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Analysis of main effect QTL for thousand grain weight in European winter wheat (Triticum aestivum L.) by genome-wide association mapping.

Zanke CD, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V, Argillier O, Stiewe G, Hinze M, Neumann F, Eichhorn A, Polley A, Jaenecke C, Ganal MW, Röder MS - Front Plant Sci (2015)

Bottom Line: The highest number of significant SNP-markers was found on chromosomes 3B and 1B, while for the SSRs most markers were significant on chromosomes 6D and 3D.Overall, TGW was determined by many markers with small effects.Only three SNP-markers had R(2) values above 6%.

View Article: PubMed Central - PubMed

Affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Germany.

ABSTRACT
Grain weight, an essential yield component, is under strong genetic control and at the same time markedly influenced by the environment. Genetic analysis of the thousand grain weight (TGW) by genome-wide association study (GWAS) was performed with a panel of 358 European winter wheat (Triticum aestivum L.) varieties and 14 spring wheat varieties using phenotypic data of field tests in eight environments. Wide phenotypic variations were indicated for the TGW with BLUEs (best linear unbiased estimations) values ranging from 35.9 to 58.2 g with a mean value of 45.4 g and a heritability of H(2) = 0.89. A total of 12 candidate genes for plant height, photoperiodism and grain weight were genotyped on all varieties. Only three candidates, the photoperiodism gene Ppd-D1, dwarfing gene Rht-B1and the TaGW-6A gene were significant explaining up to 14.4, 2.3, and 3.4% of phenotypic variation, respectively. For a comprehensive genome-wide analysis of TGW-QTL genotyping data from 732 microsatellite markers and a set of 7769 mapped SNP-markers genotyped with the 90k iSELECT array were analyzed. In total, 342 significant (-log10 (P-value) ≥ 3.0) marker trait associations (MTAs) were detected for SSR-markers and 1195 MTAs (-log10(P-value) ≥ 3.0) for SNP-markers in all single environments plus the BLUEs. After Bonferroni correction, 28 MTAs remained significant for SSR-markers (-log10 (P-value) ≥ 4.82) and 58 MTAs for SNP-markers (-log10 (P-value) ≥ 5.89). Apart from chromosomes 4B and 6B for SSR-markers and chromosomes 4D and 5D for SNP-markers, MTAs were detected on all chromosomes. The highest number of significant SNP-markers was found on chromosomes 3B and 1B, while for the SSRs most markers were significant on chromosomes 6D and 3D. Overall, TGW was determined by many markers with small effects. Only three SNP-markers had R(2) values above 6%.

No MeSH data available.


Boxplot for thousand grain weight. Boxplots for the eight field environments are depicted in blue, the BLUEs is shown in red. Asterisks mark outlier varieties. The table below indicates the minimal, maximal and mean TGW values measured in the single environments and estimated for the BLUEs.
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Figure 1: Boxplot for thousand grain weight. Boxplots for the eight field environments are depicted in blue, the BLUEs is shown in red. Asterisks mark outlier varieties. The table below indicates the minimal, maximal and mean TGW values measured in the single environments and estimated for the BLUEs.

Mentions: The means of TGW across 358 winter wheat plus 14 spring wheat varieties in eight field environments ranged from 42.3 g in the environment 10.JAN to 50.2 g in the environment 09.SEL (Figure 1). The highest phenotypic variance was observed in environment 09.WOH, which contained the lowest single value of 30.6 g as well as the highest single value of 62.0 g. The BLUEs across all eight environments ranged from 35.9 g for variety “Carenius” to 58.2 g for variety “CCB Ingénio” and with a mean value of 45.4 g (Supplemental File 4). The continuous distribution of the TGW phenotype indicated a quantitative mode of inheritance and most spring wheat varieties were found in the second half of the distribution containing the varieties with larger grains (Figure 2A). The distribution of the TGW-BLUEs was close to a normal distribution and ranged within a 95% confidence interval in a normal probability plot (Supplemental File 5).


Analysis of main effect QTL for thousand grain weight in European winter wheat (Triticum aestivum L.) by genome-wide association mapping.

Zanke CD, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V, Argillier O, Stiewe G, Hinze M, Neumann F, Eichhorn A, Polley A, Jaenecke C, Ganal MW, Röder MS - Front Plant Sci (2015)

Boxplot for thousand grain weight. Boxplots for the eight field environments are depicted in blue, the BLUEs is shown in red. Asterisks mark outlier varieties. The table below indicates the minimal, maximal and mean TGW values measured in the single environments and estimated for the BLUEs.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4555037&req=5

Figure 1: Boxplot for thousand grain weight. Boxplots for the eight field environments are depicted in blue, the BLUEs is shown in red. Asterisks mark outlier varieties. The table below indicates the minimal, maximal and mean TGW values measured in the single environments and estimated for the BLUEs.
Mentions: The means of TGW across 358 winter wheat plus 14 spring wheat varieties in eight field environments ranged from 42.3 g in the environment 10.JAN to 50.2 g in the environment 09.SEL (Figure 1). The highest phenotypic variance was observed in environment 09.WOH, which contained the lowest single value of 30.6 g as well as the highest single value of 62.0 g. The BLUEs across all eight environments ranged from 35.9 g for variety “Carenius” to 58.2 g for variety “CCB Ingénio” and with a mean value of 45.4 g (Supplemental File 4). The continuous distribution of the TGW phenotype indicated a quantitative mode of inheritance and most spring wheat varieties were found in the second half of the distribution containing the varieties with larger grains (Figure 2A). The distribution of the TGW-BLUEs was close to a normal distribution and ranged within a 95% confidence interval in a normal probability plot (Supplemental File 5).

Bottom Line: The highest number of significant SNP-markers was found on chromosomes 3B and 1B, while for the SSRs most markers were significant on chromosomes 6D and 3D.Overall, TGW was determined by many markers with small effects.Only three SNP-markers had R(2) values above 6%.

View Article: PubMed Central - PubMed

Affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Germany.

ABSTRACT
Grain weight, an essential yield component, is under strong genetic control and at the same time markedly influenced by the environment. Genetic analysis of the thousand grain weight (TGW) by genome-wide association study (GWAS) was performed with a panel of 358 European winter wheat (Triticum aestivum L.) varieties and 14 spring wheat varieties using phenotypic data of field tests in eight environments. Wide phenotypic variations were indicated for the TGW with BLUEs (best linear unbiased estimations) values ranging from 35.9 to 58.2 g with a mean value of 45.4 g and a heritability of H(2) = 0.89. A total of 12 candidate genes for plant height, photoperiodism and grain weight were genotyped on all varieties. Only three candidates, the photoperiodism gene Ppd-D1, dwarfing gene Rht-B1and the TaGW-6A gene were significant explaining up to 14.4, 2.3, and 3.4% of phenotypic variation, respectively. For a comprehensive genome-wide analysis of TGW-QTL genotyping data from 732 microsatellite markers and a set of 7769 mapped SNP-markers genotyped with the 90k iSELECT array were analyzed. In total, 342 significant (-log10 (P-value) ≥ 3.0) marker trait associations (MTAs) were detected for SSR-markers and 1195 MTAs (-log10(P-value) ≥ 3.0) for SNP-markers in all single environments plus the BLUEs. After Bonferroni correction, 28 MTAs remained significant for SSR-markers (-log10 (P-value) ≥ 4.82) and 58 MTAs for SNP-markers (-log10 (P-value) ≥ 5.89). Apart from chromosomes 4B and 6B for SSR-markers and chromosomes 4D and 5D for SNP-markers, MTAs were detected on all chromosomes. The highest number of significant SNP-markers was found on chromosomes 3B and 1B, while for the SSRs most markers were significant on chromosomes 6D and 3D. Overall, TGW was determined by many markers with small effects. Only three SNP-markers had R(2) values above 6%.

No MeSH data available.