Showing papers by "James B. Brown published in 2007"
Ewan Birney, John A. Stamatoyannopoulos1, Anindya Dutta2, Roderic Guigó3 +317 more•Institutions (44)
TL;DR: Functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project are reported, providing convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts.
Abstract: We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
5,091 citations
National Institutes of Health1, Stanford University2, University of Washington3, University of California, Santa Cruz4, University of Wisconsin-Madison5, University of California, Berkeley6, Cornell University7, Pennsylvania State University8, University of Geneva9, University of Manchester10, Baylor College of Medicine11, Washington University in St. Louis12, Broad Institute13, Massachusetts Institute of Technology14, University of British Columbia15
TL;DR: The quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments are described.
Abstract: A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization.
214 citations
01 Jan 2007
TL;DR: It is argued that, in making inference about statistics computed from “large” stretches of the genome, in the absence of real knowledge about the evolutionary path which led to the genome in question, the best method is the best.
Abstract: This paper grew out of a number of examples arising in data coming from the ENCODE project (Birney et al., 2007). Variations of some of the methods described here have been applied at various places in that paper, as well as in Margulies et al., 2007, for assessing significance and computing confidence bounds for statistics that operate along a genomic sequence. The background on these methods are described in cookbook form in the supplements to these papers, and it is the goal of this paper to describe them in more detail and rigor. We begin with some concrete examples from the data mentioned in the papers above as well as other types of genomic data in Section 1.2, and proceed with a motivated description of our model in Section 2. Our methods are discussed both qualitatively and mathematically in Sections 3 and 4. Sections 5 contain results from simulation studies and real data analysis. Finally, an appendix with proofs of theorems stated in Sections 3 and 4 completes the paper. Essentially, we will argue that, in making inference about statistics computed from “large” stretches of the genome, in the absence of real knowledge about the evolutionary path which led to the genome in question, the best
4 citations