As Chief of Scientific Intelligence at the John Wayne Cancer Institute, Dr. Hoon interacts with external academic, industry, and government agencies to develop innovative translational research opportunities. He has coauthored more than 250 peer-reviewed articles and reviews, primarily related to translational molecular oncology of human solid tumors. He has over 25 patents on his studies. As founding Director of the Department of Molecular Oncology, Dr. Hoon continues to pioneer investigations of RNA/genomic/epigenomic biomarkers for diagnostic, prognostic and predictive assessment of residual tumor cells. He also spearheads investigations of circulating DNA/miRNA biomarkers for staging cancer in patients enrolled in phase II/III clinical trials. The Department's focus on biomarker expression in both tissue and body-fluid specimens gives it a uniquely broad scope. Dr. Hoon's team has developed diagnostic tissue biomarkers for molecular staging of sentinel lymph nodes and classification of human solid tumors such as melanoma, breast cancer and gastrointestinal cancer. Dr. Hoon also has pioneered development of blood-based nucleic-acid and tumor-cell biomarkers as prognostic tools. In the last decade he and his team have designed and conducted biomarker companion studies as part of multicenter international clinical trials. On the therapeutic front, Dr. Hoon is examining functional genomic and epigenomic changes as potential targets for development of novel approaches to treat or prevent malignancy. Dr. Hoon and the Department are funded by the National Institutes of Health/National Cancer Institute, the California Breast Cancer Research Program, Susan G. Komen for the Cure, Adelson Melanoma Research Foundation, the United States Department of Defense, and the pharma-biotech industry. Dr. Hoon has served on several review study sections as a permanent member for the National Cancer Institute, and was a founding member of NCI's Cancer Biomarker Study Section. The Department of Molecular Oncology consists of over 20 MD/PhD scientists and research technicians focused on translation molecular oncology. Some of the major ongoing collaborations include: Leiden University Medical Center, Netherlands; Genome Institute Singapore, Biopolis; Broad Institute of MIT and Harvard; Keio University; MD Anderson, and Melanoma Institute Australia. Dr. Hoon has trained more than 60 postdoctoral oncology fellows, who now hold faculty appointments in numerous academic institutions.    

Malignancies caused by so-called Type I chemical and biological carcinogens provide important opportunities studying early events in cancer development, providing essential information for developing future cancer prevention strategies. In Asia, several highly lethal cancers are known to be caused by pathogens, such as stomach cancers (H. pylori), bile duct cancers (liver flukes), and certain lymphoma subtypes (Epstein-Barr Virus). For many of these conditions, treatment options are still highly limited. In this talk, I will describe how genomic analysis of infection-related Asian cancers can provide insights into cellular processes disrupted by these pathogens, and how such data can be used to identify new therapeutic targets.

The next generation sequencing technologies are profoundly influencing our way to study biology. We have previously developed cap-analysis gene expression (CAGE) to simultaneously mRNA/noncoding RNA starting sites and simultaneously detect their expression. Altogether, CAGE achieves comprehensive coverage of transcription starting site and allows to assign newly discovered promoters/5' ends to the rest of the RNA sequence (CAGEscan technology). With these technologies, we can infer the transcriptional networks that regulate gene expression. This technology is being applied to a broad range of samples to elucidate the promotome and the regulatory networks of mouse and human primary cells and tissues in the FANTOM5 project. DeepCAGE allows also detecting dynamic expression of repeat elements, which show peculiar expression patterns and provide alternative promoters and functional genome elements. We have also used deepCAGE on subcellular fractions as a part of the ENCODE project. We have detected clear patterns of expression of retrotransposon elements (RE) in a panel of human and mouse tissues, which are likely to have a regulatory role. Now, we have clearly identified specific patterns of non-coding RNAs and other RE-derived RNA in different cell compartments, with a particular interesting role of LINE elements, which seem to be preferentially bound to the chromatin. Other retrotransposon elements, like LTRs, are prevalently expressed in ES and iPS cells, where they may have a role to keep the stem cells undifferentiated. Altogether, these data are pointing at a potential function of the retrotransposon elements and other ncRNAs to regulate the epigenome.

The use of ultrahigh throughput diagnostic tests that determine genetic sequence variation to guide patient care is rapidly expanding, fueled by the enormous growth in sequencing platform development. With the emergence of novel technologies, the FDA is faced with new regulatory challenges while continuing to apply scientific evidence-based oversight. While there are no broadly accepted standards or methods to analytically validate ultrahigh throughput sequencing tests yet, there are a number of efforts underway, including establishing reference materials to aid in assessing analytical performance. The additional challenge in informed clinical application of sequence information is inadequate knowledge about correlations between genomic variations and their clinical significance. The FDA is proactively working to encourage cross-collaboration in this area. Ultimately, the FDA has to balance public safety concerns with fostering innovation and enabling the translation of emerging technologies that can improve medical care and benefit public health.

Developments in DNA sequencing technology have provided a unique opportunity for diagnosis and discovery of genetic alterations for rare diseases. Partnering with 20 academic centers in the US and globally, we have coordinated and facilitated NGS projects for rare disease. We will summarize what we learned from all these sites for the entire process from consent, sample collection, library prep, sequencing, bioinformatics, interpretation, counseling, and clinical reimbursement.

Since the introduction of second-generation DNS sequencing technologies in 2007, the cost of genome sequencing has been consistently by 33% per quarter, with the $1000 genome arriving in 2012 and the $100 genome not far off. As DNA sequencing increasingly becomes a commodity, biomedical research is rapidly evolving from a purely laboratory science to an information science in which the winners in the race to cure disease are likely to be those best able to collect, manage, analyze, and interpret data. Here I will provide an overview of the approach we have been developing to deal with the challenge of personal genomic data, including integrative approaches to data analysis and the creation of data portals focused on addressing the most common use cases presented by different user constituencies. By effectively collecting genomic and clinical data and linking information available in the public domain, we have made significant advances in uncovering the cellular networks and pathways that underlie human disease and building predictive models of those networks that may help to direct therapies.

The role of the human genome in normal and patho-biology is crucial. Applied in cancer care and in a variety of unknown disorder settings, it can provide key insights and crucial diagnostic/prognostic/predictive/other information. Its methods can also help improve clinical practices already provided. But many challenges remain that could delay its beneficial application, increase errors, or add unnecessary costs. In this talk, I will review the field of clinical genomic analysis generally and then focus on important challenges in its translation and clinical applications.

MicroRNAs are short non-coding cellular regulators of gene expression. Each microRNA controls the expression of a large set of genes, and microRNAs collectively, may regulate more than half of human genes. In the laboratory, our team focuses on understanding the function of microRNAs in health and during disease. We map their expression in developing cancer cells and in various brain disorders. We predict direct gene targets of these microRNAs sets and then pinpoint the cellular pathways affected. I will present our recent findings in the field and discuss its potential implications for prognosis and diagnosis. Overall our team pursues research that aims to deepen our understanding on the development of diseases in order to generate a significant impact through translating ideas into clinical reality.

Personalized medicine is transforming biomedical research and healthcare service delivery. Disease definition, diagnosis, treatment, and prevention are being fundamentally altered by the capacity to routinely perform comprehensive molecular characterization. Nowhere is this change happening faster than in the field of cancer. Increasingly sophisticated technology provides the capacity to describe, in multiple molecular dimensions, the tumor and the individual in which it has developed. These technologies identify the millions of variants present in normal individuals and thousands of alterations that occur during the course of the disease process. This systems-wide molecular analysis of constitutional and somatic tissues has identified a complex cacophony of inherited and acquired variation. Coherence emerges from these data when evaluated using biologic networks as analytic frameworks. These networks account for the individual heterogeneity in underlying etiology as well as the diversity of events necessary to generate a complex phenotype such as cancer. Emerging collections of analytic approaches permit analysis using genome-wide data sets and established biologic networks as models. The generation of this unprecedented amount of data presents us with the challenge contextualizing that data and converting into actionable information. The integration and interpretation of this complex multidimensional information into the evidence necessary to support clinical care exceeds the raw human cognitive capacity. Information systems have the capacity to provide the needed "tool" to tackle this challenge - to generate the necessary evidence to support the delivery of personalized medicine. Arizona State University's (ASU) Complex Adaptive Systems team is building such an Evidence Engine in its Next Generation Cyber Capability (NGCC). The ASU NGCC - composed of networks, hardware, software, and people transforms "Big Data" to information and creates the evidence necessary to enable personalized medicine.

It is widely accepted that approximately 85% of known disease-causing DNA variants affect the exons and splice junctions, which is about 1% of the whole genome. As a result, Clinical Exome Sequencing is a powerful and highly efficient diagnostic tool to identify disease-causing DNA variants in individuals. In this talk, I will discuss the methodology, validation, reporting, and bioinformatics aspects of clinical exome sequencing. In addition, I will talk about the regulations regarding reporting of incidental findings and the American College of Medical Genetics guidelines. I will include discussion of advantages and disadvantages of the methodology based on examples of positive and negative clinical exome sequencing results.

Howard J. Jacob, Ph.D., Founding Director of the Personalized Medicine Program and Human and Molecular Genetics Center and Professor in Physiology and Pediatrics at the Medical College of Wisconsin and Children's Hospital of Wisconsin. In 2010 Dr. Jacob led a team of researchers at the Medical College who for the first time ever were able to use the human genome to diagnose and treat a young boy, Nicholas Volker whose life threatening disease had baffled his doctors. Nik is now leading a fully and healthy life. Dr. Jacob completed his Ph.D. at the University of Iowa followed by fellowships at MIT, Harvard and Stanford. He has published over 230 papers. He is an entrepreneur and serves on several scientific advisory boards.    

I will describe recent advances in computational protein design which allow the generation of new protein structures and functions. I will describe the use of these methods to design ultra-stable idealized proteins, flu neutralizing proteins, high affinity ligand binding proteins, and self assembling protein nanomaterials. I will discuss possible applications to therapeutics, vaccines and diagnostics. I will also describe the contributions of the general public to these efforts through the distributed computing project Rosetta@home and the online protein folding and design game FoldIt.

The advent of massively parallel sequencing by next generation sequencing platforms now allow genomic approaches for individualizing healthcare. Genomic sequencing data reveals variants in genes related to drug metabolism that may affect efficacy or response. This presentation will describe the potential of NGS data for companion diagnostics or therapeutics and its implementation into clinical laboratories. Evaluating pharmacogenetic targets through exome analysis as well as through targeted gene panels will be discussed.

The FarGen project aims to sequence the whole genome of the entire Faroese population. Together with existing genetic records, such a comprehensive sequencing project can significantly improve treatment and prevention services in the Faroese public health system. The project has also great potential in an international research context as it can contribute significantly to our general understanding of human genetics. An understanding of genetics has proved crucial in health systems of the future, and genetic studies are already being used in Faroese health system. And with the introduction of the Human Genetics Act and the Genetic Biobank in 2006, the stage was set for a thriving genetic research environment in the Faroe Islands. The digitalisation of the Faroese genome, combined with the extensive health records in the Faroese health system, will significantly boost our general understanding of health issues, resulting in improved treatment and prevention services in the Faroe Islands. Thanks to our coherent health system, our special legislation (the Human Genetics Act), our digital public health register, and not least our digitalised genealogy records, the FarGen project has attracted a great deal of interest from international researchers. With these unique features, the Faroe Islands may well the ideal place for incorporating genetic research into the public health system. Both education and the ELSI play a significant role in a nationwide project like the FarGen and parallel to the sequencing a educational system for both health staff, school and the general public is been developed.

In this presentation, exome data from individuals with prostate cancer will be aligned against an annotated reference human genome and SNPs will be identified using DNASTARs SeqMan NGen software. SNPs and associated genes from disease samples will be compared against numerous control samples and a list of genes known to be implicated in prostate cancer or other cancers to identify additional candidate SNPs and genes in sample data. All work will be done using DNASTARs Lasergene Genomics Suite software, which is available on desktop computers or on the Amazon Cloud. The integration of these capabilities within one software package facilitates fast, comprehensive analysis, helping researchers move quickly from raw next-generation sequence data to informative results.

During IVF procedures pre-implantation genetic diagnosis (PGD) allows for genetic profiling of embryos prior to replacement. Most PGD procedures during IVF are performed to select chromosomally normal embryos as comprehensive chromosome screening (CCS), and in a smaller number of cases PGD is used for embryo selection against known genetic disease variants carried by the parents. Genomic technologies utilizing PCR, microarray, and second-generation sequencing methods are currently being used for PGD data analysis in the laboratory. With decreasing costs in second-generation sequencing technologies coupled with increased demand for PGD, adoption of "PGD-seq" methods for CCS and genetic selection will face significant future challenges in data management, analysis and information delivery to clinicians. One of our goals is to provide secure, integrated environments for clinicians to use genetic information to inform treatment strategies. I discuss challenges and strategies for storing and integrating biomedical data with other private and public data repositories. I discuss process and warehouse design, analysis methods and implementation strategies for PGD and genetics data. I discuss how we deliver and visualize PGD data for clinicians and to researchers in clinical and basic science.

The rapid advancements in next generation sequencing have served the research market very well, delivering more and more sequence for less and less money. While these advancements are still being made, the market is now looking toward serving a new customer - the clinician. For both technology platforms and informatics solutions, the emphasis is now on speed, quality and ease of use. An understanding of this market and where it is headed will help in predicting the broad implications for the future of medicine.

There has been considerable debate in the scientific and clinical communities regarding the return of results from genome sequencing to physicians and patients. Questions surrounding which health care professional(s) should deliver this information, as well as what types of results should be returned loom large. The aim of the Scripps Idiopathic Diseases of huMan (IDIOM) study is to use genome sequencing to inform diagnosis and treatment of idiopathic diseases. As part of this study, we assess patient and provider preferences surrounding the types of results returned from sequencing, as well as perceptions of the return-of-results communication itself. This is done via semi-structured interviews and standardized questionnaires. Data collected to date suggest that the majority of probands and their parents would prefer, if given the choice, to receive sequencing results for the presenting condition, as well as secondary findings in multiple disease categories (e.g., actionable and non-actionable, childhood and adult-onset). Further, data from the completed return-of-results sessions suggest notable variation in patient satisfaction with communication of results by the referring physician. This includes, in some cases, a marked discrepancy between the extent to which the physician felt results were communicated effectively versus the extent to which the patient perceived the communication to be effective. These case-by-case findings will be discussed in detail. Through the Scripps IDIOM study we have begun collection of empirical data on patient preferences and perceptions regarding return of results from genome sequencing for diagnosis and treatment of idiopathic disease. It is our hope that these data will help inform the development of an effective, sustainable, and cost-effective model of return of individual results from genome sequencing in clinical settings.There has been considerable debate in the scientific and clinical communities regarding the return of results from genome sequencing to physicians and patients. Questions surrounding which health care professional(s) should deliver this information, as well as what types of results should be returned loom large. The aim of the Scripps Idiopathic Diseases of huMan (IDIOM) study is to use genome sequencing to inform diagnosis and treatment of idiopathic diseases. As part of this study, we assess patient and provider preferences surrounding the types of results returned from sequencing, as well as perceptions of the return-of-results communication itself. This is done via semi-structured interviews and standardized questionnaires. Data collected to date suggest that the majority of probands and their parents would prefer, if given the choice, to receive sequencing results for the presenting condition, as well as secondary findings in multiple disease categories (e.g., actionable and non-actionable, childhood and adult-onset). Further, data from the completed return-of-results sessions suggest notable variation in patient satisfaction with communication of results by the referring physician. This includes, in some cases, a marked discrepancy between the extent to which the physician felt results were communicated effectively versus the extent to which the patient perceived the communication to be effective. These case-by-case findings will be discussed in detail. Through the Scripps IDIOM study we have begun collection of empirical data on patient preferences and perceptions regarding return of results from genome sequencing for diagnosis and treatment of idiopathic disease. It is our hope that these data will help inform the development of an effective, sustainable, and cost-effective model of return of individual results from genome sequencing in clinical settings.

Synthesis and assembly of DNA powerfully enables reverse genetics-based approaches to scientific discovery. I'll present recent and unpublished work on genome refactoring and redesign, focusing on identification of cryptic genetic elements and genome decompression. Next, I'll summarize work published over the past year in which we reported the first non-volatile and rewritable digital genetic data storage systems, amplifying genetic logic gates, and programmed cell-cell communication via arbitrary DNA messages. These experiences will be used to frame ten years of research in synthetic biology, by which the foundational engineering ideas of abstraction and standardization have finally been shown as not impossible to make true, and that when made true enable our designer DNA systems to work reliably the first time.

Cancer cells are characterized by major alterations in both cellular metabolism and epigenetic profiles. Current understanding of links between metabolism and chromatin in the context of cancer is currently very limited. We have previously demonstrated that acetylation of histones is sensitive to glucose availability through the enzyme ATP-citrate lyase (ACL), which produces acetyl-CoA from citrate. While this is likely to impact gene expression and other chromatin-dependent processes, the molecular mechanisms and functional significance of metabolic regulation of lysine acetylation are poorly understood. In this presentation, I will focus on current efforts to elucidate how metabolic signals are conveyed to chromatin. I will also discuss recent findings demonstrating a novel link between ACL and another chromatin-modifying enzyme, DNA methyltransferase 1, during adipocyte differentiation.

Rheumatoid Arthritis (RA) is a heterogenous disease that affects 1.5% of the population. Similar to cancer, early detection coupled with an effective treatment strategy can significantly improve patient outcomes. In the advent of new classes of RA therapies, there is an impetus to identify new serological markers that mark risk of RA development, prognosis and therapy response. 14-3-3 eta (?) is a new RA marker that is available for clinical use in the US through Quest Diagnostics. 14-3-3? is one of 7 members of the 14-3-3 family and is specifically present in the serum of patients with RA and erosive psoriatic arthritis (PsA). In the healthy state, these proteins reside within the intracellular space governing various biological processes including proliferation, differentiation and metabolism. Increased expression of different 14-3-3 isoforms correspond with worse prognosis in certain cancers and neurological disorders. In RA, the 14-3-3? protein is specifically externalized and can be measured in serum, making it a useful clinical serum marker. When 14-3-3? exists in the extracellular environment, it behaves as a soluble ligand inducing factors that drive inflammation and joint damage also making it a novel therapeutic target. This presentation will describe the discovery of 14-3-3? in arthritis, its development pathway and the biomarker's clinical utility. We will discuss how the 14-3-3? biomarker pipeline has evolved from the protein R&D programs into a 14-3-3? biomarker suite that serves as a direct companion to a first-in-class RA personalized medicine drug target.

Anticoagulation therapy is frequently employed to prevent stroke in patients with atrial fibrillation, prophylaxis of venous thromboembolism and pulmonary embolism in patients with prosthetic heart valves and myocardial infarction, and prevention of pulmonary embolism or deep vein thrombosis after orthopedic surgery or with a history of venous or arterial thromboembolism. Warfarin is an effective anticoagulant that can be prescribed for prolonged periods of time. However, warfarin causes adverse events; if under-dosed, clots may form causing stroke, and if overdosed, life-threatening bleeding may occur. Rivaroxaban and dabigatrin have recently come on the market as warfarin alternatives. While these drugs are reported to produce fewer adverse events, clinical experience suggests otherwise; adverse events do occur. More importantly, there are no reversal agents for these new drugs; managing an anticoagulant induced bleed by one of these agents is difficult. Pharmacogenomic (PG) testing has been applied to warfarin to reveal genetic variants that predict warfarin adverse events. The liver enzyme Cytochrome P450 2C9 metabolizes warfarin. Three variants have been extensively studied; these variants decrease warfarin metabolism predisposing patients to warfarin overdose. The enzyme Vitamin K Epoxide Reductase, known as VKORC1, converts Vitamin K to the reduced form required to activate clotting factors II, VII, IX, and X. Genetic variants in VKORC1 decrease enzyme activity causing warfarin to induce a more profound decrease in activated clotting factors than normal. Patients with this variant are more likely to experience warfarin-induced bleeding. Application of PG testing to large patient populations suggests that modified warfarin dosing based on results of PG reduce warfarin adverse events by more than 35%; this makes warfarin essentially equivalent to rivaroxaban in terms of efficacy. Summing the benefits of 50 plus years clinical experience with warfarin, availability of a reversal agent for warfarin-induced bleeding, and availability of PG testing to guide dosing, warfarin may be the safest anticoagulant on the market today.

There are over 1.5 Million fungal species and they play critical role in shaping Earth ecosystems. Better understanding of pathogens and symbionts is critical for a sustainable growth of plants. Fungi are the most efficient degraders of plant biomass to convert it into bioenergy. Many other new metabolic processes and enzymes are encoded in fungal genomes. Fungal genomics may offer answers to critical challenges of future such as food, medicine, energy and the environment. This talk will describe approaches used in large scale genomics- to explore phylogenetic and ecological diversity of fungi. It will also illustrated how genomic data can improve our understanding of plant-fungal interactions and enable practical applications for energy and the environment.

Dr Ivan Brukner entered into genomic era back in 1989 (ex-Yugoslavia), trying to describe and solve repeating sequence "branching motif problem" in building whole genome sequence. Next 5-10 years, his research was targeting sequence-dependent DNA structural problems, where contradictory puzzle about origin of DNA curvature and bending (crystallographic versus soft biochemistry data) was resolved (Italy, Germany and Canada). In 2000-2007, focus was directed toward design of nucleic-acid-based "ideal" point of care diagnostic device. Robust, multiplex, hybridization-based diagnostic device (which operates at standard "room" temperatures - in spite of ~90% sequence cross-similarity) was constructed and functionally tested. The universal protocol for selection of "robust" hybridization probes was result of this adventure. After joining Jewish General Hospital in Montreal (~2009), his work was becoming more clinically applicable, focusing on high volume molecular assays with strong financial and/or diagnostic impact (MRSA, C.difficile, VRE). He realized the strong need for applicability of new molecular techniques in emergency, including NGS, and definition of technological bottlenecks is subject of his talk in this secession.    

The goal of personalized medicine is to customize healthcare to the individual patient. Pharmacogenomics, the analysis of how a patient's genetic makeup affects the individual's response to certain drugs, plays a major role in the realization of personalized medicine. Pharmacogenomics studies the influence of genetic variation on the patient's drug response by correlating single-nucleotide polymorphisms (SNPs) with the drug's efficacy and/or toxicity, and therefore with the hope of optimizing drug therapy with respect to the patent's genotype, to ensure maximum efficacy with minimal adverse effects. Currently, most pharmacogenomic studies have been done using DNA chip arrays. A large amount of genetic information is generated in a cost effective way when using DNA chip arrays. However, one limitation of using this technology is that only a subset of mutations are analyzed and different manufacturers may use different SNPs to identify the same haplotype. Recent technological developments with next-generation sequencing (NGS) have enabled pharmacogenomics analysis at costs approaching to the cost of using DNA chip arrays. The advantage of using NGS is that all the SNPs corresponding to a haplotype can be analyzed. Currently, there are only a few targeting-sequencing kits for pharmacogenomics are commercially available. Because these kits may not cover some SNPs of interest, custom sequencing panels are needed to ensure that all interested SNPs are covered. This presentation will go over some of the important features of some commonly used targeted-enrichment technologies for NGS that are desirable for pharmacogenomic studies. This presentation will also highlight some of the challenges of developing and implementing pharmacogenomic NGS in a clinical laboratory for routine patient sample analysis.

Approximately 98% of the human genome comprises noncoding DNA, the function of which is largely unknown. Intriguingly, more than 85% of single nucleotide polymorphisms identified to be associated with disease in genome-wide studies (GWAS) occur within noncoding regions, suggesting that examining the role of these regions of the genome will be important for understanding and potentially treating disease. The relatively recent discovery of widespread transcription of potentially functional long noncoding RNAs (lncRNAs) from the mammalian genome led us to investigate whether or not GWAS hits in noncoding regions could be reconciled by the transcription of regulatory RNAs from these loci. LncRNAs typically show highly developmental-stage- and tissue-specific expression, and therefore cannot be easily detected by conventional RNA-Seq, which requires exponentially greater depth to detect increasingly rare transcripts. To overcome this problem, we developed a technique termed RNA-Capture-Seq, which combines custom capture tiling arrays with RNA sequencing to target transcription arising from specific areas of the genome. We have used this approach to target 300 chromosomal regions identified by GWAS. Using RNA from diverse human tissues, we identify thousands of novel transcripts associated with the majority of the targeted regions. To further realise the potential of the method to understand specific diseases, we have designed further capture arrays to target GWAS regions linked to specific diseases. For these experiments, RNA from biologically relevant normal and disease tissues were used to look for novel transcripts. As a result, we have identified numerous new lncRNAs whose expression appears to be specifically associated with disease and arise from disease-associated regions. Although functional investigation of these transcripts is still underway, we propose that the results of these experiments bring an intriguing new perspective into our understanding of how information in the genome is encoded and has considerable potential to identify novel regulators, which may prove valuable as biomarkers and therapeutic targets, involved in disease and development.

High throughput transcriptomic analyses have shown that most of the human genome is dynamically transcribed to produce an extraordinary range of overlapping and interlacing intronic, intergenic and antisense RNAs, many of which are alternatively spliced, to produce a previously hidden universe of long and short regulatory RNAs. These RNAs fulfill various functions in gene expression, with miRNAs and related species being best (although not well) understood. The functions of the long noncoding RNAs (lncRNAs), which range from hundreds to hundreds of thousands of bases in length, are varied and include central roles in the formation of various differentiation-specific subnuclear organelles. However, recent evidence suggests that the major function of lncRNAs is to guide chromatin-modifying complexes to their sites of action, to specify the architectural trajectories of development and differentiation. In addition, it appears that these RNAs are subject to context-dependent editing, particularly in the brain, which appears to be, along with transposon mobility, the molecular basis of physiological and cognitive plasticity. The transcriptome is in fact far more complex than the genome, which is best viewed as a zip file that is unpacked in highly cell-specific patterns during development. Focused RNA sequencing (using oligonucleotide capture to target specific loci, similar to exome sequencing) reveals thousands of previously unknown exons and spliced isoforms of oncogenes and tumor suppressors, as well as a rich landscape of lncRNAs expressed from genomic regions, including GWAS regions associated with complex diseases, that superficially appear to be transcriptionally bare by conventional deep sequencing. Not surprisingly, it is also emerging that variations in the sequence or expression of these RNAs not only underpin phenotypic differences between individuals and species, but also play significant roles in the etiology of complex diseases, including as cancer and neurological diseases.

Introduction Although the focus of the genomics community has largely been on DNA polymorphisms which affect disease risk, gene expression, especially of blood cells, has the potential to reflect genetic and environmental factors and to inform on both current and future disease status. The immune system dysregulation underlying many human diseases, including transplant rejection, and coronary artery disease (CAD), coupled with development of global blood gene expression profiling and quantitative RT-PCR, has enabled the clinical use of blood-based gene expression tests. Methods Blood samples were obtained from heart transplant or coronary disease patients and paired with results from gold standards of pathologist core-lab read endomyocardial biopsies (EMB) or quantitative coronary angiographic analysis on invasive angiograms, respectively. Discovery, development and validation steps were used to identify genes, develop algorithms, and validate algorithm performance with pre-specified statistical and clinical analysis plans. Development and validation cohorts were obtained in prospective multi-center trials. Finally, the performance and impact of these tests on usual care was assessed in observational or interventional studies. Results For heart transplant rejection largely independent cohorts were used to discover and develop an 11 gene algorithm to discriminate high-grade rejection from quiescence. In a set of independent patient blood samples the ROC curve AUC was 0.72; subsequent comparison of this algorithm with EMB in a prospective interventional trial met the primary endpoint of non-inferiority with a significant reduction in EMB. For CAD diagnosis, after gene discovery by microarrays, independent cohorts from a multi-center angiographic study were used to develop and validate a 23-gene whole blood RT-PCR based algorithm to discriminate obstructive CAD, with a second validation study assessing performance in patients referred for myocardial perfusion imaging. ROC AUC in these two validation studies were 0.70 and 0.79, respectively. Conclusions Blood-based gene expression tests have been developed and are being using clinically.

Long non-coding RNAs (lncRNA) are a novel class of RNA molecule that are emerging as important regulators of gene transcription and post-transcriptional events. lncRNAs have been shown to regulate a broad variety of biological processes and are often located within regions of the genome that are associated with various diseases. Repetitive elements are a major component of lncRNA and their molecular functions in lncRNA are poorly understood. Here, I describe the evolution of Alu elements in lncRNA and mRNA. Alu elements are the most abundant transposable element in the human genome (more than 1 million copies) and their composition and evolution within lncRNA and mRNA differ significantly. These striking differences are correlated with their expression and suggest a common molecular function in lncRNA and mRNA.

The remarkable diversity we see between different cell types in the human body is governed by the specificity attained through transcriptional and epigenetic regulatory programs. Cancer is a disease that targets specific tissues, and in the case of cancer-causing germline mutations, it is perplexing that primary tumors arise in a restricted subset of tissues only. Understanding why a mutation can be suppressed in one tissue but not others stands to unlock insights into tissue-specific transcriptional regulation and how these programs promote fragility or resistance of cancer-causing mutations. We have been studying cancer-causing germline mutations in the context of cell type-specific gene regulatory networks. Using a comprehensive tissue expression atlas from the FANTOM5 consortium, we have access to CAGE sequencing data that captures promoter usage and gene expression in over 1000 human samples, including primary cells, tissues and cell lines. Levering information from COSMIC, the Cancer Gene Census, and FANTOM5, two classes of genes that have tissues-specific, cancer-causing mutations have been identified - (1) genes that are expressed in the cell type where the cancer occurs, (2) genes that are expressed ubiquitously across many different cell types. For this second class, we have begun comparing regulatory networks associated with these genes in susceptible versus resistant cell types to identify changes in network topology that may change a cell type's oncogenic potential.

Increasingly genome sequence knowledge is unraveling the complexity of rare Mendelian disorders offering hope for our children's medical care through better disease diagnosis and ultimately patient care. When combined with the emerging new sequencing technologies, allowing large scale genome analysis to move rapidly into clinical laboratories, new opportunities arise for more precise medical care. Claritas Genomics was founded to deliver on the promise of science and technology merging for medical care. Our presentation will discuss the current needs for molecular diagnostics in pediatric populations and provide a better understanding of the role Claritas plays in enabling better patient decisions. Founded as a genetic diagnostic testing company, Claritas combine the power of next-generation DNA sequencing technology with the clinical expertise of the world's best pediatric specialists to assist in informing and improving patient care. Claritas offers a full range to support physician test ordering and support needed as they care for patients, navigating an increasingly complex landscape of genetic diagnostics. Our genomic interpretive services are based on the most up to date and reliable scientific findings and our reports are designed to clearly communicate this complex genetic information. Originally Boston Children's Hospital's CLIA molecular testing laboratory, and launched as an independent CLIA/GLP laboratory in February 2013, we have an existing comprehensive menu of tests, with new next-generation sequencing-based services to be launched in the fall of 2013. Through our partnership with Life Technologies, Claritas is also well positioned to offer cutting edge advances in DNA sequencing, offering products from single gene tests through to whole exomes. Claritas also maintains a close relationship with Boston Children's and its renowned investigators, to uniquely position us to translate novel research-based discoveries into diagnostic clinical practice. Thus we aim to enable health care providers to integrate genomics into the future of their routine medical practice responsibly and Claritas takes pride in our partnership with both our ordering clinicians and the genetic researchers making discoveries that will lead to new tests and clinical knowledge.

The human species is particularly prone to chromosome segregation errors during maternal meiosis in the egg and during post zygotic mitosis in the preimplantation embryo. In fact, aneuploidy represents the most common genetic abnormality in humans, and is the primary cause of infertility, affecting 1 in 6 couples. Despite the extremely limited amount of DNA available from a human embryo, development of genetic technologies, such as qPCR and next generation sequencing, now allow accurate and effective analysis of the copy number of all 24 chromosomes in preimplantation stage human embryos produced during in vitro fertilization (IVF). Selection of chromosomally normal embryos improves the efficacy of single embryo transfer, eliminating the primary complication of IVF (multiple gestations), and improves the success of treating infertility. This presentation will detail the development, validation, and future directions of new human embryo comprehensive chromosome screening technologies.

Aging is the major risk for diseases such as cancer, AD, type 2 Diabetes mellitus and cardiovascular disease. We hypothesize that a progress in preventing these diseases will occur only if we can understand the reason people age at different rates, and develop strategy to delay aging. Certainly the environment plays a major role in our aging, and environmental intervention, such as caloric restriction, can delay aging significantly in many biological models. While we can measure biological changes with aging we cannot assume they are the cause. In fact the challenge is to determine which changes may be the cause/s of aging and which are protective mechanisms against the changes that occurs. One approach to understand aging is to study the oldest old people who are relatively healthy. We established such a unique cohort of individuals with exceptional longevity (~600 Ashkenazi Jews ages 95-112) and their offspring (approximate age 70 years) and age- and sex-matched controls without a family history of unusual longevity. This matched group of offspring of exceptional longevity-proband and their controls are a powerful tool for identifying genetically controlled longevity traits.

Cervical cancer screening has evolved significantly since the PAP smear was introduced in 1949. In particular, the association with human papillomavirus (HPV) infection and the mechanism of HPV-related carcinogenesis have been elucidated over the last 20 years. Diagnostics quickly followed focusing on the presence or absence of HPV. Because HPV is ubiquitous and the presence of a high risk type of HPV results in high grade cervical lesions in a small number of instances, the field has realized that infection by HPV is not enough to appropriately triage affected individuals into treatment categories. Detection of HPV DNA has high sensitivity (95%+) for high grade cervical lesions but low specificity (

Codon-optimization describes gene engineering approaches that use synonymous codon changes to increase protein production. It is used extensively for expressing recombinant protein drugs, gene therapy, and DNA/RNA vaccines. However, it is becoming increasingly clear that codon-optimization can affect protein conformation and function, increase the immunogenicity of recombinant protein drugs, and reduce efficacy. This presentation will analyze the mechanisms and assumptions underlying codon optimization and identify additional hazards associated with this approach, including unique hazards for gene therapy and DNA/RNA vaccine applications.

In addition to the exciting promise that genome sequencing holds, concerns are also often described. These concerns relate to: privacy/confidentiality of findings; impact of findings on insurability and discrimination; autonomy and the impact of one's findings on others; questions of clinical utility; the potential for psychological distress; and equity of access. While each of these concerns may constitute a reason for some not to pursue sequencing technology at this time, others remain ready and willing to move forward immediately. Clearly the weighing of risks and benefits are different for different people. Delineating these differences will take time and require empirical exploration. One seemingly obvious bot often neglected differentiation is the starting point for individuals (or family members) - whether they are sick or healthy. Decision making in the context of illness likely (and understandably) influences the weightings given to risks and benefits - perhaps even reframing the balance of promise and concern entirely (a "game changer"). This talk will present the various concerns put forward regarding genome sequencing and discuss the ways in which these are more and/or less relevant depending upon one's relative health situation.

Susceptibility to coronary artery disease (CAD) is claimed to be 40% to 60% inherited, but until recently genetic risk factors predisposing to CAD have been elusive. Comprehensive prevention of CAD requires manipulation of genetic risk. The availability of microarrays of single-nucleotide polymorphisms enabling genome-wide association studies (GWAS) led to the discovery of 50 genetic risk variants for CAD. Surprisingly, 35 risk variants mediate their risk through unknown mechanisms, with only 17 associating with hypertension or lipids. Thus, there are several mechanisms contributing to the pathogenesis of CAD yet to be elucidated. The first risk variant discovered by GWAS was 9p21.3, which occurs in 75% of all populations except African, with a mean increased risk of 25% per copy. Of the 50 variants for CAD, the increased risk varies from 6% to 92% with a mean increased risk of 18%, occurring on average in 47% of the population. The maximum number of risk alleles per individual would be 100. In the CARDIoGRAM (Coronary Artery Disease Genome-wide Replication and Meta Analysis) study of 23 variants, the average per individual was 17, the minimum 7, and the maximum 37. The top 10th percentile has an odds ratio of 1.88 and the lowest percentile an odds ratio of 0.55. Routine genetic screening is unlikely until management is improved by genetic testing. Risk variants should provide pathophysiological insights and targets for novel therapy. While risk variants are less potent predictors of CAD, compared with biomarkers, they have the advantage of not changing in one's lifetime and are unaffected by diet, sex, age, or medication.

Sharing sequencing datasets without identifiers has become a common practice in genomics. We recently showed that some datasets can be fully re-identified by using entirely free, publicly accessible Internet resources. I will present quantitative analysis about the probability of identifying US individuals by this technique on hundreds of genetic datasets. In addition, I will demonstrate the power of our approach by tracing back the identities of multiple whole genome datasets in public sequencing repositories.

Whenever there is cell death, apoptotic cell free DNA fragments appear in the circulation of the host. These fragments, typically 145-160 base pairs in size, represent a minute fraction of total DNA in the host circulation. If care is taken to avoid host cell breakage, the apoptotic DNA fragments can be analyzed to provide information about the genome of the cells that produced them. In pregnancy, analysis of apoptotic DNA fragments has allowed the development of very effective noninvasive aneuploidy testing. Indeed it is possible to reconstruct the entire fetal genomic DNA sequence from these fragments. In cancer it is possible to view copy number, sequence, and epigenetic differences between the tumor and the host by analyzing circulating free DNA. While this work is still at early stages it is reasonable to predict that an array of useful noninvasive cancer diagnostic tests should soon result from such studies. It is furthermore likely that a careful search for informative apoptotic DNA fragments that differ in methylation from DNA in the circulation of a normal host might lead to methods for the early detection of other clinical situations that are characterized by inappropriate cell death.

RNASeq has become the primary method for studying changes in gene expression in modern genomics research. By directly sequencing the various types of RNA molecules, including mRNA, ncRNA, and small RNA, researchers can build an accurate profile of gene expression under various conditions, allowing the elucidation of gene function and regulation. RNASeq has been further refined recently with the development of stranded RNASeq, which modifies the existing RNASeq library construction methodology to preserve information regarding which DNA strand the RNA transcript originated from. Among other advantages, stranded RNASeq allows for more accurate mapping of RNASeq transcripts to reference genomes, which in turn results in a more accurate view of the transcriptome. Increasingly, researchers are designing more complex experiments involving population level transcriptomic surveys and time course studies, both of which require high throughput RNASeq library construction methods that consistently generate high quality RNASeq libraries. In response, we developed an automated RNASeq library construction method using the Beckman Coulter Biomek FXP liquid handling system in conjunction with TruSeq Stranded mRNA library preparation chemistry from Illumina. By combining Illumina's proven chemistry with the highly efficient Biomek FXP liquid handling system, we have developed a flexible library construction protocol that allows for the creation of up to 96 individually indexed Illumina stranded mRNA libraries by a single technician over the course of approximately 8.5 hours of machine time.

In the United States, invasive aspergillosis (IA), an invasive fungal infection of the upper respiratory tract of immune compromised patients, is usually caused by Aspergilus fumigatus, while Aspergillus flavus represents only a small fraction of IA cases. In some countries A. flavus is the most frequent IA pathogen. Recently, we described a novel, highly virulent, aggressively invasive, and drug resistant IA pathogen, Aspergillus tanneri. In mouse models of IA and in a non-vertebrate insect model we observed distinct virulence profiles for the three Aspergillus species. Comparative genomics showed that A. tanneri had a larger genome than the other Aspergilli, encoding nearly 1900 more genes than A. fumigatus. A. tanneri genes had numerous orthologs in the other two genomes, however an abundance of genes are unique to A. tanneri. Among the unique genes were multiple gene clusters that encode biosynthetic genes for the synthesis of secondary metabolites, suggesting that A. tanneri produces novel secondary metabolites that may play a role in its high level of pathogenicity. Analysis of genes commonly associated with drug resistance showed that A. tanneri carried CYP51A mutations resulting in or contributing to azole resistance. An important issue featured in the A. tanneri fatal cases and in clinical management of IA is the general limitation in treatment options - only four classes of drugs are available in the context of ever-increasing drug resistance. Drugs used to treat fungal infections target only two differences between human and fungal cells: the presence of ergosterol in fungal cell membranes and of glucans in their cell walls. There remains an urgent need to understand the broad range of genes encoded in the genomes of fungal pathogens that participate in the resistance to the clinically therapeutic antifungals employed in treating infections. To identify novel mechanisms that mediate azole resistance in A. fumigatus, we used whole genome sequencing of in vitro selected azole-resistant strains. To further refine the most significant mechanisms required for resistance, we developed a genetic-sexual system that enables the analysis of complex traits in A. fumigatus and revealed that at least 6 mechanisms for azole resistance exist in this organism. These include mutations in the target protein, CYP51A, and in an additional co-target HMG CoA reductase. The results from this study identify novel drug targets in A. fumigatus and also show that next-generation sequencing coupled with classical genetics experiments is a powerful way to identify genes involved in complex traits.

Massively parallel sequencing technology has proven to enable the identification of driver genetic alterations in patients' tumors that may be suppressed by targeted therapies. Through retrospective analysis of clinical specimens, one can discover genomic biomarkers that predict outcomes and therapeutic response. Longitudinal profiling of multiple tumors in a single patient can reveal factors that influence tumor progression and drug resistance. Finally, prospective sequencing of patient specimens, when coupled with complementary radiology and histology based imaging, can enhance the clinical diagnosis and treatment of cancer patients. For increasingly lower costs, one can profile clinically relevant genes for mutations, copy number alterations, and structural rearrangements, with high detection sensitivity in low purity or multi-clonal tumor tissue. Advances in target capture, sample multiplexing, and profiling of formalin-fixed paraffin embedded (FFPE) specimens have further established the clinical utility of next generation sequencing. However, challenges remain in the application of these techniques to the analysis of clinical samples. In addition to the technical challenge of analyzing scant amounts of FFPE tissue, one must overcome the biological challenges of aneuploidy and heterogeneity inherent to the genetics of cancer. I will discuss different strategies for sequencing clinical samples, including different sequencing platforms, capture methods, and breadth of testing (i.e. targeted versus comprehensive approaches). I will describe examples in which our group has performed massively parallel sequencing on clinically annotated tumor specimens to identify genomic biomarkers of drug response and resistance. Finally, I will describe additional challenges in prospectively applying these techniques for clinical diagnosis involving bioinformatics, clinical interpretation, regulatory compliance, and ethics.

Medical applications of genetics and genomics have been advancing dramatically since completion of the sequencing of the human genome. The cost of DNA sequencing has plummeted, leading to the rapid introduction of sequencing-based testing into the clinic. Genomics has already changed our approach to prevention, diagnosis, and treatment of disease; the day is not far off when most medical decisions will be to some extent informed by the outcome of a genetic or genomic test. Most practicing physicians were trained well prior to the genomic era, and even those who remember what they were taught about genetics will find that the field has changed beyond recognition. Although some of the genomics applications will be mediated through point-of-care decision support systems, there is a need for physicians to gain competency in multiple areas of genetic and genomic medicine. This includes use and interpretation of genetic and genomic predictive and diagnostic tests, using pharmacogenetic information to adjust drug administration, and customizing treatment to specific subtypes of disease defined by genetic testing. Physicians will also need to be able to incorporate the results of genome sequencing, including responding to incidental findings of genetic changes that indicate risk of disease. These educational challenges will need to be met for physicians in training and in practice, and will require the use of multiple educational modalities, including use of approaches such as online courses and case studies. Genetics and genomics may also be built into the maintenance of certification requirements in many specialty areas. There is a great need for innovative approaches to genetics and genomics education that will prepare physicians and other health providers, recognizing the increasing complexity of medical care generally and the increasing demands on the time of all practitioners.

Personalized medicine is expected to benefit from the combination of genomic information with the global monitoring of molecular components and physiological states. To ascertain whether this can be achieved, we determined the whole genome sequence of an individual at high accuracy and performed an integrated Personal Omics Profiling (iPOP) analysis, combining genomic, transcriptomic, proteomic, metabolomic, and autoantibodyomic information, over a 38-month period that included healthy and two virally infected states. Our iPOP analysis of blood components revealed extensive, dynamic and broad changes in diverse molecular components and biological pathways across healthy and disease conditions. Importantly, genomic information was also used to estimate medical risks, including Type 2 Diabetes, whose onset was observed during the course of our study. Our study demonstrates that longitudinal personal omics profiling can relate genomic information to global functional omics activity for physiological and medical interpretation of healthy and disease states.

As a component of individualized medicine, pharmacogenetics (PGx) focuses on how genetic factors influence individual responses to specific medications. The clinical goals of pharmacogenetics are to identify the right drug at the right dose for each patient. The majority of known PGx-related variability is due to variation in genes encoding drug metabolizing enzymes. Variable drug metabolism can result in adverse drug events, ineffective therapies, and noncompliance with therapy. Pharmacogenetic variability can also be due to genetic variation in genes encoding drug transporters, drug targets, and proteins involved in immune response. Drugs with known pharmacogenetic variability may be labeled with PGx-related information. One example is clopidogrel which was updated in March 2010 by the FDA to contain information regarding response to clopidogrel in cytochrome P450 2C19 (CYP2C19) poor metabolizers. It has been demonstrated that individuals with reduced function CYP2C19 alleles do not effectively convert clopidogrel to its active metabolite, and this is associated with an increased rate of subsequent cardiovascular events and death. Other examples of pharmacogenetic-related drug labeling include warfarin and CYP2C9 and VKORC1 variation, psychiatric medications and CYP2C19/CYP2C9/CYP2D6 variation, thiopurines and TPMT variation, hypersensitivy to carbamazepine and abacavir due to HLA-B variation, and irinotecan and UGT1A1 variation. These and other examples are the basis for different clinical applications in pharmacogenetics with the ultimate goal of utilizing genetic information to determine the appropriate drug and dose for each patient.

With the technical costs of genome sequencing continuously dropping, it is now feasible to offer this assay in a clinical context. Empirical evidence suggests that genome and exome sequencing may lead to a diagnosis in 25-30% of affected individuals, with even current costs of the sequencing being offset by savings in patient care management. Furthermore, the nature of the test allows for the identification of incidental findings in both affected and healthy individuals that may lead to further cost savings. In this talk, we'll detail the issues and complexities that arise from implementing genome sequencing as a clinical service, including methods and techniques to validate the assay and interpret the results. Furthermore we'll discuss approaches to create reports that return both results for the primary indication and for incidental findings, the former of which was used as the clinical report for the winning team of the recent CLARITY Challenge. We'll also detail our experiences offering genome sequencing in clinical care, including our support of the MedSeq project that is studying the return of patient genome sequence data to subspecialists and primary care physicians.

In this presentation I describe some of the approaches we are taking to identify the genetic architecture of common complex cancers with a particular focus on the etiology of lung cancer. Cancers results from joint effects of germline susceptibility along with common environmental exposures that propel risk for further stages of cancer development for some individuals. Genome-wide association studies have been highly effective in providing new insights into the etiology of these cancers. For lung cancer, genome-wide association analysis identified a key region of chromosome 15q that contains variants of nicotinic acetyl choline receptors that are expressed at low levels in most of the brain except a few selected areas, so these were not considered as primary candidates for smoking behavior nor for lung cancer risk. Further study of these loci shows they play a key role in lung cancer development as well as in tobacco use and smoking cessation. In particular, individuals with high risk variants have particular difficulty in tobacco cessation unless provided with pharmacological support. Other findings from genetic analysis of lung cancer have shown dramatic heterogeneity by histological subtype. A region on chromosome 5p21 harboring hTERT and CLPTM1L shows heterogeneity by histology, but animal models show that CLPTM1L plays a role in cancer progression. Finally, we discuss the role of sequencing for understanding the genetic architecture of cancers and how the limited resources available for genetic analysis might be applied for both sequencing and genome-wide assessment.

Our ability to view and alter biology is progressing at an exponential pace -- faster even than electronics. Next generation sequencing can be used to assess inherited, environmental and epi- genomes. CLIA typically ensures reproducibility, but not necessarily highest accuracy. Genome sequence accuracy requires haplotype phase (measured, not merely inferred). Interpretation accuracy requires deep knowledge of the interactions of genomes, environments and traits. We can now move from mere correlation to causality by systematically synthesizing millions of genomic (and epi-genomic) variants via CRISPR technologies and human pluripotent stem cells. We test these technologies and interpretation software (http://GET-evidence.org ) using data and cells from the world's only fully shareable genomics resource (http://Personalgenomes.org) -- enabling clearer preview of precision medicine. The learning objectives of this session include measuring accuracy of the underlying data, the computational integration of diverse data types -- and informed consent in an era of leaks, rich data and re-identification.

This presentation focuses on contemporary methods for detection of monoclonal proteins (M-protiens) that are associated with multiple myeloma and other plasma cell dyscrasias. The basic principles of the techniques currently used will be presented along with a triage that can be used for their implementation. None of the techniques is without the hazards of false positive and false negative results. When using serum protein electrophoresis as the screen, the main causes for false positives include the presence of fibrinogen and genetic variants of normal serum proteins. When capillary electrophoresis is used to screen serum, radiocontrast dyes and some antibiotics can mimic M-proteins. False negatives occur because will be demonstrated along with tactics to prevent them. Serum free light chain testing is a boon to detecting multiple myeloma without requiring a 24 hour urine sample, however the user needs to be aware of the high-dose hook effect which can produce falsely low results. The newest serologic test is able to measure heavy and light chain specific pairs, i.e. distinguishing between populations of IgG kappa and IgG lambda. These reagents may aid in classification and risk stratification, but more independent research will be needed to determine their utility.

Genetic testing is becoming a widespread practice and with human genome fully sequenced we want to develop best methods to do it. Single gene or single mutation screening is pretty much becoming a thing of the past. Similarly using just single PCR for identifying mutations, while cheap and quick, is being slowly replaced by highly multiplex tests.Targeted re-sequencing applications analyze a subset of human genes and/or mutations and report back the sequence of fragments tested. Currently there are two technologies for doing that: sequencing by hybridization or Next Generation Sequencing. I will discuss the technical aspects, sample and analysis workflows, and validation protocols for re-sequencing assays. I will also briefly review some of the currently available assays for targeted re-sequencing highlighting their advantages, disadvantages and clinical use.

A 2013 survey conducted by the Woodrow Wilson Synthetic Biology Project found that 75% of adults have heard just a little or nothing at all about synthetic biology, figures that were virtually unchanged since 2009. Meanwhile, the field, like DNA sequencing and systems biology before it, is growing in technological sophistication at a tremendous rate and disrupting conventional ideas and mechanisms in research, development, security and economics. It's like computers all over again, only in a different and more controversial medium ¬- life. This talk will introduce synthetic biology to a broad audience by comparing it to the evolution of computing and information technologies; describe key individuals, breakthroughs, and resources from recent years; and provide a future forward perspective based on trends and comparisons. By the the end of talk, the listener should feel a) confident that they have a basic understanding of synthetic biology; and b) some appreciation of the importance of the field to continued global technological and economic progress - if not the continued existence of the human species.