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Genome-wide association mapping of iron homeostasis in the maize association population

Overview of attention for article published in BMC Genetics, January 2015
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Title
Genome-wide association mapping of iron homeostasis in the maize association population
Published in
BMC Genetics, January 2015
DOI 10.1186/s12863-014-0153-0
Pubmed ID
Authors

Andreas Benke, Claude Urbany, Benjamin Stich

Abstract

BackgroundIron (Fe) deficiency in plants is the result of low Fe soil availability affecting 30% of cultivated soils worldwide. To improve our understanding on Fe-efficiency this study aimed to (i) evaluate the influence of two different Fe regimes on morphological and physiological trait formation, (ii) identify polymorphisms statistically associated with morphological and physiological traits, and (iii) dissect the correlation between morphological and physiological traits using an association mapping population.ResultsThe fine-mapping analyses on quantitative trait loci (QTL) confidence intervals of the intermated B73 x Mo17 (IBM) population provided a total of 13 and 2 single nucleotide polymorphisms (SNPs) under limited and adequate Fe regimes, respectively, which were significantly (FDR = 0.05) associated with cytochrome P450 94A1, invertase beta-fructofuranosidase insoluble isoenzyme 6, and a low-temperature-induced 65 kDa protein. The genome-wide association (GWA) analyses under limited and adequate Fe regimes provided in total 18 and 17 significant SNPs, respectively.ConclusionsSignificantly associated SNPs on a genome-wide level under both Fe regimes for the traits leaf necrosis (NEC), root weight (RW), shoot dry weight (SDW), water (H 2O), and SPAD value of leaf 3 (SP3) were located in genes or recognition sites of transcriptional regulators, which indicates a direct impact on the phenotype. SNPs which were significantly associated on a genome-wide level under both Fe regimes with the traits NEC, RW, SDW, H 2O, and SP3 might be attractive targets for marker assisted selection as well as interesting objects for future functional analyses.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
United States 1 2%
France 1 2%
Unknown 46 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 29%
Researcher 10 20%
Student > Doctoral Student 6 12%
Student > Master 5 10%
Student > Postgraduate 4 8%
Other 6 12%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 80%
Biochemistry, Genetics and Molecular Biology 4 8%
Nursing and Health Professions 1 2%
Chemistry 1 2%
Unknown 4 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 January 2015.
All research outputs
#3,931,241
of 4,693,373 outputs
Outputs from BMC Genetics
#424
of 514 outputs
Outputs of similar age
#131,725
of 163,905 outputs
Outputs of similar age from BMC Genetics
#23
of 27 outputs
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