Resequencing of Common Bean Identifies Regions of Inter–Gene Pool Introgression and Provides Comprehensive Resources for Molecular Breeding. Issue 2 (1st July 2018)

• Record Type: Journal Article
• Authors: Lobaton, Juan David; Miller, Tamara; Gil, Juanita; Ariza, Daniel; de la Hoz, Juan Fernando; Soler, Alvaro; Beebe, Steve; Duitama, Jorge; Gepts, Paul; Raatz, Bodo
• Is Part Of: œplant genome. Volume 11:Issue 2(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-07-01
• Subjects: Plant genomes -- Periodicals; Plant genome mapping -- Periodicals; 572.862
• DOI: 10.3835/plantgenome2017.08.0068
• Languages: English
• ISSNs: 1940-3372

Abstract

Abstract : Common bean ( Phaseolus vulgaris L.) is the most important grain legume for human consumption and is a major nutrition source in the tropics. Because bean production is reduced by both abiotic and biotic constraints, current breeding efforts are focused on the development of improved varieties with tolerance to these stresses. We characterized materials from different breeding programs spanning three continents to understand their sequence diversity and advance the development of molecular breeding tools. For this, 37 varieties belonging to P. vulgaris, Phaseolus acutifolius (A. Gray), and Phaseolus coccineus L. were sequenced by whole‐genome sequencing, identifying more than 40 million genomic variants. Evaluation of nuclear DNA content and analysis of copy number variation revealed important differences in genomic content not only between P. vulgaris and the two other domesticated Phaseolus species, but also within P. vulgaris, affecting hundreds of protein‐coding genomic regions. A large number of inter–gene pool introgressions were identified. Furthermore, interspecific introgressions for disease resistance in breeding lines were mapped. Evaluation of newly developed single nucleotide polymorphism markers within previously discovered quantitative trait loci for common bacterial blight and angular leaf spot provides improved specificity to tag sources of resistance to these diseases. We expect that this dataset will provide a deeper molecular understanding of breeding germplasm and deliver molecular tools for germplasm development, aiming to increase the efficiency of bean breeding programs.