Pattathil Sivakumar, Ingwers Miles W, Aubrey Doug P, Li Zenglu, Dahlen Joseph
Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA.
Institute of Plant Breeding, Genetics, and Genomics/ Department of Crop and Soil Sciences, University of Georgia, Athens, USA.
Carbohydr Res. 2017 Aug 7;448:128-135. doi: 10.1016/j.carres.2017.06.009. Epub 2017 Jun 19.
Glycome profiling allows for the characterization of plant cell wall ultrastructure via sequential extractions and subsequent detection of specific epitopes with a suite of glycan-specific monoclonal antibodies (mAbs). The data are often viewed as the amount of materials recovered and coinciding colored heatmaps of mAb binding are generated. Interpretation of these data can be considered qualitative in nature as it depends on detecting subtle visual differences in antibody binding strength. Here, we report a mixed model-based quantitative approach for glycome profile analyses, which accounts for the amount of materials recovered and displays the normalized values in revised heatmaps and statistical heatmaps depicting significant differences. The utility of this methodology was demonstrated on a previously published dataset investigating the effects of moisture stress on the roots and needles of Pinus taeda. An annotated R script for the quantitative methodology is included to allow future studies to utilize the same approach.
糖组分析可通过连续提取以及随后用一系列聚糖特异性单克隆抗体（mAb）检测特定表位来表征植物细胞壁超微结构。数据通常被视为回收材料的量，并生成与mAb结合相对应的彩色热图。这些数据的解释本质上可被视为定性的，因为它取决于检测抗体结合强度中细微的视觉差异。在此，我们报告了一种基于混合模型的糖组分析定量方法，该方法考虑了回收材料的量，并在经修订的热图和显示显著差异的统计热图中展示归一化值。这种方法的实用性在先前发表的一个研究水分胁迫对火炬松根和针叶影响的数据集上得到了证明。文中包含了用于该定量方法的带注释的R脚本，以便未来的研究能够采用相同的方法。
