Biology subjects

Chatsirisupachai, K.

Publications and source records attributed to Chatsirisupachai, K..

9 recordsLinked to original sources

bioRxiv2025

Molecular co-accessibility identifies coordinated regulation between distant cis-regulatory elements

In metazoans, gene expression is typically regulated by a cis-regulatory landscape (CRL) composed of a promoter and multiple enhancers. How these cis-regulatory elements (CREs) coordinate their function across large genomic distances remains unclear. For example, is the simultaneous activation of multiple enhancers required to promote transcription? Here, we combined single-molecule footprinting with long-read sequencing to quantify how often chromatin accessibility and transcription factor binding co-occur across entire CRLs in the Drosophila genome. Analysis of thousands of individual DNA molecules at each locus revealed that CREs form a specific network with shared single-molecule chromatin accessibility profiles. Co-accessibility is not limited to adjacent CREs, and is frequently observed between CREs brought into proximity by chromatin looping. Co-accessible CREs exhibit strong coordination in their cell type-specific accessibility, linking enhancer activity with transcription activation. Our data uncover dependencies between CREs genome-wide, and suggest that coordinated enhancer activation is a widespread mechanism regulating gene expression.

genomics↗

bioRxiv2025

Cumulative TF binding and H3K27 Acetylation drive enhancer activation frequency

In eukaryotes, transcription factors (TFs) must continuously compete with nucleosomes to access their binding sites, leading to cell-to-cell variability in chromatin accessibility at regulatory regions. Although critical to understand enhancer function in transcription, the mechanisms that define how frequently an enhancer is active in a cell population remain unclear. Here, we used single molecule footprinting to quantify the frequency at which chromatin is accessible at enhancers in response to TF perturbations, and changes of their chromatin environment. We find that individually most TFs open chromatin in a small fraction of the cells, and that cumulative TF binding controls enhancers activation frequency. Moreover, testing the functionality of hundreds of enhancers when inserted at an ectopic genomic location identifies H3K27Ac as a chromatin mark required for their full activation. Our data support a model where enhancer activation frequency depends on the cumulative function of multiple TFs, enhanced by activating chromatin marks.

molecular biology↗

bioRxiv2024

Mammalian promoters are characterised by low occupancy and high turnover of RNA polymerase II

The general transcription machinery and its occupancy at promoters are highly conserved across metazoans. This contrasts with the kinetics of mRNA production that considerably differ between model species such as Drosophila and mouse. The molecular basis for these kinetic differences is currently unknown. Here, we used Single Molecule Footprinting to measure RNA Polymerase II (Pol II) occupancy, the fraction of DNA molecules bound, at promoters in mouse and Drosophila cell lines. Single molecule data reveals that Pol II occupancy is on average 3-5 times more frequent at transcriptionally active Drosophila promoters than active mouse promoters. Kinetic modelling of the occupancy states suggests that these differences in Pol II occupancy are determined by the ratio between the transcription initiation and Pol II turnover rates. We used chemical perturbation of transcription initiation to determine Pol II turnover rate in both species. Integration of these data into the model shows that infrequent Pol II occupancy in mammals is explained by the combination of high Pol II turnover and low transcription initiation rates.

genomics↗

bioRxiv2023

Human Ageing Genomic Resources: updates on key databases in ageing research

Ageing is a complex and multifactorial process. For two decades, the Human Ageing Genomic Resources (HAGR) have aided researchers in the study of various aspects of ageing and its manipulation. Here we present the key features and recent enhancements of these resources, focusing on its six main databases. One database, GenAge, focuses on genes related to ageing, featuring 307 genes linked to human ageing and 2205 genes associated with longevity and ageing in model organisms. AnAge focuses on ageing, longevity, and life-history across animal species, containing data on 4645 species. DrugAge includes information about 1097 longevity drugs and compounds in model organisms such as mice, rats, flies, worms, and yeast. GenDR provides a list of 214 genes associated with the life-extending benefits of dietary restriction in model organisms. CellAge contains a catalogue of 866 genes associated with cellular senescence. The LongevityMap serves as a repository for genetic variants associated with human longevity, encompassing 3144 variants pertaining to 884 genes. Additionally, HAGR provides various tools as well as gene expression signatures of ageing, dietary restriction, and replicative senescence based on meta-analyses. Our databases are integrated, regularly updated, and manually curated by experts. HAGR is freely available online (https://genomics.senescence.info/).

bioinformatics↗

bioRxiv2022

Pan-cancer transcriptomic analysis reveals a tissue-specific loss of identity

Understanding changes in cell identity in cancer and ageing is of great importance. In this work, we analyzed how gene expression changes in human tissues are associated with tissue specificity during cancer and ageing using transcriptome data from TCGA and GTEx. We found a loss of cell identity during ageing in around 40% of tissues. In cancer, we observed a pattern of downregulation of genes specific to the tissue of origin of the tumor for most cancer types. Moreover, we observed an activation of genes not usually expressed in a tissue as well as an upregulation of genes specific to other tissues in cancer. These patterns in cancer were associated with patient survival. The age of the patient, however, does not influence these patterns. Thus, we identified a moderate but statistically significant pattern of loss of cell identity in ageing, and a clear pattern in cancer, where during tumorigenesis, cells express genes specific to other organs while suppressing the expression of genes from their original tissue. The loss of cellular identity observed in cancer is associated with prognosis and is not influenced by age, suggesting that it is a crucial stage in carcinogenesis.

bioinformatics↗

bioRxiv2021

GeneFriends 2021: Updated co-expression databases and tools for human and mouse genes and transcripts

Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have updated the GeneFriends database. Here, we present the latest version of GeneFriends, which includes updated gene and transcript co-expression networks based on RNA-seq data from 46,475 human and 34,322 mouse samples. GeneFriends is freely available at http://www.genefriends.org/

genomics↗

bioRxiv2020

An Integrative Analysis of the Age-Associated Genomic, Transcriptomic and Epigenetic Landscape across Cancers

Age is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterised genomic, transcriptomic and epigenetic alterations in relation to patients age across cancer types. We showed that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations were identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences were found in gliomas and endometrial cancer. We identified age-related global transcriptomic changes and demonstrated that these genes are controlled by age-associated DNA methylation changes. This study provides a comprehensive view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.

cancer biology↗

bioRxiv2019

A Multidimensional Systems Biology Analysis of Cellular Senescence in Ageing and Disease

Cellular senescence, a permanent state of replicative arrest in otherwise proliferating cells, is a hallmark of ageing and has been linked to ageing-related diseases like cancer. Senescent cells have been shown to accumulate in tissues of aged organisms which in turn can lead to chronic inflammation. Many genes have been associated with cell senescence, yet a comprehensive understanding of cell senescence pathways is still lacking. To this end, we created CellAge (http://genomics.senescence.info/cells), a manually curated database of 279 human genes associated with cellular senescence, and performed various integrative and functional analyses. We observed that genes promoting cell senescence tend to be overexpressed with age in human tissues and are also significantly overrepresented in anti-longevity and tumour-suppressor gene databases. By contrast, genes inhibiting cell senescence overlapped with pro-longevity genes and oncogenes. Furthermore, an evolutionary analysis revealed a strong conservation of senescence-associated genes in mammals, but not in invertebrates. Using the CellAge genes as seed nodes, we also built protein-protein interaction and co-expression networks. Clusters in the networks were enriched for cell cycle and immunological processes. Network topological parameters also revealed novel potential senescence-associated regulators. We then used siRNAs and observed that of 26 candidates tested, 19 induced markers of senescence. Overall, our work provides a new resource for researchers to study cell senescence and our systems biology analyses provide new insights and novel genes regarding cell senescence.

systems biology↗

bioRxiv2019

A Human Tissue-Specific Transcriptomic Analysis Reveals that Ageing Hinders Cancer and Boosts Cellular Senescence

Ageing is the biggest risk factor for cancer, but the mechanisms linking these two processes remain unclear. We compared genes differentially expressed with age and genes differentially expressed in cancer among nine human tissues. In most tissues, ageing and cancer gene expression surprisingly changed in the opposite direction. These overlapping gene sets were related to several processes, mainly cell cycle and the immune system. Moreover, cellular senescence signatures derived from a meta-analysis changed in the same direction as ageing and in the opposite direction of cancer signatures. Therefore, transcriptomic changes in ageing and cellular senescence might relate to a decrease in cell proliferation, while cancer transcriptomic changes shift towards an increase in cell division. Our results highlight the complex relationship between ageing, cancer and cellular senescence and suggest that in most human tissues ageing processes and senescence act in tandem while being detrimental to cancer. Our work challenges the traditional view concerning the relationship between cancer and ageing and suggests that ageing processes may hinder cancer development.

cancer biology↗