Evaluating alterations of genetic diversity in sunfish populations exposed to contaminants using RAPD assay

Aquatic Toxicology 43 (1998) 163 – 178

Evaluating alterations of genetic diversity in sunfish populations exposed to contaminants using RAPD assay Susan G. Nadig 1, K.L. Lee, S.M. Adams * En6ironmental Sciences Di6ision, Oak Ridge National Laboratory 2, Oak Ridge, TN 37831, USA Received 14 February 1997; received in revised form 2 December 1997; accepted 26 January 1998

Abstract Bioindicators of pollutant exposure can be more sensitive and ecologically relevant than simply measuring levels of pollutants in the environment and are applied here as a tool for assessing environmental stress on aquatic organisms. DNA polymorphisms, detected by using the randomly amplified polymorphic DNA (RAPD) technique, are used as biomarkers to assess genetic diversity and genetic distance among populations of redbreast sunfish (Lepomis auritus) residing in reference streams and a contaminated stream (East Fork Poplar Creek, EFPC). The RAPD technique uses the polymerase chain reaction (PCR) with short oligonucleotide primers under reduced stringency to produce DNA fragments which, when analyzed by gel electrophoresis, form banding patterns similar to DNA fingerprints. A total of 13 primers were used which produced 45 polymorphic bands among all populations of fish tested. Using this technique, only slight differences in genetic diversity were detected among populations of sunfish within EFPC although the diversity of all EFPC populations analyzed together did differ from the reference populations. Fish populations in EFPC were consistently less genetically distant from each other than they were from each of the reference sites. Differences in genetic distance between populations may be due to selection pressure of pollutants on fish in EFPC which is supported by the finding that frequencies of certain unique genotypes in EFPC sunfish were correlated with the downstream pollutant gradient. These results are discussed in relation to implications of RAPD assays and recent remediation efforts within EFPC. © 1998 Elsevier Science B.V. All rights reserved. Keywords: Genetic diversity; Contaminants; Fish populations; RAPD assay

* Corresponding author. 1 Present address: Department of Biological Sciences, 3211 Providence Dr., University of Alaska-Anchorage, Anchorage, AK 99508, USA. 2 Managed by Lockheed Martin Energy Research Corp. for the US Department of Energy under contract number DEAC05-96OR22464. ESD Pub. No. 4744.

1. Introduction Laboratory studies have identified a large number of genotoxic chemicals which are commonly found in contaminated environments. The adverse health effects of genotoxic chemicals on organ-

0166-445X/98/$ - see front matter © 1998 Elsevier Science B.V. All rights reserved. PII S0166-445X(98)00049-6

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isms often result from the consequences of direct DNA damage. While the majority of chemical-induced alterations to DNA are repaired, some are either not repaired or improperly repaired leading to mutations and changes in the genetic make-up of affected individuals (Wogan and Gorelick, 1985; Shugart et al., 1992). In addition, toxic chemicals which do not interact directly with DNA can also cause genetic effects on a population due to the selection or elimination of toxicant resistance or sensitive individuals in a population (Nevo et al., 1986; Chagnon and Guttman, 1989; Diamond et al., 1989; Gillespie and Guttman, 1989). Thus, organisms adapting to polluted environments with their associated ecological influences, such as bottlenecks and inbreeding, can result in a narrowing of genetic diversity of a exposed population (Bickham and Smolen, 1994). Individuals within natural wildlife populations are subdivided into more or less distinctive groups that differ genetically from each other. Variation in responses of organisms to toxic stress can be attributed in part to their genetic variations (Thorpe et al., 1981; Nevo et al., 1984; Kopp et al., 1994). Past studies have suggested that human activities such as pollution may influence the genetic composition of fish populations (Thorpe et al., 1981; Smith et al., 1983; Nevo et al., 1984; Schofield and Driscoll, 1987; Strittholt et al., 1988; Gillespie and Guttman, 1989), and these stressors can impose new or additional selection pressures on the population. Stressed organisms are even more vulnerable to additional stressors in the environment which may further jeopardize the survival of populations. For example, mosquitofish were collected from radionuclide contaminated ponds and reference sites and raised in the laboratory for two generations. When the F2 generations from both sites were exposed to elevated temperatures, fish originating from the contaminated sites were found to be less tolerant to thermal stress than the fish from reference site (Trabalka and Allen, 1977). Thus, the degree of genetic variation maintained by a population may be evidence of its capacity to survive future environmental alterations (Chagnon and Guttman, 1989; Gillespie and Guttman, 1989) by tempering or modulating the stress related effects of pollu-

tants and providing a mechanism of population tolerance. Genotypes which survive pollutant exposure may represent those individuals that are most tolerant of environmental stressors (Kopp et al., 1994). Assessment of genetic diversity of natural populations appears to be a useful approach for determining the effects of environmental pollution on aquatic ecosystems (Nevo et al., 1984; Benton and Guttman, 1992; Bickham and Smolen, 1994). Since ecological effects of contamination usually occur at the population or higher levels of biological organization, monitoring changes in population genetic structure can be a valuable component of ecological risk assessments (Suter, 1990; Theodorakis et al., 1996; Theodorakis and Shugart, 1997). DNA markers offer the most direct approach for measurement of genetic diversity. The randomly amplified polymorphic DNA (RAPD) technique, developed by Williams et al. (1990) and Welsh and McClelland (1990), utilizes the polymerase chain reaction (PCR) with arbitrary short primers to identify genetic polymorphisms from which the genetic diversity of the population can be determined. The appeal of the RAPD technique is the simplicity of the procedure and its requirements of only small quantities of DNA. No prior knowledge of the genome being analyzed is necessary, and many genetic loci can be potentially accessed. Thus, this technique is particularly useful in genetic studies of natural populations (Hadrys et al., 1992). Although there has been some concern in using this method for DNA fingerprinting due to its poor reproducibility during the early stage in the development of the RAPD method, many laboratories subsequently have found that this method can produce consistent and highly reproducible banding patterns provided that the PCR reaction conditions are rigidly standardized and kept constant (Berg et al., 1994; Dinesh et al., 1995). In recent years, several studies have used the RAPD technique to investigate genetic diversity and genetic distance in various fish species (Dinesh et al., 1995). In cases where RAPD was used with other methods of DNA fingerprinting, similar results have been obtained (Naish et al., 1995).

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Fig. 1. Sampling sites in East Fork Poplar Creek downstream from the effluent discharge of the nuclear weapons facility and in the two reference streams, Brushy Fork and Hinds Creek.

The objectives of this study are to (i) determine if the genetic differences in closely related sunfish populations can be determined by the RAPD technique, and (ii) to use the RAPD method to determine if the genetic diversity and genetic distance of a sentinel sunfish population can be correlated with contaminant exposure. The hypotheses tested in this study are that genetic diversity will decrease in exposed populations and that the frequencies of specific genotypes will differ between contaminated and reference populations. To test these hypotheses, populations of redbreast sunfish (Lepomis auritus) were examined from a contaminated stream on the Department of Energy’s Oak Ridge Reservation. Redbreast sunfish in this system have been exposed to a variety of contaminants for over 50 years and, therefore, provide an opportunity to investigate possible alteration of population genetic structure within the resident sunfish population. A number of oligonucleotide primers were used to identify genetic polymorphisms in exposed and reference

populations and to determined the potential for the use of RAPD genotypes as biomarkers of contaminant exposure. This genetic diversity study is a component of a large bioindicators program being conducted in several aquatic ecosystems where responses of fish populations to contaminant stress are investigated at several levels of biological organization (Adams et al., 1992; Adams and Ryon, 1994).

2. Methods

2.1. Study sites The primary study site, East Fork Poplar Creek (EFPC), receives a mixture of contaminants from a nuclear weapons components production facility at Oak Ridge, TN. The headwaters of EFPC originate a few hundred meters upstream of this facility and flow through the city of Oak Ridge and the Oak Ridge DOE reservation before its

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confluence with Poplar Creek 23.7 km downstream (Fig. 1). The reference streams, Brushy Fork and Hinds Creek, were selected for their hydrological and physical similarity to EFPC. No internal reference was available for this study because the headwaters of EFPC originate near the source of pollution. Because redbreast sunfish have restricted home ranges in streams (Gatz and Adams, 1994), little intermingling of individuals likely occur within EFPC thus preserving sample site identity for the purpose of this study. Effluent discharges from the facility at East Fork kilometer (EFK) 23.7 and from the Oak Ridge wastewater treatment facility at EFK 13.4 together constitute 39% of EFPC mean annual flow at EFK 5.3 (Hinzman, 1993). Since 1992, however, the water flow in EFPC has been reduced due to decreased waste effluent discharges at this facility. A variety of contaminants have been identified in EFPC including organics (PAHs, PCBs, and total phenol), metals (As, Cd, Pb, Hg, Ni, Ag, Zr, Cu), ammonia, oil and grease, perchloroethylene, and residual chlorine (Jimenez et al., 1990; Hinzman, 1993). Of the major pollutants in the EFPC watershed, mercury appears to be of the most concern relative to its potential genotoxicity (Leonard et al., 1983; Codina et al., 1995) and its concentration in the various media (water, sediment, and fish). From the late 1940s to the mid 1960s, elemental mercury was used extensively for weapons production, and over this period about 9× 104 kg (100 t) of mercury has entered the EFPC watershed (Talmage and Walton, 1993). Mercury is present in EFPC in various forms including inorganic species and methylmercury (Southworth et al., 1995). This stream has a distinct downstream gradient in contaminant loading with levels of mercury progressively declining in sunfish populations downstream from the industrial discharge (Adams et al., 1992). Although mercury at all EFPC sites is predominately particle-associated inorganic mercury, and inorganic mercury accumulates in small proportions in redbreast sunfish, the predominant form of mercury found in fish from EFPC is methylmercury (Southworth et al., 1995). The decrease in the

mass of mercury discharged from this facility via EFPC over the last few years is concurrent with a similar decrease in mercury concentrations measured in exposed sunfish (Southworth et al., 1995)

2.2. Sampling methods and RAPD technique During the spring sampling periods of 1994 and 1995, redbreast sunfish were collected by electrofishing at four sites along EFPC (EFK 23.4 below Lake Reality, EFK 18.3 at Rocky Top, EFK 13.8 at Jackson Farm, EFK 5.3 at the USGS gauging station), and two reference sites (Brushy Fork and Hinds Creek) (Fig. 1). For this study, a total of 410 fish were sampled and analyzed with approximately 70 fish being collected at each site except EFK 23.4 where, due to low density, only 49 fish could be collected. This species was selected as the study organism because it is the only fish which was present in sufficient numbers at all of the sample sites, and it is also the subject of the concurrent biomarker studies at this laboratory (Adams et al., 1992). Upon capture, fish were bled via caudal vein puncture into EDTA-coated Vacutainer tubes (Becton Dickinson, Rutherford, NJ) to prevent clotting. Samples were stored on ice until they could be transported to the laboratory. The blood samples were centrifuged at 5000 rpm for 5 min and plasma was removed. The crude red blood cells were washed twice with fish physiological saline (FPS: 6.44 g NaCl, 11 mg KCl, 22 mg CaCl2, 12 mg MgSO4, 7 mg KH2PO4, and 10 mg NaHCO3 per liter) and suspended in FPS. Red blood cells were lysed using sodium dodecyl sulfate and DNA was extracted by using proteinase K digestion, phenol:chloroform extraction, and ethanol precipitation (Maniatis et al., 1982). DNA concentration was measured using the TKO minifluorometer (Hoeffer Scientific Instruments, San Francisco, CA) against known DNA concentration standard. DNA stock solutions were diluted to 3.6 mg ml − 1 in sterile water and stored at − 70°C until analysis. Amplification reactions were carried out in 15ml volumes containing 2.7 ng of DNA, 3 pmol of primer, 0.1 mM each of deoxynucleotide triphosphate, 2.5 mM MgCl2, 10 mM Tris–HCl, 50 mM

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KCl, 0.6 unit Taq polymerase (Promega Corporation, Madison, WI), and 0.1 mg of bovine serum albumin (BSA). DNA amplifications were performed on a Perkin-Elmer 9600 thermocycler and the amplification protocol consisted of 1 min at 95°C followed by 55 cycles of 20 s at 94°C, 30 s at 37°C, and 2 min at 72°C. Because of the high number of amplification cycles, BSA was added to the reaction mixture to stabilize the polymerase enzyme. The standardized protocol with quantified DNA template concentrations, consistent and accurate use of reaction components, and elimination of foreign template-DNA contamination was strictly followed. Primers were obtained from Operon Technologies (Alameda, CA). Forty different primers, which included the Operon Primer A (OPA) set and OPD sets, were initially screened. Of these, 13 were found to produce distinct, reproducible banding patterns and the production of polymorphic banding patterns in at least one population of all the populations we examined. Although some primers generated distinct banding patterns in fewer cycles, additional cycles did not alter the banding pattern and other primers produced more consistent banding patterns with additional cycles. The amplified products were electrophoresed in 1.5% agarose gel containing 0.5 mg ml − 1 ethidium bromide at 2.5 V cm − 1. Gels were run for different lengths of time to produce maximum separation of bands. The molecular weight of amplified products was calculated based on the relative mobility of DNA standards (bacteriophage fX174 DNA digested with Hae III). Band patterns were visualized by UV illumination of the gel and recorded by photography. Randomly selected sets of DNA templates were periodically used as replicates to verify RAPD banding patterns across genotypes and primers. The presence or absence of bands was scored visually. Consistently sharp and reproducible bands were selected for scoring while bands which were faint or not reproducible over different amplification were not considered for scoring. All the bands scored in the present study have been confirmed by at least two separate experiments. As an indicator of contaminant exposure, activity of detoxification enzymes (EROD) in the hep-

167

atic microsomes of redbreast sunfish was measured according to the procedures outlined in Adams and Ryon (1994).

2.3. Statistical methods The RAPD method is relatively new and there is no one standard statistical method used routinely for determining genetic diversity. For comparison, two different methods, the band sharing index (BSI) (Lynch, 1990) and the nucleon diversity index (Nei, 1987) were adapted. The first method involves calculating the fraction of bands which are shared between individuals in a population to approximate the average identity-in-state for random pairs of individuals using the formula: BSIij = 2Sij /(Ni + Nj )

(1)

where Sij is the number of bands shared by individuals i and j, and Ni and Nj are the number of bands displayed by individuals i and j, respectively. The BSI was calculated for all i, j pairs and averaged within the population. The value of the index may range between 0 and 1 indicating that all individuals are completely different or completely alike with reference to their banding patterns, respectively. Differences in genetic diversity (BSI) between populations were tested by calculating the variance of the mean BSI within each population (Lynch, 1990) and using this variance to calculate a standard normal test statistic. The second method used to calculate genetic diversity is the nucleon diversity index (h) which relies upon the genotype (band pattern) frequencies of the population (Nei, 1987). This index is calculated according to the formula: m

h=[(n/(n − 1)](1− % x 2i )

(2)

I=1

where n is the sample size, xi is the frequency of the Ith genotype (banding pattern), and m is the number of genotypes in the population. Differences between populations were tested by calculating a variance for each population (Nei, 1987), and calculating a standard normal test statistic. Genetic distances between populations were calculated using Roger’s genetic distance (Nei, 1987) according to the formula:

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168 n

Dij =(1/n) % (xik −xjk )2

(3)

K=1

where n is the number of bands scored, xik is the frequency of the Kth band in population i, and xjk is the frequency of the Kth band in population j. Dij ranges between 0 and 1 when the populations are completely similar and completely different, respectively. Genetic distances were calculated for each pair of populations using genotypes generated from all primers, and the differences between different pair-wise comparisons were then tested using Student’s t-test, as suggested by Nei (1987). Neighbor joining analysis (Saitou and Nei, 1987) was performed by the NEIGHBOR program of PHYLIP 3.5c (Felenstein, 1993) using RAPDPLOT (Kambhampati et al., 1992), a computer program which calculates the matching index as an input file. NEIGHBOR utilizes the neighbor joining method of Saitou and Nei (1987) in which genetic distance computed for all pairs of individuals is used to generate an unrooted phenogram. The formula for the matching index used here is: M=NAB/NT

(4)

where M is the fraction of shared bands, NAB is the total number of matches (i.e. shared presence or absence) in individuals A and B, and NT is the total number of loci scored. Unlike BSI (Lynch, 1990) used earlier, the denominator here is fixed and the absence of a band is also scored. M ranges from 0 to 1 indicating completely different and completely identical banding patterns, respectively. A phenogram was constructed based on all individuals examined in this study. The proportions of individuals from all examined sites that constituted clusterings of similar genotypes can be identified from the phenogram. A group of bands which displayed increasing frequency at contaminated sites downstream from EFK 23.7 was used to generate a second phenogram. The bands used to generate this phenogram were OPA11525, OPA91050, OPA181070, OPA18580 and OPD121160 (the subscript indicates the size of band in base pairs generated by the designated primer). Individuals with similar genotypes which increased in

frequency at contaminated sites as compared to reference sites were identified from this phenogram.

3. Results In this study a total of 410 fish were examined. Sample sizes for each population were 49 fish at EFK 23.4, 71 at EFK 18.3, 74 at EFK 13.8, 75 at EFK 5.3, 73 from Brushy Fork (reference), and 68 from Hinds Creek (reference). Forty different primers from the OPD and OPA sets were initially used to screen polymorphic banding patterns in 50 randomly selected redbreast sunfish collected from several sites. Of these, 26 were found to produce a polymorphic banding pattern. We analyzed the genetic diversity and genetic distance among sunfish populations collected from four contaminated and two reference sites using half of the originally identified primers selected randomly. We scored a total of 78 individual bands for all 13 primers combined. Presumably, each band represents a specific genetic locus. Forty-four of these 78 bands were polymorphic in the fish examined.

3.1. Band sharing index The genetic diversity as measure by BSI calculated for each primer revealed no significant differences in diversity among the four groups of sunfish collected from the four different sites in EFPC. Also, no significant difference was found between the two reference sites using this index. Because no statistical differences were observed among contaminated sites within EFPC and between the two reference sites, contaminated sites were pooled and compared with the pooled reference sites using a one-way weighted ANOVA for each primer (Table 1). Differences were noted between contaminated and reference sites for primers OPD3 (P =0.0770), OPD8 (P= 0.0704), and OPA1 (P= 0.0773). Contaminated sites were shown to be more genetically diverse than the reference sites for these primers. There are also highly significant differences between the pooled contaminated and pooled reference sites for

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primers OPD16 (P=0.0419), OPA9 (P = 0.0436), and OPA15 (P =0.0099). For these three primers, reference sites were shown to be more diverse than the contaminated sites. No difference, however, was indicated between contaminated and reference populations based on analysis of the seven remaining primers.

Table 2 Results of the one-way weighted ANOVA for the nucleon diversity index

OPD3

3.2. Nucleon di6ersity index Using the nucleon diversity index calculated for each of 13 primers, no significant difference was detected among fish collected from the four EFPC sites. However, this index indicated differences between the two references sites for seven of the 13 primers. Therefore, for further analysis using this index, reference sites were considered indeTable 1 Results of the one-way weighted ANOVA by primer for the band sharing index Primer OPD3 OPD5 OPD8 OPD11 OPD12 OPD15 OPD16 OPA1 OPA2 OPA9 OPA11 OPA15 OPA18

I r I r I r I r I r I r I r I r I r I r I r I r I r

Weighted mean

P-value

0.8092 0.8888 0.8826 0.8914 0.8869 0.9570 0.7938 0.7944 0.7724 0.8034 0.6148 0.6170 0.9016 0.8854 0.8976 0.9330 0.9266 0.9140 0.8219 0.7477 0.8041 0.8012 0.0997 0.0768 0.78 0.7795

0.077

Primer

Weighted mean

P-value

efpc bf hc

0.8837 0.8550 0.4846

— 0.2025 0.0031

OPD5

efpc bf hc

0.7351 0.7321 0.7120

— 0.9666 0.7402

OPD8

efpc bf hc

0.6849 0.1796 0.6984

— 0.0053 0.6874

OPD11

efpc bf hc

0.7445 0.7461 0.8288

— 0.9801 0.1665

OPD12

efpc bf hc

0.5918 0.5133 0.6207

— 0.4011 0.5849

OPD15

efpc bf hc

0.4986 0.5225 0.5632

— 0.8208 0.5673

OPD16

efpc bf hc

0.6166 0.6842 0.7011

— 0.1620 0.1124

OPA1

efpc bf hc

0.7377 0.7327 0.4350

— 0.7842 0.0432

OPA2

efpc bf hc

0.5968 0.5887 0.6124

— 0.7773 0.6008

OPA9

efpc bf hc

0.4288 0.5278 0.5351

— 0.1173 0.0538

OPA11

efpc bf hc

0.5700 0.6975 0.5057

— 0.1996 0.2900

OPA15

efpc bf hc

0.4074 0.6792 0.6453

— 0.0087 0.0212

OPA18

efpc bf hc

0.8514 0.8774 0.8117

— 0.0866 0.1964

0.5327 0.0704 0.9781 0.314 0.9188 0.0419 0.0773 0.2626 0.0436 0.8818 0.0099 0.9835

Populations were pooled into two groups: impacted populations from EFPC (I) and reference populations (r).

ANOVAs were calculated for three groups: impacted sites on East Fork Poplar Creek (efpc), Brushy Fork (bf), and Hinds Creek (hc).

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Table 3 Roger’s genetic distance for RAPD genotypes

BLR RT JF GS BF HC

BLR

RT

JF

GS

BF

HC

— — — — — —

0.0398 — — — — —

0.0429 0.0427 — — — —

0.0431 0.0482 0.0382 — — —

0.0875 0.0749 0.0741 0.0733 — —

0.0882 0.0833 0.0985 0.0999 0.1209 —

Pairwise comparisons between all populations were calculated by genotypes generated using all primers. East Fork Poplar Creek populations (impacted sites) include: BLR (EFK 23.4), RT (EFK 18.3), JF (EFK 13.8), and GS (EFK 5.3). Reference sites are Brushy Fork (BF) and Hinds Creek (HC).

pendently and each was tested for differences in nucleon diversity compared to the pooled EFPC sites using a one-way weighted ANOVA (Table 2). Four primers OPD3 (P =0.0031), OPA1 (P = 0.0432), OPA9 (P=0.0538), and OPA15 (P = 0.0212) demonstrated a significant difference between pooled contaminated sites and Hinds Creek. Primers OPD3 and OPA1 showed a increase in diversity of contaminated sites while the other two primers indicated decreased levels of diversity in contaminated sites. Primers OPD8 (P= 0.0053) and OPA15 (P =0.0087) indicated a significant difference and OPA18 (P = 0.0866) a slight difference between the grouped contaminated sites and Brushy Fork. One primer, OPA15, was significantly different between the contaminated sites and each reference site. The nucleon diversity index calculated by the remaining seven primers was not significantly different between contaminated sites and either of the reference sites.

3.3. Roger’s genetic distance Roger’s genetic distance was calculated from composite genotypes compiled from all primers (Table 3). The genetic distance among all EFPC sites was relative small, indicating that all four populations of EFPC are closely related. However, the genetic distances between each of the EFPC populations and each of the reference populations were significantly different. In addition, the EFPC populations and the Brushy Fork population were less genetically distant than EFPC and the Hinds Creek population.

3.4. Neighbor joining analysis of genetic similarity The neighbor joining analysis using RAPDPLOT assigns a genotype to each of the examined fish based on RAPD bands generated by all analyzed primers and further reveals individual genetic relationships among all examined fish. Fig. 2 is a phenogram generated using all 13 primers and includes all individuals examined in this study. The results demonstrate that the genotypes of individuals among all fish are highly variable indicating the genetic diversity of natural sunfish populations can be readily analyzed by the RAPD method. The RAPDPLOT reveals that all fish can be grouped into five major clusters and several minor clusters (Fig. 2) based on their similarity of genotypes. Clusters consisted of fish from the four sites in EFPC and both reference sites. In addition, there was no observed relationship between physical distance among sites within EFPC and the estimated genetic similarity as indicated by the neighbor joining analysis. Thus, based on the analysis of all 13 primers, fish from EFPC do not confine together as a distinctive genetic group. However, more than 50% of all fish from the four EFPC sites and Brushy Fork are contained in the five major clusters while only 28% of the Hinds Creek fish are partitioned among these five clusters. The results of the neighbor joining analysis are consistent with the findings of the Roger’s genetic distance analysis in that sunfish from EFPC are more genetically related to sunfish from Brushy Fork than they are to individuals from Hinds Creek.

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Fig. 2. Phenogram generated using RAPDPLOT Neighbor joining method incorporating all primers and fish from all populations in the contaminated stream and the two reference streams. Five major clusters of genotypes (A – E) are indicated with smaller clusters within each of these major groups.

A phenogram generated by using the five bands which displayed an increased frequency of fish collected from the two most contaminated sites (EFK 23.4 and 18.3) showed that individuals

from all sites are grouped into seven different clusters based on their similarity of genotypes (genotypes A–G in Fig. 3). Individuals from one cluster (cluster A, Fig. 3) shared a specific geno-

172

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Fig. 3. Phenogram generated using bands which showed increased frequency downstream of the industrial discharge in East Fork Popular Creek. Genotype A represents fish with a genotype present in increased frequency in the more highly impacted sites compared to reference sites. Numbers in parenthesis beside each of the seven major genotypes (A – G) represent the number of fish represented by that particular genotype.

type which occurred at a much higher frequency in fish from these more contaminated sites than in those individuals from less contaminated sites.

This shared genotype is found in 30.6% of the EFK 23.4 population (most contaminated site), in 18.3% of fish from EFK 18.3 (moderately con-

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Fig. 4. Concentrations of mercury in redbreast sunfish and in water of East Fork Poplar Creek with indicators of contaminant exposure (DNA integrity and EROD) for the redbreast sunfish populations.

taminated site), 10.8% of individuals at EFK 13.8 (moderately contaminated site), 12% of the population at EFK 5.3 (least contaminated site), 4% at Brushy Fork (reference), and 7.4% of the fish at Hinds Creek (reference) populations. As a biochemical indicator of contaminant exposure, detoxification enzyme activity (EROD) was significantly elevated in sunfish at all four

EFPC sites compared to the reference (Hinds Creek) (Fig. 4). EROD activity was highest at the site immediately below the industrial outfall (EFK 23.4) and decreased progressively downstream until a slight increase in activity was noted at the lower site (EFK 5.3). This increase was probably due to discharges of the Oak Ridge sewage treatment facility located immediately of this site.

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4. Discussion Molecular techniques have been increasingly adapted for aquatic toxicology studies. Most of these studies have thus far focused primarily on individual-level effects such as DNA damage (McMahon et al., 1990; Shugart et al., 1992), differential gene expression (Campbell and Devlin, 1996; Schlenk et al., 1997; Willett et al., 1997), and characterization of genes involved in xenobiotic response (Rotchell et al., 1995; Roy et al., 1995; McDonald et al., 1996). Relatively few studies have used molecular techniques to examine population genetics in contaminated environments (Wirgin et al., 1990, 1991; Murdoch and Herbert, 1994). It has been suggested that population genetic structure of natural organisms can be used as bioindicators of water quality and health of aquatic populations living in contaminated environments (Nevo et al., 1984; Benton and Guttman, 1992; Fore et al., 1995). However, differences in genetic variability between contaminated and non-contaminated populations may not be due solely to contamination. Such changes may also result from other factors such as gene flow, random genetic drift, inbreeding, population density, habitat complexity, and natural selection and mutation (Nei et al., 1975; Hartl, 1988; Demeeus et al., 1993). In the present investigation the PCR-based RAPD method was adapted to examine genetic diversity among redbreast sunfish populations collected from contaminated and reference sites and to examine potential alteration in fish population genetics which might be caused by exposure to contaminants. Although the RAPD technique is particularly useful for population genetics studies of natural populations, there are some drawbacks to this method. Most RAPD markers are dominant limiting the ability to distinguish heterozygotes from homozygotes. Therefore, it is difficult to calculate allele frequencies using RAPD data. The RAPD bands can be amplified from various locations in the genome, from coding or non-coding regions. Thus, the genomic identity and possible biological significance of RAPD bands are unknown. Since the RAPD bands are usually identified by molecular weights

and not by nucleotide sequence, it is possible two DNA fragments with similar molecular weights but different sequences may be identified as a single band. These drawbacks are further discussed and reviewed in Williams et al. (1990) and Hadrys et al. (1992). Using 13 primers, we identified 44 randomly amplified polymorphic DNA markers. With these DNA markers, specific and unique genotypes were identified in 274 fish from the total 410 fish examined (Fig. 2) while the remaining fish had genotypes that were shared with at least one other individual fish. Furthermore, we demonstrated that these polymorphic DNA markers can be used for the analysis of genetic diversity of natural sunfish populations. Thus, the genetic diversity among natural sunfish populations can be readily analyzed by the RAPD method. Based on the analysis of two measures of genetic diversity, the band sharing index and the nucleon diversity index, groups of sunfish collected from four different sites within EFPC did not differ significantly from each other. However, the diversity of all EFPC sites when pooled together did differ from each of the reference sites. Genotoxic exposure can act as a selective force by eliminating sensitive genotypes within a population, with a predictable shift in genotype frequencies of the affected population. Even though direct evidence relating genetic diversity to contamination exposure for fish populations in EFPC cannot be definitely established in the present study, sufficient other indirect evidence exists to provide a strong case for this relationship. For example, levels of mercury in the water and in fish tissue were highly elevated in EFPC particularly in the upper reaches (Fig. 4A; see Department of Energy, 1996 and Peterson et al., 1996 for details). In addition, both EROD activity and DNA integrity indicated that redbreast sunfish had been exposed to contaminants including genotoxins in EFPC. As demonstrated by the DNA integrity index, the number of DNA strand breaks ranged from 3.5 to 8 times higher in EFPC than in sunfish collected from the reference stream (Fig. 4B; see Hinzman, 1993 for details). Similarly, induction of the mixed function oxidase enzyme, EROD, was 2–4.5 times higher in EFPC fish than

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in those individuals sampled from the reference (Fig. 4B). Thus, the weight of this evidence suggests that there is a correlation between contaminants in EFPC and alterations in genetic diversity, however, definitive cause and effect relationships cannot be established at this time. In addition to the observations of elevated contaminants in EFPC and the indicators of contaminant exposure, findings from other studies also support the possible correlation between mercury exposure and changes in genetic diversity. When a population of marine gastropods was exposed to mercury, for example, a significant differential survivorship among allozyme genotypes was observed (Nevo et al., 1981). Laboratory studies have also identified mercurytolerant allozyme genotypes occurring at higher frequencies in populations collected from mercury-contaminated sites than in animals sampled from non-contaminated habitats (Nevo et al., 1984). In addition, survival of gastropod populations collected from mercury-polluted systems was higher than individuals sampled from mercury-free sites (Baker et al., 1985). Furthermore, Culvin-Aralar and Aralar (1995) selected for metal resistance in Oreochromis niloticus by exposing fish to toxic doses of mercury and other metals. The F2 progeny of metal-exposed fish were found to be more resistant to subsequent metal exposure than were progeny of non-exposed fish. Mercury is the major pollutant in the EFPC watershed (Hinzman, 1993; Southworth et al., 1995). Because of its genotoxicity (Leonard et al., 1983; Codina et al., 1995), mercury in EFPC may represent a selective force in exposed fish populations. Thus, our observed alterations in genetic diversity are consistent with the possibility that fish populations in EFPC are under selection pressure due to the presence of genotoxic chemicals such as mercury. Although mercury compounds, primarily methylmercury (Southworth et al., 1995), have been shown to accumulate in redbreast sunfish with levels decreasing progressively downstream from the effluent discharge, the genetic diversity among contaminated EFPC populations does not appear to demonstrate this downstream pattern in contam-

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inant body burdens. The lack of differences in genetic diversity among EFPC sunfish populations could result from (i) recent remediation efforts within EFPC which may have relaxed selection pressures on fish within this system, (ii) a small degree of interchange in fish among sites within EFPC which would result in a more homogenous population within this stream, and (iii) recruitment of fish from aquatic systems outside EFPC which could be expected to decrease the probability of detecting significance differences in genetic diversity caused by pollution. Roger’s genetic distance was also used to evaluate the genetic relatedness among fish populations. Roger’s genetic distance showed no differences among populations within EFPC, but significant distances were detected between pooled EFPC populations and each of the reference sites. These results are consistent with the band sharing index and nucleon diversity observations. Even though the phenogram (Fig. 2) from the neighbor joining analysis consists of five major clusters of individuals, these clusters are composed of fish from all sample sites. There is no evidence that genotypic distributions are partitioned into defined populations analogous to each of the sample sites. Nevertheless, these results do demonstrate that the genetic relatedness of closely related populations can be determined by the RAPD method. In addition, when neighbor joining analysis was applied to certain polymorphic bands, some unique genotypes were identified. A phenogram was generated from the five bands which increased in frequency among EFPC sites as a function of downstream distance from the industrial discharge (Fig. 3). This phenogram identified a unique genotype which is present in higher frequencies at the contaminated EFPC sites than at the two reference sites. Among the EFPC populations, the number of individual fish with this particular genotype decreased progressively downstream from the effluent discharge. This finding suggests that individuals with this genotype may be selectively resistant to pollutants.

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5. Conclusions The present observations that genetic diversity is altered in fish populations from contaminated sites in EFPC compared with those from reference sites are consistent with the interpretation that genetic selection is probably due to contaminant effects. Even though direct evidence relating genetic diversity to contaminant exposure for fish populations cannot be definitely established in the present study, sufficient indirect evidence provides a strong case for this relationship. If contaminants are indeed primarily responsible for the alterations in genetic diversity observed in the exposed populations, then it is expected that similar changes in polymorphic RAPD band frequencies and genotypes would also occur in geographically separated populations exposed to the same type or group of contaminants. This type of investigation can be readily conducted with the RAPD method by using the specific primers identified in our present study. Some individual fish from the contaminated stream displayed a unique genotype, with the frequencies of this genotype consistent with both the distance that fish were collected from the effluent discharge and the downstream gradient in fish tissue levels of methylmercury. These individuals, therefore, would have a selective advantage compared to those fish not possessing this particular genotype. Identification of RAPD markers with direct correlation to exposure to particular pollutants could be a valuable research tool in that they could be employed as biomarkers of exposure in similarly contaminated populations. Future research initiatives in this area should focus on the identification of additional genetic markers that have altered frequencies or are unique to contaminated environments. These DNA indicators could serve as biomarkers of genotoxic exposure, bioindicators of potential effects on populations and communities, and function as a useful environmental management tool.

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