Evolutionary Analysis for Functional Divergence of the Toll-Like Receptor Gene Family and Altered Functional Constraints

The Toll-like receptor (TLR) gene family consists of type 1 transmembrane receptors, which play essential roles in both innate immunity and adaptive immune response by ligand recognition and signal transduction. Using all available vertebrate TLR protein sequences, we inferred the phylogenetic tree and then characterized critical amino acid residues for functional divergence by detecting altered functional constraints after gene duplications. We found that the extracellular domain of TLR genes showed higher functional divergence than that of the cytoplasmic domain, particularly in the region between leucine-rich repeat (LRR) 10 and LRR 15 of TLR 4. Our finding supports the concept that sequence evolution in the extracellular domain may be responsible for the broad diversity of TLR ligand-binding affinity, providing a testable hypothesis for potential targets that could be verified by further experimentation.     

Molecular Phylogeny,Evolution, and Functional Divergence of the LSD1-Like Gene Family: Inference from the Rice Genome

The identification of LSD1-like genes in parasite, green algae, moss, pine, and monocot and dicot species allowed us to trace the phylogenetic history of this gene family. Computational analysis showed that the diversification of members of this family could be dated back to the early stage of plant evolution. The evolution of plant LSD1-like genes was possibly shaped by two duplication events. These proteins, which contain three copies of the LSD1 zinc finger (zf-LSD1) domain within their entire polypeptides and play crucial roles in modulating disease defense and cell death, resulted from the second duplication. A gain of zf-LSD1 domain model was reasonable for explaining the origination of three-zf-LSD1 domain-containing proteins. The zf-LSD1 domain phylogeny showed that the middle (M) and C-terminal (C) domains originated from a common ancestor; the N-terminal (N) domain might be more ancient than the former two. The divergence of the N, M, and C domains was well before the monocot-dicot split. Coevolution analysis revealed that four intramolecular domain pairs, including the N domain and the interregion between the M and the C domains (INTER2), the M and C domain, the N- and C-terminus, and the M domain and C-terminus, possibly coevolved during the evolution of three-zf-LSD1 domain-containing proteins. The three zf-LSD1 domains are evolutionary conserved. Thus, the differences at the N- and C-terminus would be crucial for functional specificity of LSD1 genes. Strong functional constraints should work on the zf-LSD1 domains, whereas reduced functional constraint was found in the INTER2 region. Functional divergence analysis showed that three-zf-LSD1 domain-containing proteins were significantly functionally divergent from those proteins containing only one zf-LSD1 domain, a result demonstrating that shifted evolutionary rates between the two clusters were significantly different from each other. [Reviewing Editor: Dr. Joshua Plotkin]     

远缘杂交中不育基因的位置和效应的最大似然估计

提出了一种统计方法,利用标记位点的异常分离,来估计远缘杂交中不育基因位点的位置和效应,在回交群体中,用最大似然法对不育基因与标记位点之间的生组值和配子存活率进行估计。将表现连续分布的育性指标转化为百连续变异的遗传标记的分离,可以避免对育性直接观测所带来的重组值估计结果的不稳定,还可以同时估计雌雄配子的存活率。     

SpeciesRax: A Tool for Maximum Likelihood Species Tree Inference from Gene Family Trees under Duplication,Transfer, and Loss

Species tree inference from gene family trees is becoming increasingly popular because it can account for discordance between the species tree and the corresponding gene family trees. In particular, methods that can account for multiple-copy gene families exhibit potential to leverage paralogy as informative signal. At present, there does not exist any widely adopted inference method for this purpose. Here, we present SpeciesRax, the first maximum likelihood method that can infer a rooted species tree from a set of gene family trees and can account for gene duplication, loss, and transfer events. By explicitly modeling events by which gene trees can depart from the species tree, SpeciesRax leverages the phylogenetic rooting signal in gene trees. SpeciesRax infers species tree branch lengths in units of expected substitutions per site and branch support values via paralogy-aware quartets extracted from the gene family trees. Using both empirical and simulated data sets we show that SpeciesRax is at least as accurate as the best competing methods while being one order of magnitude faster on large data sets at the same time. We used SpeciesRax to infer a biologically plausible rooted phylogeny of the vertebrates comprising 188 species from 31,612 gene families in 1 h using 40 cores. SpeciesRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax and on BioConda.     

The Evolution of Codon Preferences in Drosophila: A Maximum-Likelihood Approach to Parameter Estimation and Hypothesis Testing

Synonymous codon usage in related species may differ as a result of variation in mutation biases, differences in the overall strength and efficiency of selection, and shifts in codon preference—the selective hierarchy of codons within and between amino acids. We have developed a maximum-likelihood method to employ explicit population genetic models to analyze the evolution of parameters determining codon usage. The method is applied to twofold degenerate amino acids in 50 orthologous genes from D. melanogaster and D. virilis. We find that D. virilis has significantly reduced selection on codon usage for all amino acids, but the data are incompatible with a simple model in which there is a single difference in the long-term N _e, or overall strength of selection, between the two species, indicating shifts in codon preference. The strength of selection acting on codon usage in D. melanogaster is estimated to be |N _e s|≈ 0.4 for most CT-ending twofold degenerate amino acids, but 1.7 times greater for cysteine and 1.4 times greater for AG-ending codons. In D. virilis, the strength of selection acting on codon usage for most amino acids is only half that acting in D. melanogaster but is considerably greater than half for cysteine, perhaps indicating the dual selection pressures of translational efficiency and accuracy. Selection coefficients in orthologues are highly correlated (ρ= 0.46), but a number of genes deviate significantly from this relationship. Received: 20 December 1998 / Accepted: 17 February 1999     

Fungi Evolution Revisited: Application of the Penalized Likelihood Method to a Bayesian Fungal Phylogeny Provides a New Perspective on Phylogenetic Relationships and Divergence Dates of Ascomycota Groups

The depiction of evolutionary relationships within phylum Ascomycota is still controversial because of unresolved branching orders in the radiation of major taxa. Here we generated a dataset of 166 small subunit (18S) rDNA sequences, representative of all groups of Fungi and used as input in a Bayesian phylogenetic analysis. This phylogeny suggests that Discomycetes are a basal group of filamentous Ascomycetes and probably maintain ancestor characters since their representatives are intermingled among other filamentous fungi. Also, we show that the evolutionary rate heterogeneity within Ascomycota precludes the assumption of a global molecular clock. Accordingly, we used the penalized likelihood method, and for calibration we included a 400 million-year-old Pyrenomycete fossil considering two distinct scenarios found in the literature, one with an estimated date of 1576 Myr for the plant–animal–fungus split and the other with an estimated date of 965 Myr for the animal–fungus split. Our data show that the current classification of the fossil as a Pyrenomycete is not compatible with the second scenario. Estimates under the first scenario are older than dates proposed in previous studies based on small subunit rDNA sequences but support estimates based on multiprotein analysis, suggesting that the radiation of the major Ascomycota groups occurred into the Proterozoic era. Reviewing Editor: Dr. Nicolas Galtier     

Weighted Likelihood Method for Grouped Survival Data in Case–Cohort Studies with Application to HIV Vaccine Trials

Summary Grouped failure time data arise often in HIV studies. In a recent preventive HIV vaccine efficacy trial, immune responses generated by the vaccine were measured from a case–cohort sample of vaccine recipients, who were subsequently evaluated for the study endpoint of HIV infection at prespecified follow‐up visits. Gilbert et al. (2005, Journal of Infectious Diseases 191 , 666–677) and Forthal et al. (2007, Journal of Immunology 178, 6596–6603) analyzed the association between the immune responses and HIV incidence with a Cox proportional hazards model, treating the HIV infection diagnosis time as a right‐censored random variable. The data, however, are of the form of grouped failure time data with case–cohort covariate sampling, and we propose an inverse selection probability‐weighted likelihood method for fitting the Cox model to these data. The method allows covariates to be time dependent, and uses multiple imputation to accommodate covariate data that are missing at random. We establish asymptotic properties of the proposed estimators, and present simulation results showing their good finite sample performance. We apply the method to the HIV vaccine trial data, showing that higher antibody levels are associated with a lower hazard of HIV infection.     

A General Method for Identifying Recessive Diploid-Specific Mutations in Saccharomyces Cerevisiae, Its Application to the Isolation of Mutants Blocked at Intermediate Stages of Meiotic Prophase and Characterization of a New Gene Sae2

We describe a general new approach for identifying recessive mutations that affect diploid strains of yeast Saccharomyces cerevisiae and the application of this method to the identification of mutations that confer an intermediate block in meiotic prophase chromosome metabolism. The method uses a temperature-sensitive conjugation mutation ste7-1 in combination with homothallism. The mutations of interest confer a defect in spore formation that is dependent upon a gene required for initiation of meiotic recombination and development of meiosis-specific chromosome structure (SPO11). Identified in this screen were null mutations of the DMC1 gene, nonnull mutations of RAD50 (rad50S), and mutations in three new genes designated SAE1, SAE2 and SAE3 (Sporulation in the Absence of Spo Eleven). Molecular characterization of the SAE2 gene and characterization of meiotic and mitotic phenotypes of sae2 mutants are also presented. The phenotypes conferred by a sae2 null mutation are virtually indistinguishable from those conferred by the previously identified nonnull mutations of RAD50 (rad50S). Most notably, both mutations confer only weak sensitivity to the radiomimetic agent methyl methane sulfonate (MMS) but completely block resection and turnover of meiosis-specific double-strand breaks. These observations provide further evidence that this constellation of phenotypes identifies a specific molecular function.     

The Use of Geographic Information Systems, Remote Sensing, and Suitability Modeling to Identify Conifer Restoration Sites with High Biological Potential for Anadromous Fish at the Cedar River Municipal Watershed in Western Washington, U.S.A.

We developed a methodology integrating several forms of remotely sensed data into a Geographic Information Systems (GIS) model that identifies suitable sites for riparian conifer restoration at the Cedar River Municipal Watershed in western Washington, U.S.A. The model integrates vegetative and geomorphic variables with information on the habitat preferences of anadromous fishes to identify riparian stands where conifer restoration would have the greatest biological benefit for salmon recovery. The high-resolution raster datasets used in our analysis were capable of characterizing the biophysical attributes of riparian areas at finer spatial scales than was previously possible. This model is intended to serve as a screening tool to identify candidate sites for riparian area restoration. The assessment approach described in this study can be applied not only to model salmonid habitat at the watershed scale but also to assess landscape patterns relevant to a wide range of restoration goals. This methodological framework offers several advantages over other approaches to restoration site selection and planning. First, the fine-scale spatial resolution of the GIS datasets (pixels ≤5 m) used in the model provides a more accurate representation of the habitat conditions than has been possible with coarser-scale data (pixels ≥5 m). Therefore, the accuracy of site identification is greatly improved. Second, the quantitative nature of the model exercises greater objectivity than some other landscape-scale planning approaches. This regional planning tool could be replicated in other watersheds with comparable datasets and could be applied to identify habitat restoration sites for other species or guilds of species by simply altering the model criteria to match the habitat needs of the target organisms.