Genome-wide association and genomic prediction identifies soybean cyst nematode resistance in common bean including a syntenic region to soybean Rhg1 locus

Abstract

A genome-wide association study (GWAS) was applied to detect single nucleotide polymorphisms (SNPs) significantly associated with resistance to Heterodera glycines (HG) also known as the soybean cyst nematode (SCN) in the core collection of common bean, Phaseolus vulgaris. There were 84,416 SNPs identified in 363 common bean accessions. GWAS identified SNPs on chromosome (Chr) 1 that were significantly associated with resistance to HG type 2.5.7. These SNPs were in linkage disequilibrium with a gene cluster orthologous to the three genes at the Rhg1 locus in soybean. A novel signal on Chr 7 was detected and associated with resistance to HG type 1.2.3.5.6.7. Genomic predictions (GPs) for resistance to these two SCN HG types in common bean achieved prediction accuracy of 0.52 and 0.41, respectively. Our study generated a high-quality SNP panel for 363 common bean accessions and demonstrated that both GWAS and GP were effective strategies to understand the genetic architecture of SCN resistance in common bean.

References

[1] Broughton, W. J. et al. Beans (Phaseolus spp.)-model food legumes . Plant Soil 252, 55-128 (2003).

[2] McClean, P. E., Kami, J. & Gepts, P. Genomics and genetic diversity in common bean. In Legume Crop Genomics (eds Wilson, R. et al. ) 60-82 (AOCS Press, Champaign, IL, USA, 2004).

[3] Singh, S. P., Gepts, P. & Debouck, D. G. Races of common bean (Phaseolus vulgaris, Fabaceae) . Econ. Bot. 45, 379-396 (1991).

[4] Singh, S. P. & Schwartz, H. F. Breeding common bean for resistance to diseases: a review. Crop Sci. 50, 2199-2223 (2010).

[5] Hartman, G. L. Worldwide importance of soybean pathogens and pests. In Compendium of Soybean Diseases and Pests (eds Hartman, G. L. et al. ) 4-5 (American Phytopathological Society, St. Paul, 2015).

[6] McCarville, M. T., Marett, C., Mullaney, M., Gebhart, G. & Tylka, G. L. Increase in soybean cyst nematode virulence and reproduction on resistant soybean varieties in Iowa from 2001 to 2015 and the effects on soybean yields. Plant Health Prog. 18, 146-155 (2017).

[7] Tylka, G. L. & Marett, C. Known distribution of the soybean cyst nematode, Heterodera glycines, in the United States and Canada, 1954 to 2017 . Plant Health Prog. 18, 167-168 (2017).

[8] Abawi, G. S. & Jacobsen, B. J. Effect of initial inoculum densities of Heterodera glycines on growth of soybean and kidney bean and their efficiency as hosts under greenhouse conditions . Phytopathology 74, 1470-1474 (1984).

[9] Melton, T. A., Noel, G. R., Jacobsen, B. J. & Hagedorn, D. J. Comparative host suitabilities of snap beans to the soybean cyst nematode (Heterodera glycines) . Plant Dis. 69, 119-122 (1985).

[10] Poromarto, S. & Nelson, B. Reproduction of soybean cyst nematode on dry bean cultivars adapted to North Dakota and northern Minnesota. Plant Dis. 93, 507-511 (2009).

[11] Poromarto, S., Nelson, B. & Goswami, R. Effect of soybean cyst nematode on growth of dry bean in the field. Plant Dis. 94, 1299-1304 (2010).

[12] Mitchum, M. G. Soybean resistance to the soybean cytst nematode Heterodera glycines: an update . Phytopathology 106, 1444-1450 (2016).

[13] Bao, Y. et al. Potential of association mapping and genomic selection to explore PI 88788 derived soybean cyst nematode resistance. Plant Genome 7, 1-13 (2014).

[14] Cook, D. E. et al. Copy number variation of multiple genes at Rhg1 mediates nematode resistance in soybean . Science 338, 1206-1209 (2012).

[15] Liu, S. et al. A soybean cyst nematode resistance gene points to a new mechanism of plant resistance to pathogens. Nature 492, 256-260 (2012).

[16] Concibido, V. C., Diers, B. W. & Arelli, P. R. A decade of QTL mapping for cyst nematode resistance in soybean. Crop Sci. 44, 1121-1131 (2004).

[17] Guo, B., Sleper, D., Arelli, P. R., Shannon, J. G. & Nguyen, H. T. Identification of QTLs associated with resistance to soybean cyst nematode races 2, 3 and 5 in soybean PI 90763. Theor. Appl. Genet. 111, 965-971 (2005).

[18] Vuong, T. D. et al. Genetic architecture of cyst nematode resistance revealed by genome-wide association study in soybean. BMC Genom., https://doi.org/10.1186/s12864-015-1811-y (2015).

[19] Han, Y. et al. Genetic characteristics of soybean resistance to HG type 0 and HG type 1.2.3.5.7 of the cyst nematode analyzed by genome-wide association mapping. BMC Genom. 16, 598 (2015).

[20] Chang, H.-X., Lipka, A., Domier, L. L. & Hartman, G. L. Characterization of disease resistance loci in the USDA Soybean Germplasm collection using genome-wide associations. Phytopathology 106, 1139-1151 (2016).

[21] Zhang, H. & Song, B.-H. RNA-seq data comparisons of wild soybean genotypes in response to soybean cyst nematode (Heterodera glycines) . Genom. Data 14, 36-39 (2017).

[22] Shi, C., Navabi, A. & Yu, K. Association mapping of common bacterial blight resistance QTL in Ontario bean breeding populations. BMC Plant Biol. 11, 1 (2011).

[23] Nemli, S. et al. Association mapping for five agronomic traits in the common bean (Phaseolus vulgaris L.) . J. Sci. Food Agr. 94, 3141-3151 (2014).

[24] Crossa, J. et al. Genomic selection and prediction in plant breeding. J. Crop Improv. 25, 239-261 (2011).

[25] Desta, Z. A. & Ortiz, R. Genomic selection: genome-wide prediction in plant improvement. Trends Plant Sci. 19, 592-601 (2014).

[26] Newell, M. A. & Jannink, J. L. Genomic selection in plant breeding. Methods Mol. Biol. 1145, 117-130 (2014).

[27] Chapman, B. P., Weiss, A. & Duberstein, P. Statistical learning for high dimensional prediction: application to criterion-keyed scale development. Psychol. Methods 21, 603-620 (2016).

[28] Gianola, D. Priors in whole-genome regression: the Bayesian alphabet returns. Genetics 194, 573-596 (2013).

[29] Chang, H.-X., Brown, P., Lipka, A., Domier, L. L. & Hartman, G. L. Genome-wide association and genomic prediction identifies associated loci and predicts the sensitivity of Tobacco ringspot virus in soybean plant introductions. BMC Genom. 17, 153 (2016).

[30] Lorenz, A. J., Smith, K. P. & Jannink, J.-L. Potential and optimization of genomic selection for Fusarium head blight resistance in six-row barley. Crop Sci. 52, 1609-1621 (2012).

[31] Rutkoski, J. et al. Genomic selection for quantitative adult plant stem rust resistance in wheat. Plant Genome 7, https://dx.doi.org/10.3835/plantgenome2014.02.0006 (2014).

[32] Tibshirani, R . Regression shrinkage and selection via the Lasso. J. R. Stat. Soc. Ser. B Stat. Methodol. 58, 267-288 (1996).

[33] Yi, N. & Xu, S. Bayesian LASSO for quantitative trait loci mapping. Genetics 179, 1045-1055 (2008).

[34] Svetnik, V., Liaw, A., Tong, C., Culberson, J. C. & Sheridan, R. P. Random forest: a classification and regression tool for compound classification and QSAR modelling. J. Chem. Inf. Comput. Sci. 43, 1947-1058 (2003).

[35] De los Campos, G., Gianola, D., Rosa, G. J., Weigel, K. A. & Crossa, J. Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods. Genet. Res. 92, 295-308 (2010).

[36] Browning, S. R. & Browning, B. L. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am. J. Hum. Genet. 81, 1064-1097 (2007).

[37] Wang, J. et al. Development and application of a novel genome-wide SNP array reveals domestication history in soybean. Sci. Rep. 9, 20728 (2016).

[38] Bassett, M. J. A new allele (Vwf) at the V locus for flower and seed coat color in common bean . J. Am. Soc. Hortic. Sci. 122, 519-521 (1997).

[39] McClean, P. E., Lee, R. K., Otto, C., Gepts, P. & Bassett, M. J. Molecular and phenotypic mapping of genes controlling seed coat pattern and color in common bean (Phaseolus vulgaris L.) . J. Hered. 93, 148-152 (2002).

[40] Nodari, R. O., Tsail, S. M., Gilbertson, R. L. & Gepts, P. Towards an integrated linkage map of common bean 2. Development of an RFLP-based linkage map. Theor. Appl. Genet. 85, 513-520 (1993).

[41] Blair, M. W., Iriarte, G. & Beebe, S. QTL analysis of yield traits in an advanced backcross population derived from a cultivated Andean wild common bean (Phaseolus vulgaris L.) cross . Theor. Appl. Genet. 112, 1149-1163 (2006).

[42] Park, S. O. et al. Mapping of QTL for seed size and shape traits in common bean. J. Am. Soc. Hortic. Sci. 125, 466-475 (2000).

[43] Tsai, S. M. et al. QTL mapping for nodule number and common bacterial blight in Phaseolus vulgaris L. . Plant Soil 204, 135-145 (1998).

[44] Schmutz, J. et al. A reference genome for common bean and genome-wide analysis of dual domestications. Nat. Genet. 46, 707-713 (2014).

[45] Concibido, V. et al. Targeted comparative genome analysis and qualitative mapping of a major partial-resistance gene to the soybean cyst nematode. Theor. Appl. Genet. 93, 234-241 (1995).

[46] Gepts, P. & Bliss, F. A. Phaseolin variability among wild and cultivated common beans (Phaseolus vulgaris) from Colombia . Econ. Bot. 40, 469-478 (1986).

[47] Li, J., Dai, X., Liu, T. & Zhao, P. X. LegumeIP: an integrative database for comparative genomics and transcriptomics of model legumes. Nucleic Acids Res. 40, D1221-D1229 (2012).

[48] Kelly, J. D., Gepts, P., Miklas, P. N. & Coyne, D. P. Tagging and mapping of genes and QTL and molecular marker-assisted selection for traits of economic importance in bean and cowpea. Field Crops Res. 82, 135-154 (2003).

[49] Schlueter, J. A. et al. Mining the EST databases to determine evolutionary events in the legumes and grasses. Genome 47, 868-876 (2004).

[50] Combs, E. & Bernardo, R. Accuracy of genome wide selection for different traits with constant population size, heritability, and number of markers. Plant Gemone 6, 1-7 (2013).

[51] Brick, M. A. et al. Reaction to three races of Fusarium wilt in the core collection. Crop Sci. 46, 1245-1252 (2006).

[52] McClean, P. E. et al. Population structure and genetic differentiation among the USDA common bean (Phaseolus vulgaris L.) core collection . Genet. Resour. Crop Evol. 59, 499-515 (2012).

[53] Doyle, J. & Doyle, J. L. Genomic plant DNA preparation from fresh tissue-CTAB method. Phytochem. Bull. 19, 11-15 (1987).

[54] Thurber, C. S., Ma, J. M., Higgins, R. H. & Brown, P. J. Retrospective genomic analysis of sorghum adaptation to temperate-zone grain production. Genome Biol. 14, 12 (2013).

[55] Glaubitz, J. C. et al. TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline. PLoS One 9, e90346 (2014).

[56] Sonah, H., Bastien, M., Iquira, E., Tardivel, A. & Légaré, G. An improved genotyping by sequencing (GBS) approach offering increased versatility and efficiency of SNP discovery and genotyping. PLoS One 8, e54603 (2013).

[57] Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357-359 (2012).

[58] Browning, B. L. & Browning, S. R. Improving the accuracy and efficiency of identity by descent detection in population data. Genetics 194, 459-471 (2013).

[59] Niblack, T. L. et al. A revised classification scheme for genetically diverse populations of Heterodera glycines . J. Nematol. 34, 279-288 (2002).

[60] Niblack, T. L. et al. A standard greenhouse method for assessing a soybean cyst nematode resistance in soybean: SCE08 (standardized cyst evaluation 2008). In Plant Health Progress (Plant Management Network, 2009).

[61] Lipka, A. et al. GAPIT: genome association and prediction integrated tool. Bioinformatics 28, 2397-2399 (2012).

[62] Zhang, Z. et al. Mixed linear model approach adapted for genome-wide association studies. Nat. Genet. 42, 355-360 (2010).