Back

The fate of mutations on Y chromosomes andautosomes: a unified Wright-Fisher frameworkaccounting for segregation time

Offenstadt, A.; Billiard, S.; Giraud, T.; Veber, A.; Jay, P.

2026-04-03 evolutionary biology
10.64898/2026.04.01.715871 bioRxiv
Show abstract

Understanding how mutations evolve on Y chromosomes is central to explaining the origin, diversity and persistence of sex chromosomes. Mutations occurring on the Y chromosome in sexual populations experience selective dynamics that differ markedly from those on autosomes, due to a reduced effective population size and the presence of large non-recombining regions containing alleles maintained in a permanently heterozygous state. These specific features alter gene transmission in the Y chromosome population compared to autosomes, even within the same pedigree. Here, we provide a two-sex diploid Wright-Fisher model that explicitly incorporates both sex chromosomes and autosomes within a unified population framework, in order to capture the influence of these specificities on the fate of mutations, not only considering fixation probabilities but also segregation times. We use diffusion approximations and provide analytical and numerical tools to compute these quantities across a wide range of parameters and selection regimes. We recover classical results on fixation probabilities in various scenarios, including purely beneficial, deleterious or overdominant mutations, and extend them in the light of mean segregation time, a key but often overlooked determinant of evolutionary outcomes over finite timescales. In particular, our analyses show that overdominant mutations are overall more likely to fix in observable time windows on the Y chromosome than on autosomes. Individual-based simulations corroborate our approximations and highlight parameter regimes where the theoretical approach is particularly useful, especially for parameter values inducing long segregation times or small fixation probabilities, for which simulations are impractical. Our results provide a comprehensive and tractable framework for clarifying how chromosome-specific features shape evolutionary dynamics beyond fixation probabilities alone.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
Genetics
225 papers in training set
Top 0.1%
43.1%
2
Evolution
199 papers in training set
Top 0.2%
12.8%
50% of probability mass above
3
PLOS Computational Biology
1633 papers in training set
Top 5%
6.6%
4
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 13%
5.0%
5
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 1.0%
4.1%
6
Theoretical Population Biology
47 papers in training set
Top 0.1%
3.7%
7
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 2%
3.7%
8
PLOS Genetics
756 papers in training set
Top 8%
1.9%
9
GENETICS
189 papers in training set
Top 0.6%
1.8%
10
Molecular Biology and Evolution
488 papers in training set
Top 3%
1.4%
11
The American Naturalist
114 papers in training set
Top 1%
1.4%
12
Journal of Evolutionary Biology
98 papers in training set
Top 0.7%
1.3%
13
Bulletin of Mathematical Biology
84 papers in training set
Top 2%
1.0%
14
Nature Communications
4913 papers in training set
Top 63%
0.7%
15
PLOS ONE
4510 papers in training set
Top 73%
0.5%
16
Heredity
53 papers in training set
Top 0.4%
0.5%
17
Evolution Letters
71 papers in training set
Top 2%
0.5%
18
Journal of The Royal Society Interface
189 papers in training set
Top 6%
0.5%
19
Scientific Reports
3102 papers in training set
Top 80%
0.5%
20
G3: Genes, Genomes, Genetics
222 papers in training set
Top 1%
0.5%
21
eLife
5422 papers in training set
Top 62%
0.5%
22
BMC Ecology and Evolution
49 papers in training set
Top 2%
0.5%