Abstract: Yellow rust infections were evaluated in seven different field experiments based on natural or artificial inoculations and using a 1-to-9 scoring scale [1: complete absence of symptoms, 9: severe infection]. Best linear unbiased estimators (BLUEs) across experiments were used as phenotypes for genome-wide association studies (GWAS). GWAS was conducted for 454 whole-genome sequenced (WGS) wheat genotypes considering a kinship matrix computed from genotyping-by-sequencing (GBS) markers. SNP-based GWAS was conducted using WGS variants mapped to Chinese Spring (RefSeq v1.0) while k-mer-based GWAS was performed using the presence/absence of 31-bp-long sequence motifs. For further details on input files and R codes, please read the “README.txt” files.
License: CC BY 4.0 (Creative Commons Attribution)
DOI: 10.5447/ipk/2022/5
Content: 2 Directories 57 Files (1.3 GB)
CONTRIBUTOR: |
Sandip M. Kale,
Fang Liu,
Yusheng Zhao,
Norman Philipp,
Maximilian Rembe,
Yong Jiang,
Ulrike Beukert,
Albrecht Serfling,
Axel Himmelbach,
Jörg Fuchs,
Markus Oppermann,
Stephan Weise,
Philipp H. G. Boeven,
Schacht Johannes,
C. Friedrich H. Longin,
Sonja Kollers,
Nina Pfeiffer,
Viktor Korzun,
Matthias Lange,
Uwe Scholz,
Nils Stein,
Martin Mascher,
Jochen C. Reif
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CREATOR: |
Albert W. Schulthess
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PUBLISHER: | e!DAL - Plant Genomics and Phenomics Research Data Repository (PGP), IPK Gatersleben, Seeland OT Gatersleben, Corrensstraße 3, 06466, Germany |
SIZE: | 1.3 GB |
SUBJECT: | yellow rust (Puccinia striiformis f. sp. tritici ), wheat (Triticum aestivum L.), field inoculations, best linear unbiased estimate (BLUE), genome-wide association study (GWAS), genotyping-by-sequencing (GBS), whole-genome sequencing (WGS), SNP, k-mers |