Fernandez Olivier, Urrutia Maria, Bernillon Stéphane, Giauffret Catherine, Tardieu François, Le Gouis Jacques, Langlade Nicolas, Charcosset Alain, Moing Annick, Gibon Yves
UMR 1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140 Villenave d'Ornon, France.
UMR 1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140 Villenave d'Ornon, France ; Plateforme Métabolome Bordeaux, CGFB, MetaboHUB-PHENOME, 33140 Villenave d'Ornon, France.
Metabolomics. 2016;12(10):158. doi: 10.1007/s11306-016-1099-1. Epub 2016 Sep 15.
In the last decade, metabolomics has emerged as a powerful diagnostic and predictive tool in many branches of science. Researchers in microbes, animal, food, medical and plant science have generated a large number of targeted or non-targeted metabolic profiles by using a vast array of analytical methods (GC-MS, LC-MS, H-NMR….). Comprehensive analysis of such profiles using adapted statistical methods and modeling has opened up the possibility of using single or combinations of metabolites as markers. Metabolic markers have been proposed as proxy, diagnostic or predictors of key traits in a range of model species and accurate predictions of disease outbreak frequency, developmental stages, food sensory evaluation and crop yield have been obtained.
(i) To provide a definition of plant performance and metabolic markers, (ii) to highlight recent key applications involving metabolic markers as tools for monitoring or predicting plant performance, and (iii) to propose a workable and cost-efficient pipeline to generate and use metabolic markers with a special focus on plant breeding.
Using examples in other models and domains, the review proposes that metabolic markers are tending to complement and possibly replace traditional molecular markers in plant science as efficient estimators of performance.
在过去十年中，代谢组学已成为许多科学领域中一种强大的诊断和预测工具。微生物学、动物学、食品科学、医学和植物科学领域的研究人员通过使用大量分析方法（气相色谱 - 质谱联用、液相色谱 - 质谱联用、氢核磁共振……）生成了大量靶向或非靶向代谢谱。使用适当的统计方法和模型对此类谱进行综合分析，开启了将单一或多种代谢物组合用作标记物的可能性。代谢标记物已被提议作为一系列模式物种关键性状的替代物、诊断指标或预测指标，并且已经实现了对疾病爆发频率、发育阶段、食品感官评价和作物产量的准确预测。
（i）给出植物性能和代谢标记物的定义，（ii）强调近期将代谢标记物作为监测或预测植物性能工具的关键应用，（iii）提出一个可行且经济高效的流程来生成和使用代谢标记物，特别关注植物育种。
通过列举其他模型和领域的例子，本综述提出代谢标记物在植物科学中作为性能的有效估计指标，正倾向于补充并可能取代传统分子标记物。
