, 214:120 | Cite as

Fine mapping of major QTLs for alkaline tolerance at the seedling stage in maize (Zea mays L.) through genetic linkage analysis combined with high-throughput DNA sequencing

  • Chunxiao Zhang
  • Fengxue Jin
  • Shufang Li
  • Wenping Liu
  • Xiaojun Ma
  • Shan Yang
  • Deguang YangEmail author
  • Xiaohui LiEmail author


Exploiting genes and quantitative trait loci (QTLs) related to maize (Zea mays L.) alkaline tolerance is helpful for improving alkaline resistance. To explore the inheritance of maize alkaline tolerance at the seedling stage, a mapping population comprising 151 F2:3 lines derived from the maize cross between Zheng58, tolerant to alkaline, and Chang7-2, sensitive to alkaline, was used to establish a genetic linkage map with 200 SSR loci across the 10 maize linkage groups, with an average interval of 6.5 cM between adjacent markers. QTLs for alkaline resistant traits of alkaline tolerance rating (ATR), germination rate (GR), relative conductivity (RC), weight per plant (WPP) and proline content (PC) were detected. The obtained results were as follows: Five QTLs on chromosomes 2, 5 and 6 (GR and WPP: chr. 2; PC and ATR: chr. 5; and RC: chr. 6) were mapped. For precise mapping of the QTLs related to alkaline resistance, two bulked deoxyribonucleic acid (DNA) pools were constructed using individual DNAs from the most tolerant 30 F2 individuals and the most sensitive 30 F2 individuals according to the ATR and used to establish a high density map of SLAF markers strongly associated with the ATR by specific locus amplified fragment sequencing (SLAF-Seq) combined with super bulked segregant analysis (superBSA). One marker-intensive region involved three SLAFs at 296,000–6,203,000 bp on chromosome 5 that were closely related to the ATR. Combined with preliminary QTL mapping with superBSA, two major QTLs on chromosome 5 associated with alkaline tolerance at the maize seedling stage were mapped to marker intervals of dCap-SLAF31521 and dCap-SLAF31535 and phi024 and dCap-SLAF31521, respectively. These QTL regions involved 9 and 75 annotated genes, respectively. These results will be helpful for improving maize alkaline tolerance at the seedling stage by marker-assisted selection programs and will be useful for fine mapping QTLs for maize breeding.


Maize (Zea mays L.) Alkaline tolerance Super bulked segregant analysis (superBSA) Specific locus amplified fragment sequencing (SLAF-Seq) 


Compliance of ethical standards


The research was supported by the Agricultural Science and Technology Innovation Program of Jilin Province “Discovery of excellent germplasms and cultivation of inbred lines suitable for mechanized harvesting in maize” and the Program for Chinese Outstanding Talents in Agricultural Scientific Research, 2016.

Supplementary material

10681_2018_2190_MOESM1_ESM.xlsx (181 kb)
Supplementary Table 1 The genetic linkage map constructed using SSR markers in this study (XLSX 180 kb)
10681_2018_2190_MOESM2_ESM.xlsx (10 kb)
Supplementary Table 2 Sequencing data for each sample (XLSX 9 kb)
10681_2018_2190_MOESM3_ESM.xlsx (11 kb)
Supplementary Table 3 Number distribution of SLAF tag, marker, and Diff_marker on each chromosome (XLSX 10 kb)
10681_2018_2190_MOESM4_ESM.xlsx (10 kb)
Supplementary Table 4 dCAPs markers used for the construction of a genetic linkage map (XLSX 10 kb)
10681_2018_2190_MOESM5_ESM.xlsx (20 kb)
Supplementary Table 5 Reported salt-alkali tolerance QTL in the study (XLSX 19 kb)


  1. Ahmadi J, Fotokian MH (2011) Identification and mapping of quantitative trait loci associated with salinity tolerance in rice (Oryza sativa L.) using SSR markers. Iranian J Biotechnol 9(1):21–30Google Scholar
  2. Du ZZ, Chen YH, Zhou YK, He T, Zou L, Wang YF, Lu RJ, Huang JH (2009) Screening of salt tolerance in barley materials of space mutation and identification in fields. Chin Agric Sci Bull 25(23):105–107Google Scholar
  3. Dubcovsky J, María GS, Epstein E, Luo MC, Dvořák J (1996) Mapping of the K +/Na + discrimination locus Kna1 in wheat. Theor Appl Genet 92(3):448–454. CrossRefPubMedGoogle Scholar
  4. Fu Y, Gao SR, Wang ZH (2009) Evaluation of salt tolerance of maize germplasm in seeding stage. J Maize Sci 17(1):36–39. CrossRefGoogle Scholar
  5. Geng X, Jiang C, Yang J, Wang LJ, Wu XM, Wei WH (2016) Rapid identification of candidate genes for seed weight using the SLAF-Seq method in Brassica napus. PLoS ONE 11(1):e0147580. CrossRefPubMedPubMedCentralGoogle Scholar
  6. Gong JM, He P, Qian Q, Shen LS, Zhu LH, Chen SY (1999) Identification of salt-tolerance QTL in rice (Oryza sativa L.). Chin Sci Bull 44(1):68–71. CrossRefGoogle Scholar
  7. Gong B, wang XF, Wei M, Yang FJ, Shi QH (2016) Overexpression of S-adenosylmethionine synthetase 1 enhances tomato callus tolerance to alkali stress through polyamine and hydrogen peroxide cross-linked networks. Plant Cell Tissue Organ Cult 124(2):377–391. CrossRefGoogle Scholar
  8. Guan FX (2012) Mapping QTL saline-alkali tolerance during bud and seedling stage using RIL in maize. Dissertation, Yangzhou University pp 20–30Google Scholar
  9. Hamwieh A, Tuyen DD, Cong H, Benitez ER, Takahashi R, Xu DH (2011) Identification and validation of a major QTL for salt tolerance in soybean. Euphytica 179:451–459. CrossRefGoogle Scholar
  10. Lee GJ, Boerma HR, Villagarcia MR, Zhou X, Carter-Jr TE, Li Z, Gibbs MO (2004) A major QTL conditioning salt tolerance in S-100 soybean and descendent cultivars. Theor Appl Genet 109:1610–1619. CrossRefPubMedGoogle Scholar
  11. Li LQ, Xie JH, Ma XQ, Li D (2016) Molecular cloning of Phosphoethanolamine N-methyltransferase (PEAMT) gene and its promoter from the halophyte Suaeda liaotungensis and their response to salt stress. Acta Physiol Plant 38(2):39. CrossRefGoogle Scholar
  12. Luo P, Shen YX, Jin SX, Huang SS, Cheng X, Wang Z, Li PL, Zhao J, Bao MZ, Ning GG (2016) Overexpression of Rosa rugosa anthocyanidin reductase enhances tobacco tolerance to abiotic stress through increased ROS scavenging and modulation of ABA signaling. Plant Sci 245:35–49. CrossRefPubMedGoogle Scholar
  13. Luo MJ, Zhao YX, Zhang RY, Xing JF, Duan MX, Li JN, Wang NS, Wang WG, Zhang SS, Chen ZH, Zhang HS, Shi Song W, Zhao JR (2017) Mapping of a major QTL for salt tolerance of mature field-grown maize plants based on SNP markers. BMC Plant Biol 17(1):140. CrossRefPubMedPubMedCentralGoogle Scholar
  14. Ma XJ, Jin FX, Yang S, Yang DG, Li XH (2015) Mapping QTLs for salt & alkaline tolerance in crops. A Mini Rev Mol Plant Breed 13(1):1–7. CrossRefGoogle Scholar
  15. Mano Y, Takeda K (1997) Mapping quantitative trait loci for salt tolerance at germination and the seedling stage in barley (Hordeum vulgare L.). Euphytica 94:263–272. CrossRefGoogle Scholar
  16. Masood MS, Seiji I, Shinwari ZK, Anwar R (2004) Mapping quantitative trait Loci (QTLs) for salt tolerance in rice (Oryza sativa) using RFLPs. Pak J Bot 36(4):825–834Google Scholar
  17. Munns R, Tester M (2008) Mech Salin Toler Plant Boil 59:651–681. CrossRefGoogle Scholar
  18. Ni XL, YF Y, Tian Y, Peng L, Shen XD (2010) Comprehensive evaluation of salt-resistance traits in four halophytes. Chin Agric Sci Bull 26(6):138–141Google Scholar
  19. Ogbonnaya FC, Huang S, Steadman E, Livinus E, Dreccer F, Lagudah ES, and Munns R (2008) Mapping quantitative trait loci associated with salinity tolerance in synthetic derived backcrossed bread lines. 11th International wheat genetics symposium, Brisbane, August, pp 197: 1–3Google Scholar
  20. Peng YL, Li WL, Wang KZ, Wang HN (2012) Effects of salt stress on seeding germination and seeding growth of salt-tolerant line and salt-sensitive line of maize. Acta Prataculturae Sin 21(4):62–71Google Scholar
  21. Qi ZM, Huang L, Zhu RS, Xin DW, Liu CY, Han X, Jiang HW, Hong WG, Hu GH, Zheng HK, Chen QS (2014) A high-density genetic map for soybean based on specific length amplified fragment sequencing. PLoS ONE 9:e104871. CrossRefPubMedPubMedCentralGoogle Scholar
  22. Siahsar BA, Aminfar Z (2010) Mapping QTLs of physiological traits associated with salt tolerance in ‘Steptoe’ × ‘Morex’ doubled haploid lines of barley at seedling stage. J Food Agric Environ 8(2):751–759Google Scholar
  23. Sun Q, Zhang SH, Hao ZF, Zhang DG, CI XK, Chen ZH, LI XH, Xie CX, Weng JF, BAI L, LI MS (2012) Comparative analysis of seedling drought tolerance of different era maize varieties. Acta Agronomica Sin 38(2):315–321. CrossRefGoogle Scholar
  24. Thomson MJ, Ocampo MD, Egdane J, Rahman MA, Sajise AG, Adorada DL, Tumimbang-Raiz E, Blumwald E, Seraj ZI, Singh RK, Gregorio GB, Ismail AM (2010) Characterizing the saltol quantitative trait locus for salinity tolerance in rice. Rice 3:148–160. CrossRefGoogle Scholar
  25. Tuyen DD, Lal SK, Xu DH (2010) Identification of a major QTL allele from wild soybean (Glycine soja Sieb. & Zucc.) for increasing alkaline salt tolerance in soybean. Theor Appl Genet 121(2):229–236. CrossRefPubMedGoogle Scholar
  26. Villicaña C, Warner N, Arce-Montoya M, Rojas M, Angulo C (2016) Andrés OrduñoGracia, Gómez-Anduro. Antiporter NHX2 differentially induced in Mesembryanthemum crystallinum natural genetic variant under salt stress. Plant Cell Tissue Organ. Culture 124(2):361–375. CrossRefGoogle Scholar
  27. Wang CM (2017) Separation of price and supplement + pricing-based marketization, the maize market entered a new price range. Feed China 02:30–34, 47Google Scholar
  28. Wang SL, Gao SR, Wang ZH, Lang SP, Wang JH (2012) Mapping of QTL associated with salt tolerance in maize inbred line during seedling stage. J Anhui Agri Sci 40(25):12363–12366Google Scholar
  29. Wang QZ, Liu Q, Gao YN, Liu X (2017) Review on the mechanisms of the response to saltinity-alkain1ty stress in plants. Acta Ecol Sin 37(16):1–13. CrossRefGoogle Scholar
  30. Wu DD (2014) QTL Mapping for salt tolerance at the seedling stage in maize (Zea mays L.). Dissertation, ShanDong University pp 31–48Google Scholar
  31. Xu R, Wang J, Li CD, Johnson P, Lu C, Zhou MX (2012) A Single Locus Is Responsible for Salinity Tolerance in a Chinese Landrace Barley (Hordeum vulgare L.). PLoS ONE 7(8):e43079. CrossRefPubMedPubMedCentralGoogle Scholar
  32. Xu F, Sun X, Chen Y, Huang Y, Tong C, Bao J (2015a) Rapid identification of major QTLs associated with rice grain weight and their utilization. PLoS ONE 10(3):e0122206. CrossRefPubMedPubMedCentralGoogle Scholar
  33. Xu XW, Lu L, Zhu BY, Xu Q, Qi XH, Chen XH (2015b) QTL mapping of cucumber fruit flesh thickness by SLAF-Seq. Sci Rep 5:1–9. CrossRefGoogle Scholar
  34. Xu Y, Huang L, Ji DH, Chen CS, Zheng HK, Xie CT (2015c) Construction of a dense genetic linkage map and mapping quantitative trait loci for economic traits of a doubled haploid population of Pyropia haitanensis (Bangiales, Rhodophyta). BMC Plant Biol 15:228. CrossRefPubMedPubMedCentralGoogle Scholar
  35. Yang SH, Zhang CX, Piao MX, Zhao ZS, Yang DG, Li WJ, Liu WG, Li XH (2011) Salt and alkaline tolerance analysis of sixty-nine maize inbred lines at seedling stage. Seed 30(3):1–6. CrossRefGoogle Scholar
  36. Yao ZP, Meng GJ, LI G (2007) Salinity tolerance identification and screening of maize inbreeds in seedling emergence stage. Acta Agric Boreali-Sin 22(5):27–30Google Scholar
  37. Zhang Y, Wang L, Xin H, Li D, Ma C, Ding X, Hong WG, Zhang XR (2013) Construction of a high-density genetic map for sesame based on large-scale marker development by specific length amplified fragment (SLAF) sequencing. BMC Plant Biol 13:141. CrossRefPubMedPubMedCentralGoogle Scholar
  38. Zhu GL, Deng XW, Zuo WN (1983) Determination of free proline content in plants. Plant Physiol Commun 1:35–37Google Scholar
  39. Zhu YF, Yin YF, Yang KJ, Li JH, Sang YL, Huang L, Fan S (2015) Construction of a high-density genetic map using specific length amplified fragment markers and identification of a quantitative trait locus for anthracnose resistance in walnut (Juglans regia L.). BMC Genom 16:614. CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Chunxiao Zhang
    • 1
  • Fengxue Jin
    • 1
  • Shufang Li
    • 1
  • Wenping Liu
    • 1
  • Xiaojun Ma
    • 2
  • Shan Yang
    • 2
  • Deguang Yang
    • 2
    Email author
  • Xiaohui Li
    • 1
    Email author
  1. 1.Crop Germplasm Resources Institute, Jilin Academy of Agricultural SciencesGongzhulingChina
  2. 2.College of Agronomy Northeast Agricultural UniversityHarbinChina

Personalised recommendations