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利用高效薄层色谱法和光密度法对紫果皮×蓝糊粉层小麦杂交种籽粒花青素进行分析和定量

Profiling and quantification of grain anthocyanins in purple pericarp × blue aleurone wheat crosses by high-performance thin-layer chromatography and densitometry.

作者信息

Böhmdorfer Stefan, Oberlerchner Josua Timotheus, Fuchs Christina, Rosenau Thomas, Grausgruber Heinrich

机构信息

1Department of Chemistry, University of Natural Resources and Life Sciences, Vienna, Konrad Lorenz Str. 24, 3430 Tulln an der Donau, Austria.

2Department of Crop Sciences, University of Natural Resources and Life Sciences, Vienna, Konrad Lorenz Str. 24, 3430 Tulln an der Donau, Austria.

出版信息

Plant Methods. 2018 Mar 31;14:29. doi: 10.1186/s13007-018-0296-5. eCollection 2018.

DOI:10.1186/s13007-018-0296-5
PMID:29610577
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5878423/
Abstract

BACKGROUND

Anthocyanins are abundant secondary metabolites responsible for most blue to blue-black, and red to purple colors of various plant organs. In wheat grains, anthocyanins are accumulated in the pericarp and/or aleurone layer. Anthocyanin pigmented wheat grains can be processed into functional foods with potential health benefits due to the antioxidant properties of the anthocyanins. The grain anthocyanin content can be increased by pyramidizing the different genes responsible for the accumulation of anthocyanins in the different grain layers. Our objective was to develop a high-performance thin-layer chromatography (HPTLC) method that allows the determination of both the anthocyanin profile and the total pigment concentration. Thereby, selection of breeding lines with significantly higher grain anthocyanin content from purple pericarp × blue aleurone wheat crosses should become more efficient than selection based on only visual scoring of grain color and the unspecific determination of anthocyanin concentration by UV/Vis spectroscopy.

RESULTS

A wide variability in the grain anthocyanin content was observed in breeding lines and check varieties. The highest concentration of anthocyanins was observed in deep purple (i.e. combination of the purple pericarp and blue aleurone genetics) grained breeding lines, followed by blue aleurone and purple pericarp genotypes. Determination of the total anthocyanin content was included into the chromatographic analysis, rendering an additional photometric analysis unnecessary. Ten target zones were identified in anthocyanin pigmented wheat grains; four of these zones were typically for blue aleurone types, five for purple pericarp types, and one (i.e. kuromanin glucoside) was characteristic for both. Chemometrics applied to the anthocyanin profile recorded by scanning densitometry revealed that peak heights and peak areas are highly correlated and that seven out of the ten target zones were responsible for about 90% of the total variation in the germplasm. Multivariate analysis of these seven target zones allowed not only a separation of the genetic material into purple, blue and deep purple grained genotypes, but also the identification of genotypes with a specific anthocyanin pattern. Thereby, the original classification by visual scoring was overruled in about one-third of the breeding lines.

CONCLUSIONS

The presented HPTLC method with à côté calibration allowed the profiling of the pigments and quantification of wheat grain anthocyanin content in a single analysis, replacing UV/Vis spectroscopy with subsequent HPLC analysis. Moreover, no sample preparation apart from extraction and filtration is required, and more than 15 samples can be evaluated in one analysis run, corresponding to several dozens of samples per day. Hence, the method fulfills the requirements for screening methods in early generations of a plant breeding program such as high-throughput, small sample size, high repeatability, fast determination, and reasonable costs per sample. Combined with multivariate statistical analysis, the anthocyanin pattern allowed the validation of the genetic background in the offspring of purple × blue wheat crosses and, therefore, the efficient selection of genotypes exhibiting both the cyanidin and delphinidin aglycon.

摘要

背景

花青素是丰富的次生代谢产物,赋予各种植物器官从蓝色到蓝黑色以及从红色到紫色的大部分颜色。在小麦籽粒中,花青素积累在果皮和/或糊粉层中。由于花青素具有抗氧化特性,富含花青素的小麦籽粒可加工成具有潜在健康益处的功能性食品。通过将负责不同籽粒层花青素积累的不同基因进行聚合,可以提高籽粒花青素含量。我们的目标是开发一种高效薄层色谱(HPTLC)方法,用于测定花青素谱和总色素浓度。因此,从紫果皮×蓝糊粉层小麦杂交后代中选择籽粒花青素含量显著更高的育种系,应比仅基于籽粒颜色的目视评分和通过紫外/可见光谱法对花青素浓度进行非特异性测定的选择更为有效。

结果

在育种系和对照品种中观察到籽粒花青素含量存在广泛差异。在深紫色(即紫果皮和蓝糊粉层基因组合)籽粒的育种系中观察到最高浓度的花青素,其次是蓝糊粉层和紫果皮基因型。将总花青素含量的测定纳入色谱分析,无需额外的光度分析。在富含花青素的小麦籽粒中鉴定出10个目标区域;其中4个区域通常为蓝糊粉层类型,5个为紫果皮类型,1个(即矢车菊素葡萄糖苷)是两者共有的特征。应用化学计量学对扫描密度计记录的花青素谱进行分析,结果表明峰高和峰面积高度相关,10个目标区域中的7个区域约占种质总变异的90%。对这7个目标区域进行多变量分析,不仅可以将遗传材料分为紫粒、蓝粒和深紫粒基因型,还可以鉴定出具有特定花青素模式的基因型。因此,约三分之一的育种系推翻了原来的目视评分分类。

结论

所提出的带旁侧校准的HPTLC方法能够在一次分析中对色素进行分析并对小麦籽粒花青素含量进行定量,取代了紫外/可见光谱法及后续的HPLC分析。此外,除了提取和过滤外无需样品制备,一次分析运行可评估15个以上的样品,相当于每天评估几十个样品。因此,该方法满足植物育种计划早期世代筛选方法的要求,如高通量、小样本量、高重复性、快速测定以及每个样品成本合理。结合多变量统计分析,花青素模式能够验证紫×蓝小麦杂交后代的遗传背景,从而有效地选择同时表现出矢车菊素和飞燕草素苷元的基因型。

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