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FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions
smORFs are small open reading frames of less than 100 codons. Recent low throughput experiments showed a lot of smORF-encoded peptides (SEPs) played crucial rule in processes such as regulation of transcription or translation, transportation through membranes and the antimicrobial activity. In order...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896265/ https://www.ncbi.nlm.nih.gov/pubmed/29675032 http://dx.doi.org/10.3389/fgene.2018.00096 |
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author | Li, Hui Xiao, Li Zhang, Lili Wu, Jiarui Wei, Bin Sun, Ninghui Zhao, Yi |
author_facet | Li, Hui Xiao, Li Zhang, Lili Wu, Jiarui Wei, Bin Sun, Ninghui Zhao, Yi |
author_sort | Li, Hui |
collection | PubMed |
description | smORFs are small open reading frames of less than 100 codons. Recent low throughput experiments showed a lot of smORF-encoded peptides (SEPs) played crucial rule in processes such as regulation of transcription or translation, transportation through membranes and the antimicrobial activity. In order to gather more functional SEPs, it is necessary to have access to genome-wide prediction tools to give profound directions for low throughput experiments. In this study, we put forward a functional smORF-encoded peptides predictor (FSPP) which tended to predict authentic SEPs and their functions in a high throughput method. FSPP used the overlap of detected SEPs from Ribo-seq and mass spectrometry as target objects. With the expression data on transcription and translation levels, FSPP built two co-expression networks. Combing co-location relations, FSPP constructed a compound network and then annotated SEPs with functions of adjacent nodes. Tested on 38 sequenced samples of 5 human cell lines, FSPP successfully predicted 856 out of 960 annotated proteins. Interestingly, FSPP also highlighted 568 functional SEPs from these samples. After comparison, the roles predicted by FSPP were consistent with known functions. These results suggest that FSPP is a reliable tool for the identification of functional small peptides. FSPP source code can be acquired at https://www.bioinfo.org/FSPP. |
format | Online Article Text |
id | pubmed-5896265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58962652018-04-19 FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions Li, Hui Xiao, Li Zhang, Lili Wu, Jiarui Wei, Bin Sun, Ninghui Zhao, Yi Front Genet Genetics smORFs are small open reading frames of less than 100 codons. Recent low throughput experiments showed a lot of smORF-encoded peptides (SEPs) played crucial rule in processes such as regulation of transcription or translation, transportation through membranes and the antimicrobial activity. In order to gather more functional SEPs, it is necessary to have access to genome-wide prediction tools to give profound directions for low throughput experiments. In this study, we put forward a functional smORF-encoded peptides predictor (FSPP) which tended to predict authentic SEPs and their functions in a high throughput method. FSPP used the overlap of detected SEPs from Ribo-seq and mass spectrometry as target objects. With the expression data on transcription and translation levels, FSPP built two co-expression networks. Combing co-location relations, FSPP constructed a compound network and then annotated SEPs with functions of adjacent nodes. Tested on 38 sequenced samples of 5 human cell lines, FSPP successfully predicted 856 out of 960 annotated proteins. Interestingly, FSPP also highlighted 568 functional SEPs from these samples. After comparison, the roles predicted by FSPP were consistent with known functions. These results suggest that FSPP is a reliable tool for the identification of functional small peptides. FSPP source code can be acquired at https://www.bioinfo.org/FSPP. Frontiers Media S.A. 2018-04-05 /pmc/articles/PMC5896265/ /pubmed/29675032 http://dx.doi.org/10.3389/fgene.2018.00096 Text en Copyright © 2018 Li, Xiao, Zhang, Wu, Wei, Sun and Zhao. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Li, Hui Xiao, Li Zhang, Lili Wu, Jiarui Wei, Bin Sun, Ninghui Zhao, Yi FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions |
title | FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions |
title_full | FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions |
title_fullStr | FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions |
title_full_unstemmed | FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions |
title_short | FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions |
title_sort | fspp: a tool for genome-wide prediction of smorf-encoded peptides and their functions |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896265/ https://www.ncbi.nlm.nih.gov/pubmed/29675032 http://dx.doi.org/10.3389/fgene.2018.00096 |
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