ArticleBiomedicines2023
A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets.
Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 13 citations in OpenAlex.
- Normalization Challenges Across Adipocyte Differentiation and Lipid-Modulating Treatments: Identifying Reliable Housekeeping Genes.International journal of molecular sciences · 2026Article
- Advances in algorithms for normalizer gene selection in qRT-PCR: implications for cancer biology and precision medicine.Frontiers in genetics · 2026Review
- Potential mitochondria-associated pathogenic genes in sepsis: a multi-omics Mendelian randomization study.Frontiers in immunology · 2026Article
- ACmix-Swin Deep Learning of 4-Day-OldGenes · 2025Article
- Exploring transcriptomic databases to identify and experimentally validate tissue-specific consensus reference gene for gene expression normalization in BALB/c mice acutely exposed to 2,3,7,8-Tetrachlorodibenzo-Current research in toxicology · 2025Article
- Identification of endogenous reference genes for RT-qPCR analysis in breast cancer and matched adjacent tissues.Frontiers in oncology · 2025Article
- A comparative assessment of reference genes in mouse brown adipocyte differentiation and thermogenesis in vitro.Adipocyte · 2024Article
- Increased expression of miR-320b in blood plasma of patients in response to SARS-CoV-2 infection.Scientific reports · 2024Article
- Optimization of preparation conditions for Salsola laricifolia protoplasts using response surface methodology and artificial neural network modeling.Plant methods · 2024Article
- Selection and evaluation of dual reference genes in silkwormScience progressArticle
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here, we devised a strategy to select appropriate reference genes for a specific clinical/experimental setting based on publicly available transcriptomic datasets and a pipeline for RT-qPCR assay design and validation. As a proof-of-principle, we applied this strategy to identify and validate reference genes for transcriptional studies of bone-marrow plasma cells from patients with AL amyloidosis. We performed a systematic review of published literature to compile a list of 163 candidate reference genes for RT-qPCR experiments employing human samples. Next, we interrogated the Gene Expression Omnibus to assess expression levels of these genes in published transcriptomic studies on bone-marrow plasma cells from patients with different plasma cell dyscrasias and identified the most stably expressed genes as candidate normalizing genes. Experimental validation on bone-marrow plasma cells showed the superiority of candidate reference genes identified through this strategy over commonly employed "housekeeping" genes. The strategy presented here may apply to other clinical and experimental settings for which publicly available transcriptomic datasets are available.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.