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Multi-environment QTL mapping in blackcurrant (Ribes nigrum L.) using mixed models
C A Hackett1, J Russell, L Jorgensen
1Biomathematics and Statistics Scotland, Invergowrie, Dundee, DD2 5DA, UK. christine@bioss.ac.uk
Summary
This study introduces a new statistical method to analyze blackcurrant (Ribes nigrum) genetic data. The approach improves the identification of quantitative trait loci (QTLs) for important traits like anthocyanin concentration and budbreak.
Area of Science:
- Plant genetics
- Quantitative genetics
- Bioinformatics
Background:
- The initial blackcurrant genetic linkage map identified quantitative trait loci (QTLs).
- Previous analysis was complicated by two subgroups within the mapping population (selfed and crossed offspring).
- QTL analysis focused on the mean trait over 3 years and only crossed offspring.
Purpose of the Study:
- To propose a mixed model multi-environment approach for blackcurrant genetic analysis.
- To combine data from selfed and crossed offspring across multiple years (environments).
- To identify additional QTLs and explore interactions between QTLs, year, and offspring type.
Main Methods:
- A mixed model multi-environment approach was developed.
- Three years of data were treated as separate environments.
- Residual terms were modeled to account for correlations between years.
- The approach was applied to re-analyze anthocyanin concentration and budbreak traits.
Main Results:
- Several additional QTLs were identified for anthocyanin concentration and budbreak.
- Some QTLs affected traits in both selfed and crossed offspring.
- Other QTLs were specific to either selfed or crossed offspring.
Conclusions:
- The proposed mixed model approach enhances QTL detection in complex blackcurrant populations.
- This method provides a more comprehensive understanding of genetic control for key agronomic traits.
- It allows for the investigation of genotype-b-environment and genotype-by-offspring type interactions.
