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Current Status and Future Prospects of Omics Tools in Climate Change Research

  • Himashree Bora
  • Sukni Bui
  • Zeiwang Konyak
  • Madhu Kamle
  • Pooja Tripathi
  • Amit Kishore
  • Vijay Tripathi
  • Pradeep Kumar
Chapter

Abstract

Omics referring to a group of biological tools has greatly influenced today’s world of modern research. Genomics, transcriptomics, proteomics, and metabolomics together they help to bring out the best of characters in plants and other organisms for its improvement and enhancement of important bioactive compounds. Genomic study for finding chromosome location, phenotypic analysis by QTL mapping, genome-wide association studies (GWAS), etc. are being practiced along with the development of genome editing by CRISPERCas9 for a variety of crop plants under stress conditions from the past few years. Studies made on yeast and Arabidopsis, transcriptome profiling, and microarray-based studies could detect the significant alteration of gene expression and some rare novel transcript to map out the physiological pathways. Mass spectroscopy-based approaches like NMR, MALDI, and GC-MS came into being to simplify protein and metabolite studies, its structure, and its function which reciprocate in many important biological signalling cascades. Physiological and morphological changes in an organism due to environmental stress are an ongoing issue and newest addition to the research field, and with time, changes in the entire genome are a matter to look into where only molecular approaches can answer it. Thus, in this chapter we tried to summarize various aspects of omics tools and its future scope which can be utilize in climate change research.

Keywords

Metagenomics Metabolomics Transcriptomics Protein analysis Sustainable agriculture Human health 

Notes

Acknowledgments

All authors are highly grateful to the higher authority of respective department and institution for their help and support. Author (PK) would like to thanks DST-SERB (file no ECR/2017/001143) for the financial support.

Author Contributions

Author PK and MK conceived and designed the manuscript. HB, SB writes the manuscript. ZK helps in the writing of the manuscript. AK, MK, VT, PK critically reviewed the manuscript and did the require editing.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Aardema M, Grego MTJ (2002) Toxicology and genetic toxicology in the new era of “toxicogenomics”: impact of “-omics” technologies. Mutat Res 499:13–25CrossRefGoogle Scholar
  2. Abdelrahmana M, Burrittc DJ, Tran L-SP (2017) The use of metabolomic quantitative trait locus mapping and osmotic adjustment traits for the improvement of crop yields under environmental stresses. Semin Cell Dev Biol.  https://doi.org/10.1016/j.semcdb.2017.06.020
  3. Acuñagalindo MA, Mason RE, Subramanian NK, Hays DB (2015) Meta-analysis of wheat QTL regions associated with adaptation to drought and heat stress. Crop Sci 55(2):477–492.  https://doi.org/10.2135/cropsci2013.11.0793 CrossRefGoogle Scholar
  4. Avonce N, Leyman B, Mascorro-Gallardo JO, Van Dijck P, Thevelein JM, Iturriaga G (2004) The Arabidopsis trehalose-6-P synthase AtTPS1 gene is a regulator of glucose, abscisic acid, and stress signaling. Plant Physiol 136(3):3649–3659.  https://doi.org/10.1104/pp.104.052084 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Beck S, Olek A, Walter J (1999) From genomics to epigenomics: a loftier view of life. Nat Biotechnol 17(12):1144CrossRefGoogle Scholar
  6. Benina M, Obata T, Mehterov N, Ivanov I, Petrov V, Toneva V, Fernie AR, Gechev TS (2013) Comparative metabolic profiling of Haberlea rhodopensis, Thellungiella halophyla, and Arabidopsis thaliana exposed to low temperature. Front Plant Sci 4.  https://doi.org/10.3389/fpls.2013.00499
  7. Bhagirath D, Yang TL, Dahiya R, Majid S, Saini S (2019) Epigenetics of prostate cancer and novel chemopreventive and therapeutic approaches. Transl Epigenetics 8:287–308.  https://doi.org/10.1016/B978-0-12-812494-9.00014-7 CrossRefGoogle Scholar
  8. Bigot S, Buges J Gilly L, Jacques C, Boulch L P, Berger M , Delcros P, Domergue B J, Koeh A, Ley-Ngardiga B, Canh VTL, Couée I (2018) Pivotal roles of environmental sensing and signaling mechanisms in plant responses to climate change.  https://doi.org/10.1111/gcb.14433
  9. Bihaqi SW (2019) Early life exposure to lead (Pb) and changes in DNA methylation: relevance to Alzheimer’s disease. Rev Environ Health 34(2):187–195Google Scholar
  10. Boyko A, Kovalchuk I (2011) Genome instability and epigenetic modification —heritable responses to environmental stress? Curr Opin Plant Biol 14(3):260–266.  https://doi.org/10.1016/j.pbi.2011.03.003 CrossRefPubMedGoogle Scholar
  11. Chang WC, Hsu GS, Chiang SM, Su MC (2006) Heavy metal removal from aqueous solution by wasted biomass from a combined AS-biofilm process. Bioresour Technol 97:1503–1508CrossRefGoogle Scholar
  12. Chen S, Harmon AC (2006) Advances in plant proteomics. Proteomics 20:5504–5516CrossRefGoogle Scholar
  13. Chen C, Harst A, You W, Xu J, Ning K, Poetsch A (2019) Proteomic study uncovers molecular principles of single-cell-level phenotypic heterogeneity in lipid storage of Nannochloropsis oceanica. Biotechnol Biofuels 12:21CrossRefGoogle Scholar
  14. Cho S, Yu S, Park J, Mao Y, Zhu J, Lee B (2017) Accession-dependent CBF gene deletion by CRISPR/Cas system in Arabidopsis. Front Plant Sci 8:1–11.  https://doi.org/10.3389/fpls.2017.01910 CrossRefGoogle Scholar
  15. D’Amelia L, Dell’Aversana E, Woodrow P, Ciarmiello LF, Carillo P (2018) Metabolomics for crop improvement against salinity stress. Salinity Responses Tolerance Plants 2:267–287.  https://doi.org/10.1007/978-3-319-90318-7_11 CrossRefGoogle Scholar
  16. Dass A, Abdin MZ, Reddy VS, Leelavathi S (2017) Isolation and characterization of the dehydration stress-inducible GhRDL1 promoter from the cultivated upland cotton (Gossypium hirsutum). J Plant Biochem Biotechnol 26(1):113–119.  https://doi.org/10.1007/s13562-016-0369-3 CrossRefGoogle Scholar
  17. Davies H (2010) A role for “omics” technologies in food safety assessment. Food Control 21:1601–1610CrossRefGoogle Scholar
  18. Debbarma J, Sarkia YN, Saikia B, Boruah DPH, Singha DL, Chikkaputtaiah C (2019) Ethylene response factor (ERF) family proteins in abiotic stresses and CRISPR–Cas9 genome editing of ERFs for multiple abiotic stress tolerance in crop plants: a review. Mol Biotechnol 61:153–172.  https://doi.org/10.1007/s12033-018-0144-x CrossRefPubMedGoogle Scholar
  19. Depledge PD, Srinivas PK, Sadaoka T, Bready D, Mori Y, Placantonakis GD, Mohr I, Wilson CA (2019) Direct RNA sequencing on nanopore arrays redefines the transcriptional complexity of a viral pathogen. Nat Commun 10:754CrossRefGoogle Scholar
  20. Deshmukh R, Sonah H, Patil G, Chen W, Prince S, Mutava R, Vuong T, Valliyodan B, Nguyen HT (2014) Integrating omic approaches for abiotic stress tolerance in soybean. Front Plant Sci 5:244.  https://doi.org/10.3389/fpls.2014.00244 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Du Q, Bert SA, Armstrong NJ, Caldon CE, Song JZ, Nair SS, Gould CM, Luu PL, Peters T, Khoury A, Qu W, Zotenko E, Stirzaker C, Clark SJ (2019) Replication timing and epigenome remodeling are associated with the nature of chromosomal rearrangements in cancer. Nat Commun 10:416.  https://doi.org/10.1038/s41467-019-08302-1 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Escandón M, Meijón M, Valledor L, Pascual J, Pinto G, Cañal MJ (2018) Metabolome integrated analysis of high-temperature response in Pinus radiata. Front Plant Sci 9:485.  https://doi.org/10.3389/fpls.2018.00485 CrossRefPubMedPubMedCentralGoogle Scholar
  23. Esfahani MN, Kusano M, Nguyen KH, Watanabe Y, Ha CV, Saito K, Suliema S, Herrera-Estrellah L, Tran LS (2016) Adaptation of the symbiotic Mesorhizobium–chickpea relationship to phosphate deficiency relies on reprogramming of whole-plant metabolism. Proc Natl Acad Sci 113(32):E4610–E4619.  https://doi.org/10.1073/pnas.1609440113 CrossRefGoogle Scholar
  24. Fiehn O (2001) Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp Funct Genomics 2(3):155–168.  https://doi.org/10.1002/cfg.82 CrossRefPubMedPubMedCentralGoogle Scholar
  25. Finnegan EJ, Genger RK, Peacock WJ, Dennis ES (1998) DNA methylation in plants. Annu Rev Plant Physiol Plant Mol Biol 49:223–247CrossRefGoogle Scholar
  26. Finnegan EJ, Peacock WJ, Dennis ES (2000) DNA methylation, a key regulator of plant development and other processes. Curr Opin Genet Dev 10:217–223CrossRefGoogle Scholar
  27. Franks SJ, Hoffmann AA (2012) Genetics of climate change adaptation. Ann Rev Genet 46(1):185–208.  https://doi.org/10.1146/annurev-genet-110711-155511 CrossRefPubMedGoogle Scholar
  28. Franssena SU, Gua J, Bergmannb N, Wintersa G, Klostermeierc UC, Rosenstielc P, Bornberg-Bauera E, Reuschb TBH (2011) Transcriptomic resilience to global warming in the seagrass Zostera marina, a marine foundation species. Proc Natl Acad Sci 108(48):19276–19281.  https://doi.org/10.1073/pnas.1107680108 CrossRefGoogle Scholar
  29. Garcia-Cela E, Verheecke-Vaessen C, Magan N, Medina A (2018) The “-omics” contributions to the understanding of mycotoxin production under diverse environmental conditions. Curr Opin Food Sci.  https://doi.org/10.1016/j.cofs.2018.08.005
  30. Ge Y, Wang DZ, Chiu JF, Cristoba S, Sheehan D, Silvestre F, Peng X, Li H, Gong Z, Lam SH, Wentao H, Iwahashi H, Liu J, Mei N, Shi L, Bruno M, Foth H, Teichman K (2013) Environmental OMICS: current status and future directions. J Integr Omics 3(2):75–87CrossRefGoogle Scholar
  31. Giavalisco P, Nordhoff E, Kreitler T, Klöppel KD, Lehrach H, Klose J, Gobom J (2005) Proteome analysis of Arabidopsis thaliana by two dimensional gel electrophoresis and matrix-assisted laser desorption/ionisation-time of flight mass spectrometry. Proteomics 5:1902–1913CrossRefGoogle Scholar
  32. Guo J, Wu J, Ji Q, Wang C, Luo L, Yuan Y, Wang Y, Wang J (2008) Genome-wide analysis of heat shock transcription factor families in rice and Arabidopsis. J Genet Genomics 35(2):105–118.  https://doi.org/10.1016/s1673-8527(08)60016-8 CrossRefPubMedGoogle Scholar
  33. Gupta B, Sengupta A, Saha J, Gupta K (2013) Plant abiotic stress: ‘omics’ approach. Plant Biochem Physiol 1:3.  https://doi.org/10.4172/2329-9029.1000e108 CrossRefGoogle Scholar
  34. Haque E, Taniguchi H, Hassan MM, Bhowmik P, Karim MR, Śmiech M et al (2018) Application of CRISPR/Cas9 genome editing technology for the improvement of crops cultivated in tropical climates: recent progress, prospects, and challenges. Front Plant Sci 9:1–12.  https://doi.org/10.3389/fpls.2018.00617 CrossRefGoogle Scholar
  35. Hashiguchi A, Ahsan N, Komatsu S (2010) Proteomics application of crops in the context of climatic changes. Food Res Int 43(7):1803–1813.  https://doi.org/10.1016/j.foodres.2009.07.033 CrossRefGoogle Scholar
  36. Horgan RP, Kenny LC (2011) SAC review ‘Omic’ technologies: genomics, transcriptomics, proteomics and metabolomics. Obstet Gynaecol 13(1):189–195.  https://doi.org/10.1576/toag.13.3.189.27672 CrossRefGoogle Scholar
  37. Hossain MA, Bhattacharjee S, Armin S-M, Qian P, Xin W, Li H-Y, Burritt DJ, Fujita M, Tran LS (2015) Hydrogen peroxide priming modulates abiotic oxidative stress tolerance: insights from ROS detoxification and scavenging. Front Plant Sci 6:420.  https://doi.org/10.3389/fpls.2015.00420 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Islam MS, Ontoy J, Subudhi PK (2019) Meta-analysis of quantitative trait loci associated with seedling-stage salt tolerance in Rice (Oryza sativa L.). Plan Theory 8(2):33.  https://doi.org/10.3390/plants8020033 CrossRefGoogle Scholar
  39. Jaenisch R, Bird A (2003) Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet 33:245–254CrossRefGoogle Scholar
  40. Jorge TF, Rodrigues JA, Caldana C, Schmidt R, Dongen JTV, Thomas-Oates J, Antonio C (2016) Mass spectrometry-based plant metabolomics:metabolite responses to abiotic stress. Mass Spectrom Rev 35(5):620–649.  https://doi.org/10.1002/mas.21449 CrossRefPubMedGoogle Scholar
  41. Kaplan F, Kopka J, Haskell WD, Zhao W, Schiller KC, Gatzke N, Sung DY, Guy CL (2004) Exploring the temperature-stress metabolome of Arabidopsis. Plant Physiol 136:4159–4168CrossRefGoogle Scholar
  42. Kavi Kishor PB, Hong Z, Miao GC, Hu CAA, Verma DPS (1995) Overexpression of [delta]1-pyrroline-5-carboxylate synthetase increases proline production and confers osmotolerance in transgenic plants. Plant Physiol 108(4):1387–1394.  https://doi.org/10.1104/pp.108.4.1387 CrossRefGoogle Scholar
  43. Khan N, Bano A, Rahman MA, Rathinasabapathi B, Babar MA (2019) UPLC-HRMS-based untargeted metabolic profiling reveals changes in chickpea (Cicer arietinum) metabolome following long-term drought stress. Plant Cell Environ 42:115–132.  https://doi.org/10.1111/pce.13195 CrossRefPubMedGoogle Scholar
  44. Kim ST, Kim SG, Hwang DH, Kang SY, Kim HJ, Lee BH, Lee JJ, Kang KY (2004) Proteomic analysis of pathogen-responsive proteins from rice leaves induced by rice blast fungus Magnaporthe grisea. Proteomics 4:3569–3578.  https://doi.org/10.1002/pmic.200400999 CrossRefPubMedGoogle Scholar
  45. Kim YH, Cho K, Yun SH, Kim JY, Kwon KH, Yoo JS, Kim S (2006) Analysis of aromatic catabolic pathways in Pseudomonas putida KT 2440 using a combined proteomic approach: 2-DE/MS and cleavable isotope-coded affinity tag analysis. Proteomics 6:1301–1318.  https://doi.org/10.1002/pmic.200500329 CrossRefPubMedGoogle Scholar
  46. Kole C, Muthamilarasan M, Henry R, Edwards D, Sharma R, Abberton M et al (2015) Application of genomics-assisted breeding for generation of climate resilient crops: progress and prospects. Front Plant Sci 6:563.  https://doi.org/10.3389/fpls.2015.00563 CrossRefPubMedPubMedCentralGoogle Scholar
  47. Kumar R, Kumari M (2018) Adaptive mechanisms of medicinal plants along altitude gradient:contribution of proteomics. Biol Plant 62(4):630–640.  https://doi.org/10.1007/s10535-018-0817-0 CrossRefGoogle Scholar
  48. Langridge P, Fleury D (2011) Making the most of ‘omics’ for crop breeding. Trends Biotechnol 29:33–40CrossRefGoogle Scholar
  49. Langridge P, Reynolds MP (2015) Genomic tools to assist breeding for drought tolerance. Curr Opin Biotechnol 32:130–135.  https://doi.org/10.1016/j.copbio.2014.11.027 CrossRefPubMedGoogle Scholar
  50. Li R, Liu C, Zhao R, Wang L, Chen L, Yu W, Zhang S, Sheng J, Shen L (2019) CRISPR/Cas9-mediated SlNPR1 mutagenesis reduces tomato plant drought tolerance. BMC Plant Biol 19(1):38.  https://doi.org/10.1186/s12870-018-1627-4 CrossRefPubMedPubMedCentralGoogle Scholar
  51. Lighten J, Incarnato D, Ward BJ, van Oosterhout C, Bradbury I, Hanson M, Bentzen P (2016) Adaptive phenotypic response to climate enabled by epigenetics in a K-strategy species, the fish Leucoraja ocellata (Rajidae). R Soc Open Sci 3:160299CrossRefGoogle Scholar
  52. Liu AQ (2013) The impact of climate change on plant epigenomes. Trends Genet 29(9):503–505CrossRefGoogle Scholar
  53. Liu D, Chen X, Liu J, Ye J, Guo Z (2012) The rice ERF transcription factor OsERF922 negatively regulates resistance to Magnaporthe oryzae and salt tolerance. J Exp Bot 63:3899–3911.  https://doi.org/10.1093/jxb/err313 CrossRefPubMedPubMedCentralGoogle Scholar
  54. Ly D, Huet S, Gauffreteau A, Rincent R, Touzy G, Mini A, Jannink JL, Cormier F, Paux E, Lafarge S, Gouis JL, Charmet G (2018) Whole-genome prediction of reaction norms to environmental stress in bread wheat (Triticum aestivum L.) by genomic random regression. Field Crop Res 216:32–41.  https://doi.org/10.1016/j.fcr.2017.08.020 CrossRefGoogle Scholar
  55. Mackelprang R, Saleska RS, Jacobsen CS, Jansson KJ, Tas N (2016) Permafrost Meta-omics and climate change. Ann Rev Earth Planet Sci 44(1):439–462.  https://doi.org/10.1146/annurev-earth-060614-105126 CrossRefGoogle Scholar
  56. May P, Liao W, Wu Y, Shuai B, McCombie WR, Zhang QM, Liu QA (2013) The effects of carbon dioxide and temperature on microRNA expression in Arabidopsis development. Nat Commun 4:2145.  https://doi.org/10.1038/ncomms3145 CrossRefPubMedGoogle Scholar
  57. McLean TI (2013) “Eco-omics”: a review of the application of genomics, transcriptomics, and proteomics for the study of the ecology of harmful algae. Microb Ecol 65:901–915CrossRefGoogle Scholar
  58. Meena KK, Sorty AM, Bitla UM, Choudhary K, Gupta P, Pareek A, Singh DP, Prabha R, Sahu PK, Gupta VK, Singh HB, Krishanani KK, Minhas PS (2017) Abiotic stress responses and microbe-mediated mitigation in plants: the omics strategies. Front Plant Sci 8:172.  https://doi.org/10.3389/fpls.2017.00172 CrossRefPubMedPubMedCentralGoogle Scholar
  59. Meng L, Tong Z, Sisi G, Scott P, Li H, Chen S (2019) Comparative proteomics and metabolomics of JAZ7-mediated drought tolerance in Arabidopsis. J Proteome 196:81–91CrossRefGoogle Scholar
  60. Miao H, Sun P, Liu Q, Liu J, Xu B, Jin Z (2017) The AGPase family proteins in banana: genome-wide identification, phylogeny, and expression analyses reveal their involvement in the development, ripening, and abiotic/biotic stress responses. Int J Mol Sci 18(8):1–17.  https://doi.org/10.3390/ijms18081581 CrossRefGoogle Scholar
  61. Mittler R, Vanderauwera S, Gollery M, Breusegem FV (2004) Reactive oxygen gene network of plants. Trends Plant Sci 9(10):490–498.  https://doi.org/10.1016/j.tplants.2004.08.009 CrossRefPubMedGoogle Scholar
  62. Muthuramalingam P, Krishnan RS, Pandian S, Ramesh M (2017) Emerging trends on abiotic stress tolerance investigation in crop plants. Adv Biotechnol Microbiol 6(1):555678.  https://doi.org/10.19080/AIBM.2017.06.555678 CrossRefGoogle Scholar
  63. My T, Hoang L, Tran TN, Kieu T, Nguyen T, Williams B, Wurm P, Bellaires S, Mundree S (2016) Improvement of salinity stress tolerance in rice: challenges and opportunities. Agronomy 6:54.  https://doi.org/10.3390/agronomy6040054 CrossRefGoogle Scholar
  64. Nakabayashi R, Saito K (2015) Integrated metabolomics for abiotic stress responses in plants. Curr Opin Plant Biol 24(6):10–16CrossRefGoogle Scholar
  65. Ni Z, Li H, Zhao Y, Peng H, Hu Z, Xin M, Sun Q (2018) Genetic improvement of heat tolerance in wheat: recent progress in understanding the underlying molecular mechanisms. Crop J 6(1):32–34Google Scholar
  66. Noctor G, Mhamdi A, Foyer CH (2014) The roles of reactive oxygen metabolism in drought: not so cut and dried. Plant Physiol 164(4):1636–1648.  https://doi.org/10.1104/pp.113.233478 CrossRefPubMedPubMedCentralGoogle Scholar
  67. Obata T, Fernie AR (2012) The use of metabolomics to dissect plant responses to abiotic stresses. Cell Mol Life Sci 69(19):3225–3243.  https://doi.org/10.1007/s00018-012-1091-5 CrossRefPubMedPubMedCentralGoogle Scholar
  68. Ou W, Mao X, Huang C, Tie W, Yan Y, Ding Z et al (2018) Genome-wide identification and expression analysis of the KUP family under abiotic stress in cassava (Manihot esculenta Crantz). Front Physiol 9:1–11.  https://doi.org/10.3389/fphys.2018.00017 CrossRefGoogle Scholar
  69. Pandey A, Mann M (2000) Proteomics to study genes and genomes. Nature 405(6788):837–846CrossRefGoogle Scholar
  70. Rahamana M, Mamidib S, Rahmana M (2018) Genome-wide association study of heat stress tolerance traits in spring-type Brassica napus L. under controlled conditions. Crop J 6(2):115–125.  https://doi.org/10.1016/j.cj.2017.08.003 CrossRefGoogle Scholar
  71. Ren B, Robert F, Wyrick JJ, Aparicio O, Jennings EG, Simon I, Zeitlinger J, Schreiber J, Hannett N (2000) Genome-wide location and function of DNA-binding proteins. Science 290:2306–2309CrossRefGoogle Scholar
  72. Rodziewicz P, Swarcewicz B, Chmielewska K, Wojakowska A, Stobiecki M (2014) Influence of abiotic stresses on plant proteome and metabolome Changes. Acta Physiol Plant 36(1):1–19.  https://doi.org/10.1007/s11738-013-1402-y CrossRefGoogle Scholar
  73. Russ GL, Ungaro P (2019) Epigenetic mechanisms of quercetin and other flavonoids in cancer therapy and prevention. Transl Epigenetics 8:187–202.  https://doi.org/10.1016/B978-0-12-812494-9.00009-3 CrossRefGoogle Scholar
  74. Scheben A, Yuan Y, Edwards D (2016) Advances in genomics for adapting crops to climate change. Curr Plant Biol 6:2–10.  https://doi.org/10.1016/j.cpb.2016.09.001 CrossRefGoogle Scholar
  75. Seki M, Umezawa T, Urano K, Shinozak K (2007) Regulatory metabolic networks in drought stress responses. Curr Opin Plant Biol 10(3):296–302.  https://doi.org/10.1016/j.pbi.2007.04.014 CrossRefPubMedGoogle Scholar
  76. Sevillano GAM, García-Barrera T, Abril N, Pueyo C, López-Barea J, Gómez-Ariza LJ (2014) Omics technologies and their applications to evaluate metal toxicity in mice Mus spretus as a bioindicator. J Proteome 104:4–23CrossRefGoogle Scholar
  77. Shah T, Xu J, Zou X, Cheng Y, Nasir M, Zhang X (2018) Omics approaches for engineering wheat production under abiotic stresses. Int J Mol Sci 19(8):2390.  https://doi.org/10.3390/ijms19082390 CrossRefPubMedCentralGoogle Scholar
  78. Singh S, Singhal NK, Srivastava G, Singh PM (2010) Omics in mechanistic and predictive toxicology. Toxicol Mech Methods 20(7):355–362CrossRefGoogle Scholar
  79. Skinner KM (2015) Environmental epigenetics and a unified theory of the molecular aspects of evolution: a neo-Lamarckian concept that facilitates neo-Darwinian evolution. Genome Biol Evol 7(5):1296–1302CrossRefGoogle Scholar
  80. Skinner JS, Szucs P, Zitzewitz JV, Marquez-Cedillo L, Filichkin T, Stockinger EJ, Thomashow MF, HH CT, Hayes PM (2006) Mapping of barley homologs to genes that regulate low temperature tolerance in Arabidopsis. Theoritical Appl Genet 112(5):832–842.  https://doi.org/10.1007/s00122-005-0185-y CrossRefGoogle Scholar
  81. Stillman JH, Armstrong E (2015) Genomics are transforming our understanding of responses to climate change. Bioscience 65(3):237–246.  https://doi.org/10.1093/biosci/biu219 CrossRefGoogle Scholar
  82. Stylianou E (2013) Epigenetics: the fine-tuner in inflammatory bowel disease. Curr Opin Gastroenterol 29:370–377CrossRefGoogle Scholar
  83. Stylianou E (2019) Epigenetics of chronic inflammatory diseases. J Inflamm Res 12:1–14CrossRefGoogle Scholar
  84. Sun QX, Quick JS (1991) Chromosomal locations of genes for heat tolerance in tetraploid wheat. Cereal Res Commun 19(4):431–437Google Scholar
  85. Szabados L, Savoure A (2010) Proline: a multifunctional amino acid. Trends Plant Sci 15(2):89–97.  https://doi.org/10.1016/j.tplants.2009.11.009 CrossRefPubMedGoogle Scholar
  86. Taji T, Ohsumi C, Iuchi S, Seki M, Kasuga M, Kobayashi M, Yamaguchi-Shinozaki K, Shinozaki K (2002) Important roles of drought- and cold-inducible genes for galactinol synthase in stress tolerance in Arabidopsis thaliana. The. Plant J 29(4):417–426.  https://doi.org/10.1046/j.0960-7412.2001.01227.x CrossRefPubMedGoogle Scholar
  87. Todgham EA, Hofmann EG (2009) Transcriptomic response of sea urchin larvae Strongylocentrotus purpuratus to CO2-driven seawater acidification. J Exp Biol 212:2579–2594CrossRefGoogle Scholar
  88. Tripathy JN, Zhang J, Robin S, Nguyen HT (2000) QTLs for cell-membrane stability mapped in rice (Oryza sativa L.) under drought stress. Theoritical Appl Genet 100(8):1197–1202.  https://doi.org/10.1007/s001220051424 CrossRefGoogle Scholar
  89. Tyers M, Mann M (2003) From genomics to proteomics. Nature 422(6928):193–197CrossRefGoogle Scholar
  90. Urano K, Maruyama K, Ogata Y, Morishita Y, Takeda M, Sakurai N, Suzuki H, Saito K, Shibata D, Kobayashi M, Yamaguchi-Shinozaki K, Shinozaki K (2009) Characterization of the ABA-regulated global responses to dehydration in Arabidopsis by metabolomics. Plant J 57(6):1065–1078.  https://doi.org/10.1111/j.1365-313X.2008.03748.x CrossRefPubMedGoogle Scholar
  91. Urano K, Kurihara Y, Seki M, Shinozaki K (2010) ‘Omics’ analyses of regulatory networks in plant abiotic stress responses. Curr Opin Plant Biol 13(1):132–138.  https://doi.org/10.1016/j.pbi.2009.12.006 CrossRefPubMedGoogle Scholar
  92. Valliyodan B, Nguyen HT (2006) Understanding regulatory networks and engineering for enhanced drought tolerance in plants. Curr Opin Plant Biol 9(2):189–195.  https://doi.org/10.1016/j.pbi.2006.01.019 CrossRefPubMedGoogle Scholar
  93. Valluru R, Reynolds MP, Davies WJ, Sukumaran S (2017) Phenotypic and genome-wide association analysis of spike ethylene in diverse wheat genotypes under heat stress. New Phytol 214(1):271–283.  https://doi.org/10.1111/nph.14367 CrossRefPubMedGoogle Scholar
  94. Varin T, Lovejoy C, Jungblut AD, Vincent WF, Corbeil J (2011) Metagenomic analysis of stress genes in microbial Mat communities from Antarctica and the high Arctic. Appl Environ Microbiol 78(2):549–559.  https://doi.org/10.1128/AEM.06354-11 CrossRefPubMedGoogle Scholar
  95. Verbruggen N, Hermans C (2008) Proline accumulation in plants: a review. Amino Acids 35(4):753–759.  https://doi.org/10.1007/s00726-008-0061-6 CrossRefPubMedGoogle Scholar
  96. Virzì MG, Clementi A, Broccal A, Cal DM, Ronco C (2017) Epigenetics: a potential key mechanism involved in the pathogenesis of cardiorenal syndromes. J Nephrol 31(3):333–341.  https://doi.org/10.1007/s40620-017-0425-7 CrossRefPubMedGoogle Scholar
  97. Vlaanderen J, Moore EL, Smith TM, Lan Q, Zhang L, Skibola FC, Rothman N, Vermeulen R (2010) Application of OMICS technologies in occupational and environmental health research; current status and projections. Occup Environ Med 67:136–143.  https://doi.org/10.1136/oem.2008.042788 CrossRefPubMedGoogle Scholar
  98. Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10:57CrossRefGoogle Scholar
  99. Wang X, Xua Y, Huc Z, Xua C (2018) Genomic selection methods for crop improvement:current status and prospects. Crop J 6(4):330–340.  https://doi.org/10.1016/j.cj.2018.03.001 CrossRefGoogle Scholar
  100. Whayne FT (2014) Epigenetics in the development, modification, and prevention of cardiovascular disease. Mol Biol Rep 42(4):765–776.  https://doi.org/10.1007/s11033-014-3727-z CrossRefPubMedGoogle Scholar
  101. Wilkins MR, Williams KL, Appel RD, Hochstrasser DF (1997) Proteome research: new frontiers in functional genomics. Springer, Berlin.  https://doi.org/10.1007/978-3-662-03493-4_5 CrossRefGoogle Scholar
  102. Xu R, Sun Q, Zhang S (1996) Chromosomal location of genes for heat tolerance as measured by membrane thermostability of common wheat cv. Hope. Hereditas 18(4):1–3Google Scholar
  103. Yan X, Hu Z, Feng Y, Hu X, Yuan J, Zhao SD et al (2015) Comprehensive genomic characterization of long non-coding RNAs across human cancers. Cancer Cell 28:529–540Google Scholar
  104. Zhang W, Li F, Nie L (2010) Integrating multiple ‘omics’ analysis for microbial biology: application and methodologies. Microbiology 156:287–301CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Himashree Bora
    • 1
  • Sukni Bui
    • 1
  • Zeiwang Konyak
    • 1
  • Madhu Kamle
    • 1
  • Pooja Tripathi
    • 2
  • Amit Kishore
    • 3
  • Vijay Tripathi
    • 4
  • Pradeep Kumar
    • 1
  1. 1.Department of ForestryNorth Eastern Regional Institute of Science and Technology (NERIST)NirjuliIndia
  2. 2.Department of Computational Biology and BioinformaticsSam Higginbottom University of Agriculture, Technology and SciencesAllahabadIndia
  3. 3.Department of BotanyKamla Nehru P.G. CollegeRaebareliIndia
  4. 4.Department of Molecular and Cellular EngineeringJacob Institute of Biotechnologyand BioengineeringAllahabadIndia

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