Although it is known that the mutation rate varies across the genome, previous estimates were based on averaging across various numbers of positions. Here, we describe a method to measure the origination rates of target mutations at target base positions and apply it to a 6-bp region in the human hemoglobin subunit beta (
HBB) gene and to the identical, paralogous hemoglobin subunit delta (
HBD) region in sperm cells from both African and European donors. The
HBB region of interest (ROI) includes the site of the hemoglobin S (HbS) mutation, which protects against malaria, is common in Africa, and has served as a classic example of adaptation by random mutation and natural selection. We found a significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than in Europeans in the
HBB region studied. Finally, the rate of the 20A→T mutation, called the “HbS mutation” when it appears in
HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African
HBB ROI, where it is of adaptive significance, representing at least three independent originations; no instances were observed elsewhere. Further studies will be needed to examine mutation rates at the single-mutation resolution across these and other loci and organisms and to uncover the molecular mechanisms responsible.It is widely known that mutation rates vary across the genome at multiple scales (
Hodgkinson and Eyre-Walker 2011;
Rahbari et al. 2016;
Carlson et al. 2018) and are affected by multiple factors, from the mutation type (
Gojobori et al. 1982;
Bulmer 1986), to the local genetic context (
Gojobori et al. 1982;
Bulmer 1986;
Blake et al. 1992;
Hwang and Green 2004;
Rahbari et al. 2016;
Carlson et al. 2018), to the general location in the genome (
Wolfe et al. 1989;
Matassi et al. 1999;
Lercher et al. 2001;
Ellegren et al. 2003). Although this knowledge is highly advanced now compared with what was known a mere decade ago (
Campbell et al. 2012;
Michaelson et al. 2012;
Francioli et al. 2015;
Rahbari et al. 2016;
Carlson et al. 2018), it could be enhanced further. In particular, rate measurements to date all have been based on averages of various kinds, such as an average across the genome (
Nachman and Crowell 2000;
Rahbari et al. 2016), or across the instances of any particular motif (
Hwang and Green 2004;
Carlson et al. 2018), or in certain cases, across the entire stretch of a gene (
Haldane 1949;
Vogel and Motulsky 1997;
Kondrashov 2003). In contrast, technological limitations have precluded measuring mutation rates at particular base positions and of particular mutations at such positions. However, such high-resolution knowledge of the mutation rate variation would bear on multiple open questions in genetics and evolution—from the relative importance of mutation rate variation to the site frequency spectrum (SFS) (
Harpak et al. 2016;
Lek et al. 2016;
Mathieson and Reich 2017), to its importance for adaptive evolution and parallelism (
Inoue et al. 2001;
Crow et al. 2009;
Dumas et al. 2012;
Losos 2017;
Kratochwil et al. 2019;
Kratochwil and Meyer 2019;
Lind 2019;
Xie et al. 2019), to its contribution to recurrent genetic disease and cancer (
Lupski 1998;
McClellan and King 2010;
Veltman and Brunner 2012;
Shendure and Akey 2015).The most precise way of measuring mutation rates, free of biases attributable to past natural selection or random genetic drift events, is offered by de novo mutations—mutations that appeared for the first time in their carrier (
Goldmann et al. 2016;
Rahbari et al. 2016). These mutations are usually detected by studies comparing the genomes of children to those of their parents, also known as “trio studies” (
Roach et al. 2010;
Conrad et al. 2011). However, because each individual carries only a small number (e.g., several dozen in humans) of de novo mutations scattered across the genome, the chance of encountering any particular target mutation of interest is miniscule, rendering it impractical to measure rates of target mutations using such studies.To overcome this barrier, we have developed a method that enables identifying and counting, with high accuracy, ultrarare genetic variants of choice in extremely narrow regions of interest (ROIs) within large populations of cells, such as a single target mutant in 100 million genomes. Because this method has both an error rate lower than the human mutation rate and sufficient yield for the purpose, it enables measuring the frequencies of target mutations of choice in human sperm samples by counting their de novo instances at a single-digit resolution. For variants that are not expected to affect sperm fertility and viability (as in the case below), this frequency is the evolutionarily relevant mutation rate in males. Note that aside from this evolutionary application, ultra-accurate methods of mutation-detection are sought after for early detection of cancer, noninvasive prenatal testing, early identification of virus within host, and more (
Salk et al. 2018).As a first target for this method, we chose two sites: a 6-bp region spanning three codons within the human hemoglobin subunit beta (
HBB) gene that is of great importance for adaptation and hematologic disease, and the identical, paralogous region within the hemoglobin subunit delta (
HBD) gene. The former region includes, among others, the site of the hemoglobin S (HbS) mutation. The most iconic balanced polymorphism mutation (
Pauling et al. 1949;
Allison 1954;
Ingram 1957;
Cavalli-Sforza and Feldman 2003;
Feng et al. 2004;
Hartl and Clark 2007), the HbS mutation is an A to T transversion (GAG→GTG, Glu→Val) in codon 6 of
HBB causing sickle-cell anemia in homozygotes (
Pauling et al. 1949) and providing substantial protection against severe malaria in heterozygotes (
Allison 1954;
Flint et al. 1998;
Kwiatkowski 2005;
Piel et al. 2010). Malaria, in turn, has been a leading cause of human morbidity and mortality, often causing more than a million deaths per year in the recent past, with Africa bearing the brunt of the disease burden (
Carter and Mendis 2002), and thus has been possibly the strongest known agent of selection in humans in recent history (
Kwiatkowski 2005). Besides the HbS mutation, many other mutations, both point mutations and indels, are also known at this site, many of which are involved in hematologic illness (
Hardison et al. 2002;
Hardison and Miller 2002). In contrast to
HBB, mutations in
HBD have a more limited effect and are not thought to confer resistance to malaria, because the
HBD’s lower expression levels make it account for <3% of the circulating red blood cell hemoglobin in adults (
Steinberg and Adams 1991). Although the population prevalence of the
HBB mutations, whether beneficial or detrimental, is normally attributed to natural selection, so far it has not been possible to examine to what degree, if at all, mutational phenomena may also be relevant to their prevalence. To address this gap, we sought to characterize the rates of mutations, including the HbS mutation, in the
HBB and
HBD ROIs in sperm samples of both African and European donors.
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