IntS6 and the Integrator phosphatase module tune the efficiency of select premature transcription termination events.

The metazoan-specific Integrator complex catalyzes 3' end processing of small nuclear RNAs (snRNAs) and premature termination that attenuates the transcription of many protein-coding genes. Integrator has RNA endonuclease and protein phosphatase activities, but it remains unclear if both are required for complex function. Here, we show IntS6 (Integrator subunit 6) over-expression blocks Integrator function at a subset of Drosophila protein-coding genes, although having no effect on snRNAs or attenuation of other loci. Over-expressed IntS6 titrates protein phosphatase 2A (PP2A) subunits, thereby only affecting gene loci where phosphatase activity is necessary for Integrator function. IntS6 functions analogous to a PP2A regulatory B subunit as over-expression of canonical B subunits, which do not bind Integrator, is also sufficient to inhibit Integrator activity. These results show that the phosphatase module is critical at only a subset of Integrator-regulated genes and point to PP2A recruitment as a tunable step that modulates transcription termination efficiency.

Approaches and challenges in genome-wide circular RNA identification and quantification.

Numerous circular RNAs (circRNAs) produced from back-splicing of exon(s) have been recently revealed on a genome-wide scale across species. Although generally expressed at a low level, some relatively abundant circRNAs can play regulatory roles in various biological processes, prompting continuous profiling of circRNA in broader conditions. Over the past decade, distinct strategies have been applied in both transcriptome enrichment and bioinformatic tools for detecting and quantifying circRNAs. Understanding the scope and limitations of these strategies is crucial for the subsequent annotation and characterization of circRNAs, especially those with functional potential. Here, we provide an overview of different transcriptome enrichment, deep sequencing and computational approaches for genome-wide circRNA identification, and discuss strategies for accurate quantification and characterization of circRNA.

QTLbase: an integrative resource for quantitative trait loci across multiple human molecular phenotypes.

Recent advances in genome sequencing and functional genomic profiling have promoted many large-scale quantitative trait locus (QTL) studies, which connect genotypes with tissue/cell type-specific cellular functions from transcriptional to post-translational level. However, no comprehensive resource can perform QTL lookup across multiple molecular phenotypes and investigate the potential cascade effect of functional variants. We developed a versatile resource, named QTLbase, for interpreting the possible molecular functions of genetic variants, as well as their tissue/cell-type specificity. Overall, QTLbase has five key functions: (i) curating and compiling genome-wide QTL summary statistics for 13 human molecular traits from 233 independent studies; (ii) mapping QTL-relevant tissue/cell types to 78 unified terms according to a standard anatomogram; (iii) normalizing variant and trait information uniformly, yielding >170 million significant QTLs; (iv) providing a rich web client that enables phenome- and tissue-wise visualization; and (v) integrating the most comprehensive genomic features and functional predictions to annotate the potential QTL mechanisms. QTLbase provides a one-stop shop for QTL retrieval and comparison across multiple tissues and multiple layers of molecular complexity, and will greatly help researchers interrogate the biological mechanism of causal variants and guide the direction of functional validation. QTLbase is freely available at http://mulinlab.org/qtlbase.

CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies.

Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.