PT  - JOURNAL ARTICLE
AU  - Benjamin Galeota-Sprung
AU  - Paul Sniegowski
AU  - Warren Ewens
TI  - Mutational load and the functional fraction of the human genome
AID  - 10.1101/785865
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 785865
4099  - http://biorxiv.org/content/early/2020/03/16/785865.short
4100  - http://biorxiv.org/content/early/2020/03/16/785865.full
AB  - The fraction of the human genome that is functional is a question of both evolutionary and practical importance. Studies of sequence divergence have suggested that the functional fraction of the human genome is likely to be no more than ∼15%. In contrast, the ENCODE project, a systematic effort to map regions of transcription, transcription factor association, chromatin structure, and histone modification, assigned function to 80% of the human genome. In this paper we examine whether and how an analysis based on mutational load might set a limit on the functional fraction. In order to do so, we characterize the distribution of fitness of a large, finite, diploid population at mutation-selection equilibrium. In particular, if mean fitness is ∼1, the fitness of the fittest individual likely to occur cannot be unreasonably high. We find that at equilibrium, the distribution of log fitness has variance nus, where u is the per-base deleterious mutation rate, n is the number of functional sites (and hence incorporates the functional fraction f), and s is the selection coefficient of deleterious mutations. In a large (N = 109) reproducing population, the fitness of the fittest individual likely to exist is . These results apply to both additive and recessive fitness schemes. Our approach is different from previous work that compared mean fitness at mutation-selection equilibrium to the fitness of an individual who has no deleterious mutations; we show that such an individual is exceedingly unlikely to exist. We find that the functional fraction is not very likely to be limited substantially by mutational load, and that any such limit, if it exists, depends strongly on the selection coefficients of new deleterious mutations.