Odelin, G. | Search bioRxiv

bioRxiv2018

Ectopic expression of Hoxb1 induces cardiac and craniofacial malformations

Members of the large family of Hox transcription factors are encoded by genes whose tightly regulated expression in development and in space within different embryonic tissues confer positional identity from the neck to the tips of the limbs. Many structures of the face, head and heart develop from cell populations expressing few or no Hox genes. Hoxb1 is the member of its chromosomal cluster expressed in the most rostral domain during vertebrate development, but never by the multipotent neural crest cell population anterior to the cerebellum. We have developed a novel floxed transgenic mouse line, CAG-Hoxb1,-EGFP (CAG-Hoxb1), which upon recombination by Cre recombinase conditionally induces robust Hoxb1 and eGFP over-expression. When induced within the neural crest lineage, pups die at birth. A variable phenotype develops from E11.5 on, associating frontonasal hypoplasia/aplasia, micrognathia/agnathia, major ocular and forebrain anomalies, and cardiovascular malformations. Neural crest derivatives in the body appear unaffected. Transcription of effectors of developmental signaling pathways (Bmp, Shh, Vegfa) and transcription factors (Pax3, Sox9) is altered in mutants. These outcomes emphasize that repression of Hoxb1, along with other paralog group 1 and 2 Hox genes, is strictly necessary in anterior cephalic NC for craniofacial, visual, auditory and cardiovascular development.

developmental biology↗

bioRxiv2017

Random Walk With Restart On Multiplex And Heterogeneous Biological Networks

Recent years have witnessed an exponential growth in the number of identified interactions between biological molecules. These interactions are usually represented as large and complex networks, calling for the development of appropriated tools to exploit the functional information they contain. Random walk with restart is the state-of-the-art guilt-by-association approach. It explores the network vicinity of gene/protein seeds to study their functions, based on the premise that nodes related to similar functions tend to lie close to each others in the networks.\n\nIn the present study, we extended the random walk with restart algorithm to multiplex and heterogeneous networks. The walk can now explore different layers of physical and functional interactions between genes and proteins, such as protein-protein interactions and co-expression associations. In addition, the walk can also jump to a network containing different sets of edges and nodes, such as phenotype similarities between diseases.\n\nWe devised a leave-one-out cross-validation strategy to evaluate the algorithms abilities to predict disease-associated genes. We demonstrate the increased performances of the multiplex-heterogeneous random walk with restart as compared to several random walks on monoplex or heterogeneous networks. Overall, our framework is able to leverage the different interaction sources to outperform current approaches.\n\nFinally, we applied the algorithm to predict genes candidate for being involved in the Wiedemann-Rautenstrauch syndrome, and to explore the network vicinity of the SHORT syndrome.\n\nThe source code and the software are freely available at: https://github.com/alberto-valdeolivas/RWR-MH.

systems biology↗