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Short Note

Development of 101 Gene-based Single Nucleotide Polymorphism Markers in Sea Cucumber, Apostichopus japonicus

Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, China
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2012, 13(6), 7080-7097; https://doi.org/10.3390/ijms13067080
Submission received: 25 April 2012 / Revised: 25 May 2012 / Accepted: 25 May 2012 / Published: 8 June 2012

Abstract

:
Single nucleotide polymorphisms (SNPs) are currently the marker of choice in a variety of genetic studies. Using the high resolution melting (HRM) genotyping approach, 101 gene-based SNP markers were developed for Apostichopus japonicus, a sea cucumber species with economic significance for the aquaculture industry in East Asian countries. HRM analysis revealed that all the loci showed polymorphisms when evaluated using 40 A. japonicus individuals collected from a natural population. The minor allele frequency ranged from 0.035 to 0.489. The observed and expected heterozygosities ranged from 0.050 to 0.833 and 0.073 to 0.907, respectively. Thirteen loci were found to depart significantly from Hardy–Weinberg equilibrium (HWE) after Bonferroni corrections. Significant linkage disequilibrium (LD) was detected in one pair of markers. These SNP markers are expected to be useful for future quantitative trait loci (QTL) analysis, and to facilitate marker-assisted selection (MAS) in A. japonicus.

1. Introduction

The sea cucumber Apostichopus japonicus (Selenka 1867), naturally distributes along the coasts of China, Japan, Korea and Russia [1]. Due to their nutritional and medicinal value, they have long been exploited as an important fishery resource in East Asian countries. Over the past decade, the aquaculture of A. japonicus has become widespread along the coasts of China, due to increasing market demand and over-exploitation of wild sea cucumbers [2]. However, the rapid expansion and intensification of sea cucumber aquaculture has resulted in some severe problems, such as wide-spread disease and stock deterioration, possibly caused by inappropriate broodstock management and inbreeding depression [2]. In order to properly manage broodstock resources and efficiently enhance aquaculture production, control of inbreeding and selection of broodstock with the desired traits, such as rapid growth and disease resistance, are currently necessary for sustainable development of the A. japonicus aquaculture. Recently, marker-assisted selection (MAS) has become a valuable tool for selecting individuals with traits of interest [3]. To perform MAS, a large number of genetic markers are usually needed to determine the quantitative trait loci (QTLs) associated with economically important traits.
Single nucleotide polymorphisms (SNPs) have been shown to be the most abundant type of genetic variations in eukaryotic genomes [4], and are currently the marker of choice in a variety of genetic studies, such as high-density genetic linkage mapping and QTL analysis. However, only a limited number of SNP markers have been reported for A. japonicus [57]. Moreover, molecular markers developed from the expressed sequence tag (EST) databases offer several advantages over anonymous genomic markers, as (i) they can detect variation in the expressed portion of the genome, so that gene tagging could give “perfect” marker-trait associations; (ii) they could alleviate the problem of null alleles which is usually associated with markers developed from the non-transcribed regions; and (iii) they are expected to have greater transferability between species, since transcribed regions are more conserved among closely related species/genera.
Previously, our group has released a large amount of EST data by 454 sequencing of the A. japonicus transcriptome [7]. By mining our EST dataset, more than 54,000 putative SNPs have been identified, 200 of which were selected in this study for marker development. SNP validation was performed using 48 A. japonicus individuals collected from four natural populations. Genetic parameters of the validated SNP markers were evaluated using 40 A. japonicus individuals from a single natural population. These SNP markers will be useful for future QTL analysis in order to facilitate MAS in A. japonicus.

2. Results and Discussion

Transcriptomic sequences represent an important resource for rapid and cost-effective development of gene-based SNPs. For the high resolution melting (HRM)-based SNP marker development, we designed PCR primers for 200 candidate SNPs (Table 1), which were previously identified from the A. japonicus transcriptome generated by 454-FLX sequencing [7]. After PCR amplification, 159 (79.5%) amplified strong bands with expected sizes. The others were discarded without further consideration, as they produced bands larger than expected (possibly caused by introns) or resulted in poor amplification (weak or non-specific amplification). During the initial HRM screen, 63.5% (101) of the 159 successfully amplified loci showed polymorphisms in 48 individuals collected from 4 natural populations, 21.4% (34) generated non-polymorphic curves, and 15.1% (24) displayed unreliable melting curves. In this study, we showed that minor allele frequency (MAF) can serve as an important selection criterion to distinguish true SNPs from sequencing errors when performing SNP mining from 454 sequencing data (Figure 1). For example, most of the validated SNPs usually have a MAF of more than 35%, whereas most non-validated SNPs usually have a MAF of less than 25%. Although our study demonstrated that SNP markers can be efficiently developed from transcriptomic resources, it should be noted that the SNPs obtained may largely represent common genetic variations due to the low coverage of the original transcriptome sequencing, and may suffer from ascertainment bias resulting from simple sample source used in the original transcriptome sequencing.
Genetic parameters of the validated SNP markers were further evaluated using 40 A. japonicus individuals from a single natural population. As expected, all 101 SNP loci were polymorphic. The minor allele frequency ranged from 0.035 to 0.489 (Table 2). The Ho ranged from 0.050 to 0.833, while the He varied from 0.073 to 0.907. Thirteen loci departed significantly (p < 0.01) from Hardy–Weinberg equilibrium (HWE) after Bonferroni correction, suggesting that these loci may be under ongoing natural selection. Significant linkage disequilibrium (LD) was detected in one pair of SNP markers (ApjSNP092_CT and ApjSNP098_CT).
As the gene-derived SNPs reside in or are immediately next to protein-coding sequences, they stand a better chance for identifying functional genes that are responsible for complex traits as well as simply inherited traits [8,9]. In our study, 70 SNP markers (Table 2) were developed from the EST sequences showing significant similarity to an entry in the NCBI nr database [10]. Among the annotation information, genes potentially involved in growth or immunity (e.g., epidermal growth factor receptor, Zinc finger protein 62 homolog and heat shock protein 90 kDa beta) were identified. It would be interesting to see whether any of these growth- or immune-related SNPs are highlighted in future QTL mapping of economically important traits, such as high growth rate and disease resistance.

3. Experimental Section

3.1. Sampling and DNA Extraction

A total of 48 A. japonicus individuals used for SNP marker validation were collected from four natural populations (Dalian, Yantai, Qingdao and Wendeng) in China. Genetic parameters of the validated SNP markers were further evaluated using 40 A. japonicus individuals from the Rongcheng (Shandong, China) population. Genomic DNA was extracted from the muscles of sea cucumbers by following the protocol developed by Zhan et al. [11]. The quantity and integrity of genomic DNA was determined using an Ultrospec™ 2100 pro UV/Visible Spectrophotometer (Amersham Biosciences, Uppsala, Sweden) and gel electrophoresis, respectively.

3.2. SNP Discovery and Genotyping

Our group has recently released a large amount of transcriptomic data by 454 sequencing of eight cDNA libraries constructed using more than 200 sea cucumber individuals. Potential SNPs were detected from the assembled contigs using the program GS Reference Mapper (version 2.6, Roche 454 Life Sciences: Branford, CT, USA, 2011) with default parameters (cDNA mode). More than 54,000 putative SNPs were identified from the dataset, 200 of which were selected in this study for marker development with the selection criteria of at least 3× occurrence of the minority allele and at least 6× contigs coverage (number of reads forming the contig). SNP genotyping was performed using a recently developed cost-effective HRM method [12]. For each locus, three non-modified oligonucleotides were used, corresponding to two PCR primers and one probe, primers were designed using Primer3 [13] with the following rules: (1) primer length should be at least 20 bases; (2) product size should not exceed 120 bp in order to decrease the probability of intron interference; (3) the primer Tm should be between 59 °C and 61 °C; (4) the primer GC% should be 40%–60%; and (5) the amplicon contains only one SNP site. Probes were designed using OligoCalc [14] with the following criteria: (1) SNP site locates in the middle of the probe; (2) the length of probe is between 20 and 35 bases; (3) Tm is about 60 °C; (4) the 3′ end of each probe is blocked by two mismatch bases; and (5) no overlap between primes and probe. Each SNP locus was first amplified by an asymmetrical PCR with HRM fluorescent dye in the PCR master mix and then interrogated by an unlabeled probe. The 48 individuals of A. japonicus collected from four natural populations were used for SNP marker validation. PCR amplifications were carried out in a 10 μL reaction mixture containing 20 ng of genomic DNA, 1× PCR buffer, 0.2 mM dNTPs, 1.5 mM MgCl2, 0.5 U Taq DNA polymerase (Takara, Dalian, China), 0.1 μM forward primer, 0.5 μM reverse primer and 1× LCGreen Plus (Idaho technology inc., Salt Lake City, Utah, USA). The amplification was programmed as: an initial denaturation at 95 °C for 5 min, followed by 55 cycles of 95 °C for 40 s, 60 °C for 40 s and 72 °C for 40 s, finishing with a final elongation at 72 °C for 5 min. The PCR products were checked by gel electrophoresis, and those with correct PCR product sizes were then subjected to probe testing. An aliquot of the appropriate probe was added in each reaction to a final concentration of 5 μM. The PCR product and probe mixture were denatured at 95 °C for 15 min and then slowly cooled to 4 °C. HRM genotyping was immediately performed on a Light Scanner instrument (HR96 model, Idaho technology inc., Salt Lake City, Utah, USA) with continuous melting curve acquisition (10 acquisitions per °C) during a 0.1 °C/s ramp from 40 to 95 °C.

3.3. Data Analysis

Data were retrieved and analyzed using the Light Scanner software followed by manual curation of the obtained genotype calls. POPGENE [15] was used to analyze allele frequency, expected (He) and observed (Ho) heterozygosities, and tests for deviation from Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium (LD).

4. Conclusions

In summary, 101 gene-based SNPs were successfully developed from the transcriptome sequences of A. japonicus. These developed markers are expected to be useful for future QTL analysis, and to facilitate MAS in A. japonicus.

Acknowledgments

Financial support for this work was provided by the National Key Technology R&D Program of China (2011BAD13B05 and 2011BAD13B06), and the National High Technology Research and Development Program of China (2012AA10A412).

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Figure 1. Distribution of SNP minor allele frequency (MAF) for Apostichopus japonicus. The number above each bar was the polymorphic rate in respective MAF categories.
Figure 1. Distribution of SNP minor allele frequency (MAF) for Apostichopus japonicus. The number above each bar was the polymorphic rate in respective MAF categories.
Ijms 13 07080f1
Table 1. Results of validation and genotyping of candidate single nucleotide polymorphisms (SNPs).
Table 1. Results of validation and genotyping of candidate single nucleotide polymorphisms (SNPs).
CategoriesNumber of SNPs
Total number of tested SNPs200
Successful PCR159
Successful genotype calling135
 Polymorphic SNPs101
 Monomorphic SNPs34
Failed SNPs65
Table 2. Characterization of 101 SNPs for the sea cucumber Apostichopus japonicus.
Table 2. Characterization of 101 SNPs for the sea cucumber Apostichopus japonicus.
Locus IDGene NamePrimers and Probes (5′–3′)Size (bp)HoHeMAMAFp-Value
ApjSNP001_CTsimilar to Mech2 proteinF:CCTCAGTCCCAATCACCACT
R:ACACTGGCATACACCAGCAA
P:CAATGACTTCTCCTTCTCCTACAGCTTCC
980.2500.431T0.1280.239
ApjSNP002_CTIron-sulfur cluster assembly 2 homologF:TGAATCAGGCAGTTGTGATGA
R:GGTCCAGCTAGTCATGCTTTT
P:TCAAAGAAATACACTATTTCATCCGATAAAGCAAG
1020.2310.485C0.3970.080
ApjSNP003_ACProtein strawberry notch homolog 2F:AGCGATTATATCCGATGCAG
R:GCTGACCAGGGTAGTTCGAC
P:TACAAGAGTAGCCAATCAGAGGCGAGC
1080.4310.583A0.4890.482
ApjSNP004_AGThiosulfate sulfurtransferaseF:CAGTTGTAACTGCACCTCAGC
R:ATGCCTACTTGGATGCCAGA
P:ACCACAGGGTGTAGCCAGGTTCGTCAG
700.3140.342A0.1780.578
ApjSNP005_AGThiosulfate sulfurtransferaseF:AGGCATCCCTACGGGTATTT
R:ACAGGAATGAAGTGGCTTGG
P:TCGCTCTAGTCATTCCGCCTCAACG
700.3740.312A0.2400.857
ApjSNP006_CTDynein heavy chain 6, axonemalF:GGGAGGTCTTACGAAGTGGA
R:CGAGGAGTTCGGAGTAGCTTT
P:ACCCTACCGACTGTCGCAGAGAATG
970.2710.273C0.3840.345
ApjSNP007_AGSodium-dependent phosphate transport protein 2BF:ACCTTGGTGGCAGATATGGA
R:TTCAGTGTCCGCAGATTTCTT
P:AGTTGAATTAACGGCTCTCGAACCAG
750.2520.432G0.2870.418
ApjSNP008_GTTestis-specific serine/threonine-protein kinase 1F:CCACAATTAGCGATGGGTTT
R:CAAAGCTCCAGGACTTCTGC
P:GTTGTAGTGAACGCATTGGTTTAGGAAGGAAAC
1020.3490.488G0.4100.058
ApjSNP009_ACDisintegrin and metalloproteinase domain-containingF:CTAAAGGGGATCACCACGAC
R:ATAAGCAGGCTTCCCTTTCG
P:ACCTTTCGCCGGCCACGCCCT
940.2080.289A0.1040.365
ApjSNP010_GTZinc finger protein 62 homologF:CCACCAGATGTCTTTGATTCG
R:TCACGACCAATACTGCTTGG
P:AGATCCGACCCATGCAAGACCAAGGT
1060.4280.512G0.4480.552
ApjSNP011_AGKelch-like protein 9F:CAGTCAGCCTAGCCCTACCA
R:TCGTTGACCTTTGGTACTGATG
P:GTGCAAACCAATCGCAAGTCATTGTCGT
930.5000.498G0.4580.574
ApjSNP012_CTTATA box-binding protein-associated factor RNAF:CCTTCACTGGTATGGCATGTT
R:TGATCCATGTAGGGAGGCTTT
P:GTACATTAACTCTCCACAAGCTCCCTTGTA
880.3140.468T0.2400.045
ApjSNP013_ATProtocadherin Fat 3F:TGTTAGCACCTCTATCAAGGATGA
R:TTCCATACCTCCTGCCAATC
P:GTTCAAGGACACTTGATGGAAAGTGTAATGATT
1020.5000.454A0.4541.000
ApjSNP014_GTSeryl-tRNA synthetase, mitochondrialF:ATTCGTGTCCAGTTCGCAAT
R:GAGATCGGGCGATATAACCA
P:TCATATCAATTTGTGCCTCGAGGATCGAC
960.2710.276G0.3860.346
ApjSNP015_CTCreatine kinase, flagellarF:TCACAGGCCATCGATCATAC
R:CCTTTTCACCAACCTCTCCA
P:TCTAAGAGGTGCTGGTGCCCAGTAC
920.4360.502C0.4460.556
ApjSNP016_AGFibrinogen-like proteinA F:AATGGCCTCAAGAAAGTGGA
R:TCCAGTACCTAGATTTGAAGGACA
P:GAATTCATGTGGAGTGAGCATCTTGGAAT
1080.4300.583A0.4830.497
ApjSNP017_GTAbhydrolase domain-containing protein 14BF:CGGGGTCTACCTCATACAACC
R:CCTCCGCCATCTACAGTGTT
P:CATATATGGAGCCATTTGCTGTATATTGTAACATG
780.2930.444T0.4750.854
ApjSNP018_AGApolipoprotein A–I-binding proteinF:CATAGGTGTCCAGAAATGTTCG
R:TGTCCCATGTCTAAAGCATAACTG
P:CACAGAGTTCCCATGGGCAGATAGAAG
930.0730.083G0.0831.000
ApjSNP019_AGN-acyl-phosphatidylethanolamine-hydrolyzingF:CGTGCTCGGTTTTAATGTTG
R:CATGGTGAAACCTGGTAGACG
P:CCAAGCACAACCAGAACCGAGAAATCCA
910.6880.505A0.3540.498
ApjSNP020_ATPolypeptide N-acetylgalactosaminyltransferase 11F:AAAGAGGTATCGACCTTGTCCA
R:TGCTCGGACTGTATGTTCATC
P:TGGAGGAACTTCCAGAAATCAATGCTGAG
1090.2500.256A0.3280.857
ApjSNP021_AGHyalinF:TTCAAGTGGTATCACGAAAACG
R:CGTGCTATTGCCTTTGGATT
P:GCTGAGGCTTCCAAAAGATGACGATTC
920.1080.333A0.2900.557
ApjSNP022_CGTransmembrane protein 129F:TGGAATGCCACTAACACCAA
R:TTGACACCACACCACCAATC
P:TTGATATGTCTGCTGGGCTATTCTGGTA
800.4420.364G0.4830.381
ApjSNP023_CTMediator of RNA polymerase II transcription subunitF:GCTGATGAGCAATCTTCACACT
R:CAAGTTTCAGACGGGACCTG
P:GTCTTGATTATCCACGAATCTGTGACATACCA
950.1460.505T0.4890.051
ApjSNP024_AGAF339450_1 hillariF:TCCATTGAACGGAGGACTTC
R:CAAACATTTCAGCCTTGTGG
P:GTCTGGGATGGGATGTAGTCGACACTTA
1080.4190.484A0.3950.376
ApjSNP025_ACProteasome subunit beta type-5F:TCCAGATCGCTACGGTCTTC
R:ACGACCAGGTAGCTGCAGAG
P:TGGTGTATCAAGGAAATTCAAACCCAGCTGT
810.2500.250A0.4230.125
ApjSNP026_AGDynactin subunit 5F:GCCTGTTGCTGTTAACTTTCG
R:CTGGCATGTAACTCTATGAAACTC
P:GTTAAGTGAAAGTTGACTGCCTCAGTATTGTA
1100.3160.365A0.4610.724
ApjSNP027_AGApoptosis-inducing factor 2F:CAGAGAAAGCTGGAGATGATGA
R:ATGATTTCAACTGGGCCATC
P:GATGATGAACCGCAGAAGGGTTCGAA
880.5160.467A0.3610.324
ApjSNP028_CTUncharacterized protein C6orf163F:ATAGTTGGGTGTGGCTTTGC
R:CCGATGCAGTGATGGAAATA
P:AAATGTCACCTAACTGTGATTGATCCTCGCC
1040.2090.190C0.1050.698
ApjSNP029_ATF-box/LRR-repeat protein 2F:CCGTGATCCTAAATGAGGCTA
R:CGCTAAGAGTAAGAGAAAGAAGCA
P:GCCTAACCATACTGGATTGGCTAGCAGT
980.2710.237A0.1350.762
ApjSNP030_CTTBC1 domain family member 10BF:CCGGAGACGTAAAAGCACTC
R:TCGTCGTGTCTGGTATCCAC
P:AAGTCTGGACAGCTGTTAGCTAAGGGC
910.1910.174T0.0950.754
ApjSNP031_CGStejaggregin-A subunit alphaF:ATCGGTGCTAGACCCAAAGA
R:TCCTTCTCTGGTGAATTGATTG
P:CATCCCAACGACGGACCGATATGGTA
810.1500.245G0.2640.358
ApjSNP032_ACLysine-specific demethylase 6AF:CGAAGGCAACCAAGTAGGAC
R:TGCCACCTCGATCATTTTCT
P:CGCTGGTGTTAATAACTTCATAGTCCGTTAC
910.1380.833C0.3830.497
ApjSNP033_AGATP synthase subunit beta, mitochondrialF:GAGTAACAACGGCCCAGAAA
R:TACAGTGCCTACACCGGTCA
P:GGTCTGACCGCTATTGGGATCAATCTGC
760.4580.467A0.2320.854
ApjSNP034_GTUbiquitin carboxyl-terminal hydrolase 8F:GGCTTGAAGAAACATGGGTAA
R:CCAGTAGATTGCATCTTTCCATC
P:TCATGTTCACTTCTTTATACCACACGATGACAT
1100.2920.314G0.0351.000
ApjSNP035_CTUncharacterized protein C7orf26 homologF:CGGTGGTGAGGTGTCTACATT
R:GGAATAGGCAACTCGAGGAA
P:GTCGGTGAAGTACGAAGCCTTCATGAA
760.4490.367T0.4850.498
ApjSNP036_AChypothetical proteinF:AAGATGCCAGACAGCAACAA
R:CATGACTGCGTCTTCTGCTC
P:CAGGAATCTCACAGACGAGAGGGAACT
1000.5450.413C0.2640.857
ApjSNP037_AGDNA replication licensing factor MCM8F:GGAACCGGAGAGATGACAGA
R:CCAGCGTCGTCACCTTTTAC
P:AGAGCAAGATCAACAGAATGAGGACAAAGTA
950.4920.502A0.4580.557
ApjSNP038_AGLRP2-binding proteinF:GATGAAAGTACCTGGGAGGAA
R:AGCTGATCATCGGTCCATCT
P:GGAGATTGAAGATTGATCCCACTGACAAACTC
830.7500.625G0.1470.381
ApjSNP039_AGEndoplasminF:ATAACGTCGGACGAGCATTC
R:AGCAACCACCATCTCTCTGC
P:AAGGGTTTGGAGTAAAACAGTCGGATGCCC
760.4090.479G0.3870.051
ApjSNP040_CTheat shock protein 90 kDa betaF:CTTTGAAGATATGATGCCCAAG
R:TTGTGTTGCTGCAGGGTTT
P:ACTCCGATGACCTGCCTCTCAATGTGA
1020.3480.291C0.1740.084
ApjSNP041_CTTitinF:AGCCATCGAGAATGAGAAGC
R:TGATGGTCTGTTCGATCCAC
P:GGTCACCGACTACGACAAGATCTCCTGC
820.3820.314T0.1920.091
ApjSNP042_AGMidasinF:CAGCCTGGAAGACCCTCAGT
R:TTGGACTTCCACCATCAGAA
P:AACCAGGCTACGATTTCATGGACCGGT
880.8000.691G0.2910.635
ApjSNP043_CTScavenger receptor cysteine-rich type 1 protein M130F:GGTTCACAACCTCAGGATGAC
R:CTTCTGCACACCGCACTTT
P:GAAATTACAACCTGCTTTAGTGTCCAGAGATAG
950.3170.505C0.4760.200
ApjSNP044_ACFK506-binding protein 15F:TCATACACTCAGGGCATCCA
R:GCGTAGGCATATGACGAGAGA
P:CAGTTTTGTGAGTGTCTTGACAGTGATAGTGG
900.5830.473A0.3320.149
ApjSNP045_ACTitinF:CGTTGAGATCCAAGTCAATGAG
R:TGTAGGTGAGTGGTGAACGTG
P:TAGAAAGAATGGACAGCGTCCCTGGAGT
1050.5120.502A0.4560.897
ApjSNP046_AGRadial spoke head protein 4 homolog AF:GGGGAAGATGAGGTAGAAACG
R:GCTCATACCGATTCCTGCTT
P:ACTCCCAAACCTACCGGAACTTATGTTTTAGA
810.1130.109G0.0560.623
ApjSNP047_CTPhenylalanyl-tRNA synthetase beta chainF:TGGCAAATCAATCGGATTCT
R:AACGGTTCAATGGTTATCTCTAGG
P:CTCAAAGTTTGAGCTTCCAAACCCATGTGGA
1020.3260.300T0.1780.653
ApjSNP048_AGMitochondrial inner membrane proteinF:CCGATGAGAGGGGTATTCAA
R:CCCCCATTCTCGTCTATCAG
P:GGGAGAGGTGGGAGAATATCCAGAGATA
980.2220.468A0.3610.002 *
ApjSNP049_CTSulfotransferase family cytosolic 1B member 1F:CCAGGGTAAAGTCAAAGGTCA
R:ACTGTAGCCCAGAACGATGC
P:TCCTTTCATTTTCCCCTCGTACAAGTCATGT
820.5240.479T0.2780.401
ApjSNP050_CTRalA-binding protein 1F:GGTTGAGGAGTTCTTGGGAGT
R:CATCAGCATGATCCAACACA
P:CTGAATGATTTGCCAACTTGTAACTACACCTTAGA
1050.2500.408C0.2750.018
ApjSNP051_GTAlpha-amylase BF:TTCGATTCATCTGGTGCTTG
R:CTTGACCTTCGCAGGTGTTT
P:TGGAGAGAGATCCGTAACATGGTCGAATTGT
1070.0960.481T0.3900.005 *
ApjSNP052_GTPutative vitellogenin receptorF:CAGTCTGAAAGAACCACTGAAGA
R:CGAGTATAGGAGGCTGAAAACG
P:GCCCAGAAGATATCGCCTCTCTTCAAATAGG
980.4110.485G0.4000.758
ApjSNP053_CTUDP-N-acetylglucosamine--peptideF:TCGAAGCTAGATTACTGTGAGCA
R:TCTGAAGGAGATGCAGGACA
P:TGATTTGGATGGCTCTGGTATAGCACTCA
1010.0710.503T0.4040.000 *
ApjSNP054_CTKanadaptinF:CAAGCCGTACATGAAAGCAA
R:TGTCCAGGTACGAGTCATCG
P:AGAAGAAGAAGAATTGGGCGGACGATCT
880.5850.506C0.4890.307
ApjSNP055_GTEpidermal growth factor receptorF:TCACGTTCCACCAGATTTTG
R:ATGATGGGGGTAATGGCATA
P:TGACCAATAGCATATTCGATGTGATGTCACCA
1040.2530.435G0.4240.518
ApjSNP056_CThypothetical proteinF:ATGCCACCCTCTTAATCTGG
R:CTTGCCTGGGTTTTCCATAC
P:TCAGACCGGTGCTTCTGACAGTACATT
1070.1250.117T0.3180.442
ApjSNP057_CGRuvB-like 2F:CCATAACACCGATGACACCA
R:GAAGCTGATAAGATGGAAGTAGCC
P:CATTGTCAAGGCAGTCATCTTGTCAGGA
1080.2950.388C0.2580.159
ApjSNP058_AGEyes absent homolog 1F:CGTATCCCGTACCACAACCT
R:AACCCGTAGGGAACCTGACT
P:GGTGTGCAACCAAACGCTGGGTACGG
790.4000.501G0.2470.485
ApjSNP059_CTWD repeat and FYVE domain-containing protein 3F:TTCCAGGGATTTGACAGAGG
R:TGGCATCTAAAGCTGCTAGTCT
P:TCCAGGAGAGATCCTAGGGTGTACTGGG
1100.5300.500C0.4460.984
ApjSNP060_ATsimilar to LOC398543 proteinF:CCACTACACATCGGTGACCA
R:CATCTCCTTCCGATAACACAGTT
P:AGATGAAGAATGTATTATTAACGCTGCACACT
1100.0950.433A0.3090.008 *
ApjSNP061_CTCoiled-coil domain-containing protein C6orf97F:GCTGTTGCCGATGAAACAAT
R:CAAATTGAACGAGATGGAGACA
P:AGAATATCCTGCCTTGGGATAACGTAAACC
1100.4790.447T0.3290.489
ApjSNP062_CTUncharacterized gene 48 proteinF:CAGAAGGATAAAGTCCAAGAGACC
R:TTCTCCTTTCTGTCCATCCTG
P:ACAGGCCTATAGCTACGATCAGGAATCG
860.1820.220T0.1980.809
ApjSNP063_ATUncharacterized protein C2orf73 homologF:CACATGTGTCACCTCTGGCTA
R:ACTGGAACAGCGCCTTTAGA
P:CAGCTCAAACCCTCACAACTATGCAAG
730.4790.586A0.3110.252
ApjSNP064_ATMethionine synthaseF:TCGATACCCTTCACCAAAGAAT
R:CGAGGGTCTTGGGAAAGGA
P:CCAGGCTTCATCATCAACAGCTTTCTAA
1030.4860.495T0.4320.654
ApjSNP065_CTTubulin alpha chainF:CATAGCTTCGGTGGTGGAAC
R:GCTTCGATTTCTTGCCGTAG
P:GGATTTGCAGCTCTACTTCTTGAACGCG
850.0610.091T0.0911.000
ApjSNP066_AGTATA element modulatory factorF:TGGTGCTCAGCTGAATCTGT
R:TGGTCTCTTCGTGAGCCTCT
P:GAAACAACAAGACAACCTCGAGAGGCTT
860.4150.100G0.3210.007 *
ApjSNP067_AGTATA element modulatory factorF:GCAACTGGAGGCAGAGAGAG
R:GGCCTGCTCGAGTTTACCT
P:AGAGACCAAGGAAGAGCTGGAAGAGAA
790.3150.400A0.2060.486
ApjSNP068_CTUncharacterized protein KIAA1704 homologF:TGACACCTATGGACCGTCTCT
R:GGAGGTAATGGTGGACCAAA
P:GGATTCAAAGGTGTCGACAAAGAGTCTGAAC
900.4120.504C0.4770.135
ApjSNP069_CTWD repeat-containing protein KIAA1875F:GGGTCTTCCAGCCAATGATA
R:ACCACGGCTACGTTTGAGTC
P:TACTGGTTGATCGCTCTGGAAGAAACAGGA
1030.3260.225C0.4710.390
ApjSNP070_AGGlycoprotein 3-alpha-l-fucosyltransferase AF:CCAGGAAGGGGTAGACTTGC
R:ATCTCGCCGTTCAAGTTGTT
P:CTCAGGAAGTTCTAGAGAGGAAGGATGTC
1020.5280.469G0.3340.051
ApjSNP071_AGN/AF:CGAAACTATAGTGACCTCTTGGTTA
R:CAAGCCCTAGTCTCTTCATTCG
P:CAGAATTTCTCTCGAAGTCCTTTGCCAG
1040.3640.470A0.3640.189
ApjSNP072_AGN/AF:GAGTTAGACCCTCGGCTAGGTA
R:GCAAAGAGCCTAGCCTTTAGGT
P:TGCATCAGTACTAGCAGCATGGAAAACT
870.3880.412G0.3330.247
ApjSNP073_AGN/AF:AAATGTACAGACCCGCATGA
R:CTGGAAAAACAGTGTGAACCAA
P:TGTAAAATTAATGAGCCGTTCGAACCAAGAG
1070.2250.309A0.1880.104
ApjSNP074_ATN/AF:GATGGTGAAAATCACGGAGAA
R:TTCTATGTCTTGTTGATGCAGAGAC
P:CACAATAACCTGGAAATATCAACCTTAGAAGAATTCA
1030.3000.404A0.2750.108
ApjSNP075_ATN/AF:GACCACGATGACAGCCAGTA
R:CTCGCCAAGTCAGGAAAAAG
P:AGGATCGTCATTCGGGCACTCTTGG
950.6300.879T0.4500.328
ApjSNP076_CTN/AF:AACTCTCGATGGAATGCAAAG
R:AACAGACTCGGTCGCATCTC
P:GATAGTTCTGACAGCGATTTAGGAGACTAA
1080.1750.392C0.2630.001 *
ApjSNP077_CTN/AF:AACCATCCTGTAGCGAAACC
R:CGGGGACGAGGATATTGTTA
P:GTGTTGAATGAAGTCGTTCGCGTAAATGC
1030.1750.339T0.2130.004 *
ApjSNP078_GTN/AF:GCCAAGCAACATACAGAAGGA
R:TAGTTGGGCTGTCTTGCTGA
P:TTGCTGCATTAATGTTTAGATGATGATGTGTCT
870.5630.907T0.4870.637
ApjSNP079_AGN/AF:TGGGCAGAAGAAAATTTGGA
R:GAGTGGCACATGACTTGGTG
P:CTGCAATTGGACAACCCCATGCTCAT
990.4750.469G0.3750.084
ApjSNP080_CTN/AF:GGGCGCTATCAGACTTTGAC
R:GCACCCTCTATTTTAGCTGTTCA
P:TCTTGCTAGCTAATGGGAAAGAACGTTAT
1100.2000.292C0.1750.062
ApjSNP081_CTN/AF:CTGGTTGCAATAGGTTATTTGG
R:TGAATACATGCCGTTTCTGA
P:GTTGGATTCAGAACACAGACTGCCATTCC
1030.0750.073C0.0380.780
ApjSNP082_CTN/AF:CAGAAACGGCATGTATTCAAAC
R:CCCGACCACAAGGAAAGATA
P:AGGGGAGTTTGTGATGACAAATTGTTGCAG
940.5000.404C0.2750.098
ApjSNP083_ACN/AF:CACGATGCCCTGTGTGTAAT
R:GTCGGCCTCCTGACTAACAG
P:GCGCAGCAGAAACGGCGTGGA
1080.3250.453C0.3380.073
ApjSNP084_CGN/AF:GGGTGGTGCATTTTCTTCAT
R:TGGCTTCAGTTACACCATCCT
P:ATCCTTGTGGTCGCCTGATCTTGTGTT
750.1500.444G0.3250.000 *
ApjSNP085_AGN/AF:CGTCATTCGCTCCAAATACC
R:GTCGTAGAGAGACATAACGATAACTGA
P:CCATAATGCATAGTGGCTGCAGCATAA
1100.8330.896A0.4870.093
ApjSNP086_AGN/AF:CGACAATATACTACAAATGCCCTGT
R:GATGATGAATGGGTTGTTTGTG
P:CAAGGCGAGTTCGTCACACGAAAAGT
830.0500.461G0.3500.000 *
ApjSNP087_ACN/AF:CACTCTGGCCTTGCACTCTT
R:TGTGAGAACAATAGGTTCACAGGT
P:GGGCAAACTGATGTCATGTTCACAGGTATGT
1090.4500.353C0.2250.252
ApjSNP088_AGN/AF:ATGAAGCATGCGTGAATGAG
R:CGATTTCACTGCTGTCATCAA
P:AACTGTGGAGATGGTAACATATTCTATGAAGAGAA
830.2500.222G0.1250.256
ApjSNP089_AGN/AF:TGGTGAGAAGCATCCACAGA
R:GTTGTTTTGAAGGCACTGATGA
P:AAGTTCTTAAATGCAGAACTGGGTCAGAACA
930.3250.468A0.3630.051
ApjSNP090_CTN/AF:TTGTACCGAGAAAGGGATGTTT
R:CCTGAACAACATCTGCCTGA
P:AGAGTATATTTCAAACGAAAACGGGAGTAGGGT
1100.1610.373T0.2420.002 *
ApjSNP091_CTN/AF:TGCGTCATTCTAACCAACCA
R:AACACTTATGTAGGCGAGTCTTGA
P:CAAAGCGCTTCATTTTCACAGCAACTA
1020.2000.380C0.2500.004 *
ApjSNP092_CTN/AF:TGACTGGACGTCAGATGTGG
R:GTGGGCTTCCAGACACAGAT
P:GGTTGCATCAAGGTCCCTGGGTACATACA
810.0750.073C0.0380.780
ApjSNP093_AGN/AF:TGAAATGTGGTGTGACTTGC
R:TGTGTGACTTCAGCATCTCTGT
P:GAATTGTATAATTGGATGCTGTGTGTCACTTAT
800.2220.282G0.1670.227
ApjSNP094_GTN/AF:TCTGCTAAGTTGTTGAGAGGATG
R:CGAACGGTTGGTATTTGTGA
P:TTCTGGTCACTTGCCCCAGGTTCCAC
1080.1710.358T0.2290.003 *
ApjSNP095_AGN/AF:ATTTGCGGCTCTTCTGTTCA
R:TGAAGTGAACTCACCCACGA
P:AAACTTGGCAACGAAGACGTCAGCAT
1100.2250.367A0.2380.018
ApjSNP096_CTN/AF:TCATTCCTGTATTGCTACTACTCTGTG
R:TGTGGTATGCCCATCGATTT
P:TAAACAATAGTACTTAATGGCATTGAAGACAACAAAC
1090.3330.491C0.4090.060
ApjSNP097_CGN/AF:CACAGTGATGTGTATGTACGTTCG
R:GACCTTCGCTTTGTGCCTAC
P:ACACACCGTATATACCGAATCTGGAAATTATCTT
940.3160.337C0.2110.698
ApjSNP098_CTN/AF:CTGTGTCAGAGAGGAAGAGTGC
R:CGAAAGCTATTTCAAACCCAGT
P:GGGTACTATCAAAATTGACTCACAAAGCGAC
1070.1580.147C0.0790.512
ApjSNP099_AGN/AF:GACCTTCTGCTCTGCCTGAC
R:CGGATATCAACAAACCAGAGC
P:TCCTCATCTTCGGTGTCTTGCGAAC
970.0750.162G0.0880.080
ApjSNP100_GTN/AF:TCCACTGAGCCATCCTGATT
R:GAAGAAAAACATGTCCCGATG
P:AGTGGCTCCCCCTGGAATGTAATCCTG
1030.5050.547T0.4580.279
ApjSNP101_GTN/AF:CTGCTGAAGTATGACAACATTAGAGAC
R:CTAGTACTTTCTTCTTCAGTAGTTGG
P:CTATTGAAAGCTCGATAGGCACATCCTG
1090.0750.240T0.1380.000 *
The underlined bases in the probe sequences indicated the positions of the SNPs; Ho, observed heterozygosity; He, expected heterozygosity; MA, minor allele; MAF, minor allele frequency; PHWE, P values for Hardy–Weinberg equilibrium (HWE) test;
*, statistically significant after sequential Bonferroni correction.

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MDPI and ACS Style

Du, H.; Bao, Z.; Yan, J.; Tian, M.; Mu, X.; Wang, S.; Lu, W. Development of 101 Gene-based Single Nucleotide Polymorphism Markers in Sea Cucumber, Apostichopus japonicus. Int. J. Mol. Sci. 2012, 13, 7080-7097. https://doi.org/10.3390/ijms13067080

AMA Style

Du H, Bao Z, Yan J, Tian M, Mu X, Wang S, Lu W. Development of 101 Gene-based Single Nucleotide Polymorphism Markers in Sea Cucumber, Apostichopus japonicus. International Journal of Molecular Sciences. 2012; 13(6):7080-7097. https://doi.org/10.3390/ijms13067080

Chicago/Turabian Style

Du, Huixia, Zhenmin Bao, Jingjing Yan, Meilin Tian, Xiaoyu Mu, Shi Wang, and Wei Lu. 2012. "Development of 101 Gene-based Single Nucleotide Polymorphism Markers in Sea Cucumber, Apostichopus japonicus" International Journal of Molecular Sciences 13, no. 6: 7080-7097. https://doi.org/10.3390/ijms13067080

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