Allele-specific transcriptional effects of subclonal copy number alterations enable genotype-phenotype mapping in cancer cells
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View abstract on PubMed
Summary
This summary is machine-generated.Subclonal copy number alterations drive cancer cell diversity. TreeAlign computationally links DNA and RNA data to reveal clone-specific expression programs, advancing cancer research.
Area Of Science
- Genomics
- Cancer Biology
- Computational Biology
Background
- Subclonal copy number alterations (SCNAs) are common in chromosomally unstable tumors.
- SCNAs contribute to cancer cell heterogeneity and distinct phenotypes.
- The impact of SCNAs on clone-specific phenotypes is not well understood.
Purpose Of The Study
- To develop a computational method for integrating single-cell DNA and RNA sequencing data.
- To accurately model the effects of SCNAs and allelic imbalance on gene expression.
- To enable high-resolution comparison of gene expression programs across distinct cancer clones.
Main Methods
- Developed TreeAlign, a computational tool for integrating single-cell DNA and RNA sequencing data.
- TreeAlign models dosage effects from SCNAs and allelic imbalance on transcription.
- The method obviates the need for a priori phylogenetic clone definition.
Main Results
- TreeAlign provides highly granular definitions of cancer clones.
- Enables high-resolution clone-clone gene expression comparisons.
- Identifies genomically independent expression programs within tumors.
Conclusions
- TreeAlign facilitates the dissection of genomic and epigenetic contributions to cancer gene expression.
- Improves understanding of how SCNAs shape cancer phenotypes.
- Advances the study of cellular heterogeneity in cancer.
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