Dataset Information

SUPERFAMILY 1.75 including a domain-centric gene ontology method.

ABSTRACT: The SUPERFAMILY resource provides protein domain assignments at the structural classification of protein (SCOP) superfamily level for over 1400 completely sequenced genomes, over 120 metagenomes and other gene collections such as UniProt. All models and assignments are available to browse and download at http://supfam.org. A new hidden Markov model library based on SCOP 1.75 has been created and a previously ignored class of SCOP, coiled coils, is now included. Our scoring component now uses HMMER3, which is in orders of magnitude faster and produces superior results. A cloud-based pipeline was implemented and is publicly available at Amazon web services elastic computer cloud. The SUPERFAMILY reference tree of life has been improved allowing the user to highlight a chosen superfamily, family or domain architecture on the tree of life. The most significant advance in SUPERFAMILY is that now it contains a domain-based gene ontology (GO) at the superfamily and family levels. A new methodology was developed to ensure a high quality GO annotation. The new methodology is general purpose and has been used to produce domain-based phenotypic ontologies in addition to GO.

SUBMITTER: de Lima Morais DA

PROVIDER: S-EPMC3013712 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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SUPERFAMILY 1.75 including a domain-centric gene ontology method.

de Lima Morais David A DA Fang Hai H Rackham Owen J L OJ Wilson Derek D Pethica Ralph R Chothia Cyrus C Gough Julian J

Nucleic acids research 20101109 Database issue

The SUPERFAMILY resource provides protein domain assignments at the structural classification of protein (SCOP) superfamily level for over 1400 completely sequenced genomes, over 120 metagenomes and other gene collections such as UniProt. All models and assignments are available to browse and download at http://supfam.org. A new hidden Markov model library based on SCOP 1.75 has been created and a previously ignored class of SCOP, coiled coils, is now included. Our scoring component now uses HMM ...[more]

PMID: 21062816

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Project description:BackgroundAmong the primary goals of microarray analysis is the identification of genes that could distinguish between different phenotypes (feature selection). Previous studies indicate that incorporating prior information of the genes' function could help identify physiologically relevant features. However, current methods that incorporate prior functional information do not provide a relative estimate of the effect of different genes on the biological processes of interest.ResultsHere, we present a method that integrates gene ontology (GO) information and expression data using Bayesian regression mixture models to perform unsupervised clustering of the samples and identify physiologically relevant discriminating features. As a model application, the method was applied to identify the genes that play a role in the cytotoxic responses of human hepatoblastoma cell line (HepG2) to saturated fatty acid (SFA) and tumor necrosis factor (TNF)-alpha, as compared to the non-toxic response to the unsaturated FFAs (UFA) and TNF-alpha. Incorporation of prior knowledge led to a better discrimination of the toxic phenotypes from the others. The model identified roles of lysosomal ATPases and adenylate cyclase (AC9) in the toxicity of palmitate. To validate the role of AC in palmitate-treated cells, we measured the intracellular levels of cyclic AMP (cAMP). The cAMP levels were found to be significantly reduced by palmitate treatment and not by the other FFAs, in accordance with the model selection of AC9.ConclusionsA framework is presented that incorporates prior ontology information, which helped to (a) perform unsupervised clustering of the phenotypes, and (b) identify the genes relevant to each cluster of phenotypes. We demonstrate the proposed framework by applying it to identify physiologically-relevant feature genes that conferred differential toxicity to saturated vs. unsaturated FFAs. The framework can be applied to other problems to efficiently integrate ontology information and expression data in order to identify feature genes.

Project description:BackgroundSOMATIC EMBRYOGENESIS RECEPTOR-LIKE KINASE (SERK) genes are part of the regulation of diverse signalling events in plants. Current evidence shows SERK proteins function both in developmental and defence signalling pathways, which occur in response to both peptide and steroid ligands. SERKs are generally present as small gene families in plants, with five SERK genes in Arabidopsis. Knowledge gained primarily through work on Arabidopsis SERKs indicates that these proteins probably interact with a wide range of other receptor kinases and form a fundamental part of many essential signalling pathways. The SERK1 gene of the model legume, Medicago truncatula functions in somatic and zygotic embryogenesis, and during many phases of plant development, including nodule and lateral root formation. However, other SERK genes in M. truncatula and other legumes are largely unidentified and their functions unknown.ResultsTo aid the understanding of signalling pathways in M. truncatula, we have identified and annotated the SERK genes in this species. Using degenerate PCR and database mining, eight more SERK-like genes have been identified and these have been shown to be expressed. The amplification and sequencing of several different PCR products from one of these genes is consistent with the presence of splice variants. Four of the eight additional genes identified are upregulated in cultured leaf tissue grown on embryogenic medium. The sequence information obtained from M. truncatula was used to identify SERK family genes in the recently sequenced soybean (Glycine max) genome.ConclusionsA total of nine SERK or SERK-like genes have been identified in M. truncatula and potentially 17 in soybean. Five M. truncatula SERK genes arose from duplication events not evident in soybean and Lotus. The presence of splice variants has not been previously reported in a SERK gene. Upregulation of four newly identified SERK genes (in addition to the previously described MtSERK1) in embryogenic tissue cultures suggests these genes also play a role in the process of somatic embryogenesis. The phylogenetic relationship of members of the SERK gene family to closely related genes, and to development and defence function is discussed.

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SUPERFAMILY 1.75 including a domain-centric gene ontology method.

Publications

SUPERFAMILY 1.75 including a domain-centric gene ontology method.

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