Scientia Agricultura Sinica ›› 2018, Vol. 51 ›› Issue (12): 2248-2262.doi: 10.3864/j.issn.0578-1752.2018.12.003

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

SSR Analyser:A Special Software Suitable for SSR Fingerprinting of Plant Varieties

WANG FengGe1, LI Xin2, YANG Yang1, YI HongMei1, JIANG Bin2, ZHANG XianChen2, HUO YongXue2, ZHU Li2, GE JianRong1, WANG Rui1, REN Jie1, WANG Lu1, TIAN HongLi1, ZHAO JiuRan1   

  1. 1Maize Research Center, Beijing Academy of Agricultural and Forestry Sciences/Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing 100097; 2BeijingTodaysoft Limited Company, Beijing 100083
  • Received:2018-02-06 Online:2018-06-16 Published:2018-06-16

Abstract: 【Objective】Develop software tools for plant variety identification by SSR fingerprinting to realize the automatic and standardized analysis of plant variety identification, solving problems of low efficiency of data collection and hard for data sharing et al for SSR markers in practice. 【Method】Based on commercialized software GeneMarker®, develop and optimize algorithms to deal with the specialty of SSR fingerprinting analysis for data analysis, panel design, database synchronization et al. SSR Analyser is generated as personalized software and tested on maize and other crops for its effectiveness. 【Result】From the perspective of processing function, the software is able to first weakly eliminate pull-up peak using matrix by system calculation. Then, use matching algorithm with single peak removal method to completely remove pull-up peak automatically and correctly. By optimizing the reading algorithm of N+1 peak, stutter peak et al, unrecognized/inaccurate/mis-reading of special peak is solved. Therefore, it is more accurate for Dinucleotide SSR markers’ fingerprinting. By completing the filtering algorithm of neighboring peak, high and low peak, and diploid crops, it solves the problem of effective peak collection for blended samples. From the perspective of panel design, the software balances the flexibility, convenience and uniformity. On the premise of standardized data collection, the software is more suitable for complicated experiment: enhances the flexibility of marker parameter settings, which include setting parameters at one time for specific species using panels, or setting parameters individually for electrophoresis gel for each primer locus; realizes that generating new panels from existing markers; ensures the unification by calling panels and its synchronous updating. By seamless connecting the software and fingerprinting database management system, it realizes the automation and standardization from sample preparation to fingerprint collection, which makes the database more intuitive and traceable. Using the SSR Analyser for building database of maize indicates that the software is more efficient than the original software, which is 10 times of efficiency; After expanding the SSR Analyser’s application scope to rice, soybean, cucumber, watermelon, Chinese cabbage and other diploid crops, and polyploidy crops such as wheat and cotton, suggests that it is more applicable to diploid crops for polyploidy crops, markers developed based on diploid principle have better application. However, other types of markers need optimization on filtering algorithm. 【Conclusion】SSR Analyser is simple and effective in data analysis, which can accurately collect special peak for SSR markers. It is suitable for fingerprint collection of mixed samples and seamless connects with fingerprint database system, which greatly improves the application of SSR markers in plant variety identification.

Key words: plant varieties, SSR, DNA fingerprinting, fluorescent capillary electrophoresis, software development

[1]    Guichoux E, Lagache L, Wagner S, Chaumeil P, LÉGer P, Lepais O, Lepoittevin C, Malausa T, Revardel E, Salin F, Petit R J. Current trends in microsatellite genotyping. Molecular Ecology Resources, 2011, 11(4): 591-611.
[2]    Lü Y, Liu Y, Zhao H. mInDel: a high-throughput and efficient pipeline for genome-wide InDel marker development. BMC Genomics, 2016, 17(1): 290.
[3]    Jones E S, Sullivan H, Bhattramakki D, Smith J S C. A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.). Theoretical and Applied Genetics, 2007, 115(3): 361-371.
[4]    Sánchez-Pérez R, Ballester J, Dicenta F, Arús P, Martínez-Gómez P. Comparison of SSR polymorphisms using automated capillary sequencers, and polyacrylamide and agarose gel electrophoresis: Implications for the assessment of genetic diversity and relatedness in almond. Scientia Horticulturae, 2006, 108(3): 310-316.
[5]    Phillips N R. Expert systems for high throughput analysis of single source samples: A comparison of GeneMarker® HID v1.71 and GeneMapper® ID v3.2 and Validation of GeneMapper® ID v3.2. Dissertations & Theses - Gradworks, 2009.
[6]    Chatterji S, Pachter L. Reference based annotation with GeneMapper. Genome Biology, 2006, 4(7): R29.
[7]    Tsukada K, Harayama Y, Itoga Y, Shimizu M, Kurasawa Y, Kasahara K. Comparison of DNA typing using AmpFlSTR Yfiler and PowerPlex Y System, for specimens subject to very long storage. Forensic Science International: Genetics Supplement Series, 2013, 4(1): e162-e163.
[8]    Bessetti J. Using GeneMapper® ID with Promega STR Systems. Profiles in DNA, 2005, 8(2): 14-15.
[9]    Holland M M, Parson W. GeneMarker® HID: A Reliable software tool for the analysis of forensic STR data. Journal of Forensic Sciences, 2011, 56(1): 29-35.
[10]   Ream W, Gellar B, Trempy J, Field K. Adding Size Standards to Peak Scanner - Molecular Microbiology Laboratory (Second Edition)-Appendix I. Molecular Microbiology Laboratory: Academic Press, 2013: 197-202.
[11]   Gill P, Sparkes R, Pinchin R, Clayton T, Whitaker J, Buckleton J. Interpreting simple STR mixtures using allele peak areas. Forensic Science International, 1998, 91: 41-53.
[12]   Bill M, Gill P, Curran J, Clayton T, Pinchin R, Healy M, Buckleton J. PENDULUM-a guideline-based approach to the interpretation of STR mixtures. Forensic Science International, 2005, 148(2/3): 181-189.
[13]   Slooten K. Validation of DNA-based identification software by computation of pedigree likelihood ratios. Forensic Science International Genetics, 2011, 5(4): 308-315.
[14]   Gill P, Kirkham A, Curran J. LoComatioN: A software tool for the analysis of low copy number DNA profiles. Forensic Science International, 2007, 166(2/3): 128-138.
[15]   Perlin M W, Legler M M, Spencer C E, Smith J L, Allan W P, Belrose J L, W D B. Validating TrueAllele® DNA Mixture Interpretation.pdf. Journal of Forensic Sciences, 2011, 56(6): 1430-1447.
[16]   Haned H. Forensim: an open-source initiative for the evaluation of statistical methods in forensic genetics. Forensic Science International Genetics, 2011, 5: 265-268.
[17]   Hansson O, Gill P. Evaluation of GeneMapper® ID-X mixture analysis tool. Forensic Science International Genetics Supplement, 2011, 3(1): e11-e12.
[18]   He H, Snyder-Leiby T, Qi R, Liu J. Analysis of DNA mixtures in GeneMarker® HID software: with or without single source reference samples. SoftGenetics, 2009.
[19]   Schumm J W, Cunningham H M, Cave C A, Stafford S, Leonard D A. The BodeChecks solution: A high throughput analysis software combining GeneMapper® ID, FSS-i3, LIMS, and artificial intelligence. Forensic Science International: Genetics Supplement Series, 2008, 1(1): 125-127.
[20]   Rossum T V, Tripp B, Daley D. SLIMS-a user-friendly sample operations and inventory management system for genotyping labs. Bioinformatics, 2010, 26(14): 1808-1810.
[21]   Hu N, Cong B, Li S, Ma C, Fu L, Zhang X. Current developments in forensic interpretation of mixed DNA samples (Review). Biomedical Reports, 2014, 2(3): 309-316.
[22]   王凤格, 唐浩, 邓超, 周泽宇, 韩瑞玺, 易红梅, 金石桥, 张力科, 赵久然, 吕波, 堵苑苑, 田红丽. NY/T2594-2016 植物品种鉴定DNA分子标记法 总则.北京: 中国农业出版社, 2016.
Wang F G, Tang H, Deng C, Zhou Z Y, Hang R X, Yi H M, Jin S Q, Zhang L K, Zhao J R, Lü B, Du Y Y, Tian H L. NY/T2594- 2016 General guideline for identification of plant varieties using DNA markers. Beijing: China Agriculture Press, 2016. (in Chinese)
[23]   White J, Hughes-Stamm S, Gangitano D. Development and validation of a rapid pcr method for the powerplex® 16 hs system for forensic DNA identification. International Journal of Legal Medicine, 2015, 129(4): 715-723.
[24]   Schumm J W, Gutierrez-Mateo C, Tan E, Selden R. A 27-locus STR assay to meet all United States and European law enforcement agency standards. Journal of Forensic Sciences, 2013, 58(6): 1584-1592.
[25]   刘文彬, 许理文, 王凤格, 赵久然, 冯博, 赵涵, 吕远大, 蔚荣海. 基于两种荧光毛细管电泳平台筛选评估玉米新型SSR引物. 玉米科学, 2017, 25(2): 24-30.
Liu W B, Xu L W, Wang F G, Zhao J R, Feng B, Zhao H, Lü Y D, Yu R H. Evaluating and screening new maize SSR primer based on two kinds of fluorescent capillary electrophoresis platform. Journal of Maize Sciences, 2017, 25(2): 24-30. (in Chinese)
[26]   Bang T C D, Raji A A, Ingelbrecht I L. A multiplex microsatellite marker kit for diversity assessment of large cassava (Manihot esculenta Crantz) germplasm. Plant Molecular Biology Reporter, 2011, 29(3): 655-662.
[27]   Soltis D E, Soltis P S, H L. Molecular data and the dynamic nature of polyploidy. Critical Reviews in Plant Sciences, 1993, 12(3): 243-273.
[28]   王凤格, 易红梅, 赵久然, 刘平, 张新明, 田红丽, 堵苑苑. NY/T 1432-2014 玉米品种鉴定技术规程 SSR标记法. 北京: 中国农业出版社, 2014.
Wang F G, Yi H M, Zhao J R, Liu P, Zhang X M, Tian H L, Du Y Y. NY/T 1432-2014 Protocol for the identification of maize varieties-SSR marker method. Beijing: China Agriculture Press, 2014. (in Chinese)
[29]   徐群, 魏兴华, 庄杰云, 吕波, 袁筱萍, 刘平, 张新明, 余汉勇, 堵苑苑. NY/T 1433-2014 水稻品种鉴定技术规程 SSR标记法.北京: 中国农业出版社,2014.
Xu Q, Wei X H, Zhuang J Y, Lü B, Yuan Y P, Liu P, Zhang X M, Yu H Y, Du Y Y. NY/T 1433-2014 Protocol for identification of rice varieties-SSR marker method. Beijing: China Agriculture Press, 2014. (in Chinese)
[30]   赵昌平, 支巨振, 邱军, 庞斌双, 刘丽华, 王立新, 谷铁城, 刘丰 泽, 吴明生, 刘阳娜, 张立平, 张风廷, 李宏博, 赵海燕. NY/T2859-2015 主要农作物品种真实性SSR分子标记检测普通小麦. 北京: 中国农业出版社, 2015.
Zhao C P, Zhi J Z, Qiu J, Pang B S, Liu L H, Wang L X, Gu T C, Liu F Z, Wu M S, Liu Y N, Zhang L P, Zhang F T, Li H B, Zhao H Y. NY/T2859-2015 Variety genuineness testing of main crops with SSR markers heat (Triticum aestivum L.). Beijing: China Agriculture Press, 2015. (in Chinese)
[31]   杨剑波, 路曦结, 何团结, 陆徐忠, 郑曙峰, 张小娟, 倪金龙. NY/T 2634-2014 棉花品种真实性鉴定 SSR分子标记法.北京: 中国农业出版社, 2014.
Yang J B, Lu X J, He T J, Lu X Z, Zheng S F, Zhang X J, Ni J L. NY/T 2634-2014 Identification genuineness of cotton varieties using SSR markers. Beijing: China Agriculture Press, 2014. (in Chinese)
[32]   李晓辉, 王凤华, 张春宵, 张学军, 周海涛, 郝彩环, 李淑芳, 刘艳芝, 陶蕊, 李万军, 徐宁. NY/T 2467-2013 高粱品种鉴定技术规程 SSR分子标记法.北京: 中国农业出版社,2013.
Li X H, Wang F H, Zhang C X, Zhang X J, Zhou H T, Hao C H, LI S F, Liu Y Z, Tao R, Li W J, Xu N. NY/T 2467-2013 Protocol for the identification of sorghum varieties- SSR marker method. Beijing: China Agriculture Press, 2013. (in Chinese)
[33]   苗晗, 张圣平, 顾兴芳, 王烨, 莫青. NY/T 2474-2013 黄瓜品种鉴定技术规程 SSR分子标记法. 北京: 中国农业出版社, 2013.
Miao H, Zhang S P, Gu X F, Wang Y, Mo Q. NY/T 2474-2013 Protocol for the identification of cucumber varieties- SSR marker method. Beijing: China Agriculture Press, 2013. (in Chinese)
[34]   王杰, 高秋, 杨国锋, 孙娟, 马金星, 冯葆昌. 国审苏丹草和高丹草品种SSR指纹图谱构建及遗传多样性分析. 草地学报, 2016, 24(1): 156-164.
Wang J, Gao Q, Yang G F, Sun J, Ma J X, Feng B C. Fingerprint constructing and genetic diversity analyzing of Sorghum sudanense and Sorghum bicolor × Sorghum sudanense with SSR markers. Acta Agrestia Sinica, 2016, 24(1): 156-164. (in Chinese)
[35]   Olejniczak M, Krzyzosiak W J. Genotyping of simple sequence repeats-factors implicated in shadow band generation revisited. Electrophoresis, 2006, 27(19): 3724-3734.
[36]   Guichoux E, Lagache L, Wagner S, Chaumeil P, Léger P, Lepais O, Lepoittevin C, Malausa T, Revardel E, Salin F, Petit RJ. Current trends in microsatellite genotyping. Molecular Ecology Resources, 2011, 11(4): 591-611.
[37]   王凤格, 杨扬, 易红梅, 赵久然, 任洁, 王璐, 葛建镕, 江彬, 张宪晨, 田红丽, 侯振华. 中国玉米审定品种标准SSR指纹库的构建. 中国农业科学, 2017, 50(1): 1-14.
Wang F G, Yang Y, Yi H M, Zhao J R, Ren J, Wang L, Ge J R, Jiang B, Zhang X C, Tian H L, Hou Z H. Construction of an SSR-Based standard fingerprint database for corn variety authorized in China. Scientia Agricultura Sinica, 2017, 50(1): 1-14. (in Chinese)
[38]   Dror I E, Hampikian G. Subjectivity and bias in forensic DNA mixture interpretation. Science & Justice, 2011, 51(4): 204-208.
[39]   郑永胜, 张晗, 王东建, 孙加梅, 王雪梅, 段丽丽, 李华, 王玮, 李汝玉. 基于荧光检测技术的小麦品种SSR鉴定体系的建立. 中国农业科学, 2014, (19): 3725-3735.
Zheng Y S, Zhang H, Wang D J, Sun J M, Wang X M, Duan L L, Li H, Wang W, Li R Y. Development of a wheat variety identification system based on fluorescently labeled SSR markers. Scientia Agricultura Sinica, 2014, 47(19): 3725-3735. (in Chinese)
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