Genetics of disease resistance: application to bovine Tuberculosis
dc.contributor.advisor
Woolliams, John
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dc.contributor.advisor
Banos, Georgios
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dc.contributor.author
Tsairidou, Smaragda
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dc.contributor.sponsor
other
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dc.date.accessioned
2017-11-02T14:42:52Z
dc.date.available
2017-11-02T14:42:52Z
dc.date.issued
2016-07-02
dc.description.abstract
Bovine Tuberculosis (bTB) is a disease of significant economic importance,
being one of the most persistent animal health problems in the UK and the Republic
of Ireland and increasingly constituting a public health concern especially for the
developing world. Limitations of the currently available diagnostic and control
methods, along with our incomplete understanding of bTB transmission, prevent
successful eradication. This Thesis addresses the development of a complementary
control strategy which will be based on animal genetics and will allow us to identify
animals genetically predisposed to be more resistant to disease. Specifically, the aim
of my PhD project is to investigate the genetic architecture of resistance to bTB and
demonstrate the feasibility of whole genome prediction for the control of bTB in
cattle. Genomic selection for disease resistance in livestock populations will assist
with the reduction of the in herd-level incidence and the severity of potential
outbreaks.
The first objective was to explore the estimation of breeding values for bTB
resistance in UK dairy cattle, and test these genomic predictions for situations when
disease phenotypes are not available on selection candidates. Through using dense
SNP chip data the results of Chapter 2 demonstrate that genomic selection for bTB
resistance is feasible (h2 = 0.23(SE = 0.06)) and bTB resistance can be predicted
using genetic markers with an estimate of prediction accuracy of r(g, ĝ) = 0.33 in
this data. It was shown that genotypes help to predict disease state (AUC ≈ 0.58) and
animals lacking bTB phenotypes can be selected based on their genotypes. In
Chapter 3, a novel approach is presented to identify loci displaying heterozygote
(dis)advantage associated with resistance to M. bovis, hypothesising underlying non-additive
genetic variation, and these results are compared with those obtained from
standard genome scans. A marker was identified suggesting an association between
locus heterozygosity and increased susceptibility to bTB i.e. a heterozygote
disadvantage, with the heterozygotes being significantly more in the cases than in the
controls (x2 = 11.50, p<0.001).
Secondly, this thesis focused on conducting a meta-analysis on two dairy
cattle populations with bTB phenotypes and SNP chip genotypes, identifying
genomic regions underlying bTB resistance and testing genomic predictions by
means of cross-validation. In Chapter 4, exploration of the genetic architecture of the
trait revealed that bTB resistance is a moderately polygenic, complex trait with
clusters of causal variants spread across a few major chromosomes collectively
controlling the trait. A region was identified on chromosome 6, putatively associated
with bTB resistance and this chromosome as a whole was shown to contribute a
major proportion (hc
2= 0.051) of the observed variation in this dataset. Genomic
prediction for bTB was shown to be feasible even when only distantly related
populations are combined (r(g,ĝ)=0.33 (SE = 0.05)), with the chromosomal
heritability results suggesting that the accuracy arises from the SNPs capturing
linkage disequilibrium between markers and QTL, as well as additive relationships
between animals (~80% of estimated genomic h2 is due to relatedness). To extend
the analysis, in Chapter 5, high density genotypes were inferred by means of
genotype imputation, anticipating that these analyses will allow the identification of
genomic regions associated with bTB resistance more closely, and that would
increase the prediction accuracy. Genotype imputation was successful, however,
using all imputed genotypes added little information. The limiting factor was found
to be the number of animals and the trait definitions rather than the density of
genotypes.
Thirdly, a quantitative genetic analysis of actual Single Intradermal
Comparative Cervical Test (SICCT) values collected during bTB herd testing was
conducted aiming to investigate if selection for bTB resistance is likely to have an
impact on the SICCT diagnostic test. This analysis demonstrated that the SICCT has
a negligibly low heritability (h2=0.0104 (SE = 0.0032)) and any effect on the
responsiveness to the test is likely to be small.
In conclusion, breeding for disease resistance in livestock is feasible and we
can predict the risk of bTB in cattle using genomic information. Further, putative
QTLs associated with bTB resistance were identified, and exploration of the genetic
architecture of bTB resistance revealed a moderately polygenic trait. These results
suggest that given that larger datasets with more phenotyped and genotyped animals
will be available, we can breed for bTB resistance and implement the genomic
selection technology in breeding programmes aiming to improve the disease status
and overall health of the livestock population. Using the genomics this can be
continued as the epidemic declines.
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dc.identifier.uri
http://hdl.handle.net/1842/25397
dc.language.iso
en
dc.publisher
The University of Edinburgh
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dc.relation.hasversion
S. Tsairidou, J. A. Woolliams, A. R. Allen, R. A. Skuce, S. H. McBride, D. M. Wright, M. L. Bermingham, R. Pong-Wong, O. Matika, S. W. J. McDowell, E. J. Glass, S. C. Bishop. (2014) Genomic Prediction for Tuberculosis Resistance in Dairy Cattle. Plos One, Vol. 9, Issue 5, e96728
en
dc.relation.hasversion
S. Tsairidou, M. L. Bermingham, S. C. Bishop, J. A. Woolliams, A. R. Allen, S. H. McBride, D. M. Wright, R. A. Skuce, R. Pong-Wong, O. Matika, S. W. J. McDowell, E. J. Glass. (2013) Genomic prediction for tuberculosis resistance in dairy cattle. Proceedings of the British Society of Animal Science, BSAS Annual Meeting 2013, Nottingham, UK.
en
dc.relation.hasversion
S. Tsairidou, J.A. Woolliams, A.R. Allen, R.A. Skuce, S.H. McBride, R. Pong- Wong, O. Matika, E.K. Finlay, D.P. Berry, D.G. Bradley, S.W.J. McDowell, E.J. Glass, S.C. Bishop. (2014) A meta-analysis for bovine tuberculosis resistance in dairy cattle. Proceedings, 10th World Congress of Genetics Applied to Livestock Production, Vancouver, Canada.
en
dc.relation.hasversion
S. Tsairidou, J.A.Woolliams, A.R. Allen, R.A. Skuce, S.H. McBride, D.M. Wright, M.L. Bermingham, R. Pong-Wong, O. Matika, C. M. Pooley, S.W.J. McDowell, E.J. Glass, S.C. Bishop. (2014) A Heterozygote Advantage Analysis For Tuberculosis Resistance In Dairy Cattle. VI International M. bovis Conference, Cardiff, Wales.
en
dc.relation.hasversion
S. Tsairidou, J.A. Woolliams, A.R. Allen, R.A. Skuce, S.H. McBride, R. Pong- Wong, O. Matika, E.K. Finlay, D.P. Berry, D.G. Bradley, S.W.J. McDowell, E.J. Glass, S.C. Bishop. (2015) A meta-analysis for bovine tuberculosis resistance in dairy cattle. Proceedings of the British Society of Animal Science, BSAS Annual Meeting 2015, Chester, UK.
en
dc.relation.hasversion
Tsairidou S., Woolliams J. A., Allen A. R., Skuce R. A., McBride S. H., et al. Genomic prediction for tuberculosis resistance in dairy cattle. PLoS One. 2014; 9 (5): e96728. Epub 2014/05/09. PubMed PMID: 24809715; PubMed Central PMCID: PMCPmc4014548.
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dc.rights
Attribution-NonCommercial-ShareAlike 4.0 International
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dc.rights.uri
http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject
bovine Tuberculosis
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dc.subject
genomic selection
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dc.subject
SICCT
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dc.subject
Single Intradermal Comparative Cervical Test
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dc.subject
prediction accuracy
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dc.subject
imputation
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dc.title
Genetics of disease resistance: application to bovine Tuberculosis
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
PhD Doctor of Philosophy
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