lacks a mitochondrial genome.

Although aerobic respiration is a hallmark of eukaryotes, a few unicellular lineages, growing in hypoxic environments, have secondarily lost this ability. In the absence of oxygen, the mitochondria of these organisms have lost all or parts of their genomes and evolved into mitochondria-related organelles (MROs). There has been debate regarding the presence of MROs in animals. Using deep sequencing approaches, we discovered that a member of the Cnidaria, the myxozoan Henneguya salminicola, has no mitochondrial genome, and thus has lost the ability to perform aerobic cellular respiration. This indicates that these core eukaryotic features are not ubiquitous among animals. Our analyses suggest that H. salminicola lost not only its mitochondrial genome but also nearly all nuclear genes involved in transcription and replication of the mitochondrial genome. In contrast, we identified many genes that encode proteins involved in other mitochondrial pathways and determined that genes involved in aerobic respiration or mitochondrial DNA replication were either absent or present only as pseudogenes. As a control, we used the same sequencing and annotation methods to show that a closely related myxozoan, Myxobolus squamalis, has a mitochondrial genome. The molecular results are supported by fluorescence micrographs, which show the presence of mitochondrial DNA in M. squamalis, but not in H. salminicola. Our discovery confirms that adaptation to an anaerobic environment is not unique to single-celled eukaryotes, but has also evolved in a multicellular, parasitic animal. Hence, H. salminicola provides an opportunity for understanding the evolutionary transition from an aerobic to an exclusive anaerobic metabolism.

Broccoli: Combining Phylogenetic and Network Analyses for Orthology Assignment.

Orthology assignment is a key step of comparative genomic studies, for which many bioinformatic tools have been developed. However, all gene clustering pipelines are based on the analysis of protein distances, which are subject to many artifacts. In this article, we introduce Broccoli, a user-friendly pipeline designed to infer, with high precision, orthologous groups, and pairs of proteins using a phylogeny-based approach. Briefly, Broccoli performs ultrafast phylogenetic analyses on most proteins and builds a network of orthologous relationships. Orthologous groups are then identified from the network using a parameter-free machine learning algorithm. Broccoli is also able to detect chimeric proteins resulting from gene-fusion events and to assign these proteins to the corresponding orthologous groups. Tested on two benchmark data sets, Broccoli outperforms current orthology pipelines. In addition, Broccoli is scalable, with runtimes similar to those of recent distance-based pipelines. Given its high level of performance and efficiency, this new pipeline represents a suitable choice for comparative genomic studies. Broccoli is freely available at https://github.com/rderelle/Broccoli.

Phylotranscriptomic evidence for pervasive ancient hybridization among Old World salamanders.

Hybridization can leave genealogical signatures in an organism's genome, originating from the parental lineages and persisting over time. This potentially confounds phylogenetic inference methods that aim to represent evolution as a strictly bifurcating tree. We apply a phylotranscriptomic approach to study the evolutionary history of, and test for inter-lineage introgression in the Salamandridae, a Holarctic salamanders group of interest in studies of toxicity and aposematism, courtship behavior, and molecular evolution. Although the relationships between the 21 currently recognized salamandrid genera have been the subject of numerous molecular phylogenetic studies, some branches have remained controversial and sometimes affected by discordances between mitochondrial vs. nuclear trees. To resolve the phylogeny of this family, and understand the source of mito-nuclear discordance, we generated new transcriptomic (RNAseq) data for 20 salamandrids and used these along with published data, including 28 mitochondrial genomes, to obtain a comprehensive nuclear and mitochondrial perspective on salamandrid evolution. Our final phylotranscriptomic data set included 5455 gene alignments for 40 species representing 17 of the 21 salamandrid genera. Using concatenation and species-tree phylogenetic methods, we find (1) Salamandrina sister to the clade of the "True Salamanders" (consisting of Chioglossa, Mertensiella, Lyciasalamandra, and Salamandra), (2) Ichthyosaura sister to the Near Eastern genera Neurergus and Ommatotriton, (3) Triturus sister to Lissotriton, and (4) Cynops paraphyletic with respect to Paramesotriton and Pachytriton. Combining introgression tests and phylogenetic networks, we find evidence for introgression among taxa within the clades of "Modern Asian Newts" and "Modern European Newts". However, we could not unambiguously identify the number, position, and direction of introgressive events. Combining evidence from nuclear gene analysis with the observed mito-nuclear phylogenetic discordances, we hypothesize a scenario with hybridization and mitochondrial capture among ancestral lineages of (1) Lissotriton into Ichthyosaura and (2) Triturus into Calotriton, plus introgression of nuclear genes from Triturus into Lissotriton. Furthermore, both mitochondrial capture and nuclear introgression may have occurred among lineages assigned to Cynops. More comprehensive genomic data will, in the future, allow testing this against alternative scenarios involving hybridization with other, extinct lineages of newts.

Evaluating the usefulness of alignment filtering methods to reduce the impact of errors on evolutionary inferences.

BACKGROUND: Multiple Sequence Alignments (MSAs) are the starting point of molecular evolutionary analyses. Errors in MSAs generate a non-historical signal that can lead to incorrect inferences. Therefore, numerous efforts have been made to reduce the impact of alignment errors, by improving alignment algorithms and by developing methods to filter out poorly aligned regions. However, MSAs do not only contain alignment errors, but also primary sequence errors. Such errors may originate from sequencing errors, from assembly errors, or from erroneous structural annotations (such as incorrect intron/exon boundaries). Even though their existence is acknowledged, the impact of primary sequence errors on evolutionary inference is poorly characterized. RESULTS: In a first step to fill this gap, we have developed a program called HmmCleaner, which detects and eliminates these errors from MSAs. It uses profile hidden Markov models (pHMM) to identify sequence segments that poorly fit their MSA and selectively removes them. We assessed its performances using > 700 amino-acid MSAs from prokaryotes and eukaryotes, in which we introduced several types of simulated primary sequence errors. The sensitivity of HmmCleaner towards simulated primary sequence errors was > 95%. In a second step, we compared the impact of segment filtering software (HmmCleaner and PREQUAL) relative to commonly used block-filtering software (BMGE and TrimAI) on evolutionary analyses. Using real data from vertebrates, we observed that segment-filtering methods improve the quality of evolutionary inference more than the currently used block-filtering methods. The formers were especially effective at improving branch length inferences, and at reducing false positive rate during detection of positive selection. CONCLUSIONS: Segment filtering methods such as HmmCleaner accurately detect simulated primary sequence errors. Our results suggest that these errors are more detrimental than alignment errors. However, they also show that stochastic (sampling) error is predominant in single-gene evolutionary inferences. Therefore, we argue that MSA filtering should focus on segment instead of block removal and that more studies are required to find the optimal balance between accuracy improvement and stochastic error increase brought by data removal.

Multiple Factors Confounding Phylogenetic Detection of Selection on Codon Usage.

Detecting selection on codon usage (CU) is a difficult task, since CU can be shaped by both the mutational process and selective constraints operating at the DNA, RNA, and protein levels. Yang and Nielsen (2008) developed a test (which we call CUYN) for detecting selection on CU using two competing mutation-selection models of codon substitution. The null model assumes that CU is determined by the mutation bias alone, whereas the alternative model assumes that both mutation bias and/or selection act on CU. In applications on mammalian-scale alignments, the CUYN test detects selection on CU for numerous genes. This is surprising, given the small effective population size of mammals, and prompted us to use simulations to evaluate the robustness of the test to model violations. Simulations using a modest level of CpG hypermutability completely mislead the test, with 100% false positives. Surprisingly, a high level of false positives (56.1%) resulted simply from using the HKY mutation-level parameterization within the CUYN test on simulations conducted with a GTR mutation-level parameterization. Finally, by using a crude optimization procedure on a parameter controlling the CpG hypermutability rate, we find that this mutational property could explain a very large part of the observed mammalian CU. Altogether, our work emphasizes the need to evaluate the potential impact of model violations on statistical tests in the field of molecular phylogenetic analysis. The source code of the simulator and the mammalian genes used are available as a GitHub repository (https://github.com/Simonll/LikelihoodFreePhylogenetics.git).

Conditional Approximate Bayesian Computation: A New Approach for Across-Site Dependency in High-Dimensional Mutation-Selection Models.

A key question in molecular evolutionary biology concerns the relative roles of mutation and selection in shaping genomic data. Moreover, features of mutation and selection are heterogeneous along the genome and over time. Mechanistic codon substitution models based on the mutation-selection framework are promising approaches to separating these effects. In practice, however, several complications arise, since accounting for such heterogeneities often implies handling models of high dimensionality (e.g., amino acid preferences), or leads to across-site dependence (e.g., CpG hypermutability), making the likelihood function intractable. Approximate Bayesian Computation (ABC) could address this latter issue. Here, we propose a new approach, named Conditional ABC (CABC), which combines the sampling efficiency of MCMC and the flexibility of ABC. To illustrate the potential of the CABC approach, we apply it to the study of mammalian CpG hypermutability based on a new mutation-level parameter implying dependence across adjacent sites, combined with site-specific purifying selection on amino-acids captured by a Dirichlet process. Our proof-of-concept of the CABC methodology opens new modeling perspectives. Our application of the method reveals a high level of heterogeneity of CpG hypermutability across loci and mild heterogeneity across taxonomic groups; and finally, we show that CpG hypermutability is an important evolutionary factor in rendering relative synonymous codon usage. All source code is available as a GitHub repository (https://github.com/Simonll/LikelihoodFreePhylogenetics.git).

The African coelacanth genome provides insights into tetrapod evolution.

The discovery of a living coelacanth specimen in 1938 was remarkable, as this lineage of lobe-finned fish was thought to have become extinct 70 million years ago. The modern coelacanth looks remarkably similar to many of its ancient relatives, and its evolutionary proximity to our own fish ancestors provides a glimpse of the fish that first walked on land. Here we report the genome sequence of the African coelacanth, Latimeria chalumnae. Through a phylogenomic analysis, we conclude that the lungfish, and not the coelacanth, is the closest living relative of tetrapods. Coelacanth protein-coding genes are significantly more slowly evolving than those of tetrapods, unlike other genomic features. Analyses of changes in genes and regulatory elements during the vertebrate adaptation to land highlight genes involved in immunity, nitrogen excretion and the development of fins, tail, ear, eye, brain and olfaction. Functional assays of enhancers involved in the fin-to-limb transition and in the emergence of extra-embryonic tissues show the importance of the coelacanth genome as a blueprint for understanding tetrapod evolution.

A software tool 'CroCo' detects pervasive cross-species contamination in next generation sequencing data.

BACKGROUND: Multiple RNA samples are frequently processed together and often mixed before multiplex sequencing in the same sequencing run. While different samples can be separated post sequencing using sample barcodes, the possibility of cross contamination between biological samples from different species that have been processed or sequenced in parallel has the potential to be extremely deleterious for downstream analyses. RESULTS: We present CroCo, a software package for identifying and removing such cross contaminants from assembled transcriptomes. Using multiple, recently published sequence datasets, we show that cross contamination is consistently present at varying levels in real data. Using real and simulated data, we demonstrate that CroCo detects contaminants efficiently and correctly. Using a real example from a molecular phylogenetic dataset, we show that contaminants, if not eliminated, can have a decisive, deleterious impact on downstream comparative analyses. CONCLUSIONS: Cross contamination is pervasive in new and published datasets and, if undetected, can have serious deleterious effects on downstream analyses. CroCo is a database-independent, multi-platform tool, designed for ease of use, that efficiently and accurately detects and removes cross contamination in assembled transcriptomes to avoid these problems. We suggest that the use of CroCo should become a standard cleaning step when processing multiple samples for transcriptome sequencing.

A phylogenomic framework and timescale for comparative studies of tunicates.

BACKGROUND: Tunicates are the closest relatives of vertebrates and are widely used as models to study the evolutionary developmental biology of chordates. Their phylogeny, however, remains poorly understood, and to date, only the 18S rRNA nuclear gene and mitogenomes have been used to delineate the major groups of tunicates. To resolve their evolutionary relationships and provide a first estimate of their divergence times, we used a transcriptomic approach to build a phylogenomic dataset including all major tunicate lineages, consisting of 258 evolutionarily conserved orthologous genes from representative species. RESULTS: Phylogenetic analyses using site-heterogeneous CAT mixture models of amino acid sequence evolution resulted in a strongly supported tree topology resolving the relationships among four major tunicate clades: (1) Appendicularia, (2) Thaliacea + Phlebobranchia + Aplousobranchia, (3) Molgulidae, and (4) Styelidae + Pyuridae. Notably, the morphologically derived Thaliacea are confirmed as the sister group of the clade uniting Phlebobranchia + Aplousobranchia within which the precise position of the model ascidian genus Ciona remains uncertain. Relaxed molecular clock analyses accommodating the accelerated evolutionary rate of tunicates reveal ancient diversification (~ 450-350 million years ago) among the major groups and allow one to compare their evolutionary age with respect to the major vertebrate model lineages. CONCLUSIONS: Our study represents the most comprehensive phylogenomic dataset for the main tunicate lineages. It offers a reference phylogenetic framework and first tentative timescale for tunicates, allowing a direct comparison with vertebrate model species in comparative genomics and evolutionary developmental biology studies.