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Abstract Detail

Comparative Genomics/Transcriptomics

Marx, Hannah [1], Maitner, Brian [1], Wisely, Eldridge [2], Jorgensen, Stacy [3], Dlugosch, Katrina [4], Barker, Michael [5].

Gene Expression Plasticity and the Persistence of Plant Species across Environmental Variation.

The ability to produce different phenotypes in different environments—phenotypic plasticity—can be essential for responding to environmental change. There is recent evidence from experimental studies that plasticity at the level of gene expression can be adaptive under changing environments, but little is known about how genomic plasticity relates to ecological success in nature. To address how genomic plasticity can be used to monitor community-wide responses to environmental change, we sampled RNA from 26 plant species at the Harvard Forest National Ecological Observatory Network (NEON) site at two points during the growing season. For each species, transcriptomes were assembled de novo from RNA-seq data, and reads from each time point were mapped back to the reference. Variation in gene expression (log 2-fold change) over time was used to quantify genomic plasticity.
Comparisons across these diverse plant lineages showed that species exhibit a tradeoff between large changes in gene expression at a small number of loci, or many modest changes in the magnitude of expression across the genome. Additionally, species with a larger niche breadth (quantified by the n-dimensional hypervolume of climatic variables over the current range) differentially express fewer loci at large magnitudes, revealing that the degree to which species employ expression strategies predicts the extent of their climatic niche. By establishing a foundation to use genomic plasticity to track responses to climate change, this approach has far-reaching applications for understanding how ecological and evolutionary processes drive the diversity that we observe in nature. Importantly, the relationship between genomic plasticity strategies and niche breadth suggests potential to use variation in gene expression to predict the success of species across environments.

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1 - University of Arizona, Ecology and Evolutionary Biology, Tucson, AZ, 85721, USA
2 - University of Arizona, Genetics, Tucson, AZ, 85721, USA
3 - University Of Arizona, Ecology & Evolutionary Biology, 1041 E Lowell St, PO Box 210088, Tucson, AZ, 85721, United States
4 - University Of Arizona, ECOL AND EVOL BIOLOGY/ EMS, P.O. Box 210088, Tucson, AZ, 85721, United States
5 - Department Of Ecology & Evolutionary Biology, P.O. Box 210088, Tucson, AZ, 85721, United States

Differential Expression Analysis
Harvard Forest

Presentation Type: Oral Paper
Session: 25, Comparative Genomics and Transcriptomics II
Location: 102/Mayo Civic Center
Date: Tuesday, July 24th, 2018
Time: 1:45 PM
Number: 25004
Abstract ID:407
Candidate for Awards:Margaret Menzel Award

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