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1.
Figure 1

Figure 1. Alignment statistics for transcriptome reads from the six clinical samples.. From: Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations.

Read counts listed in the middle section are expressed in millions (left column) or as a percentage of the total reads processed (right column) for each sample.

Brian B. Tuch, et al. PLoS One. 2010;5(2):e9317.
2.
Figure 5

Figure 5. A switch in the genomic imprinting of H19 and IGF2.. From: Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations.

There are six sites in H19 (shaded orange) and one in IGF2 (shaded blue) on chromosome 11 that are apparently heterozygous in patient 8 (five were validated by as-qPCR). In normal tissue, most detectable expression of H19 is from one allele, as expected for this imprinted, maternally expressed gene. Unexpectedly, in the tumor, nearly all detected expression is from the other, presumably paternal, allele. Observed nucleotides are from dbSNP[35].

Brian B. Tuch, et al. PLoS One. 2010;5(2):e9317.
3.
Figure 2

Figure 2. A common set of genes is differentially expressed in the tumors of three patients with oral carcinoma.. From: Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations.

(A) Transcript expression levels in each of the six samples were hierarchically clustered and, as expected, the normal and tumor tissues form tight clusters. Shades of blue indicate lowered expression, relative to the mean across samples, whereas shades of yellow indicate higher expression relative to the mean. (B) For each patient, gene expression in the tumor was compared to that in matched normal tissue. Pearson correlations indicate strong and significant (P<10−16) similarity of differential transcript expression across the three patients. (C) A scatterplot, comparing differential transcript expression between patients 8 and 33.

Brian B. Tuch, et al. PLoS One. 2010;5(2):e9317.
4.
Figure 3

Figure 3. The genes commonly mis-regulated across the three cases of oral carcinoma function in cell differentiation, adhesion, extracellular matrix digestion and muscle contraction.. From: Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations.

(A–D) Examples of gene expression at four loci. Plotted across each locus is the normalized sequence coverage on both the plus (colored red) and minus (colored orange) strands, for the tumor and normal tissue of a particular patient. (A) MMP1 in patient 51; y-axis scale is 10 to 2000. (B) INHBA in patient 8; y-axis scale is 10 to 150. (C) HMGA2 and RPSAS52 in patient 8; y-axis scale is 10 to 300 for the plus strand and 10 to 100 for the minus strand. (D) CASQ1 in patient 33; y-axis scale is 10 to 100. (E–F) The most up-regulated (E) and down-regulated (F) genes in the tumors of the three patients were submitted for gene ontology (GO) analysis [29] to identify biological processes and components that are typically mis-regulated in oral cancer. Redundant GO categories were filtered. “Count in category” indicates the total number of genes assigned to a given GO category and “count in overlap” indicates the number of up- or down- regulated genes that are also assigned to the given GO category.

Brian B. Tuch, et al. PLoS One. 2010;5(2):e9317.
5.
Figure 6

Figure 6. Large structural mutations are strongly correlated with the changes in gene expression observed in one patient's tumor.. From: Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations.

(A) A strong correlation (ρ = 0.73) is observed between changes in copy number and changes in gene expression for patient 8. The correlation is stronger (ρ = 0.84) if only copy number changes greater than 1.4-fold are considered. (B) The most strongly amplified region (9-fold more copies in the tumor than normal; chr11:68,503,204-69,987,273) contains several differentially expressed (red and orange tracks) genes, highlighted in the text. (C) One region (chr9:21,973,361-22,061,522) that is likely to have been deleted in the tumor contains two genes of interest: cyclin-dependent kinase inhibitor 2B (CDKN2B) and cyclin-dependent kinase inhibitor 2A (CDKN2A). (D) Given that gene dosage changes are strongly associated with gene expression changes, it is expected that heterozygous amplifications and deletions will be associated with the allelic imbalance of transcripts. Shown are the distributions of allelic imbalance for genomic regions that fall into one of three categories of log-transformed copy number change (CNC): low or no CNC (blue; |CNC|<1.2), moderate CNC (red; 1.2<|CNC|<1.8), and large CNC (yellow; |CNC|>1.8). The moderate and large CNC distributions are shifted to significantly higher values of allelic imbalance compared to the no CNC distribution (Mann-Whitney P-values of 10−10 and 10−3, respectively).

Brian B. Tuch, et al. PLoS One. 2010;5(2):e9317.
6.
Figure 4

Figure 4. A common set of genes, functioning in cell adhesion and development, exhibits allelic imbalance in the tumor transcriptomes of three patients with oral carcinoma.. From: Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations.

Allelic imbalance (AI) at the RNA level can arise in a number of ways, including through point mutation and changes in the relative expression of alleles (aka, allele-specific expression). (A) Illustrated is an example of two pre-existing alleles (G and T), one of which undergoes a linked promoter mutation (red asterisk) in the tumor, relative to the normal tissue. If, for example, the mutation alters a cis-regulatory element, then the balance of the two alelles (G and T) may change. (B) In principle, there is enough sequence coverage to discover AI for a large number of exons. For example, more than 25,000 exons have at least 10x coverage (averaged across all sites in the exon). (C) Genes with one or more instances of allelic imbalance in the tumors of two or more patients were submitted for GO analysis [29] to identify biological processes and components that are typically allelically imbalanced in oral cancer. Redundant GO categories were filtered. (D) A selection of genes with allelic imbalance in two or more patients is listed, along with the log2 differential expression of each gene and regions of gene structure impacted. Also noted is whether or not the gene is involved in cell adhesion or is a component of the ECM. Key: 3 = 3′ UTR, I = Intronic, NSS = Near Splice Site, Syn = Synonymous, → = Non-Synonymous.

Brian B. Tuch, et al. PLoS One. 2010;5(2):e9317.

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