Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat

Genomic prediction is a powerful tool to enhance genetic gain in plant breeding. However, the method is accompanied by various complications leading to low prediction accuracy. One of the major challenges arises from the complex dimensionality of marker data. To overcome this issue, we applied two pre-selection methods for SNP markers viz. LD-based haplotype-tagging and GWAS-based trait-linked marker identification. Six different models were tested with preselected SNPs to predict the genomic estimated breeding values (GEBVs) of four traits measured in 419 winter wheat genotypes. Ten different sets of haplotype-tagged SNPs were selected by adjusting the level of LD thresholds. In addition, various sets of trait-linked SNPs were identified with different scenarios from the training-test combined and only from the training populations. The BRR and RR-BLUP models developed from haplotype-tagged SNPs had a higher prediction accuracy for FHB and SPW by 0.07 and 0.092, respectively, compared to the corresponding models developed without marker pre-selection. The highest prediction accuracy for SPW and FHB was achieved with tagged SNPs pruned at weak LD thresholds (r2 < 0.5), while stringent LD was required for spike length (SPL) and flag leaf area (FLA). Trait-linked SNPs identified only from training populations failed to improve the prediction accuracy of the four studied traits. Pre-selection of SNPs via LD-based haplotype-tagging could play a vital role in optimizing genomic selection and reducing genotyping costs. Furthermore, the method could pave the way for developing low-cost genotyping methods through customized genotyping platforms targeting key SNP markers tagged to essential haplotype blocks.

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Main Authors: Alemu, A., Batista, L., Singh, P.K., Ceplitis, A., Chawade, A.
Format: Article biblioteca
Language:English
Published: Springer Verlag 2023
Subjects:AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, Genome-Wide Association Study, Linkage Disequilibrium, Fusarium Head Blight, BREEDING, FUSARIUM, GENETIC LINKAGE, GENETIC MARKERS, GENOTYPES, LEAF AREA, SINGLE NUCLEOTIDE POLYMORPHISM, WHEAT, Wheat,
Online Access:https://hdl.handle.net/10883/22571
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spelling dig-cimmyt-10883-225712023-04-25T16:24:07Z Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat Alemu, A. Batista, L. Singh, P.K. Ceplitis, A. Chawade, A. AGRICULTURAL SCIENCES AND BIOTECHNOLOGY Genome-Wide Association Study Linkage Disequilibrium Fusarium Head Blight BREEDING FUSARIUM GENETIC LINKAGE GENETIC MARKERS GENOTYPES LEAF AREA SINGLE NUCLEOTIDE POLYMORPHISM WHEAT Wheat Genomic prediction is a powerful tool to enhance genetic gain in plant breeding. However, the method is accompanied by various complications leading to low prediction accuracy. One of the major challenges arises from the complex dimensionality of marker data. To overcome this issue, we applied two pre-selection methods for SNP markers viz. LD-based haplotype-tagging and GWAS-based trait-linked marker identification. Six different models were tested with preselected SNPs to predict the genomic estimated breeding values (GEBVs) of four traits measured in 419 winter wheat genotypes. Ten different sets of haplotype-tagged SNPs were selected by adjusting the level of LD thresholds. In addition, various sets of trait-linked SNPs were identified with different scenarios from the training-test combined and only from the training populations. The BRR and RR-BLUP models developed from haplotype-tagged SNPs had a higher prediction accuracy for FHB and SPW by 0.07 and 0.092, respectively, compared to the corresponding models developed without marker pre-selection. The highest prediction accuracy for SPW and FHB was achieved with tagged SNPs pruned at weak LD thresholds (r2 < 0.5), while stringent LD was required for spike length (SPL) and flag leaf area (FLA). Trait-linked SNPs identified only from training populations failed to improve the prediction accuracy of the four studied traits. Pre-selection of SNPs via LD-based haplotype-tagging could play a vital role in optimizing genomic selection and reducing genotyping costs. Furthermore, the method could pave the way for developing low-cost genotyping methods through customized genotyping platforms targeting key SNP markers tagged to essential haplotype blocks. 2023-04-12T20:20:12Z 2023-04-12T20:20:12Z 2023 Article Published Version https://hdl.handle.net/10883/22571 10.1007/s00122-023-04352-8 English https://link.springer.com/article/10.1007/s00122-023-04352-8#Sec26 CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose Open Access Berlin (Germany) Springer Verlag 4 136 0040-5752 Theoretical and Applied Genetics 92
institution CIMMYT
collection DSpace
country México
countrycode MX
component Bibliográfico
access En linea
databasecode dig-cimmyt
tag biblioteca
region America del Norte
libraryname CIMMYT Library
language English
topic AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Genome-Wide Association Study
Linkage Disequilibrium
Fusarium Head Blight
BREEDING
FUSARIUM
GENETIC LINKAGE
GENETIC MARKERS
GENOTYPES
LEAF AREA
SINGLE NUCLEOTIDE POLYMORPHISM
WHEAT
Wheat
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Genome-Wide Association Study
Linkage Disequilibrium
Fusarium Head Blight
BREEDING
FUSARIUM
GENETIC LINKAGE
GENETIC MARKERS
GENOTYPES
LEAF AREA
SINGLE NUCLEOTIDE POLYMORPHISM
WHEAT
Wheat
spellingShingle AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Genome-Wide Association Study
Linkage Disequilibrium
Fusarium Head Blight
BREEDING
FUSARIUM
GENETIC LINKAGE
GENETIC MARKERS
GENOTYPES
LEAF AREA
SINGLE NUCLEOTIDE POLYMORPHISM
WHEAT
Wheat
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Genome-Wide Association Study
Linkage Disequilibrium
Fusarium Head Blight
BREEDING
FUSARIUM
GENETIC LINKAGE
GENETIC MARKERS
GENOTYPES
LEAF AREA
SINGLE NUCLEOTIDE POLYMORPHISM
WHEAT
Wheat
Alemu, A.
Batista, L.
Singh, P.K.
Ceplitis, A.
Chawade, A.
Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat
description Genomic prediction is a powerful tool to enhance genetic gain in plant breeding. However, the method is accompanied by various complications leading to low prediction accuracy. One of the major challenges arises from the complex dimensionality of marker data. To overcome this issue, we applied two pre-selection methods for SNP markers viz. LD-based haplotype-tagging and GWAS-based trait-linked marker identification. Six different models were tested with preselected SNPs to predict the genomic estimated breeding values (GEBVs) of four traits measured in 419 winter wheat genotypes. Ten different sets of haplotype-tagged SNPs were selected by adjusting the level of LD thresholds. In addition, various sets of trait-linked SNPs were identified with different scenarios from the training-test combined and only from the training populations. The BRR and RR-BLUP models developed from haplotype-tagged SNPs had a higher prediction accuracy for FHB and SPW by 0.07 and 0.092, respectively, compared to the corresponding models developed without marker pre-selection. The highest prediction accuracy for SPW and FHB was achieved with tagged SNPs pruned at weak LD thresholds (r2 < 0.5), while stringent LD was required for spike length (SPL) and flag leaf area (FLA). Trait-linked SNPs identified only from training populations failed to improve the prediction accuracy of the four studied traits. Pre-selection of SNPs via LD-based haplotype-tagging could play a vital role in optimizing genomic selection and reducing genotyping costs. Furthermore, the method could pave the way for developing low-cost genotyping methods through customized genotyping platforms targeting key SNP markers tagged to essential haplotype blocks.
format Article
topic_facet AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Genome-Wide Association Study
Linkage Disequilibrium
Fusarium Head Blight
BREEDING
FUSARIUM
GENETIC LINKAGE
GENETIC MARKERS
GENOTYPES
LEAF AREA
SINGLE NUCLEOTIDE POLYMORPHISM
WHEAT
Wheat
author Alemu, A.
Batista, L.
Singh, P.K.
Ceplitis, A.
Chawade, A.
author_facet Alemu, A.
Batista, L.
Singh, P.K.
Ceplitis, A.
Chawade, A.
author_sort Alemu, A.
title Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat
title_short Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat
title_full Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat
title_fullStr Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat
title_full_unstemmed Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat
title_sort haplotype-tagged snps improve genomic prediction accuracy for fusarium head blight resistance and yield-related traits in wheat
publisher Springer Verlag
publishDate 2023
url https://hdl.handle.net/10883/22571
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AT batistal haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat
AT singhpk haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat
AT ceplitisa haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat
AT chawadea haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat
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