การพัฒนาเครื่องหมายดีเอ็นเอสนิปในยีน Piezo-type mechanosensitive ion channel homolog (Piezo) และประสิทธิภาพในการคัดเลือกลักษณะความต้านทานโรคยอดเน่าในสับปะรด

Jeeraporn Kansup; Mallika Nualkaew; Amornrat Kidjaidiew; Suphawadee Ngorian

Authors

Jeeraporn Kansup Biotechnology Research and Development Office, Rangsit-Nakhon Nayok Rd., Thanyaburi, Pathum Thani 12110, Thailand
Mallika Nualkaew Phetchaburi Agricultural Research and Development Center, Cha-am, Phetchaburi 76120, Thailand
Amornrat Kidjaidiew Plant Protection Research and Development Office, 50 Phahonyothin Rd, Chatuchak, Bangkok 10900, Thailand
Suphawadee Ngorian Biotechnology Research and Development Office, Rangsit-Nakhon Nayok Rd., Thanyaburi, Pathum Thani 12110, Thailand

Keywords:

DNA marker, SNP, heart rot disease, pineapple, tetra-primer ARMS–PCR

Abstract

Heart rot disease caused by fungi Phytophthora spp. is a major problem in pineapple production. This research was conducted to develop a primer set specific for a nonsynonymous SNP marker in the pineapple Piezo-type mechanosensitive ion channel homolog (Piezo) gene, S13_8307911, which exhibits nucleotide sequence differences between heart rot disease-resistant and susceptible varieties. PCR conditions were optimized to detect this SNP marker using tetra-primer ARMS–PCR technique. The efficiency of the SNP markers for selecting heart rot disease resistance was assessed in a hybrid pineapple sample set of 22 lines exhibiting resistance under natural conditions, using genotype–phenotype concordance as a measure of prediction accuracy. The results showed that SNP marker S13_8307911, compared with S6_3252739 in the E3 ubiquitin-protein ligase MED25 binding RING-H2 protein 1 gene and S15_644992 in the Pathogenesis-related protein-4-like gene, exhibited marker prediction accuracies of 95.5%, 100%, and 81.8%, respectively. These findings suggest that the identified SNP markers have potential for application in marker-assisted selection of pineapple varieties resistant to heart rot disease. However, further validation in larger and genetically diverse populations is necessary to confirm their stability and predictive performance before implementation in breeding programs.

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