Genetic load

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Genetic load is the difference between the fitness of an average genotype in a population and the fitness of some reference genotype, which may be either the best present in a population, or may be the theoretically optimal genotype. The average individual taken from a population with a low genetic load will generally, when grown in the same conditions, have more surviving offspring.[1][2] Genetic load can also be seen as reduced fitness at the population level compared to what the population would have if all individuals had the reference high-fitness genotype.[3] High genetic load may put a population in danger of extinction.


Consider n genotypes , which have the fitnesses and the genotype frequencies respectively. Ignoring frequency-dependent selection, then genetic load may be calculated as:

where is either some theoretical optimum, or the maximum value of the fitnesses that are actually found in at least a single copy in the population, and is mean fitness which is calculated as the mean of all the fitnesses weighted by their corresponding frequency:

where the genotype is and has the fitness and frequency and respectively.

One problem with calculating genetic load is that it is difficult to evaluate either the theoretically optimal genotype, or the maximally fit genotype actually present in the population.[4] This is not a problem within mathematical models of genetic load, or for empirical studies that compare the relative value of genetic load in one setting to genetic load in another.


Deleterious Mutation[edit]

Deleterious mutation load is the main contributing factor to genetic load overall.[5] Most mutations are deleterious, and occur at a high rate. The Haldane-Muller theorem of mutation-selection balance says that the load depends only on the deleterious mutation rate and not on the selection coefficient.[6] Specifically, relative to an ideal genotype of fitness 1, the mean population fitness is where U is the total deleterious mutation rate summed over many independent sites. The intuition for the lack of dependence on the selection coefficient is that while mutations with stronger effects do more harm per generation, their harm is felt for fewer generations.

Slightly deleterious mutations may not stay in mutation-selection balance but may instead become fixed by genetic drift when their selection coefficient is less than one divided by the effective population size.[7] In asexual populations, the stochastic accumulation of mutation load is called Muller’s ratchet, and occurs in the absence of beneficial mutations, when after the most-fit genotype has been lost, it cannot be regained by genetic recombination. Deterministic accumulation of mutation load occurs in asexuals when the deleterious mutation rate exceeds one per replication.[8] Sexually reproducing species are expected to have lower genetic loads.[9] This is one hypothesis for the evolutionary advantage of sexual reproduction. Purging of deleterious mutations in sexual populations is facilitated by synergistic epistasis among deleterious mutations.[10]

High load can lead to a small population size, which in turn increases the accumulation of mutation load, culminating in extinction via mutational meltdown.[11][12]

The accumulation of deleterious mutations in humans has been of concern to many geneticists, including Hermann Joseph Muller,[13] James F. Crow,[10] Alexey Kondrashov,[14] W. D. Hamilton,[15] and Mike Lynch.[16]

Beneficial Mutation[edit]

New beneficial mutations create fitter genotypes than those previously present in the population. When load is calculated as the difference between the fittest genotype present and the average, this creates a substitutional load. The difference between the theoretical maximum (which may not actually be present) and the average is known as the "lag load".[17] Motoo Kimura's original argument for the neutral theory of molecular evolution was that if most differences between species were adaptive, this would exceed the speed limit to adaptation set by the substitutional load.[18] However, Kimura's argument confused the lag load with the substitutional load, using the former when it is the latter that in fact sets the maximal rate of evolution by natural selection.[19]


Inbreeding increases homozygosity. In the short run, an increase in inbreeding increases the probability with which offspring get two copies of a recessive deleterious alleles, lowering fitnesses via inbreeding depression.[20] In a species that habitually inbreeds, e.g through self-fertilization, recessive deleterious alleles are purged.[21][22]

Recombination/segregation load[edit]

Combinations of alleles that have evolved to work well together may not work when recombined with a different suite of coevolved alleles, leading to outbreeding depression. Segregation load is the presence of underdominant heterozygotes (i.e. heterozygotes that are less fit than either homozygote). Recombination load arises through unfavorable combinations across multiple loci that appear when favorable linkage disequilibria are broken down.[23] Recombination load can also arise by combining deleterious alleles subject to synergestic epistasis, i.e. whose damage in combination is greater than that predicted from considering them in isolation.[24]

Migration Load[edit]

Numerous studies suggest that the introduction of a new species into a foreign environment can lead to an initial migration load, which can negatively affect genetic fitness.

In some cases however, the effects of migration load are offset through survival and selective rounds of breeding. Through genetic diversity, the new offspring are able to adapt to the environment more successfully than the original population. Therefore, if an organism is capable of overcoming the initial effects of migration load, the effect on the genetic fitness of future generations is drastically altered.

It should be noted that due to the low chance of an organism successfully transferring genes into the base population (due to reduced genetic fitness), the effects of migration load are still present.


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