Small RNA research is a rapidly growing field. Apart from microRNAs, which are important regulators of gene expression, other types of functional small RNA molecules have been reported in animals and plants. MicroRNAs are important in host-microbe interactions and parasite microRNAs might modulate the innate immunity of the host. Furthermore, small RNAs can be detected in bodily fluids making them attractive non-invasive biomarker candidates. Given the general broad interest in small RNAs, and in particular microRNAs, a large number of bioinformatics aided analysis types are needed by the scientific community. To facilitate integrated sRNA research, we developed sRNAtoolbox, a set of independent but interconnected tools for expression profiling from high-throughput sequencing data, consensus differential expression, target gene prediction, visual exploration in a genome context as a function of read length, gene list analysis and blast search of unmapped reads. All tools can be used independently or for the exploration and downstream analysis of sRNAbench results. Workflows like the prediction of consensus target genes of parasite microRNAs in the host followed by the detection of enriched pathways can be easily established. The web-interface interconnecting all these tools is available at http://bioinfo5.ugr.es/srnatoolbox

Since the original publication of sRNAtoolbox in 2015, small RNA research experienced notable advances in different directions. New protocols for small RNA sequencing have become available to address important issues such as adapter ligation bias, PCR amplification artefacts or to include internal controls such as spike-in sequences. New microRNA reference databases were developed with different foci, either prioritizing accuracy (low number of false positives) or completeness (low number of false negatives). Additionally, other small RNA molecules as well as microRNA sequence and length variants (isomiRs) have continued to gain importance. Finally, the number of microRNA sequencing studies deposited in GEO nearly triplicated from 2014 (280) to 2018 (764). These developments imply that fast and easy-to-use tools for expression profiling and subsequent downstream analysis of miRNA-seq data are essential to many researchers. Key features in this sRNAtoolbox release include addition of all major RNA library preparation protocols to sRNAbench and improvements in sRNAde, a tool that summarizes several aspects of small RNA sequencing studies including the detection of consensus differential expression. A special emphasis was put on the user-friendliness of the tools, for instance sRNAbench now supports parallel launching of several jobs to improve reproducibility and user time efficiency.

No abstract

Progressive evolution, or the tendency towards increasing complexity, is a controversial issue in biology, which resolution entails a proper measurement of complexity. Genomes are the best entities to address this challenge, as they encode the historical information of a species’ biotic and environmental interactions. As a case study, we have measured genome sequence complexity in the ancient phylum Cyanobacteria. To arrive at an appropriate measure of genome sequence complexity, we have chosen metrics that do not decipher biological functionality but that show strong phylogenetic signal. Using a ridge regression of those metrics against root-to-tip distance, we detected positive trends towards higher complexity in three of them. Lastly, we applied three standard tests to detect if progressive evolution is passive or driven—the minimum, ancestor–descendant, and sub-clade tests. These results provide evidence for driven progressive evolution at the genome-level in the phylum Cyanobacteria.

The molecular mechanisms active during the endophytic phase of the fungus Pochonia chlamydosporia are still poorly understood. In particular, few data are available on the links between the endophyte and the root response, as modulated by noncoding small RNAs. In this study, we describe the microRNAs (miRNAs) that are differentially expressed (DE) in the roots of tomato, colonized by P. chlamydosporia. A genome-wide NGS expression profiling of small RNAs in roots, either colonized or not by the fungus, showed 26 miRNAs upregulated in inoculated roots. Their predicted target genes are involved in the plant information processing system, which recognizes, percepts, and transmits signals, with higher representations in processes such as apoptosis and plant defense regulation. RNAseq data showed that predicted miRNA target genes were downregulated in tomato roots after 4, 7, 10, and 21 days post P. chlamydosporia inoculation. The differential expression of four miRNAs was further validated using qPCR analysis. The P. chlamydosporia endophytic lifestyle in tomato roots included an intricate network of miRNAs and targets. Data provide a first platform of DE tomato miRNAs after P. chlamydosporia colonization. They indicated that several miRNAs are involved in the host response to the fungus, playing important roles for its recognition as a symbiotic microorganism, allowing endophytism by modulating the host defense reaction. Data also indicated that endophytism affects tRNA fragmentation. This is the first study on miRNAs induced by P. chlamydosporia endophytism and related development regulation effects in Solanum lycopersicum.

MiRNAs are important regulators of gene expression and are frequently deregulated under pathologic conditions. They are highly stable in bodily fluids which makes them feasible candidates to become minimally invasive biomarkers. In fact, several studies already proposed circulating miRNA-based biomarkers for different types of neoplastic, cardiovascular and degenerative diseases. However, many of these studies rely on small RNA sequencing experiments that are based on different RNA extraction and processing protocols, rendering results incomparable. We generated liqDB, a database for liquid biopsy small RNA sequencing profiles that provides users with meaningful information to guide their small RNA liquid biopsy research and to overcome technical and conceptual problems. By means of a user-friendly web interface, miRNA expression profiles from 1607 manually annotated samples can be queried and explored at different levels. Result pages include downloadable expression matrices, differential expression analysis, most stably expressed miRNAs, cluster analysis and relevant visualizations by means of boxplots and heatmaps. We anticipate that liqDB will be a useful tool in liquid biopsy research as it provides a consistently annotated large compilation of experiments together with tools for reproducible analysis, comparison and hypothesis generation. LiqDB is available at http://bioinfo5.ugr.es/liqdb.

Trichomes are specialised epidermal cells developed in the aerial surface of almost every terrestrial plant. These structures form physical barriers, which combined with their capability of synthesis of complex molecules, prevent plagues from spreading and confer trichomes a key role in the defence against herbivores. In this work, the tomato gene HAIRPLUS (HAP) that controls glandular trichome density in tomato plants was characterised. HAP belongs to a group of proteins involved in histone tail modifications although some also bind methylated DNA. HAP loss of function promotes epigenomic modifications in the tomato genome reflected in numerous differentially methylated cytosines and causes transcriptomic changes in hap mutant plants. Taken together, these findings demonstrate that HAP links epigenome remodelling with multicellular glandular trichome development and reveal that HAP is a valuable genomic tool for pest resistance in tomato breeding.

The 2017 update of NGSmethDB stores whole genome methylomes generated from short-read data sets obtained by bisulfite sequencing (WGBS) technology. To generate high-quality methylomes, stringent quality controls were integrated with third-part software, adding also a two-step mapping process to exploit the advantages of the new genome assembly models. The samples were all profiled under constant parameter settings, thus enabling comparative downstream analyses. Besides a significant increase in the number of samples, NGSmethDB now includes two additional data-types, which are a valuable resource for the discovery of methylation epigenetic biomarkers: (i) differentially methylated single-cytosines; and (ii) methylation segments (i.e. genome regions of homogeneous methylation). The NGSmethDB back-end is now based on MongoDB, a NoSQL hierarchical database using JSON-formatted documents and dynamic schemas, thus accelerating sample comparative analyses. Besides conventional database dumps, track hubs were implemented, which improved database access, visualization in genome browsers and comparative analyses to third-part annotations. In addition, the database can be also accessed through a RESTful API. Lastly, a Python client and a multiplatform virtual machine allow for program-driven access from user desktop. This way, private methylation data can be compared to NGSmethDB without the need to upload them to public servers. Database website: http://bioinfo2.ugr.es/NGSmethDB.