Meticulously curated cell line ‘omics data
Combining the power of ATCC’s gold-standard cell lines with QIAGEN’s best-in-class bioinformatics solutions, we have developed ATCC Cell Line Land—a meticulously curated, ISO 9000–compliant database designed to facilitate the discovery of biomarkers and therapeutic targets, prediction of drug efficacy, and exploration of gene regulatory pathways.
Playbook Features & benefits Application examples Resources
- Expertly curated RNA-seq and whole-exome sequencing data from ATCC's human and mouse cell lines, with over 1,000 new datasets added every year.
- Cell lines are cultured and sequenced under ISO-compliant conditions, so you can trust that data are reliable and traceable to authenticated materials.
- Essential metadata like standard culture conditions, extraction protocols, sample preparation, and NGS library preparation are provided.
- Each ‘omics dataset and associated metadata are processed and curated using our uniform data processing and metadata curation standards.
Why data provenance matters
Cell models are the starting point for preclinical studies that help researchers understand the underlying mechanisms of normal and disease biology. However, the use of misidentified cell lines and inaccurate public datasets can adversely affect biomedical research, leading to false conclusions and non-reproducible data that can compound with each subsequent study. For scientists to make insightful correlations that can translate to the development of life-saving therapeutics, it is essential that they start with high-quality, authenticated biological materials backed by curated, accurate 'omics data.
"The high-quality 'omics datasets in ATCC Cell Line Land are traceable to the authenticated cells in our biorepository. This not only guarantees maximum data provenance but also enables researchers to quickly identify and access the cell lines they need for their research, saving valuable time and resources."– Jonathan Jacobs, PhD, Senior Director of Bioinformatics, ATCC |
Features and benefits
By combining QIAGEN's best-in-class bioinformatics solutions with ATCC's fully authenticated and characterized cell lines, researchers are offered unparalleled access to authentic, reproducible, and traceable datasets that correspond to ATCC's physical material. This digital resource allows researchers to efficiently identify suitable cell models based on gene expression and mutation profiles for specific applications.
- Use as a reference control in your experimental setting
- Build hypotheses and design experiments
- Access carefully curated metadata
- Compare gene expression across or within cell lines
- Perform differential gene expression analysis
- Analyze pathway and gene interactomes
- Discover biomarkers and therapeutic targets
- Predict drug treatment responses
- Investigate molecular mechanism of disease pathogenesis
- Purchase the corresponding authenticated ATCC source material
Application examples
Predict drug sensitivity and optimize cell line selection
In this figure, we demonstrate that the baseline gene expression levels in various cancer cell lines can be evaluated. These data can be used for selecting appropriate models for drug screening against a candidate target gene. Each cell line's gene expression profile is analyzed to identify those with expression patterns most relevant to the target gene. In this example, the x-axis indicates the number of RNA sequencing datasets produced from biological replicates of the respective cell line, each containing a minimum of three biological replicates. Purple indicates induction while dark blue indicates reduction.
Evaluate the differential expression patterns of specific genes in normal and cancerous tissues
In this figure, the mRNA expression of the VHL gene shows significant differences between normal kidney tissue and kidney cancer tissue, particularly in clear cell renal cell carcinoma (ccRCC). In ccRCC, the VHL gene is often inactivated due to mutations, leading to reduced mRNA expression compared to normal kidney tissue.
Compare differentially expressed genes between cell lines
This volcano plot shows differentially expressed genes in the BDCM (ATCC CRL-2740) cell line (acute myelogenous leukemia) compared to the COLO829BL (ATCC CRL-1980) cell line (B lymphoblast normal). The x-axis represents the log2 fold change, and the y-axis represents the -log10 p-value.
