Heritability Analysis (genotype/population association)
Quantitative Trait Locus Mapping (QTLRel)
- Li Y, Cheng R, Spokas K, Palmer AA, Borevitz JO. Genetic Variation for Life History Sensitivity to Seasonal Warming in Arabidopsis thaliana. Genetics 2014
- supplementary data and code for Li et al Genetics 2014 & mapping software QTLRel
- Cheng R, Doerge R, Borevitz JO. Novel Resampling Improves Statistical Power for Multiple-Trait QTL Mapping G3 Genetics 2017 Rcode
natural Nested Association Mapping (nNAM), combining family and population data (in progress for Brachypodium and Eucalyptus)
Tools for Adaptation: integrating Environment, Genotype and Phenotype
Kevin Murray, Tim Brown, Riyan Cheng, Xavier Siralut, Justin Borevitz (ABiC abstract Oct 11-12, 2014)
To keep pace and help stabilze a changing world, agriculture and ecosystem science must aim to sustainability intensify and regenerate natural environments of the biosphere. Both managed agriculture and restored ecosystems must integrate the latest methodological advances to facilitate rapid genetic adaptation under a variable and changing climate.
TraitCapture is a platform to integrate controlled environments, plant genomics and phenomics to do just this. It includes the SpectralPhenoClimatron which provides dynamic control of plant growth conditions, simulating regional seasonal climates and with integrated high-throughput phenotyping. PlantScreen provides high throughput measures of hyper-spectral, thermal, and fluorescence image based phenotypes including photosynthetic efficiency. Computational image analysis provides quantitative, real-time metrics of growth and development on plants grown under dynamic environments. Hierarchical genomic analyses with imputation from Genotyping-by-Sequencing to low and high coverage whole-genome and epi-genome sequencing are integrated within TraitCapture. Then genome wide association studies are used to dissect phenotypic variation across environments into quantitative trait loci with candidate genes. Finally, functional structural plant models will be used to predict the performance of various genetic combinations under future variable climates to select what to plant where. Underlying the experimental pipeline is end-to-end sample tracking and data management system that is open-source allowing reproducible research and data sharing.
The TraitCapture project is funded and many components have already been implemented. TraitCapture is released under the GNU GPL, and contributions are encouraged.