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This study comprehensively evaluated the landscape of genetic and epigenetic events that predispose to synchronous bilateral Wilms tumor (BWT). We performed whole exome or whole genome sequencing, total-strand RNA-seq, and DNA methylation analysis using germline and/or tumor samples from 68 patients with BWT from St. Jude Children’s Research Hospital and the Children’s Oncology Group. We found that 25/61 (41%) of patients evaluated harbored pathogenic or likely pathogenic germline variants, with WT1 (14.8%), NYNRIN (6.6%), TRIM28 (5%) and the BRCA-related genes (5%) BRCA1, BRCA2, and PALB2 being most common. Germline WT1 variants were strongly associated with somatic paternal uniparental disomy encompassing the 11p15.5 and 11p13/WT1 loci and subsequent acquired pathogenic CTNNB1 variants. Somatic coding variants or genome-wide copy number alterations were almost never shared between paired synchronous BWT, suggesting that the acquisition of independent somatic variants leads to tumor formation in the context of germline or early embryonic, post-zygotic initiating events. In contrast, 11p15.5 status (loss of heterozygosity, loss or retention of imprinting) was shared among paired synchronous BWT in all but one case. The predominant molecular events for BWT predisposition include pathogenic germline variants or post-zygotic epigenetic hypermethylation at the 11p15.5 H19/ICR1 locus (loss of imprinting). This study demonstrates that post-zygotic somatic mosaicism for 11p15.5 hypermethylation/loss of imprinting is the single most common initiating molecular event predisposing to BWT. Evidence of somatic mosaicism for 11p15.5 loss of imprinting was detected in leukocytes of a cohort of BWT patients and long-term survivors, but not in unilateral Wilms tumor patients and long-term survivors or controls, further supporting the hypothesis that post-zygotic 11p15.5 alterations occurred in the mesoderm of patients who go on to develop BWT. Due to the preponderance of BWT patients with demonstrable germline or early embryonic tumor predisposition, BWT exhibits a unique biology when compared to unilateral Wilms tumor and therefore warrants continued refinement of its own treatment-relevant biomarkers which in turn may inform directed treatment strategies in the future.

Sexual dimorphism in gene expression is likely to be the underlying source of dimorphism in a variety of traits. Many analyses implicitly make the assumption that dimorphism only evolves when selection favors different phenotypes in the two sexes, although theory makes clear that it can also evolve as an indirect response to other kinds of selection. Furthermore, previous analyses consider the evolution of a single transcript or trait at a time, ignoring the genetic covariance with other transcripts and traits. We first show which aspects of the genetic-variance covariance matrix, G, affect dimorphism when these assumptions about selection are relaxed. We then reanalyze gene expression data from Drosophila melanogaster with these predictions in mind. Dimorphism of gene expression for individual transcripts shows the signature of both direct selection for dimorphism and indirect responses to selection. To account for the effect of measurement error on evolutionary predictions, we estimated a G matrix for eight linear combinations of expression traits. Sex-specific genetic variances in female- and male-biased transcription, as well as one relatively unbiased combination were quite unequal, ensuring that most forms of selection on these traits will have large effects on dimorphism. Predictions of response to selection based on the whole G matrix showed that sexually concordant and antagonistic selection are equally capable of changing sexual dimorphism. In addition, the indirect responses of dimorphism due to cross-trait covariances were quite substantial. The assumption that sexual dimorphism in transcription is an adaptation is likely to be incorrect in many specific cases.

A lack of relevant genetic models and cell lines hampers our understanding of hepatoblastoma pathogenesis and the development of new therapies for this neoplasm. We report a liver-specific MYC-driven hepatoblastoma murine model that faithfully recapitulates the pathological features of mixed fetal and embryonal hepatoblastoma, with transcriptomics resembling the high-risk gene signatures of the human disease. Single-cell RNA-sequencing and spatial transcriptomics identified distinct subpopulations of hepatoblastoma cells. After deriving cell lines from the mouse model, we mapped the cancer dependency genes using CRISPR-Cas9 screening and identified druggable targets shared with human hepatoblastoma (i.e., CDK7, CDK9, PRMT1, PRMT5). Our screen also revealed oncogenes and tumor suppressor genes in hepatoblastoma that engage multiple, druggable cancer signaling pathways. Chemotherapy is critical for human hepatoblastoma treatment. A genetic mapping of doxorubicin response by CRISPR-Cas9 screening identified modifiers whose loss-of-function synergizes with (e.g., PRKDC) or antagonizes (e.g., apoptosis genes) with the effect of chemotherapy. The combination of PRKDC inhibition and doxorubicin-based chemotherapy greatly enhances therapeutic efficacy. These studies have provided a useful set of resources including disease models suitable to identify and validate potential therapeutic targets in human high-risk hepatoblastoma.

Sexual dimorphism is often assumed to result from balancing the strength of antagonistic selection in favor of dimorphism against the degree of constraint imposed by the shared genome of the sexes, reflected in the B matrix of genetic intersexual covariances. To investigate the totality of forces shaping dimorphism, we reparameterized the Lande equation to predict changes in trait averages and trait differences between the sexes. As genetic constraints on the evolution of dimorphism in response to antagonistic selection become larger, dimorphism will tend to respond more rapidly to concordant selection (which favors the same direction of change in male and female traits) than to antagonistic selection. When we apply this theory to four empirical estimates of B in Drosophila melanogaster, the indirect responses of dimorphism to concordant selection are of comparable or larger magnitude than the direct responses of dimorphism to antagonistic selection in two suites of traits with typical levels of intersex correlation. Antagonistic selection is more important in two suites of traits where the intersex correlations are unusually low. This suggests that the evolution of sexual dimorphism may sometimes be dominated by concordant selection rather than antagonistic selection.

Photoperiod is a key environmental cue affecting flowering and biomass traits in plants. Key components of the photoperiodic flowering pathway have been identified in many species, but surprisingly few studies have globally examined the diurnal rhythm of gene expression with changes in day length. Using a cost-effective 3'-Tag RNA sequencing strategy, we characterize 9,010 photoperiod responsive genes with strict statistical testing across a diurnal time series in the C4 perennial grass, Panicum hallii. We show that the vast majority of photoperiod responses are driven by complex interactions between day length and sampling periods. A fine-scale contrast analysis at each sampling time revealed a detailed picture of the temporal reprogramming of cis-regulatory elements and biological processes under short- and long-day conditions. Phase shift analysis reveals quantitative variation among genes with photoperiod-dependent diurnal patterns. In addition, we identify three photoperiod enriched transcription factor families with key genes involved in photoperiod flowering regulatory networks. Finally, coexpression networks analysis of GIGANTEA homolog predicted 1,668 potential coincidence partners, including five well-known GI-interacting proteins. Our results not only provide a resource for understanding the mechanisms of photoperiod regulation in perennial grasses but also lay a foundation to increase biomass yield in biofuel crops.

Life history theory predicts that the intensity of selection declines with age, and this trend should impact how genes expressed at different ages evolve. Here we find consistent relationships between a gene’s age of expression and patterns of molecular evolution in two mammals (the human Homo sapiens and the mouse Mus musculus) and two insects (the malaria mosquito Anopheles gambiae and the fruit fly Drosophila melanogaster). When expressed later in life, genes fix nonsynonymous mutations more frequently, are more polymorphic for nonsynonymous mutations, and have shorter evolutionary lifespans, relative to those expressed early. The latter pattern is explained by a simple evolutionary model. Further, early-expressed genes tend to be enriched in similar gene ontology terms across species, while late-expressed genes show no such consistency. In humans, late-expressed genes are more likely to be linked to cancer and to segregate for dominant disease-causing mutations. Last, the effective strength of selection (Nes) decreases and the fraction of beneficial mutations increases with a gene’s age of expression. These results are consistent with the diminishing efficacy of purifying selection with age, as proposed by Medawar’s classic hypothesis for the evolution of senescence, and provide links between life history theory and molecular evolution.

In many insects, X-linked inversions fix at a higher rate and are much less polymorphic than autosomal inversions. Here we report that in Drosophila, X-linked inversions also capture 67% more genes. We estimated the number of genes captured through an Approximate Bayesian Computational (ABC) analysis of gene orders in 9 species of Drosophila. X-linked inversions fixed with a significantly larger gene content. Further, X-linked inversions of intermediate size enjoy highest fixation rate, while the fixation rate of autosomal inversions decreases with size. A less detailed analysis in Anopheles suggests a similar pattern holds in mosquitoes. We develop a population genetic model that assumes the fitness effects of inversions scale with the number of genes captured. We show that the same conditions that lead to a higher fixation rate also produce a larger size for inversions on the X.

Recombination often differs markedly between males and females. Here we present the first analysis of sex-specific recombination in Gasterosteus sticklebacks. Using whole-genome sequencing of 15 crosses between G. aculeatus and G. nipponicus, we localized 698 crossovers with a median resolution of 2.3 kb. We also used a bioinformatic approach to infer historical sex-averaged recombination patterns for both species. Recombination is greater in females than males on all chromosomes, and overall map length is 1.64 times longer in females. The locations of crossovers differ strikingly between sexes. Crossovers cluster toward chromosome ends in males, but are distributed more evenly across chromosomes in females. Suppression of recombination near the centromeres in males causes crossovers to cluster at the ends of long arms in acrocentric chromosomes, and greatly reduces crossing over on short arms. The effect of centromeres on recombination is much weaker in females. Genomic differentiation between G. aculeatus and G. nipponicus is strongly correlated with recombination rate, and patterns of differentiation along chromosomes are strongly influenced by male-specific telomere and centromere effects. We found no evidence for fine-scale correlations between recombination and local gene content in either sex. We discuss hypotheses for the origin of sexual dimorphism in recombination and its consequences for sexually antagonistic selection and sex chromosome evolution.

Intersexual genetic correlations are expected to constrain the evolution of sexual dimorphic traits, including the degree of sex-biased gene expression. Consistent with that expectation, studies in fruit flies and birds have reported that genes whose expression has a strong intersexual genetic correlation (rMF) show a lower level of sex-biased expression (SBE). However, it is known that both rMF and SBE can be affected by the environment. It is therefore unclear whether there is a consistent relationship between these 2 quantities across multiple environments. In this paper, we study this relationship in the African malaria mosquito Anopheles gambiae. We show that both rMF and SBE change between environments. The change in SBE across environments is significantly correlated with dN/dS: greater changes in SBE are associated with higher values of dN/dS. Furthermore, the relationship between rMF and SBE is sensitive to the environment. We conclude that this relationship is sufficiently plastic that environmental effects should be considered in future studies.

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing the cell-to-cell variation and cellular dynamics in populations which appear homogeneous otherwise in basic and translational biological research. However, significant challenges arise in the analysis of scRNA-seq data, including the low signal-to-noise ratio with high data sparsity, potential batch effects, scalability problems when hundreds of thousands of cells are to be analyzed among others. The inherent complexities of scRNA-seq data and dynamic nature of cellular processes lead to suboptimal performance of many currently available algorithms, even for basic tasks such as identifying biologically meaningful heterogeneous subpopulations. In this study, we developed the Latent Cellular Analysis (LCA), a machine learning–based analytical pipeline that combines cosine-similarity measurement by latent cellular states with a graph-based clustering algorithm. LCA provides heuristic solutions for population number inference, dimension reduction, feature selection, and control of technical variations without explicit gene filtering. We show that LCA is robust, accurate, and powerful by comparison with multiple state-of-the-art computational methods when applied to large-scale real and simulated scRNA-seq data. Importantly, the ability of LCA to learn from representative subsets of the data provides scalability, thereby addressing a significant challenge posed by growing sample sizes in scRNA-seq data analysis.

Photoperiod is a key environmental cue affecting flowering and biomass traits in plants. Key components of the photoperiodic flowering pathway have been identified in many species, but surprisingly few studies have globally examined the diurnal rhythm of gene expression with changes in day length. Using a cost-effective 3'-Tag RNA sequencing strategy, we characterize 9,010 photoperiod responsive genes with strict statistical testing across a diurnal time series in the C

Chromosomal inversions play an important role in local adaptation. Strong evidence exists of selection acting on inversions, but the genic targets inside them are largely unknown. Here we take a systems genetics approach, analyzing two inversion systems implicated in climatic adaption by Anopheles gambiae. We profiled physiology, behavior, and transcription in four different karyotypic backgrounds derived from a common parental colony. Acclimation to different climatic regimes resulted in pervasive inversion-driven phenotypic differences whose magnitude and direction depended upon gender, environment, and epistatic interactions between inversions. Inversion-affected loci were significantly enriched inside inversions, as predicted by local adaptation theory. Drug perturbation supported lipid homeostasis and energy balance as inversion-regulated functions, a finding supported by research on climatic adaptation in multiple systems.

Inversion polymorphisms in the African malaria vector Anopheles gambiae segregate along climatic gradients of aridity. Despite indirect evidence of their adaptive significance, little is known of the phenotypic targets of selection or the underlying genetic mechanisms. Here we adopt a systems genetics approach to explore the interaction of two inversions on opposite arms of chromosome 2 with gender, climatic conditions, and one another. We measure organismal traits and transcriptional profiles in 8-d-old adults of both sexes and four alternative homokaryotypic classes reared under two alternative climatic regimes. We show that karyotype strongly influences both organismal traits and transcriptional profiles but that the strength and direction of the effects depend upon complex interactions with gender and environmental conditions and between inversions on independent arms. Our data support the suppressed recombination model for the role of inversions in local adaptation, and—supported by transcriptional and physiological measurements following perturbation with the drug rapamycin—suggest that one mechanism underlying their adaptive role may be the maintenance of energy homeostasis.

The interaction between extrinsic factors and intrinsic signal strength governs thymocyte development, but the mechanisms linking them remain elusive. We report that mechanistic target of rapamycin complex 1 (mTORC1) couples microenvironmental cues with metabolic programs to orchestrate the reciprocal development of two fundamentally distinct T cell lineages, the αβ and γδ T cells. Developing thymocytes dynamically engage metabolic programs including glycolysis and oxidative phosphorylation, as well as mTORC1 signaling. Loss of RAPTOR-mediated mTORC1 activity impairs the development of αβ T cells but promotes γδ T cell generation, associated with disrupted metabolic remodeling of oxidative and glycolytic metabolism. Mechanistically, we identify mTORC1-dependent control of reactive oxygen species production as a key metabolic signal in mediating αβ and γδ T cell development, and perturbation of redox homeostasis impinges upon thymocyte fate decisions and mTORC1-associated phenotypes. Furthermore, single-cell RNA sequencing and genetic dissection reveal that mTORC1 links developmental signals from T cell receptors and NOTCH to coordinate metabolic activity and signal strength. Our results establish mTORC1-driven metabolic signaling as a decisive factor for reciprocal αβ and γδ T cell development and provide insight into metabolic control of cell signaling and fate decisions.

Single-cell RNA sequencing has emerged as a powerful tool for characterizing the cell-to-cell variation and dynamics. We present Latent Cellular Analysis (LCA), a machine learning– based analytical pipeline that features a dual-space model search with inference of latent cellular states, control of technical variations, cosine similarity measurement, and spectral clustering. LCA has proved to be robust, accurate, scalable, and powerful in revealing subtle diversity in cell populations.

A series of experiments are conducted to study suppression effect of multilayer wire-mesh structure on methane-air mixture explosion in linked vessels. Explosion suppression effect is analyzed for explosion suppression structures with different layers and meshes. The most reasonable multilayer wire-mesh structure is obtained. The multilayer wire-mesh has a greater impact on explosion intensity in the big vessel than that in the small vessel. The combination of different layer number and mesh number has different explosion suppression effect on explosion. Mesh number has little effect on explosion pressure in both vessels when the layers are few. When the layers are more, the explosion pressure in both vessels is greatly impacted by mesh number. Under the condition of the same mesh number, the more the layers are, the better the explosion suppression effect. 5 and 7 are the critical explosion suppression layer number for 40-mesh and 60-mesh wire-mesh structure, respectively. Compared with 5-layer 40-mesh wire-mesh structure, the effect of 7-layer 60-mesh wire-mesh structure on explosion suppression is better. So, in actual explosion protection design, the optional explosion suppression structure should be decided by taking into account of the comprehensive effect of layer number and mesh number. © 2015 American Institute of Chemical Engineers Process Saf Prog, 2015

Although freshwater (FW) is the ancestral habitat for larval mosquitoes, multiple species independently evolved the ability to survive in saltwater (SW). Here, we use quantitative trait locus (QTL) mapping to investigate the genetic architecture of osmoregulation in Anopheles mosquitoes, vectors of human malaria. We analyzed 1134 backcross progeny from a cross between the obligate FW species An. coluzzii, and its closely related euryhaline sibling species An. merus. Tests of 2387 markers with Bayesian interval mapping and machine learning (random forests) yielded six genomic regions associated with SW tolerance. Overlap in QTL regions from both approaches enhances confidence in QTL identification. Evidence exists for synergistic as well as disruptive epistasis among loci. Intriguingly, one QTL region containing ion transporters spans the 2Rop chromosomal inversion that distinguishes these species. Rather than a simple trait controlled by one or a few loci, our data are most consistent with a complex, polygenic mode of inheritance.

Y chromosomes control essential male functions in many species, including sex determination and fertility. However, because of obstacles posed by repeat-rich heterochromatin, knowledge of Y chromosome sequences is limited to a handful of model organisms, constraining our understanding of Y biology across the tree of life. Here, we leverage long single-molecule sequencing to determine the content and structure of the nonrecombining Y chromosome of the primary African malaria mosquito, Anopheles gambiae. We find that the An. gambiae Y consists almost entirely of a few massively amplified, tandemly arrayed repeats, some of which can recombine with similar repeats on the X chromosome. Sex-specific genome resequencing in a recent species radiation, the An. gambiae complex, revealed rapid sequence turnover within An. gambiae and among species. Exploiting 52 sex-specific An. gambiae RNA-Seq datasets representing all developmental stages, we identified a small repertoire of Y-linked genes that lack X gametologs and are not Y-linked in any other species except An. gambiae, with the notable exception of YG2, a candidate male-determining gene. YG2 is the only gene conserved and exclusive to the Y in all species examined, yet sequence similarity to YG2 is not detectable in the genome of a more distant mosquito relative, suggesting rapid evolution of Y chromosome genes in this highly dynamic genus of malaria vectors. The extensive characterization of the An. gambiae Y provides a long-awaited foundation for studying male mosquito biology, and will inform novel mosquito control strategies based on the manipulation of Y chromosomes.

The association between fitness-related phenotypic traits and an environmental gradient offers one of the best opportunities to study the interplay between natural selection and migration. In cases in which specific genetic variants also show such clinal patterns, it may be possible to uncover the mutations responsible for local adaptation. The malaria vector, Anopheles gambiae, is associated with a latitudinal cline in aridity in Cameroon; a large inversion on chromosome 2L of this mosquito shows large differences in frequency along this cline, with high frequencies of the inverted karyotype present in northern, more arid populations and an almost complete absence of the inverted arrangement in southern populations. Here we use a genome resequencing approach to investigate patterns of population divergence along the cline. By sequencing pools of individuals from both ends of the cline as well as in the center of the cline—where the inversion is present in intermediate frequency—we demonstrate almost complete panmixia across collinear parts of the genome and high levels of differentiation in inverted parts of the genome. Sequencing of separate pools of each inversion arrangement in the center of the cline reveals large amounts of gene flux (i.e., gene conversion and double crossovers) even within inverted regions, especially away from the inversion breakpoints. The interplay between natural selection, migration, and gene flux allows us to identify several candidate genes responsible for the match between inversion frequency and environmental variables. These results, coupled with similar conclusions from studies of clinal variation in Drosophila, point to a number of important biological functions associated with local environmental adaptation.

The African malaria mosquito Anopheles gambiae is polymorphic for chromosomal inversion 2La, whose frequency strongly correlates with degree of aridity across environmental gradients. Recent physiological studies have associated 2La with resistance to desiccation in adults and thermal stress in larvae, consistent with its proposed role in aridity tolerance. However, the genetic basis of these traits remains unknown. To identify genes that could be involved in the differential response to thermal stress, we compared global gene expression profiles of heat hardened 2La or 2L+a larvae at three time points, for up to eight hours following exposure to the heat stress. Treatment and control time series, replicated four times, revealed a common and massive induction of a core set of heat shock genes regardless of 2La orientation. However, clear differences between the 2La and 2L+a arrangements emerged at the earliest (0.25 h) time point, in the intensity and nature of the stress response. Overall, 2La was associated with the more aggressive response: larger numbers of genes were heat responsive and up-regulated. Transcriptionally induced genes were enriched for functions related to ubiquitin-proteasomal degradation, chaperoning, and energy metabolism. The more muted transcriptional response of 2L+a was largely repressive, including genes involved in proteolysis and energy metabolism. These results may help explain the maintenance of the 2La inversion polymorphism in An. gambiae, as the survival benefits offered by high thermal sensitivity in harsh climates could be offset by the metabolic costs of such a drastic response in more equable climates.

Single-cell RNA sequencing (scRNA-seq) emerges as a powerful tool to characterize cell-to-cell variation and dynamics in a seemingly homogenous population. Efficient and affordable, scRNA-seq is gaining in popularity in both basic and translational biological research areas. However, significant challenges arise in the analysis of scRNA-seq data, including low signal-to-noise ratio with high data sparsity, rising scalability hurdles with hundreds of thousands of cells, and more. Due to inherent complexities in scRNA-seq data, the performance of currently available algorithms may not always be optimal even for fundamental tasks such as identifying heterogeneous subpopulations in the data. In this study, we developed Latent Cellular Analysis (LCA), a machine learning based analytical pipeline that combines similarity measurement by latent cellular states with a graph-based clustering algorithm. LCA features a dual-space model search for both the optimal number of subpopulations and the informative cellular states distinguishing them. LCA provides heuristic solutions for population number inference, dimension reduction, feature selection and confounding factor removal without explicit gene filtering. LCA has proved to be robust, accurate and powerful by comparison to multiple state-of-the-art computational methods on large-scale real and simulated scRNA-seq data. Importantly, LCA's ability to learn from representative subsets of the data provides scalability, thereby addressing a significant challenge for growing sample size in scRNA-seq data analysis. Citation Format: Changde Cheng, John Easton, Celeste Rosencrance, Yan Li, Bensheng Ju, Wenan Chen, Xiang Chen. LCA: A robust and scalable algorithm to reveal subtle diversity in large-scale single-cell RNA-Seq data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5297.

Evolution of osmoregulatory systems is a key factor in the transition of species between fresh- and saltwater habitats. Anopheles coluzzii and Anopheles merus are stenohaline and euryhaline malaria vector mosquitoes belonging to a larger group of sibling species, the Anopheles gambiae complex, which radiated in Africa within the last 2 million years. Comparative ecological genomics of these vector species can provide insight into the mechanisms that permitted the rapid radiation of this species complex into habitats of contrasting salinity. Here, we use RNA-Seq to investigate gene expression differences between An. coluzzii and An. merus after briefly exposing both young and old larval instars of each species to either saltwater (SW) or freshwater (FW). Our study aims to identify candidate genes and pathways responsible for the greater SW tolerance of An. merus. Our results are congruent with the ability of gene induction to mediate salinity tolerance, with both species showing increasing amounts of differential gene expression between SW and FW as salt concentrations increase. Besides ion transporters such as AgAE2 that may serve as effectors for osmoregulation, we also find mitogen-activated protein kinases that may serve in a phosphorylation signalling pathway responding to salinity, and report potential cross-talk between the mosquito immune response and osmoregulation. This study provides a key step towards applying the growing molecular knowledge of these malaria vectors to improve understanding of their ecological tolerances and habitat occupancy.

Background Principal malaria vectors in Africa, An. gambiae and An. coluzzii, share an inversion polymorphism on the left arm of chromosome 2 (2La/2L+a) that is distributed non-randomly in the environment. Genomic sequencing studies support the role of strong natural selection in maintaining steep clines in 2La inversion frequency along environmental gradients of aridity, and physiological studies have directly implicated 2La in heat and desiccation tolerance, but the precise genetic basis and the underlying behavioral and physiological mechanisms remain unknown. As the insect cuticle is the primary barrier to water loss, differences in cuticle thickness and/or epicuticular waterproofing associated with alternative 2La arrangements might help explain differences in desiccation resistance. Methods To test that hypothesis, two subcolonies of both An. gambiae and An. coluzzii were established that were fixed for alternative 2La arrangements (2La or 2L+a) on an otherwise homosequential and shared genetic background. Adult mosquitoes reared under controlled environmental conditions (benign or arid) for eight days post-eclosion were collected and analyzed. Measurements of cuticle thickness were made based on scanning electron microscopy, and cuticular hydrocarbon (CHC) composition was evaluated by gas chromatography–mass spectrometry. Results After removing the allometric effects of body weight, differences in mean cuticle thickness were found between alternative 2La karyotypes, but not between alternative environments. Moreover, the thicker cuticle of the An. coluzzii 2La karyotype was contrary to the known higher rate of water loss of this karyotype relative to 2L+a. On the other hand, quantitative differences in individual CHCs and overall CHC profiles between alternative karyotypes and environmental conditions were consistent with expectation based on previous physiological studies. Conclusions Our results suggest that alternative arrangements of the 2La inversion are associated with differences in cuticle thickness and CHC composition, but that only CHC composition appears to be relevant for desiccation resistance. Differences in the CHC composition were consistent with previous findings of a lower rate of water loss for the 2L+a karyotype at eight days post-eclosion, suggesting that CHC composition is an important strategy for maintaining water balance in this genetic background, but not for 2La. Despite a higher rate of water loss at eight days, higher body water content of the 2La karyotype confers a level of desiccation resistance equivalent to that of the 2L+a karyotype.

The African malaria mosquito Anopheles gambiae is diversifying into ecotypes known as M and S forms. This process is thought to be promoted by adaptation to different larval habitats, but its genetic underpinnings remain elusive. To identify candidate targets of divergent natural selection in M and S, we performed genomewide scanning in paired population samples from Mali, followed by resequencing and genotyping from five locations in West, Central, and East Africa. Genome scans revealed a significant peak of M-S divergence on chromosome 3L, overlapping five known or suspected immune response genes. Resequencing implicated a selective target at or near the TEP1 gene, whose complement C3-like product has antiparasitic and antibacterial activity. Sequencing and allele-specific genotyping showed that an allelic variant of TEP1 has been swept to fixation in M samples from Mali and Burkina Faso and is spreading into neighboring Ghana, but is absent from M sampled in Cameroon, and from all sampled S populations. Sequence comparison demonstrates that this allele is related to, but distinct from, TEP1 alleles of known resistance phenotype. Experimental parasite infections of advanced mosquito intercrosses demonstrated a strong association between this TEP1 variant and resistance to both rodent malaria and the native human malaria parasite Plasmodium falciparum . Although malaria parasites may not be direct agents of pathogen-mediated selection at TEP1 in nature—where larvae may be the more vulnerable life stage—the process of adaptive divergence between M and S has potential consequences for malaria transmission.

In the malaria mosquito Anopheles gambiae polymorphic chromosomal inversions may play an important role in adaptation to environmental variation. Recently, we used microarray-based divergence mapping combined with targeted resequencing to map nucleotide differentiation between alternative arrangements of the 2La inversion. Here, we applied the same technique to four different polymorphic inversions on the 2R chromosome of An. gambiae. Surprisingly, divergence was much lower between alternative arrangements for all 2R inversions when compared to the 2La inversion. For one of the rearrangements, 2Ru, we successfully mapped a very small region (∼100 kb) of elevated divergence. For the other three rearrangements, we did not identify any regions of significantly high divergence, despite ample independent evidence from natural populations of geographic clines and seasonal cycling, and stable heterotic polymorphisms in laboratory populations. If these inversions are the targets of selection as hypothesized, we suggest that divergence between rearrangements may have escaped detection due to retained ancestral polymorphism in the case of the youngest 2R rearrangements and to extensive gene flux in the older 2R inversion systems that segregate in both An. gambiae and its sibling species An. arabiensis.