Marker-Assisted Backcross Breeding of Drought-Tolerant Maize Lines Transformed by Vacuolar H+-Pyrophosphatase Gene (AnVP1) from Ammopiptanthus nanus
Abstract
1. Introduction
2. Results
2.1. Polymorphic InDel Markers
2.2. Homozygous BC2F3 Lines
2.3. Stable Expression of Transgenic AnVP1 Gene
2.4. Enhancement of Drought Tolerance
2.5. Field Phenotype of Drought Tolerance
3. Discussion
4. Materials and Methods
4.1. Identification of Length Variation Sites
4.2. Design, Screening, and Evaluation of InDel Markers
4.3. Foreground Selection
4.4. InDel Marker-Assisted Background Selection
4.5. RT-PCR and RT-qPCR
4.6. Pot Evaluation of Drought Tolerance
4.7. Field Phenotyping of Drought Tolerance
4.8. Statistical Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Harrison, M.T.; Tardieu, F.; Dong, Z.; Messina, C.D.; Hammer, G.L. Characterizing drought stress and trait influence on maize yield under current and future conditions. Glob. Change Biol. 2014, 20, 867–878. [Google Scholar] [CrossRef] [PubMed]
- Wang, Y.; Zhao, W.; Zhang, Q.; Yao, Y. Characteristics of drought vulnerability for maize in the eastern part of Northwest China. Sci. Rep. 2019, 9, 964. [Google Scholar] [CrossRef]
- Rattalino Edreira, J.I.; Guilpart, N.; Sadras, V.; Cassman, K.G.; van Ittersum, M.K.; Schils, R.L.M.; Grassini, P. Water productivity of rainfed maize and wheat: A local to global perspective. Agric. For. Meteorol. 2018, 259, 364–373. [Google Scholar] [CrossRef] [PubMed]
- Wang, X.; Muller, C.; Elliot, J.; Mueller, N.D.; Ciais, P.; Jagermeyr, J.; Gerber, J.; Dumas, P.; Wang, C.; Yang, H.; et al. Global irrigation contribution to wheat and maize yield. Nat. Commun. 2021, 12, 1235. [Google Scholar] [CrossRef]
- Fuad-Hassan, A.; Tardieu, F.; Turc, O. 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 Environ. 2008, 31, 1349–1360. [Google Scholar] [CrossRef] [PubMed]
- Cooper, M.; Gho, C.; Leafgren, R.; Tang, T.; Messina, C. Breeding drought-tolerant maize hybrids for the US corn-belt: Discovery to product. J. Exp. Bot. 2014, 65, 6191–6204. [Google Scholar] [CrossRef]
- Simtowe, F.; Amondo, E.; Marenya, P.; Rahut, D.; Sonder, K.; Erenstein, O. Impacts of drought-tolerant maize varieties on productivity, risk, and resource use: Evidence from Uganda. Land Use Policy 2019, 88, 104091. [Google Scholar] [CrossRef]
- Barbosa, P.A.M.; Fritsche-Neto, R.; Andrade, M.C.; Petroli, C.D.; Burgueno, J.; Galli, G.; Willcox, M.C.; Sonder, K.; Vidal-Martinez, V.A.; Sifuentes-Ibarra, E.; et al. Introgression of maize diversity for drought tolerance: Subtropical maize landraces as source of new positive variants. Front. Plant Sci. 2021, 12, 691211. [Google Scholar] [CrossRef]
- Hu, Z.; Wu, Z.; Zhang, Y.; Li, Q.; Islam, A.R.M.T.; Pan, C. Risk assessment of drought disaster in summer maize cultivated areas of the Huang-Huai-Hai plain, eastern China. Environ. Monit. Assess. 2021, 193, 441. [Google Scholar] [CrossRef]
- Jauhar, P.P. Modern biotechnology as an integral supplement to conventional plant breeding: The prospects and challenges. Crop Sci. 2006, 46, 1841–1859. [Google Scholar] [CrossRef]
- Raymond Park, J.; McFarlane, I.; Hartley Phipps, R.; Ceddia, G. The role of transgenic crops in sustainable development. Plant Biotechnol. J. 2011, 9, 2–21. [Google Scholar] [CrossRef] [PubMed]
- Kamthan, A.; Chaudhuri, A.; Kamthan, M.; Datta, A. Genetically modified (GM) crops: Milestones and new advances in crop improvement. Theor. Appl. Genet. 2016, 129, 1639–1655. [Google Scholar] [CrossRef]
- Yu, H.; Yang, Q.; Fu, F.; Li, W. Three strategies of transgenic manipulation for crop improvement. Front. Plant Sci. 2022, 13, 948518. [Google Scholar] [CrossRef]
- Cattivelli, L.; Rizza, F.; Badeck, F.; Mazzucotelli, E.; Mastrangelo, A.M.; Francia, E.; Marè, C.; Tondelli, A.; Stanca, A.M. Drought tolerance improvement in crop plants: An integrated view from breeding to genomics. Field Crops Res. 2008, 105, 1–14. [Google Scholar] [CrossRef]
- Tollefson, J. Drought-tolerant maize gets US debut. Nature 2011, 469, 144. [Google Scholar] [CrossRef]
- Swaminathan, M.S. Can science and technology feed the world in 2025? Field Crops Res. 2007, 104, 3–9. [Google Scholar] [CrossRef]
- Wang, Z. Resource investigation and protection of Ammopiptanthus nanus. Chin. Wild Pl. Resour. 2005, 5, 41–42. [Google Scholar]
- Pan, B.; Yu, Q.; Yan, C. Study for the ecological environment and vulnerable reasons of the Ammopiptanthus nanus. Chin. J. Plant Ecol. 1992, 16, 276–282. [Google Scholar]
- Yu, H.Q.; Zhang, Y.Y.; Yong, T.M.; Liu, Y.P.; Zhou, S.F.; Fu, F.L.; Li, W.C. Cloning and functional validation of molybdenum cofactor sulfurase gene from Ammopiptanthus nanus. Plant Cell Rep. 2015, 34, 1165–1176. [Google Scholar] [CrossRef]
- Yu, H.; Zhou, X.; Wang, Y.; Zhou, S.; Fu, F.; Li, W. A betaine aldehyde dehydrogenase gene from Ammopiptanthus nanus enhances tolerance of Arabidopsis to high salt and drought stresses. Plant Growth Regul. 2017, 83, 265–276. [Google Scholar] [CrossRef]
- Liu, Y.; Zhang, L.; Hao, W.; Zhang, L.; Liu, Y.; Chen, L. Expression of two alpha-type expansins from Ammopiptanthus nanus in Arabidopsis thaliana enhance tolerance to cold and drought stresses. Int. J. Mol. Sci. 2019, 20, 5255. [Google Scholar] [CrossRef] [PubMed]
- Liu, Y.; Zhang, L.; Meng, S.; Liu, Y.; Zhao, X.; Pang, C.; Zhang, H.; Xu, T.; He, Y.; Qi, M.; et al. Expression of galactinol synthase from Ammopiptanthus nanus in tomato improves tolerance to cold stress. J. Exp. Bot. 2020, 71, 435–449. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Y.; Cao, Y.; Zheng, H.; Feng, W.; Qu, J.; Fu, F.; Li, W.; Yu, H. Ectopic expression of antifreeze protein gene from Ammopiptanthus nanus confers chilling tolerance in maize. Crop J. 2021, 9, 924–933. [Google Scholar] [CrossRef]
- Yu, H.; Qu, J.; Guo, X.; Li, L.; Zhang, X.; Yang, Q.; Lu, Y.; Li, W.; Fu, F. Overexpression of vacuolar H+-pyrophosphatase (H+-PPase) gene from Ammopiptanthus nanus enhances drought tolerance in maize. J. Agron. Crop Sci. 2022, 208, 633–644. [Google Scholar] [CrossRef]
- Asaoka, M.M.A.; Segami, S.; Ferjani, A.; Maeshima, M. Contribution of PPi-hydrolyzing function of vacuolar H+-pyrophosphatase in vegetative growth of Arabidopsis: Evidenced by expression of uncoupling mutated enzymes. Front. Plant Sci. 2016, 7, 415. [Google Scholar] [CrossRef]
- Schilling, R.K.; Tester, M.; Marschner, P.; Plett, D.C.; Roy, S.J. AVP1: One protein, many roles. Trends Plant Sci. 2017, 22, 154–162. [Google Scholar] [CrossRef]
- Gordon-Kamm, W.J.; Spencer, T.M.; Mangano, M.L.; Adams, T.R.; Daines, R.J.; Start, W.G.; O’Brien, J.V.; Chambers, S.A.; Adams, W.R.J.; Willetts, N.G.; et al. Transformation of maize cells and regeneration of fertile transgenic plants. Plant Cell 1990, 2, 603–618. [Google Scholar] [CrossRef]
- Ishida, Y.; Hiei, Y.; Komari, T. Agrobacterium-mediated transformation of maize. Nat. Protoc. 2007, 2, 1614–1621. [Google Scholar] [CrossRef]
- Lee, H.; Zhang, Z.J. Maize (Zea mays) Hi-II transformation via Agrobacterium-mediated T-DNA transfer. Curr. Protoc. Plant Biol. 2016, 1, 121–137. [Google Scholar] [CrossRef]
- Wang, K.; Zhu, H.; McCaw, M. Biolistic DNA delivery in maize immature embryos. Methods Mol. Biol. 2020, 2124, 177–195. [Google Scholar] [CrossRef]
- Azizi-Dargahlou, S.; Pouresmaeil, M. Agrobacterium tumefaciens-mediated plant transformation: A review. Mol. Biotechnol. 2024, 66, 1563–1580. [Google Scholar] [CrossRef]
- Cho, M.; Wu, E.; Kwan, J.; Yu, M.; Banh, J.; Linn, W.; Anand, A.; Li, Z.; TeRonde, S.; Register, J.C.R.; et al. Agrobacterium-mediated high-frequency transformation of an elite commercial maize (Zea mays L.) inbred line. Plant Cell Rep. 2014, 33, 1767–1777. [Google Scholar] [CrossRef]
- Yadava, P.; Abhishek, A.; Singh, R.; Singh, I.; Kaul, T.; Pattanayak, A.; Agrawal, P.K. Advances in maize transformation technologies and development of transgenic maize. Front. Plant Sci. 2017, 7, 1949. [Google Scholar] [CrossRef] [PubMed]
- Bollinedi, H.; Krishnan, S.G.; Prabhu, K.V.; Singh, N.K.; Mishra, S.; Khurana, J.P.; Singh, A.K. Molecular and functional characterization of GR2-R1 event based backcross derived lines of golden rice in the genetic background of a mega rice variety Swarna. PLoS ONE 2017, 12, e0169600. [Google Scholar] [CrossRef] [PubMed]
- Zhong, H.; Elumalai, S.; Nalapalli, S.; Richbourg, L.; Prairie, A.; Bradley, D.; Dong, S.; Su, X.J.; Gu, W.; Strebe, T.; et al. Advances in Agrobacterium-mediated maize transformation. Methods Mol. Biol. 2018, 1676, 41–59. [Google Scholar] [CrossRef]
- Biswas, P.S.; Swamy, B.P.M.; Kader, M.A.; Hossain, M.A.; Boncodin, R.; Samia, M.; Hassan, M.L.; Wazuddin, M.; MacKenzie, D.; Reinke, R. Development and field evaluation of near-isogenic lines of GR2-EBRRI dhan29 golden rice. Front. Plant Sci. 2021, 12, 619739. [Google Scholar] [CrossRef] [PubMed]
- Mumm, R.H. Backcross versus forward breeding in the development of transgenic maize hybrids: Theory and practice. Crop Sci. 2007, 47, 164–171. [Google Scholar] [CrossRef]
- Visarada, K.B.R.S.; Meena, K.; Aruna, C.; Srujana, S.; Saikishore, N.; Seetharama, N. Transgenic breeding: Perspectives and prospects. Crop Sci. 2009, 49, 1555–1563. [Google Scholar] [CrossRef]
- Kaur, A.; Sharma, U.; Singh, S.; Singh, R.; Vikal, Y.; Singh, S.; Malik, P.; Kaur, K.; Singh, I.; Bindra, S.; et al. Introgressing cry1Ac for pod borer resistance in chickpea through marker-assisted backcross breeding. Front. Genet. 2022, 13, 847647. [Google Scholar] [CrossRef]
- Zhong, G. Genetic issues and pitfalls in transgenic plant breeding. Euphytica 2001, 118, 137–144. [Google Scholar] [CrossRef]
- Bregitzer, P.; Dahleen, L.S.; Neate, S.; Schwarz, P.; Manoharan, M. A single backcross effectively eliminates agronomic and quality alterations caused by somaclonal variation in transgenic barley. Crop Sci. 2008, 48, 471–479. [Google Scholar] [CrossRef]
- Natesan, S.; Duraisamy, T.; Pukalenthy, B.; Chandran, S.; Nallathambi, J.; Adhimoolam, K.; Manickam, D.; Sampathrajan, V.; Muniyandi, S.J.; Meitei, L.J.; et al. Enhancing beta-carotene concentration in parental lines of CO6 maize hybrid through marker-assisted backcross breeding (MABB). Front. Nutr. 2020, 7, 134. [Google Scholar] [CrossRef]
- Qutub, M.; Chandran, S.; Rathinavel, K.; Sampathrajan, V.; Rajasekaran, R.; Manickam, S.; Adhimoolam, K.; Muniyandi, S.J.; Natesan, S. Improvement of a Yairipok Chujak maize landrace from north eastern Himalayan region for beta-carotene content through molecular marker-assisted backcross breeding. Genes 2021, 12, 762. [Google Scholar] [CrossRef] [PubMed]
- Neeraja, C.N.; Maghirang-Rodriguez, R.; Pamplona, A.; Heuer, S.; Collard, B.C.Y.; Septiningsih, E.M.; Vergara, G.; Sanchez, D.; Xu, K.; Ismail, A.M.; et al. A marker-assisted backcross approach for developing submergence-tolerant rice cultivars. Theor. Appl. Genet. 2007, 115, 767–776. [Google Scholar] [CrossRef] [PubMed]
- Gaur, R.; Sethy, N.K.; Choudhary, S.; Shokeen, B.; Gupta, V.; Bhatia, S. Advancing the STMS genomic resources for defining new locations on the intraspecific genetic linkage map of chickpea (Cicer arietinum L.). BMC Genom. 2011, 12, 117. [Google Scholar] [CrossRef]
- Yamagata, Y.; Yoshimura, A.; Anai, T.; Watanabe, S. Selection criteria for SNP loci to maximize robustness of high-resolution melting analysis for plant breeding. Breed. Sci. 2018, 68, 488–498. [Google Scholar] [CrossRef]
- Vali, U.; Brandstrom, M.; Johansson, M.; Ellegren, H. Insertion-deletion polymorphisms (indels) as genetic markers in natural populations. BMC Genet. 2008, 9, 8. [Google Scholar] [CrossRef]
- Li, W.; Cheng, J.; Wu, Z.; Qin, C.; Tan, S.; Tang, X.; Cui, J.; Zhang, L.; Hu, K. An InDel-based linkage map of hot pepper (Capsicum annuum). Mol. Breed. 2015, 35, 32. [Google Scholar] [CrossRef]
- Liu, C.; Hua, J.; Liu, C.; Zhang, D.; Hao, Z.; Yong, H.; Xie, C.; Li, M.; Zhang, S.; Weng, J.; et al. Fine mapping of a quantitative trait locus conferring resistance to maize rough dwarf disease. Theor. Appl. Genet. 2016, 129, 2333–2342. [Google Scholar] [CrossRef]
- Xu, Z.; Hua, J.; Wang, F.; Cheng, Z.; Meng, Q.; Chen, Y.; Han, X.; Tie, S.; Liu, C.; Li, X.; et al. Marker-assisted selection of qMrdd8 to improve maize resistance to rough dwarf disease. Breed. Sci. 2020, 70, 183–192. [Google Scholar] [CrossRef]
- Li, H.; Yang, Q.; Gao, L.; Zhang, M.; Ni, Z.; Zhang, Y. Identification of Heterosis-Associated Stable QTLs for Ear-Weight-Related Traits in an Elite Maize Hybrid Zhengdan 958 by Design III. Front. Plant Sci. 2017, 8, 561. [Google Scholar] [CrossRef]
- Tian, T.; Wang, S.; Yang, S.; Yang, Z.; Liu, S.; Wang, Y.; Gao, H.; Zhang, S.; Yang, X.; Jiang, C.; et al. Genome assembly and genetic dissection of a prominent drought-resistant maize germplasm. Nat. Genet. 2023, 55, 496–506. [Google Scholar] [CrossRef]
- Yang, Z.; Cao, Y.; Shi, Y.; Qin, F.; Jiang, C.; Yang, S. Genetic and molecular exploration of maize environmental stress resilience: Toward sustainable agriculture. Mol. Plant 2023, 16, 1496–1517. [Google Scholar] [CrossRef]
- Xiao, W.; Yang, Q.; Huang, M.; Guo, T.; Liu, Y.; Wang, J.; Yang, G.; Zhou, J.; Yang, J.; Zhu, X.; et al. Improvement of rice blast resistance by developing monogenic lines, two-gene pyramids and three-gene pyramid through MAS. Rice 2019, 12, 78. [Google Scholar] [CrossRef] [PubMed]
- Jiao, Y.; Zhao, H.; Ren, L.; Song, W.; Zeng, B.; Guo, J.; Wang, B.; Liu, Z.; Chen, J.; Li, W.; et al. Genome-wide genetic changes during modern breeding of maize. Nat. Genet. 2012, 44, 812–815. [Google Scholar] [CrossRef] [PubMed]
- Chen, S.; Zhou, Y.; Chen, Y.; Gu, J. fastp: An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018, 34, i884–i890. [Google Scholar] [CrossRef]
- Portwood, J.L.N.; Woodhouse, M.R.; Cannon, E.K.; Gardiner, J.M.; Harper, L.C.; Schaeffer, M.L.; Walsh, J.R.; Sen, T.Z.; Cho, K.T.; Schott, D.A.; et al. MaizeGDB 2018: The maize multi-genome genetics and genomics database. Nucleic Acids Res. 2019, 47, D1146–D1154. [Google Scholar] [CrossRef] [PubMed]
- Li, H.; Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009, 25, 1754–1760. [Google Scholar] [CrossRef]
- Ebbert, M.T.W.; Wadsworth, M.E.; Staley, L.A.; Hoyt, K.L.; Pickett, B.; Miller, J.; Duce, J.; Kauwe, J.S.K.; Ridge, P.G. Evaluating the necessity of PCR duplicate removal from next-generation sequencing data and a comparison of approaches. BMC Bioinform. 2016, 17 (Suppl. S7), 239. [Google Scholar] [CrossRef]
- McKenna, A.; Hanna, M.; Banks, E.; Sivachenko, A.; Cibulskis, K.; Kernytsky, A.; Garimella, K.; Altshuler, D.; Gabriel, S.; Daly, M.; et al. The genome analysis toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010, 20, 1297–1303. [Google Scholar] [CrossRef]
- Danecek, P.; Auton, A.; Abecasis, G.; Albers, C.A.; Banks, E.; DePristo, M.A.; Handsaker, R.E.; Lunter, G.; Marth, G.T.; Sherry, S.T.; et al. The variant call format and VCFtools. Bioinformatics 2011, 27, 2156–2158. [Google Scholar] [CrossRef] [PubMed]
- Visscher, P.M.; Haley, C.S.; Thompson, R. Marker-assisted introgression in backcross breeding programs. Genetics 1996, 144, 1923–1932. [Google Scholar] [CrossRef] [PubMed]
- Wang, J.; Wang, Y.; Hu, X.; Chen, Y.; Jiang, W.; Liu, X.; Liu, J.; Zhu, L.; Zeng, H.; Liu, H. A dual-RPA based lateral flow strip for sensitive, on-site detection of CP4-EPSPS and Cry1Ab/Ac genes in genetically modified crops. Food Sci. Hum. Wellness 2024, 13, 183–190. [Google Scholar] [CrossRef]
- Yu, H.; Liu, B.; Yang, Q.; Yang, Q.; Li, W.; Fu, F. Maize ZmLAZ1-3 gene negatively regulates drought tolerance in transgenic Arabidopsis. BMC Plant Biol. 2024, 24, 246. [Google Scholar] [CrossRef]
- Lu, F.; Li, W.; Peng, Y.; Cao, Y.; Qu, J.; Sun, F.; Yang, Q.; Lu, Y.; Zhang, X.; Zheng, L.; et al. ZmPP2C26 alternative splicing variants negatively regulate drought tolerance in maize. Front. Plant Sci. 2022, 13, 851531. [Google Scholar] [CrossRef]
- State Bureau of Quality and Technical Supervision. Maize; GB 1353-1999; Standards Press of China: Beijing, China, 1999.
Plant | Recovery Rate | Plant | Recovery Rate | Plant | Recovery Rate |
---|---|---|---|---|---|
BC1-1 | 86.11% | BC1-34 | 85.18% | BC1-47 | 85.19% |
BC1-5 | 87.03% | BC1-35 | 80.55% | BC1-53 | 81.48% |
BC1-6 | 81.48% | BC1-36 | 81.48% | BC1-54 | 80.55% |
BC1-8 | 83.33% | BC1-41 | 86.11% | BC1-83 | 81.48% |
BC1-20 | 81.48% | BC1-45 | 83.33% | BC1-95 | 85.18% |
BC1-27 | 87.96% | BC1-46 | 87.96% | BC1-101 | 84.26% |
Plant | Recovery Rate | Plant | Recovery Rate | Plant | Recovery Rate |
---|---|---|---|---|---|
BC2-1-1 | 92.53% | BC2-8-6 | 94.25% | BC2-36-10 | 92.44% |
BC2-1-2 | 91.95% | BC2-8-8 | 92.53% | BC2-36-11 | 92.35% |
BC2-1-3 | 93.10% | BC2-8-9 | 94.25% | BC2-36-12 | 95.40% |
BC2-1-4 | 90.80% | BC2-8-10 | 93.10% | BC2-47-1 | 92.44% |
BC2-1-5 | 93.60% | BC2-8-11 | 91.95% | BC2-47-2 | 93.53% |
BC2-1-6 | 91.95% | BC2-8-12 | 89.53% | BC2-47-3 | 90.80% |
BC2-1-7 | 93.68% | BC2-8-13 | 93.68% | BC2-47-4 | 94.25% |
BC2-1-8 | 92.44% | BC2-35-1 | 90.23% | BC2-47-5 | 90.23% |
BC2-5-1 | 90.70% | BC2-35-2 | 89.53% | BC2-47-6 | 89.66% |
BC2-5-2 | 93.10% | BC2-35-3 | 88.51% | BC2-47-7 | 94.25% |
BC2-5-3 | 93.60% | BC2-35-4 | 91.38% | BC2-47-8 | 93.10% |
BC2-5-4 | 90.80% | BC2-35-5 | 90.80% | BC2-83-1 | 94.19% |
BC2-5-5 | 94.25% | BC2-35-6 | 90.23% | BC2-83-2 | 89.08% |
BC2-5-6 | 91.38% | BC2-35-7 | 89.08% | BC2-83-4 | 91.38% |
BC2-5-7 | 91.95% | BC2-35-8 | 90.23% | BC2-83-5 | 93.10% |
BC2-5-8 | 87.93% | BC2-35-9 | 91.95% | BC2-83-6 | 93.10% |
BC2-5-9 | 93.68% | BC2-36-1 | 93.10% | BC2-83-7 | 92.77% |
BC2-5-10 | 91.86% | BC2-36-2 | 90.80% | BC2-83-8 | 90.23% |
BC2-5-12 | 89.08% | BC2-36-3 | 94.25% | BC2-83-9 | 90.80% |
BC2-5-15 | 94.77% | BC2-36-4 | 90.23% | BC2-83-10 | 89.66% |
BC2-8-1 | 90.80% | BC2-36-5 | 91.95% | BC2-83-11 | 93.02% |
BC2-8-2 | 92.53% | BC2-36-7 | 92.44% | BC2-83-12 | 92.94% |
BC2-8-3 | 93.68% | BC2-36-8 | 90.36% | ||
BC2-8-4 | 93.10% | BC2-36-9 | 88.37% |
Plant | Plant Height (cm) | Ear Height (cm) | Tassel Branch Number | Ear Length (cm) | Ear Diameter (cm) | 100 Kernel Weight (g) |
---|---|---|---|---|---|---|
Chang 7-2 | 174 | 72 | 12 | 9.5 | 4.1 | 22.4 |
BC2-36-12 | 174 | 72 | 12 | 9.5 | 4.3 | 22.0 |
BC2-5-15 | 172 | 73 | 13 | 9.7 | 4.2 | 22.6 |
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Cao, Y.; Yu, H.; Guo, X.; Lu, Y.; Li, W.; Fu, F. Marker-Assisted Backcross Breeding of Drought-Tolerant Maize Lines Transformed by Vacuolar H+-Pyrophosphatase Gene (AnVP1) from Ammopiptanthus nanus. Plants 2025, 14, 926. https://doi.org/10.3390/plants14060926
Cao Y, Yu H, Guo X, Lu Y, Li W, Fu F. Marker-Assisted Backcross Breeding of Drought-Tolerant Maize Lines Transformed by Vacuolar H+-Pyrophosphatase Gene (AnVP1) from Ammopiptanthus nanus. Plants. 2025; 14(6):926. https://doi.org/10.3390/plants14060926
Chicago/Turabian StyleCao, Yang, Haoqiang Yu, Xin Guo, Yanli Lu, Wanchen Li, and Fengling Fu. 2025. "Marker-Assisted Backcross Breeding of Drought-Tolerant Maize Lines Transformed by Vacuolar H+-Pyrophosphatase Gene (AnVP1) from Ammopiptanthus nanus" Plants 14, no. 6: 926. https://doi.org/10.3390/plants14060926
APA StyleCao, Y., Yu, H., Guo, X., Lu, Y., Li, W., & Fu, F. (2025). Marker-Assisted Backcross Breeding of Drought-Tolerant Maize Lines Transformed by Vacuolar H+-Pyrophosphatase Gene (AnVP1) from Ammopiptanthus nanus. Plants, 14(6), 926. https://doi.org/10.3390/plants14060926