Ortholog identification in the presence of domain architecture rearrangement.
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ABSTRACT:
SUBMITTER: Sjolander K
PROVIDER: S-EPMC3178056 | biostudies-literature | 2011 Sep
REPOSITORIES: biostudies-literature
Publications
Ortholog identification in the presence of domain architecture rearrangement.
Sjölander Kimmen K Datta Ruchira S RS Shen Yaoqing Y Shoffner Grant M GM
Briefings in bioinformatics 20110628 5
Ortholog identification is used in gene functional annotation, species phylogeny estimation, phylogenetic profile construction and many other analyses. Bioinformatics methods for ortholog identification are commonly based on pairwise protein sequence comparisons between whole genomes. Phylogenetic methods of ortholog identification have also been developed; these methods can be applied to protein data sets sharing a common domain architecture or which share a single functional domain but differ ...[more]
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Project description:BackgroundOrtholog assignment is a critical and fundamental problem in comparative genomics, since orthologs are considered to be functional counterparts in different species and can be used to infer molecular functions of one species from those of other species. MSOAR is a recently developed high-throughput system for assigning one-to-one orthologs between closely related species on a genome scale. It attempts to reconstruct the evolutionary history of input genomes in terms of genome rearrangement and gene duplication events. It assumes that a gene duplication event inserts a duplicated gene into the genome of interest at a random location (i.e., the random duplication model). However, in practice, biologists believe that genes are often duplicated by tandem duplications, where a duplicated gene is located next to the original copy (i.e., the tandem duplication model).ResultsIn this paper, we develop MSOAR 2.0, an improved system for one-to-one ortholog assignment. For a pair of input genomes, the system first focuses on the tandemly duplicated genes of each genome and tries to identify among them those that were duplicated after the speciation (i.e., the so-called inparalogs), using a simple phylogenetic tree reconciliation method. For each such set of tandemly duplicated inparalogs, all but one gene will be deleted from the concerned genome (because they cannot possibly appear in any one-to-one ortholog pairs), and MSOAR is invoked. Using both simulated and real data experiments, we show that MSOAR 2.0 is able to achieve a better sensitivity and specificity than MSOAR. In comparison with the well-known genome-scale ortholog assignment tool InParanoid, Ensembl ortholog database, and the orthology information extracted from the well-known whole-genome multiple alignment program MultiZ, MSOAR 2.0 shows the highest sensitivity. Although the specificity of MSOAR 2.0 is slightly worse than that of InParanoid in the real data experiments, it is actually better than that of InParanoid in the simulation tests.ConclusionsOur preliminary experimental results demonstrate that MSOAR 2.0 is a highly accurate tool for one-to-one ortholog assignment between closely related genomes. The software is available to the public for free and included as online supplementary material.
| S-EPMC2821317 | biostudies-literature
Project description:WAPL, cohesin's DNA release factor, regulates three-dimensional (3D) chromatin architecture. The 3D chromatin structure and its relevance to mature T cell functions is not well understood. We show that in vivo lymphopenic expansion, and alloantigen-driven proliferation, alters the 3D structure and function of the genome in mature T cells. Conditional deletion of WAPL, cohesin's DNA release factor, in T cells reduced long-range genomic interactions and altered chromatin A/B compartments and interactions within topologically associating domains (TADs) of the chromatin in T cells at baseline. WAPL deficiency in T cells reduced loop extensions, changed expression of cell cycling genes and reduced proliferation following in vitro and in vivo stimulation, and reduced severity of graft-versus-host disease (GVHD) following experimental allogeneic hematopoietic stem cell transplantation. These data collectively characterize 3D genomic architecture of T cells in vivo and demonstrate biological and clinical implications for its disruption by cohesin release factor WAPL.
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Project description:BACKGROUND: Identification of ortholog groups is a crucial step in comparative analysis of multiple genomes. Although several computational methods have been developed to create ortholog groups, most of those methods do not evaluate orthology at the sub-gene level. In our method for domain-level ortholog clustering, DomClust, proteins are split into domains on the basis of alignment boundaries identified by all-against-all pairwise comparison, but it often fails to determine appropriate boundaries. RESULTS: We developed a method to improve domain-level ortholog classification using multiple alignment information. This method is based on a scoring scheme, the domain-specific sum-of-pairs (DSP) score, which evaluates ortholog clustering results at the domain level as the sum total of domain-level alignment scores. We developed a refinement pipeline to improve domain-level clustering, DomRefine, by optimizing the DSP score. We applied DomRefine to domain-level ortholog groups created by DomClust using a dataset obtained from the Microbial Genome Database for Comparative Analysis (MBGD), and evaluated the results using COG clusters and TIGRFAMs models as the reference data. Thus, we observed that the agreement between the resulting classification and the classifications in the reference databases is improved at almost every step in the refinement pipeline. Moreover, the refined classification showed better agreement than the classifications in the eggNOG databases when TIGRFAMs was used as the reference database. CONCLUSIONS: DomRefine is a useful tool for improving the quality of domain-level ortholog classification among microbial genomes. Combining with a rapid domain-level ortholog clustering method, such as DomClust, it can be used to create a high-quality ortholog database that can serve as a solid basis for various comparative genome analyses.
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Project description:The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of "recent" paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome.
| S-EPMC403725 | biostudies-literature
Project description:In bacteria, the highly conserved RsmA/CsrA family of RNA-binding proteins functions as global posttranscriptional regulators acting on mRNA translation and stability. Through phenotypic complementation of an rsmA mutant in Pseudomonas aeruginosa, we discovered a family member, termed RsmN. Elucidation of the RsmN crystal structure and that of the complex with a hairpin from the sRNA, RsmZ, reveals a uniquely inserted α helix, which redirects the polypeptide chain to form a distinctly different protein fold to the domain-swapped dimeric structure of RsmA homologs. The overall β sheet structure required for RNA recognition is, however, preserved with compensatory sequence and structure differences, allowing the RsmN dimer to target binding motifs in both structured hairpin loops and flexible disordered RNAs. Phylogenetic analysis indicates that, although RsmN appears unique to P. aeruginosa, homologous proteins with the inserted α helix are more widespread and arose as a consequence of a gene duplication event.
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Project description:BACKGROUND: Orthologs are genes derived from the same ancestor gene loci after speciation events. Orthologous proteins usually have similar sequences and perform comparable biological functions. Therefore, ortholog identification is useful in annotations of newly sequenced genomes. With rapidly increasing number of sequenced genomes, constructing or updating ortholog relationship between all genomes requires lots of effort and computation time. In addition, elucidating ortholog relationships between distantly related genomes is challenging because of the lower sequence similarity. Therefore, an efficient ortholog detection method that can deal with large number of distantly related genomes is desired. RESULTS: An efficient ortholog detection pipeline DODO (DOmain based Detection of Orthologs) is created on the basis of domain architectures in this study. Supported by domain composition, which usually directly related with protein function, DODO could facilitate orthologs detection across distantly related genomes. DODO works in two main steps. Starting from domain information, it first assigns protein groups according to their domain architectures and further identifies orthologs within those groups with much reduced complexity. Here DODO is shown to detect orthologs between two genomes in considerably shorter period of time than traditional methods of reciprocal best hits and it is more significant when analyzed a large number of genomes. The output results of DODO are highly comparable with other known ortholog databases. CONCLUSIONS: DODO provides a new efficient pipeline for detection of orthologs in a large number of genomes. In addition, a database established with DODO is also easier to maintain and could be updated relatively effortlessly. The pipeline of DODO could be downloaded from http://140.109.42.19:16080/dodo_web/home.htm.
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Project description:Chromosomal rearrangements that result in oncogenic kinase activation are present in many solid and hematological malignancies, but none have been reported in multiple myeloma (MM). Here we analyzed 1421 samples from 958 myeloma patients using a targeted assay and detected fusion genes in 1.5% of patients. These fusion genes were in-frame and the majority of them contained kinase domains from either receptor tyrosine kinases (ALK, ROS1, NTRK3, and FGFR1) or cytoplasmic kinases (BRAF, MAP3K14, and MAPK14), which would result in the activation of MEK/ERK, NF-κB, or inflammatory signaling pathways. Fusion genes were present in smoldering MM, newly diagnosed MM, and relapse patient samples indicating they are not solely late events. Most fusion genes were subclonal in nature, but one EML4-ALK fusion was clonal indicating it is a driver of disease pathogenesis. Samples with fusions of receptor tyrosine kinases were not found in conjunction with clonal Ras/Raf mutations indicating a parallel mechanism of MEK/ERK pathway activation. Fusion genes involving MAP3K14 (NIK), which regulates the NF-κB pathway, were detected as were t(14;17) rearrangements involving NIK in 2% of MM samples. Activation of kinases in myeloma through rearrangements presents an opportunity to use treatments existing in other cancers.
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