ECCB edition:10 location:Ghent date:26-29 September 2010
Digital gene expression in an evo-devo approach across Drosophila species reveals conserved and divergent gene expression patterns in eye development while proving its measurements accuracy in distinct species.
Retinal differentiation is initiated in the eye imaginal disc during third instar larval development. During this process the genes eyeless and atonal activate a cascade of signaling events that end in the retina formation. Drosophila eye-development is a well-studied system but information about gene expression and gene regulatory interactions remains sparse. Here, we aim to gain further insight into the gene regulatory network underlying retinal differentiation by determining conserved and divergent patterns of gene expression in various Drosophila species using next-generation sequencing.
RNA was extracted from eye-antennal imaginal discs and wing imaginal discs (controls) during third instar larval stage from three species, namely D.melanogaster, D.yakuba and D.virilis. Tag libraries for digital gene expression were created using the NlaIII restriction enzyme and were sequenced on the Illumina GAII platform in six separate lanes. Reads were mapped against their reference genome using bowtie, considering only uniquely mapped tags. Gene expression levels were normalized as tags per million (TPM). Gene set and functional enrichment analyses were performed using GSEA.
First, we show that DGE yields meaningful expression values in D. melanogaster through a comparison with microarray data on the same tissue. Next, we confirm that gene expression divergence increases over evolutionary time, being larger for Dmel-Dvir than for Dmel-Dyak. Finally, we identified conserved expression genes in the eye disc. Surprisingly, small fraction of eye specific genes in D.melanogaster is also eye specific in the other species (30% and 17% overlap with D.yakuba and D.virilis respectively). These conserved genes are mostly involved in photoreceptor cell fate specification.
To our knowledge this is the first time that digital gene expression is used to measure tissue-specific gene expression in multiple Drosophila species. We conclude that DGE-based gene expression measurements are accurate and appropriate for determining gene expression levels for species without a microarray platform. Finally, we are able to find expression conservation and divergence patterns across Drosophila species allowing us to investigate further the evolutionary differences in the mechanisms governing gene expression.