Breaking enhancers to gain insights into developmental defects

  1. Daniel A Armendariz
  2. Anjana Sundarrajan
  3. Gary C Hon  Is a corresponding author
  1. Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, United States
  2. Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, United States
  3. Lyda Hill Department of Bioinformatics, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, United States
2 figures and 1 table


Pathway of how enhancer variants cause developmental defects.

The functional characterization of enhancer variants is a multi-step process linking genotypes to molecular phenotypes (target genes and networks), cellular phenotypes (cell state, morphology), and organismal phenotypes (developmental defect) (top row). A genetic variant of a Sonic Hedgehog enhancer driving polydactyly is one well-characterized example (bottom row). However, the role of most cis-regulatory elements in developmental disease remains unclear.

Features of enhancer perturbation studies.

Studies of enhancer variants in developmental disease have been carried out using diverse genomic perturbation methods, biosystems, and readouts. Each of these three layers can be organized into increasing levels of complexity with increasing biomedical relevance. We envision that future technologies (black dashed line) will enable analyses of higher complexity.


Table 1
Summary of genomic approaches to characterize enhancers and variants.
ApproachApplicationProsConsExample studies
VISTAMeasures in vivo enhancer reporter activity in transgenic vivo and spatial readouts of enhancer activitysingle time point (E11.5), low throughputPennacchio et al., 2006; Visel et al., 2007
Massively parallel reporter assays (MPRA), Self-transcribing active regulatory region (STARR)-SeqMeasures the activity of enhancer sequences and variants with high throughput reporter assays. Single-cell MPRA gives readouts on cell-specific enhancer activity.very high throughput, variant-level activitylacks endogenous genomic context, readouts can depend on the design of reporter constructsInoue et al., 2019; Kircher et al., 2019; Arnold et al., 2013; Zhao et al., 2023; Lalanne et al., 2022
CRISPR screenMeasures endogenous activity of enhancer by perturbating sequences with CRISPR/Cas9, using sgRNA dropout as a phenotypic readout.high throughput, endogenous genomic contextrequires a selectable phenotype, the readout is only sgRNA abundanceSanjana et al., 2016; Korkmaz et al., 2016
CRISPRi FlowFISH, HCR FlowFISHMeasures endogenous enhancer activity on the expression of candidate genes with high sensitivity.medium throughput, endogenous genomic context, sensitive transcriptional readoutonly a small number of genes can be measured in each experimentFulco et al., 2016; Reilly et al., 2021
Single-cell CRISPRi screenMeasures endogenous enhancer activity on transcriptome-wide phenotypes.high throughput, endogenous genomic context, transcriptome-wide readoutlow sensitivity for lowly expressed genes or enhancers with modest effects; expensiveGenga et al., 2019; Armendariz et al., 2022
Base editing screenMeasures endogenous activity of enhancer variants after high throughput base editing.variant-level perturbations more relevant to disease modeling, endogenous genomic contextsome base substitutions incompatible with current base editors, limited editing window restricts sgRNA design; modest effect sizesMartin-Rufino et al., 2023; Chen et al., 2022
merFISH, seqFISH, osmFISHMeasures spatial RNA expression with high sensitivity.spatial context, sensitive readout of many transcriptsexisting screens are low throughput, expensive, specialized equipmentXie et al., 2017; Eng et al., 2019; Codeluppi et al., 2018
Imaging screen (Cell Painting, optical)Measures morphological phenotypes after perturbation.spatial readout, morphological phenotypes of multiple cellular componentsenhancer perturbations may not cause morphological phenotypes; lacks gene expression readout; limited cell type compatibilityBray et al., 2016

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  1. Daniel A Armendariz
  2. Anjana Sundarrajan
  3. Gary C Hon
Breaking enhancers to gain insights into developmental defects
eLife 12:e88187.