Drosophila sechellia is a species of fruit fly endemic to the Seychelles islands. Unlike its generalist sister species, D. sechellia has evolved to be a specialist on the host plant Morinda citrifolia. This specialization is interesting because the plant’s fruit contains secondary defense compounds, primarily octanoic acid (OA), that are lethal to most other Drosophilids. Although ecological and behavioral adaptations to this toxic fruit are known, the genetic basis for evolutionary changes in OA resistance are not. Prior work showed that a genomic region on chromosome 3R containing 18 genes has the greatest contribution to differences in OA resistance between D. sechellia and D. simulans. To determine which gene(s) in this region might be involved in the evolutionary change in OA resistance, we knocked-down expression of each gene in this region in D. melanogaster with RNA interference (RNAi) (i) ubiquitously throughout development, (ii) during only the adult stage, and (iii) within specific tissues. We identified three neighboring genes in the Osiris family, Osiris 6 (Osi6), Osi7, and Osi8, that lead to decreased OA resistance when ubiquitously knocked-down. Tissue specific RNAi, however, showed that decreasing expression of Osi6 and Osi7 specifically in the fat body and/or salivary glands increased OA resistance. Gene expression analyses of Osi6 and Osi7 revealed that while standing levels of expression are higher in D. sechellia, Osi6 expression is significantly downregulated in salivary glands in response to OA exposure, suggesting that evolved tissue-specific environmental plasticity of Osi6 expression may be responsible for OA resistance in D. sechellia.

Annotation of the rice (Oryza sativa) genome has evolved significantly since release of its draft sequence, but it is far from complete. Several published transcript assembly programmes were tested on RNA-sequencing (RNA-seq) data to determine their effectiveness in identifying novel genes to improve the rice genome annotation. Cufflinks, a popular assembly software, did not identify all transcripts suggested by the RNA-seq data. Other assembly software was CPU intensive, lacked documentation, or lacked software updates. To overcome these shortcomings, a heuristic ab initio transcript assembly algorithm, Tiling Assembly, was developed to identify genes based on short read and junction alignment. Tiling Assembly was compared with Cufflinks to evaluate its gene-finding capabilities. Additionally, a pipeline was developed to eliminate false-positive gene identification due to noise or repetitive regions in the genome. By combining Tiling Assembly and Cufflinks, 767 unannotated genes were identified in the rice genome, demonstrating that combining both programmes proved highly efficient for novel gene identification. We also demonstrated that Tiling Assembly can accurately determine transcription start sites by comparing the Tiling Assembly genes with their corresponding full-length cDNA. We applied our pipeline to additional organisms and identified numerous unannotated genes, demonstrating that Tiling Assembly is an organism-independent tool for genome annotation.