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.

Localized accessibility of critical DNA sequences to the regulatory machinery is a key requirement for regulation of human genes. Here we describe a high-resolution, genome-scale approach for quantifying chromatin accessibility by measuring DNase I sensitivity as a continuous function of genome position using tiling DNA microarrays (DNase-array). We demonstrate this approach across 1% ( approximately 30 Mb) of the human genome, wherein we localized 2,690 classical DNase I hypersensitive sites with high sensitivity and specificity, and also mapped larger-scale patterns of chromatin architecture. DNase I hypersensitive sites exhibit marked aggregation around transcriptional start sites (TSSs), though the majority mark nonpromoter functional elements. We also developed a computational approach for visualizing higher-order features of chromatin structure. This revealed that human chromatin organization is dominated by large (100-500 kb) 'superclusters' of DNase I hypersensitive sites, which encompass both gene-rich and gene-poor regions. DNase-array is a powerful and straightforward approach for systematic exposition of the cis-regulatory architecture of complex genomes.

SummarySomatic mutations and large-scale depletion in mitochondrial DNA (mtDNA) have been extensively detected in various human cancers. However, it still remains unclear whether the alterations in mtDNA content are related to the clinicopathological parameters and patient prognosis in breast cancer. In the present study, we analyzed the copy number of mtDNA in 59 cases of invasive breast tumors and paired nontumorous tissues using quantitative real-time PCR. Our data showed that the level of mtDNA was significantly decreased in tumor tissues as compared to the adjacent nontumorous counterparts (P ¼ 0.001). The reduced copy number in mtDNA was associated with an older onset age ( 50 years old, P ¼ 0.035) as well as a higher histological grade (P ¼ 0.012). Survival analysis measured by the Kaplan-Meier curves and the log-rank test indicated that patients with reduced mtDNA content had significantly poorer disease-free survival (DFS, P ¼ 0.0079) and overall survival (OS, P ¼ 0.011) rate. In addition, tumors harboring mutations in displacement (D)-loop region, particularly at the polycytidine stretch (T/N ratio ¼ 64.3 + 8.2%) or close to the replication origins of the heavy-strand (T/N ratio ¼ 68.7 + 5.5%), had a significantly lower copy number of mtDNA than the ones without D-loop alterations. Together, our results suggested that reduced copy number of mtDNA may be involved in breast neoplastic transformation or progression and mtDNA content might be potentially used as a tool to predict prognosis. Somatic mutation in the D-loop region probably is one of key contributing factors leading to decreased mtDNA level in breast tumors.