HIVID技术检测HBV病毒整合

HIVID:An ef ?cient method to detect HBV integration using low coverage sequencing ☆

Weiyang Li a ,b ,1,Xi Zeng a ,1,Nikki P.Lee c ,1,Xiao Liu a ,Shengpei Chen a ,Bing Guo a ,Shang Yi a ,

Xuehan Zhuang a ,Fang Chen a ,Guan Wang a ,Ronnie T.Poon c ,Sheung Tat Fan c ,Mao Mao d ,Yingrui Li a ,Songgang Li a ,Jun Wang a ,JianWang a ,Xun Xu a ,Hui Jiang a ,Xiuqing Zhang e ,?

a

BGI-Shenzhen,Shenzhen,518083,China

b

School of Bioscience and Bioengineering,South China University of Technology,China c

Department of Surgery,University of Hong Kong,Hong Kong,China d

P ?zer Oncology,San Diego,CA 92121,USA e

The Guangdong Enterprise Key Laboratory of Human Disease Genomics,BGI-Shenzhen,Shenzhen,China

a b s t r a c t

a r t i c l e i n f o Article history:

Received 18January 2013Accepted 8July 2013Available online xxxx Keywords:

Hepatocellular carcinoma Integration Capture

High-throughput Cost-effective

We reported HIVID (high-throughput Viral Integration Detection),a novel experimental and computational method to detect the location of Hepatitis B Virus (HBV)integration breakpoints in Hepatocellular Carcinoma (HCC)genome.In this method,the fragments with HBV sequence were enriched by a set of HBV probes and then processed to high-throughput sequencing.In order to evaluate the performance of HIVID,we compared the results of HIVID with that of whole genome sequencing method (WGS)in 28HCC tumors.We detected a total of 246HBV integration breakpoints in HCC genome,113out of which were within 400bp upstream or downstream of 125breakpoints identi ?ed by WGS method,covering 89.3%(125/140)of total breakpoints.The integration was located in the gene TERT,MLL4,and CCNE1.In addition,we discovered 133novel breakpoints missed by WGS method,with 66.7%(10/15)of validation rate.Our study shows HIVID is a cost-effective methodol-ogy with high speci ?city and sensitivity to identify viral integration in human genome.

?2013The Authors.Published by Elsevier Inc.All rights reserved.

1.Introduction

More than 350million people are infected by hepatitis B virus (HBV)all over the world [1,2],and approximately 30%–50%of the estimated 320,000annual HBV-related deaths are consequences of hepatocellular carcinoma (HCC)[3].Previous studies have discovered evidence of the involvement of HBV in the tumorigenesis [4,5],indi-cating HBV integration in host genome is suspected to be one of the most important etiological events in HBV-induced HCC [6].The recur-rent HBV integration event was ?rst reported to be located at the TERT gene in two HCC tumor samples [7,8],and subsequent studies also identi ?ed HBV integration breakpoints in FAR2,ITPR1(IP3R1),IRAK2,MAPK1,MLL2and MLL4genes [9,10].Previous reports have suggested that a number of cellular genes such as hTERT and FN1were frequently targeted by HBV in HCC tissue [7,9,10].Although HBV integration into the host genome has been reported in tumors from HBV-infected individuals,the mechanism of viral-host interaction

remains elusive.However,previous studies indicated integration of HBV can change the expression level and function of endogenous https://www.360docs.net/doc/0e7900596.html,parative analysis of gene expression levels indicated that samples with HBV integration demonstrated higher expression of TERT,MLL4and CCNE1than those samples not harboring HBV DNA integration [11].It is intriguing that the overall MLL4transcription output is much higher in the affected genome,but the resulting fusion transcript lacks the AT-hook DNA-binding domain of MLL4[12].Moreover,HBV integration was also reported to relate with somatic copy number variations [11].DNA copy number analysis in this region revealed that this viral integra-tion colocalized precisely with the junction of a large DNA copy number loss [12].

Traditionally,most of the HBV integration breakpoints are detect-ed by PCR-based methods,such as Alu-HBV PCR.In the process of Alu-HBV PCR,signi ?cant bias happens towards Alu regions;in other words,only the integration near Alu region can be ef ?ciently detected [9,13].It is still a challenge to study integrations at genome-wide scale using PCR-based methods.With the rapid development of mas-sive parallel sequencing technology,whole genome sequencing (WGS)brings new insight to detect HBV integration in HCC genome [11,12,14].However,this approach is also limited by the high cost to perform population-scale studies.Thus,a sensitive low cost method is urgently needed to study the relationship between virus integration and tumorigenesis.

Genomics xxx (2013)xxx –xxx

☆This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works License,which permits non-commercial use,distribution,and reproduction in any medium,provided the original author and source are credited.

?Corresponding author.Fax:+8675525273884.E-mail address:zhangxq@https://www.360docs.net/doc/0e7900596.html, (X.Zhang).1

These authors contributed equally to this work.

YGENO-08536;No.of pages:7;4C:

0888-7543/$–see front matter ?2013The Authors.Published by Elsevier Inc.All rights reserved.https://www.360docs.net/doc/0e7900596.html,/10.1016/j.ygeno.2013.07.002

Contents lists available at ScienceDirect

Genomics

j o u r n a l h o m e p a ge :w ww.e l s e v i e r.c o m/l o c a t e /y g e n o

Here,we present a novel experimental and computational meth-od,HIVID (high-throughput viral integration detection),to effectively detect hbv integration at a single base pair resolution using HBV cap-ture sequencing (Fig.1).Probes were prepared to capture the HBV inserted fragments in host genome and these fragments were further sequenced on Illumina HiSeq 2000platform.Based on the sequence data of enriched DNA,we recruited a pair-read assemble strategy to locate the integration breakpoints.To examine the performance of HIVID,this method was tested in 28HCC samples that were previously sequenced at the whole-genome level for identifying HBV integrations [11].The integration hotspots of human genome were located in the genes TERT,MLL4and CCNE1.Most of the breakpoints were signi ?cantly enriched in a 500bp region on HBV genome from 1500bp to 2000bp.We compared the results of HIVID and WGS method,and validated the novel HBV integration using PCR and Sanger sequencing.Our study provided an accurate and cost-effective method for HBV integration re-search,which can also be adapted to other virus integration studies.2.Materials and methods

Based on our previous study [11],28Chinese HCC samples from Queen Mary Hospital,Hong Kong were selected.All patients had been diagnosed with HCC with concurrent HBV https://www.360docs.net/doc/0e7900596.html,rmed written consents were obtained from each patient.Approvals were acquired from the BGI Ethics Committee and the Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster.All samples had been previously used to discover HBV integration breakpoints.The results from 30×WGS data were used to evaluate sensitivity and speci ?city of HIVID.2.1.HBV probes preparation

Full-length HBV genome of type B and type C were ampli ?ed by PCR using biotin-labeled dNTPs.PCR mix was prepared as follows:5μl of HBV DNA (1ng/μl);5μl of 10*LA Taq Buffer;26.5μl of H 2O;

4μl of 2.5mM dNTPs (1/4dNTPs biotin-labeled);2.5μl of 10pmol P1(TTT TTC ACC TCT GCC TAA TCA);2.5μl of 10pmol P2(AAA AAGTTG CAT GGT GCT GG);and 0.5μl of LA Taq enzyme (Takara Bio,Inc.).PCR was subjected to the following cycling condition:initial denaturation for 3min at 94°C;32cycles of denaturation for 30s at 94°C,annealing for 50s at 56°C,and extension for 2.5min at 68°C;?nal extension for 10min at 72°C.Amplicons were puri ?ed by Ampure beads (Beckman Coulter,Inc.)and were then fragmented by Covaris E-210(Covaris,Inc.,Woburn,MA)to 250bp –500bp through the 2%agarose electrophoresis.Single-stranded HBV probes were generated by high temperature denaturation at 94°C for 5min.2.2.HBV-inserted fragments enrichment and sequencing

Sequencing libraries of 170bp insert size were constructed for 28samples following the instruction of Illumina.Genomic DNA was sheared to around 150bp –200bp DNA fragments by Covaris E-210(Covaris,Inc.,Woburn,MA).These fragments were puri ?ed,end blunted,“A ”tailed,and adaptor ligated.10cycles of PCR were performed after size selection in 2%agarose gel.The concentration of libraries was quanti ?ed by Bioanalyzer 2100(Agilent Technologies,Santa Clara,CA).Libraries were hybridized with HBV probes at 47°C for 24hours and then washed to remove un-captured fragments.The eluted fragments were ampli ?ed by 16cycles of PCR to generate libraries for sequencing (Fig.2).Libraries were quanti ?ed and proceeded to 101cycles paired-end index sequencing in the Illumina HiSeq 2000sequencer according to manufacturer's instructions (Illumina Inc.,San Diego,CA).2.3.HBV integration breakpoints detection

The whole pipeline for data analysis in HIVID consists of six steps (Fig.1).After we isolated the paired-end reads which may contain the signals of HBV integration,paired-end read assembly was conducted to obtain reconstructed inserted fragment and detected HBV integra-tion

breakpoints.

Fig.1.Overall work ?ow of HIVID.The pipeline includes the work ?ow of experiment and bioinformatics process.In the process,we do Raw data ?lter ?rst,then perform Raw-mapping with ?ltered raw data.After that we pick out the chimeric paired-end reads to do Paired-end read assembly.PE-assembled reads are conducted to go through Re-mapping to locate the HBV integrations sites.Finally,Signal merging and Signal ?lter are performed to obtain the ?nal results.To do the step of Paired-end reads assembly,we used a program developed by ourselves.

2W.Li et al./Genomics xxx (2013)xxx –xxx

2.3.1.Raw data ?lter

Low quality reads and duplication reads,as well as adaptor contami-nation reads,was ?rst removed to obtain clean reads for subsequent analysis.If a read whose bases with quality value (b =5)occupy 50%of the read length,the read is considered as a low quality read.We then had the clean reads for detecting the HBV integration after the low qual-ity reads and duplication reads removal.

2.3.2.Raw-mapping

Clean reads were mapped to human (NCBI build 37,HG19)and HBV genome using SOAP2(-l 40-v 5-r 1)[15].We removed reads that perfectly paired-end aligned to human or HBV genome and reserved chimeric paired-end reads (partial read sequence aligned to human genome and partial aligned to HBV genome)for assembly.This might help identify HBV integration breakpoint.

2.3.3.Paired-end reads assembly

Paired-end reads assembly was used to reconstruct around 170bp of fragment sequences,assembly which might increase the potential to locate the exact position of breakpoints.The paired-end reads were ?rst changed to the same strand.In case that the tail of an upstream end (read1)and the head of a downstream end (read2)overlap by more than 5bp where the mismatch rate was less than 0.2,the two ends would be spliced into one continuous sequence,called PE-assembled read,which was reconstructed inserted fragment (Fig.3A).

2.3.4.Re-mapping

To determine the exact location of HBV integration breakpoint,the PE-assembled reads were re-mapped to human and HBV genome using BWA 0.5.9-r16(-a 1,-b 2,-q,5,-r,2)[16].If the match length on both HBV genome reference and human genome reference for one PE-assembled read was larger than 30bp,the PE-assembled read alignment result was reported to detect a precise breakpoint.The joint position of human and HBV sequence was the breakpoints for HBV inte-gration (Fig.3B).

2.3.5.Signal merging

We also calculated the total number of support PE-assembled reads (NSS)of each HBV integration breakpoint to examine its reliability.

Considering errors in the procedure of experiment and bioinformatics analysis and highly heterogeneous nature of tumors,we merged breakpoints within 20bp to select the breakpoint with largest NSS as the representative,and reset its NSS as sum of NSS of all breakpoints in this region.

2.3.6.Signal ?lter

To minimize the impact of total sequencing data for each breakpoint frequency and remove the noise signals,we normalized NSS to Normal-ized number of support PE-assembled reads (NNSS)using its number of effective paired-reads (EFR)as following:NNSS ?NSS ?106

=EFR

Effective paired-reads are de ?ned as reads used to search breakpoints except contaminated data.NNSS could be considered as the number of supporting reads of each HBV integration breakpoint out of every million read-pairs and represents the reliability and data utilization with no bias.In this study,HBV breakpoints with NNSS N =1was regarded as true signal.

2.4.PCR and Sanger sequencing validation

PCR and Sanger sequencing was used to verify the selected HBV integration breakpoints from HIVID.PCR primers were designed based on the PE-assembled fragment,in which one primer located in human genome and the other in HBV genome.PCR were performed by GeneAmp?PCR System 9700thermal cycler and then preceded to Sanger sequencing on Applied Biosystems 3730x DNA analyzer (Life Technologies,Inc).3.Results

3.1.HBV integration breakpoints detection

To get the overall evaluation of the accuracy of breakpoint detection using HIVID approach,we compared our results to that of previously re-ported ~30×WGS approach [11].Sung et al.reported a total of 399HBV integration breakpoints in 81HBV-positive and 7HBV-negative HCC and adjacent non-tumor samples,with a validation rate of 82.0%[11].We randomly selected 28samples for HIVID to conduct HBV capture sequencing on Illumina HiSeq 2000,generating ~1.43Gb on average (Table 1).The effect of paired-end reads for the following analysis were about 6millions,among them around 83.72%and 0.08%can be aligned to human genome and HBV genome,respectively.After paired-end assembly and re-mapping,we ?nally obtained an average of 1654reads supporting HBV integration breakpoints for each sample.A total of 246HBV integration breakpoints were detected within these 28sam-ples,in average 8.8breakpoints per sample.The number of integration breakpoints varied from 1to 27among samples (Table S1).3.2.HBV integration breakpoint detection comparison

We ?rstly compared HBV integration breakpoints between HIVID and WGS approach in 28selected samples.To minimize the impact of different work ?ows we de ?ned a shared breakpoint in HIVID and WGS method when the distance of two breakpoints from the same sam-ple was less than 400bp.There were 140HBV integration breakpoints from Sung's study with at least two paired-end reads supporting and 89.3%of them (125/140)was shared with HIVID test (Tables S2and S3),suggesting that the current approach has high speci ?city when com-pared with WGS approach.In contrast,only 45.9%of HBV integration breakpoints (113/246)from HIVID approach were shared with WGS approach (Fig.4).Fourteen of 113HBV integration sites that were select-ed for validation were all validated in previous WGS study,showing 100%validation rate [11].Further analysis for the average NNSS

value,

Fig.2.HBV capture work ?ow.The different colored images marked represented differ-ent meaning.The dark yellow color represented the HBV fragments,while the glaucous color represented the human genome fragments.DNA libraries were hybridized with HBV probes at 47°C for 24hours and then washed to remove un-captured fragments.The eluted fragments were ampli ?ed by 16cycles of PCR to generate libraries for se-quencing.(For interpretation of the references to color in this ?gure legend,the reader is referred to the web version of this article).

3

W.Li et al./Genomics xxx (2013)xxx –xxx

which was 13.6for 113WGS-shared HBV integration breakpoints and 8.5for all breakpoints,indicated WGS approach might tend to identify high frequency HBV integration breakpoints due to a relatively limited sequencing depth.The comparative analysis indicated HIVID test could detect almost the same HBV integration breakpoints as WGS approach with much less sequencing data.

In the 133novel breakpoints we randomly picked 15novel HBV integration breakpoints from six samples for PCR and Sanger sequencing validation test.66.7%(10/15)of novel HBV integration sites were suc-cessfully con ?rmed (Table S4),which is signi ?cantly lower than the validation rate for WGS-shared breakpoints.We then investigated the average NNSS value of the 133novel breakpoints,which were only 4.2,compared to 13.6for WGS-shared breakpoints and 8.5for the total ones.

It was obvious that HIVID showed a notable advantage on breakpoints enrichment ef ?ciency.On average,the HIVID approach generated 6mil-lion paired-end reads,compared to 600million read pairs for WGS meth-od.Moreover,the average NNSS values of two methods were 8.5and 0.0142,representing that HIVID approach could enrich HBV integration fragments close to 600times than WGS approach.This high ef ?ciency for HBV integration sites enrichment would be bene ?t for large-scale virus-related tumor development studies.

3.3.Characteristics of HBV integration breakpoints

We also investigated the characteristics of HBV integration breakpoints,which might be related with HCC development.Integra-tion events were detected in HBV subtype C (AB014381.1).Among them,33.5%(68/203;P =2.7×10?5)were signi ?cantly enriched in a 500bp region on HBV genome from 1500bp to 2000bp (Supplemen-tary Fig.S1),which was consistent with the results of the WGS study [11,12].Additionally,we also surveyed the frequency of integration breakpoints around HBV genes,showing 38.9%(79/203)breakpoints were located in the region of pre-S1(Table S5).

The analysis for recurrent genes with HBV integration breakpoints in those 28samples was also consistent with previous studies (Fig.5)[10,17–19].Using HIVID approach,HBV integration breakpoints were detected in TERT ,MLL4and CCNE1genes,affecting 25%,17.9%,and 7.1%of HCC samples (Table 2).Notably,we identi ?ed HBV integration breakpoint in TERT gene for sample 90T and 41T,which was missed in previous WGS approach.

Besides the frequent bias of HBV integration sites in HBV and human genome,we also noticed that HBV integration events with the deletion of human genome.For example,a 49bp human genome sequence in sample 43T was replaced by a 41bp HBV sequence on ChrX:20,156,148(Table S4).In sample 49T the human genome fragment of 728,975bp in chromosome 2were replaced by 127bp HBV sequence (Fig.6).The abundant supporting reads for breakpoints provided by HIVID may be helpful to explore the complex relation.4.Discussion

In this study,we developed a novel approach for HBV integration breakpoint detection and employed 28HCC samples to estimate the performance on integration sites with high frequency and low frequen-cy.With only 1.5Gb HBV capture sequencing data,HIVID approach can identify about 90%of HBV integration breakpoints identi ?ed from ~30×WGS data,and over 50%of novel low frequent integration sites missed by WGS approach.HIVID approach shows its strength on several aspects compared with previously reported approaches.

Unlike the widely used HBV-Alu PCR method,HIVID can be uti-lized to detect integration sites at the genome-wide level instead of the regions close to Alu repeats.In fact,83.3%(205/246)of the discov-ered HBV integration breakpoints were more than 10,000bp away from Alu repeats (Table S2),signi ?cantly larger than 7.8%of WGS ap-proach [11].Although both HIVID and WGS approach are based on mas-sively parallel sequencing platform,HIVID approach has dramatically higher ef ?ciency on virus integration detection.First,HIVID approach requires much less sequencing data due to the process of HBV

fragment

Fig.3.Insight of computational process of HIVID.A,principle of pair-end reads assembly.The ?gure shows that the tail of an upstream end (read1)and the head of a downstream end (read2)were spliced into one continuous sequence,called PE-assembled read;B,determination of breakpoint.The ?gure shows that one PE-assembled read consists of the part of human sequence and part of HBV sequence.The joint position was the breakpoint for HBV integration.

4W.Li et al./Genomics xxx (2013)xxx –xxx

capture,but with an enrichment close to 600times compared with WGS approach.HIVID could also be suitable for detecting the breakpoints of other types of viruses,such as human papillomavirus,human immuno-de ?ciency virus.Moreover,it also could decrease the cost and shorten the time to generate the results.Secondly,HIVID can detect 89.3%(125/140)integration breakpoints which had been identi ?ed by WGS method,and those integration sites are also characterized by higher NNSS and validation rate.These results demonstrate the HIVID method has a high speci ?city of detecting viral integration breakpoints.Thirdly,HIVID method is more sensitive for detecting low frequency HBV inte-gration breakpoints.Although the validation rate was 66.7%(10/15),HIVID methods could identify 50%more HBV integration sites.The reduced average NNSS value of the novel sites (4.2)compared with the WGS shared ones (13.6)indicates HBV integration in these sites may be less frequent among the tumor cells.The other cause for the lower veri ?cation rate of new breakpoints could be attributed to the primer design dif ?culty for the shorter support reads.The validation

rate might be improved if we adopt the 454long reads sequencing.The long reads also will help us to get more information about the HBV insertion sequence.The major limitation of this approach com-pared with WGS is that we can only target speci ?cally one or more virus that have genome references,and identify their integrations.This is a hypothesis driven approach.Another technical limitation is that human genome reads and free virus reads take up a high propor-tion of the data.The method had a low capture speci ?city,although it had an obvious enrichment.We will get more integration breakpoints and need less sequencing data if the capture speci ?city could get im-proved.The single cell study for virus integration breakpoints could ?g-ure out monoclonal evolution and the roles of high and low frequency integration events.Since we used part of samples from our previous study,the similar hotspot regions in human and HBV genome were de-tected with these two methods.However,with more supporting reads we annotated the complicated types of HBV integration events,which were omitted in our previous study.Herein,we found a trend of dele-tion in human genome accompanying with HBV fragments insertion,which might induce chromosomal instability and further carcinogene-sis.Genetic instability triggered by HBV integration has been considered in some reports to be an important contributing factor in the pathogen-esis of HCC [20,21].HBV insertions are commonly associated with large genetic alterations:deletions,duplications and chromosomal transloca-tions,which might re ?ect the abrogation of control mechanisms that safeguard chromosomal integrity [22].However,the impact of those human structure variations on molecular mechanism of HCC still re-mains unclear.

In summary we reported the HIVID approach to detect HBV inte-gration breakpoints with high speci ?city and sensitivity using only 1.5Gb sequencing data,for which this approach can be used to screen virus integration in a large cohort of samples and leads to a systematic study for its relationship with disease etiology and tumorigenesis in a comprehensive and unbiased way.

Supplementary data to this article can be found online at https://www.360docs.net/doc/0e7900596.html,/10.1016/j.ygeno.2013.07.002.

Table 1

Data production of 28tested samples.Sample Total Bases Reads number EFR (M paired-reads)Human alignment (pair end)HBV alignment (pair end)Integration rate 101T 1.50G 7.51M;7.51M 5.8895.58%0.03%738(0.01%)43T 1.32G 6.58M;6.58M 5.6686.30%0.04%2520(0.02%)71T 1.49G 7.45M;7.45M 6.4685.05%0.11%1858(0.01%)58T 1.47G 7.33M;7.33M 6.1684.35%0.05%1230(0.01%)34T 1.39G 6.93M;6.93M 5.9884.35%0.02%480(0.00%)55T 1.53G 7.63M;7.63M 6.4782.91%0.10%602(0.00%)35T 1.64G 8.22M;8.22M 7.0585.13%0.02%188(0.00%)41T 1.15G 5.77M;5.77M 4.9784.23%0.12%1042(0.01%)32T 0.70G 3.52M;3.52M 3.1287.08%0.08%424(0.01%)186T 1.99G 9.94M;9.94M 8.5986.70%0.01%374(0.00%)49T 1.17G 5.83M;5.83M 4.9582.61%0.11%2026(0.02%)26T 1.40G 7.01M;7.01M 5.9481.78%0.03%442(0.00%)90T 1.34G 6.70M;6.70M 5.8188.05%0.20%1212(0.01%)182T 1.55G 7.74M;7.74M 6.6887.93%0.03%474(0.00%)266T 1.36G 6.80M;6.80M 5.7786.27%0.03%860(0.01%)145T 1.41G 7.03M;7.03M 5.7486.09%0.08%1398(0.01%)174T 1.35G 6.75M;6.75M 5.7887.22%0.03%290(0.00%)122T 1.52G 7.59M;7.59M 6.4885.11%0.15%1086(0.01%)114T 1.85G 9.25M;9.25M 7.5986.53%0.01%176(0.00%)17T 1.47G 7.36M;7.36M 6.4386.35%0.23%584(0.00%)200T 1.45G 7.25M;7.25M 5.6274.33%0.18%1546(0.01%)95T 1.24G 6.21M;6.21M 5.1877.77%0.04%1546(0.01%)23T 1.17G 5.83M;5.83M 4.8879.94%0.08%2634(0.03%)64T 1.17G 5.83M;5.83M 4.8777.04%0.01%136(0.00%)30T 1.66G 8.28M;8.28M 6.9380.35%0.05%572(0.00%)65T 1.80G 9.01M;9.01M 7.5677.03%0.05%482(0.00%)70T 1.04G 5.19M;5.19M 4.3479.30%0.30%1752(0.02%)82T

1.90G

9.51

M;9.51

M

8.02

78.64%

0.03%

288(0.00%)

This table shows the data production of 28samples.Including human alignment ratio of pair-end reads,HBV alignment ratio of pair-end reads,raw data quantity and integration rate,

etc.

Fig.4.Overview of breakpoints detected by HIVID.The ?gure shows that HIVID detect-ed 246breakpoints on human genome in total.There were 113novel breakpoints and 133breakpoints shared with WGS method.The shared 133breakpoints covered 89.3%of WGS result.In addition the ?gure also provides the information of NNSS value and validated rate.

5

W.Li et al./Genomics xxx (2013)xxx –xxx

Fig.5.Distribution of breakpoints on human genome.In this CIRCOS ?gure,we showed the human chromosomes,the integration frequency of each breakpoint on the level of supporting reads and on the level of samples.The outer circle represents 24chromosomes and mitochondria with different color-code and number labeled.In the middle circle,the integration frequency of each breakpoint one the level of supporting reads is displayed as height of each blue point.In the inner circle,the height of each red point represents the integration frequency of each breakpoint on the level of samples.To explore the distribution of frequency of all integration breakpoints on the level of supporting reads,we pooled all breakpoints from all samples.We merged those breakpoints which appeared in several different samples but in the same location and reset NNSS of the new merged breakpoint as sum of NNSS of all breakpoints in this location.The new NNSS could be seen as the integration frequency of each merged breakpoint on the level of supporting reads.The middle circle was ?gured based on the process above and the NNSS of each merged breakpoint is displayed as the height of each blue point.To explore the distribution of frequency of integration breakpoints on the level of samples,the human genome sequence was divided into about three million windows,each with length of 1000bp.The total number of samples that the breakpoints in each window belonged to,was calculated.Each window was considered as one new breakpoint and the number of samples in each win-dow calculated above was considered as supporting samples that supported the window as a new breakpoint.The number could be seen as the integration frequency of each breakpoint on the level of samples.The inner circle was ?gured based on the process above and the height of each red point represents the integration frequency of each breakpoint on the level of samples.(For interpretation of the references to color in this ?gure legend,the reader is referred to the web version of this article).

Table 2

The enriched region of HBV integration.Sample ID Position

NSS NNSS Gene

266T chr5:1,295,4639716.82TERT:Promoter 34T chr5:1,295,3759616.05TERT:Promoter 58T chr5:1,295,3398012.98TERT:Promoter 65T chr5:1,295,4429712.82TERT:Promoter 90T chr5:1,295,6397212.38TERT:Promoter

41T chr5:1,295,12119 3.82TERT:NM_001193376:5-UTR;TERT:NM_198253:5-UTR;64T chr5:1,295,2959 1.85TERT:Promoter

49T chr19:36,212,74121242.83MLL4:NM_014727:Intron;71T chr19:36,213,142467.12MLL4:NM_014727:Intron;186T chr19:36,214,00716619.34MLL4:NM_014727:CDS;70T chr19:36,212,313465107.03MLL4:NM_014727:CDS;95T chr19:36,212,5665711.01MLL4:NM_014727:CDS;145T chr19:30,303,49923140.24CCNE1:NM_001238:Intron;200T

chr19:30,315,366

94

16.72

CCNE1:Downstream

This table shows the hotspots of HBV integration in the 28samples.The relative genes of these integration positions have been shown in the table.

6W.Li et al./Genomics xxx (2013)xxx –xxx

Author's contributions

Conceived and designed the experiments:WL HJ.Performed the experiments:WL BG GW.Analyzed the data:XZ WL SY XHZ SC.Con-tributed reagents/materials/analysis tools:NPL RTP STF XL MM YL SL JW XX XZ.Wrote the paper:WL XZ HJ.

Acknowledgments

The study belongs to the Chinese 863program (no.2012AA02A201)and is sponsored by Guangdong Innovative Research Team Program (no.2009010016).We thank our colleagues at the BGI-Shenzhen for sequencing.We sincerely thank Laurie Goodman for excellent advice and revision of the manuscript.

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Fig.6.One HBV integration with deletion in human genome of sample 49T.The ?gure shows that a 127bp of HBV insertion was observed in a 728,975bp physical distance be-tween two breakpoints on Chr2of human genome,there was a 728,975bp human genome sequence replaced by a 127bp HBV sequence at chr2:2,053,395,701.

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