Single-Cell Clustering

Introduction

This dataset contains Single-cell RNA sequencing data coming from FACS sorted cells, sequenced using the SMART-seq2 protocol for the library construction. These cells come from fluorescent transgenic zebrafish lines that label distinct blood cell types. The aim is to study the hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution.

Dataset description

Single-cell RNA sequencing of zebrafish kidney marrow. Single cells were obtained from fluorescent transgenic zebrafish lines that label distinct blood cell types. Target cells were FACS sorted previous to sequencing them.

  • Organism: Danio rerio

  • Instrument: Illumina NextSeq 500

  • Library construction: SMART-seq2

  • Layout: Paired-end. 38 pb / read.

  • Number of cells: 246

Publication

Tang, Q., Iyer, S., Lobbardi, R., Moore, J., Chen, H., & Lareau, C. et al. (2017). Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing. Journal Of Experimental Medicine214(10), 2875-2887. https://doi.org/10.1084/jem.20170976

 Abstract

Recent advances in single-cell, transcriptomic profiling have provided unprecedented access to investigate cell heterogeneity during tissue and organ development. In this study, we used massively parallel, single-cell RNA sequencing to define cell heterogeneity within the zebrafish kidney marrow, constructing a comprehensive molecular atlas of definitive hematopoiesis and functionally distinct renal cells found in adult zebrafish. Because our method analyzed blood and kidney cells in an unbiased manner, our approach was useful in characterizing immune-cell deficiencies within DNA–protein kinase catalytic subunit (prkdc), interleukin-2 receptor γ a (il2rga), and double-homozygous–mutant fish, identifying blood cell losses in T, B, and natural killer cells within specific genetic mutants. Our analysis also uncovered novel cell types, including two classes of natural killer immune cells, classically defined and erythroid-primed hematopoietic stem and progenitor cells, mucin-secreting kidney cells, and kidney stem/progenitor cells. In total, our work provides the first, comprehensive, single-cell, transcriptomic analysis of kidney and marrow cells in the adult zebrafish.

Original Data

Bioinformatic Analysis

1.- RNA-seq Alignment

Application

RNA-Seq Alignment, STAR.

Input

Parameters

  • Upstream Files Pattern: _1

  • Downstream Files Pattern: _2

  • Provide Annotations: true

  • Annotation File: /home/biobam/Downloads/zebrafish_analysis/reference/Danio_rerio.GRCz11.104.gtf

  • Overhang: 35

  • 2-pass Mapping: true

  • Sort by Coordinate: true

  • Min. Intron Length: 20

  • Max. Intron Length: 1000000

  • Max. Distance Between Mates: 1000000

  • Max. # of Multiple Alignments: 20

  • Max. # of Mismatches: 999

  • Include Chimeric Alignments: false

  • Add Read Group Information: false

  • Save Splice Junctions: false

  • Save Unmapped Reads: false

Execution Time

4’5 hours.

Output

2.- Expression Quantification

Application

Create Count Table, Gene-level Quantification

Input

Parameters

  • Feature File: Danio_rerio.GRCz11.104.gtf

  • Quantification Level: gene

  • Group by: gene_id

  • Strand Specificity: Non Strand Specific

  • Overlap Mode: Union

  • Lowest Mapping Quality: 10

Output:

3.- Clustering

Application

Single-cell RNAseq Clustering

Input

Parameters

  • Input Type: Count Table Project

  • Minimum Cells: 1

  • Set Minimum Counts Cutoff: false

  • Set Maximum Counts Cutoff: false

  • Set Minimum Features Cutoff: true

  • Minimum Features: 500

  • Set Maximum Features Cutoff: false

  • Filter by % of Mitochondrial Genes: false

  • Multi Sample Analysis: false

  • Normalize Data: true

  • Normalization Method: Regularized Negative Binomial Regression

  • High Variable Features: 3000

  • Scale Data: false

  • Center Data: true

  • Regress Out Mitochondrial Genes: false

  • Regress Out Cell Cycle Genes: false

  • Principal Components: 50

  • Define Dimensions by: Manual

  • Number of Dimensions: 20

  • k-value: 20

  • Resolution: 0.8

  • Point's Minimum Distance: 0.3

  • Point's Spread: 1.0

Execution Time

10-20 minutes

Output