Malaria causes millions people death every year. Malaria transmission is totally dependent on the availability of competent mosquitoes. Identification of the genes that confer resistance to malaria parasites is essential to understand this biological process, which may inform new malaria control strategy. Several genetic loci for malaria resistance have been discovered in Anopheles gambiae, and genetic variations at the loci underlie the malaria resistance. However, the actual genes and their isoforms have not yet been identified. We propose a combination of bioinformatics approach and empirical approach as an efficient method to identify the genes conferring resistance to malaria parasite in A. gambiae. Our long-term goal is to use contemporary molecular and bioinformatics methods to develop new tools such as monitoring vector susceptibility to malaria parasites to aid malaria control. The goal of this application is to improve Anopheles gambiae genome annotation, detect genetic variations by informatics, and identify the genes responsible for malaria parasite resistance in A. gambiae. We will achieve this goal by the following three specific aims: 1) Improve A. gambiae genome annotation using combinational algorithm;2) Detect gene structural variations and single nucleotide polymorphisms by bioinformatics approach using EST and genome trace sequences, and distinguish the post-transcriptional alternative splicing from gene structure variations;and 3) Apply genetic variations to the discovery of parasite resistance genes. The improved genome annotation and developed gene variations in this project will be helpful research resources for Anopheles research, and identification of resistance genes will better the understanding of insect innate immunity against parasite and malaria control. Furthermore, finding a trait causative gene is a challenge, and this novel gene discovery approach might be a model for other organisms.
Anopheles gambiae is the most important malaria vector in African that causes millions people death every year. Research on this vector depends heavily on the genome annotation with correct gene annotations and gene variations. Malaria transmission is totally dependent on the availability of competent mosquitoes. Identification the gene that confer resistance to malaria parasites is essential to malaria risk assessment and understand the mosquito innate immunity against parasites that may inform new malaria control strategy. Furthermore, finding a trait causative gene is a challenge, and this bioinformatics-guided novel gene discovery approach could be a good model for other organisms.
| Wang, Xiaohong; Afrane, Yaw A; Yan, Guiyun et al. (2015) Constructing a Genome-Wide LD Map of Wild A. gambiae Using Next-Generation Sequencing. Biomed Res Int 2015:238139 |
| Li, Jun; Wang, Xiaohong; Zhang, Genwei et al. (2013) Genome-block expression-assisted association studies discover malaria resistance genes in Anopheles gambiae. Proc Natl Acad Sci U S A 110:20675-80 |
| Li, Jun; Ribeiro, Jose M C; Yan, Guiyun (2010) Allelic gene structure variations in Anopheles gambiae mosquitoes. PLoS One 5:e10699 |
