Abstract
Accurate genetic data are important prerequisite of performing genetic linkage test or association test. Currently, most analytical methods assume that the observed genotypes are correct. However, due to the constraint at the technical level, most of the genetic data that people used so far contain errors. In this paper, we considered the problem of QTL mapping based on biological data with genotyping errors. By analysing all possible genotypes of each individual in framework of multiple-interval mapping, we proposed an algorithm of inferring all model parameters through the expectation-maximization (EM) algorithm and discussed the hypothesis testing of the existence of QTL. We carried out extensive simulation studies to assess the proposed method. Simulation results showed that the new method outperforms the method that does not take the genotyping errors into account, and therefore it can decrease the impact of genotyping errors on QTL mapping. The proposed method was also applied to analyse a real barley dataset.
Similar content being viewed by others
References
Abecasis G. R., Cherny S. S. and Cardon L. R. 2001 The impact of genotyping error on family-based analysis of quantitative traits. Eur. J. Hum. Genet. 9, 130–134.
Akey J. M., Zhang K., Xiong M., Doris P. and Jin L. 2001 The effect that genotyping errors have on the robustness of common linkage disequilibrium measures. Am. J. Hun. Genet. 68, 1447–1456.
Buetow K. H. 1991 Influence of aberrant observations on high resolution linkage analysis outcomes. Am. J. Hum. Genet. 49, 985–994.
Cartwright D. A., Troggio M., Velasco R. and Gutin A. 2007 Genetic mapping in the presence of genotyping errors. Genetics 176, 2521–2527.
Chen Z. H. 2005 The full EM algorithm for the MLEs of QTL effects and positions and their estimated variances in multiple-interval mapping. Biometrics 6, 474–480.
Churchill G. A. and Doerge R. W. 1994 Empirical threshold values for quantitative trait mapping. Genetics 138, 963–971.
Dempster A. P., Laird N. M. and Rubin D. B. 1977 Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc., B 39, 1–38.
Douglas J. A., Boehnke M. and Lange K. 2000 A multipoint method for detecting genotyping errors and mutations in sibling-pair linkage data. Am. J. Hum. Genet. 66, 1287–1297.
Goldstein D. R., Zhao H. and Speed T. P. 1997 The effects of genotyping errors and interference on estimation of genetics distance. Hum. Hered. 47, 86–100.
Hou Y. J. 2011 Parameter estimation in quantitative trait loci mapping when using data with genotyping errors (in Chinese). M.Sc. dissertation. Heilongjiang University, Harbin, China.
Jeon G. J. 1995 The effects of population size and dominance of quatitative trait loci (QTL) on the detection of linkage betweenmarkers and QTL for livestock. Asian Aust. J. Anim. Sci. 8, 651–655.
Kao C. H., Zeng Z. B. and Teasdale R. D. 1999 Multiple interval mapping for quantitative trait loci. Genetics 152, 1203–1216.
Lander E. S. and Botstein D. B. 1989 Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185–199.
Lebrec J. J., Putter H., Houwing-Duistermaat J. J. and van Houwelingen H. C. 2008 Influence of genotyping errors in linkage mapping for complex traits-an analytic study. BMC Genet. 9, 57.
Louis T. A. 1982 Finding the observed information matrix when using the EM algorithm. J. R. Stat. Soc., B 44, 226–233.
Ma W. J., Zhou Y. and Zhang S. L. 2011 A two-step method for estimating QTL effects and positions in multi-marker analysis. Genet. Res. 93, 115–124.
Sobel E., Papp J. C. and Lange K. 2002 Detection and integration of genotyping errors in statistical genetics. Am. J. Hum. Genet. 70, 496–508.
Tinker N. A., Mather D. E., Rossnagel B. G., Kasha K. J. and Kleinhofs A. 1996 Regions of the genome that affect agronomic performance in two-row barley. Crop Sci. 36, 1053–1062.
Wang D. L., Zhu J., Li Z. K. L. and Paterson A. H. 1999 Mapping QTL with epistatic effects and QTL × environment interactions by mixed linear model approaches. Theor. Appl. Genet. 99, 1255–1264.
Xu S. 2007 An empirical Bayes method for estimating eqistatic effects of quantitative trait loci. Biometrics 63, 513–521.
Zeng Z. B. 1994 Precision mapping of quantitative trait loci. Genetics 135, 1457–1468.
Zhou Y. 2010 Multiple interval mapping for quantitative trait loci via EM algorithm in the presence of crossover interference. Commun. Stat.-Theor. Method 39, 3041–3057.
Acknowledgements
This research was supported by the National Natural Science Foundation of China (nos. 11201129 and 11371083), the Natural Science Foundation of Heilongjiang Province of China (A201207), the Scientific Research Foundation of Department of Education of Heilongjiang Province of China (no. 1253G044) and the Science and Technology Innovation Team in Higher Education Institutions of Heilongjiang Province (no. 2014TD005). This work was partly supported by the Science and Technology Programme of Suihua of China (no. KJZD20130112) and the Youth Fund Project in 2013 of Suihua University of China (KQ 1302004).
Author information
Authors and Affiliations
Corresponding author
Additional information
[Tong L., Ma W., Liu H., Yuan C. and Zhou Y. 2015 Simultaneous estimation of QTL effects and positions when using genotype data with errors. J. Genet. 94, xx–xx]
Rights and permissions
About this article
Cite this article
TONG, L., MA, W., LIU, H. et al. Simultaneous estimation of QTL effects and positions when using genotype data with errors. J Genet 94, 27–34 (2015). https://doi.org/10.1007/s12041-015-0487-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12041-015-0487-z