Beyond the simplicity of Mendelian inheritance

Elucidating the underlying rules that govern the phenotypic diversity observed in natural populations is an old but still unaccomplished goal in biology. In 1865, Gregor Mendel paved the way for the dissection of the underlying genetic basis of traits by setting out to understand the principles of heredity. To date, we still lack a global overview of the spectrum and continuum existing between Mendelian and complex traits within any natural population. In this respect, we recently performed a species-wide survey of Mendelian traits across a large population of isolates using the yeast Saccharomyces cerevisiae. By analyzing the distribution and the inheritance patterns of the trait, we have clearly shown that monogenic mutations can display a significant, variable, and continuous expressivity across different genetic backgrounds. Our study also demonstrated that combining the elegancy of both classical genetics and high-throughput genomics is more than valuable to dissect the genotype-phenotype relationship in natural populations.

An in silico target identification using Boolean network attractors: Avoiding pathological phenotypes

Target identification aims at identifying biomolecules whose function should be therapeutically altered to cure the considered pathology. An algorithm for in silico target identification using Boolean network attractors is proposed. It assumes that attractors correspond to phenotypes produced by the modeled biological network. It identifies target combinations which allow disturbed networks to avoid attractors associated with pathological phenotypes. The algorithm is tested on a Boolean model of the mammalian cell cycle and its applications are illustrated on a Boolean model of Fanconi anemia. Results show that the algorithm returns target combinations able to remove attractors associated with pathological phenotypes and then succeeds in performing the proposed in silico target identification. However, as with any in silico evidence, there is a bridge to cross between theory and practice. Nevertheless, it is expected that the algorithm is of interest for target identification.

[Targeted therapies in severe asthma: the discovery of new molecules]

The pathophysiological mechanisms involved in the chronicity and phenotypic heterogeneity of asthma offer the prospect of new therapeutic opportunities. A better clinical and biological characterisation of selected patients has led to the development of targeted therapies. Studies are under way to demonstrate their efficacy and tolerance and also their impact on the natural history of the disease. This revue aims to examine the therapies, developed during the last ten years, that are based on the immunological mechanisms involved in the pathophysiology of asthma, essentially in its severe form. The rapid expansion of human monoclonal antibodies has allowed testing of various immunological pathways. Anti-IgE, anti- IL-5, and anti-IL-13 strategies seem the most promising. Antagonists to TNF-alpha and I'IL-4 have not succeeded in reducing the events related to severe asthma in a convincing manner. Molecules targeted against thymic stromal lymphopoietin (TSLP) and I'IL-9 are under development. These approaches are involved in the development of therapeutic programmes adapted to the patient's phenotype, that is to say a personalised approach to care.