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Multi-omic profiling of single nuclei uncovers regulatory diversity of brain cell types and diseases

ABSTRACT: Multi-omic profiling of single nuclei uncovers regulatory diversity of brain cell types and diseases

PROVIDER: PRJNA589980 | ENA |

REPOSITORIES: ENA

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Multi-omic profiling of single nuclei uncovers regulatory diversity of brain cell types and diseases

Project description:Most existing single-cell techniques can only make one type of molecular measurements. Although computational approaches have been developed to integrate single-cell datasets, their efficacy still needs to be determined with reference to authentic single-cell multi-omic profiles. To address this challenge, we devised single-nucleus methylCytosine, Chromatin accessibility and Transcriptome sequencing (snmC2T-seq) and applied the approach to post-mortem human frontal cortex tissue. We developed a computational framework to evaluate the quality of finely defined cell types using multi-modal information and validated the efficacy of computational multi-omic integration methods. Correlation analysis in individual cells revealed gene groups showing distinct relations between methylation and expression. Integration of snmC2T-seq with other multi- and single- modal datasets enabled joint analyses of the methylome, chromatin accessibility, transcriptome, and chromatin architecture for 63 human cortical cell types. We reconstructed the regulatory lineage of these cortical cell types and found pronounced cell-type-specific enrichment of disease risks for neuropsychiatric traits, predicting causal cell types that can be targeted for treatment.

2019-12-12 | GSE140493 | GEO

Single-nuclei RNA sequencing (snRNA-seq) uncovers trophoblast cell types and lineages in the mature bovine placenta

Project description:Single-nuclei RNA sequencing (snRNA-seq) uncovers trophoblast cell types and lineages in the mature bovine placenta

| PRJNA885156 | ENA

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits [snRNA-seq]

Project description:Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (~3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.

2021-06-23 | GSE178734 | GEO

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits [snATAC-seq]

2021-06-23 | GSE178733 | GEO

Single-nuclei RNA sequencing (snRNA-seq) uncovers trophoblast cell types and lineages in the mature bovine placenta

Project description:Ruminants have a semi-invasive placenta, which possess highly vascularized placentomes formed by maternal endometrial caruncles and fetal placental cotyledons and required for fetal development to term. The synepitheliochorial placenta of cattle contains at least two trophoblast cell populations, including uninucleate (UNC) and binucleate (BNC) cells that are most abundant in the cotyledonary chorion of the placentomes. The interplacentomal placenta is more epitheliochorial in nature with the chorion developing specialized areolae over the openings of uterine glands. Of note, the cell types in the placenta and cellular and molecular mechanisms governing trophoblast differentiation and function are little understood in ruminants. To fill this knowledge gap, the cotyledonary and intercotyledonary areas of the mature day 195 bovine placenta were analyzed by single nuclei analysis. Single-nuclei RNA-seq analysis found substantial differences in cell type composition and transcriptional profiles between the two distinct regions of the placenta. Based on clustering and cell marker gene expression, five different trophoblast cell types were identified in the chorion, including proliferating and differentiating UNC and two different types of BNC in the cotyledon. Cell trajectory analyses provided a framework for understanding the differentiation of trophoblast UNC into BNC. The upstream transcription factor binding analysis of differentially expressed genes identified a candidate set of regulator factors and genes regulating trophoblast differentiation. This foundational information is useful to discover essential biological pathways underpinning the development and function of the bovine placenta.

2022-10-05 | GSE214407 | GEO

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits

Project description:Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits

| PRJNA740255 | ENA

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits [snRNA-seq]

Project description:Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits [snRNA-seq]

| PRJNA740261 | ENA

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits [snATAC-seq]

Project description:Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits [snATAC-seq]

| PRJNA740260 | ENA

Trans-omic Profiling Uncovers Molecular Controls of the Early Human Cerebral Organoid Formation

Project description:Trans-omic Profiling Uncovers Molecular Controls of the Early Human Cerebral Organoid Formation

| PRJNA1046407 | ENA

A multi-omics approach to liver diseases: integration of Single Nuclei Transcriptomics with Proteomics and Hi-Cap Bulk Data in human liver

Project description:Abstract The liver is the largest solid organ and a primary metabolic hub. In recent years, intact cell nuclei were used to perform single-nuclei RNA-seq (snRNA-seq) for tissues difficult to dissociate and for flash-frozen archived tissue samples to discover unknown and rare cell sub-populations. In this study, we performed snRNA-seq of a liver sample to identify sub-populations of cells based on nuclear transcriptomics. In 4,282 single nuclei we detected on average 1,377 active genes and we identified seven major cell types. We integrated data from 94,286 distal interactions (p<0.05) for 7,682 promoters from a targeted chromosome conformation capture technique (HiCap) and mass spectrometry (MS) proteomics for the same liver sample. We observed a reasonable correlation between proteomics and in silico bulk snRNA-seq (r=0.47) using tissue-independent gene-specific protein abundancy estimation factors. We specifically looked at genes of medical importance. The DPYD gene is involved in the pharmacogenetics of fluoropyrimidines toxicity and some of its variants are analyzed for clinical purposes. We identified a new putative polymorphic regulatory element, which may contribute to variation in toxicity. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and we investigated all known risk genes. We identified a complex regulatory landscape for the SLC2A2 gene with 16 candidate enhancers. Three of them harbor somatic motif breaking and other mutations in HCC in the Pan Cancer Analysis of Whole Genomes dataset and are candidates to contribute to malignancy. Our results highlight the potential of a multi-omics approach in the study of human diseases.

2020-12-21 | PXD017610 | Pride

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