AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH
Tuan Viet Nguyen
Submitted in fulfilment of the requirements for the degree of Master of Applied Science
School of Earth, Environmental and Biological Sciences Science and Engineering Faculty Queensland University of Technology 2015
Keywords
Tra catfish; Pangasianodon hypophthalmus; RNA-seq; next generation sequencing; transcriptome; differential gene expression; de novo assembly; salinity tolerance; pathways
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH i
Abstract
Increasing salinity level in freshwater and coastal environments caused by sea level rises linked to climate change impacts is recognised to be a major factor that can have negative effects on fish growth, especially in freshwater teleost species. Tra catfish (P. hypophthalmus) is an important freshwater fish species that is now widely farmed across the Mekong River Delta in Vietnam. Understanding the basis for tolerance and adaptation to raised environmental salinity conditions can assist the regional culture industry to mitigate predicted impacts of climate change across this region.
Recent advances in next generation sequencing technologies (specifically – RNA- seq) can allow researchers to identify and understand multiple interactions between genes that affect quantitative traits of interest including salinity tolerance. Here an
RNA-seq approach was used to investigate genes in P. hypophthalmus that potentially influence acclimation to raised sub-lethal salinity conditions.
Analysis of transcriptomic data resulted in more than 174 million raw reads from three tissue libraries (gill, kidney and intestine). Reads were then filtered and de novo assembled using a variety of de novo assemblers. A comparative analysis of results from multiple assemblers as well as a combined transcriptome were used to create an optimum reference transcriptome for P. hypophthalmus. Downstream analysis resulted in a final reference transcriptome that contained 60,585 unique transcripts with an N50 of 683bp. This resource was then further annotated using a variety of bioinformatics software. Following this step, differential gene expression analysis
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH ii
was carried out that resulted in 3,062 transcripts that were differentially expressed in catfish samples raised under two experimental conditions (0 and 12ppt). Transcripts with a potential role in salinity tolerance based on previous studies identified from a review of the relevant literature were then classified into six different functional gene categories based on their gene ontology assignments.
Finally, the current study combined the data on functional salinity tolerance genes into a hypothetical schematic model that attempted to describe the potential relationships and interactions among these genes to explain the molecular pathways that control adaptive salinity responses in Tra catfish (P. hypophthalmus). The results of the current project can form the basis for further studies to confirm the functional roles of specific genes influencing salinity tolerance in the target species and more broadly in other freshwater teleost fishes.
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH iii
Table of Contents Keywords ...... i Abstract ...... ii List of Figures ...... vi List of Tables ...... vii List of Abbreviations ...... viii Statement of Original Authorship ...... ix Acknowledgements ...... x CHAPTER 1: GENERAL INTRODUCTION ...... 1 1.1 General background ...... 1 1.1.1 Current status of aquaculture in Vietnam ...... 1 1.1.2 Predicted global impacts of climate change and consequences for farming of aquatic species ...... 2 1.2 Basic teleost physiology ...... 4 1.3 Acclimation of freshwater fish during salinity elevation ...... 6 1.4 Transcriptomic studies of non-model species ...... 13 1.5 Next generation sequencing application in non-model aquatic species ...... 16 1.6 Gene expression studies of salinity tolerance traits in aquatic species ...... 17 1.7 Target species of the current study – Tra catfish (P. hypophthalmus) ...... 20 1.7.1 Taxonomic status ...... 20 1.7.2 Biological characteristics ...... 20 1.7.3 Economic importance of P. hypophthalmus ...... 21 1.7.4 Previous studies of P. hypophthalmus ...... 22 1.8 Research goals ...... 23 Specific aims ...... 24 CHAPTER 2: REFERENCE TRANSCRIPTOME GENERATION AND DATA ANALYSIS . 25 2.1 Introduction ...... 25 2.2 Materials and methods ...... 26 2.2.1 Sample collection and RNA extraction ...... 26 2.2.2 cDNA library generation ...... 27 2.2.3 cDNA sequencing using Ion Proton Next Generation Sequencer ...... 27 2.2.4 Data filtering and quality control ...... 28 2.2.5 De novo assembly of reference transcriptome ...... 30 2.2.6 Post-assembly clustering ...... 30 2.2.7 Reference transcriptome analysis ...... 31 2.3 Results ...... 31 2.3.1 Ion Proton sequencing and quality control of raw reads ...... 31 2.3.2 Comparative de novo assembly ...... 32 2.3.3 Gene identification and annotation ...... 35 2.4 Discussion ...... 37 2.4.1 Sequencing of the cDNA library and post sequencing quality assessment ...... 37 2.4.2 Comparative de novo assembly and clustering approach ...... 38 2.4.3 Transcriptome analysis ...... 41 CHAPTER 3: DIFFERENTIAL GENE EXPRESSION AND EVALUATION OF CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE ...... 43 3.1 Introduction ...... 43 3.2 Materials and methods ...... 44 3.2.1 Differential gene expression analysis ...... 44
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH iv
3.2.2 Gene ontology and enrichment analysis ...... 45 3.3 Result ...... 45 3.3.1 Differential gene expression analysis ...... 45 3.3.2 Gene onotlogy enrichment analyses ...... 48 3.4 Discussion ...... 49 3.4.1 Genes involved in energy metabolism ...... 56 3.4.2 Genes involved in ion transport ...... 57 3.4.3 Genes involved in immune and cell protection response ...... 61 3.4.4 Genes involved in encoding structural proteins ...... 64 3.4.5 Genes involved in signal transduction ...... 65 3.4.6 Genes involved in detoxification ...... 67 CHAPTER 4: A CONCEPTUAL MODEL FOR THE SALINITY TOLERANCE PATHWAY IN P. HYPOPHTHALMUS ...... 70 CHAPTER 5: CONCLUSIONS AND FUTURE DIRECTIONS ...... 79 BIBLIOGRAPHY ...... 83 APPENDICES ...... 101 Appendix A –DVD of data files ...... 101 Appendix B – KOG and WEGO chart ...... 101 Appendix C – Gene enrichment analysis ...... 102
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH v
List of Figures
Figure 1. Map of the Mekong River Delta showing major river systems and low topographical features...... 3 Figure 2. Schematic describing osmoregulation physiology of seawater fish (Evans and Claiborne, 2006) ...... 5 Figure 3. Schematic describing osmoregulation physiology of freshwater fish (Evans and Claiborne, 2006) ...... 5 Figure 4. Bioinformatics analysis used in the current study ...... 29 Figure 5. Velvet/Oases assembly statistics ...... 33 Figure 6. SOAP de novo Trans assembly statistics ...... 33 Figure 7. Transcripts length distribution after tr2accds pipeline...... 34 Figure 8. Top-hit species distribution from BlastX ...... 36 Figure 9. Proportion of transcripts with BLASTX matches and GO term annotation ...... 37 Figure 10. Volcano plot of DGE in intestine...... 47 Figure 11. Volcano plot of DGE in gill...... 47 Figure 12. Volcano plot of DGE in kidney...... 48 Figure 13. General schematic model of the salinity tolerance pathway in P. hypophthalmus...... 71
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH vi
List of Tables
Table 1 Summary of raw reads from Ion Proton sequencing and quality control ...... 32 Table 2. Summary of de novo assembly results for Ion Proton data in (P. hypophthalmus) after the tr2accd pipeline ...... 34 Table 3. Summary of gene identification of assembled (P.hypophthalmus) transcripts...... 35 Table 4. Number of genes differentially expressed following salinity exposure ...... 46 Table 5. Candidate genes in osmoregulatory tissues differentially expressed at 0ppt and 15ppt salinity concentrations ...... 51
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH vii
List of Abbreviations
bp Base pair BW Brackish Water Contig Contiguous nucleotide sequence EC Enzyme Commission number ESTs Expressed sequence tags FC Fold change FDR False discovery rate FW Freshwater HSW Hypersaline water GIT Gastro-intestinal tract GO Gene Ontology KEGG Kyoto Encyclopaedia of Genes and Genomes KOG euKaryotic clusters of Orthologous Groups mRNA messenger RNA NCBI National Center for Biotechnology Information NGS Next generation sequencing nt nucleotide SW Seawater SAGE Serial analysis of gene expression MPSS Massive parallel signature sequence QTL Quantitative trait locus RNA-seq RNA-sequencing RPKM Reads Per Kilobase of exon per Million of mapped reads TJ Tight junction
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH viii
Statement of Original Authorship
The work contained in this thesis has not been previously submitted to meet requirements for an award at this or 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.
Signature: QUT Verified Signature
Date: June 2015
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH ix
Acknowledgements
I would like to express my gratitude to all those who gave me the possibility to complete this thesis. I want to thank the School of Earth, Environmental and Biological Science for giving me permission to commence this thesis in the first instance, to do the necessary research work and to use any laboratory equipment I needed. I am especially in debt to Professor Peter Mather, who is not only a teacher, a mentor but a second father I had in Australia. It is important to note that suggestions and stimulating encouragement from Peter and associate supervisor Dr David Hurwood was extremely useful to me in all the time of research and writing of this thesis.
I would like to express my very great appreciation to Dr Hyung Taek Jung, Dr Nguyen Minh Thanh, Ms Dania Aziz, Vincent Chand for their valuable and constructive suggestions during the planning and development of this research work. Dr Hyung Taek Jung was more than just a wise fellow, but a friend when you needed him most. I would like to express great thanks to the support team in QUT HPC center for being the most awesome computing team I’ve been to.
I really enjoy those days and night working in Australia. My deepest gratitude is given to my second family here in Brisbane, namely Uncle Luan Le, Antony Chau Luan Le and many more... Thanks all my fellas that bring me joyful after all stressful moment during the study. Most importantly, I would like to give my special thanks to Dad, Mom and my little brother for each and everything they have done. Without them, life just simply nothing to me. Lastly, all of my heart is devoted to my sweetie Kartika Dang, her unconditionally patient love is what enabled me to fulfil this journey.
AN EVALUATION OF POTENTIAL CANDIDATE GENES INVOLVED IN SALINITY TOLERANCE IN STRIPED CATFISH (PANGASIANODON HYPOPTHALMUS) USING AN RNA-SEQ APPROACH x
Chapter 1: General introduction
1.1 GENERAL BACKGROUND
1.1.1 Current status of aquaculture in Vietnam Aquaculture as a food production sector and fisheries in general have become a major
contributor to Vietnam’s economic growth over recent decades, and is now a key
industry (Duc, 2008). Vietnam’s expanding aquaculture industry now supplies major
international markets and these markets continue to expand (MOFi, 2013). Aquaculture
products from Vietnam are exported to more than 100 countries around the globe with
the primary markets including the USA, Japan, China and the EU (FAO, 2014). Total
aquaculture production in 2013 from Vietnam was estimated at 5,918 thousand tons,
and this included 4,400 thousand tons of harvested fish, an increase of 3.2% from 2012,
and 704 thousand tons of prawns, an increase of 11.7% also from 2012 (MOFi, 2013).
Aquatic species currently farmed extensively in Vietnam include; giant tiger prawn
(Penaeus monodon), Tra catfish (Pangasianodon hypophthalmus), spiny lobster
(Panulirus spp.), groupers (Epinephelus spp.), bivalves (Meretrix lyrata) and tilapia
(Oreochromis niloticus). Among the major Vietnamese aquatic products that are
exported to international markets, marine prawns and Tra catfish are currently the most
important oness and now contribute significantly to growing export value. While the
aquaculture sector in Vietnam has great potential for future growth, there are however, a
number of significant challenges ahead for this industry if growth is to be sustained;
these include climate change impacts, environmental pollution, and resource over-
exploitation (De Silva and Davy, 2010).
Chapter 1: General introduction 1
1.1.2 Predicted global impacts of climate change and consequences for farming of aquatic species There is growing concern about climate change impacts worldwide (Mieszkowska et al.,
2009; Philippart et al., 2011; Root et al., 2013). Future sustainability is considered by
many scientists to be under significant threat given that climate change impacts are
likely to increase over the next few decades (IPCC, 2007). In particular, fisheries
scientists have suggested that there are likely to be direct and indirect impacts from
climate change on both wild fish resources and fish farming. Direct effects of climate
change for the aquaculture sector will include impacts on the physiology of target
species, behaviour, growth rates, development, mortality rates and changes to natural
distributions, while indirect impacts are likely to include reductions in fish production,
loss of ecosystems and a variety of negative consequences for those individuals with
livelihoods dependent on fisheries and fish culture (Brander, 2007).
One of the major predicted outcomes of global warming will be rising sea levels. In
association with increasing sea levels over coming decades, are predicted seawater
(SW) incursions into freshwater (FW) systems leading to increased salinity levels in
many rivers and that will impact FW ecosystems as a consequence. The Mekong River
Delta (MRD) (figure 1), a low topographic region in the south of Vietnam, is an area of
40,548 km2 comprising 13 provinces that is home to more than 17.3 million people
(GSO, 2013). The MRD is a relatively flat, low topographical area that possesses a
huge expansive network of rivers and channels (Sebesvari et al., 2011). Potential
negative impacts of sea level rise on the MRD region that have consequences for
agriculture production have been identified for some time (Wassmann et al., 2004). In a
review by the IPCC (2007), the effect of climate change and predicted associated sea
level rises, will result in saline water intrusion inland in the Mekong delta and this has
been identified as a major issue for the region.
Chapter 1: General introduction 2
Figure 1. Map of the Mekong River Delta showing major river systems and low topographical features.
These predicted changes are likely to have massive impacts on local human populations
and affect sustainability across the region. In general, any change in water variables
(e.g. baseline salinity, temperature, pH, metal concentrations, dissolved oxygen) can
bring significant change to ecological and biological factors that impact farmed aquatic
species (Badjeck et al., 2010). Pörtner et al. (2001) reviewed a number of different
climate change scenarios and predicted how they are likely to affect individual growth
rates and growth performance of aquatic species. In summary, it is increasingly obvious
that, aquaculture, especially culture of FW species in the MRD, will face a significant
threat from predicted climate change impacts. Developing a better understanding
therefore, of how FW fish, crustaceans and molluscs respond to changes in background
salinity will be crucial to developing appropriate responses to predicted salinity rise
across the region.
Chapter 1: General introduction 3
1.2 BASIC TELEOST PHYSIOLOGY
Environments for aquatic species including fish are influenced by a variety of external
factors that include salinity, ion composition, dissolved oxygen levels, temperature and
pH among others. In most cases, changes in ionic and osmotic composition of
environmental water can have a critical impact on both growth and survival of fish
(Pritchard, 2003). For both SW and FW fish, the crucial problem they face relates to
balancing their body fluids with the external environment. Depending on their relative
ability to adapt to a range of salinities, fish can be classified as either stenohaline
(limited ability, can only handle narrow fluctuations in environmental salt
concentration) or euryhaline (exhibit extensive tolerance to salinity changes). Moreover,
stenohaline and euryhaline fish can be further classified into two groups: where
depending on their response they are referred to as osmoconformers or osmoregulators
depending on how they regulate their internal osmolarity. Osmolarity of
osmoconformers matches the external environmental concentration, while
osmoregulators can vary osmolarity greatly with the environment. Evolution and
adaptation overtime in some teleost fish has resulted in advanced ion/osmoregulatory
mechanisms to achieve homeostasis, that allows some species to tolerate a wide range
of different salinity conditions (Hwang and Lee, 2007)
In natural environments, marine fish species maintain an internal osmotic pressure that
ranges from 300 – 400 mOsm and will experience a passive gain of ions and loss of
water overtime. In response, individuals tend to drink large amounts of seawater in
order to balance their body fluids, absorb water to balance their internal homeostatic
environment, while excess salt is actively secreted via their gills or kidneys. Currently,
the mechanisms for NaCl secretion by SW fish are much better understood than those
for NaCl absorption by freshwater FW fish (Hwang and Lee, 2007) .
Chapter 1: General introduction 4
Figure 2. Schematic describing osmoregulation physiology of seawater fish (Evans and Claiborne, 2006)
In contrast, FW fish do not drink very much water. Unlike SW fish, FW fish suffer
diffusive loss of major ions including Na+ and Cl- to their environment, while
potentially gaining vast amounts of osmotic water. To counteract this problem, FW fish
replace ion loss via their gills or via their dietary intake, while producing large volumes
of dilute urine from their kidneys to balance their cellular water budget (Evans and
Claiborne, 2006; Hwang and Lee, 2007). Even though studies of FW fish gill Na+/Cl−
uptake mechanisms have increased, mechanisms of regulation are still poorly
understood compared with those involved with NaCl secretion (Hwang and Lee, 2007).
Figure 3. Schematic describing osmoregulation physiology of freshwater fish (Evans and Claiborne, 2006)
Chapter 1: General introduction 5
1.3 ACCLIMATION OF FRESHWATER FISH DURING SALINITY ELEVATION
In general, fish osmoregulatory organs do not work in an “isolated system” but each is
part of an integrated larger system that work synergistically to maintain an individual’s
osmotic balance. Fish can adjust their behaviour instinctively and this involves
metabolic pathways and secretion of hormones to address potential osmotic challenges
from their external environment. According to Guo (1997), to overcome osmotic
difficulties, fish adopt specific strategies to cope with changes in their external physical
environment, that include but are not limited to;
i. Reduction of osmotic gradient between body fluids and the environment.
Osmotic differences between body fluids and the external environment can be
minimized via modification of blood osmolarity in fish. Osmotic acclimation is
known to induce changes in plasma levels of metabolites including glucose, lactate,
triglycerides and/or proteins (Sangiao-Alvarellos et al., 2003). Increased plasma
glucose levels have been observed during acclimation from FW or brackish water
(BW) to SW or hypersaline water (HSW) in several species of fish including
gilthead sea bream (Sparus aurata) (Sangiao-Alvarellos et al., 2005), rainbow trout
(Oncorhynchus mykiss) (Morgan and Iwama, 1991), cut-throat trout (Oncorhynchus
clarki) (Morgan and Iwama, 1996), Mozambique tilapia (Oreochromis
mossambicus) (Morgan et al., 1997; Nakano et al., 1998) and carp
(Ctenopharyngodon idella) (Boeck et al., 2000; Yavuzcan-Yıldız and Kırkavgaç-
Uzbilek, 2001). The boosting effects of glucose and other metabolites on peripheral
tissues to solve the high demand for energy during osmotic acclimation however, has
not been widely understood. When euryhaline fish living in SW are acclimated to
BW or FW, both decreases (as seen in red sea bream (Woo and Murat, 1981) or
increases (as seen in tilapia (O. mossambicus) (Assem and Hanke, 1979)) and silver
Chapter 1: General introduction 6
seabream (Pagrus auratus) (Kelly and Woo, 1999), in plasma glucose levels have
been reported.
ii. Alteration in body surface permeability. Osmotic permeability coefficient
(Pos) is a term used to measure the net rate of water gain by the whole animal or
isolated gill in the presence of a transmural osmotic gradient. This term represents
the rate of water intake that must be balanced by fluid extraction to reach an
osmotic steady state. Changes in permeability enable some teleost fish to adapt to
osmotically unfavourable conditions.
iii. Adjustment in active transport of ions. In order to cope with the new
environment, fish tend to increase their metabolic rate via an array of molecular
responses that involve various hormones, ion protein pumps and enzymes that are
secreted during salinity fluctuation. Under a hyper or hypo osmotic challenge, fish
will face different osmotic loss scenarios. Individuals then have to increase their
ion secretion or absorption rate by activating cells to pump ions in, or out of the
body depending on the conditions experienced.
iv. Alteration in urine flow rate and/or composition. The kidney can respond
by producing a large amount of urine with a high ion concentration including Mg2+
2- or SO4 to compensate for external osmotic pressure (Marshall, 2006). A study of
Australian bass proposed that this species could potentially alter their glomerular
filtration rate by controlling blood flow through their kidney when acclimating to
different salinities (Guo, 1997).
THE GILL
Chapter 1: General introduction 7
Many studies have suggested that ion balance in fish is regulated mainly by the gills, as
they function as an ion absorption site in FW and an ion secretion site under SW
conditions (Foskett et al., 1981). Fish actively maximize their gill surface area in contact
with environmental water (which leads to increased oxygen extraction from the
surrounding water), in addition to minimizing the diffusion distance for ion/gas
exchange between the bloodstream and the external water. For many reasons therefore,
the unique functions of the gill have attracted the interest of researchers over recent
decades. Many studies have demonstrated that an increase in salinity is usually
accompanied by changes in ionocyte location (filament and/or lamellae), number and/or
size (Evans et al., 2005). The major cell types present in FW gill epithelia include;
pavement cells, respiratory cells, monocytes and mitochondria-rich cells. In particular,
mitochondria-rich cells (MR cell or chlorine cells) are specialized ionocytes that
constitute the main cells responsible for active transport of ions across the fish gill (Hiroi
et al., 2005; Hwang and Lee, 2007; Inokuchi et al., 2008). To date, three types of
mitochondria-rich cells have been identified that include; normal chloride cells,
accessory cells and dark chloride cells. Only normal chloride cells and accessory cells
however, are believed to be activated during salinity acclimation.
When FW fish encounter elevated salinity levels, the critical response is to secrete salt
(secretion of Na+ and Cl-) out of the body, while they absorb water to balance the
osmotic pressure between internal and external environments. Under the currently
accepted model of MR cells in the gill of SW-adapted fish, salt secretion is believed to
be mediated by 3 major ion transporters; Na+/K+-ATPase (NKA),
Na+/K+/2Cl−cotransporter (NKCC), and the cystic fibrosis transmembrane conductance
regulator (CFTR) channel.
Of the three major ion-transporters that contribute to Na+ and Cl- secretion from the gill
during seawater adaptation in teleosts, the role of NKA is to move sodium ions out of the
Chapter 1: General introduction 8
cell, and then to pump potassium ions back in. This results in an ionic gradient inside the
MR cell that produces a negative charge reducing Na+ levels. Following this, NKKC
uses the same gradient to bring Cl- into the cell. Finally, CFTR takes over and directly
transfers the remaining Cl- out of the cell via an apical chloride channel. Mackie et al.
(2007) have suggested that NKA, NKCC and CFTR are all up regulated following
seawater exposure, though individual responses vary between species and under
different experimental conditions.
KIDNEY AND URINARY BLADDER
Most freshwater fish have two relatively large kidneys that have evolved to process large
amounts of dilute urine and to recover important salts. Together with the gill, the kidney
is another important osmoregulatory organ in teleost fish that plays a crucial role in
secretion of ions and elimination of water in SW environments (Yan et al., 2013).
During SW acclimation, the kidney undergoes many changes in morphology, metabolic
pathways and urine production (Soengas et al., 2007). By continuously drinking water,
teleost fish are constantly replacing the water that is lost inevitably by osmosis to the
external environment. This can lead however, to an excess intake of salts that can reach
harmful concentrations (particularly divalent ions including Mg2+, Ca2+). This problem is
addressed by the teleost kidney that maintains water capacity and actively excretes salts
to produce concentrated urine. It is believed that inside the kidney, a process of
reabsorption of water occurs and this process is made possible by increasing the
penetration rate of the glomerular capillaries (Knepper, 1997). Moreover, many studies
have identified that freshwater species tend to reduce their urine flow in raised salinity
environments (Salati et al., 2011). In the mammalian kidney, water reabsorption mostly
occurs in the Loop of Henle and the ion composition of the urine is further concentrated
inside the collecting duct. Depending on the species however, the process of kidney ion
secretion can vary greatly (Beyenbach, 2004).
Chapter 1: General introduction 9
Our general understanding of fish kidney function however, is still quite limited. Some
2+ 2- studies have hypothesised, that certain ions including Mg and SO4 are extracted in the
2- kidney (Nishimura and Imai, 1982) and SO4 has also been shown to be extruded from
- kidney cells into the tubule lumen in exchange for HCO3 (Beyenbach, 2004). It is also
known that renal output in teleosts often contains a very high concentration of Mg2+.
This can be explained by reabsorption of Na+, Cl- and water in the distal nephron
(Beyenbach, 2004).
INTESTINE (GASTRO‐INTESTINAL TRACT)
Recent studies that have reviewed functions of the gastro-intestinal tract (GIT) have
suggested that this organ also plays a major role in regulating water and electrolyte status
in teleost fish. When highly dehydrated, teleost fish will drink the surrounding water and
use GIT as an organ to reabsorb water to balance osmotic loss. The first demonstration
of the fish drinking reflex was reported in the early 1930s and indicated that fish can
compensate for their osmotic conditions by continuous drinking of surrounding water
(Evans, 2008; Smith, 1930). This appears to be a key component of their osmoregulatory
strategy to compensate for high amounts of salt in their environment while achieving
balanced water net. Specifically, ingested SW is desalted in the eosophagus (active
absorption of Na+ and CL-), and then fish take advantage of the osmotic gradient
between body fluids and the intestine, to reabsorb water to balance the massive
dehydration effects of the external environment. (Karasov and Hume, 2010; Skadhauge,
- - 1969). The fish intestine also actively secretes HCO3 into the lumen in exchange for Cl
- 2+ and an elevated concentration of HCO3 is believed to precipitate divalent Mg and
Ca2+ions. The trapping mechanism for divalent ions makes them unable to be absorbed
as well as reducing intestinal fluid osmolality. Precipitated ions can then be cleared
subsequently, in the urine during excretion. To date however, only limited information is
Chapter 1: General introduction 10
available about this organ and its functional role in osmoregulation (Soengas et al.,
2007).
Smith et al. (1930) demonstrated that eels (A. anguilla) acclimated to SW showed
higher drinking rates compared with individuals in FW. The authors proposed that water
absorption must occur in the intestine, assisted by an osmotic gradient generated by
uptake of monovalent ions (Smith, 1930). Moreover, this pattern has been confirmed in
salmonids (Nielsen et al., 1999). Ion transporters related to intestinal osmoregulation
have been a subject of long investigation in teleosts, they include NKA, Na+/H+
exchanger (NHEs), carbonic anhydrase (CA), V-type H+-ATPase (V-ATPase), FXYDs
protein, claudins, Aquaporins (AQP), Na+/K+/2Cl−cotransporter (NKCC) and a set of
ionic exchangers (SLC26A6 family) (Grosell, 2011; Sundell and Sundh, 2012).
As elevated salinity in the external environment dehydrates a teleost fish, individuals
tend to drink more environmental water and to absorb FW across their membranes with
the help of an osmotic gradient generated by ion absorption, after which they eliminate
any excess salt (Kurita et al., 2008). Absorbed ions (mainly Na+ and Cl-) can be secreted
through the gill following transport in the bloodstream. In parallel, unrequired divalent
cations (Mg2+ and Ca2+) are concentrated to high levels as water absorption proceeds
and finally they are excreted with the rectal fluid via precipitation with bicarbonate
secreted into the intestinal lumen (Mekuchi et al., 2010; Shehadeh and Gordon, 1969;
Wilson and Grosell, 2003). In parallel, precipitation is hypothesized to play a role in
water reabsorption mechanisms by reducing the osmolality of intestinal fluids (Wilson
and Grosell, 2003). In teleosts, water reabsorption in the intestine can be transcellular
(through enterocytes - or intestinal absorptive cells, and then pass through the apical and
basolateral membrane of the cell) or paracellular (via tight-junctions).
Chapter 1: General introduction 11
The water absorption pathway in teleosts depends on paracellular permeability via tight
junctions (TJs). TJs are charged selective pores that control the movement of
charged/non-charged solute. Three different proteins can be found on the TJ, occludins,
claudins and junction-associated membrane protein. Total number of TJ strands has
been suggested to be correlated with membrane permeability in teleosts (Van Itallie et
al., 2008) and TJs have been shown to act as a gateway that allow movement of
molecules over time by breaking apart or joining together. This mechanism is controlled
by claudins and occludin that generate selective permeability of different molecules
(Sundell and Sundh, 2012).
It is interesting to note however, that in salmonids during smoltification, paracellular
permeability decreases in combination with an increase in transcellular activity. This
suggests a redirection of the water transfer mechanism from a paracellular route under
FW conditions to a transcellular route in SW (Sundell and Sundh, 2012). The
transcellular water absorption process is believed to be driven by a gradient of solute
created by the modulation of sodium ions. Briefly, Na+ and Cl- enter the cell by either
NKCC or NCC (Na+ – Cl- cotransporter) (Grosell, 2011; Watanabe et al., 2011), and
absorbed Na+ can then be excreted via a sodium pump (e.g. NKA). Na+ absorption
creates a gradient that allows water to diffuse in and complete reabsorption of water
occurs by fish drinking external water. Excess divalent ions can then be cleared by renal
excretion as is evidenced by high Mg2+ concentration in the urine (McDonald and
Grosell, 2006). It is also debated whether the NHE family plays a role in intestinal
water reabsorption, as NHE pumps Na+ continuously into enterocytes (the same role as
NKCC or NCC). This hypothesis has been challenged however, by recognition that
NHE may act as a Na+ importer, an H+ regulator (acid-base balancing) or may play a
+, - role in both processes. Recently, a Na HCO3 co transporter (referred to as NBC1) that
+ - allows uptake of Na and HCO3 has also been identified (Kurita et al., 2008). While the
major mechanisms of ion transport have been identified recently in teleost fish, the
Chapter 1: General introduction 12
route of water flow remains under debate and further investigation will be required to
establish conclusive evidence for a water reabsorption pathway (Sundell and Sundh,
2012). It is also believed that the lipid bilayer in the transcellular water absorption
pathway may play a significant role, since transfer of masu salmon (Oncorhynchus
masou), sturgeon (Acipenser naccarii) and rainbow trout (Salmo gairdneri R.) from FW
to SW resulted in an increase in n-3 polyunsaturated fatty acids (Leray et al., 1984; Li
and Yamada, 1992; Martínez-Alvarez et al., 2005). The authors argued that an increase
in n-3 polyunsaturated fatty acids may increase transmembrane permeability. In
addition, the water reabsorption process in the intestine is also believed to be associated
with activation of many Aquaporin isoforms (Borgnia et al., 1999; Cutler et al., 2007;
Madsen et al., 2011).
1.4 TRANSCRIPTOMIC STUDIES OF NON-MODEL SPECIES
As modern genetics has developed over recent decades, new technologies including
applied genomics and transcriptomics have allowed scientists to modify certain
production traits in many livestock species, plants and a limited number of farmed
aquatic species, impacting both stock quality and productivity (McAndrew and Napier,
2011). Modern genomic technologies allow researchers to understand often complex
quantitative production traits via gene-expression studies. In this respect, traits like
salinity tolerance, when shown to have at least a partial genetic basis, can be explored at
the molecular level. In particular, this approach can allow discovery of important genes
and functional mutations that influence individual variation in these traits in target
species.
Availability of a complete draft genome sequence for a target species can significantly
enhance outcomes and can be applied to improve stock productivity and quality.
Currently, complete genome sequences are available, or are nearly available, for most
Chapter 1: General introduction 13
major livestock species including cattle, swine, chicken, and horse (Liu, 2011).
Aquaculture is however, an emerging food production industry and has largely yet to
benefit from widespread applications of genetic and genomic technologies for stock
improvement. Currently, according to Liu (2011), genome sequencing projects are
underway for only a few farmed aquatic species including; tilapia (Guyon et al., 2012;
Lee et al., 2010; Lee et al., 2005), Atlantic salmon (S. salar) (Davidson et al., 2010),
channel catfish (I. punctatus) (Wang et al., 2010). Given however, that already currently
more than two hundred aquatic species are farmed worldwide and many new ones are
being trialed or developed, much work will be required in this area (Liu, 2011).
In spite of advances in genome sequencing using NGS platforms, whole genome
sequencing of any target species remains both costly and time-consuming. While the
genome of a specific organism is relatively stable, in contrast the transcriptome (a small
portion of the whole genome – that is transcribed into RNA molecules) is a dynamic set
of expressed genes that will change depending on an organism’s physiological
conditions and can be influenced by effects of the external environment. Recently, new
markers referred to as expressed sequence tags (EST) were developed in coding gene
sequences and soon became the primary approach for characterizing transcriptomes.
ESTs are small DNA sequences that can serve as a “tag” for characterizing functional
genes matched to existing sequence databases. EST sequencing only deals with a small-
transcribed portion of the genome of a target species, while skipping all the non-coding
regions of the genome. EST resources are also useful for development of cDNA
microarrays to identify functional genes and for analysing gene expression patterns. An
EST approach allows researchers to greatly reduce the time required to locate a specific
functional gene. In addition, EST analysis is also an effective approach for identifying
polymorphic DNA markers including microsatellites and SNPs for various applications.
The largest EST database, dbEST is a sub-division of the GenBank database that
contains sequence data and other information on "single-pass" cDNA sequences, from a
Chapter 1: General introduction 14
large number of organisms. Currently, more than 74 million EST entries are available on
the dbEST database. As an example, currently more than 1.5 million ESTs have been
recorded for zebrafish (a model teleost species) in NCBI (accessed April 2015). This
number however, is much lower than the number of ESTs available for humans (> 8
million) and that reported for mice (~ 4.8 million), but similar to the number of ESTs
available for cattle (~ 1.5 million) and pigs (~ 1.6 million). Currently, EST resources
available for common aquaculture species on NCBI, include: 528,294 for salmon (S.
salar); 290,406 for rainbow trout (O. mykiss); and 357,053 for channel catfish (I.
punctatus) (accessed April 2015). Recently, due to the expansion of next generation
sequencing,A Sequence Read Archive (SRA) was developed
(http://www.ncbi.nlm.nih.gov/Traces/sra/). SRA is a repository for storing huge amounts
of biological data generated using high-throughput sequencing platforms. Currently,
there are 6 archives available for P. hypophthalmus developed in a single project (Thanh
et al., 2014) (accessed April 2015). A review of ESTs available in the NCBI EST and
SRA database shows that currently, only a very limited number of genomics have been
recorded for the target species in the current study.
When first developed, transcriptome analysis required cloning techniques followed by
Sanger sequencing. Following this development, hybridization-based approaches (i.e
microarrays) were deployed to identify differences in gene expression patterns between
challenged and control fish. Limitations associated with a microarray based approach for
gene expression analysis however were recognised subsequently: 1) preparation of a
microarray requires characterisation of specific genome sequences from target species
for chip design (a requirement that greatly limits microarray experiments on non-model
species); 2) background noise during analysis and 3) low sensitivity associated with very
low/highly expressed genes. More recently, new techniques including SAGE (serial
analysis of gene expression) and MPSS (massive parallel signature sequence)
technologies were developed that are tag-based short sequence read approaches and have
Chapter 1: General introduction 15
been used for the same purpose. These techniques were able at least to address the
sensitivity problems associated with a microarray approach. Recently however, major
advances in sequencing technology occurred leading to the post genomics era, where
introduction of 2nd generation pyrosequencers capable of generating (hundreds of)
millions of DNA sequence reads in a single run at relatively low cost and at high speed
have changed the field radically. These technologies have revolutionised both genomics
as well as transcriptomic studies.
1.5 NEXT GENERATION SEQUENCING APPLICATIONS IN NON- MODEL AQUATIC SPECIES
DNA sequencing technologies have developed significantly in both output power and
depth of reads (Glenn, 2011). Since the invention of the Sanger sequencing technology
in 1977 (1st generation sequencing), there has been rapid development of many new
platforms and technologies. Nowadays, high-throughput (or ‘next generation’)
sequencing technologies (referred to as NGS) have delivered a quantum change in our
ability to sequence genomes/transcriptomes. NGS technology is much more advanced in
comparison with the Sanger sequencing method because it allows massive parallel
analysis and high throughput at relatively low cost (Liu et al., 2012). Currently, many
NGS systems are available, each based on a different technology. These include the
SOLiD™/Ion Torrent PGM™/Ion Proton™ from Life Technologies, Genome
Analyzer™/HiSeq 2000™/MiSeq™/NextSeq™ from Illumina, and GS FLX
Titanium™/GS Junior™ from Roche. In the near future, emerging technologies (3rd
generation sequencing) include the Oxford Nanopore and NobleGen Bioscience – that
are still in the prototype phase and are likely to further increase yield rate, lower
sequence error rates and reduce the time required for individual runs (Eisenstein, 2012).
New sequencing technologies have pushed genetic industries toward the ultimate goal of
USD $1000 per complete human genome (Martinez and Nelson, 2010).
Chapter 1: General introduction 16
To date, experimental analysis using NGS platforms have been applied to only a
relatively small number of aquatic species, including giant freshwater prawns
(Macrobrachium rosenbergii) (Jung et al., 2011; Mohd-Shamsudin et al., 2013), Pacific
white shrimp (Litopenaeus vannamei) (Li et al., 2012), common carp (Cyprinus carpio)
(Ji et al., 2012), alewife (Alosa pseudoharengus) (Czesny et al., 2012), Fujian oyster
(Crassostrea angulata) (Qin et al., 2012) and Chinese mitten crab (Eriocheir sinensis)
(He et al., 2013)… Recent development of the “personal-sized-sequencer” (bench-top
sequencers) for example; Life Technologies Ion Torrent PGM/Ion Proton or Illumina
MiSeq have unlocked huge potential for smaller laboratories to conduct transcriptomic
analyses of target species at relatively low cost.
1.6 GENE EXPRESSION STUDIES OF SALINITY TOLERANCE TRAITS IN AQUATIC SPECIES
Physiological changes are driven by regulation of gene expression that can be analysed
and characterized using a variety techniques described above. It is now possible in
theory, to explain using gene expression analysis, the way organisms respond to
fluctuations in their external environment at the molecular level. Basically, life itself is a
chain reaction with stimuli being detected by individuals that potentially generate a
response. Behind these reactions however, there will be molecular factors driving the
response. Genes can be viewed as the powerhouses that control how an individual
responds to cope with new environmental conditions and gene expression can be
considered to be the switches that control individual responses. Thus understanding how
an individual responds to changes in external salinity involves searching for genes that
are turned on or off or that are up or down regulated during external salinity change.
Over the last decade, many approaches had been conducted to understand the
mechanisms behind salinity adaptation. Various approaches include; quantitative trait
locus (QTL) analysis, generation of suppression subtractive hybridization (SSH)
Chapter 1: General introduction 17
libraries, high-throughput transcriptomic and proteomic approaches, microarray
technology and RNA-seq analysis. QTL analyses of genomic regions in Arctic char
(Salvelinus alpinus) investigated the genetic capacity of individuals with specific allelic
variation at the ATP1α1b locus (the gene known to code for the NKA protein pump) as
well as the effect of IGF-2 on salinity tolerance (Norman et al., 2011). Several QTLs for
salt tolerance were identified in this study including for; NKA activity, blood plasma
osmolality, NKCC, CFTR and claudin 10 isoforms (Norman et al., 2011). In parallel, a
comparative mapping approach was used to investigate genes associated with salinity
tolerance in three different salmonid species; Atlantic salmon (S. salar), Arctic charr
(Salvelinus alpinus) and rainbow trout (O. mykiss) and yielded information about where
critical genes are located in the salmonid genome (Norman et al., 2012).
Another approach, used SSH libraries from partial cDNA sequences that coded for
genes that were up or down regulated during hypo-osmotic challenge in sea bass
(Dicentrarchus labrax) (Boutet et al., 2006). A combination of functional genomic and
proteomic approaches including SSH, rapid amplification of cDNA end and mass
spectrometry-driven proteomics were also used to identify genes and proteins that
contributed to salinity adaptation in certain fish taxa (Kültz et al., 2007).
More recently, microarray platforms have become a powerful tool for analysing
differential gene expression patterns related to salinity acclimation in fish. This
technology was used to investigate the transcriptome from European eel (Anguilla
anguilla) transferred from FW to SW conditions. The study identified 229 discrete
cDNA sequences of which only 95 were known at the time the study was conducted.
Using the same technique, examination of the transcriptomic time-course of hyper- and
hypo-osmotic stress signalling events in the euryhaline longjaw mudsucker (Gillichthys
mirabilis) annotated 168 gene transcripts that were expressed during osmotic stress
exposure (Evans and Somero, 2008). A similar approach has been used to investigate
Chapter 1: General introduction 18
responses to salinity stress in two blue mussel strains; Mytilus galloprovincialis and M.
trossulus (Lockwood and Somero, 2011), a copepod (Lepeophtheirus salmonis)
(Sutherland et al., 2012), giant freshwater prawn (Macrobrachium rosenbergii)
(Barman et al., 2012), and larvae of the salmon louse (Lepeophtheirus salmonis)
(Sutherland et al., 2012).
Recent development of NGS capacity (in particular development of RNA-seq
technology) has allowed detection of genes that are turned on/off and that are up or
down regulated under different salinity conditions. Most recently, an RNA-seq
approach was used to characterise a variety of genes that were up or down regulated
during low salinity exposure in the marine oyster Crassostrea gigas (Zhao et al., 2012).
Deep sequencing of transcriptome data combined with proteomic analysis of Japanese
eel (Anguilla japonica) during short-term hyperosmotic stress yielded over 100 proteins
that were differentially expressed (Tse et al., 2013). In fish, an analysis of stress
response in the intestine of Asian seabass (Lates calcarifer) also yielded massive
amounts of data using RNA-seq technology (Xia et al., 2013). Recently, a combined
approach employing RNA-seq and RT-PCR was used to characterised genes involved in
salinity tolerance in black-chinned tilapia Sarotherodon melanotheron heudelotii
(Avarre et al., 2014). A comprehensive review of applications that have used next
generation sequencing (in specific, RNA-seq) on aquatic species can be found
elsewhere (Qian et al., 2014). So to summarise, new genomic technologies have
yielded massive amounts of data about the mechanisms behind a variety of molecular
responses of teleost fish during salinity acclimation.
Chapter 1: General introduction 19
1.7 TARGET SPECIES OF THE CURRENT STUDY – TRA CATFISH (P. HYPOPHTHALMUS)
1.7.1 Taxonomic status Striped catfish (Pangasianodon hypophthalmus) locally known as Tra catfish, is one of
approximately 30 teleost species in the Family Pangasiidae. Historically, a variety of
formal taxonomic names have been used to describe Tra catfish including;
Helicophagus hypophthalmus (Sauvage, 1878), Pangasianodon hypophthalmus
(Sauvage, 1878), Pangasius hypophthalmus (Sauvage, 1878), Pangasius pangasius
(non Hamilton, 1822), Pangasius pleurotaenia (non Sauvage, 1878) and Pangasius
sutchi (Fowler, 1937; (Thường, 2008).
The current accepted name, Pangasianodon hypophthalmus, was first used by Rainboth
in 1996 (Thường, 2008).
1.7.2 Biological characteristics Catfish (Order Siluriformes) are a diverse group of ray-finned fishes represented by
more than 3000 species, defined currently into 478 genera and 36 families (Ferraris,
1999). They form one of the most important groups of farmed aquatic species
worldwide. A number of Siluriformes catfish species are used in aquaculture around
the world including channel catfish (Ictalurus punctatus), blue catfish (Ictalurus
furcatus), walking catfish (Clarias fuscus) and striped catfish (P. hypophthalmus).
P. hypophthalmus referred to locally as Tra catfish in Vietnam, is a migratory, obligate
freshwater teleost. Individuals reach maturity between two and four years of age, while
maximum lifespan is believed to reach 20 years. Individuals are believed to migrate
upstream in the Mekong River at the end of the flooding season (from October to
February) and return to the main channel at the beginning of the rainy season (from
June to August) (Phuong and Oanh, 2010). P. hypophthalmus is an omnivore and
Chapter 1: General introduction 20
consumes algae, plants, zooplankton, and insects, while larger specimens can take fruit,
crustaceans and even small fish (Phuong and Oanh, 2010).
Mature fish can reach a maximum standard total length of 130 cm and up to 44 kg in
weight. This species is benthopelagic, typically living within a water pH range of 6.5 to
7.5 and temperature range from 22 to 26°C(FAO, 2010-2012). Surprisingly, the general
biological characteristics of this economically very important farmed species are still
relatively poorly known with only limited studies having been conducted on its
temperature, salinity, or pH, etc. tolerance ranges or other environmental factors that
affect growth, reproduction and survival (Hung et al., 2003). Availability of this
information will be highly relevant to predicting likely impacts of climate change on
both wild and cultured stocks in South East Asia in the future.
1.7.3 Economic importance of P. hypophthalmus Tra catfish is one of the major freshwater fish species harvested across the Mekong
River Basin and this species provides one of the largest and most important inland
fisheries in the world (FAO, 2010-2012). In Vietnam, commercial production of Tra
catfish has increased dramatically over the past decade. Total production in 2010
reached 1,141,000 tonnes and Tra product was exported to many countries with an
estimated annual export income to Vietnam of USD$ 1.4 billion (De Silva and Phuong,
2011). As a consequence of the growing importance of catfish as an export product,
many sectors of Vietnamese society have participated in development of catfish farming
in the south of the country. Vietnam is by far the world’s largest producer of P.
hypophthalmus and was ranked third in the world for total aquaculture production with
an annual average growth rate of 20.9% between 2000-2008 (FAO, 2010).
Chapter 1: General introduction 21
The catfish culture industry in Vietnam has grown rapidly since development of
successful artificial propagation techniques for Tra catfish (Cacot et al., 2002). Over the
last decade, farming of Tra catfish has expanded, and pond farming has become the
dominant practice because this approach achieves the best growth rates, flesh quality,
and hence increases value and international acceptability of the product (Phan et al.,
2009). To maintain the quality of farmed catfish product however, and to confirm Tra
catfish’s place in the market, the Vietnamese government has recognised that research
will need to focus on increasing growth rate, improving fillet yield & quality, improving
disease resistance, and more recently on increasing salinity tolerance (due to predictions
of climate change impacts in the Mekong Delta). In general, breed development via
genetic improvement programs offers great potential to optimise production efficiency
of farmed Tra catfish.
1.7.4 Previous studies of P. hypophthalmus To date, significant research effort has been directed at enhancing growth performance
of P. hypophthalmus under various environmental conditions (Güroy et al., 2013; P et
al., 2011; Shinsuke et al., 2009; Slembrouck et al., 2009; Van Sang et al., 2007;
Yukinori et al., 2010), increasing immune resistance of individuals against virulence
factors (i.e Ewardsiella ictaluri – the cause of Enteric Septicaemia of Catfish) (Bartie et
al., 2012; Crumlish et al., 2010; Dung et al., 2012; Thinh et al., 2009; Tu et al., 2008),
exposure trials of fish to toxic environmental conditions (Danyi et al., 2011; Pierrard et
al., 2012a; Pierrard et al., 2012b; Yamaguchi et al., 2007) and investigations of fish
physiology and phylogenetic relationships (Giang et al., 2012; Lefevre et al., 2011a;
Lefevre et al., 2011b; Lefevre et al., 2013; Prabjeet et al., 2011).
To date, little attention has been paid to genetic improvement of farmed Tra catfish
culture stocks. A recent study by Poen and Pornbanlualap (2013) documented genomic
Chapter 1: General introduction 22
and cDNA sequences for the growth hormone gene from P. hypophthalmus and
discussed the process for sequencing expressed and purified forms of the recombinant
protein and then analysed the folding of the protein. To date, however the only
transcriptomic analysis of P. hypophthalmus that has investigated salinity tolerance in
this species was a very recent study that exposed individuals to 9ppt salinity (Thanh et
al., 2014).
1.8 RESEARCH GOALS
In the future it is recognised that there will be a need for Tra catfish culture strains that
can tolerate raised salinity conditions as the areas of saline water-intruded land in the
MRD in Vietnam expands as a consequence of predictions of climate change impacts on
regional sea levels. The current study was designed to identity and characterise
functional genes in Tra catfish related to the trait of interest (i.e. salinity tolerance)
where the data can be applied to future breeding programs for this species in Vietnam.
Culture lines with improved salinity tolerance can potentially be developed by
integrating traditional breeding programs (selective breeding) with genetic markers
related to the traits of interest (i.e. marker assisted selection).
The aim of current study was to develop genomic data on candidate genes affecting
salinity tolerance in Tra catfish via comparison of gene expression patterns obtained
from analysis of two cDNA libraries (developed form FW and BW exposed individuals)
collected from different organs to better understand transcriptomic regulation in P.
hypophthalmus exposed to elevated salinity levels. RNA-seq technology was used to
generate transcript catalogues of up- and down-regulated genes from Tra catfish
exposed to different salinity conditions. In addition, gene regulation and expression
patterns of specific candidate genes were assessed to further understand how Tra catfish
acclimate to raised, sub-lethal osmotic environments.
Chapter 1: General introduction 23
Specific aims
Assemble a reference transcriptome dataset for P. hypophthalmus using RNA
from multiple osmoregulatory tissues.
Annotate transcripts to provide a reliable resource of genomic data for Tra
catfish.
Undertake differential gene expression analysis from selected tissues.
Develop a simple molecular model of how P. hypophthalmus potentially
acclimates to raised salinity concentrations.
Chapter 1: General introduction 24
Chapter 2: Reference transcriptome generation and data analysis
2.1 INTRODUCTION
Recent technological developments in NGS technologies have created broad interest in
genomics research. Analysis of transcript expression patterns requires mapping of raw
reads to a reference genome and this is not an easy task since genome sequencing can be
difficult and costly. Even today, full genome sequences are still only available for a
limited number of common well-studied species; thus a large portion of genome
reference sequences are not widely available for non-model species. Advances in
technologies over recent years enable researchers now to target non-model species’
transcriptomic data using a novel approach that involves assembling the transcriptome
de novo, without a requirement for a reference genome. The de novo assembly approach
provides a rapid method for unlocking the massive potential for genomics analysis of
novel species.
Some problems however, still exist with this approach, at least when considering the
software available currently for analysis of raw data. To generate the most
comprehensive reference transcriptome for a new species it is important to increase
continuity as well as assembly quality. In the current study therefore, a comparative de
novo assembly was applied, and this was linked to a post assembly clustering process
for our target organism. After generating the de novo assembled transcript, this large
dataset was annotated automatically, then assigned gene ontology classifications that are
available online (i.e. NCBI non-redundant database, SWISS-PROT, RefSeq) to provide
the basic data required for later differential gene expression analysis.
Chapter 2: Reference transcriptome generation and data analysis 25
In brief, this chapter reports on the first component of the current study; namely NGS
sequencing of the Tra catfish (P. hypophthalmus) transcriptome and generation of a
reference transcriptome for downstream analysis. Using a variety of bioinformatics
software packages were used here, to create the most comprehensive de novo
transcriptome available currently for the target species for later annotation and to
analyse transcript functionality.
2.2 MATERIALS AND METHODS
2.2.1 Sample collection and RNA extraction P. hypophthalmus fingerlings ranging from 8-10 g/individual were reared under a raised
salinity conditions (15ppt) and a control condition (0ppt) for an experimental period of
eight weeks at the International University Biotechnology Laboratory Complex, Ho Chi
Minh City, Vietnam. Before RNA sampling, fish were euthanized with MS-222 (300
mg/l), then individuals weighed and measured for body weight and length. Individuals
with the best growth performance in each salinity treatment were chosen based on size
and tissue samples taken from a variety of organs. Osmoregulatory tissues collected
included: gill, intestine and kidney. These tissues were chosen because they are
considered to be primary osmoregulatory organs in teleost fish. Tissue samples were
preserved in RNAlater (Ambion) and stored at -80oC for later use. Samples were then
transported to the Molecular Genetics Research Facility at the Queensland University of
Technology Brisbane, Australia for RNA extraction, sequencing and downstream
analysis. For each tissue type, samples from three different individuals were pooled
together to create a master pool.
In brief, tissues were first snap frozen and then homogenized in liquid nitrogen.
TRIzol/Chloroform reagent (Invitrogen) was used to aid in extraction of total RNA. For
each ground sample, 1000 ml of Trizol and 200 ml Chloroform were added to improve
Chapter 2: Reference transcriptome generation and data analysis 26
RNA quality. Total RNA was further purified using an ISOLATE II RNA Mini Kit
(Bioline). Total RNA quality was then checked using A260/280 ratios with a Beckman
Coulter spectrophotometer, visualized through gel electrophoresis and finally on a
Bioanalyzer 2100 (Agilent). All RNA had to be checked for purity, concentration as
well as RNA integrity number (RIN). Samples with high RIN values (7-10) were
chosen for cDNA library construction. Following this, mRNA from each tissue was
isolated using a Dynabeads mRNA Purification Kit (Invitrogen) according to the
manufacturer’s protocol. mRNA quality checking was performed using a Bioanalyzer
2100 (Agilent). All total RNA and mRNA profile details are available in supplementary
material (Appendix A4).
2.2.2 cDNA library generation High quality, non-degraded mRNA purified from the three tissue types was then
fragmented into 200-400 bp fragments using an Ion Total RNA-Seq kit (Life
Technologies) and cleaned with RiboMinus Concentration Module (Invitrogen). All
mRNA fragments were then converted to cDNA using the Ion Total RNA-Seq kit (Life
Technologies) according to the manufacturer’s guidelines. In brief, the cDNA library
for each tissue comprised a pool of cDNAs prepared from the three heaviest individuals
raised at each salinity concentration. cDNA yields were quantified using a Qubit 2.0
fluorometer (Invitrogen) and a Bioanalyzer 2100 (Agilent). Template preparation for
sequencing was conducted according to the Ion OneTouchTM Template Kit (Life
Technologies) using the Ion XpressTM template 200 sequencing protocol.
2.2.3 cDNA sequencing using Ion Proton Next Generation Sequencer Resulting cDNA from successful amplification and ligation with adapters from each
tissue library were then subjected to sequencing using P1 semiconductor chips and the
Ion Proton Sequencing Kit (Life Technologies) according to the manufacturer’s
Chapter 2: Reference transcriptome generation and data analysis 27
protocol at Queensland University of Technology Molecular Genetics Research Facility
(MGRF). Samples from each tissue were barcoded for identification. Two P1
semiconductor chips were used, each contained three cDNA libraries.
2.2.4 Data filtering and quality control cDNA libraries from each tissue were sequenced using the Ion Proton sequencing
platform. Following the sequencing step, adapter sequences as well as barcodes were
removed using integrated Ion suite software (Life Technologies). All FASTQ files were
exported, backed up, stored and subjected to further quality control. Raw reads were
first checked for preliminary statistics and quality using FastQC software
(http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and then filtered using the
NGSQC-toolkit (Patel and Jain, 2012) applying the following parameters: trim low-
quality sequences (Q < 20), trim short length read (length < 25), trim ambiguous bases
(Ns sequence) and removal of homopolymer sequences. All downstream analyses were
based on clean data of high quality via the bioinformatics analysis pipeline illustrated in
Figure 4.
Chapter 2: Reference transcriptome generation and data analysis 28
Figure 4. Bioinformatics analysis used in the current study
Chapter 2: Reference transcriptome generation and data analysis 29
2.2.5 De novo assembly of reference transcriptome In order to generate the highest quality reference transcriptome, we used three different
de novo assemblers to generate a reference transcriptome, namely; Trinity (Grabherr et
al., 2011; Schulz et al., 2012), Velvet/Oases (Schulz et al., 2012; Zerbino and Birney,
2008) and SOAP de novo Trans (Xie et al., 2014). All quality controlled libraries were
then merged, resulting in a single Fasta file that could be loaded on each de novo
assembler. Briefly, Trinity was run using all default parameters with a k-mer of 25.
Velvet was run using the multi k-mer approach from 55 to 103 with a k-mer step of 6.
All assemblies from Velvet were then loaded into Oases for transcript assembly. Soap
de novo Trans k-mer ranged from 43 to 97 with a k-mer increment of 6. All de novo
assemblies were checked using the Perl script Count_fasta.pl retrieved from
http://wiki.bioinformatics.ucdavis.edu/index.php/Count_fasta.pl. Assembly statistics
were recorded and a comparative analysis between de novo assemblers was conducted.
Scripts were used in the current study can be found in the supplementary material
(Appendix A5)
2.2.6 Post-assembly clustering The three independent assemblies were then merged and clustered to produce a final
single reference transcriptome for further downstream analysis. We used tr2aacds
software (Gilbert, 2013), an mRNA transcript assembly pipeline script for this task.
This pipeline processed a large number of transcripts from all assemblies, classified
them into clusters to remove redundancy and initiated final elongation of all transcripts.
The pipeline algorithm is designed based on CD-HIT-EST for fragment removal and
BLASTN algorithm to align exons in all transcript assemblies, and determine which
transcripts belong to the same or different gene loci.
0 30
2.2.7 Reference transcriptome analysis The complete reference transcriptome was then scanned against three protein databases
including the zebrafish RefSeq database, the manually curated Swiss-Prot database and
the NCBI non-redundant database (nr) using the Blastx algorithm with E values set at
1.0×10-6 using Queensland University of Technology High Performance Computing
cluster. BLAST+ version 2.26 (command line version) was used for this process
(Camacho et al., 2009). Output xml files were then processed for gene ontology
discovery using the BLAST2GO suite (Conesa et al., 2005). All annotated transcripts
were used to determine Eukaryotic Clusters of Orthologous and Groups of proteins
(KOG) terms. Finally, Web Gene Ontology Annotation Plot (WEGO) software (Ye et
al., 2006) was used to characterize the distribution of gene functions from the generated
reference transcriptome.
2.3 RESULTS
2.3.1 Ion Proton sequencing and quality control of raw reads In brief, Ion Proton cDNA sequencing was carried out on libraries constructed from
three osmoregulatory tissues type that included gills, kidney and intestine. Results from
Ion Proton sequencing produced six libraries that consisted of 174,902,133 raw reads
with read lengths varying between 8 to 351 bp. This gave a total in excess of 37.8 GB of
raw sequence data. FASTQ files of read data quality were assessed and are available in
supplementary material (Appendix A3). We checked quality statistics including
distribution of PHRED score, read length distribution, consistent GC content between
tissue samples and N bases in each tissue library. Only quality-trimmed reads were then
used in all downstream analyses. Raw reads and post quality control statistics are
summarized in table 1.
Chapter 2: 31
Table 1 Summary of raw reads from Ion Proton sequencing and quality control
Tissue Gill Intestine Kidney
Group 15ppt 0ppt 15ppt 0ppt 15ppt 0ppt
Number of raw 30,867,840 26,322,161 23,973,359 23,132,580 31,343,807 30,592,625 reads
Read length (bp) 8-341 8-344 8-341 8-351 8-344 8-347
% GC 50 48 49 49 49 48 Number of reads 28,819,795 24,307,664 22,018,855 21,643,310 28,745,087 28,484,509 after trimming
Percentage of reads after 93.46 92.35 91.85 93.56 91.70 93.11 trimming (%)
2.3.2 Comparative de novo assembly Of the three assemblers using in the current study, only Velvet/Oases and SOAP de
novo allowed a multi k-mer approach to be deployed. Trinity, in contrast was locked to
run specifically at k-mer 25, and generated 281,941 transcripts with an N50 of 578. In
contrast, Velvet/Oases and SOAP de novo software yielded different results by applying
multiple k-mer steps. Velvet/Oases appeared to provide the best N50 and average length
for k-mer step 55, 61 and 73 (figure 5), very poor assembly statistics were also noticed
with k-mer steps larger than 97, which were discarded. While SOAP de novo Trans
generated good assembly at k-mer 43 and above 67 (figure 6). Of interest, we observed
that as the k-mer step increased, fewer reads were used for the assembly, resulting in a
situation where good transcript continuity was available but the total base pair number
in transcripts generated decreased dramatically.
Chapter 2: 32
Velvet/Oases de novo assembly statistics 550 500 450
bp 400 350 300 55 61 67 73 79 58 91 97 mean length 448 447 332 461 465 463 468 403 n50 506 504 325 498 475 448 383 389
Figure 5. Velvet/Oases assembly statistics
SOAP trans de novo assembly statistics 420 400 380 360 bp 340 320 300 43 49 55 61 67 73 79 85 91 97 mean 328 316 308 310 311 333 353 370 388 404 n50 328 314 302 304 306 328 348 364 380 395
Figure 6. SOAP de novo Trans assembly statistics
Post assembly processing including combining and clustering transcripts was initiated
immediately after we recovered all fasta files from the three assemblers. All assemblies
were concatenated and renamed to avoid duplicates. After loading all assemblies into
the tr2accds pipeline, the final transcriptome reference sequence consisted of 60,585
non-redundant transcripts with an N50 transcript length of 638 and an average transcript
length of 555 bp. In total, our reference transcriptome included more than 33 million
base pairs (33Mbp). Moreover, we recorded 5,819 transcripts that were greater than
Chapter 2: 33
1,000 bp in length; the distribution of transcript length is presented in figure 7. A brief
summary of transcripts assembly statistics are provided in table 2.
30000
25000
20000 sequences 15000 of
10000 Number
5000
0
Sequence length
Figure 7. Transcripts length distribution after tr2accds pipeline. The x-axis represents the sequence length in base pairs. The y-axis represents the number of transcripts relative to the sequence length.
Table 2. Summary of de novo assembly results for Ion Proton data in (P. hypophthalmus) after the tr2accd pipeline
Number of transcripts 60,585
Total bases in transcripts 33,686,013
Number of large transcripts (>1,000bp) 5,819
N50 (bp) 638
Longest transcript size (bp) 18,156
Average transcript length (bp) 555
Chapter 2: 34
2.3.3 Gene identification and annotation Gene identification was conducted using the BLASTX algorithm. After gene
annotation, 37,965 transcripts showed significant BLAST hits against 15,178 unique
zebrafish genes. The highest number of matches was with the NCBI nr database with
39,332 transcripts associated with 21,321 unigenes. The Swiss-Prot database resulted in
a lower number of matches, this is normal since the Swiss-Prot database is manually
curated and does not contain any predicted protein sequences. A summary of gene blast
statistics is presented in table 3.
Table 3. Summary of gene identification of assembled (P.hypophthalmus) transcripts
Zebrafish RefSeq Swiss-Prot NCBI nr
Transcripts with 37,965 33,757 39,332
gene match
Unigene match 15,178 18,911 21,321
Hypothetical gene 636 0 445
Top-Hit species distribution matched against the nr protein database included; zebrafish
Danio rerio (52.01%), a model teleost species that has been studied extensively over
the last decade, Nile tilapia Oreochromis niloticus (4.96%), channel catfish Ictaulurus
punctatus (3.20%), platyfish Xiphophorus maculatus (3.12%), medaka Oryzias latipes
(2.60%) and other species (15.99%) (Figure 8).
Chapter 2: 35
Top‐hits species distribution
Others Mus musculus Homo sapiens Xenopus (Silurana) Oncorhynchus mykiss Daphnia pulex Dicentrarchus labrax Latimeria chalumnae Ictalurus furcatus Tetraodon nigroviridis Pundamilia nyererei Haplochromis burtoni Takifugu rubripes Salmo salar Maylandia zebra Oryzias latipes Xiphophorus maculatus Ictalurus punctatus Oreochromis niloticus Danio rerio 0 5000 10000 15000 20000 25000
Figure 8. Top-hit species distribution from BlastX
Using BLAST2GO, all transcripts were matched automatically with previously known
sequences in the online database and assigned a GO number that corresponded with
gene function (see figure 9). Out of 60,585 transcripts, where 27,988 transcripts
(46.19%) were fully annotated, 6,197 transcripts (10.22%) showed a blast result while
5,147 transcripts (10.22%) showed both blast and mapping results. 21,253 transcripts
(35.07%) resulted in no blast-hits in the protein sequence database. These transcripts
could potentially be novel proteins that have no similar sequence in the database or
potentially non-coding RNAs not reported previously. Further characterisation of the
reference transcriptome including WEGO and KOG data are available in Appendix B.
Chapter 2: 36
Without blast result 35% With blast result 10% Other 19%
Annotated With mapping sequence result 46% 9%
Figure 9. Proportion of transcripts with BLASTX matches and GO term annotation
2.4 DISCUSSION
2.4.1 Sequencing of the cDNA library and post sequencing quality assessment The first stage of the study was to use next generation sequencing in order to sequence
and analyse a reference transcriptome from Tra catfish. All P. hypophthalmus tissues
selected provided a broad range of transcript data in the RNA-seq experiment. We were
able to extract RNA from all tissue at high concentration that possessed good integrity
(qualified by RNA integrity number). The Ion Proton as a bench top next generation
sequencing platform allows cost-effective methods over a short runtime for generation
of cDNA as well as RNA-seq data. In the current study, over 179 million reads were
generated from the tissue samples screened, with read length varying from 10 to
approximately 350 bp. In a comparison with a recent study of the same species that
used the Ion Torrent PGM platform (Thanh et al., 2014), our study greatly increased the
number of raw sequences generated as well as the depth of analysis. It was not possible
however, to generate paired end sequencing data on the Ion Proton in order to increase
Chapter 2: 37
accuracy of this step. A comparison between relative performance of different bench-
top next generation sequencing platforms can be found elsewhere (Chen et al., 2014).
In the current study, each sample library on average produced more than 25 million
reads. The vast amount of reads was achieved to ensure good quality as well as quantity
for all downstream bioinformatics analyses. It is a requirement that raw reads need to be
first cleaned to remove bad quality reads, ambiguous Ns and short reads that may stack
up and increase error rate of assemblers (El-Metwally et al., 2013). Quality trimming
parameters were decided shortly after the report from the quality checking step was
retrieved. In the current study, raw reads were cleaned based on quality read score
(PHRED score); we chose a PHRED score threshold of 20 to ensure read quality for de
novo assembly (99.9% base call correct rate). Read length trimming was set at 25 since
the minimum k-mer used in the de novo assembly process was set at 25 (with Trinity).
Moreover, as homopolymers can be an issue previously detected with the Ion Torrent
and Ion Proton sequencers (Bragg et al., 2013; Loman et al., 2012; Quail et al., 2012),
we set the homopolymer trimming threshold at 8 to address this potential problem. As
indicated earlier however, a large proportion of reads still remained after the quality
trimming process, confirming the quality of the sequencing process.
2.4.2 Comparative de novo assembly and clustering approach A de novo assembly approach was used to generate the reference transcriptome for P.
hypophthalmus by combining the datasets for the 0ppt and 15ppt libraries. Here we
attempted to generate the highest quality reference transcriptome from raw reads by
applying independently results from three different assemblers that included Trinity,
Velvet/oases and SOAP de novo Trans. Of the three, Trinity and SOAP de novo Trans
are currently under active development, while development of Velvet/Oases has been
halted recently. All three assemblers are based on the de Bruijn graph algorithm for
Chapter 2: 38
short read transcript assembly. It is important to note however that there can be a
significant disadvantage associated with de novo assembly compared with a reference
based assembly, namely a limitation on computational resources. As the de Bruijn
graph algorithm constantly builds up graphs and nodes between reads, it can consume
all of the RAM available in the system, thus it requires the use of a cluster computing
infrastructure or cloud computing to be successful. The assembly of massive amounts
of raw data generated from a NGS platform is widely accepted currently as a major
bottleneck for bioinformatics analysis (Schadt et al., 2010). At QUT, we accessed the
local HPC cluster that is capable of running all software with 16 CPUs and more than
256GB of RAM. In spite of this computing capacity, de novo assemblies still required a
large amount of time to complete.
To date, a variety of comparative studies have been conducted on performance analysis
of de novo assemblers to assess and optimize pipelines to produce optimum reference
transcriptomes (Clarke et al., 2013; Zhao et al., 2011). As results from our study show,
different assemblers provide slightly different transcript results. Technically, Trinity by
default is locked to run at k-mer 25, while Velvet/Oases and Soap de novo Trans can
adjust their k-mer steps. Our observations showed that N50 length, average length as
well as assembly statistics varied greatly not only between de novo assemblers but also
among k-mer value employed within each assembler. Our results suggested that Trinity
to be the best de novo assembler for RNA-seq data, in comparison with the
Velvet/Oases package and SOAP de novo Trans. Moreover, we noticed as k-mer step
increased, fewer reads were used, and both assemblers appreared not to use the raw
reads as well with k-mers larger than 90. This is due to the de Bruijn graph algorithm,
where at a specific k-mer, all reads with a read length shorter than this k-mer are
discarded, so as k-mer value increased, fewer reads can be used in the assembly step,
producing this phenomenon (Zerbino, 2009). It is also important to note that there is no
golden standard for de novo assembly, each assembler can provide better assembly
Chapter 2: 39
quality for different gene loci type, as well as a large variation in k-mer value,
assembler algorithm to address bubble effect, mismatches and other errors that may
require various options and various optimized parameters. This leads to the recognition
that no single assembler is superior in assembly quality over all others (Ya and Stephen,
2013; Zhao et al., 2011). It was also previously known that transcriptome assembly
with a single k-mer cannot generate an assembly with both transcript discovery as well
as transcript contiguity. In conclusion, as has been suggested in some earlier studies, a
multi k-mer approach can improve overall assembly statistics (Robertson et al., 2010;
Surget-Groba and Montoya-Burgos, 2010; Zhao et al., 2011).
In the next step in the process, tr2aaccds, a newly developed software pipeline was used
to combine data from all three assemblies, to cluster them into similar groups and to
extend the continuity of individual transcripts. Applying the tr2accds pipeline resulted
in a significant improvement in both N50 and average length. A higher N50 length and
average transcript length are often considered to provide the benchmark for de novo
transcript assembly quality. We observed that by merging and clustering the transcripts,
a more comprehensive and less redundant transcriptome assembly was achieved.
Recently, a study that employed the tr2aacds pipeline also recorded an increment in
diversity of de novo assembled transcripts and their completeness, while limiting
sequence redundancy (Nakasugi et al., 2014). It is, therefore reasonable to assume that
merging and combining assemblies from various k-mer and various de novo assemblers
can create a much more comprehensive reference transcriptome. One possible weakness
of clustering transcripts from a number of assemblers together however, is the
unavoidable loss of isoforms. Isoform detection however, requires deep coverage of
transcriptome sequencing, as well as availability of a reliable reference genome, which
were both beyond the scope of the current study.
Chapter 2: 40
2.4.3 Transcriptome analysis Functional annotation is extremely important in any transcriptome study, with the
annotation step essentially acting as the connection between raw sequences and
downstream analysis, and allowing biological interpretation of results.
With rapid development of NGS technologies, new sequencing platform nowadays can
generate massive amounts of data (Baker, 2010; Nekrutenko and Taylor, 2012). The
major barrier now for next generation sequencing datasets is the computational
resources needed to analyse very large datasets. Automated software has been created
in order to keep pace with the amount of data generated from NGS sequencers, and as
transcripts generated during de novo assembly contain more than 100,000 transcripts,
manual annotation of all transcripts can be very time and effort consuming. BLAST+,
an automated tool is suitable for this task (Camacho et al., 2009). This software
translates all transcripts into protein sequences and scans databases (which can either be
a local or online database) for any matched protein sequences. Theoretically, thousands
of transcripts can be blasted within hours of runtime. Users can freely adjust the
parameters within the program including hits threshold, mismatch penalties and matrix
used. As implied in the blast results for the P. hypophthalmus transcriptome, a
significant number of protein hits were achieved against the NCBI non-redundant
database.
A large number of transcripts were detected with significant blast scores (e-value lower
than 10-6). Many transcripts were matched with those in closely related species, namely
channel catfish (I. punctatus) and the blue catfish (I. furcatus). The vast majority of
transcript matches, however, were matched with the well-studied model species,
zebrafish (D. rerio). This is to be expected due to the disproportionately high number of
sequences available for these species. Blast results also consisted of some microbial
Chapter 2: 41
related sequences, but this is also normal as microbial communities are found in the gut
or on the gills of P. hypophthalmus (data not shown).
Apart from BlastX, the BLAST2GO suite is a user-friendly software package that
allows fast assignment of gene ontologies. The automated search package is designed to
enhance research output, but sensitivity as well as accuracy can vary. While the
annotation that resulted from the current dataset was large in spite of the high E-value
threshold employed; a portion of transcripts still remained unannotated. This set
comprised transcripts without a coding sequence, or those that coded for a novel protein
without any match in the database. Nevertheless, more than 50% of all transcripts
generated from the de novo assembly were fully annotated. This has provided a large
resource for gene expression studies in P. hypophthalmus in the future.
Chapter 2: 42
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance
3.1 INTRODUCTION
Over recent years, new NGS technologies have had a major impact on genomic studies.
When compared with traditional methods for identifying differentially expressed genes
including microarrays, serial analysis of gene expression (SAGE) or massive parallel
signature sequence (MPSS), an RNA-seq approach using NGS offers a high throughput
direct sequencing method that provides high efficiency at relatively low cost with low
background noise. Moreover, RNA-seq has a clear advantage over other current
technologies because it can be applied to any species, overcoming the lack of genomic
resources available for non-model species that in general, are only distantly related to
species with a characterised genome. Prior to the current study, only limited genomics
resources were available for Tra catfish (P. hypophthalmus), and so an RNA-seq
approach was therefore, considered appropriate.
In brief, RNA-seq offers many clear advantages over other classical approaches for
generating transcriptomic data. RNA-seq is a direct sequencing method, that produces
very low background noise and raw reads can be used to map back to a de novo
reference transcriptome. Quantification is based on the total number of unique
sequences and this allow researchers to detect a broad range of expression patterns with
higher sensitivity (see a benchmarking approach by Sîrbu et al. (2012)). RNA-seq also
allows analysis of putative single nucleotide polymorphisms (SNPs) that have a
potential to affect gene function. Importantly, an RNA-seq approach can be undertaken
on any species, without a requirement for previous knowledge of the species
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 43
genome/transcriptome. Previously, RNA-Seq data had to be mapped to a
reference genome; however, recent advances in bioinformatics have now made it
possible to bypass this step and assemble RNA-Seq data into a de novo transcript. For
all the reasons above, RNA-seq is likely therefore, to revolutionize the manner in which
non-model eukaryotic transcriptomes are investigated in the future (Wang et al., 2009).
Comparison of gene expression patterns under varying experimental conditions can be a
very powerful approach for identifying candidate genes that affect traits of interest.
Physiological changes are often driven by regulation of gene expression that can be
analysed/characterized using a comparative transcriptome analysis approach. In the
current study, we used pooled samples, generated from combining samples from a
number of different individuals into three replicates in order to investigate the
expression pattern of genes affecting salinity tolerance in P. hypophthalmus. The goal
of this section was to gain a broad overview about physiological mechanisms in P.
hypophthalmus when individuals were exposed to elevated salinity conditions as well as
looking for possible pathways that influence the salinity tolerance trait. Data generated
from this study can be used later to examine specific candidate genes that may be
applied to trait improvement.
3.2 MATERIALS AND METHODS
3.2.1 Differential gene expression analysis For analysis of differential gene expression profiling, quality trimmed reads from each
library were mapped onto the P. hypophthalmus transcriptome reference assembly
using CLC Genomics Workbench software (CLC Inc, Aarhus, Denmark) . During
mapping, at least 90% of the read bases with a 2 mismatch allowance were required to
align with the reference transcriptome to be accepted as a “hit”. Total mapped reads
were calculated and then normalized to generate RPKM (reads per kilobase of exon per
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 44
million mapped reads). Only transcripts with a unique read count larger than 10 and
RPKM > 1 were considered to have been expressed. For statistical test purposes, a
proportions-based test was used to identify differentially expressed genes applying the
Kal Z-test (Kal et al., 1999) followed by determination of an FDR corrected p-value
(Benjamini and Hochberg, 1995). In brief, any fully annotated transcript with an
absolute fold change between the two experimental salinity conditions larger than 2 and
FDR corrected p-value ≤ 0.01 (1 false discovery for 100 transcripts) was considered to
be a differentially expressed gene. Only transcripts with previously identified gene
annotations were taken forward for further analysis.
3.2.2 Gene ontology and enrichment analysis In order to identify overrepresented GO annotated genes in the differentially expressed
transcript set, we compared the gene list statistically against the broader reference
assembly using Fisher’s exact test available in BLAST2GO software (Conesa et al.,
2005). A P-value cutoff of 0.1 was applied in this analysis. Results were exported into
an Excel spreadsheet, and then filtered prior to further analysis.
3.3 RESULTS
3.3.1 Differential gene expression analysis To test for significantly up or down-regulated genes, individual reads from each sample
were mapped back to the assembled transcriptome, merged with annotation and
statistical analysis tests applied using the RNA-seq module in the CLC Genomics
Workbench. Transcript expression levels were calculated based on RPKM value. After
setting the threshold (indicated previously in the methods section and filtering out all
unannotated transcripts), we recorded in total 3026 annotated transcripts that were
differentially expressed in three experimental osmoregulatory organ libraries (table 4).
Descriptive analysis results from the CLC Genomics Workbench are provided in table
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 45
5. Comparisons were made between two salinities (0ppt and 15ppt) in three different
osmoregulatory organs, respectively. This list consisted of many transcripts sorted
based on Fold change, p-value and FDR-corrected value. Comparisons of the gill
library yielded the highest number of differentially expressed genes among the three
tissues (twice the number of the lowest, kidney). All identified differentially expressed
transcripts from each tissue library have been included in supplementary material
(Appendix A1).
Table 4. Number of genes differentially expressed following salinity exposure
Down- Total Up-regulated Tissue regulated differentially transcripts transcripts expressed genes
Gill 736 587 1,323
Intestine 473 540 1,013
Kidney 351 339 690
Figures 10, 11 and 12 present volcano plots of differentially expressed transcripts in
intestine, gill and kidney, respectively. Each dot represents a single transcript that had a
FDR-value less than 0.01. These plots present the inverse log10 of the FDR value against
the log2fold changes.
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 46
Figure 10. Volcano plot of DGE in intestine. Dots represent transcripts that were up/down regulated in the current treatment.
Figure 11. Volcano plot of DGE in gill. Dots represent transcripts that were up/down regulated in the current treatment.
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 47
Figure 12. Volcano plot of DGE in kidney. Dots represent transcripts that were up/down regulated in the current treatment.
3.3.2 Gene onotlogy enrichment analyses All differentially expressed genes were then used to perform a GO function and
pathway analysis enrichment test. The most specific GO terms overrepresented in
upregulated genes included apoptotic process (GO: 0006915), regulation of translation
(GO: 0006417), translational elongation (GO: 0006414), regulation of actin filament
polymerization (GO: 0030833) and cellular response to xenobiotic stimulus (GO:
0071466). In contrast the most specific GO terms overrepresented by downregulated
genes after salinity challenge included; oxidation-reduction process (GO:0055114), ion
transmembrane transport (GO:0034220), intracellular protein transport (GO:0006886)
and endocytosis (GO:0006897). Results of GO enrichment analysis for P.
hypophthalmus indicate that multiple biological processes are influenced by exposure to
different salinity levels. Results of the GO pathway enrichment analysis have been
included in supplementary material (Appendix C).
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 48
3.4 DISCUSSION
Earlier, the study reported on a comparative de novo assembly approach and generation
of a reference transcriptome for P. hypophthalmus. Here, we aimed to identify and
characterize all genes that were up or down regulated in P. hypophthalmus individuals
exposed to two different environmental salinity conditions. Moreover, we aimed to
develop a broad catalogue of genes as well as target candidate genes that potentially
contribute to salinity acclimation in P. hypophthalmus under elevated salinity
conditions. CLC Genomics Workbench (CLC) was employed for the analysis of
differential gene expression between the two salinity treatments. As a commercial
product, CLC is designed to be very easy to use with a point-and-click interface.
Filtered reads can be mapped back to the annotated reference transcriptome with all
mapping parameters identified earlier (materials and methods section). CLC then
calculates the RPKM value automatically for each transcript under different treatment
conditions and then calculates the fold change between them. Only transcripts with a
unique read count larger than 10 and RPKM > 1 were considered to have been
expressed. This threshold was set to ensure sufficient expression of each transcript to
make sure the data satisfy a significant difference between experimental conditions. As
implied earlier, we applied the Kal-Z statistical test to calculate FDR p-value, a
threshold to prevent detection of false differentially expressed transcripts. Kal-Z was
considered suitable for this purpose because the test compares a single sample against
another single sample, and thus requires that each group in the experiment contains
only a single replicate.
For P. hypophthalmus, we identified 3026 unigenes that were differentially expressed in
three osmoregulatory organs: gill, kidney and intestine. Results of the gene enrichment
analysis suggest however that exposure to 15ppt salinity potentially could have
generated a negative stress response rather than an adaptive response in P.
hypophthalmus. A recently published study of P. hypophthalmus has suggested that
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 49
growth performance of P. hypophthalmus is optimal at 9ppt, while individuals
maintained at 18ppt showed a significantly compromised growth rate as well as lower
survival rate of individuals (Nguyen et al., 2014). Results indicate that at 9ppt,
osmolality between external and internal pressure in P. hypophthalmus was essentially
equal, thus individuals were able to divert energy from maintenance of osmotic pressure
to muscle growth. In contrast, exposure to higher salinities, i.e. above 9ppt can trigger
stress responses where individuals need to divert energy away from metabolism and
growth to deal with a perceived physiological osmotic stress. This is achieved by
balancing of homeostatic equilibrium and repairing as well as killing any damaged
cells. Animal cells can counteract osmotic imbalance by triggering a regulatory volume
increase (RVI), an internal process that initiates a net gain in osmolytes and/or water,
increasing cell volume that re-establishes normal values and prevents cell shrinkage.
When however, excessive cell shrinkage potentially reaches a critical point after
exposure to hyperosmotic conditions, this can result in cell death, an outcome that may
explain why there is an overrepresentation of death, programmed cell death and
apoptosis GO terms in the enrichment test at 15ppt. Meanwhile, it is possible that
overrepresentation of GO terms related to ion transport in the down regulated genes
could be related to the growth rate of the individual chosen, as individuals can store the
energy from pumping ions and redirect this towards growth.
Based on the enrichment analysis, annotation and published literature, a list of
candidate genes potentially involved in salinity acclimation in Tra catfish (P.
hypophthalmus) were categorized into six keys groups including; genes involved in
immune and cell protection, energy metabolism, signal transduction, ion transport,
protein encoding and genes involved in the detoxification process (Table 5).
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 50
Table 5. Candidate genes in osmoregulatory tissues differentially expressed at 0ppt and 15ppt salinity concentrations
Gene description Tissue Min fold Primary gene function
change
14-3-3 protein zeta delta Gill 2.34 Signal transduction
Serine threonine-protein kinase sgk1-like isoform x1 Gill 14.72 Signal transduction
Rho GTPase-activating protein 29-like isoform x1 Gill 4.44 Signal transduction
Rho GTPase-activating protein 17-like isoform x2 Gill 4.46 Signal transduction
Rho GTPase-activating protein 27-like isoform x2 Kidney 2.76 Signal transduction
Mitogen-activated protein kinase 4 Gill 4.18 Signal transduction
Mitogen-activated protein kinase 13 Intestine 2.85 Signal transduction
Mitogen-activated protein kinase 19 Kidney 4.00 Signal transduction
Aquaporin 3 Gill -2.23 Ion transporter
Apolipoprotein a-iv Intestine 2.68 Ion transporter
Solute carrier family facilitated glucose transporter member 1 Gill 2.51 Ion transporter
(GLUT1)
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 51
sodium- and chloride-dependent taurine transporter Gill 2.55 Ion transporter sodium- and chloride-dependent taurine transporter-like isoform x1 Kidney 2.09 Ion transporter
(TAUT1)
Sodium bicarbonate cotransporter 3-like protein Gill 6.63 Ion transporter
Sodium calcium exchanger 1-like Gill 12.73 Ion transporter
Sodium myo-inositol cotransporter 2 Gill 32.74 Ion transporter
Sodium myo-inositol cotransporter 2 Kidney 2.93 Ion transporter
Sodium glucose cotransporter 1 (SLGT1) Intestine 2.26 Ion transporter
Sodium glucose cotransporter 2 (SLGT2) Kidney 2.93 Ion transporter
Apoptosis-stimulating of p53 protein 1 Gill 3.45 Cell protection and immunity
Apoptosis-stimulating of p53 protein 1 Intestine 3.32 Cell protection and immunity
Bcl2 antagonist of cell death Intestine 2.32 Cell protection and immunity
Apoptosis regulator bax Gill -7.70 Cell protection and immunity
Apoptosis regulator bax-like Intestine 3.23 Cell protection and immunity
Apoptosis facilitator bcl-2-like protein 14 Kidney 7.24 Cell protection and immunity
Apoptotic protease-activating factor Gill 3.18 Cell protection and immunity
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 52
Inositol monophosphatase 1-like isoform x1 Gill 5.25 Cell protection and immunity
Inositol monophosphatase 1-like isoform x1 Intestine 2.90 Cell protection and immunity
Inositol-3-phosphate synthase 1-a-like Gill 11.14 Cell protection and immunity
Inositol-3-phosphate synthase 1-a-like Kidney 3.62 Cell protection and immunity
Atp-citrate synthase-like Gill 2.92 Energy metabolism
Succinate dehydrogenase Gill 5.87 Energy metabolism
Isocitrate dehydrogenase Gill 2.78 Energy metabolism
Isocitrate dehydrogenase Kidney 2.12 Energy metabolism
Malate cytoplasmic Gill 8.48 Energy metabolism
Malate cytoplasmic Intestine 3.86 Energy metabolism
Malate mitochondrial-like Gill 2.44 Energy metabolism
Cytidine monophosphate-n-acetylneuraminic acid hydroxylase-like Kidney 2.12 Energy metabolism
Cytidine monophosphate-n-acetylneuraminic acid hydroxylase-like Gill 7.84 Energy metabolism
Cytochrome c oxidase subunit mitochondrial precursor Gill 4.95 Energy metabolism
Cytochrome c oxidase polypeptide viii- mitochondrial precursor Gill 2.88 Energy metabolism
Cytochrome c oxidase assembly protein cox16 mitochondrial-like Kidney 2.19 Energy metabolism
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 53
Cytochrome p450 4v2-like Gill 38.51 Detoxification
Cytochrome p450 4v2-like Intestine 2.22 Detoxification
Cytochrome p450 1a Kidney 3.86 Detoxification
Cytochrome p450 2j6-like Intestine 8.21 Detoxification
Cytochrome p450 3a40-like Intestine 2.48 Detoxification
Glutathione s-transferase 3 Kidney 2.19 Detoxification
Keratin 8 Gill 3.3 Structure reorganization
Actin binding protein Gill 2.36 Structure reorganization
Myosin light chain Intestine 2.54 Structure reorganization
Myosin heavy chain Intestine 2.04 Structure reorganization
Myosin-9-like isoform Gill 2.51 Structure reorganization
Myosin-10-like isoform Gill 3.05 Structure reorganization
Myosin-11-like isoform Gill 8.93 Structure reorganization
Trio and f-actin-binding Kidney 2.25 Structure reorganization
A disintegrin and metalloproteinase with thrombospondin motifs Gill 2.38 Structure reorganization
A disintegrin and metalloproteinase with thrombospondin motifs Intestine -6.04 Structure reorganization
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 54
Collagen type i alpha 1 Kidney 3.65 Structure reorganization
Collagen type i alpha 2 Kidney 2.18 Structure reorganization
Collagen alpha-1 chain-like Gill 2.03 Structure reorganization
Collagen alpha-2 chain-like Intestine 2.21 Structure reorganization tropomyosin alpha-3 chain Gill 2.65 Structure reorganization tropomyosin alpha-3 chain isoform x7 Gill 2.05 Structure reorganization tropomyosin alpha-3 chain Kidney 2.03 Structure reorganization tropomyosin alpha-3 chain isoform 2 Kidney 2.31 Structure reorganization tubulin alpha-1b chain- partial Kidney 6.89 Structure reorganization tubulin beta chain-like Kidney 3.58 Structure reorganization tubulin beta-3 chain-like Kidney 6.21 Structure reorganization tubulin alpha-1a chain-like Intestine 2.29 Structure reorganization tubulin beta-2c chain Intestine 2.19 Structure reorganization
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 55
3.4.1 Genes involved in energy metabolism As salinity level increases, acclimation of freshwater teleosts toward elevated salinity conditions
requires a large investment of energy to maintain their homeostasic balance. It has been
estimated previously that approximately 20 – 62% of the total energy budget of a fish can be
diverted to osmoregulation under salinity elevated stress (Boeuf and Payan, 2001). It is not
surprising therefore, to find that many P. hypophthalmus genes with a primary role in energy
metabolism were upregulated during prolonged exposure to raised salinity conditions. It is well
documented that changes in components related to the electron transport chain, glycolysis, fatty
acid metabolism and ATP production are often associated with increasing salinity levels (Lavado
et al., 2013; Tine et al., 2008). Of interest, it has been suggested that regulation of these type of
genes are affected by different salinity concentration, time of exposure and specific
osmoregulatory organ (Tseng and Hwang, 2008).
Citrate synthase (CS) and isocitrate dehydrogenase (IDH) are important elements in the
tricarboxylic acid cycle (TCA). Upregulation of these genes during salinity exposure illustrates
the need for energy during osmoregulation because pyruvate is converted to acetyl-coA and then
to citrate/isocitrate in mitochondria by CS (EC 2.3.3.1) and IDH (EC 1.1.1.42), respectively. A
specific review of CS as well as IDH mechanisms can be found elsewhere (Mommsen, 1984). In
Mozambique tilapia O. mossambicus, CS activity increased in isolated gill epithelial cells after
transfer to SW for two weeks (Perry and Walsh, 1989). This response resulted from stimulation
of aerobic respiration in mitochondria during acclimation to SW. Recently, a study of lactate
dehydrogenase and citrate synthase regulation in O. mossambicus gills during acclimation to a
salinity challenge also recorded a significant change in the activities of these genes over the 1st
hour of the acclimation process (Tseng et al., 2008). In contrast, in a euryhaline fish G. mirabilis,
changes in CS activity were not detected as salinity fluctuated (Evans and Somero, 2008). We
also observed changes in another enzyme, succinate dehydrogrenase (SRQ) in our study. SRQ is
a limiting enzyme in the Krebs cycle, that has previously been shown to increase in expression
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 56
level in eel (A. anguilla) and Atlantic salmon (S. salar) gill following seawater exposure
(Langdon and Thorpe, 1984; Sargent et al., 1975). Cytoplasmic malate dehydrogenase is another
element of the electron transport chain that may show differential expression changes. In
addition, cytochrome c oxidase (COX) catalyzes electron transfer from cytochrome c to
molecular oxygen. It is unlikely however, that when salinity fluctuates, COX contributes to
oxidative phosphorylation that later provides all of the ATP required for energy demanding
processes. Our results showed that COX in P. hypophthalmus was upregulated in the gill during
salinity elevation, a pattern also seen in gills and intestine of both seawater and freshwater
adapted D. labrax (Boutet et al., 2006) and in gills of S. melanotheron (Tine et al., 2011).
Together, the patterns of differently expressed genes suggest a requirement for more energy by
P. hypophthalmus during raised salinity conditions. This energy is required to maintain a variety
of metabolic processes under stressful conditions.
3.4.2 Genes involved in ion transport During salinity acclimation, fish rely on different active and passive transporters to pump ions in
and out of cells across their cell membranes. This allows individuals to maintain their ion
balance equilibrium. Adjustment of active/passive transport of ions is considered to be the key
element in teleost fish that permits them to acclimate to fluctuations in their osmotic
environments.
Under hyper-saline conditions, significant loss of water from the cell can quickly lead to a
critical point where cells shrink and potentially die. In this sense, cells have to either synthesize
the osmolyte itself, or rely on transporters and intracellular accumulation of osmolytes including
betaine, taurine, sorbitol and myo-inositol to balance any osmotic change (Alfieri and Petronini,
2007; Ho, 2006). Taurine is therefore transported into the cell via sodium- and chloride-
dependent taurine transporters (TauT or SLC6A6) (Han et al., 2006; Takeuchi et al., 2000). TauT
has been suggested previously to be upregulated in cells to counteract any increase in osmotic
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 57
pressure that could lead to cell shrinkage (the specific TauT mechanism has been reviewed
elsewhere (Hoffmann et al., 2009)) . In P. hypophthalmus, we observed an increase in TauT
expression level in gill and kidney tissue, suggesting a role for a taurine pumping mechanism to
cope with changes in the external osmotic environment. Taurine transporter mRNA has also
been found to be highly expressed in the gill of seawater acclimated Japanese eel (A. japonica)
(Chow et al., 2009) and increased significantly when ambient osmolality increased in a common
carp cell line (Epithelioma papulosum cyprinid) (Takeuchi et al., 2000). In our study, TauT
expression declined however in the intestine, suggesting potentially a different osmolyte may
contribute to establishing osmotic equilibrium balance in this organ. Apart from taurine,
accumulation of myo-inositol, another osmolyte in cells is maintained by a sodium/myo-inositol
cotransporter (SMIT/SLC5A3), another plasma membrane protein (Coady et al., 2002). This ion
transporter has been studied extensively in yeast, humans and certain mammal species (Ho,
2006). Previous studies agree that SMIT acts as a controller that maintains intracellular
concentration of myo-inositol and is upregulated in response to hypertonic stress (Alfieri et al.,
2002; Klaus et al., 2008; Yamauchi et al., 1993). In our study, SMIT was significantly
upregulated in gill and kidney of P. hypophthalmus exposed to 15ppt salinity. This suggests a
role for this gene in salinity acclimation in Tra catfish. While a role for some osmolytes
(including taurine and myo-inositol) in cells to counteract osmotic balance is partially
understood in teleost fish, the actual mechanism and how the process is regulated, still remain
unclear (Tseng and Hwang, 2008) .
Aquaporins (AQP) are a family of small (25-34kDa), hydrophobic, integral membrane proteins
that function in transport of water across cell membranes in response to osmotic gradients
created by active solute transport (Campbell et al., 2008). When cells are exposed to a
hyperosmotic solution, they shrink in size. As AQP functions as a passive “gate” for
glycerol/ammonia/urea, a decrease in AQP-3 abundance therefore can help prevent loss of
glycerol from the cell. This allows the cell to maintain elevated intracellular glycerol levels,
improving cell volume as well as lamellae blood flow and gas exchange in seawater acclimated
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 58
fish. It is now widely accepted that AQP-3 increases as environmental salinity levels decline
(and vice versa) in fish gill, this pattern has been recorded in pufferfish Takifugu obscurus
(Jeong et al., 2013), Atlantic salmon S. salar (Tipsmark et al., 2010a), Japanese eel A. japonica
(Tse et al., 2006), and Mozambique tilapia O. mossambicus (Breves et al., 2010). Our results
also show a decrease in AQP-8a and AQP-10b expression levels in the intestine of P.
hypophthalmus. The AQP-10 gene has also been identified in gilthead seabream S. aurata
(Martinez et al., 2005; Santos et al., 2004). Aquaporin 10 is an aquaglyceroporin that is not
expressed in mammalian kidney but is located in the membrane of the small intestine, where it is
believed to participate in transport of both water and solutes (Mobasheri et al., 2004). Further
studies will be needed however, to clarify where AQP-10 is localized in P. hypophthalmus as
well as to determine the specific role for this membrane protein in osmoregulation in teleost fish.
The sodium/glucose cotransporter (SGLT) plays a major role in Na/glucose transport in the
intestine, and has been suggested as a potential gate for water transport (Madsen et al., 2011).
The two most well-known members of the SGLT family are SGLT1 and SGLT2 that are
members of the SLC5A gene family – in mammals. This solute carrier family acts as a
transporter for sugar, myo-inositol, monocarboxylates, iodide, vitamins and choline (Wright et
al., 2007). In humans, SLGT1 behaves as a water channel, a sugar-coupled water flow that
allows exchange of Na+, sugar and water stoichiometrically (Loo et al., 2002). The role of SGLT
proteins is to transport glucose and Na+ across apical membranes. The role of SGLT in water
absorption however, potentially may be minor since blocking SGLT with phlorizin in salmonids
only reduced water transport capacity by 20% (Madsen et al., 2011).
Genes associated with transporting molecules related to metabolic processes were also
modulated in association with upregulation of genes involved in ATP energy production. An
upregulation of solute carrier family facilitated glucose transporter member 1 (SLC2A1/GLUT1)
in the gill of P. hypophthalmus at 15ppt salinity was observed here. SLC2A1 has previously been
suggested to be an element for transporting glucose across plasma membranes (Olson and
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 59
Pessin, 1996). The GLUT gene family was recently identified as a target for investigating
glucose metabolism and energy supplementation during osmoregulation in zebrafish (D. rerio)
(Tseng and Hwang, 2008). Apart from glucose, free amino acids can be used energetically to
provide ATP necessary for all metabolic processes in teleosts. During salinity exposure, free
amino acids potentially may be involved in isosmotic intracellular regulation (Tseng and Hwang,
2008; Venkatachari, 1974). In brief, di/tripeptides following hydrolysis from dietary proteins can
be transported to the apical membrane of enterocytes and then can be further hydrolysed to
release their constituent amino acids. Transport is based on stoichiometric balance by uptake of
positively or negatively charged peptides. PEPT1 (SLC15A1) is a Na+ independent, H+
dependent oligopeptide transporter meditated for the process; the physiological review of PEPT1
is available elsewhere (Romano et al., 2014) . Significant fluctuations in the expression pattern
of SLC15A1 was recorded in P. hypophthalmus under the two salinity conditions in our
experiment; PEPT1 transporters provide potentially an optimal way to absorb amino acids in
fish. In teleost fish, PEPT1 is primarily expressed in the intestine and can also be found at much
lower concentrations in a variety of other organs/tissues, including kidney, liver and spleen
(Rønnestad et al., 2007). Di and tri-peptide PEPT1 have already been cloned and characterized
from certain fish species including zebrafish D. rerio (Verri et al., 2003), Atlantic cod Gadus
morhua L. (Rønnestad et al., 2007), and European seabass Dicentrarchus labrax (Sangaletti et
al., 2009). Of interest, isoforms of PEPT15 have been found to be differentially expressed under
different salinity conditions in killifish Fundulus heteroclitus (Bucking and Schulte, 2012).
While this suggests novel environment-specific expression strategies in euryhaline fish, further
investigation will be required in order to clarify the role of this transporter in salinity tolerance
mechanisms in the target species and more generally.
Earlier results of Perry (1997) showed that gill epithelial sodium/potassium ATPases (NKA)
activity appeared to increase in higher salinity environments. Tipsmark et al. (2004) suggested
that the level of NKA in fish gill can indicate the relative capacity of a species to hyper- (or
hypo-) osmoregulate. To date, NKA has been shown to play an important role during salinity
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 60
adaptation in many FW species including, in blackchin tilapia Sarotherodon melanotheron
(Ouattara et al., 2009), Mozambique tilapia O. mossambicus (Fiess et al., 2007), common carp
Cyprinus carpio (Salati et al., 2011) and a number of other species. While several NKA isoforms
have been characterized in teleost fish, there is still a lot of debate about the specific roles that
each isoform plays. In salmonids, the NKA α1b isoform is believed to be the “SW-adapted”
isoform, since this isoform is often upregulated during raised salinity exposure, while NKA α1a
acts as a “FW-adapted” isoform. Many studies have been conducted to investigate the switching
mechanism underlying this pattern (Bystriansky et al., 2006; Nilsen et al., 2007; Richards et al.,
2003; Takashi et al., 2012). Recently, in an attempt to investigate the differential regulation of
NKA during seawater exposure of Atlantic salmon parr and smolt S. salar, cellular localization
and abundance patterns of the two isoforms were clearly elucidated (McCormick et al., 2009;
McCormick et al., 2013). In this study, many NKA alpha subunit transcripts were observed, one
that was upregulated while another was down regulated in gill under the two experimental
salinity concentrations. We had hypothesized that they may represent the two isoforms identified
above in salmon. Unfortunately, due to the fact that no reference genome was available for P.
hypophthalmus, we did not have the ability to distinguish between the two isoforms. A follow up
study using RT-PCR confirmation could be employed to elucidate the actual roles of different
NKA isoforms in salinity tolerance in P. hypophthalmus.
3.4.3 Genes involved in immune and cell protection responses Cells responding to changes in external osmotic conditions rely on a variety of mechanisms
including modified ion homeostasis rate as well as repairing disturbed parts of cells to allow
them to recover their functionality. Previous research has suggested that volume regulation is a
response employed by fish cells to address osmotic challenges (Chara et al., 2011).
To compensate for prolonged hyperosmotic conditions, cells tend to accumulate osmolytes to
rebalance their tonicity equilibrium (Alfieri and Petronini, 2007). Myo-inositol is an example of
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 61
an osmolyte that is believed to accumulate in cells during salinity elevation. The myo-inositol
biosynthesis pathway (MIB) that converts glucose-6-phosphate to myo-inositol mediates this
response. This pathway consists of two enzymes; myo-inositol phosphate synthase (MIPS) and
inositol monophosphatase (IMPA) that generate myo-inositol. Of interest, we detected IMPA1
isoforms in both P. hypophthalmus gill and intestine, while in kidney we found many transcripts
that had GO terms related to inositol biosynthesis. This potentially provides a possible strategy
for P. hypophthalmus to counteract cell shrinkage under hyperosmotic environments. Previous
work on Japanese eel A. anguilla has implied that IMPA1 can be upregulated during salinity
fluctuation over both short and long term salinity challenge in the gill, kidney and/or intestine
(Kalujnaia et al., 2010; Kalujnaia et al., 2007). It is of further interest to note however, that myo-
inositol has also been suggested to act as a substrate for synthesis of phosphoinositide
compounds, an important substance involved in osmotic stress signalling events in some plants
(Munnik and Vermeer, 2010).
Many genes involved in cell apoptosis that were upregulated under salinity challenge P.
hypophthalmus were also detected. Both hyper or hyposalinity exposure stress can lead to a
critical point where fluctuating salinity level causes cell shrinkage or swelling leading to cell
death. Apoptosis, or regulated cell death can be understood as the way cells can self-destruct in
an orderly and controlled pattern, allowing replacement of damaged cells with new cells,
ensuring cellular homeostasis (Hoffmann et al., 2009). Apoptotic regulation involves a variety of
cellular signalling pathways that trigger shrinkage, nuclear fragmentation, chromatin
condensation and finally DNA fragmentation, that results in cell death (Jones, 2001). Potentially,
perceived osmotic stress imposed on P. hypophthalmus individuals at 15 ppt salinity
concentration may be correlated with upregulation of apoptotic elements including apoptosis
stimulation of p53 protein (gill and intestine), bcl2 protein, an antagonist of cell death (intestine),
apoptosis regulator bax-like (intestine), and apoptosis facilitator bcl-2-like protein 14 (kidney).
While our understanding of the apoptosis process has advanced significantly over the last 10
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 62
years, studies that specifically examine the association between apoptosis and salinity tolerance
in teleost fish, are still required.
p53 is a tumor suppressor protein and a key regulator of cell cycle arrest and apoptosis. It has
been reported that low levels of p53 triggers cell-cycle arrest while high levels can cause
apoptosis (Laptenko and Prives, 2006). Significant increases in p53 mRNA expression and
protein abundance in the gills of climbing perch Anabas testudineus were observed in response
to seawater acclimation (Ching et al., 2013). A similar result was confirmed in free-swimming
larval L. salmonis as p53 protein was reported to be an apoptotic factor that was upregulated
after short term hyposalinity challenge (Sutherland et al., 2012). Moreover, the p53 gene has
been shown to be correlated with acute acid stress in Nile tilapia O. niloticus, and was suggested
to serve as a cellular response for DNA damage caused by acid oxidative stress (Mai et al.,
2010). After p53 triggers the effect, apoptosis is orchestrated by intracellular proteases known as
caspases. Prior to this, apoptosis regulator bax-like (BAX) - a pro-apoptosis protein expressed
under stress conditions has to undergo a conformational shift that causes translocation to the
mitochondrial membrane, that releases cytochrome c into the cytosol that activates caspase-3 and
9 leading to apoptosis (Oltval et al., 1993). In our study, we found that BAX was upregulated in
the intestine while being downregulated in the gill of P. hypophthalmus. Similarly, high salinity
induced an increase in BAX expression as well as apoptosis in A. testudineus (Ching et al.,
2013). The authors suggested that these changes facilitated removal of certain types of gill cells
in the switching mechanism between freshwater cell type to seawater type. In P. hypophthalmus
however, we proposed that this pattern was more likely to involve replacement of damaged cells
with new cells rather than as a cell switching mechanism as has been reported in A. testudineus.
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 63
3.4.4 Genes involved in encoding structural proteins Osmotic imbalance can also be addressed via extensive reorganization of the cytoskeleton. In
response to cell shrinkage, arrangement of structural proteins can help to extend the ability of
cells to acclimate to hyperosmotic environmental conditions.
In this study, many genes encoding multiple structural components of the cytoskeleton were
induced in P. hypophthalmus in the 15ppt treatment including keratin, several members of the
myosin family (myosin light/heavy chain, myosin 9, 10) and collagen. These genes are known
from previous studies as adjusting elements for cell reorganization during cell volume regulation
(see review by Hoffmann et al. (2009)). Myosin light chain is believed to be a key mediator for
hyperosmotic activation in a variety of cell types where it regulates Na+–K+–2Cl− co-transporters
(NKCC) (Ciano-Oliveira et al., 2005; Di Ciano-Oliveira et al., 2006). In parallel, keratin and
collagen can act as important skeletal proteins for cellular structure (Kirfel et al., 2003). Of
interest, this type of change in reorganization of cytoskeleton structure has mostly been detected
in the gills of teleost fish. Fish gills act as the first line of defence against the external
environment, and therefore are at risk during severe osmotic fluctuation. As a result, osmotic
stress that modulates cell volume and reorganization of the cytoskeleton structure may reflect an
attempt to balance osmotic equilibrium in fish.
Another structural protein family, the claudins, consist of 24 different members, divided into
three subgroups depending on their function. These include barrier builders, mediating
permeability and some with unknown functions (Amasheh et al., 2011). In P. hypophthalmus, we
recorded down regulation of claudin-4, claudin-10b in gill and claudin-15 in the intestine. This
correlated well with results of a study on Mozambique tilapia O. mossambicus, where claudin-3
and claudin-4 like were reported in gill and expression levels decreased after seawater
acclimation (Tipsmark et al., 2008). The authors suggested that the decrease in expression
pattern of these tight-junctions is a sign of rearrangement of the gill into an ion-secreting and
leakier epithelium (Sardet et al., 1979). Our results also showed a down regulation of claudin-15
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 64
in the intestine, a claudin primarily found abundantly in the intestine of smolt (S. salar)
individuals (Tipsmark et al., 2010b). Increased renal tricellulin and claudin-3 expression in
kidney also suggests an important role for this tight-junction protein in the kidney of smolts in S.
salar (Tipsmark and Madsen, 2012). For P. hypophthalmus however, we did not observe any
change in the claudin isoform expressed in the kidney. These findings on cytoskeletal
modification under salinity elevation in P. hypophthalmus illustrate that knowledge about the
different roles of many genes during salinity fluctuation is currently very limited and will require
further investigation.
3.4.5 Genes involved in signal transduction The sensory system and intracellular transduction of stress signal is crucial for the survival of
fish during salinity fluctuation. Osmosensors detect changes in the external environment, and
send the information to the signal transduction network, that in turn triggers the effector defence
mechanism (i.e. that increase cell proliferation, cell differentiation or that change ion transporter
activity). This signalling pathway can be viewed as the connection between the perceived
external environmental shift and the physiological response of a fish (a review of signal
transduction network in both cellular and molecular levels in fish, can be found in the study by
Fiol and Kültz (2007)) .
Mitogen activated protein kinases (MAPK) are a family of proteins that have been shown to be
involved in osmosensory signal transduction in yeast, plant and animal cells – a cellular control
pathway that plays an important role in cellular response in many species (Arbabi and Maier,
2002). In brief, MAPK acts by combining and amplifying all signals received from osmosensors
and then activates appropriate downstream signals that promote physiological acclimation
processes (Fiol and Kültz, 2007). We detected many MAPK transcripts in P. hypophthalmus gill
that were both up and down regulated, while in kidney and intestine, MAPK tended to be only
upregulated at raised salinity levels. Moreover, activation of MAPK has suggested to be related
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 65
to small GTPases of the Rho family, that are thought to mediate the control of the actin
cytoskeleton as well as cell morphology under osmotic fluctuations (Lunn and Rozengurt, 2004;
Suzuki et al., 1999; Vojtek and Cooper, 1995). A number of Rho-GTPase genes showed
differentential expression patterns in our study. These data however, can best be explained by a
role for Rho-GTPase as a molecular controller that triggers various regulatory processes in the
extensive rearrangement of cytoskeletal structure (refer to the review by Di Ciano-Oliveira et al.
(2006) for detail about the roles of Rho-GTPases in osmotic stress). A similar pattern was
confirmed in the euryhaline fish longjaw mudsucker G. mirabilis, with Rho-GTPase 7 and 8
differentially expressed during hypo/hyperosmotic stress (Evans and Somero, 2008). Variable
expression of Rho-GTPase family proteins were observed in all three osmoregulatory organs
under elevated salinity conditions suggesting a role for this gene family during salinity exposure
in P. hypophthalmus.
14-3-3 protein is another element in the signal transduction network. We recorded 14-3-3 protein
transcripts that were upregulated in P. hypophthalmus gill while being down regulated in kidney
and intestine. The 14-3-3 protein family has an identified role in salinity tolerance since it is
involved in various cellular processes including signal transduction, cell-cycle control, apoptosis,
stress responses and malignant transformation (van Hemert et al., 2001). 14-3-3 proteins are the
initial “check-point” that combine all the phosphorylation-based signals (proteins including
serine or threonine) and distribute signals toward target cells (Fiol and Kültz, 2007). In an earlier
study of 14-3-3 mRNA expression in killifish F. heteroclitus, increment in expression of this
gene in the gills under euryhaline conditions was observed after transfer from seawater to
freshwater (Kültz et al., 2001; Scott et al., 2006). It is also interesting to note that changes in
environmental calcium concentration caused changes to 14-3-3 protein expression patterns in the
green spotted puffer Tetraodon nigroviridis (Pinto et al., 2010)
As mentioned above, the myo-inositol biosynthesis pathway as well as transporting myo-inositol
to counteract osmotic imbalance provides a possible strategy for P. hypophthalmus to cope with
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 66
external salinity fluctuations. Of interest, SMIT has been confirmed previously to be modulated
by serine/threonine-protein kinase, a kinase subfamily encoded by SGK1, SG2 and SGK3 genes
(Klaus et al., 2008). Previous studies have confirmed the involvement of SGK family genes in
both short and long term salinity acclimation in teleost fish including in spiny dogfish Squalus
acanthias (Waldegger et al., 1998) and killifish F. heteroclitus (Hoffmann et al., 2002; Shaw et
al., 2008). We detected significant upregulation of SKG1 in the gill of P. hypophthalmus during
raised salinity exposure, suggesting a role for this gene in the osmosensory pathway of Tra
catfish.
3.4.6 Genes involved in detoxification Biotransformation processes assist an organism to dispose of xenobiotics during environmental
shifts (e.g. salinity fluctuation). These processes can be mediated in various pathways,
categorized into Phase I and Phase II reactions. Cytochrome P450 1A (CYP1A) is an oxidative
enzyme involved in Phase I biotransformation and is believed to be involved in acclimation of
freshwater fish to elevated salinity conditions. Acclimation of rainbow trout (O. mykiss) to
seawater produced a significant increase in CYP1A gene expression (Leguen et al., 2010). This
result correlates well with outcomes from a micro-array based transcriptomic study of G.
mirabilis, that showed positive upregulation of CYP1A1 in the gill during hypo/hyper salinity
exposure (Evans and Somero, 2008). Recently, an experiment that examined a broader range of
cytochrome Phase 1 enzymes reported similar results with four orthologs of cytochrome P450
(CYP1A, CYP2K1, CYP2M1 and CYP3A27) in gill, liver and olfactory tissue, respectively.
They were found to be upregulated rapidly during transfer of fish from freshwater conditions to
various raised salinities (Lavado et al., 2013). Here we also observed a decrease in glutathione s-
transferase (GST), a gene encoding a key enzyme involved in the detoxification system that
protects cells against reactive oxygen species. This pattern is similar to one reported previously
in Japanese eel (A. anguilla) (Kalujnaia et al., 2007). The specific role of this gene in the
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 67
intestine of teleost fish and the reason for the decline in its expression under elevated salinity
conditions however, are still unknown.
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 68
Chapter 3: Differential gene expression and evaluation of candidate genes involved in salinity tolerance 69
Chapter 4: A conceptual model for the salinity tolerance pathway in P. hypophthalmus
The current study was designed not only to generate a catalogue of genes that were
differentially expressed in the target species in response to different salinity conditions,
but also to allow the data to be integrated to identify the connection as well as possible
molecular pathways that control the adaptive response. Broad functional categories of
differentially expressed genes were identified, based on gene ontology information and
from data in published studies. These data were then developed into a conceptual
schematic model that attempts to describe potential interactions between key genes
involved in salinity tolerance in Tra catfish (P. hypophthalmus). This model is
presented schematically in figure 13 below.
Chapter 4: A conceptual model for the salinity tolerance pathway in P. hypophthalmus 70
PEPT1: Peptide transporter 1, GLUT1: Glucose facilitator , AQP: Aquaporins, NKA: Sodium/Potassium ATPase alpha, SGLT: Sodium/glucose cotransporter, TAUT: Sodium- and chloride-dependent taurine transporter, SMIT: Sodium myo-inositol cotransporter 2 Peptide transporter 1, SRQ: Succinate dehydrogenase, IDH: Isocitrate dehydrogenase, NaDH sodium dehydrogenase, CS: Citrate synthase, COX: cytochrome oxidase c subunit , GST: glutathione s- transferase 3, p53: Apoptosis-stimulating of p53 protein 1, Apoptotic protease: Apoptotic protease-activating factor, Bcl-2 apoptosis facilitator: apoptosis facilitator bcl-2-like protein 14 Bcl2 antagonist: Bcl2 antagonist of cell death, Bax: Apoptosis regulator bax, SGK: Serine threonine- protein kinase sgk1-like isoform x1, MAPK: Mitogen- activated protein kinase.
Figure 13. Schematic model for the salinity tolerance pathway in P. hypophthalmus.
Chapter 4: A conceptual model for the salinity tolerance pathway in P. hypophthalmus 71
As described above, candidate genes involved in salinity tolerance were classified into
six categories based on annotation results and published studies. Category 1 included
genes that contribute to overall energy metabolism during salinity elevation. In most
instances, these genes are upregulated so that individuals can cope with the increased
demand for energy to respond to the stress associated with raised salinity conditions.
This process occurs mostly in the mitochondria of gills and the kidneys. As mentioned
above, osmoregulatory processes consume a large amount of energy, so individuals
need to invest energy to drive adaptive responses controlled by these genes to respond
to raised salinity concentrations. Category 2 consists of ion transporter genes, some of
which were up or down regulated under elevated salinity, balancing ion homeostasis as
well as osmolyte recirculation in P. hypophthalmus cells. Ion transporters, depending
on individual osmoregulatory organs, can have different functions that assist individuals
to balance their ionic equilibrium. Moreover, some ion transporters can assist in
counteracting cell shrinkage that results from raised environmental salinity level.
Category 3 contains genes that have a specific role in cell protection and the immune
system. These genes contribute to cell maintenance and repair as well as assisting in
replacement of damaged parts of cells during salinity elevation to assist them to recover
their functionality. Category 4 contains structural genes that control cytoskeleton
rearrangement, extending the ability of cells to acclimate to hyperosmotic
environmental conditions. As earlier studies have suggested, adjustment of the
cytoskeleton allows cells to acclimate to elevated salinity concentrations. Category 5
includes candidate signal transduction elements that potentially maintain connections
between the perceived external environmental shift and the physiological responses of
fish. Lastly, Category 6 consists of genes that can contribute to the detoxification
process in P. hypophthalmus potentially assisting with disposal of xenobiotics in
saltwater.
Chapter 4: A conceptual model for the salinity tolerance pathway in P. hypophthalmus 72
Acclimation to raised salinity conditions is initiated when osmosensors in the body
perceive a change in salinity that then send a signal toward the MAPK signal cascade.
This central signal can then distribute the message through many channels to specific
tissues, thus invoking specific responses (Category 5). Among them, Rho-GTPases
distribute signals to the exoskeleton proteins, including to F-actin, myosin protein
family genes and claudins. This can assist with rearranging the structure of the cell to
cope with new osmotic conditions (Category 2). While the SGK signal cascade
stimulates a signal toward SMIT, a myo-inositol pump transfers osmolytes into cells –
Category 3 (osmolytes have previously been confirmed as a method for counteracting
cell bursting via osmotic pressure elevation). SGLT and TAUT are genes in the same
group and also act as an osmolyte pump, transferring myo-inositol and taurine,
respectively to cells to protect against cells bursting. Hypersaline stress can lead to a
critical point where salinity level causes cell shrinkage or swelling that can lead in turn,
to cell death. Apoptosis, or regulated cell death is triggered, so cells can self-destruct in
an orderly and controlled pattern, allowing replacement of damaged cells with new
cells, ensuring cellular homeostasis. This involves various genes in a number of
pathways including Bax, Bcl-2. It is also important to note that during salinity
acclimation, fish rely on both active and passive transporters to maintain ion gradients
across cell membranes (Category 2). Fluctuations in external osmotic environmental
conditions in P. hypophthalmus can be addressed via the action of various ion pumping
genes including the NKA pump, Aquaporin family and NBC. In addition, GLUT and
PEPT1 potentially assist transfer of free amino acids and glucose into affected cells,
that can later be used in the TCA cycle to generate the massive energy required for the
acclimation process (Category 1). In P. hypophthalmus, we observed many genes
involved in energy generation including; CS, SHD and NaDH that were differentially
expressed during salinity elevation. As discussed earlier, energy metabolism is a crucial
process during acclimation to elevated salinity environments in teleost fish. Finally, we
also include the P450 family and GST genes, that we suspect to act as a detoxification
Chapter 4: A conceptual model for the salinity tolerance pathway in P. hypophthalmus 73
mechanism in P. hypophthalmus (Category 6). It is important to recognise however that
the current model developed here is unlikely to include all of the potential genes that
are differentially expressed in the species related to salinity acclimation. The model
does however, provide a basic molecular foundation for building up a more detailed
functional explanation of how salinity tolerance is mediated in the target species and
also more widely in others freshwater teleosts.
Limitations of the current study
As indicated in the study objective, the current study was limited to the generation of the reference transcriptome for Tra catfish (P. hypophthalmus). Some limitations related to the experimental design employed could enhance transcriptomic work on this species.
i. A lack of sufficient biological samples that could influence recognition of
up/down regulated transcript.
More biological samples would create more statistical power when assessing
whether a transcript was up/down regulated at different salinities. Because
however, as sequencing costs were high at the time of conducting the study,
we had to limit the number of samples. In future research, experiments that
employ at least 3 biological samples would allow the list of candidate gens
identified here to be confirmed with more statistical power.
ii. Creation of a master pool prior sequencing and its effect on differential gene
expression results.
A master pool would improve the resolution and allow more genetic
variations to be captured within the sequencing, resulting in a more
comprehensive transcriptome that can be used for later study.
iii. Choice of NGS platform
This was not an option at the time of sequencing for the current study. With
recent development in NGS technology, a wide variety of platforms are now
available (including Illumina NextSeq, PacBio or 3rd generation sequencing
Chapter 4: A conceptual model for the salinity tolerance pathway in P. hypophthalmus 74
platform. An additional strategy could also be applied would be to increase
the total number of reads (up to 40-50 million reads) and to enhance
sequencing quality, as this would improve assembly statistics (i.e. apply
paired-end/mate pair reads). iv. Alternative bioinformatics algorithms
As suggested by the literature, there are many different DGE packages available
online at the moment. One possible limitation of the current study is that we only used
a single software package for the DGE analysis (i.e., the CLC Genomics Workbench
RNA-seq module). A better approach would be to employ two or more DGE software
packages to yield a more comprehensive results.
Chapter 4: A conceptual model for the salinity tolerance pathway in P. hypophthalmus 75
Chapter 4: A conceptual model for the salinity tolerance pathway in P. hypophthalmus 77
Chapter 5: Conclusions and future directions
Tra catfish (P. hypophthalmus) is a species of freshwater catfish that is widely cultured
in the Mekong River Delta region of southern Vietnam. It is an important species for
the local aquaculture industry, and currently is reared in many areas across the delta and
contributes a significant percentage to total fish export turnover value in Vietnam but
also in many small provinces that rely heavily on fish farming. Due to predicted
impacts of climate change, the Tra catfish future industry is facing a massive threat
linked to forecasts of sea level rise this century. It will therefore be important to develop
catfish culture lines with improved salinity tolerance. This can be achieved by
integrating traditional breeding programs with genetic markers related to the trait of
interest (i.e. salinity tolerance). Reaching this step will require developing a better
understanding of the ability of the target species to acclimate to raised salinity
conditions, as well as identification of key genes that contribute to salinity
tolerance/acclimation in the species. The current study investigated transcriptomic
responses of P. hypophthalmus exposed to two salinity concentrations (0 and 15ppt).
The first aim of this project was to construct the most comprehensive de novo assembly
and to annotate a reference transcriptome for later differential gene expression studies.
To this end, total RNA was extracted, then purified and mRNA isolated to generate a
cDNA library. All cDNA libraries were sequenced using the Ion Proton sequencing
platform. For the de novo assembly process, we conducted a comparative assessment of
three different de novo assemblers: Trinity, Velvet/Oases and SOAP de novo Trans and
following this we combined the three assemblies to generate a single reference
transcriptome used for differential gene expression analysis of candidate genes with
potential roles in salinity acclimation.
Chapter 5: Conclusions and future directions 79
After mapping all reads against an annotated reference transcriptome and calculating
the RPKM value for each condition, results showed over 3000 transcripts that were
differentially expressed under the two salinity conditions (0 and 15ppt) across all three
osmoregulatory organs tested. Based on functional annotation and published data, we
classified all differentially expressed genes into six gene categories based on their
predicted gene function and selected a list of candidate genes based on differential
expression patterns that potentially impact P. hypophthalmus salinity tolerance. Last but
not least, we attempted to synthesize the data from the entire set of potential candidate
genes to generate a simple conceptual model for how P. hypophthalmus may respond at
the molecular level to changes in sub lethal salinity. Ultimately, these data could be
used to identify functional gene markers for application in a marker-assisted selection
program for P. hypophthalmus to allow development of raised salinity adapted forms
for the culture industry in Vietnam.
Chapter 6: Conclusions and future directions 80
Chapter 6: Conclusions and future directions 81
Bibliography
1. Alfieri, R.R., Cavazzoni, A., Petronini, P.G., Bonelli, M.A., Caccamo, A.E., Borghetti, A.F., and Wheeler, K.P. (2002) Compatible osmolytes modulate the response of porcine endothelial cells to hypertonicity and protect them from apoptosis. The Journal of Physiology 540, 499-508. 2. Alfieri, R.R. and Petronini, P.G. (2007) Hyperosmotic stress response: comparison with other cellular stresses. Pflügers Archiv-European Journal of Physiology 454, 173-185. 3. Amasheh, S., Fromm, M., and Günzel, D. (2011) Claudins of intestine and nephron - a correlation of molecular tight junction structure and barrier function. Acta physiologica (Oxford, England) 201, 133-140. 4. Arbabi, S. and Maier, R.V. (2002) Mitogen-activated protein kinases. Critical Care Medicine 30, S74-S79. 5. Assem, H. and Hanke, W. (1979) Concentrations of carbohydrates during osmotic adjustment of the euryhaline teleost, Tilapia mossambica. Comparative Biochemistry and Physiology Part A: Physiology 64, 5-16. 6. Avarre, J.C.C., Dugué, R., Alonso, P., Diombokho, A., Joffrois, C., Faivre, N., Cochet, C., and Durand, J.D.D. (2014) Analysis of the black-chinned tilapia Sarotherodon melanotheron : heudelotii, reproducing under a wide range of salinities: from RNA-seq to candidate genes. Molecular ecology resources 14, 139-149. 7. Badjeck, M.-C., Allison, E.H., Halls, A.S., and Dulvy, N.K. (2010) Impacts of climate variability and change on fishery-based livelihoods. Marine Policy 34, 375-383. 8. Baker, M. (2010) Next-generation sequencing: adjusting to data overload. nature methods 7, 495-499. 9. Barman, H., Patra, S., Das, V., Mohapatra, S., Jayasankar, P., Mohapatra, C., Mohanta, R., Panda, R., and Rath, S. (2012) Identification and characterization of differentially expressed transcripts in the gills of freshwater prawn (Macrobrachium rosenbergii) under salt stress. TheScientificWorldJournal 2012, 149361. 10. Bartie, K., Austin, F., Diab, A., Dickson, C., Dung, T., Giacomini, M., and Crumlish, M. (2012) Intraspecific diversity of Edwardsiella ictaluri isolates from diseased freshwater catfish, Pangasianodon hypophthalmus (Sauvage), cultured in the Mekong Delta, Vietnam. Journal of fish diseases 35, 671-682. 11. Benjamini, Y. and Hochberg, Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 289-300. 12. Beyenbach, K.W. (2004) Kidneys sans glomeruli. American journal of physiology. Renal physiology 286, F811-827. 13. Boeck, G.D., Vlaeminck, A., Linden, A.V.d., and Blust, R. (2000) The Energy Metabolism of Common Carp (Cyprinus carpio) When Exposed to Salt Stress: An Increase in Energy Expenditure or Effects of Starvation? Physiological and Biochemical Zoology 73, 102-111. 14. Boeuf, G. and Payan, P. (2001) How should salinity influence fish growth ? Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology 130, 411-423.
Bibliography 83
15. Borgnia, M., Nielsen, S., Engel, A., and Agre, P. (1999) Cellular and molecular biology of the aquaporin water channels. Annual review of biochemistry 68, 425-458. 16. Boutet, I., Long Ky, C., and Bonhomme, F. (2006) A transcriptomic approach of salinity response in the euryhaline teleost, Dicentrarchus labrax. Gene 379, 40-50. 17. Bragg, L.M., Stone, G., Butler, M.K., Hugenholtz, P., and Tyson, G.W. (2013) Shining a Light on Dark Sequencing: Characterising Errors in Ion Torrent PGM Data. PLoS Comput Biol 9, e1003031. 18. Brander, K.M. (2007) Global fish production and climate change. Proceedings of the National Academy of Sciences of the United States of America 104, 19709-19714. 19. Breves, J.P., Fox, B.K., Pierce, A.L., Hirano, T., and Grau, E.G. (2010) Gene expression of growth hormone family and glucocorticoid receptors, osmosensors, and ion transporters in the gill during seawater acclimation of Mozambique tilapia, Oreochromis mossambicus. Journal of experimental zoology. Part A, Ecological genetics and physiology 313, 432-441. 20. Bucking, C. and Schulte, P. (2012) Environmental and nutritional regulation of expression and function of two peptide transporter (PepT1) isoforms in a euryhaline teleost. Comparative biochemistry and physiology. Part A, Molecular & integrative physiology 161, 379-387. 21. Bystriansky, J.S., Richards, J.G., Schulte, P.M., and Ballantyne, J.S. (2006) Reciprocal expression of gill Na+/K+-ATPaseα -subunit isoforms α1a and α1b during seawater acclimation of three salmonid fishes that vary in their salinity tolerance. Journal of Experimental Biology 209, 1848-1858. 22. Cacot, P., Legendre, M., Dan, T.Q., Tung, L.T., Liem, P.T., Mariojouls, C., and Lazard, J. (2002) Induced ovulation of Pangasius bocourti (Sauvage, 1880) with a progressive hCG treatment. Aquaculture 213, 199-206. 23. Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., and Madden, T.L. (2009) BLAST+: architecture and applications. BMC Bioinformatics 10, 421. 24. Campbell, E.M., Ball, A., Hoppler, S., and Bowman, A.S. (2008) Invertebrate aquaporins: a review. J Comp Physiol B 178, 935-955. 25. Chara, O., Espelt, M.V., Krumschnabel, G., and Schwarzbaum, P.J. (2011) Regulatory volume decrease and P receptor signaling in fish cells: mechanisms, physiology, and modeling approaches. Journal of experimental zoology. Part A, Ecological genetics and physiology 315, 175-202. 26. Chen, S., Li, S., Xie, W., Li, X., Zhang, C., Jiang, H., Zheng, J., Pan, X., Zheng, H., Liu, J.S., Deng, Y., Chen, F., and Jiang, H. (2014) Performance Comparison between Rapid Sequencing Platforms for Ultra-Low Coverage Sequencing Strategy. PLoS ONE 9, e92192. 27. Ching, B., Chen, X., Yong, J., Wilson, J., Hiong, K., Sim, E., Wong, W., Lam, S., Chew, S., and Ip, Y. (2013) Increases in apoptosis, caspase activity and expression of p53 and bax, and the transition between two types of mitochondrion-rich cells, in the gills of the climbing perch, Anabas testudineus, during a progressive acclimation from freshwater to seawater. Frontiers in physiology 4, 135. 28. Chow, S.C., Ching, L.Y., Wong, A.M.F., and Wong, C.K.C. (2009) Cloning and regulation of expression of the Na+–Cl-––taurine transporter in gill cells
Bibliography 84
of freshwater Japanese eels. Journal of Experimental Biology 212, 3205- 3210. 29. Ciano-Oliveira, C.D., Lodyga, M., Fan, L., Szászi, K., Hosoya, H., Rotstein, O.D., and Kapus, A. (2005) Is myosin light-chain phosphorylation a regulatory signal for the osmotic activation of the Na+-K+-2Cl− cotransporter? American Journal of Physiology-Cell Physiology 289, C68- C81. 30. Clarke, K., Yang, Y., Marsh, R., Xie, L., and Zhang, K.K. (2013) Comparative analysis of de novo transcriptome assembly. Science China. Life sciences 56, 156-162. 31. Coady, M.J., Wallendorff, B., Gagnon, D.G., and Lapointe, J.-Y. (2002) Identification of a Novel Na+/myo-Inositol Cotransporter. Journal of Biological Chemistry 277, 35219-35224. 32. Conesa, A., Gotz, S., Garcia-Gomez, J.M., Terol, J., Talon, M., and Robles, M. (2005) Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21, 3674-3676. 33. Crumlish, M., Thanh, P., Koesling, J., Tung, V., and Gravningen, K. (2010) Experimental challenge studies in Vietnamese catfish, Pangasianodon hypophthalmus (Sauvage), exposed to Edwardsiella ictaluri and Aeromonas hydrophila. Journal of fish diseases 33, 717-722. 34. Cutler, C., Martinez, A.-S., and Cramb, G. (2007) The role of aquaporin 3 in teleost fish. Comparative biochemistry and physiology. Part A, Molecular & integrative physiology 148, 82-91. 35. Czesny, S., Epifanio, J., and Michalak, P. (2012) Genetic divergence between freshwater and marine morphs of alewife (Alosa pseudoharengus): a 'next- generation' sequencing analysis. PloS one 7. 36. Danyi, S., Widart, J., Douny, C., Dang, P., Baiwir, D., Wang, N., Tu, H., Tung, V., Phuong, N.T., Kestemont, P., and Scippo, M.L. (2011) Determination and kinetics of enrofloxacin and ciprofloxacin in Tra catfish (Pangasianodon hypophthalmus) and giant freshwater prawn (Macrobrachium rosenbergii) using a liquid chromatography/mass spectrometry method. Journal of veterinary pharmacology and therapeutics 34, 142-152. 37. Davidson, W., Koop, B., Jones, S., Iturra, P., Vidal, R., Maass, A., Jonassen, I., Lien, S., and Omholt, S. (2010) Sequencing the genome of the Atlantic salmon (Salmo salar). Genome Biology 11, 403. 38. De Silva, S. and Davy, F.B. (2010) Aquaculture Successes in Asia: Contributing to Sustained Development and Poverty Alleviation. In Success Stories in Asian Aquaculture (De Silva, S. and Davy, F.B., eds), pp. 1-14, Springer Netherlands. 39. De Silva, S.S. and Phuong, N.T. (2011) Striped catfish farming in the Mekong Delta, Vietnam: a tumultuous path to a global success. Reviews in Aquaculture 3, 45-73. 40. Di Ciano-Oliveira, C., Thirone, A.C., Szaszi, K., and Kapus, A. (2006) Osmotic stress and the cytoskeleton: the R(h)ole of Rho GTPases. Acta physiologica (Oxford, England) 187, 257-272. 41. Duc, N.M. (2008) Farmers' satisfaction with aquaculture — A logistic model in Vietnam. Ecological Economics 68, 525-531. 42. Dung, T., Chiers, K., Tuan, N., Sorgeloos, P., Haesebrouck, F., and Decostere, A. (2012) Early interactions of Edwardsiella ictaluri, with
Bibliography 85
Pangasianodon catfish and its invasive ability in cell lines. Veterinary research communications 36, 119-127. 43. Eisenstein, M. (2012) Oxford Nanopore announcement sets sequencing sector abuzz. Nat Biotech 30, 295-296. 44. El-Metwally, S., Hamza, T., Zakaria, M., and Helmy, M. (2013) Next- Generation Sequence Assembly: Four Stages of Data Processing and Computational Challenges. PLoS Comput Biol 9, e1003345. 45. Evans, D. (2008) Teleost fish osmoregulation: what have we learned since August Krogh, Homer Smith, and Ancel Keys. American journal of physiology. Regulatory, integrative and comparative physiology 295, 13. 46. Evans, D.D.H. and Claiborne, J.B. (2006) The Physiology Of Fishes. CRC, Taylor & Francis. 47. Evans, D.H., Piermarini, P.M., and Choe, K.P. (2005) The Multifunctional Fish Gill: Dominant Site of Gas Exchange, Osmoregulation, Acid-Base Regulation, and Excretion of Nitrogenous Waste. Physiological Reviews 85, 97-177. 48. Evans, T. and Somero, G. (2008) A microarray-based transcriptomic time- course of hyper- and hypo-osmotic stress signaling events in the euryhaline fish Gillichthys mirabilis: osmosensors to effectors. The Journal of experimental biology 211, 3636-3649. 49. FAO (2010) The State of World Fisheries and Aquaculture. Food and agriculture organization of the United Nations, Rome. 50. FAO (2010-2012) Cultured Aquatic Species Information Programme. Pangasius hypophthalmus. Cultured Aquatic Species Information Programme. http://www.fao.org/fishery/culturedspecies/Pangasius_hypophthalmus/en. 51. FAO (2014) National aquaculture sector overview fact sheets : Vietnam. FAO Fisheries and Aquaculture Department http://www.fao.org/fishery/countrysector/naso_vietnam/en. 52. Ferraris, C.J.D.P., Mário C C (1999) Higher-level Names for Catfishes (Actinopterygii: Ostariophysi: Siluriformes). Proceedings of the California Academy of Sciences 51. 53. Fiess, J.C., Kunkel-Patterson, A., Mathias, L., Riley, L.G., Yancey, P.H., Hirano, T., and Grau, E.G. (2007) Effects of environmental salinity and temperature on osmoregulatory ability, organic osmolytes, and plasma hormone profiles in the Mozambique tilapia (Oreochromis mossambicus). Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 146, 252-264. 54. Fiol, D. and Kültz, D. (2007) Osmotic stress sensing and signaling in fishes. The FEBS journal 274, 5790-5798. 55. Foskett, J.K., Logsdon, C.D., Turner, T., Machen, T.E., and Bern, H.A. (1981) Differentiation of the Chloride Extrusion Mechanism During Seawater Adaptation of a Teleost Fish, The Cichlid Sarotherodon Mossambicus. Journal of Experimental Biology 93, 209-224. 56. Giang, D., Van Driessche, E., and Beeckmans, S. (2012) Serum carbohydrate-binding IgM are present in Vietnamese striped catfish (Pangasianodon hypophthalmus) but not in North African catfish (Clarias gariepinus). Developmental and comparative immunology 36, 418-432. 57. Gilbert, D. (2013) Gene-omes built from mRNA seq not genome DNA. In 7th annual arthropod genomics symposium.
Bibliography 86
58. Glenn, T. (2011) Field guide to next-generation DNA sequencers. Molecular ecology resources 11, 759-769. 59. Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z., Thompson, D.A., Amit, I., Adiconis, X., Fan, L., Raychowdhury, R., and Zeng, Q. (2011) Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature biotechnology 29, 644-652. 60. Grosell, M. (2011) Intestinal anion exchange in marine teleosts is involved in osmoregulation and contributes to the oceanic inorganic carbon cycle. Acta physiologica (Oxford, England) 202, 421-434. 61. GSO (2013) Population and density distributed in regions in 2011. Vietnamese General Statistic http://www.gso.gov.vn/default.aspx?tabid=387&idmid=3&ItemID=12875. 62. Guo, R. (1997) Osmoregulation in Australian bass, Macquaria novemaculeata. 63. Güroy, B., İ, Ş., Kayalı, S., Mantoğlu, S., Canan, B., Merrifield, D.L., Davies, S.J., and Güroy, D. (2013) Evaluation of feed utilization and growth performance of juvenile striped catfish Pangasianodon hypophthalmus fed diets with varying inclusion levels of corn gluten meal. Aquaculture Nutrition 19. 64. Guyon, R., Rakotomanga, M., Azzouzi, N., Coutanceau, J.P., Bonillo, C., D'Cotta, H., Pepey, E., Soler, L., Rodier-Goud, M., D'Hont, A., Conte, M., van Bers, N., Penman, D., Hitte, C., Crooijmans, R., Kocher, T., Ozouf- Costaz, C., Baroiller, J., and Galibert, F. (2012) A high-resolution map of the Nile tilapia genome: a resource for studying cichlids and other percomorphs. BMC Genomics 13, 222. 65. Han, X., Patters, A.B., Jones, D.P., Zelikovic, I., and Chesney, R.W. (2006) The taurine transporter: mechanisms of regulation. Acta physiologica (Oxford, England) 187, 61-73. 66. He, L., Jiang, H., Cao, D., Liu, L., Hu, S., and Wang, Q. (2013) Comparative transcriptome analysis of the accessory sex gland and testis from the Chinese mitten crab (Eriocheir sinensis). PloS one 8. 67. Hiroi, J., McCormick, S., Ohtani-Kaneko, R., and Kaneko, T. (2005) Functional classification of mitochondrion-rich cells in euryhaline Mozambique tilapia (Oreochromis mossambicus) embryos, by means of triple immunofluorescence staining for Na+/K+-ATPase, Na+/K+/2Cl- cotransporter and CFTR anion channel. The Journal of experimental biology 208, 2023-2036. 68. Ho, S.N. (2006) Intracellular water homeostasis and the mammalian cellular osmotic stress response. Journal of Cellular Physiology 206, 9-15. 69. Hoffmann, E.K., Hoffmann, E., Lang, F., and Zadunaisky, J.A. (2002) Control of Cl− transport in the operculum epithelium of Fundulus heteroclitus: long- and short-term salinity adaptation. Biochimica et Biophysica Acta (BBA) - Biomembranes 1566, 129-139. 70. Hoffmann, E.K., Lambert, I.H., and Pedersen, S.F. (2009) Physiology of cell volume regulation in vertebrates. Physiol Rev 89, 193-277. 71. Hung, L., Lazard, J., Mariojouls, C., and Moreau, Y. (2003) Comparison of starch utilization in fingerlings of two Asian catfishes from the Mekong river (Pangasius bocourti Sauvage, 1880, Pangasius hypophthalmus Sauvage, 1878). Aquaculture Nutrition 9, 215-222.
Bibliography 87
72. Hwang, P.-P. and Lee, T.-H. (2007) New insights into fish ion regulation and mitochondrion-rich cells. Comparative biochemistry and physiology. Part A, Molecular & integrative physiology 148, 479-497. 73. Inokuchi, M., Hiroi, J., Watanabe, S., Lee, K., and Kaneko, T. (2008) Gene expression and morphological localization of NHE3, NCC and NKCC1a in branchial mitochondria-rich cells of Mozambique tilapia (Oreochromis mossambicus) acclimated to a wide range of salinities. Comparative biochemistry and physiology. Part A, Molecular & integrative physiology 151, 151-158. 74. IPCC (2007) Climate Change 2007. In Working Group II Report : "Impacts, Adaptation and Vulnerability" (M.L. Parry, O.F.C., J.P. Palutikof, P.J. van der Linden and C.E. Hanson, ed). 75. Jeong, S.-Y., Kim, J.-H., Lee, W.-O., Dahms, H.-U., and Han, K.-N. (2013) Salinity changes in the anadromous river pufferfish, Takifugu obscurus, mediate gene regulation. Fish Physiol Biochem. 76. Ji, P., Liu, G., Xu, J., Wang, X., Li, J., Zhao, Z., Zhang, X., Zhang, Y., Xu, P., and Sun, X. (2012) Characterization of common carp transcriptome: sequencing, de novo assembly, annotation and comparative genomics. PloS one 7. 77. Jones, A.M. (2001) Programmed cell death in development and defense. Plant Physiology 125, 94-97. 78. Jung, H., Lyons, R., Dinh, H., Hurwood, D., McWilliam, S., and Mather, P. (2011) Transcriptomics of a giant freshwater prawn (Macrobrachium rosenbergii): de novo assembly, annotation and marker discovery. PloS one 6. 79. Kal, A.J., van Zonneveld, A.J., Benes, V., van den Berg, M., Koerkamp, M.G., Albermann, K., Strack, N., Ruijter, J.M., Richter, A., Dujon, B., Ansorge, W., and Tabak, H.F. (1999) Dynamics of Gene Expression Revealed by Comparison of Serial Analysis of Gene Expression Transcript Profiles from Yeast Grown on Two Different Carbon Sources. Molecular Biology of the Cell 10, 1859-1872. 80. Kalujnaia, S., McVee, J., Kasciukovic, T., Stewart, A.J., and Cramb, G. (2010) A role for inositol monophosphatase 1 (IMPA1) in salinity adaptation in the euryhaline eel (Anguilla anguilla). The FASEB Journal 24, 3981-3991. 81. Kalujnaia, S., McWilliam, I., Zaguinaiko, V., Feilen, A., Nicholson, J., Hazon, N., Cutler, C., and Cramb, G. (2007) Transcriptomic approach to the study of osmoregulation in the European eel Anguilla anguilla. Physiological genomics 31, 385-401. 82. Karasov, W.H. and Hume, I.D. (2010) Vertebrate Gastrointestinal System. In Comprehensive Physiology, John Wiley & Sons, Inc. 83. Kelly, S.P. and Woo, N.Y.S. (1999) The response of sea bream following abrupt hyposmotic exposure. Journal of Fish Biology 55, 732-750. 84. Kirfel, J., Magin, T.M., and Reichelt, J. (2003) Keratins: a structural scaffold with emerging functions. Cellular and molecular life sciences : CMLS 60, 56- 71. 85. Klaus, F., Palmada, M., Lindner, R., Laufer, J., Jeyaraj, S., Lang, F., and Boehmer, C. (2008) Up-regulation of hypertonicity-activated myo-inositol transporter SMIT1 by the cell volume-sensitive protein kinase SGK1. The Journal of Physiology 586, 1539-1547.
Bibliography 88
86. Knepper, M.A. (1997) Molecular physiology of urinary concentrating mechanism: regulation of aquaporin water channels by vasopressin. The American journal of physiology 272, F3-12. 87. Kültz, D., Chakravarty, D., and Adilakshmi, T. (2001) A novel 14-3-3 gene is osmoregulated in gill epithelium of the euryhaline teleost Fundulus heteroclitus. Journal of Experimental Biology 204, 2975-2985. 88. Kültz, D., Fiol, D., Valkova, N., Gomez-Jimenez, S., Chan, S., and Lee, J. (2007) Functional genomics and proteomics of the cellular osmotic stress response in 'non-model' organisms. The Journal of experimental biology 210, 1593-1601. 89. Kurita, Y., Nakada, T., Kato, A., Doi, H., Mistry, A.C., Chang, M.H., Romero, M.F., and Hirose, S. (2008) Identification of intestinal bicarbonate transporters involved in formation of carbonate precipitates to stimulate water absorption in marine teleost fish. Am J Physiol Regul Integr Comp Physiol 294, R1402-1412. 90. Langdon, J.S. and Thorpe, J.E. (1984) Response of the gill Na+-K+-ATPase activity, succinic dehydrogenase activity and chloride cells to saltwater adaptation in Atlantic salmon, Salmo salar L., parr and smolt. Journal of Fish Biology 24, 323-331. 91. Laptenko, O. and Prives, C. (2006) Transcriptional regulation by p53: one protein, many possibilities. Cell Death & Differentiation 13, 951-961. 92. Lavado, R., Aparicio-Fabre, R., and Schlenk, D. (2013) Effects of salinity acclimation on the expression and activity of Phase I enzymes (CYP450 and FMOs) in coho salmon (Oncorhynchus kisutch). Fish Physiol Biochem. 93. Lee, B.-Y., Howe, A., Conte, M., D'Cotta, H., Pepey, E., Baroiller, J.-F., di Palma, F., Carleton, K., and Kocher, T. (2010) An EST resource for tilapia based on 17 normalized libraries and assembly of 116,899 sequence tags. BMC Genomics 11, 278. 94. Lee, B.-Y., Lee, W.-J., Streelman, J.T., Carleton, K.L., Howe, A.E., Hulata, G., Slettan, A., Stern, J.E., Terai, Y., and Kocher, T.D. (2005) A Second- Generation Genetic Linkage Map of Tilapia (Oreochromis spp.). Genetics 170, 237-244. 95. Lefevre, S., Huong, D.T.T., Ha, N.T.K., Wang, T., Phuong, N.T., and Bayley, M. (2011a) A telemetry study of swimming depth and oxygen level in a Pangasius pond in the Mekong Delta. Aquaculture 315, 410-413. 96. Lefevre, S., Jensen, F., Huong, D.T.T., Wang, T., Phuong, N., and Bayley, M. (2011b) Effects of nitrite exposure on functional haemoglobin levels, bimodal respiration, and swimming performance in the facultative air-breathing fish Pangasianodon hypophthalmus. Aquatic toxicology (Amsterdam, Netherlands) 104, 86-93. 97. Lefevre, S., Wang, T., Huong, D.T.T., Phuong, N., and Bayley, M. (2013) Partitioning of oxygen uptake and cost of surfacing during swimming in the air-breathing catfish Pangasianodon hypophthalmus. Journal of comparative physiology. B, Biochemical, systemic, and environmental physiology 183, 215-221. 98. Leguen, I., Odjo, N., Le Bras, Y., Luthringer, B., Baron, D., Monod, G., and Prunet, P. (2010) Effect of seawater transfer on CYP1A gene expression in rainbow trout gills. Comp Biochem Physiol A Mol Integr Physiol 156, 211- 217.
Bibliography 89
99. Leray, C., Chapelle, S., Duportail, G., and Florentz, A. (1984) Changes in fluidity and 22: 6 (< i> n- 3) content in phospholipids of trout intestinal brush-border membrane as related to environmental salinity. Biochimica et Biophysica Acta (BBA)-Biomembranes 778, 233-238. 100. Li, C., Weng, S., Chen, Y., Yu, X., Lü, L., Zhang, H., He, J., and Xu, X. (2012) Analysis of Litopenaeus vannamei transcriptome using the next- generation DNA sequencing technique. PloS one 7. 101. Li, H.-O. and Yamada, J. (1992) Changes of the fatty acid composition in smolts of masu salmon (Oncorhynchus masou), associated with desmoltification and sea-water transfer. Comparative Biochemistry and Physiology Part A: Physiology 103, 221-226. 102. Liu, L., Li, Y., Li, S., Hu, N., He, Y., Pong, R., Lin, D., Lu, L., and Law, M. (2012) Comparison of next-generation sequencing systems. Journal of biomedicine & biotechnology 2012, 251364. 103. Liu, Z. (2011) Development of genomic resources in support of sequencing, assembly, and annotation of the catfish genome. Comparative biochemistry and physiology. Part D, Genomics & proteomics 6, 11-17. 104. Lockwood, B. and Somero, G. (2011) Transcriptomic responses to salinity stress in invasive and native blue mussels (genus Mytilus). Molecular ecology 20, 517-529. 105. Loman, N.J., Misra, R.V., Dallman, T.J., Constantinidou, C., Gharbia, S.E., Wain, J., and Pallen, M.J. (2012) Performance comparison of benchtop high- throughput sequencing platforms. Nat Biotech 30, 434-439. 106. Loo, D.D., Wright, E.M., and Zeuthen, T. (2002) Water pumps. The Journal of physiology 542, 53-60. 107. Lunn, J.A. and Rozengurt, E. (2004) Hyperosmotic Stress Induces Rapid Focal Adhesion Kinase Phosphorylation at Tyrosines 397 and 577: Role of Src family kinases and Rho family GTPases. Journal of Biological Chemistry 279, 45266-45278. 108. Mackie, P.M., Gharbi, K., Ballantyne, J.S., McCormick, S.D., and Wright, P.A. (2007) Na+/K+/2Cl− cotransporter and CFTR gill expression after seawater transfer in smolts (0+) of different Atlantic salmon (Salmo salar) families. Aquaculture 272, 625-635. 109. Madsen, S.S., Olesen, J.H., Bedal, K., Engelund, M.B., Velasco-Santamaria, Y.M., and Tipsmark, C.K. (2011) Functional characterization of water transport and cellular localization of three aquaporin paralogs in the salmonid intestine. Frontiers in physiology 2, 56. 110. Mai, W.-j., Yan, J.-l., Wang, L., Zheng, Y., Xin, Y., and Wang, W.-n. (2010) Acute acidic exposure induces p53-mediated oxidative stress and DNA damage in tilapia (Oreochromis niloticus) blood cells. Aquatic toxicology 100, 271-281. 111. Marshall, W.S., & Grosell, M. (2006) Ion Transport, Osmoregulation, and Acid-Base Balance. In The Physiology of Fishes (3rd edn) (Evans, D.H. and Claiborne, J.B., eds), pp. 177, New York: CRC Press. 112. Martínez-Alvarez, R., Sanz, A., García-Gallego, M., Domezain, A., Domezain, J., Carmona, R., del Valle Ostos-Garrido, M., and Morales, A. (2005) Adaptive branchial mechanisms in the sturgeon Acipenser naccarii during acclimation to saltwater. Comparative biochemistry and physiology. Part A, Molecular & integrative physiology 141, 183-190.
Bibliography 90
113. Martinez, A.-S., Cutler, C., Wilson, G., Phillips, C., Hazon, N., and Cramb, G. (2005) Cloning and expression of three aquaporin homologues from the European eel (Anguilla anguilla): effects of seawater acclimation and cortisol treatment on renal expression. Biology of the cell / under the auspices of the European Cell Biology Organization 97, 615-627. 114. Martinez, D.A. and Nelson, M.A. (2010) The next generation becomes the now generation. PLoS Genetics 6, e1000906. 115. McAndrew, B. and Napier, J. (2011) Application of genetics and genomics to aquaculture development: current and future directions. The Journal of Agricultural Science 149, 143-151. 116. McCormick, S.D., Regish, A.M., and Christensen, A.K. (2009) Distinct freshwater and seawater isoforms of Na+/K+-ATPase in gill chloride cells of Atlantic salmon. The Journal of Experimental Biology 212, 3994-4001. 117. McCormick, S.D., Regish, A.M., Christensen, A.K., and Björnsson, B.T. (2013) Differential regulation of sodium–potassium pump isoforms during smolt development and seawater exposure of Atlantic salmon. The Journal of Experimental Biology 216, 1142-1151. 118. McDonald, M.D. and Grosell, M. (2006) Maintaining osmotic balance with an aglomerular kidney. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 143, 447-458. 119. Mekuchi, M., Hatta, T., and Kaneko, T. (2010) Mg-calcite, a carbonate mineral, constitutes Ca precipitates produced as a byproduct of osmoregulation in the intestine of seawater-acclimated Japanese eel Anguilla japonica. Fish Sci 76, 199-205. 120. Mieszkowska, N., Genner, M.J., Hawkins, S.J., and Sims, D.W. (2009) Chapter 3 Effects of Climate Change and Commercial Fishing on Atlantic Cod Gadus morhua. In Advances in Marine Biology (David, W.S., ed), pp. 213-273, Academic Press. 121. Mobasheri, A., Shakibaei, M., and Marples, D. (2004) Immunohistochemical localization of aquaporin 10 in the apical membranes of the human ileum: a potential pathway for luminal water and small solute absorption. Histochemistry and cell biology 121, 463-471. 122. MOFi (2013) Annual report in 2013, action and execution plan in 2014. Argiculture and rural development department. 123. Mohd-Shamsudin, M., Kang, Y., Lili, Z., Tan, T., Kwong, Q., Liu, H., Zhang, G., Othman, R., and Bhassu, S. (2013) In-depth tanscriptomic analysis on giant freshwater prawns. PloS one 8. 124. Mommsen, T.P. (1984) Metabolism of the fish gill. Fish physiology 10, 203- 238. 125. Morgan, J. and Iwama, G. (1996) Cortisol-induced changes in oxygen consumption and ionic regulation in coastal cutthroat trout (Oncorhynchus clarki) parr. Fish Physiol Biochem 15, 385-394. 126. Morgan, J.D. and Iwama, G.K. (1991) Effects of Salinity on Growth, Metabolism, and Ion Regulation in Juvenile Rainbow and Steelhead Trout (Oncorhynchus mykiss) and Fall Chinook Salmon (Oncorhynchus tshawytscha). Canadian Journal of Fisheries and Aquatic Sciences 48, 2083- 2094. 127. Morgan, J.D., Sakamoto, T., Grau, E.G., and Iwama, G.K. (1997) Physiological and Respiratory Responses of the Mozambique Tilapia
Bibliography 91
(Oreochromis mossambicus) to Salinity Acclimation. Comparative Biochemistry and Physiology Part A: Physiology 117, 391-398. 128. Munnik, T. and Vermeer, J.E. (2010) Osmotic stress-induced phosphoinositide and inositol phosphate signalling in plants. Plant, cell & environment 33, 655-669. 129. Nakano, K., Tagawa, M., Takemura, A., and Hirano, T. (1998) Temporal changes in liver carbohydrate metabolism associated with seawater transfer in Oreochromis mossambicus. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology 119, 721-728. 130. Nakasugi, K., Crowhurst, R., Bally, J., and Waterhouse, P. (2014) Combining Transcriptome Assemblies from Multiple De Novo Assemblers in the Allo- Tetraploid Plant Nicotiana benthamiana. PLoS ONE 9, e91776. 131. Nekrutenko, A. and Taylor, J. (2012) Next-generation sequencing data interpretation: enhancing reproducibility and accessibility. Nat Rev Genet 13, 667-672. 132. Nguyen, P.T., Do, H.T., Mather, P.B., and Hurwood, D.A. (2014) Experimental assessment of the effects of sublethal salinities on growth performance and stress in cultured tra catfish (Pangasianodon hypophthalmus). Fish Physiol Biochem. 133. Nielsen, C., Madsen, S.S., and Bjornsson, B.T. (1999) Changes in branchial and intestinal osmoregulatory mechanisms and growth hormone levels during smolting in hatchery-reared and wild brown trout. Journal of Fish Biology 54. 134. Nilsen, T., Ebbesson, L., Madsen, S., McCormick, S., Andersson, E., Björnsson, B., Prunet, P., and Stefansson, S. (2007) Differential expression of gill Na+,K+-ATPase alpha- and beta-subunits, Na+,K+,2Cl- cotransporter and CFTR anion channel in juvenile anadromous and landlocked Atlantic salmon Salmo salar. The Journal of experimental biology 210, 2885-2896. 135. Nishimura, H. and Imai, M. (1982) Control of renal function in freshwater and marine teleosts. Federation proceedings 41, 2355-2360. 136. Norman, J., Danzmann, R., Glebe, B., and Ferguson, M. (2011) The genetic basis of salinity tolerance traits in Arctic charr (Salvelinus alpinus). BMC genetics 12, 81. 137. Norman, J., Robinson, M., Glebe, B., Ferguson, M., and Danzmann, R. (2012) Genomic arrangement of salinity tolerance QTLs in salmonids: A comparative analysis of Atlantic salmon (Salmo salar) with Arctic charr (Salvelinus alpinus) and rainbow trout (Oncorhynchus mykiss). BMC Genomics 13, 1-15. 138. Olson, A.L. and Pessin, J.E. (1996) Structure, function, and regulation of the mammalian facilitative glucose transporter gene family. Annual review of nutrition 16, 235-256. 139. Oltval, Z.N., Milliman, C.L., and Korsmeyer, S.J. (1993) Bcl-2 heterodimerizes in vivo with a conserved homolog, Bax, that accelerates programed cell death. Cell 74, 609-619. 140. Ouattara, N.G., Bodinier, C., Nègre-Sadargues, G., D'Cotta, H., Messad, S., Charmantier, G., Panfili, J., and Baroiller, J.-F. (2009) Changes in gill ionocyte morphology and function following transfer from fresh to hypersaline waters in the tilapia Sarotherodon melanotheron. Aquaculture 290, 155-164.
Bibliography 92
141. P, P., W.Y, W.E.I., S, R., and R, H. (2011) Evaluation of soybean meal in the formulated diets for juvenile Pangasianodon hypophthalmus (Sauvage, 1878). Aquaculture Nutrition 17. 142. Patel, R.K. and Jain, M. (2012) NGS QC Toolkit: A Toolkit for Quality Control of Next Generation Sequencing Data. PLoS ONE 7, e30619. 143. Perry, S.F. (1997) The Chloride Cell: Structure and Function in the Gills of Freshwater Fishes. Annual Review of Physiology 59, 325-347. 144. Perry, S.F. and Walsh, P.J. (1989) Metabolism of isolated fish gill cells: contribution of epithelial chloride cells. Journal of Experimental Biology 144, 507-520. 145. Phan, L.T., Bui, T.M., Nguyen, T.T.T., Gooley, G.J., Ingram, B.A., Nguyen, H.V., Nguyen, P.T., and De Silva, S.S. (2009) Current status of farming practices of striped catfish, Pangasianodon hypophthalmus in the Mekong Delta, Vietnam. Aquaculture 296, 227-236. 146. Philippart, C.J.M., Anadón, R., Danovaro, R., Dippner, J.W., Drinkwater, K.F., Hawkins, S.J., Oguz, T., O'Sullivan, G., and Reid, P.C. (2011) Impacts of climate change on European marine ecosystems: Observations, expectations and indicators. Journal of Experimental Marine Biology and Ecology 400, 52-69. 147. Phuong, N.T. and Oanh, D.T.H. (2010) Striped Catfish Aquaculture in Vietnam: A Decade of Unprecedented Development Success Stories in Asian Aquaculture. (Silva, S.S. and Davy, F.B., eds), pp. 131-147, Springer Netherlands. 148. Pierrard, M.-A., Kestemont, P., Delaive, E., Dieu, M., Raes, M., and Silvestre, F. (2012a) Malachite green toxicity assessed on Asian catfish primary cultures of peripheral blood mononuclear cells by a proteomic analysis. Aquatic toxicology (Amsterdam, Netherlands) 114-115, 142-152. 149. Pierrard, M.-A., Kestemont, P., Phuong, N., Tran, M., Delaive, E., Thezenas, M.-L., Dieu, M., Raes, M., and Silvestre, F. (2012b) Proteomic analysis of blood cells in fish exposed to chemotherapeutics: evidence for long term effects. Journal of proteomics 75, 2454-2467. 150. Pinto, P., Matsumura, H., Thorne, M., Power, D., Terauchi, R., Reinhardt, R., and Canário, A. (2010) Gill transcriptome response to changes in environmental calcium in the green spotted puffer fish. BMC genomics 11, 476. 151. Poen, S. and Pornbanlualap, S. (2013) Growth hormone from striped catfish (Pangasianodon hypophthalmus): genomic organization, recombinant expression and biological activity. Gene 518, 316-324. 152. Pörtner, H.O., Berdal, B., Blust, R., Brix, O., Colosimo, A., De Wachter, B., Giuliani, A., Johansen, T., Fischer, T., Knust, R., Lannig, G., Naevdal, G., Nedenes, A., Nyhammer, G., Sartoris, F.J., Serendero, I., Sirabella, P., Thorkildsen, S., and Zakhartsev, M. (2001) Climate induced temperature effects on growth performance, fecundity and recruitment in marine fish: developing a hypothesis for cause and effect relationships in Atlantic cod (Gadus morhua) and common eelpout (Zoarces viviparus). Continental Shelf Research 21, 1975-1997. 153. Prabjeet, S., Soottawat, B., Sajid, M., and Hideki, K. (2011) Isolation and characterisation of collagen extracted from the skin of striped catfish (Pangasianodon hypophthalmus). Food Chemistry 124.
Bibliography 93
154. Pritchard, J. (2003) The gill and homeostasis: transport under stress. American journal of physiology. Regulatory, integrative and comparative physiology 285, R1269. 155. Qian, X., Ba, Y., Zhuang, Q., and Zhong, G. (2014) RNA-Seq technology and its application in fish transcriptomics. Omics : a journal of integrative biology 18, 98-110. 156. Qin, J., Huang, Z., Chen, J., Zou, Q., You, W., and Ke, C. (2012) Sequencing and de novo analysis of Crassostrea angulata (Fujian oyster) from 8 different developing phases using 454 GSFlx. PloS one 7. 157. Quail, M., Smith, M., Coupland, P., Otto, T., Harris, S., Connor, T., Bertoni, A., Swerdlow, H., and Gu, Y. (2012) A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers. BMC Genomics 13, 341. 158. Richards, J.G., Semple, J.W., Bystriansky, J.S., and Schulte, P.M. (2003) Na+/K+-ATPase α-isoform switching in gills of rainbow trout (Oncorhynchus mykiss) during salinity transfer. Journal of Experimental Biology 206, 4475-4486. 159. Robertson, G., Schein, J., Chiu, R., Corbett, R., Field, M., Jackman, S.D., Mungall, K., Lee, S., Okada, H.M., Qian, J.Q., Griffith, M., Raymond, A., Thiessen, N., Cezard, T., Butterfield, Y.S., Newsome, R., Chan, S.K., She, R., Varhol, R., Kamoh, B., Prabhu, A.-L.L., Tam, A., Zhao, Y., Moore, R.A., Hirst, M., Marra, M.A., Jones, S.J., Hoodless, P.A., and Birol, I. (2010) De novo assembly and analysis of RNA-seq data. Nature methods 7, 909-912. 160. Romano, A., Barca, A., Storelli, C., and Verri, T. (2014) Teleost fish models in membrane transport research: the PEPT1(SLC15A1) H+–oligopeptide transporter as a case study. The Journal of Physiology 592, 881-897. 161. Rønnestad, I., Gavaia, P.J., Viegas, C.S.B., Verri, T., Romano, A., Nilsen, T.O., Jordal, A.-E.O., Kamisaka, Y., and Cancela, M.L. (2007) Oligopeptide transporter PepT1 in Atlantic cod (Gadus morhua L.): cloning, tissue expression and comparative aspects. Journal of Experimental Biology 210, 3883-3896. 162. Root, T.L., Schneider, S.H., Warren, R., Price, J.R., and Mastrandrea, P.R. (2013) Climate Change and Wild Species. In Encyclopedia of Biodiversity (Second Edition) (Editor-in-Chief: Simon, A.L., ed), pp. 79-99, Academic Press. 163. Salati, A.P., Baghbanzadeh, A., Soltani, M., Peyghan, R., and Riazi, G. (2011) Effect of different levels of salinity on gill and kidney function in common carp Cyprinus carpio (Pisces: Cyprinidae). Italian Journal of Zoology 78. 164. Sangaletti, R., Terova, G., Peres, A., Bossi, E., Corà, S., and Saroglia, M. (2009) Functional expression of the oligopeptide transporter PepT1 from the sea bass (Dicentrarchus labrax). Pflugers Arch - Eur J Physiol 459, 47-54. 165. Sangiao-Alvarellos, S., Arjona, F.J., del Río, M.P.M., Míguez, J.M., Mancera, J.M., and Soengas, J.L. (2005) Time course of osmoregulatory and metabolic changes during osmotic acclimation in Sparus auratus. Journal of Experimental Biology 208, 4291-4304. 166. Sangiao-Alvarellos, S., Laiz-Carrion, R., Guzman, J.M., Martin del Rio, M.P., Miguez, J.M., Mancera, J.M., and Soengas, J.L. (2003) Acclimation of S. aurata to various salinities alters energy metabolism of osmoregulatory
Bibliography 94
and nonosmoregulatory organs. Am J Physiol Regul Integr Comp Physiol 285, R897-907. 167. Santos, C., Estêvão, M., Fuentes, J., Cardoso, J., Fabra, M., Passos, A., Detmers, F., Deen, P., Cerdà, J., and Power, D. (2004) Isolation of a novel aquaglyceroporin from a marine teleost (Sparus auratus): function and tissue distribution. The Journal of experimental biology 207, 1217-1227. 168. Sardet, C., Pisam, M., and Maetz, J. (1979) The surface epithelium of teleostean fish gills. Cellular and junctional adaptations of the chloride cell in relation to salt adaptation. The Journal of cell biology 80, 96-117. 169. Sargent, J.R., Thompson, A.J., and Bornancin, M. (1975) Activities and localization of succinic dehydrogenase and Na+/K+-activated adenosine triphosphatase in the gills of fresh water and sea water eels (Anguilla anguilla). Comparative Biochemistry and Physiology Part B: Comparative Biochemistry 51, 75-79. 170. Schadt, E.E., Linderman, M.D., Sorenson, J., Lee, L., and Nolan, G.P. (2010) Computational solutions to large-scale data management and analysis. Nat Rev Genet 11, 647-657. 171. Schulz, M.H., Zerbino, D.R., Vingron, M., and Birney, E. (2012) Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels. Bioinformatics 28, 1086-1092. 172. Scott, G.R., Schulte, P.M., and Wood, C.M. (2006) Plasticity of osmoregulatory function in the killifish intestine: drinking rates, salt and water transport, and gene expression after freshwater transfer. Journal of Experimental Biology 209, 4040-4050. 173. Sebesvari, Z., Le, T.T.H., and Renaud, F.G. (2011) Climate change adaptation and agrichemicals in the Mekong Delta, Vietnam. In Environmental Change and Agricultural Sustainability in the Mekong Delta, pp. 219-239, Springer. 174. Shaw, J.R., Sato, D., VanderHeide, J., LaCasse, T., Stanton, C.R., Lankowski, A., Stanton, S.E., Chapline, C., Coutermarsh, B., Barnaby, R., Karlson, K., and Stanton, B.A. (2008) The Role of SGK and CFTR in Acute Adaptation to Seawater in Fundulus Heteroclitus. Cellular Physiology and Biochemistry 22, 069-078. 175. Shehadeh, Z.H. and Gordon, M.S. (1969) The role of the intestine in salinity adaptation of the rainbow trout, Salmo gairdneri. Comparative Biochemistry and Physiology 30, 397-418. 176. Shinsuke, M., Kosuke, S., Phoutsamone, P., and Bounsong, V. (2009) Growth and morphological development of laboratory-reared larval and juvenile Pangasianodon hypophthalmus. Ichthyological Research 57. 177. Sîrbu, A., Kerr, G., Crane, M., and Ruskin, H.J. (2012) RNA-Seq vs Dual- and Single-Channel Microarray Data: Sensitivity Analysis for Differential Expression and Clustering. PLoS ONE 7, e50986. 178. Skadhauge, E. (1969) The mechanism of salt and water absorption in the intestine of the eel (Anguilla anguilla) adapted to waters of various salinities. The Journal of physiology 204, 135-158. 179. Slembrouck, J., Baras, E., Subagja, J., Hung, L.T., and Legendre, M. (2009) Survival, growth and food conversion of cultured larvae of Pangasianodon hypophthalmus, depending on feeding level, prey density and fish density. Aquaculture 294.
Bibliography 95
180. Smith, H.W. (1930) The absorption and excretion of water and salts by marine teleosts. American Journal of Physiology 93, 480-505. 181. Soengas, J.L., Sangiao-Alvarellos, S., Carrion, R.l.-., and Mancera, J.M. (2007) Energy Metabolism and osmotic acclimation in Teleost Fish. In Fish Osmoregulation (Baldisserotto, B. and Mancera Romero, J.M., eds), Science Publishers. 182. Sundell, K.S. and Sundh, H. (2012) Intestinal fluid absorption in anadromous salmonids: importance of tight junctions and aquaporins. Frontiers in physiology 3, 388. 183. Surget-Groba, Y. and Montoya-Burgos, J.I. (2010) Optimization of de novo transcriptome assembly from next-generation sequencing data. Genome research 20, 1432-1440. 184. Sutherland, B., Jantzen, S., Yasuike, M., Sanderson, D., Koop, B., and Jones, S. (2012) Transcriptomics of coping strategies in free-swimming Lepeophtheirus salmonis (Copepoda) larvae responding to abiotic stress. Molecular ecology 21, 6000-6014. 185. Suzuki, Y., Itakura, M., Kashiwagi, M., Nakamura, N., Matsuki, T., Sakuta, H., Naito, N., Takano, K., Fujita, T., and Hirose, S. (1999) Identification by differential display of a hypertonicity-inducible inward rectifier potassium channel highly expressed in chloride cells. Journal of Biological Chemistry 274, 11376-11382. 186. Takashi, Y., Stephen, D.M., and Susumu, H. (2012) Effects of environmental salinity, biopsy, and GH and IGF-I administration on the expression of immune and osmoregulatory genes in the gills of Atlantic salmon (Salmo salar). Aquaculture 362-363. 187. Takeuchi, K., Toyohara, H., and Sakaguchi, M. (2000) A hyperosmotic stress-induced mRNA of carp cell encodes Na(+)- and Cl(-)-dependent high affinity taurine transporter. Biochimica et biophysica acta 1464, 219-230. 188. Thanh, N.M., Jung, H., Lyons, R.E., Chand, V., Tuan, N.V., Thu, V.T.M., and Mather, P. (2014) A transcriptomic analysis of striped catfish (Pangasianodon hypophthalmus) in response to salinity adaptation: De novo assembly, gene annotation and marker discovery. Comparative Biochemistry and Physiology Part D: Genomics and Proteomics 10, 52-63. 189. Thinh, N., Kuo, T., Hung, L., Loc, T., Chen, S., Evensen, O., and Schuurman, H. (2009) Combined immersion and oral vaccination of Vietnamese catfish (Pangasianodon hypophthalmus) confers protection against mortality caused by Edwardsiella ictaluri. Fish & shellfish immunology 27, 773-776. 190. Thường, N.V. (2008) Classification of the Pangasianodon hypophthalmus in the Mekong River. Can Tho University Journals 2008 (1): 84-89. 191. Tine, M., de Lorgeril, J., D'Cotta, H., Pepey, E., Bonhomme, F., Baroiller, J., and Durand, J.-D. (2008) Transcriptional responses of the black-chinned tilapia Sarotherodon melanotheron to salinity extremes. Marine genomics 1, 37-46. 192. Tine, M., McKenzie, D.J., Bonhomme, F., and Durand, J.-D. (2011) Salinity- related variation in gene expression in wild populations of the black-chinned tilapia from various West African coastal marine, estuarine and freshwater habitats. Estuarine, Coastal and Shelf Science 91, 102-109. 193. Tipsmark, C., Baltzegar, D., Ozden, O., Grubb, B., and Borski, R. (2008) Salinity regulates claudin mRNA and protein expression in the teleost gill.
Bibliography 96
American journal of physiology. Regulatory, integrative and comparative physiology 294, 14. 194. Tipsmark, C. and Madsen, S. (2012) Tricellulin, occludin and claudin-3 expression in salmon intestine and kidney during salinity adaptation. Comparative biochemistry and physiology. Part A, Molecular & integrative physiology 162, 378-385. 195. Tipsmark, C., Sørensen, K., and Madsen, S. (2010a) Aquaporin expression dynamics in osmoregulatory tissues of Atlantic salmon during smoltification and seawater acclimation. The Journal of experimental biology 213, 368-379. 196. Tipsmark, C.K., Madsen, S.S., and Borski, R.J. (2004) Effect of salinity on expression of branchial ion transporters in striped bass (Morone saxatilis). Journal of Experimental Zoology Part A: Comparative Experimental Biology 301A, 979-991. 197. Tipsmark, C.K., Sorensen, K.J., Hulgard, K., and Madsen, S.S. (2010b) Claudin-15 and -25b expression in the intestinal tract of Atlantic salmon in response to seawater acclimation, smoltification and hormone treatment. Comp Biochem Physiol A Mol Integr Physiol 155, 361-370. 198. Tse, W., Au, D., and Wong, C. (2006) Characterization of ion channel and transporter mRNA expressions in isolated gill chloride and pavement cells of seawater acclimating eels. Biochemical and biophysical research communications 346, 1181-1190. 199. Tse, W.K.F., Sun, J., Zhang, H., Law, A.Y.S., Yeung, B.H.Y., Chow, S.C., Qiu, J.-W., and Wong, C.K.C. (2013) Transcriptomic and iTRAQ proteomic approaches reveal novel short-term hyperosmotic stress responsive proteins in the gill of the Japanese eel (Anguilla japonica). Journal of Proteomics 89, 81-94. 200. Tseng, Y.-C. and Hwang, P.-P. (2008) Some insights into energy metabolism for osmoregulation in fish. Comparative biochemistry and physiology. Toxicology & pharmacology : CBP 148, 419-429. 201. Tseng, Y.-C., Lee, J.-R., Chang, J.C.-H., Kuo, C.-H., Lee, S.-J., and Hwang, P.-P. (2008) Regulation of lactate dehydrogenase in tilapia (Oreochromis mossambicus) gills during acclimation to salinity challenge. Zool Stud 47, 473-480. 202. Tu, T., Haesebrouck, F., Nguyen, A., Sorgeloos, P., Baele, M., and Decostere, A. (2008) Antimicrobial susceptibility pattern of Edwardsiella ictaluri isolates from natural outbreaks of bacillary necrosis of Pangasianodon hypophthalmus in Vietnam. Microbial drug resistance (Larchmont, N.Y.) 14, 311-316. 203. van Hemert, M.J., Steensma, H.Y., and van Heusden, G.P. (2001) 14-3-3 proteins: key regulators of cell division, signalling and apoptosis. BioEssays : news and reviews in molecular, cellular and developmental biology 23, 936- 946. 204. Van Itallie, C., Holmes, J., Bridges, A., Gookin, J., Coccaro, M., Proctor, W., Colegio, O., and Anderson, J. (2008) The density of small tight junction pores varies among cell types and is increased by expression of claudin-2. Journal of cell science 121, 298-305. 205. Van Sang, N., Van Hao, N., Hung, D., Khoi, P.D., Ha, B.T.L., Dinh, V.H., and Dien, N. (2007) Selective breeding for growth and fillet yield of river catfish Pangasianodon hypophthalmus in the Mekong Delta, Vietnam. Aquaculture Asia 12, 26.
Bibliography 97
206. Venkatachari, S.A.T. (1974) Effect of salinity adaptation on nitrogen metabolism in the freshwater fish Tilapia mossambica. I. Tissue protein and amino acid levels. Mar. Biol. 24, 57-63. 207. Verri, T., Kottra, G., Romano, A., Tiso, N., Peric, M., Maffia, M., Boll, M., Argenton, F., Daniel, H., and Storelli, C. (2003) Molecular and functional characterisation of the zebrafish (Danio rerio) PEPT1-type peptide transporter. FEBS letters 549, 115-122. 208. Vojtek, A.B. and Cooper, J.A. (1995) Rho family members: activators of MAP kinase cascades. Cell 82, 527-529. 209. Waldegger, S., Barth, P., Forrest, J.N., Jr., Greger, R., and Lang, F. (1998) Cloning of sgk serine-threonine protein kinase from shark rectal gland - a gene induced by hypertonicity and secretagogues. Pflugers Archiv : European journal of physiology 436, 575-580. 210. Wang, S., Peatman, E., Abernathy, J., Waldbieser, G., Lindquist, E., Richardson, P., Lucas, S., Wang, M., Li, P., Thimmapuram, J., Liu, L., Vullaganti, D., Kucuktas, H., Murdock, C., Small, B., Wilson, M., Liu, H., Jiang, Y., Lee, Y., Chen, F., Lu, J., Wang, W., Xu, P., Somridhivej, B., Baoprasertkul, P., Quilang, J., Sha, Z., Bao, B., Wang, Y., Wang, Q., Takano, T., Nandi, S., Liu, S., Wong, L., Kaltenboeck, L., Quiniou, S., Bengten, E., Miller, N., Trant, J., Rokhsar, D., Liu, Z., and Consortium, t.C.G. (2010) Assembly of 500,000 inter-specific catfish expressed sequence tags and large scale gene-associated marker development for whole genome association studies. Genome Biology 11, R8. 211. Wang, Z., Gerstein, M., and Snyder, M. (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nature reviews. Genetics 10, 57-63. 212. Wassmann, R., Hien, N.X., Hoanh, C.T., and Tuong, T.P. (2004) Sea Level Rise Affecting the Vietnamese Mekong Delta: Water Elevation in the Flood Season and Implications for Rice Production. Climatic Change 66, 89-107. 213. Watanabe, S., Mekuchi, M., Ideuchi, H., Kim, Y.K., and Kaneko, T. (2011) Electroneutral cation-Cl- cotransporters NKCC2 beta and NCC beta expressed in the intestinal tract of Japanese eel Anguilla japonica. Comp Biochem Physiol A Mol Integr Physiol 159, 427-435. 214. Wilson, R.W. and Grosell, M. (2003) Intestinal bicarbonate secretion in marine teleost fish—source of bicarbonate, pH sensitivity, and consequences for whole animal acid–base and calcium homeostasis. Biochimica et Biophysica Acta (BBA) - Biomembranes 1618, 163-174. 215. Woo, N.Y.S. and Murat, J.C. (1981) Studies on the biology of the red sea bream Chrysophrys major III. Metabolic response to starvation in different salinities. Mar. Biol. 61, 255-260. 216. Wright, E.M., Hirayama, B.A., and Loo, D.F. (2007) Active sugar transport in health and disease. Journal of internal medicine 261, 32-43. 217. Xia, J.H., Liu, P., Liu, F., Lin, G., Sun, F., Tu, R., and Yue, G.H. (2013) Analysis of stress-responsive transcriptome in the intestine of Asian seabass (Lates calcarifer) using RNA-seq. DNA research 20, 449-460. 218. Xie, Y., Wu, G., Tang, J., Luo, R., Patterson, J., Liu, S., Huang, W., He, G., Gu, S., Li, S., Zhou, X., Lam, T.-W., Li, Y., Xu, X., Wong, G.K.-S., and Wang, J. (2014) SOAPdenovo-Trans: De novo transcriptome assembly with short RNA-Seq reads. Bioinformatics. 219. Ya, Y. and Stephen, A.S. (2013) Optimizing de novo assembly of short-read RNA-seq data for phylogenomics. BMC genomics.
Bibliography 98
220. Yamaguchi, S., Miura, C., Ito, A., Agusa, T., Iwata, H., Tanabe, S., Tuyen, B., and Miura, T. (2007) Effects of lead, molybdenum, rubidium, arsenic and organochlorines on spermatogenesis in fish: monitoring at Mekong Delta area and in vitro experiment. Aquatic toxicology (Amsterdam, Netherlands) 83, 43-51. 221. Yamauchi, A., Uchida, S., Preston, A.S., Kwon, H.M., and Handler, J.S. (1993) Hypertonicity stimulates transcription of gene for Na(+)-myo-inositol cotransporter in MDCK cells. The American journal of physiology 264, F20- 23. 222. Yan, B., Wang, Z.-H., and Zhao, J.-L. (2013) Mechanism of osmoregulatory adaptation in tilapia. Molecular biology reports 40, 925-931. 223. Yavuzcan-Yıldız, H. and Kırkavgaç-Uzbilek, M. (2001) The evaluation of secondary stress response of grass carp (Ctenopharyngodon idella, Val. 1844) after exposing to the saline water. Fish Physiol Biochem 25, 287-290. 224. Ye, J., Fang, L., Zheng, H., Zhang, Y., Chen, J., Zhang, Z., Wang, J., Li, S., Li, R., Bolund, L., and Wang, J. (2006) WEGO: a web tool for plotting GO annotations. Nucleic acids research 34, 7. 225. Yukinori, M., Audrey Daning, T., Leong Seng, L., and Syahirah, Y. (2010) Feeding behavior under dark conditions in larvae of sutchi catfish Pangasianodon hypophthalmus. Fish Sci 76. 226. Zerbino, D.R. (2009) Genome assembly and comparison using de Bruijn graphs. Hinxton, Cambridge, United Kingdom 164. 227. Zerbino, D.R. and Birney, E. (2008) Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome Research 18, 821-829. 228. Zhao, Q.-Y.Y., Wang, Y., Kong, Y.-M.M., Luo, D., Li, X., and Hao, P. (2011) Optimizing de novo transcriptome assembly from short-read RNA- Seq data: a comparative study. BMC bioinformatics 12 Suppl 14. 229. Zhao, X., Yu, H., Kong, L., and Li, Q. (2012) Transcriptomic responses to salinity stress in the Pacific oyster Crassostrea gigas. PloS one 7.
Bibliography 99
Appendices
Appendix A –DVD of data files File content of DVD:
A1_all_data
A2_assembly
A3_raw_data_qc
A4_RNA_cDNA_extraction
A5_scripts
A6_Functional_annotation_files
Appendix B – KOG and WEGO chart
Appendices 101
Appendix C – Gene enrichment analysis Over-representative GO in Down-regulated transcript
GO‐ID Term Category FDR P‐ Value GO:0051179 localization P 1.71E‐ 1.96E‐ 06 09 GO:0051234 establishment of localization P 1.50E‐ 4.78E‐ 10 14 GO:0006810 transport P 2.44E‐ 1.55E‐ 11 15 GO:0044710 single‐organism metabolic P 4.90E‐ 4.36E‐ process 08 11 GO:0044765 single‐organism transport P 8.49E‐ 1.08E‐ 11 14 GO:0044281 small molecule metabolic process P 1.23E‐ 2.35E‐ 04 07 GO:0071702 organic substance transport P 2.02E‐ 4.48E‐ 04 07 GO:0006811 ion transport P 8.85E‐ 3.38E‐ 10 13 GO:0055085 transmembrane transport P 1.29E‐ 6.57E‐ 09 13 GO:0055114 oxidation‐reduction process P 4.90E‐ 4.06E‐
Appendices 102
08 11 GO:0046907 intracellular transport P 3.50E‐ 2.69E‐ 02 04 GO:0045184 establishment of protein P 4.98E‐ 4.12E‐ localization 02 04 GO:0015031 protein transport P 2.12E‐ 1.42E‐ 02 04 GO:0016192 vesicle‐mediated transport P 1.86E‐ 1.15E‐ 02 04 GO:0034220 ion transmembrane transport P 5.87E‐ 6.36E‐ 07 10 GO:0006812 cation transport P 1.69E‐ 5.93E‐ 03 06 GO:0006886 intracellular protein transport P 1.44E‐ 8.09E‐ 02 05 GO:0019752 carboxylic acid metabolic process P 3.92E‐ 3.07E‐ 02 04 GO:0006820 anion transport P 4.39E‐ 2.79E‐ 09 12 GO:0030001 metal ion transport P 7.95E‐ 4.25E‐ 03 05 GO:0006897 endocytosis P 4.26E‐ 1.79E‐ 03 05 GO:0015672 monovalent inorganic cation P 1.19E‐ 3.63E‐ transport 03 06 GO:1901615 organic hydroxy compound P 4.94E‐ 8.48E‐ metabolic process 05 08 GO:0015711 organic anion transport P 1.99E‐ 7.43E‐ 03 06 GO:0006066 alcohol metabolic process P 1.23E‐ 2.42E‐ 04 07 GO:0006814 sodium ion transport P 2.73E‐ 6.59E‐ 04 07 GO:0015698 inorganic anion transport P 4.39E‐ 2.79E‐ 09 12 GO:0044712 single‐organism catabolic process P 5.95E‐ 2.95E‐ 03 05 GO:0044282 small molecule catabolic process P 5.95E‐ 2.95E‐ 03 05 GO:0015849 organic acid transport P 3.37E‐ 2.58E‐ 02 04 GO:0008202 steroid metabolic process P 3.73E‐ 1.53E‐ 03 05 GO:0016054 organic acid catabolic process P 3.36E‐ 2.55E‐ 02 04 GO:0046395 carboxylic acid catabolic process P 3.36E‐ 2.55E‐
Appendices 103
02 04 GO:0003014 renal system process P 3.64E‐ 9.96E‐ 04 07 GO:0006821 chloride transport P 5.54E‐ 2.65E‐ 03 05 GO:0006730 one‐carbon metabolic process P 2.03E‐ 7.76E‐ 03 06 GO:0070293 renal absorption P 2.70E‐ 3.53E‐ 06 09 GO:0015701 bicarbonate transport P 2.02E‐ 4.49E‐ 04 07 GO:0015893 drug transport P 5.61E‐ 1.57E‐ 04 06 GO:0006081 cellular aldehyde metabolic P 5.34E‐ 2.49E‐ process 03 05 GO:0072348 sulfur compound transport P 7.36E‐ 3.89E‐ 03 05 GO:0019755 one‐carbon compound transport P 1.55E‐ 3.16E‐ 04 07 GO:0008272 sulfate transport P 4.30E‐ 1.83E‐ 03 05 GO:0043388 positive regulation of DNA P 1.72E‐ 1.01E‐ binding 02 04 GO:0006826 iron ion transport P 2.47E‐ 1.70E‐ 02 04 GO:0071391 cellular response to estrogen P 4.81E‐ 3.95E‐ stimulus 02 04 GO:0015840 urea transport P 6.63E‐ 1.90E‐ 04 06 GO:0014075 response to amine stimulus P 5.09E‐ 2.23E‐ 03 05 GO:0032456 endocytic recycling P 1.59E‐ 9.12E‐ 02 05 GO:0046487 glyoxylate metabolic process P 5.71E‐ 1.02E‐ 05 07 GO:0071918 urea transmembrane transport P 1.67E‐ 5.65E‐ 03 06 GO:0006662 glycerol ether metabolic process P 4.04E‐ 3.21E‐ 02 04 GO:0006067 ethanol metabolic process P 3.73E‐ 1.51E‐ 03 05 GO:0042891 antibiotic transport P 3.73E‐ 1.51E‐ 03 05 GO:0034308 primary alcohol metabolic P 6.31E‐ 3.25E‐ process 03 05 GO:1901998 toxin transport P 1.80E‐ 1.10E‐
Appendices 104
02 04 GO:0042744 hydrogen peroxide catabolic P 1.80E‐ 1.10E‐ process 02 04 GO:0042866 pyruvate biosynthetic process P 1.73E‐ 6.15E‐ 03 06 GO:0006559 L‐phenylalanine catabolic process P 2.60E‐ 1.91E‐ 02 04 GO:0006558 L‐phenylalanine metabolic P 2.60E‐ 1.91E‐ process 02 04 GO:1902222 erythrose 4‐ P 2.60E‐ 1.91E‐ phosphate/phosphoenolpyruvate 02 04 family amino acid catabolic process GO:1902221 erythrose 4‐ P 2.60E‐ 1.91E‐ phosphate/phosphoenolpyruvate 02 04 family amino acid metabolic process GO:0042938 dipeptide transport P 1.89E‐ 1.24E‐ 02 04 GO:0009436 glyoxylate catabolic process P 1.89E‐ 1.24E‐ 02 04
APPENDIX Over-representative GO in Up-regulated transcript
GO‐ID Term Category FDR P‐Value GO:0008219 cell death P 7.36E‐ 1.51E‐ 03 05 GO:0016265 death P 7.36E‐ 1.54E‐ 03 05 GO:0012501 programmed cell death P 1.15E‐ 2.71E‐ 02 05 GO:0006915 apoptotic process P 3.99E‐ 2.25E‐ 02 04 GO:0006412 translation P 2.38E‐ 1.21E‐ 05 08 GO:0006417 regulation of translation P 3.99E‐ 2.26E‐ 02 04 GO:0051258 protein polymerization P 3.99E‐ 2.22E‐ 02 04 GO:0042246 tissue regeneration P 3.46E‐ 6.17E‐ 03 06 GO:0006414 translational elongation P 1.82E‐ 5.56E‐ 02 05 GO:0030833 regulation of actin filament P 4.25E‐ 2.51E‐ polymerization 02 04 GO:0009410 response to xenobiotic P 9.69E‐ 2.22E‐
Appendices 105
stimulus 03 05 GO:0071466 cellular response to P 7.39E‐ 1.65E‐ xenobiotic stimulus 03 05 GO:0031101 fin regeneration P 1.82E‐ 5.27E‐ 02 05 GO:0019319 hexose biosynthetic process P 2.47E‐ 8.96E‐ 02 05 GO:0046364 monosaccharide P 3.56E‐ 1.80E‐ biosynthetic process 02 04 GO:0035850 epithelial cell P 4.20E‐ 2.40E‐ differentiation involved in 02 04 kidney development GO:0006094 gluconeogenesis P 3.97E‐ 2.09E‐ 02 04 GO:0007512 adult heart development P 2.92E‐ 1.19E‐ 02 04 GO:0072012 glomerulus vasculature P 2.92E‐ 1.19E‐ development 02 04 GO:0061440 kidney vasculature P 3.97E‐ 2.12E‐ development 02 04 GO:0061437 renal system vasculature P 3.97E‐ 2.12E‐ development 02 04 GO:0051764 actin crosslink formation P 4.88E‐ 2.95E‐ 02 04 GO:0032796 uropod organization P 2.56E‐ 3.42E‐ 03 06 GO:0072104 glomerular capillary P 1.49E‐ 3.99E‐ formation 02 05 GO:0072103 glomerulus vasculature P 1.49E‐ 3.99E‐ morphogenesis 02 05 GO:0061439 kidney vasculature P 2.22E‐ 7.63E‐ morphogenesis 02 05 GO:0061438 renal system vasculature P 2.22E‐ 7.63E‐ morphogenesis 02 05 GO:0003365 establishment of cell P 2.55E‐ 1.00E‐ polarity involved in 02 04 ameboidal cell migration GO:0003379 establishment of cell P 1.40E‐ 3.49E‐ polarity involved in 02 05 gastrulation cell migration GO:0006538 glutamate catabolic process P 3.99E‐ 2.24E‐ 02 04 GO:0009253 peptidoglycan catabolic P 3.14E‐ 1.40E‐ process 02 04 GO:0000270 peptidoglycan metabolic P 3.14E‐ 1.40E‐ process 02 04
Appendices 106
GO:0042412 taurine biosynthetic P 3.14E‐ 1.40E‐ process 02 04
Appendices 107