Microarrays and high-throughput transcriptomic analysis in species with incomplete availability of genomic sequences - PubMed

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Microarrays and high-throughput transcriptomic analysis in species with incomplete availability of genomic sequences

Lorraine Pariset et al. N Biotechnol. 2009 Jun.

Abstract

Microarrays produce a measurement of gene expression based on the relative measures of dye intensities that correspond to the amount of target RNA. This technology is fast developing and its application is expanding from Homo sapiens to a wide number of species, where enough information on sequences and annotations exist. Anyway, the number of species for which a dedicated platform exists is not high. The use of heterologous array hybridization, screening for gene expression in one species using an array developed for another one, is still quite frequent, even though cross-species microarray hybridization has raised many arguments. Some methods which are high throughput and do not rely on knowledge of the DNA/RNA sequence exist, namely serial analysis of gene expression (SAGE), Massively Parallel Signature Sequencing (MPSS) and deep sequencing of full transcriptome. Although very powerful, particularly the latter, they are still quite costly and cumbersome methods. In some species where genome sequences are largely unknown, several anonymous sequences are deposited in gene banks as a result of Expressed Sequence Tags (ESTs) sequencing projects. The ESTs databases represent a valuable knowledge that can be exploited with some bioinformatic effort to build species-specific microarrays. We present here a method of high-density in situ synthesized microarrays starting from available EST sequences in, Ovis aries. Our data indicate that the method is very efficient and can be easily extended to other species of which genetic sequences are present in public databases, but neglected so far with advanced devices like microarrays. As a perspective, the approach can be applied also to species of which no sequences are available to date, thanks to high-throughput deep sequencing methods.

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