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Updated: Jun 3, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Published on: November 12, 2012
Association mapping of common bacterial blight resistance QTL in Ontario bean breeding populations
Chun Shi1, Alireza Navabi, Kangfu Yu
1Agriculture and Agri-Food Canada, Greenhouse and Processing Crops Research Centre, Harrow, ON, N0R 1G0, Canada.
Background:
Common bacterial blight (CBB), incited by Xanthomonas axonopodis pv. phaseoli (Xap), is a major yield-limiting factor of common bean (Phaseolus vulgaris L.) production around the world. Host resistance is practically the most effective and environmentally-sound approach to control CBB. Unlike conventional QTL discovery strategies, in which bi-parental populations (F2, RIL, or DH) need to be developed, association mapping-based strategies can use plant breeding populations to synchronize QTL discovery and cultivar development.
Results:
A population of 469 dry bean lines of different market classes representing plant materials routinely developed in a bean breeding program were used. Of them, 395 lines were evaluated for CBB resistance at 14 and 21 DAI (Days After Inoculation) in the summer of 2009 in an artificially inoculated CBB nursery in south-western Ontario. All lines were genotyped using 132 SNPs (Single Nucleotide Polymorphisms) evenly distributed across the genome. Of the 132 SNPs, 26 SNPs had more than 20% missing data, 12 SNPs were monomorphic, and 17 SNPs had a MAF (Minor Allelic Frequency) of less than 0.20, therefore only 75 SNPs were used for association study, based on one SNP per locus. The best possible population structure was to assign 36% and 64% of the lines into Andean and Mesoamerican subgroups, respectively. Kinship analysis also revealed complex familial relationships among all lines, which corresponds with the known pedigree history. MLM (Mixed Linear Model) analysis, including population structure and kinship, was used to discover marker-trait associations. Eighteen and 22 markers were significantly associated with CBB rating at 14 and 21 DAI, respectively. Fourteen markers were significant for both dates and the markers UBC420, SU91, g321, g471, and g796 were highly significant (p ≤ 0.001). Furthermore, 12 significant SNP markers were co-localized with or close to the CBB-QTLs identified previously in bi-parental QTL mapping studies.
Conclusions:
This study demonstrated that association mapping using a reasonable number of markers, distributed across the genome and with application of plant materials that are routinely developed in a plant breeding program can detect significant QTLs for traits of interest.
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