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Abstract Detail



Population Genetics/Genomics

Cobo-Simon, Irene [1], Herndon, Nic [2], Staton, Margaret [3], Grau, Emily [4], Buehler, Sean [5], Richter, Peter [6], Ramnath, Risharde [7], Demurjian, Charles [7], Almsaeed, Abdullah [5], Wegrzyn, Jill [8].

From CartograTree to CartograPlant: improving plant health and productivity in the context of a changing climate.

Climate change is threatening plant health and productivity at all spatial scales. To date, it remains largely unknown whether plant breeding can keep pace with the rate and direction of environmental change, as well as species’ adaptive potential. Furthermore, the frequency and impact of invasive pests and pathogens is increasing as a consequence of globalization and is exacerbated by climate change. Both forest trees and agricultural crop species are threatened. Hence, the identification of genes controlling traits which provide tolerance to both biotic and abiotic stresses constitutes one of the most important research objectives in evolutionary ecology. However, progress may be limited as these analyses require the integration of traditionally disparate data sources: genotypic, phenotypic and environmental. CartograTree is a web application that integrates, visualizes, and analyzes genotypic, phenotypic, environmental data from georeferenced trees. Environmental data is available through advanced integration of global and regional layers describing aspects of soil, aridity, precipitation, elevation, and more. The genotype and phenotype metrics are collected through direct submission of studies at the time of publication or through the biocuration efforts of affiliated databases (TreeGenes, HWG, and GDR). Currently, CartograTree hosts 150 studies and integrates data from 8,301,425 georeferenced trees. Meta-analysis is enabled by accessing the metadata associated with the public studies and providing workflows through Galaxy (https://galaxyproject.org/). CartograTree is converting to CartograPlant to provide the same resources to any georeferenced plant species. Here we describe the recent updates in data sources, functionalities, and workflows offered by CartograTree/Plant. To make the most of the potential of CartograTree/Plant, we are developing an imputation-based meta-analysis workflow for genome-wide and genome-environment association analyses. This workflow improves the ability to analyze multiple datasets from independent studies. Meta-analysis allows the integration of genomic, phenotypic and environmental data. Imputation methods are useful for low-density SNPs, since they predict unobserved genotypes, enhancing true association signals and facilitating meta-analysis. To develop this workflow, Populus trichocarpa is used as a model, given its compact genome size, economic and ecological importance, and the high number of genomic and phenotypic resources available. The implementation of this integrative workflow in CartograTree/Plant will contribute to our understanding of the genomic basis of traits providing plant tolerance to biotic and abiotic stresses. This knowledge is key to develop management strategies, such as marker-assisted selection, which will help secure plant health and productivity in the context of a changing climate.


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Related Links:
CartograTree/Plant
Galaxy


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 Tennessee, Department of Entomology and Plant Pathology, Knoxville, TN, USA
4 - University of Connecticut, Department of Ecology and Evolutionary Biology, Storrs, CT, USA
5 - University of Tennessee, Department of Entomology and Plant Pathology, Knoxville, NC, USA
6 - University of Connecticut, Department of Ecology and Evolutionary Biology, 75 N Eagleville road, unit 3043, Storrs, CT, 06269, USA
7 - University of Connecticut, 75 N Eagleville road, unit 3043, Storrs, CT, 06269, USA
8 - University of Connecticut, Ecology & Evolutionary Biology, 75 N. Eagleville Road, Unit 3043, Storrs, CT, 06269-3043, United States

Keywords:
none specified

Presentation Type: Oral Paper
Session: PGG4, Population Genetics and Genomics IV
Location: /
Date: Wednesday, July 21st, 2021
Time: 4:00 PM(EDT)
Number: PGG4005
Abstract ID:480
Candidate for Awards:Margaret Menzel Award


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