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Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing

The kidding rate is one of the most important economic traits for goat production, but the genetic mechanism that is associated with ovulation rate is poorly understood. Recently, increasing evidence has suggested that microRNAs (miRNAs) influence ovarian biological processes. The present study prov...

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Autores principales: Zi, Xiang-dong, Lu, Jian-yuan, Ma, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5432505/
https://www.ncbi.nlm.nih.gov/pubmed/28507337
http://dx.doi.org/10.1038/s41598-017-02225-x
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author Zi, Xiang-dong
Lu, Jian-yuan
Ma, Li
author_facet Zi, Xiang-dong
Lu, Jian-yuan
Ma, Li
author_sort Zi, Xiang-dong
collection PubMed
description The kidding rate is one of the most important economic traits for goat production, but the genetic mechanism that is associated with ovulation rate is poorly understood. Recently, increasing evidence has suggested that microRNAs (miRNAs) influence ovarian biological processes. The present study provides the first comparison of the ovarian miRNAs of prolific Jintang black goats (JTGs) and non-prolific Tibetan goats (TBGs) during the follicular phase using RNA-Seq technology. We generated 11.19 million (M) and 11.34 M clean reads from the TBG and JTG libraries, respectively, from which a total of 389 known miRNAs were identified and 142 novel miRNAs were predicted. A total of 191 miRNAs were differentially expressed between the two breeds. Among the 10 most abundant miRNAs, miR-21-5p was defined as differentially expressed miRNA with a higher level in the JTG library than in the TBG library, but the other miRNAs were not different between the breeds. The predicted miRNA-targeted genes were further analyzed by Gene Ontology and KEGG pathway analyses. The results revealed that miR-21, miR-99a, miRNA-143, let-7f, miR-493 and miR-200b may affect follicular development. These findings will increase the current understanding of the role of ovarian miRNAs in the regulation of ovulation rate in goats.
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spelling pubmed-54325052017-05-16 Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing Zi, Xiang-dong Lu, Jian-yuan Ma, Li Sci Rep Article The kidding rate is one of the most important economic traits for goat production, but the genetic mechanism that is associated with ovulation rate is poorly understood. Recently, increasing evidence has suggested that microRNAs (miRNAs) influence ovarian biological processes. The present study provides the first comparison of the ovarian miRNAs of prolific Jintang black goats (JTGs) and non-prolific Tibetan goats (TBGs) during the follicular phase using RNA-Seq technology. We generated 11.19 million (M) and 11.34 M clean reads from the TBG and JTG libraries, respectively, from which a total of 389 known miRNAs were identified and 142 novel miRNAs were predicted. A total of 191 miRNAs were differentially expressed between the two breeds. Among the 10 most abundant miRNAs, miR-21-5p was defined as differentially expressed miRNA with a higher level in the JTG library than in the TBG library, but the other miRNAs were not different between the breeds. The predicted miRNA-targeted genes were further analyzed by Gene Ontology and KEGG pathway analyses. The results revealed that miR-21, miR-99a, miRNA-143, let-7f, miR-493 and miR-200b may affect follicular development. These findings will increase the current understanding of the role of ovarian miRNAs in the regulation of ovulation rate in goats. Nature Publishing Group UK 2017-05-15 /pmc/articles/PMC5432505/ /pubmed/28507337 http://dx.doi.org/10.1038/s41598-017-02225-x Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zi, Xiang-dong
Lu, Jian-yuan
Ma, Li
Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing
title Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing
title_full Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing
title_fullStr Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing
title_full_unstemmed Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing
title_short Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing
title_sort identification and comparative analysis of the ovarian micrornas of prolific and non-prolific goats during the follicular phase using high-throughput sequencing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5432505/
https://www.ncbi.nlm.nih.gov/pubmed/28507337
http://dx.doi.org/10.1038/s41598-017-02225-x
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