Identification of TP-M13-SSR molecular markers and genetic relationship analysis of seven new ornamental peach germplasms

Hou Jiayin; Feng Shuxiang; Dai Songhua; Yan Shufang

doi:10.12171/j.1000-1522.20220158

Journal of Beijing Forestry University > 2023 > 45(8): 132-141. > DOI: 10.12171/j.1000-1522.20220158

Hou Jiayin, Feng Shuxiang, Dai Songhua, Yan Shufang. Identification of TP-M13-SSR molecular markers and genetic relationship analysis of seven new ornamental peach germplasms[J]. Journal of Beijing Forestry University, 2023, 45(8): 132-141. DOI: 10.12171/j.1000-1522.20220158

Citation:

PDF (1561 KB)

Identification of TP-M13-SSR molecular markers and genetic relationship analysis of seven new ornamental peach germplasms

1.
School of Biological Sciences and Biotechnology, National Engineering Research Center of Tree Breeding and Ecological Restoration, Beijing Forestry University, Beijing 100083, China
2.
Hebei Academy of Forestry and Grassland Science, Shijiazhuang 050067, Hebei, China
3.
Hebei Farun Forestry Technology Co., Ltd., Shijiazhuang 050061, Hebei, China
4.
Hebei Forest City Construction Technology Innovation Center, Shijiazhuang 050061, Hebei, China

More Information

Received Date: April 20, 2022
Revised Date: August 28, 2022
Accepted Date: June 27, 2023
Available Online: June 29, 2023
Published Date: August 24, 2023

Graphical Abstract

Abstract

Abstract

Objective Genetic diversity and genetic relationship of the leaves from 15 commercially available common types and 7 new ornamental peach germplasms were studied and identified by simple sequence repeat (SSR). The purpose of this study was to explore the genetic distance between the new germplasm and commercially available common varieties, and to provide reference for the origin, evolution, development and utilization of ornamental peach and parental selection.
Method TP-M13-SSR PCR amplification and fluorescent capillary electrophoresis detection were carried out using 36 pairs of primers, and the amplification efficiency and polymorphism were analyzed. Genetic relationship of new ornamental peach germplasm ‘T13’, ‘T9-1’, ‘T10’, ‘T20’, ‘T22’ and ‘Zaohua’ was identified, and fingerprints of 22 ornamental peach germplasm resources were constructed using 6 SSR loci, and Neighbor-Joining clustering and comprehensive analysis combined with phenotypic traits was performed.
Result 36 pairs of highly polymorphic primers were screened from 29 pairs of primers. A total of 183 polymorphic alleles and 98.396 effective alleles were detected. Average of observed heterozygosity was 0.341, and average of expected heterozygosity was 0.739. Average of Shannon’s information index was 1.546, and average of polymorphism information content of primer was 0.683, ranging from 0.510 to 0.841. The new germplasm ‘T20’ and ‘T10’ had the largest similarity coefficients with the existing variety ‘Taijie’, which were 0.95 and 0.92, respectively. ‘T20’ and ‘Taijie’ had the same phenotypic traits, including branch shape, petal color and petal type. The new germplasm ‘T13’ and the existing variety ‘Wubao tao’ had the highest similarity coefficient, which was 0.86. Similarity coefficient between the new germplasm ‘T22’ and other existing varieties was very small, and its phenotypic characters were quite different from the other 21 germplasms. Similarity coefficient of the new germplasm ‘T9-1’ and ‘Zaohua’ with the existing variety ‘Zhufen chuizhi’ was the largest, which was 0.94.
Conclusion In this study, through the construction of SSR fingerprint map, the ornamental peach germplasm resources can be identified more intuitively and quickly, providing technical and theoretical support for the later innovation of ornamental peach germplasm resources, the establishment of germplasm resource banks, and the protection and utilization of germplasm resources.
- ornamental peach,
- SSR,
- genetic relationship analysis,
- new germplasm identification

FullText(HTML)

References (43)

References

[1]	陈尚平, 苏家乐, 何丽斯. 我国观赏桃的栽培起源和发展[J]. 江苏农业科学, 2014, 42(3): 128−130. Chen S P, Su J L, He L S. The cultivation origin and development of ornamental peach in China[J]. Jiangsu Agricultural Sciences, 2014, 42(3): 128−130.
[2]	Morgante M, Olivieri A. PCR-amplified microsatellites as markers in plant genetics[J]. The Plant Journal, 1993, 3(1): 175−182. doi: 10.1111/j.1365-313X.1993.tb00020.x
[3]	Wu Q, Liang X, Dai X, et al. Molecular discrimination and ploidy level determination for elite willow cultivars[J]. Tree Genetics & Genomes, 2018, 14(5): 65.
[4]	宋跃朋, 江锡兵, 张曼, 等. 杨树Genomic-SSR与EST-SSR分子标记遗传差异性分析[J]. 北京林业大学学报, 2010, 32(5): 1−7. Song Y P, Jiang X B, Zhang M, et al. Genetic differences revealed by genomic-SSR and EST-SSR in poplar[J]. Journal of Beijing Forestry University, 2010, 32(5): 1−7.
[5]	杨雄, 杨宁, 袁启华, 等. 白皮松EST-SSR 分子标记的开发及应用[J]. 北京林业大学学报, 2021, 43(7): 1−11. Yang X, Yang N, Yuan Q H, et al. Development and application of EST-SSR molecular markers in Pinus bungeana[J]. Journal of Beijing Forestry University, 2021, 43(7): 1−11.
[6]	Gabriela R, Marco A M, Carlos M, et al. Identification of a minimal microsatellite marker panel for the fingerprinting of peach and nectarine cultivars[J]. Electronic Journal of Biotechnology, 2008, 11(5): 1−12.
[7]	Dirlewanger E, Cosson P, Tavaud M, et al. Development of microsatellite markers in peach [Prunus persica (L.) Batsch] and their use in genetic diversity analysis in peach and sweet cherry (Prunus avium L.)[J]. Theoretical and Applied Genetics, 2002, 105(1): 127−138. doi: 10.1007/s00122-002-0867-7
[8]	Mehrana K D, Tayebeh B, Karim S. Novel in silico EST-SSR markers and bioinformatic approaches to detect genetic variation among peach (Prunus persica L.) germplasm[J]. Journal of Forestry Research, 2020, 31(4): 1359−1370. doi: 10.1007/s11676-019-00922-z
[9]	王淋, 敖敦, 包文泉, 等. 基于SSR分子标记的桃品种鉴别及指纹图谱构建[J]. 中南林业科技大学学报, 2021, 41(6): 131−138. Wang L, Ao D, Bao W Q, et al. Research on the identification of main peach varieties and construction of fingerprint based on SSR markers[J]. Journal of Central South University of Forestry & Technology, 2021, 41(6): 131−138.
[10]	Xu Y, Ma R, Xie H C. Development of SSR markers for the phylogenetic analysis of almond trees from China and the Mediterranean region[J]. Genome, 2004, 47(6): 1091−1104. doi: 10.1139/g04-058
[11]	Ouni R, Zborowska A, Sehic J, et al. Genetic diversity and structure of Tunisian local pear germplasm as revealed by SSR markers[J]. Horticultural Plant Journal, 2020, 6(2): 61−70. doi: 10.1016/j.hpj.2020.03.003
[12]	陈霁, 马瑞娟, 沈志军, 等. 基于SSR标记的观赏桃亲缘关系分析[J]. 果树学报, 2011, 28(4): 580−585. Chen J, Ma R J, Shen Z J, et al. SSR analysis on the genetic relationship of ornamental peach germplasm resources[J]. Journal of Fruit Science, 2011, 28(4): 580−585.
[13]	陈丽, 薛良交, 李淑娴. 跳枝碧桃花色性状的全基因组关联分析[J]. 园艺学报, 2021, 48(3): 553−565. Chen L, Xue L J, Li S X. Genome-wide association study of flower color trait in Prunus persica f. versicolor[J]. Acta Horticulturae Sinica, 2021, 48(3): 553−565.
[14]	Momi T, Yuzuru M. Fine mapping of a locus presumably involved in hybrid inviability (HIs-1) between flowering cherry cultivar Cerasus × yedoensis ‘Somei-yoshino’ and its wild relative C. spachiana[J]. Breeding Science, 2019, 69(4): 658−664. doi: 10.1270/jsbbs.19078
[15]	Luo F, Sandefur P, Evans K, et al. A DNA test for routinely predicting mildew resistance in descendants of crabapple ‘White Angel’[J]. Molecular Breeding, 2019, 39(3): 33. doi: 10.1007/s11032-019-0933-3
[16]	Schuelke M. An economic method for the fluorescent labeling of PCR fragments[J]. Nature Biotechnology, 2000, 18(2): 233−234. doi: 10.1038/72708
[17]	Zhu Y, Hu J, Han R, et al. Fingerprinting and identification of closely related wheat (Triticum aestivum L.) cultivars using ISSR and fluorescence-labeled TP-M13-SSR markers[J]. Australian Journal of Crop Science, 2011, 5(7): 846−850.
[18]	张志军, 黄克兴, 岳杰, 等. TP-M13-SSR技术在麦芽品种鉴定中的应用[J]. 食品科学, 2018, 39(24): 183−188. Zhang Z J, Huang K X, Yue J, et al. DNA fingerprinting of malt varieties using tailed primer M13 microsatellite (TP-M13-SSR) markers[J]. Food Science, 2018, 39(24): 183−188.
[19]	Yang Z M, Shi Y, Shuai J Q, et al. Fingerprint construction and genetic diversity analysis of tree peony collected from Hunan province based on SSR markers[J]. Horticultural Science and Technology, 2021, 39(5): 684−695.
[20]	高源, 刘凤之, 王昆, 等. 基于TP-M13-SSR指纹图谱的中国原产苹果属植物分子身份证的建立[J]. 植物遗传资源学报, 2015, 16(6): 1290−1297. Gao Y, Liu F Z, Wang K, et al. TP-M13-SSR technique and its applications in analysis of genetic diversity for apple germplasm resources[J]. Journal of Plant Genetic Resources, 2015, 16(6): 1290−1297.
[21]	刘超凡, 张国君, 徐刚标. 杨树种质SSR指纹数据库构建[J]. 中南林业科技大学学报, 2021, 41(2): 97−104. Liu C F, Zhang G J, Xu G B. Construction of SSR fingerprint database of Populus germplasm[J]. Journal of Central South University of Forestry & Technology, 2021, 41(2): 97−104.
[22]	Aranzana M J, Garcia-M J, Carbó J, et al. Development and variability analysis of microsatellite markers in peach[J]. Plant Breeding, 2002, 121(1): 87−92. doi: 10.1046/j.1439-0523.2002.00656.x
[23]	关利平, 王玲玲, 曹珂, 等. 桃品种鉴定的SSR核心引物筛选及其应用[J]. 中国果树, 2021(6): 33−38. Guan L P, Wang L L, Cao K, et al. Screening and application of SSR core primers in peach variety identification[J]. China Fruits, 2021(6): 33−38.
[24]	Cipriani G, Lot G, Huang W G, et al. AC/GT and AG/CT microsatellite repeats in peach [Prunus persica (L) Batsch]: isolation, characterisation and cross-species amplification in Prunus[J]. Theoretical & Applied Genetics, 1999, 99(1−2): 65−72.
[25]	Hulce D, Li X, Snyder-Leiby T, et al. Genemarker genotyping software: tools to increase the statistical power of DNA fragment analysis[J]. Journal of Biomolecular Techniques, 2011, 22(Suppl.): S35−S36.
[26]	樊文强, 盖红梅, 孙鑫, 等. SSR数据格式转换软件DataFormater[J]. 分子植物育种, 2016, 14(1): 265−270. Fan W Q, Ge H M, Sun X, et al. DataFormater, a software for SSR data formatting to develop population genetics analysis[J]. Molecular Plant Breeding, 2016, 14(1): 265−270.
[27]	Botstein D. A theory of modular evolution for bacteriophages[J]. Annals of the New York Academy of Sciences, 2010, 354(1): 484−491.
[28]	Kato S, Matsumoto A, Yoshimura K, et al. Clone identification in Japanese flowering cherry (Prunus subgenus Cerasus) cultivars using nuclear SSR markers[J]. Breeding Science, 2012, 62(3): 248−255. doi: 10.1270/jsbbs.62.248
[29]	Li T H, Li Y X, Li Z C, et al. Simple Sequence repeat analysis of genetic diversity in primary core collection of peach (Prunus persica)[J]. Journal of Integrative Plant Biology, 2008, 50(1): 102−110. doi: 10.1111/j.1744-7909.2007.00598.x
[30]	王清明, 程怡, 马建伟, 等. 基于引物“随机组合”构建观赏桃SSR指纹图谱[J]. 广西植物, 2016, 36(3): 289−296. doi: 10.11931/guihaia.gxzw201408028 Wang Q M, Cheng Y, Ma J W, et al. Construction of SSR fingerprint for ornamental peach based on primers “random combination”[J]. Guihaia, 2016, 36(3): 289−296. doi: 10.11931/guihaia.gxzw201408028
[31]	魏姗姗, 刘兴菊, 杨敏生, 等. 基于成熟期的桃品种遗传多样性SSR分析[J]. 北方园艺, 2014, 6(12): 88−93. Wei S S, Liu X J, Yang M S, et al. Genetic diversity of SSR analysis of Prunus persica cultivars based on maturity[J]. Northern Horticulture, 2014, 6(12): 88−93.
[32]	王力荣. 中国桃品种改良历史回顾与展望[J]. 果树学报, 2021, 38(12): 2178−2195. Wang L R. History and prospect of peach breeding in China[J]. Journal of Fruit Science, 2021, 38(12): 2178−2195.
[33]	Zhang Y J, Wang J, Yang L L, et al. Development of SSR and SNP markers for identifying opium poppy[J]. International Journal of Legal Medicine, 2022, 136(5): 1261−1271. doi: 10.1007/s00414-022-02810-4
[34]	Nihad S A I, Hasan M K, Kabir A, et al. Linkage of SSR markers with rice blast resistance and development of partial resistant advanced lines of rice (Oryza sativa) through marker-assisted selection[J]. Physiology and Molecular Biology of Plants, 2022, 25(1): 153−169.
[35]	赵盼, 栗丹阳, 马锦林, 等. 油料树种千年桐的SSR标记开发、遗传多样性与群体结构分析[J]. 北京林业大学学报, 2021, 43(11): 50−61. Zhao P, Li D Y, Ma J L, et al. SSR marker development, genetic diversity and population structure analysis in oil tree species Vernicia montana[J]. Journal of Beijing Forestry University, 2021, 43(11): 50−61.
[36]	毛秀红, 朱士利, 李善文, 等. 基于荧光SSR标记的毛白杨核心种质构建[J]. 北京林业大学学报, 2020, 42(7): 40−47. Mao X H, Zhu S L, Li S W, et al. Core germplasm construction of Populus tomentosa based on the fluorescent SSR markers[J]. Journal of Beijing Forestry University, 2020, 42(7): 40−47.
[37]	Liu Z S, Zhang J, Wang Y, et al. Development and cross-species transferability of novel genomic-SSR markers and their utility in hybrid identification and trait association analysis in Chinese cherry[J]. Horticulturae, 2022, 8(3): 222. doi: 10.3390/horticulturae8030222
[38]	葛洪. 西京杂记(长安史迹丛刊)[M]. 西安: 三秦出版社, 2006. Ge H. Xijing miscellany (Chang’an historical relics series)[M]. Xi’an: Sanqin Publishing House, 2006.
[39]	胡东燕. 分子标记技术在桃花品种系统分类中的应用研究[D]. 北京: 北京林业大学, 2004. Hu D Y. Studies on ornamental peach systematics using molecular markers[D]. Beijing: Beijing Forestry University, 2004.
[40]	李雪莲, 王尚德, 刘佳棽, 等. 部分两用桃品种(系)指纹图谱的建立[J]. 西北植物学报, 2010, 30(3): 505−511. Li X L, Wang S D, Liu J Q, et al. Construction of fingerprinting map of some dual-purpose peach varieties by AFLP markers[J]. Acta Botanica Boreali-Occidentalia Sinica, 2010, 30(3): 505−511.
[41]	肖琳. 湖南观赏桃遗传多样性研究[D]. 长沙: 中南林业科技大学, 2017. Xiao L. Research on genetic diversity of ornamental peaches in Hunan Province[D]. Changsha: Central South University of Forestry & Technology, 2017.
[42]	王彩虹, 田义轲, 赵静. 来自苹果的SSRs在蔷薇科植物资源上的通用性分析[J]. 园艺学报, 2005, 32(3): 500−502. Wang C H, Tian Y K, Zhao J. General application analysis of SSRs derived from apple (Malus pumila) on other species in Rosaceae[J]. Acta Horticulturae Sinica, 2005, 32(3): 500−502.
[43]	中华人民共和国农业农村部. 桃品种鉴定SSR分子标记法: NY/T 3642—2020 [S]. 北京: 中国标准出版社, 2020. Ministry of Agriculture and Rural Affairs of the People’s Republic of China. Identification of peach (Amygdalus persica) cultivars—SSR marker method: NY/T 3642−2020[S]. Beijing: Standards Press of China, 2020.

[1]	Huang Chengwei, Qi Lei, Duojiecairen, Zhang Huaiqing, Xue Lianfeng, Yun Ting. Prediction of tree growth parameters based on cascaded recurrent network[J]. Journal of Beijing Forestry University, 2023, 45(8): 94-108. DOI: 10.12171/j.1000-1522.20230027
[2]	Zhang Jinlan, Zhang Xiangxue, Ran Ran, Wu Min, Wu Shang, Jia Liming. Leaf shedding of Populus tomentosa under drought stress based on the theory of plant segmentation hypothesis[J]. Journal of Beijing Forestry University, 2020, 42(9): 19-27. DOI: 10.12171/j.1000-1522.20190411
[3]	Jiang Tao, Wang Xinjie. Convolutional neural network for GF-2 image stand type classification[J]. Journal of Beijing Forestry University, 2019, 41(9): 20-29. DOI: 10.13332/j.1000-1522.20180342
[4]	Wu Jianzhao, Cui Yu, He Jingwen, Liu Ying, Li Jian, Lin Yongming, Wang Daojie, Wu Chengzhen. Characteristics of plants, soil nutrients and leaf stoichiometry at the early stage of ecological restoration in earthquake-affected area[J]. Journal of Beijing Forestry University, 2019, 41(2): 41-52. DOI: 10.13332/j.1000-1522.20180329
[5]	Yu Huiling, Ma Junwei, Zhang Yizhuo. Plant leaf recognition model based on two-way convolutional neural network[J]. Journal of Beijing Forestry University, 2018, 40(12): 132-137. DOI: 10.13332/j.1000-1522.20180182
[6]	ZHANG Shuai, HUAI Yong-jian.. Leaf image recognition based on layered convolutions neural network deep learning.[J]. Journal of Beijing Forestry University, 2016, 38(9): 108-115. DOI: 10.13332/j.1000-1522.20160035
[7]	LIU Nian, KAN Jiang-ming. Plant leaf identification based on the multi-feature fusion and deep belief networks method[J]. Journal of Beijing Forestry University, 2016, 38(3): 110-119. DOI: 10.13332/j.1000-1522.20150267
[8]	WANG Li-jun, HUAI Yong-jian, PENG Yue-cheng. Method of identification of foliage from plants based on extraction of multiple features of leaf images.[J]. Journal of Beijing Forestry University, 2015, 37(1): 55-69. DOI: 10.13332/j.cnki.jbfu.2015.01.006
[9]	BI Yu-hui, TANG Shou-zheng, WANG Xue-feng. Automatic segmentation of leaf images based on an improved geometric active contour model.[J]. Journal of Beijing Forestry University, 2011, 33(1): 90-93.
[10]	ZHANG Jin-tun, MENG Dong-ping, XI Yue-xiang. Ordination of self-organizing feature map neural network and its application in the study of plant communities.[J]. Journal of Beijing Forestry University, 2008, 30(1): 1-5.

Cited By

Cited by

Periodical cited type(11)

1.	黄菲，张佛熠，钟嘉琳，李心，彭辉，邹冰燕，刘玮，王琼. 南昌城市森林土壤肥力综合评价及其空间分布特征. 中南林业科技大学学报. 2024(08): 129-138 .
2.	吴家龙，张俊涛. 园林绿色废弃物资源价值实现的系统认知与路径探析——以广州市为例. 中国园林. 2024(08): 57-63 .
3.	刘国梁，吴伟，李素艳，孙向阳，岳宗伟，魏宇光. 园林绿化废弃物堆肥配施化肥对土壤腐殖质碳组分的影响. 中国土壤与肥料. 2024(12): 27-35 .
4.	史正军，潘松，冯世秀，袁峰均. 园林废弃物地表覆盖处理对植物生长及土壤细菌群落的影响. 草业学报. 2023(04): 153-160 .
5.	潘松，赵玉梅，袁峰均，史正军. 园林废弃物地表覆盖对龙船花生长发育的影响. 热带作物学报. 2023(04): 766-773 .
6.	余海洋. 基于自然解决方案的城市绿地系统营建策略. 现代园艺. 2023(11): 140-142 .
7.	高星，贾慧果. 故宫景福宫古树土壤肥力特征分析评价. 北方农业学报. 2023(01): 45-60 .
8.	闫芳彬，郑景明，宫殷婷，赵一臣，张家琦. 园林废弃物资源化处理对人工林土壤养分及微生物碳源利用的影响. 浙江农林大学学报. 2023(05): 1045-1053 .
9.	胡永恒，张程，万华琴，朱咏莉，李萍萍. 不同园林废弃物堆肥过程中化学性状变化及其对发芽指数的影响. 南京林业大学学报(自然科学版). 2023(06): 133-140 .
10.	潘松，史正军，毛晓宁，袁峰均，曾伟，焦玉佳. 园林废弃物覆盖材料组分及厚度对土壤化学性质的影响. 西部林业科学. 2022(05): 153-158 .
11.	李小羊. 黔南地区市政园林工程建设中土壤改良技术措施研究. 工程技术研究. 2022(22): 215-217 .

Other cited types(0)

Get Citation

PDF

XML

Article views (567) PDF downloads (66) Cited by(11)

Turn off MathJax

Article Contents

Abstract

References

Identification of TP-M13-SSR molecular markers and genetic relationship analysis of seven new ornamental peach germplasms