Genetic load

Substitution load (cost of selection)

Haldane observed in 1957 that for a beneficial allele to sweep, individuals with alternative alleles must die (or forgo fertility), and that this imposes a speed limit to adaptation. We clarified a complex set of related concepts, centering around the fraction of deaths that are selective, and whether finite reproductive excess is sufficient to allow this (Matheson et al. 2025b). Standard relative fitness models of population genetics, e.g. the Wright-Fisher model, implicitly assume infinite reproductive excess, but we have developed models that explicitly treat its finite nature (Bertram & Masel 2019). The "lag load" is the difference between population mean fitness and some theoretical optimal fitness that is never obtained; inappropriate use of the lag load is one contributor to confusion (panel B). The more appropriate load is the difference between the population mean fitness and the highest fitness individual actually found in a population - this quantity was rediscovered and named the "lead" (Desai & Fisher 2007).

Mutation load

In the title of a 1995 paper, Alexey Kondrashov posed the puzzle "Why have we not died 100 times over?". Simple reasoning suggests that it should take one selective death to purge one new deleterious mutation, but the mean number of new deleterious mutations per human seems to be more than 2, exceeding the number of selective deaths available. Most work on mutation load periodically renormalizes relative fitness to deal with the fact that fitness keeps declining no matter what, or else treats only a subset of the genome. Either way, this is dodging the problem, not tackling its fundamentals, which are not specific to human mutation rates or to small population sizes. One historical solution to the mutation load paradox was synergistic epistasis, often modeled in extreme forms such as truncation selection. Since then, data has come out showing that the mean effects of two deleterious mutations are extraordinarily close to multiplicative. 

We think the answer is a "ratchet" in which many small-effect deleterious fixations are counterbalanced by a much smaller number of large-effect beneficial fixations (Matheson et al. 2025a). This has some similarities with "drift barrier theory", but emphasizes that the cause of the ratchet is not small population size, but a high genome-wide deleterious mutation rate.

We are also 

• exploring the impact of weak global epistasis, compatible with data

• improving empirical estimates of the genome-wide deleterious mutation rate, to see how far about 1 it is in humans, and what sort of mutations contribute the most

• studying the evolution of mutation rate

Publications :

• Mawass W, Hernández U, Matheson JD, Berg J, Masel J. (2026) Extinction vortices are partially driven by a shortage of beneficial mutations, rather than by deleterious mutation accumulation alone, Proceedings of the Royal Society of London B 293(2072): 20260600.

• Matheson JD, Bertram J, Masel J. (2025a) Human deleterious mutation rate slows adaptation and implies high fitness variance, BioRxiv.

• Matheson JD, Exposito-Alonso M, Masel J. (2025b) Substitution load revisited: a high proportion of deaths can be selective, Genetics: iyaf011.

• Matheson JD, Masel J. (2024) Background selection from unlinked sites causes non-independent evolution of deleterious mutations, Genome Biology & Evolution evae050.

• Bertram J, Gomez K, Masel J. (2017) Predicting patterns of long-term adaptation and extinction with population genetics, Evolution 71: 204–214.