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. 2011 Jul;156(3):1230-41.
doi: 10.1104/pp.111.175612. Epub 2011 Apr 28.

Regulatory hotspots are associated with plant gene expression under varying soil phosphorus supply in Brassica rapa

John P Hammond  1 , Sean Mayes, Helen C Bowen, Neil S Graham, Rory M Hayden, Christopher G Love, William P Spracklen, Jun Wang, Sue J Welham, Philip J White, Graham J King, Martin R Broadley
Affiliations

Regulatory hotspots are associated with plant gene expression under varying soil phosphorus supply in Brassica rapa

John P Hammond et al. Plant Physiol. 2011 Jul.

Abstract

Gene expression is a quantitative trait that can be mapped genetically in structured populations to identify expression quantitative trait loci (eQTL). Genes and regulatory networks underlying complex traits can subsequently be inferred. Using a recently released genome sequence, we have defined cis- and trans-eQTL and their environmental response to low phosphorus (P) availability within a complex plant genome and found hotspots of trans-eQTL within the genome. Interval mapping, using P supply as a covariate, revealed 18,876 eQTL. trans-eQTL hotspots occurred on chromosomes A06 and A01 within Brassica rapa; these were enriched with P metabolism-related Gene Ontology terms (A06) as well as chloroplast- and photosynthesis-related terms (A01). We have also attributed heritability components to measures of gene expression across environments, allowing the identification of novel gene expression markers and gene expression changes associated with low P availability. Informative gene expression markers were used to map eQTL and P use efficiency-related QTL. Genes responsive to P supply had large environmental and heritable variance components. Regulatory loci and genes associated with P use efficiency identified through eQTL analysis are potential targets for further characterization and may have potential for crop improvement.

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Figures

Figure 1.
Figure 1.
A, Frequency distribution for the H2 of gene expression for all probes on the Agilent Brassica array. B, H2 plotted against the treatment effect calculated in the residual maximum likelihood analysis. White circles represent GEMs identified from the array data and used to generate the GEMs map for the BraIRRI mapping population.
Figure 2.
Figure 2.
Frequency distribution of genes differentially expressed between optimal and low P treatments identified in this paper (A), by Misson et al. (2005; B), by Morcuende et al. (2007; C), or by Wu et al. (2003; D) as a function of H2. Horizontal bars represent significance (P < 0.05) thresholds for overrepresentation of P-responsive genes within a bin of 3,000 genes.
Figure 3.
Figure 3.
Distribution of 125 GEMs for the BraIRRI_04_2010a map (Supplemental Table S1) across the B. rapa A genome (A) and across the 67 genotypes of the BraIRRI mapping population used to identify eQTL and QTL associated with low and optimal P availability (B).
Figure 4.
Figure 4.
Comparison between genetic and physical positions of the 14,257 eQTL for which physical positions could be identified (A) and the distribution of eQTL associated with individual markers across the B. rapa A genome (B). Probe sequences were aligned to the concatenated scaffolds of the B. rapa Chiifu-401 genome sequence (version 1.0) to determine physical positions and compared with genetic locations determined through eQTL analyses.
Figure 5.
Figure 5.
Shoot dry weight (A), shoot P concentration (B), physiological PUE (C), agronomic PUE (D), P utilization efficiency (E), and P uptake efficiency (F) for the B. rapa BraIRRI mapping population. DM, Dry matter; P, shoot P concentration; Pf, fertilizer P applied. Data are residual maximum likelihood-estimated means for plants grown in compost under CE conditions at low and optimal [P]ext. The boundaries of the box closest to and farthest from zero indicate the 25th and 75th percentiles, respectively. The solid line within the box indicatee the median. Error bars indicate the 10th and 90th percentiles. Circles indicate outliers. Parents of the mapping population are indicated.
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