Aarhus Universitets segl

Luc Janss

Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat

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Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat. / Tsai, Hsin-Yuan; Janss, Luc L; Andersen, Jeppe R et al.
I: Scientific Reports, Bind 10, Nr. 1, 3347, 2020.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Tsai H-Y, Janss LL, Andersen JR, Orabi J, Jensen JD, Jahoor A et al. Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat. Scientific Reports. 2020;10(1):3347. doi: 10.1038/s41598-020-60203-2

Author

Tsai, Hsin-Yuan ; Janss, Luc L ; Andersen, Jeppe R et al. / Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat. I: Scientific Reports. 2020 ; Bind 10, Nr. 1.

Bibtex

@article{9f664a5786574d0088b4baac53540828,
title = "Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat",
abstract = "Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter wheat breeding lines from a commercial breeding program were genotyped with the Illumina 9 K barley or 15 K wheat SNP-chip, and phenotyped in multiple years and locations. For GWAS, in spring barley, a QTL on chr. 4H associated with powdery mildew and ramularia resistance were found. There were several SNPs on chr. 4H showing genome-wide significance with yield traits. In winter wheat, GWAS identified two SNPs on chr. 6A, and one SNP on chr. 1B, significantly associated with quality trait moisture, as well as one SNP located on chr. 5B associated with starch content in the seeds. The significant SNPs identified by multiple trait GWAS were generally the same as those found in single trait GWAS. GWAS including genotype-location information in the model identified significant SNPs in each tested location, which were not found previously when including all locations in the GWAS. For GP, in spring barley, GP using the Bayesian Power Lasso model had higher accuracy than ridge regression BLUP in powdery mildew and yield traits, whereas the prediction accuracies were similar using Bayesian Power Lasso model and rrBLUP for yield traits in winter wheat.",
author = "Hsin-Yuan Tsai and Janss, {Luc L} and Andersen, {Jeppe R} and Jihad Orabi and Jensen, {Jens D} and Ahmed Jahoor and Just Jensen",
year = "2020",
doi = "10.1038/s41598-020-60203-2",
language = "English",
volume = "10",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",

}

RIS

TY - JOUR

T1 - Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat

AU - Tsai, Hsin-Yuan

AU - Janss, Luc L

AU - Andersen, Jeppe R

AU - Orabi, Jihad

AU - Jensen, Jens D

AU - Jahoor, Ahmed

AU - Jensen, Just

PY - 2020

Y1 - 2020

N2 - Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter wheat breeding lines from a commercial breeding program were genotyped with the Illumina 9 K barley or 15 K wheat SNP-chip, and phenotyped in multiple years and locations. For GWAS, in spring barley, a QTL on chr. 4H associated with powdery mildew and ramularia resistance were found. There were several SNPs on chr. 4H showing genome-wide significance with yield traits. In winter wheat, GWAS identified two SNPs on chr. 6A, and one SNP on chr. 1B, significantly associated with quality trait moisture, as well as one SNP located on chr. 5B associated with starch content in the seeds. The significant SNPs identified by multiple trait GWAS were generally the same as those found in single trait GWAS. GWAS including genotype-location information in the model identified significant SNPs in each tested location, which were not found previously when including all locations in the GWAS. For GP, in spring barley, GP using the Bayesian Power Lasso model had higher accuracy than ridge regression BLUP in powdery mildew and yield traits, whereas the prediction accuracies were similar using Bayesian Power Lasso model and rrBLUP for yield traits in winter wheat.

AB - Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter wheat breeding lines from a commercial breeding program were genotyped with the Illumina 9 K barley or 15 K wheat SNP-chip, and phenotyped in multiple years and locations. For GWAS, in spring barley, a QTL on chr. 4H associated with powdery mildew and ramularia resistance were found. There were several SNPs on chr. 4H showing genome-wide significance with yield traits. In winter wheat, GWAS identified two SNPs on chr. 6A, and one SNP on chr. 1B, significantly associated with quality trait moisture, as well as one SNP located on chr. 5B associated with starch content in the seeds. The significant SNPs identified by multiple trait GWAS were generally the same as those found in single trait GWAS. GWAS including genotype-location information in the model identified significant SNPs in each tested location, which were not found previously when including all locations in the GWAS. For GP, in spring barley, GP using the Bayesian Power Lasso model had higher accuracy than ridge regression BLUP in powdery mildew and yield traits, whereas the prediction accuracies were similar using Bayesian Power Lasso model and rrBLUP for yield traits in winter wheat.

U2 - 10.1038/s41598-020-60203-2

DO - 10.1038/s41598-020-60203-2

M3 - Journal article

C2 - 32099054

VL - 10

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 3347

ER -