A novel method predicts cancer and immune cell types from bulk tumor gene expression data with the ability to consider uncharacterized and possibly highly variable cell types, which is validated in human genome.
Protein abundance changes across human-induced pluripotent stem cell lines reflect genetic variation across donors, with underlying mechanisms including modulation of RNA expression and modification of protein-coding sequences.
A novel synthetic DNA cassette of CTCF-binding sites combined with the drug-controllable induction system of heterochromatin enabled switchable blocking of chromatin conformation and gene-enhancer interaction.
Single cell expression data can be used to determine how regulatory transcription factors and target genes are connected, and is especially useful when studying transcription factors controlling heterogeneous cell states.
A c-Myc-transcribed long noncoding RNA namely LAST (LncRNA-assisted stabilization of transcripts) collaborates with a cellular factor CNBP to promote the stability of CCND1/cyclin D1 mRNA post-transcriptionally, ensuring the proper G1/Sphase transition of the cell cycle.