玉米苗期根汞胁迫响应中miRNA的鉴定及初步验证

doi:10.3724/SP.J.1006.2022.13074

Abstract

Abstract:

Mercury is one of the most important sources of heavy mental pollution to crop production in the worldwide. MicroRNA (miRNA) is a critical regulator in plant development and abiotic stress responses. However, its function on mercury stress response is still unknown in monocots. To identify the critical miRNA in response to mercury, we analyzed phenotype changes and differentially expressed miRNA in seedlings of two maize inbred lines B73 and Zheng 58 (Z58) under HgCl₂ stress. The results showed that B73 was more sensitive to mercury than Z58 and miRNA166l was down-regulated in both B73 and Z58 under HgCl₂ stress. miRNA165/166 knock-out stable lines of Arabidopsis were created using STTM technology to validate its role in mercury stress response. These lines showed wilted and etiolated leaf and shorten root, which were similar with maize seedlings after mercury treatment. This study verified that miRNA166 was important for mercury stress modulation, which promoted us to explore the molecular mechanism of miRNA166 in heavy metal response in the following experiments.

Key words: maize, mercury stress, microRNA, STTM

QIN Yong-Tian, CHEN Li-Xia, TANG Ji-Hua, CHEN Jian-Hui, MA Shuan-Hong, ZHANG Xue-Hai, DING Dong, FU Zhi-Yuan. Identification and validation of miRNA involved in mercury stress response in maize seedling roots[J].Acta Agronomica Sinica, 2022, 48(12): 3018-3028.

Figures/Tables 6

Fig. 1

Fig. 2

Table 1

Table 2

Differentially expressed miRNA in B73 and Z58 after HgCl2 stress"

B73			郑58 Zheng 58
基因序列号 Gene ID	log₂ (Fold Change)	P_adj-value	基因序列号 Gene ID	log₂ (Fold Change)	P_adj-value
zma-miRNA156b	2.1	1.65E-09	zma-miRNA156b	2.1	5.24E-05
zma-miRNA156i	2.8	3.09E-11	zma-miRNA156i	-2.3	6.64E-03
zma-miRNA156l	2.4	7.91E-05	zma-miRNA156l	-2.2	3.29E-04
zma-miRNA159a	-3.9	3.09E-33	zma-miRNA159a	1.6	3.23E-16
zma-miRNA159b	-4.0	1.27E-27	zma-miRNA159b	1.6	3.39E-16
zma-miRNA159c	-1.4	8.17E-04	zma-miRNA159c	3.8	1.19E-45
zma-miRNA159d	-1.4	3.35E-03	zma-miRNA159d	3.9	3.94E-44
zma-miRNA159f	-3.6	2.38E-30	zma-miRNA159f	1.8	6.23E-20
zma-miRNA159j	-4.2	8.07E-40	zma-miRNA159j	1.6	2.07E-16
zma-miRNA159k	-4.0	2.70E-31	zma-miRNA159k	1.6	6.04E-17
zma-miRNA166j	-2.5	5.90E-06	zma-miRNA166j	1.1	2.65E-02
zma-miRNA166k	-3.5	3.84E-12	zma-miRNA166k	1.0	2.91E-02
zma-miRNA166l	-2.8	1.07E-05	zma-miRNA166l	-1.4	4.30E-05
zma-miRNA167b	3.1	1.14E-07	zma-miRNA167b	-2.1	3.79E-10
zma-miRNA167c	2.4	2.38E-03	zma-miRNA167c	-1.1	2.00E-02
zma-miRNA167g	1.2	1.68E-03	zma-miRNA167g	-1.6	1.90E-04
zma-miRNA169g	10.8	3.70E-05	zma-miRNA169g	-4.3	2.80E-02
zma-miRNA171d	8.9	4.04E-02	zma-miRNA171d	-7.4	3.19E-02
zma-miRNA171g	1.9	4.27E-02	zma-miRNA171g	2.2	4.80E-02
zma-miRNA171l	8.9	4.04E-02	zma-miRNA171l	-8.9	1.00E-04
zma-miRNA171n	10.3	6.35E-04	zma-miRNA171n	-8.1	3.70E-03
zma-miRNA393b	12.4	4.92E-11	zma-miRNA393b	-4.1	4.03E-02
zma-miRNA396c	2.7	1.73E-12	zma-miRNA396c	-1.9	1.57E-14
zma-miRNA396d	2.2	1.84E-10	zma-miRNA396d	-1.9	1.03E-16
zma-miRNA398a	-1.9	6.31E-04	zma-miRNA398a	1.2	7.49E-04
zma-miRNA398b	-1.3	1.30E-03	zma-miRNA398b	1.1	2.59E-04
zma-miRNA408a	-2.0	1.01E-03	zma-miRNA408a	3.9	1.02E-80
zma-miRNA408b	-2.2	6.31E-04	zma-miRNA408b	3.9	5.01E-74
zma-miRNA2118a	-24.4	1.65E-06	zma-miRNA397b	-4.7	2.33E-94
zma-miRNA159e	-23.9	2.77E-06	zma-miRNA319d	2.8	1.86E-39
zma-miRNA399a	-23.9	2.77E-06	zma-miRNA319b	2.8	1.27E-35
zma-miRNA169a	-4.1	8.97E-06	zma-miRNA319a	2.2	5.98E-20
zma-miRNA166n	-3.3	5.31E-09	zma-miRNA319c	2.2	1.70E-16
zma-miRNA2118b	-2.5	1.72E-02	zma-miRNA390b	-3.9	7.90E-14
zma-miRNA166h	-2.5	1.46E-18	zma-miRNA171f	-10.0	1.12E-07
zma-miRNA166m	-2.4	4.24E-03	zma-miRNA169b	-2.7	1.34E-06
zma-miRNA166b	-2.4	1.35E-23	zma-miRNA390a	-3.3	1.43E-05
zma-miRNA166g	-2.3	3.18E-21	zma-miRNA1432	-3.1	1.68E-05
zma-miRNA166i	-2.2	4.79E-15	zma-miRNA164b	2.5	5.24E-05
zma-miRNA166d	-2.2	7.66E-14	zma-miRNA164c	2.6	5.42E-05
zma-miRNA166f	-2.1	2.65E-13	zma-miRNA164g	2.6	9.17E-04
zma-miRNA166a	-2.1	2.27E-13	zma-miRNA172d	-8.4	1.26E-03
zma-miRNA166c	-2.0	2.95E-15	zma-miRNA164a	2.3	3.02E-03
zma-miRNA166e	-1.9	9.86E-14	zma-miRNA167d	-1.7	3.19E-03
zma-miRNA528b	-1.7	1.40E-02	zma-miRNA397a	-4.9	3.70E-03
zma-miRNA528a	-1.5	1.49E-03	zma-miRNA164h	2.4	2.04E-02
zma-miRNA167i	1.1	2.66E-03	zma-miRNA399h	-7.4	3.13E-02
zma-miRNA167j	1.3	3.96E-02	zma-miRNA164d	2.1	3.55E-02
zma-miRNA167h	1.4	4.27E-02	zma-miRNA171m	-7.4	4.00E-02
zma-miRNA827	1.5	1.63E-03
zma-miRNA171h	1.5	2.78E-02
zma-miRNA167f	1.5	8.83E-03
zma-miRNA171k	1.6	2.07E-02
zma-miRNA156d	1.7	1.36E-03
zma-miRNA168a	1.7	1.07E-05
zma-miRNA156g	1.8	1.51E-12
zma-miRNA168b	1.8	7.65E-05
zma-miRNA396f	2.0	2.41E-02
zma-miRNA162	2.0	3.46E-03
zma-miRNA156e	2.1	1.46E-18
zma-miRNA156f	2.1	3.52E-04
zma-miRNA164e	2.3	1.57E-05
zma-miRNA156a	2.3	1.55E-10
zma-miRNA396g	2.3	1.34E-02
zma-miRNA156k	2.5	4.12E-09
zma-miRNA156h	2.7	9.32E-08
zma-miRNA156h	2.7	9.32E-08
zma-miRNA169r	9.2	2.47E-02
zma-miRNA395b	9.2	2.47E-02
zma-miRNA395p	9.2	2.07E-02
zma-miRNA171b	9.4	1.11E-02
zma-miRNA171e	9.8	3.46E-03
zma-miRNA399j	10.0	1.63E-03
zma-miRNA169k	10.2	8.17E-04
zma-miRNA171i	10.6	1.20E-04
zma-miRNA169m	11.0	8.17E-06
zma-miRNA172b	22.2	1.30E-05
zma-miRNA395o	22.2	1.30E-05

Table 2

Fig. 3

Fig. 4

References 73

[1]	Gong Z, Xiong L, Shi H, Yang S, Herrera-Estrella L, Xu G, Chao D Y, Li J, Wang P Y, Qin F, Li J, Ding Y, Shi Y, Wang Y, Yang Y, Guo Y, Zhu J K. Plant abiotic stress response and nutrient use efficiency. Sci China Life Sci, 2020, 63: 635-674. doi: 10.1007/s11427-020-1683-x pmid: 32246404
[2]	Gnamuš A, Byrne A R, Horvat M. Mercury in the soil-plant-deer- predator food chain of a temperate forest in Slovenia. Environ Sci Technol, 2000, 34: 3337-3345. doi: 10.1021/es991419w
[3]	Yin R, Feng X, Wang J, Bao Z, Yu B, Chen J. Mercury isotope variations between bioavailable mercury fractions and total mercury in mercury contaminated soil in Wanshan Mercury Mine, SW China. Chem Geol, 2013, 336: 80-86. doi: 10.1016/j.chemgeo.2012.04.017
[4]	Natasha, Shahid M, Khalid S, Bibi I, Bundschuh J, Khan Niazi N K, Dumat C. A critical review of mercury speciation, bioavailability, toxicity and detoxification in soil-plant environment: ecotoxicology and health risk assessment. Sci Total Environ, 2020, 711: 134749.
[5]	Patra M, Sharma A. Mercury toxicity in plants. Bot Rev, 2000, 66: 379-422. doi: 10.1007/BF02868923
[6]	Larssen T. Mercury in Chinese reservoirs. Environ Pollut, 2010, 158: 24-25. doi: 10.1016/j.envpol.2009.07.026 pmid: 19665271
[7]	Wang Y, Greger M. Clonal differences in mercury tolerance, accumulation, and distribution in willow. J Environ Qual, 2004, 33: 1779-1785. pmid: 15356238
[8]	Gupta D K, Nicoloso F T, Schetinger M R, Rossato L V, Pereira L B, Castro G Y, Srivastava S, Tripathi R D. Antioxidant defense mechanism in hydroponically grown Zea mays seedlings under moderate lead stress. J Hazard Mater, 2009, 172: 479-484. doi: 10.1016/j.jhazmat.2009.06.141 pmid: 19625122
[9]	Natasha Shahid M Niazi N K Khalid S Murtaza B Bibi I Rashid M I. A critical review of selenium biogeochemical behavior in soil-plant system with an inference to human health. Environ Poll, 2018, 234: 915-934. doi: 10.1016/j.envpol.2017.12.019
[10]	Shahid M, Dumat C, Pourrut B, Silvestre J, Laplanche C, Pinelli E. Influence of EDTA and citric acid on lead-induced oxidative stress to Vicia faba roots. J Soil Sediment, 2014, 14: 835-843. doi: 10.1007/s11368-013-0724-0
[11]	Shahid M, Ferrand E, Schreck E, Dumat C. Behavior and impact of zirconium in the soil-plant system: plant uptake and phytotoxicity. Rev Environ Contam Toxicol, 2013, 221: 107-127. doi: 10.1007/978-1-4614-4448-0_2 pmid: 23090631
[12]	Meng d, Chen J, Yang Z M. Enhancement of tolerance of Indian mustard (Brassica juncea) to mercury by carbon monoxide. J Hazard Mater, 2011, 186: 1823-1829. doi: 10.1016/j.jhazmat.2010.12.062 pmid: 21227573
[13]	Priya M, Balakrishnan V, Kiruthika Lakshmi A, Aruna R, Ravindran K C. Mercury induced oxidative stress of antioxidants in Clitoria ternatea L. Int Lett Nat Sci, 2014, 23: 1-8.
[14]	Pirzadah T B, Malik B, Tahir I, Irfan Q M, Rehman R U. Characterization of mercury-induced stress biomarkers in Fagopyrumtataricum plants. Int J Phytoremed, 2018, 20: 225-236. doi: 10.1080/15226514.2017.1374332
[15]	Asgher M, Per T S, Anjum S, Khan M I R, Masood A, Verma S, Khan N A. Contribution of glutathione in heavy metal stress tolerance in plants. In: Khan M, Khan N, eds. Reactive Oxygen Species and Antioxidant Systems in Plants: Role and Regulation under Abiotic Stress. Springer, Singapore, 2017.
[16]	Gratão P L, Polle A, Lea P J, Azevedo R A. Making the life of heavy metal-stressed plants a little easier. Func Plant Biol, 2005, 32: 481-494. doi: 10.1071/FP05016
[17]	Huang Y, Chen H, Reinfelder J R, Liang X, Sun C, Liu C, Li F, Yi J. A transcriptomic (RNA-seq) analysis of genes responsive to both cadmium and arsenic stress in rice root. Sci Total Environ, 2019, 666: 445-460. doi: 10.1016/j.scitotenv.2019.02.281
[18]	Kostecka-Gugała A, Latowski D. Arsenic-induced oxidative stress in plants. In: Hasanuzzaman M, Nahar K, Fujita M, eds. Mechanisms of Arsenic Toxicity and Tolerance in Plants. Springer, Singapore, 2018.
[19]	Zhao L, Meng B, Feng X. Mercury methylation in rice paddy and accumulation in rice plant: a review. Ecotox Environ Safe, 2020, 195: 110462.
[20]	Cho U, Park J. Mercury-induced oxidative stress in tomato seedlings. Plant Sci, 2000, 156: 1-9. pmid: 10908800
[21]	Ansari M K A, Ahmad A, Umar S, Iqbal M. Mercury-induced changes in growth variables and antioxidative enzyme activities in Indian mustard. J Plant Interact, 2009, 4: 131-136. doi: 10.1080/17429140802716713
[22]	Tamás L, Mistrík I, Huttová J, Halusková L, Valentovicová K, Zelinová V. Role of reactive oxygen species-generating enzymes and hydrogen peroxide during cadmium, mercury and osmotic stresses in barley root tip. Planta, 2010, 231: 221-231. doi: 10.1007/s00425-009-1042-z pmid: 19898864
[23]	Tazawa M, Ohkuma E, Shibasaka M, Nakashima S. Mercurial-sensitive water transport in barley roots. J Plant Res, 1997, 110: 435-442. doi: 10.1007/BF02506803
[24]	Zhou Z S, Huang S Q, Guo K, Mehta S K, Zhang P C, Yang Z M. Metabolic adaptations to mercury-induced oxidative stress in roots of Medicago sativa L. J Inorg Biochem, 2007, 101: 1-9. doi: 10.1016/j.jinorgbio.2006.05.011
[25]	Boening D W. Ecological effects, transport, and fate of mercury: a general review. Chemosphere, 2000, 40: 1335-1351. pmid: 10789973
[26]	Zhang W H, Tyerman S D. Inhibition of water channels by HgCl₂ in intact wheat root cells. Plant Physiol, 1999, 120: 849-858. pmid: 10398721
[27]	Xylander M, Hagen C, Braune W. Mercury increases light susceptibility in the green alga Haematococcus lacustris. Bot Acta, 1996, 109: 222-228. doi: 10.1111/j.1438-8677.1996.tb00567.x
[28]	Gupta P, Jain M, Sarangthem J, Gadre R. Inhibition of 5-aminolevulinic acid dehydratase by mercury in excised greening maize leaf segments. Plant Physiol Biochem, 2013, 62: 63-69. doi: 10.1016/j.plaphy.2012.10.008
[29]	Gao J, Luo M, Peng H, Chen F, Li W. Characterization of cadmium-responsive microRNAs and their target genes in maize (Zea mays) roots. BMC Mol Biol, 2019, 20: 14. doi: 10.1186/s12867-019-0131-1 pmid: 31046674
[30]	Yu Y, Hu H, Wang C, Yang L. QTL analysis of mercury tolerance and accumulation at the seedling stage in rice (Oryza sativa L.). J Food Agric Environ, 2011, 9: 748-752.
[31]	Wang C, Wang T, Wu P, Li Z, Yang L. Quantitative trait loci for mercury tolerance in rice seedlings. Rice Sci, 2013, 20: 238-242. doi: 10.1016/S1672-6308(13)60124-9
[32]	Rugh C L, Wilde H D, Stack N M, Thompson D M, Summers A O, Meagher R B. Mercuric ion reduction and resistance in transgenic Arabidopsis thaliana plants expressing a modified bacterial merA gene. Proc Natl Acad Sci USA, 1996, 93: 3182-3187. doi: 10.1073/pnas.93.8.3182
[33]	Li R, Wu H, Ding J, Li N, Fu W, Gan L, Li Y. Transgenic merA and merB expression reduces mercury contamination in vegetables and grains grown in mercury-contaminated soil. Plant Cell Rep, 2020, 39: 1369-1380. doi: 10.1007/s00299-020-02570-8
[34]	Heaton A C, Rugh C L, Kim T, Wang N J, Meagher R B. Toward detoxifying mercury-polluted aquatic sediments with rice genetically engineered for mercury resistance. Environ Toxicol Chem, 2003, 22: 2940-2947. pmid: 14713034
[35]	Sone Y, Uraguchi S, Takanezawa Y, Nakamura R, Pan-Hou H, Kiyono M. A novel role of MerC in methylmercury transport and phytoremediation of methylmercury contamination. Biol Pharm Bull, 2017, 40: 1125-1128. doi: 10.1248/bpb.b17-00213
[36]	Chen Z, Pan Y, Wang S, Ding Y, Yang W, Zhu C. Overexpression of a protein disulfide isomerase-like protein from Methanothermobacter thermoautotrophicum enhances mercury tolerance in transgenic rice. Plant Sci, 2012, 197: 10-20. doi: 10.1016/j.plantsci.2012.08.005
[37]	Nagata T, Kiyono M, Pan-Hou H. Engineering expression of bacterial polyphosphate kinase in tobacco for mercury remediation. Appl Microb Biotechnol, 2006, 72: 777-782. doi: 10.1007/s00253-006-0336-3
[38]	Ruiz O N, Alvarez D, Torres C, Roman L, Daniell H. Metallothionein expression in chloroplasts enhances mercury accumulation and phytoremediation capability. Plant Biotechnol J, 2011, 9: 609-617. doi: 10.1111/j.1467-7652.2011.00616.x pmid: 21518240
[39]	Wang Z Q, Li G Z, Gong Q Q, Li G X, Zheng S J. OsTCTP, encoding a translationally controlled tumor protein, plays an important role in mercury tolerance in rice. BMC Plant Biol, 2015, 15: 123. doi: 10.1186/s12870-015-0500-y pmid: 25990386
[40]	Zhao Z, Fu Z, Lin Y, Chen H, Liu K, Xing X, Liu Z, Li W, Tang J. Genome-wide association analysis identifies loci governing mercury accumulation in maize. Sci Rep, 2017, 7: 247. doi: 10.1038/s41598-017-00189-6 pmid: 28325924
[41]	Fu Z, Li W, Zhang Q, Wang L, Zhang X, Song G, Fu Z, Ding D, Liu Z, Tang J. Quantitative trait loci for mercury accumulation in maize (Zea mays L.) identified using a RIL population. PLoS One, 2014, 9: e107243.
[42]	Yan J, Gu Y, Jia X, Kang W, Pan S, Tang X, Chen X, Tang G. Effective small RNA destruction by the expression of a short tandem target mimic in Arabidopsis. Plant Cell, 2012, 24: 415-427. doi: 10.1105/tpc.111.094144
[43]	Song X, Li Y, Cao X, Qi Y. MicroRNAs and their regulatory roles in plant-environment interactions. Annu Rev Plant Biol, 2019, 70: 489-525. doi: 10.1146/annurev-arplant-050718-100334 pmid: 30848930
[44]	Ma Z, Axtell M J. Long-range genomic enrichment, sequencing, and assembly to determine unknown sequences flanking a known microRNA. PloS One, 2013, 8: e83721.
[45]	Wang T, Gao X, Chen S, Li D, Chen S, Xie M, Xu Z, Yang G. Genome-wide identification and expression analysis of ethylene responsive factor family transcription factors in Juglans regia. Peer J, 2021, 9: e12429.
[46]	Yan J, Gu Y, Jia X, Kang W, Pan S, Tang X, Chen X, Tang G. Effective small RNA destruction by the expression of a short tandem target mimic in Arabidopsis. Plant Cell, 2012, 24: 415-427. doi: 10.1105/tpc.111.094144
[47]	Yuan W, Suo J, Shi B, Zhou C, Bai B, Bian H, Zhu M, Han N. The barley miR393 has multiple roles in regulation of seedling growth, stomatal density, and drought stress tolerance. Plant Physiol Biochem, 2019, 142: 303-311. doi: 10.1016/j.plaphy.2019.07.021
[48]	Zhou M, Zheng S, Liu R, Lu L, Zhang C, Zhang L, Yant L, Wu Y. The genome-wide impact of cadmium on microRNA and mRNA expression in contrasting Cd responsive wheat genotypes. BMC Genomics, 2019, 20: 615. doi: 10.1186/s12864-019-5939-z pmid: 31357934
[49]	Gao J, Luo M, Peng H, Chen F, Li W. Characterization of cadmium-responsive microRNAs and their target genes in maize (Zea mays) roots. BMC Mol Biol, 2019, 20: 14. doi: 10.1186/s12867-019-0131-1 pmid: 31046674
[50]	Zhang L, Ding H, Jiang H, Wang H, Chen K, Duan J, Feng S, Wu G. Regulation of cadmium tolerance and accumulation by miR156 in Arabidopsis. Chemosphere, 2020, 242: 125168.
[51]	Meng J G, Zhang X D, Tan S K, Zhao K X, Yang Z M. Genome-wide identification of Cd-responsive NRAMP transporter genes and analyzing expression of NRAMP 1 mediated by miR167 in Brassica napus. Biometals, 2017, 30: 917-931. doi: 10.1007/s10534-017-0057-3 pmid: 28993932
[52]	Feyissa B A, Arshad M, Gruber M Y, Kohalmi S E, Hannoufa A. The interplay between miR156/SPL13 and DFR/WD40-1 regulate drought tolerance in alfalfa. BMC Plant Biol, 2019, 19: 434. doi: 10.1186/s12870-019-2059-5 pmid: 31638916
[53]	Moradi K, Khalili F. Assessment of pattern expression of miR172 and miR169 in response to drought stress in Echinacea purpurea L. Biocat Agric Biotech, 2018, 16: 507-512. doi: 10.1016/j.bcab.2018.08.022
[54]	Luan M, Xu M, Lu Y, Zhang Q, Zhang L, Zhang C, Fan Y, Lang Z, Wang L. Family-wide survey of miR169s and NF-YAs and their expression profiles response to abiotic stress in maize roots. PLoS One, 2014, 9: e91369.
[55]	Cole C, Sobala A, Lu C, Thatcher S R, Bowman A, Brown J W, Green P J, Barton G J, Hutvagner G. Filtering of deep sequencing data reveals the existence of abundant Dicer-dependent small RNAs derived from tRNAs. RNA (New York), 2009, 15: 2147-2160.
[56]	Sakaguchi J, Watanabe Y. miR165/166 and the development of land plants. Dev Growth Differ, 2012, 54: 93-99. doi: 10.1111/j.1440-169X.2011.01318.x
[57]	Ding Y, Gong S, Wang Y, Wang F, Bao H, Sun J, Cai C, Yi K, Chen Z, Zhu C. MicroRNA166 modulates cadmium tolerance and accumulation in rice. Plant Physiol, 2018, 177: 1691-1703. doi: 10.1104/pp.18.00485 pmid: 29925586
[58]	McConnell J R, Emery J, Eshed Y, Bao N, Bowman J, Barton M K. Role of PHABULOSA and PHAVOLUTA in determining radial patterning in shoots. Nature, 2001, 411: 709-713. doi: 10.1038/35079635
[59]	Ursache R, Miyashima S, Chen Q, Vatén A, Nakajima K, Carlsbecker A, Zhao Y, Helariutta Y, Dettmer J. Tryptophan-dependent auxin biosynthesis is required for HD-ZIP III-mediated xylem patterning. Development, 2014, 141: 1250-1259. doi: 10.1242/dev.103473 pmid: 24595288
[60]	Singh A, Roy S, Singh S, Das S S, Gautam V, Yadav S, Kumar A, Singh A, Samantha S, Sarkar A K. Phytohormonal crosstalk modulates the expression of miR166/165s, target Class III HD-ZIPs, and KANADI genes during root growth in Arabidopsis thaliana. Sci Rep, 2017, 7: 3408. doi: 10.1038/s41598-017-03632-w
[61]	Hashimoto K, Miyashima S, Sato-Nara K, Yamada T, Nakajima K. Functionally diversified members of the MIR165/6 gene family regulate ovule morphogenesis in Arabidopsis thaliana. Plant Cell Physiol, 2018, 59: 1017-1026. doi: 10.1093/pcp/pcy042 pmid: 29462472
[62]	Ramachandran P, Wang G, Augstein F, de Vries J, Carlsbecker A. Continuous root xylem formation and vascular acclimation to water deficit involves endodermal ABA signalling via miR165. Development, 2018, 145: dev159202.
[63]	Tang G, Yan J, Gu Y, Qiao M, Fan R, Mao Y, Tang X. Construction of short tandem target mimic (STTM) to block the functions of plant and animal microRNAs. Methods, 2012, 58: 118-125. doi: 10.1016/j.ymeth.2012.10.006 pmid: 23098881
[64]	Zhang M, An P, Li H, Wang X, Zhou J, Dong P, Zhao Y, Wang Q, Li C. The miRNA-mediated post-transcriptional regulation of maize in response to high temperature. Int J Mol Sci, 2019, 20: 1754. doi: 10.3390/ijms20071754
[65]	Rhoades M W, Reinhart B J, Lim L P, Burge C B, Bartel B, Bartel D P. Prediction of plant microRNA targets. Cell, 2002, 110: 513-520. pmid: 12202040
[66]	Valiollahi E, Farsi M, Kakhki A M. Sly-miR166 and Sly-miR319 are components of the cold stress response in Solanum lycopersicum. Plant Biotech Rep, 2014, 8: 349-356. doi: 10.1007/s11816-014-0326-3
[67]	Kitazumi A, Kawahara Y, Onda T S, De Koeyer D, de los Reyes B G. Implications of miR166 and miR159 induction to the basal response mechanisms of an andigena potato (Solanum tuberosum subsp. andigena) to salinity stress, predicted from network models in Arabidopsis. Genome, 2015, 58: 13-24.
[68]	Zhang J, Zhang H, Srivastava A K, Pan Y, Bai J, Fang J, Shi H, Zhu J K. Knockdown of rice microRNA166 confers drought resistance by causing leaf rolling and altering stem xylem development. Plant Physiol, 2018, 176: 2082-2094. doi: 10.1104/pp.17.01432 pmid: 29367235
[69]	Peng T, Qiao M, Liu H, Teotia S, Zhang Z, Zhao Y, Wang B, Zhao D, Shi L, Zhang C, Le B, Rogers K, Gunasekara C, Duan H, Gu Y, Tian L, Nie J, Qi J, Meng F, Huang L, Chen Q, Wang Z, Tang J, Tang X, Lan T, Chen X, Wei H, Zhao Q, Tang G. A resource for inactivation of microRNAs using Short Tandem Target Mimic technology in model and crop plants. Mol Plant, 2018, 11: 1400-1417. doi: S1674-2052(18)30275-2 pmid: 30243763
[70]	Kong Y, Elling A A, Chen B, Deng X. Differential expression of microRNAs in maize inbred and hybrid lines during salt and drought stress. Am J Plant Sci, 2010, 1: 69-76. doi: 10.4236/ajps.2010.12009
[71]	Sasaki A, Yamaji N, Ma J F. Overexpression of OsHMA3 enhances Cd tolerance and expression of Zn transporter genes in rice. J Exp Bot, 2014, 65: 6013-6021. doi: 10.1093/jxb/eru340 pmid: 25151617
[72]	Li X, Ma S, Yi C. Pseudouridine: the fifth RNA nucleotide with renewed interests. Curr Opin Chem Biol, 2016, 33: 108-116. doi: 10.1016/j.cbpa.2016.06.014 pmid: 27348156
[73]	Thieme C J, Rojas-Triana M, Stecyk E, Schudoma C, Zhang W, Yang L, Miñambres M, Walther D, Schulze W X, Paz-Ares J, Scheible W R, Kragler F. Endogenous Arabidopsis messenger RNAs transported to distant tissues. Nat Plants, 2015, 1: 15025. doi: 10.1038/nplants.2015.25

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组织 Tissue	含量Content (mean±SD)		P值 P-value
组织 Tissue	CK (μg L^-1)	Hg (μg L^-1)	P值 P-value
B73地下部分Part below the ground of B73	26.79±0.21	28.41±0.09	1.07E-08^**
B73地上部分Part above the ground of B73	20.577±0.48	26.64±0.54	1.88E-06^**
郑58地下部分Part below the ground of Z58	20.29±0.82	28.25±0.04	1.86E-06^**
郑58地上部分Part above the ground of Z58	14.45±0.81	24.77±0.87	8.09E-06^**

Identification and validation of miRNA involved in mercury stress response in maize seedling roots

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