No abstract

A method based on the non-central chi-square distribution is developed for the calculation of sample sizes required to reject, with given probability, models of variation when they are "wrong ". The method is illustrated with reference to simple alternative models of variation in MZ and DZ twins reared together. Simulation of twin experiments finds the empirical power in good agreement with that predicted by the method. Tables are produced showing the sample sizes required for 95 per cent rejection at the 5 per cent level of inappropriate models of variation. For equivalent cases it is always found easier to reject an inappropriate simple genetical model of variation than an inappropriate simple environmental model. For several frequently encountered cases, more than 600 pairs of twins would be required to reject inappropriate alternative models. The optimum proportion of MZ and DZ twins in a sample will vary with the "true" model of variation but is most likely to be between two-thirds and one-half of DZ twin pairs.The possibility of detecting genetical non-additivity with the classical twin study is investigated by theoretical power calculations and simulation. In the absence of genotype-environment interactions, distributional skewness and mean-variance regression in DZ twins are found to be more powerful tests of directional dominance (or unequal gene frequencies) than the standard model fitting procedure and these tests may be worthwhile in future studies.

QTL Express is the first application for Quantitative Trait Locus (QTL) mapping in outbred populations with a web-based user interface. User input of three files containing a marker map, trait data and marker genotypes allows mapping of single or multiple QTL by the regression approach, with the option to perform permutation or bootstrap tests.

We have briefly reviewed the methods currently available for QTL analysis in segregating populations and summarized some of the conclusions arising from such analyses in plant populations. We show that the analytical methods locate QTL with poor precision (10-30 cM), unless the heritability of an individual QTL is high. Also the estimates of the QTL effects, particularly the dominance effects tend to be inflated because only large estimates are significant. Estimates of numbers of QTL per trait are generally low (8) for individual trials. This may suggest that there are few QTL but probably reflects the power of the methods. There is no large correlation between the numbers of QTL found and the amount of the variation explained. Of those cases where dominance is measurable, dominance ratios are often 1, but seldom significantly greater. These latter cases need further analysis. Many QTL map close to candidate genes, and there is growing evidence from synteny studies of corresponding chromosome regions carrying similar QTL in different species. However, unreliability of QTL location may suggest false candidates.

Although commonplace in human disease genetics, genome-wide association (GWA) studies have only relatively recently been applied to plants. Using 32 phenotypes in the inbreeding crop barley, we report GWA mapping of 15 morphological traits across ∼500 cultivars genotyped with 1,536 SNPs. In contrast to the majority of human GWA studies, we observe high levels of linkage disequilibrium within and between chromosomes. Despite this, GWA analysis readily detected common alleles of high penetrance. To investigate the potential of combining GWA mapping with comparative analysis to resolve traits to candidate polymorphism level in unsequenced genomes, we fine-mapped a selected phenotype (anthocyanin pigmentation) within a 140-kb interval containing three genes. Of these, resequencing the putative anthocyanin pathway gene HvbHLH1 identified a deletion resulting in a premature stop codon upstream of the basic helix-loop-helix domain, which was diagnostic for lack of anthocyanin in our association and biparental mapping populations. The methodology described here is transferable to species with limited genomic resources, providing a paradigm for reducing the threshold of map-based cloning in unsequenced crops.genetic variation | small grain cereals | colinearity

No abstract

SummaryTranscript abundance from cRNA hybridizations to Affymetrix microarrays can be used for simultaneous marker development and genome-wide gene expression quantitative trait locus (eQTL) analysis of crops. We have previously shown that it is easily possible to use Affymetrix expression arrays to profile individuals from a segregating population to accurately identify robust polymorphic molecular genetic markers. We applied the method to identify more than 2000 genetic polymorphisms (transcript derived markers, TDMs) from an experiment involving two commercial varieties of barley (Hordeum vulgare; Steptoe and Morex) and their doubled-haploid progeny. With this set of TDMs, we constructed a genetic map and used it for the genomewide eQTL analysis of about 16 000 genes in a relatively large population (n = 139). We identified 23 738 significant eQTLs at a genome-wide significance (P £ 0.05), affecting the expression of 12 987 genes. Over a third of these genes with expression variation have only one identified eQTL while the rest have two to six. A large proportion of the quantitatively controlled transcripts appear to be regulated by both cis and trans effects. More than half of the quantitatively controlled transcripts appear to be primarily regulated by cis eQTLs in this population. We show that although there appear to be eQTL hotspots many of these are in chromosomal regions of low recombination, such as genetic centromeres, and so have a high gene density per centimorgan. Some chromosomal regions have a significant excess of eQTL over the number expected from gene density, and many of these are biased towards eQTL for which the allele from one particular parent increases the expression level.

No abstract