BRB-seq

[4] BRB-seq builds upon technological advances in single-cell transcriptomics, where sample barcoding made the early multiplexing of hundreds to thousands of single cells possible.

Each barcoded nucleotide sequence includes an adaptor for primer annealing, a 14-nt long barcode that assigns a unique identifier to each individual RNA sample, and a random 14-nt long UMI that tags each mRNA molecule with a unique sequence to distinguish between original mRNA transcripts and duplicates that result from PCR amplification bias.

BRB-seq allows up to 384 individually barcoded RNA samples to be pooled into one tube early in the workflow to streamline subsequent steps in cDNA library preparation and sequencing.

Next, these full-length cDNA molecules undergo a process called tagmentation facilitated byTn5 transposase preloaded with adaptors necessary for library amplification.

Higher library complexity occurs when using around 20 ng of cDNA per sample for tagmentation, meaning fewer PCR amplification cycles are required.

Artificial intelligence requires vast amounts of training data to reach robust and reliable conclusions about a drug's on- or off-target biological effects and their toxicogenomic profiles.

BRB-seq is a cost-effective and time-efficient sequencing technology that allows pharmaceutical companies to extract more transcriptomic data at a lower cost to investigate the pharmacological effects of thousands of molecules on cells of interest simultaneously and at scale.

[9] BRB-seq has been used to discover a new type of cell that inhibits the formation of fat in humans, with the potential to improve treatments for obesity and type 2 diabetes,[10] to determine the expression of immune genes activated by SARS-CoV-2 at different temperatures in human airway cells[11] and to discover genes that are turned on or off at different times of the day in the fruit fly[12] Researchers also used Plant BRB-seq in agritranscriptomics to investigate the transcriptomic response of maize to nitrogen fertilizers.