The lucerne flea, Sminthurus viridis (Collembola: Sminthuridae) (L.) is a major pest of broadacre agriculture across southern Australia. Few molecular studies have been conducted on S. viridis and none have examined its population genetics, despite the importance for developing effective control strategies. Here, we characterize the genetic structure of Australian populations using three allozyme and eight microsatellite loci, as well as sequencing a fragment of the mitochondrial DNA cytochrome oxidase I gene. We found that S. viridis in Australia are diploid, sexually reproducing and exhibit significant population structure as a result of limited gene flow. Despite significant differentiation between populations, there was very low cytochrome oxidase subunit I (COI) gene sequence variation, indicating the presence of a single species in Australia. The observed structure only marginally complied with an ‘isolation by distance’ model with human-mediated long-distance dispersal likely occurring. Allozymes and microsatellites gave very similar FST estimates, although differences found for novel alternative estimates of differentiation suggest that the allozymes did not capture the full extent of the population structure. These results highlight that control strategies may need to vary for locally adapted S. viridis populations and strategies aimed at limiting the spread of any future pesticide resistance will need to manage the effects of human-mediated dispersal.

Tol2 is a member of the hAT (hobo/Activator/Tam3) transposable element family, residing as 10–30 copies per diploid genome in the medaka fish. We previously reported that this element is highly homogeneous in structure at both the restriction map level and the nucleotide sequence level. It was, however, possible that there is variation of such a low frequency as not to have been detected in our previous surveys, in which samples from 12 geographical locations were used. In the present study, we first conducted searches of genome sequence databases of medaka, and found a 119-bp-long internal deletion. We then conducted a survey of samples from 58 locations for this deletion by performing PCR preceded by restriction enzyme digestion to increase the sensitivity to this deletion. We found that copies suffering this deletion have spread, or have been generated by multiple origins, in the northern-to-central part of mainland Japan. Thus, although the high homogeneity in structure is a distinct feature of Tol2, variation does exist at low frequencies in natural populations of medaka. The current status of Tol2 is expected to provide information with which results of future surveys can be compared for clarification of determinants of population dynamics of this DNA-based element.

The pattern of the correlation of non-allele descents among linked sites is an important aspect for an insight into the genomic evolution at the population level. Here, we present a new statistical method for estimating two types of non-allele descent correlations. One is the standardized parental descent disequilibrium termed by Cockerham & Weir (1973),the other is the standardized disequilibrium between non-allele descent segments from the same chromosome. Essential to this analysis is the partitioning of the joint identity-by-state probability for a random pair of non-allele gametes into the different components of identity by descents at the two or three sites. We consider the samples of phased haplotypes of single nucleotide polymorphism (SNP) markers and the weighted least square method for fast parameter estimation. Monte Carlo simulations demonstrate that robustly unbiased estimates with appropriate precisions can be obtained with certain sample sizes, ~100 diploids, under the impacts of allele frequency distributions and linkage disequilibrium. This method can be used to construct the maps of non-allele descent correlation blocks for the population whose genetic pedigree is not required on a prior basis.

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box–Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box–Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

Although the expected relationship or proportion of genome shared by pairs of relatives can be obtained from their pedigrees, the actual quantities deviate as a consequence of Mendelian sampling and depend on the number of chromosomes and map length. Formulae have been published previously for the variance of actual relationship for a number of specific types of relatives but no general formula for non-inbred individuals is available. We provide here a unified framework that enables the variances for distant relatives to be easily computed, showing, for example, how the variance of sharing for great grandparent–great grandchild, great uncle–great nephew, half uncle–nephew and first cousins differ, even though they have the same expected relationship. Results are extended in order to include differences in map length between sexes, no recombination in males and sex linkage. We derive the magnitude of skew in the proportion shared, showing the skew becomes increasingly large the more distant the relationship. The results obtained for variation in actual relationship apply directly to the variation in actual inbreeding as both are functions of genomic coancestry, and we show how to partition the variation in actual inbreeding between and within families. Although the variance of actual relationship falls as individuals become more distant, its coefficient of variation rises, and so, exacerbated by the skewness, it becomes increasingly difficult to distinguish different pedigree relationships from the actual fraction of the genome shared.

MADS-box genes encode transcription factors that are key regulators of plant inflorescence and flower development. We examined DNA sequence variation in 32 maize MADS-box genes and 32 randomly chosen maize loci and investigated their involvement in maize domestication and improvement. Using neutrality tests and a test based on coalescent simulation of a bottleneck model, we identified eight MADS-box genes as putative targets of the artificial selection associated with domestication. According to neutrality tests, one additional MADS-box gene appears to have been under selection during modern agricultural improvement of maize. For random loci, two genes were indicated as targets of selection during domestication and four additional genes were indicated to be candidate-selected loci for maize improvement. These results suggest that MADS-box genes were more frequent targets of selection during domestication than genes chosen at random from the genome.

Empirical experience with genomic selection in dairy cattle suggests that the distribution of the effects of single nucleotide polymorphisms (SNPs) might be far from normality for some traits. An alternative, avoiding the use of arbitrary prior information, is the Bayesian Lasso (BL). Regular BL uses a common variance parameter for residual and SNP effects (BL1Var). We propose here a BL with different residual and SNP effect variances (BL2Var), equivalent to the original Lasso formulation. The λ parameter in Lasso is related to genetic variation in the population. We also suggest precomputing individual variances of SNP effects by BL2Var, to be later used in a linear mixed model (HetVar-GBLUP). Models were tested in a cross-validation design including 1756 Holstein and 678 Montbéliarde French bulls, with 1216 and 451 bulls used as training data; 51 325 and 49 625 polymorphic SNP were used. Milk production traits were tested. Other methods tested included linear mixed models using variances inferred from pedigree estimates or integrated out from the data. Estimates of genetic variation in the population were close to pedigree estimates in BL2Var but not in BL1Var. BL1Var shrank breeding values too little because of the common variance. BL2Var was the most accurate method for prediction and accommodated well major genes, in particular for fat percentage. BL1Var was the least accurate. HetVar-GBLUP was almost as accurate as BL2Var and allows for simple computations and extensions.