Utilization of NGS data and genomic selection to rescue an endangered and heritage sheep breed from Florida
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The Florida Cracker Sheep (FCS) is one of the oldest sheep breeds in the United States. This heritage breed from Florida, naturally adapted to humid and hot climate conditions, is one of the most parasite resistant breeds from the Southern US. However, approximately 1,000 individuals remain alive in the world. Therefore, more research and conservational efforts are required to support all the FCS producers from Florida and rescue FCS from extinction. Advancements in NGS technologies and reduction in genotyping costs have allowed the utilization of these tools in animal genetics and genomics. We followed up a FCS population (n = 350) from a commercial farm to evaluate parasite resistance traits (FEC, FAMACHA score, hematocrit) using a longitudinal study and genotyped 300 sheep using the GGP Ovine 50k array. Analysis with Golden Helix SVS software identified 15 SNPs with additive and non-additive effects associated with parasite resistance in chromosome 1, 2, 3, 6, 8, 10, 11,12, 13 and 21. Also, a deletion CNV was associated with parasite resistance (FEC) in chromosome 21. Some of these DNA variants were located in STAT5B, NRIPI, TRPM3, WC1, GPC5, CELF2 and RAB3IL genes which control immune response mechanisms in sheep. Validation of these results and implementation of genomic selection utilizing information from NGS, SNP genotyping and WGS can be easily performed by Golden Helix SVS software. This will allow the implementation of breeding and conservational programs in FCS farms and will improve the profitability of farms over the long term by incorporating the use of genetically parasite resistant sheep and promote local sheep meat production in Florida.
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The Molecular Diagnostics Laboratory processes around 20,000 specimens annually for various testing categories including infectious diseases, hematological malignancies, solid tumor malignancies, and inherited disorders. Next generation sequencing is proposed as a solution to provide more comprehensive genetic testing by simultaneously evaluating variations in multiple genes from a single sample. While next generation sequencing offers advantages over traditional testing methods, there are also technical and clinical challenges to address in implementation, including optimizing detection of structural variations and interpretation of variants with unclear clinical significance.
SOT2010 GeneGo presentation
This document discusses a study comparing the toxicogenomic response of three rat strains (Han Wistar, Sprague Dawley, and Fischer 344) and gender to an acute dose of cisplatin-induced renal injury. Gene expression analysis found both similarities and differences in responses. Specifically, 1) pathways related to DNA damage and apoptosis were commonly induced in males and females, reflecting cisplatin's mechanism, while 2) individual gene responses and metabolic pathways varied between strains and gender. The study demonstrates how toxicogenomic profiling can provide insight into toxicological responses at a molecular level while also highlighting inter-strain variability.
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Oncogenicity Scoring in VSClinical
This document summarizes a presentation by Golden Helix about their VSClinical software for clinical variant interpretation and reporting. It discusses key features of VSClinical including automated scoring of variants according to ACMG/AMP guidelines, integrated clinical reporting, and customization options. It also acknowledges funding support from several NIH grants.
ClinVar: Aggregating Data to Improve Variant Interpretation - Melissa Landrum
The rate of variant discovery continues to surpass the rate of clinicalgrade interpretation. This is a challenge for precision medicine, because fast, reliable access to variant interpretations is necessary to provide well-informed and timely interpretations of test results to patients. ClinVar is a public repository for interpretations of clinical significance and functional effects of variants in any gene and for any disease. Interpretations are submitted by many sources, including clinical testing laboratories, research laboratories, locus-specific databases, expert panels, practice guidelines, as well as OMIM® and GeneReviews™. Collecting variant interpretations in ClinVar depends on integrating data from these different sources, which has several benefits. First, data integration requires standardizing the data from each source. This improves the quality of the data in ClinVar as well as in each of the individual datasets. ClinVar staff validate HGVS expressions as a routine part of ClinVar submission processing. Submitters are encouraged to use standard terms in MedGen for diseases and phenotypes. Standard terms for clinical significance are used in ClinVar when available; for example, ClinVar uses the terms recommended by ACMG to classify variants for Mendelian diseases. Secondly, ClinVar aggregates all data for a variant defined by its genomic location. Therefore, HGVS descriptions on different transcripts or on different genomic sequences can be recognized as the same variant. Thirdly, integrating data from multiple submitters allows the evidence from all sources to be pooled together. This larger collection of evidence aids the re-evaluation of variant classifications, and is especially valuable for rare variants and novel gene-disease relationships. Fourthly, data integration means that variant interpretations from different sources can be viewed together and compared. Thus a ClinVar user has access to interpretations outside any internal system and knows when there is consensus in the interpretation or not. Submitting laboratories use reports of conflicting interpretations in ClinVar to prioritize variants that they should re-evaluate. ClinVar receives data from many data providers, and therefore provides clear attribution to each contributing group, including links to records in LSDBs. Each source may update their submission to ClinVar at any time. For example, a record may be updated when a variant is re-classified or when additional evidence is available to support the interpretation. Submitters may consider providing regular updates to ClinVar to prevent their interpretations from becoming out of date. Submissions to ClinVar describe variants that range in complexity from simple alleles with explicit sequence locations through copy number changes and cytogenetic rearrangements with fuzzy boundaries.
Next-Generation Sequencing Analysis in VSClinical
VarSeq is a tertiary analysis platform that allows users to filter and annotate NGS sequencing data to identify clinically relevant variants. Following this workflow, VSClinical can then be used to automate both germline and somatic variant analysis in accordance with the ACMG and AMP guidelines by using a variety of functional prediction models and clinical and reviewer-based annotations. Once variant or biomarker interpretations are completed, they can be rendered in a customizable clinical report and stored in an internal assessment catalog as an internal variant database repository. Together, implementation of VSClinical will promote increased lab throughput as well as accuracy and compliance with the ACMG and AMP guidelines, which in turn can save time and money. To show the capabilities of our software, this webcast will provide a demonstration of how to use VarSeq and VSClinical for the evaluation of both germline and somatic variants in accordance with the ACMG and AMP Guidelines.
In this webcast, we will cover:
- Filter logics for germline and somatic variants and selecting them into the VSClinical interface
- Capabilities of functional prediction and splice site algorithms for edge case variants
- The functionality of changing the clinically relevant transcript on variant interpretation
- Rendering a clinical report with germline and somatic variants with the inclusion of clinical trials
The ClinGen Sequence Variant Interpretation Working Group: Refining Criteria ...
The ClinGen Sequence Variant Interpretation Working Group: Refining Criteria ...Human Variome Project
The ClinGen Sequence Variant Interpretation Working Group aims to refine criteria for classifying genetic variants by standardizing how different types of evidence are integrated. In the short term, it will refine and modify current American College of Medical Genetics guidelines. It will work with disease-specific groups to evaluate criteria like population frequency thresholds and computational methods. The long term goal is to develop a quantitative Bayesian framework to classify variants. The working group will analyze ClinVar to identify disease genes with many reported variants to help evaluate criteria.ACMG-Based Variant Classification with VSClinical
Golden Helix is a global bioinformatics company founded in 1998 that provides software for variant annotation, filtering, and interpretation. Their flagship products are VarSeq Suite and VSClinical. VarSeq Suite allows for powerful variant filtering and annotation using curated public databases and premium annotations. VSClinical streamlines variant classification using American College of Medical Genetics and Genomics guidelines through a four-phased workflow involving variant filtering, evidence assessment, classification, and reporting. It provides consistent results and reduces learning curves for users. Golden Helix has over 400 customers globally and their software is cited in thousands of peer-reviewed publications.
Exploring New Features and Clinical Reports in the ACMG Guideline Workflow
For the past year, Golden Helix has been preparing a VarSeq release that includes ACMG Guidelines scoring and classification for not only single nucleotide variants but also copy number variants. In the past few months, our webcasts have introduced these guidelines and explored example CNVs that demonstrated the automated scoring of CNVs according to the new ACMG CNV Guidelines. However, there are many other new features and upgrades that have been incorporated into this VarSeq release. These upgrades have largely been driven by input from VarSeq users! That’s why I am very excited to explore these features together in the upcoming webcast “Exploring New Features and Clinical Reports in the ACMG Guideline Workflow”. In this webcast, we will walk through a workflow with SNVs and CNVs highlighting many of the new features and upgrades that will improve and streamline your ACMG workflow. Notably, we will see how these new features can also be incorporated into clinical reports.
Specifically, we will cover the following features:
New and improved ACMG Classifier algorithms
New and improved assessment catalogs for saving classifications and interpretations
New Project Options interface for creating patient evaluations
Now offering three new word-based clinical report templates
Inclusion of additional sections and features to the clinical reports
Enhanced report customization capability
Establishing validity, reproducibility, and utility of highly scalable geneti...
Establishing validity, reproducibility, and utility of highly scalable geneti...Human Variome Project
Background: New technologies and increased competition have, and will continue to improve the cost-effectiveness of genetic testing, making genetic analysis more accessible to medical practices worldwide. However, challenges remain to establishing the validity of such tests. Moreover many patients harbor rare or novel variants and classification is likely to remain a bottleneck in broader deployment of genetic medicine.Automating the ACMG Guidelines with VSClinical
Clinical Genetic testing requires a complex analysis using the totality of our knowledge about the clinical relevance of a variant and a gene. This includes bioinformatic evidence as well as clinical evidence. The ACMG Guidelines provided a framework in which to score variants based on this evidence, and while some of those scoring criteria require close consultation of the clinical context for a given patient, much of it can be automated.
In this webcast, we review how VSClinical automates the ACMG scoring guidelines while integrating the collective lab expertise from previously classified variants and preferences about genes. We will cover:
Using the ACMG Auto Classifier as part the filtering strategy for gene panels and trio workflows
How gene preferences such as the default transcript, inheritance model, and disorder are updated and saved from VSClinical and used in all future analysis
How the per-variant recommendation engine builds on the auto-classification with descriptive reasons for answering each criterion yes or no
Using the auto-interpretation to present the evidence for all scored criteria in a human-readable paragraph
Working with VSClinical’s self-learning knowledgebase that incorporates previously classified variants and genes inform the interpretation of new variants!
Introducing VSClinical AMP Guidelines: A Comprehensive Workflow for NGS Testi...
Golden Helix is introducing new guidelines for next-generation sequencing (NGS) testing of cancer samples using their VSClinical software. The AMP guidelines provide a comprehensive workflow for variant filtering, annotation, classification evidence levels, and integrated clinical reporting of somatic and germline variants. The software utilizes various data sources to aid in cancer interpretation and allows users to save and reuse interpretations. An upcoming webinar will demonstrate how to score somatic variants for oncogenicity using VSClinical.
Advanced Report Customization via VSClinical
This document provides a summary of a presentation about advanced customization capabilities for clinical reports using VSClinical software:
- VSClinical allows customization of clinical reports through custom HTML, XML, JSON templates and scripts to enhance Word reports and integrate with REST APIs.
- Templates are provided for germline and somatic variant analysis that include ACMG/AMP guidelines and can be further customized.
- Reports can include additional data such as gene impact analysis, drug/trial information, and machine-readable outputs like JSON can be generated.
- A product demo was given to showcase report customization features.
The BRCA Share(TM) Consortium - Christophe Beroud
The BRCA ShareTM Consortium is a public-private partnership that promotes sharing of BRCA genetic data. It has over 35,000 BRCA test results from US and French clinical labs. The goal is to accelerate BRCA research. It is a open user group co-founded by Inserm and Quest Diagnostics. BRCA ShareTM is well adopted internationally. In June 2016, it incorporated new data from private partners, increasing the number of known BRCA mutations. The consortium of French experts helps curate and reclassify variants of unknown significance based on multiple lines of evidence. This benefits all partners through improved annotation of shared variants.
Dr. Jack Dekkers - Using genetic selection and genomics to combat infectious ...
Using genetic selection and genomics to combat infectious disease - Dr. Jack Dekkers, Iowa State University, from the 2017 North American PRRS/National Swine Improvement Federation Joint Meeting, December 1‐3, 2017, Chicago, Illinois, USA.
More presentations at http://www.swinecast.com/2017-north-american-prrs-nsif-joint-meeting
Whole Genome Trait Association in SVS
Golden Helix’s SNP & Variation Suite (SVS) has been used by researchers around the world to do trait analysis and association testing on large cohorts of samples in both humans and other species. As Next-Generation Sequencing of whole genomes becomes more affordable, large cohorts of Whole Genome Sequencing (WGS) samples are available to search for additional trait association signals that were not found in array-based testing. In fact, recent papers have shown that WGS analysis using advanced GREML (Genomic Relatedness Restricted Maximum Likelihood) techniques is able to outperform micro-array based GWAS methods in the analysis of complex traits and proportion of the trait heritability explained.
Our latest update release of SVS has expanded the exiting maximum likelihood and GRM methods to support these new techniques. We have also enhanced various other association testing and prediction methodologies. This webcast showcases:
- Newly supported analysis workflow for whole genome variants using LD binning and enhanced GBLUP analysis
- Enhanced gender correction using REML
- Additional capabilities for genomic prediction and phenotype prediction
We are continually improving our products based on our customer’s feedback. We hope you enjoy this recording highlighting the exciting new features and select enhancements we have made.
Big Data and Genomic Medicine by Corey Nislow
View the webinar at: http://www.knome.com/webinar-big-data-genomic-medicine. This presentation covers an overview of genomic medicine, requirements and challenges of next-generation sequencing, bottlenecks to broader healthcare adoption, and why “we want to sequence everyone.”
1090825-陳華鍵-基因檢測現況與展望
Genetic testing identifies changes in a person's genes, chromosomes, or proteins to determine if they have or are at risk of developing a genetic disorder. Over 1,000 genetic tests are currently available and being used to assess health risks, guide treatment choices, and determine treatment responses. Specific tests like BRCA1/2 genetic testing can help determine a person's risk of developing breast or ovarian cancers. Next generation sequencing has increased genetic testing capabilities by providing higher throughput of data at a much lower cost compared to previous methods.
Phenotype-based Matching Using PhenoDB Terms in BHCMG PhenoDB to Maximize Who...
Phenotype-based Matching Using PhenoDB Terms in BHCMG PhenoDB to Maximize Who...Human Variome Project
Matchmaking initiatives like GeneMatcher, have demonstrated the utility of gene-based matching for identification of unrelated individuals with similar phenotypes and pathogenic variants in the same gene. Phenotype-based matching (PBM) has been attempted less widely because of challenges such as phenotypic variability, relative paucity of phenotypic details in clinical genomic databases, and the use of variable phenotypic terminology by clinicians and researchers. As part of the Baylor-Hopkins Center for Mendelian Genomics (BHCMG), users submit their cases to PhenoDB using PhenoDB phenotypic terms, which enables the use of semantic-similarity based methodologies to quantify phenotypic overlap within the database. To test PBM, we initially compared the following methodologies: Jacquard, Distance, Resnick (OMIM-based and PhenoDB-based corpora), and Wang. The Resnick-PhenoDB algorithm uses the phenotypic features that describe 4,114 cases in PhenoDB as the corpus for calculation of information content instead of the OMIM clinical synopses or HPO annotations. To validate the matching algorithms, we utilized a simulated set of 55 cases phenotyped by using the OMIM clinical synopsis of four well known phenotypes (OMIM 136140, 615960, 117650, 615273), and demonstrated that for 3 of the 4 disorders, all cases known to have the same disorder had the highest phenotypic similarity scores. We then tested the matching algorithms on phenotypic data from 4,114 unrelated probands in the BHCMG PhenoDB. We chose 3 phenotypes for which multiple unrelated probands are present in the database: Gomez-Lopez-Hernandez Syndrome (N=5, GLHS, OMIM 601853), Hemifacial Microsomia (N=12, HFM, OMIM 164210), and Lateral Meningocele Syndrome (N=5, LMNS, OMIM 130720). The average number of features entered per phenotype was 7.3 for GLHS, 8.14 for HFM and 0.8 for LMNS. We selected one case at random for each condition as the query case and determined the proportion of expected matching cases present in the top 1% and 5% among the 4,114 cases. Resnick-PhenoDB algorithm found that for GLHS, 3 of the 5 expected matching cases were identified among the top 1% and 4 of 5 in the top 5%. For HFM, 2 of the 12 expected matching cases were identified among the top 1% and 4 of 12 in the top 5%. For LMNS, 0 out of the 5 expected matching cases were identified among the top 1% and 0 of 5 in the top 5%. Using a simulated set of cases, we showed that all 5 algorithms performed similarly and that Resnick PhenoDB-based algorithm is able to identify and prioritize the expected matching cases among the total number of cases. Applying the Resnick PhenoDB-based algorithm to the real-world BHCMG PhenoDB showed the importance of detailed case descriptions if PBM is desired. Efforts to improve the availability and consistency of phenotypic annotations, as well as enhanced similarity calculation methodologies, will improve the fidelity and utility of PBM.Cancer Diagnostics Laboratory | NeoGenomics | April 2014 | Company Overview P...
Cancer Diagnostics Laboratory | NeoGenomics | April 2014 | Company Overview P...NeoGenomics Laboratory | Cancer Diagnostics
Cancer Diagnostics Reference Laboratory / NeoGenomics April 2014 investors company overview presentation. This presentation highlights the following:
--Fast growing cancer genetics lab servicing Oncologists, Pathologists and Hostpitals
--Strategic client partnerships created by "Tech-Only" model
--Dynamic, rapidly-growing and consolidating industry
Industry-leading revenue & test volume growth
--Strong productivity and operating leverage leading to accelerating cash flow and net income
--Strong Management Team with large cap lab experiencePharmacogenomic Prediction of Antracycline-induced Cardiotoxicity
This document discusses pharmacogenomic prediction of anthracycline-induced cardiotoxicity in childhood cancer. It outlines the background and rationale for the research, including that anthracyclines are highly effective chemotherapy drugs but can cause cardiotoxicity in some patients. The research aims to identify genetic factors that modify cardiotoxicity risk to inform treatment decisions. It describes the genome-wide association study conducted using the SNP & Variation Suite, which identified the RARG gene variant rs2229774 as a novel biomarker for cardiotoxicity risk. Functional validation showed RARG regulates the TOP2B gene linked to cardiotoxicity. The findings provide new insight into anthracycline cardiotoxicity and potential for genetic risk stratification to personal
Rare diseases in children and genetic diagnosis - part 1 [Today's paper]
Today's paper is a review for genetic diagnosis of paediatric rare diseases.
The title is "Paediatric genomics: diagnosing rare disease in children." published in 2018, Nature review genetics.
Thanks for watching!
doi: 10.1038/nrg.2017.116.
ACMG 2017 The Data Behind the Results - Bioinformatics for Clinicians
This document discusses next-generation sequencing (NGS) for clinical use. It begins with an overview of NGS compared to Sanger sequencing, noting that while NGS reads are shorter, it makes up for it with high depth coverage. It then discusses various aspects of clinical NGS testing including target preparation methods, sequencing workflows that can vary between labs, interpreting results, and the importance of detailed phenotyping for test selection and results interpretation. The document emphasizes that NGS has become a core platform with many applications but also requires significant expertise to implement well.
What's hot (20)
ClinVar: Aggregating Data to Improve Variant Interpretation - Melissa Landrum
ClinVar: Aggregating Data to Improve Variant Interpretation - Melissa Landrum
The ClinGen Sequence Variant Interpretation Working Group: Refining Criteria ...
The ClinGen Sequence Variant Interpretation Working Group: Refining Criteria ...
Exploring New Features and Clinical Reports in the ACMG Guideline Workflow
Exploring New Features and Clinical Reports in the ACMG Guideline Workflow
Establishing validity, reproducibility, and utility of highly scalable geneti...
Establishing validity, reproducibility, and utility of highly scalable geneti...
Introducing VSClinical AMP Guidelines: A Comprehensive Workflow for NGS Testi...
Introducing VSClinical AMP Guidelines: A Comprehensive Workflow for NGS Testi...
Dr. Jack Dekkers - Using genetic selection and genomics to combat infectious ...
Dr. Jack Dekkers - Using genetic selection and genomics to combat infectious ...
Phenotype-based Matching Using PhenoDB Terms in BHCMG PhenoDB to Maximize Who...
Phenotype-based Matching Using PhenoDB Terms in BHCMG PhenoDB to Maximize Who...
Cancer Diagnostics Laboratory | NeoGenomics | April 2014 | Company Overview P...
Cancer Diagnostics Laboratory | NeoGenomics | April 2014 | Company Overview P...
Pharmacogenomic Prediction of Antracycline-induced Cardiotoxicity
Pharmacogenomic Prediction of Antracycline-induced Cardiotoxicity
Rare diseases in children and genetic diagnosis - part 1 [Today's paper]
Rare diseases in children and genetic diagnosis - part 1 [Today's paper]
ACMG 2017 The Data Behind the Results - Bioinformatics for Clinicians
ACMG 2017 The Data Behind the Results - Bioinformatics for Clinicians
Similar to Utilization of NGS data and genomic selection to rescue an endangered and heritage sheep breed from Florida
Clinical Applications of Next Generation Sequencing
The Molecular Diagnostics Laboratory processes around 20,000 specimens annually for various testing categories including infectious diseases, hematological malignancies, solid tumor malignancies, and inherited disorders. Next generation sequencing is proposed as a solution to provide more comprehensive genetic testing by simultaneously evaluating variations in multiple genes from a single sample. While next generation sequencing offers advantages over traditional testing methods, there are also technical and clinical challenges to address in implementation, including optimizing detection of structural variations and interpretation of variants with unclear clinical significance.
SOT2010 GeneGo presentation
This document discusses a study comparing the toxicogenomic response of three rat strains (Han Wistar, Sprague Dawley, and Fischer 344) and gender to an acute dose of cisplatin-induced renal injury. Gene expression analysis found both similarities and differences in responses. Specifically, 1) pathways related to DNA damage and apoptosis were commonly induced in males and females, reflecting cisplatin's mechanism, while 2) individual gene responses and metabolic pathways varied between strains and gender. The study demonstrates how toxicogenomic profiling can provide insight into toxicological responses at a molecular level while also highlighting inter-strain variability.
Genetic variation in individual & population, polymorphism, Hardy-Weinberg Eq...
Genetic variation exists between individuals and populations. This document discusses genetic variation and polymorphisms, including single nucleotide polymorphisms (SNPs). It also discusses allele frequencies, the odds ratio, and Hardy-Weinberg equilibrium. The document summarizes a research article that developed a multiplex assay using SNaPshot minisequencing to simultaneously screen for SNPs associated with fetal hemoglobin levels in genes like BCL11A and HBS1L-MYB.
Copy number variants in the development of psychiatric comorbidity in the Inf...
This document describes a study aiming to identify genetic risk loci for depression and anxiety in patients with inflammatory bowel disease (IBD) using genome-wide scans. The study involved genotyping samples from IBD patients both with and without psychiatric comorbidities, performing quality control checks on the samples and copy number variant (CNV) calls, and analyzing CNVs overlapping genes to identify associations with psychiatric comorbidity in IBD. Key findings included a higher proportion of CNVs overlapping genes in IBD patients without psychiatric comorbidity compared to those with comorbidity, and several genes affected by CNVs being identified as potentially associated with psychiatric comorbidity in IBD after applying statistical tests and multiple testing correction.
Stephanie Allen-Diagnóstico prenatal no invasivo y diagnóstico genético repro...
Stephanie Allen-Diagnóstico prenatal no invasivo y diagnóstico genético repro...Fundación Ramón Areces
This document provides an overview of non-invasive prenatal diagnosis (NIPD) for single gene disorders using cell-free fetal DNA. It summarizes the development and validation of two NIPD approaches through the NIPSIGEN study: 1) Bespoke assays for specific mutations and 2) Relative haplotype dosage analysis using SNPs to track inheritance of mutated genes. It reports on the clinical implementation of these approaches in the West Midlands Regional Genetics Lab for conditions like DMD/BMD, SMA, CF, and CAH. Results from over 50 NIPD tests conducted to date show 100% accuracy compared to invasive testing. The document concludes by outlining the clinical service and pathways that are now availableDr. Ben Hause - Metagenomic Sequencing for Virus Discovery and Characterization
Metagenomic Sequencing for Virus Discovery and Characterization - Dr. Ben Hause, Kansas State University, from the 2015 North American PRRS Symposium, December 4 - 5, 2015, Chicago, IL, USA.
More presentations at http://www.swinecast.com/2015-north-american-prrs-symposium
2017 molecular profiling_wim_vancriekinge
The document discusses various topics related to molecular profiling and personalized medicine. It describes first generation molecular profiling techniques like gene sequencing, microarrays, and PCR. It then covers next generation sequencing technologies like Roche 454, Illumina, and ABI SOLID. It also discusses second generation techniques for DNA and RNA profiling including exome sequencing, ChIP-seq, and RNA-seq. Finally, it briefly mentions third generation sequencing and epigenetic profiling.
Rare copy-number variants in the development of Inflammatory Bowel Disease
This presentation took place at the Department of Biochemistry and Medical Genetics, the University of Manitoba on 22/Nov/2017. Partial study results were presented to the researchers and students.
Molecular methods in oncology
This document discusses several molecular methods used in oncology, including polymerase chain reaction (PCR), real-time PCR, allele-specific PCR, reverse transcriptase PCR, and fluorescent in situ hybridization (FISH). It describes the basic principles, requirements, steps, advantages, and limitations of these techniques. PCR is used to amplify targeted DNA sequences and detect mutations. Real-time PCR allows simultaneous quantification and detection. FISH involves hybridizing fluorescent probes to detect gene amplifications, deletions, and rearrangements at the chromosome level. These methods are important for cancer diagnosis, prognosis, and monitoring treatment response and minimal residual disease.
Gold Nanoparticle/Interferon Conjugates as Directed Drug Delivery Mechanisms
Gold nanoparticle/interferon conjugates were created as a novel targeted drug delivery mechanism for pancreatic cancer. Interferons IFN-α and IFN-β were conjugated to gold nanoparticles via PEGylation to stabilize the proteins. The conjugates were introduced to MIA PaCa-2 pancreatic cancer cell cultures. UV-Vis spectrometry and zeta potential analysis confirmed the successful creation and high stability of the 20nm GNP/interferon conjugates. A TUNEL assay showed the conjugates induced significant apoptosis in the cancer cells after 48 hours, while free interferons caused less cell death. This targeted delivery mechanism could provide a more effective treatment option for pancreatic cancer with less side effects than chemotherapy and radiation.
Sigma xi presentation
Gold nanoparticle/interferon conjugates were created as a targeted drug delivery mechanism for pancreatic cancer. Interferons IFN-α and IFN-β were conjugated to gold nanoparticles via PEGylation to stabilize the proteins. The conjugates were introduced to MIA PaCa-2 pancreatic cancer cells. UV-Vis spectrometry and zeta potential analysis confirmed the successful creation of physiologically suitable conjugates around 20nm in size with good stability. A TUNEL assay showed the conjugates induced significant apoptosis in cancer cells by 48 hours, while free interferons caused less cell death due to degradation. This novel targeted drug delivery system could provide a more effective treatment option for pancreatic cancer.
Using NGS to detect CNVs in familial hypercholesterolemia
Familial hypercholesterolemia (FH) is a heritable condition of severely elevated LDL cholesterol, characterized by premature atherosclerotic cardiovascular disease. FH affects an estimated 1 in 250 individuals worldwide, and is considered to be the most frequent monogenic disorder encountered in clinical practice. Although FH has multiple genetic etiologies, the large majority of defined cases result from autosomal codominant mutations in the LDL receptor gene (LDLR).
In providing a molecular diagnosis for FH, the current procedure often includes targeted next-generation sequencing (NGS) panels for the detection of small-scale DNA variants, followed by multiplex ligation-dependent probe amplification (MLPA) in LDLR for the detection of whole-exon copy number variants (CNVs). The latter is essential as ~10% of FH cases are attributed to CNVs in LDLR; accounting for them decreases false-negative findings. Here, we have determined the potential of replacing MLPA with bioinformatic analysis (VarSeq) applied to NGS data, which uses depth of coverage analysis as its principal method to identify whole-exon CNV events. In analysis of 388 FH patient samples, there was 100% concordance in LDLR CNV detection between these two methods: 38 reported CNVs identified by MLPA were also successfully detected by NGS + VarSeq, while 350 samples negative for CNVs by MLPA were also negative by NGS + VarSeq. This result suggests that MLPA is dispensable, significantly reducing costs, resources, and analysis time associated with the routine diagnostic screening for FH, while promoting more widespread assessment of this important class of mutations across diagnostic laboratories.
Using NGS to detect CNVs in familial hypercholesterolemia
Familial hypercholesterolemia (FH) is a heritable condition of severely elevated LDL cholesterol, characterized by premature atherosclerotic cardiovascular disease. FH affects an estimated 1 in 250 individuals worldwide, and is considered to be the most frequent monogenic disorder encountered in clinical practice. Although FH has multiple genetic etiologies, the large majority of defined cases result from autosomal codominant mutations in the LDL receptor gene (LDLR).
In providing a molecular diagnosis for FH, the current procedure often includes targeted next-generation sequencing (NGS) panels for the detection of small-scale DNA variants, followed by multiplex ligation-dependent probe amplification (MLPA) in LDLR for the detection of whole-exon copy number variants (CNVs). The latter is essential as ~10% of FH cases are attributed to CNVs in LDLR; accounting for them decreases false-negative findings. Here, we have determined the potential of replacing MLPA with bioinformatic analysis (VarSeq) applied to NGS data, which uses depth of coverage analysis as its principal method to identify whole-exon CNV events. In analysis of 388 FH patient samples, there was 100% concordance in LDLR CNV detection between these two methods: 38 reported CNVs identified by MLPA were also successfully detected by NGS + VarSeq, while 350 samples negative for CNVs by MLPA were also negative by NGS + VarSeq. This result suggests that MLPA is dispensable, significantly reducing costs, resources, and analysis time associated with the routine diagnostic screening for FH, while promoting more widespread assessment of this important class of mutations across diagnostic laboratories.
Sigma xi presentation
Gold nanoparticle/interferon conjugates were created as a novel targeted drug delivery mechanism for pancreatic cancer. Interferons IFN-α and IFN-β were conjugated to gold nanoparticles via PEGylation to stabilize the proteins. The conjugates were introduced to MIA PaCa-2 pancreatic cancer cell cultures. UV-Vis spectrometry and zeta potential analysis confirmed the successful creation and high stability of the 20nm GNP/interferon conjugates. A TUNEL assay showed the conjugates induced significant apoptosis in the cancer cells after 48 hours, while free interferons caused less cell death. This novel drug delivery system utilizes the cell-specific binding of interferons to selectively target and destroy pancreatic cancer cells through
2007. stephen chanock. technologic issues in gwas and follow up studies
This document discusses technologic issues related to genome-wide association studies (GWAS) and follow-up studies. It describes different types of polymorphisms like single nucleotide polymorphisms (SNPs) and copy number variations that can be studied. It discusses strategies for SNP selection and linkage disequilibrium. Different genotyping technologies are also reviewed, along with quality control measures for genotype calls and participant recruitment. Specific results from GWAS of prostate and breast cancer conducted by the Cancer Genetic Markers of Susceptibility (CGEMS) project are summarized.
Population Structure & Genetic Improvement in Livestock
The genetic improvement of livestock has been a hot topic for almost a century, bringing together researchers, industry, and producers to work towards a common goal. Many countries currently employ extensive genetic selection programs in their cattle with pigs, sheep, and chicken close behind.
In this webcast, Heather J. Huson, Ph.D. from Cornell University will focus on population dynamics and trait association in cattle and goats using high density SNP datasets. Population structure plays a critical role in understanding the relatedness among livestock, ancestral origins of traits, and identification of unique sub-populations or breeds for production improvement and conservation. This also lays the foundation for understanding and improving species such as the goat which is a vital food source in developing countries but has little recorded production or health data.
Understanding population structure is essential for designing complex trait association studies such as those related to production and health characteristics. Here, Huson shows examples of her lab's investigation into population structure in both goats and cattle to identify distinct groups and study traits such as thermo-tolerance.
Analytical Validation of the Oncomine™ Comprehensive Assay v3 with FFPE and C...
Analytical Validation of the Oncomine™ Comprehensive Assay v3 with FFPE and C...Thermo Fisher Scientific
The document summarizes an analytical validation of the Oncomine Comprehensive Assay v3 (OCAv3) targeted next-generation sequencing panel performed in a CLIA-certified laboratory. The validation assessed analytical sensitivity, specificity, accuracy, and precision using formalin-fixed paraffin-embedded tumor samples and cell lines. Results showed the assay met performance thresholds of 90% or higher for detecting single nucleotide variants, insertions/deletions, copy number variants, and gene fusions across a wide range of variants. Over 2,500 clinical samples were subsequently sequenced with the assay maintaining a 95% success rate and average turnaround time of 10 days.Fibromatosis
The document discusses the diagnosis of desmoid fibromatosis (DF). It states that the diagnosis is usually made through a combination of history, physical examination, imaging, and biopsy. On imaging, DF typically appears as a solid mass with variable echogenicity on ultrasound. CT and MRI are more accurate and can show the extent of infiltration. MRI is the best imaging modality, demonstrating low signal on T1-weighted imaging and variable signal on T2-weighted imaging depending on the collagen content. Biopsy is needed to confirm the diagnosis, as imaging features are non-specific. The diagnosis is usually made in young adults presenting with a painless mass or lump. Location depends on the type of DF, which can be
Cignal webina
The document describes Cignal Reporter Assays from SABiosciences that enable simple and robust analysis of signal transduction pathways. The assays utilize dual-luciferase reporters containing optimized transcriptional regulatory elements and luciferase variants to provide high sensitivity and low variability. The assays allow monitoring of 29 pathways and are available in different formats for various cell types and applications like RNAi and small molecule screening.
Molecular profiling of breast cancer
Molecular profiling of breast cancer can classify tumor types, identify appropriate therapeutic targets, determine prognosis, and predict treatment response. Techniques include immunohistochemistry, fluorescence in situ hybridization, reverse transcription PCR, microarrays, and next generation sequencing to analyze protein expression, gene copy number, mutations, and gene expression levels. Breast cancers are classified into intrinsic subtypes including luminal A/B, HER2-enriched, basal-like, and claudin-low based on distinct gene expression patterns that predict clinical behavior and response to therapy.
Similar to Utilization of NGS data and genomic selection to rescue an endangered and heritage sheep breed from Florida (20)
Clinical Applications of Next Generation Sequencing
Clinical Applications of Next Generation Sequencing
Genetic variation in individual & population, polymorphism, Hardy-Weinberg Eq...
Genetic variation in individual & population, polymorphism, Hardy-Weinberg Eq...
Copy number variants in the development of psychiatric comorbidity in the Inf...
Copy number variants in the development of psychiatric comorbidity in the Inf...
Stephanie Allen-Diagnóstico prenatal no invasivo y diagnóstico genético repro...
Stephanie Allen-Diagnóstico prenatal no invasivo y diagnóstico genético repro...
Dr. Ben Hause - Metagenomic Sequencing for Virus Discovery and Characterization
Dr. Ben Hause - Metagenomic Sequencing for Virus Discovery and Characterization
Rare copy-number variants in the development of Inflammatory Bowel Disease
Rare copy-number variants in the development of Inflammatory Bowel Disease
Gold Nanoparticle/Interferon Conjugates as Directed Drug Delivery Mechanisms
Gold Nanoparticle/Interferon Conjugates as Directed Drug Delivery Mechanisms
Using NGS to detect CNVs in familial hypercholesterolemia
Using NGS to detect CNVs in familial hypercholesterolemia
Using NGS to detect CNVs in familial hypercholesterolemia
Using NGS to detect CNVs in familial hypercholesterolemia
2007. stephen chanock. technologic issues in gwas and follow up studies
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Introducing VarSeq Dx as a Medical Device in the European Union
A transition period regarding in vitro medical device (IVD) regulation in the European Union (EU) is upon us. The former IVDD regulations are phasing out and IVDR 2017/746 has already taken its place as the acting regulation for IVD manufacturers but also lab developed tests (LDTs) and health institutions. In our upcoming webcast we will talk about the roles and significance of IVDR and ISO 13485 certification for clinical labs and for Golden Helix as a medical device manufacturer.
Join us as we will introduce VarSeq 2.6.1 complete with Dx Mode, which offers the use of VarSeq as CE marked medical device. Even more we will also present strategies to facilitate the transition of Golden Helix customers to operate in accordance with IVDR.
VarSeq 2.6.0: Advancing Pharmacogenomics and Genomic Analysis
In the rapidly evolving field of genomic analysis, staying current with the latest research, data sources, and test advancements is crucial. In this webinar, we review how VarSeq addresses the needs to stay on top of the latest with the release of VarSeq 2.6.0.
This release features an exome-optimized workflow for LOH and CNV calling as well as the introduction of VSPGx to produce pharmacogenomic reports for gene panels as well as exomes and genomes. With the recent release of gnomAD v4, we have had many requests for the integration of this large update to the most population frequency source. With VarSeq 2.6.0, the latest version of gnomAD has been integrated into VSClinical and the updated tracks spans beyond variants to cover CNVs and gene scores to update all your workflows to the latest data.
In this webcast, we will cover.
Improved VS-CNV performance and updated exome analysis workflows.
Pharmacogenomics in action: Utilizing VSPGx for exome and genome assessments.
gnomAD v4 in practice: Updated automated and manual variant interpretation workflows.
Join us for an insightful session on the latest VarSeq 2.6.0 features, bringing you the most up-to-date data and workflows for your genomic analysis.
Introducing VSPGx: Pharmacogenomics Testing in VarSeq
Inter-individual variability in drug response poses a significant challenge for clinicians, with much of this variability resulting from inherited genetic differences. While the field of pharmacogenomics (PGx) can provide powerful insights into how genomic factors affect drug response, the implementation of PGx testing in the clinic is hampered by the difficulty of translating genetic test results into actionable recommendations. In this webcast, we will discuss VarSeq’s new PGx testing capabilities, including the ability to identify actionable pharmacogenomic diplotypes and generate clinical reports.
In this webcast you will learn:
-How to identify pharmacogenomic diplotypes and drug recommendations from NGS data.
-How to incorporate externally called CNVs and SVs into your PGx annotations.
-How to generate customizable PGx reports from these annotations.
Analyzing Performance of the Twist Exome with CNV Backbone at Various Probe D...
Clinical Whole Exome Sequencing (WES) offers a high diagnostic yield test by detecting pathogenic variants in all coding genes of the human genome. WES is poised to consolidate multiple genetic tests by accurately identifying Copy Number Variation (CNV) events, typically necessitating microarray analyses. However, standard commercial exome kits are limited to targeting exon coding regions, leaving significant gaps in coverage between genes which could hinder comprehensive CNV detection.
Addressing the need for comprehensive coverage, Twist Bioscience has developed an enhanced Twist Exome 2.0 Plus Comprehensive Exome Spike-in capture panel with added "backbone" probes. These probes target common SNPs polymorphic in multiple populations and are evenly distributed in the intergenic and intronic regions, with three varying densities at 25kb, 50kb, and 100kb intervals. In this webcast, we discuss the combined efficacy of the backbone-probe enhanced exome capture kit and VS-CNV in identifying known CNVs using the Coriell CNVPANEL01 reference set.
This webcast reviews:
-The sensitivity rate for the detection of known CNV events at all three probe densities.
-The impact of best-practice quality metrics and filters on sensitivity.
-How VarSeq’s CNV annotation capabilities can be leveraged to identify likely pathogenic CNVs.
-The interpretation of clinically relevant CNVs using VSClinical.
From Panels to Genomes with VarSeq: The Complete Tertiary Platform for Short ...
From gene panels to whole genome, from short to long-read sequencing, the VarSeq suite is the solution for NGS analysis and reporting in a modern clinical lab. VarSeq handles the spectrum of variant types (SNV, Indel, CNV, Fusions) and provides automated classification and reporting capabilities following the ACMG and AMP guidelines. With our new PacBio partnership, we are more adaptable than ever with creating a spectrum of custom workflows to suit our unique user needs.
This webcast will review:
-Data analysis scaling from Gene Panel to Genome analysis with VarSeq and VSWarehouse.
-Analysis and annotation of SNVs, Indels, CNVs, and fusions.
-A close look at a PacBio long-read trio analysis.
Come join us for this showcase in modern VarSeq analysis capabilities.
Enhance Genomic Research with Polygenic Risk Score Calculations in SVS
Golden Helix’s SNP & Variation Suite (SVS) has been used by researchers around the world to do trait analysis and association testing on large cohorts of samples in both humans and other species. The latest SVS release introduces a significant leap in capabilities, with a focus on advanced Polygenic Risk Score (PRS) calculations. PRS has become a fundamental tool in genomic research, enabling the identification of correlations between genotypic variants and phenotypes across large populations.
This enhancement is particularly relevant for researchers working on large cohorts and meta-analysis. Please join us as we explore:
-SVS Workflow Review: A review of the extensive capabilities of SVS to meaningful insights from large cohorts and association test result datasets
-Computing Polygenic Risk Scores: An overview of the PRS capabilities in SVS, including Clumping and Thresholding and creation of multiple PRS models
-Evaluating and Applying PRS: Evaluating PRS models in-sample and out-of-sample and applying PRS models to perform trait prediction
-Future Implications: Brief exploration of how these advancements in SVS could influence future genomic research.
This webcast will explore how SVS facilitates the creation of multiple PRS models from large-scale genomic data, such as those obtained from extensive cohort studies or comprehensive meta-analyses. Join us to discover how these latest updates in SVS are supporting large-scale genomic research.
VarSeq 2.5.0: VSClinical AMP Workflow from the User Perspective
With our recent launch of VarSeq 2.5.0, our ability to expedite somatic analysis for NGS labs is more accessible than ever before. Our recent webcasts have shown our range of updates, including our new oncogenicity classifier and carrier status workflows:
Identifying Oncogenic Variants in VarSeq
VarSeq 2.5.0: Empowering Family Planning through Carrier Screening Analysis
In this user perspective webcast, we will highlight how the combination of our new oncogenicity classifier and the updates to our CancerKB database streamline the interpretation of oncogenic variants. In addition, as NGS labs progress from gene panels to WES analysis for ideal genomic signature generation, we will demonstrate how a VarSeq somatic workflow can scale with these increased scopes of data analysis with ease.
Our user perspective webcast will cover:
Application of virtual panels to WES tumor/normal workflows.
Use of the oncogenicity classifier to streamline filter chains.
Updates to our CancerKB database to include the CancerKB gene track.
Including parallel germline secondary findings for the whole NGS workflow.
VarSeq 2.5.0: Empowering Family Planning through Carrier Screening Analysis
Golden Helix introduced new capabilities in VarSeq 2.5.0 to support carrier screening analysis through NGS data. Key features include the ability to import partnered samples, detect shared carrier variants between samples at the gene level using a couples carrier screening workflow, and generate clinical reports that calculate reproductive risks and include variant interpretations. The software is designed to scale from gene panels to whole exomes/genomes. A demo showed how these new features streamline the carrier screening analysis process from data import and filtering to clinical reporting.
Identifying Oncogenic Variants in VarSeq
The interpretation of somatic variants can be a challenging process. While AMP Guidelines provide detailed rules for accessing the clinical evidence associated with a specific variation, they do not specify criteria for determining if a variant is likely to be a driver mutation, which generates functional changes that enhance tumor cell proliferation. In this webcast, we will discuss a new VarSeq algorithm for estimating the oncogenicity of a variant. This will include a deep dive into our oncogenicity scoring system and a discussion of the various criteria used to distinguish driver mutations from benign variations and variants of uncertain significance.
What you will learn in this webcast:
-How to use the scoring algorithm to identify variants with evidence of oncogenicity
-Which criteria are used to assess a variant's oncogenicity
-How to evaluate the oncogenicity of a variant in VSClinical
Best Practices for Validating a Next-Gen Sequencing Workflow
Validating an NGS workflow is an iterative process that begins with collaboration with personnel and planning protocols for the entire workflow from sample preparation, sequencing and variant calling, all the way to data analysis and reporting. At Golden Helix, while we do not provide pre-validated black-box workflows, we provide our customers with support to validate workflows in a transparent manner, and assist them in reaching production deadlines. This webcast will be led by members of our Field Application Scientist team, and we will explore some of the best practices for NGS workflow validation that we have observed and helped to implement based on real-world examples from our customer base. Key topics for discussion will include:
Sample preparation and collection of adequate case/control data
Designing a robust workflow with special considerations for single versus family analyses and phenotypic considerations
Generating the desired output for clinical or other reports
Real world NGS workflow validation strategies
Tune in for tips and strategies that you can deploy when designing and validating your NGS workflow.
2023 Innovation Awards Winner, Dr. Muthukumaran
Expanded carrier screening in an infertile/affected Couple for determining carrier status for genetic mutations - VarSeq Couple Carrier Workflow
VarSeq 2.4.0: VSClinical ACMG Workflow from the User Perspective
The document provides information about Golden Helix's VarSeq 2.4.0 software and its VSClinical ACMG workflow module. It summarizes a presentation given on the topic, including details about Golden Helix as a company, the content covered in the presentation, and examples that will be demonstrated including analysis of variants, copy number variants, and structural variants from PacBio long read sequencing data using VSClinical.
VarSeq 2.4.0: Structural Variants and Advanced Automation in VSClinical ACMG
Mendelian disorders can be caused by various classes of genetic mutations, from small variants to CNVs and even Structural Variants. With the introduction of VarSeq 2.4.0, we are excited to unveil the latest advancements in VSClinical ACMG, focusing on the integration of Structural Variants and the enhanced automation capabilities that streamline your analysis process.
Join us in this webcast as we dive into the following topics:
Integration of Structural Variants: Learn how VarSeq 2.4.0 enables you to import and incorporate Structural Variants into your VSClinical ACMG evaluations and reports, providing a comprehensive understanding of the genetic landscape.
Advanced Automation in the ACMG Interface: Discover how evaluation scripts can be employed to automate the VSClinical ACMG interface, allowing you to perform custom actions or eliminate manual steps, thus increasing efficiency and reducing the risk of errors.
End-to-End Automation: Explore how VSPipeline can fully automate your analysis process, from raw VCF to report, ensuring a streamlined and consistent workflow that saves time and resources.
Harnessing the Power of VSClinical: Gain insights into how VarSeq 2.4.0 empowers you to tackle complex genomic data, enabling faster and more accurate identification of Mendelian disorders and facilitating personalized patient care.
With the advanced capabilities of VarSeq 2.4.0 and VSClinical, you can now unlock a new level of precision and efficiency in diagnosing Mendelian disorders. This webcast will showcase the latest innovations in variant interpretation and automation, exemplifying why the VarSeq Clinical Suite is the premier NGS analysis platform for germline and cancer testing.
The Wide Spectrum of Next-Generation Sequencing Assays with VarSeq
There is a strong motivation for labs to bring most, if not all, of their next-gen sequencing pipeline in-house. This is especially relevant for clinical applications where there is a need to validate any routine diagnostics when seeking to provide genetic results to patients. The entirety of the NGS pipeline is highly automatable and comprised of multiple stages but from the geneticist's point of view, the tertiary stage requires the lengthiest review. This stage is where the geneticist sifts through the massive collection of genetic variants to find and report on those most relevant to the patient or population. Unfortunately, the tertiary stage can be a fairly sophisticated process and there aren’t many tools on the market that handle it comprehensively and simply. Many of the tools that are available may have severe limitations on the scale of genomic data they can process or limitations on the types of NGS assays that can be designed. Moreover, their license model may be on an individual sample basis and present cost-benefit hurdles for the user, especially when sample load will inevitably increase. Fortunately, none of these assay or cost-based issues are relevant with Golden Helix products.
The goal of this webcast is to expose our viewers to the versatility that GHI VarSeq provides when constructing your dream NGS assay. This demonstration will provide examples of germline and somatic workflows for both single and multi-sample analysis for a variety of different disorders. Please join us and learn more about the analytical possibilities you can achieve when using the VarSeq software.
Prenatal Genetic Screening with VarSeq
Our past webcast explored the current approaches for screening and diagnosis of genetic disorders in prenatal testing. While the methods available at the time were robust, they were severely limited, creating a need for a higher diagnostic yield and more efficient analysis for a wider range of genetic tests. The solution proposed was to improve and simplify prenatal screening and diagnosis with whole exome sequencing (WES).
During that webcast, we highlighted the advantages of WES over traditional methods such as karyotyping and chromosomal microarray, including improved accuracy, granularity, and cost-effectiveness. We also emphasized the potential of WES to expand diagnosis for many other adverse maternal-fetal complications beyond the large aneuploidy events previously covered. However, there was still an intimidation factor when it came to the massive data output from the exome. Fortunately, Golden Helix provided the necessary tools to build and standardize these genetic assays, simplifying the analytical process while leveraging increased diagnostic output. We explored our VarSeq software to demonstrate some example workflows of cases positive for Trisomy 21, an exon loss in DMD related to Duchenne Muscular Dystrophy, and detection of a single base change resulting in a LOF variant in RUNX1 relevant to hereditary leukemia.
Our goal was to expose our viewers to the methods of conquering this vast NGS-based data and play a role in dissolving any feeling of intimidation. Overall, exome sequencing has the potential to vastly improve diagnostic outcomes and widen discoveries in the research related to prenatal testing, and Golden Helix products are designed to facilitate this process.
Automated FASTQ to Reports with VarSeq Suite: A fast, flexible solution
NGS tests in the clinic cover more use cases than ever and are increasingly complex to implement. This leads to an increase in time to validate and bring tests to production, impacting a lab’s ability to be economically viable and serve the needs of patients. Core to the complexity is the expansion of tests to include multiple types of biomarkers and variants, including CNVs, gene fusions, and genomic signatures. The bioinformatics demands of these pipelines require powerful tools with built-in capabilities to handle the diverse needs of modern NGS tests and to integrate and automate the disparate steps leading to clinical insight.
Join us in this webinar as we explore the VarSeq suites’ capabilities as a fast, modular, and highly configurable solution for variant analysis and interpretation. We will cover:
The bioinformatic diversity of comprehensive genetic tests with NGS
Automation of FASTQ to clinical reports without losing control over the results of a test
Leverage built-in and custom automation capabilities in the VSClinical cancer guideline workflow to reduce work and improve accuracy
Reporting the relevant diagnostic and therapeutic findings for a patient based on the raw genomic data of modern NGS tests requires both human experience and advanced analysis software. We hope you can join us as we unpack how automation is a critical part of implementing NGS tests and furthering the application of precision medicine.
Maximizing the Benefits of Comprehensive Genomic Testing in Cancer Care with ...
Comprehensive genomic testing via next generation sequencing (NGS) is being increasingly adapted as part of cancer care in conjunction with molecular and immunohistochemical tests. Comprehensive genomic profiling potentially expands the number of targeted therapies that are available to patients, improves patient diagnosis and prognosis, and increases the number of clinical trials that are relevant to patients. However, with these advancements come challenges such as gaps in expertise resulting in inadequate efforts to interpret genomic data accurately and efficiently, poorly coordinated efforts to implement precision care, patients being diagnosed and treated despite inadequate access to relevant information and subsequent lack of patient exposure to all available treatment options.
Golden Helix CancerKB v2.0 provides a means of closing the gap, whether you're a beginner who is trying to capture the vast amount of knowledge in the cancer field or an expert who has high sample volume AND needs to keep up with the ever-evolving knowledge of Tier II and III variants. In this webcast, we will discuss and apply Golden Helix CancerKB in the context of cancer precision medicine. Golden Helix CancerKB is systematically curated and reviewed by experts in the field and contains information about cancer genes, biomarkers, and treatments generated from several trusted cancer resources. With VarSeq 2.3.0’s added support for comprehensive cancer genomic profiling tests, Golden Helix CancerKB has expanded to include interpretations for genomic signatures, combination biomarkers, and more investigational (tier II) biomarkers, among several other additions that will be discussed. With the Golden Helix CancerKB database, users will experience a streamlined automatic matching of biomarkers to available drugs and trials which ultimately saves users massive amounts of time and effort while reducing the possibility for errors.
A User’s Perspective: Somatic Variant Analysis in VarSeq 2.3.0
VarSeq 2.3.0 facilitates the evaluation of a multitude of somatic genomic variations with a more refined user interface to streamline variant evaluation. Our recent webcasts have shown the full range of these newly developed upgrades:
VarSeq 2.3.0: Supporting the Full Spectrum of Genomic Variation
VarSeq 2.3.0: New TSO-500 and Genomic Signature Support in VSClinical AMP
Now, we are showing it all in action from the user’s perspective. This webcast will provide a comprehensive demonstration of performing somatic variation analysis and reporting. We will review how to use workflow automation to expedite the NGS project creation process and report rendering. We will also demonstrate the streamlined capture of knowledge during variant evaluation by leveraging our clinical expert-curated interpretations with the Golden Helix Cancer Knowledge Base (CancerKB).
We hope you will join us to see VarSeq 2.3.0 from a user’s perspective, covering:
-Somatic variant workflows: necessary algorithms and filtering strategies
-Import of all relevant biomarker and genomic signatures data from TSO-500
-Review content and value of clinically curated interpretations and treatments with CancerKB
-Interpretation of structural variants in the VSClinical AMP Guidelines workflow
-Workflow automation with VSPipeline
VarSeq 2.3.0: Supporting the Full Spectrum of Genomic Variation
Next Generation Sequencing allows for the detection of a wide variety of genomic alterations. This includes small mutations, copy number variants and complex rearrangements. However, it can be difficult to annotate, filter, and interpret these alterations.
As part of our VarSeq 2.3.0 release, we have greatly simplified this process by allowing you to import, annotate, and filter mutations across all spectrums of genomic variation. This supports concurrent importation of small variants and CNVs as well as complex rearrangements. This release also includes strong support for structural variant annotation, filtering, and interpretation, including structural variant effect prediction. After filtering is complete, any clinically relevant structural variants can be interpreted with the VSClinical AMP Guidelines workflow and included in the final clinical report.
Come join us for this webcast to discuss VarSeq’s enhanced import and annotation capabilities, including:
Concurrent importation of variants CNVs and complex rearrangements
Improved multi-threaded import which dramatically speeds up the importation of large VCFs
Annotation of structural variants and prediction of effect
Interpretation of structural variants in the VSClinical AMP Guidelines workflow
Support for visualization and use of CRAM files as input for computing coverage statistics
VarSeq 2.3.0: New TSO-500 and Genomic Signature Support in VSClinical AMP
Precision medicine for cancer is rapidly accelerating because of the development and approval of targeted molecular therapies. These therapies require new genomic biomarkers as an indication for use, and require evaluating additional mutation types that are available in comprehensive genomic profiling assays as well as the small variants detected by Next-Generation Sequencing gene panels.
We are excited to announce VarSeq 2.3.0 which will update the VSClinical AMP workflow to meet the growing needs of labs conducting comprehensive genomic profiling (CGP) of tumors. This includes built-in support for the Illumina TruSight Oncology 500 (TSO-500) kit as well as similar kits from other vendors. The VSClinical AMP workflow has also gained native support for the bioinformatic outputs of CGP kits. Join us to learn about comprehensive genomic profiling in cancer, specifically:
Evaluation and clinical reporting of genomic signatures such as Microsatellite (MSI), Tumor mutation burden (TMB), PD-L1, Homologous recombination deficiency (HRD) statuses, and more.
Built-in TSO-500 import and expandable import capabilities for new genomic data types through the new advanced workflow scripting system.
Golden Helix CancerKB updates with report-ready genomic-signature interpretations written for approved therapies as well as gene interpretations for all 500 genes of the TSO-500 panel. In addition, CancerKB scopes have been extended to reference multiple relevant biomarkers in a single interpretation, capture approved therapies at the tumor type level, and include interpretations for clinically relevant negative findings.
Expanded clinical trial support to include international trials and the ability to search within proximity of European postal codes. VSClinical is accessing all active studies in AACT/ClinicalTrials.gov wherein users can search and select trials based on relevant drugs, biomarkers, and the geographic distance to the patient or testing site.
VarSeq 2.3.0 will deliver powerful capabilities for genomic profiling in cancer, enabling a new level of personalized and effective care for your patients. We look forward to demonstrating these updates and Golden Helix’s continued innovation making the VarSeq Clinical Suite the NGS analysis platform of choice for germline and cancer testing.
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Introducing VarSeq Dx as a Medical Device in the European Union
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VarSeq 2.6.0: Advancing Pharmacogenomics and Genomic Analysis
VarSeq 2.6.0: Advancing Pharmacogenomics and Genomic Analysis
Introducing VSPGx: Pharmacogenomics Testing in VarSeq
Introducing VSPGx: Pharmacogenomics Testing in VarSeq
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Enhance Genomic Research with Polygenic Risk Score Calculations in SVS
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VarSeq 2.5.0: VSClinical AMP Workflow from the User Perspective
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VarSeq 2.5.0: Empowering Family Planning through Carrier Screening Analysis
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Best Practices for Validating a Next-Gen Sequencing Workflow
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VarSeq 2.4.0: VSClinical ACMG Workflow from the User Perspective
VarSeq 2.4.0: VSClinical ACMG Workflow from the User Perspective
VarSeq 2.4.0: Structural Variants and Advanced Automation in VSClinical ACMG
VarSeq 2.4.0: Structural Variants and Advanced Automation in VSClinical ACMG
The Wide Spectrum of Next-Generation Sequencing Assays with VarSeq
The Wide Spectrum of Next-Generation Sequencing Assays with VarSeq
Automated FASTQ to Reports with VarSeq Suite: A fast, flexible solution
Automated FASTQ to Reports with VarSeq Suite: A fast, flexible solution
Maximizing the Benefits of Comprehensive Genomic Testing in Cancer Care with ...
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A User’s Perspective: Somatic Variant Analysis in VarSeq 2.3.0
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VarSeq 2.3.0: Supporting the Full Spectrum of Genomic Variation
VarSeq 2.3.0: Supporting the Full Spectrum of Genomic Variation
VarSeq 2.3.0: New TSO-500 and Genomic Signature Support in VSClinical AMP
VarSeq 2.3.0: New TSO-500 and Genomic Signature Support in VSClinical AMP
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Utilization of NGS data and genomic selection to rescue an endangered and heritage sheep breed from Florida
- 2. Outline • Introduction • FL Cracker sheep • Parasite Resistance • SNPs • Results • CNVs • Future Work
- 3. Parasite Resistance: ability to limit the establishment and fecundity of the parasite Objectives: identify DNA variants controlling parasite resistance in Florida Cracker sheep and develop tools for selective breeding What is parasite resistance?
- 4. Gastrointestinal nematode infections Dead 50,331 sheep 86,701 goats Anthelmintic resistance Southern US: high disease incidence Gastrointestinal Nematodes: major threat to small ruminant operations in the Southeast • Haemonchus contortus: the most pathogenic parasite
- 5. Potential Solution: Selection for parasite resistance (Artificial selective breeding) Resistance Limits the establishment (reduce burden) and fecundity of parasite - Innate immune response - Acquired immunity Tolerance/Resilience increase infectivity of environment and determination of status requires accurate data on the level of parasite infection Potential Solution: selection for parasite resistance
- 6. Selection for improved parasite resistance will result in a general reduction in parasite burden which in turn, may lead to reduced losses in production and meat quality in FCS vs Potential Solution: selection for parasite resistance RR SS
- 7. Phenotypic markers used to detect parasite resistance Parasitological measures FEC FAMACHA Hematocrit IgA Eosinophilia IgE IgG Immunological measures
- 8. Florida Cracker Sheep: a heritage sheep breed from Florida
- 9. Florida Cracker Sheep: naturally adapted to hot and humid conditions • The Florida Cracker is one of the oldest breeds of sheep in North America • Native and heritage breed from Florida • Adapted to hot and humid conditions like that in Florida • It is an endangered sheep breed under critical conservation priority (< 1,000)
- 10. Spain introduced 400 sheep (Churra) during St. Augustine foundation 1565 1945 Florida Native sheep re-domestication Sheep remained feral 2019 Great health and reproductive behavior Breed domesticated and naturally adapted to tropical environmental conditions of Florida Re-domestication Florida Cracker Sheep: a heritage sheep breed from the Southeast
- 11. Florida Cracker sheep population FAIRMEADOW SHEEP FARM Location: Ocala, FL • Florida Cracker sheep from commercial farm located in Ocala, FL (n = 380; 3 and 5 months old) • Phenotypes collected from 2018 -2020 • Animals were dewormed before the study. After confirmation of FEC reduction, animals were naturally infected with H. contortus.
- 12. Phenotype collection H. contortus FEC Hematocrit Body condition score & weight FAMACHA score
- 13. Objective • Identify DNA variants (SNPs, CNVs) associated with FEC, FAMACHA, hematocrit level (PCV), and average daily gain
- 14. Genotyping and Quality control of SNP data • DNA extracted from blood samples • Genotyped with GGP Ovine 50k • Call rate < 95%, MAF ≤ 0.05, LD pruning • Initial number of SNPs before quality control: 45,205 SNPs • Final number of SNPs after quality control: 32,500 SNPs
- 15. Genome Wide Association Analysis with SNP data
- 16. Results: SNPs with additive and non-additive effects associated with FEC
- 17. Results: SNPs with additive effects associated with FEC • Antigen WC1.1 gene encodes a receptor that is uniquely expressed on γδ- T cells • Previous studies with resistant Canaria Hair sheep infected with H. contortus, have suggested that immune response modulated by WC1+ γδ- T cells is the primary mechanism used for regulation of parasite growth and fecundity (González et al., 2011; Guo et al., 2016; Hernández et al., 2017)
- 18. Results: SNPs with additive and non-additive effects associated with FAMACHA and ADG
- 19. Results: SNPs with additive and non-additive effects associated with PCV
- 20. Results: SNPs with additive and non-additive effects associated with PCV • For PCV, the SNP with additive genetic effects was located close to STC1 gene whereas the SNP with recessive genetic effects was located downstream of TGFB2 gene • STC1 controls calcium transport in intestinal epithelia and negatively regulates TRP channels • Calcium entries TRP channels for agonist induction of NFKB activation which leads to IL1B production and activation of inflammatory response
- 21. Quality Control for CNV detection • Intensity values from 45,205 SNPs were available for quality control procedures using SVS Golden Helix • Principal component analysis (PCA) was applied to detect and correct for the presence of batch effects and to correct the LRR values
- 22. CNV Segmentation • The copy number analysis module (CNAM) for optimal segmenting was used to identify CNVs using the univariate method (default options) • This analysis considers only one sample at a time and detects rare or large CNVs • Univariate outlier removal, maximum number of 10 segments per 20,000 markers, a minimum of 1 marker per segment, and 2,000 permutations per pair with a p-value cutoff of 0.05 were used • Individuals with a waviness factor (WF) - 0.05>WF>0.05 were also excluded
- 23. Genome Wide Association Analysis with CNVs
- 24. Results: CNVs associated with FEC
- 25. Results: CNVs associated with FEC • A significant deletion CNV in chromosome 21 was associated with FEC • This deletion was located in intron 2 of RAB3IL gene and overlapped a QTL associated with changes in eosinophil number • This deletion was also located close to a QTL associated with FEC in sheep • Intronic polymorphisms in RABIL3 are associated with Chron’s disease (affects gastrointestinal tract) • Symptoms: diarrhea, anemia, weight loss, abdominal pain, blood in feces, etc
- 26. Results: CNVs associated with FEC • A significant deletion CNV in chromosome 21 was associated with FEC • This deletion was located in intron 2 of RAB3IL gene and overlapped a QTL associated with changes in eosinophil number • This deletion was also located close to a QTL associated with FEC in sheep • Intronic polymorphisms in RABIL3 are associated with Chron’s disease (affects gastrointestinal tract) • Symptoms: diarrhea, anemia, weight loss, abdominal pain, blood in feces, etc
- 27. Conclusions • Significant SNPs in chromosome 1, 2, 3, 6, 8, 10, 11,12, 13 and 21 and a deletion CNV in chromosome 21 may contribute to parasite resistance
- 28. Future Work Utilize SVS to: • Validate identified SNPs and CNVs in FCS • Estimate Runs of Homozygosity to identify the genomic footprint of inbreeding in FCS • Perform Genomic Selection for parasite resistance in FCS
- 29. Acknowledgments • Dr. Owen Rae (UF) • Brittany Diehl (UF) • Dr. Ibukun Ogunade (WVU) • Dr. Thomas Terrill (FVSU) • Dr. Ignacy Misztal (UGA) • Dr. Andres Pech-Cervantes (FVSU)
- 30. Acknowledgments - This research was partially supported by Sustainable Agriculture Research and Education, U.S. Department of Agriculture, under award No. GS17-173. - We thank Neogene for free genotyping.
- 31. QUESTIONS?