Although genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data.

The capacity to root from cuttings is a key factor for the mass deployment of superior genotypes in clonal forestry. We studied the genetic basis of rooting capacity by mapping quantitative trait loci (QTLs) that control growth rate and form of root traits in a full-sib family of 93 hybrids derived from an interspecific cross between two Populus species, P. deltoides and P. euramericana. The hybrid family was typed for different marker systems (including SSRs, AFLPs, RAPDs, ISSRs, and SNPs), leading to the construction of two linkage maps based on the female P. deltoides (D map) and male P. euramericana (E map) with a pseudotestcross mapping strategy. The two maps were scanned by functional mapping to detect QTLs that control early growth trajectories of two rooting traits, maximal single-root length and the total number of roots per cutting, measured at five time points in water culture. Of the six QTLs detected for these two growth traits, only one is segregating in P. deltoides with poor rooting capacity, while the other five are segregating in P. euramericana showing good rooting capacity. Tests with functional mapping suggest different developmental patterns of the genetic effects of these root QTLs in time course. Five QTLs were detected to change their effects on root growth trajectories with time, whereas one detected to affect root growth consistently in time course. Knowledge about the genetic and developmental control mechanisms of root QTLs will have important implications for the genetic improvement of vegetative propagation traits in Populus.

We used large samples of expressed sequence tags to characterize the patterns of codon usage bias (CUB) in seven different Citrus species and to analyze their evolutionary effect on selection and base composition. We found that A- and T-ending codons are predominant in Citrus species. Next, we identified 21 codons for 18 different amino acids that were considered preferred codons in all seven species. We then performed correspondence analysis and constructed plots for the effective number of codons (ENCs) to analyze synonymous codon usage. Multiple regression analysis showed that gene expression in each species had a constant influence on the frequency of optional codons (FOP). Base composition differences between the proportions were large. Finally, positive selection was detected during the evolutionary process of the different Citrus species. Overall, our results suggest that codon usages were the result of positive selection. Codon usage variation among Citrus genes is influenced by translational selection, mutational bias, and gene length. CUB is strongly affected by selection pressure at the translational level, and gene length plays only a minor role. One possible explanation for this is that the selection-mediated codon bias is consistently strong in Citrus, which is one of the most widely cultivated fruit trees.