Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers

Reproductive failure remains a significant challenge to the beef industry. The omics technologies have provided opportunities to improve reproductive efficiency. We used a multistaged analysis from blood profiles to integrate metabolome (plasma) and transcriptome (peripheral white blood cells) in be...

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Main Authors: Priyanka Banerjee, Soren P. Rodning, Wellison J. S. Diniz, Paul W. Dyce
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Metabolites
Subjects:
Online Access:https://www.mdpi.com/2218-1989/12/8/708
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author Priyanka Banerjee
Soren P. Rodning
Wellison J. S. Diniz
Paul W. Dyce
author_facet Priyanka Banerjee
Soren P. Rodning
Wellison J. S. Diniz
Paul W. Dyce
author_sort Priyanka Banerjee
collection DOAJ
description Reproductive failure remains a significant challenge to the beef industry. The omics technologies have provided opportunities to improve reproductive efficiency. We used a multistaged analysis from blood profiles to integrate metabolome (plasma) and transcriptome (peripheral white blood cells) in beef heifers. We used untargeted metabolomics and RNA-Seq paired data from six AI-pregnant (AI-P) and six nonpregnant (NP) Angus-Simmental crossbred heifers at artificial insemination (AI). Based on network co-expression analysis, we identified 17 and 37 hub genes in the AI-P and NP groups, respectively. Further, we identified <i>TGM2</i>, <i>TMEM51</i>, <i>TAC3</i>, <i>NDRG4</i>, and <i>PDGFB</i> as more connected in the NP heifers’ network. The NP gene network showed a connectivity gain due to the rewiring of major regulators. The metabolomic analysis identified 18 and 15 hub metabolites in the AI-P and NP networks. Tryptophan and allantoic acid exhibited a connectivity gain in the NP and AI-P networks, respectively. The gene–metabolite integration identified tocopherol-a as positively correlated with ENSBTAG00000009943 in the AI-P group. Conversely, tocopherol-a was negatively correlated in the NP group with <i>EXOSC2</i>, <i>TRNAUIAP</i>, and <i>SNX12</i>. In the NP group, α-ketoglutarate-<i>SMG8</i> and putrescine-<i>HSD17B13</i> were positively correlated, whereas a-ketoglutarate-<i>ALAS2</i> and tryptophan-<i>MTMR1</i> were negatively correlated. These multiple interactions identified novel targets and pathways underlying fertility in bovines.
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spelling doaj.art-551537affff0402fb0e15443df144fa52023-12-03T14:06:08ZengMDPI AGMetabolites2218-19892022-07-0112870810.3390/metabo12080708Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef HeifersPriyanka Banerjee0Soren P. Rodning1Wellison J. S. Diniz2Paul W. Dyce3Department of Animal Sciences, Auburn University, Auburn, AL 36849, USADepartment of Animal Sciences, Auburn University, Auburn, AL 36849, USADepartment of Animal Sciences, Auburn University, Auburn, AL 36849, USADepartment of Animal Sciences, Auburn University, Auburn, AL 36849, USAReproductive failure remains a significant challenge to the beef industry. The omics technologies have provided opportunities to improve reproductive efficiency. We used a multistaged analysis from blood profiles to integrate metabolome (plasma) and transcriptome (peripheral white blood cells) in beef heifers. We used untargeted metabolomics and RNA-Seq paired data from six AI-pregnant (AI-P) and six nonpregnant (NP) Angus-Simmental crossbred heifers at artificial insemination (AI). Based on network co-expression analysis, we identified 17 and 37 hub genes in the AI-P and NP groups, respectively. Further, we identified <i>TGM2</i>, <i>TMEM51</i>, <i>TAC3</i>, <i>NDRG4</i>, and <i>PDGFB</i> as more connected in the NP heifers’ network. The NP gene network showed a connectivity gain due to the rewiring of major regulators. The metabolomic analysis identified 18 and 15 hub metabolites in the AI-P and NP networks. Tryptophan and allantoic acid exhibited a connectivity gain in the NP and AI-P networks, respectively. The gene–metabolite integration identified tocopherol-a as positively correlated with ENSBTAG00000009943 in the AI-P group. Conversely, tocopherol-a was negatively correlated in the NP group with <i>EXOSC2</i>, <i>TRNAUIAP</i>, and <i>SNX12</i>. In the NP group, α-ketoglutarate-<i>SMG8</i> and putrescine-<i>HSD17B13</i> were positively correlated, whereas a-ketoglutarate-<i>ALAS2</i> and tryptophan-<i>MTMR1</i> were negatively correlated. These multiple interactions identified novel targets and pathways underlying fertility in bovines.https://www.mdpi.com/2218-1989/12/8/708beef heiferdata integrationfertilitymetabolometranscriptome
spellingShingle Priyanka Banerjee
Soren P. Rodning
Wellison J. S. Diniz
Paul W. Dyce
Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers
Metabolites
beef heifer
data integration
fertility
metabolome
transcriptome
title Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers
title_full Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers
title_fullStr Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers
title_full_unstemmed Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers
title_short Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers
title_sort co expression network and integrative analysis of metabolome and transcriptome uncovers biological pathways for fertility in beef heifers
topic beef heifer
data integration
fertility
metabolome
transcriptome
url https://www.mdpi.com/2218-1989/12/8/708
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AT wellisonjsdiniz coexpressionnetworkandintegrativeanalysisofmetabolomeandtranscriptomeuncoversbiologicalpathwaysforfertilityinbeefheifers
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