Advanced search
1 file | 1.41 MB

MorphDB : prioritizing genes for specialized metabolism pathways and gene ontology categories in plants

Author
Organization
Project
Bioinformatics: from nucleotids to networks (N2N)
Abstract
Recent times have seen an enormous growth of "omics" data, of which high-throughput gene expression data are arguably the most important from a functional perspective. Despite huge improvements in computational techniques for the functional classification of gene sequences, common similarity-based methods often fall short of providing full and reliable functional information. Recently, the combination of comparative genomics with approaches in functional genomics has received considerable interest for gene function analysis, leveraging both gene expression based guilt-by-association methods and annotation efforts in closely related model organisms. Besides the identification of missing genes in pathways, these methods also typically enable the discovery of biological regulators (i.e., transcription factors or signaling genes). A previously built guilt-by-association method is MORPH, which was proven to be an efficient algorithm that performs particularly well in identifying and prioritizing missing genes in plant metabolic pathways. Here, we present MorphDB, a resource where MORPH-based candidate genes for large-scale functional annotations (Gene Ontology, MapMan bins) are integrated across multiple plant species. Besides a gene centric query utility, we present a comparative network approach that enables researchers to efficiently browse MORPH predictions across functional gene sets and species, facilitating efficient gene discovery and candidate gene prioritization. MorphDB is available at http://bioinformatics.psb.ugent.be/webtools/morphdb/morphDB/index/. We also provide a toolkit, named "MORPH bulk" (https://github.com/arzwa/morph-bulk), for running MORPH in bulk mode on novel data sets, enabling researchers to apply MORPH to their own species of interest.
Keywords
ELEMENT-BINDING FACTORS, TURNIP CRINKLE VIRUS, TRANSCRIPTION FACTOR, ARABIDOPSIS-THALIANA, PHENYLPROPANOID METABOLISM, CATHARANTHUS-ROSEUS, SALICYLIC-ACID, GENOME, EXPRESSION, INTEGRATION, comparative co-expression networks, candidate gene prioritization, functional annotation, MORPH, defense response

Downloads

  • Zwaenepoel et al. (2018) Frontiers in Plant Science 9,352.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 1.41 MB

Citation

Please use this url to cite or link to this publication:

Chicago
Zwaenepoel, Arthur, Tim Diels, David Amar, Thomas Van Parys, Ron Shamir, Yves Van de Peer, and Oren Tzfadia. 2018. “MorphDB : Prioritizing Genes for Specialized Metabolism Pathways and Gene Ontology Categories in Plants.” Frontiers in Plant Science 9.
APA
Zwaenepoel, Arthur, Diels, T., Amar, D., Van Parys, T., Shamir, R., Van de Peer, Y., & Tzfadia, O. (2018). MorphDB : prioritizing genes for specialized metabolism pathways and gene ontology categories in plants. FRONTIERS IN PLANT SCIENCE, 9.
Vancouver
1.
Zwaenepoel A, Diels T, Amar D, Van Parys T, Shamir R, Van de Peer Y, et al. MorphDB : prioritizing genes for specialized metabolism pathways and gene ontology categories in plants. FRONTIERS IN PLANT SCIENCE. 2018;9.
MLA
Zwaenepoel, Arthur, Tim Diels, David Amar, et al. “MorphDB : Prioritizing Genes for Specialized Metabolism Pathways and Gene Ontology Categories in Plants.” FRONTIERS IN PLANT SCIENCE 9 (2018): n. pag. Print.
@article{8558237,
  abstract     = {Recent times have seen an enormous growth of {\textacutedbl}omics{\textacutedbl} data, of which high-throughput gene expression data are arguably the most important from a functional perspective. Despite huge improvements in computational techniques for the functional classification of gene sequences, common similarity-based methods often fall short of providing full and reliable functional information. Recently, the combination of comparative genomics with approaches in functional genomics has received considerable interest for gene function analysis, leveraging both gene expression based guilt-by-association methods and annotation efforts in closely related model organisms. Besides the identification of missing genes in pathways, these methods also typically enable the discovery of biological regulators (i.e., transcription factors or signaling genes). A previously built guilt-by-association method is MORPH, which was proven to be an efficient algorithm that performs particularly well in identifying and prioritizing missing genes in plant metabolic pathways. Here, we present MorphDB, a resource where MORPH-based candidate genes for large-scale functional annotations (Gene Ontology, MapMan bins) are integrated across multiple plant species. Besides a gene centric query utility, we present a comparative network approach that enables researchers to efficiently browse MORPH predictions across functional gene sets and species, facilitating efficient gene discovery and candidate gene prioritization. MorphDB is available at http://bioinformatics.psb.ugent.be/webtools/morphdb/morphDB/index/. We also provide a toolkit, named {\textacutedbl}MORPH bulk{\textacutedbl} (https://github.com/arzwa/morph-bulk), for running MORPH in bulk mode on novel data sets, enabling researchers to apply MORPH to their own species of interest.},
  articleno    = {352},
  author       = {Zwaenepoel, Arthur and Diels, Tim and Amar, David and Van Parys, Thomas and Shamir, Ron and Van de Peer, Yves and Tzfadia, Oren},
  issn         = {1664-462X},
  journal      = {FRONTIERS IN PLANT SCIENCE},
  keyword      = {ELEMENT-BINDING FACTORS,TURNIP CRINKLE VIRUS,TRANSCRIPTION FACTOR,ARABIDOPSIS-THALIANA,PHENYLPROPANOID METABOLISM,CATHARANTHUS-ROSEUS,SALICYLIC-ACID,GENOME,EXPRESSION,INTEGRATION,comparative co-expression networks,candidate gene prioritization,functional annotation,MORPH,defense response},
  language     = {eng},
  pages        = {13},
  title        = {MorphDB : prioritizing genes for specialized metabolism pathways and gene ontology categories in plants},
  url          = {http://dx.doi.org/10.3389/fpls.2018.00352},
  volume       = {9},
  year         = {2018},
}

Altmetric
View in Altmetric
Web of Science
Times cited: