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Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (Single-cell or single-nuclei RNA sequencing)

ABSTRACT: Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (Single-cell or single-nuclei RNA sequencing)

PROVIDER: PRJNA454442 | ENA |

REPOSITORIES: ENA

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Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (Single-cell or single-nuclei RNA sequencing)

Project description:In females with X-linked genetic disorders, wild-type and mutant cells coexist within brain tissue because of random X-chromosome inactivation. This cellular mosaicism leads to phenotypic variability and poses significant challenges for interpreting the effects of X-linked mutant alleles on gene expression. We present a single-nucleus RNA sequencing approach that resolves mosaicism by using single nucleotide polymorphisms in genes that are expressed in cis with the X-linked mutation to determine whether individual nuclei express the wild-type or mutant allele even when the mutant gene is not directly detected. This approach enables genome-wide comparisons of gene expression between mutant and wild-type cells within the same individual and eliminates the variability introduced by comparisons to controls with different genetic backgrounds. We apply this approach to mosaic female mouse models and humans with Rett syndrome, an X-linked neurodevelopmental disorder caused by mutations in the methyl-DNA-binding protein MECP2, and reveal that cell-type-specific DNA methylation patterns largely predict the degree of gene upregulation by MECP2 in specific neuronal subtypes. The approach described here can be broadly applied to the characterization of gene expression in additional mosaic X-linked conditions.

2018-11-15 | GSE113901 | GEO

Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (Total RNA sequencing)

2018-11-15 | GSE113902 | GEO

Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (MeCP2 ChIP-seq)

2018-11-15 | GSE113903 | GEO

Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing

Project description:Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing

| PRJNA454441 | ENA

Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (Total RNA sequencing)

Project description:Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (Total RNA sequencing)

| PRJNA454443 | ENA

Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (MeCP2 ChIP-seq)

Project description:Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing (MeCP2 ChIP-seq)

| PRJNA454444 | ENA

Single nuclei RNA-sequencing of adult human hearts

Project description:Single nuclei RNA-sequencing of adult human hearts

| PRJNA675768 | ENA

Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing.

Project description:In females with X-linked genetic disorders, wild-type and mutant cells coexist within brain tissue because of X-chromosome inactivation, posing challenges for interpreting the effects of X-linked mutant alleles on gene expression. We present a single-nucleus RNA sequencing approach that resolves mosaicism by using single-nucleotide polymorphisms in genes expressed in cis with the X-linked mutation to determine which nuclei express the mutant allele even when the mutant gene is not detected. This approach enables gene expression comparisons between mutant and wild-type cells within the same individual, eliminating variability introduced by comparisons to controls with different genetic backgrounds. We apply this approach to mosaic female mouse models and humans with Rett syndrome, an X-linked neurodevelopmental disorder caused by mutations in the gene encoding the methyl-DNA-binding protein MECP2, and observe that cell-type-specific DNA methylation predicts the degree of gene upregulation in MECP2-mutant neurons. This approach can be broadly applied to study gene expression in mosaic X-linked disorders.

| S-EPMC6261686 | biostudies-literature

Disentangling glial diversity in peripheral nerves at single-nuclei resolution [single-cell and single-nuclei RNA-seq]

Project description:Disentangling glial diversity in peripheral nerves at single-nuclei resolution [single-cell and single-nuclei RNA-seq]

| PRJNA754445 | ENA

RNA-sequencing from single nuclei.

Project description:It has recently been established that synthesis of double-stranded cDNA can be done from a single cell for use in DNA sequencing. Global gene expression can be quantified from the number of reads mapping to each gene, and mutations and mRNA splicing variants determined from the sequence reads. Here we demonstrate that this method of transcriptomic analysis can be done using the extremely low levels of mRNA in a single nucleus, isolated from a mouse neural progenitor cell line and from dissected hippocampal tissue. This method is characterized by excellent coverage and technical reproducibility. On average, more than 16,000 of the 24,057 mouse protein-coding genes were detected from single nuclei, and the amount of gene-expression variation was similar when measured between single nuclei and single cells. Several major advantages of the method exist: first, nuclei, compared with whole cells, have the advantage of being easily isolated from complex tissues and organs, such as those in the CNS. Second, the method can be widely applied to eukaryotic species, including those of different kingdoms. The method also provides insight into regulatory mechanisms specific to the nucleus. Finally, the method enables dissection of regulatory events at the single-cell level; pooling of 10 nuclei or 10 cells obscures some of the variability measured in transcript levels, implying that single nuclei and cells will be extremely useful in revealing the physiological state and interconnectedness of gene regulation in a manner that avoids the masking inherent to conventional transcriptomics using bulk cells or tissues.

| S-EPMC3856806 | biostudies-literature

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