Development of Daphnia Magna SSR Markers and Genetic Diversity Analysis Based on RAD-Seq Technology

Daphnia magna belongs to the Cladocera order and plays an important role in the water ecosystem. With the intensi�cation of water pollution, the wild population of D. magna has declined rapidly in recent years, and insu�cient molecular markers have limited effective research and conservation of this species. In our research, 26 novel microsatellite (SSR) markers were developed in an arti�cially domesticated of D. magna and 12 wild population of D. magna using restriction site-associated DNA sequencing (RAD-seq). The results showed that the observed heterozygosity (Ho) and expected heterozygosity (He) ranged from 0.083 to 0.999 and 0.085 to 0.862, respectively. The PIC ranged from 0.368 to 0.805. These results indicate that the developed SSR marker is highly polymorphic. Nei’s genetic identity (H) ranged from 0.0926 to 0.3462, with a mean of 0.2233. Shannon’s Information index (I) ranged from 0.1333 to 0.4799, with an average of 0.3073; Shanxi province had the highest value and Hunan province had the lowest. Genetic distance and Nei’s genetic identity analysis, NJ tree diagram analysis, and PCoA analysis were conducted on populations of D. magna from different regions. The results show that the D. magna genetic relationship between Liaoning and Shanxi, Hunan and Anhui, and Beijing and Hainan is relatively close, while the genetic structure of D. magna in Guangdong, Jiangsu, and Sichuan is quite different from other sampling sites. An analysis of population genetic structure divided the test D. magna samples into two major groups. These results indicate that the genetic diversity of D. magna is rich, and the genetic structure of D. magna differs considerably in different regions. These research results and the newly developed polymorphic SSR markers for D. magna are of great signi�cance in terms of the genetic breeding of D. magna, identi�cation of wild and arti�cially domesticated population and conservation genetics research.


Introduction
Daphnia magna belongs to the Daphniidae family.D. magna are an important component of the water ecosystem, mainly living in freshwater lakes, rivers, ponds, and reservoirs [1].D. magna feeds directly on phytoplankton [2], and is often used to control the population and community structure of phytoplankton in water bodies [3].In China, the arti cially domesticated D. magna has been used to inhibit Cyanobacteria blooms and restore submerged vegetation, which has been used in more than 400 ecological restoration projects [4][5].D. magna has the characteristics of wide distribution, strong adaptability, short reproduction period, allowing large-scale cultivation in the laboratory, and is highly sensitive to a variety of toxic substances in the water environment [6], so it is widely used in water pollution monitoring and aquatic organism toxicological research [7][8].It is also an ideal model organism in the eld of life science researches [9].D. magna is an extremely important zooplankton in lakes, rivers, and reservoirs.It grows fast, reproduces well, and has a strong feeding power on algae, effectively controlling the accumulation of primary products in water bodies [10].D. magna helps to increase the diversity of phytoplankton in the water body and build a stable phytoplankton community structure, as well preventing the occurrence of cyanobacteria blooms.It is the key to balance in the water ecosystem.In recent years, with the rapid expansion of the population and increases in the discharge of domestic sewage, the aquatic ecosystem has been severely damaged; relevant research shows that 54% of Asian, 53% of European, 48% of North American, 41% of South American, and 28% of African rivers are eutrophic water bodies, and eutrophication of water bodies is currently the most serious problem facing rivers and lakes [11].As a result, the habitat of D. magna has been severely damaged, and its genetic diversity is also declining sharply.In this study, we use the microsatellite marker method to understand the genetic variation, genetic structure, and gene distribution of D. magna, in order to better protect its genetic diversity.In addition, Shanghai Taihe Water Environment Technology Development Co., Ltd.invented a technology for ecological restoration of D. magna guided submerged plants, the arti cially domesticated D. magna that can quickly lter the high biomass of phytoplankton and other particulate organic matter, increasing the transparency of the water body by 1.0-1.5 m in a short time, so that the planting of submerged plants can quickly form vegetation. D. magna was rst introduced to water ecological restoration in the world and has achieved good ecological restoration effects in many rivers and water bodies [4][5].Therefore, it is very important to use the SSR markers to study identi cation of wild and arti cially domesticated species,too.SSR refers to simple sequence repeat [12], also called microsatellite DNA, which is a DNA molecular marker technology based on PCR with speci c primers.SSRs are short tandem repeat sequences composed of one to six nucleotides as repeat units in the genome.They are widely distributed in various regions of the genome, with the length generally between 100 and 200bp.SSRs are currently one of the most commonly used microsatellite markers.Because of their large number, codominance, easy operation, stable results, high polymorphism, and strong reproducibility, they have been widely used in research on gene mapping, genetic map construction, ngerprint analysis, genetic relationship identi cation, and biodiversity assessment [13][14][15].
Restriction-site associated DNA sequencing (RAD-seq) is an important sequencing technology for simplifying the genome.It has a high number of markers and high density, and can be applied in many elds [16].This technology has been widely used in research in the elds of population genetics, genetic map construction, and systematic evolution [17].Our study used RAD-seq technology to develop and screen polymorphic SSR loci of 12 wild population of D. magna and 1 species of arti cially bred D. magna, and analyze the genetic diversity and genetic structure of D. magna.The research results are of great signi cance for identi cation of wild and arti cially domesticated species, genetic breeding, evaluation of genetic diversity, genetic relationship identi cation, construction of a genetic map, and protection of germplasm resources of D. magna.

Sample collection and genomic DNA extraction
The experimental samples used in this research are one arti cially bred population and 12 wild populations (Table 1); the arti cially bred population was taken from the breeding base of Shanghai Taihe Water Environment Technology Development Co., Ltd.(Shanghai Fengjing).Hundreds of D. magna adult individuals were randomly collected from 12 wild population sampling sites and brought back to the laboratory for cultivation.The TIANGEN DP304 kit (TIANGEN BIOTECH Co., Ltd, China) was used to extract 50 parthenogenesis cultured D. magna genomic DNA at each sampling site, and the integrity was checked using 1.5% agarose gel electrophoresis.The purity and concentration of the DNA were detected using a UV spectrophotometer to ensure the genomic DNA obtained met the quality conditions for building a database.DNA samples were diluted to a concentration of 30 ng/µL and stored at -20°C (Haier BCD-576WDPU, China) until further use.(Shanghai, China).Since D. magna had no reference genome, it was necessary to use multiple restriction endonucleases to digest the DNA of D. magna separately.After digesting the genomic DNA with appropriate restriction endonuclease, P1 adapters were added.A P1 adapter contains the primer sequence required for PCR ampli cation, the sequence of the Illumina sequencing primer binding site, and the short tag sequence to distinguish different samples.Samples with different P1 adapters were mixed, physically breaking them into sequences of 300-500bp, and then P2 adapters were added.Next, we performed PCR ampli cation and enrichment of RAD-tags, construction of a paired-end library, and sequencing using the Illumina HiSeq PE150 (Illumina, USA) system.Raw data were ltered using trimmomatic software (http://www.usadellab.org/cms/uploads/supplementary/Trimmomatic) to obtain high-quality clean data and ensure smooth subsequent analysis.We removed the linker sequence in the reads and reads without inserts because of factors such as linker interconnection.Bases of lower quality were trimmed at the 3' end of the sequence and entire sequences containing base quality values less than 10 were removed, eliminating reads with a N ratio higher than 10%, and removing adapter and quality modi cation sequences of less than 75bp in length.

Ssr Loci Analysis And Primer Design
MISA (http://pgrc.ikpgatersleben.de/misa)software was used to estimate the quali ed SSR, and Primer 3 [18] software was used to design SSR primers for better SSR loci.

Ssr Loci Screening
SSR loci screening mainly includes unitary and polymorphism screening.Unitary screening uses PCR and agarose gel electrophoresis (1.5% agarose gel, 200V, 15 min) to determine whether there is a product and whether the product is single-stranded.Polymorphism screening uses uorescent primer PCR and capillary electrophoresis to determine whether the peak shape is quali ed and whether it is polymorphic.Six samples (DZ, YN, HNa, GD, JN, and SZ) were used for polymorphism screening, with PCR ampli cation using tailed primers, and the universal typing primer Common-famF (AGTCACGACGTTGTAAAACGAC).Polymerase chain reaction (PCR) ampli cation was performed in 20µL volumes containing 10µL Taq Master Mix (Vazyme Biotech Co., Ltd, China), 30ng/µL DNA template 1µL, typing primer 1µL, forward primer 0.2µL, and reverse primer 1µL, supplemented with ddH 2 O 7µL.The PCR ampli cation reaction was carried out on a Mastercycler pro PCR machine (FR-180, China).The PCR thermal cycle consisted of initial denaturation at 94°C for 5 min, followed by 35 cycles at 94°C for 30s, locus-speci c annealing temperature for 30s, (Table 2 shows the annealing temperature for each primer reaction), 72°C for 30s, nal extension at 72°C for 10 min, and then the temperature was maintained at 4°C.PCR products were electrophoresed with 1% agarose and stained with ethidium bromide (EB), observed, and photographed using the gel imaging system.

Data analysis
Genemapper 4.0 software was used to read the molecular weight data of the SSR ampli ed products, and then DataFormater software was used to determine the genotype of individual points based on the molecular weight data.The total number and number of effective alleles (Na and Ne, respectively), and observed and expected heterozygosity (Ho and He, respectively) were computed using GenAlEx 6.5 [19].Polymorphic information content was calculated using Powermaker 3.25.POPGENE software [20] was used to calculate the number of polymorphic loci (A), the percentage of polymorphic loci (P), Nei's genetic identity (H), Shannon's information index (I), and Nei's unbiased measures of genetic identity and genetic distance for each population [21].A neighbor-joining (NJ) dendrogram was constructed from the calculated genetic distance between populations using POPTREE software [22].During bootstrapping, 1000 permutations were performed to evaluate the robustness of the clusters.Principal Coordinates Analysis (PCoA) was implemented in GenAlEx 6.5 in order to analyze the genetic relationships across populations.Bayesian model-based clustering analysis was performed using STRUCTURE 2.3.4 software to estimate the most likely number of genetic clusters [23].This clustering method was used to identify genetically distinct subpopulations based on allele frequencies.The admixture model was applied, and the number of clusters (K value) was set from 2 to 10 with three independent runs for each xed K number.Each run included a burn-in length of 10,000 followed by 10,000 MCMC (Monte Carlo Markov Chain) repetitions.The most likely K value was determined based on the method described by Evanno et al. [24] by submitting all result les for K = 2 to 10 to STRUCTURE HARVESTER [25].The run with the highest log probability value among the three independent ones was chosen and represented as bar plots [26] using DISTRUCT 1.1 [27].

Polymorphism of newly developed microsatellite markers
A total of 26 polymorphic SSR loci were developed in 13 populations using RAD-seq technology.The primer sequences (5'-3'), repeat motifs, size ranges, and annealing temperatures are shown in Table 2.The value of Na and Ne across all loci was highest in ZSC_320 and lowest in ZSC_7904, with an average number of 4.654 alleles per locus, and mean effective number of alleles of 3.000.The observed heterozygosity (Ho) ranged from 0.083 to 0.999, with a mean of 0.486.The expected heterozygosity (He) was 0.085-0.862,with a mean of 0.645.The Polymorphic information content (PIC) range was 0.368-0.805,with an average of 0.576.The Shannon's information index (I) ranged from 0.173 to 1.936, with an average of 1.187.
The highest values for He, PIC, and I were found in ZSC_320, while the highest values for Ho were found in ZSC_3833.The lowest values for Ho, He, PIC, and I were all found in ZSC_7904 (Table 3).The PIC value is an important index to evaluate the degree of variation of a gene locus.If the PIC value of a gene locus is greater than 0.50, it means it is a highly polymorphic locus; if the PIC value is between 0.25 and 0.50, it means it is a moderately polymorphic locus; and if the PIC value is less than 0.25, it means there is low polymorphism.In our research, the average PIC value of 26 SSR markers in 13 populations was 0.576, with 17 loci having a PIC value higher than 0.5.These results indicate that the developed SSR marker is highly polymorphic.Genetic diversity of D. magna populations Ampli cation results for the 26 SSR markers in 13 D. magna populations showed high polymorphism.At the population level, the 26 SSR markers detected that the number of polymorphic loci ranged from 2 to 18 in the 13 populations, with an average of 9.923.The percentage of polymorphic loci ranged from 7.69-69.23%,with an average of 41.12%.The SX population ampli cation results showed the highest level of polymorphism, with a polymorphic loci percentage of 69.23%, followed by GD (65.38%),DZ (61.54%), and LN (61.54%) populations, while the JS population ampli cation results showed the lowest level of polymorphism, with a polymorphic loci percentage of only 7.69%.Furthermore, Nei's genetic identity (H) ranged from 0.0926 to 0.3462, with a mean of 0.2233.The value for SX was the highest and that for HNb was the lowest.In addition, the values for LN, GD, and DZ also exceeded 3.000.Shannon's Information index (I) ranged from 0.1333 to 0.4799, with an average of 0.3073.SX had the highest value, followed by GD, while HNb had the lowest value (Table 4).The above results show that among the 13 regions, genetic diversity of the D. magna populations in Shanxi, Guangdong, Liaoning, and Taihe Water is relatively high.Genetic diversity of the D. magna populations in Shanxi Province is the most abundant, while that in Jiangsu Province is relatively low.There are obvious genetic differences among different provinces and cities.In order to further explore the genetic structure differences of D. magna populations in different regions, we calculated Nei's genetic identity and genetic distance for the 13 sampling sites.Nei's genetic identity and genetic distance is an important indicator that re ects the distance between populations.When the genetic distance is 1 (the genetic identity is 0), it indicates that the D. magna of the two populations are completely different and there is no genetic relationship; when the genetic distance is 0 (the genetic identity is 1), it indicates that the germplasm of the two populations is identical [28].
The genetic distances for the 13 different sources of D. magna were 0.0034-0.6864,with an average value of 0.3722.The genetic distance between YT and JS was the largest, and the genetic distance between AH and HNb was the smallest.Nei's genetic identity for D. magna in the 13 different regions was 0.3220-0.9966,with an average value of 0.6461.AH and HNb had the highest Nei's genetic identity, and JS and AH had the lowest (Table 5).This shows that there are certain differences in the genetic structure of D. magna in different regions, and the genetic diversity of D. magna is extremely rich.Jiangsu and Anhui populations are relatively distantly related, while Anhui and Hunan populations are relatively closely related.In order to more intuitively show the genetic distance differences of different populations of D. magna, POPTREE software was used to construct a neighbor connection (NJ) tree diagram.The results showed that AH and HNb clustered rst, and then clustered with YN.LN and SX are clustered, and then clustered with YT, JN, and DZ, respectively.BJ clustered with HNa, and then clustered with SC.Among these 13 sampling sites, the genetic structures of GD and JS are quite different from the genetic structure of the other regions, and the genetic relationship between AH and HNb, and between BJ and HNa, is closer.The clustering results are consistent with Table 5.
Principal coordinates analysis (PCoA) is a powerful tool for evaluating the genetic structure of a population.Based on the screened SSR loci, GenAlEx 6.5 software was used to perform principal coordinates analysis on D. magna in different regions, and PCoA cluster maps of experimental samples in 13 regions were obtained (Fig. 3).It can be seen from the PCoA cluster maps that AH, HNb, YN, LN, JN, SX, YT, and DZ are clustered together.BJ and HNa are clustered together but they are obviously scattered from the other populations, while the D. magna populations for GD, JS, and SC are distributed separately and relatively scattered.These results are basically consistent with the results from population genetic distance analysis and clustering results, indicating the consistency of the clustering results.
From the tree diagram and PCoA scatter diagram, we can intuitively understand the classi cation relationship between populations, but in order to determine how many subgroups a certain group has, whether there is gene exchange between groups, and the degree of hybridization of each individual, we need a structure diagram to analyze the structure of the populations.The preset number of population subgroups is equal to 1-10, that is, K = 1-10, and the grouping situation and ancestry composition of the population are calculated based on the Bayes algorithm.Simulation results for each K value will produce the maximum likelihood.The larger the value of ln likelihood, the closer the K value is to the real situation, which means we need to determine the simulation result with the largest likelihood and smallest K value [25].It can be seen from Fig. 4 that as the value of K increases, the value of Ln(K) also gradually increases, but when K = 2, the value of ln likelihood enters a plateau, and the value of ΔK appears at its maximum with an obvious peak, indicating that D. magna in the 13 regions can be divided into two groups.Each individual is represented by a vertical colored bar, and the proportion of the color in each bar represents the probability of membership in the relevant cluster.It can be seen from Fig. 5 that D. magna at the eight sampling sites (AH, DZ, HNb, JN, LN, SX, YN, and YT) can be put into one group, and they may have a common ancestor, while BJ, HNa, and JS are divided into another group, their genetic structure is relatively simple.The colored bars for GD and SC are composed of two colors, indicating that the genetic background of the populations for GD and SC is relatively complicated, and it is likely to be derived from a cross of two ancestral subgroups, with the ancestral subgroup of GD accounting for between 40% and 60% of the pedigrees, and SC mostly belonging to the red group.

Discussion
Analysis of genetic characteristics of D. magna population by SSR markers D. magna is a small planktonic cladoceran.D. magna has been used as a model species for ecotoxicology, as it is sensitive to environmental stressors and environmental changes [29] ( Lee et al. 2019).At present, research on D. magna mainly focuses on reproduction ecology, toxic and toxicological effects [30], and water pollution puri cation [31][32].Lee et al. [29] assembled and characterized the genome of D. magna, which has greatly helped the molecular research of D. magna.Robinson et al. [33] used statistics calculated from multilocus microsatellite datasets to estimate population ages in data generated through coalescent simulations and in samples from populations of known age in a metapopulation of D. magna in Finland.Our research uses SSR markers to identi cate of wild and arti cially domesticated species.
In our study, 26 polymorphic SSR loci were developed using RAD-seq technology, and genetic diversity analysis was performed on 12 wild D. magna populations and one arti cially selected D. magna population in China.The average number of alleles for the 26 pairs of SSR primers is 4.654.With an average of more than four alleles, one can better assess the genetic diversity of a population [34], so the developed microsatellite markers show good polymorphism and can provide help in further molecular research on D. magna.Diversity analysis of D. magna populations in the 13 regions shows that the mean values of Nei's genetic identity and Shannon's Information index are 0.2233 and 0.3073, respectively, indicating that the genetic marker diversity of D. magna is relatively high.The genetic diversity of D. magna is relatively high in Shanxi and Guangdong and is the lowest in Jiangsu.In addition, it also showed good genetic diversity in arti cially domesticated D. magna (DZ).Genetic distance and Nei's genetic identity analysis, NJ cluster analysis, PCoA analysis, and STRUCTURE genetic structure analysis were conducted on germplasm samples from D. magna in different regions; the results were basically consistent and complementary.The research results showed that the genetic diversity of D. magna from different sources was quite different.The genetic relationship between Anhui and Hunan's D. magna germplasm is the closest, and the genetic relationship between Anhui and Jiangsu is the furthest.NJ cluster analysis and genetic distance analysis gave the same results.PCoA analysis results showed that D. magna in Anhui, Hunan, Jining, Liaoning, Taiheshui, Yantai, and Yunnan can be clustered into one group.The differences in D. magna in Beijing and Hainan are also small, while D. magna in Guangdong, Sichuan, and Jiangsu are quite different from other regions, and the clustering results have no correlation with geographic origin.The STRUCTURE genetic structure plot divides D. magna from the 13 regions into two groups.The genetic backgrounds of D. magna in Anhui, Hunan, Jining, Liaoning, Shanxi, Yunnan, Yantai, and Taihe Water are relatively simple, and the genetic structure of D. magna in Beijing, Hainan, and Jiangsu is also very simple but signi cantly different from the previous group, while the genes of D. magna in Guangdong and Sichuan are shared with the two groups.

Genetic differentiation of D. magna population
From the sampling site distribution and clustering results, there is no absolute correlation between the gene distribution of D. magna and its geographic origin, but on the whole, there are still large differences in the genetic structure of D. magna in the north and south of China, which may be a result of differences in temperature, climate, precipitation, and water environment.However, there are exceptions; the genetic distance between D. magna in Beijing and Hainan is relatively small, which may be due to similarities in the water environment causing D. magna in the two places to evolve in a similar direction.Human interference is an extremely signi cant activity affecting gene exchange in species, with the high similarity of D. magna genes in different regions likely to be the result of arti cial introduction.Meanwhile, zooplankton have weak swimming ability and are highly susceptible to factors such as water level uctuations, tidal currents, and water erosion [35].Ingestion by large aquatic animals such as sh, shrimps, and crabs will also accelerate gene exchange between D. magna from different regions.However, based on our research, the genetic structure of D. magna in different regions is quite different.Human construction activities destroy the habitats of D. magna, which fragment the habitat and spread populations, resulting in low genetic similarity between D. magna in different regions.In addition to its weak swimming ability, D. magna mainly reproduces asexually, which inevitably affects gene exchange between populations due to long-term geographic isolation, which may lead to obvious genetic differentiation between populations, increase in genetic distance, and decrease in population size, leading to population sel ng and genetic drift, which ultimately leads to a decrease in genetic diversity.Therefore, we should raise awareness of environmental protection, protect the safety and integrity of the water environment, and also cultivate and introduce D. magna into different regions and rivers in order to increase gene ow between populations, prevent the aggravation of genetic differentiation, and increase genetic diversity.A high level of genetic diversity can provide a source of genes to optimize the germplasm resources of D. magna.As a natural open bait for high-level aquatic animals such as sh and shrimps, high-quality D. magna germplasm resources can improve the quality of aquatic products, shorten the breeding cycle of aquatic products, and improve the economic bene ts of aquaculture [36].In addition, arti cial domestication of D. magna (Taihe Water sampling site) can quickly remove algae and other organic particles, increasing the transparency of the water body by 1.0-1.5 m in a short time, so that submerged plants can be transplanted and survive.Submerged plants quickly reduce the content of nutrients such as nitrogen and phosphorus in the water body through nutrient competition, and inhibit the growth and reproduction of blooms and algae [4], playing a major role in the restoration of water ecosystems.Therefore, studying the genetic structure of D. magna in different regions can not only protect its genetic diversity at a molecular level, but it can also enrich the D. magna gene bank and increase our understanding of its evolutionary potential.
The life history of D. magna is unique; it consists of parthenogenetic generation and bisexual reproduction, and these two reproductive methods can alternate with changes in the external environment [37].When the external environment is suitable, such as suitable temperature, su cient food, and su cient biological space, D. magna reproduces mainly by parthenogenesis, and the egg cells produced by females can directly develop into female offspring without fertilization.This is the most important way for it to reproduce.Once external conditions deteriorate, such as lack of food, high or low pH, the amount of dissolved oxygen in the water drops sharply, metabolic wastes accumulate, population density increases, or the light cycle shortens, the reproductive mode of D. magna will change from asexual to bisexual.When environmental conditions improve again, the reproductive mode of D. magna will switch from asexual reproduction to bisexual reproduction [38].All D. magna samples used in this experiment must be the offspring of asexual reproduction, so it is necessary to ensure a suitable culture environment.In wild waters environment, D. magna reproduces asexually under most conditions, but in some harsh environments, some individuals will reproduce with both sexes and produce fertilized eggs covered by a saddle to resist the poor external environment.Therefore, there will still be differences in the genetic structure of D. magna in the same water area, even if the difference is very small.In addition, the sampling sites in this study are evenly distributed, but only a few sampling sites were chosen, China has a vast territory and a large north-south span.The sampling sites of a certain river cannot fully re ect the genetic diversity of all D. magna in a province or city.
Although the polymorphic SSR markers developed in this experiment are abundant in quantity, provided reliable results, and co-dominant markers, the SSR markers still have co-migration problems.Today, the rapid development of new molecular markers such as EST, SNP, and gene chips have brought genetic diversity research more e cient and rich results and will be the focus of our next research.

Declarations Figures
Map of the sampling locations for the 13 populations of Daphnia magna in the present study

Table 1
Information on samples used for genetic marker development

Table 2
Detailed information on the 26 pairs of microsatellite primers

Table 3
Characterization of 26 novel microsatellite loci in 13 populations of Daphnia magna

Table 4
Genetic diversity index for 13 populations of D. magna analyzed using SSR markers

Table 5
Nei's genetic identity and genetic distance for 13 populations of Daphnia magna Note: Nei's genetic identity (above diagonal) and genetic distance (below diagonal).