A few occurrences of miniature inverted-repeat transposable elements (MITEs) have been reported in species of the genus Drosophila. Here, we describe msechBari, a MITE-like element in Drosophila sechellia. The element is short, approximately 90 bp in length, AT-rich and occurs in association with, or close to, genes, characteristics that are typical for MITEs. The identification was performed in silico using the sequenced genome of D. sechellia and confirmed in a laboratory strain. This short element is related to the Bari_DM transposon of Drosophila melanogaster, having terminal inverted repeats (TIRs) of a similar length and a high identity with the full-length Bari_DM element. The estimated recent origin of the element and the homogeneity observed between copies found in the genome suggests that msechBari could be active in D. sechellia.

Allelic expression of the rice yield-related gene, leucine-rich receptor-like kinase 6 (LRK6), in the hybrid of 93-11 (Oryza sativa L. subsp. Indica var. 93-11) and Nipponbare (O. sativa L. subsp. Japonica var. Nipponbare) is determined by allelic promoter cis-elements. Using deletion analysis of the LRK6 promoter, we identified two distinct regions that might contribute to LRK6 expression. Sequence alignment revealed differences in these LRK6 promoter regions in 93-11 and Nipponbare. One of the segments, named differential sequence of LRK6 promoter 2 (DSLP2), contains potential transcription factor binding sites. Using a yeast one-hybrid assay, we isolated an ethylene-responsive factor (ERF) protein that binds to DSLP2. Sequence analysis and a GCC-box assay showed that the ERF gene, O. sativa ERF 3 (OsERF3), which belongs to ERF subfamily class II, has a conserved ERF domain and an ERF-associated amphiphilic repression repressor motif. We used an in vivo mutation assay to identify a new motif (5′-TAA(A)GT-3′) located in DSLP2, which interacts with OsERF3. These results suggest that OsERF3, an AP2 (APETALA 2 Gene)/ERF transcription factor, binds the LRK6 promoter at this new motif, which might cause differential expression of LRK6 in the 93-11/Nipponbare hybrid.

The copia element is a retrotransposon that is hypothesized to have been horizontally transferred from Drosophila melanogaster to some populations of Drosophila willistoni in Florida. Here we have used PCR and Southern blots to screen for sequences similar to copia element in South American populations of D. willistoni, as well as in strains previously shown to be carriers of the element. We have not found the canonical copia element in any of these populations. Unlike the P element, which invaded the D. melanogaster genome from D. willistoni and quickly spread worldwide, the canonical copia element appears to have transferred in the opposite direction and has not spread. This may be explained by differences in the requirements for transposition and in the host control of transposition.

To identify genetic loci that regulate spontaneous arthritis in interleukin-1 receptor antagonist (IL-1ra)-deficient mice, an F2 population was created from a cross between Balb/c IL-1ra-deficient mice and DBA/1 IL-1ra-deficient mice. Spontaneous arthritis in the F2 population was examined and recorded. Genotypes of those F2 mice were determined using microsatellite markers. Quantitative trail locus (QTL) analysis was conducted with R/qtlbim. Functions of genes within QTL chromosomal regions were evaluated using a bioinformatics tool, PGMapper, and microarray analysis. Potential candidate genes were further evaluated using GeneNetwork. A total of 137 microsatellite markers with an average of 12 cM spacing along the whole genome were used for determining the correlation of arthritis phenotypes with genotypes of 191 F2 progenies. By whole-genome mapping, we obtained QTLs on chromosomes 1 and 6 that were above the significance threshold for strong Bayesian evidence. The QTL on chromosome 1 had a peak near D1Mit55 and D1Mit425 at 82·6 cM. It may account for as much as 12% of the phenotypic variation in susceptibility to spontaneous arthritis. The QTL region contained 208 known transcripts. According to their functions, Mr1, Pla2g4a and Fasl are outstanding candidate genes. From microarray analysis, 11 genes were selected as favourable candidates based on their function and expression profiles. Three of those 11 genes, Prg4, Ptgs2 and Mr1, correlated with the IL-1ra pathway. Those genes were considered to be the best candidates.

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.

Ancestral polymorphisms are defined as variants that arose by mutation prior to the speciation event that generated the species in which they segregate. Their presence may complicate the interpretation of molecular data and lead to incorrect phylogenetic inferences. They may also be used to identify regions of the genome that are under balancing selection. It is thus important to take into account the contribution of ancestral polymorphisms to variability within species and divergence between species. Here, we extend and improve a method for estimation of the proportion of ancestral polymorphisms within a species, and apply it to a dataset of 33 X-linked and 34 autosomal protein-coding genes for which sequence polymorphism data are available in both Drosophila pseudoobscura and Drosophila miranda, using Drosophila affinis as an outgroup. We show that a substantial proportion of both X-linked and autosomal synonymous variants in these two species are ancestral, and that a small number of additional genes with unusually high sequence diversity seem to have an excess of ancestral polymorphisms, suggestive of balancing selection.

The rate of insertion of transposable elements (TEs) is a fundamental parameter to understand both their dynamics and role in the evolution of the eukaryotic genome. Nonetheless, direct estimates of insertion rates are scarce because transposition is in general a rare phenomenon. A great deal of our previous work on transposition was based on a set of long-term mutation accumulation (MA) lines of Drosophila melanogaster started in 1987 (Oviedo lines), where roo was found highly active, with a rate of insertion of 7×10−4 insertions per element and generation, as compared with other 15 TE families that presented transposition rates around 10−5. Here, we study the evolution of the roo transposition rate, by in situ hybridization, after 60–75 additional generations of MA in two subsets of the Oviedo lines, O and O′, which had achieved average numbers of roo insertions of 77 and 84, respectively. In the O lines, insertions accumulated at a rate that remained constant (7×10−4 insertions per element and generation); however, the subset of lines O′ showed a lower accumulation rate of 4×10−4 insertions per element per generation, suggesting a regulation of transposition that depends on the number of elements. However, one of the O′ lines reached a number of 103 insertions, departing from the group mean by 4·6 sd, and showing that it escapes regulation. Hence, ‘de novo’ mutations affecting the regulation of transposition are relatively common. These results are discussed in relation to the possible mechanisms of containment of TEs.

We measure genetic variation in lifespan and fecundity at two food levels in 34 core lines of the Drosophila Genetic Reference Panel collection. Lines were significantly different from each other in lifespan and fecundity at both restricted and full food. There was a strong food-by-line interaction for the slope of age-specific mortality, fecundity and proportion of fertilized eggs, indicating the presence of genetic variation for the strength of the dietary restriction effect, likely to represent standing genetic variation in a natural population from which the lines used have originated. No trade-off between fecundity and lifespan manifested in life-history variation among inbred lines. Our data partially corroborate the recent proposition that availability of nutrient-free water eliminates the apparent dietary restriction at least in some conditions. Although flies on full food with water added had lifespan slightly higher than those without a water source, it was still significantly lower than that in flies on restricted food, with no indication of interaction. We fully corroborate the recently discovered effect of addition of essential amino acids to the medium: addition of 1·5 mM methionine to restricted food significantly increased fecundity without a measurable decrease in lifespan; addition of each of 10 essential amino acids increased fecundity and decreased females lifespan to the levels observed on full food, again with no evidence of line-by-food interactions. We propose a mechanistic hypothesis explaining the observed data, based on the assumption that food consumption by flies is adjusted according to flies’ saturation in water and methionine.

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.

In order to estimate the effective population size (Ne) of the current human population, two new approaches, which were derived from previous methods, were used in this study. One is based on the deviation from linkage equilibrium (LE) between completely unlinked loci in different chromosomes and another is based on the deviation from the Hardy–Weinberg Equilibrium (HWE). When random mating in a population is assumed, genetic drifts in population naturally induce linkage disequilibrium (LD) between chromosomes and the deviation from HWE. The latter provides information on the Ne of the current population, and the former provides the same when the Ne is constant. If Ne fluctuates, recent Ne changes are reflected in the estimates based on LE, and the comparison between two estimates can provide information regarding recent changes of Ne. Using HapMap Phase III data, the estimates were varied from 622 to 10 437, depending on populations and estimates. The Ne appeared to fluctuate as it provided different estimates for each of the two methods. These Ne estimates were found to agree approximately with the overall increment observed in recent human populations.

Predicting functional gene annotations remains a significant challenge, even in well-annotated genomes such as yeast and Drosophila. One promising, high-throughput method for gene annotation is to use correlated gene expression patterns to annotate target genes based on the known function of focal genes. The Drosophila melanogaster transcriptome varies genetically among wild-derived inbred lines, with strong genetic correlations among the transcripts. Here, we leveraged the genetic correlations in gene expression among known seminal fluid protein (SFP) genes and the rest of the genetically varying transcriptome to identify 176 novel candidate SFPs (cSFPs). We independently validated the correlation in gene expression between seven of the cSFPs and a known SFP gene, as well as expression in male reproductive tissues. We argue that this method can be extended to other systems for which information on genetic variation in gene expression is available.

Dealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation–Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

Bayesian regularization of artificial neural networks (BRANNs) were used to predict body mass index (BMI) in mice using single nucleotide polymorphism (SNP) markers. Data from 1896 animals with both phenotypic and genotypic (12 320 loci) information were used for the analysis. Missing genotypes were imputed based on estimated allelic frequencies, with no attempt to reconstruct haplotypes based on family information or linkage disequilibrium between markers. A feed-forward multilayer perceptron network consisting of a single output layer and one hidden layer was used. Training of the neural network was done using the Bayesian regularized backpropagation algorithm. When the number of neurons in the hidden layer was increased, the number of effective parameters, γ, increased up to a point and stabilized thereafter. A model with five neurons in the hidden layer produced a value of γ that saturated the data. In terms of predictive ability, a network with five neurons in the hidden layer attained the smallest error and highest correlation in the test data although differences among networks were negligible. Using inherent weight information of BRANN with different number of neurons in the hidden layer, it was observed that 17 SNPs had a larger impact on the network, indicating their possible relevance in prediction of BMI. It is concluded that BRANN may be at least as useful as other methods for high-dimensional genome-enabled prediction, with the advantage of its potential ability of capturing non-linear relationships, which may be useful in the study of quantitative traits under complex gene action.

DNA topoisomerases are specialized nuclear enzymes that perform topological modifications on double-stranded DNA (dsDNA) and hence are essential for DNA metabolism such as replication, transcription, recombination, condensation and segregation. In a genetic screen, we identified a temperature-sensitive mutant allele of topoisomerase 2 that exhibits conditional synthetic lethality with a chk1 knockout strain. The mutant allele of topoisomerase 2 is defective in chromosome segregation at a non-permissive temperature and there was increase in chromosome segregation defects in the double mutant of top2–10 and chk1 delete at a non-permissive temperature. More importantly, topoisomearse 2 mutant cells mildly delay the mitotic progression at non-permissive temperature that is mediated by checkpoint protein kinase Chk1. Additionally, top2–10 mutant cells also activate the Chk1 at a non-permissive temperature and this activation of Chk1 takes place at the time of mitosis. Interestingly, top2–10 mutant cells retain their viability at a non-permissive temperature if the cells are not allowed to enter into mitosis. Taking together our results, we speculate that in the top2–10 mutant, the segregation of entangled chromatids during mitosis could result in delaying the mitotic progression through the activation of Chk1 kinase.

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.

The fast multipoint maximum likelihood mapping algorithm for crosses between inbred lines, introduced by Jansen et al. (2001),is extended for mapping in a full-sib family of an outbreeding species. The method accommodates different segregation types of markers and differences in recombination between parents. The two separate parental multipoint maximum likelihood maps are joined into an integrated map by averaging lengths over anchored segments and by interpolating or extrapolating for markers segregating in one parent only. The method is illustrated with simulated data. The method will enable a more accurate estimation of maps in outbreeding species than current methods.

Quantitative trait is always controlled by multiple latent genetic loci, and genetic markers have been used to map quantitative trait loci (QTLs) auxiliarily. The method of multiple interval mapping (MIM) provides an appropriate way for mapping QTL using genetic makers. However, the computation in the MIM seems infeasible for a large number of marker intervals. Nowadays, the Dantzig selector (DS) method proves to be a more efficient method to estimate model effects in a linear model when the number of parameters is (much) larger than the sample size, which has not been applied to genetic mapping for QTL. In this paper, we developed a two-step method for mapping QTL based on the MIM, and we also illustrate the feasibility of adopting the DS to estimate marker or QTL effects. Simulation results showed that the proposed method performed satisfactorily well by comparisons with the existing MIM method, and the analysis to real data set also tested the practicability and efficiency of the DS method in genetic mapping.

The cultivar Ajaya (IET 8585) exhibits durable broad-spectrum resistance to bacterial blight (BB) disease of rice and is widely used as a resistance donor. The present study was carried out to decipher the genetics of BB resistance in Ajaya and map the gene(s) conferring resistance. Genetic analysis in the F2 indicated a quantitative/additive nature of resistance governed by two loci with equal effects. Linked marker analysis and allelic tests revealed that one of the resistance genes is xa5. Sequence analysis of a 244 bp region of the second exon of the gene-encoding Transcription factor IIAγ (the candidate gene for xa5) confirmed the presence of xa5. Bulked-segregant analysis (BSA) revealed the putative location of the two quantitative trait loci (QTLs)/genes associated with resistance on chromosomes 5 and 8. Composite interval mapping located the first locus on Chr. 5S exactly in the genomic region spanned by xa5 and the second locus (qtl BBR 8.1) on Chr. 8L. Owing to its differential disease reaction with a set of seven hyper-virulent isolates of Xanthomonas oryzae, a map location on Chr. 8L, which was distinct from xa13 and data from allelism tests, the second resistance locus in Ajaya was determined to be novel and was designated as xaAj. A contig map spanning xaAj was constructed in silico and the genomic region was delimited to a 13·5 kb physical interval. In silico analysis of the genomic region spanning xaAj identified four putatively expressed candidate genes, one of which could be involved in imparting BB resistance in Ajaya along with xa5.

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.

Vast amount of genetic marker information is being used to obtain insight into the genetic architecture of complex traits, for locating genomic regions (quantitative trait loci (QTL)) affecting disease and for enhancing the accuracy of prediction of genetic values in selection programmes. The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm is proposed.