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.

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.

ReQTL: identifying correlations between expressed SNVs and gene expression using RNA-sequencing data.

MOTIVATION: By testing for associations between DNA genotypes and gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation at expressed SNV loci can be estimated using the proportion of alleles bearing the variant nucleotide (variant allele fraction, VAFRNA). VAFRNA is a continuous measure which allows for precise allele quantitation in loci where the RNA alleles do not scale with the genotype count. We describe a method to correlate VAFRNA with gene expression and assess its ability to identify genetically regulated expression solely from RNA-sequencing (RNA-seq) datasets. RESULTS: We introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele fraction at expressed SNV loci in the transcriptome (VAFRNA). We exemplify the method on sets of RNA-seq data from human tissues obtained though the Genotype-Tissue Expression (GTEx) project and demonstrate that ReQTL analyses are computationally feasible and can identify a subset of expressed eQTL loci. AVAILABILITY AND IMPLEMENTATION: A toolkit to perform ReQTL analyses is available at https://github.com/HorvathLab/ReQTL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bacteriocin production augments niche competition by enterococci in the mammalian gastrointestinal tract.

Enterococcus faecalis is both a common commensal of the human gastrointestinal tract and a leading cause of hospital-acquired infections. Systemic infections with multidrug-resistant enterococci occur subsequent to gastrointestinal colonization. Preventing colonization by multidrug-resistant E. faecalis could therefore be a valuable approach towards limiting infection. However, little is known about the mechanisms E. faecalis uses to colonize and compete for stable gastrointestinal niches. Pheromone-responsive conjugative plasmids encoding bacteriocins are common among enterococcal strains and could modulate niche competition among enterococci or between enterococci and the intestinal microbiota. We developed a model of colonization of the mouse gut with E. faecalis, without disrupting the microbiota, to evaluate the role of the conjugative plasmid pPD1 expressing bacteriocin 21 (ref. 4) in enterococcal colonization. Here we show that E. faecalis harbouring pPD1 replaces indigenous enterococci and outcompetes E. faecalis lacking pPD1. Furthermore, in the intestine, pPD1 is transferred to other E. faecalis strains by conjugation, enhancing their survival. Colonization with an E. faecalis strain carrying a conjugation-defective pPD1 mutant subsequently resulted in clearance of vancomycin-resistant enterococci, without plasmid transfer. Therefore, bacteriocin expression by commensal bacteria can influence niche competition in the gastrointestinal tract, and bacteriocins, delivered by commensals that occupy a precise intestinal bacterial niche, may be an effective therapeutic approach to specifically eliminate intestinal colonization by multidrug-resistant bacteria, without profound disruption of the indigenous microbiota.

Inflammation, Aging and Hematopoiesis: A Complex Relationship.

All vertebrate blood cells descend from multipotent hematopoietic stem cells (HSCs), whose activity and differentiation depend on a complex and incompletely understood relationship with inflammatory signals. Although homeostatic levels of inflammatory signaling play an intricate role in HSC maintenance, activation, proliferation, and differentiation, acute or chronic exposure to inflammation can have deleterious effects on HSC function and self-renewal capacity, and bias their differentiation program. Increased levels of inflammatory signaling are observed during aging, affecting HSCs either directly or indirectly via the bone marrow niche and contributing to their loss of self-renewal capacity, diminished overall functionality, and myeloid differentiation skewing. These changes can have significant pathological consequences. Here, we provide an overview of the current literature on the complex interplay between HSCs and inflammatory signaling, and how this relationship contributes to age-related phenotypes. Understanding the mechanisms and outcomes of this interaction during different life stages will have significant implications in the modulation and restoration of the hematopoietic system in human disease, recovery from cancer and chemotherapeutic treatments, stem cell transplantation, and aging.

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.

Paneth cell defects in Crohn's disease patients promote dysbiosis.

BACKGROUND: Paneth cell dysfunction has been implicated in a subset of Crohn's disease (CD) patients. We previously stratified clinical outcomes of CD patients by using Paneth cell phenotypes, which we defined by the intracellular distribution of antimicrobial proteins. Animal studies suggest that Paneth cells shape the intestinal microbiome. However, it is unclear whether Paneth cell phenotypes alter the microbiome complexity in CD subjects. Therefore, we analyzed the correlation of Paneth cell phenotypes with mucosal microbiome composition and ileal RNA expression in pediatric CD and noninflammatory bowel disease (non-IBD) patients. METHODS: Pediatric CD (n = 44) and non-IBD (n = 62) patients aged 4 to 18 were recruited prior to routine endoscopic biopsy. Ileal mucosal samples were analyzed for Paneth cell phenotypes, mucosal microbiome composition, and RNA transcriptome. RESULTS: The prevalence of abnormal Paneth cells was higher in pediatric versus adult CD cohorts. For pediatric CD patients, those with abnormal Paneth cells showed significant changes in their ileal mucosal microbiome, highlighted by reduced protective microbes and enriched proinflammatory microbes. Ileal transcriptome profiles showed reduced transcripts for genes that control oxidative phosphorylation in CD patients with abnormal Paneth cells. These transcriptional changes in turn were correlated with specific microbiome alterations. In non-IBD patients, a subset contained abnormal Paneth cells. However, this subset was not associated with alterations in the microbiome or host transcriptome. CONCLUSION: Paneth cell abnormalities in human subjects are associated with mucosal dysbiosis in the context of CD, and these changes are associated with alterations in oxidative phosphorylation, potentially in a feedback loop. FUNDING: The research was funded by Helmsley Charitable Trust (to T.S. Stappenbeck, R.J. Xavier, and D.P.B. McGovern), Crohn's and Colitis Foundation of America (to N.H. Salzman, T.S. Stappenbeck, R.J. Xavier, and C. Huttenhower), and Doris Duke Charitable Foundation grant 2014103 (to T.C. Liu).