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• UK_RCC_GWAS

  Renal cell carcinoma (RCC) cases comprised adult patients with histologically proven RCC were collected through two sources within the UK. First, 856 cases from SORCE, a MRC collection of surgically treated RCC cases ascertained through UK clinical oncology centres. Second, 189 RCC cases collected through the ICR and Royal Marsden NHS Hospitals Trust. Cases included 590 clear cell carcinomas (CCCs), 42 papillary carcinomas (PCs), 33 chromophobe carcinomas (CCs) and 19 mixed or other histological subtypes. DNA was extracted from EDTA-venous blood samples using the conventional methods and quantified using PicoGreen (Invitrogen). Cases were genotyped using the Human OmniExpress-12 BeadChip according to the manufacturer's recommendations (Illumina Inc, San Diego, CA, USA). After strict QC, 944 cases were retained. Data provided in plink format. Controls used were data from the Wellcome Trust Case Control Consortium 2 (WTCCC2) 1958 birth cohort and the UK Blood Service Control Group (available as EGAS00000000028). 

  Dataset EGAD00010002310

• Detection of Clinically Relevant Genetic Variantsin Autism Spectrum Disorderby Whole-Genome Sequencing

  Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo muta- tions in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.

  Study EGAS00001000850

• Epigenome-wide methylation analysis of colorectal carcinoma, adenoma and normal tissue reveals novel biomarkers addressing unmet clinical needs

  Studies about CRC biomarker discovery have focused on methylation patterns in normal and colorectal tumor tissue, leading to a lack of knowledge of methylation in adenomas. Therefore, we performed the first epigenome-wide study to compare the epigenomes of all three tissue types combined, and to identify discriminatory biomarkers. Public Illumina MethylEPIC® data was collected from 552 normal, 118 carcinoma and 116 adenoma samples. Pairwise analyses were performed for discovery of differentially methylated probes (DMPs). We identified 693 813, 620 643 and 558 897 DMPs when comparing normal vs carcinoma, normal vs adenoma and adenoma vs carcinoma respectively. To double evidence (DE) these DMPs, analysis of Illumina 450K data from public datasets was performed. Through this analysis, 13 DE DMPs with │Δβ│≥0.3 were identified for adenoma vs carcinoma. A binary logistic regression model was generated to evaluate the discriminatory potential of these DE DMPS. The model was validated in an in-house experimental methylation dataset of 13 adenoma and 9 carcinoma samples. Our classifier reached a cross-validated AUC of 0.996 and 0.855 in the discovery and validation datasets respectively. A sensitivity and specificity of 96% and 95% were reached, with an overall accuracy of 96%. Our analysis show that methylation biomarkers have the potential to discriminate between normal, precursor and carcinoma tissues of the colorectum. More importantly, we highlight the power of the methylome, showing that DMPs can be used as biomarkers in the clinic to identify colorectal adenoma and carcinoma. 

  Study EGAS00001007017

• Transcriptome Sequencing PPGL (2)

  RNA-Seq data (n=81) library preparation was performed as previously reported by Calsina et al 2023 using QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015). The prepared libraries were subsequently sequenced on NovaSeq™ system (Illumina). To combine the new CNIO samples (n=81) with the CNIO+TCGA dataset generated in Calsina et al., 2023, RNA data were processed using ComBat-seq as described in that same article.

  Study EGAS50000000013

• single-cell RNA-Seq samples of CRC patients

  The dataset contains samples of 11 CRC patients (2 samples for each patient, tumor and normal adjacent tissue site, 22 samples in total). Dataset is composed by fastq file (paired end) type from 10x single-cell RNA-Seq.

  Dataset EGAD00001009634

• NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica

  This administrative supplement to the project, "The Genetic Epidemiology of Asthma in Costa Rica" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.

  Study phs000988

• Virginia PrIMeD Study

  The goal of this study was to determine whether screening children (2-16 yrs) in pediatric waiting rooms for genetic risk of type 1 diabetes (T1D) could be applied to diverse (by geography, genetic ancestry) communities, and for those at "high genetic risk," if barriers prevent subsequent screening for presence of islet autoantibodies. A total of 3,818 children were recruited from eight general pediatric and specialty clinics across Virginia. Clinical Research Coordinators were stationed at each clinic and obtained informed consent/assent, a brief medical history, and a saliva sample for DNA extraction and determination of their genetic risk using a T1D Genetic Risk Score (T1D GRS). Children were present in the clinic for a "healthy" visit, although children with and without a history of T1D were recruited into the study. Age, sex, self-reported ancestry/race, T1D history, and other medical history information was obtained. DNA was extracted from the saliva samples and genotyping with a T1D-focused array using 74 SNPs (including 26 SNPs in the HLA region) provided data to generate a T1D GRS for each individual. Of the 3,818 children recruited, there was a slight excess of males (1,959, 51.3%), a majority of white and Hispanic/Latino ancestry (82.8%), and 91 (2.4%) with prevalent T1D. A total of 542 (14.2%) had "high T1D genetic risk" (T1D GRS > 5). Although the T1D GRS included non-HLA genetic variants, 80% of those with "high genetic risk" would have been classified using only those SNPs in the HLA region alone. Of children with "high genetic risk" and without pre-existing T1D (n=494), 7.0% (34/494) consented for islet autoantibody screening. Among children with pre-existing T1D (n=91), 52% (n=48) also had a "high genetic risk." The HLA-focused T1D GRS was not significantly associated with age at onset of T1D. Of those at high genetic risk that consented for autoantibody testing (n=34) and completed the blood collection (n=28), two (2/28, 7.1%) tested positive for multiple autoantibodies and were at significant risk of developing T1D. Follow up of 55% of parents/guardians identified 2 (of 2,096, 0.095%) participants who developed T1D, one at "high genetic risk" and one with a first-degree relative with T1D. A major factor in obtaining islet autoantibody testing was concern over SARS-Cov-2 exposure and an independent non-scheduled blood collection.Individual-level data at each SNP (genotyped and imputed) for T1D genetic risk and affiliated data are provided in dbGaP.

  Study phs003609

• 20210729_EGA_BrainMet Saunus et al J Path (2015)

  Exome sequencing on HiSeq platform of 36 brain metastases with matched normal samples, 32 having matched RNA seq. Published Saunus et al J Path, (2015); https://doi.org/10.1002/path.4583

  Dataset EGAD00001007973

• DNMT3A microcephalic primordial dwarfism RRBS data

  RRBS sequence data from one control and one patient with de novo DNMT3A mutations resulting in microcephalic primordial dwarfism.

  Dataset EGAD00001004472

• Whole genome and transcriptome sequencing of lung cancer patients and cell lines at Genentech

  Version 1 Whole genome sequencing was applied to tumor and adjacent normal lung tissue in an individual non-small-cell lung cancer patient. We present an analysis of somatic changes identified throughout the tumor genome, including single-nucleotide variants, copy number variants, and large-scale chromosomal rearrangements. Over 50,000 high-confidence single-nucleotide variants were identified, revealing evidence of substantial smoking-related DNA damage as well as distinct mutational pressures within the tumor resulting in uneven distribution of somatic mutations across the genome. Version 2 Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified over 100 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. Differential usages of splice isoforms were also studied. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers.

  Study phs000299

• Mutational Signature and Transcriptomic Classification Analyses as the Decisive Diagnostic Tools for a Cancer of Unknown Primary with Neuroendocrine Differentiation

  PURPOSE: Cancer of unknown primary (CUP) is a group of metastatic tumors in which the standard diagnostic work-up fails to identify the site of origin of the tumor. The potential impact of precision oncology on this group of patients is large since their tumors might have actionable driver mutations that can provide treatment options otherwise not available for patients with these fatal cancers. This study investigated if comprehensive genomics analyses could inform on the origin of the tumor. PATIENT AND METHODS: Here we describe a patient whose tumor was misdiagnosed at least three times. Next-generation sequencing, a PDX mouse model and bioinformatics was used to identify an actionable mutation, predict resistance development to the targeted therapy, and to correctly diagnose the origin of the tumor. The Cancer Genome Atlas was used to benchmark the bioinformatics workflow. RESULTS: Despite the lack of a known primary tumor site and the absence of diagnostic immunohistochemical markers, the origin of the patient's tumor was established using the novel bioinformatics workflow. This included a mutational signature analysis of the sequenced metastases and comparison of their transcriptomic profiles to a pan-cancer panel of tumors from The Cancer Genome Atlas. We further discuss the strengths and limitations of the latter approaches in the context of three potentially incorrectly diagnosed TCGA lung tumors. CONCLUSION: Comprehensive genomics analyses could inform on the origin of tumors in patients suffering from CUP.

  Study EGAS00001003026

• 120 individuals from the TEENAGE study (Ntalla et al., 2013) have been genotyped on the Illumina HumanCoreExome-12v1-1_A array. This is a population-based study of adolescents from the Attica region in Greece

  120 individuals from the TEENAGE study (Ntalla et al., 2013) have been genotyped on the Illumina HumanCoreExome-12v1-1_A array. This is a population-based study of adolescents from the Attica region in Greece

  Study EGAS00001001733

• Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain

  These data are derived from iterative data collection and analysis partly reported in three primary publications (Gibbs et al., 2010, PMID: 20485568, Hernandez et al. 2011, PMID: 21216877, Hernandez et al. 2012, PMID: 22433082). This study includes an assessment of common genetic variability across the genome, chip based gene expression analysis and array based methylation analysis, across a series of 150 subjects from whom we had cerebellum, frontal cortex, pons, and temporal cortex tissue (600 tissue samples). In each tissue we assessed 27,578 DNA methylation sites and the expression level of 22,184 genes. This work was then expanded to include assessment of 232 additional subjects and two tissues (cerebellum and frontal cortex) for whom we collected genotype, RNA expression and DNA methylation data.

  Study phs000249

• De_novo_mutations_in_cell_free_foetal_DNA__cffDNA_

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000322

• Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell ATAC-seq

  We report a deconvolution and identification strategy of scATAC-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and acquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures in different mixed ration and cell volumes.

  Study EGAS00001007380

• De novo detection of somatic variants

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

  Dataset EGAD50000001292

• Linguistic utterance counts for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_225CaboVerde_FreeSpeech_Utterance_counts_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See See Material and Methods in Romain Laurent et al. 2022 - doi pendingColumn 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See Material and Methods in Laurent R et al. eLife 2023

  Dataset EGAD00001008978

• Breast cancer PDTX sequencing data from Bruna et al, Cell 2016

  Breast cancer PDTX sequencing data from Bruna et al, Cell 2016 - Exome Sequencing - Shallow Whole Genome Sequencing - RRBS Methylation Sequencing

  Dataset EGAD00001002685

• Sci Trans Med - Mouliere et al, 2018. Non-ovarian cancer samples - STM4

  fastq files for shallow whole genome sequencing data as described in Mouliere et al, 2018. Files are those not included in STM2 i.e. these are largely non-ovarian cancer samples

  Dataset EGAD00001006132

• Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

  Whole genome sequencing data on 10 human cancer cell lines

  Dataset EGAD00001003824

• RNA-seq data for de-methylation of FOXP3-TSDR study

  22 RNA-seq samples of ex-vivo (TN and Treg), cultured Treg, TET1 and untreated mCherry-MOCK

  Dataset EGAD00001006865

• NHLBI TOPMed: Pediatric Cardiac Genomics Consortium (PCGC)'s Congenital Heart Disease Biobank

  The Pediatric Cardiovascular Genetics Consortium (PCGC) proposes to define genetic causes for congenital heart defects (CHD) as part of the TOPMed Program are the most common form of heart disease in childhood and are also the most prevalent form of birth defects, occurring in 2-3% of live births. The PCGC has recruited and clinically characterized = 10,000 CHD probands and parents (CHD trios). From whole exome sequencing (WES) of >2800 CHD trios, we identified a substantial enrichment of damaging de novo mutations in genes important for cardiogenesis, particularly implicating histone modifier enzyme gene defects. Analysis of whole genome sequencing (WGS) of 350 probands with CHD unexplained by WES and their parents preliminarily implicated de novo mutations in enhancers of genes previously shown to cause CHD in mouse knock out models. Sequencing of RNA (RNAseq) from discarded cardiac tissues from CHD probands has revealed likely causal allele-specific expression (ASE) as well as biallelic loss of expression (LOE). We have also discovered de novo epimutations, differentially methylated regions (DMRs), some with underlying de novo DNA variation, that are detectable in peripheral blood leukocytes and appear to underlie 10% of CHD. Of note, these assorted 'omic' approaches have enabled one another, both for attributing causality and assessing functional impact. Based on these extensive preliminary data, we hypothesize that PCGC probands with uninformative exomic analyses (WES-negative) harbor de novo genetic and/or epigenetic mutations in critical regulatory elements that participate in developmental expression of cardiac genes. To identify these etiologies, we propose analyses of WGS in 1000 WES-negative CHD trios, prioritizing those with probands with banked CHD tissues (n=78), one damaging variant in a recessive CHD gene, and older fathers (age>45). We also request WGS for 230 probands, for whom we have cardiac tissues but not parental DNAs. We request RNAseq for 308 cardiac tissues. For DNA methylation, which TOPMed will offer through the Illumina 850k array platform, we are requesting analysis of DNAs from peripheral blood leukocytes for all probands for whom WGS will be performed (1000 from trios, 230 singletons) as well as DNAs from cardiac tissues (n=308) to pair with the WGS, RNAseq and blood DNA methylation data. We will use existing resources and capabilities of the PCGC to confirm relevant mutations and those of its companion consortium in the Bench to Bassinet Program, the Cardiovascular Development Consortium, to inform analyses of non-coding mutations as well as to perform confirmatory functional genomics studies using cell and animal models. We expect that the studies resulting from data generated through TOPMed will provide novel insights into the molecular basis for CHD and fundamental knowledge about genes and pathways involved in cardiac development. Aside from being relevant to CHD, we anticipate that our findings will inform the understanding of later-onset cardiovascular diseases, including some arising in adulthood.

  Study phs001735

• NHLBI Family Heart Study (FamHS-Visit1 and FamHS-Visit2)

  The Family Heart Study (FamHS) was funded by the National Heart, Lung, and Blood Institute (NHLBI). It was begun in 1992 with the ascertainment of 1,200 families, half randomly sampled, and half selected because of an excess of coronary heart disease (CHD) or risk factor abnormalities as compared with age- and sex-specific population rates (Higgins et al. 1996). The families, with approximately 6,000 individuals, were sampled on the basis of information on probands from four population-based parent studies: the Framingham Heart Study, the Utah Family Tree Study, and two Atherosclerosis Risk in Communities (ARIC) centers (Minneapolis, and Forsyth County, NC). A broad range of phenotypes were assessed at a clinic examination in broad domains of CHD, atherosclerosis, cardiac and vascular function, inflammation and hemostasis, lipids and lipoproteins, blood pressure, diabetes and insulin resistance, pulmonary function, and anthropometry (FamHS Visit 1). Approximately 8 years later, study participants belonging to the largest pedigrees were invited for a second clinical exam (FamHS Visit 2). A total of 2,756 Caucasian subjects in 508 extended families were examined. A two-phase design was adopted for the genome wide association (GWA) study. In phase-1, 1007 subjects were chosen, equally distributed between the upper and lower quartile of age- and sex-adjusted values for coronary artery calcification, assessed by CT scan in Visit 2. These subjects were chosen to be largely unrelated; 34% of the subjects were from unique families, while 200 other subjects had 1 or more siblings selected into the sample, yielding a sample of 465 unrelated subjects. The remaining family members (N=1749) were genotyped in the phase-2 for replication of the top hits from the phase-1. The results presented here represent those for the analysis of the phase-1 case-control sample for variables assessed in FamHS Visit 1 (from 1992 to 1995) and for the variables assessed in FamHS Visit 2 (from 2002 to 2003). All subjects were typed on the Illumina HumMap 550 chip (Phase 1 genotype). Of these, 33 (3.3%) were excluded due to technical errors, call rates below 98%, and discrepancies between reported sex and sex-diagnostic markers. The final sample of 974 subjects have Visit 2 phenotypes, approximately 100 of these do not have Visit 1 phenotypes. There was no significant plate-to-plate variation in allele frequencies. The covariate adjustments were performed separately by sex using cubic polynomial age and clinical centers, and retaining the terms in the stepwise regression analysis that were significant at the 5% level. Extreme outliers (>4 SD from the mean) were set aside, temporarily, for the adjustments. The final phenotypes were computed for all individuals using the best mean regression models and standardizing to 0 mean and unit variance. The FamHS has contributed GWA results in many phenotype domains (antropometric and adiposity, atherosclerosis and coronary heart disease, lipid profile, diabetes and glicemic traits, metabolic syndrome etc) to meta-analyses and various consortia, including Heard-Costa et al. 2009, Köttgen et al. 2010, Teslovich et al. 2010, Nettleton et al. 2010, Lango et al. 2010, Heid et al. 2010, Speliotes et al. 2010, Dupuis et al. 2010, Kraja et al. 2011.

  Study phs000221

• Vitamin-D-Kids Asthma

  The Vitamin D Kids Asthma Study (VDKA) was a 48-week multicenter randomized, double-blinded, placebo-controlled trial of vitamin D3 for severe asthma exacerbations in children 6-16 years old, recruited from February 28, 2016 to September 20, 2019. An ancillary study for nasal sampling was conducted at the Pittsburgh site. Prior to randomization, participants completed questionnaires and underwent collection of nasal samples for gene expression studies. VDKA was approved by the IRBs of all participating institutions, and the ancillary study was approved by the IRB of the University of Pittsburgh. Written parental consent was obtained for participating children, from whom written assent was also obtained.

  Study phs004051

• Long-read single-cell RNA sequencing uncovers cell-type specific transcript regulation in COVID-19

  SARS-CoV-2 infection leads to extensive host transcriptomic changes, but the role of alternative splicing in shaping the immune response remains underexplored. Here, we present the first application of long-read single-cell RNA sequencing on nasopharyngeal swabs from COVID-19 patients and healthy controls to resolve transcript-level changes across cell types. Leveraging the strengths of long-read sequencing, we characterize alterations in both gene and isoform expression within cell populations of the upper respiratory tract—the primary site of SARS-CoV-2 entry. This approach provides new insights into how transcriptional regulation and splicing shape host immune responses to viral infection.

  Study EGAS50000001290