Detection of quantitative trait loci in half sib dairy families: Power and bias when parents are selected.

摘要

Questions remain about detection of major genes in segregating populations. Studies were initiated to confirm an association between a quantitative trait locus (QTL) in dairy cattle and a polymorphism detected with a prolactin probe. A number of prolactin related protein genes have been found near the prolactin locus, which have high sequence similarity with each other and with prolactin. Prolactin related protein I was screened for sequence polymorphism using restriction digest and heteroduplex analysis. A HinfI/BstYI polymorphism was discovered at nucleotide 1313 (GenBank accession M25494). In addition, QTL interval mapping was performed on the telomeric end of bovine chromosome 23, using offspring and grandoffspring of sire A. Significant (experimentwise p .05) QTL chromosome substitution effects were found at loci towards the telomere for PTA milk (273 kg., +/−91), PTA net merit dollars (45 dollars, +/−16) and PTA productive life (1.21 months, +/−0.33).; Domestic populations used for QTL studies usually have a history of selection. Effects of selection on QTL detection by sib-pair regression was studied on simulated data of half sib families of 20 to 50 offspring. Power was found to be increased after selection, in part because heterozygosity in common parents was above expectations from Hardy Weinberg equilibrium. Estimates of QTL variance from sib-pair regression were unbiased in large halfsib families from populations not under selection but were biased by selection.; One possible source of bias in estimation of QTL effects is residual linkage disequilibrium between QTL and other unlinked genes due to selection in previous generations. Residual linkage disequilibrium caused a downward bias on the estimation of QTL effects by candidate gene analysis and also by segregation analysis but then only when the marker was in linkage disequilibrium with the QTL. Marker-QTL linkage disequilibrium caused an upward bias in estimates from segregation analysis but only when markers were not completely informative. When no linkage disequilibrium was present between marker and QTL, segregation analysis yielded unbiased estimates even when previous generations were selected.