Dataset Information

NAMS webserver: coding potential assessment and functional annotation of plant transcripts.

ABSTRACT: Recent advances in transcriptomics have uncovered lots of novel transcripts in plants. To annotate such transcripts, dissecting their coding potential is a critical step. Computational approaches have been proven fruitful in this task; however, most current tools are designed/optimized for mammals and only a few of them have been tested on a limited number of plant species. In this work, we present NAMS webserver, which contains a novel coding potential classifier, NAMS, specifically optimized for plants. We have evaluated the performance of NAMS using a comprehensive dataset containing more than 3 million transcripts from various plant species, where NAMS demonstrates high accuracy and remarkable performance improvements over state-of-the-art software. Moreover, our webserver also furnishes functional annotations, aiming to provide users informative clues to the functions of their transcripts. Considering that most plant species are poorly characterized, our NAMS webserver could serve as a valuable resource to facilitate the transcriptomic studies. The webserver with testing dataset is freely available at http://sunlab.cpy.cuhk.edu.hk/NAMS/.

SUBMITTER: Sun K

PROVIDER: S-EPMC8138890 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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NAMS webserver: coding potential assessment and functional annotation of plant transcripts.

Sun Kun K Wang Huating H Sun Hao H

Briefings in bioinformatics 20210501 3

Recent advances in transcriptomics have uncovered lots of novel transcripts in plants. To annotate such transcripts, dissecting their coding potential is a critical step. Computational approaches have been proven fruitful in this task; however, most current tools are designed/optimized for mammals and only a few of them have been tested on a limited number of plant species. In this work, we present NAMS webserver, which contains a novel coding potential classifier, NAMS, specifically optimized f ...[more]

PMID: 33080021

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Project description: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.

Dataset Information

NAMS webserver: coding potential assessment and functional annotation of plant transcripts.

Publications

NAMS webserver: coding potential assessment and functional annotation of plant transcripts.

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