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Selección y evaluación de mutantes knockout genéticamente editados de homólogos de AtAAP2 y AtCRF4 de arroz para la eficiencia agronómica del uso del nitrógeno (ANUE)

Gene-edited rice lines with different phenotypic features. Photo: K. Wakatabi

Resumen

El nitrógeno (N) es esencial para la síntesis de aminoácidos en la producción de arroz, pero su uso excesivo plantea una preocupación ambiental. Esta investigación tuvo como objetivo mejorar la eficiencia agronómica del uso del nitrógeno (ANUE) en el arroz mediante “knockout (KO)” de homólogos en arroz de los dos genes seleccionados de Arabidopsis thaliana: AtAAP2, una permeasa de aminoácidos involucrada en el transporte de N en los brotes, y AtCRF4, un factor de transcripción que participa en la absorción de N en las raíces. Los homólogos de estos genes en el arroz se identificaron por la similitud de la secuencia de aminoácidos y se desactivaron mediante la edición genética (GE) mediada por CRISPR/Cas9. Las líneas AAP2-KO y CRF4-KO fueron sometidas a evaluaciones agronómicas con tres dosis de N: 100% (180 kg ha-1), 50% (90 kg ha-1) y 0% (0 kg ha-1) y mostraron un aumento de 130-175% en peso de biomasa seca y un aumento de 183-313% en número de panículas en comparación con el control (WT) en el primer experimento. Estas líneas también tenían una senescencia foliar más lenta, el denominado rasgo de "permanecer verde", lo que indica el efecto de desactivación de genes del objetivo en el metabolismo del N. Sin embargo, ni AAP2-KO ni CRF4-KO mostraron mejor rendimiento o ANUE que WT. Este estudio demostró la utilidad de la tecnología de edición genética en la evaluación de genes y destacó los efectos de los genes AtAAP2 y AtCRF4 en el ciclo del N de la planta.

Palabras clave

Aminoácido permeasa 2 (AAP2), Factor de respuesta de citoquinina 4 (CRF4), Oryza sativa L., Sensores remotos

PDF (English)

Referencias

  • 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

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