In genetics, the mutation rate is the frequency of new mutations in a single gene or organism over time. Mutation rates are not constant and are not limited to a single type of mutation, therefore there are many different types of mutations. Mutation rates are given for specific classes of mutations. Point mutations are a class of mutations which are small or large scale insertions or deletions. There are also Missense and Nonsense mutations, which are variations of point mutations. The rate of these types of substitutions can be further subdivided into a mutation spectrum which describes the influence of the genetic context on the mutation rate.
There are several natural units of time for each of these rates, with rates being characterized either as mutations per base pair per cell division, per gene per generation, or per genome per generation. The mutation rate of an organism is an evolved characteristic and is strongly influenced by the genetics of each organism, in addition to strong influence from the environment. The upper and lower limits to which mutation rates can evolve is the subject of ongoing investigation. However, the mutation rate does vary over the genome. Over DNA, RNA or a single gene, mutation rates are changing.
When the mutation rate in humans increases certain health risks can occur, for example, cancer and other hereditary diseases. Having knowledge of mutation rates is vital to understanding the future of cancers and many hereditary diseases.
Different genetic variants within a species are referred to as alleles, therefore a new mutation can create a new allele. In Population genetics, each allele is characterized by a selection coefficient, which measures the expected change in an allele's frequency over time. The selection coefficient can either be negative, corresponding to an expected decrease, positive, corresponding to an expected increase, or zero, corresponding to no expected change. The distribution of fitness effects of new mutations is an important parameter in population genetics and has been the subject of extensive investigation. Although measurements of this distribution have been inconsistent in the past, it is now generally thought that the majority of mutations are mildly deleterious, that many have little effect on an organism's fitness, and that a few can be favorable.
Because of natural selection, unfavorable mutations will typically be eliminated from a population while favorable changes are generally kept for the next generation, and neutral changes accumulate at the rate they are created by mutations. This process happens by reproduction. In a particular generation the 'best fit' survive with higher probability, passing their genes to their offspring. The sign of the change in this probability defines mutations to be beneficial, neutral or harmful to organisms.
An organism's mutation rates can be measured by a number of techniques.
One way to measure the mutation rate is by the fluctuation test, also known as the Luria–Delbrück experiment. This experiment exhibits in bacteria mutations occur in the absence of selection instead of the presence of selection.
This is very important to mutation rates because it proves experimentally mutations can occur without selection being a component. Therefore, mutations occur at random in bacteria (and other organisms.)
Many sites in an organism's genome may admit mutations with small fitness effects. These sites are typically called neutral sites. Theoretically mutations under no selection become fixed between organisms at precisely the mutation rate. Fixed synonymous mutations, i.e. synonymous substitutions, are changes to the sequence of a gene that do not change the protein produced by that gene. They are often used as estimates of that mutation rate, despite the fact that some synonymous mutations have fitness effects. As an example, mutation rates have been directly inferred from the whole genome sequences of experimentally evolved replicate lines of Escherichia coli B.
Mutation Accumulation Lines
A particularly labor-intensive way of characterizing the mutation rate is the mutation accumulation line.
Mutation accumulation lines have been used to characterize mutation rates with the Bateman-Mukai Method and direct sequencing of e.g. intestinal bacteria, round-worms, yeast, fruit flies, small annual plants.
Variation in mutation rates
Mutation rates differ between species and even between different regions of the genome of a single species. These different rates of nucleotide substitution are measured in substitutions (fixed mutations) per base pair per generation. For example, mutations in intergenic, or non-coding, DNA tend to accumulate at a faster rate than mutations in DNA that is actively in use in the organism (gene expression). That is not necessarily due to a higher mutation rate, but to lower levels of purifying selection. A region which mutates at predictable rate is a candidate for use as a molecular clock.
If the rate of neutral mutations in a sequence is assumed to be constant (clock-like), and if most differences between species are neutral rather than adaptive, then the number of differences between two different species can be used to estimate how long ago two species diverged (see molecular clock). In fact, the mutation rate of an organism may change in response to environmental stress. For example, UV light damages DNA, which may result in error prone attempts by the cell to perform DNA repair.
The human mutation rate is higher in the male germ line (sperm) than the female (egg cells), but estimates of the exact rate have varied by an order of magnitude or more. This means that a human genome accumulates around 64 new mutations per generation because each full generation involves a number of cell divisions to generate gametes. Human mitochondrial DNA has been estimated to have mutation rates of ~3× or ~2.7×10−5 per base per 20 year generation (depending on the method of estimation); these rates are considered to be significantly higher than rates of human genomic mutation at ~2.5×10−8 per base per generation. Using data available from whole genome sequencing, the human genome mutation rate is similarly estimated to be ~1.1×10−8 per site per generation.
The rate for other forms of mutation also differs greatly from point mutations. An individual microsatellite locus often has a mutation rate on the order of 10−4, though this can differ greatly with length.
Some sequences of DNA may be more susceptible to mutation. For example, stretches of DNA in human sperm which lack methylation are more prone to mutation.
In general, the mutation rate in unicellular eukaryotes (and bacteria) is roughly 0.003 mutations per genome per cell generation. However, some species, especially the ciliate of the genus Paramecium have an unusually low mutation rate. For instance, Paramecium tetraurelia has a base-substitution mutation rate of ~2 × 10−11 per site per cell division. This is the lowest mutation rate observed in nature so far, being about 75× lower than in other eukaryotes with a similar genome size, and even 10× lower than in most prokaryotes. The low mutation rate in Paramecium has been explained by its transcriptionally silent germ-line nucleus, consistent with the hypothesis that replication fidelity is higher at lower gene expression levels.
The highest per base pair per generation mutation rates are found in viruses, which can have either RNA or DNA genomes. DNA viruses have mutation rates between 10−6 to 10−8 mutations per base per generation, and RNA viruses have mutation rates between 10−3 to 10−5 per base per generation.
The mutation spectrum of an organism is the rate at which different mutations occur at different sites. Typically two sites are considered, each of which may have three mutations, resulting in six total rates for most mutation spectra. The two sites are the two correct pairs possible in DNA: A:T pairs and C:G pairs;
The theory on the evolution of mutation rates identifies three principal forces involved: the generation of more deleterious mutations with higher mutation, the generation of more advantageous mutations with higher mutation, and the metabolic costs and reduced replication rates that are required to prevent mutations. Different conclusions are reached based on the relative importance attributed to each force. The optimal mutation rate of organisms may be determined by a trade-off between costs of a high mutation rate, such as deleterious mutations, and the metabolic costs of maintaining systems to reduce the mutation rate (such as increasing the expression of DNA repair enzymes. or, as reviewed by Bernstein et al. having increased energy use for repair, coding for additional gene products and/or having slower replication). Secondly, higher mutation rates increase the rate of beneficial mutations, and evolution may prevent a lowering of the mutation rate in order to maintain optimal rates of adaptation. As such, hypermutation enables some cells to rapidly adapt to changing conditions in order to avoid the entire population from becoming extinct. Finally, natural selection may fail to optimize the mutation rate because of the relatively minor benefits of lowering the mutation rate, and thus the observed mutation rate is the product of neutral processes.
Studies have shown that treating RNA viruses such as poliovirus with ribavirin produce results consistent with the idea that the viruses mutated too frequently to maintain the integrity of the information in their genomes. This is termed error catastrophe.
The high mutation rate HIV (Human Immunodeficiency Virus) of 3 x 10−5 per base and generation, coupled with its short replication cycle leads to a high antigen variability, allowing it to evade the immune system.
- Scally A (December 2016). "The mutation rate in human evolution and demographic inference". Current Opinion in Genetics & Development. 41: 36–43. doi:10.1016/j.gde.2016.07.008. PMID 27589081.
- Crow JF (August 1997). "The high spontaneous mutation rate: is it a health risk?". Proceedings of the National Academy of Sciences of the United States of America. 94 (16): 8380–6. Bibcode:1997PNAS...94.8380C. doi:10.1073/pnas.94.16.8380. PMC 33757. PMID 9237985.
- Pope CF, O'Sullivan DM, McHugh TD, Gillespie SH (April 2008). "A practical guide to measuring mutation rates in antibiotic resistance". Antimicrobial Agents and Chemotherapy. 52 (4): 1209–14. doi:10.1128/AAC.01152-07. PMC 2292516. PMID 18250188.
- Tomlinson IP, Novelli MR, Bodmer WF (December 1996). "The mutation rate and cancer". Proceedings of the National Academy of Sciences of the United States of America. 93 (25): 14800–3. Bibcode:1996PNAS...9314800T. doi:10.1073/pnas.93.25.14800. PMC 26216. PMID 8962135.
- Eyre-Walker A, Keightley PD (August 2007). "The distribution of fitness effects of new mutations". Nature Reviews. Genetics. 8 (8): 610–8. doi:10.1038/nrg2146. PMID 17637733.
- Scally A, Durbin R (October 2012). "Revising the human mutation rate: implications for understanding human evolution". Nature Reviews. Genetics. 13 (10): 745–53. doi:10.1038/nrg3295. PMID 22965354.
- "Luria–Delbrück experiment". Wikipedia. 2017-04-25.
- Wielgoss S, Barrick JE, Tenaillon O, Cruveiller S, Chane-Woon-Ming B, Médigue C, Lenski RE, Schneider D (August 2011). "Mutation Rate Inferred From Synonymous Substitutions in a Long-Term Evolution Experiment With Escherichia coli". G3. 1 (3): 183–186. doi:10.1534/g3.111.000406. PMC 3246271. PMID 22207905.
- Ossowski S, Schneeberger K, Lucas-Lledó JI, Warthmann N, Clark RM, Shaw RG, Weigel D, Lynch M (January 2010). "The rate and molecular spectrum of spontaneous mutations in Arabidopsis thaliana". Science. 327 (5961): 92–4. Bibcode:2010Sci...327...92O. doi:10.1126/science.1180677. PMC 3878865. PMID 20044577.
- Drake JW, Charlesworth B, Charlesworth D, Crow JF (April 1998). "Rates of spontaneous mutation". Genetics. 148 (4): 1667–86. PMC 1460098. PMID 9560386.
- Schneider S, Excoffier L (July 1999). "Estimation of past demographic parameters from the distribution of pairwise differences when the mutation rates vary among sites: application to human mitochondrial DNA". Genetics. 152 (3): 1079–89. PMC 1460660. PMID 10388826.
- Nachman MW, Crowell SL (September 2000). "Estimate of the mutation rate per nucleotide in humans". Genetics. 156 (1): 297–304. PMC 1461236. PMID 10978293.
- Roach JC, Glusman G, Smit AF, Huff CD, Hubley R, Shannon PT, Rowen L, Pant KP, Goodman N, Bamshad M, Shendure J, Drmanac R, Jorde LB, Hood L, Galas DJ (April 2010). "Analysis of genetic inheritance in a family quartet by whole-genome sequencing". Science. 328 (5978): 636–9. Bibcode:2010Sci...328..636R. doi:10.1126/science.1186802. PMC 3037280. PMID 20220176.
- Whittaker JC, Harbord RM, Boxall N, Mackay I, Dawson G, Sibly RM (June 2003). "Likelihood-based estimation of microsatellite mutation rates". Genetics. 164 (2): 781–7. PMC 1462577. PMID 12807796.
- Gravtiz, Lauren (28 June 2012). "Lack of DNA modification creates hotspots for mutations". Simons Foundation Autism Research Initiative.
- Sung W, Tucker AE, Doak TG, Choi E, Thomas WK, Lynch M (November 2012). "Extraordinary genome stability in the ciliate Paramecium tetraurelia". Proceedings of the National Academy of Sciences of the United States of America. 109 (47): 19339–44. Bibcode:2012PNAS..10919339S. doi:10.1073/pnas.1210663109. PMC 3511141. PMID 23129619.
- Altenberg L (June 2011). "An evolutionary reduction principle for mutation rates at multiple Loci". Bulletin of Mathematical Biology. 73 (6): 1227–70. arXiv:0909.2454. doi:10.1007/s11538-010-9557-9. PMID 20737227.
- Sniegowski PD, Gerrish PJ, Johnson T, Shaver A (December 2000). "The evolution of mutation rates: separating causes from consequences". BioEssays. 22 (12): 1057–66. doi:10.1002/1521-1878(200012)22:12<1057::AID-BIES3>3.0.CO;2-W. PMID 11084621.
- Bernstein H, Hopf FA, Michod RE (1987). "The molecular basis of the evolution of sex". Advances in Genetics. 24: 323–70. doi:10.1016/s0065-2660(08)60012-7. ISBN 9780120176243. PMID 3324702.
- Orr HA (June 2000). "The rate of adaptation in asexuals". Genetics. 155 (2): 961–8. PMC 1461099. PMID 10835413.
- Swings, Toon; Van den Bergh, Bram; Wuyts, Sander; Oeyen, Eline; Voordeckers, Karin; Verstrepen, Kevin J; Fauvart, Maarten; Verstraeten, Natalie; Michiels, Jan (2017-05-02). "Adaptive tuning of mutation rates allows fast response to lethal stress in Escherichia coli". eLife. 6. doi:10.7554/eLife.22939. ISSN 2050-084X. PMC 5429094. PMID 28460660.
- Lynch M (August 2010). "Evolution of the mutation rate". Trends in Genetics. 26 (8): 345–52. doi:10.1016/j.tig.2010.05.003. PMC 2910838. PMID 20594608.
- Sung W, Ackerman MS, Miller SF, Doak TG, Lynch M (November 2012). "Drift-barrier hypothesis and mutation-rate evolution". Proceedings of the National Academy of Sciences of the United States of America. 109 (45): 18488–92. Bibcode:2012PNAS..10918488S. doi:10.1073/pnas.1216223109. PMC 3494944. PMID 23077252.
- Crotty S, Cameron CE, Andino R (June 2001). "RNA virus error catastrophe: direct molecular test by using ribavirin". Proceedings of the National Academy of Sciences of the United States of America. 98 (12): 6895–900. Bibcode:2001PNAS...98.6895C. doi:10.1073/pnas.111085598. PMC 34449. PMID 11371613.
- Rambaut A, Posada D, Crandall KA, Holmes EC (January 2004). "The causes and consequences of HIV evolution". Nature Reviews Genetics. 5 (52–61): 52–61. doi:10.1038/nrg1246. PMID 14708016.
- Media related to Mutation rate at Wikimedia Commons