A platform has been developed to measure the activity of 23 enzymes that are involved in central carbon and nitrogen metabolism in Arabidopsis thaliana. Activities are assayed in optimized stopped assays and the product then determined using a suite of enzyme cycling assays. The platform requires inexpensive equipment, is organized in a modular manner to optimize logistics, calculates results automatically, combines high sensitivity with throughput, can be robotized, and has a throughput of three to four activities in 100 samples per person/day. Several of the assays, including those for sucrose phosphate synthase, ADP glucose pyrophosphorylase (AGPase), ferredoxin-dependent glutamate synthase, glycerokinase, and shikimate dehydrogenase, provide large advantages over previous approaches. This platform was used to analyze the diurnal changes of enzyme activities in wild-type Columbia-0 (Col-0) and the starchless plastid phosphoglucomutase (pgm) mutant, and in Col-0 during a prolongation of the night. The changes of enzyme activities were compared with the changes of transcript levels determined with the Affymetrix ATH1 array. Changes of transcript levels typically led to strongly damped changes of enzyme activity. There was no relation between the amplitudes of the diurnal changes of transcript and enzyme activity. The largest diurnal changes in activity were found for AGPase and nitrate reductase. Examination of the data and comparison with the literature indicated that these are mainly because of posttranslational regulation. The changes of enzyme activity are also strongly delayed, with the delay varying from enzyme to enzyme. It is proposed that enzyme activities provide a quasi-stable integration of regulation at several levels and provide useful data for the characterization and diagnosis of different physiological states. As an illustration, a decision tree constructed using data from Col-0 during diurnal changes and a prolonged dark treatment was used to show that, irrespective of the time of harvest during the diurnal cycle, the pgm mutant resembles a wild-type plant that has been exposed to a 3 d prolongation of the night.

MapMan is a user-driven tool that displays large genomics datasets onto diagrams of metabolic pathways or other processes. Here, we present new developments, including improvements of the gene assignments and the user interface, a strategy to visualize multilayered datasets, the incorporation of statistics packages, and extensions of the software to incorporate more biological information including visualization of coresponding genes and horizontal searches for similar global responses across large numbers of arrays.

SummaryIn order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS).We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29 355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions.We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P < 1.7 9 10 À6). Markers were found across 19 chromosomes, explained 1-13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes).The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.

SummaryEstablishing links between phenotypes and molecular variants is of central importance to accelerate genetic improvement of economically important plant species. Our work represents the first genome-wide association study to the inherently complex and currently poorly understood genetic architecture of industrially relevant wood traits.Here, we employed an Illumina Infinium 34K single nucleotide polymorphism (SNP) genotyping array that generated 29 233 high-quality SNPs in c. 3500 broad-based candidate genes within a population of 334 unrelated Populus trichocarpa individuals to establish genomewide associations.The analysis revealed 141 significant SNPs (a ≤ 0.05) associated with 16 wood chemistry/ ultrastructure traits, individually explaining 3-7% of the phenotypic variance. A large set of associations (41% of all hits) occurred in candidate genes preselected for their suggested a priori involvement with secondary growth. For example, an allelic variant in the FRA8 ortholog explained 21% of the total genetic variance in fiber length, when the trait's heritability estimate was considered. The remaining associations identified SNPs in genes not previously implicated in wood or secondary wall formation.Our findings provide unique insights into wood trait architecture and support efforts for population improvement based on desirable allelic variants.

AspectJ implementations of the GoF design patterns show modularity improvements in 17 of 23 cases. These improvements are manifested in terms of better code locality, reusability, composability, and (un)pluggability.The degree of improvement in implementation modularity varies, with the greatest improvement coming when the pattern solution structure involves crosscutting of some form, including one object playing multiple roles, many objects playing one role, or an object playing roles in multiple pattern instances.