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Cytoplasmic Genome Prediction in Cucumber (Cucumis sativus L.) Hybrid Variety Breeding

Year 2023, Volume: 9 Issue: 1, 19 - 23, 01.02.2023

Abstract

Breeding studies in Cucurbitaceae species take a long time. It has become necessary to shorten the time and support
traditional breeding methods with modern biotechnological methods to get qualified domestic cucumber varieties.
Cytoplasmic genome prediction within the scope of molecular-based breeding is a very important application. To increase
heterosis in test crosses, reciprocal ‘double way’ crosses can be made as well as single crosses. Cytoplasmic organelles
‘plastid and mitochondria’ are considered to be different from each other between individuals and reciprocal crosses are
made based on this idea. However it significantly increases the labor. In this study, 4 plastid genome regions (rbcL, psbtrnS, trnHK, trnSt) located within non-conserved regions therefore expected to be variable of 50 donor genotypes were
sequenced, analyzed and their cytoplasmic genome prediction was estimated. A total of 6300 bp including four plastid
regions indicated no polyfmorphism and all sequences were identical among the 50 donor genotypes analyzed. This may
imply no cytoplasmic organelle variation. In conclusion, reciprocal crosses were excluded from our breeding studies. So
cytoplasmic genome prediction can provide rapidity and savings in breeding by eliminating unnecessary reciprocal test
crosses.

References

  • Acquaah G, (2012). Principles of Plant Genetics and Breeding: Breeding Cucumber. 2. New York: Wiley; pp. 676–681
  • Alverson AJ, Rice DW, Dickinson S, Barry K. and Palmer JD, (2011). Origins and recombination of the bacterial-sized multichromosomal mitochondrial genome of cucumber. Plant Cell 23, 2499–2513.
  • Behera TK, Staub JE, Behera S, Delannay IY, Chen JF, (2011). Marker-assisted backcross selection in an interspecific Cucumis population broadens the genetic base of cucumber (Cucumis sativus L.). Euphytica 178, 261-272.
  • Doyle JJ and Doyle JL, (1990). Isolation of plant DNA from fresh tissue. Focus 12, 13–15.
  • Duangjit J, Causse M, and Sauvage C, (2016). Efficiency of genomic selection for tomato fruit quality. Mol. Breed. 36:29.
  • FAO, (2020). FAO of the United Nations. FAOSTAT, http://www.fao.org/faostat/en/#data/QC Accessed 05 February 2020.
  • Gezan SA, Osorio LF, Verma S, and Whitaker VM, (2017). An experimental validation of genomic selection in octoploid strawberry. Horticult. Res. 4:16070.
  • Gopalakrishnan TR, (2007). Vegetable crops. In: Peter KV, Swaminathan MS, editors. Horticulture science series – 4. India: New India Publishing Agency; p. 103
  • Gulsen O, Ceylan A, (2011). Elucidating polyploidization of bermudagrasses as assessed by organelle and nuclear DNA markers. OMICS A Journal of Integrative Biology 15 (12): 903- 912.
  • Huang, S, Li R, Zhang Z, Li L, Gu X, Fan W, Lucas WJ, Wang X, Xie B and Ni P, (2009). The genome of the cucumber, Cucumis sativus L. Nat. Genet. 41, 1275–1281.
  • Liu C, Liu X, Han Y, Wang X, Ding Y, Meng H, and Cheng Z, (2021). Genomic Prediction and the Practical Breeding of 12 Quantitative-Inherited Traits in Cucumber (Cucumis sativus L.). Front. Plant Sci. 12:729328
  • Pan YP, Wang YH, McGregor C, Liu S, Luan FS, Gao ML, et al., (2020). Genetic architecture of fruit size and shape variation in cucurbits: A comparative perspective. Theoretic. Appl. Genetics 133, 1–21.
  • Park HS, Lee WK, Lee SC, Lee HO, Joh HJ, Park JY, Kim S, Song K. and Yang TJ, (2021). Inheritance of chloroplast and mitochondrial genomes in cucumber revealed by four reciprocal F1 hybrid combinations. Scientifc Reports 11:2506.
  • Riedelsheimer C, Czedik-Eysenberg A, Grieder C, Lisec J, Technow F, Sulpice R, et al., (2012). Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat. Genet. 44, 217–220.
  • Sverrisdottir E, Sundmark EHR, Johnsen HO, Kirk HG, Asp T, Janss L, et al., (2018). The Value of expanding the training population to improve genomic selection models in tetraploid potato. Front. Plant Sci. 9:1118.
  • Tayeh N, Klein A, Le Paslier MC, Jacquin F, Houtin H, Rond C, et al., (2015). Genomic prediction in pea: Effect of marker density and training population size and composition on prediction accuracy. Front. Plant Sci. 6:941.
  • Xu SZ, Xu Y, Gong L, and Zhang QF, (2016). Metabolomic prediction of yield in hybrid rice. Plant J. 88, 219–227.
  • Yang LM, Koo DH, Li YH, Zhang XJ, Luan FS, Havey MJ, et al., (2012). Chromosome rearrangements during domestication of cucumber as revealed by high-density genetic mapping and draft genome assembly. Plant J. 71, 895–906.
Year 2023, Volume: 9 Issue: 1, 19 - 23, 01.02.2023

Abstract

References

  • Acquaah G, (2012). Principles of Plant Genetics and Breeding: Breeding Cucumber. 2. New York: Wiley; pp. 676–681
  • Alverson AJ, Rice DW, Dickinson S, Barry K. and Palmer JD, (2011). Origins and recombination of the bacterial-sized multichromosomal mitochondrial genome of cucumber. Plant Cell 23, 2499–2513.
  • Behera TK, Staub JE, Behera S, Delannay IY, Chen JF, (2011). Marker-assisted backcross selection in an interspecific Cucumis population broadens the genetic base of cucumber (Cucumis sativus L.). Euphytica 178, 261-272.
  • Doyle JJ and Doyle JL, (1990). Isolation of plant DNA from fresh tissue. Focus 12, 13–15.
  • Duangjit J, Causse M, and Sauvage C, (2016). Efficiency of genomic selection for tomato fruit quality. Mol. Breed. 36:29.
  • FAO, (2020). FAO of the United Nations. FAOSTAT, http://www.fao.org/faostat/en/#data/QC Accessed 05 February 2020.
  • Gezan SA, Osorio LF, Verma S, and Whitaker VM, (2017). An experimental validation of genomic selection in octoploid strawberry. Horticult. Res. 4:16070.
  • Gopalakrishnan TR, (2007). Vegetable crops. In: Peter KV, Swaminathan MS, editors. Horticulture science series – 4. India: New India Publishing Agency; p. 103
  • Gulsen O, Ceylan A, (2011). Elucidating polyploidization of bermudagrasses as assessed by organelle and nuclear DNA markers. OMICS A Journal of Integrative Biology 15 (12): 903- 912.
  • Huang, S, Li R, Zhang Z, Li L, Gu X, Fan W, Lucas WJ, Wang X, Xie B and Ni P, (2009). The genome of the cucumber, Cucumis sativus L. Nat. Genet. 41, 1275–1281.
  • Liu C, Liu X, Han Y, Wang X, Ding Y, Meng H, and Cheng Z, (2021). Genomic Prediction and the Practical Breeding of 12 Quantitative-Inherited Traits in Cucumber (Cucumis sativus L.). Front. Plant Sci. 12:729328
  • Pan YP, Wang YH, McGregor C, Liu S, Luan FS, Gao ML, et al., (2020). Genetic architecture of fruit size and shape variation in cucurbits: A comparative perspective. Theoretic. Appl. Genetics 133, 1–21.
  • Park HS, Lee WK, Lee SC, Lee HO, Joh HJ, Park JY, Kim S, Song K. and Yang TJ, (2021). Inheritance of chloroplast and mitochondrial genomes in cucumber revealed by four reciprocal F1 hybrid combinations. Scientifc Reports 11:2506.
  • Riedelsheimer C, Czedik-Eysenberg A, Grieder C, Lisec J, Technow F, Sulpice R, et al., (2012). Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat. Genet. 44, 217–220.
  • Sverrisdottir E, Sundmark EHR, Johnsen HO, Kirk HG, Asp T, Janss L, et al., (2018). The Value of expanding the training population to improve genomic selection models in tetraploid potato. Front. Plant Sci. 9:1118.
  • Tayeh N, Klein A, Le Paslier MC, Jacquin F, Houtin H, Rond C, et al., (2015). Genomic prediction in pea: Effect of marker density and training population size and composition on prediction accuracy. Front. Plant Sci. 6:941.
  • Xu SZ, Xu Y, Gong L, and Zhang QF, (2016). Metabolomic prediction of yield in hybrid rice. Plant J. 88, 219–227.
  • Yang LM, Koo DH, Li YH, Zhang XJ, Luan FS, Havey MJ, et al., (2012). Chromosome rearrangements during domestication of cucumber as revealed by high-density genetic mapping and draft genome assembly. Plant J. 71, 895–906.
There are 18 citations in total.

Details

Primary Language English
Subjects Agricultural Engineering
Journal Section Articles
Authors

Leyla Öztürk Akar This is me

Osman Gülsen This is me

Sinan Zengin This is me

G. Elif Vural This is me

Publication Date February 1, 2023
Published in Issue Year 2023 Volume: 9 Issue: 1

Cite

APA Akar, L. Ö., Gülsen, O., Zengin, S., Vural, G. E. (2023). Cytoplasmic Genome Prediction in Cucumber (Cucumis sativus L.) Hybrid Variety Breeding. Ekin Journal of Crop Breeding and Genetics, 9(1), 19-23.
AMA Akar LÖ, Gülsen O, Zengin S, Vural GE. Cytoplasmic Genome Prediction in Cucumber (Cucumis sativus L.) Hybrid Variety Breeding. Ekin Journal. February 2023;9(1):19-23.
Chicago Akar, Leyla Öztürk, Osman Gülsen, Sinan Zengin, and G. Elif Vural. “Cytoplasmic Genome Prediction in Cucumber (Cucumis Sativus L.) Hybrid Variety Breeding”. Ekin Journal of Crop Breeding and Genetics 9, no. 1 (February 2023): 19-23.
EndNote Akar LÖ, Gülsen O, Zengin S, Vural GE (February 1, 2023) Cytoplasmic Genome Prediction in Cucumber (Cucumis sativus L.) Hybrid Variety Breeding. Ekin Journal of Crop Breeding and Genetics 9 1 19–23.
IEEE L. Ö. Akar, O. Gülsen, S. Zengin, and G. E. Vural, “Cytoplasmic Genome Prediction in Cucumber (Cucumis sativus L.) Hybrid Variety Breeding”, Ekin Journal, vol. 9, no. 1, pp. 19–23, 2023.
ISNAD Akar, Leyla Öztürk et al. “Cytoplasmic Genome Prediction in Cucumber (Cucumis Sativus L.) Hybrid Variety Breeding”. Ekin Journal of Crop Breeding and Genetics 9/1 (February 2023), 19-23.
JAMA Akar LÖ, Gülsen O, Zengin S, Vural GE. Cytoplasmic Genome Prediction in Cucumber (Cucumis sativus L.) Hybrid Variety Breeding. Ekin Journal. 2023;9:19–23.
MLA Akar, Leyla Öztürk et al. “Cytoplasmic Genome Prediction in Cucumber (Cucumis Sativus L.) Hybrid Variety Breeding”. Ekin Journal of Crop Breeding and Genetics, vol. 9, no. 1, 2023, pp. 19-23.
Vancouver Akar LÖ, Gülsen O, Zengin S, Vural GE. Cytoplasmic Genome Prediction in Cucumber (Cucumis sativus L.) Hybrid Variety Breeding. Ekin Journal. 2023;9(1):19-23.