Dataset Information

Effects of Integrating and Non-Integrating Reprogramming Methods on Copy Number Variation and Genomic Stability of Human Induced Pluripotent Stem Cells.

ABSTRACT: Human-induced pluripotent stem cells (iPSCs) are derived from differentiated somatic cells using defined factors and provide a renewable source of autologous cells for cell therapy. Many reprogramming methods have been employed to generate human iPSCs, including the use of integrating vectors and non-integrating vectors. Maintenance of the genomic integrity of iPSCs is highly desirable if the cells are to be used in clinical applications. Here, using the Affymetrix Cytoscan HD array, we investigated the genomic aberration profiles of 19 human cell lines: 5 embryonic stem cell (ESC) lines, 6 iPSC lines derived using integrating vectors ("integrating iPSC lines"), 6 iPSC lines derived using non-integrating vectors ("non-integrating iPSC lines"), and the 2 parental cell lines from which the iPSCs were derived. The genome-wide copy number variation (CNV), loss of heterozygosity (LOH) and mosaicism patterns of integrating and non-integrating iPSC lines were investigated. The maximum sizes of CNVs in the genomes of the integrating iPSC lines were 20 times higher than those of the non-integrating iPSC lines. Moreover, the total number of CNVs was much higher in integrating iPSC lines than in other cell lines. The average numbers of novel CNVs with a low degree of overlap with the DGV and of likely pathogenic CNVs with a high degree of overlap with the ISCA (International Symposium on Computer Architecture) database were highest in integrating iPSC lines. Different single nucleotide polymorphisms (SNP) calls revealed that, using the parental cell genotype as a reference, integrating iPSC lines displayed more single nucleotide variations and mosaicism than did non-integrating iPSC lines. This study describes the genome stability of human iPSCs generated using either a DNA-integrating or non-integrating reprogramming method, of the corresponding somatic cells, and of hESCs. Our results highlight the importance of using a high-resolution method to monitor genomic aberrations in iPSCs intended for clinical applications to avoid any negative effects of reprogramming or cell culture.

SUBMITTER: Kang X

PROVIDER: S-EPMC4488894 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Effects of Integrating and Non-Integrating Reprogramming Methods on Copy Number Variation and Genomic Stability of Human Induced Pluripotent Stem Cells.

Kang Xiangjin X Yu Qian Q Huang Yuling Y Song Bing B Chen Yaoyong Y Gao Xingcheng X He Wenyin W Sun Xiaofang X Fan Yong Y

PloS one 20150701 7

Human-induced pluripotent stem cells (iPSCs) are derived from differentiated somatic cells using defined factors and provide a renewable source of autologous cells for cell therapy. Many reprogramming methods have been employed to generate human iPSCs, including the use of integrating vectors and non-integrating vectors. Maintenance of the genomic integrity of iPSCs is highly desirable if the cells are to be used in clinical applications. Here, using the Affymetrix Cytoscan HD array, we investig ...[more]

PMID: 26131765

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Project description:Human-induced pluripotent stem cells (iPSCs) are derived from differentiated somatic cells using defined factors and provide a renewable source of autologous cells for cell therapy. Many reprogramming methods have been employed to generate human iPSCs, including the use of integrating vectors and non-integrating vectors. Maintenance of the genomic integrity of iPSCs is highly desirable if the cells are to be used in clinical applications. Here, using the Affymetrix Cytoscan HD array, we investigated the genomic aberration profiles of 19 human cell lines: 5 embryonic stem cell (ESC) lines, 6 iPSC lines derived using integrating vectors (“integrating iPSC lines”), 6 iPSC lines derived using non-integrating vectors (“non-integrating iPSC lines”), and the 2 parental cell lines from which the iPSCs were derived. The genome-wide copy number variation (CNV), loss of heterozygosity (LOH) and mosaicism patterns of integrating and non-integrating iPSC lines were investigated. The maximum sizes of CNVs in the genomes of the integrating iPSC lines were 20 times higher than those of the non-integrating iPSC lines. Moreover, the total number of CNVs was much higher in integrating iPSC lines than in other cell lines. The average numbers of novel CNVs with a low degree of overlap with the DGV and of likely pathogenic CNVs with a high degree of overlap with the ISCA database were highest in integrating iPSC lines. Different SNP calls revealed that, using the parental cell genotype as a reference, integrating iPSC lines displayed more single nucleotide variations and mosaicism than did non-integrating iPSC lines. This study describes the genome stability of human iPSCs generated using either a DNA-integrating or non-integrating reprogramming method, of the corresponding somatic cells, and of hESCs. Our results highlight the importance of using a high-resolution method to monitor genomic aberrations in iPSCs intended for clinical applications to avoid any negative effects of reprogramming or cell culture. 19 human cell lines: 5 embryonic stem cell (ESC) lines, 6 iPSC lines derived using integrating vectors (“integrating iPSC lines”), 6 iPSC lines derived using non-integrating vectors (“non-integrating iPSC lines”), and the 2 parental cell lines from which the iPSCs were derived.

Project description:Copy number variations (CNVs) are gain and loss of DNA sequence of a genome. High throughput platforms such as microarrays and next generation sequencing technologies (NGS) have been applied for genome wide copy number losses. Although progress has been made in both approaches, the accuracy and consistency of CNV calling from the two platforms remain in dispute. In this study, we perform a deep analysis on copy number losses on 254 human DNA samples, which have both SNP microarray data and NGS data publicly available from Hapmap Project and 1000 Genomes Project respectively. We show that the copy number losses reported from Hapmap Project and 1000 Genome Project only have < 30% overlap, while these reports are required to have cross-platform (e.g. PCR, microarray and high-throughput sequencing) experimental supporting by their corresponding projects, even though state-of-art calling methods were employed. On the other hand, copy number losses are found directly from HapMap microarray data by an accurate algorithm, i.e. CNVhac, almost all of which have lower read mapping depth in NGS data; furthermore, 88% of which can be supported by the sequences with breakpoint in NGS data. Our results suggest the ability of microarray calling CNVs and the possible introduction of false negatives from the unessential requirement of the additional cross-platform supporting. The inconsistency of CNV reports from Hapmap Project and 1000 Genomes Project might result from the inadequate information containing in microarray data, the inconsistent detection criteria, or the filtration effect of cross-platform supporting. The statistical test on CNVs called from CNVhac show that the microarray data can offer reliable CNV reports, and majority of CNV candidates can be confirmed by raw sequences. Therefore, the CNV candidates given by a good caller could be highly reliable without cross-platform supporting, so additional experimental information should be applied in need instead of necessarily.

Project description:BackgroundAutosomal recessive osteopetrosis is a genetically and phenotypically heterogeneous disease, caused by defects in osteoclast formation and function. The only available treatment is allogeneic stem cell transplantation that has still high morbidity and mortality. The goal of the present study was to generate iPSCs from bone marrow-derived MSCs of osteopetrosis patients with three most common mutations by using two different integration-free gene transfer methods and compare their efficiencies. The secondary objective was to select the most appropriate integration-free production method for our institutional iPSC bank using this rare disease as a prototype.MethodsTwo different integration-free gene transfer methods (episomal and Sendai viral vectors) were tested and compared on the same set of patient samples exhibiting three different mutations associated with osteopetrosis. Generated iPSCs were characterized by standard assays, including immunophenotyping, immunocytochemistry, RT-PCR, embryoid body, and teratoma assays. Karyotype analyses were performed to evaluate genetic stability.ResultsiPSC lines exhibiting typical ESC-like colony morphology were shown to express pluripotency markers by immunofluorescence staining. Over 90% of the cells were found positive for SSEA-4 and OCT3/4 and negative/weak positive for CD29 by flow cytometry. Immunohistochemical staining of teratoma and spontaneously differentiated embryoid body sections confirmed their trilineage differentiation potential. All iPSC lines expressed pluripotency-related genes. Karyotype analyses were found normal. Direct sequencing of PCR-amplified DNA showed that disease-related mutations were retained in the patient-specific iPSCs.ConclusionGeneration of iPSC using SeV and episomal DNA vectors have several advantages over other methods like the ease of production, reliability, high efficiency, and safety, which is required for translational research. Furthermore, owing to the pluripotency and self-renewal capacity, patient-specific iPSCs seem to be ideal cell source for the modeling of a rare genetic bone disease like osteopetrosis to identify osteoclast defects, leading to clinical heterogeneity in osteopetrosis patients, especially among those with different mutations in the same gene.

Dataset Information

Effects of Integrating and Non-Integrating Reprogramming Methods on Copy Number Variation and Genomic Stability of Human Induced Pluripotent Stem Cells.

Publications

Effects of Integrating and Non-Integrating Reprogramming Methods on Copy Number Variation and Genomic Stability of Human Induced Pluripotent Stem Cells.

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