首页|Using runs of homozygosity and machine learning to disentangle sources of inbree ding and infer self-fertilization rates
Using runs of homozygosity and machine learning to disentangle sources of inbree ding and infer self-fertilization rates
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from bi orxiv.org: "Runs of homozygosity (ROHs) are indicative of elevated homozygosity and inbreed ing due to mating of closely related individuals. Self-fertilization can be a ma jor source of inbreeding which elevates genomewide homozygosity and thus should also create long ROHs. While ROHs are frequently used to understand inbreeding in the context of conservation and selective breeding, as well as for consanguin ity of populations and their demographic history, it remains unclear how ROH cha racteristics are altered by selfing and if this confounds expected signatures of inbreeding due to demographic change. "Using simulations, we study the impact of the mode of reproduction and demograp hic history on ROHs. We apply random forests to identify unique characteristics of ROHs, indicative of different sources of inbreeding. We pinpoint distinct fea tures of ROHs that can be used to better characterize the type of inbreeding the population was subjected to and to predict outcrossing rates and complex demogr aphic histories.
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