Genetic factors affecting EBV copy number in lymphoblastoid cell lines derived from the 1000 Genome Project samples

Epstein-Barr virus (EBV), human herpes virus 4, has been classically associated with infectious mononucleosis, multiple sclerosis and several types of cancers. Many of these diseases show marked geographical differences in prevalence, which points to underlying genetic and/or environmental factors. Those factors may include a different susceptibility to EBV infection and viral copy number among human populations. Since EBV is commonly used to transform B-cells into lymphoblastoid cell lines (LCLs) we hypothesize that differences in EBV copy number among individual LCLs may reflect differential susceptibility to EBV infection. To test this hypothesis, we retrieved whole-genome sequenced EBV-mapping reads from 1,753 LCL samples derived from 19 populations worldwide that were sequenced within the context of the 1000 Genomes Project. An in silico methodology was developed to estimate the number of EBV copy number in LCLs and validated these estimations by real-time PCR. After experimentally confirming that EBV relative copy number remains stable over cell passages, we performed a genome wide association analysis (GWAS) to try detecting genetic variants of the host that may be associated with EBV copy number. Our GWAS has yielded several genomic regions suggestively associated with the number of EBV genomes per cell in LCLs, unraveling promising candidate genes such as CAND1, a known inhibitor of EBV replication. While this GWAS does not unequivocally establish the degree to which genetic makeup of individuals determine viral levels within their derived LCLs, for which a larger sample size will be needed, it potentially highlighted human genes affecting EBV-related processes, which constitute interesting candidates to follow up in the context of EBV related pathologiesThis work was supported by Instituto de Salud Carlos III (ES) (RD07/0060); Spanish Government Grants (BFU2012-38236); Departament d'Innovació, Universitats I Empresa, Generalitat de Catalunya (2014SGR1311); Instituto de Salud Carlos III (PT13/0001/0026); FEDER (Fondo Europeo de Desarrollo Regional)/FSE (Fondo Social Europeo)

Regional association plots.

<p>Regional association plot for Asian <b>(A)</b>, European <b>(B)</b>, American <b>(C)</b> and African population <b>(D)</b> subsets produced by Locuszoom showing top SNPs from each population subset (in purple) and surrounding SNPs in the region colored by LD (r²) with the top SNP. Lower panel shows genes annotated within this region. Solid blue lines represent recombination rates.</p

Top EBV copy number-associated regions in the different population subsets.

<p>Top EBV copy number-associated regions in the different population subsets.</p

GWAS results Manhattan plot.

<p>Manhattan plots for Asian, African American and European population subsets showing top hits from each continent. The blue line indicates p-value of 10⁻⁵ and red line indicates p-value of 10⁻⁸.</p

1000 Genomes Project LCL samples used in this study.

<p>1000 Genomes Project LCL samples used in this study.</p

Genetic factors affecting EBV copy number in lymphoblastoid cell lines derived from the 1000 Genome Project samples

Epstein-Barr virus (EBV), human herpes virus 4, has been classically associated with infectious mononucleosis, multiple sclerosis and several types of cancers. Many of these diseases show marked geographical differences in prevalence, which points to underlying genetic and/or environmental factors. Those factors may include a different susceptibility to EBV infection and viral copy number among human populations. Since EBV is commonly used to transform B-cells into lymphoblastoid cell lines (LCLs) we hypothesize that differences in EBV copy number among individual LCLs may reflect differential susceptibility to EBV infection. To test this hypothesis, we retrieved whole-genome sequenced EBV-mapping reads from 1,753 LCL samples derived from 19 populations worldwide that were sequenced within the context of the 1000 Genomes Project. An in silico methodology was developed to estimate the number of EBV copy number in LCLs and validated these estimations by real-time PCR. After experimentally confirming that EBV relative copy number remains stable over cell passages, we performed a genome wide association analysis (GWAS) to try detecting genetic variants of the host that may be associated with EBV copy number. Our GWAS has yielded several genomic regions suggestively associated with the number of EBV genomes per cell in LCLs, unraveling promising candidate genes such as CAND1, a known inhibitor of EBV replication. While this GWAS does not unequivocally establish the degree to which genetic makeup of individuals determine viral levels within their derived LCLs, for which a larger sample size will be needed, it potentially highlighted human genes affecting EBV-related processes, which constitute interesting candidates to follow up in the context of EBV related pathologiesThis work was supported by Instituto de Salud Carlos III (ES) (RD07/0060); Spanish Government Grants (BFU2012-38236); Departament d'Innovació, Universitats I Empresa, Generalitat de Catalunya (2014SGR1311); Instituto de Salud Carlos III (PT13/0001/0026); FEDER (Fondo Europeo de Desarrollo Regional)/FSE (Fondo Social Europeo)