Reference‐free transcriptome assembly in non‐model animals from next‐generation sequencing data

Abstract

Next-generation sequencing (NGS) technologies offer the opportunity for population genomic study of non-model organisms sampled in the wild. The transcriptome is a convenient and popular target for such purposes. However, designing genetic markers from NGS transcriptome data requires assembling gene-coding sequences out of short reads. This is a complex task owing to gene duplications, genetic polymorphism, alternative splicing and transcription noise. Typical assembling programmes return thousands of predicted contigs, whose connection to the species true gene content is unclear, and from which SNP definition is uneasy. Here, the transcriptomes of five diverse non-model animal species (hare, turtle, ant, oyster and tunicate) were assembled from newly generated 454 and Illumina sequence reads. In two species for which a reference genome is available, a new procedure was introduced to annotate each predicted contig as either a full-length cDNA, fragment, chimera, allele, paralogue, genomic sequence or other, based on the number of, and overlap between, blast hits to the appropriate reference. Analyses showed that (i) the highest quality assemblies are obtained when 454 and Illumina data are combined, (ii) typical de novo assemblies include a majority of irrelevant cDNA predictions and (iii) assemblies can be appropriately cleaned by filtering contigs based on length and coverage. We conclude that robust, reference-free assembly of thousands of genes from transcriptomic NGS data is possible, opening promising perspectives for transcriptome-based population genomics in animals. A Galaxy pipeline implementing our best-performing assembling strategy is provided.

Characterization of Iodine-Related Molecular Processes in the Marine Microalga Tisochrysis lutea (Haptophyta)

“…These data agree with previous data from our group in the flatfish Solea senegalensis, in which 454-normalized libraries resulted in a high rate of rejected redundant sequences and more fragmented assemblies (Benzekri et al, 2014). Our data confirm that normalization is not a good strategy when a maximal number of correctly predicted full-length cDNAs is intended unless a deep coverage is expected (Cahais et al, 2012).…”

Transcriptome Analysis of Self- and Cross-pollinated Pistils of Japanese Apricot (Prunus mume Sieb. et Zucc.)

“…Among the three assemblies, the hybrid assembly of the Roche/454 and Illumina reads gave the longest unigene length. This result is consistent with the results of Cahais et al (2012), which showed that higher quality assemblies were obtained when the Roche/454 and Illumina data were combined, in comparison with the use of either Roche/454 or Illumina data alone. In this study, however, the assembly results of the hybrid data set, i.e.…”

Transcriptome Analysis for Non-Model Organism: Current Status and Best-Practices

“…Despite all these eforts, de novo assembly of short-reads, regardless of software used, results in hundreds of thousands of contigs, a set of contiguous transcript sequences. Without any further analysis such as clustering or postassembling, the inal set of contigs includes (i) partial transcripts and rudimentary isoforms (splice variants), (ii) redundant transcripts (diferent lengths of the same transcripts, mostly fragments) and (iii) chimeric (fusion) and misassembled sequences [3].…”

“…Despite huge efort, de novo sequencing of an entire genome is not an easy task, even now, and this also makes 'RNA sequencing (hereafter, RNA-Seq)-based transcriptomic analysis' appealing for non-model organisms that are generally described as having no or limited genomic resources and transcriptomic datasets as well as molecular tools [3][4][5][6]. In the ield of '-omics' disciplines, RNA-Seq is among high-throughput experimental methods and widely used for identifying all functional elements in the genome.…”