Biology subjects

He, S.

Publications and source records attributed to He, S..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Small non-coding RNAs encapsulating mammalian cells fuel innate immunity

Cell surface RNAs, notably glycoRNAs, have been reported, yet the exact surface RNA compositions in different cell types remain unclear. Here, we introduce a comprehensive suite of methodologies for imaging, profiling, quantifying, and exploring the biological functions of specific surface RNAs. Utilizing these techniques, we have identified diverse non-coding RNAs present on mammalian cell surfaces. We confirm the membrane anchorage and quantify the abundance of several representative RNAs on human primary cells. Notably, we discover a significant prevalence of Y RNAs on the surfaces of human monocytes and B cells. We find that these Y RNAs on human monocyte surfaces enrich extracellular histones, regulating interleukin-6 (IL-6) gene expression and subsequent protein secretion upon histone stimulation via NF-{kappa}B and AP-1 activation. Our study not only presents effective approaches for investigating surface RNAs, but also uncovers a previously unrecognized immune activation pathway mediated by surface Y RNAs on monocytes. In briefA comprehensive profiling of surface RNAs across diverse mammalian blood cell types unveil abundant Y RNAs on the surface of human monocytes. Subsequent investigations uncover functional roles of surface Y RNAs on monocytes as "immune sentinel" to enrich extracellular histones, revealing a previously unknown pathway of innate immune activation. HighlightsNovel methodologies for cell surface RNA mapping, validation and functional interrogation. Sequencing of surface RNAs across various mammalian blood cell types offers detailed maps of surface RNAs. Abundant Y RNAs localize on human monocyte surfaces and capture extracellular histones released by adjacent ruptured cells. Surface Y RNAs enrich extracellular histones to facilitate transcription and secretion of IL-6 through NF-{kappa}B and AP-1 activation.

molecular biology↗

bioRxiv2025

LncMamba: A Deep Learning Model for lncRNA Localization Prediction Based on the Mamba Model

Accurate prediction of long non-coding RNA (lncRNA) subcellular localization is crucial for understanding its biological functions. In this study, we propose a novel deep learning framework, LncMamba, which utilizes a two-layer FPN network for multi-scale feature extraction and introduces the Mamba network to lncRNA localization prediction tasks for the first time. Based on this, we improved the localization-specific attention mechanism, allowing the model to more effectively focus on key sequence motifs related to localization. Additionally, through statistical analysis of localization motifs, we revealed the potential relationship between nucleotide motifs and lncRNA subcellular localization.The code is available at: https://anonymous.4open.science/r/lncMamba-731F.

bioinformatics↗

bioRxiv2025

CD34 serves as an intrinsic innate immune guardrail protecting stem cells from replicating retroviruses

Stem cells are highly resistant to viral infection compared to their differentiated progeny, and this resistance is associated with stem cell-specific restriction factors and intrinsic interferon stimulated genes (ISGs). In HIV infection, proviral DNA has been detected in certain bone marrow hematopoietic stem cells, yet widespread stem cell infection in vivo is restricted. Intriguingly, exposing bone marrow stem cells to HIV in vitro led to viral replication selectively only in the CD34- population, but not in the CD34+ cells. The mechanism dictating this CD34-based HIV restriction remained a mystery, especially since HIV has a capacity to antagonize restriction factors and ISGs. CD34 is a common marker of hematopoietic stem and progenitor cells. Here, we report the intrinsic antiviral properties of CD34. Expression of CD34 in HIV-1 producer cells results in the loss of progeny virion infectivity. Conversely, removal of CD34 using CRISPR/Cas9 knockout or stem cell differentiation cytokines promotes HIV-1 replication in stem cells. These results suggest that in addition to restriction factors and intrinsic ISGs, CD34 serves as a host innate protection preventing retrovirus replication in stem cells. Mechanistically, CD34 does not block viral entry, integration, and release. Instead, it becomes incorporated onto progeny virions, which inactivates virus infectivity. These findings offer new insights into innate immunity in stem cells, and highlight intriguing retrovirus-host interactions in evolution.

immunology↗

bioRxiv2025

Obesity Increases Atherosclerosis Susceptibility via Inter-tissue miR-30e-SLC7A11 Axis

BackgroundWith obesity as a risk factor for atherosclerotic disease, recent research suggests that adipose tissue in obese animal models and humans can generate endocrine-like molecules that affect arterial health later on. Previous studies showed that microRNA-30e (miR-30e) level is elevated in atherosclerosis and solute carrier family 7 member 11 (SLC7A11), a cystine/glutamate transporter, is involved in atherogenesis. However, whether an endocrine-like link between the adipose-derived miR-30e-5p and SLC7A11 in the vascular endothelium can lead to obesity-caused atherosclerosis is unknown. MethodsMiRNA data mining and RT-PCR validations were used to demonstrate the positive association among serum level of miR-30e-5p, obesity, and coronary arterial disease in human patients. Transcriptomics (RNA-seq and single-nucleus RNA-seq), metabolomics, and in silico analysis were used to establish a miR-30e-5p-SLC7A11 regulation of central carbon metabolism, mitochondrial and endothelial cell (EC) function. Mouse models with EC-specific Slc7a11 knockout (EC-Slc7a11-/-) and gain or loss of function of miR-30e-5p were used to elucidate the detrimental role of this endocrine-like axis in obesity-related atherosclerosis. ResultsThe level of adipocyte-derived miR-30e-5p was significantly upregulated in obese humans with coronary artery disease and obese and atherosclerotic mice. Via serum exosomes, the adipocyte-generated miR-30e-5p targeted SLC7A11 mRNA in vascular ECs. SLC7A11 deficiency due to miR-30e-5p targeting dysregulated glutamate/cystine metabolism increased glycolysis, reduced oxidative phosphorylation, and impaired mitochondrial function. The EC dysfunction could be rectified by SLC7A11 overexpression or miR-30e-5p antagonism. Exogenously delivered miR-30e-5p phenocopied the increased atherosclerosis in EC-Slc7a11-/- mice. In contrast, miR-30e-5p antagomir treatment reduced atherosclerosis in Apoe-/- and ob/ob mice. ConclusionOur multi-omics approaches demonstrates that the adipose-derived miR-30e-5p downregulated SLC7A11 mRNA in ECs via tissue crosstalk. The resulting EC dysfunction led to obesity-related atherosclerosis in mice. These findings underscore a causality between obesity and atherosclerosis in the context of cardiovascular-kidney-metabolic syndrome.

molecular biology↗

bioRxiv2025

Sky islands of Southwest China. II: Unraveling hidden species diversity of talpid moles using phylogenomics and skull-based deep learning

The sky islands of Southwest China, characterized by dramatic topographical and climatic variations, are prominent hotspots of biodiversity and endemism. Organisms inhabiting middle-to-high elevation habitats in this region are geographically isolated within distinct mountain chains, which over geological time have been subjected to isolation-by-distance and isolation-by-environment. These processes have led to profound allopatric diversification and strong phylogeographic structuring, resulting in a plethora of genetically distinct cryptic species, as is becoming increasingly evident for many small mammal families. However, morphological conservatism can pose significant challenges in delineating these clades within species complexes. In this study, we leverage artificial intelligence technologies to unravel the hidden species diversity of moles (family Talpidae) in Southwest Chinas sky islands. We first employed ultraconserved elements (UCEs) to investigate the evolutionary history of talpid moles, conducted molecular species delimitation using mitochondrial and multi-locus genes, and utilized both traditional and geometric morphometrics to examine their morphological disparity. To address the challenges of morphology based cryptic species identification, we developed a deep learning Hierarchical Identification of Species NETwork (HIS-NET) to create an image-based model that analyzes four different views of the skull/mandible to distinguish genera and species hierarchically. HIS-NET not only achieved expert-level accuracy in species identification but also effectively distinguished between cryptic and known species, aiding in the identification of key morphological variation intervals. Our results support the recognition of allopatrically distributed taxa in Euroscaptor and Parascaptor as full species, thereby confirming that species diversity in this region remains underestimated. Beyond advancing our understanding of speciation in this unique and fragile ecosystem, our study serves as a proof-of-concept, demonstrating the power of deep learning in unraveling hidden biodiversity within this and other species complexes.

zoology↗

bioRxiv2025

The distinct role of human PIT in attention control

Attentional distribution depends on both endogenous and exogenous processes, but how they interact in attention allocation remains unclear. The attentional priority map, jointly determined by stimulus saliency and task relevance, provides a framework for investigating their interplay. We propose that the human posterior inferotemporal cortex (hPIT), located near object-processing cortical areas, serves as an attentional priority map. Using fMRI with behavioral tasks, we show that hPIT shows stronger attentional modulation than classical attention regions across motion, color, and shape tasks. hPIT shows lateralized attentional enhancement even in the absence of visual input, with further elevated modulation in the presence of stimuli, indicating its integrated role in priority control. Furthermore, its modulation is invariant to stimulus category but sensitive to attentional demands, and the region is functionally connected to both dorsal and ventral attentional networks. These findings highlight the hPIT as an integrator in attentional control and provide critical insights into the brains strategy for optimizing responses to the environment.

neuroscience↗

bioRxiv2025

Literature-scaled immunological gene set annotation using AI-powered immune cell knowledge graph (ICKG)

Large scale application of single-cell and spatial omics in models and patient samples has led to the discovery of many novel gene sets, particularly those from an immunotherapeutic context. However, the biological meaning of those gene sets has been interpreted anecdotally through over-representation analysis against canonical annotation databases of limited complexity, granularity, and accuracy. Rich functional descriptions of individual genes in an immunological context exist in the literature but are not semantically summarized to perform gene set analysis. To overcome this limitation, we constructed immune cell knowledge graphs (ICKGs) by integrating over 24,000 published abstracts from recent literature using large language models (LLMs). ICKGs effectively integrate knowledge across individual, peer-reviewed studies, enabling accurate, verifiable graph-based reasoning. We validated the quality of ICKGs using functional omics data obtained independently from cytokine stimulation, CRISPR gene knock-out, and protein-protein interaction experiments. Using ICKGs, we achieved rich, holistic, and accurate annotation of immunological gene sets, including those that were unannotated by existing approaches and those that are in use for clinical applications. We created an interactive website (https://kchen-lab.github.io/immune-knowledgegraph.github.io/) to perform ICKG-based gene set annotations and visualize the supporting rationale.

bioinformatics↗

bioRxiv2025

Composition and RNA binding specificity of metazoan RNase MRP

Ribonuclease (RNase) MRP is a conserved RNA-based enzyme that is essential for maturation of ribosomal RNA (rRNA) in eukaryotes. However, the composition and RNA substrate specificity of this multisubunit ribonucleoprotein complex in higher eukaryotes remain a mystery. Here, we identify NEPRO and C18ORF21 as constitutive subunits of metazoan RNase MRP. Both proteins are specific to RNase MRP and are the only ones distinguishing this enzyme from the closely related RNase P, which selectively cleaves transfer RNA-like substrates. We find that NEPRO and C18ORF21 each form a complex with all other subunits of RNase MRP, stabilize its catalytic RNA, and are required for rRNA maturation and cell proliferation. We harness our discovery to identify a full suite of in vivo RNA targets of each enzyme, including positions of potential cleavage sites at nucleotide resolution. These findings resolve the general composition of metazoan RNase MRP, illuminate its RNA binding specificity, and provide valuable assets for functional exploration of this essential eukaryotic enzyme.

molecular biology↗

bioRxiv2025

SUMO2 Promotes Histone Pre-mRNA Processing by Stabilizing Histone Locus Body Interactions and Facilitating U7 snRNP Assembly

Histone mRNAs are the only non-polyadenylated mRNAs in eukaryotic cells and require specialized processing in the histone locus body (HLB), a nuclear body where essential processing factors, including the U7 snRNP, are concentrated. Recent studies have revealed that misregulation of histone pre-mRNA processing can lead to polyadenylation of histone mRNAs and disruption of histone protein homeostasis. Despite links to human disease, the factors contributing to polyadenylation of histone mRNAs and the mechanisms underlying HLB assembly and U7 snRNP biogenesis remain unclear. Here, we report novel functions of the small ubiquitin-related modifier 2 (SUMO2) in promoting histone pre-mRNA processing. Using a SUMO2 knockout osteosarcoma cell line, we identified a defect in 3 end cleavage and a global increase in histone mRNA polyadenylation. Subsequent analysis of HLBs revealed increased dynamics and reduced levels of the U7 snRNP complex. By over-expressing U7 snRNP-specific components, Lsm11 and U7 snRNA, we rescued U7 snRNP levels and processing defects in SUMO2 knockout cells. Through analysis of Lsm11, we identified a SUMO-interacting motif in its N-terminus required for efficient formation of U7 snRNP. Collectively, we demonstrate that SUMO2 promotes histone pre-mRNA 3 end processing by stabilizing HLB interactions and facilitating U7 snRNP assembly.

molecular biology↗

bioRxiv2025

Systematic silencing of oncogenic fusion transcripts with ultra-precise CRISPR-Cas13b

Oncogenic gene fusions are key drivers of cancer, yet most remain untargetable by current therapies. Here, we establish CRISPR-PspCas13b as a personalizable platform for systematic silencing of various fusion transcripts. We reveal that recognition and cleavage of the breakpoint sequence by PspCas13b disrupts the fusion transcript, resulting in unexpected RNA nicking and ligation near the cleavage site, which generates out-of-frame, translation-incompetent transcripts. This approach efficiently degrades canonical and drug-resistant BCR::ABL1 mutants (e.g., T315I), a primary cause of resistance to tyrosine kinase inhibitors (TKIs) and relapse in chronic myeloid leukemia (CML). Silencing T315I BCR::ABL1 mRNA in drug-resistant CML cells triggers extensive transcriptomic, proteomic, and phosphoproteomic remodelling, causing erythroid differentiation and apoptosis. Beyond BCR-ABL1 mutants, personalized design of PspCas13b effectively silences other undruggable fusions, including RUNX1::RUNX1T1 and EWSR1::FLI1, key drivers in acute myeloid leukemia and in Ewing sarcoma, respectively. Collectively, this study establishes a framework for systematic, precise, and personalizable targeting of otherwise undruggable or drug-resistant oncogenic transcripts.

molecular biology↗

bioRxiv2025

Decoding yeast transcriptional regulation via a data- and mechanism-driven distributed large-scale network model

The complex transcriptional regulatory relationships among genes influence gene expression levels and play crucial roles in determining cellular phenotypes. Here, we present a novel distributed large-scale transcriptional regulatory neural network model (DLTRNM) by integrating prior knowledge into the reconstruction of pre-trained machine learning models followed with fine-tuning. Taken S. cerevisiae as the example, the transcriptional regulatory relationships, carefully compiled and documented, are utilized to define interactions between TFs and their TGs within DLTRNM. Subsequently, DLTRNM is pre-trained on pan-transcriptomic data and fine-tuned with time-series data, enabling it to accurately predict dynamic regulatory correlations between TFs and TGs, such as simulating TG responses by tuning the expression of TFs. In addition, DLTRNM can assist in identifying potential key TFs for a subset of genes, thus simplifying the complex and interrelated transcriptional regulatory networks (TRN). Based on the key TFs, it can also refine previously reported transcriptional regulatory subnetworks and highlight the core regulatory networks. DLTRNM offers a powerful tool for studying transcriptional regulation with reduced computational demands and enhanced interpretability. Thus, this study represents a significant step forward in systems biology for understanding the complicated transcriptional regulation within cells.

bioinformatics↗

bioRxiv2025

Learning single-cell spatial context through integrated spatial multiomics with CORAL

Cellular organization is central to tissue function and homeostasis, influencing development, disease progression, and therapeutic outcomes. The emergence of spatial omics technologies, including spatial transcriptomics and proteomics, has enabled the integration of molecular and histological features within tissues. Analyzing these multimodal data presents unique challenges, including variable resolutions, imperfect tissue alignment, and limited or variable spatial coverage. To address these issues, we introduce CORAL, a probabilistic deep generative model that leverages graph attention mechanisms to learn expressive, integrated representations of multimodal spatial omics data. CORAL deconvolves low-resolution spatial data into high-resolution single-cell profiles and detects functional spatial domains. It also characterizes cell-cell interactions and elucidates disease-relevant spatial features. Validated on synthetic data and experimental datasets, including Stero-CITE-seq data from mouse thymus, and paired CODEX and Visium data from hepatocellular carcinoma, CORAL demonstrates robustness and versatility. In hepatocellular carcinoma, CORAL uncovered key immune cell subsets that drive the failure of response to immunotherapy, highlighting its potential to advance spatial single-cell analyses and accelerate translational research.

bioinformatics↗

bioRxiv2025

Cryptocercus genomes expand knowledge of adaptations to xylophagy and termite sociality

Subsociality and wood-eating or xylophagy are understood as key drivers in the evolution of eusociality in Blattodea (cockroaches and termites), two features observed in the cockroach genus Cryptocercus, the sister group of all termites. We present and analyse two new high-quality genomes from this genus, C. punctulatus from North America and C. meridianus from Southeast Asia, to explore the evolutionary transitions to xylophagy and subsociality within Blattodea. Our analyses reveal evidence of relaxed selection in both Cryptocercus and termites, indicating that a reduction in effective population size may have occurred in their subsocial ancestors. These findings challenge the expected positive correlation between dN/dS ratios and social complexity, as Cryptocercus exhibits elevated dN/dS values that may exceed those of eusocial termites. Additionally, we identify positive selection on mitochondrial ribosomal proteins and components of the NADH dehydrogenase complex, suggesting significant evolutionary changes in energy production. Future studies incorporating additional genomic data from diverse blattodean species are essential to elucidate the molecular mechanisms driving transitions to xylophagy and eusociality.

evolutionary biology↗

bioRxiv2025

Unravelling termite evolution with 47 high-resolution genome assemblies

Termites are a lineage of social cockroaches abundant in tropical ecosystems where they are key decomposers of organic matter from wood to soil. Despite their ecological significance, only a handful of reference-quality termite genomes have been sequenced, which is insufficient to unravel the genetic mechanisms that have contributed to their ecological success. Here, we performed sequencing and hybrid assembly of 45 taxonomically and ecologically diverse termites and two cockroaches, resulting in haplotype-merged genome assemblies of 47 species, 22 of which were near-chromosome level. Next, we examined the link between termite dietary evolution and major genomic events. We found that Termitidae, which include [~]80% of described termite species, have larger genomes with more genes and a higher proportion of transposons than other termites. Our analyses identified a gene number expansion early in the evolution of Termitidae, including an expansion of the repertoire of CAZymes, the genes involved in lignocellulose degradation. Notably, this expansion of genomes and gene repertoires coincided with the origin of soil-feeding in Termitidae and remained unchanged in lineages that secondarily reverted to a wood-based diet. Overall, our sequencing effort multiplied the number of available termite genomes by six and provided unprecedented insights into the genome evolution of the most ancient lineage of social insects.

genomics↗

bioRxiv2025

Gut meta-virome reveals potential zoonotic pathogens and environmental RNA viruses carried by non-human primates

The majority of human infectious diseases originate from mammals and are inherently zoonotic. Non-human primates (NHPs) are not only carriers of many zoonotic pathogens, but also the best intermediary for virus shift from harmless to harmful due to their similar phylogenetic relationship with humans. Knowledge of NHP viral composition and its underlying information can therefore provide an assessment of the risk of cross-species transmission and spillover of zoonotic diseases. However, studies that have successfully eliminated the effects of different natural habitat environments on viral carriage have been limited, making it difficult to identify which zoonotic viruses and potentially species-barrier-crossing viruses are carried by widely distributed NHP hosts. Here, we analyze viruses excreted in feces from NHP hosts and reveal the presence of possible zoonotic pathogens. Most of the viruses found come from plants that are eaten by them. Analysis of the evolutionary relationships of potential pathogens suggests that other clinical isolates are genetically correlated to HIV, PBV, and EV we identified. This study provides foundational data for surveillance of NHP enteroviruses that could help to be challenging to track potential human viruses carried by NHP in the absence of clinical surveillance. ImportanceAs a result of internationalization and other factors, many viruses have broken through the limits of geographical units and spread into human society, causing many emerging and re-emerging infectious disease hazards. However, the virus spreads and is by no means infectious to humans overnight. There is a phenomenon of host shift, in which the virus does not necessarily cause disease in an intermediate host, but causes significant damage when transmitted to humans. We focus on captive non-human primates, close relatives of humans in cities, because the phenomenon of host shifts is related to both biological similarity and geographical proximity of the host. Primates may carry zoonotic viruses and viruses that are currently incapable of infecting humans but have evolved with pathogenic potential. In summary, comprehensive viral surveillance and screening of captive nonhuman primates is necessary.

ecology↗

bioRxiv2025

The role of STN beta oscillations on lower extremity muscle activity in Parkinsonian stepping

Freezing of gait (FOG) is a devastating symptom of Parkinsons disease (PD) often resulting in disabling falls and loss of independence. It affects half of patients, yet current therapeutic strategies are insufficient, and the underlying neural mechanisms remain poorly understood. This study investigated beta oscillation dynamics in the STN during different locomotor states, while examining the effects of levodopa. In particular, it aimed to identify pathological activity by analysing the relationship between the STN and lower limb muscles during stepping. Local field potentials (LFP) in the STN and muscle activity (EMG) of the gastrocnemius and peroneus longus were recorded in 14 PD patients during standing and stepping, ON and OFF levodopa. Levodopa reduced stepping variability, implying improved stepping abilities. Distinct STN beta patterns were observed between stepping and standing, with lower high-beta and higher low-beta during stepping compared to standing, suggesting a distinct role of these frequency bands in motor control during postural and movement states. Levodopa reduced low-beta but increased high-beta activity, highlighting a potential physiological function of high-beta in the STN during standing and stepping. In addition, step-phase specific effects of levodopa included reduced broad-beta band activity in the STN and lower limb muscles during the late-stance and pushing-off phase of the contralateral leg when ON medication. Further analyses suggest that pathological STN activity amplifies muscle activation around movement initiation, potentially reducing the ability of the patient to move freely. These findings offer insight for developing phase-specific stimulation strategies targeting STN beta oscillations during gait.

neuroscience↗

bioRxiv2024

Cryo-EM structure of the conjugation H-pilus reveals the cyclic nature of the TrhA pilin

Conjugation, the major driver of the spread of antimicrobial resistance genes, relies on a conjugation pilus for DNA transfer. Conjugative pili, such as the F-pilus, are dynamic tubular structures, composed of a polymerized pilin, that mediate the initial donor-recipient interactions, a process known as mating pair formation (MPF). IncH are low-copy-number plasmids, traditionally considered broad host range, which are found in bacteria infecting both humans and animals. The reference IncHI1 plasmid R27, isolated from Salmonella enterica serovar Typhi, encodes the conjugative H-pilus subunit TrhA containing 74 residues after cleavage of the signal sequence. Here, we show that the H-pilus forms long filamentous structures that mediate MPF, and describe its cryo electron-microscopic (cryo-EM) structure at 2.2 [A] resolution. Like the F pilus, the H-pilin subunits form helical assemblies with phospholipid molecules at a stochiometric ratio of 1:1. While there were previous reports that the T-pilus from Agrobacterium tumefaciens was composed of cyclic subunits, three recent cryo-EM structures of the T-pilus found no such cyclization. Here, we report that the H-pilin is cyclic, with a covalent bond connecting the peptide backbone between the N- and C-termini. Both the cryo-EM map and mass spectrometry revealed cleavage of the last five residues of the pilin, followed by cyclization via condensation of the amine and carboxylate residues. The cyclic nature of the pilin could stabilize the pilus and may explain the high incidence of IncH plasmid dissemination. SignificanceA major medical challenge is the spread of bacteria which are resistant to antibiotics. The resistance genes are spread via mobilized DNA, mainly via a process named conjugation. During conjugation, a resistant bacterium (donor), transfers the resistance DNA to another bacterium (recipient) in a contact-dependent manner. The initial donor-recipient interaction is mediated by a hollow filament expressed by the donor, named the conjugation pilus, that binds the recipient. This pilus is built via polymerization of a small protein subunit, pilin. Here, we report the atomic structure of the H-pilus, whose pilin subunit has an unusual cyclic structure where the N- and C-termini of the protein are covalently linked by a peptide bond.

microbiology↗

bioRxiv2024

Sub-cellular Imaging of the Entire Protein-Coding Human Transcriptome (18933-plex) on FFPE Tissue Using Spatial Molecular Imaging

Single-cell RNA-seq revolutionized single-cell biology, by providing a complete whole transcriptome view of individual cells. Regrettably, this was accomplished only for individual, tissue-dissociated cells. High-plex spatial biology has begun to recover the x, y, and z-coordinates of single-cells, but typically at the expense of far less than whole transcriptome coverage. To solve this problem, Bruker Spatial Biology has accomplished a commercial-grade panel (CosMx(R) Spatial Molecular Imager Whole Transcriptome Panel (WTx)), using 37,872 imaging barcodes, capable of sub-cellular imaging of the entire human protein-coding transcriptome. The imaging barcodes are encoded with 156 bits of information (4 on-cycles and 35 dark-cycles per code), at a Hamming Distance of 4 from each other to achieve a very low false-code detection. Key to achieving this high-plex capability was the ability to manufacture imaging barcodes that require no in-tissue amplification (every barcode is manufactured under GMP to contain exactly 30 fluorescent dyes) and uniform, size-exclusion purified, extremely small imaging barcodes ([~] 20 nm). A detailed study of six different human FFPE tissue types was performed (Colon, Pancreas, Hippocampus, Skin, Breast, Kidney), yielding over 5.4 billion transcripts from 2.7 million cells. We counted over 1,550 transcripts-per-cell on average and observed 900 unique genes per cell (measured as the median). Single fixed-cells containing well over 10,000 subcellularly imaged transcripts were accomplished. Advancing single-cell imaging to the whole transcriptome level opens a single unified approach to accomplish essentially all single-cell experiments, both imaging and non-imaging. Depending upon the sample type (e.g. fixed-cells, organoids, tissue sections, etc.), the transcripts per cell and genes per cell measured using the whole transcriptome panel often exceeds that obtained by the highest-resolution single-cell RNA-seq, can be performed on a single 5 {micro}m FFPE tissue section, with no dissociation bias (every cell is counted). Pathway analysis within the tumor bed of a colon adenocarcinoma sample found evidence of enrichment in pathways suggestive of an aggressive tumor type, and localized ligand-receptor analysis showed spatially restricted patterns related to adhesion, migration, and proliferation. The high-dimensional whole transcriptome data is streamed directly to a cloud-based Spatial Informatics Platform, allowing for the scalable processing of millions-of-single-cells and billions-of-transcripts per operation. The WTx data are combined with high-resolution antibody-based cell-morphology imaging and data-driven machine-learning cell segmentation algorithms, to generate the most complete view of single cell and sub-cellular spatial biology that has ever been obtained.

genomics↗