JSJovi Tan Siying

Jovi Tan Siying

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article

Previous Organizations / Institutes

The organizations / institutes from the scholar's other articles in the past ten years


Jovi Tan Siying has a total of 140 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Identification of Cyclin L1 as a Host Factor Regulating Hepatitis B Virus Replication

    by Collins Oduor Owino, Balakrishnan Chakrapani Narmada, Gian Yi Lin, Pauline Poh Kim Aw, Nivrithi Ganesh, Jovi Tan Siying, Marie-Laure Plissonnier, Thangavelu Thangavelu Matan, Niranjan Shirgaonkar, Pablo Bifani, et al.

    Background and Aims: Understanding regulatory interactions between hepatitis B virus (HBV) and host factors is essential for the development of next generation host-directed antiviral therapies and the achievement of a functional HBV cure. Here, we investigated HBV-induced alterations in host gene expression in primary human hepatocytes (PHH) to identify host factors exploited by the virus for replication and persistence. Whole-transcriptome sequencing (WTS) of HBV-infected PHH identified host pathways with potential roles in the HBV life cycle. RNA interference-based functional screening of dysregulated candidate genes identified cyclin L1 (CCNL1) as a key host factor. RNAi-mediated knockdown of CCNL1 reduced HBV gene expression, including hepatitis B surface antigen (HBsAg). Mechanistically, CCNL1 regulates phosphorylation of the C-terminal domain (CTD) of RNA polymerase II (RNAPII) at serine 2 (S2), consistent with a role in transcriptional regulation. CCNL1 knockdown further reduced the binding of total and phospho- (Ser2/Ser5) RNAPII, pan-acetylated histone H3 (H3ac), and H3K27ac to HBV covalently closed circular DNA (cccDNA), indicating impaired cccDNA-dependent transcription. In addition, CCNL1 expression was elevated in chronic hepatitis B patients compared with those with resolved infection. Collectively, these data demonstrate that CCNL1 promotes HBV transcription and replication through modulation of RNAPII phosphorylation and chromatin-associated transcriptional activity, identifying CCNL1 as a potential host susceptibility factor for HBV. Importance: Hepatitis B virus infection remains a major threat to human health in areas with high prevalence. There is need to fully understand the complex interactions between the virus and human host factors/processes to support ongoing efforts to develop anti-HBV therapies that can be used with existing therapies to achieve a better cure. HBV relies on host cellular factors and biological processes to establish and maintain efficient infection, making host–virus interactions attractive targets for therapeutic intervention. Thus, identifying host factors that support and/or restrict HBV infection is essential for understanding the molecular basis of chronic HBV infection and for developing host-targeting anti-HBV drugs. This study identifies cyclin L1 (CCNL1) as a host susceptibility factor that promotes HBV transcription and replication through regulation of RNA polymerase II activity and or post-transcriptional mechanisms.

  • Open Access

    LSTrAP-Crowd: Prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data

    by Benedict Hew, Qiao Wen Tan, William Goh, Jonathan Wei Xiong Ng, Kenny Koh, Ryan Chieh Feng Rugdee, Zheng Kai Teng, Jun Xiong Tan, Xi Yei, Qing Rong Tan, et al.

    Bacterial resistance to antibiotics is a growing problem that is projected to cause more deaths than cancer in 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the bacterial ribosomes, proteins that are involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data. The data can be used to identify other vulnerabilities or bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowdsourced.