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Laodim T, Koonawootrittriron S, Elzo MA, Suwanasopee T, Jattawa D, Sarakul M. Genetic factors influencing milk and fat yields in tropically adapted dairy cattle: insights from quantitative trait loci analysis and gene associations. Anim Biosci 2024; 37:576-590. [PMID: 37946425 PMCID: PMC10915225 DOI: 10.5713/ab.23.0246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/27/2023] [Accepted: 10/01/2023] [Indexed: 11/12/2023] Open
Abstract
OBJECTIVE The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. METHODS A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-yearseason, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. RESULTS A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. CONCLUSION Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.
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Affiliation(s)
- Thawee Laodim
- Department of Animal Science, Faculty of Agriculture at Kamphaeng Saen, Kasetsart University Kamphaeng Saen Campus, Nakhon Pathom, 73140,
Thailand
- Tropical Animal Genetic Special Research Unit (TAGU), Kasetsart University, Bangkok, 10900,
Thailand
| | - Skorn Koonawootrittriron
- Tropical Animal Genetic Special Research Unit (TAGU), Kasetsart University, Bangkok, 10900,
Thailand
- Department of Animal Science, Faculty of Agriculture, Kasetsart University, Bangkok, 10900,
Thailand
| | - Mauricio A. Elzo
- Tropical Animal Genetic Special Research Unit (TAGU), Kasetsart University, Bangkok, 10900,
Thailand
- Department of Animal Sciences, University of Florida, Gainesville, 32611-0910, FL,
USA
| | - Thanathip Suwanasopee
- Tropical Animal Genetic Special Research Unit (TAGU), Kasetsart University, Bangkok, 10900,
Thailand
- Department of Animal Science, Faculty of Agriculture, Kasetsart University, Bangkok, 10900,
Thailand
| | - Danai Jattawa
- Tropical Animal Genetic Special Research Unit (TAGU), Kasetsart University, Bangkok, 10900,
Thailand
- Department of Animal Science, Faculty of Agriculture, Kasetsart University, Bangkok, 10900,
Thailand
| | - Mattaneeya Sarakul
- Tropical Animal Genetic Special Research Unit (TAGU), Kasetsart University, Bangkok, 10900,
Thailand
- Department of Animal Science, Faculty of Agriculture and Technology, Nakhon Phanom University, Nakhon Phanom, 48000,
Thailand
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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] [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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Hong Y, Ye J, Dong L, Li Y, Yan L, Cai G, Liu D, Tan C, Wu Z. Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs. Front Genet 2021; 12:650370. [PMID: 34408768 PMCID: PMC8366400 DOI: 10.3389/fgene.2021.650370] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 06/15/2021] [Indexed: 01/08/2023] Open
Abstract
Body length, body height, and total teat number are economically important traits in pig breeding, as these traits are usually associated with the growth, reproductivity, and longevity potential of piglets. Here, we report a genetic analysis of these traits using a population comprising 2,068 Large White pigs. A genotyping-by-sequencing (GBS) approach was used to provide high-density genome-wide SNP discovery and genotyping. Univariate and bivariate animal models were used to estimate heritability and genetic correlations. The results showed that heritability estimates for body length, body height, and total teat number were 0.25 ± 0.04, 0.11 ± 0.03, and 0.22 ± 0.04, respectively. The genetic correlation between body length and body height exhibited a strongly positive correlation (0.63 ± 0.15), while a positive but low genetic correlation was observed between total teat number and body length. Furthermore, we used two different genome-wide association study (GWAS) approaches: single-locus GWAS and weighted single-step GWAS (WssGWAS), to identify candidate genes for these traits. Single-locus GWAS detected 76, 13, and 29 significant single-nucleotide polymorphisms (SNPs) associated with body length, body height, and total teat number. Notably, the most significant SNP (S17_15781294), which is located 20 kb downstream of the BMP2 gene, explained 9.09% of the genetic variance for body length traits, and it also explained 9.57% of the genetic variance for body height traits. In addition, another significant SNP (S7_97595973), which is located in the ABCD4 gene, explained 8.92% of the genetic variance for total teat number traits. GWAS results for these traits identified some candidate genomic regions, such as SSC6: 14.96–15.02 Mb, SSC7: 97.18–98.18 Mb, SSC14: 128.29–131.15 Mb, SSC17: 15.39–17.27 Mb, and SSC17: 22.04–24.15 Mb, providing a starting point for further inheritance research. Most quantitative trait loci were detected by single-locus GWAS and WssGWAS. These findings reveal the complexity of the genetic mechanism of the three traits and provide guidance for subsequent genetic improvement through genome selection.
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Affiliation(s)
- Yifeng Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Jian Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Linsong Dong
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Yalan Li
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Limin Yan
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Dewu Liu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Cheng Tan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
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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] [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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Peters SO, Kızılkaya K, Ibeagha-Awemu EM, Sinecen M, Zhao X. Comparative accuracies of genetic values predicted for economically important milk traits, genome-wide association, and linkage disequilibrium patterns of Canadian Holstein cows. J Dairy Sci 2020; 104:1900-1916. [PMID: 33358789 DOI: 10.3168/jds.2020-18489] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 08/10/2020] [Indexed: 11/19/2022]
Abstract
Genomic selection methodologies and genome-wide association studies use powerful statistical procedures that correlate large amounts of high-density SNP genotypes and phenotypic data. Actual 305-d milk (MY), fat (FY), and protein (PY) yield data on 695 cows and 76,355 genotyping-by-sequencing-generated SNP marker genotypes from Canadian Holstein dairy cows were used to characterize linkage disequilibrium (LD) structure of Canadian Holstein cows. Also, the comparison of pedigree-based BLUP, genomic BLUP (GBLUP), and Bayesian (BayesB) statistical methods in the genomic selection methodologies and the comparison of Bayesian ridge regression and BayesB statistical methods in the genome-wide association studies were carried out for MY, FY, and PY. Results from LD analysis revealed that as marker distance decreases, LD increases through chromosomes. However, unexpected high peaks in LD were observed between marker pairs with larger marker distances on all chromosomes. The GBLUP and BayesB models resulted in similar heritability estimates through 10-fold cross-validation for MY and PY; however, the GBLUP model resulted in higher heritability estimates than BayesB model for FY. The predictive ability of GBLUP model was significantly lower than that of BayesB for MY, FY, and PY. Association analyses indicated that 28 high-effect markers and markers on Bos taurus autosome 14 located within 6 genes (DOP1B, TONSL, CPSF1, ADCK5, PARP10, and GRINA) associated significantly with FY.
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Affiliation(s)
- Sunday O Peters
- Department of Animal Science, Berry College, Mount Berry, GA 30149; Department of Animal and Dairy Science, University of Georgia, Athens 30602.
| | - Kadir Kızılkaya
- Department of Animal Science, Faculty of Agriculture, Aydin Adnan Menderes University, Aydin, 09100, Turkey
| | - Eveline M Ibeagha-Awemu
- Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, 2000 Rue College, Sherbrooke, QC, J1M 0C8 Canada
| | - Mahmut Sinecen
- Department of Computer Engineering, Faculty of Engineering, Aydin Adnan Menderes University, Aydin, 09100, Turkey
| | - Xin Zhao
- Department of Animal Science, McGill University, 21,111 Lakeshore Road, Ste-Anne-De-Bellevue, QC, H9S 3V9 Canada
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Kopec T, Chládek G, Falta D, Kučera J, Večeřa M, Hanuš O. The effect of extended lactation on parameters of Wood's model of lactation curve in dairy Simmental cows. Anim Biosci 2020; 34:949-956. [PMID: 33152226 PMCID: PMC8100486 DOI: 10.5713/ajas.20.0347] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 09/13/2020] [Indexed: 11/27/2022] Open
Abstract
Objective This study was focused on the estimation of parameters of Wood’s model and description of the lactation curve using the cows which were lactated over 24 months on the first lactation. Methods The database included 1,333 pure-bred dairy Simmental primiparous cows which lactated for 24 months (732 days). The initial dataset entering the procedure of assessment of parameters of Wood’s function included 35,826 milk yield records. Milk yield was recorded throughout lactation, with the earliest record taken on day 6 and the latest on day 1,348 of lactation. This dataset was used for the assessment of parameters a, b, c of Wood’s model using the non-linear statistical procedure. These parameters were estimated for different length of lactation. The assessed parameters were used for calculation of some characteristics of lactation curves. Results The lowest value of a parameter (15.2317) of Wood’s model of lactation curve was found out in lactations up to 305 days long, contrary to b and c parameters which were highest in those lactations (0.1029 and 0.0015, respectively). The maximum value of a parameter (17.4329) was found out in lactations up to 640 days long, unlike b and c parameters which were minimal in those lactations (0.0603 and 0.0010, respectively). Conclusion It can be concluded that the parameters of Wood’s model and the shape of lactation curve are changing with the growing number of milk yield records. Also, the assessed parameters revealed a significant milk production potential after 305 days of lactation.
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Affiliation(s)
- Tomáš Kopec
- Department of Animal Breeding, Mendel University in Brno (FA), Zemědělská 1, 613 00 Brno, Czech Republic
| | - Gustav Chládek
- Department of Animal Breeding, Mendel University in Brno (FA), Zemědělská 1, 613 00 Brno, Czech Republic
| | - Daniel Falta
- Department of Animal Breeding, Mendel University in Brno (FA), Zemědělská 1, 613 00 Brno, Czech Republic
| | - Josef Kučera
- Czech Moravian Breeders Association, Benešovská 123, 252 09 Hradištko, Czech Republic
| | - Milan Večeřa
- Department of Animal Breeding, Mendel University in Brno (FA), Zemědělská 1, 613 00 Brno, Czech Republic
| | - Oto Hanuš
- Dairy Research Institute Ltd., 160 00 Prague, Czech Republic
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Gonzalez M, Villa R, Villa C, Gonzalez V, Montano M, Medina G, Mahadevan P. Inspection of real and imputed genotypes reveled 76 SNPs associated to rear udder height in Holstein cattle. J Adv Vet Anim Res 2020; 7:234-241. [PMID: 32607355 PMCID: PMC7320818 DOI: 10.5455/javar.2020.g415] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 03/24/2020] [Accepted: 03/30/2020] [Indexed: 12/14/2022] Open
Abstract
Objective This paper presents the obtained result of a study that realizes to associate a set of real and imputed single nucleotide polymorphisms (SNP) genotypes to the rear udder height in Holstein cows. Materials and methods Forty-six Holstein cows from an arid zone of Mexico were phenotyped and genotyped for this study. Blood samples were used for DNA extraction, genotyping was performed with the Illumina BovineLD Bead chip which interrogates 6,912 SNPs genome-wide, and imputation was performed using the Findhap software. After QC filters, a total of 22,251 high quality and informative SNPs were inspected. Results The results showed the detection of 76 significant SNPs throughout the complete genome. Significant SNPs fall inside 111 Quantitative Loci Traits related to protein percentage, milk yield, and fat, among others, in chromosomes 1, 2, 3, 5, 6, 9, 10, 11, 12, 13, 19, 20, 21, 23, 26, 27, and 29. Similarly, results confirm that a genotype imputation is a convenient option for genome-wide covering when selecting economic traits with low-density real SNP panels. Conclusion This study contributes to establishing a low-cost and profitable strategy for applying genomic selection in developing countries.
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Affiliation(s)
- Mirvana Gonzalez
- Laboratory of Bioinformatics and Biofotonics, Engineering Institute, Autonomous University of Baja California, Mexicali, B.C, Mexico
| | - Rafael Villa
- Laboratory of Bioinformatics and Biofotonics, Engineering Institute, Autonomous University of Baja California, Mexicali, B.C, Mexico
| | - Carlos Villa
- Laboratory of Bioinformatics and Biofotonics, Engineering Institute, Autonomous University of Baja California, Mexicali, B.C, Mexico
| | - Victor Gonzalez
- Institute for Research in Veterinary Science, Autonomous University of Baja California, Mexicali, B.C, Mexico
| | - Martin Montano
- Institute for Research in Veterinary Science, Autonomous University of Baja California, Mexicali, B.C, Mexico
| | - Gerardo Medina
- Institute for Research in Veterinary Science, Autonomous University of Baja California, Mexicali, B.C, Mexico
| | - Pad Mahadevan
- Department of Biology, University of Tampa, Tampa, FL, USA
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