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Journal of Integrative Agriculture  2014, Vol. 13 Issue (9): 1999-2004    DOI: 10.1016/S2095-3119(13)60616-4
Animal Science · Veterinary Science Advanced Online Publication | Current Issue | Archive | Adv Search |
Mapping QTLs Affecting Economic Traits on BTA3 in Chinese Holstein with Microsatellite Markers
 QIN Chun-hua, CHU Qin, CHU Gui-yan, ZHANG Yi, ZHANG Qin, ZHANG Sheng-li , SUN Dong-xiao
College of Animal Science and Technology/Key Laboratory of Animal Genetics and Breeding, Ministry of Agriculture/National Engineering
Laboratory of Animal Genetics, China Agricultural University, Beijing 100193, P.R.China
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摘要  It had been demonstrated that the strong and highly significant quantitative trait locus (QTL) can affect protein percentage on Bos Taurus Autosome 3 (BTA3) at the position 52 cM, near the microsatellite DIK4353, with the 95% confidence interval spanning from 25 to 57 cM in Chinese Holstein population using QTL-express, MQREML, and GRIDQTL softwares. This study herein focused on such region of fine mapping QTLs for milk production and functional traits with 16 microsatellite markers with coverage of 33 cM between the markers BMS2904 and MB099 on BTA3 in a daughter-designed Chinese Holstein population. A total of 1 298 Holstein cows and 7 sires were genotyped for 16 microsatellites with ABI 3700 DNA sequencer. The variance components QTL linkage analysis (LA) and linkage-disequilibrium (LD) analysis (LA/LD) was performed to map QTLs for 7 traits, i.e., 305-d milk yield, fat yield, protein yield, fat percentage, protein percentage, somatic cell score and persistency of milk yield. Four strong and highly significant QTLs were detected for fat yield, fat percentage, protein percentage and somatic cell score at the position 40, 30, 27 and 26 cM, respectively. Two minor QTLs for milk yield and persistency of milk yield were identified at 42 and 46 cM, respectively. These findings provided a general idea for the fine mapping of the causal mutation for milk production and functional traits on BTA3 in the future.

Abstract  It had been demonstrated that the strong and highly significant quantitative trait locus (QTL) can affect protein percentage on Bos Taurus Autosome 3 (BTA3) at the position 52 cM, near the microsatellite DIK4353, with the 95% confidence interval spanning from 25 to 57 cM in Chinese Holstein population using QTL-express, MQREML, and GRIDQTL softwares. This study herein focused on such region of fine mapping QTLs for milk production and functional traits with 16 microsatellite markers with coverage of 33 cM between the markers BMS2904 and MB099 on BTA3 in a daughter-designed Chinese Holstein population. A total of 1 298 Holstein cows and 7 sires were genotyped for 16 microsatellites with ABI 3700 DNA sequencer. The variance components QTL linkage analysis (LA) and linkage-disequilibrium (LD) analysis (LA/LD) was performed to map QTLs for 7 traits, i.e., 305-d milk yield, fat yield, protein yield, fat percentage, protein percentage, somatic cell score and persistency of milk yield. Four strong and highly significant QTLs were detected for fat yield, fat percentage, protein percentage and somatic cell score at the position 40, 30, 27 and 26 cM, respectively. Two minor QTLs for milk yield and persistency of milk yield were identified at 42 and 46 cM, respectively. These findings provided a general idea for the fine mapping of the causal mutation for milk production and functional traits on BTA3 in the future.
Keywords:  QTL mapping       economic traits       microsatellite markers       BTA3       Chinese Holstein  
Received: 12 April 2013   Accepted:
Fund: 

This work was supported by the High Technology Research and Development Program of China (2013AA102504), the Beijing Innovation Team of Technology System in the National Dairy Industry, the National Key Technologies R&D Program of China (2011BAD28B02, 2012BAD12B01), the Beijing Research and Technology Program, China (D121100003312001) and the Program for Changjiang Scholar and Innovation Research Team in University, China (IRT1191).

Corresponding Authors:  SUN Dong-xiao, Tel/Fax: +86-10-62734653, E-mail: sundx@cau.edu.cn     E-mail:  sundx@cau.edu.cn

Cite this article: 

QIN Chun-hua, CHU Qin, CHU Gui-yan, ZHANG Yi, ZHANG Qin, ZHANG Sheng-li , SUN Dong-xiao. 2014. Mapping QTLs Affecting Economic Traits on BTA3 in Chinese Holstein with Microsatellite Markers. Journal of Integrative Agriculture, 13(9): 1999-2004.

Ahwell M S, Heyen D W, Sonstegard T S, van Tassell C P, Da Y, VanRaden P M, Ron M, Weller J I, Lewin H A. 2004. Detection of quantitative trait loci affecting milk production, health, and reproductive traits in Holstein cattle. Journal of Dairy Science, 87, 468-475

 Ashwell M S, van Tassell C P, Sonstegard T S. 2001. Genome scan to identify quantitative trait loci affecting economically important traits in a US Holstein population. Journal of Dairy Science, 84, 2535-2342

 Bagnato A, Schiavini F, Rossoni A, Maltecca C, Dolezal M, Medugorac I, Sölkner J, Russo V, Fontanesi L, Friedmann A, Soller M, Lipkin E. 2008. Quantitative trait loci affecting milk yield and protein percentage in a three-country Brown Swiss population. Journal of Dairy Science, 91, 767-783

 Boichard D, Grohs C, Bourgeois F, Cerqueira F, Faugeras R, Neau A, Rupp R, Amigues Y, Boscher M Y, Levéziel H. 2003. Detection of genes influencing economic traits in three French dairy cattle breeds. Genetics Selection Evolution, 35, 77-101

 Calvo J H, Martínez-Royo A, Silveri L, Floriot S, Eggen A, Marcos-Carcavilla A, Serrano M. 2006. Isolation, mapping and identification of SNPs for four genes (ACP6, CGN, ANXA9, SLC27A3) from a bovine QTL region on BTA3. Cytogenet Genome Research, 114, 39-43

 Chen H Y, Zhang Q, Yin C C, Wang C K, Gong W J, Mei G. 2006. Detection of quantitative trait loci affecting milk production traits on bovine chromosome 6 in a Chinese Holstein population by the daughter design. Journal of Dairy Science, 89, 782-790

 Chu Q. 2008. QTL mapping of important economic traits on BTA3 in Chinese Holstein. Ph D thesis, China Agricultural University, China. (in Chinese)

Cohen-Zinder M, Donthu R, Larkin D M, Kumar C G, Rodriguez-Zas S L, Andropolis K E, Oliveira R, Lewin H A. 2011. Multisite haplotype on cattle chromosome 3 is associated with quantitative trait locus effects on lactation traits. Physiological Genomics, 43, 1185-1197

 Daetwyler H D, Schenkel F S, Sargolzaei M, Robinson J A. 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, 3225-3236

 Duet T, Fritz S, Boucher M, Ben-Jamaal S, Guillaume F, Durable D, Hellenic D, Lecher D, Chiron C, Boucher D, Gut I G, Egan A, Gautier M. 2008. Fine mapping of quantitative trait loci affecting female fertility in dairy cattle on BTA3 using a dense single-nucleotide polymorphism map. Genetics, 178, 2227-2235

 Geldermann H. 1975. Investigation on inheritance of quantitative characters in animals by gene markers. Genetics, 46, 300-319

 Heyen D W, Weller J I, Ron M, Band M, Beaver J E, Redresser E, Ad Y, Wiggins G R, van Aden P M, Levin H A. 1999. A genome scan for QTL influencing milk production and health traits in dairy cattle. Physiological Genomics, 1, 165-175

 Ihara N, Tamaqua A, Mizoshita K, Takeda H, Sugimoto M, Mizoguchi Y, Hirano T, Itoh T, Watanabe T, Reed K M, Snelling W M, Kappes S M, Beattie C W, Bennett G L, Sugimoto Y. 2004. A comprehensive genetic map of the cattle genome based on 3802 microsatellites. Genome Research, 14, 1987-1998

 Khatkar M S, Thomson P C, Tammen I, Raadsma H W. 2004. Quantitative trait loci mapping in dairy cattle: Review and meta-analysis. Genetics Selection Evolution, 36, 163-190

 Liu R, Sun D X, Wang Y C, Yu Y, Zhang Y, Chen H Y, Zhang Q, Zhang S L, Zhang Y. 2013. Fine mapping QTLs affecting milk production traits on BTA6 in Chinese Holstein with SNP markers. Journal of Integrative Agriculture, 12, 110-117

 Martinez-Royo A, Ordovas L, Zaragoza P, Altarriba J, Serrano M, Rodellar C, Calvo J H. 2010. The bovine annexin9 (ANXA9) is significantly associated with milk-fat yield in a Spanish Holstein-Friesian population. Research in Veterinary Science, 88, 452-455

 Mei G, Yin C C, Ding X D, Zhang Q. 2009. Fine mapping quantitative trait loci affecting milk production traits on bovine chromosome 6 in a Chinese Holstein population. Journal of Genetics and Genomics, 36, 653-660

 Olsen H G, Gomez-Raya L, Våge D I, Olsaker I, Klungland H, Svendsen M, Adnøy T, Sabry A, Klemetsdal G, Schulman N, Krämer W, Thaller G, Rønningen K, Lien S. 2002. A genome scan for quantitative trait loci affecting milk production in Norwegian dairy cattle. Journal of Dairy Science, 85, 3124-3130

 Patton S, Gendler S J, Spicer A P. 1995. The epithelial mucin, MUC1, of milk, mammary gland and other tissues. Biochimica et Biophysica Acta (Reviews on Biomembranes), 1241, 407-423

 Perucatti A, Floriot S, di Meo G P. 2006. Comparative FISH mapping of mucin 1, transmembrane (MUC1) among cattle, river buffalo, sheep and goat chromosomes: Comparison between bovine chromosome 3 and human chromosome 1. Cytogenet Genome Research, 112, 103-105

 Plante Y, Gibson J P, Nadesalingam J, Mehrabani-Yeganeh H, Lefebvre S, Vandervoort G, Jansen G B. 2001. Detection of quantitative trait loci affecting milk production traits on 10 chromosomes in Holstein cattle. Journal of Dairy Science, 84, 1516-1524

 Rodriguez-Zas S L, Southey B R, Heyen D W, Lewin H A. 2002. Interval and composite interval mapping of somatic cell score, yield, and components of milk in dairy cattle. Journal of Dairy Science, 85, 3081-3091

 Ron M, Weller J I. 2007. From QTL to QTN identification in livestock-Winning by points rather than knock-out: A review. Animal Genetics, 38, 429-439

 Rupp R, Boucher D. 2003. Genetics of resistance to mastitis in dairy cattle. Veterinary Research, 34, 671-688

 Russo V, Fontanesi L, Dolezal M, Lipkin E, Scotti E, Zambonelli P, Dall’Olio S, Bigi D, Davoli R, Canavesi F, Medugorac I, Föster M, Sölkner J, Schiavini F, Bagnato A, Soller M. 2012. A whole genome scan for QTL affecting milk protein percentage in Italian Holstein cattle, applying selective milk DNA pooling and multiple marker mapping in a daughter design. Animal Genetics, 43, 72-86

 Schulman N F, Viitala S M, de Koning D J, Virta J, Maki- Tanila A, Vilkki J H. 2004. Quantitative trait loci for health traits in Finnish Ayshire cattle. Journal of Dairy Science, 87, 443-449

 Seaton G, Hernandez J, Brunches J A, White I, Allen J, de Coning D J, Weir W, Berry D, Haley C, Knott S. 2006. GridQTL: A Grid portal for QTL mapping of compute intensive datasets. In: Proceedings of the 8th World Congress on Genetics Applied to Livestock Production. Belo Horizontal, Minas Gerais, Brazil.

Tal-Stein R, Fontanesi L, Dolezal M, Scotti E, Bagnato A, Russo V, Canavesi F, Friedmann A, Soller M, Lipkin E. 2010. A genome scan for quantitative trait loci affecting milk somatic cell score in Israeli and Italian Holstein cows by means of selective DNA pooling with single- and multiple-marker mapping. Journal of Dairy Science, 93, 4913-4927

 Viitala S M, Schulman N F, de Koning D J, Elo K, Kinos R, Virta A, Virta J, Mäki-Tanila A, Vilkki J H. 2003. Quantitative trait loci affecting milk production traits in Finnish Ayrshire dairy cattle. Journal of Dairy Science, 86, 1828-1836

 Zhang Q, Boichard D, Hoeschele I, Ernst C, Eggen A, Murkve B, Pfister-Genskow M, Witte LA, Grignola F E, Uimari P, Thaller G, Bishop M D. 1998. Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbreed pedigree. Genetics, 149, 1959-1973
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