Repeated mRNA vaccination sequentially boosts SARS-CoV-2-specific CD8+ T cells in persons with previous COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) hybrid immunity is more protective than vaccination or previous infection alone. To investigate the kinetics of spike-reactive T (TS) cells from SARS-CoV-2 infection through messenger RNA vaccination in persons with hybrid immunity, we identified the T cell receptor (TCR) sequences of thousands of index TS cells and tracked their frequency in bulk TCRß repertoires sampled longitudinally from the peripheral blood of persons who had recovered from coronavirus disease 2019 (COVID-19). Vaccinations led to large expansions in memory TS cell clonotypes, most of which were CD8+ T cells, while also eliciting diverse TS cell clonotypes not observed before vaccination. TCR sequence similarity clustering identified public CD8+ and CD4+ TCR motifs associated with spike (S) specificity. Synthesis of longitudinal bulk ex vivo single-chain TCRß repertoires and paired-chain TCRÉ‘ß sequences from droplet sequencing of TS cells provides a roadmap for the rapid assessment of T cell responses to vaccines and emerging pathogens.

SARS-CoV-2 specific immune responses in overweight and obese COVID-19 patients.

Obesity is a known risk factor for severe respiratory tract infections. In this prospective study, we assessed the impact of being obese or overweight on longitudinal SARS-CoV-2 humoral and cellular responses up to 18 months after infection. 274 patients provided blood samples at regular time intervals up to 18 months including obese (BMI ≥30, n=32), overweight (BMI 25-29.9, n=103) and normal body weight (BMI 18.5-24.9, n=134) SARS-CoV-2 patients. We determined SARS-CoV-2 spike-specific IgG, IgA, IgM levels by ELISA and neutralising antibody titres by neutralisation assay. RBD- and spike-specific memory B cells were investigated by ELISpot, spike- and non-spike-specific IFN-γ, IL-2 and IFN-γ/IL-2 secreting T cells by FluoroSpot and T cell receptor (TCR) sequencing was performed. Higher BMI correlated with increased COVID-19 severity. Humoral and cellular responses were stronger in overweight and obese patients than normal weight patients and associated with higher spike-specific IgG binding titres relative to neutralising antibody titres. Linear regression models demonstrated that BMI, age and COVID-19 severity correlated independently with higher SARS-CoV-2 immune responses. We found an increased proportion of unique SARS-CoV-2 specific T cell clonotypes after infection in overweight and obese patients. COVID-19 vaccination boosted humoral and cellular responses irrespective of BMI, although stronger immune boosting was observed in normal weight patients. Overall, our results highlight more severe disease and an over-reactivity of the immune system in overweight and obese patients after SARS-CoV-2 infection, underscoring the importance of recognizing overweight/obese individuals as a risk group for prioritisation for COVID-19 vaccination.

Durable immune responses after BNT162b2 vaccination in home-dwelling old adults.

Objectives: Elderly are an understudied, high-risk group vulnerable to severe COVID-19. We comprehensively analyzed the durability of humoral and cellular immune responses after BNT162b2 vaccination and SARS-CoV-2 infection in elderly and younger adults. Methods: Home-dwelling old (n = 100, median 86 years) and younger adults (n = 449, median 38 years) were vaccinated with two doses of BNT162b2 vaccine at 3-week intervals and followed for 9-months. Vaccine-induced responses were compared to home-isolated COVID-19 patients (n = 183, median 47 years). Our analysis included neutralizing antibodies, spike-specific IgG, memory B-cells, IFN-γ and IL-2 secreting T-cells and sequencing of the T-cell receptor (TCR) repertoire. Results: Spike-specific breadth and depth of the CD4+ and CD8+ TCR repertoires were significantly lower in the elderly after one and two vaccinations. Both vaccinations boosted IFN-γ and IL-2 secreting spike-specific T-cells responses, with 96 % of the elderly and 100 % of the younger adults responding after the second dose, although responses were not maintained at 9-months. In contrast, T-cell responses persisted up to 12-months in infected patients. Spike-specific memory B-cells were induced after the first dose in 87 % of the younger adults compared to 38 % of the elderly, which increased to 83 % after the second dose. Memory B-cells were maintained at 9-months post-vaccination in both vaccination groups. Neutralizing antibody titers were estimated to last for 1-year in younger adults but only 6-months in the older vaccinees. Interestingly, infected older patients (n = 15, median 75 years) had more durable neutralizing titers estimated to last 14-months, 8-months longer than the older vaccinees. Conclusions: Vaccine-induced spike-specific IgG and neutralizing antibodies were consistently lower in the older than younger vaccinees. Overall, our data provide valuable insights into the kinetics of the humoral and cellular immune response in the elderly after SARS-CoV-2 vaccination or infection, highlighting the need for two doses, which can guide future vaccine design.Clinical trials.gov; NCT04706390.

Symptom Burden and Immune Dynamics 6 to 18 Months Following Mild Severe Acute Respiratory Syndrome Coronavirus 2 Infection (SARS-CoV-2): A Case-control Study.

BACKGROUND: The burden and duration of persistent symptoms after nonsevere coronavirus disease 2019 (COVID-19) remains uncertain. This study aimed to assess postinfection symptom trajectories in home-isolated COVID-19 cases compared with age- and time- matched seronegative controls, and investigate immunological correlates of long COVID. METHODS: A prospective case-control study included home-isolated COVID-19 cases between February 28 and April 4, 2020, and followed for 12 (n = 233) to 18 (n = 149) months, and 189 age-matched severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-naive controls. We collected clinical data at baseline, 6, 12, and 18 months postinfection, and blood samples at 2, 4, 6, and 12 months for analysis of SARS-CoV-2-specific humoral and cellular responses. RESULTS: Overall, 46% (108/233) had persisting symptoms 12 months after COVID-19. Compared with controls, adult cases had a high risk of fatigue (27% excess risk, sex, and comorbidity adjusted odds ratio [aOR] 5.86; 95% confidence interval [CI], 3.27-10.5), memory problems (21% excess risk; aOR 7.42; CI, 3.51-15.67), concentration problems (20% excess risk; aOR 8.88; 95% CI, 3.88-20.35), and dyspnea (10% excess risk; aOR 2.66; 95% CI, 1.22-5.79). The prevalence of memory problems increased overall from 6 to 18 months (excess risk 11.5%; 95% CI, 1.5-21.5; P = .024) and among women (excess risk 18.7%; 95% CI, 4.4-32.9; P = .010). Longitudinal spike immunoglobulin G was significantly associated with dyspnea at 12 months. The spike-specific clonal CD4+ T-cell receptor ß depth was significantly associated with both dyspnea and number of symptoms at 12 months. CONCLUSIONS: This study documents a high burden of persisting symptoms after mild COVID-19 and suggests that infection induced SARS-CoV-2-specific immune responses may influence long-term symptoms.

CD8+ T cell clonotypes from prior SARS-CoV-2 infection predominate during the cellular immune response to mRNA vaccination.

Almost three years into the SARS-CoV-2 pandemic, hybrid immunity is highly prevalent worldwide and more protective than vaccination or prior infection alone. Given emerging resistance of variant strains to neutralizing antibodies (nAb), it is likely that T cells contribute to this protection. To understand how sequential SARS-CoV-2 infection and mRNA-vectored SARS-CoV-2 spike (S) vaccines affect T cell clonotype-level expansion kinetics, we identified and cross-referenced TCR sequences from thousands of S-reactive single cells against deeply sequenced peripheral blood TCR repertoires longitudinally collected from persons during COVID-19 convalescence through booster vaccination. Successive vaccinations recalled memory T cells and elicited antigen-specific T cell clonotypes not detected after infection. Vaccine-related recruitment of novel clonotypes and the expansion of S-specific clones were most strongly observed for CD8+ T cells. Severe COVID-19 illness was associated with a more diverse CD4+ T cell response to SARS-CoV-2 both prior to and after mRNA vaccination, suggesting imprinting of CD4+ T cells by severe infection. TCR sequence similarity search algorithms revealed myriad public TCR clusters correlating with human leukocyte antigen (HLA) alleles. Selected TCRs from distinct clusters functionally recognized S in the predicted HLA context, with fine viral peptide requirements differing between TCRs. Most subjects tested had S-specific T cells in the nasal mucosa after a 3rd mRNA vaccine dose. The blood and nasal T cell responses to vaccination revealed by clonal tracking were more heterogeneous than nAb boosts. Analysis of bulk and single cell TCR sequences reveals T cell kinetics and diversity at the clonotype level, without requiring prior knowledge of T cell epitopes or HLA restriction, providing a roadmap for rapid assessment of T cell responses to emerging pathogens.

Differences in SARS-CoV-2 Vaccine Response Dynamics Between Class-I- and Class-II-Specific T-Cell Receptors in Inflammatory Bowel Disease.

T-cells specifically bind antigens to induce adaptive immune responses using highly specific molecular recognition, and a diverse T-cell repertoire with expansion of antigen-specific clones can indicate robust immune responses after infection or vaccination. For patients with inflammatory bowel disease (IBD), a spectrum of chronic intestinal inflammatory diseases usually requiring immunomodulatory treatment, the T-cell response has not been well characterized. Understanding the patient factors that result in strong vaccination responses is critical to guiding vaccination schedules and identifying mechanisms of T-cell responses in IBD and other immune-mediated conditions. Here we used T-cell receptor sequencing to show that T-cell responses in an IBD cohort were influenced by demographic and immune factors, relative to a control cohort of health care workers (HCWs). Subjects were sampled at the time of SARS-CoV-2 vaccination, and longitudinally afterwards; TCR Vß gene repertoires were sequenced and analyzed for COVID-19-specific clones. We observed significant differences in the overall strength of the T-cell response by age and vaccine type. We further stratified the T-cell response into Class-I- and Class-II-specific responses, showing that Ad26.COV2.S vector vaccine induced Class-I-biased T-cell responses, whereas mRNA vaccine types led to different responses, with mRNA-1273 vaccine inducing a more Class-I-deficient T-cell response compared to BNT162b2. Finally, we showed that these T-cell patterns were consistent with antibody levels from the same patients. Our results account for the surprising success of vaccination in nominally immuno-compromised IBD patients, while suggesting that a subset of IBD patients prone to deficiencies in T-cell response may warrant enhanced booster protocols.

The T-Cell Response to SARS-CoV-2 Vaccination in Inflammatory Bowel Disease is Augmented with Anti-TNF Therapy.

T-cell and antibody responses to severe acute respiratory syndrome coronavirus 2 vaccination in inflammatory bowel disease patients are poorly correlated. T-cell responses are preserved by most biologic therapies, but augmented by anti-tumor necrosis factor (anti-TNF) treatment. While anti-TNF therapy blunts the antibody response, cellular immunity after vaccination is robust.

T cell receptor sequencing identifies prior SARS-CoV-2 infection and correlates with neutralizing antibodies and disease severity.

BACKGROUNDMeasuring the immune response to SARS-CoV-2 enables assessment of past infection and protective immunity. SARS-CoV-2 infection induces humoral and T cell responses, but these responses vary with disease severity and individual characteristics.METHODSA T cell receptor (TCR) immunosequencing assay was conducted using small-volume blood samples from 302 individuals recovered from COVID-19. Correlations between the magnitude of the T cell response and neutralizing antibody (nAb) titers or indicators of disease severity were evaluated. Sensitivity of T cell testing was assessed and compared with serologic testing.RESULTSSARS-CoV-2-specific T cell responses were significantly correlated with nAb titers and clinical indicators of disease severity, including hospitalization, fever, and difficulty breathing. Despite modest declines in depth and breadth of T cell responses during convalescence, high sensitivity was observed until at least 6 months after infection, with overall sensitivity ~5% greater than serology tests for identifying prior SARS-CoV-2 infection. Improved performance of T cell testing was most apparent in recovered, nonhospitalized individuals sampled > 150 days after initial illness, suggesting greater sensitivity than serology at later time points and in individuals with less severe disease. T cell testing identified SARS-CoV-2 infection in 68% (55 of 81) of samples with undetectable nAb titers (<1:40) and in 37% (13 of 35) of samples classified as negative by 3 antibody assays.CONCLUSIONThese results support TCR-based testing as a scalable, reliable measure of past SARS-CoV-2 infection with clinical value beyond serology.TRIAL REGISTRATIONSpecimens were accrued under trial NCT04338360 accessible at clinicaltrials.gov.FUNDINGThis work was funded by Adaptive Biotechnologies, Frederick National Laboratory for Cancer Research, NIAID, Fred Hutchinson Joel Meyers Endowment, Fast Grants, and American Society for Transplantation and Cell Therapy.

Longitudinal analysis of T cell receptor repertoires reveals shared patterns of antigen-specific response to SARS-CoV-2 infection.

T cells play a prominent role in orchestrating the immune response to viral diseases, but their role in the clinical presentation and subsequent immunity to SARS-CoV-2 infection remains poorly understood. As part of a population-based survey of the municipality of Vo', Italy, conducted after the initial SARS-CoV-2 outbreak, we sampled the T cell receptor (TCR) repertoires of the population 2 months after the initial PCR survey and followed up positive cases 9 and 15 months later. At 2 months, we found that 97.0% (98 of 101) of cases had elevated levels of TCRs associated with SARS-CoV-2. T cell frequency (depth) was increased in individuals with more severe disease. Both depth and diversity (breadth) of the TCR repertoire were positively associated with neutralizing antibody titers, driven mostly by CD4+ T cells directed against spike protein. At the later time points, detection of these TCRs remained high, with 90.7% (78 of 96) and 86.2% (25 of 29) of individuals having detectable signal at 9 and 15 months, respectively. Forty-three individuals were vaccinated by month 15 and showed a significant increase in TCRs directed against spike protein. Taken together, these results demonstrate the central role of T cells in mounting an immune defense against SARS-CoV-2 that persists out to 15 months.

The T-cell clonal response to SARS-CoV-2 vaccination in inflammatory bowel disease patients is augmented by anti-TNF therapy and often deficient in antibody-responders.

BACKGROUND: Vaccination against SARS-CoV-2 is a highly effective strategy to protect against infection, which is predominantly mediated by vaccine-induced antibodies. Postvaccination antibodies are robustly produced by those with inflammatory bowel disease (IBD) even on immune-modifying therapies but are blunted by anti-TNF therapy. In contrast, T-cell response which primarily determines long-term efficacy against disease progression,, is less well understood. We aimed to assess the post-vaccination T-cell response and its relationship to antibody responses in patients with inflammatory bowel disease (IBD) on immune-modifying therapies. METHODS: We evaluated IBD patients who completed SARS-CoV-2 vaccination using samples collected at four time points (dose 1, dose 2, 2 weeks after dose 2, 8 weeks after dose 2). T-cell clonal analysis was performed by T-cell Receptor (TCR) immunosequencing. The breadth (number of unique sequences to a given protein) and depth (relative abundance of all the unique sequences to a given protein) of the T-cell clonal response were quantified using reference datasets and were compared to antibody responses. RESULTS: Overall, 303 subjects were included (55% female; 5% with prior COVID) (Table). 53% received BNT262b (Pfizer), 42% mRNA-1273 (Moderna) and 5% Ad26CoV2 (J&J). The Spike-specific clonal response peaked 2 weeks after completion of the vaccine regimen (3- and 5-fold for breadth and depth, respectively); no changes were seen for non-Spike clones, suggesting vaccine specificity. Reduced T-cell clonal depth was associated with chronologic age, male sex, and immunomodulator treatment. It was preserved by non-anti-TNF biologic therapies, and augmented clonal depth was associated with anti-TNF treatment. TCR depth and breadth were associated with vaccine type; after adjusting for age and gender, Ad26CoV2 (J&J) exhibited weaker metrics than mRNA-1273 (Moderna) (p=0.01 for each) or BNT262b (Pfizer) (p=0.056 for depth). Antibody and T-cell responses were only modestly correlated. While those with robust humoral responses also had robust TCR clonal expansion, a substantial fraction of patients with high antibody levels had only a minimal T-cell clonal response. CONCLUSION: Age, sex and select immunotherapies are associated with the T-cell clonal response to SARS-CoV-2 vaccines, and T-cell responses are low in many patients despite high antibody levels. These factors, as well as differences seen by vaccine type may help guide reimmunization vaccine strategy in immune-impaired populations. Further study of the effects of anti-TNF therapy on vaccine responses are warranted.

From tides to nucleotides: Genomic signatures of adaptation to environmental heterogeneity in barnacles.

The northern acorn barnacle (Semibalanus balanoides) is a robust system to study the genetic basis of adaptations to highly heterogeneous environments. Adult barnacles may be exposed to highly dissimilar levels of thermal stress depending on where they settle in the intertidal (i.e., closer to the upper or lower tidal boundary). For instance, barnacles near the upper tidal limit experience episodic summer temperatures above recorded heat coma levels. This differential stress at the microhabitat level is also dependent on the aspect of sun exposure. In the present study, we used pool-seq approaches to conduct a genome wide screen for loci responding to intertidal zonation across the North Atlantic basin (Maine, Rhode Island, and Norway). Our analysis discovered 382 genomic regions containing SNPs which are consistently zonated (i.e., SNPs whose frequencies vary depending on their position in the rocky intertidal) across all surveyed habitats. Notably, most zonated SNPs are young and private to the North Atlantic. These regions show high levels of genetic differentiation across ecologically extreme microhabitats concomitant with elevated levels of genetic variation and Tajima's D, suggesting the action of non-neutral processes. Overall, these findings support the hypothesis that spatially heterogeneous selection is a general and repeatable feature for this species, and that natural selection can maintain functional genetic variation in heterogeneous environments.

T-cell receptor sequencing identifies prior SARS-CoV-2 infection and correlates with neutralizing antibody titers and disease severity.

Measuring the adaptive immune response to SARS-CoV-2 can enable the assessment of past infection as well as protective immunity and the risk of reinfection. While neutralizing antibody (nAb) titers are one measure of protection, such assays are challenging to perform at a large scale and the longevity of the SARS-CoV-2 nAb response is not fully understood. Here, we apply a T-cell receptor (TCR) sequencing assay that can be performed on a small volume standard blood sample to assess the adaptive T-cell response to SARS-CoV-2 infection. Samples were collected from a cohort of 302 individuals recovered from COVID-19 up to 6 months after infection. Previously published findings in this cohort showed that two commercially available SARS-CoV-2 serologic assays correlate well with nAb testing. We demonstrate that the magnitude of the SARS-CoV-2-specific T-cell response strongly correlates with nAb titer, as well as clinical indicators of disease severity including hospitalization, fever, or difficulty breathing. While the depth and breadth of the T-cell response declines during convalescence, the T-cell signal remains well above background with high sensitivity up to at least 6 months following initial infection. Compared to serology tests detecting binding antibodies to SARS-CoV-2 spike and nucleoprotein, the overall sensitivity of the TCR-based assay across the entire cohort and all timepoints was approximately 5% greater for identifying prior SARS-CoV-2 infection. Notably, the improved performance of T-cell testing compared to serology was most apparent in recovered individuals who were not hospitalized and were sampled beyond 150 days of their initial illness, suggesting that antibody testing may have reduced sensitivity in individuals who experienced less severe COVID-19 illness and at later timepoints. Finally, T-cell testing was able to identify SARS-CoV-2 infection in 68% (55/81) of convalescent samples having nAb titers below the lower limit of detection, as well as 37% (13/35) of samples testing negative by all three antibody assays. These results demonstrate the utility of a TCR-based assay as a scalable, reliable measure of past SARS-CoV-2 infection across a spectrum of disease severity. Additionally, the TCR repertoire may be useful as a surrogate for protective immunity with additive clinical value beyond serologic or nAb testing methods.

NetMix: A Network-Structured Mixture Model for Reduced-Bias Estimation of Altered Subnetworks.

A classic problem in computational biology is the identification of altered subnetworks: subnetworks of an interaction network that contain genes/proteins that are differentially expressed, highly mutated, or otherwise aberrant compared with other genes/proteins. Numerous methods have been developed to solve this problem under various assumptions, but the statistical properties of these methods are often unknown. For example, some widely used methods are reported to output very large subnetworks that are difficult to interpret biologically. In this work, we formulate the identification of altered subnetworks as the problem of estimating the parameters of a class of probability distributions that we call the Altered Subset Distribution (ASD). We derive a connection between a popular method, jActiveModules, and the maximum likelihood estimator (MLE) of the ASD. We show that the MLE is statistically biased, explaining the large subnetworks output by jActiveModules. Based on these insights, we introduce NetMix, an algorithm that uses Gaussian mixture models to obtain less biased estimates of the parameters of the ASD. We demonstrate that NetMix outperforms existing methods in identifying altered subnetworks on both simulated and real data, including the identification of differentially expressed genes from both microarray and RNA-seq experiments and the identification of cancer driver genes in somatic mutation data.

Ecological Load and Balancing Selection in Circumboreal Barnacles.

Acorn barnacle adults experience environmental heterogeneity at various spatial scales of their circumboreal habitat, raising the question of how adaptation to high environmental variability is maintained in the face of strong juvenile dispersal and mortality. Here, we show that 4% of genes in the barnacle genome experience balancing selection across the entire range of the species. Many of these genes harbor mutations maintained across 2 My of evolution between the Pacific and Atlantic oceans. These genes are involved in ion regulation, pain reception, and heat tolerance, functions which are essential in highly variable ecosystems. The data also reveal complex population structure within and between basins, driven by the trans-Arctic interchange and the last glaciation. Divergence between Atlantic and Pacific populations is high, foreshadowing the onset of allopatric speciation, and suggesting that balancing selection is strong enough to maintain functional variation for millions of years in the face of complex demography.

STARCH: copy number and clone inference from spatial transcriptomics data.

Tumors are highly heterogeneous, consisting of cell populations with both transcriptional and genetic diversity. These diverse cell populations are spatially organized within a tumor, creating a distinct tumor microenvironment. A new technology called spatial transcriptomics can measure spatial patterns of gene expression within a tissue by sequencing RNA transcripts from a grid of spots, each containing a small number of cells. In tumor cells, these gene expression patterns represent the combined contribution of regulatory mechanisms, which alter the rate at which a gene is transcribed, and genetic diversity, particularly copy number aberrations (CNAs) which alter the number of copies of a gene in the genome. CNAs are common in tumors and often promote cancer growth through upregulation of oncogenes or downregulation of tumor-suppressor genes. We introduce a new method STARCH (spatial transcriptomics algorithm reconstructing copy-number heterogeneity) to infer CNAs from spatial transcriptomics data. STARCH overcomes challenges in inferring CNAs from RNA-sequencing data by leveraging the observation that cells located nearby in a tumor are likely to share similar CNAs. We find that STARCH outperforms existing methods for inferring CNAs from RNA-sequencing data without incorporating spatial information.

Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection at Both Individual and Population Levels.

T cells are involved in the early identification and clearance of viral infections and also support the development of antibodies by B cells. This central role for T cells makes them a desirable target for assessing the immune response to SARS-CoV-2 infection. Here, we combined two high-throughput immune profiling methods to create a quantitative picture of the T-cell response to SARS-CoV-2. First, at the individual level, we deeply characterized 3 acutely infected and 58 recovered COVID-19 subjects by experimentally mapping their CD8 T-cell response through antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I presented viral peptides (class II data in a forthcoming study). Then, at the population level, we performed T-cell repertoire sequencing on 1,815 samples (from 1,521 COVID-19 subjects) as well as 3,500 controls to identify shared "public" T-cell receptors (TCRs) associated with SARS-CoV-2 infection from both CD8 and CD4 T cells. Collectively, our data reveal that CD8 T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the T-cell response to SARS-CoV-2 peaks about one to two weeks after infection and is detectable for at least several months after recovery. As an application of these data, we trained a classifier to diagnose SARS-CoV-2 infection based solely on TCR sequencing from blood samples, and observed, at 99.8% specificity, high early sensitivity soon after diagnosis (Day 3-7 = 85.1% [95% CI = 79.9-89.7]; Day 8-14 = 94.8% [90.7-98.4]) as well as lasting sensitivity after recovery (Day 29+/convalescent = 95.4% [92.1-98.3]). These results demonstrate an approach to reliably assess the adaptive immune response both soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points. This blood-based molecular approach to characterizing the cellular immune response has applications in clinical diagnostics as well as in vaccine development and monitoring.

netNMF-sc: leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysis.

Single-cell RNA-sequencing (scRNA-seq) enables high-throughput measurement of RNA expression in single cells. However, because of technical limitations, scRNA-seq data often contain zero counts for many transcripts in individual cells. These zero counts, or dropout events, complicate the analysis of scRNA-seq data using standard methods developed for bulk RNA-seq data. Current scRNA-seq analysis methods typically overcome dropout by combining information across cells in a lower-dimensional space, leveraging the observation that cells generally occupy a small number of RNA expression states. We introduce netNMF-sc, an algorithm for scRNA-seq analysis that leverages information across both cells and genes. netNMF-sc learns a low-dimensional representation of scRNA-seq transcript counts using network-regularized non-negative matrix factorization. The network regularization takes advantage of prior knowledge of gene-gene interactions, encouraging pairs of genes with known interactions to be nearby each other in the low-dimensional representation. The resulting matrix factorization imputes gene abundance for both zero and nonzero counts and can be used to cluster cells into meaningful subpopulations. We show that netNMF-sc outperforms existing methods at clustering cells and estimating gene-gene covariance using both simulated and real scRNA-seq data, with increasing advantages at higher dropout rates (e.g., >60%). We also show that the results from netNMF-sc are robust to variation in the input network, with more representative networks leading to greater performance gains.

Identifying structural variants using linked-read sequencing data.

MOTIVATION: Structural variation, including large deletions, duplications, inversions, translocations and other rearrangements, is common in human and cancer genomes. A number of methods have been developed to identify structural variants from Illumina short-read sequencing data. However, reliable identification of structural variants remains challenging because many variants have breakpoints in repetitive regions of the genome and thus are difficult to identify with short reads. The recently developed linked-read sequencing technology from 10X Genomics combines a novel barcoding strategy with Illumina sequencing. This technology labels all reads that originate from a small number (∼5 to 10) DNA molecules ∼50 Kbp in length with the same molecular barcode. These barcoded reads contain long-range sequence information that is advantageous for identification of structural variants. RESULTS: We present Novel Adjacency Identification with Barcoded Reads (NAIBR), an algorithm to identify structural variants in linked-read sequencing data. NAIBR predicts novel adjacencies in an individual genome resulting from structural variants using a probabilistic model that combines multiple signals in barcoded reads. We show that NAIBR outperforms several existing methods for structural variant identification-including two recent methods that also analyze linked-reads-on simulated sequencing data and 10X whole-genome sequencing data from the NA12878 human genome and the HCC1954 breast cancer cell line. Several of the novel somatic structural variants identified in HCC1954 overlap known cancer genes. AVAILABILITY AND IMPLEMENTATION: Software is available at compbio.cs.brown.edu/software. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.