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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Global patterns of enhancer activity during sea urchin embryogenesis assessed by eRNA profiling
We used capped analysis of gene expression with sequencing (CAGE-seq) to profile eRNA expression and enhancer activity during embryogenesis of a model echinoderm: the sea urchin, Strongylocentrotus purpuratus . We identified more than 18,000 enhancers that were active in mature oocytes and developing embryos and documented a burst of enhancer activation during cleavage and early blastula stages. We found that a large fraction (73.8%) of all enhancers active during the first 48 h of embryogenesis were hyperaccessible no later than the 128-cell stage and possibly even earlier. Most enhancers were located near gene bodies, and temporal patterns of eRNA expression tended to parallel those of nearby genes. Furthermore, enhancers near lineage-specific genes contained signatures of inputs from developmental gene regulatory networks deployed in those lineages. A large fraction (60%) of sea urchin enhancers previously shown to be active in transgenic reporter assays was associated with eRNA expression. Moreover, a large fraction (50%) of a representative subset of enhancers identified by eRNA profiling drove tissue-specific gene expression in isolation when tested by reporter assays. Our findings provide an atlas of developmental enhancers in a model sea urchin and support the utility of eRNA profiling as a tool for enhancer discovery and regulatory biology. The data generated in this study are available at Echinobase, the public database of information related to echinoderm genomics.
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- Award ID(s):
- 2004952
- NSF-PAR ID:
- 10342095
- Date Published:
- Journal Name:
- Genome Research
- Volume:
- 31
- Issue:
- 9
- ISSN:
- 1088-9051
- Page Range / eLocation ID:
- 1680 to 1692
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Wittkopp, Patricia (Ed.)Abstract Chromatin configuration is highly dynamic during embryonic development in animals, exerting an important point of control in transcriptional regulation. Yet there exists remarkably little information about the role of evolutionary changes in chromatin configuration to the evolution of gene expression and organismal traits. Genome-wide assays of chromatin configuration, coupled with whole-genome alignments, can help address this gap in knowledge in several ways. In this study we present a comparative analysis of regulatory element sequences and accessibility throughout embryogenesis in three sea urchin species with divergent life histories: a lecithotroph Heliocidaris erythrogramma, a closely related planktotroph H. tuberculata, and a distantly related planktotroph Lytechinus variegatus. We identified distinct epigenetic and mutational signatures of evolutionary modifications to the function of putative cis-regulatory elements in H. erythrogramma that have accumulated nonuniformly throughout the genome, suggesting selection, rather than drift, underlies many modifications associated with the derived life history. Specifically, regulatory elements composing the sea urchin developmental gene regulatory network are enriched for signatures of positive selection and accessibility changes which may function to alter binding affinity and access of developmental transcription factors to these sites. Furthermore, regulatory element changes often correlate with divergent expression patterns of genes involved in cell type specification, morphogenesis, and development of other derived traits, suggesting these evolutionary modifications have been consequential for phenotypic evolution in H. erythrogramma. Collectively, our results demonstrate that selective pressures imposed by changes in developmental life history rapidly reshape the cis-regulatory landscape of core developmental genes to generate novel traits and embryonic programs.more » « less
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The gene regulatory network (GRN) that underlies echinoderm skeletogenesis is a prominent model of GRN architecture and evolution. KirrelL is an essential downstream effector gene in this network and encodes an Ig-superfamily protein required for the fusion of skeletogenic cells and the formation of the skeleton. In this study, we dissected the transcriptional control region of the kirrelL gene of the purple sea urchin, Strongylocentrotus purpuratus . Using plasmid- and bacterial artificial chromosome-based transgenic reporter assays, we identified key cis -regulatory elements (CREs) and transcription factor inputs that regulate Sp-kirrelL , including direct, positive inputs from two key transcription factors in the skeletogenic GRN, Alx1 and Ets1. We next identified kirrelL cis -regulatory regions from seven other echinoderm species that together represent all classes within the phylum. By introducing these heterologous regulatory regions into developing sea urchin embryos we provide evidence of their remarkable conservation across ~500 million years of evolution. We dissected in detail the kirrelL regulatory region of the sea star, Patiria miniata , and demonstrated that it also receives direct inputs from Alx1 and Ets1. Our findings identify kirrelL as a component of the ancestral echinoderm skeletogenic GRN. They support the view that GRN subcircuits, including specific transcription factor–CRE interactions, can remain stable over vast periods of evolutionary history. Lastly, our analysis of kirrelL establishes direct linkages between a developmental GRN and an effector gene that controls a key morphogenetic cell behavior, cell–cell fusion, providing a paradigm for extending the explanatory power of GRNs.more » « less
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SUMMARY Gene expression is controlled and regulated by interactions between
cis ‐regulatory DNA elements (CREs) and regulatory proteins. Enhancers are one of the most important classes of CREs in eukaryotes. Eukaryotic genes, especially those related to development or responses to environmental cues, are often regulated by multiple enhancers in different tissues and/or at different developmental stages. Remarkably, little is known about the molecular mechanisms by which enhancers regulate gene expression in plants. We identified a distal enhancer,CREβ , which regulates the expression ofAtDGK7 , which encodes a diacylglycerol kinase in Arabidopsis. We developed a transgenic line containing the luciferase reporter gene (LUC ) driven byCREβ fused with a minimal cauliflower mosaic virus (CaMV) 35S promoter. TheCREβ enhancer was shown to play a role in the response to osmotic pressure of theLUC reporter gene. A forward genetic screen pipeline based on the transgenic line was established to generate mutations associated with altered expression of theLUC reporter gene. We identified a suite of mutants with variableLUC expression levels as well as different segregation patterns of the mutations in populations. We demonstrate that this pipeline will allow us to identifytrans‐ regulatory factors associated withCREβ function as well as those acting in the regulation of the endogenousAtDGK7 gene. -
INTRODUCTION Diverse phenotypes, including large brains relative to body size, group living, and vocal learning ability, have evolved multiple times throughout mammalian history. These shared phenotypes may have arisen repeatedly by means of common mechanisms discernible through genome comparisons. RATIONALE Protein-coding sequence differences have failed to fully explain the evolution of multiple mammalian phenotypes. This suggests that these phenotypes have evolved at least in part through changes in gene expression, meaning that their differences across species may be caused by differences in genome sequence at enhancer regions that control gene expression in specific tissues and cell types. Yet the enhancers involved in phenotype evolution are largely unknown. Sequence conservation–based approaches for identifying such enhancers are limited because enhancer activity can be conserved even when the individual nucleotides within the sequence are poorly conserved. This is due to an overwhelming number of cases where nucleotides turn over at a high rate, but a similar combination of transcription factor binding sites and other sequence features can be maintained across millions of years of evolution, allowing the function of the enhancer to be conserved in a particular cell type or tissue. Experimentally measuring the function of orthologous enhancers across dozens of species is currently infeasible, but new machine learning methods make it possible to make reliable sequence-based predictions of enhancer function across species in specific tissues and cell types. RESULTS To overcome the limits of studying individual nucleotides, we developed the Tissue-Aware Conservation Inference Toolkit (TACIT). Rather than measuring the extent to which individual nucleotides are conserved across a region, TACIT uses machine learning to test whether the function of a given part of the genome is likely to be conserved. More specifically, convolutional neural networks learn the tissue- or cell type–specific regulatory code connecting genome sequence to enhancer activity using candidate enhancers identified from only a few species. This approach allows us to accurately associate differences between species in tissue or cell type–specific enhancer activity with genome sequence differences at enhancer orthologs. We then connect these predictions of enhancer function to phenotypes across hundreds of mammals in a way that accounts for species’ phylogenetic relatedness. We applied TACIT to identify candidate enhancers from motor cortex and parvalbumin neuron open chromatin data that are associated with brain size relative to body size, solitary living, and vocal learning across 222 mammals. Our results include the identification of multiple candidate enhancers associated with brain size relative to body size, several of which are located in linear or three-dimensional proximity to genes whose protein-coding mutations have been implicated in microcephaly or macrocephaly in humans. We also identified candidate enhancers associated with the evolution of solitary living near a gene implicated in separation anxiety and other enhancers associated with the evolution of vocal learning ability. We obtained distinct results for bulk motor cortex and parvalbumin neurons, demonstrating the value in applying TACIT to both bulk tissue and specific minority cell type populations. To facilitate future analyses of our results and applications of TACIT, we released predicted enhancer activity of >400,000 candidate enhancers in each of 222 mammals and their associations with the phenotypes we investigated. CONCLUSION TACIT leverages predicted enhancer activity conservation rather than nucleotide-level conservation to connect genetic sequence differences between species to phenotypes across large numbers of mammals. TACIT can be applied to any phenotype with enhancer activity data available from at least a few species in a relevant tissue or cell type and a whole-genome alignment available across dozens of species with substantial phenotypic variation. Although we developed TACIT for transcriptional enhancers, it could also be applied to genomic regions involved in other components of gene regulation, such as promoters and splicing enhancers and silencers. As the number of sequenced genomes grows, machine learning approaches such as TACIT have the potential to help make sense of how conservation of, or changes in, subtle genome patterns can help explain phenotype evolution. Tissue-Aware Conservation Inference Toolkit (TACIT) associates genetic differences between species with phenotypes. TACIT works by generating open chromatin data from a few species in a tissue related to a phenotype, using the sequences underlying open and closed chromatin regions to train a machine learning model for predicting tissue-specific open chromatin and associating open chromatin predictions across dozens of mammals with the phenotype. [Species silhouettes are from PhyloPic]more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1101/gr.275684.121
