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Prospecting genomic regions associated with milk production traits in Egyptian buffalo

Published online by Cambridge University Press:  13 November 2020

Hamdy Abdel-Shafy*
Affiliation:
Department of Animal Production, Faculty of Agriculture, Cairo University, El-Gamma street, 12613Giza, Egypt
Mohamed A. A. Awad
Affiliation:
Department of Animal Production, Faculty of Agriculture, Cairo University, El-Gamma street, 12613Giza, Egypt
Hussein El-Regalaty
Affiliation:
Department of buffalo research, Animal Production Research Institute, Agricultural Research Center, Dokki, Giza, Egypt
S. E.-D. El-Assal
Affiliation:
Department of Genetics, Faculty of Agriculture, Cairo University, El-Gamma street, 12613Giza, Egypt
Samy Abou-Bakr
Affiliation:
Department of Animal Production, Faculty of Agriculture, Cairo University, El-Gamma street, 12613Giza, Egypt
*
Author for correspondence: Hamdy Abdel-Shafy, Email: hamdyabdelshafy@agr.cu.edu.eg

Abstract

The objectives of the current study were to detect putative genomic loci and to identify candidate genes associated with milk production traits in Egyptian buffalo. A total number of 161 479 daily milk yield (DMY) records and 60 318 monthly measures for fat and protein percentages (FP and PP, respectively), along with fat and protein yields (FY and PY, respectively) from 1670 animals were used. Genotyping was performed using Axiom® Buffalo Genotyping 90 K array. Genome-wide association study (GWAS) for each trait was performed using PLINK. After Bonferroni correction, 47 SNPs were associated with one or more milk production traits. These SNPs were distributed over 36 quantitative trait loci (QTL) and located on 20 buffalo chromosomes (BBU). For the 47 SNPs, one was overlapped for three traits (DMY, FY, and PY), six were associated with two traits (one for PP and PY and five for FY and PY) while the rest were associated with only one trait. Out of 36 identified QTL, eleven were overlapped with previously reported loci in buffalo and/or cattle populations. Some of these SNPs are placed within or close to potential candidate genes, for example: TPD52, ZBTB10, RALYL and SNX16 on BBU15, ADGRD1 on BBU17, ESRRG on BBU5 and GRIP1 on BBU4. This is the first reported study between genome-wide markers and milk components in Egyptian buffalo. Our findings provide useful information to explore the genetic mechanisms and relevant genes contributing to the variation in milk production traits. Further confirmation studies with larger population size are necessary to validate the findings and detect the causal genetic variants.

Type
Research Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of Hannah Dairy Research Foundation

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References

Abdel-Shafy, H, Awad, MAA, El-Regalaty, H, Ismael, A, El-Assal, SE-D and Abou-Bakr, S (2020) A single-step genomic evaluation for milk production in Egyptian buffalo. Livestock Science 234, 103977.CrossRefGoogle Scholar
Abdel-Shafy, H, Bortfeldt, RH, Tetens, J and Brockmann, GA (2014) Single nucleotide polymorphism and haplotype effects associated with somatic cell score in German Holstein cattle. Genetics Selection Evolution 46, 35.CrossRefGoogle ScholarPubMed
Anderson, CA, Pettersson, FH, Clarke, GM, Cardon, LR, Morris, AP and Zondervan, KT (2010) Data quality control in genetic case-control association studies. Nature Protocols 5, 15641573.CrossRefGoogle ScholarPubMed
Ardlie, KG, Kruglyak, L and Seielstad, M (2002) Patterns of linkage disequilibrium in the human genome. Nature Review Genetics 3, 299309.CrossRefGoogle ScholarPubMed
Awad, MAA, Abou-Bakr, S, El-Regalaty, H, El-Assal, SE-D and Abdel-Shafy, H (2020) Determination of potential candidate genes associated with milk lactose in Egyptian buffalo. World's Veterinary Journal 10, 3542.Google Scholar
Barłowska, J, Szwajkowska, M, Litwińczuk, Z and Król, J (2011) Nutritional value and technological suitability of milk from various animal species used for dairy production. Comprehensive Review in Food Science and Food Safety 10, 291302.CrossRefGoogle Scholar
Brodie, A, Azaria, JR and Ofran, Y (2016) How far from the SNP may the causative genes be? Nucleic Acids Research 44, 60466054.CrossRefGoogle Scholar
Buitenhuis, B, Janss, LL, Poulsen, NA, Larsen, LB, Larsen, MK and Sorensen, P (2014) Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle. BMC Genomics 15, 1112.CrossRefGoogle ScholarPubMed
Cardon, LR and Palmer, LJ (2003) Population stratification and spurious allelic association. Lancet (London, England) 361, 598604.CrossRefGoogle ScholarPubMed
Cecchinato, A, Ribeca, C, Maurmayr, A, Penasa, M, De Marchi, M, Macciotta, NP, Mele, M, Secchiari, P, Pagnacco, G and Bittante, G (2012) Short communication: effects of beta-lactoglobulin, stearoyl-coenzyme A desaturase 1, and sterol regulatory element binding protein gene allelic variants on milk production, composition, acidity, and coagulation properties of Brown Swiss cows. Journal of Dairy Science 95, 450454.CrossRefGoogle ScholarPubMed
Cecchinato, A, Ribeca, C, Chessa, S, Cipolat-Gotet, C, Maretto, F, Casellas, J and Bittante, G (2014) Candidate gene association analysis for milk yield, composition, urea nitrogen and somatic cell scores in Brown Swiss cows. Animal: An International Journal of Animal Bioscience 8, 10621070.CrossRefGoogle ScholarPubMed
Chang, CC, Chow, CC, Tellier, LC, Vattikuti, S, Purcell, SM and Lee, JJ (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7. Available at www.cog-genomics.org/plink/1.9/CrossRefGoogle ScholarPubMed
Cohen-Zinder, M, Seroussi, E, Larkin, DM, Loor, JJ, der Wind A, E-V, Lee, JH, Drackley, JK, Band, MR, Hernandez, AG, Shani, M, Lewin, HA, Weller, JI and Ron, M (2005) Identification of a missense mutation in the bovine ABCG2 gene with a major effect on the QTL on chromosome 6 affecting milk yield and composition in Holstein cattle. Genome Research 15, 936944.CrossRefGoogle ScholarPubMed
Cole, JB, Wiggans, GR, Ma, L, Sonstegard, TS, Lawlor, TJ Jr., Crooker, BA, Van Tassell, CP, Yang, J, Wang, S, Matukumalli, LK and Da, Y (2011) Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary U.S. Holstein cows. BMC Genomics 12, 408CrossRefGoogle ScholarPubMed
da Costa Barros, C, de Abreu Santos, DJ, Aspilcueta-Borquis, RR, de Camargo, GMF, de Araujo Neto, FR and Tonhati, H (2018) Use of single-step genome-wide association studies for prospecting genomic regions related to milk production and milk quality of buffalo. Journal of Dairy Research 85, 402406.CrossRefGoogle ScholarPubMed
Daetwyler, HD, Schenkel, FS, Sargolzaei, M and Robinson, JA (2008) A genome scan to detect quantitative trait loci for economically important traits in Holstein cattle using two methods and a dense single nucleotide polymorphism map. Journal of Dairy Science 91, 32253236.CrossRefGoogle Scholar
de Camargo, GM, Aspilcueta-Borquis, RR, Fortes, MR, Porto-Neto, R, Cardoso, DF, Santos, DJ, Lehnert, SA, Reverter, A, Moore, SS and Tonhati, H (2015) Prospecting major genes in dairy buffaloes. BMC Genomics 16, 872.CrossRefGoogle ScholarPubMed
Deb, GK, Nahar, TN, Duran, PG and Presicce, GA (2016) Safe and sustainable traditional production: the water buffalo in Asia. Frontiers in Environmental Science 4, 38.CrossRefGoogle Scholar
Devlin, B and Roeder, K (1999) Genomic control for association studies. Biometrics 55, 9971004.CrossRefGoogle ScholarPubMed
El-Halawany, N, Abdel-Shafy, H, Shawky, AA, Abdel-Latif, MA, Al-Tohamy, AFM and Abd El-Moneim, OM (2017) Genome-wide association study for milk production in Egyptian buffalo. Livestock Science 198, 1016.CrossRefGoogle Scholar
FAO (2019) FAOSTAT database collections. Food and Agriculture Organization of the United Nations. Available at http://www.fao.org/faostat/Google Scholar
Friedrich, J, Brand, B, Ponsuksili, S, Graunke, KL, Langbein, J, Knaust, J, Kuhn, C and Schwerin, M (2016) Detection of genetic variants affecting cattle behaviour and their impact on milk production: a genome-wide association study. Animal Genetics 47, 1218.CrossRefGoogle ScholarPubMed
Goddard, ME and Hayes, BJ (2009) Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Review Genetics 10, 381391.CrossRefGoogle ScholarPubMed
Hayes, BJ and Daetwyler, HD (2019) 1000 Bull genomes project to map simple and complex genetic traits in cattle: applications and outcomes. Annual Review of Animal Bioscience 7, 89102.CrossRefGoogle ScholarPubMed
Herrera, JRV, Flores, EB, Duijvesteijn, N, Gondro, C and van der Werf, JHJ (2018) Genome-wide association study for milk traits in Philippine dairy buffaloes. In Proceedings of the 11th World Congress on Genetics Applied to Livestock Production, 11–16 February 2019, Auckland, New Zealand, p. 825.Google Scholar
Hong, H, Kohli, K, Garabedian, MJ and Stallcup, MR (1997) GRIP1, a transcriptional coactivator for the AF-2 transactivation domain of steroid, thyroid, retinoid, and vitamin D receptors. Molecular and Cellular Biology 17, 27352744.CrossRefGoogle ScholarPubMed
Hu, ZL, Park, CA and Reecy, JM (2019) Building a livestock genetic and genomic information knowledgebase through integrative developments of animal QTLdb and CorrDB. Nucleic Acids Research 47, D701D710.CrossRefGoogle ScholarPubMed
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 and Williams, JL (2017) Design and validation of a 90K SNP genotyping assay for the water buffalo (Bubalus bubalis). PLoS ONE 12, e0185220.CrossRefGoogle Scholar
Iso-Touru, T, Sahana, G, Guldbrandtsen, B, Lund, MS and Vilkki, J (2016) Genome-wide association analysis of milk yield traits in Nordic red cattle using imputed whole genome sequence variants. BMC Genetics 17, 55.CrossRefGoogle ScholarPubMed
Jiang, J, Ma, L, Prakapenka, D, VanRaden, PM, Cole, JB and Da, Y (2019) A large-scale genome-wide association study in U.S. Holstein cattle. Frontiers in Genetics 10, 412.CrossRefGoogle ScholarPubMed
Kamili, A, Roslan, N, Frost, S, Cantrill, LC, Wang, D, Della-Franca, A, Bright, RK, Groblewski, GE, Straub, BK, Hoy, AJ, Chen, Y and Byrne, JA (2015) TPD52 expression increases neutral lipid storage within cultured cells. Journal of Cell Science 128, 32233238.CrossRefGoogle ScholarPubMed
Laurie, CC, Doheny, KF, Mirel, DB, Pugh, EW, Bierut, LJ, Bhangale, T, Boehm, F, Caporaso, NE, Cornelis, MC, Edenberg, HJ, Gabriel, SB, Harris, EL, Hu, FB, Jacobs, KB, Kraft, P, Landi, MT, Lumley, T, Manolio, TA, McHugh, C, Painter, I, Paschall, J, Rice, JP, Rice, KM, Zheng, X and Weir, BS (2010) Quality control and quality assurance in genotypic data for genome-wide association studies. Genetic Epidemiology 34, 591602.CrossRefGoogle ScholarPubMed
Li, C, Sun, D, Zhang, S, Wang, S, Wu, X, Zhang, Q, Liu, L, Li, Y and Qiao, L (2014) Genome wide association study identifies 20 novel promising genes associated with milk fatty acid traits in Chinese Holstein. PLoS ONE 9, e96186.CrossRefGoogle ScholarPubMed
Liu, JJ, Liang, AX, Campanile, G, Plastow, G, Zhang, C, Wang, Z, Salzano, A, Gasparrini, B, Cassandro, M and Yang, LG (2018) Genome-wide association studies to identify quantitative trait loci affecting milk production traits in water buffalo. Journal of Dairy Science 101, 433444.CrossRefGoogle ScholarPubMed
Lu, XR, Duan, AQ, Li, WQ, Abdel-Shafy, H, Rushdi, HE, Liang, SS, Ma, XY, Liang, XW and Deng, TX (2020) Genome-wide analysis reveals genetic diversity, linkage disequilibrium, and selection for milk production traits in Chinese buffalo breeds. Journal of Dairy Science 103, 45454556.CrossRefGoogle ScholarPubMed
Meredith, BK, Kearney, FJ, Finlay, EK, Bradley, DG, Fahey, AG, Berry, DP and Lynn, DJ (2012) Genome-wide associations for milk production and somatic cell score in Holstein-Friesian cattle in Ireland. BMC Genetics 13, 21.CrossRefGoogle ScholarPubMed
Michenet, A, Barbat, M, Saintilan, R, Venot, E and Phocas, F (2016) Detection of quantitative trait loci for maternal traits using high-density genotypes of Blonde d'Aquitaine beef cattle. BMC Genetics 17, 88.CrossRefGoogle ScholarPubMed
Misztal, I, Tsuruta, S, Strabel, T, Auvray, B, Druet, T and Lee, DH (2002) BLUPF90 and related programs (BGF90). In Proceedings of the 7th World Congress on Genetics Applied to Livestock Production, 19–23 August 2002, Montpellier, France, p. 28.Google Scholar
Mokhber, M (2017) Genome-wide association study for milk production in Iranian buffalo. In Proceedings of the 1st International and 5th National Conference on Organic vs. Conventional Agriculture, 16–17 August 2017, Ardabil, Iran, pp. 15.Google Scholar
Pryce, JE, Bolormaa, S, Chamberlain, AJ, Bowman, PJ, Savin, K, Goddard, ME and Hayes, BJ (2010) A validated genome-wide association study in 2 dairy cattle breeds for milk production and fertility traits using variable length haplotypes. Journal of Dairy Science 93, 33313345.CrossRefGoogle ScholarPubMed
Rodriguez-Zas, SL, Southey, BR, Heyen, DW and Lewin, HA (2002) Detection of quantitative trait loci influencing dairy traits using a model for longitudinal data. Journal of Dairy Science 85, 26812691.CrossRefGoogle Scholar
SADS (2009) Sustainable Agricultural Development Strategy towards 2030. Agricultural Research and Development Council, Ministry of Agriculture and Land Reclamation, Arab Republic of Egypt, p. 194.Google Scholar
Sanoudou, D, Duka, A, Drosatos, K, Hayes, KC and Zannis, VI (2010) Role of Esrrg in the fibrate-mediated regulation of lipid metabolism genes in human ApoA-I transgenic mice. Pharmacogenomics Journal 10, 165179.CrossRefGoogle ScholarPubMed
Szyda, J, Mielczarek, M, Fraszczak, M, Minozzi, G, Williams, JL and Wojdak-Maksymiec, K (2019) The genetic background of clinical mastitis in Holstein-Friesian cattle. Animal: An International Journal of Animal Bioscience 13, 21562163.CrossRefGoogle ScholarPubMed
Tiacci, E, Orvietani, PL, Bigerna, B, Pucciarini, A, Corthals, GL, Pettirossi, V, Martelli, MP, Liso, A, Benedetti, R, Pacini, R, Bolli, N, Pileri, S, Pulford, K, Gambacorta, M, Carbone, A, Pasquarello, C, Scherl, A, Robertson, H, Sciurpi, MT, Alunni-Bistocchi, G, Binaglia, L, Byrne, JA and Falini, B (2005) Tumor protein D52 (TPD52): a novel B-cell/plasma-cell molecule with unique expression pattern and Ca(2+)-dependent association with annexin VI. Blood 105, 28122820.CrossRefGoogle ScholarPubMed
Turner, SD (2014) qqman: an R package for visualizing GWAS results using QQ and Manhattan plots. https://doi.org/10.1101/005165CrossRefGoogle Scholar
Twomey, AJ, Berry, DP, Evans, RD, Doherty, ML, Graham, DA and Purfield, DC (2019) Genome-wide association study of endo-parasite phenotypes using imputed whole-genome sequence data in dairy and beef cattle. Genetics Selection Evolution 51, 15.CrossRefGoogle ScholarPubMed
VanRaden, PM and Wiggans, GR (1991) Derivation, calculation, and use of national animal model information. Journal of Dairy Science 74, 27372746.CrossRefGoogle ScholarPubMed
Visscher, PM, Wray, NR, Zhang, Q, Sklar, P, McCarthy, MI, Brown, MA and Yang, J (2017) 10 Years of GWAS discovery: biology, function, and translation. American Journal of Human Genetics 101, 522.CrossRefGoogle Scholar
Wanapat, M, Ngarmsang, A, Korkhuntot, S, Nontaso, N, Wachirapakorn, C, Beakes, C and Rowlinson, P (2000) A comparative study on the rumen microbial population of cattle and swamp buffalo raised under traditional village conditions in the Northeast of Thailand. Asian-Australasian Journal of Animal Science 13, 918921.CrossRefGoogle Scholar
Yang, S, Wang, Y, Wang, L, Shi, Z, Ou, X, Wu, D, Zhang, X, Hu, H, Yuan, J, Wang, W, Cao, F and Liu, G (2018) RNA-Seq reveals differentially expressed genes affecting polyunsaturated fatty acids percentage in the Huangshan Black chicken population. PLoS ONE 13, e0195132.CrossRefGoogle ScholarPubMed
Yodklaew, P, Koonawootrittriron, S, Elzo, MA, Suwanasopee, T and Laodim, T (2017) Genome-wide association study for lactation characteristics, milk yield and age at first calving in a Thai multibreed dairy cattle population. Agriculture Natural Resources 51, 223230.CrossRefGoogle Scholar
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