Printer Friendly

Genetic Diversity in Cultured and Wild Population of Clarias gariepinus (Burchell, 1822) in Nigeria Using Random Amplified Polymorphic DNA (RAPD) and Microsatellite DNA.


C. gariepinus (Burchell 1822) belongs with the ray-finned (Class Actinopterygii) and air-breathing (Family Clariidae) catfishes (Order Siluriformes). The family Clariidae is naturally distributed across Africa, south and south-east Asia with the highest genetic diversity in Africa [1]. Genetic diversity is necessary for the survival of species because it confers better adaptability to changing environment [2-4]. Genetic diversity at a level below the species leads to formation of groups referred to as stocks, which are fundamental units of evolution. They are used by fishery biologists as a basis to manage commercially important marine organisms [5]. Patterns of genetic diversities between stocks provide clues to the histories of the populations and also reveal the degree of evolutionary isolation [6].

Genetic diversity is a critical measure in population studies because, by hinting on the evolutionary history of a population, it reveals the current and future health of the population [7]. Low levels of genetic diversity causes inbreeding depression in the short run and reduced evolutionary potential in the long run [7]. Inbreeding is marked by increasing homozygosity. This leads to loss of fitness because homozygous advantage is lost and deleterious recessive genes are unmasked. The evolutionary potential, defined as the ability of a species to adapt to novel selective pressures, also declines with decreasing genetic diversity, because the limited gene pool diminishes the likelihood of the existence of adaptive alleles in the genome of affected species [7-9].

Molecular genetic markers, such as Microsatellite DNA and Random Amplified Polymorphic DNA (RAPD), have been used extensively to study genetic diversity of cultured and wild stock [10,11]. RAPD is a multilocus [12] genetic marker based on Polymerase Chain Reaction (PCR). It possesses the benefit of simplicity and speed [12], because unlike other PCR-based technologies [13], it does not require prior knowledge of the genome or the gene sequence in the organism that is being genetically interrogated. However, RAPD produces some complex and unreproducible band patterns which make comparison of results difficult. For this reason, RAPD are unsuitable for database purposes [6].

Microsatellite DNA as a PCR-based molecular marker is more robust than RAPD. It is a single locus marker and the results are highly reproducible. This makes archiving in databases and sharing of results between laboratories possible. However, the development and isolation of the loci require prior knowledge of the genome which has now been made easier by the development of the Next Generation Sequencing (NGS) methods [14].

The study of genetic diversity of the Nigerian stocks of C. gariepinus is important because the species, as an important source of animal protein, commands high commercials values due to its high fecundity, high palatability, resilience, disease resistance and rapid growth [15]. The need to monitor the levels of genetic diversity is profound because genetic diversity is closely linked to the evolutionary potential and the survival of the species.

To effectively manage brood stocks for optimum productivity, it is important to compare the genetic composition of cultured with the wild population because significant loss of genetic variation, attributable to low effective number of parents, domestication selection or the mating design, among other factors, have been reported in hatcheries. Moreover, the feral introgression of the cultured into the wild as a result of escapee fishes has a great tendency of eroding the genetic diversity of the wild, especially if the genetic composition of the cultured population had not been properly managed [16].

Chi farm, Ajanla was established in 1986 on over a hundred hectares of land and is a major producer of aquaculture, poultry and cattle products in Nigeria. The location of the farm is about 40 km from Asejire Reservoir; a wild fishery which supplies Ibadan and its environs. In this present study, seven RAPD and seven microsatellite DNA markers were used to reveal and compare the genetic structure of cultured and wild populations of C. gariepinus from Chi farm, Ajanla, and Asejire Reservoir respectively.

Materials and Methods

Sampling and study areas

Twenty samples each of C. gariepinus were collected from Chi Farm, Ajanla (7[degrees] 14' N, 3[degrees] 49' E) and Asejire Reservoir (7[degrees] 24' N, 4[degrees] 8' E), South-western Nigeria (Figure 1). The sample was identified in the laboratory using fish identification keys by Olaosebikan [17]. The caudal fins, from which DNA was extracted were excised and preserved in 80% ethanol until needed.

DNA isolation

Small sections (0.1 g) of the stored fin samples were cut, rinsed, rehydrated in distilled water, and then transferred into microcentrifuge tubes containing pre-warmed CTAB lysis buffer (60[degrees]C) in preparation for homogenization. The constituents of the CTAB buffer include; 2% CTAB (hexadecyl trimethyl ammonium bromide), 100 mM TrisHCL pH=8, 20 mM EDTA, 1.4 M NaCl, 0.2% [beta]-mercaptoethanol (added before use), 0.1 mg/ml proteinase K (added before use). The mixtures of samples and buffer were homogenised and incubated at 60[degrees]C for 30 minutes with continuous shaking. They were then allowed to cool before the addition of 200 [micro]l Chloroform. The micro-centrifuge tubes were capped and inverted several times to mix. The mixtures were then spun for 10 minutes at 14000 g in Biologix High Speed Micro-centrifuge tubes, after which the aqueous upper phase containing DNA was transferred into fresh tubes. To precipitate the DNA from the aqueous phase, 300 [micro]L of Isopropanol was added and mixed. The tubes were thereafter left on ice overnight.

The mixture was spun at 14000 g for 10 minutes on the second day and the supernatant was discarded, leaving behind the DNA pellets to which 10 [micro]L of RNase A was added. The samples were incubated again for 30 minutes at 37[degrees]C. After cooling, 500 [micro]L of ethanol was added to the samples, and incubation at room temperature (25[degrees]C) was allowed for 30 minutes. The samples were spun at 14,000 g for 10 minutes, supernatant decanted and the pellets left to dry for 30 minutes before re-suspending in 100 [micro]L of sterile water. The integrity and purity of the genomic DNA isolates was checked by loading on 1% agarose gel.

PCR and electrophoresis

A 10 [micro]l reaction comprising the following was set up for each sample DNA: 5 [micro]1 of MyTaq Master mix, 1[micro]1 of 10 [micro]M Primer (0.5 [micro]L of each of Forward and Reverse Primers for microsatellite DNA) and 3 [micro]L of Nuclease free water. The set up was prepared on ice. All PCRs were run with the following programme on the thermal cycler: initial denaturation at 95[degrees]C for 3 mins, denaturation at 94[degrees]C for 30 sec, annealing for 30 sec, and extension at 72[degrees]C for 30 sec and final extension at 72[degrees]C for 10 mins. The annealing temperature varied according to melting temperatures of the primers. A low annealing temperature of 37[degrees]C was employed for all the RAPD primers. See Tables 1 and 2 for primer sequences and the annealing temperatures for the microsatellite DNA primers. The amplified fragments were resolved by gel electrophoresis on 2% agarose SFRTM (Super Fine Resolution) procured from VWR, Canada.

Data analysis

A 100 bp DNA ladder (Norgen PCR Sizer 100 bp DNA Ladder) loaded along with the gels was used for band sizing. For microsatellite DNA, bands were manually scored and the sizes estimated by semi-log plot. RAPD bands were scored as binary data using GelQuest [18]. The data generated were analysed using the Genalex 6.502 [19,20].

Results and Discussions

Random amplified polymorphic DNA

The random amplified polymorphic DNA fingerprints (Figure 2) were scored as binary matrix according to the specification of Genalex 6.502 and accounting for missing values wherever found. A total of 474 loci with 697 amplified bands were scored in all samples for the seven primers studied. The cultured population accounted for 366 bands, while the wild populations produced 331 bands.

Popoola et al. [16,21-23] reported percentage polymorphic loci of 68.5, 100, 89.9 and 74.7 for cultured), and ~93% (and 100% for cultured) respectively, which are higher than the 47.9% and 60.8% observed in this study for the wild and cultured populations respectively. In this present study, the cultured population showed a higher level of inherent genetic diversity and allele richness than the wild as revealed by indicators such as the percentage of polymorphic loci (%P), Number of Alleles (Na), Number of effective alleles (Ne), Shannon Information index (I), and expected heterozygosity (Nei's gene diversity). The Figures respectively recorded for these statistics in this study are: 60.8%, 1.215 [+ or -] 0.045, 1.083 [+ or -] 0.004, 0.141 [+ or -] 0.006, 0.071 [+ or -] 0.003 for the cultured population, and 47.9%, 0.958 [+ or -] 0.046, 1.076 [+ or -] 0.005, 0.120 [+ or -] 0.006, 0.063 [+ or -] 0.004 for the wild (Table 3). These Figures are lower than reported in similar studies [16,21,23-25].

The AMOVA with a fixation index, OPT=0.028, indicated that the sampled populations (cultured and wild) are significantly different from each other in the levels and composition of their genetic diversities at p=0.01, but not at higher probability levels (Table 3). 97% of this variation in genetic diversity came from within the populations, while only 3% is between the populations.

In accordance with the findings of Thorpe et al [26] that 98% of populations of the same species have genetic similarity above 0.85, the Nei's genetic identity (genetic similarity) of 0.998 were observed between the wild and the cultured populations in this study (Table 4).

This lower genetic diversity in both cultured and wild compared to what was recorded in similar studies could be an outcome of several factors which include the types of RAPD primers employed [23] or it may indicate a loss or an on-going loss of variability in both the cultured and wild species which may need to be stemmed by conservation interventions [27].

Microsatellite DNA

The microsatellite DNA fingerprints (Figure 3) were scored using the base pairs of the bands; homozygotes with single bands scored as a single base pair value repeated twice and heterozygotes with double bands as two different base pair values, in accordance with the requirement of Genalex 6.502. Observed heterozygosity and expected heterozygosity, number of alleles, effective number of alleles, deviations from Hardy Weinberg equilibrium and all other statistics were computed in Genalex 6.502 [20].

All the assayed loci are polymorphic in both populations. The cultured population (Ajanla) has a higher heterozygosity of 0.419 [+ or -] 0.133 than the wild (Asejire) with 0.387 [+ or -] 0.152. Analysis across populations revealed a higher mean number of alleles in the cultured population (3.000 [+ or -] 0.724) than the wild (2.714 [+ or -] 0.286) with effective number of alleles at 1.705 [+ or -] 0.205 and 1.733 [+ or -] 0.230 respectively (Table 5). The mean heterozygosity of 40.3% observed in this study is similar to the 44.3% observed by Agbebi et al. [22] in a study comparing C. gariepinus and Heterobranchus bidorsalis, while the expected heterozygosity (0.361 [+ or -] 0.053) is lower than the 0.896 [+ or -] 0.111 reported by the same author. The lower expected heterozygosity may suggest reduced evolutionary potentials in these populations. The Shannon's Information index (I=0.629 [+ or -] 0.143 and 0.591 [+ or -] 0.115) observed in this study, which are lower than previously reported Figures from similar studies [22,28] may suggest a lower or loss of genetic diversity in the studied populations.

The Fixation Index (F), or Inbreeding coefficient, or Heterozygosity deficit, showed that the cultured population possessed excess heterozygosity with a negative coefficient of -0.173 [+ or -] 0.209, perhaps due to selection for heterozygotes through negative assortative mating. The wild population has a low rate of inbreeding (F=0.042 [+ or -] 0.243), but not an excess of heterozygotes (Table 5). In the wild and cultured populations respectively, 71.4% (5 out of 7) and 42.9% (3 out of 7) of the loci are in disequilibrium (Table 6). In the Analysis of Molecular Variance (AMOVA), the OPT for the total population is 0.719 (Table 7). This statistically demonstrates that a high level of genetic differentiation exists between and within the two populations studied.

Selection, mutation, migration (gene flow), genetic drift and population sub-structuring (Wahlund effect) are factors which can independently or unanimously cause disequilibrium. The variation in the frequencies of loci in disequilibrium between the cultured and the wild suggests that the two populations are under different selective pressures.

The disequilibrium in the wild population may be accounted for by any or a combination of poaching, population subdivision (Wahlund effect), genetic drift (Sewall Wright effect and Founder effect) and natural selection. The genetic drift resulting from overfishing may account for the low diversity recorded in the wild population. The community around the Asejire Reservoir is rural with a handful of artisanal fishermen who depend on the catch from the reservoir for their livelihood. These artisanal fishermen may resolve to overfishing in order to make ends meet and without proper enforcement of existing fishery conservation laws, the erosion of the gene pool of the Asejire reservoir is imminent. Garg et al. [27] reported that in capture fishery, excessive exploitation, combined with poor fishery management result in the depletion of the fishery stocks; such depletion can result in loss of total gene pool.

The higher number of loci in Hardy-Weinberg equilibrium may suggest that the Ajanla farm, by accident or by design, have maintained a constant genotypic and gene frequencies. A laudable explanation is the fact that the farm management may be constantly selecting for the same set of specific traits that are of economic importance. This form of artificial selection could keep the frequency of the genes for these beneficial traits, and other linked genes and sequences, constant in the farm stock. It may also be inferred that no alien breed has been allowed into the stock in the recent generation.

The existence of an artificial selection program that focuses on breeding specific desirable economic traits (Heterosis and Complementarity) may also explain the excess heterozygosity recorded in the cultured population, because the desired combination of these traits are most likely found in the heterozygotes due to hybrid vigour (heterozygous advantage). This could also explain the reason for a lower level of genetic diversity in the cultured population, because according to Barasa et al. [29] mixed ancestry of source populations poses risks to animal via outbreeding depression. Moreover, in order to prevent segregation to undesired traits, the farm management may have limited the parental stocks to few known signatures, while also actively preventing introgression of any alien breed. The low level of statistical gene-flow (Nm=0.098) between the cultured and the wild population (Table 7) underscores the point that the cultured population is actively guarded against introgression. This genetic isolation of the cultured population could limit the evolutionary potential of the stock and leave the fishes susceptible to an epidemic or any other harsh environmental conditions to which they have not adapted.

Genetic variations, which may be considered 'the raw materials for evolution,' are important for the survival of species. There is a continuous need to improve and maintain a healthy level of genetic variability in organisms, particularly in economically important species like Clarias. The result of this study suggests a possible loss of variability in both the cultured and the wild populations. This loss, in the wild, may be attributed to overfishing, poaching, population subdivision, genetic drift and natural selection, while the loss of genetic diversity in the cultured population may be a result of strict breeding programs which may have genetically isolated the stock from alien populations. There is a need to deliberately inject new breeds into both the cultured and the wild populations in order to boost the evolutionary potentials of these populations. To avoid trading one woe for another, the introduction of these new genotypes must be done systematically, because outbreeding depression is an imminent risk, if the genetic distance between the populations and the new breeds is too large.


[1.] Teugels GG (1986) A systematic revision of the African species of the genus Clarias (Pisces: Clariidae). Mus R Africa Centre 63-72.

[2.] Fisher RA (1930) The Genetic Theory of Natural Selection. Oxford University Press, UK.

[3.] Hartl DL, Clark AG (2007) Principles of Population Genetics (4th edition). Sinauer Associates, Inc. Publishers.

[4.] Chauhan T, Rajiv K (2010) Molecular Markers and Their Applications in Fisheries and Aquaculture. Advances in Bioscience and Biotechnology 1: 281-291.

[5.] Abdul-Muneer PM (2014) Application of Microsatellite Markers in Conservation Genetis and Fisheries Management: Recent Advances in Population Structure Analysis and Conservation Strategies. (NA Doggett Editor) Genetics Research International 2014: 11.

[6.] Okumus I, Ciftci Y (2003) Fish Population Genetics and Molecular Markers: II - Molecular Markers and their Applications in Fisheries and Aquaculture. Turkish Journal of Fisheries and Aquatic Sciences 3: 51-79.

[7.] Kirk H, Freeland JR (2011) Applications and Implications of Neutral versus Non-neutral Markers in Molecular Ecology. International Journal of Molecular Sciences, 12: 3966-3988.

[8.] Pujol B, Pannell JR (2008) Reduced Responses to Selection after Species Range Expansion. Science 321: 96.

[9.] Markert JA, Champlin DM, Gutjahr-Gobell R, Grear JS, Kuhn A, et al. (2010) Population Genetic Diversity and Fitness in Multiple Environments. BMC Evolutionary Biology 10: 205.

[10.] Hallerman EM, Dunham RA, Smitherman RO (1986) Selection or Drift: Isozyme Allele Frequency Changes among Channel Catfishes Selected for Rapid Growth. Transactions of American Fishery Society 115: 60-68.

[11.] Mickett K, Morton C, Feng J, Li P, Simmons M, et al. (2003) Assessing Genetic Diversity of Domestic Populations of Channel Catfish (Ictalurus punctatus) in Alabama Using AFLP Markers. Aquaculture 228: 91-105.

[12.] Fahima T, Sun GL, Beharav A, Krugman T, Beiles A, et al. (1999) RAPD Polymorphism of Wild Emmer Wheat Populations, Triticum dicoccoides, in Isreal. Theoretical and Applied Genetics 98: 434-447.

[13.] Erlich HA (1989) PCR Technology: Principles and Application for DNA Amplification. (1st Edition). New York: Macmillan Publishers.

[14.] Hoshino AA, Bravo JP, Macedo PN, Morelli KA (2012) Microsatellies as Tools for Genetic Diversity Analysis. In M. Caliskan (Editor), Genetic Diversity in Micro-organisms IntechOpen.

[15.] Agbebi OT, Ajagbe O, Makinde L, Afolabi O (2009) Production, growth and effect of varying stocking density of Clariobranchus fry. International Journal of Fisheries and Aquaculture 4: 73-78.

[16.] Popoola OM, Fashakin EA, Awopetu JI (2014) Genetic Variability in Cultured and Wild Populations of Clarias gariepinus (Osteichtys: Clariidae) Using Random Amplified Polymorphic DNA (RAPD) Marker. Croatian Journal of Fisheries 72: 5-11.

[17.] Olaosebikan BD, Raji A (2004) Field Guide to Nigerian Freshwater Fishes. Federal College of Freshwater Fisheries Technology, PMB 1500, New Bussa, Niger state, Nigeria.

[18.] GelQuest (2008) Software for analysis of DNA fingerprint data. SequentiX - Digital DNA processing, Klein Raden, Germany.

[19.] Peakall R, Smouse PE (2006) GENALEX 6: genetic anlaysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6: 288-295.

[20.] Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research - an update. Bioinformatics 28: 2537-2539.

[21.] Saad YM, Ali SF, Hanafi MS, Ezza MA, Guerges AA (2009) Genetic Signature of Some Egyptian Clarias gariepinus Populations. Global Veterinaria 3: 503-508.

[22.] Agbebi OT, Ilaboya DE, Adebambo OA (2013) Preliminary Characterization of Genetic Strains in Clariid Species, Clarias gariepinus and Heterobranchus bidorsalis using Microsatellite Markers. African Journal of Biotechnology 12: 304-309.

[23.] Ikpeme EV, Udensi OU, Ekaluo UB, Kooffreh ME, Okolo CM, et al. (2015) Unveiling the Genetic Diversity in Clarias gariepinus (Burchell, 1822) Using Random Amplified Polymorphic DNA (RAPD) Fingerprinting Technique. Asian Journal of Animal Sciences 9: 187-197.

[24.] Islam MN, Basak A, Alam MS (2011) Genetic Diversity in Wild and Hatchery Populations of Stinging Catfish (Heteropneutes fossilis Bloch) Revealed by RAPD Analysis. Journal of Bioscience 19: 81-87.

[25.] Pechsiri J, Vanichanon A (2015) Genetic Diversity in Slender Walking Catfish (Clarias nieuhofii) Populations: Implications for Population Management. Walailak Journal of Science and Technology 13: 511-519.

[26.] Thorpe JP, Sole-Cava AM (1994) The Use of Allozyme Electrophoresis in Invertebrate Systematics. Zoologica Scripta 23: 3-18.

[27.] Garg RK, Sairkar P, Silawat N, Vijay N, Batav N, et al. (2009) Genetic Diversity between Two Population of Heteropneutes fossilis (Bloch) Using RAPD Profile. International Journal of Zoological Research 5: 171-177.

[28.] Ezilrani P, Christopher GJ (2015) Genetic Variation and Differentiation in African Catfishes, Clarias gariepinus, Assessed by Heterologous Microsatellite DNA. Indian Journal of Biotechnology 14: 338-393.

[29.] Barasa JE, Mdyogolo S, Abila R, Grobler JP, Skilton RA, et al. (2017) Genetic Diversity and Population Structure of the African Catfish Clarias gariepinus (Burchell, 1822) in Kenya: Implication for Conservation and Aquaculture. Belgian Journal of Zoology 147: 105-127.

Michael O Awodiran (*) and Olumide Afolabi

Department of Zoology, Obafemi Awolowo University, Ile-Ife, Nigeria

(*) Corresponding author: Michael O Awodiran, Department of Zoology, Obafemi Awolowo University, Ile-Ife, Nigeria, Tel: +234 806 208 8776; E-mail:

Received date: April 18, 2018; Accepted date: May 24, 2018; Published date: May 30, 2018

DOI: 10.4172/2150-3508.1000247
Table 1: List RAPD markers used in the study.

Primers  Sequence (5'[right arrow]3')

OPA 02          TGC CGA GCT
OPA 03          AGT CAG CCA C
OPC 02          GTG AGG CGT TC
OPB 08          GTC CCA CAC GG
OPC 11          AAA GCT GCG G
OPA 12          TCG GCG ATA G
OPA 19          CAA ACG TCG G

Table 2: List of microsatellite primers utilized and their sequences.

Primer    Sequence (5'[right arrow]3')    Annealing Temperature

Cga 01 F  GGC TAA AAG AAC CCT GTC TG              53
Cga 02 F  GCT AGT GTG AAC GCA AGG C               53
Cga 03 F  CAC TTC TTA CAT TTG TGC CC              49.1
Cga 05 F  TCC CAC ATT AAG GAC AAC CAC CG          56.9
Cga 06 F  CAG CTC GTG TTT AAT TTG GC              54
Cga 09 F  CGT CCA CTT CCC CTA GAG CG              55.8
Cga 10 F   GCT GTA GCA AAA ATC CAG ATG C          54.4

Table 3: Basic indicators of genetic variation across populations for
the RAPD data.

Populations   %P            Na                    Ne

  Ajanla     60.8  1.215 [+ or -] 0.045  1.083 [+ or -] 0.004
  Asejire    47.9  0.958 [+ or -] 0.046  1.076 [+ or -] 0.005
   Mean      54.3  1.086 [+ or -] 0.032  1.079 [+ or -] 0.003

Populations           I                     h              NI

  Ajanla     0.141 [+ or -] 0.006  0.071 [+ or -] 0.003  0.998
  Asejire    0.120 [+ or -] 0.006  0.063 [+ or -] 0.004
   Mean      0.130 [+ or -] 0.004  0.067 [+ or -] 0.002

Na=No. of Different Alleles, Ne=No. of Effective Alleles, I=Shannon's
Information Index, h=Diversity, %P=Percentage of Polymorphic Loci,
NI=Nei's Genetic Identity.

Table 4: Analysis of Molecular Variance (AMOVA).

  Source     df    SS       MS    Est. Var.    %   [phi]PT    No. of

Among Pops    1   26.575  26.575    0.491      3%
Within Pops  38  636.45   16.749   16.749     97%
   Total     39  663.025           17.24     100%   0.028       999

df=degree of freedom, SS=Sum of Squares, MS=Mean Squares, Est.
Var.=Estimated Variance, [phi]PT=Fixation Index.

Table 5: Basic indicators of genetic diversities for Microsatellite

         %P            Na                    Ne

Ajanla   100  3.000 [+ or -] 0.724  1.705 [+ or -] 0.205
Asejire  100  2.714 [+ or -] 0.286  1.733 [+ or -] 0.230
 Mean    100  2.857 [+ or -] 0.376  1.719 [+ or -] 0.148

                  I                     Ho

Ajanla   0.629 [+ or -] 0.143  0.419 [+ or -] 0.133
Asejire  0.591 [+ or -] 0.115  0.387 [+ or -] 0.152
 Mean    0.610 [+ or -] 0.088  0.403 [+ or -] 0.097

                  He                    F

Ajanla   0.36 [+ or -] 0.075   -0.173 [+ or -] 0.209
Asejire  0.361 [+ or -] 0.082   0.042 [+ or -] 0.243
 Mean    0.361 [+ or -] 0.053   0.371 [+ or -] 0.055

Ho=Observed Heterozygosity, He=Expected Heterozygosity.

Table 6: Summary of Chi-Square tests for Hardy-Weinberg equilibrium.

Pop      Locus   Degree of    Chi   Probability  Significance
                  freedom   square

Ajanla   Cga 01      1       0.131    0.717          ns
         Cga 02     21      60.34     0             (***)
         Cga 03      6       8.5      0.204          ns
         Cga 05      1       8.889    0.003         (**)
         Cga 06      1       0.131    0.717          ns
         Cga 09      1      20        0             (***)
         Cga 10      1       0.263    0.608          ns
Asejire  Cga 01      3      18.034    0             (***)
         Cga 02      6      20.147    0.003         (**)
         Cga 03      3      10.457    0.015         (*)
         Cga 05      1       2.99     0.084          ns
         Cga 06      1       0.013    0.909          ns
         Cga 09      1      19        0             (***)
         Cga 10      3      18.017    0             (***)

Key: ns=not significant, (*) P<0.05, (**) P<0.01, (***) P<0.001.

Table 7: Analysis of molecular variance (AMOVA).

  Source     df    SS     MS     Est. Var.   %     OPT        Nm

Among pops    1  165.3  165.3      8.107     72%  0.719 (*)  0.098
Within pops  38  120.2    3.163    3.163     28%   -          -
   Total     39  285.5     -      11.27     100%   -          -
COPYRIGHT 2018 HATASO Enterprises, LLC
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2018 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:Research Article
Author:Awodiran, Michael O.; Afolabi, Olumide
Publication:Fisheries and Aquaculture Journal
Date:Apr 1, 2018
Previous Article:Extracellular Matrix Components in Bivalvia: Shell and ECM Components in Developmental and Adult Tissues.
Next Article:Gillnet Selectivity for Big Eye Barracuda, Sphyraena forsteri (Cuvier, 1829) in Thoothukudi Waters, Southeast Coast of India.

Terms of use | Privacy policy | Copyright © 2022 Farlex, Inc. | Feedback | For webmasters |