RNA Sequencing

Delivering reliable results in as fast as 3 days

RNA-Seq is a powerful and widely used technique for capturing and sequencing RNA transcripts in a sample. It enables the study of gene expression, identification of novel transcripts, splicing variants, and non-coding RNAs.

Our RNA-Seq Solutions

mRNA-Seq

mRNA-seq enriches for polyadenylated RNA molecules, capturing protein-coding messenger RNA while minimizing ribosomal RNA background. This approach provides a focused and efficient view of gene expression and is the most widely used RNA-seq method for studying transcript-level changes across biological conditions.

Sample Requirements

Recommended Quantity: 1 µg (200 ng minimum)
Recommended Concentration: >10 ng/µL
Recommended Volume: >20 µL
Quality: RIN > 7
Buffer: RNase-free water
Shipment: Ship frozen on dry ice

Gene Expression

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Biomarker Discovery

Drug Response

Pathway Analysis

Total RNA-Seq

Total RNA-seq removes ribosomal RNA (rRNA) while retaining both polyadenylated and non-polyadenylated transcripts, enabling a more comprehensive view of the transcriptome. This approach captures protein-coding genes as well as long non-coding RNAs and other regulatory RNA species, making it well suited for studies that require broader transcript coverage or involve degraded or challenging samples.

Sample Requirements

Recommended Quantity: 1 µg (200 ng minimum)
Recommended Concentration: >50 ng/µL
Recommended Volume: >20 µL
Quality: RIN > 7
Buffer: RNase-free water
Shipment: Ship frozen on dry ice

Non-Coding RNA

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Prokaryotic Studies

FFPE Samples

Whole Transcriptome

Low-Input RNA-Seq

Low-input RNA-seq is optimized for samples with limited RNA quantities, enabling reliable gene expression profiling from scarce or precious material. By using highly sensitive library preparation methods, this approach maintains data quality and reproducibility while supporting studies involving rare cell populations, small tissue sections, or clinically constrained samples.

Sample Requirements

Please email us and our sequencing team will advise you on the best approach for your project.

Rare Cell Populations

Low-Yield Samples

LCM Samples

Early-Stage Embryos

Small RNA-Seq (smRNA-Seq)

Small RNA-Seq (smRNA-Seq) is designed to capture and sequence short regulatory RNA molecules, including microRNAs and other small RNAs. This approach enables sensitive and accurate profiling of miRNA expression, supporting studies of gene regulation, biomarker discovery, and disease-associated regulatory pathways.

Sample Requirements

Recommended Quantity: 1 µg (200 ng minimum)
Recommended Concentration: >10 ng/µL
Recommended Volume: >20 µL
Quality: RIN > 7
Buffer: RNase-free water
Shipment: Ship frozen on dry ice

miRNA Expression

Biomarker Discovery

Regulatory Network

Developmental Biology

Single-Cell RNA-Seq

Single-cell RNA-seq (scRNA-seq) profiles gene expression at the level of individual cells, enabling high-resolution analysis of cellular heterogeneity within complex samples. This approach reveals distinct cell populations, rare cell types, and dynamic cell states that are not detectable with bulk RNA-seq, making it a powerful tool for studying development, immune responses, and tumor microenvironments.

Sample Requirements

Please email us and our sequencing team will advise you on the best approach for your project.

High Throughput RNA-Seq

High-throughput RNA-seq, including approaches such as BRB-seq and DRUG-seq, is designed for studies that require gene expression profiling across large numbers of samples in a cost- and time-efficient manner. By using early barcoding and streamlined library preparation, these methods enable scalable transcriptomic analysis for screening, perturbation, and large cohort studies while maintaining robust quantitative performance.

Drug Screening

Large Cohort Studies

Toxicology Research

Functional Genomics

Metatranscriptomics

Metatranscriptomic RNA-seq profiles actively expressed RNA from complex microbial communities by sequencing total RNA after ribosomal RNA (rRNA) depletion. This approach reveals functional gene activity across diverse microorganisms, enabling insights into community-level metabolism, host–microbe interactions, and dynamic responses to environmental or experimental perturbations.

Sample Requirements