Quantifying the Spiral Leaf Trait of Arabidopsis from the 3D Shape Model Towards Computational Phenomics
Quantifying the Spiral Leaf Trait of Arabidopsis from the 3D Shape Model Towards Computational Phenomics
复制标题
从计算表型组学的 3D 形状模型量化拟南芥的螺旋叶特征
DOI：
10.11234/gi1990.14.627
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Akihiko Konagaya
中科院分区：
文献类型：
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作者：
E. Kaminuma;N. Heida;Yuko Tsumoto;Minami Matsui;Tetsuro Toyoda;Akihiko Konagaya
近年来，功能基因组学取得了显著进展，计算表型组学的研究显得尤为重要.在RIKEN基因组科学中心，已经产生了超过50，000个模式植物拟南芥的突变株系，用于基因组的饱和诱变[3]。对于功能基因组学的研究来说，建立高通量的表型筛选系统是至关重要的[1]。针对高通量系统，我们提出了一种新的表型分析方法，该方法基于激光测距仪（LRF）[5]的表面测量的三维（3D）模型重建和3D重建模型上形态学性状的计算屏幕[2]。然而，由于人为的主观观察，传统的拟南芥形态性状描述大多是定性的。因此，我们需要将个体形态性状作为客观的数字参数进行定量处理。本文着重研究了莲座叶螺旋叶性状[3，4]，并提出了螺旋叶性状的定量定义。通过对野生型和突变株系的螺旋叶片性状的定量提取实验，展示了基于三维重建模型的螺旋叶片性状精确量化对计算机屏幕的重要性。
Computational phenomics becomes more important in the recently remarkable advance of functionalgenomics. In the RIKEN Genomic Sciences Center, more than 50,000 mutant lines of the modelplant Arabidopsis thaliana have been produced for the saturated mutagenesis of the genome[3]. Forthe research of functional genomics, to establish the high-throughput phenotypic screening systemis a matter of vital importance[1]. Towards the high-throughput system, we have proposed a novelmethodology of the phenotypic analysis which is based on 3-dimensional(3D) model reconstruction viasurface measurement by the laser range nder(LRF)[5] and the computational screens of morphologi-cal traits on the 3D reconstructed model[2]. However, conventional description of morphological traitsof Arabidopsis is mostly qualitative due to subjective human observations. Thus we need to de nequantitatively individual morphological traits to be handled as objectively digital parameters. In thisreport, we focus on the spiral leaf trait[3, 4] as one of 3D-speci c traits at rosette leaves, and proposea quantitative de nition of the spiral leaf trait. Through an experiment to extract the quantitativespiral leaf trait at a wild-type and a mutant line, we exhibit the importance for quantifying traitsprecisely towards computational screens based on the 3D reconstructed model.