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Archive for the ‘Next Generation Sequencing (NGS)’ Category


QIAGEN – International Leader in NGS and RNA Sequencing

Reporter: Aviva Lev-Ari, PhD, RN

 

The reader is encouraged to review all the products of QIAGEN on the company web site.

miRCURY Exosome Kits

For enrichment of exosomes and other extracellular vesicles from serum/plasma or cell/urine/CSF samples
  • Excellent recovery of exosomes and other extracellular vesicles
  • Easy and straightforward protocol that takes less than 2 hours
  • No ultracentrifugation or phenol/chloroform steps required
  • Fully compatible with the miRCURY LNA miRNA PCR System
  • Suited for a variety of applications, such as miRNA or RNA profiling

miRCURY Exosome Kits enable high-quality and scalable exosome isolation with an easy protocol that does not require special laboratory equipment. The miRCURY Exosome Serum/Plasma Kit is optimized for serum and plasma samples, while the miRCURY Exosome Cell/Urine/CSF Kit is designed for processing cell-conditioned media, urine and CSF samples. Both kits provide high exosomal recovery and seamless integration with different downstream assays.

SOURCE

https://www.qiagen.com/us/shop/sample-technologies/tumor-cells-and-exosomes/mircury-exosome-kits/#orderinginformation

QIAGEN – Product Profile

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Four patents and one patent application on Nanopore Sequencing and methods of trapping a molecule in a nanopore assigned to Genia, is been claimed in a Law Suit by The Regents of the University of California, should be assigned to UCSC

Reporter: Aviva Lev-Ari, PhD, RN

 

The university claims that while at UCSC Roger Chen’s research focused on nanopore sequencing, and that he along with others developed technology that became the basis of patent applications filed by the university. However, when Chen left the university in 2008 and cofounded Genia, he was awarded patents for technology developed while he was at UCSC, but those patents were assigned to Genia and not the university, according to the suit.

In the suit, the university notes four patents and one patent application assigned to Genia that it claims should be assigned to UCSC: US Patent Nos., 8,324,914; 8,461,854; 9,041,420; and 9,377,437; and US Patent Application 15/079,322. The patents and patent applications all relate to nanopore sequencing and specifically to methods of trapping a molecule in a nanopore and characterizing it based on the electrical stimulus required to move the molecule through the pore.

Genia was founded in 2009, and in 2014, Roche acquired the startup for $125 million in cash and up to $225 million in milestone payments. Earlier this year, the company published a proof-of-principle study of its technology in the Proceedings of the National Academy of Sciences.

Roche’s head of sequencing solutions, Neil Gunn, said that Roche would announce a commercialization timeline in 2017.

It’s unclear how the lawsuit will impact that commercialization, but Mick Watson, director of ARK-Genomics at the Roslin Institute in the UK, speculated in a blog post that if the suit is decided in favor of UCSC, it could result in a very large settlement and potentially even the end of Genia.

 

SOURCE

https://www.genomeweb.com/sequencing/university-california-files-suit-against-genia-cofounder

http://www.opiniomics.org/university-of-california-makes-legal-move-against-roger-chen-and-genia/

 

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A New Computational Method illuminates the Heterogeneity and Evolutionary Histories of cells within a Tumor

Reporter: Aviva Lev-Ari, PhD, RN

 

Start Quote

Numerous computational approaches aimed at inferring tumor phylogenies from single or multi-region bulk sequencing data have recently been proposed. Most of these methods utilize the variant allele fraction or cancer cell fraction for somatic single-nucleotide variants restricted to diploid regions to infer a two-state perfect phylogeny, assuming an infinite-site model such that each site can mutate only once and persists. In practice, convergent evolution could result in the acquisition of the same mutation more than once, thereby violating this assumption. Similarly, mutations could be lost due to loss of heterozygosity. Indeed, both single-nucleotide variants and copy number alterations arise during tumor evolution, and both the variant allele fraction and cancer cell fraction depend on the copy number state whose inference reciprocally relies on the relative ordering of these alterations such that joint analysis can help resolve their ancestral relationship (Figure 1). To tackle this outstanding problem, El-Kebir et al. (2016) formulated the multi-state perfect phylogeny mixture deconvolution problem to infer clonal genotypes, clonal fractions, and phylogenies by simultaneously modeling single-nucleotide variants and copy number alterations from multi-region sequencing of individual tumors. Based on this framework, they present SPRUCE (Somatic Phylogeny Reconstruction Using Combinatorial Enumeration), an algorithm designed for this task. This new approach uses the concept of a ‘‘character’’ to represent the status of a variant in the genome.

Commonly, binary characters have been used to represent single-nucleotide variants— that is, the variant is present or absent. In contrast, El-Kebir et al. use multi-state characters to represent copy number alterations, which may be present in zero, one, two, or more copies in the genome.

SPRUCE outperforms existing methods on simulated data, yielding higher recall rates under a variety of scenarios. Moreover, it is more robust to noise in variant allele frequency estimates, which is a significant feature of tumor genome sequencing data. Importantly, El-Kebir and colleagues demonstrate that there is often an ensemble of phylogenetic trees consistent with the underlying data. This uncertainty calls for caution in deriving definitive conclusions about the evolutionary process from a single solution.”

End Quote

 

From Original Paper

Inferring Tumor Phylogenies from Multi-region Sequencing

Zheng Hu1,2 and Christina Curtis1,2,*

1Departments of Medicine and Genetics

2Stanford Cancer Institute

Stanford University School of Medicine, Stanford, CA 94305, USA

*Correspondence: cncurtis@stanford.edu

http://dx.doi.org/10.1016/j.cels.2016.07.007

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Crowdsourcing Genetic Data Yields Discovery of DNA loci associated with Major Depressive Disorder (MDD) in European Descendants

 

Reporter: Kelly Perlman, Life Sciences Student and Research Assistant, McGill University

 

Researchers from Pfizer Global Research and Development, 23andMe, and the Massachusetts General Hospital have published a study in Nature Genetics, pinpointing 15 genetic loci associated with the risk of developing major depressive disorder (MDD) in individuals of European ancestry. Evidence from previous research suggests that MDD is heritable, but the details of the specific gene correlates are unclear. The identification of loci where single nucleotide polymorphisms (SNPs) related to MDD exist could provide better insight into the neurobiology of depression, and therefore better treatment options.

23andMe, a private biotechnology company situated in California, offers a DNA sequencing service in which consumers send in a saliva swab for testing, and later receive a report listing the findings of the analysis related to ancestry, physical and behavioral traits, along with risk of inheriting certain diseases. The participants of this study had agreed to provide the results of their genetic testing for scientific research.

The results of 75,607 participants with self-reported diagnoses of depression were compared to the results of 231,747 participants reporting having never experienced depression. This data was combined with the results of previously published MDD genome-wide association studies (GWAS). To test the whether these results could be replicated, another set of results from 23andMe was analyzed, in which there were 45,773 MDD subjects, and 106,354 controls.

After the joint analysis, 17 SNPs were identified at 15 different loci. Tissue and gene enrichment assays showed that the genes that were over-expressed in the CNS were related to functions including neurodevelopment, histone methylation, neurogenesis and synaptic modification.

The team then created a weighted genetic risk score (GRS) in which they compared the 17 SNPs with factors including medication use, comorbid diseases and behavioral phenotypes, all of which were correlated with the GRS. Of note, the GRS was very highly correlated with age of onset of MDD.

The crowdsourcing of genetic data proves to be an efficient and powerful tool for large-scale MDD studies. Pooling large subject databases together is essential in order to account for the heterogeneous nature of the disease. Despite not being able to precisely assess each subject’s disease phenotype, scientists can make more rapid headway by collaborating with biotechnology companies in the quest to better understand the biological mechanisms of depression. Ron Perlis, M.D., M.Sc., of the Massachusetts General Hospital and co-author of this paper explained that “finding genes associated with depression should help make clear that this is a brain disease, which we hope will decrease the stigma still associated with these kinds of illnesses”.

 

Details on specific significant genes:

http://www.genecards.org/cgi-bin/carddisp.pl?gene=OLFM4

http://www.genecards.org/cgi-bin/carddisp.pl?gene=TMEM161B

http://www.genecards.org/cgi-bin/carddisp.pl?gene=MEF2C

http://www.genecards.org/cgi-bin/carddisp.pl?gene=MEIS2

http://www.genecards.org/cgi-bin/carddisp.pl?gene=TMCO5A

http://www.genecards.org/cgi-bin/carddisp.pl?gene=NEGR1

 

SOURCES

Hyde, C. L., Nagle, M. W., Tian, C., Chen, X., Paciga, S. A., Wendland, J. R., . . . Winslow, A. R. (2016). Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nature Genetics Nat Genet. doi:10.1038/ng.3623

Major Depressive Disorder Loci Discovered in Large GWAS Enabled by 23andMe Participants’ Data. (2016, August 01). Retrieved August 09, 2016, from https://www.genomeweb.com/microarrays-multiplexing/major-depressive-disorder-loci-discovered-large-gwas-enabled-23andme

 

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Using Online Mendelian Inheritance in Man (OMIM) database and the Human Genome Mutation Database (HGMD) Pro 2015.2 for Quantification of the growth in gene-disease and variant-disease associations

Reporter: Aviva Lev-Ari, PhD, RN

 

Reanalysis of Clinical Exome Data Over Time Could Yield New Diagnoses

NEW YORK (GenomeWeb) – Clinical exomes that are re-evaluated in a systematic way could yield new diagnoses and prove useful to clinicians, according to a study published yesterday in Genetics in Medicine.

A team of researchers from Stanford University set out to examine whether nondiagnostic clinical exomes could provide new information for patients if they were re-examined with current bioinformatics software and knowledge of disease-related variants as presented in the literature.

Clinical exome sequencing yields no diagnosis for about 75 percent of patients evaluated for possible Mendelian disorders, wrote senior author Gill Bejerano and his colleagues. But a reanalysis of exome and phenotypic data from 40 such individuals using current methods identified a definitive diagnosis for four of them — 10 percent — the team said.

In these cases, the causative variant was de novo and found in a relevant autosomal-dominant disease gene. At the time these exomes were first sequenced, the researchers wrote, the existing literature on these causative genes was either “weak, nonexistent, or not readily located.” When the exomes were re-examined by his team, Bejerano noted, the supporting literature was more robust.

SOURCE

https://www.genomeweb.com/sequencing/reanalysis-clinical-exome-data-over-time-could-yield-new-diagnoses?utm_source=SilverpopMailing&utm_medium=email&utm_campaign=Daily%20News:%20Reanalysis%20of%20Clinical%20Exome%20Data%20Over%20Time%20Could%20Yield%20New%20Diagnoses%20-%2007/22/2016%2011:20:00%20AM

At ACMG, Researchers Report Data Re-Analysis, Matchmaking Boosts Solved Exome Cases

In addition to re-analyzing exome data, the researchers have been working on establishing causality for novel candidate disease genes through patient matches. For this, the team has been using the GeneMatcher website, which allows them to find other clinicians and researchers around the world who have patients, or animal models, with mutations in the same genes as their own patients. Through an API developed by the Matchmaker Exchange project, GeneMatcher submitters can also query the PhenomeCentral and Decipher databases. As of March, more than 4,000 genes had been submitted to GeneMatcher from more than 1,300 submitters in 48 countries, and 1,900 matches had been made, Sobreira reported.

Her team has so far submitted data from 104 families, involving 280 genes, and has had 314 matches so far, involving 113 genes. Several cases have been successes, meaning the researchers could establish that a candidate gene is indeed disease causing, and several others are pending, both from Hopkins and from other groups. The total number of solved cases tracing their success to GeneMatcher is currently unknown, Sobreira said, but the organizers are planning to survey submitters about their success rate in the near future.

SOURCE

https://www.genomeweb.com/molecular-diagnostics/acmg-researchers-report-data-re-analysis-matchmaking-boosts-solved-exome-cases

 

Related Articles

 

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New NGS Guidances for Laboratory Developed Tests (LDT): FDA’s Liz Mansfield on Audio Podcast

Reporter: Aviva Lev-Ari, PhD, RN

 

FDA’s Liz Mansfield on New NGS Guidances

Liz Mansfield, Deputy Office Director for Personalized Medicine at the FDA

Chapters:

0:00 A boss who gets it

1:53 The unique challenge of regulating NGS

7:00 How does the new guidance relate to the recent LDT guidance?

12:02 “We’d like to finalize the LDT guidance.”

On July 6th, as part of the President’s Precision Medicine Initiative, the FDA issued two new draft guidances for the oversight of next gen sequencing (NGS) tests. The first guidance is for using NGS testing to diagnose germline diseases. In the second, the FDA lists guidelines for building and using genetic variant databases.

To help us understand just what the guidance is and what led to its release, we’re joined by Liz Mansfield, the Deputy Office Director for Personalized Medicine at the FDA.

It’s unusual for the FDA to issue guidance around a single technology, but Liz says that NGS is “transformative” and is eclipsing so many of the older technologies. The biggest challenge is that NGS is a technology used for discovery and has the power to test for so many things at once.

How does the new NGS guidance relate to the much talked about guidance on LDTs that came out a couple years ago? And does the new guidance represent a more incremental, step by step approach for the FDA in dealing with the explosion of today’s molecular testing field?

“No, it’s not an attempt to break down into smaller bites the issue on LDTs. It’s to address this particular technology, regardless of who the developer is,” says Liz.

The two guidances are for very specific purposes and Liz anticipates further NGS guidances to be issued in the future. For example, guidelines for dealing with somatic mutations rather than germline mutations.

Here is a link to the new FDA Guidelines:

http://www.fda.gov/ucm/groups/fdagov-public/@fdagov-meddev-gen/documents/document/ucm509837.pdf

Use of Public Human Genetic Variant 2 Databases to Support Clinical Validity 3 for Next Generation Sequencing 4 (NGS)-Based In Vitro Diagnostics

AND

http://www.fda.gov/ucm/groups/fdagov-public/@fdagov-meddev-gen/documents/document/ucm509838.pdf

Use of Standards in FDA Regulatory 2 Oversight of Next Generation 3 Sequencing (NGS)-Based In Vitro 4 Diagnostics (IVDs) Used for 5 Diagnosing Germline Diseases

SOURCE

From: <theralpro.activehosted.com@emsd8.com> on behalf of Mendelspod <ayanna@mendelspod.com>

Reply-To: <reply-theralpro.activehosted.537.637.102329@emsd8.com>

Date: Tuesday, July 19, 2016 at 12:00 PM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: FDA’s Liz Mansfield on New NGS Guidances

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Genomic relationship between autism and bipolar disorder

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Autism and Bipolar Disorder Share Common Genetic Roots

http://www.genengnews.com/gen-news-highlights/autism-and-bipolar-disorder-share-common-genetic-roots/81252698/

New study describes genetic commonalities among various psychiatric disorders. [Jonathan Bailey, NHGRI]

Complex neurological disorders, such as autism, schizophrenia, and bipolar disorder (BD) are the likely result of the influence of both common and rare susceptibility genes. While common variation has been widely studied over the past several years, rare variant elucidation has only recently become possible through the use next-generation sequencing techniques.

Now, research from scientists at the University of Iowa (UI) Carver College of Medicine, Johns Hopkins School of Medicine, Cold Spring Harbor Laboratory, and other institutions suggests that there may be genetic susceptibility across major psychiatric disorders—this being the first study to suggest a genetic overlap between bipolar disorder and autism.

Research into BDs is critical due to its high prevalence—affecting between 1% and 3% of the population—and debilitating nature. Although many patients are helped by treatments such as lithium, about one-third of people affected by BD are intractable to current therapies. Although it’s long been known that BD is highly heritable, identifying specific genetic variants that contribute to the illness has proven difficult.

Genomic studies in the past decade have helped uncover several so-called common variations, but none of these variations alone has shown a large effect. However, massively parallel sequencing technology has now provided investigators an opportunity to find rare variations that might individually have a large effect.

“Common variations are thought to each individually have only a tiny impact—for example, increasing a person’s likelihood of getting a disease by 10–20%,” explained senior study author James Potash, M.D., professor and head of the department of psychiatry at UI. “The hope with rare variations is that they individually have a much bigger impact, like doubling or quadrupling risk for disease.”

For this study, the scientists devised a two-tiered strategy, combining a case–control approach with family-based exome sequencing to maximize their chances of identifying rare variants that contribute to BD. Their thinking was that if a genetic variant is found more often in the group of individuals who have the disease compared to a control group of people without the condition, then the gene variation might be associated with increasing susceptibility to the disease.

Moreover, comparing exome sequences of related individuals affected and unaffected by BD can distinguish variants that “travel with” or segregate with the disease. This approach has long been used to identify gene variants or mutations that are passed from parents to children that cause disease.

The findings from this study were published recently in JAMA Psychiatry in an article entitled “Exome Sequencing of Familial Bipolar Disorder.”

The researchers were able to identify, from the family study, 84 rare variants (in 82 genes) that segregated with BD and that were also predicted to be damaging to the proteins encoded by those genes. Subsequently, the research team tested the likelihood that these rare variations might be involved in causing BD by looking for them in three large case–control datasets that included genome sequences from a total of 3541 individuals with BD and 4774 control patients.

Interestingly, despite the large size of the combined datasets, the approach was not powerful enough to identify any of the individual rare variants as definitively associated with BD. However, 19 genes stood out as being overrepresented in BD cases compared to controls.

“The results were not strong enough for us to say ‘we have pinpointed the genetic culprits.’ But it was strong enough for us to remain interested in these genes as potential contributors to bipolar disorder,” noted Dr. Potash.

Yet, when the team considered the 19 genes as a group, they surmised that several were also members of groups of genes that had been implicated in autism and schizophrenia.

“It turned out that the schizophrenia and the autism genes were all more represented among our 82 genes than you would expect by chance,” Dr. Potash remarked. “And when we looked at our whittled down group of 19 genes, the autism genes continued to be unexpectedly prominent among them.

“With studies like this we are finally, after decades of effort, making real progress in nailing down groups of genes and variations in them that play a role in causing bipolar disorder,” Dr. Potash added. “The mechanistic insights we gain from identifying associated genes we hope will point us in the direction of developing new treatments to make a difference for the many people affected by this illness.

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