Efficient Application of De Novo RNA Assemblers for Proteomics Informed by Transcriptomics

Abstract

RNA sequencing is a powerful method to build reference transcriptome assemblies and eventually sample-specific protein databases for mass-spectrometry-based analyses. This novel proteomics informed by transcriptomics (PIT) workflow improves proteome characterization of dynamic and especially nonmodel organism proteomes and moreover helps to identify novel gene products. With increasing popularity of such proteogenomics applications a growing number of researchers demand qualitative but resource-friendly and easy to use analysis strategies. Most PIT applications so far rely on the initially introduced Trinity de novo assembly tool. To aid potential users to start off with PIT, we compared main performance criteria of Trinity and other alternative RNA assembly tools known from the transcriptomics field including Oases, SOAPdenovo-Trans, and Trans-ABySS. Using exemplary data sets and software-specific default parameters, Trinity and alternative assemblers produced comparable and high-quality reference data for vertebrate transcriptomes/proteomes of varying complexity. However, Trinity required large computational resources and time. We found that alternative de novo assemblers, in particular, SOAPdenovo-Trans but also Oases and Trans-ABySS, rapidly produced protein databases with far lower computational requirements. By making choice among various RNA assembly tools, proteomics researchers new to transcriptome assembly and with future projects with high sample numbers can benefit from alternative approaches to efficiently apply PIT.