Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Research article

In depth annotation of the Anopheles gambiae mosquito midgut transcriptome

Alejandro Padrón1, Alvaro Molina-Cruz1*, Mariam Quinones2, José MC Ribeiro1, Urvashi Ramphul1, Janneth Rodrigues1, Kui Shen2, Ashley Haile1, José Luis Ramirez1 and Carolina Barillas-Mury1*

Author Affiliations

1 Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA

2 Bioinformatics and Computational Biosciences Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA

For all author emails, please log on.

BMC Genomics 2014, 15:636  doi:10.1186/1471-2164-15-636

Published: 29 July 2014

Abstract

Background

Genome sequencing of Anopheles gambiae was completed more than ten years ago and has accelerated research on malaria transmission. However, annotation needs to be refined and verified experimentally, as most predicted transcripts have been identified by comparative analysis with genomes from other species. The mosquito midgut—the first organ to interact with Plasmodium parasites—mounts effective antiplasmodial responses that limit parasite survival and disease transmission. High-throughput Illumina sequencing of the midgut transcriptome was used to identify new genes and transcripts, contributing to the refinement of An. gambiae genome annotation.

Results

We sequenced ~223 million reads from An. gambiae midgut cDNA libraries generated from susceptible (G3) and refractory (L35) mosquito strains. Mosquitoes were infected with either Plasmodium berghei or Plasmodium falciparum, and midguts were collected after the first or second Plasmodium infection. In total, 22,889 unique midgut transcript models were generated from both An. gambiae strain sequences combined, and 76% are potentially novel. Of these novel transcripts, 49.5% aligned with annotated genes and appear to be isoforms or pre-mRNAs of reference transcripts, while 50.5% mapped to regions between annotated genes and represent novel intergenic transcripts (NITs). Predicted models were validated for midgut expression using qRT-PCR and microarray analysis, and novel isoforms were confirmed by sequencing predicted intron-exon boundaries. Coding potential analysis revealed that 43% of total midgut transcripts appear to be long non-coding RNA (lncRNA), and functional annotation of NITs showed that 68% had no homology to current databases from other species. Reads were also analyzed using de novo assembly and predicted transcripts compared with genome mapping-based models. Finally, variant analysis of G3 and L35 midgut transcripts detected 160,742 variants with respect to the An. gambiae PEST genome, and 74% were new variants. Intergenic transcripts had a higher frequency of variation compared with non-intergenic transcripts.

Conclusion

This in-depth Illumina sequencing and assembly of the An. gambiae midgut transcriptome doubled the number of known transcripts and tripled the number of variants known in this mosquito species. It also revealed existence of a large number of lncRNA and opens new possibilities for investigating the biological function of many newly discovered transcripts.