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Evaluating characteristics of de novo assembly software on 454 transcriptome data: a simulation approach.

ABSTRACT: 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.

SUBMITTER: Mundry M

PROVIDER: S-EPMC3288049 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Evaluating characteristics of de novo assembly software on 454 transcriptome data: a simulation approach.

Mundry Marvin M Bornberg-Bauer Erich E Sammeth Michael M Feulner Philine G D PG

PloS one 20120227 2

<h4>Background</h4>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 tha ...[more]

PMID: 22384018

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Project description: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:BackgroundLycoris aurea, also called Golden Magic Lily, is an ornamentally and medicinally important species of the Amaryllidaceae family. To date, the sequencing of its whole genome is unavailable as a non-model organism. Transcriptomic information is also scarce for this species. In this study, we performed de novo transcriptome sequencing to produce the first comprehensive expressed sequence tag (EST) dataset for L. aurea using high-throughput sequencing technology.Methodology and principal findingsTotal RNA was isolated from leaves with sodium nitroprusside (SNP), salicylic acid (SA), or methyl jasmonate (MeJA) treatment, stems, and flowers at the bud, blooming, and wilting stages. Equal quantities of RNA from each tissue and stage were pooled to construct a cDNA library. Using 454 pyrosequencing technology, a total of 937,990 high quality reads (308.63 Mb) with an average read length of 329 bp were generated. Clustering and assembly of these reads produced a non-redundant set of 141,111 unique sequences, comprising 24,604 contigs and 116,507 singletons. All of the unique sequences were involved in the biological process, cellular component and molecular function categories by GO analysis. Potential genes and their functions were predicted by KEGG pathway mapping and COG analysis. Based on our sequence analysis and published literatures, many putative genes involved in Amaryllidaceae alkaloids synthesis, including PAL, TYDC OMT, NMT, P450, and other potentially important candidate genes, were identified for the first time in this Lycoris. Furthermore, 6,386 SSRs and 18,107 high-confidence SNPs were identified in this EST dataset.ConclusionsThe transcriptome provides an invaluable new data for a functional genomics resource and future biological research in L. aurea. The molecular markers identified in this study will provide a material basis for future genetic linkage and quantitative trait loci analyses, and will provide useful information for functional genomic research in future.

Project description:The whole-genome sequence assembly (WGSA) problem is among one of the most studied problems in computational biology. Despite the availability of a plethora of tools (i.e., assemblers), all claiming to have solved the WGSA problem, little has been done to systematically compare their accuracy and power. Traditional methods rely on standard metrics and read simulation: while on the one hand, metrics like N50 and number of contigs focus only on size without proportionately emphasizing the information about the correctness of the assembly, comparisons performed on simulated dataset, on the other hand, can be highly biased by the non-realistic assumptions in the underlying read generator. Recently the Feature Response Curve (FRC) method was proposed to assess the overall assembly quality and correctness: FRC transparently captures the trade-offs between contigs' quality against their sizes. Nevertheless, the relationship among the different features and their relative importance remains unknown. In particular, FRC cannot account for the correlation among the different features. We analyzed the correlation among different features in order to better describe their relationships and their importance in gauging assembly quality and correctness. In particular, using multivariate techniques like principal and independent component analysis we were able to estimate the "excess-dimensionality" of the feature space. Moreover, principal component analysis allowed us to show how poorly the acclaimed N50 metric describes the assembly quality. Applying independent component analysis we identified a subset of features that better describe the assemblers performances. We demonstrated that by focusing on a reduced set of highly informative features we can use the FRC curve to better describe and compare the performances of different assemblers. Moreover, as a by-product of our analysis, we discovered how often evaluation based on simulated data, obtained with state of the art simulators, lead to not-so-realistic results.

Project description:BackgroundThe Himalayan or Indian Mayapple (Podophyllum hexandrum Royle) produces podophyllotoxin, which is used in the production of semisynthetic anticancer drugs. High throughput transcriptome sequences or genomic sequence data from the Indian Mayapple are essential for further understanding of the podophyllotoxin biosynthetic pathway.Results454 pyrosequencing of a P. hexandrum cell culture normalized cDNA library generated 2,667,207 raw reads and 1,503,232 high quality reads, with an average read length of 138 bp. The denovo assembly was performed by Newbler using default and optimized parameters. The optimized parameter generated 40, 380 assembled sequences, comprising 12,940 contigs and 27,440 singlets which resulted in better assembly as compared to default parameters. BLASTX analysis resulted in the annotation of 40,380 contigs/singlet using a cut-off value of ≤ 1E-03. High similarity to Medicago truncatula using optimized parameters and to Populus trichocarpa using default parameters was noted. The Kyoto encyclopedia of genes and genomes (KEGG) analysis using KEGG Automatic Annotation Server (KAAS) combined with domain analysis of the assembled transcripts revealed putative members of secondary metabolism pathways that may be involved in podophyllotoxin biosynthesis. A proposed schematic pathway for phenylpropanoids and podophyllotoxin biosynthesis was generated. Expression profiling was carried out based on fragments per kilobase of exon per million fragments (FPKM). 1036 simple sequence repeats were predicted in the P. hexandrum sequences. Sixty-nine transcripts were mapped to 99 mature and precursor microRNAs from the plant microRNA database. Around 961 transcripts containing transcription factor domains were noted. High performance liquid chromatography analysis showed the peak accumulation of podophyllotoxin in 12-day cell suspension cultures. A comparative qRT-PCR analysis of phenylpropanoid pathway genes identified in the present data was performed to analyze their expression patterns in 12-day cell culture, callus and rhizome.ConclusionsThe present data will help the identification of the potential genes and transcription factors involved in podophyllotoxin biosynthesis in P. hexandrum. The assembled transcripts could serve as potential candidates for marker discovery and conservation, which should form the foundations for future endeavors.

Project description:BackgroundNew methods are needed for genomic-scale analysis of emerging model organisms that exemplify important biological questions but lack fully sequenced genomes. For example, there is an urgent need to understand the potential for corals to adapt to climate change, but few molecular resources are available for studying these processes in reef-building corals. To facilitate genomics studies in corals and other non-model systems, we describe methods for transcriptome sequencing using 454, as well as strategies for assembling a useful catalog of genes from the output. We have applied these methods to sequence the transcriptome of planulae larvae from the coral Acropora millepora.ResultsMore than 600,000 reads produced in a single 454 sequencing run were assembled into approximately 40,000 contigs with five-fold average sequencing coverage. Based on sequence similarity with known proteins, these analyses identified approximately 11,000 different genes expressed in a range of conditions including thermal stress and settlement induction. Assembled sequences were annotated with gene names, conserved domains, and Gene Ontology terms. Targeted searches using these annotations identified the majority of genes associated with essential metabolic pathways and conserved signaling pathways, as well as novel candidate genes for stress-related processes. Comparisons with the genome of the anemone Nematostella vectensis revealed approximately 8,500 pairs of orthologs and approximately 100 candidate coral-specific genes. More than 30,000 SNPs were detected in the coral sequences, and a subset of these validated by re-sequencing.ConclusionThe methods described here for deep sequencing of the transcriptome should be widely applicable to generate catalogs of genes and genetic markers in emerging model organisms. Our data provide the most comprehensive sequence resource currently available for reef-building corals, and include an extensive collection of potential genetic markers for association and population connectivity studies. The characterization of the larval transcriptome for this widely-studied coral will enable research into the biological processes underlying stress responses in corals and evolutionary adaptation to global climate change.

Dataset Information

Evaluating characteristics of de novo assembly software on 454 transcriptome data: a simulation approach.

Publications

Evaluating characteristics of de novo assembly software on 454 transcriptome data: a simulation approach.

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