Computational methods analyze genomic data to identify genetic variants linked to drug responses, thereby guiding personalized medicine. This study analyzed 942 whole‐genome sequences from the Electricity Generating Authority of Thailand (EGAT) cohort to establish a population‐specific pharmacogenomic database (TPGxD‐1) in the Thai population. Sentieon (version 201808.08) implemented the GATK best workflow practice for variant calling. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0 and employed Stargazer v2.0.2 for star allele analysis. The analysis of 63 very important pharmacogenes (VIPGx) reveals 85,566 variants, including 13,532 novel discoveries. Notably, we identified 464 known PGx variants and 275 clinically relevant novel variants. The phenotypic prediction of 15 VIPGx demonstrated a varied metabolic profile for the Thai population. Genes like CYP2C9 (9%), CYP3A5 (45.2%), CYP2B6 (9.4%), NUDT15 (15%), CYP2D6 (47%) and CYP2C19 (43%) showed a high number of intermediate metabolizers; CYP3A5 (41%), and CYP2C19 (9.9%) showed more poor metabolizers. CYP1A2 (52.7%) and CYP2B6 (7.6%) were found to have a higher number of ultra‐metabolizers. The functional prediction of the remaining 10 VIPGx genes reveals a high frequency of decreased functional alleles in SULT1A1 (12%), NAT2 (84%), and G6PD (12%). SLCO1B1 reports 20% poor functional alleles, while PTGIS (42%), SLCO1B1 (4%), and TPMT (5.96%) showed increased functional alleles. This study discovered new variants and alleles in the 63 VIPGx genes among the Thai population, offering insights into advancing clinical pharmacogenomics (PGx). However, further validation is needed using other computational and genotyping methods.

This trio-based whole-genome sequencing (WGS) study enhances the accuracy of variant detection by leveraging parental genotypes, which facilitates the identification of de novo mutations and population-specific variants. Nonetheless, the comprehensive genetic variation data of the Thai population remain limited, posing challenges to advancing personalized medicine and population-based screening strategies. We establish the genetic variation information of a healthy Thai population by analyzing the sequences of 40 trios, yielding 120 whole genomes (excluding offspring). The resulting dataset encompasses 20.2 million variants, including 1.1 million novel and 19.1 million known variants. Within this dataset, we identify 169 pathogenic variants, of which 56 are classified as rare and 87 are absent from the ClinVar database as of version 2023. These pathogenic variants, particularly the rare and de novo mutations, will likely be of significant interest for genetic association studies. Notably, one pathogenic variant linked to a de novo mutation is found in the SF3B2 gene, which is associated with craniofacial microsomia. With its innovative methodology and comprehensive dataset, our trio-based whole-genome sequencing study provides an invaluable representation of the genetic variations in the Thai population. These data provide a critical foundation for further analyses of the pathogenic variants related to human disease phenotypes in genetic association studies.

Next‐generation sequencing (NGS) has transformed pharmacogenomics (PGx), enabling thorough profiling of pharmacogenes using computational methods and advancing personalized medicine. The Thai Pharmacogenomic Database‐2 (TPGxD‐2) analyzed 948 whole genome sequences, primarily from the Electricity Generating Authority of Thailand (EGAT) cohort. This study is an extension of the previous Thai Pharmacogenomic Database (TPGxD‐1) and specifically focused on 26 non‐very important pharmacogenes (VIPGx) genes. Variant calling was conducted using Sentieon (version 201808.08) following GATK's best workflow practices. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0. Star allele analysis was performed with Stargazer v2.0.2, which called star alleles for 22 of 26 non‐VIPGx genes. The variant analysis revealed a total of 14,529 variants in 26 non‐VIPGx genes, with TBXAS1 had the highest number of variants (27%). Among the 14,529 variants, 2328 were novel (without rsID), with 87 identified as clinically relevant. We also found 56 known PGx variants among the known variants (n = 12,201), with UGT2B7 (19.64%), CYP1B1 (8.9%), SLCO2B1 (8.9%), and POR (8.9%) being the most common. We reported a high frequency of intermediate metabolizers (IMs) in CYP2F1 (34.6%) and CYP4A11 (8.6%), and a high frequency of decreased functional alleles in POR (53.9%) and SLCO1B3 (34.9%) genes. This study enhances our understanding of pharmacogenomic profiling of 26 non‐VIPGx genes of notable clinical importance in the Thai population. However, further validation with additional computational and reference genotyping methods is necessary, and novel alleles identified in this study should undergo further orthogonal validation.