Transcript Comparative Genomics of Microbes

Comparative genomics:
Overview & Tools
Urmila Kulkarni-Kale
Bioinformatics Centre
University of Pune, Pune 411 007.
[email protected]
Genome sequence: Fact file
• 1995: The first complete genome sequence of
Haemophilus infuenzae Rd-was published
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Biological systems are dynamic and evolving
The forth dimension: Time
Genome sequence is a snapshot of evolution
Correlation between Phenotypic properties and
Genomic region is not straightforward as
phenotypic properties are result of many to many
interactions
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Genomes: the current
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status
• Published complete genomes: 303
– Archaeal: 24
– Bacterial: 240
– Eukaryal: 39
• Completed Viral genomes:
>5000
• Prokaryotic ongoing genomes: 755
• Eukaryotic ongoing genomes: 531
As of October 11, 2005
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Genome databases
• Genomes at NCBI, EBI, TIGR
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H. influenzae Complete Genome
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Function information clock of E. coli
Generated on March 2K4
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Genome analyses
• Variation in
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E. coli: 4.6Mbp
M. pneumoniae: 0.81Mbp
B. subtilis: 4.20Mbp
Genome size
GC content
B. burgdorferi: 29%
M. tuberculosis: 68%
Codon usage
Amino acid composition
G, A, P, R: GC rich
Genome organisation
I, F, Y, M, D: AT rich
• Single circular chromosomes
• Linear chromosome + extra chromosomal elements
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CG: Comparisons between genomes
• The stains of the same species
• The closely related species
• The distantly related species
– List of Orthologs
– Evolution of individual genes
– Evolution of organisms
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CG helps to ask some interesting questions
• Identification similarities/differences
between genomes may allow us to
understand :
– How 2 organisms evolved?
– Why certain bacteria cause diseases while
others do not?
– Identification and prioritization of drug targets
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CG: Unit of comparison
• Unit of comparison: Gene/Genome
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Number
Content (sequence)
Location (map position)
Gene Order
Gene Cluster (Genes that are part of a known metabolic
pathway, are found to exist as a group)
– Colinearity of gene order is referred as synteny
– A conserved group of genes in the same order in two
genomes as a syntenic groups or syntenic clusters
– Translocation: movement of genomic part from one position
to another
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Comparison of the coding regions
• Begins with the gene
identification algorithm:
infer what portions of the
genomic sequence
actively code for genes.
• There are four basic
approaches.
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Knowledge of Full Genome sequence:
Solutions or new questions…?
Correct #
of
genes…?
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• Still struggling
with the gene
counters…
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University of Pune.
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Numbers: Geneoperon
number
Structure of•tryptophan
• Arrows: Direction of transcription
• //: Dispersion of operon by 50 genes
trpB and trpA
genetically linked
separate genes
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Dandekar et al., 1998
Domain fusion
trpD and trpG
trpF and trpC
Important observations with regard to Gene Order
• Order is highly conserved in closely related
species but gets changed by rearrangements
• With more evolutionary distance, no
correspondence between the gene order of
orthologous genes
• Group of genes having similar biochemical
function tend to remain localized
– Genes required for synthesis of tryptophan (trp
genes) in E. coli and other prokaryotes
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Synteny
• Refers to regions of two genomes that show
considerable similarity in terms of
– sequence and
– conservation of the order of genes
• likely to be related by common descent.
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COGs:
Phylogenetic classification of proteins
encoded in complete genomes
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Genome analyses@NCBI
Pairwise genome comparison of protein
homologs (symmetrical best hits)
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http://www.ncbi.nlm.nih.gov/sutils/geneplot.cgi
University of Pune.
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Integr8: CG site at EBI
http://www.ebi.ac.uk/integr8
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Comparative Genomics Tools
• BLAST2
• MUMmer
• Comparisons and analyses at both
– Nucleic acid and protein level
• Comparative genomics of Parasites @ TIGR
• Microbial Genome Database (MDG) in Japan
• Comparative Genome analysis in P. Borks lab
@embl-heidelberg
• Comprehensive Microbial Resource page@TIGR
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Genome Alignment Algorithm:
MUMmer
• Developed by
– Dr. Steven Salzberg’s group at TIGR
– NAR (1999) 27:2369-2376
– NAR (2002) 30:2478-2483
• Availability
– Free
– TIGR site
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Features of MUMmer
• The algorithm assumes that sequences are closely
related
• Can quickly compare millions of bases
• Outputs:
– Base to base alignment
– Highlights the exact matches and differences in the
genomes
– Locates
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SNPs
Large inserts
Significant repeats
Tandem repeats and reversals
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Definitions are drawn from biology
• SNP: Single mutation surrounded by two
matching regions
– Regions of DNA where 2 sequences have diverged by
more than one SNP
• Large inserts: regions inserted into one of the
genomes
– Sequence reversals, lateral gene transfer
• Repeats: the form of duplication that has occurred
in either genome.
• Tandem repeats: regions of repeated DNA in
immediate succession but with different copy
number in different genomes.
– A repeat can occur 2.5 times
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Techniques used in the MUMmer
Algorithm
Compute Suffix trees for every genome
Longest Increasing Subsequence (LIS)
Alignment using Smith & Waterman algorithm
Integration of
these techniques
for genome alignment
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MUMmer: Steps in the alignment process
Read two
genomes
Using SNPs,
mutation regions,
repeats, tandem
repeats
Perform Maximum Unique
Match (MUM) of genomes
Close the gaps
in the
Alignment
Output
alignment
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Sort and order the
MUMs using LIS
• MUMs
• regions that do not
match exactly
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MUMmer steps
• Locating MUMs
• Sorting MUMs
• Closure with gaps
G1: ACTGATTACGTGAACTGGATCCA
G2: ACTCTAGGTGAAGTGATCCA
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Genome1: ACTGATTACGTGAACTGGATCCA
Genome2: ACTCTAGGTGAAGTGATCCA
Genome1: ACTGATTACGTGAACTGGATCCA
Genome2: ACTCTAGGTGAAGTGATCCA
ACTGATTACGTGAACTGGATCCA
ACTC--TAGGTGAAGT-GATCCA
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What is a MUM?
• MUM is a subsequence that occurs exactly once in
both genomes and is NOT part of any longer
sequence
• Two characters that bound a MUM are always
mismatches
GenA: tcgatcGACGATCGCCGCCGTAGATCGAATAACGAGAGAGCATAAcgactta
GenB: gcattaGACGATCGCCGCCGTAGATCGAATAACGAGAGAGCATAAtccagag
• Principle: if a long matching sequence occurs
exactly once in each genome, it is certainly to be
part of global alignment
Similar to
BLAST & FASTA!!
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Sorting & ordering MUMs
• MUMs are sorted according to their position in
Genome A
• The order of matching MUMs in Genome B is
considered
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MUM3:
Random match
Inexact repeat
MUM5:
transposition
• LIS algorithm to locate longest set of MUMs
which occur in ascending order in both genomes
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UKK,
Bioinformatics
Centre,
Leads©to
Global
MUM-alignment
University of Pune.
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MUMmer Results
• 2 strains of M. tuberculosis
– H37Rv & CDC1551
– Genome size: 4Mb
– Time: 55 s
• Generating suffix tree: 5 s
• Sorting MUMs: 45s
• S&W alignment: 5 s
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Alignment of M. tuberculosis strains
CDC1551 (Top) & H37Rv (bottom)
Single green lines
indicate SNPs
Blue lines
indicate insertions
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Comparison of 2 Mycoplasma genomes
cousins that are distantly related
• M. genitalium: 580 074 nt
• M. pneumoniae: 816 394 (+226 000)
• Analysis of proteins tell us that all M.g.
proteins are present in P.m.
• Alignment was carried using
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FASTA (dividing each genome into 1000 bp)
All-against-all searches
Fixed length of pattern (25)
Using MUMmer (length = 25)
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Comparison of 2 Mycoplasma genomes
Using FASTA
Fixed length
patterns: 25mers
MUMmer
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Post-sequencing challenges
• Genome sequencing is just the beginning to
appreciate biocomplexity
• Sequence-based function assignment approaches
fail as the sequence similarity drops …
• Structure-based function prediction approaches are
limited by the availability of structures,
association of structural motifs & associated
functional descriptor
• As a result, in any genome,
Genes with known
function: ~ 40%
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Genes with unknown
function: ~60%
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University of Pune.
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