Abstract
Objective
The ghost crab Ocypode stimpsoni (Decapoda) is designated as a protected marine species in Korea due to its declining population. In this study, we successfully identified 17 microsatellite markers for O. stimpsoni through next-generation sequencing.
Results
Out of the 63 loci examined, 26 were effectively amplified in a sample of 100 individuals. These 17 loci, comprising four tri-nucleotide and 13 tetra-nucleotide repeats, exhibited a range of 4 to 26 alleles per locus (with an average of 14.1 alleles) across 100 samples from three O. stimpsoni populations. The mean observed and expected heterozygosities were calculated to be 0.885 and 0.836, respectively. These 17 newly identified polymorphic microsatellite loci hold valuable utility for investigating the genetic structure and diversity of this protected marine species.
Keywords: Ocypode stimpsoni, Microsatellite loci, Genetic variability, Conservation
Introduction
The ghost crab, Ocypode stimpsoni Ortmann, 1897 (Ocypodidae), is a common resident of sandy beaches found along the coastlines of Korea, Japan, Taiwan and China [1–4]. Ghost crabs belonging to the Ocypode genus have gained widespread recognition as bio-indicator species, particularly with regard to assessing human impacts on exposed sandy beaches. They serve a significant ecological role by aiding in the cleaning of these environments through sediment ingestion in water [5–8]. Despite their utility as indicator species, research efforts on ghost crabs have been relatively limited [9, 10]. Notably, O. stimpsoni, which resides in Korea, has been granted protected status as a marine species and protected by a law, a designation initiated by the Ministry of Oceans and Fisheries, Korea, in 2016 in response to a rapid decrease in the population size caused by habitat loss associated with coastal development [11]. Microsatellite markers are one of the best suitable genetic markers to understand the population structure, genome variation, evolutionary process and fingerprinting purposes [12]. Therefore, it becomes imperative to delve into the genetic diversity within and among populations, shedding light on the population structure of this species to pave the way for effective conservation strategies.
Molecular methods are crucial for estimating genetic diversity among individuals by comparing their genotypes at polymorphic loci [13]. Among the various molecular markers available, microsatellites, or simple sequence repeats (SSRs), are popular and effective tools for assessing genetic diversity and distinguishing populations of rare and endangered species [14–16]. Over the past decade, the rapid advancement of sequencing technology, particularly NGS, has enabled the identification of a substantial number of microsatellite markers [17, 18]. Microsatellites with larger numbers of repeats tend to exhibit higher levels of polymorphism and stability, making them preferable for genetic studies as they produce clearer results compared to shorter repeat sequences [19]. In this study, we identified 17 novel polymorphic microsatellite markers for O. stimpsoni using the next-generation sequencing (NGS) platform Illumina MiSeq. These species-specific microsatellite markers can provide valuable information for genetic studies of this protected marine species in Korea.
Materials and methods
Sample collection and next-generation sequencing
A total of 100 O. stimpsoni samples were collected in April 2019 from three beaches on the Western coast of Korea: Yeonggwang (n = 40), Taean (n = 20), and Seocheon (n = 40). To isolate microsatellites, high-molecular-weight DNA (≥ 2 μg) was extracted from the musculature tissue of each O. stimpsoni specimen using the DNeasy Blood & Tissue kit (QIAGEN, Hilden, Germany). Among them, two DNA samples without evident smears (the DNA concentration of 19.79 ng/ul and 19.56 ng/ul, and the total amount 1,979 ug and 1,956 ug, respectively) were used to the NGS. Subsequently, a genome library was prepared according to the manufacturer’s protocol (Paired-End Library Construction) using the TruSeq Nano DNA High Throughput Library Prep kit (Illumina, San Diego, CA, USA). These DNA fragments go through the addition of a single ‘A’ base, and ligation of the TruSeq DNA UD Indexing adapters. The libraries were quantified using qPCR according to the qPCR Quantification Protocol Guide (KAPA Library Quantification kits for Illumina Sequencing platforms) and qualified using the Agilent Technologies 4200 TapeStation D1000 screentape (Agilent technologies).
Microsatellite discovery and primer screening
De novo genome assembly was conducted using the IDBA-UD assembler v1.1.1 [20, 21]. To identify SSRs among the assembled contigs (68,969), the microsatellite identification tool (MISA) software, a Perl SSR motif-scanning tool (http://pgrc.ipk-gatersleben.de/misa/), was employed. Sequences longer than 300 bp were subjected to screening using MSATCOMMANDER 1.08 [22], with a requirement of at least five repeats for di-, tri-, or tetra-nucleotide repeat motifs. Primers were designed for suitable singleton sequences utilizing the Primer3 software [23]. The primer design criteria comprised a GC content within the range of 45–55%, an optimum annealing temperature of 54–60 °C, a PCR product length of 150–500 bp, and adherence to default parameters for primer self-complementarities and quality criteria.
PCR amplification and genotyping
All 63 primer pairs, derived from suitable sequences, underwent preliminary testing for PCR amplification consistency. The initial screening employed four O. stimpsoni individuals collected in Seocheon, Korea. PCR amplification reactions were conducted in 15-μL volumes using a SimpliAmp™ Thermal Cycler (Thermo Fisher Scientific, Waltham, MA, USA). The reaction mix included 0.5 U of Ex Taq DNA polymerase (Takara Biomedical, Inc., Shiga, Japan), 1× PCR buffer, 0.2 mM dNTPs, 10 pmol of each primer, and approximately 30 ng of template DNA. The forward primer from each pair was 5′-end-labeled with 6-FAM, VIC, NED, or PET (Applied Biosystems Inc., Foster City, CA, USA). The PCR program was initiated with 10 min at 95 °C, followed by 35 cycles consisting of 20 s at 95 °C, 40 s at 59 °C, and 1 min at 72 °C, concluding with a 3-min final extension at 72 °C. Amplification success was determined by the presence of a visible band upon visualization on a 2.0% agarose gel. Subsequently, the 26 selected polymorphic loci were assessed in all the collected individuals. To enhance genotyping efficiency, fluorescently labeled PCR products with three or four markers of varying sizes were combined in a single capillary. Capillary electrophoresis on an ABI PRISM 3130 xL Genetic Analyzer (Applied Biosystems) was used for the separation of PCR products, alongside a molecular size marker (GENESCAN 500 LIZ, Applied Biosystems). GENOTYPER version 4.1 (Applied Biosystems, Foster City, CA) was employed for the final determination of allele sizes in the fluorescent DNA fragments.
Genetic analysis
CERVUS version 3.03 [24] was employed to compute various genetic parameters, including the number of alleles (NA), observed heterozygosity (Ho), expected heterozygosity (He), and polymorphic information content (PIC). To assess deviations from the Hardy–Weinberg equilibrium (HWE) [25] and linkage disequilibrium (LD), which indicate the extent of distortion from the independent segregation of loci, GENEPOP version 4.2 [26] was utilized. Significance levels were adjusted for multiple tests through the sequential Bonferroni correction [27]. Heterozygote excess was further tested using Genepop (H1: excess of heterozygotes). The total p value was obtained from a global test for deviation from Hardy-Weinberg equilibrium (H1: heterozygote excess), with significance levels adjusted for multiple comparisons using the sequential Bonferroni method [28]. Bottleneck events were evaluated using the BOTTLENECK 1.2.02 program [29]. To predict the probability of presence of null alleles and large allele dropout, Microchecker v2.2.3 was used with 95% confidence intervals and 1000 randomizations, while the presence of null alleles was estimated using Oosterhout’s estimator [30].
Results and discussion
The raw sequence data obtained from two O. stimpsoni samples comprised a total of 1,470,273,091 bp, with a quality score of Q30 = 91.69%, distributed across 5,706,546 Illumina sequencing reads. The final assembly yielded 68,969 contigs, with a cumulative length of 54,165,912 bp and an average contig length of 785 bp. The N50 scaffold size was 748 bp, and the GC content was 38.7% (Table 1). Among the 238,776 identified SSR sequences, tri-nucleotide repeats were the most common, accounting for 66.08% (157,788) of the total, followed by di- (25.69%), tetra- (7.1%), penta- (0.9%), and hexa-nucleotide repeats (0.1%).
Table 1.
Summary of illumina MiSeq sequencing
| Description | |
|---|---|
| Total number of bases | 1,470.27 Mb |
| Average read length | 257 nucleotides |
| Number of reads | 5,706,546 |
| Number of contigs | 68,969 |
| Total contigs | 54,165,912 nucleotides |
| Average contig read length | 785 nucleotides |
| Max. contig length/Min. contig length | 16,572/310 nucleotides |
| N50 | 784 nucleotides |
Out of a total of 13,195 unique sequences containing pure/compound microsatellite regions and primer-designable flanking regions, sequences were chosen for primer design based on specific criteria. These criteria included a minimum of seven tri- or tetra-nucleotide repeat motifs, sequences of sufficient length (over 100 bp), and unique sequences flanking the microsatellite array with a minimum of 100 bases. Subsequently, 63 microsatellite loci were selected for further screening, consisting of 32 tri- and 31 tetra-nucleotide repeats. In the initial assessment, 26 loci (8 tri- and 18 tetra-nucleotide repeats) were successfully amplified, while the remaining 37 primers did not amplify the desired PCR products. Among the 26 loci, 7 displayed faint or inconsistent bands, possibly due to nonspecific PCR amplification. Further screening revealed that 17 (58.3%) of these loci were polymorphic, while two loci were monomorphic. Among the 17 polymorphic microsatellite loci identified in this study, four were tri-nucleotide repeats, while the remaining 13 were tetra-nucleotide repeats. Table 2 summarizes the names of the primers, their sequences, repeat motifs, fluorescent labels, and GenBank accession numbers for the 17 new microsatellite loci and Table 3 shows comparison of characteristics of microsatellite loci among three populations. A total of 100 O. stimpsoni individuals were screened for variation using the 17 new microsatellites. A BLAST program homology search confirmed that none of the 17 sequences exhibited similarity to any sequences in GenBank.
Table 2.
Characteristics of the 17 microsatellite loci identified for Ocypode stimpsoni
| Locus (GenBank accession no.) |
Primer sequence (5′-3′) | No. indiv PCR success |
Repeat motif | Size range (bp) | N A | Ho | He | PIC | P HWE | P | Null present |
|---|---|---|---|---|---|---|---|---|---|---|---|
| OS10 | F: 6fam-ACTACTGCTACTACTACCGT | 78 | (TAT)17 | 188–291 | 16 | 0.897 | 0.899 | 0.884 | 0.000* | 0.781 | no |
| (MF461429) | R: CCCCTGATAACCTGTCGACG | ||||||||||
| OS11 | F: hex-GGCGTTATTAGCACTGCTGC | 97 | (ACT)11 | 103–148 | 26 | 0.825 | 0.936 | 0.927 | 0.000* | 1.000 | no |
| (MF461431) | R: TGTTCCTTTCCTTTTTCACTTT | ||||||||||
| OS12 | F: ned-GGCCAGCACAGGTAGAGAAA | 96 | (AGT)21 | 209–281 | 24 | 0.896 | 0.928 | 0.918 | 0.000* | 0.457 | no |
| (MF461432) | R: AGCAGCATCAGGAACAACAA | ||||||||||
| OS13 | F: 6fam-AGCAGCAGTAATAGTAGTAGCAGT | 100 | (CAG)8 | 209–278 | 18 | 0.910 | 0.850 | 0.833 | 0.000* | 0.317 | no |
| (MF461433) | R: GTGTTTCCTTCGCTCAGTGC | ||||||||||
| OS34 | F: pet-TGTCTGTCTGTCTTTTGGTCT | 100 | (TGTC)11 | 120–168 | 14 | 0.960 | 0.825 | 0.802 | 0.005* | 0.000* | no |
| (MF461434) | R: TGACCCGAGGCTTAAAACCC | ||||||||||
| OS36 | F: hex-CCCTAACCCCCTCTCTGTCT- | 100 | (CTAT)8 | 142–186 | 11 | 0.950 | 0.773 | 0.736 | 0.000* | 0.000* | no |
| (MF461435) | R: AACGTGGCAATGCATAACCG | ||||||||||
| OS41 | F: 6fam-GGAACTCTCTCTCAGCACAGG- | 100 | (TATT)7 | 206–234 | 8 | 0.920 | 0.778 | 0.743 | 0.000* | 0.012 | no |
| (MF461436) | R: GAAACACCTGTGCAGCAGTG | ||||||||||
| OS42 | F: 6fam-TTCCTCTCTTCAGCAGCACC | 99 | (TCCT)7 | 162–186 | 7 | 0.788 | 0.783 | 0.746 | 0.263 | 0.054 | no |
| (MF461438) | R: TGGGGATGACAAGAGAGCTG | ||||||||||
| OS43 | F: pet-CTTACGAAGGGGAGAGCGAG | 100 | (AGAC)8 | 225–281 | 14 | 0.850 | 0.873 | 0.855 | 0.000* | 0.594 | no |
| (MF461440) | R: TGTAATCTACCGTGCCCGAG | ||||||||||
| OS46 | F: pet-GGAAGGCAGGTATGGAGAGC | 94 | (AGGA)7 | 270–338 | 17 | 0.734 | 0.890 | 0.876 | 0.000* | 0.998 | no |
| (MF461442) | R: AATCGAAACCAAGCCCTCGT | ||||||||||
| OS47 | F: ned-CGGCGGGTGATTGTAGCTA | 100 | (GTTA)7 | 269–297 | 8 | 0.900 | 0.770 | 0.731 | 0.000* | 0.096 | no |
| (MF461443) | R: GAGCTTTGTCAAGAAGCTGCA | ||||||||||
| OS54 | F: 6fam-TTGCGACTCCAGAAGGTCAC | 99 | (ATAC)10 | 207–235 | 8 | 0.919 | 0.789 | 0.756 | 0.004* | 0.000* | no |
| (MF461444) | R: GCTCCAAGGGCAGAGGTATT | ||||||||||
| OS55 | F: hex-TGGTGGGGATTCGAATAGCG | 76 | (TAAA)7 | 192–208 | 4 | 0.868 | 0.616 | 0.533 | 0.000* | 0.000* | no |
| (MF461445) | R: TGCACCATCCACCCTCATTT | ||||||||||
| OS56 | F: hex-ACCACCCATTCGTCATGTGT | 100 | (CATA)8 | 343–393 | 14 | 0.990 | 0.861 | 0.84 | 0.025 | 0.000* | no |
| (MF461447) | R: GATGATGGACGGGTCGGTTA | ||||||||||
| OS57 | F: pet-GGTCAGGACGGTAATGGCAT | 100 | (GTAT)9 | 280–328 | 14 | 0.890 | 0.865 | 0.846 | 0.019 | 0.866 | no |
| (MF461449) | R: ACGATGAAAACGGCAAAAGTG | ||||||||||
| OS59 | F: ned-CTGACCTGCTGGCTGGTAAA | 96 | (GGCT)8 | 113–149 | 19 | 0.979 | 0.854 | 0.833 | 0.000* | 0.042 | no |
| (MF461450) | R: CACCCCAGCTCAAAGACTCA | ||||||||||
| OS63 | F: ned-CGCAACCTACACAACAGCTG | 88 | (TAAA)7 | 228–296 | 18 | 0.773 | 0.935 | 0.925 | 0.000* | 1.000 | yes |
| (MF461453) | R: GAGTGCTAGGTAGACATGCACA | (0.054) | |||||||||
| Avg | 95.47 | 14.11 | 0.885 | 0.836 | 0.810 | 0.102 | 0.365 | ||||
No indiv PCR success, Number of individuals of PCR success; NA, number of alleles per locus; Ho, observed heterozygosity; He, expected heterozygosity; PIC, polymorphism information content; PHWE, P values of Hardy Weinberg equilibrium test; P, the probability for rejecting Hardy-Weinberg equilibrium when H1 = Heterozygote excess using Genepop (Global Hardy-Weinberg tests); Avg, average. * Indicates significant difference after the application of Holm’s Sequential Bonferroni’s correction (p < 0.05/(17–rank + 1)). The presence of null alleles was investigated using MICROCHECKER v2.2.3 with 1000 randomizations with 95% confidence intervals and 1000 randomizations
Table 3.
Comparison of characteristics of Ocypode stimpsoni microsatellite loci among three populations
| Locus | Yeonggwang (n = 40) | Taean (n = 20) | Seocheon (n = 40) | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No indiv PCR success | N A | Ho | He | PIC |
P
HWE
(P) |
Null present | No indiv PCR success | N A | Ho | He | PIC |
P
HWE
(P) |
Null present | No indiv PCR success | N A | Ho | He | PIC |
P
HWE
(P) |
Null present | |||
| OS10 | 36 | 15 | 0.944 | 0.899 | 0.876 |
0.000* (0.973) |
no | 20 | 12 | 0.900 | 0.909 | 0.876 |
0.398 (0.687) |
no | 22 | 13 | 0.818 | 0.919 | 0.889 |
0.000* (0.420) |
no | ||
| OS11 | 37 | 13 | 0.946 | 0.902 | 0.880 |
0.076 (0.091) |
no | 20 | 10 | 0.950 | 0.881 | 0.844 |
0.172 (0.629) |
Yes (0.150) |
40 | 25 | 0.650 | 0.961 | 0.947 |
0.000* (1.000) |
no | ||
| OS12 | 36 | 17 | 1.000 | 0.907 | 0.885 |
0.014 (0.035) |
no | 20 | 11 | 0.850 | 0.890 | 0.854 |
0.876 (0.159) |
Yes (0.080) |
40 | 20 | 0.825 | 0.903 | 0.885 |
0.000* (0.933) |
no | ||
| OS13 | 40 | 9 | 0.975 | 0.786 | 0.750 |
0.263 (0.923) |
no | 20 | 8 | 0.950 | 0.774 | 0.729 |
0.682 (0.005) |
no | 40 | 15 | 0.825 | 0.892 | 0.87 |
0.001* (0.078) |
no | ||
| OS34 | 40 | 10 | 0.950 | 0.772 | 0.739 |
0.138 (0.023) |
no | 20 | 9 | 1.000 | 0.832 | 0.789 |
0.096 (0.015) |
no | 40 | 9 | 0.950 | 0.822 | 0.788 |
0.624 (0.008) |
no | ||
| OS36 | 40 | 10 | 0.975 | 0.797 | 0.760 |
0.144 (0.009) |
no | 20 | 6 | 1.000 | 0.745 | 0.679 |
0.049 (0.011) |
no | 40 | 7 | 0.900 | 0.770 | 0.723 |
0.003* (0.000*) |
no | ||
| OS41 | 40 | 8 | 0.900 | 0.789 | 0.751 |
0.023 (0.216) |
no | 20 | 8 | 0.800 | 0.785 | 0.743 |
0.137 (0.003*) |
no | 40 | 4 | 1.000 | 0.738 | 0.677 |
0.024 (0.192) |
no | ||
| OS42 | 40 | 6 | 1.000 | 0.818 | 0.780 |
0.035 (0.000*) |
no | 19 | 7 | 0.947 | 0.817 | 0.766 |
0.870 (0.016) |
Yes (0.197) |
40 | 6 | 0.500 | 0.666 | 0.604 |
0.000* (0.956) |
no | ||
| OS43 | 40 | 14 | 0.875 | 0.869 | 0.844 |
0.000* (0.632) |
no | 20 | 9 | 0.750 | 0.872 | 0.833 |
0.000* (0.000*) |
no | 40 | 14 | 0.875 | 0.869 | 0.844 |
0.000* (0.845) |
no | ||
| OS46 | 36 | 11 | 0.944 | 0.838 | 0.811 |
0.682 (0.565) |
no | 20 | 9 | 0.800 | 0.841 | 0.798 |
0.225 (0.024) |
Yes (0.241) |
38 | 13 | 0.500 | 0.869 | 0.842 |
0.000* (1.000) |
no | ||
| OS47 | 40 | 6 | 0.875 | 0.727 | 0.636 |
0.000* (0.886) |
no | 20 | 6 | 0.850 | 0.776 | 0.716 |
0.426 (0.024) |
no | 40 | 8 | 0.950 | 0.783 | 0.740 |
0.045 (0.058) |
no | ||
| OS54 | 40 | 8 | 1.000 | 0.798 | 0.758 |
0.001* (0.000*) |
no | 20 | 8 | 1.000 | 0.810 | 0.767 |
0.139 (0.008) |
no | 39 | 7 | 0.795 | 0.752 | 0.710 |
0.742 (0.571) |
no | ||
| OS55 | 36 | 4 | 0.833 | 0.615 | 0.526 |
0.150 (0.028) |
no | 20 | 4 | 0.900 | 0.638 | 0.545 |
0.318 (0.065) |
no | 20 | 4 | 0.900 | 0.624 | 0.529 |
0.000* (0.000*) |
no | ||
| OS56 | 40 | 11 | 1.000 | 0.863 | 0.834 |
0.444 (0.000*) |
no | 20 | 9 | 1.000 | 0.865 | 0.824 |
0.090 (0.029) |
no | 40 | 11 | 0.975 | 0.864 | 0.835 |
0.832 (0.006) |
no | ||
| OS57 | 40 | 12 | 0.975 | 0.853 | 0.824 |
0.062 (0.929) |
no | 20 | 9 | 1.000 | 0.859 | 0.819 |
0.388 (0.148) |
no | 40 | 12 | 0.750 | 0.874 | 0.848 |
0.064 (0.750) |
no | ||
| OS59 | 36 | 7 | 1.000 | 0.815 | 0.776 |
0.000* (0.000*) |
no | 20 | 6 | 1.000 | 0.735 | 0.671 |
0.266 (0.019) |
no | 40 | 15 | 0.950 | 0.900 | 0.879 |
0.000* (0.842) |
no | ||
| OS63 | 34 | 16 | 0.824 | 0.937 | 0.918 |
0.000* (1.000) |
Yes (0.054) |
19 | 8 | 0.947 | 0.878 | 0.837 |
0.126 (0.601) |
no | 35 | 17 | 0.629 | 0.915 | 0.895 |
0.033 (0.764) |
Yes (0.279) |
||
| Avg | 38.29 | 10.41 | 0.942 | 0.822 | 0.785 |
0.184 (0.371) |
19.88 | 8.17 | 0.920 | 0.818 | 0.770 |
0.328 (0.143) |
37.29 | 11.76 | 0.811 | 0.830 | 0.794 |
0.337 (0.495) |
|||||
No indiv PCR success, Number of individuals of PCR success; NA, number of alleles per locus; Ho, observed heterozygosity; He, expected heterozygosity; PIC, polymorphism information content; PHWE, P values of Hardy Weinberg equilibrium test; P, the probability for rejecting Hardy-Weinberg equilibrium when H1 = Heterozygote excess using Genepop (Global Hardy-Weinberg tests; Avg, average. * Indicates significant difference after the application of Holm’s Sequential Bonferroni’s correction (p < 0.05/(17–rank + 1)). The presence of null alleles was investigated using MICROCHECKER v2.2.3 with 1000 randomizations with 95% confidence intervals and 1000 randomizations
A total of 240 alleles were identified across the 17 loci, with the NA per locus ranging from four at OS55 to 26 at OS11, resulting in an average NA of 14.11 (Table 2). The Ho varied from 0.734 at OS46 to 0.99 at OS56, with a mean Ho of 0.885. Additionally, the He varied from 0.616 at OS55 to 0.936 at OS11, with an average of 0.836 (Table 2). All 17 loci exhibited a high level of PIC (> 0.5), and most loci featured rare alleles with a frequency of < 5%. No genotyping errors or allele dropouts due to stuttering were detected in any of the 17 loci. The likelihood of poor DNA quality influencing the results was minimal, as samples that failed to amplify upon retesting were excluded. Deviations from HWE after the application of sequential Bonferroni correction (p < 0.05/(17–rank + 1)) were observed in 14 loci (OS10, OS11, OS12, OS13, OS34, OS36, OS41, OS43, OS46, OS47, OS54, OS55, OS59 and OS63) (Table 2), and in comparison among populations, 6 loci (OS10, OS43, OS47, OS54, OS59 and OS63) were found in Yeonggwang (n = 40), one locus (OS43) in Taean (n = 20) and 10 loci (OS10, OS11, OS12, OS13, OS36, OS42, OS43, OS46, OS55 and OS59) in Seocheon (n = 40) (Table 3). Significant (p < 0.05/(17–rank + 1)) heterozygote excess is found for 4 loci (OS34, OS36, OS54 and OS55) out of 14 loci detected significant deviations from HWE (Table 2) and the remaining 10 loci (OS10, OS11, OS12, OS13, OS41, OS43, OS46, OS47, OS59 and OS63) had p values between 0.012 and 1.000, indicating HWE for heterozygote excess (Table 2). In comparison among populations, significant heterozygote excess is found for 4 loci (OS42, OS54, OS56 and OS59) in Yeonggwang, 2 loci (OS41 and OS43) in Taean and 2 loci (OS36 and OS55) in Seocheon, repectively (Table 3). The reasons for the findings are not clear, but we suggest that departures from Hardy–Weinberg proportions can be due to copy number variation, inbreeding or population substructure, migration, natural selection, genotyping error, genetic drift and mutation. Ultimately, deviations from Hardy–Weinberg proportions highlight the biological complexity of natural populations [31–34].
At the 10 loci among 17 loci, the Ho was higher than the He. The higher Ho than He at most loci in a population suggests that this population may have recently experienced a genetic bottleneck [35]. Populations that have experienced a recent bottleneck are predicted to show an excess of heterozygosity because allelic loss occurs more faster than loss of genic heterozygosity during a bottleneck [36]. The genetic bottleneck analysis results under the Infinite Alleles Model (IAM) and Two-Phase Mutation Model (TPM) suggested that all populations (Yeonggwang, Taean and Seocheon) recently experienced bottleneck events. We detected a significant heterozygosity excess (P < 0.05) for Sign test, standardized differences test, and Wilcoxon’s signed rank tests), indicating a contemporary population bottleneck. Heterozygosity excess as an indication of genetic bottleneck was detected under the IAM at all populations (Table 4). Under the TPM (a combination of the IAM 30% and SMM 70%), heterozygosity excess was also detected at all populations, except for the sign test for Yeonggwang (Table 4). Heterozygosity excess was detected only the Standardized differences test for Yeonggwang under the Stepwise Mutation Model (SMM) (Table 4). All three populations exhibited no significant shift in distribution, maintaining a normal L-shape, as shown by the allele frequency distribution test. The strict SMM is the most conservative model for evaluating a significant excess of heterozygosity due to bottlenecks, because if the locus evolves under the strict SMM, there can be situations where this heterozygosity excess is not observed [29, 37]. Taken together all the results suggest that serious demographic bottlenecks have most probably not occurred.
Table 4.
Bottleneck analysis for three populations of Ocypode Stimpsoni
| Test/Models | Yeonggwang (n = 40) | Taean (n = 20) | Seocheon (n = 40) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IAM | TPM | SMM | IAM | TPM | SMM | IAM | TPM | SMM | ||||
|
Sign test (number of loci with heterozygosity excess) |
Exp | 10.23 | 10.14 | 10.05 | 10.13 | 10.18 | 9.96 | 10.24 | 10.05 | 9.99 | ||
| Hex | 17 | 13 | 8 | 16 | 15 | 13 | 17 | 15 | 7 | |||
| Probability | 0.00018 | 0.11973 | 0.22092 | 0.00187 | 0.01199 | 0.10341 | 0.00018 | 0.01025 | 0.11053 | |||
| Standardized differences test | T2 | 3.746 | 1.812 | -1.906 | 4.125 | 2.699 | 0.601 | 4.199 | 2.393 | -1.087 | ||
| Probability | 0.00009 | 0.03500 | 0.02831 | 0.00002 | 0.00348 | 0.27404 | 0.00001 | 0.00835 | 0.13852 | |||
| Wilcoxon test |
Probability (One tail for H deficiency) |
1.00000 | 0.99605 | 0.12175 | 1.00000 | 0.99966 | 0.92728 | 1.00000 | 0.99973 | 0.17644 | ||
|
Probability (One tail for H excess) |
0.00000 | 0.00467 | 0.88766 | 0.00001 | 0.00042 | 0.07969 | 0.00000 | 0.00034 | 0.83553 | |||
|
Probability (Two tail for H excess and deficiency) |
0.00001 | 0.00934 | 0.24350 | 0.00002 | 0.00084 | 0.15938 | 0.00001 | 0.00067 | 0.35287 | |||
| Allele frequency distribution | Normal L-shaped | Normal L-shaped | Normal L-shaped | |||||||||
Estimation based on 1,000 replications, Exp: Expected number of loci with heterozygosity excess; Hex: Heterozygosity excess; IAM, infinite alleles model; TPM, 2-phase model (a combination of the IAM 30% and SMM 70%); SMM, stepwise mutation model. Significance at P < 0.05, with significant bottleneck effect indicated in bold
There was no evidence of linkage disequilibrium. Microchecker identified that the large allele dropout was not found and the OS63 locus showed the possibility of null allele presence. The selected 17 markers amplified well with an average of 95.4% of 100 individuals in PCR reaction (Table 2). In comparison among populations, the PCR amplification rates were 95.7% in Yeonggwang (n = 40), 99.4% in Taean (n = 20) and 93.2% in Seocheon (n = 40) (Table 3). These results strongly supported the effectiveness of these novel microsatellite markers with a good quality of detection, high polymorphism, and low frequency of null alleles.
These 17 highly polymorphic microsatellite markers hold significant potential for genetic diversity studies, conservation genetics research, and the implementation of effective management strategies for the protection of the O. stimpsoni marine species in Korea.
Limitations
One limitation of this study is the number of published microsatellite markers available for analysis may be insufficient for achieving optimal performance in certain genetic studies.
Acknowledgements
For help in obtaining samples, we thank (in addition to coauthors) the Dr. Min SeopKim, National Marine Biodiversity Institute of Korea.
Author contributions
H.Y. Song wrote the manuscript and analysed the data, Y.J. Choi carried out the experiment and analysed the data, D.-S. Lee planned the experiments, H.K. Choi contributed to sample preparation, K.M. Choi supported this projet and revised the manuscript, K.-Y. Yu revised the manuscript, N. Cho revised the manuscript and S. Lee design of the work and substantively revised the manuscript.
Funding
This work was supported by Korea Environment Industry & Technology Institute (KEITI) through project to make multi-ministerial national biological research resources more advanced program, funded by Korea Ministry of Environment (MOE) (RS-2023-00230404).
Data availability
Sequence data that support the findings of this study have been deposited in the NCBI, and their accession numbers are provided within the manuscript.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Sequence data that support the findings of this study have been deposited in the NCBI, and their accession numbers are provided within the manuscript.