Low-cost, low-input RNA-seq protocols perform nearly as well as high-input protocols.

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• RNA sequencing (RNA-seq) has been extended to the single-cell level.
• Concerns exist regarding potential biases introduced by low-input sample handling in single-cell RNA sequencing (scRNA-seq).
• Existing data analysis approaches may be invalidated by these potential biases.

Purpose of the Study:

• To critically evaluate several low-volume RNA-seq protocols.
• To assess the validity of existing data analysis approaches for scRNA-seq data.
• To explore cost-reduction modifications for library preparation.

Main Methods:

• Performed a critical evaluation of multiple low-volume RNA-seq protocols.
• Assessed per-gene linearity of response for each protocol.
• Investigated a modification to a specific protocol to reduce library preparation costs.

Main Results:

• Low-volume RNA-seq protocols require significantly less input sample (at least two orders of magnitude).
• Protocols showed slightly reduced performance in per-gene linearity of response compared to standard methods.
• A protocol modification reduced library preparation costs to approximately $20 per sample.

Conclusions:

• Low-volume RNA-seq protocols are a viable option for applications requiring minimal sample input.
• While minor linearity biases exist, the reduced sample requirement is a significant advantage.
• Cost-effective modifications make scRNA-seq more accessible.