Content uploaded by Appidi Krishna Reddy
All content in this area was uploaded by Appidi Krishna Reddy on Mar 18, 2016
Content may be subject to copyright.
The Israeli Journal of Aquaculture - Bamidgeh, IJA_66.1070. 7 pages
* Corresponding author: firstname.lastname@example.org
Microsatellite DNA analysis of giant freshwater prawn
(Macrobrachium rosenbergii) from India
, A.K. Reddy
, Gopal Krishna
, Rupam Sharma
, M. Sankar
, M. Sekar
and A. Kathirvelpandian
1. Division of Fish Genetics and Biotechnology, Central Institute of Fisheries Education, Mumbai
-400 061, India
2. Presently at Central Marine Fisheries Research Institute, Vizhag
3. Presently at National Bureau of Fish Genetic Resources, Lucknow
Running title: Microsatellite DNA analysis of Macrobrachium rosenbergii
Keywords: Genetic diversity; microsatellite; Macrobrachium rosenbergii; Freshwater Prawn; India.
Giant freshwater prawn (Macrobrachium rosenbergii), a commercially important crustacean
species, is widely distributed across the Indo-Pacific region. Genetic diversity of this species
from five different rivers (Krishna, Mahanadi, Hooghly, Narmada and Kalu) of India was
investigated using 5 polymorphic microsatellite loci. The number of alleles across loci varied
from 4 to 9. The mean expected and observed heterozygosity at all loci was 0.8359 and
0.5747 respectively. Most of the loci deviated significantly from Hardy-Weinberg expectations
across all the populations. Pairwise F
estimates (0.0420 to 0.0841) revealed a significant
genetic structure among M. rosenbergii populations of Indian rivers. The highest (0.5140)
genetic distance was observed between Krishna and Kalu populations. All the five wild
populations exhibited significant variation across all five microsatellite loci. The results
revealed in the study will be useful for breeding program and conservation management of
The Giant freshwater prawn, Macrobrachium rosenbergii has been one of the most desirable
candidate species for freshwater aquaculture in different parts of India – Pacific region (Ranjeet
and Kurup, 2002). The annual aquaculture production of M. rosenbergii dramatically increased from
178 tons in 1996 to 42,820 tons in 2005 in India (FAO, 2005) and then started to reach the
abysmal level of 6,600 tons in 2010-11 (www.fis.com). The reason for declining of production is
using of inbred for several generations for producing seeds at commercial farms that exhibit a
general decline in productivity involving early sexual maturity, low fecundity and larval viability and
susceptibility to diseases (Mohanakumaran Nair and Salin, 2006). In spite of these, it has vast
potential for earning of foreign exchange due to its rapid growth, disease resistance and high
demand in both domestic and export markets, and it can also compete with other cultured prawn in
terms of income, provided the species is domesticated and genetically improved for better
performance (Jahageerdar, 2003).
It is believed that genetic diversity in wild populations is declining as a result of over-
exploitation. Therefore, it is important to understand the distribution of genetic diversity in wild
stocks for developing sound conservation strategies. Recognition of unique genetic diversity will
also improve choices in breeding programs help genetic diversity of broodstocks, and the
maintenance of genetic diversity in cultured stocks (Chand et al., 2005). Genetic diversity is the
fundamental resources on which stock improvements rely, therefore, populations can receive
The IJA appears exclusively as a peer-reviewed on-line
open-access journal at http://www.siamb.org.il. To read
papers free of charge, please register online at
Sale of IJA papers is strictly forbidden.
Sale of IJA papers is strictly forbidden.
Suresh et al.
priority for selection on the basis of genetic criteria (Petit, et al., 1998; Vandeputte and Launey,
Microsatellite markers are a good choice for the characterization of genetic diversity in both wild
and cultivated M. rosenbergii due to its reliable, informative, co-dominant nature and ease of
exchange of data among different studies (Avise, 1994).
Currently, little is known about the levels and patterns of genetic diversity in Indian populations
of M. rosenbergii. In India, one study based on microsatellite markers was conducted on genetic
variation of two wild populations of M. rosenbergii (Divu et al., 2008) and another study based on
24 unrelated individuals collected from the wild (Bhat et al., 2009). Hence, the present study was
carried out to evaluate the levels of genetic diversity of five different populations of M. rosenbergii
of India using five microsatellite markers. Therefore, this study will be helpful in assisting the
selection of individuals for prawn-breeding programs, which would facilitate the domestication of
Materials and methods
M. rosenbergii samples were collected from five different rivers in India, Krishna, Andhra
45’16.91E), Mahanadi, Odisha (20
Hooghly, West Bengal (22
88’12.46”E) from the east coast, Narmada, Gujarat
15’50.47”E) and Kalu, Maharashtra (19
18’13.71”E) from the
west coast. A total of 250 samples (50 from each location) were used in the present study.
Pleopods were removed from each individual, preserved in 95 % ethanol and kept at – 20
DNA extraction and polymerase chain reaction (PCR) amplification
Total genomic DNA was extracted from the pleopod tissues using the standard phenol-
chloroform extraction method described (Sambrook et al., 2001) with minor modification. DNA
quality and quantity were determined by agarose gel electrophoresis and biophotometer
Five microsatellite loci (MRMA27, MRMB7, MRMB10, MRMA8 and Mr5-26 (Divu et al. 2008 and
Bhat et al. 2009) developed for M. rosenbergii were used to amplify DNA samples (Table 1). PCR
was performed in 25 ul volume containing 1 X PCR Buffer (Bangalore Genei, India), 200 µM dNTPs,
10 pmol each primer, 50 ng DNA and 0.25 U Taq polymerase (Bangalore Genei). PCR cycles for
each locus were as follows: initial denaturation for 5 min at 94
C, followed by 35 cycles of 1 min at
C, annealing temperature for 30 s, and 2 min at 72
C with the final extension at 72
C for 10
min. Holding temperature was set at 4
C. PCR products were subjected to electrophoresis on 7%
non-denatured polyacrylamide gel at 80 V for 4 hrs after the amplification. Gel was stained using
silver stain for further analysis. Allele sizes were determined with gene runner DNA ladder.
Table 1. Details of primer and microsatellite in M. rosenbergii in the present study
Primer sequence (5’ to 3’)
Allele size range (bp)
384 - 422
380 - 420
270 – 300
270 - 300
125 – 200
128 - 202
100 – 175
102 - 176
236 - 282
F: Forward primer; R: Reverse primer; bp: base pair; T
The Israeli Journal of Aquaculture - Bamidgeh, IJA_66.1070, x pages
email@example.com* Corresponding author:
The genetic variation within each of five populations including alleles per locus (A),
) and expected (H
) heterozygosity, and departures from Hardy-Weinberg
equilibrium (HWE) were calculated using the software GENEPOP version 3.3d
(Raymond and Rousset, 1998). The ARLEQUIN 3.11 software was used to calculate
genotypic linkage disequilibrium between these loci (Schneider et al., 2000).
Genetic differences between populations were evaluated by calculating pairwise F
values and testing their significance by bootstrapping analysis (1000 replicates) using
GENEPOP version 3.3d (Raymond and Rousset, 1998).
Expected frequency of null alleles were calculated across all populations according
to Van Oosterhout et al. (2004, 2006) using MICRO-CHECKER. Nei’s (1978) genetic
distances were calculated between all pairs of populations using POPGENE version 1.31
(Yeh et al., 1999). A dendrogram was drawn based on the genetic distance between
the populations following Unweighted Pair Group Method of Averages (UPGMA) using
the software MEGA4 (Tamura et al., 2007).
Overall genetic variability
Among the five populations 126 alleles with the allele numbers ranging from 4 to 9
were observed in 5 loci. Mean number of alleles per locus ranged from 4.40 to 6.20
across the 5 microsatellite loci. Mean values of expected heterozygosity for each
population ranged from 0.7574 to 0.8049 and observed heterozygosity ranged from
0.5333 (Narmada population) to 0.6000 (Krishna population). All populations deviated
significantly from HWE at all five microsatellite loci (Table 2). There was no significant
association indicative of linkage disequilibrium between any pair of microsatellite loci
for any population (P > 0.05), indicating independence of the five genetic markers.
Wright's (1978) fixation index (F
) a measure of heterozygote deficiency or excess
(inbreeding co-efficient), and significance values (ranged from 0.0916 to 0.4781) for
each locus in five populations are given in Table 2. F
values greater than zero (+ ve)
indicating a deficiency of heterozygotes was evident in these cases. Microsatellite loci
exhibiting + F
values were tested for presence of null alleles. Estimated null allele
frequencies assessed with MICROCHECKER were not significant (P < 0.05) indicating
the absence of null alleles and false homozygotes at any locus. Therefore information
from all five microsatellite loci was considered for the population genetic analysis.
Table 2. Summary statistics of 5 populations of M. rosenbergii using 5 microsatellite loci
2 Suresh et al.
, Number of alleles; H
, Observed Heterozygosity; H
, Expected Heterozygosity; F
, Probabiliy value of significant deviation from Hardy-Weinberg equilibrium; A
, Mean number
of alleles per locus
* Is significant at P < 0.05
** Is significant at P < 0.05 after Bonferroni adjustment
value was estimated to be 0.0666. Pair-wise F
population pairs differed significantly (P < 0.01) from 0.0420 to 0.0911 for all the pairs
of populations (Table 3). Among the five populations, Krishna and Mahanadi population
pairs were the most divergent (highest F
value=0.0911), followed by the Krishna and
Kalu populations (F
value=0.0841). The highest genetic distance (0.5140) was
observed between Krishna and Kalu populations while the lowest genetic distance
(0.2190) was observed between Krishna and Narmada populations (Table 4).
Table 3. Pairwise F
among five populations
All pairwise F
values were significant at P < 0.05
Table 4. Nei’s genetic identity values (above diagonal) and genetic distances (D
)(below diagonal) among
The dendrogram based on genetic distance computed by Nei (1978) showed four
major clusters: Krishna and Mahanadi populations formed in single cluster, and the
remaining populations (Hooghly, Narmada and Kalu) formed separate clusters.
Fig.1 UPGMA clustering using Nei’s unbiased genetic distance (1978) of M. rosenbergiipopulation
Microsatellite DNA analysis of giant freshwater prawn (Macrobrachium rosenbergii)
Five polymorphic microsatellite loci (Divu et al. 2008 and Bhat et al. 2009)
developed for M. rosenbergii were used to evaluate genetic diversity and population
differentiation in M. rosenbergii (N=250) collected from five different rivers of India.
Ruzzante (1998) confirmed that sample sizes larger than 50 individuals are adequate
for minimizing bias due to a large number of alleles in microsatellite data. Silva and
Russo (2000) also reported that sample sizes should exceed 30. In the present study,
collected sample sizes were 50 from each location. Therefore, estimates of population
differentiation obtained, were unlikely to be confounded by small sample sizes.
Number of alleles varied from 4 to 9 and mean number of alleles per locus ranged
from 4.4 to 6.2 across all microsatellite loci (Table 2). This finding is almost similar to
the results reported by Divu et al. (2008) and Bhat et al. (2009) for M. rosenbergii
sampled from two South Indian rivers. Much of the variation in polymorphism at
microsatellite loci that exist between species can be attributed to population biology
and life history and to a lesser extent to differences in natural selection acting at the
loci directly or indirectly (Neff and Gross, 2001). Hence, lesser number of alleles at
microsatellite loci in M. rosenbergii suggests lower mutations rates in the species.
Significant deviations from HWE, resulting from heterozygote deficiencies, were
detected at most loci in the sampled populations. A similar finding was reported by
Chareontawee et al. (2007) and Bhat et al. (2009) in M. rosenbergii. Benzie (2000)
and Mandal (2012) also reported low observed microsatellite heterozygosity values for
four species of penaeid prawns and P. monodon respectively.
Deviations from HWE with homozygote excesses are often attributed to either; null
alleles (Garcia DeLeon et al. 1995; Gopalakrishnan et al. 2009), selection (Garcia
DeLeon et al. 1995), unrecognized sampling of divergent gene pools (Wahlund effect)
(Gibbs et al. 1997), inbreeding, or non-random mating (Beaumont and Hoare, 2003).
MICRO-CHECKER analysis did not indicate presence of any null alleles in all five
populations sampled. This may be due to inbreeding caused by over-exploitation,
which might result in deficiency of heterozygotes and deviation from HWE. This results
are corroborated with Bhat et al. (2009), reported the decline of M. rosenbergii catch
due to over-exploitation.
value (0.0666) and pairwise F
estimates (0.0420 to 0.0911) obtained
in this study indicates a significant level of genetic differentiation among different
riverine M. rosenbergii populations. This result suggests separation of breeding
populations, restriction in movement of populations between different areas and
existence of distinct sock structure among populations. Nei's (1978) genetic distance
estimates between population pairs among sampled M. rosenbergii populations were
high with 5 microsatellite markers in the present study and the UPGMA also showed a
distinct population structure related to geographical location.
In conclusion, this study provides baseline genetic data for freshwater prawn
culture and will also be useful in devising stock-specific conservation management
plans and traceability analysis in mixed catch scenario.
Authors are grateful to Dr. Dilip Kumar (Ex Director, CIFE) and Dr. W.S. Lakra, Vice
Chancellor/Director, CIFE, Mumbai for providing facilities, support and guidance. First
author is thankful to Central Institute of Fisheries Education (Deemed University),
ICAR for providing fellowship during the study period.
Avise J.C, 1994. Molecular markers, natural history and evolution. Chapman and Hall,
Beaumont A. and K. Hoare , 2003 Biotechnology and genetics in fisheries and
aquaculture. Blackwell Publishing Company, Malden, USA.
Benzie J.A.H., 2000. Population genetic structure in penaeid prawns. Aquacult Res.,
4 Suresh et al.
Bhat S., Patel A., Das P., Meher P.K., Pillai P.R. and P. Jayasankar, 2009.
Isolation and characterization of microsatellite loci in giant freshwater prawn,
Macrobrachium rosenbergii. Conserv Genet., 10:1473 -1475.
Chand V., De bruyn M. and P.B. Mather, 2005. Microsatellite loci in the eastern
form of the giant freshwater prawn (Macrobrachium rosenbergii). Mol Eco Notes,
Charoentawee K., Poompuang S. and U. Na-Nakorn, 2007. Genetic diversity of
hatchery stocks of giant freshwater prawn (Macrobrachium rosenbergii) in Thailand.
Divu D., Khushiramani K., Malathi S., Karunasagar I. and I. Karunasagar,
2008. Isolation, characterization and evaluation of microsatellite DNA markers in giant
freshwater prawn Macrobrachiumrosenbergii, from South India. Aquaculture, 284:281-
Garcia DeLeon F.J., Dallas J.F., Chatain B., Canonne M., Versini J.J. and F.
Bonhomme,1995. Development and use of microsatellite markers in sea bass,
Dicentrarchus labrax (Linneaus 1758) (Perciformes: Serranidae). Mol Mar Biol.
Gibbs H.L., Prior K.A., Weatherhead P.J. and G. Johnson, 1997. Genetic structure
of populations of the threatened eastern massasuaga rattlesnake, Sistrurus catenatus:
evidence from microsatellite DNA markers. Mol Ecol., 6:1123–1132.
Gopalakrishnan A., Musammilu K.K., Basheer V.S., John L., Padmakumar K.G.,
Lal K.K., Mohindra V., Punia P., Dinesh K., Manjebrayakath H., Ponnia A.G. And
W.S. Lakra, 2000. Low genetic differentiation in the populations of the Malabar carp
Labeo dussumieri as revealed by allozymes, microsatellites and RAPD. Asian Fish Sci.,
Jahageerdar, S, 2003. Genetic improvement of giant freshwater prawn
Macrobrachium rosenbergii by selective breeding.In: Advances in Biology, Aquaculture
and Marketing (ed., Mohankumaran Nair, C., Nambhudiri, D. D., Sankaran, T. M.,
Jayachandran, K. V. and Stalin, K. R.). Allied Publishers Pvt. Ltd, New Delhi, pp. 493-
Mandal A., Divya R., Karuppaiah D., Gopalakrishnan A., Pozhoth J., Samraj
Y.C.T. and R.W. Doyle, 2012. Populations genetic structure of Penaeus monodon, in
relation to monsoon current patterns in Southwest, East and Andaman coastal waters
of India. Gene, 491:149-157.
Mohanakumaran Nair, C. and K.R Salin, 2006. Freshwater prawn farming in India:
Status, prospects. Global Aquaculture Advocate, 35 – 37.
Nei M.,1978. Estimation of average heterozygosity and genetic distance from a small
number of individuals. Genetics, 89:583–59.
New M.B., 2000. History and global status of freshwater prawn farming. In: New, MB
and WC Valenti (eds) Freshwaterprawn culture: The farming of Macrobrachium
rosenbergii. Blackwell Science, London, UK, pp 1–11.
Petit R.J., Mousadik El. and Pons O., 1998. Identifying populations for conservation
on the basis of genetic markers. Conservation Biology, 12, 844-855.
Ranjeet, K. and B.M. Kurup, 2002. Heterogenous Individual Growth of
Macrobrachium rosenbergii Male Morphotypes. Naga, The ICALARM Quarterly, 23: 13-
Raymond M. and F. Rousset, 1998. GENEPOP version 3.3d A population genetics
software for exact test and ecumenicism. J. Hered., 86:248–249.
Ruzzante D.E,1998. A comparison of several measures of genetic distance and
population structure with microsatellite data: bias and sampling variance. Can. J. Fish.
Aquat Sci., 55:1–14.
Sambrook J. and D.W. Russell, 2001. Molecular cloning: a laboratory manual, 3rd
edn. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY.
Schneider S., Roessli D. and L. Excoffier, 2000. ARLEQUIN: A Software for
Population Genetics Data Analysis, Version 2.000. Genetics and Biometry Laboratory,
Department of Anthropology. University of Geneva, Geneva.
Microsatellite DNA analysis of giant freshwater prawn (Macrobrachium rosenbergii)
Silva E.P. and C.A.M. Russo, 2000. Techniques and statistical data analysis on
molecular population genetics. Hydrobiologia, 420:119–135.
Tamura K., Dudley J., Nei M. and S. Kumar, 2007. MEGA4: Molecular Evolutionary
Genetics Analysis (MEGA) software version 4.0. Mol. Biol. Evol., 24:1596–1599.
Van Oosterhout C., Hutchinson W.F., Wills D.P.M. and P. Shipley, 2004. MICRO-
CHECKER: software for identifying and correcting genotyping errors in microsatellite
data. Mol. Ecol. Notes, 4:535-538.
Van OosterhoutC, Weetman D. and Hutchinson WF., 2006. Estimation and
adjustment of microsatellite null alleles in non-equilibrium populations. Mol. Ecol
Vandeputte M. and Launey S., 2004. The genetic management of fish
domestication. Productions Animales, 17, 237-242.
Wright S., 1978. Evolution and the genetics of populations. Univ. Chicago Press,
Yeh F.C., Yang R.C. and T. Boyle, 1999. POPGENE version 1.31: Microsoft windows-
based freeware for population genetic analysis. Centre for International Forestry
Research, University of Alberta, Edmonton, Alberta, Canada.