Download Gene Finding

Gene Finding
•Based partly on slides by Hedi Hegyi, Irene Liu
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“The Central Dogma”
Transcription
Translation
RNA
Protein
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Gene Finding in Prokaryotes
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Reminder: The Genetic Code
1 start, 3 stop Codons
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Finding Genes in Prokaryotes
Gene structure
High gene density
– ~85% coding in E.coli
=> is every ORF a gene?
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Finding ORFs
Many more ORFs than genes
– In E.Coli one finds 6500 ORFs while there are 4290 genes.
In random DNA, one stop codon every 64/3=21
codons on average.
Average protein is ~300 codons long.
=> search long ORFs.
Problems:
– Short genes
– Overlapping long ORFs on opposite strands
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Codon Frequencies
Coding DNA is not random:
– In random DNA, expect Leu : Ala : Trp ratio of
6:4:1
– In real proteins, 6.9 : 6.5 : 1
Different frequencies for different species.
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Using Codon Frequencies/Usage
Assume each codon is independent.
For codon abc calculate frequency
f(abc) in coding region.
Given coding sequence a1b1c1,…,
an+1bn+1cn+1
Calculate p1  f a b c  f a b c  ...  f a b c
1 1 1
2 2 2
n n n
p2  f b1c1a2  f b2c2a3  ...  f bncnan 1
p3  f c1a2b2  f c2a3b3  ...  f cnan 1bn 1
The probability that the ith reading
pi
frame is the coding region: Pi 
p1  p2  p3
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C+G Content
C+G content (“isochore”) has strong effect
on gene density, gene length etc.
– < 43% C+G : 62% of genome, 34% of genes
– >57% C+G : 3-5% of genome, 28% of genes
Gene density in C+G rich regions is 5 times
higher than moderate C+G regions and 10 times
higher than rich A+T regions
– Amount of intronic DNA is 3 times higher for A+T rich
regions. (Both intron length and number).
– Etc…
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RNA Transcription
Not all ORFs are expressed.
Transcription depends on regulatory regions.
Common regulatory region – the promoter
RNA polymerase binds tightly to a specific
DNA sequence in the promoter called the
binding site.
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Prokaryotic Promoter
One type of RNA polymerase.
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Positional Weight Matrix
For TATA box:
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Gene Finding in Eukaryotes
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Coding density
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Eukaryote gene structure
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Gene length: 30kb, coding region: 1-2kb
Binding site: ~6bp; ~30bp upstream of TSS
Average of 6 exons, 150bp long
Huge variance: - dystrophin: 2.4Mb long
– Blood coagulation factor: 26 exons, 69bp to
3106bp; intron 22 contains another unrelated gene
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Splicing
Splicing: the removal of the introns.
Performed by complexes called spliceosomes,
containing both proteins and snRNA.
The snRNA recognizes the splice sites through
RNA-RNA base-pairing
Recognition must be precise: a 1nt error can
shift the reading frame making nonsense of its
message.
Many genes have alternative splicing which
changes the protein created.
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Splice Sites
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Gene prediction programs
Scan the sequence in all 6 reading frames:
1. Start and stop codons
2. Long ORF
3. Codon usage
4. GC content
5. Gene features: promotor, terminator,
poly A sites, exons and introns, …
Frame +1
Frame +2
Frame +3
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Gene prediction programs
Genscan:
Predict location and gene features.
Can handle few genes in one sequence
http://genes.mit.edu/GENSCAN.htm•
l
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Gene prediction programs
Results:
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Genscan
Burge and Karlin, Stanford, 1997
Before The Human Genome Project
– No alignments available
– Estimated human genes count was 100,000
First program to do well on realistic
sequences
– Long, multiple genes in both orientations
Pretty good sensitivity but poor specificity
– 70% Sn, 40% Sp
GenScan Output
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An end to ab initio prediction
ab initio gene prediction is inaccurate.
High false positive rates for most predictors.
Rarely used as a final product
• Human annotation runs multiple algorithms and
scores exon predicted by multiple predictors.
• Used as a starting point for refinement/verification
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Comparative Genomics
Use homologue sequences:
1. Annotated genes.
2. mRNA sequences.
3. Proteins sequences
4. ESTs
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ESTs
EST – Expressed Sequence Tags. Short
sequences which are obtained from
cDNA (mRNA).
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Transcript-based prediction
Align transcript data to genomic sequence
using a pair-wise sequence comparison.
Gene
Model:
EST
cDNA
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Comparative Gene Predictions
Exons are more conserved than introns
•From a study of 1196 genes:
•exons: 84.6%
•protein: 85.4%
•introns: 35%
•5’ UTRs: 67%
•3’ UTRs: 69%
Gene Prediction using expressed
sequences
Improvement over previously existing
methods, in particular when predicting
CDS:
– there exists an increasing richer
representation of the transcripts content of the
human genome in public databases
Improvements in the ability to call the
coding bases, but in particular
– in connecting exons into transcripts
– in predicting alternative splice forms
Dual genome predictors
Use statistical inference and other
‘informant’ genomes: SLAM, DoubleScan,
Twinscan, SGP-2, GenomeScan etc..
Exon prediction such as ExoFish.
Twinscan
Korf, Flicek, Duan, Brent, Washington University
in St. Louis, 2001
Similar to GENSCAN, except it uses another
informant sequence as comparison.
– For Human, the informant is normally mouse
Slightly more sensitive than GENSCAN, much
more specific
– Exon sensitivity/specificity about 75%
Nature, 2005•
Nature methods, 2005•
Other predictions in UCSC 2009
N-SCAN – extension of TwinScan
– Allows for more species (currently uses
mouse)
– A richer model of sequence evolution
N-SCAN PASA-EST
– Combines conservation with evidence based
on ESTs
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Other predictions in UCSC 2009
CONSTRAST (Stanford, 2007)
– 11 informants (rhesus, mouse, cow,...,chicken)
– Machine learning two-phase approach – first predict
exons and then combine them
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Start and stop codon
classifier accuracy
increases as
informants are added.
Splice site detection
accuracy increases as
informants are added.
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Dark Matter in the Genome
Tiling arrays for human
chromosomes 20 and
22:
47% of positive probes
outside exons
What could they be?
• Novel protein-coding
genes
• Novel non-coding genes
• Antisense transcription
• 22% in introns
• Alternative isoforms
• 25% in intergenic
regions
• Biological ‘artifacts’
• False positives
Johnson et al. 2005 TRENDS in Genetics 21:93-102•
Predicting non-coding RNA?
The clues we used so far are useless!
Not clear which properties can be exploited
Sequence features such as promoters are too
weak
Histone modifications + conservation the key
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