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VCGDB: A Virtual and Dynamic Genome
Database of the Chinese Population
Jiayan Wu
Associate Professor
Director of Science and Technology Department
Director of Core Facility
Beijing Institute of Genomics, Chinese Academy of Sciences
2015-04-25
Outline
 Background
 Data source
 Analyze workflow
 Result interpretation
 Database construction
 Genome visualization tool
 Summary
 Perspective
Background (Big data)
4’V’ definition of Big data: Volume,Variety,Veracity,Velocity.
Meyer M A, Laney D. Gartner, 2012,1.
Knowledge
Information
Information
Size
Data
Data
Knowledge
Computer Science/Domain Science
Domain Science/Computer Science
Year
Background (references)
Current reference genome: linear, static sequence from limited samples.
UCSC Human Genome
Feb. 2009 (hg19)
Mar. 2006 (hg18)
May. 2004 (hg17)
NCBI Human Genome
Jul. 2003 (hg16)
Apr. 2003 (hg15)
Reference
Year
Platform
Method
Caucasian individual(CEU)
2007
ABI 3730XL
De novo assembly
Yoruba individual(YRI)
2008
Illumina GA1s
MAQ mapping
Chinese individual(YH)
2008
Illumina GA
SOAP mapping+assembly
Korean individual(AK1)
2009
Illumina GA
GMAP mapping
Irish individual
2010
Illumina GAII
SNP calling
Background (projects)
 Human Genome Draft 2001

The human genome holds an extraordinary trove of
information about human development, physiology,
medicine and evolution.
International Human Genome Mapping Consortium. Nature, 2001, 409(6822):934-941
 1000 Genomes Project 2008

The first project to sequence the genomes of a large
number of people, to provide a comprehensive
resource on human genetic variation.
1000 Genomes Project Consortium. Nature, 2010, 467(7319):1061-1073.
Data source
Code
Population
Record Sample
Read Count
Base Count
CHB Chinese Han in Beijing 2690
147
36,855,116,194
2.08E+12
CHS
762
100
21,619,855,963
1.61E+12
3452
247
58,474,972,157
3.69E+12
Chinese Han South
Total
CHN: Chinese population
CHB:
North Chinese sub-population
CHS:
South Chinese sub-population
Dynamic genome:
Data Capacity
(After Compression)
CHS RAW
1.3 TB
CHB RAW
2.0 TB
CHS BAM
2.0 TB
CHB BAM
2.8 TB
complex, dynamic, widely related personal human genomes contain
genome variations, insertions/deletions, structure variations, etc.
Concentrate
on big differentiation.
data: Quantity, Handling, Usage
to reveal
potential population
Data analyze workflow

Data preprocessing

Data size reduction

Sample level analysis

Population level analysis

Genomic annotation

Result interpretation
Data size reduction
194 pileup files, 70+GB/file, 15TB in total
Chrom
Position
Ref
Sample 1 Sample 3 Sample 4 Sample 5 Sample 6
Chr10
10001
A
AAAA
AAAAA
AAAAAA
Chr10
10002
A
AAAA
AAAAT
AA
Chr10
10003
G
GGGG
GGGGGG
GGGGG
Chr10
10004
C
CCCC
Chr11
10002
A
AAAT
AAAAAG
TTTAAA
TTTTTA
Chr11
10010
G
GG
GGGG
GGGGGT
GGG
Chr12
10003
G
CCC
CCC
CCCCCC
C
Chr12
10004
G
GGG
TTT
GGGGT
G
ChrX
10005
A
AAAAAA
AAAAAA
AAAAAA
AAAAAA
GGGGG
GGGGGG
CC
AAAAAA
AAAAAA
Candidate dynamic information
Candidate dynamic information of 55,549,120 CDPs.
Data volume reduced by 98% without losing any detail information.
10
4
CDP Average(max-min) Coverage Status
10 3
10 2
10 1
0
CHS_RANGE
CHB_RANGE
CHS_AVG
CHB_AVG
Data analyze workflow

Data preprocessing

Data size reduction

Sample level analysis

Population level analysis

Genomic annotation

Result interpretation
Genetic variation analysis
Single high-coverage sample:
AAAAAAATTAAAAAAAAGAACAAAATTTTTAAAAAAAAAATTTTCAA
Multiple low-coverage samples:
AAAAT AAAT AAT TTT AAAAG AAAAC AAAC AAAAG AAAAC
AAAAAAAAAAAAAAAAAAAAAAAAAAAATTTTTTGGCCC
AAAAT AAAT AAT TTT AAAAG AAAAC AAAC AAAAG
Sample level:
Population level:
A
A
A
T
A
AAAAAAT
A
A
A
Dynamic position types
Major allele against GRCh37 reference genome.
MAIR
High probability (≥50%) indel position.
Minor allele (>5%) against GRCh37 reference genome.
Rare variation (≤5%) against GRCh37 reference
genome.
Dynamic information statistics
Genomic annotation(Annovar)
Enrichment analysis of MAIR in GWAS trait locations in the Chinese and GRCh37 genomes
Top Matches
CHN
CHS
CHB
1
Height (110/324)
Height (108/324)
Height (110/324)
2
Multiple sclerosis (41/187)
Multiple sclerosis (41/187)
Multiple sclerosis (41/187)
3
Crohn's disease (36/181)
Crohn's disease (40/181)
Crohn's disease (38/181)
4
Body mass index (34/109)
Body mass index (34/109)
Coronary heart disease (37/151)
5
Coronary heart disease (34/151)
Coronary heart disease (33/151)
Body mass index (36/109)
6
Type 2 diabetes (33/164)
Type 2 diabetes (32/164)
Bipolar disorder (32/109)
7
Rheumatoid arthritis (31/170)
LDL cholesterol (32/114)
Type 2 diabetes (31/164)
8
LDL cholesterol (31/114)
HDL cholesterol (31/118)
Rheumatoid arthritis (30/170)
9
Bipolar disorder (30/109)
Type 1 diabetes (29/107)
Bone mineral density (30/87)
10
Bone mineral density (30/87)
Bone mineral density (29/87)
LDL cholesterol (30/114)
Chinese population comparison
Consensus Chinese genomes
Use anti-conflict algorithm to generate the consensus reference genome.
Population-specific
against ref positions
Major indels
CHS reference
HG19
reference
Analyze
conflicts
CHB reference
CHN reference
Mapping of 15 Asian genomes onto the VCG, YH and GRCh37 reference genomes.
Database Construction
Database: MySQL
Engine: MyISAM
Tables: 128
Data size: 50GB
Index size: 4.9GB
Records: 183,919,098
Database Optimizing
 Data level optimizing
 Separate data by chromosome
 “BTree” indexes support “<>=” query
 Reasonable split sequences ---- “ref table”
 MySQL level optimizing
Database Capacity
Dynamic Pos CHN Dynamic Pos CHS Dynamic Pos CHB
Autosome
33,780,152
19,591,609
24,109,529
Heterosome
1,747,140
937,088
1,222,844
1,006
673
654
35,528,298
20,529,370
25,333,027
Indel CHN
Indel CHS
Indel CHB
Autosome
392,074
454,215
345,647
Heterosome
14,360
17,323
12,346
25
20
59
406,459
471,558
358,052
Chondriosome
Total
Chondriosome
Total
Rare Variant CHN Rare Variant CHS Rare Variant CHB
Autosome
27,258,690
12,505,097
17,688,051
Heterosome
1,477,821
632,253
939,627
907
569
536
28,737,418
13,137,919
18,628,214
Chondriosome
Total
VCGDB contains 35
millions of single nucleotide
variations, 0.5 millions of
indels and 29 millions of rare
variations, associate with
position based genomic
annotation information and
consensus reference genomes
of defined populations in
China, instead of the former
static linear sequence.
http://vcg.cbi.ac.cn
Search Page
Browser Page
Web search page features
1. Fuzzy search
Web searching is implemented with
HGNC that realize fuzzy searching
of genes.
2. Dynamic level sorting
All columns containing dynamic
level of the positions can be
sorted by clicking the title.
3. VCGBrowser linkage
Help users to locate the region
they want to browse easily.
VCGBrowser development
Features:
 Searching optimization
 Cross platform
 Large region browse
 Genome comparison
 Seemless zooming
 Drag zooming
 Real-time searching
Cross platform Usage
Users have three ways to use VCGBrowser. It is both a web-based applet and
a client-based cross platform application, which can be used either in an internet
browser or downloaded as a local software. Also users can use our java web start
jnlp to run a local application online.
Web Applet
Local Application
Java Web Start JNLP
Feature: seamless zooming
VCGBrowser has a
zoom bar on the left that
support a smooth real-time
seamless zooming to any
resolution from the
genomic level that shows
the dynamic distribution of
interested region, to the
nucleotide level that all
residues and detail
information can be
recognized clearly.
Feature: drag zooming
Drag Zooming:
Drag the mouse on any
region you are interested
in, and the browser
would instantly zoom to
the region you select.
Large region browse and comparison
VCGBrowser:
Up to chromosome
level browsing.
Down to nucleoside
level comparison.
Feature: real-time querying
Reference area
GRCh37 ref
refGene
duplication
gwas
CHN dynamic bar
CHN area
CHN ref
CHN indel
CHN rare variant
CHS dynamic bar
CHS area
CHS ref
CHS indel
CHS rare variant
CHB dynamic bar
CHB area
CHB ref
CHB indel
CHB rare variant
Summary
VCGDB is a “virtual” database
VCGDB is “virtual” because the reference genome provided in the database
is the statistical result of terabases of sequencing data from hundreds of
Chinese individuals that describe the genetic variation features specific to the
Chinese population.
chr
pos
nuc
support
1
14635
A
*180
1
14636
T
*180
6
34632
G
*107
6
44632
+AA
*187
21
54322
-G
*190
X
34221
T
*93
Summary
VCGDB is a “dynamic” database
VCGDB is “dynamic” because we use methods as comentropy to analyze
and evaluate the dynamic variation rate and probability of all genetic variation
information in several levels like sample or population and integrate them with
individual characters and genomic annotation information.
T C A ACG T TACG
Gene: PALB2
GWAS: Biopolar disorder
Summary
VCGDB is a big data solution
VCGDB offers a feasible strategy for processing big data to keep pace with
the growing volume of biological data and provides a robust resource based on
the massive amounts of genomics data for genomics studies and investigations
into genetic diseases.
VCGBrowser is a flexible genome visualization tool
VCGDB also provides a highly interactive user-friendly virtual Chinese
genome browser (VCGBrowser) with functions like fuzzy searching, seamless
zooming and real-time searching. Users can use mature databases and analysis
tools process their researches.
Perspectives
Bigger data and higher coverage
Sequencing projects such as Precision Medicine Initiative, UK10K, The
Cancer Genome Atlas (TCGA), and deCODE Genetics in Iceland are and/or will
generate ultra-large volumes of human genome data with higher coverage.
How about Chinese population?
More accurate algorithm and cloud based platform
 Genome alignment software support dynamic genome
 Data analyze platform based on cloud or supercomputing
Acknowledgement
Thanks for
Dr. Yunchao Ling & Dr. Jingfa Xiao
Thank you!