Three New High-Throughput Transcriptomic Technologies for Drug Discovery

DRUG-seq, Combi-seq, and BRB-seq are three novel high-throughput transcriptomic technologies accelerating drug discovery in more disease areas than ever before. They provide unbiased, comprehensive gene expression data after treatment with large compound libraries, under multiple experimental conditions, at significantly lower costs than traditional RNA-seq methods.

High-throughput screening of compounds previously relied on singular readouts such as reporter gene expression. Novel techniques, where the whole transcriptome is measured, now allow deeper interrogation of complex changes in response to drug treatments.

In this article, we discuss recent examples of how high-throughput transcriptomic techniques such as DRUG-seq, Combi-seq, and BRB-seq are used to drive drug discovery.

DRUG-seq used for schizophrenia drug validation

Researchers used the RNA-seq based method Digital RNA with peRturbation of Genes (DRUG-seq) in a drug discovery project to develop compounds for schizophrenia (Ye et al., 2018; Li et al., 2022). DRUG-seq relies on barcodes added to the 3’ of mRNA which allows samples to be pooled and processed together, significantly reducing cost and hands-on-time.

In their recent study, Li et al. (2022) used DRUG-seq on human stem cell-derived neurons treated with NMDA receptor potentiators and zinc chelators. They detected on-target NMDA receptor activity signatures from two compounds, but also discovered some unforeseen off-target effects.

DRUG-seq helped gain a deeper picture of the complexities of compound treatment on human cells compared to singular gene readouts.

A comprehensive understanding of the transcriptomic on- and off-target effects of compound treatment may be critical in the decision-making processes in an industrial setting, and could save time and money.

Combi-seq used to assess drug combinations in oncology

Combi-seq uses a microfluidic-based barcoding strategy to generate transcriptomic data from cells treated with hundreds of combinations of compounds, which reduces cost and material required (Mathur et al., 2022).

The researchers used Combi-seq to generate transcriptomic profiles of human kidney cancer cells treated with 420 different combinations of drugs. The study found drug combinations with antagonistic effects, and others with synergistic effects which resulted in increased induction of apoptosis.

The cost-effectiveness of this strategy in an industrial setting would allow for streamlined, large combinatorial drug screening pipelines.

BRB-seq for compound toxicity screening in human mini-brains

Bulk RNA Barcoding and sequencing (BRB-seq) is similar to DRUG-seq as it adds a unique barcode to the 3’ end of mRNA (Alpern et al., 2018). This allows hundreds of samples and experimental conditions to be multiplexed and processed simultaneously, significantly reducing cost and hands-on-time.

In a recent pre-print, Subashika et al. (2022) used BRB-seq to screen the neurotoxicity of a fungicide and plastic stabilizer called trimethyltin chloride (TMT) in a human ‘mini-brain’ model.

The transcriptomic profiles from BRB-seq allowed the researchers to map biological events that dynamically occur across exposure doses and timepoints. Mini-brains treated with high doses of TMT displayed more gene expression changes compared to milder doses, with major effects on genes associated with neuron and synapse function.

This study highlights the versatility of BRB-seq for different cellular models such as organoids. Alithea Genomics has also optimized a BRB-seq protocol for blood cells, with the inclusion of globin blockers.

BRB-seq generates cost- and time-efficient, whole transcriptome data for hundreds of samples treated with drug compounds or different experimental conditions. It also provides accurate, sensitive data for small numbers of cells and poor-quality RNA; both key concerns for human samples (Alpern et al., 2018).

Future perspectives on high-throughput transcriptomics for drug discovery

Overall, novel high-throughput transcriptomic methods now drive drug discovery in many areas, with promising results. Their use provides more information about the biological effects of compound treatment on diverse human cell types and disease models.

The vast quantity of transcriptomic information about the effects of a compound could inform critical decision points in industrial high-throughput screening environments and accelerate the drug discovery pipeline.

Please contact us at to find out more about how BRB-seq could help in your high-throughput drug discovery study.



  • Alpern, D., Gardeux, V., Russeil, J., Mangeat, B., Meireles-Filho, A.C., Breysse, R., Hacker, D. and Deplancke, B., 2019. BRB-seq: ultra-affordable high-throughput transcriptomics enabled by bulk RNA barcoding and sequencing. Genome biology, 20(1), pp.1-15.
  • Li, J., Ho, D.J., Henault, M., Yang, C., Neri, M., Ge, R., Renner, S., Mansur, L., Lindeman, A., Kelly, B. and Tumkaya, T., 2022. DRUG-seq Provides Unbiased Biological Activity Readouts for Neuroscience Drug Discovery. ACS Chemical Biology. 17(6), pp.1401-1414.
  • Mathur, L., Szalai, B., Du, N.H., Utharala, R., Ballinger, M., Landry, J.J.M., Ryckelynck, M., Benes, V., Saez-Rodriguez, J. and Merten, C.A., 2022. Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets. Nature communications, 13(1), pp.1-15.
  • Subashika, G., Daniel, A., Stoppini, L., Deplancke, B. and Adrien, R., 2022. Neuro-toxicogenomic mapping of TMT induced neurotoxicity using human minibrain reveals associated adverse outcome events. bioRxiv.
  • Ye, C., Ho, D.J., Neri, M., Yang, C., Kulkarni, T., Randhawa, R., Henault, M., Mostacci, N., Farmer, P., Renner, S. and Ihry, R., 2018. DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery. Nature communications, 9(1), pp.1-9.


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