Table 1.
Pros and cons of various strategies for identifying, validating and/or characterizing enhancers
| Type | Technologies | Single cell? | Pro | Con |
|---|---|---|---|---|
| Conservation | PhyloP 224; PhastCons 225 | Not applicable | Computable genome-wide; support for critical function | Not cell-type specific; not a measurement of enhancer activity; no target gene identified |
| Sequence motif | Databases: JASPAR 226; HOCOMOCO 227 | Not applicable | Computable genome-wide; informative as to potentially bound proteins | Limited cell-type specificity; not a measurement of enhancer activity; no target gene identified |
| Open chromatin | DNase-seq 43, MNase-seq 228, ATAC-seq 229 | Yes (e.g. sci-ATAC-seq 82) | High-throughput biochemical annotation; associated with enhancer activity; cell-type specific | Not a measurement of enhancer activity; no target gene identified; unknown specificity |
| Transcription | RNA-seq, PRO-seq 230, GRO-cap 59, CoPro 231 | Yes (e.g. scRNA-seq, although usually only mRNAs) | High-throughput biochemical ‘eRNA’ annotation; implies active RNA polymerase near enhancer | Transcription does not necessarily guarantee enhancer activity; no target gene identified |
| Histone marks | Enhancer-associated histone modifications on ChIP-seq | Emerging (e.g. scChIC-seq 232) | High-throughput biochemical annotation; can support poised, active, or silenced enhancers; cell-type specific | Not a measurement of enhancer activity; no target gene identified; unknown specificity |
| Protein Binding | Transcription Factor ChIP-seq, CUT&RUN 233 | Emerging (e.g. uliCut&Run 170) | High-throughput biochemical annotation; cell-type specific | Not a measurement of enhancer activity; no target gene identified; unknown specificity |
| eQTL | Many datasets available (e.g. GTEx Consortium 136) | Emerging (e.g. sc-eQTLGen Consortium 138) | In-genome; direct measurement from human tissues; can test all variants by all transcripts | Limited to common genetic variants; variants fall in linkage disequilibrium blocks |
| 3D proximity | Chromatin conformation ‘C’s (e.g. Hi-C 141, microscopy | Yes (e.g. microscopy, sci-Hi-C 163) | High-throughput biochemical annotation; cell-type specific; informs enhancer–gene links | Not a measurement of enhancer activity; unknown specificity |
| 3D proximity + live imaging | Microscopy 172 | Yes, microscopy is inherently single-cell | Live cells, dynamic imaging of 3D proximity and transcriptional bursting across time | Limited to a small number of loci at once |
| 3D proximity + biochemical annotation | ChIA-PET 147; HiChIP 148, DNase-HiC 150, PLAC-seq 149 | None yet | High-throughput biochemical annotation; cell-type specific; informs enhancer–gene links; more cost-effective than Hi-C | Not a measurement of enhancer activity; unknown specificity |
| Computational prediction | Example: ChromHMM 234; Segway 235 | Yes (e.g. Cicero 134) | Computable genome-wide; potentially cell-type specific, can nominate enhancer–gene links | Requires experimental functional validation |
| Reporter plasmid activity | Luciferase, MPRAs 67,173,184, lentiMPRAs 190 | None yet | High throughput; relatively straightforward to implement; provides functional support | Episomal; removed from genomic context; no target gene identified; unknown specificity |
| Single-gene CRISPR screens | ‘Indel’ scans 195, long-deletion scans 203,204, CRISPRi scans 105,208 | None yet | High throughput; in native genomic context; provides functional support; informs enhancer–gene links | Only tests candidate enhancers against one gene at a time; unknown sensitivity |
| Whole-transcriptome CRISPR screens | Mosaic-seq216; multiplexed scRNA-seq 72 | Yes | High throughput; in native genomic context; provides functional support; informs enhancer–gene links; many genes at a time | Currently only implemented using epigenetic perturbation; unknown sensitivity |
| In vivo model organism: transgenic reporter | Episomal or transgenic delivery 219,221 | None yet | In vivo test across many developmental contexts | Low throughput; does not test enhancer in native genomic context |
| In vivo model organism: sequence deletion | Direct genomic sequence deletion 115 | None yet | In vivo test across many developmental contexts; potential detection of organismal phenotypes | Low throughput; not all enhancers are conserved between mouse and humans |
ATAC-seq, assay for transposase-accessible chromatin using sequencing; ChIA-PET, chromatin interaction analysis with paired-end tag sequencing; scChIC-seq, single-cell chromatin immunocleavage sequencing; ChIP-seq; chromatin immunoprecipitation followed by sequencing; CoPro, coordinated precision run-on and sequencing; ChromHMM, a chromatin state annotator based on hidden Markov models; CRISPRi, CRISPR-based transcriptional interference; CUT&RUN, cleavage under targets and release using nuclease; DNase-seq, DNaseI hypersensitivity sequencing; eQTL, expression quantitative trait locus; eQTLGen, eQTL Genetics Consortium; eRNA, enhancer RNA; GTEx, Genotype–Tissue Expression Program; GRO-cap, cap-enriched global nuclear run-on sequencing; HOCOMOCO, Homo sapiens Comprehensive Model Collection; indel, insertion or deletion; lentiMPRAs, lentiviral MPRAs; MNase-seq, micrococcal nuclease digestion combined with sequencing; MPRAs, massively parallel reporter assays; PLAC-seq, proximity ligation-assisted ChIP-seq; PRO-seq, precision run-on sequencing; RNA-seq, RNA sequencing; sc, single-cell; sci, single-cell combinatorial indexing; uli, ultra-low input.