"A comparison of thermal stress response between Drosophila melanogaster and Drosophila pseudoobscura reveals differences between species and sexes"

The environment is changing faster than anticipated due to climate change, making species more vulnerable to its impacts. The level of vulnerability of species is influenced by factors such as the degree and duration of exposure, as well as the physiological sensitivity of organisms to changes in their environments, which has been shown to vary among species, populations, and individuals. Here, we compared physiological changes in fecundity, critical thermalmaximum (CTmax), respiratory quotient (RQ), and DNA damage in ovaries in response to temperature stress in two species of fruit fly, Drosophila melanogaster (25 vs. 29.5 °C) and Drosophila pseudoobscura (20.5 vs. 25 °C). The fecundity of D. melanogaster was more affected by high temperatures when exposed during egg through adult development, while D. pseudoobscura was most significantly affected when exposed to high temperatures exclusively during egg through pupal development. Additionally, D. melanogaster males exhibited a decrease of CTmax under high temperatures, while females showed an increase of CTmax when exposed to high temperatures during egg through adult development. while D. pseudoobscura females and males showed an increased CTmax only when reared at high temperatures during egg through pupae development. Moreover, both species showed an acceleration in oogenesis and an increase in apoptosis due to heat stress. These changes can likely be attributed to key differences in the geographic range, thermal range, development time, and other different factors between these two systems. Through this comparison of variation in physiology and developmental response to thermal stress, we found important differences between species and sexes that suggest future work needs to account for these factors separately in understanding the effects of constant increased temperatures.

Induced immune reaction in the acorn worm, Saccoglossus kowalevskii, informs the evolution of antiviral immunity

Evolutionary perspectives on the deployment of immune factors following infection have been shaped by studies on a limited number of biomedical model systems with a heavy emphasis on vertebrate species. Though their contributions to contemporary immunology cannot be understated, a broader phylogenetic perspective is needed to understand the evolution of immune systems across Metazoa. In our study, we leverage differential gene expression analyses to identify genes implicated in the antiviral immune response of the acorn worm hemichordate, Saccoglossus kowalevskii, and place them in the context of immunity evolution within deuterostomes - the animal clade composed of chordates, hemichordates, and echinoderms. Following acute exposure to the synthetic viral dsRNA analog, poly(I:C), we show that S. kowalevskii responds by regulating the transcription of genes associated with canonical innate immunity signaling pathways (e.g., NF-κB and IRF signaling) and metabolic processes (e.g., lipid metabolism), as well as many genes without clear evidence of orthology with those of model species. Aggregated across all experimental time point contrasts, we identify 423 genes that are differentially expressed in response to poly(I:C). We also identify 147 genes with altered temporal patterns of expression in response to immune challenge. By characterizing the molecular toolkit involved in hemichordate antiviral immunity, our findings provide vital evolutionary context for understanding the origins of immune systems within Deuterostomia.

The brain transcriptome of the wolf spider, Schizocosa ocreata

OBJECTIVES

Arachnids have fascinating and unique biology, particularly for questions on sex differences and behavior, creating the potential for development of powerful emerging models in this group. Recent advances in genomic techniques have paved the way for a significant increase in the breadth of genomic studies in non-model organisms. One growing area of research is comparative transcriptomics. When phylogenetic relationships to model organisms are known, comparative genomic studies provide context for analysis of homologous genes and pathways. The goal of this study was to lay the groundwork for comparative transcriptomics of sex differences in the brain of wolf spiders, a non-model organism of the pyhlum Euarthropoda, by generating transcriptomes and analyzing gene expression.

DATA DESCRIPTION

To examine sex-differential gene expression, short read transcript sequencing and de novo transcriptome assembly were performed. Messenger RNA was isolated from brain tissue of male and female subadult and mature wolf spiders (Schizocosa ocreata). The raw data consist of sequences for the two different life stages in each sex. Computational analyses on these data include de novo transcriptome assembly and differential expression analyses. Sample-specific and combined transcriptomes, gene annotations, and differential expression results are described in this data note and are available from publicly-available databases.

Addressing the unique qualities of upper-level biology CUREs through the integration of skill-building

Early exposure to course-based undergraduate research experiences (CUREs) in introductory biology courses can promote positive student outcomes such as increased confidence, critical thinking, and views of applicability in lower-level courses, but it is unknown if these same impacts are achieved by upper-level courses. Upper-level courses differ from introductory courses in several ways, and one difference that could impact these positive student outcomes is the importance of balancing structure with independence in upper-level CUREs where students typically have more autonomy and greater complexity in their research projects. Here we compare and discuss two formats of upper-level biology CUREs (Guided and Autonomous) that vary along a continuum between structure and independence. We share our experiences teaching an upper-level CURE in two different formats and contrast those formats through student reported perceptions of confidence, professional applicability, and CURE format. Results indicate that the Guided Format (i.e., a more even balance between structure and independence) led to more positive impacts on student outcomes than the Autonomous Format (less structure and increased independence). We review the benefits and drawbacks to each approach while considering the unique elements of upper-level courses relative to lower-level courses. We conclude with a discussion of how implementing structured skill-building can assist instructors in adapting CUREs to their courses.

Perturbation of IIS/TOR signaling alters the landscape of sex-differential gene expression in Drosophila

Background

The core functions of the insulin/insulin-like signaling and target of rapamycin (IIS/TOR) pathway are nutrient sensing, energy homeostasis, growth, and regulation of stress responses. This pathway is also known to interact directly and indirectly with the sex determination regulatory hierarchy. The IIS/TOR pathway plays a role in directing sexually dimorphic traits, including dimorphism of growth, metabolism, stress and behavior. Previous studies of sexually dimorphic gene expression in the adult head, which includes both nervous system and endocrine tissues, have revealed variation in sex-differential expression, depending in part on genotype and environment. To understand the degree to which the environmentally responsive insulin signaling pathway contributes to sexual dimorphism of gene expression, we examined the effect of perturbation of the pathway on gene expression in male and female Drosophila heads.

Results

Our data reveal a large effect of insulin signaling on gene expression, with greater than 50% of genes examined changing expression. Males and females have a shared gene expression response to knock-down of InR function, with significant enrichment for pathways involved in metabolism. Perturbation of insulin signaling has a greater impact on gene expression in males, with more genes changing expression and with gene expression differences of larger magnitude. Primarily as a consequence of the response in males, we find that reduced insulin signaling results in a striking increase in sex-differential expression. This includes sex-differences in expression of immune, defense and stress response genes, genes involved in modulating reproductive behavior, genes linking insulin signaling and ageing, and in the insulin signaling pathway itself.

Conclusions

Our results demonstrate that perturbation of insulin signaling results in thousands of genes displaying sex differences in expression that are not differentially expressed in control conditions. Thus, insulin signaling may play a role in variability of somatic, sex-differential expression. The finding that perturbation of the IIS/TOR pathway results in an altered landscape of sex-differential expression suggests a role of insulin signaling in the physiological underpinnings of trade-offs, sexual conflict and sex differences in expression variability.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5308-3) contains supplementary material, which is available to authorized users.

Recombination rate plasticity: revealing mechanisms by design

For over a century, scientists have known that meiotic recombination rates can vary considerably among individuals, and that environmental conditions can modify recombination rates relative to the background. A variety of external and intrinsic factors such as temperature, age, sex and starvation can elicit 'plastic' responses in recombination rate. The influence of recombination rate plasticity on genetic diversity of the next generation has interesting and important implications for how populations evolve. Further, many questions remain regarding the mechanisms and molecular processes that contribute to recombination rate plasticity. Here, we review 100 years of experimental work on recombination rate plasticity conducted in Drosophila melanogaster We categorize this work into four major classes of experimental designs, which we describe via classic studies in D. melanogaster Based on these studies, we highlight molecular mechanisms that are supported by experimental results and relate these findings to studies in other systems. We synthesize lessons learned from this model system into experimental guidelines for using recent advances in genotyping technologies, to study recombination rate plasticity in non-model organisms. Specifically, we recommend (1) using fine-scale genome-wide markers, (2) collecting time-course data, (3) including crossover distribution measurements, and (4) using mixed effects models to analyse results. To illustrate this approach, we present an application adhering to these guidelines from empirical work we conducted in Drosophila pseudoobscuraThis article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.

What the X has to do with it: differences in regulatory variability between the sexes in Drosophila simulans

The mechanistic basis of regulatory variation and the prevailing evolutionary forces shaping that variation are known to differ between sexes and between chromosomes. Regulatory variation of gene expression can be due to functional changes within a gene itself (cis) or in other genes elsewhere in the genome (trans). The evolutionary properties of cis mutations are expected to differ from mutations affecting gene expression in trans. We analyze allele-specific expression across a set of X substitution lines in intact adult Drosophila simulans to evaluate whether regulatory variation differs for cis and trans, for males and females, and for X-linked and autosomal genes. Regulatory variation is common (56% of genes), and patterns of variation within D. simulans are consistent with previous observations in Drosophila that there is more cis than trans variation within species (47% vs. 25%, respectively). The relationship between sex-bias and sex-limited variation is remarkably consistent across sexes. However, there are differences between cis and trans effects: cis variants show evidence of purifying selection in the sex toward which expression is biased, while trans variants do not. For female-biased genes, the X is depleted for trans variation in a manner consistent with a female-dominated selection regime on the X. Surprisingly, there is no evidence for depletion of trans variation for male-biased genes on X. This is evidence for regulatory feminization of the X, trans-acting factors controlling male-biased genes are more likely to be found on the autosomes than those controlling female-biased genes.

A flexible Bayesian method for detecting allelic imbalance in RNA-seq data

Background

One method of identifying cis regulatory differences is to analyze allele-specific expression (ASE) and identify cases of allelic imbalance (AI). RNA-seq is the most common way to measure ASE and a binomial test is often applied to determine statistical significance of AI. This implicitly assumes that there is no bias in estimation of AI. However, bias has been found to result from multiple factors including: genome ambiguity, reference quality, the mapping algorithm, and biases in the sequencing process. Two alternative approaches have been developed to handle bias: adjusting for bias using a statistical model and filtering regions of the genome suspected of harboring bias. Existing statistical models which account for bias rely on information from DNA controls, which can be cost prohibitive for large intraspecific studies. In contrast, data filtering is inexpensive and straightforward, but necessarily involves sacrificing a portion of the data.

Results

Here we propose a flexible Bayesian model for analysis of AI, which accounts for bias and can be implemented without DNA controls. In lieu of DNA controls, this Poisson-Gamma (PG) model uses an estimate of bias from simulations. The proposed model always has a lower type I error rate compared to the binomial test. Consistent with prior studies, bias dramatically affects the type I error rate. All of the tested models are sensitive to misspecification of bias. The closer the estimate of bias is to the true underlying bias, the lower the type I error rate. Correct estimates of bias result in a level alpha test.

Conclusions

To improve the assessment of AI, some forms of systematic error (e.g., map bias) can be identified using simulation. The resulting estimates of bias can be used to correct for bias in the PG model, without data filtering. Other sources of bias (e.g., unidentified variant calls) can be easily captured by DNA controls, but are missed by common filtering approaches. Consequently, as variant identification improves, the need for DNA controls will be reduced. Filtering does not significantly improve performance and is not recommended, as information is sacrificed without a measurable gain. The PG model developed here performs well when bias is known, or slightly misspecified. The model is flexible and can accommodate differences in experimental design and bias estimation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-920) contains supplementary material, which is available to authorized users.

Purification of transcripts and metabolites from Drosophila heads

For the last decade, we have tried to understand the molecular and cellular mechanisms of neuronal degeneration using Drosophila as a model organism. Although fruit flies provide obvious experimental advantages, research on neurodegenerative diseases has mostly relied on traditional techniques, including genetic interaction, histology, immunofluorescence, and protein biochemistry. These techniques are effective for mechanistic, hypothesis-driven studies, which lead to a detailed understanding of the role of single genes in well-defined biological problems. However, neurodegenerative diseases are highly complex and affect multiple cellular organelles and processes over time. The advent of new technologies and the omics age provides a unique opportunity to understand the global cellular perturbations underlying complex diseases. Flexible model organisms such as Drosophila are ideal for adapting these new technologies because of their strong annotation and high tractability. One challenge with these small animals, though, is the purification of enough informational molecules (DNA, mRNA, protein, metabolites) from highly relevant tissues such as fly brains. Other challenges consist of collecting large numbers of flies for experimental replicates (critical for statistical robustness) and developing consistent procedures for the purification of high-quality biological material. Here, we describe the procedures for collecting thousands of fly heads and the extraction of transcripts and metabolites to understand how global changes in gene expression and metabolism contribute to neurodegenerative diseases. These procedures are easily scalable and can be applied to the study of proteomic and epigenomic contributions to disease.

Allelic imbalance in Drosophila hybrid heads: exons, isoforms, and evolution

Unraveling how regulatory divergence contributes to species differences and adaptation requires identifying functional variants from among millions of genetic differences. Analysis of allelic imbalance (AI) reveals functional genetic differences in cis regulation and has demonstrated differences in cis regulation within and between species. Regulatory mechanisms are often highly conserved, yet differences between species in gene expression are extensive. What evolutionary forces explain widespread divergence in cis regulation? AI was assessed in Drosophila melanogaster-Drosophila simulans hybrid female heads using RNA-seq technology. Mapping bias was virtually eliminated by using genotype-specific references. Allele representation in DNA sequencing was used as a prior in a novel Bayesian model for the estimation of AI in RNA. Cis regulatory divergence was common in the organs and tissues of the head with 41% of genes analyzed showing significant AI. Using existing population genomic data, the relationship between AI and patterns of sequence evolution was examined. Evidence of positive selection was found in 30% of cis regulatory divergent genes. Genes involved in defense, RNAi/RISC complex genes, and those that are sex regulated are enriched among adaptively evolving cis regulatory divergent genes. For genes in these groups, adaptive evolution may play a role in regulatory divergence between species. However, there is no evidence that adaptive evolution drives most of the cis regulatory divergence that is observed. The majority of genes showed patterns consistent with stabilizing selection and neutral evolutionary processes.

Partitioning transcript variation in Drosophila: abundance, isoforms, and alleles

Multilevel analysis of transcription is facilitated by a new array design that includes modules for assessment of differential expression, isoform usage, and allelic imbalance in Drosophila. The ∼2.5 million feature chip incorporates a large number of controls, and it contains 18,769 3' expression probe sets and 61,919 exon probe sets with probe sequences from Drosophila melanogaster and 60,118 SNP probe sets focused on Drosophila simulans. An experiment in D. simulans identified genes differentially expressed between males and females (34% in the 3' expression module; 32% in the exon module). These proportions are consistent with previous reports, and there was good agreement (κ = 0.63) between the modules. Alternative isoform usage between the sexes was identified for 164 genes. The SNP module was verified with resequencing data. Concordance between resequencing and the chip design was greater than 99%. The design also proved apt in separating alleles based upon hybridization intensity. Concordance between the highest hybridization signals and the expected alleles in the genotype was greater than 96%. Intriguingly, allelic imbalance was detected for 37% of 6579 probe sets examined that contained heterozygous SNP loci. The large number of probes and multiple probe sets per gene in the 3' expression and exon modules allows the array to be used in D. melanogaster and in closely related species. The SNP module can be used for allele specific expression and genotyping of D. simulans.

Allele-specific expression assays using Solexa

Background

Allele-specific expression (ASE) assays can be used to identify cis, trans, and cis-by-trans regulatory variation. Understanding the source of expression variation has important implications for disease susceptibility, phenotypic diversity, and adaptation. While ASE is commonly measured via relative fluorescence at a SNP, next generation sequencing provides an opportunity to measure ASE in an accurate and high-throughput manner using read counts.

Results

We introduce a Solexa-based method to perform large numbers of ASE assays using only a single lane of a Solexa flowcell. In brief, transcripts of interest, which contain a known SNP, are PCR enriched and barcoded to enable multiplexing. Then high-throughput sequencing is used to estimate allele-specific expression using sequencing counts. To validate this method, we measured the allelic bias in a dilution series and found high correlations between measured and expected values (r>0.9, p < 0.001). We applied this method to a set of 5 genes in a Drosophila simulans parental mix, F1 and introgression and found that for these genes the majority of expression divergence can be explained by cis-regulatory variation.

Conclusion

We present a new method with the capacity to measure ASE for large numbers of assays using as little as one lane of a Solexa flowcell. This will be a valuable technique for molecular and population genetic studies, as well as for verification of genome-wide data sets.

New candidate genes for sex-comb divergence between Drosophila mauritiana and Drosophila simulans

A large-effect QTL for divergence in sex-comb tooth number between Drosophila simulans and D. mauritiana was previously mapped to 73A-84AB. Here we identify genes that are likely contributors to this divergence. We first improved the mapping resolution in the 73A-84AB region using 12 introgression lines and 62 recombinant nearly isogenic lines. To further narrow the list of candidate genes, we assayed leg-specific expression and identified genes with transcript-level evolution consistent with a potential role in sex-comb divergence. Sex combs are formed on the prothoracic (front) legs, but not on the mesothoracic (middle) legs of Drosophila males. We extracted RNA from the prothoracic and mesothoracic pupal legs of two species to determine which of the genes expressed differently between leg types were also divergent for gene expression. Two good functional candidate genes, Scr and dsx, are located in one of our fine-scale QTL regions. In addition, three previously uncharacterized genes (CG15186, CG2016, and CG2791) emerged as new candidates. These genes are located in regions strongly associated with sex-comb tooth number differences and are expressed differently between leg tissues and between species. Further supporting the potential involvement of these genes in sex-comb divergence, we found a significant difference in sex-comb tooth number between co-isogenic D. melanogaster lines with and without P-element insertions at CG2791.

Quantitative trait loci responsible for variation in sexually dimorphic traits in Drosophila melanogaster

To understand the mechanisms of morphological evolution and species divergence, it is essential to elucidate the genetic basis of variation in natural populations. Sexually dimorphic characters, which evolve rapidly both within and among species, present attractive models for addressing these questions. In this report, we map quantitative trait loci (QTL) responsible for variation in sexually dimorphic traits (abdominal pigmentation and the number of ventral abdominal bristles and sex comb teeth) in a natural population of Drosophila melanogaster. To capture the pattern of genetic variation present in the wild, a panel of recombinant inbred lines was created from two heterozygous flies taken directly from nature. High-resolution mapping was made possible by cytological markers at the average density of one per 2 cM. We have used a new Bayesian algorithm that allows QTL mapping based on all markers simultaneously. With this approach, we were able to detect small-effect QTL that were not evident in single-marker analyses. Our results show that at least for some sexually dimorphic traits, a small number of QTL account for the majority of genetic variation. The three strongest QTL account for >60% of variation in the number of ventral abdominal bristles. Strikingly, a single QTL accounts for almost 60% of variation in female abdominal pigmentation. This QTL maps to the chromosomal region that Robertson et al. have found to affect female abdominal pigmentation in other populations of D. melanogaster. Using quantitative complementation tests, we demonstrate that this QTL is allelic to the bric a brac gene, whose expression has previously been shown to correlate with interspecific differences in pigmentation. Multiple bab alleles that confer distinct phenotypes appear to segregate in natural populations at appreciable frequencies, suggesting that intraspecific and interspecific variation in abdominal pigmentation may share a similar genetic basis.