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Expression differences by continent of origin point to the immortalization process.

Davis AR, Kohane IS - Hum. Mol. Genet. (2009)

Bottom Line: Analysis of recently available microarray expression data sets obtained from immortalized cell lines of the individuals represented in the HapMap project have led to inconclusive comparisons across cohorts with different ancestral continent of origin (ACOO).We further demonstrate that these differences correlate with viral titer and that both the titer and expression differences are associated with ACOO.We use the 14 genes most differentially expressed to construct an ACOO-specific 'immortalization network' comprised of 40 genes, one of which show significant correlation with genomic variation (eQTL).

View Article: PubMed Central - PubMed

Affiliation: i2b2 National Center for Biomedical Computing, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. ardavis@partners.org

ABSTRACT
Analysis of recently available microarray expression data sets obtained from immortalized cell lines of the individuals represented in the HapMap project have led to inconclusive comparisons across cohorts with different ancestral continent of origin (ACOO). To address this apparent inconsistency, we applied a novel approach to accentuate population-specific gene expression signatures for the CEU [homogeneous US residents with northern and western European ancestry (HapMap samples)] and YRI [homogenous Yoruba people of Ibadan, Nigeria (HapMap samples)] trios. In this report, we describe how four independent data sets point to the differential expression across ACOO of gene networks implicated in transforming the normal lymphoblast into immortalized lymphoblastoid cells. In particular, Werner syndrome helicase and related genes are differentially expressed between the YRI and CEU cohorts. We further demonstrate that these differences correlate with viral titer and that both the titer and expression differences are associated with ACOO. We use the 14 genes most differentially expressed to construct an ACOO-specific 'immortalization network' comprised of 40 genes, one of which show significant correlation with genomic variation (eQTL). The extent to which these measured group differences are due to differences in the immortalization procedures used for each group or reflect ACOO-specific biological differences remains to be determined. That the ACOO group differences in gene expression patterns may depend strongly on the process of transforming cells to establish immortalized lines should be considered in such comparisons.

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Related in: MedlinePlus

Analytic flow of the expression analysis of ACOO. Shaded boxes at the top represent independent data sets of gene expression profiling. The topmost three boxes are three experiments by different investigators on two expression profiling platforms measuring expression in the immortalized lymphoblasts of the YRI and CEU HapMap individuals. The fourth data set is measured on a group of children (CA and AA) who served as controls in an unrelated (autism) study. These cells in this population were not immortalized prior to measurement. Eighty probe sets were measured as significantly differentially expressed across the three immortalized cell data sets. Of those, 66 were also differentially expressed in non-immortalized data set and the subsequent analysis focused on those 14 probe sets that were only differentially expressed in the immortalized cells. Twelve of those 14 probe sets were mapped to genes in IPA, and a network (dubbed the COO Immortalization Network) of 40 genes was automatically constructed. This network was then assessed against the three original expression data sets in two ways. First, one gene was identified as having a significant eQTL based on the associated HapMap SNP data. Second, additional 11 genes from the immortalization network were differentially expressed across all three data sets in addition to the original 12 found (through a much more stringent filter).
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DDP330F1: Analytic flow of the expression analysis of ACOO. Shaded boxes at the top represent independent data sets of gene expression profiling. The topmost three boxes are three experiments by different investigators on two expression profiling platforms measuring expression in the immortalized lymphoblasts of the YRI and CEU HapMap individuals. The fourth data set is measured on a group of children (CA and AA) who served as controls in an unrelated (autism) study. These cells in this population were not immortalized prior to measurement. Eighty probe sets were measured as significantly differentially expressed across the three immortalized cell data sets. Of those, 66 were also differentially expressed in non-immortalized data set and the subsequent analysis focused on those 14 probe sets that were only differentially expressed in the immortalized cells. Twelve of those 14 probe sets were mapped to genes in IPA, and a network (dubbed the COO Immortalization Network) of 40 genes was automatically constructed. This network was then assessed against the three original expression data sets in two ways. First, one gene was identified as having a significant eQTL based on the associated HapMap SNP data. Second, additional 11 genes from the immortalization network were differentially expressed across all three data sets in addition to the original 12 found (through a much more stringent filter).

Mentions: Several recent studies of populations of different ancestral continent of origin (ACOO) have identified ACOO-specific gene expression differences. Because the sets of genes identified in these studies are largely non-overlapping, the biological interpretation of these results is challenging (1–6). Given the importance to health disparities of such studies, we have undertaken an integrative approach to determine whether indeed there is a consistent difference. We have also added a new study sample to further validate our findings. Cross-population expression studies are fraught with the well-known variability in the biology as well as the difficulties in comparing transcriptome-wide measures from different platforms (7,8) and the increasingly documented intrinsic biases of expression patterns of immortalized cell lines (6). Technical bias may affect many genes in concert, thus causing spurious correlations in clinical data sets and false associations between genes and clinical variables (9). The study of the transcriptome in groups with different ACOO is particularly problematic in that most of these studies are performed on Epstein–Barr virus (EBV) immortalized cell lines. Specifically, the International HapMap Project harvested peripheral blood lymphoblasts from the homogenous Yoruba tribe from Ibadan Nigeria (YRI) and then transformed them into immortalized cells in vitro using the EBV. This is of potential additional relevance, as the YRI population is one of the sub-Saharan populations known to suffer from an endemic childhood cancer Burkitt lymphoma (BL), caused by the EBV that environmentally saturates sub-Saharan Africa (10–13). In contrast, the CEU [homogeneous US residents with northern and western European ancestry (HapMap samples)] population as well as other populations with European ancestry has to date no reported predisposition or population-specific susceptibility to EBV infection. This raises the question of the degree to which the reported expression differences are due to laboratory technique, measurement platform difference, laboratory-specific variation in EBV-driven cell immortalization, or COO-specific responses to EBV infection and immortalization. To explore this question, we filtered samples and genes to accentuate population stratification between CEU and YRI trios. Our guiding principle was to select for samples and genes with the highest consistency within ACOO and the least overlap across ACOO. Our approach is outlined in Figure 1. We analyzed four independent recent studies, three of which were conducted on immortalized cell lines previously published (5,14,15), to find the reproducible differences by ACOO across two expression array platforms (Affymetrix and Illumina), and a fourth analysis was performed on an expression experiment of primary lymphoid cells from African Americans (AAs) and Caucasians (CAs) (16). Further description of the experiments, type of array platforms and genes analyzed are listed in Supplementary Material, Table S1. To reduce noise from the varied measurement platforms and laboratory-specific technique, this analysis was intentionally driven to high specificity at the cost of sensitivity (9) by the filtering process, as described. Our analysis identified an ‘immortalization network’ consisting of 40 genes, of which 24 genes are differentially expressed between the CEU and YRI populations. Furthermore, one of these genes, Werner syndrome helicase (WRN), is significantly correlated with EBV titer. Subsequently, we relaxed the original aggressive filtering of the data and found the large majority of the immortalization network's genes were differentially expressed across ACOO. Moreover, we identified a cis eQTL in gene POLR1A in the network with respect to ACOO.


Expression differences by continent of origin point to the immortalization process.

Davis AR, Kohane IS - Hum. Mol. Genet. (2009)

Analytic flow of the expression analysis of ACOO. Shaded boxes at the top represent independent data sets of gene expression profiling. The topmost three boxes are three experiments by different investigators on two expression profiling platforms measuring expression in the immortalized lymphoblasts of the YRI and CEU HapMap individuals. The fourth data set is measured on a group of children (CA and AA) who served as controls in an unrelated (autism) study. These cells in this population were not immortalized prior to measurement. Eighty probe sets were measured as significantly differentially expressed across the three immortalized cell data sets. Of those, 66 were also differentially expressed in non-immortalized data set and the subsequent analysis focused on those 14 probe sets that were only differentially expressed in the immortalized cells. Twelve of those 14 probe sets were mapped to genes in IPA, and a network (dubbed the COO Immortalization Network) of 40 genes was automatically constructed. This network was then assessed against the three original expression data sets in two ways. First, one gene was identified as having a significant eQTL based on the associated HapMap SNP data. Second, additional 11 genes from the immortalization network were differentially expressed across all three data sets in addition to the original 12 found (through a much more stringent filter).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2748894&req=5

DDP330F1: Analytic flow of the expression analysis of ACOO. Shaded boxes at the top represent independent data sets of gene expression profiling. The topmost three boxes are three experiments by different investigators on two expression profiling platforms measuring expression in the immortalized lymphoblasts of the YRI and CEU HapMap individuals. The fourth data set is measured on a group of children (CA and AA) who served as controls in an unrelated (autism) study. These cells in this population were not immortalized prior to measurement. Eighty probe sets were measured as significantly differentially expressed across the three immortalized cell data sets. Of those, 66 were also differentially expressed in non-immortalized data set and the subsequent analysis focused on those 14 probe sets that were only differentially expressed in the immortalized cells. Twelve of those 14 probe sets were mapped to genes in IPA, and a network (dubbed the COO Immortalization Network) of 40 genes was automatically constructed. This network was then assessed against the three original expression data sets in two ways. First, one gene was identified as having a significant eQTL based on the associated HapMap SNP data. Second, additional 11 genes from the immortalization network were differentially expressed across all three data sets in addition to the original 12 found (through a much more stringent filter).
Mentions: Several recent studies of populations of different ancestral continent of origin (ACOO) have identified ACOO-specific gene expression differences. Because the sets of genes identified in these studies are largely non-overlapping, the biological interpretation of these results is challenging (1–6). Given the importance to health disparities of such studies, we have undertaken an integrative approach to determine whether indeed there is a consistent difference. We have also added a new study sample to further validate our findings. Cross-population expression studies are fraught with the well-known variability in the biology as well as the difficulties in comparing transcriptome-wide measures from different platforms (7,8) and the increasingly documented intrinsic biases of expression patterns of immortalized cell lines (6). Technical bias may affect many genes in concert, thus causing spurious correlations in clinical data sets and false associations between genes and clinical variables (9). The study of the transcriptome in groups with different ACOO is particularly problematic in that most of these studies are performed on Epstein–Barr virus (EBV) immortalized cell lines. Specifically, the International HapMap Project harvested peripheral blood lymphoblasts from the homogenous Yoruba tribe from Ibadan Nigeria (YRI) and then transformed them into immortalized cells in vitro using the EBV. This is of potential additional relevance, as the YRI population is one of the sub-Saharan populations known to suffer from an endemic childhood cancer Burkitt lymphoma (BL), caused by the EBV that environmentally saturates sub-Saharan Africa (10–13). In contrast, the CEU [homogeneous US residents with northern and western European ancestry (HapMap samples)] population as well as other populations with European ancestry has to date no reported predisposition or population-specific susceptibility to EBV infection. This raises the question of the degree to which the reported expression differences are due to laboratory technique, measurement platform difference, laboratory-specific variation in EBV-driven cell immortalization, or COO-specific responses to EBV infection and immortalization. To explore this question, we filtered samples and genes to accentuate population stratification between CEU and YRI trios. Our guiding principle was to select for samples and genes with the highest consistency within ACOO and the least overlap across ACOO. Our approach is outlined in Figure 1. We analyzed four independent recent studies, three of which were conducted on immortalized cell lines previously published (5,14,15), to find the reproducible differences by ACOO across two expression array platforms (Affymetrix and Illumina), and a fourth analysis was performed on an expression experiment of primary lymphoid cells from African Americans (AAs) and Caucasians (CAs) (16). Further description of the experiments, type of array platforms and genes analyzed are listed in Supplementary Material, Table S1. To reduce noise from the varied measurement platforms and laboratory-specific technique, this analysis was intentionally driven to high specificity at the cost of sensitivity (9) by the filtering process, as described. Our analysis identified an ‘immortalization network’ consisting of 40 genes, of which 24 genes are differentially expressed between the CEU and YRI populations. Furthermore, one of these genes, Werner syndrome helicase (WRN), is significantly correlated with EBV titer. Subsequently, we relaxed the original aggressive filtering of the data and found the large majority of the immortalization network's genes were differentially expressed across ACOO. Moreover, we identified a cis eQTL in gene POLR1A in the network with respect to ACOO.

Bottom Line: Analysis of recently available microarray expression data sets obtained from immortalized cell lines of the individuals represented in the HapMap project have led to inconclusive comparisons across cohorts with different ancestral continent of origin (ACOO).We further demonstrate that these differences correlate with viral titer and that both the titer and expression differences are associated with ACOO.We use the 14 genes most differentially expressed to construct an ACOO-specific 'immortalization network' comprised of 40 genes, one of which show significant correlation with genomic variation (eQTL).

View Article: PubMed Central - PubMed

Affiliation: i2b2 National Center for Biomedical Computing, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. ardavis@partners.org

ABSTRACT
Analysis of recently available microarray expression data sets obtained from immortalized cell lines of the individuals represented in the HapMap project have led to inconclusive comparisons across cohorts with different ancestral continent of origin (ACOO). To address this apparent inconsistency, we applied a novel approach to accentuate population-specific gene expression signatures for the CEU [homogeneous US residents with northern and western European ancestry (HapMap samples)] and YRI [homogenous Yoruba people of Ibadan, Nigeria (HapMap samples)] trios. In this report, we describe how four independent data sets point to the differential expression across ACOO of gene networks implicated in transforming the normal lymphoblast into immortalized lymphoblastoid cells. In particular, Werner syndrome helicase and related genes are differentially expressed between the YRI and CEU cohorts. We further demonstrate that these differences correlate with viral titer and that both the titer and expression differences are associated with ACOO. We use the 14 genes most differentially expressed to construct an ACOO-specific 'immortalization network' comprised of 40 genes, one of which show significant correlation with genomic variation (eQTL). The extent to which these measured group differences are due to differences in the immortalization procedures used for each group or reflect ACOO-specific biological differences remains to be determined. That the ACOO group differences in gene expression patterns may depend strongly on the process of transforming cells to establish immortalized lines should be considered in such comparisons.

Show MeSH
Related in: MedlinePlus