Leveraging distant relatedness to quantify human

20 The rate at which human genomes mutate is a central biological parameter that 21 has many implications for our ability to understand demographic and evolutionary 22 phenomena. We present a method for inferring mutation and gene conversion rates 23 using the number of sequence differences observed in identical-by-descent (IBD) 24 segments together with a reconstructed model of recent population size history. 25 This approach is robust to, and can quantify, the presence of substantial geno26 typing error, as validated in coalescent simulations. We applied the method to 27 498 trio-phased Dutch individuals from the Genome of the Netherlands (GoNL) 28 project, sequenced at an average depth of 13x. We infer a point mutation rate of 29 1.66±0.04×10−8 per base per generation, and a rate of 1.26±0.06×10−9 for < 20 30 bp indels. Our estimated average genome-wide mutation rate is higher than most 31 pedigree-based estimates reported thus far, but lower than estimates obtained using 32 substitution rates across primates. By quantifying how estimates vary as a function 33 of allele frequency, we infer the probability that a site is involved in non-crossover 34 gene conversion as 5.99± 0.69× 10−6, consistent with recent reports. We find that 35 recombination does not have observable mutagenic effects after gene conversion is 36 accounted for, and that local gene conversion rates reflect recombination rates. We 37 detect a strong enrichment for recent deleterious variation among mismatching vari38 ants found within IBD regions, and observe summary statistics of local IBD sharing 39 to closely match previously proposed metrics of background selection, but find no 40 2 . CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/020776 doi: bioRxiv preprint first posted online Jun. 16, 2015;