Next-generation sequencing of pharmacogenes

Abstract

Because of the unmet needs of current pharmacotherapy for schizophrenia, antipsychotic pharmacogenetic research is of utmost importance. However, to date, few clinically applicable antipsychotic pharmacogenomic alleles have been identified. Nonetheless, next-generation sequencing technologies are expected to aid in the identification of clinically significant variants for this complex phenotype. The aim of this study was therefore to critically examine the ability of next-generation sequencing technologies to reliably detect variation present in pharmacogenes. Candidate antipsychotic pharmacogenes and very important pharmacogenes were identified from the literature and the Pharmacogenomics Knowledgebase. Thereafter, the percentage sequence similarity observed between these genes and their corresponding pseudogenes and paralogues, as well as the percentage low-complexity sequence and GC content of each gene, was calculated. These sequence attributes were subsequently compared with the 'inaccessible' regions of these genes as described by the 1000 Genomes Project. It was found that the percentage 'inaccessible genome' correlated well with GC content (P=9.96×10), low-complexity sequence (P=0.0002) and the presence of pseudogenes/paralogues (P=8.02×10). In addition, it was found that many of the pharmacogenes were not ideally suited to next-generation sequencing because of these genomic complexities. These included the CYP and HLA genes, both of which are of importance to many fields of pharmacogenetics. Current short read sequencing technologies are unable to comprehensively capture the variation in all pharmacogenes. Therefore, until high-throughput sequencing technologies advance further, it may be necessary to combine next-generation sequencing with other genotyping strategies.