evolution at the dna level …acggtgcagttacca… …ac----cagtccacca… mutation sequence edits...
Post on 19-Dec-2015
218 views
TRANSCRIPT
Evolution at the DNA level
…ACGGTGCAGTTACCA…
…AC----CAGTCCACCA…
Mutation
SEQUENCE EDITS
REARRANGEMENTS
Deletion
InversionTranslocationDuplication
Orthology and Paralogy
HB HumanHB Human
WB WormWB Worm
HA1 HumanHA1 Human
HA2 HumanHA2 Human
YeastYeast
WA WormWA Worm
Orthologs:Derived by speciation
Paralogs:Everything else
Orthology, Paralogy, Inparalogs, Outparalogs
Synteny maps
Comparison of human and mouse
Synteny maps
Synteny maps
Synteny maps
Building synteny maps
Recommended local aligners• BLASTZ
Most accurate, especially for genes Chains local alignments
• WU-BLAST Good tradeoff of efficiency/sensitivity Best command-line options
• BLAT Fast, less sensitive Good for
• comparing very similar sequences • finding rough homology map
Index-based local alignment
Dictionary:
All words of length k (~10)
Alignment initiated between words of alignment score T
(typically T = k)
Alignment:
Ungapped extensions until score
below statistical threshold
Output:
All local alignments with score
> statistical threshold
……
……
query
DB
query
scan
Question: Using an idea from overlap detection, better way to find all local alignments between two genomes?
Local Alignments
After chaining
Chaining local alignments
1. Find local alignments
2. Chain -O(NlogN) L.I.S.
3. Restricted DP
Progressive Alignment
• When evolutionary tree is known:
Align closest first, in the order of the tree In each step, align two sequences x, y, or profiles px, py, to generate a new
alignment with associated profile presult
Weighted version: Tree edges have weights, proportional to the divergence in that edge New profile is a weighted average of two old profiles
x
w
y
z
Example
Profile: (A, C, G, T, -)px = (0.8, 0.2, 0, 0, 0)py = (0.6, 0, 0, 0, 0.4)
s(px, py) = 0.8*0.6*s(A, A) + 0.2*0.6*s(C, A) + 0.8*0.4*s(A, -) + 0.2*0.4*s(C, -)
Result: pxy = (0.7, 0.1, 0, 0, 0.2)
s(px, -) = 0.8*1.0*s(A, -) + 0.2*1.0*s(C, -)
Result: px- = (0.4, 0.1, 0, 0, 0.5)
Threaded Blockset Aligner
Human–Cow
HMR – CDRestricted AreaProfile Alignment
Reconstructing the Ancestral Mammalian Genome
Human: C
Baboon: C
Cat: C
Dog: G
C
C or G
G
Neutral Substitution Rates
Finding Conserved Elements (1)
• Binomial method 25-bp window in the human genome Binomial distribution of k matches in N bases given the neutral
probability of substitution
Finding Conserved Elements (2)
• Parsimony Method Count minimum # of mutations explaining each column Assign a probability to this parsimony score given neutral model Multiply probabilities across 25-bp window of human genome
A
CAAG
Finding Conserved Elements
Finding Conserved Elements (3)
GERP
Phylo HMMs
HMM
Phylogenetic Tree Model
Phylo HMM
Finding Conserved Elements (3)
How do the methods agree/disagree?
Statistical Power to Detect Constraint
L
N
C: cutoff # mutationsD: neutral mutation rate: constraint mutation rate relative to neutral
Statistical Power to Detect Constraint
L
N
C: cutoff # mutationsD: neutral mutation rate: constraint mutation rate relative to neutral