A Reference Genome Assembly of Hybrid-Derived California Wild Radish (Raphanus sativus × raphanistrum). (16th December 2021)

• Record Type: Journal Article
• Authors: Alexandre, Nicolas M; Haji, Diler; Bakhtiari, Moe; Chatla, Kamalakar; Aguilar, Jessica M; Arzumanova, Ksenia; Whiteman, Noah K
• Editors: Shapiro, Beth
• Is Part Of: Journal of heredity. Volume 113:Number 2(2022)
• Page Start: 197
• Page End: 204
• Publication Date: 2021-12-16
• Subjects: California Wild Radish -- herbivory -- hybrid -- invasive -- pollination -- speciation; Breeding -- Periodicals; Plant breeding -- Periodicals; Heredity -- Periodicals; 576.5
• DOI: 10.1093/jhered/esab076
• Languages: English
• ISSNs: 0022-1503

Abstract

Abstract: For agriculturally important plants, pollination and herbivory are 2 ecological factors that play into the success of crop yields. Each is also important in natural environments where invasive plants and their effect on species interactions may alter the native ecology. The California Wild Radish ( Raphanus sativus × raphanistrum ), a hybrid derived from an agriculturally important crop and a nonnative cultivar, is common in California. Remarkably, it has recently replaced wild populations of both progenitor species. Experiments on phenotypic variation for petal color and antiherbivore defenses suggest both pairs of polymorphisms are maintained as a result of pollinator- and herbivore-mediated natural selection. This species provides an opportunity to understand how natural selection shapes the evolution of ecologically important traits when traits are constrained by 2 opposing forces. Here we provide the genome assembly of the California Wild Radish displaying improvement to currently existing genomes for agronomically important crucifers. This genome sequence provides the tools to dissect the genomic architecture of traits related to herbivory and pollination using natural variation in the wild as well as the ability to infer demographic and selective history in the context of hybridization. Study systems like these will improve our understanding and predictions of evolutionary change for correlated traits.