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Lin, B.

Publications and source records attributed to Lin, B..

At least 73 records · Page 4Linked to original sources

Comprehensive analyses of RNA-seq and genome-wide data point to enrichment of neuronal cell type subsets in neuropsychiatric disorders

Neurological and psychiatric disorders, including substance use disorders share a range of symptoms, which could be the result of shared genetic background. Many genetic loci have been identified for these disorders using genome-wide association studies, but conclusive evidence about cell types wherein these loci are active is lacking. We aimed to uncover implicated brain cell types in neuropsychiatric traits and to assess consistency in results across RNA datasets and methods. We therefore comprehensively employed cell-type enrichment methods by integrating single-cell transcriptomic data from mouse brain regions with an unprecedented dataset of 42 human genome-wide association study results of neuropsychiatric, substance use and behavioral/quantitative brain-related traits (n=12,544,007 individuals). Single-cell transcriptomic datasets from the Karolinska Institute and the 10x Genomics dataset were used. Cell type enrichment was determined using Linkage Disequilibrium Score Regression, Multi-marker Analysis of GenoMic Annotation, and Data-driven Expression Prioritized Integration for Complex Traits. We found the largest degree of consistency across methods for implication of pyramidal cells in schizophrenia and cognitive performance. For other phenotypes, such as bipolar disorder, two methods implicated the same cell types, i.e. medium spiny neurons and pyramidal cells. For autism spectrum disorders and anorexia nervosa, no consistency in implicated cell types was observed across methods. We found no evidence for astrocytes being consistently implicated in neuropsychiatric traits. In conclusion, we provide comprehensive evidence for a subset of neuronal cell types being consistently implicated in several, but not all psychiatric disorders, while non-neuronal cell types seem less implicated.

genomics↗

Complex effects of kinase localization revealed by compartment-specific regulation of protein kinase A activity

Kinase activity in signaling networks frequently depends on regulatory subunits that can both inhibit activity by interacting with the catalytic subunits and target the kinase to distinct molecular partners and subcellular compartments. Here, using a new synthetic molecular interaction system, we show that translocation of a regulatory subunit of the protein kinase A (PKA-R) to the plasma membrane has a paradoxical effect on the membrane kinase activity. It can both enhance it at lower translocation levels, even in the absence of signaling inputs, and inhibit it at higher translocation levels, suggesting its role as a linker that can both couple and decouple signaling processes in a concentration-dependent manner. We further demonstrate that superposition of gradients of PKA-R abundance across single cells can control the directionality of cell migration, reversing it at high enough input levels. Thus complex in vivo patterns of PKA-R localization can drive complex phenotypes, including cell migration.

systems biology↗

NOMA: a high-throughput microchip for robust sequential measurements of secretions from the same single-cells

Despite recent advances in single-cell analysis technologies, lacking simple methods to keep the live single-cells traceable for longitudinal detection reliably poses a significant obstacle in single-cell secretion analysis. Here we reported the high-density NOMA (narrow-opening microwell array) microchip that realized the retention of[≥] 97% of trapped single cells in dedicated spatial locations during repetitive detection procedures, verified with both adherent and suspension cells by two researchers independently. We applied it in monitoring single-cell protein secretions sequentially from the same single cells, and we found the digital protein secretion patterns dominate the protein secretion. We also demonstrated the microchip for longitudinally tracking IL-8 and the CD81+EV secretions from the same single-cells over days, which revealed the presence of "super secretors" within the cell population be more persistent to secrete protein or extracellular vesicle for an extended period. The NOMA platform reported here is simple, robust, and easy to operate for tracking sequential measurements from the same single cells, representing a novel and informative tool to inspire new observations in biomedical research. Table of Contents Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=66 SRC="FIGDIR/small/427049v4_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@aa69c7org.highwire.dtl.DTLVardef@6bc79org.highwire.dtl.DTLVardef@3fcbbforg.highwire.dtl.DTLVardef@597f4b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

Proton receptors regulate synapse-specific reconsolidation in the amygdala

When an extinction procedure is performed within the reconsolidation window, the original aversive memory can be replaced by one that is less traumatic. Recent studies revealed that carbon dioxide (CO2) inhalation during retrieval enhances memory lability. However, the effects of CO2 inhalation on the central nervous system can be extensive, and there is lack of evidence suggesting that the effects of CO2 are selective to a reactivated memory. We discovered that CO2 inhalation paired with memory retrieval potentiates the specific aversive memory trace, resulting in greater memory lability. The specific effects of CO2 depend on acid-sensing ion channels (ASICs), the proton receptors that are involved in synaptic transmission and plasticity in the amygdala. In addition, CO2 inhalation alters memory lability via synaptic plasticity at selectively targeted synapses. Overall, our results suggest that inhaling CO2 during the retrieval event increases the lability of an aversive memory through a synapse-specific reconsolidation process.

neuroscience↗

First demonstration of the FLASH effect with ultrahigh dose-rate high energy X-rays

Ultrahigh dose-rate (FLASH) radiotherapy has attracted immense attention because of its tumor control efficiency and healthy tissue protection during preclinical experiments with electrons, kilo-voltage X-rays, and protons. Using high-energy X-rays (HEXs) in FLASH is advantageous owing to its deep penetration, small divergence, and cost-effectiveness. This is the first report on the implementation of HEXs with FLASH (HEX-FLASH) and its corresponding application in vivo. With a high-current and high-energy superconducting linear accelerator, FLASH with a good dose rate and high penetration was achieved. Breast cancers artificially induced in BAL b/c mice were efficiently controlled, and normal tissues surrounding the thorax/abdomen in C57BL/6 mice were protected from radiation with HEX-FLASH. Theoretical analyses of cellular responses following HEX-FLASH irradiation were performed to interpret the experimental results and design further experiments. Thus, this study highlights the generation of HEX-FLASH for the first time and its potential in future clinical applications.

cancer biology↗

Plasma proteomics reveals tissue-specific cell death and mediators of cell-cell interactions in severe COVID-19 patients

COVID-19 has caused over 1 million deaths globally, yet the cellular mechanisms underlying severe disease remain poorly understood. By analyzing several thousand plasma proteins in 306 COVID-19 patients and 78 symptomatic controls over serial timepoints using two complementary approaches, we uncover COVID-19 host immune and non-immune proteins not previously linked to this disease. Integration of plasma proteomics with nine published scRNAseq datasets shows that SARS-CoV-2 infection upregulates monocyte/macrophage, plasmablast, and T cell effector proteins. By comparing patients who died to severely ill patients who survived, we identify dynamic immunomodulatory and tissue-associated proteins associated with survival, providing insights into which host responses are beneficial and which are detrimental to survival. We identify intracellular death signatures from specific tissues and cell types, and by associating these with angiotensin converting enzyme 2 (ACE2) expression, we map tissue damage associated with severe disease and propose which damage results from direct viral infection rather than from indirect effects of illness. We find that disease severity in lung tissue is driven by myeloid cell phenotypes and cell-cell interactions with lung epithelial cells and T cells. Based on these results, we propose a model of immune and epithelial cell interactions that drive cell-type specific and tissue-specific damage in severe COVID-19.

systems biology↗

Genome-wide analyses point to differences in genetic architecture of BMI between tall and short people

To examine differences in the genetic architecture of BMI between tall and short people, we conducted genome-wide and follow-up analyses using UK Biobank data. We identify 57 loci as height-specific, detect differences in SNP-based heritability between tall and short people and show how genetic correlations between the two rises during the lifespan. Using phenome-wide analyses (PHEWAS), a significant association between a short people-specific locus on MC4R and energy portion size was detected. We identify one locus (GPC5-GPC6) with different effect directions on BMI in short and tall people. PHEWAS indicates this locus is associated with bone mineral density. Transcriptome-wide analyses hint that genes differentially associated with BMI in short vs tall people are enriched in brain tissue. Our findings highlight the role of height in the genetic underpinnings of BMI, provide biological insight into mechanisms underlying height-dependent differences in BMI and show that in short and tall people obesity is a risk factor that differentially increases susceptibility for disease.

genetics↗

A novel saline-soluble, rapidly-metabolized RyR1 inhibitor rescues volatile anesthesia-induced death and environmental heat stroke in a mouse model relevant to malignant hyperthermia

Mutations in the type 1 ryanodine receptor (RyR1), a Ca2+ release channel in skeletal muscle, hyperactivate the channel to cause malignant hyperthermia (MH) and are implicated in severe heat stroke. Dantrolene, the only approved drug for MH, has the disadvantages of having very poor water solubility and long plasma half-life. We show here that a novel RyR1-selective inhibitor, 6,7-(methylenedioxy)-1-octyl-4-quinolone-3-carboxylic acid (Compound 1, Cpd1), effectively prevents and treats MH and heat stroke in several mouse models relevant to MH. Cpd1 reduced resting intracellular Ca2+, inhibited halothane- and isoflurane-induced Ca2+ release, suppressed caffeine-induced contracture in skeletal muscle, reduced sarcolemmal cation influx, and prevented or reversed the fulminant MH crisis induced by isoflurane anesthesia and rescued animals from heat stroke caused by environmental heat stress. Notably, Cpd1 has great advantages of better water solubility and rapid clearance in vivo over dantrolene. Cpd1 has the potential to be a promising new candidate for effective treatment of patients carrying RyR1 mutations.

pharmacology and toxicology↗

Interacting evolutionary pressures drive mutation dynamics and health outcomes in aging blood

A small population of self-renewing, hematopoietic stem cells continuously reconstitutes our immune system. As we age, these cells, or their pluripotent descendants, accumulate somatic mutations; some of these mutations provide selection advantages and increase in frequency in the peripheral blood cell population. This process of positive selection, deemed age-related clonal hematopoiesis (ARCH), is associated with increased risk for cardiac disease and blood malignancies, like acute myeloid leukemia (AML). However, it remains unclear why some people with ARCH do not progress to AML, even when their blood cells harbor well-known AML driver mutations. Here, we examine whether negative selection can play a role in determining AML progression by modelling the complex interplay of positive and negative selective processes. Using a novel approach combining deep learning and population genetic models, we detect pervasive negative selection in targeted sequence data from the blood of 92 pre-AML individuals and 385 healthy controls. We find that the relative proportion of passenger to driver mutations is critical in determining if the selective advantage conferred to a cell by a known driver mutation is able to overwhelm negative selection acting on passenger mutations and allow clones harbouring disease-predisposing mutations to rise to dominance. We find that a subset of non-driver genes is enriched for mildly damaging mutations in healthy individuals fitting purifying models of evolution suggesting that mutations in these genes might confer a protective role against disease-predisposing clonal expansions. Through exploring non drivercentric models of evolution, we show how different classes of evolution act to shape hematopoietic dynamics and subsequent health outcome which may better inform disease prediction and unveil novel therapeutic targets. We anticipate that our results and modelling techniques can be broadly applied to identify both driver mutations and those mildly damaging passenger mutations, as well as help understand the early evolution of cancer in other cells and tissues.

cancer biology↗

Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, creates an urgent need for identifying molecular mechanisms that mediate viral entry, propagation, and tissue pathology. Cell membrane bound angiotensin-converting enzyme 2 (ACE2) and associated proteases, transmembrane protease serine 2 (TMPRSS2) and Cathepsin L (CTSL), were previously identified as mediators of SARS-CoV2 cellular entry. Here, we assess the cell type-specific RNA expression of ACE2, TMPRSS2, and CTSL through an integrated analysis of 107 single-cell and single-nucleus RNA-Seq studies, including 22 lung and airways datasets (16 unpublished), and 85 datasets from other diverse organs. Joint expression of ACE2 and the accessory proteases identifies specific subsets of respiratory epithelial cells as putative targets of viral infection in the nasal passages, airways, and alveoli. Cells that co-express ACE2 and proteases are also identified in cells from other organs, some of which have been associated with COVID-19 transmission or pathology, including gut enterocytes, corneal epithelial cells, cardiomyocytes, heart pericytes, olfactory sustentacular cells, and renal epithelial cells. Performing the first meta-analyses of scRNA-seq studies, we analyzed 1,176,683 cells from 282 nasal, airway, and lung parenchyma samples from 164 donors spanning fetal, childhood, adult, and elderly age groups, associate increased levels of ACE2, TMPRSS2, and CTSL in specific cell types with increasing age, male gender, and smoking, all of which are epidemiologically linked to COVID-19 susceptibility and outcomes. Notably, there was a particularly low expression of ACE2 in the few young pediatric samples in the analysis. Further analysis reveals a gene expression program shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues, including genes that may mediate viral entry, subtend key immune functions, and mediate epithelial-macrophage cross-talk. Amongst these are IL6, its receptor and co-receptor, IL1R, TNF response pathways, and complement genes. Cell type specificity in the lung and airways and smoking effects were conserved in mice. Our analyses suggest that differences in the cell type-specific expression of mediators of SARS-CoV-2 viral entry may be responsible for aspects of COVID-19 epidemiology and clinical course, and point to putative molecular pathways involved in disease susceptibility and pathogenesis.

bioinformatics↗

The Nucleocapsid Protein of SARS-CoV-2 Abolished Pluripotency in Human Induced Pluripotent Stem Cells

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is raging across the world, leading to a global mortality rate of 3.4% (estimated by World Health Organization in March 2020). As a potential vaccine and therapeutic target, the nucleocapsid protein of SARS-CoV-2 (nCoVN) functions in packaging the viral genome and viral self-assembly. To investigate the biological effects of nCoVN to human stem cells, genetically engineered human induced pluripotent stem cells (iPSC) expressing nCoVN (iPSC-nCoVN) were generated by lentiviral expression systems, in which the expression of nCoVN could be induced by the doxycycline. The proliferation rate of iPSC-nCoVN was decreased. Unexpectedly, the morphology of iPSC started to change after nCoVN expression for 7 days. The pluripotency marker TRA-1-81 were not detectable in iPSC-nCoVN after a four-day induction. Meanwhile, iPSC-nCoVN lost the ability for differentiation into cardiomyocytes with a routine differentiation protocol. The RNA-seq data of iPSC-nCoVN (induction for 30 days) and immunofluorescence assays illustrated that iPSC-nCoVN were turning to fibroblast-like cells. Our data suggested that nCoVN disrupted the pluripotent properties of iPSC and turned them into other types of cells, which provided a new insight to the pathogenic mechanism of SARS-CoV-2.

cell biology↗

Angiotensin II induces apoptosis in human induced pluripotent stem cell-derived cardiomyocytes

BackgroundThe renin-angiotensin system (RAS) functions fundamentally to regulate the pathological process of cardiovascular diseases, such as heart failure and hypertension. As the major effector in RAS, angiotensin II activates angiotensin II receptors to initiate the downstream pathways, which lead to the phenotypes including apoptosis, hypertrophy, and cardiac remodeling. Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) are being applied as a promising platform for personalized medicine to heart diseases. However, whether angiotensin II induces apoptosis in iPSC-CM is still obscure, which raises an uncertainty about the clinical applications of iPSC-CM. MethodsWe treated iPSC-CM with angiotensin II at eight concentrations (0 nM, 1 nM, 10 nM, 100 nM, 1 M, 10 M, 100 M and 1 mM) and four incubation durations (24 hours, 48 hours, 6 days and 10 days), then PrestoBlue reagent and a apoptosis marker were used to examine the viability and apoptosis status of cardiomyocytes from each group. The expression levels of some apoptosis and proliferation related genes were also analyzed. ResultsHigh concentration angiotensin II with a long-term treatment caused apoptosis and cell viability drop-off in iPSC-CM. Specifically, under a 10-day treatment with 1 mM angiotensin II, the viability of iPSC-CM was reduced by an average of 41% (p=2.073E-08), and the percentage of apoptotic cells was 2.74 times higher than the controls averagely (p=6.248E-12). The data mining of previous RNA-seq data revealed that angiotensin II receptor type I was the major receptor in iPSC-CM. Conclusions: For the first time, our data confirmed the apoptotic effect of angiotensin II to iPSC-CM. The angiotensin II concentrations and exposure time for apoptosis induction were depicted in our study, which provided supports to iPSC-CM as an in vitro model for cardiovascular disease study.

cell biology↗

Machine learning approach reveals heterogeneous responses to FAK and Rho GTPases inhibition on smooth muscle spheroid formation

Atherosclerosis and vascular injury are characterized by neointima formation caused by the aberrant accumulation and proliferation of vascular smooth muscle cells (VSMCs) within the vessel wall. Understanding how to control VSMCs would advance the effort to treat vascular disease. However, the response to treatments aimed at VSMCs is often different among patients with the same disease condition, suggesting patient-specific heterogeneity in VSMCs. Here, we present an experimental and computational method called HETEROID (Heterogeneous Spheroid), which examines the heterogeneity of the responses to drug treatments at the single-spheroid level by combining a VSMC spheroid model and machine learning (ML) analysis. First, we established a VSMC spheroid model that mimics neointima formation induced by atherosclerosis and vascular injury. We found that FAK-Rac/Rho, but not Cdc42, pathways regulate the VSMC spheroid formation through N-cadherin. Then, to identify the morphological subpopulations of drug-perturbed spheroids, we used an ML framework that combines deep learning-based spheroid segmentation and morphological clustering analysis. Our ML approach reveals that FAK, Rac, Rho, and Cdc42 inhibitors differentially affect the spheroid morphology, suggesting there exist multiple distinct pathways governing VSMC spheroid formation. Overall, our HETEROID pipeline enables detailed quantitative characterization of morphological changes in neointima formation, that occurs in vivo, by single-spheroid analysis of various drug treatments.

cell biology↗

Genetic correlation between background EEG oscillations and genetic generalized epilepsy

ObjectiveParoxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations. MethodsConfounding factors, including the heterogeneous etiology of epilepsies and medication effects hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a GWAS on epilepsy (n=12,803 people with epilepsy and 24,218 controls) with that from a GWAS on background EEG (n=8,425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta and theta. We replicated our findings in an independent epilepsy replication dataset (n=4851 people with epilepsy and 20,428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores and Mendelian randomization analyses. ResultsOur analyses show strong genetic correlations between genetic generalized epilepsy (GGE) with background EEG oscillations, primarily with the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations. SignificanceOur results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic work-up of epilepsy.

genetics↗

Functional conservation of lncRNA JPX despite sequence and structural divergence

Long noncoding RNAs (lncRNAs) have been identified in all eukaryotes and are most abundant in the human genome. However, the functional importance and mechanisms of action for human lncRNAs are largely unknown. Using comparative sequence, structural, and functional analyses, we characterize the evolution and molecular function of human lncRNA JPX. We find that human JPX and its mouse homolog, lncRNA Jpx, have deep divergence in their nucleotide sequences and RNA secondary structures. Despite such differences, both lncRNAs demonstrate robust binding to CTCF, a protein that is central to Jpxs role in X chromosome inactivation. In addition, our functional rescue experiment using Jpx-deletion mutant cells, shows that human JPX can functionally complement the loss of Jpx in mouse embryonic stem cells. Our findings support a model for functional conservation of lncRNAs independent from sequence and structural changes. The study provides mechanistic insight into the evolution of lncRNA function.

molecular biology↗

Large particle fluorescence-activated cell sorting enables high quality single cell RNA-sequencing and functional analysis of adult cardiomyocytes

RationaleSingle cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to profile the transcriptome at single cell resolution, enabling comprehensive analysis of cellular trajectories and heterogeneity during development and disease. However, the use of scRNA-seq remains limited in cardiac pathology owing to technical difficulties associated with the isolation of single adult cardiomyocytes (CMs).\n\nObjectiveWe investigated the capability of large-particle fluorescence-activated cell sorting (LP-FACS) for isolation of viable single adult CMs.\n\nMethods and ResultsWe found that LP-FACS readily outperforms conventional FACS for isolation of struturally competent CMs, including large CMs. Additionally, LP-FACS enables isolation of fluorescent CMs from mosaic models. Importantly, the sorted CMs allow generation of high-quality scRNA-seq libraries. Unlike CMs isolated via previously utilized fluidic or manual methods, LP-FAC-isolated CMs generate libraries exhibiting normal levels of mitochondrial transcripts. Moreover, LP-FACS isolated CMs remain functionally competent and can be studied for contractile properties.\n\nConclusionsOur study enables high quality dissection of adult CM biology at single-cell resolution.

cell biology↗

Multiplexed Profiling of Single-cell Extracellular Vesicles Secretion

Extracellular vesicles (EVs) are important intercellular mediators regulating health and disease. Conventional EVs surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EVs secretion. Herein, by using spatially patterned antibodies barcode, we realized multiplexed profiling of single-cell EVs secretion from more than 1000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to deep understanding of previously undifferentiated single cell heterogeneity underlying EVs secretion. Notably, we observed the decrement of certain EV phenotypes (e.g. CD63+EVs) were associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EVs secretion and cytokines secretion simultaneously from the same single cells to investigate multidimensional spectrum of intercellular communications, from which we resolved three functional subgroups with distinct secretion profiles by visualized clustering. In particular, we found EVs secretion and cytokines secretion were generally dominated by different cell subgroups. The technology introduced here enables comprehensive evaluation of EVs secretion heterogeneity at single cell level, which may become an indispensable tool to complement current single cell analysis and EV research.\n\nSignificanceExtracellular vesicles (EVs) are cell derived nano-sized particles medicating cell-cell communication and transferring biology information molecules like nucleic acids to regulate human health and disease. Conventional methods for EV surface markers profiling cant tell the differences in the quantity and phenotypes of EVs secretion between cells. To address this need, we developed a platform for profiling an array of surface markers on EVs from large numbers of single cells, enabling more comprehensive monitoring of cellular communications. Single cell EVs secretion assay led to previously unobserved cell heterogeneity underlying EVs secretion, which might open up new avenues for studying cell communication and cell microenvironment in both basic and clinical research.

bioengineering↗

Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

Large-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short read whole genome sequencing. However, standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the advantages of short reads. Starting from only [~]1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as Linked-Reads. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes (Weisenfeld et al. 2017). In this manuscript, we show the advantages of Linked-Reads over standard short read approaches for reference based analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

genomics↗