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Updated: Jan 31, 2026

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish
Published on: October 27, 2017
Personalized discovery of disrupted pathways and significant genes in preeclampsia based on accumulated normal tissue
Ying Luo1, Xiao-Chen Ma1, Qing Gao1
1Department of Prenatal Diagnosis, Jinan Maternity and Child Care Hospital, Jinan 250001, PR China.
Purpose:
This study was designed to identify disrupted pathways in an individual with preeclampsia (PE) using accumulated normal sample data based on individualized pathway aberrance score (iPAS) method.
Materials And Methods:
Pathway data were obtained from the Reactome database. Next, the average Z algorithm was utilized to compute the iPAS. The disrupted pathways in a PE sample were identified by means of t test according to the pathway statistics values of normal and PE samples. In addition, we screened the differential expressed genes (DEGs) using SAMR package and constructed the differential co-expression network comprising DEGs. Subsequently, topological analysis for the co-expression network was conducted to identify hub genes.
Results:
Under the threshold of false discovery rate <0.05, 69 disrupted pathways were selected. Among them, formation of tubulin-folding intermediates by containing t-complex polypeptide 1 (CCT)/TCP1 ring complex (TriC) was the most remarkable pathway. Degree analysis for co-expression network of DEGs suggested that there were several hub-disrupted pathway-related genes, for instance, TCP1 and TUBA1A. More importantly, these two hub genes were enriched in the most significant pathway of formation of tubulin-folding intermediates by CCT/TriC.
Conclusion:
The iPAS method is suitable for identifying disrupted pathways in PE. Pathway of formation of tubulin folding intermediates by CCT/TriC might play important roles in PE.
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