CAFU: a Galaxy framework for exploring unmapped RNA-Seq data.

A widely used approach in transcriptome analysis is the alignment of short reads to a reference genome. However, owing to the deficiencies of specially designed analytical systems, short reads unmapped to the genome sequence are usually ignored, resulting in the loss of significant biological information and insights. To fill this gap, we present Comprehensive Assembly and Functional annotation of Unmapped RNA-Seq data (CAFU), a Galaxy-based framework that can facilitate the large-scale analysis of unmapped RNA sequencing (RNA-Seq) reads from single- and mixed-species samples. By taking advantage of machine learning techniques, CAFU addresses the issue of accurately identifying the species origin of transcripts assembled using unmapped reads from mixed-species samples. CAFU also represents an innovation in that it provides a comprehensive collection of functions required for transcript confidence evaluation, coding potential calculation, sequence and expression characterization and function annotation. These functions and their dependencies have been integrated into a Galaxy framework that provides access to CAFU via a user-friendly interface, dramatically simplifying complex exploration tasks involving unmapped RNA-Seq reads. CAFU has been validated with RNA-Seq data sets from wheat and Zea mays (maize) samples. CAFU is freely available via GitHub: https://github.com/cma2015/CAFU.

Evolution of intron-poor clades and expression patterns of the glycosyltransferase family 47.

MAIN CONCLUSION: A large-scale bioinformatics analysis revealed the origin and evolution of GT47 gene family, and identified two clades of intron-poor genes with putative functions in drought stress responses and seed development in maize. Glycosyltransferase family 47 (GT47) genes encode ß-galactosyltransferases and ß-glucuronyltransferases that synthesize pectin, xyloglucans and xylan, which are important components of the plant cell wall. In this study, we performed a systematic and large-scale bioinformatics analysis of GT47 gene family using 352 GT47 proteins from 15 species ranging from cyanobacteria to seed plants. The analysis results showed that GT47 family may originate in cyanobacteria and expand along the evolutionary trajectory to moss. Further analysis of 47 GT47 genes in maize revealed that they can divide into five clades with diverse exon-intron structures. Among these five clades, two were mainly composed with intron-poor genes, which may originate in the moss. Gene duplication analysis revealed that the expansion of GT47 gene family in maize was significantly driven from tandem duplication events and segmental duplication events. Significantly, almost all duplicated genes are intron-poor genes. Expression analysis indicated that several intron-poor GT47 genes may be involved in the drought stress response and seed development in maize. This work provides insight into the origin and evolutionary process, expansion mechanisms and expression patterns of GT47 genes, thus facilitating their functional investigations in the future.