Abstract
This study represents the first attempt at an empirical evaluation of the DNA pooling methodology by comparing it to individual genotyping and interval mapping to detect QTL in a dairy half-sib design. The findings indicated that the use of peak heights from the pool electropherograms without correction for stutter (shadow) product and preferential amplification performed as well as corrected estimates of frequencies. However, errors were found to decrease the power of the experiment at every stage of the pooling and analysis. The main sources of errors include technical errors from DNA quantification, pool construction, inconsistent differential amplification, and from the prevalence of sire alleles in the dams. Additionally, interval mapping using individual genotyping gains information from phenotypic differences between individuals in the same pool and from neighbouring markers, which is lost in a DNA pooling design. These errors cause some differences between the markers detected as significant by pooling and those found significant by interval mapping based on individual selective genotyping. Therefore, it is recommended that pooled genotyping only be used as part of an initial screen with significant results to be confirmed by individual genotyping. Strategies for improving the efficiency of the DNA pooling design are also presented.
Highlights
Linkage analysis studies to detect genes of modest effect that are expected to underlie complex traits are large costly experiments
When the objective is to determine the difference between the high and low pools it may not be necessary to determine individual allele frequencies from pools. This is because biases associated with stutter peaks and preferential amplification should apply to both high and low pools when analysis is performed within families, as was done here
While there have been some attempts at computer simulations to study the effects of technical errors and the prevalence of sire alleles in the dam population on the power of the selective DNA pooling design [2], there has been no report of an empirical evaluation of these errors and their impact on QTL detection
Summary
Linkage analysis studies to detect genes of modest effect that are expected to underlie complex traits are large costly experiments. By combining selective genotyping with DNA pooling, the costs can be lowered significantly Such a design is appealing for dairy populations, where the availability of large half-sib populations can be exploited efficiently [18, 19, 21, 25]. Which represent the most widely used class of markers in linkage studies, inferring allele frequencies from pools is complicated by the presence of stutter (shadow) product and preferential amplification. When the objective is to determine the difference between the high and low pools it may not be necessary to determine individual allele frequencies from pools This is because biases associated with stutter peaks and preferential amplification should apply to both high and low pools when analysis is performed within families, as was done here
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