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Record W2069775531 · doi:10.1186/1471-2164-9-542

Analysis of the Pythium ultimum transcriptome using Sanger and Pyrosequencing approaches

2008· article· en· W2069775531 on OpenAlexafffund
Foo Cheung, Joe Win, Jillian M. Lang, John P. Hamilton, Hue Vuong, Jan E. Leach, Sophien Kamoun, C. André Lévesque, Ned Tisserat, C. Robin Buell

Bibliographic record

VenueBMC Genomics · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsAgriculture and Agri-Food Canada
FundersNatural Sciences and Engineering Research Council of CanadaGatsby Charitable FoundationGenome CanadaOntario GenomicsOntario Genomics InstituteU.S. Department of Agriculture
KeywordsBiologySanger sequencingPyrosequencingGeneticsPythium ultimumPopulationDNA sequencingSequence analysisExpressed sequence tagComputational biologyGeneComplementary DNABotany

Abstract

fetched live from OpenAlex

BACKGROUND: Pythium species are an agriculturally important genus of plant pathogens, yet are not understood well at the molecular, genetic, or genomic level. They are closely related to other oomycete plant pathogens such as Phytophthora species and are ubiquitous in their geographic distribution and host rage. To gain a better understanding of its gene complement, we generated Expressed Sequence Tags (ESTs) from the transcriptome of Pythium ultimum DAOM BR144 (= ATCC 200006 = CBS 805.95) using two high throughput sequencing methods, Sanger-based chain termination sequencing and pyrosequencing-based sequencing-by-synthesis. RESULTS: A single half-plate pyrosequencing (454 FLX) run on adapter-ligated cDNA from a normalized cDNA population generated 90,664 reads with an average read length of 190 nucleotides following cleaning and removal of sequences shorter than 100 base pairs. After clustering and assembly, a total of 35,507 unique sequences were generated. In parallel, 9,578 reads were generated from a library constructed from the same normalized cDNA population using dideoxy chain termination Sanger sequencing, which upon clustering and assembly generated 4,689 unique sequences. A hybrid assembly of both Sanger- and pyrosequencing-derived ESTs resulted in 34,495 unique sequences with 1,110 sequences (3.2%) that were solely derived from Sanger sequencing alone. A high degree of similarity was seen between P. ultimum sequences and other sequenced plant pathogenic oomycetes with 91% of the hybrid assembly derived sequences > 500 bp having similarity to sequences from plant pathogenic Phytophthora species. An analysis of Gene Ontology assignments revealed a similar representation of molecular function ontologies in the hybrid assembly in comparison to the predicted proteomes of three Phytophthora species, suggesting a broad representation of the P. ultimum transcriptome was present in the normalized cDNA population. P. ultimum sequences with similarity to oomycete RXLR and Crinkler effectors, Kazal-like and cystatin-like protease inhibitors, and elicitins were identified. Sequences with similarity to thiamine biosynthesis enzymes that are lacking in the genome sequences of three Phytophthora species and one downy mildew were identified and could serve as useful phylogenetic markers. Furthermore, we identified 179 candidate simple sequence repeats that can be used for genotyping strains of P. ultimum. CONCLUSION: Through these two technologies, we were able to generate a robust set (approximately 10 Mb) of transcribed sequences for P. ultimum. We were able to identify known sequences present in oomycetes as well as identify novel sequences. An ample number of candidate polymorphic markers were identified in the dataset providing resources for phylogenetic and diagnostic marker development for this species. On a technical level, in spite of the depth possible with 454 FLX platform, the Sanger and pyro-based sequencing methodologies were complementary as each method generated sequences unique to each platform.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.095
GPT teacher head0.208
Teacher spread0.112 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations104
Published2008
Admission routes2
Has abstractyes

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