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Single-cell CAS-seq reveals a class of short PIWI-interacting RNAs in human oocytes

GSE95218 Macaca fascicularis; Mus musculus; Homo sapiens Single-cell RNA-seq 111 samples Submitted 2019/06/13 Platform GPL18573Platform GPL20302Platform GPL17021Platform GPL16791Platform GPL20795Platform GPL21273Platform GPL23096
At a glance

Single-cell RNA-seq · Macaca fascicularis; Mus musculus; Homo sapiens · 111 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Macaca fascicularis; Mus musculus; Homo sapiens
Samples
111 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)
Small RNAs have important functions. However, small RNAs in primate oocytes remain unexplored. Herein, we develop CAS-seq, a single-cell small RNA sequencing method, and profiled the small RNAs in human oocytes and embryos. We discover a class of ~20-nt small RNAs that are predominantly expressed in human and monkey oocytes, but not in mouse oocytes.
Read the full summary ↓
They are specifically associated with HIWI3 (PIWIL3), whereas significantly shorter than the commonly known PIWI-interacting RNAs (piRNAs), designated as oocyte short piRNAs (os-piRNAs). Notably, the os-piRNAs in human oocytes lack 2’-O-methylation at the 3’ end, a hallmark of the classic piRNAs. In addition, the os-piRNAs have a strong 1U/10A bias and are enriched on the antisense strands of recently evolved transposable elements (TEs), indicating the potential function of silencing TEs by cleavage. Therefore, our study has identified an oocyte-specific piRNA family with distinct features and provides valuable resources for studying small RNAs in primate oocytes.
This dataset
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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 GSE95218_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 PRJNA376426 and SRA study SRP100557. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 31358756) ↗
Samples in this study

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