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I investigated inter-individual variation at the cell and molecular level in relation to reproductive phenotype (egg and clutch size, timing of laying) in female zebra finches (Taeniopygia guttata). First, I developed an antibody against zebra finch apoVLDL-II. I then developed a dot-blot assay to quantify plasma apoVLDL-II levels. This revealed marked inter-individual variation in apoVLDL-II levels but this was not correlated with differences in reproductive phenotype. Second, I described variation in VTG/VLDL receptor mRNA expression in relation to variation in reproductive phenotype. VTG/VLDL-R mRNA was expressed at high levels in growing oocytes and skeletal muscle and was also detectable in liver, but these tissues contain different splice variants. VTG/VLDL-R mRNA expression decreased during follicle growth. Ovary mRNA expression was correlated with clutch size and laying interval. F3 follicle mRNA expression was correlated with egg size. Thus, VTG/VLDL receptor mRNA expression is a key determinant of inter-individual variation in reproductive phenotype.

Background Pain intensities of patients are repeatedly measured by Visual Analog Scale (VAS) and Pain Vision (PV) in a clinical research. Two measurements by VAS and PV are performed at the same time. In order to evaluate within patient consistency, intra-individual coefficient of variations (CVs) are compared between measures assuming that the pain status of each patient is stable during the research period. The correlated samples and different inter-individual variation due to different scales of the measures should be taken into account in statistical analysis. The adjustment of covariates will improve the estimation of population mean values of the measures. Methods In this paper, statistical approach to compare the intra-individual CVs is proposed. The approach consists of two steps: (1) estimating population mean values and intra-individual variances of the pain intensities by measure in a mixed effect model framework, (2) computing intra-individual CVs and comparing them between measures. The mixed effect model includes measure and some variables as fixed effects and subject by measure as a random effect. The different inter-individual variations between measures and their covariance reflect the paired sampling in the variance component. The confidence interval of the difference of intra-individual CVs is constructed using the asymptotic normality and the delta method. Bootstrap method is available if sample size is small. Results The proposed approach is illustrated using pain research data. Measure (VAS and PV), age and sex are included in the model as fixed effects. The confidence intervals of the difference of intra-individual CVs between measures are estimated by the asymptotic theory and by bootstrap using a subgroup resampling, respectively. Both confidence intervals are similar. Conclusion The proposed approach is useful to compare two intra-individual CVs taking it into account to reflect the paired sampling, different inter-individual variations between measures and some covariates. Although the inclusion of covariates did not improve the goodness-of-fit in the illustration, the proposed model with covariates will improve the accuracy and/or precision if covariates truly influence response variable. This approach can be applicable with small modification to various situations. Electronic supplementary material The online version of this article (doi:10.1186/s13104-016-1912-y) contains supplementary material, which is available to authorized users.

The potential influence of microplastic debris on marine organisms is an issue of great ecological and socioeconomic concern. Experiments exposing fishes and invertebrates to constant concentrations of microplastics often yield high variation in particle ingestion rates among individuals. Yet, despite an increasing interest in microplastic ingestion in the wild, the potential intrinsic drivers of inter-individual variation have received little attention so far. Here we assessed individual-level ingestion of Polyethylene microspheres by laboratory-reared juvenile anemonefish, Amphiprion ocellaris, in relation to (a) ambient particle concentrations and (b) repeatable behavioural traits. We show that microplastic ingestion is highly variable at all tested particle concentrations and that this variation can partially be explained by individual activity levels. Moreover, the relationship between ingestion and behavioural variation increased notably when only the most behaviourally consistent individuals (n = 40 out of 60) were considered in the analysis. Our findings indicate that microplastic ingestion rates in juvenile reef fishes may be less dependent on ambient concentrations than expected; instead they are to some degree phenotype-dependent. Care should thus be taken when reporting mean responses to microplastic exposure treatments, because some individuals may not be affected in the same way as others due to differential ingestion behaviour. We also discuss potential ramifications of non-random ingestion variability on population- and community-level responses.

Background Individual genotypes at specific loci can result in different patterns of DNA methylation. These methylation quantitative trait loci (meQTLs) influence methylation across extended genomic regions and may underlie direct SNP associations or gene-environment interactions. We hypothesized that the detection of meQTLs varies with ancestral population, developmental stage, and tissue type. We explored this by analyzing seven datasets that varied by ancestry (African American vs. Caucasian), developmental stage (neonate vs. adult), and tissue type (blood vs. four regions of postmortem brain) with genome-wide DNA methylation and SNP data. We tested for meQTLs by constructing linear regression models of methylation levels at each CpG site on SNP genotypes within 50 kb under an additive model controlling for multiple tests. Results Most meQTLs mapped to intronic regions, although a limited number appeared to occur in synonymous or nonsynonymous coding SNPs. We saw significant overlap of meQTLs between ancestral groups, developmental stages, and tissue types, with the highest rates of overlap within the four brain regions. Compared with a random group of SNPs with comparable frequencies, meQTLs were more likely to be 1) represented among the most associated SNPs in the WTCCC bipolar disorder results and 2) located in microRNA binding sites. Conclusions These data give us insight into how SNPs impact gene regulation and support the notion that peripheral blood may be a reliable correlate of physiological processes in other tissues.