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INTRODUCTION Single nucleotide polymorphisms are becoming the marker of choice for a wide variety of organisms, due to their high abundance in genomes (Gupta  et. al.,  2001), their evolutionary stability and the availability of high throughput technologies for their detection (Syvanen  et al.,  1999). SNP discovery in common bean was initiated at CIAT in 2002 by Gaitán and Tohme who found 223 SNPs in 20964pb of  P. vulgaris  genome after sequencing PCR products of ten Andean and Mesoamerican genotypes. The purposes of this project were: 1) to validate, using multiplex techniques, the SNP markers developed at CIAT (Gaitán-Solís  et. al , 2008) together with soybean-derived SNPs (developed at BARC-USDA); 2) to saturate the existing linkage map of the common bean DOR 364/G19833 cross and 3) to study the potential of SNP markers for determining the direction of gene flow in a wild-weedy-crop complex from Colombia. GENETIC MAPPING OF SNPs EXPERIMENTAL VALIDATION Among 130 SNPs, 92 were validated as true polymorphisms when evaluated in a set of ten bean genotypes from Andean and Mesoamerican origin, including wild and cultivated forms. Simultaneous genotyping up to 15 alleles in one single base extension reaction (Figure 1) was achieved using a Luminex 100  flow cytometer equipped with a Luminex XY Platform plate reader.  Mean Fluorescence Intensity 1,200 1,000 800 600 400 200 0 G G G G 464 938 526 691 976 709 791 793 799 858 893 497 523 527 578 2,000 1,500 1,000 500 0 A A A A A A A A A A A 464 938 526 691 976 709 791 793 799 858 893 497 523 527 578 SNP ID Allele ‘A’ Allele ‘G’ Experimental validation, genetic map saturation and  gene flow pilot study in a  P. vulgaris   wild-weedy-crop complex with single nucleotide polymorphisms (SNPs) Constanza Quintero 1,2 ; R.I González-Torres 1 ; E. Gaitán-Solís 3 ; R. Hidalgo 2 ; O. Toro 4 ; D.G Debouck 4  and J. Tohme 1   1 CIAT, Biotechnology Research Unit, AA6713, Cali, Colombia;   2 Universidad Nacional de Colombia, Palmira, Colombia 3 Donald Danforth Plant Science Center , Missouri, USA;  4 CIAT, Genetic Resources Unit, Cali, Colombia;  [email_address] 84% of the validated SNPs had PIC > 0.3 which is considered to be high for these biallelic markers since the highest value achievable is 0.5.  Segregation data for 155 SNPs in 87 RILs of the DOR364/G19833 mapping population were obtained. 136 SNPs were added to the existing linkage map at a minimum LOD score of 4.0 using MAPMAKER/EXP (version 3.0) (Lander  et al. , 1987).   The resulting map has 470 markers and a total cumulative length of 1980cM. Each of the eleven  P. vulgaris  linkage groups had at least six SNP markers attached and B02 and B03 had the highest number of SNPs placed on them (n=23). In almost all linkage groups, SNPs mapped regions that were not previously covered by SSRs (Figure 2), after comparison of our map with the one published by Blair  et al.  (2003).  No association of individual SNPs nor SNP haplotypes with resistance to some isolates of angular leaf spot and of anthracnose, was encountered.  Figure 1. Multiplex genotyping of 15 SNP markers in DOR364 Figure 2. SNP location in the genetic map of DOR364/G19833. Saturated regions are shown by green bars next to the linkage groups. Red and blue labels correspond to common bean and soybean derived SNPs, respectively. GENE FLOW PILOT STUDY The study of “wild-weedy-crop” complexes along common bean range of distribution in the Americas has shown no preferential gene flow direction in Colombia, Ecuador and Peru (Chacón  et al , 2006). A pilot study in the wild-weedy-crop complex G50879 from Colombia (19, wild; 32 weedy and 34 cultivated), previously evaluated with biochemical markers and SSRs, was conducted to test the potential of SNP markers as an alternate tool for the identification of gene flow events and inference about their direction.   Initial admixture analysis   The admixture coefficient MY (Bertorelle & Excoffier, 1998) was calculated, based on haplotype frequencies and the molecular distances between them.  Background of the wild-weedy crop complex G50879 Block partition and haplotype prediction within each block was done using HAP software (Halperin and Eskin, 2004).  Both linkage groups, B01 and B07, were divided in three blocks of limited diversity.  43 SNP haplotypes were observed in the wild-weedy-crop complex: 84% in weedy forms, 77% in cultivated forms and 70% wild forms.  Haplotype inference: C C C C W C Wee Wee Wee C C Wee Chloroplast haplotypes and SSR most frequent alleles  were  shared between wild and cultivated types No clear discrimination between biological forms at the DNA level could be observed No gene flow direction could be determined Seed from the original collection sorrounded by wild, weedy and cultivated forms. ACKNOWLEDGEMENTS To the “Ginés-Mera Memorial Fellowship Fund  for Postgraduate Studies in Biodiversity” for partial funding of this research. Special thanks go to Drs  Perry Cregan and Charles Quigley  ( Soybean Genomics Lab-USDA) who kindly shared the information and primers of the soybean SNPs they discovered. To Héctor F. Buendía, Myriam C. Duque and Henry Terán for helpul comments. W C Block 1, B01 PIC = 0.70  Block 2, B01 PIC = 0.76 Block 1, B07 PIC = 0.73 Haplotype variant Frequency  (%) W W W C C C C C W C W W C C C W W C C W W C C Wild Weedy Cultivated SNP haplotypes frequency in the complex Admixture model   Differences between haplotype frequencies allowed the identification of those haplotypes that described better each of the parental biological forms. In most cases, haplotypes were classified as wild types when their frequency was at least twice the observed in cultivated forms, and vice versa.  In the weedy and wild-hybrid subpopulations, the contribution of truly-cultivated was slightly higher than that of truly-wild meaning that both gene flow directions are possible and almost symmetric. For the cultivated-hybrid, the contribution of truly-cultivated was twice that of the truly-wild, suggesting more pollen flow from the cultivated types. Although we have looked only at one wild-weedy-crop complex from Colombia our results show that SNP haplotypes are informative enough to provide evidence about gene flow dynamics in  P. vulgaris .  A more accurate estimation of admixture coefficients (S.D. values close to zero) in  the hybrid subpopulations was calculated. Parental truly-wild and truly-cultivated populations were selected based on the coincidence of their phenotype with their genotype (SNP haplotypes). After admixture events, they could give rise to three hybrid subpopulations in this wild-weedy-crop complex.  REFERENCES Bertorelle G, Excoffier L. 1998. Molecular Biology and Evolution.  15:1298-1311. Chacón, M.I. González-Torres, R.I. & D. G. Debouck.  2006. Council of Science. CIAT. 2006. Gaitán-Solís E, Choi IY, Quigley C, Cregan P, Tohme J. 2008. The Plant Genome. 1(2):125-134. Gupta, P.K., J.K. Roy & M. Prasad. 2001. Current Science, 80(4):524-535. Halperin E. and E. Eskin. 2004. Bioinformatics. 20(12):1842-9. Lander ES, Green P.,Abrahamson J., Barlow A, Daly MJ, Lincoln SE, Newburg L. 1987. Genomics, 1(2):174-181. Syvanen A., U. Landegren, A. Isaksson, U. Gyllensten & A. Brookes. 1999. European Journal of Human Genetics, 7: 98-101.

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Experimental validation, genetic map saturation and gene flow pilot study in a P. vulgaris wild-weedy-crop complex with single nucleotide polymorphisms (SNPs)

  • 1. INTRODUCTION Single nucleotide polymorphisms are becoming the marker of choice for a wide variety of organisms, due to their high abundance in genomes (Gupta et. al., 2001), their evolutionary stability and the availability of high throughput technologies for their detection (Syvanen et al., 1999). SNP discovery in common bean was initiated at CIAT in 2002 by Gaitán and Tohme who found 223 SNPs in 20964pb of P. vulgaris genome after sequencing PCR products of ten Andean and Mesoamerican genotypes. The purposes of this project were: 1) to validate, using multiplex techniques, the SNP markers developed at CIAT (Gaitán-Solís et. al , 2008) together with soybean-derived SNPs (developed at BARC-USDA); 2) to saturate the existing linkage map of the common bean DOR 364/G19833 cross and 3) to study the potential of SNP markers for determining the direction of gene flow in a wild-weedy-crop complex from Colombia. GENETIC MAPPING OF SNPs EXPERIMENTAL VALIDATION Among 130 SNPs, 92 were validated as true polymorphisms when evaluated in a set of ten bean genotypes from Andean and Mesoamerican origin, including wild and cultivated forms. Simultaneous genotyping up to 15 alleles in one single base extension reaction (Figure 1) was achieved using a Luminex 100 flow cytometer equipped with a Luminex XY Platform plate reader. Mean Fluorescence Intensity 1,200 1,000 800 600 400 200 0 G G G G 464 938 526 691 976 709 791 793 799 858 893 497 523 527 578 2,000 1,500 1,000 500 0 A A A A A A A A A A A 464 938 526 691 976 709 791 793 799 858 893 497 523 527 578 SNP ID Allele ‘A’ Allele ‘G’ Experimental validation, genetic map saturation and gene flow pilot study in a P. vulgaris wild-weedy-crop complex with single nucleotide polymorphisms (SNPs) Constanza Quintero 1,2 ; R.I González-Torres 1 ; E. Gaitán-Solís 3 ; R. Hidalgo 2 ; O. Toro 4 ; D.G Debouck 4 and J. Tohme 1 1 CIAT, Biotechnology Research Unit, AA6713, Cali, Colombia; 2 Universidad Nacional de Colombia, Palmira, Colombia 3 Donald Danforth Plant Science Center , Missouri, USA; 4 CIAT, Genetic Resources Unit, Cali, Colombia; [email_address] 84% of the validated SNPs had PIC > 0.3 which is considered to be high for these biallelic markers since the highest value achievable is 0.5. Segregation data for 155 SNPs in 87 RILs of the DOR364/G19833 mapping population were obtained. 136 SNPs were added to the existing linkage map at a minimum LOD score of 4.0 using MAPMAKER/EXP (version 3.0) (Lander et al. , 1987). The resulting map has 470 markers and a total cumulative length of 1980cM. Each of the eleven P. vulgaris linkage groups had at least six SNP markers attached and B02 and B03 had the highest number of SNPs placed on them (n=23). In almost all linkage groups, SNPs mapped regions that were not previously covered by SSRs (Figure 2), after comparison of our map with the one published by Blair et al. (2003). No association of individual SNPs nor SNP haplotypes with resistance to some isolates of angular leaf spot and of anthracnose, was encountered. Figure 1. Multiplex genotyping of 15 SNP markers in DOR364 Figure 2. SNP location in the genetic map of DOR364/G19833. Saturated regions are shown by green bars next to the linkage groups. Red and blue labels correspond to common bean and soybean derived SNPs, respectively. GENE FLOW PILOT STUDY The study of “wild-weedy-crop” complexes along common bean range of distribution in the Americas has shown no preferential gene flow direction in Colombia, Ecuador and Peru (Chacón et al , 2006). A pilot study in the wild-weedy-crop complex G50879 from Colombia (19, wild; 32 weedy and 34 cultivated), previously evaluated with biochemical markers and SSRs, was conducted to test the potential of SNP markers as an alternate tool for the identification of gene flow events and inference about their direction. Initial admixture analysis The admixture coefficient MY (Bertorelle & Excoffier, 1998) was calculated, based on haplotype frequencies and the molecular distances between them. Background of the wild-weedy crop complex G50879 Block partition and haplotype prediction within each block was done using HAP software (Halperin and Eskin, 2004). Both linkage groups, B01 and B07, were divided in three blocks of limited diversity. 43 SNP haplotypes were observed in the wild-weedy-crop complex: 84% in weedy forms, 77% in cultivated forms and 70% wild forms. Haplotype inference: C C C C W C Wee Wee Wee C C Wee Chloroplast haplotypes and SSR most frequent alleles were shared between wild and cultivated types No clear discrimination between biological forms at the DNA level could be observed No gene flow direction could be determined Seed from the original collection sorrounded by wild, weedy and cultivated forms. ACKNOWLEDGEMENTS To the “Ginés-Mera Memorial Fellowship Fund for Postgraduate Studies in Biodiversity” for partial funding of this research. Special thanks go to Drs Perry Cregan and Charles Quigley ( Soybean Genomics Lab-USDA) who kindly shared the information and primers of the soybean SNPs they discovered. To Héctor F. Buendía, Myriam C. Duque and Henry Terán for helpul comments. W C Block 1, B01 PIC = 0.70 Block 2, B01 PIC = 0.76 Block 1, B07 PIC = 0.73 Haplotype variant Frequency (%) W W W C C C C C W C W W C C C W W C C W W C C Wild Weedy Cultivated SNP haplotypes frequency in the complex Admixture model Differences between haplotype frequencies allowed the identification of those haplotypes that described better each of the parental biological forms. In most cases, haplotypes were classified as wild types when their frequency was at least twice the observed in cultivated forms, and vice versa. In the weedy and wild-hybrid subpopulations, the contribution of truly-cultivated was slightly higher than that of truly-wild meaning that both gene flow directions are possible and almost symmetric. For the cultivated-hybrid, the contribution of truly-cultivated was twice that of the truly-wild, suggesting more pollen flow from the cultivated types. Although we have looked only at one wild-weedy-crop complex from Colombia our results show that SNP haplotypes are informative enough to provide evidence about gene flow dynamics in P. vulgaris . A more accurate estimation of admixture coefficients (S.D. values close to zero) in the hybrid subpopulations was calculated. Parental truly-wild and truly-cultivated populations were selected based on the coincidence of their phenotype with their genotype (SNP haplotypes). After admixture events, they could give rise to three hybrid subpopulations in this wild-weedy-crop complex. REFERENCES Bertorelle G, Excoffier L. 1998. Molecular Biology and Evolution. 15:1298-1311. Chacón, M.I. González-Torres, R.I. & D. G. Debouck. 2006. Council of Science. CIAT. 2006. Gaitán-Solís E, Choi IY, Quigley C, Cregan P, Tohme J. 2008. The Plant Genome. 1(2):125-134. Gupta, P.K., J.K. Roy & M. Prasad. 2001. Current Science, 80(4):524-535. Halperin E. and E. Eskin. 2004. Bioinformatics. 20(12):1842-9. Lander ES, Green P.,Abrahamson J., Barlow A, Daly MJ, Lincoln SE, Newburg L. 1987. Genomics, 1(2):174-181. Syvanen A., U. Landegren, A. Isaksson, U. Gyllensten & A. Brookes. 1999. European Journal of Human Genetics, 7: 98-101.