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This article is part of the supplement: Twelfth International Conference on Bioinformatics (InCoB2013): Computational Biology

Open Access Research

Gene expression analysis of induced pluripotent stem cells from aneuploid chromosomal syndromes

Ruosi Zhang12, Lili Hao1, Lingping Wang12, Meili Chen12, Wen Li3, Rujiao Li1, Jun Yu1, Jingfa Xiao1* and Jiayan Wu1*

Author Affiliations

1 The CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China

2 Graduate University of Chinese Academy of Sciences, Beijing 100049, China

3 Chinese Academy of Sciences Key Laboratory of Regenerative Biology, South China Institute for Stem Cell Biology and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Guangzhou 510530, China

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BMC Genomics 2013, 14(Suppl 5):S8  doi:10.1186/1471-2164-14-S5-S8

Published: 16 October 2013

Abstract

Background

Human aneuploidy is the leading cause of early pregnancy loss, mental retardation, and multiple congenital anomalies. Due to the high mortality associated with aneuploidy, the pathophysiological mechanisms of aneuploidy syndrome remain largely unknown. Previous studies focused mostly on whether dosage compensation occurs, and the next generation transcriptomics sequencing technology RNA-seq is expected to eventually uncover the mechanisms of gene expression regulation and the related pathological phenotypes in human aneuploidy.

Results

Using next generation transcriptomics sequencing technology RNA-seq, we profiled the transcriptomes of four human aneuploid induced pluripotent stem cell (iPSC) lines generated from monosomy × (Turner syndrome), trisomy 8 (Warkany syndrome 2), trisomy 13 (Patau syndrome), and partial trisomy 11:22 (Emanuel syndrome) as well as two umbilical cord matrix iPSC lines as euploid controls to examine how phenotypic abnormalities develop with aberrant karyotype. A total of 466 M (50-bp) reads were obtained from the six iPSC lines, and over 13,000 mRNAs were identified by gene annotation. Global analysis of gene expression profiles and functional analysis of differentially expressed (DE) genes were implemented. Over 5000 DE genes are determined between aneuploidy and euploid iPSCs respectively while 9 KEGG pathways are overlapped enriched in four aneuploidy samples.

Conclusions

Our results demonstrate that the extra or missing chromosome has extensive effects on the whole transcriptome. Functional analysis of differentially expressed genes reveals that the genes most affected in aneuploid individuals are related to central nervous system development and tumorigenesis.