MERCURIUS™

BRB-seq kits

Massively multiplexed library prep kits for purified RNA - compatible with all eukaryotic cells

Compatible with Illumina®, AVITI™ and MGI*.

*For native kits' compatibility with MGI sequencers, contact us.


Catalog number	#10813	#11013	#10814	#11014
Total preps How many library preps can be prepared in total with one kit	96	384	384	1,536
Sample multiplexing and plate format How many samples can be multiplexed in one single tube	96	96	384	384
Barcoded oligo-dT plates included	1	4	1	4
UDI pairs included How many individual libraries can be sequenced together	4	4	4	4
Documentation	User guide Barcode files

Cat ##10813
Total reactions How many library preps can be prepared in total with one kit	96
RNA multiplexing format How many library preps can be prepared in total with one kit	96
UDI pairs included How many library preps can be prepared in total with one kit	4
Download Manual

Cat ##11013
Total reactions How many library preps can be prepared in total with one kit	384
RNA multiplexing format How many library preps can be prepared in total with one kit	96
UDI pairs included How many library preps can be prepared in total with one kit	4
Download Manual

Cat ##10814
Total reactions How many library preps can be prepared in total with one kit	384
RNA multiplexing format How many library preps can be prepared in total with one kit	384
UDI pairs included How many library preps can be prepared in total with one kit	4
Download Manual

Cat ##11014
Total reactions How many library preps can be prepared in total with one kit
RNA multiplexing format How many library preps can be prepared in total with one kit	384
UDI pairs included How many library preps can be prepared in total with one kit	4
Download Manual

Benefits

The MERCURIUS™ BRB-seq library preparation kits for Illumina® and AVITI™ contain all the oligos and enzymes needed to go from purified RNA to sequencing-ready libraries.

Scalable bulk RNA sequencing: Perform up to 384 RNA-seq library preparations in a single tube. High quality, high cost-effectiveness.

BRB-seq as a flexible solution: For projects of all sizes: from 96 to 1'536 reactions in a single kit.
All-inclusive.

One-day lab workflow: Convenient and short protocol from samples to sequencing-ready libraries in one day.

Experimental workflow at a glance
Performance
Product specifications
Citations

BRB-seq-4-1

1. Uniform detection of 12'000+ genes at 1 million reads per sample across 384 samples

Distribution of the number of detected genes across 384 samples prepared with the MERCURIUS™ BRB-seq library preparation kit. The library was sequenced at an average of 1 million reads

2. Comparison of library complexity between BRB-seq and TruSeq at a comparable sequencing depth

Detected genes (left) and differentially expressed genes (right) obtained on the same samples with BRB-seq and TruSeq. At comparable sequencing depth, the performance of BRB-seq data is comparable with TruSeq libraries.

3. Benchmarking the performance of BRB-seq for DE genes at 3M reads/sample with other commercial platforms

Number of detected genes for the non-differentiated (ND) and differentiated (D) Adipose Stromal Population Cells between BRB-seq and two other commercial kits. The expressed genes are split into three categories: Lowly Expressed (left, 0 < CPM < 10), Mid expressed (middle, 10 < CPM < 100), and Highly expressed (right, CPM > 100). To note: all replicates were prepared from the same RNA sample and the sequencing depth was 3M reads/sample.

4. Benchmarking the performance for library prep between BRB-seq and two other commercial kits

Genome-wide Pearson correlation of mapped reads for the non-differentiated (ND) and differentiated (D) Adipose Stromal Population Cells between BRB-seq and two other commercial kits. A high correlation was observed both within technical replicates and across different library prep kits.

5. 4000+ DE genes with 3M reads/sample at FDR 0.5

Picture2-Nov-24-2023-01-53-09-6256-PM

Number of differentially expressed genes across three commercial platforms, including BRB-seq, at different FDR cutoff values. To note: all replicates were prepared from the same RNA sample and the sequencing depth was 3M reads/sample.

For (application)	3' mRNA sequencing
For use with (equipment)	Illumina and AVITI NGS instruments
Species compatibility	All eukaryotic species
Available formats	96, 384 and 1'536 preps
Shipping conditions	Dry ice
Storage conditions	-20C

Please visit the dedicated page for a complete list.

Sofa Pavlou, Stefanie Foskolou, Nikolaos Patikas, Sarah F. Field, Evangelia K. Papachristou, Clive D’ Santos, Abigail R. Edwards, Kamal Kishore, Rizwan Ansari, Sandeep S. Rajan, Hugo J. R. Fernandes, Emmanouil Metzakopian. 2023. CRISPR‑Cas9 genetic screen leads to the discovery of L‑Moses, a KAT2B inhibitor that attenuates Tunicamycin‑mediated neuronal cell death. Scientific Reports, 13:3934. https://www.nature.com/articles/s41598-023-31141-6
Christian, W. T., Tiphaine, O.-M., Nava, E., Christian, H., Federico, A. S., Jonathan, N., Dominique, C., Cécile, G., Laurence, M., Sophia, S. W., Shehnaz, K. H., Ioannis, T., Matthias, C., Andri, R., Manuel, B., Matthias, H., Patrick, S., Enos, B., Huldrych, F. G., Pejman, M., Paul, J. M., Charles, S. R., Caroline, B., & Jacques, F. 2020. Genetic variation near CXCL12 is associated with susceptibility to HIV-related non-Hodgkin lymphoma. Haematologica, 106(8): 2233-2241. https://haematologica.org/article/view/9813
Lalli, M., Yen, A., Thopte, U., Dong, F., Moudgil, A., Chen, X., Milbrandt, J., Dougherty, Joseph D., & Mitra, Robi D. 2022. Measuring transcription factor binding and gene expression using barcoded self-reporting transposon calling cards and transcriptomes. NAR Genomics and Bioinformatics, 4(3). https://academic.oup.com/nargab/article/4/3/lqac061/6679408
Li, Y., Schwalie, P. C., Bast-Habersbrunner, A., Mocek, S., Russeil, J., Fromme, T., Deplancke, B., & Klingenspor, M. 2019. Systems-Genetics-Based Inference of a Core Regulatory Network Underlying White Fat Browning. Cell Reports, 29(12): 4099-4113.e4095. https://doi.org/10.1016/j.celrep.2019.11.053
Litovchenko, M., Meireles-Filho, A. C. A., Frochaux, M. V., Bevers, R. P. J., Prunotto, A., Anduaga, A. M., Hollis, B., Gardeux, V., Braman, V. S., Russeil, J. M. C., Kadener, S., dal Peraro, M., & Deplancke, B. 2021. Extensive tissue-specific expression variation and novel regulators underlying circadian behavior. Science Advances, 7(5): eabc3781. https://doi.org/10.1126/sciadv.abc3781

1. Uniform detection of 12'000+ genes at 1 million reads per sample across 384 samples

Distribution of the number of detected genes across 384 samples prepared with the MERCURIUS™ BRB-seq library preparation kit. The library was sequenced at an average of 1 million reads

2. Comparison of library complexity between BRB-seq and TruSeq at a comparable sequencing depth

Detected genes (left) and differentially expressed genes (right) obtained on the same samples with BRB-seq and TruSeq. At comparable sequencing depth, the performance of BRB-seq data is comparable with TruSeq libraries.

3. Benchmarking the performance of BRB-seq for DE genes at 3M reads/sample with other commercial platforms

Number of detected genes for the non-differentiated (ND) and differentiated (D) Adipose Stromal Population Cells between BRB-seq and two other commercial kits. The expressed genes are split into three categories: Lowly Expressed (left, 0 < CPM < 10), Mid expressed (middle, 10 < CPM < 100), and Highly expressed (right, CPM > 100). To note: all replicates were prepared from the same RNA sample and the sequencing depth was 3M reads/sample.

4. Benchmarking the performance for library prep between BRB-seq and two other commercial kits

Genome-wide Pearson correlation of mapped reads for the non-differentiated (ND) and differentiated (D) Adipose Stromal Population Cells between BRB-seq and two other commercial kits. A high correlation was observed both within technical replicates and across different library prep kits.

5. 4000+ DE genes with 3M reads/sample at FDR 0.5

Number of differentially expressed genes across three commercial platforms, including BRB-seq, at different FDR cutoff values. To note: all replicates were prepared from the same RNA sample and the sequencing depth was 3M reads/sample.

Product specifications

Please visit the dedicated page for a complete list.
- Sofa Pavlou, Stefanie Foskolou, Nikolaos Patikas, Sarah F. Field, Evangelia K. Papachristou, Clive D’ Santos, Abigail R. Edwards, Kamal Kishore, Rizwan Ansari, Sandeep S. Rajan, Hugo J. R. Fernandes, Emmanouil Metzakopian. 2023. CRISPR‑Cas9 genetic screen leads to the discovery of L‑Moses, a KAT2B inhibitor that attenuates Tunicamycin‑mediated neuronal cell death. Scientific Reports, 13:3934. https://www.nature.com/articles/s41598-023-31141-6
- Christian, W. T., Tiphaine, O.-M., Nava, E., Christian, H., Federico, A. S., Jonathan, N., Dominique, C., Cécile, G., Laurence, M., Sophia, S. W., Shehnaz, K. H., Ioannis, T., Matthias, C., Andri, R., Manuel, B., Matthias, H., Patrick, S., Enos, B., Huldrych, F. G., Pejman, M., Paul, J. M., Charles, S. R., Caroline, B., & Jacques, F. 2020. Genetic variation near CXCL12 is associated with susceptibility to HIV-related non-Hodgkin lymphoma. Haematologica, 106(8): 2233-2241. https://haematologica.org/article/view/9813
- Lalli, M., Yen, A., Thopte, U., Dong, F., Moudgil, A., Chen, X., Milbrandt, J., Dougherty, Joseph D., & Mitra, Robi D. 2022. Measuring transcription factor binding and gene expression using barcoded self-reporting transposon calling cards and transcriptomes. NAR Genomics and Bioinformatics, 4(3). https://academic.oup.com/nargab/article/4/3/lqac061/6679408
- Li, Y., Schwalie, P. C., Bast-Habersbrunner, A., Mocek, S., Russeil, J., Fromme, T., Deplancke, B., & Klingenspor, M. 2019. Systems-Genetics-Based Inference of a Core Regulatory Network Underlying White Fat Browning. Cell Reports, 29(12): 4099-4113.e4095. https://doi.org/10.1016/j.celrep.2019.11.053
- Litovchenko, M., Meireles-Filho, A. C. A., Frochaux, M. V., Bevers, R. P. J., Prunotto, A., Anduaga, A. M., Hollis, B., Gardeux, V., Braman, V. S., Russeil, J. M. C., Kadener, S., dal Peraro, M., & Deplancke, B. 2021. Extensive tissue-specific expression variation and novel regulators underlying circadian behavior. Science Advances, 7(5): eabc3781. https://doi.org/10.1126/sciadv.abc3781