High‐throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome‐scale interaction mapping. Here, we report Barcode Fusion Genetics‐Yeast Two‐Hybrid (BFG‐Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG‐Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein‐pair barcodes that can be quantified via next‐generation sequencing. We applied BFG‐Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG‐Y2H increases the efficiency of protein matrix screening, with quality that is on par with state‐of‐the‐art Y2H methods.

Biogenesis and molecular function are two key subjects in the field of microRNA (miRNA) research. Deep sequencing has become the principal technique in cataloging of miRNA repertoire and generating expression profiles in an unbiased manner. Here, we describe the miRGator v3.0 update (http://mirgator.kobic.re.kr) that compiled the deep sequencing miRNA data available in public and implemented several novel tools to facilitate exploration of massive data. The miR-seq browser supports users to examine short read alignment with the secondary structure and read count information available in concurrent windows. Features such as sequence editing, sorting, ordering, import and export of user data would be of great utility for studying iso-miRs, miRNA editing and modifications. miRNA–target relation is essential for understanding miRNA function. Coexpression analysis of miRNA and target mRNAs, based on miRNA-seq and RNA-seq data from the same sample, is visualized in the heat-map and network views where users can investigate the inverse correlation of gene expression and target relations, compiled from various databases of predicted and validated targets. By keeping datasets and analytic tools up-to-date, miRGator should continue to serve as an integrated resource for biogenesis and functional investigation of miRNAs.

first draft of paper, designed experiments performed statistical analyses, performed bioinformatics analyses, performed data visualisation. M.T. wrote first draft of paper, designed experiments, generated tools & reagents, performed statistical analyses, performed bioinformatics analyses, performed data visualisation. S.M.G.E. wrote first draft of paper, generated tools & reagents, performed bioinformatics analyses, performed data visualisation. A.G.D. wrote first draft of paper, designed experiments, generated tools & reagents, performed bioinformatics analyses. M.D. generated tools & reagents. S.D. generated tools & reagents. L.Y.L. generated tools & reagents. S.S. generated tools & reagents. H.Z. generated tools & reagents. K.Z. generated tools & reagents, performed bioinformatics analyses. T.O.Y. generated tools & reagents, performed bioinformatics analyses. J.M.C. generated tools & reagents. A.B. generated tools & reagents. C.M.L. generated tools & reagents. I.U. generated tools & reagents. B.L. generated tools & reagents. W.Z. generated tools & reagents. A.D.E. generated tools & reagents, supervised research. NMW performed bioinformatics analyses, performed data visualisation. J.A.W. performed bioinformatics analyses. M.K.H.Z. performed bioinformatics analyses. C.V.A. performed bioinformatics analyses. C.P. performed data visualisation. J.T.S. supervised research. J.M.S. supervised research. D.A. supervised research. Y.G. supervised research. K.E. wrote first draft of paper, supervised research. D.C.W. designed experiments, supervised research. Q.D.M. wrote first draft of paper, designed experiments, generated tools & reagents, supervised research. P.V.L. wrote first draft of paper, designed experiments, supervised research. P.C.B. wrote first draft of paper, designed experiments, supervised research.

Chromosome translocations and gene fusions are frequent events in the human genome and have been found to cause diverse types of tumor. ChimerDB is a knowledgebase of fusion genes identified from bioinformatics analysis of transcript sequences in the GenBank and various other public resources such as the Sanger cancer genome project (CGP), OMIM, PubMed and the Mitelman’s database. In this updated version, we significantly modified the algorithm of identifying fusion transcripts. Specifically, the new algorithm is more sensitive and has detected 2699 fusion transcripts with high confidence. Furthermore, it can identify interchromosomal translocations as well as the intrachromosomal deletions or inversions of large DNA segments. Importantly, results from the analysis of next-generation sequencing data in the short read archives are incorporated as well. We updated and integrated all contents (GenBank, Sanger CGP, OMIM, PubMed publications and the Mitelman’s database), and the user-interface has been improved to support diverse types of searches and to enhance the user convenience especially in browsing PubMed articles. We also developed a new alignment viewer that should facilitate examining reliability of fusion transcripts and inferring functional significance. We expect ChimerDB 2.0, available at http://ercsb.ewha.ac.kr/fusiongene, to be a valuable tool in identifying biomarkers and drug targets.