Genomic selection in sugar beet breeding populations.

ABSTRACT:

Background

Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers.

Results

We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predi

SUBMITTER: Wurschum T 

PROVIDER: S-EPMC3848454 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature