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Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations

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An Erratum to this article was published on 31 October 2015

Abstract

Genotyping by sequencing (GBS) is the latest application of next-generation sequencing protocols for the purposes of discovering and genotyping SNPs in a variety of crop species and populations. Unlike other high-density genotyping technologies which have mainly been applied to general interest “reference” genomes, the low cost of GBS makes it an attractive means of saturating mapping and breeding populations with a high density of SNP markers. One barrier to the widespread use of GBS has been the difficulty of the bioinformatics analysis as the approach is accompanied by a high number of erroneous SNP calls which are not easily diagnosed or corrected. In this study, we use a 384-plex GBS protocol to add 30,984 markers to an indica (IR64) × japonica (Azucena) mapping population consisting of 176 recombinant inbred lines of rice (Oryza sativa) and we release our imputation and error correction pipeline to address initial GBS data sparsity and error, and streamline the process of adding SNPs to RIL populations. Using the final imputed and corrected dataset of 30,984 markers, we were able to map recombination hot and cold spots and regions of segregation distortion across the genome with a high degree of accuracy, thus identifying regions of the genome containing putative sterility loci. We mapped QTL for leaf width and aluminum tolerance, and were able to identify additional QTL for both phenotypes when using the full set of 30,984 SNPs that were not identified using a subset of only 1,464 SNPs, including a previously unreported QTL for aluminum tolerance located directly within a recombination hotspot on chromosome 1. These results suggest that adding a high density of SNP markers to a mapping or breeding population through GBS has a great value for numerous applications in rice breeding and genetics research.

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References

  • Almeida GD, Makumbi D, Magorokosho C, Nair S, Borem A, Ribaut JM, Banziger M, Prasanna BM, Crossa J, Babu R (2013) QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance. Theor Appl Genet 126(3):583–600. doi:10.1007/s00122-012-2003-7

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • 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(10):e3376. doi:10.1371/journal.pone.0003376

    Article  PubMed Central  PubMed  Google Scholar 

  • Bradbury PJ, Zhang Z, Dallas EK, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635

    Article  CAS  PubMed  Google Scholar 

  • Chen MS, Presting G, Barbazuk WB, Goicoechea JL, Blackmon B, Fang FC, Kim H, Frisch D, Yu YS, Sun SH, Higingbottom S, Phimphilai J, Phimphilai D, Thurmond S, Gaudette B, Li P, Liu JD, Hatfield J, Main D, Farrar K, Henderson C, Barnett L, Costa R, Williams B, Walser S, Atkins M, Hall C, Budiman MA, Tomkins JP, Luo MZ, Bancroft I, Salse J, Regad F, Mohapatra T, Singh NK, Tyagi AK, Soderlund C, Dean RA, Wing RA (2002) An integrated physical and genetic map of the rice genome. Plant Cell 14(3):537–545. doi:10.1105/tpc.010485

    Article  PubMed Central  PubMed  Google Scholar 

  • Clark RT, MacCurdy RB, Jung JK, Shaff JE, McCouch SR, Aneshansley DJ, Kochian LV (2011) Three-dimensional root phenotyping with a novel imaging and software platform. Plant Physiol 156(2):455–465. doi:10.1104/pp.110.169102

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Darvasi A, Weinreb A, Minke V, Weller JI, Soller M (1993) Detecting marker-QTL linkage and estimating QTL gene effect and map location using a saturated genetic map. Genetics 134(3):943–951

    PubMed Central  CAS  PubMed  Google Scholar 

  • 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(7):499–510

    Article  CAS  PubMed  Google Scholar 

  • Dupuis J, Siegmund D (1999) Statistical methods for mapping quantitative trait loci from a dense set of markers. Genetics 151(1):373–386

    PubMed Central  CAS  PubMed  Google Scholar 

  • Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011a) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 6(5):e19379. doi:10.1371/journal.pone.0019379

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011b) Powerpoint presentation: reduced representation sequencing for rapidly genotyping highly diverse species

  • Famoso AN, Zhao K, Clark RT, Tung C-W, Wright MH, Bustamante C, Kochian LV, McCouch SR (2011) Genetic architecture of aluminum tolerance in rice (Oryza sativa) determined through genome-wide association analysis and QTL mapping. PLoS Genet 7(8):e1002221. doi:10.1371/journal.pgen.1002221

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Feltus FA, Wan J, Schulze SR, Estill JC, Jiang N, Paterson AH (2004) An SNP resource for rice genetics and breeding based on subspecies Indica and Japonica genome alignments. Genome Res 14(9):1812–1819. doi:10.1101/gr.2479404

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Garavito A, Guyot R, Lozano J, Gavory F, Samain S, Panaud O, Tohme J, Ghesquière A, Lorieux M (2010) A genetic model for the female sterility barrier between Asian and African cultivated rice species. Genetics 185(4):1425–1440. doi:10.1534/genetics.110.116772

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Harushima Y, Yano M, Shomura A, Sato M, Shimano T, Kuboki Y, Yamamoto T, Lin SY, Antonio BA, Parco A, Kajiya H, Huang N, Yamamoto K, Nagamura Y, Kurata N, Khush GS, Sasaki T (1998) A high-density rice genetic linkage map with 2275 markers using a single F2 population. Genetics 148(1):479–494

    PubMed Central  CAS  PubMed  Google Scholar 

  • Harushima Y, Nakagahra M, Yano M, Sasaki T, Kurata N (2001) A genome-wide survey of reproductive barriers in an intraspecific hybrid. Genetics 159(2):883–892

    PubMed Central  CAS  PubMed  Google Scholar 

  • Harushima Y, Nakagahra M, Yano M, Sasaki T, Kurata N (2002) Diverse variation of reproductive barriers in three intraspecific rice crosses. Genetics 160(1):313–322

    PubMed Central  PubMed  Google Scholar 

  • Hemamalini GS, Shashidhar HE, Hittalmani S (2000) Molecular marker assisted tagging of morphological and physiological traits under two contrasting moisture regimes at peak vegetative stage in rice (Oryza sativa L.). Euphytica 112(1):69–78. doi:10.1023/a:1003854224905

    Article  CAS  Google Scholar 

  • Hittalmani S, Huang N, Courtois B, Venuprasad R, Shashidhar HE, Zhuang JY, Zheng KL, Liu GF, Wang GC, Sidhu JS, Srivantaneeyakul S, Singh VP, Bagali PG, Prasanna HC, McLaren G, Khush GS (2003) Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia. Theor Appl Genet 107(4):679–690. doi:10.1007/s00122-003-1269-1

    Article  PubMed  Google Scholar 

  • Huang X, Feng Q, Qian Q, Zhao Q, Wang L, Wang A, Guan J, Fan D, Weng Q, Huang T, Dong G, Sang T, Han B (2009) High-throughput genotyping by whole-genome resequencing. Genome Res 19(6):1068–1076. doi:10.1101/gr.089516.108

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Huang X, Kurata N, Wei X, Wang Z-X, Wang A, Zhao Q, Zhao Y, Liu K, Lu H, Li W, Guo Y, Lu Y, Zhou C, Fan D, Weng Q, Zhu C, Huang T, Zhang L, Wang Y, Feng L, Furuumi H, Kubo T, Miyabayashi T, Yuan X, Xu Q, Dong G, Zhan Q, Li C, Fujiyama A, Toyoda A, Lu T, Feng Q, Qian Q, Li J, Han B (2012) A map of rice genome variation reveals the origin of cultivated rice. Nature 490(7421):497–501. http://www.nature.com/nature/journal/v490/n7421/abs/nature11532.html (supplementary information)

    Google Scholar 

  • Ilut DC, Coate JE, Luciano AK, Owens TG, May GD, Farmer A, Doyle JJ (2012) A comparative transcriptomic study of an allotetraploid and its diploid progenitors illustrates the unique advantages and challenges of RNA-seq in plant species. Am J Bot 99(2):383–396. doi:10.3732/ajb.1100312

    Article  CAS  PubMed  Google Scholar 

  • Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Meth 9(4):357–359. http://www.nature.com/nmeth/journal/v9/n4/abs/nmeth.1923.html (supplementary information)

    Google Scholar 

  • Li H, Durbin R (2010) Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26(5):589–595. doi:10.1093/bioinformatics/btp698

    Article  PubMed Central  PubMed  Google Scholar 

  • Li ZK, Yu SB, Lafitte HR, Huang N, Courtois B, Hittalmani S, Vijayakumar CHM, Liu GF, Wang GC, Shashidhar HE, Zhuang JY, Zheng KL, Singh VP, Sidhu JS, Srivantaneeyakul S, Khush GS (2003) QTL √ó environment interactions in rice. I. Heading date and plant height. Theor Appl Genet 108(1):141–153. doi:10.1007/s00122-003-1401-2

    Article  CAS  PubMed  Google Scholar 

  • Lincoln SE, Lander ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14(3):604–610

    Article  CAS  PubMed  Google Scholar 

  • Maheswaran M, Subudhi PK, Nandi S, Xu JC, Parco A, Yang DC, Huang N (1997) Polymorphism, distribution, and segregation of AFLP markers in a doubled haploid rice population. Theor Appl Genet 94(1):39–45. doi:10.1007/s001220050379

    Article  CAS  PubMed  Google Scholar 

  • Mangin B, Goffinet B, Rebai A (1994) Constructing confidence intervals for QTL location. Genetics 138(4):1301–1308

    PubMed Central  CAS  PubMed  Google Scholar 

  • Matsubara K, Ebana K, Mizubayashi T, Itoh S, Ando T, Nonoue Y, Ono N, Shibaya T, Ogiso E, Hori K, Fukuoka S, Yano M (2011) Relationship between transmission ratio distortion and genetic divergence in intraspecific rice crosses. Mol Genet Genomics 286(5–6):307–319. doi:10.1007/s00438-011-0648-6

    Article  CAS  PubMed  Google Scholar 

  • McCouch SR, Chen X, Panaud O, Temnykh S, Xu Y, Cho YG, Huang N, Ishii T, Blair M (1997) Microsatellite marker development, mapping and applications in rice genetics and breeding. Plant Mol Biol 35(1–2):89–99

    Article  CAS  PubMed  Google Scholar 

  • Mei HW, Luo LJ, Ying CS, Wang YP, Yu XQ, Guo LB, Paterson AH, Li ZK (2003) Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two testcross populations. Theor Appl Genet 107(1):89–101. doi:10.1007/s00122-003-1192-5

    CAS  PubMed  Google Scholar 

  • Mei HW, Li ZK, Shu QY, Guo LB, Wang YP, Yu XQ, Ying CS, Luo LJ (2005) Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two backcross populations. Theor Appl Genet 110(4):649–659. doi:10.1007/s00122-004-1890-7

    Article  CAS  PubMed  Google Scholar 

  • Nasu S, Suzuki J, Ohta R, Hasegawa K, Yui R, Kitazawa N, Monna L, Minobe Y (2002) Search for and analysis of single nucleotide polymorphisms (SNPs) in rice (Oryza sativa, Oryza rufipogon) and establishment of SNP markers. DNA Res 9(5):163–171. doi:10.1093/dnares/9.5.163

    Article  CAS  PubMed  Google Scholar 

  • Prasad SR, Bagali PG, Hittalmani S, Shashidhar HE (2000) Molecular mapping of quantitative trait loci associated with seedling tolerance to salt stress in rice (Oryza sativa L.). Curr Sci 78(2):162–164

    CAS  Google Scholar 

  • Rosyara UR, Gonzalez-Hernandez JL, Glover KD, Gedye KR, Stein JM (2009) Family-based mapping of quantitative trait loci in plant breeding populations with resistance to Fusarium head blight in wheat as an illustration. Theor Appl Genet 118(8):1617–1631. doi:10.1007/s00122-009-1010-9

    Article  CAS  PubMed  Google Scholar 

  • Sallaud C, Lorieux M, Roumen E, Tharreau D, Berruyer R, Svestasrani P, Garsmeur O, Ghesquiere A, Notteghem JL (2003) Identification of five new blast resistance genes in the highly blast-resistant rice variety IR64 using a QTL mapping strategy. Theor Appl Genet 106(5):794–803. doi:10.1007/s00122-002-1088-9

    CAS  PubMed  Google Scholar 

  • Stangoulis JR, Huynh B-L, Welch R, Choi E-Y, Graham R (2007) Quantitative trait loci for phytate in rice grain and their relationship with grain micronutrient content. Euphytica 154(3):289–294. doi:10.1007/s10681-006-9211-7

    Article  Google Scholar 

  • This D, Comstock J, Courtois B, Xu YB, Ahmadi N, Vonhof WM, Fleet C, Setter T, McCouch S (2010) Genetic analysis of water use efficiency in rice (Oryza sativa L.) at the leaf level. Rice 3(1):72–86. doi:10.1007/s12284-010-9036-9

    Article  Google Scholar 

  • Thomson M, Zhao K, Wright M, McNally K, Rey J, Tung C-W, Reynolds A, Scheffler B, Eizenga G, McClung A, Kim H, Ismail A, de Ocampo M, Mojica C, Reveche M, Dilla-Ermita C, Mauleon R, Leung H, Bustamante C, McCouch S (2012) High-throughput single nucleotide polymorphism genotyping for breeding applications in rice using the BeadXpress platform. Mol Breed 29(4):875–886. doi:10.1007/s11032-011-9663-x

    Article  CAS  Google Scholar 

  • Virk PS, Ford-Lloyd BV, Newbury HJ (1998) Mapping AFLP markers associated with subspecific differentiation of Oryza sativa (rice) and an investigation of segregation distortion. Heredity 81:613–620. doi:10.1046/j.1365-2540.1998.00441.x

    Article  CAS  Google Scholar 

  • Vos P, Hogers R, Bleeker M, Reijans M, Vandelee T, Hornes M, Frijters A, Pot J, Peleman J, Kuiper M, Zabeau M (1995) AFLP—a new technique for DNA-fingerprinting. Nucleic Acids Res 23(21):4407–4414. doi:10.1093/nar/23.21.4407

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Walsh MLaB (1998) Genetics and analysis of quantitative traits. Sinauer Associates Inc., Sunderland

    Google Scholar 

  • Wang L, Hao L, Li X, Hu S, Ge S, Yu J (2009) SNP deserts of Asian cultivated rice: genomic regions under domestication. J Evol Biol 22(4):751–761. doi:10.1111/j.1420-9101.2009.01698.x

    Article  CAS  PubMed  Google Scholar 

  • Wenzl P, Carling J, Kudrna D, Jaccoud D, Huttner E, Kleinhofs A, Kilian A (2004) Diversity arrays technology (DArT) for whole-genome profiling of barley. Proc Natl Acad Sci USA 101(26):9915–9920. doi:10.1073/pnas.0401076101

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Wu JZ, Mizuno H, Hayashi-Tsugane M, Ito Y, Chiden Y, Fujisawa M, Katagiri S, Saji S, Yoshiki S, Karasawa W, Yoshihara R, Hayashi A, Kobayashi H, Ito K, Hamada M, Okamoto M, Ikeno M, Ichikawa Y, Katayose Y, Yano M, Matsumoto T, Sasaki T (2003) Physical maps and recombination frequency of six rice chromosomes. Plant J 36(5):720–730. doi:10.1046/j.1365-313X.2003.01903.x

    Article  CAS  PubMed  Google Scholar 

  • Wu YP, Ko PY, Lee WC, Wei FJ, Kuo SC, Ho SW, Hour AL, Hsing YI, Lin YR (2010) Comparative analyses of linkage maps and segregation distortion of two F-2 populations derived from japonica crossed with indica rice. Hereditas 147(5):225–236. doi:10.1111/j.1601-5223.2010.02120.x

    Article  PubMed  Google Scholar 

  • Xu Y, Zhu L, Xiao J, Huang N, McCouch SR (1997) Chromosomal regions associated with segregation distortion of molecular markers in F-2, backcross, doubled haploid, and recombinant inbred populations in rice (Oryza sativa L.). Mol Gen Genet 253(5):535–545

    Article  CAS  PubMed  Google Scholar 

  • Xu X, Liu X, Ge S, Jensen JD, Hu F, Li X, Dong Y, Gutenkunst RN, Fang L, Huang L, Li J, He W, Zhang G, Zheng X, Zhang F, Li Y, Yu C, Kristiansen K, Zhang X, Wang J, Wright M, McCouch S, Nielsen R, Wang W (2012) Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes. Nat Biotechnol 30(1):105–111. doi:10.1038/nbt.2050

    Article  CAS  Google Scholar 

  • Yan CJ, Liang GH, Chen F, Li X, Tang SZ, Yi CD, Tian S, Lu JF, Gu MH (2003) Mapping quantitative trait loci associated with rice grain shape based on an indica/japonica backcross population. Yi Chuan Xue Bao 30(8):711–716

    CAS  PubMed  Google Scholar 

  • Zhao Q, Zhang Y, Cheng ZK, Chen MS, Wang SY, Feng Q, Huang YC, Li Y, Tang YS, Zhou B, Chen ZH, Yu SL, Zhu JJ, Hu X, Mu J, Ying K, Hao P, Zhang L, Lu YQ, Zhang LS, Liu YL, Yu Z, Fan DL, Weng QJ, Chen L, Lu TT, Liu XH, Jia PX, Sun TG, Wu YR, Zhang YJ, Lu Y, Li C, Wang R, Lei HY, Li T, Hu H, Wu M, Zhang RQ, Guan JP, Zhu J, Fu G, Gu MH, Hong GF, Xue YB, Wing R, Jiang JM, Han B (2002) A fine physical map of the rice chromosome 4. Genome Res 12(5):817–823. doi:10.1101/gr.48902

    Article  PubMed Central  CAS  PubMed  Google Scholar 

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Acknowledgments

We thank Sharon Mitchell, Charlotte Acharya, and Wenyan Zhu with the Cornell Institute of Genomic Diversity for assistance with GBS library prep, Ed Buckler, Jeff Glaubitz, Rob Elshire, Peter Bradbury, and James Harriman at Cornell University for assistance and advice on GBS data analysis and using the TASSEL GBS pipeline, Gen Onishi for greenhouse support, Cheryl Utter for helping format the manuscript, Francisco Agosto-Perez, Genevieve DeClerck, and Chih-Wei Tung for bioinformatics support, and Mike Spindel for Python consulting and troubleshooting support.

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Authors and Affiliations

  1. Department of Plant Breeding and Genetics, Cornell University, 162 Emerson Hall, Ithaca, NY, 14853-1901, USA

    Jennifer Spindel, Mark Wright, Charles Chen, Joshua Cobb, Joseph Gage, Sandra Harrington & Susan McCouch

  2. Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), TA06/01 Avenue Agropolis, 34398, Montpellier Cedex 05, France

    Nourollah Ahmadi

  3. UMR DIADE, Institut de Recherche pour le Développement (IRD), 34394, Montpellier Cedex 5, France

    Mathias Lorieux

  4. Rice Genetics and Genomics Laboratory, International Center for Tropical Agriculture (CIAT), AA6713, Cali, Colombia

    Mathias Lorieux

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  1. Jennifer Spindel
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  2. Mark Wright
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  3. Charles Chen
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  4. Joshua Cobb
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  7. Mathias Lorieux
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  8. Nourollah Ahmadi
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  9. Susan McCouch
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Correspondence to Susan McCouch.

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Communicated by R. Snowdon.

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Spindel, J., Wright, M., Chen, C. et al. Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations. Theor Appl Genet 126, 2699–2716 (2013). https://doi.org/10.1007/s00122-013-2166-x

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