Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologsGraham, N. S., Hammond, J. P. ORCID: https://orcid.org/0000-0002-6241-3551, Lysenko, A., Mayes, S., O Lochlainn, S., Blasco, B., Bowen, H. C., Rawlings, C. J., Rios, J. J., Welham, S., Carion, P. W.C., Dupuy, L. X., King, G. J., White, P. J. and Broadley, M. R. (2014) Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologs. The Plant Cell, 26 (7). pp. 2818-2830. ISSN 1040-4651
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1105/tpc.114.128603 Abstract/SummaryAlthough Ca transport in plants is highly complex, the overexpression of vacuolar Ca2+ transporters in crops is a promising new technology to improve dietary Ca supplies through biofortification. Here, we sought to identify novel targets for increasing plant Ca accumulation using genetical and comparative genomics. Expression quantitative trait locus (eQTL) mapping to 1895 cis- and 8015 trans-loci were identified in shoots of an inbred mapping population of Brassica rapa (IMB211 × R500); 23 cis- and 948 trans-eQTLs responded specifically to altered Ca supply. eQTLs were screened for functional significance using a large database of shoot Ca concentration phenotypes of Arabidopsis thaliana. From 31 Arabidopsis gene identifiers tagged to robust shoot Ca concentration phenotypes, 21 mapped to 27 B. rapa eQTLs, including orthologs of the Ca2+ transporters At-CAX1 and At-ACA8. Two of three independent missense mutants of BraA.cax1a, isolated previously by targeting induced local lesions in genomes, have allele-specific shoot Ca concentration phenotypes compared with their segregating wild types. BraA.CAX1a is a promising target for altering the Ca composition of Brassica, consistent with prior knowledge from Arabidopsis. We conclude that multiple-environment eQTL analysis of complex crop genomes combined with comparative genomics is a powerful technique for novel gene identification/prioritization.
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