Marker breeding of white cabbage

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Abstract

Modern accelerated development of agricultural production actualizes the development of new technologies aimed at more economical and environmentally friendly production of high-quality products with specified quality and properties. In this regard, the method of molecular markers, which significantly increases the efficiency of breeding, is gaining wide popularity and demand. The technology of marker-­assisted selection accelerates selection of the required characteristics of plants at early stages of their development until their manifestation in the adult state, increasing its efficiency regardless of the environment influence. This technology is widely applied to a huge range of crops, including white cabbage. This crop is cultivated over significant areas worldwide and is important due to its high demand and health benefits. Although a significant number of new varieties and hybrids of white cabbage with individual characteristics have been developed by breeders to date, the demand for increasing its yield is becoming increasingly high. Therefore, interest in molecular marker-­assisted breeding is increasing and manipulation of agronomic and economically important traits of promising lines is becoming relevant. The lack of generalizations of material in this area is essential. Therefore, the aim of this work was to review the current state of the issue, to identify the main and most demanded directions of research in the field of marker technology in application to white cabbage and to draw attention to this currently relevant topic. Accordingly, we conducted a search and systematic review of available modern specialized literature and relevant recent scientific data over the last two decades on marker-­mediated breeding of white cabbage. In the study, markers of biotic and abiotic stress as well as quality of white cabbage were analyzed. As the collected information on markers shows, scientific research in these areas is prioritized but poorly covered in the literature. A very small proportion of promising KASP markers was observed, as well as insufficient research on the different ripeness groups of white cabbage varieties. The systematization of the available knowledge with emphasis on problem areas undertaken in this review may be important and useful for breeders and producers for their practical application in practice.

About the authors

Sergey A. Bursakov

All-Russian Research Institute of Agricultural Biotechnology

Author for correspondence.
Email: sergeymoscu@gmail.com
ORCID iD: 0000-0001-5647-9901
SPIN-code: 9864-0118

Candidate of Biological Sciences, Senior Researcher, Laboratory of Genetic Technologies and Molecular Support for Breeding of Grain and Leguminous Crops

42 Timiryazevskaya st., Moscow, 127550, Russian Federation

Gennady I. Karlov

All-Russian Research Institute of Agricultural Biotechnology

Email: karlov@gmail.com
ORCID iD: 0000-0002-9016-103X
SPIN-code: 7043-2727

Doctor of Biological Sciences, Professor, Academician of the Russian Academy of Sciences, Director

42 Timiryazevskaya st., Moscow, 127550, Russian Federation

Petr N. Kharchenko

All-Russian Research Institute of Agricultural Biotechnology

Email: iab@iab.ac.ru
ORCID iD: 0000-0002-6036-5875
SPIN-code: 8509-0240

Doctor of Biological Sciences, Professor, Academician of the Russian Academy of Sciences, Scientific Advisor

42 Timiryazevskaya st., Moscow, 127550, Russian Federation

References

  1. Jo J, Kang MY, Kim KS, Youk HR, Shim E-J, Kim H, et al. Genome-wide analysis-­based single nucleotide polymorphism marker sets to identify diverse genotypes in cabbage cultivars (Brassica oleracea var. capitata). Sci Rep. 2022;12(1):20030. doi: 10.1038/s41598-022-24477‑y
  2. Rokayya S, Li C-J, Zhao Y, Li Y, Sun C-H. Cabbage (Brassica oleracea L. var. capitata) phytochemicals with antioxidant and anti-inflammatory potential. Asian Pacific J Cancer Prev. 2013;14(11):6657—6662. doi: 10.7314/apjcp.2013.14.11.6657
  3. Lv H, Fang Z, Yang L, Zhang Y, Wang Y. An update on the arsenal: mining resistance genes for disease management of Brassica crops in the genomic era. Hortic Res. 2020;7(1):34. doi: 10.1038/s41438-020-0257-9
  4. Raza A, Razzaq A, Mehmood SS, Hussain MA, Wei S, He H, Zaman QU, et al. Omics: The way forward to enhance abiotic stress tolerance in Brassica napus L. GM Crops Food. 2021;12(1):251—281. doi: 10.1080/21645698.2020.1859898
  5. Liu S, Liu Y, Yang X, Tong C, Edwards D, Parkin IAP, et al. The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes. Nat Commun. 2014;5(1):3930. doi: 10.1038/ncomms4930
  6. Ishii T, Yonezawa K. Optimization of the marker‐based procedures for pyramiding genes from multiple donor lines: II. Strategies for selecting the objective homozygous plant. Crop Sci. 2007;47(5):1878—1886. doi: 10.2135/cropsci2006.11.0750
  7. Litvinov DY, Chernook AG, Kroupin PY, Bazhenov MS, Karlov GI, Avdeev SM, et al. A Convenient Co-­Dominant Marker for Height-­Reducing Ddw1 Allele Useful for Marker-­Assisted Selection. Agriculture. 2020;10(4):110. doi: 10.3390/agriculture10040110
  8. Bazhenov MS, Divashuk MG, Amagai Y, Watanabe N, Karlov GI. Isolation of the dwarfing Rht-­B1p (Rht17) gene from wheat and the development of an allele-­specific PCR marker. Mol Breed. 2015;35(11):213. doi: 10.1007/s11032-015-0407-1
  9. Razumova OV, Bazhenov MS, Nikitina EA, Nazarova LA, Romanov D, Chernook AG, et al. Molecular analysis of gibberellin receptor gene GID1 in Dasypyrum villosum and development of DNA marker for its identification. RUDN Journal of Agronomy and Animal Industries. 2020;15(1):62—85. doi: 10.22363/2312-797X‑2020-15-1-62-85
  10. Parkash C, Kumar S, Thakur N, Singh S, Sharma BB. Cabbage: Breeding and Genomics. Veg Sci. 2023;50(Special):231—243. doi: 10.61180/vegsci.2023.v50.spl.09
  11. Bazhenov MS, Bespalova LA, Kocheshkova AA, Chernook AG, Puzyrnaya OY, Agaeva EV, et al. The association of grain yield and agronomical traits with genes of plant height, photoperiod sensitivity and plastid glutamine synthetase in winter bread wheat (Triticum aestivum L.) collection. Int J Mol Sci. 2022;23(19):11402. doi: 10.3390/ijms231911402
  12. Berensen FA, Antonova OY, Artemyeva АM. Molecular-­genetic marking of Brassica L. species for resistance against various pathogens: achievements and prospects. Vavilov J Genet Breed. 2019;23(6):656—666. doi: 10.18699/VJ19.538
  13. Collard BC, Mackill DJ. Marker-­assisted selection: an approach for precision plant breeding in the twenty-­first century. Philos Trans R Soc B Biol Sci. 2008;363(1491):557—572. doi: 10.1098/rstb.2007.2170
  14. Xiao Z, Kong C, Han F, Yang L, Zhuang M, Zhang Y, et al. Two user-friendly molecular markers developed for the identification of hybrid lethality genes in Brassica oleracea. Agronomy. 2021;11(5):982. doi: 10.3390/agronomy11050982
  15. Lister DL, Jones H, Jones MK, O’Sullivan DM, Cockram J. Analysis of DNA polymorphism in ancient barley herbarium material: Validation of the KASP SNP genotyping platform. Taxon. 2013;62(4):779—789. doi: 10.12705/624.9
  16. Cramer GR, Urano K, Delrot S, Pezzotti M, Shinozaki K. Effects of abiotic stress on plants: a systems biology perspective. BMC Plant Biol. 2011;11(1):163. doi: 10.1186/1471-2229-11-163
  17. Xin Z, Browse J. Cold comfort farm: the acclimation of plants to freezing temperatures. Plant Cell Environ. 2000;23(9):893—902. doi: 10.1046/j.1365-3040.2000.00611.x
  18. Maibam P, Nawkar GM, Park JH, Sahi VP, Lee SY, Kang CH. The influence of light quality, circadian rhythm, and photoperiod on the CBF-mediated freezing tolerance. Int J Mol Sci. 2013;14(6):11527—11543. doi: 10.3390/ijms140611527
  19. Mickelbart MV, Hasegawa PM, Bailey-­Serres J. Genetic mechanisms of abiotic stress tolerance that translate to crop yield stability. Nat Rev Genet. 2015;16(4):237—251. doi: 10.1038/nrg3901
  20. Jha UC, Bohra A, Jha R. Breeding approaches and genomics technologies to increase crop yield under low-temperature stress. Plant Cell Rep. 2017;36(1):1—35. doi: 10.1007/s00299-016-2073-0
  21. Thomashow MF. Plant cold acclimation: freezing tolerance genes and regulatory mechanisms. Annu Rev Plant Physiol Plant Mol Biol. 1999;50(1):571—599. doi: 10.1146/annurev.arplant.50.1.571
  22. Kole C, Thormann CE, Karlsson BH, Palta JP, Gaffney P, Yandell B, et al. Comparative mapping of loci controlling winter survival and related traits in oilseed Brassica rapa and B. napus. Mol Breed. 2002;9:201—210. doi: 10.1023/A:1019759512347
  23. Song H, Kim HR, Hwang B-H, Yi H, Hur Y. Natural variation in glycine-rich region of Brassica oleracea cold shock domain protein 5 (BoCSDP5) is associated with low temperature tolerance. Genes Genomics. 2020;42(12):1407—1417. doi: 10.1007/s13258-020-01010‑x
  24. Karlson D, Imai R. Conservation of the cold shock domain protein family in plants. Plant Physiol. 2003;131(1):12—15. doi: 10.1104/pp.014472
  25. Li Q, Peng A, Yang J, Zheng S, Li Z, Mu Y, et al. A 215‑bp indel at intron I of BoFLC2 affects flowering time in Brassica oleracea var. capitata during vernalization. Theor Appl Genet. 2022;135(8):2785—2797. doi: 10.1007/s00122-022-04149-1
  26. Abuyusuf Md, Nath UK, Kim H-T, Islam Md.R, Park J-I, Nou III-S. Molecular markers based on sequence variation in BoFLC1.C9 for characterizing early- and late-flowering cabbage genotypes. BMC Genet. 2019;20(1):42. doi: 10.1186/s12863-019-0740-1
  27. Wang P, Li Z, Zhu L, Cheng M, Chen X, Wang A, et al. Fine mapping and identification of a candidate gene for the glossy green trait in cabbage (Brassica oleracea var. capitata). Plants. 2023;12(18):3340. doi: 10.3390/plants12183340
  28. Mariani M, Wolters-­Arts M. Complex Waxes. Plant Cell. 2000;12(10):1795—1798. doi: 10.1105/tpc.12.10.1795
  29. Kunst L, Samuels AL. Biosynthesis and secretion of plant cuticular wax. Prog Lipid Res. 2003;42(1):51—80. doi: 10.1016/S0163-7827(02)00045-0
  30. Kerstiens G. Cuticular water permeability and its physiological significance. J Exp Bot. 1996;47(12):1813—1832. doi: 10.1093/jxb/47.12.1813
  31. Barthlott W, Neinhuis C, Cutler D, Ditsch F, Meusel I, Theisen I, et al. Classification and terminology of plant epicuticular waxes. Bot J Linn Soc. 1998;126(3):237—260. doi: 10.1006/bojl.1997.0137
  32. Koch K, Ensikat H-J. The hydrophobic coatings of plant surfaces: Epicuticular wax crystals and their morphologies, crystallinity and molecular self-assembly. Micron. 2008;39(7):759—772. doi: 10.1016/j.micron.2007.11.010
  33. Koch K, Bhushan B, Barthlott W. Multifunctional surface structures of plants: An inspiration for biomimetics. Prog Mater Sci. 2009;54(2):137—178. doi: 10.1016/j.pmatsci.2008.07.003
  34. Liu Z, Fang Z, Zhuang M, Zhang Y, Lv H, Liu Y, et al. Fine-mapping and analysis of Cgl1, a gene conferring glossy trait in cabbage (Brassica oleracea L. var. capitata). Front Plant Sci. 2017;8:239. doi: 10.3389/fpls.2017.00239
  35. Li JT, Yang LM, Fang ZY, Liu YM, Zhuang M, Zhang YY, et al. First exploration on genetic law of glossy wax-less characteristics on cabbage (Brassica oleracea L. var. capitata L.) material 10Q‑961. China Veg. 2012;(12):37—41.
  36. Ji J, Cao W, Tong L, Fang Z, Zhang Y, Zhuang M, et al. Identification and validation of an ECERIFERUM2- LIKE gene controlling cuticular wax biosynthesis in cabbage (Brassica oleracea L. var. capitata L.). Theor Appl Genet. 2021;134:4055—4066. doi: 10.1007/s00122-021-03947-3
  37. Liu D, Dong X, Liu Z, Tang J, Zhuang M, Zhang Y, et al. Fine mapping and candidate gene identification for wax biosynthesis locus, BoWax1 in Brassica oleracea L. var. capitata. Front Plant Sci. 2018;9:309. doi: 10.3389/fpls.2018.00309
  38. Liu D, Tang J, Liu Z, Dong X, Zhuang M, Zhang Y, et al. Fine mapping of BoGL1, a gene controlling the glossy green trait in cabbage (Brassica oleracea L. var. capitata). Mol Breed. 2017;37:69. doi: 10.1007/s11032-017-0674-0
  39. Dong X, Ji J, Yang L, Fang Z, Zhuang M, Zhang Y, et al. Fine-mapping and transcriptome analysis of BoGL‑3, a wax-less gene in cabbage (Brassica oleracea L. var. capitata). Mol Genet Genomics. 2019;294:1231—1239. doi: 10.1007/s00438-019-01577-5
  40. Lee SB, Suh MC. Advances in the understanding of cuticular waxes in Arabidopsis thaliana and crop species. Plant Cell Rep. 2015;34:557—572. doi: 10.1007/s00299-015-1772-2
  41. Su Y, Liu Y, Li Z, Fang Z, Yang L, Zhuang M, et al. QTL Analysis of head splitting resistance in cabbage (Brassica oleracea L. var. capitata) using SSR and InDel makers based on whole-­genome re-sequencing. PLoS One. 2015;10(9): e0138073. doi: 10.1371/journal.pone.0138073
  42. Pang W, Li X, Choi SR, Nguyen VD, Dhandapani V, Kim YY, et al. Mapping QTLs of resistance to head splitting in cabbage (Brassica oleracea L.var. capitata L.). Mol Breed. 2015;35:126. doi: 10.1007/s11032-015-0318-1
  43. Parmar SS, Ravindra IH, Kumar R. Accelerated approaches for cabbage improvement. In: El-­Esawi MA. (ed.) Recent trends in plant breeding and genetic improvement. 2023. doi: 10.5772/intechopen.1002526
  44. Neik TX, Barbetti MJ, Batley J. Current status and challenges in identifying disease resistance genes in Brassica napus. Front Plant Sci. 2017;8:1788. doi: 10.3389/fpls.2017.01788
  45. Yerasu SR, Murugan L, Halder J, Prasanna HC, Singh A, Singh B. Screening tomato genotypes for resistance to early blight and American serpentine leafminer. Hortic Environ Biotechnol. 2019;60:427—433. doi: 10.1007/s13580-019-00130‑y
  46. Vicente JG, Holub EB. Xanthomonas campestris pv. campestris (cause of black rot of crucifers) in the genomic era is still a worldwide threat to brassica crops. Mol Plant Pathol. 2013;14(1):2—18. doi: 10.1111/j.1364-3703.2012.00833.x
  47. Fargier E, Manceau C. Pathogenicity assays restrict the species Xanthomonas campestris into three pathovars and reveal nine races within X. campestris pv. campestris. Plant Pathol. 2007;56(5):805—818. doi: 10.1111/j.1365-3059.2007.01648.x
  48. Dangl JL, Jones JD. Plant pathogens and integrated defence responses to infection. Nature. 2001;411:826—833. doi: 10.1038/35081161
  49. Dubos C, Kelemen Z, Sebastian A, Bülow L, Huep G, Xu W, et al. Integrating bioinformatic resources to predict transcription factors interacting with cis-sequences conserved in co-regulated genes. BMC Genomics. 2014;15(1):317. doi: 10.1186/1471-2164-15-317
  50. Van Der Biezen EA, Jones JDG. Plant disease-­resistance proteins and the gene-for-gene concept. Trends Biochem Sci. 1998;23(12):454—456. doi: 10.1016/s0968-0004 (98) 01311-5
  51. Bent AF, Mackey D. Elicitors, effectors, and R genes: the new paradigm and a lifetime supply of questions. Annu Rev Phytopathol. 2007;45:399—436. doi: 10.1146/annurev.phyto.45.062806.094427
  52. Wan H, Yuan W, Bo K, Shen J, Pang X, Chen J. Genome-wide analysis of NBS-encoding disease resistance genes in Cucumis sativus and phylogenetic study of NBS-encoding genes in Cucurbitaceae crops. BMC Genomics. 2013;14:109. doi: 10.1186/1471-2164-14-109
  53. Mehraj H, Akter A, Miyaji N, Miyazaki J, Shea DJ, Fujimoto R, et al. Genetics of Clubroot and Fusarium Wilt Disease Resistance in Brassica Vegetables: The application of marker assisted breeding for disease resistance. Plants. 2020;9(6):726. doi: 10.3390/plants9060726
  54. Hirani AH, Gao F, Liu J, Fu G, Wu C, Yuan Y, et al. Transferring clubroot resistance from Chinese cabbage (Brassica rapa) to canola (B. napus). Can J Plant Pathol. 2016;38(1):82—90. doi: 10.1080/07060661.2016.1141799
  55. Sato M, Shimizu M, Shea DJ, Hoque M, Kawanabe T, Miyaji N, et al. Allele specific DNA marker for fusarium resistance gene FocBo1 in Brassica oleracea. Breed Sci. 2019;69(2):308—315. doi: 10.1270/jsbbs.18156
  56. Dakouri A, Zhang X, Peng G, Falk KC, Gossen BD, Strelkov SE, et al. Analysis of genome-wide variants through bulked segregant RNA sequencing reveals a major gene for resistance to Plasmodiophora brassicae in Brassica oleracea. Sci Rep. 2018;8:17657. doi: 10.1038/s41598-018-36187-5
  57. Peng L, Zhou L, Li Q, Wei D, Ren X, Song H, et al. Identification of quantitative trait loci for clubroot resistance in Brassica oleracea with the use of Brassica SNP microarray. Front Plant Sci. 2018;9:822. doi: 10.3389/fpls.2018.00822
  58. Tomita H, Shimizu M, Asad-ud Doullah M, Fujimoto R, Okazaki K. Accumulation of quantitative trait loci conferring broad-­spectrum clubroot resistance in Brassica oleracea. Mol Breed. 2013;32:889—900. doi: 10.1007/s11032-013-9918-9
  59. Nagaoka T, Doullah MAU, Matsumoto S, Kawasaki S, Ishikawa T, Hori H, et al. Identification of QTLs that control clubroot resistance in Brassica oleracea and comparative analysis of clubroot resistance genes between B. rapa and B. oleracea. Theor Appl Genet. 2010;120:1335—1346. doi: 10.1007/s00122-010-1259‑z
  60. Farid M, Yang RC, Kebede B, Rahman H. Evaluation of Brassica oleracea accessions for resistance to Plasmodiophora brassicae and identification of genomic regions associated with resistance. Genome. 2020;63(2):91—101. doi: 10.1139/gen‑2019-0098
  61. Liu X, Han F, Kong C, Fang Z, Yang L, Zhang Y, et al. Rapid introgression of the fusarium wilt resistance gene into an elite cabbage line through the combined application of a microspore culture, genome background analysis, and disease resistance-­specific marker assisted foreground selection. Front Plant Sci. 2017;8:354. doi: 10.3389/fpls.2017.00354
  62. Pu ZJ, Shimizu M, Zhang YJ, Nagaoka T, Hayashi T, Hory H, et al. Genetic mapping of a fusarium wilt resistance gene in Brassica oleracea. Mol Breed. 2012;30(2):809—818. doi: 10.1007/s11032-011-9665-8
  63. Lv HH, Yang LM, Kang JG, Wang QB, Wang XW, Fang ZY, et al. Development of InDel markers linked to Fusarium wilt resistance in cabbage. Mol Breed. 2013;32(4):961—967. doi: 10.1007/s11032-013-9925‑x
  64. Lv H, Fang Z, Yang L, Zhang Y, Wang Q, Liu Y, et al. Mapping and analysis of a novel candidate Fusarium wilt resistance gene FOC1 in Brassica oleracea. BMC Genomics. 2014;15:1094. doi: 10.1186/1471-2164-15-1094
  65. Lv HH, Wang QB, Yang LM, Fang ZY, Liu YM, Zhuang M, et al. Breeding of cabbage (Brassica oleracea L. var. capitata) with fusarium wilt resistance based on microspore culture and marker-­assisted selection. Euphytica. 2014;200:465—473. doi: 10.1007/s10681-014-1197‑y
  66. Yu HL, Fang ZY, Liu YM, Yang LM, Zhuang M, Lv HH, et al. Development of a novel allele-­specific Rfo marker and creation of Ogura CMS fertility-­restored interspecific hybrids in Brassica oleracea. Theor Appl Genet. 2016;129:1625—1637. doi: 10.1007/s00122-016-2728-9
  67. Yu HL, Li ZY, Yang LM, Liu YM, Zhuang M, Zhang LG, et al. Morphological and molecular characterization of the second backcross progenies of Ogu-­CMS Chinese kale and rapeseed. Euphytica. 2017;213:55. doi: 10.1007/s10681-017-1842-3
  68. Kawamura K, Kawanabe T, Shimizu M, Okazaki K, Kaji M, Dennis ES, et al. Genetic characterization of inbred lines of Chinese cabbage by DNA markers; towards the application of DNA markers to breeding of F1 hybrid cultivars. Data Br. 2016;6:229—237. doi: 10.1016/j.dib.2015.11.058
  69. Shimizu M, Pu ZJ, Kawanabe T, Kitashiba H, Matsumoto S, Ebe Y, et al. Map-based cloning of a candidate gene conferring Fusarium yellows resistance in Brassica oleracea. Theor Appl Genet. 2015;128:119—130. doi: 10.1007/s00122-014-2416-6
  70. Kawamura K, Shimizu M, Kawanabe T, Pu Z, Kodama T, Kaji M, et al. Assessment of DNA markers for seed contamination testing and selection of disease resistance in cabbage. Euphytica. 2017;213:28. doi: 10.1007/s10681-016-1821-0
  71. Akter MA, Mehraj H, Itabashi T, Shindo T, Osaka M, Akter A, et al. Breeding for disease resistance in Brassica vegetables using DNA marker selection. In: Brassica Breeding and Biotechnology. IntechOpen; 2021. p.127—142. doi: 10.5772/intechopen.96263
  72. Williams PH. Black rot: a continuing threat to world crucifers. Plant Dis. 1981;64(8):736—742. doi: 10.1094/PD‑64-736
  73. Hong JE, Afrin KS, Rahim MA, Jung HJ, Nou IS. Inheritance of black rot resistance and development of molecular marker linked to Xcc races 6 and 7 resistance in cabbage. Plants. 2021;10(9):1940. doi: 10.3390/plants10091940
  74. Afrin KS, Rahim MA, Park JI, Natarajan S, Kim HT, Nou IS. Identification of NBS-encoding genes linked to black rot resistance in cabbage (Brassica oleracea var. capitata). Mol Biol Rep. 2018;45:773—785. doi: 10.1007/s11033-018-4217-5

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