OrthoMaM: a database of orthologous genomic markers for placental mammal phylogenetics

OrthoMaM v12: a database of curated single-copy ortholog alignments and trees to study mammalian evolutionary genomics

To date, the databases built to gather information on gene orthology do not provide end-users with descriptors of the molecular evolution information and phylogenetic pattern of these orthologues. In this context, we developed OrthoMaM, a database of ORTHOlogous MAmmalian Markers describing the evolutionary dynamics of coding sequences in mammalian genomes. OrthoMaM version 12 includes 15,868 alignments of orthologous coding sequences (CDS) from the 190 complete mammalian genomes currently available. All annotations and 1-to-1 orthology assignments are based on NCBI. Orthologous CDS can be mined for potential informative markers at the different taxonomic levels of the mammalian tree. To this end, several evolutionary descriptors of DNA sequences are provided for querying purposes (e.g. base composition and relative substitution rate). The graphical web interface allows the user to easily browse and sort the results of combined queries. The corresponding multiple sequence alignments and ML trees, inferred using state-of-the art approaches, are available for download both at the nucleotide and amino acid levels. OrthoMaM v12 can be used by researchers interested either in reconstructing the phylogenetic relationships of mammalian taxa or in understanding the evolutionary dynamics of coding sequences in their genomes. OrthoMaM is available for browsing, querying and complete or filtered download at https://orthomam.mbb.cnrs.fr/.

Molecular Footprints on Osmoregulation-Related Genes Associated with Freshwater Colonization by Cetaceans and Sirenians

The genetic basis underlying adaptive physiological mechanisms has been extensively explored in mammals after colonizing the seas. However, independent lineages of aquatic mammals exhibit complex patterns of secondary colonization in freshwater environments. This change in habitat represents new osmotic challenges, and additional changes in key systems, such as the osmoregulatory system, are expected. Here, we studied the selective regime on coding and regulatory regions of 20 genes related to the osmoregulation system in strict aquatic mammals from independent evolutionary lineages, cetaceans, and sirenians, with representatives in marine and freshwater aquatic environments. We identified positive selection signals in genes encoding the protein vasopressin (AVP) in mammalian lineages with secondary colonization in the fluvial environment and in aquaporins for lineages inhabiting the marine and fluvial environments. A greater number of sites with positive selection signals were found for the dolphin species compared to the Amazonian manatee. Only the AQP5 and AVP genes showed selection signals in more than one independent lineage of these mammals. Furthermore, the vasopressin gene tree indicates greater similarity in river dolphin sequences despite the independence of their lineages based on the species tree. Patterns of distribution and enrichment of Transcription Factors in the promoter regions of target genes were analyzed and appear to be phylogenetically conserved among sister species. We found accelerated evolution signs in genes ACE, AQP1, AQP5, AQP7, AVP, NPP4, and NPR1 for the fluvial mammals. Together, these results allow a greater understanding of the molecular bases of the evolution of genes responsible for osmotic control in aquatic mammals.

Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale

Adaptation in protein-coding sequences can be detected from multiple sequence alignments across species or alternatively by leveraging polymorphism data within a population. Across species, quantification of the adaptive rate relies on phylogenetic codon models, classically formulated in terms of the ratio of nonsynonymous over synonymous substitution rates. Evidence of an accelerated nonsynonymous substitution rate is considered a signature of pervasive adaptation. However, because of the background of purifying selection, these models are potentially limited in their sensitivity. Recent developments have led to more sophisticated mutation-selection codon models aimed at making a more detailed quantitative assessment of the interplay between mutation, purifying, and positive selection. In this study, we conducted a large-scale exome-wide analysis of placental mammals with mutation-selection models, assessing their performance at detecting proteins and sites under adaptation. Importantly, mutation-selection codon models are based on a population-genetic formalism and thus are directly comparable to the McDonald and Kreitman test at the population level to quantify adaptation. Taking advantage of this relationship between phylogenetic and population genetics analyses, we integrated divergence and polymorphism data across the entire exome for 29 populations across 7 genera and showed that proteins and sites detected to be under adaptation at the phylogenetic scale are also under adaptation at the population-genetic scale. Altogether, our exome-wide analysis shows that phylogenetic mutation-selection codon models and the population-genetic test of adaptation can be reconciled and are congruent, paving the way for integrative models and analyses across individuals and populations.

Evolutionary analysis of endogenous intronic retroviruses in primates reveals an enrichment in transcription binding sites associated with key regulatory processes

Background

Endogenous retroviruses (ERVs) are the result of the integration of retroviruses into host DNA following germline infection. Endogenous retroviruses are made up of three main genes: gag, pol, and env, each of which encodes viral proteins that can be conserved or not. ERVs have been observed in a wide range of vertebrate genomes and their functions are associated with viral silencing and gene regulation.

Results

In this work, we studied the evolutionary history of endogenous retroviruses associated with five human genes (INPP5B, DET1, PSMA1, USH2A, and MACROD2), which are located within intron sections. To verify the retroviral origin of the candidates, several approaches were used to detect and locate ERV elements. Both orthologous and paralogous genes were identified by Ensembl and then analyzed for ERV presence using RetroTector. A phylogenetic tree was reconstructed to identify the minimum time point of ERV acquisition. From that search, we detected ERVs throughout the primate lineage and in some other groups. Also, we identified the minimum origin of the ERVs from the parvorder Catarrhini to the Homininae subfamily.

Conclusions

With the data collected, and by observing the transcription factors annotated inside ERVs, we propose that these elements play a relevant role in gene expression regulation and they probably possess important features for tumorigenesis control.

Detecting and removing sample contamination in phylogenomic data: an example and its implications for Cicadidae phylogeny (Insecta: Hemiptera)

Contamination of a genetic sample with DNA from one or more non-target species is a continuing concern of molecular phylogenetic studies, both Sanger sequencing studies and Next-Generation Sequencing (NGS) studies. We developed an automated pipeline for identifying and excluding likely cross-contaminated loci based on detection of bimodal distributions of patristic distances across gene trees. When the contamination occurs between samples within a dataset, comparisons between a contaminated sample and its contaminant taxon will yield bimodal distributions with one peak close to zero patristic distance. This new method does not rely on a priori knowledge of taxon relatedness nor does it determine the causes(s) of the contamination. Exclusion of putatively contaminated loci from a dataset generated for the insect family Cicadidae showed that these sequences were affecting some topological patterns and branch supports, although the effects were sometimes subtle, with some contamination-influenced relationships exhibiting strong bootstrap support. Long tip branches and outlier values for one anchored phylogenomic pipeline statistic (AvgNHomologs) were correlated with the presence of contamination. While the AHE markers used here, which target hemipteroid taxa, proved effective in resolving deep and shallow level Cicadidae relationships in aggregate, individual markers contained inadequate phylogenetic signal, in part probably due to short length. The cleaned dataset, consisting of 429 loci, from 90 genera representing 44 of 56 current Cicadidae tribes, supported three of the four sampled Cicadidae subfamilies in concatenated-matrix maximum likelihood (ML) and multispecies coalescent-based species tree analyses, with the fourth subfamily weakly supported in the ML trees. No well-supported patterns from previous family-level Sanger sequencing studies of Cicadidae phylogeny were contradicted. One taxon (Aragualna plenalinea) did not fall with its current subfamily in the genetic tree, and this genus and its tribe Aragualnini is reclassified to Tibicininae following morphological re-examination. Only subtle differences were observed in trees after removal of loci for which divergent base frequencies were detected. Greater success may be achieved by increased taxon sampling and developing a probe set targeting a more recent common ancestor and longer loci. Searches for contamination are an essential step in phylogenomic analyses of all kinds and our pipeline is an effective solution.

Inferring long-term effective population size with Mutation-Selection Models

Mutation–selection phylogenetic codon models are grounded on population genetics first principles and represent a principled approach for investigating the intricate interplay between mutation, selection, and drift. In their current form, mutation–selection codon models are entirely characterized by the collection of site-specific amino-acid fitness profiles. However, thus far, they have relied on the assumption of a constant genetic drift, translating into a unique effective population size (Ne) across the phylogeny, clearly an unrealistic assumption. This assumption can be alleviated by introducing variation in Ne between lineages. In addition to Ne, the mutation rate (μ) is susceptible to vary between lineages, and both should covary with life-history traits (LHTs). This suggests that the model should more globally account for the joint evolutionary process followed by all of these lineage-specific variables (Ne, μ, and LHTs). In this direction, we introduce an extended mutation–selection model jointly reconstructing in a Bayesian Monte Carlo framework the fitness landscape across sites and long-term trends in Ne, μ, and LHTs along the phylogeny, from an alignment of DNA coding sequences and a matrix of observed LHTs in extant species. The model was tested against simulated data and applied to empirical data in mammals, isopods, and primates. The reconstructed history of Ne in these groups appears to correlate with LHTs or ecological variables in a way that suggests that the reconstruction is reasonable, at least in its global trends. On the other hand, the range of variation in Ne inferred across species is surprisingly narrow. This last point suggests that some of the assumptions of the model, in particular concerning the assumed absence of epistatic interactions between sites, are potentially problematic.

ModelTeller: Model Selection for Optimal Phylogenetic Reconstruction Using Machine Learning

Statistical criteria have long been the standard for selecting the best model for phylogenetic reconstruction and downstream statistical inference. Although model selection is regarded as a fundamental step in phylogenetics, existing methods for this task consume computational resources for long processing time, they are not always feasible, and sometimes depend on preliminary assumptions which do not hold for sequence data. Moreover, although these methods are dedicated to revealing the processes that underlie the sequence data, they do not always produce the most accurate trees. Notably, phylogeny reconstruction consists of two related tasks, topology reconstruction and branch-length estimation. It was previously shown that in many cases the most complex model, GTR+I+G, leads to topologies that are as accurate as using existing model selection criteria, but overestimates branch lengths. Here, we present ModelTeller, a computational methodology for phylogenetic model selection, devised within the machine-learning framework, optimized to predict the most accurate nucleotide substitution model for branch-length estimation. We demonstrate that ModelTeller leads to more accurate branch-length inference than current model selection criteria on data sets simulated under realistic processes. ModelTeller relies on a readily implemented machine-learning model and thus the prediction according to features extracted from the sequence data results in a substantial decrease in running time compared with existing strategies. By harnessing the machine-learning framework, we distinguish between features that mostly contribute to branch-length optimization, concerning the extent of sequence divergence, and features that are related to estimates of the model parameters that are important for the selection made by current criteria.

Harnessing machine learning to guide phylogenetic-tree search algorithms

Inferring a phylogenetic tree is a fundamental challenge in evolutionary studies. Current paradigms for phylogenetic tree reconstruction rely on performing costly likelihood optimizations. With the aim of making tree inference feasible for problems involving more than a handful of sequences, inference under the maximum-likelihood paradigm integrates heuristic approaches to evaluate only a subset of all potential trees. Consequently, existing methods suffer from the known tradeoff between accuracy and running time. In this proof-of-concept study, we train a machine-learning algorithm over an extensive cohort of empirical data to predict the neighboring trees that increase the likelihood, without actually computing their likelihood. This provides means to safely discard a large set of the search space, thus potentially accelerating heuristic tree searches without losing accuracy. Our analyses suggest that machine learning can guide tree-search methodologies towards the most promising candidate trees.

Evolutionarily conserved sequence motif analysis guides development of chemically defined hydrogels for therapeutic vascularization

Biologically active ligands (e.g., RGDS from fibronectin) play critical roles in the development of chemically defined biomaterials. However, recent decades have shown only limited progress in discovering novel extracellular matrix-protein-derived ligands for translational applications. Through motif analysis of evolutionarily conserved RGD-containing regions in laminin (LM) and peptide-functionalized hydrogel microarray screening, we identified a peptide (a1) that showed superior supports for endothelial cell (EC) functions. Mechanistic studies attributed the results to the capacity of a1 engaging both LM- and Fn-binding integrins. RNA sequencing of ECs in a1-functionalized hydrogels showed ~60% similarities with Matrigel in "vasculature development" gene ontology terms. Vasculogenesis assays revealed the capacity of a1-formulated hydrogels to improve EC network formation. Injectable alginates functionalized with a1 and MMPQK (a vascular endothelial growth factor-mimetic peptide with a matrix metalloproteinase-degradable linker) increased blood perfusion and functional recovery over decellularized extracellular matrix and (RGDS + MMPQK)-functionalized hydrogels in an ischemic hindlimb model, illustrating the power of this approach.

Survey for positively selected coding regions in the genome of the hematophagous tsetse fly Glossina morsitans identifies candidate genes associated with feeding habits and embryonic development

Tsetse flies are responsible for the transmission of Trypanossoma sp. to vertebrate animals in Africa causing huge health issues and economic loss. The availability of the genome sequence of Glossina morsitans enabled the discovery of several genes related to medically important phenotypes and novel physiological features. However, a genome-wide scan for coding regions that underwent positive selection is still missing, which is surprising given the evolution of traits associated with the hematophagy in this lineage. In this study, we employed an experimental design that controlled for the rate of false positives and we performed a scan of 3,318 G. morsitans genes. We found 145 genes with significant historical signal of positive selection. These genes were categorized into 18 functional classes after careful manual annotation. Based on their attributed functions, we identified candidate genes related with feeding habits and embryonic development. When our results were contrasted with gene expression data, we confirmed that most genes that underwent adaptive molecular evolution were frequently expressed in organs associated with key physiological evolutionary innovations in the G. morsitans lineage, namely, the salivary gland, the midgut, fat body tissue, and in the spermatophore.

Determinants of genetic variation across eco-evolutionary scales in pinnipeds

The effective size of a population (N_e), which determines its level of neutral variability, is a key evolutionary parameter. N_e can substantially depart from census sizes of present-day breeding populations (N_C) as a result of past demographic changes, variation in life-history traits and selection at linked sites. Using genome-wide data we estimated the long-term coalescent N_e for 17 pinniped species represented by 36 population samples (total n = 458 individuals). N_e estimates ranged from 8,936 to 91,178, were highly consistent within (sub)species and showed a strong positive correlation with N_C ([Formula: see text] = 0.59; P = 0.0002). N_e/N_C ratios were low (mean, 0.31; median, 0.13) and co-varied strongly with demographic history and, to a lesser degree, with species' ecological and life-history variables such as breeding habitat. Residual variation in N_e/N_C, after controlling for past demographic fluctuations, contained information about recent population size changes during the Anthropocene. Specifically, species of conservation concern typically had positive residuals indicative of a smaller contemporary N_C than would be expected from their long-term N_e. This study highlights the value of comparative population genomic analyses for gauging the evolutionary processes governing genetic variation in natural populations, and provides a framework for identifying populations deserving closer conservation attention.

Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals

Whether adaptation is limited by the beneficial mutation supply is a long-standing question of evolutionary genetics, which is more generally related to the determination of the adaptive substitution rate and its relationship with species effective population size (Ne) and genetic diversity. Empirical evidence reported so far is equivocal, with some but not all studies supporting a higher adaptive substitution rate in large-Ne than in small-Ne species. We gathered coding sequence polymorphism data and estimated the adaptive amino-acid substitution rate ωa, in 50 species from ten distant groups of animals with markedly different population mutation rate θ. We reveal the existence of a complex, timescale dependent relationship between species adaptive substitution rate and genetic diversity. We find a positive relationship between ωa and θ among closely related species, indicating that adaptation is indeed limited by the mutation supply, but this was only true in relatively low-θ taxa. In contrast, we uncover no significant correlation between ωa and θ at a larger taxonomic scale, suggesting that the proportion of beneficial mutations scales negatively with species' long-term Ne.

STELAR: a statistically consistent coalescent-based species tree estimation method by maximizing triplet consistency

Background

Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, estimating a species tree from a collection of gene trees can be complicated due to the presence of gene tree incongruence resulting from incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent process. Maximum likelihood and Bayesian MCMC methods can potentially result in accurate trees, but they do not scale well to large datasets.

Results

We present STELAR (Species Tree Estimation by maximizing tripLet AgReement), a new fast and highly accurate statistically consistent coalescent-based method for estimating species trees from a collection of gene trees. We formalized the constrained triplet consensus (CTC) problem and showed that the solution to the CTC problem is a statistically consistent estimate of the species tree under the multi-species coalescent (MSC) model. STELAR is an efficient dynamic programming based solution to the CTC problem which is highly accurate and scalable. We evaluated the accuracy of STELAR in comparison with SuperTriplets, which is an alternate fast and highly accurate triplet-based supertree method, and with MP-EST and ASTRAL – two of the most popular and accurate coalescent-based methods. Experimental results suggest that STELAR matches the accuracy of ASTRAL and improves on MP-EST and SuperTriplets.

Conclusions

Theoretical and empirical results (on both simulated and real biological datasets) suggest that STELAR is a valuable technique for species tree estimation from gene tree distributions.

CAARS: comparative assembly and annotation of RNA-Seq data

MOTIVATION

RNA sequencing (RNA-Seq) is a widely used approach to obtain transcript sequences in non-model organisms, notably for performing comparative analyses. However, current bioinformatic pipelines do not take full advantage of pre-existing reference data in related species for improving RNA-Seq assembly, annotation and gene family reconstruction.

RESULTS

We built an automated pipeline named CAARS to combine novel data from RNA-Seq experiments with existing multi-species gene family alignments. RNA-Seq reads are assembled into transcripts by both de novo and assisted assemblies. Then, CAARS incorporates transcripts into gene families, builds gene alignments and trees and uses phylogenetic information to classify the genes as orthologs and paralogs of existing genes. We used CAARS to assemble and annotate RNA-Seq data in rodents and fishes using distantly related genomes as reference, a difficult case for this kind of analysis. We showed CAARS assemblies are more complete and accurate than those assembled by a standard pipeline consisting of de novo assembly coupled with annotation by sequence similarity on a guide species. In addition to annotated transcripts, CAARS provides gene family alignments and trees, annotated with orthology relationships, directly usable for downstream comparative analyses.

AVAILABILITY AND IMPLEMENTATION

CAARS is implemented in Python and Ocaml and is freely available at https://github.com/carinerey/caars.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

OrthoMaM v10: Scaling-Up Orthologous Coding Sequence and Exon Alignments with More than One Hundred Mammalian Genomes

We present version 10 of OrthoMaM, a database of orthologous mammalian markers. OrthoMaM is already 11 years old and since the outset it has kept on improving, providing alignments and phylogenetic trees of high-quality computed with state-of-the-art methods on up-to-date data. The main contribution of this version is the increase in the number of taxa: 116 mammalian genomes for 14,509 one-to-one orthologous genes. This has been made possible by the combination of genomic data deposited in Ensembl complemented by additional good-quality genomes only available in NCBI. Version 10 users will benefit from pipeline improvements and a completely redesigned web-interface.

Divergent Evolution of TRC Genes in Mammalian Niche Adaptation

Mammals inhabit a wide variety of ecological niches, which in turn can be affected by various ecological factors, especially in relation to immunity. The canonical TRC repertoire (TRAC, TRBC, TRGC, and TRDC) codes C regions of T cell receptor chains that form the primary antigen receptors involved in the activation of cellular immunity. At present, little is known about the correlation between the evolution of mammalian TRC genes and ecological factors. In this study, four types canonical of TRC genes were identified from 37 mammalian species. Phylogenetic comparative methods (phyANOVA and PGLS) and selective pressure analyses among different groups of ecological factors (habitat, diet, and sociality) were carried out. The results showed that habitat was the major ecological factor shaping mammalian TRC repertoires. Specifically, trade-off between TRGC numbers and positive selection of TRAC and the balanced evolutionary rates between TRAC and TRDC genes were speculated as two main mechanisms in adaption to habitat and sociality. Overall, our study suggested divergent mechanisms for the evolution of TRCs, prompting mammalian immunity adaptions within diverse niches.

Digging for the spiny rat and hutia phylogeny using a gene capture approach, with the description of a new mammal subfamily

Next generation sequencing (NGS) and genomic database mining allow biologists to gather and select large molecular datasets well suited to address phylogenomics and molecular evolution questions. Here we applied this approach to a mammal family, the Echimyidae, for which generic relationships have been difficult to recover and often referred to as a star phylogeny. These South-American spiny rats represent a family of caviomorph rodents exhibiting a striking diversity of species and life history traits. Using a NGS exon capture protocol, we isolated and sequenced ca. 500 nuclear DNA exons for 35 species belonging to all major echimyid and capromyid clades. Exons were carefully selected to encompass as much diversity as possible in terms of rate of evolution, heterogeneity in the distribution of site-variation and nucleotide composition. Supermatrix inferences and coalescence-based approaches were subsequently applied to infer this family's phylogeny. The inferred topologies were the same for both approaches, and support was maximal for each node, entirely resolving the ambiguous relationships of previous analyses. Fast-evolving nuclear exons tended to yield more reliable phylogenies, as slower-evolving sequences were not informative enough to disentangle the short branches of the Echimyidae radiation. Based on this resolved phylogeny and on molecular and morphological evidence, we confirm the rank of the Caribbean hutias - formerly placed in the Capromyidae family - as Capromyinae, a clade nested within Echimyidae. We also name and define Carterodontinae, a new subfamily of Echimyidae, comprising the extant monotypic genus Carterodon from Brazil, which is the closest living relative of West Indies Capromyinae.

Influence of Recombination and GC-biased Gene Conversion on the Adaptive and Nonadaptive Substitution Rate in Mammals versus Birds

Recombination is expected to affect functional sequence evolution in several ways. On the one hand, recombination is thought to improve the efficiency of multilocus selection by dissipating linkage disequilibrium. On the other hand, natural selection can be counteracted by recombination-associated transmission distorters such as GC-biased gene conversion (gBGC), which tends to promote G and C alleles irrespective of their fitness effect in high-recombining regions. It has been suggested that gBGC might impact coding sequence evolution in vertebrates, and particularly the ratio of nonsynonymous to synonymous substitution rates (dN/dS). However, distinctive gBGC patterns have been reported in mammals and birds, maybe reflecting the documented contrasts in evolutionary dynamics of recombination rate between these two taxa. Here, we explore how recombination and gBGC affect coding sequence evolution in mammals and birds by analyzing proteome-wide data in six species of Galloanserae (fowls) and six species of catarrhine primates. We estimated the dN/dS ratio and rates of adaptive and nonadaptive evolution in bins of genes of increasing recombination rate, separately analyzing AT → GC, GC → AT, and G ↔ C/A ↔ T mutations. We show that in both taxa, recombination and gBGC entail a decrease in dN/dS. Our analysis indicates that recombination enhances the efficiency of purifying selection by lowering Hill-Robertson effects, whereas gBGC leads to an overestimation of the adaptive rate of AT → GC mutations. Finally, we report a mutagenic effect of recombination, which is independent of gBGC.

Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics

Building the Tree of Life (ToL) is a major challenge of modern biology, requiring advances in cyberinfrastructure, data collection, theory, and more. Here, we argue that phylogenomics stands to benefit by embracing the many heterogeneous genomic signals emerging from the first decade of large-scale phylogenetic analysis spawned by high-throughput sequencing (HTS). Such signals include those most commonly encountered in phylogenomic datasets, such as incomplete lineage sorting, but also those reticulate processes emerging with greater frequency, such as recombination and introgression. Here we focus specifically on how phylogenetic methods can accommodate the heterogeneity incurred by such population genetic processes; we do not discuss phylogenetic methods that ignore such processes, such as concatenation or supermatrix approaches or supertrees. We suggest that methods of data acquisition and the types of markers used in phylogenomics will remain restricted until a posteriori methods of marker choice are made possible with routine whole-genome sequencing of taxa of interest. We discuss limitations and potential extensions of a model supporting innovation in phylogenomics today, the multispecies coalescent model (MSC). Macroevolutionary models that use phylogenies, such as character mapping, often ignore the heterogeneity on which building phylogenies increasingly rely and suggest that assimilating such heterogeneity is an important goal moving forward. Finally, we argue that an integrative cyberinfrastructure linking all steps of the process of building the ToL, from specimen acquisition in the field to publication and tracking of phylogenomic data, as well as a culture that values contributors at each step, are essential for progress.

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.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1350-2) contains supplementary material, which is available to authorized users.

Toward Reducing Phylostratigraphic Errors and Biases

Phylostratigraphy is a method for estimating gene age, usually applied to large numbers of genes in order to detect nonrandom age-distributions of gene properties that could shed light on mechanisms of gene origination and evolution. However, phylostratigraphy underestimates gene age with a nonnegligible probability. The underestimation is severer for genes with certain properties, creating spurious age distributions of these properties and those correlated with these properties. Here we explore three strategies to reduce phylostratigraphic error/bias. First, we test several alternative homology detection methods (PSIBLAST, HMMER, PHMMER, OMA, and GLAM2Scan) in phylostratigraphy, but fail to find any that noticeably outperforms the commonly used BLASTP. Second, using machine learning, we look for predictors of error-prone genes to exclude from phylostratigraphy, but cannot identify reliable predictors. Finally, we remove from phylostratigraphic analysis genes exhibiting errors in simulation, which by definition minimizes error/bias if the simulation is sufficiently realistic. Using this last approach, we show that some previously reported phylostratigraphic trends (e.g., younger proteins tend to evolve more rapidly and be shorter) disappear or even reverse, reconfirming the necessity of controlling phylostratigraphic error/bias. Taken together, our analyses demonstrate that phylostratigraphic errors/biases are refractory to several potential solutions but can be controlled at least partially by the exclusion of error-prone genes identified via realistic simulations. These results are expected to stimulate the judicious use of error-aware phylostratigraphy and reevaluation of previous phylostratigraphic findings.

Hologenomic adaptations underlying the evolution of sanguivory in the common vampire bat

Adaptation to specialized diets often requires modifications at both genomic and microbiome levels. We applied a hologenomic approach to the common vampire bat (Desmodus rotundus), one of the only three obligate blood-feeding (sanguivorous) mammals, to study the evolution of its complex dietary adaptation. Specifically, we assembled its high-quality reference genome (scaffold N50 = 26.9 Mb, contig N50 = 36.6 kb) and gut metagenome, and compared them against those of insectivorous, frugivorous and carnivorous bats. Our analyses showed a particular common vampire bat genomic landscape regarding integrated viral elements, a dietary and phylogenetic influence on gut microbiome taxonomic and functional profiles, and that both genetic elements harbour key traits related to the nutritional (for example, vitamin and lipid shortage) and non-nutritional (for example, nitrogen waste and osmotic homeostasis) challenges of sanguivory. These findings highlight the value of a holistic study of both the host and its microbiota when attempting to decipher adaptations underlying radical dietary lifestyles.

Divergent Selection of Pattern Recognition Receptors in Mammals with Different Ecological Characteristics

Pattern recognition receptors (PRRs) are specialized receptors that represent a key component of the host innate immune system. Whether molecular evolutionary history of different PRR classes have involved different genetic mechanisms underlying diverse pathogen environment in mammals, and whether distinct ecology of mammals may have imposed divergent selective pressures on the evolution of the PRRs, remained unknown. To test these hypotheses, we investigated the characterization of 20 genes belonging to four PRR classes in mammals. Evidence of positive selection was found in most (17 of 20) PRR genes examined, and most positively selected sites (84%) undergoing radical changes were found to fall in important functional regions, consistent with the co-evolutionary dynamics between the hosts and their microbial counterparts. We found different evolutionary patterns in different PRR classes, with the highest level of positive selection in C-type lectin receptor (CLR) family, suggesting that the capability of CLRs in response to a wide variety of ligands might explain their malleability to selection pressures. Tests using branch models that partitioned the data along habitat and social behavior found significant evidence of divergent selective pressures of PRRs among mammalian groups. Interestingly, species-specific evolution was detected on RIG-I-like helicase genes (RLRs) in cetaceans, suggesting that RLRs might play a critical role in the defense against widespread marine RNA viruses during their divergence and radiation into marine habitats. This study provides a comprehensive look at the evolutionary patterns and implications of mammalian PRRs, and highlights the importance of ecological influences in molecular adaptation.

Stronger selective constraint on downstream genes in the oxidative phosphorylation pathway of cetaceans

The oxidative phosphorylation (OXPHOS) pathway is an efficient way to produce energy via adenosine triphosphate (ATP), which is critical for sustaining an energy supply for cetaceans in a hypoxic environment. Several studies have shown that natural selection may shape the evolution of the genes involved in OXPHOS. However, how network architecture drives OXPHOS protein sequence evolution remains poorly explored. Here, we investigated the evolutionary patterns of genes in the OXPHOS pathway across six cetacean genomes within the framework of a functional network. Our results show a negative correlation between the strength of purifying selection and pathway position. This result indicates that downstream genes were subjected to stronger evolutionary constraints than upstream genes, which may be due to the dual function of ATP synthase in the OXPHOS pathway. Additionally, there was a positive correlation between codon usage bias and omega (ω = dN/dS) and a negative correlation with synonymous substitution rate (dS), indicating that the stronger selective constraint on genes (with less biased codon usage) along the OXPHOS pathway is attributable to an increase in the rate of synonymous substitution. Surprisingly, there was no significant correlation between protein-protein interactions and the evolutionary estimates, implying that highly connected enzymes may not always show greater evolutionary constraints. Compared with that observed for terrestrial mammals, we found that the signature of positive selection detected in five genes (ATP5J, LHPP, PPA1, UQCRC1 and UQCRQ) was cetacean-specific, reflecting the importance of OXPHOS for survival in hypoxic, aquatic environments.

Macrosystematics of eutherian mammals combining HTS data to expand taxon coverage

In the last few years high-throughput sequencing technologies have permitted significant advances in mammalian phylogenetic studies from a genomic perspective. However, these studies have been restricted to a sparse number of species with available reference genomes. Thus, several issues inside the eutherian mammals phylogeny remain unresolved. This may be due in part to limited taxon sampling, as taxonomic density is known to affect phylogenetic resolution. In this context, we present a protocol to increase taxon coverage using high-throughput sequencing data (RNA or DNA) generated for other biological studies and available in public databases. Following this procedure we addressed pending or controversial issues concerning the phylogenetic position of Dermoptera, Pholidota and Chiroptera, considering multiple and independent loci. Also for Chiroptera and Arctoidea we evaluated the relationships of the lineages that compose it. Although the maximum number of genes used is moderate (95), in some cases taxon coverage doubles that of previous related studies. Globally, all coalescent-based (STAR, MP-EST and ASTRAL) and concatenated (IQ-TREE and BEAST2) methods used for species tree reconstruction were consistent to each other and most of interrogated nodes received high statistical support.

Evolution of Digestive Enzymes and RNASE1 Provides Insights into Dietary Switch of Cetaceans

Although cetaceans (whales, porpoises, and dolphins) have multi-chambered stomachs, feeding habits of modern cetaceans have dramatically changed from herbivorous to carnivorous. However, the genetic basis underlying this dietary switch remains unexplored. Here, we present the first systematic investigation of 10 digestive enzymes genes (i.e., CYP7A1, CTRC, LIPC, LIPF, PNLIP, PGC, PRSS1, SI, SLC5A1, and TMPRSS15) of representative cetaceans, and the evolutionary trajectory of RNASE1 in cetartiodactylans. Positive selections were detected with proteinases (i.e., CTRC, PRSS1, and TMPRSS15) and lipases (i.e., CYP7A1, LIPF, and PNLIP) suggesting that cetaceans have evolved an enhanced digestion capacity for proteins and lipids, the major nutritional components of their prey (fishes and invertebrates). In addition, it was found that RNASE1 gene duplicated after the cetartiodactylan speciation and two independent gene duplication events took place in Camelidae and Ruminantia. Positive selection was detected with RNASE1 of Camelidae and Bovidae, suggesting enhanced digestive efficiency in the ruminants. Remarkably, even though the ancestors of cetaceans were terrestrial artiodactyls that are herbivorous, modern cetaceans lost the pancreatic RNASE1 copy with digestive function, which is in accordance with the dietary change from herbivorous to carnivorous. In sum, this is the first study that provides new insights into the evolutionary mechanism of dietary switch in cetaceans.

Evolutionary Genetics of Hypoxia Tolerance in Cetaceans during Diving

Hypoxia was a major challenge faced by cetaceans during the course of secondary aquatic adaptation. Although physiological traits of hypoxia tolerance in cetaceans have been well characterized, the underlying molecular mechanisms remain unknown. We investigated the sequences of 17 hypoxia-tolerance-related genes in representative cetaceans to provide a comprehensive insight into the genetic basis of hypoxia tolerance in these animals. Genes involved in carrying and transporting oxygen in the blood and muscle (hemoglobin-α and β, myoglobin), and genes involved in the regulation of vasoconstriction (endothelin-1, -2, and -3; endothelin receptor type A and B; adrenergic receptor α-1D; and arginine vasopressin) appear to have undergone adaptive evolution, evidence for positive selection on their particular sites, and radical physiochemical property changes of selected condons. Interestingly, “long-diving” cetaceans had relatively higher ω (d_N/d_S) values than “short-diving” cetaceans for the hemoglobin β gene, indicating divergent selective pressure presented in cetacean lineages with different diving abilities. Additionally, parallel positive selection or amino acid changes (ADRA1D: P50A, A53G, AVPR1B: I/V270T) among animals exposed to different hypoxia habitats reflect functional convergence or similar genetic mechanisms of hypoxia tolerance. In summary, positive selection, divergent selective pressures, and parallel evolution at the molecular level provided some new insights into the genetic adaptation of hypoxia tolerance.

'Obesity' is healthy for cetaceans? Evidence from pervasive positive selection in genes related to triacylglycerol metabolism

Cetaceans are a group of secondarily adapted marine mammals with an enigmatic history of transition from terrestrial to fully aquatic habitat and subsequent adaptive radiation in waters around the world. Numerous physiological and morphological cetacean characteristics have been acquired in response to this drastic habitat transition; for example, the thickened blubber is one of the most striking changes that increases their buoyancy, supports locomotion, and provides thermal insulation. However, the genetic basis underlying the blubber thickening in cetaceans remains poorly explored. Here, 88 candidate genes associated with triacylglycerol metabolism were investigated in representative cetaceans and other mammals to test whether the thickened blubber matched adaptive evolution of triacylglycerol metabolism-related genes. Positive selection was detected in 41 of the 88 candidate genes, and functional characterization of these genes indicated that these are involved mainly in triacylglycerol synthesis and lipolysis processes. In addition, some essential regulatory genes underwent significant positive selection in cetacean-specific lineages, whereas no selection signal was detected in the counterpart terrestrial mammals. The extensive occurrence of positive selection in triacylglycerol metabolism-related genes is suggestive of their essential role in secondary adaptation to an aquatic life, and further implying that 'obesity' might be an indicator of good health for cetaceans.

The position of tree shrews in the mammalian tree: Comparing multi-gene analyses with phylogenomic results leaves monophyly of Euarchonta doubtful

The well-accepted Euarchonta grandorder is a pruned version of Archonta nested within the Euarchontoglires (or Supraprimates) clade. At present, it includes tree shrews (Scandentia), flying lemurs (Dermoptera) and primates (Primates). Here, a phylogenomic dataset containing 1912 exons from 22 representative mammals was compiled to investigate the phylogenetic relationships within this group. Phylogenetic analyses and hypothesis testing suggested that tree shrews can be classified as a sister group to Primates or to Glires or even as a basal clade within Euarchontoglires. Further analyses of both modified and original previously published datasets found that the phylogenetic position of tree shrews is unstable. We also found that two of three exonic indels reported as synapomorphies of Euarchonta in a previous study do not unambiguously support the monophyly of such a clade. Therefore, the monophyly of both Euarchonta and Sundatheria (Dermoptera + Scandentia) are suspect. Molecular dating and divergence rate analyses suggested that the ancestor of Euarchontoglires experienced a rapid divergence, which may cause the unresolved position of tree shrews even using the whole genomic data.

GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters

Inference of multiple sequence alignments (MSAs) is a critical part of phylogenetic and comparative genomics studies. However, from the same set of sequences different MSAs are often inferred, depending on the methodologies used and the assumed parameters. Much effort has recently been devoted to improving the ability to identify unreliable alignment regions. Detecting such unreliable regions was previously shown to be important for downstream analyses relying on MSAs, such as the detection of positive selection. Here we developed GUIDANCE2, a new integrative methodology that accounts for: (i) uncertainty in the process of indel formation, (ii) uncertainty in the assumed guide tree and (iii) co-optimal solutions in the pairwise alignments, used as building blocks in progressive alignment algorithms. We compared GUIDANCE2 with seven methodologies to detect unreliable MSA regions using extensive simulations and empirical benchmarks. We show that GUIDANCE2 outperforms all previously developed methodologies. Furthermore, GUIDANCE2 also provides a set of alternative MSAs which can be useful for downstream analyses. The novel algorithm is implemented as a web-server, available at: http://guidance.tau.ac.il.

Optimization of sequence alignments according to the number of sequences vs. number of sites trade-off

Background

Comparative analysis of homologous sequences enables the understanding of evolutionary patterns at the molecular level, unraveling the functional constraints that shaped the underlying genes. Bioinformatic pipelines for comparative sequence analysis typically include procedures for (i) alignment quality assessment and (ii) control of sequence redundancy. An additional, underassessed step is the control of the amount and distribution of missing data in sequence alignments. While the number of sequences available for a given gene typically increases with time, the site-specific coverage of each alignment position remains highly variable because of differences in sequencing and annotation quality, or simply because of biological variation. For any given alignment-based analysis, the selection of sequences thus defines a trade-off between the species representation and the quantity of sites with sufficient coverage to be included in the subsequent analyses.

Results

We introduce an algorithm for the optimization of sequence alignments according to the number of sequences vs. number of sites trade-off. The algorithm uses a guide tree to compute scores for each bipartition of the alignment, allowing the recursive selection of sequence subsets with optimal combinations of sequence and site numbers. By applying our methods to two large data sets of several thousands of gene families, we show that significant site-specific coverage increases can be achieved while controlling for the species representation.

Conclusions

The algorithm introduced in this work allows the control of the distribution of missing data in any sequence alignment by removing sequences to increase the number of sites with a defined minimum coverage. We advocate that our missing data optimization procedure in an important step which should be considered in comparative analysis pipelines, together with alignment quality assessment and control of sampled diversity. An open source C++ implementation is available at http://bioweb.me/physamp.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0619-8) contains supplementary material, which is available to authorized users.

GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters

Inference of multiple sequence alignments (MSAs) is a critical part of phylogenetic and comparative genomics studies. However, from the same set of sequences different MSAs are often inferred, depending on the methodologies used and the assumed parameters. Much effort has recently been devoted to improving the ability to identify unreliable alignment regions. Detecting such unreliable regions was previously shown to be important for downstream analyses relying on MSAs, such as the detection of positive selection. Here we developed GUIDANCE2, a new integrative methodology that accounts for: (i) uncertainty in the process of indel formation, (ii) uncertainty in the assumed guide tree and (iii) co-optimal solutions in the pairwise alignments, used as building blocks in progressive alignment algorithms. We compared GUIDANCE2 with seven methodologies to detect unreliable MSA regions using extensive simulations and empirical benchmarks. We show that GUIDANCE2 outperforms all previously developed methodologies. Furthermore, GUIDANCE2 also provides a set of alternative MSAs which can be useful for downstream analyses. The novel algorithm is implemented as a web-server, available at: http://guidance.tau.ac.il.

Conservation of pro-longevity genes among mammals

Genes which confer a relative longevity advantage may be regulated at the level of transcription or translation. Alternatively, pro-longevity genes may mediate their effects at the level of protein structure-functional relationships that are beneficially optimized in long-lived species. Longevity associated genes (LAGs) may be operationally defined as genes that confer beneficial effects and are relatively more conserved among long-lived species. Global and local protein sequence alignments of over 10,000 genes across at least 30 mammalian species were examined to identify LAGs. Known LAGs, including growth hormone receptor (GHR), and breast cancer 1, early onset (BRCA1), have strong associations with maximum lifespan by our analysis. Several common categories of protein function were observed among genes ranked with the strongest associations with MLS identified by all regression models. These genes included those that function in the immune system, cell cycle regulation, and DNA damage response. We provide a ranking of genes with the strongest associations with species maximum lifespan (MLS) by several phylogenetic generalized least squares regression models, including adjustment for confounding variables such as body weight and gestation length.

Naked but not Hairless: the pitfalls of analyses of molecular adaptation based on few genome sequence comparisons

The naked mole-rat (Heterocephalus glaber) is the only rodent species that naturally lacks fur. Genome sequencing of this atypical rodent species recently shed light on a number of its morphological and physiological adaptations. More specifically, its hairless phenotype has been traced back to a single amino acid change (C397W) in the hair growth associated (HR) protein (or Hairless). By considering the available species diversity, we show that this specific position is in fact variable across mammals, including in the horse that was misleadingly reported to have the ancestral Cysteine. Moreover, by sequencing the corresponding HR exon in additional rodent species, we demonstrate that the C397W substitution is actually not a peculiarity of the naked mole-rat. Instead, this specific amino acid substitution is present in all hystricognath rodents investigated, which are all fully furred, including the naked mole-rat closest relative, the Damaraland mole-rat (Fukomys damarensis). Overall, we found no statistical correlation between amino acid changes at position 397 of the HR protein and reduced pilosity across the mammalian phylogeny. This demonstrates that this single amino acid change does not explain the naked mole-rat hairless phenotype. Our case study calls for caution before making strong claims regarding the molecular basis of phenotypic adaptation based on the screening of specific amino acid substitutions using only few model species in genome sequence comparisons. It also exposes the more general problem of the dilution of essential information in the supplementary material of genome papers thereby increasing the probability that misleading results will escape the scrutiny of editors, reviewers, and ultimately readers.

Indel reliability in indel-based phylogenetic inference

It is often assumed that it is unlikely that the same insertion or deletion (indel) event occurred at the same position in two independent evolutionary lineages, and thus, indel-based inference of phylogeny should be less subject to homoplasy compared with standard inference which is based on substitution events. Indeed, indels were successfully used to solve debated evolutionary relationships among various taxonomical groups. However, indels are never directly observed but rather inferred from the alignment and thus indel-based inference may be sensitive to alignment errors. It is hypothesized that phylogenetic reconstruction would be more accurate if it relied only on a subset of reliable indels instead of the entire indel data. Here, we developed a method to quantify the reliability of indel characters by measuring how often they appear in a set of alternative multiple sequence alignments. Our approach is based on the assumption that indels that are consistently present in most alternative alignments are more reliable compared with indels that appear only in a small subset of these alignments. Using simulated and empirical data, we studied the impact of filtering and weighting indels by their reliability scores on the accuracy of indel-based phylogenetic reconstruction. The new method is available as a web-server at http://guidance.tau.ac.il/RELINDEL/.

Phylostratigraphic bias creates spurious patterns of genome evolution

Phylostratigraphy is a method for dating the evolutionary emergence of a gene or gene family by identifying its homologs across the tree of life, typically by using BLAST searches. Applying this method to all genes in a species, or genomic phylostratigraphy, allows investigation of genome-wide patterns in new gene origination at different evolutionary times and thus has been extensively used. However, gene age estimation depends on the challenging task of detecting distant homologs via sequence similarity, which is expected to have differential accuracies for different genes. Here, we evaluate the accuracy of phylostratigraphy by realistic computer simulation with parameters estimated from genomic data, and investigate the impact of its error on findings of genome evolution. We show that 1) phylostratigraphy substantially underestimates gene age for a considerable fraction of genes, 2) the error is especially serious when the protein evolves rapidly, is short, and/or its most conserved block of sites is small, and 3) these errors create spurious nonuniform distributions of various gene properties among age groups, many of which cannot be predicted a priori. Given the high likelihood that conclusions about gene age are faulty, we advocate the use of realistic simulation to determine if observations from phylostratigraphy are explainable, at least qualitatively, by a null model of biased measurement, and in all cases, critical evaluation of results.

Monte Carlo algorithms for Brownian phylogenetic models

MOTIVATION

Brownian models have been introduced in phylogenetics for describing variation in substitution rates through time, with applications to molecular dating or to the comparative analysis of variation in substitution patterns among lineages. Thus far, however, the Monte Carlo implementations of these models have relied on crude approximations, in which the Brownian process is sampled only at the internal nodes of the phylogeny or at the midpoints along each branch, and the unknown trajectory between these sampled points is summarized by simple branchwise average substitution rates.

RESULTS

A more accurate Monte Carlo approach is introduced, explicitly sampling a fine-grained discretization of the trajectory of the (potentially multivariate) Brownian process along the phylogeny. Generic Monte Carlo resampling algorithms are proposed for updating the Brownian paths along and across branches. Specific computational strategies are developed for efficient integration of the finite-time substitution probabilities across branches induced by the Brownian trajectory. The mixing properties and the computational complexity of the resulting Markov chain Monte Carlo sampler scale reasonably with the discretization level, allowing practical applications with up to a few hundred discretization points along the entire depth of the tree. The method can be generalized to other Markovian stochastic processes, making it possible to implement a wide range of time-dependent substitution models with well-controlled computational precision.

AVAILABILITY

The program is freely available at www.phylobayes.org.

Eyes underground: regression of visual protein networks in subterranean mammals

Regressive evolution involves the degeneration of formerly useful structures in a lineage over time, and may be accompanied by the molecular decay of phenotype-specific genes. The mammalian eye has repeatedly undergone degeneration in taxa that occupy dim-light environments including subterranean habitats. Here we assess whether a decrease in the amount of light that reaches the retina is associated with increased regression of retinal genes, whether the phototransduction and visual cycle pathways degrade in a predictable pattern, and if the timing of retinal gene loss is associated with the entrance of mammalian lineages into subterranean environments. Sequence data were obtained from the publically available genomes of the Cape golden mole (Chrysochloris asiatica), naked mole-rat (Heterocephalus glaber) and star-nosed mole (Condylura cristata) for 65 genes associated with phototransduction, the visual cycle, and other retinal functions. Gene sequences were inspected for inactivating mutations and, when present, pseudogene sequences were compared to sequences from subaerial outgroup species. To test whether retinal degeneration is correlated with historical entrances into subterranean environments, estimated dates of retinal gene inactivation were compared to the fossil record and phylogenetic inferences of ancestral fossoriality. Our results show that (1) lower levels of light available to the retina correspond with an increase in the number of retinal pseudogenes, (2) retinal protein networks generally degrade in a predictable manner, although the extensive loss of cone phototransduction genes in Heterocephalus raises further questions regarding SWS1-cone monochromacy versus functional rod monochromacy in this species, and (3) inactivation dates of retinal genes usually post-date inferred entrances into subterranean habitats.

Assignment of Calibration Information to Deeper Phylogenetic Nodes is More Effective in Obtaining Precise and Accurate Divergence Time Estimates

Divergence time estimation has become an essential tool for understanding macroevolutionary events. Molecular dating aims to obtain reliable inferences, which, within a statistical framework, means jointly increasing the accuracy and precision of estimates. Bayesian dating methods exhibit the propriety of a linear relationship between uncertainty and estimated divergence dates. This relationship occurs even if the number of sites approaches infinity and places a limit on the maximum precision of node ages. However, how the placement of calibration information may affect the precision of divergence time estimates remains an open question. In this study, relying on simulated and empirical data, we investigated how the location of calibration within a phylogeny affects the accuracy and precision of time estimates. We found that calibration priors set at median and deep phylogenetic nodes were associated with higher precision values compared to analyses involving calibration at the shallowest node. The results were independent of the tree symmetry. An empirical mammalian dataset produced results that were consistent with those generated by the simulated sequences. Assigning time information to the deeper nodes of a tree is crucial to guarantee the accuracy and precision of divergence times. This finding highlights the importance of the appropriate choice of outgroups in molecular dating.