Optimizing an efficient ensemble approach for high-quality de novo transcriptome assembly of Thymus daenensis.

Non-erroneous and well-optimized transcriptome assembly is a crucial prerequisite for authentic downstream analyses. Each de novo assembler has its own algorithm-dependent pros and cons to handle the assembly issues and should be specifically tested for each dataset. Here, we examined efficiency of seven state-of-art assemblers on ~ 30 Gb data obtained from mRNA-sequencing of Thymus daenensis. In an ensemble workflow, combining the outputs of different assemblers associated with an additional redundancy-reducing step could generate an optimized outcome in terms of completeness, annotatability, and ORF richness. Based on the normalized scores of 16 benchmarking metrics, EvidentialGene, BinPacker, Trinity, rnaSPAdes, CAP3, IDBA-trans, and Velvet-Oases performed better, respectively. EvidentialGene, as the best assembler, totally produced 316,786 transcripts, of which 235,730 (74%) were predicted to have a unique protein hit (on uniref100), and also half of its transcripts contained an ORF. The total number of unique BLAST hits for EvidentialGene was approximately three times greater than that of the worst assembler (Velvet-Oases). EvidentialGene could even capture 17% and 7% more average BLAST hits than BinPacker and Trinity. Although BinPacker and CAP3 produced longer transcripts, the EvidentialGene showed a higher collinearity between transcript size and ORF length. Compared with the other programs, EvidentialGene yielded a higher number of optimal transcript sets, further full-length transcripts, and lower possible misassemblies. Our finding corroborates that in non-model species, relying on a single assembler may not give an entirely satisfactory result. Therefore, this study proposes an ensemble approach of accompanying EvidentialGene pipelines to acquire a superior assembly for T. daenensis.

Ahmadi H ，Sheikh-Assadi M ，Fatahi R ，Zamani Z ，Shokrpour M ... -  《Scientific Reports》

Combining independent de novo assemblies to optimize leaf transcriptome of Persian walnut.

Sadat-Hosseini M ，Bakhtiarizadeh MR ，Boroomand N ，Tohidfar M ，Vahdati K ... -  《PLoS One》

Combining transcriptome assemblies from multiple de novo assemblers in the allo-tetraploid plant Nicotiana benthamiana.

Nakasugi K ，Crowhurst R ，Bally J ，Waterhouse P ... -  《PLoS One》

Optimizing Transcriptome Assemblies for Eleusine indica Leaf and Seedling by Combining Multiple Assemblies from Three De Novo Assemblers.

Due to rapid advances in sequencing technology, increasing amounts of genomic and transcriptomic data are available for plant species, presenting enormous challenges for biocomputing analysis. A crucial first step for a successful transcriptomics-based study is the building of a high-quality assembly. Here, we utilized three different de novo assemblers (Trinity, Velvet, and CLC) and the EvidentialGene pipeline tr2aacds to assemble two optimized transcript sets for the notorious weed species, Eleusine indica. Two RNA sequencing (RNA-seq) datasets from leaf and aboveground seedlings were processed using three assemblers, which resulted in 20 assemblies for each dataset. The contig numbers and N50 values of each assembly were compared to study the effect of read number, k-mer size, and in silico normalization on assembly output. The 20 assemblies were then processed through the tr2aacds pipeline to remove redundant transcripts and to select the transcript set with the best coding potential. Each assembly contributed a considerable proportion to the final transcript combination with the exception of the CLC-k14. Thus each assembler and parameter set did assemble better contigs for certain transcripts. The redundancy, total contig number, N50, fully assembled contig number, and transcripts related to target-site herbicide resistance were evaluated for the EvidentialGene and Trinity assemblies. Comparing the EvidentialGene set with the Trinity assembly revealed improved quality and reduced redundancy in both leaf and seedling EvidentialGene sets. The optimized transcriptome references will be useful for studying herbicide resistance in E. indica and the evolutionary process in the three allotetraploid E. indica offspring.

Chen S ，McElroy JS ，Dane F ，Peatman E ... -  《Plant Genome》

Comprehensive evaluation of de novo transcriptome assembly programs and their effects on differential gene expression analysis.

Wang S ，Gribskov M 《-》