Limits...
Comparative analysis of regulatory information and circuits across distant species.

Boyle AP, Araya CL, Brdlik C, Cayting P, Cheng C, Cheng Y, Gardner K, Hillier LW, Janette J, Jiang L, Kasper D, Kawli T, Kheradpour P, Kundaje A, Li JJ, Ma L, Niu W, Rehm EJ, Rozowsky J, Slattery M, Spokony R, Terrell R, Vafeados D, Wang D, Weisdepp P, Wu YC, Xie D, Yan KK, Feingold EA, Good PJ, Pazin MJ, Huang H, Bickel PJ, Brenner SE, Reinke V, Waterston RH, Gerstein M, White KP, Kellis M, Snyder M - Nature (2014)

Bottom Line: Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time.We find that structural properties of regulatory networks are remarkably conserved and that orthologous regulatory factor families recognize similar binding motifs in vivo and show some similar co-associations.Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA [2].

ABSTRACT
Despite the large evolutionary distances between metazoan species, they can show remarkable commonalities in their biology, and this has helped to establish fly and worm as model organisms for human biology. Although studies of individual elements and factors have explored similarities in gene regulation, a large-scale comparative analysis of basic principles of transcriptional regulatory features is lacking. Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time. We find that structural properties of regulatory networks are remarkably conserved and that orthologous regulatory factor families recognize similar binding motifs in vivo and show some similar co-associations. Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections. The comparative maps of regulatory circuitry provided here will drive an improved understanding of the regulatory underpinnings of model organism biology and how these relate to human biology, development and disease.

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Networks(a) Statistics of the transcription regulatory networks in human, worm, fly and their hierarchical organization. (b) An example of the hierarchical network for worm. (c) Network motif enrichment. The human, worm and fly networks are mostly consistent in terms of motif enrichment. The motif feed-forward loop is the most enriched motif in all three networks. (d) Different transcription factors have different tendencies to appear as top, middle and bottom regulators in a FFL. The lists of human, worm, fly TFs with corresponding tendencies are displayed.
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Figure 3: Networks(a) Statistics of the transcription regulatory networks in human, worm, fly and their hierarchical organization. (b) An example of the hierarchical network for worm. (c) Network motif enrichment. The human, worm and fly networks are mostly consistent in terms of motif enrichment. The motif feed-forward loop is the most enriched motif in all three networks. (d) Different transcription factors have different tendencies to appear as top, middle and bottom regulators in a FFL. The lists of human, worm, fly TFs with corresponding tendencies are displayed.

Mentions: We next constructed regulatory networks in each species by predicting gene targets of each RF using TIP23 and used simulated annealing to reveal the organization of RFs in three layers of master-regulators, intermediate regulators, and low-level regulators (Fig. 3a–b). The algorithm found only 7% of RFs at the top layer of the network in fly and 13% in worm, compared to 33% in human. We also found that more edges are upward flowing in human (30%) than worm and fly (22% and 7%). This suggests differences in the global network organization with more extensive feedback and a higher number of master regulators in human.


Comparative analysis of regulatory information and circuits across distant species.

Boyle AP, Araya CL, Brdlik C, Cayting P, Cheng C, Cheng Y, Gardner K, Hillier LW, Janette J, Jiang L, Kasper D, Kawli T, Kheradpour P, Kundaje A, Li JJ, Ma L, Niu W, Rehm EJ, Rozowsky J, Slattery M, Spokony R, Terrell R, Vafeados D, Wang D, Weisdepp P, Wu YC, Xie D, Yan KK, Feingold EA, Good PJ, Pazin MJ, Huang H, Bickel PJ, Brenner SE, Reinke V, Waterston RH, Gerstein M, White KP, Kellis M, Snyder M - Nature (2014)

Networks(a) Statistics of the transcription regulatory networks in human, worm, fly and their hierarchical organization. (b) An example of the hierarchical network for worm. (c) Network motif enrichment. The human, worm and fly networks are mostly consistent in terms of motif enrichment. The motif feed-forward loop is the most enriched motif in all three networks. (d) Different transcription factors have different tendencies to appear as top, middle and bottom regulators in a FFL. The lists of human, worm, fly TFs with corresponding tendencies are displayed.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4336544&req=5

Figure 3: Networks(a) Statistics of the transcription regulatory networks in human, worm, fly and their hierarchical organization. (b) An example of the hierarchical network for worm. (c) Network motif enrichment. The human, worm and fly networks are mostly consistent in terms of motif enrichment. The motif feed-forward loop is the most enriched motif in all three networks. (d) Different transcription factors have different tendencies to appear as top, middle and bottom regulators in a FFL. The lists of human, worm, fly TFs with corresponding tendencies are displayed.
Mentions: We next constructed regulatory networks in each species by predicting gene targets of each RF using TIP23 and used simulated annealing to reveal the organization of RFs in three layers of master-regulators, intermediate regulators, and low-level regulators (Fig. 3a–b). The algorithm found only 7% of RFs at the top layer of the network in fly and 13% in worm, compared to 33% in human. We also found that more edges are upward flowing in human (30%) than worm and fly (22% and 7%). This suggests differences in the global network organization with more extensive feedback and a higher number of master regulators in human.

Bottom Line: Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time.We find that structural properties of regulatory networks are remarkably conserved and that orthologous regulatory factor families recognize similar binding motifs in vivo and show some similar co-associations.Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA [2].

ABSTRACT
Despite the large evolutionary distances between metazoan species, they can show remarkable commonalities in their biology, and this has helped to establish fly and worm as model organisms for human biology. Although studies of individual elements and factors have explored similarities in gene regulation, a large-scale comparative analysis of basic principles of transcriptional regulatory features is lacking. Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time. We find that structural properties of regulatory networks are remarkably conserved and that orthologous regulatory factor families recognize similar binding motifs in vivo and show some similar co-associations. Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections. The comparative maps of regulatory circuitry provided here will drive an improved understanding of the regulatory underpinnings of model organism biology and how these relate to human biology, development and disease.

Show MeSH