Summary Eukaryotic cells make many types of primary and processed RNAs that are found either in specific sub-cellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic sub-cellular localizations are also poorly understood. Since RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell’s regulatory capabilities are focused on its synthesis, processing, transport, modifications and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations taken together prompt to a redefinition of the concept of a gene.

A key challenge of functional genomics today is to generate well-annotated data sets that can be interpreted across different platforms and technologies. Large-scale functional genomics data often fail to connect to standard experimental approaches of gene characterization in individual laboratories. Furthermore, a lack of universal annotation standards for phenotypic data sets makes it difficult to compare different screening approaches. Here we address this problem in a screen designed to identify all genes required for the first two rounds of cell division in the Caenorhabditis elegans embryo. We used RNA-mediated interference to target 98% of all genes predicted in the C. elegans genome in combination with differential interference contrast time-lapse microscopy. Through systematic annotation of the resulting movies, we developed a phenotypic profiling system, which shows high correlation with cellular processes and biochemical pathways, thus enabling us to predict new functions for previously uncharacterized genes.

A restriction fragment length polymorphism (RFLP) map for the A genome of Avena has been developed using F3 families from the cross A. atlantica × A. hirtula. The main source of markers were an oat cDNA and a barley cDNA library. A total of 194 RFLP markers was used, 192 of which were mapped or assigned to linkage groups. Seven main linkage groups, presumably corresponding to the seven chromosomes of the haploid genome, were identified. The linkage groups varied in size from 30 to 118 cM for a total map length of 614 cM. This map provides a tool for the interpretation of genome organization in Avena and for marker selection in the development of a map of hexaploid oats.Key words: restriction fragment length polymorphism, Avena, mapping.

Motivation: The avalanche of data arriving since the development of NGS technologies have prompted the need for developing fast, accurate and easily automated bioinformatic tools capable of dealing with massive datasets. Among the most productive applications of NGS technologies is the sequencing of cellular RNA, known as RNA-Seq. Although RNA-Seq provides similar or superior dynamic range than microarrays at similar or lower cost, the lack of standard and user-friendly pipelines is a bottleneck preventing RNA-Seq from becoming the standard for transcriptome analysis.Results: In this work we present a pipeline for processing and analyzing RNA-Seq data, that we have named Grape (Grape RNA-Seq Analysis Pipeline Environment). Grape supports raw sequencing reads produced by a variety of technologies, either in FASTA or FASTQ format, or as prealigned reads in SAM/BAM format. A minimal Grape configuration consists of the file location of the raw sequencing reads, the genome of the species and the corresponding gene and transcript annotation.Grape first runs a set of quality control steps, and then aligns the reads to the genome, a step that is omitted for prealigned read formats. Grape next estimates gene and transcript expression levels, calculates exon inclusion levels and identifies novel transcripts.Grape can be run on a single computer or in parallel on a computer cluster. It is distributed with specific mapping and quantification tools, but given its modular design, any tool supporting popular data interchange formats can be integrated.Availability: Grape can be obtained from the Bioinformatics and Genomics website at: http://big.crg.cat/services/grape.Contact: david.gonzalez@crg.eu or roderic.guigo@crg.eu