Pollen dispersal was characterized within a population of the narrowly endemic perennial herb, Centaurea corymbosa, using exclusion-based and likelihood-based paternity analyses carried out on microsatellite data. Data were used to fit a model of pollen dispersal and to estimate the rates of pollen flow and mutation/genotyping error, by developing a new method. Selfing was rare (1.6%). Pollen dispersed isotropically around each flowering plant following a leptokurtic distribution, with 50% of mating pairs separated by less than 11 m, but 22% by more than 40 m. Estimates of pollen flow lacked precision (0-25%), partially because mutations and/or genotyping errors (0.03-1%) could also explain the occurrence of offspring without a compatible candidate father. However, the pollen pool that fertilized these offspring was little differentiated from the adults of the population whereas strongly differentiated from the other populations, suggesting that pollen flow rate among populations was low. Our results suggest that pollen dispersal is too extended to allow differentiation by local adaptation within a population. However, among populations, gene flow might be low enough for such processes to occur.
Using synchronized tobacco Bright Yellow-2 cells and cDNAamplified fragment length polymorphism-based genomewide expression analysis, we built a comprehensive collection of plant cell cycle-modulated genes. Approximately 1,340 periodically expressed genes were identified, including known cell cycle control genes as well as numerous unique candidate regulatory genes. A number of plant-specific genes were found to be cell cycle modulated. Other transcript tags were derived from unknown plant genes showing homology to cell cycle-regulatory genes of other organisms. Many of the genes encode novel or uncharacterized proteins, indicating that several processes underlying cell division are still largely unknown.
SummaryGenetical metabolomics [metabolite profiling combined with quantitative trait locus (QTL) analysis] has been proposed as a new tool to identify loci that control metabolite abundances. This concept was evaluated in a case study with the model tree Populus. Using HPLC, the peak abundances were analyzed of 15 closely related flavonoids present in apical tissues of two full-sib poplar families, Populus deltoides cv. S9-2 · P. nigra cv. Ghoy and P. deltoides cv. S9-2 · P. trichocarpa cv. V24, and correlation and QTL analysis were used to detect flux control points in flavonoid biosynthesis. Four robust metabolite quantitative trait loci (mQTL), associated with rate-limiting steps in flavonoid biosynthesis, were mapped. Each mQTL was involved in the flux control to one or two flavonoids. Based on the identities of the affected metabolites and the flavonoid pathway structure, a tentative function was assigned to three of these mQTL, and the corresponding candidate genes were mapped. The data indicate that the combination of metabolite profiling with QTL analysis is a valuable tool to identify control points in a complex metabolic pathway of closely related compounds.
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