Location: Grain Legume Genetics Physiology ResearchTitle: Application of in silico bulked segregant analysis for rapid development of markers linked to Bean common mosaic virus resistance in common bean
|BELLO, MARCO - Washington State University|
|MOGHADDAM, SAMIRA - North Dakota State University|
|MASSOUDI, MARK - Ag Biotech, Llc|
|MCCLEAN, PHILIP - North Dakota State University|
|Miklas, Phillip - Phil|
Submitted to: BMC Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/6/2014
Publication Date: 10/16/2014
Citation: Bello, M., Moghaddam, S., Massoudi, M., Mcclean, P., Cregan, P.B., Miklas, P.N. 2014. Application of in silico bulked segregant analysis for rapid development of markers linked to Bean common mosaic virus resistance in common bean. Biomed Central (BMC) Genomics. 15:903.
Interpretive Summary: Given the genomic revolution has arrived recently for common bean there has been an influx of genomic tools available for fine-mapping economicallyimportant loci. This has resulted in many of the marker-gene associations used for marker-assisted selection to be revisited with the goal of developing more tightly linked and thus better diagnostic markers for the selected traits. The I-gene in common bean linked with the marker SW13 is one such combination used for marker-assisted selection that has been in need of a better marker. The I-gene conditions resistance to many viruses that otherwise plague common bean production. This study used new genomic tools and strategies to identify a better/more diagnostic marker for use in marker-assisted selection of the I-gene. The new marker will assist breeders directly in developing new cultivars with I gene and the strategies employed will contribute to finding better markers for marker-assisted selection of other important genes in common bean.
Technical Abstract: Common bean was one of the first crops that benefited from the development and utilization of molecular markers in tagging major disease resistance genes for marker-assisted selection (MAS). Efficiency of MAS breeding in common bean is still hampered; however, due to the dominance, linkage phase, and loose linkage of previously developed markers. Here we applied in silico bulked segregant analysis (BSA) to the BeanCAP diversity panel, composed of over 500 lines and genotyped with the BARCBEAN_3 6K SNP BeadChip, to develop codominant and tightly linked markers to the I gene controlling resistance to Bean Common Mosaic Virus (BCMV). Results we physically mapped the genomic region underlying the I gene. This locus, in the distal arm of chromosome Pv02, contains seven putative NBS-LRR-type disease resistance genes. Two contrasting bulks, containing BCMV-differentials and ten BeanCAP lines with known disease reaction to BCMV, were subjected to in silico BSA for targeting the I gene and flanking sequences. Two distinct haplotypes, containing a cluster of six single nucleotide polymorphisms (SNP), were associated to resistance or susceptibility to BCMV. One-hundred and twenty two lines,including 115 of the BeanCAP panel, were screened for BCMV resistance in the greenhouse, and all of the resistant or susceptible plants displayed distinct SNP haplotypes as those found in the two bulks. The resistant/susceptible haplotypes were validated in 98 recombinant inbred lines segregating for BCMV resistance. The closest SNP (~25-32 kb) to the distal NBS-LRR gene model at the I gene locus was targeted for conversion to codominant KASP (Kompetitive Allele Specific PCR) and CAPS (Cleaved Amplified Polymorphic Sequence) markers. Both markers systems accurately predicted the disease reaction to BCMV conferred by the I gene in all screened lines of this study. Conclusions we demonstrated the utility of the in silico BSA approach using genetically diverse germplasm, genotyped with a high-density SNP chip array, to discover SNP variation at a specific targeted genomic region. In common bean, many disease resistance genes are mapped and their physical genomic position can now be determined, thus the application of this approach could facilitate the development of codominant and tightly linked markers for use in MAS.