Spontaneous gene flow from rapeseed (Brassica napus) to wild Brassica oleracea.

Research on the environmental risks of gene flow from genetically modified (GM) crops to wild relatives has traditionally emphasized recipients yielding most hybrids. For GM rapeseed (Brassica napus), interest has centred on the 'frequently hybridizing' Brassica rapa over relatives such as Brassica oleracea, where spontaneous hybrids are unreported in the wild. In two sites, where rapeseed and wild B. oleracea grow together, we used flow cytometry and crop-specific microsatellite markers to identify one triploid F1 hybrid, together with nine diploid and two near triploid introgressants. Given the newly discovered capacity for spontaneous introgression into B. oleracea, we then surveyed associated flora and fauna to evaluate the capacity of both recipients to harm cohabitant species with acknowledged conservational importance. Only B. oleracea occupies rich communities containing species afforded legislative protection; these include one rare micromoth species that feeds on B. oleracea and warrants further assessment. We conclude that increased attention should now focus on B. oleracea and similar species that yield few crop-hybrids, but possess scope to affect rare or endangered associates.

Design and construction of a versatile synthetic network for bistable gene expression in mammalian systems.

We constructed and modeled a novel synthetic network which may be able to exhibit bistable expression of a reporter gene in mammalian cells. This network is based on an aptamer-fused short-hairpin RNA (shRNA) directed against a single mRNA encoding both a EGFP reporter gene and the repressor tTR-KRAB, which, in turn, represses transcription of the shRNA. The activity of the shRNA can be controlled by an inducer molecule (theophylline) which prevents the aptamer-fused shRNA to be properly processed. Repression of the tTR-KRAB can be relieved by treatment with doxycyline. This reciprocal negative feed-back loop can exhibit a bistable response, as shown through the mathematical analysis performed here. Specifically, the network can be controlled to induce sustained expression of a shRNA, or the reporter gene, with a transient input of two different inducer molecules.

Modeling RNA interference in mammalian cells.

BACKGROUND: RNA interference (RNAi) is a regulatory cellular process that controls post-transcriptional gene silencing. During RNAi double-stranded RNA (dsRNA) induces sequence-specific degradation of homologous mRNA via the generation of smaller dsRNA oligomers of length between 21-23nt (siRNAs). siRNAs are then loaded onto the RNA-Induced Silencing multiprotein Complex (RISC), which uses the siRNA antisense strand to specifically recognize mRNA species which exhibit a complementary sequence. Once the siRNA loaded-RISC binds the target mRNA, the mRNA is cleaved and degraded, and the siRNA loaded-RISC can degrade additional mRNA molecules. Despite the widespread use of siRNAs for gene silencing, and the importance of dosage for its efficiency and to avoid off target effects, none of the numerous mathematical models proposed in literature was validated to quantitatively capture the effects of RNAi on the target mRNA degradation for different concentrations of siRNAs. Here, we address this pressing open problem performing in vitro experiments of RNAi in mammalian cells and testing and comparing different mathematical models fitting experimental data to in-silico generated data. We performed in vitro experiments in human and hamster cell lines constitutively expressing respectively EGFP protein or tTA protein, measuring both mRNA levels, by quantitative Real-Time PCR, and protein levels, by FACS analysis, for a large range of concentrations of siRNA oligomers. RESULTS: We tested and validated four different mathematical models of RNA interference by quantitatively fitting models' parameters to best capture the in vitro experimental data. We show that a simple Hill kinetic model is the most efficient way to model RNA interference. Our experimental and modeling findings clearly show that the RNAi-mediated degradation of mRNA is subject to saturation effects. CONCLUSIONS: Our model has a simple mathematical form, amenable to analytical investigations and a small set of parameters with an intuitive physical meaning, that makes it a unique and reliable mathematical tool. The findings here presented will be a useful instrument for better understanding RNAi biology and as modelling tool in Systems and Synthetic Biology.