* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download The World of Microbes on the Internet
Extrachromosomal DNA wikipedia , lookup
Gene expression programming wikipedia , lookup
Gene therapy wikipedia , lookup
Ridge (biology) wikipedia , lookup
Synthetic biology wikipedia , lookup
Medical genetics wikipedia , lookup
Genomic imprinting wikipedia , lookup
Transposable element wikipedia , lookup
Quantitative trait locus wikipedia , lookup
No-SCAR (Scarless Cas9 Assisted Recombineering) Genome Editing wikipedia , lookup
Point mutation wikipedia , lookup
Vectors in gene therapy wikipedia , lookup
Epigenetics of neurodegenerative diseases wikipedia , lookup
Epigenetics of human development wikipedia , lookup
Pharmacogenomics wikipedia , lookup
Nutriepigenomics wikipedia , lookup
Human genetic variation wikipedia , lookup
Oncogenomics wikipedia , lookup
Therapeutic gene modulation wikipedia , lookup
Whole genome sequencing wikipedia , lookup
Gene expression profiling wikipedia , lookup
Biology and consumer behaviour wikipedia , lookup
Genetic engineering wikipedia , lookup
Genomic library wikipedia , lookup
Metagenomics wikipedia , lookup
Helitron (biology) wikipedia , lookup
Non-coding DNA wikipedia , lookup
Pathogenomics wikipedia , lookup
Site-specific recombinase technology wikipedia , lookup
Minimal genome wikipedia , lookup
Human genome wikipedia , lookup
Human Genome Project wikipedia , lookup
Designer baby wikipedia , lookup
History of genetic engineering wikipedia , lookup
Genome (book) wikipedia , lookup
Microevolution wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Genome editing wikipedia , lookup
Genome evolution wikipedia , lookup
Bioinformatics Genomic Biology as a Quantitative Science Stuart M. Brown, Ph.D. Director, Research Computing, NYU School of Medicine A Genome Revolution is underway in Biology and Medicine We are in the midst of a "Golden Era" of biology The Human Genome Project has produced a huge storehouse of data that will be used to change every aspect of biological research and medicine The revolution is about treating biology as an information science, not about specific technologies. The Human Genome Project The job of the biologist is changing As more biological information becomes available and laboratory equipment becomes more automated ... – The biologist will spend more time using computers & on experimental design and data analysis (and less time doing tedious lab biochemistry) – Biology will become a more quantitative science (think how the periodic table affected chemistry) Biological Information Protein 2-D gel mRNA Expression Protein 3-D Structure Mass Spec. Genome sequence The Cell A review of some basic genetics DNA 4 bases (G, C, T, A) base pairs G--C T--A genes non-coding regions Decoding Genes Classic Molecular Biology A gene is a DNA sequence at a particular locus on a chromosome that encodes a protein. The Central Dogma of Molecular Biology: DNA ––—> RNA ——> Protein A mutation changes the DNA sequence - leads to a change in protein sequence - or no protein. Alleles are slightly different DNA sequences of the same gene. The human genome is the the complete DNA content of the 23 pairs of human chromosomes - 44 autosomes plus two sex chromosomes - approximately 3.2 billion base pairs. Bold Words from Francis Collins: “The history of biology was forever altered a decade ago by the bold decision to launch a research program that would characterize in ultimate detail the complete set of genetic instructions of the human being.” Francis S. Collins Director of the National Human Genome Research Institute N Engl J Med 1999 882:42-65 Genome Projects Complete genomic sequences: – Dozens of microorganisms – Yeast, C. elegans, Drosophila – Mouse – Human Comparative genomics All this data is enabling new kinds of research for those with the computational skills to take advantage of it. How does genome sequencing technology work? Molecular biology of the Sanger method Sub-cloning of fragments - BAC, PAC, cosmid, plasmid, phage Automated sequencers The need for computers to assemble the "reads" and manage the workflow Automated sequencing machines, particularly those made by PE Applied Biosystems, use 4 colors, so they can read all 4 bases at once. Raw Genome Data: Lots of Sequence Data How to extract useful knowledge from all of this data? Need sophisticated computer tools – – – – Find the genes Figure out what they do (function) Diagnostic tests Medical treatments Finding genes in genome sequence is not easy About 1% of human DNA encodes functional genes. Genes are interspersed among long stretches of non-coding DNA. Repeats, pseudo-genes, and introns confound matters Gene prediction tools - look for Start and Stop codons, intron splice sites, similarity to known genes and cDNAs, etc. Data Mining Tools Scientists need to work with a lot of layers of information about the genome – – – – – coding sequence of known genes and cDNAs genetic maps (known mutations and markers) gene expression Protein sequence (from Mass Spectroscopy) cross species homology Most of the best tools are free on the Web UCSC Ensembl at EBI/EMBL What comes after Genome Sequencing? We are now in the "Post-Genomic" era. It is possible to use the genome sequence plus a variety of automated laboratory equipment to do entirely new kinds of biology. Not just scaled-up, but comprehensive Relate genes to Organisms Diseases – OMIM: Human Genetic Disease Metabolic and regulatory pathways – KEGG – Cancer Genome Project Human Alleles The OMIM (Online Mendelian Inheritance in Man) database at the NCBI tracks all human mutations with known phenotypes. It contains a total of about 2,000 genetic diseases [and another ~11,000 genetic loci with known phenotypes - but not necessarily known gene sequences] It is designed for use by physicians: – can search by disease name – contains summaries from clinical studies KEGG: Kyoto Encylopedia of Genes and Genomes Enzymatic and regulatory pathways Mapped out by EC number and crossreferenced to genes in all known organisms (wherever sequence information exits) Parallel maps of regulatory pathways Genomics What is Genomics? – An operational definition: • The application of high throughput automated technologies to molecular biology. – A philosophical definition: • A wholistic or systems approach to the study of information flow within a cell. Genomics Technologies Automated DNA sequencing Automated annotation of sequences DNA microarrays – gene expression (measure RNA levels) SNP Genotyping – Genome diagnostics (genetic testing) Proteomics – Protein identification – Protein-protein interactions DNA chip microarrays Put a large number (~100K) of cDNA sequences or synthetic DNA oligomers onto a glass slide (or other substrate) in known locations on a grid. Label an RNA sample and hybridize Measure amounts of RNA bound to each square in the grid Make comparisons – Cancerous vs. normal tissue – Treated vs. untreated – Time course Many applications in both basic and clinical research Spot your own Chip (plans available for free from Pat Brown’s website) Robot spotter QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. Ordinary glass microscope slide cDNA spotted microarrays Goal of Microarray experiments Microarrays are a very good way of identifying a bunch of genes involved in a disease process – Differences between cancer and normal tissue – Tuberculosis infected vs resistant lung cells Mapping out a pathway – Co-regulated genes Finding function for unknown genes – Involved these processes Direct Medical Applications Diagnosis – Type of cancer – Aggressive or benign? Monitor treatment outcome – Is a treatment having the desired effect on the target tissue? When you go looking… …you will certainly find something! Human Genetic Variation Every human has essentially the same set of genes But there are different forms of each gene -- known as alleles – blue vs. brown eyes – genetic diseases such as cystic fibrosis or Huntington’s disease are caused by dysfunctional alleles Alleles are created by mutations in the DNA sequence of one person - which are passed on to their descendants Clinical Manifestations of Genetic Variation (All disease has a genetic component) Susceptibility vs. resistance Variations in disease severity or symptoms Reaction to drugs (pharmacogenetics) All of these traits can be traced back to particular genes (or sets of genes) Pharmacogenomics People react differently to drugs – Side effects – Variable effectiveness There are genes that control these reactions SNP markers can be used to identify these genes (profiles) Use the Profiles Genetic profiles of new patients can then be used to prescribe drugs more effectively & avoid adverse reactions. – Sell a drug with a gene test Can also speed clinical trials by testing on those who are likely to respond well. Toxicogenomics There are a number of common pathways for drug toxicity (or environmental tox. ) It is possible to compile genomic signatures (gene expression data) for these pathways. Candidate drug molecules can be screened in cell culture or in animals for induction of these toxicity pathways. Planning for a Genomics Revolution Bioinformatics support must be integral in the planning process for the development of new genomics research facilities. Genome Project sequencing centers have more staff and more $$$ spent on data analysis than on the sequencing itself. Microarray facilities will be even more skewed toward data analysis It is an information-intensive business! Implications for Biomedicine Physicians will use genetic information to diagnose and treat disease. » Virtually all medical conditions have a genetic component. Faster drug development research » Individualized drugs » Gene therapy All Biologists will use gene sequence information in their daily work Training "computer savvy" scientists Know the right tool for the job Get the job done with tools available Network connection is the lifeline of the scientist Jobs change, computers change, projects change, scientists need to be adaptable Long Term Implications A "periodic table for biology" will lead to an explosion of research and discoveries we will finally have the tools to start making systematic analyses of biological processes (quantitative biology). Understanding the genome will lead to the ability to change it - to modify the characteristics of organisms and people in a wide variety of ways Genomics Education Genomics scientists need basic training in both Molecular Biology and Computing Specific training in the use of automated laboratory equipment, the analysis of large datasets, and bioinformatics algorithms Particularly important for the training of medical doctors - at least a familiarity with the technology Genomics in Medical Education “The explosion of information about the new genetics will create a huge problem in health education. Most physicians in practice have had not a single hour of education in genetics and are going to be severely challenged to pick up this new technology and run with it." Francis Collins Bioinformatics: A Biologist's Guide to Biocomputing and the Internet Stuart M. Brown, Ph.D. [email protected] www.med.nyu/rcr