Repetitive DNA symmetry elements negatively regulate gene expression in embryonic stem cells.

Transcription factor (TF) binding to genomic DNA elements constitutes one of the key mechanisms that regulates gene expression program in cells. Both consensus and nonconsensus DNA sequence elements influence the recognition specificity of TFs. Based on the analysis of experimentally determined c-Myc binding preferences to genomic DNA, here we statistically predict that certain repetitive, nonconsensus DNA symmetry elements can relatively reduce TF-DNA binding preferences. This is in contrast to a different set of repetitive, nonconsensus symmetry elements that can increase the strength of TF-DNA binding. Using c-Myc enhancer reporter system containing consensus motif flanked by nonconsensus sequences in embryonic stem cells, we directly demonstrate that the enrichment in such negatively regulating repetitive symmetry elements is sufficient to reduce the gene expression level compared with native genomic sequences. Negatively regulating repetitive symmetry elements around consensus c-Myc motif and DNA sequences containing consensus c-Myc motif flanked by entirely randomized sequences show similar expression baseline. A possible explanation for this observation is that rather than complete repression, negatively regulating repetitive symmetry elements play a regulatory role in fine-tuning the reduction of gene expression, most probably by binding TFs other than c-Myc.

Esrrb is a cell-cycle-dependent associated factor balancing pluripotency and XEN differentiation.

Cell cycle and differentiation decisions are linked; however, the underlying principles that drive these decisions are unclear. Here, we combined cell-cycle reporter system and single-cell RNA sequencing (scRNA-seq) profiling to study the transcriptomes of embryonic stem cells (ESCs) in the context of cell-cycle states and differentiation. By applying retinoic acid, to G1 and G2/M ESCs, we show that, while both populations can differentiate toward epiblast stem cells (EpiSCs), only G2/M ESCs could differentiate into extraembryonic endoderm cells. We identified Esrrb, a pluripotency factor that is upregulated during G2/M, as a driver of extraembryonic endoderm stem cell (XEN) differentiation. Furthermore, enhancer chromatin states based on wild-type (WT) and ESRRB knockout (KO) ESCs show association of ESRRB with XEN poised enhancers. G1 cells overexpressing Esrrb allow ESCs to produce XENs, while ESRRB-KO ESCs lost their potential to differentiate into XEN. Overall, this study reveals a vital link between Esrrb and cell-cycle states during the exit from pluripotency.

DNA methylation patterns expose variations in enhancer-chromatin modifications during embryonic stem cell differentiation.

In mammals, cellular identity is defined through strict regulation of chromatin modifications and DNA methylation that control gene expression. Methylation of cytosines at CpG sites in the genome is mainly associated with suppression; however, the reason for enhancer-specific methylation is not fully understood. We used sequential ChIP-bisulfite-sequencing for H3K4me1 and H3K27ac histone marks. By collecting data from the same genomic region, we identified enhancers differentially methylated between these two marks. We observed a global gain of CpG methylation primarily in H3K4me1-marked nucleosomes during mouse embryonic stem cell differentiation. This gain occurred largely in enhancer regions that regulate genes critical for differentiation. The higher levels of DNA methylation in H3K4me1- versus H3K27ac-marked enhancers, despite it being the same genomic region, indicates cellular heterogeneity of enhancer states. Analysis of single-cell RNA-seq profiles demonstrated that this heterogeneity correlates with gene expression during differentiation. Furthermore, heterogeneity of enhancer methylation correlates with transcription start site methylation. Our results provide insights into enhancer-based functional variation in complex biological systems.

ConSurf-DB: An accessible repository for the evolutionary conservation patterns of the majority of PDB proteins.

Patterns observed by examining the evolutionary relationships among proteins of common origin can reveal the structural and functional importance of specific residue positions. In particular, amino acids that are highly conserved (i.e., their positions evolve at a slower rate than other positions) are particularly likely to be of biological importance, for example, for ligand binding. ConSurf is a bioinformatics tool for accurately estimating the evolutionary rate of each position in a protein family. Here we introduce a new release of ConSurf-DB, a database of precalculated ConSurf evolutionary conservation profiles for proteins of known structure. ConSurf-DB provides high-accuracy estimates of the evolutionary rates of the amino acids in each protein. A reliable estimate of a query protein's evolutionary rates depends on having a sufficiently large number of effective homologues (i.e., nonredundant yet sufficiently similar). With current sequence data, ConSurf-DB covers 82% of the PDB proteins. It will be updated on a regular basis to ensure that coverage remains high-and that it might even increase. Much effort was dedicated to improving the user experience. The repository is available at https://consurfdb.tau.ac.il/. BROADER AUDIENCE: By comparing a protein to other proteins of similar origin, it is possible to determine the extent to which each amino acid position in the protein evolved slowly or rapidly. A protein's evolutionary profile can provide valuable insights: For example, amino acid positions that are highly conserved (i.e., evolved slowly) are particularly likely to be of structural and/or functional importance, for example, for ligand binding and catalysis. We introduce here a new and improved version of ConSurf-DB, a continually updated database that provides precalculated evolutionary profiles of proteins with known structure.

CRISPys: Optimal sgRNA Design for Editing Multiple Members of a Gene Family Using the CRISPR System.

The development of the CRISPR-Cas9 system in recent years has made eukaryotic genome editing, and specifically gene knockout for reverse genetics, a simple and effective task. The system is directed to a genomic target site by a programmed single-guide RNA (sgRNA) that base-pairs with it, subsequently leading to site-specific modifications. However, many gene families in eukaryotic genomes exhibit partially overlapping functions, and thus, the knockout of one gene might be concealed by the function of the other. In such cases, the reduced specificity of the CRISPR-Cas9 system, which may lead to the modification of genomic sites that are not identical to the sgRNA, can be harnessed for the simultaneous knockout of multiple homologous genes. We introduce CRISPys, an algorithm for the optimal design of sgRNAs that would potentially target multiple members of a given gene family. CRISPys first clusters all the potential targets in the input sequences into a hierarchical tree structure that specifies the similarity among them. Then, sgRNAs are proposed in the internal nodes of the tree by embedding mismatches where needed, such that the efficiency to edit the induced targets is maximized. We suggest several approaches for designing the optimal individual sgRNA and an approach to compute the optimal set of sgRNAs for cases when the experimental platform allows for more than one. The latter may optionally account for the homologous relationships among gene-family members. We further show that CRISPys outperforms simpler alignment-based techniques by in silico examination over all gene families in the Solanum lycopersicum genome.