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The geographic separation of New Zealand (NZ) from other major land masses for >80 million years has resulted in the evolution of unique flora and fauna. Among these are scarab beetles, whose larvae consume plant biomass including roots, wood, and humus. Like ruminant herbivores, NZ scarab beetles rely on a community of cellulolytic endosymbiotic microorganisms in their gut to convert recalcitrant plant matter into useful end products, such as energy. We hypothesized that scarab insect guts function as miniature bioreactors and are, thus, a useful model to obtain fundamental insights into the digestion of complex plant material. To begin testing this idea we employed next generation sequencing (NGS) to look for candidate genes involved in a range of enzymatic activities from the hindgut of NZ scarab larvae. Here we wish to discuss bioinformatics methods to analyse the NGS dataset. More than 100 Gbp of RNA-Seq (Illumina HiSeq, paired-end, 100bp, 400bp insert) were generated. We want to mine this data for cellulolytic genes and species/organisms present within scarab hindgut tissue. The absence of a reference genome for scarab makes this a challenging meta-transcriptomics study. We tested some of the commonly used tools available and discuss to what extend they are relevant for our dataset. A strategy combining the best parts of publicly available tools with our own adjustments is presented.