Oral communication, GL5

Official XXIst International Pigment Cell Conference website - 21-24 Sept 2011, Bordeaux - France | updated: September 04 2011

Availability of transcriptional regulatory network analysis by next-generation sequencer

SPEAKER Y. Hayashizaki #whois submiter ?
AUTHOR(s) Y. Hayashizaki

The emergence of high-throughput techniques has led to so-called data-driven biology, in which data obtained doesn’t need a hypothesis about the biology, as opposed to when a hypothesis is tested within the framework of a pre-existing theory. We take a hybrid approach, in which high-throughput biology is driven by computational predictions of hypothetical genes. In FANTOM (Functional Annotation of Mammalian Genome), an international consortium we initiated, we recently have shown transcriptional control in the human monocytic cell line THP-1 throughout a differentiation time course. Using deepCAGE (a new deep sequencing application) we measured the dynamics of genome-wide transcription start site (TSS) usage over time for the first time and used comparative genomic regulatory site predictions in the regions by deepCAGE to identify the key transcription factors driving differentiation, their time-dependent activities, and their target genes. Using systematic siRNA knockdown of key transcription factors we have confirmed the role of individual factors in the differentiation process and mapped a suite of transcription factors required to maintain the undifferentiated state as well asto change from proliferation to differentiation. Our analysis of growth arrest and differentiation goes against the concept of a single “master regulator”, Instead we emphasize that cellular states are constrained by complex networks involving substantial numbers of both positive and negative regulators. We have found 29,857 active promoters during differentiation of monoblast to monocyte (with 99.99% accuracy). In the FANTOM collaboration we have created a map of transcription regulation using the concept of motif activity and the degree of activity. If you introduce these key factors to the cell you can control its phenotype, for example, from fibroblast to monocyte (precursor cell to mature or highly differentiated cell). Such knowledge is very useful in applications of regenerative medicine and most importantly the information can be used to examine the potential for oncogenicity and monitor the safety of “destination” (the target) cell.



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Université de Bordeaux 2 & Conseil Régional Aquitaine