Genetic status of Oreochromis mossambicus populations as revealed by microsatellite DNA markers

doi:10.21203/rs.3.rs-2071161/v1

Genetic diversity is considered to be necessary for the long-term survival of species as it enables environmental adaptations to increase a species' or population's chances of survival, but it is being threatened by several environmental changes and anthropological interventions. Five microsatellite markers were employed to analyze the genetic diversity of Oreochromis mossambicus (Mozambique Tilapia) from River Jhelum. Average values of allelic number (Na) and allelic richness (Ar) ranged from 2.40 to 3.60. The average observed (H_O) and expected heterozygosity (He) values ranged from 0.55 to 0.69 and 0.54 to 0.67, respectively. The inbreeding coefficient F_IS values showed the highest level of inbreeding in Rasool Barrage and lowest in Pind Dadan Khan. Significant departure from HWE was observed in 3 out of 25 tests. The AMOVA specified that majority of variation (87.050%) was attributed to “within individuals”. UPGMA dendrogram revealed that PDK, RB, MD and JB populations were highly related, while THW appeared to differ significantly from other populations. The findings of this research will be helpful for the management of the concerned populations to maintain their genetic quality in in Pakistan.

Oreochromis mossambicus

genetic diversity

microsatellite loci

population genetics

For the long-term survival of a species, genetic diversity is imperative since it assure the fitness of species by giving them the ability to endure pressure from natural selection as well as varying environmental conditions and for successful adaptation to environmental changes (Banerjee et al. 2008; Reed and Frankham 2003). Understanding how genetic diversity is spread throughout species' geographic ranges, i.e., the genetic structure of their populations, can give valuable evolutionary, ecological, and life-history data. During last several decades, anthropogenic interventions including overfishing, pollution, introduction of exotic species, hydrological alterations, introduction of exotic species and environmental hazards such as climatic change and floods are major factors effecting the survival of fish species (Vandewoestijne et al. 2008). In these circumstances, assessing genetic diversity in wild populations is critical for determining species ecological and evolutionary responses to these changes, as well as providing helpful information for biodiversity management, conservation, and monitoring (Allendorf et al. 2010).

Globally, freshwater resources are the most species-rich ecosystems, accounting for 40% of total fish variety along with 20% classified as threatened (Darwall and Freyhof 2016). Oreochromis mossambicus is well-known aquaculture species and a member of the 'tilapias,' a varied paraphyletic group of primarily African cichlids best known for their widespread usage in tropical and subtropical aquaculture in the second half of the twentieth century (Strecker et al. 2011; Firmat et al. 2012). It is an omnivore fish that feeds on grass, small insects, native aquatic plants, small fish, spawn, organic detritus and is the most frequent exotic fish used as a source of food, found in Thailand, Pakistan, Egypt, and Indonesia (FAO 2012; Luna 2012). This fish is a rapid breeder, breeds three to four times in a year and can tolerate water with high temperature, salt concentration and pH, therefore, O. mossambicus has successfully established in almost every region in which they have been cultured or imported (Strecker et al. 2011; Mirza 2012; Bhanbhro et al. 2017).

The Mozambique tilapia, O. mossambicus, is a near threatened species because of its frequent hybridization with the widely introduced O. niloticus, but the genetic integrity of this species is declined due to many anthropological factors such as introduction of exotic species, habitat degradation, water quality deterioration, and overexploitation (Cambray and Swartz 2007; Angienda et al. 2011). Changes in environmental conditions due to agricultural runoff, sewage, pesticides, chemical pollutants and fertilizers have resulted in decline of genetic variability among fish population (Abdul-Muneer 2014). Dam construction has resulted in habitat fragmentation, pollution, overfishing, and habitat deterioration, which has resulted in the extinction of entire populations in some cases (Meldgaard et al. 2003). Therefore, maintenance of genetic diversity is important for the advancement in aquaculture practices and to conserve the healthy and beneficial varieties of fish species (Collares-pereira and Cowx 2004).

The development of molecular markers has enabled the genetic analysis of economically important fish for genetic management and conservation (Yousefian and Laloei 2011). Among the available molecular markers, microsatellites have become the marker of choice because of their extensive distribution in eukaryotic genomes, co dominance, high degrees of polymorphism and ease of analysis by Polymerase Chain Reaction (PCR) (Launey et al. 2002; Defaveri et al. 2013; Kim et al. 2013). Microsatellite markers are useful in aquaculture and fisheries research because they can be used in a variety of situations, especially when there are limited genetic differences within and between populations (Yousefian and Laloei 2011). Information of microsatellite markers on fish genetic stock structure, inbreeding and genetic connectedness is critical for long-term management of fisheries resources and successful genetic conservation (Abdul-Muneer et al. 2009). The information on current genetic study would be very helpful in making policy for the management of natural population and conservation of genetic resources.

Sample collection and DNA extraction

Fish samples of O. mossambicus were caught off their natural habitat (River Jhelum viz. Pind Dadan Khan (PDK), Mangla Dam (MD), Rasool Barrage (RB), Jhelum Bridge (JB) as well as Trimmu Headworks (TH)) with the cooperation of local fishermen. Muscle tissues were excised on-site from fresh specimen and then transported to laboratory under refrigerated conditions. Total genomic DNA was extracted following phenol/chloroform extraction protocol provided by Sambrook and Russell (2001), with slight modifications. Precipitated DNA was suspended in TE buffer, concentration was ascertained by nanodrop and diluted to 50ng/µL. Quality of extracted DNA was checked by AGE and bands were observed under UV light in geldoc system (UVCI, Major Science, USA).

Microsatellite analyses

Five microsatellite loci namely UNH123, UNH140, UNH146, UNH185 and UNH207 (Mireku 2017) taken from Gene Link were employed in this study. The features of microsatellite primers are given in Table 1. PCR was carried out in 25μL reaction mixture volume comprising 3μL of template DNA, 12μL of PCR Master Mix 2X (Thermo Scientific, USA), 2μL of each primer (forward and reverse) and 6μL of nuclease free water. After preheating at 94^oC for 5 minutes, amplification profiles (in a MultiGene OptiMax Thermal Cycler, Labnet, USA) were as follows: initial denaturation of 1 min at 94^oC; annealing temperature (primer-specific) for 30 sec followed by elongation for 1 min at 72°C. At the end, a final extension period for 5 min at 72°C was appended. After confirmation, amplicons were resolved electrophoretically on a 5% PAG stained with silver nitrate (Sanguinetti et al. 1994). DNA ladder (Thermo Fisher Scientific, USA) was also run alongside samples as a reference marker to compare allelic bands.

Table 1 Characteristics of microsatellite loci and PCR conditions used to genotype O. mossambicus samples

Sr.#	No. of Locus	Sequence of Primer (5-3)	T_a (°C)	No. of Alleles
1	UNH123	F: CATCATCACAGACAGATTAGA R: GATTGAGATTTCATTCAAG	37.45	4
2	UNH140	F: GATCAGAGGGTCAATGTGG R: CAGCAGAGTACTATGGAAGA	38.30	4
3	UNH146	F: CCACTCTGCCTGCCCTCTAT R: AGCTGCGTCAAACTCTCAAAAG	50.30	3
4	UNH185	F: CAGACACACTAGACACATTCTA R: GTGTTTCCATGTGTCTGTAC	57.8	3
5	UNH207	F: ACACAACAAGCAGATGGAGAC R: CAGGTGTGCAAGCAGAAGC	56.8	2

Scoring and analysis of data

Large allele dropout, strutting bands and null alleles (probable genotyping errors) were analyzed with software MICROCHECKER ver. 2.2.3. (Oosterhout et al. 2004). Allele frequency, allelic number (Na), allelic richness (Ar), inbreeding coefficient (F_IS) and pair-wise F_ST were assessed using FSTAT (Goudet 2001). AMOVA was incorporated using ARLEQUIN (ver. 3.5.2.2) to clarify the differences and similarities in molecular patterns across and within the five populations (Excoffier and Lische 2010). Heterozygosity (H) and effective alleles number (Nae) were calculated to characterize the diversity and the distribution of genetic variations using ‘POPGENE’ program (Yeh et al. 1999).

Deviations from HWE, unbiased measurement of genetic distance (GD) based on Nei (1972) will be drawn in TFPGA ver. 1.3 (Miller 1997). STRUCTURE 2.3.2 (Falush et al. 2003) was used to examine population structuring, with burn-in lengths of 50,000 and 100,000 MCMC iterations. For each k-value, 5 independent runs were performed and it was determined how many genetic clusters were there using STRUCTURE HARVESTER (Earl and Vonholdt 2012).

Genetic diversity: The MICROCHECKER software was used to examine genotypic data for the O. mossambicus population, which revealed no grading mistakes due to the null allele and every microsatellite locus was found to be polymorphic. Average allele frequency and allele size ranged from 0.060 to 0.534 and 102 to 450bp, respectively.

On average, Na and Ar per locus ranged from 2.400 to 3.600, THW population had highest average Na and Ar, whereas PDK population had lowest. Number of effective alleles (Nae) ranged from 2.712 to 3.15 in examined populations. In all populations, moderate level of heterozygosity (H) was observed. The O. mossambicus population from JB had the lowest (0.550) while the PDK population had the highest (0.693) HO values. Expected heterozygosity (He) varied from 0.542 (THW) to 0.676 (MD). In most of the screened microsatellite loci, 1-Ho/He values were found to be negative, with the exception of a few loci where positive values were also found (Table 2).

Except for PDK population, the average inbreeding coefficient (F_IS) value was found to be positive in O. mossambicus populations. The highest average F_IS was found in the RB (0.055) population, while the lowest was found in the PDK (-0.100) populations of O. mossambicus. At several tested loci, only 3 out of 25 tests significantly deviated from HWE after applying multiple test correction (p<0.05) (Table 2). Graphical comparison of genetic diversity metrics is given in Fig. 1.

Table 2 Genetic diversity metrics at microsatellite loci in O. mossambicus populations

Population	Parameters	Loci					Average
Population	Parameters	UNH123	UNH140	UNH147	UNH185	UNH207	Average
PDK	Na	2.000	3.000	2.000	2.000	3.000	2.400
	Ar	2.000	3.000	2.000	2.000	3.000	2.400
	Nae	3.488	3.571	2.922	1.923	3.846	3.150
	Ho	0.533	0.400	0.566	0.266	0.630	0.479
	He	0.925	0.785	0.689	0.688	0.875	0.792
	1-Ho/He	0.423	0.490	0.179	0.613	0.280	0.397
	F_IS	-0.035	0.151	-0.600	-0.082	0.062	-0.100
	PHWE	0.69^NS	1.000^NS	0.446^NS	0.001*	0.681^NS	---------
MD	Na	4.000	3.000	4.000	3.000	4.000	3.600
	Ar	4.000	3.000	3.999	3.000	4.000	3.599
	Nae	2.898	2.907	3.973	2.773	2.698	3.050
	Ho	0.490	0.710	0.233	0.125	0.680	0.447
	He	0.666	0.667	0.761	0.650	0.640	0.676
	1-Ho/He	0.264	-0.064	0.694	0.808	-0.063	0.328
	F_IS	-0.094	0.011	0.101	0.135	0.062	0.043
	PHWE	0.706^NS	0.708^NS	1.000^NS	1.000^NS	1.000^NS	--------
RB	Na	3.000	4.000	3.000	4.000	2.000	3.200
	Ar	3.000	4.000	3.000	4.000	2.000	3.200
	Nae	3.488	3.571	2.922	1.923	3.150	3.011
	Ho	0.733	0.800	0.666	0.466	0.800	0.693
	He	0.867	0.933	0.668	0.588	0.852	0.781
	1-Ho/He	0.154	0.143	0.003	0.207	0.061	0.114
	F_IS	0.003	0.037	0.021	0.218	0.000	0.055
	PHWE	0.001*	1.000^NS	0.467^NS	0.389^NS	1.000^NS	--------
JB	Na	3.000	3.000	3.000	4.000	3.000	3.200
	Ar	3.000	3.000	3.000	4.000	3.000	3.200
	Nae	1.834	2.799	3.696	3.696	2.662	2.937
	Ho	0.413	0.342	0.566	0.153	0.366	0.368
	He	0.579	0.959	0.739	0.899	0.689	0.773
	1-Ho/He	0.286	0.643	0.234	0.830	0.469	0.493
	F_IS	-0.008	0.027	-0.191	0.239	0.048	0.023
	PHWE	0.707^NS	0.454^NS	0.674^NS	0.040*	0.454^NS	--------
THW	Na	4.000	3.000	4.000	3.000	4.000	3.600
	Ar	4.000	3.000	4.000	3.000	4.000	3.600
	Nae	3.742	3.742	1.834	2.409	1.834	2.712
	Ho	0.100	0.321	0.433	0.566	0.721	0.428
	He	0.794	0.648	0.994	0.774	0.962	0.834
	1-Ho/He	0.874	0.505	0.564	0.269	0.251	0.492
	F_IS	-0.064	0.011	-0.111	0.080	0.205	0.024
	PHWE	1.000^NS	1.000^NS	1.000^NS	1.000^NS	0.074^NS	--------

Population genetic structure

The pair-wise population differentiation (F_ST) across all screened microsatellite loci found to be statistically significant (p<0.05) and indicated genetically non-homogenous groups. The maximum level of divergence was 0.164 between the THW-JB, while the lowest level was 0.029 between the RB-PDK population pairs. The population pairs of THW-JB had the greatest geographical distance, while the JB-MD population pair had the lowest (Fig. 2). With the increase of geographical distance, the genetic differentiation among population was also increased (Table 3). Among pairs of populations, GD showed considerable variation (p<0.05) in magnitude. The highest value of GD was recorded 0.646 between the population pair of THW-JB while, the minimum value was recorded 0.037 between the RB-PDK (Table 4).

Table 3: Pair-wise F_ST (below diagonal) and geographical distance (above diagonal) values

Populations	PDK	MD	RB	JB	THW
PDK	---------	118	49	75	204
MD	0.088 ^NS	---------	80	36	166
RB	0.029*	0.136 ^NS	---------	47	301
JB	0.099 ^NS	0.066 ^NS	0.124 ^NS	---------	338
THW	0.106^NS	0.112^NS	0.154^NS	0.164^NS	---------

*Significant at P<0.05

Table 4: GD between populations of O. mossambicus

Populations	PDK	MD	RB	JB	THW
PDK	---------
MD	0.224 ^NS	---------
RB	0.037*	0.283^NS	---------
JB	0.243^NS	0.153 ^NS	0.241^NS	---------
THW	0.251^NS	0.275 ^NS	0.310^NS	0.646^NS	---------

AMOVA demonstrated that 2.028% of genetic variation was contributed by “b/w individuals within populations”, 10.921% variation “among populations” while majority of variations (87.050%) was attributed to “within individuals” (Table 5). The largest value of gene flow (Nm) was examined at locus UNH123 (5.228) while the lowest at locus UNH185 (1.367) with mean value 3.970 (Table 6). The phylogenetic tree “UPGMA dendrogram” was constructed on the basis of neighbour joining method. PDK, RB, MD and JB populations were highly related, while THW appeared to differ significantly from other populations. (Figure 3).

Table 5 AMOVA table inferred by microsatellite markers

SOV	df	MSS	Variance	% Variation
Among populations	4	52.958	0.195	10.921
Between individuals within Populations	143	234.098	0.03	2.028
Within individuals	148	231.500	1.561	87.050

Table 6 Gene flow (Nm) at different microsatellite loci

Locus	Sample size	Nm
UNH123	300	5.228
UNH140	300	2.583
UNH146	300	2.927
UNH185	300	1.367
UNH207	300	2.065
Mean	300	3.970

Microsatellite data analysis using the STRUCTURE grouping algorithm revealed the existence of three different groups in the O. mossambicus populations. Across the six autonomous runs, constant results were obtained for each value of K. The STRUCTURE HARVESTER admixture model inferences yielded the highest estimated log likelihood mean value and delta-k value for K = 3 (Fig. 4).

A lot of studies have been done on growth and development, physiology, culture and toxicity of Mozambique Tilapia in Pakistan but the genetic issue remained unattempted. The appraisal fish; Oreochromis mossambicus is an important freshwater fish but now considered as a threatened species due to hybridization, pollution and habitat loss. The data on genetic diversity of O. mossambicus is limited only to the studies conducted on Southern Mozambique and South Africa. To assess the factors which are mainly responsible for the lack of genetic diversity of O. mossambicus populations, this is the first study being conducted in Pakistan from River Jhelum, Punjab, Pakistan.

In the present study, moderate level of genetic diversity was revealed by the studied microsatellite loci. All the microsatellite loci were polymorphic according to the 0.95% allele frequency criteria. The results are in conformity with Simbine et al. (2014) who used five microsatellite loci (UNH104, UNH129, UNH142, UNH222 and UNH222) to examine the genetic diversity of O. mossambicus collected from four rivers in southern Mozambique. High level of polymorphism among all the loci was observed.

Average Na and Ar per locus ranged from 2.400 to 3.600, which are lower than reported by Rutten et al. (2004) who observed the average Na per locus varying from 5.0 to 7.5. In all populations, moderate level of heterozygosity was observed. The values of Ho and He ranged from 0.550 to 0.693 and 0.542 to 0.676, respectively. He was observed higher as compared to Ho which suggests homozygosity at a locus or a population experiencing a bottleneck. Parallel findings to ours were given by Sultana et al. (2015) but contrary results were reported by Kariuki et al. (2021) who detected the very similar levels of expected and observed heterozygosity.

Except PDK population which exhibited negative average value, increasing values of F_IS demonstrated heterozygote deficiency. Findings are quite parallel to Ukenye et al. (2016) whose results showed that inbreeding coefficient (F_IS) was positive across seven loci reflecting excess of homozygotes. Out of 25 tests, a total of 3 tests deviated from HWE significantly after applying multiple test correction. Similar conclusions were reported by Bbole et al. (2020) in the case of Oreochromis andersonii and O. macrochir, two Southern African cichlid species. These findings demonstrated a significant divergence from HWE, but it was more apparent in O. andersonii. Deficits of the heterozygotes could be the cause of deviation from the HWE. In natural populations, inbreeding, fishing pressure, non-random sampling, genetic drift, intra-population structure could be the reason of the heterozygote deficit (Abbas et al. 2010). In the second half of last century, due to large scale hydrological alterations, there has been a decline in the diversity of fish populations and this might be the reason of heterozygote deficiency in the riverine populations of Pakistan.

F _ST is one of the most used methods for measuring genetic differentiation within and between populations, and it can offer crucial information on the evolutionary procedures that lead to genetic differentiation between populations (Holsinger and Weir 2009). The F_ST estimates indicated that all the populations were non-homogenous. The highest differentiation level was found between the population pair of THW-JB that specified dissimilar genetic origin. Lowest differentiation level was between the population of RB-PDK that might be due to physical connectivity and hence, gene flow among two riverine populations. Diyie et al. (2021) revealed low genetic differentiation in some population pairs of O. niloticus that could be due on-going gene flow in population subdivisions. Compared finding to ours are also reported by Ahmed and Abbas (2018), Nazish et al. (2018) and Diyei et al. (2021).

Analysis of molecular variance (AMOVA) was performed to determine genetic variability within and among populations, which specified that majority of variations (87.050%) were attributed to “within individuals” in wild populations. These results are in agreement with Nazish et al. (2018) in populations of Hypophthalmichthys molitrix inferred by microsatellite markers.

Based on Nei’s genetic distance, phylogenetic tree was constructed which yielded two clusters; PDK, RB, MD and JB populations were in one cluster while THW population alone was in second cluster. Although populations in one cluster are geographically separate, but share genetic similarity to similar origin. Genetic relatedness was further explored by a structural grouping technique using STRUCTURE HARVESTER. Maximum yielded log probability mean value and delta k value was k = 3. However, Evanno et al. (2005) asserted that estimation of the precise number of groups could be accomplished by calculating the delta k with as few as five microsatellite markers.

In O. mossambicus populations from numerous sites of Jhelum River, a general assessment of microsatellite DNA-based genetic diversity revealed a moderate level of genetic diversity and population differentiation. Meanwhile, the IUCN Red List has listed the Mozambique tilapia, O. mossambicus, as "near threatened" due to hybridization with the commonly introduced O. niloticus. Sustainable resource usage and the preservation of significant genetic variations are necessary for the sustainable management of freshwater fish species. The best strategy is to routinely monitor fish stocks in natural habitats, prevent overfishing, and enhance breeding and feeding grounds by optimizing riverine water flow.

Author contributions

Zahira Rehman and Muhammad Waseem developed the concept and idea and conducted the experiment. Khalid Abbas and Tanveer Ahmed planned the research layout and revised the manuscript critically. Taqwa Safdar and Muhammad Sarfraz Ahmed assisted in results interpretation, wrote manuscript and finalized the manuscript. All authors have read and approved the manuscript in its final form.

Funding This work was not supported by any funding organizations.

Conflict of interest The authors declare that they have no conflict of interest.

Ethical approval Not applicable.

Consent for publication Not applicable.

Consent to participate Not applicable.

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No competing interests reported.

Genetic status of Oreochromis mossambicus populations as revealed by microsatellite DNA markers

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Abstract

Figures

Introduction

Methodology

Results

Discussion

Declarations

References

Additional Declarations

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