ArticleFrontiers in microbiology2012
Identifying reference genes with stable expression from high throughput sequence data.
Article in Frontiers in microbiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Polyphosphate Polymerase-A Key Enzyme for the Phosphorus Economy of the Microalgal Cell and the Sustainable Usage of This Nutrient.Plants (Basel, Switzerland) · 2025Review
- Differences in the suitability of published honey bee (Apis mellifera) reference genes between the African subspecies Apis mellifera scutellata and European derived Apis mellifera.Molecular ecology · 2025Article
- Differential Expression of Stress Adaptation Genes in a DiatomInternational journal of molecular sciences · 2024Article
- Gene expression dynamics of natural assemblages of heterotrophic flagellates during bacterivory.Microbiome · 2023Article
- Transcriptome-Based Selection and Validation of Reference Genes for Gene Expression Analysis ofFrontiers in microbiology · 2021Article
- Pan-Cancer Analysis of TCGA Data Revealed Promising Reference Genes for qPCR Normalization.Frontiers in genetics · 2019Article
- Selection and Validation of Reference Genes for Quantitative Real-Time PCR Normalization Under Ethanol Stress Conditions inFrontiers in microbiology · 2018Article
- Article
- Evaluation and selection of reference genes for ecotoxicogenomic study of the green alga Closterium ehrenbergii using quantitative real-time PCR.Ecotoxicology (London, England) · 2015Article
- Metatranscriptome analyses indicate resource partitioning between diatoms in the field.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Genetic indicators of iron limitation in wild populations of Thalassiosira oceanica from the northeast Pacific Ocean.The ISME journal · 2015Article
- De novo assembly of Aureococcus anophagefferens transcriptomes reveals diverse responses to the low nutrient and low light conditions present during blooms.Frontiers in microbiology · 2014Article
- High-throughput identification of reference genes for research and clinical RT-qPCR analysis of breast cancer samples.Journal of clinical bioinformatics · 2013Article
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Authors and funding
6 authors.
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Abstract
Genes that are constitutively expressed across multiple environmental stimuli are crucial to quantifying differentially expressed genes, particularly when employing quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) assays. However, the identification of these potential reference genes in non-model organisms is challenging and is often guided by expression patterns in distantly related organisms. Here, transcriptome datasets from the diatom Thalassiosira pseudonana grown under replete, phosphorus-limited, iron-limited, and phosphorus and iron co-limited nutrient regimes were analyzed through literature-based searches for homologous reference genes, k-means clustering, and analysis of sequence counts (ASC) to identify putative reference genes. A total of 9759 genes were identified and screened for stable expression. Literature-based searches surveyed 18 generally accepted reference genes, revealing 101 homologs in T. pseudonana with variable expression and a wide range of mean tags per million. k-means analysis parsed the whole transcriptome into 15 clusters. The two most stable clusters contained 709 genes, but still had distinct patterns in expression. ASC analyses identified 179 genes that were stably expressed (posterior probability < 0.1 for 1.25 fold change). Genes known to have a stable expression pattern across the test treatments, like actin, were identified in this pool of 179 candidate genes. ASC can be employed on data without biological replicates and was more robust than the k-means approach in isolating genes with stable expression. The intersection of the genes identified through ASC with commonly used reference genes from the literature suggests that actin and ubiquitin ligase may be useful reference genes for T. pseudonana and potentially other diatoms. With the wealth of transcriptome sequence data becoming available, ASC can be easily applied to transcriptome datasets from other phytoplankton to identify reference genes.
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