The answer matters more than it might first appear. Quantitative real-time PCR, or RT-qPCR, is the workhorse technique for measuring gene expression. It works by amplifying target DNA sequences and measuring how many cycles of amplification are needed before the signal crosses a detection threshold, a value known as the Ct. Lower Ct values mean more of the original messenger RNA was present, and therefore the gene was more active. But the raw numbers from an RT-qPCR experiment are meaningless on their own, because they are influenced by everything from the amount of starting material to the efficiency of the enzymatic reaction. To correct for these technical variables, researchers normalize their results against internal reference genes, sometimes called housekeeping genes, which are assumed to be expressed at roughly constant levels regardless of experimental conditions.

The problem, and the reason this study exists, is that the assumption of constant expression is frequently wrong. Reference genes are real genes with real biological functions, and under stress their activity can shift dramatically. If a chosen reference gene changes its expression in response to salt stress or drought, every downstream measurement becomes distorted, sometimes reversing the apparent direction of a result. A comprehensive literature search conducted by the team revealed that no suitable reference genes had ever been reported for Rubia cordifolia, either in China or internationally. For a species routinely used in clinical practice as a traditional Chinese medicinal herb, and increasingly studied at the molecular level for the pharmacologically active compounds it produces, this was a conspicuous gap.

To fill it, the researchers assembled a panel of twelve candidate reference genes and profiled their expression across a demanding set of experimental conditions. Samples were taken from various tissues of the plant, and whole plants were subjected to five distinct abiotic stress treatments: salt stress induced by sodium chloride, dehydration stress, and treatments with three chemically distinct signaling molecules that plants use to orchestrate stress responses, namely salicylic acid, methyl jasmonate, and abscisic acid. This design is important because reference gene stability is condition-specific. A gene that holds steady in leaves may wobble in roots, and a gene unperturbed by salt may fluctuate during dehydration. By spanning tissues and stress types, the study aimed to identify genes whose stability is robust rather than accidental.

Measuring the candidates, however, is only half the task. The raw stability data must be interpreted, and different analytical algorithms can weight the evidence differently, sometimes reaching different conclusions from the same numbers. The team therefore ran their dataset through four widely used algorithms. geNorm evaluates pairwise variation among candidate genes and calculates an expression stability measure, on the logic that truly stable genes should vary in concert with one another. NormFinder builds a statistical model that estimates expression variation while accounting for subgroup structure, such as different tissues or treatments. BestKeeper takes a correlation-based approach, comparing each candidate directly against an index constructed from the whole panel. The comparative delta Ct method, as its name suggests, compares relative expression values between pairs of candidates to rank their stability.

Each algorithm contributed to a consensus picture. Across the tissues and stress conditions, hnRNP, UBQ, HIS3.3, PP2A, and PTBP2 emerged as the most stable of the twelve candidates, while ACT7 and EF-1α proved to be the least stable. That last finding carries a cautionary lesson for the wider field: ACT and EF-1α are among the most frequently used reference genes in plant studies precisely because of their housekeeping reputations, yet reputations do not transfer automatically across species or conditions. To synthesize the four individual analyses, the team also employed RefFinder, an integrative tool that aggregates the rankings from geNorm, NormFinder, BestKeeper, and the delta Ct method into a single comprehensive assessment. The integrated analysis confirmed hnRNP, HIS3.3, PTBP2, PP2A, and RPL5 as the top five most stable reference genes overall.

Identifying candidates is one thing; proving they actually improve experimental accuracy is another. For validation, the researchers turned to a target gene called MVK, which encodes mevalonate kinase, an enzyme embedded in the mevalonate pathway that underpins the biosynthesis of isoprenoid compounds. This pathway is directly relevant to the pharmacological interest in Rubia cordifolia, since many of the plant’s bioactive secondary metabolites are built from isoprenoid precursors. By measuring MVK expression and normalizing the results against each candidate reference gene in turn, the team could see in practice how the choice of reference gene changed the apparent answer. Normalization against the most stable references produced consistent, reliable MVK profiles, confirming that the screened genes are not merely statistically stable but functionally dependable as baselines for real experiments.

The technical significance of the work extends beyond a single species. Reference gene validation studies follow a well-established template, but each new species requires its own screen because orthologous genes can behave very differently across evolutionary lineages, and even within a species, stability varies with tissue, developmental stage, and stressor. By establishing a validated reference set for Rubia cordifolia, the study removes a fundamental source of error from all future gene expression work in this plant, whether the goal is understanding how the herb responds to salinity in cultivation, deciphering the enzymatic routes to its medicinal compounds, or engineering enhanced production of valuable metabolites. The authors describe the work as a foundational step toward reliable functional genomics research in the species, paving the way for accurate elucidation of gene function.

The study also arrived with appropriate scientific and ethical diligence. The work was funded by the High-Level Key Discipline Construction Project of Traditional Chinese Medicine of the National Administration of Traditional Chinese Medicine under grant number SATCM-RH[2023]85. In collecting plant and seed samples, the researchers state that they strictly abided by the policy statements of the International Union for Conservation of Nature concerning research involving endangered species, as well as the guiding principles of the Convention on International Trade in Endangered Species of Wild Fauna and Flora. The authors declared no competing interests, and the article is published open access under a Creative Commons license, making the data and conclusions freely available to researchers worldwide.

For practitioners of plant molecular biology, the practical takeaway is straightforward but consequential: never assume a reference gene is stable, and never borrow one on reputation alone. The Henan team’s finding that ACT7 and EF-1α, two of the plant kingdom’s most popular normalizers, rank as the least stable candidates in Rubia cordifolia is a vivid reminder that every species tells its own molecular story. With hnRNP, UBQ, HIS3.3, PP2A, PTBP2, and RPL5 now validated as dependable anchors, researchers studying this ancient medicinal herb can finally measure its genes with confidence, and the quiet, meticulous science of normalization has delivered one of its characteristically unglamorous but genuinely enabling victories.

Subject of Research: Validation of stable internal reference genes for RT-qPCR gene expression analysis in Rubia cordifolia under abiotic stress

Article Title: Screening and validation of suitable internal reference genes for gene expression analysis in Rubia cordifolia L. under different abiotic stresses

Article References: Screening and validation of suitable internal reference genes for gene expression analysis in Rubia cordifolia L. under different abiotic stresses. (n.d.). https://doi.org/10.1186/s12864-026-13415-1

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13415-1

Keywords: Rubia cordifolia, RT-qPCR, internal reference genes, gene expression, abiotic stress, geNorm, NormFinder, BestKeeper, RefFinder, BMC Genomics, traditional Chinese medicine, functional genomics