Laurakay Bruhn

Mapping and sequencing of structural variation from eight human genomes

Genetic variation among individual humans occurs on many different scales, ranging from gross alterations in the human karyotype to single nucleotide changes. Here we explore variation on an intermediate scale—particularly insertions, deletions and inversions affecting from a few thousand to a few million base pairs. We employed a clone-based method to interrogate this intermediate structural variation in eight individuals of diverse geographic ancestry. Our analysis provides a comprehensive overview of the normal pattern of structural variation present in these genomes, refining the location of 1,695 structural variants. We find that 50% were seen in more than one individual and that nearly half lay outside regions of the genome previously described as structurally variant. We discover 525 new insertion sequences that are not present in the human reference genome and show that many of these are variable in copy number between individuals. Complete sequencing of 261 structural variants reveals considerable locus complexity and provides insights into the different mutational processes that have shaped the human genome. These data provide the first high-resolution sequence map of human structural variation—a standard for genotyping platforms and a prelude to future individual genome sequencing projects.

Tissue classification with gene expression profiles

Constantly improving gene expression profiling technologies are expected to provide understanding and insight into cancer related cellular processes. Gene expression data is also expected to significantly and in the development of efficient cancer diagnosis and classification platforms. In this work we examine two sets of gene expression data measured across sets of tumor and normal clinical samples One set consists of 2,000 genes, measured in 62 epithelial colon samples [1]. The second consists of ≈ 100,000 clones, measured in 32 ovarian samples (unpublished, extension of data set described in [26]). We examine the use of scoring methods, measuring separation of tumors from normals using individual gene expression levels. These are then coupled with high dimensional classification methods to assess the classification power of complete expression profiles. We present results of performing leave-one-out cross validation (LOOCV) experiments on the two data sets. employing SVM [8], AdaBoost [13] and a novel clustering based classification technique. As tumor samples can differ from normal samples in their cell-type composition we also perform LOOCV experiments using appropriately modified sets of genes, attempting to eliminate the resulting bias. We demonstrate success rate of at least 90% in tumor vs normal classification, using sets of selected genes, with as well as without cellular contamination related members. These results are insensitive to the exact selection mechanism, over a certain range.

Diversity of human copy number variation and multicopy genes

Evolution, Gene Number, and Disease Slight variations in the numbers of copies of genes influence human disease and other characters. Variants can be hard to detect when they lie in heavily duplicated and widely similar regions of sequence known as “dark matter.” Sudmant et al. (p. 641) have methods to tease apart the duplicated regions to reveal singly unique nucleotide identifiers. These have turned out to be among the most variable seen in different human population groups—most notably among genes for neurodevelopment and neurological diseases. Such polymorphisms can be genotyped with specificity and may help us understand how variation in copy number may affect human evolution and disease. Specific gene copies can be identified in regions of high copy number variability in the human genome. Copy number variants affect both disease and normal phenotypic variation, but those lying within heavily duplicated, highly identical sequence have been difficult to assay. By analyzing short-read mapping depth for 159 human genomes, we demonstrated accurate estimation of absolute copy number for duplications as small as 1.9 kilobase pairs, ranging from 0 to 48 copies. We identified 4.1 million “singly unique nucleotide” positions informative in distinguishing specific copies and used them to genotype the copy and content of specific paralogs within highly duplicated gene families. These data identify human-specific expansions in genes associated with brain development, reveal extensive population genetic diversity, and detect signatures consistent with gene conversion in the human species. Our approach makes ~1000 genes accessible to genetic studies of disease association.

Tissue classification with gene expression profiles.

Constantly improving gene expression profiling technologies are expected to provide understanding and insight into cancer-related cellular processes. Gene expression data is also expected to significantly aid in the development of efficient cancer diagnosis and classification platforms. In this work we examine three sets of gene expression data measured across sets of tumor(s) and normal clinical samples: The first set consists of 2,000 genes, measured in 62 epithelial colon samples (Alon et al., 1999). The second consists of approximately equal to 100,000 clones, measured in 32 ovarian samples (unpublished extension of data set described in Schummer et al. (1999)). The third set consists of approximately equal to 7,100 genes, measured in 72 bone marrow and peripheral blood samples (Golub et al, 1999). We examine the use of scoring methods, measuring separation of tissue type (e.g., tumors from normals) using individual gene expression levels. These are then coupled with high-dimensional classification methods to assess the classification power of complete expression profiles. We present results of performing leave-one-out cross validation (LOOCV) experiments on the three data sets, employing nearest neighbor classifier, SVM (Cortes and Vapnik, 1995), AdaBoost (Freund and Schapire, 1997) and a novel clustering-based classification technique. As tumor samples can differ from normal samples in their cell-type composition, we also perform LOOCV experiments using appropriately modified sets of genes, attempting to eliminate the resulting bias. We demonstrate success rate of at least 90% in tumor versus normal classification, using sets of selected genes, with, as well as without, cellular-contamination-related members. These results are insensitive to the exact selection mechanism, over a certain range.

The Fine-Scale and Complex Architecture of Human Copy-Number Variation

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.

Novel Role for the Potent Endogenous Inotrope Apelin in Human Cardiac Dysfunction

Background—Apelin is among the most potent stimulators of cardiac contractility known. However, no physiological or pathological role for apelin–angiotensin receptor-like 1 (APJ) signaling has ever been described. Methods and Results—We performed transcriptional profiling using a spotted cDNA microarray with 12 814 unique clones on paired samples of left ventricle obtained before and after placement of a left ventricular assist device in 11 patients. The significance analysis of microarrays and a novel rank consistency score designed to exploit the paired structure of the data confirmed that natriuretic peptides were among the most significantly downregulated genes after offloading. The most significantly upregulated gene was the G-protein–coupled receptor APJ, the specific receptor for apelin. We demonstrate here using immunoassay and immunohistochemical techniques that apelin is localized primarily in the endothelium of the coronary arteries and is found at a higher concentration in cardiac tissue after mechanical offloading. These findings imply an important paracrine signaling pathway in the heart. We additionally extend the clinical significance of this work by reporting for the first time circulating human apelin levels and demonstrating increases in the plasma level of apelin in patients with left ventricular dysfunction. Conclusions—The apelin-APJ signaling pathway emerges as an important novel mediator of cardiovascular control.

Chemically modified guide RNAs enhance CRISPR-Cas genome editing in human primary cells.

CRISPR-Cas-mediated genome editing relies on guide RNAs that direct site-specific DNA cleavage facilitated by the Cas endonuclease. Here we report that chemical alterations to synthesized single guide RNAs (sgRNAs) enhance genome editing efficiency in human primary T cells and CD34+ hematopoietic stem and progenitor cells. Co-delivering chemically modified sgRNAs with Cas9 mRNA or protein is an efficient RNA- or ribonucleoprotein (RNP)-based delivery method for the CRISPR-Cas system, without the toxicity associated with DNA delivery. This approach is a simple and effective way to streamline the development of genome editing with the potential to accelerate a wide array of biotechnological and therapeutic applications of the CRISPR-Cas technology.

Characterization of missing human genome sequences and copy-number polymorphic insertions

The extent of human genomic structural variation suggests that there must be portions of the genome yet to be discovered, annotated and characterized at the sequence level. We present a resource and analysis of 2,363 new insertion sequences corresponding to 720 genomic loci. We found that a substantial fraction of these sequences are either missing, fragmented or misassigned when compared to recent de novo sequence assemblies from short-read next-generation sequence data. We determined that 18–37% of these new insertions are copy-number polymorphic, including loci that show extensive population stratification among Europeans, Asians and Africans. Complete sequencing of 156 of these insertions identified new exons and conserved noncoding sequences not yet represented in the reference genome. We developed a method to accurately genotype these new insertions by mapping next-generation sequencing datasets to the breakpoint, thereby providing a means to characterize copy-number status for regions previously inaccessible to single-nucleotide polymorphism microarrays.

Population-genetic properties of differentiated human copy-number polymorphisms

Copy-number variants (CNVs) can reach appreciable frequencies in the human population, and recent discoveries have shown that several of these copy-number polymorphisms (CNPs) are associated with human diseases, including lupus, psoriasis, Crohn disease, and obesity. Despite new advances, significant biases remain in terms of CNP discovery and genotyping. We developed a method based on single-channel intensity data and benchmarked against copy numbers determined from sequencing read depth to successfully obtain CNP genotypes for 1495 CNPs from 487 human DNA samples of diverse ethnic backgrounds. This microarray contained CNPs in segmental duplication-rich regions and insertions of sequences not represented in the reference genome assembly or on standard SNP microarray platforms. We observe that CNPs in segmental duplications are more likely to be population differentiated than CNPs in unique regions (p = 0.015) and that biallelic CNPs show greater stratification when compared to frequency-matched SNPs (p = 0.0026). Although biallelic CNPs show a strong correlation of copy number with flanking SNP genotypes, the majority of multicopy CNPs do not (40% with r > 0.8). We selected a subset of CNPs for further characterization in 1876 additional samples from 62 populations; this revealed striking population-differentiated structural variants in genes of clinical significance such as OCLN, a tight junction protein involved in hepatitis C viral entry. Our microarray design allows these variants to be rapidly tested for disease association and our results suggest that CNPs (especially those that cannot be imputed from SNP genotypes) might have contributed disproportionately to human diversity and selection.

Differences in Vascular Bed Disease Susceptibility Reflect Differences in Gene Expression Response to Atherogenic Stimuli

Atherosclerosis occurs predominantly in arteries and only rarely in veins. The goal of this study was to test whether differences in the molecular responses of venous and arterial endothelial cells (ECs) to atherosclerotic stimuli might contribute to vascular bed differences in susceptibility to atherosclerosis. We compared gene expression profiles of primary cultured ECs from human saphenous vein (SVEC) and coronary artery (CAEC) exposed to atherogenic stimuli. In addition to identifying differentially expressed genes, we applied statistical analysis of gene ontology and pathway annotation terms to identify signaling differences related to cell type and stimulus. Differential gene expression of untreated venous and arterial endothelial cells yielded 285 genes more highly expressed in untreated SVEC (P<0.005 and fold change >1.5). These genes represented various atherosclerosis-related pathways including responses to proliferation, oxidoreductase activity, antiinflammatory responses, cell growth, and hemostasis functions. Moreover, stimulation with oxidized LDL induced dramatically greater gene expression responses in CAEC compared with SVEC, relating to adhesion, proliferation, and apoptosis pathways. In contrast, interleukin 1&bgr; and tumor necrosis factor &agr; activated similar gene expression responses in both CAEC and SVEC. The differences in functional response and gene expression were further validated by an in vitro proliferation assay and in vivo immunostaining of &agr;&bgr;-crystallin protein. Our results strongly suggest that different inherent gene expression programs in arterial versus venous endothelial cells contribute to differences in atherosclerotic disease susceptibility.