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Resistance to insecticides inAnophelesmosquitoes threatens the effectiveness of the most widespread tools currently used to control malaria. The genetic underpinnings of resistance are still only partially understood, with much of the variance in resistance phenotype left unexplained. We performed a multi-country large scale genome-wide association study of resistance to two insecticides widely used in malaria control: deltamethrin and pirimiphos-methyl. Using a bioassay methodology designed to maximise the phenotypic difference between resistant and susceptible samples, we sequenced 969 phenotyped femaleAn. gambiaeandAn. coluzziifrom ten locations across four countries in West Africa (Benin, Côte d’Ivoire, Ghana and Togo), identifying single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) segregating in the populations. The patterns of resistance association were highly multiallelic and variable between populations, with different genomic regions contributing to resistance, as well as different mutations within a given region. While the strongest and most consistent association with deltamethrin resistance came from the region aroundCyp6aa1, this resistance was based on a combination of several independent CNVs inAn. coluzzii, and on a non-CNV bearing haplotype inAn. gambiae. Further signals involved a range of cytochrome P450, mitochondrial, and immunity genes. Similarly, for pirimiphos-methyl, while the strongest signal came from the region ofAce1, more widespread signals included cytochrome P450s, glutathione S-transferases, and a subunit of thenAChRtarget site of neonicotinoid insecticides. The regions aroundCyp9k1and theTepfamily of immune genes were associated with resistance to both insecticide classes, suggesting possible cross-resistance mechanisms. These locally-varying, multigenic and multiallelic patterns highlight the challenges involved in genomic monitoring and surveillance of resistance, and form the basis for improvement of methods used to detect and predict resistance. Based on simulations of resistance variants, we recommend that yet larger scale studies, exceeding 500 phenotyped samples per population, are required to better identify associated genomic regions.

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 and 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 probably due to cross-resistance with previously used insecticides. Our findings highlight the phenotypic value of this complex resistance haplotype and clarify its evolutionary history, providing tools to understand the current and future effectiveness of pirimiphos-methyl based interventions.

The evolution of insecticide resistance mechanisms in natural populations ofAnophelesmalaria vectors is a major public health concern across Africa. Using genome sequence data, we study the evolution of resistance mutations in theresistance to dieldrin locus(Rdl), a GABA receptor targeted by several insecticides, but most notably by the long-discontinued cyclodiene, dieldrin. The twoRdlresistance mutations (296Gand296S) spread across West and Central AfricanAnophelesvia two independent hard selective sweeps that included likely compensatory nearby mutations, and were followed by a rare combination of introgression across species (fromA. gambiaeandA. arabiensistoA. coluzzii) and across non-concordant karyotypes of the 2La chromosomal inversion.Rdlresistance 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.

BackgroundPolymorphisms in the copy number of a genetic region can influence gene expression, coding sequence and zygosity, making them powerful actors in the evolutionary process. Copy number variants (CNVs) are however understudied, being more difficult to detect than single nucleotide polymorphisms. We take advantage of the intense selective pressures on the major malaria vector Anopheles gambiae, caused by the widespread use of insecticides for malaria control, to investigate the role of CNVs in the evolution of insecticide resistance.ResultsUsing the whole-genome sequencing data from 1142 samples in the An. gambiae 1000 genomes project, we identified 1557 independent increases in copy number, encompassing a total of 267 genes, which were enriched for gene families linked to metabolic insecticide resistance. The five major candidate genes for metabolic resistance were all found in at least one CNV, and were often the target of multiple independent CNVs, reaching as many as 16 CNVs in Cyp9k1. These CNVs have furthermore been spreading due to positive selection, indicated by high local CNV frequencies and extended haplotype homozygosity.ConclusionsOur results demonstrate the importance of CNVs in the response to selection, with CNVs being closely associated with genes involved in the evolution of resistance to insecticides, highlighting the urgent need to identify their relative contributions to resistance and to track their spread as the application of insecticide in malaria endemic countries intensifies. Our detailed descriptions of CNVs found across the species range provides the tools to do so.

Resistance to pyrethroid insecticides is a major concern for malaria vector control, because these are the compounds used in almost all insecticide-treated bed-nets (ITNs), and are also widely used for indoor residual spraying (IRS). Pyrethroids target the voltage-gated sodium channel (VGSC), an essential component of the mosquito nervous system, but substitutions in the amino acid sequence can disrupt the activity of these insecticides, inducing a resistance phenotype. Here we use Illumina whole-genome sequence data from phase 1 of theAnopheles gambiae1000 Genomes Project (Ag1000G) to provide a comprehensive account of genetic variation in theVgscgene in mosquito populations from eight African countries. In addition to the three known resistance alleles, we describe 20 non-synonymous nucleotide substitutions at appreciable frequency in one or more populations that are previously unknown inAnophelesmosquitoes. Thirteen of these novel alleles were found to occur almost exclusively on haplotypes carrying the knownL995Fresistance allele (L1014F inMusca domesticuscodon numbering), and may enhance or compensate for theL995Fresistance pheno-type. A novel mutation I1527T, which is adjacent to a predicted pyrethroid binding site, was found in tight linkage with either of two alleles causing a V402L substitution, similar to a combination of substitutions found to cause pyrethroid resistance in several other insect species. We analyse the genetic backgrounds on which non-synonymous alleles are found, to determine which alleles have experienced recent positive selection, and to refine our understanding of the spread of resistance between species and geographical locations. We describe twelve distinct haplotype groups with evidence of recent positive selection, five of which carry the knownL995Fresistance allele, five of which carry the knownL995Sresistance allele, one of which carries the novel I1527T allele, and one of which carries a novel M490I allele. Seven of these groups are localised to a single geographical location, and five comprise haplotypes from different countries, in one case separated by over 3000 km, providing new information about the geographical distribution and spread of resistance. We also find evidence for multiple introgression events transmitting resistance alleles betweenAn. gambiaeandAn. coluzzii. We identify markers that could be used to design high-throughput, low-cost genetic assays for improved surveillance of pyrethroid resistance in the field. Our results demonstrate that the molecular basis of target-site pyrethroid resistance in malaria vectors is more complex than previously appreciated, and provide a foundation for the development of new genetic tools to track the spread insecticide resistance and improve the design of strategies for insecticide resistance management.

The sustainability of malaria control in Africa is threatened by rising levels of insecticide resistance, and new tools to prevent malaria transmission are urgently needed. To gain a better understanding of the mosquito populations that transmit malaria, we sequenced the genomes of 765 wild specimens ofAnopheles gambiaeandAnopheles coluzziisampled from 15 locations across Africa. The data reveal high levels of genetic diversity, with over 50 million single nucleotide polymorphisms across the 230 Mbp genome. We observe complex patterns of population structure and marked variations in local population size, some of which may be due at least in part to malaria control interventions. Insecticide resistance genes show strong signatures of recent selection associated with multiple independent mutations spreading over large geographical distances and between species. The genetic variability of natural populations substantially reduces the target space for novel gene-drive strategies for mosquito control. This large dataset provides a foundation for tracking the emergence and spread of insecticide resistance and developing new vector control tools.

The emergence of next generation DNA sequencing technology is enabling high-resolution cancer genome analysis. Large-scale projects like the International Cancer Genome Consortium (ICGC) are systematically scanning cancer genomes to identify recurrent somatic mutations. Second generation DNA sequencing, however, is still an evolving technology and procedures, both experimental and analytical, are constantly changing. Thus the research community is still defining a set of best practices for cancer genome data analysis, with no single protocol emerging to fulfil this role. Here we describe an extensive benchmark exercise to identify and resolve issues of somatic mutation calling. Whole genome sequence datasets comprising tumor-normal pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, were shared within the ICGC and submissions of somatic mutation calls were compared to verified mutations and to each other. Varying strategies to call mutations, incomplete awareness of sources of artefacts, and even lack of agreement on what constitutes an artefact or real mutation manifested in widely varying mutation call rates and somewhat low concordance among submissions. We conclude that somatic mutation calling remains an unsolved problem. However, we have identified many issues that are easy to remedy that are presented here. Our study highlights critical issues that need to be addressed before this valuable technology can be routinely used to inform clinical decision-making.

As next-generation sequencing becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Through the International Cancer Genome Consortium (ICGC), we compared sequencing pipelines at five independent centers (CNAG, DKFZ, OICR, RIKEN and WTSI) using a single tumor-blood DNA pair. Analyses by each center and with one standardized algorithm revealed significant discrepancies. Although most pipelines performed well for coding mutations, library preparation methods and sequencing coverage metrics clearly influenced downstream results. PCR-free methods showed reduced GC-bias and more even coverage. Increasing sequencing depth to ~100x (two- to three-fold higher than current standards) showed a benefit, as long as the tumor:control coverage ratio remained balanced. To become part of routine clinical care, high-throughput sequencing must be globally compatible and comparable. This benchmarking exercise has highlighted several fundamental parameters to consider in this regard, which will allow for better optimization and planning of both basic and translational studies.

Mosquito control remains a central pillar of efforts to reduce malaria burden in sub-Saharan Africa. However, insecticide resistance is entrenched in malaria vector populations, and countries with a high malaria burden face a daunting challenge to sustain malaria control with a limited set of surveillance and intervention tools. Here we report on the second phase of a project to build an open resource of high-quality data on genome variation among natural populations of the major African malaria vector species Anopheles gambiae and Anopheles coluzzii. We analyzed whole genomes of 1142 individual mosquitoes sampled from the wild in 13 African countries, as well as a further 234 individuals comprising parents and progeny of 11 laboratory crosses. The data resource includes high-confidence single-nucleotide polymorphism (SNP) calls at 57 million variable sites, genome-wide copy number variation (CNV) calls, and haplotypes phased at biallelic SNPs. We use these data to analyze genetic population structure and characterize genetic diversity within and between populations. We illustrate the utility of these data by investigating species differences in isolation by distance, genetic variation within proposed gene drive target sequences, and patterns of resistance to pyrethroid insecticides. This data resource provides a foundation for developing new operational systems for molecular surveillance and for accelerating research and development of new vector control tools. It also provides a unique resource for the study of population genomics and evolutionary biology in eukaryotic species with high levels of genetic diversity under strong anthropogenic evolutionary pressures.