In ecotoxicology, the state of the art for effect assessment of chemical mixtures is through multiple dose-response analysis of single compounds and their combinations. Investigating whether such data deviate from the reference models of concentration addition and/or independent action to identify overall synergism or antagonism is becoming routine. However, recent data show that more complex deviation patterns, such as dose ratio-dependent deviation and dose level-dependent deviation, need to be addressed. For concentration addition, methods to detect such deviation patterns exist, but they are stand-alone methods developed separately in literature, and conclusions derived from these analyses are therefore difficult to compare. For independent action, hardly any methods to detect such deviations from this reference model exist. This paper describes how these well-established mixture toxicity principles have been incorporated in a coherent data analysis procedure enabling detection and quantification of dose level-and dose ratio-specific synergism or antagonism from both the concentration addition and the independent action models. Significance testing of which deviation pattern describes the data best is carried out through maximum likelihood analysis. This analysis procedure is demonstrated through various data sets, and its applicability and limitations in mixture research are discussed.

All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of microrecoveries observed in natural time series. Such dynamic indicators of resilience may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethinking of our approach to the adaptive management of health and resilience.

Recent genetical genomics studies have provided intimate views on gene regulatory networks. Gene expression variations between genetically different individuals have been mapped to the causal regulatory regions, termed expression quantitative trait loci. Whether the environment-induced plastic response of gene expression also shows heritable difference has not yet been studied. Here we show that differential expression induced by temperatures of 16 °C and 24 °C has a strong genetic component in Caenorhabditis elegans recombinant inbred strains derived from a cross between strains CB4856 (Hawaii) and N2 (Bristol). No less than 59% of 308 trans-acting genes showed a significant eQTL-by-environment interaction, here termed plasticity quantitative trait loci. In contrast, only 8% of an estimated 188 cis-acting genes showed such interaction. This indicates that heritable differences in plastic responses of gene expression are largely regulated in trans. This regulation is spread over many different regulators. However, for one group of trans-genes we found prominent evidence for a common master regulator: a transband of 66 coregulated genes appeared at 24 °C. Our results suggest widespread genetic variation of differential expression responses to environmental impacts and demonstrate the potential of genetical genomics for mapping the molecular determinants of phenotypic plasticity.

The Hawaiian strain (CB4856) of Caenorhabditis elegans is one of the most divergent from the canonical laboratory strain N2 and has been widely used in developmental, population, and evolutionary studies. To enhance the utility of the strain, we have generated a draft sequence of the CB4856 genome, exploiting a variety of resources and strategies. When compared against the N2 reference, the CB4856 genome has 327,050 single nucleotide variants (SNVs) and 79,529 insertion–deletion events that result in a total of 3.3 Mb of N2 sequence missing from CB4856 and 1.4 Mb of sequence present in CB4856 but not present in N2. As previously reported, the density of SNVs varies along the chromosomes, with the arms of chromosomes showing greater average variation than the centers. In addition, we find 61 regions totaling 2.8 Mb, distributed across all six chromosomes, which have a greatly elevated SNV density, ranging from 2 to 16% SNVs. A survey of other wild isolates show that the two alternative haplotypes for each region are widely distributed, suggesting they have been maintained by balancing selection over long evolutionary times. These divergent regions contain an abundance of genes from large rapidly evolving families encoding F-box, MATH, BATH, seven-transmembrane G-coupled receptors, and nuclear hormone receptors, suggesting that they provide selective advantages in natural environments. The draft sequence makes available a comprehensive catalog of sequence differences between the CB4856 and N2 strains that will facilitate the molecular dissection of their phenotypic differences. Our work also emphasizes the importance of going beyond simple alignment of reads to a reference genome when assessing differences between genomes.

Gene expression becomes more variable with age, and it is widely assumed that this is due to a decrease in expression regulation. But currently there is no understanding how gene expression regulatory patterns progress with age. Here we explored genome-wide gene expression variation and regulatory loci (eQTL) in a population of developing and aging C. elegans recombinant inbred worms. We found almost 900 genes with an eQTL, of which almost half were found to have a genotype-by-age effect ( gxa eQTL). The total number of eQTL decreased with age, whereas the variation in expression increased. In developing worms, the number of genes with increased expression variation (1282) was similar to the ones with decreased expression variation (1328). In aging worms, the number of genes with increased variation (1772) was nearly five times higher than the number of genes with a decreased expression variation (373). The number of cis-acting eQTL in juveniles decreased by almost 50% in old worms, whereas the number of trans-acting loci decreased by~27%, indicating that cis-regulation becomes relatively less frequent than trans-regulation in aging worms. Of the 373 genes with decreased expression level variation in aging worms,~39% had an eQTL compared with~14% in developing worms. gxa eQTL were found for~21% of these genes in aging worms compared with only~6% in developing worms. We highlight three examples of linkages: in young worms (pgp-6), in old worms (daf-16), and throughout life (lips-16). Our findings demonstrate that eQTL patterns are strongly affected by age, and suggest that gene network integrity declines with age.

Model organisms are of great importance to understanding basic biology and to making advances in biomedical research. However, the influence of laboratory cultivation on these organisms is underappreciated, especially how that environment can affect research outcomes. Recent experiments led to insights into how the widely used laboratory reference strain of the nematode Caenorhabditis elegans compares to natural strains. Here, we describe potential selective pressures that led to fixation of laboratory-derived alleles for the genes npr-1, glb-5, and nath-10. These alleles influence a large number of traits, resulting in behaviors that affect experimental interpretations. Furthermore, strong phenotypic effects caused by these laboratory-derived alleles hinder the discovery of natural alleles. We highlight strategies to reduce the influences of laboratory-derived alleles and to harness the full power of C. elegans.

BackgroundCryptic genetic variation (CGV) is the hidden genetic variation that can be unlocked by perturbing normal conditions. CGV can drive the emergence of novel complex phenotypes through changes in gene expression. Although our theoretical understanding of CGV has thoroughly increased over the past decade, insight into polymorphic gene expression regulation underlying CGV is scarce. Here we investigated the transcriptional architecture of CGV in response to rapid temperature changes in the nematode Caenorhabditis elegans. We analyzed regulatory variation in gene expression (and mapped eQTL) across the course of a heat stress and recovery response in a recombinant inbred population.ResultsWe measured gene expression over three temperature treatments: i) control, ii) heat stress, and iii) recovery from heat stress. Compared to control, exposure to heat stress affected the transcription of 3305 genes, whereas 942 were affected in recovering animals. These affected genes were mainly involved in metabolism and reproduction. The gene expression pattern in recovering animals resembled both the control and the heat-stress treatment. We mapped eQTL using the genetic variation of the recombinant inbred population and detected 2626 genes with an eQTL in the heat-stress treatment, 1797 in the control, and 1880 in the recovery. The cis-eQTL were highly shared across treatments. A considerable fraction of the trans-eQTL (40–57%) mapped to 19 treatment specific trans-bands. In contrast to cis-eQTL, trans-eQTL were highly environment specific and thus cryptic. Approximately 67% of the trans-eQTL were only induced in a single treatment, with heat-stress showing the most unique trans-eQTL.ConclusionsThese results illustrate the highly dynamic pattern of CGV across three different environmental conditions that can be evoked by a stress response over a relatively short time-span (2 h) and that CGV is mainly determined by response related trans regulatory eQTL.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3899-8) contains supplementary material, which is available to authorized users.

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