Evidence map›Paper›PMID 28255670›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2017

Detection and validation of genomic regions associated with resistance to rust diseases in a worldwide hexaploid wheat landrace collection using BayesR and mixed linear model approaches.

Raj K Pasam, Urmil Bansal, Hans D Daetwyler, Kerrie L Forrest, Debbie Wong, Joanna Petkowski, Nicholas Willey, Mandeep Randhawa, Mumta Chhetri, Hanif Miah and 3 more

Abstract read
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In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
9.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Watkins wheat landraces: a treasure of stripe rust resistance alleles identified using multi-model association analyses.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  4. Review
  5. Mining QTLs and candidate genes in bread wheat associated with kernel hardness through GWAS.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  6. Article
  7. Wheat yellow rust in Uruguay: understanding the genetic resistance in a panel of breeding and commercial germplasm.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Mining the Vavilov wheat diversity panel for new sources of adult plant resistance to stripe rust.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 2 countries.

Raj K PasamDepartment of Economic Development, Jobs, Transport and Recourses, AgriBio Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Urmil BansalFaculty of Agriculture and Environment, Plant Breeding Institute-Cobbitty, The University of Sydney, PMB4011, Narellan, NSW, 2567, Australia.
Hans D DaetwylerDepartment of Economic Development, Jobs, Transport and Recourses, AgriBio Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Kerrie L ForrestDepartment of Economic Development, Jobs, Transport and Recourses, AgriBio Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Debbie WongDepartment of Economic Development, Jobs, Transport and Recourses, AgriBio Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Joanna PetkowskiDepartment of Economic Development, Jobs, Transport and Recourses, AgriBio Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Nicholas WilleyFaculty of Agriculture and Environment, Plant Breeding Institute-Cobbitty, The University of Sydney, PMB4011, Narellan, NSW, 2567, Australia.
Mandeep RandhawaFaculty of Agriculture and Environment, Plant Breeding Institute-Cobbitty, The University of Sydney, PMB4011, Narellan, NSW, 2567, Australia.
Mumta ChhetriFaculty of Agriculture and Environment, Plant Breeding Institute-Cobbitty, The University of Sydney, PMB4011, Narellan, NSW, 2567, Australia.
Hanif MiahFaculty of Agriculture and Environment, Plant Breeding Institute-Cobbitty, The University of Sydney, PMB4011, Narellan, NSW, 2567, Australia.
Josquin TibbitsDepartment of Economic Development, Jobs, Transport and Recourses, AgriBio Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Harbans BarianaFaculty of Agriculture and Environment, Plant Breeding Institute-Cobbitty, The University of Sydney, PMB4011, Narellan, NSW, 2567, Australia. matthew.hayden@ecodev.vic.gov.au.
Matthew J HaydenDepartment of Economic Development, Jobs, Transport and Recourses, AgriBio Centre for AgriBioscience, Bundoora, VIC, 3083, Australia. harbans.bariana@sydney.edu.au.
AgriBio · AUUniversity of Sydney · AULa Trobe University · AUCentro Internacional de Mejoramiento de Maíz Y Trigo · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

key messageBayesR and MLM association mapping approaches in common wheat landraces were used to identify genomic regions conferring resistance to Yr, Lr, and Sr diseases. Deployment of rust resistant cultivars is the most economically effective and environmentally friendly strategy to control rust diseases in wheat. However, the highly evolving nature of wheat rust pathogens demands continued identification, characterization, and transfer of new resistance alleles into new varieties to achieve durable rust control. In this study, we undertook genome-wide association studies (GWAS) using a mixed linear model (MLM) and the Bayesian multilocus method (BayesR) to identify QTL contributing to leaf rust (Lr), stem rust (Sr), and stripe rust (Yr) resistance. Our study included 676 pre-Green Revolution common wheat landrace accessions collected in the 1920-1930s by A.E. Watkins. We show that both methods produce similar results, although BayesR had reduced background signals, enabling clearer definition of QTL positions. For the three rust diseases, we found 5 (Lr), 14 (Yr), and 11 (Sr) SNPs significant in both methods above stringent false-discovery rate thresholds. Validation of marker-trait associations with known rust QTL from the literature and additional genotypic and phenotypic characterisation of biparental populations showed that the landraces harbour both previously mapped and potentially new genes for resistance to rust diseases. Our results demonstrate that pre-Green Revolution landraces provide a rich source of genes to increase genetic diversity for rust resistance to facilitate the development of wheat varieties with more durable rust resistance.

Indexed as

BasidiomycotaBayes TheoremChromosome MappingDisease ResistanceGenetic Association StudiesGenetic VariationGenotypeLinear ModelsPhenotypePlant DiseasesPolymorphism, Single NucleotidePolyploidyQuantitative Trait LociTriticum

Identifiers

PMID28255670
OpenAlexW2594400855

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.