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Development of SNP Marker Sets for Marker-Assisted Background Selection in Cultivated Cucumber Varieties

Authors :
Eun Su Lee
Hee-Bum Yang
Jinhee Kim
Hye-Eun Lee
Ye-Rin Lee
Do-Sun Kim
Source :
Agronomy, Vol 12, Iss 2, p 487 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Marker-assisted background selection is a powerful molecular tool that can enhance breeding efficiency through the analysis of a large number of markers representing the entire genomic background for precise selection. In the present study, the transcriptomes of 38 cucumber inbred lines with diverse traits were sequenced for single nucleotide polymorphism (SNP) mining for practical application to commercial cucumber breeding. A total of 62,378 high-quality SNPs were identified, of which 2462 SNPs were chosen based on the stringent filtering parameters. Finally, 363 evenly distributed common background selection markers (BMs) were developed and validated through polymorphism analysis and phylogenetic analysis using breeding materials with different genetic backgrounds; 327 out of 363 common BMs were useful for background selection. Moreover, the results of the phylogenetic analysis carried out using 50 selected core BMs were consistent with those for 327 common BMs. However, when the genotypes of breeding materials belonging to only the Baekdadagi-type were analyzed, the 327 common BMs showed a significant reduction in polymorphisms within the biased genomic locations. To address this issue, 59 highly polymorphic markers were selected as Baekdadagi BMs, as they showed better selection ability for the Baekdadagi-type. The 327 common BMs developed in the present study will enable efficient marker-assisted background selection in cucumber. Additionally, to reduce the genotyping cost, we suggested an alternative background selection strategy using both evenly distributed core BMs and biased Baekdadagi BMs for the improvement of commercial cucumber breeding programs.

Details

Language :
English
ISSN :
20734395
Volume :
12
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Agronomy
Publication Type :
Academic Journal
Accession number :
edsdoj.8243fdcdfa584a53902fa11db761e32e
Document Type :
article
Full Text :
https://doi.org/10.3390/agronomy12020487