Reference Citation Analysis: Find an Article, Find a Category, Find a Journal, Find a Scholar

For: Goszczynski DE, Mazzucco JP, Ripoli MV, Villarreal EL, Rogberg-Muñoz A, Mezzadra CA, Melucci LM, Giovambattista G. Genetic characterisation of PPARG, CEBPA and RXRA, and their influence on meat quality traits in cattle. J Anim Sci Technol 2016;58:14. [PMID: 27042330 PMCID: PMC4818460 DOI: 10.1186/s40781-016-0095-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 03/15/2016] [Indexed: 11/14/2022]

For:	Goszczynski DE, Mazzucco JP, Ripoli MV, Villarreal EL, Rogberg-Muñoz A, Mezzadra CA, Melucci LM, Giovambattista G. Genetic characterisation of PPARG, CEBPA and RXRA, and their influence on meat quality traits in cattle. J Anim Sci Technol 2016;58:14. [PMID: 27042330 PMCID: PMC4818460 DOI: 10.1186/s40781-016-0095-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 03/15/2016] [Indexed: 11/14/2022]

Number

Cited by Other Article(s)

Ran H, He Q, Han Y, Wang J, Wang H, Yue B, Zhang M, Chai Z, Cai X, Zhong J, Wang H. Functional study and epigenetic targets analyses of SIRT1 in intramuscular preadipocytes via ChIP-seq and mRNA-seq. Epigenetics 2023;18:2135194. [PMID: 36264146 PMCID: PMC9980681 DOI: 10.1080/15592294.2022.2135194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open

Affiliation(s)

Hongbiao Ran Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Qiuya He Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, People's Republic of China
Yuting Han Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Jikun Wang Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Haibo Wang Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Binglin Yue Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Ming Zhang Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Zhixin Chai Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Xin Cai Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Jincheng Zhong Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China
Hui Wang Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, People's Republic of China

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Helal M, Ali MA, Nadrin AH, Awad YI, Younis NK, Alasyed BM, Jamal M, Eid DH, Soliman HA, Eissa SA, Ragab M. Association between IRS-1, PPAR-γ and LEP genes polymorphisms and growth traits in rabbits. Anim Biotechnol 2023;34:2391-2399. [PMID: 35767350 DOI: 10.1080/10495398.2022.2092743] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]

Lyu Y, Ren Y, Qu K, Quji S, Zhuzha B, Lei C, Chen N. Local ancestry and selection in admixed Sanjiang cattle. STRESS BIOLOGY 2023;3:30. [PMID: 37676416 PMCID: PMC10441984 DOI: 10.1007/s44154-023-00101-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 06/29/2023] [Indexed: 09/08/2023]

Abdelrahman M, Wang W, Shaukat A, Kulyar MFEA, Lv H, Abulaiti A, Yao Z, Ahmad MJ, Liang A, Yang L. Nutritional Modulation, Gut, and Omics Crosstalk in Ruminants. Animals (Basel) 2022;12:ani12080997. [PMID: 35454245 PMCID: PMC9029867 DOI: 10.3390/ani12080997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/31/2022] [Accepted: 04/05/2022] [Indexed: 11/30/2022] Open

Abstract

Simple Summary

Over the last decade, animal nutrition science has been significantly developed, supported by the great advancements in molecular technologies. For scientists, the present "feedomics and nutrigenomics" era continues to evolve and shape how research is designed, performed, and understood. The new omics interpretations have established a new point of view for the nutrition–gene interaction, integrating more comprehensive findings from animal physiology, molecular genetics, and biochemistry. In the ruminant model, this modern approach addresses rumen microbes as a critical intermediate that can deepen the studies of diet–gut interaction with host genomics. The present review discusses nutrigenomics’ and feedomics’ potential contribution to diminishing the knowledge gap about the DNA cellular activities of different nutrients. It also presents how nutritional management can influence the epigenetic pathway, considering the production type, life stage, and species for more sustainable ruminant nutrition strategies.

Abstract

Ruminant nutrition has significantly revolutionized a new and prodigious molecular approach in livestock sciences over the last decade. Wide-spectrum advances in DNA and RNA technologies and analysis have produced a wealth of data that have shifted the research threshold scheme to a more affluent level. Recently, the published literature has pointed out the nutrient roles in different cellular genomic alterations among different ruminant species, besides the interactions with other factors, such as age, type, and breed. Additionally, it has addressed rumen microbes within the gut health and productivity context, which has made interpreting homogenous evidence more complicated. As a more systematic approach, nutrigenomics can identify how genomics interacts with nutrition and other variables linked to animal performance. Such findings should contribute to crystallizing powerful interpretations correlating feeding management with ruminant production and health through genomics. This review will present a road-mapping discussion of promising trends in ruminant nutrigenomics as a reference for phenotype expression through multi-level omics changes.

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Affiliation(s)

Mohamed Abdelrahman Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.) Animal Production Department, Faculty of Agriculture, Assuit University, Asyut 71515, Egypt
Wei Wang Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.)
Aftab Shaukat Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.)
Muhammad Fakhar-e-Alam Kulyar College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China;
Haimiao Lv Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.)
Adili Abulaiti Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.)
Zhiqiu Yao Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.)
Muhammad Jamil Ahmad Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.)
Aixin Liang Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.) National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Huazhong Agricultural University, Wuhan 430070, China
Liguo Yang Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China; (M.A.); (W.W.); (A.S.); (H.L.); (A.A.); (Z.Y.); (M.J.A.); (A.L.) National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Huazhong Agricultural University, Wuhan 430070, China Correspondence: ; Tel.: +86-138-7105-6592

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Ma J, Gao X, Li J, Gao H, Wang Z, Zhang L, Xu L, Gao H, Li H, Wang Y, Zhu B, Cai W, Wang C, Chen Y. Assessing the Genetic Background and Selection Signatures of Huaxi Cattle Using High-Density SNP Array. Animals (Basel) 2021;11:ani11123469. [PMID: 34944246 PMCID: PMC8698132 DOI: 10.3390/ani11123469] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 11/24/2021] [Accepted: 12/02/2021] [Indexed: 11/16/2022] Open

Affiliation(s)

Jun Ma Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Xue Gao Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Junya Li Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Huijiang Gao Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Zezhao Wang Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Lupei Zhang Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Lingyang Xu Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Han Gao Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Hongwei Li Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Yahui Wang Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Bo Zhu Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Wentao Cai Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
Congyong Wang Beijing Lianyu Beef Cattle Breeding Technology Limited Company, Beijing 100193, China;
Yan Chen Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.) Correspondence:

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Li Z, Liu X, Li Y, Wang W, Wang N, Xiao F, Gao H, Guo H, Li H, Wang S. Chicken C/EBPζ gene: Expression profiles, association analysis, and identification of functional variants for abdominal fat. Domest Anim Endocrinol 2021;76:106631. [PMID: 33979717 DOI: 10.1016/j.domaniend.2021.106631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 04/06/2021] [Accepted: 04/06/2021] [Indexed: 10/21/2022]

Abstract

CCAAT enhancer binding protein ζ (C/EBPζ) plays an important role in adipose proliferation and differentiation in humans. However, very little is known about the effect of C/EBPζ on the growth and development of adipose tissues in domesticated animals. The present study attempted to investigate the mRNA expression profiles of chicken C/EBPζ in a variety of tissues; analyze the association of its variants with abdominal fat; and identify the functional variants for abdominal fat. The tissue expression profiles revealed that C/EBPζ was highly expressed in 19 tissues obtained from broilers. The expression level of C/EBPζ in fat broilers was significantly lower than that in lean broilers in the duodenum, ileum, cecum, kidney, pectoral muscle, and liver (P < 0.05). Among 170 polymorphic loci of C/EBPζ, 9 single nucleotide polymorphisms (SNPs) demonstrated a significant association with chicken abdominal fat traits (P < 0.05) as well as significant discrepancies in their allelic frequencies between fat and lean birds. Particularly, only C/EBPζ g.7085A>C exhibited significant correlation with abdominal fat traits (P < 0.00015) using the Bonferroni method. The results revealed that, in preadipocyte immortalized cells (ICPI), the luciferase activity of the A allele of g.7085A>C locus was remarkably stronger than that of the C allele (P < 0.05). In silico analysis showed that g.7085A>C locus was located in the binding region of the transcription factor SOX5, which possesses the ability to transform C/EBPζ transcription efficiency through binding with SOX5. In summary, the data obtained from this study suggested that C/EBPζ is a potential candidate gene responsible for abdominal fat deposition in chicken and that g.7085A>C is a functional SNP that can be promisingly leveraged for marker assisted selection (MAS) in future chicken breeding programs.

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Affiliation(s)

Z Li Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
X Liu Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
Y Li Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
W Wang Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
N Wang Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
F Xiao Fujian Sunnzer Biotechnology Development Co., Ltd, 354100, Guangze, Fujian Province, China
H Gao Fujian Sunnzer Biotechnology Development Co., Ltd, 354100, Guangze, Fujian Province, China
H Guo Fujian Sunnzer Biotechnology Development Co., Ltd, 354100, Guangze, Fujian Province, China
H Li Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
S Wang Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China.

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Cao H, Wen Y, Xu X, Liu K, Liu H, Tan Y, Zhou W, Mao H, Dong X, Xu N, Yin Z. Investigation of the CEBPA gene expression pattern and association analysis of its polymorphisms with meat quality traits in chickens. Anim Biotechnol 2020;33:448-456. [PMID: 32776801 DOI: 10.1080/10495398.2020.1803343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]

Wang X, Cheng J, Qin W, Chen H, Chen G, Shang X, Zhang M, Balsai N, Chen H. Polymorphisms in 5' proximal regulating region of THRSP gene are associated with fat production in pigs. 3 Biotech 2020;10:267. [PMID: 32509500 DOI: 10.1007/s13205-020-02266-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 05/18/2020] [Indexed: 01/17/2023] Open

Grigoletto L, Ferraz JBS, Oliveira HR, Eler JP, Bussiman FO, Abreu Silva BC, Baldi F, Brito LF. Genetic Architecture of Carcass and Meat Quality Traits in Montana Tropical^® Composite Beef Cattle. Front Genet 2020;11:123. [PMID: 32180796 PMCID: PMC7057717 DOI: 10.3389/fgene.2020.00123] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 02/03/2020] [Indexed: 12/16/2022] Open

Abstract

The Montana Tropical^® Composite is a recently developed beef cattle population that is rapidly expanding in Brazil and other tropical countries. This is mainly due to its improved meat quality and adaptation to tropical climate conditions compared to Zebu and Taurine cattle breeds, respectively. This study aimed to investigate the genetic architecture of ultrasound-based carcass and meat quality traits in Montana Tropical^® Composite beef cattle. Therefore, we estimated variance components and genetic parameters and performed genome-wide association studies using the weighted single-step Genomic Best Linear Unbiased Prediction (GBLUP) approach. A pedigree dataset containing 28,480 animals was used, in which 1,436 were genotyped using a moderate-density Single Nucleotide Polymorphism panel (30K; 30,105 SNPs). A total of 9,358, 5,768, 7,996, and 1,972 phenotypic records for the traits Longissimus muscle area (LMA), backfat thickness (BFT), rump fat thickness (RFT), and for marbling score (MARB), respectively, were used for the analyses. Moderate to high heritability estimates were obtained and ranged from 0.16 ± 0.03 (RFT) to 0.33 ± 0.05 (MARB). A high genetic correlation was observed between BFT and RFT (0.97 ± 0.02), suggesting that a similar set of genes affects both traits. The most relevant genomic regions associated with LMA, BFT, RFT, and MARB were found on BTA10 (5.4–5.8 Mb), BTA27 (25.2–25.5 Mb), BTA18 (60.6–61.0 Mb), and BTA21 (14.8–15.4 Mb). Two overlapping genomic regions were identified for RFT and MARB (BTA13:47.9–48.1 Mb) and for BFT and RFT (BTA13:61.5–62.3 Mb). Candidate genes identified in this study, including PLAG1, LYN, WWOX, and PLAGL2, were previously reported to be associated with growth, stature, skeletal muscle growth, fat thickness, and fatty acid composition. Our results indicate that ultrasound-based carcass and meat quality traits in the Montana Tropical^® Composite beef cattle are heritable, and therefore, can be improved through selective breeding. In addition, various novel and already known genomic regions related to these traits were identified, which contribute to a better understanding of the underlying genetic background of LMA, BFT, RFT, and MARB in the Montana Tropical Composite population.

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Do DN, Schenkel F, Miglior F, Zhao X, Ibeagha-Awemu EM. Targeted genotyping to identify potential functional variants associated with cholesterol content in bovine milk. Anim Genet 2020;51:200-209. [PMID: 31913546 DOI: 10.1111/age.12901] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 12/03/2019] [Accepted: 12/10/2019] [Indexed: 01/04/2023]

Abstract

High blood cholesterol concentration, mainly caused by high dietary cholesterol, is a potential risk factor for human health. Dairy products are important sources of human dietary cholesterol intake. Therefore, monitoring bovine milk cholesterol concentration is important for human health benefit. Genetic selection for improvement of cow milk cholesterol content requires understanding of the genetics of milk cholesterol. For this purpose, we performed analyses of additive and dominance effects of 126 potentially functional SNPs within 43 candidate genes with milk cholesterol content [expressed as mg of cholesterol in 100 g of fat (CHL_fat) or in 100 mg of milk (CHL_milk)]. The additive and dominance effects of SNPs rs380643365 in AGPAT1 (P = 0.04) and rs134357240 in SOAT1 (P = 0.035) genes associated significantly with CHL_fat. Moreover, five (rs109326954 and rs523413537 in DGAT1, rs109376747 in LDLR, rs42781651 in FAM198B and rs109967779 in ACAT2) and four (rs137347384 in RBM19, rs109376747 in LDLR, rs42016945 in PPARG and rs110862179 in SCAP) SNPs were significantly associated with CHL_milk (P < 0.05) based on additive and dominance effect analyses respectively. Rs109326954 and rs523413537 in DGAT1 explained a considerable portion of the phenotypic variance of CHL_milk (7.54 and 6.84% respectively), and might be useful in selection programs for reduced milk cholesterol content. Several significantly associated SNPs were in genes (such as ACAT2 and LDLR) involved in cholesterol metabolism in the liver or cholesterol transport, suggesting multiple mechanisms regulating milk cholesterol content. Nine and seven SNPs identified by additive or dominance effect analyses associated significantly with milk yield and fat yield respectively. Further analyses are required to better understand the consequences of these variants and their potential use in genomic selection of the studied traits.

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Fonseca PADS, Id-Lahoucine S, Reverter A, Medrano JF, Fortes MS, Casellas J, Miglior F, Brito L, Carvalho MRS, Schenkel FS, Nguyen LT, Porto-Neto LR, Thomas MG, Cánovas A. Combining multi-OMICs information to identify key-regulator genes for pleiotropic effect on fertility and production traits in beef cattle. PLoS One 2018;13:e0205295. [PMID: 30335783 PMCID: PMC6193631 DOI: 10.1371/journal.pone.0205295] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Accepted: 09/21/2018] [Indexed: 12/21/2022] Open

Abstract

The identification of biological processes related to the regulation of complex traits is a difficult task. Commonly, complex traits are regulated through a multitude of genes contributing each to a small part of the total genetic variance. Additionally, some loci can simultaneously regulate several complex traits, a phenomenon defined as pleiotropy. The lack of understanding on the biological processes responsible for the regulation of these traits results in the decrease of selection efficiency and the selection of undesirable hitchhiking effects. The identification of pleiotropic key-regulator genes can assist in developing important tools for investigating biological processes underlying complex traits. A multi-breed and multi-OMICs approach was applied to study the pleiotropic effects of key-regulator genes using three independent beef cattle populations evaluated for fertility traits. A pleiotropic map for 32 traits related to growth, feed efficiency, carcass and meat quality, and reproduction was used to identify genes shared among the different populations and breeds in pleiotropic regions. Furthermore, data-mining analyses were performed using the Cattle QTL database (CattleQTLdb) to identify the QTL category annotated in the regions around the genes shared among breeds. This approach allowed the identification of a main gene network (composed of 38 genes) shared among breeds. This gene network was significantly associated with thyroid activity, among other biological processes, and displayed a high regulatory potential. In addition, it was possible to identify genes with pleiotropic effects related to crucial biological processes that regulate economically relevant traits associated with fertility, production and health, such as MYC, PPARG, GSK3B, TG and IYD genes. These genes will be further investigated to better understand the biological processes involved in the expression of complex traits and assist in the identification of functional variants associated with undesirable phenotypes, such as decreased fertility, poor feed efficiency and negative energetic balance.

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Affiliation(s)

Pablo Augusto de Souza Fonseca University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, Guelph, Ontario, Canada Universidade Federal de Minas Gerais, Departamento de Biologia Geral, Belo Horizonte, Minas Gerais, Brazil
Samir Id-Lahoucine University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, Guelph, Ontario, Canada
Antonio Reverter CSIRO Agriculture and Food, Queensland Bioscience Precinct, Brisbane, Queensland, Australia
Juan F. Medrano University of California-Davis, Department of Animal Science, Davis, California, United States of America
Marina S. Fortes The University of Queensland, School of Chemistry and Molecular Biosciences, Brisbane, Queensland, Australia
Joaquim Casellas Universitat Autònoma de Barcelona, Departament de Ciència Animal i dels Aliments, Barcelona, Bellaterra, Barcelona, Spain
Filippo Miglior University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, Guelph, Ontario, Canada Canadian Dairy Network, Guelph, Ontario, Canada
Luiz Brito University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, Guelph, Ontario, Canada
Maria Raquel S. Carvalho Universidade Federal de Minas Gerais, Departamento de Biologia Geral, Belo Horizonte, Minas Gerais, Brazil
Flávio S. Schenkel University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, Guelph, Ontario, Canada
Loan T. Nguyen The University of Queensland, School of Chemistry and Molecular Biosciences, Brisbane, Queensland, Australia
Laercio R. Porto-Neto CSIRO Agriculture and Food, Queensland Bioscience Precinct, Brisbane, Queensland, Australia
Milton G. Thomas Colorado State University, Department of Animal Science, Fort-Colins, Colorado, United States of America
Angela Cánovas University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, Guelph, Ontario, Canada * E-mail:

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