The recent advances in the next-generation massively parallel sequencing (MPS) technologies (Roche 454 GS FLX, Illumina HiSeq and Life Technologies IonTorrent) has entirely changed the way in which quantitative transcriptomics can be done. These new technologies have significantly reduced the costs and running time required making the use of sequencing a cost-effective option for many experimental approaches [1-2].

Traditionally applied to genome sequencing, MPS has recently been utilized also to directly survey the RNA content of cells, without requiring any of the traditional cloning associated with EST sequencing (expressed sequence tags).

This approach, called “RNA-seq”, can generate quantitative expression scores that are equivalent to microarrays, with the supplementary benefit that the whole transcriptome is analyzed without the prerequisite of a priori knowledge of transcribed regions [1-2].

All RNA-seq experiments follow a comparable protocol: total RNA is isolated from a sample of interest, which, depending on the type of RNA to be profiled, may be purified to enrich for mRNAs, micro-RNA, long non-coding RNA, etc., prior to preparing an RNA library. Library preparation may involve steps as reverse transcription to cDNA, cDNA fragmentation and PCR amplification and may or may not preserve strandedness information. Sequencing can produce one read in a single-end sequencing reaction, or two ends separated by a not sequenced fragment in paired-end reactions. The produced reads (usually ten or more millions for each experiments) can be used to quantify expression level of genes annotated into a reference genome or alternatively can be assembled “de novo” into a reference transcriptome using ad hoc bioinformatic pipelines (Figure 1). The important advantage of this technique is that not only it can quantitatively measures the expression levels of genes and transcripts, but transcript structures including alternatively spliced transcript isoforms, can also be identified. Results derived by RNA-seq studies have already altered our view of eukaryotic transcriptomes revealing that the transcriptome is significantly more complex that previously envisioned [3].

Very recently, RNA-seq has started to be applied also to comparative population transcriptomics analyses showing the great potential for reference-free applications in non-model organisms such as SNP discovery, speciation genomics and phylogenomics [4-5]. Furthermore, RNA-seq based transcriptomic approach could also be very useful for the direct discovery of viruses in wild-caught vector animals highlighting the power and feasibility of MPS techniques for detection of unsuspected or novel etiologic agents [6-7-8].

In our research project we will apply Illumina sequencing technology and Trinity-based assembling pipelines (Figure 2) [9] to laboratory strain and individuals from natural populations to clarify sex determination of Ae. albopictus and P. perniciosus and to understand the genetic structure of the populations present in the Campania region (southern Italy). In addition, this approach will possibly permit to obtain a survey of the presence and distribution of parasites and viruses in vector populations.


FIGURA 1 | RNA-seq reads usage FIGURA 2 | Trinity assembler analysis pipeline