Alternative splicing (AS) generates remarkable regulatory and proteomic complexity in metazoans. However, the functions of most AS events are not known, and programs of regulated splicing remain to be identified. To address these challenges, we describe the Vertebrate Alternative Splicing and Transcription Database (VastDB), the largest resource of genome-wide, quantitative profiles of AS events assembled to date. VastDB provides readily accessible quantitative information on the inclusion levels and functional associations of AS events detected in RNA-seq data from diverse vertebrate cell and tissue types, as well as developmental stages. The VastDB profiles reveal extensive new intergenic and intragenic regulatory relationships among different classes of AS and previously unknown and conserved landscapes of tissue-regulated exons. Contrary to recent reports concluding that nearly all human genes express a single major isoform, VastDB provides evidence that at least 48% of multiexonic protein-coding genes express multiple splice variants that are highly regulated in a cell/tissue-specific manner, and that >18% of genes simultaneously express multiple major isoforms across diverse cell and tissue types. Isoforms encoded by the latter set of genes are generally coexpressed in the same cells and are often engaged by translating ribosomes. Moreover, they are encoded by genes that are significantly enriched in functions associated with transcriptional control, implying they may have an important and wide-ranging role in controlling cellular activities. VastDB thus provides an unprecedented resource for investigations of AS function and regulation.

The subcellular localization of long noncoding RNAs (lncRNAs) holds valuable clues to their molecular function. However, measuring localization of newly discovered lncRNAs involves time-consuming and costly experimental methods. We have created “lncATLAS,” a comprehensive resource of lncRNA localization in human cells based on RNA-sequencing data sets. Altogether, 6768 GENCODE-annotated lncRNAs are represented across various compartments of 15 cell lines. We introduce relative concentration index (RCI) as a useful measure of localization derived from ensemble RNA-seq measurements. LncATLAS is accessible through an intuitive and informative webserver, from which lncRNAs of interest are accessed using identifiers or names. Localization is presented across cell types and organelles, and may be compared to the distribution of all other genes. Publication-quality figures and raw data tables are automatically generated with each query, and the entire data set is also available to download. LncATLAS makes lncRNA subcellular localization data available to the widest possible number of researchers. It is available at lncatlas.crg.eu.

Long non-coding RNAs (lncRNAs) are functional non-translated molecules greater than 200 nt. Their roles are diverse and they are usually involved in transcriptional regulation. LncRNAs still remain largely uninvestigated in plants with few exceptions. Experimentally validated plant lncRNAs have been shown to regulate important agronomic traits such as phosphate starvation response, flowering time and interaction with symbiotic organisms, making them of great interest in plant biology and in breeding. There is still a lack of lncRNAs in most sequenced plant species, and in those where they have been annotated, different methods have been used, so making the lncRNAs less useful in comparisons within and between species. We developed a pipeline to annotate lncRNAs and applied it to 37 plant species and six algae, resulting in the annotation of more than 120 000 lncRNAs. To facilitate the study of lncRNAs for the plant research community, the information gathered is organised in the Green Non-Coding Database (GreeNC, http://greenc.sciencedesigners.com/).

The turbot is a flatfish (Pleuronectiformes) with increasing commercial value, which has prompted active genomic research aimed at more efficient selection. Here we present the sequence and annotation of the turbot genome, which represents a milestone for both boosting breeding programmes and ascertaining the origin and diversification of flatfish. We compare the turbot genome with model fish genomes to investigate teleost chromosome evolution. We observe a conserved macrosyntenic pattern within Percomorpha and identify large syntenic blocks within the turbot genome related to the teleost genome duplication. We identify gene family expansions and positive selection of genes associated with vision and metabolism of membrane lipids, which suggests adaptation to demersal lifestyle and to cold temperatures, respectively. Our data indicate a quick evolution and diversification of flatfish to adapt to benthic life and provide clues for understanding their controversial origin. Moreover, we investigate the genomic architecture of growth, sex determination and disease resistance, key traits for understanding local adaptation and boosting turbot production, by mapping candidate genes and previously reported quantitative trait loci. The genomic architecture of these productive traits has allowed the identification of candidate genes and enriched pathways that may represent useful information for future marker-assisted selection in turbot.

CRISPR-Cas9 technology can be used to engineer precise genomic deletions with pairs of single guide RNAs (sgRNAs). This approach has been widely adopted for diverse applications, from disease modelling of individual loci, to parallelized loss-of-function screens of thousands of regulatory elements. However, no solution has been presented for the unique bioinformatic design requirements of CRISPR deletion. We here present CRISPETa, a pipeline for flexible and scalable paired sgRNA design based on an empirical scoring model. Multiple sgRNA pairs are returned for each target, and any number of targets can be analyzed in parallel, making CRISPETa equally useful for focussed or high-throughput studies. Fast run-times are achieved using a pre-computed off-target database. sgRNA pair designs are output in a convenient format for visualisation and oligonucleotide ordering. We present pre-designed, high-coverage library designs for entire classes of protein-coding and non-coding elements in human, mouse, zebrafish, Drosophila melanogaster and Caenorhabditis elegans. In human cells, we reproducibly observe deletion efficiencies of ≥50% for CRISPETa designs targeting an enhancer and exonic fragment of the MALAT1 oncogene. In the latter case, deletion results in production of desired, truncated RNA. CRISPETa will be useful for researchers seeking to harness CRISPR for targeted genomic deletion, in a variety of model organisms, from single-target to high-throughput scales. CRISPR-Cas9 is a revolutionary biological technique for precisely editing cells’ genomes. Amongst its many capabilities is the deletion of defined regions of DNA, creating a wide range of applications from modelling rare human diseases, to performing very large knock-out screens of candidate regulatory DNA. CRISPR-Cas9 requires researchers to design small RNA molecules called sgRNAs to target their region of interest. A large number of bioinformatic tools exist for this task. However, CRISPR deletion requires the design of optimised pairs of such RNA molecules. This manuscript describes the first pipeline designed to accomplish this, called CRISPETa, with a range of useful features. We use CRISPETa to design comprehensive libraries of paired sgRNA for many thousands of target regions that may be used by the scientific community. Using CRISPETa designs in human cells, we show that predicted pairs of sgRNAs produce the expected deletions at high efficiency. Finally, we show that these deletions of genomic DNA give rise to correspondingly truncated RNA molecules, supporting the power of this technology to create cells with precisely deleted DNA.

The direct RNA sequencing platform offered by Oxford Nanopore Technologies allows for direct measurement of RNA molecules without the need of conversion to complementary DNA, fragmentation or amplification. As such, it is virtually capable of detecting any given RNA modification present in the molecule that is being sequenced, as well as provide polyA tail length estimations at the level of individual RNA molecules. Although this technology has been publicly available since 2017, the complexity of the raw Nanopore data, together with the lack of systematic and reproducible pipelines, have greatly hindered the access of this technology to the general user. Here we address this problem by providing a fully benchmarked workflow for the analysis of direct RNA sequencing reads, termed MasterOfPores. The pipeline starts with a pre-processing module, which converts raw current intensities into multiple types of processed data including FASTQ and BAM, providing metrics of the quality of the run, quality-filtering, demultiplexing, base-calling and mapping. In a second step, the pipeline performs downstream analyses of the mapped reads, including prediction of RNA modifications and estimation of polyA tail lengths. Four direct RNA MinION sequencing runs can be fully processed and analyzed in 10 h on 100 CPUs. The pipeline can also be executed in GPU locally or in the cloud, decreasing the run time fourfold. The software is written using the NextFlow framework for parallelization and portability, and relies on Linux containers such as Docker and Singularity for achieving better reproducibility. The MasterOfPores workflow can be executed on any Unix-compatible OS on a computer, cluster or cloud without the need of installing any additional software or dependencies, and is freely available in Github (https://github.com/biocorecrg/master_of_pores). This workflow simplifies direct RNA sequencing data analyses, facilitating the study of the (epi)transcriptome at single molecule resolution.