Predicting the age of mosquitoes using transcriptional profiles.

Peter Cook, Leon Hugo, Inaki Iturbe-Ormaetxe, Craig Williams, Stephen Chenoweth, Scott Ritchie, Peter Ryan, Brian Kay, Mark Blows, Scott Leslie O'Neill

Research output: Contribution to journalArticleResearchpeer-review

31 Citations (Scopus)

Abstract

The use of transcriptional profiles for predicting mosquito age is a novel solution for the longstanding problem of determining the age of field-caught mosquitoes. Female mosquito age is of central importance to the transmission of a range of human pathogens. The transcriptional age-grading protocol we present here was developed in Aedes aegypti, principally as a research tool. Age predictions are made on the basis of transcriptional data collected from mosquitoes of known age. The abundance of eight candidate gene transcripts is quantified relative to a reference gene using quantitative reverse transcriptase-PCR (RT-PCR). Normalized gene expression (GE) measures are analyzed using canonical redundancy analysis to obtain a multivariate predictor of mosquito age. The relationship between the first redundancy variate and known age is used as the calibration model. Normalized GE measures are quantified for wild-caught mosquitoes, and ages are then predicted using this calibration model. Rearing of mosquitoes to specific ages for calibration data can take up to 40 d. Molecular analysis of transcript abundance, and subsequent age predictions, should take similar to 3-5 d for 100 individuals.
Original languageEnglish
Pages (from-to)2796 - 2806
Number of pages11
JournalNature Protocols
Volume2
Issue number11
DOIs
Publication statusPublished - 2007
Externally publishedYes

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