CAGE profiling of ncRNAs in hepatocellular carcinoma reveals widespread activation of retroviral LTR promoters in virus-induced tumors

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Abstract

An increasing number of noncoding RNAs (ncRNAs) have been implicated in various human diseases including cancer; however, the ncRNA transcriptome of hepatocellular carcinoma (HCC) is largely unexplored. We used CAGE to map transcription start sites across various types of human and mouse HCCs with emphasis on ncRNAs distant from protein-coding genes. Here, we report that retroviral LTR promoters, expressed in healthy tissues such as testis and placenta but not liver, are widely activated in liver tumors. Despite HCC heterogeneity, a subset of LTR-derived ncRNAs were more than 10-fold up-regulated in the vast majority of samples. HCCs with a high LTR activity mostly had a viral etiology, were less differentiated, and showed higher risk of recurrence. ChIP-seq data show that MYC and MAX are associated with ncRNA deregulation. Globally, CAGE enabled us to build a mammalian promoter map for HCC, which uncovers a new layer of complexity in HCC genomics.

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Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin (2009)

Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk

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edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

Mark Robinson, Davis J. McCarthy, Gordon K. Smyth (2009)

Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au

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Global cancer statistics.

Ahmedin Jemal, Freddie Bray, Melissa M Center … (2011)

The global burden of cancer continues to increase largely because of the aging and growth of the world population alongside an increasing adoption of cancer-causing behaviors, particularly smoking, in economically developing countries. Based on the GLOBOCAN 2008 estimates, about 12.7 million cancer cases and 7.6 million cancer deaths are estimated to have occurred in 2008; of these, 56% of the cases and 64% of the deaths occurred in the economically developing world. Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females, accounting for 23% of the total cancer cases and 14% of the cancer deaths. Lung cancer is the leading cancer site in males, comprising 17% of the total new cancer cases and 23% of the total cancer deaths. Breast cancer is now also the leading cause of cancer death among females in economically developing countries, a shift from the previous decade during which the most common cause of cancer death was cervical cancer. Further, the mortality burden for lung cancer among females in developing countries is as high as the burden for cervical cancer, with each accounting for 11% of the total female cancer deaths. Although overall cancer incidence rates in the developing world are half those seen in the developed world in both sexes, the overall cancer mortality rates are generally similar. Cancer survival tends to be poorer in developing countries, most likely because of a combination of a late stage at diagnosis and limited access to timely and standard treatment. A substantial proportion of the worldwide burden of cancer could be prevented through the application of existing cancer control knowledge and by implementing programs for tobacco control, vaccination (for liver and cervical cancers), and early detection and treatment, as well as public health campaigns promoting physical activity and a healthier dietary intake. Clinicians, public health professionals, and policy makers can play an active role in accelerating the application of such interventions globally.

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Author and article information

Journal

Journal ID (nlm-ta): Genome Res

Journal ID (iso-abbrev): Genome Res

Journal ID (hwp): genome

Journal ID (pmc): genome

Journal ID (publisher-id): GENOME

Title: Genome Research

Publisher: Cold Spring Harbor Laboratory Press

ISSN (Print): 1088-9051

ISSN (Electronic): 1549-5469

Publication date (Print): December 2015

Publication date PMC-release: December 2015

Volume: 25

Issue: 12

Pages: 1812-1824

Affiliations

[1 ]RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, 230-0045 Japan;

[2 ]INSERM, U1193, Paul-Brousse Hospital, Hepatobiliary Centre, 94800 Villejuif, France;

[3 ]Université Paris Saclay, Faculté de Médecine Le Kremlin Bicêtre, 94800 Villejuif, France;

[4 ]European Institute of Oncology (IEO), Department of Experimental Oncology, IFOM-IEO Campus, 20139 Milan, Italy;

[5 ]RIKEN Center for Life Science Technologies, Division of Bio-function Dynamics Imaging, Wako, Saitama, 351-0198, Japan;

[6 ]VIB Center for the Biology of Disease, KU Leuven Center for Human Genetics, B-3000 Leuven, Belgium;

[7 ]Assistance Publique-Hôpitaux de Paris (AP-HP), Pôle de Biologie Médicale, Paul-Brousse Hospital, 94800 Villejuif, France

Author notes

Corresponding authors: carninci@ 123456riken.jp , jamila.faivre@ 123456inserm.fr

Article

Medline ID: 9509184

DOI: 10.1101/gr.191031.115

PMC ID: 4665003

PubMed ID: 26510915

SO-VID: 1005553d-f302-45f2-bd01-a7e6e690a13d

License:

This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.

History

Date received : 14 February 2015

Date accepted : 30 September 2015

Page count

Pages: 13

Funding

Funded by: European Union's Seventh Framework Programme

Award ID: 259743

Funded by: Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) http://dx.doi.org/10.13039/501100001700

CAGE profiling of ncRNAs in hepatocellular carcinoma reveals widespread activation of retroviral LTR promoters in virus-induced tumors

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IET: COVID-19 related research

Most cited references 55

Fast and accurate short read alignment with Burrows–Wheeler transform

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

Global cancer statistics.

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