Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise

Feed‐forward loops (FFLs) can filter out noise, but whether their overrepresentation in GRNs reflects adaptive evolution for this function is debated. Here, the authors develop a null model of regulatory evolution and find that FFLs evolve readily under selection for the noise filtering function.

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Autores principales:	Kun Xiong, Alex K. Lancaster, Mark L. Siegal, Joanna Masel
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/fa643ad0636c418e840b324feb672761
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spelling	oai:doaj.org-article:fa643ad0636c418e840b324feb6727612021-12-02T15:35:30ZFeed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise10.1038/s41467-019-10388-62041-1723https://doaj.org/article/fa643ad0636c418e840b324feb6727612019-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-10388-6https://doaj.org/toc/2041-1723Feed‐forward loops (FFLs) can filter out noise, but whether their overrepresentation in GRNs reflects adaptive evolution for this function is debated. Here, the authors develop a null model of regulatory evolution and find that FFLs evolve readily under selection for the noise filtering function.Kun XiongAlex K. LancasterMark L. SiegalJoanna MaselNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-13 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Kun Xiong Alex K. Lancaster Mark L. Siegal Joanna Masel Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise
description	Feed‐forward loops (FFLs) can filter out noise, but whether their overrepresentation in GRNs reflects adaptive evolution for this function is debated. Here, the authors develop a null model of regulatory evolution and find that FFLs evolve readily under selection for the noise filtering function.
format	article
author	Kun Xiong Alex K. Lancaster Mark L. Siegal Joanna Masel
author_facet	Kun Xiong Alex K. Lancaster Mark L. Siegal Joanna Masel
author_sort	Kun Xiong
title	Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise
title_short	Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise
title_full	Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise
title_fullStr	Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise
title_full_unstemmed	Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise
title_sort	feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/fa643ad0636c418e840b324feb672761
work_keys_str_mv	AT kunxiong feedforwardregulationadaptivelyevolvesviadynamicsratherthantopologywhenthereisintrinsicnoise AT alexklancaster feedforwardregulationadaptivelyevolvesviadynamicsratherthantopologywhenthereisintrinsicnoise AT marklsiegal feedforwardregulationadaptivelyevolvesviadynamicsratherthantopologywhenthereisintrinsicnoise AT joannamasel feedforwardregulationadaptivelyevolvesviadynamicsratherthantopologywhenthereisintrinsicnoise
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Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise

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