Oxidase gene from sweetpotato

Polyphenol oxidase is the enzyme responsible for enzymatic browning in sweetpotato that decreases the commercial value of sweetpotato products. Here we reported the cloning and characterization of a new cDNA encoding PPO from sweetpotato, designated as IbPPO (GeneBank accession number: AY822711). The full-length cDNA of IbPPO is 1984 bp with a 1767 bp open reading frame (ORF) encoding a 588 amino acid polypeptide with calculated molecular weight of 65.7 kDa and theoretical pI of 6.28. The coding sequence of IbPPO was also directly amplified from the genomic DNA of sweetpotato that demonstrated that IbPPO was an intron-free gene. The computational comparative analysis revealed that IbPPO showed homology to other PPOs of plant origin and contained a 50 amino acid plastidial transit peptides at its N-terminal and the two conserved CuA and CuB copper-binding motifs in the catalytic region of IbPPO. A highly conserved serine-rich motif was firstly found in the transit peptides of plant PPO enzymes. Then the homology-based structural modeling of IbPPO showed that IbPPO had the typical structure of PPO: the catalytic copper center was accommodated in a central four-helix bundle located in a hydrophobic pocket close to the surface. Finally, the results of the semi-quantitative RT-PCR analysis of IbPPO in different tissues demonstrated that IbPPO could express in all the organs of sweetpotato including: mature leaves, young leaves, the stems of mature leaves (petioles), the storage roots and the veins but at different levels. The highest-level expression of IbPPO was found in veins, followed by storage roots, young leaves and mature leaves; and the lowest-level expression of IbPPO was found in petioles. The present researches will facilitate the development of anti-brown sweetpotato by genetic engineering.     

Learning about gene regulatory networks from gene deletion experiments

Gene regulatory networks are a major focus of interest in molecular biology. A crucial question is how complex regulatory systems are encoded and controlled by the genome. Three recent publications have raised the question of what can be learned about gene regulatory networks from microarray experiments on gene deletion mutants. Using this indirect approach, topological features such as connectivity and modularity have been studied.     

Assessing reliability of gene clusters from gene expression data

The rapid development of microarray technologies has raised many challenging problems in experiment design and data analysis. Although many numerical algorithms have been successfully applied to analyze gene expression data, the effects of variations and uncertainties in measured gene expression levels across samples and experiments have been largely ignored in the literature. In this article, in the context of hierarchical clustering algorithms, we introduce a statistical resampling method to assess the reliability of gene clusters identified from any hierarchical clustering method. Using the clustering trees constructed from the resampled data, we can evaluate the confidence value for each node in the observed clustering tree. A majority-rule consensus tree can be obtained, showing clusters that only occur in a majority of the resampled trees. We illustrate our proposed methods with applications to two published data sets. Although the methods are discussed in the context of hierarchical clustering methods, they can be applied with other cluster-identification methods for gene expression data to assess the reliability of any gene cluster of interest. Electronic Publication     

Detecting recombination from gene trees

In this article, a method is proposed for detecting recombination in the sequences of a gene from a set of closely related organisms. The method, the Homoplasy Test, is appropriate when the sequences are rather similar, differing by 1%-5% of nucleotides. It is effective in detecting relatively frequent recombination between a set of rather similar strains, in contrast to previous methods which detect rare or unique transfers between more distant strains. It is based on the fact that, if there is no recombination and if no repeated mutations have occurred (homoplasy), then the number of polymorphic sites, v, is equal to the number of steps, t, in a most-parsimonious tree. If the number of "apparent homoplasies" in the most-parsimonious tree, h = t-v, is greater than zero, then either homoplasies have occurred by mutation or there has been recombination. An estimate of the distribution of h expected on the null hypothesis of no recombination depends on Se, the "effective site number," defined as follows: if ps is the probability that two independent substitutions in the gene occur at the same site, then Se = 1/ps. Se can be estimated if a suitable outgroup is available. The Homoplasy Test is applied to three bacterial genes and to simulated gene trees with varying amounts of recombination. Methods of estimating the rate, as opposed to the occurrence, of recombination are discussed.      

Information-based methods for predicting gene function from systematic gene knock-downs

Background  

The rapid annotation of genes on a genome-wide scale is now possible for several organisms using high-throughput RNA interference assays to knock down the expression of a specific gene. To date, dozens of RNA interference phenotypes have been recorded for the nematode Caenorhabditis elegans. Although previous studies have demonstrated the merit of using knock-down phenotypes to predict gene function, it is unclear how the data can be used most effectively. An open question is how to optimally make use of phenotypic observations, possibly in combination with other functional genomics datasets, to identify genes that share a common role.     

Recursive regularization for inferring gene networks from time-course gene expression profiles

Background  

Inferring gene networks from time-course microarray experiments with vector autoregressive (VAR) model is the process of identifying functional associations between genes through multivariate time series. This problem can be cast as a variable selection problem in Statistics. One of the promising methods for variable selection is the elastic net proposed by Zou and Hastie (2005). However, VAR modeling with the elastic net succeeds in increasing the number of true positives while it also results in increasing the number of false positives.     

A geraniol-synthase gene from Cinnamomum tenuipilum

Geraniol may accumulate up to 86-98% of the leaf essential oils in geraniol chemotypes of the evergreen camphor tree Cinnamomum tenuipilum. A similarity-based cloning strategy yielded a cDNA clone that appeared to encode a terpene synthase and which could be phylogenetically grouped within the angiosperm monoterpene synthase/subfamily. After its expression in Escherichia coli and enzyme assay with prenyl diphosphates as substrates, the enzyme encoded by the putative C. tenuipilum monoterpene synthase gene was shown to specifically convert geranyl diphosphate to geraniol as a single product by GC-MS analysis. Biochemical characterization of the partially purified recombinant protein revealed a strong dependency for Mg2+ and Mn2+, and an apparent Michaelis constant of 55.8 microM for geranyl diphosphate. Thus, a new member of the monoterpene synthase family was identified and designated as CtGES. The genome contains a single copy of CtGES gene. Expression of CtGES was exclusively observed in the geraniol chemotype of C. tenuipilum. Furthermore, in situ hybridization analysis demonstrated that CtGES mRNA was localized in the oil cells of the leaves.     

Lessons learned from gene transfer approaches

Recent technological advances allow the transfer of genes to the synovial lining of joints. As well as opening novel opportunities for therapy, these techniques provide valuable new tools for the study of synovitis and other aspects of the biology of joints in health and disease. This article reviews briefly the results of experiments in which selected genes have been transferred to the knee joints of healthy rabbits and rabbits with antigen-induced arthritis.     

More to learn from gene knockouts

Gene targeting by homologous recombination in mouse embryonic stem cells is a powerful technique to determine the physiological function of any gene product in embryonic and postnatal development and in molecular pathogenesis. Although the technique is very demanding and still in its developing stage several knockout mice carrying disrupted genes, which were once thought important for the development or molecular pathogenesis of certain tissues, have given unexpected results. A gene/function redundancy or superfluous and on-functional theory has been advanced by many investigatiors to explain the unexpected results. These surprising results may teach us a new lesson and lead to a revision of the strongly held view that highly conserved and abundantly expressed genes have a prominent role and function in cell physiology and development Additional, they may also support the notion that molecular cross-talk among the genes may play an important role in determining the minimal phenotype.