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ChIP-Enrich: gene set enrichment testing for ChIP-seq data.

Welch RP, Lee C, Imbriano PM, Patil S, Weymouth TE, Smith RA, Scott LJ, Sartor MA - Nucleic Acids Res. (2014)

Bottom Line: Adjustment for gene locus length is necessary because it is often positively associated with the presence of one or more peaks and because many biologically defined gene sets have an excess of genes with longer or shorter gene locus lengths.We identify DNA-binding proteins, including CTCF, JunD and glucocorticoid receptor α (GRα), that show different enrichment patterns for peaks closer to versus further from transcription start sites.We also identify known and potential new biological functions of GRα.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Biostatistics Department, University of Michigan, Ann Arbor, MI 48109, USA.

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Comparison of GRα enrichment results for ChIP-seq (using two locus definitions) and RNA-seq data from A549 cells. Enriched GO terms for differentially expressed transcripts and GRα binding following 100-nM DEX treatment show stronger overlap using the ‘nearest TSS’ locus definition than using the ‘≤1 kb from TSS’ definition. (a) Observed spline fit for GRα fits neither FET nor the binomial test assumption (orange); bar plot of the proportion of peaks at different distances from the TSS. See Figure 2(4a) and (b) for further details. (b) Using the ‘nearest TSS’ locus definition with GRα results in more overlapping terms with RNA-seq results than using ‘≤1 kb from TSS’. (c) Using the top 195 ranked terms for each test, FET and the binomial test have more overlap with ChIP-Enrich than with each other. (d)–(f) Comparison of –log10(P-values) for GO term enrichment tests based on ChIP-seq data (ChIP-Enrich) and/or RNA-seq (GOseq) data. (f) Many enriched RNA-seq terms would have been missed in the ChIP-seq data if only peaks in promoter regions were considered. GO terms enriched and FDR ≤ 0.05: for Y-axis test only (green); for X-axis test only (blue); for X- and Y-axis tests (orange); for neither (black). Vasculature development and related GO terms (triangles). The majority of GO terms that overlap between ‘≤1 kb from TSS’ and ‘nearest TSS’ are related to fatty acid metabolism, reactive oxygen species and unfolded proteins, or blood coagulation.
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Figure 4: Comparison of GRα enrichment results for ChIP-seq (using two locus definitions) and RNA-seq data from A549 cells. Enriched GO terms for differentially expressed transcripts and GRα binding following 100-nM DEX treatment show stronger overlap using the ‘nearest TSS’ locus definition than using the ‘≤1 kb from TSS’ definition. (a) Observed spline fit for GRα fits neither FET nor the binomial test assumption (orange); bar plot of the proportion of peaks at different distances from the TSS. See Figure 2(4a) and (b) for further details. (b) Using the ‘nearest TSS’ locus definition with GRα results in more overlapping terms with RNA-seq results than using ‘≤1 kb from TSS’. (c) Using the top 195 ranked terms for each test, FET and the binomial test have more overlap with ChIP-Enrich than with each other. (d)–(f) Comparison of –log10(P-values) for GO term enrichment tests based on ChIP-seq data (ChIP-Enrich) and/or RNA-seq (GOseq) data. (f) Many enriched RNA-seq terms would have been missed in the ChIP-seq data if only peaks in promoter regions were considered. GO terms enriched and FDR ≤ 0.05: for Y-axis test only (green); for X-axis test only (blue); for X- and Y-axis tests (orange); for neither (black). Vasculature development and related GO terms (triangles). The majority of GO terms that overlap between ‘≤1 kb from TSS’ and ‘nearest TSS’ are related to fatty acid metabolism, reactive oxygen species and unfolded proteins, or blood coagulation.

Mentions: We asked whether ChIP-Enrich could identify known and potential new biology of a well-characterized transcription factor, the GRα (47). Previous analysis identified 4392 peaks in A549 cells treated with 100-nM DEX (dexamethasone stimulates GR activity); only 4.7% of the peaks were within 1 kb of a TSS (Figure 4a). GO term enrichment testing yielded largely distinct subsets of significant (FDR ≤ 0.05) terms for ‘nearest TSS’ (195 terms) and ‘≤1 kb from TSS’ (72 terms) with only 16 overlapping terms (Figure 4b and d; Supplementary Table S5). The most significant terms (after collapsing similar terms) are shown in Table 3. Terms significant using one or both locus definitions include ‘epithelial cell differentiation’ (q-values: nearest TSS = 1.8 × 10−6; ≤1 kb from TSS = 1.0) and ‘negative regulation of blood coagulation’ (q-values: nearest TSS = 0.077; ≤1 kb from TSS = 3.19 × 10−7, with the related term ‘regulation of wound healing’ (q-values: nearest TSS = 0.0064; ≤1 kb from TSS = 0.0029). In addition, we observed ‘response to glucocorticoid stimulus’ (q-values: nearest TSS = 0.0035; ≤1 kb from TSS = 0.55) and ‘regulation of lipid metabolic process’ (q-values: nearest TSS = 0.0062; ≤1 kb from TSS = 0.74). GRα is known to be involved in the response to steroids and the activation of lipolysis (48,49), although knowledge of the transcriptional role of GRα in wound healing and blood coagulation is more limited. We also tested for enrichment using non-overlapping locus definitions for regions closer to a TSS (≤5 kb from TSS; 14.5% of peaks) and further from a TSS (>10 kb from TSS; 75.6% of peaks) and again identified largely distinct gene sets (Supplementary Figure S10).


ChIP-Enrich: gene set enrichment testing for ChIP-seq data.

Welch RP, Lee C, Imbriano PM, Patil S, Weymouth TE, Smith RA, Scott LJ, Sartor MA - Nucleic Acids Res. (2014)

Comparison of GRα enrichment results for ChIP-seq (using two locus definitions) and RNA-seq data from A549 cells. Enriched GO terms for differentially expressed transcripts and GRα binding following 100-nM DEX treatment show stronger overlap using the ‘nearest TSS’ locus definition than using the ‘≤1 kb from TSS’ definition. (a) Observed spline fit for GRα fits neither FET nor the binomial test assumption (orange); bar plot of the proportion of peaks at different distances from the TSS. See Figure 2(4a) and (b) for further details. (b) Using the ‘nearest TSS’ locus definition with GRα results in more overlapping terms with RNA-seq results than using ‘≤1 kb from TSS’. (c) Using the top 195 ranked terms for each test, FET and the binomial test have more overlap with ChIP-Enrich than with each other. (d)–(f) Comparison of –log10(P-values) for GO term enrichment tests based on ChIP-seq data (ChIP-Enrich) and/or RNA-seq (GOseq) data. (f) Many enriched RNA-seq terms would have been missed in the ChIP-seq data if only peaks in promoter regions were considered. GO terms enriched and FDR ≤ 0.05: for Y-axis test only (green); for X-axis test only (blue); for X- and Y-axis tests (orange); for neither (black). Vasculature development and related GO terms (triangles). The majority of GO terms that overlap between ‘≤1 kb from TSS’ and ‘nearest TSS’ are related to fatty acid metabolism, reactive oxygen species and unfolded proteins, or blood coagulation.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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Figure 4: Comparison of GRα enrichment results for ChIP-seq (using two locus definitions) and RNA-seq data from A549 cells. Enriched GO terms for differentially expressed transcripts and GRα binding following 100-nM DEX treatment show stronger overlap using the ‘nearest TSS’ locus definition than using the ‘≤1 kb from TSS’ definition. (a) Observed spline fit for GRα fits neither FET nor the binomial test assumption (orange); bar plot of the proportion of peaks at different distances from the TSS. See Figure 2(4a) and (b) for further details. (b) Using the ‘nearest TSS’ locus definition with GRα results in more overlapping terms with RNA-seq results than using ‘≤1 kb from TSS’. (c) Using the top 195 ranked terms for each test, FET and the binomial test have more overlap with ChIP-Enrich than with each other. (d)–(f) Comparison of –log10(P-values) for GO term enrichment tests based on ChIP-seq data (ChIP-Enrich) and/or RNA-seq (GOseq) data. (f) Many enriched RNA-seq terms would have been missed in the ChIP-seq data if only peaks in promoter regions were considered. GO terms enriched and FDR ≤ 0.05: for Y-axis test only (green); for X-axis test only (blue); for X- and Y-axis tests (orange); for neither (black). Vasculature development and related GO terms (triangles). The majority of GO terms that overlap between ‘≤1 kb from TSS’ and ‘nearest TSS’ are related to fatty acid metabolism, reactive oxygen species and unfolded proteins, or blood coagulation.
Mentions: We asked whether ChIP-Enrich could identify known and potential new biology of a well-characterized transcription factor, the GRα (47). Previous analysis identified 4392 peaks in A549 cells treated with 100-nM DEX (dexamethasone stimulates GR activity); only 4.7% of the peaks were within 1 kb of a TSS (Figure 4a). GO term enrichment testing yielded largely distinct subsets of significant (FDR ≤ 0.05) terms for ‘nearest TSS’ (195 terms) and ‘≤1 kb from TSS’ (72 terms) with only 16 overlapping terms (Figure 4b and d; Supplementary Table S5). The most significant terms (after collapsing similar terms) are shown in Table 3. Terms significant using one or both locus definitions include ‘epithelial cell differentiation’ (q-values: nearest TSS = 1.8 × 10−6; ≤1 kb from TSS = 1.0) and ‘negative regulation of blood coagulation’ (q-values: nearest TSS = 0.077; ≤1 kb from TSS = 3.19 × 10−7, with the related term ‘regulation of wound healing’ (q-values: nearest TSS = 0.0064; ≤1 kb from TSS = 0.0029). In addition, we observed ‘response to glucocorticoid stimulus’ (q-values: nearest TSS = 0.0035; ≤1 kb from TSS = 0.55) and ‘regulation of lipid metabolic process’ (q-values: nearest TSS = 0.0062; ≤1 kb from TSS = 0.74). GRα is known to be involved in the response to steroids and the activation of lipolysis (48,49), although knowledge of the transcriptional role of GRα in wound healing and blood coagulation is more limited. We also tested for enrichment using non-overlapping locus definitions for regions closer to a TSS (≤5 kb from TSS; 14.5% of peaks) and further from a TSS (>10 kb from TSS; 75.6% of peaks) and again identified largely distinct gene sets (Supplementary Figure S10).

Bottom Line: Adjustment for gene locus length is necessary because it is often positively associated with the presence of one or more peaks and because many biologically defined gene sets have an excess of genes with longer or shorter gene locus lengths.We identify DNA-binding proteins, including CTCF, JunD and glucocorticoid receptor α (GRα), that show different enrichment patterns for peaks closer to versus further from transcription start sites.We also identify known and potential new biological functions of GRα.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Biostatistics Department, University of Michigan, Ann Arbor, MI 48109, USA.

Show MeSH
Related in: MedlinePlus