SUMMARY: Large-scale sharing of genomic quantification data requires standardized access interfaces. In this Global Alliance for Genomics and Health project, we developed RNAget, an API for secure access to genomic quantification data in matrix form. RNAget provides for slicing matrices to extract desired subsets of data and is applicable to all expression matrix-format data, including RNA sequencing and microarrays. Further, it generalizes to quantification matrices of other sequence-based genomics such as ATAC-seq and ChIP-seq. AVAILABILITY AND IMPLEMENTATION: https://ga4gh-rnaseq.github.io/schema/docs/index.html.

Tandem alternative splice sites (TASS) is a special class of alternative splicing events that are characterized by a close tandem arrangement of splice sites. Most TASS lack functional characterization and are believed to arise from splicing noise. Based on the RNA-seq data from the Genotype Tissue Expression project, we present an extended catalogue of TASS in healthy human tissues and analyze their tissue-specific expression. The expression of TASS is usually dominated by one major splice site (maSS), while the expression of minor splice sites (miSS) is at least an order of magnitude lower. Among 46k miSS with sufficient read support, 9k (20%) are significantly expressed above the expected noise level, and among them 2.5k are expressed tissue-specifically. We found significant correlations between tissue-specific expression of RNA-binding proteins (RBP), tissue-specific expression of miSS, and miSS response to RBP inactivation by shRNA. In combination with RBP profiling by eCLIP, this allowed prediction of novel cases of tissue-specific splicing regulation including a miSS in QKI mRNA that is likely regulated by PTBP1. The analysis of human primary cell transcriptomes suggested that both tissue-specific and cell-type-specific factors contribute to the regulation of miSS expression. More than 20% of tissue-specific miSS affect structured protein regions and may adjust protein-protein interactions or modify the stability of the protein core. The significantly expressed miSS evolve under the same selection pressure as maSS, while other miSS lack signatures of evolutionary selection and conservation. Using mixture models, we estimated that not more than 15% of maSS and not more than 54% of tissue-specific miSS are noisy, while the proportion of noisy splice sites among non-significantly expressed miSS is above 63%.

MOTIVATION: Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon-skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the majority of human splicing events are more complex than single-exon skipping. RESULTS: In this short report, we present a framework that generalizes the metric to arbitrary classes of splicing events. We change the view from exon centric to intron centric and split the value of into two indices, and , measuring the rate of splicing at the 5' and 3' end of the intron, respectively. The advantage of having two separate indices is that they deconvolute two distinct elementary acts of the splicing reaction. The completeness of splicing index is decomposed in a similar way. This framework is implemented as bam2ssj, a BAM-file-processing pipeline for strand-specific counting of reads that align to splice junctions or overlap with splice sites. It can be used as a consistent protocol for quantifying splice junctions from RNA-seq data because no such standard procedure currently exists. AVAILABILITY: The C code of bam2ssj is open source and is available at https://github.com/pervouchine/bam2ssj CONTACT: [email protected]

Cells that produce intrinsic theta oscillations often contain the hyperpolarization-activated current I(h). In this article, we use models and dynamic clamp experiments to investigate the synchronization properties of two such cells (stellate cells of the entorhinal cortex and O-LM cells of the hippocampus) in networks with fast-spiking (FS) interneurons. The model we use for stellate cells and O-LM cells is the same, but the stellate cells are excitatory and the O-LM cells are inhibitory, with inhibitory postsynaptic potential considerably longer than those from FS interneurons. We use spike time response curve methods (STRC), expanding that technique to three-cell networks and giving two different ways in which the analysis of the three-cell network reduces to that of a two-cell network. We show that adding FS cells to a network of stellate cells can desynchronize the stellate cells, while adding them to a network of O-LM cells can synchronize the O-LM cells. These synchronization and desynchronization properties critically depend on I(h). The analysis of the deterministic system allows us to understand some effects of noise on the phase relationships in the stellate networks. The dynamic clamp experiments use biophysical stellate cells and in silico FS cells, with connections that mimic excitation or inhibition, the latter with decay times associated with FS cells or O-LM cells. The results obtained in the dynamic clamp experiments are in a good agreement with the analytical framework.