Genetic characterization of Atlantic blue crab (Callinectes sapidus) in Charleston Harbor, South Carolina.
KEY WORDS: Callinectes Sapidus, Atlantic blue crab, population genetics, genetic health
The Atlantic blue crab (Callinectes sapidus', hereafter blue crab) is a common decapod crustacean found in estuarine and nearshore waters from Nova Scotia in Canada to Rio de la Plata in Argentina, including the entire coast of the Gulf of Mexico and throughout the Caribbean Sea (Williams 1974). Mating occurs in the early spring to late fall (February-November, depending on latitude; Van Engel 1958, Tagatz 1968, Williams 1971, Jaworski 1972, Perry 1975, Eldridge & Waltz 1977) in low-salinity portions of the estuary (Millikin & Williams 1984). Although males may mate several times, females only mate once in a lifetime, storing sperm until spawning occurs (Hard 1942, Van Engel 1958, Millikin & Williams 1984). Females migrate to high-salinity areas at river mouths and in coastal waters where they spawn, producing eggs that are transported on their abdomens until hatching transpires (Churchill 1919, Millikin & Williams 1984). Larvae molt into megalopae before recruiting back to the estuaries (Boicourt 1982, Sulkin & van Heukelem 1982) where they become juveniles inhabiting the shallow, lowsalinity portions of the river (Churchill 1919, Van Engel 1958). Sexual maturity is reached from 10 to 20 mo, depending on latitude and the timing of spawning (Van Engel 1958, Tagatz 1968, Lippson 1973, Perry 1975), and maximum lifespan is 3 y (Churchill 1919). Although blue crab juveniles of certain sizes (usually <12.7 cm) and brooding females (referred to as "sponge crabs") are restricted for harvest in many areas of the United States, their predictable life history and proximity to shore have allowed the blue crab to become a lucrative fishery species.
Blue crabs support valuable commercial and recreational fisheries throughout their range. In the United States, blue crab landings totaled almost 61 million kilograms and were valued at nearly 192 million dollars in 2013 (NMFS 2014). In South Carolina (SC), blue crab rank first in commercial shellfish landings by weight and are second only to penaeid shrimps in terms of commercial value (South Carolina Department of Natural Resources [SCDNR] unpublished data).
In the mid-2000s, blue crab alone accounted for 10% of the total value of all commercial landings in SC; and an average of about 2.7 million kilograms were landed each year in the commercial fisheries with an overall worth of 3-4 million dollars (SCDNR 2007). The recreational catch in SC has been estimated to be as large as 1/3 of the commercial catch (D. Whitaker, personal communication). Blue crab thus experiences substantial harvest pressure from both commercial and recreational fishing. Although blue crab population abundances in SC demonstrate high annual fluctuations, fishery-independent landings have shown a decline in blue crab abundance in SC over the past decade, which appears to be related to the recent long-term drought conditions in addition to possible influences from climate change and fishing pressure (SCDNR 2015a). Catch per unit effort (CPUE) of adult blue crab from fisheries-independent trawl and pot surveys conducted by the Crustacean Management Section of the SCDNR remained above the long-term mean from the late 1980s until the late 1990s, but it has been declining such that CPUE exceeded the long-term mean for only 4 y over the past 15 y (J. Brunson, personal communication). Blue crab is managed directly by state jurisdictions, being overseen by SCDNR in SC. Blue crab is considered a "highest priority" species by SCDNR for conservation and research (SCDNR 2015b), and the reduction in CPUE highlights the need for assembling data that can be used for preservation and management of blue crab in SC.
Although much of blue crab biology has been determined, many key aspects of blue crab life history such as overwintering behavior, habitat limitations, and reproductive output of estuaries are unknown in SC. One of such data deficiencies that exist for blue crab involves the genetic diversity and number of contributing spawners in SC estuaries. Genetic structure of blue crab populations along the Atlantic Coast of the United States has been investigated (Cole & Morgan 1978, McMillen-Jackson et al. 1994, McMillen-Jackson & Bert 2004). Few examinations of genetic diversity, however, have been conducted (McMillen-Jackson & Bert 2004), particularly in SC, and no estimates of effective population size have been generated, leaving crucial information on the genetic "health" of the blue crab population in SC relatively unknown. Here we use a suite of microsatellite loci to estimate the genetic diversity and effective population size of blue crab in Charleston Harbor, SC. This study provides a baseline genetic characterization of the Charleston Harbor estuary, which can be used to inform management decisions regarding this vital fisheries species in SC.
MATERIALS AND METHODS
A total of 116 blue crab samples from the Charleston Harbor estuary (Charleston Harbor proper, Ashley River. Orangegrove Creek. Rathall Creek, James Island Creek, and Fort Johnson Creek; Fig. 1) were collected from June 28, 2012, to May 21, 2013, by SCDNR using either crab pots or a 20-foot trawl. Collection data, including carapace length and sex, were recorded for each individual and a single walking leg was placed in a 15-ml vial containing 95% ethanol.
Muscle tissue was dissected from the walking legs and placed into ~1 ml of autoclaved sterile water (d[H.sub.2]O) for 1 h to flush excess ethanol from the sample. Crustacean tissue contains pigments that may inhibit enzymatic digestion, so the water was drained and the samples were taken through a chelex extraction protocol to remove pigments from the tissues. The samples were mixed with 200 [micro]l of a 5% chelex solution and 20 [micro]l of 5% SDS and allowed to digest at 95[degrees]C for 5 min to lyse the cells and allow the pigments to bind to the chelex resin. The samples were then cooled to room temperature. Finally, 20 [micro]l of a 20 mg/ml proteinase-K solution was added, and the tissue samples were allowed to digest at 55[degrees]C overnight. Deoxyribonucleic acid was isolated from the resulting solution using a Qiagen DNeasy Blood and Tissue Kit (Qiagen Inc., Gaithersburg, MD), following the manufacturer's instructions.
Blue crab samples were genotyped across a suite of six Callinectes sapidus-specific microsatellite primers developed by Steven et al. (2005; Table 1). Four of the markers were combined into 11 [micro]l multiplexed polymerase chain reactions (PCR) containing: d[H.sub.2]O, IX HotMaster PCR Buffer (5 Prime Inc.; Gaithersburg, MD), 2.0 mm Mg[Cl.sub.2], 0.8 mm dNTPs (0.2 mm each), 0.5 [micro]m each of forward and reverse primer (for individual primer concentrations see Table 2), 0.03 U/[micro]l of HotMaster Taq (5 Prime Inc.), and 1 [micro]l of DNA (2-40 ng/[micro]l). Polymerase chain reaction amplifications were performed on BIORAD iCyclers (Bio-Rad Laboratories; Hercules, CA) with final reactions commencing with an initial denaturation step of 2 min at 94[degrees]C; followed by 14 cycles of 94[degrees]C for 30 sec, 64[degrees]C for 1 min (decreasing by 2[degrees]C every two cycles), and 70[degrees]C for 1 min; followed by 35 cycles of 94[degrees]C for 30 sec, 52[degrees]C for 1 min, and 70[degrees]C for 1 min; and ending with a final extension at 70[degrees]C for 60 min. The remaining two loci (CSC-007 and CSA-073) were run in individual PCR reactions using the same reagents and concentrations as the multiplexed reactions. Polymerase chain reaction amplifications for CSA-073 and CSC-007 were performed individually on BIORAD iCyclers with final reactions commencing with an initial denaturation step of 2 min at 94[degrees]C; followed by 35 cycles of 94[degrees]C for 30 sec, 66[degrees]C (CSA-073) or 57[degrees]C (CSC-007) for 1 min, and 70[degrees]C for 1 min; and ending with a final extension at 70[degrees]C for 60 min.
Each locus was labeled with a Well-Red fluorescent dye (Sigma-Aldrich, St. Louis, MO; Table 1) for separation on a Beckman CEQ 8000 capillary electrophoresis system (Beckman Coulter Inc., Brea, CA). Multiplex reactions, which contained four loci, were placed directly onto the CEQ, whereas the individual reactions for CSA-073 and CSC-007 were mixed together in a ratio of 3:2, respectively, before being placed on the CEQ. Polymerase chain reaction products (3 [micro]l) were mixed with 40 [micro]l of sample loading solution (0.01% fluorescently labeled 400-bp size standard in formamide) and separated by capillary electrophoresis. Resulting chromatograms were scored using CEQ Fragment Analysis Software (Beckman Coulter Inc.). To maintain quality control, all data were scored independently by two readers and differences were resolved by conference or reprocessing of the samples.
All six loci were tested for Hardy-Weinberg equilibrium (HWE), linkage disequilibrium, and the possibility of null alleles. Examinations for HWE were conducted using exact tests performed with Markov chain randomization in the programs Arlequin v184.108.40.206 (Excoffier & Lischer 2010) and Genepop v4.1 (Rousset 2008); parameters for both programs were set on default values. Tests for linkage disequilibrium between all microsatellite pairs were executed in Arlequin and Genepop using default parameters. The frequency of potential null alleles segregating at each locus was evaluated in CERVUS 3.0 (Kalinowski et al. 2007). Significance levels for all analyses were adjusted using a Bonferroni correction (Rice 1989).
Basic molecular diversity indices including the number of alleles, allelic size range, observed and expected heterozygosities, and inbreeding coefficients (F\$ Weir & Cockerham 1984) were determined for each locus in Arlequin and Genepop. Measurements of heterozygosity and FIS were also averaged across loci for the Charleston Harbor estuary. FSTAT v220.127.116.11 (Goudet 1995) was used to calculate allelic richness (number of alleles corrected for sample size) for each locus.
Effective population size (Nc) for the Charleston Harbor estuary was calculated using the single-sample program LDNe v1.2 (Waples & Do 2008). Genetic drift generates nonrandom associations among unlinked loci; LDNe analyzes this linkage disequilibrium between a set of unlinked loci to determine contemporary Ne for a single time point, producing three values based on preset allele frequency exclusion criteria. Allele frequency exclusion criteria were set at default values (<0.01, <0.02, and <0.05) and a random mating model was assumed. The "jackknife on loci" option was chosen for the confidence intervals (CI).
After correction for multiple comparisons, no linkage disequilibrium was detected at any loci and all loci met the expectations of HWE (all P > 0.008; Table 2) except for CSC007. The frequency of potential null alleles was low (<0.05) for all loci with the exception of CSC-007 and CSC-094. All six loci were retained; however, analyses were preformed using both six loci and five loci (dropping both CSC-094 and CSC-007 in turn). Removing either CSC-007 or CSC-094 did not have an appreciable effect on the results (average heterozygosities and inbreeding or effective size).
Based on our evaluation of 116 blue crab samples, all loci were polymorphic with 5-47 alleles per locus (Table 2). Allelic richness ranged from 5.0 to 45.9, and the majority of loci had a very large number of alleles (>30; Table 2). Observed ([H.sub.O]) and expected ([H.sub.E]) heterozygosities (Table 2) were high (>0.85) for four loci (MIH-SSR, CSA-035, CSA-035, and CSC-007), moderate (>0.63) for one locus (CSC-094), and low (0.29) for one locus (CSA-121). The low level of diversity at CSA-121 is likely the result of the small number of alleles that were observed at this locus (n = 5). Average heterozygosities, taken across all loci, were moderately high ([H.sub.O] = 0.763, [H.sub.E] = 0.811). Levels of inbreeding ([F.sub.IS]) were low (<0.10) for most loci (Table 2), and the average inbreeding coefficient, taken across all loci, was relatively low ([F.sub.IS] = 0.06) for the Charleston Harbor estuary.
LDNe produced negative estimates of effective population size (Ne) for all three allele frequencies (<0.01, <0.02, and <0.05) for the Charleston Harbor estuary. Negative estimates are given by LDNe when there is no evidence for any disequilibrium caused by genetic drift due to a finite number of parents (i.e., the genetic results can be explained by sampling alone without incorporating genetic drift). In this case, the data cannot verify thai the population is not "very large" (Waples & Do 2010). Also, the upper CI on all values were unbounded (i.e., indicating that effective population size is likely large ([N.sub.e] [greater than or equal to] 1000). Upper bounds on Ne estimates in LDNe are typically not well defined for large populations even with robust sample sizes (n [greater than or equal to] 200; Waples & Do 2010); however, the finite lower bound of the CI is still informative with respect to the minimum limits of [N.sub.e] and can be used for conservation purposes. The lower bound for the jackknife CI at all three allele frequencies ranged from 334-4,267.
The evaluation of genetic diversity and effective population size in our study provides important information on the genetic characteristics of the Charleston Harbor blue crab population, which was previously unknown. Reduced genetic diversity, coupled with inbreeding, may negatively impacted a species' fitness and ability to respond to environmental stochasticity (Saccheri et al. 1998, Frankham et al. 2002, Keller and Waller 2002, Reed and Frankham 2003, Frankham 2005), thus increasing the risk of extirpation (i.e., location extinction). Consequently, measurements of genetic diversity provide valuable indicators of the overall genetic "health" of a population. Genetic diversity of the Charleston Harbor blue crab population was relatively high as evidenced by the large number of alleles ([N.sub.a] = 5-M alleles per locus), elevated allelic richness (R = 5.0-45.9), and fairly high values for observed and expected heterozygosity ([H.sub.O] = 0.763, [H.sub.E] = 0.811). These findings are in agreement with previous assessments of blue crab, which detected high genetic diversity with mitochondrial markers (Darden 2004, McMillen-Jackson & Bert 2004). Relatively low levels of inbreeding were also found for the Charleston Harbor estuary, indicating a robust population size.
Effective population size ([N.sub.e]) is one of the most important measures in conservation biology (Waples 2002, Frankham 2005), as reduced fitness and an increased likelihood of extirpation have been linked to low effective sizes (Newman & Pilson 1997). The estimation method of [N.sub.e] used in our study considers genetic drift to be the sole contributor to the signal in the data (i.e., no selection, mutation, migration, or overlapping generations). Microsatellite markers are considered to be selectively neutral and short-term estimates of [N.sub.e] are not appreciably affected by mutation rate (Waples & Do 2010). Blue crabs have a short generation time (~1 y; Millikin & Williams 1984) and so do not exhibit overlapping generations. Long-distance migration and subsequent gene flow is possible for blue crab. Adult blue crabs, particularly females, have been known to travel great lengths for the purpose of spawning (>800 km; Oesterling & Evink 1977, Steele 1991), and blue crab larvae, which have a 37-69-day planktonic stage (Williams 1965), may not settle within their estuaries of origin (settlement may in fact be on a regional scale; Epifanio 1995, Johnson & Perry 1999). Conversely, Fischler and Walburg (1962) found that most tagged adult blue crab in SC did not migrate between estuaries, and suggested that blue crab management be concentrated on individual estuaries. Genetic examinations on the subject of population differentiation have been varied, sometimes finding genetic homogeneity (Cole & Morgan 1978, McMillen-Jackson et al. 1994, BerthelemyOkazaki & Okazaki 1997) and other times displaying genetic heterogeneity (Burton & Feldman 1982, Kordos & Burton 1993, Darden 2004, McMillen-Jackson & Bert 2004) across differing spatial scales. It is suggested that gene flow in blue crab may rely heavily on local current circulation and larval migration behavior (McMillen-Jackson et al. 1994. McMillen-Jackson & Bert 2004), and may show an isolation-by-distance pattern (Darden 2004). The possibility that migration of adults and/or larvae between Charleston Harbor and other local estuaries, therefore, cannot be completely ruled out, and the estimates of [N.sub.e] obtained in this our may be close approximations of local [N.sub.e] for the Charleston Harbor estuary or may represent a more regional estimation of effective size (Waples & England 2011) for SC. In either case, conservative effective population estimates were on the order of a few hundred to a thousand individuals ([N.sub.e] = 334-4,267), which is above the minimum number of 50 recommended to avoid significant inbreeding and maintain short-term fitness of a population (Franklin 1980) and is within the minimum values recommended to maintain the evolutionary potential (i.e., quantitative trait heritability; Frankham 1995) and long-term viability of a population ([N.sub.e] = 500-1,000; Franklin & Frankham 1998, or [N.sub.e] = 1,000-5,000; Lynch & Lande 1998).
In conclusion, estimates of genetic diversity and effective population size suggest the current Charleston Harbor blue crab population is genetically "healthy" despite recent declines. It may, however, be advantageous to periodically monitor measurements of genetic diversity and [N.sub.e] in SC, as recent decreases in population size are often not immediately reflected in the level of genetic diversity. Our study provides a baseline genetic characterization of blue crab in the Charleston Harbor estuary, which helps to further our knowledge of Callinectes sapidus in this area and can be used as the foundation for future inquires. Results obtained this study and succeeding research can provide valuable information on blue crab ecology and life history that can be incorporated into management decisions to monitor and preserve the important blue crab fishery in SC.
We are very grateful to all those from SCDN R's Crustacean Research Section who were involved in sample collection for our project, including J. Brunson, J. Leffler, and L. DeLancy. A thank you all the members of the SCDNR Genetics lab at the Hollings Marine Laboratory, including D. Farrae, M. Jamison, S. Johnson, T. O'Donnell, and M. Walker, for providing second reads on all chromatograms. A special thank you for D. Farrae for generating Figure 1. Our project was funded by the SC Salt Water Recreational License Program (SRFAC) and the SC Sea Grant Consortium (NA100AR4170073-P/M-2T Ml IT). This is publication number #757 from the Marine Resources Research Institute, South Carolina Department of Natural Resources.
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ELIZABETH CLJSHMAN * AND TANYA DARDEN
South Carolina Department of Natural Resources, Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412
* Corresponding author. E-mail: email@example.com
Caption: Figure 1. Sampling locations for Atlantic blue crab (Callinectes sapidus) in the Charleston Harbor estuary.
TABLE 1. Characteristics for Callinectes sapidus-specific microsatellite loci. Locus Dye Motif Final (primer) GenBank number ([micro]m) MIH-SSR D4 [(GT) 24] 0.063 U19764 CSA-035 D2 [(GT).sub.29] 0.066 AY359558 CSA-121 D3 [(AGAC).sub.9] 0.308 AY359568 CSC-094 D4 [(TCTG).sub.6] 0.063 AY359548 CSC-007 D3 [(GA).sub.35] 0.500 AY359535 CSA-073 D2 [(GT).sub.57] 0.500 AY359564 Dye = fluorescent label on forward primer; motif = repeat motif; final (primer) = final polymerase chain reactions concentration of the marker. TABLE 2. Number of genotvped samples (IV), number of alleles (Na), allelic richness (R), allelic size range (A), observed ([H.sub.O]) and expected heterozygosity ([H.sub.E]), probability of divergence from HWE (bold text indicates significance at P < 0.008), inbreeding coefficients ([F.sub.IS]), and the frequency of any possible null alleles (Null) for six blue crab loci in the Charleston Harbor estuary. Primer name N NA R A [H.sub.O] MIH-SSR 116 31 30.6 135-203 0.931 CSA-035 116 47 45.9 148-256 0.957 CSA-121 116 5 5.0 186-210 0.293 CSC-094 112 11 10.9 232-256 0.625 CSA-073 109 41 40.5 192-294 0.927 CSC-007 104 35 35.0 166-258 0.846 Primer name [H.sub.E] HWE [F.sub.IS] Null MIH-SSR 0.959 0.122 0.030 0.013 CSA-035 0.969 0.409 0.013 0.004 CSA-121 0.287 0.306 -0.023 0.000 CSC-094 0.746 0.028 0.163 0.093 CSA-073 0.952 0.184 0.027 0.012 CSC-007 0.955 <0.0005 0.115 0.059
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|Author:||Cushman, Elizabeth; Darden, Tanya|
|Publication:||Journal of Shellfish Research|
|Date:||Apr 1, 2017|
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