Deng et al. have recently proposed that estimates of an upper limit to the rate of spontaneous mutations and their average heterozygous effect can be obtained from the mean and variance of a given fitness trait in naturally segregating populations, provided that allele frequencies are maintained at the balance between mutation and selection. Using simulations they show that this estimation method generally has little bias and is very robust to violations of the mutation–selection balance assumption. Here I show that the particular parameters and models used in these simulations generally reduce the amount of bias that can occur with this estimation method. In particular, the assumption of a large mutation rate in the simulations always implies a low bias of estimates. In addition, the specific model of overdominance used to check the violation of the mutation–selection balance assumption is such that there is not a dramatic decline in mean fitness from overdominant mutations, again implying a low bias of estimates. The assumption of lower mutation rates and/or other models of balancing selection may imply considerably larger biases of the estimates, making the reliability of the proposed method highly questionable.

This study is aimed at improving the analysis of data used in identifying marker-associated effects on quantitative traits, specifically to account for possible departures from a Gaussian distribution of the trait data and to allow for asymmetry of marker effects attributable to phenotypic divergence between parental lines. A Bayesian procedure for analysing marker effects at the whole-genome level is presented. The procedure adopts a skewed t-distribution as a prior distribution of marker effects. The model with the skewed t-process includes Gaussian prior distributions, skewed Gaussian prior distributions and symmetric t-distributions as special cases. A Markov Chain Monte Carlo algorithm for obtaining marginal posterior distributions of the unknowns is also presented. The method was applied to a dataset on three traits (live weight, carcass length and backfat depth) measured in an F2 cross between Iberian and Landrace pigs. The distribution of marker effects was clearly asymmetric for carcass length and backfat depth, whereas it was symmetric for live weight. The t-distribution seems more appropriate for describing the distribution of marker effects on backfat depth.

The loop design of Kerr and Churchill is a clever application of incomplete blocks of size 2 to two-channel microarray experiments. In this paper, we extend the loop design to include more replicates, biological and technical replication, multi-factor experiments, and blocking. Loop and extended loop designs are shown to be more efficient than the reference design for any given number of arrays. We also show that adding new treatments to a loop design requires the same number of additional arrays as adding treatments to a reference design, with a greater gain in power. Given the flexibility of extended loop designs and their power, we propose that these should be the designs of choice for most experiments using two-channel microarrays.

Agrostis species are mainly used in athletic fields and golf courses. Their integrity is maintained by fungicides, which makes the development of disease-resistance varieties a high priority. However, there is a lack of knowledge about resistance (R) genes and their use for genetic improvement in Agrostis species. The objective of this study was to identify and clone constitutively expressed cDNAs encoding R gene-like (RGL) sequences from three Agrostis species (colonial bentgrass (A. capillaris L.), creeping bentgrass (A. stolonifera L.) and velvet bentgrass (A. canina L.)) by PCR-based motif-directed RNA fingerprinting towards relatively conserved nucleotide binding site (NBS) domains. Sixty-one constitutively expressed cDNA sequences were identified and characterized. Sequence analysis of ESTs and probable translation products revealed that RGLs are highly conserved among these three Agrostis species. Fifteen of them were shown to share conserved motifs found in other plant disease resistance genes such as MLA13, Xa1, YR6, YR23 and RPP5. The molecular evolutionary forces, analysed using the Ka/Ks ratio, reflected purifying selection both on NBS and leucine-rich repeat (LRR) intervening regions of discovered RGL sequences in these species. This study presents, for the first time, isolation and characterization of constitutively expressed RGL sequences from Agrostis species revealing the presence of TNL (TIR-NBS-LRR) type R genes in monocot plants. The characterized RGLs will further enhance knowledge on the molecular evolution of the R gene family in grasses.

Indirect estimates of the genomic rate of deleterious mutations (λ), their average homozygous effect (s) and their degree of dominance (h) can be obtained from genetic parameters of natural populations, assuming that the frequencies of the loci controlling a given fitness trait are at mutation–selection equilibrium. In 1996, H.-W. Deng and M. Lynch developed a general methodology for obtaining these estimates from inbreeding/outbreeding experiments. The prediction of the sign and magnitude of the biases incurred by these estimators is essential for a correct interpretation of the empirical results. However, the assessment of these biases has been tested so far under a rather limited model of the distribution of dominance effects. In this paper, the application of this method to outbred populations is evaluated, focusing on the level of variation in h values (σh2) and the magnitude of the negative correlation (rs,h) between s and h. It is shown that the method produces upwardly biased estimates of λ and downwardly biased estimates of the average s in the reference situation where rs,h=0, particularly for large values of σh2, and biases of different sign depending on the magnitude of the correlation. A modification of the method, substituting the estimates of the average h for alternative ones, allows estimates to be obtained with little or no bias for the case of rs,h=0, but is otherwise biased. Information on rs,h and σh2, gathered from mutation-accumulation experiments, suggests that σh2 may be rather large and rs,h is usually negative but not higher than about −0·2, although the data are scarce and noisy, and should be used with caution.