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| 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.
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Received: 12 April 2013
Accepted:
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| 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). |
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Corresponding Authors:
SUN Dong-xiao, Tel/Fax: +86-10-62734653, E-mail: sundx@cau.edu.cn
E-mail: sundx@cau.edu.cn
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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.
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