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Search Results: 1 - 10 of 10469 matches for " Jonathan Pevsner "
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Visualization of Shared Genomic Regions and Meiotic Recombination in High-Density SNP Data
Elisha D. O. Roberson, Jonathan Pevsner
PLOS ONE , 2009, DOI: 10.1371/journal.pone.0006711
Abstract: Background A fundamental goal of single nucleotide polymorphism (SNP) genotyping is to determine the sharing of alleles between individuals across genomic loci. Such analyses have diverse applications in defining the relatedness of individuals (including unexpected relationships in nominally unrelated individuals, or consanguinity within pedigrees), analyzing meiotic crossovers, and identifying a broad range of chromosomal anomalies such as hemizygous deletions and uniparental disomy, and analyzing population structure. Principal Findings We present SNPduo, a command-line and web accessible tool for analyzing and visualizing the relatedness of any two individuals using identity by state. Using identity by state does not require prior knowledge of allele frequencies or pedigree information, and is more computationally tractable and is less affected by population stratification than calculating identity by descent probabilities. The web implementation visualizes shared genomic regions, and generates UCSC viewable tracks. The command-line version requires pedigree information for compatibility with existing software and determining specified relationships even though pedigrees are not required for IBS calculation, generates no visual output, is written in portable C++, and is well-suited to analyzing large datasets. We demonstrate how the SNPduo web tool identifies meiotic crossover positions in siblings, and confirm our findings by visualizing meiotic recombination in synthetic three-generation pedigrees. We applied SNPduo to 210 nominally unrelated Phase I / II HapMap samples and, consistent with previous findings, identified six undeclared pairs of related individuals. We further analyzed identity by state in 2,883 individuals from multiplex families with autism and identified a series of anomalies including related parents, an individual with mosaic loss of chromosome 18, an individual with maternal heterodisomy of chromosome 16, and unexplained replicate samples. Conclusions SNPduo provides the ability to explore and visualize SNP data to characterize the relatedness between individuals. It is compatible with, but distinct from, other established analysis software such as PLINK, and performs favorably in benchmarking studies for the analyses of genetic relatedness.
Hidden Markov models for the assessment of chromosomal alterations using high-throughput SNP arrays
Robert B. Scharpf,Giovanni Parmigiani,Jonathan Pevsner,Ingo Ruczinski
Statistics , 2008, DOI: 10.1214/07-AOAS155
Abstract: Chromosomal DNA is characterized by variation between individuals at the level of entire chromosomes (e.g., aneuploidy in which the chromosome copy number is altered), segmental changes (including insertions, deletions, inversions, and translocations), and changes to small genomic regions (including single nucleotide polymorphisms). A variety of alterations that occur in chromosomal DNA, many of which can be detected using high density single nucleotide polymorphism (SNP) microarrays, are linked to normal variation as well as disease and are therefore of particular interest. These include changes in copy number (deletions and duplications) and genotype (e.g., the occurrence of regions of homozygosity). Hidden Markov models (HMM) are particularly useful for detecting such alterations, modeling the spatial dependence between neighboring SNPs. Here, we improve previous approaches that utilize HMM frameworks for inference in high throughput SNP arrays by integrating copy number, genotype calls, and the corresponding measures of uncertainty when available. Using simulated and experimental data, we, in particular, demonstrate how confidence scores control smoothing in a probabilistic framework. Software for fitting HMMs to SNP array data is available in the R package VanillaICE.
Unexpected Relationships and Inbreeding in HapMap Phase III Populations
Eric L. Stevens, Joseph D. Baugher, Matthew D. Shirley, Laurence P. Frelin, Jonathan Pevsner
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0049575
Abstract: Correct annotation of the genetic relationships between samples is essential for population genomic studies, which could be biased by errors or omissions. To this end, we used identity-by-state (IBS) and identity-by-descent (IBD) methods to assess genetic relatedness of individuals within HapMap phase III data. We analyzed data from 1,397 individuals across 11 ethnic populations. Our results support previous studies (Pemberton et al., 2010; Kyriazopoulou-Panagiotopoulou et al., 2011) assessing unknown relatedness present within this population. Additionally, we present evidence for 1,657 novel pairwise relationships across 9 populations. Surprisingly, significant Cotterman's coefficients of relatedness K1 (IBD1) values were detected between pairs of known parents. Furthermore, significant K2 (IBD2) values were detected in 32 previously annotated parent-child relationships. Consistent with a hypothesis of inbreeding, regions of homozygosity (ROH) were identified in the offspring of related parents, of which a subset overlapped those reported in previous studies (Gibson et al. 2010; Johnson et al. 2011). In total, we inferred 28 inbred individuals with ROH that overlapped areas of relatedness between the parents and/or IBD2 sharing at a different genomic locus between a child and a parent. Finally, 8 previously annotated parent-child relationships had unexpected K0 (IBD0) values (resulting from a chromosomal abnormality or genotype error), and 10 previously annotated second-degree relationships along with 38 other novel pairwise relationships had unexpected IBD2 (indicating two separate paths of recent ancestry). These newly described types of relatedness may impact the outcome of previous studies and should inform the design of future studies relying on the HapMap Phase III resource.
Efficient Array-Based Identification of Novel Cardiac Genes through Differentiation of Mouse ESCs
Ronald A. Miller, Nicolas Christoforou, Jonathan Pevsner, Andrew S. McCallion, John D. Gearhart
PLOS ONE , 2008, DOI: 10.1371/journal.pone.0002176
Abstract: Remarkably, although cardiac disease accounts for the largest proportion of adult mortality and morbidity in the industrialized world, the genetic programs controlling early cardiogenesis are largely incompletely understood. To better understand this process, we set out to identify genes whose expression is enriched within early cardiac fated populations, obtaining the transcriptional signatures of mouse embryonic stem cells (mESCs) at defined intervals during their differentiation along a cardiac path. We compared the RNA profiles of cardiac precursors cells (CPCs) with time-matched non-CPCs and undifferentiated mESCs, using a transgenic mESC line harboring an Nkx2-5 cardiac-specific regulatory sequence driving green fluorescent protein (GFP) to facilitate selection of CPCs. We identify 176 transcripts that are significantly elevated in their abundance within CPCs compared with other assayed populations, predicting that they will likely play a role in cardiogenesis. Of note, approximately 24% (43/176) of the cardiogenic candidate transcripts have known roles in cardiac function or development. Importantly, we evaluated the biological relevance of a significant subset 31/133 (23%) of the remaining candidate genes by in situ hybridization at multiple time points during development (embryonic day, E7.5–9.5) and report that all were expressed in key cardiac structures during cardiogenesis. Furthermore 9/31, of which many were previously uncharacterized, were detected as early as the formation of the cardiac crescent. These data demonstrate the potential power of integrating genomic approaches with mESC differentiation to illuminate developmental processes, and provides a valuable resource that may be mined to further elucidate the genetic programs underlying cardiogenesis.
Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan
Jason C Ting, Ying Ye, George H Thomas, Ingo Ruczinski, Jonathan Pevsner
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-25
Abstract: We have developed SNPscan, a web-accessible tool to analyze and visualize high density SNP data. It enables researchers (1) to visually and quantitatively assess the quality of user-generated SNP data relative to a benchmark data set derived from a control population, (2) to display SNP intensity and allelic call data in order to detect chromosomal copy number anomalies (duplications and deletions), (3) to display uniparental isodisomy based on loss of heterozygosity (LOH) across genomic regions, (4) to compare paired samples (e.g. tumor and normal), and (5) to generate a file type for viewing SNP data in the University of California, Santa Cruz (UCSC) Human Genome Browser. SNPscan accepts data exported from Affymetrix Copy Number Analysis Tool as its input. We validated SNPscan using data generated from patients with known deletions, duplications, and uniparental disomy. We also inspected previously generated SNP data from 90 apparently normal individuals from the Centre d'étude du Polymorphisme Humain (CEPH) collection, and identified three cases of uniparental isodisomy, four females having an apparently mosaic X chromosome, two mislabelled SNP data sets, and one microdeletion on chromosome 2 with mosaicism from an apparently normal female. These previously unrecognized abnormalities were all detected using SNPscan. The microdeletion was independently confirmed by fluorescence in situ hybridization, and a region of homozygosity in a UPD case was confirmed by sequencing of genomic DNA.SNPscan is useful to identify chromosomal abnormalities based on SNP intensity (such as chromosomal copy number changes) and heterozygosity data (including regions of LOH and some cases of UPD). The program and source code are available at the SNPscan website http://pevsnerlab.kennedykrieger.org/snpscan.htm webcite.A single nucleotide polymorphism (SNP) is a variation in a DNA sequence that occurs in an appreciable portion of the population. High density SNP microarrays provide infor
Locations and patterns of meiotic recombination in two-generation pedigrees
Jason C Ting, Elisha DO Roberson, Duane G Currier, Jonathan Pevsner
BMC Medical Genetics , 2009, DOI: 10.1186/1471-2350-10-93
Abstract: Several methods have been introduced to identify crossovers using high density single nucleotide polymorphism (SNP) array technologies, although programs are not widely available to implement such analyses.Here we present a two-generation "reverse pedigree analysis" method (analyzing the genotypes of two children relative to each parent) and a web-accessible tool to determine and visualize inheritance differences among siblings and crossover locations on each parental gamete. This approach is complementary to existing methods and uses informative markers which provide high resolution for locating meiotic crossover sites. We introduce a segmentation algorithm to identify crossover sites, and used a synthetic data set to determine that the segmentation algorithm specificity was 92% and sensitivity was 89%. The use of reverse pedigrees allows the inference of crossover locations on the X chromosome in a maternal gamete through analysis of two sons and their father. We further analyzed genotypes from eight multiplex autism families, observing a 1.462 maternal to paternal recombination ratio and no significant differences between affected and unaffected children. Meiotic recombination results from pediSNP can also be used to identify haplotypes that are shared by probands within a pedigree, as we demonstrated with a multiplex autism family.Using "reverse pedigrees" and defining unique sets of genotype markers within pedigree data, we introduce a method that identifies inherited allelic differences and meiotic crossovers. We implemented the method in the pediSNP software program, and we applied it to several data sets. This approach uses data from two generations to identify crossover sites, facilitating studies of recombination in disease. pediSNP is available online at http://pevsnerlab.kennedykrieger.org/pediSNP webcite.Meiotic recombination or crossing over assures that each child inherits distinct genetic material from parental chromosomes. The process of meiotic rec
Inference of Relationships in Population Data Using Identity-by-Descent and Identity-by-State
Eric L. Stevens equal contributor,Greg Heckenberg equal contributor,Elisha D. O. Roberson equal contributor,Joseph D. Baugher,Thomas J. Downey,Jonathan Pevsner
PLOS Genetics , 2011, DOI: 10.1371/journal.pgen.1002287
Abstract: It is an assumption of large, population-based datasets that samples are annotated accurately whether they correspond to known relationships or unrelated individuals. These annotations are key for a broad range of genetics applications. While many methods are available to assess relatedness that involve estimates of identity-by-descent (IBD) and/or identity-by-state (IBS) allele-sharing proportions, we developed a novel approach that estimates IBD0, 1, and 2 based on observed IBS within windows. When combined with genome-wide IBS information, it provides an intuitive and practical graphical approach with the capacity to analyze datasets with thousands of samples without prior information about relatedness between individuals or haplotypes. We applied the method to a commonly used Human Variation Panel consisting of 400 nominally unrelated individuals. Surprisingly, we identified identical, parent-child, and full-sibling relationships and reconstructed pedigrees. In two instances non-sibling pairs of individuals in these pedigrees had unexpected IBD2 levels, as well as multiple regions of homozygosity, implying inbreeding. This combined method allowed us to distinguish related individuals from those having atypical heterozygosity rates and determine which individuals were outliers with respect to their designated population. Additionally, it becomes increasingly difficult to identify distant relatedness using genome-wide IBS methods alone. However, our IBD method further identified distant relatedness between individuals within populations, supported by the presence of megabase-scale regions lacking IBS0 across individual chromosomes. We benchmarked our approach against the hidden Markov model of a leading software package (PLINK), showing improved calling of distantly related individuals, and we validated it using a known pedigree from a clinical study. The application of this approach could improve genome-wide association, linkage, heterozygosity, and other population genomics studies that rely on SNP genotype data.
Primary and secondary transcriptional effects in the developing human Down syndrome brain and heart
Rong Mao, Xiaowen Wang, Edward L Spitznagel, Laurence P Frelin, Jason C Ting, Huashi Ding, Jung-whan Kim, Ingo Ruczinski, Thomas J Downey, Jonathan Pevsner
Genome Biology , 2006, DOI: 10.1186/gb-2005-6-13-r107
Abstract: We measured levels of transcripts in human fetal cerebellum and heart tissues using DNA microarrays and demonstrated a dosage-dependent increase in transcription across different tissue/cell types as a result of trisomy 21. Moreover, by having a larger sample size, combining the data from four different tissue and cell types, and using an ANOVA approach, we identified individual genes with significantly altered expression in trisomy 21, some of which showed this dysregulation in a tissue-specific manner. We validated our microarray data by over 5,600 quantitative real-time PCRs on 28 genes assigned to chromosome 21 and other chromosomes. Gene expression values from chromosome 21, but not from other chromosomes, accurately classified trisomy 21 from euploid samples. Our data also indicated functional groups that might be perturbed in trisomy 21.In Down syndrome, there is a primary transcriptional effect of disruption of chromosome 21 gene expression, without a pervasive secondary effect on the remaining transcriptome. The identification of dysregulated genes and pathways suggests molecular changes that may underlie the Down syndrome phenotypes.Human autosomal abnormality is the leading cause of early pregnancy loss, neonatal death, and multiple congenital malformations [1,2]. Among all the autosomal aneuploidies, Down syndrome (DS), with an incidence of 1 in approximately 800 live births, is most frequently compatible with postnatal survival. It is characterized by mental retardation, hypotonia, short stature, and several dozen other anomalies [3-5].It has been known since 1959 that DS is caused by the triplication of a G group chromosome, now known to be human chromosome 21 [6,7]. As for all aneuploidies, the phenotype of DS is thought to result from the dosage imbalance of multiple genes. By the 1980s, a primary effect of increased gene products, proportional to gene dosage, was established for dozens of enzymes in studies of various aneuploidies [5]. More recently
Whole-Genome Sequencing of a Single Proband Together with Linkage Analysis Identifies a Mendelian Disease Gene
Nara L. M. Sobreira equal contributor,Elizabeth T. Cirulli equal contributor,Dimitrios Avramopoulos equal contributor,Elizabeth Wohler,Gretchen L. Oswald,Eric L. Stevens,Dongliang Ge,Kevin V. Shianna,Jason P. Smith,Jessica M. Maia,Curtis E. Gumbs,Jonathan Pevsner,George Thomas,David Valle ?,Julie E. Hoover-Fong ?,David B. Goldstein ?
PLOS Genetics , 2010, DOI: 10.1371/journal.pgen.1000991
Abstract: Although more than 2,400 genes have been shown to contain variants that cause Mendelian disease, there are still several thousand such diseases yet to be molecularly defined. The ability of new whole-genome sequencing technologies to rapidly indentify most of the genetic variants in any given genome opens an exciting opportunity to identify these disease genes. Here we sequenced the whole genome of a single patient with the dominant Mendelian disease, metachondromatosis (OMIM 156250), and used partial linkage data from her small family to focus our search for the responsible variant. In the proband, we identified an 11 bp deletion in exon four of PTPN11, which alters frame, results in premature translation termination, and co-segregates with the phenotype. In a second metachondromatosis family, we confirmed our result by identifying a nonsense mutation in exon 4 of PTPN11 that also co-segregates with the phenotype. Sequencing PTPN11 exon 4 in 469 controls showed no such protein truncating variants, supporting the pathogenicity of these two mutations. This combination of a new technology and a classical genetic approach provides a powerful strategy to discover the genes responsible for unexplained Mendelian disorders.
Under the Flag of Blue and White: Mary as an A-NationalSymbol in the Greek-Orthodox Community in Israel  [PDF]
Jonathan Ventura
Sociology Mind (SM) , 2011, DOI: 10.4236/sm.2011.14029
Abstract: Marian devotion and rituals have been the apex of Christian believers’ journey for centuries. In spite of its importance in many disciplines, Marian devotion and rituals in Israel have been neglected. In this article I will outline several social and religious aspects of Marian devotion in the Greek-Orthodox community in Israel. Using several case-studies of Marian devotion around the world I will address the question is Mary a national symbol in Israel? Since one of the most important Marian devotion sites is located in Israel and centered in Mary’s place of ascension in Gethsemane, addressing this site directly is crucial. I will express a new concept more fitting to the Israeli case—Mary as an a-national symbol. This research is based upon a combination of two main methodologies: participant observations and in-depth interviews with believers (local Greek and Palestinian residents as well as pilgrims) and clergymen. The research focuses on a procession taking place in the Old City of Jerusalem in the end of August, celebrating Mary’s legacy and resurrection.
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