Using phylogeny to improve genome-wide distant homology recognition.
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ABSTRACT:
SUBMITTER: Abeln S
PROVIDER: S-EPMC1779300 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:MotivationThe success of genome sequencing techniques has resulted in rapid explosion of protein sequences. Collections of multiple homologous sequences can provide critical information to the modeling of structure and function of unknown proteins. There are however no standard and efficient pipeline available for sensitive multiple sequence alignment (MSA) collection. This is particularly challenging when large whole-genome and metagenome databases are involved.ResultsWe developed DeepMSA, a new open-source method for sensitive MSA construction, which has homologous sequences and alignments created from multi-sources of whole-genome and metagenome databases through complementary hidden Markov model algorithms. The practical usefulness of the pipeline was examined in three large-scale benchmark experiments based on 614 non-redundant proteins. First, DeepMSA was utilized to generate MSAs for residue-level contact prediction by six coevolution and deep learning-based programs, which resulted in an accuracy increase in long-range contacts by up to 24.4% compared to the default programs. Next, multiple threading programs are performed for homologous structure identification, where the average TM-score of the template alignments has over 7.5% increases with the use of the new DeepMSA profiles. Finally, DeepMSA was used for secondary structure prediction and resulted in statistically significant improvements in the Q3 accuracy. It is noted that all these improvements were achieved without re-training the parameters and neural-network models, demonstrating the robustness and general usefulness of the DeepMSA in protein structural bioinformatics applications, especially for targets without homologous templates in the PDB library.Availability and implementationhttps://zhanglab.ccmb.med.umich.edu/DeepMSA/.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC7141871 | biostudies-literature
Project description:BackgroundThe explosion in availability of whole genome data provides the opportunity to build phylogenetic hypotheses based on these data as well as the ability to learn more about the genomes themselves. The biological history of genes and genomes can be investigated based on the taxomonic history provided by the phylogeny. A phylogenetic hypothesis based on complete genome data is presented for the genus Shewanella (Gammaproteobacteria: Alteromonadales: Shewanellaceae). Nineteen taxa from Shewanella (16 species and 3 additional strains of one species) as well as three outgroup species representing the genera Aeromonas (Gammaproteobacteria: Aeromonadales: Aeromonadaceae), Alteromonas (Gammaproteobacteria: Alteromonadales: Alteromonadaceae) and Colwellia (Gammaproteobacteria: Alteromonadales: Colwelliaceae) are included for a total of 22 taxa.ResultsPutatively homologous regions were found across unannotated genomes and tested with a phylogenetic analysis. Two genome-wide data-sets are considered, one including only those genomic regions for which all taxa are represented, which included 3,361,015 aligned nucleotide base-pairs (bp) and a second that additionally includes those regions present in only subsets of taxa, which totaled 12,456,624 aligned bp. Alignment columns in these large data-sets were then randomly sampled to create smaller data-sets. After the phylogenetic hypothesis was generated, genome annotations were projected onto the DNA sequence alignment to compare the historical hypothesis generated by the phylogeny with the functional hypothesis posited by annotation.ConclusionsIndividual phylogenetic analyses of the 243 locally co-linear genome regions all failed to recover the genome topology, but the smaller data-sets that were random samplings of the large concatenated alignments all produced the genome topology. It is shown that there is not a single orthologous copy of 16S rRNA across the taxon sampling included in this study and that the relationships among the multiple copies are consistent with 16S rRNA undergoing concerted evolution. Unannotated whole genome data can provide excellent raw material for generating hypotheses of historical homology, which can be tested with phylogenetic analysis and compared with hypotheses of gene function.
| S-EPMC3107185 | biostudies-literature
Project description:Meta-BASIC (http://basic.bioinfo.pl) is a novel sensitive approach for recognition of distant similarity between proteins based on consensus alignments of meta profiles. Specifically, Meta-BASIC compares sequence profiles combined with predicted secondary structure by utilizing several scoring systems and alignment algorithms. In our benchmarking tests, Meta-BASIC outperforms many individual servers, including fold recognition servers, and it can compete with meta predictors that base their strength on the structural comparison of models. In addition, Meta-BASIC, which enables detection of very distant relationships even if the tertiary structure for the reference protein is not known, has a high-throughput capability. This new method is applied to 860 PfamA protein families with unknown function (DUF) and provides many novel structure-functional assignments available on-line at http://basic.bioinfo.pl/duf.pl. Detailed discussion is provided for two of the most interesting assignments. DUF271 and DUF431 are predicted to be a nucleotide-diphospho-sugar transferase and an alpha/beta-knot SAM-dependent RNA methyltransferase, respectively.
| S-EPMC441508 | biostudies-literature
Project description:The LOMETS2 server (https://zhanglab.ccmb.med.umich.edu/LOMETS/) is an online meta-threading server system for template-based protein structure prediction. Although the server has been widely used by the community over the last decade, the previous LOMETS server no longer represents the state-of-the-art due to aging of the algorithms and unsatisfactory performance on distant-homology template identification. An extension of the server built on cutting-edge methods, especially techniques developed since the recent CASP experiments, is urgently needed. In this work, we report the recent advancements of the LOMETS2 server, which comprise a number of major new developments, including (i) new state-of-the-art threading programs, including contact-map-based threading approaches, (ii) deep sequence search-based sequence profile construction and (iii) a new web interface design that incorporates structure-based function annotations. Large-scale benchmark tests demonstrated that the integration of the deep profiles and new threading approaches into LOMETS2 significantly improve its structure modeling quality and template detection, where LOMETS2 detected 176% more templates with TM-scores >0.5 than the previous LOMETS server for Hard targets that lacked homologous templates. Meanwhile, the newly incorporated structure-based function prediction helps extend the usefulness of the online server to the broader biological community.
| S-EPMC6602514 | biostudies-literature
Project description:We present the first genome-wide molecular phylogeny of jumping spiders (Araneae: Salticidae), inferred from Anchored Hybrid Enrichment (AHE) sequence data. From 12 outgroups plus 34 salticid taxa representing all but one subfamily and most major groups recognized in previous work, we obtained 447 loci totalling 96,946 aligned nucleotide sites. Our analyses using concatenated likelihood, parsimony, and coalescent methods (ASTRAL and SVDQuartets) strongly confirm most previous results, resolving as monophyletic the Spartaeinae, Salticinae (with the hisponines sister), Salticoida, Amycoida, Saltafresia, and Simonida. The agoriines, previously difficult to place beyond subfamily, are finally placed confidently within the saltafresians as relatives of the chrysillines and hasariines. Relationships among the baviines, astioids, marpissoids, and saltafresians remain uncertain, though our analyses tentatively conclude the first three form a clade together. Deep relationships, among the seven subfamilies, appear to be largely resolved, with spartaeines, lyssomanines, and asemoneines forming a clade. In most analyses, Onomastus (representing the onomastines) is strongly supported as sister to the hisponines plus salticines. Overall, the much-improved resolution of many deep relationships despite a relatively sparse taxon sample suggests AHE is a promising technique for salticid phylogenetics.
| S-EPMC5673835 | biostudies-literature
Project description:BackgroundPhylogenetic hypotheses based on complete genome data are presented for the Gammaproteobacteria family Vibrionaceae. Two taxon samplings are presented: one including all those taxa for which the genome sequences are complete in terms of arrangement (chromosomal location of fragments; 19 taxa) and one for which the genome sequences contain multiple contigs (44 taxa). Analyses are presented under the Maximum Parsimony and Maximum Likelihood optimality criteria for total evidence datasets, the two chromosomes separately, and individual analyses of locally collinear blocks. Three of the genomes included in the 44 taxon dataset, those of Vibrio gazogenes, Salinivibrio costicola, and Aliivibrio logei have been newly sequenced and their genome sequences are documented here.ResultsPhylogenetic results for the 19-taxon datasets show similar levels of collinear subset of dataset incongruence as a previous study of 22 taxa from the sister family Shewanellaceae, while also echoing the strong phylogenetic performance of random subsets of data also shown in this study. Phylogenetic results for both the 19-taxon and 44-taxon datasets corroborate previous hypotheses about the placement of Photobacterium and Aliivibrio within Vibrionaceae and also highlight problems with how Photobacterium is delimited and indicate that it likely should be dissolved into Vibrio to produce a phylogenetic taxonomy. The 19-taxon and 44-taxon trees based on the large chromosome are congruent for the majority of taxa that are present in both datasets. Analyses of the 44-taxon sampling based on the second, small chromosome are quite different from those based on the large chromosome, which is not surprising given the dramatically divergent nature of the small chromosome and the difficulty in postulating primary homologies.ConclusionsThe phylogenetic analyses presented here represent the most comprehensive genome-level phylogenetic analyses in terms of taxa and data. Based on the availability of genome data for many bacterial species on GenBank, many other bacterial groups would also be amenable to similar genome-scale phylogenetic analyses even when present in multiple contigs. The result that collinear subsets of data are incongruent with the concatenated dataset and with each other while random data subsets show very little incongruence echoes the result of previous work on Shewanellaceae. The 44-taxon phylogenetic analysis presented here thus represents the future of phylogenomic analyses in scope and complexity.
| S-EPMC3663674 | biostudies-literature
Project description:Background/aimsGenome-wide association (GWA) studies have reported susceptible regions in the human genome for many common diseases and traits; however, these loci only explain a minority of trait heritability. To boost the power of a GWA study, substantial research endeavors have been focused on integrating other available genomic information in the analysis. Advances in high through-put technologies have generated a wealth of genomic data and made combining SNP and gene expression data become feasible.ResultsIn this paper, we propose a novel procedure to incorporate gene expression information into GWA analysis. This procedure utilizes weights constructed by gene expression measurements to adjust p values from a GWA analysis. RESULTS from simulation analyses indicate that the proposed procedures may achieve substantial power gains, while controlling family-wise type I error rates at the nominal level. To demonstrate the implementation of our proposed approach, we apply the weight adjustment procedure to a GWA study on serum interferon-regulated chemokine levels in systemic lupus erythematosus patients. The study results can provide valuable insights for the functional interpretation of GWA signals.AvailabilityThe R source code for implementing the proposed weighting procedure is available at http://www.biostat.umn.edu/∼yho/research.html.
| S-EPMC4152945 | biostudies-literature
Project description:Cell fate determination depends in part on the establishment of specific transcriptional programs of gene expression. These programs result from the interpretation of the genomic cis-regulatory information by sequence-specific factors. Decoding this information in sequenced genomes is an important issue. Here, we developed statistical analysis tools to computationally identify the cis-regulatory elements that control gene expression in a set of coregulated genes. Starting with a small number of validated and/or predicted cis-regulatory modules (CRMs) in a reference species as a training set, but with no a priori knowledge of the factors acting in trans, we computationally predicted transcription factor binding sites (TFBSs) and genomic CRMs underlying coregulation. This method was applied to the gene expression program active in Drosophila melanogaster sensory organ precursor cells (SOPs), a specific type of neural progenitor cells. Mutational analysis showed that four, including one newly characterized, out of the five top-ranked families of predicted TFBSs were required for SOP-specific gene expression. Additionaly, 19 out of the 29 top-ranked predicted CRMs directed gene expression in neural progenitor cells, i.e., SOPs or larval brain neuroblasts, with a notable fraction active in SOPs (11/29). We further identified the lola gene as the target of two SOP-specific CRMs and found that the lola gene contributed to SOP specification. The statistics and phylogeny-based tools described here can be more generally applied to identify the cis-regulatory elements of specific gene regulatory networks in any family of related species with sequenced genomes.
| S-EPMC2930411 | biostudies-literature
Project description:The evolutionary history of all life forms is usually represented as a vertical tree-like process. In prokaryotes, however, the vertical signal is partly obscured by the massive influence of horizontal gene transfer (HGT). The HGT creates widespread discordance between evolutionary histories of different genes as genomes become mosaics of gene histories. Thus, the Tree of Life (TOL) has been questioned as an appropriate representation of the evolution of prokaryotes. Nevertheless a common hypothesis is that prokaryotic evolution is primarily tree-like, and a routine effort is made to place new isolates in their appropriate location in the TOL. Moreover, it appears desirable to exploit non-tree-like evolutionary processes for the task of microbial classification. In this work, we present a novel technique that builds on the straightforward observation that gene order conservation ('synteny') decreases in time as a result of gene mobility. This is particularly true in prokaryotes, mainly due to HGT. Using a 'synteny index' (SI) that measures the average synteny between a pair of genomes, we developed the phylogenetic reconstruction tool 'Phylo SI'. Phylo SI offers several attractive properties such as easy bootstrapping, high sensitivity in cases where phylogenetic signal is weak and computational efficiency. Phylo SI was tested both on simulated data and on two bacterial data sets and compared with two well-established phylogenetic methods. Phylo SI is particularly efficient on short evolutionary distances where synteny footprints remain detectable, whereas the nucleotide substitution signal is too weak for reliable sequence-based phylogenetic reconstruction. The method is publicly available at http://research.haifa.ac.il/ssagi/software/PhyloSI.zip.
| S-EPMC3936750 | biostudies-literature
Project description:In the post-genomic era where sequences are being determined at a rapid rate, we are highly reliant on computational methods for their tentative biochemical characterization. The Pfam database currently contains 3,786 families corresponding to "Domains of Unknown Function" (DUF) or "Uncharacterized Protein Family" (UPF), of which 3,087 families have no reported three-dimensional structure, constituting almost one-fourth of the known protein families in search for both structure and function.We applied a 'computational structural genomics' approach using five state-of-the-art remote similarity detection methods to detect the relationship between uncharacterized DUFs and domain families of known structures. The association with a structural domain family could serve as a start point in elucidating the function of a DUF. Amongst these five methods, searches in SCOP-NrichD database have been applied for the first time. Predictions were classified into high, medium and low- confidence based on the consensus of results from various approaches and also annotated with enzyme and Gene ontology terms. 614 uncharacterized DUFs could be associated with a known structural domain, of which high confidence predictions, involving at least four methods, were made for 54 families. These structure-function relationships for the 614 DUF families can be accessed on-line at http://proline.biochem.iisc.ernet.in/RHD_DUFS/ . For potential enzymes in this set, we assessed their compatibility with the associated fold and performed detailed structural and functional annotation by examining alignments and extent of conservation of functional residues. Detailed discussion is provided for interesting assignments for DUF3050, DUF1636, DUF1572, DUF2092 and DUF659.This study provides insights into the structure and potential function for nearly 20 % of the DUFs. Use of different computational approaches enables us to reliably recognize distant relationships, especially when they converge to a common assignment because the methods are often complementary. We observe that while pointers to the structural domain can offer the right clues to the function of a protein, recognition of its precise functional role is still 'non-trivial' with many DUF domains conserving only some of the critical residues. It is not clear whether these are functional vestiges or instances involving alternate substrates and interacting partners.
| S-EPMC4520260 | biostudies-literature