Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Worldwide acceleration of mountain erosion under a cooling climate

Climate influences the erosion processes acting at the Earth’s surface. However, the effect of cooling during the Late Cenozoic era, including the onset of Pliocene–Pleistocene Northern Hemisphere glaciation (about two to three million years ago), on global erosion rates remains unclear1, 2, 3, 4. The uncertainty arises mainly from a lack of consensus on the use of the sedimentary record as a proxy for erosion3, 4 and the difficulty of isolating the respective contributions of tectonics and climate to erosion5, 6, 7. Here we compile 18,000 bedrock thermochronometric ages from around the world and use a formal inversion procedure8 to estimate temporal and spatial variations in erosion rates. This allows for the quantification of erosion for the source areas that ultimately produce the sediment record on a timescale of millions of years. We find that mountain erosion rates have increased since about six million years ago and most rapidly since two million years ago. The increase of erosion rates is observed at all latitudes, but is most pronounced in glaciated mountain ranges, indicating that glacial processes played an important part. Because mountains represent a considerable fraction of the global production of sediments9, our results imply an increase in sediment flux at a global scale that coincides closely with enhanced cooling during the Pliocene and Pleistocene epochs10, 11

Time Delay Estimation in Room Acoustic Environments: An Overview

<p/> <p>Time delay estimation has been a research topic of significant practical importance in many fields (radar, sonar, seismology, geophysics, ultrasonics, hands-free communications, etc.). It is a first stage that feeds into subsequent processing blocks for identifying, localizing, and tracking radiating sources. This area has made remarkable advances in the past few decades, and is continuing to progress, with an aim to create processors that are tolerant to both noise and reverberation. This paper presents a systematic overview of the state-of-the-art of time-delay-estimation algorithms ranging from the simple cross-correlation method to the advanced blind channel identification based techniques. We discuss the pros and cons of each individual algorithm, and outline their inherent relationships. We also provide experimental results to illustrate their performance differences in room acoustic environments where reverberation and noise are commonly encountered.</p