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.
Highlights
Groups of genes involved in a common biological process are often defined as pathways, which are traditionally studied as if they were isolated groups
In genome-wide runs, we provide as input to MORPH a genomescale functional annotation as acquired from public repositories or popular software tools (e.g., Blast2GO or InterProScan)
We showed how MORPH can be used in bulk mode on non-model species, such as C. roseus and Z. marina, for rendering putative gene functions by analyzing bait gene sets defined by Gene Ontology (GO) categories
Summary
Groups of genes involved in a common biological process are often defined as pathways, which are traditionally studied as if they were isolated groups. Despite more than two decades of functional genomics research, the functions of most plant genes remain unknown. These problems are exacerbated in newly sequenced genomes and non-model organisms (Rhee and Mutwil, 2014). Sequence similarity based tools such as Blast2GO (Conesa et al, 2005; Conesa and Götz, 2008), BlastKOALA (Kanehisa et al, 2016), PlantCyc’s EP2P (Schläpfer et al, 2017) and InterProScan (Zdobnov and Apweiler, 2001; Jones et al, 2014), are often used to provide a first clue about the function of a gene in a newly sequenced and annotated genome. After the delineation of groups of homologous genes, annotations are transferred between orthologs under the assumption that evolutionary conservation implies a conserved function
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