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Raja TV, Alex R, Singh U, Kumar S, Das AK, Sengar G, Singh AK. Genome wide mining of SNPs and INDELs through ddRAD sequencing in Sahiwal cattle. Anim Biotechnol 2023; 34:4885-4899. [PMID: 37093232 DOI: 10.1080/10495398.2023.2200517] [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: 04/25/2023]
Abstract
The study was conducted in Sahiwal cattle for genome wide identification and annotation of single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs) in Sahiwal cattle. The double digest restriction-site associated DNA (ddRAD) sequencing, a reduced representation method was used for the identification of variants at nucleotide level. A total of 1,615,211 variants were identified at RD10 and Q30 consisting of 1,480,930 SNPs and 134,281 INDELs with respect to the Bos taurus reference genome. The SNPs were annotated for their location, impact and functional class. The SNPs identified in Sahiwal cattle were found to be associated with a total of 26,229 genes. A total of 1819 SNPs were annotated for 209 candidate genes associated with different production and reproduction traits. The variants identified in the present study may be useful to strengthen the existing bovine SNP chips for reducing the biasness over the taurine cattle breeds. The diversity analysis provides the insight of the genetic architecture of the Sahiwal population Studied. The large genetic variations identified at the nucleotide level provide ample scope for implementing an effective and efficient breed improvement programme for increasing the productivity of Sahiwal cattle.
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Affiliation(s)
- Thiruvothur Venkatesan Raja
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut Cantt, Uttar Pradesh, India
| | - Rani Alex
- ICAR-National Dairy Research Institute, Karnal, Haryana, India
| | - Umesh Singh
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut Cantt, Uttar Pradesh, India
| | - Sushil Kumar
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut Cantt, Uttar Pradesh, India
| | - Achintya Kumar Das
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut Cantt, Uttar Pradesh, India
| | - Gyanendra Sengar
- National Research Centre on Pigs, Rani (Near Airport), Guwahati, Assam, India
| | - Amit Kumar Singh
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut Cantt, Uttar Pradesh, India
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Raja TV, Alex R, Singh U, Kumar S, Das AK, Sengar G, Singh AK, Ghosh A, Saha S, Mitra A. Genome-wide identification and annotation of SNPs for economically important traits in Frieswal™, newly evolved crossbred cattle of India. 3 Biotech 2023; 13:310. [PMID: 37621321 PMCID: PMC10444711 DOI: 10.1007/s13205-023-03701-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 06/26/2023] [Indexed: 08/26/2023] Open
Abstract
The Frieswal™ is a crossbred cattle evolved by ICAR-Central Institute for Research on Cattle utilizing more than 15,000 cattle maintained at more than 37 military farms spread all over the agro-climatic regions of the country. The ddRAD sequencing method was used to identify and annotate the SNPs and INDELs. The results of variant calling revealed 1,487,851 SNPs and 128,175 INDELs at a read depth of 10. A total of 3,775,079 effects were identified, and majority (66.41%) of the effects were in the intron region of the genome followed by intergenic (21.87%). Majority (99.18%) of the variants had the modifier effect. The results revealed a higher magnitude of transitions as compared to the transversion. The classification of SNPs by functional class revealed a majority of missense (43%) and silent (56%) effects. Out of 26,278 genes identified, 1841 SNPs were annotated in 207 candidate genes responsible for various milk production and reproduction traits. The observed heterozygosity was 0.2804 against the expected heterozygosity value of 0.2978. The overall average inbreeding coefficient (FIS) was 0.0604. The pathway analysis revealed that the prolactin signaling pathway (GO:0038161) was significant biological process complete for both milk production and reproduction traits. The SNP variations can be effectively used as markers for early and accurate identification of the QTLs and for formulating an efficient and effective breed improvement program in Frieswal™ cattle. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-023-03701-0.
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Affiliation(s)
- Thiruvothur Venkatesan Raja
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut, Uttar Pradesh 650 001 India
| | - Rani Alex
- National Dairy Research Institute, Karnal, Haryana India
| | - Umesh Singh
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut, Uttar Pradesh 650 001 India
| | - Sushil Kumar
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut, Uttar Pradesh 650 001 India
| | - Achintya Kumar Das
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut, Uttar Pradesh 650 001 India
| | - Gyanendra Sengar
- National Research Centre on Pigs, Rani (Near Airport), Guwahati, Assam 781 131 India
| | - Amit Kumar Singh
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut, Uttar Pradesh 650 001 India
| | - Abhirupa Ghosh
- Division of Bioinformatics, Bose Institute, Unified Campus Salt Lake, College More, EN Block, Sector V, Kolkata, West Bengal 700091 India
| | - Sudipto Saha
- Division of Bioinformatics, Bose Institute, Unified Campus Salt Lake, College More, EN Block, Sector V, Kolkata, West Bengal 700091 India
| | - Abhijit Mitra
- Molecular Genetics Laboratory, Cattle Genetics and Breeding Division, ICAR-Central Institute for Research on Cattle, Meerut, Uttar Pradesh 650 001 India
- Present Address: Animal Husbandry Commissioner, Department of Animal Husbandry and Dairying, Government of India, New Delhi, India
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Bakhshaei F, Sharifiyazdi H, Rowshan-Ghasrodashti A, Zare HR, Mirzaei A, Nazifi S. Polymorphism in neutrophil cytosolic factor 4 (NCF4) of dairy cows had mastitis in previous lactations, and the relationship with the respiratory burst. Res Vet Sci 2023; 160:39-44. [PMID: 37263099 DOI: 10.1016/j.rvsc.2023.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 05/09/2023] [Accepted: 05/11/2023] [Indexed: 06/03/2023]
Abstract
Nicotinamide adenine dinucleotide phosphate oxidase (NADPH oxidase), as a key factor in innate immunity, consists of several components, one of them is p40phox which is encoded by neutrophil cytosolic factor 4 (NCF4). Respiratory burst and reactive oxygen species (ROS) production are antimicrobial mechanisms associated with NADPH oxidase. This study evaluated the effects of g.18174 A > G and g.18270C > T single-nucleotide polymorphisms (SNP) in NCF4 on bovine mastitis and the respiratory burst capacity of neutrophils. SNPs of 160 dairy cattle were determined using a novel PCR-RFLP protocol by employing restriction enzymes, MboI and FokI. Also, the flow cytometry measured respiratory burst in 82 blood samples. Our results indicated that only g.18174 A > G SNP reduced the respiratory burst capacity. However, both SNPs were not significantly correlated with clinical mastitis. We concluded that g.18174 A > G decreases the function of NADPH oxidase. However, both SNPs were not significantly correlated with clinical mastitis.
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Affiliation(s)
- Farnoosh Bakhshaei
- Department of Clinical Sciences, School of Veterinary Medicine, Shiraz University, Shiraz, Iran
| | - Hassan Sharifiyazdi
- Department of Clinical Sciences, School of Veterinary Medicine, Shiraz University, Shiraz, Iran
| | - Abbas Rowshan-Ghasrodashti
- Large Animal Internal Medicine, Department of Clinical Studies, School of Veterinary Medicine, Islamic Azad University, Kazerun Branch, Shiraz, Iran
| | - Hamid-Reza Zare
- Department of Immunology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran; Department of Flowcytometry, Sa'adati Pathobiology Laboratory, Shiraz, Iran
| | - Abdollah Mirzaei
- Department of Clinical Sciences, School of Veterinary Medicine, Shiraz University, Shiraz, Iran
| | - Saeed Nazifi
- Department of Clinical Sciences, School of Veterinary Medicine, Shiraz University, Shiraz, Iran.
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Khan MZ, Wang J, Ma Y, Chen T, Ma M, Ullah Q, Khan IM, Khan A, Cao Z, Liu S. Genetic polymorphisms in immune- and inflammation-associated genes and their association with bovine mastitis resistance/susceptibility. Front Immunol 2023; 14:1082144. [PMID: 36911690 PMCID: PMC9997099 DOI: 10.3389/fimmu.2023.1082144] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 01/06/2023] [Indexed: 02/25/2023] Open
Abstract
Bovine mastitis, the inflammation of the mammary gland, is a contagious disease characterized by chemical and physical changes in milk and pathological changes in udder tissues. Depressed immunity and higher expression of inflammatory cytokines with an elevated milk somatic cell count can be observed during mastitis in dairy cattle. The use of somatic cell count (SCC) and somatic cell score (SCS) as correlated traits in the indirect selection of animals against mastitis resistance is in progress globally. Traditional breeding for mastitis resistance seems difficult because of the low heritability (0.10-0.16) of SCC/SCS and clinical mastitis. Thus, genetic-marker-selective breeding to improve host genetics has attracted considerable attention worldwide. Moreover, genomic selection has been found to be an effective and fast method of screening for dairy cattle that are genetically resistant and susceptible to mastitis at a very early age. The current review discusses and summarizes the candidate gene approach using polymorphisms in immune- and inflammation-linked genes (CD4, CD14, CD46, TRAPPC9, JAK2, Tf, Lf, TLRs, CXCL8, CXCR1, CXCR2, C4A, C5, MASP2, MBL1, MBL2, LBP, NCF1, NCF4, MASP2, A2M, and CLU, etc.) and their related signaling pathways (Staphylococcus aureus infection signaling, Toll-like receptor signaling, NF-kappa B signaling pathway, Cytokine-cytokine receptor, and Complement and coagulation cascades, etc.) associated with mastitis resistance and susceptibility phenotypic traits (IL-6, interferon-gamma (IFN-γ), IL17, IL8, SCS, and SCC) in dairy cattle.
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Affiliation(s)
- Muhammad Zahoor Khan
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
- Faculty of Veterinary and Animal Sciences, The University of Agriculture, Dera Ismail Khan, Pakistan
| | - Jingjun Wang
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yulin Ma
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Tianyu Chen
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Mei Ma
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Qudrat Ullah
- Faculty of Veterinary and Animal Sciences, The University of Agriculture, Dera Ismail Khan, Pakistan
| | - Ibrar Muhammad Khan
- Anhui Province Key Laboratory of Embryo Development and Reproduction Regulation, Anhui Province Key Laboratory of Environmental Hormone and Reproduction, School of Biological and Food Engineering, Fuyang Normal University, Fuyang, China
| | - Adnan Khan
- Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zhijun Cao
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Shuai Liu
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Chakraborty D, Sharma N, Kour S, Sodhi SS, Gupta MK, Lee SJ, Son YO. Applications of Omics Technology for Livestock Selection and Improvement. Front Genet 2022; 13:774113. [PMID: 35719396 PMCID: PMC9204716 DOI: 10.3389/fgene.2022.774113] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 05/16/2022] [Indexed: 12/16/2022] Open
Abstract
Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high generation intervals. With the advent of high-throughput omics techniques and the availability of multi-omics technologies and sophisticated analytic packages, several promising tools and methods have been developed to estimate the actual genetic potential of the animals. It has now become possible to collect and access large and complex datasets comprising different genomics, transcriptomics, proteomics, metabolomics, and phonemics data as well as animal-level data (such as longevity, behavior, adaptation, etc.,), which provides new opportunities to better understand the mechanisms regulating animals’ actual performance. The cost of omics technology and expertise of several fields like biology, bioinformatics, statistics, and computational biology make these technology impediments to its use in some cases. The population size and accurate phenotypic data recordings are other significant constraints for appropriate selection and breeding strategies. Nevertheless, omics technologies can estimate more accurate breeding values (BVs) and increase the genetic gain by assisting the section of genetically superior, disease-free animals at an early stage of life for enhancing animal productivity and profitability. This manuscript provides an overview of various omics technologies and their limitations for animal genetic selection and breeding decisions.
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Affiliation(s)
- Dibyendu Chakraborty
- Division of Animal Genetics and Breeding, Faculty of Veterinary Sciences and Animal Husbandry, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Ranbir Singh Pura, India
| | - Neelesh Sharma
- Division of Veterinary Medicine, Faculty of Veterinary Sciences and Animal Husbandry, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Ranbir Singh Pura, India
- *Correspondence: Neelesh Sharma, ; Young Ok Son,
| | - Savleen Kour
- Division of Veterinary Medicine, Faculty of Veterinary Sciences and Animal Husbandry, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Ranbir Singh Pura, India
| | - Simrinder Singh Sodhi
- Department of Animal Biotechnology, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, India
| | - Mukesh Kumar Gupta
- Department of Biotechnology and Medical Engineering, National Institute of Technology, Rourkela, India
| | - Sung Jin Lee
- Department of Animal Biotechnology, College of Animal Life Sciences, Kangwon National University, Chuncheon-si, South Korea
| | - Young Ok Son
- Department of Animal Biotechnology, Faculty of Biotechnology, College of Applied Life Sciences and Interdisciplinary Graduate Program in Advanced Convergence Technology and Science, Jeju National University, Jeju, South Korea
- *Correspondence: Neelesh Sharma, ; Young Ok Son,
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Jaiswal S, Jagannadham J, Kumari J, Iquebal MA, Gurjar AKS, Nayan V, Angadi UB, Kumar S, Kumar R, Datta TK, Rai A, Kumar D. Genome Wide Prediction, Mapping and Development of Genomic Resources of Mastitis Associated Genes in Water Buffalo. Front Vet Sci 2021; 8:593871. [PMID: 34222390 PMCID: PMC8253262 DOI: 10.3389/fvets.2021.593871] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 04/30/2021] [Indexed: 12/16/2022] Open
Abstract
Water buffalo (Bubalus bubalis) are an important animal resource that contributes milk, meat, leather, dairy products, and power for plowing and transport. However, mastitis, a bacterial disease affecting milk production and reproduction efficiency, is most prevalent in populations having intensive selection for higher milk yield, especially where the inbreeding level is also high. Climate change and poor hygiene management practices further complicate the issue. The management of this disease faces major challenges, like antibiotic resistance, maximum residue level, horizontal gene transfer, and limited success in resistance breeding. Bovine mastitis genome wide association studies have had limited success due to breed differences, sample sizes, and minor allele frequency, lowering the power to detect the diseases associated with SNPs. In this work, we focused on the application of targeted gene panels (TGPs) in screening for candidate gene association analysis, and how this approach overcomes the limitation of genome wide association studies. This work will facilitate the targeted sequencing of buffalo genomic regions with high depth coverage required to mine the extremely rare variants potentially associated with buffalo mastitis. Although the whole genome assembly of water buffalo is available, neither mastitis genes are predicted nor TGP in the form of web-genomic resources are available for future variant mining and association studies. Out of the 129 mastitis associated genes of cattle, 101 were completely mapped on the buffalo genome to make TGP. This further helped in identifying rare variants in water buffalo. Eighty-five genes were validated in the buffalo gene expression atlas, with the RNA-Seq data of 50 tissues. The functions of 97 genes were predicted, revealing 225 pathways. The mastitis proteins were used for protein-protein interaction network analysis to obtain additional cross-talking proteins. A total of 1,306 SNPs and 152 indels were identified from 101 genes. Water Buffalo-MSTdb was developed with 3-tier architecture to retrieve mastitis associated genes having genomic coordinates with chromosomal details for TGP sequencing for mining of minor alleles for further association studies. Lastly, a web-genomic resource was made available to mine variants of targeted gene panels in buffalo for mastitis resistance breeding in an endeavor to ensure improved productivity and the reproductive efficiency of water buffalo.
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Affiliation(s)
- Sarika Jaiswal
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Jaisri Jagannadham
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Juli Kumari
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Anoop Kishor Singh Gurjar
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Varij Nayan
- Indian Council of Agricultural Research (ICAR)-Central Institute for Research on Buffaloes, Hisar, India
| | - Ulavappa B Angadi
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Sunil Kumar
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Rakesh Kumar
- Animal Biotechnology Centre, Indian Council of Agricultural Research (ICAR)-National Dairy research Institute, Karnal, India
| | - Tirtha Kumar Datta
- Animal Biotechnology Centre, Indian Council of Agricultural Research (ICAR)-National Dairy research Institute, Karnal, India
| | - Anil Rai
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
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Identification of Genomic Regions Associated with Concentrations of Milk Fat, Protein, Urea and Efficiency of Crude Protein Utilization in Grazing Dairy Cows. Genes (Basel) 2021; 12:genes12030456. [PMID: 33806889 PMCID: PMC8004844 DOI: 10.3390/genes12030456] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/16/2021] [Accepted: 03/19/2021] [Indexed: 01/01/2023] Open
Abstract
The objective of this study was to identify genomic regions associated with milk fat percentage (FP), crude protein percentage (CPP), urea concentration (MU) and efficiency of crude protein utilization (ECPU: ratio between crude protein yield in milk and dietary crude protein intake) using grazing, mixed-breed, dairy cows in New Zealand. Phenotypes from 634 Holstein Friesian, Jersey or crossbred cows were obtained from two herds at Massey University. A subset of 490 of these cows was genotyped using Bovine Illumina 50K SNP-chips. Two genome-wise association approaches were used, a single-locus model fitted to data from 490 cows and a single-step Bayes C model fitted to data from all 634 cows. The single-locus analysis was performed with the Efficient Mixed-Model Association eXpedited model as implemented in the SVS package. Single nucleotide polymorphisms (SNPs) with genome-wide association p-values ≤ 1.11 × 10−6 were considered as putative quantitative trait loci (QTL). The Bayes C analysis was performed with the JWAS package and 1-Mb genomic windows containing SNPs that explained > 0.37% of the genetic variance were considered as putative QTL. Candidate genes within 100 kb from the identified SNPs in single-locus GWAS or the 1-Mb windows were identified using gene ontology, as implemented in the Ensembl Genome Browser. The genes detected in association with FP (MGST1, DGAT1, CEBPD, SLC52A2, GPAT4, and ACOX3) and CPP (DGAT1, CSN1S1, GOSR2, HERC6, and IGF1R) were identified as candidates. Gene ontology revealed six novel candidate genes (GMDS, E2F7, SIAH1, SLC24A4, LGMN, and ASS1) significantly associated with MU whose functions were in protein catabolism, urea cycle, ion transportation and N excretion. One novel candidate gene was identified in association with ECPU (MAP3K1) that is involved in post-transcriptional modification of proteins. The findings should be validated using a larger population of New Zealand grazing dairy cows.
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The functions and mechanisms of sequence differences of DGAT1 gene on milk fat synthesis between dairy cow and buffalo. J DAIRY RES 2021; 87:170-174. [PMID: 32482199 DOI: 10.1017/s0022029920000126] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
In this research communication we describe the DGAT1 sequence and promoter region in dairy cows and buffalo and compare the activities of DGAT1 between the two species in order to increase knowledge of the cause of milk fat variation. pGL-3 basic vectors were used to construct the reporter gene. Based on the predicted promoter region, 4 truncated plasmid vectors were constructed in cow-DGAT1 and 3 plasmid vectors in buffalo-DGAT1. Each reporter plasmid was transfected into the bovine mammary epithelial cell (BMEC), 293T cell, and CHO cells to analyze the activity using Dual-Luciferase Reporter Assay System. The results show that the region between -93 to -556 bp was essential for cow promoter activity while -84 to -590 bp was essential for buffalo promoter activity revealing these regions contain core promoter. The buffalo has higher promoter activity than cow yet it was not statistically significant. Comparison of candidate mutation K232A between cow and buffalo population revealed the presence of both the allelic population in dairy cows (lysine and alanine) however, only K (lysine) allelic amino acid was found in buffalo population. The absence of the alanine allelic population from buffalo explains the higher fat content of buffalo milk.
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Han B, Yuan Y, Shi L, Li Y, Liu L, Sun D. Identification of single nucleotide polymorphisms of PIK3R1 and DUSP1 genes and their genetic associations with milk production traits in dairy cows. J Anim Sci Biotechnol 2019; 10:81. [PMID: 31709048 PMCID: PMC6833155 DOI: 10.1186/s40104-019-0392-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 09/06/2019] [Indexed: 01/15/2023] Open
Abstract
Background Previously, phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1) and dual specificity phosphatase 1 (DUSP1) were identified as promising candidate genes for milk production traits due to their being differentially expressed between the dry period and the peak of lactation in livers of dairy cows. Hence, in this study, the single nucleotide polymorphisms (SNPs) of PIK3R1 and DUSP1 genes were identified and their genetic associations with milk yield, fat yield, fat percentage, protein yield, and protein percentage, were investigated using 1067 Chinese Holstein cows from 40 sire families. Results By re-sequencing the entire coding region and 2000 bp of the 5′ and 3′ flanking regions of the two genes, one SNP in the 5′ untranslated region (UTR), three in the 3′ UTR, and two in the 3′ flanking region of PIK3R1 were identified, and one in the 5′ flanking region, one in the 3′ UTR, and two in the 3′ flanking region of DUSP1 were found. Subsequent single-locus association analyses showed that five SNPs in PIK3R1, rs42590258, rs210389799, rs208819656, rs41255622, rs133655926, and rs211408208, and four SNPs in DUSP1, rs207593520, rs208460068, rs209154772, and rs210000760, were significantly associated with milk, fat and protein yields in the first or second lactation (P values ≤ 0.0001 and 0.0461). In addition, by the Haploview 4.2 software, the six and four SNPs in PIK3R1 and DUSP1 respectively formed one haplotype block, and the haplotype-based association analyses showed significant associations between their haplotype combinations and the milk traits in both two lactations (P values ≤ 0.0001 and 0.0364). One SNP, rs207593520(T/G), was predicted to alter the transcription factor binding sites (TFBSs) in the 5′ flanking region of DUSP1. Further, the dual-luciferase assay showed that the transcription activity of allele T in rs207593520 was significantly higher than that of allele G, suggesting the activation of transcriptional activity of DUSP1 gene by allele T of rs207593520. Thus, the rs207593520 SNP was highlighted as a potential causal mutation that should be further verified. Conclusions We demonstrated novel and significant genetic effects of the PIK3R1 and DUSP1 genes on milk production traits in dairy cows, and our findings provide information for use in dairy cattle breeding.
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Affiliation(s)
- Bo Han
- 1Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193 China
| | - Yuwei Yuan
- 1Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193 China
| | - Lijun Shi
- 1Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193 China
| | - Yanhua Li
- 1Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193 China.,Beijing Dairy Cattle Center, Beijing, 100192 China
| | - Lin Liu
- Beijing Dairy Cattle Center, Beijing, 100192 China
| | - Dongxiao Sun
- 1Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193 China
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Associations between Bovine β-Defensin 4 Genotypes and Production Traits of Polish Holstein-Friesian Dairy Cattle. Animals (Basel) 2019; 9:ani9100723. [PMID: 31557942 PMCID: PMC6827129 DOI: 10.3390/ani9100723] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 09/22/2019] [Accepted: 09/23/2019] [Indexed: 01/01/2023] Open
Abstract
Simple Summary Mastitis negatively affects dairy cattle, causing inferior milk quality and premature animal culling, which leads to economic losses. Therefore, selection based on genetic markers (i.g., marker-assisted selection) should also include functional traits with low heritability, such as resistance to udder inflammation. Single nucleotide polymorphisms (SNPs) identified in genes involved in the immune system, such as defensins with antibacterial properties, could be valuable markers. We chose two SNPs within the bovine neutrophil beta-defensin 4 (BNBD4) gene analyzed in a previous study related to milk production and udder health. Since these SNPs are located very close to each other in the gene intron, it is useful to analyze their association with production traits as a combined genotype. The results showed that these genotypes are indeed associated with productivity, as well as functional traits (milk, fat, and protein yields, fat, protein, lactose, and dry matter contents, and somatic cell count). The differences between the results based on the phenotypic data and the breeding values of studied traits may confirm the results of simulation studies that indicate a high rate of false-positives in genome-wide association study (GWAS) based on classically calculated estimated breeding values (EBVs) using best linear unbiased prediction (BLUP) methodology. Abstract This study analyzed the associations between two single-nucleotide polymorphisms (C2239T and A1674C), used together as a genotype located in BNBD4, and milk traits and breeding values of productivity traits of Polish Holstein-Friesian dairy cows. The research was carried out on 322 cows, with 7070 milk parameter and somatic cell count records in daily milking, as well as 897 records covering data on whole lactations, and 2209 breeding value records for productivity traits. The DMU statistical package with a one-trait repeatability test-day animal model was used to estimate the associations. The differences between the genotype effects were analyzed using Duncan’s post-hoc tests. The CC/AA and CT/AC genotypes had the highest frequencies (0.62 and 0.23, respectively). For use in marker-assisted selection, the CC/AC genotype is the most promising as an indicator of high-yielding cows potentially resistant to mastitis, because it was associated with the lowest somatic cell count (SCC), highest milk, fat, and protein yields in daily milking, as well as with milk yield in the whole lactation. The studied genotypes were also related to the breeding values of all the investigated production traits. However, some simulation studies have indicated a high rate of false-positives in GWAS based on classically calculated EBVs.
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Yang F, Chen F, Li L, Yan L, Badri T, Lv C, Yu D, Zhang M, Jang X, Li J, Yuan L, Wang G, Li H, Li J, Cai Y. Three Novel Players: PTK2B, SYK, and TNFRSF21 Were Identified to Be Involved in the Regulation of Bovine Mastitis Susceptibility via GWAS and Post-transcriptional Analysis. Front Immunol 2019; 10:1579. [PMID: 31447828 PMCID: PMC6691815 DOI: 10.3389/fimmu.2019.01579] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 06/24/2019] [Indexed: 12/25/2022] Open
Abstract
Bovine mastitis is a common inflammatory disease caused by multiple factors in early lactation or dry period. Genome wide association studies (GWAS) can provide a convenient and effective strategy for understanding the biological basis of mastitis and better prevention. 2b-RADseq is a high-throughput sequencing technique that offers a powerful method for genome-wide genetic marker development and genotyping. In this study, single nucleotide polymorphisms (SNPs) of the immune-regulated gene correlative with mastitis were screened and identified by two stage association analysis via GWAS-2b-RADseq in Chinese Holstein cows. We have screened 10,058 high quality SNPs from 7,957,920 tags and calculated their allele frequencies. Twenty-seven significant SNPs were co-labeled in two GWAS analysis models [Bayesian (P < 0.001) and Logistic regression (P < 0.01)], and only three SNPs (rs75762330, C > T, PIC = 0.2999; rs88640083, A > G, PIC = 0.1676; rs20438858, G > A, PIC = 0.3366) were annotated to immune-regulated genes (PTK2B, SYK, and TNFRSF21). Identified three SNPs are located in non-coding regions with low or moderate genetic polymorphisms. However, independent sample population validation (Case-control study) data showed that three important SNPs (rs75762330, P < 0.025, OR > 1; rs88640083, P < 0.005, OR > 1; rs20438858, P < 0.001, OR < 1) were significantly associated with clinical mastitis trait. Importantly, PTK2B and SYK expression was down-regulated in both peripheral blood leukocytes (PBLs) of clinical mastitis cows and in vitro LPS (E. coli)-stimulated bovine mammary epithelial cells, while TNFRSF21 was up-regulated. Under the same conditions, expression of Toll-like receptor 4 (TLR4), AKT1, and pro-inflammatory factors (IL-1β and IL-8) were also up-regulated. Interestingly, network analysis indicated that PTK2B and SYK are co-expressed in innate immune signaling pathway of Chinese Holstein. Taken together, these results provided strong evidence for the study of SNPs in bovine mastitis, and revealed the role of SYK, PTK2B, and TNFRSF21 in bovine mastitis susceptibility/tolerance.
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Affiliation(s)
- Fan Yang
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Fanghui Chen
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Lili Li
- National Animal Husbandry Station, Beijing, China
| | - Li Yan
- Department of Radiation Oncology, Linyi People Hospital, Linyi, China
| | - Tarig Badri
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Chenglong Lv
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Daolun Yu
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Manling Zhang
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Xiaojun Jang
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Jie Li
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Lu Yuan
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Genlin Wang
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Honglin Li
- Department of Biochemistry and Molecular Biology, Medical College of Georgia, Augusta University, Augusta, GA, United States
| | - Jun Li
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Yafei Cai
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
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Polymorphism of bovine lipocalin-2 gene and its impact on milk production traits and mastitis in Holstein Friesian cattle. ELECTRON J BIOTECHN 2019. [DOI: 10.1016/j.ejbt.2019.04.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
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Han B, Yuan Y, Li Y, Liu L, Sun D. Single Nucleotide Polymorphisms of NUCB2 and their Genetic Associations with Milk Production Traits in Dairy Cows. Genes (Basel) 2019; 10:E449. [PMID: 31200542 PMCID: PMC6627143 DOI: 10.3390/genes10060449] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 06/04/2019] [Accepted: 06/12/2019] [Indexed: 02/07/2023] Open
Abstract
We previously used the RNA sequencing technique to detect the hepatic transcriptome of Chinese Holstein cows among the dry period, early lactation, and peak of lactation, and implied that the nucleobindin 2 (NUCB2) gene might be associated with milk production traits due to its expression being significantly increased in early lactation or peak of lactation as compared to dry period (q value < 0.05). Hence, in this study, we detected the single nucleotide polymorphisms (SNPs) of NUCB2 and analyzed their genetic associations with milk yield, fat yield, fat percentage, protein yield, and protein percentage. We re-sequenced the entire coding and 2000 bp of 5' and 3' flanking regions of NUCB2 by pooled sequencing, and identified ten SNPs, including one in 5' flanking region, two in 3' untranslated region (UTR), and seven in 3' flanking region. The single-SNP association analysis results showed that the ten SNPs were significantly associated with milk yield, fat yield, fat percentage, protein yield, or protein percentage in the first or second lactation (p values <= 1 × 10-4 and 0.05). In addition, we estimated the linkage disequilibrium (LD) of the ten SNPs by Haploview 4.2, and found that the SNPs were highly linked in one haplotype block (D' = 0.98-1.00), and the block was also significantly associated with at least one milk traits in the two lactations (p values: 0.0002-0.047). Further, we predicted the changes of transcription factor binding sites (TFBSs) that are caused by the SNPs in the 5' flanking region of NUCB2, and considered that g.35735477C>T might affect the expression of NUCB2 by changing the TFBSs for ETS transcription factor 3 (ELF3), caudal type homeobox 2 (CDX2), mammalian C-type LTR TATA box (VTATA), nuclear factor of activated T-cells (NFAT), and v-ets erythroblastosis virus E26 oncogene homolog (ERG) (matrix similarity threshold, MST > 0.85). However, the further study should be performed to verify the regulatory mechanisms of NUCB2 and its polymorphisms on milk traits. Our findings first revealed the genetic effects of NUCB2 on the milk traits in dairy cows, and suggested that the significant SNPs could be used in genomic selection to improve the accuracy of selection for dairy cattle breeding.
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Affiliation(s)
- Bo Han
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| | - Yuwei Yuan
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| | - Yanhua Li
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
- Beijing Key Laboratory of Dairy Cattle Genetic, Breeding and Reproduction, Beijing Dairy Cattle Center, Beijing 100192, China.
| | - Lin Liu
- Beijing Key Laboratory of Dairy Cattle Genetic, Breeding and Reproduction, Beijing Dairy Cattle Center, Beijing 100192, China.
| | - Dongxiao Sun
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
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Vijayakumar P, Bakyaraj S, Singaravadivelan A, Vasanthakumar T, Suresh R. Meta-analysis of mammary RNA seq datasets reveals the molecular understanding of bovine lactation biology. Genome 2019; 62:489-501. [PMID: 31071269 DOI: 10.1139/gen-2018-0144] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
A better understanding of the biology of lactation, both in terms of gene expression and the identification of candidate genes for the production of milk and its components, is made possible by recent advances in RNA seq technology. The purpose of this study was to understand the synthesis of milk components and the molecular pathways involved, as well as to identify candidate genes for milk production traits within whole mammary transcriptomic datasets. We performed a meta-analysis of publically available RNA seq transcriptome datasets of mammary tissue/milk somatic cells. In total, 11 562 genes were commonly identified from all RNA seq based mammary gland transcriptomes. Functional annotation of commonly expressed genes revealed the molecular processes that contribute to the synthesis of fats, proteins, and lactose in mammary secretory cells and the molecular pathways responsible for milk synthesis. In addition, we identified several candidate genes responsible for milk production traits and constructed a gene regulatory network for RNA seq data. In conclusion, this study provides a basic understanding of the lactation biology of cows at the gene expression level.
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Affiliation(s)
- Periyasamy Vijayakumar
- a Veterinary College and Research Institute, TANUVAS, Orathanadu-614 625, Thanjavur, Tamil Nadu, India
| | - Sanniyasi Bakyaraj
- b College of Poultry Production and Management, TANUVAS, Hosur-635 110, Krishnagiri, Tamil Nadu, India
| | | | - Thangavelu Vasanthakumar
- a Veterinary College and Research Institute, TANUVAS, Orathanadu-614 625, Thanjavur, Tamil Nadu, India
| | - Ramalingam Suresh
- a Veterinary College and Research Institute, TANUVAS, Orathanadu-614 625, Thanjavur, Tamil Nadu, India
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Han B, Yuan Y, Liang R, Li Y, Liu L, Sun D. Genetic Effects of LPIN1 Polymorphisms on Milk Production Traits in Dairy Cattle. Genes (Basel) 2019; 10:genes10040265. [PMID: 30986988 PMCID: PMC6523124 DOI: 10.3390/genes10040265] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 03/27/2019] [Accepted: 03/28/2019] [Indexed: 12/16/2022] Open
Abstract
Our initial RNA sequencing work identified that lipin 1 (LPIN1) was differentially expressed during dry period, early lactation, and peak of lactation in dairy cows, and it was enriched into the fat metabolic Gene Ontology (GO) terms and pathways, thus we considered LPIN1 as the candidate gene for milk production traits. In this study, we detected the polymorphisms of LPIN1 and verified their genetic effects on milk yield and composition in a Chinese Holstein cow population. We found seven SNPs by re-sequencing the entire coding region and partial flanking region of LPIN1, including one in 5′ flanking region, four in exons, and two in 3′ flanking region. Of these, four SNPs, c.637T > C, c.708A > G, c.1521C > T, and c.1555A > C, in the exons were predicted to result in the amino acid replacements. With the Haploview 4.2, we found that seven SNPs in LPIN1 formed two haplotype blocks (D′ = 0.98–1.00). Single-SNP association analyses showed that SNPs were significantly associated with milk yield, fat yield, fat percentage, or protein yield in the first or second lactation (p = < 0.0001–0.0457), and only g.86049389C > T was strongly associated with protein percentage in both lactations (p = 0.0144 and 0.0237). The haplotype-based association analyses showed that the two haplotype blocks were significantly associated with milk yield, fat yield, protein yield, or protein percentage (p = < 0.0001–0.0383). By quantitative real-time PCR (qRT-PCR), we found that LPIN1 had relatively high expression in mammary gland and liver tissues. Furthermore, we predicted three SNPs, c.637T > C, c.708A > G, and c.1521C > T, using SOPMA software, changing the LPIN1 protein structure that might be potential functional mutations. In summary, we demonstrated the significant genetic effects of LPIN1 on milk production traits, and the identified SNPs could serve as genetic markers for dairy breeding.
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Affiliation(s)
- Bo Han
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| | - Yuwei Yuan
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| | - Ruobing Liang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| | - Yanhua Li
- Beijing Dairy Cattle Center, Qinghe'nanzhen Deshengmenwai Street, Chaoyang District, Beijing 100192, China.
| | - Lin Liu
- Beijing Dairy Cattle Center, Qinghe'nanzhen Deshengmenwai Street, Chaoyang District, Beijing 100192, China.
| | - Dongxiao Sun
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
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Han B, Liang W, Liu L, Li Y, Sun D. Genetic association of the ACACB gene with milk yield and composition traits in dairy cattle. Anim Genet 2018. [PMID: 29521460 DOI: 10.1111/age.12651] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Previously, we re-sequenced the whole genomes of eight Holstein bulls with high or low milk protein and fat percentage, and we detected two indels in the ACACB (acetyl-CoA carboxylase beta) gene that were polymorphic between the two groups. Thus, we considered ACACB as a promising candidate gene potentially affecting milk composition traits. Herein, we verified the genetic effects of ACACB on five milk traits in a Chinese Holstein population. We identified six SNPs in the 5'-promoter region, five in the 5'- untranslated region (UTR), 11 in exons, four in the 3'-UTR and three in the 3'-flanking region by re-sequencing the entire coding and regulatory regions of ACACB. One of these SNPs (ss1987461005) is reported here for the first time, and three of the SNPs (rs109482081, rs110819816 and rs109281947) were predicted to result in amino acid replacements. Genotype-phenotype association analyses showed that all the identified SNPs, except for ss1987461005, rs208919019 and rs134447911, were significantly associated with milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.0001 to 0.0484). Linkage disequilibrium analyses were conducted among the identified SNPs to confirm the genetic associations. Two SNPs-rs135874354 (g.66218726T>C) and rs210928430 (g.66218117G>A)-were predicted to alter transcription factor binding sites in the 5'-promoter region of ACACB. A luciferase activity assay showed that the promoter activity of haplotype TG was significantly higher than that of CG (P = 0.0002) and that the promoter activity of haplotype TA was remarkably higher than that of CA (P = 7.4285E-09), showing that the T allele of rs135874354 increased promoter activity. Thus, rs135874354 was considered to be a potentially functional mutation. Our findings have, for the first time, profiled the genetic effect of ACACB on milk production traits in dairy cattle and revealed a potentially causal mutation that requires further the in-depth validation.
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Affiliation(s)
- B Han
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, China Agricultural University, Beijing, 100193, China
| | - W Liang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, China Agricultural University, Beijing, 100193, China
| | - L Liu
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - Y Li
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - D Sun
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, China Agricultural University, Beijing, 100193, China
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