Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle
Beef tenderness, a complex trait affected by many factors, is economically important to beef quality, industry, and consumer’s palatability. In this study, RNA-Seq was used in network analysis to better understand the biological processes that lead to differences in beef tenderness. Skeletal muscle...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-10-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2018.00441/full |
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| author | Tássia Mangetti Gonçalves Luciana Correia de Almeida Regitano James E. Koltes Aline Silva Mello Cesar Sónia Cristina da Silva Andrade Sónia Cristina da Silva Andrade Gerson Barreto Mourão Gustavo Gasparin Gabriel Costa Monteiro Moreira Elyn Fritz-Waters James M. Reecy Luiz Lehmann Coutinho |
| author_facet | Tássia Mangetti Gonçalves Luciana Correia de Almeida Regitano James E. Koltes Aline Silva Mello Cesar Sónia Cristina da Silva Andrade Sónia Cristina da Silva Andrade Gerson Barreto Mourão Gustavo Gasparin Gabriel Costa Monteiro Moreira Elyn Fritz-Waters James M. Reecy Luiz Lehmann Coutinho |
| author_sort | Tássia Mangetti Gonçalves |
| collection | DOAJ |
| description | Beef tenderness, a complex trait affected by many factors, is economically important to beef quality, industry, and consumer’s palatability. In this study, RNA-Seq was used in network analysis to better understand the biological processes that lead to differences in beef tenderness. Skeletal muscle transcriptional profiles from 24 Nellore steers, selected by extreme estimated breeding values (EBVs) for shear force after 14 days of aging, were analyzed and 22 differentially expressed transcripts were identified. Among these were genes encoding ribosomal proteins, glutathione transporter ATP-binding cassette, sub-family C (CFTR/MRP), member 4 (ABCC4), and synaptotagmin IV (SYT4). Complementary co-expression analyses using Partial Correlation with Information Theory (PCIT), Phenotypic Impact Factor (PIF) and the Regulatory Impact Factor (RIF) methods identified candidate regulators and related pathways. The PCIT analysis identified ubiquitin specific peptidase 2 (USP2), growth factor receptor-bound protein 10 (GBR10), anoctamin 1 (ANO1), and transmembrane BAX inhibitor motif containing 4 (TMBIM4) as the most differentially hubbed (DH) transcripts. The transcripts that had a significant correlation with USP2, GBR10, ANO1, and TMBIM4 enriched for proteasome KEGG pathway. RIF analysis identified microRNAs as candidate regulators of variation in tenderness, including bta-mir-133a-2 and bta-mir-22. Both microRNAs have target genes present in the calcium signaling pathway and apoptosis. PIF analysis identified myoglobin (MB), enolase 3 (ENO3), and carbonic anhydrase 3 (CA3) as potentially having fundamental roles in tenderness. Pathways identified in our study impacted in beef tenderness included: calcium signaling, apoptosis, and proteolysis. These findings underscore some of the complex molecular mechanisms that control beef tenderness in Nellore cattle. |
| first_indexed | 2024-12-17T01:52:05Z |
| format | Article |
| id | doaj.art-f0c1a2e3747e4f4dbea3dd1224b3e06b |
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| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-17T01:52:05Z |
| publishDate | 2018-10-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Genetics |
| spelling | doaj.art-f0c1a2e3747e4f4dbea3dd1224b3e06b2022-12-21T22:08:03ZengFrontiers Media S.A.Frontiers in Genetics1664-80212018-10-01910.3389/fgene.2018.00441400232Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore CattleTássia Mangetti Gonçalves0Luciana Correia de Almeida Regitano1James E. Koltes2Aline Silva Mello Cesar3Sónia Cristina da Silva Andrade4Sónia Cristina da Silva Andrade5Gerson Barreto Mourão6Gustavo Gasparin7Gabriel Costa Monteiro Moreira8Elyn Fritz-Waters9James M. Reecy10Luiz Lehmann Coutinho11Department of Animal Science, University of São Paulo, Piracicaba, BrazilEmbrapa Southeast-Cattle Research Center, São Carlos, BrazilDepartment of Animal Science, Iowa State University, Ames, IA, United StatesDepartment of Animal Science, University of São Paulo, Piracicaba, BrazilDepartment of Animal Science, University of São Paulo, Piracicaba, BrazilDepartment of Genetics and Evolutionary Biology, University of São Paulo, São Paulo, BrazilDepartment of Animal Science, University of São Paulo, Piracicaba, BrazilDepartment of Animal Science, University of São Paulo, Piracicaba, BrazilDepartment of Animal Science, University of São Paulo, Piracicaba, BrazilDepartment of Animal Science, Iowa State University, Ames, IA, United StatesDepartment of Animal Science, Iowa State University, Ames, IA, United StatesDepartment of Animal Science, University of São Paulo, Piracicaba, BrazilBeef tenderness, a complex trait affected by many factors, is economically important to beef quality, industry, and consumer’s palatability. In this study, RNA-Seq was used in network analysis to better understand the biological processes that lead to differences in beef tenderness. Skeletal muscle transcriptional profiles from 24 Nellore steers, selected by extreme estimated breeding values (EBVs) for shear force after 14 days of aging, were analyzed and 22 differentially expressed transcripts were identified. Among these were genes encoding ribosomal proteins, glutathione transporter ATP-binding cassette, sub-family C (CFTR/MRP), member 4 (ABCC4), and synaptotagmin IV (SYT4). Complementary co-expression analyses using Partial Correlation with Information Theory (PCIT), Phenotypic Impact Factor (PIF) and the Regulatory Impact Factor (RIF) methods identified candidate regulators and related pathways. The PCIT analysis identified ubiquitin specific peptidase 2 (USP2), growth factor receptor-bound protein 10 (GBR10), anoctamin 1 (ANO1), and transmembrane BAX inhibitor motif containing 4 (TMBIM4) as the most differentially hubbed (DH) transcripts. The transcripts that had a significant correlation with USP2, GBR10, ANO1, and TMBIM4 enriched for proteasome KEGG pathway. RIF analysis identified microRNAs as candidate regulators of variation in tenderness, including bta-mir-133a-2 and bta-mir-22. Both microRNAs have target genes present in the calcium signaling pathway and apoptosis. PIF analysis identified myoglobin (MB), enolase 3 (ENO3), and carbonic anhydrase 3 (CA3) as potentially having fundamental roles in tenderness. Pathways identified in our study impacted in beef tenderness included: calcium signaling, apoptosis, and proteolysis. These findings underscore some of the complex molecular mechanisms that control beef tenderness in Nellore cattle.https://www.frontiersin.org/article/10.3389/fgene.2018.00441/fullmeatbovineRNA-SeqtranscriptomenetworksmicroRNA |
| spellingShingle | Tássia Mangetti Gonçalves Luciana Correia de Almeida Regitano James E. Koltes Aline Silva Mello Cesar Sónia Cristina da Silva Andrade Sónia Cristina da Silva Andrade Gerson Barreto Mourão Gustavo Gasparin Gabriel Costa Monteiro Moreira Elyn Fritz-Waters James M. Reecy Luiz Lehmann Coutinho Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle Frontiers in Genetics meat bovine RNA-Seq transcriptome networks microRNA |
| title | Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle |
| title_full | Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle |
| title_fullStr | Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle |
| title_full_unstemmed | Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle |
| title_short | Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle |
| title_sort | gene co expression analysis indicates potential pathways and regulators of beef tenderness in nellore cattle |
| topic | meat bovine RNA-Seq transcriptome networks microRNA |
| url | https://www.frontiersin.org/article/10.3389/fgene.2018.00441/full |
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