Evidence map›Paper›PMID 38760694›Full record

ArticleBMC plant biology2024

Genome-wide association study identifies novel loci and candidate genes for rust resistance in wheat (Triticum aestivum L.).

Hanif Khan, Gopalareddy Krishnappa, Sudheer Kumar, Narayana Bhat Devate, Nagenahalli Dharmegowda Rathan, Satish Kumar, Chandra Nath Mishra, Sewa Ram, Ratan Tiwari, Om Parkash and 4 more

Abstract read
In one paragraph

Article in BMC plant biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

14 authors.

Hanif KhanICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Gopalareddy KrishnappaICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India. gopalareddy.k@icar.gov.in.
Sudheer KumarICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Narayana Bhat DevateInternational Centre for Agriculture Research in the Dry Area - Food Legume Research Platform, Amlaha, MP, 466113, India.
Nagenahalli Dharmegowda RathanCorteva Agriscience, Hyderabad, Telangana, 500081, India.
Satish KumarICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Chandra Nath MishraICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Sewa RamICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Ratan TiwariICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Om ParkashICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Om Parkash AhlawatICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Harohalli Masthigowda MamruthaICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Gyanendra Pratap SinghICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.
Gyanendra SinghICAR-Indian Institute of Wheat and Barley Research, Karnal, 132001, India.

Funding

Bill & Melinda Gates Foundation OPP1194767
6 · The paper itself

Abstract

backgroundWheat rusts are important biotic stresses, development of rust resistant cultivars through molecular approaches is both economical and sustainable. Extensive phenotyping of large mapping populations under diverse production conditions and high-density genotyping would be the ideal strategy to identify major genomic regions for rust resistance in wheat. The genome-wide association study (GWAS) population of 280 genotypes was genotyped using a 35 K Axiom single nucleotide polymorphism (SNP) array and phenotyped at eight, 10, and, 10 environments, respectively for stem/black rust (SR), stripe/yellow rust (YR), and leaf/brown rust (LR).

resultsForty-one Bonferroni corrected marker-trait associations (MTAs) were identified, including 17 for SR and 24 for YR. Ten stable MTAs and their best combinations were also identified. For YR, AX-94990952 on 1A + AX-95203560 on 4A + AX-94723806 on 3D + AX-95172478 on 1A showed the best combination with an average co-efficient of infection (ACI) score of 1.36. Similarly, for SR, AX-94883961 on 7B + AX-94843704 on 1B and AX-94883961 on 7B + AX-94580041 on 3D + AX-94843704 on 1B showed the best combination with an ACI score of around 9.0. The genotype PBW827 have the best MTA combinations for both YR and SR resistance. In silico study identifies key prospective candidate genes that are located within MTA regions. Further, the expression analysis revealed that 18 transcripts were upregulated to the tune of more than 1.5 folds including 19.36 folds (TraesCS3D02G519600) and 7.23 folds (TraesCS2D02G038900) under stress conditions compared to the control conditions. Furthermore, highly expressed genes in silico under stress conditions were analyzed to find out the potential links to the rust phenotype, and all four genes were found to be associated with the rust phenotype.

conclusionThe identified novel MTAs, particularly stable and highly expressed MTAs are valuable for further validation and subsequent application in wheat rust resistance breeding. The genotypes with favorable MTA combinations can be used as prospective donors to develop elite cultivars with YR and SR resistance.

Indexed as

BasidiomycotaDisease ResistanceGenome-Wide Association StudyPlant DiseasesPolymorphism, Single NucleotideTriticumGenes, PlantGenotypePhenotypePucciniaQuantitative Trait LociGWASLinkage disequilibriumSNPStem rustStripe rustWheat rust

Identifiers

PMID38760694
PMCPMC11100168

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.