Researchers Published Novel BenchDrop-seq Workflow

The study validated a microfluidics-free RNA sequencing method using long and short-read data from healthy human blood cells.

Updated on Oct. 1, 2026 in Life Sciences

Isometric editorial illustration of a glass petri dish with a droplet and a pipette, representing a microfluidics-free RNA sequencing workflow. — Researchers have released the BenchDrop-seq workflow, a new microfluidics-free method for RNA sequencing that analyzes blood cells using long and short-read data. AI Illustration. Upload story photo >

Scientists have released raw sequence reads from a new BenchDrop-seq workflow that eliminates the need for microfluidic instruments. The research provides a comparative analysis of long-read and short-read RNA sequencing data derived from healthy donor blood cells.

Why it matters

This study aims to determine whether microfluidics-free capture technology can effectively quantify gene expression and resolve complex transcript isoforms. The methodology offers a potential alternative for researchers seeking to bypass traditional microfluidic constraints in single-cell sequencing.

The study utilized PBMCs isolated via density gradient and partitioned with PIPseq T20 3' v4.0 PLUS technology. Sequencing was performed across Illumina NextSeq 2000 and Oxford Nanopore PromethION platforms to recover transcript identities.

The players

Wistar Institute

An independent biomedical research organization based in Philadelphia that facilitated the collection of blood samples for the study.

The details

The workflow utilizes a non-microfluidic approach to partition samples and sequence barcoded full-length cDNA. Researchers employed the Bagpiper pipeline to successfully recover cell barcodes and transcript identities from the resulting long-read libraries.

Raw sequence data became publicly available via dbGaP on October 1, 2026.

The Big Picture

This research follows established data sharing protocols set by the GEO series GSE318099 data repository. By contributing processed count matrices, the project extends existing open-science standards for genomic sequencing datasets.

This development could eventually lead to more accessible or cost-effective genomic sequencing tools that do not rely on expensive microfluidic equipment. Researchers and diagnostic labs may find this method lowers the barrier to performing high-resolution transcriptomic analysis.

The takeaway

The BenchDrop-seq workflow demonstrates that high-quality RNA sequencing is achievable without relying on traditional microfluidic partitioning instruments. This methodological shift highlights a growing trend toward simplifying complex laboratory workflows in genomic research.