Original scientific paper

QTL MAPPING FOR GRAIN QUALITY TRAITS IN TESTCROSSES OF A MAIZE BIPARENTAL POPULATION USING GENOTYPING-BY-SEQUENCING DATA

Vlatko Galić ; Agricultural Institute Osijek, Department of Maize Breeding and Genetics, Južno predgrađe 17, 31103 Osijek, Croatia
Mario Franić ; Agricultural Institute Osijek, Department of Maize Breeding and Genetics, Južno predgrađe 17, 31103 Osijek, Croatia
Antun Jambrović ; Agricultural Institute Osijek, Department of Maize Breeding and Genetics, Južno predgrađe 17, 31103 Osijek, Croatia
Zvonimir Zdunić ; Centre of Excellence for Biodiversity and Molecular Plant Breeding, Svetošimunska 25, 10000 Zagreb, Croatia
Andrija Brkić ; Agricultural Institute Osijek, Department of Maize Breeding and Genetics, Južno predgrađe 17, 31103 Osijek, Croatia
Domagoj Šimić ; Agricultural Institute Osijek, Department of Maize Breeding and Genetics, Južno predgrađe 17, 31103 Osijek, Croatia

Abstract

We performed QTL mapping in testcrosses of maize population IBMSyn4 for three grain quality traits: oil and protein contents and test weight. 191 phenotyped and genotyped lines were used as a training set while 85 genotyped only lines comprised a validation set used to calculate best linear unbiased predictions (BLUP), making a total of 276 phenotypes for the QTL analysis. 92000 filtered Genotyping-By-Sequencing (GBS) SNP markers were used to calculate BLUPs, while a set of 2178 genetically mapped SSRs was used in QTL analysis. By simple QTL scan, we scored several minor effect QTLs: one for oil content (chromosome 1), one for protein content (chromosome 10) and four for test weight (chromosomes 1, 3, 5 and 10). QTLs associated with test weight were found to be additive, and 18.25% of phenotypic variance was explained by their joint effect. Only one QTL for test weight was found to be significant in composite interval mapping and it was mapped on chromosome 5. This QTL accounted for 9.97% of phenotypic variance. QTLs detected in this study represent monitoring of commercially most successful elite maize germplasm for grain quality traits.

Keywords

best linear unbiased predictions; IBM population; maize; quantitative trait loci; grain quality traits

Hrčak ID:

182881

URI

https://hrcak.srce.hr/182881

Publication date:

7.6.2017.

Article data in other languages: croatian

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