Ocean currents influence the genetic structure of an intertidal mollusc in southeastern Australia – implications for predicting the movement of passive dispersers across a marine biogeographic barrier

Major disjunctions among marine communities in southeastern Australia have been well documented, although explanations for biogeographic structuring remain uncertain. Converging ocean currents, environmental gradients, and habitat discontinuities have been hypothesized as likely drivers of structuring in many species, although the extent to which species are affected appears largely dependent on specific life histories and ecologies. Understanding these relationships is critical to the management of native and invasive species, and the preservation of evolutionary processes that shape biodiversity in this region. In this study we test the direct influence of ocean currents on the genetic structure of a passive disperser across a major biogeographic barrier. Donax deltoides (Veneroida: Donacidae) is an intertidal, soft‐sediment mollusc and an ideal surrogate for testing this relationship, given its lack of habitat constraints in this region, and its immense dispersal potential driven by year‐long spawning and long‐lived planktonic larvae. We assessed allele frequencies at 10 polymorphic microsatellite loci across 11 sample locations spanning the barrier region and identified genetic structure consistent with the major ocean currents of southeastern Australia. Analysis of mitochondrial DNA sequence data indicated no evidence of genetic structuring, but signatures of a species range expansion corresponding with historical inundations of the Bassian Isthmus. Our results indicate that ocean currents are likely to be the most influential factor affecting the genetic structure of D. deltoides and a likely physical barrier for passive dispersing marine fauna generally in southeastern Australia.     

Use of polyethyleneimine polymer in cell culture as attachment factor and lipofection enhancer

Background  

Several cell lines and primary cultures benefit from the use of positively charged extracellular matrix proteins or polymers that enhance their ability to attach to culture plates. Polyethyleneimine is a positively charged polymer that has gained recent attention as a transfection reagent. A less known use of this cationic polymer as an attachment factor was explored with several cell lines.     

Proteomics-based target identification: bengamides as a new class of methionine aminopeptidase inhibitors

LAF389 is a synthetic analogue of bengamides, a class of marine natural products that produce inhibitory effects on tumor growth in vitro and in vivo. A proteomics-based approach has been used to identify signaling pathways affected by bengamides. LAF389 treatment of cells resulted in altered mobility of a subset of proteins on two-dimensional gel electrophoresis. Detailed analysis of one of the proteins, 14-3-3gamma, showed that bengamide treatment resulted in retention of the amino-terminal methionine, suggesting that bengamides directly or indirectly inhibited methionine aminopeptidases (MetAps). Both known MetAps are inhibited by LAF389. Short interfering RNA suppression of MetAp2 also altered amino-terminal processing of 14-3-3gamma. A high resolution structure of human MetAp2 co-crystallized with a bengamide shows that the compound binds in a manner that mimics peptide substrates. Additionally, the structure reveals that three key hydroxyl groups on the inhibitor coordinate the di-cobalt center in the enzyme active site.     

Running as fast as it can: How spiking dynamics form object groupings in the laminar circuits of visual cortex

How spiking neurons cooperate to control behavioral processes is a fundamental problem in computational neuroscience. Such cooperative dynamics are required during visual perception when spatially distributed image fragments are grouped into emergent boundary contours. Perceptual grouping is a challenge for spiking cells because its properties of collinear facilitation and analog sensitivity occur in response to binary spikes with irregular timing across many interacting cells. Some models have demonstrated spiking dynamics in recurrent laminar neocortical circuits, but not how perceptual grouping occurs. Other models have analyzed the fast speed of certain percepts in terms of a single feedforward sweep of activity, but cannot explain other percepts, such as illusory contours, wherein perceptual ambiguity can take hundreds of milliseconds to resolve by integrating multiple spikes over time. The current model reconciles fast feedforward with slower feedback processing, and binary spikes with analog network-level properties, in a laminar cortical network of spiking cells whose emergent properties quantitatively simulate parametric data from neurophysiological experiments, including the formation of illusory contours; the structure of non-classical visual receptive fields; and self-synchronizing gamma oscillations. These laminar dynamics shed new light on how the brain resolves local informational ambiguities through the use of properly designed nonlinear feedback spiking networks which run as fast as they can, given the amount of uncertainty in the data that they process.     

On the NMR analysis of pKa values in the unfolded state of proteins by extrapolation to zero denaturant

Detailed knowledge of the pH-dependence in both folded and unfolded states of proteins is essential to understand the role of electrostatics in protein stability. The increasing number of natively disordered proteins constitutes an excellent source for the NMR analysis of pKa values in the unfolded state of proteins. However, the tendency of many natively disordered proteins to aggregate via intermolecular hydrophobic clusters limits their NMR analysis over a wide pH range. To assess whether the pKa values in natively disordered polypeptides can be extrapolated from NMR measurements in the presence of denaturants, the natively disordered backbone of the C-terminal fragment 75 to 105 of Human Thioredoxin was studied. First, assignments using triple resonance experiments were performed to confirm lack of secondary structure. Then the pH-dependence of the amides and carboxylate side chains of Glu residues (Glu88, Glu95, Glu98, and Glu103) in the pH range from 2.0 to 7.0 was monitored using 2D 1H15N HSQC and 3D C(CO)NH experiments, and the behavior of their amides and corresponding carboxyl groups was compared to confirm the absence of nonlocal interactions. Lastly, the effect of increasing dimethyl urea concentration on the pKa values of these Glu residues was monitored. The results indicate that: (i) the dispersion in the pKa of carboxyl groups and the pH midpoints of amides in Glu residues is about 0.5 pH units and 0.6 pH units, respectively; (ii) the backbone amides of the Glu residues exhibit pH midpoints which are within 0.2 pH units from those of their carboxylates; (iii) the addition of denaturant produces upshifts in the pKa values of Glu residues that are nearly independent of their position in the sequence; and (iv) these upshifts show a nonlinear behavior in denaturant concentration, complicating the extrapolation to zero denaturant. Nevertheless, the relative ordering of the pKa values of Glu residues is preserved over the whole range of denaturant concentrations indicating that measurements at high denaturant concentration (e.g. 4 M dimethyl urea) can yield a qualitatively correct ranking of the pKa of these residues in natively disordered proteins whose pH-dependence cannot be monitored directly by NMR.     

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (C_ANA). The C_ANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of C_ANA) and blood lactate concentration analysis (lactic anaerobic contributions of C_ANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s^-1) and LMS (1.3±0.1 m·s^-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min^-1; r = 0.72) and C_ANA (4.7±1.5 L·O₂; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, C_ANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance.     

Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation

Evolve and resequence (E&R) is a new approach to investigate the genomic responses to selection during experimental evolution. By using whole genome sequencing of pools of individuals (Pool-Seq), this method can identify selected variants in controlled and replicable experimental settings. Reviewing the current state of the field, we show that E&R can be powerful enough to identify causative genes and possibly even single-nucleotide polymorphisms. We also discuss how the experimental design and the complexity of the trait could result in a large number of false positive candidates. We suggest experimental and analytical strategies to maximize the power of E&R to uncover the genotype–phenotype link and serve as an important research tool for a broad range of evolutionary questions.Experimental evolution has a long tradition in biology (Garland and Rose, 2009). By exposing an evolving population to conditions chosen by the researcher, it is possible to study the response to this selection regime. A recent review highlighted the broad range of applications that have been investigated with this methodology and concluded that the breadth of research questions is only limited by the creativity of the experimenter (Kawecki et al., 2012). In addition to the great diversity of experimental designs, experimental evolution provides a unique advantage compared with other evolutionary analyses: the ability to replicate an experiment under identical conditions. Through this replication, experimenters are able to distinguish between stochastic and deterministic effects. Until recently, experimental evolution has mainly focused on phenotypes, sometimes combined with the analysis of a small number of markers (see, for example, Nuzhdin et al., 1993; Teotonio et al., 2009). In the wake of the latest sequencing technologies and the ongoing drop in DNA sequencing costs, however, the ultimate goal to connect the phenotypic response to the underlying genetic changes during an experimental evolution study has now come within reach.Depending on the starting population, two conceptually different approaches of experimental evolution can be distinguished. Either the experiment starts from a genetically homogeneous (invariable) population or from a polymorphic population. In the first approach, adaptation occurs through the accumulation of new beneficial mutations during the experiment (Elena and Lenski, 2003). These experiments therefore require very large population sizes and many generations to ensure a sufficient mutation supply and are thus largely restricted to microorganisms. Alternatively, experiments starting with a polymorphic population do not require novel mutations as selection can act on beneficial alleles that are already present at the beginning of the experiment. Given the massive genetic variation that is present in the starting population, the key challenge for this approach is distinguishing between selected and neutral variants. Neither randomly selected markers nor whole genome sequencing of a few representative individuals can provide sufficient information about the true target(s) of selection. Rather, genome-wide polymorphism data are needed.As whole genome sequencing is still not feasible for large numbers of individuals, experimental evolution studies starting from polymorphic base populations rely on a modified next-generation sequencing approach. Rather than sequencing individuals separately, DNA of multiple individuals from a population are sequenced together (Pool-Seq). This method is more cost effective than sequencing of individuals (Futschik and Schlötterer, 2010) and yields highly accurate genome-wide allele frequency estimates (reviewed in Rellstab et al., 2013; Schlötterer et al., 2014). The combination of experimental evolution with Pool-Seq is also known as Evolve and Resequence (E&R; Turner et al., 2011; Figure 1). Here, we review the state of the art of whole genome polymorphism analysis in experimental evolution studies relying primarily on segregating variation in the starting population.Open in a separate windowFigure 1Overview of E&R studies. (a) A population of flies is exposed for 60 generations to ultraviolet (UV) radiation (purple arrows). We assume here, for the sake of illustration, that darker pigmentation is beneficial in high UV environments, whereby darker flies will increase in frequency. (b) At the genotypic level, the allele frequency of the causative allele (dark brown) will increase, more so than hitchhiking variants (dark gray background) that will be recombined onto other backgrounds (breaks between dark and light gray background). (c) The allele frequencies of the starting population and the selected population are measured with Pool-Seq. (d) Causative variants can be identified by contrasting the allele frequencies between base and selected population and visualized with Manhattan plots. A full color version of this figure is available at the Heredity journal online.In many experimental evolution studies, researchers select for a well-defined trait in a controlled environment. This assures that both the phenotypic and the underlying genomic response are triggered either directly or indirectly by the selection regime applied during the experiment. Thus, E&R studies provide a complementary approach to genome-wide association studies (GWASs) and linkage mapping experiments as strategies to connect genotype and phenotype.     

Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains

Background

Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers.

Results

The Pheno2Geno tool uses mixture modeling to select phenotypes and transform them into genetic markers suitable for construction and/or saturation of a genetic map. Pheno2Geno excludes candidate genetic markers that show evidence for multiple possibly epistatically interacting QTL and/or interaction with the environment, in order to provide a set of robust markers for follow-up QTL mapping.We demonstrate the use of Pheno2Geno on gene expression data of 370,000 probes in 148 A. thaliana recombinant inbred lines. Pheno2Geno is able to saturate the existing genetic map, decreasing the average distance between markers from 7.1 cM to 0.89 cM, close to the theoretical limit of 0.68 cM (with 148 individuals we expect a recombination every 100/148=0.68 cM); this pinpointed almost all of the informative recombinations in the population.

Conclusion

The Pheno2Geno package makes use of genome-wide molecular profiling and provides a tool for high-throughput de novo map construction and saturation of existing genetic maps. Processing of the showcase dataset takes less than 30 minutes on an average desktop PC. Pheno2Geno improves QTL mapping results at no additional laboratory cost and with minimum computational effort. Its results are formatted for direct use in R/qtl, the leading R package for QTL studies. Pheno2Geno is freely available on CRAN under “GNU GPL v3”. The Pheno2Geno package as well as the tutorial can also be found at: http://pheno2geno.nl.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0475-6) contains supplementary material, which is available to authorized users.     

Aspects of the biology of Galaxias maculatus

The biology of three landlocked and a riverine population of Galaxias maculatus were examined in western Victoria, Australia. All systems supported reproducing populations of these fish, including Lake Corangamite which had salinities that on occasion reached 82. Spawning sites in Lake Corangamite were located in adjacent tributaries and not in the main lake as was the case for other populations. The smallest fish were found in the fresh water Lake Purrumbete and the largest in the hypersaline Lake Corangamite. The size at which 50% of the population attained sexual maturity varied across sites, with fish maturing at a smaller size in Lake Purrumbete, followed by the Merri River, Lake Bullen Merri and Lake Corangamite. Condition was higher in the freshwater Lake Purrumbete and there was no relationship between condition and temperature, conductivity, turbidity and pH; but there was a positive relationship between condition and dissolved oxygen. Length frequency analysis suggested that the majority of fishes live for a year.