RNA sequencing (RNA-seq) has become a go-to method for exploring how genes are expressed across different biological conditions. It plays a vital role in cancer research, immunology, neuroscience, and developmental biology. However, traditional RNA-seq workflows typically require a time-consuming and delicate step—extracting RNA from cells or tissues before library preparation. This step can introduce sample loss, variability, and increased cost, especially when dealing with large numbers of samples or fragile inputs.

A team of researchers at the Walter and Eliza Hall Institute of Medical Research has introduced a new method called TIRE-seq (Turbocapture Integrated RNA Expression Sequencing), designed to streamline RNA sequencing workflows. TIRE-seq simplifies the process by removing the need for separate RNA extraction. Instead, it integrates mRNA purification directly into the library prep process. That means researchers can start from crude cell lysates—essentially a broken-up cell mix—without the need to isolate RNA first.

What does this mean in practice? For starters, shorter turnaround times, fewer handling steps, and reduced risk of sample loss—all of which translate to more reliable data and lower costs. When the team compared TIRE-seq to a popular existing method called Prime-seq, they found that TIRE-seq provided better sequencing efficiency, especially with unprocessed samples.

The researchers tested TIRE-seq in three different biological applications:

1. Human T Cell Activation – TIRE-seq captured gene expression changes associated with immune cell stimulation, highlighting how T cells ramp up gene activity in response to a trigger.

2. Mouse Dendritic Cell Differentiation – It revealed important genes involved in the process by which precursor cells become specialized immune cells.

3. Brain Tumor Drug Response – Using patient-derived neurospheres (a model for glioblastoma), the team tracked how gene expression shifted in response to varying doses and exposure times of the chemotherapy drug temozolomide.

Across all these tests, TIRE-seq not only produced high-quality data but also consistently identified genes and pathways relevant to each biological context.

TIRE-seq outperforms Prime-seq on cell lysates

(a) Overview of the TIRE-seq workflow. Cells are lysed directly in media and transferred to Qiagen TurboCapture plates. mRNA hybridizes to immobilized poly-T oligos, followed by washing and reverse transcription. After well barcoding, samples are pooled, and library preparation occurs on the pooled material. Gene expression is quantified using 5’ tag sequencing. (b) Read mapping statistics for Prime-seq, TIRE-seq, and TruSeq (GSE122633). “Intact cells” refers to FACS-sorted cells. “Lysate” refers to crude homogenized lysates, and “Purified RNA” refers to RNA purified using silica columns. (c) Downsampling analysis of 11 ng Universal Human Reference RNA (UHRR). Janjic = E-MTAB-10139, TruSeq = GSE47774. Top: Median number of genes detected. Bottom: Median number of unique molecules (UMIs) detected. Error bars represent the median absolute deviation of replicates. (d) Performance of TIRE-seq on 10,000 cell equivalents from HEK293T cell lysates. TruSeq = GSE122633. (e) Pearson correlation of logCPM for UHRR replicates across protocols. (g) Binned transcript coverage across protocols. ShortRead = Illumina 70-nt tag sequencing. LongRead = Oxford Nanopore sequencing of full-length Prime-seq cDNA.

In short, TIRE-seq offers a powerful, user-friendly alternative to conventional RNA-seq protocols. It opens the door for more labs—especially those handling high-throughput or difficult samples—to generate meaningful gene expression data faster and with fewer technical barriers.