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Acta Agronomica Sinica ›› 2020, Vol. 46 ›› Issue (11): 1667-1677.doi: 10.3724/SP.J.1006.2020.04043

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Development of molecular markers and fine mapping of qBN-18 locus related to branch number in soybean (Glycine max L.)

WU Hai-Tao1,3(), ZHANG Yong2, SU Bo-Hong1,3, Lamlom F Sobhi3,4, QIU Li-Juan3,*()   

  1. 1 College of Agriculture, Northeast Agricultural University, Harbin 150030, Heilongjiang, China
    2 Keshan Branch of Heilongjiang Academy of Agricultural Sciences, Qiqihar 161606, Heilongjiang, China
    3 National Key Facility for Gene Resources and Genetic Improvement / Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    4 Plant Production Department, Faculty of Agriculture Saba Basha, Alexandria University, Alexandria, Egypt
  • Received:2020-02-25 Accepted:2020-06-02 Online:2020-11-12 Published:2020-06-22
  • Contact: Li-Juan QIU E-mail:1960478192@qq.com;qiulijuan@caas.cn
  • Supported by:
    The study was supported by the National Key Research and Development Program of China(2016YFD0100201);the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences, and the Protection and Utilization of Soybean Germplasm Resources(2019NWB036-05)

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Abstract:

The branch number is one of the important factors influencing soybean yield, which is directly related to pod setting rate. At the same time, it is also an important component of soybean plant type, and further affects the yield by adjusting the population structure and planting density. At present, there is few report related to map-based cloning of genes related to branch number. Therefore, the discovery of genes/QTL involved in the regulation of soybean branching is of great significance for the basic research on the establishment of plant type and the applied research on the development of high-yielding varieties. In this study, based on the F2 of crossing low-branched variety Kenfeng 19 (KF19) and high-branched variety Kennong 24 (KN24), we developed the F7:8 recombinant inbred line (RIL) population, consisting of 606 lines, and two backcrossing populations consisting of 1486 individuals for KF19-BC3F2 and 1150 individuals for KN24-BC2F2. Within the localization interval of the new QTL of the branch number of chromosome 18 (qBN-18), 11 polymorphism SSR markers were screened out to identify the RIL population, and region of qBN-18 was reduced from 1.6 Mb to 113 kb. After developing two InDel markers BR69 and BR77 in the mapping region, the backcross population was used to screen the exchange individuals, the interval of qBN-18 was further reduced to 63.7 kb, including 9 genes. Those results provide the information for gene map-based cloning and molecular marker assisted breeding of branch number in soybean.

Key words: soybean, branch number, QTL mapping, candidate genes

Table 1

Molecular markers information for fine mapping"

引物名称
Primer name		 物理位置
Physical position (bp)		 正向引物
Forward primer (5'-3')		 反向引物
Reverse primer (5'-3')
BARCSOYSSR_18_1777 54,744,147-54,744,204 CGTTCTTGCATTAAAGGTGGA AACTTCATTGAATTGACGGTGA
BARCSOYSSR_18_1791 54,975,880-54,975,949 TGACCAGTCAATTGTTCATTCTTT TTTACTCAACCATCTCCGCA
BARCSOYSSR_18_1797 55,076,726-55,076,764 AAGCAAAGAGAACCAAAGCG AAAACACGAAAAGGAAGGCA
BARCSOYSSR_18_1803 55,244,106-55,244,173 TTTCGCACTCAATGTCCGTA GTTTCCAAACCACATGGACC
BARCSOYSSR_18_1825 55,701,309-55,701,352 GAATCCACCATCACCAAACC CAATGGCAACCCAGTAAGGT
BARCSOYSSR_18_1827 55,714,562-55,714,637 GCCCCACTCGATGAAATAAA GCTTTGGCAGAAATTCAAGG
BARCSOYSSR_18_1831 55,763,781-55,763,814 TGTTTTTGTTAAATCTTTTGTTTGG TGTGTATGTTTGTGTGTGCACTT
BARCSOYSSR_18_1832 55,775,899-55,775,922 AAAAGCTGAGAGCACAAGGC CGTGCTTTTTCAGTCCCATT
BARCSOYSSR_18_1834 55,877,756-55,877,781 TTGAAGAGGAGAGAAGAATGGTG GGATGTGATTGTTAGAAAAGAAGAA
BARCSOYSSR_18_1841 55,990,705-55,990,750 TGCACGAGGCCATTACATAG TGAAGCGCATATGACTCAACTT
BARCSOYSSR_18_1847 56,075,087-56,075,116 TGGTAGGAGTACTCTGAAGTCATTTTT AGCGCTCAAATGAGATTCCT
BARCSOYSSR_18_1852 56,172,124-56,172,157 TGTGTGCGTAAGGGAGATCA CTACCAACCTCCGCATGTCT
BARCSOYSSR_18_1856 56,223,172-56,223,217 TGGCCATATGCCTAGCTGAT ATGGTGAGCAAACGTCATTG
BARCSOYSSR_18_1875 56,797,313-56,797,366 TGAAAAAGAACGTGTTCAAAATG CGAGTTTCATTCTCGGAAGC

Table 2

Positions of two InDel markers, the primers and the expected length of the amplified fragment"

引物名称
Primer name		 物理位置
Physical
position (bp)		 正向引物
Forward primer (5'-3')		 反向引物
Reverse primer (5'-3')		 片段长度Product size (bp)
垦农24
Kennong 24		 垦丰19
Kenfeng 19
BR69 55,882,229-55,882,378 AGTTGACAGGAACTAAAGTC GATAATTCAAGTAAATAGCGA 156 15
BR77 55,946,063-55,946,342 TCTCTTTGTGTATGTCTTCTCC TTGTTGCATCCAAATGAGAG 268 280

Fig. 1

Identification of branch numbers in KF19, KN24 and the population A: parent plant; B-C: KN24 and KF19 branch number phenotypes in 2018 and 2019, respectively; D-E: histogram of frequency distribution of F7 and F7:8 branch numbers, respectively; F: histogram of the frequency distribution of branch number F2 in the backcross population in 2018. Mean value and standard deviation of parental phenotypes are indicated by vertical dotted lines. Curve represents density plot. ***: P < 0.001."

Table 3

Descriptive statistics of branch number (BN) in parental lines of KN24 and KF19 and their populations of F7, F7:8 in 2018 and 2019"

年份
Year		 分枝数的平均值±标准差
Mean±SD of BN		 群体的分枝数参数
Parameters of BN in populations
KN24 KF19 平均值±标准差
Mean±SD		 范围
Range		 偏度
Skewness		 峰度
Kurtosis
2018 5.5±1.0 0.5±0.5 4.5±1.9 0-10 0.2740 -0.3887
2019 6.8±1.2 0.7±0.6 3.4±1.5 0-8 0.3390 -0.5720

Fig. 2

Branch number QTL qBN-18 of soybean chromosome 18 was located by the RIL populations consisted of KF19 and KN24"

Table 4

Branch number QTLS identified in the F7:8 population of KF19 ×KN24"

群体
Population		 染色体
Chr.		 标记区间
Marker interval		 区间物理位置
Physical position of
interval (bp, Wm82.a2.v1)		 LOD值
LOD value		 表型变异率
PVE (%)		 加性效应
Additive effect
F7:8 18 BARCSOYSSR_18_1834-BARCSOYSSR_18_1841 55,877,756-55,990,750 19.33 14.24 0.75

Fig. 3

Correlation analysis between genotype and phenotypic by BR69 and BR77 markers in RIL population A: correlation analysis between genotype and phenotype of BR69; B: correlation analysis between genotype and phenotype of BR77. The abscissa is the genotype, the multiple branches are denoted as a, the few branches are denoted as b, and the vertical ordinate is the number of branches. ***P < 0.001."

Fig. 4

Validation of qBN-18 locus A: qBN-18 loci between marker BARCSOYSSR_18_1777 and BARCSOYSSR_18_1875 was identified using 1486 individuals of KF19-BC3F2 and 1150 individuals of KN24-BC2F2; B: BARCSOYSSR_18_1791, BARCSOYSSR_18_1803, BARCSOYSSR_18_1827 and BARCSOYSSR_18_1856 were used to identify 568 recombinant strains between BARCSOYSSR_18_1777 and BARCSOYSSR_18_1875; C: qBN-18 is located between tag BR69 and tag BR77. H: heterozygous genotype."

Table 5

Homologous genes and gene annotation of genes in the location interval"

基因
Gene		 同源基因
Homologous gene		 基因注释
Gene annotation
Glyma.18g276900 AT5G11390.1 WPP domain-interacting protein 1
Glyma.18g277000 AT3G02030.1 Pentatricopeptide repeat (PPR) superfamily protein
Glyma.18g277100 AT3G30530.1 Basic leucine-zipper 42
Glyma.18g277300 AT3G02060.1 6-phosphogluconate dehydrogenase family protein
Glyma.18g277600 AT4G25760.1 Glutamine dumper 2
Glyma.18g277700 AT4G15733.1 SCR-like 11

Fig. 5

Expression profiles of nine genes by Phytozome v12.1"

[1] 黄中文, 赵团结, 喻德跃, 陈受宜, 盖钧镒. 大豆产量有关性状QTL的检测. 中国农业科学, 2009,42:4155-4165.
Huang Z W, Zhao T J, Yu D Y, Chen S Y, Gai J Y. Detection of QTLs of yield related traits in soybean. Sci Agric Sin, 2009,42:4155-4165 (in Chinese with English abstract).
[2] 刘金刚, 孙恩玉, 曹永强, 刘艳辉, 刘凤丽. 大豆主要生育性状与产量间的关系分析. 杂粮作物, 2005,25(2):81-83.
Liu J G, Sun E Y, Cao Y Q, Liu Y H, Liu F L. Correlation analysis of the major breeding traits and yield of soybean. Rain Fed Crops, 2005,25(2):81-83 (in Chinese with English abstract).
[3] 胡珀, 韩天富. 植物茎秆性状形成与发育的分子基础. 植物学通报, 2008,25(1):1-13.
Hu B, Han T F. Molecular basis of stem trait formation and development in plants. Chin Bull Bot, 2008,25(1):1-13 (in Chinese with English abstract).
[4] 张永强, 张娜, 王娜, 唐江华, 徐文修, 李亚杰. 种植密度对夏大豆光合特性及产量构成的影响. 核农学报, 2015,29:1386-1391.
Zhang Y Q, Zhang N, Wang N, Tang J H, Xu W X, Li Y J. Effects of plant population on photosynthetic characteristics and yield components of summer soybean. J Nucl Agric Sci, 2015,29:1386-1391 (in Chinese with English abstract).
[5] 董钻, 孙卓韬. 大豆株型、群体结构与产量关系的研究, 第一报: 大豆群体的自动调节和群体内光强、CO2的分布. 大豆科学, 1984,3(2):110-119.
Dong Z, Sun Z T. Research on the relation of soybean plant form, group structure and output I. The automatic regulation of soybean group and the distribution of light intensity and CO2. Soybean Sci, 1984,3(2):110-119 (in Chinese).
[6] Agudamu, Yoshihira T, Shiraiwa T. TBranch development responses to planting density and yield stability in soybean cultivars. Plant Prod Sci, 2016,19:331-339.
[7] Beveridge C A. Axillary bud outgrowth: sending a message. Curr Opin Plant Biol, 2006,9:35-40.
pmid: 16325456
[8] 关荣霞. 大豆重要农艺性状的QTL定位及中国大豆与日本大豆的遗传多样性分析. 中国农业科学院博士后研究工作报告, 北京, 2004.
Guan R X. QTL Mapping of Soybean Agronomic Characters and Genetic Diversity Analysis of Soybean Cultivars from China and Japan. Post Doctoral Working Repor of Chinese Academy of Agricultural Sciences, Beijing, China, 2004 (in Chinese with English abstract).
[9] 陈庆山, 张忠臣, 刘春燕, 辛大伟, 单大鹏, 邱红梅, 单彩云. 大豆主要农艺性状的QTL分析. 中国农业科学, 2007,40:41-47.
Chen Q S, Zhang Z C, Liu C Y, Xin D W, Shan D P, Qiu H M, Shan C Y. QTL analysis of major agronomic traits in soybean. Sci Agric Sin, 2007,40:41-47 (in Chinese with English abstract).
[10] 王珍. 大豆SSR遗传图谱构建及重要农艺性状QTL分析. 广西大学硕士学位论文, 广西南宁, 2004.
Wang Z. Construction of Soybean SSR Based Map and QTL Analysis of Important Agronomic Traits. MS Thesis of Guangxi University, Nanning, Guangxi, China, 2004 (in Chinese with English abstract).
[11] 位艳丽. 大豆农艺和品质性状遗传模型分析与QTL定位. 河南农业大学硕士学位论文, 河南郑州, 2011.
Wei Y L. Genetic Model Analysis and QTL Mapping of Agronomic and Quality Traits in Soybean. MS Thesis of Henan Agricultural University, Zhengzhou, Henan, China, 2011 (in Chinese with English abstract).
[12] 梁慧珍, 余永亮, 杨红旗, 张海洋, 董薇, 李彩云. 大豆产量及主要农艺性状QTL的上位性互作和环境互作分析. 作物学报, 2014,40:37-44.
Liang H Z, Yu Y L, Yang H Q, Zhang H Y, Dong W, Li C Y. Epistatic effects and QTL × environment interaction effects of QTLs for yield and agronomic traits in soybean. Acta Agron Sin, 2014,40:37-44 (in Chinese with English abstract).
[13] 何冉, 关荣霞, 刘章雄, 朱晓丽, 常汝镇, 邱丽娟. 用分离群体中的残余杂合系定位大豆C1连锁群的分枝数qBN-c1-1位点. 中国农业科学, 2009,42:1152-1157.
He R, Guan R X, Liu Z X, Zhu X L, Chang R Z, Qiu L J. Mapping the qBN-c1-1 locus to LG C1 for soybean branching using residual heterozygous lines derived from a segregation population. Sci Agric Sin, 2009,42:1152-1157 (in Chinese with English abstract).
[14] 程立国. 大豆遗传图谱构建和重要性状的QTL定位. 南京农业大学硕士学位论文, 江苏南京, 2008.
Cheng L G. Construction of Genetic Linkage Map and QTL Mapping of Important Traits in Soybean [Glycine max (L.) Merrill]. MS Thesis of Nanjing Agricultural University, Nanjing, Jiangsu, China, 2008 (in Chinese with English abstract).
[15] 丁卉. 利用SSR标记研究大豆对胞囊线虫抗性和主要农艺性状的自然选择效应. 南京农业大学硕士学位论文,江苏南京, 2009.
Ding H. The Natural Selection Effect on Resistance to SCN and Major Agronomic Characters of Soybean by SSR Analysis. MS Thesis of Nanjing Agricultural University, Nanjing, Jiangsu, China, 2009 (in Chinese with English abstract).
[16] 洪雪娟, 黄婧, 丁卉, 侯金锋, 李永春, 盖钧镒, 邢邯. 大豆异地衍生重组自交系群体产量相关性状的QTL定位. 中国油料作物学报, 2014,36:572-579.
doi: 10.7505/j.issn.1007-9084.2014.05.003
Hong H J, Huang J, Ding H, Hou J F, Li Y C, Gai J Y, Xing H. Detection of soybean QTLs on yield-related traits in RIL populations derived from Peking × 7605 in two sites. Chin J Oil Crop Sci, 2014,36:572-579 (in Chinese with English abstract).
[17] 袁道华. 大豆抗胞囊线虫基因遗传机制及育种价值分析. 河南农业大学硕士学位论文, 河南郑州, 2010.
Yuan D H. Genetic Mechanisms and Breeding Value Analysis of Soybean Cyst Nematode Resistance Gene. MS Thesis of Henan Agricultural University, Zhengzhou, Henan, China, 2010 (in Chinese with English abstract).
[18] Sayama T, Hwang T Y, Yamazaki H, Yamaguchi N, Komatsu K, Takahashi M, Suzuki C, Miyoshi T, Tanaka Y, Xia Z J, Tsubokura Y, Watanabe S, Harada K, Funatsuki H, Ishimoto M. Mapping and comparison of quantitative trait loci for soybean branching phenotype in two locations. Breed Sci, 2010,60:380-389.
[19] Yao D, Liu Z Z, Zhang J, Liu S Y, Qu J, Guan S Y, Pan L D, Wang D, Liu J W, Wang P W. Analysis of quantitative trait loci for main plant traits in soybean. Genet Mol Res: GMR, 2015,14:6101-6109.
doi: 10.4238/2015.June.8.8 pmid: 26125811
[20] 张霞. 大豆分枝相关基因的发掘与利用. 中国农业科学院硕士学位论文,北京, 2017.
Zhang X. Identification and Utilization of Genes Related to Branching in Soybean . MS Thesis of Chinese Academy of Agricultural Sciences, Beijing, China, 2017 (in Chinese with English abstract).
[21] Shim S, Kim M Y, Ha J, Lee Y H, Lee S H. Identification of QTLs for branching in soybean [Glycine max(L.) Merrill]. Euphytica, 2017,213:225-233.
doi: 10.1007/s10681-017-2016-z
[22] 谭冰, 郭勇, 邱丽娟. 大豆全基因组分枝相关基因发掘及与QTL共定位. 遗传, 2013,35:793-804.
Tan B, Guo Y, Qiu L J. Whole genome discovery of genes related to branching and co-localization with QTLs in soybean.. Hereditas (Beijing), 2013,35:793-804 (in Chinese with English abstract).
[23] 邱丽娟. 大豆种质资源描述规范和数据标准. 北京: 中国农业出版社, 2006. p 22.
Qiu L J. Description and Data Standards for Soybean [Glycine max (L.) Merrill]. Beijing: China Agriculture Press, 2006. p 22 (in Chinese).
[24] Meng L, Li H H, Zhang L Y, Wang J K. QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations. Crop J, 2015,3:269-283.
doi: 10.1016/j.cj.2015.01.001
[25] Yano M. Genetic and molecular dissection of naturally occurring variation. Curr Opin Plant Biol, 2001,4:130-135.
doi: 10.1016/s1369-5266(00)00148-5 pmid: 11228435
[26] Ashikari M, Matsuoka M. Identification, isolation and pyramiding of quantitative trait loci for rice breeding. Trends Plant Sci, 2006,11:344-350.
doi: 10.1016/j.tplants.2006.05.008 pmid: 16769240
[27] 鲁宁宁, 赵云雷, 王红梅, 陈伟, 赵佩, 龚海燕, 崔艳利, 桑晓慧, 张凯. 基于RIL群体鉴定棉花抗黄萎病相关QTLs. 棉花学报, 2019,31:254-262.
doi: 10.11963/1002-7807.lnnwhm.20190515
Lu N N, Zhao Y L, Wang H M, Chen W, Zhao P, Gong H Y, Cui Y L, Sang X H, Zhang K. Identification of QTLs related to Verticillium wilt resistance based on RIL population. Cotton Sci, 2019,31:254-262 (in Chinese with English abstract).
[28] Kim K S, Diers B W, Hyten D L, Rouf Mian M A, Shannon J G, Nelson R L. Identification of positive yield QTL alleles from exotic soybean germplasm in two backcross populations. Theor Appl Genet, 2012,125:1353-1369.
pmid: 22869284
[29] Takagi H, Abe A, Yoshida K, Kosugi S, Natsume S, Mitsuoka C, Uemura A, Utsushi H, Tamiru M, Takuno S, Innan H, Cano L M, Kamoun S, Terauchi R. QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. Plant J, 2013,74:174-183.
doi: 10.1111/tpj.12105
[30] 巩鹏涛, 李迪. 植物分枝发育的遗传控制. 分子植物育种, 2005,3:151-162.
Gong P T, Li D. Genetic control of plant shoot branching. Mol Plant Breed, 2005,3:151-162 (in Chinese with English abstract).
[31] Kebrom T H, Spielmeyer W, Finnegan E J. Grasses provide new insights into regulation of shoot branching. Trends Plant Sci, 2013,18:41-48.
doi: 10.1016/j.tplants.2012.07.001 pmid: 22858267
[32] Thimann K V, Skoog F. Studies on the growth hormone of plants: III. The inhibiting action of the growth substance on bud development. Proc Natl Acad Sci USA, 1933,19:714-716.
pmid: 16577553
[33] Patel S, Rose A, Meulia T, Dixit R, Cyr R J, Meier I. Arabidopsis WPP-domain proteins are developmentally associated with the nuclear envelope and promote cell division. Plant Cell, 2005,16:3260-3273.
doi: 10.1105/tpc.104.026740 pmid: 15548735
[34] Cao L R, Lu X M, Zhang P Y, Wang G R, Wei L, Wang T C. Systematic analysis of differentially expressed maize ZmbZIP genes between drought and rewatering transcriptome reveals bZIP family members involved in abiotic stress responses. Int J Mol Sci, 2019,20:4103-4127.
doi: 10.3390/ijms20174103
[35] Riechmann J L, Heard J, Martin G, Reuber L, Jiang C Z, Keddie J, Adam L, Pineda O, Ratcliffe D J, Yu G. Arabidopsis transcription factors: Genome-wide comparative analysis among eukaryotes. Science, 2000,290:2105-2110.
pmid: 11118137
[36] Jakoby M, Weisshaar B, Dröge-Laser W, Vicente-Carbajosa J, Tiedemann J, Kroj T, Parcy F. bZIP transcription factors in Arabidopsis. Trends Plant Sci, 2002,7:106-111.
doi: 10.1016/s1360-1385(01)02223-3 pmid: 11906833
[37] Nijhawan A, Jain M, Tyagi A K, Khurana J P. Genomic survey and gene expression analysis of the basic leucine zipper transcription factor family in rice. Plant Physiol, 2008,146:333-350.
doi: 10.1104/pp.107.112821 pmid: 18065552
[38] Silveira A B, Gauer L, Tomaz J P, Cardoso P R, Carmello- Guerreiro S, Vincentz M. The Arabidopsis AtbZIP9 protein fused to the VP16 transcriptional activation domain alters leaf and vascular development. Plant Sci(Oxford), 2007,172:1148-1156.
[39] Fukazawa J, Sakai T, Ishida S, Yamaguchi I, Kamiya Y, Takahashi Y. Repressionr of shoot growth, a bZIP transcriptional activator, regulates cell elongation by controlling the level of gibberellins. Plant Cell, 2000,12:901-915.
doi: 10.1105/tpc.12.6.901 pmid: 10852936
[40] Guan Y C, Ren H B, Xie H, Ma Z Y, Chen F. Identification and characterization of bZIP-type transcription factors involved in carrot (Daucus carota L.) somatic embryogenesis. Plant J, 2009,60:207-217.
doi: 10.1111/j.1365-313X.2009.03948.x pmid: 19519801
[41] Ulm R, Baumann A, Oravecz A, Mate Z, Adam E, Oakeley E J, Schafer E, Nagy F. Genome-wide analysis of gene expression reveals function of the bZIP transcription factor HY5 in the UV-B response of Arabidopsis. Proc Natl Acad Sci USA, 2004,101:1397-1402.
pmid: 14739338
[42] Weltmeier F, Ehlert A, Mayer C S, Dietrich K, Wang X, Schutze K, Alonso R, Harter K, Vicente-Carbajosa J, Droge-Laser W. Combinatorial control of Arabidopsis proline dehydrogenase transcription by specific heterodimerisation of bZIP transcription factors. EMBO J, 2006,25:3133-3143.
doi: 10.1038/sj.emboj.7601206 pmid: 16810321
[43] Kruger N J, Schaewen A V. The oxidative pentose phosphate pathway: Structure and organisation. Curr Opin Plant Biol, 2003,6:236-246.
doi: 10.1016/s1369-5266(03)00039-6 pmid: 12753973
[44] Spielbauer G, Li L, Römisch M L, Do P T, Fouquet R, Fernie A R, Eisenreich W, Gierl A, Settles A M. Chloroplast- localized 6-phosphogluconate dehydrogenase is critical for maize endosperm starch accumulation. J Exp Bot, 2013,64:2231-2242.
doi: 10.1093/jxb/ert082 pmid: 23530131
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