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Motivation Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species. Results To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii. The underlying model is designed to capture sequence patterns and regulatory signals with minimal prior knowledge on the host organism and can be applied to a multitude of species and applications. Availability and implementation Source code (MATLAB, C) and binaries are freely available for download for non-commercial use at http://www.cs.tau.ac.il/~tamirtul/ChimeraUGEM/, and supported on macOS, Linux and Windows. Supplementary information Supplementary data are available at Bioinformatics online.

Viral genomes not only code the protein content, but also include silent, overlapping codes which are important to the regulation of the viral life cycle and affect its evolution. Due to the high density of these codes, their non-modular nature and the complex intracellular processes they encode, the ability of current approaches to decipher them is very limited. We describe the first computational-experimental pipeline for studying the effects of viral silent and non-silent information on its fitness. The pipeline was implemented to study the Porcine Circovirus type 2 (PCV2), the shortest known eukaryotic virus, and includes the following steps: (1) Based on the analyses of 2100 variants of PCV, suspected silent codes were inferred. (2) Five hundred variants of the PCV2 were designed to include various ‘smart’ silent mutations. (3) Using state of the art synthetic biology approaches, the genomes of these five hundred variants were generated. (4) Competition experiments between the variants were performed in Porcine kidney-15 (PK15) cell-lines. (5) The variant titers were analyzed based on novel next-generation sequencing (NGS) experiments. (6) The features related to the titer of the variants were inferred and their analyses enabled detection of various novel silent functional sequence and structural motifs. Furthermore, we demonstrate that 50 of the silent variants exhibit higher fitness than the wildtype in the analyzed conditions.

Motivation The COP9 signalosome is a highly conserved multi-protein complex consisting of eight subunits, which influences key developmental pathways through its regulation of protein stability and transcription. In Arabidopsis thaliana, mutations in the COP9 signalosome exhibit a number of diverse pleiotropic phenotypes. Total or partial loss of COP9 signalosome function in Arabidopsis leads to misregulation of a number of genes involved in DNA methylation, suggesting that part of the pleiotropic phenotype is due to global effects on DNA methylation. Results We determined and analyzed the methylomes and transcriptomes of both partial- and total-loss-of-function Arabidopsis mutants of the COP9 signalosome. Our results support the hypothesis that the COP9 signalosome has a global genome-wide effect on methylation and that this effect is at least partially encoded in the DNA. Our analyses suggest that COP9 signalosome-dependent methylation is related to gene expression regulation in various ways. Differentially methylated regions tend to be closer in the 3D conformation of the genome to differentially expressed genes. These results suggest that the COP9 signalosome has a more comprehensive effect on gene expression than thought before, and this is partially related to regulation of methylation. The high level of COP9 signalosome conservation among eukaryotes may also suggest that COP9 signalosome regulates methylation not only in plants but also in other eukaryotes, including humans. Supplementary information Supplementary data are available at Bioinformatics online.

Background Synthetic virology is an important multidisciplinary scientific field, with emerging applications in biotechnology and medicine, aiming at developing methods to generate and engineer synthetic viruses. In particular, many of the RNA viruses, including among others the Dengue and Zika, are widespread pathogens of significant importance to human health. The ability to design and synthesize such viruses may contribute to exploring novel approaches for developing vaccines and virus based therapies. Results Here we develop a full multidisciplinary pipeline for generation and analysis of synthetic RNA viruses and specifically apply it to Dengue virus serotype 2 (DENV-2). The major steps of the pipeline include comparative genomics of endogenous and synthetic viral strains. Specifically, we show that although the synthetic DENV-2 viruses were found to have lower nucleotide variability, their phenotype, as reflected in the study of the AG129 mouse model morbidity, RNA levels, and neutralization antibodies, is similar or even more pathogenic in comparison to the wildtype master strain. Additionally, the highly variable positions, identified in the analyzed DENV-2 population, were found to overlap with less conserved homologous positions in Zika virus and other Dengue serotypes. These results may suggest that synthetic DENV-2 could enhance virulence if the correct sequence is selected. Conclusions The approach reported in this study can be used to generate and analyze synthetic RNA viruses both on genotypic and on phenotypic level. It could be applied for understanding the functionality and the fitness effects of any set of mutations in viral RNA and for editing RNA viruses for various target applications. Electronic supplementary material The online version of this article (10.1186/s12859-018-2132-3) contains supplementary material, which is available to authorized users.

Synthetic virology is an important multidisciplinary scientific field, with emerging applications in biotechnology and medicine, aiming at developing methods to generate and engineer synthetic viruses. Here we demonstrate a full multidisciplinary pipeline for generation and analysis of synthetic RNA viruses and specifically apply it to Dengue virus type 2 (DENV-2). The major steps of the pipeline include comparative genomics of endogenous and synthetic viral strains. In particular, we show that although the synthetic DENV-2 viruses were found to have lower nucleotide variability, their phenotype, as reflected in the study of the AG129 mouse model morbidity, RNA levels, and neutralization antibodies, is similar or even more pathogenic in comparison to the wildtype master strain. These results may suggest that synthetic DENV-2 may enhance virulence if the correct sequence is selected. The approach reported here can be used for understanding the functionality and the fitness effects of any set of mutations in viral RNA. It can be also used for editing RNA viruses for various target applications.