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Dive into the research topics where Kelly A. Frazer is active.

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Featured researches published by Kelly A. Frazer.


Nature Reviews Genetics | 2009

Human genetic variation and its contribution to complex traits.

Kelly A. Frazer; Sarah S. Murray; Nicholas J. Schork; Eric J. Topol

The last few years have seen extensive efforts to catalogue human genetic variation and correlate it with phenotypic differences. Most common SNPs have now been assessed in genome-wide studies for statistical associations with many complex traits, including many important common diseases. Although these studies have provided new biological insights, only a limited amount of the heritable component of any complex trait has been identified and it remains a challenge to elucidate the functional link between associated variants and phenotypic traits. Technological advances, such as the ability to detect rare and structural variants, and a clear understanding of the challenges in linking different types of variation with phenotype, will be essential for future progress.


Nature | 2011

9p21 DNA variants associated with coronary artery disease impair interferon-γ signalling response.

Olivier Harismendy; Dimple Notani; Xiaoyuan Song; Nazli G Rahim; Bogdan Tanasa; Nathaniel D. Heintzman; Bing Ren; Xiang-Dong Fu; Eric J. Topol; Michael G. Rosenfeld; Kelly A. Frazer

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) in the 9p21 gene desert associated with coronary artery disease (CAD) and type 2 diabetes. Despite evidence for a role of the associated interval in neighbouring gene regulation, the biological underpinnings of these genetic associations with CAD or type 2 diabetes have not yet been explained. Here we identify 33 enhancers in 9p21; the interval is the second densest gene desert for predicted enhancers and six times denser than the whole genome (P < 6.55 × 10−33). The CAD risk alleles of SNPs rs10811656 and rs10757278 are located in one of these enhancers and disrupt a binding site for STAT1. Lymphoblastoid cell lines homozygous for the CAD risk haplotype show no binding of STAT1, and in lymphoblastoid cell lines homozygous for the CAD non-risk haplotype, binding of STAT1 inhibits CDKN2BAS (also known as CDKN2B-AS1) expression, which is reversed by short interfering RNA knockdown of STAT1. Using a new, open-ended approach to detect long-distance interactions, we find that in human vascular endothelial cells the enhancer interval containing the CAD locus physically interacts with the CDKN2A/B locus, the MTAP gene and an interval downstream of IFNA21. In human vascular endothelial cells, interferon-γ activation strongly affects the structure of the chromatin and the transcriptional regulation in the 9p21 locus, including STAT1-binding, long-range enhancer interactions and altered expression of neighbouring genes. Our findings establish a link between CAD genetic susceptibility and the response to inflammatory signalling in a vascular cell type and thus demonstrate the utility of genome-wide association study findings in directing studies to novel genomic loci and biological processes important for disease aetiology.


American Journal of Human Genetics | 2005

High-resolution whole-genome association study of Parkinson disease.

Demetrius M. Maraganore; Mariza de Andrade; Timothy G. Lesnick; Kari J. Strain; Matthew J. Farrer; Walter A. Rocca; P.V. Krishna Pant; Kelly A. Frazer; D. R. Cox; Dennis G. Ballinger

We performed a two-tiered, whole-genome association study of Parkinson disease (PD). For tier 1, we individually genotyped 198,345 uniformly spaced and informative single-nucleotide polymorphisms (SNPs) in 443 sibling pairs discordant for PD. For tier 2a, we individually genotyped 1,793 PD-associated SNPs (P<.01 in tier 1) and 300 genomic control SNPs in 332 matched case-unrelated control pairs. We identified 11 SNPs that were associated with PD (P<.01) in both tier 1 and tier 2 samples and had the same direction of effect. For these SNPs, we combined data from the case-unaffected sibling pair (tier 1) and case-unrelated control pair (tier 2) samples and employed a liberalization of the sibling transmission/disequilibrium test to calculate odds ratios, 95% confidence intervals, and P values. A SNP within the semaphorin 5A gene (SEMA5A) had the lowest combined P value (P=7.62 x 10(-6)). The protein encoded by this gene plays an important role in neurogenesis and in neuronal apoptosis, which is consistent with existing hypotheses regarding PD pathogenesis. A second SNP tagged the PARK11 late-onset PD susceptibility locus (P=1.70 x 10(-5)). In tier 2b, we also selected for genotyping additional SNPs that were borderline significant (P<.05) in tier 1 but that tested a priori biological and genetic hypotheses regarding susceptibility to PD (n=941 SNPs). In analysis of the combined tier 1 and tier 2b data, the two SNPs with the lowest P values (P=9.07 x 10(-6); P=2.96 x 10(-5)) tagged the PARK10 late-onset PD susceptibility locus. Independent replication across populations will clarify the role of the genomic loci tagged by these SNPs in conferring PD susceptibility.


Proceedings of the National Academy of Sciences of the United States of America | 2009

Genomewide SNP variation reveals relationships among landraces and modern varieties of rice.

Kenneth L. McNally; Kevin L. Childs; Regina Bohnert; Rebecca M. Davidson; Keyan Zhao; Victor Jun Ulat; Georg Zeller; Richard M. Clark; Douglas R. Hoen; Thomas E. Bureau; Renee Stokowski; Dennis G. Ballinger; Kelly A. Frazer; D. R. Cox; Badri Padhukasahasram; Carlos Bustamante; Detlef Weigel; David J. Mackill; Richard Bruskiewich; Gunnar Rätsch; C. Robin Buell; Hei Leung; Jan E. Leach

Rice, the primary source of dietary calories for half of humanity, is the first crop plant for which a high-quality reference genome sequence from a single variety was produced. We used resequencing microarrays to interrogate 100 Mb of the unique fraction of the reference genome for 20 diverse varieties and landraces that capture the impressive genotypic and phenotypic diversity of domesticated rice. Here, we report the distribution of 160,000 nonredundant SNPs. Introgression patterns of shared SNPs revealed the breeding history and relationships among the 20 varieties; some introgressed regions are associated with agronomic traits that mark major milestones in rice improvement. These comprehensive SNP data provide a foundation for deep exploration of rice diversity and gene–trait relationships and their use for future rice improvement.


Nature Biotechnology | 2009

Microdroplet-based PCR enrichment for large-scale targeted sequencing

Ryan Tewhey; Jason Warner; Masakazu Nakano; Brian Libby; Martina Medkova; Patricia H David; Steve Kotsopoulos; Michael L. Samuels; J. Brian Hutchison; Jonathan W. Larson; Eric J. Topol; Michael Weiner; Olivier Harismendy; Jeff Olson; Darren R. Link; Kelly A. Frazer

Targeted enrichment of specific loci of the human genome is a promising approach to enable sequencing-based studies of genetic variation in large populations. Here we describe an enrichment approach based on microdroplet PCR, which enables 1.5 million amplifications in parallel. We sequenced six samples enriched by microdroplet or traditional singleplex PCR using primers targeting 435 exons of 47 genes. Both methods generated similarly high-quality data: 84% of the uniquely mapping reads fell within the targeted sequences; coverage was uniform across ∼90% of targeted bases; sequence variants were called with >99% accuracy; and reproducibility between samples was high (r2 = 0.9). We scaled the microdroplet PCR to 3,976 amplicons totaling 1.49 Mb of sequence, sequenced the resulting sample with both Illumina GAII and Roche 454, and obtained data with equally high specificity and sensitivity. Our results demonstrate that microdroplet technology is well suited for processing DNA for massively parallel enrichment of specific subsets of the human genome for targeted sequencing.


Nature | 2007

A sequence-based variation map of 8.27 million SNPs in inbred mouse strains.

Kelly A. Frazer; Eleazar Eskin; Hyun Min Kang; Molly A. Bogue; David A. Hinds; Erica Beilharz; Robert V. Gupta; Julie Montgomery; Matt Morenzoni; Geoffrey B. Nilsen; Charit Pethiyagoda; Laura L. Stuve; Frank M. Johnson; Mark J. Daly; Claire M. Wade; D. R. Cox

A dense map of genetic variation in the laboratory mouse genome will provide insights into the evolutionary history of the species and lead to an improved understanding of the relationship between inter-strain genotypic and phenotypic differences. Here we resequence the genomes of four wild-derived and eleven classical strains. We identify 8.27 million high-quality single nucleotide polymorphisms (SNPs) densely distributed across the genome, and determine the locations of the high (divergent subspecies ancestry) and low (common subspecies ancestry) SNP-rate intervals for every pairwise combination of classical strains. Using these data, we generate a genome-wide haplotype map containing 40,898 segments, each with an average of three distinct ancestral haplotypes. For the haplotypes in the classical strains that are unequivocally assigned ancestry, the genetic contributions of the Mus musculus subspecies—M. m. domesticus, M. m. musculus, M. m. castaneus and the hybrid M. m. molossinus—are 68%, 6%, 3% and 10%, respectively; the remaining 13% of haplotypes are of unknown ancestral origin. The considerable regional redundancy of the SNP data will facilitate imputation of the majority of these genotypes in less-densely typed classical inbred strains to provide a complete view of variation in additional strains.


Nature Genetics | 2006

Common deletions and SNPs are in linkage disequilibrium in the human genome

David A. Hinds; Andrew P Kloek; Michael Jen; Xiyin Chen; Kelly A. Frazer

Humans show great variation in phenotypic traits such as height, eye color and susceptibility to disease. Genomic DNA sequence differences among individuals are responsible for the inherited components of these complex traits. Reports suggest that intermediate and large-scale DNA copy number and structural variations are prevalent enough to be an important source of genetic variation between individuals. Because association studies to identify genomic loci associated with particular phenotypic traits have focused primarily on genotyping SNPs, it is important to determine whether common structural polymorphisms are in linkage disequilibrium with common SNPs, and thus can be assessed indirectly in SNP-based studies. Here we examine 100 deletion polymorphisms ranging from 70 bp to 7 kb. We show that common deletions and SNPs ascertained with similar criteria have essentially the same distribution of linkage disequilibrium with surrounding SNPs, indicating that these polymorphisms may share evolutionary history and that most deletion polymorphisms are effectively assayed by proxy in SNP-based association studies.


Genome Research | 2000

Active Conservation of Noncoding Sequences Revealed by Three-Way Species Comparisons

Inna Dubchak; Michael Brudno; Gabriela G. Loots; Lior Pachter; Chris Mayor; Edward M. Rubin; Kelly A. Frazer

Human and mouse genomic sequence comparisons are being increasingly used to search for evolutionarily conserved gene regulatory elements. Large-scale human-mouse DNA comparison studies have discovered numerous conserved noncoding sequences of which only a fraction has been functionally investigated A question therefore remains as to whether most of these noncoding sequences are conserved because of functional constraints or are the result of a lack of divergence time.


Genetics in Medicine | 2013

Implementing genomic medicine in the clinic: the future is here

Teri A. Manolio; Rex L. Chisholm; Brad Ozenberger; Dan M. Roden; Marc S. Williams; Richard Wilson; David P. Bick; Erwin P. Bottinger; Murray H. Brilliant; Charis Eng; Kelly A. Frazer; Bruce R. Korf; David H. Ledbetter; James R. Lupski; Clay B. Marsh; David A. Mrazek; Michael F. Murray; Peter H. O'Donnell; Daniel J. Rader; Mary V. Relling; Alan R. Shuldiner; David Valle; Richard M. Weinshilboum; Eric D. Green; Geoffrey S. Ginsburg

Although the potential for genomics to contribute to clinical care has long been anticipated, the pace of defining the risks and benefits of incorporating genomic findings into medical practice has been relatively slow. Several institutions have recently begun genomic medicine programs, encountering many of the same obstacles and developing the same solutions, often independently. Recognizing that successful early experiences can inform subsequent efforts, the National Human Genome Research Institute brought together a number of these groups to describe their ongoing projects and challenges, identify common infrastructure and research needs, and outline an implementation framework for investigating and introducing similar programs elsewhere. Chief among the challenges were limited evidence and consensus on which genomic variants were medically relevant; lack of reimbursement for genomically driven interventions; and burden to patients and clinicians of assaying, reporting, intervening, and following up genomic findings. Key infrastructure needs included an openly accessible knowledge base capturing sequence variants and their phenotypic associations and a framework for defining and cataloging clinically actionable variants. Multiple institutions are actively engaged in using genomic information in clinical care. Much of this work is being done in isolation and would benefit from more structured collaboration and sharing of best practices.Genet Med 2013:15(4):258–267


Nature Genetics | 2007

New models of collaboration in genome-wide association studies: the Genetic Association Information Network.

Teri A. Manolio; Laura Lyman Rodriguez; Lisa D. Brooks; Gonçalo R. Abecasis; Dennis G. Ballinger; Mark J. Daly; Peter Donnelly; Stephen V. Faraone; Kelly A. Frazer; Stacey Gabriel; Pablo V. Gejman; Alan E. Guttmacher; Emily L. Harris; Thomas R. Insel; John R. Kelsoe; Eric S. Lander; Norma McCowin; Matthew D. Mailman; Elizabeth G. Nabel; James Ostell; Elizabeth W. Pugh; Stephen T. Sherry; Patrick F. Sullivan; John F. Thompson; James H. Warram; David Wholley; Patrice M. Milos; Francis S. Collins

The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.

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Erin N. Smith

University of California

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Hiroko Matsui

University of California

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Kristen Jepsen

University of California

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