Data from: Studying developmental variation with Geometric Morphometric Image Analysis (GMIA)

The ways in which embryo development can vary across individuals of a population determine how genetic variation translates into adult phenotypic variation. The study of developmental variation has been hampered by the lack of quantitative methods for the joint analysis of embryo shape and the spatial distribution of cellular activity within the developing embryo geometry. By drawing from the strength of geometric morphometrics and pixel/voxel-based image analysis, we present a new approach for the biometric analysis of two-dimensional and three-dimensional embryonic images. Well-differentiated structures are described in terms of their shape, whereas structures with diffuse boundaries, such as emerging cell condensations or molecular gradients, are described as spatial patterns of intensities. We applied this approach to microscopic images of the tail fins of larval and juvenile rainbow trout. Inter-individual variation of shape and cell density was found highly spatially structured across the tail fin and temporally dynamic throughout the investigated period.

种群内不同个体的胚胎发育差异模式，决定了遗传变异如何转化为成体表型变异。由于此前缺乏可同时分析胚胎形态与发育中胚胎几何结构内细胞活性空间分布的定量方法，发育变异研究的推进受到了阻碍。本研究结合几何形态测量学（geometric morphometrics）与基于像素/体素（pixel/voxel）的图像分析技术的优势，提出了一种面向二维、三维胚胎图像的生物计量分析新方法。对于边界清晰的分化成熟结构，可通过其形态特征进行描述；而对于边界模糊的结构（如新生细胞凝聚体或分子梯度），则可通过强度空间分布模式进行表征。我们将该方法应用于虹鳟（rainbow trout）幼体与稚鱼尾鳍的显微图像分析。研究发现，尾鳍内个体间的形态与细胞密度差异呈现高度的空间结构性，且在整个研究周期内具有显著的时间动态性。