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Databases: A Weapon from theĀ Arsenal of Bioinformatics for Plant Abiotic Stress Research

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Recent Approaches in Omics for Plant Resilience to Climate Change

Abstract

Plants are an essential part of every food chain on earth. In addition, the humans utterly rely on plants for their every single need including food, shelter, oils, drugs, dyes, flavors, perfumes, etc. Due to the perpetually increasing population, the burden is increasing at an alarming rate. The whole scenario is worsened by changing climatic conditions, overexploitation of natural resources, and deforestation. Due to the combination of all these factors, there is a serious level of pressure which enforces stress on the plants. As a result, abiotic stresses including flooding, drought, heat shock, cold stress, etc. majority hampers crop productivity. Similar to the overall productivity of crops in the post-genomic era, the rates for various types of sequencing, MS analysis, and metabolite profiling have also fallen down. As a result, several genes, proteins, and metabolites which play role in stress tolerance have been identified and annotated. This flow of information with respect to abiotic stress research has resulted in a number of databases for different omics approaches including genomics, proteomics, miRNAomics, transcriptomics, metabolomics, etc. These various technologies provide a holistic picture of stress responses and hence provide a way to better strategies for the current situation challenges. In this book chapter, we have highlighted various useful databases available to the crop scientists and breeders.

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References

  • Abdurakhmonov IY (2016) Genomics era for plants and crop speciesā€“advances made and needed tasks ahead. In: Plant genomics. InTech, Croatia

    ChapterĀ  Google ScholarĀ 

  • Abola EE, Bernstein FC, Koetzle TF (1984) The protein data bank. In: Neutrons in biology. Springer, Boston, MA, pp 441ā€“441

    ChapterĀ  Google ScholarĀ 

  • Afendi FM, Okada T, Yamazaki M, Hirai-Morita A, Nakamura Y, Nakamura K et al (2011) KNApSAcK family databases: integrated metaboliteā€“plant species databases for multifaceted plant research. Plant Cell Physiol 53:e1

    ArticleĀ  PubMedĀ  CASĀ  Google ScholarĀ 

  • Agrawal GK, Pedreschi R, Barkla BJ, Bindschedler LV, Cramer R, Sarkar A et al (2012) Translational plant proteomics: a perspective. J Proteome 75:4588ā€“4601

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Akiyama K, Chikayama E, Yuasa H, Shimada Y, Tohge T, Shinozaki K et al (2008) PRIMe: a web site that assembles tools for metabolomics and transcriptomics. In Silico Biol 8:339ā€“345

    CASĀ  PubMedĀ  Google ScholarĀ 

  • Alaux M, Rogers J, Letellier T, Flores R, Alfama F, Pommier C et al (2018) Linking the international wheat genome sequencing consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biol 19:111

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Alter S, Bader KC, Spannagl M, Wang Y, Bauer E, Schƶn C-C et al (2015) Drought DB: an expert-curated compilation of plant drought stress genes and their homologs in nine species. Database 2015:bav046. https://doi.org/10.1093/database/bav1046

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Altpeter F, Springer NM, Bartley LE, Blechl AE, Brutnell TP, Citovsky V et al (2016) Advancing crop transformation in the era of genome editing. Plant Cell 28:1510ā€“1520

    CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • AmĆ¢ncio S, GerĆ³s H, Dietz K-J, Blumwald E (2017) The use of systems biology for enhancing crop abiotic stress tolerance. Front Plant Sci

    Google ScholarĀ 

  • Arivaradarajan P, Misra G (2019) Omics approaches, technologies and applications: integrative approaches for understanding OMICS data. Springer, Singapore

    Google ScholarĀ 

  • Atkins P, Bowler I (2016) Food in society: economy, culture, geography. Routledge, London

    Google ScholarĀ 

  • Atkinson NJ, Urwin PE (2012) The interaction of plant biotic and abiotic stresses: from genes to the field. J Exp Bot 63:3523ā€“3543

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Bagati S, Mahajan R, Nazir M, Dar AA, Zargar SM (2018) ā€œOmicsā€: a gateway towards abiotic stress tolerance. In: Abiotic stress-mediated sensing and signaling in plants: an omics perspective. Springer, Singapore, pp 1ā€“45

    Google ScholarĀ 

  • Barlett PF (2016) Agricultural decision making: anthropological contributions to rural development. Academic Press, Cambridge, MA

    Google ScholarĀ 

  • Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C et al (2006) NCBI GEO: mining tens of millions of expression profilesā€”database and tools update. Nucleic Acids Res 35:D760ā€“D765

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Bauer E, Schmutzer T, Barilar I, Mascher M, Gundlach H, Martis MM et al (2017) Towards a whole-genome sequence for rye (Secale cereale L.). Plant J 89:853ā€“869

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Baxevanis AD, Bateman A (2015) The importance of biological databases in biological discovery. Curr Protoc Bioinformatics 50:1.1.1ā€“1.1.8

    ArticleĀ  Google ScholarĀ 

  • Bellard C, Bertelsmeier C, Leadley P, Thuiller W, Courchamp F (2012) Impacts of climate change on the future of biodiversity. Ecol Lett 15:365ā€“377

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL (2004) GenBank: update. Nucleic Acids Res 32:D23ā€“D26

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Bilofsky HS, Burks C, Fickett JW, Goad WB, Lewitter FI, Rindone WP et al (1986) The GenBank genetic sequence databank. Nucleic Acids Res 14:1ā€“4

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Bolser D, Staines DM, Pritchard E, Kersey P (2016) Ensembl plants: integrating tools for visualizing, mining, and analyzing plant genomics data. In: Plant bioinformatics. Springer, New York, NY, pp 115ā€“140

    ChapterĀ  Google ScholarĀ 

  • Bonnet E, He Y, Billiau K, Van de Peer Y (2010) TAPIR, a web server for the prediction of plant microRNA targets, including target mimics. Bioinformatics 26:1566ā€“1568

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Bonthala V, Gajula M (2016) PvTFDB: a Phaseolus vulgaris transcription factors database for expediting functional genomics in legumes. Database 2016:baw114

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Borkotoky S, Saravanan V, Jaiswal A, Das B, Selvaraj S, Murali A et al (2013) The Arabidopsis stress responsive gene database. Int J Plant Genom 2013:949564. https://doi.org/10.1155/2013/949564

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Boutet E, Lieberherr D, Tognolli M, Schneider M, Bairoch A (2007) Uniprotkb/swiss-prot. In: Plant bioinformatics. Springer, New York, NY, pp 89ā€“112

    ChapterĀ  Google ScholarĀ 

  • Bowne J, Bacic A, Tester M, Roessner U (2018) Abiotic stress and metabolomics. Annual Plant Rev 43:61ā€“85

    ArticleĀ  Google ScholarĀ 

  • Brown JW, Echeverria M, Qu L-H, Lowe TM, Bachellerie J-P, HĆ¼ttenhofer A et al (2003) Plant snoRNA database. Nucleic Acids Res 31:432ā€“435

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Brown JW, Shaw PJ, Shaw P, Marshall DF (2005) Arabidopsis nucleolar protein database (AtNoPDB). Nucleic Acids Res 33:D633ā€“D636

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Brun M, Blanc P, Otto H (2016) Global perspective of natural resources. Ciheam. Zero waste in the mediterranean, Natural Resources, Food and Knowledge, Presses de SciencesPo, pp 1ā€“48

    Google ScholarĀ 

  • Burks C (2018) The flow of nucleotide sequence data into data banks: role and impact of large-scale sequencing projects. In: Computers and DNA. Routledge, London, pp 35ā€“45

    ChapterĀ  Google ScholarĀ 

  • Camon E, Barrell D, Lee V, Dimmer E, Apweiler R (2003) The gene ontology annotation (GOA) database-an integrated resource of GO annotations to the UniProt knowledgebase. In Silico Biol 4:5ā€“6

    PubMedĀ  Google ScholarĀ 

  • Chawla K, Barah P, Kuiper M, Bones AM (2011) Systems biology: a promising tool to study abiotic stress responses. In: Tuteja N (ed) Omics and plant abiotic stress tolerance, pp 163ā€“172

    ChapterĀ  Google ScholarĀ 

  • Chen D, Yuan C, Zhang J, Zhang Z, Bai L, Meng Y et al (2011) PlantNATsDB: a comprehensive database of plant natural antisense transcripts. Nucleic Acids Res 40:D1187ā€“D1193

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Chen J, Hu Q, Zhang Y, Lu C, Kuang H (2013) P-MITE: a database for plant miniature inverted-repeat transposable elements. Nucleic Acids Res 42:D1176ā€“D1181

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Chen C, Huang H, Wu CH (2017) Protein bioinformatics databases and resources. In: Protein bioinformatics. Springer, New York, NY, pp 3ā€“39

    ChapterĀ  Google ScholarĀ 

  • Chen F, Dong W, Zhang J, Guo X, Chen J, Wang Z et al (2018) The sequenced angiosperm genomes and genome databases. Front Plant Sci 9:418

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • ChĆ©rel I, Gaillard I (2019) The complex fine-tuning of k+ fluxes in plants in relation to osmotic and ionic abiotic stresses. Int J Mol Sci 20:715

    ArticleĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Chien C-H, Chow C-N, Wu N-Y, Chiang-Hsieh Y-F, Hou P-F, Chang W-C (2015) EXPath: a database of comparative expression analysis inferring metabolic pathways for plants. BMC Genomics 16:S6

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Choudhury FK, Rivero RM, Blumwald E, Mittler R (2017) Reactive oxygen species, abiotic stress and stress combination. Plant J 90:856ā€“867

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Conijn JG, Bindraban PS, Schrƶder JJ, Jongschaap REE (2018) Can our global food system meet food demand within planetary boundaries? Agric Ecosyst Environ 251:244ā€“256

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Consortium U (2014) UniProt: a hub for protein information. Nucleic Acids Res 43:D204ā€“D212

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Cooper L, Meier A, Laporte M-A, Elser JL, Mungall C, Sinn BT et al (2017) The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics. Nucleic Acids Res 46:D1168ā€“D1180

    ArticleĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Cramer GR, Urano K, Delrot S, Pezzotti M, Shinozaki K (2011) Effects of abiotic stress on plants: a systems biology perspective. BMC Plant Biol 11:163

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Cseke LJ, Kirakosyan A, Kaufman PB, Warber S, Duke JA, Brielmann HL (2016) Natural products from plants. CRC Press, Boca Raton, FL

    BookĀ  Google ScholarĀ 

  • Das NN (2019) Relevance of poly-omics in system biology studies of industrial crops. OMICS-Based Approaches in Plant Biotechnology 167:167

    Google ScholarĀ 

  • Davuluri RV, Sun H, Palaniswamy SK, Matthews N, Molina C, Kurtz M et al (2003) AGRIS: Arabidopsis gene regulatory information server, an information resource of Arabidopsis cis-regulatory elements and transcription factors. BMC Bioinformat 4:25

    ArticleĀ  Google ScholarĀ 

  • Debnath M, Pandey M, Bisen P (2011) An omics approach to understand the plant abiotic stress. OMICS 15:739ā€“762

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Degtyarenko K, De Matos P, Ennis M, Hastings J, Zbinden M, McNaught A et al (2007) ChEBI: a database and ontology for chemical entities of biological interest. Nucleic Acids Res 36:D344ā€“D350

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Dereeper A, Bocs S, Rouard M, Guignon V, Ravel S, Tranchant-Dubreuil C et al (2014) The coffee genome hub: a resource for coffee genomes. Nucleic Acids Res 43:D1028ā€“D1035

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Di Silvestre D, Bergamaschi A, Bellini E, Mauri P (2018) Large scale proteomic data and network-based systems biology approaches to explore the plant world. Proteome 6:27

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Doolittle RF (2018) What we have learned and will learn from sequence databases. In: Computers and DNA. Routledge, London, pp 21ā€“31

    ChapterĀ  Google ScholarĀ 

  • dos Reis SP, Marques DN, Barros NLF, Costa CNM, de Souza CRB (2018) Genetically engineered food crops to abiotic stress tolerance. In: Genetically engineered foods. Elsevier, Amsterdam, pp 247ā€“279

    ChapterĀ  Google ScholarĀ 

  • Dunn WB, Ellis DI (2005) Metabolomics: current analytical platforms and methodologies. TrAC Trend Analyt Chem 24:285ā€“294

    ArticleĀ  CASĀ  Google ScholarĀ 

  • El-Metwally S, Ouda OM, Helmy M (2014) First-and next-generations sequencing methods. Springer, New York, NY

    BookĀ  Google ScholarĀ 

  • Fahimirad S, Ghorbanpour M (2019) Omics approaches in developing abiotic stress tolerance in rice (Oryza sativa L.). In: Advances in rice research for abiotic stress tolerance. Elsevier, Amsterdam, pp 767ā€“779

    ChapterĀ  Google ScholarĀ 

  • Fan K, Zhang Q, Liu M, Ma L, Shi Y, Ruan J (2019) Metabolomic and transcriptional analyses reveal the mechanism of C, N allocation from source leaf to flower in tea plant (Camellia sinensis. L). J Plant Physiol 232:200ā€“208

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Fiehn O (2002) Metabolomicsā€”the link between genotypes and phenotypes. In: Functional genomics. Springer, New York, NY, pp 155ā€“171

    ChapterĀ  Google ScholarĀ 

  • Fredslund J (2008) DATFAP: a database of primers and homology alignments for transcription factors from 13 plant species. BMC Genomics 9:140

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Furbank RT, Tester M (2011) Phenomicsā€“technologies to relieve the phenotyping bottleneck. Trends Plant Sci 16:635ā€“644

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Gao J, Agrawal GK, Thelen JJ, Xu D (2008) P3DB: a plant protein phosphorylation database. Nucleic Acids Res 37:D960ā€“D962

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Garnatje T, Canela MƁ, Garcia S, Hidalgo O, Pellicer J, SĆ”nchez-JimĆ©nez I et al (2011) GSAD: a genome size in the Asteraceae database. Cytometry A 79:401ā€“404

    ArticleĀ  PubMedĀ  CASĀ  Google ScholarĀ 

  • Gendler K, Paulsen T, Napoli C (2007) ChromDB: the chromatin database. Nucleic Acids Res 36:D298ā€“D302

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Ghosh A, Mehta A (2017) Concept, development, and application of computational methods for the analysis and integration of omics data. In: Plant bioinformatics. Springer, New York, NY, pp 241ā€“266

    ChapterĀ  Google ScholarĀ 

  • Ghosh D, Xu J (2014) Abiotic stress responses in plant roots: a proteomics perspective. Front Plant Sci 5:6

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Goodstein DM, Shu S, Howson R, Neupane R, Hayes RD, Fazo J etĀ al (2011) Phytozome: a comparative platform for green plant genomics. Nucleic Acids Res 40:D1178ā€“D1186

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Grafton RQ, Daugbjerg C, Qureshi ME (2015) Towards food security by 2050. Food Security 7:179ā€“183

    ArticleĀ  Google ScholarĀ 

  • Grover A, Pareek A, Singla SL, Minhas D, Katiyar S, Ghawana S et al (1998) Engineering crops for tolerance against abiotic stresses through gene manipulation. Curr Sci 75:689ā€“696

    Google ScholarĀ 

  • Gupta B, Sengupta A, Saha J, Gupta K (2013) Plant abiotic stress: ā€˜Omicsā€™ approach. J Plant Biochem Physiol 1:1ā€“3

    CASĀ  Google ScholarĀ 

  • Gurjar AKS, Panwar AS, Gupta R, Mantri SS (2016) PmiRExAt: plant miRNA expression atlas database and web applications. Database 2016:baw060. https://doi.org/10.1093/database/baw1060

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Hamilton JP, Robin Buell C (2012) Advances in plant genome sequencing. Plant J 70:177ā€“190

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Heazlewood JL, Durek P, Hummel J, Selbig J, Weckwerth W, Walther D et al (2007) PhosPhAt: a database of phosphorylation sites in Arabidopsis thaliana and a plant-specific phosphorylation site predictor. Nucleic Acids Res 36:D1015ā€“D1021

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Helmy M, Tomita M, Ishihama Y (2011) OryzaPG-DB: rice proteome database based on shotgun proteogenomics. BMC Plant Biol 11:63

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Helmy M, Crits-Christoph A, Bader GD (2016) Ten simple rules for developing public biological databases. PLoS Comput Biol 12(11):e1005128

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Heyman HM, Dubery IA (2016) The potential of mass spectrometry imaging in plant metabolomics: a review. Phytochem Rev 15:297ā€“316

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Hivrale V, Zheng Y, Puli COR, Jagadeeswaran G, Gowdu K, Kakani VG et al (2016) Characterization of drought-and heat-responsive microRNAs in switchgrass. Plant Sci 242:214ā€“223

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Hong J, Yang L, Zhang D, Shi J (2016) Plant metabolomics: an indispensable system biology tool for plant science. Int J Mol Sci 17:767

    ArticleĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Hooper CM, Castleden IR, Tanz SK, Aryamanesh N, Millar AH (2016) SUBA4: the interactive data analysis Centre for Arabidopsis subcellular protein locations. Nucleic Acids Res 45:D1064ā€“D1074

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Hossain MA, Li Z-G, Hoque TS, Burritt DJ, Fujita M, MunnĆ©-Bosch S (2018) Heat or cold priming-induced cross-tolerance to abiotic stresses in plants: key regulators and possible mechanisms. Protoplasma 255:399ā€“412

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Hu J, Rampitsch C, Bykova NV (2015) Advances in plant proteomics toward improvement of crop productivity and stress resistancex. Front Plant Sci 6:209

    PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Hu H, Scheben A, Edwards D (2018) Advances in integrating genomics and bioinformatics in the plant breeding pipeline. Agriculture 8:75

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Huala E, Dickerman AW, Garcia-Hernandez M, Weems D, Reiser L, LaFond F et al (2001) The Arabidopsis information resource (TAIR): a comprehensive database and web-based information retrieval, analysis, and visualization system for a model plant. Nucleic Acids Res 29:102ā€“105

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Iida K, Seki M, Sakurai T, Satou M, Akiyama K, Toyoda T et al (2005) RARTF: database and tools for complete sets of Arabidopsis transcription factors. DNA Res 12:247ā€“256

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • International Arabidopsis Informatics Consortium, Doherty C, Friesner J, Gregory B, Loraine A, Megraw M et al (2019) Arabidopsis bioinformatics resources: the current state, challenges, and priorities for the future. Plant Direct 3:e00109

    ArticleĀ  Google ScholarĀ 

  • Jain M, Olsen HE, Paten B, Akeson M (2016) The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biol 17:239

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Jin J, Zhang H, Kong L, Gao G, Luo J (2013) PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors. Nucleic Acids Res 42:D1182ā€“D1187

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Johnson C, Bowman L, Adai AT, Vance V, Sundaresan V (2006) CSRDB: a small RNA integrated database and browser resource for cereals. Nucleic Acids Res 35:D829ā€“D833

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Johnson CH, Ivanisevic J, Siuzdak G (2016) Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol 17:451ā€“459

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Jorge TF, Rodrigues JA, Caldana C, Schmidt R, van Dongen JT, Thomas-Oates J etĀ al (2016) Mass spectrometry-based plant metabolomics: metabolite responses to abiotic stress. Mass Spectrom Rev 35:620ā€“649

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Joshi HJ, Hirsch-Hoffmann M, Baerenfaller K, Gruissem W, Baginsky S, Schmidt R et al (2011) MASCP gator: an aggregation portal for the visualization of Arabidopsis proteomics data. Plant Physiol 155:259ā€“270

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Jung S, Jesudurai C, Staton M, Du Z, Ficklin S, Cho I et al (2004) GDR (genome database for Rosaceae): integrated web resources for Rosaceae genomics and genetics research. BMC Bioinformat 5:130

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M (2013) Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res 42:D199ā€“D205

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Kera K, Fine DD, Wherritt DJ, Nagashima Y, Shimada N, Ara T et al (2018) Pathway-specific metabolome analysis with 18O2-labeled Medicago truncatula via a mass spectrometry-based approach. Metabolomics 14:71

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Kersey PJ (2019) Plant genome sequences: past, present, future. Curr Opin Plant Biol 48:1ā€“8

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Kim E, Hwang S, Lee I (2016) SoyNet: a database of co-functional networks for soybean Glycine max. Nucleic Acids Res 45:D1082ā€“D1089

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Kim S, Chen J, Cheng T, Gindulyte A, He J, He S et al (2018) PubChem 2019 update: improved access to chemical data. Nucleic Acids Res 47:D1102ā€“D1109

    ArticleĀ  PubMed CentralĀ  Google ScholarĀ 

  • Kodama Y, Mashima J, Kosuge T, Kaminuma E, Ogasawara O, Okubo K et al (2017) DNA data bank of Japan: 30th anniversary. Nucleic Acids Res 46:D30ā€“D35

    ArticleĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • KosovĆ” K, VĆ­tĆ”mvĆ”s P, PrĆ”Å”il IT, Renaut J (2011) Plant proteome changes under abiotic stressā€”contribution of proteomics studies to understanding plant stress response. J Proteome 74:1301ā€“1322

    ArticleĀ  CASĀ  Google ScholarĀ 

  • KosovĆ” K, VĆ­tĆ”mvĆ”s P, Urban MO, PrĆ”Å”il IT, Renaut J (2018) Plant abiotic stress proteomics: the major factors determining alterations in cellular proteome. Front Plant Sci 9:122

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Kreszies T, Shellakkutti N, Osthoff A, Yu P, Baldauf JA, Zeisler-Diehl VV et al (2019) Osmotic stress enhances suberization of apoplastic barriers in barley seminal roots: analysis of chemical, transcriptomic and physiological responses. New Phytol 221:180ā€“194

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Kudo T, Akiyama K, Kojima M, Makita N, Sakurai T, Sakakibara H (2013) UniVIO: a multiple omics database with hormonome and transcriptome data from rice. Plant Cell Physiol 54:e9ā€“e9

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Kudo T, Terashima S, Takaki Y, Tomita K, Saito M, Kanno M et al (2017) PlantExpress: a database integrating OryzaExpress and ArthaExpress for single-species and cross-species gene expression network analyses with microarray-based transcriptome data. Plant Cell Physiol 58:e1

    ArticleĀ  PubMedĀ  CASĀ  Google ScholarĀ 

  • Kudoh H (2016) Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments. New Phytol 210:399ā€“412

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Kumar S, Shanker A (2018) Bioinformatics resources for the stress biology of plants. In: Biotic and abiotic stress tolerance in plants. Springer, Singapore, pp 367ā€“386

    ChapterĀ  Google ScholarĀ 

  • Kumar SA, Kumari PH, Sundararajan VS, Suravajhala P, Kanagasabai R, Kishor PK (2014) PSPDB: plant stress protein database. Plant Mol Biol Report 32:940ā€“942

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Kumar J, Pratap A, Kumar S (2015) Phenomics in crop plants: trends, options and limitations. Springer, India

    Google ScholarĀ 

  • KĆ¼nne C, Lange M, Funke T, Miehe H, Thiel T, Grosse I et al (2005) CR-EST: a resource for crop ESTs. Nucleic Acids Res 33:D619ā€“D621

    ArticleĀ  PubMedĀ  Google ScholarĀ 

  • Kushwaha UKS, Deo I, Jaiswal JP, Prasad B (2017) Role of bioinformatics in crop improvement. Global J Sci Front Res D 17:1ā€“13

    Google ScholarĀ 

  • Lai K, Lorenc MT, Edwards D (2012) Genomic databases for crop improvement. Agronomy 2:62ā€“73

    ArticleĀ  Google ScholarĀ 

  • Lamesch P, Berardini TZ, Li D, Swarbreck D, Wilks C, Sasidharan R et al (2011) The arabidopsis information resource (TAIR): improved gene annotation and new tools. Nucleic Acids Res 40:D1202ā€“D1210

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Lavarenne J, Guyomarcā€™h S, Sallaud C, Gantet P, Lucas M (2018) The spring of systems biology-driven breeding. Trends Plant Sci 23:706ā€“720

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Lawrence CJ, Dong Q, Polacco ML, Seigfried TE, Brendel V (2004) MaizeGDB, the community database for maize genetics and genomics. Nucleic Acids Res 32:D393ā€“D397

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Lee T-H, Tang H, Wang X, Paterson AH (2012) PGDD: a database of gene and genome duplication in plants. Nucleic Acids Res 41:D1152ā€“D1158

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Lee T, Yang S, Kim E, Ko Y, Hwang S, Shin J etĀ al (2014) AraNet v2: an improved database of co-functional gene networks for the study of Arabidopsis thaliana and 27 other nonmodel plant species. Nucleic Acids Res 43:D996ā€“D1002

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Lee T, Oh T, Yang S, Shin J, Hwang S, Kim CY et al (2015) RiceNet v2: an improved network prioritization server for rice genes. Nucleic Acids Res 43:W122ā€“W127

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Leinonen R, Akhtar R, Birney E, Bower L, Cerdeno-TĆ”rraga A, Cheng Y et al (2010) The European nucleotide archive. Nucleic Acids Res 39:D28ā€“D31

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Leisner CP, Yendrek CR, Ainsworth EA (2017) Physiological and transcriptomic responses in the seed coat of field-grown soybean (Glycine max L. Merr.) to abiotic stress. BMC Plant Biol 17:242. https://doi.org/10.1186/s12870-12017-11188-y

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Letunic I, Bork P (2017) 20 years of the SMART protein domain annotation resource. Nucleic Acids Res 46:D493ā€“D496

    ArticleĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Li J, Dai X, Liu T, Zhao PX (2011) LegumeIP: an integrative database for comparative genomics and transcriptomics of model legumes. Nucleic Acids Res 40:D1221ā€“D1229

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Li M, Xia L, Zhang Y, Niu G, Li M, Wang P et al (2018) Plant editosome database: a curated database of RNA editosome in plants. Nucleic Acids Res 47:D170ā€“D174

    ArticleĀ  PubMed CentralĀ  Google ScholarĀ 

  • Liu Y, Tian T, Zhang K, You Q, Yan H, Zhao N et al (2017) PCSD: a plant chromatin state database. Nucleic Acids Res 46:1157ā€“D1167

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Lo CG, HernĆ”ndez I, Ceci L, Pesole G, Picardi E (2019) RNA editing in plants: a comprehensive survey of bioinformatics tools and databases. Plant Physiol Biochem 137:53ā€“61

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Luan H, Shen H, Pan Y, Guo B, Lv C, Xu R (2018) Elucidating the hypoxic stress response in barley (Hordeum vulgare L.) during waterlogging: a proteomics approach. Sci Rep 8:9655

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • MagaƱa Ugarte R, Escudero A, GavilĆ”n RG (2019) Metabolic and physiological responses of Mediterranean high-mountain and alpine plants to combined abiotic stresses. Physiol Plant

    Google ScholarĀ 

  • MagaƱa UR, Escudero A, GavilĆ”n RG (2019) Metabolic and physiological responses of mediterranean high-mountain and alpine plants to combined abiotic stresses. Physiol Plant 165:403ā€“412

    Google ScholarĀ 

  • Makita Y, Shimada S, Kawashima M, Kondou-Kuriyama T, Toyoda T, Matsui M (2014) MOROKOSHI: transcriptome database in Sorghum bicolor. Plant Cell Physiol 56:e6

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Matsuda F, Hirai MY, Sasaki E, Akiyama K, Yonekura-Sakakibara K, Provart NJ et al (2010) AtMetExpress development: a phytochemical atlas of Arabidopsis development. Plant Physiol 152:566ā€“578

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • McCombie WR, McPherson JD, Mardis ER (2018) Next-generation sequencing technologies. Cold Spring Harb Perspect Med

    Google ScholarĀ 

  • McGlew K, Shaw V, Zhang M, Kim RJ, Yang W, Shorrosh B et al (2015) An annotated database of Arabidopsis mutants of acyl lipid metabolism. Plant Cell Rep 34:519ā€“532

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Members BIG Data Center (2019) Database resources of the BIG data Center in 2019. Nucleic Acids Res 47:D8

    ArticleĀ  Google ScholarĀ 

  • Miettinen K, Inigo S, Kreft L, Pollier J, De Bo C, Botzki A et al (2017) The TriForC database: a comprehensive up-to-date resource of plant triterpene biosynthesis. Nucleic Acids Res 46:D586ā€“D594

    ArticleĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Mihara M, Itoh T, Izawa T (2009) SALAD database: a motif-based database of protein annotations for plant comparative genomics. Nucleic Acids Res 38:D835ā€“D842

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Mir RR, Reynolds M, Pinto F, Khan MA, Bhat MA (2019) High-throughput phenotyping for crop improvement in the genomics era. Plant Sci

    Google ScholarĀ 

  • Mishra NS, Tripathi A, Goswami K, Shukla RN, Vasudevan M, Goswami H (2018) ARMOURā€“A Rice miRNA: mRNA interaction resource. Front Plant Sci 9:602. https://doi.org/10.3389/fpls.2018.00602

    ArticleĀ  Google ScholarĀ 

  • Mittler R (2006) Abiotic stress, the field environment and stress combination. Trends Plant Sci 11:15ā€“19

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Mo Q, Shen R, Guo C, Vannucci M, Chan KS, Hilsenbeck SG (2017) A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data. Biostatistics 19:71ā€“86

    ArticleĀ  PubMed CentralĀ  Google ScholarĀ 

  • Moreno-Risueno MA, Busch W, Benfey PN (2010) Omics meet networksā€”using systems approaches to infer regulatory networks in plants. Curr Opin Plant Biol 13:126ā€“131

    ArticleĀ  PubMedĀ  Google ScholarĀ 

  • Mosa KA, Ismail A, Helmy M (2017) Omics and system biology approaches in plant stress research. In: Plant stress tolerance. Springer, New York, NY, pp 21ā€“34

    ChapterĀ  Google ScholarĀ 

  • Mueller LA, Zhang P, Rhee SY (2003) AraCyc: a biochemical pathway database for Arabidopsis. Plant Physiol 132:453ā€“460

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Mueller LA, Solow TH, Taylor N, Skwarecki B, Buels R, Binns J etĀ al (2005) The SOL genomics network. A comparative resource for Solanaceae biology and beyond. Plant Physiol 138:1310ā€“1317

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Muthuramalingam P, Jeyasri R, Kalaiyarasi D, Pandian S, Krishnan SR, Satish L et al (2019) Emerging advances in computational omics tools for systems analysis of gramineae family grass species and their abiotic stress responsive functions. OMICS-Based Approach Plant Biotechnol 185:185

    Google ScholarĀ 

  • Mutwil M, Klie S, Tohge T, Giorgi FM, Wilkins O, Campbell MM et al (2011) PlaNet: combined sequence and expression comparisons across plant networks derived from seven species. Plant Cell 23:895ā€“910

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Naithani S, Preece J, D'Eustachio P, Gupta P, Amarasinghe V, Dharmawardhana PD et al (2016) Plant Reactome: a resource for plant pathways and comparative analysis. Nucleic Acids Res 45:D1029ā€“D1039

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Newton A, Lyon G, Marshall B (2002) DRASTIC: a database resource for analysis of signal transduction in cells. BSPP Newslett 42:36ā€“37

    Google ScholarĀ 

  • Obayashi T, Kinoshita K, Nakai K, Shibaoka M, Hayashi S, Saeki M et al (2006) ATTED-II: a database of co-expressed genes and cis elements for identifying co-regulated gene groups in Arabidopsis. Nucleic Acids Res 35:D863ā€“D869

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Oldeman LR, Hakkeling R, Sombroek WG (2017) World map of the status of human-induced soil degradation: an explanatory note. International Soil Reference and Information Centre

    Google ScholarĀ 

  • Orchard S, Kerrien S, Abbani S, Aranda B, Bhate J, Bidwell S et al (2012) Protein interaction data curation: the international molecular exchange (IMEx) consortium. Nat Methods 9:345ā€“350

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Pandey P, Irulappan V, Bagavathiannan MV, Senthil-Kumar M (2017) Impact of combined abiotic and biotic stresses on plant growth and avenues for crop improvement by exploiting physio-morphological traits. Front Plant Sci 8:537

    PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Parida AK, Panda A, Rangani J (2018) Metabolomics-guided elucidation of abiotic stress tolerance mechanisms in plants. In: Ahmad P, Ahanger MA, Singh VP, Tripathi DK, Alam P, Alyemeni MN (eds) Plant metabolites and regulation under environmental stress. Elsevier, Amsterdam, pp 89ā€“131

    ChapterĀ  Google ScholarĀ 

  • Pence HE, Williams A (2010) ChemSpider: an online chemical information resource. J Chem Educ 87:1123ā€“1124

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Picardi E, Regina TMR, Brennicke A, Quagliariello C (2006) REDIdb: the RNA editing database. Nucleic Acids Res 35:D173ā€“D177

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Pilcher JM (2017) Food in world history. Routledge, London

    BookĀ  Google ScholarĀ 

  • Popescu GV, Noutsos C, Popescu SC (2016) Big data in plant science: resources and data mining tools for plant genomics and proteomics. In: Data mining techniques for the life sciences. Springer, New York, NY, pp 533ā€“547

    ChapterĀ  Google ScholarĀ 

  • Prabha R, Ghosh I, Singh DP (2011) Plant stress gene database: a collection of plant genes responding to stress condition. ARPN J Sci Technol 1:28ā€“31

    Google ScholarĀ 

  • Proost S, Van Bel M, Sterck L, Billiau K, Van Parys T, Van de Peer Y et al (2009) PLAZA: a comparative genomics resource to study gene and genome evolution in plants. Plant Cell 21:3718ā€“3731

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Pruitt KD, Tatusova T, Maglott DR (2005) NCBI reference sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res 33:D501ā€“D504

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Ramegowda V, Senthil-Kumar M (2015) The interactive effects of simultaneous biotic and abiotic stresses on plants: mechanistic understanding from drought and pathogen combination. J Plant Physiol 176:47ā€“54

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Rao VS, Das SK, Rao VJ, Srinubabu G (2008) Recent developments in life sciences research: role of bioinformatics. Afr J Biotechnol 7:495ā€“503

    CASĀ  Google ScholarĀ 

  • Raubenheimer D, Simpson SJ, Mayntz D (2009) Nutrition, ecology and nutritional ecology: toward an integrated framework. Funct Ecol 23:4ā€“16

    ArticleĀ  Google ScholarĀ 

  • Reuter JA, Spacek DV, Snyder MP (2015) High-throughput sequencing technologies. Mol Cell 58:586ā€“597

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • RiaƱo-PachĆ³n DM, Ruzicic S, Dreyer I, Mueller-Roeber B (2007) PlnTFDB: an integrative plant transcription factor database. BMC Bioinformat 8:42

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Romeuf I, Tessier D, Dardevet M, Branlard G, Charmet G, Ravel C (2010) wDBTF: an integrated database resource for studying wheat transcription factor families. BMC Genomics 11:185

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Ruiz M, Rouard M, Raboin LM, Lartaud M, Lagoda P, Courtois B (2004) TropGENE-DB, a multi-tropical crop information system. Nucleic Acids Res 32:D364ā€“D367

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Saeed M (2018) Abiotic stress tolerance in Rice (Oryza sativa L.): a genomics perspective of salinity tolerance. In: Rice crop-current developments. IntechOpen, Croatia

    Google ScholarĀ 

  • Sakurai T, Satou M, Akiyama K, Iida K, Seki M, Kuromori T et al (2005) RARGE: a large-scale database of RIKEN Arabidopsis resources ranging from transcriptome to phenome. Nucleic Acids Res 33:D647ā€“D650

    ArticleĀ  PubMedĀ  Google ScholarĀ 

  • Sakurai N, Ara T, Ogata Y, Sano R, Ohno T, Sugiyama K et al (2010) KaPPA-View4: a metabolic pathway database for representation and analysis of correlation networks of gene co-expression and metabolite co-accumulation and omics data. Nucleic Acids Res 39:D677ā€“D684

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Salgotra R, Gupta B, Stewart C (2014) From genomics to functional markers in the era of next-generation sequencing. Biotechnol Lett 36:417ā€“426

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Sandelin A, Alkema W, Engstrƶm P, Wasserman WW, Lenhard B (2004) JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res 32:D91ā€“D94

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Sato Y, Antonio BA, Namiki N, Takehisa H, Minami H, Kamatsuki K et al (2010) RiceXPro: a platform for monitoring gene expression in japonica rice grown under natural field conditions. Nucleic Acids Res 39:D1141ā€“D1148

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Sato Y, Namiki N, Takehisa H, Kamatsuki K, Minami H, Ikawa H et al (2012) RiceFREND: a platform for retrieving coexpressed gene networks in rice. Nucleic Acids Res 41:D1214ā€“D1221

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Schaeffer ML, Harper LC, Gardiner JM, Andorf CM, Campbell DA, Cannon EK, Sen TZ, Lawrence CJ (2011) MaizeGDB: curation and outreach go hand-in-hand. Database, 2011

    Google ScholarĀ 

  • Scheben A, Batley J, Edwards D (2018) Revolution in genotyping platforms for crop improvement. Plant Genet Molecul Biol:37ā€“52

    Google ScholarĀ 

  • Schilling CH, Edwards JS, Palsson BO (1999) Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol Prog 15:288ā€“295

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Schmitt T, Ogris C, Sonnhammer EL (2013) FunCoup 3.0: database of genome-wide functional coupling networks. Nucleic Acids Res 42:D380ā€“D388

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Seren Ɯ, Grimm D, Fitz J, Weigel D, Nordborg M, Borgwardt K et al (2016) AraPheno: a public database for Arabidopsis thaliana phenotypes. Nucleic Acids Res:D1054ā€“D1059

    Google ScholarĀ 

  • Shameer K, Ambika S, Varghese SM, Karaba N, Udayakumar M, Sowdhamini R (2009) STIFDBā€”Arabidopsis stress responsive transcription factor dataBase. Int J Plant Genomics 2009:583429

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Shang Y, Huang S (2019) Multi-omics data-driven investigations of metabolic diversity of plant triterpenoids. Plant J 97:101ā€“111

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Sharma N, Mittal D, Mishra NS (2017) Micro-regulators of hormones and stress. Mechanism of plant hormone signaling under. Stress 2:319ā€“351

    Google ScholarĀ 

  • Shen L, Gong J, Caldo RA, Nettleton D, Cook D, Wise RP et al (2005) BarleyBaseā€”an expression profiling database for plant genomics. Nucleic Acids Res 33:D614ā€“D618

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Shen W, Li H, Teng R, Wang Y, Wang W, Zhuang J (2018) Genomic and transcriptomic analyses of HD-zip family transcription factors and their responses to abiotic stress in tea plant (Camellia sinensis). Genomics. https://doi.org/10.1016/j.ygeno.2018.07.009

  • Singh A, Sharma AK, Singh NK, Sharma TR (2017) PpTFDB: a pigeonpea transcription factor database for exploring functional genomics in legumes. PLoS One 12:e0179736

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Singh B, Mishra S, Bohra A, Joshi R, Siddique KH (2018a) Crop phenomics for abiotic stress tolerance in crop plants. In: Biochemical, physiological and molecular avenues for combating abiotic stress tolerance in plants. Elsevier, Amsterdam, pp 277ā€“296

    ChapterĀ  Google ScholarĀ 

  • Singh RK, Lee J-K, Selvaraj C, Singh R, Li J, Kim S-Y et al (2018b) Protein engineering approaches in the post-genomic era. Curr Protein Pept Sci 19:5ā€“15

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Smalter HA, Shan Y, Lushington G, Visvanathan M (2013) An overview of computational life science databases & exchange formats of relevance to chemical biology research. Combinat Chem High Throughp Screen 16:189ā€“198

    ArticleĀ  Google ScholarĀ 

  • Spannagl M, Nussbaumer T, Bader KC, Martis MM, Seidel M, Kugler KG et al (2015) PGSB PlantsDB: updates to the database framework for comparative plant genome research. Nucleic Acids Res 44:D1141ā€“D1147

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Speed D, Balding DJ (2015) Relatedness in the post-genomic era: is it still useful? Nat Rev Genet 16:33ā€“44

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Stein LD (2003) Integrating biological databases. Nat Rev Genet 4:337

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Stone SL (2019) Role of the ubiquitin proteasome system in plant response to abiotic stress. In: International review of cell and molecular biology. Elsevier, Amsterdam, pp 65ā€“110

    Google ScholarĀ 

  • Sun Q, Zybailov B, Majeran W, Friso G, Olinares PDB, van Wijk KJ (2008) PPDB, the plant proteomics database at Cornell. Nucleic Acids Res 37:D969ā€“D974

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Szcześniak MW, Deorowicz S, Gapski J, Kaczyński Ł, Makałowska I (2011) miRNEST database: an integrative approach in microRNA search and annotation. Nucleic Acids Res 40:D198ā€“D204

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Szklarczyk D, Jensen LJ (2015) Protein-protein interaction databases. In: Protein-protein interactions. Springer, New York, NY, pp 39ā€“56

    Google ScholarĀ 

  • Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J etĀ al (2014) STRING v10: proteinā€“protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447ā€“D452

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Tardieu F, Tuberosa R (2010) Dissection and modelling of abiotic stress tolerance in plants. Curr Opin Plant Biol 13:206ā€“212

    ArticleĀ  PubMedĀ  Google ScholarĀ 

  • Tateno Y, Gojobori T (1997) DNA data Bank of Japan in the age of information biology. Nucleic Acids Res 25:14ā€“17

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Tello-Ruiz MK, Naithani S, Stein JC, Gupta P, Campbell M, Olson A et al (2017) Gramene 2018: unifying comparative genomics and pathway resources for plant research. Nucleic Acids Res 46:D1181ā€“D1189

    ArticleĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Tsesmetzis N, Couchman M, Higgins J, Smith A, Doonan JH, Seifert GJ et al (2008) Arabidopsis reactome: a foundation knowledgebase for plant systems biology. Plant Cell 20:1426ā€“1436

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Tyanova S, Temu T, Cox J (2016) The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc 11:2301

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Udayakumar M, Chandar DP, Arun N, Mathangi J, Hemavathi K, Seenivasagam R (2012) PMDB: plant Metabolome databaseā€”a metabolomic approach. Med Chem Res 21:47ā€“52

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Upadhyay J, Joshi R, Singh B, Bohra A, Vijayan R, Bhatt M et al (2017) Application of bioinformatics in understanding of plant stress tolerance. In: Plant bioinformatics. Springer, Cham, pp 347ā€“374

    ChapterĀ  Google ScholarĀ 

  • Urano K, Kurihara Y, Seki M, Shinozaki K (2010) ā€˜Omicsā€™ analyses of regulatory networks in plant abiotic stress responses. Curr Opin Plant Biol 13:132ā€“138

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Valentine AJ, Benedito VA, Kang Y (2011) Legume nitrogen fixation and soil abiotic stress: from physiology to genomics and beyond. Ann Plant Rev 43:207ā€“248

    Google ScholarĀ 

  • Van Wyk B-E, Wink M (2017) Medicinal plants of the world. CABI, Wallingford

    BookĀ  Google ScholarĀ 

  • Vassilev D, Nenov A, Atanassov A, Dimov G, Getov L (2006) Application of bioinformatics in fruit plant breeding. J Fruit Ornament Plant Res 14:145

    CASĀ  Google ScholarĀ 

  • Vaughan MM, Block A, Christensen SA, Allen LH, Schmelz EA (2018) The effects of climate change associated abiotic stresses on maize phytochemical defenses. Phytochem Rev 17:37ā€“49

    ArticleĀ  CASĀ  Google ScholarĀ 

  • VĆ­t P, Krak K, TrĆ”vnƭček P, Douda J, Lomonosova MN, MandĆ”k B (2016) Genome size stability across eurasian chenopodium species (Amaranthaceae). Bot J Linn Soc 182:637ā€“649

    ArticleĀ  Google ScholarĀ 

  • VranovĆ” E, Hirsch-Hoffmann M, Gruissem W (2011) AtIPD: a curated database of Arabidopsis isoprenoid pathway models and genes for isoprenoid network analysis. Plant Physiol 156:1655ā€“1660

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Wang Y, You FM, Lazo GR, Luo M-C, Thilmony R, Gordon S et al (2012) PIECE: a database for plant gene structure comparison and evolution. Nucleic Acids Res 41:D1159ā€“D1166

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Wang P, Su L, Gao H, Jiang X, Wu X, Li Y et al (2018) Genome-wide characterization of bHLH genes in grape and analysis of their potential relevance to abiotic stress tolerance and secondary metabolite biosynthesis. Front Plant Sci 9:64

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Wani SH (2018) Biochemical, physiological and molecular avenues for combating abiotic stress in plants. Academic Press, Cambridge, MA

    Google ScholarĀ 

  • Ware D, Jaiswal P, Ni J, Pan X, Chang K, Clark K et al (2002) Gramene: a resource for comparative grass genomics. Nucleic Acids Res 30:103ā€“105

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Weckwerth W (2003) Metabolomics in systems biology. Annu Rev Plant Biol 54:669ā€“689

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Winter G, Krƶmer JO (2013) Fluxomicsā€“connecting ā€˜omics analysis and phenotypes. Environ Microbiol 15:1901ā€“1916

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Wise R, Caldo R, Hong L, Wu S, Cannon E, Dickerson J (2006) BarleyBase/PLEXdb: a unifited expression prolfiling database for plants and plant pathogens. Method Molecul Biol 406:347ā€“363

    Google ScholarĀ 

  • Wu H-J, Ma Y-K, Chen T, Wang M, Wang X-J (2012) PsRobot: a web-based plant small RNA meta-analysis toolbox. Nucleic Acids Res 40:W22ā€“W28

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Yi X, Zhang Z, Ling Y, Xu W, Su Z (2014) PNRD: a plant non-coding RNA database. Nucleic Acids Res 43:D982ā€“D989

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Yilmaz A, Nishiyama MY, Fuentes BG, Souza GM, Janies D, Gray J etĀ al (2009) GRASSIUS: a platform for comparative regulatory genomics across the grasses. Plant Physiol 149:171ā€“180

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Yoshida T, Mogami J, Yamaguchi-Shinozaki K (2015) Omics approaches toward defining the comprehensive abscisic acid signaling network in plants. Plant Cell Physiol 56:1043ā€“1052

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Yu J, Jung S, Cheng C-H, Ficklin SP, Lee T, Zheng P et al (2013) CottonGen: a genomics, genetics and breeding database for cotton research. Nucleic Acids Res 42:D1229ā€“D1236

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Yuan C, Meng X, Li X, Illing N, Ingle RA, Wang J etĀ al (2016) PceRBase: a database of plant competing endogenous RNA. Nucleic Acids Res 45:D1009ā€“D1014

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Yura K, Sulaiman S, Hatta Y, Shionyu M, Go M (2009) RESOPS: a database for analyzing the correspondence of RNA editing sites to protein three-dimensional structures. Plant Cell Physiol 50:1865ā€“1873

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Zandalinas SI, Mittler R, BalfagĆ³n D, Arbona V, GĆ³mez-Cadenas A (2018) Plant adaptations to the combination of drought and high temperatures. Physiol Plant 162:2ā€“12

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Zargar SM, Rai V (2017) Plant molecular breeding: way forward through next-generation sequencing. In: Plant OMICS and crop breeding. Apple Academic Press, Ontario, pp 226ā€“259

    ChapterĀ  Google ScholarĀ 

  • Zhang B (2015) MicroRNA: a new target for improving plant tolerance to abiotic stress. J Exp Bot 66:1749ā€“1761

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Zhang Z, Yu J, Li D, Zhang Z, Liu F, Zhou X et al (2009) PMRD: plant microRNA database. Nucleic Acids Res 38:D806ā€“D813

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

  • Zhang S, Yue Y, Sheng L, Wu Y, Fan G, Li A et al (2013) PASmiR: a literature-curated database for miRNA molecular regulation in plant response to abiotic stress. BMC Plant Biol 13:33

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Zhang L, Li X, Ma B, Gao Q, Du H, Han Y et al (2017a) The tartary buckwheat genome provides insights into rutin biosynthesis and abiotic stress tolerance. Mol Plant 10:1224ā€“1237

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Zhang P, Meng X, Chen H, Liu Y, Xue J, Zhou Y et al (2017b) PlantCircNet: a database for plant circRNAā€“miRNAā€“mRNA regulatory networks. Database 2017:bax089. https://doi.org/10.1093/database/bax1089

    ArticleĀ  PubMed CentralĀ  PubMedĀ  Google ScholarĀ 

  • Zhang X, Xu Y, Huang B (2018a) Lipidomic reprogramming associated with drought stress priming-enhanced heat tolerance in tall fescue (Festuca arundinacea). Plant Cell Environ. https://doi.org/10.1111/pce.13405

    ArticleĀ  CASĀ  Google ScholarĀ 

  • Zhang X, Yao C, Fu S, Xuan H, Wen S, Liu C et al (2018b) Stress2TF: a manually curated database of TF regulation in plant response to stress. Gene 638:36ā€“40

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  • Zheng Y, Wu S, Bai Y, Sun H, Jiao C, Guo S et al (2018) Cucurbit genomics database (CuGenDB): a central portal for comparative and functional genomics of cucurbit crops. Nucleic Acids Res 47:D1128ā€“D1136

    ArticleĀ  PubMed CentralĀ  Google ScholarĀ 

  • Zhu J-K (2016) Abiotic stress signaling and responses in plants. Cell 167:313ā€“324

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Zielezinski A, Dolata J, Alaba S, Kruszka K, Pacak A, Swida-Barteczka A et al (2015) mirEX 2.0-an integrated environment for expression profiling of plant microRNAs. BMC Plant Biol 15:144

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  • Zou D, Sun S, Li R, Liu J, Zhang J, Zhang Z (2014) MethBank: a database integrating next-generation sequencing single-base-resolution DNA methylation programming data. Nucleic Acids Res 43:D54ā€“D58

    ArticleĀ  PubMedĀ  PubMed CentralĀ  CASĀ  Google ScholarĀ 

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Anamika, Mehta, S., Singh, B., Patra, A., Islam, M.A. (2019). Databases: A Weapon from theĀ Arsenal of Bioinformatics for Plant Abiotic Stress Research. In: Wani, S. (eds) Recent Approaches in Omics for Plant Resilience to Climate Change. Springer, Cham. https://doi.org/10.1007/978-3-030-21687-0_7

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