Dataset Information

Collaborative Annotation Redefines Gene Sets for Crucial Phytopathogens.

ABSTRACT: Accurate and comprehensive annotation of genomic sequences underpins advances in managing plant disease. However, important plant pathogens still have incomplete and inconsistent gene sets and lack dedicated funding or teams to improve this annotation. This paper describes a collaborative approach to gene curation to address this shortcoming. In the first instance, over 40 members of the Botrytis cinerea community from eight countries, with training and infrastructural support from Ensembl Fungi, used the gene editing tool Apollo to systematically review the entire gene set (11,707 protein coding genes) in 6-7 months. This has subsequently been checked and disseminated. Following this, a similar project for another pathogen, Blumeria graminis f. sp. hordei, also led to a completely redefined gene set. Currently, we are working with the Zymoseptoria tritici community to enable them to achieve the same. While the tangible outcome of these projects is improved gene sets, it is apparent that the inherent agreement and ownership of a single gene set by research teams as they undergo this curation process are consequential to the acceleration of research in the field. With the generation of large data sets increasingly affordable, there is value in unifying both the divergent data sets and their associated research teams, pooling time, expertise, and resources. Community-driven annotation efforts can pave the way for a new kind of collaboration among pathogen research communities to generate well-annotated reference data sets, beneficial not just for the genome being examined but for related species and the refinement of automatic gene prediction tools.

SUBMITTER: Pedro H

PROVIDER: S-EPMC6854995 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Collaborative Annotation Redefines Gene Sets for Crucial Phytopathogens.

Pedro Helder H Yates Andrew D AD Kersey Paul J PJ De Silva Nishadi H NH

Frontiers in microbiology 20191107

Accurate and comprehensive annotation of genomic sequences underpins advances in managing plant disease. However, important plant pathogens still have incomplete and inconsistent gene sets and lack dedicated funding or teams to improve this annotation. This paper describes a collaborative approach to gene curation to address this shortcoming. In the first instance, over 40 members of the <i>Botrytis cinerea</i> community from eight countries, with training and infrastructural support from Ensemb ...[more]

PMID: 31787936

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Project description:BACKGROUND: Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO) implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence) or text-mining of the published scientific literature (literature profiling). RESULTS: We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human) and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2) and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells). CONCLUSION: The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions.

Dataset Information

Collaborative Annotation Redefines Gene Sets for Crucial Phytopathogens.

Publications

Collaborative Annotation Redefines Gene Sets for Crucial Phytopathogens.

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