i

Impacts of traditional husbandry practices on exploitable levels of

genetic diversity in cultured ‘Tra’ catfish (Pangasianodon

hypophthalmus) in the Mekong Delta, Vietnam’

Bui, Thi Lien Ha

B.Sc, University of Natural Sciences, Vietnam

Biogeosciences

Faculty of Science and Technology FaST

Queensland University of Technology

Brisbane, Australia

Submitted in fulfillment of the requirement of the degree of Master of Science

September 2011

ii

Abstract

Sutchi catfish (Pangasianodon hypophthalmus) – known more universally by the

Vietnamese name ‘Tra’ is an economically important freshwater fish in the Mekong

Delta in Vietnam that constitutes an important food resource. Artificial propagation

technology for Tra catfish has only recently been developed along the main

branches of the Mekong River where more than 60% of the local human population

participate in fishing or aquaculture. Extensive support for catfish culture in general,

and that of Tra (P. hypophthalmus) in particular, has been provided by the

Vietnamese government to increase both the scale of production and to develop

international export markets. In 2006, total Vietnamese catfish exports reached

approximately 286,602 metric tons (MT) and were valued at 736.87 $M with a

number of large new export destinations being developed. Total value of production

from catfish culture has been predicted to increase to approximately USD 1 billion

by 2020. While freshwater catfish culture in Vietnam has a promising future,

concerns have been raised about long-term quality of fry and the effectiveness of

current brood stock management practices, issues that have been largely neglected

to date.

In this study, four DNA markers (microsatellite loci: CB4, CB7, CB12 and CB13) that

were developed specifically for Tra (P. hypophthalmus) in an earlier study were

applied to examine the genetic quality of artificially propagated Tra fry in the Mekong

Delta in Vietnam. The goals of the study were to assess: (i) how well available levels

of genetic variation in Tra brood stock used for artificial propagation in the Mekong

Delta of Vietnam (breeders from three private hatcheries and Research Institute of

Aquaculture No2 (RIA2) founders) has been conserved; and (ii) whether or not

genetic diversity had declined significantly over time in a stock improvement

program for Tra catfish at RIA2. A secondary issue addressed was how genetic

markers could best be used to assist industry development. DNA was extracted

from fins of catfish collected from the two main branches of the Mekong River inf

Vietnam, three private hatcheries and samples from the Tra improvement program

at RIA2.

iii

Study outcomes:

i) Genetic diversity estimates for Tra brood stock samples were similar to, and

slightly higher than, wild reference samples. In addition, the relative contribution by

breeders to fry in commercial private hatcheries strongly suggest that the true Ne is

likely to be significantly less than the breeder numbers used; ii) in a stock

improvement program for Tra catfish at RIA2, no significant differences were

detected in gene frequencies among generations (FST=0.021, P=0.036>0.002 after

Bonferroni correction); and only small differences were observed in alleles

frequencies among sample populations.

To date, genetic markers have not been applied in the Tra catfish industry, but in the

current project they were used to evaluate the levels of genetic variation in the Tra

catfish selective breeding program at RIA2 and to undertake genetic correlations

between genetic marker and trait variation. While no associations were detected

using only four loci, they analysis provided training in the practical applications of

the use of molecular markers in aquaculture in general, and in Tra culture, in

particular.

iv

TABLE OF CONTENTS

Chapter 1. GENERAL INTRODUCTION ............................................................................. 1 1.1. Status of world fisheries and aquaculture ....................................................... 1 1.2. Role of genetics and population genetics in aquaculture ................................ 4 1.3. Genetic improvement - moving from wild to improved culture strains ............. 8 1.4. The Tra catfish culture industry in Vietnam ................................................... 10 1.5. Tra fry cohort production in private hatchery practices in the Mekong Delta . 12 1.6. Genetic marker applications in aquaculture .................................................. 15 1.7. Specific aims of the current study ................................................................. 18

Chapter 2. MATERIALS AND METHODS ........................................................................ 19 2.1. The Tra catfish selective breeding program at RIA2 ..................................... 19 2.2. Propagation of fry at 3 private hatcheries in the Mekong Delta ..................... 20 2.3. Sample collection .......................................................................................... 20 2.4. Genomic DNA extraction ............................................................................... 22 2.5. Genotyping procedures ................................................................................. 22 2.6. Data analysis................................................................................................. 23

Chapter 3. RESULTS ........................................................................................................ 25 3.1. Part A - Characterisation of genetic variation in cultured and wild populations of Tra catfish ........................................................................................................ 25

3.1.1 Pair wise linkage disequilibrium .............................................................. 26 3.1.2. Conformation to HWE results ................................................................ 26 3.1.3 AMOVA analysis of hierarchical differentiation within and among populations ....................................................................................................... 31 3.1.4. Genetic characterization of sampled Tra catfish culture stocks .............. 32

3.2. Part B - Assessment of the relative contribution by breeders to fry cohorts in three private hatcheries in the Mekong Delta ....................................................... 33

3.2.1. Estimation based on the number of males and females in the brood stock .......................................................................................................................... 34 3.2.2. Estimated number of males and females actually contributing to offspring, based on the results of pedigree analyses using CERVUS v3.0 software. ....... 35

Chapter 4. EVALUATION OF THE LEVELS OF GENETIC VARIATION IN THE TRA CATFISH SELECTIVE BREEDING PROGRAM AT RIA2 AND GENETIC CORRELATIONS BETWEEN GENETIC MARKER AND TRAIT VARIATION (% FILLET YIELD). .............................................................................................................................. 39

4.1. Introduction ................................................................................................... 39 4.2. Methods and Materials .................................................................................. 41 4.3. Results .......................................................................................................... 41

4.3.1. Levels of genetic variation in 3 generations in the Tra catfish selective breeding program ............................................................................................. 41 4.3.2. Genetic correlations between genetic markers and a production trait (% fillet yield) .......................................................................................................... 43

Chapter 5. DISCUSSION .................................................................................................. 47 5.1. Characterisation of genetic variation in cultured and wild populations of Tra catfish ................................................................................................................... 47 5.2. The relative contribution by breeders to fry cohorts in three private hatcheries in the Mekong Delta ............................................................................................. 50

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5.3 The levels of genetic variation in the Tra catfish selection breeding program at RIA2 and genetic correlations between genetic marker and trait variation (% fillet yield) ................................................................................................................................. 51 Chapter 6. GENERAL CONCLUSIONS ............................................................................ 52

6.1. Genetic Diversity in selected Tra catfish lines in cultured and a reference wild populations in the Mekong Delta of Vietnam ........................................................ 52 6.2. Individual brood stock contribution to fry cohorts in three private hatcheries in the Mekong Delta ................................................................................................. 53 6.3. Assessment of possible correlations among genotypes and trait quality ...... 54

REFERENCES .................................................................................................................. 55 APPENDICES ................................................................................................................... 62

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List of figures

Figure 1: Diagram of the structure of the catfish selective breeding program at RIA219 Figures 2: Gelscan images of genetic diversity in RIA2 34 brood fish samples (2a)

and from 3 private hatcheries (n=31) (2b) at locus CB 12; gelscan images of allelic diversity in high fillet yield individuals (2c) and of low fillet yield individuals (n= 24) (2d) at locus CB 12. .................................................... 24

Figure 3: Map of Mekong Delta identifying the main areas where Tra catfish are cultured (grey colour) ................................................................................ 34

Figure 4: Ne estimate for Hau brood fish contributions to offspring on day one and day two for individuals confidently assigned to specific parental pairs. ..... 37

Figure 5: Relative allele frequencies at the CB4, CB7, CB12 and CB13 loci in 3 generations of Tra catfish used in the selective breeding program. .......... 42

vii

List of tables

Table 1: Sample name, sample size, collection date and source of samples for the whole study. ............................................................................................... 21

Table 2: Primer sequence details of the four microsatellite loci screened ............... 23 Table 3: The potential for null alleles for each locus by sample detected using

MICRO-CHECKER..................................................................................... 25 Table 4: Observed and expected heterozygosities (Obs. And Exp, respectively),

probability value (P-value) and standard deviation (sd). Significant deviations from HWE indicated as heterozygote deficiency (def), heterozygote excess (excess) or not significant (ns) after Bonferroni correction. .................................................................................................. 27

Table 5: Microsatellite polymorphism in 7 sample populations of wild and cultured Tra catfish populations. .............................................................................. 30

Table 6: The statistical significance of FST values of population differentiation ...... 31 Table 7: Statistical significance of FST values (the significance of population) among

sample pairs. P values that were significant after Bonferroni correction (α (Bonf) = 0.05/number of test = 0.05/ 21 = 0.002) are highlighted ............... 32

Table 8: Estimation of Ne in three private hatcheries based on the number of male and female brood stock .............................................................................. 35

Table 9: Parentage assignment rate of 3 groups of brood fish and 3 groups of fry . 36 Table 10: Genetic correlations between genetic marker and % fillet yield phenotypic

classes ....................................................................................................... 44

viii

Statement of Original Authorship

The work contained in this thesis has not been previously submitted for a degree or

diploma at any other higher education institution. To the best of my knowledge and

belief, the thesis contains no material previously published or written by another

person except where due reference is made.

Signed:

Date: 09/ 09 /2011

ix

Acknowledgements:

Special thanks to my supervisors Professor Peter Mather and Dr David Hurwood

(Discipline of Biogeosciences, Queensland University of Technology) for their

mentorship and kindness. Thank you to Vincent Chand for laboratory assistance

and technical support. I especially would like to thank my good friend Eleanor

Adamson for all her help and encouragement throughout my time in Australia. I

would also like to thank all my friends in Biogeosciences at QUT.

1

Chapter 1. GENERAL INTRODUCTION

1.1. Status of world fisheries and aquaculture

Fish and other aquatic organisms produced in aquaculture have become a major

world food production system that has been called on increasingly to fill the gap

between demand for, and supply of, seafood products for human consumption

(Knibb 2000; Lymbery 2000). Fish produced from culture provide an important

human food resource and can reduce pressure on wild fish stocks in the natural

environment (Lymbery 2000; Primmer, 2005). Aquaculture moreover, is now a key

industry and plays an increasingly important role in global fish production and to

meet rising demand for fish and seafood as many wild fish stocks have declined

over recent decades (Dunham 2000). Under pressure for increased production of

seafood and the need to develop more productive culture strains, many aquaculture

industries are trialling new stock management approaches and attempting to

improve their stock quality (Subasinghe et al. 2000). Development of sustainable

aquaculture production systems that are economically viable and that provide

incomes and livelihoods for poor people in many parts of the globe, is an important

goal in many developing regions around the world.

A number of approaches are being implemented worldwide currently to assist

aquaculture development and to promote a move away from a major reliance on

wild fish resources. They include application of traditional stock improvement

practices (domestication, crossbreeding, hybridisation and artificial selection) that

can deliver more productive culture stocks. This change has required application of

a variety of new technologies including identification of Quantitative Trait Loci

(QTLs), Marker Assisted Selection (MAS) and development and application of

genetic markers among others. The combination of application of traditional

breeding practices with appropriate molecular technologies has been demonstrated

in some aquaculture species to deliver significant productivity increases for culture

industries (Dunham 2000). For example, gene maps are now available for some

important aquaculture species, notably. Channel catfish, tiger shrimp, Japanese

flounder, rainbow trout and Atlantic salmon (Liu 2004).

2

Aquaculture Genetics is a relatively new science in many parts of the world, but

where it has been applied it is transforming the performance traits of many cultured

organisms and moving the industry towards enhanced sustainability. For example,

development of the Kansas strain of Channel catfish (Ictalurus punctatus) provides

an excellent example of the potential that applied genetics can offer. This fish is the

oldest domesticated strain of Channel catfish having spent more than a century in

culture. During domestication, growth rates of this strain have increased 3 to 6% per

generation in culture while growth rates of crossbred strains of both Channel catfish

and rainbow trout are 55% and 22% higher, respectively (Dunham 2000). Other

examples include: positive heterosis identified in carp crossbreeds in Israel,

Vietnam, China and Hungary (Moav et al. 1964; Moav and Wohlfarth 1974; Nagy et

al. 1984; Wohlfarth 1993; Hulata 1995); Common carp crossbred lines in Hungary

have shown almost 20% improvement in growth rate compared with pure lines while

a Vietnamese x Hungarian common carp crossbreed is now particularly popular,

due to fast growth and high survival rates under a variety of production

environments; in Bangladesh, a crossing program was instituted for three carp

strains referred to as “Bangladesh”, “Thailand” and “Indonesian” with growth rates

of females from six inter-strain crosses reported to be 23% higher for average

growth rate compared with parental strains (Dunham 2000).

A stock improvement program for European catfish, Silurus glanis, has produced a

culture strain that can tolerate warm water conditions and that can accommodate

mixed diet feeding systems that was achieved via a crossbreeding approach

(Krasznai and Marian 1985). Another example where improved culture lines have

been developed is for walking catfish, Clarias macrocephalus, where improved

tolerance of Aeromonas hydrophila infections was developed by careful application

of a breeding program directed at genes that influence resistance traits (Prarom

1990).

The earliest modern genetic selection program directed at an aquatic species was to

improve survival rate in brook trout (Salvelinus fontinalis), a species that was

susceptible to endemic furunculosis and this program was initiated in the 1920s.

The outcome of this program was to increase survival rate from 2% to 69% after

three generations of artificial selection. Later in 1932, simple selection approaches

were applied to improve the growth rate and fecundity of rainbow trout

3

(Oncorhynchus mykiss) in culture (Donaldson and Paul 1957). After 35 years of

direct individual selection, this strain is now widely cultured in the USA and more

widely in other regions across the world (Parsons 1998 cited in Hulata 2000). In

Norway, large stock improvement programs were initiated for Atlantic salmon and

rainbow trout in 1971 and these programs have achieved genetic gains estimated to

be 10 to 15% per generation over the first two generations. Following this, growth

rate and age at sexual maturation traits were targeted from the fifth generation, and

in later generations, disease resistance and meat quality traits were subjected to

artificial selection (Gjedrem 2000). The selected Atlantic salmon culture strain in the

fourth generation showed 77% faster growth rate than control wild fish from the

Namsen River. In 1993, Kirpichnikov reported the outcome of a breeding program in

common carp that employed mass selection to improve resistance to dropsy and

that increased growth rate in Krasnodar in the former Soviet Union (Hulata 2001).

A genetic selection program on gilthead sea bream (Sparus aurata) was also

successful with single-pair offspring groups (full- and half-sibs) employed to improve

production traits (Knibb et al. 1997a). The most widespread fish cultured in Asia

today is a genetically improved strain, the GIFT tilapia (Genetic Improvement of

Farmed Tilapia) and increasingly male hybrid tilapia stocks are also produced widely

(Subasinghe 2000). Several studies have reported, for tilapia strains (Oreochromis

mossambicus, red tilapia, O. aureus and O. niloticus) that mass selection can

improve body weight significantly. Family selection for improved growth rate in the

GIFT Nile tilapia has achieved 77% to 123% improvement with an 11% genetic gain

achieved per generation (Padi 1995).

Carcass quality and percent fillet recovery traits have also been targeted for

improvement in salmonids and catfish (Dunham 1996a). In Thailand, selection for

improved growth rate and disease resistance are currently being trialled for a

number of important native and exotic culture species including pangasiid

freshwater catfish (Pangasius sutchi, syn. of P. hypophthalmus), rohu (Labeo

rohita), Thai walking catfish (Clarias macrocephalus), Java barb (Barbodes

gonionotus), bighead carp (Aristichthys nobilis) and Asian rock oyster (Saccostrea

cucullata) (Dunham 2000). In Australia, genetic improvement programs have been

trialled recently for Pacific oyster (Crassostrea gigas) and Sydney rock oyster

(Saccostrea glomerata). Haley et al. (1975) reported on selection in a related oyster

4

species, C. virginica, where adult oysters showed an apparent strong response to

mass selection to improve growth rate (Dunham 2000).

More recently, selection responses reported for body weight at harvest size using a

mass selection approach conducted on Channel catfish (I. punctatus) were high with

genetic gains of 29% for the Kansas strain and 21% for the Marion strain with

associated heritability values of 0.16 and 0.23, respectively (Rezk et al. 2003).

Over the years however, traditional approaches for improving culture stocks have

faced a number of serious challenges with both a decline in the quality of important

production traits and erosion of the response to selection becoming significant

issues for the industry (Knibb 2000; Lymbery 2000). Of increasing interest also are critical concerns about the threats to genetic diversity levels in cultured fish

populations and why there is high risk associated with erosion of exploitable

variation in culture. Understanding the unique attributes of many aquatic species

that make them potentially much more vulnerable to rapid loss of genetic diversity in

culture compared with their terrestrial live stock counterparts will be critical to

developing better breed improvement programs that can assist new aquaculture

industries in many parts of the world.

1.2. Role of genetics and population genetics in aquaculture

Genetic variation or genetic diversity in a population consists of the heritable

information contained in the genome of any population of a species (Kottelat and

Whitten 1996). It describes the diversity of different alleles, or alternative forms of a

given gene that can be found in the target population. Genetic variation implies

presence in individuals in a population of different alleles that if expressed, may

produce a variety of phenotypes. In theory this variation will reflect a population’s

ability to adapt to changes in its environment (Gjedrem 2005). While individuals in a

population cannot predict future environmental change, the more variation that

exists in their collective genomes, the better placed a population will be to adapt to

change if and when it occurs. Thus variable populations will generally respond

better than non-variable ones to environmental change because more exploitable

variation remains.

5

In aquaculture, where relatively small brood stock populations are often maintained

separately, the genetic constitution of farmed fish stocks can change rapidly over

just a few generations and where populations are small they will tend to lose genetic

variation rapidly (Gjedrem 2005). This is a critical issue in aquaculture, because

achieving genetic gains from a selective breeding program will ultimately depend on

there being sufficient genetic diversity present in the original brood stock (Yu and Li

2007). The amount of genetic variability present in a target population will ultimately

be influenced by diversity levels in the parental stock and the mating system

employed. Genetic variation is essential for population persistence because

populations with higher levels of genetic diversity have greater adaptive potential

and hence provide the best resources for selective breeding programs (Kottelat and

Whitten 1996, Mable and Adam 2007).

Many studies conducted on a variety of different cultured aquatic species including

brown trout – Salmo trutta (Aho et al. 2006), catla – Catla catla (Alam and Islam

2005), rainbow trout – Oncornhynchus mykiss (Pante et al. 2001), black tiger shrimp

– Penaeus monodon (Xu et al. 2001), sole – Solea senegalensis (Porta et al. 2006)

and Pacific white shrimp – Penaeus vannamei (Moss et al. 2008) have reported

ongoing declines in genetic variation over generations during the very early stages

of domestication with some even reporting complete population homozygosity. In

some instances, virtually all of the natural levels of variation can be lost as a result

of poor stock management practices, so this has become an important issue for

aquaculture.

Aquatic species, unlike most terrestrial farmed livestock species, are particularly

vulnerable to rapid loss of genetic diversity because of inherent characteristics that

are very different to their terrestrial counterparts. First, most aquatic species used in

culture are highly fecund, producing large numbers of gametes per individual with

females often capable of producing millions of eggs in a single mating event. While

survival of fertilised eggs in the wild is usually extremely low (90%) in culture. Thus large numbers of offspring can be

generated form even a single mated pair in culture situations. This is important for

hatchery managers because it means that they often require only a few breeders to

generate all the fry or larvae they will need to meet demand. This immediately

creates problems with conserved genetic diversity levels because while fry/larvae

6

numbers may be very high (a good outcome for breeders due to the reduced costs

of producing them), diversity can be low compared with equivalent wild-spawned

offspring cohorts where individual survival rates are often very low.

Where effective population size (Ne) is low, genetic drift and inbreeding can rapidly

erode population levels of genetic diversity and change gene frequencies without

regard to their adaptive potential. Ne is defined as "the number of breeding

individuals in an idealized population that would show the same amount of

dispersion of allele frequencies under random genetic drift or the same amount of

inbreeding as the population under consideration” (Hallerman 2003). Another way of

understanding the concept is that effective population size refers to the number of

individuals that contribute genes in equal proportions to the next generation

(Bensten and Gjerde 1994, Doyle et al. 2001, Bensten and Olesen 2002, Yu and Li

2007). Effective population size is usually considered to be a significant parameter

in many population genetics models and in practice effective population size is often

much smaller than observed population size (N) (Brown et al. 2005, Primmer 2005).

As an example, while there are estimated to be 2000 mature individuals of winter

chinook salmon (Oncorhynchus tshawytscha) in the Sacramento River in California,

the Ne of this population has been estimated to be as low as 85 breeding individuals

each reproductive cycle (Bartley et al. 1992). Japanese flounder, Paralichthys

olivaceus, provides another illustration of Ne

7

Population genetics is a field of biology that studies the genetic composition of

biological populations (allele frequency distributions) and the changes in genetic

composition that result from evolutionary forces of which natural selection, genetic

drift, mutation and gene flow are considered to be the major ones that influence

gene frequencies in both natural and cultured populations (Hartl and Clark 1997,

Hallerman 2003). Important applications of population genetics in fisheries and

aquaculture have included delineation of wild stock structure, identification of

breeding units, generating theoretical estimates of effective population size,

assessment of inbreeding rate and documenting levels of genetic variation in target

populations (Tave 1993; Gjedrem 2005).

Population genetic methodologies when applied appropriately in aquaculture can

help to address issues associated with negative impacts of animal husbandry

practices that have the potential to severely impact levels of genetic diversity and

hence cause loss of fitness in cultured aquatic populations. The genetic risks

associated with the domestication process employed to produce fish artificially has

also become an important issue in recent times. Many farmed fish strains have

relatively low levels of genetic variation compared with their wild progenitors

(Hansen et al.1997; Yu and Li 2007). If this causes a decline in stock productivity,

then inbreeding depression (where alleles of low fitness may accumulate in the

stock due to combined impacts of genetic drift and inbreeding) has often been

implicated as a major causal factor. The use of only a limited number of broodstock

can potentially lead to high population levels of inbreeding and consequently cause

rapid declines in population genetic diversity levels. This can be reflected in random

changes in frequency or even total loss of critical alleles responsible for important

production traits (Gaffney 2006). The importance of maintaining high levels of

genetic variation in any brood stock is now appreciated more widely and is

considered to be essential for a stock’s long-term sustainability and productivity

(Mustafa 2003). Small effective population size, line breeding or close relative

mating, are all factors that can contribute to increased levels of inbreeding and

ultimately may result in inbreeding depression; therefore, to limit this potential effect,

where possible animal breeders should maintain pedigree records for their brood

stock. This practice, will allow development of strategies that contribute to

maintenance of a sustainable base population for culture (Reisenbichler and Rubin

1999).

8

Understanding the individual attributes of aquatic animal species used in culture,

especially their genetic characteristics, will support science and aquaculture to

provide better solutions to current problems. Thus traditional stock improvement

approaches in aquaculture and modern genomics can benefit from population

genetic theory and methodologies that identify, monitor and conserve genetic

diversity in culture lines.

1.3. Genetic improvement - moving from wild to improved culture strains

Genetic stock improvement programs provide a powerful means for enhancing both

preferred qualitative and quantitative traits in any cultured population (Eknath et al.

1998). Stock enhancement in essence, aims to increase the biomass of the target

species with little or no disadvantageous impacts on native gene pools (Ward 2006).

Maintaining genetic quality in fish stock management is now therefore considered to

be a priority for many aquaculture sectors (Lymbery 2000). While in general, stock

improvement can be used to enhance the majority of desirable traits in seed stocks

(Allan 1999), in reality, however, this practice is often difficult and requires long-term

effort from a large number of scientists with access to appropriate technologies,

facilities and adequate financial support (Hulata 2001; Knibb 2000). Genetic

improvement involves making decisions about which individuals to mate (selection)

and how to mate them in the most optimal way (mating systems) (Allan 1999), while

stock improvement is the ability to select brood stock individuals with an appropriate

combination of superior breeding values for selected economic traits (William 1991).

This outcome will result from fully understanding the genetic variation present in a

stock and applying sound breeding practices. Developing genetically improved

stocks however, requires a complex link between theory and practice and so

requires understanding both an individual’s biological and genetic backgrounds. The

objective of selection is to improve the stock genetically by increasing the frequency

of desirable genes (alleles) while decreasing the frequency of less-desirable ones

(Allan 1999). This needs to occur without significantly eroding exploitable genetic

variation levels to a point where any future response to selection may be

compromised. Additionally, while the focus is on optimizing favourable alleles, this

needs to be achieved without increasing the inbreeding rate to a point where

inbreeding depression may result (Davis and Hetzel 2000).

9

Genetic improvement programs in farmed aquatic species around the world for the

most part, have been very successful (Knibb 2000). The power of genetic programs

is to change a cultured stock attributes to fit a purpose or production environment.

Records of genetic enhancement activities were evident in terrestrial agriculture

from the time early humans first made the transition from being hunter-gatherers to

farmers and producers. These achievements not only solved problems associated

with obtaining necessary food resources but also reduced the risk of loss of wild

genetic diversity (Booke 1999). In particular, genetic enhancement can provide

solutions to ongoing emergence of pathogens and parasites in high-density culture

that often result in serious new disease outbreaks. Good genetic management and

selection of strains that are resistant to important pathogens have the potential to

address this emerging problem (Chevassus and Dorson 1990). Furthermore, stock

enhancement can open up new profit opportunities for companies and export

industries.

In fisheries and aquaculture, genetic improvement and stock enhancement efforts

continue to create new opportunities (Liao et al. 2004). Increased demand for

aquatic products together with the significant contribution that aquaculture can make

to world food resources makes the role of genetic stock enhancement an emerging

practice in aquaculture, worldwide (Mustafa 2003). A decade ago, genetically

improved fish and shellfish contributed only around 1% to total global aquaculture

production (Gjedrem 2000); of which only a few species made the major contribution

to this component e.g. 75% of Penaeus japonicus farm stock in Australia were

genetically improved (Hulata 2001). According to well-documented records (Hulata

2001), effective aquatic stock enhancement programs are still in the pioneering

stage and only a limited number of species have been addressed intensively to

date, mostly in developed countries especially Atlantic salmon in Norway and

Channel catfish in the USA.

More recently, a long term and large-scale breeding program was initiated for

Channel catfish (Ictalurus punctatus) and after three generations of selection the

program achieved a 10-20% gain in growth rate per generation (Mahmound et al.

2003). Genetic stock improvement via artificial selection has also been successful in

several other breeding programs including in a cultivated strain of Penaeus

(Litopenaeus) vannamei (Donato et al. 2005), that was then used for stock

enhancement of depleted wild populations (Davenport et al. 1999), There is also a

10

long history of stock enhancement in Japan for three finfish species: Japanese

flounder (Paralichthys olivaceus), red sea bream (Pagrus major) and black sea

bream (Acanthopagrus schlegeli) (Fushimi 2001). Moreover, some aquaculture

stock improvement programs in developing countries have achieved positive

outcomes over the past few decades for silver barb (Barbodes gonionotus) selected

for better growth performance in Bangladesh (Hussain et al. 2002) and a

commercial crossbreeding program for common carp in Vietnam (Thien and Thang

1993). Thus, the evidence is clear, where well-designed stock improvement

programs have been implemented for aquatic species, genetic gains can be rapid

and can enhance industry development. Genetic gains from breeding programs for

aquatic species often produce much more rapid gains than equivalent programs in

terrestrial species because genetic variation levels in broodstock are often quite

high as they have only recently been sourced from the wild while terrestrial species

have been domesticated for 100s if not 1000s of generations by humans.

In the current study Pangasianodon hypophthalmus referred to as Tra catfish was

the target species and this species has become a key export industry in Vietnam.

While the Tra catfish culture industry in Vietnam is quite young, it now contributes

significantly to export revenue there, but also the industry is a significant provider of

employment for many poor farmers most importantly, in the Mekong Delta region.

1.4. The Tra catfish culture industry in Vietnam

Two Vietnamese catfish species (Pangasianodon hypophthalmus – Tra) and

(Pangasius bocourti – Basa) are native freshwater fishes that are common and

widely distributed across the Mekong Delta in Vietnam. Both species constitute very

important food fishes in the region (Trong 2007) and occur naturally in both main

branches of the Mekong River. P. hypophthalmus and P. bocourti provide major

protein resources and livelihoods for many rural households particularly during the

flood season. Originally, catfish culture in Vietnam was small-scale and was

generally poorly organized such that most fish were used only for family or local

domestic consumption. Only low quantities were produced in culture and

management of quality was essentially absent. Over a number of decades, a

number of long-term trials were undertaken to close the life cycle of both species in

hatcheries and practices were developed simultaneously by a number of

Vietnamese research institutes, in the south of Vietnam (Mekong Delta) in particular

11

by Trinh et al. (2002) that allowed production of catfish fry in sufficient quantities to

support development of a large culture industry. From this simple beginning, culture

of P. hypophthalmus and P. bocourti has gradually become a significant economic

driver and a key income generator for thousands of poor households in the Mekong

Delta.

Covering approximately 40,000 square km and possessing a large young population

of approximately 17 million, the region accounts for 21% of Vietnam’s population

and more than 60% of people participate in fishing there. In 2006, the Vietnamese

fisheries sector accounted for an estimated 6.1% of Gross Domestic Product (GDP)

producing US$ 3.4 billion in export revenue (Nortvedt 2007). Recently, P.

hypophthalmus and P. bocourti were selected to become Vietnam’s aquaculture

product trademark, as cultured catfish has become a major export product.

Following a recent trade war however, the Vietnamese government adjusted

aquaculture export strategies and supported policies for protecting local fish

farmers, processing and export plants. The Vietnamese government has also

recently contributed significantly to, and promoted expansion of, catfish aquaculture

in the Mekong Delta and now sees the industry as playing a major role in social and

economic development for the nation (Monti et al. 2006).

Over recent years, Vietnamese catfish producers have successfully established and

expanded export markets that ensure annual export targets are met. In parallel, the

industry has decreased dependence on the US export market, and has diversified

the variety of available catfish products (Tung et al. 2004). In 2006, the largest

export destinations for Tra and Basa catfish were European countries with export of

123,212 metric tons (MT) worth approximately US$ 343.4 million per annum,

followed by Russia with 42,779 MT estimated value at US$ 83.2 million per annum,

while the American market accepted only 24,281 MT producing US$ 72.9 million per

annum while Australia consumed 10,149 MT valued at US$ 31.0 million per annum.

Thus total catfish exports in 2006 were approximately 286,602 MT valued at a total

of US$ 736.87 million per annum (Nortvedt 2007). Increasing popularity of

Vietnamese catfish in the international aquaculture market reflects recent significant

improvements in product quality. Today more than 60 processing plants have been

developed across the Mekong Delta that produce a variety of catfish products

compared with only eight plants that existed in 1997 (Monti et al. 2006). As a

12

consequence, of all fish cultured in Vietnam, catfish now accounts for approximately

80% of exported fish product. Vietnamese catfish production has shown a 36-fold

increase in production since 1997 and this is linked to an increase of 40% in export

of frozen fillets. This now results in a total production of over 825,000 MT

(Lobegeiger 2007), most now going to high value consumers in developed countries

outside Asia.

1.5. Tra fry cohort production in private hatchery practices in the

Mekong Delta Results of a survey by Yen and Trieu (2008) of 30 catfish hatcheries in the Mekong

Delta showed that the majority of brood stock used to produce fry were sourced

from first or second generation domesticated stock. Most hatchery owners possess

only low educational levels rarely above high school level. Initially, most hatchery

owners employed staff with only simple technical training in hatchery techniques

that had been learnt from government extension training programs. From this basic

starting point, practices used in hatcheries were established and now most hatchery

owners undertake their own fry production. In general, two to ten people are

employed in most hatcheries, with the majority being family members. The number

of brood stock held by each hatchery ranges from approximately 100 to over 1000

individuals depending on the hatchery size. For example, one large hatchery in the

Mekong Delta holds approximately 1,700 brood fish (estimated 4 kg each) with a

capacity to produce more than 200 million fry per year (Hung et al. 2008). 47% of

the 30 hatcheries surveyed had collected their brood fish from the wild while 30%

had obtained brood fish from other hatcheries and 23% routinely obtained their

brood fish from both sources. In terms of broodstock management practices,

approximately 73% of hatcheries regularly sourced their brood fish from commercial

grow out ponds, 17% kept their own fry to become brood fish and only 10% of

hatcheries used wild fish to replenish their brood stock supplies (Yen et al. 2008).

While brood stock age varied, most were less than 7 years old while 70% of brood

fish were younger than 5 years because the best reproductive age is 3 to 5 year old

fish with an average weight of 3 to 5 kg. With this approach, brood stocks are

usually replaced every 2 to 3 years. 40% of hatcheries replace brood fish every

year, 60% of the remaining hatcheries have more than two generations of brood fish

while a single hatchery maintains 4 generations of brood fish (Yen and Trieu 2008).

13

Fish used as brood stock are tagged on their head with a mark and kept separately

in small concrete ponds while two of the 30 hatcheries screened did not tag their

brood stock (Yen and Trieu 2008). Artificial propagation of Tra catfish is carried out

by each farmer where they use sperm from a single male to fertilize 3-5 females

each cycle with an average estimated 120,000 egg/kg female. Some hatcheries mix

the sperm from multiple males to increase their fertilization rate. Almost all of the

hatcheries surveyed produce fry for commercial sale directly, but a few also keep up

to 12.5% for nursing to a larger size before sale. Number of hatchery runs (batches)

varies from 17 to 19 times per year and each brood stock individual is spawned two

to four times per year using a sex ratio of one male to four females. When asked to

comment on fry quality, 70% of Tra hatchery owners considered that fry from

artificial propagation were better or at least of equal quality to fry spawned from wild

brood fish. This is the major reason why 60% of hatchery owners routinely source

their brood fish from their own ponds while only 10% of owners believe that use of

wild fish contributes to better quality fry. A diversity of different breeding practices

have been adopted by hatchery owners from use of only a single pair of fish to

combining batches of fry from multiple crosses to sourcing fry from neighbouring

provinces (Yen and Trieu 2008, Hung et al. 2008). Hatchery owners were surveyed

about issues associated with levels of inbreeding in their hatcheries, with only 40%

responding that they knew that mating related fish can increase the inbreeding rate

and this can affect fry quality; 56% said it was not necessary to consider genetic

relationships among brood fish when producing fry for culture.

During field sampling of brood stock from three private hatcheries in the Hong Ngu

district of Dong Thap Province, specific details of practices in hatcheries were

documented. Two hatchery owners possessed high school level training and the

third was a local aquaculture official. Each produced fry in their hatcheries

themselves and employed 3-5 of their relatives (to assist). Assistants in hatcheries

were also employed elsewhere as teachers or rice farmers or were otherwise

unemployed. Each hatchery had approximately 500 to 1,000 brood stock cages

along the river or brood stock were held in earthen ponds behind houses. No

information was available however, about the number of brood stock used regularly

for spawning, or whether all fish were used to produce fry. Common practice was to

initiate artificial propagation using 40-80 female and 5-10 male brood fish for each

cycle. Before each batch, brood stocks were selected based on visual inspection; if

14

they possessed good phenotypes and were healthy. For the initial spawning in each

batch, hatchery owners used about 10-15 quality fish with an average weight of 2-3

kg/individual that were ready to spawn. All eggs were collected from 10-15 females

into a plastic basket and combined with milt from 2-3 males. A single female was

used for 3 to 4 repeat spawns per year and after 2-3 years; individuals were

replaced. In some instances, hatchery managers employed brood fish from other

hatcheries or even wild fish obtained from Cambodia. Most hatchery owners were

quite secretive about their practices and often will not cooperate with government

officials or volunteer information because they think it is not essential and do not like

their business practices being scrutinised. Only a very few owners were interested

in genetic or inbreeding issues with their stocks or saw the relevance of these

issues to their operations.

Provision of appropriate support can allow cultured catfish from Vietnam to become

as well-known an aquaculture brand as has been achieved for Norwegian salmon.

Recent strategies employed in the Mekong Delta industry have increased the catfish

breeding area to 10,200 ha with 1,900 fish cages to be introduced by late 2010 with

a total capacity now exceeding 860,000 MT in output. Export targets predict a

potential production of 230,000 MT of Tra and Basa catfish fillet, earning 600 million

USD in 2010 and this is forecast to increase to 460,000 MT with an estimated

turnover of 1.2 billion USD by 2020 (TheFishSite). There are many reasons why the

catfish culture industry in Vietnam has expanded so rapidly including: the industry

has addressed specific demands from foreign consumers, Pangasius catfish culture

makes an important contribution to household incomes and Vietnam’s export

income has grown and increased employment opportunities in the Mekong Delta.

Improving the quality and productivity of Tra and Basa aquaculture is now seen as a

significant opportunity for Vietnam and if issues are addressed appropriately this will

allow the industry to continue to expand. Currently, virtually nothing is known

however, about how existing management practices of cultured catfish stocks in

Vietnam are impacting levels of genetic diversity. Understanding what impacts (if

any) have occurred will allow better breeding practices to be designed in the future,

if they prove necessary.

15

1.6. Genetic marker applications in aquaculture

Exploiting advanced genetic marker technologies can be useful at three levels for

management of aquatic species: i) for detecting simple inherited traits; ii) finding loci

that affect variation in quantitative traits; and iii) for assisting with optimizing

selective breeding outcomes based on marker assisted selection. Examples where

markers have applications in aquaculture include: gene mapping, identification of

sex, individual identification and parentage assignment, population genetic

applications, detecting effects of selection and trans-genesis (Lo Presti 2009).

For example, the basic objective of gene mapping studies is to elucidate the location

of functional genes responsible for important performance and production traits

(Davis and Hetzel 2000; Liu 2006). The position of gene loci encoding simple

inherited characteristics can be located in the genome of a target species by

analysing correlations between allelic variation in families that co-segregate with

markers after linkage analysis (Georges 1998 cited in Davis and Hetzel 2000). Once

identified, gene markers allow screening of parents and progeny and development

of a diagnostic test such as the simple genetic markers used widely for human

disease diagnostics (Hartl and Clark 1997). Many genomics projects have used

microsatellite markers to develop aquaculture databases for target species. For

example, in Europe, there are a number of genetic improvement programs that have

developed more than 100 microsatellite markers for species such as common carp

(Cyprinus carpio), approximately 1,700 microsatellites for Atlantic salmon (Salmo

salar), and more than 250 microsatellites for European sea bass (Dicentrarchus

maximus). Other important species in European aquaculture include flat oyster,

lobster, and Atlantic cod where more than 50 microsatellite markers are available for

each species (Blohm et al. 2006). A very large and long-term project is applying

genetic markers (based on microsatellites) to developing a saturated linkage map

for Channel catfish (Ictalus punctatus). Several hundred microsatellite markers have

been developed over the recent decade for both Channel and blue catfish families

by Liu et al. (2006) and these will contribute to the resulting linkage map. Another

study of Channel catfish developed 293 microsatellite markers to add to the growing

genetic linkage map (Geoffrey et al. 2001). To date, two genetic linkage map

frameworks have been published for the species. The first map developed by

16

Waldbieser et al. (2001) was established using Channel catfish intra-specific

resource families, and the other was initiated by Liu et al. (2003) using Channel

catfish X blue catfish inter-specific families (Liu 2006). Linkage maps for salmonids

are also under construction with over 228,000 bacterial artificial chromosome (BAC)

clones fingerprinted from Atlantic salmon (Liu 2006). Tilapia, oysters, shrimps and

striped bass are other species where concentrated efforts are being made to map

each species’ entire genome (Liu 2006).

Identification of sex of cultured individuals can also be important in some aquatic

species because one sex may perform better when produced in monosex culture

stocks, an example being culture of all-male freshwater prawn (Macrobrachium

rosenbergii) (Sagi et al. 1998) or Nile tilapia (Oreochromis niloticus niloticus)

(Angienda et al. 2000). Discrimination of phenotypic sex can be quite difficult in the

early larval stages for many aquatic species, but molecular genetics has proven to

be very effective at addressing the problem via detection of sex-linked DNA markers

in different species (Devlin and Nagahama 2002).

For individual identification and parentage assignment, genetic markers can not only

solve problems associated with physical tags that are often difficult or even

impossible to apply in juveniles or farmed molluscs etc. but also significantly

decrease the cost and time required to keep different families in separate ponds, a

process that also limits the number of animals available for selection (Lymbery

2000, Bentsen and Olesen 2002, Liu and Crodes 2004). In parentage analysis,

genetic markers can identify individuals effectively using distinct genotypes from

allelic diversity and allele frequency data. Once genetic information is available for

parental pairs (sires and dams) and their offspring, breeders can construct simple

pedigrees (Martinez 2007). Individual identification combined with pedigree data,

allow the researcher to identify individuals and their genetic relationships to select

those with the best breeding values (Bentsen and Olesen 2002). This can help to

estimate selection response and to optimise breeding parameters (Zhang et al.

2006).

In selection programs, molecular markers can be used to identify genetically

superior individuals; this process is referred to as marker assisted selection (MAS).

17

MAS or genome wide marker assisted selection (G-MAS) is a selection process in

which specific candidate genes are identified based on genotypes using molecular

markers (Liu and Crodes 2004) and results from the use of gene markers linked to

QTLs in genetic improvement programs (Davis and Hetzel 2000). To employ MAS,

researchers need to have a clear and high-density linkage map and to understand

comprehensively the number of QTLs that affect each phenotypic characteristic,

their mode of inheritance and potential interactions of different QTLs on traits and

the economic characteristics of the traits studied (Poompuang and Hallerman 1997

cited in Liu and Crodes 2004). MAS in general, is applied mostly to traits that are

otherwise difficult or expensive to measure and QTLs are loci that exert a major

influence on important quantitative traits. Many commercially important traits that

show continuous variation (quantitative traits) are generally influenced by a group of

genes of small additive effect (Falconer 1989). In genetic improvement programs,

QTLs are evaluated as complementary to breeding value estimates of genetic merit

(Davis and Hetzel 2000). QTLs are usually detected by combined analysis of

phenotypes with linked marker maps and they have been applied in a number of

aquaculture stock improvement programs because of their capacity to assist animal

breeders to reach specific breeding goals.

Some examples where molecular genetic approaches have been broadly applied in

genetic improvement programs include Appleyard and Ward (2005), who reported

that 8 microsatellite markers were useful in a mass selection program for Pacific

oyster (Crassostrea gigas) in Australia and New Zealand. Similarly, MacAvoy et al.

(2008) published 49 microsatellite primer sets for a selective breeding program in

the New Zealand GreenshellTM mussel (Perna canaliculus). Asian aquaculture

researchers have also contributed recently to world genetic databases. Eleven

microsatellites were developed to estimate kinship for brood stock management in

Japanese flounder (Paralichthys olivaceus) to minimise risk of inbreeding (Sekino et

al. 2004), while Wang et al. (2006) used 240 microsatellites to screen 24

chromosomes in the karyotype of Asian sea bass (Lates calcarifer), known locally

as Barramundi in Australia. They mapped 5 significant and 24 putative QTLs that

influenced individual body weight. A four-way tilapia cross in Israel also initiated a

linkage map for QTL studies of this important culture species. 20 microsatellites

were found to be associated with two significant QTL traits, one for cold tolerance

and the other for individual growth rate (Moen et al. 2004).

18

Currently, much effort and cooperation worldwide is directed at developing QTL

maps or MAS for specific aquaculture species. In Channel catfish, rainbow trout and

tilapias, QTL markers for growth, feed conversion efficiency, tolerance to bacterial

disease, spawning time, embryonic developmental rates and cold tolerance have all

been reported (LaPatra et al. 1993, 1996). In trout and salmon, a candidate DNA

marker linked to infectious haematopoietic necrosis (IHN) disease resistance was

also identified recently (Houston et al. 2008). Thus, genetic markers can assist

animal breeders to improve the quality of their culture stocks.

1.7. Specific aims of the current study

There were four aims in the current study:

i. To assess the genetic status of cultured Tra catfish (Pangasianodon

hypophthalmus) populations in the Mekong Delta of Vietnam,

ii. To evaluate the levels of genetic variation in the Tra catfish selective breeding

program at RIA2 after 3 generations and to estimate the effective population size

and other related genetic parameters in this population.

iii. To assess the percent contribution by individual breeders to fry cohorts and to

estimate effective population size and inbreeding coefficients in three private

hatcheries in the Mekong Delta,

iv. To trial genetic correlations between genetic markers and an important

production trait (fillet yield).

19

Chapter 2. MATERIALS AND METHODS

2.1. The Tra catfish selective breeding program at RIA2

A selective breeding program for Tra catfish commenced at the Research Institute

for Aquaculture No 2 (RIA2), Ho Chi Minh City, in 2001. Brood stock used were

obtained as fry produced from wild parents sourced from three private hatcheries–

Truong, Duong, and Ro (WP – TDR). After brood stock were raised for 3 years

(2004), fish were mated as families and tagged for breeding selection at RIA2. The

parental generation was referred to as the ‘P’ generation.

The selective breeding program at RIA2 was initiated to improve fillet yield in 2004.

In 2005, when F1 individuals were 8 months old, the average time to market size, all

individuals were measured. Each fish was measured for total length, weight, and

body depth. Following this, 30 individuals were chosen at random from a sample of

100 fish from each family and individuals were euthanized by professional filleters at

the Angiang catfish-processing plant to assess fillet metrics per family. After filleting,

each individual was weighed for total fillet yield and remaining body components.

Figure 1: Diagram of the structure of the catfish selective breeding program at RIA2

20

2.2. Propagation of fry at 3 private hatcheries in the Mekong Delta

In private hatcheries in the Mekong Delta, broodstock are selected as breeders

based on their individual growth performance. In some instances brood stock are

also sourced directly from the wild or are domesticated fish obtained from the

hatchery. Breeders are selected at approximately 2 years of age when they weigh

approximately 3 kg (Yen and Trieu 2008). Of the three hatcheries examined here,

two-employed wild caught brood stock from a local river (Khanh and Hau) while the

third hatchery employed only domesticated stock (Nam). For each fry propagation

cycle, approximately 40 females and 10 males were separated to become brood

stock for artificial spawning. Sperm from two or three males were employed

commonly to fertilize eggs combined from 8 females. Spawns were then pooled

together into a few large batches (depending on the number of eggs produced).

After hatching, newly spawned fry resulting from multiple batches were combined

automatically into a large single circular nursery tank. Samples for the current study

were then collected randomly on the first and second days after fry had hatched. On

the second day, remaining fry were sold to farmers. Samples of fins from all brood

stock individuals and a random sample of whole larvae from brood-tanks were

collected and stored in 70% ethanol at 4°C prior to DNA extraction and genetic

analysis.

2.3. Sample collection

Two groups of samples were available:

Group A (RIA 2 group): The first group comprised individuals from the catfish

selective breeding program at RIA2. This group consisted of 48 founder individuals

collected form the wild in 2001 (WP called TDR); 34 offspring from P (F1) that

contributed to reproduction events in 2005; and 120 selected individuals (F2) that

included 48 high fillet yield individuals, 48 low fillet yield individuals and 24 random

individuals (Controls) in 2006. In addition, 27 individuals were collected from the wild

as a reference sample of wild diversity levels and these individuals were sourced

from two branches of the lower Mekong River (HW: Hau River Wild = 20 fingerlings

and TW: Tien River Wild = 7 samples) in 2008 and 2009, respectively (see Table 1).

21

A small piece of fin tissue was removed from each adult fish and samples stored in

70% ethanol at 4°C prior to DNA extraction.

Group B (Private hatcheries group): The second group comprised individuals from

three private hatcheries: Hau, Nam and Khanh owned by smallholders in one of the

two main branches of the Mekong River and (Tien River) that produced fry cohorts

for commercial culture that were chosen for the study in 2008. Sampling was

conducted during fry propagation periods. Eggs were mass hatched in 100 litre

containers and fry were transferred to a 3000 litre tank for nursing; 200 larvae were

sampled on the first and second days (100 each day) after hatching and samples

fixed in 70% ethanol at 4°C prior to DNA extraction. A total of 31 samples of

parental individuals and 600 fry from 3 hatcheries were sampled for the study.

Details of the sampling (Table 1) are presented below.

Table 1: Sample name, sample size, collection date and source of samples for the

whole study.

Sample name Abbreviation Place

Year

n

RIA 2 group (A)

Wild Parents TDR Tien River - wild 2001 47

F1 RIA2 RIA2 - domestic 2005 34

F2 - High fillet H RIA2 - selection 2006 48

F2 - Low fillet L RIA2 - selection 2006 48

F2 - Random R RIA2 - selection 2006 24

Wild reference HW Hau River – wild offspring 2009 20

Wild reference TW Tien River – wild adult 2008 7

Hatcheries group (B)

Hau brood HB Tien River 2008 10

Hau offspring H1 and H2 196

Nam brood NB Domestic 2008 10

22

Nam offspring N1 and N2 196

Khanh brood KB Tien River 2008 11

Khanh offspring K1 and K2 196

2.4. Genomic DNA extraction

Total genomic DNA was extracted from all mature brood stock individuals from

approximately 50mg of caudal fin tissue using a standard salt procedure, as

described in the QUT Ecological genetics laboratory manual, a procedure adapted

from Miller et al. (1988).

Total genomic DNA was also extracted from first day, and second day old larvae

using a Chelex procedure (QUT Ecological genetics laboratory manual 2004). This

procedure required that whole larvae were digested overnight at 55°C in 100 μl of

10% Chelex 20mg/ml Proteinase K.

2.5. Genotyping procedures Multi-locus microsatellite genotypes were obtained for each sample individual via

polymerase chain reaction (PCR) amplification using four microsatellite primer sets

purchased from a Thai commercial company (DNA Technology Laboratory, BIOTEC

– Kasetsart University - Thailand) with support from RIA2. Primers were specifically

designed for P. hypophthalmus. Four dinucleotide repeat loci (CB4, CB7, CB12 and

CB13, Table 2) of the ten loci available for Tra catfish were polymorphic and were

screened in the samples available here. PCR amplifications were performed in 10 μl

volumes reaction mixtures containing 1 μl approximately 50 ng of extracted P.

hypophthalmus DNA template, 1 μl of 10X reaction buffer [500 mM KCl, 200 mM

Tris-HCl (pH 8.4)], 1.5 mM MgCl2, 2.5 mM of each DNTP, 5 pM of each primer, 0.5

units of Taq DNA polymerase (Promega, Madison, WI). Thermal cycling was carried

out as follows: initial denaturation at 95oC for 4 min, followed by 30 cycles consisting

of 30 sec denaturising at 95oC, 30 sec annealing at the optimized annealing

temperature (see Table 2), 30 sec extension at 72oC, with a final extension of 10

min at 72oC.

23

Table 2: Primer sequence details of the four microsatellite loci screened

Locus Sequence Primer Annealing

Temp (oC) Forward (5’…………………………→3’) Reverse (5’……………………→3’)

CB4 CCA CAT CCT TAT CAC CCT GAA C ACA ATA CAG AGA AAT CCC CAA GG 55

CB7 GAA CAT CCA CAA ACA CAT CAC AC ACT TTC CCG GAG TAA TCG TTG 55

CB12 GCG ATA GAG ACA GAG AGT CAT GG ATC TGG GTC AAA ATG ATT GGA AC 55

CB13 GTG TGT CAA GTT GGG ATC ATG G CTC CAT TTA CAG ACC ATC CGT AG 55

2.6. Data analysis PCR amplified products were screened in acrylamide gels using a Gel-Scan-3000

(Corbet Research) genotyper. Genotypes were scored using One D-scan version

2.05 software (Scanalytics, Inc., 1998). Data were then stored in MSExcel format

(2003). For the pre-data analysis step, allelic data were checked for presence of null

alleles (signified by an excess of homozygotes), large allele drop out (preferential

amplification of small alleles) or incorrect scoring due to stutter bands (created by

slippage during PCR extension) using MICROCHECKER software version 2.2.3

(Van Oosterhout et al. 2004). Microsatellite polymorphisms were quantified by

assessing genetic diversity parameters and how diversity was partitioned within and

among samples: observed (Ho) and expected (He) heterozygosity; inbreeding

coefficients (FIS) and genetic differentiation among samples (FST), using ARLEQUIN

v3.1 software (Schneider et al., 2000). Statistical significance of F statistics was

determined using a non-parametric permutation process incorporating 100

iterations. Allelic richness (An) was estimated using FSTAT v2.9.3 (Goudet 1995).

Exact P-values that test for conformity of genotypes to Hardy–Weinberg proportions

and linkage equilibrium were estimated using a Markov chain method (1000

dememorization steps, 1000 batches, 1000 iterations per batch) using ARLEQUIN.

Estimates of levels of genetic variation in three generations of Tra catfish used in

the selective breeding program at RIA2 and pedigree analysis of hatchery juveniles

were undertaken using CERVUS v3.0 (Kalinowski 2007) software employing

10000 cycles. In all analyses, levels of significance for multiple tests were corrected

using Bonferroni adjustment (Rice, 1989). With exact P value for all experimental

tests set at α = 0.05; after Bonferroni, α (Bonf) = 0.05/ number of tests.

http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T4D-4SGKB98-3&_user=62921&_coverDate=08%2F01%2F2008&_rdoc=1&_fmt=full&_orig=search&_cdi=4972&_sort=d&_docanchor=&view=c&_searchStrId=1173002344&_rerunOrigin=scholar.google&_acct=C000005418&_version=1&_urlVersion=0&_userid=62921&md5=d2e514892737afdee954b175a7408245#bib33

24

Effective population size (Ne) of hatchery stocks from three rivers were estimated

using two methods: i) estimation based on the number of males and females in the

brood stock (Hartl and Clark, 1997) and ii) number of males and females that

actually contributed to offspring, based on results from the pedigree analysis

(parentage assignment) using CERVUS v3.0 software. Assessment of genetic

correlations between genetic markers and production trait (% fillet yield) were

assessed using GENECLASS v2.0. software (Piry et al. 2004). Representative

examples of microsatellite Gelscan images are presented in Figures 2 a-d.

Figures 2: Gelscan images of genetic diversity in RIA2 34 brood fish samples (2a)

and from 3 private hatcheries (n=31) (2b) at locus CB 12; gelscan

images of allelic diversity in high fillet yield individuals (2c) and of low

fillet yield individuals (n= 24) (2d) at locus CB 12.

2a 2b

2c 2d

http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T4D-4SGKB98-3&_user=62921&_coverDate=08%2F01%2F2008&_rdoc=1&_fmt=full&_orig=search&_cdi=4972&_sort=d&_docanchor=&view=c&_searchStrId=1173002344&_rerunOrigin=scholar.google&_acct=C000005418&_version=1&_urlVersion=0&_userid=62921&md5=d2e514892737afdee954b175a7408245#bib14

25

Chapter 3. RESULTS

3.1. Part A - Characterisation of genetic variation in cultured and wild

populations of Tra catfish

The pairwise linkage disequilibrium results from the sampled populations are

presented in Appendix 1. Initial analysis of the raw data assessed presence of null

alleles, linkage disequilibrium and sample conformation to Hardy Weinberg

Equilibrium (HWE). The four microsatellite loci (CB4, CB7, CB12 and CB13)

screened in the Tra catfish samples showed amplified fragments that ranged in size

from 195 to 277bp. Individual sample amplification success ranged from 88 to 95%

across the four loci with observed number of alleles per locus ranging from 2 (Locus

CB7) to 10 (Locus CB12) MICROCHECKER analysis indicated that null alleles were

present in high frequency at two loci; CB4 and CB 12 (>50%) (Table 3).

Table 3: The potential for null alleles for each locus by sample detected using

MICRO-CHECKER.

locus CB4 CB7 CB12 CB13

population

Wild no no yes no

TDR no no yes yes

RIA2 yes no yes yes

Fillet yes yes no yes

Hau yes no yes no

Nam yes no yes yes

Khanh yes no yes yes

Average expected number of homozygotes at locus CB4 and CB12 were 14.5 and

7.5, respectively while average observed homozygotes at these loci were 24.8 and

16.7, respectively. In most instances, visualization of gel images of the two loci

26

suggested that null alleles were a likely reason for higher than expected

homozygotes numbers at the two loci in most sampled populations.

3.1.1 Pair wise linkage disequilibrium

Pair wise linkage disequilibrium analysis using an exact P value (α = 0.05), after

Bonferroni correlation (α Bonf = 0.05/75 = 0.0007) showed no evidence for

significant linkage disequilibrium among the four loci (P< 0.0007). This result

indicates that the four loci screened in the Tra samples examined here provided

independent assessments of genetic diversity in the sample populations. A

complete statistical summary of the linkage disequilibrium results are presented in

table 4.

3.1.2. Conformation to HWE results

Table 4 presents expected and observed heterozygosity estimates and exact P

values for Hardy Weinberg Equilibrium (HWE) tests (α = 0.05), after Bonferroni

correction (α Bonf = 0.05/60 = 0.0008). A substantial number of tests revealed

significant deviations from HWE. In most cases this was in the form of heterozygote

deficiency, however several instances of heterozygote excess were also observed.

While these data could be used to infer a serious problem with null alleles, there is

strong evidence from the different broodstock samples and wild population sample

that this is unlikely to be the case. Out of the 16 HWE tests for H Brood, N Brood, K

Brood and the wild sample, only two indicated heterozygote deficiency. It is more

likely that the result seen here for the offspring reflect non-random mating in the

broodstock (a function of the breeding protocols used in the hatcheries), differential

contribution of breeders and/or differential survival of fry from particular crosses.

(Tave 1994).

27

Table 4: Observed and expected heterozygosities (Obs. And Exp, respectively),

probability value (P-value) and standard deviation (sd). Significant

deviations from HWE indicated as heterozygote deficiency (def),

heterozygote excess (excess) or not significant (ns) after Bonferroni

correction. Pop/Locus Obs.Het Exp.Het P-value s.d Dev. from

HWE

H1

CB4 0.52083 0.72818 0.00006 0.00002 def

CB7 0.00000 0.60929 0.00000 0.00000 def

CB12 0.88542 0.67828 0.00000 0.00000 excess

CB13 0.67708 0.67294 0.00000 0.00000 excess

H2

CB4 0.71875 0.65211 0.09747 0.00079 ns

CB7 0.62500 0.52285 0.06969 0.00080 ns

CB12 0.42708 0.53916 0.00000 0.00000 def

CB13 0.72917 0.70370 0.14440 0.00122 ns

H Brood

CB4 0.50000 0.78947 0.11528 0.00082 ns

CB7 0.60000 0.51053 0.43256 0.00140 ns

CB12 0.50000 0.84737 0.01231 0.00031 ns

CB13 0.80000 0.78947 0.17228 0.00145 ns

N1

CB4 0.25532 0.65588 0.00000 0.00000 def

CB7 0.54255 0.58078 0.00000 0.00000 def

CB12 0.51685 0.68152 0.00000 0.00000 def

CB13 0.75532 0.72193 0.00000 0.00000 excess

N2

CB4 0.62637 0.67245 0.00386 0.00019 def

CB7 0.63441 0.58983 0.18024 0.00106 ns

CB12 0.58889 0.79963 0.00000 0.00000 def

CB13 0.74468 0.68819 0.00000 0.00000 excess

N Brood

28

Pop/Locus Obs.Het Exp.Het P-value s.d Dev. from HWE

CB4 0.50000 0.66842 0.26167 0.00124 ns

CB7 0.70000 0.59474 0.49094 0.00151 ns

CB12 0.60000 0.62105 0.19733 0.00088 ns

CB13 0.80000 0.60526 0.81148 0.00100 ns

K1

CB4 0.63441 0.64940 0.79725 0.00139 ns

CB7 0.62766 0.67306 0.11780 0.00085 ns

CB12 0.57778 0.79081 0.00000 0.00000 def

CB13 0.68085 0.61230 0.03387 0.00064 ns

K2

CB4 0.21277 0.61617 0.00000 0.00000 def

CB7 0.65625 0.62778 0.79531 0.00130 ns

CB12 0.35065 0.79611 0.00000 0.00000 def

CB13 0.69565 0.78326 0.00000 0.00000 def

K Brood

CB4 0.90909 0.65801 0.13736 0.00089 ns

CB7 0.63636 0.49784 1.00000 0.00000 ns

CB12 0.54545 0.73593 0.07103 0.00080 ns

CB13 0.90909 0.71429 0.56921 0.00135 ns

Wild

CB4 0.25926 0.47799 0.00151 0.00011 ns

CB7 0.59259 0.64570 0.28614 0.00140 ns

CB12 0.22222 0.72816 0.00000 0.00000 def

CB13 0.66667 0.81551 0.00769 0.00023 ns

TDR

CB4 0.57143 0.70711 0.01556 0.00037 ns

CB7 0.54545 0.59953 0.12716 0.00121 ns

CB12 0.50000 0.85829 0.00000 0.00000 def

CB13 0.55556 0.79526 0.00000 0.00000 def

Ria2

29

Pop/Locus Obs.Het Exp.Het P-value s.d Dev. from HWE

CB4 0.14706 0.64311 0.00000 0.00000 def

CB7 0.47059 0.58824 0.00376 0.00015 ns

CB12 0.43750 0.66964 0.00358 0.00016 ns

CB13 0.35294 0.77217 0.00000 0.00000 def

High

CB4 0.39535 0.57346 0.00396 0.00020 ns

CB7 0.52174 0.71261 0.00402 0.00019 ns

CB12 0.64444 0.87241 0.00000 0.00000 def

CB13 0.64103 0.76190 0.00060 0.00007 def

Low

CB4 0.27083 0.63136 0.00000 0.00000 def

CB7 0.66667 0.64320 0.97791 0.00045 ns

CB12 0.65909 0.76959 0.04750 0.00026 ns

CB13 0.48936 0.78609 0.00000 0.00000 def

Random

CB4 0.08696 0.53816 0.00000 0.00000 def

CB7 0.43478 0.61836 0.04401 0.00057 ns

CB12 0.52381 0.83624 0.00000 0.00000 def

CB13 0.34783 0.76715 0.00000 0.00000 def

30

Table 5: Microsatellite polymorphism in 7 sample populations of wild and cultured Tra catfish populations.

Group/ Locus

A An

CB4 P A An

CB7 P A An

CB12 P A An

CB13 P Average gene

diversity Average

number of alleles

Hau Brood (n=10)

5 5.00 0.13 3 3.00 0.42 7 7.00 0.01 6 6.00 0.17 0.73 +/- 0.45 5.30 +/- 1.48

Nam Brood (n=10)

4 4.00 0.26 4 4.00 0.48 6 6.00 0.18 4 4.00 0.82 0.62 +/- 0.39 4.50 +/- 0.87

Khanh Brood (n=10)

4 3.91 0.13 3 2.99 1.00 6 5.72 0.07 4 3.91 0.56 0.65 +/- 0.40 4.25 +/- 1.09

Wild 1

(n=20)

3 3.54 0.01 4 3.36 0.65 6 4.64 0.00 6 5.68 0.01 0.64 +/- 0.38 4.75 +/- 1.29

Wild 2

(n=7)

4 3.54 0.09 2 3.36 0.44 3 4.64 0.02 4 5.68 0.46 0.63 +/- 0.40 3.25 +/- 0.83

Founder

(TDR n=45)

3 3.75 0.02 4 2.99 0.12 10 7.58 0.00 6 5.55 0.00 0.68 +/- 0.47 5.75 +/- 2.68

RIA2 Brood (n=34)

3 2.99 0.00 6 4.02 0.00 6 4.53 0.00 5 4.74 0.00 0.67 +/- 0.42 5.00 +/- 1.23

31

3.1.3 AMOVA analysis of hierarchical differentiation within and among

populations

ARLQUIN 3.1 software was used to assess hierarchical differentiation among

sample populations at two levels; within and among populations employing analysis

of molecular variance (AMOVA). AMOVA allows estimation of the statistical

significance of FST values between sample pairs, i.e. the significance of population

differentiation. The following settings; 100 permutations for significance with 10000

steps were employed in the Markov chain.

Table 6: The statistical significance of FST values of population differentiation

Source of variation d.f Percentage of variation

Among samples 6 7.41

Within samples 267 92.59

FST = 0.0741, P < 0.0000 +/- 0.0000

The results show that the majority of variation present was evident within

populations (92.6 %) while only 7.4% variation was evident among populations.

Variation among populations however, was highly significant (P

32

Table 7: Statistical significance of FST values (the significance of population) among

sample pairs. P values that were significant after Bonferroni correction (α

(Bonf) = 0.05/number of test = 0.05/ 21 = 0.002) are highlighted

P values →

FST ↓ Hau

Brood

Nam

Brood

Khanh

Brood

Wild Wild 2 TDR RIA2

Hau Brood - 0.000 0.0270 0.000 0.0270 0.1351 0.0811

Nam Brood 0.0668 - 0.000 0.0090 0.000 0.000 0.000

Khanh Brood 0.0477 0.1009 - 0.000 0.0090 0.000 0.000

Wild 0.1098 0.0623 0.1404 - 0.000 0.000 0.000

Wild 2 0.7060 0.1706 0.0599 0.1184 - 0.0090 0.0180

TDR 0.0236 0.0819 0.0557 0.0951 0.0776 - 0.0360

RIA2 0.0406 0.1435 0.0834 0.1232 0.0770 0.0212 -

Genetic variation among parents representing the 6 populations (average gene

diversity ranged from 0.62 – 0.73 and average number of alleles per locus ranged

from 4.25 – 5.75). Allelic richness (An) across the sampled populations was highest

at the CB12 locus (10 alleles) and lowest at the CB7 locus (2 alleles) (Table 5).

3.1.4. Genetic characterization of sampled Tra catfish culture stocks

Microsatellite polymorphism was quantified by estimating gene diversity within

samples (FIS) and between samples (FST), observed (Ho) and expected (He)

heterozygosity, and estimating level of differentiation among stocks. Seven

populations were available for comparisons of genetic differentiation among sample

populations (Table 7). Brood stock samples were available from 3 private hatcheries

namely: the Hau and Khanh brood stocks and Nam hatcheries of which the Nam

hatchery had developed the first domesticated brood stock in the Mekong Delta

region. The TDR as sourced from wild fish and the first domesticated generation

from the TDR brood fish at RIA2 were used for the selective breeding program. Wild

1 and Wild 2 were wild caught individuals collected from the Tien and Hau River as

a wild reference for comparison of genetic diversity levels in culture stocks.

33

Parameters for genetic variation (Table 5) in 6 sample populations of Tra catfish in

culture and wild are presented as mean number of alleles per locus (A), allelic

richness (An), observed heterozygosity (Ho), expected heterozygosity (He) and

average gene diversity. For wild Tra catfish, these values showed A = 3.25–4.75;

allelic richness, An = 3.3–5.6; observed heterozygosity, Ho = 0.15–0.71; expected

heterozygosity, He = 0.3–0.82 and average gene diversity = 0.64, and hatchery

samples showed A = 4.25–5.75; An = 2.99–7.58; Ho = 0.14–0.91; He = 0.49–0.82.

3.2. Part B - Assessment of the relative contribution by breeders to fry

cohorts in three private hatcheries in the Mekong Delta

The majority of Tra brood stock examined in the current study was sampled from the

main Mekong River in Dong Thap Province (RIA2 founder and 3 private hatcheries).

Dong Thap Province in the Mekong River Delta is recognised as the premier region

(An Giang, Can Tho and Vinh Long and Hau Giang) for Tra catfish culture in

Vietnam. P. hypophthalmus culture has become a major industry in the south of

Vietnam because there is abundant supply of fresh water available year-round. In

2006, this province produced 300,000 MT of catfish that contributed 37.5% to the

total production of catfish from aquaculture in Vietnam. The industry in this province

also employs approximately 40,000 people of the 1.6 million people who live in the

region (Phuong et al. 2007). In 2007, 87 catfish hatcheries were operational in Dong

Thap Province, producing more than 4.4 billion fry per year constituting the majority

of catfish seed supplied to the industry across the whole Mekong Delta.

34

Figure 3: Map of Mekong Delta identifying the main areas where Tra catfish are

cultured (grey colour)

The current experiment was designed to estimate the effective population size (Ne)

of fish in a closed system and follow them from spawning to hatching. For example,

at the Hau hatchery for the first spawn, eggs from 8 female fish and sperm from 2

males were pooled and hatched as a single composite cohort. On the first day, 100

fry were sampled randomly followed by a second sample of fry (n = 100) on day two

before remaining fry were sold to farmers. The design employed to estimate Ne had

to be suitable to fit into commercial hatchery practices employed on farms while

allowing molecular assessment and analysis of the relative contributions by parents

that potentially contributed to the fry cohorts.

3.2.1. Estimation based on the number of males and females in the

brood stock

According to Hartl and Clark (1997), to ensure the highest Ne during spawning,

under ideal conditions all brood stock should contribute equally to offspring.

However, Ne will be substantially less than N if there is unequal representation of

the sexes and Ne will be impacted more by the rare sex. A simple statistic for

estimating Ne is where:

http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T4D-4SGKB98-3&_user=62921&_coverDate=08%2F01%2F2008&_rdoc=1&_fmt=full&_orig=search&_cdi=4972&_sort=d&_docanchor=&view=c&_searchStrId=1173002344&_rerunOrigin=scholar.google&_acct=C000005418&_version=1&_urlVersion=0&_userid=62921&md5=d2e514892737afdee954b175a7408245#bib14

35

with Nm and Nf being the numbers of male and female brood stock,

respectively.Table 8 provides estimates of Ne for the three private hatcheries using

this method. While the Ne estimates are all less than the total numbers of brood

stock in each case, there is no insight into the relative contributions of each breeder.

Unequal contribution will lead to a further decline in approximation of the true Ne

and therefore needs to be assessed in order to provide a more realistic estimate.

Table 8: Estimation of Ne in three private hatcheries based on the number