Network-guided genome-wide studies reveal a complex genetic architecture of warfarin resistance in the Norway rat (Rattus norvegicus)

dc.contributor.advisorKohn, Michael H.
dc.contributor.committeeMemberPutnam, Nicholas H.
dc.contributor.committeeMemberNakhleh, Luay K.
dc.contributor.committeeMemberKimmel, Marek
dc.contributor.committeeMemberPeng, Bo
dc.creatorLi, Shuwei
dc.date.accessioned2013-09-16T15:49:03Z
dc.date.accessioned2013-09-16T15:49:46Z
dc.date.available2013-09-16T15:49:03Z
dc.date.available2013-09-16T15:49:46Z
dc.date.created2013-05
dc.date.issued2013-09-16
dc.date.submittedMay 2013
dc.date.updated2013-09-16T15:49:47Z
dc.description.abstractA fundamental challenge in evolutionary biology and medical genetic research is to connect the phenotype (a disease in humans or an adaptive trait in animals or plants) with the genotype. Using a classical example of an adaptive trait with a strong Mendelian genetic basis - warfarin resistance in the Norway rat (Rattus norvegicus), my dissertation tests the main hypothesis that speculated ‘simple’ adaptive trait has a more complex genetic architecture. Warfarin is an anticoagulant rodenticide used since the 1950s, and also is a widely prescribed blood-thinning drug in human. As a rodenticide, warfarin has initially been very effective. However, resistant rodents have evolved quickly and Vkorc1 (vitamin K epoxide reductase complex subunit 1) is the known resistance gene. As a popular drug, warfarin has a narrow therapeutic window with several genes VKORC1, CYP2C9, CYP4F2 established as biomarkers predicting warfarin dose in humans, suggesting a complex genetic architecture of warfarin resistance in rodents. In my thesis I performed network-guided genomic association studies (NetGWAS) and gene expression analysis to identify candidate genes involved in warfarin resistance based on a sample of ~600 wild rats from 19 populations in Germany. My thesis work revealed that the resistance mutation in Vkorc1 likely is under balancing selection and was recently introduced to the rat population in our study area. A key innovation of my thesis is adopting a NetGWAS approach to prioritize true associations and conducting co-expression network analysis to detect expression changes related to warfarin. My work shows that additional candidate genes are connected to the vitamin K pathway of which Vkorc1 is an essential component. While the validation of identified genes remains a challenge, the value of my thesis for future investigation is shown: one candidate gene Calu (Calumenin) is associated with warfarin resistance in multiple populations and is an essential part of the vitamin K cycle. Finally, my thesis briefly examines the genetics underlying a newly postulated cost of resistance, arterial calcification. This dissertation provides us an innovative framework in which we learned the genetic architecture of an adaptive trait in multiple dimensions: nucleotide or expression variation, genomic distribution and gene-gene interactions.
dc.format.mimetypeapplication/pdf
dc.identifier.citationLi, Shuwei. "Network-guided genome-wide studies reveal a complex genetic architecture of warfarin resistance in the Norway rat (Rattus norvegicus)." (2013) Diss., Rice University. <a href="https://hdl.handle.net/1911/71986">https://hdl.handle.net/1911/71986</a>.
dc.identifier.slug123456789/ETD-2013-05-578
dc.identifier.urihttps://hdl.handle.net/1911/71986
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectNetworks
dc.subjectWarfarin
dc.subjectRats
dc.subjectResistance adaptation
dc.titleNetwork-guided genome-wide studies reveal a complex genetic architecture of warfarin resistance in the Norway rat (Rattus norvegicus)
dc.typeThesis
dc.type.materialText
thesis.degree.departmentEcology and Evolutionary Biology
thesis.degree.disciplineNatural Sciences
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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