Editing Gene regulatory network (section)

== Structure and evolution ==

=== Global feature ===
Gene regulatory networks are generally thought to be made up of a few highly connected [[node (graph theory)|node]]s ([[network topology|hubs]]) and many poorly connected nodes nested within a hierarchical regulatory regime. Thus gene regulatory networks approximate a [[Network topology|hierarchical]] [[Scale-free network|scale free network]] topology.<ref name=":0">{{cite journal | vauthors = Barabási AL, Oltvai ZN | title = Network biology: understanding the cell's functional organization | journal = Nature Reviews. Genetics | volume = 5 | issue = 2 | pages = 101–113 | date = February 2004 | pmid = 14735121 | doi = 10.1038/nrg1272 | s2cid = 10950726 }}</ref> This is consistent with the view that most genes have limited [[pleiotropy]] and operate within regulatory [[Modularity (biology)|modules]].<ref>{{cite journal | vauthors = Wagner GP, Zhang J | title = The pleiotropic structure of the genotype-phenotype map: the evolvability of complex organisms | journal = Nature Reviews. Genetics | volume = 12 | issue = 3 | pages = 204–213 | date = March 2011 | pmid = 21331091 | doi = 10.1038/nrg2949 | s2cid = 8612268 }}</ref> This structure is thought to evolve due to the [[preferential attachment]] of [[Gene duplication|duplicated genes]] to more highly connected genes.<ref name=":0" /> Recent work has also shown that natural selection tends to favor networks with sparse connectivity.<ref>{{cite journal | vauthors = Leclerc RD | title = Survival of the sparsest: robust gene networks are parsimonious | journal = Molecular Systems Biology | volume = 4 | issue = 1 | pages = 213 | date = August 2008 | pmid = 18682703 | pmc = 2538912 | doi = 10.1038/msb.2008.52 }}</ref>

There are primarily two ways that networks can evolve, both of which can occur simultaneously. The first is that network topology can be changed by the addition or subtraction of nodes (genes) or parts of the network (modules) may be expressed in different contexts. The'' [[Drosophila]]'' [[Hippo signaling pathway]] provides a good example. The Hippo signaling pathway controls both mitotic growth and post-mitotic cellular differentiation.<ref name=":1">{{cite journal | vauthors = Jukam D, Xie B, Rister J, Terrell D, Charlton-Perkins M, Pistillo D, Gebelein B, Desplan C, Cook T | display-authors = 6 | title = Opposite feedbacks in the Hippo pathway for growth control and neural fate | journal = Science | volume = 342 | issue = 6155 | pages = 1238016 | date = October 2013 | pmid = 23989952 | pmc = 3796000 | doi = 10.1126/science.1238016 }}</ref> Recently it was found that the network the Hippo signaling pathway operates in differs between these two functions which in turn changes the behavior of the Hippo signaling pathway. This suggests that the Hippo signaling pathway operates as a conserved regulatory module that can be used for multiple functions depending on context.<ref name=":1" /> Thus, changing network topology can allow a conserved module to serve multiple functions and alter the final output of the network. The second way networks can evolve is by changing the strength of interactions between nodes, such as how strongly a transcription factor may bind to a [[cis-regulatory element]]. Such variation in strength of network edges has been shown to underlie between species variation in vulva cell fate patterning of ''[[Caenorhabditis]]'' worms.<ref>{{cite journal | vauthors = Hoyos E, Kim K, Milloz J, Barkoulas M, Pénigault JB, Munro E, Félix MA | title = Quantitative variation in autocrine signaling and pathway crosstalk in the Caenorhabditis vulval network | journal = Current Biology | volume = 21 | issue = 7 | pages = 527–538 | date = April 2011 | pmid = 21458263 | pmc = 3084603 | doi = 10.1016/j.cub.2011.02.040 | bibcode = 2011CBio...21..527H }}</ref>

=== Local feature ===
[[File:Feed-forward motif.GIF|thumb|Feed-forward loop]]

Another widely cited characteristic of gene regulatory network is their abundance of certain repetitive sub-networks known as [[network motif]]s. Network motifs can be regarded as repetitive topological patterns when dividing a big network into small blocks. Previous analysis found several types of motifs that appeared more often in gene regulatory networks than in randomly generated networks.<ref>{{cite journal | vauthors = Shen-Orr SS, Milo R, Mangan S, Alon U | title = Network motifs in the transcriptional regulation network of Escherichia coli | journal = Nature Genetics | volume = 31 | issue = 1 | pages = 64–68 | date = May 2002 | pmid = 11967538 | doi = 10.1038/ng881 | s2cid = 2180121 | doi-access = free }}</ref><ref>{{cite journal | vauthors = Lee TI, Rinaldi NJ, Robert F, Odom DT, Bar-Joseph Z, Gerber GK, Hannett NM, Harbison CT, Thompson CM, Simon I, Zeitlinger J, Jennings EG, Murray HL, Gordon DB, Ren B, Wyrick JJ, Tagne JB, Volkert TL, Fraenkel E, Gifford DK, Young RA | display-authors = 6 | title = Transcriptional regulatory networks in Saccharomyces cerevisiae | journal = Science | volume = 298 | issue = 5594 | pages = 799–804 | date = October 2002 | pmid = 12399584 | doi = 10.1126/science.1075090 | s2cid = 4841222 | bibcode = 2002Sci...298..799L }}</ref><ref name=":2">{{cite journal | vauthors = 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 | display-authors = 6 | title = Comparative analysis of regulatory information and circuits across distant species | journal = Nature | volume = 512 | issue = 7515 | pages = 453–456 | date = August 2014 | pmid = 25164757 | pmc = 4336544 | doi = 10.1038/nature13668 | bibcode = 2014Natur.512..453B }}</ref> As an example, one such motif is called feed-forward loops, which consist of three nodes. This motif is the most abundant among all possible motifs made up of three nodes, as is shown in the gene regulatory networks of fly, nematode, and human.<ref name=":2" />

The enriched motifs have been proposed to follow [[convergent evolution]], suggesting they are "optimal designs" for certain regulatory purposes.<ref>{{cite journal | vauthors = Conant GC, Wagner A | title = Convergent evolution of gene circuits | journal = Nature Genetics | volume = 34 | issue = 3 | pages = 264–266 | date = July 2003 | pmid = 12819781 | doi = 10.1038/ng1181 | s2cid = 959172 }}</ref> For example, modeling shows that feed-forward loops are able to coordinate the change in node A (in terms of concentration and activity) and the expression dynamics of node C, creating different input-output behaviors.<ref>{{cite journal | vauthors = Mangan S, Alon U | title = Structure and function of the feed-forward loop network motif | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 100 | issue = 21 | pages = 11980–11985 | date = October 2003 | pmid = 14530388 | pmc = 218699 | doi = 10.1073/pnas.2133841100 | doi-access = free | bibcode = 2003PNAS..10011980M }}</ref><ref>{{cite journal | vauthors = Goentoro L, Shoval O, Kirschner MW, Alon U | title = The incoherent feedforward loop can provide fold-change detection in gene regulation | journal = Molecular Cell | volume = 36 | issue = 5 | pages = 894–899 | date = December 2009 | pmid = 20005851 | pmc = 2896310 | doi = 10.1016/j.molcel.2009.11.018 }}</ref> The [[galactose]] utilization system of ''[[E. coli]]'' contains a feed-forward loop which accelerates the activation of galactose utilization [[operon]] ''galETK'', potentially facilitating the metabolic transition to galactose when glucose is depleted.<ref>{{cite journal | vauthors = Mangan S, Itzkovitz S, Zaslaver A, Alon U | title = The incoherent feed-forward loop accelerates the response-time of the gal system of Escherichia coli | journal = Journal of Molecular Biology | volume = 356 | issue = 5 | pages = 1073–1081 | date = March 2006 | pmid = 16406067 | doi = 10.1016/j.jmb.2005.12.003 | citeseerx = 10.1.1.184.8360 }}</ref> The feed-forward loop in the [[arabinose]] utilization systems of ''E.coli'' delays the activation of arabinose catabolism operon and transporters, potentially avoiding unnecessary metabolic transition due to temporary fluctuations in upstream signaling pathways.<ref>{{cite journal | vauthors = Mangan S, Zaslaver A, Alon U | title = The coherent feedforward loop serves as a sign-sensitive delay element in transcription networks | journal = Journal of Molecular Biology | volume = 334 | issue = 2 | pages = 197–204 | date = November 2003 | pmid = 14607112 | doi = 10.1016/j.jmb.2003.09.049 | citeseerx = 10.1.1.110.4629 }}</ref> Similarly in the Wnt signaling pathway of ''[[Xenopus]]'', the feed-forward loop acts as a fold-change detector that responses to the fold change, rather than the absolute change, in the level of β-catenin, potentially increasing the resistance to fluctuations in β-catenin levels.<ref>{{cite journal | vauthors = Goentoro L, Kirschner MW | title = Evidence that fold-change, and not absolute level, of beta-catenin dictates Wnt signaling | journal = Molecular Cell | volume = 36 | issue = 5 | pages = 872–884 | date = December 2009 | pmid = 20005849 | pmc = 2921914 | doi = 10.1016/j.molcel.2009.11.017 }}</ref> Following the convergent evolution hypothesis, the enrichment of feed-forward loops would be an [[adaptation]] for fast response and noise resistance. A recent research found that yeast grown in an environment of constant glucose developed mutations in glucose signaling pathways and growth regulation pathway, suggesting regulatory components responding to environmental changes are dispensable under constant environment.<ref>{{cite journal | vauthors = Kvitek DJ, Sherlock G | title = Whole genome, whole population sequencing reveals that loss of signaling networks is the major adaptive strategy in a constant environment | journal = PLOS Genetics | volume = 9 | issue = 11 | pages = e1003972 | date = November 2013 | pmid = 24278038 | pmc = 3836717 | doi = 10.1371/journal.pgen.1003972 | doi-access = free }}</ref>

On the other hand, some researchers hypothesize that the enrichment of network motifs is non-adaptive.<ref>{{cite journal | vauthors = Lynch M | title = The evolution of genetic networks by non-adaptive processes | journal = Nature Reviews. Genetics | volume = 8 | issue = 10 | pages = 803–813 | date = October 2007 | pmid = 17878896 | doi = 10.1038/nrg2192 | s2cid = 11839414 }}</ref> In other words, gene regulatory networks can evolve to a similar structure without the specific selection on the proposed input-output behavior. Support for this hypothesis often comes from computational simulations. For example, fluctuations in the abundance of feed-forward loops in a model that simulates the evolution of gene regulatory networks by randomly rewiring nodes may suggest that the enrichment of feed-forward loops is a side-effect of evolution.<ref>{{cite journal | vauthors = Cordero OX, Hogeweg P | title = Feed-forward loop circuits as a side effect of genome evolution | journal = Molecular Biology and Evolution | volume = 23 | issue = 10 | pages = 1931–1936 | date = October 2006 | pmid = 16840361 | doi = 10.1093/molbev/msl060 | doi-access =  }}</ref> In another model of gene regulator networks evolution, the ratio of the frequencies of gene duplication and gene deletion show great influence on network topology: certain ratios lead to the enrichment of feed-forward loops and create networks that show features of hierarchical scale free networks. De novo evolution of coherent type 1 feed-forward loops has been demonstrated computationally in response to selection for their hypothesized function of filtering out a short spurious signal, supporting adaptive evolution, but for non-idealized noise, a dynamics-based system of feed-forward regulation with different topology was instead favored.<ref>{{cite journal | vauthors = Xiong K, Lancaster AK, Siegal ML, Masel J | title = Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise | journal = Nature Communications | volume = 10 | issue = 1 | pages = 2418 | date = June 2019 | pmid = 31160574 | pmc = 6546794 | doi = 10.1038/s41467-019-10388-6 | bibcode = 2019NatCo..10.2418X }}</ref>