Inferring the gene network underlying the branching of tomato inflorescence.

The architecture of tomato inflorescence strongly affects flower production and subsequent crop yield. To understand the genetic activities involved, insight into the underlying network of genes that initiate and control the sympodial growth in the tomato is essential. In this paper, we show how the...

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Autores principales:	Laura Astola, Hans Stigter, Aalt D J van Dijk, Raymond van Daelen, Jaap Molenaar
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6a697374ad30486289d78a638b18e9cf
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spelling	oai:doaj.org-article:6a697374ad30486289d78a638b18e9cf2021-11-18T08:25:09ZInferring the gene network underlying the branching of tomato inflorescence.1932-620310.1371/journal.pone.0089689https://doaj.org/article/6a697374ad30486289d78a638b18e9cf2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24699171/?tool=EBIhttps://doaj.org/toc/1932-6203The architecture of tomato inflorescence strongly affects flower production and subsequent crop yield. To understand the genetic activities involved, insight into the underlying network of genes that initiate and control the sympodial growth in the tomato is essential. In this paper, we show how the structure of this network can be derived from available data of the expressions of the involved genes. Our approach starts from employing biological expert knowledge to select the most probable gene candidates behind branching behavior. To find how these genes interact, we develop a stepwise procedure for computational inference of the network structure. Our data consists of expression levels from primary shoot meristems, measured at different developmental stages on three different genotypes of tomato. With the network inferred by our algorithm, we can explain the dynamics corresponding to all three genotypes simultaneously, despite their apparent dissimilarities. We also correctly predict the chronological order of expression peaks for the main hubs in the network. Based on the inferred network, using optimal experimental design criteria, we are able to suggest an informative set of experiments for further investigation of the mechanisms underlying branching behavior.Laura AstolaHans StigterAalt D J van DijkRaymond van DaelenJaap MolenaarPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 4, p e89689 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Laura Astola Hans Stigter Aalt D J van Dijk Raymond van Daelen Jaap Molenaar Inferring the gene network underlying the branching of tomato inflorescence.
description	The architecture of tomato inflorescence strongly affects flower production and subsequent crop yield. To understand the genetic activities involved, insight into the underlying network of genes that initiate and control the sympodial growth in the tomato is essential. In this paper, we show how the structure of this network can be derived from available data of the expressions of the involved genes. Our approach starts from employing biological expert knowledge to select the most probable gene candidates behind branching behavior. To find how these genes interact, we develop a stepwise procedure for computational inference of the network structure. Our data consists of expression levels from primary shoot meristems, measured at different developmental stages on three different genotypes of tomato. With the network inferred by our algorithm, we can explain the dynamics corresponding to all three genotypes simultaneously, despite their apparent dissimilarities. We also correctly predict the chronological order of expression peaks for the main hubs in the network. Based on the inferred network, using optimal experimental design criteria, we are able to suggest an informative set of experiments for further investigation of the mechanisms underlying branching behavior.
format	article
author	Laura Astola Hans Stigter Aalt D J van Dijk Raymond van Daelen Jaap Molenaar
author_facet	Laura Astola Hans Stigter Aalt D J van Dijk Raymond van Daelen Jaap Molenaar
author_sort	Laura Astola
title	Inferring the gene network underlying the branching of tomato inflorescence.
title_short	Inferring the gene network underlying the branching of tomato inflorescence.
title_full	Inferring the gene network underlying the branching of tomato inflorescence.
title_fullStr	Inferring the gene network underlying the branching of tomato inflorescence.
title_full_unstemmed	Inferring the gene network underlying the branching of tomato inflorescence.
title_sort	inferring the gene network underlying the branching of tomato inflorescence.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/6a697374ad30486289d78a638b18e9cf
work_keys_str_mv	AT lauraastola inferringthegenenetworkunderlyingthebranchingoftomatoinflorescence AT hansstigter inferringthegenenetworkunderlyingthebranchingoftomatoinflorescence AT aaltdjvandijk inferringthegenenetworkunderlyingthebranchingoftomatoinflorescence AT raymondvandaelen inferringthegenenetworkunderlyingthebranchingoftomatoinflorescence AT jaapmolenaar inferringthegenenetworkunderlyingthebranchingoftomatoinflorescence
_version_	1718421807057338368

Inferring the gene network underlying the branching of tomato inflorescence.

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