Determination of Quantitative Trait Loci Contributing to Differential Drug Response
Research For Life
CA Roberts, PH Atkinson
School of Biological Sciences
Individual variation in drug response, in terms of both efficacy and adverse reactions, poses significant problems in terms of being able to provide optimal patient care, or avoiding serious or fatal side effects. A portion of this individual variation has a genetic basis and cannot be predicted from the primary mechanism of the drug in question; thus performing an unbiased genomic investigation can provide significant insight into the reasons underlying this phenomenon. To research this we utilised a powerful new approach, which combines segregation analysis and next-generation sequencing, to directly map genetic loci that contribute to either resistance or sensitivity to the antifungal agents benomyl and ketoconazole.
We used the baker’s yeast Saccharomyces cerevisiae as a model system of a eukaryotic cell, because it has incredible amenability to laboratory use and genetic study, while maintaining good homology to higher eukaryotic systems. Natural yeast individual strains have been reported to contain similar levels of genetic variation to human individuals and were used as a proxy for human individuals in studies of drug response. 34 of such yeast individual strains (sourced from the Sanger Institute’s Saccharomyces Genome Resequencing Project) have been tested in terms of growth inhibition in a series of dose-response studies to the two agents described above. The strains displayed a continuum of resistance/sensitivity (response) to each drug, and further studies indicated the contribution of multiple genetic factors to this drug-response phenotype. Similar dose-response studies have been carried out for the anti-atherosclerotic drug atorvastatin/Lipitor but were discontinued owing to the lack of response from the panel of available yeast strains.
Based on these findings, the most resistant and most sensitive strains for benomyl and ketoconazole each were subjected to next-generation sequencing bulk segregant analysis (NGS-BSA). This is a powerful approach for mapping genes that contribute to drug resistance between two strains of interest. Briefly, it consists of two stages. The first stage entails whole-genome sequencing in order to identify marker points of genetic variation, such as single nucleotide polymorphisms (SNPs) and insertion-deletion mutations (indels) between the two strains of interest. The second stage consists of selecting for drug-resistant offspring from the cross between the two parental strains and performing another round of whole-genome sequencing—this time on a pooled population of such offspring. Funding granted by WMRF allowed us to carry out Illumina sequencing for this purpose through Macrogen Inc in South Korea.
The first round of whole-genome sequencing provided over 10 Gb of high-quality Illumina raw sequencing data. Bioinformatic analysis was performed by alignment of the reads to the reference yeast genome using the software package Burrows-Wheeler Aligner (BWA). Variants were called using the Genome Analysis Toolkit (GATK; Broad Institute, Boston) in order to identify markers between the parental strains of interest. Analysis is still in progress—however, preliminary results from the ketoconazole-resistant strain NCYC110 indicate the presence of a total of 78 041 high quality genetic variants; 75 685 of those are SNPs, with the remainder being indels. This translates to a variant approximately every 150 bp in the yeast genome. From this we have assembled a high-density genetic map from these markers which will be used for a follow-on QTL study to identify those variants that are causal for ketoconazole resistance. The same procedure will be performed with the strains Y12 (ketoconazole sensitive), UWOPS87-2421 (benomyl resistant) and L-1374 (benomyl sensitive).
The second round of whole-genome sequencing was carried out on populations of over 105 segregant individuals; each population pool was covered to over 400X coverage, producing over 100 Gb of raw data. This sequencing round has just been completed and analysis is still ongoing. Briefly, in addition to the reference alignment that was performed in the first round, this analysis will also involve applying sophisticated methods for determining the allele frequencies of one parent versus the other at each marker site. Sites where the allele of either parents are significantly over-represented are presumed to contribute to drug resistance/susceptibility phenotype.
Funding from WMRF has allowed us to apply this technologically advanced approach to explore the genetic underpinning of individual drug response. The whole-genome sequencing has to this point produced high quality maps of genetic markers and the analysis of population genome sequencing will further demarcate which of those variants are actually causal for the drug response phenotype. This can produce clinical benefits, such as development of better anti-fungal drugs or producing new candidate genes to test in higher systems in order to ultimately improve drug treatment regimes.