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Markie YNA 2012


Grade: 11 | State: Vermont

Genetic Analysis of the Brown, Brook, and Tiger Trout Populations in the Lake Champlain Basin


The brook trout (Salvelinus fontinalis) was designated by the state of Vermont as the official Vermont State coldwater fish in 1978 (“Vermont Fish and Wildlife”). It has been designated as the New York State fish as well. This pilot study came out of a concern that the population of native brook trout in the Lake Champlain Basin (in Vermont and New York State) was declining. It was hypothesized (Hypothesis 1) that this was occurring because of the probable mating of female brook trout with non-native stocked brown trout (Salmo trutta), thus producing a sterile hybrid tiger trout (Salvelinus fontinalis x Salmo trutta). This would threaten the longevity of the native brook trout species. This possibility was assessed using six genetic markers for comparison across the three species. The DNA of each of the species of trout caught was tested to determine if the suspected hybridization was in fact occurring. A second hypothesis (Hypothesis 2) in the study was that the further apart the test sites, the greater the genetic diversity within the trout populations. To evaluate this premise, GPS coordinates were determined for each site, the length of each trout was measured, and water and air temperatures were recorded. Both hypotheses were supported. Regarding Hypothesis 1, the results showed that the proposed tiger trout had DNA alleles that were consistent with both brook and brown trout. Additionally, phylogenetic tree analysis using DNA sequences maintained these findings. Hypothesis 2, which predicted that the genetic diversity within the trout populations would be greater the further apart the test sites, was as well supported by the phylogenetic tree analysis using DNA sequences. The results of this research could contribute to planning decisions about habitat protection made by area biologists to help maintain a healthy ecosystem, but could also offer valuable information to the field of biology. Another consideration is that last year’s (2011) record snowfall, rainfall, and Tropical Storm Irene had such a destructive impact on the trout populations in this area in that many fish were washed out of their normal habitat. These findings make the results of this study even more important in that it speaks to the effect that climate change can have on ecosystems in any geographical area.



Figure 1: Map of the Lake Champlain Basin with the collection sites mapped based on GPS coordinates.

The Lake Champlain Basin covers 8,234 square miles in Vermont and New York (Figure 1) (New York State Department of Environmental Conservation). I have a special relationship with Lake Champlain. I was almost 14 years old when my family moved from southern California to Vermont, and I was used to living by the ocean. The move gave me culture shock. Buying our house on an island in Lake Champlain helped mitigate the trauma created by the drastic change in my life. Although living in a place where you had to drive across a sandbar to get to your home has its own special challenges, I have a big body of water right in front of my house. I can walk across our yard and be standing by the edge of the lake. I’ve spent many hours sitting on the rocks, looking into the water and studying the small pebbles on the bottom, the waving underwater plant life, and all the small and sometimes not-so-small species of fish swimming and flicking along. I’ve watched the sun glimmer across the top of the water, making little ripples look like the shiniest of diamonds. I’ve watch the light rays penetrate into the water toward the shallow bottom, exposing a brilliant showcase of underwater life. My near-daily summer rides in my kayak helped expose me to all the natural wonders Lake Champlain has to offer.

For as long as I can remember, I have had an appreciation of and interest in our environment and the delicate balance of bugs, plants, trees, and all living things. Only later did I gain a more scientific understanding of my childhood observations by thinking about habitats and ecosystems. I feel the pull of learning more about the complex interrelationships of all things in our environment. I’ve become a young biologist with an interest in ecology and a budding interest in genetics. My exposure to genetics was a lucky connection made with a professor at S.U.N.Y. Plattsburgh (Dr. Nancy Elwess) when I was 15 years old and attended a talk she gave at the local library on the DNA analysis of Mayan skeletons. At the end of her talk, I worked up my courage and asked if I could have her e-mail address. She had mentioned running a genetics lab at the university, and I was excited about the possibility of seeing all the equipment there. I offered to do maintenance or cleanup work just to be able to observe. Her response was that anyone who came into her lab would do his or her own research project, and if I decided to come, then that’s what I would be doing. My response was, “Awesome!” So every day in the summer of 2011, I took the ferry from the Vermont side over to the New York side and back, and planned out and executed my first research project in genetics. Wanting to address a relevant issue, I decided I should look at the trout populations in Lake Champlain and inquire into why brook trout species seem to be declining. For the past several years, the New York State Department of Environmental Conservation (NYDEC) has made genetic monitoring of brook trout, Salvelinus fontinalis, a priority because of their declining numbers (NYDEC). Genetic markers are increasingly used to analyze population genetics (Anger et. al, 1995). Brook trout also serve as indicators for the quality of coldwater habitats. The NYDEC, the Fish and Wildlife Division of the U.S. Department of the Interior, and the Lake Champlain Research Institute support genetic monitoring of these fish in order to produce quantitative indicators concerning the health of this ecosystem (NYDEC). It is important to note that non-native brown trout, Salmo trutta, are stocked in tributaries of the Lake Champlain Basin. The concern is that native brook trout populations in the Lake Champlain Basin are declining due to the mating of female brook trout with non-native male brown trout (hybridization), thus producing a sterile tiger trout, Salvelinus fontinalis x Salmo trutta. Tiger trout exist in other parts of the country (“Utah Fishing Information”) because of interbreeding, but it is not known if this hybridization is occurring in the Lake Champlain Basin. This is an important community issue for two reasons: the need to consider the negative impact on the native brook trout species of stocking non-native brown trout, and the impact this practice has on the fishing industry in the region, which is a significant part of the rural economy.


1) Since hybridization has already occurred between brook and brown trout in other parts of the country, is hybridization occurring between native brook trout and non-native stocked brown trout in the Lake Champlain Basin (in my own backyard) and resulting in the production of a sterile tiger trout?  

2) Since no genetic inventory has ever been done on either the brook or brown trout populations in the Lake Champlain Basin, is there genetic diversity within each of these trout species?

Hypothesis #1:  I hypothesize that there is interbreeding occurring between the brook trout and the brown trout resulting in the production a sterile tiger trout, and that genetic testing using six genetic markers can help to determine if and where this hybridization is occurring.

Hypothesis #2: I hypothesize that the native brook and the non-native brown trout populations will be more genetically diverse the further apart the test sites are located, and that the genetic markers proposed for use could help to determine if this genetic diversity is in fact occurring. 

Methods and Materials:

Brook and brown trout were caught and released in True Brook in Saranac, New York, and Great Brook in Plainfield, Vermont, by electroshocking the water at extremely low voltage. The trout (N=26) were scooped up in nets, and small fin clippings were taken from the caudal fin or adipose fin; the samples were put in sterile collection tubes. Each fish was measured for length; and weather conditions, GPS satellite positioning and water temperatures were recorded (Figure 2). The collected fish were identified as brown trout, brook trout, and possible tiger trout (unknowns). Gloves were worn when handling each fish. After collecting the samples, the fish were released before moving on to the next site.


Figure 2: Collecting trout samples from True Brook (Saranac, NY) with fish biologist Dr. Timothy Mihuc (left) and in Great Brook, Plainfield, VT (right), with fish biologist Madeleine Lyttle.

Preparing myself to go out in the field to collect my samples was an exciting experience. I was wearing full-body waders made of canvas and rubber and pack boots, tramping through fields, forests, hills and down to the rocky brookside, swinging my fish net along and my GPS recording device dangling from my neck. When I was collecting my specimens on the Vermont side of the basin, I was accompanied by fish biologist Madeleine Lyttle, as well as my mentor Dr. Elwess and four other people on my research team; on the New York side my team and I were accompanied by fish biologist Dr. Timothy Mihuc. Once in the brook, we all had our different strategies for keeping our footing and not falling in. The biggest challenge was catching the fish in the nets. Although we used an electroshock device to stun the fish so that we could catch them, it was set at an extremely low voltage so as not to endanger them in any way. What that meant was that it was not very effective, and if it did stun a fish, it lasted less than a second. This resulted in all of us rushing toward any fish we saw that had been “stunned,” plowing through the water in an excited panicked attempt to catch the fish in one of our nets, ducking around so as not to net someone else’s head. Off and on, one of us would get shocked, and this let us know just how the fish may have felt! Once caught, I would carefully hold each fish, and when I took the tiny clipping of its fin with my scissors, I was careful to do this so as not to harm or hurt the fish. This was incredibly important to me and the entire team.

Once back in the lab, DNA isolation using the fin clippings was done following Animal Tissue Spin Column Protocol from DNeasy® Blood and Tissue Protocol from Qiagen. The isolated genomic DNA used polymerase chain reactions (PCR) with PuReTaq Ready-To-Go PCR beads, 200-400 ng of DNA, and 2 µM of forward and reverse primers (Table 1). The thermal cycler was programmed for 35 cycles of 94 degrees C for 30 seconds, 56 degrees C for 30 seconds, and 72 degrees C for 45 seconds. Samples were assayed for allelic diversity using six microsatellite markers that were known to be polymorphic; they were Sfo-C129, Sfo-C79, Sfo-C113, Sfo-292, Sfo-262 and MST-85 (Table 1). After PCR, 5 µl of 5x loading dye was mixed with 20 µl of each DNA sample and loaded into a 1.25% agarose gel containing ethidium bromide. Following DNA gel electrophoresis, each gel was visualized and photographed using a gel documentation system. DNA analysis was done using a bio-analyzer to determine the exact size of each PCR product. Samples were also sequenced using Sanger sequencing and analyzed through a sequence alignment program (GeneBee) that produced phylogenetic trees.

Table 1. Genetic Marker Primer Sequences

Marker Sequences Reference
Sfo 262



Perry et al., 2005
Sfo 292



Perry et al., 2005



Presa & Guyomard, 1996



Stott et al., 2010



Stott et al., 2010



Stott et al., 2010

Figure 4: A DNA gel documentation system in the molecular genetics research laboratory was used to determine sizes of alleles.

The DNA-analysis equipment I was introduced to while doing this research seemed out of this world! It was amazing to me to be in a real laboratory, seeing the equipment for real, learning what each piece does, learning how to use it, and then learning how to analyze the results I obtained from it; it was a spectacular experience. The idea that the bio-analyzer (Figure 3), for example, could take just one microliter of DNA (smaller than the period at the end of a sentence) and yield the exact size of DNA fragments, seemed unbelievable. (Figure 4) DNA is so small that it cannot be seen by the naked eye. I was now standing in front of a machine called a thermal cycler that could duplicate it so many times, I could see it with my own eyes—the genetic material that codes for life traits. Another experience emerges when I think about the people who taught me about this equipment and all that can be accomplished and learned through using it—so educated, knowledgeable, talented and creative. I was in remarkable company.


Figure 3: Bioanalyzer results for a brown trout DNA sample using the Sfo-C113 genetic marker. The arrows represent the three areas used in the analysis of determining the size of the PCR product (133 bp).

Table 2. Summary of variations for microsatellite markers

Sfo-C113 Microsatellite Brown Trout Brook Trout Unknowns
Allele range in base pairs 131-137 bp 137-155 bp 129-149 bp
Number of Alleles 3 6 3
Sfo262 Microsatellite Brown Trout Brook Trout Unknowns
Allele range in base pairs 356-375 bp 320-412 bp 323-375 bp
Number of Alleles 5 9 4
Sfo292 Microsatellite Brown Trout Brook Trout Unknowns
Allele range in base pairs 205-327 bp 197-292 bp 197-293 bp
Number of Alleles 15 11 5
Sfo-C79 Microsatellite Brown Trout Brook Trout Unknowns
Allele range in base pairs 100-104 bp 104-108 bp 100-108 bp
Number of Alleles 2 2 2
Sfo-C129 Microsatellite Brown Trout Brook Trout Unknowns
Allele range in base pairs 239-247 bp 241-256 bp 249-259 bp
Number of Alleles 3 6 3



Figure 5: DNA electrophoresis results for Sfo-C113 marker. M=100 bp marker. Lanes 1-4, 6, 7 = brook trout samples; Lane 5 = suspected tiger trout sample, with two bands present.

All the genetic markers tested on the trout samples produced a wide range of alleles (Table 2). Genetic marker Sfo-292 had the greatest number of alleles for brown trout (15), brook trout (11), and tiger trout (5), as well as the largest size range in base pairs (197–327 bp) (Table 2). The Sfo-C79 marker had the least number of alleles (2) for each trout tested and had the smallest size range (100–108 bp) (Table 2). Marker Sfo-C113 exhibited a range of 129–155 bp, with brown trout having three alleles, brook trout six alleles and the unknown three alleles (Table 2). Sfo-C129 had the same allele rate as the Sfo-C113 marker but with a range of 239–259 bp (Table 2). Marker MST-85 created too many DNA fragments and hence was not useful (data not shown). The Sfo-C113 and Sfo-292 results for the unknowns had alleles present that matched both the brook and brown trout alleles (Figure 5, Lane 5; Figure 6 and Figure 7, Lane 8). 


Figure 6: Allele frequency results for Sfo-C113 genetic marker. Brook trout alleles were 137–155 bp; brown trout alleles 131, 135, and 137 bp. Unknown trout had alleles which matched both brook trout (149 bp) and brown trout (131 and 137 bp).


Figure 7: DNA electrophoresis results for Sfo-292 marker. M = 100 bp marker, blue arrow = 200 bp. Lanes 1-2, 6-7= brown trout samples; Lanes 3-5 = brook trout samples; lane 8 = suspected tiger trout sample, with two bands (yellow arrows) present that match both brook and brown trout bands.

The Sfo-262 genetic marker also showed that the unknown trout had alleles that matched alleles from both brook (338 and 350 bp) and brown trout (375 bp) (Figure 8). DNA sequencing and phlyogenetic analysis for the Sfo-C129 genetic marker also supported this relationship (Figure 9 & 10). Phylogenetic tree results also showed the genetic diversity between test sites (Figure 11, Table 3).



Figure 8: Percentages of allele frequency for the Sfo-262 genetic marker. Brook trout alleles were 320–356 bp and 392–412 bp; brown trout alleles were 356–375 bp. Unknown trout had alleles that matched alleles from brook trout (338 and 350 bp) and an allele from brown trout (375 bp).


Figure 9: Chromatogram of DNA Brook trout 3 Sfo-C129 Sequence. The highlighted blue sequence represents the sequence shown in the chromatogram.


Figure 10: Phylogenetic tree using GeneBee software on trout samples for the Sfo-C129 sequences. The proposed tiger trout sequences (Tiger? and Unknown2) are closely related to both brook and brown trout sequences.


Figure 11: Phylogenetic tree for Sfo-C-79 for brook trout sequences. Samples were collected from two different states, and several sites along True Brook. GeneBee software was used to generate image

Table 3. Distances for Brook Sequence Using Sfo-C79 Marker | Distance Matrix

  1 2 3 4 5 6 7 8
1 Brook8 0.000 0.033 0.000 0.016 0.016 0.033 0.000 0.099
2 Brook2 0.033 0.000 0.033 0.016 0.016 0.016 0.033 0.083
3 Brook6 0.000 0.033 0.000 0.016 0.016 0.033 0.000 0.099
4 Brook4 0.016 0.016 0.016 0.000 0.000 0.016 0.016 0.083
5 Brook5 0.016 0.016 0.016 0.000 0.000 0.016 0.016 0.083
6 Brook3 0.033 0.016 0.033 0.016 0.016 0.000 0.033 0.067
7 Brook7 0.000 0.033 0.000 0.016 0.016 0.033 0.000 0.099
8 Brook1 0.099 0.083 0.099 0.083 0.083 0.067 0.099 0.000

Discussion and Conclusions:

Improvement of genetic markers has supplied a source of polymorphism needed for genetic identification in fish. The purpose of this pilot study was twofold: First, DNA was tested to determine whether hybridization of native brook and non-native brown trout was producing a proposed tiger trout. Second, the genetic diversity in both the brook trout and brown trout populations in the Lake Champlain Basin was assessed using six DNA markers.  

Initial screening of all DNA samples using the six genetic markers produced results. The level of polymorphisms produced by the brook and brown trout in this project were comparable to those examined in other studies (Presa and Guyomard 1996; Angers and Bernatchez 1998; Angers et al., 1995; Fopp-Bayat et al., 2007; Perry et al., 2005). However, the MST-85 results showed more alleles than those from previous studies (Presa and Guyomard 1996), making this particular marker unreliable for this study. Genetic markers Sfo-C113, Sfo-262, and Sfo-292 showed promise for identifying tiger trout as well as for identifying genetic diversity (the latter discussed below). The Sfo-C113 marker showed the smallest number of alleles (Table 2) but did produce two DNA bands for one of the proposed tiger trout (Figure 5, Lane 5). The bottom band (Figure 5, Lane 5) matched the size range for brown trout, while the top band was within the range for brook trout (Figure 6, Table 2). On the other hand, the Sfo-292 produced the greatest number of alleles (Table 2); it also produced two distinct DNA bands for the proposed tiger trout samples (Figure 3, Lane 8). Here again, the two DNA bands (Figure 7, Lane 8) matched both the brook and brown trout DNA bands. The Sfo-262 marker showed the brook trout alleles fell within the range of 320–356 bp and 392–412 bp, while the brown trout alleles were measured to be 356–375 bp (Figure 8). The proposed tiger trout had alleles that matched two alleles from brook trout (338 and 350 bp) and one allele from brown trout (375 bp). Further testing on more trout samples will need to be done using these markers.

DNA sequencing of all the trout samples was done; Figure 9 is the DNA sequence for brook trout 3 using Sfo-C129. Phylogenetic trees were created based on the DNA sequences. The phylogenetic tree for Sfo-C129 (Figure 10) supported the hybridization of the proposed tiger trout; the tiger trout and unknown trout DNA sequences fell between brook and brown trout branches. Regarding the question of genetic diversity of the brook and brown trout populations, when brook trout DNA samples were entered into the GeneBee phylogenetic tree software program, it showed the diversity of the samples (Figure 11; Table 3) according to the collection sites. For example, brook trout Samples 1 and 8 showed the greatest distance based on their DNA sequences (Table 3). Additionally, the brown trout samples also showed genetic diversity between their collection sites (data not shown). I feel that the data presented here is promising in that it lends support and gives validation to both of the hypotheses, especially the hypothesis that hybridization is occurring in the Lake Champlain Basin.

Further Research:

Due to several areas of concern, follow-up studies need to be done. First, the number of trout samples collected was quite small, so the number of genetic comparisons that could be made within samples was accordingly limited. At the time I collected my trout specimens in the summer of 2011, the state of Vermont had just come out of a winter season that was remarkable for record snowfall during the winter (USA Today) and record rainfall during the spring (Burlington Free Press).   The weather produced swollen, fast-moving streams, which had an impact on the number of trout in the streams. More brook trout (this species is in general a smaller, lighter-weight fish) than brown trout were probably washed downstream and out of the area. This may be one reason why there were more brown trout than brook trout samples collected at the Plainfield, Vermont location, and more brook trout than brown trout samples collected at True Brook stream near Saranac, New York. Because of the small number of each trout species at the location sites, it was difficult to compare genetic differences between the brook trout populations and brown trout populations at the two sites. Our specimen collection overall was small, so the genetic comparisons that could be made across the three species (including the proposed tiger trout as the third species) were compromised as well. My research requires follow-up studies to fully evaluate the validity of my two hypotheses. A much larger of number of specimens from each species of trout needs to be collected and tested to truly evaluate brook and brown trout populations, the genetic diversity within trout populations, and the possible sustained presence of tiger trout. More collection sites on the Lake Champlain Basin need to be included in the follow-up studies, as this pilot project relied on only two locations. Finally, the oldest and most established markers (Sfo8, Sfo12, Sfo18, and Sfo23; Angers et al, 1995) should be included in any follow-up research to promote consistency, as they are widely used and familiar to scientists within the “trout community.”

This personal experience with scientific research was incredibly rewarding to me for many reasons. Coming out of my sophomore year in high school, I had an incredible opportunity to do research in a university-level genetics laboratory. I met intelligent, educated, skilled, creative people who were knowledgeable about all aspects of our natural environment. My personal gain has definitely been greater than the experience of doing the study itself. One of the many effects the study had on me was in highlighting the disturbing observation that introducing non-native species of any kind (plants, animals, insects) into a new environment can have disastrous effects on that habitat. In this example, stocking Lake Champlain with non-native brown trout is resulting in the creation of sterile tiger trout, which means that not only is there a whole new species of fish in Lake Champlain, but also the long-term survival of the native brook trout species is in danger. This is the Vermont State fish! This is the New York State fish! Why is this happening? Why isn’t the lake being stocked with native brook trout to keep the ecosystem stable? Are brown trout cheaper to purchase? Biologists need to have more of a voice in such decisions, and educate the politicians and the people who make these decisions. The focus on spending less money means less caution about preserving our natural habitats, which in turn harms the fishing industry in our region, which in turn hurts the economy of this small rural state. This is a huge chain reaction! My study has increased my awareness of the issue. Even though I am just one person, I can raise awareness by discussing this issue and the study’s results.

Use of Vertebrates

For my project, trout samples were collected in their natural environment very carefully; after a very small fin clipping was taken while we were standing in the brook, the trout were released back into the water. I was mentored by two fish biologists in the field: Madeleine Lyttle, from the U.S. Department of Fish and Wildlife, who had permits and permissions from the State of Vermont for the capture and release of fish samples; and Dr. Timothy Mihuc, director of the Lake Champlain Research Institute, who had permits and permissions for the capture and release of fish samples from New York State.


I give special thanks to wildlife biologist Madeleine Lyttle, from the U.S. Department of Fish and Wildlife in Vermont, and Dr. Timothy Mihuc, director of the Champlain Research Institute in New York, for accompanying me to my collection sites and teaching me how to collect samples from fish and do no harm. Thanks also to everyone on my research team who made being out in the field such a fun adventure. My most special and heartfelt thanks are saved for Dr. Nancy Elwess, my mentor, advisor and friend, who guided me through this experience, permitted me to use the equipment in her molecular genetics laboratory, and who, without reservation, allowed me to enter the world of genetics.


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Angers, Bernard, Louis Bernatchez, Annie Angers, and L. Desgroseillers. “Specific microsatellite loci for brook charr reveal strong population subdivision on a microgeographic scale.” Journal of Fish Biology 47, Supp. A (1995): 177-185.

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Perry, Guy, Tim King, Jerome St-Cyr, Manon Valcourt, and Louis Bernatchez. “Isolation and cross-familial amplification of 41 microsatellites for the brook charr (Salvelinus fontinalis).” Molecular Ecology Notes 5 (2005): 346-351.

Presa, Pablo, and Rene Guyomard. “Conservations of microsatellites in three species of salmonids.” Journal of Fish Biology 49 (1996): 1326-1329.

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Stott, Wendylee, Henry Quinlan, Owen Gorman, and Tim King. “Genetic structure and diversity among brook trout from Isle Royale, Lake Nipigon, and three Minnesota tributaries of Lake Superior.” North American Journal of Fisheries Management 30.2 (2010): 400-411.

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