Alternative splicing (AS) can critically affect gene function and disease, yet mapping splicing variations remains a challenge. Here, we propose a new approach to define and quantify mRNA splicing in units of local splicing variations (LSVs). LSVs capture previously defined types of alternative splicing as well as more complex transcript variations. Building the first genome wide map of LSVs from twelve mouse tissues, we find complex LSVs constitute over 30% of tissue dependent transcript variations and affect specific protein families. We show the prevalence of complex LSVs is conserved in humans and identify hundreds of LSVs that are specific to brain subregions or altered in Alzheimer's patients. Amongst those are novel isoforms in the Camk2 family and a novel poison exon in Ptbp1, a key splice factor in neurogenesis. We anticipate the approach presented here will advance the ability to relate tissue-specific splice variation to genetic variation, phenotype, and disease.DOI: http://dx.doi.org/10.7554/eLife.11752.001

Elucidating the global function of a transcription factor implies the identification of its target genes and genomic binding sites. The role of chromatin in this context is unclear, but the dominant view is that factors bind preferentially to nucleosome-depleted regions identified as DNaseI-hypersensitive sites (DHS). Here we show by ChIP, MNase, and DNaseI assays followed by deep sequencing that the progesterone receptor (PR) requires nucleosomes for optimal binding and function. In breast cancer cells treated with progestins, we identified 25,000 PR binding sites (PRbs). The majority of these sites encompassed several copies of the hexanucleotide TGTYCY, which is highly abundant in the genome. We found that functional PRbs accumulate around progesterone-induced genes, mainly in enhancers. Most of these sites overlap with DHS but exhibit high nucleosome occupancy. Progestin stimulation results in remodeling of these nucleosomes with displacement of histones H1 and H2A/H2B dimers. Our results strongly suggest that nucleosomes are crucial for PR binding and hormonal gene regulation.

Motivation: High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein–DNA and protein–RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing.Results: We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics.Availability: Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxyContact: eduardo.eyras@upf.eduSupplementary Information: Supplementary data are available at Bioinformatics online.