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Resistance to insecticides in Anopheles mosquitoes threatens the effectiveness of malaria control, but the genetics of resistance are only partially understood. We performed a large scale multi-country genome-wide association study of resistance to two widely used insecticides: deltamethrin and pirimiphos-methyl, using sequencing data from An. gambiae and An. coluzzii from ten locations in West Africa. Resistance was highly multi-genic, multi-allelic and variable between populations. While the strongest and most consistent association with deltamethrin resistance came from Cyp6aa1 , this was based on several independent copy number variants (CNVs) in An. coluzzii , and on a non-CNV haplotype in An. gambiae . For pirimiphos-methyl, signals included Ace1 , cytochrome P450s, glutathione S-transferases and the nAChR target site of neonicotinoid insecticides. The regions around Cyp9k1 and the Tep family of immune genes showed evidence of cross-resistance to both insecticides. These locally-varying, multi-allelic patterns highlight the challenges involved in genomic monitoring of resistance, and may form the basis for improved surveillance methods. Insecticide resistance in mosquitoes threatens the success of malaria control programmes. This study found that in different populations of a malaria mosquito species in West Africa, resistance is associated with different genes or different mutations in the same set of genes.

The evolution of insecticide resistance mechanisms in natural populations of Anopheles malaria vectors is a major public health concern across Africa. Using genome sequence data, we study the evolution of resistance mutations in the resistance to dieldrin locus (Rdl), a GABA receptor targeted by several insecticides, but most notably by the long-discontinued cyclodiene, dieldrin. The two Rdl resistance mutations (296G and 296S) spread across West and Central African Anopheles via two independent hard selective sweeps that included likely compensatory nearby mutations, and were followed by a rare combination of introgression across species (from A. gambiae and A. arabiensis to A. coluzzii) and across nonconcordant karyotypes of the 2La chromosomal inversion. Rdl resistance evolved in the 1950s as the first known adaptation to a large-scale insecticide-based intervention, but the evolutionary lessons from this system highlight contemporary and future dangers for management strategies designed to combat development of resistance in malaria vectors.

To keep ahead of the evolution of resistance to insecticides in mosquitoes, national malaria control programmes must make use of a range of insecticides, both old and new, while monitoring resistance mechanisms. The outdoor-biting malaria vector Anopheles arabiensis is of increasing concern for malaria transmission because it is apparently less susceptible to many indoor control interventions, yet knowledge of its mechanisms of resistance remains limited. Furthermore, comparatively little is known in general about resistance to non-pyrethroid insecticides such as pirimiphos-methyl (PM), which are crucial for effective control in the context of globally high resistance to pyrethroids. We performed a genome-wide association study to determine the molecular mechanisms of resistance to the pyrethroid deltamethrin (commonly used in bednets) and PM (widespread use for indoor spraying), in An . arabiensis from 2 regions in Tanzania. Genomic regions of positive selection in these populations were largely driven by copy number variants (CNVs) in gene families involved in metabolic resistance. We found evidence of a new gene cluster involved in resistance to PM, identifying a strong selective sweep tied to a CNV in the carboxylesterase genes Coeae2g - Coeae6g . Using complementary data from another malaria vector, An . coluzzii , in Ghana, we show that copy number at this locus is significantly associated with PM resistance. Similarly, for deltamethrin, resistance was strongly associated with a novel CNV allele in the Cyp6aa / Cyp6p cluster ( Cyp6aap _Dup33). Against this background of metabolic resistance, resistance caused by mutations in the insecticide target sites was very rare or absent. Mutations in the pyrethroid target site Vgsc were at very low frequency in Tanzania, yet combining these samples with 3 An . arabiensis individuals from West Africa revealed a startling evolutionary diversity, with up to 5 independent origins of Vgsc -995 mutations found within just 8 haplotypes. Thus, despite having been first recorded over 10 years ago, Vgsc resistance mutations in Tanzanian An . arabiensis have remained at stable low frequencies. Overall, our results provide a new copy number marker for monitoring resistance to PM in malaria mosquitoes, and reveal the complex picture of resistance patterns in An . arabiensis .

Vector population control using insecticides is a key element of current strategies to prevent malaria transmission in Africa. The introduction of effective insecticides, such as the organophosphate pirimiphos-methyl, is essential to overcome the recurrent emergence of resistance driven by the highly diverse Anopheles genomes. Here, we use a population genomic approach to investigate the basis of pirimiphos-methyl resistance in the major malaria vectors Anopheles gambiae and A . coluzzii . A combination of copy number variation and a single non-synonymous substitution in the acetylcholinesterase gene, Ace1 , provides the key resistance diagnostic in an A . coluzzii population from Côte d’Ivoire that we used for sequence-based association mapping, with replication in other West African populations. The Ace1 substitution and duplications occur on a unique resistance haplotype that evolved in A . gambiae and introgressed into A . coluzzii , and is now common in West Africa primarily due to selection imposed by other organophosphate or carbamate insecticides. Our findings highlight the predictive value of this complex resistance haplotype for phenotypic resistance and clarify its evolutionary history, providing tools to for molecular surveillance of the current and future effectiveness of pirimiphos-methyl based interventions.

Pyrethroid-impregnated bed nets have driven considerable reductions in malaria-associated morbidity and mortality in Africa since the beginning of the century 1 . The intense selection pressure exerted by bed nets has precipitated widespread and escalating resistance to pyrethroids in African Anopheles populations, threatening to reverse the gains that been made by malaria control 2 . Here we show that expression of a sensory appendage protein (SAP2), which is enriched in the legs, confers pyrethroid resistance to Anopheles gambiae . Expression of SAP2 is increased in insecticide-resistant populations and is further induced after the mosquito comes into contact with pyrethroids. SAP2 silencing fully restores mortality of the mosquitoes, whereas SAP2 overexpression results in increased resistance, probably owing to high-affinity binding of SAP2 to pyrethroid insecticides. Mining of genome sequence data reveals a selective sweep near the SAP2 locus in the mosquito populations of three West African countries (Cameroon, Guinea and Burkina Faso) with the observed increase in haplotype-associated single-nucleotide polymorphisms mirroring the increasing resistance of mosquitoes to pyrethroids reported in Burkina Faso. Our study identifies a previously undescribed mechanism of insecticide resistance that is likely to be highly relevant to malaria control efforts. The leg-enriched sensory appendage protein, SAP2, confers pyrethroid resistance to Anopheles gambiae , through high-affinity binding of pyrethroid insecticides; an observed selective sweep in field mosquitoes mirrors the increasing resistance reported in Africa.

Background 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD) is the most potent congener of the dioxin class of environmental contaminants. Exposure to TCDD causes a wide range of toxic outcomes, ranging from chloracne to acute lethality. The severity of toxicity is highly dependent on the aryl hydrocarbon receptor (AHR). Binding of TCDD to the AHR leads to changes in transcription of numerous genes. Studies evaluating the transcriptional changes brought on by TCDD may provide valuable insight into the role of the AHR in human health and disease. We therefore compiled a collection of transcriptomic datasets that can be used to aid the scientific community in better understanding the transcriptional effects of ligand-activated AHR. Results Specifically, we have created a datasets package – TCDD.Transcriptomics – for the R statistical environment, consisting of 63 unique experiments comprising 377 samples, including various combinations of 3 species (human derived cell lines, mouse and rat), 4 tissue types (liver, kidney, white adipose tissue and hypothalamus) and a wide range of TCDD exposure times and doses. These datasets have been fully standardized using consistent preprocessing and annotation packages (available as of September 14, 2015). To demonstrate the utility of this R package, a subset of “AHR-core” genes were evaluated across the included datasets. Ahrr , Nqo1 and members of the Cyp family were significantly induced following exposure to TCDD across the studies as expected while Aldh3a1 was induced specifically in rat liver. Inmt was altered only in liver tissue and primarily by rat-AHR. Conclusions Analysis of the “AHR-core” genes demonstrates a continued need for studies surrounding the impact of AHR-activity on the transcriptome; genes believed to be consistently regulated by ligand-activated AHR show surprisingly little overlap across species and tissues. Until now, a comprehensive assessment of the transcriptome across these studies was challenging due to differences in array platforms, processing methods and annotation versions. We believe that this package, which is freely available for download ( http://labs.oicr.on.ca/boutros-lab/tcdd-transcriptomics ) will prove to be a highly beneficial resource to the scientific community evaluating the effects of TCDD exposure as well as the variety of functions of the AHR.

SeqControl uses 15 quality metrics of high-throughput sequencing experiments to predict how much sequencing is needed to reach a desired depth of coverage. As high-throughput sequencing continues to increase in speed and throughput, routine clinical and industrial application draws closer. These 'production' settings will require enhanced quality monitoring and quality control to optimize output and reduce costs. We developed SeqControl, a framework for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, basewise coverage and basewise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references, we derived multivariate models that predict sequencing quality and depth. SeqControl robustly predicted how much sequencing was required to reach a given coverage depth (area under the curve (AUC) = 0.993), accurately classified clinically relevant formalin-fixed, paraffin-embedded samples, and made predictions from as little as one-eighth of a sequencing lane (AUC = 0.967). These techniques can be immediately incorporated into existing sequencing pipelines to monitor data quality in real time. SeqControl is available at http://labs.oicr.on.ca/Boutros-lab/software/SeqControl/ .

We describe the presentation, management, and clinical outcome of a massive acinic cell carcinoma of the parotid gland. The primary tumor and blood underwent exome sequencing which revealed deletions in CDKN2A as well as PPP1R13B, which induces p53. A damaging nonsynonymous mutation was noted in EP300, a histone acetylase which plays a role in cellular proliferation. This study provides the first insights into the genetic underpinnings of this cancer. Future large-scale efforts will be necessary to define the mutational landscape of salivary gland malignancies to identify therapeutic targets and biomarkers of treatment failure.

Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates. Genomic analyses of localized, non-indolent prostate cancer identify recurrent aberrations that can predict relapse, and also highlight differences between early prostate cancer and metastatic, castration-resistant disease. Genomics of localized prostate cancer Robert Bristow, Paul Boutros and colleagues report genomic analyses of localized, non-indolent prostate cancer, which is a common disease state at initial clinical presentation that shows intermediate risk and cure rates. The analyses include 200 whole-genome and 477 whole-exome sequences of localized prostate cancer tumours, and analyses of copy-number alterations, genomic rearrangements and methylation. The authors highlight differences in mutational profiles between localized intermediate risk and metastatic, castrate-resistant prostate cancer.

Genome sequencing analyses from 765 specimens of Anopheles gambiae and Anopheles coluzzii from 15 locations across Africa characterize patterns of gene flow and variations in population size, and provide a resource for studying the evolution of natural malaria vector populations. Mosquito genetic diversity dataset Anopheles gambiae is the primary mosquito vector responsible for the transmission of malaria in most of sub-Saharan Africa. Alistair Miles, Dominic Kwiatkowski and colleagues report analyses from the Anopheles gambiae 1000 Genomes Project (Ag1000G), including low-coverage genome sequences of 765 specimens of Anopheles gambiae and Anopheles coluzzii , caught in the wild at 15 locations across 8 countries in Africa. The authors analyse genetic variation, finding a high level of genetic diversity in these populations, and characterize patterns of gene flow and variations in population size. These datasets provide a resource for studies into the evolution of malaria vector populations that could guide control strategies and be used to address problems such as the evolution of insecticide resistance. The sustainability of malaria control in Africa is threatened by the rise of insecticide resistance in Anopheles mosquitoes, which transmit the disease 1 . To gain a deeper understanding of how mosquito populations are evolving, here we sequenced the genomes of 765 specimens of Anopheles gambiae and Anopheles coluzzii sampled from 15 locations across Africa, and identified over 50 million single nucleotide polymorphisms within the accessible genome. These data revealed complex population structure and patterns of gene flow, with evidence of ancient expansions, recent bottlenecks, and local variation in effective population size. Strong signals of recent selection were observed in insecticide-resistance genes, with several sweeps spreading over large geographical distances and between species. The design of new tools for mosquito control using gene-drive systems will need to take account of high levels of genetic diversity in natural mosquito populations.