Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat

BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution ‘nullisomic-tetrasomic’ lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. RESULTS: We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. CONCLUSIONS: We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution

HANDS: a tool for genome-wide discovery of subgenome-specific base-identity in polyploids

BACKGROUND: The analysis of polyploid genomes is problematic because homeologous subgenome sequences are closely related. This relatedness makes it difficult to assign individual sequences to the specific subgenome from which they are derived, and hinders the development of polyploid whole genome assemblies. RESULTS: We here present a next-generation sequencing (NGS)-based approach for assignment of subgenome-specific base-identity at sites containing homeolog-specific polymorphisms (HSPs): ‘HSP base Assignment using NGS data through Diploid Similarity’ (HANDS). We show that HANDS correctly predicts subgenome-specific base-identity at >90% of assayed HSPs in the hexaploid bread wheat (Triticum aestivum) transcriptome, thus providing a substantial increase in accuracy versus previous methods for homeolog-specific base assignment. CONCLUSION: We conclude that HANDS enables rapid and accurate genome-wide discovery of homeolog-specific base-identity, a capability having multiple applications in polyploid genomics

A Bayesian Approach to the Evolution of Metabolic Networks on a Phylogeny

The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions) or complex (incorporating dependencies among reactions) stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves.The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats.We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data

Evolutionary modelling and analysis of Metabolic networks

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Rahnuma: Hypergraph based tool for metabolic pathway prediction and network comparison

Summary: We present a tool called Rahnuma for prediction and analysis of metabolic pathways and comparison of metabolic networks. Rahnuma represents metabolic networks as hypergraphs and computes all possible pathways between two or more metabolites. It provides an intuitive way to answer biological questions focusing on differences between organisms or the evolution of different species by allowing pathway based metabolic network comparisons at an organism as well as at a phylogenetic level. Availability: Rahnuma is available online a

A cell-based high-throughput screen identifies inhibitors that overcome P-glycoprotein (Pgp)-mediated multidrug resistance.

Multidrug resistance (MDR) to chemotherapeutic drugs remains one of the major impediments to the treatment of cancer. Discovery and development of drugs that can prevent and reverse the acquisition of multidrug resistance constitute a foremost challenge in cancer therapeutics. In this work, we screened a library of 1,127 compounds with known targets for their ability to overcome Pgp-mediated multidrug resistance in cancer cell lines. We identified four compounds (CHIR-124, Elesclomol, Tyrphostin-9 and Brefeldin A) that inhibited the growth of two pairs of parental and Pgp-overexpressing multidrug-resistant cell lines with similar potency irrespective of their Pgp status. Mechanistically, CHIR-124 (a potent inhibitor of Chk1 kinase) inhibited Pgp activity in both multidrug-resistant cell lines (KB-V1 and A2780-Pac-Res) as determined through cell-based Pgp-efflux assays. Other three inhibitors on the contrary, were effective in Pgp-overexpressing resistant cells without increasing the cellular accumulation of a Pgp substrate, indicating that they overcome resistance by avoiding efflux through Pgp. None of these compounds modulated the expression of Pgp in resistant cell lines. PIK-75, a PI3 Kinase inhibitor, was also determined to inhibit Pgp activity, despite being equally potent in only one of the two pairs of resistant and parental cell lines. Strong binding of both CHIR-124 and PIK-75 to Pgp was predicted through docking studies and both compounds inhibited Pgp in a biochemical assay. The inhibition of Pgp causes accumulation of these compounds in the cells where they can modulate the function of their target proteins and thereby inhibit cell proliferation. In conclusion, we have identified compounds with various cellular targets that overcome multidrug resistance in Pgp-overexpressing cell lines through mechanisms that include Pgp inhibition and efflux evasion. These compounds, therefore, can avoid challenges associated with the co-administration of Pgp inhibitors with chemotherapeutic or targeted drugs such as additive toxicities and differing pharmacokinetic properties

Data from: Local adaptation is associated with zinc tolerance in Pseudomonas endophytes of the metal-hyperaccumulator plant Noccaea caerulescens

Metal hyperaccumulating plants, which are hypothesised to use metals for defence against pests and pathogens, provide a unique context in which to study plant–pathogen co-evolution. Previously, we demonstrated that the high concentrations of zinc found in leaves of the hyperaccumulator Noccaea caerulescens provide protection against bacterial pathogens, with a potential trade-off between metal-based and pathogen-induced defences. We speculated that an evolutionary arms race between zinc-based defences in N. caerulescens and zinc tolerance in pathogens might have driven the development of the hyperaccumulation phenotype. Here, we investigate the possibility of local adaptation by bacteria to the zinc-rich environment of N. caerulescens leaves and show that leaves sampled from the contaminated surroundings of a former mine site harboured endophytes with greater zinc tolerance than those within plants of an artificially created hyperaccumulating population. Experimental manipulation of zinc concentrations in plants of this artificial population influenced the zinc tolerance of recovered endophytes. In laboratory experiments, only endophytic bacteria isolated from plants of the natural population were able to grow to high population densities in any N. caerulescens plants. These findings suggest that long-term co-existence with zinc hyperaccumulating plants leads to local adaptation by endophytic bacteria to the environment within their leaves