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Whole-genome sequencing reveals high complexity of copy number variation at insecticide resistance loci in malaria mosquitoes.

ABSTRACT: Polymorphisms in genetic copy number 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. Using the whole-genome sequencing data from 1142 samples in the An. gambiae 1000 genomes project, we identified 250 gene-containing CNVs, encompassing a total of 267 genes of which 28 were in gene families linked to metabolic insecticide resistance, representing significant enrichment of these families. The five major gene clusters for metabolic resistance all contained CNVs, with 44 different CNVs being found across these clusters and multiple CNVs frequently covering the same genes. These 44 CNVs are widespread (45% of individuals carry at least one of them) and have been spreading through positive selection, indicated by their high local frequencies and extended haplotype homozygosity. Our results demonstrate the importance of CNVs in the response to selection, highlighting the urgent need to identify the contribution of each CNV to insecticide resistance and to track their spread as the use of insecticides in malaria endemic countries intensifies and as the operational deployment of next-generation bed nets targeting metabolic resistance gathers pace. Our detailed descriptions of CNVs found across the species range provide the tools to do so.

SUBMITTER: Lucas ER

PROVIDER: S-EPMC6673711 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Whole-genome sequencing reveals high complexity of copy number variation at insecticide resistance loci in malaria mosquitoes.

Lucas Eric R ER Miles Alistair A Harding Nicholas J NJ Clarkson Chris S CS Lawniczak Mara K N MKN Kwiatkowski Dominic P DP Weetman David D Donnelly Martin J MJ

Genome research 20190725 8

Polymorphisms in genetic copy number 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 <i>Anopheles gambiae</i>, caused by the widespread use of insecticides for malaria control, to investigate the role of CNVs in the evolution ...[more]

PMID: 31345938

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Project description:BackgroundWhole genome sequencing enables a high resolution view of the human genome and provides unique insights into genome structure at an unprecedented scale. There have been a number of tools to infer copy number variation in the genome. These tools, while validated, also include a number of parameters that are configurable to genome data being analyzed. These algorithms allow for normalization to account for individual and population-specific effects on individual genome CNV estimates but the impact of these changes on the estimated CNVs is not well characterized. We evaluate in detail the effect of normalization methodologies in two CNV algorithms FREEC and CNV-seq using whole genome sequencing data from 8 individuals spanning four populations.MethodsWe apply FREEC and CNV-seq to a sequencing data set consisting of 8 genomes. We use multiple configurations corresponding to different read-count normalization methodologies in FREEC, and statistically characterize the concordance of the CNV calls between FREEC configurations and the analogous output from CNV-seq. The normalization methodologies evaluated in FREEC are: GC content, mappability and control genome. We further stratify the concordance analysis within genic, non-genic, and a collection of validated variant regions.ResultsThe GC content normalization methodology generates the highest number of altered copy number regions. Both mappability and control genome normalization reduce the total number and length of copy number regions. Mappability normalization yields Jaccard indices in the 0.07 - 0.3 range, whereas using a control genome normalization yields Jaccard index values around 0.4 with normalization based on GC content. The most critical impact of using mappability as a normalization factor is substantial reduction of deletion CNV calls. The output of another method based on control genome normalization, CNV-seq, resulted in comparable CNV call profiles, and substantial agreement in variable gene and CNV region calls.ConclusionsChoice of read-count normalization methodology has a substantial effect on CNV calls and the use of genomic mappability or an appropriately chosen control genome can optimize the output of CNV analysis.

Dataset Information

Whole-genome sequencing reveals high complexity of copy number variation at insecticide resistance loci in malaria mosquitoes.

Publications

Whole-genome sequencing reveals high complexity of copy number variation at insecticide resistance loci in malaria mosquitoes.

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