Temporal and spatial transcriptional programs in murine kidney development

physiological genomics ( PG ) publishes, on a quarterly basis, brief editorial perspectives entitled “Physiological genomics in PG and beyond.” These editorial perspectives provide brief, accessible highlights of the studies published in PG in the most recent quarter, and relate those studies to

Widespread use of microarray technology that led to highly complex datasets often is addressing similar or related biological questions. In translational medicine research is often based on measurements that have been obtained at different points in time. However, the researcher looks at them as a progression over time. If a biological stimulus shows an effect on a particular gene that is reversed over time, this would show, for instance, as a peak in the gene's temporal expression profile. Our program SPOT helps researchers find these patterns in large sets of microarray data. We created the software tool using open-source platforms and the Semantic Web tool Protégé-OWL.

Overexpression of Robo2 causes defects in the recruitment of metanephric mesenchymal cells and ureteric bud branching morphogenesis

Essential roles of Sall1 in kidney development

Rho kinase acts at separate steps in ureteric bud and metanephric mesenchyme morphogenesis during kidney development

The significance of Itga8 and Vangl2 in kidney development: Insights from yotari mice.

Immunohistochemical expression pattern of RIP5, FGFR1, FGFR2 and HIP2 in the normal human kidney development

High throughput gene expression analysis using qPCR is commonly used to identify molecular markers of complex cellular processes. However, statistical analysis of multi-dimensional, temporal gene expression data is complicated by limited biological replicates and large number of measurements. Moreover, many available statistical tools for analysis of time series data assume that the data sequence is static and does not evolve over time. With this assumption, the parameters used to model the time series are fixed and thus, can be estimated by pooling data together. However, in many cases, dynamic processes of biological systems involve abrupt changes at unknown time points, making the assumption of stationary time series break down. We addressed this problem using a combination of statistical methods including hierarchical clustering, change point detection, and multiple testing. We applied this multi-step method to multi-dimensional, temporal gene expression data that resulted from our study of colony size-dependent neural cell differentiation of stem cells. The gene expression data were time series as the observations were recorded sequentially over time. Hierarchical clustering segregated the genes into three distinct clusters based on their temporal expression profiles; change point detection identified specific time points at which the entire dataset was divided into several homogenous subsets to allow a separate analysis of each subset; and multiple testing procedure identified the differentially expressed genes in each cluster within each subset of data. We established that our multi-step approach pinpoints specific sets of genes that underlie colony size-mediated neural differentiation of stem cells and demonstrated its advantages over conventional parametric and non-parametric tests that do not take into account temporal dynamics of the data. Importantly, our proposed approach is broadly applicable to any multivariate data sets of limited sample size from high throughput and high content screening such as in drug and biomarker discovery studies.

Chapter 4 - RET Signaling in Ureteric Bud Formation and Branching

The kidney develops through mutual interactions between the metanephric mesenchyme and the ureteric bud, the former of which contains nephron progenitors that give rise to glomeruli and renal tubules. Bone morphogenetic protein (BMP) signaling and its modifiers play important roles in many steps of kidney development. BMP4 inhibits ureteric bud attraction, and the BMP antagonist Gremlin is essential for the initial stage of ureteric budding. During mid-gestation, BMP7 maintains the nephron progenitors and, at the same time, sensitizes them to the ureteric bud-derived differentiation signal. Crossveinless2 is a pro-BMP factor, and its absence leads to kidney hypoplasia. After birth, when nephron progenitors have disappeared, Dullard, a phosphatase that inactivates BMP receptors, keeps BMP signaling at an appropriate level. Deletion of Dullard results in excessive BMP signaling and apoptosis of the postnatal nephrons. In this review I discuss the similarities and differences of BMP functions in kidney development, as well as in diseases.

This chapter reviews some currently available methodologies for constructing mathematical models in kidney development. Mammalian nephrogenesis is a complex biological process, which in its earliest stages involves migration, condensation, proliferation, and differentiation of metanephric mesenchymal (MM) cells interacting with the uroepithelial cells of the ureteric bud (UB). First, the mathematical modelling in biology is generally described. Secondly, some accounts to biological pattern formation in modelling are given in general, including models that transcend the Turing model. This is followed by a short assessment on the main branch of models in the kidney development, the evaluation of the branching morphogenesis of the kidney. Finally, two alternative models in the early kidney development processes are given as an example. They also elucidate the difficulties in the model building process. Firstly, a computational model building with the CompuCell3D program for the early nephron progenitor cell movements with the key extracellular signaling effectors is depicted. This collective migration leads to the first pretubular aggregate (PTA). The simulation parameters of the program imitate the program's cell sorting example with different adhesions and chemoattractants. The program utilizes Cellular Potts Model (CPM) to describe the development. Secondly, an example of PTA to renal vesicle (RV) transition modelling is described. In that case, the model is unique, where the model process is based on the chemoattractants from UB.

DNA microarray technology provides a powerful vehicle for exploring biological processes on a genomic scale. Machine-learning approaches such as association rule mining (ARM) have been proven very effective in extracting biologically relevant associations among different genes. Despite of the usefulness of ARM, time relations among associated genes cannot be modeled with a standard ARM approach, though temporal information is critical for the understanding of regulatory mechanisms in biological processes. Sequential rule mining (SRM) methods have been proposed for mining temporal relations in temporal data instead. Although successful, existing SRM applications on temporal microarray data have been exclusively designed for in vitro experiments in yeast and none extension to in vivo data sets has been proposed to date. Contrary to what happen with in vitro experiments, when dealing with microarray data derived from humans or animals the “subject variability” is the main issue to address, so that databases include multiple sequences instead of a single one. A wide variety of SRM approaches could be used to handle with these particularities. In this study, we propose an adaptation of the particular SRM method “CMRules” to extract sequential association rules from temporal gene expression data derived from humans. In addition to the data mining process, we further propose the validation of extracted rules through the integration of results along with external resources of biological knowledge (functional and pathway annotation databases). The employed data set consists on temporal gene expression data collected in three different time points during the course of a dietary intervention in 57 subjects with obesity (data set available with identifier GSE77962 in the Gene Expression Omnibus repository). Published by Vink [1], the original clinical trial investigated the effects on weight loss of two different dietary interventions (a low-calorie diet or a very low-calorie diet). In conclusion, the proposed method demonstrated a good ability to extract sequential association rules with further biological relevance within the context of obesity. Thus, the application of this method could be successfully extended to other longitudinal microarray data sets derived from humans.

Mammalian nephrogenesis constitutes a series of complex developmental processes in which there is a differentiation and rapid proliferation of pluripotent cells leading to the formation of a defined sculpted tissue mass, and this is followed by a continuum of cell replication and terminal differentiation. Metanephrogenesis ensues with the intercalation of epithelial ureteric bud into loosely organized metanephric mesenchyme. Such an interaction is reciprocal, such that the intercalating ureteric bud induces the conversion of metanephric mesenchyme into an epithelial phenotype, while the mesenchyme stimulates the iterations of the ureteric bud. The induced mesenchyme then undergoes a series of developmental stages to form a mature glomerulus and tubular segments of the kidney. Coincidental with the formation of these nephric elements, the developing kidney is vascularized by the process of vasculogenesis and angiogenesis. Thus, the process of metanephric development is quite complex, and it involves a diverse group of molecules who's biological activities are inter-linked with one another and they regulate, in a concerted manner, the differentiation and maturation of the mammalian kidney. This diverse group of molecules include extracellular matrix (ECM) proteins and their receptors, ECM-degrading enzymes and their inhibitors, growth factors and their receptors, proto-oncogenes and transcription factors. A large body of literature data are available, which suggest a critical role of these molecules in metanephric development, and this review summarizes the recent developments that relate to metanephrogenesis.

c-kit delineates a distinct domain of progenitors in the developing kidney

Implication of Wt1 in the Pathogenesis of Nephrogenic Failure in a Mouse Model of Retinoic Acid-Induced Caudal Regression Syndrome