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Bioinformatics lectures at Rice
University
Li Zhang
Lecture 10: Networks and integrative genomic analysis-2
Genome instability and DNA copy number data
http://odin.mdacc.tmc.edu/~llzhang/RiceCourse
April 2014
Trends in bioinformatics research
Increase in sample sizes (more patients)
More data types (DNA, RNA, protein,
methylation, nucleosome)
More features ( more genes, transcript, short
reads )
More complicated inference (Translocation,
mutation, deletion/insertion, amplification)
More involvement of systems biology, which
speaks of pathways and networks
TCGA to Study More than 20 Cancers
over Next Two Years
The Cancer Genome Atlas has received $275 million in new
funding from the National Institutes of Health — including about
$125 million allocated for sequencing — to study more than 20
types of cancer over the next two years. Within the next five years,
the project plans to generate comprehensive genomic maps for
these cancers
URL:cancergenome.nih.gov
DNA copy number changes reflect
chromosomal abnormality in cancer
DNA copy number data obtained from microarrays
Characteristics of DNA copy number data
1.Piecewise constant + noise
2.Noise
3.Bias
SNP arrays can obtain allele-specific copy number changes
BAF = B/(A+B)
More characteristics of DNA copy number data
4. Copy changes are often allele-specific, i.e., only one of the homologous
chromosome is affected. In some cases, an loss allele can be compensated by
gain of the other allele, i.e., CNN-LOH, copy number neutral loss of
heterozygosity, or UPD, uni-parental disomy. It is rare that both alleles get
affected.
More characteristics of DNA copy number data
5. Denoised copy number values often follow comb-like distributions.
Exceptions to this rule may indicate presence of multiple clones. Double is loss
is very rare. Copy number>6 are considered amplicons, which play critical role in
cancer.
Next generation sequencing can provide more detailed genome structural changes
Paired-end sequencing  translocations
Chromothripsis
Algorithms
1. CBS: Identify copy number profile segments
2. Data processing to correct for biases.
3. GISTIC: Identify cancer genes with frequent
gains/losses
Biases distort the DNA copy number profile
More characteristics of DNA copy number data
6. Scope of gain or loss vary probably due to different causes. Large chunks may
be miss-segregated during mitosis. Small chunks may be affected by mistakes in
DNA repair.
Cancer genes often reside in regions with Focal SCNAs
Tumor suppressors
Oncogenes
mRNA and DNA copy number
•
Correlation matrices of genome copy
number and gene expression in
meningiomas. A, Pearson's correlations
among DNA copy numbers (Panel A)
and between DNA copy number and
gene expression (Panel B) are plotted as
a function of chromosomal location.
Only correlations greater than 0.82
(red) and less than -0.82 (blue) are
shown on the intensity map. The
association between loss on
chromosome 14 and gain on
chromosome 1q (black arrow), loss on
chromosome 14 and loss on
chromosome 6q (brown arrow) and loss
on chromosome 7p and gain on
chromosome 20 (black arrowhead) are
indicated.
Copy number breakpoint and gene fusion
Wang et al, 2009, Nature Biotechnology.