JoVE Journal > Environment
Summary
Abstract
Introduction
Protocol
Results
Discussion
Disclosures
Acknowledgements
Materials
References
자동 번역
환경과학

Kartoffelvirus x-baseret microRNA-lyddæmpning (VbMS) i kartoffel.

Published: May 11, 2020
doi:
10.3791/61067
, ,
1Texas A&M AgriLife Research Center at Dallas,Texas A&M University System, 2Department of Plant Pathology, Microbiology,Texas A&M University

Summary

Vi præsenterer en detaljeret protokol for kartoffelvirus X (PVX)-baserede microRNA silencing (VbMS) system til funktionelt karakterisere endogene mikroRNA’er (miRNAs) i kartoffel. Target mimic (TM) molekyler af miRNA af interesse er integreret i PVX vektor og forbigående udtrykt i kartoffel til tavshed målet miRNA eller miRNA familie.

Abstract

Virusbaseret microRNA-lyddæmpning (VbMS) er et hurtigt og effektivt værktøj til funktionel karakterisering af mikroRNA’er (miRNAs) i planter. VbMS-systemet er udviklet og anvendt til forskellige plantearter, herunder Nicotiana benthamiana, tomat, arabidopsis, bomuld og monokotplanter som hvede og majs. Her beskriver vi en detaljeret protokol ved hjælp af PVX-baserede VbMS-vektorer til at lukke munden på endogene miRNA’er i kartoffel. For at nedbryde udtrykket af en bestemt miRNA, mål efterligne (TM) molekyler af miRNA af interesse er designet, integreret i plantevirus vektorer, og udtrykt i kartoffel ved Agrobacterium infiltration at binde direkte til den endogene miRNA af interesse og blokere dens funktion.

Introduction

Plant microRNAs (miRNAs) er karakteriseret som 20-24 nukleotid-lange, atomkodede regulatoriske RNA’er1 og spiller grundlæggende roller i næsten alle aspekter af plantebiologiske processer, herunder vækst og udvikling2,3, fotosyntese og metabolisme4,5,6,7, hormonsyntese og signalering8,9, biotiske og abiotiske reaktioner10, 11,12,13, og næringsstof og energi regulering14,15. De regulatoriske roller plante miRNA’er er godt programmeret og opfyldt typisk på post-transcriptional niveauer ved enten kløvning eller translationelt undertrykke målet mRNAs.

Der er gjort enorme fremskridt i retning af identifikation, transskriptionel profilering og målforudsigelse af miRNA’er i kartoffel16,17,18,19,20,21. Imidlertid har den funktionelle karakterisering af miRNA’er i planter, herunder kartoffel, haltet bagefter andre organismer på grund af manglen på effektive og højgennemløb genetiske tilgange. Det er udfordrende at udføre funktionel analyse af individuelle miRNA ved standard tab-af funktion analyse, fordi de fleste miRNAs tilhører familier med betydelig genetisk redundans22. Derudover kan en enkelt miRNA kontrollere flere målgener23, og flere forskellige miRNA’er kan modulere den samme molekylære vej sammen24,25. Disse egenskaber gør det vanskeligt at karakterisere funktionen af en bestemt miRNA eller en miRNA-familie.

Meget af den funktionelle analyse af miRNA’er har i høj grad været afhængig af gain-of-function tilgange, der har åbenlyse begrænsninger. Den kunstige miRNA (amiRNA) metode udnytter de endogene primære udskrifter (pri-miRNAs) til at producere miRNA’er på et højt niveau, hvilket fører til hæmning af målgenekspression26,27,28,29. Aktiveringsmærkning og miRNA-overekspression ved hjælp af en stærk konstituerende 35S-promotor fører imidlertid ofte til øget udtryk for miRNA’er, der ikke er repræsentative for in vivo-forhold og derfor muligvis ikke afspejler miRNAs’ endogene funktion30. Der er udviklet en alternativ tilgang, der involverer ekspression af miRNA-resistente former for målgener, der indeholder urentable mutationer i bindings- og/eller kavalergangsstederne31,32,33. Men denne tilgang kan også potentielt forårsage fejlfortolkning af fænotypen stammer fra miRNA-resistente måltransgene på grund af transgene artefakter. Derfor bør der drages konklusioner af disse gain-of-function-undersøgelser med forsigtighed34. En anden væsentlig begrænsning af de ovenfor beskrevne tilgange er, at de kræver transformation, som er arbejdskrævende og tidskrævende. Desuden gælder de transgeneafhængige tilgange næppe for transform-genstridige plantearter. Derfor er det vigtigt at udvikle en hurtig og effektiv tilgang til tab af funktion for at optrævle miRNA’ernes funktion.

For at omgå forudsætningen for transformationsproceduren er virusbaseret microRNA-lyddæmpning (VbMS) blevet etableret ved at kombinere mål efterligne (TM) strategier med virus-afledte vektorer. I VbMS-systemet udtrykkes kunstigt designede TM-molekyler forbigående fra en virus rygrad, der tilbyder et kraftfuldt, højt gennemløb og tidsbesparende værktøj til at dissekere funktionen af plante endogene miRNAs35,36. VbMS blev oprindeligt udviklet i N. benthamiana og tomat med tobak rattle virus (TRV)35,36,37 og er blevet udvidet til Arabidopsis, bomuld, hvede og majs ved hjælp af forskellige andre virus udtryk systemer, herunder kartoffel virus X (PVX)38, bomuld blad krølle virus (ClCrV)39, agurk mosaik virus (CMV)40,41,42, kinesisk hvede mosaik virus (CWMV)43 og bygstribemosaikvirus (BSMV)44,45.

Kartoffel (Solanum tuberosum) er den fjerde vigtigste fødevareafgrøde og den mest dyrkede ikke-dødelige afgrøde i verden primært på grund af dens høje næringsværdi, høj energiproduktion og relativt lave inputbehov46. Flere funktioner i kartoffel gør det til en attraktiv dicotyledonous model plante. Det er en vegetativt formeret polyploid afgrøde med høj outcrossing sats, heterozygosity, og genetisk mangfoldighed. Til dato er der dog ingen rapport, der karakteriserer funktionen af miRNA’er i kartoffel ved hjælp af VbMS. Her præsenterer vi en ligation-uafhængig kloning (LIC)-tilpasset kartoffel PVX-baseret VbMS tilgang til at evaluere funktionen af miRNA’er i kartoffelplanter38. Vi valgte miR165/166 familien til at illustrere VbMS assay, fordi miR165/166 familien og deres mål mRNAs og klasse III homeodomain / Leu lynlås (HD-ZIP III) transskription faktorer har været omfattende karakteriseret22,47,48. HS-ZIP III-generne er centrale regulatorer for meristemudvikling og organpolaritet, og undertrykkelse af miR165/166-funktionen fører til øget udtryk for HS-ZIP III-generne, hvilket resulterer i pleotropiske udviklingsdefekter såsom reduceret apikal dominans og afvigende mønstre af bladpolaritet22,35,38,41 . De letbrændte udviklingsfænotyper korreleret med lyddæmpning af miRNA165/166 muliggør en nøjagtig evaluering af effektiviteten af den PVX-baserede VbMS-analyse.

I denne undersøgelse viser vi, at det PVX-baserede VbMS-system effektivt kan blokere funktionen af miRNA’er i kartoffel. Fordi PVX-baserede virus-induceret genhæmning (VIGS) system er blevet etableret i en række kartoffel sorter49,50,51,52, denne PVX-baserede VbMS tilgang kan sandsynligvis anvendes til en bred vifte af diploid og tetraploid kartoffel arter.

Protocol

1. Dyrk kartoffelplanter. Formere in vitro kartoffelplanter i kulturrør (25 x 150 mm) med Murashige og Skoog (MS) medier plus Gamborgs vitamin (MS basal salt blanding, Gamborgs vitamin, 30 g/L saccharose, 3,5 g/L agar, pH = 5,7). Placer rørene i vækstrummet under 20-22 °C, 16 timer lys/8 h mørk fotoperiode og lysintensitet 120 μmol/m2∙s1.BEMÆRK: Nye skud og rødder udvikler sig normalt om 1-2 uger fra planter. Former planter med friske MS/Gamborgs vitaminmedier hver måned.</l…

Representative Results

Figur 2 viser PVX-STTM165/166 kartoffelplanter (Katahdin) med ektopisk vækst af bladvæv fra abaxialsiden af bladlamina langs venerne. Mere alvorlige fænotyper såsom trompet-formet bladdannelse er også blevet observeret. I modsætning hertil blev der ikke observeret nogen fænotypisk abnormitet i PVX-kontrolanlæggene. Disse resultater viser, at VbMS-systemet var effektivt til at undertrykke endogene miRNA-funktion i tetraploid kartoffelplanter, og PVX-VbMS-systemet var et robust genetis…

Discussion

Vi præsenterer et PVX-baseret miRNA lyddæmpningssystem for at karakterisere funktionen af endogene miRNA’er i kartoffel ved at integrere STTM-designet i PVX-vektoren. VbMS-systemet viste sig at være effektivt til at lukke munden på miRNA165/166 i kartoffel, en meget bevaret miRNA-familie på tværs af plantearter.

TM-tilgangen er udviklet til at forstyrre udtrykket af miRNA’er baseret på en kunstig miRNA-mål efterligner, der er designet til at skabe en mismatch loop på det forventede ka…

Disclosures

The authors have nothing to disclose.

Acknowledgements

Vi takker Dr. Yule Liu fra Tsinghua University for at give PVX-LIC vektor. Dette arbejde blev støttet af en start-up fond fra Texas A &M AgriLife Research og Hatch Project TEX0-1-9675 fra USDA National Institute of Food and Agriculture til JS.

Materials

100 µM dATP and 100 µM dTTP Omega Bio-tek, Inc., Norcross, Norcross, GA 30071 , USA TQAC136
3 M Sodium acetate, pH 4.0. Teknova, Hollister, CA 95023, USA #S0297
Acetosyringone TCI America, Portland, OR 97203, USA D2666-25G
Agrobacterium tumefaciens strains: GV3101, GV2260 or EHA105.
Chloroform VWR Corporate, Radnor, PA 19087-8660, USA VWRV0757-950ML
Dimethyl sulfoxide, DMSO TCI America, Portland, OR 97203, USA D0798-25G
DTT VWR Corporate, Radnor, PA 19087-8660, USA VWRV0281-25G
E. coli DB3.1 for maintenance of PVX-LIC and pTRV2e containing the ccdB gene
E. coli DH5α for the destination constructs generated by LIC cloning
Fertilizer: Peters Peat Lite Special 15-0-15 Dark Weather Feed ICL Specialty Fertilizers, Summerville, SC 29483, USA G99260
High fidelity PCR reagents: KAPA HiFi DNA Polymerase with dNTPs Roche Sequencing and Life Science, Kapa Biosystems,
Wilmington, MA, USA		 7958960001
Isoamyl alcohol VWR Corporate, Radnor, PA 19087-8660, USA VWRV0944-1L
Koptec Pure Ethanol – 200 Proof Decon Labs, King of Prussia, PA 19406 , USA V1005M
MES TCI America, Portland, OR 97203, USA M0606-250G
MgCl2 ThermoFisher, Waltham, MA 02451, USA MFCD00149781
M-MuLV Reverse Transcriptase New England BioLabs, Ipswich, MA 01938-2723 USA M0253L
Nano-drop spectrometer: NanoDrop OneC Microvolume UV-Vis Spectrophotometer with Wi-Fi ThermoFisher, Waltham, MA 02451, USA ND-ONEC-W
PCR machine: Bio-Rad MyCycler PCR System Bio-Rad, Hercules, California 94547, USA 170-9703
PCR machine: Eppendorf Mastercycler pro Eppendorf, Hauppauge, NY 11788, USA 950030010
pH meter Sper Scientific, Scottsdale, AZ 85260, USA Benchtop pH / mV Meter – 860031
Phenol:chloroform:isoamyl alcohol (25:24:1), pH 6.7/8.0. VWR Corporate, Radnor, PA 19087-8660, USA VWRV0883-400ML
Phytagel: Gellan Gum Alfa Aesar, Tewksbury, MA 01876, USA J63423-A1
PVX VIGS vector: PVX-LIC Zhao et al., 2016
Real-time PCR machine: QuantStudio 6 Flex Real-Time PCR System ThermoFisher, Waltham, MA 02451, USA 4485697
Real-time PCR reagent: KAPA SYBR® FAST qPCR Master Mix (2x) Kit Roche Sequencing and Life Science, Kapa Biosystems,
Wilmington, MA 01887, USA		 7959389001
Restriction enzyme: SmaI New England BioLabs, Ipswich, MA 01938-2723 USA R0141S
Reverse transcription reagents: qScript cDNA SuperMix Quanta BioSciences, Gaithersburg, MD 20877 , USA 95107-100
RNA extraction Kit: E.Z.N.A. Plant RNA Kit Omega Bio-tek, Inc., Norcross, Norcross, GA 30071 , USA SKU: D3485-01
RNase Inhibitor Murine New England BioLabs, Ipswich, MA 01938-2723 USA M0314L
RNAzol RT Sigma-Aldrich, St. Louis, MO 63103, USA R4533
Soil: Metro-Mix 360 Sun Gro Horticulture, Agawam, MA 01001-2907, USA Metro-Mix 360
T4 DNA polymerase and buffer New England BioLabs, Ipswich, MA 01938-2723 USA M0203S
DOWNLOAD MATERIALS LIST

References

  1. Axtell, M. J., Meyers, B. C. Revisiting Criteria for Plant MicroRNA Annotation in the Era of Big Data. The Plant Cell. 30 (2), 272-284 (2018).
  2. Chen, X. Small RNAs and Their Roles in Plant Development. Annual Review of Cell and Developmental Biology. 25 (1), 21-44 (2009).
  3. Rubio-Somoza, I., Weigel, D. MicroRNA networks and developmental plasticity in plants. Trends in Plant Science. 16 (5), 258-264 (2011).
  4. Zhang, J. -. P., et al. MiR408 Regulates Grain Yield and Photosynthesis via a Phytocyanin Protein. Plant Physiology. 175 (3), 1175-1185 (2017).
  5. Gupta, O. P., Karkute, S. G., Banerjee, S., Meena, N. L., Dahuja, A. Contemporary Understanding of miRNA-Based Regulation of Secondary Metabolites Biosynthesis in Plants. Frontiers in Plant Science. 8 (374), (2017).
  6. May, P., et al. The effects of carbon dioxide and temperature on microRNA expression in Arabidopsis development. Nature Communications. 4 (1), 2145 (2013).
  7. Krützfeldt, J., Stoffel, M. MicroRNAs: A new class of regulatory genes affecting metabolism. Cell Metabolism. 4 (1), 9-12 (2006).
  8. Damodharan, S., Corem, S., Gupta, S. K., Arazi, T. Tuning of SlARF10A dosage by sly-miR160a is critical for auxin-mediated compound leaf and flower development. The Plant Journal. 96 (4), 855-868 (2018).
  9. Nizampatnam, N. R., Schreier, S. J., Damodaran, S., Adhikari, S., Subramanian, S. microRNA160 dictates stage-specific auxin and cytokinin sensitivities and directs soybean nodule development. The Plant Journal. 84 (1), 140-153 (2015).
  10. Chinnusamy, V., Zhu, J., Zhu, J. -. K. Cold stress regulation of gene expression in plants. Trends in Plant Science. 12 (10), 444-451 (2007).
  11. Covarrubias, A. A., Reyes, J. L. Post-transcriptional gene regulation of salinity and drought responses by plant microRNAs. Plant, Cell, Environment. 33 (4), 481-489 (2010).
  12. Wang, S., et al. Suppression of nbe-miR166h-p5 attenuates leaf yellowing symptoms of potato virus X on Nicotiana benthamiana and reduces virus accumulation. Molecular Plant Pathology. 19 (11), 2384-2396 (2018).
  13. Canto-Pastor, A., et al. Enhanced resistance to bacterial and oomycete pathogens by short tandem target mimic RNAs in tomato. Proceedings of the National Academy of Sciences. 116 (7), 2755-2760 (2019).
  14. Chiou, T. -. J., Lin, S. -. I. Signaling Network in Sensing Phosphate Availability in Plants. Annual Review of Plant Biology. 62 (1), 185-206 (2011).
  15. Sunkar, R., Chinnusamy, V., Zhu, J., Zhu, J. -. K. Small RNAs as big players in plant abiotic stress responses and nutrient deprivation. Trends in Plant Science. 12 (7), 301-309 (2007).
  16. Kwenda, S., Birch, P. R. J., Moleleki, L. N. Genome-wide identification of potato long intergenic noncoding RNAs responsive to Pectobacterium carotovorum subspecies brasiliense infection. BMC Genomics. 17 (1), 614 (2016).
  17. Lakhotia, N., et al. Identification and characterization of miRNAome in root, stem, leaf and tuber developmental stages of potato (Solanum tuberosum L.) by high-throughput sequencing. BMC Plant Biology. 14 (1), 6 (2014).
  18. Koc, I., Filiz, E., Tombuloglu, H. Assessment of miRNA expression profile and differential expression pattern of target genes in cold-tolerant and cold-sensitive tomato cultivars. Biotechnology, Biotechnological Equipment. 29 (5), 851-860 (2015).
  19. Zhang, N., et al. Identification of Novel and Conserved MicroRNAs Related to Drought Stress in Potato by Deep Sequencing. PLoS One. 9 (4), 95489 (2014).
  20. Xie, F., Frazier, T. P., Zhang, B. Identification, characterization and expression analysis of MicroRNAs and their targets in the potato (Solanum tuberosum). Gene. 473 (1), 8-22 (2011).
  21. Zhang, R., Marshall, D., Bryan, G. J., Hornyik, C. Identification and Characterization of miRNA Transcriptome in Potato by High-Throughput Sequencing. PLoS One. 8 (2), 57233 (2013).
  22. Yan, J., et al. Effective Small RNA Destruction by the Expression of a Short Tandem Target Mimic in Arabidopsis. The Plant Cell. 24 (2), 415-427 (2012).
  23. Roodbarkelari, F., Groot, E. P. Regulatory function of homeodomain-leucine zipper (HD-ZIP) family proteins during embryogenesis. New Phytologist. 213 (1), 95-104 (2017).
  24. Reichel, M., Millar, A. A. Specificity of plant microRNA target MIMICs: Cross-targeting of miR159 and miR319. Journal of Plant Physiology. 180, 45-48 (2015).
  25. Taylor, R. S., Tarver, J. E., Hiscock, S. J., Donoghue, P. C. J. Evolutionary history of plant microRNAs. Trends in Plant Science. 19 (3), 175-182 (2014).
  26. Schwab, R., Ossowski, S., Riester, M., Warthmann, N., Weigel, D. Highly Specific Gene Silencing by Artificial MicroRNAs in Arabidopsis. The Plant Cell. 18 (5), 1121-1133 (2006).
  27. Martin, A., et al. Graft-transmissible induction of potato tuberization by the microRNA miR172. Development. 136 (17), 2873-2881 (2009).
  28. Yang, L., et al. Overexpression of potato miR482e enhanced plant sensitivity to Verticillium dahliae infection. Journal of Integrative Plant Biology. 57 (12), 1078-1088 (2015).
  29. Tang, Y., et al. Virus-based microRNA expression for gene functional analysis in plants. Plant Physiology. 153 (2), 632-641 (2010).
  30. Voinnet, O. Origin, Biogenesis, and Activity of Plant MicroRNAs. Cell. 136 (4), 669-687 (2009).
  31. Teotia, S., Tang, G. To Bloom or Not to Bloom: Role of MicroRNAs in Plant Flowering. Molecular Plant. 8 (3), 359-377 (2015).
  32. Wu, G., Poethig, R. S. Temporal regulation of shoot development in Arabidopsis thaliana by miR156 and its target SPL3. Development. 133 (18), 3539-3547 (2006).
  33. Zhao, L., Kim, Y., Dinh, T. T., Chen, X. miR172 regulates stem cell fate and defines the inner boundary of APETALA3 and PISTILLATA expression domain in Arabidopsis floral meristems. The Plant Journal. 51 (5), 840-849 (2007).
  34. Li, J., Millar, A. A. Expression of a microRNA-Resistant Target Transgene Misrepresents the Functional Significance of the Endogenous microRNA: Target Gene Relationship. Molecular Plant. 6 (2), 577-580 (2013).
  35. Sha, A., et al. Virus-based microRNA silencing in plants. Plant Physiology. 164 (1), 36-47 (2014).
  36. Zhao, J., Liu, Y. Virus-based MicroRNA Silencing. Bio-protocol. 6 (2), 1714 (2016).
  37. Yan, F., et al. A virus-based miRNA suppression (VbMS) system for miRNA loss-of-function analysis in plants. Biotechnology Journal. 9 (5), 702-708 (2014).
  38. Zhao, J., et al. An efficient Potato virus X-based microRNA silencing in Nicotiana benthamiana. Scientific Reports. 6, 20573 (2016).
  39. Gu, Z., Huang, C., Li, F., Zhou, X. A versatile system for functional analysis of genes and microRNAs in cotton. Plant Biotechnology Journal. 12 (5), 638-649 (2014).
  40. Du, Z., et al. Using a viral vector to reveal the role of microRNA159 in disease symptom induction by a severe strain of cucumber mosaic virus. Plant Physiology. 164 (3), 1378-1388 (2014).
  41. Liao, Q., Tu, Y., Carr, J. P., Du, Z. An improved cucumber mosaic virus-based vector for efficient decoying of plant microRNAs. Scientific Reports. 5, 13178 (2015).
  42. Liu, X., et al. Analyses of MiRNA Functions in Maize Using a Newly Developed ZMBJ-CMV-2bN81-STTM Vector. Frontiers in Plant Science. 10, 1277 (2019).
  43. Yang, J., et al. Chinese Wheat Mosaic Virus-Induced Gene Silencing in Monocots and Dicots at Low Temperature. Frontiers in Plant Science. 9, 1627 (2018).
  44. Jiao, J., Wang, Y., Selvaraj, J. N., Xing, F., Liu, Y. Barley Stripe Mosaic Virus (BSMV) Induced MicroRNA Silencing in Common Wheat (Triticum aestivum L.). PLoS One. 10 (5), 0126621 (2015).
  45. Jian, C., et al. Virus-Based MicroRNA Silencing and Overexpressing in Common Wheat (Triticum aestivum L.). Frontiers in Plant Science. 8, 500 (2017).
  46. Barrell, P. J., Meiyalaghan, S., Jacobs, J. M. E., Conner, A. J. Applications of biotechnology and genomics in potato improvement. Plant Biotechnology Journal. 11 (8), 907-920 (2013).
  47. Peng, T., et al. A Resource for Inactivation of MicroRNAs Using Short Tandem Target Mimic Technology in Model and Crop Plants. Molecular Plant. 11 (11), 1400-1417 (2018).
  48. Teotia, S., Zhang, D., Tang, G., Kaufmann, M., Klinger, C., Savelsbergh, A. . Functional Genomics: Methods and Protocols. , 337-349 (2017).
  49. Dommes, A. B., Herbert, D. B., Kivivirta, K. I., Gross, T., Becker, A. Virus-induced gene silencing: empowering genetics in non-model organisms. Journal of Experimental Botany. 70 (3), 757-770 (2018).
  50. Lacomme, C., Chapman, S. Use of Potato Virus X (PVX)-Based Vectors for Gene Expression and Virus-Induced Gene Silencing (VIGS). Current Protocols in Microbiology. 8 (1), 11-16 (2008).
  51. Lim, H. -. S., et al. Efficiency of VIGS and gene expression in a novel bipartite potexvirus vector delivery system as a function of strength of TGB1 silencing suppression. Virology. 402 (1), 149-163 (2010).
  52. Gleba, Y., Klimyuk, V., Marillonnet, S. Viral vectors for the expression of proteins in plants. Current Opinion in Biotechnology. 18 (2), 134-141 (2007).
  53. Tang, G., et al. Construction of short tandem target mimic (STTM) to block the functions of plant and animal microRNAs. Methods. 58 (2), 118-125 (2012).
  54. Kozomara, A., Griffiths-Jones, S. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Research. 39, 152-157 (2010).
  55. Kozomara, A., Griffiths-Jones, S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Research. 42 (1), 68-73 (2013).
  56. Griffiths-Jones, S. The microRNA Registry. Nucleic Acids Research. 32, 109-111 (2004).
  57. Griffiths-Jones, S., Grocock, R. J., van Dongen, S., Bateman, A., Enright, A. J. miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Research. 34, 140-144 (2006).
  58. Griffiths-Jones, S., Saini, H. K., van Dongen, S., Enright, A. J. miRBase: tools for microRNA genomics. Nucleic Acids Research. 36, 154-158 (2007).
  59. Kozomara, A., Birgaoanu, M., Griffiths-Jones, S. miRBase: from microRNA sequences to function. Nucleic Acids Research. 47 (1), 155-162 (2018).
  60. Yin, K., Tang, Y., Zhao, J. Genome-wide characterization of miRNAs involved in N Gene-mediated Immunity in response to tobacco mosaic virus in Nicotiana benthamiana. Evolutionary Bioinformatics. , 1-11 (2015).
  61. Dunker, F., et al. Oomycete small RNAs invade the plant RNA-induced silencing complex for virulence. bioRxiv. , 689190 (2019).
  62. Green, M. R., Sambrook, J. . Molecular Cloning. A Laboratory Mannual 4th. , (2014).
  63. Sambrook, J., Russell, D. . Molecular Cloning: A Laboratory Manual. 3rd Edition. , (2001).
  64. Anderson, S., et al. Sequence and organization of the human mitochondrial genome. Nature. 290 (5806), 457-465 (1981).
  65. Sanger, F., Nicklen, S., Coulson, A. R. DNA sequencing with chain-terminating inhibitors. Proceedings of the National Academy of Sciences. 74 (12), 5463-5467 (1977).
  66. Qian, L., et al. Hsp90 Interacts With Tm-22 and Is Essential for Tm-22-Mediated Resistance to Tobacco mosaic virus. Frontiers in Plant Science. 9 (411), (2018).
  67. Voinnet, O., Baulcombe, D. C. Systemic signalling in gene silencing. Nature. 389 (6651), 553 (1997).
  68. Li, C., et al. A cis Element within Flowering Locus T mRNA Determines Its Mobility and Facilitates Trafficking of Heterologous Viral RNA. Journal of Virology. 83 (8), 3540-3548 (2009).
  69. Chen, C., et al. Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Research. 33 (20), 179 (2005).
  70. Varkonyi-Gasic, E., Hellens, R. P., Kodama, H., Komamine, A. . RNAi and Plant Gene Function Analysis: Methods and Protocols. , 145-157 (2011).
  71. Varkonyi-Gasic, E., Wu, R., Wood, M., Walton, E. F., Hellens, R. P. Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs. Plant Methods. 3 (1), 12 (2007).
  72. Varkonyi-Gasic, E., Kovalchuk, I. . Plant Epigenetics: Methods and Protocols. , 163-175 (2017).
  73. Czimmerer, Z., et al. A Versatile Method to Design Stem-Loop Primer-Based Quantitative PCR Assays for Detecting Small Regulatory RNA Molecules. PLoS One. 8 (1), 55168 (2013).
  74. Dai, X., Zhuang, Z., Zhao, P. X. psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Research. 46 (1), 49-54 (2018).
  75. Untergasser, A., et al. Primer3-new capabilities and interfaces. Nucleic Acids Research. 40 (15), 115 (2012).
  76. Livak, K. J., Schmittgen, T. D. Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method. Methods. 25 (4), 402-408 (2001).
  77. Schmittgen, T. D., Livak, K. J. Analyzing real-time PCR data by the comparative CT method. Nature Protocols. 3 (6), 1101-1108 (2008).
  78. Todesco, M., Rubio-Somoza, I., Paz-Ares, J., Weigel, D. A Collection of Target Mimics for Comprehensive Analysis of MicroRNA Function in Arabidopsis thaliana. PLoS Genetics. 6 (7), 1001031 (2010).
  79. Franco-Zorrilla, J. M., et al. Target mimicry provides a new mechanism for regulation of microRNA activity. Nature Genetics. 39 (8), 1033-1037 (2007).
  80. Jiang, N., et al. Tomato lncRNA23468 functions as a competing endogenous RNA to modulate NBS-LRR genes by decoying miR482b in the tomato-Phytophthora infestans interaction. Horticulture Research. 6 (1), 28 (2019).
  81. Ivashuta, S., et al. Regulation of gene expression in plants through miRNA inactivation. PLoS One. 6 (6), 21330 (2011).
  82. Reichel, M., Li, Y., Li, J., Millar, A. A. Inhibiting plant microRNA activity: molecular SPONGEs, target MIMICs and STTMs all display variable efficacies against target microRNAs. Plant Biotechnology Journal. 13 (7), 915-926 (2015).
  83. Wong, G., Alonso-Peral, M., Li, B., Li, J., Millar, A. A. MicroRNA MIMIC binding sites: Minor flanking nucleotide alterations can strongly impact MIMIC silencing efficacy in Arabidopsis. Plant Direct. 2 (10), 00088 (2018).
  84. Paschoal, A. R., Lozada-Chávez, I., Domingues, D. S., Stadler, P. F. ceRNAs in plants: computational approaches and associated challenges for target mimic research. Briefings in Bioinformatics. 19 (6), 1273-1289 (2018).
  85. Faivre-Rampant, O., et al. Potato Virus X-Induced Gene Silencing in Leaves and Tubers of Potato. Plant Physiology. 134 (4), 1308-1316 (2004).
  86. Zhao, J., et al. Virus-Induced Gene Silencing in Diploid and Tetraploid Potata Species. Methods in Molecular Biology. , (2019).
  87. Leisner, C. P., et al. Genome sequence of M6, a diploid inbred clone of the high-glycoalkaloid-producing tuber-bearing potato species Solanum chacoense, reveals residual heterozygosity. The Plant Journal. 94 (3), 562-570 (2018).
  88. Aversano, R., et al. The Solanum commersonii Genome Sequence Provides Insights into Adaptation to Stress Conditions and Genome Evolution of Wild Potato Relatives. The Plant Cell. 27 (4), 954-968 (2015).
  89. The Potato Genome Sequencing, C. et al. Genome sequence and analysis of the tuber crop potato. Nature. 475, 189 (2011).
  90. Navarro, C., et al. Control of flowering and storage organ formation in potato by FLOWERING LOCUS T. Nature. 478 (7367), 119-122 (2011).
  91. Lehretz, G. G., Sonnewald, S., Hornyik, C., Corral, J. M., Sonnewald, U. Post-transcriptional Regulation of FLOWERING LOCUS T Modulates Heat-Dependent Source-Sink Development in Potato. Current Biology. 29 (10), 1614-1624 (2019).
  92. Natarajan, B., et al. MiRNA160 is associated with local defense and systemic acquired resistance against Phytophthora infestans infection in potato. Journal of Experimental Botany. 69 (8), 2023-2036 (2018).
  93. Li, F., et al. MicroRNA regulation of plant innate immune receptors. Proceedings of the National Academy of Sciences. 109 (5), 1790-1795 (2012).
  94. Weiberg, A., et al. Fungal Small RNAs Suppress Plant Immunity by Hijacking Host RNA Interference Pathways. Science. 342 (6154), 118-123 (2013).
  95. Huang, C. -. Y., Wang, H., Hu, P., Hamby, R., Jin, H. Small RNAs – Big Players in Plant-Microbe Interactions. Cell Host, Microbe. 26 (2), 173-182 (2019).
  96. Shahid, S., et al. MicroRNAs from the parasitic plant Cuscuta campestris target host messenger RNAs. Nature. 553 (7686), 82-85 (2018).
  97. Weiberg, A., Jin, H. Small RNAs-the secret agents in the plant-pathogen interactions. Current Opinion in Plant Biology. 26, 87-94 (2015).

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Keywords: Potato Virus XMicroRNA SilencingVbMSVirus-based MicroRNA SilencingMiRNAFunctional CharacterizationShort Tandem Target MimicPVXLigation Independent Cloning
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Zhao, J., Rios, C. G., Song, J. Potato Virus X-Based microRNA Silencing (VbMS) In Potato.. J. Vis. Exp. (159), e61067, doi:10.3791/61067 (2020).
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