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Tan, S. X.

Publications and source records attributed to Tan, S. X..

2 recordsLinked to original sources

A chromosome-scale Plasmodium cynomolgi Berok genome reveals a distinct subtelomeric architecture and a highly diverged primate malaria lineage

Plasmodium cynomolgi is the closest relative of P. vivax and the primary experimental model for relapsing malaria, hypnozoite biology, and blood-stage drug susceptibility. Yet existing reference genomes remain fragmented, leaving structurally complex, AT-rich regions largely unresolved. We generated a chromosome-scale genome assembly for the K4-A7 cloned line of P. cynomolgi Berok by combining Hi-C chromosome conformation capture, Oxford Nanopore long reads, PacBio, and Illumina sequencing. The assembly spans 14 chromosomes plus mitochondrial and apicoplast genomes, with only seven unplaced minor contigs, the fewest for any non-P. falciparum Plasmodium genome, and an N50 of 3.06 Mb. Critically, this hybrid strategy resolved approximately 8 Mb of extremely AT-rich (~20% GC) sequence onto chromosomes 4, 8, and 13, anchoring what were previously unplaced or absent contigs into a continuous chromosomal framework. These subtelomere-like expansions (SLEs) constitute ~26.5% of the chromosomal genome and are enriched for PIR/VIR, STP1, variable surface antigen, and methyltransferase pseudogene families. Despite low gene density, SLE-encoded genes are transcriptionally active and show stage-specific expression across the erythrocytic cycle. Integrated lifecycle transcriptomics across 7,006 genes revealed a ~54-hour erythrocytic cycle with a "just-in-time" transcriptional cascade closely resembling that of P. vivax. Phylogenomic analyses and pairwise amino acid comparisons across more than 2,600 single-copy orthologs show that Berok forms a deeply diverged P. cynomolgi lineage, suggesting a distinct subspecies. This assembly establishes a high-resolution genomic foundation for comparative malaria biology, drug discovery, and the study of subtelomeric architecture, host adaptation, and lineage boundaries in primate Plasmodium.

microbiology↗

Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types

Cutaneous squamous cell carcinoma (cSCC), basal cell carcinoma (BCC), and melanoma - the three major skin cancers - collectively comprise over 70% of all cancer cases. Despite their prevalence, much understanding of cellular interactions in the skin cancer microenvironment is needed, both in the outer skin layer where the cancer originates and at the deeper junctional and dermal layers into which it progresses. To address this gap, we integrated 12 complementary spatial and single-cell technologies to generate orthogonally-validated cell signatures, spatial maps, and interactomes for cSCC, BCC, and melanoma. Through comprehensive comparisons and integrating these spatial methods, we provided practical benchmarking guidelines for experimental design and analysis. By identifying keratinocyte cancer cells and melanomas, we found distinct signatures of these cells compared to non-cancer keratinocytes and melanocytes. Spatial integration of transcriptomics, proteomics and glycomics uncovered cancer niches enriched for cancer initiating cells (melanocytes or keratinocytes) and fibroblast and T-cell (MKFT) clusters, with altered tyrosine and pyrimidine metabolism. Ligand-receptor analysis across >700 cell-type combinations and >1.5 million interactions highlighted key roles for CD44, integrins, and collagens, with CD44-FGF2 emerging as a potential therapeutic target. Consistently, melanoma showed strong MFT interactions, validated by Opal Polaris, RNAScope, Proximal Ligation Assay and two additional single-cell spatial platforms (making a total of 14 technologies). For population-scale generalisation, genetic associations from >500,000 individuals were mapped onto spatial skin tissues, identifying SNPs enriched in domains containing melanocytes and T cells and their ligand-receptor pairs, shedding light on functional mechanisms linking genetic heritability to cells within cancer tissue. We built an interactive multiomics resource for exploring spatially-resolved molecular signatures and cellular crosstalk in skin cancer, available at https://skincanceratlas.com.

cancer biology↗