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Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome
Published on: June 15, 2016
Seven non-differentially expressed 'dark biomarkers' show transcriptional dysregulation in chronic lymphocytic
Ruihao Xin1,2, Xin Feng3,4, Hang Zhang2
1College of Computer Science and Technology & Key Laboratory of Symbolic Computation & Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China.
Abstract:
Aim: Transcriptional regulation is actively involved in the onset and progression of various diseases. This study used the feature-engineering approach model-based quantitative transcription regulation to quantitatively measure the correlation between mRNA and transcription factors in a reference dataset of chronic lymphocytic leukemia (CLL) transcriptomes. Methods: A comprehensive investigation of transcriptional regulation changes in CLL was conducted using 973 samples in six independent datasets. Results & conclusion: Seven mRNAs were detected to have significantly differential model-based quantitative transcription regulation values but no differential expression between CLL patients and controls. We called these genes 'dark biomarkers' because their original expression levels did not show differential changes in the CLL patients. The overlapping lncRNAs might have contributed their transcripts to the expression miscalculations of these dark biomarkers.

