Biology subjects

Charoensawan, V.

Publications and source records attributed to Charoensawan, V..

6 recordsLinked to original sources

bioRxiv2026

A Community-Driven Single-Cell PBMC Reference Integrating Landmark Datasets Spanning Health and Disease

Blood provides an accessible window into human health, yet the absence of a peripheral blood mononuclear cells (PBMCs) reference with standardized immune cell annotations has constrained comparisons between single-cell RNA sequencing (scRNAseq) studies. Here, we present HARP (Human Cell Atlas Reference for PBMCs), an integrated atlas of ~9 million PBMCs from >2,600 donors across 15 studies spanning four continents, encompassing diverse populations, neonates to 97 years, across health and diverse immune-related diseases. We developed optimized integration workflows, including novel label-free metrics to assess integration quality, and generated community-driven consensus annotations for 192 immune cell subsets, identifying rare populations representing as few as 0.004% of PBMCs. HARP reveals coordinated cellular modules associated with age, sex, and disease, identifies female-biased interferon and inflammatory gene programs and their perturbation by COVID-19, and uncovers a novel sexual dimorphism in prostaglandin signaling. Finally, we introduce scTiger, a hierarchical label-transfer framework that accurately projects these 192 cell annotations onto ~18 million additional PBMCs, providing a robust and transferable reference for harmonizing future PBMC studies. HARP provides a high-resolution community-driven reference atlas for PBMC annotation and analysis, as a basis for emerging clinical applications of single-cell genomics.

immunology↗

bioRxiv2026

Cellular Complexity and Systemic Immune Profiles across Ancestral Diversity in Thailand and Mainland Southeast Asia

Mainland Southeast Asia (MSEA) remains under-represented in global immunogenomic references despite its extensive genetic heterogeneity. We present the first single-cell immune atlas of an MSEA population, utilizing Thai individuals from the Asian Immune Diversity Atlas (AIDA) as a representative cohort. We demonstrate that the Thai population is highly genetically diverse, reflecting its history as a geographic nexus for Asian admixture. By integrating single-cell transcriptomics with high-resolution genotyping, we show that genetic ancestry significantly shapes innate immune profiles, specifically CD14+ monocytes, highlighting potential evolutionary adaptations to regional pathogens. We identify specific sex-by-ancestry interactions that may drive the baseline activation of pro-inflammatory pathways in females, providing a long-sought cellular rationale for the high prevalence of autoimmune disorders observed in Southeast Asian populations. Ultimately, our study reveals that population-specific genetic architecture dictates immune heterogeneity often missed by self-reported ethnicity or country of origin, providing a critical immunogenomic reference for precision medicine in MSEA regions.

systems biology↗

bioRxiv2020

Predicting the impact of sequence motifs on gene regulation using single-cell data

BackgroundBinding of transcription factors (TFs) at proximal promoters and distal enhancers is central to gene regulation. Yet, identification of TF binding sites, also known as regulatory motifs, and quantification of their impact on gene expression remains challenging. ResultsHere we infer putative regulatory motifs along with their cell type-specific importance using a convolutional neural network trained on single-cell data. Comparison of the importance score to expression levels across cells allows us to identify the TFs most likely to be binding at a given motif. Using multiple mouse tissues we obtain a model with cell type resolution which explains 29% of the variance in gene expression. Finally, by applying scover to distal enhancers identified using scATAC-seq from the mouse cerebral cortex we characterize changes in distal regulatory motifs during development. ConclusionsIt is possible to identify regulatory motifs as well as their importance from single-cell data using a neural network model where all of the parameters and outputs are easily interpretable to the user.

bioinformatics↗

bioRxiv2020

Role of PIF4 and FLC in controlling flowering time under daily variable temperature profile

Initiation of flowering is a crucial developmental event that requires both internal and environmental signals to determine when floral transition should occur to maximize reproductive success. Ambient temperature is one of the key environmental signals that highly influence flowering time, not only seasonally but also in the context of drastic temperature fluctuation due to global warming. Molecular mechanisms of how high or low constant temperatures affect the flowering time have been largely characterized in the model plant Arabidopsis thaliana; however, the effect of natural daily variable temperature outside laboratories is only partly explored. Several groups of flowering genes have been shown to play important roles in temperature responses, including two temperature-responsive transcription factors (TFs), namely PHYTOCHROME INTERACTING FACTOR 4 (PIF4) and FLOWERING LOCUS C (FLC), that act antagonistically to regulate flowering time by activating or repressing floral integrator FLOWERING LOCUS T (FT). In this study, we have demonstrated that the daily variable temperature (VAR) causes early flowering in both natural accessions Col-0, C24 and their late flowering hybrid C24xCol, which carries both functional floral repressor FLC and its activator FRIGIDA (FRI), as compared to a constant temperature (CON). The loss-of-function mutation of PIF4 exhibits later flowering in VAR, suggesting that PIF4 at least in part, contributes to acceleration of flowering in response to the daily variable temperature. We find that VAR increases PIF4 transcription at the end of the day when temperature peaks at 32 {degrees}C. The FT transcription is also elevated in VAR, as compared to CON, in agreement with earlier flowering observed in VAR. In addition, VAR causes a decrease in FLC transcription in 4-week-old plants, and we further show that overexpression of PIF4 can reduce FLC transcription, suggesting that PIF4 might also regulate FT indirectly through the repression of FLC. To further conceptualize an overall model of gene regulatory mechanisms involving PIF4 and FLC in controlling flowering in response to temperature changes, we construct a co-expression - transcriptional regulatory network by combining publicly available transcriptomic data and gene regulatory interactions of our flowering genes of interest and their partners. The network model reveals the conserved and tissue-specific regulatory functions of 62 flowering-time-relating genes, namely PIF4, PIF5, FLC, ELF3 and their immediate neighboring genes, which can be useful for confirming and predicting the functions and regulatory interactions between the key flowering genes.

plant biology↗

bioRxiv2019

DEK influences the trade-off between growth and arrest via H2A.Z-nucleosomes in Arabidopsis

The decision of whether to grow and proliferate or to restrict growth and develop resilience to stress is a key biological trade-off. In plants, constitutive growth results in increased sensitivity to environmental stress1,2. The underlying mechanisms controlling this decision are however not well understood. We used temperature as a cue to discover regulators of this process in plants, as it both enhances growth and development rates within a specific range and is also a stress at extremes. We found that the conserved chromatin-associated protein DEK plays a central role in balancing the response between growth and arrest in Arabidopsis, and it does this via H2A.Z-nucleosomes. DEK target genes show two distinct categories of chromatin architecture based on the distribution of H2A.Z in +1 nucleosome and gene body, and these predict induction or repression by DEK. We show that these chromatin signatures of DEK target genes are conserved in human cells, suggesting that DEK may act through an evolutionarily conserved mechanism to control the balance between growth and arrest in plants and animals.

plant biology↗

bioRxiv2017

The G-box transcriptional regulatory code in Arabidopsis

Plants have significantly more transcription factor (TF) families than animals and fungi, and plant TF families tend to contain more genes--these expansions are linked to adaptation to environmental stressors (1, 2). Many TF family members bind to similar or identical sequence motifs, such as G-boxes (CACGTG), so it is difficult to predict regulatory relationships. We determine that the flanking sequences near G-boxes help determine in vitro specificity, but that this is insufficient to predict the transcription pattern of genes near G-boxes. Therefore, we construct a gene regulatory network that identifies the set of bZIPs and bHLHs that are most predictive of the gene expression of genes downstream of perfect G-boxes. This network accurately predicts transcriptional patterns and reconstructs known regulatory subnetworks. Finally, we present Ara-BOX-cis (araboxcis.org), a website that provides interactive visualisations of the G-box regulatory network, a useful resource for generating predictions for gene regulatory relations.

plant biology↗