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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abdurakhmonov IY (2016) Genomics era for plants and crop speciesāadvances made and needed tasks ahead. In: Plant genomics. InTech, Croatia
Abola EE, Bernstein FC, Koetzle TF (1984) The protein data bank. In: Neutrons in biology. Springer, Boston, MA, pp 441ā441
Afendi FM, Okada T, Yamazaki M, Hirai-Morita A, Nakamura Y, Nakamura K et al (2011) KNApSAcK family databases: integrated metaboliteāplant species databases for multifaceted plant research. Plant Cell Physiol 53:e1
Agrawal GK, Pedreschi R, Barkla BJ, Bindschedler LV, Cramer R, Sarkar A et al (2012) Translational plant proteomics: a perspective. J Proteome 75:4588ā4601
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 8:339ā345
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
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
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 28:1510ā1520
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
Arivaradarajan P, Misra G (2019) Omics approaches, technologies and applications: integrative approaches for understanding OMICS data. Springer, Singapore
Atkins P, Bowler I (2016) Food in society: economy, culture, geography. Routledge, London
Atkinson NJ, Urwin PE (2012) The interaction of plant biotic and abiotic stresses: from genes to the field. J Exp Bot 63:3523ā3543
Bagati S, Mahajan R, Nazir M, Dar AA, Zargar SM (2018) āOmicsā: a gateway towards abiotic stress tolerance. In: Abiotic stress-mediated sensing and signaling in plants: an omics perspective. Springer, Singapore, pp 1ā45
Barlett PF (2016) Agricultural decision making: anthropological contributions to rural development. Academic Press, Cambridge, MA
Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C et al (2006) NCBI GEO: mining tens of millions of expression profilesādatabase and tools update. Nucleic Acids Res 35:D760āD765
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 89:853ā869
Baxevanis AD, Bateman A (2015) The importance of biological databases in biological discovery. Curr Protoc Bioinformatics 50:1.1.1ā1.1.8
Bellard C, Bertelsmeier C, Leadley P, Thuiller W, Courchamp F (2012) Impacts of climate change on the future of biodiversity. Ecol Lett 15:365ā377
Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL (2004) GenBank: update. Nucleic Acids Res 32:D23āD26
Bilofsky HS, Burks C, Fickett JW, Goad WB, Lewitter FI, Rindone WP et al (1986) The GenBank genetic sequence databank. Nucleic Acids Res 14:1ā4
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 115ā140
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 26:1566ā1568
Bonthala V, Gajula M (2016) PvTFDB: a Phaseolus vulgaris transcription factors database for expediting functional genomics in legumes. Database 2016:baw114
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
Boutet E, Lieberherr D, Tognolli M, Schneider M, Bairoch A (2007) Uniprotkb/swiss-prot. In: Plant bioinformatics. Springer, New York, NY, pp 89ā112
Bowne J, Bacic A, Tester M, Roessner U (2018) Abiotic stress and metabolomics. Annual Plant Rev 43:61ā85
Brown JW, Echeverria M, Qu L-H, Lowe TM, Bachellerie J-P, HĆ¼ttenhofer A et al (2003) Plant snoRNA database. Nucleic Acids Res 31:432ā435
Brown JW, Shaw PJ, Shaw P, Marshall DF (2005) Arabidopsis nucleolar protein database (AtNoPDB). Nucleic Acids Res 33:D633āD636
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 1ā48
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 35ā45
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 4:5ā6
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 163ā172
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:D1187āD1193
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:D1176āD1181
Chen C, Huang H, Wu CH (2017) Protein bioinformatics databases and resources. In: Protein bioinformatics. Springer, New York, NY, pp 3ā39
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
ChƩrel 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
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
Choudhury FK, Rivero RM, Blumwald E, Mittler R (2017) Reactive oxygen species, abiotic stress and stress combination. Plant J 90:856ā867
Conijn JG, Bindraban PS, Schrƶder JJ, Jongschaap REE (2018) Can our global food system meet food demand within planetary boundaries? Agric Ecosyst Environ 251:244ā256
Consortium U (2014) UniProt: a hub for protein information. Nucleic Acids Res 43:D204āD212
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:D1168āD1180
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
Cseke LJ, Kirakosyan A, Kaufman PB, Warber S, Duke JA, Brielmann HL (2016) Natural products from plants. CRC Press, Boca Raton, FL
Das NN (2019) Relevance of poly-omics in system biology studies of industrial crops. OMICS-Based Approaches in Plant Biotechnology 167:167
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
Debnath M, Pandey M, Bisen P (2011) An omics approach to understand the plant abiotic stress. OMICS 15:739ā762
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:D344āD350
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:D1028āD1035
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
Doolittle RF (2018) What we have learned and will learn from sequence databases. In: Computers and DNA. Routledge, London, pp 21ā31
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 247ā279
Dunn WB, Ellis DI (2005) Metabolomics: current analytical platforms and methodologies. TrAC Trend Analyt Chem 24:285ā294
El-Metwally S, Ouda OM, Helmy M (2014) First-and next-generations sequencing methods. Springer, New York, NY
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 767ā779
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 232:200ā208
Fiehn O (2002) Metabolomicsāthe link between genotypes and phenotypes. In: Functional genomics. Springer, New York, NY, pp 155ā171
Fredslund J (2008) DATFAP: a database of primers and homology alignments for transcription factors from 13 plant species. BMC Genomics 9:140
Furbank RT, Tester M (2011) Phenomicsātechnologies to relieve the phenotyping bottleneck. Trends Plant Sci 16:635ā644
Gao J, Agrawal GK, Thelen JJ, Xu D (2008) P3DB: a plant protein phosphorylation database. Nucleic Acids Res 37:D960āD962
Garnatje T, Canela MĆ, Garcia S, Hidalgo O, Pellicer J, SĆ”nchez-JimĆ©nez I et al (2011) GSAD: a genome size in the Asteraceae database. Cytometry A 79:401ā404
Gendler K, Paulsen T, Napoli C (2007) ChromDB: the chromatin database. Nucleic Acids Res 36:D298āD302
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 241ā266
Ghosh D, Xu J (2014) Abiotic stress responses in plant roots: a proteomics perspective. Front Plant Sci 5:6
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:D1178āD1186
Grafton RQ, Daugbjerg C, Qureshi ME (2015) Towards food security by 2050. Food Security 7:179ā183
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 75:689ā696
Gupta B, Sengupta A, Saha J, Gupta K (2013) Plant abiotic stress: āOmicsā approach. J Plant Biochem Physiol 1:1ā3
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
Hamilton JP, Robin Buell C (2012) Advances in plant genome sequencing. Plant J 70:177ā190
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:D1015āD1021
Helmy M, Tomita M, Ishihama Y (2011) OryzaPG-DB: rice proteome database based on shotgun proteogenomics. BMC Plant Biol 11:63
Helmy M, Crits-Christoph A, Bader GD (2016) Ten simple rules for developing public biological databases. PLoS Comput Biol 12(11):e1005128
Heyman HM, Dubery IA (2016) The potential of mass spectrometry imaging in plant metabolomics: a review. Phytochem Rev 15:297ā316
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 242:214ā223
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
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:D1064āD1074
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 255:399ā412
Hu J, Rampitsch C, Bykova NV (2015) Advances in plant proteomics toward improvement of crop productivity and stress resistancex. Front Plant Sci 6:209
Hu H, Scheben A, Edwards D (2018) Advances in integrating genomics and bioinformatics in the plant breeding pipeline. Agriculture 8:75
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 29:102ā105
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 12:247ā256
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
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
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:D1182āD1187
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:D829āD833
Johnson CH, Ivanisevic J, Siuzdak G (2016) Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol 17:451ā459
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 35:620ā649
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 155:259ā270
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
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:D199āD205
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
Kersey PJ (2019) Plant genome sequences: past, present, future. Curr Opin Plant Biol 48:1ā8
Kim E, Hwang S, Lee I (2016) SoyNet: a database of co-functional networks for soybean Glycine max. Nucleic Acids Res 45:D1082āD1089
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:D1102āD1109
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:D30āD35
KosovĆ” K, VĆtĆ”mvĆ”s P, PrĆ”Å”il IT, Renaut J (2011) Plant proteome changes under abiotic stressācontribution of proteomics studies to understanding plant stress response. J Proteome 74:1301ā1322
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
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 221:180ā194
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:e9āe9
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
Kudoh H (2016) Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments. New Phytol 210:399ā412
Kumar S, Shanker A (2018) Bioinformatics resources for the stress biology of plants. In: Biotic and abiotic stress tolerance in plants. Springer, Singapore, pp 367ā386
Kumar SA, Kumari PH, Sundararajan VS, Suravajhala P, Kanagasabai R, Kishor PK (2014) PSPDB: plant stress protein database. Plant Mol Biol Report 32:940ā942
Kumar J, Pratap A, Kumar S (2015) Phenomics in crop plants: trends, options and limitations. Springer, India
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:D619āD621
Kushwaha UKS, Deo I, Jaiswal JP, Prasad B (2017) Role of bioinformatics in crop improvement. Global J Sci Front Res D 17:1ā13
Lai K, Lorenc MT, Edwards D (2012) Genomic databases for crop improvement. Agronomy 2:62ā73
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:D1202āD1210
Lavarenne J, Guyomarcāh S, Sallaud C, Gantet P, Lucas M (2018) The spring of systems biology-driven breeding. Trends Plant Sci 23:706ā720
Lawrence CJ, Dong Q, Polacco ML, Seigfried TE, Brendel V (2004) MaizeGDB, the community database for maize genetics and genomics. Nucleic Acids Res 32:D393āD397
Lee T-H, Tang H, Wang X, Paterson AH (2012) PGDD: a database of gene and genome duplication in plants. Nucleic Acids Res 41:D1152āD1158
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:D996āD1002
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:W122āW127
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:D28āD31
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
Letunic I, Bork P (2017) 20 years of the SMART protein domain annotation resource. Nucleic Acids Res 46:D493āD496
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:D1221āD1229
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:D170āD174
Liu Y, Tian T, Zhang K, You Q, Yan H, Zhao N et al (2017) PCSD: a plant chromatin state database. Nucleic Acids Res 46:1157āD1167
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 137:53ā61
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
MagaƱa Ugarte R, Escudero A, GavilƔn RG (2019) Metabolic and physiological responses of Mediterranean high-mountain and alpine plants to combined abiotic stresses. Physiol Plant
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 165:403ā412
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
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 152:566ā578
McCombie WR, McPherson JD, Mardis ER (2018) Next-generation sequencing technologies. Cold Spring Harb Perspect Med
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 34:519ā532
Members BIG Data Center (2019) Database resources of the BIG data Center in 2019. Nucleic Acids Res 47:D8
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:D586āD594
Mihara M, Itoh T, Izawa T (2009) SALAD database: a motif-based database of protein annotations for plant comparative genomics. Nucleic Acids Res 38:D835āD842
Mir RR, Reynolds M, Pinto F, Khan MA, Bhat MA (2019) High-throughput phenotyping for crop improvement in the genomics era. Plant Sci
Mishra NS, Tripathi A, Goswami K, Shukla RN, Vasudevan M, Goswami H (2018) ARMOURāA Rice miRNA: mRNA interaction resource. Front Plant Sci 9:602. https://doi.org/10.3389/fpls.2018.00602
Mittler R (2006) Abiotic stress, the field environment and stress combination. Trends Plant Sci 11:15ā19
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 19:71ā86
Moreno-Risueno MA, Busch W, Benfey PN (2010) Omics meet networksāusing systems approaches to infer regulatory networks in plants. Curr Opin Plant Biol 13:126ā131
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 21ā34
Mueller LA, Zhang P, Rhee SY (2003) AraCyc: a biochemical pathway database for Arabidopsis. Plant Physiol 132:453ā460
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 138:1310ā1317
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
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 23:895ā910
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:D1029āD1039
Newton A, Lyon G, Marshall B (2002) DRASTIC: a database resource for analysis of signal transduction in cells. BSPP Newslett 42:36ā37
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:D863āD869
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
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 9:345ā350
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
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 89ā131
Pence HE, Williams A (2010) ChemSpider: an online chemical information resource. J Chem Educ 87:1123ā1124
Picardi E, Regina TMR, Brennicke A, Quagliariello C (2006) REDIdb: the RNA editing database. Nucleic Acids Res 35:D173āD177
Pilcher JM (2017) Food in world history. Routledge, London
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 533ā547
Prabha R, Ghosh I, Singh DP (2011) Plant stress gene database: a collection of plant genes responding to stress condition. ARPN J Sci Technol 1:28ā31
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 21:3718ā3731
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:D501āD504
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 176:47ā54
Rao VS, Das SK, Rao VJ, Srinubabu G (2008) Recent developments in life sciences research: role of bioinformatics. Afr J Biotechnol 7:495ā503
Raubenheimer D, Simpson SJ, Mayntz D (2009) Nutrition, ecology and nutritional ecology: toward an integrated framework. Funct Ecol 23:4ā16
Reuter JA, Spacek DV, Snyder MP (2015) High-throughput sequencing technologies. Mol Cell 58:586ā597
RiaƱo-PachĆ³n DM, Ruzicic S, Dreyer I, Mueller-Roeber B (2007) PlnTFDB: an integrative plant transcription factor database. BMC Bioinformat 8:42
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
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:D364āD367
Saeed M (2018) Abiotic stress tolerance in Rice (Oryza sativa L.): a genomics perspective of salinity tolerance. In: Rice crop-current developments. IntechOpen, Croatia
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:D647āD650
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:D677āD684
Salgotra R, Gupta B, Stewart C (2014) From genomics to functional markers in the era of next-generation sequencing. Biotechnol Lett 36:417ā426
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:D91āD94
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:D1141āD1148
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:D1214āD1221
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
Scheben A, Batley J, Edwards D (2018) Revolution in genotyping platforms for crop improvement. Plant Genet Molecul Biol:37ā52
Schilling CH, Edwards JS, Palsson BO (1999) Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol Prog 15:288ā295
Schmitt T, Ogris C, Sonnhammer EL (2013) FunCoup 3.0: database of genome-wide functional coupling networks. Nucleic Acids Res 42:D380āD388
Seren Ć, Grimm D, Fitz J, Weigel D, Nordborg M, Borgwardt K et al (2016) AraPheno: a public database for Arabidopsis thaliana phenotypes. Nucleic Acids Res:D1054āD1059
Shameer K, Ambika S, Varghese SM, Karaba N, Udayakumar M, Sowdhamini R (2009) STIFDBāArabidopsis stress responsive transcription factor dataBase. Int J Plant Genomics 2009:583429
Shang Y, Huang S (2019) Multi-omics data-driven investigations of metabolic diversity of plant triterpenoids. Plant J 97:101ā111
Sharma N, Mittal D, Mishra NS (2017) Micro-regulators of hormones and stress. Mechanism of plant hormone signaling under. Stress 2:319ā351
Shen L, Gong J, Caldo RA, Nettleton D, Cook D, Wise RP et al (2005) BarleyBaseāan expression profiling database for plant genomics. Nucleic Acids Res 33:D614āD618
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
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 277ā296
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 19:5ā15
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 16:189ā198
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:D1141āD1147
Speed D, Balding DJ (2015) Relatedness in the post-genomic era: is it still useful? Nat Rev Genet 16:33ā44
Stein LD (2003) Integrating biological databases. Nat Rev Genet 4:337
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 65ā110
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:D969āD974
SzczeÅniak MW, Deorowicz S, Gapski J, KaczyÅski Å, MakaÅowska I (2011) miRNEST database: an integrative approach in microRNA search and annotation. Nucleic Acids Res 40:D198āD204
Szklarczyk D, Jensen LJ (2015) Protein-protein interaction databases. In: Protein-protein interactions. Springer, New York, NY, pp 39ā56
Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J etĀ al (2014) STRING v10: proteināprotein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447āD452
Tardieu F, Tuberosa R (2010) Dissection and modelling of abiotic stress tolerance in plants. Curr Opin Plant Biol 13:206ā212
Tateno Y, Gojobori T (1997) DNA data Bank of Japan in the age of information biology. Nucleic Acids Res 25:14ā17
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:D1181āD1189
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 20:1426ā1436
Tyanova S, Temu T, Cox J (2016) The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc 11:2301
Udayakumar M, Chandar DP, Arun N, Mathangi J, Hemavathi K, Seenivasagam R (2012) PMDB: plant Metabolome databaseāa metabolomic approach. Med Chem Res 21:47ā52
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 347ā374
Urano K, Kurihara Y, Seki M, Shinozaki K (2010) āOmicsā analyses of regulatory networks in plant abiotic stress responses. Curr Opin Plant Biol 13:132ā138
Valentine AJ, Benedito VA, Kang Y (2011) Legume nitrogen fixation and soil abiotic stress: from physiology to genomics and beyond. Ann Plant Rev 43:207ā248
Van Wyk B-E, Wink M (2017) Medicinal plants of the world. CABI, Wallingford
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
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 17:37ā49
VĆt P, Krak K, TrĆ”vnĆÄek P, Douda J, Lomonosova MN, MandĆ”k B (2016) Genome size stability across eurasian chenopodium species (Amaranthaceae). Bot J Linn Soc 182:637ā649
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 156:1655ā1660
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:D1159āD1166
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
Wani SH (2018) Biochemical, physiological and molecular avenues for combating abiotic stress in plants. Academic Press, Cambridge, MA
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 30:103ā105
Weckwerth W (2003) Metabolomics in systems biology. Annu Rev Plant Biol 54:669ā689
Winter G, Krƶmer JO (2013) Fluxomicsāconnecting āomics analysis and phenotypes. Environ Microbiol 15:1901ā1916
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 406:347ā363
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:W22āW28
Yi X, Zhang Z, Ling Y, Xu W, Su Z (2014) PNRD: a plant non-coding RNA database. Nucleic Acids Res 43:D982āD989
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 149:171ā180
Yoshida T, Mogami J, Yamaguchi-Shinozaki K (2015) Omics approaches toward defining the comprehensive abscisic acid signaling network in plants. Plant Cell Physiol 56:1043ā1052
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:D1229āD1236
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:D1009āD1014
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 50:1865ā1873
Zandalinas SI, Mittler R, BalfagĆ³n D, Arbona V, GĆ³mez-Cadenas A (2018) Plant adaptations to the combination of drought and high temperatures. Physiol Plant 162:2ā12
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 226ā259
Zhang B (2015) MicroRNA: a new target for improving plant tolerance to abiotic stress. J Exp Bot 66:1749ā1761
Zhang Z, Yu J, Li D, Zhang Z, Liu F, Zhou X et al (2009) PMRD: plant microRNA database. Nucleic Acids Res 38:D806āD813
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
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 10:1224ā1237
Zhang P, Meng X, Chen H, Liu Y, Xue J, Zhou Y et al (2017b) PlantCircNet: a database for plant circRNAāmiRNAāmRNA regulatory networks. Database 2017:bax089. https://doi.org/10.1093/database/bax1089
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
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 638:36ā40
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:D1128āD1136
Zhu J-K (2016) Abiotic stress signaling and responses in plants. Cell 167:313ā324
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
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:D54āD58
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
Ā© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-21687-0_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-21686-3
Online ISBN: 978-3-030-21687-0
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)