Functional Genomic Analysis of Variation on Beef Tenderness Induced by Acute Stress in Angus ...

12 Pages·2014·1.99 MB·English

HindawiPublishingCorporation
ComparativeandFunctionalGenomics
Volume2012,ArticleID756284,11pages
doi:10.1155/2012/756284
Research Article
Functional Genomic Analysis of
Variation on Beef Tenderness Induced by
Acute Stress in Angus Cattle
ChunpingZhao,1,2FeiTian,2YingYu,2,3JuanLuo,2ApratimMitra,2FeiZhan,2YaliHou,2
GeorgeLiu,4LinsenZan,1M.ScottUpdike,2,5andJiuzhouSong2
1CollegeofAnimalScienceandTechnology,NorthwestA&FUniversity,Yangling,Shaanxi712100,China
2DepartmentofAnimal&AvianSciences,UniversityofMaryland,CollegePark,MD20742,USA
3DepartmentofAnimalBreedingandGenetics,CollegeofAnimalSciences,ChinaAgriculturalUniversity,Beijing100193,China
4BovineFunctionalGenomicLaboratory,AnimalandNaturalResourcesInstitute,USDA-AgriculturalResearchService,
Beltsville,MD20705,USA
5StanderdsDivision,USDA-AgriculturalMarketingService-NationalOrganicProgram,Washington,DC20250,USA
CorrespondenceshouldbeaddressedtoLinsenZan,[email protected],[email protected]
Received29November2011;Accepted19January2012
AcademicEditor:GiuliaPiaggio
Copyright©2012ChunpingZhaoetal. This is an open access article distributed under the Creative Commons Attribution
License,whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkisproperly
cited.
Beefisoneoftheleadingsourcesofprotein,Bvitamins,iron,andzincinhumanfood.Beefpalatabilityisbasedonthreegeneral
criteria:tenderness,juiciness,andflavor,ofwhichtendernessisthoughttobethemostimportantfactor.Inthisstudy,wefound
thatbeeftenderness,measuredbytheWarner-Bratzlershearforce(WBSF),wasdramaticallyincreasedbyacutestress.Microarray
analysisandqPCRidentifiedavarietyofgenesthatweredifferentiallyexpressed.Pathwayanalysisshowedthatthesegeneswere
involvedinimmuneresponseandregulationofmetabolismprocessasactivatorsorrepressors.Furtheranalysisidentifiedthat
thesechangesmayberelatedwithCpGmethylationofseveralgenes.Therefore,theresultsfromthisstudyprovideanenhanced
understandingofthemechanismsthatgeneticandepigeneticregulationscontrolmeatqualityandbeeftenderness.
1.Introduction [12–20]. High-throughput transcriptomics and proteomics
werealsousedtoexplorethemechanismofcontrollingbeef
Beef is a source of high-quality nutrition for human pop- quality and tenderness [21–27]. These researches focused
ulations. Beef palatability is generally determined by three much attention on genetic factors influencing beef tender-
general criteria: tenderness, juiciness, and flavor. Of these ness.Anecdotally,farmersfoundthatbeefproducedbycattle
factors, beef consumers usually consider tenderness as the which suffered from acute stress, such as injury, surgery,
most important palatability trait leading to a good eating or hardware disease, has much lower quality compared to
experience [1–3]. Inconsistency in tenderness has been beef from normal cattle [28–31]. This phenomenon like
reported as the most important factor in determining con- hardwarediseasemayoccuroften;thereforetheunderlying
sumer satisfaction with beef quality [4–9]. It is well known mechanismneedstobeexploredtobetterunderstandwhat
that beef tenderness is influenced not only by genetic drivesbeeftendernessandtoultimatelyimproveprofitability
factors but also environmental aspects. Many studies have and efficiency of beef production. So far, we have not seen
beenperformedonbeefqualityandtenderness,identifying research which examines the mechanisms of beef quality
variousimportantcandidategenes[10,11],quantitativetrait alteration attributed to acute stress. In this experiment, we
loci (QTL), and single-nucleotide polymorphisms (SNPs) found an acute stress event that altered beef tenderness.
2 ComparativeandFunctionalGenomics
Since stress is a general phenomenon in beef industry, it is microarray scanner, and the resulting image files were
meaningfultoexplorethebiochemicalmechanismsonbeef analyzed with Agilent Feature Extraction software (Version
qualityinfluencedbyacutestress. 9.5.1). All procedures were carried out according to the
In this study, we hypothesized that a one time, acute manufacturer’sprotocols.Backgroundadjustment,quantile
stresseventwouldalterbeeftendernessandqualitythrough normalization across 7 microarrays, and statistical analysis
gene expression changes, which may be mediated by epige- were performed using the Limma package (linear models
neticmechanisms.Theaimsoftheresearchweretofurther for microarray data). Significantly expressed probes, in the
detect the influence of stress on beef tenderness, to explore comparisons of stress versus nonstress, were screened for
underlying genes, pathways, and networks regulating beef subsequentpathwayandnetworkanalysis.
quality,andtoobtaindeepinsightsintothemechanismsof
beeftendernessaffectedbystress. 2.4.ClusteringandNetworkAnalysis. Hierarchicalclustering
ofexpressionprofileswasperformedusingCluster3.0[33].
2.MaterialsandMethods Thedatawerefurthernormalized.Averagelinkageclustering
was performed and visualized using Treeview [33]. The
2.1. Sample Preparation and Experimental Design. Seven
initial information on gene ontology (GO) functions and
purebred Angus steers were obtained from the Wye Angus
functional relevance of significantly expressed probes were
farm (Queenstown, MD, USA). The steers were acclimated
obtained from the Gene Ontology Enrichment Analysis
toapelletedforgedietdesignedtomeetmaintenanceneeds.
SoftwareToolkit(GOEAST)[34].Ingenuitypathwayanalysis
At10monthsofage,4steersunderwentasurgicalprocedure
(IPA) (Ingenuity System, http://www.ingenuity.com/) was
that involved anesthetization and placement of a rumen
used to generate networks and assess statistically relevant
catheter.Thesurgerywasanacutestressevent.Threesteers
biofunctions and canonical pathways. A dataset containing
receivednosurgery.
genename,logFC(foldchange),andP valuewasuploaded
Attheapproximateageof1year,thesteerswereserially
and mapped to corresponding expression genes in the
harvested.Immediatelyafterharvest,samplesoflongissimus
Ingenuity knowledge database. The biofunctional analysis
dorsi (LD) from the right side of the carcass were placed in
identified“molecularandcellularfunction”and“physiolog-
RNAlatersolution(Qiagen,Valencia,CA,USA)at−80◦Cfor
ical system development and function.” Canonical pathway
furtheranalysis.Thecarcasseswerethenchilledfor48hours
analysis identified pathways most significantly represented
at 4◦C. Steaks of the LD from the 12∼13th rib (2.59cm)
inthedataset.Thesignificancebetweenthedatasetandthe
wereobtained,vacuumpacked,storedat4◦Cforatotalof14
canonicalpathwaywasmeasuredusingFisher’sexacttestfor
dayspostharvest,andthenfrozenat−20◦C.Onceallsteaks
aPvalueandaBenjamini-Hochbergcorrectionformultiple
wereobtained,aged,andthenfrozen,thesteakswerethawed
testingapplied.
at 4◦C, cooked to an internal temperature at 70◦C, cooled,
cored,andthenanalyzedforWBSFaspreviouslydescribed
2.5.QuantitativeReal-TimePCR. Tovalidatethemicroarray
[32]. All procedures followed the standard animal welfare
results, genes were selected based on their functions and
andusedguidelinesfromtheUniversityofMaryland.
significance in the results of microarray. Quantitative real-
time PCR primers were designed online with primer 3
2.2. RNA Isolation and Microarray Hybridization. About (http://frodo.wi.mit.edu/primer3/). The uniqueness of the
20∼30mgLDsampleswerehomogenizedinTRizolReagent designed primer pairs was validated by a BLAST homol-
(Invitrogen, Carlsbad, CA, USA), and total RNA was ogy search (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi) to
extracted as described in the manufacturer’s instructions ensure that homologous genes were not cross-amplified
(Invitrogen). Total RNA was purified using DNase I (Qia- by the same primer pair. Whenever possible, primers
gen) and the RNA easy Mini column (Qiagen). The RNA were designed to span intron/exon boundaries. All primers
was quantified by NanoDrop ND 1000 Spectrophotome- for target genes examined are given in Supplementary
ter (Thermo Scientific, Wilmington, DE, USA) and RNA Table 1 (see Supplementary Materials available online at
integrity determined by 2100 Bioanalyzer (Agilent Tech- doi:10.1155/2012/756284).
nologies, Santa Clara, CA, USA). Agilent 4×44K bovine TotalRNAfromthesameLDsamplewasisolated,puri-
microarrayswereusedinthisstudy.Thisarraywasdesigned fied,quantified,andingenuitydeterminedinthesamepro-
based on the whole bovine genome sequence. RNAs from cedureasthemicroarrayexperiment.ThefirststrandcDNA
all samples were mixed to an RNA pool as a reference was synthesized from 1μg of total RNA using SuperScript
sample. Two microgram RNA of each sample was labeled IIReverseTranscriptase(Invitrogen)witholigo(dT)primers
withCy3usingtheAgilentQuick-AmplabelingKit(Agilent (Invitrogen).Sampleswerethenanalyzedbyreal-timePCR
Technologies) while 2μg reference RNA was labeled with using an iCycler iQ PCR system (Bio-Rad, Hercules, CA,
Cy5. Then 825ng of the appropriate Cy3- and Cy5-labeled USA).Thereal-timePCRreactionswereperformedinafinal
complementary RNAs (cRNA) were hybridized to the 4 × volume of 20μL with a QuantiTect SYBR Green PCR Kit
44K Agilent bovine arrays, and a total of 7 arrays were (Qiagen) according to the manufacturer’s instruction. The
hybridized. efficiencies of target genes and glyceraldehyde-3-phosphate
dehydrogenase (GAPDH)amplificationwereinvestigated by
2.3.DataCollection,Normalization,andAnalysis. Following performing a serial dilution of total RNA (1μg to 0.1ng)
stringencywashes,slideswerescannedonanAgilentG2505B followingrecommendations[35].ThemRNAexpressionwas
ComparativeandFunctionalGenomics 3
Table1:SignificantGOterms137significantprobeswereinvolvedin.
GOID Ontology Term Genenumber Pvalue
GO:0019222 biological process Regulationofmetabolicprocess 16 0.032133
Regulationofcellularmetabolic
GO:0031323 biological process 15 0.032133
process
GO:0032502 biological process Developmentalprocess 15 0.034002
GO:0030154 biological process Celldifferentiation 12 0.018268
GO:0048869 biological process Cellulardevelopmentalprocess 12 0.021079
Negativeregulationofcellular
GO:0048523 biological process 10 0.043805
process
GO:0042221 biological process Responsetochemicalstimulus 9 0.042394
GO:0006955 biological process Immuneresponse 7 0.032133
Monocarboxylicacidmetabolic
GO:0032787 biological process 6 0.021079
process
GO:0006006 biological process Glucosemetabolicprocess 5 0.016802
GO:0019318 biological process Hexosemetabolicprocess 5 0.023776
Monosaccharidemetabolic
GO:0005996 biological process 5 0.031139
process
GO:0050873 biological process Brownfatcelldifferentiation 4 0.006619
GO:0045444 biological process Fatcelldifferentiation 4 0.016802
GO:0006094 biological process Gluconeogenesis 3 0.023776
GO:0019319 biological process Hexosebiosyntheticprocess 3 0.025047
Monosaccharidebiosynthetic
GO:0046364 biological process 3 0.032133
process
Positiveregulationoflipid
GO:0032370 biological process 2 0.046664
transport
Regulationoffatcell
GO:0045598 biological process 2 0.046664
differentiation
Negativeregulationofreceptor
GO:0010871 biological process 2 0.046664
Biosyntheticprocess
GO:0044421 cellular component Extracellularregionpart 9 0.032203
GO:0005615 cellular component Extracellularspace 8 0.023776
GO:0005125 molecular function Cytokineactivity 5 0.024213
GO:0005126 molecular function Cytokinereceptorbinding 5 0.032133
GO:0019864 molecular function IgGbinding 2 0.046664
normalizedagainstthehousekeepinggeneGAPDH,themost (http://genome.ucsc.edu/),andpromotersequencesofthese
commonlyusedhousekeepinggene[36].Eachreal-timePCR genes were downloaded from NCBI (http://www.ncbi.nlm
program was run for 15 minutes at 95◦C, followed by 40 .nih.gov/).AfterCGswerereplacedtoYGsandthenCswere
repeatsof15sat94◦C,30sat58◦C,and30sat70◦C.Data convertedtoTs,thesequencewasinputintothePSQAssay
wereanalyzedusingthe2−(cid:2)(cid:2)CT method[35].Thestatistical Designsoftware(PyroMarkID,Qiagen),andbisulfited-PCR
significance of the raw Ct values representing differences primers were designed to amplify these promoter regions.
in mRNA expression level was determined by two-tailed The primers for methylation detection, including forward
student’s t-test. The correlation analysis between real-time primer, reverse primer, and sequencing, are listed in the
PCR and microarray expression data was conducted using SupplementaryTable2.
CORRprocedureofSAS(SASInst.Inc.)[37]. Genomic DNA was isolated from the same LD sample
using NucleoSpin kit (Macherey-Nagel, Bethlehem, PA,
2.6. Methylation Pattern Analysis of the Significant Genes. USA). One microgram of DNA was treated with a sodium
Genes were selected based on their functions and sig- bisulfate conversion reagent (EZ DNA Methylation Golden
nificance in microarray and CpG island enrichment on Kit)(ZymoResearchCorporation,Irvine,CA,USA)accord-
their promoters. CpG island distributions in promoter ingtotheinstructionmanual.Theamplificationefficiencies
regions were checked using the UCSC Genome browser ofprimerswereinvestigatedbyperformingdilutionseriesof
4 ComparativeandFunctionalGenomics
bisulfited DNA and PCR. Then the diluted bisulfited DNA 25
served asthe templateforbisulfited PCR using theHotStar
Taq polymerase (Qiagen), and a biotin-labeled universal ∗∗∗
primer was added in each PCR reaction. Pyrosequencing 20
analysis by Pyro Q-CpG system (PyroMark ID, Qiagen)
was performed to detect methylation level of each CpG
site using 30μL of PCR products, which were analyzed kg) 15
by gel electrophoresis to confirm that the PCR amplified F (
S
B
successfully[38]. W 10
3.Results
5
3.1.TendernessofAngusBeefinThisExperiment. Foursteers
were anesthetized and given a surgery to place a rumen
0
catheter. This surgical procedure is an acute stress event Nonstress Tough stress
compared with 3 controls. To evaluate variation of beef
Figure1:TheresultsofWBSFbetweennonstressgroupandtough-
tenderness caused by this acute stress, the Warner-Bratzler stressgroup.Dataareshowninmean±SE(∗∗∗P < 0.0001).
shearforces(WBSF)weremeasured[39].TheWBSFresults
showed that the stress group was much tougher than the
control (nonstress) group (P < 0.0001) (Figure1). In
addition,allofthecarcasseswerequalitativelygraded.Thus
directions and fold changes of these genes were highly
differencesinmarblingdidnotcontributetoanydifferences consistentbetweenRT-PCRandmicroarray(R2=0.9595).
intenderness.Further,allofthesteerswereapproximately1
yearofage,soageeffectsduetocollagencrosslinkingshould
3.4. Functional Annotation of Significantly Differentially
be minimized. Then, we performed further microarray
Expressed Genes. To investigate the functionality that these
analysisbasedonthesestressandcontrolgroups.
significantly expressed genes are involved in, GO term
analysis was employed and the results showed that sig-
3.2. Differentially Expressed Genes in Divergent Stress Status. nificantly differentially expressed genes in GO biological
Todeterminethedifferentiallyexpressedgenesbetweenthese process terms were enriched in regulation of fatty acid and
two groups of differential stress status, cDNA microarray protein metabolic process, receptor biosynthetic process,
analysis was done using LD samples. With the aid of the receptor of myeloid cell apoptosis, negative regulation of
Limma package in Bioconductor, we selected significant neurondifferentiation,responsetoglucosestimulus,mono-
expressedprobesbasedonastringentstatisticalsignificance carboxylic acid metabolic process, gluconeogenesis, and so
threshold(P < 0.05,|lgFC| > 1.5,andfalsediscoveryrate forth. In cellular component category, GO terms related to
(FDR) <0.3). The results showed that a total of 215 probes extracellularregionpartandextracellularspace.Themolec-
were significantly differentially expressed, which attribute ular function category of GO term showed that cytokine
137uniqueprobes.Ofthese137probes,102wereassignedto activity, cytokine receptor binding, and IgG binding were
geneswhile35wereassignedtoESTs.Amongthese137genes enriched. Summaries of the enriched GO term categories
(orESTs),73weredownregulatedwhile64wereupregulated for significantly differentially expressed genes are shown in
intoughstresscomparedtononstress.Torevealtheoverall Table1.
expressionprofileofthesesignificantgenes(orESTs)inthese To further visualize the pathways and networks these
twogroups,clusteringanalysiswasperformedaspreviously significantly differentially expressed genes functioned in,
described[33].Thevisualizationshowedthattheexpression IPA was conducted. After uploading the gene set, 79 from
pattern of these significant genes was apparently different 102 genesmapped to the IPA knowledge database. Analysis
results showed that carbohydrate metabolism, gene expres-
betweenthesetwogroups.Also,mostofthegeneshadhighly
sion, lipid metabolism, small-molecule biochemistry, and
consistentlyexpressionlevelwithineachgroup(Figure2).
moleculartransportwererankedinthetop5of“molecular
and cellular functions.” While differential regulation of
3.3. Quantitative Real-Time PCR Results. Four genes, heat cytokine production in macrophages and T helper cells
shock70kDaprotein1A(HSPA1A),chemokine(C-X-Cmotif) by IL-17A and IL-17F, differential regulation of cytokine
ligand 2 (CXCL1), interleukin 12A (IL12A), and Josephin in intestinal epithelial by IL-17A and IL-17F, LXR/RXR
domain containing 1 (JOSD1) which function in immune activation,TR/RXRactivation,andthyroidcancersignaling
response and also significantly differentially expressed in wereamongthetopcanonicalpathways.Themostsignificant
microarraybetweentoughstressandnonstress,werechosen networks functioned in cellular growth and proliferation,
to perform RT-PCR to validate microarray results. qRT- cellularmovement,andlipidmetabolism.Summariesofthe
PCR results showed that gene expression patterns of these enrichednetworks,theirfunctionsareshowninTable2,and
4 genes were of significant difference between these two graphicalnetworksarerepresentedinFigure4,Supplemen-
groups(Figure3)(P < 0.05).Inaddition,thedysregulation taryFigure1,andSupplementaryFigure2.
ComparativeandFunctionalGenomics 5
Topfunctions Cellulargrowthandproliferation,cellularmovement,lipidmetabolism Embryonicdevelopment,reproductivesystemdevelopmentandfunction,nutritionaldisease Drugmetabolism,endocrinesystemdevelopmentandfunction,lipidmetabolism Aminoacidmetabolism,smallmoleculebiochemistry,geneexpressionCellcycle,reproductivesystemdevelopmentandfunction,celldeathGeneexpressionCardiovascularsystemdevelopmentandfunction,organmorphology,organismalinjuryandabnormalitiesCellcycle,cellmorphology,cell-to-cellsignalingandinteractionGeneexpression,embryonicdevelopment,organismaldevelopmentCellmorphology,hematologicalsystemdevelopmentandfunction,inflammatoryresponseDevelopmentaldisorder,geneticdisorder,skeletalandmusculardisorders
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Table2:Topsignifi MoleculesinnetworkAkt,Ap1,ARG2,ASGR1,ATF3,CCL8,CCL24,CLDN11,CNN1,CREM,CXCL1,DLL4,ERK1/2,FABP4,FASN,G0S2,hCG,Histoneh3,HSPA1A/HSPA1B,IL13,IL12A,MAPKAP1,NFkB(complex),NPR3,Nr1h,NR4A3,PCK1,PDGF,PPP1R15A,RCAN1,RET,RGSSCD,SDC4,TNFRSF12AAconitase,ANKRD1,AP2B1,APCS,ASPM,BLNK,CA12,CDX2,DGAT2,EFNA3,ENPP1,FCGR3A,GADD45G,HAS1,HDGF,HNF1A,HTT,IFRD1,IgG,IL1B,ITPA,KIF20A,NGEF,PFK,PPL,RARA,RNApolymeraseII,S100G,SERPING1,SGK2,SIM1,SOATTGFB1,UGT1A8,YY1ABLIM,ACP2,ACSL5,ADCY9,ARPC1A,ATPIF1,CIDEC,CREBBDUSP3,DYRK3,FBP2,FSH,GLUL,GNLY,HGD,HOXB6,ING2,LEP,Lh,LHCGR,LOC81691,NR2F1,NR3C1,NR5A1,P4HA2,PDLIM3,PLCL1,POP5,PRKX,RAB5C,RGS5,RGS16,SREBF1,THRSP,TLK1 NAALAD2,RORA FIGLA,TEKT1 ZHX1,ZHX3 AGTR1,HSPA6,RFWD2 AHR,GPI,STEAP4 CBX4,HOXA2,MBD1,MEOX1 FBL,NFE2,PSMD14,STMN1,TUBB1 DMD,SGCA,SGCB,SGCD,SGCE,SGCG
D 0 1
I 1 2 3 4 5 6 7 8 9 1 1
6 ComparativeandFunctionalGenomics
Nonstress 1
Nonstress 2
Nonstress 3
Tough stress 1
Tough stress 2
Tough stress 3
Tough stress 4
CB535104LOC614805LOC539228LOC541100LOC514143LOC615731AW430375BM087935CB464270LOC536048LOC518746CB428330EE961698CB439033CB460171FCGR3AMGC20235LOC524150LOC537280EE894495LOC533228NR2F1CCL8LOC539095PCK1SCDDGAT2THRSPFASNLOC507436LOC534741CB432241BUCS1ASGR1CALB3LOC534607FBP2LOC617258FABP4ACRP30LOC528877RGS16CB431046BI774724LOC540072JOSD1EE893095LOC506900LOC533794BI681661CB449769LOXL4GLULMGC127247BP110200LOC513055LOC534583EE905006LOC514688HSPA1BLOC615520EE893417KBTBD5EE905802AV605331CB441198LOC517013LOC522886LOC515266MGC12776SCB438825ANKRD1LOC509670MGC128596CXCL1LOC508133LOC520120TSCOTAV606554LOC515924LOC531228LOC540756LOC504207LOC504939LOC617439LOC617888CB463123MGC133641ARG2HSPA1ALOC539835
Figure2:Clusteranalysisofsignificantgenesinmicroarray.ThesegeneswerevisualizedwithTreeviewafterhierarchicalclustering.Each
geneisrepresentedbyasinglerowofcoloredboxes;eachindividualfromtwogroupsisrepresentedbyasinglecolumn.Redcolorindicates
upregulatedwhilegreenindicatesdownregulated.Genesthatwereexpressedathigherlevelsareassignedprogressivelybrightershadesofred
whilegenesexpressedatlowerlevelsareassignedprogressivelybrightershadesofgreen.
1 regions were selected to detect methylation levels in LD
0.9 muscle using pyrosequencing. The results showed that the
methylationlevelsof3CpGsitesinthepromoterofHSPA1A
0.8
significantlyincreasedinthestressgroupcomparedwiththe
on 0.7 controlgroup(P<0.05)andthemethylationlevelsof2CpG
essi 0.6 sitesinLOC614805significantlydecreasedinthestressgroup
xpr 0.5 ∗ compared with the control group (P < 0.05) (Figure5).
e
Relative 00..34 ∗ Cleovemlsbiinninmgitchreoamrreatyh,ywlaetiofnoupnadttetrhnast afnodr tgheenseeegxepnreesssitohne
methylation levelsincreased whilethegeneexpression level
0.2 ∗ decreased and vice versa, implying that the gene expression
∗
0.1 levelswereinverselycorrelatedwiththemethylationlevelsin
0 promoterregionsinthisstudy.
HSPA1A CXCL1 IL12A JOSD1
4.Discussion
Control
Stress
Beef tenderness is deemed the most important palatability
Figure3:Theq-RT-PCRresultsshowedtherelativeexpressionof attribute.Thus,improvingtendernessandprovidingconsis-
4 genes. All the 4 genes were significantly differentially expressed tently tender beef are the priority for beef industry. More
betweenstressgroupandcontrolgroup(∗P<0.05). efforts have been put on factors influencing production,
includingbreed,sex,feed,handling,environment,finishing
weightandageatslaughter,andsoforth[40].Inthisstudy,
after a one-time acute stress event, those cattle produced
3.5. Methylation Patterns Analysis of Significantly Differen- beef with significantly higher WBSF, indicating that acute
tially Expressed Genes. To ascertain whether a stress stim- stress has tremendous influence on beef tenderness. From
ulus induces any epigenetic alterations, DNA methylation cDNA microarray analysis in LD muscles of control and
patterns of several genes were checked. We blasted these stress groups, we identified 137 differently expressed genes
significant genes in the bovine genome; 6 differentially (or ESTs) related to variations on stress status and beef
expressed genes enriched with CpG islands in promoter quality.
ComparativeandFunctionalGenomics 7
Extracellular space Unknown
DLL4 IL12A G0S2
CCL24
CXCL1 CCL8
IL13
PDGF BB
Plasma membrane
NPP3
TNFRSF12A CLDN11
RET
SDC4
ASGR1
Cytoplasm
Akt ERK12
CNN1
HSPA1A/HSPA1B∗
MAPKAP1 PPP1R15A
FABP4
PCK1
FASN SCD
ARG2
Nucleus
NFKB (complex)
AP1
ATF3
RGS2
Histone h3
CREM
NR4A3
Nr1h RCAN1 hCG
Figure4:ThetopNo.1networksignificantlydifferentiallyexpressedgenesinvolved.Solidlinerepresentsdirectinteractionanddashline
representsindirectinteraction.
Notably, acute stress can induce strong immune re- stimulatemyoblastmigrationandareinvolvedinthecellular
sponse. The pathway analysis on significantly differentially differentiation process [45]. Meanwhile, cytokines are pro-
expressedgenesshowedthatseveralchemokineorcytokine teinaceous signaling compounds that are major mediators
encoded genes, such as interleukin 12A (IL12A), interleukin of the immune response. Multiple findings indicate that
13(IL13),chemokine(C-Cmotif)ligand8(CCL8),chemokine cytokinesinfluencedifferentphysiologicfunctionsofskeletal
(C-C motif) ligand 24 (CCL24), and chemokine (C-X-C muscle cells, such as anabolic and catabolic processes and
motif)ligand1(CXCL1),wereinvolvedinimmuneresponse, programmedcelldeath[46].Ithasbeenfoundthatcytokines
implicating that immune response to this acute stress by can regulate different stages of myocyte development,
chemokine or cytokine may play important roles in beef including proliferation and differentiation of myoblasts,
tenderness variation. Chemokines play fundamental roles expression of myogenic proteins, and fusion of myotubes
in the development, homeostasis, and function in the [47].Somestudiesalsofoundthatcytokineswereimportant
immune system, especially in skeletal muscle regeneration, regulatory molecules in the complex network of signals
althoughthemechanismsinvolvedarestillpoorlyelucidated that control muscle protein breakdown [46]. Here, these
[41–44]. Some chemokines, such as CXCL1, can directly chemokine-orcytokine-encodedgenesweredysregulatedin
8 ComparativeandFunctionalGenomics
70 30
HSPA1A LOC614805
60 ∗
25
∗
50
∗
%) 20
vel ( 40
e
n l 15
o ∗
ylati 30
h
et
M 10
20 ∗
5
10
0 0
Site 1 Site 2 Site 3 Site 1 Site 2
Nonstress Nonstress
Tough stress Tough stress
(a) (b)
Figure5:Significantchangesofmethylationlevelinthepromoterregionofsignificantgenesbetweentough-stressandnonstressgroups.
x-axisrepresentsCpGsitesonthepromoter;y-axisrepresentsDNAmethylationlevelofthesesites(∗P<0.05).
stress group, implying that a complex network, combining Helix-Loop-Helix/Per-Arnt-SIM(bHLH-PAS)transcription
these chemokine and cytokine regulators together, may factor[53].ItisreportedthatSIM1expressionisassociated
coregulatemuscleproteindevelopmentandbreakdownand with the early step of muscle progenitor cell migration in
even postmortem proteolysis during carcass ageing, which chickandmouse[54].TwoSNPsonthisgenewerefoundto
directly influences meat quality and tenderness. But the beassociatedwithcarcassandmeatqualitytraitsinaporcine
mechanism needs to be further explored in the future population [55]. GADD45G is involved in stress signaling
research. inresponsetophysiologicalorenvironmentalstressors,and
Theacutestressisassociatedwithregulationofmetabolic thisproteinfunctionsasstresssensors[56].ProteinNR2F1
process. The most significant GO terms identified were consists of ligand-inducible transcription factors and can
enriched with genes involved in regulation of metabolism, stimulate initiation of transcription [57]. ZHX3 encodes
including activating transcription factor 3 (ATF3), regulator a member of the zinc fingers and homeoboxes (ZHX)
of Calcineurin 1 (RCAN1), adiponectin, C1Q and col- gene family. In the nucleus, the dimerized ZHX3 protein
lagen domain containing (ADIPOQ), growth arrest and interacts with the a subunit of the ubiquitous transcription
DNA-damage-inducible,gamma(GADD45G),single-minded factorandmayfunctionasatranscriptionalrepressor[58].
homolog 1 (SIM1), nuclear receptor subfamily 2, group F, Gsx2 can regulate the balance between proliferation and
member 1 (NR2F1), zinc fingers and homeoboxes 3 (ZHX3), differentiation of the neuronal progenitor [59, 60]. Taking
GS homeobox 2 (Gsx2), and so forth. Further study of the together,allofthesegenesencodingactivatorsorrepressors
functionsofthesegenesdeterminedthattheyplayedrolesin dysregulated between stress and control groups, but how
regulationofmetabolismasactivatorsorrepressors.ATF3is they cooperate together to regulate muscle proliferation
amemberofthemammalianactivationtranscriptionfactor. and differentiation and beef tenderness needs to be further
This protein binds the cAMP response element (CRE) and explored.
repressestranscriptionfrompromoterswithATFsites[48]. Most importantly, we found that in some genes
RCAN1 is a dose-sensitive gene whose overexpression has the methylation levels increased while expression levels
beenlinkedtodiseaseneuropathologyandtotheresponseof decreasedandviceversa,implicatingthatthegeneexpression
cellstostressstimuli.Theproteinencodedbythisgeneinter- levels were inversely correlated with the methylation levels
acts with calcineurin A and inhibits calcineurin-dependent in promoter regions, which supports the previous report
signaling pathways [49, 50]. ADIPOQ is involved in the thatDNAmethylationrepressesgeneexpression[38].Also,
control of fat metabolism and insulin sensitivity [51]. This detection of different DNA methylation patterns of these
proteincanstimulateAMPKphosphorylationandactivation severalgenesfurthersupportsourhypothesisthatepigenetic
in the liver and the skeletal muscle, enhancing glucose mechanisms involve in the acute stimulus through altering
utilization and fatty acid combustion [52]. SIM1 is a basic expression of genes, suggesting that epigenetic mechanisms
ComparativeandFunctionalGenomics 9
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