Bicaudal C1 promotes pancreatic NEUROG3+ endocrine progenitor differentiation and ductal morphogenesis.

In human, mutations in bicaudal C1 (BICC1), an RNA binding protein, have been identified in patients with kidney dysplasia. Deletion of Bicc1 in mouse leads to left-right asymmetry randomization and renal cysts. Here, we show that BICC1 is also expressed in both the pancreatic progenitor cells that line the ducts during development, and in the ducts after birth, but not in differentiated endocrine or acinar cells. Genetic inactivation of Bicc1 leads to ductal cell over-proliferation and cyst formation. Transcriptome comparison between WT and Bicc1 KO pancreata, before the phenotype onset, reveals that PKD2 functions downstream of BICC1 in preventing cyst formation in the pancreas. Moreover, the analysis highlights immune cell infiltration and stromal reaction developing early in the pancreas of Bicc1 knockout mice. In addition to these functions in duct morphogenesis, BICC1 regulates NEUROG3(+) endocrine progenitor production. Its deletion leads to a late but sustained endocrine progenitor decrease, resulting in a 50% reduction of endocrine cells. We show that BICC1 functions downstream of ONECUT1 in the pathway controlling both NEUROG3(+) endocrine cell production and ductal morphogenesis, and suggest a new candidate gene for syndromes associating kidney dysplasia with pancreatic disorders, including diabetes.

HTSstation: a web application and open-access libraries for high-throughput sequencing data analysis.

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch.

Spatially and genetically distinct control of seed germination by phytochromes A and B.

Phytochromes phyB and phyA mediate a remarkable developmental switch whereby, early upon seed imbibition, canopy light prevents phyB-dependent germination, whereas later on, it stimulates phyA-dependent germination. Using a seed coat bedding assay where the growth of dissected embryos is monitored under the influence of dissected endosperm, allowing combinatorial use of mutant embryos and endosperm, we show that canopy light specifically inactivates phyB activity in the endosperm to override phyA-dependent signaling in the embryo. This interference involves abscisic acid (ABA) release from the endosperm and distinct spatial activities of phytochrome signaling components. Under the canopy, endospermic ABA opposes phyA signaling through the transcription factor (TF) ABI5, which shares with the TF PIF1 several target genes that negatively regulate germination in the embryo. ABI5 enhances the expression of phytochrome signaling genes PIF1, SOMNUS, GAI, and RGA, but also of ABA and gibberellic acid (GA) metabolic genes. Over time, weaker ABA-dependent responses eventually enable phyA-dependent germination, a distinct type of germination driven solely by embryonic growth.

High-throughput analysis of promoter occupancy reveals new targets for Arx, a gene mutated in mental retardation and interneuronopathies.

Genetic investigations of X-linked intellectual disabilities have implicated the ARX (Aristaless-related homeobox) gene in a wide spectrum of disorders extending from phenotypes characterised by severe neuronal migration defects such as lissencephaly, to mild or moderate forms of mental retardation without apparent brain abnormalities but with associated features of dystonia and epilepsy. Analysis of Arx spatio-temporal localisation profile in mouse revealed expression in telencephalic structures, mainly restricted to populations of GABAergic neurons at all stages of development. Furthermore, studies of the effects of ARX loss of function in humans and animal models revealed varying defects, suggesting multiple roles of this gene during brain development. However, to date, little is known about how ARX functions as a transcription factor and the nature of its targets. To better understand its role, we combined chromatin immunoprecipitation and mRNA expression with microarray analysis and identified a total of 1006 gene promoters bound by Arx in transfected neuroblastoma (N2a) cells and in mouse embryonic brain. Approximately 24% of Arx-bound genes were found to show expression changes following Arx overexpression or knock-down. Several of the Arx target genes we identified are known to be important for a variety of functions in brain development and some of them suggest new functions for Arx. Overall, these results identified multiple new candidate targets for Arx and should help to better understand the pathophysiological mechanisms of intellectual disability and epilepsy associated with ARX mutations.

A parallel scheme for comparing transcription factor binding sites matrices.

Gene regulation implies many mechanisms. Their identification is a crucial task to construct regulatory networks, and is necessary to understand the pathology in many cases. This requires the identification of transcription factors that play a role in regulation. Numerous motif discovery tools are now available. Combining efficiently their results appears useful for comparing and clustering these motifs in order to reduce redundancies and to identify the corresponding transcription factor. We develop a method that produces, compares and clusters a set of motifs and identifies some close motifs in databases like JASPAR and the public version of Transfac. Unlike previous comparison methods, where each matrix column is compared independently, we have developed a global method to compare motifs that also helps to reduce the number of false positives. We also propose an original graph motif model that generalizes the classical position specific pattern matrices. Finally, we present an application of our method to study ChIP-chip data sets in the context of an eukaryotic organism.