Stacey Gabriel

Correlation of MLASA2 Clinical Phenotype and Survival with Mt-TyrRS Protein Damage: Linking Systematic Review, Meta-Analysis and 3D Hotspot Mapping

Population-scale Long-read Sequencing in the All of Us Research Program

Whole genome sequence-based association analysis of African American individuals with bipolar disorder and schizophrenia

A neoantigen vaccine generates antitumour immunity in renal cell carcinoma

Dysanapsis Genetic Risk Predicts Lung Function Across the Lifespan

Rationale Dysanapsis refers to a mismatch between airway tree caliber and lung size arising early in life. Dysanapsis assessed by computed tomography (CT) is evident by early adulthood and associated with chronic obstructive pulmonary disease (COPD) risk later in life. Objective By examining the genetic factors associated with CT-assessed dysanapsis, we aimed to elucidate its molecular underpinnings and physiological significance across the lifespan. Methods We performed a genome-wide association study (GWAS) of CT-assessed dysanapsis in 11,951 adults, including individuals from two population-based and two COPD-enriched studies. We applied colocalization analysis to integrate GWAS and gene expression data from whole blood and lung. Genetic variants associated with dysanapsis were combined into a genetic risk score that was applied to examine association with lung function in children from a population-based birth cohort (n=1,278) and adults from the UK Biobank (n=369,157). Measurements and Main Results CT-assessed dysanapsis was associated with genetic variants from 21 independent signals in 19 gene regions, implicating

Genetic sex validation for sample tracking in next-generation sequencing clinical testing

Objective Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups. Results Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.

BickNature

Genomic data in the All of Us Research Program

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics 1–4 . The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health 5,6 . Here we describe the programme’s genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.

Multiplexed CRISPR-based microfluidic platform for clinical testing of respiratory viruses and identification of SARS-CoV-2 variants

The coronavirus disease 2019 (COVID-19) pandemic has demonstrated a clear need for high-throughput, multiplexed and sensitive assays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory viruses and their emerging variants. Here, we present a cost-effective virus and variant detection platform, called microfluidic Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (mCARMEN), which combines CRISPR-based diagnostics and microfluidics with a streamlined workflow for clinical use. We developed the mCARMEN respiratory virus panel to test for up to 21 viruses, including SARS-CoV-2, other coronaviruses and both influenza strains, and demonstrated its diagnostic-grade performance on 525 patient specimens in an academic setting and 166 specimens in a clinical setting. We further developed an mCARMEN panel to enable the identification of 6 SARS-CoV-2 variant lineages, including Delta and Omicron, and evaluated it on 2,088 patient specimens with near-perfect concordance to sequencing-based variant classification. Lastly, we implemented a combined Cas13 and Cas12 approach that enables quantitative measurement of SARS-CoV-2 and influenza A viral copies in samples. The mCARMEN platform enables high-throughput surveillance of multiple viruses and variants simultaneously, enabling rapid detection of SARS-CoV-2 variants.

Transmission from vaccinated individuals in a large SARS-CoV-2 Delta variant outbreak

An outbreak of over 1,000 COVID-19 cases in Provincetown, Massachusetts (MA), in July 2021-the first large outbreak mostly in vaccinated individuals in the US-prompted a comprehensive public health response, motivating changes to national masking recommendations and raising questions about infection and transmission among vaccinated individuals. To address these questions, we combined viral genomic and epidemiological data from 467 individuals, including 40% of outbreak-associated cases. The Delta variant accounted for 99% of cases in this dataset; it was introduced from at least 40 sources, but 83% of cases derived from a single source, likely through transmission across multiple settings over a short time rather than a single event. Genomic and epidemiological data supported multiple transmissions of Delta from and between fully vaccinated individuals. However, despite its magnitude, the outbreak had limited onward impact in MA and the US overall, likely due to high vaccination rates and a robust public health response.

Proteogenomic characterization of pancreatic ductal adenocarcinoma

A vast resource of allelic expression data spanning human tissues

Allele expression (AE) analysis robustly measures cis -regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis -regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

The GTEx Consortium atlas of genetic regulatory effects across human tissues

The Genotype-Tissue Expression (GTEx) project dissects how genetic variation affects gene expression and splicing.

Determinants of telomere length across human tissues

Telomere shortening is a hallmark of aging. Telomere length (TL) in blood cells has been studied extensively as a biomarker of human aging and disease; however, little is known regarding variability in TL in nonblood, disease-relevant tissue types. Here, we characterize variability in TLs from 6391 tissue samples, representing >20 tissue types and 952 individuals from the Genotype-Tissue Expression (GTEx) project. We describe differences across tissue types, positive correlation among tissue types, and associations with age and ancestry. We show that genetic variation affects TL in multiple tissue types and that TL may mediate the effect of age on gene expression. Our results provide the foundational knowledge regarding TL in healthy tissues that is needed to interpret epidemiological studies of TL and human health.

The mutational constraint spectrum quantified from variation in 141,456 humans

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes¹. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

Gene- and tissue-level interactions in normal gastrointestinal development and Hirschsprung disease

The development of the gut from endodermal tissue to an organ with multiple distinct structures and functions occurs over a prolonged time during embryonic days E10.5-E14.5 in the mouse. During this process, one major event is innervation of the gut by enteric neural crest cells (ENCCs) to establish the enteric nervous system (ENS). To understand the molecular processes underpinning gut and ENS development, we generated RNA-sequencing profiles from wild-type mouse guts at E10.5, E12.5, and E14.5 from both sexes. We also generated these profiles from homozygous Ret null embryos, a model for Hirschsprung disease (HSCR), in which the ENS is absent. These data reveal 4 major features: 1) between E10.5 and E14.5 the developmental genetic programs change from expression of major transcription factors and its modifiers to genes controlling tissue (epithelium, muscle, endothelium) specialization; 2) the major effect of Ret is not only on ENCC differentiation to enteric neurons but also on the enteric mesenchyme and epithelium; 3) a muscle genetic program exerts significant effects on ENS development; and 4) sex differences in gut development profiles are minor. The genetic programs identified, and their changes across development, suggest that both cell autonomous and nonautonomous factors, and interactions between the different developing gut tissues, are important for normal ENS development and its disorders.

Molecular Genetic Anatomy and Risk Profile of Hirschsprung’s Disease

Among the patients in our study, Hirschsprung's disease arose from common noncoding variants, rare coding variants, and copy-number variants affecting genes involved in enteric neural-crest cell fate that exacerbate the widespread genetic susceptibility associated with RET. For individual patients, the genotype-specific odds ratios varied by a factor of approximately 67, which provides a basis for risk stratification and genetic counseling. (Funded by the National Institutes of Health.).

Impaired human hematopoiesis due to a cryptic intronic GATA1 splicing mutation

Studies of allelic variation underlying genetic blood disorders have provided important insights into human hematopoiesis. Most often, the identified pathogenic mutations result in loss-of-function or missense changes. However, assessing the pathogenicity of noncoding variants can be challenging. Here, we characterize two unrelated patients with a distinct presentation of dyserythropoietic anemia and other impairments in hematopoiesis associated with an intronic mutation in GATA1 that is 24 nucleotides upstream of the canonical splice acceptor site. Functional studies demonstrate that this single-nucleotide alteration leads to reduced canonical splicing and increased use of an alternative splice acceptor site that causes a partial intron retention event. The resultant altered GATA1 contains a five-amino acid insertion at the C-terminus of the C-terminal zinc finger and has no observable activity. Collectively, our results demonstrate how altered splicing of GATA1, which reduces levels of the normal form of this master transcription factor, can result in distinct changes in human hematopoiesis.

There was a statistically significant association between an LOF variant in the TTN gene and early-onset AF.

Recall by genotype and cascade screening for familial hypercholesterolemia in a population-based biobank from Estonia

Genotype-guided recall of probands and subsequent cascade screening for familial hypercholesterolemia is feasible within a population-based biobank and may facilitate more appropriate clinical management.

Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

Index swapping in pooled libraries is a prevalent phenomenon that we observe at a rate of 0.2 to 6% in all sequencing runs on HiSeqX, HiSeq 4000/3000, and NovaSeq. Utilizing non-redundant dual indexing allows for the removal (flagging/filtering) of these swapped reads and eliminates swapping induced sample contamination, which is critical for sensitive applications such as RNA-seq, single cell, blood biopsy using circulating tumor DNA, or clinical sequencing.