TITLE: FLASH-seq Low-Amplification protocol (V1)
AUTHORS: Simone   Picelli, Vincent  Hahaut

[DESCRIPTION]
Building upon the existing Smart-seq2/3 workflows, we developed FLASH-seq (FS), a new full-length scRNA-seq method capable of detecting a significantly higher number of genes than both previous versions, requiring limited hands-on time and with a great potential for customization.
FLASH-seq Low-Amplification (FS-LA), represents FS quickest iteration, generating sequencing-ready libraries in 4.5 hours by removing intermediate cleanups and QC steps and without sacrificing performance. FS-LA is the best choice when a large number of plates need to be processed in parallel.

[BEFORE_START]
The protocol should be carried out in a clean environment, ideally on a dedicated PCR workstation or on a separate bench used only for this purpose. Before starting, clean the bench and wipe any piece of equipment with RNAseZAP or 0.5% sodium hypochlorite. Rinse with nuclease-free water to avoid corrosion of delicate equipment.

Work quickly and preferably on ice.

Reagent mixes should be prepared shortly before use.

Mix thoroughly each mix before dispensing. For higher accuracy use liquid handling robots and/or nanodispensers whenever possible. In FLASH-Seq we use the I.DOT (​​Dispendix) for all the dispensing steps and the Fluent 780 liquid handling robot (Tecan) for sample cleanup, reagent transfers and pooling.

The protocol described below is meant to be carried out in 384-well plates. When using 96-well plates, we recommend using 5 times larger volume to guarantee successful cell sorting and prevent evaporation issues.

Always use LoBind plates and tubes (especially for long-term storage) to prevent the cDNA/DNA from sticking to plastic.

[GUIDELINES]
FLASH-Seq Low-Amplification (FS-LA) is a variation of FLASH-Seq, where the cDNA after RT is amplified for a limited number of cycles, in order to reduce PCR bias and reduce library preparation time. Three parameters need to be considered when setting up a FS-LA experiment:

1 --- RNA content of the cell type: this is going to determine how many pre-amplification cycles are required to generate enough cDNA for the tagmentation, while minimizing unmapped / intergenic reads. 
⇒ The exact number of PCR cycles cannot be determined based on the wet-lab results but rather evaluated based on the sequencing results. We recommend performing a pilot study on a subset of cells processed with varying numbers of PCR cycles and choose the value that minimises the background noise.  

2 --- Reaction volume: as the cDNA is not purified prior to tagmentation, it is important to dilute enough the salts and additives of the RT-PCR mix. We recommend diluting the unpurified cDNA 10 times for the best results, although lower dilutions might also work. The increased costs associated with higher reaction volumes are generally negligible when working with in-house Tn5 transposase. When working with the ATM mix contained in the NexteraXT kit we recommend pre-diluting your cDNA 1:10 and performing the tagmentation reaction in 2 µL.

3 --- Amount of Tn5: that needs to be adjusted case by case, depending on the cell type, number of pre-amplification cycles as well as specific activity of each Tn5 batch. 
⇒ The exact value can be evaluated at the wet-lab stage based on the library size distribution.

As a guideline, we recommend choosing 10-12 PCR cycles when working with large cells and/or cell lines (i.e. HEK 293 cells) and 14-16 cycles when working with cells containing smaller amounts of mRNA (i.e. PBMC). Refer to FLASH-Seq manuscript and extended files #2 for more information (Hahaut et al). 

[STEPS]
SECTION: Prepare lysis mix
1. 
 Prepare the following lysis mix:
    ReagentReaction concentrationVolume (µl)384-well plateTriton-X100 (10% v/v)0.2%0.0208.448dNTP mix (25 mM each)6 mM0.240101.376SMART dT30VN (100 µM)1.8 mM0.0187.603RNAse inhibitor (40 U/µL)1.2 U/µL0.03012.672DTT (100 mM)1.2 mM0.0125.069FS TSO (100 µM)9.2 µM0.09238.861dCTP (100 µM)9 mM0.09038.016Betaine (5 M)1 M0.20084.480Nuclease-free water -0.298125.875Total volume (µL) 1.000422.400

 Add 1 µL lysis mix to each well of a 384-well plate

Seal the plate with a PCR seal and quickly spin it down to collect the lysis mix to the bottom.
 
Proceed immediately to the next step or store the plate at -20 °C  long-term. Plates that are going to be used on the same day can be stored in the fridge or kept on ice.
 

SECTION: Sample collection
2. Sort single cells into 384-well plates containing  1 µL lysis mix.

Seal the plate with an aluminium seal. If processing multiple plates at once, keep each plate on dry ice until ready to transfer them all at -80 °C  for long-term storage. Plates containing single cells should ideally be processed within 6 months.
SECTION: Cell lysis
3. Remove the plates from the -80 °C  freezer and check that the aluminium seal is still intact. If damaged or not sticking to the plate anymore, wait a few minutes for the plate to partially thaw, remove the damaged foil and replace it with a new one.

Place the plate in a thermocycler with a heated lid and incubate for 3 min  at 72 °C , followed by a 4 °C  hold step.

Spin down any condensation droplets that may have formed during the incubation and return the plate to a cool rack. Proceed quickly to the next step. If not ready with the RT-PCR mix, keep the plate on the cool rack at all times.
SECTION: RT-PCR reaction
4. While the plate is in the thermocycler, prepare the following RT-PCR mix:
    ReagentReaction concentrationVolume (µL)384-well plateDTT (0.1 M)4.8 mM0.238100.531MgCl2 (1 M)9.2 mM0.04619.430Betaine (5 M)800 mM0.800337.920RNAse inhibitor (40 U/µL)0.8 U/µL0.09640.550SuperScript IV (200 U/µlL2.00 U/µL0.05021.120KAPA HiFi HotStart Ready Mix (2x)1x2.5001056.000Nuclease-free water-0.270114.048Total volume (µL)4.0001689.600

 Add 4 µL  RT-PCR mix into each well of the 384-well plate.

Seal the plate with a PCR seal, gently vortex and spin down to collect the liquid at the bottom.

Place it in a thermocycler with heated lid and start the following RT-PCR program:

     StepTemperatureTimeCyclesRT50ºC60 min1xPCRInitial denaturation98ºC3 min1xDenaturation98ºC20 sec18-21x*Annealing67ºC20 secElongation72ºC6 min15ºCHold

 

 
 
SECTION: Tagmentation and enrichment PCR
5. Please note that the Tn5 transposase amount is a suggested starting point only. Optimisation might be necessary, depending on the specific activity of each batch of Tn5 and desired library size.
Indexing primers can be purchased from Illumina (Nextera XT index kit v2) or ordered from your local oligo manufacturer. In the "Materials" section we have added additional sequences for higher multiplexing.
SECTION: Tagmentation and enrichment PCR
5.1. 
 

Prepare the tagmentation mix as described below:
   ReagentVolume (µL)Final concentrationTAPS-Mg buffer, pH=7.3 (5x)2.00010 mM TAPS, 5 mM MgCl2Dimethylformamide (DMF) (100%)2.00020%Tn5 transposase (2 µM working dil.)0.0255 nMNuclease-free water4.975Total volume (µL)9.000

 

 Dispense 9 µL  tagmentation mix in a new 384-well plate.

Add 1 µL  unpurified cDNA to each well containing the tagmentation mix.

Seal the plate, vortex, spin down, and carry out the tagmentation reaction: 55 °C  for 8 min , 4 °C  hold. Upon completion proceed immediately to the next step.

Add 2.5 µL  0.2% SDS to each well. Seal the plate, vortex, spin down and incubate 5 min at room temperature. Do not put the plate back on ice.

Add 2.5 µL  N7xx + S5xx index adaptors (5 micromolar (µM)  each).

Add 10 µL  enrichment PCR mix to each well:
   ReagentVolume (µL)Final concentrationKAPA HiFi enzyme (1U/μL)0.500.02 U/μLKAPA HiFi Buffer (5x)5.001xdNTPs (10 mM)0.75300 nMNuclease-free water3.75Total volume (µL)10.00

Seal the plate, vortex, spin down, and place it in a thermocycler and carry out the enrichment PCR reaction. Adjust the number of PCR cycles according to the number of processed cells AND the number of pre-amplification cycles used in the RT-PCR reaction.
     StepTemperatureTimeCyclesGap filling72ºC3 min1xEnrichment PCRInitial denaturation98ºC30 sec1xDenaturation98ºC10 sec12-14xAnnealing55ºC30 secElongation72ºC30 sec15ºChold

 

 
SECTION: Library cleanup and quantification
6. Take an aliquot from each sample for the final library cleanup (i.e. 5 µl). and transfer it to a 1.5-ml Eppendorf tube. The rest of the library can be stored long-term at -20 °C .

Remove the Sera-Mag SpeedBeads™ working solution from the 4 °C  storage and equilibrate it at room temperature for 15 min .

Add Sera-Mag SpeedBeads™ working solution to a final ratio of 0.8 x and mix well to homogenisation.

Incubate the tube off the magnetic stand for 5 min  at Room temperature .

Place the tube on the magnetic stand and leave it for 5 min  or until the solution appears clear.

Remove the supernatant without disturbing the beads.

Recommended: wash the pellet with 1 mL  80% v/v ethanol. Incubate 30 s  without removing the tube from the magnetic stand.

Remove any trace of ethanol and let the bead pellet dry for 2 min  or until small cracks appear. Do not cap the tube or remove it from the magnetic stand during this time. Do not completely air-dry the beads.

Remove the tube from the magnetic stand, add 50 µL  nuclease-free water and mix well by pipetting or vortexing to resuspend the beads.

Incubate 2 min  off the magnetic stand.

Place the tube back on the magnetic stand and incubate for 2 min or until the solution appears clear.

Remove 49 µL  of the supernatant and transfer it to a new 1.5-ml LoBind tube. Store the cDNA at -20 °C long-term or until ready for sequencing.

Use Qubit fluorometer to quantify the library. Library yield can vary depending on the number of cells being pooled.

Check the final library size on the Agilent Bioanalyzer.

Use the average size indicated on the Bioanalyzer and the concentration reported after Qubit measurement to determine the exact molarity required for sequencing.


 


 

SECTION: Pooling and sequencing
7. The purified library can be sequenced on any Illumina sequencer. Follow the specifications reported for each instrument. Single-end 75 bp is generally sufficient but longer read modes or paired-end sequencing can be an option, depending on the question at hand.
SECTION: Data processing
8. These instructions briefly describe the data processing of the sequencing results. The final pipeline will likely have to be adapted to the question at hand. The following lines assume that all the programs and their dependencies are installed on your machine and that the data are single-end reads (75 bp). Some values, such as the number of threads and RAM usage may have to be adapted to your machine settings. 

It should be noted that there are many other ways to analyse full-length single-cell RNA-sequencing data. Pseudo-alignment tools (e.g., Salmon or Kallisto) or automatic pipelines (zUMIs) could be used as well.

Requirements (tested version):

bcl2fastq (v2.20)
STAR (v2.7.3)
FeatureCounts (v1.6.5)
BBMAP (v38.86)
samtools (v1.9)
IGV
SECTION: Data processing
8.1. Sample demultiplexing

Sequencing results will be delivered as demultiplexed FASTQ or raw bcl2 files. To convert bcl2 files to FASTQ, bcl2fastq program (Illumina) can be used. 
 

 
When sequencing on a NextSeq 550 instrument, the sample sheet should contain the following information in a csv file:

  
Illumina Experiment Manager can be used to assist you in creating the sample sheet. 

We recommend exploring the barcode combinations left in the undetermined reads looking to confirm that all the cells have been properly demultiplexed.
 
as well as the read distribution between samples:
 

SECTION: Data processing
8.2. Index the genome

The reference genome needs to be indexed prior to any mapping. The FASTA and GTF references can be obtained from ENSEMBL, Gencode, UCSC, ... 
 

 

 

SECTION: Data processing
8.3. FASTQ trimming (optional)

If you observe sequencing primer left-overs the FASTQ files can be trimmed using BBDUK or Trimmomatic.
 

 

SECTION: Data processing
8.4. Mapping

The FASTQ file can then be mapped onto the reference genome. Example for one sample, use a loop or parallelise this task to process all the cells:
 

 

 

SECTION: Data processing
8.5. Data visualization (optional)

Once the reads have been mapped we highly recommend using the Integrated Genome Viewer (IGV) to visualise the mapping results and ensure that the results make sense. As a quick check-up visualise a few housekeeping genes (i.e., ACTB, GAPDH, …) and cell specific markers to look for reads mapping to exon, intron, exon-intron junctions. Look for abnormalities such as read piles falling in intergenic or centromeric regions.
No single-cell RNA sequencing protocol is perfect and non-specific priming, genomic DNA contaminations, … can happen but should represent rare events.
Recurrent soft-clipping could also indicate the presence of sequencing adaptor left-overs that could affect the mapping rate. 

SECTION: Data processing
8.6. Count matrix

Finally, t​he number of reads associated with each gene can be obtained as follows:
 

SECTION: Data processing
8.7. Post-processing

The post-processing steps will vary depending on the question at hand. The online book “Orchestrating Single-Cell Analysis with Bioconductor” (https://bioconductor.org/books/release/OSCA/) is a gold mine of information that can be used to help you design your own pipeline. Alternatively, Seurat (R, https://satijalab.org/seurat/) or scanpy (python, https://scanpy.readthedocs.io/en/stable/) provide tools compatible with FLASH-seq data. Given their similarities, we currently recommend using Smart-seq2 guidelines when processing FLASH-seq data.