RNA Sequencing Test: Gene Expression, Fusions, and Results

RNA sequencing, often called RNA-seq, examines the RNA molecules that cells produce when genes are active. Unlike DNA testing, which mainly identifies inherited or acquired changes in the genetic code, RNA sequencing shows how that code is being used. It can measure gene activity, detect abnormal RNA splicing, and identify fusion transcripts created when parts of different genes join together. These capabilities make RNA sequencing especially useful in cancer testing and in selected inherited disorders that remain unexplained after DNA analysis.

The meaning of an RNA-seq result depends heavily on the specimen, laboratory method, and clinical question. RNA is less stable than DNA, and many genes are active only in particular tissues. A negative blood test therefore may not exclude an abnormality that is visible in muscle, skin cells, or tumor tissue. Results should be interpreted alongside symptoms, pathology findings, imaging, family history, and DNA-based tests rather than viewed as a stand-alone diagnosis.

• RNA sequencing measures transcripts—the RNA copies produced from active genes.
• It can detect gene fusions, abnormal splicing, and unusually high or low gene expression.
• Targeted RNA panels examine selected genes, while transcriptome sequencing surveys a much broader set of RNA molecules.
• Sample type and RNA quality strongly affect whether clinically important changes can be found.
• A negative result does not rule out every genetic disorder or cancer-driving alteration.

Table of Contents

• What RNA Sequencing Examines
• Targeted Panels and Transcriptome Sequencing
• How the Test Is Performed
• Clinical Uses in Cancer and Inherited Disease
• How RNA-Seq Results Are Reported
• Sample Selection and RNA Quality
• Accuracy, Limitations, and Follow-Up

What RNA Sequencing Examines

RNA sequencing examines the collection of RNA molecules present in a specimen at the time it is collected. Most clinical assays focus on messenger RNA, or mRNA, because it carries instructions from DNA to the cell’s protein-making machinery. The complete set of transcripts in a cell or tissue is often called the transcriptome.

A gene may be present in DNA but inactive in a particular tissue. When it is active, the cell copies the relevant DNA sequence into a preliminary RNA molecule. That RNA is processed before it is used. Noncoding segments called introns are usually removed, and coding segments called exons are joined. Different combinations of exons can produce different transcripts from the same gene, a process known as alternative splicing.

RNA sequencing can provide several kinds of information:

• Gene expression: The number of sequence reads associated with a gene can be used to estimate how active that gene is relative to other genes or control samples.
• RNA sequence changes: Some DNA variants can also be observed in RNA when the altered gene is expressed and the relevant region is captured.
• Abnormal splicing: RNA-seq can show exon skipping, creation of a new splice site, retention of an intron, or other transcript changes caused by a DNA variant.
• Gene fusions: Reads that span two different genes may reveal a fusion transcript produced by a chromosomal rearrangement.
• Allele-specific expression: When two gene copies can be distinguished, the assay may show that one is expressed less than the other or not at all.
• Expression outliers: A gene may be expressed at an unusually high or low level compared with appropriate reference samples.

These categories overlap. A structural DNA change can create a fusion, alter expression, and disrupt normal splicing at the same time. Conversely, an unusual RNA pattern does not always identify the underlying DNA event. The laboratory may recommend confirmation with DNA sequencing, fluorescence in situ hybridization, chromosomal analysis, or a focused gene fusion test.

RNA sequencing is different from a conventional RNA expression panel. Some expression panels use a fixed set of genes and a validated mathematical score for a specific clinical decision, such as estimating recurrence risk in a defined cancer population. Broader RNA-seq methods generate sequence-level data and may assess expression, splicing, and fusions together. The report should state exactly which type of analysis was performed.

Targeted Panels and Transcriptome Sequencing

Clinical RNA tests range from small targeted panels to broad transcriptome studies. The best method depends on whether the laboratory is looking for a known class of alteration, evaluating one disease area, or searching broadly for an explanation.

Targeted RNA sequencing

A targeted RNA panel captures transcripts from a selected list of genes. Cancer panels often emphasize genes that commonly participate in actionable fusions, such as ALK, RET, ROS1, NTRK1, NTRK2, NTRK3, and other tumor-specific targets. In inherited disease, a targeted assay may focus on one gene or a small group when abnormal splicing is suspected.

Targeted testing usually offers deeper coverage of the included genes than a broad assay. This can improve sensitivity when tumor content is limited or a fusion transcript is present at a low level. It also simplifies analysis because fewer transcripts are evaluated. The main limitation is scope: alterations involving genes, exons, or fusion partners outside the validated target design may be missed.

Some targeted assays require knowledge of both fusion partners. Others use anchored methods that start from one known gene and can detect many possible partners. The report or laboratory methodology should clarify whether novel partners can be found and whether all exons are covered.

Whole-transcriptome RNA sequencing

Whole-transcriptome sequencing aims to examine RNA from thousands of genes without restricting the analysis to a narrow panel. It can support expression profiling, fusion discovery, splice analysis, and research into unexpected transcript changes. In rare disease, it may be used after exome or genome sequencing to determine whether a candidate DNA variant actually disrupts RNA processing.

Broad sequencing generates much more data, but more data do not automatically mean a more conclusive result. Analysis requires appropriate reference samples, statistical methods, and filters that distinguish disease-related findings from ordinary differences among tissues and individuals. Some genes may still have inadequate coverage because they are expressed at very low levels in the tested specimen.

Short-read and long-read methods

Most clinical RNA sequencing uses short-read technology. RNA is converted into many small complementary DNA fragments, sequenced, and computationally aligned to the genome or transcriptome. Short reads are efficient and well supported by established analytic pipelines, but reconstructing full transcripts can be difficult when a gene has many similar isoforms.

Long-read RNA sequencing can read much larger portions of a transcript and may define complex splice forms or fusion structures more directly. Its role in routine clinical testing is still developing, and availability varies. Laboratories must validate performance for each claimed use rather than assuming that a newer platform is superior for every specimen or alteration.

The distinction between panel and transcriptome testing is separate from the distinction between DNA and RNA analysis. Many laboratories combine both in a single next-generation sequencing panel. DNA analysis identifies sequence and copy-number changes, while RNA analysis can confirm their functional effects and improve detection of expressed fusions.

How the Test Is Performed

RNA sequencing begins with a specimen that contains the cells relevant to the clinical question. Depending on the indication, this may be fresh or frozen tissue, formalin-fixed paraffin-embedded tumor, blood, bone marrow, cultured skin fibroblasts, muscle, or another tissue. A pathologist may mark a tumor-rich area so the laboratory can extract material from the most informative region.

The main laboratory steps are:

1. RNA extraction: Cells are broken open and RNA is purified. Because RNA degrades readily, collection, storage, and transport conditions matter.
2. Quality and quantity assessment: The laboratory estimates how much RNA is available and whether it is sufficiently intact. Some assays accept fragmented RNA, while others require higher-quality material.
3. Conversion to complementary DNA: Reverse transcriptase converts RNA into complementary DNA, or cDNA, because most sequencing platforms read DNA rather than RNA directly.
4. Library preparation: The cDNA is fragmented or selectively captured, adapters are attached, and the material is prepared for sequencing. The method may enrich messenger RNA, remove abundant ribosomal RNA, or amplify specified genes.
5. Sequencing: The instrument reads millions of fragments. The required read depth depends on whether the goal is expression measurement, fusion detection, or broad transcript discovery.
6. Bioinformatic analysis: Software removes low-quality reads, aligns sequences, counts transcripts, identifies splice junctions, and searches for candidate fusions or expression outliers.
7. Clinical review: Qualified laboratory professionals assess technical quality, compare findings with databases and published evidence, and decide which results meet reporting criteria.

Fusion analysis looks for reads that join sequences from different genes or from distant regions of the same gene. A credible call usually requires multiple supporting reads, appropriate orientation, a biologically plausible breakpoint, and enough evidence to exclude mapping errors. Laboratories may also evaluate whether the fusion preserves the reading frame and retains a functional domain, such as an active kinase region.

Splice analysis compares observed exon junctions with expected transcripts. A pathogenic DNA variant near a splice boundary may cause an exon to be omitted, activate a hidden splice site, or leave part of an intron in the mature transcript. RNA evidence can therefore help reclassify a DNA variant that was previously uncertain. However, abnormal splice products can occur at low levels in healthy cells, so interpretation requires controls and disease context.

Expression analysis normally involves normalization. Raw read counts cannot be compared directly without accounting for sequencing depth, gene length, sample composition, and technical variation. In clinical testing, the laboratory should use a validated reference set matched as closely as possible for tissue type and processing method. An unusually high expression value may support a diagnosis, but it is rarely interpreted without other molecular or clinical evidence.

Clinical Uses in Cancer and Inherited Disease

RNA sequencing has two major clinical roles: characterizing tumors and clarifying the consequences of suspected inherited variants. The exact utility differs between these settings.

Cancer testing

Many cancers are driven by gene fusions. A chromosomal rearrangement can place the active portion of one gene next to another, producing an abnormal protein that promotes cell growth. Because the rearranged DNA may contain large introns or an unknown partner, it can be easier to identify the expressed fusion transcript in RNA than to locate the exact breakpoint in DNA.

RNA-based fusion testing is widely used in selected lung cancers, sarcomas, thyroid tumors, leukemias, brain tumors, and other malignancies. A detected fusion may:

• establish or refine a tumor diagnosis;
• identify a target for an approved therapy;
• indicate eligibility for a clinical trial;
• provide prognostic information in a defined disease;
• resolve an otherwise difficult pathology classification.

For example, kinase fusions involving ALK, ROS1, RET, or NTRK genes can be clinically actionable in appropriate cancers. The significance depends on tumor type, fusion structure, current treatment guidance, and whether the result has been confirmed by a validated assay. Not every detected fusion produces a functional cancer-driving protein.

RNA sequencing can also identify exon-skipping events, such as transcripts that omit a clinically important exon, and can measure expression signatures. In tumor profiling, RNA results are often interpreted together with DNA variants, copy-number changes, tumor purity, and microscopic findings. A combined DNA/RNA approach can reduce blind spots because each analyte detects different alteration types well.

Inherited and rare disease testing

DNA sequencing sometimes finds a variant whose effect is uncertain. This is common for changes near splice sites, deep within introns, or in regulatory regions. RNA sequencing can show whether the variant produces an abnormal transcript in patient cells.

Broad RNA-seq may also identify a gene with abnormally low expression, monoallelic expression, or an unusual splice pattern that points investigators back to a hidden DNA variant. In some cases, this helps solve a disorder that remained unexplained after whole-exome sequencing.

The value of RNA testing is strongly tissue dependent. A gene involved in muscular dystrophy may be highly expressed in muscle but barely detectable in blood. A neurologic disease gene may not be expressed in an accessible specimen at a useful level. Cultured fibroblasts or other surrogate tissues can sometimes provide evidence, but they may not reproduce the transcript pattern of the affected organ.

RNA evidence can strengthen or weaken the case that a DNA variant is pathogenic, yet it does not replace formal variant classification. The laboratory still considers population frequency, predicted protein effect, inheritance pattern, family segregation, functional evidence, and the match between the gene and the patient’s features.

How RNA-Seq Results Are Reported

RNA-seq reports vary widely because the method can answer different questions. The first step in reading a report is to identify the test’s intended purpose and validated scope. A fusion panel, a tumor expression classifier, and a rare-disease transcriptome assay do not produce interchangeable results.

Positive or clinically significant finding

A positive report may describe a fusion transcript, an abnormal splice event, or a disease-relevant expression pattern. For a fusion, the report often lists both genes, the involved exons, transcript identifiers, read support, and an interpretation of clinical significance. It may state whether the alteration is associated with a diagnosis or targeted treatment.

For inherited disease, the report may connect an RNA abnormality to a specific DNA variant. A result could state that a variant causes partial skipping of an exon, introduces a premature stop signal, or reduces normal transcript levels. The laboratory may then update the DNA variant from uncertain significance to likely pathogenic or pathogenic if the total evidence supports that change.

Expression outlier

An expression outlier means a gene’s RNA level differs substantially from the laboratory’s reference group. Low expression may suggest nonsense-mediated decay, promoter disruption, or another mechanism that reduces stable transcript. High expression may occur because of gene activation, amplification, fusion, inflammation, cell-type composition, or technical factors.

An outlier is not automatically a diagnosis. The result is stronger when it matches the clinical phenotype, occurs in an appropriate tissue, and is supported by a DNA change or another independent test. A dedicated RNA expression panel may report a validated score rather than individual outlier genes.

Variant or finding of uncertain significance

A laboratory may identify an unusual fusion or splice pattern but lack enough evidence to decide whether it causes disease. Such findings can be labeled uncertain, indeterminate, or investigational. They should not generally be used alone for irreversible treatment or predictive testing in relatives.

Uncertainty may decrease as additional cases, functional studies, or family data become available. Patients with inherited-disease findings can ask whether the laboratory offers reinterpretation and whether relatives’ samples would help clarify the result.

Negative result

A negative result means that the assay did not identify a reportable abnormality within its tested scope and quality limits. It does not prove that all RNA processing and expression are normal. Relevant explanations include:

• the causative gene was not expressed in the submitted tissue;
• the abnormal transcript was rapidly degraded;
• RNA quality or quantity was inadequate;
• the alteration fell outside the panel or analytic pipeline;
• tumor cells made up too little of the specimen;
• expression differed only under conditions not present when the sample was collected;
• the disorder is caused by a mechanism the test does not assess.

Some reports use “no fusion detected” rather than “negative.” This wording is more precise because the test may not have evaluated other types of RNA abnormality.

Inconclusive or failed test

A test can be inconclusive when RNA extraction, library preparation, sequencing, or quality-control metrics do not meet requirements. Formalin-fixed tissue is often fragmented, and very small biopsies may contain too little material. Repeating the assay on another block, a fresh specimen, or a different tissue may be recommended.

Sample Selection and RNA Quality

Specimen choice is one of the most important determinants of RNA-seq success. RNA profiles vary among organs, cell types, developmental stages, and disease states. The ideal sample contains the cells in which the suspected gene or tumor process is active.

For solid tumors, a pathologist reviews the specimen to estimate tumor percentage and identify necrosis, inflammation, or normal tissue that may dilute the signal. Decalcified bone specimens and old formalin-fixed blocks can yield highly degraded RNA. Laboratories may request unstained slides, a tissue block, or curls cut from a selected area.

For blood cancers, peripheral blood or bone marrow may be suitable when malignant cells are present. For inherited disorders, blood is convenient but not universally informative. Muscle, skin fibroblasts, or another disease-relevant tissue may be needed. A clinician should discuss the trade-off between diagnostic yield and the invasiveness of obtaining that tissue.

Pre-analytic factors include:

• delay before stabilization or freezing;
• temperature during storage and shipment;
• fixation time and fixative type;
• repeated freeze-thaw cycles;
• tissue age and block storage conditions;
• contamination with DNA, chemicals, or another specimen;
• proportion of the relevant cell population.

Laboratories assess RNA using measures of concentration, purity, fragment size, or amplifiability. A commonly used integrity score can be useful for fresh tissue but may not fully predict performance in formalin-fixed specimens. Some modern targeted assays are designed for fragmented RNA and use short capture regions, allowing testing of samples that would be unsuitable for whole-transcriptome analysis.

The key preparation issue is obtaining the right specimen and ensuring that the pathology or laboratory team receives complete clinical information. For tumor testing, the request should include diagnosis, biopsy site, tumor percentage if known, and the treatment question. For rare disease, phenotype details, family history, and prior DNA findings guide interpretation.

Turnaround time ranges from days to several weeks, depending on test complexity, specimen preparation, and whether confirmatory studies are required.

Accuracy, Limitations, and Follow-Up

RNA sequencing can be highly sensitive for specific validated targets, but accuracy is not a single fixed percentage. Performance depends on the assay design, alteration type, expression level, read depth, specimen quality, and analytic thresholds. A laboratory should validate sensitivity, specificity, reproducibility, and reportable range for each claimed use.

False-negative results can occur when a transcript is rare, unstable, or absent from the tested tissue. Nonsense-mediated decay may destroy RNA carrying a premature stop signal, leaving too few abnormal molecules to detect. Low tumor purity can similarly hide a fusion transcript. A panel cannot detect targets it was not designed or validated to analyze.

False-positive or misleading signals can result from mapping errors, laboratory contamination, reverse-transcription artifacts, normal low-level read-through transcription, or complex alternative splicing. Gene families with highly similar sequences are especially difficult to align. Bioinformatic fusion callers may disagree, which is why laboratories use quality filters and manual review.

Expression data create additional challenges. Age, sex, ancestry, medication, inflammation, time of collection, tissue handling, and the mixture of cell types can all affect transcript levels. A comparison group that is poorly matched to the patient sample may create apparent outliers that are not disease related.

Clinical follow-up should be based on the finding:

• Actionable tumor fusion: Confirm that the alteration and tumor type meet current treatment criteria. An oncologist may integrate the result with stage, prior therapy, and other biomarkers.
• Diagnostic fusion: A pathologist may correlate it with tumor morphology and immunohistochemistry before final classification.
• Abnormal splicing in inherited disease: The laboratory may combine RNA evidence with DNA data and issue an amended classification.
• Uncertain RNA finding: Family studies, another tissue, targeted reverse-transcription PCR, Sanger sequencing, or additional functional work may be suggested.
• Negative result despite strong suspicion: DNA genome sequencing, copy-number analysis, methylation testing, repeat-expansion testing, or a more appropriate tissue may be considered.

A detected RNA fusion is often confirmed by an independent method when the result will guide major treatment or when assay policy requires it. However, a thoroughly validated RNA panel may serve as the primary clinical test. The need for confirmation should be determined by the laboratory’s validation, professional guidance, and the consequences of the decision.

RNA-seq results may also change over time as transcript annotations, disease associations, and therapy evidence evolve. Patients should keep a copy of the report and ask whether reinterpretation is available. In inherited conditions, genetic counseling can explain implications for relatives, reproductive planning, and whether targeted family testing is appropriate. In cancer, discussion with the treating oncology team is essential because a molecular finding does not by itself establish that a treatment will be effective or accessible.

The most useful RNA sequencing result is one interpreted in context. The test is strongest when the correct tissue is studied, the laboratory method matches the suspected alteration, quality metrics are adequate, and RNA findings are integrated with DNA, pathology, and clinical evidence.

References

• Current status of molecular diagnostics for lung cancer — 2024 Review.
• Splicing defects in rare diseases: transcriptomics and machine learning — 2023 Review.
• Trio RNA sequencing in a cohort of medically complex children — 2023 Study.
• Standardized practices for RNA diagnostics using clinically accessible specimens reclassifies 75% of putative splicing variants — 2022 Study.
• Fusion-positive non-small cell lung carcinoma — 2022 Review.
• Towards a single-assay approach: a combined DNA/RNA sequencing panel eliminates diagnostic redundancy and detects clinically-relevant fusions in lung adenocarcinoma — 2022 Study.

Disclaimer

This article is for general education and does not replace advice from a physician, genetic counselor, pathologist, or other qualified professional. Test methods, report terminology, and clinical recommendations vary among laboratories and may change as evidence develops. Medical decisions should be based on the complete clinical picture and the interpretation provided by the testing laboratory and treating team.