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D E Mather

Publications and source records attributed to D E Mather.

4 recordsLinked to original sources

Effect of population size on the estimation of QTL: a test using resistance to barley stripe rust.

The limited population sizes used in many quantitative trait locus (QTL) detection experiments can lead to underestimation of QTL number, overestimation of QTL effects, and failure to quantify QTL interactions. We used the barley/barley stripe rust pathosystem to evaluate the effect of population size on the estimation of QTL parameters. We generated a large (n = 409) population of doubled haploid lines derived from the cross of two inbred lines, BCD47 and Baronesse. This population was evaluated for barley stripe rust severity in the Toluca Valley, Mexico, and in Washington State, USA, under field conditions. BCD47 was the principal donor of resistance QTL alleles, but the susceptible parent also contributed some resistance alleles. The major QTL, located on the long arm of chromosome 4H, close to the Mlo gene, accounted for up to 34% of the phenotypic variance. Subpopulations of different sizes were generated using three methods-resampling, selective genotyping, and selective phenotyping-to evaluate the effect of population size on the estimation of QTL parameters. In all cases, the number of QTL detected increased with population size. QTL with large effects were detected even in small populations, but QTL with small effects were detected only by increasing population size. Selective genotyping and/or selective phenotyping approaches could be effective strategies for reducing the costs associated with conducting QTL analysis in large populations. The method of choice will depend on the relative costs of genotyping versus phenotyping.

Analysis of Variance↗

Effectiveness of selective genotyping for detection of quantitative trait loci: an analysis of grain and malt quality traits in three barley populations.

Marker genotype data and grain and malt quality phenotype data from three barley (Hordeum vulgare L.) mapping populations were used to investigate the feasibility of selective genotyping for detection of quantitative trait loci (QTLs). With selective genotyping, only individuals with high and low phenotypic values for the trait of interest are genotyped. Here, genotyping of 10 to 70% of each population (i.e., 5 to 35% in each tail of the phenotypic distribution) was considered. Genomic positions detected by selective genotyping were compared to QTL position estimates from interval mapping analysis using marker genotype data from the entire population. Selective genotyping reliably detected almost all of the mapped QTLs, often with only 10% of the population genotyped. Selective genotyping also detected spurious QTLs in regions of the genome where no significant QTL had been mapped. Even with additional genotyping to verify putative QTLs, the total genotyping effort for detection of QTLs for a single trait by selective genotyping was usually less than 30% of that required for conventional interval mapping. Simultaneous investigation of two or more traits by selective genotyping would require additional genotyping effort, but could still be worthwhile.

Genotype↗

A method for detecting DNA polymorphism in large populations.

Molecular markers linked to loci of interest can be used for fine mapping a particular area of a genome or for marker-assisted selection. We present an approach for screening individual plants with polymorphic markers that facilitates phenotyping in large populations. Polymorphic DNA fragments, amplified by PCR, are labelled with digoxigenin and used as probes on slot blots of amplified DNA from the individual plants to be tested. DNA is obtained by a simple two-tube purification method. The colorimetric detection of alleles on the blots is more reliable, and more amenable to automation, than conventional staining of electrophoresis gels.

DNA↗

Estimation of phenotypic selection differentials for predicting genetic responses to ratio-based selection.

Ratios of the phenotypic values of two traits may be used as selection criteria in animal and plant breeding to improve the ratio traits themselves or to effect changes in their two component (numerator and denominator) traits. Prediction of genetic responses to ratio-based selection would facilitate quantitative analysis and evaluation of selection based on ratios. Methods for predicting such responses are derived and presented here. They employ expressions for the truncation value of a ratio and for the phenotypic selection differentials of the numerator and denominator traits. The derivation of these expressions is based upon the assumption that the phenotypic values of each of these traits are normally distributed. Worked examples relating to livestock and crop improvement are included to demonstrate how responses to selection for ratios may be predicted.

Agriculture↗