Dataset Information

De novo sequence assembly of Albugo candida reveals a small genome relative to other biotrophic oomycetes.

ABSTRACT: BACKGROUND: Albugo candida is a biotrophic oomycete that parasitizes various species of Brassicaceae, causing a disease (white blister rust) with remarkable convergence in behaviour to unrelated rusts of basidiomycete fungi. RESULTS: A recent genome analysis of the oomycete Hyaloperonospora arabidopsidis suggests that a reduction in the number of genes encoding secreted pathogenicity proteins, enzymes for assimilation of inorganic nitrogen and sulphur represent a genomic signature for the evolution of obligate biotrophy. Here, we report a draft reference genome of a major crop pathogen Albugo candida (another obligate biotrophic oomycete) with an estimated genome of 45.3 Mb. This is very similar to the genome size of a necrotrophic oomycete Pythium ultimum (43 Mb) but less than half that of H. arabidopsidis (99 Mb). Sequencing of A. candida transcripts from infected host tissue and zoosporangia combined with genome-wide annotation revealed 15,824 predicted genes. Most of the predicted genes lack significant similarity with sequences from other oomycetes. Most intriguingly, A. candida appears to have a much smaller repertoire of pathogenicity-related proteins than H. arabidopsidis including genes that encode RXLR effector proteins, CRINKLER-like genes, and elicitins. Necrosis and Ethylene inducing Peptides were not detected in the genome of A. candida. Putative orthologs of tat-C, a component of the twin arginine translocase system, were identified from multiple oomycete genera along with proteins containing putative tat-secretion signal peptides. CONCLUSION: Albugo candida has a comparatively small genome amongst oomycetes, retains motility of sporangial inoculum, and harbours a much smaller repertoire of candidate effectors than was recently reported for H. arabidopsidis. This minimal gene repertoire could indicate a lack of expansion, rather than a reduction, in the number of genes that signify the evolution of biotrophy in oomycetes.

SUBMITTER: Links MG

PROVIDER: S-EPMC3206522 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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De novo sequence assembly of Albugo candida reveals a small genome relative to other biotrophic oomycetes.

Links Matthew G MG Holub Eric E Jiang Rays H Y RH Sharpe Andrew G AG Hegedus Dwayne D Beynon Elena E Sillito Dean D Clarke Wayne E WE Uzuhashi Shihomi S Borhan Mohammad H MH

BMC genomics 20111013

<h4>Background</h4>Albugo candida is a biotrophic oomycete that parasitizes various species of Brassicaceae, causing a disease (white blister rust) with remarkable convergence in behaviour to unrelated rusts of basidiomycete fungi.<h4>Results</h4>A recent genome analysis of the oomycete Hyaloperonospora arabidopsidis suggests that a reduction in the number of genes encoding secreted pathogenicity proteins, enzymes for assimilation of inorganic nitrogen and sulphur represent a genomic signature f ...[more]

PMID: 21995639

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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 ability to generate recombinant drug target proteins is important for drug discovery research as it facilitates the investigation of drug-target-interactions in vitro. To accomplish this, the target's exact protein sequence is required. Public databases, such as Ensembl, UniProt and RefSeq, are extensive protein and nucleotide sequence repositories. However, many sequences for non-human organisms are predicted by computational pipelines and may thus be incomplete or incorrect. This could lead to misinterpreted experimental outcomes due to gaps or errors in orthologous drug target sequences. Transcriptome analysis by RNA-Seq has been established as a standard method for gene expression analysis. Apart from this common application, paired-end RNA-Seq data can also be used to obtain full coverage cDNA sequences via de novo transcriptome assembly.MethodsTo assess whether de novo transcriptome assemblies can be used to determine a protein's sequence by searching the assembly for a known orthologous sequence, we generated 3 × 6 = 18 tissue specific assemblies (three organs: brain, kidney and liver; six species: human, mouse, rat, dog, pig and cynomolgus monkey). These assemblies and the manually curated human protein sequences from UniProtKB/Swiss-Prot were used in a reciprocal BLAST search to identify best matching hits. We automated and generalised our approach and present the a&o-tool, a workflow which exploits de novo assemblies of paired-end RNA-Seq data and orthology information for target sequence validation and refinement across related species. Furthermore, the a&o-tool extracts best hits' sequences from a reciprocal BLAST search, translates them into protein sequences, computes a multiple sequence alignment and quantifies the refinement.ResultsFor the three human assemblies we observed a hit rate greater than 60% with 100% sequence coverage and identity. For assemblies from the other species we observed similar hit rates and coverage with highest identities for cynomolgus monkey.ConclusionsIn summary, we show how to refine protein sequences using RNA-Seq data and sequence information from closely related species. With the a&o-tool we provide a fully automated pipeline to perform refinement including cDNA translation and multiple sequence alignment for visual inspection. The major prerequisite for applying the a&o-tool is high quality sequencing data.

Dataset Information

De novo sequence assembly of Albugo candida reveals a small genome relative to other biotrophic oomycetes.

Publications

De novo sequence assembly of Albugo candida reveals a small genome relative to other biotrophic oomycetes.

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