The transcription factor Myc is induced by mitogenic signals and regulates downstream cellular responses. If overexpressed, Myc promotes malignant transformation. Myc modulates expression of diverse genes in experimental systems, but few are proven direct targets. Here, we present a large-scale screen for genomic Myc-binding sites in live human cells. We used bioinformatics to select consensus DNA elements (CACGTG or E-boxes) situated in the 5 regulatory region of genes and measured Myc binding to those sequences in vivo by quantitative chromatin immunoprecipitation. Strikingly, most promoter-associated E-boxes showed selective recovery with Myc, unlike non-E-box promoters or E-boxes in bulk genomic DNA. Promoter E-boxes were distributed in two groups bound by Myc at distinct frequencies. The high-affinity group included an estimated 11% of all cellular loci, was highly conserved among different cells, and was bound independently of Myc expression levels. Overexpressed Myc associated at increased frequency with low-affinity targets and, at extreme levels, also with other sequences, suggesting that some binding was not sequence-specific. The strongest DNA-sequence parameter defining high-affinity targets was the location of E-boxes within CpG islands, correlating with an open, preacetylated state of chromatin. Myc further enhanced histone acetylation, with or without accompanying induction of mRNA expression. Our findings point to a high regulatory and biological diversity among Myc-target genes.[Keywords: Human; genome; chromatin; transcription factor; Myc] Supplemental material is available at http://www.genesdev.org.

Survivin is an inhibitor of apoptosis protein, which is over-expressed in most tumors. Aberrant expression of survivin and loss of wild-type p53 in many tumors prompted us to investigate a possible link between these two events. Here we show that wild-type p53 represses survivin expression at both mRNA and protein levels. Transient transfection analyses revealed that the expression of wild-type p53, but not mutant p53, was associated with strong repression of the survivin promoter in various cell types. The over-expression of exogenous survivin protein rescues cells from p53-induced apoptosis in a dose-dependent manner, suggesting that loss of survivin mediates, at least, in part the p53-dependent apoptotic pathway. In spite of the presence of two putative p53-binding sites in the survivin promoter, deletion and mutation analyses suggested that neither site is required for transcriptional repression of survivin expression. This was con®rmed by chromatin immunoprecipitation assays. Further analyses suggested that the modi®cation of chromatin within the survivin promoter could be a molecular explanation for silencing of survivin gene transcription by p53.

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.