CG000284 • Rev A

TECHNICAL NOTE

Chromium Connect: Consistent Automated Single Cell
Gene Expression Library GenerationIntroduction
Chromium Connect automates the preparation of sequencing-ready, single cell libraries from input cell samples,
minimizing technical variation in single cell gene expression data. Generation of Chromium Single Cell 3’ Gene
Expression libraries on the Chromium Connect instrument includes automated Gel Beads-in-emulsion (GEM)
generation, barcoding, and library preparation from single cell suspensions, along with additional functionalities
for library quantification and pooling. This Technical Note highlights the consistency and reproducibility of single
cell gene expression data derived from libraries generated using the Chromium Connect automated workflow.
Chromium Connect
Automated Workflow

The Chromium Connect automated workflow (Figure 1) generates Chromium Single Cell 3’
Gene Expression libraries from up to 8 single cell samples per run, using Chromium Connect
specific automation-compatible reagents and consumables with minimal user interaction.
The libraries can be sequenced and the data analyzed and visualized using Cell Ranger andLoupe Cell Browser for assessing single cell gene expression.

Figure 1. Chromium Connect with integrated components for an automatedworkflow for single cell library generation.

Methods

Peripheral Blood Mononuclear Cell (PBMC) single cell suspension was prepared as describedin Demonstrated Protocol for Fresh Frozen Human Peripheral Blood Mononuclear Cells forSingle Cell RNA Sequencing (Document CG00039). Cells were drawn from the same pool and
Chromium Single Cell 3’ Gene Expression libraries were generated targeting 10,000 cells/
sample for each of the 8 channels, using either Chromium Connect instruments (up to 4) forthe automated workflow or the Chromium Next GEM Single Cell 3’ Reagent Kits v3.1 protocol(Document CG000204) for the manual workflow.

Results

Highly consistent and reproducible data derived from Chromium Single Cell 3’ Gene
Expression libraries generated using the Chromium Connect automated workflow is shownin Table 1. A comparison of single cell gene expression data generated using the Chromium
Connect automated workflow and the manual workflow is depicted in Table 2.

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Technical Note – Chromium Connect: Consistent Automated Single Cell Library Generation • Rev A

Table 1. Chromium Single Cell 3’ Gene Expression libraries generated using the Chromium Connect automated workflow show
highly consistent and reproducible data.
Automated Workflow–Data Consistency & Reproducibility
QC Traces: Channel-to-channel consistency
PBMC single cell suspension samples (1 replicate in each of the 8 channels in an instrument) were used to generate
single cell gene expression libraries using the Chromium Connect automated workflow. Consistent cDNA QC andlibrary QC traces were observed across all 8 channels of the chip used in the automated workflow, as shown in the
representative Agilent BioAnalyzer traces. All sample traces showed comparable size distribution and concentration,
indicating highly consistent performance.
cDNA QC: Representative Traces

Library QC: Representative Traces

Gene Expression Profile: Channel-to-channel consistency
Each of the libraries generated across the 8 channels of the Chromium Connect instrument showed highly consistentgene expression profiles. As shown below, the correlation value of gene expression profile of libraries derived form
each channel relative to channel 1 was >0.99.
Channel 3

Channel 4Channel 5

Channel 6

Channel 7

Channel 8

R2=0.999

R2=1.0R2=0.999

R2=0.999

R2=1.0R2=0.999

R2=0.999

Channel 1

Channel 2

Gene Expression Profile: Instrument-to-instrument consistency
The gene expression profiles of PBMCs used for generating single cell gene expression libraries across 4 different
Chromium Connect instruments showed high degree of consistency and correlation.
Instrument 2

Instrument 3

Instrument 4

R =0.999

R =1.0R2=0.999

2Instrument 12

Technical Note – Chromium Connect: Consistent Automated Single Cell Library Generation • Rev A2

Table 2. Comparison of data derived from Chromium Single Cell 3’ Gene Expression libraries generated using either theChromium Connect automated workflow or the manual workflow.
Single Cell Gene Expression Data—Automated vs. Manual Workflow
Minimal User Variability
The Chromium Connect automated hands-off workflow minimizes user variability. Differences in user handling likely
contribute to a wider distribution of median genes and Unique Molecular Identifier (UMI) counts recovered per cell in
96 libraries prepared using the manual workflow compared to 96 libraries generated using the Chromium Connect
automated workflow (over multiple days, targeting 500-10,000 cells/sample).
Median UMI CountMedian genes/cell (50k raw read pairs/cell)Median UMI counts/cell (50k raw read pairs/cell)Median Genes

Automated

Workflow

ManualAutomated

Workflow

ManualConsistent Cell Type Profiling
The gene expression profiles compared in libraries generated from 10,000 PBMCs using either the manual or theChromium Connect automated workflow identifies all major PBMC cell types. The single cell barcode tSNE plots show
the gene expression data analyzed and visualized using Cell Ranger and Loupe Cell Browser, respectively. Major cell
populations in each cluster were identified via marker gene expression. Comparable cell type profile among the twosets of data is also shown in the graph below. This demonstrates that the automated workflow generates consistentgene expression data for cell type profiling.
Automated Workflow: Cell Type Profile

Manual Workflow: Cell Type Profile

Percentage of cell population (%)

Cell Types

Automated
ManualCell Types

Technical Note – Chromium Connect: Consistent Automated Single Cell Library Generation • Rev A3

Table 2 contd. Comparison of data derived from Chromium Single Cell 3’ Gene Expression libraries generated using either theChromium Connect automated workflow or the manual workflow.
Single Cell Gene Expression Data—Automated vs. Manual Workflow
Accurate Cell Type Marker Detection
To investigate possible changes in gene expression due to automated workflow, expression of major blood cell typemarkers were compared in data generated using either the automated or the manual workflows. All the key markers
were detected in both datasets (see t-SNE plots below).

T cells(IL7R, CD8a)

B cells(CD79a)Myeloid cells(S100A9)Natural Killer cells(NCAM1)

Automated
Workflow

ManualWorkflow

Comparison of cell type marker expression data generated from 10,000 PBMCs using 4 channels in one Chromium
Connect run highly correlated with the data generated using the manual workflow (4 channels/run by 1user) with acorrelation value of >0.99, as shown in the plot below.
Automated

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Technical Note – Chromium Connect: Consistent Automated Single Cell Library Generation • Rev A4