Qiao Hui, Tan Jingze, Yan Jun, Sun Chang, Yin Xing, Li Zijun, Wu Jiazi, Guan Haijuan, Wen Shaoqing, Zhang Menghan, Xu Shuhua, Jin Li
State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China.
Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China.
iScience. 2024 Feb 24;27(3):109325. doi: 10.1016/j.isci.2024.109325. eCollection 2024 Mar 15.
The phenotype-first approach (PFA) and data-driven approach (DDA) have both greatly facilitated anthropological studies and the mapping of trait-associated genes. However, the pros and cons of the two approaches are poorly understood. Here, we systematically evaluated the two approaches and analyzed 14,838 facial traits in 2,379 Han Chinese individuals. Interestingly, the PFA explained more facial variation than the DDA in the top 100 and 1,000 except in the top 10 phenotypes. Accordingly, the ratio of heterogeneous traits extracted from the PFA was much greater, while more homogenous traits were found using the DDA for different sex, age, and BMI groups. Notably, our results demonstrated that the sex factor accounted for 30% of phenotypic variation in all traits extracted. Furthermore, we linked DDA phenotypes to PFA phenotypes with explicit biological explanations. These findings provide new insights into the analysis of multidimensional phenotypes and expand the understanding of phenotyping approaches.
表型优先方法（PFA）和数据驱动方法（DDA）都极大地促进了人类学研究以及性状相关基因的定位。然而，人们对这两种方法的优缺点了解甚少。在此，我们系统地评估了这两种方法，并分析了2379名汉族个体的14838种面部特征。有趣的是，除了前10种表型外，在排名前100和前1000的特征中，PFA解释的面部变异比DDA更多。因此，从PFA中提取的异质性特征比例要大得多，而使用DDA在不同性别、年龄和BMI组中发现的同质性特征更多。值得注意的是，我们的结果表明，性别因素在所有提取的特征中占表型变异的30%。此外，我们将DDA表型与PFA表型联系起来，并给出了明确的生物学解释。这些发现为多维表型分析提供了新的见解，并扩展了对表型分析方法的理解。
