Genome-wide association study of infectious bovine keratoconjunctivitis in Angus cattle

22 Pages·2016·0.46 MB·English

Animal Science Publications Animal Science
3-26-2013
Genome-wide association study of infectious
bovine keratoconjunctivitis in Angus cattle
Kadir Kizilkaya
Iowa State University, [email protected]
Richard G. Tait Jr.
Iowa State University, [email protected]
Dorian J. Garrick
Iowa State University, [email protected]
Rohan L. Fernando
Iowa State University, [email protected]
James M. Reecy
Iowa State University, [email protected]
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Genome-wide association study of infectious bovine keratoconjunctivitis
in Angus cattle
Abstract
Background Infectious Bovine Keratoconjunctivitis (IBK) in beef cattle, commonly known as pinkeye, is a
bacterial disease caused by Moraxella bovis. IBK is characterized by excessive tearing and ulceration of the
cornea. Perforation of the cornea may also occur in severe cases. IBK is considered the most important ocular
disease in cattle production, due to the decreased growth performance of infected individuals and its
subsequent economic effects. IBK is an economically important, lowly heritable categorical disease trait. Mass
selection of unaffected animals has not been successful at reducing disease incidence. Genome-wide studies
can determine chromosomal regions associated with IBK susceptibility. The objective of the study was to
detect single-nucleotide polymorphism (SNP) markers in linkage disequilibrium (LD) with genetic variants
associated with IBK in American Angus cattle.
Results
The proportion of phenotypic variance explained by markers was 0.06 in the whole genome analysis of IBK
incidence classified as two, three or nine categories. Whole-genome analysis using any categorisation of (two,
three or nine) IBK scores showed that locations on chromosomes 2, 12, 13 and 21 were associated with IBK
disease. The genomic locations on chromosomes 13 and 21 overlap with QTLs associated with Bovine
spongiform encephalopathy, clinical mastitis or somatic cell count.
Conclusions
Results of these genome-wide analyses indicated that if the underlying genetic factors confer not only IBK
susceptibility but also IBK severity, treating IBK phenotypes as a two-categorical trait can cause information
loss in the genome-wide analysis. These results help our overall understanding of the genetics of IBK and have
the potential to provide information for future use in breeding schemes.
Keywords
Keratoconjunctivitis, Pinkeye, BayesB, Threshold model, Genome-wide analysis
Disciplines
Agriculture | Animal Sciences | Genetics
Comments
This article is fromBMC Genetics14 (2013): 23, doi:10.1186/1471-2156-14-23.
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BMC Genetics
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Genome-wide association study of infectious bovine keratoconjunctivitis in
Angus cattle
BMC Genetics 2013, 14:23 doi:10.1186/1471-2156-14-23
Kadir Kizilkaya ([email protected])
Richard G Tait ([email protected])
Dorian J Garrick ([email protected])
Rohan L Fernando ([email protected])
James M Reecy ([email protected])
ISSN 1471-2156
Article type Research article
Submission date 18 October 2012
Acceptance date 22 February 2013
Publication date 26 March 2013
Article URL http://www.biomedcentral.com/1471-2156/14/23
Like all articles in BMC journals, this peer-reviewed article can be downloaded, printed and
distributed freely for any purposes (see copyright notice below).
Articles in BMC journals are listed in PubMed and archived at PubMed Central.
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©2013Kizilkayaetal.
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Genome-wide association study of infectious
bovine keratoconjunctivitis in Angus cattle
KadirKizilkaya1,2
Email: [email protected]
RichardGTait1
Email: [email protected]
DorianJGarrick1,3
Email: [email protected]
RohanLFernando1
Email: [email protected]
JamesMReecy1∗
∗Correspondingauthor
Email: [email protected]
1DepartmentofAnimalScience,IowaStateUniversity,Ames,IA50011USA
2DepartmentofAnimalScience,AdnanMenderesUniversity,Aydin09100Turkey
3Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Palmerston
North,NewZealand
Abstract
Background
Infectious Bovine Keratoconjunctivitis (IBK) in beef cattle, commonly known as pinkeye, is a bac-
terial disease caused by Moraxella bovis. IBK is characterized by excessive tearing and ulceration
of the cornea. Perforation of the cornea may also occur in severe cases. IBK is considered the most
important ocular disease in cattle production, due to the decreased growth performance of infected
individuals and its subsequent economic effects. IBK is an economically important, lowly heritable
categorical disease trait. Mass selection of unaffected animals has not been successful at reducing
disease incidence. Genome-wide studies can determine chromosomal regions associated with IBK
susceptibility. Theobjectiveofthestudywastodetectsingle-nucleotidepolymorphism(SNP)mark-
ers in linkage disequilibrium (LD) with genetic variants associated with IBK in American Angus
cattle.
Results
Theproportionofphenotypicvarianceexplainedbymarkerswas0.06inthewholegenomeanalysis
of IBKincidence classifiedas two, three or nine categories. Whole-genome analysis using anycate-
gorisationof(two,threeornine)IBKscoresshowedthatlocationsonchromosomes2,12,13and21
were associated with IBK disease. The genomic locations on chromosomes 13 and 21 overlap with
QTLsassociatedwithBovinespongiformencephalopathy,clinicalmastitisorsomaticcellcount.
Conclusions
Resultsofthesegenome-wideanalysesindicatedthatiftheunderlyinggeneticfactorsconfernotonly
IBKsusceptibilitybutalsoIBKseverity,treatingIBKphenotypesasatwo-categoricaltraitcancause
information loss in the genome-wide analysis. These results help our overall understanding of the
geneticsofIBKandhavethepotentialtoprovideinformationforfutureuseinbreedingschemes.
Keywords
Keratoconjunctivitis,Pinkeye,BayesB,Thresholdmodel,Genome-wideanalysis
Background
InfectiousBovineKeratoconjunctivitis(IBK),commonlyknownaspinkeye,isahighlycontagiousoc-
ular bacterial cattle disease which occurs in cattle populations throughout the world. IBK is caused by
the Gram negative bacterium Moraxella bovis [1] and is characterized by excessive tearing, inflamma-
tion of the conjunctiva, and ulceration of the cornea in one or both eyes. As the disease progresses the
corneabecomescloudyorwhite. Inseverecases,perforationofthecorneamayoccurwhichcanleadto
permanentblindness.
IBK is non-fatal; however, it is considered the most important ocular disease in cattle, due to the de-
creased growth performance of infected individuals. The United State National Animal Health Moni-
toring System survey [2] and Australian postal survey [3] reported IBK as an economically important
diseaseinanimalproduction. Majoreconomiclossesaretheresultofinappetenceandpoorweightgain
inaffectedanimalssufferingfromocularpainandvisualimpairment[1]. IthasbeenestimatedthatIBK
costsbeefproducers150millionUS$intheUnitedStates[4]and22millionAUD$inAustralia[3]per
annum.
There has been little research to quantify genetic variation in susceptibility to IBK. Breed differences
insusceptibilitytoIBKhavebeendemonstratedandHerefordcattlewerefoundtobemoresusceptible
compared with all other purebreds (Angus, Braunvieh, Charolais, Gelbvieh, Limousin, Pinzgauer, Red
Poll and Simmental) and Bos Indicus breeds [5,6]. Heritability estimates (0.10 - 0.25) different from
zerohavebeenreported,highlightingthepresenceofwithin-breedgeneticvariationinsusceptibilityto
IBK.
Putative QTL on Chromosomes 1 (66 to 110 cM) and 20 (2 to 35 cM) have been reported [7] to be
associated with resistance to IBK. Reducing IBK through selection would be advantageous, because
genetic gain is cumulative and permanent. Once the loci associated with susceptibility or resistance to
IBKareidentified,relevantmarkerscanbeusedforselectioninbreedingschemes.
In recent years, high-density single nucleotide polymorphism (SNP) genotyping assays for cattle have
become available [8]. In addition, statistical methodologies have been developed to make use of these
SNPpanels todetect associationbetween SNPandeconomically importanttraits. The useof genome-
widestudieshelpsidentifychromosomalregionsassociatedwithdiseaseincidenceinimmunity-related
diseases such as IBK. The objective of this study was to detect SNP markers in linkage disequilibrium
(LD)withgeneticvariantsassociatedwithIBKinAnguscattle.
Methods
Ethicsstatement
AllanimalprocedureswereapprovedbytheIowaStateUniversityAnimalCareandUseCommittee.
Phenotypicdata
Records of IBK were collected from 860 animals born and raised in the Iowa State University Angus
researchherdfromspring2004throughspring2008. TheIBKstatusofeachanimalwasdeterminedat
weaningtimeandwasscoredsubjectivelyintofivecategoriesforleftandrighteyesasfollows:
1 normalcorneawithnoapparentlesions,
2 alesioncoveringlessthan1/3ofthecornea,

y = 3 alesioncovering1/3to2/3ofthecornea, (1)
L/R,i 


4 alesioncoveringmorethan2/3ofthecornea,
5 perforationofthecornea,






where y is the left (L) or right (R) eye IBK score of animal i and i = 1,...,n (Table 1). Infection
L/R,i
statuswasstudiedbypoolingleftandrighteyeIBKscoresinvariousmanners(Table2).
Table 1 Number of animals diagnosed with different severities of Infectious Bovine Keratocon-
junctivitisforleft,rightorbotheyes
Righteye
Lefteye 1 2 3 4 5 Total
1 539 47 26 14 16 642
2 63 23 9 6 3 104
3 30 13 10 3 1 57
4 16 7 1 4 1 29
5 15 3 3 2 5 28
Total 663 93 49 29 26 860
Table 2 Number of animals diagnosed with different severities of Infectious Bovine Keratocon-
junctivitisclassifiedwithintwo,threeorninecategories
IBKscore
Category 1 2 3 4 5 6 7 8 9
2 539 321
3 539 227 94
9 539 110 79 52 54 10 8 3 5
First,leftandrightIBKscoreswerecombinedtoformaclassificationinvolvingtwocategories(c = 2):
Incidencewasscoredas1forbotheyesunaffectedandas2otherwise.
1 y = 1andy = 1,
L,i R,i
y = (2)
c=2,i

2 otherwise.


Second,leftandrightIBKscoreswerecombinedintoathreecategoryclassification(c = 3): Incidence
wasscoredas1forbotheyesunaffected,2forasingleaffectedeyeand3forbothaffectedeyes.
1 y = 1andy = 1,
L,i R,i

yc=3,i = 2 yL,i 6= 1oryR,i 6= 1, (3)



3 y 6= 1andy 6= 1,
L,i R,i





Third,leftandrightIBKscoreswereclassifiedinninecategories(c = 9): Incidencewasscoredfrom1
to9byaddingthescoresoftheleftandrighteyes(y +y −1).
L,i R,i
1
2
.
yc=9,i = .. yL,i+yR,i−1, (4)


8
9







50kSNPdata
High-density (53,367) SNP genotypes of purebred American Angus cattle were obtained using the
Bovine SNP50 Infinium II BeadChip (Illumina, Inc., San Diago CA). The Illumina A/B allele calls
were used to compute a covariate for each locus that had values 0, 1, or 2 to represent the number
of B alleles. Missing genotypes represented less than 0.2% of total observations and were replaced
with average covariate values. All genotypes were retained in the analysis regardless of minor allele
frequency.
BayesBthresholdmodel
The threshold model for ordered categorical data assumes the existence of a set of ordered thresholds
τ = −∞ < τ < τ < ... < τ < τ = ∞ for the trait and an underlying or latent variable l for
0 1 2 c−1 c i
each animal i. When the latent variable for animal i is between thresholds τ and τ the categorical
j−1 j
phenotypey foranimalitakesvaluej[9,10].
i
TheBayesB[11]modelforgenome-wideanalysisofcontinuoustraitshaspreviouslybeenextended[12]
toanalyzecategoricalphenotypesassumingathresholdmodelasdescribedbelow. Inthisapproach,the
latentvariablel correspondingtoy,theIBKcategoricalphenotype,ismodeledasfollows:
i i
K
l = x′β + z α +e, i = 1,.....,n (5)
i i ik k i
k=1
X
where β is a px1 vector of fixed effects, x′ is a known incidence row vector corresponding to fixed
i
effects in β, K is the number of marker loci, z is the value of the covariate for marker k in individual
ik
i, α is the random substitution effect for locus k, with α ∼ N(0,σ2) with probability 1-π or α = 0
k k αk k
with probability π. For a locus included in the model, the locus-specific variance, σ2, is assumed to
αk
have a scaled inverse chi-square distribution with degrees of freedom ν =4 and scale parameter S2 =
α α
σg2(να−2) ,wherep istheBallelefrequencyofmarkerkandσ2istheadditivegeneticvariance
(1−π) Kk=12pk(1−pk)να k g
explainedbymarkers[13,14]. Foralocusnotinthemodel,σ2 issettozero. Aflatpriorwasassumed
P αk
forthefixedeffectsandthresholds,andtheresidual,e,wasassumedtobedistributedN(0,σ2 = 1).
i e
Thejointposteriordensityofβ,α,τ,σ2 andl[10]isgivenby:
α
n
p(β,α,l,τ,σ2,|y) = [Pr(y = j|l,τ)p(l|β,α)]p(β,α,τ,σ2) (6)
α i i i α
i=1
Y
whereα,σ2,τ andlarethevectorsofmarkereffects,markervariances,thresholdsandliabilities.
α
Giventhethresholdmodel,theconditionalprobabilityPr(y = j|l,τ)inequation(6)iseither1orzero,
i i
andfollowingAlbertandChib[15]thisprobabilitycanbewrittenas:
c
Pr(y = j|l,τ) = I(τ < l < τ)I(y = j), (7)
i i j−1 i j i
j=1
X
whereI(.)isanindicatorfunctiontakingthevalue1whenexpression(.) istrueand0otherwise.
Itisassumedthat,giventhelocationparametersβ andα,thedensityfunctionofthelatentvariablel in
i
equation(6)isnormal:
K
p(l|β,α) = N(x′β + z α ,1). (8)
i i ik k
k=1
X
Thedensityofthejointpriordistributioninequation(6)hastheform
p(β,α,τ,σ2) = p(β)p(α)p(τ)p(σ2). (9)
α α
A Gibbs sampler was used to construct an irreducible, Markov chain with the joint posterior as its
stationarydistribution[10,16,17]. InferencesweremadefromtheMarkovchain. IntheGibbssampler,
samplesareobtainedfromthefullconditionalposteriorsratherthanthejointposterior[10,16,17]. The
fullconditionalposteriorsusedinthispaperaredescribedbelow.
Thefullconditionalposteriorforthefixedeffectβ givenallotherunknownsisanormaldistribution:
m
p(β |β ,α) = N(βˆ ,(x′ x )−1) (10)
m −m m m m
where
K
x′ (l−[X β + z α ])
m −m −m k k
βˆ = k=1 , (11)
m x′ x P
m m
X is the matrix X with the column associated with m deleted, and β is β with the mth element
−m −m
deleted.
Atlocusk,followingMeuwissenetal[11],thelocus-specificmarkervariance,σ2,andtheSNPeffect,
αk
α , were sampled from their joint full conditional posterior distribution. The strategy they used was to
k
sample σ2 fromthe marginal of the fullconditional posterior and then sampleα fromthe conditional
αk k
posteriorgiventhesampledvalueforσ2 [11].
αk
This full-conditional distribution does not have a closed form, and thus the Metropolis-Hasting (MH)
algorithmisusedtosampleσ2. Meuwissenetal[11]usedthepriordistributionofσ2 astheproposal
αk αk
distributionintheMHalgorithm. HereweusedtheproposaldistributiondescribedbyHabieretal.[14].
Giventhesampledvalueofσ2,themarkereffectα wassampledfromitsconditionalposterior:
αk k
0 σ2 = 0,
αk|σα2k = ∼ N(z′krk,C−1) σα2k > 0, (12)
( Ck k αk
K
wherer = l−[Xβ + z α ]andC = z′z +(σ2)−1 [14].
k k′ k′ k k k αk
k′6=k
P
Following Cowles [18], the latent variables and thresholds were sampled jointly from their joint full
conditional distribution. Cowles [18] samples the thresholds from the marginal of this full conditional
posterior, which is obtained by integrating out the latent variables [19]. The marginal full conditional
doesnothaveaclosedformandanMHalgorithmisusedtodrawsamplesofthethresholds[18]. Then,
given the sampled values of the thresholds, each of the latent variables is sampled from its conditional
posterior,whichistruncatednormal:
K c
p(l|β,α,τ,l ,y) ∝ N(x′β + z α ,1) I(τ < l < τ)I(y = j) , (13)
i −i i ik k  j−1 i j i 
j=1 j=1
X X
 
asdescribedbyDevroye[20].
Geneticvarianceandheritability
Theposteriormeansofthegeneticvarianceandoftheheritabilityforthelatentvariablewereestimated
fromtheMarkovChainMonteCarlo(MCMC)samplesasfollows. IneachMCMCstep,thevectorgof
breedingvaluesofallanimalswassampledas:
K
g(t) = z α(t), (14)
k k
k=1
X
whereα(t) isthesampledvalueofα instept. Now,vectorg(t) wasusedtosamplethegeneticvariance
k k
σ2(t) as
g
n(g(t)−g¯(t))2
σ2(t) = i i , (15)
g n
P
where
ng(t)
g¯(t) = i i .
n
P
Theheritabilityh2(t) wasthensampledas
σ2(t)
h2(t) = g . (16)
σ2(t)+1
g
Thearithmeticmeansofthesesampleswereusedtoestimatetheirposteriormeans.
Windowvariance
Thegeneticvarianceattributedtoagenomicwindowisdefinedasfollows. First,thebreedingvaluefor
agenomicwindowisdefinedas
g = z α , (17)
w k k
k∈W
X
whereα istheeffectofSNPk andW isthesetof indicesof SNPsthatbelongtogenomicwindoww.
k
Thegeneticvarianceattributedforgenomicwindowwisnowdefinedas
n(g −g¯ )2
σ2 = i wi w , (18)
gw n
P
where
ng
g¯ = i wi.
w
n
P
Samples of window variances were obtained using (15) but with g(t) computed with only the sampled
SNP effects for window w [21] . These samples were used to compute posterior means and posterior
probabilitiesforpercentwindowvariancesandwereusedforinferencesonlocationsofcausalvariants.
Bioinformaticsandidentificationofcandidategenes
SNP effects from genome-wide analysis were obtained using the threshold model
in GenSel software [22] and the estimated effects were uploaded into SNPLOTz
(http://www.animalgenome.org/tools/snplotz). SNPLOTzvisualizedtheestimatedSNPeffectsandtheir
genomic location and was dynamically linked to Gbrowse (http://www.animalgenome.org/gbrowse),
whichallowedvisualizationofSNPwithothertypesofgenomefeatures(i.e.,annotatedgenes,curated
QTL,transcripts,etc.)[23]. TheSNPpositionswithinachromosomewerebasedonBostaurusgenome
assembly(UMD3.1).
Resultsanddiscussion
The distribution of IBK records by left and right eyes are presented in Table 1. The rates for severity
of IBK that was scored into five categories from cornea with no apparent lesions to perforation of the
cornea were 75, 12, 7, 3 and 3 % for left eye and 77, 11, 6, 3 and 3 % for right eye. These results
indicated similarity between left and right eyes for IBK incidence rates. Rodriguez [24] studied the
effectsofIBKincidenceseverityonproductiontraitsinAngusbreedandfoundsimilarincidencerates
betweenleftandrighteyes.
The distribution of IBK scores classified in two, three or nine categories of infection can be seen in
Table 2. The rates of unaffected, affected, only one-eye affected and two-eye affected animals were
63, 37, 26 and 11%, respectively. The severity score of IBK within the nine category classification
system varied from 12.8% to 0.58% for infected animals. These results were found to be similar with
those from Rodriguez [24]; however, higher than those (3.7%) from Snowder et al. [6], that studied
environmentaleffectsandgeneticfactorsinfluencingtheincidenceofIBKamongninebreedsincluding
Angus. Asignificantbetween-breeddifferenceinIBKincidencehasbeenreported[25],withpurebred