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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24699171/?tool=EBI |
| _version_ | 1819180818673696768 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-22T22:20:23Z |
| format | Article |
| id | doaj.art-6a697374ad30486289d78a638b18e9cf |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-22T22:20:23Z |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-6a697374ad30486289d78a638b18e9cf2022-12-21T18:10:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0194e8968910.1371/journal.pone.0089689Inferring the gene network underlying the branching of tomato inflorescence.Laura AstolaHans StigterAalt D J van DijkRaymond van DaelenJaap MolenaarThe 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.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24699171/?tool=EBI |
| spellingShingle | Laura Astola Hans Stigter Aalt D J van Dijk Raymond van Daelen Jaap Molenaar Inferring the gene network underlying the branching of tomato inflorescence. PLoS ONE |
| title | 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_short | Inferring the gene network underlying the branching of tomato inflorescence. |
| title_sort | inferring the gene network underlying the branching of tomato inflorescence |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24699171/?tool=EBI |
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