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Kurosawa, K.

Publications and source records attributed to Kurosawa, K..

2 recordsLinked to original sources

ncBAF, a chromatin remodeler, enhances PXR-mediated transcriptional activation in the human and mouse liver

Pregnane X receptor (PXR) is one of the key regulators of drug metabolism, gluconeogenesis, and lipid synthesis in the human liver. Activation of PXR by drugs such as rifampicin, simvastatin, and efavirenz causes adverse reactions such as drug{square}drug interaction, hyperglycemia, and dyslipidemia. The inhibition of PXR activation has merit in preventing such adverse events. Here, we demonstrated that bromodomain containing protein 9 (BRD9), a component of non-canonical brahma-related gene 1-associated factor (ncBAF), one of the chromatin remodelers, interacts with PXR. Rifampicin-mediated induction of CYP3A4 expression was attenuated by iBRD9, an inhibitor of BRD9, in human primary hepatocytes and CYP3A/PXR-humanized mice, indicating that BRD9 enhances the transcriptional activation of PXR in vitro and in vivo. Chromatin immunoprecipitation assay reveled that iBRD9 treatment resulted in attenuation of the rifampicin-mediated binding of PXR to the CYP3A4 promoter region, suggesting that ncBAF functions to facilitate the binding of PXR to its response elements. Efavirenz-induced hepatic lipid accumulation was attenuated by iBRD9 in C57BL/6J mice, suggesting that the inhibition of BRD9 would be useful to reduce the risk of efavirenz-induced hepatic steatosis. Collectively, we found that inhibitors of BRD9, a component of ncBAF that plays a role in assisting transactivation by PXR, would be useful to reduce the risk of PXR-mediated adverse reactions.

pharmacology and toxicology↗

Exome-wide benchmark of difficult-to-sequence regions using short-read next-generation DNA sequencing

Next-generation DNA sequencing (NGS) in short-read mode has been recently used for genetic testing in various clinical settings. NGS data accuracy is crucial in clinical settings, and several reports regarding quality control of NGS data, focusing mostly on establishing NGS sequence read accuracy, have been published thus far. Variant calling is another critical source of NGS errors that remains mostly unexplored despite its established significance. In this study, we used a machine-learning-based method to establish an exome-wide benchmark of difficult-to-sequence regions using 10 genome sequence features on the basis of real-world NGS data accumulated in The Genome Aggregation Database (gnomAD) of the human reference genome sequence (GRCh38/hg38). We used the obtained metrics, designated "UNMET score," along with other lines of structural information of the human genome to identify difficult-to-sequence genomic regions using conventional NGS. Thus, the UNMET score could provide appropriate caveats to address potential sequential errors in protein-coding exons of the human reference genome sequence GRCh38/hg38 in clinical sequencing.

genomics↗