genome-wide transcription analysis of histidine-related
TRANSCRIPT
Genome-wide transcription analysis of histidine-related cataractin Atlantic salmon (Salmo salar L)
Christiane Tröße,1 Rune Waagbø,1 Olav Breck,2 Anne-Kristin Stavrum,3 Kjell Petersen,4 Pål A. Olsvik1
1National Institute of Nutrition and Seafood Research (NIFES), Bergen, Norway; 2Marine Harvest Norway AS, Bergen, Norway;3Department of Clinical Medicine, University of Bergen, Bergen, Norway; 4Computational Biology Unit (CBU), Bergen Center forComputational Science (BCCS), University of Bergen, Bergen, Norway
Purpose: Elevated levels of dietary histidine have previously been shown to prevent or mitigate cataract formation infarmed Atlantic salmon (Salmo salar L). The aim of this study was to shed light on the mechanisms by which histidineacts. Applying microarray analysis to the lens transcriptome, we screened for differentially expressed genes in search fora model explaining cataract development in Atlantic salmon and possible markers for early cataract diagnosis.Methods: Adult Atlantic salmon (1.7 kg) were fed three standard commercial salmon diets only differing in the histidinecontent (9, 13, and 17 g histidine/kg diet) for four months. Individual cataract scores for both eyes were assessed by slit-lamp biomicroscopy. Lens N-acetyl histidine contents were measured by high performance liquid chromatography(HPLC). Total RNA extracted from whole lenses was analyzed using the GRASP 16K salmonid microarray. Themicroarray data were analyzed using J-Express Pro 2.7 and validated by quantitative real-time polymerase chain reaction(qRT–PCR).Results: Fish developed cataracts with different severity in response to dietary histidine levels. Lens N-acetyl histidinecontents reflected the dietary histidine levels and were negatively correlated to cataract scores. Significance analysis ofmicroarrays (SAM) revealed 248 significantly up-regulated transcripts and 266 significantly down-regulated transcriptsin fish that were fed a low level of histidine compared to fish fed a higher histidine level. Among the differentially expressedtranscripts were metallothionein A and B as well as transcripts involved in lipid metabolism, carbohydrate metabolism,regulation of ion homeostasis, and protein degradation. Hierarchical clustering and correspondence analysis plot confirmeddifferences in gene expression between the feeding groups. The differentially expressed genes could be categorized as“early” and “late” responsive according to their expression pattern relative to progression in cataract formation.Conclusions: Dietary histidine regimes affected cataract formation and lens gene expression in adult Atlantic salmon.Regulated transcripts selected from the results of this genome-wide transcription analysis might be used as possiblebiological markers for cataract development in Atlantic salmon.
A cataract is defined as the loss of transparency of the eyelens. The eye lens is composed of two types of cells, an outermonolayer of epithelial cells and underlying fiber cells, whichare nourished by the outer monolayer. As the lens grows,epithelial cells differentiate into fiber cells covering the olderlayers of fiber cells like the skins of an onion. The fiber cellseventually lose their nuclei and other organelles. The furtherthe fiber cells are from the epithelial cells, the lower themetabolic activity. The fiber cells contain the major lensproteins, the crystallins. These proteins are highly ordered andtightly packed, which enables light to pass through the clearlens and to be absorbed by the retina where vision occurs [1].Cataracts can be caused by a variety of factors includingphysical damage, oxidative stress, age, and geneticpredisposition. Several nutrient deficiencies have been foundto provoke cataracts. Since cataracts are a major problem forhumans, especially elderly people, several mammalian
Correspondence to: Christiane Tröße, National Institute of Nutritionand Seafood Research (NIFES), P.O. Box 2029 Nordnes, N-5817,Bergen, Norway; Phone: +47 41453083; FAX: +47 55905299;email: [email protected]
models, mostly rodents, have been developed to study thedisease. However, cataracts are not unique to mammals. Theyhave also been observed in populations of wild and farmedfish, mainly Atlantic salmon (Salmo salar L) [2]. For the fishfarming industry, this constitutes a serious problem with thepotential for economic losses. Affected fish have reducedgrowth rates and increased susceptibility to secondarydiseases compared to healthy fish [3]. Numerous nutritionalfactors have been related to cataract formation in farmed fish[4], and during the last few years, advances in feedcomposition have reduced both the incidence and severity ofcataract outbreaks.
Dietary levels of the essential amino acid histidine (His)above the suggested minimum requirement for salmonids of7 g His/kg diet [5] have been found to prevent or slow theprogression of cataract development in Atlantic salmonsmolts [6-9]. The His derivative N- acetyl histidine (NAH) isa major component of the salmon lens free amino acid pool.Lens NAH concentrations directly reflect dietary His levels,and NAH has therefore been established as a lens-specificmarker for the His status of salmon [6,9]. It has been proposed
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141>Received 30 March 2009 | Accepted 5 July 2009 | Published 9 July 2009
© 2009 Molecular Vision
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that NAH may act as an osmolyte in the goldfish lens,transporting water out of the cell along the NAH gradientfollowed by immediate hydrolysis and active uptake of acetateand His back into the cell [10]. Studies with Atlantic salmonhave supported a role of NAH in lens water homeostasis,although the exact mechanism remains unknown [6].Additional possible cataract preventative functions of His andHis-related compounds include anti-oxidation [11,12], anti-inflammation [13], anti-glycation [14], and buffering capacity[15].
However, at present, it is still unclear how His preventsor mitigates cataract development in salmon, and themolecular basis of cataractogenesis in the salmon lens isunclear. Increased knowledge of these underlyingmechanisms would enable us to better advise the fish farmingindustry on how to eliminate risk factors leading to cataractdevelopment, especially in connection with the increasedinclusion of alternative feed resources in aquaculture. Thiswould not only improve fish welfare but may also increasefish production with low additional cost. Research performedin teleost fish may also contribute to our understanding ofcataract development in higher vertebrates including humans.
The aim of this study was to shed light on the mechanismsby which dietary His prevents or delays cataract developmentin Atlantic salmon. Using microarray analysis of thetranscriptome in lenses of salmon that were fed diets withdifferent His content, we screened for differentially expressedgenes in search for a model explaining cataract developmentin salmon and possible markers for early cataract diagnosis.
METHODSFish feeding experiment: The feeding experiment wasperformed at Lerang Research Station (Lerang, Norway). Theexperimental procedures were approved by and animalshandled according to the guidelines of the Norwegian StateCommission for Laboratory Animals. Atlantic salmon in theirsecond year in sea with a mean start weight of 1,662 g(n=1,834) were fed three diets containing low (L), medium(M), or high (H) levels of His (L: 9 g/kg diet; M: 13 g/kg diet;H: 17 g/kg diet) in duplicate sea net pens. The diets were basedon a commercial feed and had a similar overall composition(protein: 375 g/kg; fat: 342 g/kg; ash: 73 g/kg; moisture 83 g/kg). The trial, which was run from June to October, 2006, wasdivided into three experimental periods defined by twointermediate sampling points in July and September inaddition to start and end point sampling. At all samplingpoints, tissue was sampled and cataract status diagnosed byslit-lamp biomicroscopic inspection of both eyes. The cataractscore per lens was assessed on a scale from zero (clear lens)to four (completely clouded lens), summing up to a possiblemaximum score of eight per fish [16]. We screened fordifferences in the lens transcriptome in two selected dietarygroups, the low-His group LLL (diet L during all threeexperimental periods; sampled after the third period) and the
medium-His group MMM (diet M during all threeexperimental periods; sampled after the third period). Eachdietary group contained 11 biological replicates.Tissue sampling: The fish were anesthetized with metacaineand killed by a blow to the head. The lens was dissectedquickly after opening the cornea by an incision along thelimbus. Muscle tissue attached to the lens was removed, andthe lens was cleaned of aqueous humor by rolling it gently onbench paper. The lens was then immediately frozen in a 2 mlRNase-free microcentrifuge tube by placing the tube on dryice. Of each sampled fish, the right eye lens was used for RNAextraction while the left eye lens was used for NAH analysis.The lenses were stored at -80 °C until RNA isolation.NAH analysis: Lens NAH concentrations were analyzed byisocratic reverse phase high performance liquidchromatography (HPLC) with ultraviolet (UV) absorbance at210 nm using external standard calibration as previouslydescribed by Breck and coworkers [9].RNA purification: The samples were homogenized on day oneusing a Retsch MM 301 homogenizer (Retsch Gmbh, Haan,Germany) and were then further processed on the foursuccessive days in randomized order. The number of samplesbelonging to each group was balanced for each of the fourdays. Total RNA was extracted using TRIzol reagent(Invitrogen, Carlsbad, CA). Genomic DNA was eliminatedfrom the samples by DNase treatment (DNA-free; Ambion,Austin, TX). RNA for microarray analysis was furtherpurified using the RNeasy MinElute Cleanup Kit (Qiagen,Hilden, Germany). The amount and purity of the isolated RNAwas measured with a NanoDrop ND-1000 UV-VisSpectrophotometer (NanoDrop Technologies, Wilmington,DE). The A260/A280 ratios lay between 2.08 and 2.12 for allRNA samples. RNA quality was determined with the Agilent2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). Oneof the samples had a RNA integrity number (RIN) of 7.9, andthe others lay between 8.1 and 9.2. The isolated RNA wasstored at -80 °C.Microarray experiment: A common reference design with apool of all RNA samples as the reference was used for the two-channel microarray experiment. All samples were labeledwith Cy5, and the reference was labeled with Cy3. The RNAwas hybridized to 16K GRASP v. 2.0 arrays [17] on a TecanHS 4800™ hybridization station (Tecan Group Ltd.,Männedorf, Switzerland). The arrays were scanned with aTecan LS Reloaded scanner (Tecan Group Ltd.) and analyzedusing the Axon GenePix 5.1 software (MDS Inc., Toronto,Canada).
The raw data were filtered and normalized using J-Express Pro v.2.7 [18]. The foreground signal intensity valuesfor each channel were extracted per spot from the data files,and all empty, flagged, and control spots were filtered outbefore the data were normalized using a nonlinearnormalization method, global lowess [19]. After
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
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Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
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TAB
LE 1
. TR
AN
SCR
IPT
NA
MES
, SH
OR
T N
AM
ES, A
CC
ESSI
ON
NU
MB
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PRIM
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QU
ENC
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MPL
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AN
D FO
LD C
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NG
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PRES
SIO
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INED
BY
MIC
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ame
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pri
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by
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roar
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T–
PCR
40S
ribos
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pro
tein
S20
RPS2
0B
G93
6672
GC
AG
AC
CTT
ATC
CG
TGG
AG
CTA
TGG
TGA
TGC
GC
AG
AG
TCTT
G85
HSP
90-b
eta
HSP
90B
AF1
3511
7C
TCTG
GG
ATG
AG
CTC
CTC
AC
AC
CTT
TGA
CC
TCTT
TGA
GA
AC
AA
GA
A98
Elon
gatio
n fa
ctor
1A
AEF
1AA
AF3
2183
6C
CC
CTC
CA
GG
AC
GTT
TAC
AA
AC
AC
AC
GG
CC
CA
CA
GG
TAC
A57
Elon
gatio
n fa
ctor
1A
BEF
1AB
BG
9338
53TG
CC
CC
TCC
AG
GA
TGTC
TAC
CA
CG
GC
CC
AC
AG
GTA
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59M
etal
loth
ione
in B
MT-
BC
K99
0996
TGA
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AA
GA
AG
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GTT
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81.
5*Fa
tty a
cid
bind
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prot
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B51
1332
TTA
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GA
AG
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GC
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AA
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ATG
AA
GA
108
−2.2
−2.5*
Gam
ma
crys
talli
n M
2C
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M2
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5101
88G
GA
GA
AG
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GT
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125
−1.8
−1.8*
Epen
dym
in p
recu
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CA
0420
89TC
CA
GTT
TAG
CG
TCC
TGA
CA
GA
CA
AG
AC
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GC
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CT
104
−1.7
−2.3*
Fruc
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se B
Aldo
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A04
3730
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TGG
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TCTC
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CTC
TTC
C11
6−1.7
−1.1
Sodi
um/p
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sium
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nspo
rting
ATP
ase
subu
nit a
lpha
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recu
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A05
4630
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CTA
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GC
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A85
1.4
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Cal
pain
smal
l sub
unit
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APN
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B50
5442
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CC
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CTC
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144
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104
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101
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d-in
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ble
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bind
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bpC
A06
2835
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GA
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CC
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AG
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CC
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CC
GTT
TCTT
104
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1.1
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xire
doxi
n-6
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A06
2947
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GG
GA
TGTT
TGG
AG
GA
AC
GG
GG
CG
TAA
CTT
TGA
TGA
GA
126
−1.2
−1.1
SPA
RC
pre
curs
orSP
ARC
CA
0521
60C
CA
AG
GC
GA
TGTA
CTT
GTC
AG
GTT
CC
TGTC
CC
AC
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AG
AG
117
1.3
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fibe
r mem
bran
ein
trins
ic p
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inLI
M2
CA
0391
29C
CA
GG
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GTT
CA
CC
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AC
TTA
ATC
GC
AG
GC
ATT
CTC
TCC
147
−1.3
−1.3*
Hea
t sho
ck c
ogna
te 7
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apr
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SC71
CA
7678
16A
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TT13
81.
21.
2*
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vy su
buni
tFe
rriti
n H
CA
0528
52G
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GG
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GA
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110
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prec
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B50
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GTA
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A12
61.
21.
1
The
first
four
row
s in
the
tabl
e co
ntai
n th
e se
lect
ed re
fere
nce
gene
s tha
t are
not
diff
eren
tially
exp
ress
ed in
lens
es fr
om th
e di
ffer
ent d
ieta
ry g
roup
s. Ex
pres
sion
of
the 1
6 tra
nscr
ipts
in th
e sub
sequ
ent r
ows w
as si
gnifi
cant
ly d
iffer
ent b
etw
een
the d
ieta
ry g
roup
s whe
n an
alyz
ed b
y m
icro
arra
y an
d SA
M, b
ut o
nly
11 o
f the
tran
scrip
tsw
ere
sign
ifica
ntly
diff
eren
t whe
n an
alyz
ed b
y qR
T–PC
R a
naly
sis a
nd M
ann–
Whi
tney
test
(FC
s are
mar
ked
with
an
aste
risk
in th
e ta
ble)
.
normalization, weak spots with a foreground signal intensitybelow the sum of the background signal intensity and 1.5times the standard deviation of the background signalintensity in at least one channel were filtered out. All arrayswere compiled into a single expression profile data matrix(gene by sample) containing the log ratio of the twoforeground signal intensities. Eexpressed sequence tag (EST)clones with more than 30% missing values were removedfrom the analysis. Missing values were estimated and replacedusing the method introduced by Bø et al. [20],LSimpute_adaptive.
Correspondence analysis (CA) [21], significance analysisof microarrays (SAM) [22], and hierarchical clustering ofsamples and transcripts were performed on the sub-data sets inJ-Express. Functional annotation of the transcripts in the datasets was done using the Blast2GO platform [23]. The Gossiptool [24] integrated in Blast2GO was used for functionalenrichment analysis applying Fisher's exact test. Themicroarray experiment was designed to comply with theMinimum Information about a Microarray Experiment(MIAME) guidelines [25]. The applied protocols and finalresults were uploaded to BASE. MIAME-compliantmicroarray data were finally uploaded to the ArrayExpressdatabase (accession number: E-TABM-678).
Quantitative real-time PCR: The results of the microarrayexperiment were validated by two-step quantitative real-timepolymerase chain reaction (qRT–PCR) of selected transcriptsthat were up-regulated or down-regulated in the low-Hisgroup. Primers were designed within the coding sequences
Figure 1. Cataract scores in selected dietary groups throughout theexperimental period. The cataract score for each dietary group isgiven as the mean of the sums of the scores for both eyes, resultingin a possible maximum score of 8 (4 for each lens). Error bars showthe standard error of the mean (SEM). The number of fish per group(n) varied from 31 to 113.
using Primer3Plus [26]. Isoform-specific primers were usedto amplify sodium/potassium-transporting ATPase subunitalpha-1C (ATPA1C) [27]. We tested four potential referencegenes that had shown constant expression rates among theexperimental groups in the microarray experiment. Three ofthem have been previously used as reference genes in qRT–PCR analysis in Atlantic salmon [28]. An overview over thetarget genes and the respective PCR primers is given in Table1.
Total lens RNA (500 ng) was reverse transcribed tocDNA using TaqMan Reverse Transcription Reagents(Applied Biosystems, Foster City, CA). Each RNA samplewas reverse transcribed in triplicates. A standard curvecomposed of a six-point twofold serial dilution (1,000–31.25ng) of a pool of all RNA samples was run in triplicates tocalculate real-time PCR efficiencies for each gene. All cDNAsamples were diluted 1:4 in Milli-Q water (Millipore,Billerica, MA). Real-time PCR was performed on 384 wellplates in a reaction volume of 10 μl containing 1X LightCycler 480 SYBR Green I Master (Roche Applied Science,Basel, Switzerland), gene specific primers (0.5 μM each), and2 µl cDNA template. A melting curve analysis was applied toconfirm the amplification of the expected gene-specificproduct.
The second derivative maximum method was applied tocalculate crossing point (CP) values using the Lightcycler 480Software (Roche Applied Science). CP values were furtherconverted into quantities using gene-specific efficiencyvalues calculated from the standard curves according to thegeNorm manual [29]. Dividing the mean of the triplicatequantities for each sample by a normalization factor led tomean normalized expression (MNE) values for the particulargenes. The normalization factor was determined using thegeNorm VBA applet for Microsoft Excel version 3.4 [29]. Allfour potential reference genes tested were highly stable withgene expression stability (M) values below 0.3, and hence allfour were used to calculate the normalization factor.Statistical analysis: Differences in the lens NAH contentsbetween LLL and MMM fish were tested by t-test, anddifferences in the cataract scores between LLL and MMM fishwere tested by the Mann–Whitney test. Individual lens NAHconcentrations were correlated to cataract scores by Spearmanrank order test. The qRT–PCR data were analyzed by Mann–Whitney test, and correlation between fold change (FC) valuesobtained by microarray and qRT–PCR was tested bySpearman rank order test using GraphPad Prism version 5.01for Windows (GraphPad Software, San Diego, CA).Correlation between individual cataract scores and geneexpression values was tested by Spearman rank order testusing the Statistica data analysis software system version 7.1.(StatSoft Inc., Tulsa, OK).
RESULTSCataract scores and lens NAH concentrations: During thesecond and third experimental period, the fish developed
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
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cataracts with different severity depending on the dietary Hisregimes. Fish that were fed the low-His diet during the firstand second period had a higher cataract frequency and severitythan fish that were fed the medium- and high-His diet (Figure1) [30]. The medium-His group was selected for microarrayanalysis to avoid possible negative effects of too high Hisconcentrations in the high-His group. At the end of the trial,when samples for the microarray experiment were taken, therewere significant differences in both cataract severity (Mann–Whitney test, p=0.001) and lens NAH concentration (t-test,p<0.001) between the low-His group and the medium-Hisgroup. The mean NAH concentration was 4.4±0.8 μmol/g(mean±SEM) in the low-His group and 10.4±0.3 μmol/g inthe medium-His group. The individual single lens cataractscores and lens NAH concentrations are shown in Figure 2A.Lens NAH concentrations were significantly negativelycorrelated to the respective cataract scores (Spearman ranktest; r=-0.63, p<0.002, n=22), which is shown in Figure 2B.
Correspondence analysis plot: Global differences in lens geneexpression between the dietary groups were analyzed bymicroarray. After the pre-processing and filtering steps, thedata set contained 4,242 transcripts. Correspondence analysis(CA) [21] was applied to look for associations between thesamples and expression levels of the transcripts in the data set.Deviations from the null hypothesis (no association betweensamples and expression levels) add to the total χ2. This totalχ2 is decomposed in the CA plot shown in Figure 3 where thetwo largest dimensions, analogous to the principal
components in factor analysis, are plotted on the x- and y-axis.The LLL and MMM samples were clearly separated along the
Figure 3. Correspondence analysis plot. The principal components 1and 2, which explain the highest amounts of variance in the data set,are shown on the x- and y-axis of the plot, respectively. The samplesare colored according to the dietary groups. The low-His samples(LLL) are blue, and the medium-His samples (MMM) are dark red.The dark red and blue lines are plotted from the point of originthrough the respective group medians, which are marked by anequally colored dot. The total variance retained in the plot is16.349%, the x-axis component variance is 10.623%, and the y-axiscomponent variance is 5.726%.
Figure 2. Individual cataract scores and N-acetyl histidine (NAH) concentrations in lenses of the fish used for microarray analysis. The rightlens of the fish was used for microarray analysis, and thus the cataract scores (on a scale from 0 to 4) of the right lens are presented in thegraphs. The NAH concentrations were determined in the left lens of the same fish. A: Cataract scores and NAH concentrations for the individualsamples are shown in this graph. Under the sample names, the sample clustering (obtained by hierarchical clustering of genes and samples,see Figure 4) is shown to relate individual cataract scores and NAH concentrations to gene expression patterns (the closer the samples are inthe cluster tree, the more similar is the lens transcriptome). B: Lens NAH concentrations were significantly negatively correlated to the cataractscores of the right lens (Spearman rank test; r=−0.63, p<0.002, n=22).
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
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first principal component (PC 1), which is the dimensionexplaining the largest amount of variance in the data set. Thelines plotted from the point of origin through the groupmedians formed an angle of nearly 180°, indicating a clearseparation of the dietary groups.Significance analysis of microarrays: Significance analysis ofmicroarrays (SAM) [22] ranks the transcripts in a data setaccording to the regularized t-score that it calculates. It alsoprovides a q value, which is a measure of the statisticalsignificance of the differences in expression levels betweenthe compared groups. The q value is a false discovery rate,which states the expected number of false positives on the list.In other words, SAM ranks the transcripts according to thesignificance of the difference in expression levels between thetwo dietary groups. On top of the SAM ranking list (Appendix1) were 514 transcripts with a significant q value below 5%.Of these transcripts, 248 were up-regulated and 266 weredown-regulated in the low-His group (LLL) compared to themedium-His group (MMM). Furthermore, 145 of these 514transcripts had a highly significant q value of 0% (Table 2).Of these 145 transcripts, 59 transcripts were up-regulated and86 were down-regulated in the low-His group compared to themedium-His group. The highest FC was 2.1 for the strongestup-regulated transcript and −2.5 for the strongest down-regulated transcript.
Hierarchical clustering: Hierarchical clustering of samplesand transcripts was performed with the most significantlydifferentially expressed transcripts in the SAM top listincluding transcripts with q=0% (Figure 4). The transcripts(on the left side of the heat map) are clustered into two maingroups, transcripts up-regulated in the low-His group andtranscripts down-regulated in the low-His group. The samples(on top of the heat map) are arranged into three main clusters,representing the two dietary groups. The samples LLL2,LLL4, and LLL8 formed a main cluster together with theMMM samples with many transcripts displaying similarexpression levels in this main cluster, which is shown bysimilar colors. In Figure 2A, the sample clustering is shownin relation to individual cataract scores and lens NAHconcentrations to visualize the interactions between lens Hisstatus, cataract scores, and gene expression patterns inindividual fish of the two dietary groups. There are three mainclusters, cluster 1, cluster 2, and cluster 3. While cluster 1including samples LLL1, LLL6, LLL3, LLL11, LLL5, LLL9,LLL7, and LLL10 is relatively uniform with high cataractscores and low NAH concentrations, cluster 2 with samplesLLL2, LLL4, and LLL8 shows both high and low cataractscores and high and low NAH concentrations. In cluster 3containing all MMM samples, NAH concentrations areequally high, and cataract scores are relatively low.
Functional enrichment analysis using Blast2GO: Functionalenrichment analysis was performed using the Blast2GOplatform with the aim to see if groups of transcripts belonging
to the same functional classes were enriched among the mostsignificantly differentially expressed transcripts. The top ofthe SAM list (including transcripts with q<5%) was comparedto the complete SAM list. The complete analysis results canbe found in (Appendix 2). Among others, the functionalcategories described by the following Gene Ontology (GO)terms were enriched with a false discovery rate (FDR) of lessthan or equal to 5% (with the respective transcript names):“Cysteine-type endopeptidase activity” (Calpain smallsubunit 1, Cathepsin L precursor, Ubiquitin carboxyl-terminalhydrolase 32, Cathepsin L2 precursor, Calpain-2 catalyticsubunit precursor, Cathepsin B precursor, Calpain-2 catalyticsubunit), “Glycolysis” (Fructose-bisphosphate aldolase B,Glyceraldehyde-3-phosphate dehydrogenase, Hexokinase-2,
Figure 4. Hierarchical clustering of samples and transcripts. Thesamples are arranged in columns, and the transcripts are arranged inrows. Only the transcripts with a q-value of 0% in the SAM list wereclustered. Negative log intensity ratios are shown in green andpositive log intensity ratios are shown in red in the heat map asindicated by the color bar. The blue color represents missing values.The transcripts divide into two distinct clusters. The first clustercontains the transcripts that are up-regulated in the low-His groupcompared to the medium-His group and is marked by a red bar at theright side of the heat map. The second cluster contains the down-regulated transcripts and is marked by a green bar at the right side ofthe heat map. The samples divide into three main clusters, reflectingthe His feeding regimes. Low-His samples are clearly separated frommedium-His samples.
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
1337
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
1338
TAB
LE 2
. SA
M R
AN
KED
GEN
E LI
ST.
Ran
kA
cces
sion
Num
ber
Tra
nscr
ipt n
ame
d[i]
de[i]
Fold
Cha
nge
q-va
lue
Reg
ulat
ion
cate
gory
*1
CK
9909
96M
etal
loth
ione
in B
−7.5
57−2
.868
1.75
70
L2
CA
0621
18PR
EDIC
TED
: sim
ilar t
o PO
MT2
[Dan
io re
rio]
5.97
72.
89−1
.907
0L
3C
A05
1877
UN
KN
OW
N5.
144
2.66
−1.8
550
E4
CB
5077
22M
etal
loth
ione
in B
−5.1
19−2
.649
1.58
0E
5C
B49
3454
Lipo
calin
pre
curs
or4.
976
2.52
1−1
.666
0E
6C
B49
8358
Fatty
aci
d-bi
ndin
g pr
otei
n. in
test
inal
4.87
52.
439
−2.4
030
L7
CA
0546
59Fa
tty a
cid-
bind
ing
prot
ein.
inte
stin
al4.
766
2.38
2−2
.539
0L
8C
B49
2836
Lipo
calin
pre
curs
or4.
564
2.33
−1.6
390
L9
CA
0642
04Pr
otei
n S1
00-B
4.53
92.
293
−1.5
790
L10
CN
4425
45C
ytoc
hrom
e c
oxid
ase
subu
nit 3
−4.5
29−2
.528
1.50
40
L11
CK
9905
92M
etal
loth
ione
in B
−4.4
93−2
.447
1.54
90
L12
CB
5099
92Li
poca
lin p
recu
rsor
4.43
92.
256
−1.5
270
E13
CB
4964
07B
etai
ne a
ldeh
yde
dehy
drog
enas
e4.
406
2.22
5−1
.824
0L
14C
B51
5799
UN
KN
OW
N−4
.403
−2.3
851.
638
0L
15C
A06
3208
UN
KN
OW
N4.
387
2.19
4−1
.951
0E
16C
A76
9320
Fatty
aci
d-bi
ndin
g pr
otei
n. in
test
inal
4.36
12.
167
−2.2
470
L17
CB
4986
06Fa
tty a
cid-
bind
ing
prot
ein.
inte
stin
al4.
328
2.14
2−2
.372
0L
18C
B51
1332
Fatty
aci
d-bi
ndin
g pr
otei
n. in
test
inal
4.29
72.
119
−2.1
560
L19
CB
4921
97M
etal
loth
ione
in A
−4.2
76−2
.336
1.48
70
L20
CB
5152
13B
-cel
l lin
ker p
rote
in4.
275
2.09
8−1
.604
0L
21C
A04
6225
Met
allo
thio
nein
B−4
.218
−2.2
941.
512
0L
22C
A05
1958
Traf
ficki
ng p
rote
in p
artic
le c
ompl
ex su
buni
t 34.
213
2.07
9−1
.60
L23
CA
0514
80U
NK
NO
WN
4.2
2.06
−20
L24
CA
0443
16Ex
clud
ed (C
him
era)
4.19
62.
044
−1.4
330
L25
CB
4946
99G
amm
a cr
ysta
llin
M2
4.19
22.
028
−1.5
440
L26
CK
9904
22U
NK
NO
WN
4.17
22.
013
−1.6
690
L27
CA
0596
85U
NK
NO
WN
−4.1
63−2
.258
1.71
30
E28
CB
4986
30A
polip
opro
tein
Eb
prec
urso
r−4
.161
−2.2
251.
818
0L
29C
A05
8895
Apo
lipop
rote
in E
b pr
ecur
sor
−4.0
7−2
.195
2.11
30
E30
CA
0642
47C
D9
antig
en4.
068
1.99
8−1
.866
0L
31C
A05
3993
UN
KN
OW
N4.
062
1.98
5−1
.736
0L
32C
B49
9689
Chr
omod
omai
n-he
licas
e-D
NA
-bin
ding
pro
tein
24.
059
1.97
1−1
.74
0L
33C
A05
5129
UN
KN
OW
N4.
045
1.95
8−1
.573
0L
34C
A04
2615
SH3
dom
ain-
bind
ing
glut
amic
aci
d-ric
h-lik
e pr
otei
n4.
039
1.94
6−1
.52 8
0L
35C
B51
0889
Puta
tive
poly
pept
ide
N-a
cety
lgal
acto
sam
inyl
trans
fera
se-li
ke p
rote
in 4
4.02
21.
935
−1.4
610
L36
CA
0616
51PR
EDIC
TED
: sim
ilar t
o ca
lmod
ulin
-dep
ende
nt p
hosp
hodi
este
rase
[Dan
io re
rio]
3.96
11.
924
−1.8
10
L37
CA
0413
85Pr
oact
ivat
or p
olyp
eptid
e pr
ecur
sor
−3.8
88−2
.169
1.39
60
E38
CA
0420
89Ep
endy
min
pre
curs
or3.
868
1.91
3−1
.684
0E
39C
B51
0842
Cal
cium
-reg
ulat
ed h
eat s
tabl
e pr
otei
n 1
3.86
71.
902
−1.9
520
L40
CB
4927
48pi
gmen
t epi
thel
ium
-der
ived
fact
or [P
aral
icht
hys o
livac
eus]
>gi
|710
6331
3|gb
|A
AZ2
2324
.1| p
igm
ent e
pith
eliu
m-d
eriv
ed fa
ctor
[Par
alic
hthy
s oliv
aceu
s]3.
866
1.89
2−1
.625
0L
41C
A05
8611
Clu
ster
in p
recu
rsor
−3.8
63−2
.145
1.69
80
L42
CB
5106
15U
NK
NO
WN
3.85
21.
883
−1.4
70
L43
CA
0636
71U
NK
NO
WN
−3.8
41−2
.123
1.75
10
L44
CA
0429
30U
NK
NO
WN
3.83
21.
875
−1.6
120
L45
CA
0621
17Pr
otei
n FA
M44
B3.
795
1.86
5−1
.72
0L
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
1339
TAB
LE 2
. DA
TA C
ON
TIN
UED
Ran
kA
cces
sion
Num
ber
Tra
nscr
ipt n
ame
d[i]
de[i]
Fold
Cha
nge
q-va
lue
Reg
ulat
ion
cate
gory
*46
CN
4425
58C
ytoc
hrom
e c
oxid
ase
subu
nit 3
−3.7
45−2
.103
1.43
30
L47
CA
0431
14M
eprin
A su
buni
t alp
ha p
recu
rsor
3.74
41.
855
−1.7
380
L48
CA
0437
30Fr
ucto
se-b
isph
osph
ate
aldo
lase
B3.
741.
847
−1.6
740
L49
CB
4943
96G
lycy
lpep
tide
N-te
trade
cano
yltra
nsfe
rase
13.
717
1.83
9−1
.719
0E
50C
B49
4172
Ker
atin
. typ
e II
cyt
oske
leta
l 8−3
.716
−2.0
861.
533
0L
51C
A05
2024
UN
KN
OW
N3.
709
1.83
−1.7
960
L52
CB
5106
53Sa
lvel
inus
alp
inus
met
allo
thio
nein
B g
ene.
intro
ns 1
and
2 a
nd p
artia
l cds
−3.7
08−2
.068
1.37
60
L53
CB
5060
47Th
ymos
in b
eta-
12−3
.674
−2.0
521.
504
0L
54C
A05
2938
UN
KN
OW
N3.
663
1.82
2−1
.828
0L
55C
A05
4630
Sodi
um/p
otas
sium
-tran
spor
ting
ATP
ase
subu
nit a
lpha
-1 p
recu
rsor
−3.6
6−2
.036
1.40
90
L56
CB
5113
71G
amm
a cr
ysta
llin
M3
3.65
41.
814
−1.5
840
L57
CA
0632
07U
NK
NO
WN
3.65
31.
806
−1.7
760
L58
CA
0556
38U
NK
NO
WN
3.65
11.
799
−1.4
970
L59
CA
0444
10U
NK
NO
WN
3.65
1.79
2−1
.561
0L
60C
B49
8510
UN
KN
OW
N3.
644
1.78
5−1
.652
0L
61C
B51
0188
Gam
ma
crys
talli
n M
23.
643
1.77
8−1
.825
0L
62C
B51
1962
Salm
o sa
lar T
NF-
alph
a 2
gene
. com
plet
e cd
s3.
613
1.77
−1.3
920
L63
CN
4425
25A
TP sy
ntha
se a
cha
in−3
.603
−2.0
21.
298
0L
64C
B51
2365
UN
KN
OW
N3.
61.
764
−1.4
510
E65
CA
0479
79U
NK
NO
WN
−3.5
99−2
.006
1.48
20
L66
CB
5088
72G
DP-
L-fu
cose
synt
heta
se−3
.584
−1.9
921.
388
0L
67C
A05
6904
UN
KN
OW
N3.
573
1.75
7−1
.75
0L
68C
K99
0888
UN
KN
OW
N−3
.567
−1.9
81.
234
0L
69C
A05
2962
Pent
raxi
n fu
sion
pro
tein
pre
curs
or3.
567
1.75
−1.6
390
L70
CA
0623
71U
NK
NO
WN
3.56
61.
743
−1.6
220
L71
CB
5178
93U
NK
NO
WN
−3.5
59−1
.967
1.65
70
L72
CB
5145
28A
nnex
in A
2-A
−3.5
43−1
.956
1.43
0L
73C
B49
3750
Thym
osin
bet
a-12
−3.5
41−1
.944
1.53
0L
74C
B50
5442
Cal
pain
smal
l sub
unit
1−3
.541
−1.9
321.
395
0L
75C
B50
2127
UN
KN
OW
N3.
539
1.73
8−1
.836
0L
76C
A03
9176
Gam
ma
crys
talli
n M
23.
538
1.73
2−1
.321
0L
77C
B51
1903
Unc
hara
cter
ized
pro
tein
C1o
rf74
hom
olog
3.53
51.
725
−1.6
820
L78
CN
4425
36C
ytoc
hrom
e c
oxid
ase
subu
nit 3
−3.5
34−1
.921
1.3
0L
79C
A06
3802
UN
KN
OW
N3.
514
1.71
9−1
.455
0L
80C
A04
7126
Gly
cera
ldeh
yde-
3-ph
osph
ate
dehy
drog
enas
e−3
.499
−1.9
111.
378
0L
81C
A05
1479
UN
KN
OW
N3.
471.
714
−1.9
280
L82
CA
0507
51A
spar
agin
yl-tR
NA
synt
heta
se. c
ytop
lasm
ic−3
.47
−1.8
991.
390
L83
CA
0612
52Pl
ecks
trin
hom
olog
y-lik
e do
mai
n fa
mily
A m
embe
r 13.
457
1.70
8−1
.62
0L
84C
B50
2503
Cat
heps
in L
pre
curs
or3.
453
1.70
2−1
.306
0L
85C
B50
9531
Clu
ster
in p
recu
rsor
−3.4
47−1
.89
1.62
60
L86
CA
0578
24A
polip
opro
tein
Eb
prec
urso
r−3
.436
−1.8
81.
626
0E
87C
A05
9732
Onc
orhy
nchu
s myk
iss S
YPG
1 (S
YPG
1). P
HF1
(PH
F1).
and
RG
L2 (R
GL2
) gen
es.
com
plet
e cd
s; D
Nas
eII p
seud
ogen
e. c
ompl
ete
sequ
ence
; LG
N-li
ke. P
BX
2 (P
BX
2).
NO
TCH
-like
. TA
P1 (T
AP1
). an
d B
RD
2 (B
RD
2) g
enes
. com
plet
e cd
s; a
nd M
HC
II-a
lpha
and
Raf
tlin-
like
pseu
doge
nes.
com
plet
e se
quen
ce
3.42
31.
697
−1.7
160
L
88C
B51
3063
Perf
orin
-1 p
recu
rsor
3.41
71.
692
−1.4
630
L89
CA
7687
41U
NK
NO
WN
−3.4
13−1
.871
1.35
70
L90
CK
9907
4160
S ac
idic
ribo
som
al p
rote
in P
13.
398
1.68
7−1
.421
0L
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
1340
TAB
LE 2
. DA
TA C
ON
TIN
UED
.
Ran
kA
cces
sion
Num
ber
Tra
nscr
ipt n
ame
d[i]
de[i]
Fold
Cha
nge
q-va
lue
Reg
ulat
ion
cate
gory
*91
CB
5121
34M
yosi
n lig
ht p
olyp
eptid
e 6
−3.3
88−1
.863
1.42
30
E92
CB
4984
94G
amm
a cr
ysta
llin
M2
3.36
31.
681
−1.3
450
L93
CB
5024
83Fr
ucto
se-b
isph
osph
ate
aldo
lase
B3.
358
1.67
6−1
.485
0L
94C
A04
7466
UN
KN
OW
N3.
344
1.67
1−1
.338
0L
95C
B49
6999
UN
KN
OW
N−3
.34
−1.8
541.
273
0L
96C
A06
0333
Hyp
oxan
thin
e-gu
anin
e ph
osph
orib
osyl
trans
fera
se3.
339
1.66
6−1
.267
0L
97C
A06
2021
UN
KN
OW
N−3
.323
−1.8
451.
348
0L
98C
A76
8027
Ubi
quiti
n ca
rbox
yl-te
rmin
al h
ydro
lase
32
3.32
11.
661
−1.4
360
L99
CA
0632
61H
exok
inas
e-2
3.31
61.
656
−1.6
330
L10
0C
N44
2552
Cyt
ochr
ome
c ox
idas
e su
buni
t 3−3
.312
−1.8
371.
334
0L
101
CA
0429
61Eu
kary
otic
pep
tide
chai
n re
leas
e fa
ctor
subu
nit 1
−3.3
09−1
.829
1.34
50
L10
2C
A05
7781
Nas
cent
pol
ypep
tide-
asso
ciat
ed c
ompl
ex su
buni
t alp
ha3.
308
1.65
1−1
.241
0L
103
CA
0456
38U
biqu
itin-
conj
ugat
ing
enzy
me
E2 D
43.
304
1.64
6−1
.39
0L
104
CA
0528
00TH
O c
ompl
ex su
buni
t 13.
285
1.64
1−1
.274
0L
105
CB
5116
09C
athe
psin
L p
recu
rsor
−3.2
79−1
.821
1.36
70
L10
6C
B51
1219
Gam
ma
crys
talli
n M
23.
279
1.63
6−1
.504
0E
107
CK
9907
61C
ytoc
hrom
e b
−3.2
75−1
.813
1.38
70
L10
8C
A05
6981
UN
KN
OW
N3.
274
1.63
1−1
.37
0E
109
CA
0635
26O
ncor
hync
hus m
ykis
s G-p
rote
in (P
-ras
) mR
NA
. com
plet
e cd
s3.
263
1.62
7−1
.681
0L
110
CN
4424
97C
ytoc
hrom
e c
oxid
ase
subu
nit 3
−3.2
59−1
.805
1.40
30
L11
1C
A05
1104
Salm
o sa
lar T
NF-
alph
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250
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Excl
uded
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mer
a)−3
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curs
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cium
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Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
1341
TAB
LE 2
. DA
TA C
ON
TIN
UED
.
Ran
kA
cces
sion
Num
ber
Tra
nscr
ipt n
ame
d[i]
de[i]
Fold
Cha
nge
q-va
lue
Reg
ulat
ion
cate
gory
*13
6C
A03
9269
UN
KN
OW
N3.
094
1.57
6−1
.282
0L
137
CK
9903
81B
eta
crys
talli
n B
33.
092
1.57
2−1
.312
0L
138
CK
9905
33K
erat
in. t
ype
II c
ytos
kele
tal 8
−3.0
77−1
.706
1.61
90
L13
9C
A05
2374
UN
KN
OW
N3.
071
1.56
8−1
.41
0L
140
CA
0634
99U
NK
NO
WN
3.05
51.
564
−1.3
270
L14
1C
A04
3660
Nuc
lear
rece
ptor
0B
2−3
.044
−1.7
011.
378
0E
142
CA
0641
48U
NK
NO
WN
−3.0
38−1
.696
1.27
10
L14
3C
B49
4413
UN
KN
OW
N−3
.009
−1.6
91.
345
0L
144
CB
4989
81R
AB
3A-in
tera
ctin
g pr
otei
n3.
003
1.56
1−1
.661
0L
145
CA
0462
17U
NK
NO
WN
−3.0
02−1
.685
1.35
70
L
The
trans
crip
ts sh
own
are
thos
e w
ith a
q-v
alue
of 0
% w
ith th
e m
ost s
igni
fican
tly d
iffer
entia
lly e
xpre
ssed
tran
scrip
ts o
n to
p of
the
list.
The
com
plet
e lis
t is g
iven
inA
ppen
dix
1. A
bbre
viat
ions
use
d in
the
tabl
e he
ader
are
: d[i]
, SA
M s
core
for a
tran
scrip
t i; d
e[i],
exp
ecte
d SA
M s
core
for a
tran
scrip
t i. *
The
term
"R
egul
atio
nca
tego
ry" i
n th
e hea
der o
f the
last
colu
mn
refe
rs to
a ca
tego
rizat
ion
of th
e tra
nscr
ipts
det
erm
ined
by
appe
aran
ce o
f the
gra
phs r
esul
ting
from
corr
elat
ion
of ex
pres
sion
leve
ls to
indi
vidu
al c
atar
act s
core
s (se
e R
esul
ts se
ctio
n). T
he tw
o ca
tego
ries a
re n
amed
E (“
early
” re
gula
ted
trans
crip
ts),
and
L (“
late
” re
gula
ted
trans
crip
ts).
Triose phosphate isomerase), and “Lipid metabolic process”(Lipocalin precursor, Clusterin precursor, Sodium/potassium-transporting ATPase subunit alpha-1 precursor,Peroxiredoxin-6, Proactivator polypeptide precursor, Fattyacid binding protein 3 (FABP3), Phospholipid hydroperoxideglutathione peroxidase, mitochondrial precursor, Triosephosphate isomerase, Acyl-CoA-binding protein,Prostaglandin E synthase 3, Diacylglycerol O-acyltransferase2).Correlation of gene expression to cataract score and lensNAH concentrations: In the microarray experiment, westatistically compared samples from different dietary groups.To further elaborate the results of the microarray experiment,we correlated individual gene expression data of the 145highly significantly differentially expressed transcripts(q=0% in the SAM top list) to the cataract score and the NAHconcentration of the respective lens. The expression of mostof the transcripts (99%) was significantly correlated to thecataract score (Spearman rank test; p<0.05, n=22). Similarly,expression of 94% of the transcripts was significantlycorrelated to the lens NAH concentration (Spearman rank test;p<0.05, n=22). According to their expression pattern relativeto the cataract score, the transcripts could roughly be dividedinto two regulation categories, “early” regulated and “late”regulated transcripts. To illustrate the observed patterns,Figure 5 shows graphs for SPARC precursor (SPARC),metallothionein B (MT-B), ependymin (EPN), and fatty acidbinding protein 2 (FABP2).
For the “early” regulated transcripts, the expressionlevels changed continuously from lenses with cataract score0 to the highest observed cataract score, which was 3. Todistinguish between “early” and “late” regulation for atranscript, we used the difference between the mean logintensity ratios of the lenses that scored 0 and the lenses thatscored 1. For “early” regulated transcripts, we defined thisdifference to be 0.2 or greater. “Early” regulated transcriptshad either consistently increasing (Figure 5A) or decreasing(Figure 5C) expression levels, or had a maximum in lenseswith cataract score 1 and decreasing expression levels at thehigher cataract scores (data not shown). In contrast, for the“late” regulated transcripts, there were no apparentdifferences in expression levels between lenses with a scoreof 0 and lenses with a score of 1 (the differences in logintensity ratios between the mean of the lenses with score 0and the mean of the lenses with score 1 were less than 0.2).With more severe cataracts, i.e., higher cataract scores, theexpression levels increased (Figure 5B) or decreased (Figure5D). Appendix 1 and Table 2 summarize which type ofregulation category the transcripts with q=0% in the SAM toplist could be assigned to. The majority of the transcripts (88%)were found to be “late” regulated.Validation: From the transcripts that were significantly up-regulated or down-regulated (q<5%) in the low-His group
when compared to the medium-His group in the microarrayexperiment, we selected sixteen EST clones for qRT–PCRvalidation. Eleven of these sixteen transcripts weresignificantly differentially expressed between the two dietarygroups when tested by qRT–PCR and Mann–Whitney test,thereby confirming the microarray results. The FC valuesobtained by microarray and qRT–PCR analysis are listed inTable 1. The FC values of the qRT–PCR results werecalculated based on the median of the MNE values of thesamples in both dietary groups. There was a significantcorrelation between the FC values obtained by microarray andqRT–PCR analysis (Spearman rank test; r=0.89, p<0.0001,n=16; Figure 6).
DISCUSSIONThe occurrence of cataracts in Atlantic salmon is related todietary histidine: The present feeding experiment showed thatadult Atlantic salmon in sea water that were fed a low-His dietduring the first experimental period from June to July and/orthe second period from July to September developed severecataracts, appearing mainly after the second period (Figure 1).However, the levels of dietary His did not affect the growth
Figure 5. Examples of transcripts with different expression patternsrelated to cataract score. For four selected significantly differentiallyexpressed transcripts, the log intensity ratios are plotted against thecataract score of the respective sample, not taking into account whichdietary group the samples belong to. For a certain transcript, if thedifference between the mean log intensity ratios of the lenses with ascore of 0 and the lenses with a score of 1 was 0.2 or greater, thistranscript was classified as “early” regulated. If this difference wasless than 0.2, the transcript was classified as “late” regulated. A:SPARC precursor (SPARC; CA052160) was chosen as an examplefor “early” up-regulated transcripts. B: Metallothionein B (MT-B;CK990996) was chosen as an example of “late” up-regulatedtranscripts. C: Ependymin (EPN; CA042089) was chosen as anexample of “early” down-regulated transcripts. D: Fatty acid bindingprotein 2 (FABP2; CA054659) was chosen as an example of “late”down-regulated transcripts.
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
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of the fish in the different feeding groups during the trial[30]. Since there were no other known variables in this feedingexperiment, the differences in cataract development and geneexpression observed between the dietary groups are assumedto be solely due to dietary His feeding regimes. Thisassumption was supported by the concentration differences ofthe His derivative NAH in the lenses (Figure 2A), theconcentration of imidazoles in muscle tissue [30], and thestrong negative correlation between individual lens NAHconcentrations and cataract scores (Figure 2B). A similar His-related cataract development was reported in younger Atlanticsalmon smolt after sea transfer [9]. The current His minimumrequirement for Atlantic salmon is estimated to be 7 g/kg diet[5]. All experimental diets contained more than 7 g/kg diet.Even so, the incidences of cataract observed during this trialstrongly indicate that the current theoretical His minimumrequirement level is not sufficient to prevent development ofcataracts in adult Atlantic salmon in their second year in seawater.Methodological considerations on the microarrayexperiment: The present microarray study was undertaken toexplore molecular events connected to the observed dietaryHis-related cataract development in Atlantic salmon.Interpretation of the microarray data by correspondenceanalysis, SAM, and hierarchical clustering revealed cleardifferences in the lens transcriptome between the compareddietary groups. Both by CA of the whole data set (Figure 3)and hierarchical clustering of the significantly differentiallyexpressed transcripts (Figure 4), the three samples LLL2,LLL4, and LLL8 were situated close to the MMM samples,showing that this relation is not only restricted to the highlysignificantly differentially expressed transcripts. In these
Figure 6. Correlation between fold change values obtained bymicroarray analysis and qRT–PCR for 16 selected transcripts. Foldchange (FC) values obtained by microarray analysis weresignificantly correlated to those obtained by qRT–PCR (Spearmanrank test; r=0.89, p<0.0001, n=16).
three samples, the expression patterns of the significantlydifferentially expressed transcripts were similar (Figure 4),but the lens NAH concentrations and cataract scores weredifferent (Figure 2A). This might indicate that geneexpression is also influenced by individual predisposition.
Our findings clearly confirm that changed geneexpression is involved in the process of His-related cataractdevelopment. Although the differences in the expressionlevels, given as fold change (FC) values, were generally low,a considerable number of transcripts were found to besignificantly differentially expressed. The main cataractoutbreak was registered in the period from July to September,while lenses for the microarray experiment were sampled inOctober. Some of the observed differences in gene expressionlevels might thus reflect secondary and compensatoryreactions to pathophysiologic changes in the lenses over alonger period of time rather than processes directly involvedin cataract development.
In contrast to the human genome and to model specieslike the mouse and rat, the annotation of the salmon genomeis rather poor. The salmonid microarray used in the study isbased on EST clones, and the annotation is mainly based onsequence similarities to other species [17]. Only fewtranscripts on the array are characterized in salmonids. TheSAM list contained about 25% uncharacterized EST clones(named UNKNOWN in Appendix 1 and Table 2) while 75%had been identified and were annotated with a transcript name.Using Blast2GO, approximately 67% of these identifiedtranscripts (about 50% of all transcripts in the SAM list) werefunctionally annotated with at least one GO term. This leftabout 25% of the transcripts in the SAM list identified butwithout functional annotation. These 25% were not includedin the functional enrichment analysis. An example for this isthe intestinal type fatty acid binding protein (FABP2), whichwas not included in the functional category “Lipid metabolicprocess”, although it is known to be involved in lipidmetabolic processes. Thus, the functional enrichment analysisresults do not give a complete view of the functionalcategories enriched in the data set.Selected differentially expressed transcripts and theirpossible role in His-related cataract: The first transcript inthe SAM list (Table 2) is an EST clone coding formetallothionein B (MT-B). Metallothionein A (MT-A) isnumber 19 in the list. Both isoforms are up-regulated in thelow-His group. Metallothioneins are multifunctional stressproteins induced by a variety of stresses. They can take partin the detoxification of heavy metals, the regulation of zinclevels in the cell, and the protection against oxidative stress[31]. While heavy metals such as cadmium [32] and lead[33] have been linked to cataract development, oxidativestress is generally one of the major factors associated withcataracts [34,35]. Direct evidence of the involvement ofmetallothioneins in cataract-related processes has been given
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
1343
by the study of Kantorow et al. [36], who detected increasedlevels of metallothionein IIA transcripts in human age-relatedcataractous lenses relative to clear lenses by RT–PCRdifferential display. Hawse et al. [37] showed later thatmetallothionein IIA defended lens epithelial cells againstoxidative stress induced by cadmium and tertiary butylhydroperoxide.
We hypothesized that oxidative stress related to cataracttriggered the increased expression of metallothioneins in thelow-His group and assumed that other antioxidant genespresent in the data set might be regulated similarly to MT-Band MT-A. Other transcripts with an antioxidant function thatare present in the SAM list with q<5% were peroxiredoxin-6(PRDX6), phospholipid hydroperoxide glutathioneperoxidase (GPX4), selenoprotein Pb precursor, andthioredoxin (TRX; Appendix 1 and Table 2). Only GPX4 wasup-regulated. Although significant with fold changes around1.2, none of the above mentioned antioxidant genes were asclearly regulated as the metallothionein transcripts. In contrastto our first hypothesis, down-regulation of antioxidant genescould lead to decreased antioxidant capacity and increasedoxidative stress, which might in turn lead to cataractdevelopment. This effect might have been observed in a studyon the impact of elevated water oxygen levels on cataractformation in smolting salmon [38]. The authors found trendsof down-regulation of the antioxidant genes Cu/Zn superoxidedismutase (Cu/Zn SOD) and glutathione S-transferase (GST)in lenses of the treatment groups that developed more severecataracts. Despite the suggested antioxidative properties ofimidazoles, we cannot conclude which role oxidative stressmight play in the present His-related cataracts observed inAtlantic salmon. More confirmative work has to be done toaddress this question. It also has to be considered that theexpression of the stress-responsive antioxidant genes is oftenrapidly regulated upon the inducing stress. The fact that thedevelopment of cataracts in our study probably was more likea chronic stress to the lens further complicates theinterpretation of the results.
One of the functional categories of transcripts revealedby functional enrichment analysis was related to lipidmetabolism. Among the strongest down-regulated transcriptsin the low-His group were lipocalin precursor (presumablycoding for a lipocalin-type prostaglandin-D synthase, Ptgds)and the intestinal type fatty acid binding protein (FABP2).Ptgds is one of the most abundantly expressed transcripts inhuman [39] and zebrafish (Danio rerio) [40] lenses. Ptgds hastwo functions, the synthesis of the prostaglandin PGD2 inseveral tissues and binding to a variety of lipophilic ligandslike biliverdin, bilirubin, retinaldehyde, and retinoic acid[41]. PGD2 is the major prostaglandin in the central nervoussystem and is involved in numerous physiologic functions. Inthe eye, PGD2 lowers the intraocular pressure and triggersinflammatory effects on the conjunctiva [42]. Cataractformation in lens epithelial cells is preceded by programmed
cell death (apoptosis) [43]. Ptgds has been shown to protectneurons and oligodendrocytes against apoptosis in a mousemodel of a demyelinating disease [44], but also a pro-apoptotic function has been reported [45]. The exact role ofPtgds in the cataractous salmon lens remains to be identified,but it might be involved in lens compensation mechanismsand repair.
FABP2 belongs to the fatty acid binding proteins. Themembers of this protein family are generally thought tofacilitate lipid transport in the cell but may also be involvedin lipid signaling pathways [46]. Fatty acid binding proteinsubtypes are expressed in numerous tissues. The expressionof more than one subtype in a cell type indicates specificfunctions of the subtypes. Our data indicates the expression ofFABP2,FABP3,FABP4, and FABP7 in the salmon lens(Appendix 1). In bovine, human, and rat lenses, the expressionof the epidermal type fatty acid binding protein (FABP5) hasbeen demonstrated [47,48]. It has recently been shown thatFABP2 stimulates mitochondrial β-oxidation and affects thecellular cholesterol transport in human intestine epithelialcells [49]. Given a similar function in the salmon lens, thedecreased expression of FABP2 would enhance cholesterolabsorption and decrease fatty acid oxidation, leading todecreased energy production in the lenses of fish in the low-His group.
In contrast to Ptgds and FABP2, apolipoprotein Eb (ApoEb) and clusterin precursor were up-regulated in the low-Hisgroup. Apo Eb serves as an extracellular transport protein forcholesterol and other lipids via binding to low densitylipoprotein (LDL) receptors on the target cell surface, but alsofunctions in repair response to tissue injury,immunoregulation, and modulation of cell growth anddifferentiation have been reported [50]. Expression of Apo Ebis activated by peroxisome proliferator-activated receptor γ(PPARγ) [51]. Clusterin is associated with high densitylipoprotein (HDL) in the plasma and is also calledapolipoprotein J [52,53]. Clusterin is up-regulated indevelopmental remodeling, apoptotic states inneurodegeneration, response to injuries, and other stresses andinteracts with a variety of molecules [54]. Its expression isregulated by the heat shock transcription factor, HSF-1, andclusterin was proposed as an extracellular chaperone [55]. Atruncated form acts as a death signal in the nucleus [56] whilethe normal secreted form promotes cell survival [57,58]. Inthe cataractous salmon lens, Apo Eb and clusterin mightpossibly play a role in tissue repair, similar to what is observedin nerve tissue.
However, a pure lipid transporting role of this group oftranscripts, which maintain the cellular lipid homeostasis, issupported by the fact that the water temperature at the researchstation rose from 10 °C to 20 °C from June to July. As anadaptation to the environmental temperature changes, themembrane lipid composition in poikilotherms is changed to
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
1344
maintain fluidity and thus proper function [59]. A rapid andstrict regulation of the membrane lipid composition in thesalmon lens is assumed to be essential to keep the crystallinelens clear. A temperature-induced change in expressionlevels, however, would be expected to have declined afterthree months. Nevertheless, there is some evidence in theliterature for the importance of lipids in relation to cataracts.Atlantic salmon that were fed diets based on plant lipidsources in a full life cycle feeding experiment seemed to bemore prone to cataract development than fish that were feddiets based on conventional lipids of marine origin [60].Similarly, age-related cataracts in humans have been relatedto dietary fat intake. Elevated intakes of 18:2n-6 (linoleic acid)and 18:3n-3 (α-linolenic acid) may increase the risk forcataract [61], while higher intakes of n-3 polyunsaturated fattyacids (PUFA) from fatty fish consumption may contribute tocataract prevention [62]. The study of lipid-related processesin the Atlantic salmon lens will be important to resolveprocesses leading to cataract development, especially seen inthe light of the increasing importance of alternativesustainable lipid sources like plant oils in fish feed.
Glucose is the main energy source for the lens [1]. Severaltranscripts involved in carbohydrate metabolism weredifferentially regulated in the low-His group: fructose-bisphosphate aldolase B (down), glyceraldehyde-3-phosphatedehydrogenase (up), hexokinase-2 (down), and triosephosphate isomerase (up). The encoded proteins are all partof the glycolytic pathway, and three of them can also catalyzethe reverse reaction in gluconeogenesis. The fourth,hexokinase-2, catalyzes the first step in the glycolyticpathway, and its down-regulation thus indicates a decrease inthe energy-producing glycolytic activity in the low-His group.A central enzyme in the non-oxidative pentose phosphateshunt, transaldolase, was also down-regulated in the low-Hisgroup. The pentose phosphate shunt is the main source forreduced coenzyme, nicotinamide adenine dinucleotidephosphate (NADPH), which is needed for lipid biosynthesisand to regenerate oxidized glutathione, the major antioxidantin the lens [63,64]. The lack of reduced glutathione mightcritically impair the redox state of the lens cells and thuspromote oxidative damage leading to cataract.
One transcript up-regulated in the low-His group was anEST clone encoding the α-1 subunit of Na+/K+ ATPase. Na+/K+ ATPase plays an important role in the regulation of the Na+
and K+ ion balance and thus the osmotic balance in cells,which is especially important to maintain transparency in thelens. Different Na+/K+ ATPase subunit isoforms are expressedin lenses of different species, and the isoform expressionpattern is also specific for cell type and localization in the lens[65]. There are at least five isoforms of the α subunit inAtlantic salmon [66]. In several studies, Na+/K+ ATPase hasbeen found to be involved in cataract-related processes. Itsactivity was impaired by H2O2-induced oxidative stress incultured bovine lenses [67] and by the lipid peroxidation
product, 4-hydroxynonenal [68]. In cataractous human lenses,the Na+/K+ ATPase activity was found to be decreased [69],and inhibition of the Na+/K+ ATPase activity has been shownto increase opacity in cultured rat lenses [70]. Disturbance ofthe ion balance by the ionophore, amphotericin B, led toincreased Na+/K+ ATPase α-2 expression in porcine lensepithelium [71]. The upregulation of Na+/K+ ATPase α-1 seenin our study might be a sign of disturbed lens ion balance inthe low-His group. NAH has been suggested as a majorosmolyte in the fish lens [7,10], and the low concentrations ofNAH in the low-His group (Figure 2A) suggest a lowerpreparedness to osmotic challenges and impacts on otheractors in osmoregulation. The activity of Na+/K+ ATPase isalso very energy-demanding, and the increased expressionmight be an attempt to compensate for decreased enzymaticactivity caused by the lack of energy, resulting from theindicated decrease in glycolytic activity in the low-His group.
Several proteases were up-regulated in the low-Hisgroup, the regulatory and catalytic subunits of calpain andcathepsin L and B. Calpain is a calcium-dependent neutralprotease that plays a role in the process of apoptosis [72].Apoptosis has been related to cataract [43], and calpain hasbeen found to be activated in various types of cataracts inrodents [73-75]. Possible calpain substrates in the lens are β-crystallins [76] and aquaporin 0, the main water channel in thelens [77]. Cathepsins are lysosomal cysteine proteases thatparticipate in the degradation of structural proteins in the post-mortem muscle of salmon [78]. Cathepsins also seem to beinvolved in cataract-related processes since cathepsin Aactivity in the aqueous humor of cataract patients was foundto be increased when compared to the aqueous humor ofpatients with other ocular diseases [79]. These proteases mostprobably play roles in secondary repair processes in thecataractous salmon lenses.Potential early cataractogenesis markers: In addition toconventional microarray data analysis, we explored our datafurther by correlating individual gene expression valuesdirectly to the respective cataract scores and lens NAHconcentrations without considering the dietary background.The results of this approach strengthen our findings andconfirm the role of lens NAH as a marker for dietary His levelsand the impact of dietary His regimes on lens gene expression.According to their expression pattern relative to cataractscore, the transcripts could roughly be divided into tworegulation categories, “early” regulated and “late” regulatedtranscripts (Figure 5). “Early” regulated transcripts areprobably more directly involved in or affected by cataractdevelopment and might be used as biological markers for earlycataract detection in future experiments. “Late” regulatedtranscripts might be induced or repressed by secondarychanges and compensatory mechanisms in the cataractouslens. One of the “early” up-regulated transcripts is SPARC,which is also among the most abundant transcripts in thezebrafish lens [40]. SPARC is an extracellular matrix-
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
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associated glycoprotein with multiple functions in tissuedevelopment and remodeling, cell turnover, and tissue repair[80,81]. Kantorow and coworkers [82] detected increasedlevels of SPARC transcripts in cataractous lenses whencompared to normal lenses, and the same was shown on theprotein level [83]. SPARC was also increased in cataractouslenses when compared to normal lenses as revealed by amicroarray study [84]. Deletion of SPARC in mice leads tocataract development [85,86]. Emerson and coworkers [87]proposed a chaperone-like activity for SPARC.
One of the “early” down-regulated transcripts isependymin. Ependymin is a glycoprotein and a majorcomponent of the brain extracellular fluid of goldfish(Carassius aureatus) and is involved in neuroplasticity,memory and learning, and tissue regeneration [88]. Itsexpression is induced by cold in zebrafish and carp (Cyprinuscarpio) brain [89]. A trypsin-derived peptide fragment ofependymin activates the transcription factor, AP-1, in mouseneuroblastoma cells [90] and increases the expression of theantioxidant enzymes superoxide dismutase (SOD), catalase(CAT), and glutathione peroxidase (GPX) in rat primarycortical cultures [91]. As mentioned earlier, trends of down-regulation of the antioxidant genes, Cu/Zn SOD and GST,were observed in smolting salmon that were developingcataracts after exposure to elevated water oxygen levels [38].Further dedicated experiments must be undertaken tostrengthen and verify the indications we obtained by relatinggene expression levels directly to cataract scores, and toestablish the proposed transcripts (or correspondingfunctional analyses) as markers for early cataractogenesis.
Dietary histidine regimes affected cataract formation inadult Atlantic salmon and lens gene expression. Among thedifferentially expressed transcripts found in this study weremetallothionein A and B as well as transcripts involved in lipidmetabolism, carbohydrate metabolism, regulation of ionhomeostasis, and protein degradation. In addition to providingnew directions for cataract research in Atlantic salmon, theresults of this genome-wide transcription analysis allowed usto suggest selected transcripts as possible biological markersfor early cataract diagnosis in Atlantic salmon and with apotential for use in mammalian experiments.
ACKNOWLEDGMENTSSkretting ARC is thanked for providing the research facilitiesat Lerang, and the authors like to thank the staff for rearingthe fish and their help with the samplings. Ben F. Koop andWillie Davidson of the Consortium of Genome Research onAll Salmon Project at the University of Victoria, Canada(cGRASP) are acknowledged for providing the microarrays.Atle van Beelen Granlund of the Norwegian MicroarrayConsortium (NMC) is thanked for doing the microarrayhybridizations at the national technology platform inTrondheim, supported by the Functional Genomics Program(FUGE) in the Norwegian Research Council (NRC). Thisresearch was supported by the NRC Grant 168435/S40.
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Appendix 1. SAM complete ranked gene list.
To access the data, click or select the words “Appendix1.” This will initiate the download of a compressed (pdf)archive that contains the file. The most significantlydifferentially expressed transcripts are on top of the list.Transcripts with a q-value under 5% are regarded significantlydifferentially expressed between the two dietary groups.Abbreviations used in the table header are: d[i], SAM score
for a transcript i; de[i], expected SAM score for a transcript i.* The term "Regulation category" in the header of the lastcolumn refers to a categorization of the transcripts determinedby appearance of the graphs resulting from correlation ofexpression levels to individual cataract scores (see Resultssection). The two categories are named E (“early” regulatedtranscripts), and L (“late” regulated transcripts).
Appendix 2. Functional enrichment analysis.
To access the data, click or select the words “Appendix2.” This will initiate the download of a Microsoft Excelworksheet (xls) file. Functional annotations for the transcriptsin the data set were assigned using the Blast2GO software.We compared transcripts with q-values less than 5% in theSAM top list to the complete SAM list to find functionalcategories overrepresented among the significantly
differentially expressed transcripts. Listed are functionalcategories enriched with a false discovery rate (FDR) of 0.5or below. In the table headings, “Test” stands for the testedSAM top list with q-values of less than 5%, and “Ref” standsfor the remaining transcripts in the SAM list. FWER: familywise error rate.
Molecular Vision 2009; 15:1332-1350 <http://www.molvis.org/molvis/v15/a141> © 2009 Molecular Vision
The print version of this article was created on 8 July 2009. This reflects all typographical corrections and errata to the articlethrough that date. Details of any changes may be found in the online version of the article.
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