What Can Causal Networks Tell Us about Metabolic Pathways?

Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies

Using a limited mapping strategy to identify major QTLs for resistance to grapevine powdery mildew (Erysiphe necator) and their use in marker-assisted breeding

A limited genetic mapping strategy based on simple sequence repeat (SSR) marker data was used with five grape populations segregating for powdery mildew (Erysiphe necator) resistance in an effort to develop genetic markers from multiple sources and enable the pyramiding of resistance loci. Three populations derived their resistance from Muscadinia rotundifolia ‘Magnolia’. The first population (06708) had 97 progeny and was screened with 137 SSR markers from seven chromosomes (4, 7, 9, 12, 13, 15, and 18) that have been reported to be associated with powdery or downy mildew resistance. A genetic map was constructed using the pseudo-testcross strategy and QTL analysis was carried out. Only markers from chromosome 13 and 18 were mapped in the second (04327) and third (06712) populations, which had 47 and 80 progeny, respectively. Significant QTLs for powdery mildew resistance with overlapping genomic regions were identified for different tissue types (leaf, stem, rachis, and berry) on chromosome 18, which distinguishes the resistance in ‘Magnolia’ from that present in other accessions of M. rotundifolia and controlled by the Run1 gene on chromosome 12. The ‘Magnolia’ resistance locus was termed as Run2.1. Powdery mildew resistance was also mapped in a fourth population (08391), which had 255 progeny and resistance from M. rotundifolia ‘Trayshed’. A locus accounting for 50% of the phenotypic variation mapped to chromosome 18 and was named Run2.2. This locus overlapped the region found in the ‘Magnolia’-based populations, but the allele sizes of the flanking markers were different. ‘Trayshed’ and ‘Magnolia’ shared at least one allele for 68% of the tested markers, but alleles of the other 32% of the markers were not shared indicating that the two M. rotundifolia selections were very different. The last population, 08306 with 42 progeny, derived its resistance from a selection Vitis romanetii C166-043. Genetic mapping discovered a major powdery mildew resistance locus termed Ren4 on chromosome 18, which explained 70% of the phenotypic variation in the same region of chromosome 18 found in the two M. rotundifolia resistant accessions. The mapping results indicate that powdery mildew resistance genes from different backgrounds reside on chromosome 18, and that genetic markers can be used as a powerful tool to pyramid these loci and other powdery mildew resistance loci into a single line

Exploring the Diversity of Plant DNA Viruses and Their Satellites Using Vector-Enabled Metagenomics on Whiteflies

Current knowledge of plant virus diversity is biased towards agents of visible and economically important diseases. Less is known about viruses that have not caused major diseases in crops, or viruses from native vegetation, which are a reservoir of biodiversity that can contribute to viral emergence. Discovery of these plant viruses is hindered by the traditional approach of sampling individual symptomatic plants. Since many damaging plant viruses are transmitted by insect vectors, we have developed “vector-enabled metagenomics” (VEM) to investigate the diversity of plant viruses. VEM involves sampling of insect vectors (in this case, whiteflies) from plants, followed by purification of viral particles and metagenomic sequencing. The VEM approach exploits the natural ability of highly mobile adult whiteflies to integrate viruses from many plants over time and space, and leverages the capability of metagenomics for discovering novel viruses. This study utilized VEM to describe the DNA viral community from whiteflies (Bemisia tabaci) collected from two important agricultural regions in Florida, USA. VEM successfully characterized the active and abundant viruses that produce disease symptoms in crops, as well as the less abundant viruses infecting adjacent native vegetation. PCR assays designed from the metagenomic sequences enabled the complete sequencing of four novel begomovirus genome components, as well as the first discovery of plant virus satellites in North America. One of the novel begomoviruses was subsequently identified in symptomatic Chenopodium ambrosiodes from the same field site, validating VEM as an effective method for proactive monitoring of plant viruses without a priori knowledge of the pathogens. This study demonstrates the power of VEM for describing the circulating viral community in a given region, which will enhance our understanding of plant viral diversity, and facilitate emerging plant virus surveillance and management of viral diseases

Cloning and functional characterization of a class III chitinase gene from grapevine: Inhibition of fungal growth by recombinant VvChiF III

To characterize the structure and function of chitinase genes, a class III chitinase gene (VvChiF III) was isolated from Vitis vinifera cv. Flame seedless. The VvChiF III open reading frame comprised 894nucleotides with no introns and encoded a protein of 297 amino acids. The amino acid sequence encoded by VvChiF III showed a high identity to that of a class III chitinase isolated from V. vinifera cv. Koshu and to other acidic chitinase. Analysis of the VvChiF III amino acid sequence showed that this gene corresponds to the Glyco-hydro-18 super family that consisting of a signal peptide with the length of 25 amino acids. Purified VvChiF III showed chitinase activity toward the soluble substrate,glycolchitin and antifungal activity against Botrytis cinerea

A cDNA from grapevine (Vitis vinifera L.), which shows homology to AGAMOUS and SHATTER�PROOF, is not only expressed in flowers but also throughout berry development.

AgriwetenskappeInstituut Vir WynbiotegnologiePlease help us populate SUNScholar with the post print version of this article. It can be e-mailed to: [email protected]