A Comprehensive Bioinformatics Analysis of the Nudix Superfamily in Arabidopsis thaliana

Nudix enzymes are a superfamily with a conserved common reaction mechanism that provides the capacity for the hydrolysis of a broad spectrum of metabolites. We used hidden Markov models based on Nudix sequences from the PFAM and PROSITE databases to identify Nudix hydrolases encoded by the Arabidopsis genome. 25 Nudix hydrolases were identified and classified into 11 individual families by pairwise sequence alignments. Intron phases were strikingly conserved in each family. Phylogenetic analysis showed that all multimember families formed monophyletic clusters. Conserved familial sequence motifs were identified with the MEME motif analysis algorithm. One motif (motif 4) was found in three diverse families. All proteins containing motif 4 demonstrated a degree of preference for substrates containing an ADP moiety. We conclude that HMM model-based genome scanning and MEME motif analysis, respectively, can significantly improve the identification and assignment of function of new members of this mechanistically-diverse protein superfamily

NUCLEAR FACTOR Y Transcription Factors Have Both Opposing and Additive Roles in ABA-Mediated Seed Germination

The authors thank Bing Zhang and Taylor Fore for use of the Zeiss AxioImager microscope and technical assistance. We additionally thank Krishna Suthar and Ashley Robbins for technical support in the lab.Conceived and designed the experiments: BFH RWK. Performed the experiments: RWK CLS KKG JRR NS. Analyzed the data: RWK BFH. Wrote the paper: RWK BFH.In the model organism Arabidopsis thaliana the heterotrimeric transcription factor NUCLEAR FACTOR Y (NF-Y) has been shown to play multiple roles in facilitating plant growth and development. Although NF-Y itself represents a multi-protein transcriptional complex, recent studies have shown important interactions with other transcription factors, especially those in the bZIP family. Here we add to the growing evidence that NF-Y and bZIP form common complexes to affect many processes. We carried out transcriptional profiling on nf-yc mutants and through subsequent analyses found an enrichment of bZIP binding sites in the promoter elements of misregulated genes. Using NF-Y as bait, yeast two hybrid assays yielded interactions with bZIP proteins that are known to control ABA signaling. Accordingly, we find that plants mutant for several NF-Y subunits show characteristic phenotypes associated with the disruption of ABA signaling. While previous reports have shown additive roles for NF-YC family members in photoperiodic flowering, we found that they can have opposing roles in ABA signaling. Collectively, these results demonstrated the importance and complexity of NF-Y in the integration of environmental and hormone signals.Yeshttp://www.plosone.org/static/editorial#pee

Differential (2+1) Jet Event Rates and Determination of alpha_s in Deep Inelastic Scattering at HERA

Events with a (2+1) jet topology in deep-inelastic scattering at HERA are studied in the kinematic range 200 < Q^2< 10,000 GeV^2. The rate of (2+1) jet events has been determined with the modified JADE jet algorithm as a function of the jet resolution parameter and is compared with the predictions of Monte Carlo models. In addition, the event rate is corrected for both hadronization and detector effects and is compared with next-to-leading order QCD calculations. A value of the strong coupling constant of alpha_s(M_Z^2)= 0.118+- 0.002 (stat.)^(+0.007)_(-0.008) (syst.)^(+0.007)_(-0.006) (theory) is extracted. The systematic error includes uncertainties in the calorimeter energy calibration, in the description of the data by current Monte Carlo models, and in the knowledge of the parton densities. The theoretical error is dominated by the renormalization scale ambiguity.Comment: 25 pages, 6 figures, 3 tables, submitted to Eur. Phys.

Measurements of Transverse Energy Flow in Deep-Inelastic Scattering at HERA

Measurements of transverse energy flow are presented for neutral current deep-inelastic scattering events produced in positron-proton collisions at HERA. The kinematic range covers squared momentum transfers Q^2 from 3.2 to 2,200 GeV^2, the Bjorken scaling variable x from 8.10^{-5} to 0.11 and the hadronic mass W from 66 to 233 GeV. The transverse energy flow is measured in the hadronic centre of mass frame and is studied as a function of Q^2, x, W and pseudorapidity. A comparison is made with QCD based models. The behaviour of the mean transverse energy in the central pseudorapidity region and an interval corresponding to the photon fragmentation region are analysed as a function of Q^2 and W.Comment: 26 pages, 8 figures, submitted to Eur. Phys.

Multiplicity Structure of the Hadronic Final State in Diffractive Deep-Inelastic Scattering at HERA

The multiplicity structure of the hadronic system X produced in deep-inelastic processes at HERA of the type ep -> eXY, where Y is a hadronic system with mass M_Y< 1.6 GeV and where the squared momentum transfer at the pY vertex, t, is limited to |t|<1 GeV^2, is studied as a function of the invariant mass M_X of the system X. Results are presented on multiplicity distributions and multiplicity moments, rapidity spectra and forward-backward correlations in the centre-of-mass system of X. The data are compared to results in e+e- annihilation, fixed-target lepton-nucleon collisions, hadro-produced diffractive final states and to non-diffractive hadron-hadron collisions. The comparison suggests a production mechanism of virtual photon dissociation which involves a mixture of partonic states and a significant gluon content. The data are well described by a model, based on a QCD-Regge analysis of the diffractive structure function, which assumes a large hard gluonic component of the colourless exchange at low Q^2. A model with soft colour interactions is also successful.Comment: 22 pages, 4 figures, submitted to Eur. Phys. J., error in first submission - omitted bibliograph

Multi-Jet Event Rates in Deep Inelastic Scattering and Determination of the Strong Coupling Constant

Jet event rates in deep inelastic ep scattering at HERA are investigated applying the modified JADE jet algorithm. The analysis uses data taken with the H1 detector in 1994 and 1995. The data are corrected for detector and hadronization effects and then compared with perturbative QCD predictions using next-to-leading order calculations. The strong coupling constant alpha_S(M_Z^2) is determined evaluating the jet event rates. Values of alpha_S(Q^2) are extracted in four different bins of the negative squared momentum transfer~\qq in the range from 40 GeV2 to 4000 GeV2. A combined fit of the renormalization group equation to these several alpha_S(Q^2) values results in alpha_S(M_Z^2) = 0.117+-0.003(stat)+0.009-0.013(syst)+0.006(jet algorithm).Comment: 17 pages, 4 figures, 3 tables, this version to appear in Eur. Phys. J.; it replaces first posted hep-ex/9807019 which had incorrect figure 4

Uncertainty in Simulating Wheat Yields Under Climate Change

Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1,3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking