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Partial correlation analysis of transcriptomes helps detangle the growth and defense network in spruce
Author(s) -
Porth Ilga,
White Richard,
Jaquish Barry,
Ritland Kermit
Publication year - 2018
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.15075
Subject(s) - biology , gene , partial correlation , transcriptome , genetics , weevil , correlation , identification (biology) , gene regulatory network , gene expression , computational biology , evolutionary biology , botany , geometry , mathematics
Summary 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.