Association between microsatellite markers and milk production traits in Egyptian buffaloes H.E., Moghaieb R.E.A., Abdel-Shafy H., Ibrahim M.A.M. (2017): Association between microsatellite markers and milk production traits in Egyptian buffaloes. Czech J. Anim. Sci., 62: 384-391.
download PDF
The objectives were to evaluate polymorphism in ten microsatellite markers and to demonstrate their association with milk production traits in the Egyptian buffaloes, based on the cross-species transferability of microsatellites from cattle to buffalo. A total of 17 439 daily milk records from the first five lactations were subjected to analyses, in which records from 5 to 290 days in milk were only included. The analysis revealed that eight out of the ten bovine markers analyzed were polymorphic. The means of the number of alleles, effective number of alleles, and fixation index within markers were 4.125, 2.479, and 0.062, respectively. The means of the observed and expected heterozygosity were 0.491 and 0.527 per marker, respectively. The eight polymorphic microsatellites (BM1706, BMS711, BM143, BM415, BM6438, ETH131, BM1443, ETH2) showed significant (P < 0.001) associations with average daily milk yield deviation. Protein percentage was significantly associated with microsatellites BM6438 (P < 0.01) and ETH131 (P < 0.001). Only marker BM415 had a significant (P < 0.05) influence on protein yield. None of the analyzed markers revealed significant effect on fat yield and percentage. The results obtained support future application of the polymorphic microsatellites for detailed studies of the Egyptian buffalo genome.
Cribiu E.P., Di Berardino D., Di Meo G.P., Eggen A., Gallagher D.S., Gustavsson I., Hayes H., Iannuzzi L., Popescu C.P., Rubes J., Schmutz S., Stranzinger G., Vaiman A., Womack J. (2001): International System for Chromosome Nomenclature of Domestic Bovids (ISCNDB 2000). Cytogenetic and Genome Research, 92, 283-299
El-Kholy A.F., Hoda Z.H., Amin A.M.S., Hassanane M.S. (2007): Genetic diversity in Egyptian buffalo using microsatellite markers. Arab Journal of Biotechnology, 10, 219–232.
Georges M., Nielsen D., Mackinnon M., Mishra A., Okimoto R., Pasquino A.T., Sargeant L.S., Sorensen A., Steele M.R., Zhao X. (1995): Mapping quantitative trait loci controlling milk production in dairy cattle by exploiting progeny testing. Genetics, 139, 907–920.
Heyen D.W., Weller J.I., Ron M., Band M., Beever J.E., Feldmesser E., Da Y., Wiggans G.R., VanRaden P.M., Lewin H.A. (1999): A genome scan for QTL influencing milk production and health traits in dairy cattle. Physio-logical Genomics, 1, 165–175.
Hu Z.L., Park C.A., Reecy J.M. (2016): Developmental progress and current status of the Animal QTLdb. Nucleic Acids Research, 44, D827–D833.
Ihara N. (2004): A Comprehensive Genetic Map of the Cattle Genome Based on 3802 Microsatellites. Genome Research, 14, 1987-1998
Iheshiulor Oscar O. M., Woolliams John A., Yu Xijiang, Wellmann Robin, Meuwissen Theo H. E. (2016): Within- and across-breed genomic prediction using whole-genome sequence and single nucleotide polymorphism panels. Genetics Selection Evolution, 48, -
Mekkawy W., Hafez Y.M., Attia M., Abdel-Salam S.A.M., Abou-Bakr S. (2012): Association analysis between microsatellite DNA markers and milk yield and its components in Egyptian buffaloes using random regression model. Egyptian Journal of Animal Production, 49, 9–18.
Meredith Brian K, Kearney Francis J, Finlay Emma K, Bradley Daniel G, Fahey Alan G, Berry Donagh P, Lynn David J (2012): Genome-wide associations for milk production and somatic cell score in Holstein-Friesian cattle in Ireland. BMC Genetics, 13, 21-
Michelizzi Vanessa N., Wu Xiaolin, Dodson Michael V., Michal Jennifer J., Zambrano-Varon Jorge, McLean Derek J., Jiang Zhihua (2011): A Global View of 54,001 Single Nucleotide Polymorphisms (SNPs) on the Illumina BovineSNP50 BeadChip and Their Transferability to Water Buffalo. International Journal of Biological Sciences, 7, 18-27
Nadesalingam Jeyakumary, Plante Yves, Gibson John P. (2001): Detection of QTL for milk production on Chromosomes 1 and 6 of Holstein cattle. Mammalian Genome, 12, 27-31
Navani N., Jain P. K., Gupta S., Sisodia B. S., Kumar S. (2002): A set of cattle microsatellite DNA markers for genome analysis of riverine buffalo (Bubalus bubalis). Animal Genetics, 33, 149-154
Peakall R., Smouse P.E. (2012): GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research – an update. Bioinformatics, 28, 2537–2539.
Shokrollahi B., Amirinia C., Djadid N.D., Amirmozaffari N., Kamali M.A. (2009): Development of polymorphic microsatellite loci for Iranian river buffalo (Bubalus bubalis). African Journal of Biotechnology, 8, 6750–6755.
Sikka P., Sethi R.K. (2008): Genetic variability in production performance of Murrah buffaloes (Bubalus bubalis) using microsatellite polymorphism. Indian Journal of Biotechnology, 7, 103–107.
Venturini G.C., Cardoso D.F., Baldi F., Freitas A.C., Aspilcueta-Borquis R.R., Santos D.J.A., Camargo G.M.F., Stafuzza N.B., Albuquerque L.G., Tonhati H. (2014): Association between single-nucleotide polymorphisms and milk production traits in buffalo. Genetics and Molecular Research, 13, 10256-10268
Weller J.I., Kashi Y., Soller M. (1990): Power of Daughter and Granddaughter Designs for Determining Linkage Between Marker Loci and Quantitative Trait Loci in Dairy Cattle. Journal of Dairy Science, 73, 2525-2537
Wilmink J.B.M. (1987): Adjustment of test-day milk, fat and protein yield for age, season and stage of lactation. Livestock Production Science, 16, 335-348
Wu J.J., Song L.J., Wu F.J., Liang X.W., Yang B.Z., Wathes D.C., Pollott G.E., Cheng Z., Shi de S., Liu Q.Y., Yang L.G., Zhang S.J. (2013): Investigation of transferability of BovineSNP50 BeadChip from cattle to water buffalo for genome wide association study. Molecular Biology Research, 40, 743–750.
Zabolewicz T., Czarnik U., Strychalski J., Pareek C.S., Pierzchala M. (2011): The association between microsatellite BM6438 and milk performance traits in Polish Holstein-Friesian cattle. Czech Journal of Animal Science, 56, 107–113.
download PDF

© 2020 Czech Academy of Agricultural Sciences