This method can be used to accurately phenotype recombinants by analyzing trait-marker associations in progeny [ 22- 24].
We analyzed trait composition and functional diversity (functional dispersion) of spiders and carabids in woody and herbaceous LLE.
The performance of this model is demonstrated on a real data example, where the analyzed trait, being milk fat or protein yield, was either measured only on a cow or a bull reference population, or recorded on both.
Estimates of branch length, such as divergence time, genetic distance or any other metric proportional to the expected variance for the evolution of each analyzed trait, are unavailable.
QTDT was performed for each analyzed trait in the Finnish and Dutch families, both separately and in the combined dataset.
The use of these criteria provides information on the model performance for each analyzed trait, but they lack an overall measure of the multivariate model performance.
For those genes within the significant QTL confidence intervals (±2 LOD), functional annotations were queried to identify functional relationship between the positional candidate genes and each analyzed trait.
To determine the relationships among the analyzed traits, a Pearson correlation coefficient analysis was performed as shown in Table 2.
In conclusion, we were able to locate QTL for all 3 analyzed traits, and overlapping QTL for several traits were observed.
Least squares regression was used to map loci affecting the analyzed traits, and permutation tests were used to set significance thresholds.
After the repeatability and reproducibility of the system were evaluated, according to our results, the appraisers used the whole scale and showed an adequate level of repeatability (≥0.95), and the reproducibility of analyzed traits was over 0.90 for all traits.
