Transcript Opportunities in Bioinformatics for Computer - People

Opportunities in Bioinformatics
for Computer Science
Lenwood S. Heath
Virginia Tech
Blacksburg, VA 24061
[email protected]
University of Iowa
November 16, 2001
November 16, 2001
Slide 1
Overview
• The New Biology
• Existing bioinformatics tools
• Bioinformatics challenges
• Bioinformatics at Virginia Tech
November 16, 2001
Slide 2
Some Molecular Biology
• The instruction set for a cell is contained in its
chromosomes.
• Each chromosome is a long molecule called DNA.
• Each DNA molecule contains 100s or 1000s of genes.
• Each gene encodes a protein.
• A gene is transcribed to mRNA in the nucleus.
• An mRNA is translated to a protein in a ribosome.
November 16, 2001
Slide 3
Transcription and Translation
Transcription
DNA
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Translation
mRNA
Protein
Slide 4
Elaborating Cellular Function
Regulation
Degradation
Transcription
DNA
Translation
mRNA
(Genetic Code)
Protein
Reverse
Transcription
Functions:
• Structure
• Catalyze chemical reactions
• Respond to environment
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Slide 5
Chromosomes
• Long molecules of DNA: 10^4 to 10^8 base pairs
• 26 matched pairs in humans
• A gene is a subsequence of a chromosome that
encodes a protein.
• Proteins associated with cell function, structure,
and regulation.
• Only a fraction of the genes are in use at any
time.
• Every gene is present in every cell.
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Slide 6
DNA Strand
A= adenine complements T= thymine
C = cytosine complements G=guanine
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Slide 7
Complementary DNA Strands
Double-Stranded DNA
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Slide 8
RNA Strand
U=uracil replaces T= thymine
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Slide 9
Amino Acids
• Protein is a large molecule that is a chain of
amino acids (100 to 5000).
• There are 20 common amino acids
(Alanine, Cysteine, …, Tyrosine)
• Three bases --- a codon --- suffice to encode
an amino acid.
• There are also START and STOP codons.
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Slide 10
Genetic Code
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Slide 11
Translation to a Protein
Unlike DNA, proteins have three-dimensional structure
Protein folds to a three-dimensional shape that
minimizes energy
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Slide 12
Cell’s Fetch-Execute Cycle
• Stored Program: DNA, chromosomes, genes
• Fetch/Decode: RNA, ribosomes
• Execute Functions: Proteins --- oxygen
transport, cell structures, enzymes
• Inputs: Nutrients, environmental signals,
external proteins
• Outputs: Waste, response proteins, enzymes
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Slide 13
The Language of the New
Biology
A new language has been created. Words in the
language that are useful for today’s talk.
Genomics
Functional Genomics
Proteomics
cDNA microarrays
Global Gene Expression Patterns
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Slide 14
Genomics
•Discovery of genetic sequences and the ordering of
those sequences into
• individual genes;
• gene families;
• chromosomes.
• Identification of
• sequences that code for gene products/proteins;
• sequences that act as regulatory elements.
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Slide 15
Genome Sequencing Projects
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Drosophila
Yeast
Mouse
Rat
Arabidopsis
Human
Microbes
…
November 16, 2001
Slide 16
Drosophila Genome
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Slide 17
Functional Genomics
• The biological role of individual genes;
• mechanisms underlying the regulation of their
expression;
• regulatory interactions among them.
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Slide 18
Glycolysis, Citric Acid Cycle, and
Related Metabolic Processes
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Slide 19
Gene Expression
• Only certain genes are “turned on” at any particular
time.
• When a gene is transcribed (copied to mRNA), it is
said to be expressed.
• The mRNA in a cell can be isolated. Its contents give
a snapshot of the genes currently being expressed.
• Correlating gene expressions with conditions gives
hints into the dynamic functioning of the cell.
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Slide 20
Gene Expression:
Control Points
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Slide 21
Free Radicals
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Slide 22
Responses to Environmental Signals
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Slide 23
Effects of Drought Stress
Virginia Tech:
Plant Biologists: Ruth Alscher, Boris Chevone.
CS: Lenny Heath, Naren Ramakrishnan, and colleagues.
Statistics: Ina Hoeschele, Shun-Hwa Li.
NC State (Forest Biotechnology):
Ying-Hsuan Sun, Ron Sederoff, Ross Whetten
November 16, 2001
Slide 24
Intracellular Decision Making
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Slide 25
Relative Abundance
Detection
Detection
Treatment
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Control
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Mix
Spots: 1
2
(Sequences affixed to slide)
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3
Hybridization
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Slide 26
Gene Expression Varies
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Slide 27
Existing Computational Tools
in Bioinformatics
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Sequence similarity
Multiple sequence alignments
Database searching
Evolutionary (phylogenetic) tree construction
Sequence assemblers
Gene finders
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Slide 28
Challenges for Bioinformatics
• Analyzing and synthesizing complex
experimental data
• Representing and accessing vast quantities
of information
• Pattern matching
• Data mining
• Gene discovery
• Function discovery
• Modeling the dynamics of cell function
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Slide 29
Bioinformatics at Virginia Tech
Computer science interacts with the life sciences.
• Computer Science in Bioinformatics:
• Joint research with: plant biologists, microbial
biologists, biochemists, cell-cycle biologists, animal
scientists, crop scientists, statisticians.
• Projects: Expresso; Nupotato; MURI; Arabidopsis
Genome; Barista; Cell-Cycle Modeling
• Graduate option in bioinformatics
• Virginia Bioinformatics Institute (VBI)
November 16, 2001
Slide 30
Expresso: A Problem Solving
Environment (PSE) for Microarray
Experiment Design and Analysis
• Integration of design and procedures
• Integration of image analysis tools and statistical
analysis
• Data mining using inductive logic programming
(ILP)
• Closing the loop
• Integrating models
November 16, 2001
Slide 31
Flow of a Microarray Experiment
PCR
Select cDNAs
Replication and
Randomization
Robotic Printing
Hypotheses
Identify Spots
Intensities
Statistics
Hybridization
Test of
Hypotheses
Extract RNA
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Clustering
Reverse
Transcription and
Fluorescent
Labeling
Data Mining, ILP
Slide 32
Expresso: A Microarray Experiment
Management System
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Slide 33
Nupotato
• Potatoes originated in the Andes, where
there are many varieties.
• Many varieties survive at high altitude in
cold, dry conditions.
• Microarray technology can be used to
investigate genes that are responsible for
stress resistance and that are responsible for
the production of nutrients.
November 16, 2001
Slide 34
MURI
• Some microorganisms have the ability to
survive drying out or intense radiation.
• Their genomes are just being sequenced.
• Using microarrays and proteomics, we will
try to correlate computationally the genes in
the genomes with the special traits of the
microorganisms.
• We are currently using multiple genome
analysis.
November 16, 2001
Slide 35
Arabidopsis Genome Project
• Arabidopsis is a model higher plant.
• It is the first higher plant whose genome has
been fully sequenced.
• Gene finder software has been used to
identify putative genes.
• We are computationally mining the
regulatory regions of these genes for
promoter patterns.
November 16, 2001
Slide 36
Barista
• Barista serves Expresso!
• Software development team across projects
to minimize duplication of effort.
• Work with Linux, Perl, C, Python, cvs,
Apache, PHP, …
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Slide 37
Virginia Bioinformatics
Institute (VBI)
• Research institute based at Virginia Tech
• Established July 1, 2000, with $3 million
• Will occupy 2 building and have 100+
employees in 4 years
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Slide 38
Getting Into Bioinformatics
• Learn some biology --- genetics, cell
biology
• Study computational (molecular) biology
• Get involved with bioinformatics research
in interdisciplinary teams
• Work with biologists to solve their problems
November 16, 2001
Slide 39