English: Recent estimates of the human genome-wide mutation rate. The human germline mutation rate is approximately 0.5×10^-9 bp^-1 yr^-1.

Estimates are shown as yearly rates, scaled where necessary using a mean generation time of 29 yrs [17]; confidence intervals (90% or 95%) are shown where reported. Citation numbers and publication years are given on the x-axis. family: Family sequencing compares genomes sampled from consecutive generations in one or more families, and within each one identifies de novo mutations present in offspring and in neither parent [3-12]. Per-generation mutation rate is calculated as the mean number of de novo mutations seen divided by the length of `callable' genome sequenced (the number of genomic positions where a de novo mutation would have been called if present). IBD: Estimation based on identity by descent (IBD) detects de novo mutations as differences between chromosomal tracts which have been inherited IBD within or between individuals, for example in samples which are related to each other within a multi-generation pedigree. Information about the number of generations separating chromosomes may come from genealogical records [13] and/or from genetic inference [14]. aDNA: Estimation based on branch shortening in ancient DNA uses genome sequence data from an ancient human sample of known age (established with radioisotope dating) and divides the mean number of extra mutations found in present-day humans by the separation in time [18]. PSMC: The pairwise sequential Markovian coalescent method infers ancestral effective population size from diploid genome sequence data [19]. A mutation rate can be estimated as the one which best aligns effective population size histories inferred from modern and ancient samples after accounting for the known age difference between them [18]. other: Methods based on comparison with other mutational clocks: calibration using coalescent time estimates based on microsatellite mutations [15]; calibration against the recombination rate and expected variation of heterozygosity in diploid genomes [16]. Inset: Indicative timescales over which mutations detected by each method (or which otherwise influence its estimate) have accumulated.

• [3] Roach JC, Glusman G, Smit AFA, Huff CD, Hubley R, Shannon PT, Rowen L, Pant KP, Goodman N, Bamshad M, et al.: Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science (New York, NY) 2010. 328:636-9. PMC 3037280
• [4] Awadalla P, Gauthier J, Myers RA, Casals F, Hamdan FF, Griffng AR, C^ote M, Henrion E, Spiegelman D, Tarabeux J, et al.: Direct Measure of the De Novo Mutation Rate in Autism and Schizophrenia Cohorts. The American Journal of Human Genetics 2010. 87:316-324. PMC 2933353
• [5] 1000 Genomes Project Consortium: A map of human genome variation from population-scale sequencing. Nature 2010. 467:1061-1073. PMC 3042601
• [6] Conrad DF, Keebler JEM, DePristo Ma, Lindsay SJ, Zhang Y, Casals F, Idaghdour Y, Hartl CL, Torroja C, Garimella KV, et al.: Variation in genome-wide mutation rates within and between human families. Nature Genetics 2011. 43:712-714. PMC 3322360
• [7] Michaelson JJ, Shi Y, Gujral M, Zheng H, Malhotra D, Jin X, Jian M, Liu G, Greer D, Bhandari A, et al.: Whole-Genome Sequencing in Autism Identifies Hot Spots for De Novo Germline Mutation. Cell 2012. 151:1431-1442. PMC 3712641
• [8] Kong A, Frigge ML, Masson G, Besenbacher S, Sulem P, Magnusson G, Gudjonsson Sa, Sigurdsson A, Jonasdottir A, Jonasdottir A, et al.: Rate of de novo mutations and the importance of father's age to disease risk. Nature 2012. 488:471-475. PMC 3548427
• [9] Genome of the Netherlands Consortium: Whole-genome sequence variation, population structure and demographic history of the dutch population. Nature Genetics 2014. 46:818-825. PMC 4366498
• [10] Besenbacher S, Liu S, Izarzugaza JMG, Grove J, Belling K, Bork-Jensen J, Huang S, Als TD, Li S, Yadav R, et al.: Novel variation and de novo mutation rates in population-wide de novo assembled Danish trios. Nature Communications 2015. 6:5969. PMC 4309431
• [11] Rahbari R, Wuster A, Lindsay SJ, Hardwick RJ, Alexandrov LB, Al Turki S, Dominiczak A, Morris A, Porteous D, Smith B, et al.: Timing, rates and spectra of human germline mutation. Nature Genetics 2015. 1-11. PMC 4731925
• [12] Wong WSW, Solomon BD, Bodian DL, Kothiyal P, Eley G, Huddleston KC, Baker R, Thach DC, Iyer RK, Vockley JG, et al.: New observations on maternal age effect on germline de novo mutations. Nature Communications 2016. 7:10486. PMC 4735694
• [13] Campbell CD, Chong JX, Malig M, Ko A, Dumont BL, Han L, Vives L, O'Roak BJ, Sudmant PH, Shendure J, et al.: Estimating the human mutation rate using autozygosity in a founder population. Nature Genetics 2012. 44:1277-1281. PMC 3483378
• [14] Palamara PF, Francioli LC, Wilton PR, Genovese G, Gusev A, Finucane HK, Sankararaman S, Sunyaev SR, De Bakker PIW, Wakeley J, et al.: Leveraging Distant Relatedness to Quantify Human Mutation and Gene-Conversion Rates. American Journal of Human Genetics 2015. 97:775-789. PMC 4678427
• [15] Sun JX, Helgason A, Masson G, Ebenesersdottir SS, Li H, Mallick S, Gnerre S, Patterson N, Kong A, Reich D, et al.: A direct characterization of human mutation based on microsatellites. Nature Genetics 2012. 44:1161-1165. PMC 3459271
• [16] Lipson M, Loh PR, Sankararaman S, Patterson N, Berger B, Reich D: Calibrating the Human Mutation Rate via Ancestral Recombination Density in Diploid Genomes. PLoS Genetics 2015. 11:e1005550. PMC 4642934
• [17] Fenner JN: Cross-cultural estimation of the human generation interval for use in genetics-based population divergence studies. American Journal of Physical Anthropology 2005. 128:415-423. [1]
• [18] Fu Q, Li H, Moorjani P, Jay F, Slepchenko SM, Bondarev Aa, Johnson PLF, Aximu-Petri A, Pr?ufer K, de Filippo C, et al.: Genome sequence of a 45,000-year-old modern human from western Siberia. Nature 2014. 514:445-449. PMC 4753769