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George L, Alex R, Gowane G, Vohra V, Joshi P, Kumar R, Verma A. Weighted single step GWAS reveals genomic regions associated with economic traits in Murrah buffaloes. Anim Biotechnol 2024; 35:2319622. [PMID: 38437001 DOI: 10.1080/10495398.2024.2319622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
The objective of the present study was to identify genomic regions influencing economic traits in Murrah buffaloes using weighted single step Genome Wide Association Analysis (WssGWAS). Data on 2000 animals, out of which 120 were genotyped using a double digest Restriction site Associated DNA (ddRAD) sequencing approach. The phenotypic data were collected from NDRI, India, on growth traits, viz., body weight at 6M (month), 12M, 18M and 24M, production traits like 305D (day) milk yield, lactation length (LL) and dry period (DP) and reproduction traits like age at first calving (AFC), calving interval (CI) and first service period (FSP). The biallelic genotypic data consisted of 49353 markers post-quality check. The heritability estimates were moderate to high, low to moderate, low for growth, production, reproduction traits, respectively. Important genomic regions explaining more than 0.5% of the total additive genetic variance explained by 30 adjacent SNPs were selected for further analysis of candidate genes. In this study, 105 genomic regions were associated with growth, 35 genomic regions with production and 42 window regions with reproduction traits. Different candidate genes were identified in these genomic regions, of which important are OSBPL8, NAP1L1 for growth, CNTNAP2 for production and ILDR2, TADA1 and POGK for reproduction traits.
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Affiliation(s)
- Linda George
- National Dairy Research Institute, Karnal, India
| | - Rani Alex
- National Dairy Research Institute, Karnal, India
| | - Gopal Gowane
- National Dairy Research Institute, Karnal, India
| | - Vikas Vohra
- National Dairy Research Institute, Karnal, India
| | - Pooja Joshi
- National Dairy Research Institute, Karnal, India
| | - Ravi Kumar
- National Dairy Research Institute, Karnal, India
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Ristanic M, Zorc M, Glavinic U, Stevanovic J, Blagojevic J, Maletic M, Stanimirovic Z. Genome-Wide Analysis of Milk Production Traits and Selection Signatures in Serbian Holstein-Friesian Cattle. Animals (Basel) 2024; 14:669. [PMID: 38473054 DOI: 10.3390/ani14050669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/05/2024] [Accepted: 02/14/2024] [Indexed: 03/14/2024] Open
Abstract
To improve the genomic evaluation of milk-related traits in Holstein-Friesian (HF) cattle it is essential to identify the associated candidate genes. Novel SNP-based analyses, such as the genetic mapping of inherited diseases, GWAS, and genomic selection, have led to a new era of research. The aim of this study was to analyze the association of each individual SNP in Serbian HF cattle with milk production traits and inbreeding levels. The SNP 60 K chip Axiom Bovine BovMDv3 was deployed for the genotyping of 334 HF cows. The obtained genomic results, together with the collected phenotypic data, were used for a GWAS. Moreover, the identification of ROH segments was performed and served for inbreeding coefficient evaluation and ROH island detection. Using a GWAS, a polymorphism, rs110619097 (located in the intron of the CTNNA3 gene), was detected to be significantly (p < 0.01) associated with the milk protein concentration in the first lactation (adjusted to 305 days). The average genomic inbreeding value (FROH) was 0.079. ROH islands were discovered in proximity to genes associated with milk production traits and genomic regions under selection pressure for other economically important traits of dairy cattle. The findings of this pilot study provide useful information for a better understanding of the genetic architecture of milk production traits in Serbian HF dairy cows and can be used to improve lactation performances in Serbian HF cattle breeding programs.
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Affiliation(s)
- Marko Ristanic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Minja Zorc
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Groblje 3, 1000 Ljubljana, Slovenia
| | - Uros Glavinic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Jevrosima Stevanovic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Jovan Blagojevic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Milan Maletic
- Department of Reproduction, Fertility and Artificial Insemination, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Zoran Stanimirovic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
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Pathak RK, Kim JM. Veterinary systems biology for bridging the phenotype-genotype gap via computational modeling for disease epidemiology and animal welfare. Brief Bioinform 2024; 25:bbae025. [PMID: 38343323 PMCID: PMC10859662 DOI: 10.1093/bib/bbae025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 01/02/2024] [Accepted: 01/15/2024] [Indexed: 02/15/2024] Open
Abstract
Veterinary systems biology is an innovative approach that integrates biological data at the molecular and cellular levels, allowing for a more extensive understanding of the interactions and functions of complex biological systems in livestock and veterinary science. It has tremendous potential to integrate multi-omics data with the support of vetinformatics resources for bridging the phenotype-genotype gap via computational modeling. To understand the dynamic behaviors of complex systems, computational models are frequently used. It facilitates a comprehensive understanding of how a host system defends itself against a pathogen attack or operates when the pathogen compromises the host's immune system. In this context, various approaches, such as systems immunology, network pharmacology, vaccinology and immunoinformatics, can be employed to effectively investigate vaccines and drugs. By utilizing this approach, we can ensure the health of livestock. This is beneficial not only for animal welfare but also for human health and environmental well-being. Therefore, the current review offers a detailed summary of systems biology advancements utilized in veterinary sciences, demonstrating the potential of the holistic approach in disease epidemiology, animal welfare and productivity.
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Affiliation(s)
- Rajesh Kumar Pathak
- Department of Animal Science and Technology, Chung-Ang University, Anseong-si, Gyeonggi-do 17546, Republic of Korea
| | - Jun-Mo Kim
- Department of Animal Science and Technology, Chung-Ang University, Anseong-si, Gyeonggi-do 17546, Republic of Korea
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Mir MA, Ahmad T, Gupta ID, Magotra A, Singh AP, Singh M, Pandit A, Muzhupilezhikethu Raveendran V. Association of polymorphisms in exon 6 and 3′-untranslated region of the OLR1 gene with milk production traits in Sahiwal cattle. JOURNAL OF APPLIED ANIMAL RESEARCH 2023. [DOI: 10.1080/09712119.2023.2167822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Mohsin Ayoub Mir
- Division of Animal Genetics and Breeding, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
| | - Tavsief Ahmad
- Division of Animal Genetics and Breeding, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
| | - Ishwar Dayal Gupta
- Animal Genetics and Breeding Division, ICAR-National Dairy Research Institute, Karnal, India
| | - Ankit Magotra
- Animal Genetics and Breeding Division, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar, India
| | - Arun Pratap Singh
- Department of Livestock Production and Management, Krishi Vigyan Kendra, Ajmer, India
| | | | - Arif Pandit
- Assistant Director Research, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
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Ghiasi H, Khaldari M, Taherkhani R. Identification of hub genes associated with somatic cell score in dairy cow. Trop Anim Health Prod 2023; 55:349. [PMID: 37796357 DOI: 10.1007/s11250-023-03766-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 09/19/2023] [Indexed: 10/06/2023]
Abstract
CONTEXT Somatic cell count (SCC) is used as an indicator of udder health. The log transformation of SCC is called somatic cell score (SCS). AIM Several QTL and genes have been identified that are associated with SCS. This study aimed to identify the most important genes associated with SCS. METHODS This study compiled 168 genes that were reported to be significantly linked to SCS. Pathway analysis and network analysis were used to identify hub genes. KEY RESULTS Pathway analysis of these genes identified 73 gene ontology (GO) terms associated with SCS. These GO terms are associated with molecular function, biological processes, and cellular components, and the identified pathways are directly or indirectly linked with the immune system. In this study, a gene network was constructed, and from this network, the 17 hub genes (CD4, CXCL8, TLR4, STAT1, TLR2, CXCL9, CCR2, IGF1, LEP, SPP1, GH1, GHR, VWF, TNFSF11, IL10RA, NOD2, and PDGFRB) associated to SCS were identified. The subnetwork analysis yielded 10 clusters, with cluster 1 containing all identified hub genes (except for the VWF gene). CONCLUSION Most hub genes and pathways identified in our study were mainly involved in inflammatory and cytokine responses. IMPLICATIONS Result obtained in current study provides knowledge of the genetic basis and biological mechanisms controlling SCS. Therefore, the identified hub genes may be regarded as the main gene for the genomic selection of mastitis resistance.
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Affiliation(s)
- Heydar Ghiasi
- Department of Animal Science, Faculty of Agricultural Science, Payame Noor University, Tehran, 19395-4697, Iran.
| | - Majid Khaldari
- Department of Animal Science, Faculty of Agriculture, Lorestan University, Khorram-Abad, Iran
| | - Reza Taherkhani
- Department of Animal Science, Faculty of Agricultural Science, Payame Noor University, Tehran, 19395-4697, Iran
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Bekele R, Taye M, Abebe G, Meseret S. Genomic Regions and Candidate Genes Associated with Milk Production Traits in Holstein and Its Crossbred Cattle: A Review. Int J Genomics 2023; 2023:8497453. [PMID: 37547753 PMCID: PMC10400298 DOI: 10.1155/2023/8497453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 05/09/2023] [Accepted: 07/19/2023] [Indexed: 08/08/2023] Open
Abstract
Genome-wide association studies (GWAS) are a powerful tool for identifying genomic regions and causative genes associated with economically important traits in dairy cattle, particularly complex traits, such as milk production. This is possible due to advances in next-generation sequencing technology. This review summarized information on identified candidate genes and genomic regions associated with milk production traits in Holstein and its crossbreds from various regions of the world. Milk production traits are important in dairy cattle breeding programs because of their direct economic impact on the industry and their close relationship with nutritional requirements. GWAS has been used in a large number of studies to identify genomic regions and candidate genes associated with milk production traits in dairy cattle. Many genomic regions and candidate genes have already been identified in Holstein and its crossbreds. Genes and single nucleotide polymorphisms (SNPs) that significantly affect milk yield (MY) were found in all autosomal chromosomes except chromosomes 27 and 29. Half of the reported SNPs associated with fat yield and fat percentage were found on chromosome 14. However, a large number of significant SNPs for protein yield (PY) and protein percentage were found on chromosomes 1, 5, and 20. Approximately 155 SNPs with significant influence on multiple milk production traits have been identified. Several promising candidate genes, including diacylglycerol O-acyltransferase 1, plectin, Rho GTPase activating protein 39, protein phosphatase 1 regulatory subunit 16A, and sphingomyelin phosphodiesterase 5 were found to have pleiotropic effects on all five milk production traits. Thus, to improve milk production traits it is of practical relevance to focus on significant SNPs and pleiotropic genes frequently found to affect multiple milk production traits.
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Affiliation(s)
- R. Bekele
- School of Animal and Range Sciences, College of Agriculture, Hawassa University, P.O. Box 5, Hawassa, Ethiopia
- Department of Animal Science, College of Agriculture and Natural Resource Sciences, Debre Berhan University, P.O. Box 445, Debre Berhan, Ethiopia
| | - M. Taye
- School of Animal and Range Sciences, College of Agriculture, Hawassa University, P.O. Box 5, Hawassa, Ethiopia
| | - G. Abebe
- School of Animal and Range Sciences, College of Agriculture, Hawassa University, P.O. Box 5, Hawassa, Ethiopia
| | - S. Meseret
- Livestock Genetics, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
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Pathak RK, Kim JM. Vetinformatics from functional genomics to drug discovery: Insights into decoding complex molecular mechanisms of livestock systems in veterinary science. Front Vet Sci 2022; 9:1008728. [PMID: 36439342 PMCID: PMC9691653 DOI: 10.3389/fvets.2022.1008728] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 10/31/2022] [Indexed: 09/28/2023] Open
Abstract
Having played important roles in human growth and development, livestock animals are regarded as integral parts of society. However, industrialization has depleted natural resources and exacerbated climate change worldwide, spurring the emergence of various diseases that reduce livestock productivity. Meanwhile, a growing human population demands sufficient food to meet their needs, necessitating innovations in veterinary sciences that increase productivity both quantitatively and qualitatively. We have been able to address various challenges facing veterinary and farm systems with new scientific and technological advances, which might open new opportunities for research. Recent breakthroughs in multi-omics platforms have produced a wealth of genetic and genomic data for livestock that must be converted into knowledge for breeding, disease prevention and management, productivity, and sustainability. Vetinformatics is regarded as a new bioinformatics research concept or approach that is revolutionizing the field of veterinary science. It employs an interdisciplinary approach to understand the complex molecular mechanisms of animal systems in order to expedite veterinary research, ensuring food and nutritional security. This review article highlights the background, recent advances, challenges, opportunities, and application of vetinformatics for quality veterinary services.
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Affiliation(s)
| | - Jun-Mo Kim
- Department of Animal Science and Technology, Chung-Ang University, Anseong-si, South Korea
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Wang P, Li X, Zhu Y, Wei J, Zhang C, Kong Q, Nie X, Zhang Q, Wang Z. Genome-wide association analysis of milk production, somatic cell score, and body conformation traits in Holstein cows. Front Vet Sci 2022; 9:932034. [PMID: 36268046 PMCID: PMC9578681 DOI: 10.3389/fvets.2022.932034] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 09/09/2022] [Indexed: 11/04/2022] Open
Abstract
Milk production and body conformation traits are critical economic traits for dairy cows. To understand the basic genetic structure for those traits, a genome wide association study was performed on milk yield, milk fat yield, milk fat percentage, milk protein yield, milk protein percentage, somatic cell score, body form composite index, daily capacity composite index, feed, and leg conformation traits, based on the Illumina Bovine HD100k BeadChip. A total of 57, 12 and 26 SNPs were found to be related to the milk production, somatic cell score and body conformation traits in the Holstein cattle. Genes with pleiotropic effect were also found in this study. Seven significant SNPs were associated with multi-traits and were located on the PLEC, PLEKHA5, TONSL, PTGER4, and LCORL genes. In addition, some important candidate genes, like GPAT3, CEBPB, AGO2, SLC37A1, and FNDC3B, were found to participate in fat metabolism or mammary gland development. These results can be used as candidate genes for milk production, somatic cell score, and body conformation traits of Holstein cows, and are helpful for further gene function analysis to improve milk production and quality.
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Affiliation(s)
- Peng Wang
- Heilongjiang Animal Husbandry Service, Harbin, China
| | - Xue Li
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China,Bioinformatics Center, Northeast Agricultural University, Harbin, China
| | - Yihao Zhu
- Heilongjiang Animal Husbandry Service, Harbin, China
| | - Jiani Wei
- School of mathematics, University of Edinburgh, Edinburgh, United Kingdom
| | - Chaoxin Zhang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China,Bioinformatics Center, Northeast Agricultural University, Harbin, China
| | - Qingfang Kong
- Heilongjiang Animal Husbandry Service, Harbin, China
| | - Xu Nie
- Heilongjiang Animal Husbandry Service, Harbin, China
| | - Qi Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhipeng Wang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China,Bioinformatics Center, Northeast Agricultural University, Harbin, China,*Correspondence: Zhipeng Wang
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Unraveling structural and conformational dynamics of DGAT1 missense nsSNPs in dairy cattle. Sci Rep 2022; 12:4873. [PMID: 35318385 PMCID: PMC8940929 DOI: 10.1038/s41598-022-08833-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 02/28/2022] [Indexed: 11/28/2022] Open
Abstract
Cattle are domestic animals that have been nourishing humans for thousands of years. Milk from cattle represents a key source of high-quality protein, fat, and other nutrients. The nutritional value of milk and dairy products is closely associated with the fat content, providing up to 30% of the total fat consumed in the human diet. The fat content in cattle milk represents a major concern for the scientific community due to its association with human health. The relationship between milk fat content and diacylglycerol o-acyltransferase 1 gene (DGAT1) is well described in literature. Several studies demonstrated the difference in fat contents and other milk production traits in a wide range of cattle breeds, to be associated with missense non-synonymous single nucleotide polymorphisms (nsSNPs) of the DGAT1 gene. As a result, an nsSNPs analysis is crucial for unraveling the DGAT1 structural and conformational dynamics linked to milk fat content. DGAT1-nsSNPs are yet to be studied in terms of their structural and functional impact. Therefore, state-of-the-art computational and structural genomic methods were used to analyze five selected variants (W128R, W214R, C215G, P245R, and W459G), along with the wild type DGAT1. Significant structural and conformational changes in the variants were observed. We illustrate how single amino acid substitutions affect DGAT1 function, how this contributes to our understanding of the molecular basis of variations in DGAT1, and ultimately its impact in improving fat quality in milk.
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