Genome-wide association of hypoxia-inducible factor (HIF)-1alpha and HIF-2alpha DNA binding with expression profiling of hypoxia-inducible transcripts

Abstract

Hypoxia-inducible factor (HIF) controls an extensive range of adaptive responses to hypoxia. To better understand this transcriptional cascade we performed genome-wide chromatin immunoprecipitation using antibodies to two major HIF-alpha subunits, and correlated the results with genome-wide transcript profiling. Within a tiled promoter array we identified 546 and 143 sequences that bound, respectively, to HIF-1alpha or HIF-2alpha at high stringency. Analysis of these sequences confirmed an identical core binding motif for HIF-1alpha and HIF-2alpha (RCGTG) but demonstrated that binding to this motif was highly selective, with binding enriched at distinct regions both upstream and downstream of the transcriptional start. Comparison of HIF-promoter binding data with bidirectional HIF-dependent changes in transcript expression indicated that whereas a substantial proportion of positive responses (>20% across all significantly regulated genes) are direct, HIF-dependent gene suppression is almost entirely indirect. Comparison of HIF-1alpha- versus HIF-2alpha-binding sites revealed that whereas some loci bound HIF-1alpha in isolation, many bound both isoforms with similar affinity. Despite high-affinity binding to multiple promoters, HIF-2alpha contributed to few, if any, of the transcriptional responses to acute hypoxia at these loci. Given emerging evidence for biologically distinct functions of HIF-1alpha versus HIF-2alpha understanding the mechanisms restricting HIF-2alpha activity will be of interest.

FIGURE 1.

Functional classification of HIF-binding gene loci. The highest stringency (MA score >4) HIF-1α and HIF-2α immunoprecipitating gene loci were stratified by gene ontology using the DAVID Bioinformatics Resource. The number of immunoprecipitating gene loci in each functional category is displayed.

FIGURE 2.

Distribution of HIF-1α- and HIF-2α-binding sites. A, distribution of high stringency (MA score >4) HIF-1α- and HIF-2α-binding sites referred to the nearest transcriptional start site. Number of HIF-binding peaks expressed per 500-bp bin is shown. B, frequency distribution of RCGTG motifs at gene loci that bind HIF-1α or HIF-2α. The number of RCGTG motifs expressed per 500-bp bin is shown.

FIGURE 3.

Intersection between HIF-1α- and HIF-2α-binding gene loci. A, gene loci that bound either HIF-1α or HIF-2α or both isoforms with a Z-score >4. B, defining HIF-1α capture with a Z-score of 3 encompasses almost all HIF-2α binding loci. C, defining HIF-2α capture with a Z-score of 3 excludes almost one-third of HIF-1α binding loci.

FIGURE 4.

Capture by HIF-1α and HIF-2α at common binding sites. Using a Z-score of 2 for each immunoprecipitation identified 992 genomic regions that bound both HIF-1α and HIF-2α. For each of these sequences the maximum enrichment by HIF-2α immunoprecipitation was plotted against that for the HIF-1α immunoprecipitation. More points lie above than below the line of identity indicating greater average enrichment by HIF-2α immunoprecipitation at these common binding loci.

FIGURE 5.

Relationship between amplitude and direction of regulation and chromatin immunoprecipitation by anti-HIF-1α or HIF-2α. Gene loci were assigned to functional groups according to fold up- or down-regulation by DMOG in the Affymetrix expression array. The proportion of gene loci captured by either of the anti-HIF-α immunoprecipitations is given for each of the functional group.