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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.


POEM reveals a widespread trans-acting, non-epistatic pairwise effects in murine dendritic cells. (A) Shown are the number of identified groups (left) and the number of expression traits within them (right, y-axis) for real (black) and permuted (white) data across different types of groups (x-axis). Based on the permutation test, POEM yielded an empirical false discovery rate (FDR) < 0.006 for predicted poeModules and FDR < 0.0015 for the number of expression traits within the predicted poeModule. (B) Shown is the number of identified expression traits within the poeModules (y-axis), which are associated by cis-cis-acting (left), cis-trans-acting (middle), and trans-trans-acting (right) eQTL pairs. Significant and nonsignificant interaction terms (FDR < 0.01) are marked in black and white, respectively. *Significant difference
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Figure 3: POEM reveals a widespread trans-acting, non-epistatic pairwise effects in murine dendritic cells. (A) Shown are the number of identified groups (left) and the number of expression traits within them (right, y-axis) for real (black) and permuted (white) data across different types of groups (x-axis). Based on the permutation test, POEM yielded an empirical false discovery rate (FDR) < 0.006 for predicted poeModules and FDR < 0.0015 for the number of expression traits within the predicted poeModule. (B) Shown is the number of identified expression traits within the poeModules (y-axis), which are associated by cis-cis-acting (left), cis-trans-acting (middle), and trans-trans-acting (right) eQTL pairs. Significant and nonsignificant interaction terms (FDR < 0.01) are marked in black and white, respectively. *Significant difference

Mentions: Here we focus on the poeModules that were generated after six iterative steps (k = 6). To assess the empirical false discovery rate (FDR) generated by POEM, we repeated the analysis 100 times with permuted gene-expression data generated by randomly shuffling the labels of strains (Section Materials and Methods). Using the permuted data, we found an average of 0.2 poeModules, indicating significant poeModules at FDR < 0.006. Similar results were obtained when we counted the numbers of identified traits within the poeModules (FDR < 0.0015; Figure 3A). This is in contrast to the relatively large number of primary and secondary groups generated using permuted data (leading to FDR < 0.28 and 0.26 for primary and secondary groups, respectively; Figure 3A). These results are in agreement with our selection of a permissive InVamod cutoff (P < 0.01) for the generation of intermediate groups, while using a stringent overlap cutoff (P < 10−3–10−6) for the generation of the final poeModules (see Section Materials and Methods). Taken together, although the intermediate groups may consist of false discoveries, POEM successfully controls the FDR in its final poeModules output.


POEM: Identifying Joint Additive Effects on Regulatory Circuits.

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

POEM reveals a widespread trans-acting, non-epistatic pairwise effects in murine dendritic cells. (A) Shown are the number of identified groups (left) and the number of expression traits within them (right, y-axis) for real (black) and permuted (white) data across different types of groups (x-axis). Based on the permutation test, POEM yielded an empirical false discovery rate (FDR) < 0.006 for predicted poeModules and FDR < 0.0015 for the number of expression traits within the predicted poeModule. (B) Shown is the number of identified expression traits within the poeModules (y-axis), which are associated by cis-cis-acting (left), cis-trans-acting (middle), and trans-trans-acting (right) eQTL pairs. Significant and nonsignificant interaction terms (FDR < 0.01) are marked in black and white, respectively. *Significant difference
© Copyright Policy
Related In: Results  -  Collection

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

Figure 3: POEM reveals a widespread trans-acting, non-epistatic pairwise effects in murine dendritic cells. (A) Shown are the number of identified groups (left) and the number of expression traits within them (right, y-axis) for real (black) and permuted (white) data across different types of groups (x-axis). Based on the permutation test, POEM yielded an empirical false discovery rate (FDR) < 0.006 for predicted poeModules and FDR < 0.0015 for the number of expression traits within the predicted poeModule. (B) Shown is the number of identified expression traits within the poeModules (y-axis), which are associated by cis-cis-acting (left), cis-trans-acting (middle), and trans-trans-acting (right) eQTL pairs. Significant and nonsignificant interaction terms (FDR < 0.01) are marked in black and white, respectively. *Significant difference
Mentions: Here we focus on the poeModules that were generated after six iterative steps (k = 6). To assess the empirical false discovery rate (FDR) generated by POEM, we repeated the analysis 100 times with permuted gene-expression data generated by randomly shuffling the labels of strains (Section Materials and Methods). Using the permuted data, we found an average of 0.2 poeModules, indicating significant poeModules at FDR < 0.006. Similar results were obtained when we counted the numbers of identified traits within the poeModules (FDR < 0.0015; Figure 3A). This is in contrast to the relatively large number of primary and secondary groups generated using permuted data (leading to FDR < 0.28 and 0.26 for primary and secondary groups, respectively; Figure 3A). These results are in agreement with our selection of a permissive InVamod cutoff (P < 0.01) for the generation of intermediate groups, while using a stringent overlap cutoff (P < 10−3–10−6) for the generation of the final poeModules (see Section Materials and Methods). Taken together, although the intermediate groups may consist of false discoveries, POEM successfully controls the FDR in its final poeModules output.

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.