Enhancers integrate combinatorial inputs from sequence-specific transcription factors (TFs) and their activity must be calibrated to achieve precise spatiotemporal control of transcript dosage. Here we demonstrate that the sequence-specific repressors SNAI1 and SNAI2 (i.e. SNAIL and SLUG) quantitatively tune enhancer activity. In human neural crest cells, SNAI1/2 occupy a subset of active enhancers, where their depletion increases H3K27ac, chromatin accessibility, and enhancer regulatory potential. Changes in SNAI1/2 binding motifs contribute to enhancer divergence between human and chimpanzee, suggesting an evolutionary role for the repressor-mediated tuning. Single-molecule chromatin profiling using Deaminase-Assisted Fiber-seq (DAF-seq) reveals that individual enhancers toggle between an ensemble of open and nucleosome-dense chromatin states. While transcriptional activators increase the fraction of the open states, SNAI1/2 shift the equilibrium toward nucleosome-occupied states. This impedes binding of activator TFs, without fully repressing the enhancer. We propose that SNAI1/2 function as a molecular dimmer switch—modulating nucleosome dynamics to calibrate enhancer output.
Lucia Ichino, Kaelan J. Brennan, Ben Mallory et al.· bioRxiv· 0 citations
SUMMARY Human genome sequencing typically relies on mapping reads to a reference genome to call variants, but this approach introduces technical biases, excluding duplicated and structurally polymorphic regions of the genome. To overcome this, we present a telomere-to-telomere genome benchmark with near-perfect accuracy across 99.4% of the diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), which were absent from prior benchmarks. We annotated genes and repeats on both haplotypes, including 19,956 protein-coding genes on the maternal haplotype and 19,190 on the paternal haplotype, and developed new methods to measure the accuracy of reads, phased variant call sets, and assemblies against a diploid reference. Genome-wide analyses show that de novo assembly resolves 2%–7% more sequence and outperforms variant calling accuracy by an order of magnitude, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.
Nancy F. Hansen, Nathan Dwarshuis, Hyun Joo Ji et al.· Cell· 7 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
