High througput phenotyping and its role in a strategy for improving complex traits
New Genotype To Phenotype Models At The Intersection Of Genetics, Physiology And Statistics; Smart Tools For Prediction And Improvement Of Crop Yield
Type of presentation: poster
Authors:
Fred van Eeuwijk, Anja Dieleman, Alain Palloix , Marnik Vuylsteke, Chris Glasbey, Attila Barocsi, Juan Jose Magan Cañadas, Ep Heuvelink, Gerie van der Heijden, Roeland Voorrips, Marco Bink
Presenter:
Dr. Marco Bink
Abstract:
The prediction of phenotypic responses from genetic and environmental information is an area of active research in genetics, physiology and statistics. Rapidly increasing amounts of information become available on the phenotype as a consequence of high throughput phenotyping techniques, while more and cheaper genotypic data follow from the development of new genotyping platforms. In between genotype and phenotype, a wide array of -omics data can be generated. Continuous monitoring of environmental conditions has become an accessible option. This wealth of data requires a drastic rethinking of the traditional quantitative genetic approach to modeling phenotypic variation in terms of genetic and environmental differences. Where in the past a single phenotypic trait was partitioned in a genetic and environmental component by analysis of variance techniques, we nowadays desire to model multiple, and often time dependent, phenotypic traits as a function of genes (QTLs) and environmental inputs, where we would like to include intermediate genomic information as well. The U project ‘Smart tools for Prediction and Improvement of CropYield’ (KBB -2008-211347), or SPICY, aims at the development of genotype-to-phenotype models that fully integrate genetic, genomic, physiological and environmental information to achieve accurate phenotypic predictions across a wide variety of genetic and environmental configurations. In the presentation the objectives and structure of SPICY as well as its philosophy will be discussed
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