Abstract
Bioinformatics has the major role to play in decoding of the genomes of plants and animals. Bioinformatics is making progress in each and every field of life sciences, and similarly, the field of crop improvement has also been influenced by it. Bioinformatics allows capturing, managing, analyzing, and integrating the huge amount of metabolomics, genomics, and proteomics data enabling its efficient interpretation by the users. Bioinformatics makes available data and various tools to every individual, company, or industries so as to increase nutritional value and yield of crops. Detection of complex protein–protein interactions, modeling the protein structures, and unraveling the high-resolution genetic and physical network in plants can also be easily accomplished using in silico studies. This book chapter basically reviews the different role and applications of bioinformatics in plant breeding, gene network analysis, and molecular marker-assisted crop improvement techniques.
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References
Atanassov A, Leunissen J, Dimov G, Nenov A, Vassilev D (2014) Application of bioinformatics in plant breeding. Biotechnol Biotechnol Equip 19(sup3):139–152
Athar A, Fullgrabe A, George N, Iqbal H, Huerta L et al (2019) Arrayexpress update—from bulk to single-cell expression data. Nucleic Acids Res 47(D1):D711–D715
Ballabh G, Singh UK, Kushwaha B, Deo I, Jaiswal JP, Prasad B (2017) Role of bioinformatics in crop improvement. Type Double Blind Peer Rev Int Res J Publ Glob J Inc [Internet] 17(1)
Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF et al (2013) NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res 41:D991–D995
Basantani MK, Gupta D, Mehrotra R, Mehrotra S, Vaish S, Singh A (2017) An update on bioinformatics resources for plant genomics research. Curr Plant Biol 11–12:33–40. Available from: https://doi.org/10.1016/j.cpb
Caspi R, Altman T, Billington R, Dreher K, Foerster H et al (2014) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res 42:D459–D471
Chaitieng B, Kaga A, Han OK, Wang YW, Wongkaew S (2002) Mapping a new source of resistance to powdery mildew in mungbean. Plant Breed 121:521–525
Duran Y, Vega PM (2004) Assessment of genetic variation and species relationships in a collection of lens using RAPD and ISSR. Span J Agric Res 2:538–544
Humphry ME, Magner CJ, Mcintyr ET, Aitken EABCL, Liu CJ (2003) Identification of major locus conferring resistance to powdery mildew in mungbean by QTL analysis. Genome 46:738–744
Ikeo K, Ishi-I J, Tamura T, Gojobori T, Tateno Y (2003) CIBEX: center for information biology gene EXpression database. CR Biol 326:1079–1082
Jennings PR (1979) Concluding remarks. In: Proceedings of the rice blast workshop. International Rice Research Institute, Manila, Philippines, pp 217–222
Joshi SP, Gupta VS, Aggarwal RK, Ranjekar PK, Brar DS (2000) Genetic diversity and phylogenetic relationship as revealed by inter-simple sequence repeat (ISSR) polymorphism in the genus Oryza. Theo Appl Genet 100:1311–1320
Kallio MA, Tuimala JT, Hupponen T, Klemelä P, Gentile M et al (2011) Chipster: user-friendly analysis software for microarray and other high-throughput data. BMC Genom 12:507
Kanehisa M, Sato Y, Furumichi M, Morishima K, Tanabe M (2019) New approach for understanding genome variations in KEGG. Nucleic Acids Res 47:D590–D595
Koschmieder A, Zimmermann K, Trißl S, Stoltmann T, Leser U (2012) Tools for managing and analyzing microarray data. Brief Bioinform 13:46–60
Kumar A, Tiwari KL, Jadhav SK, Singh M, Datta D (2011) Microsatellite (SSR) markers for ToLCV susceptible and resistant tomato genotype identification and F^ sub 1^ purity. J Plant Sci Res 27:199
Martin GB, Brommonschenkel SH, Chunwongse J, Frary A, Ganal MW et al (1993) Map-based cloning of a protein kinase gene conferring disease resistance in tomato. Science 262:1432–1436
Maurer M, Molidor R, Sturn A, Hartler J, Hackl H et al (2005) MARS: microarray analysis, retrieval, and storage system. BMC Bioinformatics 6:101
Mochida K, Shinozaki K (2010) Genomics and bioinformatics resources for crop improvement. Plant Cell Physiol 51:497–523
Mueller LA, Zhang P, Rhee SY (2003) AraCyc: a biochemical pathway database for arabidopsis. Plant Physiol 132:453–460
Naithani S, Preece J, D’Eustachio P, Gupta P, Amarasinghe V et al (2017) Plant reactome: a resource for plant pathways and comparative analysis. Nucleic Acids Res 45(D1):D1029–D1039
Ogawa T, Yamamoto T, Khush GS, Mew TW, Kaku H (1988) Near-isogenic lines as international differentials for resistance to bacterial blight of rice. Rice Genet Newsl 5:106–107
Ogawa T, Yamamoto T, Khush GS, Mew TW (1991) Breeding of near-isogenic lines of rice with single genes for resistance to bacterial blight pathogen (Xanthomonas campestris pv oryzae). Jpn J Breed 41:523–529
Paine JA, Shipton CA, Chaggar S, Howells RM, Kennedy MJ, Vernon G et al (2005) Improving the nutritional value of golden rice through increased pro-vitamin A content. Nat Biotechnol 23:482–487
Salomonis N, Hanspers K, Zambon AC, Vranizan K, Lawlor SC et al (2007) GenMAPP 2: new features and resources for pathway analysis. BMC Bioinformatics 8:217
Schlötterer (2004) The evolution of molecular markers—just a matter of fashion? Nature Rev Genet 5:63
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504
Sholihin, Hautea DM (2002) Molecular mapping of drought resistance in mungbean (Vigna radiata): 2: QTL linked to drought resistance. J Biotechnol Pertanian 7:55–61
Souframanien J, Manjaya JG, Krishna TG, Pawar SE (2003) Random amplified polymorphic DNA analyses of cytoplasmic male-sterile and male fertile pigeonpea [Cajanus cajan (L.) Millsp.]. Euphytica 129:293–299
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. PNAS 102:15545–15550
Sucaet Y, Deva T (2011) Evolution and applications of plant pathway resources and databases. Brief Bioinform 12:530–544
Tien Lea D, Duc Chua H, Quynh Lea N (2016) Improving nutritional quality of plant proteins through genetic engineering. Curr Genomics 17:220–229
Vallon-Christersson J, Nordborg N, Svensson M, Häkkine J (2009) BASE—2nd generation software for microarray data management and analysis. BMC Bioinformatics 10:330
Vassilev D, Leunissen J, Atanassov A, Nenov A, Dimov G (2005) Application of bioinformatics in plant breeding. Biotechnol Biotechnol Equip 19:139–152
Vilanova S, Cañizares J, Pascual L, Blanca JM, DĂez MJ, Prohens J et al (2012) Application of genomic tools in plant breeding. Curr Genomics 13:179–195
Yoshimura S, Yoshimura A, Saito A, Kishimoto N, Kawase M et al (1992) RFLP analysis of introgressed chromosomal segments in three near-isogenic lines of rice for bacterial blight resistance genes, Xa-1, Xa-3 andXa-4. Jpn J Genet 67:29–37
Young ND, Danesh D, Menancio-Hautea D, Kumar L (1993) Mapping oligogenic resistance to powdery mildew in mungbean with RFLPs. Theo Appl Genet 87:243–249
Zhang P (2005) MetaCyc and AraCyc. Metabolic pathway databases for plant research. Plant Physiol 138:27–37
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The authors are thankful to DBT-BIF facility, Centre for Bioinformatics, Maharshi Dayanand University for providing the necessary resources for successful compilation of this book chapter.
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Dangi, M., Jakhar, R., Deswal, S., Chhillar, A.K. (2019). Role and Applications of Bioinformatics in Improvement of Nutritional Quality and Yield of Crops. In: Jaiwal, P., Chhillar, A., Chaudhary, D., Jaiwal, R. (eds) Nutritional Quality Improvement in Plants. Concepts and Strategies in Plant Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-95354-0_16
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DOI: https://doi.org/10.1007/978-3-319-95354-0_16
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