Evidence map›Paper›PMID 41906791›Full record

ArticleThe plant genome2026

GWAS and genomic prediction of crown rust resistance in the southern US elite oat (Avena sativa L.) germplasm.

Janam Prabhat Acharya, Md Ali Babar, Kathy Esvelt Klos, Stephen Harrison, Noah DeWitt, Amir M H Ibrahim, Paul Murphy, Raja Sekhar Nandety, Jason Fiedler

Abstract read
In one paragraph

Article in The plant genome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Janam Prabhat AcharyaDepartment of Agronomy, University of Florida, Gainesville, Florida, USA.
Md Ali BabarDepartment of Agronomy, University of Florida, Gainesville, Florida, USA.ORCID https://orcid.org/0000-0001-9951-6856
Kathy Esvelt KlosUSDA-ARS, Pacific West Area, Small Grains and Potato Germplasm Research Unit, Aberdeen, Idaho, USA.ORCID https://orcid.org/0000-0002-7129-657X
Stephen HarrisonSchool of Plant, Environmental and Soil Sciences, Louisiana State University, Baton Rouge, Los Angeles, USA.
Noah DeWittSchool of Plant, Environmental and Soil Sciences, Louisiana State University, Baton Rouge, Los Angeles, USA.ORCID https://orcid.org/0000-0001-9055-993X
Amir M H IbrahimAgriLife Research, Texas A&M University, College Station, Texas, USA.
Paul MurphyDepartment of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina, USA.
Raja Sekhar NandetyUSDA-ARS Cereal Crops Improvement Research Unit, Edward T. Schafer Agricultural Research Center, Fargo, North Dakota, USA.ORCID https://orcid.org/0000-0002-1129-0790
Jason FiedlerUSDA-ARS Cereal Crops Improvement Research Unit, Edward T. Schafer Agricultural Research Center, Fargo, North Dakota, USA.ORCID https://orcid.org/0000-0001-7736-4484

Funding

USDA-ARS & World Food Crops Breeding Program, University of Florida 00123842USDA-ARS & World Food Crops Breeding Program, University of Florida AWD10111
6 · The paper itself

Abstract

Crown rust (CR), caused by Puccinia coronata f. sp. avenae, is a major constraint to oat (Avena sativa L.) production in the southern United States. We dissected the genetic architecture of CR resistance and assessed genomic prediction in 234 winter and facultative oat lines adapted to the southern United States. Using multi-environment phenotyping across five CR-prone sites and 8,234 high-quality single-nucleotide polymorphisms, we conducted genome-wide association study (GWAS) and genomic prediction analyses. GWAS detected 13 significant loci, nine of which co-localized with reported quantitative trait loci  or contained plausible resistance candidates such as leucine-rich repeat (LRR), nucleotide-binding site-LRR, and serine/threonine kinases. A stable locus on chromosome 3D was repeatedly identified in Baton Rouge, LA (2016); Castroville, TX (2016); Winnsboro, LA (2017); and in the combined analysis, indicating cross-environment consistency. Additional loci were supported on chromosome 4C (Citra and Quincy, FL, in 2017, and the combined analysis) and 2A (Winnsboro, LA, in 2017 and the combined analysis). Allele stacking was associated with large phenotypic gains. Lines with five or more favorable alleles showed >56% lower crust and 63% lower Crust_Per than lines with none, supporting marker-assisted pyramiding. Genomic prediction models achieved high prediction accuracy. Parametric models, particularly BayesA and RRBLUP, performed strongly across cross-validation schemes; random forest was broadly comparable; and gradient boosting was lower. These results underscore the effectiveness of using GWAS and genomic prediction to enhance breeding for durable CR resistance in oat and provide a genomic framework for developing resilient cultivars suited to southern United States growing conditions.

Indexed as

AvenaDisease ResistancePlant DiseasesPucciniaGenome, PlantGenome-Wide Association StudyPhenotypePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID41906791
PMCPMC13034105

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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.