ArticleProceedings of the National Academy of Sciences of the United States of America2020
Pheno-RNA, a method to associate genes with a specific phenotype, identifies genes linked to cellular transformation.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- Omics-driven plant breeding through phenomics-enviromics crosstalk.Nature communications · 2026Review
- Opportunities for RNA sequencing in physiology: from big data to understanding homeostasis and heterogeneity.Function (Oxford, England) · 2026Review
- From biogenesis to host modulation: the expanding biology of oral streptococcal membrane vesicles.FEMS microbiology reviews · 2026Review
- Changes in leaf economic trait relationships across a precipitation gradient are related to differential gene expression in a CThe New phytologist · 2025Article
- Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine.Annual review of biomedical data science · 2024Review
- Environmental influences on Streptococcus sanguinis membrane vesicle biogenesis.The ISME journal · 2023Article
- RNA-seq transcriptome profiling of pigs' liver in response to diet with different sources of fatty acids.Frontiers in genetics · 2023Article
- Intermittent glucocorticoid treatment enhances skeletal muscle performance through sexually dimorphic mechanisms.The Journal of clinical investigation · 2022Article
- Evaluation of twoMolecular therapy. Methods & clinical development · 2021Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Cellular transformation is associated with dramatic changes in gene expression, but it is difficult to determine which regulated genes are oncogenically relevant. Here we describe Pheno-RNA, a general approach to identifying candidate genes associated with a specific phenotype. Specifically, we generate a "phenotypic series" by treating a nontransformed breast cell line with a wide variety of molecules that induce cellular transformation to various extents. By performing transcriptional profiling across this phenotypic series, the expression profile of every gene can be correlated with the strength of the transformed phenotype. We identify ∼200 genes whose expression profiles are very highly correlated with the transformation phenotype, strongly suggesting their importance in transformation. Within biological categories linked to cancer, some genes show high correlations with the transformed phenotype, but others do not. Many genes whose expression profiles are highly correlated with transformation have never been associated with cancer, suggesting the involvement of heretofore unknown genes in cancer.
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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 OpenQuestion graph.