Theoretical and Applied Genetics

, Volume 114, Issue 4, pp 683–692 | Cite as

Detection and resolution of genetic loci affecting circadian period in Brassica oleracea

  • Neeraj Salathia
  • James R. Lynn
  • Andrew J. MillarEmail author
  • Graham J. KingEmail author
Original Paper


Circadian rhythms regulate many aspects of plant growth, fitness and vigour. The components and detailed mechanism of circadian regulation to date have been dissected in the reference species Arabidopsis thaliana. To determine the genetic basis and range of natural allelic variation for intrinsic circadian period in the closest crop relatives, we used an accurate and high throughput data capture system to record rhythmic cotyledon movement in two immortal segregating populations of Brassica oleracea, derived from parent lines representing different crop types. Periods varied between 24.4 and 26.1 h between the parent lines, with transgressive segregation between extreme recombinant lines in both populations of ∼3.5 h. The additive effect of individual QTL identified in each population varied from 0.17 to 0.36 h. QTL detected in one doubled haploid population were verified and the mapping intervals further resolved by determining circadian period in genomic substitution lines derived from the parental lines. Comparative genomic analysis based on collinearity between Brassica and Arabidopsis also allowed identification of candidate orthologous genes known to regulate period in Arabidopsis, that may account for the additive circadian effects of specific QTL. The distinct QTL positions detected in the two populations, and the extent of transgressive segregation suggest that there is likely to be considerable scope for modulating the range of available circadian periods in natural populations and crop species of Brassica. This may provide adaptive advantage for optimising growth and development in different latitudes, seasons or climate conditions.


Linkage Group Double Haploid Circadian Clock Clock Gene Double Haploid Line 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was funded by the UK Biotechnology and Biological Sciences Research Council (BBSRC). We are grateful to Dr. G.R. Teakle for provision of the reference integrated linkage map.


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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.FAS Center for Systems BiologyHarvard UniversityCambridgeUSA
  2. 2.Warwick HRI, WellesbourneWarwickUK
  3. 3.University of EdinburghEdinburghUK
  4. 4.Rothamsted ResearchHarpendenUK

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