Page Comparison

General comparison between QS When switching from QuantSeq-FWD to QuantSeq-Pool, there are certain considerations researchers should take to ensure QuantSeq-Pool is the appropriate kit for their application.

General comparison between QuantSeq-FWD (Cat. No. 191-196) and

...

QuantSeq-Pool (Cat. No. 139)

...

	QuantSeq-FWD	QuantSeq-Pool
Input

amount

amounts

1ng - 500ng

**lower inputs possible with protocol modifications
I prefer not to mention any input lower than 1 ng.
I would rather indicate:
1 ng - 500 ng

* *low input protocol

modification

modifications available for 1 ng - 10 ng.

10ng - 120ng per sample

(first strand synthesis or FSS) into FSS

into First Strand Synthesis. 80ng - 960ng per pool

(second strand synthesis or SSS) into SSS

into Second Strand Synthesis.

RNA quality

N/A - both high

High and low quality RNA is acceptable, as well as FFPE RNA.

Medium

-

to high quality RNA required (i.e., RIN >6).
Blood samples	Compatible with

RS-

Globin

block modules
cat n°

Block Modules (Cat. No. 070 (Homo sapiens)

cat n°

and 071 (Sus scrofa)).

Not recommended

UMI

optional with UMI Add-on Cat n° 081.
UMI

.
Unique Molecular Identifiers (UMIs)	Optional with UMI Second Strand Synthesis Module (Cat. No. 081). UMIs are 6 nt long (

with

plus a 4

-

nt spacer) and added during

second strand synthesis included

Second Strand Synthesis.

Included. UMIs are 10 nt long

Added during first strand synthesis

and added during First Strand Synthesis.
First Strand Synthesis Primer	Oligo(dT) primer with partial Illumina adapter sequence.	Oligo(dT) primer with

12nt

12 nt i1 barcode,

10nt

10 nt UMI, and partial Illumina adapter sequence.
Library Quality Control (QC)	QC individual libraries and pool at equimolar ratio.	QC final, pooled library; individual library QC not possible due to early pooling after reverse transcription.
Average Library Size	~335 – 456 bp (based on UHRR)* *Can vary based on RNA quality and sample type.	~650 bp (based on UHRR)* *Can vary based on RNA quality and sample type.
Sequencing mode	Single Read (SR) Read 1: insert; 50 – 150bp	Paired End Read (PE) Read 1: insert; 50 – 150bp Read 2: UMI and i1 barcode; 22bp
Demultiplexing	i5/i7 demultiplexing required

(can be done with bcl2fastq)
I would like to promote idemux here

.

Suggestion:

If only using Lexogen 12 nt UDI in your sequencing lane (e.g., with other Lexogen libraries), we recommend

idemux

iDemux for demultiplexing and optimal error correction.

i5/i7 demultiplexing optional (if UDI are used). i1 demultiplexing required (

idemux

iDemux recommended)

i5/i7 demultiplexing optional

. If only using Lexogen 12 nt UDI in your sequencing lane (e.g., with other Lexogen libraries), we recommend

idemux

iDemux for demultiplexing and optimal error correction.

What components are interchangeable

...

between QuantSeq-FWD and QuantSeq-Pool?

• Use same input amountCompare samples at same read depth - down sample the same sample type and same input amounts.

• Include technical replicates to assess handling variability (QuantSeq-FWD samples are processed separately whereas QuantSeq-Pool samples are processed together).

• Optional: Include spike-in RNA controls (SIRVs) for assessing differential gene expression to determine “ground truth” (comparing expected vs observed).

• Compare samples using the same read depth and downsample if necessary (e.g., if you have 10 million reads in library for Sample A and 1 million reads in library for Sample B, you need to randomly - through bioinformatics - decrease the number of analysed reads in library A down to 1 million)Same randomly discard a specified fraction of reads so Sample A and Sample B both have 1 million reads.). If you have questions about downsampling, please contact support@lexogen.com.

• Use the same Read 1 length (i.e., insert length). We recommend >75bp for Read 1.

• Do not collapse UMIs, even if UMIs are included in QuantSeq-FWD (with SSS UMI Module)

• Include Recommend including technical replicates to assess handling variability (QSF samples processed separately whereas QSP samples processed together)

• Include Recommend including controls (SIRVs) as “ground truth” (compare expected vs observed) to assess differential gene expression DEG, if interested in this parameter (compare expected vs observed)

What can also cause differences:

• Differences in chemistries and protocol. It is instead advised to check the correlation of non-collapsed samples.