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Convergent phenotypic evolution provides some of the strongest evidence for adaptation. However, the extent to which recurrent phenotypic adaptation has arisen via parallelism at the molecular level remains unresolved, as does the evolutionary origin of alleles underlying such adaptation. Here, we investigate genetic mechanisms of convergent highland adaptation in maize landrace populations and evaluate the genetic sources of recurrently selected alleles. Population branch excess statistics reveal substantial evidence of parallel adaptation at the level of individual single-nucleotide polymorphism (SNPs), genes, and pathways in four independent highland maize populations. The majority of convergently selected SNPs originated via migration from a single population, most likely in the Mesoamerican highlands, while standing variation introduced by ancient gene flow was also a contributor. Polygenic adaptation analyses of quantitative traits reveal that alleles affecting flowering time are significantly associated with elevation, indicating the flowering time pathway was targeted by highland adaptation. In addition, repeatedly selected genes were significantly enriched in the flowering time pathway, indicating their significance in adapting to highland conditions. Overall, our study system represents a promising model to study convergent evolution in plants with potential applications to crop adaptation across environmental gradients., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

The plant root system traverses one of the most complex environments on earth. Understanding how roots support plant life on land requires knowing how soil properties affect the availability of nutrients and water and how roots manipulate the soil environment to optimize acquisition of these resources. Imaging of roots in soil allows the integrated analysis and modeling of environmental interactions occurring at micro- to macroscales. Advances in phenotyping of root systems is driving innovation in cross-platform-compatible methods for data analysis. Root systems acclimate to the environment through architectural changes that act at the root-type level as well as through tissue-specific changes that affect the metabolic needs of the root and the efficiency of nutrient uptake. A molecular understanding of the signaling mechanisms that guide local and systemic signaling is providing insight into the regulatory logic of environmental responses and has identified points where crosstalk between pathways occurs.