Crops ›› 2024, Vol. 40 ›› Issue (1): 40-47.doi: 10.16035/j.issn.1001-7283.2024.01.006

;

Previous Articles     Next Articles

Analysis on Genetic Diversity and Population Structure for Japonica Rice Varieties in Liaoning Province

Liu Dan1(), Wang Jiayu2(), Feng Zhangli1, Feng Bo3, Chen Wenfu2   

  1. 1College of Biology and Agriculture of Zunyi Normal University, Zunyi 563006, Guizhou, China
    2Rice Research Institute of Shenyang Agricultural University / Key Laboratory of Northeast Rice Biology and Genetic Breeding, Ministry of Agriculture and Rural Affairs, Shenyang 110866, Liaoning, China
    3College of Resources and Environment of Zunyi Normal University, Zunyi 563006, Guizhou, China
  • Received:2022-08-15 Revised:2023-01-12 Online:2024-02-15 Published:2024-02-20
  • Contact: Wang Jiayu E-mail:danlius@163.com;wangjiayu@syau.edu.cn

RichHTML

4

PDF (PC)

127

Abstract:

To clarify the genetic relationship of japonica rice in Liaoning province, genetic diversity and population structure of 58 japonica rice varieties from nine breeding units in Liaoning province were analyzed using 54 pairs of SSR molecular markers. The results showed that among the 54 SSR primers, a total of 48 primers were polymorphic, accounting for 88.89%. A total of 150 alleles were detected by 48 polymorphic primers, and the alleles (Na) per locus ranged from 2 to 6 with the mean value of 3.13. The gene diversity indices (H) varied from 0.03 to 0.78 with an average of 0.33. The polymorphism information content (PIC) was changed from 0.03 to 0.74 with the average of 0.29. Comparative analysis of varieties bred by different breeding units, the genetic diversity of rice varieties from Liaoning Institute of Saline-Alkali Land Utilization was highest, the average PIC and the H were 0.30 and 0.34, respectively, while the Tieling Academy of Agricultural Sciences was lowest, the average PIC and the average H were 0.11 and 0.14, respectively. NJ cluster showed that 58 varieties could be divided into three groups, the “Dangeng” rice bred by Dandong Academy of Agricultural Sciences and “Tiegeng” rice bred by Tieling Academy of Agricultural Sciences were grouped Ⅰ and Ⅲ, respectively. The genetic structure analysis was performed based on model, 58 rice varieties could be divided into two groups, 32 of which belonged to group A and 26 belonged to group B.

Key words: Liaoning province, Japonica rice, SSR, Genetic diversity, Population structure

Table 1

The materials and their origins"

编号
Number		 材料名称
Material name		 来源
Origin		 城市
City		 编号
Number		 材料名称
Material name		 来源
Origin		 城市
City
1 辽农9911 辽宁省农业科学院耕作栽培研究所 沈阳 30 辽星10 辽宁省水稻研究所 沈阳
2 辽农979 辽宁省农业科学院耕作栽培研究所 沈阳 31 辽201 辽宁省水稻研究所 沈阳
3 辽农968 辽宁省农业科学院耕作栽培研究所 沈阳 32 沈稻47 沈阳农业大学 沈阳
4 辽盐2 辽宁省盐碱地利用研究所 盘锦 33 沈稻18 沈阳农业大学 沈阳
5 辽盐241 辽宁省盐碱地利用研究所 盘锦 34 沈稻9 沈阳农业大学 沈阳
6 辽盐283 辽宁省盐碱地利用研究所 盘锦 35 沈稻3 沈阳农业大学 沈阳
7 辽盐16 辽宁省盐碱地利用研究所 盘锦 36 沈稻6 沈阳农业大学 沈阳
8 盐粳34 辽宁省盐碱地利用研究所 盘锦 37 沈稻7 沈阳农业大学 沈阳
9 盐粳68 辽宁省盐碱地利用研究所 盘锦 38 沈农6014 沈阳农业大学 沈阳
10 盐粳48 辽宁省盐碱地利用研究所 盘锦 39 沈农159 沈阳农业大学 沈阳
11 盐粳456 辽宁省盐碱地利用研究所 盘锦 40 沈农9903 沈阳农业大学 沈阳
12 盐丰47 辽宁省盐碱地利用研究所 盘锦 41 沈农9816 沈阳农业大学 沈阳
13 盐188 辽宁省盐碱地利用研究所 盘锦 42 沈农606 沈阳农业大学 沈阳
14 雨田7号 盘锦北方农业技术开发有限公司 盘锦 43 沈农016 沈阳农业大学 沈阳
15 辽粳28 辽宁省水稻研究所 沈阳 44 千重浪2 沈阳农业大学 沈阳
16 辽粳5 辽宁省水稻研究所 沈阳 45 千重浪1 沈阳农业大学 沈阳
17 辽粳294 辽宁省水稻研究所 沈阳 46 沈农129 沈阳农业大学 沈阳
18 辽粳534 辽宁省水稻研究所 沈阳 47 沈农265 沈阳农业大学 沈阳
19 辽粳101 辽宁省水稻研究所 沈阳 48 沈农9741 沈阳农业大学 沈阳
20 辽粳454 辽宁省水稻研究所 沈阳 49 营8433 大石桥市农业技术推广中心 营口
21 辽粳326 辽宁省水稻研究所 沈阳 50 铁粳4 铁岭市农业科学院 铁岭
22 辽粳371 辽宁省水稻研究所 沈阳 51 铁粳7 铁岭市农业科学院 铁岭
23 辽粳9 辽宁省水稻研究所 沈阳 52 铁粳9 铁岭市农业科学院 铁岭
24 辽粳287 辽宁省水稻研究所 沈阳 53 丹粳10 丹东农业科学院 丹东
25 辽星1 辽宁省水稻研究所 沈阳 54 丹粳11 丹东农业科学院 丹东
26 辽星5 辽宁省水稻研究所 沈阳 55 丹粳1 丹东农业科学院 丹东
27 辽星12 辽宁省水稻研究所 沈阳 56 丹粳3 丹东农业科学院 丹东
28 辽星13 辽宁省水稻研究所 沈阳 57 丹粳9 丹东农业科学院 丹东
29 辽星20 辽宁省水稻研究所 沈阳 58 港源8 东港市示范繁殖农场 丹东

Table 2

Genetic diversity analysis of part japonica rice varieties in Liaoning with polymorphic SSR markers"

位点Locus Maf Na H PIC 位点Locus Maf Na H PIC
RM495 0.97 2.00 0.07 0.06 RM455 0.97 2.00 0.07 0.06
RM1 0.75 3.00 0.39 0.33 RM408 0.98 2.00 0.03 0.03
RM283 0.52 3.00 0.54 0.44 RM152 0.93 3.00 0.13 0.13
RM259 0.86 3.00 0.25 0.23 RM25 0.90 3.00 0.19 0.18
RM312 0.93 2.00 0.13 0.12 RM44 0.40 5.00 0.67 0.61
RM5 0.40 4.00 0.69 0.62 RM223 0.69 4.00 0.49 0.46
RM246 0.47 5.00 0.67 0.62 RM284 0.91 3.00 0.16 0.15
RM237 0.95 2.00 0.10 0.09 RM447 0.53 3.00 0.51 0.40
RM154 0.59 2.00 0.49 0.37 RM316 0.98 2.00 0.03 0.03
RM327 0.57 4.00 0.58 0.52 PSM338 0.41 3.00 0.63 0.55
RM452 0.97 2.00 0.07 0.06 RM215 0.41 4.00 0.70 0.65
PSM122 0.68 3.00 0.44 0.36 PSM406 0.60 6.00 0.57 0.52
RM208 0.48 3.00 0.61 0.53 RM271 0.86 3.00 0.24 0.23
OSR13 0.97 3.00 0.07 0.07 RM171 0.88 3.00 0.22 0.20
RM338 0.91 3.00 0.16 0.15 RM484 0.69 3.00 0.47 0.42
PSM132 0.56 6.00 0.63 0.59 RM20B 0.52 3.00 0.52 0.40
RM55 0.98 2.00 0.03 0.03 RM536 0.43 4.00 0.62 0.55
RM514 0.79 2.00 0.33 0.27 RM287 0.93 3.00 0.13 0.13
PSM326 0.80 3.00 0.32 0.28 RM21 0.26 6.00 0.78 0.74
RM413 0.95 2.00 0.10 0.09 RM19 0.97 2.00 0.07 0.06
RM161 0.71 3.00 0.43 0.36 RM247 0.74 6.00 0.43 0.41
RM334 0.95 2.00 0.10 0.09 RM277 0.90 2.00 0.19 0.17
RM510 0.95 2.00 0.10 0.09 平均值Mean 0.76 3.13 0.33 0.29
RM454 0.83 2.00 0.29 0.24 最大值Max. 0.98 6.00 0.78 0.74
RM162 0.91 4.00 0.16 0.16 最小值Min. 0.26 2.00 0.03 0.03
RM11 0.95 3.00 0.10 0.10

Table 3

Genetic diversity analysis of japonica rice among different breeding units"

育种单位Breeding unit 品种数量Number of varieties Maf Na H PIC
丹东农业科学院DAAS 5 0.79abcAB 1.83bBC 0.28abA 0.23abAB
辽宁省水稻研究所LRRI 17 0.77bcB 2.44aA 0.30abA 0.26aAB
辽宁省盐碱地利用研究所LISLU 10 0.74cB 2.29aAB 0.34aA 0.30aA
辽宁省农业科学院耕作栽培研究所TCRILAAS 3 0.83abAB 1.50bcCD 0.21bcAB 0.17bcBC
沈阳农业大学SAU 17 0.82abAB 2.21aAB 0.25abAB 0.22abAB
铁岭市农业科学院TAAS 3 0.90aA 1.31cD 0.14cB 0.11cC
总体水平Total level 55 0.76 3.10 0.32 0.29

Fig.1

Cluster of japonica rices of Liaoning using NJ"

Fig.2

Cluster of breeding units using NJ"

Fig.3

The change curve of Log-likelihood function value lnP(D) and ΔK based on the K value of subgroup numbers"

Fig.4

Population structure analysis on 58 varieties The red bars and green bars represent group A and group B, respectively. (1) to (9) represent nine breeding units in sequence of TCRILAAS, LISLU, PNATDCL, LRRI, SAU, ATECDC, TAAS, DAAS, DDBF."

Fig.5

Pedigree of part rice cultivars"

[1] 国家水稻数据中心, 中国水稻品种及其系谱数据库. [2022-08- 10].http://www.ricedata.cn/variety/.
[2] Liu D, Wang J Y, Wang X X, et al. Genetic diversity and elite gene introgression reveal the japonica rice breeding in northern China. Journal of Integrative Agriculture, 2015, 14(5):811-822.
doi: 10.1016/S2095-3119(14)60898-4
[3] 李红宇, 侯昱铭, 陈英华, 等. 用SSR标记评估东北三省水稻推广品种的遗传多样性. 中国水稻科学, 2009, 23(4):383-390.
doi: 10.3969/j.issn.1001-7216.2009.04.08
[4] 张科, 魏海锋, 卓大龙, 等. 黑龙江省近年审定水稻品种基于SSR标记的遗传多样性分析. 植物遗传资源学报, 2016, 17(3):447-454.
[5] 张佳琦, 郭宗珊, 刘长华, 等. 黑龙江省水稻品种的遗传多样性. 中国农学通报, 2022, 38(17):1-9.
doi: 10.11924/j.issn.1000-6850.casb2021-1183
[6] 孙健, 王敬国, 刘化龙, 等. 黑龙江省主栽水稻品种的遗传多样性分析. 作物杂志, 2011(1):63-66.
[7] 张希瑞, 高文硕, 王敬国, 等. 吉林省水稻品种的遗传多样性及株型演化分析. 江苏农业学报, 2019, 35(3):497-505.
[8] Liu K, Muse S V. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics, 2005, 21(9):2128- 2129.
doi: 10.1093/bioinformatics/bti282 pmid: 15705655
[9] Tamura K, Dudley J, Nei M, et al. MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Molecular Biology and Evolution, 2007, 24:1596-1599.
doi: 10.1093/molbev/msm092 pmid: 17488738
[10] Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology, 2005, 14:2611-2620.
doi: 10.1111/j.1365-294X.2005.02553.x pmid: 15969739
[11] 张立娜, 曹桂兰, 韩龙植. 利用SSR标记揭示中国粳稻地方品种遗传多样性. 中国农业科学, 2012, 45(3):405-413.
doi: 10.3864/j.issn.0578-1752.2012.03.001
[12] Salem K F M, Sallam A. Analysis of population structure and genetic diversity of Egyptian and exotic rice (Oryza sativa L.) genotypes. Comptes Rendus Biologies, 2016, 339(1):1-9.
doi: 10.1016/j.crvi.2015.11.003
[13] Li W, Bian C M, Wei Y M, et al. Evaluation of genetic diversity of Sichuan common wheat landraces in China by SSR Markers. Journal of Integrative Agriculture, 2013, 12(9):1501-1511.
doi: 10.1016/S2095-3119(13)60418-9
[14] Li L J, Yang K C, Pan G T, et al. Genetic diversity of maize populations developed by two kinds of recurrent selection methods investigated with SSR Markers. Agricultural Sciences in China, 2008, 7(9):1037-1045.
doi: 10.1016/S1671-2927(08)60144-3
[15] 李修平, 刘琪, 邵红, 等. 寒地水稻种质资源遗传多样性分析. 分子植物育种, 2021, 19(16):5528-5534.
[16] 王敬国. 东北亚地区粳稻遗传多样性及主要株型性状与SSR标记的关联分析. 哈尔滨:东北林业大学, 2014.
[17] 邵国军, 李玉福, 邱福林. 辽宁省水稻育种研究与进展. 辽宁农业科学, 1995(6):28-32.
[18] 刘丹, 王嘉宇, 刘进, 等. 黑龙江省部分育成粳稻资源的遗传多样性分析. 植物遗传资源学报, 2019, 20(1):60-68.
[19] 程芳艳, 李春光, 刘永巍, 等. 寒地部分粳稻的遗传多样性及遗传结构分析. 沈阳农业大学学报, 2014, 45(6):649-654.
[1] Sun Yuantao, Long Wenjing, Li Yuan, Liu Tianpeng, Zhao Ganlin, Ding Guoxiang, Ni Xianlin. Genetic Diversity Analysis of 45 Glutinous Sorghum Germplasms Based on Major Agronomic Traits and SSR Markers [J]. Crops, 2024, 40(1): 57-64.
[2] Wang Yueying, Fan Baojie, Cao Zhimin, Wang Yan, Su Qiuzhu, Zhang Zhixiao, Wang Shen, Shi Huiying, Shen Yingchao, Cheng Xuzhen, Liu Changyou, Tian Jing. Genetic Diversity Analysis of Landraces and Improved Varieties of Mung Bean by EST-SSR Markers [J]. Crops, 2024, 40(1): 73-79.
[3] Zhao Feng, Bao Qijun, Pan Yongdong, Liu Xiaoning, Zhang Huayu, Niu Xiaoxia. Comprehensive Evaluation of Genetic Diversity in 70 Barley Germplasms [J]. Crops, 2023, 39(6): 54-61.
[4] Yang Enze, Wang Shuyan, Liu Ruixiang, Shi Fengyuan, Zhang Jinhao, Li Jiana, Li Zhiwei, Guo Zhanbin. Genetic Diversity Analysis of Quinoa Germplasm Resources Based on SRAP [J]. Crops, 2023, 39(6): 79-85.
[5] Liu Qiuyuan, Li Meng, Gao Yangguang, Shi Mengyu, Wei Yunfei, Ji Xin, Li Li, Liu Yali, Wang Fujuan. Effects of Different Nitrogen Fertilization Patterns on Yield and Quality of Conventional Japonica Rice under Reduced Nitrogen [J]. Crops, 2023, 39(5): 131-137.
[6] Zhang Shangpei, Yang Junxue, Luo Shiwu, Wang Yong, Zhang Xiaojuan, Cheng Bingwen. Genetic Diversity and Yielding Ability Analysis of Agronomic Traits in Broom Corn Millet [J]. Crops, 2023, 39(5): 37-42.
[7] Gao Zhanning, Yang Yongqian, Wang Shujie, Feng Hui, Xue Zhenggang. Comprehensive Evaluation of 143 Barley Germplasm Resources [J]. Crops, 2023, 39(5): 59-65.
[8] Zhai Jing, Yang Shengming, Wang Yuzhen, Shi Linlin. Effects of Multi-Year Organic Fertilizer Application on Starch Physicochemical Properties of Mid-Mature Soft Japonica Rice [J]. Crops, 2023, 39(5): 91-97.
[9] ChenZhikai , Hou Wanwei. Evaluation and Selection of Pisumsativum L. Germplasm Resources Based on Agronomic Traits [J]. Crops, 2023, 39(4): 38-43.
[10] Li Qingfeng, Gao Jie, Peng Qiu. Genetic Diversity Analysis of Agronomic and Quality Characteristics of Amaranthus Resources in Guizhou Province [J]. Crops, 2023, 39(4): 60-64.
[11] Li Hongsheng, Li Shaoxiang, Yang Zhonghui, Yang Jiali, Liu Kun, Xiong Shian, Li Fuqian, Guo Hui, Yang Mujun. Comparison ofPhenotype and Marker Detection in Seed Purity of Thermo-Photo Sensitive Two-Line WheatHybrids [J]. Crops, 2023, 39(4): 71-76.
[12] Chen Cuiping, Yan Dianhai, Zhang Shumiao, Zuo Haonan, Gao Sen, Liu Yang. Fingerprint Construction and Genetic Diversity Analysis of Quinoa Based on SSR Markers [J]. Crops, 2023, 39(3): 35-42.
[13] Song Yun, Zhang Xinrui, He Jiaxin, Li Zheng, Sun Zhe, Li Aoxuan, Qiao Yonggang. Genetic Diversity Analysis of Sophora flavescens Ait. Germplasm Resources Based on cpSSR Markers [J]. Crops, 2023, 39(1): 30-37.
[14] Guo Huanle, Tang Bin, Li Han, Cao Zhongyang, Zeng Qiang, Liu Liangwu, Chen Zhihui. Comprehensive Evaluation of Phenotypic Traits and Classification of Maize Landraces in Hunan Province [J]. Crops, 2022, 38(6): 33-41.
[15] Zhao Xiaoqin, Jia Ruiling, Liu Junxiu, Liu Yanming, Wen Yinhua, Shi Lili, Zhang Juanning, Ma Ning. Agronomic Traits and Genetic Diversity Analysis of 120 Foxtail Millet Germplasms [J]. Crops, 2022, 38(6): 61-69.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!