Gene Structure and Identification

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Gene Structure and Identification

• Eukaryotic Genes and Genomes
• Gene Finding

Previous reading 1.3, 9.1-9.6 Reading 10.2,
10.4, 10.6-8
BIO520 Bioinformatics Jim Lund
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Complex Genome DNA

• 10 highly repetitive (300 Mbp)
• NOT GENES
• 25 moderate repetitive (750 Mbp)
• Some genes
• 25 exons and introns (800 Mbp)
• 40?
• Regulatory regions
• Intergenic regions

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Eukaryotic Gene Expression
Promoter
Transcribed Region
Terminator
Enhancer
Transcription
RNA Polymerase II
Primary transcript 5
3
Intron1
Exon1
Exon2
Cap Splice Cleave/Polyadenylate
Translation
7mG
An
N
C
Transport
7mG
An
Polypeptide
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Yeast

• ORFSgenes!

Small ORFS (RNA genes) Regulatory Sequences
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Eukaryotes, contd

• large Eukaryotes
• introns common, LONGER than exons
• Promoter/enhancer
• genome sparse

• Fungi
• introns common, short relative to exons
• promoter/enhancer
• genome dense

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Intron Prevalence
of genes
Introns
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Intron Size
of genes
Introns
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Exon Size
of genes
Exon size (bps)
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Fungi

• Sew together exons
• ORF regions
• consensus sequences
• domain/polypeptide matches

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Exon/Intron Structure
CCACATTgtn(30-10,000)an(5-20)agCAGAA
...CCACATTCAGAA... ...ProHisSerGlu...
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Alternative Splice
CCACATTgtn(30-10,000)an(5-20)agcagAA
...CCACATTAA... ...ProHisSTOP
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Gene prediction targets

• Internal exons (donor-acceptor)
• Initial exons (5-donor)
• Terminal exons (acceptor-3)
• Single exon genes (5-3)

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Gene prediction

• Sequence based
• Consensus sites
• Signal sequences
• Homology
• Confirm prediction is a protein
• Known coding sequences
• cDNAs, SAGE
• Comparative analysis
• Identify exons, promoter/enhancer elements

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Codon Bias/Nucleotide Frequency-useful?

• High bias high confidence
• Low bias low confidence

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Finding Functional Sequences

• Known Consensus Sequences
• Consensus Sequence Generation
• Functional Tests

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Describing consensus sequences

• Position Weight Matrices
• Sequence Logos
• Hidden Markov Models

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Translation Initiation Sites
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Splicing Consensus
A64G73GTA62A68G84T63 Y80NY80Y87R75AY95C65AGNN V
ert
GTRNGT(N)30-1000 CTRAC(N)5-15YAG Fungi
Alternate Splicing!??
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Linguistic approach to combining gene features

• Non-repetitive DNA!!
• Long ORF
• similar to known protein
• ORF extended by reasonable splices
• ORF begins with good ATG
• Promoter/terminator flanks

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DATABASE SEARCH

• BLASTN
• DNADNA comparison (ALWAYS!)
• Not sensitive (DNA conservation low)
• BLASTX/TBLASTX
• ?6 frame ORFSpolypeptide database
• 6 frames vs. 6 frames of a DNA database

www.ncbi.nlm.nih.gov
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Protein Database Matches

• Very helpful for the known
• What about the unknown???

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Transcript Initiation

• Basal Promoters
• Enhancers/Silencers/Regulatory Sites
• Boundary elements?
• Transcription Initation

Prokaryotes vs Eukaryotes Organism-to-Organism
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Basal Promoter Analysis
Myers and Maniatis, Genes VI, 831

• TATA-box -25 to -30 TBP
• CCAAT-box -212 to -57 CTF/NF1
• GC-box -164 to 1 SP1
• K C W K Y Y Y Y 1 to 5 cap signal

1
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Basal Promoter Analysis
Cao and Moi, Ped Res 51415-421 (2002)
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mRNA processing

• Exon/Intron
• Alternate splicing
• Polyadenylation/Cleavage
• Stability

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PolyA sites

• Metazoans
• AATAAA, ATTAAA
• 15-20 bps 5 of polyA addition site.
• YGTGTTYY (diffusive GT-rich sequence)
• 100-700 bps 3 UTR typical.
• Yeast-different

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Translation

• Initiation site
• 1st AUG used 95 of the time.
• Translational regulatory elements
• translational enhancers
• upstream ORFs

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Tools-WWW

• Genscan
• Genie
• GRAIL II integrated gene parsing
• GenLang
• HMMGene (lock ESTs, etc.)
• GENEMARK

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Hidden Markov Models

• Probabilistic Models
• Applicable to linear sequences
• P(all states)1, infer probabilities of all
  states from observed (hidden states unobserved)
• Work best when local correlations unimportant
• Genefinding, phylogeny, secondary structure,
  genetic mapping
• Parameters are set using a Training Set of gene
  annotations
• Quantitative probabilities

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Accuracy Assessment
PPpredicted coding APreal positive TPnumber
correct positive TNnumber correct
negative FPnumber false positive FNnumber
false negative
SensitivitySnTP/AP SpecificitySpTP/PP
Approximate Correlation (AC) ((TP/(TPFN))
(TP/(TPFP)) (TN/(TNFP)) (TN/(TNFN))) / 2
- 1
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Accuracy Levels
Bp Exon
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NEXT

• Regulatory Sequences
• Known Consensus Sequences
• Consensus Sequence Generation
• Functional (Lab) Data
• Real examples