Cell Lysate BRB-seq
Library Preparation kit for 24, 96, 384 and 1536 samples
PN 10840, 10841, 10851, 11041, 11051
User Guide
v.0.1.6.revC November 2022
FOR RESEARCH USE ONLY
ALITHEAGENOMICS.COM

Related Products

10540
Cell Lysate BRB-seq Library| 10841| Barcoded Oligo-dT Adapters Module 96 samples| 10513
Preparation 96 kit| Cell Lysate Library Preparation and UDI Module 96 samples| 10541
Cell Lysate BRB-seq Library| 10851| Barcoded Oligo-dT Adapters Module 384 samples| 10515
Preparation 384 kit| Cell Lysate Library Preparation and UDI Module 384 samples| 10551
Cell Lysate BRB-seq Library| 11041| Barcoded Oligo-dT Adapters Module 4 x 96 samples| 10513
Preparation 384 (4×96) kit| Cell Lysate Library Preparation and UDI Module 4 x 96 samples| 10555
Cell Lysate BRB-seq Library| 11051| Barcoded Oligo-dT Adapters Module 4 x 384 samples| 10515
Preparation 1536 (4×384) kit| Cell Lysate Library Preparation and UDI Module 4 x 384 samples| 10556

Kit Components

Reagents supplied
Barcoded Oligo-dT Adapters Set V5A Module

Component Name| Label| Amount provided per kit|
---|---|---|---
24 samples (PN 10840)| 96
samples
(PN 10841)
–| 384 samples
(PN 10851)| 4 x 384
samples
(PN 11051)| 4 x 384
samples
(PN 11051)|     Storage
Plate with 24 barcoded oligo-dT
primers, set V5A (PN 10514)| 24 V5A
OdT| 1 plate| –| -)| –| –| -20°C
Plate with 96 barcoded oligo-dT
primers, set V5A (PN 10513)| 96 V5A
OdT| –| 1 plate| –| 4 plates| –| -20°C
Plate with 384 barcoded oligo-dT
primers, set V5A (PN 10515)| 384 V5A
OdT| –| –| 1 plate| –| 4 plates| -20°C
Aluminium Seal| –| 3 pcs| 3 pcs| 3 pcs| 12 pcs| 12 pcs| 20°C/RT

Cell Lysate Library Preparation and UDI Module

Component Name| Label| Cap colour| 24 samples
(PN 10540)| 96 samples
(PN 10541)| Volume (µL)
384 samples
(PN 10551)| 4 x 96
samples
(PN
10555)| 4 x 384
samples
(PN
10556)|     Storage
---|---|---|---|---|---|---|---|---
RT Enzyme| RTE| magenta| 10| 11| 43| 43| 4 x 43| -20°C
RT Buffer| RTB| magenta| 135| 550| 1100| 2 x 1100| 4 x 1100| -20°C
| EXO| purple| 10| 10| 10| 10| 10| -20°C
| EXB| purple| 20| 20| 20| 20| 20| -20°C
| SSE| orange| 20| 20| 20| 20| 20| -20°C
| SSB| orange| 45| 45| 45| 45| 45| -20°C
| TE| red| 10| 10| 10| 10| 10| -20°C
| TAB| red| 40| 40| 40| 40| 40| -20°C
| LAM| green| 200| 200| 200| 200| 200| -20°C
Control Human RNA| Ctrl hRNA| blue| 10| 10| 10| 10| 10| -20°C
UDI Adapter Mix 1| MQ.UDI.1| transparent| 10| 10| 10| 10| 10| -20°C
UDI Adapter Mix 2| MQ.UDI.2| transparent| –| 10| 10| 10| 10| -20°C
UDI Adapter Mix 3| MQ.UDI.3| transparent| –| 10| 10| 10| 10| -20°C
UDI Adapter Mix 4| MQ.UDI.4| transparent| –| 10| 10| 10| 10| -20°C
Nuclease-Free Water| NFW| transparent| 1800| 1800| 1800| 2 x 1800| 8 x 1800| -20°C
Cell Lysis Buffer| CLB| yellow| 90| 355| 700| 2 x 700| 4 x 700| -20°C
RNase Inhibitor| INH| yellow| 25| 95| 170| 2 x 170| 4 x 170| -20°C

Additional required reagents and equipment (supplied by the user)

6101/6131

Protocol Overview and Timing

The MERCURIUSTM Cell Lysate BRB-seq kits allow the preparation of Illumina- compatible 3`RNA sequencing libraries for up to 1536 RNA samples in a time and cost-efficient manner. The kits include a mild cell lysis buffer to prepare crude cell lysates that can be used directly in RT reaction, skipping the tedious RNA purification step. The kits are provided in the following formats:

Kit format| PN| PCR plate format| Maximum number of samples in one pool| Maximum number of samples processable| Number of UDI Libraries
---|---|---|---|---|---
24-sample| 10840| 96WP| 24| 24| 1
96-sample| 10841| 96WP| 96| 96| 4
384-sample| 10851| 384WP| 384| 384| 4
4×96-sample| 11041| 96WP| 96| 384| 4
4×384-sample| 11051| 384WP| 384| 1536| 4

Every kit contains barcoded MERCURIUSTM Oligo-dT primers designed to tag polyA+ RNA from lysate samples with individual barcodes during the first strand synthesis reaction, allowing the pooling of the resulting cDNA samples from each experimental group into a single tube for streamlined sequencing library preparation. The 24sample kit contains barcoded oligo-dT primers in the first three columns (1-3) of the 96-well plate.
The BRB-seq technology can be used to generate high-quality sequencing data from 5k – 100k mammalian cells per well. However, for optimal results, the starting amount of at least 5k cells per well and pooling of at least 16 barcoded samples is recommended. Notably, the kit can be used to pool any number of samples up to the capacity of the provided plate (24, 96 or 384) with two considerations:

• The total cell number per pool should be at least 80k.
• Pooling less than eight samples may result in low complexity reads during sequencing, decreasing the overall sequencing quality. If necessary, the latter can be improved by increasing the proportion of

PhiX spike-in control during sequencing (see Part 3).
Each library indexing is performed using a Unique Dual Indexing (UDI) strategy, which minimizes the risk of barcode misassignment after NGS. The kits contain four UDI adapters, besides the 24-sample kit that includes only one. Every adapter can be used to prepare an individual BRB-seq library. Libraries with different UDI adapters can be pooled and sequenced in a single flow cell. Below is an estimation of the time required to accomplish each protocol step.

1.        Cell lysis (optional)
a.        Cell lysis buffer distribution
b.        Incubation
c.        Cell lysates transfer| 20 min
15 min
5 min| 25 min hands-on
40 min total
Safe stop -80°C
2.     Reverse transcription| | |
a.     RNA samples preparation| 20 min| 8 am|
b.     RT mix preparation| 5 min| |
c.     Incubation| 60 min| 8:30 am| 50 min hands-on
d.     Samples pooling| 20 min| | 2h 30 min total
e.     Reaction preparation| 5 min| |
f.      Incubation| 50 min| 11 am| Safe stop +4°C
3.     Second strand synthesis| | |
a.     Reaction preparation| 5 min| | 35 min hands-on
b.     Incubation| 50 min| 12 pm| 1h 30 min total
c.     Beads clean-up| 30 min| | Safe stop -20°C
4. Tagmentation
a.  Reaction preparation| 5 min| 1:45 pm| 35 min hands-on
b.     Incubation| 7 min| | 50 min total
c.     Beads clean-up| 30 min| |
5.     Library amplification| | |
a.     Reaction preparation| 5 min| 2:35 pm| 35 min hands-on
b.     PCR| 50 min| | 1h 25 min total
c.     Beads clean-up| 30 min| | Safe stop -20°C
6.     Library QC| | |
a.     Qubit quantification| 10 min| 4 pm| 10 min hands-on
b.     Smear analysis| 60 min| 5:10 pm| 1h 10 min total

Protocol Workflow

Figure 1 Schematic illustration of the protocol workflow

Part 1. PREPARATION OF CELL LYSATE SAMPLES

1.1. Essential considerations for input cells

•  The recommended input range of cells is 10-50k/well of 96WP and 5-10k/well of 384WP.
• Cells must be seeded a few days in advance for the best results.
• Depending on the type of cells (human, mouse, cancer, or primary cells) and experimental design (e.g., induction of differentiation or apoptosis, cell cycle arrest, etc.), consider the doubling time of cells after the seeding and potential effect of the treatment on a cell number during the experiment.
• To ensure an even distribution of reads after sequencing, the amount of starting material must be as uniform as possible. For this, we suggest using automatized cell seeding instruments or doubleverified cell count.
• The cell lysate used in the RT reaction should be at most 50% of the final volume.

1.2. Cell lysates preparation
At this step, plated cells are lysed directly in a 96 or 384-well plate by adding a cell lysis buffer to prewashed cells. The lysates can be directly used for the reverse transcription reaction
Preparation
Prepare working solution of Cell Lysis Buffer with RNase Inhibitor:

Pipette a prepared mix gently a few times, and briefly spin the tube. Keep the mix on ice until further use
Procedure for adherent cells preparation
1.2.1. Seed the cells in a flat bottom 96WP or 384WP at the density that will enable harvest:
■ 96WP: 10-50k cells per well
■ 384WP: 5-10k cells per well
1.2.2. Gently aspirate culture media from the plate and wash cells by adding the following:
■ 96WP: 80-100 µL DPBS in each well
■ 384WP: 30-50 µL DPBS in each well
1.2.3. Gently tap the plate and aspirate as much DPBS as possible without disturbing the cell pellet.
1.2.4. Immediately proceed to step 1.2.11.
Procedure for suspension cells preparation
1.2.5. Seed the cells in a flat bottom or U-shaped 96WP or 384WP at the density that will enable harvest:
■ 96WP: 10-50k cells per well
■ 384WP: 5-10k cells per well
1.2.6. Centrifuge the plate at 300x g for 5 minutes.
1.2.7. Gently aspirate culture media from the plate without disturbing the cell pellet and wash cells by adding:
■ 96WP: 80-100 µL of DPBS in each well
■ 384WP: 30-50 µL of DPBS in each well
1.2.8. Centrifuge the plate at 300x g for 5 minutes.
1.2.9. Gently tap the plate and aspirate as much DPBS as possible without disturbing the cell pellet.
1.2.10. Immediately proceed to step 1.2.11.
Procedure for cell lysis
1.2.11. Using a multi dispenser, distribute prepared CLB in every well.
■ 96WP: 10 µL per well
■ 384WP: 5 µL per well
1.2.12. Gently tap the plate to ensure that CLB is uniformly distributed on the surface of each well.
1.2.13. Incubate the plate on ice for 15 min, slightly agitating it from time to time.
1.2.14. Label a new 96- or 384-well PCR plate and transfer the entire volume of cell lysates from every well to a corresponding well of the new 96 or 384-well PCR plate. Preferably use a multichannel pipette and avoid intensive pipetting to reduce bubbles.
1.2.15. Seal the plate with an Aluseal provided and briefly spin it down.
1.2.16. The lysates can be used directly for library preparation or safely stored at -80°C.
NOTE: If several plates must be processed, perform the procedure with each plate individually one by one to avoid keeping plates at room temperature for a prolonged time.

Part 2. LIBRARY PREPARATION PROTOCOL

2.1. Reverse transcription
Each individual cell lysate sample is reverse-transcribed at this step using barcoded oligo-dT primers provided in 96-well (96WP) or 384-well (384WP) formats depending on the kit type. Subsequently, all barcoded samples can be pooled in one tube. If you would like to include the Control RNA sample to assess the library preparation process at each step, see Appendix 1 for the details.
Preparation

• Thaw the cell lysate samples on ice.
• Thaw the RTB reagent at room temperature and mix well before use.
• Briefly spin down the 96WP or 384WP plate(s) containing dried oligo-dT primers. This plate will be referred to as the RT-plate(s).
• Prepare the Program 1_RT on the thermocycler (set the lid at 90°C):

Procedure for 96WP and 384WP
2.1.1. Keep the RT-plate on ice; using a multichannel pipette, transfer the following volume of cell lysate directly to the corresponding wells and pipette 3-5 times to ensure proper reconstitution of dried oligo-dT:
■ 96WP: 10 µL
■ 384WP: 5 µL
2.1.2. Carefully re-seal the RT-plate(s) and briefly spin it in the centrifuge.
2.1.3. Leave the RT-plate(s) on ice for 5 min.
2.1.4. Prepare the Master Mix for RT reaction (+10%) as follows:

Per well
(µL)| 24 wells
+10% (µL)| 96 wells
+10% (µL)|
wells| Per wel(µL)| 384 wells
+10% (µL)|
wells
RTB| 5| 132| 528| | 2.5| 1056|
RTE| 0.1| 2.65| 10.6| | 0.1| 43|
NFW| 4.9| 129.4| 517.5| | 2.4| 1014|
TOTAL| 10| 264| 1056.1| | 5| 2113|

2.1.5. Keep the RT-plate(s) on ice and using a multichannel pipette transfer the following volume of Master Mix to each well containing the cell lysate sample:
■ 96WP: 10 µL
■ 384WP: 5 µL
2.1.6. Carefully re-seal the RT-plate(s) and briefly spin it in the centrifuge.
2.1.7. Transfer the plate to the thermocycler and start the Program 1_RT.
Safe stop: After this step, the RT-plate(s) can be kept at 4°C overnight.
2.2. Samples pooling and column purification
The barcoded RT samples are pooled and purified at this step using Zymo Clean & Concentration Kit (Zymo, D4014). A high-capacity Zymo-Spin IIICG column (Zymo, C1006-50-G) is required to purify large volumes resulting from 384 sample pooling.
After the cDNA from each well is pooled in a reservoir, mix it with a 7x volume of DNA binding buffer (Zymo, D40041-L).
We strongly recommend using a vacuum manifold for the cDNA purification to avoid column membrane damage due to multiple centrifugation rounds. A bench- top centrifuge can be used in case of pooling 24 samples or less.
NOTE: A pool may contain some cell debris, which could block a column membrane during purification leading to a long waiting time. To avoid this, it is recommended to perform a pre-cleaning of the RT pool by passing it through the Zymo column (see below) before mixing it with 7x DNA Binding buffer

| | | For 24 wells| For 96 wells| For 384 wells
---|---|---|---|---|---
Recommended pipetting strategy| –| –| multichannel pipette| | pipetting robot
Plasticware
Pooling reservoir type| –| –| 25 mL  (Integra #4382)| 150 mL (Integra #6318)| 150 mL (Integra #6318)
Zymo-Spin column type| –| –| I
(#D4014)| I
(#D4014)| IIICG (C1006-50-G)
Pooling volumes| Plate format| Per well (µL)| For 24 wells| For 96 wells| For 384 wells
First strand cDNA (mL)| 96WP| 20| 0.48| 1.92| –
384WP| 10| –| –| 3.84
DNA Binding Buffer| 96WP| 140| 3.36| 13.44| –
384WP| 70| –| –| 26.88
TOTAL (mL)| 96WP| 160| 3.84| 15.36| –
384WP| 80| –| –| 30.72

Table 1 Overview of the recommended pipetting strategy, plasticware, and reagents volumes to be used depending on the number of pooled samples
Preparation
• Make sure Zymo DNA Wash buffer has Ethanol added.
Procedure of a pool pre-cleaning and cDNA purification with vacuum manifold (>24 samples)
2.2.1. According to the Table 1, use a multichannel pipette, or pipetting robot, to transfer the entire RT volume (20 µL for 96WP, 10 µL for 384WP) of each sample into a specified reservoir.
2.2.2. Mix well the pool and transfer it to a falcon tube with a pipette.
2.2.3. For the RT pool pre-cleaning, place a Zymo column in a new 2 mL tube, add 800 µL of the collected pool, and briefly centrifuge.
2.2.4. Collect a cleaned flowthrough in a new falcon tube. Repeat step 2.2.3 until all pool passes through the Zymo column. Discard the column.
2.2.5. Using a pipette, measure the volume of the pool after cleaning, transfer it to a 50 mL falcon tube and add a 7x DNA Binding buffer accordingly (see the table).
2.2.6. Add a volume of the 7x DNA Binding buffer according to the combined volume of the RT (Table 1).
2.2.7. Connect the 25 mL funnel (Zymo, C1039-25) to a Zymo column suitable for purification volume
(Table 1) and place it on a vacuum manifold.
2.2.8. Gently mix the cDNA in the binding buffer mixture in a reservoir and, using a pipetboy, transfer it to 25 ml funnel.
2.2.9. Turn on the vacuum pump and let the liquid pass through the column.
2.2.10. Transfer any remaining volume to the funnel, do not let the membrane overdry.
2.2.11. After the entire pool mix passed through the column, add 200 µL of DNA Wash buffer (with Ethanol added) directly to the membrane of the column.
2.2.12. Repeat step 2.2.11 once the wash buffer passed through the filter.
2.2.13. Remove the column from a vacuum manifold, put it in a 1.5ml tube, and centrifuge for 1 min to remove leftovers from the washing buffer.
2.2.14. Depending on the Zymo-Spin column type used, perform the following:
■ For the type I column used with ≤96 samples (96WP), add 20 µL of NFW to the column matrix and incubate for 1 min.
■ For the type IIICG column used with 384 samples (384WP), add 38 µL of NFW to the column matrix and incubate for 1 min.
2.2.15. Transfer the column into a new labelled 1.5 mL tube and centrifuge for 30 sec.
2.2.16. Immediately proceed to step 2.3.
Procedure of cDNA purification with a centrifuge (≤24 samples)
Follow the protocol provided in Zymo Clean & Concentration Kit (Zymo, D4014). After cDNA elution in 20 µL, immediately proceed to step 2.3.
2.3. Free primer digestion
It is recommended to perform the non-incorporated primer digestion immediately after pooling.
Preparation

• Label 0.2 mL PCR tubes corresponding to the number of pools prepared.
• Thaw EXB at room temperature.
• Keep EXO on ice.
• Prepare the Program 2_FPD on the thermocycler (set the lid at 90°C):

Procedure
2.3.1. Transfer 17 µL eluate from each tube from step 2.2.15 into a new labelled 0.2 mL PCR tube. For 384WP protocol, split the eluate into two 0.2 mL tubes of ~17 µL each.
2.3.2. Prepare the EXO reaction mix as follows:

Reagent| Per reaction (µL)| For 2 reactions (µL)| For 4 reactions (µL)
---|---|---|---
EXB| 2.0| 4.4| 8.8
EXO| 1.0| 2.2| 4.4
TOTAL| 3.0| 6.6| 13.2

2.3.3. Transfer 3 µL of EXO reaction mix into each PCR tube with purified cDNA.
2.3.4. Mix by pipetting up and down 5 times.
2.3.5. Briefly spin down in the bench-top centrifuge.
2.3.6. Incubate in thermocycler Program 2_FPD.
2.3.7. Proceed immediately to step 2.4. or keep the tube at 4°C overnight.
Safe stop: After this step, the tube(s) can be kept at 4°C overnight. 2.4. Second strand synthesis
The double-stranded full-length cDNA is generated and purified at this step using magnetic beads.
Preparation

• Pre-warm SPRI beads at room temperature for ~30 min.
• Prepare 5 mL of 80% ethanol.
• Thaw the SSB reagent at room temperature and mix well before use.
• Keep SSE reagent constantly on ice.
• Prepare the Program 3_SSS on the thermocycler (set the lid at 70°C):

Second strand synthesis reaction setup
2.4.1. Prepare the SSS reaction mix for the second strand synthesis as follows:

Reagent| Per reaction (µL)| For 2 reactions (µL)| For 4 reactions (µL)
---|---|---|---
SSB| 5.0| 11.0| 22.0
SSE| 2.0| 4.4| 8.8
TOTAL| 7.0| 15.4| 30.8

2.4.2. Transfer 7 µL of SSS reaction mix to the tube from step 2.3.7 and mix well by pipetting up and down 5 times.
2.4.3. Incubate in thermocycler Program 3_SSS.
2.4.4. Proceed immediately to step 2.4.5.
Full-length cDNA clean-up with SPRI beads
Perform the double-stranded cDNA purification with SPRI magnetic beads using a 0.6x ratio (i.e., 30 µL of bead slurry plus 50 µL of cDNA):
■ For 96WP protocol: adjust the cDNA volume in each tube to 50 µL with NFW
■ For 384WP protocol: combine the cDNA from both tubes and adjust the volume to 50 µL with NFW if necessary
NOTE: Use pre-warmed beads and vortex them vigorously before pipetting.
2.4.5. Complement the final volume to 50 µL with NFW.
2.4.6. Add 30 µL of beads and mix by pipetting up and down 10 times.
2.4.7. Incubate for 5 min at room temperature.
2.4.8. Place the tube on the magnetic stand, wait 5 min, and carefully remove and discard the supernatant.
2.4.9. To wash the beads, pipette 200 µL of freshly prepared 80% ethanol into the tube.
2.4.10. Incubate for 30 sec.
2.4.11. Carefully remove the ethanol without touching the beads pellet.
2.4.12. Repeat step 2.4.9 for the total of two washes.
2.4.13. Remove the tube from the magnetic stand and let the beads dry for 1-2 min.
2.4.14. Resuspend the beads in 21 µL of NFW.
2.4.15. Incubate for 1 min.
2.4.16. Place tubes on the magnetic stand, wait 5 min, and carefully transfer 20 µL of the supernatant into a new tube to avoid bead carry-over.
2.4.17. Use 2 µL to measure the concentration with Qubit.
Safe stop: At this step, the cDNA can be safely kept at -20°C for up to a few weeks.
2.5. Tagmentation
At this step, the full-length cDNA is tagmented using a Tn5 transposase pre- loaded with adapters for library amplification. It is recommended to use 20 ng of cDNA for tagmentation to obtain a higher library complexity with less PCR amplification.
Preparation

• Pre-warm SPRI beads at room temperature for ~30 min.
• If needed, prepare fresh 5 mL of 80% ethanol.
• Thaw the TAB reagent at room temperature and mix well before use.
• Keep the TE reagent constantly on ice.
• Set the PCR machine at 55°C incubation.

Procedure
2.5.1. Prepare the Tagmentation mix on ice in a PCR tube. If several cDNA samples are tagmented, prepare the Master mix as follows (with 10% excess):

| Per reaction (µL), for cDNA inputs
---|---
Reagent| ≤ 9 ng| 10-14 ng| 15-20 ng| N +10% (µL)
TAB| 4.0| 4.0| 4.0|
TE| 1.0| 2.0| 3.0|
cDNA| X µL| X µL| X µL|
NFW| 15.0 – X| 14.0 – X| 13.0 – X|
TOTAL| 20| 20| 20|

2.5.2. Keep the mix on ice and pipette up and down 10 times with the pipette set at 5 µL. Pay attention to mixing the reaction volume thoroughly.
2.5.3. Incubate for 7 min at 55°C in the PCR machine.
2.5.4. Immediately put the tube on ice and add 30 µL of water for the final volume of 50 µL. Tagmented cDNA clean-up with SPRI beads
Purify the tagmented cDNA with SPRI magnetic beads using a 0.6x ratio.
NOTE: Use pre-warmed beads and vortex them vigorously before pipetting.
2.5.5. Add 30 µL of beads to 50 µL of tagmented cDNA and mix by pipetting up and down 10 times.
2.5.6. Incubate for 5 min at room temperature.
2.5.7. Place the tubes on the magnetic stand, wait 5 min, and carefully remove and discard the supernatant.
2.5.8. To wash the beads, pipette 200 µL of freshly prepared 80% ethanol into the tube.
2.5.9. Incubate for 30 sec.
2.5.10. Carefully remove the ethanol without touching the beads pellet.
2.5.11. Repeat steps 2.5.8 – 2.5.10 for a total of two washes.
2.5.12. Remove tubes from the magnetic stand and let the beads dry for 1-2 minutes.
2.5.13. Resuspend the beads in 21 µL of NFW.
2.5.14. Incubate for 1 min.
2.5.15. Place tubes on the magnetic stand, wait 5 min and carefully transfer 20 µL of the supernatant into a new tube to avoid bead carry-over.
Safe stop: At this step, the cDNA libraries can be safely kept at -20°C for up to a few weeks
2.6. Library indexing and amplification
At this step, the 5’ terminal fragments are amplified using Unique Dual Indexing (UDI) adapter primers.
The kit contains 4 Illumina-compatible primer pairs to generate UDI libraries. The index sequences are indicated in Appendix 2.
The number of amplification cycles required for library preparation is usually in the range of 12-17. The actual number may depend on the RNA samples and the input cDNA amount used for tagmentation. To determine the optimal number of cycles, follow the Library Quantification Protocol in Appendix 3.
It is strongly recommended to perform the final library beads clean-up twice to remove the primer dimer fragments.
Preparation

• Pre-warm the SPRI beads at room temperature for ~30 mins.
• Prepare 10 mL of 80% ethanol.
• Thaw the LAM reagent on ice and mix well before use.
• Thaw the required number of MQ.UDI Adapters at room temperature, briefly spin before use.
• Prepare the Program 4_TN5AMP (set the lid at 100°C) on the thermocycler (* The exact number of PCR cycles should be determined following Appendix 3):

Library amplification reaction setup
2.6.1. Prepare the PCR amplification reaction as follows:

2.6.2. Pipette up and down 5 times.
2.6.3. Put the tube in the PCR machine and start the Program 4_TN5AMP with the default 15 PCR cycles or follow Appendix 3 to determine the optimal number of amplification cycles. Indexed cDNA library clean-up with SPRI beads
Purify the final cDNA library with SPRI magnetic beads using a 0.7x ratio (35 µL of bead slurry for 50 µL cDNA library).
NOTE: Use pre-warmed beads and vortex them vigorously before pipetting.
2.6.4. Adjust the library volume to 50 µL with NFW.
2.6.5. Add 35 µL of beads and mix by pipetting up and down 10 times.
2.6.6. Incubate for 5 min at room temperature.
2.6.7. Place the tubes on the magnetic stand, wait 5 min, carefully remove, and discard the supernatant.
2.6.8. To wash the beads pipette 200 µL of freshly prepared 80% ethanol into the tube.
2.6.9. Incubate for 30 sec.
2.6.10. Carefully remove the ethanol without touching the beads pellet.
2.6.11. Repeat step 2.6.8 for a total of two washes.
2.6.12. Remove tubes from the magnetic stand and let the beads dry for 1-2 min.
2.6.13. Resuspend the beads in 21 µL of NFW.
2.6.14. Incubate for 1 min.
2.6.15. Place tubes on the magnetic stand, wait 5 minutes, and carefully remove 20 µL of supernatant into a new tube to avoid bead carry-over.
2.6.16. Perform the bead clean-up once again by repeating the procedure from step 2.6.4.
Safe stop: At this step, the cDNA libraries can be safely kept at -20°C for up to a few weeks.
2.7. Library quality control
Pooled library quality control
Before sequencing, the libraries should be subjected to fragment analysis (with Fragment analyzer, Bioanalyzer, or TapeStation) and quantification (with Qubit). This information is required to assess the molarity of the libraries and prepare the appropriate library dilution for sequencing. A successful library contains fragments in the range of 300 – 1000 bp with a peak at 400-700 bp; see Figure 2 for an example of a standard BRB-seq library profile.
Importantly, libraries with primer dimer peaks at 180 bp and ranging at 250 – 290 bp will likely produce lower quality sequencing data with a reduced proportion of mappable reads (Figure 3). Therefore, it is strongly recommended to remove those peaks by performing an additional round of SPRI beads purification with the 0.7x ratio (see step 2.6.4).
Undertagmented libraries have a broader fragment range distribution with a peak at 1000-1200 bp (Figure 4). Only a fraction of such libraries contains fragments that can be efficiently sequenced; therefore, it is recommended to re-tagment the cDNA for the best results.
Library quantification can also be done unbiasedly by qPCR using standard Illumina library quantification kits (i.e., KAPA HiFi, Roche).
Pre-sequencing library QC:

• Use 2 µL of the library to measure the concentration with Qubit.
• Use 2 µL of the library to assess the profile with the Fragment Analyzer instrument or similar.
• If necessary, re-purify the libraries by following steps 2.6.4 – 2.6.15 to remove the peaks <300 bp.

Figure 2 The successful library profile with fragments 300-1000 bp
Figure 3 The example of an overtagmented library profile with a peak at 290 bp and an adapter peak at 160 bp Figure 4 The example of an undertagmented library profile with a major peak > 1000 bp Assessing uniformity of reads distribution across the samples.
For projects involving highly heterogeneous RNA samples, it is recommended to validate the uniformity of reads coverage across the samples by shallow library sequencing (see step 2.2). This approach ensures that every sample will obtain enough reads required for the analysis. BRB-seq libraries can be added as spike-ins to the compatible sequencing run (see Part 3). For this validation 0.5-1M sequencing reads per library is sufficient to assess the fraction of reads attributed to every sample.

Part 3. LIBRARY SEQUENCING

The libraries prepared with MERCURIUSTM Cell Lysate BRB-seq kit carry Illumina-compatible adapter sequences. They are ready to be processed on any Illumina instrument (i.e., HiSeq, NextSeq, MiSeq, iSeq, and NovaSeq).
The MERCURIUSTM Cell Lysate BRB-seq libraries are Dual Indexed and potentially can be pooled in a sequencing run with other libraries if the sequencing structure is compatible (see Table 2).

Read

| Length (cycles)|

Comment

---|---|---
Read1| 25-28| Default is 28. Sample barcode and UMI
i7 index| 8| Library Index
i5 index| 8| Library Index (optional and valid for UDI libraries)
Read2| 60-90| Gene fragment

Table 2 Sequencing structure of BRB-seq libraries
NOTES: Sequencing depth

1. The recommended sequencing depth is 1-5 M reads per sample. Deeper sequencing can also be performed to enable the detection of very low expressed genes.
2. If only one library is sequenced in a flow cell, the Index reads can be skipped.
3. The loading molarity for the library depends on the sequencing instrument (see Table 3) and should be discussed with the sequencing facility or an experienced person.

Table 3 Reference loading concentrations for various Illumina instruments

Part 4. SEQUENCING DATA PROCESSING

Following Illumina sequencing and standard library index demultiplexing, the user obtains raw read1 and read2 fastq sequencing files (e.g., mylibrary_R1.fastq.gz and mylibrary_R2.fastq.gz).
This section explains how to generate ready-for-analysis gene, and UMI read count matrices from raw fastq files.
4.1. OPTION 1: Cloud-based platform for data processing
The users of BRB-seq kits are offered free access to the devoted cloud-based BRB-seq data processing pipeline. This easy-to-use workflow enables the data processing to generate gene and UMI count matrices for the downstream RNA-seq analysis from the raw fastq files. The pipeline also produces a QC report and can be operated by a user without bioinformatics or coding skills.
The pipeline, still in the developer beta testing mode, is accessible via the following link (https://gcw-portalali.genomsys.com/).
Please request credentials to access the pipeline by email at info@alitheagenomics.com
Currently, only the human, mouse, and fly genomes are supported.
4.2. OPTION 2: Manual data processing
To obtain the data read for analysis, the user needs to align the sequencing reads to the genome and perform the gene/UMI read count generation that can be done in parallel with the sample demultiplexing.
The user requires a terminal and a server or powerful computer with an installed set of standard bioinformatic tools for manual data processing.
4.2.1. Required software

• fastQC (version v0.11.7 or greater). Software for QC of fastq or bam files. This software is used to assess the quality of the sequencing reads, such as the number of duplicates, adapter contamination, repetitive sequence contamination, and GC content. The software is freely available from https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. The website also contains informative examples of good and poor quality data.
• STAR (version 2.7.10a). Software for reads alignment on reference genome (Dobin et al., 2013). It can be downloaded from Github (https://github.com/alexdobin/STAR). STAR can only be run on UNIX systems and requires:
• x86-64 compatible processors
• 64-bit Linux or Mac OS X.
• ~30-40Gb of RAM
• FeatureCounts (v.1.6.0 or greater). Software for counting genome-aligned reads for genomic features, such as genes and exons.
• Picard (v.2.17.8 or greater) and Samtools (v.1.9 or greater). Collections of command-line utilities to manipulate with BAM files. Note: Picard requires Java version 8 or higher to be installed.
• R Software (version 3 or greater).
• (Optional) BRBseqTools (version 1.6). The software suite for processing BRB-seq libraries is available from: https://github.com/DeplanckeLab/BRB-seqTools.

4.2.2. Merging fastq files from individual lanes and/or libraries (Optional)
4.2.2.1 Depending on the type of instrument used for sequencing, one or multiple R1/R2 fastq files per library may result from individual lanes of a flow cell. The fastq files from individual lanes should be merged into a single R1.fastq and a single R2.fastq files to simplify the following steps. This is an example of fastq files obtained from HiSeq 4 lane sequencing:

mylibrary_L001_R1.fastq.gz, mylibrary_L002_R1.fastq.gz,mylibrary_L003_R1.fastq.gz, mylibrary_L004_R1.fastq.gz
mylibrary_L001_R2.fastq.gz, mylibrary_L002_R2.fastq.gz, mylibrary_L003_R2.fastq.gz, mylibrary_L004_R2.fastq.gz
4.2.2.2 To merge the fastq files from different lanes use a cat command in a terminal. This will generate two files: mylibrary_R1.fastq.gz and mylibrary_R2.fastq.gz, containing the information of the entire library.
cat mylibrary_L001_R1.fastq.gz mylibrary_L002_R1.fastq.gz mylibrary_L003_R1.fastq.gz mylibrary_L004_R1.fastq.gz > mylibrary_R1.fastq.gz
cat mylibrary_L001_R2.fastq.gz mylibrary_L002_R2.fastq.gz mylibrary_L003_R2.fastq.gz mylibrary_L004_R2.fastq.gz > mylibrary_R2.fastq.gz
4.2.2.3 Move these 2 fastq files in a new folder, which will be referenced in this manual as $fastqfolder.
NOTE: This step can also be done if you sequenced your library in multiple sequencing runs.
Warning: The order of merging files should be kept the same (e.g., L001, L002, L003, L004, not L002, L001 …) to avoid issues when demultiplexing the samples.
4.2.3. Sequencing data quality check
4.2.3.1 Run fastQC on both R1 and R2 fastq files. Use –outdir option to indicate the path to the output directory. This directory will contain HTML reports produced by the software.
fastqc –-outdir $QCdir/ mylibrary_R1.fastq.gz
fastqc –-outdir $QCdir/ mylibrary_R2.fastq.gz
4.2.3.2 Check fastQC reports to assess the quality of the samples (see Software and materials).
NOTES:
• Report for R1 fastq file may contain some “red flags” because it contains barcodes/UMIs. Still, it can provide useful information on the sequencing quality of the barcodes/UMIs.
• The main point of this step is to check the R2 fastq report. Of note, per base sequence content and kmer content are rarely green. If some adapter contamination or overrepresented sequence is detected in the data, it may not be an issue (if the effect is limited to <10~20%). These are lost reads, but most of them will be filtered out during the next step.
4.2.4. Preparing the reference genome
The fastq files must be aligned (or “mapped”) on a reference genome. The STAR (Dobin et al., 20131) aligner is one of the most efficient tools for RNA-seq reads mapping. It contains a “soft-clipping” tool that automatically cuts the beginning or the end of the reads to improve the mapping efficiency, thus allowing the user to skip the step of trimming the reads for adapter contamination. Moreover, STAR has a mode called STARsolo, designed to align multiplexed data (such as BRB-seq) and directly generate count matrices.
The STAR aligner requires a genome assembly together with a genome index file. The index file generation is a time-consuming process that is only performed once on a given genome assembly so that it can be complete in advance and the index files can be  tored on the server for subsequent analyses.
4.2.4.1 Download the right genome assembly fasta file (e.g.
Homo_sapiens.GRCh38.dna.primary_assembly.fa) and gene annotation file in gtf format (e.g. Homo_sapiens.GRCh38.102.gtf) from Ensembl or UCSC repository. Below is an example for a human assembly:
wget ftp:// ftp.ensembl.org/pub/release102/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz
 gzip -d Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz # unzip
wget ftp:// ftp.ensembl.org/pub/release102/gtf/homo_sapiens/Homo_sapiens.GRCh38.102.gtf.gz
gzip -d Homo_sapiens.GRCh38.102.gtf.gz # unzip
1 Alexander Dobin, Carrie A. Davis, Felix Schlesinger, Jorg Drenkow, Chris Zaleski, Sonali Jha, Philippe Batut, Mark Chaisson, Thomas R. Gingeras, STAR: ultrafast universal RNA-seq aligner, Bioinformatics, Volume 29, Issue 1, January 2013, Pages 15–21, https://doi.org/10.1093/bioinformatics/bts635
NOTE: It’s recommended to download the primary_assembly fasta file when possible (without the ‘sm’ or ‘rm’ tags). If not available, download the top_level assembly. For the gtf, download the one that does not have the ‘chr’ or ‘abinitio’ tags.
4.2.4.2 Use STAR to create an index for the genome assembly. Indicate the output folder name containing the index files using –genomeDir option:
STAR –runMode genomeGenerate –genomeDir /path/to/genomeDir -genomeFastaFiles Homo_sapiens.GRCh38.dna.primary_assembly.fa–sjdbGTFfile
Homo_sapiens.GRCh38.102.gtf –runThreadN 8
NOTES:

• The –runThreadN parameter can be modified depending on the number of cores available on your machine. The larger is this number, the more parallelized/fast will be the indexing.
• Depending on the genome assembly, STAR can use up to 32-40Gb of RAM. So, you should use a machine that has this RAM capacity.

4.2.5. Aligning to the reference genome and generation of count matrices
After the genome index is created, both R1 and R2 fastq files can be aligned to this reference genome.
For this step, use the “solo” mode of STAR, which not only aligns the reads to the reference genome but also creates the gene read count and UMI (unique molecular identifier) count matrices.
The following parameters should be adjusted according to the sequencing information:
• –soloCBwhitelist: a text file with the list of barcodes (one barcode sequence per lane) which is used  by STAR for demultiplexing. This file is provided according to version of the MERCURIUS kit used.
Example of “barcodes_96_V5A_star.txt”:

TACGTTATTCCGAA
AACAGGATAACTCC
ACTCAGGCACCTCC
ACGAGCAGATGCAG

• –soloCBstart: Start position of the barcode in the R1 fastq file, equal to

1. • –soloCBlen: Length of the barcode. This value should match the length of the barcode sequence in the file specified by –soloCBwhitelist. The barcode length depends on the version of the oligo-dT barcodes provided in the kit. For the barcodes plate set V5 the default value is 14.
   • –soloUMIstart: Start position of the UMI, it’s soloCBlen + 1 since the UMI starts right after the barcode sequence.
   • –soloUMIlen: The length of UMI. This parameter depends on the version of the oligo-dT barcodes in the kit and number of sequencing cycles performed for the Read1. For barcodes plate set V5 the default value is 14.
   • –readFilesIn: name and path to the input fastq files.
   The order of the fastq files provided in the script is important. The first fastq must contain genomic information, while the second the barcode and UMI content. Thus, files should be provided for STARsolo  in the following order: –readFilesIn mylibray_R2 mylibrary_R1.
   • –genomeDir: a path to the genome indices directory generated before ($genomeDir).
   Output count matrix parameters:
   By default, STARsolo produces UMI count matrix, i.e., containing unique non- duplicated reads per sample for each gene. This type of count data is a standard for single cell RNA-seq analysis. For bulk RNA-seq analysis a gene read count matrix is usually used. Following parameters will enable to generate the output of interest.
   –soloUMIdedup NoDedup, will generate a read count matrix output
   –soloUMIdedup NoDedup 1MM_All, will generate b//oth UMI and read count matrices in mtx format.
   This step will output bam files and count matrices in the folder $bamdir.

   STAR –runMode alignReads –outSAMmapqUnique 60 –runThreadN 8 -outSAMunmapped Within –soloStrand Forward –quantMode GeneCounts — outBAMsortingThreadN 8 –genomeDir $genomeDir –soloType CB_UMI_Simple -soloCBstart 1 –soloCBlen 14 –soloUMIstart 15 –soloUMIlen 14 -soloUMIdedup NoDedup 1MM_All –soloCellFilter None –soloCBwhitelist barcodes.txt –soloBarcodeReadLength 0 –soloFeatures Gene -outSAMattributes NH HI nM AS CR UR CB UB GX GN sS sQ sM — outFilterMultimapNmax 1 –readFilesCommand zcat –outSAMtype BAM SortedByCoordinate –outFileNamePrefix $bamdir –readFilesIn mylibrary_R2.fastq.gz mylibrary_R1.fastq.gz
   The demultiplexing statistics can be found in the “bamdir/Solo.out/Barcodes.stats” file.
   The alignment quality and performance metrics can be found in the “bamdir/Log.final.out” file.
   NOTE: The most important statistic at this step is the proportion of “Uniquely mapped reads” which is expected to be greater than 70% (for human, mouse or drosophila).
   4.2.6. Generating the count matrix from .mtx file
   STARsolo will generate a count matrix (matrix.mtx file) located in the bamdir/Solo.out/Gene/raw folder.
   This file is a sparse matrix format that can be transformed into standard count matrix using an R script provided below:

   Myscript.R

   library(data.table)
   library(Matrix)
   matrix_dir <- “$bamdir/Solo.out/Gene/raw”
   f <- file(paste0(matrix_dir, “matrix.mtx”), “r”)
   mat <- as.data.frame(as.matrix(readMM(f)))
   close(f)
   feature.names = fread(paste0(matrix_dir, “features.tsv”), header = FALSE, stringsAsFactors = FALSE, data.table = F)
   barcode.names = fread(paste0(matrix_dir, “barcodes.tsv”), header = FALSE, stringsAsFactors = FALSE, data.table = F)
   colnames(mat) <- barcode.names$V1
   rownames(mat) <- feature.names$V1
   fwrite(mat, file = umi.counts.txt, sep = “\t”, quote = F, row.names = T, col.names = T)
   The resulting UMI/gene count matrix can be used for a standard expression analysis following conventional bioinformatic tools.
   4.2.7. Demultiplexing bam files (Optional)
   Generation of demultiplexed bam files, i.e., individual bam file for each sample, might be needed in some cases, for example, for submitting the raw data to an online repository that does not accept multiplexed data (for example, GEO or ArrayExpress), or for running an established bulk RNA-seq data analysis pipeline.
   For this purpose, the Picard tool can be used with the following parameters:

• $out_dir, The output dir for demultiplexed bam files
• $path_to_bam, the path to multiplexed single bam file
• $barcode_brb.txt, the tab-delimited file containing 2 columns: sample_id and barcode seq. Example of barcode_96_V5A_brb.txt:

  Sample1 TACGTTATTCCGAA
  Sample2 AACAGGATAACTCC
  Sample3 ACTCAGGCACCTCC
  Sample4 ACGAGCAGATGCAG

NOTE: this file differs from the list of barcodes files provided to STAR.
Run the following Picard script

!/bin/bash

demultiplexed_bam_out_dir=$out_dir
input_bam=$path_to_bam
barcode_info=$barcode_brb.txt

while IFS=$’\t’ read -r -a line
do
sample_id=”${line[0]}”
tag_value=”${line[1]}”

java -jar /path/to/picard.jar FilterSamReads \
I=${input_bam} \
O=${demultiplexed_bam_out_dir}/${sample_id}.bam \
TAG=CR TAG_VALUE=${tag_value} \
FILTER=includeTagValues
done < “$barcode_info”
NOTE: Please contact us at info@alitheagenomics.com in case you don’t have the barcode sequences (in your email, please indicate the name of the barcode set and the PN of the barcode module)
4.2.8. Generating the read count matrix with per-sample stats (Optional)
After splitting (demultiplexing) the bam file into files for each sample, produce a read counting matrix with per-sample statistics using the featureCounts tool with the following code:

!/bin/bash

gtf=homo_sapience.gtf

GTF genome annotation file

output_name=read_counts.txt

Name of the final count

output file
bam_dir=mypath/bam_demult

Directory with demultiplexed bam files

featureCounts [options] -t exon -g gene_id -s 1 -a $gtf -o $output_name ${bam_dir}/*.bam
The resulting read count matrices can be used for subsequent gene expression analysis using established pipelines and tools.

Appendix 1. Assessing the kit performance with inline Control Human RNA

Introduction
Control Human RNA (Ctrl hRNA) is provided in the BRB-seq kits as a positive control to assess the kit’s performance during the library preparation. The tube provided in the kit contains 10 µL of 0.5 µg/µL (5 µg) of human total RNA from HEK293T cells. It can be used at various amounts per well for RT reaction (e.g., at 50 ng/well for 96 wells or 1 µg/well for 5 wells). The section below describes the best practices and the expected results from using 0.5-5 µg of RNA per well and following the detailed protocol in 0 of this User Guide.
Expected results during library preparation
The RT was performed using the reagents from a BRB-seq kit (PN 10811) in 20 µL per well using 0.5-5 µg of total RNA. Each sample was either directly purified using DNA Clean and concentrator kit (Zymo, D4014), or wells were pooled (RT from 5 wells with 1 µg of RNA each) before column purification. After elution, each sample was treated with Exo and subjected to the second strand synthesis. Samples were then purified using AMPure beads (0.6x ratio, Beckman Coulter CNGS-0050) and eluted in 20 µL with water. cDNA was quantified using Qubit and profiled with a Fragment Analyzer (Agilent, model 5200). Figure 5A shows the estimation of cDNA yield, and Figure 5B demonstrates the expected cDNA profile.Figure 5 A. Expected cDNA yield from total human RNA used in a single RT reaction (0.5-5 µg/reaction) or 5 RT reactions with 1 µg/well (n= 4). B. Expected cDNA profile.
Various amounts (5-20 ng) of cDNA prepared from control RNA were used for the library preparation following the tagmentation, purification with AMPure beads (0.6x), PCR amplification, and two rounds of purification with AMPure beads (0.6x). The amount of cDNA for tagmentation can vary, and we recommend keeping some cDNA for a backup. Typically, 10 ng of cDNA is sufficient to obtain 20-40 ng of DNA library after 13-14 cycles of amplification.
Table 4 shows the approximate amount of amplification cycles and expected library yield, and Figure 6 shows the fragment size distribution.

Table 4 Expected yield of BRB-seq libraries from different amount of tagmented cDNA.
The final yield of the library and the profile may vary depending on RNA quality and species of origin as well as on the pipetting manipulations during the purification steps.
Figure 6 BRB-seq library profiles prepared by tagmentation of 5 (black), 10 (blue) or 20 (red) ng of cDNA.

Appendix 2. Unique Dual Indexing adapter sequences

Name| Type| i7 index sequence| i5 index sequence Workflow A| i5 index sequence Workflow B
---|---|---|---|---
MQ.UDI.1| UDI (i7/i5)| TAAGGCGA| AGGCTATA| TATAGCCT
MQ.UDI.2| UDI (i7/i5)| CGTACTAG| GCCTCTAT| ATAGAGGC
MQ.UDI.3| UDI (i7/i5)| AGGCAGAA| AGGATAGG| CCTATCCT
MQ.UDI.4| UDI (i7/i5)| GCGTTGGA| AAGTCCAA| TTGGACTT

Table 5 UDI adapter sequences
Workflow A: NovaSeq 6000, MiSeq, HiSeq 2500, or HiSeq 2000
Workflow B: iSeq 100, MiniSeq, NextSeq, HiSeq X, HiSeq 4000, or HiSeq 3000

Appendix 3. Library quantification with qPCR

To determine the optimal number of cycles, the following library quantification procedure using real-time PCR is recommended at step 2.6.3.

• After purification of the tagmented library, set up the PCR amplification reaction and perform 5 cycles of library preamplification (Program 4_TN5AMP).
• Put the tube on ice.
• Use 5 µL aliquot from the PCR reaction to prepare a qPCR reaction mix in the appropriate PCR tube or plate as follows:

| |
---|---|---
Reagent| Per reaction, µL| N +10%, µL
5 cycles pre-amplified library| 5.0|
SYBR 100X*| 0.1|
LAM| 2.5|
NFW| 2.4|
TOTAL| 10.0|

• Prepare 100X dilution with NFW from 10’000X stock
  • Put it in the qPCR machine and run it with the following program:

Initial denaturation
Denaturation| 98°C
98°C| 1 min10 sec| 25
Annealing
Extension + acquisition| 63°C
72°C| 30 sec
1 min|

• Determine the cycle number depending on the growth curve in the multicomponent plot, as in Figure 7.
• Perform PCR with a determined additional number of cycles with the tube containing the remaining 45 µL of the pre-amplified library.

Figure 7 Determination of the additional number of amplification cycles with qPCR. ![ALITHEA GENOMICS PN 10840 Cell Lysate BRB seq Library Preparation Kit

• Figure 7](https://manuals.plus/wp-content/uploads/2023/10/ALITHEA-GENOMICS- PN-10840-Cell-Lysate-BRB-seq-Library-Preparation-Kit-Figure-7.jpg)

Contact information

Alithea Genomics SA
Route de la Corniche 5
1066 Épalinges
Switzerland
Tel: +41 78 830 31 39
www.alitheagenomics.com
info@alitheagenomics.com
User Guide: Cell Lysate BRB-seq
Library Preparation kit for 24, 96, 384 and 1536 samples
v.0.1.6.revC November 2022
Alithea Genomics
www.alitheagenomics.com

References

• Alithea Genomics | Large-scale RNA sequencing
• Alithea Genomics | Large-scale RNA sequencing
• STAR: ultrafast universal RNA-seq aligner | Bioinformatics | Oxford Academic
• GitHub - alexdobin/STAR: RNA-seq aligner
• GitHub - DeplanckeLab/BRB-seqTools: Suite of tools for processing BRB-seq data
• Babraham Bioinformatics - FastQC A Quality Control tool for High Throughput Sequence Data

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