We describe a simple and highly effective means for global identification of genes that are expressed within specific cell types within complex tissues. It involves transgenic expression of nuclear-targeted green fluorescent protein in a cell-type-specific manner. The fluorescent nuclei are then purified from homogenates by fluorescence-activated sorting, and the RNAs employed as targets for microarray hybridization. We demonstrate the validity of the approach through the identification of 12 genes that are selectively expressed in phloem.
Background: In the most general sense, studies involving global analysis of gene expression aim to provide a comprehensive catalog of the components involved in the production of recognizable cellular phenotypes. These studies are often limited by the available technologies. One technology, based on microarrays, categorizes gene expression in terms of the abundance of RNA transcripts, and typically employs RNA prepared from whole cells, where cytoplasmic RNA predominates.
Recombination and reassortment of viral genomes are major processes contributing to the creation of new, emerging viruses. These processes are especially significant in long-term persistent infections where multiple viral genotypes co-replicate in a single host, generating abundant genotypic variants, some of which may possess novel host-colonizing and pathogenicity traits. In some plants, successive vegetative propagation of infected tissues and introduction of new genotypes of a virus by vector transmission allows for viral populations to increase in complexity for hundreds of years allowing co-replication and subsequent recombination of the multiple viral genotypes. Using a resequencing microarray, we examined a persistent infection by a Citrus tristeza virus (CTV) complex in citrus, a vegetatively propagated, globally important fruit crop, and found that the complex comprised three major and a number of minor genotypes. Subsequent deep sequencing analysis of the viral population confirmed the presence of the three major CTV genotypes and, in addition, revealed that the minor genotypes consisted of an extraordinarily large number of genetic variants generated by promiscuous recombination between the major genotypes. Further analysis provided evidence that some of the recombinants underwent subsequent divergence, further increasing the genotypic complexity. These data demonstrate that persistent infection of multiple viral genotypes within a host organism is sufficient to drive the large-scale production of viral genetic variants that may evolve into new and emerging viruses.
To study carbohydrate-mediated adherence of Streptococcus pneumoniae to the human airway, we measured binding of liveS. pneumoniae organisms to a cultured cell line derived from the lining of the conjunctiva and to primary monolayers of human bronchial epithelial cells in the presence and absence of oligosaccharide inhibitors. Both encapsulated and nonencapsulated strains of S. pneumoniae grown to mid-logarithmic phase in suspension culture adhered to cultured primary respiratory epithelial cells and the conjunctival cell line. Adherence of nine clinically prevalent S. pneumoniaecapsular types studied was inhibited preferentially by sialylated oligosaccharides that terminate with the disaccharide NeuAcα2-3(or 6)Galβ1. Adherence of some strains also was weakly inhibited by oligosaccharides that terminate with lactosamine (Galβ1-4GlcNAcβ1). When sialylated oligosaccharides were covalently coupled to human serum albumin at a density of approximately 20 oligosaccharides per molecule of protein, the molar inhibitory potency of the oligosaccharide inhibitor was enhanced 500-fold. The above-mentioned experiments reveal a previously unreported dependence upon sialylated carbohydrate ligands for adherence of S. pneumoniae to human upper airway epithelial cells. Enhanced inhibitory potencies of polyvalent over monovalent forms of oligosaccharide inhibitors of adherence suggest that the putative adhesin(s) that recognizes the structure NeuAcα2-3(or 6)Galβ1 is arranged on the bacterial surface in such a manner that it may be cross-linked by oligosaccharides covalently linked to human serum albumin.
BackgroundGenomics studies are being revolutionized by the next generation sequencing technologies, which have made whole genome sequencing much more accessible to the average researcher. Whole genome sequencing with the new technologies is a developing art that, despite the large volumes of data that can be produced, may still fail to provide a clear and thorough map of a genome. The Plantagora project was conceived to address specifically the gap between having the technical tools for genome sequencing and knowing precisely the best way to use them.Methodology/Principal FindingsFor Plantagora, a platform was created for generating simulated reads from several different plant genomes of different sizes. The resulting read files mimicked either 454 or Illumina reads, with varying paired end spacing. Thousands of datasets of reads were created, most derived from our primary model genome, rice chromosome one. All reads were assembled with different software assemblers, including Newbler, Abyss, and SOAPdenovo, and the resulting assemblies were evaluated by an extensive battery of metrics chosen for these studies. The metrics included both statistics of the assembly sequences and fidelity-related measures derived by alignment of the assemblies to the original genome source for the reads. The results were presented in a website, which includes a data graphing tool, all created to help the user compare rapidly the feasibility and effectiveness of different sequencing and assembly strategies prior to testing an approach in the lab. Some of our own conclusions regarding the different strategies were also recorded on the website.Conclusions/SignificancePlantagora provides a substantial body of information for comparing different approaches to sequencing a plant genome, and some conclusions regarding some of the specific approaches. Plantagora also provides a platform of metrics and tools for studying the process of sequencing and assembly further.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.