Long-read transcriptome sequencing analysis with IsoTools

Long-read transcriptome sequencing (LRTS) holds the promise to boost our understanding of alternative splicing. Recent advances in accuracy and throughput have diminished the major limitations and enabled the direct quantification of isoforms. Considering the complexity of the data and the broad range of potential applications, it is clear that highly flexible, accurate analysis tools are crucial. Here, we present IsoTools, a comprehensive Python-based analysis package, for the improvement of alternative and differential splicing analysis. Iso-Tools provides a comprehensive data structure that integrates genomic information from LRTS transcripts together with the reference annotation, and enables broad functionality to quality control, visualize and analyze the data. Additionally, we implemented a graph-based method for the identification of alternative splicing events and a statistical approach based on the beta binomial distribution for the detection of differential events. To demonstrate our methods, we generated PacBio Iso-Seq data of human hepatocytes treated with the HDAC inhibitor valproic acid, a compound known to induce widespread transcriptional changes. Contrasted with short read RNA-Seq of the same samples, this analysis shows that LRTS provides valuable additional insights for a better understanding of alternative splicing, in particular with respect to complex novel and differential splicing events. IsoTools is made available for the community along with extensive documentation at https://github.com/MatthiasLienhard/isotools

Characterization of hundreds of regulatory landscapes in developing limbs reveals two regimes of chromatin folding

Complex regulatory landscapes control the pleiotropic transcriptional activities of developmental genes. For most genes, the number, location and dynamic of their associated regulatory elements are unknown. In this work we characterized the three-dimensional chromatin micro-architecture and regulatory landscape of 446 limb-associated gene loci in mouse using Capture-C, ChIP-seq and RNA-seq in forelimb, hindlimb at three developmental stages and midbrain. The fine mapping of chromatin interactions revealed a strong preference for functional genomic regions such as repressed or active domains. By combining chromatin marks and interaction peaks, we annotated more than one thousand putative limb enhancers and their associated genes. Moreover, the analysis of chromatin interactions revealed two regimes of chromatin folding, one producing interactions stable across tissues and stages and another one associated with tissue and/or stage-specific interactions. Whereas stable interactions associate strongly with CTCF/RAD21 binding, the intensity of variable interactions correlates with changes in underlying chromatin modifications, specifically at the viewpoint and at the interaction site. In conclusion, this comprehensive dataset provides a resource for the characterization of hundreds of limb-associated regulatory landscapes and a framework to interpret the chromatin folding dynamics observed during embryogenesis