Basics of the Molecular Biology: From Genes to Its Function

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Genomics Data Analysis for Crop Improvement

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Abstract

The discipline of molecular biology primarily delineates by unravelling the interactions between deoxyribonucleic acid, ribonucleic acid and proteins and their connections to various metabolic activities of the cell. The knowledge of molecular biology is essential to understand the mechanisms by which information in the genes translates into functional proteins in a highly coordinated and regulated manner in prokaryotic, eukaryotic and multicellular organisms. Several techniques have been developed to study these biomolecules and their regulations, which are getting increasingly popular amongst researchers of genetics and other closely associated fields. In this chapter, we have discussed the basic concept of genes and the central dogma of molecular biology. Various molecular biological tools that are used to study cellular biomolecules, including DNA, RNA and proteins have been reviewed in the later part of the chapter. We have also given a brief account of different DNA sequencing methods and their importance in understanding the functions of genes.

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References

  1. Payne DA (2016) Basics of molecular biology. In: Leonard D (ed) Molecular pathology in clinical practice. Springer, Cham

    Google Scholar 

  2. Hirsch ED (2002) The new dictionary of cultural literacy. Houghton Mifflin, Boston

    Google Scholar 

  3. Seltsam A, Hallensleben M, Kollmann A, Blasczyk R (2003) The nature of diversity and diversification at the ABO locus. Blood 102(8):3035–3042

    Article  CAS  PubMed  Google Scholar 

  4. Sinden RR (1994) DNA structure and function. Academic

    Google Scholar 

  5. Chatterjee K, Wan Y (2018) RNA. Encyclopedia Britannica. https://www.britannica.com/science/RNA

  6. Darnell JE (1977) mRNA structure and function. Prog Nucleic Acid Res Mol Biol 19:493–511. https://doi.org/10.1016/S0079-6603(08)60941-1

    Article  Google Scholar 

  7. Oeffinger M, Zenklusen D (2019) The biology of mRNA: structure and function, 1st edn. Springer, Cham

    Book  Google Scholar 

  8. Noller HF (1984) Structure of ribosomal RNA. Annu Rev Biochem 53:119–162

    Article  CAS  PubMed  Google Scholar 

  9. Sharp SJ, Schaack J, Cooley L, Burke DJ, Soil D (1985) Structure and transcription of eukaryotic tRNA gene. Crit Rev Biochem 19:107–144

    Article  CAS  Google Scholar 

  10. Statello L, Guo CJ, Chen LL et al (2021) Gene regulation by long non-coding RNAs and its biological functions. Nat Rev Mol Cell Biol 22:96–118. https://doi.org/10.1038/s41580-020-00315-9

    Article  CAS  PubMed  Google Scholar 

  11. Ransohoff J, Wei Y, Khavari P (2018) The functions and unique features of long intergenic non-coding RNA. Nat Rev Mol Cell Biol 19:143–157. https://doi.org/10.1038/nrm.2017.104

    Article  CAS  PubMed  Google Scholar 

  12. Zhang P, Li S, Chen M (2020) Characterization and function of circular RNAs in plants. Front Mol Biosci 7:91. https://doi.org/10.3389/fmolb.2020.00091

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Wang J, Mei J, Ren G (2019) Plant microRNAs: biogenesis, homeostasis, and degradation. Front Plant Sci 10:360. https://doi.org/10.3389/fpls.2019.00360

    Article  PubMed  PubMed Central  Google Scholar 

  14. Li LC (2014) Chromatin remodeling by the small RNA machinery in mammalian cells. Epigenetics 9(1):45–52. https://doi.org/10.4161/epi.26830; Epub 2013 Oct 22

    Article  CAS  PubMed  Google Scholar 

  15. Ozata DM, Gainetdinov I, Zoch A et al (2019) PIWI-interacting RNAs: small RNAs with big functions. Nat Rev Genet 20:89–108

    Article  CAS  PubMed  Google Scholar 

  16. Liang J, Wen J, Huang Z, Chen X, Zhang B, Chu L (2019) Small nucleolar RNAs: insight into their function in cancer. Front Oncol 9:587. https://doi.org/10.3389/fonc.2019.00587

    Article  PubMed  PubMed Central  Google Scholar 

  17. Shuai P, Liang D, Tang S, Zhang Z, Ye CY, Su Y et al (2014) Genome-wide identification and functional prediction of novel and drought-responsive lincRNAs in Populus trichocarpa. J Exp Bot 65:4975–4983

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Pattanayak D, Solanke AU, Kumar PA (2012) Plant RNA interference pathways: diversity in function, similarity in action. Plant Mol Biol Report 31:493–506

    Article  Google Scholar 

  19. O’Connor CM, Adams JU (2010) Essentials of cell biology. NPG Education, Cambridge, MA

    Google Scholar 

  20. Crick F (1970) Central dogma of molecular biology. Nature 227(5258):561–563

    Article  CAS  PubMed  Google Scholar 

  21. Barry P (2007) Genome 2.0 mountains of new data are challenging old views. Science News

    Google Scholar 

  22. Hewitt SM (2020) Negative consequences of the central dogma. J Histochem Cytochem 68(11):731

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Tan CL, Anderson E (2020) The new central dogma of molecular biology. https://www.researchgate.net/publication/340062231_The_New_Central_Dogma_of_Molecular_Biology. Accessed 14 June 2020

  24. Gray SG (2015) Epigenetic cancer therapy. Academic Press, Boston, MA, pp 393–425

    Google Scholar 

  25. Daus ML (2016) Disease transmission by misfolded prion-protein isoforms, prion-like amyloids, functional amyloids and the central dogma. Biology (Basel) 5:2

    PubMed  Google Scholar 

  26. Wain HM, Bruford EA, Lovering RC, Lush MJ, Wright MW, Povey S (2002) Guidelines for human gene nomenclature. Genomics 79:464–470

    Article  CAS  PubMed  Google Scholar 

  27. Pearson H (2006) Genetics: what is a gene? Nature 441:398–401

    Article  CAS  PubMed  Google Scholar 

  28. Berget SM, Moore C, Sharp PA (1977) Spliced segments at the 5 terminus of adenovirus 2 late mRNA. Proc Natl Acad Sci U S A 74:3171–3175

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Gelinas RE, Roberts RJ (1977) One predominant 5-undecanucleotide in adenovirus 2 late messenger RNAs. Cell 11:533–544

    Article  CAS  PubMed  Google Scholar 

  30. Gerstein MB, Bruce C, Rozowsky JS, Zheng D, Du JJ, Korbel JO, Emanuelsson O, Zhang ZD, Weissman S, Snyder M (2007) What is a gene, post ENCODE? History and updated definition. Genome Res 17:669–681

    Article  CAS  PubMed  Google Scholar 

  31. Bateson W, Saunders ER (1902) The facts of heredity in the light of Mendel’s discovery. Reports to the Evolution Committee of the Royal Society, pp 125–160

    Google Scholar 

  32. Smigielski EM, Sirotkin K, Ward M, Sherry ST (2000) dbSNP: a database of single nucleotide polymorphisms. Nucleic Acids Res 28(1):352–355

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Daniel H, Jones EW (2005) Essential genetics: a genomics perspective, 4th edn. Jones & Bartlett Publishers, p 600

    Google Scholar 

  34. Saiki RK, Scharf S, Faloona F, Mullis KB, Horn GT, Erlich HA, Arnheim N (1985) Enzymatic amplification of beta-globin genomic sequences and restriction site analysis for diagnosis of sickle cell anemia. Science 230(4732):1350–1354

    Article  CAS  PubMed  Google Scholar 

  35. Lan L, Xu D, Ye G, **a C, Wang S, Li Y, Xu H (2020) Positive RT-PCR test results in patients recovered from COVID-19. JAMA 323(15):1502–1503

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Ninfa A, Ballou D, Benore M (2009) Fundamental laboratory approaches for biochemistry and biotechnology. Wiley, Hoboken, NJ, pp 408–410

    Google Scholar 

  37. Hindson BJ, Ness KD, Masquelier DA, Belgrader P et al (2011) High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem 83:8604–8610

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Taylor SC, Laperriere G, Germain H (2017) Droplet digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data. Sci Rep 7:2409

    Article  PubMed  PubMed Central  Google Scholar 

  39. Pramanik D, Shelake RM, Kim MJ, Kim JY (2021) CRISPR-mediated engineering across the central dogma in plant biology for basic research and crop improvement. Mol Plant 14:127–150

    Article  CAS  PubMed  Google Scholar 

  40. Kryndushkin DS, Ter-Avanesyan MD, Kushnirov VV (2003) Yeast [PSI+] prion aggregates are formed by small Sup35 polymers fragmented by Hsp104. J Biol Chem 278(49):49636–49643

    Article  CAS  PubMed  Google Scholar 

  41. Sambrook J, Russel DW (2001) Molecular cloning: a laboratory manual, 3rd edn. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY

    Google Scholar 

  42. Berg JM, Tymoczko JL, Stryer JL (2002) Biochemistry, 5th edn. WH Freeman

    Google Scholar 

  43. Taub FE, DeLeo JM, Thompson EB (1983) Sequential comparative hybridizations analyzed by computerized image processing can identify and quantitate regulated RNAs. DNA 2(4):309–327

    Article  CAS  PubMed  Google Scholar 

  44. Behjati S, Tarpey PS (2013) What is next generation sequencing? Arch Dis Child Educ Pract Ed 98(6):236–238

    Article  PubMed  PubMed Central  Google Scholar 

  45. Pekin D, Skhiri Y, Baret JC, Le Corre D, Mazutis L, Salem CB et al (2011) Quantitative and sensitive detection of rare mutations using droplet-based microfluidics. Lab Chip 11(13):2156–2166

    Article  CAS  PubMed  Google Scholar 

  46. Maxam AM, Gilbert W (1977) A new method for sequencing DNA. Proc Natl Acad Sci U S A 74(2):560–564

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Sanger F, Nicklen S, Coulson AR (1977) DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci U S A 74(12):5463–5477

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Olsvik O, Wahlberg J, Petterson B, Uhlén M, Popovic T, Wachsmuth IK, Fields PI (1993) Use of automated sequencing of polymerase chain reaction-generated amplicons to identify three types of cholera toxin subunit B in Vibrio cholerae O1 strains. J Clin Microbiol 31(1):22–25

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Pettersson E, Lundeberg J, Ahmadian A (2009) Generations of sequencing technologies. Genomics 93(2):105–111

    Article  CAS  PubMed  Google Scholar 

  50. Fiers W, Contreras R, Duerinck F, Haegeman G, Iserentant D, Merregaert J, Jou WM, Molemans F, Raeymaekers A, Van den Berghe A, Volckaert G, Ysebaert M (1976) Complete nucleotide sequence of bacteriophage MS2 RNA: primary and secondary structure of the replicase gene. Nature 260(5551):500–507

    Article  CAS  PubMed  Google Scholar 

  51. Quail MA, Gu Y, Swerdlow H, Mayho M (2012) Evaluation and optimisation of preparative semi-automated electrophoresis systems for Illumina library preparation. Electrophoresis 33(23):3521–3528

    Article  CAS  PubMed  Google Scholar 

  52. Duhaime MB, Deng L, Poulos BT, Sullivan MB (2012) Towards quantitative metagenomics of wild viruses and other ultra-low concentration DNA samples: a rigorous assessment and optimization of the linker amplification method. Environ Microbiol 14(9):2526–2537

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Hall N (2007) Advanced sequencing technologies and their wider impact in microbiology. J Exp Biol 210:1518–1525

    Article  CAS  PubMed  Google Scholar 

  54. Bosch JR, Grody WW (2008) Kee** up with the next generation. J Mol Diagn 10(6):484–492

    Article  PubMed  PubMed Central  Google Scholar 

  55. Tucker T, Marra M, Friedman JM (2009) Massively parallel sequencing: the next big thing in genetic medicine. Am J Hum Genet 85(2):142–154

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Straiton J, Free T, Sawyer A, Martin J (2019) From Sanger sequencing to genome databases and beyond. Biotechniques 66(2):60–63

    Article  CAS  PubMed  Google Scholar 

  57. Wolf JB (2013) Principles of transcriptome analysis and gene expression quantification: an RNA-seq tutorial. Mol Ecol Resour 13:559–572

    Article  CAS  PubMed  Google Scholar 

  58. Pietu G, Mariage-Samson R, Fayein NA et al (1999) The genexpress IMAGE knowledge base of the human brain transcriptome: a prototype integrated resource for functional and computational genomics. Genome Res 9:195–209

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Martin JA, Wang Z (2011) Next-generation transcriptome assembly. Nat Rev Genet 12:671–682

    Article  CAS  PubMed  Google Scholar 

  60. Metzker ML (2009) Sequencing technologies − the next generation. Nat Rev Genet 11:31–46

    Article  PubMed  Google Scholar 

  61. Varshney RK, Hoisington DA, Nayak SN, Graner A (2009a) Molecular plant breeding: methodology and achievements. In: Somers DJ, Langridge P, Gustafson JP (eds) Plant genomics-methods and protocols. Humana Press, New York, pp 283–304

    Google Scholar 

  62. Varshney RK, Nayak SN, May GD, Jackson SA (2009b) Next-generation sequencing technologies and their implications for crop genetics and breeding. Trends Biotechnol 27:522–530

    Article  CAS  PubMed  Google Scholar 

  63. Varshney RK, Bohra A, Roorkiwal M, Barmukh R, Cowling WA et al (2021) Fast-forward breeding for a food-secure world. Trends Genet 37(12):1124–1136

    Article  CAS  PubMed  Google Scholar 

  64. Dirks R, van Dun K, de Snoo CB, van den Berg M, Lelivelt CL, Voermans W et al (2009) Reverse breeding: a novel breeding approach based on engineered meiosis. Plant Biotechnol J 7(9):837–845

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Ma L, Kong F, Sun K, Wang T, Guo T (2021) From classical radiation to modern radiation: past, present, and future of radiation mutation breeding. Front Public Health 9:768071

    Article  PubMed  PubMed Central  Google Scholar 

  66. Gardner CO (1963) Estimates of genetic parameters in cross-fertilizing plants and their implications in plant breeding. In: Hanson WD, Robinson HF (eds) Statistical genetics and plant breeding. National Academy of Sciences—National Research Council, Washington, DC, pp 225–252

    Google Scholar 

  67. Matzinger DF (1963) Experimental estimates of genetic parameters and their applications in self-fertilizing plants. In: Hanson WD, Robinson HF (eds) Statistical genetics and plant breeding. National Academy of Sciences—National Research Council, Washington DC, pp 253–279

    Google Scholar 

  68. Hallauer AR, Miranda JB (1988) Quantitative genetics in maize breeding, 2nd edn. Iowa State University Press

    Google Scholar 

  69. Dudley JW, Moll RH (1969) Interpretation and use of estimates of heritability and genetic variances in plant breeding. Crop Sci 9:257–262

    Article  Google Scholar 

  70. Kearsey MJ, Farquhar AGL (1998) QTL analysis in plants; where are we now? Heredity 80:137–142

    Article  PubMed  Google Scholar 

  71. Bernardo R (2020) Breeding for quantitative traits in plants, 3rd edn. Stemma Press, Woodbury, MN

    Google Scholar 

  72. Collard BCY, Jahufer MZZ, Brouwer JB, Pang ECK (2005) An introduction to markers, quantitative trait loci (QTL) map** and marker-assisted selection for crop improvement: the basic concepts. Euphytica 142:169–196

    Article  CAS  Google Scholar 

  73. Bergelson J, Roux F (2010) Towards identifying genes underlying ecologically relevant traits in Arabidopsis thaliana. Nat Rev Genet 11:867–879

    Article  CAS  PubMed  Google Scholar 

  74. Mendez-Vigo B, Martinez-Zapater JM, Alonso-Blanco C (2013) The flowering repressor SVP underlies a novel Arabidopsis thaliana QTL interacting with the genetic background. PLoS Genet 9:e1003289

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Schlötterer C, Tobler R, Kofler R, Nolte V (2014) Sequencing pools of individuals — mining genome-wide polymorphism data without big funding. Nat Rev Genet 15:749–763

    Article  PubMed  Google Scholar 

  76. Sloan DB, Keller SR, Berardi AE, Sanderson BJ, Karpovich JF, Taylor DR (2012) De novo transcriptome assembly and polymorphism detection in the flowering plant Silene vulgaris (Caryophyllaceae). Mol Ecol Resour 12:333–343

    Article  CAS  PubMed  Google Scholar 

  77. Schneeberger K, Ossowski S, Lanz C, Juul T, Petersen AH, Nielsen KL et al (2009) SHOREmap: simultaneous map** and mutation identification by deep sequencing. Nat Methods 6:550–551. https://doi.org/10.1038/nmeth0809-550

    Article  CAS  PubMed  Google Scholar 

  78. Austin RS, Vidaurre D, Stamatiou G, Breit R, Provart NJ, Bonetta D et al (2011) Next-generation map** of Arabidopsis genes. Plant J 67:715–725

    Article  CAS  PubMed  Google Scholar 

  79. Uchida N, Sakamoto T, Kurata T, Tasaka M (2011) Identification of EMS-induced causal mutations in a non-reference Arabidopsis thaliana accession by whole genome sequencing. Plant Cell Physiol 52:716–722. https://doi.org/10.1093/pcp/pcr029

    Article  CAS  PubMed  Google Scholar 

  80. Abe A, Kosugi S, Yoshida K, Natsume S, Takagi H, Kanzaki H et al (2012) Genome sequencing reveals agronomically important loci in rice using MutMap. Nat Biotechnol 30:174–178

    Article  CAS  PubMed  Google Scholar 

  81. Hartwig B, James GV, Konrad K, Schneeberger K, Turck F (2012) Fast isogenic map**-by-sequencing of ethyl methanesulfonate-induced mutant bulks. Plant Physiol 160:591–600. https://doi.org/10.1104/pp.112.200311

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Lindner H, Raissig MT, Sailer C, Shimosato-Asano H, Bruggmann R, Grossniklaus U (2012) SNP-ratio map** (SRM): identifying lethal alleles and mutations in complex genetic backgrounds by next-generation sequencing. Genetics 191:1381–1386. https://doi.org/10.1534/genetics.112.141341

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Fekih R, Takagi H, Tamiru M, Abe A, Natsume S, Yaegashi H et al (2013) MutMap plus: genetic map** and mutant identification without crossing in rice. PLoS One 8:e68529. https://doi.org/10.1371/journal.pone.0068529

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Takagi H, Uemura A, Yaegashi H, Tamiru M, Abe A, Mitsuoka C et al (2013b) MutMap-gap: whole-genome resequencing of mutant F2 progeny bulk combined with de novo assembly of gap regions identifies the rice blast resistance gene Pii. New Phytol 200:276–283. https://doi.org/10.1111/nph.12369

    Article  CAS  PubMed  Google Scholar 

  85. Takagi H, Tamiru M, Abe A, Yoshida K, Uemura A, Yaegashi H et al (2015) MutMap accelerates breeding of a salt-tolerant rice cultivar. Nat Biotechnol 33:445–449. https://doi.org/10.1038/nbt.3188

    Article  CAS  PubMed  Google Scholar 

  86. Zheng W, Wang Y, Wang L, Ma Z, Zhao J, Wang P et al (2016) Genetic map** and molecular marker development for Pi65(t), a novel broad-spectrum resistance gene to rice blast using next-generation sequencing. Theor Appl Genet 129:1035–1044. https://doi.org/10.1007/s00122-016-2681-7

    Article  CAS  PubMed  Google Scholar 

  87. Liu SZ, Yeh CT, Tang HM, Nettleton D, Schnable PS (2012) Gene map** via bulked segregant RNA-Seq (BSR-Seq). PLoS One 7:e36406. https://doi.org/10.1371/journal.pone.0036406

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Haase NJ, Beissinger T, Hirsch CN, Vaillancourt B, Deshpande S, Barry K et al (2015) Shared genomic regions between derivatives of a large segregating population of maize identified using bulked segregant analysis sequencing and traditional linkage analysis. G3 (Bethesda) 5:1593–1602. https://doi.org/10.1534/g3.115.017665

    Article  CAS  PubMed  Google Scholar 

  89. Mascher M, Jost M, Kuon JE, Himmelbach A, Assfalg A, Beier S et al (2014) Map**-by-sequencing accelerates forward genetics in barley. Genome Biol 15:R78. https://doi.org/10.1186/Gb-2014-15-6-R78

    Article  PubMed  PubMed Central  Google Scholar 

  90. Campbell BW, Hofstad AN, Sreekanta S, Fu F, Kono TJY, O’Rourke JA et al (2016) Fast neutron-induced structural rearrangements at a soybean NAP1 locus result in gnarled trichomes. Theor Appl Genet 129:1725–1738

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Dobbels AA, Michno JM, Campbell BW, Virdi KS, Stec AO, Muehlbauer GJ et al (2017) An induced chromosomal translocation in soybean disrupts a KASI ortholog and is associated with a high-sucrose and low-oil seed phenotype. G3 (Bethesda) 7:1215–1223

    Article  CAS  PubMed  Google Scholar 

  92. Kover PX, Rowntree JK, Scarcelli N, Savriama Y, Eldridge T, Schaal BA (2009) Pleiotropic effects of environment-specific adaptation in Arabidopsis thaliana. New Phytol 183:816–825

    Article  CAS  PubMed  Google Scholar 

  93. Pascual L, Desplat N, Huang BE, Desgroux A, Bruguier L et al (2015) Potential of a tomato MAGIC population to decipher the genetic control of quantitative traits and detect causal variants in the resequencing era. Plant Biotechnol J 13:565–577

    Article  CAS  PubMed  Google Scholar 

  94. Huang BE, George AW, Forrest KL, Kilian A, Hayden MJ, Morell M, Cavanagh C (2012) A multiparent advanced generation inter-cross population for genetic analysis in wheat. Plant Biotechnol J 10(7):826–839

    Article  CAS  PubMed  Google Scholar 

  95. Mackay IJ, Bansept-Basler P, Barber T, Bentley AR, Cockram J, Gosman N, Greenland AJ, Horsnell R, Howells RM, O’Sullivan DM, Rose GA, Howell P (2014) An eight-parent multiparent advanced generation inter-cross population for winter-sown wheat: creation, properties, and validation. G3 (Bethesda) 4:1603–1610

    Article  PubMed  Google Scholar 

  96. Holland JB (2015) MAGIC maize: a new resource for plant genetics. Genome Biol 16:163

    Article  PubMed  PubMed Central  Google Scholar 

  97. Bandillo NB, Raghavan C, Muyco PA, Sevilla MA, Lobina IT, Dilla-Ermita CJ, Tung C, Mccouch S, Thomson MJ, Mauleon R, Singh RK, Gregorio GB, Redoña ED, Leung H (2013) Multi-parent advanced generation inter-cross (MAGIC) populations in rice: progress and potential for genetics research and breeding. Rice (N Y) 6:11

    Article  PubMed  Google Scholar 

  98. Gaur PM, Jukanti AK, Varshney RK (2012) Impact of genomic technologies on chickpea breeding strategies. Agronomy 2:199–221

    Article  Google Scholar 

  99. Su J, Wu R (2004) Stress-inducible synthesis of proline in transgenic rice confers faster growth under stress conditions than that with constitutive synthesis. Plant Sci 166(4):941–948

    Article  CAS  Google Scholar 

  100. Fahad S, Bajwa AA, Nazir U, Anjum SA, Farooq A, Zohaib A et al (2017) Crop production under drought and heat stress: plant responses and management options. Front Plant Sci 8:1147

    Article  PubMed  PubMed Central  Google Scholar 

  101. Ghneim-Herrera T, Selvaraj MG, Meynard D, Fabre D, Pena A, Ben Romdhane W et al (2017) Expression of the Aeluropus littoralis AlSAP gene enhances rice yield under field drought at the reproductive stage. Front Plant Sci 8:994

    Article  PubMed  PubMed Central  Google Scholar 

  102. Li J, Li Y, Yin Z, Jiang J, Zhang M, Guo X et al (2017) OsASR5 enhances drought tolerance through a stomatal closure pathway associated with ABA and H2O2 signalling in rice. Plant Biotechnol J 15:183–196

    Article  CAS  PubMed  Google Scholar 

  103. Liu X, Li X, Dai C, Zhou J, Yan T, Zhang J (2017) Improved short-term drought response of transgenic rice over-expressing maize C4 phosphoenolpyruvate carboxylase via calcium signal cascade. J Plant Physiol 218:206–221

    Article  CAS  PubMed  Google Scholar 

  104. Sadhu MJ, Bloom JS, Day L, Kruglyak L (2016) CRISPR-directed mitotic recombination enables genetic map** without crosses. Science 352:1113–1116

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Arora L, Narula A (2017) Gene editing and crop improvement using CRISPR-Cas9 system. Front Plant Sci 8:1932

    Article  PubMed  PubMed Central  Google Scholar 

  106. Jaganathan D, Ramasamy K, Sellamuthu G, Jayabalan S, Venkataraman G (2018) CRISPR for crop improvement: an update review. Front Plant Sci 9:985

    Article  PubMed  PubMed Central  Google Scholar 

  107. Chen SJ (2019) Minimizing off-target effects in CRISPR-Cas9 genome editing. Cell Biol Toxicol 35:399–401

    Article  PubMed  PubMed Central  Google Scholar 

  108. Varshney RK, Pandey MK, Bohra A et al (2019) Towards sequence-based breeding in legumes in post-genome sequencing era. Theor Appl Genet 132:797–816

    Article  CAS  PubMed  Google Scholar 

  109. Khan MA (2012) Current status of genomic based approaches to enhance drought tolerance in rice (Oryza sativa L.), an over view. Mol Plant Breed 3(1):1–10

    Google Scholar 

  110. Shamsudin NA, Swamy BM, Ratnam W, Cruz MT, Raman A, Kumar A (2016) Marker assisted pyramiding of drought yield QTLs into a popular Malaysian rice cultivar, MR219. BMC Genet 17(1):30

    Article  PubMed  PubMed Central  Google Scholar 

  111. Provart NJ, Alonso J, Assmann SM, Bergmann D, Brady SM et al (2016) 50 years of Arabidopsis research: highlights and future directions. New Phytol 209:921–944

    Article  CAS  PubMed  Google Scholar 

  112. Huang X, Han B (2014) Natural variations and genome-wide association studies in crop plants. Annu Rev Plant Biol 65:531–551

    Article  CAS  PubMed  Google Scholar 

  113. Huang X, Wei X, Sang T, Zhao Q, Feng Q, Zhao Y, Li C, Zhu C, Lu T, Zhang Z, Li M, Fan D, Guo Y, Wang A, Wang L, Deng L, Li W, Lu Y, Weng Q, Liu K, Huang T, Zhou T, **g Y, Li W, Lin Z, Buckler ES, Qian Q, Zhang Q, Li J, Han B (2010) Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet 42:961–967

    Article  CAS  PubMed  Google Scholar 

  114. Tian F, Bradbury PJ, Brown PJ, Hung H, Sun Q, Flint-Garcia SA, Rocheford T, McMullen MD, Holland JB, Buckler ES (2011) Genome-wide association study of leaf architecture in the maize nested association map** population. Nat Genet 43:159–162

    Article  CAS  PubMed  Google Scholar 

  115. Jia G, Huang X, Zhi H, Zhao Y, Zhao Q, Li W, Chai Y, Yang L, Liu K, Lu H, Zhu C, Lu Y et al (2013) A haplotype map of genomic variations and genome-wide association studies of agronomic traits in foxtail millet (Setaria italica). Nat Genet 45:957–961

    Article  CAS  PubMed  Google Scholar 

  116. Ramakrishnan M, Antony Ceasar S, Duraipandiyan V, Vinod KK, Kalpana K, Al-Dhabi NA, Ignacimuthu S (2016) Tracing QTLs for leaf blast resistance and agronomic performance of finger millet (Eleusine coracana (L.) Gaertn.) genotypes through association map** and in silico comparative genomics analyses. PLoS One 11:e0159264

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Shakoor N, Ziegler G, Dilkes BP, Brenton ZW, Boyles RE, Connolly EL, Kresovich S, Baxter IR (2015) Integration of experiments across diverse environments identifies the genetic determinants of variation in Sorghum bicolor seed element composition. bioRxiv

    Google Scholar 

  118. Iwata H, Minamikawa MF, Kajiya-Kanegae H, Ishimori M, Hayashi T (2016) Genomics-assisted breeding in fruit trees. Breed Sci 66:100–115

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Huang X, Zhao Y, Wei X, Li C, Wang A, Zhao Q, Li W, Guo Y, Deng L, Zhu C, Fan D, Lu Y, Weng Q, Liu K, Zhou T, **g Y, Si L, Dong G, Huang T, Lu T, Feng Q, Qian Q, Li J, Han B (2012) Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nat Genet 44:32–39

    Article  Google Scholar 

  120. Wallace JG, Bradbury PJ, Zhang N, Gibon Y, Stitt M, Buckler ES (2014) Association map** across numerous traits reveals patterns of functional variation in maize. PLoS Genet 10:e1004845

    Article  PubMed  PubMed Central  Google Scholar 

  121. Yang N, Lu Y, Yang X, Huang J, Zhou Y, Ali F, Wen W, Liu J, Li J, Yan J (2014) Genome wide association studies using a new nonparametric model reveal the genetic architecture of 17 agronomic traits in an enlarged maize association panel. PLoS Genet 10:e1004573

    Article  PubMed  PubMed Central  Google Scholar 

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Mukhopadhyay, R., Nath, S., Kumar, D., Sahana, N., Mandal, S. (2024). Basics of the Molecular Biology: From Genes to Its Function. In: Anjoy, P., Kumar, K., Chandra, G., Gaikwad, K. (eds) Genomics Data Analysis for Crop Improvement. Springer Protocols Handbooks. Springer, Singapore. https://doi.org/10.1007/978-981-99-6913-5_14

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  • DOI: https://doi.org/10.1007/978-981-99-6913-5_14

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