| Abstract Detail
Molecular Ecology Cobo, Irene [1], Herndon, Nic [2], Grau, Emily [3], Buehler, Sean [3], Richter, Peter [3], Ramnath, Risharde [3], Demurjian, Charles [3], Strickland, Emily [3], Burton, Victoria [3], Butch, Nicole [3], Abrams, Alicia [2], Lowe, Alex [2], Singh, Umed [4], Holguin-Herrera, Brian [4], Almsaeed, Abdullah [4], Staton, Margaret [5], Wegrzyn, Jill [6]. CartograPlant: Cyberinfrastructure to improve plant health and productivity in the context of a changing climate. Climate change is threatening plant health and productivity at all special scales. To date, it remains largely unknown whether plant breeding can keep pace with the rate and direction of environmental change. In addition, the frequency and impact of invasive pests and pathogens is increasing as a consequence of our warming planet. Hence, the identification of genes controlling traits which provide plant resilience to biotic and abiotic stresses constitutes one of the most important research objectives in evolutionary ecology. However, this research is often hindered by challenges associated with the access and integration of genotypic, phenotypic and environmental data sets. The expanding scope and scale of next generation sequencing experiments in ecological plant genomics also brings new challenges for computational analysis. The development of databases and applications collecting and integrating these three data types may help overcome these challenges. Notwithstanding, today, repositories provide limited access, curation and integration for non-model plant organisms, and do not provide tools for data analysis suitable for non-model species and on a population or community level. Thus, researchers spend a huge amount of time gathering, formatting, filtering, visualizing and analyzing data collected from disparate sources.
CartograPlant is the first web-based application that integrates, visualizes and analyzes genotypic, phenotypic and environmental data, and their associated metadata, from georeferenced plants following the FAIR principles: Findability, Accessibility, Interoperability and Reusability. Hence, CartograPlant is an analytic framework that supports data visualization and workflows. Analysis can be conducted in an independent manner (by study) or across multiple via meta-analysis. This is possible through the ontologies and standards applied during data collection.
Currently genotypes and/or phenotypes from over 8.3M plants and 176 studies are available. They are integrated with 914 environmental layers that address regional and global variables. Analytic workflows are designed to perform meta-analysis of both genotype by phenotype (GWAS) and genotype by environment (GEA) association studies. The use of these two approaches together (GWAS and GEA) may uncover patterns induced by adaptive processes that cannot be detected using one approach alone. Thus, CartograPlant is intended to serve as a community resource for plant molecular ecology. Here, we describe the recent updates in data sources, functionalities, and workflows offered by CartograPlant.
Related Links:
CartograPlant webpage
1 - University Of Connecticut EEB Dept., Ecology & Evolutionary Biology, 75 N Eagleville Rd Unit 3043, Storrs, CT, 06269, United States
2 - East Carolina University, Department of Computer Science, NC, USA
3 - University of Connecticut, Department of Ecology and Evolutionary Biology, CT, USA
4 - University of Tennessee, Department of Entomology and Plant Pathology, TN, USA
5 - University Of Tennessee, Knoxville, 2505 EJ Chapman Drive, 370 PBB, 2505 EJ Chapman Drive, 370 PBB, Knoxville, TN, 37996, United States
6 - University Of Connecticut, EEB, 67 N. Eagleville Road, Unit 3124, Storrs, CT, 06269, United States
Keywords:
plant DNA
climate change
FAIR
open source
Open Access
Data analysis.
Presentation Type: Oral Paper
Number: ME2005
Abstract ID:816
Candidate for Awards:None |
