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Relationship: 1981


A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Energy Deposition leads to Increase, Mutations

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Deposition of energy leading to lung cancer non-adjacent High High Brendan Ferreri-Hanberry (send email) Open for citation & comment WPHA/WNT Endorsed
Deposition of energy leading to occurrence of cataracts non-adjacent High High Arthur Author (send email) Open for citation & comment

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI
rat Rattus norvegicus High NCBI
mouse Mus musculus High NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Unspecific High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
All life stages High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Energy can be deposited on biomolecules from various forms of radiation. Radiation with high linear energy transfer (LET) tends to produce more complex, dense structural damage than low LET radiation; both, however, can lead to detrimental damage within a cell (Hada & Georgakilas, 2008; Okayasu, 2012; Lorat et al., 2015; Nikitaki et al., 2016). The DNA is particularly susceptible to damage which can be in the form of DNA strand breaks and the inadequate repair of these lesions can lead to mutations. DNA damage can be caused by direct and indirect mechanisms. Indirect involves formation of free radicals from the breakage of water molecules that can oxidize DNA and direct involves action on the DNA leading to strand breaks and complex lesions (Cannan & Pederson, 2016). Mutations may occur in germ cells or somatic cells; mutations in germ stem and progenitor cells are often of the greatest concern, as they may persist and be propagated to offspring. Regardless of the cell type, there are several different categories of mutations including: missense, nonsense, insertion, deletion, duplication, and frame-shift mutations.  These mutations can present with different downstream effects which are not predictable but can potentially initiate a path to carcinogenesis.

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.   More help

The biological rationale for linking direct deposition of energy by ionizing radiation to mutation induction is strong. The structural and functional relationships in this KER contribute sufficiently to the overall biological plausibility.

There are numerous studies that demonstrate, using various model systems, an increase in mutation frequency in response to radiation exposure (Russell et al., 1957; Winegar et al., 1994; Gossen et al., 1995; Suzuki & Hei 1996; Albertini et al., 1997; Dubrova et al., 1998; Kraemer et al., 2000; Dubrova, Plumb, et al., 2000; Canova et al., 2002; Dubrova et al., 2002; Dubrova & Plumb, 2002; Masumura et al., 2002; Somers et al., 2004; Burr et al., 2007; Ali et al., 2012; Bolsunovsky et al., 2016; Mcmahon et al., 2016; Matuo et al., 2018; Nagashima et al., 2018; Wu et al., 1999; Hei et al., 1997; Nagasawa and Little, 1999; Barnhart and Cox, 1979; Thacker at al., 1982; Zhu et al., 1982; Metting et al., 1992; Schwartz et al., 1991; Chen et al., 1984; Albertini et al., 1997). The process of mutation induction by radiation is initiated when cells are exposed to ionizing radiation. These high-energy waves or particles interact with the genetic material in the nucleus, damaging the DNA and triggering a cascade of signalling events and activities aimed at repairing the damage. It has been shown that various dose rates of radiation exposure can lead to distinct types of damage. High dose-rate radiation has been observed to generate a higher number of DNA strand breaks, resulting in a variety of mutations, including small base changes and deletions. Moreover, the likelihood of insufficient repair is elevated, contributing to an overall increase in mutation frequency. In contrast, low dose-rate radiation has been found to have a significantly lower  mutation frequency, particularly in deletions and rearrangements (Brooks et al., 2016; Sankaranarayanan & Nikjoo, 2015). Of note, radiation is not likely to impact only one gene; more often than not, the random nature of energy deposition by radiation results in mutations to many genes and genomic sites clustered in the same area (Sankaranarayanan & Nikjoo, 2015; Adewoye et al., 2015). Many of the radiation-induced mutations have been documented as deletions (Gossen et al., 1995; Behjati et al., 2016), often of differing sizes in a number of different genes (Sankaranarayanan & Nikjoo, 2015). The mechanism for radiation-induced mutations is thought to be similar to the process for spontaneously-occurring mutations, as the structure of radiation-induced mutations examined at expanded simple tandem repeat (ESTR) loci was not found to differ from the structure of spontaneous mutations (Dubrova, 2005). Moreover, exposure to radiation may produce specific mutational signatures. Two ionizing radiation-specific mutational signatures were found when 12 radiation-induced secondary tumours across 4 different tumour types underwent whole-genome sequencing and bioinformatics processing. In particular, these radiation-exposed tumours were significantly enriched in small deletions and balanced inversions. These results were validated when the same mutational signatures were observed in radiation-exposed but not radiation-naïve prostate tumours from a previously-published dataset (Behjati et al., 2016). Similarly, another study examining mutations present in radiation-induced tumours of Nf1 heterozygous and wild-type mice revealed three distinctive mutational signatures. Interestingly, these signatures were found in all of the tumours regardless of its histology or of the animal’s genotype. Moreover, these signatures were still present after removal of the 33 most mutated samples from the analysis, after analysis of only the non-synonymous substitutions, and after analysis of only the synonymous substitutions (though the third mutational signature could not be extracted in this last analysis group) (Sherborne et al. 2015). There were also common cellular pathways that were found to be frequently mutated in the tumours of these mice. In sarcomas from mice of both genetic backgrounds (Nf1 heterozygous and wild-type), the top two pathways harbouring mutations were those influencing cellular assembly and organization, and those involved in cellular function and maintenance. Additionally, Ras pathways were commonly mutated in tumours from both genetic backgrounds. Specific to wild-type sarcomas, mutations were also found in cell cycle and cell signalling pathways (Sherborne et al., 2015). Supporting the finding that different genetic backgrounds in mice do not affect mutational signatures in tumours (Sherborne et al., 2015), there also does not appear to be strain-specific differences in ESTR mutational frequencies in response to radiation. One study examined five different strains of male mice that were irradiated and mated to unirradiated females at least 4 weeks post-irradiation. Although there was a difference in doubling doses between strains, the ESTR mutations themselves were not significantly different. Furthermore, there were no significant differences found between strains in terms of germline mutation induction (Dubrova, 2005).

Germline mutations have been further interrogated in studies examining the effects of radiation exposure on germ cells. There is evidence from mouse studies suggesting that the germ cells of radiation-exposed males have elevated ESTR mutations and that the offspring of these irradiated males inherit more ESTR mutations as a result of the germline mutations (Dubrova et al., 1998; Dubrova, Bersimbaev, et al., 2000; Dubrova & Plumb, 2002; Somers et al., 2004; Barber et al., 2009; Ali et al., 2012; T.E. Wilson et al., 2015). This was reviewed by Somers et al. (2006). Interestingly, in utero irradiation of embryos at day 12 resulted in increased ESTR mutations across several tissue types in males and females; however, only the offspring of the irradiated males showed an elevated ESTR mutation rate (Barber et al., 2009). On a genome-wide scale, the offspring of irradiated males were found to have significantly more clustered single nucleotide variants (SNVs) and insertion/deletion events compared to offspring from unirradiated fathers (Adewoye et al., 2015).

Human studies have also shown correlations in radiation exposure and increased germline mutations. This relationship was assessed in families exposed accidently to high doses of ionizing radiation after the Chernobyl accident in Ukraine, and in families living in close proximity to the Semipalatinsk nuclear test site in Kazakhstan. In both cases, germline mutations were evaluated using eight hypervariable minisatellite probes. In the Chernobyl study, the paternal mutation rate in the exposed group was significantly increased by 1.6-fold relative to an unexposed control group; there was, however, no significant difference in the maternal germline mutation rates between the exposed group and the unexposed control group (Dubrova et al., 2002C). In the Semipalatinsk study, analysis of families living in the affected region over three generations found that germline mutations in the first and second generation were significantly increased relative to unexposed families living in a low-radiation area. Overall, the germline mutation rate in the families exposed to radiation from this test site was doubled (Dubrova, Bersimbaev, et al., 2000).

Uncertainties and Inconsistencies
Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

Uncertainties and inconsistencies in this KER are as follows:

  1. In a review paper describing the role ionizing radiation plays in elevating mutation frequency in the germline and therefore genetic risk, Sankaranarayanan & Nikjoo (2015) stated that most radiation-induced mutations tended to be deletions. In contrast, an examination of ESTR loci mutations in offspring and their irradiated fathers found that the ESTR mutations tended to be gains more often than losses (Dubrova ,2005). This may, however, highlight a characteristic specific to ESTR mutations rather than mutations in general.
  2. In a study examining the long-term of effects of in utero radiation exposure, males irradiated at embryonic day 12 showed significant increases in both somatic and germline ESTR mutations as adults, and produced offspring with significantly elevated ESTR mutations in their sperm (Barber et al., 2009). In contrast, male mice exposed to radiation during their neonatal days (6 - 8 days old) or pubertal stage (18 - 25 days) did not have increased mutations in adult spermatozoa, as mutant frequencies that were present in spermatogenesis stages immediately after radiation returned to normal levels later in the spermatogenesis process (Xu et al., 2008).
  3. Factors such as dose, dose-rate, tissue type and radiation quality can influence mutation rate induction (Hooker et al., 2004; Rydberg et al., 2005; Day et al., 2007; Okudaira et al., 2010; Brooks et al., 2016). 
  4. Difference in measurements of mutational frequency can affect the interpretation of the data.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help

There are several factors that have been documented to affect the relationship between direct deposition of energy and increased mutation frequency. The sex, age, and use of adaptive dosing have been demonstrated to affect the radiation-induced mutations present in offspring. In contrast to male mice, female mice that were irradiated in utero (Barber et al., 2009) or as adults (Ali et al., 2012)(Ali, 2012) did not produce offspring with increased ESTR mutations. This suggests that radiation-induced mutations are only heritable through the paternal line. As such, the age of the father may affect the mutant frequency in the offspring, as increased mutations were present in spermatogenic cells of older male mice relative to younger males both at baseline levels and post-irradiation (Xu et al., 2012). Lastly, the use of ‘adaptive’ radiation dosing, or giving a very small dose 24 hours prior to the full radiation dose, may also affect offspring’s mutational frequency. In male mice who received adaptive dosing relative to males who received only the full radiation dose, there were significant decreases in germline mutation frequencies and in the rate of paternal mutations in their offspring (Somers et al., 2004)


The radiation-mutation relationship may also be impacted by the genetics of the organism, as the genotype appears to play an important role in determining how the biological system responds to radiation. In yeast with inactivated rad50 or rad52, the radiation-induced mutation frequency was significantly increased relative to wild-type yeast (Matuo et al., 2018). Msh2 knock-out mice (Burr et al., 2007) and medaka fish (Otozai et al., 2014) both had significantly increased baseline mutation frequencies relative to wild-type animals. Irradiation, however, did not change this mutation rate from baseline for these Msh2 knock-out animals (Burr et al., 2007; Otozai et al., 2014). Similarly, BRCA2 knock-out embryos had significantly elevated baseline mutation rates relative to wild-type littermates; however, in utero radiation was found to increase the mutation rate of all genotypes. Thus irradiated BRCA2 knock-out embryos also had a significantly increased mutation frequency relative to wild-type embryos by approximately three-fold (Tutt et al., 2002). Finally, baseline mutation levels in p53 knock-out medaka fish did not differ from wild-types; however, p53 knock-out fish exposed to radiation were found to have a 24-fold increase in mutation frequency relative to unirradiated p53 knock-out fish (Otozai et al., 2014). Construction of a dose response curve found the following mutation rates for wild-type, Msh2 knock-out, p53 knockout, and Msh2/p53 double knock-out medaka fish, respectively: 1.1x10-4 mutations/allele/Gy, 1.1x10-4 mutations/allele/Gy, 4.3x10-4 mutations/allele/Gy, and 5.6x10-4 mutations/allele/Gy (Otozai et al., 2014).


Finally, factors such as dose, dose-rate, tissue type and radiation quality can influence mutation rate induction (Suzuki & Hei ,1996; Hooker et al., 2004; Rydberg et al., 2005; Day et al., 2007; Okudaira et al., 2010; Brooks et al., 2016)

Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help

There is evidence of a positive response-response relationship between the radiation dose and the frequency of mutations (Russell et al., 1957; Suzuki & Hei, 1996; Albertini et al., 1997; Kraemer et al., 2000; Canova et al., 2002; Dubrova & Plumb, 2002; J.W. Wilson et al., 2015; Bolsunovsky et al., 2016; Mcmahon et al., 2016; Nagashima et al., 2018) . Most studies found that the response-response relationship was linear (Russell et al., 1957; Albertini et al., 1997; Canova et al., 2002; Dubrova et al., 2002; Nagashima et al., 2018). There were however, two exceptions. In a study using normal human bronchial epithelial cells irradiated with 1 - 6 Gy of gamma-rays, the relationship between the number of induced HPRT mutants and the radiation dose was described as non-linear (Suzuki & Hei, 1996) Similarly, in a study examining HPRT mutations in isolated peripheral blood T-lymphocytes irradiated with low LET gamma-rays, the slope of the line from 0 - 2 Gy differed from the slope at the 2 - 4 Gy interval; thus this was described as two different linear relationships or an overall linear-quadratic relationship (Albertini et al., 1997). In a study with V79 Chinese hamster cells, a curvilinear response was also seen as a result of x-ray response while a linear response was seen for Am-241 alpha-particle exposure (Schmidt and Keifer, 1998).

Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help

The time scale relationship between radiation exposure and the frequency of mutations is not well defined. Most studies look for manifestation of mutations days or weeks after irradiation, making it particularly difficult to pinpoint exactly when the mutations first occur. Analysis of various organs from mice after in vivo radiation found that mutations were present at 2 days (Winegar et al., 1994; Masumura et al., 2002) and 3 days (Gossen et al., 1995)(Gossen, 1995) post-exposure. Mutations were still present at 7 days and 14 days (Winegar et al., 1994), and 10 days and 21 days (Gossen, 1995) following irradiation. One study documented a doubling in the number of mutations from 7 to 14 days (Winegar et al., 1994) while the other reported a two-fold decrease from 3 to 21 days  (Gossen et al., 1995).


An attempt to better define this time scale relationship was made in a study using Salmonella typhimurium bacteria. This study was designed to determine how mutation frequency was affected by constant cesium-137 gamma-ray radiation exposure at defined dose rates of 67.8 uGy/hour, 3.2 uGy/hour, and 0.6 uGy/hour; these mutation frequencies were compared to a control group exposed to background radiation levels (0.09 uGy/hour). Mutation frequencies were evaluated after 24, 48, 72 and 96 hours of constant exposure. At 24 hours, the 67.8 uGy/hour, 3.2 uGy/hour and 0.6 uGy/hour mutant frequencies were significantly higher than background exposure controls. Interestingly, however, these levels were decreased at 48 hours and continued to decline gradually towards control frequencies over time. This decline was proposed to be due to an elimination of the highly mutated cells, leaving behind an increasing number of cells that had adapted to the radiation and were thus more equipped for survival (Bolsunovsky et al., 2016). Other studies are required to build a more complete understanding of this timeline.

Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Not identified.

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

The domain of applicability applies to single-celled organisms such as bacteria and yeast, eukaryotic cells, and multi-cellular organisms such as fish, mice and humans.


List of the literature that was cited for this KER description. More help

Adewoye, A.B. et al. (2015),  "Mutation induction in the mammalian germline.", Nature Comm. 6:(6684), doi:10.1038/ncomms7684.

Albertini, R.J. et al. (1997), "Radiation Quality Affects the Efficiency of Induction and the Molecular Spectrum of HPRT Mutations in Human T Cells", Radiat Res. 148(5 Suppl):S76-86

Ali, A.H.E., R.C. Barber & Y.E. Dubrova (2012), "The effects of maternal irradiation during adulthood on mutation induction and transgenerational instability in mice.", Mutat Res. 732:21–25. doi:10.1016/j.mrfmmm.2012.01.003.

Barber, R.C. et al. (2009), "The effects of in utero irradiation on mutation induction and transgenerational instability in mice.", Mutat Res. 664:6–12. doi:10.1016/j.mrfmmm.2009.01.011.

Barnhart BJ and SH Cox. 1979. Mutagenicity and Cytotoxicity of 4.4-MeV alpha-particles Emitted by Plutonium-238. Radiat Res. 80:542-548.

Behjati, S. et al. (2016), "Mutational signatures of ionzing radiation in second malignancies". 7:12605, doi:10.1038/ncomms12605.

Bolsunovsky, A. et al. (2016), "Low doses of gamma-radiation induce SOS response and increase mutation frequency in Escherichia coli and Salmonella typhimurium cells.", Ecotoxicol Environ Saf. 134:233–238. doi:10.1016/j.ecoenv.2016.09.009.

Brooks, A.L., D.G. Hoel & R.J. Preston (2016), "The role of dose rate in radiation cancer risk: evaluating the effect of dose rate at the molecular, cellular and tissue levels using key events in critical pathways following exposure to low LET radiation.", Int. J. Radiat. Biol. 92(8):405–426. doi:10.1080/09553002.2016.1186301.

Burr, K.L. et al. (2007), "The effects of MSH2 deficiency on spontaneous and radiation-induced mutation rates in the mouse germline.", 617(1-2):147–151. doi:10.1016/j.mrfmmm.2007.01.010.

Canova, S. et al. (2002), "Minisatellite and HPRT Mutations in V79 And Human Cells Irradiated with Gamma Rays.", Radiat Prot. Dosimetry, 99:207–209. doi: 10.1093/oxfordjournals.rpd.a006763

Chen DJ, Striniste GF, Tokita N. 1984. The Genotoxicity of Alpha Particles in Human Embryonic Skin Fibroblasts. Radiat Res. 100:321-327.

Day, T.K. et al. (2007), "Adaptive Response for Chromosomal Inversions in pKZ1 Mouse Prostate Induced by Low Doses of X Radiation Delivered after a High Dose.", Radiat Res. 167(6):682–692. doi:10.1667/rr0764.1.

Dubrova, Y.E. (2005), "Radiation-Induced Mutation at Tandem Repeat DNA Loci in the Mouse Germline: Spectra and Doubling Doses", Radiat Res., 163(2):200-207 doi: 10.1667/RR3296.

Dubrova, Y.E. et al. (2002), "Nuclear Weapons Tests and Human Germline Mutation Rate.", Science, 295(5557):1037, doi:10.1126/science.1068102.

Dubrova, Y.E. et al. (2002), "Elevated Minisatellite Mutation Rate in the Post-Chernobyl Families from Ukraine.", Am. J. Hum. Genet. 74(4):801-809, doi: 10.1086/342729.

Dubrova, Y.E. et al. (2000), "Induction of minisatellite mutations in the mouse germline by low-dose chronic exposure to Y -radiation and fission neutrons.", Mutat Res. 453(1):17–24. doi: 10.1016/s0027-5107(00)00068-3.

Dubrova. Y.E. et al. (1998), "Stage specificity, dose response, and doubling dose for mouse minisatellite germ-line mutation induced by acute radiation.", Proc. natl. Acad. Sci. 95(11):6251–6255. doi: 10.1073/pnas.95.11.6251.

Dubrova, Y.E. & M.A. Plumb (2002), "Ionising radiation and mutation induction at mouse minisatellite loci The story of the two generations.", Mutat Res., 499(2):143–150. doi: 10.1016/s0027-5107(01)00284-6.

Gossen, J.A. et al. (1995), "Spontaneous and X-ray-induced deletion mutations in a LacZ plasmid-based transgenic mouse model.", Mutat Res., 331(1):89–97.

Hada, M. & A.G. Georgakilas (2008), "Formation of Clustered DNA Damage after High-LET Irradiation: A Review.", J. Radiat. Res., 49(3):203–210. doi:10.1269/jrr.07123.

Hei TK, Wu LJ, Liu SX, Vannais D, Waldren CA, Randers-Pehrson G. 1997. Mutagenic effects of a single and an exact number of alpha particles in mammalian cells. Proc Natl Acad Sci USA. 94:1765-3770.

Hooker, A.M. et al. (2004), "Cancer-associated genes can affect somatic intrachromosomal recombination early in carcinogenesis.", Mutat Res. - Fundam Mol Mech Mutagen. 550(1–2):1–10. doi:10.1016/j.mrfmmm.2004.01.003.

Valentin J. (2005), "Low-dose Extrapolation of Radiation-related Cancer Risk.", Ann. ICRP, 35(4):1-140

Jostes, R.F. (1996), "Genetic, cytogenetic, and carcinogenic effects of radon: a review.", Mutat. Res. / Rev. in Genet. Toxicol. 340(2-3):125–139. doi: 10.1016/s0165-1110(96)90044-5.

Kraemer, S.M. et al., (2000), Measuring the Spectrum of Mutation Induced by Nitrogen Ions and Protons in the Human-Hamster Hybrid Cell Line ALC., Rad Res., 153:743-751. doi: 10.1667/0033-7587(2000)153[0743:mtsomi];2.

Lorat. Y. et al. (2015), "Nanoscale analysis of clustered DNA damage after high-LET irradiation by quantitative electron microscopy – The heavy burden to repair.", DNA Repair (Amst). 28:93–106. doi:10.1016/j.dnarep.2015.01.007.

Masumura, K. et al. (2002), "Heavy-Ion-Induced Mutations in the gpt Delta Transgenic Mouse : Comparison of Mutation Spectra Induced by Heavy-Ion , X-Ray , and - Y-Ray Radiation.", Envrion. Mol. Mutagen, 40(3):207–215. doi:10.1002/em.10108.

Matuo, Y. et al. (2018), "Biological effects of carbon ion beams with various LETs on budding yeast Saccharomyces cerevisiae.", Mutat Res Fund Mol Mech Mutagen. 810(November 2017):45–51. doi:10.1016/j.mrfmmm.2017.10.003.

McMahon, S.J. et al. (2016), "Mechanistic Modelling of DNA Repair and Cellular Survival Following Radiation-Induced DNA Damage.", Nat. Publ. Gr.(April):1–14. doi:10.1038/srep33290.

Metting NF, Palayoor ST, Macklis RM, Atcher RW, Liber HL, Little JB. 1992. Induction of Mutations by Bismuth-212 Alpha Particles at Two Genetic Loci in Human B-Lymphoblasts. Radiat Res. 132:339-345.

Nagasawa H, Robertson J, Little JB. 1990b. Induction of chromosomal aberrations and sister chromatid exchanges by alpha particles in density-inhibited cultures of mouse 10T1/2 and 3T3 cells. Int J Radiat Biol. 57(1):35-44.

Nagashima, H. et al. (2018), "Induction of somatic mutations by low-dose X-rays : the challenge in recognizing radiation-induced events.", J. Radiat. Res., 59(October 2017):11–17. doi:10.1093/jrr/rrx053.

Nikitaki, Z. et al. (2016), "Measurement of complex DNA damage induction and repair in human cellular systems after exposure to ionizing radiations of varying linear energy transfer ( LET ).", Free Radic Res., 5762. doi:10.1080/10715762.2016.1232484.

Okayasu, R. (2012), "Heavy ions — a mini review.", 1000:991–1000. doi:10.1002/ijc.26445.

Okudaira, N. et al. (2010), "Radiation Dose-Rate Effect on Mutation Induction in Spleen and Liver of gpt delta Mice.", Radiat Res. 173(2):138–147. doi:10.1667/rr1932.1.

Otozai, S. et al. (2014), "p53 -Dependent suppression of genome instability in germ cells.", Mutat. Res. 760:24–32. doi: 10.1016/j.mrfmmm.2013.12.004.

Robertson, A. et al. (2013), "The Cellular and Molecular Carcinogenic Effects of Radon Exposure: A Review.", Int. J. Mol. Sci., doi: 10.3390/ijms140714024.

Russell, W.L. et al. (1957), "Radiation Dose Rate and Mutation Frequency.", Science, 128(3338):1546-50. doi: 10.1126/science.128.3338.1546.

Rydberg, B. et al. (2005), "Dose-Dependent Misrejoining of Radiation-Induced DNA Double-Strand Breaks in Human Fibroblasts: Experimental and Theoretical Study for High- and Low-LET Radiation.", Radiat. Res. 163(5):526–534. doi:10.1667/RR3346.

Sankaranarayanan, K. & H. Nikjoo (2015), "Genome-based, mechanism-driven computational modeling of risks of ionizing radiation: The next frontier in genetic risk estimation?", Mutat Res. 764:1–15. doi:10.1016/j.mrrev.2014.12.003.

Schmidt, P. and J. Kiefer, (1998), Deletion-pattern analysis of a-particle and x-ray induced mutations at the HPRT locus of V79 Chinese hamster cells., Mutat Res. 412:149-161. doi: 10.1016/s0027-5107(98)00159-6.

Schwartz JL, Ashman CR, Atcher RW, Sedita BA, Shadley JD, Tang J, Whitlock JL, Rotmensch J. 1991. Differential locus sensitivity to mutation induction by ionizing radiations of different LETs in Chinese hamster ovary K1 cells. Carcinog. 12(9):1721-1726.

Sherborne, A.L. et al. (2015), "Mutational Analysis of Ionizing Radiation Induced Article Mutational Analysis of Ionizing Radiation Induced Neoplasms.", Cell Reports. 12(11):1915–1926. doi:10.1016/j.celrep.2015.08.015.

Somers, C.M. (2006), "Expanded simple tandem repeat (ESTR) mutation induction in the male germline: Lessons learned from lab mice.", Mutat Res., 598(1-2):35-49 doi:10.1016/j.mrfmmm.2006.01.018.

Somers, C.M. et al. (2004), "Gamma radiation-induced heritable mutations at repetitive DNA loci in out-bred mice.", Mutat. Res., 568(1):69–78. doi:10.1016/j.mrfmmm.2004.06.047.

Suzuki, K. & T.K. Hei (1996), "Mutation induction in gamma-irradiated primary human bronchial epithelial cells and molecular analysis of the HPRT- mutants.", Mutat Res., 349(1):33-41. doi: 10.1016/0027-5107(95)00123-9.

Thacker J, Stretch A, Goodhead DT. 1982. The Mutagenicity of Alpha-Particle from Plutonium-238. Radiat Res. 92:343-352.

Tutt, A.N.J. et al. (2002), "Disruption of Brca2 increases the spontaneous mutation rate in vivo : synergism with ionizing radiation.", EMBO Rep., 3(3):255–260. doi: 10.1093/embo-reports/kvf037.

Wilson, J.W. et al. (2015), "The effects of extremely low frequency magnetic fields on mutation induction in mice.", Mutat Res - Fundam Mol Mech Mutagen. 773:22–26. doi:10.1016/j.mrfmmm.2015.01.014.

Wilson, T.E. et al. (2015), "Large transcription units unify copy number variants and common fragile sites arising under replication stress.", Genome Res. 25(2):189–200. doi:10.1101/gr.177121.114.

Winegar, R.A. et al. (1994), "Radiation-induced point mutations, deletions and micronuclei in lacI transgenic mice.", Mutat Res., 307(2):479–487. doi:  10.1016/0027-5107(94)90258-5.

Wu LJ, Randers-Pehrson G, Xu A, Waldren CA, Geard CR, Yu ZL, Hei TK. 1999. Targeted cytoplasmic irradiation with alpha particles induces mutations in mammalian cells. Proc Natl Acad Sci USA. 96:4959-4964.

Xu, G. et al. (2008), "Recovery of a low mutant frequency after ionizing radiation-induced mutagenesis during spermatogenesis.", Mutat Res., 654(2):150–157. doi:10.1016/j.mrgentox.2008.05.012.

Xu, G. et al. (2012), "Ionizing radiation-induced mutant frequencies increase transiently in male germ cells of older mice.", Mutat Res., 744(2):135–139. doi:10.1016/j.mrgentox.2012.01.003.

Zhu LX, Waldren CA, Vannais D, Hei TK. 1996. Cellular and Molecular Analysis of Mutagenesis Induced by Charged Particles of Defined Linear Energy Transfer. Radiat Res. 145:251-259.