Phenotype Analysis Method for Identification of Gene Functions Involved in Asymmetric Division of Caenorhabditis elegans.
In gene function analysis, it is arduous to identify gene function individually, and the way to screen out all involved genes according to a particular phenotype or disease usually shows us little information for a specific problem. We present a data-driven analysis system based on wild type (WT) embryos to study the concrete function of each gene associated with certain category of abnormal phenotypes. It can be applied to genes with very few RNAi embryos. Instead of presupposing the particular function of a gene, its function is confirmed by the statistical testing of built models. The scheme includes the following five: first, verify the to be detected genes and determine related recognized features according to the given category; second, compute the value of each feature based on WT embryos and merge them by principal component analysis (PCA); third, for each of the selected components of PCA, build a normal distribution and verify its normality; fourth, project the RNAi embryos to each component and probe them; and finally, analyze the more detailed functions of each gene based on the physical or biological meaning of each component. Choosing the first-round asymmetric division process of Caenorhabditis elegans as the phenotype, experimental results show that on the different aspects of the asymmetric division process, par-2, par-3, and let-754 are related to scalar differences; dcn-1 and mcm-5 are associated with the divergences of scalar variation, which may reflect the disaccord in development; and dcn-1, par-2, and par-3 are involved with morphological discrepancies.
1 Graduate School of Information Science and Engineering, Ritsumeikan University , Kusatsu, Shiga, Japan .|2 College of Computer Science and Technology, Huaqiao University , Xiamen, Fujian, China .
Sihai
S
Yang
1 Graduate School of Information Science and Engineering, Ritsumeikan University , Kusatsu, Shiga, Japan .
Xianhua
X
Han
3 Laboratory for Developmental Dynamics, RIKEN Quantitative Biology Center , Kobe, Hyogo, Japan .
Yukako
Y
Tohsato
3 Laboratory for Developmental Dynamics, RIKEN Quantitative Biology Center , Kobe, Hyogo, Japan .
Koji
K
Kyoda
3 Laboratory for Developmental Dynamics, RIKEN Quantitative Biology Center , Kobe, Hyogo, Japan .
Shuichi
S
Onami
1 Graduate School of Information Science and Engineering, Ritsumeikan University , Kusatsu, Shiga, Japan .
Ikuko
I
Nishikawa
1 Graduate School of Information Science and Engineering, Ritsumeikan University , Kusatsu, Shiga, Japan .
Yenwei
Y
Chen
D000465:Algorithms; D000818:Animals; D060049:Asymmetric Cell Division; D017173:Caenorhabditis elegans / Q000196:embryology / Q000235:genetics / Q000502:physiology*; D029742:Caenorhabditis elegans Proteins / Q000235:genetics* / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods; D018507:Gene Expression Regulation, Developmental; D020868:Gene Silencing; D010641:Phenotype; D025341:Principal Component Analysis
D029742:Caenorhabditis elegans Proteins
C. elegans; PCA; asymmetric division; gene function analysis; shape