Copyright © 2008 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 82, Issue 3, 631-640, 28 February 2008
doi:10.1016/j.ajhg.2007.12.015
Article
Wei Zhang1, 5, Shiwei Duan1, 5, Emily O. Kistner2, Wasim K. Bleibel1, R. Stephanie Huang1, Tyson A. Clark4, Tina X. Chen4, Anthony C. Schweitzer4, John E. Blume4, Nancy J. Cox1, 3 and M. Eileen Dolan1,
, 
1 Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
2 Department of Health Studies, The University of Chicago, Chicago, IL 60637, USA
3 Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
4 Expression Research, Affymetrix Laboratory, Affymetrix, Santa Clara, CA 95051, USA
Corresponding authorAbstract
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.
| The Fine-Scale and Complex Architecture of Human Copy-Number Variation The American Journal of Human Genetics, Volume 82, Issue 3, 3 March 2008, Pages 685-695 George H. Perry, Amir Ben-Dor, Anya Tsalenko, Nick Sampas, Laia Rodriguez-Revenga, Charles W. Tran, Alicia Scheffer, Israel Steinfeld, Peter Tsang, N. Alice Yamada, Han Soo Park, Jong-Il Kim, Jeong-Sun Seo, Zohar Yakhini, Stephen Laderman, Laurakay Bruhn and Charles Lee Abstract Despite considerable excitement over the potential functional significance of copy-number variants (CNVs), we still lack knowledge of the fine-scale architecture of the large majority of CNV regions in the human genome. In this study, we used a high-resolution array-based comparative genomic hybridization (aCGH) platform that targeted known CNV regions of the human genome at approximately 1 kb resolution to interrogate the genomic DNAs of 30 individuals from four HapMap populations. Our results revealed that 1020 of 1153 CNV loci (88%) were actually smaller in size than what is recorded in the Database of Genomic Variants based on previously published studies. A reduction in size of more than 50% was observed for 876 CNV regions (76%). We conclude that the total genomic content of currently known common human CNVs is likely smaller than previously thought. In addition, approximately 8% of the CNV regions observed in multiple individuals exhibited genomic architectural complexity in the form of smaller CNVs within larger ones and CNVs with interindividual variation in breakpoints. Future association studies that aim to capture the potential influences of CNVs on disease phenotypes will need to consider how to best ascertain this previously uncharacterized complexity. Abstract | | |
| Structural Variation of Chromosomes in Autism Spectrum Disorder The American Journal of Human Genetics, Volume 82, Issue 2, 8 February 2008, Pages 477-488 Christian R. Marshall, Abdul Noor, John B. Vincent, Anath C. Lionel, Lars Feuk, Jennifer Skaug, Mary Shago, Rainald Moessner, Dalila Pinto, Yan Ren, Bhooma Thiruvahindrapduram, Andreas Fiebig, Stefan Schreiber, Jan Friedman, Cees E.J. Ketelaars, Yvonne J. Vos, Can Ficicioglu, Susan Kirkpatrick, Rob Nicolson, Leon Sloman, Anne Summers, Clare A. Gibbons, Ahmad Teebi, David Chitayat, Rosanna Weksberg, Ann Thompson, Cathy Vardy, Vicki Crosbie, Sandra Luscombe, Rebecca Baatjes, Lonnie Zwaigenbaum, Wendy Roberts, Bridget Fernandez, Peter Szatmari and Stephen W. Scherer Abstract Structural variation (copy number variation [CNV] including deletion and duplication, translocation, inversion) of chromosomes has been identified in some individuals with autism spectrum disorder (ASD), but the full etiologic role is unknown. We performed genome-wide assessment for structural abnormalities in 427 unrelated ASD cases via single-nucleotide polymorphism microarrays and karyotyping. With microarrays, we discovered 277 unbalanced CNVs in 44% of ASD families not present in 500 controls (and re-examined in another 1152 controls). Karyotyping detected additional balanced changes. Although most variants were inherited, we found a total of 27 cases with de novo alterations, and in three (11%) of these individuals, two or more new variants were observed. De novo CNVs were found in ∼7% and ∼2% of idiopathic families having one child, or two or more ASD siblings, respectively. We also detected 13 loci with recurrent/overlapping CNV in unrelated cases, and at these sites, deletions and duplications affecting the same gene(s) in different individuals and sometimes in asymptomatic carriers were also found. Notwithstanding complexities, our results further implicate the SHANK3-NLGN4-NRXN1 postsynaptic density genes and also identify novel loci at DPP6-DPP10-PCDH9 (synapse complex), ANKRD11, DPYD, PTCHD1, 15q24, among others, for a role in ASD susceptibility. Our most compelling result discovered CNV at 16p11.2 (p = 0.002) (with characteristics of a genomic disorder) at ∼1% frequency. Some of the ASD regions were also common to mental retardation loci. Structural variants were found in sufficiently high frequency influencing ASD to suggest that cytogenetic and microarray analyses be considered in routine clinical workup. Abstract | | |
| Detection, Imputation, and Association Analysis of Small Deletions and Null Alleles on Oligonucleotide Arrays The American Journal of Human Genetics, Volume 82, Issue 6, 6 June 2008, Pages 1316-1333 Lude Franke, Carolien G.F. de Kovel, Yurii S. Aulchenko, Gosia Trynka, Alexandra Zhernakova, Karen A. Hunt, Hylke M. Blauw, Leonard H. van den Berg, Roel Ophoff, Panagiotis Deloukas, David A. van Heel and Cisca Wijmenga Abstract Copy-number variation (CNV) is a major contributor to human genetic variation. Recently, CNV associations with human disease have been reported. Many genome-wide association (GWA) studies in complex diseases have been performed with sets of biallelic single-nucleotide polymorphisms (SNPs), but the available CNV methods are still limited. We present a new method (TriTyper) that can infer genotypes in case-control data sets for deletion CNVs, or SNPs with an extra, untyped allele at a high-resolution single SNP level. By accounting for linkage disequilibrium (LD), as well as intensity data, calling accuracy is improved. Analysis of 3102 unrelated individuals with European descent, genotyped with Illumina Infinium BeadChips, resulted in the identification of 1880 SNPs with a common untyped allele, and these SNPs are in strong LD with neighboring biallelic SNPs. Simulations indicate our method has superior power to detect associations compared to biallelic SNPs that are in LD with these SNPs, yet without increasing type I errors, as shown in a GWA analysis in celiac disease. Genotypes for 1204 triallelic SNPs could be fully imputed, with only biallelic-genotype calls, permitting association analysis of these SNPs in many published data sets. We estimate that 682 of the 1655 unique loci reflect deletions; this is on average 99 deletions per individual, four times greater than those detected by other methods. Whereas the identified loci are strongly enriched for known deletions, 61% have not been reported before. Genes overlapping with these loci more often have paralogs (p = 0.006) and biologically interact with fewer genes than expected (p = 0.004). Abstract | | |