Abstract
A comprehensive reannotation of the Anopheles gambiae genome using a combination of comparative and ab initio gene prediction algorithms has identified novel coding sequences.
Highlights
Complete genome annotation is a necessary tool as Anopheles gambiae researchers probe the biology of this potent malaria vector
coding sequences (CDSs) predicted by GENSCAN and GeneWise were joined using the EGU algorithm (Figure 1)
These two gene model sets were used because GENSCAN was found to be one of the most accurate ab initio gene prediction tools [11,12], and GeneWise was one of the most accurate comparative prediction methods [12]
Summary
Complete genome annotation is a necessary tool as Anopheles gambiae researchers probe the biology of this potent malaria vector. A mosquito-transmitted disease caused by parasites of the genus Plasmodium, infects as many as 500 million people per year. Two million people die from malaria each year, with 75% of the deaths occurring in African children [1]. Human malaria parasites are transmitted by anopheline mosquitoes, of which Anopheles gambiae is the most prevalent vector in Africa. A thorough understanding of the A. gambiae genome and the genes and protein products integral to successful parasite transmission may inform malaria control strategies, including those capitalizing on natural malaria resistance and those using transgenic approaches. There are two main approaches for gene prediction. Comparative algorithms such as Genewise [2] base gene prediction on similarity to known proteins, while ab initio prediction programs, such as GENSCAN [3], GeneMark [4] and SNAP [5], typically use the hidden Markov model (HMM) trained with known gene structures
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