Advertisement

Euphytica

, Volume 206, Issue 1, pp 117–131 | Cite as

Mining for low-nitrogen tolerance genes by integrating meta-analysis and large-scale gene expression data from maize

  • Bowen Luo
  • Haitao Tang
  • Hailan Liu
  • Su Shunzong
  • Suzhi Zhang
  • Ling Wu
  • Dan Liu
  • Shibin Gao
Article

Abstract

Nitrogen (N) is the most important macronutrient for plant growth and development. Hence, understanding genetic architectures and functional genes involved in the response to N deficiency can greatly facilitate the development of low-N-tolerant cultivars. In this study, we collected 212 quantitative trait loci (QTL) of agronomically important traits under low-N stress conditions in maize. We then identified 21 consensus QTL (cQTL) strongly induced for low-N tolerance after excluding overlapping cQTL containing QTL simultaneously identified in meta-analyses of studies performed under other environmental conditions. Among the 21 cQTL, 30 candidate maize genes were identified from maize large-scale differential expression data derived from analyses of low-N stress, and the 12 most important maize orthologs were identified using homologous BLAST analyses of genes with known functions in N use efficiency in model plants. Furthermore, maize orthologs associated with low-N tolerance and metabolism were also predicted using large-scale expression data from other model plants. The present genetic loci and candidate genes indicate the molecular mechanisms of low-N tolerance in maize and may provide information for QTL fine mapping and molecular marker-assisted selection.

Keywords

Low-N tolerance Maize Quantitative trait loci Consensus QTL Candidate genes 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (31361140364 and 31471511), the 948 Project of Ministry of Agriculture of China (2011-G15-2 and 2013-Z38), and the Key Technologies R&D Program of China during the 12th Five-Year Plan period (2011BAD35B01).

Supplementary material

10681_2015_1481_MOESM1_ESM.pdf (154 kb)
Supplementary material 1 (PDF 153 kb)
10681_2015_1481_MOESM2_ESM.pdf (151 kb)
Supplementary material 2 (PDF 151 kb)
10681_2015_1481_MOESM3_ESM.pdf (263 kb)
Supplementary material 3 (PDF 262 kb)
10681_2015_1481_MOESM4_ESM.pdf (86 kb)
Supplementary material 4 (PDF 85 kb)
10681_2015_1481_MOESM5_ESM.pdf (942 kb)
Supplementary material 5 (PDF 942 kb)
10681_2015_1481_MOESM6_ESM.pdf (174 kb)
Supplementary material 6 (PDF 174 kb)

References

  1. Agrama HAS, Zakaria AG, Said FB, Tuinstra M (1999) Identification of quantitative trait loci for nitrogen use efficiency in maize. Mol Breed 5:187–195CrossRefGoogle Scholar
  2. Araki R, Hasegawa H (2006) Expression of rice (Oryza sativa L.) genes involved in high-affinity nitrate transport during the period of nitrate induction. Breed Sci 56:295–302CrossRefGoogle Scholar
  3. Bi YM, Wang RL, Zhu T, Rothstein SJ (2007) Global transcription profiling reveals differential responses to chronic nitrogen stress and putative nitrogen regulatory components in Arabidopsis. BMC Genom. doi: 10.1186/1471-2164-8-281 Google Scholar
  4. Bi YM, Kant S, Clark J, Gidda S, Ming F, Xu JY, Rochon A, Shelp BJ, Hao LX, Zhao R, Mullen R, Zhu T, Rothstein SJ (2009) Increased nitrogen-use efficiency in transgenic rice plants over-expressing a nitrogen-responsive early nodulin gene identified from rice expression profiling. Plant Cell Environ 32:1749–1760CrossRefPubMedGoogle Scholar
  5. Cai H, Chu Q, Gu R, Yuan L, Liu J, Zhang X, Chen F, Mi G, Zhang F (2012a) Identification of QTLs for plant height, ear height and grain yield in maize (Zea mays L.) in response to nitrogen and phosphorus supply. Plant Breed 131:502–510CrossRefGoogle Scholar
  6. Cai H, Chu Q, Yuan L, Liu J, Chen X, Chen F, Mi G, Zhang F (2012b) Identification of quantitative trait loci for leaf area and chlorophyll content in maize (Zea mays) under low nitrogen and low phosphorus supply. Mol Breed 30:251–266CrossRefGoogle Scholar
  7. Cai H, Lu Y, Xie W, Zhu T, Lian X (2012c) Transcriptome response to nitrogen starvation in rice. J Biosci 37:731–747CrossRefPubMedGoogle Scholar
  8. Chardon F, Virlon B, Moreau L, Falque M, Joets J, Decousset L, Murigneux A, Charcosset A (2004) Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome. Genetics 168:2169–2185PubMedCentralCrossRefPubMedGoogle Scholar
  9. Chen L, Bush DR (1997) LHTl, a lysine-and histidine-specific transporter in Arabidopsis amino acid. Plant Physiol 115:1127–1134PubMedCentralCrossRefPubMedGoogle Scholar
  10. Chen R, Tian M, Wu X, Huang Y (2011) Differential global gene expression changes in response to low nitrogen stress in two maize inbred lines with contrasting low nitrogen tolerance. Genes Genomics 33:491–497CrossRefGoogle Scholar
  11. Coque M, Gallais A (2006) Genomic regions involved in response to grain yield selection at high and low nitrogen fertilization in maize. Theor Appl Genet 112:1205–1220CrossRefPubMedGoogle Scholar
  12. Coque M, Martin A, Veyrieras JB, Hirel B, Gallais A (2008) Genetic variation for N-remobilization and postsilking N-uptake in a set of maize recombinant inbred lines.3. QTL detection and coincidences. Theor Appl Genet 117:729–747CrossRefPubMedGoogle Scholar
  13. Eveland AL, Satoh-Nagasawa N, Goldshmidt A, Meyer S, Beatty M, Sakai H, Ware D, Jackson D (2010) Digital gene expression signatures for maize development. Plant Physiol 154:1024–1039PubMedCentralCrossRefPubMedGoogle Scholar
  14. Frink CR, Waggoner PE, Ausubel JH (1999) Nitrogen fertilizer: retrospect and prospect. Proc Natl Acad Sci USA 96:1175–1180PubMedCentralCrossRefPubMedGoogle Scholar
  15. Fu J, Tian H, Gao YJ (2013) Study progress of molecular approaches in improving nitrogen use efficiency of crop plants. Soil Fertil Sci China 4:79–82Google Scholar
  16. Garnett T, Conn V, Kaiser BN (2009) Root based approaches to improving nitrogen use efficiency in plants. Plant Cell Environ 32:1272–1283CrossRefPubMedGoogle Scholar
  17. Gifford ML, Dean A, Gutierrez RA, Coruzzi GM, Birnbaum KD (2008) Cell-specific nitrogen responses mediate developmental plasticity. Proc Natl Acad Sci USA 105:803–808PubMedCentralCrossRefPubMedGoogle Scholar
  18. Giles J (2005) Nitrogen study fertilizes fears of pollution. Nature 433:791–791CrossRefPubMedGoogle Scholar
  19. Goffinet B, Gerber S (2000) Quantitative trait loci: a meta-analysis. Genetics 155:463–473PubMedCentralPubMedGoogle Scholar
  20. Hao Z, Li X, Liu X, Xie C, Li M, Zhang D, Zhang S (2010) Meta-analysis of constitutive and adaptive QTL for drought tolerance in maize. Euphytica 174:165–177CrossRefGoogle Scholar
  21. Himer A, Ladwig F, Stransky H, Okumoto S, Keinath M, Harms A, Frommer WB, Koch W (2006) Arabidopsis LHT1 is a high-affinity transporter for cellular amino acid uptake in both root epidermis and leaf mesophyll. Plant Cell 18:1931–1946CrossRefGoogle Scholar
  22. Hirel B, Bertin P, Quilleré I, Bourdoncle W, Attagnant C, Dellay C, Gouy A, Cadiou S, Catherine R, Falque M, Gallais A (2001) Towards a better understanding of the genetic and physiological basis for nitrogen use efficiency in maize. Plant Physiol 125:1258–1270PubMedCentralCrossRefPubMedGoogle Scholar
  23. Ho CH, Lin SH, Hu HC, Tsay YF (2009) CHL1 functions as a nitrate sensor in plants. Cell 138:1184–1194CrossRefPubMedGoogle Scholar
  24. Hu HC, Wang YY, Tsay YF (2009) AtCIPK8, a CBL-interacting protein kinase, regulates the low-affinity phase of the primary nitrate response. Plant J 57:264–278CrossRefPubMedGoogle Scholar
  25. Humbert S, Subedi S, Cohn J, Zeng B, Chen X, Zhu T, McNicholas PD, Rothstein SJ (2013) Genome-wide expression profiling of maize in response to individual and combined water and nitrogen stresses. BMC Genom. doi: 10.1186/1471-2164-14-3 Google Scholar
  26. Hung HY, Shannon LM, Tian F, Bradbury PJ, Chen C, Flint-Garcia SA, McMullen MD, Ware D, Buckler ES, Doebley JF, Holland JB (2012) ZmCCT and the genetic basis of day-length adaptation underlying the postdomestication spread of maize. Proc Natl Acad Sci USA 109:1913–1921CrossRefGoogle Scholar
  27. Ishiyama K, Inoue E, Tabuchi M, Yamaya T, Takahashi H (2004) Biochemical background and compartmentalized functions of cytosolic glutamine synthetase for active ammonium assimilation in rice roots. Plant Cell Physiol 45:1640–1647CrossRefPubMedGoogle Scholar
  28. Kant S, Bi YM, Rothstein SJ (2011) Understanding plant response to nitrogen limitation for the improvement of crop nitrogen use efficiency. J Exp Bot 62:1499–1509CrossRefPubMedGoogle Scholar
  29. Krapp A, Berthomé R, Orsel M, Mercey-Boutet S, Yu A, Castaings L, Elftieh S, Major H, Renou JP, Daniel-vedele F (2011) Arabidopsis roots and shoots show distinct temporal adaptation patterns toward nitrogen starvation. Plant Physiol 157:1255–1282PubMedCentralCrossRefPubMedGoogle Scholar
  30. Krouk G, Grawford NM, Coruzzi GM, Tsay YF (2010) Nitrate signaling: adaptation to fluctuating environments. Curr Opin Plant Biol 13:266–273CrossRefPubMedGoogle Scholar
  31. Kurai T, Wakayama M, Abiko T, Schuichi Y, Aoki N, Ohugi R (2011) Introduction of the ZmDof1 gene into rice enhances carbon and nitrogen assimilation under low-nitrogen conditions. Plant Biotechnol J 9:826–837CrossRefPubMedGoogle Scholar
  32. Li JY, Fu YL, Pike SM, Bao J, Tian W, Zhang Y, Chen CZ, Zhang Y, Li HM, Huang J, Li LG, Schroeder JI, Gassmann W, Gong JM (2010a) The Arabidopsis nitrate transporter NRT1.8 functions in nitrate removal from the xylem sap and mediates cadmium tolerance. Plant Cell 22:1633–1646PubMedCentralCrossRefPubMedGoogle Scholar
  33. Li L, Li H, Li J, Xu S, Yang X, Li J, Yan J (2010b) A genome-wide survey of maize lipid-related genes: candidate genes mining, digital gene expression profiling and co-location with QTL for maize kernel oil. Sci China Life Sci 53:690–700CrossRefPubMedGoogle Scholar
  34. Li WJ, Liu ZZ, Shi YS, Song YC, Wang TY, Xu CW, Li Y (2010c) Detection of consensus genomic region of QTLs relevant to drought-tolerance in maize by QTL meta-analysis and bioinformatics approach. Acta Agron Sin 36:1457–1467CrossRefGoogle Scholar
  35. Li L, Li H, Li Q, Yang X, Zheng D, Warburton M, Chai Y, Zhang P, Guo Y, Yan J, Li J (2011) An 11-bp insertion in Zea mays fatb reduces the palmitic acid content of fatty acids in maize grain. PLoS One. doi: 10.1371/journal.pone.0024699 Google Scholar
  36. Liang G, He H, Yu D (2012) Identification of nitrogen starvation-responsive microRNAs in Arabidopsis thaliana. PLoS One. doi: 10.1371/journal.pone.0048951 Google Scholar
  37. Liseron-Monfils C, Bi YM, Downs GS, Wu W, Signorelli T, Lu G, Chen X, Bondo E, Zhu T, Lukens LN, Colasanti J, Rothstein SJ, Raizada MN (2013) Nitrogen transporter and assimilation genes exhibit developmental stage-selective expression in maize (Zea mays L.) associated with distinct cis-acting promoter motifs. Plant Signal Behav. doi: 10.4161/psb.26056 PubMedCentralPubMedGoogle Scholar
  38. Liu XH, He SL, Zheng ZP, Huang YB, Tan ZB, Li Z, He C, Wu X, Pu QB (2010a) Identification of the QTLs for grain yield using RIL population under different nitrogen regimes in maize. Afr J Agric Res 5:2002–2007Google Scholar
  39. Liu XH, Zheng ZP, Tan ZB, Li Z, He C (2010b) Quantitative trait locus (QTL) mapping for 100-kernel weight of maize (Zea mays L.) under different nitrogen regimes. Afr J Biotechnol 9:8283–8289Google Scholar
  40. Liu XH, He SL, Zheng ZP, Huang YB, Tan ZB, Wu X (2010c) QTL identification for row number per ear and grain number per row in maize. Maydica 55:127–133Google Scholar
  41. Liu XH, He S, Zheng Z, Tan Z, Liu D (2010d) Identification of the quantitative trait loci for grain rate in maize. Afr J Biotechnol 9:8007–8012Google Scholar
  42. Liu XH, Zheng ZP, Tan ZB, Li Z, He C (2010e) Genetic analysis of two new quantitative trait loci for ear weight in maize inbred line Huangzao4. Genet Mol Res 9:2140–2147CrossRefPubMedGoogle Scholar
  43. Liu R, Zhang H, Zhao P, Zhang Z, Liang W, Tian Z, Zheng Y (2012) Mining of candidate maize genes for nitrogen use efficiency by integrating gene expression and QTL data. Plant Mol Biol Rep 30:297–308CrossRefGoogle Scholar
  44. Loqué D, Wirén NV (2004) Regulatory levels for the transport of ammonium in plant roots. J Exp Bot 55:1293–1305CrossRefPubMedGoogle Scholar
  45. Lu H, Xue J, Ma G, Zhang R, Zhang X (2010) Effects of low nitrogen stress on source-sink characters and grain-filling traits of different genotypes summer maize. Chin J Appl Ecol 21:1277–1282Google Scholar
  46. Martin A, Lee J, Kichey T, Gerentes D, Zivy M, Tatout C, Dubois F, Balliau T, Valot B, Davanture M, Laforgue TT, Quilleré I, Coque M, Gallais A, Gonzalez-Moro MB, Bethencourt L, Habash DZ, Lea PJ, Charcosset A, Perez P, Murigneux A, Sakakibara H, Edwards KJ, Hirel B (2006) Two cytosolic glutamine synthetase isoforms of maize are specifically involved in the control of grain production. Plant Cell 18:3252–3274PubMedCentralCrossRefPubMedGoogle Scholar
  47. Peng M, Bi YM, Zhu T, Rothstein SJ (2007) Genome-wide analysis of Arabidopsis responsive transcriptome to nitrogen limitation and its regulation by the ubiquitin ligase gene NLA. Plant Mol Biol 65:775–797CrossRefPubMedGoogle Scholar
  48. Plett D, Toubia J, Garnett T, Tester M, Kaiser BN, Ute B (2010) Dichotomy in the NRT gene families of dicots and grass species. PLoS One. doi: 10.1371/journal.pone.0015289 Google Scholar
  49. Ribaut JM, Frachebound Y, Monneveux P, Banziger M, Vargas M, Jiang C (2007) Quantitative trait loci for yield and correlated traits under high and low soil nitrogen conditions in tropical maize. Mol Breed 20:15–29CrossRefGoogle Scholar
  50. Semagn K, Beyene Y, Warburton ML, Tarekegne A, Mugo S, Meisel B, Sehabiague P, Prasanna BM (2013) Meta-analyses of QTL for grain yield and anthesis silking interval in 18 maize populations evaluated under water-stressed and well-watered environments. BMC Genom. doi: 10.1186/1471-2164-14-313 Google Scholar
  51. Sun H, Qian Q, Wu K, Luo J, Wang S, Zhang C, Ma Y, Liu Q, Huang X, Yuan Q, Han R, Zhao M, Dong G, Guo L, Zhu X, Gou Z, Wang W, Wu Y, Lin H (2014) Fu X (2014) Heterotrimeric G proteins regulate nitrogen-use efficiency in rice. Nat Genet 46:652–656CrossRefPubMedGoogle Scholar
  52. Swamy BPM, Sarla N (2011) Meta-analysis of yield QTLs derived from inter-specific crosses of rice reveals consensus regions and candidate genes. Plant Mol Biol Rep 29:663–680CrossRefGoogle Scholar
  53. Tsay YF, Schroeder JI, Feldmann KA, Crawford NM (1993) The herbicide sensitivity gene CHL1 of Arabidopsis encodes a nitrate-inducible nitrate transporter. Cell 72:705–713CrossRefPubMedGoogle Scholar
  54. Tuberosa R, Salvi S, Sanguineti MC, Landi P, Maccaferri M, Conti S (2002) Mapping QTL regulating morpho-physiological traits and yield: case studies, shortcomings and perspectives in drought-stressed maize. Ann Bot 89:941–963PubMedCentralCrossRefPubMedGoogle Scholar
  55. Wu X, Liu Y, Tian M, Chen R, Zheng Z, He C, Huang Y, Zhang J, Liu H, Li Z (2011) Genomics analysis of genes expressed reveals differential responses to low chronic nitrogen stress in maize. Afr J Biotechnol 10:939–949CrossRefGoogle Scholar
  56. Xu Z, Zhong S, Li X, Li W, Rothstein SJ, Zhang S, Bi Y, Xie C (2011) Genome-wide identification of microRNAs in response to low nitrate availability in maize leaves and roots. PLoS One. doi: 10.1371/journal.pone.0028009 Google Scholar
  57. Xu G, Fan X, Miller AJ (2012a) Plant nitrogen assimilation and use efficiency. Annu Rev Plant Biol 63:153–182CrossRefPubMedGoogle Scholar
  58. Xu J, Liu Y, Cao M, Wang J, Lan H, Xu Y, Lu Y, Pan G, Rong T (2012b) The genetic architecture of flowering time and photoperiod sensitivity in maize as revealed by QTL review and meta analysis. J Integr Plant Biol 54:358–373CrossRefPubMedGoogle Scholar
  59. Yao Q, Hu F, Xu J (2011) The effects of low-N stress on plant morphology and photosynthesis of maize landraces at seedling stage. J Henan Agric Sci 40:37–41Google Scholar
  60. Zamboni A, Astolfi S, Zuchi S, Pii Y, Guardini K, Tononi P, Varanini Z (2014) Nitrate induction triggers different transcriptional changes in a high and a low nitrogen use efficiency maize inbred line. J Integr Plant Biol 56:1080–1089CrossRefPubMedGoogle Scholar
  61. Zhang H, Forde BG (1998) An Arabidopsis MADS box gene that controls nutrient-induced changes in root architecture. Science 279:407–409CrossRefPubMedGoogle Scholar
  62. Zhang W, Zhao Z, Bai G, Fu F, Cao S (2007) Response on water stress and low nitrogen in different maize hybrid varieties and evaluation for their adversity-resistance. Sci Agric Sin 40:1361–1370Google Scholar
  63. Zhang H, Zheng Z, Liu X, Li Z, He C, Liu D, Luo Y, Zhang G, Tan Z, Li R (2010a) QTL mapping for ear length and ear diameter under different nitrogen regimes in maize. Afr J Agric Res 5:626–630Google Scholar
  64. Zhang X, Xue J, Liu W, Li F, Zhang R (2010b) Screening and identification of low nitrogen tolerance in different maize hybrids. Acta Agric Boreal Occident Sin 19:65–68Google Scholar
  65. Zhang J, Xu L, Wang F, Deng M, Yi K (2012) Modulating the root elongation by phosphate/nitrogen starvation in an OsGLU3 dependant way in rice. Plant Signal Behav 7:1144–1145PubMedCentralCrossRefPubMedGoogle Scholar
  66. Zhang HW, Uddin MS, Zou C, Xie C, Xu Y, Li WX (2014) Meta-analysis and candidate gene mining of low-phosphorus tolerance in maize. J Integr Plant Biol 56:262–270CrossRefPubMedGoogle Scholar
  67. Zhao XQ, Shi WM (2006) Expression analysis of the glutamine synthetase and glutamate synthase gene families in young rice (Oryza sativa) seedlings. Plant Sci 170:748–754CrossRefGoogle Scholar
  68. Zhao M, Tai H, Sun S, Zhang F, Xu Y, Li WX (2012) Cloning and characterization of maize miRNAs involved in responses to nitrogen deficiency. PLoS One. doi: 10.1371/journal.pone.0029669 Google Scholar
  69. Zheng ZP, Liu XH (2013a) Genetic analysis of agronomic traits associated with plant architecture by QTL mapping in maize. Genet Mol Res 12:1243–1253CrossRefPubMedGoogle Scholar
  70. Zheng ZP, Liu XH (2013b) QTL identification of ear leaf morphometric traits under different nitrogen regimes in maize. Genet Mol Res 12:4342–4351CrossRefPubMedGoogle Scholar
  71. Zheng Z, He C, Li Z, Huang Y (2005) Detecting QTLs for ear length under two nitrogen levels. J Maize Sci 13:102–104Google Scholar
  72. Zheng ZP, Liu XH, Wu X, Zhang YS, He C (2011) Genetic loci mapping for ear axis weight using recombinant inbred line (RIL) population under different nitrogen regimes in maize. Afr J Biotechnol 10:8255–8259Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Bowen Luo
    • 1
    • 2
  • Haitao Tang
    • 3
  • Hailan Liu
    • 1
    • 2
  • Su Shunzong
    • 1
    • 2
  • Suzhi Zhang
    • 1
    • 2
  • Ling Wu
    • 1
    • 2
  • Dan Liu
    • 1
    • 2
  • Shibin Gao
    • 1
    • 2
  1. 1.Maize Research InstituteSichuan Agricultural UniversityChengduChina
  2. 2.Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMinistry of AgricultureChengduChina
  3. 3.Crop Research InstituteSichuan Academy of Agricultural SciencesChengduChina

Personalised recommendations