Is Over-parameterization a Problem for Profile Mixture Models?

Biochemical constraints on the admissible amino acids at specific sites in proteins lead to heterogeneity of the amino acid substitution process over sites in alignments. It is well known that phylogenetic models of protein sequence evolution that do not account for site heterogeneity are prone to long-branch attraction (LBA) artifacts. Profile mixture models were developed to model heterogeneity of preferred amino acids at sites via a finite distribution of site classes each with a distinct set of equilibrium amino acid frequencies. However, it is unknown whether the large number of parameters in such models associated with the many amino acid frequency vectors can adversely affect tree topology estimates because of over-parameterization. Here, we demonstrate theoretically that for long sequences, over-parameterization does not create problems for estimation with profile mixture models. Under mild conditions, tree, amino acid frequencies, and other model parameters converge to true values as sequence length increases, even when there are large numbers of components in the frequency profile distributions. Because large sample theory does not necessarily imply good behavior for shorter alignments we explore the performance of these models with short alignments simulated with tree topologies that are prone to LBA artifacts. We find that over-parameterization is not a problem for complex profile mixture models even when there are many amino acid frequency vectors. In fact, simple models with few site classes behave poorly. Interestingly, we also found that misspecification of the amino acid frequency vectors does not lead to increased LBA artifacts as long as the estimated cumulative distribution function of the amino acid frequencies at sites adequately approximates the true one. In contrast, misspecification of the amino acid exchangeability rates can severely negatively affect parameter estimation. Finally, we explore the effects of including in the profile mixture model an additional "F-class" representing the overall frequencies of amino acids in the data set. Surprisingly, the F-class does not help parameter estimation significantly and can decrease the probability of correct tree estimation, depending on the scenario, even though it tends to improve likelihood scores.

Asymmetric dimerization in a transcription factor superfamily is promoted by allosteric interactions with DNA

Transcription factors, such as nuclear receptors achieve precise transcriptional regulation by means of a tight and reciprocal communication with DNA, where cooperativity gained by receptor dimerization is added to binding site sequence specificity to expand the range of DNA target gene sequences. To unravel the evolutionary steps in the emergence of DNA selection by steroid receptors (SRs) from monomeric to dimeric palindromic binding sites, we carried out crystallographic, biophysical and phylogenetic studies, focusing on the estrogen-related receptors (ERRs, NR3B) that represent closest relatives of SRs. Our results, showing the structure of the ERR DNA-binding domain bound to a palindromic response element (RE), unveil the molecular mechanisms of ERR dimerization which are imprinted in the protein itself with DNA acting as an allosteric driver by allowing the formation of a novel extended asymmetric dimerization region (KR-box). Phylogenetic analyses suggest that this dimerization asymmetry is an ancestral feature necessary for establishing a strong overall dimerization interface, which was progressively modified in other SRs in the course of evolution.

Independent rediploidization masks shared whole genome duplication in the sturgeon-paddlefish ancestor

Whole genome duplication (WGD) is a dramatic evolutionary event generating many new genes and which may play a role in survival through mass extinctions. Paddlefish and sturgeon are sister lineages that both show genomic evidence for ancient WGD. Until now this has been interpreted as two independent WGD events due to a preponderance of duplicate genes with independent histories. Here we show that although there is indeed a plurality of apparently independent gene duplications, these derive from a shared genome duplication event occurring well over 200 million years ago, likely close to the Permian-Triassic mass extinction period. This was followed by a prolonged process of reversion to stable diploid inheritance (rediploidization), that may have promoted survival during the Triassic-Jurassic mass extinction. We show that the sharing of this WGD is masked by the fact that paddlefish and sturgeon lineage divergence occurred before rediploidization had proceeded even half-way. Thus, for most genes the resolution to diploidy was lineage-specific. Because genes are only truly duplicated once diploid inheritance is established, the paddlefish and sturgeon genomes are thus a mosaic of shared and non-shared gene duplications resulting from a shared genome duplication event.

An excavate root for the eukaryote tree of life

Much of the higher-order phylogeny of eukaryotes is well resolved, but the root remains elusive. We assembled a dataset of 183 eukaryotic proteins of archaeal ancestry to test this root. The resulting phylogeny identifies four lineages of eukaryotes currently classified as "Excavata" branching separately at the base of the tree. Thus, Parabasalia appear as the first major branch of eukaryotes followed sequentially by Fornicata, Preaxostyla, and Discoba. All four excavate branch points receive full statistical support from analyses with commonly used evolutionary models, a protein structure partition model that we introduce here, and various controls for deep phylogeny artifacts. The absence of aerobic mitochondria in Parabasalia, Fornicata, and Preaxostyla suggests that modern eukaryotes arose under anoxic conditions, probably much earlier than expected, and without the benefit of mitochondrial respiration.

Phylogenomics and systematics of Entomobryoidea (Collembola): marker design, phylogeny and classification

Entomobryoidea has been the focus of phylogenetic studies in recent years owing to a divergence between morphological and genetic data. Recent phylogenies have converged on the sister relationship of Orchesellidae with the remaining Entomobryoidea, and on the non-monophyly of the traditional Paronellidae and Entomobryidae, but still lack resolution. Known molecular phylogenies of the superfamily differ greatly between mitogenomic and multilocus markers. For this reason, we designed universal single-copy orthologue (USCO) and ultraconserved element (UCE) marker sets specific for Entomobryoidea, based on 11 genome assemblies. Upon the newly designed 3406 USCOs and 4030 UCEs, we analysed 34 species covering all Entomobryoidea families and major subfamilies. New data for 26 species were mined from whole-genome sequencing. Phylogenetic inference confirmed the Orchesellidae as an independent family and the Entomobryinae remained the most puzzling taxon gathering scaled and unscaled lineages of both traditional Entomobryidae and Paronellidae. To accommodate Paronellides, Zhuqinia and related genera, Paronellidinae subfam. nov. is proposed within Entomobryidae. The sampled representatives of Paronellinae were recovered as the sister group of (Seirinae+Lepidocyrtinae), suggesting that reduction on the dorsal macrochaetotaxy and trunk sensillar pattern may have occurred independently within the Lepidocyrtinae and Paronellinae or represent their symplesiomorphy posteriorly modified in the Seirinae. The current systematics of the superfamily are revised here, with Entomobryidae now comprising six subfamilies, including all taxa with smooth dens. Our data also point out that all the main events of cladogenesis of the families and subfamilies of Entomobryoidea occurred during the Jurassic. Our genome-scale phylogenomics provides a complete, reliable example for systematics of Entomobryoidea, as well as other invertebrates in the big data era.

Evidence for a Putative Isoprene Reductase in Acetobacterium wieringae

Recent discoveries of isoprene-metabolizing microorganisms suggest they might play an important role in the global isoprene budget. Under anoxic conditions, isoprene can be used as an electron acceptor and is reduced to methylbutene. This study describes the proteogenomic profiling of an isoprene-reducing bacterial culture to identify organisms and genes responsible for the isoprene hydrogenation reaction. A metagenome-assembled genome (MAG) of the most abundant (89% relative abundance) lineage in the enrichment, Acetobacterium wieringae, was obtained. Comparative proteogenomics and reverse transcription-PCR (RT-PCR) identified a putative five-gene operon from the A. wieringae MAG upregulated during isoprene reduction. The operon encodes a putative oxidoreductase, three pleiotropic nickel chaperones (2 × HypA, HypB), and one 4Fe-4S ferredoxin. The oxidoreductase is proposed as the putative isoprene reductase with a binding site for NADH, flavin adenine dinucleotide (FAD), two pairs of canonical [4Fe-4S] clusters, and a putative iron-sulfur cluster site in a Cys₆-bonding environment. Well-studied Acetobacterium strains, such as A. woodii DSM 1030, A. wieringae DSM 1911, or A. malicum DSM 4132, do not encode the isoprene-regulated operon but encode, like many other bacteria, a homolog of the putative isoprene reductase (~47 to 49% amino acid sequence identity). Uncharacterized homologs of the putative isoprene reductase are observed across the Firmicutes, Spirochaetes, Tenericutes, Actinobacteria, Chloroflexi, Bacteroidetes, and Proteobacteria, suggesting the ability of biohydrogenation of unfunctionalized conjugated doubled bonds in other unsaturated hydrocarbons. IMPORTANCE Isoprene was recently shown to act as an electron acceptor for a homoacetogenic bacterium. The focus of this study is the molecular basis for isoprene reduction. By comparing a genome from our isoprene-reducing enrichment culture, dominated by Acetobacterium wieringae, with genomes of other Acetobacterium lineages that do not reduce isoprene, we shortlisted candidate genes for isoprene reduction. Using comparative proteogenomics and reverse transcription-PCR we have identified a putative five-gene operon encoding an oxidoreductase referred to as putative isoprene reductase.

The Structure of Evolutionary Model Space for Proteins across the Tree of Life

The factors that determine the relative rates of amino acid substitution during protein evolution are complex and known to vary among taxa. We estimated relative exchangeabilities for pairs of amino acids from clades spread across the tree of life and assessed the historical signal in the distances among these clade-specific models. We separately trained these models on collections of arbitrarily selected protein alignments and on ribosomal protein alignments. In both cases, we found a clear separation between the models trained using multiple sequence alignments from bacterial clades and the models trained on archaeal and eukaryotic data. We assessed the predictive power of our novel clade-specific models of sequence evolution by asking whether fit to the models could be used to identify the source of multiple sequence alignments. Model fit was generally able to correctly classify protein alignments at the level of domain (bacterial versus archaeal), but the accuracy of classification at finer scales was much lower. The only exceptions to this were the relatively high classification accuracy for two archaeal lineages: Halobacteriaceae and Thermoprotei. Genomic GC content had a modest impact on relative exchangeabilities despite having a large impact on amino acid frequencies. Relative exchangeabilities involving aromatic residues exhibited the largest differences among models. There were a small number of exchangeabilities that exhibited large differences in comparisons among major clades and between generalized models and ribosomal protein models. Taken as a whole, these results reveal that a small number of relative exchangeabilities are responsible for much of the structure of the "model space" for protein sequence evolution. The clade-specific models we generated may be useful tools for protein phylogenetics, and the structure of evolutionary model space that they revealed has implications for phylogenomic inference across the tree of life.

Evidence for existence of an apoptosis-inducing BH3-only protein, sayonara, in Drosophila

Cells need to sense stresses to initiate the execution of the dormant cell death program. Since the discovery of the first BH3-only protein Bad, BH3-only proteins have been recognized as indispensable stress sensors that induce apoptosis. BH3-only proteins have so far not been identified in Drosophila despite their importance in other organisms. Here, we identify the first Drosophila BH3-only protein and name it sayonara. Sayonara induces apoptosis in a BH3 motif-dependent manner and interacts genetically and biochemically with the BCL-2 homologous proteins, Buffy and Debcl. There is a positive feedback loop between Sayonara-mediated caspase activation and autophagy. The BH3 motif of sayonara phylogenetically appeared at the time of the ancestral gene duplication that led to the formation of Buffy and Debcl in the dipteran lineage. To our knowledge, this is the first identification of a bona fide BH3-only protein in Drosophila, thus providing a unique example of how cell death mechanisms can evolve both through time and across taxa.

Protein-chromophore interactions controlling photoisomerization in red/green cyanobacteriochromes

Photoreceptors in the phytochrome superfamily use 15,16-photoisomerization of a linear tetrapyrrole (bilin) chromophore to photoconvert between two states with distinct spectral and biochemical properties. Canonical phytochromes include master regulators of plant growth and development in which light signals trigger interconversion between a red-absorbing 15Z dark-adapted state and a metastable, far-red-absorbing 15E photoproduct state. Distantly related cyanobacteriochromes (CBCRs) carry out a diverse range of photoregulatory functions in cyanobacteria and exhibit considerable spectral diversity. One widespread CBCR subfamily typically exhibits a red-absorbing 15Z dark-adapted state similar to that of phytochrome that gives rise to a distinct green-absorbing 15E photoproduct. This red/green CBCR subfamily also includes red-inactive examples that fail to undergo photoconversion, providing an opportunity to study protein-chromophore interactions that either promote photoisomerization or block it. In this work, we identified a conserved lineage of red-inactive CBCRs. This enabled us to identify three substitutions sufficient to block photoisomerization in photoactive red/green CBCRs. The resulting red-inactive variants faithfully replicated the fluorescence and circular dichroism properties of naturally occurring examples. Converse substitutions restored photoconversion in naturally red-inactive CBCRs. This work thus identifies protein-chromophore interactions that control the fate of the excited-state population in red/green cyanobacteriochromes.

Comparing partitioned models to mixture models: Do information criteria apply?

The use of information criteria to distinguish between phylogenetic models has become ubiquitous within the field. However, the variety and complexity of available models are much greater now than when these practices were established. The literature shows an increasing trajectory of healthy skepticism with regard to the use of information theory-based model selection within phylogenetics. We add to this by analyzing the specific case of comparison between partition and mixture models. We argue from a theoretical basis that information criteria are inherently more likely to favor partition models over mixture models, and we then demonstrate this through simulation. Based on our findings, we suggest that partition and mixture models are not suitable for information-theory based model comparison. [AIC, BIC; information criteria; maximum likelihood; mixture models; partitioned model; phylogenetics.]

SEQUENCE-FREE PHYLOGENETICS WITH MASS SPECTROMETRY

An alternative, more rapid, sequence-free approach to build phylogenetic trees has been conceived and implemented. Molecular phylogenetics has continued to mostly focus on improvement in tree construction based on gene sequence alignments. Here protein-based phylogenies are constructed using numerical data sets ("phylonumerics") representing the masses of peptide segments recorded in a mass mapping experiment. This truly sequence-free method requires no gene sequences, nor their alignment, to build the trees affording a considerable time and cost-saving to conventional phylogenetics methods. The approach also calculates single point amino acid mutations from a comparison of mass pairs from different maps in the data set and displays these at branch nodes across the tree together with their frequency. Studies of the consecutive, and near-consecutive, ancestral and descendant mutations across interconnected branches of a mass tree allow putative adaptive, epistatic, and compensatory mutations to be identified in order to investigate mechanisms associated with evolutionary processes and pathways. A side-by-side comparison of this sequence-free approach and conventional gene sequence phylogenetics is discussed.

Protein Structure, Models of Sequence Evolution, and Data Type Effects in Phylogenetic Analyses of Mitochondrial Data: A Case Study in Birds

Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein-coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acid exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution matrix for transmembrane helices estimated using a variety of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

TwinCons: Conservation score for uncovering deep sequence similarity and divergence

We have developed the program TwinCons, to detect noisy signals of deep ancestry of proteins or nucleic acids. As input, the program uses a composite alignment containing pre-defined groups, and mathematically determines a 'cost' of transforming one group to the other at each position of the alignment. The output distinguishes conserved, variable and signature positions. A signature is conserved within groups but differs between groups. The method automatically detects continuous characteristic stretches (segments) within alignments. TwinCons provides a convenient representation of conserved, variable and signature positions as a single score, enabling the structural mapping and visualization of these characteristics. Structure is more conserved than sequence. TwinCons highlights alternative sequences of conserved structures. Using TwinCons, we detected highly similar segments between proteins from the translation and transcription systems. TwinCons detects conserved residues within regions of high functional importance for the ribosomal RNA (rRNA) and demonstrates that signatures are not confined to specific regions but are distributed across the rRNA structure. The ability to evaluate both nucleic acid and protein alignments allows TwinCons to be used in combined sequence and structural analysis of signatures and conservation in rRNA and in ribosomal proteins (rProteins). TwinCons detects a strong sequence conservation signal between bacterial and archaeal rProteins related by circular permutation. This conserved sequence is structurally colocalized with conserved rRNA, indicated by TwinCons scores of rRNA alignments of bacterial and archaeal groups. This combined analysis revealed deep co-evolution of rRNA and rProtein buried within the deepest branching points in the tree of life.

A Tetratricopeptide Repeat Scaffold Couples Signal Detection to OdhI Phosphorylation in Metabolic Control by the Protein Kinase PknG

Signal transduction is essential for bacteria to adapt to changing environmental conditions. Among many forms of posttranslational modifications, reversible protein phosphorylation has evolved as a ubiquitous molecular mechanism of protein regulation in response to specific stimuli. The Ser/Thr protein kinase PknG modulates the fate of intracellular glutamate by controlling the phosphorylation status of the 2-oxoglutarate dehydrogenase regulator OdhI, a function that is conserved among diverse actinobacteria. PknG has a modular organization characterized by the presence of regulatory domains surrounding the catalytic domain. Here, we present an investigation using in vivo experiments, as well as biochemical and structural methods, of the molecular basis of the regulation of PknG from Corynebacterium glutamicum (CgPknG), in the light of previous knowledge available for the kinase from Mycobacterium tuberculosis (MtbPknG). We found that OdhI phosphorylation by CgPknG is regulated by a conserved mechanism that depends on a C-terminal domain composed of tetratricopeptide repeats (TPRs) essential for metabolic homeostasis. Furthermore, we identified a conserved structural motif that physically connects the TPR domain to a β-hairpin within the flexible N-terminal region that is involved in docking interactions with OdhI. Based on our results and previous reports, we propose a model in which the TPR domain of PknG couples signal detection to the specific phosphorylation of OdhI. Overall, the available data indicate that conserved PknG domains in distant actinobacteria retain their roles in kinase regulation in response to nutrient availability.

Respiratory Heme A-Containing Oxidases Originated in the Ancestors of Iron-Oxidizing Bacteria

Respiration is a major trait shaping the biology of many environments. Cytochrome oxidase containing heme A (COX) is a common terminal oxidase in aerobic bacteria and is the only one in mammalian mitochondria. The synthesis of heme A is catalyzed by heme A synthase (CtaA/Cox15), an enzyme that most likely coevolved with COX. The evolutionary origin of COX in bacteria has remained unknown. Using extensive sequence and phylogenetic analysis, we show that the ancestral type of heme A synthases is present in iron-oxidizing Proteobacteria such as Acidithiobacillus spp. These bacteria also contain a deep branching form of the major COX subunit (COX1) and an ancestral variant of CtaG, a protein that is specifically required for COX biogenesis. Our work thus suggests that the ancestors of extant iron-oxidizers were the first to evolve COX. Consistent with this conclusion, acidophilic iron-oxidizing prokaryotes lived on emerged land around the time for which there is the earliest geochemical evidence of aerobic respiration on earth. Hence, ecological niches of iron oxidation have apparently promoted the evolution of aerobic respiration.

Scalable Empirical Mixture Models That Account for Across-Site Compositional Heterogeneity

Biochemical demands constrain the range of amino acids acceptable at specific sites resulting in across-site compositional heterogeneity of the amino acid replacement process. Phylogenetic models that disregard this heterogeneity are prone to systematic errors, which can lead to severe long-branch attraction artifacts. State-of-the-art models accounting for across-site compositional heterogeneity include the CAT model, which is computationally expensive, and empirical distribution mixture models estimated via maximum likelihood (C10–C60 models). Here, we present a new, scalable method EDCluster for finding empirical distribution mixture models involving a simple cluster analysis. The cluster analysis utilizes specific coordinate transformations which allow the detection of specialized amino acid distributions either from curated databases or from the alignment at hand. We apply EDCluster to the HOGENOM and HSSP databases in order to provide universal distribution mixture (UDM) models comprising up to 4,096 components. Detailed analyses of the UDM models demonstrate the removal of various long-branch attraction artifacts and improved performance compared with the C10–C60 models. Ready-to-use implementations of the UDM models are provided for three established software packages (IQ-TREE, Phylobayes, and RevBayes).

The Roles of Protein Structure, Taxon Sampling, and Model Complexity in Phylogenomics: A Case Study Focused on Early Animal Divergences

Despite the long history of using protein sequences to infer the tree of life, the potential for different parts of protein structures to retain historical signal remains unclear. We propose that it might be possible to improve analyses of phylogenomic datasets by incorporating information about protein structure. We test this idea using the position of the root of Metazoa (animals) as a model system. We examined the distribution of “strongly decisive” sites (alignment positions that support a specific tree topology) in a dataset comprising >1500 proteins and almost 100 taxa. The proportion of each class of strongly decisive sites in different structural environments was very sensitive to the model used to analyze the data when a limited number of taxa were used but they were stable when taxa were added. As long as enough taxa were analyzed, sites in all structural environments supported the same topology regardless of whether standard tree searches or decisive sites were used to select the optimal tree. However, the use of decisive sites revealed a difference between the support for minority topologies for sites in different structural environments: buried sites and sites in sheet and coil environments exhibited equal support for the minority topologies, whereas solvent-exposed and helix sites had unequal numbers of sites, supporting the minority topologies. This suggests that the relatively slowly evolving buried, sheet, and coil sites are giving an accurate picture of the true species tree and the amount of conflict among gene trees. Taken as a whole, this study indicates that phylogenetic analyses using sites in different structural environments can yield different topologies for the deepest branches in the animal tree of life and that analyzing larger numbers of taxa eliminates this conflict. More broadly, our results highlight the desirability of incorporating information about protein structure into phylogenomic analyses.

Crystal structure of a far-red-sensing cyanobacteriochrome reveals an atypical bilin conformation and spectral tuning mechanism

Cyanobacteriochromes (CBCRs) are small, linear tetrapyrrole (bilin)-binding photoreceptors in the phytochrome superfamily that regulate diverse light-mediated adaptive processes in cyanobacteria. More spectrally diverse than canonical red/far-red-sensing phytochromes, CBCRs were thought to be restricted to sensing visible and near UV light until recently when several subfamilies with far-red-sensing representatives (frCBCRs) were discovered. Two of these frCBCRs subfamilies have been shown to incorporate bilin precursors with larger pi-conjugated chromophores, while the third frCBCR subfamily uses the same phycocyanobilin precursor found in the bulk of the known CBCRs. To elucidate the molecular basis of far-red light perception by this third frCBCR subfamily, we determined the crystal structure of the far-red-absorbing dark state of one such frCBCR Anacy_2551g3 from Anabaena cylindrica PCC 7122 which exhibits a reversible far-red/orange photocycle. Determined by room temperature serial crystallography and cryocrystallography, the refined 2.7-Å structure reveals an unusual all-Z,syn configuration of the phycocyanobilin (PCB) chromophore that is considerably less extended than those of previously characterized red-light sensors in the phytochrome superfamily. Based on structural and spectroscopic comparisons with other bilin-binding proteins together with site-directed mutagenesis data, our studies reveal protein-chromophore interactions that are critical for the atypical bathochromic shift. Based on these analyses, we propose that far-red absorption in Anacy_2551g3 is the result of the additive effect of two distinct red-shift mechanisms involving cationic bilin lactim tautomers stabilized by a constrained all-Z,syn conformation and specific interactions with a highly conserved anionic residue.

IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

Evidence for sponges as sister to all other animals from partitioned phylogenomics with mixture models and recoding

Resolving the relationships between the major lineages in the animal tree of life is necessary to understand the origin and evolution of key animal traits. Sponges, characterized by their simple body plan, were traditionally considered the sister group of all other animal lineages, implying a gradual increase in animal complexity from unicellularity to complex multicellularity. However, the availability of genomic data has sparked tremendous controversy as some phylogenomic studies support comb jellies taking this position, requiring secondary loss or independent origins of complex traits. Here we show that incorporating site-heterogeneous mixture models and recoding into partitioned phylogenomics alleviates systematic errors that hamper commonly-applied phylogenetic models. Testing on real datasets, we show a great improvement in model-fit that attenuates branching artefacts induced by systematic error. We reanalyse key datasets and show that partitioned phylogenomics does not support comb jellies as sister to other animals at either the supermatrix or partition-specific level.

Identification and Characterization of Zebrafish Tlr4 Coreceptor Md-2

The zebrafish (Danio rerio) is a powerful model organism for studies of the innate immune system. One apparent difference between human and zebrafish innate immunity is the cellular machinery for LPS sensing. In amniotes, the protein complex formed by TLR4 and myeloid differentiation factor 2 (Tlr4/Md-2) recognizes the bacterial molecule LPS and triggers an inflammatory response. It is believed that zebrafish have neither Md-2 nor Tlr4; Md-2 has not been identified outside of amniotes, whereas the zebrafish tlr4 genes appear to be paralogs, not orthologs, of amniote TLR4s We revisited these conclusions. We identified a zebrafish gene encoding Md-2, ly96 Using single-cell RNA sequencing, we found that ly96 is transcribed in cells that also transcribe genes diagnostic for innate immune cells, including the zebrafish tlr4-like genes. In larval zebrafish, ly96 is expressed in a small number of macrophage-like cells. In a functional assay, zebrafish Md-2 and Tlr4ba form a complex that activates NF-κB signaling in response to LPS. In larval zebrafish ly96 loss-of-function mutations perturbed LPS-induced cytokine production but gave little protection against LPS toxicity. Finally, by analyzing the genomic context of tlr4 genes in 11 jawed vertebrates, we found that tlr4 arose prior to the divergence of teleosts and tetrapods. Thus, an LPS-sensitive Tlr4/Md-2 complex is likely an ancestral feature shared by mammals and zebrafish, rather than a de novo invention on the tetrapod lineage. We hypothesize that zebrafish retain an ancestral, low-sensitivity Tlr4/Md-2 complex that confers LPS responsiveness to a specific subset of innate immune cells.

QMaker: Fast and accurate method to estimate empirical models of protein evolution

Amino acid substitution models play a crucial role in phylogenetic analyses. Maximum likelihood (ML) methods have been proposed to estimate amino acid substitution models; however, they are typically complicated and slow. In this article, we propose QMaker, a new ML method to estimate a general time-reversible \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$Q$\end{document} matrix from a large protein data set consisting of multiple sequence alignments. QMaker combines an efficient ML tree search algorithm, a model selection for handling the model heterogeneity among alignments, and the consideration of rate mixture models among sites. We provide QMaker as a user-friendly function in the IQ-TREE software package (http://www.iqtree.org) supporting the use of multiple CPU cores so that biologists can easily estimate amino acid substitution models from their own protein alignments. We used QMaker to estimate new empirical general amino acid substitution models from the current Pfam database as well as five clade-specific models for mammals, birds, insects, yeasts, and plants. Our results show that the new models considerably improve the fit between model and data and in some cases influence the inference of phylogenetic tree topologies.[Amino acid replacement matrices; amino acid substitution models; maximum likelihood estimation; phylogenetic inferences.]

Evolutionary model of protein secondary structure capable of revealing new biological relationships

Ancestral sequence reconstruction has had recent success in decoding the origins and the determinants of complex protein functions. However, phylogenetic analyses of remote homologues must handle extreme amino acid sequence diversity resulting from extended periods of evolutionary change. We exploited the wealth of protein structures to develop an evolutionary model based on protein secondary structure. The approach follows the differences between discrete secondary structure states observed in modern proteins and those hypothesized in their immediate ancestors. We implemented maximum likelihood-based phylogenetic inference to reconstruct ancestral secondary structure. The predictive accuracy from the use of the evolutionary model surpasses that of comparative modeling and sequence-based prediction; the reconstruction extracts information not available from modern structures or the ancestral sequences alone. Based on a phylogenetic analysis of a sequence-diverse protein family, we showed that the model can highlight relationships that are evolutionarily rooted in structure and not evident in amino acid-based analysis.

Ancestral sequence reconstruction: accounting for structural information by averaging over replacement matrices

MOTIVATION

Ancestral sequence reconstruction (ASR) is widely used to understand protein evolution, structure and function. Current ASR methodologies do not fully consider differences in evolutionary constraints among positions imposed by the three-dimensional (3D) structure of the protein. Here, we developed an ASR algorithm that allows different protein sites to evolve according to different mixtures of replacement matrices. We show that assigning replacement matrices to protein positions based on their solvent accessibility leads to ASR with higher log-likelihoods compared to naïve models that assume a single replacement matrix for all sites. Improved ASR log-likelihoods are also demonstrated when solvent accessibility is predicted from protein sequences rather than inferred from a known 3D structure. Finally, we show that using such structure-aware mixture models results in substantial differences in the inferred ancestral sequences.

AVAILABILITY AND IMPLEMENTATION

http://fastml.tau.ac.il.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Phylogenetic tree building in the genomic age

Knowing phylogenetic relationships among species is fundamental for many studies in biology. An accurate phylogenetic tree underpins our understanding of the major transitions in evolution, such as the emergence of new body plans or metabolism, and is key to inferring the origin of new genes, detecting molecular adaptation, understanding morphological character evolution and reconstructing demographic changes in recently diverged species. Although data are ever more plentiful and powerful analysis methods are available, there remain many challenges to reliable tree building. Here, we discuss the major steps of phylogenetic analysis, including identification of orthologous genes or proteins, multiple sequence alignment, and choice of substitution models and inference methodologies. Understanding the different sources of errors and the strategies to mitigate them is essential for assembling an accurate tree of life.

Ambiguity Coding Allows Accurate Inference of Evolutionary Parameters from Alignments in an Aggregated State-Space

How can we best learn the history of a protein’s evolution? Ideally, a model of sequence evolution should capture both the process that generates genetic variation and the functional constraints determining which changes are fixed. However, in practical terms the most suitable approach may simply be the one that combines the convenience of easily available input data with the ability to return useful parameter estimates. For example, we might be interested in a measure of the strength of selection (typically obtained using a codon model) or an ancestral structure (obtained using structural modeling based on inferred amino acid sequence and side chain configuration).

But what if data in the relevant state-space are not readily available? We show that it is possible to obtain accurate estimates of the outputs of interest using an established method for handling missing data. Encoding observed characters in an alignment as ambiguous representations of characters in a larger state-space allows the application of models with the desired features to data that lack the resolution that is normally required. This strategy is viable because the evolutionary path taken through the observed space contains information about states that were likely visited in the “unseen” state-space. To illustrate this, we consider two examples with amino acid sequences as input. We show that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$$\omega$$\end{document}, a parameter describing the relative strength of selection on nonsynonymous and synonymous changes, can be estimated in an unbiased manner using an adapted version of a standard 61-state codon model. Using simulated and empirical data, we find that ancestral amino acid side chain configuration can be inferred by applying a 55-state empirical model to 20-state amino acid data. Where feasible, combining inputs from both ambiguity-coded and fully resolved data improves accuracy. Adding structural information to as few as 12.5% of the sequences in an amino acid alignment results in remarkable ancestral reconstruction performance compared to a benchmark that considers the full rotamer state information. These examples show that our methods permit the recovery of evolutionary information from sequences where it has previously been inaccessible. [Ancestral reconstruction; natural selection; protein structure; state-spaces; substitution models.]

Phylogenetic Analyses of Sites in Different Protein Structural Environments Result in Distinct Placements of the Metazoan Root

Phylogenomics, the use of large datasets to examine phylogeny, has revolutionized the study of evolutionary relationships. However, genome-scale data have not been able to resolve all relationships in the tree of life; this could reflect, at least in part, the poor-fit of the models used to analyze heterogeneous datasets. Some of the heterogeneity may reflect the different patterns of selection on proteins based on their structures. To test that hypothesis, we developed a pipeline to divide phylogenomic protein datasets into subsets based on secondary structure and relative solvent accessibility. We then tested whether amino acids in different structural environments had distinct signals for the topology of the deepest branches in the metazoan tree. We focused on a dataset that appeared to have a mixture of signals and we found that the most striking difference in phylogenetic signal reflected relative solvent accessibility. Analyses of exposed sites (residues located on the surface of proteins) yielded a tree that placed ctenophores sister to all other animals whereas sites buried inside proteins yielded a tree with a sponge+ctenophore clade. These differences in phylogenetic signal were not ameliorated when we conducted analyses using a set of maximum-likelihood profile mixture models. These models are very similar to the Bayesian CAT model, which has been used in many analyses of deep metazoan phylogeny. In contrast, analyses conducted after recoding amino acids to limit the impact of deviations from compositional stationarity increased the congruence in the estimates of phylogeny for exposed and buried sites; after recoding amino acid trees estimated using the exposed and buried site both supported placement of ctenophores sister to all other animals. Although the central conclusion of our analyses is that sites in different structural environments yield distinct trees when analyzed using models of protein evolution, our amino acid recoding analyses also have implications for metazoan evolution. Specifically, our results add to the evidence that ctenophores are the sister group of all other animals and they further suggest that the placozoa+cnidaria clade found in some other studies deserves more attention. Taken as a whole, these results provide striking evidence that it is necessary to achieve a better understanding of the constraints due to protein structure to improve phylogenetic estimation.

Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift

Inferring genome-scale metabolic networks in emerging model organisms is challenged by incomplete biochemical knowledge and partial conservation of biochemical pathways during evolution. Therefore, specific bioinformatic tools are necessary to infer biochemical reactions and metabolic structures that can be checked experimentally. Using an integrative approach combining genomic and metabolomic data in the red algal model Chondrus crispus, we show that, even metabolic pathways considered as conserved, like sterols or mycosporine-like amino acid synthesis pathways, undergo substantial turnover. This phenomenon, here formally defined as "metabolic pathway drift," is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if the underlying molecular mechanisms are changing. We present a proof of concept with a methodological approach to formalize the logical reasoning necessary to infer reactions and molecular structures, abstracting molecular transformations based on previous biochemical knowledge.

Water in Ras Superfamily Evolution

The Ras GTPase superfamily of proteins coordinates a diverse set of cellular outcomes, including cell morphology, vesicle transport, and cell proliferation. Primary amino acid sequence analysis has identified Specificity determinant positions (SDPs) that drive diversified functions specific to the Ras, Rho, Rab, and Arf subfamilies (Rojas et al. 2012, J Cell Biol 196:189-201). The inclusion of water molecules in structural and functional adaptation is likely to be a major response to the selection pressures that drive evolution, yet hydration patterns are not included in phylogenetic analysis. This article shows that conserved crystallographic water molecules coevolved with SDP residues in the differentiation of proteins within the Ras superfamily of small GTPases. The patterns of water conservation between protein subfamilies parallel those of sequence-based evolutionary trees. Thus, hydration patterns have the potential to help elucidate functional significance in the evolution of amino acid residues observed in phylogenetic analysis of homologous proteins. © 2019 Wiley Periodicals, Inc.

The Relative Importance of Modeling Site Pattern Heterogeneity Versus Partition-Wise Heterotachy in Phylogenomic Inference

Large taxa-rich genome-scale data sets are often necessary for resolving ancient phylogenetic relationships. But accurate phylogenetic inference requires that they are analyzed with realistic models that account for the heterogeneity in substitution patterns amongst the sites, genes and lineages. Two kinds of adjustments are frequently used: models that account for heterogeneity in amino acid frequencies at sites in proteins, and partitioned models that accommodate the heterogeneity in rates (branch lengths) among different proteins in different lineages (protein-wise heterotachy). Although partitioned and site-heterogeneous models are both widely used in isolation, their relative importance to the inference of correct phylogenies has not been carefully evaluated. We conducted several empirical analyses and a large set of simulations to compare the relative performances of partitioned models, site-heterogeneous models, and combined partitioned site heterogeneous models. In general, site-homogeneous models (partitioned or not) performed worse than site heterogeneous, except in simulations with extreme protein-wise heterotachy. Furthermore, simulations using empirically-derived realistic parameter settings showed a marked long-branch attraction (LBA) problem for analyses employing protein-wise partitioning even when the generating model included partitioning. This LBA problem results from a small sample bias compounded over many single protein alignments. In some cases, this problem was ameliorated by clustering similarly-evolving proteins together into larger partitions using the PartitionFinder method. Similar results were obtained under simulations with larger numbers of taxa or heterogeneity in simulating topologies over genes. For an empirical Microsporidia test data set, all but one tested site-heterogeneous models (with or without partitioning) obtain the correct Microsporidia+Fungi grouping, whereas site-homogenous models (with or without partitioning) did not. The single exception was the fully partitioned site-heterogeneous analysis that succumbed to the compounded small sample LBA bias. In general unless protein-wise heterotachy effects are extreme, it is more important to model site-heterogeneity than protein-wise heterotachy in phylogenomic analyses. Complete protein-wise partitioning should be avoided as it can lead to a serious LBA bias. In cases of extreme protein-wise heterotachy, approaches that cluster similarly-evolving proteins together and coupled with site-heterogeneous models work well for phylogenetic estimation.

NR3E receptors in cnidarians: A new family of steroid receptor relatives extends the possible mechanisms for ligand binding

Steroid hormone receptors are important regulators of development and physiology in bilaterian animals, but the role of steroid signaling in cnidarians has been contentious. Cnidarians produce steroids, including A-ring aromatic steroids with a side-chain, but these are probably made through pathways different than the one used by vertebrates to make their A-ring aromatic steroids. Here we present comparative genomic analyses indicating the presence of a previously undescribed nuclear receptor family within medusozoan cnidarians, that we propose to call NR3E. This family predates the diversification of ERR/ER/SR in bilaterians, indicating that the first NR3 evolved in the common ancestor of the placozoan and cnidarian-bilaterian with lineage-specific loss in the anthozoans, even though multiple species in this lineage have been shown to produce aromatic steroids, whose function remain unclear. We discovered serendipitously that a cytoplasmic factor within epidermal cells of transgenic Hydra vulgaris can trigger the nuclear translocation of heterologously expressed human ERα. This led us to hypothesize that aromatic steroids may also be present in the medusozoan cnidarian lineage, which includes Hydra, and may explain the translocation of human ERα. Docking experiments with paraestrol A, a cnidarian A-ring aromatic steroid, into the ligand-binding pocket of Hydra NR3E indicates that, if an aromatic steroid is indeed the true ligand, which remains to be demonstrated, it would bind to the pocket through a partially distinct mechanism from the manner in which estradiol binds to vertebrate ER.

Relative Evolutionary Rates in Proteins Are Largely Insensitive to the Substitution Model

The relative evolutionary rates at individual sites in proteins are informative measures of conservation or adaptation. Often used as evolutionarily aware conservation scores, relative rates reveal key functional or strongly selected residues. Estimating rates in a phylogenetic context requires specifying a protein substitution model, which is typically a phenomenological model trained on a large empirical data set. A strong emphasis has traditionally been placed on selecting the "best-fit" model, with the implicit understanding that suboptimal or otherwise ill-fitting models might bias inferences. However, the pervasiveness and degree of such bias has not been systematically examined. We investigated how model choice impacts site-wise relative rates in a large set of empirical protein alignments. We compared models designed for use on any general protein, models designed for specific domains of life, and the simple equal-rates Jukes Cantor-style model (JC). As expected, information theoretic measures showed overwhelming evidence that some models fit the data decidedly better than others. By contrast, estimates of site-specific evolutionary rates were impressively insensitive to the substitution model used, revealing an unexpected degree of robustness to potential model misspecification. A deeper examination of the fewer than 5% of sites for which model inferences differed in a meaningful way showed that the JC model could uniquely identify rapidly evolving sites that models with empirically derived exchangeabilities failed to detect. We conclude that relative protein rates appear robust to the applied substitution model, and any sensible model of protein evolution, regardless of its fit to the data, should produce broadly consistent evolutionary rates.

Drosophila melanogaster Models of Friedreich's Ataxia

Friedreich's ataxia (FRDA) is a rare inherited recessive disorder affecting the central and peripheral nervous systems and other extraneural organs such as the heart and pancreas. This incapacitating condition usually manifests in childhood or adolescence, exhibits an irreversible progression that confines the patient to a wheelchair, and leads to early death. FRDA is caused by a reduced level of the nuclear-encoded mitochondrial protein frataxin due to an abnormal GAA triplet repeat expansion in the first intron of the human FXN gene. FXN is evolutionarily conserved, with orthologs in essentially all eukaryotes and some prokaryotes, leading to the development of experimental models of this disease in different organisms. These FRDA models have contributed substantially to our current knowledge of frataxin function and the pathogenesis of the disease, as well as to explorations of suitable treatments. Drosophila melanogaster, an organism that is easy to manipulate genetically, has also become important in FRDA research. This review describes the substantial contribution of Drosophila to FRDA research since the characterization of the fly frataxin ortholog more than 15 years ago. Fly models have provided a comprehensive characterization of the defects associated with frataxin deficiency and have revealed genetic modifiers of disease phenotypes. In addition, these models are now being used in the search for potential therapeutic compounds for the treatment of this severe and still incurable disease.

Modeling Site Heterogeneity with Posterior Mean Site Frequency Profiles Accelerates Accurate Phylogenomic Estimation

Proteins have distinct structural and functional constraints at different sites that lead to site-specific preferences for particular amino acid residues as the sequences evolve. Heterogeneity in the amino acid substitution process between sites is not modeled by commonly used empirical amino acid exchange matrices. Such model misspecification can lead to artefacts in phylogenetic estimation such as long-branch attraction. Although sophisticated site-heterogeneous mixture models have been developed to address this problem in both Bayesian and maximum likelihood (ML) frameworks, their formidable computational time and memory usage severely limits their use in large phylogenomic analyses. Here we propose a posterior mean site frequency (PMSF) method as a rapid and efficient approximation to full empirical profile mixture models for ML analysis. The PMSF approach assigns a conditional mean amino acid frequency profile to each site calculated based on a mixture model fitted to the data using a preliminary guide tree. These PMSF profiles can then be used for in-depth tree-searching in place of the full mixture model. Compared with widely used empirical mixture models with $k$ classes, our implementation of PMSF in IQ-TREE (http://www.iqtree.org) speeds up the computation by approximately $k$/1.5-fold and requires a small fraction of the RAM. Furthermore, this speedup allows, for the first time, full nonparametric bootstrap analyses to be conducted under complex site-heterogeneous models on large concatenated data matrices. Our simulations and empirical data analyses demonstrate that PMSF can effectively ameliorate long-branch attraction artefacts. In some empirical and simulation settings PMSF provided more accurate estimates of phylogenies than the mixture models from which they derive.

Coevolution of the Toll-Like Receptor 4 Complex with Calgranulins and Lipopolysaccharide

Toll-like receptor 4 (TLR4) induces inflammation in response to both pathogen- and host-derived molecules. Lipopolysaccharide (LPS) recognition by TLR4 has been shown to occur across the amniotes, but endogenous signaling through TLR4 has not been validated outside of placental mammals. To determine whether endogenous danger signaling is also shared across amniotes, we studied the evolution of TLR4-activation by the calgranulin proteins (S100A8, S100A9, and S100A12), a clade of host molecules that potently activate TLR4 in placental mammals. We performed phylogenetic and syntenic analysis and found MRP-126—a gene in birds and reptiles—is likely orthologous to the mammalian calgranulins. We then used an ex vivo TLR4 activation assay to establish that calgranulin pro-inflammatory activity is not specific to placental mammals, but is also exhibited by representative marsupial and sauropsid species. This activity is strongly dependent on the cofactors CD14 and MD-2 for all species studied, suggesting a conserved mode of activation across the amniotes. Ortholog complementation experiments between the calgranulins, TLR4, CD14, and MD-2 revealed extensive lineage specific-coevolution and multi-way interactions between components that are necessary for the activation of NF-κB signaling by calgranulins and LPS. Our work demonstrates that calgranulin activation of TLR4 evolved at least ~320 million years ago and has been conserved in the amniote innate immune system.

Conservation of Specificity in Two Low-Specificity Proteins

Many regulatory proteins bind peptide regions of target proteins and modulate their activity. Such regulatory proteins can often interact with highly diverse target peptides. In many instances, it is not known if the peptide-binding interface discriminates targets in a biological context, or whether biological specificity is achieved exclusively through external factors such as subcellular localization. We used an evolutionary biochemical approach to distinguish these possibilities for two such low-specificity proteins: S100A5 and S100A6. We used isothermal titration calorimetry to study the binding of peptides with diverse sequence and biochemistry to human S100A5 and S100A6. These proteins bound distinct, but overlapping, sets of peptide targets. We then studied the peptide binding properties of orthologs sampled from across five amniote species. Binding specificity was conserved along all lineages, for the last 320 million years, despite the low specificity of each protein. We used ancestral sequence reconstruction to determine the binding specificity of the last common ancestor of the paralogs. The ancestor bound the entire set of peptides bound by modern S100A5 and S100A6 proteins, suggesting that paralog specificity evolved via subfunctionalization. To rule out the possibility that specificity is conserved because it is difficult to modify, we identified a single historical mutation that, when reverted in human S100A5, gave it the ability to bind an S100A6-specific peptide. These results reveal strong evolutionary constraints on peptide binding specificity. Despite being able to bind a large number of targets, the specificity of S100 peptide interfaces is likely important for the biology of these proteins.

Ferredoxin-dependent bilin reductases in eukaryotic algae: Ubiquity and diversity

Linear tetrapyrroles (bilins) are produced from heme by heme oxygenase, usually forming biliverdin IXα (BV). Fungi and bacteria use BV as chromophore for phytochrome photoreceptors. Oxygenic photosynthetic organisms use BV as a substrate for ferredoxin-dependent bilin reductases (FDBRs), enzymes that produce diverse reduced bilins used as light-harvesting pigments in phycobiliproteins and as photoactive photoreceptor chromophores. Bilin biosynthesis is essential for phototrophic growth in Chlamydomonas reinhardtii despite the absence of phytochromes or phycobiliproteins in this organism, raising the possibility that bilins are more generally required for phototrophic growth by algae. We here leverage the recent expansion in available algal transcriptomes, cyanobacterial genomes, and environmental metagenomes to analyze the distribution and diversification of FDBRs. With the possible exception of euglenids, FDBRs are present in all photosynthetic eukaryotic lineages. Phylogenetic analysis demonstrates that algal FDBRs belong to the three previously recognized FDBR lineages. Our studies provide new insights into FDBR evolution and diversification.

Improved mitochondrial amino acid substitution models for metazoan evolutionary studies

BACKGROUND

Amino acid substitution models play an essential role in inferring phylogenies from mitochondrial protein data. However, only few empirical models have been estimated from restricted mitochondrial protein data of a hundred species. The existing models are unlikely to represent appropriately the amino acid substitutions from hundred thousands metazoan mitochondrial protein sequences.

RESULTS

We selected 125,935 mitochondrial protein sequences from 34,448 species in the metazoan kingdom to estimate new amino acid substitution models targeting metazoa, vertebrates and invertebrate groups. The new models help to find significantly better likelihood phylogenies in comparison with the existing models. We noted remarkable distances from phylogenies with the existing models to the maximum likelihood phylogenies that indicate a considerable number of incorrect bipartitions in phylogenies with the existing models. Finally, we used the new models and mitochondrial protein data to certify that Testudines, Aves, and Crocodylia form one separated clade within amniotes.

CONCLUSIONS

We introduced new mitochondrial amino acid substitution models for metazoan mitochondrial proteins. The new models outperform the existing models in inferring phylogenies from metazoan mitochondrial protein data. We strongly recommend researchers to use the new models in analysing metazoan mitochondrial protein data.

The phycocyanobilin chromophore of streptophyte algal phytochromes is synthesized by HY2

Land plant phytochromes perceive red and far-red light to control growth and development, using the linear tetrapyrrole (bilin) chromophore phytochromobilin (PΦB). Phytochromes from streptophyte algae, sister species to land plants, instead use phycocyanobilin (PCB). PCB and PΦB are synthesized by different ferredoxin-dependent bilin reductases (FDBRs): PΦB is synthesized by HY2, whereas PCB is synthesized by PcyA. The pathway for PCB biosynthesis in streptophyte algae is unknown. We used phylogenetic analysis and heterologous reconstitution of bilin biosynthesis to investigate bilin biosynthesis in streptophyte algae. Phylogenetic results suggest that PcyA is present in chlorophytes and prasinophytes but absent in streptophytes. A system reconstituting bilin biosynthesis in Escherichia coli was modified to utilize HY2 from the streptophyte alga Klebsormidium flaccidum (KflaHY2). The resulting bilin was incorporated into model cyanobacterial photoreceptors and into phytochrome from the early-diverging streptophyte alga Mesostigma viride (MvirPHY1). All photoreceptors tested incorporate PCB rather than PΦB, indicating that KflaHY2 is sufficient for PCB synthesis without any other algal protein. MvirPHY1 exhibits a red-far-red photocycle similar to those seen in other streptophyte algal phytochromes. These results demonstrate that streptophyte algae use HY2 to synthesize PCB, consistent with the hypothesis that PΦB synthesis arose late in HY2 evolution.

Robustness of Reconstructed Ancestral Protein Functions to Statistical Uncertainty

Hypotheses about the functions of ancient proteins and the effects of historical mutations on them are often tested using ancestral protein reconstruction (APR)-phylogenetic inference of ancestral sequences followed by synthesis and experimental characterization. Usually, some sequence sites are ambiguously reconstructed, with two or more statistically plausible states. The extent to which the inferred functions and mutational effects are robust to uncertainty about the ancestral sequence has not been studied systematically. To address this issue, we reconstructed ancestral proteins in three domain families that have different functions, architectures, and degrees of uncertainty; we then experimentally characterized the functional robustness of these proteins when uncertainty was incorporated using several approaches, including sampling amino acid states from the posterior distribution at each site and incorporating the alternative amino acid state at every ambiguous site in the sequence into a single "worst plausible case" protein. In every case, qualitative conclusions about the ancestral proteins' functions and the effects of key historical mutations were robust to sequence uncertainty, with similar functions observed even when scores of alternate amino acids were incorporated. There was some variation in quantitative descriptors of function among plausible sequences, suggesting that experimentally characterizing robustness is particularly important when quantitative estimates of ancient biochemical parameters are desired. The worst plausible case method appears to provide an efficient strategy for characterizing the functional robustness of ancestral proteins to large amounts of sequence uncertainty. Sampling from the posterior distribution sometimes produced artifactually nonfunctional proteins for sequences reconstructed with substantial ambiguity.

Inferring Trees

Molecular evolution can reveal the relationship between sets of homologous sequences and the patterns of change that occur during their evolution. An important aspect of these studies is the inference of a phylogenetic tree, which explicitly describes evolutionary relationships between homologous sequences. This chapter provides an introduction to evolutionary trees and how to infer them from sequence data using some commonly used inferential methodology. It focuses on statistical methods for inferring trees and how to assess the confidence one should have in any resulting tree, with a particular emphasis on the underlying assumptions of the methods and how they might affect the tree estimate. There is also some discussion of the underlying algorithms used to perform tree search and recommendations regarding the performance of different algorithms. Finally, there are a few practical guidelines, including how to combine multiple software packages to improve inference, and a comparison between Bayesian and Maximum likelihood phylogenetics.

Cyanobacteriochrome Photoreceptors Lacking the Canonical Cys Residue

Cyanobacteriochromes (CBCRs) are cyanobacterial photoreceptors that sense near-ultraviolet to far-red light. Like the distantly related phytochromes, all CBCRs reported to date have a conserved Cys residue (the "canonical Cys" or "first Cys") that forms a thioether linkage to C3¹ of the linear tetrapyrrole (bilin) chromophore. Detection of ultraviolet, violet, and blue light is performed by at least three subfamilies of two-Cys CBCRs that require both the first Cys and a second Cys that forms a second covalent linkage to C10 of the bilin. In the well-characterized DXCF subfamily, the second Cys is part of a conserved Asp-Xaa-Cys-Phe motif. We here report novel CBCRs lacking the first Cys but retaining the DXCF Cys as part of a conserved Asp-Xaa-Cys-Ile-Pro (DXCIP) motif. Phylogenetic analysis demonstrates that DXCIP CBCRs are a sister to a lineage of DXCF CBCR domains from phototaxis sensors. Three such DXCIP CBCR domains (cce_4193g1, Cyan8802_2776g1, and JSC1_24240) were characterized after recombinant expression in Escherichia coli engineered to produce phycocyanobilin. All three covalently bound bilin and showed unidirectional photoconversion in response to green light. Spectra of acid-denatured proteins in the dark-adapted state do not correspond to those of known bilins. One DXCIP CBCR, cce_4193g1, exhibited very rapid dark reversion consistent with a function as a power sensor. However, Cyan8802_2776g1 exhibited slower dark reversion and would not have such a function. The full-length cce_4193 protein also possesses a DXCF CBCR GAF domain (cce_4193g2) with a covalently bound phycoviolobilin chromophore and a blue/green photocycle. Our studies indicate that CBCRs need not contain the canonical Cys residue to function as photochromic light sensors and that phototaxis proteins containing DXCIP CBCRs may potentially perceive both light quality and light intensity.

The Identification of the Closest Living Relative(s) of Tetrapods: Phylogenomic Lessons for Resolving Short Ancient Internodes

Identifying the closest living relative(s) of tetrapods is an important, yet still contested question in vertebrate phylogenetics. Three hypotheses are possible and ruling out alternatives has proven difficult even with large molecular data sets due to weak phylogenetic signal coupled nonphylogenetic noise resulting from relatively rapid speciation events that occurred a long time ago ([Formula: see text]400 Ma). Here, we revisit the identity of the closest living relative of land vertebrates from a phylogenomic perspective and include new genomic data for all extant lungfish genera. RNA-seq proves to be a great alternative to genomic sequencing, which currently is technically not feasible in lungfishes due to their huge (50-130 Gb) and repetitive genomes. We examined the most important sources of systematic error, namely long-branch attraction (LBA), compositional heterogeneity and distribution of missing data and applied different correction techniques. A multispecies coalescent approach is used to account for deep coalescence that might come from the short and deep internodes separating early sarcopterygian splits. Concatenation methods favored lungfishes as the closest living relatives of tetrapods with strong statistical support. Amino acid profile mixture models can unambiguously resolve this difficult internode thanks to their ability to avoid systematic error. We assessed the performance of different site-heterogeneous models and data partitioning and compared the ability of different strategies designed to overcome LBA, including taxon manipulation, reduction of among-lineage rate heterogeneity and removal of fast-evolving or compositionally heterogeneous positions. The identification of lungfish as sister group of tetrapods is robust regarding the effects of nonstationary composition and distribution of missing data. The multispecies coalescent method reconstructed strongly supported topologies that were congruent with concatenation, despite pervasive gene tree heterogeneity. We reject alternative topologies for early sarcopterygian relationships by increasing the signal-to-noise ratio in our alignments. The analytical pipeline outlined here combines probabilistic phylogenomic inference with methods for evaluating data quality, model adequacy, and assessing systematic error, and thus is likely to help resolve similarly difficult internodes in the tree of life. [Coalescence; coelacanth; compositional heterogeneity; gene tree; long-branch attraction; lungfish; missing data; model misspecification; phylogenomic; species tree; systematic error.].

Genome-wide analysis identifies gain and loss/change of function within the small multigenic insecticidal Albumin 1 family of Medicago truncatula

BACKGROUND

Albumin 1b peptides (A1b) are small disulfide-knotted insecticidal peptides produced by Fabaceae (also called Leguminosae). To date, their diversity among this plant family has been essentially investigated through biochemical and PCR-based approaches. The availability of high-quality genomic resources for several fabaceae species, among which the model species Medicago truncatula (Mtr), allowed for a genomic analysis of this protein family aimed at i) deciphering the evolutionary history of A1b proteins and their links with A1b-nodulins that are short non-insecticidal disulfide-bonded peptides involved in root nodule signaling and ii) exploring the functional diversity of A1b for novel bioactive molecules.

RESULTS

Investigating the Mtr genome revealed a remarkable expansion, mainly through tandem duplications, of albumin1 (A1) genes, retaining nearly all of the same canonical structure at both gene and protein levels. Phylogenetic analysis revealed that the ancestral molecule was most probably insecticidal giving rise to, among others, A1b-nodulins. Expression meta-analysis revealed that many A1b coding genes are silent and a wide tissue distribution of the A1 transcripts/peptides within plant organs. Evolutionary rate analyses highlighted branches and sites with positive selection signatures, including two sites shown to be critical for insecticidal activity. Seven peptides were chemically synthesized and folded in vitro, then assayed for their biological activity. Among these, AG41 (aka MtrA1013 isoform, encoded by the orphan TA24778 contig.), showed an unexpectedly high insecticidal activity. The study highlights the unique burst of diversity of A1 peptides within the Medicago genus compared to the other taxa for which full-genomes are available: no A1 member in Lotus, or in red clover to date, while only a few are present in chick pea, soybean or pigeon pea genomes.

CONCLUSION

The expansion of the A1 family in the Medicago genus is reminiscent of the situation described for another disulfide-rich peptide family, the "Nodule-specific Cysteine-Rich" (NCR), discovered within the same species. The oldest insecticidal A1b toxin was described from the Sophorae, dating the birth of this seed-defense function to more than 58 million years, and making this model of plant/insect toxin/receptor (A1b/insect v-ATPase) one of the oldest known.