Genome Research誌からENCODE関連論文３つ

Encodeに関連したGenome Research誌からいくつか・・・

September 11, 2012

Genome Res. Published in Advance September 11, 2012

Extensive somatic L1 retrotransposition in colorectal tumors

1. Szilvia Solyom1,
2. Adam D. Ewing2,
3. Eric P. Rahrmann3,
4. Tara T. Doucet4,
5. Heather H. Nelson3,
6. Michael B. Burns3,
7. Reuben S. Harris3,
8. David F. Sigmon4,
9. Alex Casella4,
10. Bracha Erlanger5,
11. Sarah Wheelan5,
12. Kyle R. Upton6,
13. Ruchi Shukla6,
14. Geoffrey J. Faulkner7,
15. David A. Largaespada3 and
16. Haig H. Kazazian1,8

+ Author Affiliations

1. ¹ Johns Hopkins Univ. School of Medicine;
2. ² UCSC;
3. ³ UMin;
4. ⁴ IGM;
5. ⁵ JHU;
6. ⁶ Roslin;
7. ⁷ Brisbane

1. ↵* Corresponding author; email: kazazian@jhmi.edu

Abstract

L1 retrotransposons comprise 17% of the human genome, and are its only autonomous mobile elements. Although L1-induced insertional mutagenesis causes Mendelian disease, their mutagenic load in cancer has been elusive. Using L1-targeted re-sequencing of 16 colorectal tumor and matched normal DNAs, we found that certain cancers were excessively mutagenized by human-specific L1s, while no verifiable insertions were present in normal tissues. We confirmed de novo L1 insertions in malignancy by both validating and sequencing 69/107 tumor-specific insertions and retrieving both 5' and 3' junctions for 35. In contrast to germline polymorphic L1s, all insertions were severely 5' truncated. Validated insertion numbers varied from up to 17 in some tumors to none in 3 others, and correlated with the age of the patients. Numerous genes with a role in tumorigenesis were targeted, including ODZ3, ROBO2, PTPRM, PCM1, and CDH11. Thus, somatic retrotransposition may play an etiologic role in colorectal cancer.

• Received July 2, 2012.
• Accepted August 30, 2012.

• © 2012, Published by Cold Spring Harbor Laboratory Press

ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia

• Stephen G. Landt,
• Georgi K. Marinov,
• Anshul Kundaje,
• Pouya Kheradpour,
• Florencia Pauli,
• Serafim Batzoglou,
• Bradley E. Bernstein,
• Peter Bickel,
• James B. Brown,
• Philip Cayting,
• Yiwen Chen,
• Gilberto DeSalvo,
• Charles Epstein,
• Katherine I. Fisher-Aylor,
• Ghia Euskirchen,
• Mark Gerstein,
• Jason Gertz,
• Alexander J. Hartemink,
• Michael M. Hoffman,
• Vishwanath R. Iyer,
• Youngsook L. Jung,
• Subhradip Karmakar,
• Manolis Kellis,
• Peter V. Kharchenko,
• Qunhua Li,
• Tao Liu,
• X. Shirley Liu,
• Lijia Ma,
• Aleksandar Milosavljevic,
• Richard M. Myers,
• Peter J. Park,
• Michael J. Pazin,
• Marc D. Perry,
• Debasish Raha,
• Timothy E. Reddy,
• Joel Rozowsky,
• Noam Shoresh,
• Arend Sidow,
• Matthew Slattery,
• John A. Stamatoyannopoulos,
• Michael Y. Tolstorukov,
• Kevin P. White,
• Simon Xi,
• Peggy J. Farnham,
• Jason D. Lieb,
• Barbara J. Wold,
• and Michael Snyder

Genome Res. September 2012 22: 1813-1831; doi:10.1101/gr.136184.111

Abstract

Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and utility of any global ChIP experiment. Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals.

RNA editing in the human ENCODE RNA-seq data

• Eddie Park,
• Brian Williams,
• Barbara J. Wold,
• and Ali Mortazavi

Genome Res. September 2012 22: 1626-1633; doi:10.1101/gr.134957.111

Abstract

RNA-seq data can be mined for sequence differences relative to the reference genome to identify both genomic SNPs and RNA editing events. We analyzed the long, polyA-selected, unstranded, deeply sequenced RNA-seq data from the ENCODE Project across 14 human cell lines for candidate RNA editing events. On average, 43% of the RNA sequencing variants that are not in dbSNP and are within gene boundaries are A-to-G(I) RNA editing candidates. The vast majority of A-to-G(I) edits are located in introns and 3′ UTRs, with only 123 located in protein-coding sequence. In contrast, the majority of non–A-to-G variants (60%–80%) map near exon boundaries and have the characteristics of splice-mapping artifacts. After filtering out all candidates with evidence of private genomic variation using genome resequencing or ChIP-seq data, we find that up to 85% of the high-confidence RNA variants are A-to-G(I) editing candidates. Genes with A-to-G(I) edits are enriched in Gene Ontology terms involving cell division, viral defense, and translation. The distribution and character of the remaining non–A-to-G variants closely resemble known SNPs. We find no reproducible A-to-G(I) edits that result in nonsynonymous substitutions in all three lymphoblastoid cell lines in our study, unlike RNA editing in the brain. Given that only a fraction of sites are reproducibly edited in multiple cell lines and that we find a stronger association of editing and specific genes suggests that the editing of the transcript is more important than the editing of any individual site.