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A predictive model of the oxygen and heme regulatory network in yeast.

Kundaje A, Xin X, Lan C, Lianoglou S, Zhou M, Zhang L, Leslie C - PLoS Comput. Biol. (2008)

Bottom Line: We used a novel margin-based score to extract significant condition-specific regulators and assemble a global map of the oxygen sensing and regulatory network.In each case, deletion of the candidate regulator resulted in the predicted effect on promoter activity, confirming that several novel regulators identified by MEDUSA are indeed involved in oxygen regulation.Supplemental data are included.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Columbia University, New York, New York, United States of America.

ABSTRACT
Deciphering gene regulatory mechanisms through the analysis of high-throughput expression data is a challenging computational problem. Previous computational studies have used large expression datasets in order to resolve fine patterns of coexpression, producing clusters or modules of potentially coregulated genes. These methods typically examine promoter sequence information, such as DNA motifs or transcription factor occupancy data, in a separate step after clustering. We needed an alternative and more integrative approach to study the oxygen regulatory network in Saccharomyces cerevisiae using a small dataset of perturbation experiments. Mechanisms of oxygen sensing and regulation underlie many physiological and pathological processes, and only a handful of oxygen regulators have been identified in previous studies. We used a new machine learning algorithm called MEDUSA to uncover detailed information about the oxygen regulatory network using genome-wide expression changes in response to perturbations in the levels of oxygen, heme, Hap1, and Co2+. MEDUSA integrates mRNA expression, promoter sequence, and ChIP-chip occupancy data to learn a model that accurately predicts the differential expression of target genes in held-out data. We used a novel margin-based score to extract significant condition-specific regulators and assemble a global map of the oxygen sensing and regulatory network. This network includes both known oxygen and heme regulators, such as Hap1, Mga2, Hap4, and Upc2, as well as many new candidate regulators. MEDUSA also identified many DNA motifs that are consistent with previous experimentally identified transcription factor binding sites. Because MEDUSA's regulatory program associates regulators to target genes through their promoter sequences, we directly tested the predicted regulators for OLE1, a gene specifically induced under hypoxia, by experimental analysis of the activity of its promoter. In each case, deletion of the candidate regulator resulted in the predicted effect on promoter activity, confirming that several novel regulators identified by MEDUSA are indeed involved in oxygen regulation. MEDUSA can reveal important information from a small dataset and generate testable hypotheses for further experimental analysis. Supplemental data are included.

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Venn diagrams showing the statistically significant, high ranking regulators mediating the regulation of oxygen-regulated, heme-regulated, and Co2+-inducible genes in HAP1 and Δhap1 cells.(A) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 and Δhap1 cells, and heme-suppressed genes. (B) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 and Δhap1 cells, and Co2+-inducible genes. (C) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 cells at 1.5 or 6 hours after shifting to anaerobic growth conditions. (D) A Venn diagram illustrating the regulators involved in controlling hypoxically suppressed (oxygen-induced) genes in HAP1 cells at 1.5 or 6 hours after shifting to anaerobic growth conditions.
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pcbi-1000224-g005: Venn diagrams showing the statistically significant, high ranking regulators mediating the regulation of oxygen-regulated, heme-regulated, and Co2+-inducible genes in HAP1 and Δhap1 cells.(A) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 and Δhap1 cells, and heme-suppressed genes. (B) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 and Δhap1 cells, and Co2+-inducible genes. (C) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 cells at 1.5 or 6 hours after shifting to anaerobic growth conditions. (D) A Venn diagram illustrating the regulators involved in controlling hypoxically suppressed (oxygen-induced) genes in HAP1 cells at 1.5 or 6 hours after shifting to anaerobic growth conditions.

Mentions: We also identified and compared statistically significant regulators that may mediate the regulation of hypoxically induced genes in cells bearing the Hap1 expression plasmid (HAP1) and the empty vector (Δhap1) and those that mediate heme deficiency-induced (heme-suppressed) genes (Figure 5A and Figure S3). Likewise, we identified and compared regulators that may mediate the regulation of Co2+-inducible genes with those mediating the regulation of hypoxically induced genes (Figure 5B and Figure S4). The comparison of these regulators mediating oxygen regulation, heme regulation, and Co2+-inducible regulation provides several important insights into the regulatory network mediating oxygen sensing and regulation. First, more than half of the MEDUSA-identified regulators mediating heme regulation may also be involved in mediating oxygen regulation both in HAP1 cells (12 out of 20 regulators) and in Δhap1 cells (15 out of 20 regulators) (Figure 4A). Many regulators predicted to be involved in heme suppression of target genes may also be involved in oxygen induction in wild type HAP1 cells (13 out of 18) and in Δhap1 cells (11 out of 18) (Figure 5A). These results are consistent with the previous idea that heme serves as a secondary messenger of oxygen and plays a major role in mediating oxygen regulation of target genes. Second, Hap1 plays a major role in oxygen regulation. In the absence of Hap1, the number of regulators mediating oxygen regulation may be significantly increased both for oxygen-induced genes (Figure 4A) and hypoxically induced genes (Figure 5A).


A predictive model of the oxygen and heme regulatory network in yeast.

Kundaje A, Xin X, Lan C, Lianoglou S, Zhou M, Zhang L, Leslie C - PLoS Comput. Biol. (2008)

Venn diagrams showing the statistically significant, high ranking regulators mediating the regulation of oxygen-regulated, heme-regulated, and Co2+-inducible genes in HAP1 and Δhap1 cells.(A) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 and Δhap1 cells, and heme-suppressed genes. (B) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 and Δhap1 cells, and Co2+-inducible genes. (C) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 cells at 1.5 or 6 hours after shifting to anaerobic growth conditions. (D) A Venn diagram illustrating the regulators involved in controlling hypoxically suppressed (oxygen-induced) genes in HAP1 cells at 1.5 or 6 hours after shifting to anaerobic growth conditions.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2573020&req=5

pcbi-1000224-g005: Venn diagrams showing the statistically significant, high ranking regulators mediating the regulation of oxygen-regulated, heme-regulated, and Co2+-inducible genes in HAP1 and Δhap1 cells.(A) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 and Δhap1 cells, and heme-suppressed genes. (B) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 and Δhap1 cells, and Co2+-inducible genes. (C) A Venn diagram illustrating the regulators involved in controlling hypoxically induced (oxygen-suppressed) genes in HAP1 cells at 1.5 or 6 hours after shifting to anaerobic growth conditions. (D) A Venn diagram illustrating the regulators involved in controlling hypoxically suppressed (oxygen-induced) genes in HAP1 cells at 1.5 or 6 hours after shifting to anaerobic growth conditions.
Mentions: We also identified and compared statistically significant regulators that may mediate the regulation of hypoxically induced genes in cells bearing the Hap1 expression plasmid (HAP1) and the empty vector (Δhap1) and those that mediate heme deficiency-induced (heme-suppressed) genes (Figure 5A and Figure S3). Likewise, we identified and compared regulators that may mediate the regulation of Co2+-inducible genes with those mediating the regulation of hypoxically induced genes (Figure 5B and Figure S4). The comparison of these regulators mediating oxygen regulation, heme regulation, and Co2+-inducible regulation provides several important insights into the regulatory network mediating oxygen sensing and regulation. First, more than half of the MEDUSA-identified regulators mediating heme regulation may also be involved in mediating oxygen regulation both in HAP1 cells (12 out of 20 regulators) and in Δhap1 cells (15 out of 20 regulators) (Figure 4A). Many regulators predicted to be involved in heme suppression of target genes may also be involved in oxygen induction in wild type HAP1 cells (13 out of 18) and in Δhap1 cells (11 out of 18) (Figure 5A). These results are consistent with the previous idea that heme serves as a secondary messenger of oxygen and plays a major role in mediating oxygen regulation of target genes. Second, Hap1 plays a major role in oxygen regulation. In the absence of Hap1, the number of regulators mediating oxygen regulation may be significantly increased both for oxygen-induced genes (Figure 4A) and hypoxically induced genes (Figure 5A).

Bottom Line: We used a novel margin-based score to extract significant condition-specific regulators and assemble a global map of the oxygen sensing and regulatory network.In each case, deletion of the candidate regulator resulted in the predicted effect on promoter activity, confirming that several novel regulators identified by MEDUSA are indeed involved in oxygen regulation.Supplemental data are included.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Columbia University, New York, New York, United States of America.

ABSTRACT
Deciphering gene regulatory mechanisms through the analysis of high-throughput expression data is a challenging computational problem. Previous computational studies have used large expression datasets in order to resolve fine patterns of coexpression, producing clusters or modules of potentially coregulated genes. These methods typically examine promoter sequence information, such as DNA motifs or transcription factor occupancy data, in a separate step after clustering. We needed an alternative and more integrative approach to study the oxygen regulatory network in Saccharomyces cerevisiae using a small dataset of perturbation experiments. Mechanisms of oxygen sensing and regulation underlie many physiological and pathological processes, and only a handful of oxygen regulators have been identified in previous studies. We used a new machine learning algorithm called MEDUSA to uncover detailed information about the oxygen regulatory network using genome-wide expression changes in response to perturbations in the levels of oxygen, heme, Hap1, and Co2+. MEDUSA integrates mRNA expression, promoter sequence, and ChIP-chip occupancy data to learn a model that accurately predicts the differential expression of target genes in held-out data. We used a novel margin-based score to extract significant condition-specific regulators and assemble a global map of the oxygen sensing and regulatory network. This network includes both known oxygen and heme regulators, such as Hap1, Mga2, Hap4, and Upc2, as well as many new candidate regulators. MEDUSA also identified many DNA motifs that are consistent with previous experimentally identified transcription factor binding sites. Because MEDUSA's regulatory program associates regulators to target genes through their promoter sequences, we directly tested the predicted regulators for OLE1, a gene specifically induced under hypoxia, by experimental analysis of the activity of its promoter. In each case, deletion of the candidate regulator resulted in the predicted effect on promoter activity, confirming that several novel regulators identified by MEDUSA are indeed involved in oxygen regulation. MEDUSA can reveal important information from a small dataset and generate testable hypotheses for further experimental analysis. Supplemental data are included.

Show MeSH
Related in: MedlinePlus