Rapid development of high-throughput sequencing (HTS) techniques has led biology into the "big-data" era. Data analysis using various bioinformatics softwares or pipelines relying on programming and command-line environment is challenging and time-consuming for most wet-lab biologists. Bioinformatics tools with a user-friendly interface are preferred. Here, we present TBtools (a Toolkit for Biologists integrating various biological data handling tools), a stand-alone software with a user-friendly interface. It has powerful data handling engines for both bulk sequence processing and interactive data visualization. It includes a large collection of functions, which may facilitate much simple, routine but elaborate work on biological data, such as bulk sequence extraction, gene set enrichment analysis, Venn diagram preparation, heatmap illustration, comparative sequence visualization, etc. Availability and implementation:TBtools is a platform-independent software that can be run under all operating systems with Java Runtime Environment 1.

18The rapid development of high-throughput sequencing (HTS) techniques has led biology into 19 the big-data era. Data analyses using various bioinformatics tools rely on programming and 20 command-line environments, which are challenging and time-consuming for most wet-lab 21biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data 22

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 .

BackgroundWRKY 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.ResultsIn 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.ConclusionsFifty 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.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4880-x) contains supplementary material, which is available to authorized users.

Small RNAs are key regulators in plant growth and development. One subclass, phased siRNAs (phasiRNAs) require a trigger microRNA for their biogenesis. In grasses, two pathways yield abundant phasiRNAs during anther development; miR2275 triggers one class, 24-nt phasiRNAs, coincident with meiosis, while a second class of 21-nt phasiRNAs are present in premeiotic anthers. Here we report that the 24-nt phasiRNA pathway is widely present in flowering plants, indicating that 24-nt reproductive phasiRNAs likely originated with the evolutionary emergence of anthers. Deep comparative genomic analyses demonstrated that this miR2275/24-nt phasiRNA pathway is widely present in eudicots plants, however, it is absent in legumes and in the model plant Arabidopsis, demonstrating a dynamic evolutionary history of this pathway. In Solanaceae species, 24-nt phasiRNAs were observed, but the miR2275 trigger is missing and some loci displaying 12-nt phasing. Both the miR2275-triggered and Solanaceae 24-nt phasiRNAs are enriched in meiotic stages, implicating these phasiRNAs in anther and/or pollen development, a spatiotemporal pattern consistent in all angiosperm lineages that deploy them.