Genome-wide quantification of the effects of DNA methylation on human gene regulation, bioRxiv, 2017-06-08
AbstractChanges in DNA methylation are important in development and disease, but not all regulatory elements act in a methylation-dependent (MD) manner. Here, we developed mSTARR-seq, a high-throughput approach to quantify the effects of DNA methylation on regulatory element function. We assay MD activity in 14% of the euchromatic human genome, identify 2,143 MD regulatory elements, and predict MD activity using sequence and chromatin state information. We identify transcription factors associated with higher activity in unmethylated or methylated states, including an association between pioneer transcription factors and methylated DNA. Finally, we use mSTARR-seq to predict DNA methylation-gene expression correlations in primary cells. Our findings provide a map of MD regulatory activity across the human genome, facilitating interpretation of the many emerging associations between methylation and trait variation.
biorxiv genomics 0-100-users 2017Genetic identification Of brain cell types underlying schizophrenia, bioRxiv, 2017-06-03
AbstractWith few exceptions, the marked advances in knowledge about the genetic basis for schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. Applying knowledge of the cellular taxonomy of the brain from single-cell RNA-sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. The common variant genomic results consistently mapped to pyramidal cells, medium spiny neurons, and certain interneurons but far less consistently to embryonic, progenitor, or glial cells. These enrichments were due to distinct sets of genes specifically expressed in each of these cell types. Many of the diverse gene sets associated with schizophrenia (including antipsychotic targets) implicate the same brain cell types. Our results provide a parsimonious explanation the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. While some of the genetic risk is associated with GABAergic interneurons, this risk largely does not overlap with that from projecting cells.
biorxiv genomics 0-100-users 2017Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low cost microfluidic instrumentation, bioRxiv, 2017-05-23
AbstractDroplet-based single cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While these approaches offer the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective, reliable, and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we have developed a microfluidic control instrument that can be easily assembled from 3D printed parts and commercially available components costing approximately $540. We adapted this instrument for massively parallel scRNA-seq and deployed it in a clinical environment to perform single cell transcriptome profiling of disaggregated synovial tissue from a rheumatoid arthritis patient. We sequenced 8,716 single cells from a synovectomy, revealing 16 transcriptomically distinct clusters. These encompass a comprehensive and unbiased characterization of the autoimmune infiltrate, including inflammatory T and NK subsets that contribute to disease biology. Additionally, we identified fibroblast subpopulations that are demarcated via THY1 (CD90) and CD55 expression. Further experiments confirm that these represent synovial fibroblasts residing within the synovial intimal lining and subintimal lining, respectively, each under the influence of differing microenvironments. We envision that this instrument will have broad utility in basic and clinical settings, enabling low-cost and routine application of microfluidic techniques, and in particular single-cell transcriptome profiling.
biorxiv genomics 100-200-users 2017A comparison between single cell RNA sequencing and single molecule RNA FISH for rare cell analysis, bioRxiv, 2017-05-19
AbstractThe development of single cell RNA sequencing technologies has emerged as a powerful means of profiling the transcriptional behavior of single cells, leveraging the breadth of sequencing measurements to make inferences about cell type. However, there is still little understanding of how well these methods perform at measuring single cell variability for small sets of genes and what “transcriptome coverage” (e.g. genes detected per cell) is needed for accurate measurements. Here, we use single molecule RNA FISH measurements of 26 genes in thousands of melanoma cells to provide an independent reference dataset to assess the performance of the DropSeq and Fluidigm single cell RNA sequencing platforms. We quantified the Gini coefficient, a measure of rare-cell expression variability, and find that the correspondence between RNA FISH and single cell RNA sequencing for Gini, unlike for mean, increases markedly with per-cell library complexity up to a threshold of ∼2000 genes detected. A similar complexity threshold also allows for robust assignment of multi-genic cell states such as cell cycle phase. Our results provide guidelines for selecting sequencing depth and complexity thresholds for single cell RNA sequencing. More generally, our results suggest that if the number of genes whose expression levels are required to answer any given biological question is small, then greater transcriptome complexity per cell is likely more important than obtaining very large numbers of cells.
biorxiv genomics 0-100-users 2017Cohesin loss eliminates all loop domains, leading to links among superenhancers and downregulation of nearby genes, bioRxiv, 2017-05-19
SUMMARYThe human genome folds to create thousands of intervals, called “contact domains,” that exhibit enhanced contact frequency within themselves. “Loop domains” form because of tethering between two loci - almost always bound by CTCF and cohesin – lying on the same chromosome. “Compartment domains” form when genomic intervals with similar histone marks co-segregate. Here, we explore the effects of degrading cohesin. All loop domains are eliminated, but neither compartment domains nor histone marks are affected. Loci in different compartments that had been in the same loop domain become more segregated. Loss of loop domains does not lead to widespread ectopic gene activation, but does affect a significant minority of active genes. In particular, cohesin loss causes superenhancers to co-localize, forming hundreds of links within and across chromosomes, and affecting the regulation of nearby genes. Cohesin restoration quickly reverses these effects, consistent with a model where loop extrusion is rapid.
biorxiv genomics 0-100-users 2017scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells, bioRxiv, 2017-05-18
AbstractParallel single-cell sequencing protocols represent powerful methods for investigating regulatory relationships, including epigenome-transcriptome interactions. Here, we report a novel single-cell method for parallel chromatin accessibility, DNA methylation and transcriptome profiling. scNMT-seq (single-cell nucleosome, methylation and transcription sequencing) uses a GpC methyltransferase to label open chromatin followed by bisulfite and RNA sequencing. We validate scNMT-seq by applying it to differentiating mouse embryonic stem cells, finding links between all three molecular layers and revealing dynamic coupling between epigenomic layers during differentiation.
biorxiv genomics 100-200-users 2017