Summary

风土通过概念葡萄果实代谢组学和转录组解释的

Published: October 05, 2016
doi:

Summary

本文描述了为了深入了解风土概念, 非靶向代谢组学,转录和多元统计分析,以葡萄果实成绩单和代谢产物的应用中,环境对果实品质性状的影响。

Abstract

风土指的是,根据特定的生境和管理实践影响作物的特性,如葡萄( 葡萄 )的环境因素的结合。本文将介绍如何某些风土签名可以使用多元统计分析小道消息科维纳品种的浆果代谢和转录组进行检测。该方法首先需要一个适当的采样计划。在这个案例研究中,科维纳品种的特定克隆选择遗传差异最小化,并从代表在三个不同的生长季节三种不同的宏观区域7葡萄园收集样品。一个不相关的LC-MS代谢物组学的方法是,由于其高灵敏度,建议使用MZmine软件和基于碎片树分析的代谢物的识别策略伴有有效的数据处理。可以使用微阵列可以实现全面的转录组分析含探针涵盖〜所有预测葡萄基因的99%,允许所有的差异表达的基因在不同风土的上下文中同时分析。最后,基于投影的方法多元数据分析可以被用来克服强特异性复古效果,允许代谢和转录数据被集成并详细分析以识别信息相关性。

Introduction

根据植物的基因组,转录组,蛋白质组和代谢组大规模数据分析提供了前所未有的洞察复杂系统,如葡萄酒的风土特性反映葡萄植物及其环境之间的相互作用的行为。因为即使在相同的葡萄无性系在不同的葡萄园种植葡萄酒的风土可以是不同的,基因组学分析是没有多大用处,因为克隆的基因组是相同的。相反,它是必要看看基因表达和浆果,决定葡萄酒的品质性状的代谢特性之间的相关性。基因表达在所有转录物的化学性质相似,它通过在芯片开发通用的特点,如杂交固定的探针有利于定量分析转录福利水平的分析。与此相反,普遍在蛋白质组学分析方法第二代谢是由于个别蛋白质和代谢物的巨大的物理和化学多样性更具挑战性。在代谢组学的情况下,这种多样性是更为极端,因为个体代谢物的大小,极性,丰度和波动性大大不同,所以不存在单一的提取工艺或分析方法提供了一个全面的方法。

之间合适的非易失性代谢物的分析平台,那些基于高效液相色谱耦合质谱(HPLC-MS)比等替代性HPLC用紫外线或二极管阵列检测器(HPLC-UV,HPLC-DAD敏感得多)或核磁共振(NMR)谱,但是通过HPLC-MS定量分析可以通过的现象,如基质效应和离子抑制/增强1-3的影响。这种影响通过HPLC-MS的科维纳葡萄果实的分析过程中使用电喷雾离子源(HPLC-E的调查SI-MS),表明糖和其他分子具有最低保留时间强烈低估,也可能反映在这一区域中的大数目的分子,而其它分子的丰度可能被低估,由基体效应高估或未受影响的的,但对基体效应的数据归一化似乎对总体结果4,5-影响有限。本文所描述的方法是成熟期间积聚在高水平葡萄浆果中等极性代谢物的分析优化,这是由风土显著影响。它们包括花青素,黄酮醇,黄烷-3-醇,花青素,类黄酮等,白藜芦醇,二苯乙烯,羟基酸和羟基苯甲酸,它们共同决定了颜色,口味和葡萄酒的健康相关的属性。其它代谢物,如糖和脂族有机酸,是由于基质短跑运动员忽略,因为定量通过HPLC-MS是不可靠T和离子抑制现象5。内通过该方法选择的极性范围,该方法是在它的目的是检测许多不同的代谢物尽可能6未定位。

转录方法,使成千上万的小道消息成绩单可以同时监控由完整的葡萄基因组序列7,8的可用性提供便利。基于高通量测序的cDNA转录早期方法已经发展下一代测序的到来进入统称为RNA测序技术的过程的集合。这种方法正迅速成为首选转录研究方法。然而,基于芯片,这也让成千上万的成绩单并行通过杂交来量化大量文献,积累了葡萄。事实上,在此之前RNA测序成为一种主流技术,很多专门的商用微阵列平台已经开发允许小道消息转录,并详细检查。在广阔的各种平台,只有两个允许的全基因组转录组分析9。最进化阵列允许在单个设备上多达12个独立样品的杂交,从而减少每个实验的成本。 12个子阵列的每个组成代表29549小道消息成绩单135000 60-mer的探针。该装置已在大量的研究10-24被使用。现在这两个平台已经停产,但一个新的定制芯片最近已经设计并表示最近的发展,因为它包含代表附加新发现的基因葡萄树25探头的更大的数字。

通过转录组和代谢组学分析产生的大数据集销售需要对数据进行分析合适的统计方法,包括多元技术来确定不同形式之间的相关性s的数据的。最广泛使用的多元技术是那些基于投影,并且这些可以是无监督,如主成分分析(PCA),或监督,如双向正交投影到潜结构判别分析(O2PLS-DA)26。在这篇文章中介绍的协议采用PCA进行探索性数据分析和O2PLS-DA来确定样本的群体之间的差异。

Protocol

1.选择合适的材料和构造一个抽样计划通过制定适当的采样计划,开始实验。有没有通用的和普遍的方法,使评价对案件逐案基础上每一项计划。确保抽样方案规定的抽样地点,时间和精确的抽样程序。参见图1在这种情况下,研究中使用的抽样方案。 注:在这个案例中,从单一的克隆( 葡萄品种科维纳,克隆48)葡萄浆果从七个商业葡萄园收集于维罗纳省三个不?…

Representative Results

本文中介绍的案例研究产生了最终的数据矩阵包括552信号(M / Z功能),包括分子离子以及它们的同位素,加合物和一些片断,其中189样本相对量化(7葡萄园×3成熟期×3生长季点¯x 3生物学重复)。因此104328用于数据点的总数为。碎片树分析导致282 M / Z功能注释,相应的代谢产物加合物,同位素和片段。由主成分分析整个数据矩阵的探索性分析表明根据熟化?…

Discussion

本文介绍了用于解释葡萄果实风土理念代谢组学,转录和统计分析的协议。通过HPLC-ESI-MS代谢分析是不够敏感,同时检测大量的代谢产物,但相对定量是由基体效应和离子抑制/增强的影响。然而,类似的做法已经被用来形容科维纳浆果的成熟和收获后枯萎,和基体效应的修正对结果5的影响有限。此外,最近的大型多仪器实验室间研究,以确定NMR和LC-MS的用于使用相同样品非靶向代谢物组?…

Divulgazioni

The authors have nothing to disclose.

Acknowledgements

This work benefited from the networking activities coordinated within the EU-funded COST ACTION FA1106 “An integrated systems approach to determine the developmental mechanisms controlling fleshy fruit quality in tomato and grapevine”. This work was supported by the ‘Completamento del Centro di Genomica Funzionale Vegetale’ project funded by the CARIVERONA Bank Foundation and by the ‘Valorizzazione dei Principali Vitigni Autoctoni Italiani e dei loro Terroir (Vigneto)’ project funded by the Italian Ministry of Agricultural and Forestry Policies. SDS was financed by the Italian Ministry of University and Research FIRB RBFR13GHC5 project “The Epigenomic Plasticity of Grapevine in Genotype per Environment Interactions”.

Materials

Mill Grinder IKA IKA A11 basic
HPLC Autosampler Beckman Coulter  - System Gold 508 Autosampler
HPLC System Beckman Coulter  - System Gold 127 Solvent Module HPLC
C18 Guard Column Grace  - Alltima HP C18 (7.5×2.1mm; 5μm) Guard Column
C18 Column Grace  - Alltima HP C18 (150×2.1mm; 3μm) Column
Mass Spectometer Bruker Daltonics  - Bruker Esquire 6000; The mass spectometer was equipped with an ESI source and the analyzer was an ion trap.
Extraction solvents and HPLC buffers Sigma 34966 Methanol LC-MS grade
Sigma 94318 Formic acid LC-MS grade
Sigma 34967 Acetonitrile LC-MS grade
Sigma 39253 Water  LC-MS grade
Minisart RC 4 Syringe filters (0.2 μm) Sartorius 17764
Softwares for data collection (a) and processing (b) Bruker Daltonics Bruker Daltonics Esquire 5.2 Control (a); Esquire 3.2 Data Analysis and MzMine 2.2 softwares (b)
Spectrum Plant Total RNA kit Sigma-Aldrich STRN250-1KT For total RNA extractino from grape pericarps
Nanodrop 1000 Thermo Scientific 1000
BioAnalyzer 2100 Agilent Technologies G2939A
RNA 6000 Nano Reagents Agilent Technologies 5067-1511
RNA Chips Agilent Technologies 5067-1511
Agilent Gene Expression Wash Buffer 1 Agilent Technologies 5188-5325
Agilent Gene Expression Wash Buffer 2 Agilent Technologies 5188-5326
LowInput QuickAmp Labeling kit One-Color Agilent Technologies 5190-2305
Kit RNA Spike In – One-Color Agilent Technologies 5188-5282
Gene Expression Hybridization Kit Agilent Technologies 5188-5242
RNeasy Mini Kit (50) Qiagen 74104 For cRNA Purification
Agilent SurePrint HD 4X44K 60-mer Microarray Agilent Technologies G2514F-048771 
eArray Agilent Technologies https://earray.chem.agilent.com/earray/
Gasket slides Agilent Technologies G2534-60012 Enable Agilent SurePrint Microarray 4-array Hybridization
Thermostatic bath Julabo
Hybridization Chamber Agilent Technologies G2534-60001
Microarray Hybridization Oven Agilent Technologies G2545A
Hybridization Oven Rotator Rack Agilent Technologies G2530-60029
Rotator Rack Conversion Rod Agilent Technologies G2530-60030
Staining kit Bio-Optica 10-2000 Slide-staining dish and Slide rack
Magnetic stirrer device AREX Heating Magnetic Stirrer F20540163 
Thermostatic Oven Thermo Scientific Heraeus – 6030
Agilent Microarray Scanner Agilent Technologies G2565CA
Scanner Carousel, 48-position Agilent Technologies G2505-60502
Slide Holders Agilent Technologies G2505-60525
Feature extraction software v11.5 Agilent Technologies inside the Agilent Microarray Scanner G2565CA
SIMCA + V13 Software Umetrics

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Citazione di questo articolo
Dal Santo, S., Commisso, M., D’Incà, E., Anesi, A., Stocchero, M., Zenoni, S., Ceoldo, S., Tornielli, G. B., Pezzotti, M., Guzzo, F. The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics. J. Vis. Exp. (116), e54410, doi:10.3791/54410 (2016).

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