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Record W2972091110 · doi:10.3389/fpls.2019.01247

Mapping of Genetic Loci Conferring Resistance to Leaf Rust From Three Globally Resistant Durum Wheat Sources

2019· article· en· W2972091110 on OpenAlexafffund
Dhouha Kthiri, Alexander Loladze, Amidou N’Diaye, Kirby T. Nilsen, Sean Walkowiak, Susanne Dreisigacker, Karim Ammar, Curtis Pozniak

Bibliographic record

VenueFrontiers in Plant Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of Saskatchewan
FundersGenome PrairieWestern Grains Research FoundationMinistry of Agriculture - SaskatchewanUniversity of SaskatchewanGenome Canada
KeywordsQuantitative trait locusRust (programming language)BiologyAgronomyWheat leaf rustChromosomePopulationCommon wheatGeneticsGene

Abstract

fetched live from OpenAlex

Genetic resistance in the host plant is the most economical and environmentally friendly strategy for controlling wheat leaf rust, caused by Puccinia triticina Eriks. The durum wheat lines Gaza (Middle East), Arnacoris (France) and Saragolla (Italy) express high levels of resistance to the Mexican races of P. triticina. Three recombinant inbred line (RIL) populations, derived from crosses of each of these resistance sources to the susceptible line ATRED #2, were evaluated for leaf rust reactions at CIMMYT’s leaf rust nurseries in Mexico. Genetic analyses of host reactions suggested oligogenic control of resistance in all populations. The F8 RILs from each cross were genotyped using the Illumina iSelect 90K array, and high-density genetic maps were constructed for each population. Using composite interval mapping, a total of seven quantitative trait loci (QTL) that provide resistance to leaf rust were identified. Two QTL designated as QLr.usw-6BS and QLr.usw-6BL were identified on chromosome 6B in Gaza, which explained up to 78.5% and 21.3% of the observed leaf rust severity variance, respectively. A major QTL designated as QLr.usw-7BL was detected on the long arm of chromosome 7B in Arnacoris, which accounted for up to 65.9% of the disease severity variance. Arnacoris also carried a minor QTL on chromosome 1BL, designated as QLr.usw-1BL.1 that explained up to 17.7% of the phenotypic variance. Three QTL conferred leaf rust resistance in Saragolla, namely QLr.usw-2BS, QLr.usw-3B and QLr.usw-1BL.2, which accounted for up to 42.3%, 9.4% and 7.1% of the phenotypic variance, respectively. Markers flanking each QTL were physically mapped against the durum wheat reference sequence and candidate genes involved in disease resistance were identified within the QTL intervals. The QTL identified in this study and their closely linked markers are useful resources for gene pyramiding and breeding for durable leaf rust resistance in durum wheat.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.192
Teacher spread0.179 · 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

Citations34
Published2019
Admission routes2
Has abstractyes

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