Tissue effect on genetic control of transcript isoform variation - PubMed (original) (raw)
Comparative Study
. 2009 Aug;5(8):e1000608.
doi: 10.1371/journal.pgen.1000608. Epub 2009 Aug 14.
Elin Grundberg, Vonda Koka, Bing Ge, Kevin C L Lam, Christel Dias, Andreas Kindmark, Hans Mallmin, Osten Ljunggren, Fernando Rivadeneira, Karol Estrada, Joyce B van Meurs, Andre Uitterlinden, Magnus Karlsson, Claes Ohlsson, Dan Mellström, Olle Nilsson, Tomi Pastinen, Jacek Majewski
Affiliations
- PMID: 19680542
- PMCID: PMC2719916
- DOI: 10.1371/journal.pgen.1000608
Comparative Study
Tissue effect on genetic control of transcript isoform variation
Tony Kwan et al. PLoS Genet. 2009 Aug.
Abstract
Current genome-wide association studies (GWAS) are moving towards the use of large cohorts of primary cell lines to study a disease of interest and to assign biological relevance to the genetic signals identified. Here, we use a panel of human osteoblasts (HObs) to carry out a transcriptomic survey, similar to recent studies in lymphoblastoid cell lines (LCLs). The distinct nature of HObs and LCLs is reflected by the preferential grouping of cell type-specific genes within biologically and functionally relevant pathways unique to each tissue type. We performed cis-association analysis with SNP genotypes to identify genetic variations of transcript isoforms, and our analysis indicates that differential expression of transcript isoforms in HObs is also partly controlled by cis-regulatory genetic variants. These isoforms are regulated by genetic variants in both a tissue-specific and tissue-independent fashion, and these associations have been confirmed by RT-PCR validation. Our study suggests that multiple transcript isoforms are often present in both tissues and that genetic control may affect the relative expression of one isoform to another, rather than having an all-or-none effect. Examination of the top SNPs from a GWAS of bone mineral density show overlap with probeset associations observed in this study. The top hit corresponding to the FAM118A gene was tested for association studies in two additional clinical studies, revealing a novel transcript isoform variant. Our approach to examining transcriptome variation in multiple tissue types is useful for detecting the proportion of genetic variation common to different cell types and for the identification of cell-specific isoform variants that may be functionally relevant, an important follow-up step for GWAS.
Conflict of interest statement
The authors have declared that no competing interests exist.
Figures
Figure 1. Validation of the genetic effect of FAM118A probeset expression.
(A) RefSeq transcript variants, NM_001104595 and NM_017911, for the FAM118A gene and (B) all corresponding probesets included on the Affymetrix Human 1.0 ST Exon array. RMA normalized expression scores for all probesets, as shown by vertical bars (C), indicate expression of additional probesets that differ from the RefSeq variants. Validation studies by RT–PCR and 5′ RACE confirmed expression of probesets marked in red (A) and represent a novel FAM118A transcript variant (D). Fine-mapped SNPs (E) show highly significant associations with expression of probeset 3948567 (marked as green throughout the figure) and P-values represented as –log10(P-value) are shown as vertical bars (F). Dashed line indicates cutoff P = 10e-4.
Figure 2. Validation of microarray association using real-time RT–PCR.
The effect of SNPs on FAM118A probeset expression was validated by quantitative real-time PCR in HObs (n = 31, lower panel) and LCLs (n = 8, upper panel). The rs104664 and rs738177 represent the top significant SNPs associated with probeset expression in the microarray analysis in HObs and LCLs, respectively. Primers were designed to amplify probesets 3948567 (left panel) and 3948555/3948556 (right panel), respectively. Relative expressions were calculated using the comparative CT method using 18S as a housekeeping gene and associations were assessed using a linear regression model. The P-values and R2 of the linear regression statistic are shown within each boxplot.
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