Dense and pleiotropic regulatory information in a developmental enhancer

Fuqua, Timothy; Jordan, Jeff; Breugel, Maria Elize van; Halavatyi, Aliaksandr; Tischer, Christian; Polidoro, Peter; Abe, Namiko; Tsai, Albert; Mann, Richard S.; Stern, David L.; Crocker, Justin

doi:10.1038/s41586-020-2816-5

Cited by 65 publications

(105 citation statements)

References 31 publications

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“…Here, we presented a framework for addressing fundamental questions in the evolution and evolvability of cis-regulatory sequences (6,40). The use of large scale random sequence libraries (42) and sensitive reporter assays (5,6,(75)(76)(77)(78)(79) allowed us to measure the expression driven by a large number of sequences without inherent bias towards naturally occurring sequences (19). Using advanced deep learning approaches (49) and cutting edge computing hardware(80) for training and inference (Methods), we built a model from these empirical measurements that captures the complexity of cis-regulation and generalizes accurately in the sequence space.…”

Section: Discussionmentioning

confidence: 99%

“…Changes in cis-regulatory elements (CREs) play a major role in the evolution of gene expression (1,2). Mutations in CREs can affect their interactions with transcription factors (TFs), change the timing, location and level of gene expression, and impact organismal phenotype and fitness (3)(4)(5)(6). While TFs evolve slowly because they each regulate many target genes, CREs evolve much faster and are thought to drive substantial phenotypic variation (7)(8)(9)(10).…”

Section: Introductionmentioning

confidence: 99%

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A comprehensive fitness landscape model reveals the evolutionary history and future evolvability of eukaryoticcis-regulatory DNA sequences

Vaishnav

Boer

Regev

2021

Preprint

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Mutations in non-coding cis-regulatory DNA sequences can alter gene expression, organismal phenotype, and fitness. Fitness landscapes, which map DNA sequence to organismal fitness, are a long-standing goal in biology, but have remained elusive because it is challenging to generalize accurately to the vast space of possible sequences using models built on measurements from a limited number of endogenous regulatory sequences. Here, we construct a sequence-to-expression model for such a landscape and use it to decipher principles of cis-regulatory evolution. Using tens of millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Sacccharomyces cerevisiae, we construct a deep transformer neural network model that generalizes with exceptional accuracy, and enables sequence design for gene expression engineering. Using our model, we predict and experimentally validate expression divergence under random genetic drift and strong selection weak mutation regimes, show that conflicting expression objectives in different environments constrain expression adaptation, and find that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for detecting selective constraint on gene expression using our model and natural sequence variation, and validate it using observed cis-regulatory diversity across 1,011 yeast strains, cross-species RNA-seq from three different clades, and measured expression-to-fitness curves. Finally, we develop a characterization of regulatory evolvability, use it to visualize fitness landscapes in two dimensions, discover evolvability archetypes, quantify the mutational robustness of individual sequences and highlight the mutational robustness of extant natural regulatory sequence populations. Our work provides a general framework that addresses key questions in the evolution of cis-regulatory sequences.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A comprehensive fitness landscape model reveals the evolutionary history and future evolvability of eukaryoticcis-regulatory DNA sequences

Vaishnav

Boer

Regev

2021

Preprint

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“…Recently, the development of more robust and scalable in vivo enhancer assays, such as the site-directed enhancer-reporter assay (enSERT), has allowed systematic assessment of more than 100 variants in an essential limb enhancer (Kvon et al, 2020). For invertebrates like Drosophila, unbiased, automated enhancer mutational scanning has been established using robotic systems, which permits multi-stage quantitative measurement of enhancer activities in development (Fuqua et al, 2020). Developing similar systems for vertebrates will greatly improve our capacity in assessing vertebrate enhancer functions and advance our understanding of how regulatory information is encoded in developmental enhancers.…”

Section: Emerging Techniques For the Functional Dissection Of Heart Ementioning

confidence: 99%

Heart Enhancers: Development and Disease Control at a Distance

2021

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Bound by lineage-determining transcription factors and signaling effectors, enhancers play essential roles in controlling spatiotemporal gene expression profiles during development, homeostasis and disease. Recent synergistic advances in functional genomic technologies, combined with the developmental biology toolbox, have resulted in unprecedented genome-wide annotation of heart enhancers and their target genes. Starting with early studies of vertebrate heart enhancers and ending with state-of-the-art genome-wide enhancer discovery and testing, we will review how studying heart enhancers in metazoan species has helped inform our understanding of cardiac development and disease.

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“…To address this, we developed Flyspresso, a customizable syringe-based microplate washer to carry out Drosophila embryo experiments at a higher throughput, and an adaptive feedback confocal microscope pipeline that allows the automated acquisition of samples 10 . Our pipeline automates several critical steps: (1) embryo fixation, (2) vitelline membrane removal, (3) antibody or chemical staining of embryos, and (4) the automated imaging of embryos.…”

Section: Introductionmentioning

confidence: 99%

An open-source semi-automated robotics pipeline for embryo immunohistochemistry

Fuqua

Jordan

Halavatyi

et al. 2021

Sci Rep

Self Cite

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A significant challenge for developmental systems biology is balancing throughput with controlled conditions that minimize experimental artifacts. Large-scale developmental screens such as unbiased mutagenesis surveys have been limited in their applicability to embryonic systems, as the technologies for quantifying precise expression patterns in whole animals has not kept pace with other sequencing-based technologies. Here, we outline an open-source semi-automated pipeline to chemically fixate, stain, and 3D-image Drosophila embryos. Central to this pipeline is a liquid handling robot, Flyspresso, which automates the steps of classical embryo fixation and staining. We provide the schematics and an overview of the technology for an engineer or someone equivalently trained to reproduce and further improve upon Flyspresso, and highlight the Drosophila embryo fixation and colorimetric or antibody staining protocols. Additionally, we provide a detailed overview and stepwise protocol for our adaptive-feedback pipeline for automated embryo imaging on confocal microscopes. We demonstrate the efficiency of this pipeline compared to classical techniques, and how it can be repurposed or scaled to other protocols and biological systems. We hope our pipeline will serve as a platform for future research, allowing a broader community of users to build, execute, and share similar experiments.

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Dense and pleiotropic regulatory information in a developmental enhancer

Cited by 65 publications

References 31 publications

A comprehensive fitness landscape model reveals the evolutionary history and future evolvability of eukaryoticcis-regulatory DNA sequences

A comprehensive fitness landscape model reveals the evolutionary history and future evolvability of eukaryoticcis-regulatory DNA sequences

Heart Enhancers: Development and Disease Control at a Distance

An open-source semi-automated robotics pipeline for embryo immunohistochemistry

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