Domestication as a process: modeling demography and selection in maize using ancient DNA
Plant Genetics and Genomics
Plant Breeding and Plant Pathology
Final Report Abstract
The domestication of animals and crops profoundly changed the human lifestyle. Crop domestication changed a number of physiological and morphological traits, defining the characteristics of the crops. While domestication is often modeled as an instantaneous event in genetic analysis, archaeological data shows that traits defining domesticated. The assumption that few new mutation in key domestication genes alone has driven the changes converting wild plants to crops is challenged by the empirical findings of standing genetic variation at domestication associated loci in the wild ancestors of our crops and persistence of variation in the crop. Quantitative genetic analyses in crops have shown that many traits are controlled by a large number of genes. The domestication of crops can be modeled as drastic shift in trait optima. How populations adapt to these shifts depends on a number of parameters including the genetic basis of the trait as well as population demography. In this project, we simulated a number of traits and in different populations to study the underlying basis of polygenic adaptation to distant trait optima. We then use random forest machine learning to learn the relative importance of input parameters on trait adaptation, including the speed of adaptation, the relative frequency of hard sweeps and sweeps from standing variation, or the final genetic architecture of the trait. We find that selective sweeps occur even in traits under relatively weak selection and our machine learning analyses find that demography and the effect sizes of mutations have the largest influence on genetic variation after adaptation. Though most sweeps occur from variation segregating in the ancestral population, new mutations can be important for traits under strong stabilizing selection that undergo a large optimum shift. Employing maize domestication as model for trait adaptation accompanied by demographic changes, we show how two example traits under a maize specific demography adapt to a distant optimum and demonstrate that polygenic adaptation is a well suited model for crop domestication even for traits with major effect loci. Overall we show how extensive forward in time simulations can be used to train machine learning models and learn the influence of parameters on summary statistics. This framework might be well suited to detect and describe polygenic adaptation in empirical data.
Publications
- (2018) From zero to hero: the past, present and future of grain amaranth breeding. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik 131 (9) 1807–1823
Joshi, Dinesh C.; Sood, Salej; Hosahatti, Rajashekara; Kant, Lakshmi; Pattanayak, A.; Kumar, Anil; Yadav, Dinesh; Stetter, Markus G.
(See online at https://doi.org/10.1007/s00122-018-3138-y) - Genetic architecture and selective sweeps after polygenic adaptation to distant trait optima, 2018, PLOS Genetics
Markus G Stetter, Kevin Thornton and Jeffrey Ross-Ibarra
(See online at https://doi.org/10.1371/journal.pgen.1007794)
