Characterization of noncoding regulatory DNA in the human genome

Journal name:
Nature Biotechnology
Volume:
35,
Pages:
732–746
Year published:
DOI:
doi:10.1038/nbt.3863
Received
Accepted
Published online

Abstract

Genetic variants associated with common diseases are usually located in noncoding parts of the human genome. Delineation of the full repertoire of functional noncoding elements, together with efficient methods for probing their biological roles, is therefore of crucial importance. Over the past decade, DNA accessibility and various epigenetic modifications have been associated with regulatory functions. Mapping these features across the genome has enabled researchers to begin to document the full complement of putative regulatory elements. High-throughput reporter assays to probe the functions of regulatory regions have also been developed but these methods separate putative regulatory elements from the chromosome so that any effects of chromatin context and long-range regulatory interactions are lost. Definitive assignment of function(s) to putative cis-regulatory elements requires perturbation of these elements. Genome-editing technologies are now transforming our ability to perturb regulatory elements across entire genomes. Interpretation of high-throughput genetic screens that incorporate genome editors might enable the construction of an unbiased map of functional noncoding elements in the human genome.

At a glance

Figures

  1. Genome-wide identification of candidate regulatory regions.
    Figure 1: Genome-wide identification of candidate regulatory regions.

    (a) The conditions in which each gene is expressed are determined by a complex interplay between cis-regulatory DNA elements embedded near the gene's transcription start site (TSS) (the gene's promoter region, typically taken as 1,000 bp upstream to 200 bp downstream of the TSS) and distal enhancer elements located far (along the linear genomic DNA) from the gene's TSS. These DNA elements are bound by TFs that modulated the efficiency by which RNA polymerase is recruited to the gene's TSS to initiate transcription. Image adapted with permission from Figure 1, ref. 21, Springer Nature. (b) Distinct chromatin marks correlate with different regulatory states. Thus, epigenomic profiling of chromatin accessibility, histone modifications and TF binding in large panels of cell lines and tissues predicts comprehensive maps of putative regulatory elements across the genome and indicates the conditions under which each element is active. Reprinted from Figure 2, ref. 157, Mol. Cell., 55, Plank, J.L. & Dean, A., Enhancer function: mechanistic and genome-wide insights come together. 514 (2014), with permission from Elsevier. (c) Bidirectional production of eRNAs emerges as an effective mark of active enhancers. Thus, expression profiling of eRNAs is used on top of the epigenomic layers to improve the identification of enhancers and delineate the conditions in which they are activated. This cartoon shows tracks for epigenetic hallmarks of enhancers (DHS, histone marks and TF binding sites (TF BS) in addition to bidirectional production of eRNAs (as detected by GRO-seq)).

  2. High-throughput measurements of enhancer activity using exogenous assays.
    Figure 2: High-throughput measurements of enhancer activity using exogenous assays.

    (a) MPRA, MPFD and CRE-seq assays use plasmid constructs in which the tested DNA segments are inserted upstream of a minimal promoter and a reporter gene while a barcode is inserted into the 3′ UTR of the gene. On the other hand, STARR-seq exploits the fact that enhancers function independently of their position relative to their target promoter, and inserts the tested enhancers themselves in the 3′ UTR of the reporter gene, so the enhancer sequences are included in the RNA transcripts, and thus obviate the need for barcoding the library vectors. (b) Cells are transfected by the enhancer library, and the region that corresponds to the barcode sequences (in MPREA, MFDA and CRE-seq) or the enhancer sequences (in STARR-seq) on the transcribed RNAs is extracted and deep-sequenced. For normalization, these regions are also sequenced from the plasmid DNA, to control for differences in transfection efficiencies. Normalized counts provide estimates of the relative activity of tested enhancers in the assayed cells/conditions.

  3. Elucidation of functional variants in regulatory elements.
    Figure 3: Elucidation of functional variants in regulatory elements.

    (a) Neighbor SNP alleles in the human genome are frequently inherited together (that is, they form a haplotype). GWAS usually genotype only a single or very few SNPs from each haplotype (genotypes of other SNPs in the haplotype can be computationally imputed with accuracy that is increased with the strength of linkage disequilibrium between the genotyped and imputed variants). Linkage disequilibrium between pairs of SNPs is typically measured on a 0–1 scale and presented in linkage disequilibrium (LD) plots. Thus, variants that were associated by GWAS with increased disease susceptibility (here, SNP1) are only tag SNPs. Any SNP with strong linkage disequilibrium with a tag SNP is similarly likely to be a causal variant (SNP 6, which is in perfect linkage disequilibrium with the tag SNP, is the causal variant and it acts by disrupting a regulatory element). Image adapted with permission from Figure 1, ref. 66, Cold Spring Harbor Laboratory Press. (b) Epigenetic QTL analyses examine associations between the SNP genotype and the signal of the epigenetic mark in the region in which the variant is located. Such association suggests a functional effect for the examined variant (or for a variant that is in strong linkage disequilibrium with it) on local chromatin state. Adapted from graphical abstract, ref. 76, Cell, 162, Grubert, F. et al., Genetic control of chromatin states in humans involves local and distal chromosomal interactions. 10511065 (2015), with permission from Elsevier. (c) Left: many GWAS SNPs are bQTLs, indicating that modulation of TF binding affinity is a central mode of action of genetic variation that affect human traits. The C allele of a SNP associated with human disease disrupts a TF binding motif and hence results in lower binding of the TF to this regulatory element. Right: allelic-imbalanced binding observed in individuals who are heterozygous for the SNP provide additional support for a functional effect for the examined SNP. The analyzed TF binds with much higher affinity to the site with the G allele than the one with the C allele, and thus, in ChIP-seq performed in individuals who are heterozygous for this SNP, many more reads originate from the binding site that carry the G allele. Image adapted with permission from Figure 1, ref. 158, Cold Spring Harbor Laboratory Press.

  4. Inference of enhancer-promoter links.
    Figure 4: Inference of enhancer-promoter links.

    (a) Enhancer-promoter (E-P) interactions are predicted based on their correlated activation pattern measured over a large panel of cells and tissues. Activation pattern could be measured by epigenetic marks, DHS or transcriptional activity (e.g., mRNA and eRNA levels). (b) Top: eQTL analysis detects associations between SNP genotypes and expression level of target genes. In this example, individuals who are homozygous for the reference allele (GG) show significantly lower expression of the target gene than individuals who are homozygous for the alternative allele (AA). Heterozygous individuals show an intermediate expression level. If either the eQTL SNP itself or any other SNP that is in strong linkage disequilibrium with it is located within a regulatory element, then a putative functional link between that enhancer and the promoter of the associated gene is predicted. Bottom: allele-specific expression analysis requires the presence of a heterozygous SNP within the target RNA (in the figure, the SNP with the T/C alleles), and tests for imbalanced expression from the two copies (maternal and paternal copies) of the gene. Imbalanced expression of the two copies implies that the individual is also heterozygous for another SNP that modulates the activity of a cis-regulatory element that controls the expression of the target gene. The A allele of the SNP located within the enhancer increases the enhancer activity and thus causes elevated expression of the copy of the gene encoded on the same chromosome (the copy of the gene that carries the C allele).

  5. Mapping physical interactions between putative enhancers and promoters.
    Figure 5: Mapping physical interactions between putative enhancers and promoters.

    (a) ChIA-PET combines TF ChIP with chromosome conformation capture that is based on nuclear proximity ligation. This procedure enables the detection of genomic segments that, although they might be located far away from each other on the linear DNA sequence, are brought into close spatial proximity by long-range chromatin looping. Such long-range chromatin interactions are inferred from inter-ligation PET products. Image adapted from Figure 1, ref. 159, under a Creative Commons license (http://creativecommons.org/licenses/by/2.0). (b) ChIA-PET detects, with very high resolution (<500 bp), physical interactions between different genomic loci that involve the immunoprecipitated protein factor. (c) Hi-C experiments detected the organization of the genome into TADs and demonstrated that E-E and E-P interactions are largely restricted by TAD boundaries.

  6. Functional screens for DNA regulatory elements using genome-editing tools.
    Figure 6: Functional screens for DNA regulatory elements using genome-editing tools.

    Genome-editing screens that were so far applied to study the noncoding genome were either gene-centric or TF-centric. Gene-centric screens apply saturation mutagenesis analysis that systematically tiles and targets the genome in the surrounding of selected target genes. TF-centric screens use sgRNA libraries that systematically target TF binding sites within putative enhancer regions. The readout of these screens is based on either sorting the pooled cell population using GFP or endogenous gene expression or on acquisition of proliferation advantage/disadvantage by specific sgRNA clones. DNA segments that include the incorporated sgRNAs are amplified and deep-sequenced. The prevalence of each sgRNA is calculated in the two pools and enrichment scores are calculated (after normalization of counts). Functional elements are detected by identification of sgRNA with significant enrichment (or depletion) scores. From Figure 1, ref. 130, Sanjana, N.E. et al. High-resolution interrogation of functional elements in the nongenome. Science 353, 15451549 (2016). Adapted with permission from AAAS.

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Affiliations

  1. Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv, Israel.

    • Ran Elkon
  2. Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.

    • Ran Elkon
  3. Division of Oncogenomics, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

    • Reuven Agami
  4. Erasmus MC, Rotterdam University, The Netherlands.

    • Reuven Agami

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