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POEM: Identifying Joint Additive Effects on Regulatory Circuits.

Botzman M, Nachshon A, Brodt A, Gat-Viks I - Front Genet (2016)

Bottom Line: POEM is specifically designed to achieve high performance in the case of additive joint effects.Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network.These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Research and Immunology, The George S. Wise Faculty of Life Sciences, Tel Aviv University Tel Aviv, Israel.

ABSTRACT

Motivation: Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such "modularization" approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects.

Results: Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

Availability: The software described in this article is available at csgi.tau.ac.il/POEM/.

No MeSH data available.


Related in: MedlinePlus

An integrated model of the TLR signaling pathway modulated by the multifurcating motif of poeModules M14-M18. Shown is the TLR/RLR signaling pathways in response to the poly I:C, PAM and LPS pathogenic-like ligands. Transcriptional regulation is shown as dashed lines. Each associated trait in poeModules M14-M18 is accompanied with the gene name, the relevant stimulus (*poly IC;†PAM), and a rectangle that is color coded with its primary (left) and secondary (right) underlying eQTLs. The plot suggests the existence of a single general (secondary) eQTL that acts pleiotropically on the TLR signaling network while cooperating with several specific (primary) eQTLs to control the expression of particular genes within this network.
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Figure 5: An integrated model of the TLR signaling pathway modulated by the multifurcating motif of poeModules M14-M18. Shown is the TLR/RLR signaling pathways in response to the poly I:C, PAM and LPS pathogenic-like ligands. Transcriptional regulation is shown as dashed lines. Each associated trait in poeModules M14-M18 is accompanied with the gene name, the relevant stimulus (*poly IC;†PAM), and a rectangle that is color coded with its primary (left) and secondary (right) underlying eQTLs. The plot suggests the existence of a single general (secondary) eQTL that acts pleiotropically on the TLR signaling network while cooperating with several specific (primary) eQTLs to control the expression of particular genes within this network.

Mentions: Next, we demonstrate the multifurcating structure of poeModules M14−M18 (Figure 4B), which relate to five distinct primary eQTLs and share the same secondary eQTL in chr13:94–97 Mbp (Supplementary Table 4). The structure consists of 53 traits that are significantly enriched with Toll-like receptor (TLR) signaling genes (P < 0.08, Fisher's exact test). To build a regulatory model of this network, we focused on the particular anti-viral and inflammatory TLR signaling pathways that are triggered by the pathogenic stimulations in our dataset: poly I:C, PAM, and LPS (Figure 5). We included all downstream genes that are directly bound by the key transcription factors in this network (see Section Materials and Methods; Supplementary Table 5). We further annotated each trait (from poeModules M14-M18) in this network with its primary and secondary eQTLs and with its corresponding stimulus. We find that the same signaling pathway is enriched with M14-M18 genes (31 out of 53 genes, P < 3 × 10−6, Fisher's exact test). Interestingly, whereas a pleiotropic secondary eQTL has an effect on all 31 genes, a variety of primary effects are more specific to particular subsets of genes. For example, three components of the NFκB complex, which plays a key role in TLR signaling, have the same secondary eQTL with distinct primary eQTLs (Nfκbiz and Rel in M14; Nfκb1 in M15). This observation highlights the central role of combinatorial regulation in molecular processes, and emphasizes the importance of pairwise additive effects for interrogating regulatory circuits.


POEM: Identifying Joint Additive Effects on Regulatory Circuits.

Botzman M, Nachshon A, Brodt A, Gat-Viks I - Front Genet (2016)

An integrated model of the TLR signaling pathway modulated by the multifurcating motif of poeModules M14-M18. Shown is the TLR/RLR signaling pathways in response to the poly I:C, PAM and LPS pathogenic-like ligands. Transcriptional regulation is shown as dashed lines. Each associated trait in poeModules M14-M18 is accompanied with the gene name, the relevant stimulus (*poly IC;†PAM), and a rectangle that is color coded with its primary (left) and secondary (right) underlying eQTLs. The plot suggests the existence of a single general (secondary) eQTL that acts pleiotropically on the TLR signaling network while cooperating with several specific (primary) eQTLs to control the expression of particular genes within this network.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835676&req=5

Figure 5: An integrated model of the TLR signaling pathway modulated by the multifurcating motif of poeModules M14-M18. Shown is the TLR/RLR signaling pathways in response to the poly I:C, PAM and LPS pathogenic-like ligands. Transcriptional regulation is shown as dashed lines. Each associated trait in poeModules M14-M18 is accompanied with the gene name, the relevant stimulus (*poly IC;†PAM), and a rectangle that is color coded with its primary (left) and secondary (right) underlying eQTLs. The plot suggests the existence of a single general (secondary) eQTL that acts pleiotropically on the TLR signaling network while cooperating with several specific (primary) eQTLs to control the expression of particular genes within this network.
Mentions: Next, we demonstrate the multifurcating structure of poeModules M14−M18 (Figure 4B), which relate to five distinct primary eQTLs and share the same secondary eQTL in chr13:94–97 Mbp (Supplementary Table 4). The structure consists of 53 traits that are significantly enriched with Toll-like receptor (TLR) signaling genes (P < 0.08, Fisher's exact test). To build a regulatory model of this network, we focused on the particular anti-viral and inflammatory TLR signaling pathways that are triggered by the pathogenic stimulations in our dataset: poly I:C, PAM, and LPS (Figure 5). We included all downstream genes that are directly bound by the key transcription factors in this network (see Section Materials and Methods; Supplementary Table 5). We further annotated each trait (from poeModules M14-M18) in this network with its primary and secondary eQTLs and with its corresponding stimulus. We find that the same signaling pathway is enriched with M14-M18 genes (31 out of 53 genes, P < 3 × 10−6, Fisher's exact test). Interestingly, whereas a pleiotropic secondary eQTL has an effect on all 31 genes, a variety of primary effects are more specific to particular subsets of genes. For example, three components of the NFκB complex, which plays a key role in TLR signaling, have the same secondary eQTL with distinct primary eQTLs (Nfκbiz and Rel in M14; Nfκb1 in M15). This observation highlights the central role of combinatorial regulation in molecular processes, and emphasizes the importance of pairwise additive effects for interrogating regulatory circuits.

Bottom Line: POEM is specifically designed to achieve high performance in the case of additive joint effects.Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network.These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Research and Immunology, The George S. Wise Faculty of Life Sciences, Tel Aviv University Tel Aviv, Israel.

ABSTRACT

Motivation: Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such "modularization" approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects.

Results: Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

Availability: The software described in this article is available at csgi.tau.ac.il/POEM/.

No MeSH data available.


Related in: MedlinePlus