Open Access Research article

Evaluation of diversity among common beans (Phaseolus vulgaris L.) from two centers of domestication using 'omics' technologies

Meghan M Mensack1, Vanessa K Fitzgerald1, Elizabeth P Ryan2, Matthew R Lewis3, Henry J Thompson1* and Mark A Brick4

Author Affiliations

1 Cancer Prevention Laboratory, Department of Horticulture, Colorado State Univ., Fort Collins, CO, 80523-1173, USA

2 Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State Univ., Fort Collins, CO, 80523-1678, USA

3 Proteomics and Metabolomics Facility, Department of the Vice President for Research, Colorado State Univ., Fort Collins, CO, 80523-2021, USA

4 Department of Soil and Crop Sciences, Colorado State Univ., Fort Collins, CO, 80523-1173, USA

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BMC Genomics 2010, 11:686  doi:10.1186/1471-2164-11-686

Published: 2 December 2010



Genetic diversity among wild accessions and cultivars of common bean (Phaseolus vulgaris L.) has been characterized using plant morphology, seed protein allozymes, random amplified polymorphic DNA, restriction fragment length polymorphisms, DNA sequence analysis, chloroplast DNA, and microsatellite markers. Yet, little is known about whether these traits, which distinguish among genetically distinct types of common bean, can be evaluated using omics technologies.


Three 'omics' approaches: transcriptomics, proteomics, and metabolomics were used to qualitatively evaluate the diversity of common bean from two Centers of Domestication (COD). All three approaches were able to classify common bean according to their COD using unsupervised analyses; these findings are consistent with the hypothesis that differences exist in gene transcription, protein expression, and synthesis and metabolism of small molecules among common bean cultivars representative of different COD. Metabolomic analyses of multiple cultivars within two common bean gene pools revealed cultivar differences in small molecules that were of sufficient magnitude to allow identification of unique cultivar fingerprints.


Given the high-throughput and low cost of each of these 'omics' platforms, significant opportunities exist for their use in the rapid identification of traits of agronomic and nutritional importance as well as to characterize genetic diversity.