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Sequence Analysis with Artemis
&
Artemis Comparison Tool (ACT)
South East Asian Training Course on
Bioinformatics Applied to Tropical Diseases - 2005
(Sponsored by UNDP/World Bank/WHO/TDR)
International Centre For Genetic Engineering And Biotechnology ,
New Delhi, INDIA
Gene finding
atcttttacttttttcatcatctatacaaaaaatcatagaatattcatcatgttgtttaaaataatgtattccattatgaactttattacaaccctcgtt
tttaattaattcacattttatatctttaagtataatatcatttaacattatgttatcttcctcagtgtttttcattattatttgcatgtacagtttatca
tttttatgtaccaaactatatcttatattaaatggatctctacttataaagttaaaatctttttttaattttttcttttcacttccaattttatattccg
cagtacatcgaattctaaaaaaaaaaataaataatatataatatataataaataatatataataaataatatataatatataataaataatatataatat
ataatatataataaataatatataatatataatatataataaataatatataataaataatatataatatataatatataatactttggaaagattattt
atatgaatatatacacctttaataggatacacacatcatatttatatatatacatataaatattccataaatatttatacaacctcaaataaaataaaca
tacatatatatatataaatatatacatatatgtatcattacgtaaaaacatcaaagaaatatactggaaaacatgtcacaaaactaaaaaaggtattagg
agatatatttactgattcctcatttttataaatgttaaaattattatccctagtccaaatatccacatttattaaattcacttgaatattgttttttaaa
ttgctagatatattaatttgagatttaaaattctgacctatataaacctttcgagaatttataggtagacttaaacttatttcatttgataaactaatat
tatcatttatgtccttatcaaaatttattttctccatttcagttattttaaacatattccaaatattgttattaaacaagggcggacttaaacgaagtaa
ttcaatcttaactccctccttcacttcactcattttatatattccttaatttttactatgtttattaaattaacatatatataaacaaatatgtcactaa
taatatatatatatatatatatatatatatatattataaatgttttactctattttcacatcttgtccttttttttttaaaaatcccaattcttattcat
taaataataatgtattttttttttttttttttttttttattaattattatgttactgttttattatatacactcttaatcatatatatatatttatatat
atatatatatatatatatatattattcccttttcatgttttaaacaagaaaaaaaactaaaaaaaaaaaaaataataaaatatatttttataacatatgt
attattaaaatgtatatataaaaatatatattccatttattattatttttttatatacattgttataagagtatcttctcccttctggtttatattacta
ccatttcactttgaacttttcataaaaattaatagaatatcaaatatgtataatatataacaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaata
tatatatatatatatatacatataatatatatttcatctaatcatttaaaattattattatatattttttaaaaaatatatttatgataacataaaaaga
atttaattttaattaaatatatataattacatacatctaatattattatatatatataataagttttccaaatagaatacttatatattatatatatata
tatatatatatatattcttccataaaaagaataaaataaaataaaaacaccttaaaagtatttgtaaaaaattccccacattgaatatatagttgtattt
ataaaattaaagaaaaagcataaagttaccatttaatagtggagattagtaacattttcttcattatcaaaaatatttatttcctaattttttttttttg
taaaatatatttaaaaatgtaatagattatgtattaaataatataaatatagcaaaatgttcaattttagaaatttgcctctttttgacaaggataattc
aaaagatacaggtaaaaaaaaaaaaataaagtaaaacaaaacaaaacaaaaaacaaaaaaaaaaaaaaaaaaaaaaatgacatgttataatataatataa
taaataaaaattatgtaatatatcataatcgaagaaacatatatgaaaccaaaaagaaacagatcttgatttattaatacatatataactaacattcata
tctttatttttgtagatgatataaaaaattttataaactcttatgaagggatatatttttcatcatccaataaatttataaatgtatttctagacaaaat
tctgatcattgatccgtcttccttaaatgttattacaataaatacagatctgtatgtagttgatttcctttttaatgagaaaaataagaatcttattgtt
ttagggtaatgaaatatatatagatttatatttttatttatttattatatattattttttaatttttcttttatatatttattttatttagtgtataaaa
tgatatcctttatatttatatttacatgggatattcaaataataacaaaaatgagtatacacatatatatatatatatatatatatatgtatattttttt
tttttttttatgttcctataggaaagggaagaattcactgatttgtagtgtttacaatattagggaatgcaactttacacttttgaaaaaaattcagtta
agcaaaaatattaataacattaaaaagacactgatagcaaaatgtaatgaatatataataacattagaaaataagaaaattactttttatttcttaaata
aagattatagtataaatcaaagtgaattaatagaagacggaaaagaacttattgaaaatatctatttgtcaaaaaatcatatcttgttagtaataaaaaa
ttcatatgtatatatataccaattagatattaaaaattcccatattagttatacacttattgatagtttcaatttaaatttatcctacctcagagaatct
ataaataataaaaaaaagcatataaataaaataaatgatgtatcaaataatgacccaaaaaaggataataatgaaaaaaatacttcatctaataatataa
cacataacaattataatgacatatcaaataataataataataataataatattaatggggtgaaagaccatataaataataacactctggaaaataatga
tgaaccaatcttatctatatataatgaagatcttaatgttttatatatatgccaaaatatgtataacgtcctttttgttttgaatttaaataacctaagt
atcttttacttttttcatcatctatacaaaaaatcatagaatattcatcatgttgtttaaaataatgtattccattatgaactttattacaaccctcgtt
tttaattaattcacattttatatctttaagtataatatcatttaacattatgttatcttcctcagtgtttttcattattatttgcatgtacagtttatca
tttttatgtaccaaactatatcttatattaaatggatctctacttataaagttaaaatctttttttaattttttcttttcacttccaattttatattccg
cagtacatcgaattctaaaaaaaaaaataaataatatataatatataataaataatatataataaataatatataatatataataaataatatataatat
ataatatataataaataatatataatatataatatataataaataatatataataaataatatataatatataatatataatactttggaaagattattt
atatgaatatatacacctttaataggatacacacatcatatttatatatatacatataaatattccataaatatttatacaacctcaaataaaataaaca
tacatatatatatataaatatatacatatatgtatcattacgtaaaaacatcaaagaaatatactggaaaacatgtcacaaaactaaaaaaggtattagg
agatatatttactgattcctcatttttataaatgttaaaattattatccctagtccaaatatccacatttattaaattcacttgaatattgttttttaaa
ttgctagatatattaatttgagatttaaaattctgacctatataaacctttcgagaatttataggtagacttaaacttatttcatttgataaactaatat
tatcatttatgtccttatcaaaatttattttctccatttcagttattttaaacatattccaaatattgttattaaacaagggcggacttaaacgaagtaa
ttcaatcttaactccctccttcacttcactcattttatatattccttaatttttactatgtttattaaattaacatatatataaacaaatatgtcactaa
taatatatatatatatatatatatatatatatattataaatgttttactctattttcacatcttgtccttttttttttaaaaatcccaattcttattcat
taaataataatgtattttttttttttttttttttttttattaattattatgttactgttttattatatacactcttaatcatatatatatatttatatat
atatatatatatatatatatattattcccttttcatgttttaaacaagaaaaaaaactaaaaaaaaaaaaaataataaaatatatttttataacagatgt
attattaaaatgtatatataaaaatatatattccatttattattatttttttatatacattgttataagagtatcttctcccttctggtttatattacta
ccatttcactttgaacttttcataaaaattaatagaatatcaaatatgtataatatataacaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaata
tatatatatatatatatacatataatatatatttcatctaatcatttaaaattattattatatattttttaaaaaatatatttatgataacataaaaaga
atttaattttaattaaatatatataattacatacatctaatattattatatatatataataagttttccaaatagaatacttatatattatatatatata
tatatatatatatattcttccataaaaagaataaaataaaataaaaacaccttaaaagtatttgtaaaaaattccccacattgaatatatagttgtattt
ataaaattaaagaaaaagcataaagttaccatttaatagtggagattagtaagtttttcttcattatcaaaaatatttatttcctaattttttttttttg
taaaatatatttaaaaatgtaatagattatgtattaaataatataaatatagcaaaatgttcaattttagaaatttgcctctttttgacaaggataattc
aaaagatacaggtaaaaaaaaaaaaataaagtaaaacaaaacaaaacaaaaaacaaaaaaaaaaaaaaaaaaaaaaatgacatgttataatataatataa
taaataaaaattatgtaatatatcataatcgaagaaacatatatgaaaccaaaaagaaacagatcttgatttattaatacatatataactaacattcata
tctttatttttgtagatgatataaaaaattttataaactcttatgaagggatatatttttcatcatccaataaatttataaatgtatttctagacaaaat
tctgatcattgatccgtcttccttaggtgttattacaataaatacagatctgtatgtagttgatttcctttttaatgagaaaaataagaatcttattgtt
ttagggtaatgaaatatatatagatttatatttttatttatttattatatattattttttaatttttcttttatatatttattttatttagtgtataaaa
tgatatcctttatatttatatttacatgggatattcaaataataacaaaaatgagtatacacatatatatatatatatatatatatatgtatattttttt
tttttttttatgttcctataggaaagggaagaattcactgatttgtagtgtttacaatattagggaatgcaactttacacttttgaaaaaaattcagtta
agcaaaaatattaataacattaaaaagacactgatagcaaaatgtaatgaatatataataacattagaaaataagaaaattactttttatttcttaaata
aagattatagtataaatcaaagtgaattaatagaagacggaaaagaacttattgaaaatatctatttgtcaaaaaatcatatcttgttagtaataaaaaa
ttcatatgtatatatataccaattagatattaaaaattcccatattagttatacacttattgatagtttcaatttaaatttatcctacctcagagaatct
ataaataataaaaaaaagcatataaataaaataaatgatgtatcaaataatgacccaaaaaaggataataatgaaaaaaatacttcatctaataatataa
cacataacaattataatgacatatcaaataataataataataataataatattaatggggtgaaagaccatataaataataacactctggaaaataatga
tgaaccaatcttatctatatataatgaagatcttaatgttttatatatatgccaaaatatgtataacgtcctttttgttttgaatttaaataacctaagt
Gene prediction programs:
ORFs and CDSs
ORFs are not equivalent to CDSs
Not all open reading frames are coding sequences
Gene prediction
Orpheus
PHAT
GeneMark
Glimmer
Gene finder
Genefinding programs
• Genefinding software packages use Hidden
Markov Models.
• Predict coding, intergenic and intron
sequences
• Need to be trained on a specific organism.
• Never perfect!
Gene prediction programs: Problems
• ORFs are not equivalent to CDSs
• Gene prediction programs find new genes that share
properties with a given set of genes.
• They can be confounded by:
–
–
–
–
–
Sequence constraints (ribosomal proteins etc.)
Sequence biases
Different sets of genes
Horizontal gene transfer
Non-coding DNA
Gene prediction programs: Problems
Different gene training sets: Plasmodium falciparum
Original annotation
Updated annotation
Gene prediction programs: Problems
Non-protein coding regions: S. typhi ribosomal RNA genes
final
genefinder
orpheus
glimmer
glimmer
orpheus
genefinder
final
Gene prediction programs: Problems
Non-protein coding regions: N. meningitidis DNA repeats
final
orpheus
glimmer
glimmer
orpheus
final
Gene prediction programs: Problems
Pseudogenes
M. leprae
Gene prediction programs: Problems
Pseudogenes: M. leprae
Glimmer
Gene prediction programs: Problems
Pseudogenes: M. leprae
ORPHEUS
Gene prediction programs: Problems
Pseudogenes: M. leprae
WUBLASTX vs. M. tuberculosis
Gene prediction programs: Problems
Pseudogenes: M. leprae
Final annotation
Gene prediction programs: Statistics
CDS prediction
1
Glimmer
Campylobacter jejuni
1.641
30.55
1761
1518
Neisseria meningitidis A
2.184
51.81
3134
2024
2121
Mycobacterium leprae
3.268
57.80
949
4427
1605 intact
1115 pseudo
Salmonella typhi
4.809
52.09
5194
Yersinia pestis
4.654
47.64
2
3
4
5
http://www.tigr.org/softlab/glimmer/glimmer.html
http://pedant.mips.biochem.mpg.de/orpheus/index.html
Start-to-stop >100 aa
TIGR CMR (http://www.tigr.org/)
GeneFinder (Krogh+Larson pers comm)
5679
ORPHEUS
2
G+C
1
G2
1
Size (Mb)
Organism
4
4666
2654
4312
other
1783
4973
Final
3
5
1654
4600
4011
The Gene Prediction Process
ESTs
ANNALYSIS SOFTWARE
DNA SEQUENCE
FASTA
BlastX
Gene finders
Codon Usage
AT content
Annotator
Usefull
CDS
Prediction
Eukaryotic gene
5’UTR
Exon I intron
ATG
GT
AG
stop
Exon III 3’UTR
Exon II
GT
AG
CAP
AAAAAAAAAA
CAP
AAAAAAAAAA
mRNA
TTTTTTTTT
cDNA
TTTTTTTTT
EST
EST
AT content
• Coding regions have higher GC content in
AT rich genomes
AT content
CODON USAGE
• Codon bias is different for each organism.
• DNA content in coding regions is restricted
– but it is not restricted in non coding regions.
• The codon usage for any particular gene can
influence expression.
Codon usage
• All organisms have a preferred set of
codons.
Malaria
GUU
GUC
GUA
GUG
0.41
0.06
0.42
0.11
Trypanosoma
GUU
GUC
GUA
GUG
0.28
0.19
0.14
0.39
Codon Usage
• http://www.kazusa.or.jp/codon/
Codon Usage in Artemis
Forward
frames
Reverse
frames
Codon usage & gene finding in : Leishmania
Transcriptional units in Leishmania: DNA strand-switches
GC frame plot
• Plots the third position GC content of each
frame of a DNA sequence.
• In coding DNA the GC content of the 3rd
base is often higher.
• Good prediction of coding in malaria and
trypanosomes.
GC frame plot of tubulin gene cluster on T. brucei Chr 1
Large-scale nucleotide plots in Artemis I: S. typhi genome
GC content, GC deviation, Karlin signature
Homology Data
• Coding regions are more conserved than non
coding regions due to selective pressure.
• Comparing all possible translations against
all known proteins will give clues to known
genes.
• Blastx
Gene finding: using ACT
P. yoelii
P. falciparum
P. knowlesi
TBLASTX comparisons
Using FASTA / BLAST Results
• FASTA is a global alignment tool
• BLAST is a local alignment tool
BLAST
FASTA
Global alignments can be more informative and trustworthy when
looking at modular proteins or multifunctional proteins.
Domain problems:
Matches between similar functional domains in otherwise different proteins can lead
to incorrect transfer of annotation