Identification of novel universal housekeeping genes by statistical analysis of microarray data

Identification of novel reference genes using multiplatform expression data and their validation for quantitative gene expression analysis

Normalization of mRNA levels using endogenous reference genes (ERGs) is critical for an accurate comparison of gene expression between different samples. Despite the popularity of traditional ERGs (tERGs) such as GAPDH and ACTB, their expression variability in different tissues or disease status has been reported. Here, we first selected candidate housekeeping genes (HKGs) using human gene expression data from different platforms including EST, SAGE, and microarray, and 13 novel ERGs (nERGs) (ARL8B, CTBP1, CUL1, DIMT1L, FBXW2, GPBP1, LUC7L2, OAZ1, PAPOLA, SPG21, TRIM27, UBQLN1, ZNF207) were further identified from these HKGs. The mean coefficient variation (CV) values of nERGs were significantly lower than those of tERGs and the expression level of most nERGs was relatively lower than high expressing tERGs in all dataset. The higher expression stability and lower expression levels of most nERGs were validated in 108 human samples including formalin-fixed paraffin-embedded (FFPE) tissues, frozen tissues and cell lines, through quantitative real-time RT-PCR (qRT-PCR). Furthermore, the optimal number of nERGs required for accurate normalization was as few as two, while four genes were required when using tERGs in FFPE tissues. Most nERGs identified in this study should be better reference genes than tERGs, based on their higher expression stability and fewer numbers needed for normalization when multiple ERGs are required.

Analysis of variance components reveals the contribution of sample processing to transcript variation

The proper design of DNA microarray experiments requires knowledge of biological and technical variation of the studied biological model. For the filamentous fungus Aspergillus niger, a fast, quantitative real-time PCR (qPCR)-based hierarchical experimental design was used to determine this variation. Analysis of variance components determined the contribution of each processing step to total variation: 68% is due to differences in day-to-day handling and processing, while the fermentor vessel, cDNA synthesis, and qPCR measurement each contributed equally to the remainder of variation. The global transcriptional response to d-xylose was analyzed using Affymetrix microarrays. Twenty-four statistically differentially expressed genes were identified. These encode enzymes required to degrade and metabolize D-xylose-containing polysaccharides, as well as complementary enzymes required to metabolize complex polymers likely present in the vicinity of D-xylose-containing substrates. These results confirm previous findings that the d-xylose signal is interpreted by the fungus as the availability of a multitude of complex polysaccharides. Measurement of a limited number of transcripts in a defined experimental setup followed by analysis of variance components is a fast and reliable method to determine biological and technical variation present in qPCR and microarray studies. This approach provides important parameters for the experimental design of batch-grown filamentous cultures and facilitates the evaluation and interpretation of microarray data.

A transcriptome atlas of rice cell types uncovers cellular, functional and developmental hierarchies

The functions of the plant body rely on interactions among distinct and nonequivalent cell types. The comparison of transcriptomes from different cell types should expose the transcriptional networks that underlie cellular attributes and contributions. Using laser microdissection and microarray profiling, we have produced a cell type transcriptome atlas that includes 40 cell types from rice (Oryza sativa) shoot, root and germinating seed at several developmental stages, providing patterns of cell specificity for individual genes and gene classes. Cell type comparisons uncovered previously unrecognized properties, including cell-specific promoter motifs and coexpressed cognate binding factor candidates, interaction partner candidates and hormone response centers. We inferred developmental regulatory hierarchies of gene expression in specific cell types by comparison of several stages within root, shoot and embryo.

Genomic selection of reference genes for real-time PCR in human myocardium

Background

Reliability of real-time PCR (RT-qPCR) data is dependent on the use of appropriate reference gene(s) for normalization. To date, no validated reference genes have been reported for normalizing gene expression in human myocardium. This study aimed to identify validated reference genes for use in gene expression studies of failed and non-failed human myocardium.

Methods

Bioinformatic analysis of published human heart gene expression arrays (195 failed hearts, 16 donor hearts) was used to identify 10 stable and abundant genes for further testing. The expression stability of these genes was investigated in 28 failed and 28 non-failed human myocardium samples by RT-qPCR using geNorm software.

Results

Signal recognition particle 14 kDa (SRP14), tumor protein, translationally-controlled 1 (TPT1) and eukaryotic elongation factor 1A1 (EEF1A1) were ranked the most stable genes. The commonly used reference gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was ranked the least stable of the genes tested. The normalization strategy was tested by comparing RT-qPCR data of both normalized and raw expression levels of brain natriuretic peptide precursor (NPPB), a gene known to be up-regulated in heart failure. Non-normalized levels of NPPB exhibited a marginally significant difference between failed and non-failed samples (p = 0.058). In contrast, normalized NPPB expression levels were significantly higher in heart-failed patients compared with controls (p = 0.023).

Conclusion

This study used publicly available gene array data to identify a strategy for normalization involving two reference genes in combination that may have broad application for accurate and reliable normalization of RT-qPCR data in failed and non-failed human myocardium.

A comprehensive functional analysis of tissue specificity of human gene expression

BACKGROUND

In recent years, the maturation of microarray technology has allowed the genome-wide analysis of gene expression patterns to identify tissue-specific and ubiquitously expressed ('housekeeping') genes. We have performed a functional and topological analysis of housekeeping and tissue-specific networks to identify universally necessary biological processes, and those unique to or characteristic of particular tissues.

RESULTS

We measured whole genome expression in 31 human tissues, identifying 2374 housekeeping genes expressed in all tissues, and genes uniquely expressed in each tissue. Comprehensive functional analysis showed that the housekeeping set is substantially larger than previously thought, and is enriched with vital processes such as oxidative phosphorylation, ubiquitin-dependent proteolysis, translation and energy metabolism. Network topology of the housekeeping network was characterized by higher connectivity and shorter paths between the proteins than the global network. Ontology enrichment scoring and network topology of tissue-specific genes were consistent with each tissue's function and expression patterns clustered together in accordance with tissue origin. Tissue-specific genes were twice as likely as housekeeping genes to be drug targets, allowing the identification of tissue 'signature networks' that will facilitate the discovery of new therapeutic targets and biomarkers of tissue-targeted diseases.

CONCLUSION

A comprehensive functional analysis of housekeeping and tissue-specific genes showed that the biological function of housekeeping and tissue-specific genes was consistent with tissue origin. Network analysis revealed that tissue-specific networks have distinct network properties related to each tissue's function. Tissue 'signature networks' promise to be a rich source of targets and biomarkers for disease treatment and diagnosis.

Verification of reference genes for relative quantification of gene expression by real-time reverse transcription PCR in the pig

The aim of this study was to develop a set of reliable reference genes for quantification of mRNA expression in the pig. The mRNA expression stability in pig tissues was studied for 4 genes: EEF1A1, GAPDH, HPRT1 and TOP2B. The level of expression was characterized by Ct values for each gene and each tissue. By using the geNorm algorithm, the stability of the reference genes was determined in the diaphragm, heart, kidney, liver, lungs, longissimus muscle, and spleen. On the basis of this information, suitable reference genes can be selected for mRNA expression studies in relevant pig tissues.

The transcriptome of retinal Müller glial cells

Müller glial cells are the major type of glia in the mammalian retina. To identify the molecular machinery that defines Müller glial cell identity and function, single cell gene expression profiling was performed on Affymetrix microarrays. Identification of a cluster of genes expressed at high levels suggests a Müller glia core transcriptome, which likely underlies many of the functions of Müller glia. Expression of components of the cell cycle machinery and the Notch pathway, as well as of growth factors, chemokines, and lipoproteins might allow communication between Müller glial cells and the neurons that they support, including modulation of neuronal activity. This approach revealed a set of transcripts that were not previously characterized in (Müller) glia; validation of the expression of some of these genes was performed by in situ hybridization. Genes expressed exclusively by Müller glia were identified as novel markers. In addition, a novel BAC transgenic mouse that expresses Cre in Müller glia cells was generated. The molecular fingerprint of Müller glia provides a foundation for further studies of Müller glia development and function in normal and diseased states.

Using ribosomal protein genes as reference: a tale of caution

Background

Housekeeping genes are needed in every tissue as their expression is required for survival, integrity or duplication of every cell. Housekeeping genes commonly have been used as reference genes to normalize gene expression data, the underlying assumption being that they are expressed in every cell type at approximately the same level. Often, the terms “reference genes” and “housekeeping genes” are used interchangeably. In this paper, we would like to distinguish between these terms. Consensus is growing that housekeeping genes which have traditionally been used to normalize gene expression data are not good reference genes. Recently, ribosomal protein genes have been suggested as reference genes based on a meta-analysis of publicly available microarray data.

Methodology/Principal Findings

We have applied several statistical tools on a dataset of 70 microarrays representing 22 different tissues, to assess and visualize expression stability of ribosomal protein genes. We confirmed the housekeeping status of these genes, but further estimated expression stability across tissues in order to assess their potential as reference genes. One- and two-way ANOVA revealed that all ribosomal protein genes have significant expression variation across tissues and exhibit tissue-dependent expression behavior as a group. Via multidimensional unfolding analysis, we visualized this tissue-dependency. In addition, we explored mechanisms that may cause tissue dependent effects of individual ribosomal protein genes.

Conclusions/Significance

Here we provide statistical and biological evidence that ribosomal protein genes exhibit important tissue-dependent variation in mRNA expression. Though these genes are most stably expressed of all investigated genes in a meta-analysis they cannot be considered true reference genes.

Down-regulation of ATM protein in HRS cells of nodular sclerosis Hodgkin's lymphoma in children occurs in the absence ofATMgene inactivation

The tumour component of classical Hodgkin's lymphoma (cHL), Hodgkin Reed-Sternberg (HRS) cells, are believed to be derived from germinal centre (GC) B cells but intriguingly display a characteristic loss of B cell receptor (BCR) expression. The precise mechanisms by which BCR-negative HRS cell progenitors survive negative selection during the GC reaction remain obscure. Individuals with ataxia telangiectasia, caused by biallelic inactivation of the DNA damage response gene, ataxia telangiectasia mutated (ATM), have a higher risk of cHL development. Here we show that, in contrast to normal GC B cells that expressed low but detectable ATM protein, ATM protein was not detected in HRS cells of 17/18 cases of paediatric cHL, all but one with nodular sclerosis (NS) subtype. A comprehensive analysis of the ATM gene in microdissected HRS cells of nine representative tumours showed no evidence of either loss of heterozygosity or consistent pathogenic mutations. Furthermore, bisulphite sequencing of the ATM promoter from HRS cells of five tumours also revealed the absence of hypermethylation. Since our microarray data suggested significantly reduced ATM transcription in HRS cells compared to GC B cells, we conclude that loss of ATM expression could be the result of alterations in upstream regulators of ATM transcription. Importantly, ATM loss in paediatric cHLs has clinical implications and could be potentially exploited to guide future, less toxic, tumour-specific treatments.