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Updated: May 24, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
Published on: August 3, 2018
A model for biased fractionation after whole genome duplication
David Sankoff1, Chunfang Zheng, Baoyong Wang
1Department of Mathematics and Statistics, University of Ottawa, Ottawa K1N 6N5, Canada. sankoff@uottawa.ca
Background:
Paralog reduction, the loss of duplicate genes after whole genome duplication (WGD) is a pervasive process. Whether this loss proceeds gene by gene or through deletion of multi-gene DNA segments is controversial, as is the question of fractionation bias, namely whether one homeologous chromosome is more vulnerable to gene deletion than the other.
Results:
As a null hypothesis, we first assume deletion events, on either homeolog, excise a geometrically distributed number of genes with unknown mean μ, and a number r of these events overlap to produce deleted runs of length l. There is a fractionation bias 0 ≤ φ ≤ 1 for deletions to fall on one homeolog rather than the other. The parameter r is a random variable with distribution π(·). We simulate the distribution of run lengths l, as well as the underlying π(·), as a function of μ, φ and θ, the proportion of remaining genes in duplicate form. We show how sampling l allows us to estimate μ and φ. The main part of this work is the derivation of a deterministic recurrence to calculate each π(r) as a function of μ, φ and θ.
Conclusions:
The recurrence for π provides a deeper mathematical understanding of fractionation process than simulations. The parameters μ and φ can be estimated based on run lengths of single-copy regions.
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