Association mapping by pooled sequencing identifies TOLL 11 as a protective factor against Plasmodium falciparum in Anopheles gambiae

Redmond et al. BMC Genomics (2015) 16:779 DOI 10.1186/s12864-015-2009-z RESEARCH ARTICLE Open Access Association mapping by pooled sequencing identifies TOLL 11 as a protective factor against Plasmodium falciparum in Anopheles gambiae Seth N. Redmond1,2, Karin Eiglmeier1,2, Christian Mitri1,2, Kyriacos Markianos3, Wamdaogo M. Guelbeogo4, Awa Gneme4, Alison T. Isaacs1,2, Boubacar Coulibaly5, Emma Brito-Fravallo1,2, Gareth Maslen6,7, Daniel Mead6,7, Oumou Niare5, Sekou F. Traore5, N’Fale Sagnon4, Dominic Kwiatkowski6,7, Michelle M. Riehle8 and Kenneth D. Vernick1,2,5* Abstract Background: The genome-wide association study (GWAS) techniques that have been used for genetic mapping in other organisms have not been successfully applied to mosquitoes, which have genetic characteristics of high nucleotide diversity, low linkage disequilibrium, and complex population stratification that render population-based GWAS essentially unfeasible at realistic sample size and marker density. Methods: We designed a novel mapping strategy for the mosquito system that combines the power of linkage mapping with the resolution afforded by genetic association. We established founder colonies from West Africa, controlled for diversity, linkage disequilibrium and population stratification. Colonies were challenged by feeding on the infectious stage of the human malaria parasite, Plasmodium falciparum, mosquitoes were phenotyped for parasite load, and DNA pools for phenotypically similar mosquitoes were Illumina sequenced. Phenotype-genotype mapping was carried out in two stages, coarse and fine. Results: In the first mapping stage, pooled sequences were analysed genome-wide for intervals displaying relativereduction in diversity between phenotype pools, and candidate genomic loci were identified for influence upon parasite infection levels. In the second mapping stage, focused genotyping of SNPs from the first mapping stage was carried out in unpooled individual mosquitoes and replicates. The second stage confirmed significant SNPs in a locus encoding two Toll-family proteins. RNAi-mediated gene silencing and infection challenge revealed that TOLL 11 protects mosquitoes against P. falciparum infection. Conclusions: We present an efficient and cost-effective method for genetic mapping using natural variation segregating in defined recent Anopheles founder colonies, and demonstrate its applicability for mapping in a complex non-model genome. This approach is a practical and preferred alternative to population-based GWAS for first-pass mapping of phenotypes in Anopheles. This design should facilitate mapping of other traits involved in physiology, epidemiology, and behaviour. Keywords: Mosquito, Malaria, Genetic analysis, GWAS, Host-pathogen interaction, Population genomics, Pooled sequencing * Correspondence: Michelle M. Riehle and Kenneth D. Vernick are Senior authors. 1 Department of Parasites and Insect Vectors, Institut Pasteur, Unit of Insect Vector Genetics and Genomics, 28 rue du Docteur Roux, Paris 75015, France 2 CNRS Unit of Hosts, Vectors and Pathogens, Paris, France (URA3012), 28 rue du Docteur Roux, Paris 75015, France Full list of author information is available at the end of the article © 2015 Redmond et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Redmond et al. BMC Genomics (2015) 16:779 Background The mosquito Anopheles gambiae is the principal vector of human malaria in sub-Saharan Africa, particularly of the most deadly malaria species, Plasmodium falciparum. Mosquito susceptibility to P. falciparum has a strong genetic component, indicated by populationbased mapping of quantitative trait loci (QTLs) [1–3], and laboratory-based phenotypic selection of resistant lines [4]. However, the genome-wide association study (GWAS) techniques that have been used to map human [5, 6] and Plasmodium genes [7], have not been successfully applied to the mosquito. Previous QTL mapping in wild A. gambiae pedigrees identified a cluster of loci that form the Plasmodium resistance island (PRI) [3], a region containing a number of novel immune genes. The PRI region was found to explain 89 % of the variation in resistance to P. falciparum. QTL mapping has high power to detect loci, but the extended linkage blocks reduce resolving power, and the 15 Mb PRI contains over 900 genes. Association mapping in a complex population in principle can resolve loci to many fewer genes. Population-based association testing of a small panel of candidate immune genes was applied to the mosquito in two studies [8, 9], which were limited because association requires large sample sizes, careful exclusion of population subdivision among the samples, and replication using independent phenotyped samples, which are all difficult in A. gambiae. Successful GWAS is reliant on a combination of linkage, diversity, and allele penetrance. Linkage disequilibrium (LD) is a particularly important determinant of the power to detect a locus, while high levels of genetic diversity decrease the power of detection at a feasible sample size. Optimum statistical power is achieved when LD is highest (i.e., r2 = 1), the frequency difference between alleles is near 0, and the variation in phenotype can be explained by a single allele of strong effect. However, A. gambiae offers conditions far from optimal, with negligible levels of LD (r2 ~ 0.05 within 1 kb [10, 11]), and nucleotide diversity at least an order of magnitude greater than that found in human [12]. Modified experimental approaches combining the strengths of linkage mapping with the resolution of association mapping have been used in some model systems. Controlled-diversity colonies enable fine-resolution mapping under tractable genetic conditions in, for example, the mouse Diversity Outbred lines and the Drosophila Synthetic Population Resource [13–16]. Both of these approaches use material derived from advanced inter-crosses of inbred lines (often with known phenotypic traits), with breeding controlled to prevent excessive genetic drift. The challenge in Anopheles is similar, yet the context very different. In model organisms, the interest is to map a wide range of phenotypes within a series of highly controlled Page 2 of 13 lines that still display sufficient phenotypic diversity. In comparison, vector biologists are more interested in particular phenotypes related to disease transmission such as pathogen interaction, behaviour and (...truncated)