Deciphering the genome's regulatory code: The many languages of DNA

Rister, Jens; Desplan, Claude

doi:10.1002/bies.200900197

Cited by 23 publications

(21 citation statements)

References 31 publications

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“…Through the use of ChIP (including ChIP-chip and ChIP-Seq) and 3-C (chromatin conformation capture), TCF has been found to bind at multiple sites—ranging from 330,000 base pairs upstream of the major start site to 30,000 base pairs downstream—and it is generally agreed on the basis of 3C experiments that TCF that is bound at these various sites loops to the promoter to stimulate c-myc expression 29–34. The degree to which these individual sites are redundant or are components of independently acting cis -regulatory modules (CRMs) is not known 35. The biological relevance of these sites is attested to by the presence of a colon cancer–associated SNP, 450 kb upstream of the c-myc transcription start site, that converts a weaker TCF4-binding site into a stronger one.…”

Section: C-myc Is Regulated By a Host Of Signals Transcription Factomentioning

confidence: 99%

"You Don't Muck with MYC"

Levens

2010

Genes & Cancer

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MYC homeostasis is critical for major cellular and organismal processes. The physiological and pathologic patterns of c-myc transcription are programmed by a large number of cis-elements and transfactors (RNAs and proteins). These elements and factors receive inputs from a multitude of intracellular and extracellular pathways. Because c-myc regulation has customarily been dissected element by element and factor by factor, it has been difficult to appreciate how the c-myc promoter and regulatory sequences operate as a system. A full accounting of the regulation of c-myc transcription will require an understanding of the dynamic interplay of these factors and elements with one another, with chromatin, and with the changes in DNA structure and topology that are inevitably coupled with gene activity.

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Section: C-myc Is Regulated By a Host Of Signals Transcription Factomentioning

confidence: 99%

"You Don't Muck with MYC"

Levens

2010

Genes & Cancer

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“…61 To answer such questions we will need to learn a lot more about the preferred modes of mutational change during evolution (cf. review of transposition in this issue of Evolutionary Anthropology), 62 the grammar of gene regulation, 63 and the logic of developmental pathways. 64 How was the original circuitry tweaked genetically over evolutionary time to reconfigure developmental processes so that an old structure could serve a new function?…”

Section: Organ Shaping Via Origami Foldingmentioning

confidence: 99%

The evolutionary geometry of human anatomy: Discovering our inner fly

Held¹

2010

Evolutionary Anthropology

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The human body is one still frame in a very long evolutionary movie. Anthropologists focus on the last few scenes, whereas geneticists try to trace the screenplay back as far as possible. Despite their divergent time scales (millions versus billions of years), both disciplines share a reliance on a third field of study whose scope spans only a matter of days to months, depending on the organism. Embryology is crucial for understanding both the pliability of anatomy and the modularity of gene circuitry. The relevance of human embryology to anthropology is obvious. What is not so obvious is the notion that equally useful clues about human anatomy can be gleaned by studying the development of the fruit fly, an animal as different from us structurally as it is distant from us evolutionarily. The underlying kinship between ourselves and flies has only become apparent recently, thanks to revelations from the nascent field of evolutionary developmental biology, or evo-devo. All bilaterally symmetric animals, it turns out, share a common matrix of body axes, a common lexicon of intercellular signals, and a common arsenal of genetic gadgetry that evolution has tweaked in different ways in different lineages to produce a dazzling spectrum of shapes and patterns. Anthropologists can exploit this deep commonality to search our genome more profitably for the mutations that steered us so far astray from our fellow apes.

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“…Among other possible arrangements, a typical CRM consists of dense clusters of similar signals (Halfon 2006), which is a key feature exploited by the statistical methods developed for their detection (see below). The identification of CRMs has been an object of intensive bioinformatics research (Wasserman & Sandelin 2004, Elnitski et al 2006, van Nimwegen 2007, Rister & Desplan 2010, Medina-Rivera et al 2011. For a long time, the detection of DNA elements on a genomic scale was only attempted in silico and with limited success (Wasserman & Sandelin 2004, Hannenhalli 2008.…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics applied to gene transcription regulation

Altobelli

2012

Journal of Molecular Endocrinology

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Understanding regulation of gene transcription is central to molecular biology as well as being of great interest in medicine. The molecular syntax of the concerted transcriptional activation/repression of gene networks in mammal cells, which shape the physiological response to the molecular signals, is often unknown or not completely understood. Combining genome-wide experiments within silicoapproaches opens the way to a more systematic comprehension of the molecular mechanisms of transcription regulation. Diverse bioinformatics tools have been developed to help unravel these mechanisms, by handling and processing data at different stages: from data collection and storage to the identification of molecular targets and from the detection of DNA motif signatures in the regulatory sequences of functionally related genes to the identification of relevant regulatory networks. Moreover, the large amount of genome-wide scale data recently produced has attracted professionals from diverse backgrounds to this cutting-edge realm of molecular biology. This mini-review is intended as an orientation for multidisciplinary professionals, introducing a streamlined workflow in gene transcription regulation with emphasis on sequence analysis. It provides an outlook on tools and methods, selected from a host of bioinformatics resources available today. It has been designed for the benefit of students, investigators, and professionals who seek a coherent yet quick introduction toin silicoapproaches to analyzing regulation of gene transcription in the post-genomic era.

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Deciphering the genome's regulatory code: The many languages of DNA

Cited by 23 publications

References 31 publications

"You Don't Muck with MYC"

"You Don't Muck with MYC"

The evolutionary geometry of human anatomy: Discovering our inner fly

Bioinformatics applied to gene transcription regulation

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