Housekeeping and tissue-specific genes in mouse tissues

Notch inhibits osteoblast differentiation and causes osteopenia

Notch receptors are determinants of cell fate decisions. To define the role of Notch in the adult skeleton, we created transgenic mice overexpressing the Notch intracellular domain (NICD) under the control of the type I collagen promoter. First-generation transgenics were small and osteopenic. Bone histomorphometry revealed that NICD caused a decrease in bone volume, secondary to a reduction in trabecular number; osteoblast and osteoclast number were decreased. Low fertility of founder mice and lethality of young pups did not allow the complete establishment of transgenic lines. To characterize the effect of Notch overexpression in vitro, NICD was induced in osteoblasts and stromal cells from Rosa(notch) mice, in which a STOP cassette flanked by lox(P) sites is upstream of NICD, by transduction with an adenoviral vector expressing Cre recombinase (Cre) under the control of the cytomegalovirus (CMV) promoter (Ad-CMV-Cre). NICD impaired osteoblastogenesis and inhibited Wnt/beta-catenin signaling. To determine the effects of notch1 deletion in vivo, mice in which notch1 was flanked by lox(P) sequences (notch1(loxP/loxP)) were mated with mice expressing Cre recombinase under the control of the osteocalcin promoter. Conditional null notch1 mice had no obvious skeletal phenotype, possibly because of rescue by notch2; however, 1-month-old females exhibited a modest increase in osteoclast surface and eroded surface. Osteoblasts from notch1(loxP/loxP) mice, transduced with Ad-CMV-Cre and transfected with Notch2 small interfering RNA, displayed increased alkaline phosphatase activity. In conclusion, Notch signaling in osteoblasts causes osteopenia and impairs osteo-blastogenesis by inhibiting the Wnt/beta-catenin pathway.

Identification of transcripts with enriched expression in the developing and adult pancreas

BACKGROUND

Despite recent advances, the transcriptional hierarchy driving pancreas organogenesis remains largely unknown, in part due to the paucity of comprehensive analyses. To address this deficit we generated ten SAGE libraries from the developing murine pancreas spanning Theiler stages 17-26, making use of available Pdx1 enhanced green fluorescent protein (EGFP) and Neurog3 EGFP reporter strains, as well as tissue from adult islets and ducts.

RESULTS

We used a specificity metric to identify 2,536 tags with pancreas-enriched expression compared to 195 other mouse SAGE libraries. We subsequently grouped co-expressed transcripts with differential expression during pancreas development using K-means clustering. We validated the clusters first using quantitative real time PCR and then by analyzing the Theiler stage 22 pancreas in situ hybridization staining patterns of over 600 of the identified genes using the GenePaint database. These were then categorized into one of the five expression domains within the developing pancreas. Based on these results we identified a cascade of transcriptional regulators expressed in the endocrine pancreas lineage and, from this, we developed a predictive regulatory network describing beta-cell development.

CONCLUSION

Taken together, this work provides evidence that the SAGE libraries generated here are a valuable resource for continuing to elucidate the molecular mechanisms regulating pancreas development. Furthermore, our studies provide a comprehensive analysis of pancreas development, and insights into the regulatory networks driving this process are revealed.

Galectins: structure, function and therapeutic potential

Galectins are a family of animal lectins that bind beta-galactosides. Outside the cell, galectins bind to cell-surface and extracellular matrix glycans and thereby affect a variety of cellular processes. However, galectins are also detectable in the cytosol and nucleus, and may influence cellular functions such as intracellular signalling pathways through protein-protein interactions with other cytoplasmic and nuclear proteins. Current research indicates that galectins play important roles in diverse physiological and pathological processes, including immune and inflammatory responses, tumour development and progression, neural degeneration, atherosclerosis, diabetes, and wound repair. Some of these have been discovered or confirmed by using genetically engineered mice deficient in a particular galectin. Thus, galectins may be a therapeutic target or employed as therapeutic agents for inflammatory diseases, cancers and several other diseases.

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.

Individual retinal progenitor cells display extensive heterogeneity of gene expression

The development of complex tissues requires that mitotic progenitor cells integrate information from the environment. The highly varied outcomes of such integration processes undoubtedly depend at least in part upon variations among the gene expression programs of individual progenitor cells. To date, there has not been a comprehensive examination of these differences among progenitor cells of a particular tissue. Here, we used comprehensive gene expression profiling to define these differences among individual progenitor cells of the vertebrate retina. Retinal progenitor cells (RPCs) have been shown by lineage analysis to be multipotent throughout development and to produce distinct types of daughter cells in a temporal, conserved order. A total of 42 single RPCs were profiled on Affymetrix arrays. In situ hybridizations performed on both retinal sections and dissociated retinal cells were used to validate the results of the microarrays. An extensive amount of heterogeneity in gene expression among RPCs, even among cells isolated from the same developmental time point, was observed. While many classes of genes displayed heterogeneity of gene expression, the expression of transcription factors constituted a significant amount of the observed heterogeneity. In contrast to previous findings, individual RPCs were found to express multiple bHLH transcription factors, suggesting alternative models to those previously developed concerning how these factors may be coordinated. Additionally, the expression of cell cycle related transcripts showed differences among those associated with G2 and M, versus G1 and S phase, suggesting different levels of regulation for these genes. These data provide insights into the types of processes and genes that are fundamental to cell fate choices, proliferation decisions, and, for cells of the central nervous system, the underpinnings of the formation of complex circuitry.

Using generalized procrustes analysis (GPA) for normalization of cDNA microarray data

BACKGROUND

Normalization is essential in dual-labelled microarray data analysis to remove non-biological variations and systematic biases. Many normalization methods have been used to remove such biases within slides (Global, Lowess) and across slides (Scale, Quantile and VSN). However, all these popular approaches have critical assumptions about data distribution, which is often not valid in practice.

RESULTS

In this study, we propose a novel assumption-free normalization method based on the Generalized Procrustes Analysis (GPA) algorithm. Using experimental and simulated normal microarray data and boutique array data, we systemically evaluate the ability of the GPA method in normalization compared with six other popular normalization methods including Global, Lowess, Scale, Quantile, VSN, and one boutique array-specific housekeeping gene method. The assessment of these methods is based on three different empirical criteria: across-slide variability, the Kolmogorov-Smirnov (K-S) statistic and the mean square error (MSE). Compared with other methods, the GPA method performs effectively and consistently better in reducing across-slide variability and removing systematic bias.

CONCLUSION

The GPA method is an effective normalization approach for microarray data analysis. In particular, it is free from the statistical and biological assumptions inherent in other normalization methods that are often difficult to validate. Therefore, the GPA method has a major advantage in that it can be applied to diverse types of array sets, especially to the boutique array where the majority of genes may be differentially expressed.

Characterization of ceramide synthase 2: tissue distribution, substrate specificity, and inhibition by sphingosine 1-phosphate

Ceramide is an important lipid signaling molecule and a key intermediate in sphingolipid biosynthesis. Recent studies have implied a previously unappreciated role for the ceramide N-acyl chain length, inasmuch as ceramides containing specific fatty acids appear to play defined roles in cell physiology. The discovery of a family of mammalian ceramide synthases (CerS), each of which utilizes a restricted subset of acyl-CoAs for ceramide synthesis, strengthens this notion. We now report the characterization of mammalian CerS2. qPCR analysis reveals that CerS2 mRNA is found at the highest level of all CerS and has the broadest tissue distribution. CerS2 has a remarkable acyl-CoA specificity, showing no activity using C16:0-CoA and very low activity using C18:0, rather utilizing longer acyl-chain CoAs (C20-C26) for ceramide synthesis. There is a good correlation between CerS2 mRNA levels and levels of ceramide and sphingomyelin containing long acyl chains, at least in tissues where CerS2 mRNA is expressed at high levels. Interestingly, the activity of CerS2 can be regulated by another bioactive sphingolipid, sphingosine 1-phosphate (S1P), via interaction of S1P with two residues that are part of an S1P receptor-like motif found only in CerS2. These findings provide insight into the biochemical basis for the ceramide N-acyl chain composition of cells, and also reveal a novel and potentially important interplay between two bioactive sphingolipids that could be relevant to the regulation of sphingolipid metabolism and the opposing functions that these lipids play in signaling pathways.