Dataset Information

A Vavilovian approach to discovering crop-associated microbes with potential to enhance plant immunity.

ABSTRACT: Through active associations with a diverse community of largely non-pathogenic microbes, a plant may be thought of as possessing an "extended genotype," an interactive cross-organismal genome with potential, exploitable implications for plant immunity. The successful enrichment of plant microbiomes with beneficial species has led to numerous commercial applications, and the hunt for new biocontrol organisms continues. Increasingly flexible and affordable sequencing technologies, supported by increasingly comprehensive taxonomic databases, make the characterization of non-model crop-associated microbiomes a widely accessible research method toward this end; and such studies are becoming more frequent. A summary of this emerging literature reveals, however, the need for a more systematic research lens in the face of what is already a metagenomics data deluge. Considering the processes and consequences of crop evolution and domestication, we assert that the judicious integration of in situ crop wild relatives into phytobiome research efforts presents a singularly powerful tool for separating signal from noise, thereby facilitating a more efficient means of identifying candidate plant-associated microbes with the potential for enhancing the immunity and fitness of crop species.

SUBMITTER: Hale IL

PROVIDER: S-EPMC4167000 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Vavilovian approach to discovering crop-associated microbes with potential to enhance plant immunity.

Hale Iago L IL Broders Kirk K Iriarte Gloria G

Frontiers in plant science 20140918

Through active associations with a diverse community of largely non-pathogenic microbes, a plant may be thought of as possessing an "extended genotype," an interactive cross-organismal genome with potential, exploitable implications for plant immunity. The successful enrichment of plant microbiomes with beneficial species has led to numerous commercial applications, and the hunt for new biocontrol organisms continues. Increasingly flexible and affordable sequencing technologies, supported by inc ...[more]

PMID: 25278956

Similar Datasets

Project description:We systematically compared the adverse effects of cancer drugs to detect event outliers across different clinical trials using a data-driven approach. Because many cancer drugs are toxic to patients, better understanding of adverse events of cancer drugs is critical for developing therapies that could minimize the toxic effects. However, due to the large variabilities of adverse events across different cancer drugs, methods to efficiently compare adverse effects across different cancer drugs are lacking. To address this challenge, we present an exploration study that integrates multiple adverse event reports from clinical trials in order to systematically compare adverse events across different cancer drugs. To demonstrate our methods, we first collected data on 186,339 clinical trials from ClinicalTrials.gov and selected 30 common cancer drugs. We identified 1602 cancer trials that studied the selected cancer drugs. Our methods effectively extracted 12,922 distinct adverse events from the clinical trial reports. Using the extracted data, we ranked all 12,922 adverse events based on their prevalence in the clinical trials, such as nausea 82%, fatigue 77%, and vomiting 75.97%. To detect the significant drug outliers that could have a statistically high possibility of causing an event, we used the boxplot method to visualize adverse event outliers across different drugs and applied Grubbs' test to evaluate the significance. Analyses showed that by systematically integrating cross-trial data from multiple clinical trial reports, adverse event outliers associated with cancer drugs can be detected. The method was demonstrated by detecting the following four statistically significant adverse event cases: the association of the drug axitinib with hypertension (Grubbs' test, P < 0.001), the association of the drug imatinib with muscle spasm (P < 0.001), the association of the drug vorinostat with deep vein thrombosis (P < 0.001), and the association of the drug afatinib with paronychia (P < 0.01).

Dataset Information

A Vavilovian approach to discovering crop-associated microbes with potential to enhance plant immunity.

Publications

A Vavilovian approach to discovering crop-associated microbes with potential to enhance plant immunity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets