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Ma X, Yang G, Zhang J, Ma R, Shen J, Feng F, Yu D, Huang C, Ma X, La Y, Wu X, Guo X, Chu M, Yan P, Liang C. Association between Single Nucleotide Polymorphisms of PRKD1 and KCNQ3 Gene and Milk Quality Traits in Gannan Yak ( Bos grunniens). Foods 2024; 13:781. [PMID: 38472894 DOI: 10.3390/foods13050781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/28/2024] [Accepted: 02/28/2024] [Indexed: 03/14/2024] Open
Abstract
Protein kinase D1 (PRKD1) functions primarily in normal mammary cells, and the potassium voltage-gated channel subfamily Q member 3 (KCNQ3) gene plays an important role in controlling membrane potential and neuronal excitability, it has been found that this particular gene is linked to the percentage of milk fat in dairy cows. The purpose of this study was to investigate the relationship between nucleotide polymorphisms (SNPs) of PRKD1 and KCNQ3 genes and the milk quality of Gannan yak and to find molecular marker sites that may be used for milk quality breeding of Gannan yak. Three new SNPs were detected in the PRKD1 (g.283,619T>C, g.283,659C>A) and KCNQ3 gene (g.133,741T>C) of 172 Gannan lactating female yaks by Illumina yak cGPS 7K liquid-phase microarray technology. Milk composition was analyzed using a MilkoScanTM milk composition analyzer. We found that the mutations of these three loci significantly improved the lactose, milk fat, casein, protein, non-fat milk solid (SNF) content and acidity of Gannan yaks. The lactose content of the TC heterozygous genotype population at g.283,619T>C locus was significantly higher than that of the TT wild-type population (p < 0.05); the milk fat content of the CA heterozygous genotype population at g.283,659C>A locus was significantly higher than that of the CC wild-type and AA mutant populations (p < 0.05); the casein, protein and acidity of the CC mutant and TC heterozygous groups at the g.133,741T>C locus were significantly higher than those of the wild type (p < 0.05), and the SNF of the TC heterozygous group was significantly higher than that of the mutant group (p < 0.05). The results showed that PRKD1 and KCNQ3 genes could be used as candidate genes affecting the milk traits of Gannan yak.
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Affiliation(s)
- Xiaoyong Ma
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Guowu Yang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Juanxiang Zhang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Rong Ma
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Jinwei Shen
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Fen Feng
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Daoning Yu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Chun Huang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xiaoming Ma
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Yongfu La
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xiaoyun Wu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xian Guo
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Min Chu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Ping Yan
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
- Institute of Western Agriculture, The Chinese Academy of Agricultural Sciences, Changji 831100, China
| | - Chunnian Liang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Kumar H, Panigrahi M, G Strillacci M, Sonejita Nayak S, Rajawat D, Ghildiyal K, Bhushan B, Dutt T. Detection of genome-wide copy number variation in Murrah buffaloes. Anim Biotechnol 2023; 34:3783-3795. [PMID: 37381739 DOI: 10.1080/10495398.2023.2227670] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
Riverine Buffaloes, especially the Murrah breed because of their adaptability to harsh climatic conditions, is farmed in many countries to convert low-quality feed into valuable dairy products and meat. Here, we investigated the copy number variations (CNVs) in 296 Murrah buffalo using the Axiom® Buffalo Genotyping Array 90K (Affymetrix, Santa Clara, CA, USA). The CNVs were detected on the autosomes, using the Copy Number Analysis Module (CNAM) using the univariate analysis. 7937 CNVs were detected in 279 Buffaloes, the average length of the CNVs was 119,048.87 bp that ranged between 7800 and 4,561,030 bp. These CNVs were accounting for 10.33% of the buffalo genome, which was comparable to cattle, sheep, and goat CNV analyses. Further, CNVs were merged and 1541 CNVRs were detected using the Bedtools-mergeBed command. 485 genes were annotated within 196 CNVRs that were identified in at least 10 animals of Murrah population. Out of these, 40 CNVRs contained 59 different genes that were associated with 69 different traits. Overall, the study identified a significant number of CNVs and CNVRs in the Murrah breed of buffalo, with a wide range of lengths and frequencies across the autosomes. The identified CNVRs contained genes associated with important traits related to production and reproduction, making them potentially important targets for future breeding and genetic improvement efforts.
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Affiliation(s)
- Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, India
| | - Maria G Strillacci
- Department of Veterinary Medicine and Animal Sciences, University of Milan, Lodi, Italy
| | | | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, India
| | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, India
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Rajawat D, Panigrahi M, Nayak SS, Ghildiyal K, Sharma A, Kumar H, Parida S, Bhushan B, Gaur GK, Mishra BP, Dutt T. Uncovering genes underlying coat color variation in indigenous cattle breeds through genome-wide positive selection. Anim Biotechnol 2023; 34:3920-3933. [PMID: 37493405 DOI: 10.1080/10495398.2023.2240387] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
The identification of candidate genes related to pigmentation and under selective sweep provides insights into the genetic basis of pigmentation and the evolutionary forces that have shaped this variation. The selective sweep events in the genes responsible for normal coat color in Indian cattle groups are still unknown. To find coat color genes displaying signs of selective sweeps in the indigenous cattle, we compiled a list of candidate genes previously investigated for their association with coat color and pigmentation. After that, we performed a genome-wide scan of positive selection signatures using the BovineSNP50K Bead Chip in 187 individuals of seven indigenous breeds. We applied a wide range of methods to find evidence of selection, such as Tajima's D, CLR, iHS, varLD, ROH, and FST. We found a total of sixteen genes under selective sweep, that were involved in coat color and pigmentation physiology. These genes are CRIM1 in Gir, MC1R in Sahiwal, MYO5A, PMEL and POMC in Tharparkar, TYRP1, ERBB2, and ASIP in Red Sindhi, MITF, LOC789175, PAX3 and TYR in Ongole, and IRF2, SDR165 and, KIT in Nelore, ADAMTS19 in Hariana. These genes are related to melanin synthesis, the biology of melanocytes and melanosomes, and the migration and survival of melanocytes during development.
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Affiliation(s)
- Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Subhashree Parida
- Pharmacology and Toxicology Division, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - G K Gaur
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - B P Mishra
- Animal Biotechnology Division, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
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Atashi H, Chen Y, Wilmot H, Bastin C, Vanderick S, Hubin X, Gengler N. Single-step genome-wide association analyses for selected infrared-predicted cheese-making traits in Walloon Holstein cows. J Dairy Sci 2023; 106:7816-7831. [PMID: 37567464 DOI: 10.3168/jds.2022-23206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/01/2023] [Indexed: 08/13/2023]
Abstract
This study aimed to perform genome-wide association study to identify genomic regions associated with milk production and cheese-making properties (CMP) in Walloon Holstein cows. The studied traits were milk yield, fat percentage, protein percentage, casein percentage (CNP), calcium content, somatic cell score (SCS), coagulation time, curd firmness after 30 min from rennet addition, and titratable acidity. The used data have been collected from 2014 to 2020 on 78,073 first-parity (485,218 test-day records), 48,766 second-parity (284,942 test-day records), and 21,948 third-parity (105,112 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA) of 6,617 animals (1,712 males), were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 KB) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for positional candidate genes. Heritability estimates for the studied traits ranged from 0.10 (SCS) to 0.53 (CNP), 0.10 (SCS) to 0.50 (CNP), and 0.12 (SCS) to 0.49 (CNP) in the first, second, and third parity, respectively. Genome-wide association analyses identified 6 genomic regions (BTA1, BTA14 [4 regions], and BTA20) associated with the considered traits. Genes including the SLC37A1 (BTA1), SHARPIN, MROH1, DGAT1, FAM83H, TIGD5, MROH6, NAPRT, ADGRB1, GML, LYPD2, JRK (BTA14), and TRIO (BTA20) were identified as positional candidate genes for the studied CMP. The findings of this study help to unravel the genomic background of a cow's ability for cheese production and can be used for the future implementation and use of genomic evaluation to improve the cheese-making traits in Walloon Holstein cows.
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Affiliation(s)
- H Atashi
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-13131 Shiraz, Iran.
| | - Y Chen
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - H Wilmot
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; National Fund for Scientific Research (FRS-FNRS), 1000 Brussels, Belgium
| | - C Bastin
- National Fund for Scientific Research (FRS-FNRS), 1000 Brussels, Belgium
| | - S Vanderick
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - X Hubin
- Elevéo asbl Awé Group, 5590 Ciney, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
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Haque MA, Alam MZ, Iqbal A, Lee YM, Dang CG, Kim JJ. Genome-Wide Association Studies for Body Conformation Traits in Korean Holstein Population. Animals (Basel) 2023; 13:2964. [PMID: 37760364 PMCID: PMC10526087 DOI: 10.3390/ani13182964] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/15/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
The objective of this study was to identify quantitative trait loci (QTL) and nearby candidate genes that influence body conformation traits. Phenotypic data for 24 body conformation traits were collected from a population of 2329 Korean Holstein cattle, and all animals were genotyped using the 50 K Illumina bovine SNP chip. A total of 24 genome-wide significant SNPs associated with 24 body conformation traits were identified by genome-wide association analysis. The selection of the most promising candidate genes was based on gene ontology (GO) terms and the previously identified functions that influence various body conformation traits as determined in our study. These genes include KCNA1, RYBP, PTH1R, TMIE, and GNAI3 for body traits; ANGPT1 for rump traits; MALRD1, INHBA, and HOXA13 for feet and leg traits; and CDK1, RHOBTB1, and SLC17A1 for udder traits, respectively. These findings contribute to our understanding of the genetic basis of body conformation traits in this population and pave the way for future breeding strategies aimed at enhancing desirable traits in dairy cattle.
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Affiliation(s)
- Md Azizul Haque
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Gyeongbuk, Republic of Korea; (M.A.H.); (M.Z.A.); (A.I.); (Y.-M.L.)
| | - Mohammad Zahangir Alam
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Gyeongbuk, Republic of Korea; (M.A.H.); (M.Z.A.); (A.I.); (Y.-M.L.)
| | - Asif Iqbal
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Gyeongbuk, Republic of Korea; (M.A.H.); (M.Z.A.); (A.I.); (Y.-M.L.)
| | - Yun-Mi Lee
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Gyeongbuk, Republic of Korea; (M.A.H.); (M.Z.A.); (A.I.); (Y.-M.L.)
| | - Chang-Gwon Dang
- Animal Breeding and Genetics Division, National Institute of Animal Science, Cheonan 31000, Chungcheongnam-do, Republic of Korea
| | - Jong-Joo Kim
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Gyeongbuk, Republic of Korea; (M.A.H.); (M.Z.A.); (A.I.); (Y.-M.L.)
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Atashi H, Chen Y, Wilmot H, Vanderick S, Hubin X, Soyeurt H, Gengler N. Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows. J Dairy Sci 2023; 106:6299-6315. [PMID: 37479585 DOI: 10.3168/jds.2022-22432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 03/17/2023] [Indexed: 07/23/2023]
Abstract
The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.
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Affiliation(s)
- H Atashi
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-13131 Shiraz, Iran.
| | - Y Chen
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - H Wilmot
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; National Fund for Scientific Research (F.R.S.-FNRS), 1000 Brussels, Belgium
| | - S Vanderick
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - X Hubin
- Elevéo asbl Awé Group, 5590 Ciney, Belgium
| | - H Soyeurt
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
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Persichilli C, Senczuk G, Mastrangelo S, Marusi M, van Kaam JT, Finocchiaro R, Di Civita M, Cassandro M, Pilla F. Exploring genome-wide differentiation and signatures of selection in Italian and North American Holstein populations. J Dairy Sci 2023; 106:5537-5553. [PMID: 37291034 DOI: 10.3168/jds.2022-22159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 02/07/2023] [Indexed: 06/10/2023]
Abstract
Among Italian dairy cattle, the Holstein is the most reared breed for the production of Parmigiano Reggiano protected designation of origin cheese, which represents one of the most renowned products in the entire Italian dairy industry. In this work, we used a medium-density genome-wide data set consisting of 79,464 imputed SNPs to study the genetic structure of Italian Holstein breed, including the population reared in the area of Parmigiano Reggiano cheese production, and assessing its distinctiveness from the North American population. Multidimensional scaling and ADMIXTURE approaches were used to explore the genetic structure among populations. We also investigated putative genomic regions under selection among these 3 populations by combining 4 different statistical methods based either on allele frequencies (single marker and window-based) or extended haplotype homozygosity (EHH; standardized log-ratio of integrated EHH and cross-population EHH). The genetic structure results allowed us to clearly distinguish the 3 Holstein populations; however, the most remarkable difference was observed between Italian and North American stock. Selection signature analyses identified several significant SNPs falling within or closer to genes with known roles in several traits such as milk quality, resistance to disease, and fertility. In particular, a total of 22 genes related to milk production have been identified using the 2 allele frequency approaches. Among these, a convergent signal has been found in the VPS8 gene which resulted to be involved in milk traits, whereas other genes (CYP7B1, KSR2, C4A, LIPE, DCDC1, GPR20, and ST3GAL1) resulted to be associated with quantitative trait loci related to milk yield and composition in terms of fat and protein percentage. In contrast, a total of 7 genomic regions were identified combining the results of standardized log-ratio of integrated EHH and cross-population EHH. In these regions candidate genes for milk traits were also identified. Moreover, this was also confirmed by the enrichment analyses in which we found that the majority of the significantly enriched quantitative trait loci were linked to milk traits, whereas the gene ontology and pathway enrichment analysis pointed to molecular functions and biological processes involved in AA transmembrane transport and methane metabolism pathway. This study provides information on the genetic structure of the examined populations, showing that they are distinguishable from each other. Furthermore, the selection signature analyses can be considered as a starting point for future studies in the identification of causal mutations and consequent implementation of more practical application.
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Affiliation(s)
- Christian Persichilli
- Department of Agricultural, Environmental and Food Sciences, University of Molise, Via A. De sanctis, 86100 Campobasso (CB), Italy
| | - Gabriele Senczuk
- Department of Agricultural, Environmental and Food Sciences, University of Molise, Via A. De sanctis, 86100 Campobasso (CB), Italy.
| | - Salvatore Mastrangelo
- Department of Agricultural, Food and Forest Sciences, University of Palermo, Viale delle Scienze, 90128 Palermo (PA), Italy
| | - Maurizio Marusi
- National Association of Italian Holstein, Brown and Jersey Breeders, Via Bergamo, 292, 26100 Cremona (CR), Italy
| | - Jan-Thijs van Kaam
- National Association of Italian Holstein, Brown and Jersey Breeders, Via Bergamo, 292, 26100 Cremona (CR), Italy
| | - Raffaella Finocchiaro
- National Association of Italian Holstein, Brown and Jersey Breeders, Via Bergamo, 292, 26100 Cremona (CR), Italy
| | - Marika Di Civita
- Department of Agricultural, Environmental and Food Sciences, University of Molise, Via A. De sanctis, 86100 Campobasso (CB), Italy
| | - Martino Cassandro
- National Association of Italian Holstein, Brown and Jersey Breeders, Via Bergamo, 292, 26100 Cremona (CR), Italy; Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - Fabio Pilla
- Department of Agricultural, Environmental and Food Sciences, University of Molise, Via A. De sanctis, 86100 Campobasso (CB), Italy
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9
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Hu M, Jiang H, Lai W, Shi L, Yi W, Sun H, Chen C, Yuan B, Yan S, Zhang J. Assessing Genomic Diversity and Signatures of Selection in Chinese Red Steppe Cattle Using High-Density SNP Array. Animals (Basel) 2023; 13:ani13101717. [PMID: 37238146 DOI: 10.3390/ani13101717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/13/2023] [Accepted: 05/19/2023] [Indexed: 05/28/2023] Open
Abstract
Chinese Red Steppe Cattle (CRS), a composite cattle breed, is well known for its milk production, high slaughter rate, carcass traits, and meat quality. Nowadays, it is widely bred in Jilin and Hebei Province and the Inner Mongolia Autonomous region. However, the population structure and the genetic basis of prominent characteristics of CRS are still unknown. In this study, we systematically describe their population structure, genetic diversity, and selection signature based on genotyping data from 61 CRS individuals with GGP Bovine 100 K chip. The results showed that CRS cattle had low inbreeding levels and had formed a unique genetic structure feature. Using two complementary methods (including comprehensive haplotype score and complex likelihood ratio), we identified 1291 and 1285 potentially selected genes, respectively. There were 141 genes annotated in common 106 overlapping genomic regions covered 5.62 Mb, including PLAG1, PRKG2, DGAT1, PARP10, TONSL, ADCK5, and BMP3, most of which were enriched in pathways related to muscle growth and differentiation, milk production, and lipid metabolism. This study will contribute to understanding the genetic mechanism behind artificial selection and give an extensive reference for subsequent breeding.
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Affiliation(s)
- Mingyue Hu
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Hao Jiang
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Weining Lai
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Lulu Shi
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Wenfeng Yi
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Hao Sun
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Chengzhen Chen
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Bao Yuan
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Shouqing Yan
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Jiabao Zhang
- College of Animal Science, Jilin University, Changchun 130062, China
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11
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Arnal M, Robert-Granié C, Ducrocq V, Larroque H. Validation of single-step genomic BLUP random regression test-day models and SNP effects analysis on milk yield in French Saanen goats. J Dairy Sci 2023:S0022-0302(23)00210-2. [PMID: 37164843 DOI: 10.3168/jds.2022-22550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 01/04/2023] [Indexed: 05/12/2023]
Abstract
The shape of the lactation curve is linked to an animal's health, feed requirements, and milk production throughout the year. Random regression models (RRM) are widely used for genetic evaluation of total milk production throughout the lactation and for milk yield persistency. Genomic information used with the single-step genomic BLUP method (ssGBLUP) substantially improves the accuracy of genomic prediction of breeding values in the main dairy cattle breeds. The aim of this study was to implement an RRM using ssGBLUP for milk yield in Saanen dairy goats in France. The data set consisted of 7,904,246 test-day records from 1,308,307 lactations of Saanen goats collected in France between 2000 and 2017. The performance of this type of evaluation was assessed by applying a validation step with data targeting candidate bucks. The model was compared with a nongenomic evaluation and a traditional evaluation that use cumulated performance throughout the lactation model (LM). The incorporation of genomic information increased correlations between daughter yield deviations (DYD) and estimated breeding values (EBV) obtained with a partial data set for candidate bucks. The LM and the RRM had similar correlation between DYD and EBV. However, the RRM reduced overestimation of EBV and improved the slope of the regression of DYD on EBV obtained at birth. This study shows that a genomic evaluation from a ssGBLUP RRM is possible in dairy goats in France and that RRM performance is comparable to a LM but with the additional benefit of a genomic evaluation of persistency. Variance of adjacent SNPs was studied with LM and RRM following the ssGBLUP. Both approaches converged on approximately the same regions explaining more than 1% of total variance. Regions associated with persistency were also found.
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Affiliation(s)
- M Arnal
- GenPhySE, Université de Toulouse, INRAE, INPT, ENVT, 31326 Castanet-Tolosan, France; Institut de l'Elevage, Chemin de Borde Rouge, 31326 Castanet-Tolosan Cedex, France.
| | - C Robert-Granié
- GenPhySE, Université de Toulouse, INRAE, INPT, ENVT, 31326 Castanet-Tolosan, France
| | - V Ducrocq
- Université Paris-Saclay, INRAE, AgroParisTech, UMR GABI, 78350 Jouy-en-Josas, France
| | - H Larroque
- GenPhySE, Université de Toulouse, INRAE, INPT, ENVT, 31326 Castanet-Tolosan, France
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Bordbar F, Mohammadabadi M, Jensen J, Xu L, Li J, Zhang L. Identification of Candidate Genes Regulating Carcass Depth and Hind Leg Circumference in Simmental Beef Cattle Using Illumina Bovine Beadchip and Next-Generation Sequencing Analyses. Animals (Basel) 2022; 12:1103. [PMID: 35565529 PMCID: PMC9102740 DOI: 10.3390/ani12091103] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/14/2022] [Accepted: 04/21/2022] [Indexed: 12/27/2022] Open
Abstract
Genome-wide association studies are a robust means of identifying candidate genes that regulate economically important traits in farm animals. The aim of this study is to identify single-nucleotide polymorphisms (SNPs) and candidate genes potentially related to carcass depth and hind leg circumference in Simmental beef cattle. We performed Illumina Bovine HD Beadchip (~670 k SNPs) and next-generation sequencing (~12 million imputed SNPs) analyses of data from 1252 beef cattle, to which we applied a linear mixed model. Using a statistical threshold (p = 0.05/number of SNPs identified) and adopting a false discovery rate (FDR), we identified many putative SNPs on different bovine chromosomes. We identified 12 candidate genes potentially annotated with the markers identified, including CDKAL1 and E2F3, related to myogenesis and skeletal muscle development. The identification of such genes in Simmental beef cattle will help breeders to understand and improve related traits, such as meat yield.
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Rajawat D, Panigrahi M, Kumar H, Nayak SS, Parida S, Bhushan B, Gaur GK, Dutt T, Mishra BP. Identification of important genomic footprints using eight different selection signature statistics in domestic cattle breeds. Gene 2022; 816:146165. [PMID: 35026292 DOI: 10.1016/j.gene.2021.146165] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 12/13/2021] [Accepted: 12/20/2021] [Indexed: 12/25/2022]
Abstract
In the present study, the population genomic data of different cattle breeds were explored to decipher the genomic regions affected due to selective events and reflected in the productive, reproductive, thermo-tolerance, and health-related traits. To find out these genomic deviations due to selective sweeps, we used eight different statistical tools (Tajima's D, Fu & Li's D*, CLR, ROH, iHS, FST, FLK, and hapFLK) on seven indigenous and five exotic cattle breeds. We further performed composite analysis by comparing their covariance matrix. Several candidate genes were found to be related to milk production (ADARB, WDR70, and CA8), reproductive (PARN, FAM134B2, and ZBTB20), and health-related traits (SP110, CXCL2, CLXCL3, CXCL5, IRF8, and MYOM1). The outcome of this investigation provides a basis for detecting selective sweeps that explain the genetic variation of traits. They may possess functional importance for multiple cattle breeds in different subcontinents. However, further studies are required to improve the findings using high-density arrays or whole-genome sequencing with higher resolution and greater sample sizes.
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Affiliation(s)
- Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Subhashree Parida
- Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - G K Gaur
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - B P Mishra
- Division of Animal Biotechnology, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
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14
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Buaban S, Lengnudum K, Boonkum W, Phakdeedindan P. Genome-wide association study on milk production and somatic cell score for Thai dairy cattle using weighted single-step approach with random regression test-day model. J Dairy Sci 2021; 105:468-494. [PMID: 34756438 DOI: 10.3168/jds.2020-19826] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Accepted: 08/24/2021] [Indexed: 12/26/2022]
Abstract
Genome-wide association studies are a powerful tool to identify genomic regions and variants associated with phenotypes. However, only limited mutual confirmation from different studies is available. The objectives of this study were to identify genomic regions as well as genes and pathways associated with the first-lactation milk, fat, protein, and total solid yields; fat, protein, and total solid percentage; and somatic cell score (SCS) in a Thai dairy cattle population. Effects of SNPs were estimated by a weighted single-step GWAS, which back-solved the genomic breeding values predicted using single-step genomic BLUP (ssGBLUP) fitting a single-trait random regression test-day model. Genomic regions that explained at least 0.5% of the total genetic variance were selected for further analyses of candidate genes. Despite the small number of genotyped animals, genomic predictions led to an improvement in the accuracy over the traditional BLUP. Genomic predictions using weighted ssGBLUP were slightly better than the ssGBLUP. The genomic regions associated with milk production traits contained 210 candidate genes on 19 chromosomes [Bos taurus autosome (BTA) 1 to 7, 9, 11 to 16, 20 to 21, 26 to 27 and 29], whereas 21 candidate genes on 3 chromosomes (BTA 11, 16, and 21) were associated with SCS. Many genomic regions explained a small fraction of the genetic variance, indicating polygenic inheritance of the studied traits. Several candidate genes coincided with previous reports for milk production traits in Holstein cattle, especially a large region of genes on BTA14. We identified 141 and 5 novel genes related to milk production and SCS, respectively. These novel genes were also found to be functionally related to heat tolerance (e.g., SLC45A2, IRAG1, and LOC101902172), longevity (e.g., SYT10 and LOC101903327), and fertility (e.g., PAG1). These findings may be attributed to indirect selection in our population. Identified biological networks including intracellular cell transportation and protein catabolism implicate milk production, whereas the immunological pathways such as lymphocyte activation are closely related to SCS. Further studies are required to validate our findings before exploiting them in genomic selection.
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Affiliation(s)
- S Buaban
- Bureau of Animal Husbandry and Genetic Improvement, Department of Livestock Development, Pathum Thani 12000, Thailand
| | - K Lengnudum
- Bureau of Biotechnology in Livestock Production, Department of Livestock Development, Pathum Thani 12000, Thailand
| | - W Boonkum
- Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand
| | - P Phakdeedindan
- Department of Animal Husbandry, Faculty of Veterinary Science, Chulalongkorn University, Bangkok 10330, Thailand; Genomics and Precision Dentistry Research Unit, Department of Physiology, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand.
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15
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Vohra V, Chhotaray S, Gowane G, Alex R, Mukherjee A, Verma A, Deb SM. Genome-Wide Association Studies in Indian Buffalo Revealed Genomic Regions for Lactation and Fertility. Front Genet 2021; 12:696109. [PMID: 34616425 PMCID: PMC8488374 DOI: 10.3389/fgene.2021.696109] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 08/16/2021] [Indexed: 12/26/2022] Open
Abstract
Murrah breed of buffalo is an excellent dairy germplasm known for its superior milk quality in terms of milk fat and solids-not-fat (SNF); however, it is often reported that Indian buffaloes had lower lactation and fertility potential compared to the non-native cattle of the country. Recent techniques, particularly the genome-wide association studies (GWAS), to identify genomic variations associated with lactation and fertility traits offer prospects for systematic improvement of buffalo. DNA samples were sequenced using the double-digestion restriction-associated DNA (RAD) tag genotyping-by-sequencing. The bioinformatics pipeline was standardized to call the variants, and single-nucleotide polymorphisms (SNPs) qualifying the stringent quality check measures were retained for GWAS. Over 38,000 SNPs were used to perform GWAS on the first two principal components of test-day records of milk yields, fat percentages, and SNF percentages, separately. GWAS was also performed on 305 days’ milk yield; lactation persistency was estimated through the rate of decline after attaining the peak yield method, along with three other standard methods; and breeding efficiency, post-partum breeding interval, and age at sexual maturity were considered fertility traits. Significant association of SNPs was observed for the first principal component, explaining the maximum proportion of variation in milk yield. Furthermore, some potential genomic regions were identified to have a potential role in regulating milk yield and fertility in Murrah. Identification of such genomic regions shall help in carrying out an early selection of high-yielding persistent Murrah buffaloes and, in the long run, would be helpful in shaping their future genetic improvement programs.
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Affiliation(s)
- Vikas Vohra
- Buffalo Breeding Lab, Animal Genetics and Breeding Division, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India
| | - Supriya Chhotaray
- Buffalo Breeding Lab, Animal Genetics and Breeding Division, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India
| | - Gopal Gowane
- Buffalo Breeding Lab, Animal Genetics and Breeding Division, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India
| | - Rani Alex
- Buffalo Breeding Lab, Animal Genetics and Breeding Division, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India
| | - Anupama Mukherjee
- Buffalo Breeding Lab, Animal Genetics and Breeding Division, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India
| | - Archana Verma
- Buffalo Breeding Lab, Animal Genetics and Breeding Division, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India
| | - Sitangsu Mohan Deb
- Buffalo Breeding Lab, Animal Genetics and Breeding Division, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India
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Kim S, Lim B, Cho J, Lee S, Dang CG, Jeon JH, Kim JM, Lee J. Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle. Animals (Basel) 2021; 11:ani11051392. [PMID: 34068321 PMCID: PMC8153329 DOI: 10.3390/ani11051392] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 05/07/2021] [Accepted: 05/11/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Milk production traits that are economically important in the dairy industry have been considered the main selection criteria for breeding. The present genome-wide association study was performed to identify chromosomal loci and candidate genes with potential effects on milk production phenotypes in a Korean Holstein population. A total of eight significant quantitative trait locus regions were identified for milk yield (Bos taurus autosome (BTA) 7 and 14), adjusted 305-d fat yield (BTA 3, 5, and 14), adjusted 305-d protein yield (BTA 8), and somatic cell score (BTA 8 and 23) of milk production traits. Furthermore, we discovered three main candidate genes (diacylglycerol O-acyltransferase 1 (DGAT1), phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) through bioinformatics analysis. These genes may help to understand better the underlying genetic and molecular mechanisms for milk production phenotypes in the Korean Holstein population. Abstract We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in Korean Holstein cattle (n = 2780). We identified four significant SNPs for each phenotype in the single marker regression model: AX-311625843 and AX-115099068 on Bos taurus autosome (BTA) 14 for milk yield (MY) and adjusted 305-d fat yield (FY), respectively, AX-428357234 on BTA 18 for adjusted 305-d protein yield (PY), and AX-185120896 on BTA 5 for somatic cell score (SCS). Using the BayesC model, we discovered significant 1-Mb window regions that harbored over 0.5% of the additive genetic variance effects for four milk production phenotypes. The concordant significant SNPs and 1-Mb window regions were characterized into quantitative trait loci (QTL). Among the QTL regions, we focused on a well-known gene (diacylglycerol O-acyltransferase 1 (DGAT1)) and newly identified genes (phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) for MY and FY, and observed that DGAT1 is involved in glycerolipid metabolism, fat digestion and absorption, metabolic pathways, and retinol metabolism, and PDE4B is involved in cAMP signaling. Our findings suggest that the candidate genes in QTL are strongly related to physiological mechanisms related to the fat production and consequent total MY in Korean Holstein cattle.
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Affiliation(s)
- Sangwook Kim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
| | - Byeonghwi Lim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
| | - Joohyeon Cho
- Dairy Cattle Genetic Improvement Center, Nonghyup, Goyang 10292, Gyeonggi-do, Korea; (J.C.); (S.L.)
| | - Seokhyun Lee
- Dairy Cattle Genetic Improvement Center, Nonghyup, Goyang 10292, Gyeonggi-do, Korea; (J.C.); (S.L.)
| | - Chang-Gwon Dang
- Animal Genetics and Breeding Division, National Institute of Animal Science, RDA, Cheonan 31000, Chungcheongnam-do, Korea;
| | - Jung-Hwan Jeon
- Animal Welfare Research Team, National Institute of Animal Science, RDA, Wanju 55365, Jeollabuk-do, Korea;
| | - Jun-Mo Kim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
- Correspondence: (J.-M.K.); (J.L.); Tel.: +82-31-670-3263 (J.-M.K. & J.L.); Fax: +82-31-675-3108 (J.-M.K. & J.L.)
| | - Jungjae Lee
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
- Correspondence: (J.-M.K.); (J.L.); Tel.: +82-31-670-3263 (J.-M.K. & J.L.); Fax: +82-31-675-3108 (J.-M.K. & J.L.)
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Korkuć P, Arends D, May K, König S, Brockmann GA. Genomic Loci Affecting Milk Production in German Black Pied Cattle (DSN). Front Genet 2021; 12:640039. [PMID: 33763120 PMCID: PMC7982544 DOI: 10.3389/fgene.2021.640039] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 02/11/2021] [Indexed: 01/14/2023] Open
Abstract
German Black Pied cattle (DSN) is an endangered population of about 2,550 dual-purpose cattle in Germany. Having a milk yield of about 2,500 kg less than the predominant dairy breed Holstein, the preservation of DSN is supported by the German government and the EU. The identification of the genomic loci affecting milk production in DSN can provide a basis for selection decisions for genetic improvement of DSN in order to increase market chances through the improvement of milk yield. A genome-wide association analysis of 30 milk traits was conducted in different lactation periods and numbers. Association using multiple linear regression models in R was performed on 1,490 DSN cattle genotyped with BovineSNP50 SNP-chip. 41 significant and 20 suggestive SNPs affecting milk production traits in DSN were identified, as well as 15 additional SNPs for protein content which are less reliable due to high inflation. The most significant effects on milk yield in DSN were detected on chromosomes 1, 6, and 20. The region on chromosome 6 was located nearby the casein gene cluster and the corresponding haplotype overlapped the CSN3 gene (casein kappa). Associations for fat and protein yield and content were also detected. High correlation between traits of the same lactation period or number led to some SNPs being significant for multiple investigated traits. Half of all identified SNPs have been reported in other studies, previously. 15 SNPs were associated with the same traits in other breeds. The other associated SNPs have been reported previously for traits such as exterior, health, meat and carcass, production, and reproduction traits. No association could be detected between DGAT1 and other known milk genes with milk production traits despite the close relationship between DSN and Holstein. The results of this study confirmed that many SNPs identified in other breeds as associated with milk traits also affect milk traits in dual-purpose DSN cattle and can be used for further genetic analysis to identify genes and causal variants that affect milk production in DSN cattle.
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Affiliation(s)
- Paula Korkuć
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Animal Breeding Biology and Molecular Genetics, Humboldt University Berlin, Berlin, Germany
| | - Danny Arends
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Animal Breeding Biology and Molecular Genetics, Humboldt University Berlin, Berlin, Germany
| | - Katharina May
- Institute of Animal Breeding and Genetics, Justus-Liebig-University of Giessen, Giessen, Germany
| | - Sven König
- Institute of Animal Breeding and Genetics, Justus-Liebig-University of Giessen, Giessen, Germany
| | - Gudrun A Brockmann
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Animal Breeding Biology and Molecular Genetics, Humboldt University Berlin, Berlin, Germany
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Ariel O, Brouard JS, Marete A, Miglior F, Ibeagha-Awemu E, Bissonnette N. Genome-wide association analysis identified both RNA-seq and DNA variants associated to paratuberculosis in Canadian Holstein cattle 'in vitro' experimentally infected macrophages. BMC Genomics 2021; 22:162. [PMID: 33678157 PMCID: PMC7938594 DOI: 10.1186/s12864-021-07487-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 02/26/2021] [Indexed: 12/22/2022] Open
Abstract
Background Mycobacterium avium ssp. paratuberculosis (MAP) is the causative agent of paratuberculosis, or Johne’s disease (JD), an incurable bovine disease. The evidence for susceptibility to MAP disease points to multiple interacting factors, including the genetic predisposition to a dysregulation of the immune system. The endemic situation in cattle populations can be in part explained by a genetic susceptibility to MAP infection. In order to identify the best genetic improvement strategy that will lead to a significant reduction of JD in the population, we need to understand the link between genetic variability and the biological systems that MAP targets in its assault to dominate macrophages. MAP survives in macrophages where it disseminates. We used next-generation RNA (RNA-Seq) sequencing to study of the transcriptome in response to MAP infection of the macrophages from cows that have been naturally infected and identified as positive for JD (JD (+); n = 22) or negative for JD (healthy/resistant, JD (−); n = 28). In addition to identifying genetic variants from RNA-seq data, SNP variants were also identified using the Bovine SNP50 DNA chip. Results The complementary strategy allowed the identification of 1,356,248 genetic variants, including 814,168 RNA-seq and 591,220 DNA chip variants. Annotation using SnpEff predicted that the 2435 RNA-seq genetic variants would produce high functional effect on known genes in comparison to the 33 DNA chip variants. Significant variants from JD(+/−) macrophages were identified by genome-wide association study and revealed two quantitative traits loci: BTA4 and 11 at (P < 5 × 10− 7). Using BovineMine, gene expression levels together with significant genomic variants revealed pathways that potentially influence JD susceptibility, notably the energy-dependent regulation of mTOR by LKB1-AMPK and the metabolism of lipids. Conclusion In the present study, we succeeded in identifying genetic variants in regulatory pathways of the macrophages that may affect the susceptibility of cows that are healthy/resistant to MAP infection. RNA-seq provides an unprecedented opportunity to investigate gene expression and to link the genetic variations to biological pathways that MAP normally manipulate during the process of killing macrophages. A strategy incorporating functional markers into genetic selection may have a considerable impact in improving resistance to an incurable disease. Integrating the findings of this research into the conventional genetic selection program may allow faster and more lasting improvement in resistance to bovine paratuberculosis in dairy cattle. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07487-4.
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Affiliation(s)
- Olivier Ariel
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, J1M 0C8, Canada
| | - Jean-Simon Brouard
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, J1M 0C8, Canada
| | - Andrew Marete
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, J1M 0C8, Canada
| | - Filippo Miglior
- Center of Genetic Improvement of Livestock, University of Guelph, Guelph, ON, N1G 2W1, Canada.,Canadian Dairy Network, Guelph, ON, N1K 1E5, Canada
| | - Eveline Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, J1M 0C8, Canada
| | - Nathalie Bissonnette
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, J1M 0C8, Canada.
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Islam S, Reddy UK, Natarajan P, Abburi VL, Bajwa AA, Imran M, Zahoor MY, Abdullah M, Bukhari AM, Iqbal S, Ashraf K, Nadeem A, Rehman H, Rashid I, Shehzad W. Population demographic history and population structure for Pakistani Nili-Ravi breeding bulls based on SNP genotyping to identify genomic regions associated with male effects for milk yield and body weight. PLoS One 2020; 15:e0242500. [PMID: 33232358 PMCID: PMC7685427 DOI: 10.1371/journal.pone.0242500] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 11/03/2020] [Indexed: 11/20/2022] Open
Abstract
The domestic Nili-Ravi water buffalo (Bubalus bubalis) is the best dairy animal contributing 68% to total milk production in Pakistan. In this study, we identified genome-wide single nucleotide polymorphisms (SNPs) to estimate various population genetic parameters such as diversity, pairwise population differentiation, linkage disequilibrium (LD) distribution and for genome-wide association study for milk yield and body weight traits in the Nili-Ravi dairy bulls that they may pass on to their daughters who are retained for milking purposes. The genotyping by sequencing approach revealed 13,039 reference genome-anchored SNPs with minor allele frequency of 0.05 among 167 buffalos. Population structure analysis revealed that the bulls were grouped into two clusters (K = 2), which indicates the presence of two different lineages in the Pakistani Nili-Ravi water buffalo population, and we showed the extent of admixture of these two lineages in our bull collection. LD analysis revealed 4169 significant SNP associations, with an average LD decay of 90 kb for these buffalo genome. Genome-wide association study involved a multi-locus mixed linear model for milk yield and body weight to identify genome-wide male effects. Our study further illustrates the utility of the genotyping by sequencing approach for identifying genomic regions to uncover additional demographic complexity and to improve the complex dairy traits of the Pakistani Nili-Ravi water buffalo population that would provide the lot of economic benefits to dairy industry.
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Affiliation(s)
- Saher Islam
- Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Umesh K. Reddy
- Department of Biology, West Virginia State University, Institute, West Virginia, United States of America
| | - Purushothaman Natarajan
- Department of Biology, West Virginia State University, Institute, West Virginia, United States of America
| | - Venkata Lakshmi Abburi
- Department of Biology, West Virginia State University, Institute, West Virginia, United States of America
| | - Amna Arshad Bajwa
- Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Muhammad Imran
- Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Muhammad Yasir Zahoor
- Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Muhammad Abdullah
- Department of Livestock Production, University of Veterinary and Animal Sciences, Pattoki, Pakistan
| | - Aamir Mehmood Bukhari
- Semen Production Unit, Qadirabad, District Sahiwal, Pakistan
- Livestock and Dairy Development Department, Government of the Punjab, Lahore, Pakistan
| | - Sajid Iqbal
- Semen Production Unit, Qadirabad, District Sahiwal, Pakistan
- Livestock and Dairy Development Department, Government of the Punjab, Lahore, Pakistan
| | - Kamran Ashraf
- Department of Parasitology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Asif Nadeem
- Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Habibur Rehman
- Department of Physiology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Imran Rashid
- Department of Parasitology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Wasim Shehzad
- Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan
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20
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Su R, Qiao X, Gao Y, Li X, Jiang W, Chen W, Fan Y, Zheng B, Zhang Y, Liu Z, Wang R, Wang Z, Wang Z, Wan W, Dong Y, Li J. Draft Genome of the European Mouflon ( Ovis orientalis musimon). Front Genet 2020; 11:533611. [PMID: 33329689 PMCID: PMC7710762 DOI: 10.3389/fgene.2020.533611] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 10/26/2020] [Indexed: 11/13/2022] Open
Abstract
Mouflon (Ovis orientalis) with its huge and beautiful horns is considered as one of the ancestors of domesticated sheep. The European mouflon (Ovis orientalis musimon) is in the Asiatic mouflon (O. orientalis) clade. In order to provide novel genome information for mouflon, moreover promote genetic analysis of genus Ovis both domestic and wild, we propose to sequence the mouflon genome. We assembled the highly heterozygous mouflon genome based on Illumina HiSeq platform using the next-generation sequencing technology. Finally, the draft genome we accessed approximately 2.69 Gb (42.15% GC), while N50 sizes of contig and scaffold are 110.1 kb and 10.4 Mb, respectively. The contiguity of this assembly is obviously better than earlier versions. Further analyses predicted 20,814 protein-coding genes in the mouflon genome and 12,390 shared gene families among bovine species. It is estimated that the divergence time between O. orientalis musimon and Ovis aries was 7.6 million years ago. The draft mouflon genome assembly will provide data support and theoretical basis for various investigations of the genus Ovis species in future.
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Affiliation(s)
- Rui Su
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, Hohhot, China
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China
- Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, China
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xian Qiao
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Yun Gao
- NOWBIO Technology Co. Ltd, Kunming, China
| | - Xiaokai Li
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Wei Jiang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Wei Chen
- College of Biological Big Data, Yunnan Agricultural University, Kunming, China
- Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, China
| | - Yixing Fan
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Bingwu Zheng
- Daqingshan Wild Animal Park, Hohhot Gardens Management Bureau, Hohhot, China
| | - Yanjun Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, Hohhot, China
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China
- Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, China
| | - Zhihong Liu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, Hohhot, China
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China
- Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, China
| | - Ruijun Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, Hohhot, China
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China
- Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, China
| | - Zhiying Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, Hohhot, China
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China
- Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, China
| | - Zhixin Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, Hohhot, China
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China
- Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, China
| | - Wenting Wan
- Key Laboratory for Space Bioscience and Biotechnology, Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi’an, China
| | - Yang Dong
- College of Biological Big Data, Yunnan Agricultural University, Kunming, China
- Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, China
| | - Jinquan Li
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, Hohhot, China
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China
- Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, China
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Mohammadi A, Alijani S, Rafat SA, Abdollahi-arpanahi R. Genome-Wide Association Study and Pathway Analysis for Female Fertility Traits in Iranian Holstein Cattle. Annals of Animal Science 2020; 20:825-51. [DOI: 10.2478/aoas-2020-0031] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Abstract
Female fertility is an important trait that contributes to cow’s profitability and it can be improved by genomic information. The objective of this study was to detect genomic regions and variants affecting fertility traits in Iranian Holstein cattle. A data set comprised of female fertility records and 3,452,730 pedigree information from Iranian Holstein cattle were used to predict the breeding values, which were then employed to estimate the de-regressed proofs (DRP) of genotyped animals. A total of 878 animals with DRP records and 54k SNP markers were utilized in the genome-wide association study (GWAS). The GWAS was performed using a linear regression model with SNP genotype as a linear covariate. The results showed that an SNP on BTA19, ARS-BFGL-NGS-33473, was the most significant SNP associated with days from calving to first service. In total, [69] significant SNPs were located within 27 candidate genes. Novel potential candidate genes include OSTN, DPP6, EphA5, CADPS2, Rfc1, ADGRB3, Myo3a, C10H14orf93, KIAA1217, RBPJL, SLC18A2, GARNL3, NCALD, ASPH, ASIC2, OR3A1, CHRNB4, CACNA2D2, DLGAP1, GRIN2A and ME3. These genes are involved in different pathways relevant to female fertility and other characteristics in mammals. Gene set enrichment analysis showed that thirteen GO terms had significant overrepresentation of genes statistically associated with female fertility traits. The results of network analysis identified CCNB1 gene as a hub gene in the progesterone-mediated oocyte maturation pathway, significantly associated with age at first calving. The candidate genes identified in this study can be utilized in genomic tests to improve reproductive performance in Holstein cattle.
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Rasheed A, Usman T, Niaz K. A Review on Bovine Mastitis with Special Focus on CD4 as a Potential Candidate Gene for Mastitis Resistance – A Review. Annals of Animal Science 2020; 20:735-55. [DOI: 10.2478/aoas-2020-0024] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Abstract
Mastitis is аn inflammation оf thе mammary gland, caused by the invasion and duplication оf Escherichia coli (E. coli), Staphylococcus uberis (S. uberis) аnd Staphylococcus aureus (S. aureus) аnd а wide variety оf оthеr microorganisms thrоugh teat оr damaged nipple, decreasing potential milk production іn thе affected quarter оf mammary gland. Economic, animal productivity, international trade and animal welfare issues associated with mastitis play an important role in the agricultural industry. Therefore, worldwide dairy cattle breeding programmes are trying to breed cows wіth improved resistance tо mastitis. Mastitis can’t be eliminated but can be reduced to a low level. It can be achieved by breeding strategies, reducing the exposure to pathogen and increasing the resistance to intramammary infection. Numerous therapeutic, prophylactic аnd management techniques аrе uѕеd аѕ control and reduce the mastitis. However, а widely proposed strategy marker assisted selection uѕіng candidate gene approach which іѕ based оn improving thе host genetics. One of them is cluster of differentiation 4 (CD4) gene, which is а glycoprotein located оn receptors оf immune cells. CD4 exhibit аn essential role іn a variety of inflammation related conditions іn mаnу species. Therefore, CD4 as a candidate gene for resistance to mastitis has received considerable attention. The review is based on a study of CD4 in association with improving resistance to mastitis and it may be helpful in formulating breeding programmes and marker assisted selection to lower the mastitis.
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23
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Affiliation(s)
- Wenjun Zhu
- Department of Space Information Engineering, Henan College of Surveying and Mapping, Henan, China
| | - Huisheng Shi
- Department of Remote Sensing Engineering, Henan College of Surveying and Mapping, Henan, China
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Li C, Cai W, Liu S, Zhou C, Cao M, Yin H, Sun D, Zhang S, Loor JJ. Association of UDP-galactose-4-epimerase with milk protein concentration in the Chinese Holstein population. Asian-Australas J Anim Sci 2020; 33:1725-1731. [PMID: 32106650 PMCID: PMC7649079 DOI: 10.5713/ajas.19.0549] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 02/14/2020] [Indexed: 01/20/2023]
Abstract
Objective An initial RNA-Sequencing study revealed that UDP-galactose-4-epimerase (GALE) was one of the most promising candidates for milk protein concentration in Chinese Holstein cattle. This enzyme catalyzes the interconversion of UDP-galactose and UDP-glucose, an important step in galactose catabolism. To further validate the genetic effect of GALE on milk protein traits, genetic variations were identified, and genotypes-phenotypes associations were performed. Methods The entire coding region and the 5′-regulatory region (5′-UTR) of GALE were re-sequenced using pooled DNA of 17 unrelated sires. Association studies for five milk production traits were performed using a mixed linear animal model with a population encompassing 1,027 Chinese Holstein cows. Results A total of three variants in GALE were identified, including two novel variants (g.2114 A>G and g.2037 G>A) in the 5′-UTR and one previously reported variant (g.3836 G>C) in an intron. All three single nucleotide polymorphisms (SNPs) were associated with milk yield (p<0.0001), fat yield (p = 0.0006 to <0.0001), protein yield (p = 0.0232 to <0.0001) and protein percentage (p<0.0001), while no significant associations were detected between the SNPs and fat percentage. A strong linkage disequilibrium (D’ = 0.96 to 1.00) was observed among all three SNPs, and a 5 Kb haplotype block involving three main haplotypes with GAG, AGC, and AGG was formed. The results of haplotype association analyses were consistent with the results of single locus association analysis (p<0.0001). The phenotypic variance ratio above 3.00% was observed for milk protein yield that was explained by SNP-g.3836G >C. Conclusion Overall, our findings provided new insights into the polymorphic variations in bovine GALE gene and their associations with milk protein concentration. The data indicate their potential uses for marker-assisted breeding or genetic selection schemes.
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Affiliation(s)
- Cong Li
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Wentao Cai
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Shuli Liu
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Chenghao Zhou
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Mingyue Cao
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Hongwei Yin
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Dongxiao Sun
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Shengli Zhang
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Juan J Loor
- Mammalian NutriPhysioGenomics, Department of Animal Sciences and Division of Nutritional Sciences, University of Illinois, Urbana, IL 61801, USA
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Do DN, Bissonnette N, Lacasse P, Miglior F, Zhao X, Ibeagha-Awemu EM. A targeted genotyping approach to enhance the identification of variants for lactation persistency in dairy cows. J Anim Sci 2019; 97:4066-4075. [PMID: 31581300 DOI: 10.1093/jas/skz279] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 09/13/2019] [Indexed: 12/19/2022] Open
Abstract
Lactation persistency (LP), defined as the ability of a cow to maintain milk production at a high level after milk peak, is an important phenotype for the dairy industry. In this study, we used a targeted genotyping approach to scan for potentially functional single nucleotide polymorphisms (SNPs) within 57 potential candidate genes derived from our previous genome wide association study on LP and from the literature. A total of 175,490 SNPs were annotated within 10-kb flanking regions of the selected candidate genes. After applying several filtering steps, a total of 105 SNPs were retained for genotyping using target genotyping arrays. SNP association analyses were performed in 1,231 Holstein cows with 69 polymorphic SNPs using the univariate liner mixed model with polygenic effects using DMU package. Six SNPs including rs43770847, rs208794152, and rs208332214 in ADRM1; rs209443540 in C5orf34; rs378943586 in DDX11; and rs385640152 in GHR were suggestively significantly associated with LP based on additive effects and associations with 4 of them (rs43770847, rs208794152, rs208332214, and rs209443540) were based on dominance effects at P < 0.05. However, none of the associations remained significant at false discovery rate adjusted P (FDR) < 0.05. The additive variances explained by each suggestively significantly associated SNP ranged from 0.15% (rs43770847 in ADRM1) to 5.69% (rs209443540 in C5orf34), suggesting that these SNPs might be used in genetic selection for enhanced LP. The percentage of phenotypic variance explained by dominance effect ranged from 0.24% to 1.35% which suggests that genetic selection for enhanced LP might be more efficient by inclusion of dominance effects. Overall, this study identified several potentially functional variants that might be useful for selection programs for higher LP. Finally, a combination of identification of potentially functional variants followed by targeted genotyping and association analysis is a cost-effective approach for increasing the power of genetic association studies.
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Affiliation(s)
- Duy Ngoc Do
- Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC, Canada.,Department of Animal Science and Aquaculture, Dalhousie University, Truro, Canada
| | - Nathalie Bissonnette
- Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC, Canada
| | - Pierre Lacasse
- Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC, Canada
| | - Filippo Miglior
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Canada
| | - Xin Zhao
- Department of Animal Science, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Eveline M Ibeagha-Awemu
- Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC, Canada
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Bordbar F, Jensen J, Zhu B, Wang Z, Xu L, Chang T, Xu L, Du M, Zhang L, Gao H, Xu L, Li J. Identification of muscle-specific candidate genes in Simmental beef cattle using imputed next generation sequencing. PLoS One 2019; 14:e0223671. [PMID: 31600309 PMCID: PMC6786524 DOI: 10.1371/journal.pone.0223671] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 09/25/2019] [Indexed: 01/01/2023] Open
Abstract
Genome-wide association studies (GWAS) have commonly been used to identify candidate genes that control economically important traits in livestock. Our objective was to detect potential candidate genes associated mainly with muscle development traits related to dimension of hindquarter in cattle. A next generation sequencing (NGS) dataset to imputed to 12 million single nucleotide polymorphisms (SNPs) (from 1252 Simmental beef cattle) were used to search for genes affecting hindquarter traits using a linear, mixed model approach. We also used haplotype and linkage disequilibrium blocks to further support our identifications. We identified 202 significant SNPs in the bovine BTA4 chromosome region associated with width of hind leg, based on a stringent statistical threshold (p = 0.05/ effective number of SNPs identified). After exploring the region around these SNPs, we found candidate genes that were potentially related to the associated markers. More importantly, we identified a region of approximately 280 Kb on the BTA4 chromosome that harbored several muscle specific candidate genes, genes to be in a potential region for muscle development. However, we also found candidate gene SLC13A1 on BTA4, which seems to be associated with bone disorders (such as chondrodysplasia) in Simmental beef cattle.
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Affiliation(s)
- Farhad Bordbar
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Just Jensen
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Bo Zhu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zezhao Wang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lei Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianpeng Chang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ling Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Min Du
- Department of Animal Sciences, Washington Center for Muscle Biology, Washington State University, Pullman, Washington, United States of America
| | - Lupei Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huijiang Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lingyang Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
- * E-mail: (JYL); (LYX)
| | - Junya Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
- * E-mail: (JYL); (LYX)
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Atashi H, Salavati M, De Koster J, Ehrlich J, Crowe M, Opsomer G, Hostens M. Genome-wide association for milk production and lactation curve parameters in Holstein dairy cows. J Anim Breed Genet 2019; 137:292-304. [PMID: 31576624 PMCID: PMC7217222 DOI: 10.1111/jbg.12442] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 09/07/2019] [Accepted: 09/12/2019] [Indexed: 12/31/2022]
Abstract
The aim of this study was to identify genomic regions associated with 305‐day milk yield and lactation curve parameters on primiparous (n = 9,910) and multiparous (n = 11,158) Holstein cows. The SNP solutions were estimated using a weighted single‐step genomic BLUP approach and imputed high‐density panel (777k) genotypes. The proportion of genetic variance explained by windows of 50 consecutive SNP (with an average of 165 Kb) was calculated, and regions that accounted for more than 0.50% of the variance were used to search for candidate genes. Estimated heritabilities were 0.37, 0.34, 0.17, 0.12, 0.30 and 0.19, respectively, for 305‐day milk yield, peak yield, peak time, ramp, scale and decay for primiparous cows. Genetic correlations of 305‐day milk yield with peak yield, peak time, ramp, scale and decay in primiparous cows were 0.99, 0.63, 0.20, 0.97 and −0.52, respectively. The results identified three windows on BTA14 associated with 305‐day milk yield and the parameters of lactation curve in primi‐ and multiparous cows. Previously proposed candidate genes for milk yield supported by this work include GRINA, CYHR1, FOXH1, TONSL, PPP1R16A, ARHGAP39, MAF1, OPLAH and MROH1, whereas newly identified candidate genes are MIR2308, ZNF7, ZNF34, SLURP1, MAFA and KIFC2 (BTA14). The protein lipidation biological process term, which plays a key role in controlling protein localization and function, was identified as the most important term enriched by the identified genes.
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Affiliation(s)
- Hadi Atashi
- Department of Reproduction, Obstetrics and Herd Health, Ghent University, Merelbeke, Belgium.,Department of Animal Science, Shiraz University, Shiraz, Iran
| | - Mazdak Salavati
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
| | - Jenne De Koster
- Department of Reproduction, Obstetrics and Herd Health, Ghent University, Merelbeke, Belgium
| | | | - Mark Crowe
- University College Dublin, Dublin, Ireland
| | - Geert Opsomer
- Department of Reproduction, Obstetrics and Herd Health, Ghent University, Merelbeke, Belgium
| | | | - Miel Hostens
- Department of Reproduction, Obstetrics and Herd Health, Ghent University, Merelbeke, Belgium
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Xu L, Yang L, Zhu B, Zhang W, Wang Z, Chen Y, Zhang L, Gao X, Gao H, Liu GE, Li J. Genome-wide scan reveals genetic divergence and diverse adaptive selection in Chinese local cattle. BMC Genomics 2019; 20:494. [PMID: 31200634 DOI: 10.1186/s12864-019-5822-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 05/21/2019] [Indexed: 01/18/2023] Open
Abstract
Background Understanding the population structure and genetic bases of well-adapted cattle breeds to local environments is one of the most essential tasks to develop appropriate genetic improvement programs. Results We performed a comprehensive study to investigate the population structure, divergence and selection signatures at genome-wide level in diverse Chinese local cattle using Bovine HD SNPs array, including two breeds from North China, one breed from Northwest China, three breeds from Southwest China and two breeds from South China. Population genetic analyses revealed the genetic structures of these populations were mostly related to the geographic locations. Notably, we detected 294 and 1263 candidate regions under selection using the di and iHS approaches, respectively. A series of group-specific and breed-specific candidate genes were identified, which are involved in immune response, sexual maturation, stature related, birth and bone weight, embryonic development, coat colors and adaptation. Furthermore, haplotype diversity and network pattern for candidate genes, including LPGAT1, LCORL, PPP1R8, RXFP2 and FANCA, suggest that these genes have been under differential selection pressures in various environmental conditions. Conclusions Our results shed insights into diverse selection during breed formation in Chinese local cattle. These findings may promote the application of genome-assisted breeding for well-adapted local breeds with economic and ecological importance. Electronic supplementary material The online version of this article (10.1186/s12864-019-5822-y) contains supplementary material, which is available to authorized users.
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Xu L, Shi L, Liu L, Liang R, Li Q, Li J, Han B, Sun D. Analysis of Liver Proteome and Identification of Critical Proteins Affecting Milk Fat, Protein, and Lactose Metabolism in Dariy Cattle with iTRAQ. Proteomics 2019; 19:e1800387. [DOI: 10.1002/pmic.201800387] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 03/12/2019] [Indexed: 02/02/2023]
Affiliation(s)
- Lingna Xu
- Department of Animal GeneticsBreeding and ReproductionCollege of Animal Science and TechnologyKey Laboratory of Animal GeneticsBreeding and Reproduction of Ministry of Agriculture and Rural AffairsNational Engineering Laboratory for Animal BreedingChina Agricultural University Beijing 100193 China
| | - Lijun Shi
- Department of Animal GeneticsBreeding and ReproductionCollege of Animal Science and TechnologyKey Laboratory of Animal GeneticsBreeding and Reproduction of Ministry of Agriculture and Rural AffairsNational Engineering Laboratory for Animal BreedingChina Agricultural University Beijing 100193 China
| | - Lin Liu
- Beijing Dairy Cattle Center Beijing 100192 China
| | - Ruobing Liang
- Department of Animal GeneticsBreeding and ReproductionCollege of Animal Science and TechnologyKey Laboratory of Animal GeneticsBreeding and Reproduction of Ministry of Agriculture and Rural AffairsNational Engineering Laboratory for Animal BreedingChina Agricultural University Beijing 100193 China
| | - Qian Li
- Department of Animal Production and Environmental ControlCollege of Animal Science and TechnologyHebei Agricultural University Baoding 071001 China
| | - Jianguo Li
- Department of Animal Production and Environmental ControlCollege of Animal Science and TechnologyHebei Agricultural University Baoding 071001 China
| | - Bo Han
- Department of Animal GeneticsBreeding and ReproductionCollege of Animal Science and TechnologyKey Laboratory of Animal GeneticsBreeding and Reproduction of Ministry of Agriculture and Rural AffairsNational Engineering Laboratory for Animal BreedingChina Agricultural University Beijing 100193 China
| | - Dongxiao Sun
- Department of Animal GeneticsBreeding and ReproductionCollege of Animal Science and TechnologyKey Laboratory of Animal GeneticsBreeding and Reproduction of Ministry of Agriculture and Rural AffairsNational Engineering Laboratory for Animal BreedingChina Agricultural University Beijing 100193 China
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Jiang J, Liu L, Gao Y, Shi L, Li Y, Liang W, Sun D. Determination of genetic associations between indels in 11 candidate genes and milk composition traits in Chinese Holstein population. BMC Genet 2019; 20:48. [PMID: 31138106 PMCID: PMC6537361 DOI: 10.1186/s12863-019-0751-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 05/20/2019] [Indexed: 01/20/2023] Open
Abstract
Background We have previously identified 11 promising candidate genes for milk composition traits by resequencing the whole genomes of 8 Holstein bulls with extremely high and low estimated breeding values for milk protein and fat percentages (high and low groups), including FCGR2B, CENPE, RETSAT, ACSBG2, NFKB2, TBC1D1, NLK, MAP3K1, SLC30A2, ANGPT1 and UGDH those contained 25 indels between high and low groups. In this study, the purpose was to further examine whether these candidates have significant genetic effects on milk protein and fat traits. Results With PCR product sequencing, 13 indels identified by whole genome resequencing were successfully genotyped. With association analysis in 769 Chinese Holstein cows, we found that the indel in FCGR2B was significantly associated with milk yield, protein yield and protein percentage (P = 0.0041 to 0.0297); five indels in CENPE and one indel in MAP3K1 were markedly relevant to milk yield, fat yield and protein yield (P < 0.0001 to 0.0073); polymorphism in RETSAT was evidently associated with milk yield, fat yield, protein yield and protein percentage (P = 0.0001 to 0.0237); variant in ACSBG2 affected fat yield and protein percentage (P = 0.0088 and 0.0052); one indel in TBC1D1 was with respect to fat percentage and protein percentage (P = 0.0224 and 0.0209). Significant associations were shown between indels in NLK and protein yield and protein percentage (P = 0.0012 to 0.0257); variant in UGDH was related to the milk yield (P = 0.0312). The two exonic indels in FCGR2B and CENPE were predicted to change the mRNA and protein secondary structures, and resulted in the corresponding protein dysfunction. Conclusion Our findings presented here provide the first evidence for the associations of eight functional genes with milk yield and composition traits in dairy cattle. Electronic supplementary material The online version of this article (10.1186/s12863-019-0751-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jianping Jiang
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100193, China.,College of Animal Science and Technology, Guangxi University, Nanning, 530004, China
| | - Lin Liu
- Beijing Dairy Cattle Center, Beijing, 100085, China
| | - Yahui Gao
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100193, China
| | - Lijun Shi
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100193, China
| | - Yanhua Li
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100193, China.,Beijing Dairy Cattle Center, Beijing, 100085, China
| | - Weijun Liang
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100193, China
| | - Dongxiao Sun
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100193, China.
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Gebreyesus G, Buitenhuis AJ, Poulsen NA, Visker MHPW, Zhang Q, van Valenberg HJF, Sun D, Bovenhuis H. Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition. BMC Genomics 2019; 20:178. [PMID: 30841852 PMCID: PMC6404302 DOI: 10.1186/s12864-019-5573-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Accepted: 02/28/2019] [Indexed: 01/23/2023] Open
Abstract
Background The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation. GWAS often detect broader genomic regions containing several positional candidate genes making it difficult to untangle the causative candidates. Post-GWAS analyses with data on pathways, ontology and tissue-specific gene expression status might allow prioritization among positional candidate genes. Results Multi-population GWAS for 16 FA traits quantified using gas chromatography (GC) in sample populations of the Chinese, Danish and Dutch Holstein with high-density (HD) genotypes detects 56 genomic regions significantly associated to at least one of the studied FAs; some of which have not been previously reported. Pathways and gene ontology (GO) analyses suggest promising candidate genes on the novel regions including OSBPL6 and AGPS on Bos taurus autosome (BTA) 2, PRLH on BTA 3, SLC51B on BTA 10, ABCG5/8 on BTA 11 and ALG5 on BTA 12. Novel genes in previously known regions, such as FABP4 on BTA 14, APOA1/5/7 on BTA 15 and MGST2 on BTA 17, are also linked to important FA metabolic processes. Conclusion Integration of multi-population GWAS and enrichment analyses enabled detection of several novel genomic regions, explaining relatively smaller fractions of the genetic variation, and revealed highly likely candidate genes underlying the effects. Detection of such regions and candidate genes will be crucial in understanding the complex genetic control of FA metabolism. The findings can also be used to augment genomic prediction models with regions collectively capturing most of the genetic variation in the milk FA traits. Electronic supplementary material The online version of this article (10.1186/s12864-019-5573-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- G Gebreyesus
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Blichers Allé 20, P.O. Box 50, DK-8830, Tjele, Denmark. .,Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, the Netherlands.
| | - A J Buitenhuis
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Blichers Allé 20, P.O. Box 50, DK-8830, Tjele, Denmark
| | - N A Poulsen
- Department of Food Science, Aarhus University, Blichers Allé 20, P.O. Box 50, DK-8830, Tjele, Denmark
| | - M H P W Visker
- Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, the Netherlands
| | - Q Zhang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H J F van Valenberg
- Dairy Science and Technology Group, Wageningen University and Research, P.O. Box 17, 6700 AA, Wageningen, the Netherlands
| | - D Sun
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H Bovenhuis
- Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, the Netherlands
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Li Y, Han B, Liu L, Zhao F, Liang W, Jiang J, Yang Y, Ma Z, Sun D. Genetic association of DDIT3, RPL23A, SESN2 and NR4A1 genes with milk yield and composition in dairy cattle. Anim Genet 2019; 50:123-135. [PMID: 30815908 DOI: 10.1111/age.12750] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2018] [Indexed: 01/15/2023]
Abstract
Previously, we identified by RNA sequencing that DDIT3, RPL23A, SESN2 and NR4A1 genes were significantly differentially expressed between the mammary glands of lactating Holstein cows with extremely high and low milk protein and fat percentages; thus, these four genes are considered as promising candidates potentially affecting milk yield and composition traits in dairy cattle. In the present study, we further verified whether these genes have genetic effects on milk traits in a Chinese Holstein population. By re-sequencing part of the non-coding and the entire coding regions of the DDIT3, RPL23A, SESN2 and NR4A1 genes, a total of 35 SNPs and three insertions/deletions were identified, of which three were found in DDIT3, 12 in RPL23A, 16 in SESN2 and seven in NR4A1. Moreover, two of the insertions/deletions-g.125714860_125714872del and g.125714806delinsCCCC in SESN2-were novel and have not been reported previously. Subsequent single SNP analyses revealed multiple significant association with all 35 SNPs and three indels regressed against the dairy production traits (P-value = <0.0001-0.0493). In addition, with a linkage disequilibrium analysis, we found one, one, three, and one haplotype blocks in the DDIT3, RPL23A, SESN2 and NR4A1 genes respectively. Haplotype-based association analyses revealed that some haplotypes were also significantly associated with milk production traits (P-value = <0.0001-0.0461). We also found that 12 SNPs and two indels (two in DDIT3, two in RPL23A, nine in SESN2 and one in NR4A1) altered the specific transcription factor binding sites in the promoter, thereby regulating promoter activity, suggesting that they might be promising potential functional variants for milk traits. In summary, our findings first determined the genetic associations of DDIT3, RPL23A, SESN2 and NR4A1 with milk yield and composition traits in dairy cattle and also suggested potentially causal variants, which require in-depth validation.
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Affiliation(s)
- Y Li
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Beijing, 100193, China.,Beijing Dairy Cattle Center, Beijing, 100192, China
| | - B Han
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Beijing, 100193, China
| | - L Liu
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - F Zhao
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - W Liang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Beijing, 100193, China
| | - J Jiang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Beijing, 100193, China
| | - Y Yang
- Beijing Municipal Bureau of Agriculture, Beijing, 100101, China
| | - Z Ma
- 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, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Beijing, 100193, China
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Li C, Wang M, Cai W, Liu S, Zhou C, Yin H, Sun D, Zhang S. Genetic Analyses Confirm SNPs in HSPA8 and ERBB2 are Associated with Milk Protein Concentration in Chinese Holstein Cattle. Genes (Basel) 2019; 10:E104. [PMID: 30704154 DOI: 10.3390/genes10020104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 01/25/2019] [Accepted: 01/28/2019] [Indexed: 11/17/2022] Open
Abstract
Heat shock 70 kDa protein 8 (HSPA8) and erb-b2 receptor tyrosine kinase 2 (ERBB2) were the promising candidates for milk protein concentration in dairy cattle revealed through previous RNA sequencing (RNA-Seq) study. The objective of this post-RNA-Seq study was to confirm genetic effects of HSPA8 and ERBB2 on milk protein concentration in a large Chinese Holstein population and to evaluate the genetic effects of both genes on other milk production traits. There were 2 single-nucleotide polymorphisms (SNPs) identified for HSPA8 and 11 SNPs for ERBB2 by sequencing 17 unrelated Chinese Holstein sires. The SNP-rs136632043 in HSPA8 had significant associations with all five milk production traits (p = 0.0086 to p < 0.0001), whereas SNP-rs132976221 was remarkably associated with three yield traits (p < 0.0001). Nine (ss1996900615, rs109017161, rs109122971, ss1996900614, rs110133654, rs109941438, rs110552983, rs133031530, and rs109763505) of 11 SNPs in ERBB2 were significantly associated with milk protein percentage (p = 0.0177 to p < 0.0001). A 12 Kb haplotype block was formed in ERBB2 and haplotype associations revealed similar effects on milk protein traits. Our findings confirmed the significant genetic effects of HSPA8 and ERBB2 on milk protein concentration and other milk production traits and SNP phenotypic variances above 1% may serve as genetic markers in dairy cattle breeding programs.
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HONG MINWOOK, CHOI SOYOUNG, SINGH NARESHKUMAR, KIM HUN, YANG SONGYI, KWAK KYEONGROK, KIM JONGBOK, LEE SUNGJIN. Genome-wide association analysis to identify QTL for carcass traits in Hanwoo (Korean native cattle). Indian J of Anim Sci 2019. [DOI: 10.56093/ijans.v89i1.86384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
A genome-wide association study (GWAS) was performed to investigate the genetic markers associated with carcass traits of Hanwoo (Bos taurus coreanae) steer in the Gangwon region of Korea. Hanwoo steer (139) from the Gangwon region were genotyped with Bovine SNP50K BeadChip, and 35,769 SNPs were analyzed for five specific carcass traits after applying several filters. A total of seven quantitative trait loci were detected, of which four, one, and 2 SNPs were detected on various B. taurus autosomal chromosomes (BTA) by the respective model. The four significant SNPs associated with backfat thickness were ARS-BFGL-NGS–41475 on BTA 5, ARS-BFGLNGS- 36359 on BTA 19, ARS-BFGL-NGS-56813 on BTA 22, and Hapmap25048-BTA-138242 on BTA 25. Among the detected SNPs, one and two SNPs were associated with marbling score (ARS-BFGL-NGS-110066 on BTA 23) and meat colour (BTB-01920239 on BTA 15 and ARS-BFGL-NGS-24934 on BTA 18). In this GWAS, we identified three positional candidate genes for carcass traits, backfat thickness (Fibulin-2, FBLN2; Sorting nexin 29, SNX29) and meat colour (WW domain containing oxidoreductase, WWOX). Our results suggest that the candidate SNP markers do affect the genomic selection of associated carcass traits for Hanwoo in the Gangwon region.
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SHARMA UPASNA, BANERJEE PRIYANKA, JOSHI JYOTI, KAPOOR PRERNA, VIJH RAMESHKUMAR. Identification of quantitative trait loci for fat percentage in buffaloes. Indian J of Anim Sci 2018. [DOI: 10.56093/ijans.v88i6.80890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
The milk fat percentage records of 2174 daughters belonging to 12 half sib families were analyzed for the identification of QTLs on 8 chromosomes in buffaloes using chromosome scans. The single marker analysis revealed 49 markers to be associated with milk fat percentage in 10 sire families. The interval mapping using R/qtl identified 43 QTLs on 8 chromosomes of buffalo. The meta-QTL analysis was carried out to define consensus QTLs in buffaloes and total 28 meta-QTL regions could be identified for milk fat percentage. Most of the QTLs identified in the experiments have been reported for cattle; however, few new chromosomal locations were also identified to be associated with fat percentage in buffaloes. The additional QTLs identified in buffalo may be due to high level of heterozygosity in buffalo compared to Holstein Friesian and other exotic milk breeds for which QTLs have beenreported. Assuming buffalo-cattle synteny, a total of 1118 genes were identified underlying the QTL regions, out of these 45 genes were identified to be associated with lipid metabolism. The interaction among the genes and gene ontology analysis confirmed their association with lipid metabolism. These 45 genes have potential to be candidate genes for milk fat percentage in buffaloes and underlie the QTL regions identified in buffaloes in the present study.
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Wang Q, Bovenhuis H. Genome-wide association study for milk infrared wavenumbers. J Dairy Sci 2018; 101:2260-2272. [DOI: 10.3168/jds.2017-13457] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Accepted: 11/20/2017] [Indexed: 12/28/2022]
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Chen Z, Yao Y, Ma P, Wang Q, Pan Y. Haplotype-based genome-wide association study identifies loci and candidate genes for milk yield in Holsteins. PLoS One 2018; 13:e0192695. [PMID: 29447209 DOI: 10.1371/journal.pone.0192695] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Accepted: 01/29/2018] [Indexed: 11/23/2022] Open
Abstract
Since milk yield is a highly important economic trait in dairy cattle, the genome-wide association study (GWAS) is vital to explain the genetic architecture underlying milk yield and to perform marker-assisted selection (MAS). In this study, we adopted a haplotype-based empirical Bayesian GWAS to identify the loci and candidate genes for milk yield. A total of 1 092 Holstein cows were sequenced by using the genotyping by genome reducing and sequencing (GGRS) method. After filtering, 164 312 high-confidence SNPs and 13 476 haplotype blocks were identified to use for GWAS. The results indicated that 17 blocks were significantly associated with milk yield. We further identified the nearest gene of each haplotype block and annotated the genes with milk-associated quantitative trait locus (QTL) intervals and ingenuity pathway analysis (IPA) networks. Our analysis showed that four genes, DLGAP1, AP2B1, ITPR2 and THBS4, have relationships with milk yield, while another three, ARHGEF4, TDRD1 and KIF19, were inferred to have potential relationships. Additionally, a network derived from the IPA containing one inferred (ARHGEF4) and all four confirmed genes likely regulates milk yield. Our findings add to the understanding of identifying the causal genes underlying milk production traits and could guide follow up studies for further confirmation of the associated genes, pathways and biological networks.
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Iamartino D, Nicolazzi EL, Van Tassell CP, Reecy JM, Fritz-Waters ER, Koltes JE, Biffani S, Sonstegard TS, Schroeder SG, Ajmone-Marsan P, Negrini R, Pasquariello R, Ramelli P, Coletta A, Garcia JF, Ali A, Ramunno L, Cosenza G, de Oliveira DAA, Drummond MG, Bastianetto E, Davassi A, Pirani A, Brew F, Williams JL. Design and validation of a 90K SNP genotyping assay for the water buffalo (Bubalus bubalis). PLoS One 2017; 12:e0185220. [PMID: 28981529 PMCID: PMC5628821 DOI: 10.1371/journal.pone.0185220] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2016] [Accepted: 09/10/2017] [Indexed: 11/28/2022] Open
Abstract
Background The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here. Methods The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K. Results This 90K “SNP-Chip” was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production. Conclusion The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised.
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Affiliation(s)
- Daniela Iamartino
- AIA-LGS Associazione Italiana Allevatori–Laboratorio Genetica e Servizi, Cremona, Italy
- Fondazione Parco Tecnologico Padano, Lodi, Italy
- * E-mail:
| | | | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | - Eric R. Fritz-Waters
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | - James E. Koltes
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | | | - Tad S. Sonstegard
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - Paolo Ajmone-Marsan
- Institute of Zootechnics, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Riccardo Negrini
- AIA-LGS Associazione Italiana Allevatori–Laboratorio Genetica e Servizi, Cremona, Italy
- Institute of Zootechnics, Università Cattolica del S. Cuore, Piacenza, Italy
| | | | | | - Angelo Coletta
- ANASB-Associazione Nazionale Allevatori Specie Bufalina, Centurano—Caserta, Italy
| | - José F. Garcia
- Universidade Estadual Paulista (UNESP), Câmpus de Araçatuba, Sao Paulo, Brazil
| | - Ahmad Ali
- COMSATS Institute of Information Technology, Sahiwal, Pakistan
| | - Luigi Ramunno
- Dipartimento di Scienze Zootecniche ed Ispezione degli Alimenti, Facoltà di Agraria, Università degli Studi di Napoli Federico II, Portici (NA), Italy
| | - Gianfranco Cosenza
- Dipartimento di Scienze Zootecniche ed Ispezione degli Alimenti, Facoltà di Agraria, Università degli Studi di Napoli Federico II, Portici (NA), Italy
| | | | | | | | | | - Ali Pirani
- Affymetrix UK Ltd, High Wycombe, United Kingdom
| | - Fiona Brew
- Affymetrix UK Ltd, High Wycombe, United Kingdom
| | - John L. Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, Australia
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Martin P, Palhière I, Maroteau C, Bardou P, Canale-Tabet K, Sarry J, Woloszyn F, Bertrand-Michel J, Racke I, Besir H, Rupp R, Tosser-Klopp G. A genome scan for milk production traits in dairy goats reveals two new mutations in Dgat1 reducing milk fat content. Sci Rep 2017; 7:1872. [PMID: 28500343 PMCID: PMC5431851 DOI: 10.1038/s41598-017-02052-0] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Accepted: 04/05/2017] [Indexed: 11/21/2022] Open
Abstract
The quantity of milk and milk fat and proteins are particularly important traits in dairy livestock. However, little is known about the regions of the genome that influence these traits in goats. We conducted a genome wide association study in French goats and identified 109 regions associated with dairy traits. For a major region on chromosome 14 closely associated with fat content, the Diacylglycerol O-Acyltransferase 1 (DGAT1) gene turned out to be a functional and positional candidate gene. The caprine reference sequence of this gene was completed and 29 polymorphisms were found in the gene sequence, including two novel exonic mutations: R251L and R396W, leading to substitutions in the protein sequence. The R251L mutation was found in the Saanen breed at a frequency of 3.5% and the R396W mutation both in the Saanen and Alpine breeds at a frequencies of 13% and 7% respectively. The R396W mutation explained 46% of the genetic variance of the trait, and the R251L mutation 6%. Both mutations were associated with a notable decrease in milk fat content. Their causality was then demonstrated by a functional test. These results provide new knowledge on the genetic basis of milk synthesis and will help improve the management of the French dairy goat breeding program.
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Affiliation(s)
- Pauline Martin
- GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
| | - Isabelle Palhière
- GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
| | - Cyrielle Maroteau
- GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
- Division of Molecular and Clinical Medecine, School of Medecine, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
| | - Philippe Bardou
- GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
- INRA, Sigenae, Castanet-Tolosan, France
| | - Kamila Canale-Tabet
- GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
| | - Julien Sarry
- GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
| | - Florent Woloszyn
- GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
| | | | - Ines Racke
- Protein Expression and Purification Core Facility, EMBL Heidelberg, Heidelberg, Germany
| | - Hüseyin Besir
- Protein Expression and Purification Core Facility, EMBL Heidelberg, Heidelberg, Germany
| | - Rachel Rupp
- GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
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Gao Y, Jiang J, Yang S, Hou Y, Liu GE, Zhang S, Zhang Q, Sun D. CNV discovery for milk composition traits in dairy cattle using whole genome resequencing. BMC Genomics 2017; 18:265. [PMID: 28356085 PMCID: PMC5371188 DOI: 10.1186/s12864-017-3636-3] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2016] [Accepted: 03/17/2017] [Indexed: 01/08/2023] Open
Abstract
Background Copy number variations (CNVs) are important and widely distributed in the genome. CNV detection opens a new avenue for exploring genes associated with complex traits in humans, animals and plants. Herein, we present a genome-wide assessment of CNVs that are potentially associated with milk composition traits in dairy cattle. Results In this study, CNVs were detected based on whole genome re-sequencing data of eight Holstein bulls from four half- and/or full-sib families, with extremely high and low estimated breeding values (EBVs) of milk protein percentage and fat percentage. The range of coverage depth per individual was 8.2–11.9×. Using CNVnator, we identified a total of 14,821 CNVs, including 5025 duplications and 9796 deletions. Among them, 487 differential CNV regions (CNVRs) comprising ~8.23 Mb of the cattle genome were observed between the high and low groups. Annotation of these differential CNVRs were performed based on the cattle genome reference assembly (UMD3.1) and totally 235 functional genes were found within the CNVRs. By Gene Ontology and KEGG pathway analyses, we found that genes were significantly enriched for specific biological functions related to protein and lipid metabolism, insulin/IGF pathway-protein kinase B signaling cascade, prolactin signaling pathway and AMPK signaling pathways. These genes included INS, IGF2, FOXO3, TH, SCD5, GALNT18, GALNT16, ART3, SNCA and WNT7A, implying their potential association with milk protein and fat traits. In addition, 95 CNVRs were overlapped with 75 known QTLs that are associated with milk protein and fat traits of dairy cattle (Cattle QTLdb). Conclusions In conclusion, based on NGS of 8 Holstein bulls with extremely high and low EBVs for milk PP and FP, we identified a total of 14,821 CNVs, 487 differential CNVRs between groups, and 10 genes, which were suggested as promising candidate genes for milk protein and fat traits. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3636-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yahui Gao
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jianping Jiang
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Shaohua Yang
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yali Hou
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Md, 20705, USA
| | - Shengli Zhang
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Qin Zhang
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Dongxiao Sun
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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Do D, Bissonnette N, Lacasse P, Miglior F, Sargolzaei M, Zhao X, Ibeagha-Awemu E. Genome-wide association analysis and pathways enrichment for lactation persistency in Canadian Holstein cattle. J Dairy Sci 2017; 100:1955-1970. [DOI: 10.3168/jds.2016-11910] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Accepted: 11/08/2016] [Indexed: 12/22/2022]
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Nayeri S, Sargolzaei M, Abo-Ismail M, Miller S, Schenkel F, Moore S, Stothard P. Genome-wide association study for lactation persistency, female fertility, longevity, and lifetime profit index traits in Holstein dairy cattle. J Dairy Sci 2017; 100:1246-1258. [DOI: 10.3168/jds.2016-11770] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 10/13/2016] [Indexed: 12/12/2022]
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Yang S, Gao Y, Zhang S, Zhang Q, Sun D. Identification of Genetic Associations and Functional Polymorphisms of SAA1 Gene Affecting Milk Production Traits in Dairy Cattle. PLoS One 2016; 11:e0162195. [PMID: 27610623 PMCID: PMC5017741 DOI: 10.1371/journal.pone.0162195] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 08/18/2016] [Indexed: 11/19/2022] Open
Abstract
Our initial RNA sequencing (RNA-seq) revealed that the Serum amyloid A1 (SAA1) gene was differentially expressed in the mammary glands of lactating Holstein cows with extremely high versus low phenotypic values of milk protein and fat percentage. To further validate the genetic effect and potential molecular mechanisms of SAA1 gene involved in regulating milk production traits in dairy cattle, we herein performed a study through genotype-phenotype associations. Six identified SNPs were significantly associated with one or more milk production traits (0.00002< P < 0.0025), providing additional evidence for the potential role of SAA1 variants in milk production traits in dairy cows. Subsequently, both luciferase assay and electrophoretic mobility shift assay (EMSA) clearly demonstrated that the allele A of g.-963C>A increased the promoter activity by binding the PARP factor while allele C did not. Bioinformatics analysis indicated that the secondary structure of SAA protein changed by the substitution A/G in the locus c. +2510A>G. Our findings were the first to reveal the significant associations of the SAA1 gene with milk production traits, providing basis for further biological function validation, and two identified SNPs, g.-963C>A and c. +2510A>G, may be considered as genetic markers for breeding in dairy cattle.
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Affiliation(s)
- Shaohua Yang
- 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
| | - Yahui Gao
- 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
| | - Shengli Zhang
- 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
| | - Qin Zhang
- 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
| | - Dongxiao Sun
- 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
- * E-mail:
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Bai X, Zheng Z, Liu B, Ji X, Bai Y, Zhang W. Whole blood transcriptional profiling comparison between different milk yield of Chinese Holstein cows using RNA-seq data. BMC Genomics 2016; 17 Suppl 7:512. [PMID: 27557137 PMCID: PMC5001199 DOI: 10.1186/s12864-016-2901-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Background The objective of this research was to investigate the variation of gene expression in the blood transcriptome profile of Chinese Holstein cows associated to the milk yield traits. Results We used RNA-seq to generate the bovine transcriptome from the blood of 23 lactating Chinese Holstein cows with extremely high and low milk yield. A total of 100 differentially expressed genes (DEGs) (p < 0.05, FDR < 0.05) were revealed between the high and low groups. Gene ontology (GO) analysis demonstrated that the 100 DEGs were enriched in specific biological processes with regard to defense response, immune response, inflammatory response, icosanoid metabolic process, and fatty acid metabolic process (p < 0.05). The KEGG pathway analysis with 100 DEGs revealed that the most statistically-significant metabolic pathway was related with Toll-like receptor signaling pathway (p < 0.05). The expression level of four selected DEGs was analyzed by qRT-PCR, and the results indicated that the expression patterns were consistent with the deep sequencing results by RNA-Seq. Furthermore, alternative splicing analysis of 100 DEGs demonstrated that there were different splicing pattern between high and low yielders. The alternative 3’ splicing site was the major splicing pattern detected in high yielders. However, in low yielders the major type was exon skipping. Conclusion This study provides a non-invasive method to identify the DEGs in cattle blood using RNA-seq for milk yield. The revealed 100 DEGs between Holstein cows with extremely high and low milk yield, and immunological pathway are likely involved in milk yield trait. Finally, this study allowed us to explore associations between immune traits and production traits related to milk production. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2901-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xue Bai
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Zhuqing Zheng
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China.,Institute of ATCG Nei Mongol Bio-Information, Hohhot, 010020, China
| | - Bin Liu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China.,Institute of ATCG Nei Mongol Bio-Information, Hohhot, 010020, China.,Nei Mongol BioNew Technology Co.Ltd, Hohhot, 010018, China
| | - Xiaoyang Ji
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China.,Institute of ATCG Nei Mongol Bio-Information, Hohhot, 010020, China
| | - Yongsheng Bai
- Department of Biology, Indiana State University, Terre Haute, IN, 47809, U.S.A..
| | - Wenguang Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China. .,Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
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Ibeagha-Awemu EM, Peters SO, Akwanji KA, Imumorin IG, Zhao X. High density genome wide genotyping-by-sequencing and association identifies common and low frequency SNPs, and novel candidate genes influencing cow milk traits. Sci Rep 2016; 6:31109. [PMID: 27506634 DOI: 10.1038/srep31109] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Accepted: 07/14/2016] [Indexed: 11/17/2022] Open
Abstract
High-throughput sequencing technologies have increased the ability to detect sequence variations for complex trait improvement. A high throughput genome wide genotyping-by-sequencing (GBS) method was used to generate 515,787 single nucleotide polymorphisms (SNPs), from which 76,355 SNPs with call rates >85% and minor allele frequency ≥1.5% were used in genome wide association study (GWAS) of 44 milk traits in 1,246 Canadian Holstein cows. GWAS was accomplished with a mixed linear model procedure implementing the additive and dominant models. A strong signal within the centromeric region of bovine chromosome 14 was associated with test day fat percentage. Several SNPs were associated with eicosapentaenoic acid, docosapentaenoic acid, arachidonic acid, CLA:9c11t and gamma linolenic acid. Most of the significant SNPs for 44 traits studied are novel and located in intergenic regions or introns of genes. Novel potential candidate genes for milk traits or mammary gland functions include ERCC6, TONSL, NPAS2, ACER3, ITGB4, GGT6, ACOX3, MECR, ADAM12, ACHE, LRRC14, FUK, NPRL3, EVL, SLCO3A1, PSMA4, FTO, ADCK5, PP1R16A and TEP1. Our study further demonstrates the utility of the GBS approach for identifying population-specific SNPs for use in improvement of complex dairy traits.
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Nayeri S, Sargolzaei M, Abo-Ismail MK, May N, Miller SP, Schenkel F, Moore SS, Stothard P. Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle. BMC Genet 2016; 17:75. [PMID: 27287773 DOI: 10.1186/s12863-016-0386-1] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Accepted: 06/01/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) are a powerful tool for detecting genomic regions explaining variation in phenotype. The objectives of the present study were to identify or refine the positions of genomic regions affecting milk production, milk components and fertility traits in Canadian Holstein cattle, and to use these positions to identify genes and pathways that may influence these traits. RESULT Several QTL regions were detected for milk production (MILK), fat production (FAT), protein production (PROT) and fat and protein deviation (FATD, PROTD respectively). The identified QTL regions for production traits (including milk production) support previous findings and some overlap with genes with known relevant biological functions identified in earlier studies such as DGAT1 and CPSF1. A significant region on chromosome 21 overlapping with the gene FAM181A and not previous linked to fertility in dairy cattle was identified for the calving to first service interval and days open. A functional enrichment analysis of the GWAS results yielded GO terms consistent with the specific phenotypes tested, for example GO terms GO:0007595 (lactation) and GO:0043627 (response to estrogen) for milk production (MILK), GO:0051057 (positive regulation of small GTPase mediated signal transduction) for fat production (FAT), GO:0040019 (positive regulation of embryonic development) for first service to calving interval (CTFS) and GO:0043268 (positive regulation of potassium ion transport) for days open (DO). In other cases the connection between the enriched GO terms and the traits were less clear, for example GO:0003279 (cardiac septum development) for FAT and GO:0030903 (notochord development) for DO trait. CONCLUSION The chromosomal regions and enriched pathways identified in this study confirm several previous findings and highlight new regions and pathways that may contribute to variation in production or fertility traits in dairy cattle.
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Ibeagha-Awemu EM, Li R, Ammah AA, Dudemaine PL, Bissonnette N, Benchaar C, Zhao X. Transcriptome adaptation of the bovine mammary gland to diets rich in unsaturated fatty acids shows greater impact of linseed oil over safflower oil on gene expression and metabolic pathways. BMC Genomics 2016; 17:104. [PMID: 26861594 PMCID: PMC4748538 DOI: 10.1186/s12864-016-2423-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Accepted: 02/01/2016] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Nutritional strategies can decrease saturated fatty acids (SFAs) and increase health beneficial fatty acids (FAs) in bovine milk. The pathways/genes involved in these processes are not properly defined. Next-generation RNA-sequencing was used to investigate the bovine mammary gland transcriptome following supplemental feeding with 5% linseed oil (LSO) or 5% safflower oil (SFO). Holstein cows in mid-lactation were fed a control diet for 28 days (control period) followed by supplementation with 5% LSO (12 cows) or 5% SFO (12 cows) for 28 days (treatment period). Milk and mammary gland biopsies were sampled on days-14 (control period), +7 and +28 (treatment period). Milk was used to measure fat(FP)/protein(PP) percentages and individual FAs while RNA was subjected to sequencing. RESULTS Milk FP was decreased by 30.38% (LSO) or 32.42% (SFO) while PP was unaffected (LSO) or increased (SFO). Several beneficial FAs were increased by LSO (C18:1n11t, CLA:10t12c, CLA:9c11t, C20:3n3, C20:5n3, C22:5n3) and SFO (C18:1n11t, CLA:10t12c, C20:1c11, C20:2, C20:3n3) while several SFAs (C4:0, C6:0, C8:0, C14:0, C16:0, C17:0, C24:0) were decreased by both treatments (P < 0.05). 1006 (460 up- and 546 down-regulated) and 199 (127 up- and 72 down-regulated) genes were significantly differentially regulated (DE) by LSO and SFO, respectively. Top regulated genes (≥ 2 fold change) by both treatments (FBP2, UCP2, TIEG2, ANGPTL4, ALDH1L2) are potential candidate genes for milk fat traits. Involvement of SCP2, PDK4, NQO1, F2RL1, DBI, CPT1A, CNTFR, CALB1, ACADVL, SPTLC3, PIK3CG, PIGZ, ADORA2B, TRIB3, HPGD, IGFBP2 and TXN in FA/lipid metabolism in dairy cows is being reported for the first time. Functional analysis indicated similar and different top enriched functions for DE genes. DE genes were predicted to significantly decrease synthesis of FA/lipid by both treatments and FA metabolism by LSO. Top canonical pathways associated with DE genes of both treatments might be involved in lipid/cholesterol metabolism. CONCLUSION This study shows that rich α-linolenic acid LSO has a greater impact on mammary gland transcriptome by affecting more genes, pathways and processes as compared to SFO, rich in linoleic acid. Our study suggest that decrease in milk SFAs was due to down-regulation of genes in the FA/lipid synthesis and lipid metabolism pathways while increase in PUFAs was due to increased availability of ruminal biohydrogenation metabolites that were up taken and incorporated into milk or used as substrate for the synthesis of PUFAs.
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Affiliation(s)
- Eveline M Ibeagha-Awemu
- Agriculture and Agri-Food Canada, Research and Development Centre, Sherbrooke, Quebec, J1M 0C8, Canada.
| | - Ran Li
- Agriculture and Agri-Food Canada, Research and Development Centre, Sherbrooke, Quebec, J1M 0C8, Canada.
| | - Adolf A Ammah
- Agriculture and Agri-Food Canada, Research and Development Centre, Sherbrooke, Quebec, J1M 0C8, Canada.
| | - Pier-Luc Dudemaine
- Agriculture and Agri-Food Canada, Research and Development Centre, Sherbrooke, Quebec, J1M 0C8, Canada.
| | - Nathalie Bissonnette
- Agriculture and Agri-Food Canada, Research and Development Centre, Sherbrooke, Quebec, J1M 0C8, Canada.
| | - Chaouki Benchaar
- Agriculture and Agri-Food Canada, Research and Development Centre, Sherbrooke, Quebec, J1M 0C8, Canada.
| | - Xin Zhao
- Department of Animal Science, McGill University, Ste-Anne-de-Bellevue, Quebec, H9X 3 V9, Canada.
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Yang SH, Bi XJ, Xie Y, Li C, Zhang SL, Zhang Q, Sun DX. Validation of PDE9A Gene Identified in GWAS Showing Strong Association with Milk Production Traits in Chinese Holstein. Int J Mol Sci 2015; 16:26530-42. [PMID: 26556348 PMCID: PMC4661835 DOI: 10.3390/ijms161125976] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Revised: 07/24/2015] [Accepted: 08/18/2015] [Indexed: 12/24/2022] Open
Abstract
Phosphodiesterase9A (PDE9A) is a cyclic guanosine monophosphate (cGMP)-specific enzyme widely expressed among the tissues, which is important in activating cGMP-dependent signaling pathways. In our previous genome-wide association study, a single nucleotide polymorphism (SNP) (BTA-55340-no-rs(b)) located in the intron 14 of PDE9A, was found to be significantly associated with protein yield. In addition, we found that PDE9A was highly expressed in mammary gland by analyzing its mRNA expression in different tissues. The objectives of this study were to identify genetic polymorphisms of PDE9A and to determine the effects of these variants on milk production traits in dairy cattle. DNA sequencing identified 11 single nucleotide polymorphisms (SNPs) and six SNPs in 5' regulatory region were genotyped to test for the subsequent association analyses. After Bonferroni correction for multiple testing, all these identified SNPs were statistically significant for one or more milk production traits (p < 0.0001~0.0077). Interestingly, haplotype-based association analysis revealed similar effects on milk production traits (p < 0.01). In follow-up RNA expression analyses, two SNPs (c.-1376 G>A, c.-724 A>G) were involved in the regulation of gene expression. Consequently, our findings provide confirmatory evidences for associations of PDE9A variants with milk production traits and these identified SNPs may serve as genetic markers to accelerate Chinese Holstein breeding program.
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Affiliation(s)
- Shao-Hua Yang
- 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.
| | - Xiao-Jun Bi
- 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.
| | - Yan Xie
- 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.
| | - Cong Li
- 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.
| | - Sheng-Li Zhang
- 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.
| | - Qin Zhang
- 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.
| | - Dong-Xiao Sun
- 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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Szewczuk M. Polymorphism of the Insulin-like growth factor 1 receptor gene (IGF1R/e10/MspI and IGF1R/e16/RsaI) in four dairy breeds and its association with milk traits. Livest Sci 2015. [DOI: 10.1016/j.livsci.2015.09.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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