MétaCan
Menu
Back to cohort
Record W4210947463 · doi:10.1186/s12864-022-08344-8

Genome sequencing-based coverage analyses facilitate high-resolution detection of deletions linked to phenotypes of gamma-irradiated wheat mutants

2022· article· en· W4210947463 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBMC Genomics · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Genetic and Mutation Studies
Canadian institutionsnot available
FundersInstitute of GeneticsMinistry of Agriculture, Forestry and FisheriesMinistry of Education, Culture, Sports, Science and Technology
KeywordsBiologyGenomeGeneticsLocus (genetics)MutantGeneReference genomeCommon wheatChromosome

Abstract

fetched live from OpenAlex

BACKGROUND: Gamma-irradiated mutants of Triticum aestivum L., hexaploid wheat, provide novel and agriculturally important traits and are used as breeding materials. However, the identification of causative genomic regions of mutant phenotypes is challenging because of the large and complicated genome of hexaploid wheat. Recently, the combined use of high-quality reference genome sequences of common wheat and cost-effective resequencing technologies has made it possible to evaluate genome-wide polymorphisms, even in complex genomes. RESULTS: To investigate whether the genome sequencing approach can effectively detect structural variations, such as deletions, frequently caused by gamma irradiation, we selected a grain-hardness mutant from the gamma-irradiated population of Japanese elite wheat cultivar "Kitahonami." The Hardness (Ha) locus, including the puroindoline protein-encoding genes Pina-D1 and Pinb-D1 on the short arm of chromosome 5D, primarily regulates the grain hardness variation in common wheat. We performed short-read genome sequencing of wild-type and grain-hardness mutant plants, and subsequently aligned their short reads to the reference genome of the wheat cultivar "Chinese Spring." Genome-wide comparisons of depth-of-coverage between wild-type and mutant strains detected ~ 130 Mbp deletion on the short arm of chromosome 5D in the mutant genome. Molecular markers for this deletion were applied to the progeny populations generated by a cross between the wild-type and the mutant. A large deletion in the region including the Ha locus was associated with the mutant phenotype, indicating that the genome sequencing is a powerful and efficient approach for detecting a deletion marker of a gamma-irradiated mutant phenotype. In addition, we investigated a pre-harvest sprouting tolerance mutant and identified a 67.8 Mbp deletion on chromosome 3B where Viviparous-B1 and GRAS family transcription factors are located. Co-dominant markers designed to detect the deletion-polymorphism confirmed the association with low germination rate, leading to pre-harvest sprouting tolerance. CONCLUSIONS: Short read-based genome sequencing of gamma-irradiated mutants facilitates the identification of large deletions linked to mutant phenotypes when combined with segregation analyses in progeny populations. This method allows effective application of mutants with agriculturally important traits in breeding using marker-assisted selection.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.253
Teacher spread0.178 · 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