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Transcriptome Analysis of the Capra hircus Ovary
BACKGROUND: Capra hircus is an important economic livestock animal, and therefore, it is necessary to discover transcriptome information about their reproductive performance. In this study, we performed de novo transcriptome sequencing to produce the first transcriptome dataset for the goat ovary us...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4378920/ https://www.ncbi.nlm.nih.gov/pubmed/25822507 http://dx.doi.org/10.1371/journal.pone.0121586 |
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author | Zhao, Zhong Quan Wang, Li Juan Sun, Xiao Wei Zhang, Jiao Jiao Zhao, Yong Ju Na, Ri Su Zhang, Jia Hua |
author_facet | Zhao, Zhong Quan Wang, Li Juan Sun, Xiao Wei Zhang, Jiao Jiao Zhao, Yong Ju Na, Ri Su Zhang, Jia Hua |
author_sort | Zhao, Zhong Quan |
collection | PubMed |
description | BACKGROUND: Capra hircus is an important economic livestock animal, and therefore, it is necessary to discover transcriptome information about their reproductive performance. In this study, we performed de novo transcriptome sequencing to produce the first transcriptome dataset for the goat ovary using high-throughput sequencing technologies. The result will contribute to research on goat reproductive performance. METHOD AND RESULTS: RNA-seq analysis generated more than 38.8 million clean paired end (PE) reads, which were assembled into 80,069 unigenes (mean size = 619 bp). Based on sequence similarity searches, 64,824 (60.6%) genes were identified, among which 29,444 and 11,271 unigenes were assigned to Gene Ontology (GO) categories and Clusters of Orthologous Groups (COG), respectively. Searches in the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG) showed that 27,766 (63.4%) unigenes were mapped to 258 KEGG pathways. Furthermore, we investigated the transcriptome differences of goat ovaries at two different ages using a tag-based digital gene expression system. We obtained a sequencing depth of over 5.6 million and 5.8 million tags for the two ages and identified a large number of genes associated with reproductive hormones, ovulatory cycle and follicle. Moreover, many antisense transcripts and novel transcripts were found; clusters with similar differential expression patterns, enriched GO terms and metabolic pathways were revealed for the first time with regard to the differentially expressed genes. CONCLUSIONS: The transcriptome provides invaluable new data for a functional genomic resource and future biological research in Capra hircus, and it is essential for the in-depth study of candidate genes in breeding programs. |
format | Online Article Text |
id | pubmed-4378920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-43789202015-04-09 Transcriptome Analysis of the Capra hircus Ovary Zhao, Zhong Quan Wang, Li Juan Sun, Xiao Wei Zhang, Jiao Jiao Zhao, Yong Ju Na, Ri Su Zhang, Jia Hua PLoS One Research Article BACKGROUND: Capra hircus is an important economic livestock animal, and therefore, it is necessary to discover transcriptome information about their reproductive performance. In this study, we performed de novo transcriptome sequencing to produce the first transcriptome dataset for the goat ovary using high-throughput sequencing technologies. The result will contribute to research on goat reproductive performance. METHOD AND RESULTS: RNA-seq analysis generated more than 38.8 million clean paired end (PE) reads, which were assembled into 80,069 unigenes (mean size = 619 bp). Based on sequence similarity searches, 64,824 (60.6%) genes were identified, among which 29,444 and 11,271 unigenes were assigned to Gene Ontology (GO) categories and Clusters of Orthologous Groups (COG), respectively. Searches in the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG) showed that 27,766 (63.4%) unigenes were mapped to 258 KEGG pathways. Furthermore, we investigated the transcriptome differences of goat ovaries at two different ages using a tag-based digital gene expression system. We obtained a sequencing depth of over 5.6 million and 5.8 million tags for the two ages and identified a large number of genes associated with reproductive hormones, ovulatory cycle and follicle. Moreover, many antisense transcripts and novel transcripts were found; clusters with similar differential expression patterns, enriched GO terms and metabolic pathways were revealed for the first time with regard to the differentially expressed genes. CONCLUSIONS: The transcriptome provides invaluable new data for a functional genomic resource and future biological research in Capra hircus, and it is essential for the in-depth study of candidate genes in breeding programs. Public Library of Science 2015-03-30 /pmc/articles/PMC4378920/ /pubmed/25822507 http://dx.doi.org/10.1371/journal.pone.0121586 Text en © 2015 Zhao et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Zhao, Zhong Quan Wang, Li Juan Sun, Xiao Wei Zhang, Jiao Jiao Zhao, Yong Ju Na, Ri Su Zhang, Jia Hua Transcriptome Analysis of the Capra hircus Ovary |
title | Transcriptome Analysis of the Capra hircus Ovary |
title_full | Transcriptome Analysis of the Capra hircus Ovary |
title_fullStr | Transcriptome Analysis of the Capra hircus Ovary |
title_full_unstemmed | Transcriptome Analysis of the Capra hircus Ovary |
title_short | Transcriptome Analysis of the Capra hircus Ovary |
title_sort | transcriptome analysis of the capra hircus ovary |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4378920/ https://www.ncbi.nlm.nih.gov/pubmed/25822507 http://dx.doi.org/10.1371/journal.pone.0121586 |
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