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Abstract Genetic engineering of cis-regulatory elements in crop plants is a promising strategy to ensure food security. However, such engineering is currently hindered by our limited knowledge of plant cis-regulatory elements. Here, we adapted self-transcribing active regulatory region sequencing (STARR-seq)—a technology for the high-throughput identification of enhancers—for its use in transiently transformed tobacco (Nicotiana benthamiana) leaves. We demonstrate that the optimal placement in the reporter construct of enhancer sequences from a plant virus, pea (Pisum sativum) and wheat (Triticum aestivum), was just upstream of a minimal promoter and that none of these four known enhancers was active in the 3′ untranslated region of the reporter gene. The optimized assay sensitively identified small DNA regions containing each of the four enhancers, including two whose activity was stimulated by light. Furthermore, we coupled the assay to saturation mutagenesis to pinpoint functional regions within an enhancer, which we recombined to create synthetic enhancers. Our results describe an approach to define enhancer properties that can be performed in potentially any plant species or tissue transformable by Agrobacterium and that can use regulatory DNA derived from any plant genome.
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Comprehensive Genomic Discovery of Non-Coding Transcriptional Enhancers in the African Malaria Vector Anopheles coluzzii
Almost all regulation of gene expression in eukaryotic genomes is mediated by the action of distant non-coding transcriptional enhancers upon proximal gene promoters. Enhancer locations cannot be accurately predicted bioinformatically because of the absence of a defined sequence code, and thus functional assays are required for their direct detection. Here we used a massively parallel reporter assay, Self-Transcribing Active Regulatory Region sequencing (STARR-seq), to generate the first comprehensive genome-wide map of enhancers in Anopheles coluzzii , a major African malaria vector in the Gambiae species complex. The screen was carried out by transfecting reporter libraries created from the genomic DNA of 60 wild A. coluzzii from Burkina Faso into A. coluzzii 4a3A cells, in order to functionally query enhancer activity of the natural population within the homologous cellular context. We report a catalog of 3,288 active genomic enhancers that were significant across three biological replicates, 74% of them located in intergenic and intronic regions. The STARR-seq enhancer screen is chromatin-free and thus detects inherent activity of a comprehensive catalog of enhancers that may be restricted in vivo to specific cell types or developmental stages. Testing of a validation panel of enhancer candidates using manual luciferase assays confirmed enhancer function in 26 of 28 (93%) of the candidates over a wide dynamic range of activity from two to at least 16-fold activity above baseline. The enhancers occupy only 0.7% of the genome, and display distinct composition features. The enhancer compartment is significantly enriched for 15 transcription factor binding site signatures, and displays divergence for specific dinucleotide repeats, as compared to matched non-enhancer genomic controls. The genome-wide catalog of A. coluzzii enhancers is publicly available in a simple searchable graphic format. This enhancer catalogue will be valuable in linking genetic and phenotypic variation, in identifying regulatory elements that could be employed in vector manipulation, and in better targeting of chromosome editing to minimize extraneous regulation influences on the introduced sequences. Importance: Understanding the role of the non-coding regulatory genome in complex disease phenotypes is essential, but even in well-characterized model organisms, identification of regulatory regions within the vast non-coding genome remains a challenge. We used a large-scale assay to generate a genome wide map of transcriptional enhancers. Such a catalogue for the important malaria vector, Anopheles coluzzii , will be an important research tool as the role of non-coding regulatory variation in differential susceptibility to malaria infection is explored and as a public resource for research on this important insect vector of disease.
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- Award ID(s):
- 1947257
- PAR ID:
- 10312953
- Date Published:
- Journal Name:
- Frontiers in Genetics
- Volume:
- 12
- ISSN:
- 1664-8021
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Introduction Various sequencing based approaches are used to identify and characterize the activities of cis -regulatory elements in a genome-wide fashion. Some of these techniques rely on indirect markers such as histone modifications (ChIP-seq with histone antibodies) or chromatin accessibility (ATAC-seq, DNase-seq, FAIRE-seq), while other techniques use direct measures such as episomal assays measuring the enhancer properties of DNA sequences (STARR-seq) and direct measurement of the binding of transcription factors (ChIP-seq with transcription factor-specific antibodies). The activities of cis -regulatory elements such as enhancers, promoters, and repressors are determined by their sequence and secondary processes such as chromatin accessibility, DNA methylation, and bound histone markers. Methods Here, machine learning models are employed to evaluate the accuracy with which cis -regulatory elements identified by various commonly used sequencing techniques can be predicted by their underlying sequence alone to distinguish between cis -regulatory activity that is reflective of sequence content versus secondary processes. Results and discussion Models trained and evaluated on D. melanogaster sequences identified through DNase-seq and STARR-seq are significantly more accurate than models trained on sequences identified by H3K4me1, H3K4me3, and H3K27ac ChIP-seq, FAIRE-seq, and ATAC-seq. These results suggest that the activity detected by DNase-seq and STARR-seq can be largely explained by underlying DNA sequence, independent of secondary processes. Experimentally, a subset of DNase-seq and H3K4me1 ChIP-seq sequences were tested for enhancer activity using luciferase assays and compared with previous tests performed on STARR-seq sequences. The experimental data indicated that STARR-seq sequences are substantially enriched for enhancer-specific activity, while the DNase-seq and H3K4me1 ChIP-seq sequences are not. Taken together, these results indicate that the DNase-seq approach identifies a broad class of regulatory elements of which enhancers are a subset and the associated data are appropriate for training models for detecting regulatory activity from sequence alone, STARR-seq data are best for training enhancer-specific sequence models, and H3K4me1 ChIP-seq data are not well suited for training and evaluating sequence-based models for cis -regulatory element prediction.more » « less
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Abstract Insulators arecis-regulatory elements that separate transcriptional units, whereas silencers are elements that repress transcription regardless of their position. In plants, these elements remain largely uncharacterized. Here, we use the massively parallel reporter assay Plant STARR-seq with short fragments of eight large insulators to identify more than 100 fragments that block enhancer activity. The short fragments can be combined to generate more powerful insulators that abolish the capacity of the strong viral 35S enhancer to activate the 35S minimal promoter. Unexpectedly, when tested upstream of weak enhancers, these fragments act as silencers and repress transcription. Thus, these elements are capable of both insulating or repressing transcription dependent upon regulatory context. We validate our findings in stable transgenicArabidopsis, maize, and rice plants. The short elements identified here should be useful building blocks for plant biotechnology efforts.more » « less
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Comparative genomic studies of social insects suggest that changes in gene regulation are associated with evolutionary transitions in social behavior, but the activity of predicted regulatory regions has not been tested empirically. We used STARR-seq, a high-throughput enhancer discovery tool, to identify and measure the activity of enhancers in the socially variable sweat bee,Lasioglossum albipes. We identified over 36,000 enhancers in theL. albipesgenome from three social and three solitary populations. Many enhancers were identified in only a subset ofL. albipespopulations, revealing rapid divergence in regulatory regions within this species. Population-specific enhancers were often proximal to the same genes across populations, suggesting compensatory gains and losses of regulatory regions may preserve gene activity. We also identified 1182 enhancers with significant differences in activity between social and solitary populations, some of which are conserved regulatory regions across species of bees. These results indicate that social trait variation inL. albipesis driven both by the fine-tuning of ancient enhancers as well as lineage-specific regulatory changes. Combining enhancer activity with population genetic data revealed variants associated with differences in enhancer activity and identified a subset of differential enhancers with signatures of selection associated with social behavior. Together, these results provide the first empirical map of enhancers in a socially flexible bee and highlight links between cis-regulatory variation and the evolution of social behavior.more » « less
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Abstract Transcription is the primary regulatory step in gene expression. Divergent transcription initiation from promoters and enhancers produces stable RNAs from genes and unstable RNAs from enhancers1,2. Nascent RNA capture and sequencing assays simultaneously measure gene and enhancer activity in cell populations3. However, fundamental questions about the temporal regulation of transcription and enhancer–gene coordination remain unanswered, primarily because of the absence of a single-cell perspective on active transcription. In this study, we present scGRO–seq—a new single-cell nascent RNA sequencing assay that uses click chemistry—and unveil coordinated transcription throughout the genome. We demonstrate the episodic nature of transcription and the co-transcription of functionally related genes. scGRO–seq can estimate burst size and frequency by directly quantifying transcribing RNA polymerases in individual cells and can leverage replication-dependent non-polyadenylated histone gene transcription to elucidate cell cycle dynamics. The single-nucleotide spatial and temporal resolution of scGRO–seq enables the identification of networks of enhancers and genes. Our results suggest that the bursting of transcription at super-enhancers precedes bursting from associated genes. By imparting insights into the dynamic nature of global transcription and the origin and propagation of transcription signals, we demonstrate the ability of scGRO–seq to investigate the mechanisms of transcription regulation and the role of enhancers in gene expression.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fgene.2021.785934
