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Genomics and Bioinformatics

Genomics and Bioinformatics. Gabriel Cap Biomedical Engineering Survey Wednesday, March 1, 2006. Outline. Basic principles of molecular biology Major types of data in genome projects Practical applications and uses of genomic data

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Genomics and Bioinformatics

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  1. Genomics and Bioinformatics Gabriel Cap Biomedical Engineering Survey Wednesday, March 1, 2006

  2. Outline • Basic principles of molecular biology • Major types of data in genome projects • Practical applications and uses of genomic data • Understanding the major topics in the field of bioinformatics and DNA sequence analysis • Learn about key bioinformatics databases and web resources Chapter 13: Genomics and Bioinformatics

  3. Introduction • Genomic Era • In April 2003 the human genome was sequenced • 3 billion nucleotides • Importance? • 1631 human genetic diseases are associated with known DNA sequences • Only 100 known before genome was sequenced Chapter 13: Genomics and Bioinformatics

  4. Genomic Era • Human Genome not the only item to be sequences • The complete genomes were available for many items • 1557 viruses • 165 microbes • 26 eukaryotes • Yeast • Rice Chapter 13: Genomics and Bioinformatics

  5. Genomes • Important so that genes can be compared in order to eliminate deadly threats • Advance in technologies are needed • Speed up pace • Reduce expense • Methods to interpret data • Applications to medicine Chapter 13: Genomics and Bioinformatics

  6. DNA • Phosphate and Deoxyribose Backbone • Adenine binds with thyamine • Cytosine binds with guanine Chapter 13: Genomics and Bioinformatics

  7. Ratios of Bases Chapter 13: Genomics and Bioinformatics

  8. Arrangement • DNA is doubled and • twisted to form a • double helix Chapter 13: Genomics and Bioinformatics

  9. Double Helix Chapter 13: Genomics and Bioinformatics

  10. Background • DNA to RNA to Protein • 3 Steps • Storing Genetic Information • Processing Information • Transmitting Information from parent to offspring • Genetic Information Stored in DNA • Deoxyribose sugar • Genome size has some effect on organism complexity • Genes to Protein • Not a one to one ratio, one gene does not mean 1 protein • Single lines can produce multiple genes Chapter 13: Genomics and Bioinformatics

  11. Genes to Proteins • Transcription of DNA • RNA Polymerase binds to gene • Creates RNA Molecule • This mRNA will serve as template for protein • Introns and Extrons help split up the sequence to isolate certain strands • Translation of RNA • Reads the mRNA template • Produces Protein Chapter 13: Genomics and Bioinformatics

  12. DNA Replication Chapter 13: Genomics and Bioinformatics

  13. Protein Translation • Nucleotides line up in protein • Group up in codons (3) • Ribosomes interact with tRNA to interpret codon • Each codon encodes one amino acid • 20 amino acids make up the protein Chapter 13: Genomics and Bioinformatics

  14. Core Laboratory Technologies • Genome science driven by advances in order to allow for rapid and inexpensive data collection techniques • 3 Prominent Uses • Provide the starting point to understand the underpinnings of an organism • Facilitate studies of gene regulation • Understanding the variation between different species Chapter 13: Genomics and Bioinformatics

  15. Gene Sequencing • The most widely used sequencing technique • Reporter attached to nucleotide and speed measured as it travels through a medium • DNA sequences have an orientation • 5’ left end • 3’ right end • Through a series of tests one can complete the target sequence Chapter 13: Genomics and Bioinformatics

  16. Sanger Sequencing • Uses fluorescent dyes to mark nucleotides • Laser based systems read the sequences • Modern devices can read 800 nucleotides at a time • Graphs and statistical analysis produce results of which bases are at each position • Also give error probably for each site • A single DNA sequencer can produce 1,000,000 nucleotides per day Chapter 13: Genomics and Bioinformatics

  17. Whole Genome Sequencing • Shotgun Sequencing for large regions of DNA • Copy genome • Randomly cut genome into fragments • Align the overlapping fragments • Read the complete genome sequence by following a gap free path Chapter 13: Genomics and Bioinformatics

  18. Gene Expression • Uses to survey the abundance of the gene products • Microarray Experiment • Compare normal tissue and tumor tissue • Look for differences in genes in biological process • Time Course Experiment • The change in expression is measured against time • Groups are formed where they experience an increase or decrease in expression levels Chapter 13: Genomics and Bioinformatics

  19. Mutations Chapter 13: Genomics and Bioinformatics

  20. Diagnosis • If gene expression matches reference samples • Patient can be diagnosed • Microarray technology has greatly improved accuracy of diagnosis • Types of Gene Sequencing • cDNA microarrays • Creation of microarray slide • Oligonucleotide arrays Chapter 13: Genomics and Bioinformatics

  21. Polymorphisms • Variations from individual to individual • SNP Consortium • Characterized 1.8 million polymorphisms in humans • Should help accelerate the process of the description of genetic diseases • Simple Sequence Repeats also used Chapter 13: Genomics and Bioinformatics

  22. Core Bioinformatics Technologies • Bioinformatics-analysis of Genomic data • Database systems • Engineering • Mathematical Analysis • Computational Chapter 13: Genomics and Bioinformatics

  23. Genomics Databases • Project data from scientific community available • National Center for Biotechnology Information • Contains Genbank of DNA and RNA sequences • Has BLAST database searching tools • Uses algorithms to find sequence alignments in Chapter 13: Genomics and Bioinformatics

  24. Sequence Alignment • Most fundamental computational algorithm • Goals • Accept two or more sequences • Identify similar sequences • Output sequences with the similar positions aligned in columns Chapter 13: Genomics and Bioinformatics

  25. Uses of Sequence Alignment • Uses • Determine whether sequences have similar functions • Shows patterns of similarity • Can infer history of species • Reconstruct sequences in ancestral organisms • Can pick which parts have been added or deleted Chapter 13: Genomics and Bioinformatics

  26. Database Searching • Searching GenBank for sequences that are similar to a sequence of interest • Most common bioinformatics task • Can help narrow down what type of disease or what similar types of viruses are formed from strand Chapter 13: Genomics and Bioinformatics

  27. Hidden Markov Models • HMMs are a class of mathematic tools • Identify important regions • Genes • Binding sites • Come in the form of relatively short contiguous blocks of DNA • Proved to be an excellent tool for identifying genes in newly sequenced genomes • Can determine which nucleotides are in each region Chapter 13: Genomics and Bioinformatics

  28. Gene Prediction • Purpose • Take a long sequence of DNA • Identify the locations of genes • Identify start and stop codons • Problems • Could lead to a high false positive rate • HMMs also very suited for gene finding • Gene finding algorithms Chapter 13: Genomics and Bioinformatics

  29. Functional Annotation • Once genome is sequenced • The biological function of the genes is determined • Two approaches for function are used • Comparative Genomics • HMMs • Database comparisons are used to determine other genes with similar functions • Genes compared to proteins in the PFAM database Chapter 13: Genomics and Bioinformatics

  30. Identifying Differentially Expressed Genes • Two different “treatments” used to compare two types of tissue • Technologies • Microarray • Oligonucleotide • Genes leave spots on microarray so they can provide measurements of gene expressions • These results are graphed an analyzed Chapter 13: Genomics and Bioinformatics

  31. Clustering Genes • Used to identify sets of genes that respond to two or more treatments • Used in time course study • Expression levels are measured at specific intervals • Plots produced and compared Chapter 13: Genomics and Bioinformatics

  32. Conclusion • Genomic Science opened the door for new technology • Started the wave of using computers for analysis • Diagnostic Procedures are changing due to genomics • More medicines will develop from our studies in genomics • Gene therapies are the next step to allow for repair of genetic defects Chapter 13: Genomics and Bioinformatics

  33. The End • Questions? • Comments? • Arguments? • Rebuttal? • Discourses? • Problems? • Issues • Queries? Chapter 13: Genomics and Bioinformatics

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