Biological network analysis is a powerful approach to gain systems-level understanding of patterns of gene expression in different cell types, disease states and other biological/experimental conditions. Three consecutive steps are required - identification of genes or proteins of interest, network construction and network analysis and visualization. To date, researchers have to learn to use a combination of several tools to accomplish this task. In addition, interactive visualization of large networks has been primarily restricted to locally installed programs. To address these challenges, we have developed NetworkAnalyst, taking advantage of state-of-the-art web technologies, to enable high performance network analysis with rich user experience. NetworkAnalyst integrates all three steps and presents the results via a powerful online network visualization framework. Users can upload gene or protein lists, single or multiple gene expression datasets to perform comprehensive gene annotation and differential expression analysis. Significant genes are mapped to our manually curated protein-protein interaction database to construct relevant networks. The results are presented through standard web browsers for network analysis and interactive exploration. NetworkAnalyst supports common functions for network topology and module analyses. Users can easily search, zoom and highlight nodes or modules, as well as perform functional enrichment analysis on these selections. The networks can be customized with different layouts, colors or node sizes, and exported as PNG, PDF or GraphML files. Comprehensive FAQs, tutorials and context-based tips and instructions are provided. NetworkAnalyst currently supports protein-protein interaction network analysis for human and mouse and is freely available at http://www.networkanalyst.ca.

The rate and spectrum of spontaneous mutations are critical parameters in basic and applied biology because they dictate the pace and character of genetic variation introduced into populations which is a prerequisite for evolution. We use a mutation-accumulation (MA) approach to estimate mutation parameters from whole genome sequence data from multiple genotypes from multiple populations of Daphnia magna, an ecological and evolutionary model system. We report extremely high base substitution mutation rates (µ-n,bs = 8.96 x 10−9/bp/generation [95% CI: 6.66-11.97 x 10−9/bp/generation] in the nuclear genome and µ-m,bs= 8.7x10−7/bp/generation [95% CI: 4.40-15.12 x 10−7/bp/generation] in the mtDNA), the highest of any eukaryote examined using this approach. Levels of intraspecific variation based on the range of estimates from the 9 genotypes collected from three populations (Finland, Germany, and Israel) span 1 and 3 orders of magnitude, respectively, resulting in up to a ∼300-fold difference in rates among genomic partitions within the same lineage. In contrast, mutation spectra exhibit very consistent patterns across genotypes and populations, suggesting the mechanisms underlying the mutational process may be similar, even when the rates at which they occur differ. We discuss the implications of high levels of intraspecific variation in rates, the importance of estimating gene conversion rates using an MA approach, and the interacting factors influencing the evolution of mutation parameters. Our findings deepen our knowledge about mutation and provide both challenges to and support for current theories aimed at explaining the evolution of the mutation rate, as a trait, across taxa.

The study was designed to test the hypothesis that male aging is associated with a change in reproductive function in the zebrafish. Young (290 ± 37 d) and older (911 ± 48 d) males were combined with females (604 ± 24 d) to test the effect of male age on the number and fertility of eggs laid by their mates. 48% of breeding trials with young males and 25% of the trails with older males resulted in egg deposition. Although young males were associated with significantly more successful breeding attempts than older males, number of eggs laid per clutch, number and percent of fertilized eggs and the number and percent living embryos were not statistically different between young and older males. These data suggest that male aging is associated with altered reproductive behavior and/or female response but not in sperm quality per se. Consistent with this interpretation were the findings that percent motility and sperm motility characteristics did not differ between sperm from young and older males as assessed by computer-assisted sperm analysis. However, older males contained higher quantities of extractable sperm than did young males, perhaps associated with fewer successful breeding attempts. Age-related effects on male reproductive in the zebrafish may therefore be a consequence of behavioral or morphological features that play a role in female mate choice and/ or male sexual response.

We used the Nadia, Gaighatta, Scientific Hatcheries, and TM1 zebrafish (Danio rerio) strains to test the hypothesis that variation among populations influences the behavioral and transcriptional responses to selenium supplementation. When fed a diet with control levels of selenium, zebrafish strains differed significantly in behavior, characterized as their mean horizontal and vertical swimming positions within the tank. The four strains also differed in brain expression of selenoprotein P1a (sepp1a), glutathione peroxidase 3 (gpx3), thioredoxin reductase 1 (txnrd1), and tRNA selenocysteine associated protein 1 (secp43). Iodothyronine deiodinase 2 (dio2) did not differ among strains but showed a sex-specific expression pattern. When supplemented with selenium, all strains spent a greater proportion of time near the front of the tank, but the response of vertical swimming depth varied by strain. Selenium supplementation also caused changes in selenoprotein expression in the brain that varied by strain for sepp1a, secp43, and dio2, and varied by strain and sex for txnrd1. Expression of gpx3 was unaffected by selenium. Our data indicate that selenium homeostasis in the brain may be a regulator of behavior in zebrafish, and the strainspecific effects of selenium supplementation suggest that genetic heterogeneity among populations can influence the results of selenium supplementation studies.

Studies of how the microbiome varies among individuals, populations, and abiotic conditions are critical for understanding this key component of an organism's biology and ecology. In the case of Daphnia, aquatic microcrustaceans widely used in population/community ecology and environmental science studies, understanding factors that influence microbiome shifts among individuals is useful for both basic and applied research contexts. In this study, we assess differences in the microbiome among genotypes of D. magna collected from three regions along a large latitudinal gradient (Finland, Germany, and Israel). After being reared in the lab for many years, we sought to characterize any differences in genotype-or population-specific microbial communities, and to assess whether the microbiota varied among temperatures. Our study is similar to a recent comparison of the microbial communities among D. magna genotypes raised in different temperatures published by Sullam et al. (Microb Ecol 76(2):506-517, 2017), and as such represents one of the first examples of a reproducible result in microbiome research. Like the previous study, we find evidence for a strong effect of temperature on the microbiome of D. magna, although across a much smaller temperature range representing potential near-future climates. In addition, we find evidence that the microbiomes of D. magna genotypes from different regions are distinct, even years after being brought into the laboratory. Finally, our results highlight a potentially common finding in the expanding area of microbiome research-differences among treatments are not necessarily observed in the most abundant taxonomic groups. This highlights the importance of considering sampling scheme and depth of coverage when characterizing the microbiome, as different experimental designs can significantly impact taxon-specific results, even when large-scale effects are reproduced.

Microsatellite loci (tandem repeats of short nucleotide motifs) are highly abundant in eukaryotic genomes and often used as genetic markers because they can exhibit variation both within and between populations. Although widely recognized for their mutability and utility, the mutation rates of microsatellites have only been empirically estimated in a few species, and have rarely been compared across genotypes and populations within a species. Here, we investigate the dynamics of microsatellite mutation over long- and short-time periods by quantifying the starting abundance and mutation rates for microsatellites for six different genotypes of Daphnia magna, an aquatic microcrustacean, collected from three populations (Finland, Germany, and Israel). Using whole-genome sequences of these six starting genotypes, descendent mutation accumulation (MA) lines, and large population controls (non-MA lines), we find each genotype exhibits a distinctive initial microsatellite profile which clusters according to the population-of-origin. During the period of MA, we observe motif-specific, highly variable, and rapid microsatellite mutation rates across genotypes of D. magna, the average of which is order of magnitude greater than the recently reported rate observed in a single genotype of the congener, Daphnia pulex. In our experiment, genotypes with more microsatellites starting out exhibit greater losses and those with fewer microsatellites starting out exhibit greater gains—a context-dependent mutation bias that has not been reported previously. We discuss how genotype-specific mutation rates and spectra, in conjunction with evolutionary forces, can shape both the differential accumulation of repeat content in the genome and the evolution of mutation rates.

No abstract

The potential benefits of selenium (Se) supplementation are currently under investigation for prevention of certain cancers and treatment of neurological disorders. However, little is known concerning the response of the brain to increased dietary Se under conditions of Se sufficiency, despite the majority of Se supplementation trials occurring in healthy, Se sufficient subjects. We evaluated the transcriptional response of Se-dependent genes, selenoproteins and the genes necessary for their synthesis (the selenoproteome), in the zebrafish (Danio rerio) brain to supplementation with nutritionally relevant levels of dietary Se (sodium selenite) during conditions of assumed Se sufficiency. We first used a microarray approach to analyze the response of the brain selenoproteome to dietary Se supplementation for 14 days and then assessed the immediacy and time-scale transcriptional response of the brain selenoproteome to 1, 7, and 14 days of Se supplementation by quantitative real-time PCR (qRT-PCR). The microarray approach did not indicate large-scale influences of Se on the brain transcriptome as a whole or the selenoproteome specifically; only one nonselenoproteome gene (si:ch73-44m9.2) was significantly differentially expressed. Our qRT-PCR results, however, indicate that increases of dietary Se cause small, but significant transcriptional changes within the brain selenoproteome, even after only 1 day of supplementation. These responses were dynamic over a short period of supplementation in a manner highly dependent on sex and the duration of Se supplementation. In nutritional intervention studies, it may be necessary to utilize methods such as qRT-PCR, which allow larger sample sizes, for detecting subtle transcriptional changes in the brain.