7 research outputs found

    Comparing de novo assemblers for 454 transcriptome data

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    <p>Abstract</p> <p>Background</p> <p>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 <it>Litomosoides sigmodontis</it>.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p

    Transcriptome Sequencing and De Novo Analysis for Yesso Scallop (Patinopecten yessoensis) Using 454 GS FLX

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    BACKGROUND: Bivalves comprise 30,000 extant species, constituting the second largest group of mollusks. However, limited genetic research has focused on this group of animals so far, which is, in part, due to the lack of genomic resources. The advent of high-throughput sequencing technologies enables generation of genomic resources in a short time and at a minimal cost, and therefore provides a turning point for bivalve research. In the present study, we performed de novo transcriptome sequencing to first produce a comprehensive expressed sequence tag (EST) dataset for the Yesso scallop (Patinopecten yessoensis). RESULTS: In a single 454 sequencing run, 805,330 reads were produced and then assembled into 32,590 contigs, with about six-fold sequencing coverage. A total of 25,237 unique protein-coding genes were identified from a variety of developmental stages and adult tissues based on sequence similarities with known proteins. As determined by GO annotation and KEGG pathway mapping, functional annotation of the unigenes recovered diverse biological functions and processes. Transcripts putatively involved in growth, reproduction and stress/immune-response were identified. More than 49,000 single nucleotide polymorphisms (SNPs) and 2,700 simple sequence repeats (SSRs) were also detected. CONCLUSION: Our data provide the most comprehensive transcriptomic resource currently available for P. yessoensis. Candidate genes potentially involved in growth, reproduction, and stress/immunity-response were identified, and are worthy of further investigation. A large number of SNPs and SSRs were also identified and ready for marker development. This resource should lay an important foundation for future genetic or genomic studies on this species

    New approaches to Prunus transcriptome analysis

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