Colbert Matthew W, Rowe Timothy
University of Texas High-Resolution X-ray CT Facility, Jackson School of Geosciences, University of Texas at Austin, Austin, Texas 78712, USA.
J Exp Zool B Mol Dev Evol. 2008 Jul 15;310(5):398-416. doi: 10.1002/jez.b.21212.
Ontogenetic sequences are a pervasive aspect of development and are used extensively by biologists for intra- and interspecific comparisons. A tacit assumption behind most such analyses is that sequence is largely invariant within a species. However, recent embryological and experimental work emphasizes that ontogenetic sequences can be variable and that sequence polymorphism may be far more prevalent than is generally realized. We present a method that uses parsimony algorithms to map hierarchic developmental patterns that capture variability within a sample. This technique for discovering and formalizing sequences is called the "Ontogenetic Sequence Analysis" (OSA). Results of OSA include formalized diagrams of reticulating networks, describe all most parsimonious sequences, and can be used to develop statistics and metrics for comparison of both intraspecific and interspecific sequence variation. The method is tested with examples of human postnatal skeletal ossification, comprising a time-calibrated data set of human hand and wrist epiphyseal unions, and a longitudinal data set of human wrist ossification. Results illustrate the validity of the method for discovering sequence patterns and for predicting morphologies not represented in analytic samples. OSA demonstrates the potential and challenges of incorporating ontogenetic sequences of morphological information into evolutionary analyses.
个体发生序列是发育过程中普遍存在的一个方面,被生物学家广泛用于种内和种间比较。大多数此类分析背后隐含的一个假设是,序列在一个物种内基本不变。然而,最近的胚胎学和实验研究强调,个体发生序列可能是可变的,而且序列多态性可能比普遍认识到的更为普遍。我们提出了一种方法,该方法使用简约算法来绘制层次发育模式,以捕捉样本中的变异性。这种发现和形式化序列的技术被称为“个体发生序列分析”(OSA)。OSA的结果包括网状网络的形式化图表,描述所有最简约的序列,并且可用于开发统计数据和指标,以比较种内和种间的序列变异。该方法通过人类出生后骨骼骨化的例子进行了测试,包括一个经过时间校准的人类手部和腕部骨骺联合数据集,以及一个人类腕部骨化的纵向数据集。结果说明了该方法在发现序列模式和预测分析样本中未出现的形态方面的有效性。OSA展示了将形态信息的个体发生序列纳入进化分析的潜力和挑战。