一种基于E-index方法区分复杂性状的分析工具

doi:10.13523/j.cb.20170214

中国生物工程杂志

2017, Vol. 37

Issue (2): 93-100 DOI: 10.13523/j.cb.20170214

综述

一种基于E-index方法区分复杂性状的分析工具

孙鉴锋¹, 王建新^1,2

1. 北京林业大学信息学院北京 100083;
2. 北京林业大学计算生物学中心北京 100083

An Analysis Tool Based on E-index Method for Differentiating Complex Traits

SUN Jian-feng¹, WANG Jian-xin^1,2

1. School of Information, Beijing Forestry University, Beijing 100083, China;
2. Center for Computational Biology, Beijing Forestry University, Beijing 100083, China

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摘要：

目前，生物遗传学领域在区分复杂性状的研究上正面临着巨大挑战，许多方法都被用来应对这项挑战，其中分子标记法，QTL作图法和序列分析法等就是用来区分控制复杂性状基因的主要应对策略。测定生物复杂性状对于研究生物多样性具有重要意义，也是进一步研究基因控制性状作用机理的重要途径，但是，现有的方法并不成熟也不完善，因此给有效区分复杂性状带来了一定难度。近年来，由于生长曲线能够有效地描述复杂性状，基于生长曲线来区分复杂性状的方法是目前常用的方式，Functional Mapping（FM）就是其中具有代表性的一种方法。在过去的十年间，FM方法是复杂性状区分效果最好的，但不能有效处理非单调类型的生长曲线。Earliness index（E-index）方法的问世，解决了非单调类型的曲线不能有效识别的难题，它能够将任意生物类型的复杂性状发展过程描述为生长曲线并加以区分。基于E-index方法的原理，开发了一套E-index Application（EIA）分析工具，该工具中集成了E-index方法，利用生物数据可视化技术动态绘制生长曲线，包含数据获取、数据处理和结果输出等功能，为遗传工作者的研究提供了良好平台。仿真实验的结果证明了EIA分析工具具有高效、实时和准确的性能，是区分复杂性状的有力工具。

关键词： EIA分析工具; 复杂性状; 生物数据可视化; 生长曲线; E-index

Abstract:

Currently, there are enormous challenges for the research on differentiating complex traits in the field of biogenetics, and many methods are employed to tackle these challenges, among which molecular marker, QTL mapping and sequence analysis are useful in targeting controlling genes for complex traits and thus serve as main coping strategies. To differentiate complex traits is of great importance for biodiversity research and studying genes, and is a key approach to understand the underlying mechanism of gene controlling. The existing methods, however, are not mature and perfect, which therefore have brought much difficulty in effectively differentiating complex traits in the field of biogenetics. Since complex traits can be effectively described as growth curves, methods based on growth curves in recent years are common way to differentiate complex traits, among which functional mapping (FM) is a representative method. although FM method has been one of the best approaches for differentiating complex traits over the past decade, it has been so far confined to deal with those where growth curve is monotonic. Earliness index (E-index) method emerges as required and successfully solves the non-monotonicity situation. Moreover, it is able to deal with any type of biological complex developmental process. Based on the principle of E-index, E-index application (EIA) analysis tool was developed, which provides a good platform for potential genetic researchers and scientists, helping them in several aspects, including data acquisition, drawing growth curves by dynamic data visualization technology, data processing and result retrieval. Results from simulation experiments show that EIA analysis tool is efficient, real-time and accurate, being a powerful tool to differentiate complex traits.

Key words: E-index Biological visualization Complex traits Growth curve EIA analysis tool

收稿日期: 2016-08-26 出版日期: 2017-02-25

ZTFLH:

Q819

基金资助:

国家自然科学基金（61170268）、林业公益性行业科研专项（201404102）资助项目

通讯作者: 王建新 E-mail: wangjx@bjfu.edu.cn

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引用本文:

孙鉴锋, 王建新. 一种基于E-index方法区分复杂性状的分析工具[J]. 中国生物工程杂志, 2017, 37(2): 93-100.

SUN Jian-feng, WANG Jian-xin. An Analysis Tool Based on E-index Method for Differentiating Complex Traits. China Biotechnology, 2017, 37(2): 93-100.

链接本文:

https://manu60.magtech.com.cn/biotech/CN/10.13523/j.cb.20170214 或 https://manu60.magtech.com.cn/biotech/CN/Y2017/V37/I2/93

[1] Sousa S A, Leit?o J H, Martins R C, et al. Bioinformatics applications in life sciences and technologies. Biomed Research International, 2016, 2016(1):1-2.
[2] Wu R, Lin M. Functional mapping——how to map and study the genetic architecture of dynamic complex traits. Nature Reviews Genetics, 2006, 7(3):229-237.
[3] Qi J, Sun J, Wang J. E-index for differentiating complex dynamic traits. Biomed Research International, 2015, 2016(1):1-13.
[4] 陈英, 黄敏仁, 王明麻. 植物遗传转化新技术和新方法. 中国生物工程杂志, 2005, 25(9):94-98. Chen Y, Huang M R, Wang M M. The application of new technology and methods in plant transformation. China Biotechnology, 2005, 25(9):94-98.
[5] Yu G, Wang L G, He Q Y. ChIP seeker:an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics, 2015, 31(14):2382-2383.
[6] Kannan S. Multi-dimensional, multi-configuration compilation phase output visualization technique. Journal of Computing in Civil Engineering, 2016, 23(6):363-371.
[7] Che D, Wang H. GIV:A tool for genomic islands visualization. Bioinformation, 2013, 9(17):879-882.
[8] Geldermann H. Investigations on inheritance of quantitative characters in animals by gene markers I. Methods Tag Theoretical & Applied Genetics Theoretische Und Angewandte Genetik, 1975, 46(7):319-330.
[9] Jansen R C, Nap J P. Genetical genomics:the added value from segregation. Trends in Genetics, 2001, 17(7):388-391.
[10] Martinez M L, Vukasinovic N, Freeman G A. Random model approach for QTL mapping in half-sib families. Genetics Selection Evolution, 1999, 31(4):319-340.
[11] Lander E S, Botstein D. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics, 1989, 121(1):185-199.
[12] Jansen R C. Interval mapping of multiple quantitative trait loci. Genetics, 1993, 135(1):205-211.
[13] Kao C H, Zeng Z B, Teasdale R D. Multiple interval mapping for quantitative trait loci. Genetics, 1999, 152(3):1203-1216.
[14] Zhao W, Chen Y Q, Casella G, et al. A non-stationary model for functional mapping of complex traits. Bioinformatics, 2005, 21(10):2469-2477.
[15] Rieseberg L H, Sinervo B, Linder C R, et al. Role of gene interactions in hybrid speciation:evidence from ancient and experimental hybrids. Science, 1996, 272(5262):741-745.
[16] Wu R, Ma C X, Casella G. Functional mapping of quantitative trait loci underlying the character process:a theoretical framework. Genetics, 2002, 161(4):1751-1762.
[17] Morihara N. An anthropological study on somatometrical characters with growth of the head and face of the Bunun tribe in Taiwan aborigines. Journal of the Kyushu Dental Society, 1988, 42:559-579.
[18] James R M, Panico V D. Evaluation of drag integral using cubic splines. Journal of Aircraft, 2015, 11(8):494-496.
[19] Zimmerman D W. Comparative power of student T test and Mann-Whitney U Test for unequal sample size and variances. Journal of Experimental Education, 2014, 55(3):171-174.
[20] Lawlor B, Walsh P. Engineering bioinformatics:building reliability, performance and productivity into bioinformatics software. Bioengineered, 2015, 6(4):193-203.
[21] Lei M, Li H, Zhang L, et al. QTL Ici mapping:integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations. Crop Journal, 2015, 121(3):269-283.
[22] Hu B, Deng C, Ye J. Design and implementation of visual electronic commerce based on browser/server architecture. Advanced Materials Research, 2011, 271-273:336-339.
[23] 孙清鹏. 生物信息学应用教程. 北京:中国林业出版社, 2012. Sun Q P. Bioinformatics Application Tutorial. Beijing:China Forestry Publication, 2012.
[24] Dan T, Léger S, Belliveau L, et al. Metabo Hunter:an automatic approach for identification of metabolites from 1 H-NMR spectra of complex mixtures. Bmc Bioinformatics, 2011, 12(1):1-22.
[25] Komatsu H, Iguchi T, Ueda M, et al. Clinical and biological significance of transcription termination factor, RNA polymerase I in human liver hepatocellular carcinoma. Oncology Reports, 2016, 35(4):2073-2080.
[26] 高颖, 褚维伟, 张霞,等. 猪粪除臭微生物筛选及其生长曲线测定. 山地农业生物学报, 2011, 30(1):47-51. Gao Y, Zhu W W, Zhang X,et al. Isolation and determination of growth curve of deoderizing microorganism from swine manure. Journal of Mountain Agriculture and Biology, 2011, 30(1):47-51.
[27] Bailey B, Izarra A, Alvarez R, et al. Cardiac stem cell genetic engineering using the αMHC promoter. Regenerative Medicine, 2016, 4(6):823-833.
[28] 郭春叶, 龚月生, 刘林丽,等. 酵母菌生长曲线的测定及其转葡萄芪合酶基因重组菌遗传稳定性的检测. 安徽农业科学, 2007, 35(7):1909-1910. Guo C Y, Gong Y S, Liu L L, et al. Measurement of yeast growth curve and genetic stability examination of recombinant yeast transferred grape stilbene synthase (STS). Journal of Anhui Agricultural Sciences, 2007, 35(7):1909-1910.
[29] Yu C H, Pal L R, Moult J. Consensus genome-wide expression quantitative trait loci and their relationship with human complex trait disease. Omics A Journal of Integrative Biology, 2016, 20(7):400-414.
[30] 李志刚, 朱志军. 大数据时代:生活、工作与思维的大变革. 浙江:浙江人民出版社, 2013. Li Z G, Zhu Z J. Big Data Age:A Revolution That Will Transform How We Live, Work, and Think. Zhejiang:Zhejiang People Press, 2013.
[31] 尤元海, 张建中. 基因表达谱芯片的数据挖掘. 中国生物工程杂志, 2009, 29(10):87-91. You Y H, Zhang J Z.Data mining from microarray gene expression profile. China Biotechnology, 2009, 29(10):87-91.
[32] Kyoda K, Tohsato Y, Ho K H, et al. Biological dynamics markup language (BDML):an open format for representing quantitative biological dynamics data. Bioinformatics, 2015, 31(7):1044-1052.
[33] Kadoch C, Hargreaves D C, Hodges C, et al. Proteomic and bioinformatic analysis of mammalian SWI/SNF complexes identifies extensive roles in human malignancy. Nature Genetics, 2013, 45(6):592-601.
[34] Luo W, Brouwer C. Pathview:an R/Bioconductor package for pathway-based data integration and visualization. Bioinformatics, 2013, 29(14):1830-1831.
[35] Salman A, Malony A, Turovets S, et al. Concurrency in electrical neuroinformatics:parallel computation for studying the volume conduction of brain electrical fields in human head tissues. Concurrency & Computation Practice & Experience, 2015, 28(7):2213-2236.

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