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An extension of the Cx(Co)m model of crossover patterning to account for experimental mortality in Drosophila melanogaster

Koury, S. A.; Shiran, M. G.; Hammonds, E.; Schneider, C.; Stevison, L. S.

2026-01-08 genetics
10.64898/2026.01.07.697413 bioRxiv
Show abstract

Classic recombination experiments designed to test genetic and environmental treatments do not directly measure crossing-over, instead rates and distribution of meiotic events in F1 meiocytes is inferred from genetic markers in F2 adults. In Drosophila melanogaster females this procedure introduces a substantial "missing data problem" because 75% of meiotic chromatids segregate to polar body nuclei and another 11% are transmitted to inviable F2 zygotes which cannot be scored for recombination. To address these sources of uncertainty and bias we extend the Cx(Co)m model of the data-generating process by assuming: 1) programmed double strand breaks occur as a Poisson point process, 2) crossover maturation is a stationary renewal process, 3) chromosome segregation is random one-half thinning of this process, 4) fertilization by X-versus Y-bearing sperm is mendelian, and 5) egg-to-adult survival is binomially distributed with a rate parameter determined by F2 marker alleles. To quantify experimental mortality, we performed egg counts in a 6-point X chromosome testcross and marker-free controls on identical genetic backgrounds under standard laboratory conditions. The 19,927 fly dataset reveals 44% F2 experimental mortality, and likelihood ratio tests support a model where 36 of the 44% is due to sex-specific, marker-associated viability defects. Variability in X chromosome genetic lengths with experimental mortality can be simulated and we provide case-control 80% power curves to guide experimental design. We propose that differential mortality should be the de facto null hypothesis when comparing F2 recombinant fractions and provide probabilistic models of the data-generating process to improve characterization of patterns in F1 meiotic events.

Published in GENETICS (predicted rank #1) · training set

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