Using archaeogenomic and computational approaches to unravel the history of local adaptation in crops

Philos Trans R Soc Lond B Biol Sci. 2015 Jan 19;370(1660):20130377. doi: 10.1098/rstb.2013.0377.

Abstract

Our understanding of the evolution of domestication has changed radically in the past 10 years, from a relatively simplistic rapid origin scenario to a protracted complex process in which plants adapted to the human environment. The adaptation of plants continued as the human environment changed with the expansion of agriculture from its centres of origin. Using archaeogenomics and computational models, we can observe genome evolution directly and understand how plants adapted to the human environment and the regional conditions to which agriculture expanded. We have applied various archaeogenomics approaches as exemplars to study local adaptation of barley to drought resistance at Qasr Ibrim, Egypt. We show the utility of DNA capture, ancient RNA, methylation patterns and DNA from charred remains of archaeobotanical samples from low latitudes where preservation conditions restrict ancient DNA research to within a Holocene timescale. The genomic level of analyses that is now possible, and the complexity of the evolutionary process of local adaptation means that plant studies are set to move to the genome level, and account for the interaction of genes under selection in systems-level approaches. This way we can understand how plants adapted during the expansion of agriculture across many latitudes with rapidity.

Keywords: ancient DNA; archaeogenomics; domestication; local adaptation.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Adaptation, Biological / genetics*
  • Adaptation, Biological / physiology
  • Computational Biology / methods*
  • Crops, Agricultural / genetics*
  • Crops, Agricultural / physiology
  • Egypt
  • Environment*
  • Evolution, Molecular*
  • Genomics / methods*
  • Geography
  • Hordeum / genetics
  • Models, Genetic*
  • Paleontology / methods*
  • Selection, Genetic