Partial correlation analysis of transcriptomes helps detangle the growth and defense network in spruce

© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Détails bibliographiques
Publié dans:The New phytologist. - 1984. - 218(2018), 4 vom: 15. Juni, Seite 1349-1359
Auteur principal: Porth, Ilga (Auteur)
Autres auteurs: White, Richard, Jaquish, Barry, Ritland, Kermit
Format: Article en ligne
Langue:English
Publié: 2018
Accès à la collection:The New phytologist
Sujets:Journal Article Research Support, Non-U.S. Gov't Picea gene networks genetic correlations growth herbivory perennials
Description
Résumé:© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.
In plants, there can be a trade-off between resource allocations to growth vs defense. Here, we use partial correlation analysis of gene expression to make inferences about the nature of this interaction. We studied segregating progenies of Interior spruce subject to weevil attack. In a controlled experiment, we measured pre-attack plant growth and post-attack damage with several morphological measures, and profiled transcriptomes of 188 progeny. We used partial correlations of individual transcripts (expressed sequence tags, ESTs) with pairs of growth/defense traits to identify important nodes and edges in the inferred underlying gene network, for example, those pairs of growth/defense traits with high mutual correlation with a single EST transcript. We give a method to identify such ESTs. A terpenoid ABC transporter gene showed strongest correlations (P = 0.019); its transcript represented a hub within the compact 166-member gene-gene interaction network (P = 0.004) of the negative genetic correlations between growth and subsequent pest attack. A small 21-member interaction network (P = 0.004) represented the uncovered positive correlations. Our study demonstrates partial correlation analysis identifies important gene networks underlying growth and susceptibility to the weevil in spruce. In particular, we found transcripts that strongly modify the trade-off between growth and defense, and allow identification of networks more central to the trade-off
Description:Date Completed 01.10.2019
Date Revised 30.09.2020
published: Print-Electronic
Citation Status MEDLINE
ISSN:1469-8137
DOI:10.1111/nph.15075