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Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains

Malnutrition of iron (Fe) affects two billion people worldwide. Therefore, enhancing grain Fe concentration (GFeC) in wheat (Triticum aestivum L.) is an important goal for breeding. Here we study the genetic factors underlying GFeC trait by genome-wide association studies (GWAS) and the prediction a...

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Autores principales: Alomari, Dalia Z., Eggert, Kai, von Wirén, Nicolaus, Polley, Andreas, Plieske, Jörg, Ganal, Martin W., Liu, Fang, Pillen, Klaus, Röder, Marion S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6337276/
https://www.ncbi.nlm.nih.gov/pubmed/30585193
http://dx.doi.org/10.3390/ijms20010076
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author Alomari, Dalia Z.
Eggert, Kai
von Wirén, Nicolaus
Polley, Andreas
Plieske, Jörg
Ganal, Martin W.
Liu, Fang
Pillen, Klaus
Röder, Marion S.
author_facet Alomari, Dalia Z.
Eggert, Kai
von Wirén, Nicolaus
Polley, Andreas
Plieske, Jörg
Ganal, Martin W.
Liu, Fang
Pillen, Klaus
Röder, Marion S.
author_sort Alomari, Dalia Z.
collection PubMed
description Malnutrition of iron (Fe) affects two billion people worldwide. Therefore, enhancing grain Fe concentration (GFeC) in wheat (Triticum aestivum L.) is an important goal for breeding. Here we study the genetic factors underlying GFeC trait by genome-wide association studies (GWAS) and the prediction abilities using genomic prediction (GP) in a panel of 369 European elite wheat varieties which was genotyped with 15,523 mapped single-nucleotide polymorphism markers (SNP) and a subpanel of 183 genotypes with 44,233 SNP markers. The resulting means of GFeC from three field experiments ranged from 24.42 to 52.42 μg·g(−1) with a broad-sense heritability (H(2)) equaling 0.59 over the years. GWAS revealed 41 and 137 significant SNPs in the whole and subpanel, respectively, including significant marker-trait associations (MTAs) for best linear unbiased estimates (BLUEs) of GFeC on chromosomes 2A, 3B and 5A. Putative candidate genes such as NAC transcription factors and transmembrane proteins were present on chromosome 2A (763,689,738–765,710,113 bp). The GP for a GFeC trait ranged from low to moderate values. The current study reported GWAS of GFeC for the first time in hexaploid wheat varieties. These findings confirm the utility of GWAS and GP to explore the genetic architecture of GFeC for breeding programs aiming at the improvement of wheat grain quality.
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spelling pubmed-63372762019-01-22 Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains Alomari, Dalia Z. Eggert, Kai von Wirén, Nicolaus Polley, Andreas Plieske, Jörg Ganal, Martin W. Liu, Fang Pillen, Klaus Röder, Marion S. Int J Mol Sci Article Malnutrition of iron (Fe) affects two billion people worldwide. Therefore, enhancing grain Fe concentration (GFeC) in wheat (Triticum aestivum L.) is an important goal for breeding. Here we study the genetic factors underlying GFeC trait by genome-wide association studies (GWAS) and the prediction abilities using genomic prediction (GP) in a panel of 369 European elite wheat varieties which was genotyped with 15,523 mapped single-nucleotide polymorphism markers (SNP) and a subpanel of 183 genotypes with 44,233 SNP markers. The resulting means of GFeC from three field experiments ranged from 24.42 to 52.42 μg·g(−1) with a broad-sense heritability (H(2)) equaling 0.59 over the years. GWAS revealed 41 and 137 significant SNPs in the whole and subpanel, respectively, including significant marker-trait associations (MTAs) for best linear unbiased estimates (BLUEs) of GFeC on chromosomes 2A, 3B and 5A. Putative candidate genes such as NAC transcription factors and transmembrane proteins were present on chromosome 2A (763,689,738–765,710,113 bp). The GP for a GFeC trait ranged from low to moderate values. The current study reported GWAS of GFeC for the first time in hexaploid wheat varieties. These findings confirm the utility of GWAS and GP to explore the genetic architecture of GFeC for breeding programs aiming at the improvement of wheat grain quality. MDPI 2018-12-25 /pmc/articles/PMC6337276/ /pubmed/30585193 http://dx.doi.org/10.3390/ijms20010076 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Alomari, Dalia Z.
Eggert, Kai
von Wirén, Nicolaus
Polley, Andreas
Plieske, Jörg
Ganal, Martin W.
Liu, Fang
Pillen, Klaus
Röder, Marion S.
Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains
title Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains
title_full Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains
title_fullStr Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains
title_full_unstemmed Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains
title_short Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains
title_sort whole-genome association mapping and genomic prediction for iron concentration in wheat grains
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6337276/
https://www.ncbi.nlm.nih.gov/pubmed/30585193
http://dx.doi.org/10.3390/ijms20010076
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