In embryonic stem cells (ESCs), a core transcription factor (TF) network establishes the gene expression program necessary for pluripotency. To address how interactions between four key TFs contribute to cis-regulation in mouse ESCs, we assayed two massively parallel reporter assay (MPRA) libraries composed of binding sites for SOX2, POU5F1 (OCT4), KLF4, and ESRRB. Comparisons between synthetic cis-regulatory elements and genomic sequences with comparable binding site configurations revealed some aspects of a regulatory grammar. The expression of synthetic elements is influenced by both the number and arrangement of binding sites. This grammar plays only a small role for genomic sequences, as the relative activities of genomic sequences are best explained by the predicted occupancy of binding sites, regardless of binding site identity and positioning. Our results suggest that the effects of transcription factor binding sites (TFBS) are influenced by the order and orientation of sites, but that in the genome the overall occupancy of TFs is the primary determinant of activity.

The overall survival of lung cancer patients remains dismal despite the availability of targeted therapies. Oncofetal protein SALL4 is a novel cancer target. We herein report that SALL4 was aberrantly expressed in a subset of lung cancer patients with poor survival. SALL4 silencing by RNA interference or SALL4 peptide inhibitor treatment led to impaired lung cancer cell growth. Expression profiling of SALL4-knockdown cells demonstrated that both the EGFR and IGF1R signaling pathways were affected. Connectivity Map analysis revealed the HDAC inhibitor entinostat as a potential drug in treating SALL4-expressing cancers, and this was confirmed in 17 lung cancer cell lines. In summary, we report for the first time that entinostat can target SALL4-positive lung cancer. This lays the foundation for future clinical studies evaluating the therapeutic efficacy of entinostat in SALL4-positive lung cancer patients.

A classical model of gene regulation is that enhancers provide specificity whereas core promoters provide a modular site for the assembly of the basal transcriptional machinery. However, examples of core promoter specificity have led to an alternate hypothesis in which specificity is achieved by core promoters with different sequence motifs that respond differently to genomic environments containing different enhancers and chromatin landscapes. To distinguish between these models, we measured the activities of hundreds of diverse core promoters in four different genomic locations and, in a complementary experiment, six different core promoters at thousands of locations across the genome. Although genomic locations had large effects on expression, the intrinsic activities of different classes of promoters were preserved across genomic locations, suggesting that core promoters are modular regulatory elements whose activities are independently scaled up or down by different genomic locations. This scaling of promoter activities is nonlinear and depends on the genomic location and the strength of the core promoter. Our results support the classical model of regulation in which diverse core promoter motifs set the intrinsic strengths of core promoters, which are then amplified or dampened by the activities of their genomic environments.

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One model for how cells integrate cis-regulatory information is that different classes of core promoters respond specifically to certain genomic environments. We tested this model using a genome-integrated massively parallel reporter assay (MPRA) to measure the activity of hundreds of diverse core promoters at four genomic locations and, in a complementary experiment, six core promoters at thousands of genomic locations. While genomic locations had large effects on expression, the relative strengths of core promoters were preserved across locations regardless of promoter class, suggesting that their intrinsic activities are scaled by diverse genomic environments. The extent of scaling depends on the genomic location and the strength of the core promoter, but not on its class. Our results support a modular genome in which genomic environments scale the activities of core promoters.

Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This 'noise' in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome. To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we performed the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We found that the mean and noise of expression correlate with different histone modifications. We quantified the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assigned the extrinsic component to differences between the CD24+ 'stem-like' sub-state and the more 'differentiated' sub-state. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for 'safe-harbor' loci. Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome, and that the data generated by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.

We developed a single-cell massively parallel reporter assay (scMPRA) to measure the activity of libraries of cis-regulatory sequences (CRSs) across multiple cell-types simultaneously. As a proof of concept, we assayed a library of core promoters in a mixture of HEK293 and K562 cells and showed that scMPRA is a reproducible, highly parallel, single-cell reporter gene assay. Our results show that housekeeping promoters and CpG island promoters have lower activity in K562 cells relative to HEK293, which likely reflects developmental differences between the cell lines. Within K562 cells, scMPRA identified a subset of developmental promoters that are upregulated in the CD34+/CD38− sub-state, confirming this state as more “stem-like.” Finally, we deconvolved the intrinsic and extrinsic components of promoter cell-to-cell variability and found that developmental promoters have a higher proportion of extrinsic noise compared to housekeeping promoters, which may reflect the responsiveness of developmental promoters to the cellular environment. We anticipate scMPRA will be widely applicable for studying the role of CRSs across diverse cell types.

Single cell biology has the potential to elucidate many critical biological processes and diseases, from development and regeneration to cancer. Single cell analyses are uncovering the molecular diversity of cells, revealing a clearer picture of the variation among and between different cell types. New techniques are beginning to unravel how differences in cell state-transcriptional, epigenetic, and other characteristics-can lead to different cell fates among genetically identical cells, which underlies complex processes such as embryonic development, drug resistance, response to injury, and cellular reprogramming. Single cell technologies also pose significant challenges relating to processing and analyzing vast amounts of data collected. To realize the potential of single cell technologies, new computational approaches are needed. On March 17-19, 2021, experts in single cell biology met virtually for the Keystone eSymposium "Single Cell Biology" to discuss advances both in single cell applications and technologies.