ScSNViz: a user-friendly toolset for visualization and analysis of Cell-Specific Expressed SNVs.

Motivation: Understanding genetic variation at the single-cell level is crucial for insights into cellular heterogeneity, clonal evolution, and gene expression regulation, but there is a scarcity of tools for visualizing and analyzing cell-level genetic variants. Results: We introduce scSNViz, a comprehensive R-based toolset for visualization and analysis of cell-specific expressed Single Nucleotide Variants (sceSNVs) within cell-barcoded single-cell RNA-sequencing (scRNA-seq) data. ScSNViz offers 3D sceSNV visualization capabilities for dimensionally reduced scRNA-seq gene expression data, compatibility with popular scRNA-seq processing tools like Seurat, cell-type classification tools such as SingleR and scType, and trajectory inference computation using Slingshot. Furthermore, scSNViz conducts estimation, summary, and graphical representation of statistical metrics pertaining to sceSNVs distribution and expression across individual cells. It also provides support for the analysis of individual sceSNVs as well as sets comprising multiple expressed sceSNVs of interest. Availability: ScSNViz is implemented as user-friendly R-scripts, freely available on https://horvathlab.github.io/NGS/scSNViz , supported by help utilities, and requiring no specialized bioinformatics skills for use.

Embryonic stem cell factor FOXD3 (Genesis) defects in gastrointestinal stromal tumors.

Gastrointestinal stromal tumors (GISTs) are mesenchymal neoplasms, believed to originate from the interstitial cells of Cajal (ICC), often caused by overexpression of tyrosine kinase receptors (TKR) KIT or PDGFRA. Here, we present evidence that the embryonic stem cell factor FOXD3, first identified as 'Genesis' and involved in both gastrointestinal and neural crest cell development, is implicated in GIST pathogenesis; its involvement is investigated both in vitro and in zebrafish and a mouse model of FOXD3 deficiency. Samples from a total of 58 patients with wild-type GISTs were used for molecular analyses, including Sanger sequencing, comparative genomic hybridization, and methylation analysis. Immunohistochemistry and western blot evaluation were used to assess FOXD3 expression. Additionally, we conducted in vitro functional studies in tissue samples and in transfected cells to confirm the pathogenicity of the identified genetic variants. Germline partially inactivating FOXD3 sequence variants (p.R54H and p.Ala88_Gly91del) were found in patients with isolated GISTs. Chromosome 1p loss was the most frequent chromosomal abnormality identified in tumors. In vitro experiments demonstrate the impairment of FOXD3 in the presence of those variants. Animal studies showed disruption of the GI neural network and changes in the number and distribution in the ICC. FOXD3 suppresses KIT expression in human cells; its inactivation led to an increase in ICC in zebrafish, as well as mice, providing evidence for a functional link between FOXD3 defects and KIT overexpression leading to GIST formation.

TRIM28 promotes luminal cell plasticity in a mouse model of prostate cancer.

The Tripartite motif-containing 28 (TRIM28) transcriptional cofactor is significantly upregulated in high-grade and metastatic prostate cancers. To study the role of TRIM28 in prostate cancer progression in vivo, we generated a genetically-engineered mouse model, combining prostate-specific inactivation of Trp53, Pten and Trim28. Trim28 inactivated NPp53T mice developed an inflammatory response and necrosis in prostate lumens. By conducting single-cell RNA sequencing, we found that NPp53T prostates had fewer luminal cells resembling proximal luminal lineage cells, which are cells with progenitor activity enriched in proximal prostates and prostate invagination tips in wild-type mice with analogous populations in human prostates. However, despite increased apoptosis and reduction of cells expressing proximal luminal cell markers, we found that NPp53T mouse prostates evolved and progressed to invasive prostate carcinoma with a shortened overall survival. Altogether, our findings suggest that TRIM28 promotes expression of proximal luminal cell markers in prostate tumor cells and provides insights into TRIM28 function in prostate tumor plasticity.

BRCA1 deficiency in mature CD8+ T lymphocytes impairs antitumor immunity.

Women with BRCA1 germline mutations have approximately an 80% lifetime chance of developing breast cancer. While the tumor suppressor function of BRCA1 in breast epithelium has been studied extensively, it is not clear whether BRCA1 deficiency in non-breast somatic cells also contribute to tumorigenesis. Here, we report that mouse Brca1 knockout (KO) in mature T lymphocytes compromises host antitumor immune response to transplanted syngeneic mouse mammary tumors. T cell adoptive transfer further corroborates CD8+ T cell-intrinsic impact of Brca1 KO on antitumor adaptive immunity. T cell-specific Brca1 KO mice exhibit fewer total CD8+, more exhausted, reduced cytotoxic, and reduced memory tumor-infiltrating T cell populations. Consistent with the preclinical data, cancer-free BRCA1 mutation-carrying women display lower abundance of circulating CD8+ lymphocytes than the age-matched control group. Thus, our findings support the notion that BRCA1 deficiency in adaptive immunity could contribute to BRCA1-related tumorigenesis. We also suggest that prophylactic boosting of adaptive immunity may reduce cancer incidence among at-risk women.

Prostate cancer cell-platelet bidirectional signaling promotes calcium mobilization, invasion and apoptotic resistance via distinct receptor-ligand pairs.

Platelets play a crucial role in cancer and thrombosis. However, the receptor-ligand repertoire mediating prostate cancer (PCa) cell-platelet interactions and ensuing consequences have not been fully elucidated. Microvilli emanating from the plasma membrane of PCa cell lines (RC77 T/E, MDA PCa 2b) directly contacted individual platelets and platelet aggregates. PCa cell-platelet interactions were associated with calcium mobilization in platelets, and translocation of P-selectin and integrin αIIbß3 onto the platelet surface. PCa cell-platelet interactions reciprocally promoted PCa cell invasion and apoptotic resistance, and these events were insensitive to androgen receptor blockade by bicalutamide. PCa cells were exceedingly sensitive to activation by platelets in vitro, occurring at a PCa cell:platelet coculture ratio as low as 1:10 (whereas PCa patient blood contains 1:2,000,000 per ml). Conditioned medium from cocultures stimulated PCa cell invasion but not apoptotic resistance nor platelet aggregation. Candidate transmembrane signaling proteins responsible for PCa cell-platelet oncogenic events were identified by RNA-Seq and broadly divided into 4 major categories: (1) integrin-ligand, (2) EPH receptor-ephrin, (3) immune checkpoint receptor-ligand, and (4) miscellaneous receptor-ligand interactions. Based on antibody neutralization and small molecule inhibitor assays, PCa cell-stimulated calcium mobilization in platelets was found to be mediated by a fibronectin1 (FN1)-αIIbß3 signaling axis. Platelet-stimulated PCa cell invasion was facilitated by a CD55-adhesion G protein coupled receptor E5 (ADGRE5) axis, with contribution from platelet cytokines CCL3L1 and IL32. Platelet-stimulated PCa cell apoptotic resistance relied on ephrin-EPH receptor and lysophosphatidic acid (LPA)-LPA receptor (LPAR) signaling. Of participating signaling partners, FN1 and LPAR3 overexpression was observed in PCa specimens compared to normal prostate, while high expression of CCR1 (CCL3L1 receptor), EPHA1 and LPAR5 in PCa was associated with poor patient survival. These findings emphasize that non-overlapping receptor-ligand pairs participate in oncogenesis and thrombosis, highlighting the complexity of any contemplated clinical intervention strategy.

SCExecute: custom cell barcode-stratified analyses of scRNA-seq data.

MOTIVATION: In single-cell RNA-sequencing (scRNA-seq) data, stratification of sequencing reads by cellular barcode is necessary to study cell-specific features. However, apart from gene expression, the analyses of cell-specific features are not sufficiently supported by available tools designed for high-throughput sequencing data. RESULTS: We introduce SCExecute, which executes a user-provided command on barcode-stratified, extracted on-the-fly, single-cell binary alignment map (scBAM) files. SCExecute extracts the alignments with each cell barcode from aligned, pooled single-cell sequencing data. Simple commands, monolithic programs, multi-command shell scripts or complex shell-based pipelines are then executed on each scBAM file. scBAM files can be restricted to specific barcodes and/or genomic regions of interest. We demonstrate SCExecute with two popular variant callers-GATK and Strelka2-executed in shell-scripts together with commands for BAM file manipulation and variant filtering, to detect single-cell-specific expressed single nucleotide variants from droplet scRNA-seq data (10X Genomics Chromium System).In conclusion, SCExecute facilitates custom cell-level analyses on barcoded scRNA-seq data using currently available tools and provides an effective solution for studying low (cellular) frequency transcriptome features. AVAILABILITY AND IMPLEMENTATION: SCExecute is implemented in Python3 using the Pysam package and distributed for Linux, MacOS and Python environments from https://horvathlab.github.io/NGS/SCExecute. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Extracellular vesicles carrying HIV-1 Nef induce long-term hyperreactivity of myeloid cells.

A possible explanation for chronic inflammation in HIV-infected individuals treated with anti-retroviral therapy is hyperreactivity of myeloid cells due to a phenomenon called "trained immunity." Here, we demonstrate that human monocyte-derived macrophages originating from monocytes initially treated with extracellular vesicles containing HIV-1 protein Nef (exNef), but differentiating in the absence of exNef, release increased levels of pro-inflammatory cytokines after lipopolysaccharide stimulation. This effect is associated with chromatin changes at the genes involved in inflammation and cholesterol metabolism pathways and upregulation of the lipid rafts and is blocked by methyl-ß-cyclodextrin, statin, and an inhibitor of the lipid raft-associated receptor IGF1R. Bone-marrow-derived macrophages from exNef-injected mice, as well as from mice transplanted with bone marrow from exNef-injected animals, produce elevated levels of tumor necrosis factor α (TNF-α) upon stimulation. These phenomena are consistent with exNef-induced trained immunity that may contribute to persistent inflammation and associated co-morbidities in HIV-infected individuals with undetectable HIV load.

Sex-dependent transcription of cardiac electrophysiology and links to acetylation modifiers based on the GTEx database.

Development of safer drugs based on epigenetic modifiers, e.g., histone deacetylase inhibitors (HDACi), requires better understanding of their effects on cardiac electrophysiology. Using RNAseq data from the genotype-tissue-expression database (GTEx), we created models that link the abundance of acetylation enzymes (HDAC/SIRT/HATs), and the gene expression of ion channels (IC) via select cardiac transcription factors (TFs) in male and female adult human hearts (left ventricle, LV). Gene expression data (transcripts per million, TPM) from GTEx donors (21-70 y.o.) were filtered, normalized and transformed to Euclidian space to allow quantitative comparisons in 84 female and 158 male LVs. Sex-specific partial least-square (PLS) regression models, linking gene expression data for HDAC/SIRT/HATs to TFs and to ICs gene expression, revealed tight co-regulation of cardiac ion channels by HDAC/SIRT/HATs, with stronger clustering in the male LV. Co-regulation of genes encoding excitatory and inhibitory processes in cardiac tissue by the acetylation modifiers may help explain their predominantly net-neutral effects on cardiac electrophysiology. ATP1A1, encoding for the Na/K pump, represented an outlier-with orthogonal regulation by the acetylation modifiers to most of the ICs. The HDAC/SIRT/HAT effects were mediated by strong (+) TF regulators of ICs, e.g., MEF2A and TBX5, in both sexes. Furthermore, for male hearts, PLS models revealed a stronger (+/-) mediatory role on ICs for NKX25 and TGF1B/KLF4, respectively, while RUNX1 exhibited larger (-) TF effects on ICs in females. Male-trained PLS models of HDAC/SIRT/HAT effects on ICs underestimated the effects on some ICs in females. Insights from the GTEx dataset about the co-expression and transcriptional co-regulation of acetylation-modifying enzymes, transcription factors and key cardiac ion channels in a sex-specific manner can help inform safer drug design.

Selective disruption of trigeminal sensory neurogenesis and differentiation in a mouse model of 22q11.2 deletion syndrome.

22q11.2 Deletion Syndrome (22q11DS) is a neurodevelopmental disorder associated with cranial nerve anomalies and disordered oropharyngeal function, including pediatric dysphagia. Using the LgDel 22q11DS mouse model, we investigated whether sensory neuron differentiation in the trigeminal ganglion (CNgV), which is essential for normal orofacial function, is disrupted. We did not detect changes in cranial placode cell translocation or neural crest migration at early stages of LgDel CNgV development. However, as the ganglion coalesces, proportions of placode-derived LgDel CNgV cells increase relative to neural crest cells. In addition, local aggregation of placode-derived cells increases and aggregation of neural crest-derived cells decreases in LgDel CNgV. This change in cell-cell relationships was accompanied by altered proliferation of placode-derived cells at embryonic day (E)9.5, and premature neurogenesis from neural crest-derived precursors, reflected by an increased frequency of asymmetric neurogenic divisions for neural crest-derived precursors by E10.5. These early differences in LgDel CNgV genesis prefigure changes in sensory neuron differentiation and gene expression by postnatal day 8, when early signs of cranial nerve dysfunction associated with pediatric dysphagia are observed in LgDel mice. Apparently, 22q11 deletion destabilizes CNgV sensory neuron genesis and differentiation by increasing variability in cell-cell interaction, proliferation and sensory neuron differentiation. This early developmental divergence and its consequences may contribute to oropharyngeal dysfunction, including suckling, feeding and swallowing disruptions at birth, and additional orofacial sensory/motor deficits throughout life.

Expanding the prostate cancer cell line repertoire with ACRJ-PC28, an AR-negative neuroendocrine cell line derived from an African-Caribbean patient.

Prostate cell lines from diverse backgrounds are important to addressing disparities in prostate cancer (PCa) incidence and mortality rates among Black men. ACRJ-PC28 was developed from a transrectal needle biopsy and established via inactivation of the CDKN2A locus and simultaneous expression of human telomerase. Characterization assays included growth curve analysis, immunoblots, IHC, 3D cultures, immunofluorescence imaging, confocal microscopy, flow cytometry, WGS, and RNA-Seq. ACRJ-PC28 has been passaged more than 40 times in vitro over 10 months with a doubling time of 45 hours. STR profiling confirmed the novelty and human origin of the cell line. RNA-Seq confirmed the expression of prostate specific genes alpha-methylacyl-CoA racemase (AMACR) and NKX3.1 and Neuroendocrine specific markers synaptophysin (SYP) and enolase 2 (ENO2) and IHC confirmed the presence of AMACR. Immunoblots indicated the cell line is of basal-luminal type; expresses p53 and pRB and is AR negative. WGS confirmed the absence of exonic mutations and the presence of intronic variants that appear to not affect function of AR, p53, and pRB. RNA-Seq data revealed numerous TP53 and RB1 mRNA splice variants and the lack of AR mRNA expression. This is consistent with retention of p53 function in response to DNA damage and pRB function in response to contact inhibition. Soft agar anchorage-independent analysis indicated that the cells are transformed, confirmed by principal component analysis (PCA) where ACRJ-PC28 cells cluster alongside other PCa tumor tissues, yet was distinct. The novel methodology described should advance prostate cell line development, addressing the disparity in PCa among Black men.

Improved SNV Discovery in Barcode-Stratified scRNA-seq Alignments.

Currently, the detection of single nucleotide variants (SNVs) from 10 x Genomics single-cell RNA sequencing data (scRNA-seq) is typically performed on the pooled sequencing reads across all cells in a sample. Here, we assess the gaining of information regarding SNV assessments from individual cell scRNA-seq data, wherein the alignments are split by cellular barcode prior to the variant call. We also reanalyze publicly available data on the MCF7 cell line during anticancer treatment. We assessed SNV calls by three variant callers-GATK, Strelka2, and Mutect2, in combination with a method for the cell-level tabulation of the sequencing read counts bearing variant alleles-SCReadCounts (single-cell read counts). Our analysis shows that variant calls on individual cell alignments identify at least a two-fold higher number of SNVs as compared to the pooled scRNA-seq; these SNVs are enriched in novel variants and in stop-codon and missense substitutions. Our study indicates an immense potential of SNV calls from individual cell scRNA-seq data and emphasizes the need for cell-level variant detection approaches and tools, which can contribute to the understanding of the cellular heterogeneity and the relationships to phenotypes, and help elucidate somatic mutation evolution and functionality.

SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data.

BACKGROUND: Recent studies have demonstrated the utility of scRNA-seq SNVs to distinguish tumor from normal cells, characterize intra-tumoral heterogeneity, and define mutation-associated expression signatures. In addition to cancer studies, SNVs from single cells have been useful in studies of transcriptional burst kinetics, allelic expression, chromosome X inactivation, ploidy estimations, and haplotype inference. RESULTS: To aid these types of studies, we have developed a tool, SCReadCounts, for cell-level tabulation of the sequencing read counts bearing SNV reference and variant alleles from barcoded scRNA-seq alignments. Provided genomic loci and expected alleles, SCReadCounts generates cell-SNV matrices with the absolute variant- and reference-harboring read counts, as well as cell-SNV matrices of expressed Variant Allele Fraction (VAFRNA) suitable for a variety of downstream applications. We demonstrate three different SCReadCounts applications on 59,884 cells from seven neuroblastoma samples: (1) estimation of cell-level expression of known somatic mutations and RNA-editing sites, (2) estimation of cell- level allele expression of biallelic SNVs, and (3) a discovery mode assessment of the reference and each of the three alternative nucleotides at genomic positions of interest that does not require prior SNV information. For the later, we applied SCReadCounts on the coding regions of KRAS, where it identified known and novel somatic mutations in a low-to-moderate proportion of cells. The SCReadCounts read counts module is benchmarked against the analogous modules of GATK and Samtools. SCReadCounts is freely available ( https://github.com/HorvathLab/NGS ) as 64-bit self-contained binary distributions for Linux and MacOS, in addition to Python source. CONCLUSIONS: SCReadCounts supplies a fast and efficient solution for estimation of cell-level SNV expression from scRNA-seq data. SCReadCounts enables distinguishing cells with monoallelic reference expression from those with no gene expression and is applicable to assess SNVs present in only a small proportion of the cells, such as somatic mutations in cancer.

Differences in the Platelet mRNA Landscape Portend Racial Disparities in Platelet Function and Suggest Novel Therapeutic Targets.

The African American (AA) population displays a 1.6 to 3-fold higher incidence of thrombosis and stroke mortality compared with European Americans (EAs). Current antiplatelet therapies target the ADP-mediated signaling pathway, which displays significant pharmacogenetic variation for platelet reactivity. The focus of this study was to define underlying population differences in platelet function in an effort to identify novel molecular targets for future antiplatelet therapy. We performed deep coverage RNA-Seq to compare gene expression levels in platelets derived from a cohort of healthy volunteers defined by ancestry determination. We identified > 13,000 expressed platelet genes of which 480 were significantly differentially expressed genes (DEGs) between AAs and EAs. DEGs encoding proteins known or predicted to modulate platelet aggregation, morphology, or platelet count were upregulated in AA platelets. Numerous G-protein coupled receptors, ion channels, and pro-inflammatory cytokines not previously associated with platelet function were likewise differentially expressed. Many of the signaling proteins represent potential pharmacologic targets of intervention. Notably, we confirmed the differential expression of cytokines IL32 and PROK2 in an independent cohort by quantitative real-time polymerase chain reaction, and provide functional validation of the opposing actions of these two cytokines on collagen-induced AA platelet aggregation. Using Genotype-Tissue Expression whole blood data, we identified 516 expression quantitative trait locuses with Fst values > 0.25, suggesting that population-differentiated alleles may contribute to differences in gene expression. This study identifies gene expression differences at the population level that may affect platelet function and serve as potential biomarkers to identify cardiovascular disease risk. Additionally, our analysis uncovers candidate novel druggable targets for future antiplatelet therapies.

Genomics of Black American colon cancer disparities: An RNA sequencing (RNA-Seq) study from an academic, tertiary referral center.

BACKGROUND: Black Americans have a higher incidence and mortality rate from colorectal cancer compared to their non-Hispanic White American counterparts. Even when controlling for sociodemographic differences between these 2 populations, Black Americans remain disproportionately affected by colorectal cancer. The purpose of our study was to determine if differences in gene expression between Black American and non-Hispanic White American colon cancer specimens could help explain differences in the incidence and mortality rate between these 2 populations. METHODS: Black Americans and non-Hispanic White Americans undergoing colon resection for stages I, II, or III colon cancer at a single institution were identified. Black American and non-Hispanic White American patients were matched for age, sex, and colon cancer stage to minimize the risk of confounding variables. Tissue samples were obtained at the time of colon resection and were analyzed using RNA sequencing to determine if there were differences in the expression of genes and biologic processes between the 2 groups. RESULTS: A total of 17 colon cancer specimens were analyzed; 8 (47.1%) patients were Black Americans. A total of 456 genes were identified as being expressed differently (ie, up or downregulated) in Black American compared to non-Hispanic White American colon cancer specimens. Moreover, 500 different genetic pathways were noted to be significantly over-represented with differentially expressed genes in our comparison of Black American and non-Hispanic White American colon cancer specimens, the majority of which plays a role in inflammation and immune cell function. CONCLUSION: Significant differences in gene expression and genetic pathways exist between Black Americans and non-Hispanic White Americans. Additional and multi-institutional and registry-based studies are needed to validate our findings and to further elucidate the contribution that these differences have to the overall incidence and mortality rate from colon cancer in these 2 patient populations.

scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets.

BACKGROUND: Recently, pioneering expression quantitative trait loci (eQTL) studies on single cell RNA sequencing (scRNA-seq) data have revealed new and cell-specific regulatory single nucleotide variants (SNVs). Here, we present an alternative QTL-related approach applicable to transcribed SNV loci from scRNA-seq data: scReQTL. ScReQTL uses Variant Allele Fraction (VAFRNA) at expressed biallelic loci, and corelates it to gene expression from the corresponding cell. RESULTS: Our approach employs the advantage that, when estimated from multiple cells, VAFRNA can be used to assess effects of SNVs in a single sample or individual. In this setting scReQTL operates in the context of identical genotypes, where it is likely to capture RNA-mediated genetic interactions with cell-specific and transient effects. Applying scReQTL on scRNA-seq data generated on the 10 × Genomics Chromium platform using 26,640 mesenchymal cells derived from adipose tissue obtained from three healthy female donors, we identified 1272 unique scReQTLs. ScReQTLs common between individuals or cell types were consistent in terms of the directionality of the relationship and the effect size. Comparative assessment with eQTLs from bulk sequencing data showed that scReQTL analysis identifies a distinct set of SNV-gene correlations, that are substantially enriched in known gene-gene interactions and significant genome-wide association studies (GWAS) loci. CONCLUSION: ScReQTL is relevant to the rapidly growing source of scRNA-seq data and can be applied to outline SNVs potentially contributing to cell type-specific and/or dynamic genetic interactions from an individual scRNA-seq dataset. AVAILABILITY: https://github.com/HorvathLab/NGS/tree/master/scReQTL.

Evaluation of an angiotensin Type 1 receptor blocker on the reconsolidation of fear memory.

Inhibition of the angiotensin type 1 receptor (AT1R) has been shown to decrease fear responses in both humans and rodents. These effects are attributed to modulation of extinction learning, however the contribution of AT1R to alternative memory processes remains unclear. Using classic Pavlovian conditioning combined with radiotelemetry and whole-genome RNA sequencing, we evaluated the effects of the AT1R antagonist losartan on fear memory reconsolidation. Following the retrieval of conditioned auditory fear memory, animals were given a single intraperitoneal injection of losartan or saline. In response to the conditioned stimulus (CS), losartan-treated animals exhibited significantly less freezing at 24 h and 1 week; an effect that was dependent upon memory reactivation and independent of conditioned cardiovascular reactivity. Using an unbiased whole-genome RNA sequencing approach, transcriptomic analysis of the basolateral amygdala (BLA) identified losartan-dependent differences in gene expression during the reconsolidation phase. These findings demonstrate that post-retrieval losartan modifies behavioral and transcriptomic markers of conditioned fear memory, supporting an important regulatory role for this receptor in reconsolidation and as a potential pharmacotherapeutic target for maladaptive fear disorders such as PTSD.

GeTallele: A Method for Analysis of DNA and RNA Allele Frequency Distributions.

Variant allele frequencies (VAF) are an important measure of genetic variation that can be estimated at single-nucleotide variant (SNV) sites. RNA and DNA VAFs are used as indicators of a wide-range of biological traits, including tumor purity and ploidy changes, allele-specific expression and gene-dosage transcriptional response. Here we present a novel methodology to assess gene and chromosomal allele asymmetries and to aid in identifying genomic alterations in RNA and DNA datasets. Our approach is based on analysis of the VAF distributions in chromosomal segments (continuous multi-SNV genomic regions). In each segment we estimate variant probability, a parameter of a random process that can generate synthetic VAF samples that closely resemble the observed data. We show that variant probability is a biologically interpretable quantitative descriptor of the VAF distribution in chromosomal segments which is consistent with other approaches. To this end, we apply the proposed methodology on data from 72 samples obtained from patients with breast invasive carcinoma (BRCA) from The Cancer Genome Atlas (TCGA). We compare DNA and RNA VAF distributions from matched RNA and whole exome sequencing (WES) datasets and find that both genomic signals give very similar segmentation and estimated variant probability profiles. We also find a correlation between variant probability with copy number alterations (CNA). Finally, to demonstrate a practical application of variant probabilities, we use them to estimate tumor purity. Tumor purity estimates based on variant probabilities demonstrate good concordance with other approaches (Pearson's correlation between 0.44 and 0.76). Our evaluation suggests that variant probabilities can serve as a dependable descriptor of VAF distribution, further enabling the statistical comparison of matched DNA and RNA datasets. Finally, they provide conceptual and mechanistic insights into relations between structure of VAF distributions and genetic events. The methodology is implemented in a Matlab toolbox that provides a suite of functions for analysis, statistical assessment and visualization of Genome and Transcriptome allele frequencies distributions. GeTallele is available at: https://github.com/SlowinskiPiotr/GeTallele.

Estimating the Allele-Specific Expression of SNVs From 10× Genomics Single-Cell RNA-Sequencing Data.

With the recent advances in single-cell RNA-sequencing (scRNA-seq) technologies, the estimation of allele expression from single cells is becoming increasingly reliable. Allele expression is both quantitative and dynamic and is an essential component of the genomic interactome. Here, we systematically estimate the allele expression from heterozygous single nucleotide variant (SNV) loci using scRNA-seq data generated on the 10×Genomics Chromium platform. We analyzed 26,640 human adipose-derived mesenchymal stem cells (from three healthy donors), sequenced to an average of 150K sequencing reads per cell (more than 4 billion scRNA-seq reads in total). High-quality SNV calls assessed in our study contained approximately 15% exonic and >50% intronic loci. To analyze the allele expression, we estimated the expressed variant allele fraction (VAFRNA) from SNV-aware alignments and analyzed its variance and distribution (mono- and bi-allelic) at different minimum sequencing read thresholds. Our analysis shows that when assessing positions covered by a minimum of three unique sequencing reads, over 50% of the heterozygous SNVs show bi-allelic expression, while at a threshold of 10 reads, nearly 90% of the SNVs are bi-allelic. In addition, our analysis demonstrates the feasibility of scVAFRNA estimation from current scRNA-seq datasets and shows that the 3'-based library generation protocol of 10×Genomics scRNA-seq data can be informative in SNV-based studies, including analyses of transcriptional kinetics.

Dysregulated metabolic pathways in age-related macular degeneration.

Age-related macular degeneration is a major cause of vision impairment in the Western world among people of 55 years and older. Recently we have shown that autophagy is dysfunctional in the retinal pigment epithelium (RPE) of the AMD donor eyes (AMD RPE). We also showed increased reactive oxygen (ROS) production, increased cytoplasmic glycogen accumulation, mitochondrial dysfunction and disintegration, and enlarged and annular LAMP-1-positive organelles in AMD RPE. However, the underlying mechanisms inducing these abnormalities remain to be elucidated. Here, by performing a comprehensive study, we show increased PAPR2 expression, deceased NAD+, and SIRT1, increased PGC-1α acetylation (inactive form), lower AMPK activity, and overactive mTOR pathway in AMD RPE as compared to normal RPE. Metabolomics and lipidomics revealed dysregulated metabolites in AMD RPE as compared to normal RPE, including glycerophospholipid metabolism, involved in autophagy, lipid, and protein metabolisms, glutathione, guanosine, and L-glutamic acid, which are implicated in protection against oxidative stress and neurotoxicity, further supporting our observations. Our data show dysregulated metabolic pathways as important contributors to AMD pathophysiology, and facilitate the development of new treatment strategies for this debilitating disease of the visual system.