Advertisement

Molecular Breeding

, 39:37 | Cite as

Development of multiple SNP marker panels affordable to breeders through genotyping by target sequencing (GBTS) in maize

  • Zifeng Guo
  • Hongwu Wang
  • Jiajun Tao
  • Yonghong Ren
  • Cheng Xu
  • Kunsheng Wu
  • Cheng Zou
  • Jianan ZhangEmail author
  • Yunbi XuEmail author
Article
  • 439 Downloads

Abstract

The development of a high-throughput genotyping platform with high quality, flexibility, and affordable genotyping cost is critical for marker-assisted breeding. In this study, a genotyping by target sequencing (GBTS) platform was developed in maize, which can be realized for a small number of markers (several to 5 K) through multiplex PCR (GenoPlexs) and for a large number of markers (1 to 45 K) through in-solution capture. The later was used for development of four SNP marker panels (GenoBaits Maize) containing 20 K, 10 K, 5 K, and 1 K markers. Two genotype panels, one consisting 96 representative worldwide maize inbred lines and the other containing 387 breeding lines developed in our maize breeding programs, were used to test and validate the developed marker panels. First, a 20 K SNP panel, with markers evenly distributed across maize genome, was developed from a 55 K SNP array with improved genome coverage. From this single marker panel, 20 K, 10 K, 5 K, and 1 K SNP markers can be generated by sequencing the samples at the average sequencing depths of 50×, 20×, 7.5×, and 2.5×, respectively. Highly consistent marker genotypes were obtained between the four marker panels and the 55 K array (over 95%) and between two biological replications (over 98%). Also, highly consistent phylogenetic relationships were generated by using four marker panels and two genotype panels, providing strong evidence for the reliability of SNP markers and GBTS genotyping platform. Cost-benefit analysis indicated that the genotypic selection cost based on the GBTS in maize was lower than phenotypic selection, allowing GBTS an affordable genotyping platform for marker-assisted breeding. Integration of this affordable genotyping platform with other breeding platforms and open-source breeding network would greatly facilitate the molecular breeding activities in small- and medium-size companies and developing countries. The four marker panels could be used for many fields of marker application, including germplasm evaluation, genetic mapping, marker-assisted selection (including genomic selection), and plant variety protection.

Keywords

Maize Single nucleotide polymorphism(SNP) Genotyping by target sequencing(GBTS) Molecular breeding Marker-assisted selection 

Notes

Funding information

This research is supported by the National Key Research and Development Program of China (2016YFD0101201 and 2017YFD0101201) and the Agricultural Science and Technology Innovation Program (ASTIP) of Chinese Academy of Agricultural Sciences (CAAS) (CAAS-XTCX2016009), and Research activities of CIMMYT staff were supported by the Bill and Melinda Gates Foundation and the CGIAR Research Program MAIZE.

Supplementary material

11032_2019_940_MOESM1_ESM.pdf (264 kb)
Supplementary Fig. 1 Distribution of minor allele frequency (MAF) for maize 20 K SNP marker panel as revealed by 96 representative inbred lines (96-genotype panel) (PDF 263 kb)
11032_2019_940_MOESM2_ESM.pdf (285 kb)
Supplementary Fig. 2 Distribution of polymorphic information contents (PICs) for four marker panels using 96 representative inbred lines (96-genotype panel) (PDF 284 kb)
11032_2019_940_MOESM3_ESM.pdf (296 kb)
Supplementary Fig. 3 Distribution of gene diversity (GD) as revealed by 96 maize inbred lines (96-genotype panel) and four marker panels (PDF 295 kb)
11032_2019_940_MOESM4_ESM.pdf (284 kb)
Supplementary Fig. 4 Distribution of polymorphic rates as revealed by 96 maize inbred lines (96-genotype panel) and four marker panels (PDF 284 kb)
11032_2019_940_MOESM5_ESM.pdf (1.8 mb)
Supplementary Fig. 5 Phylogenetic trees constructed using 387 maize breeding lines and 96 representative maize inbred lines (483 genotypes) (PDF 1883 kb)
11032_2019_940_MOESM6_ESM.xlsx (15 kb)
Supplementary Table 1 The 96 diverse maize inbred lines (96-genotype panel) were used in this study (XLSX 14 kb)
11032_2019_940_MOESM7_ESM.xlsx (24 kb)
Supplementary Table 2 The 387 breeding lines (387-genotype panel) selected from the ongoing breeding programs at CAAS (XLSX 24 kb)
11032_2019_940_MOESM8_ESM.xlsx (13 kb)
Supplementary Table 3 Pairwise differences among eight heterotic groups of maize inbred lines as revealed by four marker panels. The lower diagonal are the average genetic distances between groups. The diagonal cells are pairwise nucleotide diversities within groups (XLSX 13 kb)
11032_2019_940_MOESM9_ESM.xlsx (14 kb)
Supplementary Table 4 The field cost involved in phenotypic selection across three experimental stations in China (XLSX 14 kb)
11032_2019_940_MOESM10_ESM.xlsx (13 kb)
Supplementary Table 5 Savings that can be achieved by marker-assisted selection for Fusarium verticillioides ear rot across three experimental stations in China (XLSX 13 kb)

References

  1. Baird NA, Etter PD, Atwood TS, Currey MC, Shiver AL, Lewis ZA, Selker EU, Cresko WA, Johnson EA (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS One 3:e3376CrossRefGoogle Scholar
  2. Bernardo R (2008) Molecular marker and selection for complex traits in plants: learning from the last 20 years. Crop Sci 48:1649–1664CrossRefGoogle Scholar
  3. Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphism. Am J Hum Genet 32:314–331PubMedPubMedCentralGoogle Scholar
  4. Collard BC, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos Trans R Soc London Ser B 363:557–572CrossRefGoogle Scholar
  5. Davey JW, Hohenlohe PA, Etter PD, Boone JQ, Catchen JM, Blaxter ML (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet 12:499–510CrossRefGoogle Scholar
  6. Dreher K, Khairallah M, Ribaut JM, Morris M (2003) Money matters (I): costs of field and laboratory procedures associated with conventional and marker-assisted maize breeding at CIMMYT. Mol Breed 11:221–234CrossRefGoogle Scholar
  7. Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6:e19379CrossRefGoogle Scholar
  8. Fan JB, Oliphant A, Shen R, Kermani BG, Garcia F, Gunderson KL, Hansen M, Steemers F, Butler SL, Deloukas P, Galver L, Hunt S, McBride C, Bibikova M, Rubano T, Chen J, Wickham E, Doucet D, Chang W, Campbell D, Zhang B, Kruglyak S, Bentley D, Haas J, Rigault P, Zhou L, Stuelpnagel J, Chee MS (2003) Highly parallel SNP genotyping. Cold Spring Harb Symp Quant Biol 68:69–78CrossRefGoogle Scholar
  9. Ganal MW, Durstewitz G, Polley A, Bérard A, Buckler ES, Charcosset A, Clarke JD, Graner EM, Joets J, Le Paslier MC, McMullen MD, Montalent P, Rose M, Schön CC, Sun Q, Walter H, Martin OC, Falque M (2011) A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. PLoS One 6:e28334CrossRefGoogle Scholar
  10. Huang X, Wei X, Sang T, Zhao Q, Feng Q, Zhao Y, Li C, Zhu C, Lu T, Zhang Z, Li M, Fan D, Guo Y, Wang A, Wang L, Deng L, Li W, Lu Y, Weng Q, Liu K, Huang T, Zhou T, Jing Y, Li W, Lin Z, Buckler ES, Qian Q, Zhang Q, Li JY, Han B (2010) Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet 42:961–967CrossRefGoogle Scholar
  11. Huang YF, Poland JA, Wight CP, Jackson EW, Tinker NA (2014) Using genotyping-by-sequencing (GBS) for genomic discovery in cultivated oat. PLoS One 9:e102448CrossRefGoogle Scholar
  12. Hyten DL, Song Q, Choi IY, Yoon MS, Specht JE, Matukumalli LK, Nelson RL, Shoemaker RC, Young ND, Cregan PB (2008) High-throughput genotyping with the GoldenGate assay in the complex genome of soybean. Theor Appl Genet 116:945–952CrossRefGoogle Scholar
  13. Jiang L, Liu X, Yang J, Wang H, Jiang J, Liu L, He S, Ding X, Liu J, Zhang Q (2014) Targeted resequencing of GWAS loci reveals novel genetic variants for milk production traits. BMC Genomics 15:1105PubMedPubMedCentralGoogle Scholar
  14. Krasileva KV, Vasquez-Gross HA, Howell T, Bailey P, Paraiso F, Clissold L, Simmonds J, Ramirez-Gonzalez RH, Wang X, Borrill P, Fosker C, Ayling S, Phillips AL, Uauy C, Dubcovsky J (2017) Uncovering hidden variation in polyploid wheat. Proc Natl Acad Sci U S A 114:E913–E921CrossRefGoogle Scholar
  15. Kuchel H, Ye GY, Fox R, Jefferies S (2005) Genetic and economic analysis of a targeted marker-assisted wheat breeding strategy. Mol Breed 16:67–78CrossRefGoogle Scholar
  16. Li L, Fang Z, Zhou J, Chen H, Hu Z, Gao L, Chen L, Ren S, Ma H, Lu L, Zhang W, Peng H (2017) An accurate and efficient method for large-scale SSR genotyping and applications. Nucleic Acids Res 45:e88CrossRefGoogle Scholar
  17. Liu K, Goodman M, Muse S, Smith JS, Buckler E, Doebley J (2003) Genetic structure and diversity among maize inbred lines as inferred from DNA microsatellites. Genetics 165:2117–2128PubMedPubMedCentralGoogle Scholar
  18. Lu Y, Yan J, Guimarães CT, Taba S, Hao Z, Gao S, Chen S, Li J, Zhang S, Vivek BS, Magorokosho C, Mugo S, Makumbi D, Parentoni SN, Shah T, Rong T, Crouch JH, Xu Y (2009) Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms. Theor Appl Genet 120:93–115CrossRefGoogle Scholar
  19. Mamanova L, Coffey AJ, Scott CE, Kozarewa I, Turner EH, Kumar A, Howard E, Shendure J, Turner DJ (2010) Target-enrichment strategies for next-generation sequencing. Nat Methods 7:111–118CrossRefGoogle Scholar
  20. Prasanna BM, Pixley K, Warburton ML, Xie CX (2010) Molecular marker-assisted breeding options for maize improvement in Asia. Mol Breed 26:339–356CrossRefGoogle Scholar
  21. Rasheed A, Hao YF, Xia XC, Khan A, Xu YB, RK HZH (2017) Crop breeding chips and genotyping platforms: progress, challenges, and perspectives. Mol Plant 10:1047–1064CrossRefGoogle Scholar
  22. Rousselle Y, Jones E, Charcosset A, Moreau P, Robbins K, Stich B, Knaak C, Flament P, Karaman Z, Martinant JP, Fourneau M, Taillardat A, Romestant M, Tabel C, Bertran J, Ranc N, Lespinasse D, Blanchard P, Kahler A, Chen J, Kahler J, Dobrin S, Warner T, Ferris R, Smith S (2015) Study on essential derivation in maize: III. Selection and evaluation of a panel of single nucleotide polymorphism loci for use in European and North American germplasm. Crop Sci 55:1170–1180CrossRefGoogle Scholar
  23. Saghai-Maroof MA, Soliman KM, Jorgensen RA, Allard RW (1984) Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proc Natl Acad Sci U S A 81:8014–8018CrossRefGoogle Scholar
  24. Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetics trees. Mol Biol Evol 4:406–425PubMedGoogle Scholar
  25. Samorodnitsky E, Datta J, Jewell BM, Hagopian R, Miya J, Wing MR, Damodaran S, Lippus JM, Reeser JW, Bhatt D, Timmers CD, Roychowdhury S (2015) Comparison of custom capture for targeted next-generation DNA sequencing. J Mol Diagn 17:64–75CrossRefGoogle Scholar
  26. Schlötterer C, Tobler R, Kofler R, Nolte V (2014) Sequencing pools of individuals—mining genome-wide polymorphism data without big funding. Nucleic Acids Res 15:749–763Google Scholar
  27. Semagn K, Babu R, Hearne S, Olsen M (2013) Single nucleotide polymorphism genotyping using Kompetitive allele specific PCR (KASP): overview of the technology and its application in crop improvement. Mol Breed 33:1–14CrossRefGoogle Scholar
  28. Tanksley SD, Young ND, Paterson AH, Bonierbale MW (1989) RFLP mapping in plant breeding: new tools for an old science. Bio/Technology 7:257–264Google Scholar
  29. Unterseer S, Bauer E, Haberer G, Seidel M, Knaak C, Ouzunova M, Meitinger T, Strom TM, Fries R, Pausch H, Bertani C, Davassi A, Mayer KF, Schön CC (2014) A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array. BMC Genomics 15:823CrossRefGoogle Scholar
  30. Wu X, Li Y, Shi Y, Song Y, Wang T, Huang Y, Li Y (2014) Fine genetic characterization of elite maize germplasm using high-throughput SNP genotyping. Theor Appl Genet 127:621–631CrossRefGoogle Scholar
  31. Xu C, Ren Y, Jian Y, Guo Z, Zhang Y, Xie C, Fu J, Wang H, Wang G, Xu Y, Li P, Zou C (2017b) Development of a maize 55K SNP array with improved genome coverage for molecular breeding. Mol Breed 37:20CrossRefGoogle Scholar
  32. Xu Y (2003) Developing marker-assisted selection in plant breeding hybrid rice. Plant Breed Rev 23:73–174Google Scholar
  33. Xu Y (2010) Molecular plant breeding. CABI Publishing, WallingfordCrossRefGoogle Scholar
  34. Xu Y, Crouch JH (2008) Marker-assisted selection in plant breeding: from publications to practice. Crop Sci 48:391–407CrossRefGoogle Scholar
  35. Xu Y, Li P, Zou C, Lu YL, Xie C, Zhang X, Prasanna BM, Olsen MS (2017a) Enhancing genetic gain in the era of molecular breeding. J Exp Bot 68:2641–2666CrossRefGoogle Scholar
  36. Yan J, Yang X, Shah T, Sánchez H, Li J, Warburton M, Zhou Y, Crouch JH, Xu Y (2010) High-throughput SNP genotyping with the GoldenGate assay in maize. Mol Breed 25:441–451CrossRefGoogle Scholar
  37. Yang L, Yin X, Wu L, Chen N, Zhang H, Li G, Ma Z (2013) Targeted exome capture and sequencing identifies novel PRPF31 mutations in autosomal dominant retinitis pigmentosa in Chinese families. BMJ Open 3:e004030CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Zifeng Guo
    • 1
  • Hongwu Wang
    • 1
  • Jiajun Tao
    • 2
  • Yonghong Ren
    • 3
  • Cheng Xu
    • 1
  • Kunsheng Wu
    • 2
  • Cheng Zou
    • 1
  • Jianan Zhang
    • 2
    • 4
    Email author
  • Yunbi Xu
    • 1
    • 5
    Email author
  1. 1.Institute of Crop ScienceChinese Academy of Agricultural SciencesBeijingChina
  2. 2.Mol Breeding Biotechnology Co., Ltd.ShijiazhuangChina
  3. 3.CapitalBio Technology Corporation, 18 Life Science ParkwayBeijingChina
  4. 4.National Foxtail Millet Improvement Center, Minor Cereal Crops Laboratory of Hebei Province, Institute of Millet CropsHebei Academy of Agriculture and Forestry SciencesShijiazhuangChina
  5. 5.International Maize and Wheat Improvement Center (CIMMYT)TexcocoMexico

Personalised recommendations