Day 2 :
- Track 6: Digital Gene Expression & Modern Genetics
Track 7: Evolutionary and Comparitive Genomics
Track 8: Genomic Technology and Methodology Development
Track 9: Next Generation Sequences and Services
Genomics GPS, LLC USA
Time : 10:00-10:20
Dr. Stephens research career spans over 35 years in academia, government, biotech, and the pharmaceutical industry. A double major in zoology and mathematics from Duke University preceded a PhD in genetics from the University of Georgia, where he specialized in theoretical population genetics. He was fortunate in having postdoctoral training with Bruce Weir at NCSU and subsequently with Masatoshi Nei at UTHSC-H, where his interests began to shift from theory to data analysis, and in particular to the analysis of human molecular genetic data. This pursuit ultimately lead to stints at the Yale-HHMI Human Gene Mapping Library and NCI. As the transformative potential of human genetic research became increasingly more apparent, Stephens made the leap into industry in 1999, first at Genaissance Pharmaceuticals, then Motif BioSciences, and most recently Pfizer. In industry he is continuing efforts to leverage the application of industrial-scale genomics to human health and drug development.
The current paradigm for biosample collection and genotyping is two-phased: sample collection and storage, followed by sample retrieval and genotyping. Quite often the second phase is months or years after sample collection, if it occurs at all. This practice is conservative, in that it avoids genotyping expense up front, but at a cost of incurring huge delays in access to data. Furthermore, costs of storing, retrieving and prepping samples prior to genotyping are significant. For these and other technological reasons, we advocate a paradigm in which the genotypic data is generated immediately, upon sample collection, which now places an emphasis on data storage, access, and analysis.
George Washington University Medical Center, USA
Patricia Berg received her bachelors degree in mathematics from the University of Chicago, her Ph.D. in microbiology at the Illinois Institute of Technology in Chicago, then pursued Post Doctoral studies at the University of Chicago in molecular biology. Further work at the National Institutes of Health followed, where she cloned the first repressor of the human beta-globin gene, with the idea of using it in therapy of sickle cell anemia to repress the mutant beta-globin gene. Currently she is a Professor of Biochemistry and Molecular Medicine at the George Washington University in Washington, DC, where she is director of a cancer research laboratory. Her work centers on the BP1 gene, which she cloned, and its involvement in breast cancer, the topic of her presentation. Dr. Berg research has been featured on network television and in the New York Times, Washington Post, Washington Times, Los Angeles Times, AP, and Reuters among other major media, and Hillary Clinton and congressional leaders have headlined an event supporting her work.
BP1, a gene we identified and cloned, is a member of the homeobox gene family of transcription factors (TF). BP1 is overexpressed in breast cancer, prostate cancer, ovarian cancer, acute myeloid leukemia, non-small cell lung cancer, and possibly other malignancies as well. Important characteristics of BP1 in breast cancer, our main focus, include findings that: (1) BP1 is expressed in 80% of invasive ductal breast tumors, including 89% of the tumors of African American women compared with 57% of the tumors of Caucasian women. (2) BP1 expression correlates with the progression of breast tumors, from 0% in normal breast tissue to 21% in hyperplasia and 46% in ductal carcinoma in situ. (3) Expression of BP1 is associated with larger tumor size in both women and mice. (4) BP1 appears to be associated with metastasis. Forty-six cases of inflammatory breast cancer were examined and all were positive for BP1 expression, as well as matched lymph nodes in the nine metastatic cases. (5) BP1 overexpression induces oncogene expression. BP1 protein (pBP1) activates the BCL-2 gene; high BCL-2 protein levels are associated with resistance to drug and radiation therapy. BP1 also activates VEGF and c-MYC, as well as other genes important in angiogenesis, invasion and metastasis. pBP1 down-regulates BRCA1. (6) BP1 up-regulates ER alpha and induces estrogen independence. High pBP1 levels can lead to estrogen independence in ER positive breast cancer cells and tumors in mice. In summary, BP1 appears to confer properties on breast cancer cells that lead to a more invasive and aggressive phenotype. Since the functions of homeotic TF are highly conserved, it is likely that BP1 regulates many of the same processes and genes in other malignancies.
The George Washington University, USA
Time : 10:40-11:00
Simon Berkovich received MS in Applied Physics from Moscow Physical-Technical Institute (1960) and Ph.D. in Computer Science from the Institute of Precision Mechanics and Computer Technology of the USSR Academy of Sciences (1964). He played a leading role in a number of projects on the design of advanced hardware and software systems. He has several hundred publications in various areas of physics, electronics, computer science, and biology. In 2002, Professor Simon Berkovich was elected a member of the European Academy of Sciences "for an outstanding contribution to computer science and the development of fundamental computational algorithms".
On the epigenetic properties of the DNA information. Commonly, the genome is considered as a collection of functional units responsible for particular traits of an organism. This idea turns out to be inadequate urging for an epigenetic extension. The amount of genes in humans, about 20,000, is low for purposeful activities. Appealing to the non-protein coding part of the genome is futile since even in its entirety the genome does not contain sufficient information for full organism control. In our view, the DNA molecules present pseudo-random numbers with slight classification adaptations. Establishing biological individuality, the DNA information serves as a multi-access code for Cloud Computing and thus acquires necessary epigenetic facilities. Physical foundation for this supposition, a sort of quantum computing in the Holographic Universe, has been described elsewhere. The conventional interpretation of the DNA without epigenetics has limited operational significance. Consider for illustration a population of telephone customers with two types of area code genes: 406-xxx-xxxx (Montana) and 407-yyy-yyyy (Florida); so, revealing that some individuals have furs one might treat the corresponding gene as a factor responsible for this circumstance. Another line of reasoning: suppose someone wants to build a car from scratch; a straight 20,000 words text with instructions could not be enough; however, such a text having appropriate references to manuals may suffice. With the suggested paradigm of Epigenetics coming from Cloud Computing the construction of an organism occurs not by the information that the genome contains, but also by the references that it provides.
Fisher graduated from St. Louis University School of Medicine and completed his residency in Obstetrics & Gynecology at Emory University. He is Fellowship trained and Boarded Certified in both Maternal-Fetal Medicine and Medical Genetics. He offers comprehensive care to women with high-risk pregnancies, prenatal diagnosis, ultrasound and preconception counseling for high risk patients. Dr. Fisher is also active in many organizations and has a number of publications. He is a Franklin Award honoree from the March of Dimes and has a number of other awards for teaching and his research.
For over 40 years, chromosomal analysis in the prenatal arena has been limited. Since 2005, microarray analysis has been offered to the American public for an option for further information for their pregnancies. Until recently, there has been limited information for this population. The aim of the lecture is to demonstrate the utility of microarray analysis in conjunction of prenatal diagnosis in a multitude of ultrasound findings and their added significance. We will also review the pitfalls of karyotyping and noninvasive prenatal testing in comparison to microarray analysis. Future applications and suggested protocols will be reviewed as well.
University of North Carolina, USA
Time : 11:40-12:00
Piotr Mieczkowski has completed his Ph.D. at the Institute of Biochemistry and Biophysics Polish Academy of Sciences and postdoctoral studies at the University of North Carolina at Chapel Hill and Duke University. He is the Director of the High Throughput Sequencing Facility at UNC. He has published more than 56 papers in reputed journals. His work is focused around new applications for next generation sequencing technology, genome stability and mutagenesis.
Free circulating DNA (fcDNA) in peripheral blood is a subject of increasing interest in the circles of medical diagnostic and cancer research. We decided to evaluate methods used for extraction and analysis of the cfDNA. The blood from patients was collected into three types of tubes: ACT, EDTA and Streck cell free DNA BCT. The cell free BCT tubes stabilize blood cells and do not allow for the uncontrolled release DNA or RNA to the plasma during the handling and preparation procedure. Extraction of DNA was performed using both column (Qiagen) and magnetic bead (SNOVA and OMEGA) protocols according to the manual provided by the manufacturer. The undergoing result of comparison methods for DNA purification from plasma will be presented. Extracted DNA was subject for sequencing on Illumina Sequencing platform. We used three major methods for DNA sequence analysis - Whole Genome Sequencing, TruSeq DNA Capture and Amplicon protocols. We focused on Molecular Tag Amplicon sequencing strategy since this technology is most clinically relevant at this time. Therefore, data for a SNP targets amplified on PCR or Fluidigm Access Array platform used for cancer research will be presented during the meeting.
Clemson University, South Carolina, USA
Title: Structure-based modeling of the effects of missense mutations associated with human disorders
Time : 12:00-12:20
Emil Alexov has received MS in Physics from Sofia University, Bulgaria in 1983 and PhD in Physics in 1990. Since then he assumed various positions in academia and in research institutions as Sofia University, Bulgaria; RIKEN Institute, Japan; City College of New York and Columbia University, New York. Since 2005 he moved to Clemson University, SC where he currently is Professor of Physics. His lab work on various projects the main being maintenance and further development of DelPhi and modeling effects of human DNA variations with respect to human diseases. He coauthored more than hundred peer reviewed papers, serves on several Editorial Boards and reviews for various journals. He has co-organized and will co-organize scientific meeting including g incoming Gordon Research Conference of Human Single Nucleotide Polymorphism and Disease August 3-8, 2014.
Human DNA sequence differs among individuals and the most common variations are known as single nucleotide polymorphisms, or SNPs. Studies have shown that non-synonymous coding SNPs (nsSNPs - SNPs occurring in protein coding regions which lead to amino acid substitutions) can be responsible for many human diseases or cause the natural differences among the individuals by affecting the structure, function, interactions and other properties of expressed proteins. Of particular interest are mono-genetic diseases resulting from missense mutations affecting the wild type characteristics of a specific protein. Using various cases of disorders, it is demonstrated that almost always the mutations do not directly affect the functional properties of the corresponding protein, but rather indirectly alter its wild type characteristics. This provides an opportunity the disease-causing effect to be tackled with small molecule binding. In addition, it is demonstrated that disease-causing mutations do not necessary destabilize protein stability or protein-protein interactions, but can be stabilizing and still be harmful. Overall, a detailed computational analysis combined with an analysis of the corresponding biological function is needed to make reasonable prediction of the disease association of missense mutations.
Shinshu University, Japan
Title: Emergence of novel CpG island is the key genomic change for the evolution of mammalian genomic imprinting
Time : 12:20-12:40
Shunsuke Suzuki has completed his PhD from Tokyo Institute of Technology in 2006 and postdoctoral studies at Tokyo Medical and Dental University (2006-2009) and The University of Melbourne, Australia (2009-2012). He is now an Assistant Professor (tenure-track) at Epigenomics Division, Frontier Agriscience and Technology Center, Faculty of Agriculture, Shinshu University, Japan. His work is focused on the role of retrotransposons in the evolution of gene regulatory mechanisms in mammals.
Genomic imprinting is an epigenetic mechanism which induces parent-of-origin-dependent expression to subset of genes. In higher vertebrates, genomic imprinting has been found only in viviparous mammals (the eutherians and marsupials) and some imprinted genes have essential functions in fetal and placental development and maternal behavior for post-natal care. Therefore, how genomic imprinting arose during mammalian evolution is of great importance to understand its relevance to the evolution of these mammalian traits. Parent-of-origin-dependent expression of imprinted genes is mostly associated with parental allele-specific DNA methylation of the CpG islands called differentially methylated regions (DMRs). Although the essential role of DMRs for genomic imprinting mechanism has been well established, little is known about how they evolved. Comparative genome analysis in the SGCE-PEG10 domain revealed that PEG10, a retrotransposon-derived imprinted gene essential for placental development, was acquired in the common ancestor of marsupials and eutherians. Furthermore, in the tammar wallaby, both imprinting and differential methylation were restricted to PEG10 unlike eutherians, suggesting that the insertion of PEG10 was the origin of imprinting in this domain. Also, comparative genome analyses in other imprinted domains showed that most DMRs have emerged as novel CpG islands during mammalian evolution. I suppose that the emergence of novel CpG island consequent of retrotransposon insertion was the key genomic change for the acquisition of DMRs that evolved imprinted domains during mammalian evolution.
The Jackson Laboratory for Genomic Medicine, USA
Title: mMAP database and metabolomics data analysis pipeline for mouse functional genomics experiments
Time : 12:40-13:00
Preeti Bais is an associate scientist at the computational sciences group at the Jackson Lab new research institute at University of Connecticut - JAX Genomics Medicine (JGM). It is an independent, nonprofit organization focusing on mammalian genetics research to advance human health. Preeti holds a PhD in bioinformatics and computational biology. She is interested in applying metabolomics for the functional genomics analysis; human embryonic (hES) and induced pluripotent stem (IPS) cells based assays for drug toxicity screening, and cancer drug efficacy testing using orthotropic mouse models of cancer.
Metabolomics is a newer omics technology that can help in generating a more comprehensive view of a biological system when combined with the genomic, transcriptomic and proteomic technologies. However, the bioinformatics infrastructure to analyze and interpret metabolomics data still faces many barriers. For example, there is lack of standardization in nomenclature for metabolites, limited availability of dedicated experiment databases and the lack of metadata reporting standards hamper the reproducibility and sharing of data across researchers, and finally there are very limited automated data analysis pipelines that the researchers can use to incorporate metabolomics data into their research. We present a web based database and automated data analysis pipeline mMAP that addresses these issues for mass spectrometry based metabolomics experiments in mice. mMAP provides metabolomics data and the metadata along with web based automated tools that use many univariate and multivariate data analysis algorithms to generate both tabular and graphical outputs. The portal is linked with other external databases like KEGG, PubMed, LipidMaps, MouseCyc, etc. so a user can make biological interpretation and integrate the metabolomics data with other omics data by generating a list of genes and proteins associated with metabolic pathways of interest. This external database links can also be used to retrieve the Gene Ontology (GO) and Mammalian Phenotype annotations for these genes along with curated disease associations between mouse genes and their human orthologs based on data from the On-Line Mendelian Inheritance in Man (OMIM).
Soochow University, China
Title: Computational biomarker discovery in the big data era: From translational biomedical informatics to systems medicine
Time : 14:00-14:20
Bairong Shen is a professor in Center for Systems Biology of Soochow University. He received his PhD degrees in Chemistry from Fudan University in 1997. He became an associate professor of Physical Chemistry at Fudan University in 1999. He changed his research to bioinformatics as a post-doc in 1999 and became an assistant professor of Bioinformatics at University of Tampere in 2004. He joined Soochow University and established the center for systems biology research in 2008. His recent researches focus on computational analyses of the disease associated systems and translational biomedical informatics.
The biomedical big data era is coming with the accumulation of high throughput biomedical data, especially the next generation sequencing data. It becomes possible to integrate these biomedical data to identify important molecular features for the early diagnosis, prognosis and treatment of complex diseases. We may face many challenges for the integration and modeling of these heterogeneous and even non-structural data, such as 1) the modeling and simulation of the heterogeneous data at a systems network level; 2) the collection of paired biological and personalized medical data to reconstruct personalized models for the precise diagnosis, prognosis and treatment of complex diseases. To take the advantage of these biomedical data and overcome these challenges as well as promote the application of informatics to translational research, we take prostate cancer as a case study and applied novel biomedical informatics methods to the integration and analysis of prostate cancer associated data to identify the putative prostate cancer biomarkers for diagnosis and prognosis, the identified biomarkers were further validated by experimental and informatics analysis. We concluded that, in the big data ear, the translational biomedical informatics will become the driver for discovery of biomarkers for complex diseases.
Chung -Shan Medical University, Taiwan
Time : 14:20-14:40
Y.C. Li has completed her Ph.D from Tsing-Hua University, Taiwan in 2002 and postdoctoral studies from Fox Chase Cancer Center, PA in 2003-2004. She is the professor of Chung-Shan Medical University, Taiwan since 2006. She has published more than 35 papers in reputed journals. She has been endowed herself in studying the role of mammalian centromeric satellite DNAs families in karyotype evolution and centromeric function for the past several years. Recently, she is interested in the comparative genomic studies.
It has been proposed that pericentromeric satellite DNA arises from the progressive proximal expansion of ancient centromeric DNA. We recently isolated a novel cervid satellite DNA element (designated as satVI) in a mini-library that was generated from the microdissected pericentromeric/centromeric DNA of the chromosome X+3 of Indian muntjac. SatVI is organized as 11 bp-monomeric (ATCACGTGGGA) tandem repeats. Its repeats have approximately 5 kb in length along with approximately 3 kb of interspersed repetitive sequences in an Indian muntjac BAC clone and stretch over approximately 850 kb in the Indian muntjac genome. FISH studies revealed that satVI is predominately located on the distal pericentromeric region of the Indian muntjac chromosome X+3 and on the pericentromeres of several Old World deer species studied. SatVI is also presented in the genome of Bovidae and Suidae. Based on the chromosomal localization, genomic and sequence organization, and copy numbers of satVI in species studied, we postulate that this newly found satVI DNA could be a putative ancient cervidic centromeric DNA that may already be preserved in the ancestor of the Artiodactyla family. Interestingly, many monomers of satVI harbor the identical yeast CDEI sequences. Several zipper-like d(GGGA)2 motifs were also found in the (ATCACGTGGGA)n repeat of satVI DNA. Whether the satVI is structurally and functionally correlated with the CDEI of centromere of the budding yeast and whether a zipper-like structure in satVI has any significant role, both require further studies.
Shanghai Biotechnology Corporation, China
Time : 14:40--15:00
Yuhua Li completed her PhD degree from Peking Union Medical College and MD from Zhengzhou University. She also received postdoctoral trainings from University of Pennsylvanian and Georgia Tech. She is the Assistant General Manager and in charge of Global Marketing & Business Development at Shanghai Biotechnology Corporation (SBC). She used to be the QA Director of SBC, VP of Otogenetics Corporation, Director of Yerkes Microarray Core Facility at Emory University and Research Scientist in Georgia Tech. She has more than 50 publications and supported hundreds of genomics projects.
Shanghai Biotechnology Corporation (SBC), a subsidiary of Shanghai Biochip Co., Ltd. /National Engineering Center for Biochip at Shanghai, is a leading global CRO genomics service provider in China. SBC offers full services for biomarker discovery and validation with technologies of microarray analysis, next generation sequencing, qPCR, molecular pathology and bioinformatics/biostatistics, etc. In China, SBC is the first service provider certified by Affymetrix, the only microarray service provider certified by Agilent, Illumina Certified Service Provider (CSPro), and SOLID Demo Lab certified by ABI. SBC has completed more than 5000 projects for more than 1500 clients including the top ten pharmaceutical companies. Our team and clients have published more than 500 papers on SCI. We have extensive experience with technologies in genomics and pharmacogenomics analysis, and have developed real-world solutions to incorporate biomarker testing into preclinical and clinical studies, meet the highest regulatory standards and aid in timely execution of biomarker discovery project.
The Jackson Laboratory, USA
Time : 15:00-15:20
Mei Xiao has completed her Ph.D from UMass/Boston and postdoctoral studies from University of Calgary. She is a senior software engineer of the Jackson Laboratory, a premier mammalian genetics research organization. She is interested in artificial intelligence, human-computer interaction and data visualization, bio-medical image analysis and bioinformatics.
Monitoring phenotype changes and linking them with potential genetic mutations has becoming an important tool for building disease models and developing biomarkers and disease diagnosis methods. Phenotypic analysis of tissue changes demands automated, high-throughput image analysis tools in communities such as human health informatics and mammalian genetic communities. Image alignment is an essential step to remove image distortions caused by experiment subjects movements and device system noise. Analyzing the aligned images is also important for comparing tissue changes over time. We will discuss two image alignment technologies here. First, technological breakthroughs in the fields of electronics and wireless communication will allow real-time monitoring of the human body movements and vital signals. Putting landmarks onto the captured human tissue models for further statistical shape analysis is a powerful tool to find the covariance of the organisms phenotype changes. Second, intensity based image alignment will allow us to remove image distortions caused by tissue movements and capture device background noise. For example, we can use the optical coherence tomography technology (OCT) to capture retina images of a large amount of experimental subjects. Despite the high resolution and noninvasive imaging, OCT suffers poor penetration depth through tissues and speckle noise. Aligning the repeatedly captured images will allow us to average the intensities to create shaper images to reveal more detailed tissue structures and changes.