Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1050618 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR27162018_1.fastq.gz | Fastqsanger.gz | |||
| SRR27162018_2.fastq.gz | Fastqsanger.gz | |||
| SRR27162019_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 4 of 4 |
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Project description:species type strains Genome sequencing and assembly
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Project description:<p>The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens.</p> <p>We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.</p>
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Project description:Coevolutionary change requires reciprocal selection between interacting species, i.e., that the partner genotypes that are favored in one species depend on the genetic composition of the interacting species. Coevolutionary genetic variation is manifested as genotype ´ genotype (G ´ G) interactions for fitness from interspecific interactions. Although quantitative genetic approaches have revealed abundant evidence for G ´ G interactions in symbioses, the molecular basis of this variation remains unclear. Here we study the molecular basis of G ´ G interactions in a model legume-rhizobium mutualism using gene expression microarrays. We find that, like quantitative traits such as fitness, variation in the symbiotic transcriptome may be partitioned into additive and interactive genetic components. Our results suggest that plant genetic variation is the largest influence on nodule gene expression, and that plant genotype and the plant genotype ´ rhizobium genotype interaction determine global shifts in rhizobium gene expression that in turn feedback to influence plant fitness benefits. Moreover, the transcriptomic variation we uncover implicates regulatory changes in both species as drivers of symbiotic gene expression variation. Our study is the first to partition genetic variation in a symbiotic transcriptome, and illuminates potential molecular routes of coevolutionary change. We assayed gene expression using three biological replicates for each plant genotype × rhizobium genotype combination (4 combinations) for a total of 12 chips. We compared gene expression in each of four combinations of Medicago truncatula families and Sinorhizobium meliloti strains using Affymetrix Medicago GeneChips to study how the entire transcriptome and individual genes responded to differences between plant families, between rhizobium strains, and due to the plant family × rhizobium strain (G × G) interaction.
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Project description:We report an small RNA sequencing (sRNA-seq) approach to identify host sRNAs involved in the nitrogen fixing symbiosis between Mesoamerican Phaseolus vulgaris and Rhizobium etli strains with different degrees in nodulation efficiency. This approach identified conserved and known microRNAs (miRNAs) differentially accumulated in Mesoamerican P. vulgaris roots in response to a highly efficient strain, to a less efficient one or to both strains.
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Project description:The genome X genome interactions between rhizobium and plant in the early interaction phase was evaluated using RNA-sequencing
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Project description:Various species of rhizobium establish compatible symbiotic relationships with soybean (Glycine max) leading to the formation of nitrogen-fixing nodules in roots. The formation of functional nodules is mediated through complex developmental and transcriptional reprogramming that involves the activity of thousands of plant genes. However, host transcriptome responses that determine the outcome of the symbiotic interactions leading to the formation of functional or non-functional nodules remain unexplored. In this study, we investigated differential compatibilities between rhizobium strains (Bradyrhizobium diazoefficiens USDA 110Bradyrhizobium sp. strain LVM 105) and cultivated and wild soybeans. The nodulation assays revealed that both USDA 110 and LVM 105 strains effectively nodulate G. soja but only USDA 110 can form symbiotic relationships with Williams 82. RNA-seq data revealed that USDA 110 and LVM 105 induce distinct transcriptome programming in functional mature nodules formed on G. soja roots where genes involved in nucleosome assembly, DNA replication, regulation of cell cycle, and defense responses play key roles. Transcriptome comparison also suggested that activation of genes associated with cell wall biogenesis and organization and defense responses together with downregulation of genes involved in the biosynthesis of isoprenoids and antioxidant stress are associated with the formation of non-functional nodules on Williams 82 roots. Moreover, our analysis implies that increased activity of genes involved in oxygen binding, amino acid transport, and nitrate transport differentiates between fully-developed nodules in cultivated versus wild soybeans.
2024-08-19 | GSE267634 | GEO
Project description:Type and Reference strains of multiple species Genome sequencing and assembly
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Project description:10 strains of Rhizobium genome sequencing and assembly
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Project description:Coevolutionary change requires reciprocal selection between interacting species, i.e., that the partner genotypes that are favored in one species depend on the genetic composition of the interacting species. Coevolutionary genetic variation is manifested as genotype ´ genotype (G ´ G) interactions for fitness from interspecific interactions. Although quantitative genetic approaches have revealed abundant evidence for G ´ G interactions in symbioses, the molecular basis of this variation remains unclear. Here we study the molecular basis of G ´ G interactions in a model legume-rhizobium mutualism using gene expression microarrays. We find that, like quantitative traits such as fitness, variation in the symbiotic transcriptome may be partitioned into additive and interactive genetic components. Our results suggest that plant genetic variation is the largest influence on nodule gene expression, and that plant genotype and the plant genotype ´ rhizobium genotype interaction determine global shifts in rhizobium gene expression that in turn feedback to influence plant fitness benefits. Moreover, the transcriptomic variation we uncover implicates regulatory changes in both species as drivers of symbiotic gene expression variation. Our study is the first to partition genetic variation in a symbiotic transcriptome, and illuminates potential molecular routes of coevolutionary change. We assayed gene expression using three biological replicates for each plant genotype × rhizobium genotype combination (4 combinations) for a total of 12 chips.
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