AUTHOR=Zanke Christine D., Ling Jie , Plieske Jörg , Kollers Sonja , Ebmeyer Erhard , Korzun Viktor , Argillier Odile , Stiewe Gunther , Hinze Maike , Neumann Felix , Eichhorn Andrea , Polley Andreas , Jaenecke Cornelia , Ganal Martin W., Röder Marion S.

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

JOURNAL=Frontiers in Plant Science

VOLUME=6

YEAR=2015

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2015.00644

DOI=10.3389/fpls.2015.00644

ISSN=1664-462X

ABSTRACT=<p>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 (<italic>Triticum aestivum</italic> 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<sup>2</sup> = 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 <italic>Ppd-D1</italic>, dwarfing gene <italic>Rht-B1</italic>and the <italic>TaGW-6A</italic> 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 (-log<sub>10</sub> (<italic>P</italic>-value) ≥ 3.0) marker trait associations (MTAs) were detected for SSR-markers and 1195 MTAs (−log<sub>10</sub>(<italic>P</italic>-value) ≥ 3.0) for SNP-markers in all single environments plus the BLUEs. After Bonferroni correction, 28 MTAs remained significant for SSR-markers (−log<sub>10</sub> (<italic>P</italic>-value) ≥ 4.82) and 58 MTAs for SNP-markers (−log<sub>10</sub> (<italic>P</italic>-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<sup>2</sup> values above 6%.</p>