Testing Proximity of Genomic Regions to Transcription Start Sites and Enhancers Complements Gene Set Enrichment Testing

Lee, Christopher; Wang, Kai; Qin, Tingting; Sartor, Maureen A.

doi:10.3389/fgene.2020.00199

Cited by 5 publications

(3 citation statements)

References 60 publications

(65 reference statements)

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“…Linking enhancers to their target promoters remains a challenging problem [79][80][81][82]. To the best of our knowledge, the most successful approach so far was to link promoters to enhancers based on 100 K distance proximity of chromatin-accessible regions [83][84][85][86][87], without considering possible interference of neighbouring expressed genes. Our approach, which takes into account distance to the nearest transcribed gene, chromatin accessibility, and TAD borders, could allow for the detection of more precise promoter-enhancer links for developmental genes.…”

Section: Discussionmentioning

confidence: 99%

Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation

Abnizova,

Stapel,

Boekhorst

et al. 2024

BMC Biol

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Background Regulation of transcription is central to the emergence of new cell types during development, and it often involves activation of genes via proximal and distal regulatory regions. The activity of regulatory elements is determined by transcription factors (TFs) and epigenetic marks, but despite extensive mapping of such patterns, the extraction of regulatory principles remains challenging. Results Here we study differentially and similarly expressed genes along with their associated epigenomic profiles, chromatin accessibility and DNA methylation, during lineage specification at gastrulation in mice. Comparison of the three lineages allows us to identify genomic and epigenomic features that distinguish the two classes of genes. We show that differentially expressed genes are primarily regulated by distal elements, while similarly expressed genes are controlled by proximal housekeeping regulatory programs. Differentially expressed genes are relatively isolated within topologically associated domains, while similarly expressed genes tend to be located in gene clusters. Transcription of differentially expressed genes is associated with differentially open chromatin at distal elements including enhancers, while that of similarly expressed genes is associated with ubiquitously accessible chromatin at promoters. Conclusion Based on these associations of (linearly) distal genes’ transcription start sites (TSSs) and putative enhancers for developmental genes, our findings allow us to link putative enhancers to their target promoters and to infer lineage-specific repertoires of putative driver transcription factors, within which we define subgroups of pioneers and co-operators.

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Section: Discussionmentioning

confidence: 99%

Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation

Abnizova,

Stapel,

Boekhorst

et al. 2024

BMC Biol

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“…1 C: Evaluation of the Enhancer-Target gene Definition), to identify the EnTDefs with greatest concordance. The assumption of this approach, used previously in [ 72 , 73 ], is that TFs tend to the regulate genes in the biological processes to which they belong, and thus greater overlap with TF GO BP annotation indicates more accurate enrichment results, and thus more accurate peak-to-gene assignments. We used the Gene Ontology Biological Process (GO BP) terms that each of the 34 TFs were assigned to by the GO database [ 74 , 75 ], and extracted the GOBP-to-gene assignments from the human annotation Bioconductor package org.Hs.eg.db [ 76 ].…”

Section: Methodsmentioning

confidence: 99%

Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data

Qin

Lee

et al. 2022

Genome Biol

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Background Revealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1860 human genome-wide distal enhancer-to-target gene definitions (EnTDefs). To evaluate performance, we used gene set enrichment (GSE) testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology annotations, and other benchmarks. Results The top ranked 741 (40%) EnTDefs significantly outperform the common, naïve approach of linking distal regions to the nearest genes, and the top 10 EnTDefs perform well when applied to ChIP-seq data of other cell types. The GSE-based ranking of EnTDefs is highly concordant with ranking based on overlap with curated benchmarks of enhancer-gene interactions. Both our top general EnTDef and cell-type-specific EnTDefs significantly outperform seven independent computational and experiment-based enhancer-gene pair datasets. We show that using our top EnTDefs for GSE with either genome-wide DNA methylation or ATAC-seq data is able to better recapitulate the biological processes changed in gene expression data performed in parallel for the same experiment than our lower-ranked EnTDefs. Conclusions Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.

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“…the GOBP terms assigned to the 34 TFs by the GO database, excluding the terms with <15 or >2000 assigned genes) ( Figure 1C: Evaluation of the Enhancer-Target gene Definition), to identify the EnTDefs with greatest concordance. The assumption of this approach, used previously in [70,71], is that TFs tend to the regulate genes in the biological processes to which they belong, and thus greater overlap with TF GO BP annotation indicates more accurate enrichment results, and thus more accurate peak-to-gene assignments. For a full justification of this, see Supplementary Methods.…”

Section: Evaluation Of Enhancer-target Gene Definitionsmentioning

confidence: 99%

Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data

Qin

Lee

Cavalcante

et al. 2020

Preprint

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Revealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1,860 human genome-wide distal Enhancer to Target gene Definitions (EnTDefs). To evaluate performance, we used gene set enrichment testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology (GO) annotations., assuming that greater concordance with TF-GO annotation signifies better enrichment results and thus more accurate enhancer-to-gene assignments. Notably, the top ranked 741 (40%) EnTDefs significantly outperformed the common, na&iumlve approach of linking distal regions to the nearest genes (FDR < 0.05), and the top 10 ranked EnTDefs performed well when applied to ChIP-seq data of other cell types. These general EnTDefs also showed comparable performance to EnTDefs generated using cell-type-specific data. Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.

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Testing Proximity of Genomic Regions to Transcription Start Sites and Enhancers Complements Gene Set Enrichment Testing

Cited by 5 publications

References 60 publications

Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation

Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation

Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data

Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data

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