Download - Genomics and Bioinformatics
Genomics and Bioinformatics
Gabriel CapBiomedical Engineering Survey
Wednesday, March 1, 2006
Wednesday, March 1, 2006 Chapter 13: Genomics and Bioinformatics 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
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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
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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
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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
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DNA•Phosphate and Deoxyribose Backbone
•Adenine binds with thyamine
•Cytosine binds with guanine
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Ratios of Bases
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Arrangement
DNA is doubled and twisted to form a double helix
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Double Helix
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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
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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
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DNA Replication
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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
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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
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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
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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
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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
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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
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Mutations
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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
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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
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Core Bioinformatics Technologies Bioinformatics-analysis of Genomic data
Database systems Engineering Mathematical Analysis Computational
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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
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Sequence Alignment
Most fundamental computational algorithm Goals
Accept two or more sequences Identify similar sequences Output sequences with the similar positions
aligned in columns
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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
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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
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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
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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
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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
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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
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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
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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
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The End
Questions? Comments? Arguments? Rebuttal? Discourses? Problems? Issues Queries?