Genetic Assessment of Silver Carp Populations in River Chenab (Pakistan) as Revealed by SSR Markers

Abstract

Freshwater fish stocks are being exposed to increasing threats as a result of fisheries and aquaculture practices. Integrating genetic knowledge into fisheries and aquaculture management is becoming increasingly important in order to ensure the sustainability of species. So, I used SSR markers to evaluate the pattern of genetic variability in Silver Carp populations (175 samples) from five different sites of River Chenab, Pakistan. DNA was isolated and processed for analysis. There were no scoring errors related to large allele, no stuttering bands, and no null allele. The mean values of number of alleles, allelic richness, effective number of alleles, observed (Ho) and expected (He) heterozygosites, 1-Ho/He, inbreeding coefficient, pairwise population differentiation, and the gene flow provided data indicating loss of genetic diversity of silver carp in River Chenab (Pakistan). Reasons are overhunting, pollution, inbreeding, and poor control measures.

1. Introduction

Fishes are the most diverse group of organisms. They are facing altered environmental conditions resulting from human activities. Freshwater fish biodiversity is progressively threatened by overexploitation, pollution, habitat loss, introduction of non-native species, and the climate change [1]. Global climate change is causing ocean acidification and rising aquatic temperatures, and it is expected to cause regional changes in salinity, dissolved oxygen supply, and circulation patterns in aquatic environments, which fishes will eventually have to cope with [2].

Aquaculture has been a key contributor to increasing food production for human nutrition and food security. In 2016, global per capita fish consumption was 20.3 kg, with fish accounting for 20% of animal protein intake for over 3.2 billion people around the world [3, 4]. Aquaculture in Asia provides for over 91% of global production, but it will need to continue to increase to fulfill the demands of a fast-growing human population [5]. In 2017, a total of 53.4 million tonnes of fish were produced. Freshwater fish species produced 83.6% of total fish production. Freshwater carps and cyprinids account for over 53.1% of total fish production in the aquaculture industry [6]. One of the most important freshwater fish species in aquaculture is silver carp, Hypophthalmichtys molitrix. Silver Carp have been brought into many nations across the world for biological control (algal blooms) and aquaculture purposes. It reproduces naturally in few sites in the ecosystem, which are comparable to the original environment [7].

The conservation and management of aquatic resources are critical for the prolong usage of fisheries potential for the economic growth of farmers and fishery workers today and in the future. Fisheries and aquaculture are playing a significant role in social development by providing nutritional security for the human population and contributing to the economic improvement of farmers and fishery employees. The fishing sector also contributes foreign exchange profits, amounting to several millions of dollars. Furthermore, aquatic resources are proving to be an essential source of a variety of items with pharmacological and economic significance [8].

As natural environment provides resources for all living communities, so it is essential to protect the natural environment for the conservation and preservation of living species. Unfortunately, human activities are constantly altering aquatic ecosystems around the world [9]. This change has negative impact on fish community structures as well as in other aquatic animals and may be responsible for the extinction of many species.

Genetic diversity evaluates alternate types of genes or noncoding loci within population diversity. The evolution and adaptation of a population are linked to both heterozygosity and the total alleles present within a population. Populations facing stressful environmental conditions have reduced genetic diversity, declined population viability and high extinction likelihood [10].

Both extinction and the speciation have been an indispensable part of life since past. Present extinction rate is very high as compared with historical background. Chemical contamination of the environment has resulted in decline of many populations. Certain environmental toxicants cause reproductive destruction in wildlife. Conservation biology mainly focuses on the conservation of genetic diversity. Chemical contamination causes somatic and germline mutations, which reduce genetic diversity of populations. Chemical contamination damage is at the molecular level as well as population level, which results in loss of genetic diversity [11, 12, 13].

One of the most necessary aspects for the preservation and conservation of living species is the protection of the natural environment. This natural environment provides perfect conditions for all living communities. Human activities, unfortunately, continue to alter aquatic ecosystems all over the world. This change is thought to have a huge effect on fish community structures and other aquatic organisms, and it could lead to the extinction of a lot of species [9]. Humans are attempting to change approximately every environment at an unprecedented rate, and they may now be the most important biotic selective power on the planet [14]. The introduction of species outside of their historical ranges has also some problems along with benefits. Furthermore, anthropogenic disturbances can result in the creation of new environments that are beneficial to exotic species [15].

Commercially, about 40% of fisheries have collapsed or at verge of extinction. The cause for this is a lack of understanding about the fitness of genetic diversity. The majority of breeding programs do not sustain genetic adaptations [16]. Artificial breeding programs should be employed when populations are in danger of extinction. These programs are often employed to improve wild populations in fisheries management. These strategies may have raised stock sizes while also preserving genetic variability, lowering the risk of local extinction [17].

Any measure that quantifies the magnitude of genetic variability within a population is termed as genetic diversity. It provides the insight for evolution by natural selection and influence fitness of the ecosystem as well as affects the growth, productivity, constancy, and inter-specific and intra-specific interactions. Knowledge about variation in either discrete allelic states or phenotypic features can be used in genetic diversity. Variation in phenotype or genotype (allelic states) might be neutral or non-neutral regarding fitness consequences. Molecular markers, for example, microsatellites, straight DNA sequences, AFLPs, or protein polymorphisms often indicate discrete allelic states that are thought to be neutral [18].

Microsatellites are extremely popular in population analysis because of their selective neutrality and the ease with which microsatellite-based data can be replicated and compared in other populations [19]. Ecological and evolutionary similarity drivers affect diversity in communities and populations. Random changes in composition are linked to community drift and genetic drift, migration and gene flow, individuals and species, and selection and coexistence processes (e.g., competition, predation). All these parameters non-randomly influence on allelic or species composition. Speciation and mutation also contribute to genetic and species diversity, but they are generally weak forces that impact composition only over extended periods of time [20].

The degradation of environmental in aquatic ecosystems is increasing, which can result in declines in diversity, reflecting population size reductions and the extinction of intolerant species [21].

Molecular markers are applied to analyze genetic variability in a variety of fish species, and they are significant tool for analyzing patterns of genetic diversity. Microsatellite DNA markers are the most informative and polymorphic markers that can be used to evaluate genetic variability at the molecular level [22]. Microsatellites are the marker of choice for genetic, evolutionary, and ecological research studies because of their high mutation rates, high level of polymorphism, great number, and even distribution across the genome, co-dominance, and ease of analysis using PCR. These microsatellites are also used to determine the genetic variability and structure of farmed food fish species [23].

Different kinds of polymorphic markers have been utilized to analyze genetic diversity such as protein based markers (i.e. allozymes) and DNA-based markers such as microsatellites, amplified fragment length polymorphisms (AFLPs), restriction fragment length polymorphisms (RFLPs), random amplification of polymorphic DNA (RAPD), and mitochondrial DNA (mtDNA). Microsatellites markers have been most frequently utilized in the analysis of the carp genetic diversity. The extreme success of microsatellites in the population analysis comes directly from the selective neutrality of these markers and effective replication and validity of microsatellite-based data in different populations. Microsatellites are especially helpful for the assessment of genetic biodiversity. Microsatellites, also known as “simple sequence repeats,” possess 2–9 bp that are widely distributed across the genome and have a high degree of polymorphism. The majority of microsatellite loci are short and easy to amplify using PCR. SSR markers are used to construct a genetic fingerprint and to demonstrate connections between individuals. SSR markers are widely employed in fish population genetics and conservation research studies [24].

2. Review of literature

David et al. [25] studied 47 microsatellite markers in carp species, Cyprinus carpio and Ctenopharyngodon idella, and observed polymorphism by applying the AFLP (Amplified Fragment Length Polymorphism). The average number of allele was found 4.02 and mostly SSRs contain CA and CT motifs. The calculated fixation index (F_ST) for microsatellites and AFLP markers was 0.37 and 0.39. About half of the SSRs markers were used to genotype the grass carp. Their results indicated that grass carp is phylogenetically distinct from other populations.

The researchers [26] explored the population structure and genetic variability of two Hungarian common carp farms (80 and 196 individuals) by synthesizing primers to the flanking regions of eight microsatellites: MFW4, MFW7, MFW9, MFW13, MFW17, MFW20, MFW26, and MFW31. Samples were chosen at random from Attala, Dinnyes, Boszormeny, Bikal, Szajol, wild-Danube, and wild-Tisza. They detected 47 alleles in these groups. All these groups had similar allele frequencies, with the exception of wild carps. Private allele frequency was extremely low, with a value 0.003 to maximum of 0.027. At the Attala and the Dinnyes stock, the average He was 0.83 and 0.81, respectively, while Ho was 0.69 for both stocks. Most loci of these two populations were in disequilibrium when tested for HWE. These findings could aid in the identification of wild carp taxonomic status and genetic variability as well as their relatedness to domesticated stocks.

The researchers [27] analyzed 54 primers for amplification of microsatellite loci in 84 samples of kali rohu, Labeo dyocheilus (Family Cyprinidae) from four rivers, namely Satluj, Jiabharali, Beas, and Yamuna. Successful amplification was observed in 15 primers pairs. Seven microsatellites, MFW1, MFW2, MFW9, MFW15, MFW17, R-12F, and Ca12, were polymorphic having three to nine alleles. Ho values ranged from 0.34 to maximum 0.53. Mean number of alleles was 3.42–4.71. There was found no significant deviation from HWE in allele frequencies except at locus Ca12 in the sample of Jiabharali. The reason may be the presence of null allele at locus Ca12, which was not amplified. Rest of the alleles showed highly nominate heterogeneity in all the sample sets. The identified microsatellite loci could be used in fine-scale population structure analysis of L. dyocheilus.

Li et al. [28] analyzed six wild populations of Common Carp (C. carpio L.) using 30 microsatellite loci. Different types of parameters for genetic diversity such as number of effective alleles (A_e), polymorphic information content (PIC), expected heterozygosity (H_e) and observed hererozygosity (H_o), genetic distance, and genetic similarity index were detected. There were present total 210 alleles in these six populations and 3–13 alleles were amplified in 30 loci. In each locus, the average number of alleles was seven. These six wild common carp showed high population variation. Effective alleles were ranging from 1.04 to maximum 4.72. The result indicated low-to-moderate level of genetic variability in these populations. PIC values of these C. carpio populations were 0.45, 0.51, 0.52, 0.56, 0.62, and 0.63, respectively. The average values of He were 0.51, 0.60, 0.57, 0.57, 0.58, and 0.55 respectively. On average, the number of effective alleles (Nae), observed hererozygosity (H_o), expected heterozygosity (H_e), and PIC were 2.71, 0.57, 0.58, and 0.48 respectively. Clustering result and the geographical distribution were in correlation with each other.

Wang et al. [29] developed SSR markers for common carp (C. carpio). Total 32 samples of common carp were collected from Dongting Lake in China. Most of the SSRs of common carp were found to consist of dinucleotide (AC/TG, AG/TC, and CG/GC) and trinucleotide (AAT and ATC) repeats. Polymorphism was observed in only 25 loci out of 60 SSRs in the common carp population under examination. The number of alleles/locus varied from three to seventeen. The value of H_o and H_e ranged 0.13–1.00 and 0.12–0.91, respectively. Six SSRs did not follow Hardy-Weinberg equilibrium (HWE), while the remaining 19 loci did. Mutation rates in gene-coding sequences are lower than in non-coding genomic sequences due to evolutionary conservation. Furthermore, polymorphism was not totally determined by repeat length.

Zhu et al. [30] analyzed the genetic variability of five Silver Carp populations in the middle and lower reaches of the Yangtze River. For this purpose, 30 SSR markers were utilized and total 144 alleles were found with 1–10 alleles in each locus (average 4.0 to 4.1). In total, 83.33% (25 loci) were polymorphic. The average values of observed hererozygosity (H_o) and expected heterozygosity (H_e) ranged from 0.3233 to maximum 0.3511 and 0.4421 to maximum 0.4704, respectively, and the average PIC value ranged from 0.4068 to 0.4286. These populations were moderately differentiated and partially deviated from HWE as revealed by Fst value and Chi-square test, respectively. The genetic distance and genetic similarity coefficient values were from 0.0893 to 0.1665 and from 0.8466 to 0.9146, respectively.

Cheng et al. [31] evaluated genetic structure of bighead carp (Aristichthys nobilis) by using microsatellite markers and documented their cross-species amplification in Silver Carp (Hypophthalmichthys molitrix). For this purpose, 30 individuals of each species were collected from Zhangdu Lake of the Yangtze River, China. Forty-two pairs of primer development were synthesized from which only 30 produced desired products. Polymorphism was seen in 16 loci having 2–7 alleles/locus with an average value of 3.263 and the Ho was 0.100–0.690 with an average value of 0.392. By applying the same PCR conditions in the cross-species amplifications, it was observed that 11 out of 16 microsatellites of bighead carp fish were also polymorphic in Silver Carp fish.

Wang et al. [32] analyzed the genetic viability of two Silver Carp populations by applying 39 microsatellite markers. The samples were collected from the middle and upper reaches of the Yangtze River, China. There were in total 260 alleles. The averages of number of alleles were 6.130 and 4.980, and averages of effective number of alleles (Nae) were 4.108 and 3.385 among the Wanzhou population and Jianli populations, respectively. The polymorphic informatics content varied between 0.077 and 0.865 (average 0.617). The average Ho and He were 0.834 and 0.775 and 0.713 and 0.623, respectively, for studied populations. There was a clear genetic differentiation between these two populations.

Li et al. [33] studied that SSR markers are significant DNA markers, which are accessible to figure out population structure. The Grass Carp populations were analyzed for genetic variability and genetic structure by using 45 polymorphic microsatellite loci. Different types of parameters for genetic diversity were measured such as number of alleles/locus (N_a), effective number of allele/loci (N_e), expected heterozygosity (H_e), and observed hererozygosity (H_o). The values of the parameter were found to be: number of alleles/locus was 7.26, effective number of allele/loci was 4.21, Ho was 0.73, and He was 0.68. It was found that population genetic diversity is significantly affected by loci number, sample size, and polymorphism information of microsatellite markers.

Alam et al. [34] determined the genetic structure and genetic diversity of Indian major carp, Labeo rohite sampled from River Halda, River Jamuna, and River Padma in Bangladesh. They analyzed four polymorphic microsatellite loci. On average, there were 2.75–3.75 alleles with size ranging from 144 bp to 190 bp. The populations differed in terms of the frequency and the number of alleles, as well as observed (Ho) and expected heterozygosity (He) in the loci studied. A significant (P < 0.05) population differentiation (F_ST) was found between the Halda and the Jamuna population. Between the Padma and Jamuna populations, there was relatively high gene flow. The findings demonstrated a rather low amount of genetic diversity in L rohita populations in Bangladesh. The alleles Lr3 and Lr21 were present only in population of River Jamuna with the frequency of 0.04 and 0.02, respectively, so termed as private alleles for the Jamuna population. There was no allelic drop-out in the Jamuna population while highest allelic drop-out was observed in the Halda population. The values of Ho and He were ranging from 0.17 to 0.65 and from 0.24 to 0.62, respectively. Two clusters were delivered by UPGMA dendrogram. The Halda population was in one cluster, and Jamuna and Padma populations were in the other cluster.

Abbas et al. [35] utilized total nine polymorphic microsatellite markers to determine the genetic diversity and population structure of five populations of Yellowcheek carp (Elopichthys bambusa) in the Yangtze River basin in China. There was observed low-to-moderate genetic diversity. The number of alleles/locus varied from three to maximum eight with an average value of 4.6 alleles/locus. The values of Ho were 0.15–1.00. All these loci represented significant deviations (P < 0.01) from HWE. There occurred loss of heterozygosity within populations as indicated by the values of inbreeding coefficient. Lower but significant value (P < 0.01) of FST indicated genetic divergence between populations of E. bambusa. About 93.81% variance was within populations, and 7.05% of the total variance was among the populations as shown by AMOVA results. Mantel tests provided no evidence for an increase of the genetic differences with geographic distance. Due to anthropogenic interventions, the populations are reproductively isolated as revealed by UPGMA dendrogram. These findings could contribute to the effective management and prolonged conservation of E. bambusa populations.

Hulak et al. [36] studied the population structure and parameters of genetic diversity of 11 Carp populations in the Czech Republic. Mean heterozygosity was 0.584–0.700. Mean number of alleles was 5.0–9.8. It was found significant heterozygote deficit. Most of tests of the analyzed loci were deviated significantly (P < 0.05) from the Hardy-Weinberg equilibrium. Inter-population genetic variation was 21%, while intra-population genetic variation was 79% as revealed by AMOVA. Mostly, inter-population genetic was responsible for microsatellite loci variations.

Adams et al. [37] collected 56 samples of the Grass Carp (C. idella) population to study the genetic structure from Missouri and Mississippi River basins, USA. The numbers of alleles/locus were 2–8 across all the polymorphic microsatellite markers. Locus Ci04 did not produced any amplicons for all the collected samples. Average allelic diversity was low along basins of these rivers and highest in the upstream reach of the Missouri River and the Mississippi River. There was found no significant differences in levels of inbreeding between these populations. Fourteen out of 16 loci produced least values of both observed and expected heterozygosity. A significant bottleneck phenomenon was observed along the basins of both the rivers.

Sahu et al. [38] studied Raho (Labeo rohita) from normalized cDNA libraries to investigate genetic structure and genetic diversity. They assembled 3631 unique sequences (709 contigs and 2922 singletons) from 6161 random clones sequences. In total, 182 unique sequences out of 3631 unique sequences (709 contigs and 2922 singletons) were found to be associated with reproduction-related gene. Polymorphism was seen in 20 loci in 36 unrelated individuals, and their allele frequency ranged from 2 to 7 per locus. From these 20 polymorphic loci, 14 loci deviated from HWE (p < 0.05). In 3631 unique sequences, AG repeats were most frequent motif. The values of expected heterozygosity H_e and observed heterozygosity H_o ranged from 0.109 to 0.801 and from 0.096 to 0.774, respectively. These microsatellite loci did not show any linkage disequilibrium.

Sahoo et al. [39] evaluated the genetic variation of L. rohita. Eleven microsatellites loci were used to assess the genetic diversity of three wild and one farm population of rohu. For this purpose, total 192 samples were analyzed, and the number of alleles were found to be four to maximum 23, observed heterozygosity 0.500–0.870, and expected heterozygosity from 0.389 to 0.878. At least, one locus was not in HWE in these riverine samples. Negative values of inbreeding coefficients (FIS) indicated little genetic differentiation but very high level of genetic diversity among populations. Micro-Checker did not revealed any null alleles. There was reported minimum scoring error. FST values ranged from 0.005 to 0.043. All of the rohu populations had a high allelic richness and were genetically diverse.

Tibihika et al. [40] described the genetic structure of East African Nile tilapia (Oreochromis niloticus) by using SSR-GBS technique. For this purpose, 2,403,293 paired reads were produced for primer design containing 6724 SSR motifs, from which 35 SSRs were developed, and only 26 produced amplified products. F_is values deviated from HWE for all 26 loci. Most loci were polymorphic and four loci deviated from HWE. PIC values for 18 loci were above 0.5 showing that they were highly informative markers and for remaining four loci, PIC values were between 0.25 and 0.5 indicating slightly informative markers.

Fang et al. [41] developed 12 SSRs for cross-species amplification in silver carp (H. molitrix) and bighead carp (Hypophthalmichthys nobilis). The values of number of alleles (Na), the observed heterozygosity (Ho) and expected heterozygosity (He), and the polymorphic information content (PIC) vary from 5 to 20, 0.189–0.956, 0.177–901, and 0.169–0.887, respectively. All these loci were polymorphic. Genetic structure was similar for population of same species and obvious genetic differentiations was present between populations from different species. Private alleles were ranging from 1 to 6 in H. nobilis and 3–10 in H. molitrix individuals.

Zhou et al. [42] studied that there are rare population genetic studies for Black carp (Mylopharyngodon piceus) in the Yangtze River basin and developed 31 novel microsatellite markers. Ten microsatellite markers were used to access the genetic variability of Black Carp. Mean number of alleles (N_a) was 14, and number of effective alleles (A_e) was 6. Their study explained that wild populations had higher genetic diversities than cultured populations. The values of H_o, H_e, and PIC parameters for genetic diversity of wild populations were 0.767, 0.806, and 0.767, respectively. The values of H_o, H_e, and PIC parameters for genetic diversity of cultured populations were 0.730, 0.722, and 0.6731, respectively. Founder effects may be one of the most probable causes of the reduction of genetic variation in cultured populations.

Fang et al. [22] evaluated the genetic status of eight populations of Silver Carp in Jiangsu province and four populations of Silver Carp from Lower Reaches of the Yangtze River (LRYR) in China by using microsatellite loci. High polymorphism was observed between all the loci. There were in total 3–33 alleles/locus with mean value ranging from 5.727 to 14.818. The range of effective number of alleles per locus was 4.19 to maximum value 6.526. The average observed heterozygosity (Ho) ranged from 0.625 to 0.727, and the average expected heterozygosity (He) ranged from 0.69 to 0.784. Gene flow values (Nm) were high across all populations, ranging from 3.496 to 79.845. With AMOVA analysis, the majority of differentiation variations (95.85%) were assigned within populations, with only 4.15% existing between populations. Most populations were potentially threatened by inbreeding depression. Fst values ranged from 0.003 to 0.067, and all groups exhibited moderate genetic difference.

3. Materials and methods

3.1 Fish sampling, DNA isolation, and quantification and microsatellite amplification

Sampling of Silver Carp (H. molitrix) was done from five selective sites of River Chenab, namely Trimmu Barrage, Marala Headworks, Khanki Headworks, Qadirabad Headworks, and Chiniot Bridge (Table 1) and in total 175 samples were collected (35 samples from each site). By following Sambrook and Russell [43], DNA isolation protocol having slight modifications, DNA was extracted from dorsal muscle tissues. By using scissors, spines and scales were removed as much as possible from frozen tissues. Standard proteinase-K and phenol/chloroform method was used for isolating DNA. Genomic DNA isolation consisted of following steps:

Ssr #	Name of the site	Site code	Geographical location	No. of samples
1	Trimmu Headwork	TH	31.1443° N 72.1464° E	35
2	Marala Headwork	MH	32°39′ 0″ N 74°30′ 0″ E	35
3	Khanki Headwork	KH	32°24′ 0″ N 73°59′ 0″ E	35
4	Qadirabad Headwork	QH	31° 9′ 54″ N 74°20′ 6″ E	35
5	Chiniot Bridge	CB	31°43′12″ N 72°58′44″E	35

Table 1.

H. molitrix sampling details.

Tissue lysis buffer:

• Tris HCl (100 mM)

• EDTA (0.5 M)

• SDS (10%)

• NaCl (5 M)

• ddH₂O

3.2 Preparations for DNA washing and precipitation

• Phenol

• PCI = Phenol: chloroform: iso-amyl alcohol (25:24:1)

• Cl = Chloroform: iso-amyl alcohol (24:1)

• Ethanol 70%

• Absolute ethanol 95%

• 3 M solution of sodium acetate

3.3 DNA quantification

In total, 0.8% agarose gel electrophoresis (ATTO Corporation AE 6220) was used for checking the isolated DNA quality. For making gel-like suspension, 0.8 g agarose was added into 100 mL 1X TAE buffer.

3.4 Analysis of DNA

Nanodrop was used for assessing the quality of isolated DNA. One microliter DNA sample was used for checking the convention of isolated DNA. The convention of isolated DNA was adjusted at 50 ng/μL for PCR by mixing the stock solution of DNA with nuclease-free water.

Calculation was done by applying the following formula:

$${\mathrm{C}}_1{\mathrm{V}}_1={\mathrm{C}}_2{\mathrm{V}}_2$$

Where.

C₁ = Stock DNA solution concentration.

V₁ = Volume of DNA required.

C₂ = Diluted DNA solution concentration.

V₂ = Total volume of dilution required.

3.5 Microsatellite amplification

Genomic DNA was PCR amplified by H. molitrix. Five primers, namely BL8–1, BL14, BL52, BL108, and BL123, were used taken from Gene Library (Table 2).

Sr.#	Locus and accession no.	Repeat motif	Primer sequence (5′-3′)	Size range (bp)	Ta (˚C)	Na
1	BL8-1 DQ136005	(TCCA)6	F: TATTGACTGCATCTGGGTCTT; R: AGGTTATGTTTAGCCCAGTCG	157–162	59	3
2	BL14 DQ136008	(GT)13	F: CGGCACTCAGAAATGATGGGG; R: CATGGAGAGCAGGAAGAGTTG	312–338	54	9
3	BL52 DQ136015	(TG)12	F: CAGAATCCAGAGCCGTCAG; R: CACCGAACAGGGAACCAA	210–220	54	5
4	BL108 DQ674845	(GT)9	F: GATGAATCGCAGGGCGTGAGG; R: GCAGAACACGCACAATGGAGA	383–389	54	4
5	BL123 DQ674850	(TG)9	F: GCGACAGGAACAGTGAAAAC; R: CAAAGAAGGCACAAAGGATT	227–244	54	8

Table 2.

SSR markers of H. molitrix with details.

PCR reaction was conducted at 25 μL reaction mixture by using (Multigene Optimax, Lab Net, USA) that contained the following ingredients (Table 3)

• PCR master mix (2X)

• Forward primer

• Reverse primer

• Template DNA

• Nuclease-free water

S #	Reagents	Quantity
1	PCR master mix (2X)	12 μL
2	Forward primer	2 μL
3	Reverse primer	2 μL
4	Template DNA	3 μL
5	Nuclease free water	6 μL
Total 25 μL

Table 3.

Reaction mixture formation for PCR amplification.

3.6 Thermocycler conditions

• Preheated for 5 minutes at 94°C.

• For 30 cycles, thermal denaturation temperature was set at 94°C for 1 minute.

• Annealing temperature was primer-specific that was set at for 55°C 30 seconds.

• Extension of amplified DNA at 72°C for 1 minute.

• Final elongation at 72°C for 4 minutes (Table 4)

Table 4.

Thermocycler conditions for PCR.

3.7 Electrophoresis and visualization for separation of amplified products

The PCR products were isolated on a 5% non-denaturing PAG containing 19:1 acrylamide: bis-acrylamide and visualized by silver-staining method. Electrophoresis was conducted using a SequiGen sequencing gel electrophoresis method. For the visualization of DNA bands, silver-staining method was used.

3.8 Software and analytical packages

Software and analytical packages for genome mapping were provided by [44, 45, 46, 47, 48, 49, 50, 51].

1. FSTST (ver.2.9.3.2)

2. GENPOP (ver. 1.2)

3. ARLEQUIN (ver. 2.000)

4. TFPGA (ver. 1.3)

5. POPGENE (ver. 32)

3.9 Data analysis

Allele frequency, allelic richness (Ar), observed heterozygosity (Ho), and expected heterozygosity (He) were estimated with FSTAT ver. 2.9.3.2 to summarize the genetic composition of the population [44, 50]. The GENEPOP ver. 1.2 was used to test linkage disequilibrium (LD) between all pairs of luci [46]. ARLEQUIN ver. 2.000 was used to calculate deviation from HWE across each locus using the Markov-chain random walk algorithm [51]. To maintain a within-sample type-1 error rate of α = 0.05 for each locus, the statistical significance of deviations from HWE was corrected using the sequential Benferroni correction.

Inbreeding coefficient (Fis) and level of population subdivision/population over loci were determined by unbiased F-statistics by using software FSTAT ver. 2.9.3.2 [44]. Genetic divergence Fst among subdivisions for all pairs comparisons between sampling locations was deduced by calculating Weir and Cockerham’s (1984) [44]. The significance of estimates of Fst was assessed using 10,000/mutations. The hierarchical partition of genetic diversity was estimate by conducting analyses of molecular variance (AMOVA) using ARLEQUIN ver. 2.000.

ARLEQUIN ver. 2.000 was used to calculate the pairwise estimates of Fst values and test their significance by bootstrapping analysis (1000 replicates) for genetic differentiation evaluation between populations. Exact tests for population differentiation (Raymond and Rousset, 1995) were conducted using GENEPOP. UPGMA dendrogram based on Nei’s (1987) [50] unbiased distance was interpreted using TFPGA software.

4. Results

4.1 Genetic diversity in H. molitrix populations

In current study, the “Micro-checker” software was applied to the genotypie data obtained for H. molitrix populations that showed no scoring errors related to large allele, no stuttering hands, and no presence of null alleles at all the loci. In the current study, the screened microsatellite loci in all the examined H. molirix populations were demonstrated to be varied. The patterns of genetic diversity fluctuate depending on the screened microsatellite locus and the studied fish population. The average allele frequency and allele size ranged from 0.003 to 0.574 and from 157 to 389 base pairs, respectively, were observed at different screene d loci in H. molitrix populations in the present study (Figure 1, Table 5)

Figure 1.

Map of Pakistan showing Chenab River.

Locus	Allele size (bp)	populations					average
		TH	MH	KH	QH	CB
BL 8-1	157; 158; 159; 160	0.221; 0.368; 0.412; 0.000	0.429; 0.557; 0.014; 0.000	0.574; 0.368; 0.044; 0.015	0.426; 0.529; 0.044; 0.000	0.471; 0.471; 0.057; 0.000	0.424; 0.459; 0.116; 0.003
BL 14	312; 314; 319; 322; 325; 329; 331; 335; 338	0.214; 0.271; 0.229; 0.143; 0.057; 0.029; 0.029; 0.029; 0.000	0.206; 0.294; 0.250; 0.147; 0.029; 0.029; 0.015; 0.015; 0.015	0.235; 0.368; 0.235; 0.059; 0.029; 0.029; 0.015; 0.015; 0.015	0.071; 0.229; 0.257; 0.129; 0.086; 0.100; 0.057; 0.071; 0.000	0.271; 0.229; 0.300; 0.100; 0.043; 0.014; 0.014; 0.014; 0.014	0.199; 0.277; 0.254; 0.116; 0.049; 0.040; 0.026; 0.029; 0.009
BL 52	210; 212; 214; 216; 218; 220	0.121; 0.212; 0.212; 0.212; 0.227; 0.015	0.191; 0.544; 0.235; 0.015; 0.015; 0.000	0.294; 0.500; 0.162; 0.044; 0.000; 0.000	0.273; 0.409; 0.242; 0.061; 0.015; 0.000	0.348; 0.409; 0.152; 0.076; 0.015; 0.000	0.246; 0.416; 0.201; 0.081; 0.054; 0.003
BL 108	383; 385; 387; 388; 389	0.191; 0.221; 0.235; 0.353; 0.000	0.457; 0.429; 0.114; 0.000; 0.000	0.250; 0.676; 0.059; 0.015; 0.000	0.314; 0.529; 0.114; 0.029; 0.014	0.100; 0.557; 0.300; 0.043; 0.000	0.263; 0.483; 0.165; 0.087; 0.003
BL 123	227; 230; 232; 234; 236; 238; 240; 242; 244	0.162; 0.191; 0.147; 0.147; 0.103; 0.147; 0.088; 0.015; 0.000	0.071; 0.486; 0.257; 0.129; 0.014; 0.014; 0.014; 0.014; 0.000	0.338; 0.353; 0.132; 0.074; 0.059; 0.015; 0.015; 0.015; 0.000	0.257; 0.229; 0.300; 0.100; 0.071; 0.014; 0.014; 0.014; 0.000	0.074; 0.574; 0.162; 0.044; 0.059; 0.029; 0.029; 0.015; 0.015	0.180; 0.366; 0.201; 0.099; 0.061; 0.044; 0.032; 0.015; 0.003

Table 5.

Allele frequency and size (bp) noticed at each locus in all populations of H. molitrix.

4.2 Allelic diversity (Na) and Allelic Richness (Ar)

In current study, the number of alleles (Na) per locus extended from 3.00 to 9.00 with an average from 5.6 to 9.0, While the values of allelic richness (Ar) were ranging from 2.943 to 8.940 with an average value varying from 5.513 to 5.942 in various H. molitrix populations. The largest average value of number of alleles and allelic richness were noted in the population of CB and minimum in the population of MH. At locus BL 14, the highest values of number of alleles and allelic richness were found 8.911 in the MH population. The average values of Na and Ar in the populations of TH, MH, KH, QH, and CB were observed as 5.8 (Ar = 5.79), 5.6 (Ar = 5.513), 5.8 (Ar = 5.753), 5.8 (Ar = 5.754), and 6.0 (Ar = 5.942) respectively (Table 6–10, Figures 2–7).

Loci	Genetic diversity parameters
	Na	Ar	Nae	Ho	He	1-Ho/He	Fis	PHWE
BL 8-1	3.000	3.000	2.8857	0.6000	0.6629	0.0949	0.060	0.4779^NS
BL 14	8.000	7.993	5.0515	0.8000	0.8137	0.0168	0.017	1.0000 ^NS
BL 52	6.000	6.000	5.1148	0.8286	0.8161	−0.0153	−0.085	0.6501 ^NS
BL 108	4.000	4.000	3.8222	0.6000	0.7491	0.1990	0.174	0.7061 ^NS
BL 123	8.000	7.971	6.7680	0.8000	0.8646	0.0747	0.050	1.0000 ^NS
Average	5.8	5.79	4.7284	0.7257	0.7812	0.0740	0.040	—

Table 6.

Genetic diversity at different microsatellite loci in TH populations of H. molitrix.

Loci	Genetic diversity parameters
	Na	Ar	Nae	Ho	He	1-Ho/He	Fis	PHWE
BL 8-1	3.000	2.943	2.0231	0.7143	0.5130	−0.3924	−0.400	0.0160 ^*
BL 14	9.000	8.911	4.6402	0.5714	0.7959	0.2821	0.264	0.4143 ^NS
BL 52	5.000	4.941	2.6458	0.5143	0.6311	0.1851	0.149	1.0000 ^NS
BL 108	3.000	3.000	2.4648	0.4000	0.6029	0.3365	0.340	0.0874 ^NS
BL 123	8.000	7.771	3.0818	0.6571	0.6853	0.0411	0.042	0.7349 ^NS
Average	5.6	5.513	2.9711	0.5714	0.6456	0.0905	0.104	—

Table 7.

Genetic diversity at different microsatellite loci in MH populations of H. molitrix.

Loci	Genetic diversity parameters
	Na	Ar	Nae	Ho	He	1-Ho/He	Fis	PHWE
BL 8-1	4.000	3.971	2.1157	0.6857	0.5337	−0.2848	−0.309	0.0409^*
BL 14	9.000	8.911	3.9773	0.6000	0.7594	0.2099	0.189	0.2904 ^NS
BL 52	4.000	4.000	2.7684	0.6000	0.6480	0.0741	0.043	1.0000 ^NS
BL 108	4.000	3.971	1.9647	0.5143	0.4981	−0.0325	−0.097	1.0000 ^NS
BL 123	8.000	7.912	3.6953	0.8286	0.7400	−0.1197	−0.147	0.0019^*
Average	5.8	5.753	2.9043	0.6343	0.6361	−0.0306	−0.048	—

Table 8.

Genetic diversity at different microsatellite loci in KH populations of H. molitrix.

Loci	Genetic diversity parameters
	Na	Ar	Nae	Ho	He	1-Ho/He	Fis	PHWE
BL 8-1	3.000	3.000	2.1624	0.3429	0.5453	0.3712	0.355	0.0936 ^NS
BL 14	8.000	8.000	6.0345	0.4000	0.8464	0.5274	0.531	0.0022^*
BL 52	5.000	5.000	3.2974	0.4000	0.7068	0.4341	0.403	0.2947 ^NS
BL 108	5.000	4.940	2.5494	0.4571	0.6166	0.2586	0.261	0.1733 ^NS
BL 123	8.000	7.829	4.4627	0.6000	0.7872	0.2378	0.240	0.4491 ^NS
Average	5.8	5.754	3.7013	0.4400	0.7005	0.3658	0.365	—

Table 9.

Genetic diversity at different microsatellite loci in QH populations of H. molitrix.

Loci	Genetic diversity parameters
	Na	Ar	Nae	Ho	He	1-Ho/He	Fis	PHWE
BL 8-1	3.000	3.000	2.2334	0.6000	0.5602	−0.0710	−0.072	0.7403 ^NS
BL 14	9.000	8.771	4.3750	0.8571	0.7826	−0.0952	−0.097	1.0000 ^NS
BL 52	5.000	5.000	3.0934	0.7143	0.6865	−0.0405	−0.095	0.4700 ^NS
BL 108	4.000	4.000	2.4257	0.6857	0.5963	−0.1499	−0.153	0.3086 ^NS
BL 123	9.000	8.940	2.8389	0.5714	0.6571	0.1304	0.084	1.0000 ^NS
Average	6.0	5.942	2.9933	0.6800	0.6533	−0.0452	−0.067	—

Table 10.

Genetic diversity at different microsatellite loci in CB populations of H. molitrix.

Figure 2.

Comparative distribution of number of alleles (Na) at different SSR loci in H. molitrix populations.

Figure 3.

Comparative distribution of allelic richness (Ar) at different SSR loci in H. molitrix populations.

Figure 4.

Comparative distribution of effective number of alleles (Nae) at different SSR loci in H. molitrix populations.

Figure 5.

Comparative distribution of observed heterozygosity (Ho) at different SSR loci in H. molitrix populations.

Figure 6.

Comparative distribution of expected heterozygosity (He) at different SSR loci in H. molitrix populations.

Figure 7.

Comparative distribution of 1-Ho/He at different SSR loci in H. molitrix populations.

4.3 Effective number of alleles (Nae)

The values of effective number of alleles (Nae) were observed ranging from 1.9647 to 6.7680 in various studied H. molitrix populations. The average value of Nae was observed as 4.7284, 2.9711, 2.9043, 3.7013, and 2.9933 in TH, MH, KH, QH, and CB, respectively. The largest value of Nae was observed in population collected from TH while the lowest in the population of KH (Tables 6–10, Figures 2–7).

4.4 Heterozygosity (H)

In the present study, heterozygosity (H) level was observed moderate to high in all examined H. molitrix populations. In various examined H. molitrix populations, the values of observed heterozygosity (Ho) were measured ranging from 0.3429 to 0.8571. The average Ho value was observed as 0.7257, 0.5714, 0.6343, 0.4400, and 0.6800 in TH, MH, KH, QH, and CB, respectively. The fish population sampled from QH revealed the lowest value of Ho and TH and CB population showed the highest value as compared with others (Tables 6–10, Figures 2–7). The values of expected heterozygosity (He) were ranging from 0.4981 to 0.8646 in various selected H. molitrix populations. The average values of He were determined as 0.7812, 0.6456, 0.6361, 0.7005, and 0.6533 in TH, MH, KH, QH, and CB, respectively.

4.5 Inbreeding coefficient (FIS)

On average, three populations of H. molitrix showed positive inbreeding coefficient (Fis) values, while two populations showed negative in the present study. At the screened SSR loci in the examined H. molitrix populations, Fis values ranging from −0.400 to 0.531 were recorded. Highest average Fis value was measured 0.365 for QH while the lowest −0.067 for CB population of H. molitrix. The mean values of Fis in TH, MH, and KH were observed as 0.040, 0.104, and − 0.048, respectively (Tables 6–10). The comparative dispersal of Fis values over the screened SSR loci in each H. molitrix population is shown in the Figure 8.

Figure 8.

Comparative distribution of inbreeding coefficient (F_IS) at different SSR loci in H. molitrix populations.

4.6 Deviation from Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium

Four out of 25 tests deviated from HWE significantly after applying multiple test correction (Tables 6–10). At various screened loci, the pairwise p value was found significant at p < 0.05 in examined H. molitrix population.

4.7 Population genetic structure of H. molitrix populations

4.7.1 Genetic differentiation (F_ST) and geographical distance (KM)

The pairwise population differentiation (F_ST) across all screened microsatellite loci among the H. molitrix populations was assessed using the windows-based software FSTAT. For the majority of the population pairs in this investigation, F_ST was statistically significant (p < 0.05) revealing genetically nonhomogenous groups. For the majority of the stocks in this investigation, the noteworthy findings relating population genetic differentiation revealed genetically nonhomogeneous groups (Table 11). A moderate level of F_ST was indicated by the pairwise estimates of F_ST. Highest level of F_ST was found 0.1033 in the population-pair of TH-KH, while the least 0.0120 between the population-pair of MH-QH in this study (Table 11, Figure 9).

Populations	TH	MH	KH	QH	CB
TH	—
MH	0.0920^NS	—
KH	0.1033 ^NS	0.0321*	—
QH	0.0664 ^NS	0.0120*	0.0139*	—
CB	0.0859 ^NS	0.0284*	0.0285*	0.0314*	—

Table 11.

Pairwise population differentiation (F_ST) between natural populations of H. molitrix.

*

Significant at P < 0.05

Figure 9.

Correlation of geographic distance (GD) and population genetic differentiation (F_ST) values among H. molitrix populations.

Table 12 depicts the pairwise geographical distance (KM) between H. molitrix populations. The population pair MH-TH had the greatest geographical distance, while the population pair KH-QH had the smallest geographical distance. Figure 9 depicts a graphical comparison of population genetic differentiation and geographical distance among the various H. molitrix populations studied. The graph demonstrated a direct relationship between geographic distance and population genetic differentiation. The genetic differentiation in populations was observed to increase as geographical distance increased.

Populations	TH	MH	KH	QH	CB
TH	—
MH	331	—
KH	237	75	—
QH	243	104	41	—
CB	122	207	162	116	—

Table 12.

Pairwise geographical distance between natural populations of H. molitrix.

4.7.2 Genetic distance (GD) and genetic identity (GI)

The genetic distance (GD) and genetic identity (GI) were calculated using the windows-based software TFPGA, based on allele frequency data from all of the studied populations. Only two population pairs yielded statistically significant results (P < 0.05). The highest GD was 0.2943 between the TH-KH population pairs, while the lowest was 0.0289 between the MH-QH population pairs (Table 13). Similarly, the population pair QH-MH had the highest GI value of 0. 9715, while the population pair TH-KH had the lowest GI value of 0.7451(Table 14).

Populations	TH	MH	KH	QH	CB
TH	—
MH	0.2620^NS	—
KH	0.2943^NS	0.0614^NS	—
QH	0.2248^NS	0.0289*	0.0293*	—
CB	0.2461^NS	0.0559^NS	0.0527^NS	0.0734^NS	—

Table 13.

Pairwise Nei’s unbiased genetic distance (GD) between populations of H. molitrix.

*

Significant at P < 0.05

Populations	TH	MH	KH	QH	CB
TH	—
MH	0.7695	—
KH	0.7451	0.9404	—
QH	0.7987	0.9715	0.9711	—
CB	0.7819	0.9456	0.9487	0.9292	—

Table 14.

Pairwise Nei’s unbiased genetic identity (GI) between natural populations of H. molitrix.

Figures 10 and 11, respectively, show a graphical comparison of geographical distance versus genetic identity and genetic distance versus genetic identity in the various Hypophthalmichthys molitrix populations. These graph revealed a negative relationship between genetic distance and genetic identity, as well as a negative relationship between genetic identity and geographical distance. The genetic identity of populations was seen to decrease as the genetic distance between them increased (Figure 12).

Figure 10.

Correlation of Geographic distance (KM) and genetic distance (GD) values among H. molitrix populations.

Figure 11.

Correlation of Geographic distance (KM) and genetic identity (GI) values among H. molitrix populations.

Figure 12.

Correlation of genetic distance (GD) and genetic identity (GI) values among H. molitrix populations.

4.7.3 Analysis of molecular variance (AMOVA)

The AMOVA revealed a low variation percentage (7.81141%) between individuals within populations while the majority of variations (87.05210%) were occurring within individuals and 5.13648% variations among populations of H. molitrix in present study (Table 15).

Source of variance	df	MSS	Variance	%Variance
Among populations	4	6.554	0.09245	5.13648
Between individual within populations	166	1.7576	0.14060	7.81141
Within individual	171	1.5343	1.56690	87.05210

Table 15.

Analysis of molecular variance (AMOVA) for natural populations of H. molitrix.

4.7.4 Gene flow (Nm)

The gene flow (Nm) rate in various H. molitrix populations across all screened microsatellite loci was measured by using the windows-based program Popgene. The highest value of Nm (17.4152) was found at locus BL 14, while the lowest value (2.4769) was found at locus BL 108. BL 8–1, BL 52, and BL 123 were the remaining screened loci in this study, with Nm values of 3.4775, 5.5691, and 4.4293, respectively. Nm was found to be 4.5654 on average across all SSR loci (Table 16).

Locus	Sample size	Nm
BL 8-1	350	3.4775
BL 14	350	17.4152
BL 52	350	5.5691
BL 108	350	2.4769
BL 123	350	4.4293
Mean	350	4.5654

Table 16.

Gene flow (Nm) for natural populations of H. molitrix.

* Nm = Gene flow estimated from Fst = 0.25(1 - Fst)/Fst.

4.7.5 Clustering patterns

The UPGMA dendrogram was used to investigate genetic relatedness. There were two major clusters, or clades A and B, predicting the close relationship between these populations. Cluster A is divided into two sub-clusters: A1 and A2. Cluster A1 contained the riverine population of H. molitrix collected from KH, QH, and MH, while cluster A2 contained the population of CB. In cluster B, there was a population of TH (Figure 13).

Figure 13.

UPGMA dendograms based on Nei’s genetic distance showing the relationship and clustering patterns between natural populations of H. molitrix.

For the populations of H. molitrix, microsatellite data analyses by the STRUCTURE grouping algorithm method proposed the presence of two distinct genetic clusters. For each K value, constant results were obtained across the six autonomous runs. STRUCTURE HARVESTER admixture model inferences showed highest estimated log-likelihood mean value and delta-k value in this study. The two distinct colors of the column represent the estimated probability of belonging to two populations, and each vertical column represents one individual. Distinct colors in the same individual indicate the percentage of the genome shared with each cluster (Figure 14).

Figure 14.

Genetic structure patterns among populations of H. molitrix as revealed by structure analysis. The two distinct colors of column represent the estimated probability of belonging to two populations and each vertical column represents one individual. Distinct colors in the same individual indicate the percentage of the genome shared with each cluster.

5. Discussion

Fish that have been exposed to altered environmental conditions as a result of human activities. Overfishing, pollution, loss of habitat, climate change, and the introduction of nonnative species are all threatening freshwater fish biodiversity [1]. Aquaculture has played a significant role in increasing food production for human nutrition. Asia accounts for more than 91% of global aquaculture production [5]. Freshwater carps and cyprinids account for over 53.1% of total aquaculture fish production [6]. Many countries around the world have introduced silver carp (freshwater fish species) for biological control (algal blooms) and aquaculture [52].

Because the natural environment provides resources for all living communities, protecting the natural environment is critical for the conservation and preservation of living species. In comparison to historical data, the current rate of extinction of species is extremely high. Approximately 40% of commercial fisheries are on the verge of collapse due to lack of understanding of the genetic diversity [17]. Many populations have declined as a result of environmental contamination. The field of conservation biology is primarily concerned with the preservation of genetic diversity [11]. Humans are attempting to alter nearly every environment at an unprecedented rate, and they may now be the planet’s most powerful biotic selector [15]. The degradation of the environment in aquatic ecosystems is increasing, which could lead to a loss of diversity, as population sizes shrink and intolerant species become extinct [53].

We used microsatellite markers to examine the genetic variability of H. molitrix and evaluate the genetic structure of the populations in the region in order to offer good genetic data for effective management and conservation of the species. Because of the growing interest in and attention on Silver Carp culture in Pakistan, it is critical to study several genetic features of the fish. Genetic variety is essential for adapting to environmental changes and stock improvement initiatives. More heterozygous individuals are superior then less heterozygous individuals. All of the genetic criteria used in this investigation suggested that the wild population had higher levels of genetic diversity. The wild fish populations had the largest average number of alleles (Na), allelic richness (Ar), and effective number of alleles (Nae).

Genetic drift, natural selection, mutation, and gene flow are all factors that influence the allele frequency in a population. Allelic diversity (Na) and heterozygosity (Ho and He) are important for genetic variation, although Na is significantly more dependent on effective population size than heterozygosity [50]. As a result, Na is suitable for estimating genetic diversity in a population for selection, conservation, and enhancement programs [54].

In present work, the average number of alleles (Na) and allelic richness (Ar) in H. molitrix populations were measured as 5.60–9.00 and 5.51–5.94, respectively. The average values for an effective number of alleles (Nae) assessed varied from 2.9043 to maximum 4.7284. The highest value of Ne (6.7680) was found in a TH fish population, while the lowest (1.9647) was found in a KH population. The value of Ne was found to be lower than the Na, indicating that alleles are being lost in the populations, and it means that the frequencies of all alleles are not equal. The researchers [28] reported seven alleles in each locus on average and 1.04–4.72 average number effective alleles. The researchers [55] reported average number of allele as 9.2 at microsatellite loci in freshwater Silver Carp species. The results of this study were reinforced by the findings of Fang et al. (2021), who reported average number of alleles ranging from 4.19 to 6.526 in Silver Carp.

In all of the H. molitrix populations studied, the heterozygosity level ranged from moderate to high. In the populations, average values of observed heterozygosity (Ho) ranged from 0.4400 to 0.7257. The fish population from TH had the greatest Ho value, whereas the population from QH had the lowest, which may be due to small number of individuals, limited gene flow, and errors in reading alleles. The expected heterozygosity (He) average values in populations of H. molitrix ranged from 0.6361 to 0.7812. The fish population from TH had the greatest He value, whereas the population from KH had the lowest. Similarly, increased values of He can be attributable to the existence of null alleles at the loci studied, selection pressure on specific loci, or inbreeding when compared with Ho [56, 57]. 1-Ho/He averages were 0.0740, 0.0905, −0.0306, 0.7005, and − 0.0452. According to [22], mean Ho was between 0.625 and 0.727, and mean He was between 0.69 and 0.784 for Silver Carp. [55] found Ho and He values for Silver Carp ranging from 0.37 to 1.00 (average 0.74) and from 0.40 to 0.93 (average 0.76), respectively.

On an average, F_IS values were ranging from −0.067 to 0.365 in several H. molitrix populations examined in this study. The highest average F_IS value was found in the QH fish stock, while the lowest was found in the CB population. The value of F_IS ranged between 0 and 1. Zero value indicates that there is occurring neither inbreeding nor outbreeding, which means that the population is in Hardy-Weinberg expectation or mate randomly. If F_IS value is 1, it indicates the population is totally inbreeding and − 1 shows the population is totally outbreeding. A negative F_IS value indicated heterozygosity excess and suggested that this group does not lose heterozygosity, implying that individuals in this population are outbreed. Positive F_IS readings indicate a population’s homozygosity excess and significant divergence from the HWE [35].

Inbreeding, genetic drift, bottleneck effect, innate gene pool contamination by introgression, overexploitation, bio-invasion (introduction of exotic species), environmental pollution, habitat degradation, hydrological manipulations, and climate change are all factors that can cause a fish species’ genetic structure to change over time. The strength of natural and human involvements determines the pattern and severity of changes. Microsatellite markers have a high resolving power, allowing them to identify very low amounts of genetic alteration caused by the different variables [58, 59].

Geographic distance separating populations has likely attracted the most attention from an environmental perspective [2]. In this work, pairwise FST estimations revealed intermediate genetic differentiation in wild populations of H. molitrix. A low level of genetic differentiation is indicated by an FST value of 0–0.05. If FST is 0, it means there is no differentiation or structure; if it is 1, it means fully differentiated. The lower FST value suggested that populations were of similar genetic origin and had reduced genetic integrity. Second, its possible that it is owing to the exchange of brooders between different populations. The maximum level of genetic divergence showed that these groups were of divergent genetic origin, whereas the lowest level indicated that they were of close genetic origin [47]. Hypothetically, if Nm is less than 1, genetic drift is assumed to be the most important mechanism in genetic differentiation. Similarly, if Nm is greater than 1, gene flow is the most important component in genetic differentiation [60].

The unbiased genetic distance between pairs of populations showed a lot of variance in magnitude. The values of genetic identity were shown to be contradictory to those of genetic distance. A large genetic distance indicates that both populations have a dissimilar genetic background and vice versa [61].

AMOVA is an appropriate benchmark for assessing population genetic structure and determining genetic similarity and differentiation between populations [51]. The AMOVA revealed that the majority of variation in wild populations of H. molitrix occurs within individuals. Clustering patterns in populations represent relationships. The genetic relationship between populations with the highest levels of genetic identity will be the closest, while those with the lowest levels of genetic identity will have the furthest genetic relationship. The UPGMA dendrogram was used to study the genetic structural patterns among populations. A close genetic link had been discovered among groups in the same cluster.

Biodiversity conservation has become increasingly important in recent years. As the human population grows, habitat loss is causing numerous animal populations to decline and potentially become extinct. Genetic variety is essential for a species’ evolutionary survival. Genetic diversity levels can be maximized through effective management. Genetic monitoring programs for a fish population are necessary for an effective management approach. Molecular markers are effective tools for assessing and evaluating the genetic status of species. These markers can be used to manage pure stocks in the natural environment and to assist in the genetic conservation of H. molitrix species. The present data are important for considering its management and conservation. However, because there are wide regions of floodplains and river branches to design a good management policy, more research involving genetic analysis with more markers and population samples covering different wild sources throughout Pakistan is still needed.

6. Summary

The objective of the present research work entitled “Genetic assessment Silver Carp (H. molitrix) population in River Chenab as revealed by SSR markers” was to assess the levels of genetic diversity, population structure, and genetic differentiation among five different populations of River Chenab, Pakistan by using SSR markers. A total of 175 samples of H. molitrix were collected from five different sites of River Chenab, Pakistan. DNA was isolated by using the standard “proteinase-K and phenol/chloroform” method, by following Sambrook and Russell (2001) [43], having slight modifications and quantified with the help of agarose gel electrophoresis and nanodrop and separated on PAGE. Genomic DNA was PCR amplified by H. molitrix by using five primers. Data were analyzed by using different software including FSTAT, TFPGA, STRUCTURE, MICRO-CHECKER, POPGENE, and ARLEQUIN.

The analysis of data gave following results:

• The Micro-checker software was applied to the genotypic data obtained for H. molitrix populations that indicated no scoring errors related to large allele, no stuttering bands, and no null allele presence at all the loci employed for genotyping in this study. The average allele frequency and allele size ranged from 0.0036 to 0.574 and from 157 to 389 base pairs, respectively, were observed at various screened loci in H. molitrix populations in the present study.

• In current study, Na (the number of alleles) and Ar (allelic richness) per locus ranging from 3.00 to 9.00 with an average 2.943 to 8.940, respectively, were observed in various H. molitrix populations. Regarding number of alleles and allelic richness, the largest average value was noted in the population of CB and minimum in the population of MH. At locus BL 14, the highest value of Ar was found 8.911 in the population collected from MH. The average values of Na and Ar in the populations of TH, MH, KH, QH, and CB were observed as 5.8 (Ar = 5.79), 5.6 (Ar = 5.513), 5.8 (Ar = 5.753),), 5.8 (Ar = 5.754), and 6.0 (Ar = 5.942), respectively.

• The mean values of Nae (effective number of alleles) were observed ranging from 1.9647 to 6.7680 in various studied H. molitrix populations. The decreasing order of average value of Nae was observed as 4.728, 3.701, 2.993, 2.971, and 2.904 in TH, QH, CB, MH, and KH, respectively. The largest value of Nae was seen in TH population while the lowest in the KH population.

• In various examined H. molitrix populations, the average values of observed (Ho) and expected (He) heterozygosities were measured ranging from 0.440 to 0.726 and from 0.636 to 0.781. The decreasing order of average Ho value was observed as 0.726, 0.680, 0.634, 0.571, and 0.440 in TH, CB, KH, MH, and QH, respectively. Whereas the decreasing order of average He value was detected as 0.781, 0.701, 0.653, 0.646, and 0.636 in TH, QH, CB, MH, and KH, respectively.

• The values of 1-Ho/He were found positive mostly at all the screened SSR loci with exception at some loci where negative values were also observed in this study (Tables 6–10). On the average base, populations showed positive values for 1-Ho/He except two populations, i.e., CB and KH. The mean values of 1-Ho/He in TH, MH, KH, QH, and CB were observed as 0.074, 0.091, −0.306, 0.366, and − 0.0452, respectively.

• On average, the inbreeding coefficient (FIS) values were found to be positive in all the studied stocks of H. molitrix except two populations, i.e., CB and KH that showed negative mean values in the present study. FIS values ranged from −0.129 to 0.0074 recorded at various screened SSR loci in the examined H. molitrix populations. Highest average F_IS value was measured for QH (0.365) while the lowest for CB (−0.067). The mean values of FIS in TH, MH, and KH were observed as 0.040, 0.104, and − 0.048, respectively

• Out of 25 tests, a total of four tests were found to deviate from HWE significantly after applying multiple test correction. At various screened loci, the pairwise p value was found significant at p < 0.05 in examined H. molitrix populations.

• Pairwise population differentiation FST across all the screened microsatellite loci among various examined H. molitrix populations was found to be statistically significant (P < 0.05). In this study, the highest amount of differentiation was discovered in the TH-KH population at 0.1033, while the lowest level of differentiation was identified in the MK-QH groups at 0.0120.

• In the present study, the unbiased genetic distance among pairs of populations indicated considerable variation (P < 0.05) in magnitude. The highest value of genetic distance was noted 0.2943 in TH-KH while, the minimum 0.0289 between the MH-QH. Similarly, maximum value of genetic identity was observed 0.9715 between QH-MH and lowest 0.7451 in TH-KH.

• The graphical comparison of genetic distance and geographical distance in various observed H. molitrix populations showed positive association. As the geographical distance increased, the genetic distance in various riverine populations was also seen to be increased. Similarly, the graphical comparison in geographical distance and genetic identity and genetic distance and genetic identity showed negative association. As the genetic distance increased, the genetic identity among populations was seen to be decreased.

• The AMOVA indicated low variation percentage (7.81141%) between individuals within populations and revealed that most of the variation (87.05210%) lies within the individuals. The AMOVA further specified that 5.13648% variation was contributed due to the variation between natural populations of H. molitrix in this study.

• In the current study, across all the screened microsatellite loci, the gene flow (Nm) rate in various examined populations of H. molitrix was measured by using the windows-based program POPGENE. The largest value of Nm was observed 17.4152 at locus BL 14 while the lowest value of Nm was noted 2.4769 at locus BL 108. Over the all SSR loci, the average value of Nm was observed as 4.5654.

• Genetic relatedness was further investigated by constructing UPGMA dendrogram. Two major clusters or clades A and B were observed, which predict that the populations in both clusters had shown a close relationship. Cluster A was divided further into A1 and A2. A1 was further clustered in two groups containing KH, QH, and MH, whereas A2 consisted of CB. Cluster B further divided into cluster B1 and B2. The riverine population of H. molitrix TH was present in cluster B.

So far, no research on microsatellites in this species has been reported in Pakistan. The primary goals of this work were to use latest molecular techniques to monitor the genetic status of H. molitrix in the River Chenab and develop strategies for successful management and protection of this vital fish resource.