Project description:Hairy vetch (Vicia villosa Roth) is recognized as a beneficial winter cover crop in the Midwestern U.S. DNA microarrays are used for assessing gene expression significance. The objective of the study was to identify a set of genes expressed in hairy vetch, that could be further analyzed for their potential in improving the crop. The RNA of four targets (soybean (Glycine max), hairy vetch, Vicia pannonica PI 170008, and Vicia pannonica PI 515988) were purified, labeled, and hybridized to 142 cDNA clones of biotic stress genes and gene sequences of soybean that were robotically spotted onto aminosilicated slides with duplicate spots and three arrays per slide. The microarray experiments were completed in a reference design experiment incorporating a two-dye system. The data were analyzed using the individual fluorescence intensities to fit two statistical models in a mixed model analysis of variance. In this analysis, systematic error effects were observed to account for 24% of the total variation. The use of a Bonferroni adjusted significance threshold allowed for adequate control over the number of falsely identified significant genes showing expression in the different target comparisons. We observed that 64 of the 142 gene sequences (45%) were differentially expressed in at least one of the target comparisons. Two of these expressed genes in hairy vetch encoded for a cold tolerance indicator, proline, and two other gene sequences encode for stress tolerance indicators, myo-inositol and calmodulin. A soybean cDNA microarray was used effectively to differentiate gene expression in hairy vetch. Keywords: comparative genomic hybridization (cross-species)
2005-12-01 | GSE3263 | GEO
Project description:Differences in nitrogen fixation between Vicia villosa Roth. and Vicia sativa
| PRJNA1076883 | ENA
Project description:RNA Sequencing of Hairy Vetch (Vicia villosa)
Project description:The metagenomes of complex microbial communities are rich sources of novel biocatalysts. We exploited the metagenome of a mixed microbial population for isolation of more than 15 different genes encoding novel biocatalysts by using a combined cultivation and direct cloning strategy. A 16S rRNA sequence analysis revealed the presence of hitherto uncultured microbes closely related to the genera Pseudomonas, Agrobacterium, Xanthomonas, Microbulbifer, and Janthinobacterium. Total genomic DNA from this bacterial community was used to construct cosmid DNA libraries, which were functionally searched for novel enzymes of biotechnological value. Our searches in combination with cosmid sequencing resulted in identification of four clones encoding 12 putative agarase genes, most of which were organized in clusters consisting of two or three genes. Interestingly, nine of these agarase genes probably originated from gene duplications. Furthermore, we identified by DNA sequencing several other biocatalyst-encoding genes, including genes encoding a putative stereoselective amidase (amiA), two cellulases (gnuB and uvs080), an alpha-amylase (amyA), a 1,4-alpha-glucan branching enzyme (amyB), and two pectate lyases (pelA and uvs119). Also, a conserved cluster of two lipase genes was identified, which was linked to genes encoding a type I secretion system. The novel gene aguB was overexpressed in Escherichia coli, and the enzyme activities were determined. Finally, we describe more than 162 kb of DNA sequence that provides a strong platform for further characterization of this microbial consortium.
Project description:Here, we report 17 metagenome-assembled genomes (MAGs) recovered from microbial consortia of forest and pasture soils in the Brazilian Eastern Amazon. The bacterial MAGs have the potential to act in important ecological processes, including carbohydrate degradation and sulfur and nitrogen cycling.
Project description:The Arecibo Observatory (AO) located in Arecibo, Puerto Rico, is the most sensitive, powerful and active planetary radar system in the world [1]. One of its principal components is the 305 m-diameter spherical reflector dish (AORD), which is exposed to high frequency electromagnetic waves. To unravel the microbial communities that inhabit this environment, soil samples from underneath the AORD were collected, DNA extracted, and sequenced using Illumina MiSeq. Taxonomic and functional profiles were generated using the MG-RAST server. The most abundant domain was Bacteria (91%), followed by Virus (8%), Archaea (0.9%) and Eukaryota (0.9%). The most abundant phylum was Proteobacteria (54%), followed by Actinobacteria (8%), Bacteroidetes (5%) and Firmicutes (4%). In terms of functions, the most abundant among the metagenome corresponded to phages, transposable elements and plasmids (16%), followed by clustering-based subsystems (11%), carbohydrates (10%), and amino acids and derivatives (9%). This is the first soil metagenomic dataset from dish antennas and radar systems, specifically, underneath the AORD. Data can be used to explore the effect of high frequency electromagnetic waves in soil microbial composition, as well as the possibility of finding bioprospects with potential biomedical and biotechnological applications.
Project description:Soil microbial communities contain the highest level of prokaryotic diversity of any environment, and metagenomic approaches involving the extraction of DNA from soil can improve our access to these communities. Most analyses of soil biodiversity and function assume that the DNA extracted represents the microbial community in the soil, but subsequent interpretations are limited by the DNA recovered from the soil. Unfortunately, extraction methods do not provide a uniform and unbiased subsample of metagenomic DNA, and as a consequence, accurate species distributions cannot be determined. Moreover, any bias will propagate errors in estimations of overall microbial diversity and may exclude some microbial classes from study and exploitation. To improve metagenomic approaches, investigate DNA extraction biases, and provide tools for assessing the relative abundances of different groups, we explored the biodiversity of the accessible community DNA by fractioning the metagenomic DNA as a function of (i) vertical soil sampling, (ii) density gradients (cell separation), (iii) cell lysis stringency, and (iv) DNA fragment size distribution. Each fraction had a unique genetic diversity, with different predominant and rare species (based on ribosomal intergenic spacer analysis [RISA] fingerprinting and phylochips). All fractions contributed to the number of bacterial groups uncovered in the metagenome, thus increasing the DNA pool for further applications. Indeed, we were able to access a more genetically diverse proportion of the metagenome (a gain of more than 80% compared to the best single extraction method), limit the predominance of a few genomes, and increase the species richness per sequencing effort. This work stresses the difference between extracted DNA pools and the currently inaccessible complete soil metagenome.