Інновації в сучасній освіті

22 ref. doi: 10.1093/nar/gng158International audienc

Direct comparison of nick-joining activity of the nucleic acid ligases from bacteriophage T4

The genome of bacteriophage T4 encodes three polynucleotide ligases, which seal the backbone of nucleic acids during infection of host bacteria. The T4Dnl (T4 DNA ligase) and two RNA ligases [T4Rnl1 (T4 RNA ligase 1) and T4Rnl2] join a diverse array of substrates, including nicks that are present in double-stranded nucleic acids, albeit with different efficiencies. To unravel the biochemical and functional relationship between these proteins, a systematic analysis of their substrate specificity was performed using recombinant proteins. The ability of each protein to ligate 20 bp double-stranded oligonucleotides containing a single-strand break was determined. Between 4 and 37 °C, all proteins ligated substrates containing various combinations of DNA and RNA. The RNA ligases ligated a more diverse set of substrates than T4Dnl and, generally, T4Rnl1 had 50-1000-fold lower activity than T4Rnl2. In assays using identical conditions, optimal ligation of all substrates was at pH 8 for T4Dnl and T4Rnl1 and pH 7 for T4Rnl2, demonstrating that the protein dictates the pH optimum for ligation. All proteins ligated a substrate containing DNA as the unbroken strand, with the nucleotides at the nick of the broken strand being RNA at the 3'-hydroxy group and DNA at the 5'-phosphate. Since this RNA-DNA hybrid was joined at a similar maximal rate by T4Dnl and T4Rnl2 at 37 °C, we consider the possibility that this could be an unexpected physiological substrate used during some pathways of 'DNA repair'

Transcriptomic Events Involved in Melon Mature-Fruit Abscission Comprise the Sequential Induction of Cell-Wall Degrading Genes Coupled to a Stimulation of Endo and Exocytosis

Background: Mature-fruit abscission (MFA) in fleshy-fruit is a genetically controlled process with mechanisms that, contrary to immature-fruit abscission, has not been fully characterized. Here, we use pyrosequencing to characterize the transcriptomes of melon abscission zone (AZ) at three stages during AZ-cell separation in order to understand MFA control at an early stage of AZ-activation. Principal Findings: The results show that by early induction of MFA, the melon AZ exhibits major gene induction, while by late induction of MFA, melon AZ shows major gene repression. Although some genes displayed similar regulation in both early and late induction of abscission, such as EXT1-EXT4, EGase1, IAA2, ERF1, AP2D15, FLC, MADS2, ERAF17, SAP5 and SCL13 genes, the majority had different expression patterns. This implies that time-specific events occur during MFA, and emphasizes the value of characterizing multiple time-specific abscission transcriptomes. Analysis of gene-expression from these AZs reveal that a sequential induction of cell-wall-degrading genes is associated with the upregulation of genes involved in endo and exocytosis, and a shift in plant-hormone metabolism and signaling genes during MFA. This is accompanied by transcriptional activity of small-GTPases and synthaxins together with tubulins, dynamins, V-type ATPases and kinesin-like proteins potentially involved in MFA signaling. Early events are potentially controlled by down-regulation of MADS-box, AP2/ERF and Aux/IAA transcription-factors, and up-regulation of homeobox, zinc finger, bZIP, and WRKY transcription-factors, while late events may be controlled by up-regulation of MYB transcription-factors. Significance: Overall, the data provide a comprehensive view on MFA in fleshy-fruit, identifying candidate genes and pathways associated with early induction of MFA. Our comprehensive gene-expression profile will be very useful for elucidating gene regulatory networks of the MFA in fleshy-fruit

Characterization of the cork oak transcriptome dynamics during acorn development

Background: Cork oak (Quercus suber L.) has a natural distribution across western Mediterranean regions and is a keystone forest tree species in these ecosystems. The fruiting phase is especially critical for its regeneration but the molecular mechanisms underlying the biochemical and physiological changes during cork oak acorn development are poorly understood. In this study, the transcriptome of the cork oak acorn, including the seed, was characterized in five stages of development, from early development to acorn maturation, to identify the dominant processes in each stage and reveal transcripts with important functions in gene expression regulation and response to water. Results: A total of 80,357 expressed sequence tags (ESTs) were de novo assembled from RNA-Seq libraries representative of the several acorn developmental stages. Approximately 7.6 % of the total number of transcripts present in Q. suber transcriptome was identified as acorn specific. The analysis of expression profiles during development returned 2,285 differentially expressed (DE) transcripts, which were clustered into six groups. The stage of development corresponding to the mature acorn exhibited an expression profile markedly different from other stages. Approximately 22 % of the DE transcripts putatively code for transcription factors (TF) or transcriptional regulators, and were found almost equally distributed among the several expression profile clusters, highlighting their major roles in controlling the whole developmental process. On the other hand, carbohydrate metabolism, the biological pathway most represented during acorn development, was especially prevalent in mid to late stages as evidenced by enrichment analysis. We further show that genes related to response to water, water deprivation and transport were mostly represented during the early (S2) and the last stage (S8) of acorn development, when tolerance to water desiccation is possibly critical for acorn viability. Conclusions: To our knowledge this work represents the first report of acorn development transcriptomics in oaks. The obtained results provide novel insights into the developmental biology of cork oak acorns, highlighting transcripts putatively involved in the regulation of the gene expression program and in specific processes likely essential for adaptation. It is expected that this knowledge can be transferred to other oak species of great ecological value.Fundação para a Ciência e a Tecnologi

RNA Captor: A Tool for RNA Characterization

Background: In the genome era, characterizing the structure and the function of RNA molecules remains a major challenge. Alternative transcripts and non-protein-coding genes are poorly recognized by the current genome-annotation algorithms and efficient tools are needed to isolate the less-abundant or stable RNAs. Results: A universal RNA-tagging method using the T4 RNA ligase 2 and special adapters is reported. Based on this system, protocols for RACE PCR and full-length cDNA library construction have been developed. The RNA tagging conditions were thoroughly optimized and compared to previous methods by using a biochemical oligonucleotide tagging assay and RACE PCRs on a range of transcripts. In addition, two large-scale full-length cDNA inventories relying on this method are presented. Conclusion: The RNA Captor is a straightforward and accessible protocol. The sensitivity of this approach was shown to be higher compared to previous methods, and applicable on messenger RNAs, non-protein-coding RNAs, transcription-start sites and microRNA-directed cleavage sites of transcripts. This strategy could also be used to study other classes of RNA and in deep sequencing experiments

Genomic and expression analysis of multiple Sry loci from a single Rattus norvegicus Y chromosome

BACKGROUND: Sry is a gene known to be essential for testis determination but is also transcribed in adult male tissues. The laboratory rat, Rattus norvegicus, has multiple Y chromosome copies of Sry while most mammals have only a single copy. DNA sequence comparisons with other rodents with multiple Sry copies are inconsistent in divergence patterns and functionality of the multiple copies. To address hypotheses of divergence, gene conversion and functional constraints, we sequenced Sry loci from a single R. norvegicus Y chromosome from the Spontaneously Hypertensive Rat strain (SHR) and analyzed DNA sequences for homology among copies. Next, to determine whether all copies of Sry are expressed, we developed a modification of the fluorescent marked capillary electrophoresis method to generate three different sized amplification products to identify Sry copies. We applied this fragment analysis method to both genomic DNA and cDNA prepared from mRNA from testis and adrenal gland of adult male rats. RESULTS: Y chromosome fragments were amplified and sequenced using primers that included the entire Sry coding region and flanking sequences. The analysis of these sequences identified six Sry loci on the Y chromosome. These are paralogous copies consistent with a single phylogeny and the divergence between any two copies is less than 2%. All copies have a conserved reading frame and amino acid sequence consistent with function. Fragment analysis of genomic DNA showed close approximations of experimental with predicted values, validating the use of this method to identify proportions of each copy. Using the fragment analysis procedure with cDNA samples showed the Sry copies expressed were significantly different from the genomic distribution (testis p < 0.001, adrenal gland p < 0.001), and the testis and adrenal copy distribution in the transcripts were also significantly different from each other (p < 0.001). Total Sry transcript expression, analyzed by real-time PCR, showed significantly higher levels of Sry in testis than adrenal gland (p, 0.001). CONCLUSION: The SHR Y chromosome contains at least 6 full length copies of the Sry gene. These copies have a conserved coding region and conserved amino acid sequence. The pattern of divergence is not consistent with gene conversion as the mechanism for this conservation. Expression studies show multiple copies expressed in the adult male testis and adrenal glands, with tissue specific differences in expression patterns. Both the DNA sequence analysis and RNA transcript expression analysis are consistent with more than one copy having function and selection preventing divergence although we have no functional evidence

Construction and analysis of full-length and normalized cDNA libraries from citrus

[EN] We have developed an integrated method to generate a normalized cDNA collection enriched in full-length and rare transcripts from citrus, using different species and multiple tissues and developmental stages. Interpretation of ever-increasing raw sequence information generated by modern genome sequencing technologies faces multiple challenges, such as gene function analysis and genome annotation. In this regard, the availability of full-length cDNA clones facilitates functional analysis of the corresponding genes enabling manipulation of their expression and the generation of a variety of tagged versions of the native protein. The development of full-length cDNA sequences has the power to improve the quality of genome annotation, as well as provide tools for functional characterization of genesThe authors would like to thank to all participants in the Spanish Citrus Functional Genomic Project, specially to Drs. Javier Forment, Jose Gadea, and Vicente Conejero. This work was funded by grants from the Spanish Government GEN2001-4885-CO5-01 and GEN2001-4885-CO5-02.Marques, MC.; Perez Amador, MA. (2012). Construction and analysis of full-length and normalized cDNA libraries from citrus. Functional Genomics: Methods and Protocols. 815:51-65. https://doi.org/10.1007/978-1-61779-424-7_5S5165815Carninci P, Kvam C, Kitamura A, Ohsumi T, Okazaki Y, Itoh M, Kamiya M, Shibata K, Sasaki N, Izawa M, Muramatsu M, Hayashizaki Y, and Schneider C (1996) High-efficiency full-length cDNA cloning by biotinylated CAP trapper. Genomics 37 327–336.Carninci P, Shibata Y, Hayatsu N, Sugahara Y, Shibata K, Itoh M, Konno H, Okazaki Y, Muramatsu M, and Hayashizaki Y (2000) Normalization and subtraction of CAP-trapper-selected cDNAs to prepare full-length cDNA libraries for rapid discovery of new genes. Genome Res. 10, 1617–1630.Suzuki Y, and Sugano S (2003) Construction of a full-length enriched and a 5’-end enriched cDNA library using the Oligo-capping method. Methods Mol. Biol. 221 73–91.Clepet C, Le Clainche I, and Caboche M (2004) Improved full-length cDNA production based on RNA tagging by T4 DNA ligase. Nucleic Acids Res. 32 e6.Zhu YY, Machleder EM, Chenchik A, Li R, and Siebert PD (2001) Reverse transcriptase template switching: a SMART approach for full-length cDNA library construction. Biotechniques 30 892–897.Zhulidov PA, Bogdanova EA, Shcheglov AS, Vagner LL, Khaspekov GL, Kozhemyako VB, Matz MV, Meleshkevitch E, Moroz LL, Lukyanov SA, and Shagin DA (2004) Simple cDNA normalization using Kamchatka crab duplex-specific nuclease. Nucleic Acids Res. 32 e37.Zhulidov PA, Bogdanova EA, Shcheglov AS, Shagina IA, Wagner LL, Khazpekov GL, Kozhemyako VV, Lukyanov SA, and Shagin DA (2005) A method for the preparation of normalized cDNA libraries enriched with full-length sequences. Russian J. Bioorg. Chem. 31 170–177.Anisimova VE, Rebrikov DV, Zhulidov PA, Staroverov DB, Lukyanov SA, and Shcheglov AS (2006) Renaturation, activation, and practical use of recombinant duplex-specific nuclease from Kamchatka crab. Biochem.-Moscow 71 513–519.Toru M, Matsui T, Heidaran MA, and Aaronson SA (1989) An efficient directional cloning system to construct cDNA libraries containing full-length inserts at high frequency. Gene 83 137–146.Castelli V, Aury JM, Jaillon O, Wincker P, Clepet C, Menard M, Cruaud C, Quétier F, Scarpelli C, Schächter V, Temple G, Caboche M, Weissenbach J, and Salanoubat M (2004) Whole genome sequence comparisons and “Full-length” cDNA sequences: a combined approach to evaluate and improve Arabidopsis genome annotation. Genome Res. 14 406–413.Earley KW, Haag JR, Pontes O, Opper K, Juehne T, Song KM, and Pikaard CS (2006) Gateway-compatible vectors for plant functional genomics and proteomics. Plant J. 45 616–629.Karimi M, Inzé D, and Depicker A (2002) GATEWAY™ vectors for Agrobacterium- mediated plant transformation. TRENDS Plant Sci. 7 193–195.Hartley JL, Temple GF, and Brasch MA (2000) DNA cloning using in vitro site-specific recombination. Genome Res. 10 1788–1795.Marques M C, Alonso-Cantabrana H, Forment J, Arribas R, Alamar S, Conejero V, and Perez-Amador MA (2009) A new set of ESTs and cDNA clones from full-length and normalized libraries for gene discovery and functional characterization in citrus. BMC Genomics 10, 428

Analysis of expressed sequence tags generated from full-length enriched cDNA libraries of melon

Abstract Background Melon (Cucumis melo), an economically important vegetable crop, belongs to the Cucurbitaceae family which includes several other important crops such as watermelon, cucumber, and pumpkin. It has served as a model system for sex determination and vascular biology studies. However, genomic resources currently available for melon are limited. Result We constructed eleven full-length enriched and four standard cDNA libraries from fruits, flowers, leaves, roots, cotyledons, and calluses of four different melon genotypes, and generated 71,577 and 22,179 ESTs from full-length enriched and standard cDNA libraries, respectively. These ESTs, together with ~35,000 ESTs available in public domains, were assembled into 24,444 unigenes, which were extensively annotated by comparing their sequences to different protein and functional domain databases, assigning them Gene Ontology (GO) terms, and mapping them onto metabolic pathways. Comparative analysis of melon unigenes and other plant genomes revealed that 75% to 85% of melon unigenes had homologs in other dicot plants, while approximately 70% had homologs in monocot plants. The analysis also identified 6,972 gene families that were conserved across dicot and monocot plants, and 181, 1,192, and 220 gene families specific to fleshy fruit-bearing plants, the Cucurbitaceae family, and melon, respectively. Digital expression analysis identified a total of 175 tissue-specific genes, which provides a valuable gene sequence resource for future genomics and functional studies. Furthermore, we identified 4,068 simple sequence repeats (SSRs) and 3,073 single nucleotide polymorphisms (SNPs) in the melon EST collection. Finally, we obtained a total of 1,382 melon full-length transcripts through the analysis of full-length enriched cDNA clones that were sequenced from both ends. Analysis of these full-length transcripts indicated that sizes of melon 5' and 3' UTRs were similar to those of tomato, but longer than many other dicot plants. Codon usages of melon full-length transcripts were largely similar to those of Arabidopsis coding sequences. Conclusion The collection of melon ESTs generated from full-length enriched and standard cDNA libraries is expected to play significant roles in annotating the melon genome. The ESTs and associated analysis results will be useful resources for gene discovery, functional analysis, marker-assisted breeding of melon and closely related species, comparative genomic studies and for gaining insights into gene expression patterns.This work was supported by Research Grant Award No. IS-4223-09C from BARD, the United States-Israel Binational Agricultural Research and Development Fund, and by SNC Laboratoire ASL, de Ruiter Seeds B.V., Enza Zaden B.V., Gautier Semences S.A., Nunhems B.V., Rijk Zwaan B.V., Sakata Seed Inc, Semillas Fitó S.A., Seminis Vegetable Seeds Inc, Syngenta Seeds B.V., Takii and Company Ltd, Vilmorin and Cie S.A. and Zeraim Gedera Ltd (all of them as part of the support to ICuGI). CC was supported by CNRS ERL 8196.Peer Reviewe

Genomics, evolution, and crystal structure of a new family of bacterial spore kinases

Bacterial spore formation is a complex process of fundamental relevance to biology and human disease. The spore coat structure is complex and poorly understood, and the roles of many of the protein components remain unclear. We describe a new family of spore coat proteins, the bacterial spore kinases (BSKs), and the first crystal structure of a BSK, YtaA (CotI) from Bacillus subtilis. BSKs are widely distributed in spore-forming Bacillus and Clostridium species, and have a dynamic evolutionary history. Sequence and structure analyses indicate that the BSKs are CAKs, a prevalent group of small molecule kinases in bacteria that is distantly related to the eukaryotic protein kinases. YtaA has substantial structural similarity to CAKs, but also displays distinctive features that broaden our understanding of the CAK group. Evolutionary constraint analysis of the protein surfaces indicates that members of the BSK family have distinct clade-conserved patterns in the substrate binding region, and probably bind and phosphorylate distinct targets. Several classes of BSKs have apparently independently lost catalytic activity to become pseudokinases, indicating that the family also has a major noncatalytic function. Proteins 2010. © 2009 Wiley-Liss, Inc

Inferring the Regulatory Network of the miRNA-mediated Response to Biotic and Abiotic Stress in Melon

[EN] Background: MiRNAs have emerged as key regulators of stress response in plants, suggesting their potential as candidates for knock-in/out to improve stress tolerance in agricultural crops. Although diverse assays have been performed, systematic and detailed studies of miRNA expression and function during exposure to multiple environments in crops are limited. Results: Here, we present such pioneering analysis in melon plants in response to seven biotic and abiotic stress conditions. Deep-sequencing and computational approaches have identified twenty-four known miRNAs whose expression was significantly altered under at least one stress condition, observing that down-regulation was preponderant. Additionally, miRNA function was characterized by high scale degradome assays and quantitative RNA measurements over the intended target mRNAs, providing mechanistic insight. Clustering analysis provided evidence that eight miRNAs showed a broad response range under the stress conditions analyzed, whereas another eight miRNAs displayed a narrow response range. Transcription factors were predominantly targeted by stressresponsive miRNAs in melon. Furthermore, our results show that the miRNAs that are down-regulated upon stress predominantly have as targets genes that are known to participate in the stress response by the plant, whereas the miRNAs that are up-regulated control genes linked to development. Conclusion: Altogether, this high-resolution analysis of miRNA-target interactions, combining experimental and computational work, Illustrates the close interplay between miRNAs and the response to diverse environmental conditions, in melon.The authors thank Dr. A. Monforte for providing melon seeds and Dra. B. Pico (Cucurbits Group - COMAV) for providing melon seeds and Monosporascus isolate respectively. This work was supported by grants AGL2016-79825-R, BIO2014-61826-EXP (GG), and BFU2015-66894-P (GR) from the Spanish Ministry of Economy and Competitiveness (co-supported by FEDER). The funders had no role in the experiment design, data analysis, decision to publish, or preparation of the manuscript.Sanz-Carbonell, A.; Marques Romero, MC.; Bustamante-González, AJ.; Fares Riaño, MA.; Rodrigo Tarrega, G.; Gomez, GG. (2019). Inferring the Regulatory Network of the miRNA-mediated Response to Biotic and Abiotic Stress in Melon. BMC Plant Biology. 1-17. https://doi.org/10.1186/s12870-019-1679-0S117Zhang B. MicroRNAs: a new target for improving plant tolerance to abiotic stress. J Exp Bot. 2015;66:1749–61.Zhu JK. Abiotic stress signaling and responses in plants. Cell. 2016;167:313–24.Bielach A, Hrtyan M, Tognetti VB. Plants under stress: involvement of auxin and Cytokinin. Int J Mol Sci. 2017;4(18):7.Zarattini M, Forlani G. Toward unveiling the mechanisms for transcriptional regulation of proline biosynthesis in the plant cell response to biotic and abiotic stress conditions. Front Plant Sci. 2017;2(8):927.Nolan T, Chen J, Yin Y. Cross-talk of Brassinosteroid signaling in controlling growth and stress responses. Biochem J. 2017;474:2641–61.Mittler R. Abiotic stress, the field environment and stress combinations. Trends Plant Sci. 2006;11:15–9.Djami-Tchatchou AT, Sanan-Mishra N, Ntushelo K, Dubery IA. Functional roles of microRNAs in Agronomically important plants—potential as targets for crop improvement and protection. Front Plant Sci. 2017;8:378.Baxter A, Mittler R, Suzuki N. ROS as key players in plant stress signaling. J Exp Bot. 2014;65:1229–40.Golldack D, Li C, Mohan H, Probst N. Tolerance to drought and salt stress in plants: unraveling the signaling networks. Front Plant Sci. 2014;5:151.Lee SH, Li HW, Koh KW, Chuang HY, Chen YR, Lin CS, Chan MT. MSRB7 reverses oxidation of GSTF2/3 to confer tolerance of Arabidopsis thaliana to oxidative stress. J Exp Bot. 2014;65:5049–62.Carrera J, Rodrigo G, Jaramillo A, Elena SF. Reverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditions. Genome Biol. 2009;10(9):R96.Shriram V, Kumar V, Devarumath RM, Khare TS, Wani SH. MicroRNAs as potential targets for abiotic stress tolerance in plants. Front Plant Sci. 2016;7:817.Sunkar R, Chinnusamy V, Zhu J, Zhu JH. Small RNAs as big players in plant abiotic stress responses and nutrient deprivation. Trends Plant Sci. 2007;12:301–9.Kumar R. Role of microRNAs in biotic and abiotic stress responses in crop plants. Appl Biochem Biotechnology. 2014;174:93–115.Reis RS, Eamens AL, Waterhouse PM. Missing pieces in the puzzle of plant MicroRNAs. Trends Plant Sci. 2015;20:721–8.Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116:281–97.Borges F, Martienssen RA. The expanding world of small RNAs in plants. Nat Rev Mol Cell Biol. 2015;16:727–41.Axtell MJ, Bartel DP. Antiquity of microRNAs and their targets in land-plants. Plant Cell. 2005;17:1658–73.Cuperus JT, Fahlgren N, Carrington JC. Evolution and functional diversification of MIRNA genes. Plant Cell. 2011;23:431–42.Cui J, You C, Chen X. The evolution of microRNAs in plants. Current Opinions in Plant Biology. 2016;35:61–7.Sunkar R, Li YF, Jagadeeswaran G. Functions of microRNAs in plant stress responses. Trends Plant Sci. 2012;17:196–203.Zhang T, Zhao YL, Zhao JH, Wang S, Jin Y, Chen ZQ, Fang YY, Hua CL, Ding SW, Guo HS. Cotton plants export microRNAs to inhibit virulence gene expression in a fungal pathogen. Nature Plants. 2016;2(10):16153.Chaloner T, vanKan JA, Grant-Downton R. RNA ‘Information Warfare’ in pathogenic and mutualistic interactions. Trends Plant Sci. 2016;9:738–48.Niu D, Wang Z, Wang S, Qiao L Zhao H. Profiling of small RNAs involved in plant-pathogen interactions. Methods Molecular Biology. 2015;1287:61–79.Wei S, Wang L, Zhang Y, Huang D. Identification of early response genes to salt stress in roots of melon (Cucumis melo L.) seedlings. Molecular Biology Report. 2013;40:2915–26.Clepet C, Joobeur T, Zheng Y, Jublot D, Huang M, Truniger V, et al. Analysis of expressed sequence tags generated from full-length enriched cDNA libraries of melon. BMC Genomics. 2011;12:252.González M, Xu M, Esteras C, Roig C, Monforte AJ, Troadec C, et al. Towards a TILLING platform for functional genomics in Piel de Sapo melons. BMC Research Notes. 2011;4:289.García MJ. The genome of melon (Cucumis melo L.). Proc Natl Acad Sci U S A. 2012;109:11872–7.Pollack FG, Uecker FA. Monosporascus cannonballus: an unusual ascomycete in cantaloupe roots. Mycologia. 1974;66:346–9.Kofalvi S, Marcos J, Cañizares MC, Pallas V, Candresse T. Hop stunt viroid (HSVd) sequence variants from Prunus species: evidence for recombination between HSVd isolates. J Gen Virol. 1997;78:3177–86.Sattar S, Song Y, Anstead J, Sunkar R, Thompson G. Cucumis melo expression profile during aphid herbivory in a resistant and susceptible interaction. Mol Plant-Microbe Interact. 2012;25:839–48.Herranz MC, Navarro JA, Sommen E, Pallas V. Comparative analysis among the small RNA populations of source, sink and conductive tissues in two different plant-virus pathosystems. BMC Genomics. 2015;16:117.Jagadeeswaran G, Nimmakayala P, Zheng Y, Gowdu K, Reddy UK, Sunkar R. Characterization of the small RNA component of leaves and fruits from four different cucurbit species. BMC Genomics. 2012;13:329.Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42:D68–73.Barciszewska-Pacak M, Milanowska K, Knop K, Bielewicz D, Nuc P, Plewka P, et al. Arabidopsis microRNA expression regulation in a wide range of abiotic stress responses. Front Plant Sci. 2015;6:410.Zhou L, Liu Y, Liu Z, Kong D, Duan M, Luo L. Genome-wide identification and analysis of drought-responsive microRNAs in Oryza sativa. J Exp Bot. 2010;61:4157–68.Samad A, Sajad M, Nazaruddin N, Fauzi I, Murad A, Zainal Z, Ismanizan Ismail I. MicroRNA and transcription factor: key players in plant regulatory network. Front Plant Sci. 2017;8:565.Danisman S. TCP transcription factors at the Interface between environmental challenges and the Plant’s growth responses. Front Plant Sci. 2016;7:1930.Llave C, Xie Z, Kasschau KD, Carrington JC. Cleavage of scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA. Science. 2002;297:2053–6.Gupta OP, Meena NL, Sharma I, et al. Differential regulation of microRNAs in response to osmotic, salt and cold stresses in wheat. Mol Biol Rep. 2014;41:4623.Wang M, Wang Q, Zhang B. 2013. Response of miRNAs and their targets to salt and drought stresses in cotton (Gossypium hirsutum ). Gene 30: 26–32.Savageau MA. Demand theory of gene regulation. I. Quantitative development of the theory. Genetics. 1998;149:1665–76.Negrão S, Schmöckel SM, Tester M. Evaluating physiological responses of plants to salinity stress. Ann Bot. 2017;119:1–11.Barabasi AL, Oltvai ZN. Network biology: understanding the cell's functional organization. Nat Rev Genet. 2004;5(2):101–13.Megraw M, Cumbie J, Ivanchenko M, Filichkin S. Small genetic circuits and MicroRNAs: big players in polymerase II transcriptional control in plants. Plant Cell. 2016;28:286–303.Wang St, Sun Xl, Hoshino Y, Yu Y, Jia B, et al. 2014. MicroRNA319 Positively Regulates Cold Tolerance by Targeting OsPCF6 and OsTCP21 in Rice (Oryza sativa). PLoS ONE 9(3): e91357.Fang Y, Xie K, Xiong L. Conserved miR164-targeted NAC genes regulate drought resistence in rice. J Exp Bot. 2014;65:2119–35.Goossens A, de la Fuente N, Forment J, Serrano R, Portillo F. Regulation of yeast H+-ATPase by protein kinases belonging to a family dedicated to activation of plasma membrane transporters. Mol Cell Biol. 2000;20:7654–61.Roig C, Fita A, Ríos G, Hammond JP, Nuez F, Picó B. Root transcriptional responses of two melon genotypes with contrasting resistance to Monosporascus cannonballus (Pollack et Uecker) infection. BMC Genomics. 2012;13:601.Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet Journal. 2011;17:10–2.R Core Team 2013. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3–900051–07-0, URL http://www.R-project.org /.Tarazona S, Furió-Tarí P, Turrà D, Di Pietro A, Nueda MJ, Ferrer A, Conesa A. Data quality aware analysis of differential expression in RNA-seq with NOISeq R/bioc package. Nucleic Acids Res. 2015;43:e140.Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.Czimmerer Z, Hulvely J, Simandi Z, Varallyay E, Havelda Z, Szabo E, Balint BL. A versatile method to design stem-loop primer-based quantitative PCR assays for detecting small regulatory RNA molecules. PLoS One. 2013;8(1):e55168.Zhai J, Arikit S, Simon S, Kingham B, Meyers B. Rapid construction of parallel analysis of RNA end (PARE) libraries for Illumina sequencing. Methods. 2014;67:84–90.Pink S, Vogel S. 2014. D3NETWORK: Stata module to create network visualizations using D3.js http://EconPapers.repec.org/RePEc:boc:bocode:s457844 .Csardi G, Nepusz T. The igraph software package for complex network research. Int J Complex Systems. 2006;1695:1–9