Evolutionary and structural annotation of disease-associated mutations in human aminoacyl-tRNA synthetases

Background

Mutation(s) in proteins are a natural byproduct of evolution but can also cause serious diseases. Aminoacyl-tRNA synthetases (aaRSs) are indispensable components of all cellular protein translational machineries, and in humans they drive translation in both cytoplasm and mitochondria. Mutations in aaRSs have been implicated in a plethora of diseases including neurological conditions, metabolic disorders and cancer.

Results

We have developed an algorithmic approach for genome-wide analyses of sequence substitutions that combines evolutionary, structural and functional information. This pipeline enabled us to super-annotate human aaRS mutations and analyze their linkage to health disorders. Our data suggest that in some but not all cases, aaRS mutations occur in functional and structural sectors where they can manifest their pathological effects by altering enzyme activity or causing structural instability. Further, mutations appear in both solvent exposed and buried regions of aaRSs indicating that these alterations could lead to dysfunctional enzymes resulting in abnormal protein translation routines by affecting inter-molecular interactions or by disruption of non-bonded interactions. Overall, the prevalence of mutations is much higher in mitochondrial aaRSs, and the two most often mutated aaRSs are mitochondrial glutamyl-tRNA synthetase and dual localized glycyl-tRNA synthetase. Out of 63 mutations annotated in this work, only 12 (~20%) were observed in regions that could directly affect aminoacylation activity via either binding to ATP/amino-acid, tRNA or by involvement in dimerization. Mutations in structural cores or at potential biomolecular interfaces account for ~55% mutations while remaining mutations (~25%) remain structurally un-annotated.

Conclusion

This work provides a comprehensive structural framework within which most defective human aaRSs have been structurally analyzed. The methodology described here could be employed to annotate mutations in other protein families in a high-throughput manner.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1063) contains supplementary material, which is available to authorized users.     

Novel and unique domains in aminoacyl-tRNA synthetases from human fungal pathogens Aspergillus niger,Candida albicans and Cryptococcus neoformans

Background

Some species of fungi can cause serious human diseases, particularly to immuno-compromised individuals. Opportunistic fungal infections are a leading cause of mortality, and present an emerging challenge that requires development of new and effective therapeutics. Aminoacyl-tRNA synthetases (aaRSs) are indispensable components of cellular protein translation machinery and can be targeted for discovery of novel anti-fungal agents.

Results

Validation of aaRSs as potential drug targets in pathogenic microbes prompted us to investigate the genomic distribution of aaRSs within three fungi that infect humans – A. niger, C. albicans and C. neoformans. Hidden Markov Models were built for aaRSs and related proteins to search for homologues in these fungal genomes. Here, we provide a detailed and comprehensive annotation for 3 fungal genome aaRSs and their associated proteins. We delineate predicted localizations, subdomain architectures and prevalence of unusual motifs within these aaRSs. Several fungal aaRSs have unique domain appendages of unknown function e.g. A. niger AsxRS and C. neoformans TyrRS have additional domains that are absent from human homologs.

Conclusions

Detailed comparisons of fungal aaRSs with human homologs suggest key differences that could be exploited for specific drug targeting. Our cataloging and structural analyses provide a comprehensive foundation for experimentally dissecting fungal aaRSs that may enable development of new anti-fungal agents.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1069) contains supplementary material, which is available to authorized users.     

Plant protein peptidase inhibitors: an evolutionary overview based on comparative genomics

Background

Peptidases are key proteins involved in essential plant physiological processes. Although protein peptidase inhibitors are essential molecules that modulate peptidase activity, their global presence in different plant species remains still unknown. Comparative genomic analyses are powerful tools to get advanced knowledge into the presence and evolution of both, peptidases and their inhibitors across the Viridiplantae kingdom.

Results

A genomic comparative analysis of peptidase inhibitors and several groups of peptidases in representative species of different plant taxonomic groups has been performed. The results point out: i) clade-specific presence is common to many families of peptidase inhibitors, being some families present in most land plants; ii) variability is a widespread feature for peptidase inhibitory families, with abundant species-specific (or clade-specific) gene family proliferations; iii) peptidases are more conserved in different plant clades, being C1A papain and S8 subtilisin families present in all species analyzed; and iv) a moderate correlation among peptidases and their inhibitors suggests that inhibitors proliferated to control both endogenous and exogenous peptidases.

Conclusions

Comparative genomics has provided valuable insights on plant peptidase inhibitor families and could explain the evolutionary reasons that lead to the current variable repertoire of peptidase inhibitors in specific plant clades.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-812) contains supplementary material, which is available to authorized users.     

The Distribution of GYR- and YLP-Like Motifs in Drosophila Suggests a General Role in Cuticle Assembly and Other Protein-Protein Interactions

Background

Arthropod cuticle is composed predominantly of a self-assembling matrix of chitin and protein. Genes encoding structural cuticular proteins are remarkably abundant in arthropod genomes, yet there has been no systematic survey of conserved motifs across cuticular protein families.

Methodology/Principal Findings

Two short sequence motifs with conserved tyrosines were identified in Drosophila cuticular proteins that were similar to the GYR and YLP Interpro domains. These motifs were found in members of the CPR, Tweedle, CPF/CPFL, and (in Anopheles gambiae) CPLCG cuticular protein families, and the Dusky/Miniature family of cuticle-associated proteins. Tweedle proteins have a characteristic motif architecture that is shared with the Drosophila protein GCR1 and its orthologs in other species, suggesting that GCR1 is also cuticular. A resilin repeat, which has been shown to confer elasticity, matched one of the motifs; a number of other Drosophila proteins of unknown function exhibit a motif architecture similar to that of resilin. The motifs were also present in some proteins of the peritrophic matrix and the eggshell, suggesting molecular convergence among distinct extracellular matrices. More surprisingly, gene regulation, development, and proteolysis were statistically over-represented ontology terms for all non-cuticular matches in Drosophila. Searches against other arthropod genomes indicate that the motifs are taxonomically widespread.

Conclusions

This survey suggests a more general definition for GYR and YLP motifs and reveals their contribution to several types of extracellular matrix. They may define sites of protein interaction with DNA or other proteins, based on ontology analysis. These results can help guide experimental studies on the biochemistry of cuticle assembly.     

Cost-Effectiveness of a Community Pharmacist-Led Sleep Apnea Screening Program – A Markov Model

Background

Despite the high prevalence and major public health ramifications, obstructive sleep apnea syndrome (OSAS) remains underdiagnosed. In many developed countries, because community pharmacists (CP) are easily accessible, they have been developing additional clinical services that integrate the services of and collaborate with other healthcare providers (general practitioners (GPs), nurses, etc.). Alternative strategies for primary care screening programs for OSAS involving the CP are discussed.

Objective

To estimate the quality of life, costs, and cost-effectiveness of three screening strategies among patients who are at risk of having moderate to severe OSAS in primary care.

Design

Markov decision model.

Data Sources

Published data.

Target Population

Hypothetical cohort of 50-year-old male patients with symptoms highly evocative of OSAS.

Time Horizon

The 5 years after initial evaluation for OSAS.

Perspective

Societal.

Interventions

Screening strategy with CP (CP-GP collaboration), screening strategy without CP (GP alone) and no screening.

Outcomes measures

Quality of life, survival and costs for each screening strategy.

Results of base-case analysis

Under almost all modeled conditions, the involvement of CPs in OSAS screening was cost effective. The maximal incremental cost for “screening strategy with CP” was about 455€ per QALY gained.

Results of sensitivity analysis

Our results were robust but primarily sensitive to the treatment costs by continuous positive airway pressure, and the costs of untreated OSAS. The probabilistic sensitivity analysis showed that the “screening strategy with CP” was dominant in 80% of cases. It was more effective and less costly in 47% of cases, and within the cost-effective range (maximum incremental cost effectiveness ratio at €6186.67/QALY) in 33% of cases.

Conclusions

CP involvement in OSAS screening is a cost-effective strategy. This proposal is consistent with the trend in Europe and the United States to extend the practices and responsibilities of the pharmacist in primary care.     

The Evolutionary History of Protein Domains Viewed by Species Phylogeny

Background

Protein structural domains are evolutionary units whose relationships can be detected over long evolutionary distances. The evolutionary history of protein domains, including the origin of protein domains, the identification of domain loss, transfer, duplication and combination with other domains to form new proteins, and the formation of the entire protein domain repertoire, are of great interest.

Methodology/Principal Findings

A methodology is presented for providing a parsimonious domain history based on gain, loss, vertical and horizontal transfer derived from the complete genomic domain assignments of 1015 organisms across the tree of life. When mapped to species trees the evolutionary history of domains and domain combinations is revealed, and the general evolutionary trend of domain and combination is analyzed.

Conclusions/Significance

We show that this approach provides a powerful tool to study how new proteins and functions emerged and to study such processes as horizontal gene transfer among more distant species.     

Integrating protein structural dynamics and evolutionary analysis with Bio3D

Background

Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution.

Results

Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case.

Conclusions

The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0399-6) contains supplementary material, which is available to authorized users.     

A Novel Fibronectin Binding Motif in MSCRAMMs Targets F3 Modules

Background

BBK32 is a surface expressed lipoprotein and fibronectin (Fn)-binding microbial surface component recognizing adhesive matrix molecule (MSCRAMM) of Borrelia burgdorferi, the causative agent of Lyme disease. Previous studies from our group showed that BBK32 is a virulence factor in experimental Lyme disease and located the Fn-binding region to residues 21–205 of the lipoprotein.

Methodology/Principal Findings

Studies aimed at identifying interacting sites between BBK32 and Fn revealed an interaction between the MSCRAMM and the Fn F3 modules. Further analysis of this interaction showed that BBK32 can cause the aggregation of human plasma Fn in a similar concentration-dependent manner to that of anastellin, the superfibronectin (sFn) inducing agent. The resulting Fn aggregates are conformationally distinct from plasma Fn as indicated by a change in available thermolysin cleavage sites. Recombinant BBK32 and anastellin affect the structure of Fn matrices formed by cultured fibroblasts and inhibit endothelial cell proliferation similarly. Within BBK32, we have located the sFn-forming activity to a region between residues 160 and 175 which contains two sequence motifs that are also found in anastellin. Synthetic peptides mimicking these motifs induce Fn aggregation, whereas a peptide with a scrambled sequence motif was inactive, suggesting that these motifs represent the sFn-inducing sequence.

Conclusions/Significance

We conclude that BBK32 induces the formation of Fn aggregates that are indistinguishable from those formed by anastellin. The results of this study provide evidence for how bacteria can target host proteins to manipulate host cell activities.     

MOSBIE: a tool for comparison and analysis of rule-based biochemical models

Background

Mechanistic models that describe the dynamical behaviors of biochemical systems are common in computational systems biology, especially in the realm of cellular signaling. The development of families of such models, either by a single research group or by different groups working within the same area, presents significant challenges that range from identifying structural similarities and differences between models to understanding how these differences affect system dynamics.

Results

We present the development and features of an interactive model exploration system, MOSBIE, which provides utilities for identifying similarities and differences between models within a family. Models are clustered using a custom similarity metric, and a visual interface is provided that allows a researcher to interactively compare the structures of pairs of models as well as view simulation results.

Conclusions

We illustrate the usefulness of MOSBIE via two case studies in the cell signaling domain. We also present feedback provided by domain experts and discuss the benefits, as well as the limitations, of the approach.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-316) contains supplementary material, which is available to authorized users.     

A computational screen for type I polyketide synthases in metagenomics shotgun data

Background

Polyketides are a diverse group of biotechnologically important secondary metabolites that are produced by multi domain enzymes called polyketide synthases (PKS).

Methodology/Principal Findings

We have estimated frequencies of type I PKS (PKS I) – a PKS subgroup – in natural environments by using Hidden-Markov-Models of eight domains to screen predicted proteins from six metagenomic shotgun data sets. As the complex PKS I have similarities to other multi-domain enzymes (like those for the fatty acid biosynthesis) we increased the reliability and resolution of the dataset by maximum-likelihood trees. The combined information of these trees was then used to discriminate true PKS I domains from evolutionary related but functionally different ones. We were able to identify numerous novel PKS I proteins, the highest density of which was found in Minnesota farm soil with 136 proteins out of 183,536 predicted genes. We also applied the protocol to UniRef database to improve the annotation of proteins with so far unknown function and identified some new instances of horizontal gene transfer.

Conclusions/Significance

The screening approach proved powerful in identifying PKS I sequences in large sequence data sets and is applicable to many other protein families.     

A Genome-Wide Analysis of Genetic Diversity in Trypanosoma cruzi Intergenic Regions

Background

Trypanosoma cruzi is the causal agent of Chagas Disease. Recently, the genomes of representative strains from two major evolutionary lineages were sequenced, allowing the construction of a detailed genetic diversity map for this important parasite. However this map is focused on coding regions of the genome, leaving a vast space of regulatory regions uncharacterized in terms of their evolutionary conservation and/or divergence.

Methodology

Using data from the hybrid CL Brener and Sylvio X10 genomes (from the TcVI and TcI Discrete Typing Units, respectively), we identified intergenic regions that share a common evolutionary ancestry, and are present in both CL Brener haplotypes (TcII-like and TcIII-like) and in the TcI genome; as well as intergenic regions that were conserved in only two of the three genomes/haplotypes analyzed. The genetic diversity in these regions was characterized in terms of the accumulation of indels and nucleotide changes.

Principal Findings

Based on this analysis we have identified i) a core of highly conserved intergenic regions, which remained essentially unchanged in independently evolving lineages; ii) intergenic regions that show high diversity in spite of still retaining their corresponding upstream and downstream coding sequences; iii) a number of defined sequence motifs that are shared by a number of unrelated intergenic regions. A fraction of indels explains the diversification of some intergenic regions by the expansion/contraction of microsatellite-like repeats.     

Non-coding RNA gene families in the genomes of anopheline mosquitoes

Background

Only a small fraction of the mosquito species of the genus Anopheles are able to transmit malaria, one of the biggest killer diseases of poverty, which is mostly prevalent in the tropics. This diversity has genetic, yet unknown, causes. In a further attempt to contribute to the elucidation of these variances, the international “Anopheles Genomes Cluster Consortium” project (a.k.a. “16 Anopheles genomes project”) was established, aiming at a comprehensive genomic analysis of several anopheline species, most of which are malaria vectors. In the frame of the international consortium carrying out this project our team studied the genes encoding families of non-coding RNAs (ncRNAs), concentrating on four classes: microRNA (miRNA), ribosomal RNA (rRNA), small nuclear RNA (snRNA), and in particular small nucleolar RNA (snoRNA) and, finally, transfer RNA (tRNA).

Results

Our analysis was carried out using, exclusively, computational approaches, and evaluating both the primary NGS reads as well as the respective genome assemblies produced by the consortium and stored in VectorBase; moreover, the results of RNAseq surveys in cases in which these were available and meaningful were also accessed in order to obtain supplementary data, as were “pre-genomic era” sequence data stored in nucleic acid databases. The investigation included the identification and analysis, in most species studied, of ncRNA genes belonging to several families, as well as the analysis of the evolutionary relations of some of those genes in cross-comparisons to other members of the genus Anopheles.

Conclusions

Our study led to the identification of members of these gene families in the majority of twenty different anopheline taxa. A set of tools for the study of the evolution and molecular biology of important disease vectors has, thus, been obtained.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1038) contains supplementary material, which is available to authorized users.     

Genome holography: deciphering function-form motifs from gene expression data

Background

DNA chips allow simultaneous measurements of genome-wide response of thousands of genes, i.e. system level monitoring of the gene-network activity. Advanced analysis methods have been developed to extract meaningful information from the vast amount of raw gene-expression data obtained from the microarray measurements. These methods usually aimed to distinguish between groups of subjects (e.g., cancer patients vs. healthy subjects) or identifying marker genes that help to distinguish between those groups. We assumed that motifs related to the internal structure of operons and gene-networks regulation are also embedded in microarray and can be deciphered by using proper analysis.

Methodology/Principal Findings

The analysis presented here is based on investigating the gene-gene correlations. We analyze a database of gene expression of Bacillus subtilis exposed to sub-lethal levels of 37 different antibiotics. Using unsupervised analysis (dendrogram) of the matrix of normalized gene-gene correlations, we identified the operons as they form distinct clusters of genes in the sorted correlation matrix. Applying dimension-reduction algorithm (Principal Component Analysis, PCA) to the matrices of normalized correlations reveals functional motifs. The genes are placed in a reduced 3-dimensional space of the three leading PCA eigen-vectors according to their corresponding eigen-values. We found that the organization of the genes in the reduced PCA space recovers motifs of the operon internal structure, such as the order of the genes along the genome, gene separation by non-coding segments, and translational start and end regions. In addition to the intra-operon structure, it is also possible to predict inter-operon relationships, operons sharing functional regulation factors, and more. In particular, we demonstrate the above in the context of the competence and sporulation pathways.

Conclusions/Significance

We demonstrated that by analyzing gene-gene correlation from gene-expression data it is possible to identify operons and to predict unknown internal structure of operons and gene-networks regulation.     

Assessing the role of tandem repeats in shaping the genomic architecture of great apes

Background

Ancestral reconstructions of mammalian genomes have revealed that evolutionary breakpoint regions are clustered in regions that are more prone to break and reorganize. What is still unclear to evolutionary biologists is whether these regions are physically unstable due solely to sequence composition and/or genome organization, or do they represent genomic areas where the selection against breakpoints is minimal.

Methodology and Principal Findings

Here we present a comprehensive study of the distribution of tandem repeats in great apes. We analyzed the distribution of tandem repeats in relation to the localization of evolutionary breakpoint regions in the human, chimpanzee, orangutan and macaque genomes. We observed an accumulation of tandem repeats in the genomic regions implicated in chromosomal reorganizations. In the case of the human genome our analyses revealed that evolutionary breakpoint regions contained more base pairs implicated in tandem repeats compared to synteny blocks, being the AAAT motif the most frequently involved in evolutionary regions. We found that those AAAT repeats located in evolutionary regions were preferentially associated with Alu elements.

Significance

Our observations provide evidence for the role of tandem repeats in shaping mammalian genome architecture. We hypothesize that an accumulation of specific tandem repeats in evolutionary regions can promote genome instability by altering the state of the chromatin conformation or by promoting the insertion of transposable elements.     

Phylum-wide comparative genomics unravel the diversity of secondary metabolism in Cyanobacteria

Background

Cyanobacteria are an ancient lineage of photosynthetic bacteria from which hundreds of natural products have been described, including many notorious toxins but also potent natural products of interest to the pharmaceutical and biotechnological industries. Many of these compounds are the products of non-ribosomal peptide synthetase (NRPS) or polyketide synthase (PKS) pathways. However, current understanding of the diversification of these pathways is largely based on the chemical structure of the bioactive compounds, while the evolutionary forces driving their remarkable chemical diversity are poorly understood.

Results

We carried out a phylum-wide investigation of genetic diversification of the cyanobacterial NRPS and PKS pathways for the production of bioactive compounds. 452 NRPS and PKS gene clusters were identified from 89 cyanobacterial genomes, revealing a clear burst in late-branching lineages. Our genomic analysis further grouped the clusters into 286 highly diversified cluster families (CF) of pathways. Some CFs appeared vertically inherited, while others presented a more complex evolutionary history. Only a few horizontal gene transfers were evidenced amongst strongly conserved CFs in the phylum, while several others have undergone drastic gene shuffling events, which could result in the observed diversification of the pathways.

Conclusions

Therefore, in addition to toxin production, several NRPS and PKS gene clusters are devoted to important cellular processes of these bacteria such as nitrogen fixation and iron uptake. The majority of the biosynthetic clusters identified here have unknown end products, highlighting the power of genome mining for the discovery of new natural products.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-977) contains supplementary material, which is available to authorized users.     

Clinical and Biochemical Function of Polymorphic NR0B1 GGAA-Microsatellites in Ewing Sarcoma: A Report from the Children's Oncology Group

Background

The genetics involved in Ewing sarcoma susceptibility and prognosis are poorly understood. EWS/FLI and related EWS/ETS chimeras upregulate numerous gene targets via promoter-based GGAA-microsatellite response elements. These microsatellites are highly polymorphic in humans, and preliminary evidence suggests EWS/FLI-mediated gene expression is highly dependent on the number of GGAA motifs within the microsatellite.

Objectives

Here we sought to examine the polymorphic spectrum of a GGAA-microsatellite within the NR0B1 promoter (a critical EWS/FLI target) in primary Ewing sarcoma tumors, and characterize how this polymorphism influences gene expression and clinical outcomes.

Results

A complex, bimodal pattern of EWS/FLI-mediated gene expression was observed across a wide range of GGAA motifs, with maximal expression observed in constructs containing 20–26 GGAA motifs. Relative to white European and African controls, the NR0B1 GGAA-microsatellite in tumor cells demonstrated a strong bias for haplotypes containing 21–25 GGAA motifs suggesting a relationship between microsatellite function and disease susceptibility. This selection bias was not a product of microsatellite instability in tumor samples, nor was there a correlation between NR0B1 GGAA-microsatellite polymorphisms and survival outcomes.

Conclusions

These data suggest that GGAA-microsatellite polymorphisms observed in human populations modulate EWS/FLI-mediated gene expression and may influence disease susceptibility in Ewing sarcoma.     

Transfer of energy pathway genes in microbial enhanced biological phosphorus removal communities

Background

Lateral gene transfer (LGT) is an important evolutionary process in microbial evolution. In sewage treatment plants, LGT of antibiotic resistance and xenobiotic degradation-related proteins has been suggested, but the role of LGT outside these processes is unknown. Microbial communities involved in Enhanced Biological Phosphorus Removal (EBPR) have been used to treat wastewater in the last 50 years and may provide insights into adaptation to an engineered environment. We introduce two different types of analysis to identify LGT in EBPR sewage communities, based on identifying assembled sequences with more than one strong taxonomic match, and on unusual phylogenetic patterns. We applied these methods to investigate the role of LGT in six energy-related metabolic pathways.

Results

The analyses identified overlapping but non-identical sets of transferred enzymes. All of these were homologous with sequences from known mobile genetic elements, and many were also in close proximity to transposases and integrases in the EBPR data set. The taxonomic method had higher sensitivity than the phylogenetic method, identifying more potential LGTs. Both analyses identified the putative transfer of five enzymes within an Australian community, two in a Danish community, and none in a US-derived culture.

Conclusions

Our methods were able to identify sequences with unusual phylogenetic or compositional properties as candidate LGT events. The association of these candidates with known mobile elements supports the hypothesis of transfer. The results of our analysis strongly suggest that LGT has influenced the development of functionally important energy-related pathways in EBPR systems, but transfers may be unique to each community due to different operating conditions or taxonomic composition.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1752-5) contains supplementary material, which is available to authorized users.     

DiscML: an R package for estimating evolutionary rates of discrete characters using maximum likelihood

Background

The study of discrete characters is crucial for the understanding of evolutionary processes. Even though great advances have been made in the analysis of nucleotide sequences, computer programs for non-DNA discrete characters are often dedicated to specific analyses and lack flexibility. Discrete characters often have different transition rate matrices, variable rates among sites and sometimes contain unobservable states. To obtain the ability to accurately estimate a variety of discrete characters, programs with sophisticated methodologies and flexible settings are desired.

Results

DiscML performs maximum likelihood estimation for evolutionary rates of discrete characters on a provided phylogeny with the options that correct for unobservable data, rate variations, and unknown prior root probabilities from the empirical data. It gives users options to customize the instantaneous transition rate matrices, or to choose pre-determined matrices from models such as birth-and-death (BD), birth-death-and-innovation (BDI), equal rates (ER), symmetric (SYM), general time-reversible (GTR) and all rates different (ARD). Moreover, we show application examples of DiscML on gene family data and on intron presence/absence data.

Conclusion

DiscML was developed as a unified R program for estimating evolutionary rates of discrete characters with no restriction on the number of character states, and with flexibility to use different transition models. DiscML is ideal for the analyses of binary (1s/0s) patterns, multi-gene families, and multistate discrete morphological characteristics.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-320) contains supplementary material, which is available to authorized users.