Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.

<strong>Objective</strong> <br /> In spite of the importance of fertility in different species, there has been little success dissecting the levels of OMICS. To better understand the molecular basis of fertility, we study transcriptome profiling of different tissues. <br /> ...

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Main Authors: Amin Shahabi, Mojtaba Tahmoorespour, Ali Kazemipour
Format: Article
Language:fas
Published: Shahid Bahonar University of Kerman 2019-08-01
Series:مجله بیوتکنولوژی کشاورزی
Subjects:
Online Access:https://jab.uk.ac.ir/article_2388_78c008689c7247b616e25e232fd8e91a.pdf
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spelling doaj-bc14dc690fab48359bc45c36843aa7a12020-11-25T03:55:18ZfasShahid Bahonar University of Kermanمجله بیوتکنولوژی کشاورزی2228-67052228-65002019-08-01112577810.22103/jab.2019.13510.11122388Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.Amin Shahabi0Mojtaba Tahmoorespour1Ali Kazemipour2Department of Animal Science, Ferdowsi University of Mashhad, Mashhad, IranDepartment of Animal Science, Ferdowsi University of Mashhad, Mashhad, IranAssistant Professor, Shahid Bahonar University of Kerman, Iran.<strong>Objective</strong> <br /> In spite of the importance of fertility in different species, there has been little success dissecting the levels of OMICS. To better understand the molecular basis of fertility, we study transcriptome profiling of different tissues. <br />  <br /><strong>Materials and methods</strong> <br /><strong> </strong>liver, muscle, endometrium and corpus luteum tissues between cows with either good or poor genetic merit for fertility using RNA-Seq data sets. We first compiled a master list of genes related to corpus luteum that change with level of fertility and then reconstructed the network. <br />  <br /><strong>Results</strong> <br />A few genes were identified in liver, muscle and endometrium between high and low fertile cows but in corpus luteum circumstance was different. 264 genes and 6 key modules were disclosed through clustering for mRNA master list for corpus luteum. All these genes, being involved in at least one of the biological process, namely proteolysis, actin cytoskeleton organization, immune system process, biological adhesion, cell differentiation and lipid metabolic process, have an overexpression pattern (<em>P </em>< 0.01). <br /><strong>Conclusions</strong> <br />Finally, the identification of genes and the construction of their regulatory networks may give new insights into biological procedures. As well as, this study increases our understanding of the contribution of different tissues transcriptome to phenotypic fertility in dairy cattle.https://jab.uk.ac.ir/article_2388_78c008689c7247b616e25e232fd8e91a.pdffertilitytranscriptomeco-expression gene networkreconstruction of gene networks
collection DOAJ
language fas
format Article
sources DOAJ
author Amin Shahabi
Mojtaba Tahmoorespour
Ali Kazemipour
spellingShingle Amin Shahabi
Mojtaba Tahmoorespour
Ali Kazemipour
Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.
مجله بیوتکنولوژی کشاورزی
fertility
transcriptome
co-expression gene network
reconstruction of gene networks
author_facet Amin Shahabi
Mojtaba Tahmoorespour
Ali Kazemipour
author_sort Amin Shahabi
title Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.
title_short Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.
title_full Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.
title_fullStr Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.
title_full_unstemmed Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.
title_sort reconstruction, analysis and comparison of gene networks topology based on rna-seq data involved in reproductive and fertility complex traits.
publisher Shahid Bahonar University of Kerman
series مجله بیوتکنولوژی کشاورزی
issn 2228-6705
2228-6500
publishDate 2019-08-01
description <strong>Objective</strong> <br /> In spite of the importance of fertility in different species, there has been little success dissecting the levels of OMICS. To better understand the molecular basis of fertility, we study transcriptome profiling of different tissues. <br />  <br /><strong>Materials and methods</strong> <br /><strong> </strong>liver, muscle, endometrium and corpus luteum tissues between cows with either good or poor genetic merit for fertility using RNA-Seq data sets. We first compiled a master list of genes related to corpus luteum that change with level of fertility and then reconstructed the network. <br />  <br /><strong>Results</strong> <br />A few genes were identified in liver, muscle and endometrium between high and low fertile cows but in corpus luteum circumstance was different. 264 genes and 6 key modules were disclosed through clustering for mRNA master list for corpus luteum. All these genes, being involved in at least one of the biological process, namely proteolysis, actin cytoskeleton organization, immune system process, biological adhesion, cell differentiation and lipid metabolic process, have an overexpression pattern (<em>P </em>< 0.01). <br /><strong>Conclusions</strong> <br />Finally, the identification of genes and the construction of their regulatory networks may give new insights into biological procedures. As well as, this study increases our understanding of the contribution of different tissues transcriptome to phenotypic fertility in dairy cattle.
topic fertility
transcriptome
co-expression gene network
reconstruction of gene networks
url https://jab.uk.ac.ir/article_2388_78c008689c7247b616e25e232fd8e91a.pdf
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