Evidence map›Paper›PMID 41318398›Full record

ArticleBMC plant biology2025

Development and application of a multiple nucleotide polymorphism (MNP)-based molecular identification system for pear cultivars.

Xiang Yang, Zhiwei Fang, Yufen Cao, Luming Tian, Hai Peng, Ying Zhang, Jiayu Xu, Junfei Zhou, Hongliang Huo, Dan Qi and 3 more

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Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Xiang Yang *Research Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China.
Zhiwei Fang *Institute for Systems Biology, Jianghan University, Wuhan, 430056, China.
Yufen CaoResearch Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China.
Luming TianResearch Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China.
Hai PengInstitute for Systems Biology, Jianghan University, Wuhan, 430056, China.
Ying ZhangResearch Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China.
Jiayu XuResearch Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China.
Junfei ZhouInstitute for Systems Biology, Jianghan University, Wuhan, 430056, China.
Hongliang HuoResearch Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China.
Dan QiResearch Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China.
Chao LiuResearch Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China.
Tiantian LiInstitute for Systems Biology, Jianghan University, Wuhan, 430056, China. jatiantianli@126.com.
Xingguang DongResearch Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, 125100, China. dongxingguangde@126.com.

Funding

CAAS-ASTIP-RIP CARS-28-01
6 · The paper itself

Abstract

backgroundPear is one of the most popular and widely cultivated fruits globally, with rich cultivar diversity. Pyrus species are characterized by self-incompatibility and the absence of reproductive barriers between species, leading to extensive gene flow and genetic recombination among different types of cultivars. As a result, cultivar identification technologies have considerable practical significance in pear production. Multiple nucleotide polymorphism (MNP) technology, which combines multiplex PCR amplification and high-throughput sequencing, offers high efficiency and accuracy in pear cultivar identification, and meets the needs of cultivar innovation and industry development.

resultsWe applied MNP technology to pear cultivar identification for the first time, establishing fingerprints for major pear cultivars and exploring the feasibility of MNP markers for pear population structure analysis. Based on genomic resequencing data from 143 pear accessions, 558 marker loci were initially developed, and 310 core markers were retained after screening. The 310 MNP markers showed high polymorphism, with an average of 18.14 alleles per marker locus and PIC values ranging from 0.57 to 0.99. Validation using 76 representative pear cultivars demonstrated reproducibility and accuracy rates exceeding 99% for the 310 MNP markers. A total of 2,850 pairwise comparisons among the 76 cultivars showed an average genetic differentiation of 90.89%. Population structure analyses based on MNP markers effectively reflected the classification relationships among the 76 cultivars, clearly distinguishing European from Asian pears.

conclusionIn summary, the developed pear MNP markers possess high polymorphism, stability, and cultivar-discrimination capability, promising extensive future applications in pear cultivar identification and population genetic research.

Indexed as

Polymorphism, Single NucleotidePyrusGenetic MarkersHigh-Throughput Nucleotide SequencingMultiplex Polymerase Chain ReactionGenetic MarkersCultivar identificationGenetic similarityMNP LociPearPopulation structure

Identifiers

PMID41318398
PMCPMC12772083

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