Evidence map›Paper›PMID 42533217›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2026

From QTL to candidate genes: a data-driven approach to unravel the genetic architecture of yellow rust resistance in central European wheat.

Jiaojiao Wang, Renate H Schmidt, Guoliang Li, Albrecht Serfling, Jochen C Reif, Yong Jiang

Abstract read
In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

6 authors.

Jiaojiao WangLeibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.
Renate H SchmidtLeibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.
Guoliang LiLeibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.
Albrecht SerflingJulius Kühn Institute (Federal Research Centre for Cultivated Plants), Quedlinburg, Germany.
Jochen C ReifLeibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany. reif@ipk-gatersleben.de.
Yong JiangLeibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany. jiang@ipk-gatersleben.de.

Funding

German Federal Ministry of Research FKZ031B1280C
6 · The paper itself

Abstract

Key message A data mining strategy capitalizing on high-resolution SNP information, sequence variant annotation and QTL information from three populations facilitated an efficient nomination of candidate genes for YR resistance, supported by Yr27 and functional annotations.Abstract Genome-wide association studies (GWAS) have become routine in many crops, but the prioritization of candidate genes remains challenging. Here, we developed a new approach to identify environment-specific quantitative trait loci (QTL) using GWAS and analyzed 5,840 wheat genotypes distributed over three experimental populations, including 5,243 single-cross hybrids and 597 elite lines. Resequencing the parental genotypes identified over 640,000 single-nucleotide polymorphisms (SNPs) after filtering. The hybrid panels were tested in 19 environments for susceptibility to Puccinia striiformis f. sp. tritici (Pst), a pathogen responsible for severe yellow rust (YR) epidemics especially after 2012. QTL patterns in diverse environments showed substantial differences, reflecting spatial and temporal dynamics. Combining high-resolution SNP information, sequence variant annotation and QTL information from different populations obtained via a novel GWAS approach enabled the efficient nomination of candidate genes for YR resistance loci of particular relevance for Central European wheat. The power of the developed strategy for mining data from different experimental populations was demonstrated as the validated resistance gene Yr27 was identified as sole candidate gene for one QTL region.

Indexed as

Disease ResistancePlant DiseasesQuantitative Trait LociTriticumBasidiomycotaChromosome MappingGenes, PlantGenome-Wide Association StudyGenotypePhenotypePolymorphism, Single NucleotidePuccinia

Identifiers

PMID42533217
PMCPMC13423923

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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.