High-coverage nanopore sequencing of samples from the 1000 Genomes Project to build a comprehensive catalog of human genetic variation.

Fewer than half of individuals with a suspected Mendelian or monogenic condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control data sets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project (1KGP) Oxford Nanopore Technologies Sequencing Consortium aims to generate LRS data from at least 800 of the 1KGP samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37× and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.

Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies.

Large-scale, multi-ethnic whole-genome sequencing (WGS) studies, such as the National Human Genome Research Institute Genome Sequencing Program's Centers for Common Disease Genomics (CCDG), play an important role in increasing diversity for genetic research. Before performing association analyses, assessing Hardy-Weinberg equilibrium (HWE) is a crucial step in quality control procedures to remove low quality variants and ensure valid downstream analyses. Diverse WGS studies contain ancestrally heterogeneous samples; however, commonly used HWE methods assume that the samples are homogeneous. Therefore, directly applying these to the whole dataset can yield statistically invalid results. To account for this heterogeneity, HWE can be tested on subsets of samples that have genetically homogeneous ancestries and the results aggregated at each variant. To facilitate valid HWE subset testing, we developed a semi-supervised learning approach that predicts homogeneous ancestries based on the genotype. This method provides a convenient tool for estimating HWE in the presence of population structure and missing self-reported race and ethnicities in diverse WGS studies. In addition, assessing HWE within the homogeneous ancestries provides reliable HWE estimates that will directly benefit downstream analyses, including association analyses in WGS studies. We applied our proposed method on the CCDG dataset, predicting homogeneous genetic ancestry groups for 60,545 multi-ethnic WGS samples to assess HWE within each group.

Multi-omic analysis of Huntington's disease reveals a compensatory astrocyte state.

The mechanisms underlying the selective regional vulnerability to neurodegeneration in Huntington's disease (HD) have not been fully defined. To explore the role of astrocytes in this phenomenon, we used single-nucleus and bulk RNAseq, lipidomics, HTT gene CAG repeat-length measurements, and multiplexed immunofluorescence on HD and control post-mortem brains. We identified genes that correlated with CAG repeat length, which were enriched in astrocyte genes, and lipidomic signatures that implicated poly-unsaturated fatty acids in sensitizing neurons to cell death. Because astrocytes play essential roles in lipid metabolism, we explored the heterogeneity of astrocytic states in both protoplasmic and fibrous-like (CD44+) astrocytes. Significantly, one protoplasmic astrocyte state showed high levels of metallothioneins and was correlated with the selective vulnerability of distinct striatal neuronal populations. When modeled in vitro, this state improved the viability of HD-patient-derived spiny projection neurons. Our findings uncover key roles of astrocytic states in protecting against neurodegeneration in HD.

Omics Approaches to Investigate the Pathogenesis of Suicide.

Suicide is the second leading cause of death in U.S. adolescents and young adults and is generally associated with a psychiatric disorder. Suicidal behavior has a complex etiology and pathogenesis. Moderate heritability suggests genetic causes. Associations between childhood and recent life adversity indicate contributions from epigenetic factors. Genomic contributions to suicide pathogenesis remain largely unknown. This article is based on a workshop held to design strategies to identify molecular drivers of suicide neurobiology that would be putative new treatment targets. The panel determined that while bulk tissue studies provide comprehensive information, single-nucleus approaches that identify cell type-specific changes are needed. While single-nuclei techniques lack information on cytoplasm, processes, spines, and synapses, spatial multiomic technologies on intact tissue detect cell alterations specific to brain tissue layers and subregions. Because suicide has genetic and environmental drivers, multiomic approaches that combine cell type-specific epigenome, transcriptome, and proteome provide a more complete picture of pathogenesis. To determine the direction of effect of suicide risk gene variants on RNA and protein expression and how these interact with epigenetic marks, single-nuclei and spatial multiomics quantitative trait loci maps should be integrated with whole-genome sequencing and genome-wide association databases. The workshop concluded with a recommendation for the formation of an international suicide biology consortium that will bring together brain banks and investigators with expertise in cutting-edge omics technologies to delineate the biology of suicide and identify novel potential treatment targets to be tested in cellular and animal models for drug and biomarker discovery to guide suicide prevention.

Rare genetic variation in fibronectin 1 (FN1) protects against APOEε4 in Alzheimer's disease.

The risk of developing Alzheimer's disease (AD) significantly increases in individuals carrying the APOEε4 allele. Elderly cognitively healthy individuals with APOEε4 also exist, suggesting the presence of cellular mechanisms that counteract the pathological effects of APOEε4; however, these mechanisms are unknown. We hypothesized that APOEε4 carriers without dementia might carry genetic variations that could protect them from developing APOEε4-mediated AD pathology. To test this, we leveraged whole-genome sequencing (WGS) data in the National Institute on Aging Alzheimer's Disease Family Based Study (NIA-AD FBS), Washington Heights/Inwood Columbia Aging Project (WHICAP), and Estudio Familiar de Influencia Genetica en Alzheimer (EFIGA) cohorts and identified potentially protective variants segregating exclusively among unaffected APOEε4 carriers. In homozygous unaffected carriers above 70 years old, we identified 510 rare coding variants. Pathway analysis of the genes harboring these variants showed significant enrichment in extracellular matrix (ECM)-related processes, suggesting protective effects of functional modifications in ECM proteins. We prioritized two genes that were highly represented in the ECM-related gene ontology terms, (FN1) and collagen type VI alpha 2 chain (COL6A2) and are known to be expressed at the blood-brain barrier (BBB), for postmortem validation and in vivo functional studies. An independent analysis in a large cohort of 7185 APOEε4 homozygous carriers found that rs140926439 variant in FN1 was protective of AD (OR = 0.29; 95% CI [0.11, 0.78], P = 0.014) and delayed age at onset of disease by 3.37 years (95% CI [0.42, 6.32], P = 0.025). The FN1 and COL6A2 protein levels were increased at the BBB in APOEε4 carriers with AD. Brain expression of cognitively unaffected homozygous APOEε4 carriers had significantly lower FN1 deposition and less reactive gliosis compared to homozygous APOEε4 carriers with AD, suggesting that FN1 might be a downstream driver of APOEε4-mediated AD-related pathology and cognitive decline. To validate our findings, we used zebrafish models with loss-of-function (LOF) mutations in fn1b-the ortholog for human FN1. We found that fibronectin LOF reduced gliosis, enhanced gliovascular remodeling, and potentiated the microglial response, suggesting that pathological accumulation of FN1 could impair toxic protein clearance, which is ameliorated with FN1 LOF. Our study suggests that vascular deposition of FN1 is related to the pathogenicity of APOEε4, and LOF variants in FN1 may reduce APOEε4-related AD risk, providing novel clues to potential therapeutic interventions targeting the ECM to mitigate AD risk.

Nanopore sequencing of 1000 Genomes Project samples to build a comprehensive catalog of human genetic variation.

Less than half of individuals with a suspected Mendelian condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control datasets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project ONT Sequencing Consortium aims to generate LRS data from at least 800 of the 1000 Genomes Project samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37x and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.

Genomic analysis of 116 autism families strengthens known risk genes and highlights promising candidates.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a strong genetic component in which rare variants contribute significantly to risk. We performed whole genome and/or exome sequencing (WGS and WES) and SNP-array analysis to identify both rare sequence and copy number variants (SNVs and CNVs) in 435 individuals from 116 ASD families. We identified 37 rare potentially damaging de novo SNVs (pdSNVs) in the cases (n = 144). Interestingly, two of them (one stop-gain and one missense variant) occurred in the same gene, BRSK2. Moreover, the identification of 8 severe de novo pdSNVs in genes not previously implicated in ASD (AGPAT3, IRX5, MGAT5B, RAB8B, RAP1A, RASAL2, SLC9A1, YME1L1) highlighted promising candidates. Potentially damaging CNVs (pdCNVs) provided support to the involvement of inherited variants in PHF3, NEGR1, TIAM1 and HOMER1 in neurodevelopmental disorders (NDD), although mostly acting as susceptibility factors with incomplete penetrance. Interpretation of identified pdSNVs/pdCNVs according to the ACMG guidelines led to a molecular diagnosis in 19/144 cases, although this figure represents a lower limit and is expected to increase thanks to further clarification of the role of likely pathogenic variants in ASD/NDD candidate genes not yet established. In conclusion, our study highlights promising ASD candidate genes and contributes to characterize the allelic diversity, mode of inheritance and phenotypic impact of de novo and inherited risk variants in ASD/NDD genes.

A multi-cohort genome-wide association study in African ancestry individuals reveals risk loci for primary open-angle glaucoma.

Primary open-angle glaucoma (POAG), the leading cause of irreversible blindness worldwide, disproportionately affects individuals of African ancestry. We conducted a genome-wide association study (GWAS) for POAG in 11,275 individuals of African ancestry (6,003 cases; 5,272 controls). We detected 46 risk loci associated with POAG at genome-wide significance. Replication and post-GWAS analyses, including functionally informed fine-mapping, multiple trait co-localization, and in silico validation, implicated two previously undescribed variants (rs1666698 mapping to DBF4P2; rs34957764 mapping to ROCK1P1) and one previously associated variant (rs11824032 mapping to ARHGEF12) as likely causal. For individuals of African ancestry, a polygenic risk score (PRS) for POAG from our mega-analysis (African ancestry individuals) outperformed a PRS from summary statistics of a much larger GWAS derived from European ancestry individuals. This study quantifies the genetic architecture similarities and differences between African and non-African ancestry populations for this blinding disease.

Whole genome analysis of rare deleterious variants adds further evidence to BRSK2 and other risk genes in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a strong genetic component in which rare variants contribute significantly to risk. We have performed whole genome and/or exome sequencing (WGS and WES) and SNP-array analysis to identify both rare sequence and copy number variants (SNVs and CNVs) in 435 individuals from 116 ASD families. We identified 37 rare potentially damaging de novo SNVs (pdSNVs) in cases (n = 144). Interestingly, two of them (one stop-gain and one missense variant) occurred in the same gene, BRSK2. Moreover, the identification of 9 severe de novo pdSNVs in genes not previously implicated in ASD (RASAL2, RAP1A, IRX5, SLC9A1, AGPAT3, MGAT3, RAB8B, MGAT5B, YME1L1), highlighted novel candidates. Potentially damaging CNVs (pdCNVs) provided support to the involvement of inherited variants in PHF3, NEGR1, TIAM1 and HOMER1 in neurodevelopmental disorders (NDD), although mostly acting as susceptibility factors with incomplete penetrance. Interpretation of identified pdSNVs/pdCNVs according to the ACMG guidelines led to a molecular diagnosis in 19/144 cases, but this figure represents a lower limit and is expected to increase thanks to further clarification of the role of likely pathogenic variants in new ASD/NDD candidates. In conclusion, our study strengthens the role of BRSK2 and other neurodevelopmental genes in ASD risk, highlights novel candidates and contributes to characterize the allelic diversity, mode of inheritance and phenotypic impact of de novo and inherited risk variants in ASD/NDD genes.

Multi-OMIC analysis of Huntington disease reveals a neuroprotective astrocyte state.

Huntington disease (HD) is an incurable neurodegenerative disease characterized by neuronal loss and astrogliosis. One hallmark of HD is the selective neuronal vulnerability of striatal medium spiny neurons. To date, the underlying mechanisms of this selective vulnerability have not been fully defined. Here, we employed a multi-omic approach including single nucleus RNAseq (snRNAseq), bulk RNAseq, lipidomics, HTT gene CAG repeat length measurements, and multiplexed immunofluorescence on post-mortem brain tissue from multiple brain regions of HD and control donors. We defined a signature of genes that is driven by CAG repeat length and found it enriched in astrocytic and microglial genes. Moreover, weighted gene correlation network analysis showed loss of connectivity of astrocytic and microglial modules in HD and identified modules that correlated with CAG-repeat length which further implicated inflammatory pathways and metabolism. We performed lipidomic analysis of HD and control brains and identified several lipid species that correlate with HD grade, including ceramides and very long chain fatty acids. Integration of lipidomics and bulk transcriptomics identified a consensus gene signature that correlates with HD grade and HD lipidomic abnormalities and implicated the unfolded protein response pathway. Because astrocytes are critical for brain lipid metabolism and play important roles in regulating inflammation, we analyzed our snRNAseq dataset with an emphasis on astrocyte pathology. We found two main astrocyte types that spanned multiple brain regions; these types correspond to protoplasmic astrocytes, and fibrous-like - CD44-positive, astrocytes. HD pathology was differentially associated with these cell types in a region-specific manner. One protoplasmic astrocyte cluster showed high expression of metallothionein genes, the depletion of this cluster positively correlated with the depletion of vulnerable medium spiny neurons in the caudate nucleus. We confirmed that metallothioneins were increased in cingulate HD astrocytes but were unchanged or even decreased in caudate astrocytes. We combined existing genome-wide association studies (GWAS) with a GWA study conducted on HD patients from the original Venezuelan cohort and identified a single-nucleotide polymorphism in the metallothionein gene locus associated with delayed age of onset. Functional studies found that metallothionein overexpressing astrocytes are better able to buffer glutamate and were neuroprotective of patient-derived directly reprogrammed HD MSNs as well as against rotenone-induced neuronal death in vitro. Finally, we found that metallothionein-overexpressing astrocytes increased the phagocytic activity of microglia in vitro and increased the expression of genes involved in fatty acid binding. Together, we identified an astrocytic phenotype that is regionally-enriched in less vulnerable brain regions that can be leveraged to protect neurons in HD.

Molecular and Clinical Epidemiology of SARS-CoV-2 Infection among Vaccinated and Unvaccinated Individuals in a Large Healthcare Organization from New Jersey.

New Jersey was among the first states impacted by the COVID-19 pandemic, with one of the highest overall death rates in the nation. Nevertheless, relatively few reports have been published focusing specifically on New Jersey. Here we report on molecular, clinical, and epidemiologic observations, from the largest healthcare network in the state, in a cohort of vaccinated and unvaccinated individuals with laboratory-confirmed SARS-CoV-2 infection. We conducted molecular surveillance of SARS-CoV-2-positive nasopharyngeal swabs collected in nine hospitals from December 2020 through June 2022, using both whole genome sequencing (WGS) and a real-time RT-PCR screening assay targeting spike protein mutations found in variants of concern (VOCs) within our region. De-identified clinical data were obtained retrospectively, including demographics, COVID-19 vaccination status, ICU admission, ventilator support, mortality, and medical history. Statistical analyses were performed to identify associations between SARS-CoV-2 variants, vaccination status, clinical outcomes, and medical risk factors. A total of 5007 SARS-CoV-2-positive nasopharyngeal swabs were successfully screened and/or sequenced. Variant screening identified three predominant VOCs, including Alpha (n = 714), Delta (n = 1877), and Omicron (n = 1802). Omicron isolates were further sub-typed as BA.1 (n = 899), BA.2 (n = 853), or BA.4/BA.5 (n = 50); the remaining 614 isolates were classified as "Other". Approximately 31.5% (1577/5007) of the samples were associated with vaccine breakthrough infections, which increased in frequency following the emergence of Delta and Omicron. Severe clinical outcomes included ICU admission (336/5007 = 6.7%), ventilator support (236/5007 = 4.7%), and mortality (430/5007 = 8.6%), with increasing age being the most significant contributor to each (p < 0.001). Unvaccinated individuals accounted for 79.7% (268/336) of ICU admissions, 78.3% (185/236) of ventilator cases, and 74.4% (320/430) of deaths. Highly significant (p < 0.001) increases in mortality were observed in individuals with cardiovascular disease, hypertension, cancer, diabetes, and hyperlipidemia, but not with obesity, thyroid disease, or respiratory disease. Significant differences (p < 0.001) in clinical outcomes were also noted between SARS-CoV-2 variants, including Delta, Omicron BA.1, and Omicron BA.2. Vaccination was associated with significantly improved clinical outcomes in our study, despite an increase in breakthrough infections associated with waning immunity, greater antigenic variability, or both. Underlying comorbidities contributed significantly to mortality in both vaccinated and unvaccinated individuals, with increasing risk based on the total number of comorbidities. Real-time RT-PCR-based screening facilitated timely identification of predominant variants using a minimal number of spike protein mutations, with faster turnaround time and reduced cost compared to WGS. Continued evolution of SARS-CoV-2 variants will likely require ongoing surveillance for new VOCs, with real-time assessment of clinical impact.

Genetic Predisposition to Neurological Complications in Patients with COVID-19.

Several studies have identified rare and common genetic variants associated with severe COVID-19, but no study has reported genetic determinants as predisposition factors for neurological complications. In this report, we identified rare/unique structural variants (SVs) implicated in neurological functions in two individuals with neurological manifestations of COVID-19. This report highlights the possible genetic link to the neurological symptoms with COVID-19 and calls for a collective effort to study these cohorts for a possible genetic linkage.

High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios.

The 1000 Genomes Project (1kGP) is the largest fully open resource of whole-genome sequencing (WGS) data consented for public distribution without access or use restrictions. The final, phase 3 release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low-coverage WGS. Here, we present a high-coverage 3,202-sample WGS 1kGP resource, which now includes 602 complete trios, sequenced to a depth of 30X using Illumina. We performed single-nucleotide variant (SNV) and short insertion and deletion (INDEL) discovery and generated a comprehensive set of structural variants (SVs) by integrating multiple analytic methods through a machine learning model. We show gains in sensitivity and precision of variant calls compared to phase 3, especially among rare SNVs as well as INDELs and SVs spanning frequency spectrum. We also generated an improved reference imputation panel, making variants discovered here accessible for association studies.

Genomic Epidemiology and Serology Associated with a SARS-CoV-2 R.1 Variant Outbreak in New Jersey.

Examining the neutralizing capacity of monoclonal antibodies (MAbs) used to treat COVID-19, as well as antibodies recovered from unvaccinated, previously vaccinated, and infected individuals, against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) remains critical to study. Here, we report on a SARS-CoV-2 nosocomial outbreak caused by the SARS-CoV-2 R.1 variant harboring the E484K mutation in a 281-bed psychiatric facility in New Jersey among unvaccinated inpatients and health care professionals (HCPs). A total of 81 inpatients and HCPs tested positive for SARS-Cov-2 by reverse transcription (RT)-PCR from 29 October 9 to 30 November 2020. The R.1 variant exhibits partial or complete resistance to two MAbs in clinical use, as well as 2 receptor binding domain MAbs and 4 N-terminal domain (NTD) MAbs. NTD MAbs against pseudovirus harboring single characteristic R.1 mutations highlight the role of S255F in loss of activity. Additionally, we note dampened neutralization capacity by plasma from individuals with previous SARS-CoV-2 infection or sera from vaccinated individuals. The relative resistance of the R.1 variant is likely lower than that of B.1.351 and closer to that of P.1 and B.1.526. The R.1 lineage has been reported in 47 states in the United States and 40 countries. Although high proportions exhibited symptoms (26% and 61% among patients and HCPs, respectively) and relative antibody resistance, we detected only 10 R.1 variants from over 2,900 samples (~0.34%) collected from January to October 2021. Among 3 vaccinated individuals previously infected with R.1, we observed robust neutralizing antibody responses against SARS-CoV-2 wild type and VOCs. IMPORTANCE The neutralizing capacities of monoclonal antibodies used to treat COVID-19 and of those recovered from previously infected and vaccinated individuals against SARS-CoV-2 variants of concern (VOCs) remain important questions. We report on a nosocomial outbreak caused by a SARS-CoV-2 R.1 variant harboring an E484K mutation among 81 unvaccinated inpatients and health care professionals. We note high attack rates with symptoms in nearly 50% of infected individuals, in sharp contrast to an unrelated institutional outbreak caused by the R.1 variant among a vaccinated population. We found little evidence of significant community spillover. This variant exhibits partial or complete resistance to two monoclonal antibodies in clinical use and dampened the neutralization capacity of convalescent-phase plasma from individuals with previous infection or sera from vaccinated individuals. Among three vaccinated individuals previously infected with R.1, we observed robust neutralizing antibody responses against SARS-CoV-2 wild type and VOCs. These findings underscore the importance of vaccination for prevention of symptomatic COVID-19 disease.

Accounting for population structure in genetic studies of cystic fibrosis.

CFTR F508del (c.1521_1523delCTT, p.Phe508delPhe) is the most common pathogenic allele underlying cystic fibrosis (CF), and its frequency varies in a geographic cline across Europe. We hypothesized that genetic variation associated with this cline is overrepresented in a large cohort (N > 5,000) of persons with CF who underwent whole-genome sequencing and that this pattern could result in spurious associations between variants correlated with both the F508del genotype and CF-related outcomes. Using principal-component (PC) analyses, we showed that variation in the CFTR region disproportionately contributes to a PC explaining a relatively high proportion of genetic variance. Variation near CFTR was correlated with population structure among persons with CF, and this correlation was driven by a subset of the sample inferred to have European ancestry. We performed genome-wide association studies comparing persons with CF with one versus two copies of the F508del allele; this allowed us to identify genetic variation associated with the F508del allele and to determine that standard PC-adjustment strategies eliminated the significant association signals. Our results suggest that PC adjustment can adequately prevent spurious associations between genetic variants and CF-related traits and are therefore effective tools to control for population structure even when population structure is confounded with disease severity and a common pathogenic variant.

Pangenome-based genome inference allows efficient and accurate genotyping across a wide spectrum of variant classes.

Typical genotyping workflows map reads to a reference genome before identifying genetic variants. Generating such alignments introduces reference biases and comes with substantial computational burden. Furthermore, short-read lengths limit the ability to characterize repetitive genomic regions, which are particularly challenging for fast k-mer-based genotypers. In the present study, we propose a new algorithm, PanGenie, that leverages a haplotype-resolved pangenome reference together with k-mer counts from short-read sequencing data to genotype a wide spectrum of genetic variation-a process we refer to as genome inference. Compared with mapping-based approaches, PanGenie is more than 4 times faster at 30-fold coverage and achieves better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (≥50 bp) and variants in repetitive regions, enabling the inclusion of these classes of variants in genome-wide association studies. PanGenie efficiently leverages the increasing amount of haplotype-resolved assemblies to unravel the functional impact of previously inaccessible variants while being faster compared with alignment-based workflows.

Nasal airway transcriptome-wide association study of asthma reveals genetically driven mucus pathobiology.

To identify genetic determinants of airway dysfunction, we performed a transcriptome-wide association study for asthma by combining RNA-seq data from the nasal airway epithelium of 681 children, with UK Biobank genetic association data. Our airway analysis identified 95 asthma genes, 58 of which were not identified by transcriptome-wide association analyses using other asthma-relevant tissues. Among these genes were MUC5AC, an airway mucin, and FOXA3, a transcriptional driver of mucus metaplasia. Muco-ciliary epithelial cultures from genotyped donors revealed that the MUC5AC risk variant increases MUC5AC protein secretion and mucus secretory cell frequency. Airway transcriptome-wide association analyses for mucus production and chronic cough also identified MUC5AC. These cis-expression variants were associated with trans effects on expression; the MUC5AC variant was associated with upregulation of non-inflammatory mucus secretory network genes, while the FOXA3 variant was associated with upregulation of type-2 inflammation-induced mucus-metaplasia pathway genes. Our results reveal genetic mechanisms of airway mucus pathobiology.

Familial long-read sequencing increases yield of de novo mutations.

Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children-a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10-8 substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone.

System-wide transcriptome damage and tissue identity loss in COVID-19 patients.

The molecular mechanisms underlying the clinical manifestations of coronavirus disease 2019 (COVID-19), and what distinguishes them from common seasonal influenza virus and other lung injury states such as acute respiratory distress syndrome, remain poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match these data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue-compartment-specific damage wrought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, evident as a function of varying viral loads during the clinical course of infection and tissue-type-specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.