Investigating the Quantitative Trait Loci Contributing to Individual Variation in Drug Response

<p>Individuals often display a wide variety of phenotypic responses to drug treatment, in terms of both efficacy and side effects. Part of this variation appears to have an individual genetic basis which is not well understood. It is well established in the literature that most traits, including drug response, are not controlled by a single gene, but rather arise from multiple loci known as quantitative trait loci (QTL). This thesis investigated the genetic basis of individual variability of response to two antifungal agents whose targets are known—namely benomyl (an industrial fungicide) and ketoconazole (a medicinal fungicide). A collection of 33 Saccharomyces cerevisiae yeast strains, sourced from the Saccharomyces Genome Resequencing Project (SGRP, Sanger Institute) was used to model individuals as these strains carry natural variation in terms of single nucleotide polymorphisms (SNPs) akin to human individuals. Drug response measurements using serial spot dilution and high-throughput 384-colony robotic pinning screens were used to select four SGRP strains on the basis of drug resistance or sensitivity relative to the laboratory strain BY. These were L-1374 that was sensitive to benomyl compared to BY; UWOPS87-2421 that was resistant to benomyl compared to BY; Y12 that was sensitive to ketoconazole compared to BY; DBVPG6044 that was resistant ketoconazole compared to BY. The four strains described were crossed individually with the BY laboratory strain and the resultant diploids were sporulated to obtain meiotic recombinant offspring. Spores were then subjected ten cycles of intercrossing in order to obtain advanced intercross lines (AILs); these contain reduced linkage disequilibrium between marker and trait genomic position and act to refine the localising potential of the QTL. The segregant offspring produced following the setup of AIL were subjected to studies to investigate the heritability of drug response to intermediate and high dose of benomyl or ketoconazole. It was concluded that in each of the crosses trialled, the drug response was a multigenic trait. Furthermore, the broad sense heritability estimates were high (L-1374×BY: H² = 0.91 and 0.92 for response to 75 μM and 137.5 μM benomyl respectively; UWOPS87-2421×BY: H² = 0.75 and 0.87 for response to 150 μM and 250 μM benomyl; Y12×BY: H² = 0.9 and 0.88 for response to 60 μM and 100 μM ketoconazole). This indicates that most of the variance seen in drug response arises due to genetic variance. Additionally, the relative drug sensitivity in each of the crosses trialled was found to be either a dominant trait (either partially or fully so). Finally QTL mapping through next generation sequencing bulk segregant analysis (NGS-BSA) confirmed the multigenic nature of the drug response in the selected strains. The effect of intermediate versus high dose drug treatment revealed that the QTL network is largely conserved between treatment regimens (L-1374×BY cross: three and five QTL upon treatment with 30 μM and 50 μM benomyl respectively; UWOPS87-2421×BY cross: nine and 18 QTL upon treatment with 45 μM and 80 μM of benomyl; Y12×BY cross: 41 and 56 QTL for response to 11.5 μM and 15 μM of ketoconazole; DBVPG6044×BY cross: 12 and 10 QTL for the response to 25 μM and 65 μM ketoconazole). In order to investigate the contribution of individual variation to drug response, the QTL network of the sensitive and the resistant strain for each drug were compared. It was revealed that although there is a conserved core of QTL for response to benomyl and ketoconazole respectively, the individual strains possess a considerable number of strain-specific QTL. This suggested that individual variation may indeed play a significant role in drug response. Analysis of the top-ranking QTL (in terms of LOD score) for each of the four strains revealed that each of them harboured genes that have literature-supported relationships to their relevant drug. This thesis presents a significant contribution to existing literature in terms of elucidating the QTL network underlying individual response to benomyl and ketoconazole. The findings from this study have practical potential to provide improved insight into factors that can produce antifungal resistance (a growing and significant clinical problem). Furthermore, it provides insight into better therapeutic regimens that can improve medicinal treatment for individuals.</p>