Gene-Centered Yeast One-Hybrid Assays

Bass, Juan I. Fuxman; Reece‐Hoyes, John S.; Walhout, Albertha J.M.

doi:10.1101/pdb.top077669

Cited by 16 publications

(11 citation statements)

References 31 publications

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“…The importance of the GGG motif in neuronal enhancers was evident in most of our analyses; however, its interpretation was a challenge because the binding TFs were unknown. While yeast one‐hybrid (Y1H) experiments have been previously used to reverse‐engineer which transcription factors can bind a motif of interest, lowly expressed TFs may be underrepresented in the cDNA library and interactions that occur in vivo may be missed (such as those dependent of post‐transcriptional modifications) (Southall et al , ; Fuxman Bass et al , ). Here, we have used a novel in vivo approach, in which we identify the changes that overexpression of potential TF candidates causes in chromatin accessibility at the bulk ATAC‐seq level.…”

Section: Discussionmentioning

confidence: 99%

Identification of genomic enhancers through spatial integration of single‐cell transcriptomics and epigenomics

González-Blas

Quan

Duran-Romaña

et al. 2020

Molecular Systems Biology

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Single-cell technologies allow measuring chromatin accessibility and gene expression in each cell, but jointly utilizing both layers to map bona fide gene regulatory networks and enhancers remains challenging. Here, we generate independent single-cell RNA-seq and singlecell ATAC-seq atlases of the Drosophila eye-antennal disc and spatially integrate the data into a virtual latent space that mimics the organization of the 2D tissue using ScoMAP (Single-Cell Omics Mapping into spatial Axes using Pseudotime ordering). To validate spatially predicted enhancers, we use a large collection of enhancerreporter lines and identify~85% of enhancers in which chromatin accessibility and enhancer activity are coupled. Next, we infer enhancer-to-gene relationships in the virtual space, finding that genes are mostly regulated by multiple, often redundant, enhancers. Exploiting cell type-specific enhancers, we deconvolute cell typespecific effects of bulk-derived chromatin accessibility QTLs. Finally, we discover that Prospero drives neuronal differentiation through the binding of a GGG motif. In summary, we provide a comprehensive spatial characterization of gene regulation in a 2D tissue.

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Section: Discussionmentioning

confidence: 99%

Identification of genomic enhancers through spatial integration of single‐cell transcriptomics and epigenomics

González-Blas

Quan

Duran-Romaña

et al. 2020

Molecular Systems Biology

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“…Such perturbations in CRE sites within putative promoter regions of stem-expressed genes resulted in different GRNs for BTx623 and Della cultivars. However, further studies are needed to confirm “real” TF-target interactions through experiments such as yeast-one hybrid (Y1H) (Arda and Walhout, 2009; Fuxman Bass, Reece-Hoyes and Walhout, 2016) or DAP-seq (O’Malley et al , 2016). Nonetheless, the current study provides a starting point for more in-depth experiments to assess the extent to which these promoter elements are tissue-specific through targeted mutagenesis, for example, using tissue-specific genome modification (Schürholz et al , 2018; Decaestecker et al , 2019; Shi et al , 2019; Ali, Mahfouz and Mansoor, 2020).…”

Section: Discussionmentioning

confidence: 99%

Sorghum bicolorcultivars have divergent and dynamic gene regulatory networks that control the temporal expression of genes in stem tissue

Arachchilage

Mullet

Marshall‐Colón

2020

Preprint

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The genetic engineering of value-added traits such as the accumulation of bioproducts 21 in high biomass C4 grass stems is one promising strategy to make plant-derived biofuels more 22 economical for industrial use. A first step toward achieving this goal is to identify stem-specific 23 promoters that can drive the expression of genes of interest with good temporal and spatial 24 specificity. However, a comprehensive characterization of the spatial-temporal regulatory 25 elements of stem tissue-specific promoters for C4 grasses has not been reported. Therefore, we 26 performed an in-silico analysis on Sorghum bicolor cv BTx623 transcriptomes from multiple 27 tissues over development to identify stem-expressed genes. The analysis identified 10 genes that 28 are "Always-On-Stem-Specific," 59 genes that are "Temporally-Stem-Specific during early 29 development," and 21 genes that are "Temporally-Stem-Specific during late development." 30 Promoter analysis revealed common and/or unique cis-regulatory elements in promoters of genes within each of the three categories. Subsequent gene regulatory network (GRN) analysis revealed 32 that different transcriptional regulatory programs are responsible for the temporal activation of the 33 stem-expressed genes. The analysis of temporal stem GRNs between sweet (cv Della) and grain 34 (cv BTx623) sorghum varieties revealed genetic variation that could influence the regulatory 35 landscape. This study provides new insights about sorghum stem biology, and information for 36 future genetic engineering efforts to fine-tune the spatial-temporal expression of transgenes in C4 37 grass stems. 38 39 40 High biomass grasses, such as sorghum (Sorghum bicolor), miscanthus (Miscanthus x 41 giganteus), switchgrass (Panicum virgatum), and sugarcane (Saccharum sp.), offer an abundant 42 and renewable source of biomass for biofuels production (McLaughlin and Kszos, 2005; Rooney 43 et al.

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“…This method involves two components: a ‘DNA-bait’ such as cytokine gene promoter, and a ‘TF-prey’. The DNA-bait is cloned upstream of two reporter genes (LacZ and HIS3) and both constructs are integrated into the yeast genome ( 24 , 25 ). The DNA-bait strains generated are then mated with yeast strains expressing TFs fused to the yeast Gal4 activation domain (AD), and if the TF binds the regulatory region, the AD moiety activates the reporter genes.…”

Section: Methodsmentioning

confidence: 99%

Global landscape of mouse and human cytokine transcriptional regulation

Pro

Imedio

Santoso

et al. 2018

Nucleic Acids Research

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Cytokines are cell-to-cell signaling proteins that play a central role in immune development, pathogen responses, and diseases. Cytokines are highly regulated at the transcriptional level by combinations of transcription factors (TFs) that recruit cofactors and the transcriptional machinery. Here, we mined through three decades of studies to generate a comprehensive database, CytReg, reporting 843 and 647 interactions between TFs and cytokine genes, in human and mouse respectively. By integrating CytReg with other functional datasets, we determined general principles governing the transcriptional regulation of cytokine genes. In particular, we show a correlation between TF connectivity and immune phenotype and disease, we discuss the balance between tissue-specific and pathogen-activated TFs regulating each cytokine gene, and cooperativity and plasticity in cytokine regulation. We also illustrate the use of our database as a blueprint to predict TF–disease associations and identify potential TF–cytokine regulatory axes in autoimmune diseases. Finally, we discuss research biases in cytokine regulation studies, and use CytReg to predict novel interactions based on co-expression and motif analyses which we further validated experimentally. Overall, this resource provides a framework for the rational design of future cytokine gene regulation studies.

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Gene-Centered Yeast One-Hybrid Assays

Cited by 16 publications

References 31 publications

Identification of genomic enhancers through spatial integration of single‐cell transcriptomics and epigenomics

Identification of genomic enhancers through spatial integration of single‐cell transcriptomics and epigenomics

Sorghum bicolorcultivars have divergent and dynamic gene regulatory networks that control the temporal expression of genes in stem tissue

Global landscape of mouse and human cytokine transcriptional regulation

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