Project description:Arabidopsis gene expression is regulated by more than 1,900 transcription factors (TFs), which have been identified genome-wide by the presence of well-conserved DNA binding domains. Activator TFs contain activation domains (ADs) that recruit coactivator complexes; however, for most Arabidopsis TFs, we lack knowledge about the presence, location, and transcriptional strength of their ADs. To address this gap, we experimentally identified Arabidopsis ADs on a proteome-wide scale, finding that over half of Arabidopsis TFs carry an AD. We annotated 1,553 ADs, the vast majority of which were previously unknown. We used the dataset generated to develop a neural network to accurately predict ADs and to identify sequence features necessary to recruit coactivator complexes. We uncovered six distinct sequence feature combinations that resulted in activation activity, providing a framework to interrogate activation domain sub-functionalization. Furthermore, we identified activation domains within the ancient AUXIN RESPONSE FACTOR (ARF) family of transcription factors, finding conservation of AD positioning in distinct clades. Our findings provide a deep resource for understanding transcriptional activation, a framework for examination of function within intrinsically disordered regions, and a predictive model of activation domains.
Project description:Genomes are arranged non-randomly in the 3D space of the cell nucleus. Here, we have developed HIPMap, a high-precision, high-throughput, automated fluorescent in situ hybridization imaging pipeline, for mapping of the spatial location of genome regions at large scale. High-throughput imaging position mapping (HIPMap) enabled an unbiased siRNA screen for factors involved in genome organization in human cells. We identify 50 cellular factors required for proper positioning of a set of functionally diverse genomic loci. Positioning factors include chromatin remodelers, histone modifiers, and nuclear envelope and pore proteins. Components of the replication and post-replication chromatin re-assembly machinery are prominently represented among positioning factors, and timely progression of cells through replication, but not mitosis, is required for correct gene positioning. Our results establish a method for the large-scale mapping of genome locations and have led to the identification of a compendium of cellular factors involved in spatial genome organization.
Project description:Viruses encode transcriptional regulatory proteins critical for controlling viral and host gene expression. Given their multifunctional nature and high sequence divergence, it is unclear which viral proteins can affect transcription and which specific sequences contribute to this function. Using a high-throughput assay, we measured the transcriptional regulatory potential of over 60,000 protein tiles across ~1,500 proteins from 11 coronaviruses and all nine human herpesviruses. We discovered hundreds of new transcriptional effector domains, including a conserved repression domain in all coronavirus Spike homologs, dual activation-repression domains in VIRFs, and an activation domain in six herpesvirus homologs of the single-stranded DNA-binding protein that we show is important for viral replication and late gene expression in KSHV. For the effector domains we identified, we investigated their mechanisms via high-throughput sequence and chemical perturbations, pinpointing sequence motifs essential for function. This work massively expands viral protein annotations, serving as a springboard for studying their biological and health implications and providing new candidates for compact gene regulation tools.
Project description:Plant tissues are composed of diverse cell populations, but their individual transcriptional profiles are not well characterized. High-throughput single cell RNA sequencing technologies can deconvolute heterogeneous tissues but have not been adopted for plants. Exploiting Arabidopsis root protoplasts as a model, we used Drop-seq to profile >4,000 individual plant cells, capturing a diversity of cell types, identifying novel marker genes, and illuminating developmental trajectories of endodermis and hair cells.
Project description:We introduce the Multiplexed Editing Regulatory Assay (MERA), a high-throughput CRISPR/Cas9-based approach that analyzes the regulatory genome for function in its native context. By tiling thousands of mutations across ~40 kb of cis-regulatory genomic space and using knock-in GFP reporters to read out gene activity, we obtain quantitative information on the contribution of cis-regulatory regions to gene expression. In addition, we performed a deep-sequencing strategy to find basepair-resolution functional motifs involved in regulation of the gene by sequencing thousands of functional and non-functional genotypes at genomic locations perturbed by specific guide RNAs.
Project description:We introduce the Multiplexed Editing Regulatory Assay (MERA), a high-throughput CRISPR/Cas9-based approach that analyzes the regulatory genome for function in its native context. By tiling thousands of mutations across ~40 kb of cis-regulatory genomic space and using knock-in GFP reporters to read out gene activity, we obtain quantitative information on the contribution of cis-regulatory regions to gene expression. In addition, we performed a deep-sequencing strategy to find basepair-resolution functional motifs involved in regulation of the gene by sequencing thousands of functional and non-functional genotypes at genomic locations perturbed by specific guide RNAs. Design of 3908 gRNAs to perturb regulatory regions associated with the genes Tdgf1,Nanog,Zfp42 and Rpp25 as well as 10 GFP-targetting positive controls. Also, deep-sequencing of genomic regions mutated by 6 selected gRNAs after sorting the electroporated cells into GFP-positive and GFP-negative populations.
Project description:Deciphering immune recognition is critical for understanding a broad range of diseases and for the development of effective vaccines and immunotherapies. Efforts to do so are limited by a lack of technologies capable of simultaneously capturing the complexity of adaptive immunoreceptor repertoires and the landscape of potential antigens. To address this, we present receptor-antigen pairing by targeted retroviruses, which combines viral pseudotyping and molecular engineering approaches to enable one-pot library-on-library interaction screens by displaying antigens on the surface of lentiviruses and encoding their identity in the viral genome. Antigen-specific viral infection of cell lines expressing human T or B cell receptors allows readout of both antigen and receptor identities via single-cell sequencing. The resulting system is modular, scalable and compatible with any cell type. These techniques provide a suite of tools for targeted viral entry, molecular engineering and interaction screens with broad potential applications.