Gene-set analysis identifies master transcription factors in developmental courses.
Transcriptional regulation plays key roles in many biological processes. The regulation is dynamic in time and space. Identifying transcription factors that play major roles in a developmental time course is very important for understanding the regulation. This cannot be realized by studying the relation between the expression of individual genes. We developed a gene-set analysis approach to study master regulators and their actively regulated targets during a time course from gene expression data. We applied the method to a mouse liver development data and a mouse embryonic stem cell (mESC) development data, and identified 14 and 9 transcription factors that play major regulatory roles in the two development courses, respectively. Some transcription factors could not be identified as active in the process by studying their correlation with individual targets. The method was also extended for studying other regulation factors or pathways from time-course expression data.
Liu
Ying
Y
MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China.
Jiang
Bo
B
Zhang
Xuegong
X
D000818:Animals; D053595:Embryonic Stem Cells; D018507:Gene Expression Regulation, Developmental; D053263:Gene Regulatory Networks; D008099:Liver; D051379:Mice; D013997:Time Factors; D014157:Transcription Factors / Q000502:physiology*
D014157:Transcription Factors