Copyright © 2008 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 82, Issue 4, 971-981, 03 April 2008
doi:10.1016/j.ajhg.2008.02.016
Article
Christelle Borel1, Maryline Gagnebin1, Corinne Gehrig1, Evgenia V. Kriventseva1, 4, Evgeny M. Zdobnov1, 2, 3 and Stylianos E. Antonarakis1,
, 
1 Department of Genetic Medicine and Development, University of Geneva Medical School and University Hospitals of Geneva, Geneva 1211, Switzerland
2 Swiss Institute of Bioinformatics, Geneva 1211, Switzerland
3 Division of Cell and Molecular Biology, Faculty of Natural Sciences, Imperial College London, London, UK
4 Department of Structural Biology and Bioinformatics, University of Geneva Medical School, Geneva 1211, Switzerland
Corresponding authorAbstract
The elucidation of the largely unknown transcriptome of small RNAs is crucial for the understanding of genome and cellular function. We report here the results of the analysis of small RNAs (< 50 nt) in the ENCODE regions of the human genome. Size-fractionated RNAs from four different cell lines (HepG2, HelaS3, GM06990, SK-N-SH) were mapped with the forward and reverse ENCODE high-density resolution tiling arrays. The top 1% of hybridization signals are termed SmRfrags (Small RNA fragments). Eight percent of SmRfrags overlap the GENCODE genes (CDS), given that the majority map to intergenic regions (34%), intronic regions (53%), and untranslated regions (UTRs) (5%). In addition, 9.6% and 16.8% of SmRfrags in the 5′ UTR regions overlap significantly with His/Pol II/TAF250 binding sites and DNase I Hypersensitive sites, respectively (compared to the 5.3% and 9% expected). Interestingly, 17%–24% (depending on the cell line) of SmRfrags are sense-antisense strand pairs that show evidence of overlapping transcription. Only 3.4% and 7.2% of SmRfrags in intergenic regions overlap transcribed fragments (Txfrags) in HeLa and GM06990 cell lines, respectively. We hypothesized that a fraction of the identified SmRfrags corresponded to microRNAs. We tested by Northern blot a set of 15 high-likelihood predictions of microRNA candidates that overlap with smRfrags and validated three potential microRNAs (∼20 nt length). Notably, most of the remaining candidates showed a larger hybridizing band (∼100 nt) that could be a microRNA precursor. The small RNA transcriptome is emerging as an important and abundant component of the genome function.
| Genetic Architecture of Transcript-Level Variation in Humans The American Journal of Human Genetics, Volume 82, Issue 5, 9 May 2008, Pages 1101-1113 Shiwei Duan, R. Stephanie Huang, Wei Zhang, Wasim K. Bleibel, Cheryl A. Roe, Tyson A. Clark, Tina X. Chen, Anthony C. Schweitzer, John E. Blume, Nancy J. Cox and M. Eileen Dolan Abstract We report here the results of testing the pairwise association of 12,747 transcriptional gene-expression values with more than two million single-nucleotide polymorphisms (SNPs) in samples of European (CEPH from Utah; CEU) and African (Yoruba from Ibadan; YRI) ancestry. We found 4,677 and 5,125 significant associations between expression quantitative nucleotides (eQTNs) and transcript clusters in the CEU and the YRI samples, respectively. The physical distance between an eQTN and its associated transcript cluster was referred to as the intrapair distance. An association with 4 Mb or less intrapair distance was defined as local; otherwise, it was defined as distant. The enrichment analysis of functional categories shows that genes harboring the local eQTNs are enriched in the categories related to nucleosome and chromatin assembly; the genes harboring the distant eQTNs are enriched in the categories related to transmembrane signal transduction, suggesting that these biological pathways are likely to play a significant role in regulation of gene expression. We highlight in the EPHX1 gene a deleterious nonsynonymous SNP that is distantly associated with gene expression of ORMDL3, a susceptibility gene for asthma. Abstract | | |
| Characterization of Apparently Balanced Chromosomal Rearrangements from the Developmental Genome Anatomy Project The American Journal of Human Genetics, Volume 82, Issue 3, 3 March 2008, Pages 712-722 Anne W. Higgins, Fowzan S. Alkuraya, Amy F. Bosco, Kerry K. Brown, Gail A.P. Bruns, Diana J. Donovan, Robert Eisenman, Yanli Fan, Chantal G. Farra, Heather L. Ferguson, James F. Gusella, David J. Harris, Steven R. Herrick, Chantal Kelly, Hyung-Goo Kim, Shotaro Kishikawa, Bruce R. Korf, Shashikant Kulkarni, Eric Lally, Natalia T. Leach, Emma Lemyre, Janine Lewis, Azra H. Ligon, Weining Lu, Richard L. Maas, Marcy E. MacDonald, Steven D.P. Moore, Roxanna E. Peters, Bradley J. Quade, Fabiola Quintero-Rivera, Irfan Saadi, Yiping Shen, Jay Shendure, Robin E. Williamson and Cynthia C. Morton Abstract Apparently balanced chromosomal rearrangements in individuals with major congenital anomalies represent natural experiments of gene disruption and dysregulation. These individuals can be studied to identify novel genes critical in human development and to annotate further the function of known genes. Identification and characterization of these genes is the goal of the Developmental Genome Anatomy Project (DGAP). DGAP is a multidisciplinary effort that leverages the recent advances resulting from the Human Genome Project to increase our understanding of birth defects and the process of human development. Clinically significant phenotypes of individuals enrolled in DGAP are varied and, in most cases, involve multiple organ systems. Study of these individuals' chromosomal rearrangements has resulted in the mapping of 77 breakpoints from 40 chromosomal rearrangements by FISH with BACs and fosmids, array CGH, Southern-blot hybridization, MLPA, RT-PCR, and suppression PCR. Eighteen chromosomal breakpoints have been cloned and sequenced. Unsuspected genomic imbalances and cryptic rearrangements were detected, but less frequently than has been reported previously. Chromosomal rearrangements, both balanced and unbalanced, in individuals with multiple congenital anomalies continue to be a valuable resource for gene discovery and annotation. Abstract | | |
| Evaluation of Genetic Variation Contributing to Differences in Gene Expression between Populations The American Journal of Human Genetics, Volume 82, Issue 3, 3 March 2008, Pages 631-640 Wei Zhang, Shiwei Duan, Emily O. Kistner, Wasim K. Bleibel, R. Stephanie Huang, Tyson A. Clark, Tina X. Chen, Anthony C. Schweitzer, John E. Blume, Nancy J. Cox and M. Eileen Dolan Abstract Gene expression is a complex quantitative trait partially regulated by genetic variation in DNA sequence. Population differences in gene expression could contribute to some of the observed differences in susceptibility to common diseases and response to drug treatments. We characterized gene expression in the full set of HapMap lymphoblastoid cell lines derived from individuals of European and African ancestry for 9156 transcript clusters (gene-level) evaluated with the Affymetrix GeneChip Human Exon 1.0 ST Array. Gene expression was found to differ significantly between these samples for 383 transcript clusters. Biological processes including ribosome biogenesis and antimicrobial humoral response were found to be enriched in these differential genes, suggesting their possible roles in contributing to the population differences at a higher level than that of mRNA expression and in response to environmental information. Genome-wide association studies for local or distant genetic variants that correlate with the differentially expressed genes enabled identification of significant associations with one or more single-nucleotide polymorphisms (SNPs), consistent with the hypothesis that genetic factors and not simply population identity or other characteristics (age of cell lines, length of culture, etc.) contribute to differences in gene expression in these samples. Our results provide a comprehensive view of the genes differentially expressed between populations and the enriched biological processes involved in these genes. We also provide an evaluation of the contributions of genetic variation and nongenetic factors to the population differences in gene expression. Abstract | | |