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Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development.

ABSTRACT: Plant developmental dynamics can be heritable, genetically correlated with fitness and yield, and undergo selection. Therefore, characterizing the mechanistic connections between the genetic architecture governing plant development and the resulting ontogenetic dynamics of plants in field settings is critically important for agricultural production and evolutionary ecology. We use hierarchical Bayesian Function-Valued Trait (FVT) models to estimate Brassica rapa growth curves throughout ontogeny, across two treatments, and in two growing seasons. We find genetic variation for plasticity of growth rates and final sizes, but not the inflection point (transition from accelerating to decelerating growth) of growth curves. There are trade-offs between growth rate and duration, indicating that selection for maximum yields at early harvest dates may come at the expense of late harvest yields and vice versa. We generate eigengene modules and determine which are co-expressed with FVT traits using a Weighted Gene Co-expression Analysis. Independently, we seed a Mutual Rank co-expression network model with FVT traits to identify specific genes and gene networks related to FVT. GO-analyses of eigengene modules indicate roles for actin/cytoskeletal genes, herbivore resistance/wounding responses, and cell division, while MR networks demonstrate a close association between metabolic regulation and plant growth. We determine that combining FVT Quantitative Trait Loci (QTL) and MR genes/WGCNA eigengene expression profiles better characterizes phenotypic variation than any single data type (i.e. QTL, gene, or eigengene alone). Our network analysis allows us to employ a targeted eQTL analysis, which we use to identify regulatory hotspots for FVT. We examine cis vs. trans eQTL that mechanistically link FVT QTL with structural trait variation. Colocalization of FVT, gene, and eigengene eQTL provide strong evidence for candidate genes influencing plant height. The study is the first to explore eQTL for FVT, and specifically do so in agroecologically relevant field settings.

SUBMITTER: Baker RL

PROVIDER: S-EPMC6759183 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development.

Baker Robert L RL Leong Wen Fung WF Brock Marcus T MT Rubin Matthew J MJ Markelz R J Cody RJC Welch Stephen S Maloof Julin N JN Weinig Cynthia C

PLoS genetics 20190912 9

Plant developmental dynamics can be heritable, genetically correlated with fitness and yield, and undergo selection. Therefore, characterizing the mechanistic connections between the genetic architecture governing plant development and the resulting ontogenetic dynamics of plants in field settings is critically important for agricultural production and evolutionary ecology. We use hierarchical Bayesian Function-Valued Trait (FVT) models to estimate Brassica rapa growth curves throughout ontogeny ...[more]

PMID: 31513571

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Project description:The aim of this study was to identify eQTL in Brassica rapa grown under altered soil phosphorus (P) supply, to understand better the genetic architecture of P-use efficiency (PUE) in plants. Recombinant inbred lines (RILs) of the BraIRRI mapping population were grown at adequate and growth-limiting soil P. Variation in leaf gene expression was quantified using an Agilent Brassica 95k oligonucleotide array. Informative gene expression markers (GEMs) were used to map eQTL and PUE-related QTL. Gene expression was highly dependent on soil P supply. However, the altered expression of many genes, including known P-responsive genes, was highly heritable. Interval mapping using P supply as a covariate revealed 18,876 eQTL, representing 15,912 unique probes. Notable trans-eQTL hotspots occurred on chromosomes A06 and A01; these were enriched with protein modification and phosphorus metabolism-related (A06), as well as chloroplast and photosynthesis-related (A01) transcripts. Regulatory loci and genes associated with P-use efficiency identified through eQTL analysis are potential targets for further characterisation and may have potential for crop improvement. Availability of the annotated B. rapa genome sequence will facilitate their study, including the separation of cis- and trans- effects. The experiment was designed to identify expression QTL associated with availability of phosphorus in Brassica rapa. Seventy-eight informative lines from the “BraIRRI” mapping population of Brassica rapa L. (2n = 2x = 10; A-genome) and the two parent lines (IMB211, female; R500, male) were selected for study. The establishment of the BraIRRI population is described by Iniguez-Luy et al. (2009). Plants were grown from seed in compost, under two [P]ext treatments of 9 mg L-1 (low) or 30 mg L-1 (optimal) Olsen extractable P. RNA was extracted from leaf samples from one experimental run (78 lines at low and optimal [P]ext, with one line duplicated i.e. 158 samples), and from leaf samples from the parent lines at low and optimal P in all three experimental runs (12 samples) using a modified TRIzol extraction method (Hammond et al., 2006).

Dataset Information

Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development.

Publications

Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development.

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