The complete (172,282 base pairs) nucleotide sequence of the B95-8 strain of Epstein-Barr virus has been established using the dideoxynucleotide/M13 sequencing procedure. Many RNA polymerase II promoters have been mapped and the mRNAs from these promoters have been assigned to the latent or early/late productive virus cycles. Likely protein-coding regions have been identified and three of these have been shown to encode a ribonucleotide reductase, a DNA polymerase and two surface glycoproteins.

Two methods for increasing the length of DNA sequence data that can be read off a polyacrylamide gel are described. We have developed a rapid way to pour a buffer concentration gradient gel that, by altering the vertical band separation on an autoradiograph, allows more sequence to be obtained from a gel. We also show that the use of deoxyadenosine 5'-(a-[3S]thio)triphosphate as the label incorporated in dideoxynucleotide sequence reactions increases the sharpness of the bands on an autoradiograph and so increases the resolution achieved.Both major rapid DNA sequence determination methods (1, 2) rely on thin denaturing polyacrylamide gels (3) to fractionate single-stranded DNA reaction products. To determine a sufficient length of sequence data from an experiment, it is usual to load aliquots from a reaction onto two or more gels run for various times. It would be advantageous to be able to obtain more sequence from each gel because this would allow either more total sequence to be obtained or fewer gels to be run per reaction. We describe two methods for increasing the amount of readable sequence per gel and demonstrate their effectiveness with the dideoxy sequence analysis technique.One of the main limits on the length of sequence obtainable from an autoradiograph is the progressively poor separation of the bands corresponding to longer DNA molecules. Yet the spacing between the shorter DNA molecules is wider than is required for correct interpretation of the sequence pattern. It is possible, by use of a suitable gradient positioned only in the lower (anode) end of a gel, to selectively reduce the spacing between these shorter DNA molecules. By virtue of having traveled through a greater length of polyacrylamide gel, the higher molecular weight DNA molecules, lying above the gradient, will have an increased separation. We have found that an effective gradient consists of an increase in Tris/borate/EDTA (TBE) buffer concentration towards the bottom of the gel. A limit on the use of gradient gels has been the inconvenience and length of time needed for pouring such gels. We present a rapid technique, using simple apparatus, for pouring gradient gels, making their routine use for DNA sequence analysis realistic.The principle by which a buffer gradient can be used to reduce the vertical band spacing on a polyacrylamide sequencing gel is that, as the buffer concentration increases progressively in the lower 10-15 cm of the gel, electrical resistance per cm down the gel decreases. This is because the buffer is the major charge carrier in the gel. Because the current is constant throughout the length of the gel, by Ohm's law the voltage drop per unit length will also decrease towards the anode. It is the potential difference across the gel that drives the polynucleotide migration, and so a fall in voltage drop per cm will cause a reduction in band migration rate. Thus the spacing between DNA molecules of n and n + 1 nucleotide residues can be reduced as they enter a gradient of increasing buffer concentratio...

Polycomb group (PcG) complexes are multiprotein assemblages that bind to chromatin and establish chromatin states leading to epigenetic silencing. PcG proteins regulate homeotic genes in flies and vertebrates, but little is known about other PcG targets and the role of the PcG in development, differentiation and disease. Here, we determined the distribution of the PcG proteins PC, E(Z) and PSC and of trimethylation of histone H3 Lys27 (me3K27) in the D. melanogaster genome. At more than 200 PcG target genes, binding sites for the three PcG proteins colocalize to presumptive Polycomb response elements (PREs). In contrast, H3 me3K27 forms broad domains including the entire transcription unit and regulatory regions. PcG targets are highly enriched in genes encoding transcription factors, but they also include genes coding for receptors, signaling proteins, morphogens and regulators representing all major developmental pathways.

Identifying the genomic regions bound by sequence-specific regulatory factors is central both to deciphering the complex DNA cis-regulatory code that controls transcription in metazoans and to determining the range of genes that shape animal morphogenesis. We used whole-genome tiling arrays to map sequences bound in Drosophila melanogaster embryos by the six maternal and gap transcription factors that initiate anterior–posterior patterning. We find that these sequence-specific DNA binding proteins bind with quantitatively different specificities to highly overlapping sets of several thousand genomic regions in blastoderm embryos. Specific high- and moderate-affinity in vitro recognition sequences for each factor are enriched in bound regions. This enrichment, however, is not sufficient to explain the pattern of binding in vivo and varies in a context-dependent manner, demonstrating that higher-order rules must govern targeting of transcription factors. The more highly bound regions include all of the over 40 well-characterized enhancers known to respond to these factors as well as several hundred putative new cis-regulatory modules clustered near developmental regulators and other genes with patterned expression at this stage of embryogenesis. The new targets include most of the microRNAs (miRNAs) transcribed in the blastoderm, as well as all major zygotically transcribed dorsal–ventral patterning genes, whose expression we show to be quantitatively modulated by anterior–posterior factors. In addition to these highly bound regions, there are several thousand regions that are reproducibly bound at lower levels. However, these poorly bound regions are, collectively, far more distant from genes transcribed in the blastoderm than highly bound regions; are preferentially found in protein-coding sequences; and are less conserved than highly bound regions. Together these observations suggest that many of these poorly bound regions are not involved in early-embryonic transcriptional regulation, and a significant proportion may be nonfunctional. Surprisingly, for five of the six factors, their recognition sites are not unambiguously more constrained evolutionarily than the immediate flanking DNA, even in more highly bound and presumably functional regions, indicating that comparative DNA sequence analysis is limited in its ability to identify functional transcription factor targets.

Transcription factor binding in Drosophila

Distinct developmental fates in Drosophila melanogaster are specified by quantitative differences in transcription factor occupancy on a common set of bound regions.

To fully understand animal transcription networks, it is essential to accurately measure the spatial and temporal expression patterns of transcription factors and their targets. We describe a registration technique that takes image-based data from hundreds of Drosophila blastoderm embryos, each costained for a reference gene and one of a set of genes of interest, and builds a model VirtualEmbryo. This model captures in a common framework the average expression patterns for many genes in spite of significant variation in morphology and expression between individual embryos. We establish the method's accuracy by showing that relationships between a pair of genes' expression inferred from the model are nearly identical to those measured in embryos costained for the pair. We present a VirtualEmbryo containing data for 95 genes at six time cohorts. We show that known gene-regulatory interactions can be automatically recovered from this data set and predict hundreds of new interactions.

To understand how transcription factors function, it is essential to determine the range of genes that they each bind and regulate in vivo. Here I review evidence that most animal transcription factors each bind to a majority of genes over a quantitative series of DNA occupancy levels. These continua span functional, quasifunctional, and nonfunctional DNA binding events. Factor regulatory specificities are distinguished by quantitative differences in DNA occupancy patterns. I contrast these results with models for transcription networks that define discrete sets of direct target and nontarget genes and consequently do not fully capture the complexity observed in vivo.

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