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Cooper G.M.,HudsonAlpha Institute for Biotechnology | Shendure J.,University of Washington
Nature Reviews Genetics | Year: 2011

Genome and exome sequencing yield extensive catalogues of human genetic variation. However, pinpointing the few phenotypically causal variants among the many variants present in human genomes remains a major challenge, particularly for rare and complex traits wherein genetic information alone is often insufficient. Here, we review approaches to estimate the deleteriousness of single nucleotide variants (SNVs), which can be used to prioritize disease-causal variants. We describe recent advances in comparative and functional genomics that enable systematic annotation of both coding and non-coding variants. Application and optimization of these methods will be essential to find the genetic answers that sequencing promises to hide in plain sight. © 2011 Macmillan Publishers Limited. All rights reserved. Source


Hong L.Z.,Stanford University | Li J.,Stanford University | Schmidt-Kuntzel A.,Conservation Fund | Warren W.C.,University of Washington | And 2 more authors.
Genome Research | Year: 2011

Next-generation sequencing technologies offer new approaches for global measurements of gene expression but are mostly limited to organisms for which a high-quality assembled reference genome sequence is available. We present a method for gene expression profiling called EDGE, or EcoP15I-tagged Digital Gene Expression, based on ultra-high-throughput sequencing of 27-bp cDNA fragments that uniquely tag the corresponding gene, thereby allowing direct quantification of transcript abundance. We show that EDGE is capable of assaying for expression in >99% of genes in the genome and achieves saturation after 6-8 million reads. EDGE exhibits very little technical noise, reveals a large (106) dynamic range of gene expression, and is particularly suited for quantification of transcript abundance in non-model organisms where a high-quality annotated genome is not available. In a direct comparison with RNA-seq, both methods provide similar assessments of relative transcript abundance, but EDGE does better at detecting gene expression differences for poorly expressed genes and does not exhibit transcript length bias. Applying EDGE to laboratory mice, we show that a loss-of-function mutation in the melanocortin 1 receptor (Mc1r), recognized as a Mendelian determinant of yellow hair color in many different mammals, also causes reduced expression of genes involved in the interferon response. To illustrate the application of EDGE to a non-model organism, we examine skin biopsy samples from a cheetah (Acinonyx jubatus) and identify genes likely to control differences in the color of spotted versus non-spotted regions. © 2011 by Cold Spring Harbor Laboratory Press. Source


Cooper G.M.,HudsonAlpha Institute for Biotechnology
Genome Research | Year: 2015

Human genome sequencing is routine and will soon be a staple in research and clinical genetics. However, the promise of sequencing is often just that, with genome data routinely failing to reveal useful insights about disease in general or a person's health in particular. Nowhere is this chasm between promise and progress more evident than in the designation, "variant of uncertain significance" (VUS). Although it serves an important role, careful consideration of VUS reveals it to be a nebulous description of genomic information and its relationship to disease, symptomatic of our inability to make even crude quantitative assertions about the disease risks conferred by many genetic variants. In this perspective, I discuss the challenge of "variant interpretation" and the value of comparative and functional genomic information in meeting that challenge. Although already essential, genomic annotations will become even more important as our analytical focus widens beyond coding exons. Combined with more genotype and phenotype data, they will help facilitate more quantitative and insightful assessments of the contributions of genetic variants to disease. © 2015 Cooper. Source


Patent
HudsonAlpha Institute for Biotechnology and Stanford University | Date: 2014-03-13

The present disclosure provides for and relates to the identification of novel biomarkers for diagnosis and prognosis of prostate cancer or the biochemical reoccurence of prostate cancer. The biomarkers of the invention show altered methylation levels of certain CpG loci relative to normal prostate tissue, as set forth.


Gertz J.,HudsonAlpha Institute for Biotechnology | Reddy T.E.,HudsonAlpha Institute for Biotechnology | Reddy T.E.,Duke University | Varley K.E.,HudsonAlpha Institute for Biotechnology | And 2 more authors.
Genome Research | Year: 2012

Endogenous estrogens that are synthesized in the body impact gene regulation by activating estrogen receptors in diverse cell types. Exogenous compounds that have estrogenic properties can also be found circulating in the blood in both children and adults. The genome-wide impact of these environmental estrogens on gene regulation is unclear. To obtain an integrated view of gene regulation in response to environmental and endogenous estrogens on a genome-wide scale, we performed ChIP-seq to identify estrogen receptor 1 (ESR1; previously estrogen receptor a) binding sites, and RNA-seq in endometrial cancer cells exposed to bisphenol A (BPA; found in plastics), genistein (GEN; found in soybean), or 17bestradiol (E2; an endogenous estrogen). GEN and BPA treatment induces thousands of ESR1 binding sites and >50 gene expression changes, representing a subset of E2-induced gene regulation changes. Genes affected by E2 were highly enriched for ribosome-associated proteins; however, GEN and BPA failed to regulate most ribosome-associated proteins and instead enriched for transporters of carboxylic acids. Treatment-dependent changes in gene expression were associated with treatment-dependent ESR1 binding sites, with the exception that many genes up-regulated by E2 harbored a BPAinduced ESR1 binding site but failed to show any expression change after BPA treatment. GEN and BPA exhibited a similar relationship to E2 in the breast cancer line T-47D, where cell type specificity played a much larger role than treatment specificity. Overall, both environmental estrogens clearly regulate gene expression through ESR1 on a genome-wide scale, although with lower potency resulting in less ESR1 binding sites and less gene expression changes compared to the endogenous estrogen, E2. © 2012, Published by Cold Spring Harbor Laboratory Press. Source

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