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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Format: | Article biblioteca |
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Springer Verlag
2023
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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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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 |
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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 |
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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 |
work_keys_str_mv |
AT alemua haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat AT batistal haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat AT singhpk haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat AT ceplitisa haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat AT chawadea haplotypetaggedsnpsimprovegenomicpredictionaccuracyforfusariumheadblightresistanceandyieldrelatedtraitsinwheat |
_version_ |
1764985230606729216 |