Use of Genetic Markers as a Screening Tool for Ecological Risk Assessment at the Idaho National Engineering and Environmental Laboratory: Microsatellite Mutation Rate of Burrowing Mammals

The purpose of this research was to explore the utility of molecular genetic techniques as screening tools for evaluating the risk to natural populations from contaminant exposure. These tools can be used to help evaluate the need for site remediation. If remediation is implemented, genetic characterization of populations can provide insight on the effectiveness of the remediation through long-term monitoring.

This was a three-year study to determine if radiological contamination affects the genome of deer mice (Peromyscus maniculatus). Radiological and genetic analysis were performed on deer mice collected outside the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) sites of the stationary low-power reactor number 1 (SL-1) and the Radioactive Waste Management Complex (RWMC), and two control sites (Burn and Atomic City).

Radiological and hazardous wastes have been disposed of at the INEEL since 1952. Escape of radionuclides and hazardous constituents from uncontained wastes, deterioration of waste containers, and waste disposal practices have resulted in contamination of the subsurface soils at the INEEL's Subsurface Disposal Area (SDA) and at other facilities. To assess the risks to human and environmental health, the potential impacts of contaminant exposure on identified receptors must be determined.

Burrowing and excavation of the soil by small mammals, including deer mice, has been shown to be responsible for some radionuclide transport through the SDA environment; however, the genomic effects of exposure to contaminants at the INEEL was not known. Research was needed to develop new techniques to determine the effects of that exposure to the genome of individuals, so that environmental and remedial actions can be properly implemented. The objectives of this research were to:

  • Perform comparative analysis of mother/offspring genotypes across the study areas using allelic data compiled from two consecutive field seasons (14 genetic markers: 147 females; 529 embryos; and 9464 Polymerase Chain Reactions).
  • Identify mutant alleles in all samples and perform statistical analysis.
  • Perform microsatellite genetic analysis of the four study area populations to determine population structure using a variety of genetic software packages.
  • Analyze radiological data obtained from all the females collected during fiscal years 2001 and 2002 and perform statistical analysis.


Laboratory Experimental Procedures - Fourteen genetic markers were used to perform microsatellite genetic analysis. Data were organized by population and families; allelic maternal segregation of the offspring was determined, paternal alleles inferred, and mutations identified. Only mutations of alleles segregated from the mother were used for this analysis. Not all the families provided useful data and some had to be removed for the genetic analysis (36 percent of the families were removed).

Mutation Rate Analysis Results - The ratio of microsatellite mutant alleles versus the non-mutant alleles was used as a direct assessment of mutation using parent/offspring comparison of allele differences. Allele scoring was performed with 14 microsatellite markers for females and offspring from the four study areas. The proportion of mutant alleles from each population was pair-wise compared between populations and tested for significant differences using the Fisher's exact test. The statistical analysis suggests that there is no significant difference when comparing the two contaminated sites (RWMC and SL-1) with the two control sites (Burn and Atomic City).

Population Genetic Structure Analysis - Four different approaches were used to test for population genetic structure:

  • The allele frequency differences among populations were tested using the Fisher's exact test, where an unbiased estimate of the p-value of the probability test is obtained. The null hypothesis (Ho) "the allelic distribution is uniform across populations" was tested for each locus on a contingency table.
  • The differences in genotype distribution across the populations were based on estimates of Wright's F-statistics. The null hypothesis, Fst = 0 "the genotypic distribution is uniform across
    populations" was tested for all loci using a chi-square goodness-of-fit test.
  • The estimate of Rhost statistics is a measure analogous to Fst but incorporates allele size estimates and assumes a step-wise mutation model.
  • Finally, an assignment test was performed using GeneClass. This test uses a Bayesian approach to detect immigrants by using multilocus genotypes.

The null hypothesis was rejected in the first two methods; that is, the differences in allele frequency distribution and the genotype distribution differences between populations are statistically significant. The third method indicates that some level of gene flow occurs between populations but not enough that the distributions of alleles or genotypes between them are homogenized. The assignment test also supports population genetic structure because 98.61 percent of the individuals were correctly assigned to their population of origin.

Radiological Analysis - Samples from 80 females were used for this analysis: 43 from Atomic City; 21 from SL-1; and 16 from RWMC (the Burn site was excluded from the analysis due to small available sample size). Female carcasses were processed and analyzed for presence of radiological contaminants. None of the females showed exposure at levels higher than background. Statistical analysis of the radiological data indicates that the differences between the populations are not significant. That is, female mice collected from RWMC and SL-1 had similar levels of radiological (background) contamination compared to the Atomic City control site.


The populations have different allelic frequency composition, and even though there is evidence that some level of gene flow occurs, and that they are not isolated completely, the migration rate is not strong enough to create a panmictic population (a population with no genetic structure). This study indicates that the four populations are distinctive when comparing the two control sites with SL-1 and RWMC population.

It is assumed that natural populations share the same level of mutation rate, because this is an evolutionary force that is stochastic. This means that it is not affected by any of the evolutionary selective forces, and it occurs at a very low frequency. If there are no other contributing factors such as anthropogenic activities, it is predicted that in all of the studied populations the mutation rates should be similar. This study shows that there is no difference in the rate of mutation in populations exposed to anthropogenic activities in comparison with populations that have had little or no exposure. This suggests that no external forces (outside from evolutionary forces) are acting on this population.

The population genetic analysis and the mutation rate data support each other. The population genetic analysis suggests that there is a geographical component that plays a role in population differentiation. The radiological analysis indicated that the animals collected at the RWMC site have the same level of background exposure as the ones from the other three sites. Based on this study, we cannot conclude that exposure to radiological contaminants is an issue of concern for mice collected at RWMC or SL-1. One observation that is important to make, however, is that samples were not allowed to be collected from areas of known soil contamination. Therefore, the question of whether microsatellites are a good tool for identifying mutation differences caused by exposure still needs to be tested.

Further research should be pursued using this species as a biological indicator for environmental monitoring of contaminants, as well as long-term stewardship and ecotoxicological studies.

This research is part of a long-term plan for building a capability at INEEL in the use of genetic markers to address environmental issues. Once the technology is established, numerous applications using other species as environmental monitoring indicators can be explored. This information will help researchers focus resources and efforts on environmental monitoring at sites where there is a high probability of adverse biological impact caused by the presence of contaminants.

Investigators and Affiliations

Angela Stormberg, Principal Scientist, Idaho National Engineering and Environmental Laboratory, Idaho Falls, ID

Joseph Cook, Department of Biological Sciences, Idaho State University, Pocatello, ID

Funding Sources
Laboratory Directed Research and Development (LDRD)


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