Split Sequence Analysis

Split-pool ligation-based transcriptome sequencing (SPLiT-seq) is a scRNA-seq method that enables transcriptional profiling of hundreds of thousands of fixed cells or nuclei in a single experiment. SPLiT-seq does not require partitioning single cells into individual compartments (droplets, microwells, or wells) but relies on the cells themselves as compartments , see [1], its steps are presented visually in the following figure [2].

split sequence Analysis process

SPLiT-seq has four steps (reference [1]): 1) Reverse transcription: first round of barcoding, cells are distributed into a 96-well plate, and cDNA is generated with an in-cell reverse transcription (RT). 2) Ligation: cells from all wells are pooled and redistributed into a new 96-well plate, where an in-cell ligation reaction appends a second well-specific barcode to the cDNA. 3) Ligation: The third-round barcode, which also contains a unique molecular identifier (UMI), is then appended with another round of pooling, splitt- ing, and ligation. At this step, cells will be pooled and subsequently split into between one and eight distinct populations we call sublibraries. Each sublibrary will contain a different 4th barcode (the Illumina index) and can be sequenced separately, see [3]. 4) Lys and PCR: After three rounds of barcoding, the cells are pooled and split into sublibraries, and sequencing barcodes are introduced by polymerase chain reaction (PCR). This final step pro- vides a fourth barcode, while also making it possible to sequence different numbers of cells in each sublibrary. After sequencing, each transcriptome is assembled by combining reads containing the same four-barcode combination

Analysis Flowchart

split sequence Analysis process

Here we present a split-seq workflow analysis.

• Fastq: one use bcl2fastq to generate fastq.

• Prepare reference: run the split-pipe with --mode mkref to create an indexed reference genome for the genome (Homo_sapiens.GRCh38.93.gtf.gz), genes (Homo_sapiens.GRCh38.93.gtf.gz), and a specific version version of star and samtools.

• Process analyis: in this step you need to run split-pipe to run the following sub-steps
  • pre: Pre-process fastq files (barcode correction + cDNA).
  • align: Align barcode-corrected reads (STAR).
  • post: Post-process read alignment (sort bam, samtools).
  • mol: Molecule info extraction (barcodes, tscps, genes from reads).
  • dge: Digital gene expression matrix creation and stats.
  • ana: Analysis of called cells and samples (clustering, etc).
  • rep: Generate output reports for each sample.
  • clean: Clean up intermediate files (compress / delete).
    The split-pipe with --mode all, run all these sub-steps.
• Combine: in this step, one needs to combine the results from the processed sublibraries.
• Analysis output: the output of running the pipeline includes
  • <sample-name>\_analysis_summary.html contains summary statistics and plots for a given sample.
  • <sample-name>\_analysis_summary.csv contains pipeline metrics about the sample.
  • DGE.mtx is a sparse matrix with cell-gene counts. Each row corresponds to a cell and each column corresponds to a gene (see genes.csv file for names/gene-id of each column).
  • genes.csv contains the gene name, gene id, and genome for each column in DGE.mtx.
  • cell_metadata.csv file contains information about each cell including the cell barcode, species, sample, well in each round of barcoding, and number of transcript/genes detected.

Tools used in this workflow:

1. bcl2fastq
2. split-pipe

Bibliography:

[1]. Rosenberg AB, Roco CM, Muscat RA, Kuchina A, Sample P, Yao Z, Graybuck LT, Peeler DJ, Mukherjee S, Chen W, Pun SH. Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding. Science. 2018 Apr 13;360(6385):176-82.PMID: 29545511

[2]. Single-Cell RNA Sequencing May Be Split By Parse Biosciences Internet

[3]. Parse Biosciences company Internet