Tuesday, 10 September 2013

iOES Poster: Using Next Generation Sequencing to Understand Plant Acclimation and Adaptation to the Changing Environment

Alex Watson-Lazowski, Yunan Lin, Jennifer DeWoody, Richard Edwards and Gail Taylor.

1st International Environmental Omics Synthesis (iEOS) Conference, Cardiff, UK (Sept 11-13, 2013). Poster EcO-15.

Abstract:

Plant adaptation to elevated atmospheric carbon dioxide (CO2) is of great interest, as the concentration of this gas in the atmosphere has risen by more than 30% to 388 ╬╝mol mol-1 since the industrial revolution. On average there has been a rise of 3 ppm per year. Plant fossil samples suggest that atmospheric CO2 may be acting as a selective agent driving evolution, but limited evidence is available to support this idea for plants subjected to future predicted concentrations. Studying evolutionary responses to this aspect of environmental change is difficult, but here we use a CO2 spring site where plants have been exposed for multiple generations to concentrations of CO2 predicted for 2050. From this, detailed phenotyping data was collected, including data for stomatal patterning. Considerable evidence exists to show that stomatal numbers have declined across geological time and that this is linked to CO2 concentration, but few CO2-sensitive stomatal patterning genes have ever been identified. When grown under elevated CO2 concentrations P. lanceolata (the narrow leaf plantain), seeds collected from the spring site showed a counter-intuitive change in stomatal index and density. Here, in this non- model plant we have investigated the gene expression changes underlying this stomatal patterning response to elevated CO2.

RNA-Seq allows for in depth analysis of plant species with no previous information required, enabling rapid evaluation of any of novel plant acclimations and adaptions. Using this approach we have identified a set of novel genes for stomatal patterning in high CO2 and confirmed previously observed acclimation responses.

RNA-Seq refers to the use of high-throughput deep-sequencing technologies to sequence cDNA in order to get information about the transcriptome of a given biological sample.

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