Genetic Structure at the Major Histocompatibility Complex
in the Endangered Barrens Topminnow (Fundulus julisia)
Carla Hurt, Natalie Ellis, Alexis Harman, and Courtney Savage
Southeastern Naturalist, Volume 18, Issue 1 (2019): 19–36
Full-text pdf (Accessible only to subscribers.To subscribe click here.)
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C. Hurt, N. Ellis, A. Harman, and C. Savage
22001199 SOUTHEASTERN NATURALIST Vo1l8.( 118):,1 N9–o3. 61
Genetic Structure at the Major Histocompatibility Complex
in the Endangered Barrens Topminnow (Fundulus julisia)
Carla Hurt1,*, Natalie Ellis1, Alexis Harman1, and Courtney Savage1
Abstract - Genetic diversity at the Major Histocompatibility Complex (MHC)
is particularly important for species viability as it allows populations to respond
to emerging pathogens and infectious disease. Patterns of variation at this gene
complex serve as a useful complement to information obtained from neutral loci
for planning management and conservation strategies that seek to ensure the adaptive
potential of at-risk species. In this study, we investigated patterns of genetic
variation at exon 2 of the MHC class II gene in the critically endangered Fundulus
julisia (Barrens Topminnow). This species has undergone dramatic declines over
the last 30 years, leading to its recent proposal for federal protection under the Endangered
Species Act. Patterns of nucleotide substitution and phylogenetic analyses
revealing trans-species polymorphisms suggest that this locus has been of adaptive
importance in the history of this species. Despite recent population declines and
documented population bottlenecks, measures of genetic diversity were high in
comparison to patterns observed at putatively neutral microsatellite and mitochondrial
markers. Results from this study are discussed in the context of recovery plans
for the Barrens Topminnow and lend support to the previous designation of evolutionary
significant units and management units based on neutral markers.
Introduction
The preservation of adaptive genetic variation is a fundamental consideration
for establishing and prioritizing management units at or below the species level.
Selectively neutral genetic markers such as microsatellites or single nucleotide
polymorphisms (SNPs) are valuable for determining the demographic histories
and distinctiveness of populations. However, neutral markers may not necessarily
reflect evolutionarily relevant and adaptive processes (Cote et al. 2005). For
example, studies in primates have demonstrated a correlation between a specific
MHC supertype and parasite burden, despite a lack of association between overall
neutral genetic diversity and overall parasite load (Schwensow et al. 2007). Patterns
of nucleotide diversity at the major histocompatibility complex (MHC) suggest that
this gene family is particularly important for adaptive fitness in vertebrates (Sommer
2005). MHC class II genes code for proteins that are expressed on the surface
of antigen-presenting cells, where they present exogenously derived antigens to
CD4+ T helper cells, triggering an immune response. MHC variants may influence
1Department of Biology, Tennessee Technological University, Cookeville, TN 38505. *Corresponding
author - churt@tntech.edu.
Manuscript Editor: Benjamin Keck
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susceptibility to infectious diseases (Harf and Sommer 2005, Wegner 2003), autoimmune
responses (Ridgway et al. 1999), mate recognition (Wedekind et al. 1995),
and maternal–fetal interactions (Schmidt et al. 1993, see Ujvari and Belov 2011 for
further review). As evidence of their functional importance, genes within MHC are
the most polymorphic loci known in vertebrates, with as many as 349 identified
alleles at a single locus (Robinson et al. 2000). Reduction of functional genetic
diversity is a threat to many endangered species as it can increase susceptibility to
infectious disease and parasites (Edwards and Potts 1996). MHC variability reflects
adaptive processes within and between populations and can be used to inform management
strategies that prioritize the maintenance of adaptive genetic variation of
endangered species.
Fundulus julisia Williams and Etnier (Barrens Topminnow [BTM]) has undergone
a dramatic decline since the 1980s. Historically, populations of BTM
were known from 3 separate drainages in the Barrens plateau region of middle
Tennessee: Duck River, Elk River, and Caney Fork. Prior to 1993, a total of 20
populations throughout all 3 drainages were known to occur (Etnier 1983); these
numbers dropped to only a few hundred adults at 7 localities by 1995 (Rakes 1996).
Currently, natural populations are known to persist in only 3 areas within the Collins
River of the Caney Fork Drainage (Fig. 1; Kuhajda et al. 2014). BTM generally
Figure 1. Location of
5 native sites sampled
for genetic analysis:
McMahan Creek (n =
3), Pedigo Highway
(n = 15), Pedigo Farm
(n = 16), Benedict
Spring (n = 14), and
Pond Spring (n = 15).
Star on map inset indicates
Nashville, TN.
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2019 Vol. 18, No. 1
inhabit small, spring-fed ponds or streams and are vulnerable to any activity that
disturbs groundwater quality or quantity. While loss of habitat has negatively impacted
BTM populations, their most significant threat has been the introduction
of Gambusia affinis (Baird and Gerard) (Western Mosquitofish) throughout their
range. Mosquitofish jeopardize the persistence of BTM primarily through predation
of juveniles and aggression towards and harassment of adults (Laha and Mattingly
2007). Western Mosquitofish invasion of middle Tennessee has occurred over the
past 60 years, and the species was confirmed in the Barrens Fork River system in
the 1980s (Etnier and Starnes 2001). All locations where BTM populations had
been extirpated and that possessed ideal habitat for BTM had become inhabited by
mosquitofish (Rakes 1989, 1996). In response to its dramatic decline, in January
2018 the US Fish and Wildlife proposed to list the BTM as an endangered species
under the Endangered Species Act (USFWS 2018).
Fortunately, conservation efforts for the species began in 2001; these efforts
have included propagation of captive populations and the establishment of new
populations throughout the historical species range (Hurt et al. 2017). To ensure
long-term effectiveness of these continuing recovery efforts, maintenance of
remaining adaptive genetic variation should be prioritized. Information on the
patterns of genetic variation within and between populations is necessary for determination
of evolutionarily significant units (ESUs) and management units (MUs)
within species (Waples 1995) that help to prioritize conservation needs.
Surveys of genetic variation at putatively neutral loci (mitochondrial control
region and microsatellites) suggest that population declines in BTM have led to a
reduction of overall genetic variation (Adams et al. 2006, Feldheim et al. 2014, Hurt
et al. 2017). Population-level sequence analysis at a portion of the mitochondrial
control region showed that all surveyed natural and introduced populations within
the Caney Fork and Duck River drainages share a single haplotype. Individuals
from the Elk River drainage were polymorphic for 2 unique haplotypes that differed
by a single base substitution and a 1 base-pair (bp) indel from the Caney Fork
haplotype. Surveys at 14 polymorphic microsatellite loci also showed low levels of
heterozygosity within populations relative to observations from other congeneric
species. There was significant structuring of microsatellite allele frequencies across
loci indicating that Elk River BTM should be managed as a distinct ESU (Hurt et
al. 2017). However, nothing is known for BTM about levels of genetic diversity
and partitioning of genetic variation in putatively adaptive regions of the genome.
Patterns of variation and divergence at adaptive loci frequently differ from patterns
observed in neutral markers (Pfrender et al. 2000, Ujvari and Belov 2011). Balancing
selection may counteract the effects of genetic drift in small populations and
retain functionally important diversity at regions of the genome under selection
(Aguilar et al. 2004).
Here we examine patterns of genetic variation at a class II MHC B gene from
the 3 remaining natural populations (4 sites) and 1 recently extirpated population of
BTM. We looked for evidence of historical balancing selection by comparing levels
of heterozygosity at MHC to heterozygosity estimates obtained from microsatellite
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loci in the same populations. We also compared partitioning of genetic variation
between populations to test for evidence of differential selection at MHC compared
to neutral loci in geographically isolated populations of BTM. Results from this
study are interpreted in the context of management and conservation planning.
Materials and Methods
A total of 63 individuals from the 5 remaining natural sites of BTM were sampled
for the present study (Fig. 1). These include 4 extant sites in the Collins River
of the Caney Fork drainage: Benedict Spring, Pedigo Farm, Pedigo Highway, and
McMahan Creek. In addition, we included samples from the recently extirpated
population at Pond Spring in the Elk River drainage. Fin clips were obtained during
routine monitoring of populations by collaborators at the Tennessee Aquarium in
Chattanooga, TN. Tissues from Pond Spring fish were collected by USFWS in 2011
prior to the apparent extirpation of this population. All DNA samples used in this
work were used in a previous study, where they were genotyped at 14 microsatellite
loci (Hurt et al. 2017). Samples from the Duck River were not available for study
as no Duck River BTMs are known to exist in the wild or in captivity. Tissues were
stored in 95% ethanol at -20 °C prior to extraction of DNA. We isolated DNA from
fin clips using a modification of the protocol by Wang and Storm (2006) and diluted
the samples to a concentration of 50–100 ng/μl.
PCR amplification of the MHC class II B gene utilized a newly designed forward
primer, Fuju-408 (5’- CTGATCAGCTGTTTATTCAGAGTC -3’), and degenerate
reverse primer MRS (5’- RCTYACCTGATTTAKMCAGA -3’), designed for the
congeneric Fundulus heteroclitus (L.) (Mummichog) (Cohen 2002). These primers
amplify the 3’ end of intron 1 and nearly all of exon 2 in the β1 unit, with the
exception of 14 bases at the 3’ end of exon 2 that are included in the primer sequence.
We selected this region for study as it is thought to code for functionally important
peptide binding region (PBR; Sommer 2005). For the PCR reaction, we followed
manufacturer’s recommended conditions using Q5 High-Fidelity DNA polymerase
in a 50-μl reaction. PCR cycling conditions were 98 °C for 30 s; 35 cycles at 98 °C for
10 s, 54 °C for 30 s, and 72°C for 30 s; and a final extension at 72 °C for 2 minutes.
We ligated PCR products into NEB PCR cloning vector (New England Biolabs,
Ipswich, MA). We screened clones in PCR reactions with cloning analysis forward
and reverse primers (New England Biolabs). We selected between 8 and 16 clones
of the appropriate sizes for sequencing and cleaned them using shrimp alkaline
phosphatase-exonuclease reaction prior to cycle sequencing on an ABI 3730 automated
sequencer (MCLAB). We imported and visualized sequence chromatograms
using SEQUENCHER version 5.2 (Gene Codes Corp., Ann Arbor, MI). Sequences
were exported to the program Bioedit (Hall 1999) and aligned using the ClustalW
multiple alignment algorithm (Larkin et al. 2007), and we adjusted the alignment
by eye.
We aligned all sequenced clones to each other and to sequences generated directly
from genomic PCR amplification to obtain individual genotypes. We checked individual
alignments for PCR recombination events and for PCR errors that can arise
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during sequencing of cloned PCR products. We identified recombinant products as
sequences in which the first segment was identical to one allele and the second segment
was identical to a different allele, and PCR errors as sequences that differed by
1–2 nucleotides from redundant sequences and contained peaks that were not corroborated
by sequences generated from PCR from genomic template DNA.
Statistical analysis
Variation at MHC within populations. Population allele frequencies, observed
and expected heterozygosities (Ho and He), and FIS values were estimated with the
program FSTAT (Goudet 1995). We performed tests for Hardy-Weinberg equilibrium
with the program Genepop 4.7 (Rousset 2008), and characterized genetic
diversity using allelic richness with the program FSTAT and nucleotide diversity
using the program Arlequin (Excoffier et al. 2005).
Tests for selection. We tested selection at the MHC using 3 different methods.
First, we calculated the ratio of non-synonymous to synonymous substitutions
(dN/dS). If nonsynonymous mutations are maintained in populations by balancing
selection and/or positive selection, then ω is predicted to be greater than 1. We used
the Nei-Gojobori method with Jukes Cantor correction to calculate the overall average
ω for all sites, the peptide binding region (PBR), and non-PBR separately as
implemented in MEGA 5 (Tamura et al. 2011). We inferred the PBR codons from
the human model of the MHC class 2 DRB1 locus (Fig. 2; Brown et al. 1993). We
determined the significance of dN > dS using a Z-test for selection where the null
hypothesis is dN - dS = 0.
Next, we used a maximum likelihood method (Yang et al. 2005) to identify
individual codons under selection using the program CODEML (Yang 1997). In
this approach, a likelihood-ratio test (LRT) is used to compare 2 pairs of models
of sequence evolution. In the first pair of models, the M1 (nearly neutral) model
experiences weak purifying selection, so that ω can vary between <1 and 0, and the
M2 (selection) model is an extension of M1 where a proportion of sites experience
positive selection (dN/dS >1). In the second pair of models, the M7 (beta) model
allows ω to vary in a beta distribution between 0 and 1, while the M8 (beta dN/dS)
model extends the M7 model and accounts for positive selection by assigning a
Figure 2. Amino acid sequences inferred from DNA sequences of BTM class II B exon 2.
Inferred PBR sites are indicated at the top of the alignment with asterisks. Numbering corresponds
with the mature protein (Ono et al. 1993). Highlighted/shaded columns indicate
sites with codons that were significant for positive selection using the Bayesian Empirical
Bayes (BEB) method for both model M2 and model M8.
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subset of sites with ω > 1. A LRT is used to compare the M1 model to the M2
model and to compare the M7 model to the M8 model. Positive selection is inferred
if the difference in log-likelihood values between the 2 models is greater than the
χ2 critical value with df = 1. We then used the Bayes empirical Bayes (BEB) approach
to identify the subset of codons that had experienced positive selection
(Yang et al. 2005). Using MEGA, we constructed a neighbor-joining tree under the
Kimura-2-parameter model of nucleotide substitution to use as an input phylogeny
for CODEML analyses.
Finally, balancing selection can alter the distribution of allele frequencies in
populations. Specifically, under balancing selection, alleles are maintained at intermediate
frequency resulting in a positive value for Tajima’s D, which we calculated
using the software DNAsp v6.10.01 (Rozas et al. 2003). We obtained statistical
significance of the D statistic using a 2-tailed test and assuming that D follows a
beta distribution (Tajima 1989).
Phylogenetic analysis. We estimated phylogenetic relationships among MHC
alleles within BTM by employing the neighbor-net algorithm based on Kimura
2-parameter genetic distance using the software SplitsTree 4.14.5 (Huson and Bryant
2006). Traditional phylogenetic methods may not appropriately represent the
history of MHC alleles due to incompatible phylogenetic signals. This approach
may more accurately reflect the relationships between alleles at the MHC as it reveals
conflicting signals that result from gene conversion and r ecombination.
In a second analysis, we blasted alleles found in BTM against all Fundulus
alleles available in GenBank to detect instances of shared functional variation
across the genus. We used maximum likelihood and Bayesian phylogenetic reconstructions
to explore how BTM alleles are related to congeneric heterospecific
MHC alleles. The best-fit model of nucleotide substitution was determined as the
Kimura 2-parameter Gamma model using Bayesian Information Criterion (BIC)
as performed by MEGA. We performed the maximum likelihood reconstruction
in MEGA with 5000 bootstrap replicates, and the Bayesian reconstruction
in MrBayes 3.2 (Ronquist and Huelsenbeck 2003). We performed 2 independent
runs of 4 Metropolis coupled Markov chain Monte Carlo for 1 × 107 generations
and sampled every 1000 generations. The burn-in fraction was set at 0.25, resulting
in 15,000 trees.
Population differentiation and comparisons with microsatellites
To investigate differences in partitioning of putatively adaptive and neutral genetic
variation, we used a hierarchical analysis of molecular variance (AMOVA;
Weir and Cockerham 1984) performed separately for microsatellites and MHC
sequence data. We used ɸ-statistics to estimate the proportion of genetic variation
found among populations (ɸ ST), among populations within drainages (ɸSC), and
among drainages (ɸCT). We evaluated significance of the fixation indices through
random allelic permutation (1000 permutations).
We evaluated the correlation between measures of population differentiation
at microsatellites and MHC by performing a Mantel test on estimates of pairwise
FST values between all populations using the R package Ecodist (Goslee 2007).
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For microsatellite genotype data, Weir and Cockerham’s (1984) estimator of FST
values between all pairs of populations was calculated in FSTAT 2.9.3.2 (Goudet
1995). We calculated pairwise MHC FST values in Arlequin using only haplotype
frequency data.
Results
MHC sequences and polymorphism
A total of 63 individuals were cloned and sequenced for a 398-bp amplified gene
fragment. Comparisons with other Fundulus species confirmed that the amplified
sequences are from the exon 2 of a class II MHC gene. No stop codons or indels
were detected within the exon region, and a maximum of 2 alleles were detected
within an individual. Thus, the alleles found in this study are inferred to represent
a single functional locus. This finding is consistent with MHC class II surveys in
the congeneric Mummichog, which showed amplification of a single locus using
the same reverse primer and a species-specific forward primer .
A total of 12 unique alleles were identified across the 5 sampled populations
(Table 1; Genbank accessions MK391390–MK391401). The number of alleles per
population varied from 2 in McMahan Spring to 6 in Pond Spring. Pond Spring
possessed 4 private alleles not sequenced in other populations. Benedict Spring
and McMahan Spring both possessed a single private allele. All other alleles were
shared across multiple populations. Tests for Hardy–Weinberg equilibrium detected
a significant deficiency of heterozygotes in 2 populations (Pond Spring and Pedigo
Highway). Allelic richness was highest for Pond Spring (AR = 3.66) and lowest for
McMahan Spring (AR = 2.00), averaging 2.83 across the 5 populations examined
(Table 2). Nineteen of the 84 amino-acid positions examined were variable (22.6%)
(Fig. 2). The proportion of variable amino acids at putative binding sites was higher
(29.2%; 7 out of 24 sites) than the proportion of variable amino acids at non-peptide
binding sites (20.0%; 12 out of 60 sites). Nucleotide diversity was highest for Pond
Table 1. The frequency of the 12 MHC alleles found in 63 individuals from the 5 natural Fundulus
julisia (Barrens Topminnow) sites. Sample sizes are shown in parentheses next to site names.
Sites
Allele Benedict (14) McMahan (3) Pedigo F. (16) Pedigo H. (15) Pond (15) Mean
Fuju001 0.679 - - - - 0.136
Fuju002 0.107 - 0.219 0.100 - 0.085
Fuju003 0.036 0.333 0.281 0.667 0.167 0.297
Fuju004 0.143 - 0.094 0.067 - 0.061
Fuju005 0.036 - - - - 0.007
Fuju006 - 0.667 - - - 0.133
Fuju007 - - 0.375 0.167 - 0.108
Fuju008 - - 0.031 - 0.133 0.033
Fuju009 - - - - 0.233 0.047
Fuju010 - - - - 0.367 0.073
Fuju011 - - - - 0.067 0.013
Fuju012 - - - - 0.033 0.007
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Spring (π = 0.034) and lowest for Pedigo Highway (π = 0.011), averaging 0.023
across populations.
Tests for selection
The average nonsynonymous distance (dN) was greater than the average synonymous
distance (dS) for both PBR codons and non-PBR codons; however, this
difference was only significant for non-PBR segments (Table 3). The dN/dS ratios
for PBR and non-PBR codons were 1.265 (P = 0.305) and 4.083 (P = 0.014), respectively.
The LRT for models M1 (ln L = -643.14) and M2 (lnL = -619.59) and
for models M7 (lnL -644.89) and M8 (lnL = -623.71) were significantly positive
(P < 0.0001) for both tests indicating the evidence of positive selection at a subset
of sites within the sequence alignment. In the BEB analysis, the same subset of 13
codons showed evidence of positive selection with both the M2 and M8 model.
Six of these codons (3, 7, 32, 55, 80, 83) were within putative PBR in the exon,
while the remaining 7 codon (6, 23, 30, 33, 56, 81, 84) were not part of the putative
PBR. However, all 7 of the positively selected codons not part of the putative
PBR were directly adjacent to putative PBR codons. Estimates of Tajima’s D were
positive for all populations; however, statistically significant estimates were only
obtained for 2 populations, Benedict Spring and Pedigo Farm.
Phylogenetic reconstruction
The neighbor-net network analysis resulted in a boxed network implying that
conflicting signals were present in the dataset and suggesting that recombination
Table 3. Results from the dN/dS ratio test for selection in five natural sites of Fundulus julisia (Barrens
Topminnow), presented separately for all codons, PBR codons and non-PBR codons.
All PBR Non-PBR
Statistic codons codons codons
Mean number of synonymous differences between sequences 1.58 1.50 0.43
Mean number of non-synonymous differences between sequences 10.91 4.28 6.62
Substitutions per synonymous site (dS) 0.029 0.068 0.012
Substitutions per non-synonymous site (dN) 0.059 0.086 0.049
dN/dS 2.034 1.265 4.083
Z 0.029 0.511 2.237
P-value 0.013 0.305 0.014
Table 2. Summary of genetic variability at MHC: sample size (n), number of alleles (NA), allelic
richness (AR), nucleotide diversity (π), observed heterozygosity (Ho), expected heterozygosity (He),
inbreeding coefficient (FIS), Tajima’s D (D). Significance denoted by *P < 0.05, **P less than 0.01.
Site n NA AR π Ho He FIS D
Benedict Spring 14 5 2.60 0.027 0.36 0.52 0.37 1.958*
McMahan Creek 3 2 2.00 0.022 0.00 0.53 1.00 1.337
Pedigo Farm 16 5 3.31 0.020 0.75 0.75 -0.01 2.907**
Pedigo Highway 15 4 2.57 0.011 0.13 0.53 0.76* 0.119
Pond Spring 15 6 3.66 0.034 0.47 0.79 0.42* 1.189
Mean 4.40 2.83 0.023 0.34 0.62
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between alleles and/or gene conversion may have occurred (Fig. 3A). The allele
Fuju009 was connected by a single long edge to all other BTM alleles and was
exclusively identified in Pond Spring.
The Mummichog was the only other species within the genus Fundulus for
which homologous MHC class II alleles were available. Although there were no
shared alleles between the 2 taxa, traditional phylogenetic reconstructions of all
27 recovered Mummichog MHC alleles and the 12 BTM alleles revealed multiple
instances of polyphyly from both maximum likelihood (data not shown) and
Figure 3. (A) SPLITSTREE neighbor network of 12 MHC alleles identified from BTM.
(B) Bayesian reconstruction of 12 MHC alleles from BTM and Fundulus alleles from
Genbank. Triangles denote sequences obtained from BTM. Posterior probabilities shown
for nodes with 95% support or greater. Taxonomic identifiers for sequences from Genbank
correspond to Genbank accession numbers.
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Bayesian reconstructions (Fig. 3B). Specifically, the BTM allele Fuju009 was
more closely related to 3 alleles from Mummichog (Genbank accession numbers
AF529617, XM_012860333, AF529588) than to other BTM alleles. BTM alleles
Fuju001 and Fuju006 formed a clade with 2 Mummichog alleles (Genbank accession
numbers XM_012860362 and XM_021314911). Finally the Mummichog
alleles XM_012860177 and XM012860241 were part of a well-supported clade in
both ML and Bayesian topologies that included all 12 BTM alleles. Alleles found
within BTM did not cluster by population; 5 out of the 12 BTM alleles were shared
across multiple BTM populations.
Population differentiation and comparison with microsatellites. Results from
AMOVA of microsatellite genotype data indicated that genetic variation was
partitioned both by drainages (21%) and by populations within drainages (23%)
(Table 4). All variance components were significantly greater than zero, and the
overall ɸST at microsatellites was 0.436. The AMOVA results for MHC sequence
data indicated less structuring by populations and drainages than results from
microsatellite data (Table 4). The percent of variation attributed to differentiation
among drainages was slightly negative (-0.18%), which can occur by chance in the
absence of genetic structure. Differentiation between populations within drainages
accounted for 32% of the total variation. The fixation indices ɸSC and ɸST were both
significantly greater than zero; however, ɸCT was not significant. The overall ɸST at
MHC was 0.313, slightly less than what was found at microsatellite markers.
Patterns of population differentiation in putatively adaptive MHC markers
mirrored what was found at microsatellites (Fig. 4). Pairwise FST values for the 2
classes of marker were significantly correlated (rM = 0.849, P = 0.020). Average
pairwise FST values across all population comparisons were higher for microsatellite
genotypes than for MHC sequences (0.421 and 0.299, respectively), indicating
that populations were more divergent, on average, at microsatellite loci than at this
MHC gene.
Table 4. Summary of the AMOVA results that partition genetic variation of the MHC class II alleles
among 5 populations of Fundulus julisia (Barrens Topminnow). The significance values for fixation
indices were obtained by permutation of alleles 1023 times.
Sum of Variance % Fixation
Source of variation d.f. squares component variation indices P-value
Microsatellites
Among drainages 1 82.99 0.583 Va 20.62 ɸCT = 0.206 0.202
Among populations within drainages 3 61.14 0.612 Vb 23.01 ɸSC =0.290 < 0.001
Within populations 191 286.20 1.498 Vc 56.37 ɸST = 0.436 < 0.001
Total 195 430.33 2.658
MHC
Among drainages 1 58.68 -0.010 Va -0.18 ɸCT = 0.002 0.401
Among populations within drainages 3 137.40 1.858 Vb 31.47 ɸSC = 0.314 less than 0.001
Within populations 121 490.72 4.055 Vc 68.72 ɸST = 0.313 less than 0.001
Total 125 686.79 5.903
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Discussion
Implementing evolutionary principles into effective conservation of at-risk species
requires an understanding of patterns of adaptive variation within and among
populations. Here we present results from an examination of diversity, selection,
and population structure of a putative adaptive locus, exon 2 of the MHC class II
B gene, in the imperiled BTM. Because of the dramatic decline of this species,
conservation planning requires a multifaceted approach that includes artificial
propagation, translocations, and habitat improvement. Identification of source
populations for captive stocks and translocations, and prioritization of populations
for habitat monitoring and improvement should consider the ability of species and
populations to respond to selection. Our survey provides a first glimpse at the organization
of adaptive genetic variation in the BTM that can be used as a guide for
informing conservation practices that will maintain adaptive potential of BTM.
Genetic diversity at the MHC
Levels of allelic variation among the 5 surveyed sites of BTM were moderate
compared to observations from the congeneric Mummichog. We identified 12
unique alleles from 64 individuals of BTM. In a similar survey of MHC class II B
gene in 5 populations (42 individuals) of Mummichog, 41 unique alleles were identified,
so that only a few alleles were found more than once in different individuals
Figure 4. Correlation between the levels of genetic differentiation (pairwise FST) between
populations of BTM for microsatellite genotypes and MHC sequence data.
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(Cohen 2002). However, Mummichog is likely to harbor greater levels of genetic
variation overall as it is a widespread species known for its hardiness and tolerance
to environmental change, and is likely to support larger populations. MHC surveys
in other imperiled fishes with restricted habitats and similar histories of population
decline to the BTM report lower levels of allelic diversity, comparable to what we
observed here. In a survey of 5 relict lineages (103 individuals) of the threatened
Oncorhynchus gilae gilae (Miller) (Gila Trout) only 5 unique alleles were identified
across all populations. In the federally endangered Poecilliopsis occidentalis (S.F.
Baird and Girard) (Gila Topminnow), Hedrick and Parker (1998) describe 9 unique
alleles identified from 40 individuals across 4 populations. Allelic diversity at the
MHC in the BTM is likely limited by its inherently small population sizes as well
as a recent history of demographic decline.
Despite moderate allelic diversity relative to MHC surveys in more widespread
species, levels of expected heterozygosity at the MHC were significantly higher
than heterozygosity estimates from putatively neutral microsatellite loci at the same
populations. The average expected heterozygosity for microsatellites and for MHC
across the 5 study sites was 0.333 and 0.624, respectively (1-way ANOVA: P =
0.012). Mitochondrial variation was also remarkably low; 4 out of 5 of the natural
populations examined here were fixed for a single mitochondrial control region
haplotype (Hurt et al. 2017). Collectively these results are consistent with the selective
maintenance of genetic variation at the MHC above background neutral loci.
Selection at the MHC
Tests for balancing selection at the MHC can be categorized as tests that detect
selection over the history of species and tests that allow detection of selection in
contemporary populations and in the current generation. We found multiple lines
of evidence that positive and/or balancing selection has influenced patterns of
MHC diversity over species and population timescales; however, evidence for
selection in the present generation is lacking. The most commonly applied test
for positive selection on evolutionary timescales is the test for dN/dS > 1. It was
significantly greater than 1 when considering the entire codon sequence and in the
LRT comparing models with and without selection. However, it is not possible to
pinpoint the timing of this selection as mutational events that result in elevated
dN/dS ratios can take hundreds of thousands of generations to accumulate, and
these patterns can take even longer to be erased (Garrigan and Hedrick 2003).
Secondly, the retention of ancestral polymorphisms that result in polyphyletic
topologies in gene trees spanning multiple related species is also interpreted as
evidence of balancing selection (Klein et al 1998). Again, the timing of processes
that result in trans-species polymorphisms span species boundaries and do not
necessarily imply recent selection.
Selection at MHC over the history of populations may shape the extent of
population subdivision and result in patterns of population differentiation that differ
from patterns found at neutral loci. Under balancing selection, differentiation
between populations is predicted to be reduced compared to neutral loci because
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2019 Vol. 18, No. 1
(1) fewer alleles are lost to drift as alleles are kept at equal frequencies and
(2) incoming migrant alleles may be selected for and successfully maintained in
a population (Schierup et al. 2000). In the BTM, comparisons between measures
of population structure at MHC show reduced differentiation at the population
level relative to patterns from microsatellite loci. Results from the AMOVA
analysis show that at the MHC, sequence variation is not partitioned by drainages,
and 69% of the variance is found within populations compared to 56% for
microsatellites. Pairwise FST values were highly correlated for MHC and microsatellites;
however, BTM populations were more divergent at microsatellites
than at MHC. Finally, within the current population, an excess of heterozygotes
relative to expectations under Hardy–Weinberg proportions is expected under
balancing selection. We did not find an excess of heterozygosity in any of the
populations examined; instead, 2 out of 5 populations showed a heterozygote
deficiency. Collectively, these results suggest that selection at the MHC has
historically influenced patterns of nucleotide substitutions at some time in the
history of this species and may have reduced that overall level divergence among
populations. However, correlations of pairwise FST values imply that random genetic
drift has also shaped patterns of differentiation between populations at the
MHC and may be overriding selection in the current population.
One unexpected result from the analysis of patterns of nucleotide substitution
was the elevated dN/dS ratio in non-PBR codons within the MHC exon. Typically
dN/dS ratios are highest at sites that interact with foreign peptides (Aguilar and
Garza 2006, Bernatchez and Landry 2003, Cohen 2002). Surprisingly we found
dN/dS to be only slightly, but non-significantly, elevated at PBR sites, and higher
dN/dS were recovered at non-PBR regions. In addition, of the 13 sites identified as
being under selection in the BEB analysis, 7 were not part of the PBR but were
next to PBR codons. Similar results were obtained in a study of MHC variation
in Gila Trout where dN/dS was elevated in codons adjacent to putative PBR sites
that were identified by alignment with human HLA-DR1 genes (Peters and Turner
2008). These results cast doubt on the identity of the PBR codons in BTM and suggest
that models of MHC protein structure in humans may not adequately describe
functional peptide-binding sites in other species.
Population structure and units of conservation
The designation of ESUs and MUs below the species level should incorporate
information about both the adaptive differences between populations as well as
patterns at neutral markers (Hedrick et al. 2001). Partitioning of alleles among populations
at the MHC support the previous recommendation based on microsatellite
and mitochondrial markers that Pond Spring be managed as a separate ESU. Pond
Spring possessed the most private alleles of any of the natural sites examined here.
Four of the 6 alleles identified from Pond Spring were unique to this site, including
the allele Fuju009, which was highly diverged in the neighbor-net reconstruction
and formed a clade with Mummichog alleles in the Bayesian analysis (Fig. 3). Pond
Spring was also the most genetically diverse population at MHC as measured by
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2019 Vol. 18, No. 1
32
allelic richness (AR = 3.66), expected heterozygosity (He = 0.79), and nucleotide
diversity (π = 0.034). Unfortunately, surveys over the last 3 years indicate that this
population has been extirpated, most likely due to occupation of this site by Western
Mosquitofish (Kuhajda 2014). However, captive populations initiated with brood
fish from this site are currently being maintained, and a number of stocked populations
have been initiated from this captive population. Our results emphasize the
importance of the continued maintenance of this lineage.
Our results also support the earlier recommendations based on microsatellites
and mitochondrial loci of 2 separate MU’s within the Caney Fork River drainage.
The first MU would include Benedict Spring site, which is formed by a spring
emanating from a cave in the headwaters of the West Fork of Hickory Creek and is
the type locale for the species (Goldsworthy and Bettoli 2005). Here we identified
2 unique alleles not found in any other BTM population. Benedict Spring had the
highest average pairwise FST estimate (0.40 ) at the MHC, due to the high frequency
of the unique allele Fuju001. This site has undergone a series of bottlenecks due to
recent droughts; this spring has dried up 3 times since 2006. During each drought,
between 120 and 1000 fish were removed and held in captivity until they could be
returned (Kuhajda 2014). Likely as a result of these bottlenecks, Benedict Spring
possessed the lowest levels of genetic variation at microsatellites of any natural
population. At the MHC, however, this site demonstrated substantial diversity (π =
0.027, He = 0.52) consistent with balancing selection maintaining functional allelic
diversity despite demographic declines and loss of neutral variation. Benedict
Spring has also served as a source for brood fish for a separate captive population
that has been used to stock numerous sites within the historical distribution of
BTM. The second MU within the Caney Fork is composed of the Pedigo Farm and
Pedigo Highway sites, which are adjacently located in Lewis Creek within the Barren
Fork watershed. These 2 sites possessed nearly overlapping sets of alleles and
both shared a private allele (Fuju007) not found at other sites. Due to the limitation
of available tissues samples, we are unable to make robust conclusions about
the genetic structure of McMahan Spring. It is worthwhile to note that 2 out of 3
individuals possessed a unique allele, Fuju006, suggesting that this allele is likely
to be at high frequency in this population, although further sampling of this site is
needed to assess the genetic composition of this population. In general, results from
our survey of MHC lend support for the designation of conservation units based on
microsatellite and mitochondrial markers.
Conclusions
Information on patterns of adaptive genetic variation is increasingly playing a
role in conservation and management planning for imperiled species (Gebremedhin
et al. 2009). Genes from the MHC offer unparalleled opportunity for understanding
adaptive differences in natural populations (Bernatchez and Landery 2003, Ujvari
and Belov 2011). Results from this survey of a single MHC locus in the endangered
BTM suggest that this gene has been of adaptive significance in the history of the
species, although drift likely also influenced current patterns of differentiation.
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C. Hurt, N. Ellis, A. Harman, and C. Savage
2019 Vol. 18, No. 1
Recent demographic declines have reduced neutral variation as evidenced at both
microsatellite and mitochondrial markers, yet substantial allelic diversity was found
at the MHC. Nevertheless, information provided by any single locus survey may not
reflect the genome as a whole. Management decisions should take into account as
many genetic markers as possible. As genomic tools continue to be applied to nonmodel
systems, we expect to see a shift away from analysis of single candidate genes
towards the identification and surveys of genome-wide neutral and adaptive loci that
enable monitoring of microevolutionary processes in at-risk species.
Acknowledgments
We thank Bernard Kuhajda, the Tennessee Aquarium, and Conservation Fisheries Inc.
for obtaining tissue samples of BTMs. We thank Robert Paine for construction of maps
used in this publication. We also thank Philip Hedrick for providing comments on an earlier
version of this manuscript. Funding for this project was provided by the US Fish and
Wildlife service and by the URECA program at Tennessee Technological University.
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