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Single-neuron transcriptome and methylome sequencing for epigenomic analysis of aging.

ABSTRACT: Enormous heterogeneity in transcription and signaling is the feature that slows down progress in our understanding of the mechanisms of normal aging and age-related diseases. This is critical for neurobiology of aging where the enormous diversity of neuronal populations presents a significant challenge in experimental design. Here, we introduce Aplysia as a model for genomic analysis of aging at the single-cell level and provide protocols for integrated transcriptome and methylome profiling of individually identified neurons during the aging process. These single-cell RNA-seq and DNA methylation assays (methyl-capture/methyl enrichment) are compatible with all major next generation sequencing platforms (we used Roche/454 and SOLiD/Life Technologies as illustrative examples) and can be used to integrate an epigenetic signature with transcriptional output. The described sequencing library construction protocol provides both quantitative and directional information from transcriptional profiling of individual cells. Our results also confirm that different copies of DNA in polyploid Aplysia neurons behave similarly with respect to their DNA methylation.

SUBMITTER: Moroz LL

PROVIDER: S-EPMC4045448 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Single-neuron transcriptome and methylome sequencing for epigenomic analysis of aging.

Moroz Leonid L LL Kohn Andrea B AB

Methods in molecular biology (Clifton, N.J.) 20130101

Enormous heterogeneity in transcription and signaling is the feature that slows down progress in our understanding of the mechanisms of normal aging and age-related diseases. This is critical for neurobiology of aging where the enormous diversity of neuronal populations presents a significant challenge in experimental design. Here, we introduce Aplysia as a model for genomic analysis of aging at the single-cell level and provide protocols for integrated transcriptome and methylome profiling of i ...[more]

PMID: 23929113

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Project description:N6-methyladenosine (m6A) is the most abundant internal modification on eukaryotic mRNAs. There is increasing evidence that m6A plays a key role in tumor progression, so it is important to analyze m6A modifications within the transcriptome-wide in lung adenocarcinoma (LUAD). Three pairs of LUAD samples and tumor-adjacent normal tissues were obtained from the South University of Science and Technology Hospital. And then methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RNA sequencing (RNA-seq) were used to identify differential m6A modifications between tumor and tumor-adjacent normal tissues. We identified 4041 aberrant m6A peaks, of which 1192 m6A peaks were upregulated and 2849 m6A peaks downregulated. It was found that genes with the dysregulated m6A peaks were enriched in the pathways in cancer, Rap1 signaling pathway, and insulin resistance. Additionally, 612 genes with abnormal regulation of m6A peaks and RNA expression were identified by combining MeRIP-seq and RNA-seq data. Through KEGG analysis, the 612 genes were enriched in cancer-related signaling pathways, such as the cGMP-PKG signaling pathway, and the Rap1 signaling pathway. What's more, GSEA enrichment analysis showed these genes were enriched in cell cycle phase transition, cell division, cellular response to DNA damage stimulus, and chromosome organization. To further explore the relationship between differential m6A modified genes and clinical parameters of LUAD patients, we searched The Cancer Genome Atlas (TCGA) and identified 2 genes (FCRL5 and GPRIN1) that were associated with the prognosis and diagnosis of LUAD patients. Furthermore, we found a positive correlation between GPRIN1 and m6A reader YTHDF1 in the GEPIA2 database. It was verified that YTHDF1 binds to GPRIN1 mRNA and regulates its expression. Our study results suggest that m6A modification plays important role in the progression and prognosis of LUAD and maybe a potential new therapeutic target for LUAD patients in the future.

Dataset Information

Single-neuron transcriptome and methylome sequencing for epigenomic analysis of aging.

Publications

Single-neuron transcriptome and methylome sequencing for epigenomic analysis of aging.

Similar Datasets

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