With the completion of Human Genome Project,International HapMap Project and the publication of copy number variation in human genome,a great number of accurate,rapid,and cost-effective technologies for SNP analysis have been developed,promoting the research of the complex diseases.This article presents a review of widely used genotyping techniques,and the progress and prospect in the study of complex diseases in terms of the projects and achievements of Chinese National Human Genome Center at Shanghai(CHGCs).
SHI JinXiu,WANG Ying & HUANG Wei Shanghai-MOST Key Laboratory of Health and Disease Genomics,Chinese National Human Genome Center at Shanghai,Shanghai 201203,China
microRNAs (miRNAs) have been reported to be associated with the pathogenesis and progression of breast cancer.However,little is known about the pathways through which miRNAs regulate these processes,e.g.,the interaction between miRNAs and their target genes with regard to different pathological status of breast cancer,such as histological grades.This study investigated the possible roles of miRNAs in the differentiation of histological grades of breast cancer with a computational approach.Based on a microarray dataset,15 candidate miRNAs were identified,whose predicted target genes are enriched as differentially expressed between grade I and grade III breast tumors.Among them,9 key miRNAs focalize their target genes on 6 central signaling pathways.The SMAD7 protein,the main inhibitory protein in the TGF-β pathway,is predicted as a target of several miRNAs and is also regulated by several other pathways that are possibly targeted by miRNAs.It was hypothesized that miRNAs participate in the differentiation of breast cancer and the TGF-β pathway acts as a major implementary pathway on which several miRNAs take effect through multiple channels.The prediction power of the predicted miRNA target genes was validated on three independent datasets.The differential expression of three miRNAs was validated by real-time PCR on breast carcinoma samples of 10 patients.
