Volume 16, Issue 4 - Special Section: “15th International Symposium on Integrative Bioinformatics, Paris, France, 2019 / Guest Editor: Cyril Pommier”

Genetic variance within the genotype of population and its mapping to phenotype variance in a systematic and high throughput manner is of interest for biodiversity and breeding research. Beside the established and efficient high throughput genotype technologies, phenotype capabilities got increased focus in the last decade. This results in an increasing amount of phenotype data from well scaling, automated sensor platform. Thus, data stewardship is a central component to make experimental data from multiple domains interoperable and re-usable. To ensure a standard and comprehensive sharing of scientific and experimental data among domain experts, FAIR data principles are utilized for machine read-ability and scale-ability. In this context, BrAPI consortium, provides a comprehensive and commonly agreed FAIRed guidelines to offer a BrAPI layered scientific data in a RESTful manner. This paper presents the concepts, best practices and implementations to meet these challenges. As one of the worlds leading plant research institutes it is of vital interest for the IPK-Gatersleben to transform legacy data infrastructures into a bio-digital resource center for plant genetics resources (PGR). This paper also demonstrates the benefits of integrated database back-ends, established data stewardship processes, and FAIR data exposition in a machine-readable, highly scalable programmatic interfaces.

JIB.tools 2.0 is a new approach to more closely embed the curation process in the publication process. This website hosts the tools, software applications, databases and workflow systems published in the Journal of Integrative Bioinformatics (JIB). As soon as a new tool-related publication is published in JIB, the tool is posted to JIB.tools and can afterwards be easily transferred to bio.tools, a large information repository of software tools, databases and services for bioinformatics and the life sciences. In this way, an easily-accessible list of tools is provided which were published in JIB a well as status information regarding the underlying service. With newer registries like bio.tools providing these information on a bigger scale, JIB.tools 2.0 closes the gap between journal publications and registry publication. (Reference: https://jib.tools).

The infection mechanism and pathogenicity of Human T-lymphotropic virus 1 (HTLV-1) are ambiguously known for hundreds of years. Our knowledge about this virus is recently emerging. The purpose of the study is to design a vaccine targeting the envelope glycoprotein, GP62, an outer membrane protein of HTLV-1 that has an increased number of epitope binding sites. Data collection, clustering and multiple sequence alignment of HTLV-1 glycoprotein B, variability analysis of envelope Glycoprotein GP62 of HTLV-1, population protection coverage, HLA-epitope binding prediction, and B-cell epitope prediction were performed to predict an effective vaccine. Among all the predicted peptides, ALQTGITLV and VPSSSTPL epitopes interact with three MHC alleles. The summative population protection coverage worldwide by these epitopes as vaccine candidates was found nearly 70%. The docking analysis revealed that ALQTGITLV and VPSSSTPL epitopes interact strongly with the epitope-binding groove of HLA-A*02:03, and HLA-B*35:01, respectively, as this HLA molecule was found common with which every predicted epitope interacts. Molecular dynamics simulations of the docked complexes show they form stable complexes. So, these potential epitopes might pave the way for vaccine development against HTLV-1.

In this article, we propose a semi-automated method to rebuild genome ancestors of chloroplasts by taking into account gene duplication. Two methods have been used in order to achieve this work: a naked eye investigation using homemade scripts, whose results are considered as a basis of knowledge, and a dynamic programming based approach similar to Needleman-Wunsch. The latter fundamentally uses the Gestalt pattern matching method of sequence matcher to evaluate the occurrences probability of each gene in the last common ancestor of two given genomes. The two approaches have been applied on chloroplastic genomes from Apiales , Asterales , and Fabids orders, the latter belonging to Pentapetalae group. We found that Apiales species do not undergo indels, while they occur in the Asterales and Fabids orders. A series of experiments was then carried out to extensively verify our findings by comparing the obtained ancestral reconstruction results with the latest released approach called MLGO (Maximum Likelihood for Gene-Order analysis).

Functional coupling and comparative genomics analysis have been applied to study functional associations of orthologs of enterococcal cAD1 sex pheromone (P13268) known to be responsible for biofilm formation, conjugative plasmid transfer and spreading of bacterial antibiotics resistance. cAD1 peptide pheromone is released from the membrane lipoprotein with the peptide precursor encoded by a gene cad (tr|C2JQE7). Our analysis of genomic neighbourhood of cad and motifs of the encoded polypeptide and its orthologs suggests a close functional association between cAD1 and ApbE protein (Q82Z24), a FMN insertion and trafficking facilitator. The cad and apbE orthologs were coupled in the genomes and ApbE-specific motifs for FMN covalent attachment were identified in cad -encoded protein sequence and its orthologs. These findings suggest a potential role of FMN-based reductase function of the cAD1 lipoprotein precursor in its processing and release of the active sex pheromone peptide. They may lead to a new approach in prevention of antibiotic resistance spread via targeting sex pheromone processing chaperones or by suppression of the FMN availability and covalent binding. This methods can be also applied to a controlled evolution of bacterial pathogenicity in microbial fuel cells, as the findings suggest the crosstalk between bacterial pathogenicity and bacterial electro-activity.

Modern high-throughput experiments provide us with numerous potential associations between genes and diseases. Experimental validation of all the discovered associations, let alone all the possible interactions between them, is time-consuming and expensive. To facilitate the discovery of causative genes, various approaches for prioritization of genes according to their relevance for a given disease have been developed. In this article, we explain the gene prioritization problem and provide an overview of computational tools for gene prioritization. Among about a hundred of published gene prioritization tools, we select and briefly describe 14 most up-to-date and user-friendly. Also, we discuss the advantages and disadvantages of existing tools, challenges of their validation, and the directions for future research.