Development and assessment of simple PCR markers for SNP genotyping in barley.

Simple molecular marker assays underpin routine plant breeding and research activities in many laboratories worldwide. With the rapid growth of single nucleotide polymorphism (SNP) resources for many important crop plants, the availability of routine, low-tech marker assays for genotyping SNPs is of increased importance. In this study, we demonstrate that temperature-switch PCR (TSP) supports the rapid development of robust, allele-specific PCR markers for codominant SNP genotyping on agarose gel. A total of 87 TSP markers for assessing gene diversity in barley were developed and used to investigate the efficacy for marker development, assay reliably and genotyping accuracy. The TSP markers described provide good coverage of the barley genome, are simple to use, easy to interpret and score, and are amenable to assay automation. They provide a resource of informative SNP markers for assessing genetic relationships among individuals, populations and gene pools of cultivated barley (Hordeum vulgare L.) and its wild relative H. spontaneum K. Koch. TSP markers provide opportunities to use available SNP resources for marker-assisted breeding and plant genetic research, and to generate information that can be integrated with SNP data from different sources and studies. TSP markers are expected to provide similar advantages for any animal or plant species.

QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses.

Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to 'trait-based' analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to 'marker-based' analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and (or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.

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.

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.

Pooled DNA for linkage analysis: practical and statistical considerations.

In an F2 population, the alleles at two loci with a recombination fraction r < 0.5 are in linkage disequilibrium. If r is small, then a pool of DNA from k diploid individuals that are fixed at one locus has a relatively high probability (P = (1 − r)2k) of containing only the coupled allele at the second locus. Based on this principle, several methods have been described to detect linkage (using one or two pools) or to estimate r (using a group of n pools). This report compares maximum likelihood and approximate estimators of r for use in pooled-DNA analysis and illustrates the use of this analysis for dominant markers. Expected values and expected mean squares for estimators of r were computed for varying levels of r, k, and n. Both estimators were biased, but the bias and variability were slightly smaller for the maximum-likelihood estimator. Bias was not severe except when k was large relative to r and (or) n. Methods for optimizing k are discussed relative to several criteria: minimizing variance, minimizing bias, minimizing the probability that linkage cannot be detected, and minimizing the number of samples that must be screened.

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.

Random amplified polymorphic DNA and pedigree relationships in spring barley.

We investigated random amplified polymorphic DNA (RAPD) in 27 inbred barley lines with varying amounts of common ancestry and in 20 doubled-haploid (DH) lines from a biparental cross. Of 33 arbitrary 10 base primers that were tested, 19 distinguished a total of 31 polymorphisms. All polymorphisms were scored as dominant genetic markers except for 1, where Southern analysis indicated the presence of two codominant amplification products. The inheritance of 19 RAPD polymorphisms and one morphological trait was studied in the DH lines. There was no evidence for segregation distortion, but a group of four tightly linked loci was detected. The frequencies of RAPD polymorphism in pairs of inbred lines were used to compute values of genetic distance (d), which were compared to kinship coefficients (r) between the same pairs of lines. A linear relationship between r and d was evident, but low values of r gave poor predictions of d. Cluster analysis showed that groups of inbred lines based on r were similar to those based on d with some notable exceptions. RAPD markers can be used to gain information about genetic similarities or differences that are not evident from pedigree information.

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.