Selection and evaluation of gene-edited knockout mutants of AtAAP2 and AtCRF4 homologs of rice for agronomic nitrogen use efficiency (ANUE)
Abstract
Nitrogen (N) is essential for amino acid synthesis in rice production, but its excessive use poses an environmental concern. This research aimed to improve rice agronomic nitrogen use efficiency (ANUE) by knockout (KO) of rice homologs of the two selected genes from Arabidopsis thaliana: AtAAP2, an amino acid permease involved in N transportation in shoots, and AtCRF4, a transcription factor participating in N uptake in roots. The homologs of these genes in rice were identified based on amino acid sequence similarity and knocked out using CRISPR/Cas9 mediated gene editing (GE). The AAP2-KO and CRF4-KO lines were subjected to agronomic evaluations with three N doses: 100% (180 kg ha-1), 50% (90 kg ha-1), and 0% (0 kg ha-1) and showed a 130-175% increase in dry biomass weight and a 183-313% increase in panicle number compared to wild type (WT) in the first experiment. These lines also had slower leaf senescence, the so-called “stay-green” trait, indicating the KO effect of target genes in N metabolism. However, neither AAP2-KO nor CRF4-KO showed better yield or ANUE than WT. This study demonstrated the usefulness of GE technology in gene evaluation and highlighted the effects of AtAAP2 and AtCRF4 genes in the plant N cycle.
Keywords
Amino acid permease 2 (AAP2), Cytokinin response factor 4 (CRF4), Oryza sativa L., Remote sensing
References
- Barnes, E.M., T.R. Clarke, S.E. Richards, P.D. Colaizzi, J. Haberland, P. Waller, C. Choi, E. Riley, T. Thompson, R.J. Lascano, H. Li, and M.S. Moran. 2000. Coincident detection of crop water stress, nitrogen status, and canopy density using ground based multispectral data. In: Proc. 5th Int. Conf. Precision Agric. ASA-CSSA-SSSA, Madison WI.
- Berrío, L.E., L.R. Sanint, F. Correa, and E. Tulande. 2002. Respuesta al uso de nitrógeno en variedades de arroz sembradas en Colombia, 1950-1999. Foro Arrocero Latinoam. 8(2), 22-23. http://ciat-library.ciat.cgiar.org/Articulos_CIAT/flar/respuesta.pdf
- Boiarskii, B. and H. Hasegawa. 2019. Comparison of NDVI and NDRE indices to detect differences in vegetation and chlorophyll content. J. Mech. Continua Math. Sci. (Suppl. 4). Doi: https://doi.org/10.26782/jmcms.spl.4/2019.11.00003
- Borrell, A.K., G.L. Hammer, and A.C.L. Douglas. 2000. Does maintaining green leaf area in sorghum improve yield under drought? I. Leaf growth and senescence. Crop Sci. 40(4), 1026-1037. Doi: https://doi.org/10.2135/cropsci2000.4041026x
- Borrell, A., G. Hammer, and E. Van Oosterom. 2001. Stay-green: a consequence of the balance between supply and demand for nitrogen during grain filling? Ann. Appl. Biol. 138(1), 91-95. Doi: https://doi.org/10.1111/j.1744-7348.2001.tb00088.x
- Brooks, M.D., J. Cirrone, A.V. Pasquino, J.M. Alvarez, J. Swift, S. Mittal, C.-L. Juang, K. Varala, R.A. Gutiérrez, G. Krouk, D. Shasha, and G.M. Coruzzi. 2019. Network walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions. Nat. Commun. 10, 1569. Doi: https://doi.org/10.1038/s41467-019-09522-1
- Cha, K.-W., Y.-J. Lee, H.-J. Koh, B.-M. Lee, Y.-W. Nam, and N.-C. Paek. 2002. Isolation, characterization, and mapping of the stay green mutant in rice. Theor. Appl. Genet. 104, 526-532. Doi: https://doi.org/10.1007/s001220100750
- Chen, J., Y. Zhang, Y. Tan, M. Zhang, L. Zhu, G. Xu, and X. Fan. 2016. Agronomic nitrogen-use efficiency of rice can be increased by driving OsNRT2.1 expression with the OsNAR2.1 promoter. Plant Biotechnol. J. 14(8), 1705-1715. Doi: https://doi.org/10.1111/pbi.12531
- Chivenge, P., S. Sharma, M.A. Bunquin, and J. Hellin. 2021. Improving nitrogen use efficiency—a key for sustainable rice production systems. Front. Sustain. Food Syst. 5, 737412. Doi: https://doi.org/10.3389/fsufs.2021.737412
- Collard, B.C.Y., C.M. Vera Cruz, K.L. McNally, P.S. Virk, and D.J. Mackill. 2008. Rice molecular breeding laboratories in the genomics era: current status and future considerations. Int. J. Plant Genomics 2008, 524847. Doi: https://doi.org/10.1155/2008/524847
- Congreves, K.A., O. Otchere, D. Ferland, S. Farzadfar, S. Williams, and M.M. Arcand. 2021. Nitrogen use efficiency definitions of today and tomorrow. Front. Plant Sci. 12, 637108. Doi: https://doi.org/10.3389/fpls.2021.637108
- Craswell, E.T. and D.C. Godwin. 1984. The efficiency of nitrogen fertilizers applied to cereals in different climates. Adv. Plant Nutr. 1, 1-55.
- Feng, H., M. Yan, X. Fan, B. Li, Q. Shen, A.J. Miller, and G. Xu. 2011. Spatial expression and regulation of rice high-affinity nitrate transporters by nitrogen and carbon status. J. Exp. Bot. 62(7), 2319-2332. Doi: https://doi.org/10.1093/jxb/erq403
- Fitzgerald, M.A., S.R. McCouch, and R.D. Hall. 2009. Not just a grain of rice: the quest for quality. Trends Plant Sci. 14(3), 133-139. Doi: https://doi.org/10.1016/j.tplants.2008.12.004
- Fu, J.-D., Y.-F. Yan, and B.-W. Lee. 2009. Physiological characteristics of a functional stay-green rice “SNU-SG1” during grain-filling period. J. Crop Sci. Biotechnol. 12(1), 47-52. Doi: https://doi.org/10.1007/s12892-009-0078-8
- Hu, B., W. Wang, S. Ou, J. Tang, H. Li, R. Che, Z. Zhang, X. Chai, H. Wang, Y. Wang, C. Liang, L. Liu, Z. Piao, Q. Deng, K. Deng, C. Xu, Y. Liang, L. Zhang, L. Li, and C. Chu. 2015. Variation in NRT1.1B contributes to nitrate-use divergence between rice subspecies. Nat. Genet. 47(7), 834-838. Doi: https://doi.org/10.1038/ng.3337
- Katayama, H., M. Mori, Y. Kawamura, T. Tanaka, M. Mori, and H. Hasegawa. 2009. Production and characterization of transgenic rice plants carrying a high-affinity nitrate transporter gene (OsNRT2.1). Breed. Sci. 59(3), 237-243. Doi: https://doi.org/10.1270/jsbbs.59.237
- Lee, S. and C. Masclaux-Daubresse. 2021. Current understanding of leaf senescence in rice. Int. J. Mol. Sci. 22(9), 4515. Doi: https://doi.org/10.3390/ijms22094515
- Luche, H.S., J.A.G. Silva, L.C. Maia, and A.C. Oliveira. 2015. Stay-green: a potentiality in plant breeding. Cienc. Rural 45(10), 1755-1760. Doi: https://doi.org/10.1590/0103-8478cr20140662
- Martínez-Dalmau, J., J. Berbel, and R. Ordóñez-Fernández. 2021. Nitrogen fertilization. A review of the risks associated with the inefficiency of its use and policy responses. Sustainability 13(10), 5625. Doi: https://doi.org/10.3390/su13105625
- Miyao, A., M. Nakagome, T. Ohnuma, H. Yamagata, H. Kanamori, Y. Katayose, A. Takahashi, T. Matsumoto, and H. Hirochika. 2012. Molecular spectrum of somaclonal variation in regenerated rice revealed by whole-genome sequencing. Plant Cell Physiol. 53(1), 256-264. Doi: https://doi.org/10.1093/pcp/pcr172
- Mofijul, S.M., Y.K. Gaihre, A.L. Shah, U. Singh, M.I.U. Sarkar, M.A. Satter, J. Sanabria, and J.C. Biswas. 2016. Rice yields and nitrogen use efficiency with different fertilizers and water management under intensive lowland rice cropping systems in Bangladesh. Nutr. Cycl. Agroecosyst. 106(2), 143-156. Doi: https://doi.org/10.1007/s10705-016-9795-9
- Perchlik, M. and M. Tegeder. 2018. Leaf amino acid supply affects photosynthetic and plant nitrogen use efficiency under nitrogen stress. Plant Physiol. 178(1), 174-188. Doi: https://doi.org/10.1104/pp.18.00597
- Pingali, P.L. 2012. Green revolution: impacts, limits, and the path ahead. Proc.Natl. Acad. Sci. U.S.A. 109(31), 12302-12308. Doi: https://doi.org/10.1073/pnas.0912953109
- Risterucci, A.M., L. Grivet, J.A.K. N’Goran, I. Pieretti, M.H. Flament, and C. Lanaud. 2000. A high-density linkage map of Theobroma cacao L. Theor. Appl. Genet. 101, 948-955. Doi: https://doi.org/10.1007/s001220051566
- Sakuraba, Y., W. Piao, J.H. Lim, S.-H. Han, Y.-S. Kim, G. An, and N.-C. Paek. 2015. Rice ONAC106 inhibits leaf senescence and increases salt tolerance and tiller angle. Plant Cell Physiol. 56(12), 2325-2339. Doi: https://doi.org/10.1093/pcp/pcv144
- Selvaraj, M.G., M. Valderrama, D. Guzman, M. Valencia, H. Ruiz, and A. Acharjee. 2020. Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz). Plant Methods, 16, 87. Doi: https://doi.org/10.1186/s13007-020-00625-1
- Selvaraj, M.G., M.O. Valencia, S. Ogawa, Y. Lu, L. Wu, C. Downs, W. Skinner, Z. Lu, J.C. Kridl, M. Ishitani, and J. van Boxtel. 2017. Development and field performance of nitrogen use efficient rice lines for Africa. Plant Biotechnol. J. 15(6), 775-787. Doi: https://doi.org/10.1111/pbi.12675
- Shillito, R.D., S. Whitt, M. Ross, F. Ghavami, D. De Vleesschauwer, K. D’Halluin, A. Van Hoecke, and F. Meulewaeter. 2021. Detection of genome edits in plants—from editing to seed. In Vitro Cell. Dev. Biol.-Plant 57, 595-608. Doi: https://doi.org/10.1007/s11627-021-10214-z
- Sonoda, Y., A. Ikeda, S. Saiki, N. Von Wirén, T. Yamaya, and J. Yamaguchi. 2003. Distinct expression and function of three ammonium transporter genes (OsAMT1;1-1;3) in rice. Plant Cell Physiol. 44(7), 726-734. Doi: https://doi.org/10.1093/pcp/pcg083
- Thomas, H. and C.J. Howarth. 2000. Five ways to stay green. J. Exp. Bot. 51(Suppl. 1), 329-337. Doi: https://doi.org/10.1093/jexbot/51.suppl_1.329
- Tucker, C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8(2), 127-150. Doi: https://doi.org/10.1016/0034-4257(79)90013-0
- Varala, K., A. Marshall-Colón, J. Cirrone, M.D. Brooks, A.V. Pasquino, S. Léran, S. Mittal, T.M. Rock, M.B. Edwards, G.J. Kim, S. Ruffel, W.R. McCombie, D. Shasha, and G.M. Coruzzi. 2018. Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants. Proc. Natl. Acad. Sci. U.S.A. 115(25), 6494-6499. Doi: https://doi.org/10.1073/pnas.1721487115
- Wang, C. and B. Han. 2022. Twenty years of rice genomics research: from sequencing and functional genomics to quantitative genomics. Mol. Plant 15(4), 593-619. Doi: https://doi.org/10.1016/j.molp.2022.03.009
- Wang, J., K. Lu, H. Nie, Q. Zeng, B. Wu, J. Qian, and Z. Fang. 2018. Rice nitrate transporter OsNPF7.2 positively regulates tiller number and grain yield. Rice 11, 12. Doi: https://doi.org/10.1186/s12284-018-0205-6
- Zang, Y., Y. Yao, Z. Xu, B. Wang, Y. Mao, W. Wang, W. Zhang, H. Zhang, L. Liu, Z. Wang, G. Liang, J. Yang, Y. Zhou, and J. Gu. 2022. The relationships among “STAY-GREEN” trait, post-anthesis assimilate remobilization, and grain yield in rice (Oryza sativa L.). Int. J. Mol. Sci. 23(22), 13668. Doi: https://doi.org/10.3390/ijms232213668
- Zhang, L., Q. Tan, R. Lee, A. Trethewy, Y.-H. Lee, and M. Tegeder. 2010. Altered xylem-phloem transfer of amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis. Plant Cell 22(11), 3603-3620. Doi: https://doi.org/10.1105/tpc.110.073833
- Zhang, X.-H., L.Y. Tee, X.-G. Wang, Q.-S. Huang, and S.-H. Yang. 2015. Off-target effects in CRISPR/Cas9-mediated genome engineering. Mol. Ther. Nucleic Acids 4, e264. Doi: https://doi.org/10.1038/mtna.2015.37
- Zhang, Y., K. Massel, I.D. Godwin, and C. Gao. 2019. Applications and potential of genome editing in crop improvement. Genome Biol. 20(1), 13. Doi: https://doi.org/10.1186/s13059-019-1622-6