Parameters of genetic diversity for three populations of H. septemfasciatus.
Abstract
Hyporthodus septemfasciatus is a commercially important proliferation fish which is distributed in the coastal waters of Japan, Korea, and China. We used the fluorescent AFLP technique to check the genetic differentiations between broodstock and offspring populations. A total of 422 polymorphic bands (70.10%) were detected from the 602 amplified bands. A total of 308 polymorphic loci were checked for broodstock I (Pbroodstock I = 55.50%) coupled with 356 and 294 for broodstock II (Pbroodstock II = 63.12%) and offspring (Poffspring = 52.88%), respectively. The levels of population genetic diversities for broodstock were higher than those for offspring. Both AMOVA and Fst analyses showed that significant genetic differentiation existed among populations, and limited fishery recruitment to the offspring was detected. STRUCTURE and PCoA analyses indicated that two management units existed and most offspring individuals (95.0%) only originated from 44.0% of the individuals of broodstock I, which may have negative effects on sustainable fry production.
Keywords
- genetic diversity
- population structure
- fluorescent AFLP technology
- Hyporthodus septemfasciatus
- sustainable management
1. Introduction
Genetic diversity is one of the most important natural properties for commercially interesting species, because it can influence the species’ adaptive capacity to environmental change, and loss of genetic variation is destructive to domestication of cultured stocks [1, 2]. Limited effective population size and the effects of artificial selection on hatchery progeny may lead to population genetic drift, which will cause offspring to differentiate from broodstock [3]. Monitoring population genetic diversity and genetic structure, therefore, has become a key aspect and long-term mission for the success of commercial breeding programs [4].
Seven-band grouper,
Research reports of genetic diversity and population structure between wild and hatchery populations of
2. Population genetic differentiation for marine fishes based on fluorescent AFLP markers
2.1 Materials and methods
2.1.1 Material information
Sixty-two specimens with two broodstock and one offspring populations were gathered from Korea (broodstock II), Japan (broodstock I), and China (offspring—Rizhao) during May 2014 to September 2014 (Figure 1, Table 1). We used the
Primer pairs | Population | |||||
---|---|---|---|---|---|---|
FAM-E-AAC/M-CTC | Rizhao | 0.190 ± 0.029 | 0.125 ± 0.020 | 1.211 ± 0.037 | 0.200/0.227 | 0.116 |
Japan | 0.199 ± 0.030 | 0.131 ± 0.021 | 1.223 ± 0.038 | |||
Korea | 0.266 ± 0.031 | 0.176 ± 0.022 | 1.297 ± 0.040 | |||
Average | 0.218 ± 0.017 | 0.144 ± 0.012 | 1.244 ± 0.022 | |||
0.152 ± 0.027 | 0.098 ± 0.018 | 1.162 ± 0.034 | ||||
FAM-E-AAC/M-CTG | Rizhao | 0.234 ± 0.027 | 0.153 ± 0.018 | 1.249 ± 0.032 | 0.229/0.256 | 0.107 |
Japan | 0.232 ± 0.027 | 0.153 ± 0.019 | 1.260 ± 0.036 | |||
Korea | 0.272 ± 0.027 | 0.177 ± 0.019 | 1.290 ± 0.034 | |||
Average | 0.246 ± 0.016 | 0.161 ± 0.011 | 1.266 ± 0.019 | |||
0.195 ± 0.027 | 0.130 ± 0.019 | 1.225 ± 0.036 | ||||
FAM-E-ACA/M-CAT | Rizhao | 0.196 ± 0.024 | 0.129 ± 0.017 | 1.214 ± 0.030 | 0.199/0.249 | 0.197 |
Japan | 0.242 ± 0.025 | 0.159 ± 0.017 | 1.265 ± 0.032 | |||
Korea | 0.237 ± 0.025 | 0.155 ± 0.017 | 1.260 ± 0.032 | |||
Average | 0.225 ± 0.014 | 0.148 ± 0.010 | 1.246 ± 0.018 | |||
0.157 ± 0.023 | 0.104 ± 0.016 | 1.176 ± 0.029 | ||||
FAM-E-ACA/M-CTT | Rizhao | 0.254 ± 0.024 | 0.168 ± 0.017 | 1.284 ± 0.030 | 0.234/0.266 | 0.119 |
Japan | 0.227 ± 0.023 | 0.148 ± 0.016 | 1.250 ± 0.030 | |||
Korea | 0.306 ± 0.024 | 0.201 ± 0.017 | 1.338 ± 0.031 | |||
Average | 0.262 ± 0.014 | 0.173 ± 0.010 | 1.291 ± 0.018 | |||
0.150 ± 0.022 | 0.102 ± 0.015 | 1.180 ± 0.029 | ||||
FAM-E-ACC/M-ACT | Rizhao | 0.298 ± 0.022 | 0.199 ± 0.016 | 1.343 ± 0.029 | 0.257/0.285 | 0.099 |
Japan | 0.287 ± 0.022 | 0.191 ± 0.016 | 1.328 ± 0.029 | |||
Korea | 0.305 ± 0.021 | 0.201 ± 0.015 | 1.340 ± 0.029 | |||
Average | 0.297 ± 0.013 | 0.197 ± 0.009 | 1.337 ± 0.017 | |||
0.234 ± 0.022 | 0.157 ± 0.016 | 1.274 ± 0.029 | ||||
Total | Rizhao | 0.243 ± 0.011 | 0.161 ± 0.008 | 1.271 ± 0.014 | 0.229/0.261 | 0.124 |
Japan | 0.244 ± 0.011 | 0.161 ± 0.008 | 1.272 ± 0.015 | |||
Korea | 0.281 ± 0.011 | 0.185 ± 0.008 | 1.310 ± 0.015 | |||
Average | 0.256 ± 0.007 | 0.169 ± 0.005 | 1.284 ± 0.008 | |||
0.182 ± 0.011 | 0.121 ± 0.008 | 1.210 ± 0.014 |
2.1.2 Genomic DNA extraction and AFLP processes
We used a standard phenol-chloroform method to extract the genomic DNA from the fin-clip tissue with proteinase K digestion. The process of AFLP experiment was followed with the procedures developed by Vos et al. [7] and Wang et al. [8]. The genomic DNA with about 100 ng was digested using 1 unit of
Similarity indices were calculated using the formula S = 2Nab/(Na + Nb), where Na and Nb were the number of bands in individuals a and b, respectively, and Nab was the number of sharing bands. Genetic distances between individuals were computed using the formula D = −ln S. Genetic relationship among populations was constructed based on unweighted pair-group method analysis (UPGMA) by TFPGA [9].
2.2 Data analysis
2.2.1 AFLP data analysis
We used the ABI 3730xl Genetic Analyzer (Applied Biosystems) to check the PCR products, which were genotyped by using the internal size standard LIZ 500 (Applied Biosystems) and scored using the GeneScan3.1 software (Applied Biosystems) in Shanghai Personal Biotechnology Co., Ltd.
2.2.2 Genetic variability parameter analyses
The fragment size with length ranging from 70 to 1000 bp was used for further analyses. Firstly, the clear and unambiguous AFLP bands were scored with 1 or 0, and then we transformed the bands into 0/1 binary matrix. The genetic variability parameters with polymorphic bands, effective number of alleles per loci (
Genetic differentiation between population pairs was evaluated by fixation indices
2.3 Results
2.3.1 Polymorphic information of different AFLP primers
To remove false-positive bands, a total of 602 clear and unambiguous bands were detected from two broodstock and one offspring populations by using five-pair selective primers. A total of 422 polymorphic bands (70.10%) were detected from the 602 amplified bands (Table 1). The average bands of polymorphic sites for five-pair primers were 84.4, which were ranged from 52 to 129 (Table 1). The maximum of polymorphic bands was detected in the FAM-E-ACC/M-ACT primer pair (129 bands), and the minimum of polymorphic bands was found in the FAM-E-AAC/M-CTC primer pair (52 bands). Three hundred and eight polymorphic loci were checked for broodstock I (
2.3.2 Genetic variability of H. septemfasciatus
The average values of
Though the five primer pairs showed different genetic differentiations among populations, the values of genetic structure (
We used the software of STRUCTURE to estimate the ancestor composition based on the coalescent theory. Three clusters were checked between broodstock and offspring populations based on a clear maximum for Δ
The relationship of individuals was further illustrated by a dendrogram using the UPGMA algorithm based on Nei’s genetic distance (Figure 5). Significant genealogical structure was detected in
3. Conclusions
In this study, significant genetic differentiations were checked among the broodstock and offspring populations of
High level of polymorphic sites (70.10%) was detected for
The genetic variability is one of the most crucial foundations for the conservation of marine species from long-time objective. Although significant degradation of genetic variations has been previously reported between broodstock and offspring in other marine fishes, no significant reduction of genetic diversity was checked between broodstock I (Japan,
Significant genetic differentiations were detected between broodstock I population from Japan and broodstock II population from Korea for
Understanding of population genetic diversity and genetic structure has become a key aspect and long-standing issue in speciation and biological conservation. Uncovering the situation of marine population genetic diversity and gene flow is critical for the decision about sustainable exploitation. Evaluating population genetic diversity and structure also can be a vital tool for managing and maintaining a productive fishery [23]. Severe population size declines can also result in the loss of genetic diversity [24]. These results also indicate that genetic drift has led to negative effects on the reproductive capacity of the stock, which may have resulted in significant genetic differentiation between broodstock and offspring populations. The present study of
Acknowledgments
This study was supported by a grant from the National Natural Science Foundation of China (No. 41506170, No. 31672672, and No. 31872195), Shandong Province Key Research and Invention Program (2017GHY15102, 2017GHY15106), Qingdao Source Innovation Program (17-1-1-57-jch), Marine Fishery Institute of Zhejiang Province, Key Laboratory of Mariculture and Enhancement of Zhejiang Province (2016KF002), Qingdao National Laboratory for Marine Science and Technology (2015ASKJ02, 2015ASKJ02-03-03), and STS project (KFZD-SW-106, ZSSD-019).
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