ArticleBMC medical genomics2019
Defining housekeeping genes suitable for RNA-seq analysis of the human allograft kidney biopsy tissue.
Article in BMC medical genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 77 citations in OpenAlex.
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- Identification of Important Modules and Hub Gene in Chronic Kidney Disease Based on WGCNA.Journal of immunology research · 2022Article
- Development of an RNA sequencing panel to detect gene fusions in thyroid cancer.Genomics & informatics · 2021Article
- In-silico performance, validation, and modeling of the Nanostring Banff Human Organ transplant gene panel using archival data from human kidney transplants.BMC medical genomics · 2021Article
- Variable expression of eighteen common housekeeping genes in human non-cancerous kidney biopsies.PloS one · 2021Article
- Technical considerations when designing a gene expression panel for renal transplant diagnosis.Scientific reports · 2020Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundRNA-seq is poised to play a major role in the management of kidney transplant patients. Rigorous definition of housekeeping genes (HKG) is essential for further progress in this field. Using single genes or a limited set HKG is inherently problematic since their expression might be altered by specific diseases in the patients being studied.
methodsTo generate a HKG set specific for kidney transplantation, we performed RNA-sequencing from renal allograft biopsies collected in a variety of clinical settings. Various normalization methods were applied to identify transcripts that had a coefficient of variation of expression that was below the 2nd percentile across all samples, and the corresponding genes were designated as housekeeping genes. Comparison with transcriptomic data from the Gene Expression Omnibus (GEO) database, pathway analysis and molecular biological functions were utilized to validate the housekeeping genes set.
resultsWe have developed a bioinformatics solution to this problem by using nine different normalization methods to derive large HKG gene sets from a RNA-seq data set of 47,611 transcripts derived from 30 biopsies. These biopsies were collected in a variety of clinical settings, including normal function, acute rejection, interstitial nephritis, interstitial fibrosis/tubular atrophy and polyomavirus nephropathy. Transcripts with coefficient of variation below the 2nd percentile were designated as HKG, and validated by showing their virtual absence in diseased allograft derived transcriptomic data sets available in the GEO. Pathway analysis indicated a role for these genes in maintenance of cell morphology, pyrimidine metabolism, and intracellular protein signaling.
conclusionsUtilization of these objectively defined HKG data sets will guard against errors resulting from focusing on individual genes like 18S RNA, actin & tubulin, which do not maintain constant expression across the known spectrum of renal allograft pathology.
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