The chromatin of cancer

Peer reviewe

Structural perspective of cooperative transcription factor binding

In prokaryotes, individual transcription factors (TFs) can recognize long DNA motifs that are alone sufficient to define the genes that they induce or repress. In contrast, in higher organisms that have larger genomes, TFs recognize sequences that are too short to define unique genomic positions. In addition, development of multicellular organisms requires molecular systems that are capable of executing combinatorial logical operations. Co-operative recognition of DNA by multiple TFs allows both definition of unique genomic positions in large genomes, and complex information processing at the level of individual regulatory elements. The TFs can co-operate in multiple different ways, and the precise mechanism used for co-operation determines important features of the regulatory interactions. Here, we present an overview of the structural basis of the different mechanisms by which TFs can cooperate, focusing on insight from recent functional studies and structural analyses of specific TF-TF-DNA complexes.Peer reviewe

Seed-driven Learning of Position Probability Matrices from Large Sequence Sets

Peer reviewe

Counting absolute number of molecules using unique molecular identifiers

Advances in molecular biology have made it easy to identify different DNA or RNA species and to copy them. Identification of nucleic acid species can be accomplished by reading the DNA sequence; currently millions of molecules can be sequenced in a single day using massively parallel sequencing. Efficient copying of DNA-molecules of arbitrary sequence was made possible by molecular cloning, and the polymerase chain reaction. Differences in the relative abundance of a large number of different sequences between two or more samples can in turn be measured using microarray hybridization and/or tag sequencing. However, determining the relative abundance of two different species and/or the absolute number of molecules present in a single sample has proven much more challenging. This is because it is hard to detect individual molecules without copying them, and even harder to make defined number of copies of molecules. We show here that this limitation can be overcome by using unique molecular identifiers (umis), which make each molecule in the sample distinct

MODER2: First-order Markov Modeling and Discovery of Monomeric and Dimeric Binding Motifs

Motivation: Position-specific probability matrices (PPMs, also called position-specific weight matrices) have been the dominating model for transcription factor (TF)-binding motifs in DNA. There is, however, increasing recent evidence of better performance of higher order models such as Markov models of order one, also called adjacent dinucleotide matrices (ADMs). ADMs can model dependencies between adjacent nucleotides, unlike PPMs. A modeling technique and software tool that would estimate such models simultaneously both for monomers and their dimers have been missing. Results: We present an ADM-based mixture model for monomeric and dimeric TF-binding motifs and an expectation maximization algorithm MODER2 for learning such models from training data and seeds. The model is a mixture that includes monomers and dimers, built from the monomers, with a description of the dimeric structure (spacing, orientation). The technique is modular, meaning that the co-operative effect of dimerization is made explicit by evaluating the difference between expected and observed models. The model is validated using HT-SELEX and generated datasets, and by comparing to some earlier PPM and ADM techniques. The ADM models explain data slightly better than PPM models for 314 tested TFs (or their DNA-binding domains) from four families (bHLH, bZIP, ETS and Homeodomain), the ADM mixture models by MODER2 being the best on average.Peer reviewe

Transcriptional networks controlling the cell cycle.

In this work, we map the transcriptional targets of 107 previously identified Drosophila genes whose loss caused the strongest cell-cycle phenotypes in a genome-wide RNA interference screen and mine the resulting data computationally. Besides confirming existing knowledge, the analysis revealed several regulatory systems, among which were two highly-specific and interconnected feedback circuits, one between the ribosome and the proteasome that controls overall protein homeostasis, and the other between the ribosome and Myc/Max that regulates the protein synthesis capacity of cells. We also identified a set of genes that alter the timing of mitosis without affecting gene expression, indicating that the cyclic transcriptional program that produces the components required for cell division can be partially uncoupled from the cell division process itself. These genes all have a function in a pathway that regulates the phosphorylation state of Cdk1. We provide evidence showing that this pathway is involved in regulation of cell size, indicating that a Cdk1-regulated cell size checkpoint exists in metazoans

Upregulation of ribosome biogenesis via canonical E-boxes is required for Myc-driven proliferation

The transcription factor Myc drives cell growth across animal phyla and is activated in most forms of human cancer. However, it is unclear which Myc target genes need to be regulated to induce growth and whether multiple targets act additively or if induction of each target is individually necessary. Here, we identified Myc target genes whose regulation is conserved between humans and flies and deleted Myc-binding sites (E-boxes) in the promoters of fourteen of these genes in Drosophila. E-box mutants of essential genes were homozygous viable, indicating that the E-boxes are not required for basal expression. Eight E-box mutations led to Myc-like phenotypes; the strongest mutant, ppan(Ebox-/-), also made the flies resistant to Myc-induced cell growth without affecting Myc-induced apoptosis. The ppan(Ebox-/-) flies are healthy and display only a minor developmental delay, suggesting that it may be possible to treat or prevent tumorigenesis by targeting individual downstream targets of Myc.Peer reviewe

A competitive precision CRISPR method to identify the fitness effects of transcription factor binding sites

Here we describe a competitive genome editing method that measures the effect of mutations on molecular functions, based on precision CRISPR editing using template libraries with either the original or altered sequence, and a sequence tag, enabling direct comparison between original and mutated cells. Using the example of the MYC oncogene, we identify important transcriptional targets and show that E-box mutations at MYC target gene promoters reduce cellular fitness. A competitive CRISPR method discovers targets and phenotypic effects of the MYC oncogene.Peer reviewe

Nucleosome-bound SOX2 and SOX11 structures elucidate pioneer factor function.

'Pioneer' transcription factors are required for stem-cell pluripotency, cell differentiation and cell reprogramming1,2. Pioneer factors can bind nucleosomal DNA to enable gene expression from regions of the genome with closed chromatin. SOX2 is a prominent pioneer factor that is essential for pluripotency and self-renewal of embryonic stem cells3. Here we report cryo-electron microscopy structures of the DNA-binding domains of SOX2 and its close homologue SOX11 bound to nucleosomes. The structures show that SOX factors can bind and locally distort DNA at superhelical location 2. The factors also facilitate detachment of terminal nucleosomal DNA from the histone octamer, which increases DNA accessibility. SOX-factor binding to the nucleosome can also lead to a repositioning of the N-terminal tail of histone H4 that includes residue lysine 16. We speculate that this repositioning is incompatible with higher-order nucleosome stacking, which involves contacts of the H4 tail with a neighbouring nucleosome. Our results indicate that pioneer transcription factors can use binding energy to initiate chromatin opening, and thereby facilitate nucleosome remodelling and subsequent transcription