The Role of Epigenomics in Aquatic Toxicology.

Over the past decade, the field of molecular biology has rapidly incorporated epigenetic studies to evaluate organism-environment interactions that can result in chronic effects. Such responses arise from early life stage stress, the utilization of genetic information over an individuals life time, and transgenerational inheritance. Knowledge of epigenetic mechanisms provides the potential for a comprehensive evaluation of multigenerational and heritable effects from environmental stressors, such as contaminants. Focused studies have provided a greater understanding of how many responses to environmental stressors are driven by epigenetic modifiers. We discuss the promise of epigenetics and suggest future research directions within the field of aquatic toxicology, with a particular focus on the potential for identifying key heritable marks with consequential impacts at the organism and population levels. Environ Toxicol Chem 2017;36:2565-2573. © 2017 SETAC

Natural Variation in Fish Transcriptomes: Comparative Analysis of the Fathead Minnow (Pimephales promelas) and Zebrafish (Danio rerio).

Fathead minnow and zebrafish are among the most intensively studied fish species in environmental toxicogenomics. To aid the assessment and interpretation of subtle transcriptomic effects from treatment conditions of interest, better characterization and understanding are needed for natural variation in gene expression among fish individuals from lab cultures. Leveraging the transcriptomics data from a number of our toxicogenomics studies conducted over the years, we conducted a meta-analysis of nearly 600 microarrays generated from the ovary tissue of untreated, reproductively mature fathead minnow and zebrafish samples. As expected, there was considerable batch-to-batch transcriptomic variation; this batch-effect appeared to differentially impact subsets of fish transcriptomes in a nonsystematic way. Temporally more closely spaced batches tended to share a greater transcriptomic similarity among one another. The overall level of within-batch variation was quite low in fish ovary tissue, making it a suitable system for studying chemical stressors with subtle biological effects. The observed differences in the within-batch variability of gene expression, at the levels of both individual genes and pathways, were probably both technical and biological. This suggests that biological interpretation and prioritization of genes and pathways targeted by experimental conditions should take into account both their intrinsic variability and the size of induced transcriptional changes. There was significant conservation of both the genomes and transcriptomes between fathead minnow and zebrafish. The high degree of conservation offers promising opportunities in not only studying fish molecular responses to environmental stressors by a comparative biology approach, but also effective sharing of a large amount of existing public transcriptomics data for developing toxicogenomics applications

Analysis of life insurance market in Czech republic

In this bachelor's thesis I analyze life insurance market in the Czech Republic, which will be examined from several points of view. In the beggining I focus on historical development of Czech insurance market, which was very specific and led to the shape of the market as we know it nowadays. This is followed by analysis of individual life insurance products, that are available. In the main part of the thesis I focus on the analysis of the insurance market itself through chosen indicators, that make it possible to better understand actual trends on Czech insurance market. In this part of my thesis I also compare Czech insurance market to the insurance markets in European Union. In the end of my thesis I analyze prices of individual life insurance products in chosen insurance companies operating on the Czech insurance market

Additional file 3: Figure S1. of Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles

Relative transcriptomic impact of various treatment conditions in fathead minnow. Effects are measured by the percentages of transcriptome determined to be DEGs. (PPTX 39 kb

Intraspecific correlation between the average CV and average intensity by KEGG pathways.

<p>A total of 136 pathways (eight outliers excluded) were included for fathead minnow (A) and 144 pathways for zebrafish (B). The CCs were −0.68 and −0.70 respectively, with both p-values = 0. The p-values of normality test of error distribution for linear regressions were 0.094 (no significant departure from normality) and 0 (significant non-normality) respectively.</p

Interspecific correlation by average intensity and average coefficient of variation of individual pathways.

<p>A total of 84 (three outliers excluded) KEGG pathways were calculated for their average intensities (A), and 53 (two outliers excluded) pathways for their average CVs (B), based on a combined total of 6617 orthologous genes. To be included, each pathway must have at least five orthologs and a p-value of ≤0.1 for the correlation of the intensities or CVs of its member genes as estimated within a batch. The CCs were 0.86 and 0.80 for the average intensity and average CV by pathway respectively, with the both p-values = 0. The p-values of normality test of error distribution for linear regressions were 0.045 and 0.585 respectively.</p

Within-batch variation as measured by coefficient of variation (CV).

<p>The CVs were calculated for each probe by individual batches under the Experiment factor and averaged over all batches. Further averaging these CVs across the entire transcriptome yielded an overall CV of 0.056 for fathead minnow (PPR) and 0.051 for zebrafish (DRE). The total number of orthologous genes identified between Agilent 015064 and 019597 was 6617, represented by 9311 and 6950 unique probes respectively. The PPR probes mapped to their EST sequences and ESTs to NCBI databases by BLAST all had a minimum E-value of E-06.</p><p>Within-batch variation as measured by coefficient of variation (CV).</p

Interspecific correlation by within-batch intensity and coefficient of variation of orthologs.

<p>The within-batch intensities (A) and coefficients of variation (CV; B) were based on 6617 orthologous genes. The orthologs were represented by 9311 zebrafish (DRE) and 6950 fathead minnow (PPR) probes. The intensity and CV of an ortholog with duplicated probes were probe means. The correlation coefficients over the orthologs for the two metrics were 0.49 and 0.33 respectively, with the both p-values = 0.</p