mRNA-sequencing (mRNA-seq)
Uncover a complete view of gene activity from expressed transcripts
Turnaround for Library Preparation & Sequencing
10-15 days
US Operations
100%
Working with challenging samples
>10 years
What is mRNA-sequencing (mRNA-seq)?
The Technology
Messenger RNA sequencing (mRNA-seq) is a specialized form of RNA sequencing method that focuses on analyzing messenger RNA (mRNA) - the molecules that carry genetic instructions from DNA to ribosomes for protein production.
By sequencing these RNA molecules, researchers can capture a snapshot of which genes are actively expressed in a given sample, and to an extent, generating detailed gene expression profiles across different cell types and conditions
A typical mRNA-seq workflow starts with RNA extraction from RNA samples, followed by isolating mature mRNA transcripts - often through poly(A) selection, which enriches for mature polyadenylated mRNA transcripts while removing most ribosomal RNA and many non-polyadenylated RNA species. The purified RNA is then converted into complementary DNA (cDNA) and built into an RNA seq library.
Using next-generation sequencing (NGS) platforms, these libraries are converted into sequenced reads, with read length varying by platform and experimental design. Short-read platforms deliver highly cost-effective, high-throughput data for standard gene expression profiling, while long-read sequencing offers a complementary option when full-length transcript resolution is the priority. Downstream read alignment and bioinformatics analysis is then used to quantify gene expression levels, detect alternative splicing events, and identify novel or aberrant transcripts.
Because it captures a complete view of cellular activity, mRNA-seq provides valuable insights into cellular activity and regulation, making it a widely used RNA sequencing analysis approaches for comparing healthy versus diseased states, studying developmental processes, evaluating responses to treatments, and discovering potential biomarkers.
At Admera Health, we offer end-to-end mRNA-seq services, from RNA extraction and library preparation and high-throughput sequencing to advanced mRNA-seq analysis, helping researchers generate high-quality, reliable gene expression data for a wide range of applications.
FIND THE RIGHT SOLUTION FOR YOUR RESEARCH
mRNA-Seq vs. Other RNA Sequencing Methods
Choosing the right RNA sequencing method depends on your research question. mRNA-seq focuses specifically on polyadenylated, protein-coding transcripts, making it the most cost-effective option when your goal is gene expression profiling of the coding transcriptome.
mRNA-seq: Best for gene expression profiling, novel isoform discovery, and biomarker studies. Short-read mRNA-seq can identify alternative splicing and infer isoforms, but full-length isoform discovery is much better accomplished using long-read approaches such as PacBio Iso-Seq.
Total RNA-seq: Captures the full transcriptome - including rRNA-depleted coding and non-coding RNA (lncRNA, circRNA) - best when non-coding regulatory RNA is relevant to your study or when working with degraded samples like FFPE.
Small RNA-seq: Specifically enriches for microRNAs (miRNAs), piRNAs, tRNA fragments, and other short regulatory RNA species, used for a different layer of gene regulation entirely.
If you're unsure which approach fits your experimental design, our scientists can help you choose during a free project consultation.
| Method | What it captures | Best for | Notes |
|---|---|---|---|
| mRNA-seq | Polyadenylated, protein-coding transcripts | Gene expression profiling, novel isoform discovery, biomarker studies | Most cost-effective; short-read can infer splicing, but full-length isoforms need long-read (e.g. PacBio Iso-Seq) |
| Total RNA-seq | Full transcriptome: rRNA-depleted coding + non-coding RNA (lncRNA, circRNA) | Studies involving non-coding regulatory RNA | Also best choice for degraded samples, e.g. FFPE |
| Small RNA-seq | miRNAs, piRNAs, tRNA fragments, other short regulatory RNAs | Studying a distinct layer of gene regulation | Enriches specifically for short RNA species |
Did you know?
Admera Health has over 10 years specifically working with challenging samples for RNA-seq workflows which has propelled countless studies forward.
From FFPE tissue to low-input and rare sample types, our optimized RNA extraction protocols are built to handle difficult starting material without compromising library or data quality.
WHY CHOOSE US
Admera Health’s combines deep RNA expertise, CAP-accredited quality systems, and scientist-led support to take your project from sample to publication-ready insight.
CLIA-Certified, CAP-Accredited Quality
Our lab operates under CLIA/CAP standards with quality-assurance-verified SOPs at every processing stage, so your mRNA-seq data holds up to peer-review scrutiny.
Rigorous, Multi-Layer Data QC
We use Unique Dual Indexes (UDIs) to minimize index hopping and Unique Molecular Identifiers (UMIs) to correct for PCR duplicates, with stringent quality control checks throughout library preparation and sequencing to guarantee data quality.
Scientist-to-Scientist Support
Our team of PhD-level scientists is embedded in your project from experimental design through analysis - not just processing samples but helping you reach a meaningful scientific outcome.
Flexible for Challenging Sample Types
From FFPE tissue to low-input and rare sample types, our optimized RNA extraction protocols are built to handle difficult starting material without compromising library or data quality.
Platform Flexibility & Scalability
Choose from Illumina, PacBio, and other sequencing platforms, and workflows ranging from standard mRNA-seq to high-throughput, cost-effective options like 3' Tag-seq, DRUG-seq, and BRB-seq for large-scale studies. For studies requiring full-length isoform resolution rather than short-read inference, long-read RNA sequencing on the PacBio Revio platform captures complete transcripts end-to-end, without assembly.
Fast, Reliable Turnaround
Standard turnaround is typically 10–15 business days, with expedited options available so your gene expression data keeps pace with your research timeline.
Publication-Ready, Every Time
Every sample and every run follow quality-assurance-verified SOPs, delivering consistent, reliable results your team can publish and defend with confidence.
Why Researchers Choose Admera Every Single Time
WORKFLOW
Our mRNA-Seq Workflow
Admera Health's mRNA-seq workflow is designed for consistency and data quality at every stage, from RNA extraction to final analysis.
1. RNA Extraction & QC
2. Library Preparation
3. Sequencing
4. Bioinformatics & Data Analysis
What types of analysis to expect with Admera
Standard Deliverables
Raw data as FASTQ files
Quality control report
Trimming & read alignment
Counting & normalization
Differential Gene Expression (DE) Analysis & Visualization
Functional enrichment analysis
Available upon request
Differential Alternative Splicing Analysis
Skipped exon (SE) events
Alternative 5' splice site (A5SS) events
Alternative 3' splice site (A3SS) events
Mutually exclusive exons (MXE) events
Retained intron (RI) events
GETTING STARTED
Frequently asked questions
We offer a range of solutions designed to meet your needs—whether you're just getting started or scaling something bigger.
Everything is tailored to help you move forward with clarity and confidence.
Sample Preparation & Requirements
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We accept a wide variety of sample types, including FFPE, fresh frozen tissue, blood, cell pellets, and purified RNA. For purified RNA, we require a minimum concentration of 50 ng/µL in a total volume of 50 µL. We recommend providing a higher input amount for low-abundance transcripts. Please submit a completed sample submission form with your shipment.
See Sample Submission Guidelines here. -
If your sample does not meet our quality control standards at any point in the workflow, we will contact you immediately. We will discuss the specific failure point and provide options, which may include re-submitting the sample, proceeding with a modified workflow, or canceling the project. We believe in transparency and working with you to achieve the best possible outcome.
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Our workflows are designed to maximize data quality from start to finish. We use specialized protocols for challenging samples like FFPE to ensure high-quality RNA extraction. During library preparation, we use Unique Dual Indexes (UDIs) to minimize index hopping and Unique Molecular Identifiers (UMIs) to correct for PCR duplicates, ensuring accurate quantification. We also perform stringent quality control checks at every step to guarantee reliable and usable data.
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Admera Health offers flexible input requirements, including low-input and FFPE samples, down to ultra-low input — near single-cell levels. Lab operations are CLIA-certified/CAP-accredited, and PhD-level bioinformatics support is included with every project.
Submitting Samples? Get The Guide
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The "best" service depends on your sample type, budget, and depth needs — but look for a provider with CLIA-certified/CAP-accredited lab operations, flexible input requirements (including low-input and FFPE samples), and end-to-end support from extraction through bioinformatics. Admera Health offers exactly this: bulk RNA sequencing down to ultra-low input, near single-cell levels, PhD-level bioinformatics support, and fast turnaround (typically 10–15 business days, expedited on request) — one of the most complete RNA sequencing services for research available today.
Admera Health offers exactly this: bulk RNA-seq down to ultra-low input, near single-cell levels, PhD-level bioinformatics support, and fast turnaround (typically 10–15 business days, expedited on request).
Tissue-Specific Questions
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Yes. We specialize in handling challenging and low-input samples, including FFPE, blood, fresh frozen tissue, and cell pellets. Our optimized workflows for FFPE samples include a high-yield extraction protocol with improved proteinase K digestion and DNase treatment to minimize DNA and rRNA contamination. This ensures a high success rate and provides the necessary input quality for robust downstream analysis.
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Yes. In xenograft (PDX) tumor RNA-seq, sequencing captures RNA from both the implanted human tumor cells and the mouse host tissue stromal/immune microenvironment. Without deconvolution, mouse reads contaminate your human gene expression data. Admera's dedicated xenograft pipeline eliminates this problem:
Dual-genome alignment: every read is aligned independently to GRCh38 (human) and GRCm38/mm10 (mouse) using STAR.
XenofilteR deconvolution: reads are classified as human-specific or mouse-specific by comparing alignment mismatch scores; ambiguous reads are discarded, resulting in clean human-only BAM files.
Human-only quantification: HTSeq raw gene counts and StringTie FPKM/TPM values are generated from deconvoluted, human-specific reads.
Rigorous QC reporting: Picard RNA metrics + interactive MultiQC HTML dashboard delivered with every project.
What is the client impact? Without species deconvolution, a substantial fraction of aligned reads in xenograft samples can originate from mouse host tissue, severely distorting human tumor signal. Admera's pipeline delivers accurate human tumor transcriptomes — ready for differential expression analysis, pathway analysis, and publication-grade methods documentation.
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Yes. Admera has delivered RNA-seq for non-human, non-mouse organisms across a broad range of species, including:
Schistosoma mansoni: parasitology / tropical disease vaccine research
Xenopus laevis: developmental biology and amphibian models
Atelopus zeteki (Panamanian golden frog): wildlife conservation genomics
Batrachochytrium dendrobatidis (chytrid fungus): host-pathogen interaction studies
Bos taurus (bovine): agricultural and veterinary transcriptomics
Gallus gallus (chicken): poultry disease and agricultural research
Saccharomyces cerevisiae: yeast model systems and fermentation biology
Clostridium saccharoperbutylacetonicum: microbial metabolic engineering
For species with reference genomes, Admera uses standard alignment-based pipelines. For non-model organisms without a reference, de novo transcriptome assembly (Trinity) followed by functional annotation is available. Contact Admera with your organism and study design for a project-specific recommendation.
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Yes. Many real-world studies involve more than one experimental variable — for example, treatment condition crossed with a physiological variable such as stress, diet, age, or sex. Admera's bioinformatics team is experienced in factorial experimental design RNA-seq analysis, including:
Multi-factor DESeq2 models: Designs with two or more independent variables (e.g., treatment × condition) are modeled using interaction terms, allowing Admera to detect main effects and gene-level interactions between factors.
Complex contrast matrices: Beyond simple A-vs-B comparisons, Admera generates custom contrast sets — combined group comparisons, marginal effects, and interaction contrasts — tailored to your experimental hypothesis.
Parallel multi-tissue RNA-seq analysis:: When the same experimental design is applied across multiple tissue types or cell compartments, Admera processes and analyzes each tissue using a consistent pipeline, enabling cross-tissue comparison.
Tissue-specific and shared DEG identification: Venn diagrams and overlap analyses identify which differentially expressed genes and pathways are shared across tissues versus tissue-specific — critical for understanding systemic vs. local transcriptomic responses.
What is the client impact? Factorial experimental designs reflect how experiments are actually conducted in the lab. Forcing complex designs into simple pairwise comparisons loses statistical power and misses interaction effects. Admera designs the right statistical model for your study from the start.
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Yes. Dual or multi-organism transcriptomics is a supported capability. In studies profiling both a host organism and an infecting pathogen, researchers need to understand not just how the host responds to infection, but also how the pathogen itself changes its gene expression. Admera handles this by running parallel, organism-specific analysis pipelines on the same set of samples:
Organism-specific alignment and quantification: Reads from each sample are aligned to the host organism reference genome and the infecting pathogen reference genome independently, with species-specific gene counts and expression profiles generated for each.
Host immune response profiling: Differential expression, GO, and KEGG enrichment analysis reveals which host immune, metabolic, and stress-response pathways are activated or suppressed during infection.
Pathogen transcriptome analysis: The pathogen's own gene expression profile is characterized simultaneously, identifying virulence-associated, metabolic, or adaptive genes differentially expressed during active infection vs. control conditions.
Non-model and non-annotated organisms: For host or pathogen species with limited genome annotation, Admera applies de novo assembly or uses best-available reference genomes with custom annotation pipelines.
Conservation and wildlife genomics: This approach has been applied to endangered and non-standard wildlife species, informing conservation and disease management strategies.
What is the client impact? Host organism–infecting pathogen dual transcriptomics requires coordinating multiple reference genomes, handling ambiguous multi-mapping reads, and interpreting results across two entirely different organisms. Admera's team manages this end-to-end, delivering separate, clearly organized results for host and pathogen alongside a unified interpretation
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Yes. Admera Health supports BRB-seq (Bulk RNA Barcoding and sequencing) and equivalent high-throughput barcoded bulk RNA-seq protocols (including DRUG-seq and other plate-based multiplexing protocols). These methods use unique sample barcodes and UMIs to pool tens to hundreds of samples into a single sequencing run — dramatically reducing per-sample cost while maintaining full-transcriptome coverage. Admera's end-to-end BRB-seq workflow covers:
Barcode-aware alignment with STARsolo: demultiplexes pooled samples, assigns reads to individual samples via a barcode whitelist, and generates UMI-collapsed gene count matrices in a single pass.
UMI-based deduplication: PCR duplicates are collapsed using UMI information (1-mismatch directional correction), giving more accurate quantification than standard read-count-based RNA-seq.
High-throughput dose-response and compound screening: ideal for experiments where many conditions — multiple drug concentrations, compound panels, or perturbation libraries — need to be profiled simultaneously.
Custom targeted gene panel analysis: expression of a curated gene panel can be extracted and summarized across all samples alongside the full differential expression output.
Full downstream analysis pipeline: BRB-seq count matrices feed directly into Admera's standard bulk RNA-seq downstream pipeline.
Cost efficiency at scale: by pooling many samples into one flow cell lane, BRB-seq and equivalent protocols can reduce per-sample sequencing cost by 5–10× compared to individually indexed standard libraries.
What is the client impact? BRB-seq is particularly well-suited for drug discovery, compound screening, and perturbation studies where transcriptomic profiling of many conditions is required but budget or throughput is a constraint.
Platform Selection
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Our standard turnaround time is typically 10-15 business days, though this can vary depending on the sample type, project complexity, and required sequencing depth. Expedited services are available upon request. Please contact us for a detailed quote and timeline specific to your project.
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Yes. Rush processing is available for an additional fee. Contact us as early as possible.
Turnaround Time
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Our bioinformatics pipelines are comprehensive and customizable. For Bulk RNA-seq, we provide trimming and QC, mapping, counting, normalization, and differential expression analysis (DE). For projects involving non-model organisms, we offer de novo transcriptome assembly. Additional analysis options include alternative splicing detection, gene fusion analysis, and functional enrichment analysis (MA-plot, PCA, heatmaps, volcano plots, and GO enrichment).
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A standard mRNA-seq workflow moves from RNA extraction and QC, to poly-A selection or rRNA depletion, library prep, sequencing, and bioinformatics analysis.
On the analysis side, Admera Health provides trimming and QC, alignment, transcript counting, normalization, and differential expression (DE) analysis, PCA, volcano plots, heatmaps, functional enrichment (GO/KEGG), plus optional add-ons like alternative splicing detection and gene fusion analysis. For non-model organisms without a reference genome, de novo transcriptome assembly is also available.
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Admera's bioinformatics pipeline for RNA-seq covers the full path from raw reads to biological insight: quality trimming, alignment/mapping, quantification, normalization, DE analysis, pathway/GO enrichment. Depending on project goals, this can extend to isoform-level analysis, splice variant detection, gene fusion calling, alternative splicing detection, and other custom analysis — all delivered as publication-ready reports.
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Yes. This is a clinical-grade strength. Admera's bioinformatics team supports multi-arm clinical trials comparing multiple dose cohorts across longitudinal timepoints, with parallel arms across geographically or demographically distinct sample groups. Key capabilities:
Flexible DESeq2 designs: Per-timepoint and per-dose-group pairwise comparisons across any combination of groups and visit days.
Cross-population batch correction: ComBat or limma-based correction when samples span geographically or demographically distinct cohorts.
Publication-grade statistics: DEGs filtered by FDR-adjusted p-value (BH padj < 0.05) and log2FC thresholds.
Full GO/KEGG enrichment: clusterProfiler-based GO (BP, CC, MF) and KEGG enrichment — separately for up-regulated, down-regulated, and all DEGs.
Immunogenomics add-ons: immunoglobulin gene expression heatmaps (IgG, IgA, IgE, IgM) per dose group and timepoint, critical for vaccine immunogenomics studies
What is the client impact? Admera's PhD bioinformaticians design the full statistical framework for your study — including cross-population comparisons across longitudinal timepoints — and produce manuscript-ready figures and methods sections supporting submissions to Nature Communications, PLOS Pathogens, and similar peer-reviewed journals.
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Absolutely. Admera Health has executed multi-compound, time-course RNA-seq studies designed to characterize antibody and small-molecule drug mechanisms of action (MOA):
Compound comparison panels: Parallel RNA-seq profiling of multiple test compounds at defined timepoints vs. appropriate controls.
Compound signature analysis: Identifies transcriptomic signatures that stratify compounds by functional phenotype.
Variant vs. reference compound analysis: Characterizes how structural or formulation modifications alter gene expression relative to reference compounds.
Predictive classification support: Signature gene sets derived from known compounds can predict the functional phenotype of new, untested molecules.
Rich visualization: Volcano plots, heatmaps, PCA clustering, and Venn diagrams across all compound-comparison pairs.
What is the client impact? For biopharma and biotech clients, Admera's transcriptomic MOA analysis enables lead compound ranking, safety signal detection, and mechanistic differentiation — without requiring in-house bioinformatics infrastructure.
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Bioinformatics reproducibility and pipeline quality are technical and compliance requirements, not marketing claims:
Snakemake + conda environments: All RNA-seq projects run through a Snakemake-based pipeline with conda environment version pinning.
Automated vs. manual benchmarking: Admera routinely validates automated pipeline outputs against manually curated analyses before any workflow is deployed to client projects.
Interactive QC dashboards: every project receives a MultiQC HTML report aggregating FastQC, STAR alignment, Picard RNA metrics, and HTSeq/StringTie statistics.
Documented methods for publication: Reference genome versions, tool versions, and comparison definitions are documented in manuscript-formatted Methods sections.
Secure data handling: All sequencing data and analysis outputs are stored in a compliant AWS environment; client data is never processed or stored outside approved infrastructure.
What is the client impact? In regulated research contexts — clinical trials, grant applications, regulatory submissions — Admera's documented, version-controlled workflows deliver the reproducibility and pipeline quality expected by institutional compliance teams, grant reviewers, and journal peer reviewers.
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Admera's standard RNA-seq deliverable package includes:
Raw and trimmed FASTQ files: available via secure AWS S3 or SFTP transfer.
Gene count matrix: HTSeq raw counts per sample — ready for DESeq2 or edgeR.
Transcript abundance tables: StringTie FPKM/TPM values for visualization and isoform-level analysis.
Differential expression results: significant DEGs with FDR-adjusted p-values, log2FC, and gene annotations (CSV format).
GO/KEGG enrichment reports: tables and publication-ready figures for up- and down-regulated gene sets.
Interactive MultiQC QC report: per-sample QC metrics — alignment rates, gene body coverage, rRNA contamination, read distribution.
Publication-ready figures: volcano plots, heatmaps, PCA plots, Venn diagrams (PDF + PNG).
Manuscript Methods text: formatted methods section with all software versions and parameters.
PhD bioinformatician consultation: review of results and interpretation support included.
Bioinformatic Analysis
Sending samples?
See our RNA sample submission guidelines for best practices on sample preparation, packaging, and shipment for the highest quality results.
Get the Most out of Your Study
Maximize your project’s potential with advanced analysis solutions. Our team of expert bioinformaticians curate pipelines tailored to your project’s experimental design.
See RNA-seq in Action
Admera Health provides comprehensive support for all projects, and delivers publication-ready data. Discover how researchers are using Admera Health to advance their Transcriptomics studies.