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Identification of Candidate Transcripts Related to Drought Stress using Secondary Traits and qRT-PCR in Tropical Maize (Zea mays L.)

  • Kim, Hyo Chul (Department of Life Science, Dongguk University-Seoul) ;
  • Song, Kitae (Department of Life Science, Dongguk University-Seoul) ;
  • Moon, Jun-Cheol (Agriculture and Life Sciences Research Institute, Kangwon National University) ;
  • Kim, Jae Yoon (Department of Plant Resources, College of Industrial Science, Kongju National University) ;
  • Kim, Kyung-Hee (Department of Life Science, Dongguk University-Seoul) ;
  • Lee, Byung-Moo (Department of Life Science, Dongguk University-Seoul)
  • 투고 : 2019.11.02
  • 심사 : 2019.11.13
  • 발행 : 2019.12.31

초록

Global climate change exerts adverse effects on maize production. Among abiotic stresses, drought stress during the tasseling stage (VT) can increase anthesis-silking intervals (ASI) and decrease yield. We performed an evaluation of ASI and yield using a drought-sensitive line (Ki3) and a drought-tolerant line (Ki11) to analyze the correlation with ASI and yield. Moreover, the de novo data of Ki11 were analyzed to find putative novel transcripts related todrought stress in tropical maize. A total of 182 transcripts, with a log2 ratio >1.5, were found by comparing drought conditions to a control. The top 40 transcripts of high expression levels in the de novo analysis were selected and analyzed with PCR. Of the 40 transcripts, six novel transcripts were detected by quantitative real-time PCR (qRT-PCR) using seedling and VT stage samples. Five transcripts (transcripts_1, 12, 34, 35, and 40) were up-regulated in the Ki11 shoot at seedling stage, and transcripts_1, 12, and 40 were up-regulated at the re-watering stage after 12 h of drought stress. The transcripts_32 and 34 were up-regulated at the VT stage. Hence, transcript_34 possibly plays a significant role in drought tolerance during the seedling and VT stages. The transcript_32 was identified as chloramphenicol acetyltransferase (CAT) by Pfam domain analysis. The function of the other transcripts remained unknown. Further characterization of these novel transcripts in genetic regulation will be of great value for the improvement of maize production.

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참고문헌

  1. Almeida, G. D., D. Makumbi, C. Magorokosho, S. Nair, A. Borem, J.-M. Ribaut, M. Banziger, B. M. Prasanna, J. Crossa, and R. Babu. 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. https://doi.org/10.1007/s00122-012-2003-7
  2. Baker, M. 2012. De novo genome assembly: what every biologist should know. Nat. Methods. 9 : 333. https://doi.org/10.1038/nmeth.1935
  3. Banzinger, M., G. O. Edmeades, D. L. Beck, and M. Bellon. 2000. Breeding for drought and N stress tolerance in maize: from theory to practice. CIMMYT, Mexico, D. F.
  4. Banzinger, M., P. S. Setimela, D. Hodson, and B. Vivek. 2006. Breeding for improved abiotic stress tolerance in maize adapted to southern Africa. Agr. Water Manage. 80 : 1-3 https://doi.org/10.1016/j.agwat.2005.07.002
  5. Bassetti, P. and M. E. Westgate. 1993. Water deficit affects receptivity of maize silks. Crop Sci. 33 : 279-282. https://doi.org/10.2135/cropsci1993.0011183X003300020013x
  6. Bawa, A., I. K. Addai, and J. X. Kugbe. 2015. Evaluation of some genotypes of maize (Zea mays L.) for tolerance to drought in Northern Ghana. Plant Biol. 5(6) : 19-29.
  7. Birol, I., S. D. Jackman, C. B. Nielsen, J. Q. Qian, R. Varhol, G. Stazyk, R. D. Morin, Y. Zhao, M. Hirst, J. E. Schein, D. E. Horsman, J. M. Connors, R. D. Gascoyne, M. A. Marra, and S. J. M. Jones. 2009. De novo transcriptome assembly with ABySS. Bioinformatics. 25(21) : 2872-7. https://doi.org/10.1093/bioinformatics/btp367
  8. Bohnert, H. J., D. E. Nelson, and R. G. Jensen. 1995. Adaptations to environmental stresses. The plant cell. 7(7) : 1099-1111. https://doi.org/10.2307/3870060
  9. Bolanos, J. and G. O. Edmeades. 1993. Eight cycle of selection for drought tolerance in lowland tropical maize. II. Responses in reproductive behavior. Field Crops Res. 31 : 269-289. https://doi.org/10.1016/0378-4290(93)90066-V
  10. Bolanos, J. and G. O. Edmeades. 1996. The importance of the anthesis-silking interval in breeding for drought tolerance in tropical maize. Field Crops Research. 48 : 65-80. https://doi.org/10.1016/0378-4290(96)00036-6
  11. Bradnam, K. R., J. N. Fass, A. Alexandrov, P. Baranay, M. Bechner, I. Birol, S. Boisvert, J. A. Chapman, G. Chapuis, R. Chikhi, H. Chitsaz, W. C. Chou, J. Corbeil, C. Del Fabbro, T. R. Docking, R. Durbin, D. Earl, S. Emrich, P. Fedotov, N. A. Fonseca, G. Ganapathy, R. A. Gibbs, S. Gnerre, E. Godzaridis, S. Goldstein, M. Haimel, G. Hall, D. Haussler, J. B. Hiatt, I. Y. Ho, J. Howard, M. Hunt, S. D. Jackman, D. B. Jaffe, E. D. Jarvis, H. Jiang, S. Kazakov, P. J. Kersey, J. O. Kitzman, J. R. Knight, S. Koren, T. W. Lam, D. Lavenier, F. Laviolette, Y. Li, Z. Li, B. Liu, Y. Liu, R. Luo, I. Maccallum, M. D. Macmanes, N. Maillet, S. Melnikov, D. Naquin, Z. Ning, T. D. Otto, B. Paten, O. S. Paulo, A. M. Phillippy, F. Pina-Martins, M. Place, D. Przybylski, X. Qin, C. Qu, F. J. Ribeiro, S. Richards, D. S. Rokhsar, J. G. Ruby, S. Scalabrin, M. C. Schatz, D. C. Schwartz, A. Sergushichev, T. Sharpe, T. I. Shaw, J. Shendure, Y. Shi, J. T. Simpson, H. Song, F. Tsarev, F. Vezzi, R. Vicedomini, B. M. Vieira, J. Wang, K. C. Worley, S. Yin, S. M. Yiu, J. Yuan, G. Zhang, H. Zhang, S. Zhou, and I. F. Korf. 2013. Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species. Gigascience. 2 : 1-31. https://doi.org/10.1186/2047-217X-2-1
  12. Bray, E. A. 1993. Molecular responses to water deficit. Plant Physiol. 103(4) : 1035-1040. https://doi.org/10.1104/pp.103.4.1035
  13. Briskine, R. V. and K. K. Shimizu. 2017. Positional bias in variant calls against draft reference assemblies. BMC Genomics. 18 : 1. https://doi.org/10.1186/s12864-016-3406-7
  14. Buckler, E. S., J. B. Holland, P. J. Bradbury, C. Acharya, P. J. Brown, C. Browne, E. Ersoz, S. Flint-Garcia, A. Garcia, J. C. Glaubitz, M. M. Goodman, C. Harjes, K. Guill, D. E. Kroon, S. Larsson, N. K. Lepak, H. Li, S. E. Mitchell, G. Pressoir, J. A. Peiffer, M. O. Rosas, T. R. Rocheford, M. C. Romay, S. Romero, S. Salvo, V. H. Sanchez, H. S. da Silva, Q. Sun, F. Tian, N. Upadyayula, D. Ware, H. Yates, J. Yu, Z. Zhang, S. Kresovich, and M. D. McMullen. 2009. The genetic architecture of maize flowering time. Science. 325 : 714-718. https://doi.org/10.1126/science.1174276
  15. Byrne, P. F., J. Bolanos, G. O. Edmeades, and D. L. Eaton. 1995. Gains from selection under drought versus multilocation testing in related tropical maize populations. Crop Science. 35 : 63. https://doi.org/10.2135/cropsci1995.0011183X003500010011x
  16. Chapman, S. C. and G. O. Edmeades. 1999. Selection improves drought tolerance in tropical maize populations : II. Direct and correlated responses among secondary traits. Crop Science. 39 : 1315-1324. https://doi.org/10.2135/cropsci1999.3951315x
  17. Duan, J., C. Xia, G. Zhao, J. Jia, and X. Kong. 2012. Optimizing de novo common wheat transcriptome assembly using short-read RNA-Seq data. BMC Genomics. 13(1) : 392. https://doi.org/10.1186/1471-2164-13-392
  18. Edmeades, G. O., M. Banziger, A. Elings, S. C. Chapman, and J. M. Ribaut. 1997. Recent advances in breeding for drought tolerance in maize. Applications of Systems Approaches at the Field Level. 63-78.
  19. Edmeades, G. O., J. Bolanos, A. Elings, J. M. Ribaut, M. Banziger, and M. E. Westgate. 2000. The role and regulation of the anthesis-silking interval in maize. In: Westgate, M. E. and K. J. Boote. (eds). Physiology and Modeling Kernel Set in Maize. CSSA, Madison, WI, CSSA Special Publication No. 29. pp. 43-73.
  20. Fan, H., Y. Xiao, Y. Yang, W. Xia, A. S. Mason, Z. H. Xia, F. Qiao, S. L. Zhao, and H. R. Tang. 2013. RNA-Seq analysis of Cocos nucifera : transcriptome sequencing and de novo assembly for subsequent functional genomics approaches. PloS one. 8(3) : e59997. https://doi.org/10.1371/journal.pone.0059997
  21. Fuad-Hassan, A., F. Tardieu, and O. Turc. 2008. Drought-induced changes in anthesis-silking interval are related to silk expansion: a spatio-temporal growth analysis in maize plants subjected to soil water deficit. Plant, Cell and Environ. 31 : 1349-1360. https://doi.org/10.1111/j.1365-3040.2008.01839.x
  22. Grabherr, M. G., B. J. Haas, M. Yassour, J. Z. Levin, D. A. Thompson, I. Amit, X. Adiconis, L. Fan, R. Raychowdhury, Q. Zeng, Z. Chen, E. Mauceli, N. Hacohen, A. Gnirke, N. Rhind, F. di Palma, B. W. Birren, C. Nusbaum, K. Lindblad-Toh, N. Friedman, and A. Regev. 2011. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 29(7) : 644-52. https://doi.org/10.1038/nbt.1883
  23. Gong, F., L. Yang, F. Tai, X. Hu, and W. Wang. 2014. "Omics" of maize stress response for sustainable food production: opportunities and challenges. Omics 18(12) : 714-732. https://doi.org/10.1089/omi.2014.0125
  24. Hall, A. J., J. H. Lemcoff, and N. Trapani. 1981. Water stress before and during flowering in maize and its effects on yield, its components, and their determinants. Maydica. 26 : 19-38.
  25. Harder, H. J., R. E. Carlson, and R. H. Shaw. 1982. Yield, yield components, and nutrient content of corn grains as influenced by post-silking moisture stress. Agronomy J. 74(2) : 275-278. https://doi.org/10.2134/agronj1982.00021962007400020005x
  26. Kim, H. C., J.-C. Moon, J. Y. Kim, K. Song, K.-H. Kim, and B.-M. Lee. 2017. Evaluation of drought tolerance using anthesissilking interval in maize. Korean J. Crop Sci. 62(1) : 24-31. https://doi.org/10.7740/kjcs.2016.62.1.024
  27. Lehtimaki, N., M. Lintala, Y. Allahverdiyeva, E. M. Aro, and P. Mulo. 2010. Drought stress-induced upregulation of components involved in ferredoxin-dependent cyclic electron transfer. J Plant Physiol. 167 : 1018-1022. https://doi.org/10.1016/j.jplph.2010.02.006
  28. Li, R., C. Yu, Y. Li, T. W. Lam, S. M. Yiu, K. Kristiansen, and J. Wang. 2009. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics. 25(15) : 1966-1997. https://doi.org/10.1093/bioinformatics/btp336
  29. Li, Y. X., C. Li, P. J. Bradbury, X. Liu, F. Lu, C. M. Romay, J. C. Glaubitz, X. Wu1, B. Peng, Y. Shi, Y. Song, D. Zhang, E. S. Buckler, Z. Zhang, Y. Li, and T. Wang. 2016. Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population. Plant J. 86 : 391-402. https://doi.org/10.1111/tpj.13174
  30. Lischer, H. E. L. and K. K. Shimizu. 2017. Reference-guided de novo assembly approach improves genome reconstruction for related species. BMC Bioinformatics. 18 : 474. https://doi.org/10.1186/s12859-017-1911-6
  31. Livak, K. J. and T. D. Schmittgen. 2001. Analysis of relative gene expression data using real-time quantitative PCR and the $2^{-{\Delta}{\Delta}CT}$ Method. Methods. 25 : 402-408. https://doi.org/10.1006/meth.2001.1262
  32. Lu, Y., Z. Hao, C. Xie, J. Crossa, J. L. Arus, S. Gao, B. S. Vivek, C. Magorokosho, S. Mugo, D. Makumbi, S. Taba, G. Pan, X. Li, T. Rong, S. Zhang, and Y. Xu. 2011. Large-scale screening for maize drought resistance using multiple selection criteria evaluated under water-stressed and well-watered environments. Field Crops Res. 124(1) : 37-45. https://doi.org/10.1016/j.fcr.2011.06.003
  33. Manoli, A., A. Sturaro, S. Trevisan, S. Quaggiotti, and A. Nonis. 2012. Evaluation of candidate reference genes for qPCR in maize. J. Plant Physiol. 169 : 807-815. https://doi.org/10.1016/j.jplph.2012.01.019
  34. Moon, J.-C., S. Shin, H. C. Kim, K. Song, J. Y. Kim, K.-H. Kim, and B.-M. Lee. 2018. Assessment of the candidate genes of expression marker associated with drought stress in maize seedling. Korean J. Breed. Sci. 50(3) : 229-240.
  35. Moss, G. I. and L. A. Downey. 1971. Influence of drought stress on female gametophyte development in corn (Zea mays L.) and subsequent grain yield. Crop Sci. 11(3) : 368-372. https://doi.org/10.2135/cropsci1971.0011183X001100030017x
  36. Mulo, P. 2011. Chloroplast-targeted ferredoxin-NADP+oxidoreductase (FNR): Structure, function and location. Biochim Biophys Acta. 1807 : 927-934. https://doi.org/10.1016/j.bbabio.2010.10.001
  37. Shendure, J. and H. Ji. 2008. Next-generation DNA sequencing. Nat Biotechnol. 26 : 1135-1145. https://doi.org/10.1038/nbt1486
  38. Schulz, M. H., D. R. Zerbino, M. Vingron, and E. Birney. 2012. Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels. Bioinformatics 28(8) : 1086-1092. https://doi.org/10.1093/bioinformatics/bts094
  39. Shin, S. H., J. S. Lee, S. G. Kim, T. H. Go, J. Y. Shon, S. G. Kang, J.-S. Lee, H. H. Bae, J.-T. Kim, K.-B. Shim, W. Yang, and M.-O. Woo. 2015. Yield of maize (Zea mays L.) logistically declined with increasing length of the consecutive visible wilting days during flowering. J. Crop Sci. Biotech. 18(4) : 237-248. https://doi.org/10.1007/s12892-015-0112-y
  40. Song, K., K.-H. Kim, H. C. Kim, J.-C. Moon, J. Y. Kim, S.-B. Baek, Y. U. Kwon, and B.-M. Lee. 2015. Evaluation of drought tolerance in maize seedling using leaf rolling. Korean J. Crop sci. 60(1) : 8-16. https://doi.org/10.7740/kjcs.2014.60.1.008
  41. Song, K., H. C. Kim, K.-H. Kim, J.-C. Moon, J. Y. Kim, S.-K. Lee, and B.-M. Lee. 2018. Gene Expression Analysis and Polymorphism Discovery to Investigate Drought Responsive System in Tropical Maize. Plant Breeding and Biotechnology. 6(4) : 354-362. https://doi.org/10.9787/PBB.2018.6.4.354
  42. Treangen, T. J. and S. L. Salzberg. 2012. Repetitive DNA and nextgeneration sequencing: computational challenges and solutions. Nat. Rev. Genet. 13(1) : 36-46. https://doi.org/10.1038/nrg3117
  43. Udomprasert, N., J. Kijjanon, K. C. Iam, and A. Machuay. 2005. Effects of water deficit at tasseling on photosynthesis, development, and yield of corn. Kastsart J. (Nat. Sci.). 39 : 546-551.
  44. Westgate, M. E. and J. S. Boyer. 1985. Carbohydrate re-serves and reproductive development at low leaf water potentials in maize. Crop Sci. 25(5) : 762-769. https://doi.org/10.2135/cropsci1985.0011183X0025000500010x
  45. Xia, Z., H. Xu, J. Zhai, D. Li, H. Luo, C. He, and X. Huang. 2011. RNA-Seq analysis and de novo transcriptome assembly of Hevea brasiliensis. Plant Molecular Biology. 77(3) : 299. https://doi.org/10.1007/s11103-011-9811-z
  46. Zhao, Q. T., Y. Wang, Y. M. Kong, D. Luo, X. Li, and P. Hao. 2011. Optimizing de novo transcriptome assembly from short-read RNA-Seq data: a comparative study. BMC Bioinformatics. 12 (suppl. 14) : S2.
  47. Ziyomo, C. and R. Bernardo. 2013. Drought tolerance in maize: indirect selection through secondary traits versus genomewide selection. Crop Science. 53 : 1269. https://doi.org/10.2135/cropsci2012.11.0651