Innovative super-resolution in spatial transcriptomics: a transformer model exploiting histology images and spatial gene expression.

Spatial transcriptomics technologies have shed light on the complexities of tissue structures by accurately mapping spatial microenvironments. Nonetheless, a myriad of methods, especially those utilized in platforms like Visium, often relinquish spatial details owing to intrinsic resolution limitations. In response, we introduce TransformerST, an innovative, unsupervised model anchored in the Transformer architecture, which operates independently of references, thereby ensuring cost-efficiency by circumventing the need for single-cell RNA sequencing. TransformerST not only elevates Visium data from a multicellular level to a single-cell granularity but also showcases adaptability across diverse spatial transcriptomics platforms. By employing a vision transformer-based encoder, it discerns latent image-gene expression co-representations and is further enhanced by spatial correlations, derived from an adaptive graph Transformer module. The sophisticated cross-scale graph network, utilized in super-resolution, significantly boosts the model's accuracy, unveiling complex structure-functional relationships within histology images. Empirical evaluations validate its adeptness in revealing tissue subtleties at the single-cell scale. Crucially, TransformerST adeptly navigates through image-gene co-representation, maximizing the synergistic utility of gene expression and histology images, thereby emerging as a pioneering tool in spatial transcriptomics. It not only enhances resolution to a single-cell level but also introduces a novel approach that optimally utilizes histology images alongside gene expression, providing a refined lens for investigating spatial transcriptomics.

Nasal epithelial gene expression and total IgE in children and adolescents with asthma.

BACKGROUND: Little is known about nasal epithelial gene expression and total IgE in youth. OBJECTIVE: We aimed to identify genes whose nasal epithelial expression differs by total IgE in youth, and group them into modules that could be mapped to airway epithelial cell types. METHODS: We conducted a transcriptome-wide association study of total IgE in 469 Puerto Ricans aged 9 to 20 years who participated in the Epigenetic Variation and Childhood Asthma in Puerto Ricans study, separately in all subjects and in those with asthma. We then attempted to replicate top findings for each analysis using data from 3 cohorts. Genes with a Benjamini-Hochberg-adjusted P value of less than .05 in the Epigenetic Variation and Childhood Asthma in Puerto Ricans study and a P value of less than .05 in the same direction of association in 1 or more replication cohort were considered differentially expressed genes (DEGs). DEGs for total IgE in subjects with asthma were further dissected into gene modules using coexpression analysis, and such modules were mapped to specific cell types in airway epithelia using public single-cell RNA-sequencing data. RESULTS: A higher number of DEGs for total IgE were identified in subjects with asthma (n = 1179 DEGs) than in all subjects (n = 631 DEGs). In subjects with asthma, DEGs were mapped to 11 gene modules. The top module for positive correlation with total IgE was mapped to myoepithelial and mucus secretory cells in lower airway epithelia and was regulated by IL-4, IL5, IL-13, and IL-33. Within this module, hub genes included CDH26, FETUB, NTRK2, CCBL1, CST1, and CST2. Furthermore, an enrichment analysis showed overrepresentation of genes in signaling pathways for synaptogenesis, IL-13, and ferroptosis, supporting interactions between interleukin- and acetylcholine-induced responses. CONCLUSIONS: Our findings for nasal epithelial gene expression support neuroimmune coregulation of total IgE in youth with asthma.

Cis- and trans-eQTM analysis reveals novel epigenetic and transcriptomic immune markers of atopic asthma in airway epithelium.

BACKGROUND: Expression quantitative trait methylation (eQTM) analyses uncover associations between DNA methylation markers and gene expression. Most eQTM analyses of complex diseases have focused on cis-eQTM pairs (within 1 megabase). OBJECTIVES: This study sought to identify cis- and trans-methylation markers associated with gene expression in airway epithelium from youth with and without atopic asthma. METHODS: In this study, the investigators conducted both cis- and trans-eQTM analyses in nasal (airway) epithelial samples from 158 Puerto Rican youth with atopic asthma and 100 control subjects without atopy or asthma. The investigators then attempted to replicate their findings in nasal epithelial samples from 2 studies of children, while also examining whether their results in nasal epithelium overlap with those from an eQTM analysis in white blood cells from the Puerto Rican subjects. RESULTS: This study identified 9,108 cis-eQTM pairs and 2,131,500 trans-eQTM pairs. Trans-associations were significantly enriched for transcription factor and microRNA target genes. Furthermore, significant cytosine-phosphate-guanine sites (CpGs) were differentially methylated in atopic asthma and significant genes were enriched for genes differentially expressed in atopic asthma. In this study, 50.7% to 62.6% of cis- and trans-eQTM pairs identified in Puerto Rican youth were replicated in 2 smaller cohorts at false discovery rate-adjusted P < .1. Replicated genes in the trans-eQTM analysis included biologically plausible asthma-susceptibility genes (eg, HDC, NLRP3, ITGAE, CDH26, and CST1) and are enriched in immune pathways. CONCLUSIONS: Studying both cis- and trans-epigenetic regulation of airway epithelial gene expression can identify potential causal and regulatory pathways or networks for childhood asthma. Trans-eQTM CpGs may regulate gene expression in airway epithelium through effects on transcription factor and microRNA target genes.

Anti-C5a antibody vilobelimab treatment and the effect on biomarkers of inflammation and coagulation in patients with severe COVID-19: a substudy of the phase 2 PANAMO trial.

We recently reported in the phase 3 PANAMO trial that selectively blocking complement 5a (C5a) with vilobelimab led to improved survival in critically ill COVID-19 patients. C5a is an important contributor to the innate immune system and can also activate the coagulation system. High C5a levels have been reported in severely ill COVID-19 patients and correlate with disease severity and mortality. Previously, we assessed the potential benefit and safety of vilobelimab in severe COVID-19 patients. In the current substudy of the phase 2 PANAMO trial, we aim to explore the effects of vilobelimab on various biomarkers of inflammation and coagulation. Between March 31 and April 24, 2020, 17 patients with severe COVID-19 pneumonia were enrolled in an exploratory, open-label, randomised phase 2 trial. Blood markers of complement, endothelial activation, epithelial barrier disruption, inflammation, neutrophil activation, neutrophil extracellular trap (NET) formation and coagulopathy were measured using enzyme-linked immunosorbent assay (ELISA) or utilizing the Luminex platform. During the first 15 days after inclusion, change in biomarker concentrations between the two groups were modelled with linear mixed-effects models with spatial splines and compared. Eight patients were randomized to vilobelimab treatment plus best supportive care (BSC) and nine patients were randomized to BSC only. A significant decrease over time was seen in the vilobelimab plus BSC group for C5a compared to the BSC only group (p < 0.001). ADAMTS13 levels decreased over time in the BSC only group compared to the vilobelimab plus BSC group (p < 0.01) and interleukin-8 (IL-8) levels were statistically more suppressed in the vilobelimab plus BSC group compared to the BSC group (p = 0.03). Our preliminary results show that C5a inhibition decreases the inflammatory response and hypercoagulability, which likely explains the beneficial effect of vilobelimab in severe COVID-19 patients. Validation of these results in a larger sample size is warranted.

Differential gene expression in nasal airway epithelium from overweight or obese youth with asthma.

BACKGROUND: The mechanisms underlying the known link between overweight/obesity and childhood asthma are unclear. We aimed to identify differentially expressed genes and pathways associated with obesity-related asthma through a transcriptomic analysis of nasal airway epithelium. METHODS: We compared the whole transcriptome in nasal airway epithelium of youth with overweight or obesity and asthma with that of youth of normal weight and asthma, using RNA sequencing data from a cohort of 235 Puerto Ricans aged 9-20 years (EVA-PR) and an independent cohort of 66 children aged 6-16 years in Pittsburgh (VDKA). Differential expression analysis adjusting for age, sex, sequencing plate number, and sample sorting protocol, and the first five principal components were performed independently in each cohort. Results from the two cohorts were combined in a transcriptome-wide meta-analysis. Gene enrichment and network analyses were performed on top genes. RESULTS: In the meta-analysis, 29 genes were associated with obesity-related asthma at an FDR-adjusted p <.05, including pro-inflammatory genes known to be differentially expressed in adipose tissue of obese subjects (e.g., CXCL11, CXCL10, and CXCL9) and several novel genes. Functional enrichment analyses showed that pathways for interferon signaling, and innate and adaptive immune responses were down-regulated in overweight/obese youth with asthma, while pathways related to ciliary structure or function were up-regulated. Upstream regulatory analysis predicted significant inhibition of the IRF7 pathway. Network analyses identified "hub" genes like GBP5 and SOCS1. CONCLUSION: Our transcriptome-wide analysis of nasal airway epithelium identified biologically plausible genes and pathways for obesity-related asthma in youth.

BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data.

Droplet-based single cell transcriptome sequencing (scRNA-seq) technology, largely represented by the 10× Genomics Chromium system, is able to measure the gene expression from tens of thousands of single cells simultaneously. More recently, coupled with the cutting-edge Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), the droplet-based system has allowed for immunophenotyping of single cells based on cell surface expression of specific proteins together with simultaneous transcriptome profiling in the same cell. Despite the rapid advances in technologies, novel statistical methods and computational tools for analyzing multi-modal CITE-Seq data are lacking. In this study, we developed BREM-SC, a novel Bayesian Random Effects Mixture model that jointly clusters paired single cell transcriptomic and proteomic data. Through simulation studies and analysis of public and in-house real data sets, we successfully demonstrated the validity and advantages of this method in fully utilizing both types of data to accurately identify cell clusters. In addition, as a probabilistic model-based approach, BREM-SC is able to quantify the clustering uncertainty for each single cell. This new method will greatly facilitate researchers to jointly study transcriptome and surface proteins at the single cell level to make new biological discoveries, particularly in the area of immunology.

Biosynthetic code for divergolide assembly in a bacterial mangrove endophyte.

Divergolides are structurally diverse ansamycins produced by a bacterial endophyte (Streptomyces sp.) of the mangrove tree Bruguiera gymnorrhiza. By genomic analyses a gene locus coding for the divergolide pathway was detected. The div gene cluster encodes genes for the biosynthesis of 3-amino-5-hydroxybenzoate and the rare extender units ethylmalonyl-CoA and isobutylmalonyl-CoA, polyketide assembly by a modular type I polyketide synthase (PKS), and enzymes involved in tailoring reactions, such as a Baeyer-Villiger oxygenase. A detailed PKS domain analysis confirmed the stereochemical integrity of the divergolides and provided valuable new insights into the formation of the diverse aromatic chromophores. The bioinformatic analyses and the isolation and full structural elucidation of four new divergolide congeners led to a revised biosynthetic model that illustrates the formation of four different types of ansamycin chromophores from a single polyketide precursor.

Effect of structural isomerism on magnetic dynamics: from single-molecule magnet to single-chain magnet.

This Paper reports the first examples of O-P-O bridged Mn2(salen)2 (salen = N,N'-bis(salicylidene)ethylenediamine) chain compounds, namely, [Mn2(salen)2(2-FC6H4PO3H)](ClO4)·1/2CH3OH (1) and [Mn2(salen)2(4-FC6H4PO3H)](ClO4) (2). The phosphonate ligands adopt a syn-anti bidentate bridging mode in 1 and a syn-syn bidentate bridging mode in 2, originated from the isomeric phosphonate ligands. The different bridging modes cause a significant change in the Mn-O···O-Mn torsion angle over the O-P-O bridge, which are 96.6 and 1.9° for 1 and 2, respectively. As a result, the antiferromagnetic (AF) exchange couplings mediated through the O-P-O pathway are extremely weak in 1, and the overall magnetic behaviors are dominated by the Mn2(salen)2 moieties. Single-molecule magnetic behavior is observed in 1. For compound 2, the AF interaction over the O-P-O bridge is much stronger. The coexistence of metamagnetism and single-chain magnetic behavior is observed for 2.

A unified model-based framework for doublet or multiplet detection in single-cell multiomics data.

Droplet-based single-cell sequencing techniques rely on the fundamental assumption that each droplet encapsulates a single cell, enabling individual cell omics profiling. However, the inevitable issue of multiplets, where two or more cells are encapsulated within a single droplet, can lead to spurious cell type annotations and obscure true biological findings. The issue of multiplets is exacerbated in single-cell multiomics settings, where integrating cross-modality information for clustering can inadvertently promote the aggregation of multiplet clusters and increase the risk of erroneous cell type annotations. Here, we propose a compound Poisson model-based framework for multiplet detection in single-cell multiomics data. Leveraging experimental cell hashing results as the ground truth for multiplet status, we conducted trimodal DOGMA-seq experiments and generated 17 benchmarking datasets from two tissues, involving a total of 280,123 droplets. We demonstrated that the proposed method is an essential tool for integrating cross-modality multiplet signals, effectively eliminating multiplet clusters in single-cell multiomics data-a task at which the benchmarked single-omics methods proved inadequate.

A cis-regulatory module underlies retinal ganglion cell genesis and axonogenesis.

Atoh7 is transiently expressed in retinal progenitor cells (RPCs) and is required for retinal ganglion cell (RGC) differentiation. In humans, a deletion in a distal non-coding regulatory region upstream of ATOH7 is associated with optic nerve atrophy and blindness. Here, we functionally interrogate the significance of the Atoh7 regulatory landscape to retinogenesis in mice. Deletion of the Atoh7 enhancer structure leads to RGC deficiency, optic nerve hypoplasia, and retinal blood vascular abnormalities, phenocopying inactivation of Atoh7. Further, loss of the Atoh7 remote enhancer impacts ipsilaterally projecting RGCs and disrupts proper axonal projections to the visual thalamus. Deletion of the Atoh7 remote enhancer is also associated with the dysregulation of axonogenesis genes, including the derepression of the axon repulsive cue Robo3. Our data provide insights into how Atoh7 enhancer elements function to promote RGC development and optic nerve formation and highlight a key role of Atoh7 in the transcriptional control of axon guidance molecules.

Synthetic remodeling of the chartreusin pathway to tune antiproliferative and antibacterial activities.

Natural products of the benzonaphthopyranone class, such as chartreusin, elsamicin A, gilvocarcin, and polycarcin, represent potent leads for urgently needed anticancer therapeutics and antibiotics. Since synthetic protocols for altering their architectures are limited, we harnessed enzymatic promiscuity to generate a focused library of chartreusin derivatives. Pathway engineering of the chartreusin polyketide synthase, mutational synthesis, and molecular modeling were employed to successfully tailor the structure of chartreusin. For the synthesis of the aglycones, improved synthetic avenues to substituted coumarin building blocks were established. Using an engineered mutant, in total 11 new chartreusin analogs (desmethyl, methyl, ethyl, vinyl, ethynyl, bromo, hydroxy, methoxy, and corresponding (1→2) abeo-chartreusins) were generated and fully characterized. Their biological evaluation revealed an unexpected impact of the ring substituents on antiproliferative and antibacterial activities. Irradiation of vinyl- and ethynyl-substituted derivatives with blue light resulted in an improved antiproliferative potency against a colorectal cancer cell line. In contrast, the replacement of a methyl group by hydrogen caused a drastically decreased cytotoxicity but markedly enhanced antimycobacterial activity. Furthermore, mutasynthesis of bromochartreusin led to the first crystal structure of a chartreusin derivative that is not modified in the glycoside residue. Beyond showcasing the possibility of converting diverse, fully synthetic polyphenolic aglycones into the corresponding glycosides in a whole-cell approach, this work identified new chartreusins with fine-tuned properties as promising candidates for further development as therapeutics.

Methyl-TWAS: A powerful method for in silico transcriptome-wide association studies (TWAS) using long-range DNA methylation.

In silico transcriptome-wide association studies (TWAS) are commonly used to test whether expression of specific genes is linked to a complex trait. However, genotype-based in silico TWAS such as PrediXcan, exhibit low prediction accuracy for a majority of genes because genotypic data lack tissue- and disease-specificity and are not affected by the environment. Because methylation is tissue-specific and, like gene expression, can be modified by environment or disease status, methylation should predict gene expression with more accuracy than SNPs. Therefore, we propose Methyl-TWAS, the first approach that utilizes long-range methylation markers to impute gene expression for in silico TWAS through penalized regression. Methyl-TWAS 1) predicts epigenetically regulated/associated expression (eGReX), which incorporates tissue-specific expression and both genetically- (GReX) and environmentally-regulated expression to identify differentially expressed genes (DEGs) that could not be identified by genotype-based methods; and 2) incorporates both cis- and trans- CpGs, including various regulatory regions to identify DEGs that would be missed using cis- methylation only. Methyl-TWAS outperforms PrediXcan and two other methods in imputing gene expression in the nasal epithelium, particularly for immunity-related genes and DEGs in atopic asthma. Methyl-TWAS identified 3,681 (85.2%) of the 4,316 DEGs identified in a previous TWAS of atopic asthma using measured expression, while PrediXcan could not identify any gene. Methyl-TWAS also outperforms PrediXcan for expression imputation as well as in silico TWAS in white blood cells. Methyl-TWAS is a valuable tool for in silico TWAS, leveraging a growing body of publicly available genome-wide DNA methylation data for a variety of human tissues.

Targeting Bcl-xL is a potential therapeutic strategy for extranodal NK/T cell lymphoma.

Extranodal natural killer/T cell lymphoma, nasal type (ENKTL) is an aggressive lymphoid malignancy with a poor prognosis and lacks standard treatment. Targeted therapies are urgently needed. Here we systematically investigated the druggable mechanisms through chemogenomic screening and identified that Bcl-xL-specific BH3 mimetics effectively induced ENKTL cell apoptosis. Notably, the specific accumulation of Bcl-xL, but not other Bcl-2 family members, was verified in ENKTL cell lines and patient tissues. Furthermore, Bcl-xL high expression was shown to be closely associated with worse patient survival. The critical role of Bcl-xL in ENKTL cell survival was demonstrated utilizing selective inhibitors, genetic silencing, and a specific degrader. Additionally, the IL2-JAK1/3-STAT5 signaling was implicated in Bcl-xL dysregulation. In vivo, Bcl-xL inhibition reduced tumor burden, increased apoptosis, and prolonged survival in ENKTL cell line xenograft and patient-derived xenograft models. Our study indicates Bcl-xL as a promising therapeutic target for ENKTL, warranting monitoring in ongoing clinical trials by targeting Bcl-xL.

Comprehensive benchmarking of CITE-seq versus DOGMA-seq single cell multimodal omics.

The recently developed method TEA-seq and similar DOGMA-seq single cell trimodal omics assays provide unprecedented opportunities for understanding cell biology, but independent evaluation is lacking. We explore the utility of DOGMA-seq compared to the bimodal CITE-seq assay in activated and stimulated human peripheral blood T cells. We find that single cell trimodal omics measurements after digitonin (DIG) permeabilization were generally better than after an alternative "low-loss lysis" (LLL) permeabilization condition. Next, we find that DOGMA-seq with optimized DIG permeabilization and its ATAC library provides more information, although its mRNA and cell surface protein libraries have slightly inferior quality, compared to CITE-seq.

Integrative analysis of spatial transcriptome with single-cell transcriptome and single-cell epigenome in mouse lungs after immunization.

Understanding lung immunity requires an unbiased profiling of tissue-resident T cells at their precise anatomical locations within the lung, but such information has not been characterized in the immunized mouse model. In this pilot study, using 10x Genomics Chromium and Visium platform, we performed an integrative analysis of spatial transcriptome with single-cell RNA-seq and single-cell ATAC-seq on lung cells from mice after immunization using a well-established Klebsiella pneumoniae infection model. We built an optimized deconvolution pipeline to accurately decipher specific cell-type compositions by anatomic location. We discovered that combining scATAC-seq and scRNA-seq data may provide more robust cell-type identification, especially for lineage-specific T helper cells. Combining all three modalities, we observed a dynamic change in the location of T helper cells as well as their corresponding chemokines. In summary, our proof-of-principle study demonstrated the power and potential of single-cell multi-omics analysis to uncover spatial- and cell-type-dependent mechanisms of lung immunity.

SECANT: a biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics.

The recent advance of single cell sequencing (scRNA-seq) technology such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) allows researchers to quantify cell surface protein abundance and RNA expression simultaneously at single cell resolution. Although CITE-seq and other similar technologies have gained enormous popularity, novel methods for analyzing this type of single cell multi-omics data are in urgent need. A limited number of available tools utilize data-driven approach, which may undermine the biological importance of surface protein data. In this study, we developed SECANT, a biology-guided SEmi-supervised method for Clustering, classification, and ANnoTation of single-cell multi-omics. SECANT is used to analyze CITE-seq data, or jointly analyze CITE-seq and scRNA-seq data. The novelties of SECANT include (1) using confident cell type label identified from surface protein data as guidance for cell clustering, (2) providing general annotation of confident cell types for each cell cluster, (3) utilizing cells with uncertain or missing cell type label to increase performance, and (4) accurate prediction of confident cell types for scRNA-seq data. Besides, as a model-based approach, SECANT can quantify the uncertainty of the results through easily interpretable posterior probability, and our framework can be potentially extended to handle other types of multi-omics data. We successfully demonstrated the validity and advantages of SECANT via simulation studies and analysis of public and in-house datasets from multiple tissues. We believe this new method will be complementary to existing tools for characterizing novel cell types and make new biological discoveries using single-cell multi-omics data.

The PROTAC selectively degrading Bcl-xL represents a novel Hedgehog pathway inhibitor with capacity of combating resistance to Smoothened inhibitors while sparing bone growth.

Rationale: Primary and acquired resistance to Smoothened (Smo) inhibitors largely hampered their clinical efficacy. Given the important functions of hedgehog (Hh) pathway in bone formation and development, the permanent defects in bone growth caused by Smo inhibitors further restrict the use of Smo inhibitors for pediatric tumor patients. Anti-apoptotic Bcl-2 proteins regulate Hh activity by engaging a Bcl-2 homology (BH) domain sequence found in suppressor of fused (Sufu). In this study, we tested the effect of SIAIS361034, a Proteolysis Targeting Chimera (PROTAC) specifically targeting B-cell lymphoma extra large (Bcl-xL) to the celeblon (CRBN) E3 ligase for degradation, on combating the resistance and reducing the toxicity of bone growth caused by Hh inhibition. Methods: Fluorescence polarization, homogeneous time-resolved fluorescence (HTRF) assay, immunoblot, and immunoprecipitation (IP) were used to evaluate whether SIAIS361034 is an appropriate Bcl-xL PROTAC. Dual luciferase reporter assay, real-time quantitative PCR (RT-qPCR), depilatory model, and SmoA1 model were established to assess the effect of SIAIS361034 on the activity of Hh signaling pathway and its ability to overcome drug resistance in vitro and in vivo. Molecular mechanisms of SIAIS361034 for inhibiting Hh activity were demonstrated by dual luciferase reporter assay, immunoblot, and immunofluorescence staining. PET-CT and histopathology of bone tissues were used to assess the effects of SIAIS361034 on bone growth. Results: We observed that SIAIS361034 efficiently and selectively inhibits the activity of the Hh pathway in vitro and in vivo, by interrupting Bcl-xL/Sufu interaction, therefore, promoting the interaction of Sufu with Gli1. Moreover, SIAIS361034 possesses the ability of combating resistance to current Smo inhibitors caused by Smo mutations and Gli2 amplification and remarkably inhibits the growth of SmoA1 tumors in vivo. In contrast to von Hippel-Lindau (VHL) E3 ligase, our result further reveals little detectable expression of CRBN in two types of cells critical for bone development, human articular chondrocytes and human fetal osteoblastic cells. Moreover, treatment with SIAIS361034 results in no impairment on the bone growth of young mice, accompanying no alteration of the expression of Bcl-xL and Gli1 proteins. Conclusion: Our findings demonstrate that selectively targeting Bcl-xL by PROTAC is a promising strategy for combating resistance to Smo inhibitors without causing on-target drug toxicities of bone growth.

Nasal DNA methylation at three CpG sites predicts childhood allergic disease.

Childhood allergic diseases, including asthma, rhinitis and eczema, are prevalent conditions that share strong genetic and environmental components. Diagnosis relies on clinical history and measurements of allergen-specific IgE. We hypothesize that a multi-omics model could accurately diagnose childhood allergic disease. We show that nasal DNA methylation has the strongest predictive power to diagnose childhood allergy, surpassing blood DNA methylation, genetic risk scores, and environmental factors. DNA methylation at only three nasal CpG sites classifies allergic disease in Dutch children aged 16 years well, with an area under the curve (AUC) of 0.86. This is replicated in Puerto Rican children aged 9-20 years (AUC 0.82). DNA methylation at these CpGs additionally detects allergic multimorbidity and symptomatic IgE sensitization. Using nasal single-cell RNA-sequencing data, these three CpGs associate with influx of T cells and macrophages that contribute to allergic inflammation. Our study suggests the potential of methylation-based allergy diagnosis.

ChromInst: A single cell sequencing technique to accomplish pre-implantation comprehensive chromosomal screening overnight.

Next Generation Sequencing (NGS) is a powerful tool getting into the field of clinical examination. Its preliminary application in pre-implantation comprehensive chromosomal screening (PCCS) of assisted reproduction (test-tube baby) has shown encouraging outcomes that improves the success rate of in vitro fertilization. However, the conventional NGS library construction is time consuming. In addition with the whole genome amplification (WGA) procedure in prior, makes the single cell NGS assay hardly be accomplished within an adequately short turnover time in supporting fresh embryo implantation. In this work, we established a concise single cell sequencing protocol, ChromInst, in which the single cell WGA and NGS library construction were integrated into a two-step PCR procedure of ~ 2.5hours reaction time. We then validated the feasibility of ChromInst for overnight PCCS assay by examining 14 voluntary donated embryo biopsy samples in a single sequencing run of Miseq with merely 13M reads production. The good compatibility of ChromInst with the restriction of Illumina sequencing technique along with the good library yield uniformity resulted superior data usage efficiency and reads distribution evenness that ensures precisely distinguish of 6 normal embryos from 8 abnormal one with variable chromosomal aneuploidy. The superior succinctness and effectiveness of this protocol permits its utilization in other time limited single cell NGS applications.