Adaptations in wild radish (Raphanus raphanistrum) flowering time, Part 1: Individual-based modeling of a polygenic trait

Gayle J. Somerville, Michael B. Ashworth, Hugh J. Beckie

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


This study investigated replicating six generations of glasshouse-based flowering date selection in wild radish (Raphanus raphanistrum L.) using an adaptation of the population model SOMER (Spatial Orientated Modelling of Evolutionary Resistance). This individual-based model was chosen because it could be altered to contain varying numbers of genes, along with varying levels of environmental influence on the phenotype (namely the heritability). Accurate replication of six generations of genetic change that had occurred in a previous glasshouse-based selection was achieved, without intermediate adjustments. This study found that multiple copies of just two genes were required to reproduce the polygenic flowering time adaptations demonstrated in that previous research. The model included major effect type M1 genes, with linkage and crossing over, and minor effect type M2 genes undergoing independent assortment. Within the model, transmissibility (heritability of each gene type) was parameterized at 0.60 for the M1 genes and 0.45 for the M2 genes. The serviceable parameterization of the genetics of flowering in R. raphanistrum within a population model means that simulated examinations of the effects of external weed control on flowering time adaptations are now more feasible. An accurate and simplified Mendelian-based model replicating the adaptive shifts of flowering time that is controlled by a complex array of genes is useful in predicting life-cycle adaptations to evade weed control measures such as harvest weed seed control, which apply intense adaptive selections on traits that affect seed retention, including flowering time.

Original languageEnglish
Pages (from-to)137-142
Number of pages6
JournalWeed Science
Issue number2
Early online date9 Jan 2024
Publication statusPublished - 9 Mar 2024


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