Alternative splicing is a crucial mechanism by which diverse gene products can be generated from a limited number of genes, and is thought to be involved in complex orchestration of eukaryotic gene expression. Next-generation sequencing technologies, with reduced time and cost, provide unprecedented opportunities for deep interrogation of alternative splicing at the genome-wide scale. In this study, an integrated software SplicingViewer has been developed for unambiguous detection, annotation and visualization of splice junctions and alternative splicing events from RNA-Seq data. Specifically, it allows easy identification and characterization of splice junctions, and holds a versatile computational pipeline for in-depth annotation and classification of alternative splicing with different patterns. Moreover, it provides a user-friendly environment in which an alternative splicing landscape can be displayed in a straightforward and flexible manner. In conclusion, SplicingViewer can be widely used for studying alternative splicing easily and efficiently. SplicingViewer can be freely accessed at http://bioinformatics.zj.cn/splicingviewer.

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BackgroundProtein-coding regions in human genes harbor 85% of the mutations that are associated with disease-related traits. Compared with whole-genome sequencing of complex samples, exome sequencing serves as an alternative option because of its dramatically reduced cost. In fact, exome sequencing has been successfully applied to identify the cause of several Mendelian disorders, such as Miller and Schinzel-Giedio syndrome. However, there remain great challenges in handling the huge data generated by exome sequencing and in identifying potential disease-related genetic variations.ResultsIn this study, Exome-assistant (http://122.228.158.106/exomeassistant), a convenient tool for submitting and annotating single nucleotide polymorphisms (SNPs) and insertion/deletion variations (InDels), was developed to rapidly detect candidate disease-related genetic variations from exome sequencing projects. Versatile filter criteria are provided by Exome-assistant to meet different users’ requirements. Exome-assistant consists of four modules: the single case module, the two cases module, the multiple cases module, and the reanalysis module. The two cases and multiple cases modules allow users to identify sample-specific and common variations. The multiple cases module also supports family-based studies and Mendelian filtering. The identified candidate disease-related genetic variations can be annotated according to their sample features.ConclusionsIn summary, by exploring exome sequencing data, Exome-assistant can provide researchers with detailed biological insights into genetic variation events and permits the identification of potential genetic causes of human diseases and related traits.

Sphingomonas xenophaga QYY is an efficient anthraquinone-degrading strain. Here, we present a 4.2-Mb assembly of the first genome sequence of S. xenophaga. We have annotated 36 coding sequences (CDSs) encoding aromatic catabolism and 216 CDSs responsible for toxic resistance and stress response, which may provide insights into the degradation of complex aromatics.