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


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


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


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


DNA•Phosphate and Deoxyribose Backbone

•Adenine binds with thyamine

•Cytosine binds with guanine


Ratios of Bases


Arrangement

DNA is doubled and twisted to form a double helix


Double Helix


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


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


DNA Replication


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


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


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


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


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


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


Mutations


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


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


Core Bioinformatics Technologies Bioinformatics-analysis of Genomic data

Database systems Engineering Mathematical Analysis Computational


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


Sequence Alignment

Most fundamental computational algorithm Goals

Accept two or more sequences Identify similar sequences Output sequences with the similar positions

aligned in columns


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


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


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


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


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


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


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


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


The End

Questions? Comments? Arguments? Rebuttal? Discourses? Problems? Issues Queries?

Genomics and Bioinformatics

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