Assembly, Assessment, and Availability of De novo Generated Eukaryotic Transcriptomes

Abstract

De novo assembly of a complete transcriptome without the need for a guiding reference genome is attractive, particularly where the cost and complexity of generating a eukaryote genome is prohibitive. The transcriptome should not however be seen as just a quick and cheap alternative to building a complete genome. Transcriptomics allows the understanding and comparison of spatial and temporal samples within an organism, and allows surveying of multiple individuals or closely related species. De novo assembly in theory allows the building of a complete transcriptome without any prior knowledge of the genome. It also allows the discovery of alternate splice forms of coding RNAs and also non-coding RNAs, which are often missed by proteomic approaches, or are incompletely annotated in genome studies. The limitations of the method are that the generation of a truly complete assembly is unlikely, and so we require some methods for the assessment of the quality and appropriateness of a generated transcriptome. Whilst no single consensus pipeline or tool is agreed as optimal, various algorithms, and easy to use software do exist making transcriptome generation a more common approach. With this expansion of data, questions still exist relating to how do we make these datasets fully discoverable, comparable and most useful to understand complex biological systems?

Generation and Characterisation of a Reference Transcriptome for Phalaris (Phalaris aquatica L.)

“…The software tool BUSCO was recently developed for assessment of sequence assemblies, by comparison of gene sets or transcriptomes to a core set of single-copy orthologs, allowing the calculation of levels of completeness, duplication, and fragmentation. BUSCO-derived results have been demonstrated to be more consistent than those from previously used software packages such as CEGMA, and more accurate than the commonly used N50 statistic [30], and so BUSCO has been promoted in several recent studies [28,31] [30]) demonstrated a relatively low level of duplication in the phalaris reference set, and comparable levels of missing orthologues. When compared to an additional set of de novo-assembled transcriptomes from multiple organisms, mainly of non-plant origin [30], the level of completeness and duplication is generally superior in the phalaris dataset, while fragmentation is comparable.…”

“…Despite a c. 10 3 -fold variation in genome size across the angiosperms [26], transcriptomes of diploid species typically vary over a much narrower range, from 50-80 Mbp [27]. Sampling of RNA samples from multiple developmental stages or environmental conditions can allow construction of a transcription atlas, supporting gene isolation, development of gene-associated molecular genetic markers, comparative genomics, identification of differentially regulated gene sets, and quantification of gene expression, as well as ultimate annotation of genome sequences [25,28]. A transcriptome study has previously been performed for another member of the Phalaris genus, P. arundinacea, in order to provide data on differential gene expression in response to environmental stress [29].…”

EnTAP: Bringing faster and smarter functional annotation to non‐model eukaryotic transcriptomes

“…One of the most popular transcriptome assemblers, Trinity, traverses the De Bruijn graph to assemble each isoform (Martin & Wang, 2011). The inherent challenges of assembling these short-reads leads to chimeric sequences, fragmented transcripts, and erroneous contigs (Moreton, Izquierdo, & Emes, 2016). It is not unusual to generate a very large number of transcripts, often three to four times greater than the estimated gene space for the assessed organism.…”

Assessing the Gene Content of the Megagenome: Sugar Pine (Pinus lambertiana)

“…Short read technologies, available through the numerous Illumina platforms, provide substantial depth at a low cost with reads that typically range from 50 to 300 nucleotides (nt) in length (Cahill et al 2010). In the absence of a contiguous genome assembly, researchers rely on de novo assembly techniques to organize those short reads into full-length transcripts (Moreton et al 2015). Recently, the precision and sensitivity of RNA-seq have come into question, especially for transcriptome reconstruction (Korf 2013).…”