Santhilal Subhash
University of Gothenburg
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Publication
Featured researches published by Santhilal Subhash.
Nature Communications | 2015
Tanmoy Mondal; Santhilal Subhash; Roshan Vaid; Stefan Enroth; Sireesha Uday; Björn Reinius; Sanhita Mitra; Arif Mohammed; Alva Rani James; Emily Hoberg; Aristidis Moustakas; Ulf Gyllensten; Steven J.M. Jones; Claes M. Gustafsson; Andrew H. Sims; Fredrik Westerlund; Eduardo Gorab; Chandrasekhar Kanduri
Long noncoding RNAs (lncRNAs) regulate gene expression by association with chromatin, but how they target chromatin remains poorly understood. We have used chromatin RNA immunoprecipitation-coupled high-throughput sequencing to identify 276 lncRNAs enriched in repressive chromatin from breast cancer cells. Using one of the chromatin-interacting lncRNAs, MEG3, we explore the mechanisms by which lncRNAs target chromatin. Here we show that MEG3 and EZH2 share common target genes, including the TGF-β pathway genes. Genome-wide mapping of MEG3 binding sites reveals that MEG3 modulates the activity of TGF-β genes by binding to distal regulatory elements. MEG3 binding sites have GA-rich sequences, which guide MEG3 to the chromatin through RNA–DNA triplex formation. We have found that RNA–DNA triplex structures are widespread and are present over the MEG3 binding sites associated with the TGF-β pathway genes. Our findings suggest that RNA–DNA triplex formation could be a general characteristic of target gene recognition by the chromatin-interacting lncRNAs.
Cancer Cell | 2014
Gaurav Kumar Pandey; Sanhita Mitra; Santhilal Subhash; Falk Hertwig; Meena Kanduri; Kankadeb Mishra; Susanne Fransson; Abiarchana Ganeshram; Tanmoy Mondal; Sashidhar Bandaru; Malin Östensson; Levent M. Akyürek; Jonas Abrahamsson; Susan Pfeifer; Erik Larsson; Leming Shi; Zhiyu Peng; Matthias Fischer; Tommy Martinsson; Fredrik Hedborg; Per Kogner; Chandrasekhar Kanduri
Neuroblastoma is an embryonal tumor of the sympathetic nervous system and the most common extracranial tumor of childhood. By sequencing transcriptomes of low- and high-risk neuroblastomas, we detected differentially expressed annotated and nonannotated long noncoding RNAs (lncRNAs). We identified a lncRNA neuroblastoma associated transcript-1 (NBAT-1) as a biomarker significantly predicting clinical outcome of neuroblastoma. CpG methylation and a high-risk neuroblastoma associated SNP on chromosome 6p22 functionally contribute to NBAT-1 differential expression. Loss of NBAT-1 increases cellular proliferation and invasion. It controls these processes via epigenetic silencing of target genes. NBAT-1 loss affects neuronal differentiation through activation of the neuronal-specific transcription factor NRSF/REST. Thus, loss of NBAT-1 contributes to aggressive neuroblastoma by increasing proliferation and impairing differentiation of neuronal precursors.
Cell Cycle | 2014
Matthieu Meryet-Figuiere; Babak Alaei-Mahabadi; Mohamad Moustafa Ali; Sanhita Mitra; Santhilal Subhash; Gaurav Kumar Pandey; Erik Larsson; Chandrasekhar Kanduri
Transcriptional events during S-phase are critical for cell cycle progression. Here, by using a nascent RNA capture assay coupled with high-throughput sequencing, we determined the temporal patterns of transcriptional events that occur during S-phase. We show that genes involved in critical S-phase-specific biological processes such as nucleosome assembly and DNA repair have temporal transcription patterns across S-phase that are not evident from total RNA levels. By comparing transcription timing with replication timing in S-phase, we show that early replicating genes show increased transcription late in S-phase whereas late replicating genes are predominantly transcribed early in S-phase. Global anti-correlation between replication and transcription timing was observed only based on nascent RNA but not total RNA. Our data provides a detailed view of ongoing transcriptional events during the S-phase of cell cycle, and supports that transcription and replication are temporally separated.
BMC Bioinformatics | 2016
Santhilal Subhash; Chandrasekhar Kanduri
BackgroundHigh-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools to interpret the biological significance of the affected genes from these high-throughput studies. However, currently available functional enrichment tools need to be updated frequently to adapt to new entries from the functional database repositories. Hence there is a need for a simplified tool that can perform functional enrichment analysis by using updated information directly from the source databases such as KEGG, Reactome or Gene Ontology etc.ResultsIn this study, we focused on designing a command-line tool called GeneSCF (Gene Set Clustering based on Functional annotations), that can predict the functionally relevant biological information for a set of genes in a real-time updated manner. It is designed to handle information from more than 4000 organisms from freely available prominent functional databases like KEGG, Reactome and Gene Ontology. We successfully employed our tool on two of published datasets to predict the biologically relevant functional information. The core features of this tool were tested on Linux machines without the need for installation of more dependencies.ConclusionsGeneSCF is more reliable compared to other enrichment tools because of its ability to use reference functional databases in real-time to perform enrichment analysis. It is an easy-to-integrate tool with other pipelines available for downstream analysis of high-throughput data. More importantly, GeneSCF can run multiple gene lists simultaneously on different organisms thereby saving time for the users. Since the tool is designed to be ready-to-use, there is no need for any complex compilation and installation procedures.
Nature Communications | 2018
Mohamad Moustafa Ali; Vijay Suresh Akhade; Subazini Thankaswamy Kosalai; Santhilal Subhash; Luisa Statello; Matthieu Meryet-Figuiere; Jonas Abrahamsson; Tanmoy Mondal; Chandrasekhar Kanduri
Despite improvement in our understanding of long noncoding RNAs (lncRNAs) role in cancer, efforts to find clinically relevant cancer-associated lncRNAs are still lacking. Here, using nascent RNA capture sequencing, we identify 1145 temporally expressed S-phase-enriched lncRNAs. Among these, 570 lncRNAs show significant differential expression in at least one tumor type across TCGA data sets. Systematic clinical investigation of 14 Pan-Cancer data sets identified 633 independent prognostic markers. Silencing of the top differentially expressed and clinically relevant S-phase-enriched lncRNAs in several cancer models affects crucial cancer cell hallmarks. Mechanistic investigations on SCAT7 in multiple cancer types reveal that it interacts with hnRNPK/YBX1 complex and affects cancer cell hallmarks through the regulation of FGF/FGFR and its downstream PI3K/AKT and MAPK pathways. We also implement a LNA-antisense oligo-based strategy to treat cancer cell line and patient-derived tumor (PDX) xenografts. Thus, this study provides a comprehensive list of lncRNA-based oncogenic drivers with potential prognostic value.Although we know lncRNAs play a role in cancer, the identification of clinically relevant and functional lncRNAs is lacking. Here, the authors identify 633 prognostic markers, 570 S-phase cancer-associated lncRNAs, and show SCAT7 regulates FGF/FGFR and PI3K/AKT/MAPK pathways via interaction with hnRNPK/YBX1 complexes.
Cancer Cell | 2018
Tanmoy Mondal; Prasanna Kumar Juvvuna; Agnete Kirkeby; Sanhita Mitra; Subazini Thankaswamy Kosalai; Larissa Traxler; Falk Hertwig; Sara Wernig-Zorc; Caroline Miranda; Lily Deland; Ruth Volland; Christoph Bartenhagen; Deniz Bartsch; Sashidhar Bandaru; Anne Engesser; Santhilal Subhash; Tommy Martinsson; Helena Carén; Levent M. Akyürek; Leo Kurian; Meena Kanduri; Maite Huarte; Per Kogner; Matthias Fischer; Chandrasekhar Kanduri
Trait-associated loci often map to genomic regions encoding long noncoding RNAs (lncRNAs), but the role of these lncRNAs in disease etiology is largely unexplored. We show that a pair of sense/antisense lncRNA (6p22lncRNAs) encoded by CASC15 and NBAT1 located at the neuroblastoma (NB) risk-associated 6p22.3 locus are tumor suppressors and show reduced expression in high-risk NBs. Loss of functional synergy between 6p22lncRNAs results in an undifferentiated state that is maintained by a gene-regulatory network, including SOX9 located on 17q, a region frequently gained in NB. 6p22lncRNAs regulate SOX9 expression by controlling CHD7 stability via modulating the cellular localization of USP36, encoded by another 17q gene. This regulatory nexus between 6p22.3 and 17q regions may lead to potential NB treatment strategies.
Archive | 2018
Tanmoy Mondal; Santhilal Subhash; Chandrasekhar Kanduri
Researchers have recently had a growing interest in understanding the functional role of long noncoding RNAs (lncRNAs) in chromatin organization. Accumulated evidence suggests lncRNAs could act as interphase molecules between chromatin and chromatin remodelers to define the epigenetic code. However, it is not clear how lncRNAs target chromatin remodelers to specific chromosomal regions in order to establish a functionally distinct epigenetic state of chromatin. We developed and optimized chromatin RNA immunoprecipitation (ChRIP) technology to characterize the lncRNAs associated with active and inactive chromatin compartments. Use of ChRIP to identify chromatin-bound lncRNA will further improve our knowledge regarding the functional role of lncRNAs in establishing epigenetic modifications of chromatin.
Nucleic Acids Research | 2018
Santhilal Subhash; Kankadeb Mishra; Vijay Suresh Akhade; Meena Kanduri; Tanmoy Mondal; Chandrasekhar Kanduri
Abstract Recently lncRNAs have been implicated in the sub-compartmentalization of eukaryotic genome via genomic targeting of chromatin remodelers. To explore the function of lncRNAs in the maintenance of active chromatin, we characterized lncRNAs from the chromatin enriched with H3K4me2 and WDR5 using chromatin RNA immunoprecipitation (ChRIP). Significant portion of these enriched lncRNAs were arranged in antisense orientation with respect to their protein coding partners. Among these, 209 lncRNAs, commonly enriched in H3K4me2 and WDR5 chromatin fractions, were named as active chromatin associated lncRNAs (active lncCARs). Interestingly, 43% of these active lncCARs map to divergent transcription units. Divergent transcription (XH) units were overrepresented in the active lncCARs as compared to the inactive lncCARs. ChIP-seq analysis revealed that active XH transcription units are enriched with H3K4me2, H3K4me3 and WDR5. WDR5 depletion resulted in the loss of H3K4me3 but not H3K4me2 at the XH promoters. Active XH CARs interact with and recruit WDR5 to XH promoters, and their depletion leads to decrease in the expression of the corresponding protein coding genes and loss of H3K4me2, H3K4me3 and WDR5 at the active XH promoters. This study unravels a new facet of chromatin-based regulation at the divergent XH transcription units by this newly identified class of H3K4me2/WDR5 chromatin enriched lncRNAs.
Journal of Visualized Experiments | 2017
Santhilal Subhash; Meena Kanduri
The role of long noncoding RNAs (lncRNAs) in cancer is coming to the forefront due to growing interest in understanding their mechanistic functions during cancer development and progression. Despite this, the global epigenetic regulation of lncRNAs and repetitive sequences in cancer has not been well investigated, particularly in chronic lymphocytic leukemia (CLL). This study focuses on a unique approach: the immunoprecipitation-based capture of double-stranded, methylated DNA fragments using methyl-binding domain (MBD) proteins, followed by next-generation sequencing (MBD-seq). CLL patient samples belonging to two prognostic subgroups (5 IGVH mutated samples + 5 IGVH unmutated samples) were used in this study. Analysis revealed 5,800 hypermethylated and 12,570 hypomethylated CLL-specific differentially methylated genes (cllDMGs) compared to normal healthy controls. Importantly, these results identified several CLL-specific, differentially methylated lncRNAs, repetitive elements, and protein-coding genes with potential prognostic value. This work outlines a detailed protocol for an MBD-seq and bioinformatics pipeline developed for the comprehensive analysis of global methylation profiles in highly CpG-rich regions using CLL patient samples. Finally, a protein-coding gene and an lncRNA were validated using pyrosequencing, which is a highly quantitative method to analyze CpG methylation levels to further corroborate the findings from the MBD-seq protocol.
Clinical Epigenetics | 2016
Santhilal Subhash; Per-Ola Andersson; Subazini Thankaswamy Kosalai; Chandrasekhar Kanduri; Meena Kanduri