Gene Structure and Identification

1
Gene Structure and Identification

• Eukaryotic Genes and Genomes
• Gene Finding

Assigned reading Ch 5 Prev. reading Ch 1, Ch 3,
Ch 11, Ch 12
BIO520 Bioinformatics Jim Lund
2
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

3
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
4
Yeast

• ORFSgenes!

Small ORFS (RNA genes) Regulatory Sequences
5
Eukaryotes, contd

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

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

6
Intron Prevalence
of genes
Introns
7
Intron Size
of genes
Introns
8
Exon Size
of genes
Exon size (bps)
9
Fungi

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

10
Exon/Intron Structure
CCACATTgtn(30-10,000)an(5-20)agCAGAA
...CCACATTCAGAA... ...ProHisSerGlu...
11
Alternative Splice
CCACATTgtn(30-10,000)an(5-20)agcagAA
...CCACATTAA... ...ProHisSTOP
12
Gene prediction targets

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

13
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

14
Codon Bias/Nucleotide Frequency-useful?

• High bias high confidence
• Low bias low confidence

15
Codon Bias/Nucleotide Frequency-useful?

• High bias high confidence
• Low bias low confidence

16
Finding Functional Sequences

• Known Consensus Sequences
• Consensus Sequence Generation
• Functional Tests

17
Consensus Inference

• Position Weight Matrices
• Sequence Logos
• Hidden Markov Models

18
Translation Initiation Sites
19
Splicing Consensus
A64G73GTA62A68G84T63 Y80NY80Y87R75AY95C65AGNN V
ert
GTRNGT(N)30-1000 CTRAC(N)5-15YAG Fungi
Alternate Splicing!??
20
Linguistic Approach

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

21
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
22
Protein Database Matches

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

23
Transcript Initiation

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

Prokaryotes vs Eukaryotes Organism-to-Organism
24
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
25
Basal Promoter Analysis
Cao and Moi, Ped Res 51415-421 (2002)
26
mRNA processing

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

27
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

28
Translation

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

29
Tools-WWW

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

30
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
• Pararmeters are set using a Training Set of
  gene annotations
• Quantitative probabilities

31
Accuracy Assessment
PPpredicted coding PNpredicted
non-coding APreal positive ANreal
negatives TPnumber correct positive TNnumber
correct negative FPnumber false
positive FNnumber false negative
SnTP/AP SpTP/PP
AC ((TP/(TPFN)) (TP/(TPFP))
(TN/(TNFP)) (TN/(TNFN))) / 2 - 1
32
Accuracy Levels
Bp Exon
33
NEXT

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

34
Gene Regulatory Sequences

• Functional sites
• Consensus
• Experimental tests
• Inferred sites
• Transcriptome analysis

35
Regulatory Sites

• Transcript initiation
• mRNA processing
• Translation sites

36
Regulatory Factors

• lacI, trpR, CAP, araC.
• GAL4, NDT80

Known from experiment Infer from genome? Infer
from expression data?
37
EUKARYOTES

• More complex signals
• More genes
• More dispersed signals
• Combinatoric regulation common

38
Enhancer Elements

• DNA element Protein
• Octamer OCT1, OCT2
• ?B NF ?B
• ATF ATF
• AP1 AP1
• ..

False , False -
39
Consensus Sequence Databases

• WWW-based
• TFD (transcription factor database)
• BCM Search launcher

40
Transcriptome Analyses

• Microarray transcription analysis
• Expression
• Transcription factor binding
• MEME analysis of clusters

More later....
41
Practical Gene Finding

• Use ALL tools
• Comparative
• BLASTN, BLASTX
• Predictive Stitch together a consensus
• HMM, GRAIL
• ORF finders
• Findpatterns (and WWW pattern searches)
• cDNA OR protein OR genetic evidence

42
FRAMES-aldolase gene
43
If aldolase is so tough, how do you really do it?

• Combine DNA sequence
• with other data!

44
Genome-cDNA
P
DNA sequencing
Align (GAP)
cDNA
45
Comparative Genomics

• Conservation of coding regions
• Identification of transcription signals
• words in common
• Example-yeast comparisons