Genomic prediction with haplotype blocks in wheat.

Haplotype blocks might carry additional information compared to single SNPs and have therefore been suggested for use as independent variables in genomic prediction. Studies in different species resulted in more accurate predictions than with single SNPs in some traits but not in others. In addition, it remains unclear how the blocks should be built to obtain the greatest prediction accuracies.

Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials.

Genomic prediction has been established in breeding programs to predict the genotypic values of selection candidates without phenotypic data. First results in wheat showed that genomic predictions can also prove useful to select among material for which phenotypic data are available. In such a scenario, the selection candidates are evaluated with low intensity in the field.

Dynamics and interactions of cobalamin and folate status during advanced aging - a longitudinal study in a community-dwelling cohort with multiple follow-ups.

Background: Older people are reported to be prone to imbalances between cobalamin and folate status with possible adverse effects on health. This longitudinal study investigates dynamics and interactions of cobalamin and folate status in a cohort of community-dwelling older adults by considering possible influencing factors.

Methods: In total, 332 subjects ≥ 60 years were investigated over a mean observation period of 12 years.

Prediction of Means and Variances of Crosses With Genome-Wide Marker Effects in Barley.

The expected genetic variance is an important criterion for the selection of crossing partners which will produce superior combinations of genotypes in their progeny. The advent of molecular markers has opened up new vistas for obtaining precise predictors for the genetic variance of a cross, but fast prediction methods that allow plant breeders to select crossing partners based on already available data from their breeding programs without complicated calculations or simulation of breeding populations are still lacking. The main objective of the present study was to demonstrate the practical applicability of an analytical approach for the selection of superior cross combinations with experimental data from a barley breeding program.

Prediction of hybrid performance in maize with a ridge regression model employed to DNA markers and mRNA transcription profiles.

Background: Ridge regression models can be used for predicting heterosis and hybrid performance. Their application to mRNA transcription profiles has not yet been investigated. Our objective was to compare the prediction accuracy of models employing mRNA transcription profiles with that of models employing genome-wide markers using a data set of 98 maize hybrids from a breeding program.