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.
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
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.
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.