METHODS: Genomic DNA obtained from a 55 years old, self-declared healthy, anonymous male of Malay descent was sequenced. The subject's mother died of lung cancer and the father had a history of schizophrenia and deceased at the age of 65 years old. A systematic, intuitive computational workflow/pipeline integrating custom algorithm in tandem with large datasets of variant annotations and gene functions for genetic variations with pharmacogenomics impact was developed. A comprehensive pathway map of drug transport, metabolism and action was used as a template to map non-synonymous variations with potential functional consequences.

PRINCIPAL FINDINGS: Over 3 million known variations and 100,898 novel variations in the Malay genome were identified. Further in-depth pharmacogenetics analysis revealed a total of 607 unique variants in 563 proteins, with the eventual identification of 4 drug transport genes, 2 drug metabolizing enzyme genes and 33 target genes harboring deleterious SNVs involved in pharmacological pathways, which could have a potential role in clinical settings.

RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure).

METHODS: COVID-19 samples that tested positive by reverse transcription polymerase chain reaction and with cycle threshold values <30 were obtained throughout Malaysia. Sequencing of SARS-CoV-2 complete genomes was performed using Illumina, Oxford Nanopore, or Ion Torrent platforms. A total of 6163 SARS-CoV-2 complete genome sequences were generated over the surveillance period. All sequences were submitted to the Global Initiative on Sharing All Influenza Data database.

RESULTS: From June 2021 to January 2022, Malaysia experienced the fourth wave of COVID-19 dominated by the Delta variant of concern, including the original B.1.617.2 lineage and descendant AY lineages. The B.1.617.2 lineage was identified as the early dominant circulating strain throughout the country but over time, was displaced by AY.59 and AY.79 lineages in Peninsular (west) Malaysia, and the AY.23 lineage in east Malaysia. In December 2021, pilgrims returning from Saudi Arabia facilitated the introduction and spread of the BA.1 lineage (Omicron variant of concern) in the country.