Clustered gene expression changes flank targeted gene loci in knockout mice

Background

Gene expression profiling using microarrays is a powerful technology widely used to study regulatory networks. Profiling of mRNA levels in mutant organisms has the potential to identify genes regulated by the mutated protein.

Methodology/Principle Findings

Using tissues from multiple lines of knockout mice we have examined genome-wide changes in gene expression. We report that a significant proportion of changed genes were found near the targeted gene.

Conclusions/Significance

The apparent clustering of these genes was explained by the presence of flanking DNA from the parental ES cell. We provide recommendations for the analysis and reporting of microarray data from knockout mice     

Gene expression analysis of in vivo fluorescent cells

Background

The analysis of gene expression for tissue homogenates is of limited value because of the considerable cell heterogeneity in tissues. However, several methods are available to isolate a cell type of interest from a complex tissue, the most reliable one being Laser Microdissection (LMD). Cells may be distinguished by their morphology or by specific antigens, but the obligatory staining often results in RNA degradation. Alternatively, particular cell types can be detected in vivo by expression of fluorescent proteins from cell type-specific promoters.

Methodology/Principal Findings

We developed a technique for fixing in vivo fluorescence in brain cells and isolating them by LMD followed by an optimized RNA isolation procedure. RNA isolated from these cells was of equal quality as from unfixed frozen tissue, with clear 28S and 18S rRNA bands of a mass ratio of ∼2∶1. We confirmed the specificity of the amplified RNA from the microdissected fluorescent cells as well as its usefulness and reproducibility for microarray hybridization and quantitative real-time PCR (qRT-PCR).

Conclusions/Significance

Our technique guarantees the isolation of sufficient high quality RNA obtained from specific cell populations of the brain expressing soluble fluorescent marker, which is a critical prerequisite for subsequent gene expression studies by microarray analysis or qRT-PCR.     

SNP array profiling of mouse cell lines identifies their strains of origin and reveals cross-contamination and widespread aneuploidy

Background

The crisis of Misidentified and contaminated cell lines have plagued the biological research community for decades. Some repositories and journals have heeded calls for mandatory authentication of human cell lines, yet misidentification of mouse cell lines has received little publicity despite their importance in sponsored research. Short tandem repeat (STR) profiling is the standard authentication method, but it may fail to distinguish cell lines derived from the same inbred strain of mice. Additionally, STR profiling does not reveal karyotypic changes that occur in some high-passage lines and may have functional consequences. Single nucleotide polymorphism (SNP) profiling has been suggested as a more accurate and versatile alternative to STR profiling; however, a high-throughput method for SNP-based authentication of mouse cell lines has not been described.

Results

We have developed computational methods (Cell Line Authentication by SNP Profiling, CLASP) for cell line authentication and copy number analysis based on a cost-efficient SNP array, and we provide a reference database of commonly used mouse strains and cell lines. We show that CLASP readily discriminates among cell lines of diverse taxonomic origins, including multiple cell lines derived from a single inbred strain, intercross or wild caught mouse. CLASP is also capable of detecting contaminants present at concentrations as low as 5%. Of the 99 cell lines we tested, 15 exhibited substantial divergence from the reported genetic background. In all cases, we were able to distinguish whether the authentication failure was due to misidentification (one cell line, Ba/F3), the presence of multiple strain backgrounds (five cell lines), contamination by other cells and/or the presence of aneuploid chromosomes (nine cell lines).

Conclusions

Misidentification and contamination of mouse cell lines is potentially as widespread as it is in human cell culture. This may have substantial implications for studies that are dependent on the expected background of their cell cultures. Laboratories can mitigate these risks by regular authentication of their cell cultures. Our results demonstrate that SNP array profiling is an effective method to combat cell line misidentification.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-847) contains supplementary material, which is available to authorized users.     

Identification of G1-Regulated Genes in Normally Cycling Human Cells

Background

Obtaining synchronous cell populations is essential for cell-cycle studies. Methods such as serum withdrawal or use of drugs which block cells at specific points in the cell cycle alter cellular events upon re-entry into the cell cycle. Regulatory events occurring in early G1 phase of a new cell cycle could have been overlooked.

Methodology and Findings

We used a robotic mitotic shake-off apparatus to select cells in late mitosis for genome-wide gene expression studies. Two separate microarray experiments were conducted, one which involved isolation of RNA hourly for several hours from synchronous cell populations, and one experiment which examined gene activity every 15 minutes from late telophase of mitosis into G1 phase. To verify synchrony of the cell populations under study, we utilized methods including BrdU uptake, FACS, and microarray analyses of histone gene activity. We also examined stress response gene activity. Our analysis enabled identification of 200 early G1-regulated genes, many of which currently have unknown functions. We also confirmed the expression of a set of genes candidates (fos, atf3 and tceb) by qPCR to further validate the newly identified genes.

Conclusion and Significance

Genome-scale expression analyses of the first two hours of G1 in naturally cycling cells enabled the discovery of a unique set of G1-regulated genes, many of which currently have unknown functions, in cells progressing normally through the cell division cycle. This group of genes may contain future targets for drug development and treatment of human disease.     

Highly parallel genome-wide expression analysis of single mammalian cells

Background

We have developed a high-throughput amplification method for generating robust gene expression profiles using single cell or low RNA inputs.

Methodology/Principal Findings

The method uses tagged priming and template-switching, resulting in the incorporation of universal PCR priming sites at both ends of the synthesized cDNA for global PCR amplification. Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R²∼0.76–0.80 between individual cells and R²∼0.69 between 50 pg total RNA replicates. Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R²∼0.80). Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.

Conclusions/Significance

In summary, our method facilitates whole-genome gene expression profiling in contexts where starting material is extremely limiting, particularly in areas such as the study of progenitor cells in early development and tumor stem cell biology.