Towards a comprehensive catalogue of validated and target-linked human enhancers

In the paper

“The classic model is that enhancers recruit cell- and condition-specific TFs and then loop in 3D space to interact with their target promoter90.”

What the sources say

• Partly supported

  The Results (Chromatin state and dynamic interactions; Allelic imbalances in gene expression, page not available) describe cell-type-specific enhancer looping and interactions between enhancers and target promoters. The Discussion (page not available) mentions transcription-factor binding sites at cell-type-specific interaction regions, but our copy does not say that enhancers recruit cell- and condition-specific transcription factors as a step preceding those loops. (LLM, conf=0.85)

  cites [90] Dixon, J. R. et al. Chromatin architecture reorganization during stem cell differentiation. Nature 518, 331–336 (2015). This study shows compelling use of Hi-C contact maps to study the dynamics of enhancer–promoter interactions through cellular differentiation. sourceExperimental — accuracy not yet measured

In the paper

“Other studies have found enhancer mobility, rather than proximity per se, to be a key determinant of activation154.”

What the sources say

• Partly supported

  The paper reports greater Fgf5 enhancer mobility in actively transcribing cells and links mobility to transcriptional activity (Abstract; page unavailable). But it does not establish mobility, rather than proximity, as a key determinant of activation. Its proposed mechanism is tentative: mobility may increase enhancer–promoter encounters and reinforce expression after transcription begins. (LLM, conf=0.88)

  cites [154] Gu, B. et al. Transcription-coupled changes in nuclear mobility of mammalian cis-regulatory elements. Science 359, 1050–1055 (2018). sourceExperimental — accuracy not yet measured

In the paper

“Although most causal genetic variants for Mendelian disorders fall in protein-coding regions, the heritable component of common disease risk distributes largely to non-coding regions, and appears to be particularly enriched in enhancers that are specific to disease-relevant cell types.”

What the sources say

• Partly supported

  The Abstract reports that about 93% of disease- and trait-associated GWAS variants lie in noncoding sequence. The Discussion and ‘De novo identification of pathogenic cell types’ section report enrichment in regulatory DNA active in disease-relevant cell types. The paper measures enrichment in DNase I hypersensitive sites, however, not specifically in enhancers, and does not quantify the heritable component of risk. (LLM, conf=0.85)

  cites [65] Maurano, M. T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190–1195 (2012). sourceExperimental — accuracy not yet measured

In the paper

“Evolutionary conservation can support the functional candidacy of a region39, but not all enhancers are conserved123-125126.”

What the sources say

• Supported

  Citation 39 is attached to the first clause, about conservation supporting a region’s functional candidacy. The Abstract reports that extreme evolutionary conservation was used to identify putative regulatory elements and was a powerful predictor of mammalian tissue-specific enhancers. The separate claim that not all enhancers are conserved is attributed to citations 123–126, not this paper. (LLM, conf=0.94)

  cites [39] Pennacchio, L. A. et al. In vivo enhancer analysis of human conserved non-coding sequences. Nature 444, 499–502 (2006). source
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites 123-125126

In the paper

“Although the endogenous distributions of enhancer sizes and enhancer–gene distances remain an important topic of exploration, a typical enhancer is probably hundreds of base-pairs in length70,71, and acts over a few to tens of kilobases72.”

What the sources say

• ?Not checked — no full text of the sourcecites [70] Blackwood, E. M. & Kadonaga, J. T. Going the distance: a current view of enhancer action. Science 281, 60–63 (1998). source
• Partly supported

  The Introduction says enhancers can range from about 10 to 1,000 base pairs, so a length of hundreds of base pairs is consistent with the source. It does not establish that hundreds of base pairs is typical. The distance claim is attached to a different citation in the citing sentence and is not judged here. (LLM, conf=0.78)

  cites [71] Li, L. & Wunderlich, Z. An enhancer’s length and composition are shaped by its regulatory task. Front. Genet. 8, 63 (2017). sourceExperimental — accuracy not yet measured
• Partly supported

  Citation 72 attaches to the distance claim, not the enhancer-length claim. The Results section, “Distance between Paired Enhancers and Promoters,” reports a median enhancer-to-target-TSS distance of 24.1 kb, supporting a distance of tens of kilobases. But that estimate is limited to high-confidence upstream pairs among the nonintronic enhancers surveyed, so it does not establish the distance for a typical enhancer generally. (LLM, conf=0.84)

  cites [72] Gasperini, M. et al. A genome-wide framework for mapping gene regulation via cellular genetic screens. Cell 176, 377–390 (2019). sourceExperimental — accuracy not yet measured

In the paper

“Some enhancers reside in clusters of a handful116 to even hundreds (‘super enhancers’76,117), whereas many are solo.”

What the sources say

• ?Not checked — no full text of the sourcecites [116] Levings, P. P. & Bungert, J. The human β-globin locus control region. Eur. J. Biochem. 269, 1589–1599 (2002). source
• Partly supported

  The Results section describes super-enhancers as clusters of constituent enhancers and says the vast majority of enhancers in the studied embryonic stem cells are typical enhancers. The passages do not establish that a super-enhancer contains hundreds of enhancers or that the typical enhancers are necessarily solo; no page numbers are available in our copy. (LLM, conf=0.82)

  cites [76] Whyte, W. A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 153, 307–319 (2013). sourceExperimental — accuracy not yet measured
• Supported

  The citation is attached to the term “super enhancers.” The Introduction describes super-enhancers as clusters of enhancers, and the Results likewise defines them as enhancer clusters. The source therefore supports the identification for which it is cited; the separate citations and uncited wording about cluster sizes and solo enhancers are not attributed specifically to this paper. (LLM, conf=0.90)

  cites [117] Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013). source

In the paper

“Although unquestionably useful, it remains unknown what proportion of candidate enhancers identified solely by biochemical marks are technical false positives130-132 or a product of having enhancer-like biochemical features but no meaningful impact on the expression of cis encoded genes133.”

What the sources say

• ?Not checked — no full text of the sourcecites [130] Teytelman, L., Thurtle, D. M., Rine, J. & van Oudenaarden, A. Highly expressed loci are vulnerable to misleading ChIP localization of multiple unrelated proteins. Proc. Natl Acad. Sci. USA 110, 18602–18607 (2013). source
• Partly supported

  The Background (page unavailable) says ChIP-seq peaks can be shaped by technical influences, including non-specific antibody pull-down, and leaves open whether some peaks arise from other causes. That supports the possibility of technical false positives, but the paper examines transcription-factor ChIP-seq peaks, not the proportion of biochemically identified candidate enhancers that are false positives. The separate claim about enhancer-like features having no meaningful effect on cis-gene expression is attached to citation 133, not this source. (LLM, conf=0.83)

  cites [131] Worsley Hunt, R. & Wasserman, W. W. Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets. Genome Biol. 15, 412 (2014). sourceExperimental — accuracy not yet measured
• Partly supported

  The Discussion reports that some ChIP-seq enrichments may be false-positive Phantom Peaks and says it cannot determine which overlapping signals represent genuine binding. The cited paper does not assess candidate enhancers identified solely by biochemical marks or estimate what proportion of them are technical false positives. The separate claim about enhancer-like features without an effect on cis-gene expression is attached to citation 133, not this source. (LLM, conf=0.84)

  cites [132] Jain, D., Baldi, S., Zabel, A., Straub, T. & Becker, P. B. Active promoters give rise to false positive ‘phantom peaks’ in ChIP-seq experiments. Nucleic Acids Res. 43, 6959–6968 (2015). sourceExperimental — accuracy not yet measured
• Supported

  The Abstract (page unavailable) says biochemical signatures were used to annotate millions of candidate regulatory elements, but that their contributions to target-gene expression still need functional characterization. The Results (page unavailable) likewise say it was unclear which of 174 candidates with regulatory chromatin features were involved in POU5F1 expression. This supports the uncertainty attributed to this source; the separate technical-false-positive clause is cited to other sources. (LLM, conf=0.87)

  cites [133] Diao, Y. et al. A new class of temporarily phenotypic enhancers identified by CRISPR/Cas9-mediated genetic screening. Genome Res. 26, 397–405 (2016). source

In the paper

“Many enhancers are spatially proximate to their target promoter in 3D109,110, but exceptions have been described111-114.”

What the sources say

• Supported

  The Results section reports frequent loops connecting known enhancers with known promoters, including 2,854 such peaks in the GM12878 map. The Discussion describes promoter–enhancer loops as common. These passages support the spatial-proximity claim; the separately cited exceptions are not attributed to this source. (LLM, conf=0.91)

  cites [109] Rao, S. S. P. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014). source
• Supported

  The citation is attached to the first clause, not the statement about exceptions. The Introduction says enhancers regulate promoters of nearby or distant genes through physical contacts involving DNA loops, supporting spatial proximity in 3D. (LLM, conf=0.90)

  cites [110] Weintraub, A. S. et al. YY1 Is a structural regulator of enhancer-promoter loops. Cell 171, 1573–1588.e28 (2017). source
• Supported

  In “Nuclear colocalisation of the GCR and 5′ HoxD in distal posterior cells” (page unavailable), the paper reports substantially greater spatial colocalisation of the GCR regulatory region with Hoxd13 in the distal posterior limb bud. The same section reports no significantly increased colocalisation for another potential regulatory region, island III, at the stage examined. These findings support the cited sentence’s general point through examples, rather than establishing how common proximity or exceptions are. (LLM, conf=0.87)

  cites [111] Williamson, I. et al. Anterior–posterior differences in HoxD chromatin topology in limb development. Development 139, 3157–3167 (2012). source
• ?Not checked — no full text of the sourcecites [112] Ghavi-Helm, Y. et al. Enhancer loops appear stable during development and are associated with paused polymerase. Nature 512, 96–100 (2014). source
• Supported

  The citation is attached to the statement that exceptions to enhancer–promoter proximity have been described. The Abstract reports decreased spatial proximity between Shh and its enhancers during activation, and the Introduction notes that enhancer–promoter looping is not universal. The supplied passages do not specify page numbers. (LLM, conf=0.94)

  cites [113] Benabdallah, N. S. et al. Decreased enhancer-promoter proximity accompanying enhancer activation. Mol. Cell 76, 473–484 (2019). source
• Supported

  The Results section (page unavailable) reports Sox2 transcriptional bursts without colocalization of its promoter and the SCR enhancer. The Discussion likewise reports no association between their measured proximity and transcription, while cautioning that brief contacts cannot be ruled out. This supports the cited exception to enhancer–promoter proximity. (LLM, conf=0.92)

  cites [114] Alexander, J. M. et al. Live-cell imaging reveals enhancer-dependent Sox2 transcription in the absence of enhancer proximity. eLife 8, e41769 (2019). source

In the paper

“The eQTL framework is very powerful, and for variants residing within distally located candidate enhancers, can provide in vivo validation of those enhancers while also linking them to their target genes136.”

What the sources say

• Partly supported

  In “Functional characterization of cis-eQTLs” (page unavailable), the paper reports that eVariants are enriched in predicted enhancers and that more distant secondary eVariants show increased enhancer enrichment and contact with target-gene promoters. This supports using eQTLs to connect candidate enhancer regions with genes, but the passage does not establish in vivo validation of individual candidate enhancers. (LLM, conf=0.82)

  cites [136] GTEx Consortium et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017). sourceExperimental — accuracy not yet measured

In the paper

“On the other hand, the framework has clear limitations, including its reliance on naturally occurring human genetic variation (most enhancers do not harbour common variants that substantially perturb their activity), linkage disequilibrium [G] (multiple variants in a haplotype block may equivalently explain an association), and restriction to cell types and tissues that can be practically obtained”

What the sources say

• Partly supported

  In the paper’s main text (indexed under Abstract; page unavailable), two variants in strong linkage disequilibrium are reported as both associated with SCN5A expression. This illustrates the linkage underlying the cited limitation, but the paper does not say that the variants equivalently explain the association or explicitly identify linkage disequilibrium as a limitation of eQTL analysis. (LLM, conf=0.78)

  cites [137] Strober, B. J. et al. Dynamic genetic regulation of gene expression during cellular differentiation. Science 364, 1287–1290 (2019). sourceExperimental — accuracy not yet measured
• Partly supported

  The main text (page unavailable) reports near-perfect linkage disequilibrium between an eQTL SNP and a diabetes-associated SNP, supporting the cited point that linkage disequilibrium is relevant to interpreting associations. It does not state that multiple variants in a haplotype block may equivalently explain an association. The Online Methods describe analysis of common variants in donor blood cells, but do not establish the claim about most enhancers or a general restriction to practically obtainable tissues. (LLM, conf=0.76)

  cites [138] van der Wijst, M. G. P. et al. Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs. Nat. Genet. 50, 493–497 (2018). sourceExperimental — accuracy not yet measured

In the paper

“It is now widely recognized that a major component of the heritability of nearly all common diseases partitions to these regions, and in particular to regions that have enhancer-like signatures in disease-relevant cell types65.”

What the sources say

• Partly supported

  The section “Disease- and trait-associated variants are concentrated in regulatory DNA” (page unavailable) reports enrichment of GWAS-associated variants in DNase I hypersensitive sites across many diseases and traits. “De novo identification of pathogenic cell types” reports enrichment in particular cell types for Crohn’s disease, multiple sclerosis, and a cardiac trait. The paper does not quantify the share of heritability partitioning to these regions, establish this for nearly all common diseases, or show that the enriched regions specifically have enhancer-like signatures. (LLM, conf=0.87)

  cites [65] Maurano, M. T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190–1195 (2012). sourceExperimental — accuracy not yet measured

In the paper

“Enhancers may have complex relationships with promoters, including feedback loops or competition with neighbouring genes121,122.”

What the sources say

• Partly supported

  The Results section reports that PVT1 enhancers preferentially contact the PVT1 promoter, but shift toward the neighbouring MYC promoter when PVT1 is silenced; the Discussion describes this as promoter competition. Our copy does not describe feedback loops between enhancers and promoters, so it supports only the competition part of the claim. No page number is available in our copy. (LLM, conf=0.84)

  cites [121] Cho, S. W. et al. Promoter of lncRNA Gene PVT1 Is a tumor-suppressor DNA boundary element. Cell 173, 1398–1412.e22 (2018). sourceExperimental — accuracy not yet measured
• Partly supported

  The Discussion (page unavailable) proposes an intrinsic negative feedback mechanism between an intragenic enhancer and its host-gene promoter. It also reports that the enhancer can activate distant genes while attenuating its host gene, but it does not describe competition with neighbouring genes. (LLM, conf=0.84)

  cites [122] Cinghu, S. et al. Intragenic enhancers attenuate host gene expression. Mol. Cell 68, 104–117.e6 (2017). sourceExperimental — accuracy not yet measured

In the paper

“Finally, there are multiple models for how enhancers interact with their target promoter(s), including tracking, linking/chaining, short- or long-range looping, transcription factory and hub/condensate models (reviewed in 102), more than one of which may be correct.”

What the sources say

• Supported

  The “Models of enhancer-promoter communication” section lists tracking, linking, looping, and transcription factories. “Transcription hubs” describes a hub-and-condensate model that incorporates features of the classical models, supporting the point that these mechanisms need not be mutually exclusive. The supplied passages do not give page numbers. (LLM, conf=0.91)

  cites [102] Furlong, E. E. M. & Levine, M. Developmental enhancers and chromosome topology. Science 361, 1341–1345 (2018). source

In the paper

“However, it should be emphasized that this is not an inexorable chain of events. For example, stimulus-responsive enhancers may exhibit open chromatin and 3D interactions with their promoters before activation92,93.”

What the sources say

• Partly supported

  The paper reports that stimulation-responsive enhancers can be identified in unstimulated cells and that IL2RA enhancer sites overlap accessible chromatin and elements that loop to the promoter (Abstract, p. unavailable; Extended Data Figure 5, p. unavailable). It does not establish that chromatin accessibility and promoter interactions were both present before activation in the same cells; that timing is the unsupported part. (LLM, conf=0.78)

  cites [92] Simeonov, D. R. et al. Discovery of stimulation-responsive immune enhancers with CRISPR activation. Nature 549, 111–115 (2017). sourceExperimental — accuracy not yet measured
• Partly supported

  The section “Pre-programmed chromatin architecture is conserved across metazoans” (page unavailable) reports that contacts between heat-shock-regulated genes and distal HSF1-bound elements were preformed before heat shock, supporting the pre-activation 3D-interaction claim. Our copy does not establish that those enhancers had open chromatin before activation; the Introduction discusses changes in chromatin accessibility upon heat shock instead. (LLM, conf=0.87)

  cites [93] Ray, J. et al. Chromatin conformation remains stable upon extensive transcriptional changes driven by heat shock. Proc. Natl Acad. Sci. USA 116, 19431–19439 (2019). sourceExperimental — accuracy not yet measured

In the paper

“Enhancers are ‘punctate’ relative to broader chromatin domains (e.g. chromosomes, topologically associating domains [G] (TADs) and sub-compartments of TADs87), but their in vivo functionality is dependent on both the chromatin context in which they reside88 and on the trans milieu (e.g. cell-type-specific TFs)89.”

What the sources say

• Supported

  Citation 87 is attached to the mention of TAD sub-compartments, not the later claims about chromatin context or the trans milieu. In “Insulated neighborhoods are the mechanistic basis of TADs” (page unavailable), the paper says some TADs contain multiple insulated neighborhoods and many comprise smaller TAD-like domains. (LLM, conf=0.91)

  cites [87] Hnisz, D., Day, D. S. & Young, R. A. Insulated neighborhoods: structural and functional units of mammalian gene control. Cell 167, 1188–1200 (2016). source
• Supported

  The citation to this paper is attached to the claim that enhancer functionality depends on chromatin context, not to the separate claims about enhancers being ‘punctate’ or the trans milieu. The paper’s introductory passage states that activities of local cis-regulatory sequences, including enhancers, are heavily influenced by regional chromatin state; its reported results also describe genomic position as scaling their activity. (LLM, conf=0.93)

  cites [88] Maricque, B. B., Chaudhari, H. G. & Cohen, B. A. A massively parallel reporter assay dissects the influence of chromatin structure on cis-regulatory activity. Nat. Biotechnol. 37, 90–95 (2019). source
• Supported

  The citation to this source is attached to the trans-milieu point, specifically cell-type-specific transcription factors. In Conclusions and perspective (page not supplied), the paper says that the combination of active transcription factors determines which enhancers will be functional in a cell type-specific manner. (LLM, conf=0.92)

  cites [89] Heinz, S., Romanoski, C. E., Benner, C. & Glass, C. K. The selection and function of cell type-specific enhancers. Nat. Rev. Mol. Cell Biol. 16, 144–154 (2015). source

In the paper

“At least a few enhancers reside at great distances from their target gene (e.g. the ZRS enhancer located 1 Mb from the Shh gene118, and a MYC enhancer located 1.7 Mb downstream119), although most are much more proximal to their target promoters72.”

What the sources say

• Supported

  The Abstract identifies ZRS as an enhancer that regulates Shh and states that it lies 1 Mb from the gene. Citation 118 is attached to that example, not to the separate MYC example or the claim that most enhancers are more proximal. (LLM, conf=0.95)

  cites [118] Lettice, L. A. et al. A long-range Shh enhancer regulates expression in the developing limb and fin and is associated with preaxial polydactyly. Hum. Mol. Genet. 12, 1725–1735 (2003). source
• ?Could not verify

  The cited source is an Author Correction (Nature 558, E4). Its correction notice discusses a duplicated reference, not the location of a MYC enhancer. Searches for “MYC enhancer located 1.7 Mb downstream” and “1.7 Mb downstream of Myc enhancer” found no passage in our copy addressing that distance. (LLM, conf=0.78)

  cites [119] Bahr, C. et al. Author correction: A Myc enhancer cluster regulates normal and leukaemic haematopoietic stem cell hierarchies. Nature 558, E4 (2018). sourceExperimental — accuracy not yet measured
• Supported

  Citation 72 is attached to the claim that most enhancers are relatively proximal to their target promoters, not to the ZRS or MYC examples. In Results, “Distance between Paired Enhancers and Promoters,” the paper reports a median enhancer-to-target-TSS distance of 24.1 kb for its surveyed class and says this supports a strong role for proximity. That finding is bounded by the study’s selection of enhancers and high-confidence upstream pairs. (LLM, conf=0.92)

  cites [72] Gasperini, M. et al. A genome-wide framework for mapping gene regulation via cellular genetic screens. Cell 176, 377–390 (2019). source

In the paper

“Regardless of any such mechanistic heterogeneity, a common property is that the activity of individual enhancers is generally cell-type-specific or even condition-specific99, and this specificity is a function of the expression levels of the TFs that are able to bind to it89.”

What the sources say

• Supported

  The citation to this paper follows the cell-type- and condition-specificity claim; the transcription-factor explanation has a separate citation. The Abstract describes cell-specific enhancers, and “An environment-dependent transcriptional network” reports gains and losses of enhancer-associated H3K27ac when microglia were moved into culture, supporting condition-dependent activity. The indexed passages provide no page numbers. (LLM, conf=0.88)

  cites [99] Gosselin, D. et al. An environment-dependent transcriptional network specifies human microglia identity. Science 356, eaal3222 (2017). source
• Supported

  The citation to this source is attached to the explanation of enhancer specificity, rather than the preceding claim cited to reference 99. In “Enhancer selection > The role of signal-dependent transcription factors” (page unavailable), the paper says that restricted cell-type-specific expression of lineage-determining transcription factors imposes cell-type-specific enhancer selection at sites with the appropriate motifs. It also reports that environmental signals regulate TF expression and activity to selectively activate enhancers. (LLM, conf=0.89)

  cites [89] Heinz, S., Romanoski, C. E., Benner, C. & Glass, C. K. The selection and function of cell type-specific enhancers. Nat. Rev. Mol. Cell Biol. 16, 144–154 (2015). source

In the paper

“Genes can be affected by a single enhancer or multiple enhancers acting in concert115; conversely, individual enhancers can regulate multiple genes72.”

What the sources say

• Supported

  Citation 115 supports the first clause, not the claim about individual enhancers regulating multiple genes, which is attached to citation 72. The Abstract reports effects of single-enhancer deletions in a sensitized genetic background and phenotypes after paired deletions; the Text describes pairs of enhancers acting additively on gene expression. No page numbers are provided in our copy. (LLM, conf=0.91)

  cites [115] Osterwalder, M. et al. Enhancer redundancy provides phenotypic robustness in mammalian development. Nature 554, 239–243 (2018). source
• Supported

  Citation 72 is attached to the claim that individual enhancers can regulate multiple genes, not to the preceding claim about multiple enhancers acting together. In Results, “A Scaled Multiplex Enhancer-Gene Pair Screen Targeting 5,779 Candidate Enhancers,” targeting 53 candidate enhancers downregulated more than one gene. The authors caution that some multiple-gene pairings may reflect indirect effects. (LLM, conf=0.90)

  cites [72] Gasperini, M. et al. A genome-wide framework for mapping gene regulation via cellular genetic screens. Cell 176, 377–390 (2019). source

In the paper

“To some degree this can be overcome by correlative approaches (e.g. correlating open chromatin status between promoters and enhancers across large numbers of cell types) but such links remain inferential45,134,135.”

What the sources say

• Supported

  In “A genome-wide map of distal DHS-to-promoter connectivity” (page unavailable), the paper correlates distal and promoter chromatin accessibility across 79 cell types to identify candidate enhancer–promoter connections. It then uses interaction and reporter assays to validate some connections, consistent with the claim that correlation alone yields inferential links. (LLM, conf=0.90)

  cites [45] Thurman, R. E. et al. The accessible chromatin landscape of the human genome. Nature 489, 75–82 (2012). source
• Partly supported

  The Methods describe Cicero inferring promoter–distal-element links from correlations in chromatin accessibility, and the Limitations section explicitly calls those links putative and says regulatory influence requires downstream experimentation. The cited paper analyzes single cells during myoblast differentiation, however; it does not establish the sentence’s specific example of correlations across large numbers of cell types. No page numbers are available in our copy. (LLM, conf=0.84)

  cites [134] Pliner, H. A. et al. Cicero predicts cis-regulatory DNA Interactions from single-cell chromatin accessibility data. Mol. Cell 71, 858–871.e8 (2018). sourceExperimental — accuracy not yet measured
• Partly supported

  The Results section, “Correlations in activity profiles link enhancers to target genes” (page not provided), says the authors correlated enhancer activity with gene expression across cell types to link enhancers probabilistically to target genes. The Discussion calls these interactions “inferred,” supporting the claim that the links remain inferential. This paper does not describe the specific example of correlating open-chromatin status between promoters and enhancers. (LLM, conf=0.83)

  cites [135] Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011). sourceExperimental — accuracy not yet measured

In the paper

“Not all distal conserved elements are detectably enhancers39 and far more of the gene-distal non-coding genome is annotated as a regulatory element than is conserved60,104.”

What the sources say

• Supported

  Only the first clause is attributed to this paper; the second has separate citations. The Abstract (page unavailable) reports that only 45% of 167 extremely conserved noncoding sequences reproducibly acted as enhancers in the embryonic-day-11.5 assay. It also cautions that some negative results may be enhancers active at other developmental times, consistent with the claim’s word “detectably.” (LLM, conf=0.92)

  cites [39] Pennacchio, L. A. et al. In vivo enhancer analysis of human conserved non-coding sequences. Nature 444, 499–502 (2006). source
• Partly supported

  The citation to this paper is attached to the second clause, not the claim about distal conserved elements and enhancers. The Summary of ENCODE-identified elements (page unavailable) reports that a conservative measure of regulatory-associated bases covers about twice as much of the genome as estimated pan-mammalian constraint, and the Conclusions say many regulatory elements are not constrained. Those passages support the broad comparison, but do not establish it specifically for the gene-distal non-coding genome. (LLM, conf=0.83)

  cites [60] ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012). This report summarizes the wealth of data generated by the ENCODE Consortium. Hundreds of genome-wide datasets are used across hundreds of cell types and tissues to ascribe a function to the majority of the genome via biochemical annotation. sourceExperimental — accuracy not yet measured
• Partly supported

  The Detection of constrained sequence section reports that constrained elements span 4.2% of the genome. The Chromatin signatures section reports regulatory-associated chromatin states among noncoding constrained elements, but does not directly establish that far more of the gene-distal noncoding genome is annotated as regulatory than conserved. The first clause is attached to a different citation and is not assessed here; page numbers are unavailable in our copy. (LLM, conf=0.74)

  cites [104] Lindblad-Toh, K. et al. A high-resolution map of human evolutionary constraint using 29 mammals. Nature 478, 476–482 (2011). sourceExperimental — accuracy not yet measured

In the paper

“Third, biochemical annotations fail to specify which gene(s) a putative enhancer regulates, let alone the degree of activation conferred78,79.”

What the sources say

• ?Could not verify

  The Abstract and Discussion report that changes in chromatin topology do not reliably predict gene-expression changes. The Online Methods describe using DNase hypersensitivity and enhancer annotations, but our copy does not assess whether biochemical annotations identify an enhancer’s target genes or quantify the activation it confers. Searches for those specific points found no deciding passage; page numbers were unavailable in our copy. (LLM, conf=0.73)

  cites [78] Ghavi-Helm, Y. et al. Highly rearranged chromosomes reveal uncoupling between genome topology and gene expression. Nat. Genet. 51, 1272–1282 (2019). sourceExperimental — accuracy not yet measured
• ?Could not verify

  The Methods section on enhancer-to-gene assignment (page unavailable) describes proximity-based assignment strategies, and the reported STARR-seq results measure promoter-specific activation. Neither passage assesses whether biochemical annotations can identify an enhancer’s target genes or quantify its activation. Searches for biochemical annotations, target-gene prediction, and quantitative activity found no passage making that comparison. (LLM, conf=0.69)

  cites [79] Zabidi, M. A. et al. Enhancer-core-promoter specificity separates developmental and housekeeping gene regulation. Nature 518, 556–559 (2015). STARR-seq utilizing different classes of promoters in D. melanogaster shows that enhancers often do not work in a promoter-generic fashion. sourceExperimental — accuracy not yet measured

In the paper

“Enhancers regulating housekeeping genes may act via a distinct sets of TFs and cofactors than enhancers regulating developmentally specific genes79,120.”

What the sources say

• Supported

  The paper reports that DREF and Trl/GAF preferentially bind and activate housekeeping and developmental enhancers, respectively (Abstract; no page given). It also proposes that compatibility between these enhancer-bound factors and different components of the core-promoter transcription apparatus may mediate the distinction. That supports the citing sentence’s hedged claim about distinct TFs and cofactors. (LLM, conf=0.88)

  cites [79] Zabidi, M. A. et al. Enhancer-core-promoter specificity separates developmental and housekeeping gene regulation. Nature 518, 556–559 (2015). STARR-seq utilizing different classes of promoters in D. melanogaster shows that enhancers often do not work in a promoter-generic fashion. source
• Supported

  The Abstract reports distinct TF-motif enrichment in enhancers associated with developmental versus housekeeping genes and shows that those enhancers preferentially activate different core-promoter groups. It links that enhancer–promoter specificity to compatibility with distinct cofactors, supporting the claim’s tentative wording. (LLM, conf=0.88)

  cites [120] Haberle, V. et al. Transcriptional cofactors display specificity for distinct types of core promoters. Nature 570, 122–126 (2019). source

In the paper

“Through projects such as ENCODE, these annotations underlie the classification of over one million candidate regulatory elements in the human genome as potential enhancers in one or more cell types60,64.”

What the sources say

• Partly supported

  The Abstract (page unavailable) says ENCODE classified 399,124 regions with enhancer-like features, supporting the claim that its annotations identify candidate enhancers. It does not support the attributed count of over one million potential enhancers; the paper's Genome-wide integration section also describes its enhancer classifications as predictions. (LLM, conf=0.88)

  cites [60] ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012). This report summarizes the wealth of data generated by the ENCODE Consortium. Hundreds of genome-wide datasets are used across hundreds of cell types and tissues to ascribe a function to the majority of the genome via biochemical annotation. sourceExperimental — accuracy not yet measured
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [64] ENCODE Project. SCREEN: search candidate regulatory elements by ENCODE. ENCODE Project http://screen.encodeproject.org/index/about (2019).

In the paper

“Although enriched, histone modification and cofactor binding is not completely predictive of enhancer activity54,58,72,77,105.”

What the sources say

• Partly supported

  The Discussion reports that p300 cofactor binding predicted tissue-specific enhancer activity in 80% of tested cases, supporting enrichment without perfect prediction. The paper does not establish the same claim for histone modifications; its Discussion mentions epigenetic marks generally but does not test their predictive accuracy. (LLM, conf=0.87)

  cites [54] Visel, A. et al. ChIP-seq accurately predicts tissue-specific activity of enhancers. Nature 457, 854–858 (2009). sourceExperimental — accuracy not yet measured
• Partly supported

  The Results section (“Bidirectional pairs of capped RNAs identify active enhancers”; page unavailable) reports that untranscribed candidate enhancers defined by histone modifications were much less likely to show reporter activity, supporting the point that those marks do not fully predict activity. The Methods section (“Correlation between ENCODE epigenomic data and CAGE-defined enhancers”; page unavailable) says the authors assessed P300 and transcription-factor binding, but the passages do not establish the claim that cofactor binding is enriched yet incompletely predictive. (LLM, conf=0.82)

  cites [58] Andersson, R. et al. An atlas of active enhancers across human cell types and tissues. Nature 507, 455–461 (2014). This article reports an integrated analysis of cap analysis of gene expression (CAGE) datasets across hundreds of cell types and tissues performed to generate biochemical annotations of thousands of cell type-specific enhancers by their signatures of bidirectional transcription. sourceExperimental — accuracy not yet measured
• Supported

  The Results section reports enrichment of the enhancer-associated histone marks H3K27ac and H3K4me1 and the co-activators p300 and BRD4 among candidate enhancers with measured regulatory effects. The Discussion says a classifier informed by biochemical marks did not appreciably improve the screen’s hit rate, supporting the qualification that these features are not completely predictive. (LLM, conf=0.91)

  cites [72] Gasperini, M. et al. A genome-wide framework for mapping gene regulation via cellular genetic screens. Cell 176, 377–390 (2019). source
• Partly supported

  In Results, “HiDRA elements are enriched in promoters and enhancers” (page unavailable), the paper reports enrichment of active-enhancer-associated histone marks in active fragments. The Introduction and “Regulatory activity outside promoters and enhancers” explain why epigenomic marks do not fully predict reporter activity. The paper discusses enrichment of transcription-factor motifs and binding, but the available passages do not establish the claim specifically for cofactor binding. (LLM, conf=0.83)

  cites [77] Wang, X. et al. High-resolution genome-wide functional dissection of transcriptional regulatory regions and nucleotides in human. Nat. Commun. 9, 5380 (2018). sourceExperimental — accuracy not yet measured
• Partly supported

  The supplied Abstract passages report that H3K27ac signal distinguished most functional MYC enhancers but did not rank their effects correctly, supporting the point that a histone modification is informative but not fully predictive. They also report transcription-factor binding at the seven enhancers, but do not establish that cofactor binding is enriched or test its predictive value. (LLM, conf=0.83)

  cites [105] Fulco, C. P. et al. Systematic mapping of functional enhancer-promoter connections with CRISPR interference. Science 354, 769–773 (2016). sourceExperimental — accuracy not yet measured

In the paper

“A major advantage of MPRAs is that sequences to be tested can simply be synthesized, enabling straightforward saturation mutagenesis [G] of enhancers67,184,185 as well as programming synthetic enhancers to inform modelling of their properties186,187.”

What the sources say

• Supported

  The citation supports the saturation-mutagenesis portion of the sentence. The Introduction describes synthesizing enhancer variants with programmed mutations, and Results (“Synthetic saturation mutagenesis and massively parallel readout”) report libraries representing all possible single-nucleotide substitutions in three enhancers. The separate claim about programming synthetic enhancers is assigned to other citations in the citing sentence. (LLM, conf=0.91)

  cites [67] Patwardhan, R. P. et al. Massively parallel functional dissection of mammalian enhancers in vivo. Nat. Biotechnol. 30, 265–270 (2012). Along with Melnikov et al. (2012), this study is the first application of an MPRA to enhancer sequences. source
• Supported

  The Introduction says MPRA libraries are made by synthesizing oligonucleotides containing regulatory elements. In Results (Experimental design and mutagenesis strategies), the authors report synthesizing enhancer variants that include all possible single substitutions; the Discussion describes using synthesis and sequence-activity models to develop novel regulatory elements. Our copy provides section labels but no page numbers. (LLM, conf=0.91)

  cites [184] Melnikov, A. et al. Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay. Nat. Biotechnol. 30, 271 (2012). Along with Patwardhan et al. (2012), this study shows the first application of an MPRA to variants of enhancer sequences, in addition to coining the term ‘massively parallel reporter assay’. source
• Partly supported

  The Results section, “Construction of saturation mutagenesis libraries,” confirms that the authors used MPRAs to test mutations in regulatory elements, including enhancers. But their Methods describe generating sequence variants by error-prone PCR, not by synthesizing the sequences to be tested. The separate claim about programming synthetic enhancers is attached to other citations in the citing sentence. (LLM, conf=0.86)

  cites [185] Kircher, M. et al. Saturation mutagenesis of twenty disease-associated regulatory elements at single base-pair resolution. Nat. Commun. 10, 3583 (2019). sourceExperimental — accuracy not yet measured
• Supported

  The Materials and Methods describe synthesizing oligonucleotide libraries for the MPRA. The Results describe systematic mutations in candidate enhancers, and the pool descriptions document synthetic enhancers assembled from selected motifs. The paper also models how motif composition predicts enhancer activity. Our copy provides no page numbers for these passages. (LLM, conf=0.91)

  cites [186] Grossman, S. R. et al. Systematic dissection of genomic features determining transcription factor binding and enhancer function. Proc. Natl Acad. Sci. USA 114, E1291–E1300 (2017). source
• Supported

  The Abstract describes synthesizing a library of synthetic regulatory elements and testing their activity with a massively parallel reporter assay. It says the experiment tested binding-site copy number, spacing, combination and order, providing support for a model of regulatory-element activity. This supports the synthetic-enhancer programming portion of the sentence to which this paper is cited; the saturation-mutagenesis portion has separate citations. (LLM, conf=0.92)

  cites [187] Smith, R. P. et al. Massively parallel decoding of mammalian regulatory sequences supports a flexible organizational model. Nat. Genet. 45, 1021–1028 (2013). source

In the paper

“As scRNA-seq is costly and individual enhancers most likely only regulate one or a few genes in cis, we developed a related approach wherein ~28 gRNAs were introduced per cell, enabling 5,779 candidate enhancers to be evaluated in a single experiment72.”

What the sources say

• Supported

  The Results section, “A Scaled Multiplex Enhancer-Gene Pair Screen Targeting 5,779 Candidate Enhancers,” describes one experiment targeting 5,779 candidate enhancers and reports a median of 28 gRNAs per cell. This supports both quantities in the attributed claim. (LLM, conf=0.94)

  cites [72] Gasperini, M. et al. A genome-wide framework for mapping gene regulation via cellular genetic screens. Cell 176, 377–390 (2019). source

In the paper

“Further challenges include linkage disequilibrium, the possibility that more than one variant contributes to a given association, the need to match the cell type in which functional characterization and/or biochemical annotation is being carried out with the disease in question, and the fact that the mechanisms by which non-coding variants exert their effects on disease risk remain unclear223.”

What the sources say

• Partly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [223] Boyle, E. A., Li, Y. I. & Pritchard, J. K. An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–1186 (2017). sourceExperimental — accuracy not yet measured

In the paper

“However, at least as they are usually implemented, MPRAs remain limited by several factors, including the length constraints and cost of DNA synthesis or the immense complexity of shotgun libraries, the confounding effect of the reporter’s minimal promoter, and the use of episomes whose chromatin may have different properties than that of the genome189.”

What the sources say

• ?Could not verify

  The “Supercoiling domains” and “Effects of supercoiling on DNA” sections discuss DNA topology and chromatin, not limitations of massively parallel reporter assays. Searches for MPRAs, episomes, minimal promoters, DNA synthesis costs, and shotgun libraries found no passage addressing the attributed claim. (LLM, conf=0.75)

  cites [189] Gilbert, N. & Allan, J. Supercoiling in DNA and chromatin. Curr. Opin. Genet. Dev. 25, 15–21 (2014). sourceExperimental — accuracy not yet measured

In the paper

“Activating domains (dCas9–VPR or dCas9–p300) have also been used to scan for poised enhancers in an approach termed CRISPR activation or ‘CRISPRa’92,208(Figure 2d).”

What the sources say

• Partly supported

  The Abstract reports using CRISPRa to scan genomic regions and identify stimulation-responsive enhancers in unstimulated cells. But it specifies dCas9-VP64, not either dCas9-VPR or dCas9-p300; the Methods section on cell generation likewise identifies dCas9-VP64. No page numbers are available in our copy. (LLM, conf=0.88)

  cites [92] Simeonov, D. R. et al. Discovery of stimulation-responsive immune enhancers with CRISPR activation. Nature 549, 111–115 (2017). sourceExperimental — accuracy not yet measured
• Partly supported

  The Results section (“Epigenetic Activation Reveals Gene Regulatory Elements”; page unavailable) describes a dCas9-p300 gain-of-function screen for regulatory elements near HER2, and the Discussion says dCas9-p300 can activate expression from distal elements. Our copy does not describe those elements as poised enhancers or report using dCas9-VPR. The cited paper therefore supports the dCas9-p300 screening component, but not the full wording of the claim. (LLM, conf=0.83)

  cites [208] Klann, T. S. et al. CRISPR–Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome. Nat. Biotechnol. 35, 561 (2017). sourceExperimental — accuracy not yet measured

In the paper

“How are we to explain the fact that the vast majority of biochemically nominated candidate enhancers, when perturbed by CRISPRi, do not result in detectable changes in expression of genes located in cis72?”

What the sources say

• Supported

  The Discussion reports detectable cis expression changes for only ~10% of the candidate enhancers tested, supporting the claim that the vast majority showed no detectable change. It also notes technical and biological reasons why a negative CRISPRi result need not mean an element lacks enhancer activity. (LLM, conf=0.93)

  cites [72] Gasperini, M. et al. A genome-wide framework for mapping gene regulation via cellular genetic screens. Cell 176, 377–390 (2019). source

In the paper

“For example, single-cell ATAC-seq has enabled the in vivo profiling of accessible chromatin at the scale of a whole organism82,83.160,161.”

What the sources say

• Partly supported

  The Abstract describes ATAC-seq-based chromatin accessibility profiling in more than 15,000 single cells. The experiments described in our copy use mixtures of cultured human and mouse cell lines, not in vivo profiling across a whole organism; the paper discusses broader tissue characterization only as a future possibility. (LLM, conf=0.88)

  cites [82] Cusanovich, D. A. et al. Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348, 910–914 (2015). sourceExperimental — accuracy not yet measured
• Partly supported

  The Main section (page unavailable) reports that scATAC-seq maps accessible chromatin in individual cells. Its experiments used captured cells from cell lines; the paper does not report in vivo profiling at the scale of a whole organism. (LLM, conf=0.88)

  cites [83] Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486–490 (2015). sourceExperimental — accuracy not yet measured
• Supported

  The Introduction says the study used sci-ATAC-seq to measure chromatin accessibility in about 100,000 single cells from 13 adult mouse tissues. This supports in vivo profiling at an organism-wide scale; it does not imply that every tissue was sampled. (LLM, conf=0.89)

  cites [160] Cusanovich, D. A. et al. A single-cell atlas of in vivo mammalian chromatin accessibility. Cell 174, 1309–1324.e18 (2018). source
• Supported

  The paper’s opening passage (section labeled Abstract; no page given) reports sci-ATAC-seq profiling of chromatin accessibility in more than 20,000 nuclei from whole Drosophila embryos across three developmental stages. Its methods passage specifies that the nuclei came from fixed embryos, supporting organism-scale profiling without implying measurement in living embryos. (LLM, conf=0.88)

  cites [161] Cusanovich, D. A. et al. The cis-regulatory dynamics of embryonic development at single-cell resolution. Nature 555, 538–542 (2018). source

In the paper

“Second, CRISPR technology has recently made it much more straightforward to delete genomic sequences in the mouse, enabling new insights into aspects such as enhancer redundancy115 and the consequences of disrupting TADs220.”

What the sources say

• Supported

  The Text section reports using CRISPR/Cas9 to delete enhancers in mice and, through double-enhancer knockouts, finding evidence of enhancer redundancy. The Methods section describes how the mouse deletions were made. The separate claim about TAD disruption is attached to citation 220, not this source. (LLM, conf=0.92)

  cites [115] Osterwalder, M. et al. Enhancer redundancy provides phenotypic robustness in mammalian development. Nature 554, 239–243 (2018). source
• Supported

  The citation is attached to the consequences of disrupting TADs, not to enhancer redundancy. The Results section on CRISPR-mediated re-engineering describes making mice with human-disease rearrangements, and the Results section on EPHA4 TAD boundaries shows that preserving boundary regions prevented ectopic interactions, misexpression, and limb abnormalities. Page numbers are unavailable in our copy. (LLM, conf=0.91)

  cites [220] Lupiáñez, D. G. et al. Disruptions of topological chromatin domains cause pathogenic rewiring of gene–enhancer interactions. Cell 161, 1012–1025 (2015). This article demonstrates that rearrangement across TAD boundaries can cause a pathogenic phenotype in humans; the study also uses CRISPR–Cas9 to effectively reconstruct human patient genome rearrangements in mouse models. source

In the paper

“The fact that most MPRAs only test for enhancer activity using a single promoter, or at best a handful79, could contribute to a high false negative rate.”

What the sources say

• Partly supported

  The study tested enhancer activity with two core promoters, and its results show that many enhancers were much more active with one than the other (Abstract; page not provided). It therefore supports the relevance of testing more than one promoter, but does not establish the cited claim that most MPRAs use only one or a handful of promoters. The possible false-negative consequence is framed as the citing authors’ inference. (LLM, conf=0.82)

  cites [79] Zabidi, M. A. et al. Enhancer-core-promoter specificity separates developmental and housekeeping gene regulation. Nature 518, 556–559 (2015). STARR-seq utilizing different classes of promoters in D. melanogaster shows that enhancers often do not work in a promoter-generic fashion. sourceExperimental — accuracy not yet measured

In the paper

“MPRAs have been applied to assess biochemically annotated candidate enhancers77,176-178, candidate enhancers harbouring variants that potentially mediate eQTLs179-182, and even scans of the entire human genome108,183.”

What the sources say

• Partly supported

  This source is cited for the genome-wide-scan portion of the sentence. The Introduction reports a genome-wide HiDRA assay, but says its approximately 7 million tested fragments were preferentially selected from accessible chromatin in GM12878 cells. The Results (‘HiDRA experimental method overview’; page unavailable) likewise say the library targeted accessible DNA rather than randomly sampling the entire genome, so the claim overstates its scope. (LLM, conf=0.86)

  cites [77] Wang, X. et al. High-resolution genome-wide functional dissection of transcriptional regulatory regions and nucleotides in human. Nat. Commun. 9, 5380 (2018). sourceExperimental — accuracy not yet measured
• Supported

  The Results section (‘Quantifying DEX-induced regulatory element activity’; page unavailable) reports testing GR binding sites with ChIP-reporter assays and finding significant regulatory activity at 1,376 sites. The Methods (‘ChIP-reporter Input Library Construction’; page unavailable) describe adapting ChIP-seq libraries to STARR-seq. This supports the biochemically annotated candidate-enhancer clause to which this paper is cited; the eQTL and entire-genome clauses have separate citations. (LLM, conf=0.90)

  cites [176] Vockley, C. M. et al. Direct GR binding sites potentiate clusters of TF binding across the human genome. Cell 166, 1269–1281.e19 (2016). source
• Supported

  The citation is attached to the first part of the sentence, about assessing biochemically annotated candidate enhancers. In “Experimental design of the CapStarr-seq approach” (page unavailable), the paper describes selecting putative regulatory regions using DNaseI-seq and transcription-factor ChIP-seq, then testing their enhancer activity with CapStarr-seq. The eQTL and whole-human-genome examples have separate citations. (LLM, conf=0.93)

  cites [177] Vanhille, L. et al. High-throughput and quantitative assessment of enhancer activity in mammals by CapStarr-seq. Nat. Commun. 6, 6905 (2015). source
• Supported

  This citation supports the first clause, about biochemically annotated candidate enhancers; the later clauses have separate citations. The Results section, “Identification of candidate hominoid-specific enhancers” (page not available), says the authors selected candidates using H3K27ac peaks and ChromHMM strong-enhancer annotations, then tested them with an MPRA. (LLM, conf=0.94)

  cites [178] Klein, J. C., Keith, A., Agarwal, V., Durham, T. & Shendure, J. Functional characterization of enhancer evolution in the primate lineage. Genome Biol. 19, 99 (2018). source
• Partly supported

  The Introduction and Experimental Procedures describe an MPRA screening variants linked to red-blood-cell GWAS hits, and the Discussion reports that some tested variants lie within endogenous enhancers. The paper does not say these candidates were selected because they might mediate eQTLs; it mentions eQTL studies in the Introduction as a separate way to identify target genes. This verdict concerns the enhancer-variant clause to which this source is attached, not the separately cited whole-genome scans. (LLM, conf=0.85)

  cites [179] Ulirsch, J. C. et al. Systematic functional dissection of common genetic variation affecting red blood cell traits. Cell 165, 1530–1545 (2016). sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [180] Tewhey, R. et al. Direct identification of hundreds of expression-modulating variants using a multiplexed reporter assay. Cell 172, 1132–1134 (2018). source
• Supported

  This source supports the eQTL-related clause, not the separately cited claims about other enhancer applications or genome-wide scans. The Results section, “Fine mapping genetic associations with phenotypes” (page unavailable), describes a population-scale reporter assay of variants associated with LINC00881 expression and identifies one that altered regulatory activity. (LLM, conf=0.91)

  cites [181] Vockley, C. M. et al. Massively parallel quantification of the regulatory effects of noncoding genetic variation in a human cohort. Genome Res. 25, 1206–1214 (2015). source
• Partly supported

  The Introduction says MPRAs have been used to characterize variants underlying eQTLs, and the Results identify two tested osteoarthritis-associated SNPs as eQTLs. This paper’s own MPRA, however, selected variants associated with osteoarthritis GWAS signals rather than candidate enhancers selected for potentially mediating eQTLs. The cited paper therefore supports the general eQTL application, but not that more specific description of its screen. (LLM, conf=0.81)

  cites [182] Klein, J. C. et al. Functional testing of thousands of osteoarthritis-associated variants for regulatory activity. Nat. Commun. 10, 2434 (2019). sourceExperimental — accuracy not yet measured
• Supported

  This paper supports the genome-wide scan clause to which it is cited. The Experimental Methods (STARR-seq; page unavailable) describe genome-wide STARR-seq libraries made from human genomic DNA and genome-wide screens in HeLa-S3 cells. (LLM, conf=0.93)

  cites [108] Muerdter, F. et al. Resolving systematic errors in widely used enhancer activity assays in human cells. Nat. Methods 15, 141–149 (2018). source
• Supported

  This source is cited for the whole-human-genome scan, not the earlier examples concerning annotated enhancers or eQTL variants. The Conclusions (page unavailable) state that the authors extended STARR-seq enhancer profiling to the entire human genome. (LLM, conf=0.94)

  cites [183] Liu, Y. et al. Functional assessment of human enhancer activities using whole-genome STARR-sequencing. Genome Biol. 18, 219 (2017). source

In the paper

“The initial CRISPR screens of regulatory elements delivered an individual gRNA per cell195.”

What the sources say

• Supported

  In “Tiled pooled enhancer editing in situ” (page not available), the paper says the lentiviral sgRNA library was delivered at low multiplicity so that nearly all selected cells contained a single integrant. This supports the claim’s description of an individual guide per cell, with the qualification that the paper says “nearly all,” not every cell. (LLM, conf=0.90)

  cites [195] Canver, M. C. et al. BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis. Nature 527, 192–197 (2015). This study is the first CRISPR-based screen to identify functional non-coding sequence within an enhancer. source

In the paper

“A clear strength of MPRAs is their ability to simultaneously test large numbers of sequences for regulatory activity via a relatively straightforward, widely accessible toolkit (i.e. oligonucleotide synthesis, molecular biology, cell culture, and sequencing)175.”

What the sources say

• Partly supported

  The Abstract says massively parallel reporter assays map regulatory sequence–function relationships and can assess hundreds to thousands of variants in one experiment. The Construction of a variant library and Sequencing to count variant frequency sections describe oligonucleotide libraries and sequencing, but the paper does not establish that the toolkit is relatively straightforward or widely accessible; it describes library construction as challenging. (LLM, conf=0.84)

  cites [175] Gasperini, M., Starita, L. & Shendure, J. The power of multiplexed functional analysis of genetic variants. Nat. Protoc. 11, 1782–1787 (2016). sourceExperimental — accuracy not yet measured

In the paper

“CRISPRi has subsequently been used in multiple single-gene screens of regulatory elements105,208,209.”

What the sources say

• Supported

  The paper’s Abstract describes pooled CRISPRi screens for regulatory elements near the individual genes MYC and GATA1. It is therefore an example of the single-gene regulatory-element screens cited in the sentence; the word “multiple” refers to the cited studies collectively. (LLM, conf=0.90)

  cites [105] Fulco, C. P. et al. Systematic mapping of functional enhancer-promoter connections with CRISPR interference. Science 354, 769–773 (2016). source
• Supported

  The Abstract describes screens using the dCas9KRAB repressor to identify regulatory elements at the β-globin and HER2 loci. The Results section on epigenetic repression also reports a dCas9KRAB screen of elements affecting HER2 expression, making this paper an example of the cited use of CRISPRi. (LLM, conf=0.91)

  cites [208] Klann, T. S. et al. CRISPR–Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome. Nat. Biotechnol. 35, 561 (2017). source
• Supported

  The Abstract reports CRISPRi-FlowFISH screens for 30 genes, testing candidate regulatory elements for their effects on gene expression. The Methods describe staining each screen for a gene of interest, supporting the description of multiple single-gene screens. No page number is supplied in our copy. (LLM, conf=0.92)

  cites [209] Fulco, C. P. et al. Activity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations. Nat. Genet. 51, 1664–1669 (2019). source

In the paper

“Consequent to these limitations, automatic sequence-based enhancer annotation is helpful and worthwhile129, but performs modestly for predicting enhancers and the contexts in which they are active.”

What the sources say

• ?Not checked — no full text of the sourcecites [129] Van Loo, P. & Marynen, P. Computational methods for the detection of cis-regulatory modules. Brief. Bioinform. 10, 509–524 (2009). source

In the paper

“In light of this heterogeneity, a ‘one-size-fits-all’ set of annotations to catalogue enhancers seems problematic.”

In the paper

“As a consequence, the field lacks a clear framework for identifying enhancers, with different subfields (e.g. biochemistry, genomics, etc.) using different definitions and criteria, even though we are all ostensibly studying the same underlying biological phenomenon.”

In the paper

“Enhancers are only one class of non-coding DNA regulatory element, although they are widely presumed to be the most numerically prevalent (Box 2).”

In the paper

“TF sequence motifs alone are poorly predictive, as only a small fraction of potential TF binding sites in the genome are typically bound in a cell type where the TF is expressed68.”

What the sources say

• ?Not checked — no full text of the sourcecites [68] Spitz, F. & Furlong, E. E. M. Transcription factors: from enhancer binding to developmental control. Nat. Rev. Genet. 13, 613–626 (2012). source

In the paper

“Finally, there may be in vivo enhancers that are non-canonically marked, or that have contextual dependencies that are not maintained in a reporter assay.”

In the paper

“There may be sequences that activate transcription in the context of a reporter assay but do not meaningfully do so in vivo.”

In the paper

“Our present understanding is that enhancers are bound by cell-type-specific TFs, are associated with regions of open chromatin, and are flanked by histones carrying H3K27ac and/or H3K4me1 modifications.”

What the sources say

• ?Not checked — no full text of the sourcecites [68] Spitz, F. & Furlong, E. E. M. Transcription factors: from enhancer binding to developmental control. Nat. Rev. Genet. 13, 613–626 (2012). source
• ?Not checked — no full text of the sourcecites [69] Shlyueva, D., Stampfel, G. & Stark, A. Transcriptional enhancers: from properties to genome-wide predictions. Nat. Rev. Genet. 15, 272–286 (2014). source

In the paper

“The recruited TFs directly or indirectly (e.g. via a co-activator) facilitate chromatin remodelling and recruitment of the basal transcriptional machinery at the promoter (Figure 1a), thereby enhancing transcription91.”

What the sources say

• ?Not checked — no full text of the sourcecites [91] Thanos, D. & Maniatis, T. Virus induction of human IFNβ gene expression requires the assembly of an enhanceosome. Cell 83, 1091–1100 (1995). source

In the paper

“They interact with their cognate promoters in 3D space, and can be latent, primed, or active68,69.”

What the sources say

• ?Not checked — no full text of the sourcecites [68] Spitz, F. & Furlong, E. E. M. Transcription factors: from enhancer binding to developmental control. Nat. Rev. Genet. 13, 613–626 (2012). source
• ?Not checked — no full text of the sourcecites [69] Shlyueva, D., Stampfel, G. & Stark, A. Transcriptional enhancers: from properties to genome-wide predictions. Nat. Rev. Genet. 15, 272–286 (2014). source

In the paper

“New data types, e.g. based on massively parallel reporter assays (MPRAs) or genome editing, are further complicating the picture, particularly as biochemical annotations and functional data are not always in agreement.”

In the paper

“The human gene catalogue is essentially complete, but we lack an equivalently vetted inventory of bona fide human enhancers.”

In the paper

“However, methods for profiling chromatin state in single cells are advancing quickly and have the potential to overcome this challenge.”

In the paper

“Furthermore, the presence of a motif for an expressed TF does not mean that it is bound, and even if it is, not all binding is functional68.”

What the sources say

• ?Not checked — no full text of the sourcecites [68] Spitz, F. & Furlong, E. E. M. Transcription factors: from enhancer binding to developmental control. Nat. Rev. Genet. 13, 613–626 (2012). source

In the paper

“Although we have many clues, the mechanistic details of how enhancers activate expression of their target genes have yet to be fully worked out (Figure 1a).”

In the paper

“This has resulted in the cataloguing of over one million candidate cis-regulatory elements with enhancer-like signatures; these collectively span ~16% of the human genome64.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [64] ENCODE Project. SCREEN: search candidate regulatory elements by ENCODE. ENCODE Project http://screen.encodeproject.org/index/about (2019).

In the paper

“Hundreds-of-thousands of candidate enhancers have been nominated by biochemical annotations; however, only a handful of these are validated and confidently linked to their target gene(s).”

In the paper

“However, despite their clear importance to both basic and disease biology, there is a tremendous amount that we still do not understand about the repertoire of human enhancers, including where they reside, how they work, and what genes they mediate their effects through.”

In the paper

“Rather, our understanding of the core characteristics of enhancers, based largely on a few paradigmatic examples, is being challenged by studies that suggest a more heterogeneous landscape.”

In the paper

“On one hand, given the diversity of epigenomic contexts traversed during development, eQTL studies may represent our only hope for comprehensively observing the consequences of human enhancer disruption (as all engineered mutations will be in models such as cell lines, organoids, or mice).”

In the paper

“This may lead to false positives (e.g. through spreading of KRAB repressive effects, or unnatural activation by VPR) or false negatives (e.g. an active enhancer that is not susceptible to CRISPRi-mediated inactivation).”

In the paper

“Single-cell methods may also enable the identification of candidate enhancers that appear to be active in extremely specific developmental contexts, or heterogeneously active within a single cell type.”

In the paper

“In a coding screen, the indels resulting from NHEJ at a single DSB are likely to result in a frameshift and the gene’s complete loss of function.”

In the paper

“The disadvantages of in vivo reporter assays are similar to MPRAs, including that elements are tested outside of their native genomic context, and the elements are not linked to their endogenous target gene(s).”

In the paper

“Heterogeneous classes of data will be available for many variants (e.g. biochemical annotations, molecular QTLs, computational predictions of variant effects, MPRAs, and CRISPR perturbation) but will not always agree.”

In the paper

“By contrast, wholesale deletions of candidate enhancers are unambiguously disruptive of a bounded region.”

In the paper

“A further challenge is that although technologies are rapidly improving, it may simply not be realistic to test every candidate enhancer with every functional approach in every cell type of interest.”

In the paper

“Relying on epigenetic perturbations, rather than genetic ones, bypasses many of these limitations, e.g. allowing all alleles in a given cell to be more consistently perturbed.”

In the paper

“An MPRA tests the functional activity of thousands of candidate regulatory sequences in a single experiment.”

In the paper

“Practitioners of MPRAs, including ourselves, typically fail to confirm that each ‘positive’ element fully meets the original Banerji definition (i.e. active in both orientations and from many positions).”

In the paper

“In this vein, the ability of single guide scans to fully ‘tile’ a region is limited both by the distribution of protospacer adjacent motif [G] (PAM) sites and the non-random distribution of NHEJ-mediated mutations.”

In the paper

“Overall, single-cell methods have the potential to replace conventional bulk 1D and 3D biochemical assays.”

In the paper

“The first such screen delivered one CRISPRi perturbation per cell, targeting 71 candidate enhancers across 7 genomic loci216.”

What the sources say

• ?Not checked — no full text of the sourcecites [216] Xie, S., Duan, J., Li, B., Zhou, P. & Hon, G. C. Multiplexed engineering and analysis of combinatorial enhancer activity in single cells. Mol. Cell 66, 285–299.e5 (2017). This study reports the first use of single-cell RNA-seq to phenotype pools of candidate enhancer perturbations in a ‘whole-transcriptome’ screen. source

In the paper

“On the other side of the balance sheet, putative enhancers identified by CRISPR screens may fail to show activity in MPRAs.”

In the paper

“Although small indels are probably capable of disrupting TF binding sites within an enhancer, they might only do so if directly overlapping the binding site itself.”

In the paper

“All of the aforementioned methods (biochemical annotations, MPRAs, CRISPR screens, etc.) are performed in vitro on cell lines, and are therefore only capable of accessing a limited number of biological contexts.”

In the paper

“We note that many of the challenges highlighted here apply not only to candidate enhancers, but also to non-coding variants located within them.”

In the paper

“Advances in scalable methods for the biochemical annotation and functional characterization of regulatory elements are paving the way to a comprehensive catalogue of human enhancers.”

In the paper

“Additionally, we also note that our definition may not be easily adaptable to candidate enhancers that overlap promoters or protein-coding regions.”

In the paper

“However, like the biochemical annotations on which they are based, any such candidate links will still lack functional validation.”

In the paper

“Such ‘long deletion’ scans deliver pairs of gRNAs per cell that target closely located sites, which can result in clean deletion of the intervening sequence.”

In the paper

“Furthermore, such multiplex screens may be limited to epigenetic perturbation, particularly if large numbers of DSBs are toxic to cells.”

In the paper

“However, a challenge is that the further apart the pair of cuts induced by the gRNAs, the less often full deletion occurs, e.g. ~20% for a 365 bp deletion204.”

What the sources say

• ?Not checked — no full text of the sourcecites [204] Gasperini, M. et al. CRISPR/Cas9-mediated scanning for regulatory elements required for HPRT1 expression via thousands of large, programmed genomic deletions. Am. J. Hum. Genet. 101, 192–205 (2017). source

In the paper

“Conventional MPRAs also fail to capture how each sequence affects and is affected by its genomic neighbourhood, nor which promoter(s) an ‘active’ enhancer endogenously affects.”

In the paper

“The fact that MPRAs test each sequence of interest entirely out of context is on one hand a strength, as it isolates that sequence in order to study its properties independently of that context. But it is also a weakness in that properties observed out-of-context may be irrelevant when that native context is restored.”

In the paper

“As discussed above, eQTL studies are powerful for assessing in vivo effects, but are limited in critical ways.”