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Record W2963897764 · doi:10.1186/s13007-019-0464-2

Methodology: ssb-MASS: a single seed-based sampling strategy for marker-assisted selection in rice

2019· article· en· W2963897764 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePlant Methods · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsIntertek (Canada)
FundersBill and Melinda Gates Foundation
KeywordsSelection (genetic algorithm)BiologyMarker-assisted selectionPanicleBiotechnologySampling (signal processing)Genetic markerAgronomyComputer scienceGeneticsArtificial intelligenceGene

Abstract

fetched live from OpenAlex

BACKGROUND: Integrated breeding approaches such as combining marker-assisted selection and rapid line fixation through single-seed-descent, can effectively increase the frequency of desirable alleles in a breeding program and increase the rate of genetic gain for quantitative traits by shortening the breeding cycle. However, with most genotyping being outsourced to 3rd party service providers' nowadays, sampling has become the bottleneck for many breeding programs. While seed-chipping as prevailed as an automatable seed sampling protocol in many species, the symmetry of rice seeds makes this solution as laborious and costly as sampling leaf tissue. The aim of this study is to develop, validate and deploy a single seed sampling strategy for marker-assisted selection of fixed lines in rice that is more efficient, cost-effective and convenient compared to leaf-based sampling protocols without compromising the accuracy of the marker-assisted selection results. RESULTS: ) with different physical and/or chemical properties were not significantly different. Nor were there significant differences between single seeds collected 15 days after panicle initiation compared to those harvested at maturity. A large-scale comparison between single seed and leaf-based methodologies showed not only high levels of genotypic concordance between both protocols (~ 99%) but also higher SNP call rates in single seed (99.24% vs. 97.5% in leaf). A cost-benefit analysis showed that this single seed sampling strategy decreased the cost of sampling fourfold. An advantage of this approach is that desirable genotypes can be selected before investing in planting activities reducing the cost associated with field operations. CONCLUSION: This study reports the development of a cost-effective and simple single seed genotyping strategy that facilitates the adoption and deployment of marker-assisted selection strategies in rice. This will allow breeders to increase the frequency of favorable alleles and combine rapid generation advancement techniques much more cost-effectively accelerating the process and efficiency of parental selection and varietal development.

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)0.001
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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.156
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.141
GPT teacher head0.367
Teacher spread0.226 · 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