Multiple Interval Mapping

2016 ◽  
pp. 151-186
Keyword(s):  
Interval Mapping ◽  
Multiple Interval Mapping

scholarly journals Multiple Interval Mapping for Quantitative Trait Loci

Genetics ◽  
1999 ◽  
Vol 152 (3) ◽  
pp. 1203-1216
Author(s):  
Chen-Hung Kao ◽  
Zhao-Bang Zeng ◽  
Robert D Teasdale
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genetic Parameters ◽  
Interval Mapping ◽  
Ratio Test ◽  
Data Set ◽  
Multiple Interval Mapping ◽  
Total Genetic Variation ◽  
Trait Loci

Abstract A new statistical method for mapping quantitative trait loci (QTL), called multiple interval mapping (MIM), is presented. It uses multiple marker intervals simultaneously to fit multiple putative QTL directly in the model for mapping QTL. The MIM model is based on Cockerham's model for interpreting genetic parameters and the method of maximum likelihood for estimating genetic parameters. With the MIM approach, the precision and power of QTL mapping could be improved. Also, epistasis between QTL, genotypic values of individuals, and heritabilities of quantitative traits can be readily estimated and analyzed. Using the MIM model, a stepwise selection procedure with likelihood ratio test statistic as a criterion is proposed to identify QTL. This MIM method was applied to a mapping data set of radiata pine on three traits: brown cone number, tree diameter, and branch quality scores. Based on the MIM result, seven, six, and five QTL were detected for the three traits, respectively. The detected QTL individually contributed from ∼1 to 27% of the total genetic variation. Significant epistasis between four pairs of QTL in two traits was detected, and the four pairs of QTL contributed ∼10.38 and 14.14% of the total genetic variation. The asymptotic variances of QTL positions and effects were also provided to construct the confidence intervals. The estimated heritabilities were 0.5606, 0.5226, and 0.3630 for the three traits, respectively. With the estimated QTL effects and positions, the best strategy of marker-assisted selection for trait improvement for a specific purpose and requirement can be explored. The MIM FORTRAN program is available on the worldwide web (http://www.stat.sinica.edu.tw/~chkao/).

scholarly journals Limitations of a two-step moment method for mapping linked multiple QTL

2004 ◽  
Vol 84 (3) ◽  
pp. 145-152
Author(s):  
MANFRED MAYER
Keyword(s):  
Moment Method ◽  
Interval Mapping ◽  
Ratio Test ◽  
Residual Variance ◽  
Test Statistics ◽  
Conditional Probabilities ◽  
Multiple Interval Mapping ◽  
Variance Estimates ◽  
Empirical Standard ◽  
Qtl Effects

As an alternative to multiple-interval mapping a two-step moment method was recently proposed to map linked multiple quantitative trait loci (QTLs). The advantage of this moment method was supposed to be its simplicity and computational efficiency, especially in detecting closely linked QTLs within a marker bracket, but also in mapping QTLs in different marker intervals. Using simulations it is shown that the two-step moment method may give poor results compared with multiple-interval mapping, irrespective of whether the QTLs are in the same or in different marker intervals, especially if linked QTLs are in repulsion. The criteria of comparison are number of identified QTLs, likelihood ratio test statistics, means and empirical standard errors of the QTL position and QTL effects estimates, and the accuracy of the residual variance estimates. Further, the joint conditional probabilities of QTL genotypes for two putative QTLs within a marker interval were derived and compared with the unmodified approach ignoring the non-independence of the conditional probabilities.

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