Skip to main content
SpringerLink
Log in

Efficient QTL detection of flowering date in a soybean RIL population using the novel restricted two-stage multi-locus GWAS procedure

  • Original Article
  • Published:
Theoretical and Applied Genetics Aims and scope Submit manuscript

Abstract

Key message

Eighty-six R1 QTLs accounting for 89.92% phenotypic variance in a soybean RIL population were identified using RTM-GWAS with SNPLDB marker which performed superior over CIM and MLM-GWAS with BIN/SNPLDB marker.

Abstract

A population (NJRIKY) composed of 427 recombinant inbred lines (RILs) derived from Kefeng-1 × NN1138-2 (MGII × MGV, MG maturity group) was applied for detecting flowering date (R1) quantitative trait locus (QTL) system in soybean. From a low-depth re-sequencing (~ 0.75 ×), 576,874 SNPs were detected and organized into 4737 BINs (recombination breakpoint determinations) and 3683 SNP linkage disequilibrium blocks (SNPLDBs), respectively. Using the association mapping procedures “Restricted Two-stage Multi-locus Genome-wide Association Study” (RTM-GWAS), “Mixed Linear Model Genome-wide Association Study” (MLM-GWAS) and the linkage mapping procedure “Composite Interval Mapping” (CIM), 67, 36 and 10 BIN-QTLs and 86, 14 and 23 SNPLDB-QTLs were detected with their phenotypic variance explained (PVE) 88.70–89.92% (within heritability 98.2%), 146.41–353.62% (overflowing) and 88.29–172.34% (overflowing), respectively. The RTM-GWAS with SNPLDBs which showed to be more efficient and reasonable than the others was used to identify the R1 QTL system in NJRIKY. The detected 86 SNPLDB-QTLs with their PVE from 0.02 to 30.66% in a total of 89.92% covered 51 out of 104 R1 QTLs in 18 crosses in SoyBase and 26 out of 139 QTLs in a nested association mapping population, while the rest 29 QTLs were novel ones. From the QTL system, 52 candidate genes were annotated, including the verified gene E1, E2, E9 and J, and grouped into 3 categories of biological processes, among which 24 genes were enriched into three protein–protein interaction networks, suggesting gene networks working together. Since NJRIKY involves only MGII and MGV, the QTL/gene system among MG000–MGX should be explored further.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Alvarez-Buylla ER, Azpeitia E, Barrio R, Benitez M, Padilla-Longoria P (2010) From ABC genes to regulatory networks, epigenetic landscapes and flower morphogenesis: making biological sense of theoretical approaches. Semin Cell Dev Biol 21:108–117

    CAS  PubMed  Google Scholar 

  • Atwell S, Huang YS, Vilhjalmsson BJ, Willems G, Horton M, Li Y, Meng D, Platt A, Tarone AM, Hu TT, Jiang R, Muliyati NW, Zhang X, Amer MA, Baxter I, Brachi B, Chory J, Dean C, Debieu M, de Meaux J, Ecker JR, Faure N, Kniskern JM, Jones JD, Michael T, Nemri A, Roux F, Salt DE, Tang C, Todesco M, Traw MB, Weigel D, Marjoram P, Borevitz JO, Bergelson J, Nordborg M (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature 465:627–631

    CAS  PubMed  PubMed Central  Google Scholar 

  • Barabaschi D, Guerra D, Lacrima K, Laino P, Michelotti V, Urso S, Vale G, Cattivelli L (2012) Emerging knowledge from genome sequencing of crop species. Mol Biotechnol 50:250–266

    CAS  PubMed  Google Scholar 

  • Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21:263–265

    Article  CAS  PubMed  Google Scholar 

  • Beckmann L, Fischer C, Obreiter M, Rabes M, Chang-Claude J (2005) Haplotype-sharing analysis using Mantel statistics for combined genetic effects. BMC Genet 6(Suppl 1):S70

    PubMed  PubMed Central  Google Scholar 

  • Bernard R (1971) Two major genes for time of flowering and maturity in soybeans. Crop Sci 11:242–244

    Google Scholar 

  • Bland JM, Altman DG (1995) Multiple significance tests: the Bonferroni method. BMJ 310:170

    CAS  PubMed  PubMed Central  Google Scholar 

  • Bonato ER, Vello NA (1999) E6, a dominant gene conditioning early flowering and maturity in soybeans. Genet Mol Biol 22:229–232

    Google Scholar 

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

    CAS  PubMed  Google Scholar 

  • Broman KW, Speed TP (1999) A review of methods for identifying QTLs in experimental crosses. Institute of Mathematical Statistics, Hayward

    Google Scholar 

  • Buzzell R (1971) Inheritance of a soybean flowering response to fluorescent-daylength conditions. Can J Genet Cytol 13:703–707

    Google Scholar 

  • Buzzell R, Voldeng H (1980) Inheritance of insensitivity to long daylength. Soybean Genet Newsl 7:26–29

    Google Scholar 

  • Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971

    CAS  PubMed  PubMed Central  Google Scholar 

  • Cober ER, Voldeng HD (2001) A new soybean maturity and photoperiod-sensitivity locus linked to E1 and T. Crop Sci 41:698–701

    Google Scholar 

  • Du Z, Zhou X, Ling Y, Zhang Z, Su Z (2010) agriGO: a GO analysis toolkit for the agricultural community. Nucleic Acids Res 38:W64–W70

    CAS  PubMed  PubMed Central  Google Scholar 

  • Fehr WR, Caviness CE, Burmood DT, Pennington JS (1971) Stage of development descriptions for soybeans, Glycine Max (L.) Merrill. Merrill Crop Sci 11:929–931

    Google Scholar 

  • Funatsuki H, Kawaguchi K, Matsuba S, Sato Y, Ishimoto M (2005) Mapping of QTL associated with chilling tolerance during reproductive growth in soybean. TAG Theor Appl Genet Theoretische und angewandte Genetik 111:851–861

    CAS  PubMed  Google Scholar 

  • Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R, Ward R, Lander ES, Daly MJ, Altshuler D (2002) The structure of haplotype blocks in the human genome. Science 296:2225–2229

    CAS  PubMed  Google Scholar 

  • Gai J (2013) Quantitative inheritance. In: Maloy S, Hughes K (eds) Brenner’s encyclopedia of genetics, vol 6, 2nd edn. Academic Press, San Diego, pp 18–21

    Google Scholar 

  • Gai J, Wang Y, Zhang M, Wang J, Chang R (2001) Studies on the classification of maturity groups of soybeans in China. Acta Agron Sin 27:286–292

    Google Scholar 

  • Gai J, Wang Y, Wu X, Chen S (2007) A comparative study on segregation analysis and QTL mapping of quantitative traits in plants—with a case in soybean. Front Agric China 1:1–7

    Google Scholar 

  • Githiri SM, Yang D, Khan NA, Xu D, Komatsuda T, Takahashi R (2007) QTL analysis of low temperature induced browning in soybean seed coats. J Hered 98:360–366

    CAS  PubMed  Google Scholar 

  • Hanson WD (1985) Association of seed yield with partitioned lengths of the reproductive period in soybean genotypes. Crop Sci 25:525–529

    Google Scholar 

  • Harris RS (2007) Ph.D. Thesis: improved pairwise alignment of genomic DNA. Dissertations & Theses—Gradworks

  • He J, Meng S, Zhao T, Xing G, Yang S, Li Y, Guan R, Lu J, Wang Y, Xia Q, Yang B, Gai J (2017) An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding. TAG Theor Appl Genet Theoretische und angewandte Genetik 130:2327–2343

    CAS  PubMed  Google Scholar 

  • Hisano H, Sato S, Isobe S, Sasamoto S, Wada T, Matsuno A, Fujishiro T, Yamada M, Nakayama S, Nakamura Y, Watanabe S, Harada K, Tabata S (2007) Characterization of the soybean genome using EST-derived microsatellite markers. DNA Res 14:271–281

    CAS  PubMed  Google Scholar 

  • Hu H, Liu W, Fu Z, Homann L, Technow F, Wang H, Song C, Li S, Melchinger AE, Chen S (2013) QTL mapping of stalk bending strength in a recombinant inbred line maize population. TAG Theor Appl Genet Theoretische und angewandte Genetik 126:2257–2266

    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 19:1068–1076

    CAS  PubMed  PubMed Central  Google Scholar 

  • Jansen RC (1993) Interval mapping of multiple quantitative trait loci. Genetics 135:205

    CAS  PubMed  PubMed Central  Google Scholar 

  • Jourjon MF, Jasson S, Marcel J, Ngom B, Mangin B (2005) MCQTL: multi-allelic QTL mapping in multi-cross design. Bioinformatics 21:128–130

    CAS  PubMed  Google Scholar 

  • Jun TH, Freewalt K, Michel AP, Mian R (2014) Identification of novel QTL for leaf traits in soybean. Plant Breed 133:61–66

    CAS  Google Scholar 

  • Kantolic AG, Slafer GA (2001) Photoperiod sensitivity after flowering and seed number determination in indeterminate soybean cultivars. Field Crops Res 72:109–118

    Google Scholar 

  • Kong F, Liu B, Xia Z, Sato S, Kim BM, Watanabe S, Yamada T, Tabata S, Kanazawa A, Harada K, Abe J (2010) Two coordinately regulated homologs of FLOWERING LOCUS T are involved in the control of photoperiodic flowering in soybean. Plant Physiol 154:1220–1231

    CAS  PubMed  PubMed Central  Google Scholar 

  • Kong FJ, Nan HY, Cao D, Li Y, Wu FF, Wang JL, Lu SJ, Yuan XH, Cober ER, Abe J, Liu BH (2014) A new dominant gene E9 conditions early flowering and maturity in soybean. Crop Sci 54:2529–2535

    Google Scholar 

  • Kuroda Y, Kaga A, Tomooka N, Yano H, Takada Y, Kato S, Vaughan D (2013) QTL affecting fitness of hybrids between wild and cultivated soybeans in experimental fields. Ecol Evol 3:2150–2168

    PubMed  PubMed Central  Google Scholar 

  • Lander ES, Botstein D (1989) Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199

    CAS  PubMed  PubMed Central  Google Scholar 

  • Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25:1754–1760

    CAS  PubMed  PubMed Central  Google Scholar 

  • Li H, Ribaut JM, Li Z, Wang J (2008) Inclusive composite interval mapping (ICIM) for digenic epistasis of quantitative traits in biparental populations. TAG Theor Appl Genet Theoretische und angewandte Genetik 116:243–260

    PubMed  Google Scholar 

  • Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Genome Project Data Processing S (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079

    PubMed  PubMed Central  Google Scholar 

  • Li H, Hearne S, Banziger M, Li Z, Wang J (2010a) Statistical properties of QTL linkage mapping in biparental genetic populations. Heredity 105:257–267

    CAS  PubMed  Google Scholar 

  • Li HH, Zhang LY, Wang JK (2010b) Analysis and answers to frequently asked questions in quantitative trait locus mapping. Acta Agron Sin 36:918–931

    Google Scholar 

  • Li H, Peng Z, Yang X, Wang W, Fu J, Wang J, Han Y, Chai Y, Guo T, Yang N, Liu J, Warburton ML, Cheng Y, Hao X, Zhang P, Zhao J, Liu Y, Wang G, Li J, Yan J (2013) Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels. Nat Genet 45:43–50

    CAS  PubMed  Google Scholar 

  • Li S, Cao Y, He J, Zhao T, Gai J (2017) Detecting the QTL-allele system conferring flowering date in a nested association mapping population of soybean using a novel procedure. TAG Theor Appl Genet Theoretische und angewandte Genetik 130:2297–2314

    CAS  PubMed  Google Scholar 

  • Liu B, Kanazawa A, Matsumura H, Takahashi R, Harada K, Abe J (2008) Genetic redundancy in soybean photoresponses associated with duplication of the phytochrome A gene. Genetics 180:995–1007

    CAS  PubMed  PubMed Central  Google Scholar 

  • Liu B, Watanabe S, Uchiyama T, Kong F, Kanazawa A, Xia Z, Nagamatsu A, Arai M, Yamada T, Kitamura K, Masuta C, Harada K, Abe J (2010) The soybean stem growth habit gene Dt1 is an ortholog of Arabidopsis TERMINAL FLOWER1. Plant Physiol 153:198–210

    CAS  PubMed  PubMed Central  Google Scholar 

  • Lu S, Zhao X, Hu Y, Liu S, Nan H, Li X, Fang C, Cao D, Shi X, Kong L, Su T, Zhang F, Li S, Wang Z, Yuan X, Cober ER, Weller JL, Liu B, Hou X, Tian Z, Kong F (2017) Natural variation at the soybean J locus improves adaptation to the tropics and enhances yield. Nat Genet 49:773–779

    CAS  PubMed  Google Scholar 

  • Mackay I, Powell W (2007) Methods for linkage disequilibrium mapping in crops. Trends Plant Sci 12:57–63

    CAS  PubMed  Google Scholar 

  • Malosetti M, van Eeuwijk FA, Boer MP, Casas AM, Elia M, Moralejo M, Bhat PR, Ramsay L, Molina-Cano JL (2011) Gene and QTL detection in a three-way barley cross under selection by a mixed model with kinship information using SNPs. TAG Theor Appl Genet Theoretische und angewandte Genetik 122:1605–1616

    PubMed  Google Scholar 

  • Mcblain BA, Bernard RL (1987) A new gene affecting the time of flowering and maturity in soybeans. J Hered 78:160–162

    Google Scholar 

  • Murakami M, Ashikari M, Miura K, Yamashino T, Mizuno T (2003) The evolutionarily conserved OsPRR quintet: rice pseudo-response regulators implicated in circadian rhythm. Plant Cell Physiol 44:1229–1236

    CAS  PubMed  Google Scholar 

  • Murray MG, Thompson WF (1980) Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res 8:4321–4325

    CAS  PubMed  PubMed Central  Google Scholar 

  • Nowack MK, Grini PE, Jakoby MJ, Lafos M, Koncz C, Schnittger A (2006) A positive signal from the fertilization of the egg cell sets off endosperm proliferation in angiosperm embryogenesis. Nat Genet 38:63–67

    CAS  PubMed  Google Scholar 

  • Nyquist WE (1991) Estimation of heritability and prediction of selection response in plant-populations. Crit Rev Plant Sci 10:235–322

    Google Scholar 

  • O’Maoileidigh DS, Graciet E, Wellmer F (2014) Gene networks controlling Arabidopsis thaliana flower development. New Phytol 201:16–30

    PubMed  Google Scholar 

  • Ooijen JWV (2006) JoinMap® 4.0: software for the calculation of genetic linkage maps in experimental population. Kyazma BV, Wageningen

    Google Scholar 

  • Ooijen JWV, Ooijen J, Ooijen JW (2009) MapQTL 6: software for the mapping of quantitative trait loci in experimental populations of diploid species. Wageningen, Kyazma BV

    Google Scholar 

  • Orf JH, Chase K, Jarvik T, Mansur LM, Cregan PB, Adler FR, Lark KG (1999) Genetics of soybean agronomic traits: I. Comparison of three related recombinant inbred populations. Crop Sci 39:1642–1651

    Google Scholar 

  • Piepho HP, Mohring J (2007) Computing heritability and selection response from unbalanced plant breeding trials. Genetics 177:1881–1888

    PubMed  PubMed Central  Google Scholar 

  • Rakitsch B, Lippert C, Stegle O, Borgwardt K (2013) A Lasso multi-marker mixed model for association mapping with population structure correction. Bioinformatics 29:206–214

    CAS  PubMed  Google Scholar 

  • Ray JD, Hinson K, Mankono JEB, Malo MF (1995) Genetic-control of a long-juvenile trait in soybean. Crop Sci 35:1001–1006

    Google Scholar 

  • Schmutz J, Cannon SB, Schlueter J, Ma J, Mitros T, Nelson W, Hyten DL, Song Q, Thelen JJ, Cheng J, Xu D, Hellsten U, May GD, Yu Y, Sakurai T, Umezawa T, Bhattacharyya MK, Sandhu D, Valliyodan B, Lindquist E, Peto M, Grant D, Shu S, Goodstein D, Barry K, Futrell-Griggs M, Abernathy B, Du J, Tian Z, Zhu L, Gill N, Joshi T, Libault M, Sethuraman A, Zhang XC, Shinozaki K, Nguyen HT, Wing RA, Cregan P, Specht J, Grimwood J, Rokhsar D, Stacey G, Shoemaker RC, Jackson SA (2010) Genome sequence of the palaeopolyploid soybean. Nature 463:178–183

    CAS  PubMed  Google Scholar 

  • Segura V, Vilhjalmsson BJ, Platt A, Korte A, Seren U, Long Q, Nordborg M (2012) An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations. Nat Genet 44:825–830

    CAS  PubMed  PubMed Central  Google Scholar 

  • Shinozuka H, Cogan NO, Smith KF, Spangenberg GC, Forster JW (2010) Fine-scale comparative genetic and physical mapping supports map-based cloning strategies for the self-incompatibility loci of perennial ryegrass (Lolium perenne L.). Plant Mol Biol 72:343–355

    CAS  PubMed  Google Scholar 

  • Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ, von Mering C (2015) STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447–D452

    CAS  PubMed  Google Scholar 

  • Tasma IM, Lorenzen LL, Green DE, Shoemaker RC (2001) Mapping genetic loci for flowering time, maturity, and photoperiod insensitivity in soybean. Mol Breed 8:25–35

    CAS  Google Scholar 

  • Tian Z, Wang X, Lee R, Li Y, Specht JE, Nelson RL, McClean PE, Qiu L, Ma J (2010) Artificial selection for determinate growth habit in soybean. Proc Natl Acad Sci USA 107:8563–8568

    CAS  PubMed  PubMed Central  Google Scholar 

  • Verbyla AP, George AW, Cavanagh CR, Verbyla KL (2014) Whole-genome QTL analysis for MAGIC. TAG Theor Appl Genet Theoretische und angewandte Genetik 127:1753–1770

    PubMed  Google Scholar 

  • Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, Yang J (2017) 10 years of GWAS discovery: biology, function, and translation. Am J Hum Genet 101:5–22

    CAS  PubMed  PubMed Central  Google Scholar 

  • Wang Y (2009) Genomic characterization of simple sequence repeats and establishment, integration and application of high density genetic linkage map in soybean. Ph.D. Dissertation, Nanjing Agricultural University (in Chinese)

  • Wang DG, Fan JB, Siao CJ, Berno A, Young P, Sapolsky R, Ghandour G, Perkins N, Winchester E, Spencer J, Kruglyak L, Stein L, Hsie L, Topaloglou T, Hubbell E, Robinson E, Mittmann M, Morris MS, Shen N, Kilburn D, Rioux J, Nusbaum C, Rozen S, Hudson TJ, Lipshutz R, Chee M, Lander ES (1998) Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Science 280:1077–1082

    CAS  PubMed  Google Scholar 

  • Wang Y, Wu X, He C, Zhang J, Chen S, Gai J (2003) A soybean genetic linkage map constructed after the mapping population being tested and adjusted. Sci Agric Sin 11:3

    CAS  Google Scholar 

  • Wang L, Wang AH, Huang XH, Zhao QA, Dong GJ, Qian QA, Sang T, Han B (2011) Mapping 49 quantitative trait loci at high resolution through sequencing-based genotyping of rice recombinant inbred lines. Theor Appl Genet 122:327–340

    PubMed  Google Scholar 

  • Watanabe S, Hideshima R, Xia Z, Tsubokura Y, Sato S, Nakamoto Y, Yamanaka N, Takahashi R, Ishimoto M, Anai T, Tabata S, Harada K (2009) Map-based cloning of the gene associated with the soybean maturity locus E3. Genetics 182:1251–1262

    CAS  PubMed  PubMed Central  Google Scholar 

  • Watanabe S, Xia Z, Hideshima R, Tsubokura Y, Sato S, Yamanaka N, Takahashi R, Anai T, Tabata S, Kitamura K, Harada K (2011) A map-based cloning strategy employing a residual heterozygous line reveals that the GIGANTEA gene is involved in soybean maturity and flowering. Genetics 188:395–407

    CAS  PubMed  PubMed Central  Google Scholar 

  • Watanabe S, Harada K, Abe J (2012) Genetic and molecular bases of photoperiod responses of flowering in soybean. Breed Sci 61:531–543

    CAS  PubMed  PubMed Central  Google Scholar 

  • Xia Z, Watanabe S, Yamada T, Tsubokura Y, Nakashima H, Zhai H, Anai T, Sato S, Yamazaki T, Lu S, Wu H, Tabata S, Harada K (2012) Positional cloning and characterization reveal the molecular basis for soybean maturity locus E1 that regulates photoperiodic flowering. Proc Natl Acad Sci USA 109:E2155–E2164

    CAS  PubMed  PubMed Central  Google Scholar 

  • Xie W, Feng Q, Yu H, Huang X, Zhao Q, Xing Y, Yu S, Han B, Zhang Q (2010) Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing. Proc Natl Acad Sci USA 107:10578–10583

    CAS  PubMed  PubMed Central  Google Scholar 

  • Xu X, Zeng L, Tao Y, Vuong T, Wan J, Boerma R, Noe J, Li Z, Finnerty S, Pathan SM, Shannon JG, Nguyen HT (2013) Pinpointing genes underlying the quantitative trait loci for root-knot nematode resistance in palaeopolyploid soybean by whole genome resequencing. Proc Natl Acad Sci USA 110:13469–13474

    CAS  PubMed  PubMed Central  Google Scholar 

  • Yamanaka N, Ninomiya S, Hoshi M, Tsubokura Y, Yano M, Nagamura Y, Sasaki T, Harada K (2001) An informative linkage map of soybean reveals QTLs for flowering time, leaflet morphology and regions of segregation distortion. DNA Res 8:61–72

    CAS  PubMed  Google Scholar 

  • Yang J, Hu C, Hu H, Yu R, Xia Z, Ye X, Zhu J (2008) QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics 24:721–723

    PubMed  Google Scholar 

  • Yasui Y, Tanaka W, Sakamoto T, Kurata T, Hirano HY (2017) Genetic enhancer analysis reveals that FLORAL ORGAN NUMBER2 and OsMADS3 co-operatively regulate maintenance and determinacy of the flower meristem in rice. Plant Cell Physiol 58:893–903

    CAS  PubMed  Google Scholar 

  • Yoshikawa T, Ito M, Sumikura T, Nakayama A, Nishimura T, Kitano H, Yamaguchi I, Koshiba T, Hibara K, Nagato Y, Itoh J (2014) The rice FISH BONE gene encodes a tryptophan aminotransferase, which affects pleiotropic auxin-related processes. Plant J 78:927–936

    CAS  PubMed  Google Scholar 

  • Yu JM, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208

    CAS  PubMed  Google Scholar 

  • Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468

    CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang K, Deng M, Chen T, Waterman MS, Sun F (2002) A dynamic programming algorithm for haplotype block partitioning. Proc Natl Acad Sci USA 99:7335–7339

    CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang WK, Wang YJ, Luo GZ, Zhang JS, He CY, Wu XL, Gai JY, Chen SY (2004) QTL mapping of ten agronomic traits on the soybean (Glycine max L. Merr.) genetic map and their association with EST markers. Theor Appl Genet 108:1131–1139

    CAS  PubMed  Google Scholar 

  • Zhang Y, He J, Wang Y, Xing G, Zhao J, Li Y, Yang S, Palmer RG, Zhao T, Gai J (2015a) Establishment of a 100-seed weight quantitative trait locus-allele matrix of the germplasm population for optimal recombination design in soybean breeding programmes. J Exp Bot 66:6311–6325

    CAS  PubMed  Google Scholar 

  • Zhang YH, Liu MF, He JB, Wang YF, Xing GN, Li Y, Yang SP, Zhao TJ, Gai JY (2015b) Marker-assisted breeding for transgressive seed protein content in soybean [Glycine max (L.) Merr]. TAG Theor Appl Genet Theoretische und angewandte Genetik 128:1061–1072

    CAS  PubMed  Google Scholar 

  • Zhao H, Pfeiffer R, Gail MH (2003) Haplotype analysis in population genetics and association studies. Pharmacogenomics 4:171–178

    PubMed  Google Scholar 

  • Zhao C, Takeshima R, Zhu J, Xu M, Sato M, Watanabe S, Kanazawa A, Liu B, Kong F, Yamada T, Abe J (2016) A recessive allele for delayed flowering at the soybean maturity locus E9 is a leaky allele of FT2a, a FLOWERING LOCUS T ortholog. BMC Plant Biol 16:20

    PubMed  PubMed Central  Google Scholar 

  • Zhou Z, Jiang Y, Wang Z, Gou Z, Lyu J, Li W, Yu Y, Shu L, Zhao Y, Ma Y, Fang C, Shen Y, Liu T, Li C, Li Q, Wu M, Wang M, Wu Y, Dong Y, Wan W, Wang X, Ding Z, Gao Y, Xiang H, Zhu B, Lee SH, Wang W, Tian Z (2015) Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean. Nat Biotechnol 33:408–414

    CAS  PubMed  Google Scholar 

  • Zuo QM, Hou JF, Zhou B, Wen ZX, Zhang SY, Gai JY, Xing H (2013) Identification of QTLs for growth period traits in soybean using association analysis and linkage mapping. Plant Breed 132:317–323

    CAS  Google Scholar 

Download references

Acknowledgments

This work was financially supported through the grants from the National Key R&D Program for Crop Breeding in China (2017YFD0101500), the Natural Science Foundation of China (31701447), the MOE 111 Project (B08025), the MOE Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT_17R55), the MOA CARS-04 program, the Jiangsu Higher Education PAPD Program, the Fundamental Research Funds for the Central Universities and the Jiangsu JCIC-MCP. The funders had no role in work design, data collection and analysis, and decision and preparation of the manuscript. We would thank the State Key Laboratory of Agricultural Genomics (BGI-Shenzhen, Shenzhen 518083, China) for their service in sequencing the materials. Specific thanks go to Dr. Hans-Peter Piepho for providing consulting in calculation the adjusted heritabilities for unbalanced data.

Author information

Authors and Affiliations

  1. Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China

    Liyuan Pan, Jianbo He, Tuanjie Zhao, Guangnan Xing, Yufeng Wang, Deyue Yu & Junyi Gai

  2. National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China

    Liyuan Pan, Jianbo He, Tuanjie Zhao, Guangnan Xing, Yufeng Wang, Deyue Yu & Junyi Gai

  3. Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China

    Liyuan Pan, Jianbo He, Tuanjie Zhao, Guangnan Xing, Deyue Yu & Junyi Gai

  4. National Key Laboratory for Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China

    Liyuan Pan, Jianbo He, Tuanjie Zhao, Guangnan Xing, Deyue Yu & Junyi Gai

  5. State Key Lab of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China

    Shouyi Chen

Authors
  1. Liyuan Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianbo He
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tuanjie Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guangnan Xing
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yufeng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Deyue Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Shouyi Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Junyi Gai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Junyi Gai.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Communicated by Mikko J. Sillanpaa.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 395 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pan, L., He, J., Zhao, T. et al. Efficient QTL detection of flowering date in a soybean RIL population using the novel restricted two-stage multi-locus GWAS procedure. Theor Appl Genet 131, 2581–2599 (2018). https://doi.org/10.1007/s00122-018-3174-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-018-3174-7

Search

Navigation