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Record W2116911053 · doi:10.1186/1471-2164-14-702

Generation, functional annotation and comparative analysis of black spruce (Picea mariana) ESTs: an important conifer genomic resource

2013· article· en· W2116911053 on OpenAlexafffund
Ishminder K. Mann, Jill Wegrzyn, Om P. Rajora

Bibliographic record

VenueBMC Genomics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of New BrunswickDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie University
KeywordsBiologyExpressed sequence tagGeneticsGenomicsBlack spruceDNA sequencingGenomeGenBankGeneSequence assemblycDNA libraryGenome projectReference genomeFunctional genomicsTranscriptomeComputational biologyComplementary DNATaigaEcologyGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: EST (expressed sequence tag) sequences and their annotation provide a highly valuable resource for gene discovery, genome sequence annotation, and other genomics studies that can be applied in genetics, breeding and conservation programs for non-model organisms. Conifers are long-lived plants that are ecologically and economically important globally, and have a large genome size. Black spruce (Picea mariana), is a transcontinental species of the North American boreal and temperate forests. However, there are limited transcriptomic and genomic resources for this species. The primary objective of our study was to develop a black spruce transcriptomic resource to facilitate on-going functional genomics projects related to growth and adaptation to climate change. RESULTS: We conducted bidirectional sequencing of cDNA clones from a standard cDNA library constructed from black spruce needle tissues. We obtained 4,594 high quality (2,455 5' end and 2,139 3' end) sequence reads, with an average read-length of 532 bp. Clustering and assembly of ESTs resulted in 2,731 unique sequences, consisting of 2,234 singletons and 497 contigs. Approximately two-thirds (63%) of unique sequences were functionally annotated. Genes involved in 36 molecular functions and 90 biological processes were discovered, including 24 putative transcription factors and 232 genes involved in photosynthesis. Most abundantly expressed transcripts were associated with photosynthesis, growth factors, stress and disease response, and transcription factors. A total of 216 full-length genes were identified. About 18% (493) of the transcripts were novel, representing an important addition to the Genbank EST database (dbEST). Fifty-seven di-, tri-, tetra- and penta-nucleotide simple sequence repeats were identified. CONCLUSIONS: We have developed the first high quality EST resource for black spruce and identified 493 novel transcripts, which may be species-specific related to life history and ecological traits. We have also identified full-length genes and microsatellite-containing ESTs. Based on EST sequence similarities, black spruce showed close evolutionary relationships with congeneric Picea glauca and Picea sitchensis compared to other Pinaceae members and angiosperms. The EST sequences reported here provide an important resource for genome annotation, functional and comparative genomics, molecular breeding, conservation and management studies and applications in black spruce and related conifer species.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.253
Teacher spread0.212 · 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 designObservational
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

Citations11
Published2013
Admission routes2
Has abstractyes

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