? Malaria is one of the world?s major infectious diseases. The highest global disease prevalence is in Africa, where the most important vectors are members of the Anopheles gambiae species complex. In nature, genetic differences among individual mosquitoes and between population subgroups underlie many of the characteristics that make these mosquitoes such a widespread, efficient and persistent malaria vectorial system, including differences in malaria susceptibility, ecological adaptation, biting behavior, and insecticide resistance. However, the vast majority of phenotypic variation in animals (>90% estimated from studies in Drosophila and human) is controlled by genetic variation of non-coding regulatory DNA, while genetic variation of protein-coding sequence contributes little to phenotypic variation. Description of non-coding regulatory elements in mosquitoes, and their influence on mosquito biology and malaria transmission, remains essentially unexplored. Gene enhancers are an important class of non-coding regulatory elements. Enhancers influence gene transcriptional levels independent of position or orientation in the genome, even at a distance. Enhancers cannot yet be reliably identified by sequence signatures, but rather require functional assays for comprehensive detection. The availability of next-generation deep-sequencing has led to new strategies to screen non-coding DNA for functional enhancers.
In Aim 1 we will use a recently developed RNAseq-based method, STARR-seq, to generate a genome-wide map of functional gene enhancer sites in two Anopheles sister taxa, A. gambiae and A. coluzzii.
In Aim 2, the comprehensive enhancer map and existing whole genome sequence data will be used in two exploratory biological projects on the role of natural enhancer variation for: i) the population divergence of two malaria vector species, A. gambiae and A. coluzzii, and ii) genetic differences between individual mosquitoes for susceptibility to malaria infection. The project will generate a novel genomic database resource, the functionally derived genome-wide map of A. gambiae and A. coluzzii enhancer elements. This new technical tool will, for the first time, open for analysis a source of genetic variation with considerably more impact on phenotype than the coding variation that is currently accessible through genome annotation in mosquitoes. The resulting enhancer map will be applied to two important biological problems in Anopheles genetics that are only partially understood based on analysis using only interpretable coding nucleotide variation.

Public Health Relevance

. Extensive genomic information now exists for Anopheles species, but a significant gap remains in associating the extensive nucleotide variation with relevant phenotypes. Across all organisms, the ability to link changes in genotype with disease phenotype is complicated by the fact that most currently interpretable variation explains only a small proportion of the genetic basis of phenotypes. We will assign function to non-coding mosquito sequence that is currently not interpretable, and is likely to influence malaria transmission.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Exploratory/Developmental Grants (R21)
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Vector Biology Study Section (VB)
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Costero-Saint Denis, Adriana
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University of Minnesota Twin Cities
Schools of Medicine
United States
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Carissimo, Guillaume; Pain, Adrien; Belda, Eugeni et al. (2018) Highly focused transcriptional response of Anopheles coluzzii to O'nyong nyong arbovirus during the primary midgut infection. BMC Genomics 19:526
Riehle, Michelle M; Bukhari, Tullu; Gneme, Awa et al. (2017) The Anopheles gambiae 2La chromosome inversion is associated with susceptibility to Plasmodium falciparum in Africa. Elife 6:
Belda, Eugeni; Coulibaly, Boubacar; Fofana, Abdrahamane et al. (2017) Preferential suppression of Anopheles gambiae host sequences allows detection of the mosquito eukaryotic microbiome. Sci Rep 7:3241