Here’s a sneak preview of what will be presented at the upcoming Phenome 2017 conference, to be held on Feb. 10-14 in Tucson, AZ.
Phenome 2017 will provide a unique opportunity for plant biologists, engineers, computer and information scientists, chemists, mathematicians, geologists, physicists, and meteorologists to mingle, forge collaborations, share insights, and develop strategies to tackle real-world problems.
The Plasticity in Plant Traits general session will take place on the morning of Monday, February 13, at Phenome 2017 (Tucson, AZ, USA, February 10–14, 2017).
It has not always been easy to connect plant traits with the genes or environmental conditions that modulate them. However, research in this area is moving apace, and at Phenome 2017, a general session dedicated to Plasticity in Plant Traits will address this very topic.
Speakers from the US and Europe will explore genotype-by-environment interactions, and the genetic and epigenetic mechanisms by which plasticity is regulated – key knowledge in efforts to manipulate plant traits, especially in the face of rapid human population growth and climate change.
For example, José Gutierrez-Marcos (University of Warwick, UK) is interested in the influences of cell–cell communication and the environment on developmental plasticity in Arabidopsis. Also, Zsuzsanna Mérai (Gregor Mendel Institute, Austria) explores phenotypes in non-model plants that have so far evaded the Arabidopsis researcher.
Tools and technologies to collect plant phenotyping data are, of course, essential for understanding plant trait plasticity. Bob Schmitz (University of Georgia), who is developing methods for epimutagenesis in plants, and Nathan Springer (University of Minnesota), who studies natural variation in maize, both said they’re particularly looking forward to meeting scientists developing high-throughput phenotyping platforms during the session.
There are many innovative approaches to analyzing large-scale data sets, but the final speaker in the session, Frank Johannes (Technical University of Munich, Germany), combines bioinformatics with statistical genetics to develop software to characterize patterns of epigenetic variation in plant populations.