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An Updated Functional Annotation of Protein-Coding Genes in the Cucumber Genome

Overview of attention for article published in Frontiers in Plant Science, March 2018
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Title
An Updated Functional Annotation of Protein-Coding Genes in the Cucumber Genome
Published in
Frontiers in Plant Science, March 2018
DOI 10.3389/fpls.2018.00325
Pubmed ID
Authors

Hongtao Song, Kui Lin, Jinglu Hu, Erli Pang

Abstract

Background: Although the cucumber reference genome and its annotation were published several years ago, the functional annotation of predicted genes, particularly protein-coding genes, still requires further improvement. In general, accurately determining orthologous relationships between genes allows for better and more robust functional assignments of predicted genes. As one of the most reliable strategies, the determination of collinearity information may facilitate reliable orthology inferences among genes from multiple related genomes. Currently, the identification of collinear segments has mainly been based on conservation of gene order and orientation. Over the course of plant genome evolution, various evolutionary events have disrupted or distorted the order of genes along chromosomes, making it difficult to use those genes as genome-wide markers for plant genome comparisons.Results:Using the localized LASTZ/MULTIZ analysis pipeline, we aligned 15 genomes, including cucumber and other related angiosperm plants, and identified a set of genomic segments that are short in length, stable in structure, uniform in distribution and highly conserved across all 15 plants. Compared with protein-coding genes, these conserved segments were more suitable for use as genomic markers for detecting collinear segments among distantly divergent plants. Guided by this set of identified collinear genomic segments, we inferred 94,486 orthologous protein-coding gene pairs (OPPs) between cucumber and 14 other angiosperm species, which were used as proxies for transferring functional terms to cucumber genes from the annotations of the other 14 genomes. In total, 10,885 protein-coding genes were assigned Gene Ontology (GO) terms which was nearly 1,300 more than results collected in Uniprot-proteomic database. Our results showed that annotation accuracy would been improved compared with other existing approaches.Conclusions:In this study, we provided an alternative resource for the functional annotation of predicted cucumber protein-coding genes, which we expect will be beneficial for the cucumber's biological study, accessible from http://cmb.bnu.edu.cn/functional_annotation. Meanwhile, using the cucumber reference genome as a case study, we presented an efficient strategy for transferring gene functional information from previously well-characterized protein-coding genes in model species to newly sequenced or "non-model" plant species.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 29%
Student > Bachelor 4 29%
Student > Doctoral Student 2 14%
Student > Ph. D. Student 2 14%
Professor 1 7%
Other 0 0%
Unknown 1 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 50%
Biochemistry, Genetics and Molecular Biology 3 21%
Engineering 2 14%
Unknown 2 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 March 2018.
All research outputs
#20,472,403
of 23,031,582 outputs
Outputs from Frontiers in Plant Science
#16,452
of 20,570 outputs
Outputs of similar age
#294,870
of 333,794 outputs
Outputs of similar age from Frontiers in Plant Science
#429
of 481 outputs
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So far Altmetric has tracked 20,570 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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