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History


         Conceived by Dr. Marshall Anderson (Director, Department of Environmental Health) and Dr. Ranjan Deka (Professor and Director of Division of Biostatistics and Epidemiology at the Department of Environmental Health), and supported by Dr. John Hutton (Dean of the College of Medicine, University of Cincinnati) and Dr. Donald Harrison (Senior Vice President and Provost, University of Cincinnati), the Center for Genome Information was established in Fall 2001 at the Department of Environmental Health of the University of Cincinnati College of Medicine at Cincinnati, Ohio. This was made possible with the recruitment of Dr. Ranajit Chakraborty, an internationally well known statistical geneticist and genetic epidemiologist, who brought with him a research team consisting of two faculty members and their associated research staff. Housed in two floors of the Kettering Laboratory of the medical center campus of the University of Cincinnati, currently the Center occupies a space of over 3,700 sq. ft. in two floors of the building. In addition of directing the Center, Dr. Chakraborty is also the Robert A. Kehoe Professor at the Department of Environmental Health. Current faculty members of the Center include Dr. Li Jin (Professor and Director of the Core Laboratory), Dr. Ranjan Deka (Professor and Team leader of Population Studies), Dr. Bing Su (Research Assistant Professor engaged in Comparative Genomic Studies), Dr. Mario Medevedovic (Research Assistant Professor working on interpretation and modeling of gene expression data); with a supporting research staff of 24 persons. The components of the Center already in operation include: a high throughput genotyping and sequencing laboratory, a comparative genomics laboratory, gene expression laboratory, cell line facility, genomic marker laboratory for population- and family-based studies, and a computational biology laboratory.

         Within the six months of establishment of the Center, the high-throughput laboratories and gene expression laboratories are already in operation (with a capability of producing nearly 100,000 genotyping per day), the computer server at the computational biology laboratory is equipped with all necessary software for genome- wide linkage and gene discovery algorithms, and a number of new computational routines have been written to search sequence databases for gene discovery between specified mapped genetic markers of the human genome, and to conduct fast and precise deconvolution analysis of multi-site genotype data to gather haplotype information at individual as well as population level. In addition, CGI has also initiated a number of projects and collaborations with researchers at the campus, as well as with collaborators at national and international level. New NIH projects funded from such collaborations include studies on genetic and environmental risk factors for hemorrhagic stroke (PI: Joseph P. Broderick, Professor and Chairman of the Department of Neurology at the UC College of Medicine), sequence variation and association with cancer susceptibility (PI: David Nelson, Baylor College of Medicine, Houston, Texas), and genetic susceptibility of scleroderma (PI: Frank Arnett, University of Texas Medical School at Houston, Texas). In addition, the center faculties have also been instrumental in submitting projects for studying early detection of lung cancer (PI: Marshall Anderson, Department of Environmental Health), immunogenetics and biomarkers of the asthma phenotype (PI: Gurjit K. Khurana Hershey, Children's Hospital Medical Center), and population genomics of inhabitants of North Adriatic Islands (PI: Ranjan Deka).

         Even at this young stage of the development of the Center, CGI has gained national and as well as international attention. Examples of these include: Dr. Chakraborty being selected to be a member of the Advisory Board to Celera Genomics for victim identification of the World Trade Center episode of September 11, 2001; invited presentation of Dr. Chakraborty on novel methods of analyzing multilocus genomic data at the International Symposium on "Evolutionary Genomics" at Atami, Japan (November 4-6, 2001), organized by the National Institute of Genetics, Mishima, Japan; keynote presentations on strategies for studying complex diseases by Drs. Chakraborty and Deka at the "Symposio International – Ciencias Genómicas y Salud" (February 1-2, 2002) at the University of Guadalajara, Mexico; and CGI researchers under the direction of Dr. Chakraborty being selected to annotate the full-length cDNA sequences of the entire human genome in collaboration with an international team organized by the Center for Information Biology (CIB) and Japan Biological Research Center (JRIRC) of Japan (agreement reached in March 2002). Dr. Li Jin has also established research ties with the Fudan University Medical School and Genome Centers at PRC, China, for which an initial meeting for formalizing collaborative work is scheduled in mid-April 2002, when the CGI researchers will be visiting Shanghai being invited by the Chinese genome researchers.

         Some of the current research activities of the Center include:

  •     Development of robust techniques of haplotype inference from multilocus genotype data on sites exhibiting Single Nucleotide Polymorphism (SNP);
  •     Detecting and distinguishing signatures of recombination and recurrent mutations at SNP sites;
  •     Incorporation of mutation models more realistic (and perhaps more complex) than the currently used ones, e.g., the infinite site model, single step stepwise mutation model, by taking into account factors like finite number of allelic states (not necessarily bi- allelic), and transition/transversion bias of mutations;
  •     Study of evolutionary dynamics of disease-gene association measures in populations with various models of past demographic history;
  •     Study of relative efficiencies of different sampling designs for studying etiology of complex diseases, including gene-gene and gene-environment interaction using the context of the phenotype as well as population-history of the study samples;
  •     Development of more refined computational techniques of interpretation of gene expression data for functional genomic studies;
  •     Initiation of comprehensive whole genome analysis of all members of specific isolated populations for the purpose of applying the above analytical techniques for a better understanding of etiology of complex diseases; and
  •     Study of pattern of genome diversity using microsatellite, SNP as well as sequence data.

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