1. Identification and characterization of
copy number variation in Indian population and its association with disease
Pankaj Kumar
CAS-MPG Presentation
07 May 2012

2. Introduction
CNVs are
- variations in the # of copies of genomic regions
- Can be insertions, deletions and duplications
- have size ranging from > 1 Kb to Mbs
CNV vs. SNPS
CNV
SNP
Total Number
38,406
14,708,752
% of Reference Genome
29.74%
<1%

3. Introduction contd.. C D A B Origin Types Occurrence F Polymorphism
Deletion
Polymorphism
Phenotypic Variability
Disease Susceptibility A B E
Duplication
Mutation
Frequency
Origin
Types
Occurrence

4. Introduction contd.. Consequence of CNVs Unmask recessive alleles
Disrupt genes
Cumulative effects
Alter regulation
Scherer et al. Nature Review Genetics 2006

5. Objectives: To identify CNVs in diverse Indian populations
To map CNV regions with disease susceptibility
To study consequence of CNV in disease
To explore the role of CNV in Spinocerebellar Ataxia

6. Proof -of-concept study
CNV & Diseases
Proof -of-concept study

7. APOBEC3b: insertion/ deletion polymorphism
Cytidine deaminase family of proteins
29 kb insertion/deletion polymorphism
Kidds et al. PLoS Genetics, 2007 7

8. Spectrum of APOBEC3B deletion frequency in Indian populations studied

9. APOBEC3b insertion/deletion polymorphism & malaria endemicity
White - insertion
Dark - deletion

10. Comparisons (Fisher's test)
Significant association of APOBEC3b with falciparum malaria
Malaria cohort
Comparisons (Fisher's test)
Genotypes
Odds Ratio (95 % CI)
P value
Endemic
Non-severe vs. control
AB & AA
(3.20 to 15.97)
1x10-7
Severe vs. control
(2.62 to 26.59)
1.7x10-5
Severe vs. non-severe
1.14
(0.37 to 3.81)
0.8
Non-endemic
(0.16 to 0.93)
0.0211
BB & AB
(1.76 to 24.99)
0.0012
BB & (AA+AB)
(1.10 to 10.32)
0.0177
A - insertion allele
B- deletion allele
Insertion allele of APOBEC3B seems to be protective for malaria

11. EHH and Haplotype Analysis
Positive Selection for APOBEC3B locus in Malaria
APOBEC3B
500 Kb upstream
500 Kb downstream
EHH and Haplotype Analysis
Positive selection
markers 5' 3'
???

12. Haplotype based analysis for larger linkage disequilibrium
Endemic case
Endemic control
Non-endemic case
Non-endemic control
Selection for ABOPEC3B region has not been observed in malaria

13. Schematic representation of APOBEC gene cluster and segmental duplication region
duplication regions
Due to large no. of segmental duplication regions in this locus selection for
APOBEC3B was not observed

14. Conclusions
Insertion allele of APOBEC3B seems to be protective for malaria
APOBEC3B locus has not Shown signature of positive selection by conventional methods may be due to high recombination events
Since this gene is expressed in liver & spleen this might provide a new
mechanism of host protective response

15. Identification of CNVs in the Indian population
A basal Database

16. (~58000 SNPs with av. inter-marker distance 50 kb)
Identification of large CNVs (>100k) in the Indian population : Methodology
Sampling of IGV populations
Cluster 1
Cluster 2
Cluster 3
Cluster 4
Cluster 5
IE -W-IP2
IE-E-LP2
IE-N-LP1
IE-N-LP9
IE-N-LP18
TB-N-IP1
TB-N-SP1
IE-W-LP3
IE-W-LP1
IE-W-LP2
IE-E-IP1
IE-NE-IP1
AA-NE-IP1
TB-NE-LP1
IE-N-IP2
IE-N-LP10
IE-N-SP4
AA-E-IP3
AA-C-IP5
DR-S-LP
IE-W-LP4
OG-W-IP
DR-S-LP3
IE-N-LP5
IE-E-LP4
IE-NE-LP1
DR-C-IP2
Affy 50k array
(~58000 SNPs with av. inter-marker distance 50 kb)
Raw intensity files
Retrieve segments >100 kb length & minimum 10 probes using G-Console
CNV calling and QC
(Genotyping Console+SVS7)
Validation using Sequenom
massARRAY QGE assay
477 samples, 26 populations 16

17. Instances of genomic segment prone to CNVs
Results
Instances of genomic segment prone to CNVs
Raw CNV deletion = (<1Mb segment size) and 212 (>1Mb segment size)
Raw CNV duplication = (<1Mb segment size) and 60 (>1Mb segment size)
Total CNVRs deletions = 1425
Total CNVRs duplications = 1337

18. Extent of CNVs in IGV populations
result contd..
Extent of CNVs in IGV populations

19. Chromosomal landscape of common CNV regions in all the populations pooled together

20. Concordance of dataset using two independent algorithms
result contd..
Concordance of dataset using two independent algorithms
5750
(65%)
2048
(23%)
1006
(11%)
Deletion
Duplication
GTC 3.0.2
2986
(50%)
1461
(25%)
1515
Deletion
Duplication
SVS 7
~ 60% of copy number variable regions showed deletion and duplication both
Comparison using both the software shown 50% concordance prone to CNVs
Points-
1- Earlier the common genes (in deletion and duplication) were 63 and 55% in GTC and SVS7 respectively. Has not changed much.

21. CNV Validation and Heterogeneity
result contd..
CNV Validation and Heterogeneity
Validation using Sequenom MassARRAY QGE
Amplification
Deletion
Less validation due to heterogeneity in CNV boundaries
Selection of probe for validation is a also key factor

22. CNVs and Population Structure
result contd..
TB populations
and isolated
Himalayan
populations
AA and DR isolated
IE large
Populations clustered according to genetic and linguistic affinity

23. CNVs present in IGV map to genes that are associated with diseasesSN
GENE_SYMBOL
Disorder name
Class 1
KDR
Hemangioma, capillary infantile, somatic
Cancer 2
IRF4
Multiple myeloma 3
BRAF
Adenocarcinoma of lung, somatic 4
KCNE2
Atrial fibrillation, familial, Long QT syndrome-6
Cardiovascular 5
AGT,AGTR1
Hypertension, essential, Renal tubular dysgenesis 6
ADRB1
Congestive heart failure, susceptibility to, Resting heart rate 7
KRT6A
Pachyonychia congenita, Jadassohn-Lewandowsky type
Dermatological 8
GTF2H5
Trichothiodystrophy, complementation group A, 9
PRSS2
Pancreatitis, chronic
Gastrointestinal 10
IL23R
Crohn disease 11
ABCG5
Sitosterolemia
Metabolic 12
HGD
Alkaptonuria 13
PPM2C
Pyruvate dehydrogenase phosphatase deficiency 14
A2M,APP
Alzheimer disease, susceptibility to, Emphysema due to alpha-2-macroglobulin deficiency
Neurological 15
ATXN8OS
Spinocerebellar ataxia 8 16
ATXN1
Spinocerebellar ataxia-1 17
PRKCH
Cerebral infarction 18
BFSP1
Cataract, cortical, juvenile-onset
Ophthamological 19
HTRA1
Macular degeneration, age-related, 7, Macular degeneration, age-related, neovascular type 20
HMCN1
Macular degeneration, age-related, 1, Posterior column ataxia with retinitis pigmentosa 21
PTGDR,IL12B,HNMT,PTGER2
Asthma
Respiratory

24. Conclusions
Observed 0.05 % to 1.46% of genomic fraction per individual
A set of genes that are encompassed in CNVRs are novel and not reported
in DGV (database of genomic variation).
Validation process of individual CNVs showed substantial heterogeneity
in the boundaries of CNVs within a gene.
CNVs can be shared between genetically related populations
Basal data for genomic region prone to CNVs in Indian population
CNV regions predispose to many diseases in Indian populations.

25. Role of CNVs as a genetic modifier in SCA12 phenotype

26. Investigating the involvement of CNV in sub-phenotypes of SCA12
Neuro-degenerative disorder
CAG repeat expansion in 5’ UTR region of PPP2R2B gene
Two distinct sub-phenotypes have been observed
Tremor dominant
Gait dominant
Could CNV be involved????

27. Validation (RealTime method) Functional annotation clustering
Workflow of CNV Identification
10 index cases of Gait
14 index cases of Tremor
SCA12
(CAG repeat in PPP2R2B)
Affymetrix 6.0 SNP array
CNV calling (PennCNV)
Gene Annotation
Validation (RealTime method)
Data QC
Functional annotation clustering
IE large populations

28. Copy number state distribution in SCA12 and IE population
CN state
Count in SCA12
Count in IE
987
389 1
2697
1226 3
257
465 4
158
Case control association analysis between gait and tremor groups
Chr
CNV start
CNV end
Sizes in Kb
Genes
Gait Del
Gait Dup
HT Del
HT Dup
p value
odds ratio (OR)
chr1
3.17
Non genic 1 4 2
Inf
chr1 4
32.1 6
chr5 51
GOLPH 3 5

29. Amplification of chr5p13.3 region in Gait Ataxia
GOLPH3 amplification
Real Time validation
5/8 of gait samples
0/14 of HT samples

30. GOLPH3 (golgi phosphoprotein 3 (coat-protein))
A Golgi localized protein
Have a regulatory role in Golgi trafficking
Identified as potent oncogene
modulates mTOR signaling
Inhibition of mTOR induces autophagy and reduces toxicity of polyglutamine expansions in fly and mouse models of Huntington disease
Brinda Ravikumar et al. Nature Genetics (2004)
Autophagy induction reduces mutant ataxin-3 levels and toxicity in a mouse model of spinocerebellar ataxia type 3
Fiona M. Menzies et al. Brain (2009)

31. Functional annotation clustering of genes under CNV specific to SCA12
Term
Count %
P value
Bonferron i
Benjamin i
Fold Enrichme nt
GO; ~ ion channel activity 18
6.593
3.74E-05
0.0172
3.2549
GO: ~substr ate specific channel activity
5.48E-05
0.0252
0.0084
3.1568
GO: ~chann el activity
8.39E-05
0.0383
0.0097
3.0495
GO: ~passiv e transmembrane transpore activity
8.64E-05
0.0394
0.0080
3.0421
significant enrichment of ion channel activity processes in SCA12

32. A multigene enrichment analysis for dissection of biological system
Biological process
Molecular functions

33. Cellular components
CNV in ion channel genes and its involvement in different biological, molecular
and cellular functions suggest physiological impairment in SCA12

34. Future direction

35. Conclusions
Although SCA12 is a monogenic disorder, phenotypic variability could be
due to other Genetic factors.
Amplification in GOLPH3 gene could be a modifier gene that leads to gait
ataxia feature.
As Autophagy pathway is influenced by GOLPH3 through mTOR pathway
that finally leads to Autophagolysis of inclusion bodies.
GOLPH3 could be good intervention molecule for SCA12 pathogenesis.
Ion channel genes and its implication in different neurological diseases,
suggests physiochemical abnormalities in SCA12

36. Conclusion of my PhD work ……………
“Any two individual genomes taken from nature, in any species, will have dozens
to hundreds of differences in their total number of functional genes.”
[Daniel R. Schrider and Matthew W. Hahn, Proc. R. Soc. B; 2010]
In conclusion our genome is less static and CNVs could play an
important role in dynamics of the genome that facilitates evolution,
adaptation and selection in populations and diseases due to dosage
effect of functional genes/regions.

37. Publications
Jha P, Sinha S, Kanchan K, Qidwai T, Narang A, Singh PK, Pati SS, Mohanty S, Mishra SK, Sharma SK, Awasthi S, Venkatesh V, Jain S, Basu A, Xu S; Indian Genome Variation Consortium, Mukerji M, Habib S. Deletion of the APOBEC3B gene strongly impacts susceptibility to falciparum malaria. Infect Genet Evol Jan;12(1):142-8.
Datta S, Chowdhury A, Ghosh M, Das K, Jha P, Colah R, Mukerji M, Majumder PP. A Genome-Wide Search for Non-UGT1A1 Markers Associated with Unconjugated Bilirubin Level Reveals Significant Association with a Polymorphic Marker Near a Gene of the Nucleoporin Family. Ann Hum Genet Jan;76(1):33-41.
Abhimanyu, Indian Genome variation consortium, Jha P and Mridula Bose. Footprints of genetic susceptibility to pulmonary tuberculosis: Cytokine gene variants in north Indians. Indian J Med Res., 2011 (accepted)
Lall M, Thakur S, Puri R, Verma I, Mukerji M, Jha P. A 54 Mb 11qter duplication and 0.9 Mb 1q44 deletion in a child with laryngomalacia and agenesis of corpus callosum. Mol Cytogenet Sep 21;4:19.

38. Gautam P*, Jha P*, Kumar D, Tyagi S, Varma B, Dash D, Mukhopadhyay A;
Indian Genome Variation Consortium, Mukerji M. Spectrum of large copy number
variations in 26 diverse Indian populations: potential involvement in phenotypic diversity.
Hum Genet Jul 9. * Equal contributing authors.
Ankita Narang*, Jha P*, Vimal Rawat, Arijit Mukhopadhayay, Debasis Dash, Analabha Basu,
Mitali Mukerji. Recent admixture in an Indian population of African ancestry.
Am. J. Hum. Genet Jul 5. * Equal contributing authors.
Jha P, Suri V, Sharma V, Singh G, Sharma MC, Pathak P, Chosdol K, Jha P, Suri A,
Mahapatra AK, Kale SS, Sarkar C. IDH1 mutations in gliomas: First series from a tertiary care
centre in India with comprehensive review of literature. Exp Mol Pathol. 2011
May 3;91(1):
Abhimanyu, Jha P, Jain A, Arora K, Bose M. Genetic association study suggests a role for
SP110 variants in lymph node tuberculosis but not pulmonary tuberculosis in north Indians.
Hum Immunol Apr 20.
Abhimanyu, Mangangcha IR, Jha P, Arora K, Mukerji M, Banavaliker JN, Consortium IG,
Brahmachari V, Bose M. Differential serum cytokine levels are associated with cytokine gene
polymorphisms in north Indian populations with active pulmonary tuberculosis.
Infect Genet Evol Apr 1.

39. Jha P, Suri V, Jain A, Sharma MC, Pathak P, Jha P, Srivastava A, Suri A, Gupta D, Chosdol K, Chattopadhyay P, Sarkar C. O6-methylguanine DNA methyltransferase gene promoter methylation status in gliomas and its correlation with other molecular alterations: first Indian report with review of challenges for use in customized treatment. Neurosurgery Dec; 67(6):
Jha P, Jha P, Pathak P, Chosdol K, Suri V, Sharma MC, Kumar G, Singh M, Mahapatra AK, Sarkar C. TP53 polymorphisms in gliomas from Indian patients: Study of codon 72 genotype, rs , rs , and 16 base pair insertion in intron-3. Exp Mol Pathol Apr;90(2): (2010) Nov 27.
Aggarwal S, Negi S, Jha P, Singh PK, Stobdan T, Pasha MA, Ghosh S, Agrawal A; Indian Genome Variation Consortium, Prasher B, Mukerji M. EGLN1 involvement in high-altitude adaptation revealed through genetic analysis of extreme constitution types defined in Ayurveda. Proc Natl Acad Sci U S A. (2010) Nov 2;107(44):
HUGO Pan-Asian SNP Consortium, Mapping human genetic diversity in Asia. Science. (2009) Dec 11;326(5959):1541-5
Indian Genome Variation Consortium. Genetic landscape of the people of India: a canvas for disease gene exploration. J Genet. (2008) Apr;87(1):3-20.

40. Acknowledgements TCGA for Genotyping Facility
CSIR
TCGA for Genotyping Facility
Indian Genome Variation Consortium

41. Thank you

42. Extra slides

43. Copy Number Variation in Indian Population
547 healthy individuals from26 Reference Population
from Indian Genome Variation Consortium
Affymetrix 50k Xba 240 array
(raw intensity file)
CNV calling and QC
(Genotyping Console+SVS7)
≥ 10 probes
≥ 100 kb segment
Reference Sample(30)
Test Sample(447)
Common CNV
(> 5% of samples)
Rare CNV
(< 5% of samples)
Validation using Sequenom
massARRAY QGE assay
(a subset of 12 genes)
Functional Enrichment
Analysis
Mapping with Disease
Associated regions
Genotype QC

46. Too many heterozygotes
Test for HWE
Ins Homo
Heterozygote
Del Homo
HWE test p-value
Endemic case 29 41 3
0.018
Too many heterozygotes
Endemic control 64 18
0.586
Non-endemic case 56 11 17
7.95 × 10-9
Loss of too many heterozygotes
Non-endemic control 51 25 5
0.508
HWD generally indicates some kind of natural selection, after data quality control
for genotyping error and population stratification

48. Points-
1- Chromosomal landscape is sparser as compared to earlier.

51. Future direction SCA12 modifier genes GOLPH3 Amplification
mTOR Pathway
AUTOPHAGY
Amplification
Induction of
mTOR pathway
Autophagy Inhibition
Aggregate formation
Neurodegeneration
SCA12 modifier genes