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one combination (Combination 2 of seed hull color trait: K ¼ 281)
due to the biased distribution of genotypes of this combination
(Supplementary Figure S4). Therefore, we believe the threshold of
K > 100 may be appropriate to detect candidate epistatic genomic
regions in most cases. However, spurious epistasis may be possibly identified due to the bias of genotypes in a population, and
careful validation is needed to conclude the epistatic effect of
candidate loci. The identified regions may contain multiple
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Here, we successfully specified strong candidate genes presumably controlling the seed hull phenotype using knowledge about
the candidate genes and the sequence analysis. However, this approach may not be applicable in every case. There may be several
approaches to validate the epistatic relationship between the
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by specific genes (Gilad et al. 2008; Feltus 2014). Combining information from other sources of evidence with RIL-StEp results may
enhance our capability to identify interacting genes.
To summarize, we propose a novel approach based on simple
linear models to detect epistatic interactions underlying quantitative traits in the RIL population. By applying RIL-StEp, we succeeded in identifying genomic regions related to rice seed hull
color and chlorophyll content. Incorporating additional information allowed us to identify candidate genes involved in seed hull
color. Thus, our approach has the potential to identify epistasis
in various biological traits.
R.T. and T.S. conceptualized the study. T.S., A.A., and M.S. performed the research. The original draft was written by T.S. and
reviewed by R.T., A.A., and M.S. All authors read and approved
the final manuscript.
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