title: An eQTL analysis of partial resistance to Puccinia hordei in barley.
abstract: BACKGROUND
  Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes.
  
  
  RESULTS
  We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis.
  
  
  CONCLUSIONS
  The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this population.
authors.affiliation: Genetics Programme, Scottish Crop Research Institute, Dundee, United Kingdom. xinwei.chen@scri.ac.uk
authors.forename: Xinwei
authors.initials: X
authors.lastname: Chen
authors.forename: Christine A
authors.initials: CA
authors.lastname: Hackett
authors.forename: Rients E
authors.initials: RE
authors.lastname: Niks
authors.forename: Peter E
authors.initials: PE
authors.lastname: Hedley
authors.forename: Clare
authors.initials: C
authors.lastname: Booth
authors.forename: Arnis
authors.initials: A
authors.lastname: Druka
authors.forename: Thierry C
authors.initials: TC
authors.lastname: Marcel
authors.forename: Anton
authors.initials: A
authors.lastname: Vels
authors.forename: Micha
authors.initials: M
authors.lastname: Bayer
authors.forename: Iain
authors.initials: I
authors.lastname: Milne
authors.forename: Jenny
authors.initials: J
authors.lastname: Morris
authors.forename: Luke
authors.initials: L
authors.lastname: Ramsay
authors.forename: David
authors.initials: D
authors.lastname: Marshall
authors.forename: Linda
authors.initials: L
authors.lastname: Cardle
authors.forename: Robbie
authors.initials: R
authors.lastname: Waugh
mesh_terms: D005658:Fungi / Q000472:pathogenicity*; D017343:Genes, Plant; D001467:Hordeum / Q000235:genetics* / Q000382:microbiology; D040641:Quantitative Trait Loci