1. Precise Identification of Structural Variations in the Human Genome by Splitting Shotgun Reads
Zemin Ning1, Anthony Cox1, David Adams1, Paul Flicek2, Charles Shaw-Smith1,
Mark Griffiths1, Adam Spargo1, Jane Rogers1 and Richard Durbin1
1The Wellcome Trust Sanger Institute
2EMBL-EBI, Wellcome Trust Genome Campus,
Hinxton, Cambridge CB10 1SA UK S
Target Site Duplications and Length Distribution
INTRODUCTION
  A large extent of structural variations exists in the human genome between individuals1,2. Disease and disease susceptibility may be associated with this type of genetic variation.. Current experimental or computational methods provide a means to study human diversity and investigations include copy-number variations using array CGH3,4, identification of insertions/deletions using sequencing traces5, and fine scale mapping using pair-ending fosmids6, from which hundreds of submicroscopic copy-number variants and inversions have been identified. It was reported that the sequences involved sometimes contained entire genes and their regulatory regions, up to millions of DNA bases in size. However, the comparative microarray studies reported in the literature lack the sequence level precision on breakpoints and also the surveys were only on a small fraction of the sequence. The in silico strategy6 using fosmid ends achieved higher resolution, but it still cannot, in most cases, provide exact loci for breakpoints, nor a solution to detect variants less than 5 kb. Short indels (<50 bps) can be identified by aligning shotgun reads against the genome assembly. However, there is still much progress to be made in order to detect accurately all types of structural variations in the different size ranges.
We have developed a computational method for the precise identification of structural variants across the genome by aligning shotgun reads against the reference sequence. As individual reads covering the boundaries of variation regions are split, this enables us to pinpoint the exact breakpoint loci as well as to extract sequences involved between the boundaries if applicable. DNA samples used in this analysis were from 10 different human individuals and one chimpanzee male with a total number of 74 million shotgun reads, providing a wealth of resources and diversity in studying structural variations in the human genome.
Reference
Sample Reads
VNTR a b
d ’
d ’’
Deletion d
Figure 1. Length distribution of structural variants with Chimp ancestral data included.
Figure 2. Length distribution of target site duplications.
Detection of Structural Variants
Deletion b a
(a) Deletion
Sample Reads
Reference
Insertion
VNTR
(b) Insertion
(d) VNTRs
(c) Insertion with sequence 2’ A’ 1
A’’ 1’ 2
Experimental validation – PCR Tests
1. Insertion Chr1:
2. Deletion Chr1:
4. Insertion Chr13:
3. Deletion Chr6:
Results and Conclusion
DNA Sources and Reads
Exonic, Intronic and Noncoding Mapping
2549
145
236
285
1831
1281 A B C
  A total number of 7,293 structural variants have been identified: 2,500 deletions, 2,358 insertions and 2,435 VNTRs, using 44 million shotgun reads from 10 different human individuals. To assess the ancentral states of variation with the chimpanzee genome, we also used 30 million chimp reads. Compared with one existing database dbRIP7 of structural variations, there are 545 exact matches among 2095 retrotransposon insertion polymorphisms (L1, Alu and SVA).
66% of sequences of structural variants can be masked as retrotransposons; 28% of human variants share the same location with the chimp, i.e. ancestral states; 89% of ancestral deletions are retrotransposons, 66% for VNTRs; 38% of variants are located in exon/intro regions;
Conclusion: Mobile transposons are significantly more active in the intro-genetic regions and this might lead to phenotype differences among human individuals.
Type of Variation
Coding_Exonic
Coding_Intronic
Noncoding
Total
SV_deletion 17
892
1591
2500
SV_insertion 2
897
1459
2358
SV_VNTRs 8
966
1461
2435
Species
Cell lines
Number of reads
Human
HAPMAP 17109
1,841,054
HAPMAP 17119
5,977,374
HAPMAP 11321
4,488,765
HAPMAP 07340
3,728,821
HAPMAP 10470
557,845
Celera HuAA
2,788,046
Celera HuBB
19,397,599
Celera HuCC
1,745,337
Celea HuDD
2,011,152
Celera HuFF
1,507,522
Total Human
44,043,515
Chimpanzee
Clint
30,838,333
Total Reads
74,881,848
Genes Affected by Detected Variants
Type of Variation
Chr
Name of the gene
offset_start
offset_end
SV_deletion 1
SEC22L1 10
ENSG
SFMBT2 11
ENK17_HUMAN
FAM55A 16
UBN1 18
DHFR 21
BAGE4 22
ARVCF
GSTT2
Q8N7Q6_HUMAN
XP_ 3
PFN2
Q96EG4_HUMAN 4
Q9UN78_HUMAN 6
ENSG
KIAA1949
SV_insertion 12
KRT4 2
ENSG
SV_VNTRs 13
ENSG
Q8WYY0_HUMAN
NP_
655266
655362 17
KRTAP4-10
ENOSF1
702428
702517
CU025_HUMAN
KIF25 X
FMR1NB
(a)
230
331
903
658
296
1171 C B A
(b)
Chromosomes, Reads and Structural Variants
Figure 3. Data overlaps among three datasets:
A – Devine_lab5; B – This Study; C – dbRIP7.
(a) Deletion; (b) Insertion.
Chr
No Reads
Chr_Size
Deleletion
Deletion/Size
Insertion
Insertion/Size
VNTRs
VNTRs/Size
Total
Total/Size 1
194
191
182
567 2
147
146
127
420 3
128
114
123
365 4
139
104
115
358 5
110 80 86
276 6
224
219
662 7
154
132
400 8
112 83 74
269 9
119
100
333 10
149
158
456 11
152
168
130
450 12
142
430 13
141
416 14
886057 58 48 55
161 15
959438 64 72 71
207 16
858369 70 51 85
206 17
848567 61 50 78
189 18
744095 57
155 19
636170 41 35 20 82 81
245 21
399977 37 22
811301 54 62 88
204 X
105 69
255 Y
96878
2500
0.813
2358
0.767
2435
0.791
7293
2.371
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Acknowledgement: The Project is funded by the Wellcome Trust.