Genetic diversity analysis of Perinereis aibuhitensis based on ISSR and SRAP markers of Chinese coast populations

Biochemical Systematics and Ecology 57 (2014) 262e269

Contents lists available at ScienceDirect

Biochemical Systematics and Ecology journal homepage: www.elsevier.com/locate/biochemsyseco

Genetic diversity analysis of Perinereis aibuhitensis based on ISSR and SRAP markers of Chinese coast populations Fei Liu a, b, c, d, Qiao-sheng Guo b, Hong-zhuan Shi b, Fu Lv a, *, Ye-bing Yu a, Lin-lan Lv a, Jin-tian Huang a, Ai-ming Wang a, Hui-xing Liang d a

Key Laboratory for Aquaculture and Ecology of Coastal Pool of Jiangsu Province, Department of Ocean Technology, Yancheng Institute of Technology, Yancheng 224051, China b Institute of Chinese Medicinal Materials, Nanjing Agricultural University, Nanjing 210095, China c Biology Postdoctoral, Nanjing Agricultural University, Nanjing, 210095, PR China d School of Chemical and Biological Engineering, Yancheng Institute of Technology, Yancheng 224051, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 30 June 2014 Accepted 24 August 2014 Available online

The objective of this study was to obtain an overview of the genetic relationships within Perinereis aibuhitensis using Inter-Simple Sequence Repeat (ISSR) and Sequence-Related Amplified Polymorphism (SRAP) markers that were derived from related populations residing in the Chinese coasts. The percentage of polymorphic bands, Nei's gene diversity and Shannon's information index revealed a high level of genetic diversity at the species level. The analysis of molecular variance revealed that 81.22% (ISSR) and 76.29% (SRAP) of variability were partitioned among individuals within populations, which indicated the coherent trend by Nei's genetic differentiation (Gst) (0.2568/0.2876). The gene flow number (Nm) was 1.4470/1.2385, which indicated that there was limited gene exchange between populations. The phylogenetic tree of the ten P. aibuhitensis populations was separated into four major clusters using the neighbor-joining (NJ) method. These results provide a simple and useful basis for P. aibuhitensis germplasm research and aquaculture breeding. © 2014 Elsevier Ltd. All rights reserved.

Keywords: Perinereis aibuhitensis ISSR SRAP Molecular markers Genetic diversity

1. Introduction Perinereis aibuhitensis, a Polychaete with high medicinal value (Liu et al., 2002), colonizes estuarine and shallow softbottom environments in the temperate and tropical zones of the Northwest Pacific (Sun and Yang, 2004). Near the coasts of China, this species is commonly found in estuarine habitats and in intertidal areas that have clay sand bottoms. P. aibuhitensis is a commercially important species that can be used as a high quality feed in both aquaculture and recreational fisheries, and has been cultured in Northern China. Due to its high tolerance to stressors, P. aibuhitensis was also proposed as a target species for the biomonitoring of pollution (Mouneyrac et al., 2003). Wild populations of P. aibuhitensis have been decreasing in recent years because of overfishing. Therefore, it is important to perform germplasm resource protection and artificial breeding of P. aibuhitensis. Previous studies identified species that have a similar appearance to the P. aibuhitensis population, but exhibit differences in their genetic structure. The life cycle (Jiang

* Corresponding author. Tel./fax: þ86 515 88298190. E-mail addresses: fl[email protected], [email protected], fl[email protected] (F. Lv). http://dx.doi.org/10.1016/j.bse.2014.08.025 0305-1978/© 2014 Elsevier Ltd. All rights reserved.

F. Liu et al. / Biochemical Systematics and Ecology 57 (2014) 262e269

263

and Zheng, 2002), gonad development (Yang et al., 2010) and ecological culture (Fang et al., 2014; Sun et al., 2009) of P. aibuhitensis have been extensively studied in recent years. However, the knowledge of their phylogenetic relationships and genetic diversity is currently limited (Liu et al., 2012a; Wang et al., 2014). It is difficult to study the genetic diversity and genetic relationship solely on morphological characteristics. Therefore, it is necessary to employ additional DNA markers for further evaluation at a molecular level. Molecular markers can be appropriate tools for identifying relationships between species. Moreover, molecular markers are effective for DNA fingerprinting, genetic diversity analyses and germplasm evaluation. Sequence-Related Amplified Polymorphism (SRAP) (Li and Quiros, 2001; Liu et al., 2008) and Inter-Simple Sequence Repeat (ISSR) markers have been recognized as a new and useful molecular marker system in buffalograss (Budak et al., 2004), medicinal Chrysanthemum morifolium (Shao et al., 2010) and Whitmania pigra (Liu et al., 2013). The genetic characteristics of P. aibuhitensis, however, are currently unknown. To our knowledge, no study to date has examined the application of SRAP markers to study the genetic diversity of P. aibuhitensis. The present study was conducted to understand the genetic diversity and genetic relationships of the various accessions sampled from ten representative populations in China (150 individuals) using ISSR and SRAP markers. The objectives of this study were to more clearly define the genetic diversity of P. aibuhitensis in China. This study will aid in the long-term objective of identifying genetic diversity analyses among and within populations of P. aibuhitensis using molecular markers. 2. Materials and methods 2.1. Animal materials The animal materials used in this investigation were isolated from ten populations and represented almost all of the natural distribution areas of P. aibuhitensis in China. These populations can be grouped into four regions: The Bohai Sea coast (DL), the Yellow Sea coast (LYG, SY, DT, RD and TZ), the East China Sea coast (NB and WZ), and the South China Sea coast (YJ and QZ) (Fig. 1 and Table 1). A total of 150 individuals from the ten populations were included in this study. Fresh abdominal muscle from each animal was collected and immediately dried with silica gel. All samples were stored at 70  C until processing. 2.2. DNA extraction Total genomic DNA was extracted using the protocol established by Sambrook and Russell (2001). The quality and quantity of the DNA were determined using 0.8% agarose gel electrophoresis. DNA samples were diluted to 50 ng ml1 with 1  TE buffer and stored at 20  C prior to PCR amplification. 2.3. ISSR-PCR and SRAP-PCR amplification For all methods, the polymerase chain reaction (PCR) mixtures and electrophoresis conditions were performed as described by Liu et al. (2013). The amplifications were performed using a PTC-200™ thermal cycler (MJ Research Company, USA) using the following conditions: an initial 5 min denaturing step at 94  C, followed by 45 cycles of 45 s at 94  C, 45 s annealing at 45e56  C, and a 1 min extension at 72  C, ending with a final extension of 4 min at 72  C for ISSR. 4 min of denaturing at 94  C, 5 cycles of 1 min at 94  C, 1 min at 35  C and 1 min at 72  C; 30 cycles of 1 min at 94  C, 1 min at 55  C and 1 min at 72  C; 1 cycle of 4 min; and 1 cycle of 4 min at 10  C for SRAP. The ISSR products were visualized by electrophoresis on 1.5% (w/w) agarose gels containing 0.5 mg ethidium bromide ml l1 in 1  TAE (40 mM Triseacetic acid and 1 mM EDTA pH 8.3) buffer and then photographed under ultraviolet light using a JS-380B automatic gel imaging analyzer (PeiQing Co. Ltd.). A Gene Ruler™ 100 bp Ladder Plus (Sangon Co. Ltd., China) marker was used as a molecular size ladder. A Hoefer vertical-gel apparatus (JY-SCZ6) was used to fractionate 10 ml of SRAP amplified products on an 8.0% nondenatured polyacrylamide gels. The gels consisted of acrylamide (19 acrylamide:1 bisacrylamide) in 1  TBE buffer (90 mM Triseboracic acid, 2 mM EDTA; pH 8.0). Electrophoresis was run at 200 V for 2.5 h at room temperature. The gel was then subjected to rapid silver staining for detection (Liu et al., 2013). Thirty ISSR primers and 36 SRAP primer pairs combinations were selected for their consistent amplification and clear banding patterns (Table 2). 2.4. Data analysis The presence or absence of each fragment was coded as “1” or “0”, respectively. POPGENE version 1.32 (Yeh et al., 1999), AMOVA (Excoffier et al., 1992) and the Numerical Taxonomy Multivariate Analysis System (NTSYS-pc) version 2.10 software package (Rohlf, 2004) were used to calculate the parameters for the distance matrix and genetic diversity. Shannon's information index (I) (Shannon and Weaver, 1949) and Nei's gene diversity (He) (Nei, 1972) were used to compute Nei's standard genetic distance coefficients (Nei and Li, 1979) and to construct a neighbor-joining (NJ) method with Molecular Evolutionary Genetics Analysis (MEGA) 5.1 software (Tamura et al., 2011). Gene differentiation between populations was estimated by the coefficient of gene differentiation (Gst) and gene flow (Nm) (Slatkin, 1987) using POPGENE

264

F. Liu et al. / Biochemical Systematics and Ecology 57 (2014) 262e269

Fig. 1. The locations of the populations sampled in this study were separated into four geographical regions, as described in Table 1.

version 1.32 (Yeh et al., 1999). To examine the genetic relationships between populations, Nei and Li (1979) genetic distance was also generated by POPGENE. A Mantel test between geographic and Nei's genetic distance was performed using NTSYS-pc version 2.1 (Rohlf, 2004). The correlation between similarity matrices generated by ISSR and the SRAP datasets was estimated by using the Mantel test (Mantel, 1967). Principal Coordinate Analysis (PCA) was used to construct a three-dimensional array of eigenvectors using the DCENTER module of the NTSYS-pc program (Sneath and Sokal, 1973). 3. Results 3.1. Polymorphism levels Of the ISSR markers analyzed, 268 bands were observed in total, 267 of which (99.63%) were polymorphic among the P. aibuhitensis biotypes and were shared between at least four individuals. Table 3 shows the average genetic diversity and PPB Table 1 P. aibuhitensis populations examined in the present study. Population code

Sample size

Location

Longitude (E)

Latitude (N)

Origin

DL LYG SY DT RD TZ NB WZ YJ QZ

15 15 15 15 15 15 15 15 15 15

Dalian, Liaoning Province Lianyungang, Jiangsu Province Sheyang, Jiangsu Province Dongtai, Jiangsu Province Rudong, Jiangsu Province Tongzhou, Jiangsu Province Ningbo, Zhejiang Province Wenzhou, Zhejiang Province Yangjiang, Guangdong Province Qinzhou, Guangxi Province

38.44 34.48 33.42 32.46 32.17 32.05 30.26 27.83 21.71 21.73

121.10 119.11 120.28 120.50 121.22 120.59 121.38 120.77 111.86 108.56

Semi-wild Wild Semi-wild Wild Wild Wild Wild Wild Wild Wild

F. Liu et al. / Biochemical Systematics and Ecology 57 (2014) 262e269

265

Table 2 The primers used for the molecular analysis. Primer

Sequence

Primer

Sequence

(a) ISSR ISSR-1 ISSR-2 ISSR-5 ISSR-9 ISSR-14 ISSR-17 ISSR-22 ISSR-24 ISSR-26 ISSR-27 ISSR-30 ISSR-33 ISSR-34 ISSR-35 ISSR-42

ACACACACACACACACT ACACACACACACACACAT ACACACACACACACACTG CTCCTCCTCCTCCTCCTC TCTTCTTCTTCTTCTTCT GACAGACAGACAGACA ACACACACACACACACAA ACACACACACACACACTC ACACACACACACACACCC TGTGTGTGTGTGTGTGCG TGTGTGTGTGTGTGTGTC AGAGAGAGAGAGAGAGAT AGAGAGAGAGAGAGAGAA AGAGAGAGAGAGAGAGTA ACACACACACACACACCG

ISSR-44 ISSR-48 ISSR-49 ISSR-50 ISSR-56 ISSR-57 ISSR-58 ISSR-60 ISSR-61 ISSR-64 ISSR-65 ISSR-68 ISSR-69 ISSR-70 ISSR-76

ACACACACACACACACGA TGTGTGTGTGTGTGTGAA TGTGTGTGTGTGTGTGAC TGTGTGTGTGTGTGTGAG AGAGAGAGAGAGAGAGTT AGAGAGAGAGAGAGAGTG AGAGAGAGAGAGAGAGGA AGAGAGAGAGAGAGAGGG AGAGAGAGAGAGAGAGGT AGAGAGAGAGAGAGAGCG AGAGAGAGAGAGAGAGCC TCTCTCTCTCTCTCAG TCTCTCTCTCTCTCTG TCTCTCTCTCTCTCGA AGTCAGTCAGTCAGTC

(b) SRAP E1 E2 E3 E4 E5 E6 E7 E8 E9 E10

GACTGCGTACGAATTCAA GACTGCGTACGAATTCTG GACTGCGTACGAATTGAC GACTGCGTACGAATTTGA GACTGCGTACGAATTAAC GACTGCGTACGAATTGCA GACTGCGTACGAATTGAG GACTGCGTACGAATTGCC GACTGCGTACGAATTTCA GACTGCGTACGAATTCAT

M1 M2 M3 M4 M5 M6 M7 M8 M9

TGAGTCCAAACCGGATA TGAGTCCAAACCGGAGC TGAGTCCAAACCGGACC TGAGTCCAAACCGGACA TGAGTCCAAACCGGTGC TGAGTCCAAACCGGAGA TGAGTCCAAACCGGACG TGAGTCCAAACCGGAAA TGAGTCCAAACCGGAAC

M1

M2

M3

(c) Polymorphism of different SRAP primer combination E1 þ  þ E2  þ  E3 þ  þ E4    E5 þ þ  E6  þ þ E7    E8    E9 þ   E10   þ

M4

M5

M6

M7

M8

M9

þ   þ þ     

þ  þ   þ þ þ þ þ

þ  þ    þ   

   þ   þ   

 þ þ  þ þ þ  þ þ

 þ þ       þ

(a) For the ISSR analysis; (b) for the SRAP analysis; (c) polymorphisms of the different SRAP primer combinations. Horizontal lines are forward primers; vertical row are reverse primers. : Monomorphism, þ: Polymorphism.

for each population, with a total average genetic diversity of 0.8420. The “QZ” population had the highest PPB (90.23%) and the “DL” population had the lowest (76.35%). The Ae was also lower than the Ao, ranging from 1.3314 to 1.4206. Shannon's information index (I) ranged from 0.4756 to 0.5683, and a similar trend was observed for PPB and He. The genetic variation indices at the species' level were: PPB ¼ 99.63%, Ao ¼ 1.9963, Ae ¼ 1.7823, He ¼ 0.6587 and I ¼ 0.5230 (Table 3). In total, 466 of the 468 SRAP markers (99.57%) were polymorphic among the P. aibuhitensis biotypes. The average genetic diversity and percentage of polymorphic bands for each population are summarized in Table 3. The “QZ” population had the highest PPB (83.55%) and the “SY” population had the lowest (75.00%). The Ae ranged from 1.3268 to 1.4289 and was slightly higher than the Ao. Shannon's information index (I) ranged from 0.4816 to 0.5796 and showed a similar trend that was observed for the PPB and He. The genetic variations indicated at the species level were: PPB ¼ 99.57%, Ao ¼ 1.9957, Ae ¼ 1.7524, He ¼ 0.6889 and I ¼ 0.7256 (Table 3). 3.2. Level of diversity and molecular variance Based on the values for Nei's total gene diversity (Ht ¼ 0.3869) and Nei's gene diversity within populations (Hs ¼ 0.1506), Nei's genetic differentiation (Gst) was calculated to be 0.2568 in the ISSRs using the POPGENE software, whereas Ht ¼ 0.4105, Hs ¼ 0.2156 and Gst ¼ 0.2876 for the SRAPs. Therefore, a relatively higher level of genetic differentiation within the populations was indicated by the ISSRs; however, the Gst was 0.2876 in the SRAPs, indicating that 28.76% of gene differentiation occurred among populations and 71.24% occurred within populations. These results indicate a relatively high level of genetic differentiation within the populations. The average number of individuals exchanged between populations per generation (Nm) (the number of migrating individuals deduced from the gene differentiation coefficient) was 1.4470 and 1.2385 by the ISSRs and SRAPs, respectively.

266

F. Liu et al. / Biochemical Systematics and Ecology 57 (2014) 262e269

Table 3 Genetic variations between the ten populations of P. aibuhitensis. Population

ISSR

SRAP

PPB (%)

Ao

Ae

He

I

PPB( %)

Ao

Ae

He

I

DL LYG SY DT RD TZ NB WZ YJ QZ

76.35 80.23 82.36 81.79 83.97 87.45 83.55 86.73 89.38 90.23

1.7635 1.8023 1.8236 1.8179 1.8397 1.8745 1.8355 1.8673 1.8938 1.9023

1.3317 1.3527 1.3586 1.3577 1.3612 1.3605 1.3985 1.3826 1.4157 1.4206

0.3018 0.3256 0.3562 0.3459 0.3579 0.3586 0.3787 0.3789 0.3946 0.4215

0.4756 0.4925 0.5126 0.5165 0.5182 0.5179 0.5328 0.5356 0.5600 0.5683

77.32 78.26 75.00 78.65 79.48 79.36 82.18 81.65 83.39 83.55

1.7732 1.7826 1.7500 1.7865 1.7948 1.7936 1.8218 1.8165 1.8339 1.8355

1.3268 1.3421 1.3489 1.3502 1.3569 1.3573 1.3858 1.3879 1.4258 1.4289

0.3125 0.3378 0.3402 0.3486 0.3493 0.3505 0.3785 0.3825 0.4151 0.4219

0.4816 0.4895 0.5258 0.5235 0.5289 0.5284 0.5386 0.5420 0.5705 0.5796

Mean Species level

84.20 99.63

1.8420 1.9963

1.3740 1.7823

0.3620 0.6587

0.5230 0.7344

79.88 99.57

1.7988 1.9957

1.3711 1.7524

0.3637 0.6889

0.5308 0.7256

PPB: Percentage of polymorphic bands; Ao: Observed number of alleles per locus; Ae: Effective number of alleles per locus; He: Nei's gene diversity; I: Shannon's information index.

3.3. Phylogenetic analysis The genetic similarities among all populations ranged from 0.8518 to 0.9862, with a mean similarity of 0.9174 in the ISSRs and SRAPs. The Nei's genetic distances and geographical distances are described in Table 4. Based on the NJ analysis, the ten populations were grouped into 4 main clusters of the Bohai Sea coast, the Yellow Sea coast, the East China Sea coast and the South China Sea coast (Fig. 2). The results of the PCA analysis were comparable to those obtained using the cluster analysis. The three most informative PC components explained 71.06% of the total variation by the ISSRs and SRAPs (Fig. 3). Analysis of molecular variance (AMOVA) was performed to study the ten populations of P. aibuhitensis and to estimate the genetic variation within and among populations (Table 5). Significant genetic variation (P < 0.001) was shown among the studied groups. The highest genetic identity was between “RD” and “TZ” whereas the lowest was found between “QZ” and “DL” in the ISSRs and SRAPs. The Mantel test was performed between Nei's genetic and pairwise geographical distances. The Mantel test indicated no significant correlation between geographical and genetic distances (P > 0.005). 4. Discussion 4.1. Genetic diversity in P. aibuhitensis An accurate estimate of genetic diversity is useful for aquaculture breeding, resource assessment and species identification purposes. DNA analysis using ISSR markers has proved to be an efficient and inexpensive way to provide molecular data to assess genetic diversity and has been used for DNA fingerprinting and to successfully to determine genetic relationships (Moreno et al., 1998; Budak et al., 2004; Shao et al., 2010; Liu et al., 2013). SRAP is a novel marker system that preferentially detects polymorphisms in coding sequences, which are more conserved among cultivars and have a relatively low mutation rate, making it a more efficient technique due to its capacity to reveal relatively more informative bands (Li and Quiros, 2001; Liu et al., 2008). Therefore, genetic diversity and phylogenetic relationships within populations of P. aibuhitensis may be obtained using ISSR and SRAP markers. In this study, the potential of two different techniques was assessed for the genetic characterization of ten populations. According to molecular markers, the genetic similarity coefficient between accessions was calculated to range from 0.8518 to 0.9862, with a mean similarity of 0.9174, as measured by the respective analysis techniques of ISSRs and SRAPs. These results were consistent with Wang's studies on the genetic diversity of P. aibuhitensis using ISSR markers for other populations (Wang et al., 2014). Table 4 Genetic identities and distances of the ten P. aibuhitensis populations based on the ISSR and SRAP data. ID

DL

LYG

SY

DT

RD

TZ

NB

WZ

YJ

QZ

DL LYG SY DT RD TZ NB WZ YJ QZ

e 0.0723 0.0589 0.0612 0.0654 0.0663 0.0921 0.0848 0.1380 0.1482

476 e 0.0369 0.0427 0.0439 0.0462 0.0823 0.0797 0.1309 0.1431

570 172 e 0.0326 0.0397 0.0408 0.0807 0.0752 0.1205 0.1386

677 281 114 e 0.0265 0.0278 0.0803 0.0698 0.1202 0.1375

712 342 169 62 e 0.0138 0.0751 0.0692 0.1209 0.1479

751 364 195 83 31 e 0.0763 0.0683 0.1189 0.1436

982 563 435 305 265 232 e 0.0366 0.0973 0.1128

1208 791 656 541 507 473 256 e 0.0969 0.1109

2106 1616 1560 1500 1506 1478 1333 1111 e 0.0423

2250 1785 1768 1716 1727 1709 1589 1393 340 e

Note: Nei's genetic distances are given below the diagonal and geographical distances (km) are given above the diagonal.

F. Liu et al. / Biochemical Systematics and Ecology 57 (2014) 262e269

267

Fig. 2. The phylogenetic tree for the ten populations of P. aibuhitensis based on ISSR and SRAP markers using the NJ method with MEGA 5.1 software.

Fig. 3. A three-dimensional plot of the principal component analysis based on ISSRs and SRAPs.

Table 5 AMOVA analysis of the genetic variances within and among the populations of P. aibuhitensis. Source of variation

d.f.

Sum of squares

Variation components

ISSR Among populations Within populations

9 140

12.256 56.262

0.11492 0.49702

Total

149

68.518

0.61194

SRAP Among populations Within populations

9 140

16.369 57.170

0.15877 0.51086

Total

149

73.539

0.66963

Total variation (%) 18.78 81.22

P-value P < 0.001 P < 0.001

100

23.71 76.29 100

P < 0.001 P < 0.001

268

F. Liu et al. / Biochemical Systematics and Ecology 57 (2014) 262e269

Compared with the genetic diversity of Portunus trituberculatus (PPB ¼ 100%) revealed by SSR (Liu et al., 2012b), Culter alburnus (PPB ¼ 37%e69.17%, with an overall of 91.15%) revealed by AFLP (Wang et al., 2007) and Mugil cephalus (PPB ¼ 46.52%e64.78%, with an average of 53.91%) revealed by AFLP (Liu et al., 2009), the extent of genetic diversity of P. aibuhitensis identified in this study was higher. Such genetic diversity provides a good level of choice for parental selection in further breeding programs. Species with a higher genetic diversity will have a wider natural distribution and stronger environmental adaptability according to Hamrick and Godt (1996) evolutionary potential of species. Genetic diversity is essential for the long-term survival of a species and its adaptability to the environment. Thus, it is very important to be aware of the genetic diversity between and within species when designing protection and management strategies for endangered species. It believe that the genetic diversity of the ten P. aibuhitensis populations investigated using the ISSR and SRAP marker method was relatively moderate, which also indicates that the level of genetic structure among the populations is relatively moderate, according to Nei's genetic diversity analysis. Based on the differences in PPB, the genetic diversity of the South China Sea coasts and the East China Sea coasts was relatively higher than the genetic diversity of the Bohai Sea coasts and the Yellow Sea coasts. This result might be due to two reasons. First, bio-resources are more abundant in the south tropical and sub-tropical regions, such as Qinzhou, Yangjiang, Wenzhou and Ningbo, compared to the north temperate regions, such as Dalian, Lianyungang, Sheyang, Dongtai, Rudong and Tongzhou. Second, the Shandong peninsula is a natural barrier, blocking the movement of sea water between the Yellow Sea coast and the Bohai Sea coast. This type of geographic isolation causes inter-group limited gene flow and genetic differentiation among populations. The insights gained from exploring the genetic diversity of P. aibuhitensis populations are important in developing a sound program for its conservation and utilization. The results from this study indicate that there is a high level of genetic diversity between populations (Table 3). Therefore, it is suggested that P. aibuhitensis conservation areas for core populations of genetic diversity should be immediately established. According to our field survey, some of the genetic diversity of certain populations was degraded due to the low temperature and ocean current off of the Bohai Sea coast. 4.2. Cluster analysis The genetic relationships between populations in a species sometimes do not accord with their geographical distance, especially for a species with a large distribution area (Ding et al., 2013; Qiu et al., 2004). However, sometimes the genetic relationships between populations do accord with their geographical distance (Liu et al., 2013). In our study, the Mantel test indicated no significant correlation between geographical and genetic distances (P > 0.005). Furthermore, some populations located far from each other had a higher genetic distance. According to the NJ dendrogram of genetic relationships among ten P. aibuhitensis populations, it was also easy to find that most accessions from the same or adjacent regions were classified together based on ISSRs and SRAPs. Similar results were confirmed by Wang et al. (2014) and Liu et al. (2013). One possible explanation is that genetic variation of P. aibuhitensis is mostly due to environment factors. 4.3. Population genetic structure analysis The genetic structures of P. aibuhitensis partly result from the interaction of gene flow and genetic drift (Hutchison and Templeton, 1999). Nei's analysis of gene diversity analysis revealed that the vast majority of genetic variation occurred within populations based on ISSR and SRAP markers (Gst ¼ 0.2568/0.2876). Generally, gene flow (Nm ¼ 1) can prevent the genetic differentiation of a population due to genetic drift (Slatkin, 1987). In this study, the gene flow (Nm) of the population was 1.4470 and 1.2385 by ISSR and SRAP markers, respectively. The Nms for both markers were more than 1, indicating that the gene flow among these populations was limited high and would be able to resist the population differentiation caused by interspecies' genetic drift (Slatkin, 1985). It is suggested that limited higher levels of gene flow (Nm ¼ 1.4470 and 1.2385) exist between these populations. A possible cause of a higher gene flow among these populations is the transfer of P. aibuhitensis by farmers who trade P. aibuhitensis between each other and between these areas. P. aibuhitensis larvae from these populations could also migrate between each other by currents. Moreover, there is a higher genetic differentiation between populations. This results from their greater geographical isolation, different water temperature and reproductive season. The genetic structure of animal populations reflects the interactions of various processes such as the long-term evolutionary history of the species (e.g., habitat fragmentation, population isolation, and shifts in distribution), gene flow, mutations, genetic drift and selection (Schaal et al., 1998). In conclusion, the present study highlights the utility of ISSR and SRAP techniques for the study of genetic diversity on the DNA level in P. aibuhitensis. A high percentage of polymorphisms observed by the two markers indicated a high level of genetic diversity, which existed among different populations of P. aibuhitensis. These results showed no significant correlation between geographical and genetic distances. However, to understand the relationship between geographical distance and genetic diversity in P. aibuhitensis, further studies are necessary. Acknowledgments This study was supported by the Jiangsu Natural Science Foundation (BK2012675), the National Spark Program Project (2013GA690330), a China Postdoctoral Science Foundation funded project (2014M551614), the Natural Science Research

F. Liu et al. / Biochemical Systematics and Ecology 57 (2014) 262e269

269

Program of College of Jiangsu Province (No. 12KJD18007) and Yancheng City Agricultural Science and Technology Projects (YKN2012025). References Budak, H., Shearman, R.C., Parmaksiz, I., Gaussoin, R.E., Riordan, T.P., Dweikat, I., 2004. Molecular characterization of buffalograss germplasm using sequence related amplified polymorphism markers. Theor. Appl. Genet. 108, 328e334. Ding, G., Zhang, D.Z., Yu, Y.Q., Zhao, L.L., Zhang, B.B., 2013. Analysis of genetic variability and population structure of the endemic medicinal Limonium sinense using molecular markers. Gene 520, 189e193. Excoffier, L., Smouse, P.E., Quattro, J.M., 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: applications to human mitochondrial DNA restriction data. Genetics 131, 479e491. Fang, J.H., Zhang, J.H., Wu, W.G., Mao, Y.Z., Gao, Y.P., Jiang, Z.J., Fang, J.G., 2014. The carbon and nitrogen budget in the Japanese flounder cage culture integrated model with Perinereis aibuhitensis. J. Fish. Sci. China 21 (2), 331e339. Hamrick, J.L., Godt, M.J.W., 1996. Effects of life history traits on genetic diversity in plant species. Philos. Trans. R. Soc. Lond. B 351, 1291e1298. Hutchison, D.W., Templeton, A.R., 1999. Correlation of pairwise genetic and geographic distance measures: inferring the relative influences of gene flow and drift on the distribution of genetic variability. Evolution 53, 1898e1914. Jiang, X.M., Zheng, Z.M., 2002. Observation on the swarming behavior of Perinereis aibuhitensis. Chin. J. Zool. 37 (5), 54e56. Li, G., Quiros, C.F., 2001. Sequence-related amplified polymorphism (SRAP), a new marker system based on a simple PCR reaction: its application to mapping and gene tagging in Brassica. Theor. Appl. Genet. 103, 455e461. Liu, F., Guo, Q.S., Shi, H.Z., Wang, T., Zhu, Z.B., 2013. Genetic diversity and phylogenetic relationships among and within populations of Whitmania pigra and Hirudo nipponica based on ISSR and SRAP markers. Biochem. Syst. Ecol. 51, 215e223. Liu, H.J., Liu, M., Ge, S.S., Wang, Q.X., Yu, D.D., Guan, S.G., 2012a. Population structuring and historical demography of a common clam worm Perinereris aibuhitensis near the coasts of Shandong Peninsula. Biochem. Syst. Ecol. 44, 70e78. Liu, J.Y., Lun, Z.R., Zhang, J.B., Yang, T.B., 2009. Population genetic structure of striped mullet, Mugil cephalus, along the coast of China, inferred by AFLP fingerprinting. Biochem. Syst. Ecol. 37, 266e274. Liu, L.W., Zhao, L.P., Gong, Y.Q., Wang, M.X., Chen, L.M., Yang, J.L., Wang, Y., Yu, F.M., Wang, L.Z., 2008. DNA fingerprinting and genetic diversity analysis of late-bolting radish cultivars with RAPD, ISSR and SRAP markers. Sci. Hortic. 116, 240e247. Liu, X.H., Ge, F., Pan, W.D., 2002. Analysis of nutrient composition from tissues of Perinereis aibuhitensis. Chin. J. Mar. Drugs 90 (2), 35e41. Liu, Y.G., Guo, Y.H., Hao, J., Liu, L.X., 2012b. Genetic diversity of swimming crab (Portunus trituberculatus) populations from Shandong peninsula as assessed by microsatellite markers. Biochem. Syst. Ecol. 41, 91e97. Mantel, N., 1967. The detection of disease clustering and generalized regression approach. Cancer Res. 27, 209e220. Moreno, S., Martin, J.P., Ortiz, J.M., 1998. Inter-simple sequence repeat PCR for characterization of closely related grapevine germplasm. Euphytica 101, 117e125. Mouneyrac, C., Mastain, O., Amiard, J.C., Amiard-Triquet, C., Beaunier, P., Jeantet, A.Y., Smith, B.D., Rainbow, P.S., 2003. Trace-metal detoxification and tolerance of the estuarine worm Hediste diversicolor chronically exposed in their environment. Mar. Biol. 143 (4), 731e744. Nei, M., 1972. Genetic distance between populations. Am. Nat. 106, 283e292. Nei, M., Li, W.H., 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. U.S.A. 76, 5269e5273. Qiu, Y.X., Hong, D.Y., Fu, C.X., Kenneth, M.C., 2004. Genetic variation in the endangered and endemic species Changium smyrnioides (Apiaceae). Biochem. Syst. Ecol. 32, 583e596. Rohlf, F.J., 2004. NTSYS-pc: Numerical Taxonomy and Multivariate Analysis System. Version 2.1 User Guide. Exeter Software. Applied Biostatistics Inc., New York. Sambrook, J., Russell, D.W., 2001. Molecular Cloning: a Laboratory Manual, third ed. Cold Spring Harbor Laboratory Press, New York, pp. 21e66. Schaal, B.A., Hayworth, D.A., Olsen, K.M., Rauscher, J.T., Smith, W.A., 1998. Phylogeographic studies in plants: problems and prospects. Mol. Ecol. 7, 465e474. Shannon, C.E., Weaver, W., 1949. The Mathematical Theory of Communication. University of Illinois Press, Chicago, IL. Shao, Q.S., Guo, Q.S., Deng, Y.M., Guo, H.P., 2010. A comparative analysis of genetic diversity in medicinal Chrysanthemum morifolium based on morphology, ISSR and SRAP markers. Biochem. Syst. Ecol. 38, 1160e1169. Slatkin, M., 1985. Gene flow in natural populations. Annu. Rev. Ecol. Syst. 16, 393e430. Slatkin, M., 1987. Gene flow and the geographic structure of natural populations. Science 236, 787e792. Sneath, P.H.A., Sokal, R.R., 1973. Numerical Taxonomy. Freeman, San Francisco. Sun, F.H., Zhou, Q.X., Wang, M., An, J., 2009. Joint stress of copper and petroleum hydrocarbons on the polychaete Perinereis aibuhitensis at biochemical levels. Ecotoxicol. Environ. Saf. 72 (7), 1887e1892. Sun, R., Yang, D.J., 2004. Fauna sinica, invertebrate. In: Annelida, Polychaeta (II), Nereidida, vol. 33. Science Press, Beijing, China. Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., Kumar, S., 2011. MEGA 5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol. Biol. Evol. 28, 2731e2739. Wang, W., Chen, L., Yang, P., Hou, L., He, C., Gu, Z., Liu, Z., 2007. Assessing genetic diversity of populations of topmouth culter (Culter alburnus) in China using AFLP markers. Biochem. Syst. Ecol. 35, 662e669. Wang, Y.X., Ren, H.W., Zhu, Y.J., Zhao, H., Yang, D.Z., Zhou, Y.B., 2014. Genetic diversity of different geographic populations in Perinereis aibuhitensis by ISSR and CO I markers. J. Agr. Sci. Tech-Iran 16 (1), 139e147. Yang, D.Z., Zhou, Y.B., Kou, N., 2010. The histological observation of gametogenesis on sludge worm Perinereis aibuhitensis Grube. J. Dalian Ocean Univ. 25 (1), 29e33. Yeh, F.C., Yang, R.C., Boyle, T.B.J., Ye, Z.H., Mao, J.X., 1999. PopGene Version 1.32: the User-friendly Shareware for Population Genetic Analysis. Molecular Biology and Biotechnology Center, University of Albert, Edmonton, Canada.