Caenorhabditis elegans SynMuv B gene activity is down-regulated during a viral infection to enhance RNA interference.

Small RNA pathways regulate eukaryotic antiviral defense. Many of the Caenorhabditis elegans mutations that were identified based on their enhanced RNAi, the synMuv B genes, also emerged from unrelated genetic screens for increased growth factor signaling. The dozen synMuv B genes encode homologues of the mammalian dREAM complex found in nearly all animals and plants, which includes the lin-35 /retinoblastoma oncogene. We show that a set of highly induced mRNAs in synMuv B mutants is congruent with mRNAs induced by Orsay RNA virus infection of C. elegans . In wild type animals, a combination of a synMuv A mutation and a synMuv B mutation are required for the Muv phenotype of increased growth factor signaling. But we show that Orsay virus infection of a single synMuv A mutant can induce a Muv phenotype, unlike the uninfected single synMuv A mutant. This suggests that decreased synMuv B activity, which activates the antiviral RNAi pathway, is a defense response to viral infection. Small RNA deep sequencing analysis of various dREAM complex mutants uncovers distinct siRNA profiles indicative of such an siRNA response. We conclude that the synMuv B mutants maintain an antiviral readiness state even in the absence of actual infection. The enhanced RNAi and conservation of the dREAM complex mutants suggests new therapeutic avenues to boost antiviral defenses.

tiny-count: a counting tool for hierarchical classification and quantification of small RNA-seq reads with single-nucleotide precision.

Summary: tiny-count is a highly flexible counting tool that allows for hierarchical classification and quantification of small RNA reads from high-throughput sequencing data. Selection rules can be used to filter reads by 5' nucleotide, length, position of alignments in relation to reference features, and by the number of mismatches to reference sequences. tiny-count can quantify reads aligned to a genome or directly to small RNA or transcript sequences. With tiny-count, users can quantify a single class of small RNAs or multiple classes in parallel. tiny-count can resolve distinct classes of small RNAs, for example, piRNAs and siRNAs, produced from the same locus. It can distinguish small RNA variants, such as miRNAs and isomiRs, with single-nucleotide precision. tRNA, rRNA, and other RNA fragments can also be quantified. tiny-count can be run alone or as part of tinyRNA, a workflow that provides a basic all-in-one command line-based solution for small RNA-seq data analysis, with documentation and statistics generated at each step for accurate and reproducible results. Availability and implementation: tiny-count and other tinyRNA tools are implemented in Python, C++, Cython, and R, and the workflow is coordinated with CWL. tiny-count and tinyRNA are free and open-source software distributed under the GPLv3 license. tiny-count can be installed via Bioconda (https://anaconda.org/bioconda/tiny-count) and both tiny-count and tinyRNA documentation and software downloads are available at https://github.com/MontgomeryLab/tinyRNA. Reference data, including genome and feature information, for certain species can be found at https://www.MontgomeryLab.org.

The International Bathymetric Chart of the Arctic Ocean Version 4.0.

Bathymetry (seafloor depth), is a critical parameter providing the geospatial context for a multitude of marine scientific studies. Since 1997, the International Bathymetric Chart of the Arctic Ocean (IBCAO) has been the authoritative source of bathymetry for the Arctic Ocean. IBCAO has merged its efforts with the Nippon Foundation-GEBCO-Seabed 2030 Project, with the goal of mapping all of the oceans by 2030. Here we present the latest version (IBCAO Ver. 4.0), with more than twice the resolution (200 × 200 m versus 500 × 500 m) and with individual depth soundings constraining three times more area of the Arctic Ocean (∼19.8% versus 6.7%), than the previous IBCAO Ver. 3.0 released in 2012. Modern multibeam bathymetry comprises ∼14.3% in Ver. 4.0 compared to ∼5.4% in Ver. 3.0. Thus, the new IBCAO Ver. 4.0 has substantially more seafloor morphological information that offers new insights into a range of submarine features and processes; for example, the improved portrayal of Greenland fjords better serves predictive modelling of the fate of the Greenland Ice Sheet.