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Common Deletion Polymorphisms in the Human Genome

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Title: Common Deletion Polymorphisms in the Human Genome


1
Common Deletion Polymorphisms in the Human Genome
Instructor Yao-Ting Huang
Bioinformatics Laboratory, Department of Computer
Science Information Engineering, National Chung
Cheng University.
2
Polymorphisms in the Human Population
  • So far we have extensively focused on Single
    Nucleotide Polymorphisms (SNPs).

3
Polymorphisms in the Human Population
  • However, we are distinguished from one another by
    all sorts of mutations in the human genome.
  • e.g., deletion, insertion, and inversion.

-A C T T T G C T C-
-A C T T T G C T C-
Deletion polymorphisms
4
Types of Deletions
  • Recall our human genome is a diploid.
  • Each DNA segment should be observed with two
    copies if no deletion.

C CT TT TC CC CA AC C
5
Types of Deletions
  • Recall our human genome is a diploid.
  • Deletion may occur in one or both chromosomes.
  • Homozygous deletion
  • Hemizygous deletion

C CT TT CC CC CA AC C
C CT TT CC CC CA AC C
6
Disease Association with Deletion
  • It has been known that deletions can also lead to
    a variety of serious disorders.
  • Tumor suppressor gene are often found to be
    deleted in cancer cells.
  • With one copy he or she may stay healthy.
  • However, the remaining copy of the tumor
    suppressor gene can be inactivated by a point
    mutation, leaving no tumor suppressor gene to
    protect the body.

7
References
  • McCarroll et al. Common deletion polymorphisms in
    the human genome. Nature Genetics, 2006.
  • Conrad et al. A high-resolution survey of
    deletion polymorphism in the human genome. Nature
    Genetics, 2006.
  • Hinds et al. Common deletions and SNPs are in
    linkage disequilibrium in the human genome.
    Nature Genetics, 2006.
  • Evan E.E. Widening the spectrum of human genetic
    variation, Nature Genetics, 2006.

8
The International HapMap Project
  • 269 samples from four populations are genotyped
    to provide a dense map of SNPs.
  • SNP genotypes are generated at ten genotyping
    centers using seven different genotyping
    technologies.
  • SNPs are discarded if they fail to pass the
    quality control (genotyping errors or failure).
  • These authors utilize several signatures of
    deletions left in SNP genotyping.
  • That is, SNPs of genotyping errors or failure are
    re-scanned for detecting the presence of deletion
    polymorphisms.

9
The International HapMap Project
  • The deletions usually left two common signatures
    in SNP genotyping.
  • (1) Homozygous deletions resulted in null
    genotypes.
  • We fail to obtain the SNP alleles of these
    genotypes (i.e. missing data in the microarray
    chip).
  • Null genotypes could be due to either the failure
    of genotyping or deletion.
  • (2) Hemizygous deletions resulted in SNP
    genotypes miscalled as homozygous.
  • We will still obtain SNP alleles for this type of
    deletions.

10
Footprints of Deletions in SNPs (1/3)
  • (1) Homozygous deletions tend to result in
    cluster of null genotypes.
  • Genotyping failure are less likely to be
    clustered and specific to an individual.

deletions
A CT TA AA CT CA CC T
C CT CA CA CT CA CC C
A CT TA CA CT C A AC T
C CT CA CC CC CA AC T
SNP1
SNP2
Genotyping failuare
11
Footprints of Deletions in SNPs (2/3)
  • (2) Hemizygous deletions resulted in SNPs
    genotypes miscalled as homozygous.
  • These hemizygous deletions often violate the law
    of Mendelian inheritance.
  • An allele in a child could not have been received
    from any of their parents.

A CT CA CG CA CA CC T
A CT TT TC CC C A AC T
C CT CT CC CC CA CC C
12
Gregor Mendel
  • Gregor Mendel is called Father of modern
    genetics.
  • His study of the inheritance of traits in pea
    plants is the fundamental basis of genetics
    (1866).

13
Footprints of Deletions in SNPs (2/3)
  • (2) Hemizygous deletions resulted in SNPs
    genotypes miscalled as homozygous.
  • These hemizygous deletions often lead to Mendel
    inconsistency.
  • e.g., TT of the child violates the Mendelian law.

A CT CA CG CA CA CC T
A CT TT TC CC C A AC T
C CT CT CC CC CA CC C
14
Hardy-Weinberg Equilibrium
  • Hardy-Weinberg Equilibrium describes a
    relationship between the frequencies of alleles
    and the genotypes observed in a population.
  • Frequencies of alleles Pr(A) and Pr(a)
  • Frequencies of genotypes Pr(AA), Pr(Aa), and
    Pr(aa).

Father
Mother
15
Hardy-Weinberg Equilibrium
  • Hardy-Weinberg Equilibrium describes a
    relationship between the frequencies of alleles
    and the genotypes observed in a population.
  • Let Pr(A)p and Pr(a)q.
  • Ideally, Pr(AA) p2, Pr(Aa) 2pq, and Pr(aa)
    q2.

16
Deviation of HWE
  • Inbreeding
  • Breeding between close relatives, which causes an
    increase in homozygosity for all genes.
  • Assortative mating
  • When individuals tend to mate with individuals
    like themselves or dissimilar, which increase or
    reduce genetic diversity.
  • Small population size (sampling)
  • It is easy to observe a random change in
    genotypic frequencies, particularly when the
    population is very small.

17
Footprints of Deletions in SNPs (3/3)
  • Cluster of deviation from Hardy-Weinberg
    equilibrium.
  • We have Pr(A) p gt 0 and Pr(a) q gt 0.
  • But no heterozygous SNPs (e.g., AC) are found.

18
Methods for Finding Clusters of Null Genotypes
(1/3)
  • Formulate each SNP as a binary vector.
  • 0 normal genotypes 1 null genotypes.

19
Methods for Finding Clusters of Null Genotypes
(1/3)
  • Formulate each SNP as a binary vector.
  • Genotyping failure tend to scatter in the matrix.

20
Genotyping Errors
  • Formulate each SNP as a binary vector.
  • Homozygous deletions tend to be clustered.

21
Methods for Finding Clusters of Null Genotypes
(2/3)
  • They cluster is determined based on the
    correlation coefficient r2.

22
Methods for Finding Clusters of Null Genotypes
(2/3)
  • They cluster is determined based on the
    correlation coefficient r2.
  • If SNP3, SNP4, and SNP5 have r2 gt 0.8, they are
    considered to be similar patterns and put in a
    cluster.

23
Methods for Finding Clusters of Null Genotypes
(3/3)
  • Highly similar patterns (r2gt0.8) of null
    genotypes or Mendel failures tend to be
    physically clustered in the genome.

24
Step 1 Identify a list of clusters
  • A list of candidate clusters was determined by
    considering every consecutive pair and
    consecutive trio of observations of that pattern,
    together with any other intervening SNP assays.

25
Step 2 Compute P value for each cluster
Chromosome
CandidateClusters
  • For each candidate cluster, a cluster P value is
    computed to access the binomial probability of
    observing a cluster at least as tight as that
    cluster, given
  • the background frequency of the pattern,
  • the number of SNPs spanned by the cluster, and
  • the total number of SNPs genotyped.

26
Clustering P Value
  • Suppose the pattern frequency is 0.001.

27
Clustering P Value
  • A significance threshold is chosen somewhat to
    the left of a knee in the distribution.

28
Flow of the Process
Identify clusters of null genotypes or Mendel
inconsistency
CandidateClusters
CandidateClusters
29
Results
  • They identify 541 deletions ranging from 1 kb to
    745 kb in size.
  • 94 are novel and 120 are homozygous deletions.

30
Experimental Validation
31
How Many Copy Number Polymorphisms (CNPs) are
Deletions?
  • CNPs imply a deletion or a duplication.
  • Copy number polymorphisms in the human genome,
    Science, 2004. (76 CNPs)
  • Detection of large-scale variation in the human
    genome. Nature Genetics, 2004. (255 CNPs)
  • Segmental duplications and copy number variation
    in the human genome, AJHG, 2005. (119 CNPs)
  • Only 11 deletions are overlapped with previously
    identified CNPs.
  • They speculate that most of these CNPs are
    resulted from duplications rather than deletions.

32
Exons of Genes Removed by Deletions
  • 266 genes are affected by deletions in at least
    one individual.
  • Ten genes are found to be deleted with sufficient
    frequency.

33
Linkage Disequilibrium (LD) between SNPs and
Deletions (1/2)
  • If deletions result from ancestral events, they
    will be often in LD with nearby SNPs.
  • Ten deletions (/, /-, -/-) obtained by
    quantitative PCR over 269 HapMap samples are
    tested.
  • The phase of deletions and all SNPs flanking
    200kb to one deletion are obtained by Haploview.

34
Linkage Disequilibrium (LD) between SNPs and
Deletions (2/2)
35
Capture Deletions by Tag SNPs
  • SNP3 can be the tag SNP for this deletion.
  • i.e., the allele C at this locus indicates a
    deletion.
  • This implies that the upcoming genome-wide
    association studies using tag SNPs is also
    sufficient to detect deletions.

36
Linkage Disequilibrium (LD) between SNPs and
Deletions
  • Six of the ten deletions have a perfect proxy.
  • These deletion are connected with the same allele
    across populations.
  • This implies they are ancestral deletion before
    migration from Africa to Europe or to Asia.

37
More Evidence from Larger Collection
  • Based on 51 deletions validated by PCR,
  • The haplotype homozygosity of SNPs flanking
    homozygous deletions are significantly elevated.
  • This indicates the deletion travel only on
    specific haplotypes.

38
Concluding Remarks
  • These papers provide a similar method for
    identifying deletion polymorphisms using SNPs.
  • Mainly based on cluster of SNPs containg Mendel
    failures or null genotypes.
  • The CNPs are mostly resulted from duplications
    instead of from deletions.
  • This speculation is not convincible since
    recently discovered deletions are shown to be
    poorly overlapped.
  • The deletion polymorphisms and SNPs are in high
    LD.
  • A single genotyping platform is sufficient to
    detect both SNPs and deletions.

39
Notes of Methods
  • The process of patterns of Mendel inconsistency
    are similar to that of null genotypes.
  • The vector is changed to length of 60 containing
    two elements per trio in CEU and YRI.
  • The Hardy-Weinberg disequilibrium is only used
    for extending the clusters identified by using
    null genotypes or Mendel inconsistency.
  • It is estimated by (hetobs/hetexp) and by setting
    a cutoffs of 0.4 or 0.7.
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