GEO series

Localization and Abundance Analysis of Human lncRNAs at Single Cell and Single Molecule Resolution

GSE57049 Homo sapiens (human) Single-cell RNA-seq 7 samples Submitted 2015/01/07 Platform GPL9115Platform GPL11154

At a glance

Single-cell RNA-seq · human · 7 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 7 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.

Summary (written by the submitters)

Long noncoding RNAs (lncRNAs) have emerged as key players in different cellular processes and are required for diverse functions in vivo. However, fundamental aspects of lncRNA biology remain poorly characterized, including their subcellular localization, abundance and variation at a single cell resolution.

Read the full summary ↓

Here, we used single molecule, single-cell RNA fluorescence in situ hybridization (RNA FISH) to survey 61 lncRNAs, chosen by properties such as conservation, tissue specific expression, and expression abundance, and to catalog their abundance and cellular localization patterns in three human cell types. Our lncRNAs displayed diverse sub-cellular localization patterns ranging from strictly nuclear localization to almost exclusive cytoplasmic localization, with the majority localized primarily in the nucleus. The low abundance of these lncRNAs as measured in bulk cell populations cannot be explained by high expression in a small subset of 'jackpot' cells. Simultaneous analysis of lncRNAs and mRNAs from corresponding divergently transcribed loci showed that divergent lncRNAs do not present a distinct localization pattern and are not always co-regulated with their neighbor. Overall, our study highlights important differences and similarities between lncRNAs and mRNAs. The rich set of localization patterns we observe are consistent with a broad range of potential functions for lncRNA, and assists in hypothesis generation for mechanistic studies. Here we provide the RNA-Seq expression matrix, as well as RNA-Seq raw data, which we used for comparison with RNA FISH molecule counts.

This dataset

Open GSE57049 in finder → Find more human RNA-seq datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE57049_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA245725 and SRA study SRP041508. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25630241) ↗

Samples in this study

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+ 7 more — browse all 7 samples with per-sample file links →

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