PANOMICS meets germplasm

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, ranslational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding

Time-resolved impulse response of the magnetoplasmon resonance in a two-dimensional electron gas

We have used optically excited ultrashort electrical pulses to measure the magnetoplasmon resonance of a two-dimensional electron gas formed in an AlGaAs/GaAs heterostructure at frequencies up to 200 gigahertz. This is accomplished by incorporating the sample into a guided wave probe operating in a pumped (^{3}He) system. We are able to detect the resonance by launching a stimulus pulse in the guide, and monitoring the system response in a time resolved pump-probe arrangement. Data obtained from measurements yield resonant frequencies that agree with the magnetoplasmon dispersion relation.Comment: 4 pages, 4 figure

PhosPhAt: a database of phosphorylation sites in Arabidopsis thaliana and a plant-specific phosphorylation site predictor

The PhosPhAt database provides a resource consolidating our current knowledge of mass spectrometry-based identified phosphorylation sites in Arabidopsis and combines it with phosphorylation site prediction specifically trained on experimentally identified Arabidopsis phosphorylation motifs. The database currently contains 1187 unique tryptic peptide sequences encompassing 1053 Arabidopsis proteins. Among the characterized phosphorylation sites, there are over 1000 with unambiguous site assignments, and nearly 500 for which the precise phosphorylation site could not be determined. The database is searchable by protein accession number, physical peptide characteristics, as well as by experimental conditions (tissue sampled, phosphopeptide enrichment method). For each protein, a phosphorylation site overview is presented in tabular form with detailed information on each identified phosphopeptide. We have utilized a set of 802 experimentally validated serine phosphorylation sites to develop a method for prediction of serine phosphorylation (pSer) in Arabidopsis. An analysis of the current annotated Arabidopsis proteome yielded in 27 782 predicted phosphoserine sites distributed across 17 035 proteins. These prediction results are summarized graphically in the database together with the experimental phosphorylation sites in a whole sequence context. The Arabidopsis Protein Phosphorylation Site Database (PhosPhAt) provides a valuable resource to the plant science community and can be accessed through the following link http://phosphat.mpimp-golm.mpg.d

Otopathogenic Staphylococcus aureus Invades Human Middle Ear Epithelial Cells Primarily through Cholesterol Dependent Pathway

Chronic suppurative otitis media (CSOM) is one of the most common infectious diseases of the middle ear especially affecting children, leading to delay in language development and communication. Although Staphylococcus aureus is the most common pathogen associated with CSOM, its interaction with middle ear epithelial cells is not well known. In the present study, we observed that otopathogenic S. aureus has the ability to invade human middle ear epithelial cells (HMEECs) in a dose and time dependent manner. Scanning electron microscopy demonstrated time dependent increase in the number of S. aureus on the surface of HMEECs. We observed that otopathogenic S. aureus primarily employs a cholesterol dependent pathway to colonize HMEECs. In agreement with these findings, confocal microscopy showed that S. aureus colocalized with lipid rafts in HMEECs. The results of the present study provide new insights into the pathogenesis of S. aureus induced CSOM. The availability of in vitro cell culture model will pave the way to develop novel effective treatment modalities for CSOM beyond antibiotic therapy

Thermodynamic Signature of a Two-Dimensional Metal-Insulator Transition

We present a study of the compressibility, K, of a two-dimensional hole system which exhibits a metal-insulator phase transition at zero magnetic field. It has been observed that dK/dp changes sign at the critical density for the metal-insulator transition. Measurements also indicate that the insulating phase is incompressible for all values of B. Finally, we show how the phase transition evolves as the magnetic field is varied and construct a phase diagram in the density-magnetic field plane for this system.Comment: 4 pages, 4 figures, submitted to Physical Review Letters; version 1 is identical to version 2 but didn't compile properl

Coulomb drag between one-dimensional conductors

We have analyzed Coulomb drag between currents of interacting electrons in two parallel one-dimensional conductors of finite length $L$ attached to external reservoirs. For strong coupling, the relative fluctuations of electron density in the conductors acquire energy gap $M$. At energies larger than $\Gamma = const \times v_- \exp (-LM/v_-)/L + \Gamma_{+}$, where $\Gamma_{+}$ is the impurity scattering rate, and for $L>v_-/M$, where $v_-$ is the fluctuation velocity, the gap leads to an ``ideal'' drag with almost equal currents in the conductors. At low energies the drag is suppressed by coherent instanton tunneling, and the zero-temperature transconductance vanishes, indicating the Fermi liquid behavior.Comment: 5 twocolumn pages in RevTex, added 1 eps-Figure and calculation of trans-resistanc

Unpredictability of metabolism—the key role of metabolomics science in combination with next-generation genome sequencing

Next-generation sequencing provides technologies which sequence whole prokaryotic and eukaryotic genomes in days, perform genome-wide association studies, chromatin immunoprecipitation followed by sequencing and RNA sequencing for transcriptome studies. An exponentially growing volume of sequence data can be anticipated, yet functional interpretation does not keep pace with the amount of data produced. In principle, these data contain all the secrets of living systems, the genotype–phenotype relationship. Firstly, it is possible to derive the structure and connectivity of the metabolic network from the genotype of an organism in the form of the stoichiometric matrix N. This is, however, static information. Strategies for genome-scale measurement, modelling and predicting of dynamic metabolic networks need to be applied. Consequently, metabolomics science—the quantitative measurement of metabolism in conjunction with metabolic modelling—is a key discipline for the functional interpretation of whole genomes and especially for testing the numerical predictions of metabolism based on genome-scale metabolic network models. In this context, a systematic equation is derived based on metabolomics covariance data and the genome-scale stoichiometric matrix which describes the genotype–phenotype relationship

Consistency analysis of metabolic correlation networks

<p>Abstract</p> <p>Background</p> <p>Metabolic correlation networks are derived from the covariance of metabolites in replicates of metabolomics experiments. They constitute an interesting intermediate between topology (i.e. the system's architecture defined by the set of reactions between metabolites) and dynamics (i.e. the metabolic concentrations observed as fluctuations around steady-state values in the metabolic network).</p> <p>Results</p> <p>Here we analyze, how such a correlation network changes over time, and compare the relative positions of metabolites in the correlation networks with those in established metabolic networks derived from genome databases. We find that network similarity indeed decreases with an increasing time difference between these networks during a day/night course and, counter intuitively, that proximity of metabolites in the correlation network is no indicator of proximity of the metabolites in the metabolic network.</p> <p>Conclusion</p> <p>The organizing principles of correlation networks are distinct from those of metabolic reaction maps. Time courses of correlation networks may in the future prove an important data source for understanding these organizing principles.</p

Multiomics approach unravels fertility transition in a pigeonpea line for a two‐line hybrid system

Pigeonpea [Cajanus cajan (L.) Millsp.] is a pulse crop cultivated in the semi-arid regions of Asia and Africa. It is a rich source of protein and capable of alleviating malnutrition, improving soil health and the livelihoods of small-holder farmers. Hybrid breeding has provided remarkable improvements for pigeonpea productivity, but owing to a tedious and costly seed production system, an alternative two-line hybrid technology is being explored. In this regard, an environmentsensitive male sterile line has been characterized as a thermosensitive male sterile line in pigeonpea precisely responding to day temperature. The male sterile and fertile anthers from five developmental stages were studied by integrating transcriptomics, proteomics and metabolomics supported by precise phenotyping and scanning electron microscopic study. Spatio-temporal analysis of anther\ud transcriptome and proteome revealed 17 repressed DEGs/DEPs in sterile anthers that play a critical role in normal cell wall morphogenesis and tapetal cell development. The male fertility to sterility transitionwasmainly due to a perturbation in auxin homeostasis, leading to impaired cellwallmodification and sugar transport. Limited nutrient utilization thus leads to microspore starvation in response to moderately elevated day temperature which could be restored with auxin-treatment in the male sterile line. Our findings outline a molecular mechanism that underpins fertility transition responses thereby providing a process-oriented two-line hybrid breeding framework for pigeonpea