Comparing de novo assemblers for 454 transcriptome data.
ABSTRACT: Roche 454 pyrosequencing has become a method of choice for generating transcriptome data from non-model organisms. Once the tens to hundreds of thousands of short (250-450 base) reads have been produced, it is important to correctly assemble these to estimate the sequence of all the transcripts. Most transcriptome assembly projects use only one program for assembling 454 pyrosequencing reads, but there is no evidence that the programs used to date are optimal. We have carried out a systematic comparison of five assemblers (CAP3, MIRA, Newbler, SeqMan and CLC) to establish best practices for transcriptome assemblies, using a new dataset from the parasitic nematode Litomosoides sigmodontis.Although no single assembler performed best on all our criteria, Newbler 2.5 gave longer contigs, better alignments to some reference sequences, and was fast and easy to use. SeqMan assemblies performed best on the criterion of recapitulating known transcripts, and had more novel sequence than the other assemblers, but generated an excess of small, redundant contigs. The remaining assemblers all performed almost as well, with the exception of Newbler 2.3 (the version currently used by most assembly projects), which generated assemblies that had significantly lower total length. As different assemblers use different underlying algorithms to generate contigs, we also explored merging of assemblies and found that the merged datasets not only aligned better to reference sequences than individual assemblies, but were also more consistent in the number and size of contigs.Transcriptome assemblies are smaller than genome assemblies and thus should be more computationally tractable, but are often harder because individual contigs can have highly variable read coverage. Comparing single assemblers, Newbler 2.5 performed best on our trial data set, but other assemblers were closely comparable. Combining differently optimal assemblies from different programs however gave a more credible final product, and this strategy is recommended.
Project description:BACKGROUND: The quantity of transcriptome data is rapidly increasing for non-model organisms. As sequencing technology advances, focus shifts towards solving bioinformatic challenges, of which sequence read assembly is the first task. Recent studies have compared the performance of different software to establish a best practice for transcriptome assembly. Here, we adapted a simulation approach to evaluate specific features of assembly programs on 454 data. The novelty of our study is that the simulation allows us to calculate a model assembly as reference point for comparison. FINDINGS: The simulation approach allows us to compare basic metrics of assemblies computed by different software applications (CAP3, MIRA, Newbler, and Oases) to a known optimal solution. We found MIRA and CAP3 are conservative in merging reads. This resulted in comparably high number of short contigs. In contrast, Newbler more readily merged reads into longer contigs, while Oases produced the overall shortest assembly. Due to the simulation approach, reads could be traced back to their correct placement within the transcriptome. Together with mapping reads onto the assembled contigs, we were able to evaluate ambiguity in the assemblies. This analysis further supported the conservative nature of MIRA and CAP3, which resulted in low proportions of chimeric contigs, but high redundancy. Newbler produced less redundancy, but the proportion of chimeric contigs was higher. CONCLUSION: Our evaluation of four assemblers suggested that MIRA and Newbler slightly outperformed the other programs, while showing contrasting characteristics. Oases did not perform very well on the 454 reads. Our evaluation indicated that the software was either conservative (MIRA) or liberal (Newbler) about merging reads into contigs. This suggested that in choosing an assembly program researchers should carefully consider their follow up analysis and consequences of the chosen approach to gain an assembly.
Project description:BACKGROUND: As more and more reference genome sequences are assembled, it becomes practical to assemble individual genomes from large amount of raw read data based on a reference sequence. However, most available assembly tools are designed for de-novo genome assembly. There is one commercial tool box (Newbler) developed for re-sequencing projects based on the Roche 454 sequencing platform. However, the genome with large repeat regions cannot be well assembled in Newbler. FINDINGS: We developed a new sequence assembly tool (BIGrat, Beijing Institute of Genomics Re-Assembly Tool) for pyrosequencing-based re-sequencing projects, such as data generated from Roche 454 and IonTorrent platforms. BIGrat improves the output of Newbler when evaluated on genome assemblies including chloroplast, mitochondrial, bacterial, and plant nuclear genomes. CONCLUSION: We presented a novel sequence assembly tool BIGrat for pyrosequencing-based re-sequencing projects, which can easily be integrated into Newbler pipelines for next-generation sequencing assembly and analysis.
Project description:DNA sequence reads from Sanger and pyrosequencing platforms differ in cost, accuracy, typical coverage, average read length and the variety of available paired-end protocols. Both read types can complement one another in a 'hybrid' approach to whole-genome shotgun sequencing projects, but assembly software must be modified to accommodate their different characteristics. This is true even of pyrosequencing mated and unmated read combinations. Without special modifications, assemblers tuned for homogeneous sequence data may perform poorly on hybrid data.Celera Assembler was modified for combinations of ABI 3730 and 454 FLX reads. The revised pipeline called CABOG (Celera Assembler with the Best Overlap Graph) is robust to homopolymer run length uncertainty, high read coverage and heterogeneous read lengths. In tests on four genomes, it generated the longest contigs among all assemblers tested. It exploited the mate constraints provided by paired-end reads from either platform to build larger contigs and scaffolds, which were validated by comparison to a finished reference sequence. A low rate of contig mis-assembly was detected in some CABOG assemblies, but this was reduced in the presence of sufficient mate pair data.The software is freely available as open-source from http://wgs-assembler.sf.net under the GNU Public License.
Project description:Next generation sequencing platforms have recently been used to rapidly characterize transcriptome sequences from a number of non-model organisms. The present study compares two of the most frequently used platforms, the Roche 454-pyrosequencing and the Illumina sequencing-by-synthesis (SBS), on the same RNA sample obtained from an intertidal gastropod mollusc species, Haliotis midae. All the sequencing reads were deposited in the Short Read Archive (SRA) database are retrievable under the accession number [SRR071314 (Illumina Genome Analyzer II)] and [SRR1737738, SRR1737737, SRR1737735, SRR1737734 (454 GS FLX)] in the SRA database of NCBI. Three transcriptomes, composed of either pure 454 or Illumina reads or a mixture of read types (Hybrid), were assembled using CLC Genomics Workbench software. Illumina assemblies performed the best de novo transcriptome characterization in terms of contig length, whereas the 454 assemblies tended to improve the complete assembly of gene transcripts. Both the Hybrid and Illumina assemblies produced longer contigs covering more of the transcriptome than 454 assemblies. However, the addition of 454 significantly increased the number of genes annotated.
Project description:BACKGROUND: Expressed Sequence Tags (ESTs) have played significant roles in gene discovery and gene functional analysis, especially for non-model organisms. For organisms with no full genome sequences available, ESTs are normally assembled into longer consensus sequences for further downstream analysis. However current de novo EST assembly programs often generate large number of assembly errors that will negatively affect the downstream analysis. In order to generate more accurate consensus sequences from ESTs, tools are needed to reduce or eliminate errors from de novo assemblies. RESULTS: We present iAssembler, a pipeline that can assemble large-scale ESTs into consensus sequences with significantly higher accuracy than current existing assemblers. iAssembler employs MIRA and CAP3 assemblers to generate initial assemblies, followed by identifying and correcting two common types of transcriptome assembly errors: 1) ESTs from different transcripts (mainly alternatively spliced transcripts or paralogs) are incorrectly assembled into same contigs; and 2) ESTs from same transcripts fail to be assembled together. iAssembler can be used to assemble ESTs generated using the traditional Sanger method and/or the Roche-454 massive parallel pyrosequencing technology. CONCLUSION: We compared performances of iAssembler and several other de novo EST assembly programs using both Roche-454 and Sanger EST datasets. It demonstrated that iAssembler generated significantly more accurate consensus sequences than other assembly programs.
Project description:BACKGROUND: Pyrosequencing techniques allow scientists to perform prokaryotic genome sequencing to achieve the draft genomic sequences within a few days. However, the assemblies with shotgun sequencing are usually composed of hundreds of contigs. A further multiplex PCR procedure is needed to fill all the gaps and link contigs into complete chromosomal sequence, which is the basis for prokaryotic comparative genomic studies. In this article, we study various pyrosequencing strategies by simulated assembling from 100 prokaryotic genomes. FINDINGS: Simulation study shows that a single end 454 Jr. run combined with a paired end 454 Jr. run (8 kb library) can produce: 1) ~90% of 100 assemblies with < 10 scaffolds and ~95% of 100 assemblies with < 150 contigs; 2) average contig N50 size is over 331 kb; 3) average single base accuracy is > 99.99%; 4) average false gene duplication rate is < 0.7%; 5) average false gene loss rate is < 0.4%. CONCLUSIONS: A single end 454 Jr. run combined with a paired end 454 Jr. run (8 kb library) is a cost-effective way for prokaryotic whole genome sequencing. This strategy provides solution to produce high quality draft assemblies for most of prokaryotic organisms within days. Due to the small number of assembled scaffolds, the following multiplex PCR procedure (for gap filling) would be easy. As a result, large scale prokaryotic whole genome sequencing projects may be finished within weeks.
Project description:Next generation sequencing (NGS) technologies have greatly changed the landscape of transcriptomic studies of non-model organisms. Since there is no reference genome available, de novo assembly methods play key roles in the analysis of these data sets. Because of the huge amount of data generated by NGS technologies for each run, many assemblers, e.g., ABySS, Velvet and Trinity, are developed based on a de Bruijn graph due to its time- and space-efficiency. However, most of these assemblers were developed initially for the Illumina/Solexa platform. The performance of these assemblers on 454 transcriptomic data is unknown. In this study, we evaluated and compared the relative performance of these de Bruijn graph based assemblers on both simulated and real 454 transcriptomic data. The results suggest that Trinity, the Illumina/Solexa-specialized transcriptomic assembler, performs the best among the multiple de Bruijn graph assemblers, comparable to or even outperforming the standard 454 assembler Newbler which is based on the overlap-layout-consensus algorithm. Our evaluation is expected to provide helpful guidance for researchers to choose assemblers when analyzing 454 transcriptomic data.
Project description:BACKGROUND: Until recently, read lengths on the Solexa/Illumina system were too short to reliably assemble transcriptomes without a reference sequence, especially for non-model organisms. However, with read lengths up to 100 nucleotides available in the current version, an assembly without reference genome should be possible. For this study we created an EST data set for the common pond snail Radix balthica by Illumina sequencing of a normalized transcriptome. Performance of three different short read assemblers was compared with respect to: the number of contigs, their length, depth of coverage, their quality in various BLAST searches and the alignment to mitochondrial genes. RESULTS: A single sequencing run of a normalized RNA pool resulted in 16,923,850 paired end reads with median read length of 61 bases. The assemblies generated by VELVET, OASES, and SeqMan NGEN differed in the total number of contigs, contig length, the number and quality of gene hits obtained by BLAST searches against various databases, and contig performance in the mt genome comparison. While VELVET produced the highest overall number of contigs, a large fraction of these were of small size (< 200bp), and gave redundant hits in BLAST searches and the mt genome alignment. The best overall contig performance resulted from the NGEN assembly. It produced the second largest number of contigs, which on average were comparable to the OASES contigs but gave the highest number of gene hits in two out of four BLAST searches against different reference databases. A subsequent meta-assembly of the four contig sets resulted in larger contigs, less redundancy and a higher number of BLAST hits. CONCLUSION: Our results document the first de novo transcriptome assembly of a non-model species using Illumina sequencing data. We show that de novo transcriptome assembly using this approach yields results useful for downstream applications, in particular if a meta-assembly of contig sets is used to increase contig quality. These results highlight the ongoing need for improvements in assembly methodology.
Project description:BACKGROUND: The main limitations in the analysis of viral metagenomes are perhaps the high genetic variability and the lack of information in extant databases. To address these issues, several bioinformatic tools have been specifically designed or adapted for metagenomics by improving read assembly and creating more sensitive methods for homology detection. This study compares the performance of different available assemblers and taxonomic annotation software using simulated viral-metagenomic data. RESULTS: We simulated two 454 viral metagenomes using genomes from NCBI's RefSeq database based on the list of actual viruses found in previously published metagenomes. Three different assembly strategies, spanning six assemblers, were tested for performance: overlap-layout-consensus algorithms Newbler, Celera and Minimo; de Bruijn graphs algorithms Velvet and MetaVelvet; and read probabilistic model Genovo. The performance of the assemblies was measured by the length of resulting contigs (using N50), the percentage of reads assembled and the overall accuracy when comparing against corresponding reference genomes. Additionally, the number of chimeras per contig and the lowest common ancestor were estimated in order to assess the effect of assembling on taxonomic and functional annotation. The functional classification of the reads was evaluated by counting the reads that correctly matched the functional data previously reported for the original genomes and calculating the number of over-represented functional categories in chimeric contigs. The sensitivity and specificity of tBLASTx, PhymmBL and the k-mer frequencies were measured by accurate predictions when comparing simulated reads against the NCBI Virus genomes RefSeq database. CONCLUSIONS: Assembling improves functional annotation by increasing accurate assignations and decreasing ambiguous hits between viruses and bacteria. However, the success is limited by the chimeric contigs occurring at all taxonomic levels. The assembler and its parameters should be selected based on the focus of each study. Minimo's non-chimeric contigs and Genovo's long contigs excelled in taxonomy assignation and functional annotation, respectively.tBLASTx stood out as the best approach for taxonomic annotation for virus identification. PhymmBL proved useful in datasets in which no related sequences are present as it uses genomic features that may help identify distant taxa. The k-frequencies underperformed in all viral datasets.
Project description:The common blue mussel, Mytilus edulis, has a bimineralic shell composed of approximately equal proportions of the two major polymorphs of calcium carbonate: calcite and aragonite. The exquisite biological control of polymorph production is the focus of research interest in terms of understanding the details of biomineralisation and the proteins involved in the process of complex shell formation. Recent advances in ease and availability of pyrosequencing and assembly have resulted in a sharp increase in transcriptome data for invertebrate biominerals. We have applied Roche 454 pyrosequencing technology to profile the transcriptome for the mantle tissue of the bivalve M. edulis. A comparison was made between the results of several assembly programs: Roche Newbler assembler versions 2.3, 2.5.2 and 2.6 and MIRA 3.2.1 and 3.4.0. The Newbler and MIRA assemblies were subsequently merged using the CAP3 assembler to give a higher consensus in alignments and a more accurate estimate of the true size of the M. edulis transcriptome. Comparison sequence searches show that the mantle transcripts for M. edulis encode putative proteins exhibiting sequence similarities with previously characterised shell proteins of other species of Mytilus, the Bivalvia Pinctada and haliotid gastropods. Importantly, this enhanced transcriptome has detected several transcripts that encode proteins with sequence similarity with previously described shell biomineral proteins including Shematrins and lysine-rich matrix proteins (KRMPs) not previously found in Mytilus.