Chromatin regulators play a major role in establishing and maintaining gene expression states. Yet how they control gene expression in single cells, quantitatively and over time, remains unclear. We used time-lapse microscopy to analyze the dynamic effects of four silencers associated with diverse modifications: DNA methylation, histone deacetylation, and histone methylation. For all regulators, silencing and reactivation occurred in all-or-none events, enabling the regulators to modulate the fraction of cells silenced rather than the amount of gene expression. These dynamics could be described by a three-state model involving stochastic transitions between active, reversibly silent, and irreversibly silent states. Through their individual transition rates, these regulators operate over different time scales and generate distinct types of epigenetic memory. Our results provide a framework for understanding and engineering mammalian chromatin regulation and epigenetic memory.

Production of most eukaryotic mRNAs requires splicing of introns from pre-mRNA. The splicing reaction requires definition of splice sites, which are initially recognized in either intron-spanning (‘intron definition’) or exon-spanning (‘exon definition’) pairs. To understand how exon and intron length and splice site recognition mode impact splicing, we measured splicing rates genome-wide in Drosophila, using metabolic labeling/RNA sequencing and new mathematical models to estimate rates. We found that the modal intron length range of 60–70 nt represents a local maximum of splicing rates, but that much longer exon-defined introns are spliced even faster and more accurately. We observed unexpectedly low variation in splicing rates across introns in the same gene, suggesting the presence of gene-level influences, and we identified multiple gene level variables associated with splicing rate. Together our data suggest that developmental and stress response genes may have preferentially evolved exon definition in order to enhance the rate or accuracy of splicing.

Production of most eukaryotic mRNAs requires splicing of introns from pre-mRNA. The splicing reaction requires definition of splice sites, which are initially recognized in either intron-spanning ("intron definition") or exon-spanning ("exon definition") pairs. To understand how exon and intron length and splice site recognition mode impact splicing, we measured splicing rates genome-wide in Drosophila, using metabolic labeling/RNA sequencing and new mathematical models to estimate rates. We found that the modal intron length range of 60-70 nt represents a local maximum of splicing rates, but that much longer exon-defined introns are spliced even faster and more accurately. Surprisingly, we observed low variation in splicing rates across introns in the same gene, suggesting the presence of gene-level influences, and we identified multiple gene level variables associated with splicing rate. Together our data suggest that developmental and stress response genes may have preferentially evolved exon definition in order to enhance rates of splicing.

Classifying taxa, including those that have not previously been identified, is a key task in characterizing the microbial communities of under-described habitats, including permanently ice-covered lakes in the dry valleys of the Antarctic. Current supervised phylogeny-based methods fall short on recognizing species assembled from metagenomic datasets from such habitats, as they are often incomplete or lack closely known relatives. Here, we report an efficient software suite, "Genome Constellation", that is capable of rapidly characterizing a large number of metagenome-assembled genomes. Genome Constellation estimates similarities between genomes based on their k-mer matches, and subsequently uses these similarities for classification, clustering, and visualization. The clusters of reference genomes formed by Genome Constellation closely resemble known phylogenetic relationships while simultaneously revealing unexpected connections. In a dataset containing 1,693 draft genomes assembled from the Antarctic lake communities where only 40% could be placed in a phylogenetic tree, Genome Constellation improves taxa assignment to 61%. The clustering-based analysis revealed several novel taxa groups, including six clusters that may represent new bacterial phyla. Remarkably, we discovered 63 new giant viruses, 3 of which could not be found by using the traditional marker-based approach. In summary, we demonstrate that Genome Constellation provides an unbiased option to rapidly analyze a large number of microbial genomes and visually explore their relatedness. The software is available under BSD license at: https://bitbucket.org/berkeleylab/jgi-genomeconstellation/.

Production of most eukaryotic mRNAs requires splicing of introns from pre-mRNA.The splicing reaction requires definition of splice sites, which are initially recognized in either intron-spanning ('intron definition') or exon-spanning ('exon definition') pairs. To understand how exon and intron length and splice site recognition mode impact splicing, we measured splicing rates genome-wide in Drosophila, using metabolic labeling/RNA sequencing and new mathematical models to estimate rates. We found that the modal intron length range of 60-70 nt represents a local maximum of splicing rates, but that much longer exon-defined introns are spliced even faster and more accurately. We observed unexpectedly low variation in splicing rates across introns in the same gene, suggesting the presence of gene-level influences, and we identified multiple gene level variables associated with splicing rate. Together our data suggest that developmental and stress response genes may have preferentially evolved exon definition in order to enhance the rate or accuracy of splicing.