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Mapping QTLs on BTA6 affecting milk production traits in a Chinese Holstein population

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Chinese Science Bulletin

Abstract

A Chinese Holstein population with daughter design was analyzed using 14 microsatellites covering a map distance of 55.7 cM on chromosome 6 to fine map QTL for five milk production traits. 26 paternal half-sib families with 2356 daughters were involved. Two different approaches, linear regression approach and variance component approach, were employed, with a one-QTL model and two-QTL model fitted. With a one-QTL model, the linear regression approach revealed a QTL near BMS470 with effects on milk yield, fat yield, protein yield, and fat percentage, and another QTL near BMS2460 for protein percentage. The variance component approach confirmed the results of linear regression approach for the three yield traits, with the exception that the QTL for fat yield was mapped to a different position near BMS1242. The 95% confidence intervals resulted from linear regression, obtained by bootstrapping, were generally large, ranging from 31 to 53 cM, whereas the variance component approach revealed very small confidence intervals, calculated by LOD drop-off method, for the three yield traits, only 4–5 cM. With a two-QTL model, both approaches provided strong evidence for the existence of two QTLs for the three yield traits. Along with the QTLs identified in one-QTL model analyses, the linear regression approach revealed a second QTL near BP7 with effects on all the three yield traits, whereas the variance component approach located the second QTL near ILSS035, BMS470, and BP7 for the three traits, respectively.

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References

  1. Georges, M., Nielsen, D., Mackinnon, M. et al., Mapping quantitative trait loci controlling milk pro duction in dairy cattle by exploiting progeny testing, Genetics, 1995, 139: 907–920.

    Google Scholar 

  2. Zhang, Q., Boichard, D., Hoeschele, I. et al., Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree, Genetics, 1998, 149: 1959–1973.

    Google Scholar 

  3. Maki-Tanila, A., de Koning, D. J., Elo, K. et al., Mapping of multiple quantitative trait loci by regression in half sib designs, Proc. 6th World Congr. Genet. Appl. Livest. Prod., 1998: 269–272.

  4. Ashwell, M. S., van Tassell, C. P., Sonstegard, T. S., A genome scan to identify quantitative trait loci affecting economically important traits in a US Holstein population, J. Dairy. Sci., 2001, 84: 2535–2542.

    Google Scholar 

  5. Mosig, M. O., Lipkin, E., Khutoreskaya, G. et al., A whole genome scan for quantitative trait loci affecting milk protein percentage in Israeli-Holstein cattle, by means of selective milk DNA pooling in a daughter design, using an adjusted false discovery rate criterion, Genetics, 2001, 157: 1683–1698.

    Google Scholar 

  6. Kappes, S. M., Keele, J. W., Stone, R. T. et al., A second-generation linkage map of the bovine genome, Genome Res., 1997, 7: 235–249.

    Article  Google Scholar 

  7. Ron, M., Kliger, D., Feldmesser, E. et al., Multiple quantitative trait locus analysis of bovine chromosome 6 in the Israeli Holstein population by a daughter design, Genetics, 2001, 159: 727–735.

    Google Scholar 

  8. Cohen, M., Reichenstein, M., van der Wind, A. E. et al., Cloning and characterization of FAM13A1-a gene near a milk protein QTL on BTA6: Evidence for population-wide linkage disequilibrium in Israeli Holsteins, Genomics, 2004, 84: 374–383.

    Article  Google Scholar 

  9. Olsen, H. G., Lien, S., Gautier, M. et al., Mapping of a milk production QTL to a 420 kb region on bovine chromosome 6, Genetics, 2005, 169: 275–283.

    Article  Google Scholar 

  10. Lipkin, E. M., Mosig, O., Darvasi, E. A. et al., Quantitative trait locus mapping in dairy cattle by means of selective milk DNA pooling using dinucleotide microsatellite markers: Analysis of milk protein percentage, Genetics, 1998, 149: 1557–1567.

    Google Scholar 

  11. Ashwell, M. S., Schnabel, R. D., Sonstegard, T. S. et al., Fine-mapping of QTL affecting protein percent and fat percent on BTA6 in a popular U.S. Holstein family, Proc. 7th World Congr. Genet. Appl. Livest. Prod., 2002, Section 09–29.

  12. Freyer, G., Sorensen, P., Kuhn, C. et al., Search for pleiotropic QTL on chromosome BTA6 affecting yield traits for milk production, J. Dairy Sci., 2003, 86: 999–1008.

    Article  Google Scholar 

  13. Zhang, S. L., Shi, W. H., Zheng, W. T. et al., Application of animal model BLUP in genetic evaluation of dairy cattle in Beijing, Processing Beijing International Conference and Exhibition on Dairy, 2000, 72–75.

  14. Wiener, P., Maclean, I., Williams, J. L. et al., Testing for the presence of previously identified QTL for milk production traits in new populations, Anim. Genet., 2000, 31: 385–395.

    Article  Google Scholar 

  15. Knott, S. A., Elsen, J. M., Haley, C. S., Methods for multiple marker mapping of quantitative trait loci in half-sib populations, Theor. Appl. Genet., 1996, 93: 71–80.

    Article  Google Scholar 

  16. Grignola, F. E., Hoeschele, I., Tier, B., Mapping quantitative trait loci in outcross populations via residual maximum likelihood, I. Methodol. Genet. Sel. Evol., 1996, 28: 479–490.

    Article  Google Scholar 

  17. Grignola, F. E., Zhang, Q., Hoeschele, I., Mapping linked quantitative trait loci via residual maximum likelihood, Genet. Sel. Evol., 1997, 29: 529–544.

    Article  Google Scholar 

  18. Zhang, Q., Hoeschele, I., Multiple QTL mapping in outcross populations via residual maximum likelihood, Proc. 6th World Congr. Genet. Appl. Livest. Prod., 1998: 265–268.

  19. Seaton, G., Haley, C. S., Knott, S. A. et al., QTL express: Mapping quantitative trait loci in simple and complex pedigrees, Bioinformatics, 2001, 18: 339–340.

    Article  Google Scholar 

  20. Visscher, P. M., Thompson, R., Haley, C. S., Confidence intervals in QTL mapping by bootstrapping, Genetics, 1996, 143: 1013–1020.

    Google Scholar 

  21. Hoeschele, I., Grignola, F. E., Li, Y. J. et al., MQREML, MQAREML, MPLGIB, and NQTLGIB: Software for QTL mapping in outcross or complex pedigrees, Proc. 6th World Congr. Genet. Appl. Livest. Prod., 1998: 441–442.

  22. Lander, E. S., Botstein, D. B., Mapping mendelian factors underlying quantitative traits using RFLP linkage maps, Genetics, 1989, 121: 185–199.

    Google Scholar 

  23. Kühn, C., Freyer, G., Weikard, R. et al., Detection of QTL for milk production traits in cattle by application of a specifically developed marker map of BTA6. Anim. Genet, 1999, 30: 333–340.

    Article  Google Scholar 

  24. Weikard, R., Kühn, C., Goldammer, T. et al., A high resolution comparative map for a bovine chromosome 6 (BTA6) region containing QTL for production, health and conformation traits, Proc. 7th World Congr. Genet. Appl. Livest. Prod., 2002, Section 09–30.

  25. Spelman, R. J., Coppieters, W., Karim, L. et al., Quantitative trait loci analysis for five milk production traits on chromosome six in the Dutch Holstein-Friesian population, Genetics, 1996, 144: 1799–1808.

    Google Scholar 

  26. Velmala, R., Vilkki, J., Elo, K. et al., A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle, Anim. Genet, 1999, 30: 136–143.

    Article  Google Scholar 

  27. Olsen, H. G., Lien, S., Svendsen, M. et al., Fine mapping of milk production QTL on BTA6 by combined linkage and linkage disequilibrium analysis, J. Dairy. Sci., 2004, 87: 690–698.

    Google Scholar 

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Correspondence to Qin Zhang.

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Chen, H., Zhang, Q., Wang, C. et al. Mapping QTLs on BTA6 affecting milk production traits in a Chinese Holstein population. Chin.Sci.Bull. 50, 1737–1742 (2005). https://doi.org/10.1360/982005-725

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  • DOI: https://doi.org/10.1360/982005-725

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