SoybeanGDB: A comprehensive genomic and bioinformatic platform for soybean genetics and genomics.

Soybean (Glycine max (L.) Merr.) is a globally significant crop, widely cultivated for oilseed production and animal feeds. In recent years, the rapid growth of multi-omics data from thousands of soybean accessions has provided unprecedented opportunities for researchers to explore genomes, genetic variations, and gene functions. To facilitate the utilization of these abundant data for soybean breeding and genetic improvement, the SoybeanGDB database (https://venyao.xyz/SoybeanGDB/) was developed as a comprehensive platform. SoybeanGDB integrates high-quality de novo assemblies of 39 soybean genomes and genomic variations among thousands of soybean accessions. Genomic information and variations in user-specified genomic regions can be searched and downloaded from SoybeanGDB, in a user-friendly manner. To facilitate research on genetic resources and elucidate the biological significance of genes, SoybeanGDB also incorporates a variety of bioinformatics analysis modules with graphical interfaces, such as linkage disequilibrium analysis, nucleotide diversity analysis, allele frequency analysis, gene expression analysis, primer design, gene set enrichment analysis, etc. In summary, SoybeanGDB is an essential and valuable resource that provides an open and free platform to accelerate global soybean research.

LIRBase: a comprehensive database of long inverted repeats in eukaryotic genomes.

Small RNAs (sRNAs) constitute a large portion of functional elements in eukaryotic genomes. Long inverted repeats (LIRs) can be transcribed into long hairpin RNAs (hpRNAs), which can further be processed into small interfering RNAs (siRNAs) with vital biological roles. In this study, we systematically identified a total of 6 619 473 LIRs in 424 eukaryotic genomes and developed LIRBase (https://venyao.xyz/lirbase/), a specialized database of LIRs across different eukaryotic genomes aiming to facilitate the annotation and identification of LIRs encoding long hpRNAs and siRNAs. LIRBase houses a comprehensive collection of LIRs identified in a wide range of eukaryotic genomes. In addition, LIRBase not only allows users to browse and search the identified LIRs in any eukaryotic genome(s) of interest available in GenBank, but also provides friendly web functionalities to facilitate users to identify LIRs in user-uploaded sequences, align sRNA sequencing data to LIRs, perform differential expression analysis of LIRs, predict mRNA targets for LIR-derived siRNAs, and visualize the secondary structure of candidate long hpRNAs encoded by LIRs. As demonstrated by two case studies, collectively, LIRBase bears the great utility for systematic investigation and characterization of LIRs and functional exploration of potential roles of LIRs and their derived siRNAs in diverse species.

Development of interactive biological web applications with R/Shiny.

Development of interactive web applications to deposit, visualize and analyze biological datasets is a major subject of bioinformatics. R is a programming language for data science, which is also one of the most popular languages used in biological data analysis and bioinformatics. However, building interactive web applications was a great challenge for R users before the Shiny package was developed by the RStudio company in 2012. By compiling R code into HTML, CSS and JavaScript code, Shiny has made it incredibly easy to build web applications for the large R community in bioinformatics and for even non-programmers. Over 470 biological web applications have been developed with R/Shiny up to now. To further promote the utilization of R/Shiny, we reviewed the development of biological web applications with R/Shiny, including eminent biological web applications built with R/Shiny, basic steps to build an R/Shiny application, commonly used R packages to build the interface and server of R/Shiny applications, deployment of R/Shiny applications in the cloud and online resources for R/Shiny.

Phase-transfer-assisted synthesis of cysteine-Ag nanoparticles/graphene oxide nanocomposite and its enhanced performance in antibiosis and biosensing.

We report a facile, rapid, phase-transfer-assisted process to prepare Ag nanoparticles (AgNP) loaded graphene oxide (GO) nanocomposite, by using cysteine as a highly-effective phase transfer agent for AgNP movement from organic phase to water and subsequently as a covalent linkage for immobilizing AgNP on GO. The obtained c-Ag/GO nanocomposite possesses high nanoparticle loading efficiency, small particle size and monodispersity, strong binding force and good water dispersibility, which endow it with great potential in a variety of bio-applications. To illustrate potentail application, c-Ag/GO and its derivatives c-Ag/rGO were used for antibiosis and biosensing, respectively. The c-Ag/GO composite demonstrates high antibacterial activity against E. coli with a minimal bactericidal concentration of 10 µg ml-1. The biosensor based on c-Ag/rGO exhibits rapid and sensitive response for uric acid detection with a detection limit of 0.025 µM, a sensitivity of 5.76 µA mM-1 and a wide linear range of 0.025 ∼ 2250 µM. The comparative analysis with relevant nanocomposites also reveals the precedence of c-Ag/GO in these applications, thus highlighting the advantages of the developed preparation method for c-Ag/GO.

intansv: an R package for integrative analysis of structural variations.

Identification of structural variations between individuals is very important for the understanding of phenotype variations and diseases. Despite the existence of dozens of programs for prediction of structural variations, none of them is the golden standard in this field and the results of multiple programs were usually integrated to get more reliable predictions. Annotation and visualization of structural variations are important for the understanding of their functions. However, no program provides these functions currently as far as we are concerned. We report an R package, intansv, which can integrate the predictions of multiple programs as well as annotate and visualize structural variations. The source code and the help manual of intansv is freely available at https://github.com/venyao/intansv and http://www.bioconductor.org/packages/devel/bioc/html/intansv.html.

Molecular dynamics and composition of crude oil by low-field nuclear magnetic resonance.

Nuclear magnetic resonance (NMR) techniques are widely used to identify pure substances and probe protein dynamics. Oil is a complex mixture composed of hydrocarbons, which have a wide range of molecular size distribution. Previous work show that empirical correlations of relaxation times and diffusion coefficients were found for simple alkane mixtures, and also the shape of the relaxation and diffusion distribution functions are related to the composition of the fluids. The 2D NMR is a promising qualitative evaluation method for oil composition. But uncertainty in the interpretation of crude oil indicated further study was required. In this research, the effect of each composition on relaxation distribution functions is analyzed in detail. We also suggest a new method for prediction of the rotational correlation time distribution of crude oil molecules using low field NMR (LF-NMR) relaxation time distributions. A set of down-hole NMR fluid analysis system is independently designed and developed for fluid measurement. We illustrate this with relaxation-relaxation correlation experiments and rotational correlation time distributions on a series of hydrocarbon mixtures that employ our laboratory-designed downhole NMR fluid analyzer. The LF-NMR is a useful tool for detecting oil composition and monitoring oil property changes. Copyright © 2016 John Wiley & Sons, Ltd.