Chengjie Chen

Abstract Various softwares or pipelines have been developed for biological information mining from high-throughput sequencing (HTS) data, and most of them relies on programming and command-line environment with which most biologists are unfamiliar. Bioinformatic tools with an user-friendly interface are preferred by wet-lab biologists. Here, we describe TBtools, a Toolkit for Biologists integrating various HTS-data handling tools with a user-friendly interface. It includes a large collection of functions, which facilitate many simple, routine but elaborate tasks working on HTS data, such as bulk sequence extraction, gene set functional enrichment, venn diagram and etc. TBtools can run under all operating systems with JRE1.6 and is freely available at github.com/CJ-Chen/TBtools. Since its development, it has been used by many researchers. It will be a useful toolkit for wet-lab biologists to work on all kinds of high-throughput data.

The genomic signatures of positive selection and evolutionary constraints can be detected by analyses of nucleotide sequences. One of the most widely used programs for this purpose is CodeML, part of the PAML package. Although a number of bioinformatics tools have been developed to facilitate the use of CodeML, these have various limitations. Here, we present a wrapper tool named EasyCodeML that provides a user-friendly graphical interface for using CodeML. EasyCodeML has a custom running mode in which parameters can be adjusted to meet different requirements. It also offers a preset running mode in which an evolutionary analysis pipeline and publication-quality tables can be exported by a single click. EasyCodeML allows visualized, interactive tree labelling, which greatly simplifies the use of the branch, branch-site, and clade models of selection. The program allows comparison of major codon-based models for analyses of selection. EasyCodeML is a stand-alone package that is supported in Windows, Mac, and Linux operating systems, and is freely available at https://github.com/BioEasy/EasyCodeML.

BACKGROUND: WRKY proteins comprise a large family of transcription factors that play important roles in many aspects of physiological processes and adaption to environment. However, little information was available about the WRKY genes in pineapple (Ananas comosus), an important tropical fruits. The recent release of the whole-genome sequence of pineapple allowed us to perform a genome-wide investigation into the organization and expression profiling of pineapple WRKY genes. RESULTS: In the present study, 54 pineapple WRKY (AcWRKY) genes were identified and renamed on the basis of their respective chromosome distribution. According to their structural and phylogenetic features, the 54 AcWRKYs were further classified into three main groups with several subgroups. The segmental duplication events played a major role in the expansion of pineapple WRKY gene family. Synteny analysis and phylogenetic comparison of group III WRKY genes provided deep insight into the evolutionary characteristics of pineapple WRKY genes. Expression profiles derived from transcriptome data and real-time quantitative PCR analysis exhibited distinct expression patterns of AcWRKY genes in various tissues and in response to different abiotic stress and hormonal treatments. CONCLUSIONS: Fifty four WRKY genes were identified in pineapple and the structure of their encoded proteins, their evolutionary characteristics and expression patterns were examined in this study. This systematic analysis provided a foundation for further functional characterization of WRKY genes with an aim of pineapple crop improvement.