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Record W3103665450 · doi:10.3389/fpls.2020.583738

Identification of New Leaf Rust Resistance Loci in Wheat and Wild Relatives by Array-Based SNP Genotyping and Association Genetics

2020· article· en· W3103665450 on OpenAlexafffundabout
Fizza Fatima, Brent McCallum, Curtis Pozniak, Colin W. Hiebert, Curt A. McCartney, George Fedak, Frank M. You, Sylvie Cloutier

Bibliographic record

VenueFrontiers in Plant Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of SaskatchewanAgriculture and Agri-Food CanadaUniversity of Ottawa
FundersAgriculture and Agri-Food Canada
KeywordsBiologyGeneticsIntrogressionSingle-nucleotide polymorphismPlant disease resistanceQuantitative trait locusGermplasmCandidate geneGenome-wide association studyAssociation mappingRust (programming language)GeneGenotypeBotany

Abstract

fetched live from OpenAlex

Leaf rust caused by Puccinia triticina is the most widespread rust disease of wheat. As pathogen populations are constantly evolving, identification of novel sources of resistance is necessary to maintain disease resistance and stay ahead of this plant-pathogen evolutionary arms race. The wild genepool of wheat is a rich source of genetic diversity, accounting for 44% of the Lr genes identified. Here we performed a genome-wide association study (GWAS) on a diverse germplasm of 385 accessions, including 27 different Triticum and Aegilops species. Genetic characterization using the wheat 90K array and subsequent filtering identified a set of 20,501 single nucleotide polymorphic (SNP) markers. Of those, 9,570 were validated using exome capture and mapped onto the Chinese Spring reference sequence v1.0. Phylogenetic analyses illustrated four major clades, clearly separating the wild species from the T. aestivum and T. turgidum species. GWAS was conducted using eight statistical models for infection types against six leaf rust isolates and leaf rust severity rated in field trials for 3-4 years at 2-3 locations in Canada. Functional annotation of genes containing significant quantitative trait nucleotides (QTNs) identified 96 disease-related loci associated with leaf rust resistance. A total of 21 QTNs were in haplotype blocks or within flanking markers of at least 16 known Lr genes. The remaining significant QTNs were considered loci that putatively harbor new Lr resistance genes. Isolation of these candidate genes will contribute to elucidate their role in leaf rust resistance and promote their usefulness in marker-assisted selection and introgression.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.141

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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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 teacher head, 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

Citations41
Published2020
Admission routes3
Has abstractyes

Explore more

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