Variation in tissue-specific gene expression among natural populations

Abstract

Background: Variation in gene expression is extensive among tissues, individuals, strains, populations and species. The interactions among these sources of variation are relevant for physiological studies such as disease or toxic stress; for example, it is common for pathologies such as cancer, heart failure and metabolic disease to be associated with changes in tissue-specific gene expression or changes in metabolic gene expression. But how conserved these differences are among outbred individuals and among populations has not been well documented. To address this we examined the expression of a selected suite of 192 metabolic genes in brain, heart and liver in three populations of the teleost fish Fundulus heteroclitus using a highly replicated experimental design.

Results: Half of the genes (48%) were differentially expressed among individuals within a population-tissue group and 76% were differentially expressed among tissues. Differences among tissues reflected well established tissue-specific metabolic requirements, suggesting that these measures of gene expression accurately reflect changes in proteins and their phenotypic effects. Remarkably, only a small subset (31%) of tissue-specific differences was consistent in all three populations.

Conclusions: These data indicate that many tissue-specific differences in gene expression are unique to one population and thus are unlikely to contribute to fundamental differences between tissue types. We suggest that those subsets of treatment-specific gene expression patterns that are conserved between taxa are most likely to be functionally related to the physiological state in question.

Figure 1

Variation within individuals (technical variance) and among individuals within populations and tissues (biological variance) for each of 192 genes indicated by the mean square error (MS) of measurements. Points above the dashed line indicate genes with greater variance among individuals than within. F-crit is the critical value of the F-statistic (F = MS_among/MS_within, with 12 and 27 degrees of freedom and α = 0.05) for testing significant differences in gene expression between individuals. For 48% of genes, MS_among/MS_within > F-crit (solid red line). These genes are therefore differentially expressed among individuals within treatments.

Figure 2

Volcano plot of differences between tissues and corresponding p-values. Differences in expression for each gene is the log₂ ratio of tissue mean expression minus grand mean; a twofold difference in expression between tissues is indicated by one unit separation along the x-axis. p-values for differences in gene expression among tissues were calculated using ANOVA, and illustrated as -log(p). A p-value of 10^-4 is expressed as 4 on the y-axis, and the α = 0.05 threshold is indicated by the red dashed line (1 - log(0.05) = 1.3).

Figure 3

Dendrogram of gene expression patterns across samples for genes significantly different between tissues (ANOVA, p < 0.05). Clustering indicates similar expression patterns among samples (top axis) and among genes (left axis). Samples cluster as livers (yellow), hearts (pink) and brains (blue). Genes involved in oxidative phosphorylation are highlighted in green, and expression patterns that are consistent across all three populations are highlighted with a blue triangle.

Figure 4

Number of genes differentially expressed among tissue groups for each population. Tissue-specific genes are those that are expressed more highly in a tissue than in the other tissues (for example, L > H, B) or lower in a tissue than in the other tissues (for example, L < H, B).

Figure 5

Similarity of expression patterns among tissues. (a) Proportion of 192 genes that are similarly expressed between heart and brain (black bar), brain and liver (gray bar) and liver and heart (white bar), for each population including Maine (ME), New Jersey (NJ) and Georgia (GA). (b) Neighbor-joining trees of global similarity of expression patterns among samples (L, liver; H, heart; B, brain) for each population. Distance between samples is the sum of differences of log₂ expression values over all genes.

Figure 6

Shared expression patterns among populations.

Figure 7

Gene expression in liver, brain and heart (three symbols for each line) for the three different populations (three lines per gene). Each letter represents a gene, expression values are log₂ transformed and are indicated for liver, brain and heart (left to right) in each of Maine (circles), New Jersey (triangles) and Georgia (squares) populations. (a) Genes consistently different among tissues in all three populations are grouped as those involved in oxidative phosphorylation (upper panel) and those involved in other metabolic pathways (lower panel). (b) A representative subset of genes not consistently different among tissues in all populations. Gene names associated with letters are provided in Table 1 and Additional data file 1.

Figure 8

Experimental design for hybridizations. Each arrow represents an array hybridization, with the samples at arrow base and head labeled with Cy3 and Cy5, respectively. Liver, heart and brain samples are indicated as purple, red and blue circles, respectively. Three individuals were assayed per tissue and from each of three populations. ME, Maine; NJ, New Jersey; GA, Georgia.

Figure 9

Split-plot ANOVA statistical design. Populations (ME, Maine; NJ, New Jersey; GA, Georgia) are treated as blocks, replicate individuals within each population (1, 2 and 3) as plots, and tissue (L, liver; H, heart; B, brain) within an individual as the split-plot factor. Nested within each tissue-by-individual sample are technical replicates including two dyes (Cy3 and Cy5) within each sample, two replicate hybridizations (A and B) per dye, and six replicate spots per hybridization. GM, grand mean.