ArticleBiomedical engineering online2017
Automated identification of reference genes based on RNA-seq data.
Article in Biomedical engineering online, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Selection of reference genes for quantitative PCR: identifying reference genes for airway epithelial cells exposed toAmerican journal of physiology. Lung cellular and molecular physiology · 2020Pooled it
- Screening of reliable reference genes for the normalization of RT-qPCR in chicken liver tissues and LMH cells.Scientific reports · 2024Article
- Genomic and Transcriptomic Insights into the Genetic Basis of Foam Secretion in Rice SpittlebugInternational journal of molecular sciences · 2024Article
- Effects of TmTak1 silencing on AMP production as an Imd pathway component in Tenebrio molitor.Scientific reports · 2023Article
- OliveAtlas: A Gene Expression Atlas Tool forPlants (Basel, Switzerland) · 2023Article
- TheJournal of fungi (Basel, Switzerland) · 2023Article
- RNA-Seq is not required to determine stable reference genes for qPCR normalization.PLoS computational biology · 2022Article
- Identification of stably expressed reference genes for expression studies inFrontiers in plant science · 2022Article
- Investigation of chicken housekeeping genes using next-generation sequencing data.Frontiers in genetics · 2022Article
- Xyloglucan processing machinery in Xanthomonas pathogens and its role in the transcriptional activation of virulence factors.Nature communications · 2021Article
- Article
- Selection of Suitable Reference Genes for qRT-PCR Gene Expression Studies in Rice.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Differential expression of genes in olive leaves and buds of ON- versus OFF-crop trees.Scientific reports · 2020Article
- S100A4 mRNA-protein relationship uncovered by measurement noise reduction.Journal of molecular medicine (Berlin, Germany) · 2020Article
- Reference gene selection and validation for mRNA expression analysis by RT-qPCR in murine M1- and M2-polarized macrophage.Molecular biology reports · 2020Article
- Selection of suitable reference genes for gene expression studies in myxosporean (Myxozoa, Cnidaria) parasites.Scientific reports · 2019Article
- Genome wide search to identify reference genes candidates for gene expression analysis in Gossypium hirsutum.BMC plant biology · 2019Article
- Pan-Cancer Analysis of TCGA Data Revealed Promising Reference Genes for qPCR Normalization.Frontiers in genetics · 2019Article
- Identification and Functional Annotation of Genes Differentially Expressed in the Reproductive Tissues of the Olive Tree (Frontiers in plant science · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene expression analyses demand appropriate reference genes (RGs) for normalization, in order to obtain reliable assessments. Ideally, RG expression levels should remain constant in all cells, tissues or experimental conditions under study. Housekeeping genes traditionally fulfilled this requirement, but they have been reported to be less invariant than expected; therefore, RGs should be tested and validated for every particular situation. Microarray data have been used to propose new RGs, but only a limited set of model species and conditions are available; on the contrary, RNA-seq experiments are more and more frequent and constitute a new source of candidate RGs.
resultsAn automated workflow based on mapped NGS reads has been constructed to obtain highly and invariantly expressed RGs based on a normalized expression in reads per mapped million and the coefficient of variation. This workflow has been tested with Roche/454 reads from reproductive tissues of olive tree (Olea europaea L.), as well as with Illumina paired-end reads from two different accessions of Arabidopsis thaliana and three different human cancers (prostate, small-cell cancer lung and lung adenocarcinoma). Candidate RGs have been proposed for each species and many of them have been previously reported as RGs in literature. Experimental validation of significant RGs in olive tree is provided to support the algorithm.
conclusionRegardless sequencing technology, number of replicates, and library sizes, when RNA-seq experiments are designed and performed, the same datasets can be analyzed with our workflow to extract suitable RGs for subsequent PCR validation. Moreover, different subset of experimental conditions can provide different suitable RGs.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.