MicroRNA396 negatively regulates shoot regeneration in tomato

Abstract

Numerous studies have been dedicated to genetically engineering crops to enhance their yield and quality. One of the key requirements for generating genetically modified plants is the reprogramming of cell fate. However, the efficiency of shoot regeneration during this process is highly dependent on genotypes, and the underlying molecular mechanisms remain poorly understood. Here, we identified microRNA396 (miR396) as a negative regulator of shoot regeneration in tomato. By selecting two genotypes with contrasting shoot regeneration efficiencies and analyzing their transcriptome profiles, we found that miR396 and its target transcripts, which encode GROWTH-REGULATING FACTORs (GRFs), exhibit differential abundance between high- and low-efficiency genotypes. Suppression of miR396 functions significantly improved shoot regeneration rates along with increased expression of GRF s in transformed T0 explants, suggesting that miR396 is a key molecule involved in the determination of regeneration efficiency. Notably, we also showed that co-expression of a miR396 suppressor with the gene-editing tool can be employed to generate gene-edited plants in the genotype with a low capacity for shoot regeneration. Our findings show the critical role of miR396 as a molecular barrier to shoot regeneration in tomato and suggest that regeneration efficiency can be improved by blocking this single microRNA.

Acknowledgements

We thank Dr. Suk Yoon Kwon for providing the tomato SK genotype seeds. This research was supported by the New Breeding Technologies Development Program (Project No. PJ01653001) provided by the Rural Development Administration of Korea, the Basic Research Program provided by the National Research Foundation of Korea (NRF-2023R1A2C1003963 and NRF-2022R1I1A2073565), and the KRIBB Research Initiative Programs (KGM5372322 and KGM1002311).

Author contributions

S.-J.P., H.-S.K., and H.-J.L. conceived the study, designed the experiments, and analyzed the data. S.-J.P. performed tomato regeneration, transformation, and qRT-PCR with the assistance by J.H.Y. S.-J.P. and J.-S.P. prepared the plant materials and extracted total RNA for RNA- and small RNA-sequencing. S.-J.P. and H.-J.L. analyzed sequencing data. S.-J.P. and K.-B.M. analyzed gene editing. K.-B.M. constructed Cas9-gRNA vector targeting SlPDS. S.-J.P. and S.Y.S. prepared experimental reagents and plant materials. J.-H.J. and H.-S.K. provided experimental equipment and scientific discussions.

Data availability statement

All data generated in this study are included in this article and the Source data files. The raw data for RNA- and small RNA-sequencing are deposited in KoNA (https://www.kobic.re.kr/kona). Accession numbers for RNA- and small RNA-sequencing data are KRA2301039 and KRA2301040, respectively.

Conflict of interest

None declared.

Supplementary information

Supplementary data is available at Horticulture Research online.

References

[1] Nam HY, Gupta A, Nam HJ. et al. JULGI-mediated increment in phloem transport capacity relates to fruit yield in tomato. Plant Biotechnol J. 2022; 20 :1533-45

[2] Moon KB, Park SJ, Park JS. et al. Editing of StSR4 by Cas9-RNPs confers resistance to Phytophthora infestans in potato. Front Plant Sci. 2022; 13 :997888

[3] Delporte F, Jacquemin JM, Masson P. et al. Insights into the regenerative property of plant cells and their receptivity to transgenesis. Plant Signal Behav. 2012; 7 :1608-20

[4] Ikeuchi M, Favero DS, Sakamoto Y. et al. Molecular mechanisms of plant regeneration. Annu Rev Plant Biol. 2019; 70 :377-406

[5] Radhakrishnan D, Kareem A, Durgaprasad K. et al. Shoot regeneration: a journey from acquisition of competence to completion. Curr Opin Plant Biol. 2018; 41 :23-31

[6] Fan M, Xu C, Xu K. et al. LATERAL ORGAN BOUNDARIES DOMAIN transcription factors direct callus formation in Arabidopsis regeneration. Cell Res. 2012; 22 :1169-80

[7] Kareem A, Durgaprasad K, Sugimoto K. et al. PLETHORA genes control regeneration by a two-step mechanism. Curr Biol. 2015; 25 :1017-30

[8] Meng WJ, Cheng ZJ, Sang YL. et al. Type-B ARABIDOPSIS RESPONSE REGULATORs specify the shoot stem cell niche by dual regulation of WUSCHEL. Plant Cell. 2017; 29 :1357-72

[9] Zhang TQ, Lian H, Zhou CM. et al. A two-step model for de novo activation of WUSCHEL during plant shoot regeneration. Plant Cell. 2017; 29 :1073-87

[10] Lee K, Seo PJ. Dynamic epigenetic changes during plant regeneration. Trends Plant Sci. 2018; 23 :235-47

[11] Lee MH, Lee JY, Jie EY. et al. Temporal and spatial expression analysis of shoot-regeneration regulatory genes during the adventitious shoot formation in hypocotyl and cotyledon explants of tomato (cv. Micro-tom). Int J Mol Sci. 2020; 21 : 5309

[12] Xiao Y, Chen Y, Ding Y. et al. Effects of GhWUS from upland cotton ( Gossypium hirsutum L. ) on somatic embryogenesis and shoot regeneration. Plant Sci. 2018; 270 :157-65

[13] Lee KH, Kim JH, Park OS. et al. Ectopic expression of WOX5 promotes cytokinin signaling and de novo shoot regeneration. Plant Cell Rep. 2022; 41 :2415-22

[14] Jabeen N, Chaudhry Z, Rashid H. et al. Effect of genotype and explant type on in vitro shoot regeneration of tomato ( Lycopersicon esculentum mill. ). Pak J Bot. 2005; 37 :899-903

[15] Zhao Y, Huang S, Zhang Y. et al. Establishment of an efficient shoot regeneration system in vitro in Brassica rapa. In Vitro Cell Dev Biol. 2021; 57 :977-86

[16] Prado JR, Segers G, Voelker T. et al. Genetically engineered crops: from idea to product. Annu Rev Plant Biol. 2014; 65 :769-90

[17] Ladics GS, Bartholomaeus A, Bregitzer P. et al. Genetic basis and detection of unintended effects in genetically modified crop plants. Transgenic Res. 2015; 24 :587-603

[18] Lowe K, Wu E, Wang N. et al. Morphogenic regulators Baby boom and Wuschel improve monocot transformation. Plant Cell. 2016; 28 :1998-2015

[19] Debernardi JM, Tricoli DM, Ercoli MF. et al. A GRF-GIF chimeric protein improves the regeneration efficiency of transgenic plants. Nat Biotechnol. 2020; 38 :1274-9

[20] Kong J, Martin OS, Finer J. et al. Overexpression of the transcription factor GROWTH-REGULATING FACTOR5 improves transformation of dicot and monocot species. Front Plant Sci. 2020; 11 :572319

[21] Jones-Rhoades MW, Bartel DP. Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell. 2004; 14 :787-99

[22] Cao D, Wang J, Ju Z. et al. Regulations on growth and development in tomato cotyledon, flower and fruit via destruction of miR396 with short tandem target mimic. Plant Sci. 2016; 247 :1-12

[23] Liu Y, Yan J, Wang K. et al. MiR396-GRF module associates with switchgrass biomass yield and feedstock quality. Plant Biotechnol J. 2021; 19 :1523-36

[24] Gao F, Wang K, Liu Y. et al. Blocking miR396 increases rice yield by shaping inflorescence architecture. Nat Plants. 2015; 2 :15196

[25] Bazin J, Khan GA, Combier JP. et al. miR396 affect mycorrhization and root meristem activity in the legume Medicago truncatula. Plant J. 2013; 74 :920-34

[26] Szczygieł-Sommer A, Gaj MD. The miR396-GRF regulatory module controls the embryogenic response in Arabidopsis via an auxin-related pathway. Int Mol Sci. 2019; 20 :5221

[27] Schmülling T, Werner T, Riefler M. et al. Structure and function of cytokinin oxidase/dehydrogenase genes of maize, rice, Arabidopsis and other species. J Plant Res. 2003; 116 :241-52

[28] Castro-Mondragon JA, Riudavets-Puig R, Rauluseviciute I. et al. JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles. Nucleic Acids Res. 2022; 50 :D165-73

[29] Yan J, Gu Y, Jia X. et al. Effective small RNA destruction by the expression of a short tandem target mimic in Arabidopsis. Plant Cell. 2012; 24 :415-27

[30] Pan C, Ye L, Qin L. et al. CRISPR/Cas9-mediated efficient and heritable targeted mutagenesis in tomato plants in the first and later generations. Sci Rep. 2016; 6 :24765

[31] Pramanik D, Shelake RM, Park JY. et al. CRISPR/Cas9-mediated generation of pathogen-resistant tomato against tomato yellow leaf curl virus and powdery mildew. Int J Mol Sci. 2021; 22 :1878

[32] Shang S, Wu C, Huang C. et al. Genome-wide analysis of the GRF family reveals their involvement in abiotic stress response in cassava. Genes. 2018; 9 :110

[33] Chen F, Yang Y, Luo X. et al. Genome-wide identification of GRF transcription factors in soybean and expression analysis of GmGRF family under shade stress. BMC Plant Biol. 2019; 19 :269

[34] Victorathisayam T, Sridevi G. Ectopic expression of WUSCHEL (AtWUS) gene alters plant growth and development in rice. Plant. 2020; 8 :43-53

[35] Chen X, Cheng J, Chen L. et al. Auxin-independent NAC pathway acts in response to explant-specific wounding and promotes root tip emergence during de novo root organogenesis in Arabidopsis. Plant Physiol. 2016; 170 :2136-45

[36] Jia D, Gong X, Li M. et al. Overexpression of a novel apple NAC transcription factor gene, MdNAC1, confers the dwarf phenotype in transgenic apple (Malus domestica). Genes. 2018; 9 :229

[37] Demirer GS, Zhang H, Matos JL. et al. High aspect ratio nanomaterials enable delivery of functional genetic material without DNA integration in mature plants. Nat Nanotechnol. 2019; 14 : 456-64

[38] Demirer GS, Zhang H, Goh NS. et al. Carbon nanocarriers deliver siRNA to intact plant cells for efficient gene knockdown. Sci Adv. 2020; 6 :eaaz0795

[39] Eulgem T, Somssich IE. Networks of WRKY transcription factors in defense signaling. Curr Opin Plant Biol. 2007; 10 :366-71

[40] Adachi H, Nakano T, Miyagawa N. et al. WRKY transcription factors phosphorylated by MAPK regulate a plant immune NADPH oxidase in Nicotiana benthamiana. Plant Cell. 2015; 27 :2645-63

[41] Hu Z, Wang R, Zheng M. et al. TaWRKY51 promotes lateral root formation through negative regulation of ethylene biosynthesis in wheat ( Triticum aestivum L.). Plant J. 2018; 96 :372-88

[42] Guo D, Zhang J, Wang X. et al. The WRKY transcription factor WRKY71/EXB1 controls shoot branching by transcriptionally regulating RAX genes in Arabidopsis. Plant Cell. 2015; 27 : 3112-27

[43] Raines T, Blakley IC, Tsai YC. et al. Characterization of the cytokinin-responsive transcriptome in rice. BMC Plant Biol. 2016; 16 :260

[44] Varkonyi-Gasic E, Wu R, Wood M. et al. Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs. Plant Methods. 2007; 3 :12

[45] Lei J, Sun Y. miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data. Bioinformatics. 2014; 30 :2837-9

[46] Dai X, Zhuang Z, Zhao PX. psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res. 2018; 46 : W49-54