API

Event: 336

Key Event Title

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Increase, Heritable mutations in offspring

Short name

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Increase, Heritable mutations in offspring

Key Event Component

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Process Object Action
mutation deoxyribonucleic acid increased

Key Event Overview


AOPs Including This Key Event

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Stressors

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Level of Biological Organization

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Biological Organization
Individual



Taxonomic Applicability

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Term Scientific Term Evidence Link
Mus musculus Mus musculus Strong NCBI
medaka Oryzias latipes Moderate NCBI
Drosophila melanogaster Drosophila melanogaster Moderate NCBI

Life Stages

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Sex Applicability

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How This Key Event Works

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Mutations occurring in the offspring are the adverse effect. These mutations may have many eventual consequences including embryonic or fetal death, or genetic disease in the offspring. If mutations are viable, the specific sites and sequence changes of the mutations will govern the phenotypic outcome of the inherited mutation.

DETAILS: Evolutionarily advantageous or beneficial mutations are expected to be rare. Thus, the majority of inherited mutations will be neutral, with a somewhat smaller proportion expected to be harmful. For example, Keightley (2012) used phylogenetic analysis to estimate that approximately 70 new mutations occur per generation, 2.2 of which, on average, are deleterious. These deleterious mutations affect the fitness of the organism (decreasing probability of reproducing) and thus impact the population. Alternatively, one must also consider pathogenic mutations, including those that do not affect fitness (e.g., diseases that may occur later in life and do not affect ability to reproduce). It is currently not possible to fully measure the consequences of pathogenic mutations, because we lack appropriate methods to measure their penetrance (e.g., mutations with low odds ratios, diverse phenotypes, or that contribute to multigenic disorders, etc.). Thus, we currently do not have precise mechanisms to evaluate the full impacts of de novo mutations. However, increasing use of whole genome sequencing is shedding light on the rate, spectrum, and consequences of de novo mutations. Evidence is accumulating on the major role of de novo mutations in rare Mendelian and genetically heterogeneous diseases (e.g., reviewed in Veltman and Brunner, 2012; Geschwind and Flint, 2015; Walsch et al. 2010). The rate and spectrum of human mutations is reviewed in Campbell and Eichler (2013), and potential consequences of mutations explored in Shendure and Akey (2015). Estimates indicate approximately 100 loss-of-function variants in a human genome, with as many as 20 exhibiting complete loss of gene function (McLaughlin et al. 2010). As an example, based on full genome sequencing data, paternal de novo sequence mutations are expected to account for an equal amount of the genetic burden of disease in ageing fathers as maternal aneuploidies due to ageing (Hurles, 2012). It is important to note that although mutations in coding regions are expected to have large effects on fitness, the absolute number of mutations in non-coding sequence that is under selection is actually greater than coding sequence (Green and Ewing, 2013). In general, it is widely accepted that de novo mutations contribute to the overall population genetic disease burden. The application of whole genome sequencing in the clinic is providing new knowledge on the unprecedented extent to which de novo mutations are contributing to a whole host of idiopathic human genetic disorders (e.g., Lupski et al., 2011; Ku et al., 2013; Gilissen et al., 2014).


How It Is Measured or Detected

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A heritable mutation is measured as a mutation occurring in the offspring that is not present in the parents and that is present in every cell type (the latter is not typically measured). Heritable mutations were previously measured using the Mouse Specific Locus Test (SLT) and variations on this assay (in rodents, fish and Drosophila). The Oak Ridge National Laboratory's SLT test, established by William and Lianne Russell, was the gold standard for heritable mutation screening for several decades. Transmission of mutations from exposed males to their offspring can also be measured by analysis of tandem repeat mutations, an accepted though not widely used method. No OECD guideline exists for either assay.


Mouse SLT or variations of this assay: The SLT and dominant cataract methods are no longer used today because they require too many rodents, but there is a fairly large database from the application of these methods. The SLT is based on the use of seven dominant visible trait markers in mice (Davis and Justice, 1998; Russell et al., 1979). Male mice are exposed to the mutagen and mated at varying times post-exposure to evaluate effects on different stages of spermatogenesis. Males are mated with females carrying recessive alleles at the seven loci screened in the assay. Functional mutations at the dominant (male) locus results in expression of the recessive phenotype in the offspring. These phenotypes include changes in coat colour, skeletal malformations, and other traits. Variations on this assay include looking at other visible traits including 34 common skeletal malformations and dominant cataracts. Additional variations include protein electrophoresis to explore protein changes (e.g., Lewis et al., 1991).

Tandem repeat mutation: Tandem repeat mutations can be measured in offspring using a similar approach. Male mice are exposed to the mutagen and mated various times post-exposure to non-exposed females. DNA fingerprinting is used to measure changes in repeat length in offspring relative to their parents. This is currently the only assay that is able to measure the same mutational endpoint in sperm as in offspring, supporting that transmission of mutations from sperm to the offspring occurs. For methodologies please see Vilarino-Guell et al. (2003). A wide range of human genetic disorders are associated with de novo length change mutations in tandem repeat sequences (Mirkin, 2007). However, it should also be noted that the mutations are induced through indirect mechanisms that are likely to be associated with polymerase errors during cell cycle arrest, rather than direct lesions at the locus (Yauk et al., 2002)

Next generation sequencing: With the advent and improvement in sequencing technologies, it is anticipated that heritable mutations will be measured by directly sequencing the offspring of males exposed to mutagenic agents. Current approaches require the exposure of parental gametes to a mutagenic agent, followed by mating and collection of offspring. Whole genome sequencing is applied to compare the genome sequences of parents and offspring to identify and haplotype (i.e., determine the parental origin) of de novo mutations (identified as mutations occurring in offspring but not their parents). Studies such as these have demonstrated that increasing paternal age causes an increase in both single nucleotide variants and tandem repeats in the offspring (Kong et al., 2012; Sun et al., 2012). Proof of principle of the ability of application of genomics tools (array comparative genome hybridization and next generation sequencing) has been published for male mice exposed to radiation (Adewoye et al., 2015). The authors show that the frequency of de novo copy number variants (CNVs) and insertion/deletion events (indels) are significantly elevated in offspring of radiation-exposed fathers. Several papers have described how research in this field should proceed (Beal and Somers, 2011; Yauk et al., 2012; Yauk et al., 2015) and propose that this will be a paradigm-changing technology.

Note: The Dominant Lethal test (OECD TG 478) is used to measure the effects of DNA damage in sperm on dominant lethality in the offspring. The overwhelming majority of dominant lethal mutations are due to chromosomal effects rather than gene mutations (Marchetti et al., 2005). Thus, this TG is not generally suited to the measurement of inherited gene mutations.


Evidence Supporting Taxonomic Applicability

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Heritable mutations are the basis of evolution and occur in every species.


Regulatory Examples Using This Adverse Outcome

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Heritable mutations are an important regulatory endpoint for most agencies around the world (reviewed in Yauk et al. 2015). Strategies and guidelines for regulatory toxicology testing in various national regulatory jurisdictions, including requirements for germ cell mutation assays, have been described extensively by Cimino (2006), and have not changed significantly. While no jurisdiction requires germ cell testing per se in an initial test battery, many regulatory authorities can request germ cell tests for follow-up studies, e.g. in the U.S.A (U.S. EPA), Canada (Health Canada), the United Kingdom (Committee on Mutagenicity: COM), and Europe (Registration, Evaluation, Authorization and Restriction of Chemicals, i.e. REACH). For example, within the REACH strategy a substance that is genotoxic in somatic cells is evaluated from the literature to see if it is a potential germ cell mutagen based on bioavailability to the germ cells and appropriate in vivo data. If such an evaluation shows that the literature is insufficient to determine whether the agent is or is not a potential germ cell mutagen, then that agent can be tested in a suitable germ cell genotoxicity assay. Although germ cell testing is not specifically required under the Canadian Environmental Protection Act (CEPA) New Substances Notification Regulations, germ cell mutation tests are requested and evaluated when necessary. For new chemical assessments under CEPA from 1994 to 2012, a total of 19 chemicals have been evaluated for germ cell mutagenicity (12 for which the test was submitted, plus 7 for which the test was referenced on the MSDS); importantly, this is comparable to the number for which testing in rodent cancer assays was evaluated (i.e. total of 20; 17 for which the test was submitted, plus 3 for which test was referenced on the MSDS) (Personal Communication, New Substances Assessment and Control Bureau, Health Canada). These examples illustrates the regulatory importance of heritable mutations as an adverse outcome.

For pharmaceuticals, the ICH Technical Requirements for Registration of Pharmaceuticals for Human Use does not require germ cell tests and assumes that in vivo somatic tests and carcinogenicity data will provide sufficient predictivity/protection for germ cell effects (ICH, 2011)

The World Health Organization (WHO)/International Programme on Chemical Safety (IPCS) has developed a harmonized scheme for mutagenicity testing. In this document the relationship between somatic cell mutagenicity and germ cell risk is summarized in the following statement. “For substances that give positive results for mutagenic effects in somatic cells in vivo, their potential to affect germ cells should be considered. If there is toxicokinetic or toxicodynamic evidence that germ cells are actually exposed to the somatic mutagen or its bioactive metabolites, it is reasonable to assume that the substance may also pose a mutagenic hazard to germ cells and thus a risk to future generations.” (Eastmond et al. 2009).

The Global Harmonization Scheme (GHS; UN, 2013) is a germ cell mutation classification system developed by the United Nations that identifies them according to the categories noted in the Table below. To date over 60 countries have implemented this programme, and are in the process of integrating it into their relevant regulations. To date its implementation is focussed on product labelling legislation in the respective countries and regulatory jurisdictions.

Categorization of mutagens by GHS Category Description 1A Chemicals known to induce heritable mutations in germ cells of humans 1B Chemicals that should be regarded as if they induce heritable mutations in germ cells of humans 2 Chemicals that cause concern for induction of heritable mutations in germ cells of humans

Finally, we note that mouse data obtained with the specific locus test and other recessive mutation analyses played an important role in estimating radiation dose risk in the human population (BEIR VII 2006).


References

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Adewoye, A.B., S.J. Lindsay, Y.E. Dubrova and M.E. Hurles (2015), "The genome-wide effects of ionizing radiation on mutation induction in the mammalian germline", Nat Commun., 6: 6684.

Beal, M.A., T.C. Glenn and C.M. Somers (2011), "Whole genome sequencing for quantifying germline mutation frequency in humans and model species: cautious optimism", Mutation Research, 750(2): 96-106

Beal, M.A., A. Rowan-Carroll, C. Campbell, A. Williams, C.M. Somers, F. Marchetti and C.L. Yauk (2015), "Single-molecule PCR analysis of an unstable microsatellite for detecting mutations in sperm of mice exposed to chemical mutagens", Mutat. Res., 775: 26-32.

BEIR VII (2006), "Health Risks from Exposure to Low Levels of Ionizing Radiation", Academies NRCotN, editor. Washington, D.C.: National Academies Press.

Campbell, C.D. and E.E. Eichler (2013), "Properties and rates of germline mutations in humans", Trends Genet., 29(10): 575-584.

Cimino, M.C. (2006), "Comparative overview of current international strategies and guidelines for genetic toxicology testing for regulatory purposes", Environ. Mol. Mutagen., 47: 362–390.

Davis, A.P. and M.J. Justice (1998), "An Oak Ridge legacy: the specific locus test and its role in mouse mutagenesis", Genetics, 148(1): 7-12.

Geschwind, D.H. and J. Flint (2015), "Genetics and genomics of psychiatric disease", Science, 349(6255): 1489-1494

Green, P. and B. Ewing (2013), "Comment on “Evidence of abundant purifying selection in humans for recently acquired regulatory functions”", Science, 340(682) discussion 682.

Gilissen, C., J.Y. Hehir-Kwa, D.T. Thung, M. van de Vorst, B.W. van Bon, M.H. Willemsen, M. Kwint, I.M. Janssen, A. Hoischen, A. Schenck, R. Leach, R. Klein, R. Tearle, T. Bo, R. Pfundt, H.G. Yntema, B.B. de Vries, T. Kleefstra, H.G. Brunner, L.E. Vissers and J.A. Veltman (2014), "Genome sequencing identifies major causes of severe intellectual disability", Nature, 511(7509): 344-347.

Eastmond, D.A., A. Hartwig, D. Anderson, W.A. Anwar, M.C. Cimino, I. Dobrev, G.R. Douglas, T. Nohmi, D.H. Phillips and C. Vickers (2009), "Mutagenicity testing for chemical risk assessment: update of the WHO/IPCS Harmonized Scheme", Mutagenesis, 24(4): 341-349.

Kong, A., M.L. Frigge, G. Masson, S. Besenbacher, P. Sulem, G. Magnusson, S.A. Gudjonsson, A. Sigurdsson, A. Jonasdottir, W.S. Wong, G. Sigurdsson, G.B. Walters, S. Steinberg, H. Helgason, G. Thorleifsson, D.F. Gudbjartsson, A. Helgason, O.T. Magnusson, U. Thorsteinsdottir and K. Stefansson K. (2012), "Rate of de novo mutations and the importance of father's age to disease risk", Nature, 488(7412): 471-475.

Hurles, M. (2012), Older males beget more mutations", Nature Genetics, 44(11): 1174-1176.

International Conference on Harmonisation (ICH) (2011), "Guidance On Genotoxicity Testing And Data Interpretation For Pharmaceuticals Intended For Human Use S2(R1)" ICH Harmonised Tripartite Guideline, International Conference on Harmonization, Geneva, Switzerland.

Keightley, P.D. (2012), "Rates and Fitness Consequences of New Mutations in Humans", Genetics, 190(2): 295–304.

Ku, C. S., E.K. Tan and D.N. Cooper (2013), "From the periphery to centre stage: de novo single nucleotide variants play a key role in human genetic disease", J. Med. Genet., 50(4): 203-211.

Lewis, S.E., L.B. Barnett, B.M. Sadler and M.D. Shelby MD (1991), "ENU mutagenesis in the mouse electrophoretic specific-locus test, 1. Dose-response relationship of electrophoretically-detected mutations arising from mouse spermatogonia treated with ethylnitrosourea", Mutat Res., 249(2): 311-5.

Lupski, J.R., J.W. Belmont, E. Boerwinkle and R.A. Gibbs (2011), "Clan genomics and the complex architecture of human disease", Cell, 147(1): 32-43.

Marchetti, F. and A.J. Wyrobek (2005), "Mechanisms and consequences of paternally-transmitted chromosomal abnormalities", Birth Defects Res C Embryo Today, 75(2): 112-129.

Mirkin, S.M. (2007), "Expandable DNA repeats and human disease", Nature, 447(7147): 932-940.

Russell, W.L., E.M. Kelly, P.R. Hunsicker, J.W. Bangham, S.C. Maddux and E.L. Phipps (1979), "Specific-locus test shows ethylnitrosourea to be the most potent mutagen in the mouse" Proceedings of the National Academy of Sciences of the United States of America, 76(11): 5818-5819.

Russel, L.B. (2004), "Effects of male germ-cell stage on the frequency, nature and spectrum of induced specific-locus mutations in the mouse", Genetica, 122: 25-36.

Shendure, J. and J.M. Akey (2015), "The origins, determinants, and consequences of human mutations", Science, 349(6255): 1478-1483.

Sun, J.X., A. Helgason, G. Masson, S.S. Ebenesersdottir, H. Li, S. Mallick, S. Gnerre, N. Patterson, A. Kong, D. Reich and K. Stefansson (2012), "A direct characterization of human mutation based on microsatellites", Nat. Genet., 44(10): 1161-1165.

Veltman, J.A. and H.G. Brunner (2012), "De novo mutations in human genetic disease", Nat. Rev. Genet., 13(8): 565-575.

Vilarino-Guell, C., A.G. Smith and Y.E. Dubrova (2003), "Germline mutation induction at mouse repeat DNA loci by chemical mutagens" Mutation Research, 526(1-2): 63-73.

Walsh, T., M.K. Lee, S. Casadei, A.M. Thornton, S.M. Stray, C. Pennil, A.S. Nord, J.B. Mandell, E.M. Swisher and M.C. King (2010) "Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing", Proc Natl Acad Sci U S A., 107(28): 12629-12633.

United Nations (UN) (2013), "Globally Harmonized System of Classification and Labelling of Chemicals (GHS)", United Nations, New York, USA.

Yauk, C.L., Y.E. Dubrova, G.R. Grant and A.J. Jeffreys (2002), "A novel single molecule analysis of spontaneous and radiation-induced mutation at a mouse tandem repeat locus" Mutation Research. 500(1-2): 147-56.

Yauk, C.L., L.J. Argueso, S.S. Auerbach, P. Awadalla, S.R. Davis, D.M. Demarini, G.R. Douglas, Y.E. Dubrova, R.K. Elespuru, T.M. Glover, B.F. Hales , M.E. Hurles, C.B. Klein, J.R. Lupski, D.K. Manchester, F. Marchetti, A. Montpetit, J.J. Mulvihill, B. Robaire, W.A. Robbins, G.A. Rouleau, D.T. Shaughnessy, C.M. Somers, J.G. Taylor 6th, J. Trasler, M.D. Waters, T.E. Wilson, K.L. Witt and J.B. Bishop (2013), "Harnessing genomics to identify environmental determinants of heritable disease" Mutation Research, 752(1): 6-9.

Yauk, C.L., M.J. Aardema, J. van Benthem, J.B. Bishop, K.L. Dearfield, D.M. DeMarini, Y.E. Dubrova, M. Honma, J.R. Lupski, F. Marchetti, M.L. Meistrich, F. Pacchierotti, J. Stewart, M.D. Waters and G.R. Douglas (2015), "Approaches for Identifying Germ Cell Mutagens: Report of the 2013 IWGT Workshop on Germ Cell Assays", Mutat. Res. Genet. Toxicol. Environ. Mutagen. 783:36-54.