Microsatellite Markers Used for Genetic Monitoring of Exotic Common Carp Variants (Common Carp and Scale Carp) in the River Chenab, Punjab, Pakistan

Fouzia Tabassum1,2, Muhammad Farhan Khan3, Muhammad Tayyab4, Shakeela Parveen2*, Muhammad Hussain5, Uzma Batool2, Areeba Safdar6 and Laiba Shafique1*

1Guangxi Key Laboratory of Beibu Gulf Marine Biodiversity Conservation, Beibu Gulf University, Guangxi 535011, PR China

2Department of Zoology, Government Sadiq College Women University, Bahawalpur, 63100, Punjab, Pakistan

3Department of Chemistry, Gomal University, Dera Ismail Khan 29050, Pakistan

4Department of Zoology, Wildlife & Fisheries, University of Agriculture, Faisalabad 38000, Punjab, Pakistan

5Department of Veterinary Sciences, University of Veterinary and animal sciences, Lahore, Pakistan

6Department of Zoology, Bahauddin Zakariya University, Multan

Fouzia Tabassum and Muhammad Farhan Khan made equal contributions.

ABSTRACT

Understanding the genetic composition and diversity of invasive species is crucial for the effective management and conservation of native wildlife. In this study, 300 samples of common carp (Cyprinus carpio linnaeus) and scale carp (Cyprinus carpio communis) from five natural populations in the Chenab River, Pakistan, were collected for genotyping and 10 microsatellite markers were used. The analysis revealed that both strains exhibited low to moderate levels of heterozygosity. The average FIS values for common carp ranged from 0.507 to 0.5914, while scale carp showed values ranging from 0.53 to 0.62. FST analysis indicated minimal genetic differentiation between the strains, with the greatest genetic differences observed between strains and the least within individual strain populations. According to AMOVA, 90.38% of the genetic variance in common carp was attributed to intra-population variability, while inter-population variability accounted for 9.62%. Conversely, in scale carp, intra-population variability contributed to 12.92% of the total genetic variance, with 87.08% attributed to inter-population diversity. Bayesian clustering analysis identified 10 distinct groups among the populations of both strains, with no genetic evidence of admixture found in the pure, original strains. The high observed heterozygosity compared to expected heterozygosity in common carp populations suggest the possibility of a bottleneck event. The directed relative migration network highlighted HT (common carp) as the core population, showing the highest genetic exchange with the other five peripheral populations. In contrast, except for the scale carp population in Head Khanki, no significant migration was observed in the other populations. A dendrogram constructed using the Unweighted Pair Group Method with Averages (UPGMA) distinguished common carp and scale carp as two separate groups. This study provides valuable insights that could enhance the management strategies for invasive species.

Article Information

Received 05 October 2024

Revised 25 October 2024

Accepted 03 November 2024

Available online 26 February 2026

(early access)

Published 25 May 2026

Authors’ Contribution

SP and LS design the study. FT and MFK wrote the manuscript text. FT, UB and MT analyzed the data. FT, MH and AS prepared figures. FT and MFK prepared the tables.

Key words

Genetic structure, Exotic species, Scale carp, Common carp, Genetic diversity, Heterozygosity

DOI: https://dx.doi.org/10.17582/journal.pjz/20241005051145

* Corresponding author: [email protected], [email protected]

0030-9923/2026/0004-1785 $ 9.00/0

Copyright 2026 by the authors. Licensee Zoological Society of Pakistan.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

INTRODUCTION

In freshwater conditions and aquaculture systems across Pakistan, the species Cyprinus carpio, sometimes referred to as the European or common carp, and its variation, Cyprinus carpio communis, are extensively distributed (Yaqoob, 2021). The native fish population has been steadily declining as a result of the introduction of foreign strains of common carp (Kang et al., 2023; Kovalenko et al., 2021). Originally found only in Central Asia and a few European countries, the common carp is now found on every continent with the exception of Antarctica and Northern Asia. As of right now, it may be found spreading from Siberia to the Mediterranean in Southeast Asia, China, India, and Pakistan (Nakajima et al., 2019; Souza et al. 2022). In order to increase fish output in a variety of aquatic environments, including ponds, tanks, lakes, and reservoirs, common carp and scale carp were introduced to Pakistan using composite fish farming techniques. Although the recipient ecosystems may suffer from the introduction of non-native fish species, there may be significant economic benefits as well (Bilal and Khan, 2003). Additionally, carps developed themselves in Punjab, Pakistan’s riverine system, bolstering a robust commercial fisheries operation.The organism’s invasive characteristics such as its quick growth rate, strong reproductive potential, early sexual maturity, and tolerance to different food sources are primarily responsible for its success in a variety of environments (Khan et al., 2021; Hayat et al., 2020). On the other hand, the reduction of native fish species in these rivers may be caused by the introduction of carp into riverine system of Punjab, Pakistan (Imran et al., 2021a; Parveen et al. 2018). The introduction of a certain species has a clear correlation with the continued reduction of many fish species in the fauna (Barletta et al., 2010).

Because of the way carp eat in benthic habitats, sediments are disturbed, nutrients are released, and water turbidity is subsequently raised (Mutethya and Yongo, 2021). Some fish species capacity to forage is therefore restricted by elevated turbidity. Furthermore, carp may interfere with other fish species’ ability to reproduce as well as compete for resources like food and habitat (Imran et al., 2021b). Because of factors like competition, hybridization, predation, and indirect effects; the introduction of non-native species frequently causes the number of native species in an environment to decrease (Chen et al., 2023; Erarto and Getahun, 2020). Because common carp strains seriously disturb aquatic populations and the environment, they are regarded as nuisance fish in many western nations (Sorensen, 2021; Yaqoob, 2021; Mutethya and Yongo, 2021). The most significant threat to the variety of plant and animal species in the ecosystems of shallow lakes and wetlands in the United States is generally acknowledged to be the common carp (Pearson et al., 2019). Fish species in Pakistan’s natural reservoirs have declined substantially in recent years as a result of pollution, illicit fishing, natural catastrophes, habitat degradation, and the introduction of non-native species (Abro et al., 2020; Parveen et al., 2024).

Unintentional risks from exotic species on native fauna might result from fisheries management that ignores genetic diversity and population dynamics (Pyšek et al., 2020). There is a dearth of research on the genetic diversity patterns of exotic species, despite the vast study of invasion mechanisms. Initiating management initiatives to address their genetic diversity is crucial. An efficient way to evaluate the biodiversity of invasive species is through the use of microsatellite-based markers (Fazzi-Gomes et al., 2021; Pandolfi et al., 2021). The genetic variability of common carp has been extensively examined in the literature using microsatellite markers (Yick et al., 2021). Because of its impartiality in sample selection and the simplicity with which results derived from them may be cross-validated and compared across other populations, microsatellites are unique in the field of population research (Guo et al., 2022). Reducing and maintaining the quantity of scale carp and common carp below ecological thresholds might be important to enhance the quality of the water and boost the population of local fish species.

It has long been acknowledged that determining the fine-scale genetic structure is essential to developing policies for managing freshwater fisheries. We investigate the patterns of genetic diversity in populations of exotic common carp and scale carp in Punjab, Pakistan’s River Chenab. Using microsatellite markers, our study investigates the organization and genetic diversity of the scale carp and common carp strains in the River Chenab and also analyzes the population structure of both represented species which play a crucial role in effectively controlling these strains within river ecosystems. Policies for the sustainable management of alien species’ fisheries will benefit from this genetic data.

MATERIALS AND METHODS

Collecting samples and DNA extraction

Five sample locations (Head Muhammad Wala, Head Qadir abad, Head Khanki, Head Marala and Head Trimmu) along the River Chenab yielded a total of 150 specimens of all strains of carps (scale carp and common carp) (Fig. 1, Table I). Out of the five sample locations, thirty specimens of every carp strain were gathered, for a total of 150 specimens per strain. With a few minor adjustments, a typical phenol: chloroform technique was used to isolate genomic DNA (Ghatak et al., 2013). We used 1% agarose gel electrophoresis to evaluate the integrity of the DNA. Additionally, we used the Thermo Scientific, US NanoDrop 2000c spectrophotometer to measure the concentration and purity of the DNA. After being separated, the DNA was diluted to a final concentration of around 50 ng/μL and kept cold until the PCR amplification process.

 

Table I. Details of sampling sites.

Site code	City of sampling site	Sampling point	Geographic location	Date of capture	Sample size
Common carp
HT	Jhang	Head Trimmu	31°8'41.23"N, 72°8'46.38"E	11/11/2021	30
HM	Sialkot	Head Marala	32°40'20.64"N, 74°27'51.8"E	21/12/2021	30
HK	Gujranwala	Head Khanki	32°24'09.65” N, 73°58'14.30” E	5/1/2022	30
HQ	Hafizabad	Head Qadirabad	32°19'60" N, 73°43'60" E	13/01/2022	30
HMW	Muzzafargarh	Head M. Wala	30° 18' 2N, 71° 20' 42E	3/2/2022	30
Scale carp
HT	Jhang	Head Trimmu	31°8'41.23"N, 72°8'46.38"E	11/11/2021	30
HM	Sialkot	Head Marala	32°40'20.64"N, 74°27'51.8"E	21/12/2021	30
HK	Gujranwala	Head Khanki	32°24'09.65” N, 73°58'14.30” E	5/1/2022	30
HQ	Hafizabad	Head Qadirabad	32°19'60" N, 73°43'60" E	13/01/2022	30
HMW	Muzzafargarh	Head M. Wala	30° 18' 2N, 71° 20' 42E	3/2/2022	30

 

Table II. Characteristics of common carp specific microsatellite loci.

S. No.	Locus no.	Primer sequence 5`→3`	Fragment size	Annealing temperature	Allele no.
1	AMFW3	F:GATCAGAAGGTACAGAGAAG R:CCTTACAGAAAACCTGTTTGC	134-240	58	7
2	AMFW4	F:TCCAAGTCAGTTTAATCACCG R:GGGAAGCGTTGACAACAAGC	138-253	59	5
3	AMFW6	F:ACCTGATCAATCCCTGGCTC R:TTGGGACTTTTAAATCACGTTG	158-212	60	5
4	AMFW7	F:GATCTGCAAGCATATCTGTCG R:ATCTGAACCTGCAGCTCCTC	132-152	59	7
5	AMFW11	F:GCATTTGCCTTGATGGTTGTG R:TCGTCTGGTTTAGAGTGCTGC	110-196	60	5
6	AMFW13	F:ATGATGAGAACATTGTTTACAG R:TGAGAGAACAATGTGGATGAC	192-270	58	7
7	AMFW15	F:CTCCTGTTTTGTTTTGTGAAA R:GTTCACAAGGTCATTTCCAGC	159-283	59	5
8	AMFW17	F:CAGTGAGACGATTACCTTGG R:GTGAGCAGCCCACATTGAAC	254-312	60	6
9	AMFW26	F:CCCTGAGATAGAAACCACTG R:CACCATGCTTGGATGCAAAAG	151-221	60	7
10	AMFW31	F:CCTTCCTCTGGCCATTCTCAC R:TACATCGCAGAGAATTCGTAAG	283-305	60	3

 

A= Crooijmans et al. (1997); F, forward; R, reverse.

 

Genotyping of microsatellite loci

Using 10 species-specific primers and a gradient heat cycler (Cycler-25, CA.95070, USA), the target microsatellite loci were amplified. MFW3, MFW4, MFW6, MFW7, MFW11, MFW13, MFW15, MFW17, MFW26, and MFW31 are the primers that were identified from two common carp strains (Tóth et al., 2019). Additionally, these loci have been investigated for cross-species amplification in common carp and scale carp. The following is a summary of the specifics for all loci, including fragment sizes, primer-specific annealing and primer sequences demonstrated in the Table II.

 

In the PCR cycle, double-stranded DNA is denaturized at 94°C after Taq polymerase activation takes place at 95°C during incubation. At 72°C, primers anneal, and eventually the cycle; DNA strand elongation carries out. 8% polyacrylamide gel electrophoresis (PAGE), which enables the detection of DNA bands of anticipated fragment sizes, was used for the analysis of amplicons. The information required for statistical analysis is provided by these bands. To act as a size marker for the amplicons, 3 µl of a sequence ladder was put into the center region of the gel. In addition, 5 µl of the PCR product from each sample was loaded in separate wells together with 1 µl of the loading dye, bromophenol blue. Following that, the PCR products underwent washing and were stained with silver. The gel was shaken continuously for 8–10 min with silver stain to visualize the PCR products. After that, gel findings were shown using a UV transilluminator (Sambrook et al., 1989).

Genetic diversity

The following summary statistics were used to quantify genetic variation: expected heterozygosity (He), observed heterozygosity (Ho), allelic richness (Ar), average number of alleles, and within-strain inbreeding coefficient (FIS). These statistics and the corresponding 95% confidence intervals for the statistical analysis were generated using the software programs GenAlEx 6.41, FSTAT v.2.9.3.2, and POPGENE 1.32.

Population structure

Using the FSTAT program version 5, the pairwise genetic differences between strains were calculated in accordance with the normal protocols outlined in the product instructions (García-Ramos and Kirkpatrick 1997). Nei’s genetic distance approach was used to produce a genetic distance-based tree, which was then used to create the dendrogram (Nei, 1978) in the TFPGA software. The purpose of this investigation was to investigate the links between the two strains various populations. Using Arlequin 3.5.2.2, Analysis of Molecular Variance (AMOVA) was used to evaluate the genetic structural patterns in both carps strain populations, with a particular emphasis on allele frequencies in microsatellite data. To determine each pairwise comparison in order to achieve statistical significance, a thousand random permutations were carried out.

The Bayesian approach presented in structure 2.3.4 was used to evaluate the genetic structures between strains. An admixture model with associated allele frequencies was used in the investigation. One million Markov Chain Monte Carlo (MCMC) repeats followed a burn-in phase of 100,000 iterations. For every K value between 1 and 10, which denotes the number of clusters, 10 separate runs were carried out in order to guarantee consistency and detect genetic clusters. One cluster was added to all strains for purpose to find the maximum number of clusters, which made it possible to identify possible substructures in the data. By utilizing Structure Harvester’s Evanno approach to calculate ΔK, the ideal K genetic cluster was evaluated. The program CLUMPP 1.1.2 was then used to provide visual representations of the clustering findings and to evaluate greatest similarity coefficient for different values of K over several runs.

Bottleneck analysis

The two-phase model (TPM) was applied, containing 1000 replications and 90% single-step mutations (Yang et al., 2022) was used with the Bottleneck v1.2.02 program to determine if populations of common carp had undergone bottlenecks recently. To assess bottleneck effects in each population of common carp strains, the mode shift test was also performed.

Gene flow analysis

In order to investigate patterns of gene flow among the populations, relative migration rates were evaluated using the GST statistic technique (Nei, 1973). The divMigrate-online program (Sundqvist et al., 2016), available at https://popgen.shinyapps.io/divMigrate-online/, was used to perform this study. Additionally, 1000 bootstrap iterations were used to infer asymmetric relationships between population pairs.

RESULTS

Genetic diversity

Ten microsatellite loci unique to each species of both represented species; common carp and scale carp were used to analyze five populations of each strain: MFW3, MFW4, MFW6, MFW7, MFW11, MFW13, MFW15, MFW17, MFW26, and MFW31. It was discovered that every locus under analysis was polymorphic and exhibited Mendelian inheritance patterns. There were on average between 3.8 and 6.0 alleles per locus. Each strain’s five populations showed different quantities of alleles at each locus, indicating that each population’s origins were different. The highest average allelic richness (Ar) value for common carp was found in the HT (Head Trimmu). The highest average Ar value for scale carp was discovered in both HT (Head Trimmu) and HK (Head Khanki). The strain with the lowest average Ar value was identified as HMW (Head Muhammad Wala) in both cases. Geographic differences among all the populations are indicated by the variances in average allelic richness (Ar) values. Low to moderate levels of heterozygosity were seen. The average observed heterozygosity (Ho) for common carp varied from 0.3167 to 0.443. In HQ, the lowest average value of Ho was discovered (Head Qadirabad). The highest average Ho value for common carp was discovered in HT (Head Trimmu). These Ho values show that HT had the highest average amount of genetic diversity among all common carp populations, whereas HQ (Head Qadirabad) had the lowest average level. The average observed values of Ho for scale carp varied from 0.3067 to 0.4067. HMW (Head Muhammad Wala) had the lowest genetic diversity among the five populations of scale carp, while HT had the highest genetic diversity. For both strains, the highest average value of Ho was discovered in HT. For every locus across all populations, the Ho in both strains was less than the corresponding predicted heterozygosity (He). For any population in either strain, there were no negative Ho/He values found. Both strains exhibit substantial levels of polymorphism at the MFW3 and MFW15 loci, suggesting that these loci have a major role in the total amount of genetic variation found. In contrast, both strains exhibit the least amount of variation at the chromosomal locus MFW31. Using FSTAT software, the study computed the very locus in every population as well as every sample within every population had its FIS population inbreeding coefficient determined. Findings show that various populations’ average FIS levels vary. The average observed FIS values for common carp varied from 0.507 to 0.5914. Head Qadir Abad (HQ) had the highest average FIS value, while Head Trimmu (HT) had the lowest. The FIS averages for scale carp varied from 0.5310 to 0.6166. Supplementary Table S1 showed that HM (Head Marala) had the lowest average value of FIS and HMW (Head Muhammad Wala) had the highest average value.

Population genetic structure

The allelic data were analyzed using pairwise comparisons of each population to ascertain the genetic composition of the common carp and scale carp populations. Significant genetic difference between groups was shown by statistically significant results from several of these comparisons. Significant variation across all analyzed groups is indicated by the FST values. The 10 populations average FST values vary from 0.0471 to 0.173. In particular, the FST value of 0.173 showed complete isolation and no genetic material transfer between the two scale carp populations (HK and HMW). Conversely, a higher degree of genetic similarity between the common carp populations HT and HK indicated by the lowest FST value of 0.047 (Table III).

 

Table III. Pairwise measures of population differentiation (Garcia-Ramos et al.) below diagonal between populations of common carp and scale carp.

Populations	Populations
	HT	HM	HK	HQ	HMW
Common carp
HT	--
HM	0.065	---
HK	0.047*	0.074	---
HQ	0.068	0.108	0.114	---
HMW	0.100	0.155	0.139	0.089	---
Scale carp
HT	---
HM	0.077	---
HK	0.128	0.111	---
HQ	0.141	0.128	0.132	---
HMW	0.142	0.140	0.173	0.116	---

 

HT, Head Trimmu; HM, Head Marala; HK, Head Khanki; HQ, Head Qadir Abad; HMW, Head Mohammad Wala

 

Genetic distance

The following measures were taken of the pairwise genetic identities and distances among all sample points as demonstrated in Table III. The population genetic identity values for the comparisons are as follows: HT against HK: 0.7739), HT vs HQ: 0.7235, HT vs HMW: 0.6551, HT vs HM: 0.7061). The genetic identity (similarity) between the HT population and each of the HM, HK, HQ, and HMW populations is shown by these values. For the aforementioned pairings, the genetic distances are: HT vs HK= 0.2563; HT vs HM= 0.3480; HT vs HQ= 0.3237; HT vs HMW= 0.4230, respectively. The genetic differences between each of the HM, HK, HQ, and HMW populations and the HT population are represented by these values. Greater genetic divergence is indicated by higher genetic distance values, whereas lower genetic distance values implied closer genetic resemblance. The values of genetic distance and population genetic identity for the designated pairs of scale carp are as follows: (HT vs HM = 0.6970); (HT vs HK = 0.5294); (HT vs HQ= 0.4837); ( HT vs HMW= 0.4971); (HT vs HM= 0.3610); (HT vs HK= 0.6359); (HT vs HQ= 0.7263); (HT vs HMW= 0.6990), within scale carp, these numbers represent the genetic distance (distance) and genetic similarity (identity) between the HT population and each of the HM, HK, HQ, and HMW populations as shown in the Table IV.

 

Table IV. Genetic distance and identity between populations of common carp and scale carp.

Populations compared	Biased		Unbiased
	Dist.	Ident.	Dist.	Ident.
Common carp
HT vs. HM	0.3480	0.7061	0.3186	0.7272
HT vs. HK	0.2563	0.7739	0.2269	0.7970
HT vs. HQ	0.3237	0.7235	0.2960	0.7438
HT vs. HMW	0.4230	0.6551	0.3976	0.6719
HM vs. HK	0.3518	0.7034	0.3261	0.7217
HM vs. HQ	0.4985	0.6074	0.4747	0.6221
HM vs. HMW	0.7165	0.4884	0.6950	0.4991
HK vs. HQ	0.5303	0.5885	0.5064	0.6027
HK vs. HMW	0.5998	0.5489	0.5783	0.5609
HQ vs. HMW	0.3096	0.7337	0.2899	0.7483
Scale carp
HT vs. HM	0.3610	0.6970	0.3356	0.7149
HT vs. HK	0.6359	0.5294	0.6120	0.5423
HT vs. HQ	0.7263	0.4837	0.7020	0.4956
HT vs. HMW	0.6990	0.4971	0.6757	0.5088
HM vs. HK	0.4802	0.6186	0.4579	0.6326
HM vs. HQ	0.5785	0.5607	0.5560	0.6735
HM vs. HMW	0.6347	0.5301	0.6131	0.5417
HK vs. HQ	0.5504	0.5767	0.5292	0.5891
HK vs. HMW	0.8116	0.4442	0.7913	0.4532
HQ vs. HMW	0.4554	0.6342	0.4349	0.6473

 

See Table III for abbreviation.

 

Hierarchal AMOVA analysis

Molecular variance analysis was performed with ARLEQUIN software (version 2.000) to assess overall population diversity. 90.38% of the variants in the species common carp were found inside populations, showing a high level of intra-population variety. On the other hand, 9.62% of the changes found were explained by inter-population variability. Within population diversity in common carp accounted for 12.92% of the observed differences, but inter-population diversity explained 87.08% of the variances, as reported in Table V.

 

Table V. Hierarchal AMOVA analysis of common carp and scale carp populations.

Strains	Source of variation	Sum of squares	Variance components	Percentage of variation
Common carp	Among populations	111.223	0.4007	9.62
	Within populations	1110.4	3.7641	90.38
	Total	1221.62	4.1647
Scale carp	Among populations	146.453	0.5486	12.92
	Within populations	1090.6	3.697	87.08
	Total	1237.05	4.2456

 

UPGMA dendrogram

A UPGMA dendrogram created with TFPGA software was used to evaluate the genetic links between each group, taking into account Nei’s Genetic Distance (1972). This investigation revealed that both strains showed the segregation of three separate populations: HT, HM, and HK, in contrast to the other two populations, HQ and HMW. Two main clusters, each with two sub-clusters, are shown forming in the graphic. Individuals HT and HK of the species common carp are isolated from HM in the first cluster. On the other hand, HM and HT separated from HK in the first cluster in the subspecies scale carp, as depicted in Figure 2.

 

Linkage disequilibrium

Using chi-square software, we calculated linkage disequilibrium (LD) among all loci using Fisher’s exact test. The loci (MFW3, MFW6); (MFW4, MFW7); (MFW3, MFW11); (MFW7, MFW11); (MFW3, MFW13); (MFW6, MFW15); (MFW13, MFW15); (MFW15, MFW17); and (MFW11, MFW26) showed significant non-random associations of alleles and genetic drift, as indicated by their non-significant results, according to the LD analysis.

 

Structure-based analyses

The two strains are kept in a pure condition, and their different populations HM in common carp, HK in common carp, HMW in common carp, HT in scale carp, HM in scale carp, and HMW in scale carp showed genetic diversity in their development, according to the results of the Structure analysis (Fig. 3A-D). It is commonly known that heterozygous advantage is necessary for the maintenance of stable polymorphism. Four populations of common carp (HT in common carp; HQ in common carp; HK in scale carp; and HQ in scale carp) have shown genetic evidence of mixing. Although successful breeding programs can improve this state of affairs, they must be carefully considered because of the possibility of uncontrolled interbreeding (Fig. 3A-D).

Bottleneck analysis

The two-phase model (TPM) with a 90% single-step mutation rate and the mode shift test, which was established by Ye et al. (2022), were used in the study to evaluate possible recent bottlenecks in populations of common carp and scale carp strains. Over 1000 replications were also undertaken (Table VI). A possible bottleneck event may have occurred in some populations of common carp strains, as indicated by the notable difference between observed and anticipated heterozygosity. To be more precise, all 10 of the loci that were examined showed heterozygosity excess in the common carp populations, HQ common carp and HMW common carp, and no locus showed heterozygosity deficit. The two-phase mutation hypothesis explained these observations. By using the Wilcoxon test, it was found that in non-bottlenecked, equilibrium populations, the observed ratio of 9:1 substantially differed from the predicted ratio of 1:1. For the HQ common carp population,

 

Table VI. Heterozygosity excess under two-phase mutation model at ten microsatellite loci in each population of common carp strains.

Species	Populations	Sign test		Wilcoxon test
		Hex/Hd	P	P (One tail for Hex)
Common carp	HT	5/5	0.43	0.931
	HM	6/4	0.41	0.923
	HK	7/3	0.35	0.834
	HQ	9/1	0.34	0.055
	HMW	8/2	0.32	0.069
Scale carp	HT	5/5	0.42	0.542
	HM	6/4	0.28	0.451
	HK	7/3	0.26	0.067
	HQ	8/2	0.21	0.038
	HMW	9/1	0.16	0.037

 

P, probability; Hex, Heterozygosity excess; Hd, Heterozygosity deficiency. See, Table III for abbreviation.

 

Table VII. Directional relative migration network of the studied common carp strains populations constructed with divMigrate.

Strains	Pops	Common carp					Scale carp
		HT	HM	HK	HQ	HMW	HT	HM	HK	HQ	HMW
Common carp	HT	0	0.368	0.32	0.243	0.117	0.074	0.062	0.105	0.042	0.04
	HM	0.799	0	0.347	0.181	0.113	0.07	0.055	0.059	0.039	0.031
	HK	1	0.552	0	0.193	0.12	0.061	0.051	0.102	0.054	0.045
	HQ	0.704	0.331	0.221	0	0.302	0.05	0.064	0.079	0.082	0.065
	HMW	0.863	0.248	0.336*	0.64	0	0.061	0.068	0.09	0.061	0.05
Scale carp	HT	0.091	0.058	0.057	0.044	0.037	0	0.426	0.139	0.134	0.13
	HM	0.117	0.09	0.049	0.078	0.054	0.392	0	0.235	0.177	0.14
	HK	0.258	0.097	0.129	0.104	0.067	0.212	0.214	0	0.226	0.178
	HQ	0.116	0.063	0.056	0.104	0.056	0.129	0.161	0.178	0	0.249
	HMW	0.081	0.064	0.057	0.076	0.069	0.18	0.178	0.101	0.328	0

 

See Table III for abbreviation.

 

the sign test produced a p-value of 0.34 and the one-tailed Wilcoxon test for heterozygosity excess (Hex) produced a p-value of 0.055. For the HMW scale carp population, the sign test produced a p-value of 0.16 and the one-tailed Wilcoxon test for heterozygosity excess (Hex) produced a p-value of 0.037. The HM common carp and HK scale carp populations records, on the other hand, did not exhibit a statistically significant increase of heterozygosity. The sign test produced p-values of 0.26 for HK common carp and 0.41 for HM scale carp. Moreover, HM common carp and HK scale carp yielded p-values of 0.923 and 0.067, respectively, from the one-tailed Wilcoxon test used to evaluate heterozygosity. These results imply that there could have been a bottleneck among the populations under consideration, albeit the data only sporadically support the importance of this conclusion. The Hex/Hd ratio of 5/5 indicates that there was no statistically significant excess of heterozygosity in the datasets derived from HT populations of strains.

Directional relative migration network

The directed relative migration network analysis among the populations of common carp strains tested indicated that the HT (common carp) population acted as the core population and showed considerable genetic exchange with six periphery populations (Supplementary Fig. S1). These peripheral populations are connected to the HQ, HMW, HM, and HK areas. There was little genetic exchange between the groups designated as HK common carp; HM common carp; HMW common carp; HMW scale carp; HQA scale carp; and HK scale carp and the core population. It is believed that the two strains of carps which are common carp and scale carp, came from different parts of the world. 10 populations in total (five for each strain) were examined in order to determine the directional relative migration network. Every population was recognized as a wild population. According to the research, there was the greatest relative migration value from HMW scale carp to HT common carp, and the lowest relative migration from HMW scale carp to HM common carp (0.08) (Table VII).

DISCUSSION

It is vitally important to comprehend the migration patterns, population structure and genetic diversity of invasive species in order to prevent their spread. The objective of this study was to examine the genetic variability and population composition of rare varieties of represented species common carp and scale carp in River Chenab of Punjab Pakistan. The recent study found that there were 3 to 8 alleles per locus. Five populations of all strains factually had varying numbers of alleles at all loci suggests that the populations came from distinct sources. The variances in Ar values across all groups show disparities in geography. The HT population of common carp had the highest average Ar value. The populations from HT and HK had the highest average Ar value for scale carp. The HMW population in both strains had the lowest average Ar value. This indicates that as there is a dearth of space and mating partners, HMW has relatively low genetic diversity for strains of common carp.

Genetic diversity

The heterozygosity levels, which varied from low to moderate, were evaluated. We found that (Tóth et al., 2020), the observed heterozygosity of common carp strains was comparatively low. For common carp, the estimated values of heterozygosity varied from 0.3167 to 0.443, while for scale carp, they ranged from 0.3067 to 0.4067. On the other hand, (Napora-Rutkowski et al., 2017) the estimated value of heterozygosity, which varied from 0.418 to 0.781, was reported with somewhat higher values. In comparison to predicted heterozygosity (He), the study observed heterozygosity (Ho) results were somewhat lower. The genetic diversity of the populations under investigation was lowest in the HQ and HMW strains of common carp and scale carp, and highest in the HT strains. Every one of the 10 microsatellite loci showed polymorphism across the groups; MFW 3 and MFW 15 had significant genetic variation, whereas MFW 31 showed the least amount of polymorphism in both strains. The study used FSTAT software to determine the FIS population inbreeding coefficient for every locus in each population. The obtained values were recorded, exposing variations in average FIS values throughout populations (Napora-Rutkowski et al., 2017; Tóth et al., 2020) according to the theory behind the inbreeding coefficient, a large number of fish strains have an excess of heterozygotes, which predicts a decreased risk of inbreeding depression. Low to moderate heterozygosity levels in the study; might be the result of restricted allele variety and a potentially small sample size; prior research indicates that around 25–30 individuals per community are required for reliable estimations of genetic diversity derived from microsatellite data (Hale et al., 2012). Previous studies has demonstrated that there are very slight advantages to expanding the sample size in these types of studies with regard to projected heterozygosity and allele frequency (Sánchez-Montes et al., 2017). Ultimately, the primary objective is to precisely estimate the frequency and diversity of alleles; identifying every allele is not as important as identifying relevant information since rare alleles could not have a substantial impact on the assessment of population genetic diversity or structure. The average FIS values for common carp varied from 0.507 to 0.5914, with the greatest FIS values seen in the HQ, HMW, HK, HM, and HT populations, in that order. The average FIS values in scale carp were found to vary from 0.5310 to 0.6166, with the HMW population displaying the greatest FIS, followed by the HQ, HK, HM, and HT populations, following this order. The populations with the highest FIS scores indicated unfavorable environmental circumstances, which included things like low levels of nutrients and minerals, poor soil texture, and deteriorated water quality. These high FIS values also suggested fewer brooders and less-than-ideal management techniques.

Population structure

Each population pairwise, the study investigated genetic difference within populations. Significant variation across all populations is indicated by the FST values. Our results are in line with previous studies that found little genetic difference across several common carp strains in the Czech Republic (Tóth et al., 2020; mean Fst = 0.183) and France (Napora-Rutkowski et al., 2017; mean Fst = 0.250). Numerous reasons, like small number of strains were examined, the existence of null alleles, or genotyping mistakes, might be the cause of the low FST values. It is essential to acknowledge that these variables may impact the uniqueness of the strains that were sampled (Napora-Rutkowski et al., 2017). The five populations’ average FST values range from 0.0471 to 0.173. Significant isolation and restricted gene flow between populations HK and HMW are indicated by a high FST score of 0.173. Conversely, populations HT and HK have a lower FST value of 0.047, which indicates a tighter genetic link between these two groups. In light of these observations (Tóth et al., 2020) Based on allelic frequency data, we calculated genetic distance (D) across all populations using POPGENE software. In common carp, populations HT and HMW had the greatest genetic difference (D = 0.4230), whereas populations HT and HK had the shortest genetic distance (D = 0.1919). The populations of HT and HQA in scale carp showed the greatest genetic difference (D = 0.7263), whereas the populations of HT and HM showed the least genetic distance (D= 0.3610) (Tóth et al., 2019), Arlequin (version 2.000) software was used to conduct an analysis of molecular variance (AMOVA) and undertake other analysis. Higher levels of variation within populations and smaller levels of variation across populations were seen in both strains. These outcomes agree with the conclusions of earlier research (Napora-Rutkowski et al., 2017), who noticed a comparable pattern of variation between populations in Polish-bred strains of common carp. Most loci revealed deviations from linkage disequilibrium (LD), although several loci yielded noteworthy findings (Xu et al., 2019) looked at seven fish populations with sufficient sample sizes to investigate linkage disequilibrium (LD). As the distance between populations grew, the LD patterns changed. The study investigated genetic differentiation among seven fish populations, observing varying patterns of linkage disequilibrium influenced by geographical distances between populations. According to a previous study (Ye et al., 2022), breeding introductions significantly influenced the genetic structure of carp populations co-cultivated in southern Zhejiang Province paddies (Zhu et al., 2022) discovered that the predicted genetic clusters had high probability, with either two or four clusters detected, based on delta K values. Every person showed a combination of genetic clusters in different ratios.

Genetic bottleneck and contemporary gene flow

Genetic bottlenecks decrease genetic variety and impede population survival and adaptability. They are frequently associated with habitat fragmentation. Unexpectedly high levels of heterozygosity in the data point to recent bottlenecks. Common carp populations that are declining exhibit high heterozygosity despite differences in the results of genetic testing; this is probably because to the factors including habitat degradation and overexploitation. This emphasizes how serious bottlenecks may be (Thai et al., 2007) using microsatellite DNA markers, it investigated bottleneck effects in endangered common carp populations. Their genetic information research improves the accuracy and efficiency of managing invasive species by helping to pinpoint high-risk locations and create focused management plans. Furthermore, knowledge of genetic linkage across groups might facilitate direct efforts to prevent future spread and use resources more wisely.

Conservation implications

The outcomes of this study have important implications for the conservation and management of invasive represented species in the River Chenab. Based on the genetic diversity and important role in gene flow, it is crucial to prioritize HT population. It is important to develop this approach to retain the genetic diversity and connectedness in the river systems by ensuring the health of carp populations in the region. Recognizing health of the HT population is crucial because it is not only beneficial for their own population’s health but also for other populations that depend on the gene flow in the River Chenab (Sanda et al., 2024).

Genetic bottlenecks inbreeding, and isolation in the HQ and HMW populations, it is important to observe effective conservation measures. Such measures might involve restoring habitats to improve between populations, establishing genetic links to enhance the flow of genes, and starting programs to increase population densities, thereby reducing the effects of inbreeding and genetic drift (Paganelli et al., 2024). Furthermore, managing the impacts of the changes in environment like preservation of habitats could support in alleviating the genetic challenges that these populations are experiencing. Such measures would ensure the sustainability and ability of the HQ and HMW populations to survive and thrive in the future.

Genetic diversity seems to be less in River Chenab populations than the Jhelum River. This implies that the Chenab populations might be more sensitive to the environmental changes as well to anthropogenic pressures. There is a need for effective conservation of these populations in order to address genetic and ecological challenges that these populations encounter to ensure viable and sustainable future of these species. Therefore, understanding the environment in its broader sense by considering the conservation measures that the invasive and native species have the possibility of crossbreeding, which may be important in dealing with issues of genetic diversity. The insights of these factors is vital to define strategies and management techniques that would protect genetic integrity and overall viability of both invasive and native species in the Chenab River system (Gozlan et al., 2024).

Importance of study and future research directions

Inbreeding of represented species populations may have potential negative genetic impacts on local strains. Future research is crucial to evaluate changes in the genetic diversity and population structure of these carp populations over time to compare the effectiveness of conservation approaches and to determine other potential genetic shifts that may take place. This is specifically important to understand changes that occur in genetic diversity, inbreeding and gene flow over time in order to evaluate the prospects of long-term conservations of such populations and make informed decisions on their management. In addition, understanding the environmental and ecological factors that may be influential of the observed genetic patterns including the fragmentation of habitats, the quality of water, and intensity of fishing which can provide more focused and efficient mitigation approaches. More populations are needed from different river systems in order to have further improvement on the genetic analysis. This will enable us to place the conclusions derived from the present study on the Chenab River in a broader context, and may even reveal other trends of genetic diversity and population structure of the invasive carp in the region. Further research is much needed to examine the impact of climate change on the genetic diversity and population dynamics of the represented species. Climate change may thus affect the distribution range of these species, their breeding time, and availability of the proper habitat. They could have a significant effect on their genetic diversity and population structure. Developing adaptive management strategies is essential to the continued sustainability of these populations and mechanism of sustainable management flexibly adopting to the dynamic nature of the production environments.

In conclusion, this study provides an understanding of genetic variations and population dynamics of common carp and scale carp in the Chenab River with important consequences for their conservation. These, in turn, underscore the need to conserve technologically distinct though however small, such as HT, and specifically target other at-risk populations. Therefore, research and conservation should sustain for the protection of these populations in future and for less impact of invasive species on the Chenab River ecosystem.

CONCLUSION

Concerning the spread and regulating the effects of invasion species requires a thorough understanding of the represented species’ genetic diversity, population structure, and movement patterns. In the present study aimed to understand the population structure and genetic diversity of invasive strains of common carp and scale carp in the river Chenab in Punjab, Pakistan. Outcomes of the study showed that these strains demonstrate from low to moderate level of heterozygosity. The average FIS values varied in a range between 0.51 to 0.59 for common carp and from 0.53 to 0.62 for scale carp. FST analysis showed moderate genetic differentiation between the strains. In common carp, 9.62% of the genetic variation was attributed to inter-population differences, while 90.38% was due to intra-population variability. For scale carp, AMOVA results showed that 87.08% of the genetic variation was due to inter-population differences, with 12.92% attributed to intra-population diversity. Bayesian clustering analysis identified 10 distinct categories among the populations of both strains, with no genetic evidence of admixture found in the pure original strains. The high observed heterozygosity compared to expected heterozygosity in common carp populations suggest the presence of a bottleneck event. The directed relative migration network highlighted HT common carp as the core population with the greatest genetic exchange, while no significant migratory events were observed in other scale carp populations, except for the HK population. The findings of this genetic study contribute to identifying high-risk areas and guiding targeted management strategies, thereby improving the effectiveness and precision of controlling invasive species. Additionally, the available genetic connectivity data between populations can inform resource allocation and mitigation strategies for future dispersal. Understanding the origin populations of non-native species is critical for comprehending their introduction routes and developing effective countermeasures. This knowledge facilitates the creation of programs aimed at regulating further investigations and managing invasive species effectively.

Declarations

Acknowledgement

The authors gratefully acknowledge the Government Sadiq College Women University, Bahawalpur, Department of Zoology, for providing essential chemicals and laboratory facilities necessary for the successful completion of this research.

Ethical statement

All experimental study was approved and reviewed by the Department of Animal Welfare and Ethical Committee of Department of Zoology, Government Sadiq College Women University Bahawalpur 63100, Pakistan.

Data availability statement

The data supporting this study’s findings are included in the manuscript or the supplementary information.

Supplementary material

There is supplementary material associated with this article. Access the material online at: https://dx.doi.org/10.17582/journal.pjz/20241005051145

Generative AI and AI-assisted technology statement

During the preparation of this article, the author did not utilize generative AI and AI-assisted technology.

Statement of conflict of interest

The authors have declared no conflict of interest.

REFERENCES

Abro, N.A., Waryani, B., Narejo, T.N., Ferrando, S., Abro, A.S., Abbasi, R.A., Lashari, K.P., Laghari, Y.M., Jamali, Q.G., Naz, G., Hussain, M. and -Ul -Hassan, H., 2020. Diversity of freshwater fish in the lower reach of Indus River, Sindh province section, Pakistan. Egypt. J. aquat. Biol. Fish., 24: 243-265. https://doi.org/10.21608/ejabf.2020.111114

Barletta, M., Jaureguizar, A.J., Baigun, C., Fontoura, N.F., Agostinho, A.A., Almeida-Val, V.M.F., Val, A.L., Torres, R.A., Jimenes-Segura, L.F., Giarrizzo, T., Fabré, N.N., Batista, V.S., Lasso, C., Taphorn, D.C., Costa, M.F., Chaves, P.T., Vieira, J.P. and Corrêa, M.F.M., 2010. Fish and aquatic habitat conservation in South America: A continental overview with emphasis on neotropical systems. J. Fish Biol., 76: 2118-2176. https://doi.org/10.1111/j.1095-8649.2010.02684.x

Bilal, W. and Khan, A.M., 2003. Pros and cons of alien fish introductions: A case scenario from Pakistan. J. Xi’. Shi., 19: 859-877.

Chen, X., Jähnig, S.C., Jeschke, J.M., Evans, T.G. and He, F., 2023. Do alien species affect native freshwater megafauna? Freshw. Biol., 68: 903-914. https://doi.org/10.1111/fwb.14073

Erarto, F. and Getahun, A., 2020. Impacts of introductions of alien species with emphasis on fishes. Int. J. Fish Aquat. Stud., 8: 207-216.

Fazzi-Gomes, P.F., Aguiar, J.D.P., Marques, D., Fonseca, C.G., Moreira, F.C., Rodrigues, M.D.N., Silva, C.S., Hamoy, I. and Santos, S., 2021. Novel microsatellite markers used for determining genetic diversity and tracing of wild and farmed populations of the Amazonian giant fish Arapaima gigas. Genes, 12: 1324. https://doi.org/10.3390/genes12091324

García-Ramos, G. and Kirkpatrick, M., 1997. Genetic models of adaptation and gene flow in peripheral populations. Evolution, 51: 21-28. https://doi.org/10.1111/j.1558-5646.1997.tb02384.x

Ghatak, S., Muthukumaran, R.B. and Nachimuthu, S.K., 2013. A simple method of genomic DNA extraction from human samples for PCR-RFLP analysis. J. Biomol. Tech., 24: 224. https://doi.org/10.7171/jbt.13-2404-001

Gozlan, R.E., Bommarito, C., Caballero-Huertas, M., Givens, J., Mortillaro, J.-M., Pepey, E., Ralaiarison, R.P., Senff, P. and Combe, M., 2024. A one-health approach to non-native species, aquaculture, and food security. Wat. Biol. Sec., 3: 1-16. https://doi.org/10.1016/j.watbs.2024.100250.

Guo, X.Z., Chen, H.M., Wang, A.B. and Qian, X.Q., 2022. Population genetic structure of the yellow catfish (Pelteobagrus fulvidraco) in China inferred from microsatellite analyses: Implications for fisheries management and breeding. J. World Aquacult. Soc., 53: 174-191. https://doi.org/10.1111/jwas.12844

Hale, M.L., Burg, T.M. and Steeves, T.E., 2012. Sampling for microsatellite-based population genetic studies: 25 to 30 individuals per population is enough to accurately estimate allele frequencies. https://doi.org/10.1371/journal.pone.0045170

Hayat, S., Malik, A., Ali, Q., Ishtiaq, A. and Akhtar, M.N., 2020. Length-weight relationships of Cyprinus carpio from the Indus River at Chashma Lake, District Mianwali, Punjab, Pakistan. J. Wildl. Biodiv., 4: 72-80.

Imran, M., Khan, A., Altaf, M., Ameen, M., Ahmad, R., Waseem, M. and Sarwar, G., 2021a. Impact of alien fishes on the distribution pattern of indigenous freshwater fishes of Punjab, Pakistan. Braz. J. Biol., 82: e238096. https://doi.org/10.1590/1519-6984.238096

Imran, M., Khan, A.M. and Waseem, M.T., 2021b. Dietary overlap between native and exotic fishes revealed through gut content analysis at Head Baloki, Punjab, Pakistan. J. Bio. Manage., 8: 10. https://doi.org/10.35691/JBM.1202.0169

Kang, B., Vitule, J.R.S., Li, S., Shuai, F., Huang, L., Huang, X., Fang, J., Shi, X., Zhu, Y., Xu, D., Yan, Y. and Lou, F., 2023. Introduction of non-native fish for aquaculture in China: A systematic review. Rev. Aquacult., 15: 676-703. https://doi.org/10.1111/raq.12751

Khan, W., Khan, M., Hussain, S., Masood, Z., Shadman, M., Baset, A., Rahman, A., Mohsin, M. and Alfarraj, S., 2021. Comparative analysis of brain in relation to the body length and weight of common carp (Cyprinus carpio) in captive (hatchery) and wild (river system) populations. Braz. J. Biol., 82. https://doi.org/10.1590/1519-6984.242897

Kovalenko, K.E., Pelicice, F.M., Kats, L.B., Kotta, J. and Thomaz, S.M., 2021. Aquatic invasive species: Introduction to the special issue and dynamics of public interest. Hydrobiologia, 848: 1939-1953. https://doi.org/10.1007/s10750-021-04585-y

Mutethya, E. and Yongo, E., 2021. A comprehensive review of invasion and ecological impacts of introduced common carp (Cyprinus carpio) in Lake Naivasha, Kenya. Lakes Reservoirs Sci. Policy Manage. Sustain. Use, 26: e12386. https://doi.org/10.1111/lre.12386

Nakajima, T., Hudson, M.J., Uchiyama, J., Makibayashi, K. and Zhang, J., 2019. Common carp aquaculture in Neolithic China dates back 8,000 years. Nat. Ecol. Evol., 3: 1415-1418.

Napora-Rutkowski, Ł., Rakus, K., Nowak, Z., Szczygieł, J., Pilarczyk, A., Ostaszewska, T. and Irnazarow, I., 2017. Genetic diversity of common carp (Cyprinus carpio L.) strains breed in Poland based on microsatellite, AFLP, and mtDNA genotype data. Aquaculture, 473: 433-442. https://doi.org/10.1016/j.aquaculture.2017.03.005

Nei, M., 1972. Genetic Distance between populations. Am. Naturalist, 106: 283-292. http://dx.doi.org/10.1086/282771

Nei, M., 1973. Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci., 70: 3321-3323. https://doi.org/10.1073/pnas.70.12.3321

Nei, M., 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89: 583-590. https://doi.org/10.1093/genetics/89.3.583

Paganelli, D., Bellati, A., Gazzola, A., Bracco, F. and Pellitteri-Rosa, D., 2024. Impacts, potential benefits and eradication feasibility of aquatic alien species in an integral natural state reserve. Biology, 13:1-13. https://doi.org/10.3390/biology13010064

Pandolfi, V.C.F., Yamachita, A.L., de Souza, F.P., de Godoy, S.M., de Lima, E.C.S., Feliciano, D.C., de Pádua Pereira, U., Povh, J.A., Ayres, D.R., Bignardi, A.B., Penafort, J.M., de Fátima Ruas, C. and Lopera-Barrero, N.M., 2021. Development of microsatellite markers and evaluation of genetic diversity of the Amazonian ornamental fish Pterophyllum scalare. Aquacult. Int., 29: 2435-2449. https://doi.org/10.1007/s10499-021-00757-8

Parveen, S., Abbas, K., Afzal, M. and Hussain, M., 2018. Prediction of potential hybridization between three major carps in ravi river (Punjab, Pakistan) basin by using microsatellite markers. Turk. J. Fish. Aquacult. Sci., 18: 27-35.

Parveen, S., Abbas, K., Tayyab, M., Hussain, M., Naz, H. and Shafique, L., 2024. Microsatellite and mtDNA-based exploration of inter-generic hybridization and patterns of genetic diversity in major carps of Punjab, Pakistan. Aquacult. Int., 12: 1-28. https://doi.org/10.1007/s10499-024-01425-3

Pearson, J., Dunham, J., Ryan, B.J. and Lyons, D., 2019. Modeling control of common carp (Cyprinus carpio) in a shallow lake wetland system. Wetlands Ecol. Manage., 27: 663-682. https://doi.org/10.1007/s11273-019-09685-0

Pyšek, P., Hulme, P.E., Simberloff, D., Bacher, S., Blackburn, T.M., Carlton, J.T., Dawson, W., Essl, F., Foxcroft, L.C., Genovesi, P., Jeschke, J.M., Kühn, I., Liebhold, A.M., Mandrak, N.E., Meyerson, L.A., Pauchard, A., Pergl, J., Roy, H.E., Seebens, H., van Kleunen, M., Vilà, M., Wingfield, M.J. and Richardson, D.M., 2020. Scientists warning on invasive alien species. Biol. Rev., 95: 1511-1534. https://doi.org/10.1111/brv.12627

Sambrook, J., Fritsch, E.F. and Maniatis, T., 1989. Molecular cloning: A laboratory manual. Cold spring harbor laboratory press.

Sanda, M.K., Metcalfe, N.B. and Barbara K.M., 2024. The potential impact of aquaculture on the genetic diversity and conservation of wild fish in sub-Saharan Africa. Aquat. Conserv. Mar. Freshw. Ecosyst., 34: 1-19. https://doi.org/10.1002/aqc.4105

Sánchez-Montes, G., Ariño, A.H., Vizmanos, J.L., Wang, J. and Martínez-Solano, Í., 2017. Effects of sample size and full sibs on genetic diversity characterization: A case study of three syntopic Iberian pond-breeding amphibians. J. Heredit., 108: 535-543. https://doi.org/10.1093/jhered/esx038

Sorensen, P.W., 2021. Introduction to the biology and control of invasive fishes and a special issue on this topic. Fishes, 6: 69. https://doi.org/10.3390/fishes6040069

Souza, A.T., Argillier, C., Blabolil, P., Děd, V., Jarić, I., Monteoliva, A.P., Reynaud, N., Ribeiro, F., Ritterbusch, D., Sala, P., Šmejkal, M., Volta, P. and Kubečka, J., 2022. Empirical evidence on the effects of climate on the viability of common carp (Cyprinus carpio) populations in European lakes. Biol. Invasions, 24: 1213-1227. https://doi.org/10.1007/s10530-021-02710-5

Sundqvist, L., Keenan, K., Zackrisson, M., Prodöhl, P. and Kleinhans, D., 2016. Directional genetic differentiation and relative migration. Ecol. Evol., 6: 3461-3475. https://doi.org/10.1002/ece3.2096

Thai, B.T., Burridge, C.P. and Austin, C.M., 2007. Genetic diversity of common carp (Cyprinus carpio L.) in Vietnam using four microsatellite loci. Aquaculture, 269: 174-186. https://doi.org/10.1016/j.aquaculture.2007.05.017

Tóth, B., Bagi, Z., Kézi, T. and Kusza, S., 2019. Optimization of microsatellite markers in Hungarian common carp (Cyprinus carpio L.) strains. preliminary report. Állattenyésztés és Takarmányozás, 68: 302-312.

Tóth, B., Khosravi, R., Ashrafzadeh, M. R., Bagi, Z., Fehér, M., Bársony, P., Kovács, G. and Kusza, S., 2020. Genetic diversity and structure of common carp (Cyprinus carpio L.) in the Centre of Carpathian Basin: Implications for conservation. Genes, 11: 1268. https://doi.org/10.3390/genes11111268

Xu, J., Jiang, Y., Zhao, Z., Zhang, H., Peng, W., Feng, J., Dong, C., Chen, B., Tai, R. and Xu, P., 2019. Patterns of geographical and potential adaptive divergence in the genome of the common carp (Cyprinus carpio). Front. Genet., 10: 660. https://doi.org/10.3389/fgene.2019.00660

Yang, X., Ye, J. and Wang, X., 2022. Factorizing knowledge in neural networks. In: European conference on computer vision: Springer. pp. 73-91. https://doi.org/10.1007/978-3-031-19830-4_5

Yaqoob, S., 2021. A review of structure, origin, purpose and impact of common carp (Cyprinuscarpio) in India. Ann. Roman. Soc. Cell Biol., 25: 34-47.

Ye, Y., Ren, W., Zhang, S., Zhao, L., Tang, J., Hu, L. and Chen, X., 2022. Genetic diversity of fish in aquaculture and of common carp (Cyprinus carpio) in traditional rice fish coculture. Agriculture, 12: 997. https://doi.org/10.3390/agriculture12070997

Yick, J.L., Wisniewski, C., Diggle, J. and Patil, J.G., 2021. Eradication of the invasive common carp, Cyprinus carpio from a Large Lake: Lessons and insights from the Tasmanian experience. Fishes, 6: 6. https://doi.org/10.3390/fishes6010006

Zhu, W., Fu, J., Luo, M., Wang, L., Wang, P., Liu, Q. and Dong, Z., 2022. Genetic diversity and population structure of bighead carp (Hypophthalmichthys nobilis) from the middle and lower reaches of the Yangtze River revealed using microsatellite markers. Aquacult. Rep., 27: 101377. https://doi.org/10.1016/j.aqrep.2022.101377