Despite progress in reducing malaria transmission with insecticide-based vector control, the disease continues to claim over 500,000 lives per year, most of which are African children. A significant impediment to control in Africa is the presence of Anopheles gambiae - a uniquely efficient mosquito vector endemic to the continent. While great advancements have been made in the molecular biology and genetics of An. gambiae over the past decade, inadequate data on recombination rate in this species prevents novel and traditional vector control strategies from being deployed with maximum effectiveness. Recombination is a fundamental biological process with profound evolutionary implications. In mosquitoes and other sexual eukaryotes, recombination between homologous chromosomes is required for both the proper formation of haploid gametes from diploid germ cells and the production of new combinations of alleles. However, the rate at which recombination occurs varies with genomic position, sex, and the presence of chromosomal inversions. Such variation in recombination rate influences a myriad of evolutionary processes including the efficacy of natural selection, levels of standing diversity, and the elimination of deleterious mutations. Usin high-throughput next generation sequencing techniques, this project aims to: 1) create a high-resolution recombination rate map for female An. gambiae, 2) create a high-resolution recombination rate map for male An. gambiae, and 3) systematically determine the effect of inversions on recombination. Our quantitative data on recombination will aid in the design, implementation, and evaluation of control strategies targeting An. gambiae, while also greatly improving the power of population genetics and whole-genome association studies in this species. Ultimately, this project provides a critical tool in the fight against malaria.

Public Health Relevance

Recombination occurs when chromosomes exchange genetic material in the parent before being passed on to the offspring. We will create high-resolution recombination rate maps for the African malaria mosquito, which can be used to evaluate and refine vector control strategies that will ultimately reduce disease transmission to humans.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI113248-03
Application #
9060275
Study Section
Vector Biology Study Section (VB)
Program Officer
Costero-Saint Denis, Adriana
Project Start
2014-06-01
Project End
2019-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
3
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of California Riverside
Department
Zoology
Type
Earth Sciences/Resources
DUNS #
627797426
City
Riverside
State
CA
Country
United States
Zip Code
92521
Fouet, Caroline; Atkinson, Peter; Kamdem, Colince (2018) Human Interventions: Driving Forces of Mosquito Evolution. Trends Parasitol 34:127-139
Li, Ming; Akbari, Omar S; White, Bradley J (2018) Highly Efficient Site-Specific Mutagenesis in Malaria Mosquitoes Using CRISPR. G3 (Bethesda) 8:653-658
Kamdem, Colince; Fouet, Caroline; White, Bradley J (2017) Chromosome arm-specific patterns of polymorphism associated with chromosomal inversions in the major African malaria vector, Anopheles funestus. Mol Ecol 26:5552-5566
Fouet, Caroline; Kamdem, Colince; Gamez, Stephanie et al. (2017) Genomic insights into adaptive divergence and speciation among malaria vectors of the Anopheles nili group. Evol Appl 10:897-906
Cassone, Bryan J; Kay, Raissa G G; Daugherty, Matthew P et al. (2017) Comparative Transcriptomics of Malaria Mosquito Testes: Function, Evolution, and Linkage. G3 (Bethesda) 7:1127-1136
Pombi, Marco; Kengne, Pierre; Gimonneau, Geoffrey et al. (2017) Dissecting functional components of reproductive isolation among closely related sympatric species of the Anopheles gambiae complex. Evol Appl 10:1102-1120
Fouet, Caroline; Kamdem, Colince; Gamez, Stephanie et al. (2017) Extensive genetic diversity among populations of the malaria mosquito Anopheles moucheti revealed by population genomics. Infect Genet Evol 48:27-33
Kamdem, Colince; Fouet, Caroline; Gamez, Stephanie et al. (2017) Pollutants and Insecticides Drive Local Adaptation in African Malaria Mosquitoes. Mol Biol Evol 34:1261-1275
Turissini, David A; Gamez, Stephanie; White, Bradley J (2014) Genome-wide patterns of polymorphism in an inbred line of the African malaria mosquito Anopheles gambiae. Genome Biol Evol 6:3094-104