Instituto de Biotecnología, CICVyA, INTA, Nicolas Repetto y de los Reseros s/n, Hurlingham, (1686) Buenos Aires, Argentina.
CONICET, Nicolas Repetto y de los Reseros s/n, Hurlingham, (1686) Buenos Aires, Argentina.
Gigascience. 2018 Jul 1;7(7). doi: 10.1093/gigascience/giy073.
Recently, great technical progress has been achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it possible to extract shape and size parameters for genetic, physiological, and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of the platform and segmentation software used are still lacking, and shape descriptions still rely on ad hoc or even contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis, and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations among groups and measure them in shape distance units.
Here, a particular scheme of landmark placement on Arabidopsis rosette images is proposed to study shape variation in viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown, and reproducibility issues are assessed.
Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner.
最近，植物表型领域取得了巨大的技术进步。高通量平台和改进的罗勒叶图像分割算法的发展使得大规模提取遗传、生理和环境研究的形状和大小参数成为可能。低成本表型平台和免费软件资源的开发使得广泛扩展拟南芥表型分析工具成为可能。然而，仍然缺乏可以独立于所使用的平台和分割软件的形状参数客观描述符，并且形状描述仍然依赖于特定的甚至相互矛盾的描述符，这可能使得比较困难，甚至不准确。现代几何形态计量学是定量生物学中的一组方法，被提议成为新兴的表型研究领域的数据和分析工具的主要来源。基于对成像标本上的地标（对应点）的位置，并结合几何、多元分析和强大的统计技术，这些工具提供了在组间重现性和准确地解释形状变化并以形状距离单位进行测量的可能性。
在这里，提出了一种在拟南芥罗勒叶图像上放置地标位置的特定方案，以研究病毒感染过程中的形状变化。在整个感染过程中定量比较对照和感染植物之间的形状差异，并可视化显示。展示了两个不相关的 ssRNA+ 病毒之间的定量比较，并评估了重现性问题。
与最新的自动化平台和植物分割程序相结合，几何形态计量工具可以以客观、可重复的方式促进表型特征的提取和处理。
