BACKGROUND
variation in transcript abundance between individuals has important implications for microarray experimental design and significance testing  <cit> .
ideally, microarray experiments are designed with samples from multiple individuals in each treatment group.
this biological replication provides the variance estimator that is required to establish the statistical significance of between-group differences.
in this study, we collected multiple samples of tissues within each of several genetically identical mice.
multiple sampling within individuals is not necessary in an experiment aimed at making between-group comparisons, but it is essential if the aim is to identify significant variation between individuals within the same experimental treatment group.
an important procedural detail in this type of study is to determine how to collect and at what stage to divide the tissues to create multiple samples.
in this study, we elected to split tissues immediately after dissection and before rna extraction in order to restrict the possible sources of between-mouse variation to events that occur prior to dissection.
with this experimental design, transcript variation can be decomposed into within-mouse and between-mouse variance components.
between-mouse variance reflects differences in whole-tissue transcript abundance between genetically identical mice.
within-mouse variance captures variation due to rna extraction, array processing, and heterogeneity of gene expression within tissues, which may be amplified by dissection and tissue collection procedures.
individual variation in gene expression can have important phenotypic consequences.
however, only a few studies have previously attempted to characterize gene expression variation in genetically identical mice.
koza et al.
<cit>  described gene expression signatures in adipose tissue that are predictive of future adiposity among genetically identical c57bl/6j mice.
the use of multiple biopsy samples in this time-course study was essential to establish the link between gene expression variation and late-life adiposity.
however, biopsy sampling may be subject to unexpected variation introduced by tissue heterogeneity, as we illustrate below.
two previous studies have used multiple sampling within individuals to provide a statistical basis for detecting transcript variation between genetically identical mice.
pritchard et al.
<cit>  examined  <dig> tissues in each of  <dig> c57bl/6j mice and reported that immune function, stress response, and hormone regulation were important sources of biological variation.
pritchard et al.
<cit>  examined liver tissue in  <dig> animals from each of  <dig> inbred mouse strains and found that genes differentially expressed within strains were enriched for cell growth, cytokine activity, amine metabolism, and ubiquitination.
in these experiments, technical replicates were obtained by splitting samples after rna extraction.
this approach confounds variation due to dissection and rna preparation with variation between mice.
we designed and carried out an experiment to study transcript abundance variation in four tissues among young adult male c57bl/6j mice .
our sampling design enabled us to partition the variance for each gene into within-mouse and between-mouse components, with a division line that corresponds to the step of splitting tissues.
we examined within-mouse and between-mouse variation in more than  <dig>  protein coding genes and identified groups of genes with shared patterns of variation that are enriched for known biological functions.
to facilitate exploration of our data, we have created an on-line resource that includes graphical displays, test statistics, and gene groupings for all transcripts characterized in this study http://cgd.jax.org/individualvariation.shtml.
RESULTS
we performed a microarray experiment using the illumina sentrix® mouse- <dig> v <dig>  beadchip microarray platform to study transcript variation in 10-week old male c57bl/6j mice .
six pairs of siblings were co-housed from weaning under uniform environmental conditions.
from each mouse we obtained duplicate samples of adipose , heart, kidney, and liver tissues by splitting whole organs or tissues prior to homogenization and rna extraction.
adipose, heart, and liver tissues were coarsely cut into pieces and divided into two samples that were homogenized separately in order to extract rna.
the left and right kidneys were also homogenized separately.
we computed a decomposition of variance for each probe on the array .
the within-mouse variance component captures biological variance between two dissected tissue samples as well as technical variance due to sample and microarray processing.
the between-mouse variance component reflects differences between individual mice.
we repeated gene expression assays on the liver samples, using the affymetrix whole-transcript mouse gene  <dig>  st array, to provide validation on a different measurement platform.
expressed genes and variable genes
we declared a gene to be expressed if the probe intensity was greater than the 95th percentile of the negative control probes for both samples in at least  <dig> of the  <dig> mice.
a total of  <dig> genes, representing 55% of the annotated probes on the array, were expressed in at least one of the four tissues.
across tissues, the number of expressed genes ranged from  <dig>  in liver to  <dig>  in adipose tissue .
shown in this table are: the number of expressed genes out of the  <dig> annotated genes on the array .
the number of variable genes based on the  <dig> ,  <dig>  and  <dig>  tails of the scaled χ <dig> distribution .
the number of genes with significant between-mouse variance, based on the fs test with family-wise adjusted error ; false discovery rate ; and the estimated proportion of differentially expressed genes  .
the number of genes with large maximal fold-change between mice .
all numbers are given as percentages of the annotated genes in parentheses.
we computed the total variance, s <dig>  across all samples for each gene in each tissue .
liver and kidney have relatively few genes of high variability but heart and adipose have many.
we tested the hypothesis that the distribution of total variance occurred by chance using a χ <dig> test  and found significantly greater variance than expected in each tissue .
we applied coexpression network analysis to the top  <dig> genes in each tissue, which we refer to as the variable genes.
we decomposed total variance for each gene into within-mouse  and between-mouse  components.
the distribution of between-mouse variance components was similar across all four tissues .
adipose tissue showed the greatest number of genes with a large within-mouse component followed by heart, kidney, and liver .
the variable genes include the  <dig> ,  <dig> ,  <dig> , and  <dig>  genes with the largest between-mouse variance.
they also include the  <dig> ,  <dig> ,  <dig> , and  <dig>  genes with the largest within-mouse variance.
significance of between-mouse variance
within each tissue, for each gene, we computed a test statistic to assess the significance of the between-mouse variance component relative to the within-mouse variance component.
we applied a family-wise error rate correction  <cit>    <cit> ) and found few genes with significant between-mouse variation .
we applied a false discovery rate  adjustment  <cit>    <cit> ) and found no differentially expressed genes in adipose or heart and only modest numbers in kidney  and liver  .
we estimated the proportions of differentially expressed genes  using the q-value software  <cit>  and found similar results .
a different picture of the variability in gene expression across tissues emerges when we look at the maximal fold change between mice .
in adipose,  <dig> % of all genes exhibit maximal fold changes greater than  <dig>  whereas  <dig> - <dig> % of all genes show fold changes this large in the other three tissues.
although the fold-change is not a statistical criterion, the differences across tissues are dramatic.
there are many genes with large maximal fold changes between mice but, particularly in adipose tissue, these same genes also have large within-mouse variance, which reduces their statistical significance.
variable genes form clusters that are enriched for specific biological functions
we used co-expression network analysis  <cit>  to cluster the variable genes into modules with correlated patterns of expression  .
module sizes ranged from  <dig> to  <dig> genes with an average module size of  <dig> genes .
we identified  <dig> to  <dig> modules in each tissue comprising 97% , 80% , 61% , and 54%  of the variable genes.
for each module, we applied principal components analysis to compute a module eigengene  <cit>  that represents the dominant pattern of variation .
the percentage of variation explained by the module eigengene ranges from 47% to 88%, indicating that the eigengenes are representative of expression profiles of the individual genes in each module.
in the following, we refer to modules using a colour code within each tissue .
best enrichment scores of co-expression modules are shown.
within each tissue, modules are listed by the colour code orders of figure  <dig>  the number of genes in the module, the number of variable genes in the highest scoring functional category, the overlap between these two sets of genes, the enrichment p-value for the highest scoring category  <cit> , and the median intraclass correlation, c, for genes in the module are shown.
only categories with between  <dig> and  <dig> genes and a minimum overlap of  <dig> genes were considered.
for each gene, we computed the intraclass correlation coefficient, c ≡ sb2/, which is the proportion of total variance attributable to the between-mouse component.
median values by module ranged from c =  <dig>   to c =  <dig>   .
kidney and liver, respectively, have  <dig> and  <dig> modules with high intraclass correlation  indicating substantial between-mouse variance while adipose has two and heart has no modules with high intraclass correlation .
each tissue also has at least one module with low intraclass correlation  indicating that differences between samples within mice are greater than differences between mice.
for each module, we computed enrichment scores  <cit>  for the go biological process, cellular component, and molecular function terms and for kegg pathways.
the highest scoring enrichment category for each module is listed in table  <dig>  each module can be divided into two subsets such that all correlations within a subset are positive .
we also tested for enrichment within each of these subsets .
many of the module enrichment scores are highly significant indicating that correlated groups of variable genes are enriched for specific biological functions.
most modules in a given tissue share similar features with at least one module in another tissue .
several sets of modules shared similar patterns of between-mouse variation and had significant gene overlap and functional enrichment.
other sets of modules shared similar patterns of within-mouse variation, but with distinct between-mouse variation.
several pairs of modules had significant gene overlap but did not have correlated patterns of variation.
examples of each are described below.
between-mouse patterns of variation are shared across tissues
modules from different tissues that are enriched for similar functional categories typically have high intraclass correlation and similar patterns of between-mouse variation.
to quantify this similarity, we computed a between-mouse correlation, rb, for all pairs of module eigengenes by averaging the two within-mouse samples before computing the pearson correlation.
each of the four tissues has at least one module that is enriched for immune response.
the heart-brown , kidney-gold , and liver-pink  modules are enriched for the go category exogenous antigen presentation .
the between-mouse correlations, rb, range from  <dig>  to  <dig> , and the genes in these modules overlap significantly based on a hypergeometric test .
pairwise overlaps range from  <dig> to  <dig> genes and seven genes  are found in all  <dig> modules.
the kidney-blue  and liver-brown  modules are enriched for go category extracellular matrix, each containing more than  <dig> genes of that category.
their between-mouse profiles are correlated  and they share  <dig> genes in common  including adamts <dig>  col5a <dig>  col6a <dig>  col14a <dig>  ecm <dig>  igfbp <dig>  tgfbi and timp <dig>
the adipose-red , heart-blue , kidney-brown  and liver-black  modules are enriched for the go category apoptosis and have between-mouse correlations, rb, ranging from  <dig>  to  <dig> .
these modules overlap with  <dig> genes present in at least  <dig> of the  <dig> modules including ccrn4l, gadd45g, and map3k <dig>  the liver-blue module  also has a high between-mouse correlation  and significant gene overlap with these adipose, heart and kidney modules including fkbp <dig> and per <dig>
the kidney-pink  and liver-magenta  modules have correlated between-mouse profiles , and each contains  <dig> or more genes of the go category dna-dependent regulation of transcription.
their gene overlap  includes bcl <dig>  cish, rgs <dig>  and socs <dig>
the between-mouse profiles of the kidney-green  and liver-red  modules are correlated  and each module contains  <dig> or more genes of the go category cellular lipid metabolic process.
they have  <dig> genes in common  including acaa <dig>  acadm, agxt2l <dig>  cyp26b <dig>  cyp4a <dig>  cyp4a <dig> and slc2a <dig>
within-mouse patterns are similar across modules of the same tissue
some modules had similar patterns of within-mouse variation but different patterns of between-mouse variation.
to measure similarity of within-mouse variation, we centred the sample values on individual mouse means and then computed a pearson correlation, rw.
this measure is only meaningful for comparisons within the same tissue as there is no correspondence between the duplicate samples from different tissues.
adipose and heart each have multiple highly correlated modules .
the adipose-green, adipose-red, adipose-black, and adipose-magenta modules have distinct patterns of between-mouse variation and different functional enrichment, but they all share high within-mouse correlation .
a similar relationship was observed for the heart-green, heart-red, heart-turquoise, heart-blue, heart-brown, and heart-gold modules .
uncorrelated modules have gene overlap and similar functional enrichment
some modules share genes and functional enrichment categories but do not have correlated patterns of variation.
the adipose-gold , heart-red , and kidney-black  modules have a high gene overlap .
they are enriched for the go category fatty acid metabolic process.
the adipose-magenta  and heart-gold modules  share  <dig> out of  <dig> genes including cd8b <dig> and lck and are enriched for the go category immune system process.
the adipose-brown module  shares  <dig> out of  <dig> genes with the heart-green module  and  <dig> out of  <dig> genes with the liver-turquoise module .
these modules are enriched for the go actin cytoskeleton category and share  <dig> genes in common including ckm and myl <dig>  the adipose-turquoise  and kidney-turquoise  modules share  <dig> out of  <dig> genes including apoal, cyp8b <dig>  and ugt2b <dig> and are enriched for the kegg pathway complementation and coagulation cascades.
the adipose-green  and heart-turquoise  modules are overlapping in  <dig> out of  <dig> genes including ccl <dig>  cxcl <dig>  egr <dig>  fos, and hmox <dig> and are enriched for chemokine activity.
the adipose-black , heart-black , kidney-magenta , and liver-green  modules have pairwise overlaps ranging from  <dig> to  <dig> genes.
twenty-two genes are shared among all  <dig> of these modules and they are enriched for kegg pathway oxidative phosphorylation and the go category mitochondrial inner membrane.
comparison across platform
we repeated the gene expression assays for only the liver samples on a different platform, the affymetrix whole-transcript mouse gene  <dig>  st array.
to facilitate comparison, we generated a cross-platform probe map based on gene annotation .
using this map, we computed eigengenes of the previously defined clusters from the affymetrix data.
correlation of the eigengenes across platforms was very high for  <dig> of the  <dig> modules .
two modules with lower correlation  had less than 20% of variance explained by the eigengene with affymetrix data.
however, for the liver-gold module, low expression for mouse  <dig> was a consistent pattern across platforms.
the profiles of all  <dig> genes that are highlighted in the discussion  are highly correlated across platform .
discussion
there are several mechanisms that may contribute to between-mouse variation in gene expression in c57bl/6j mice.
new mutations that create single nucleotide or copy number variants may result in variable gene expression.
we expect such events to be rare.
however, we have observed a striking pattern of differential expression  in the insulin degrading enzyme  with approximately two-fold higher expression in all  <dig> tissues for the two mice of cage  <dig>  we speculate that these siblings may have inherited a copy number variant at this locus on chromosome  <dig> for which copy number changes have been observed previously in c57bl/6j mice  <cit> .
genes that display circadian or other periodic expression patterns can be out of phase in different animals.
we attempted to control for cyclical variation by collecting samples in a consistent and narrow time frame for all mice.
variation in feeding behaviour is another possible factor and although we implemented a 4-hour fast prior to tissue collection, some variation in time since last feeding is inevitable.
epigenetic differences may affect the expression of genes as a result of variable access to nutrients in utero, birth order, maternal stress or other pre- or post-partum events.
slight differences in phenotype at birth may be magnified over time.
response to subtle differences in local environment may have an effect on gene expression and finally, the expression of some genes may be sensitive to events just prior to euthanasia  <cit> .
within-mouse transcript variation could reflect stochastic variation in gene expression, which has been observed within individual cells and across cell populations  <cit> .
however, if it is present, this effect seems to be dominated by other factors in our study.
tissue heterogeneity due, for example, to localization of stem and progenitor cell populations can result in sampling variation  <cit> .
this variation may be amplified by dissection, especially in tissues with imprecise boundaries.
even a relatively homogenous and easily isolated tissue such as liver will have internal structure that can influence local gene expression  <cit> .
phenotypic implications of between- and within-mouse variation in adipose tissue
adipose tissue is compartmentalized into adipocytes, preadipocytes, and vascular epithelium  <cit> .
the degree of vascularisation can vary significantly across different regions of the same fat pad and is expected to be greater in the portion of the inguinal fat pad that is near the inguinal lymph node  <cit> .
vascularised adipose tissue tends to be more metabolically active  <cit> .
we found a large number of genes that have within-mouse variation related to vascularisation in the adipose-magenta module .
the positively correlated subset of this module is enriched for go biological processes immune response, t cell activation, and lymphocyte activation  and include genes expressed in lymphocytes such as lck, cd8b <dig>  and elf <dig> .
some genes within the adipose-magenta module, which is dominated by within-mouse variation, also have large between-mouse fold changes.
these genes, including bmp <dig>  sfrp <dig>  mest, lep and trp53inp <dig>  are positively correlated with body weight and were previously found to be predictive for adiposity  <cit>  .
they are also negatively correlated with the module eigengene, which is consistent with higher expression in the less vascularised region of the inguinal fat pad, suggesting an inverse relationship between vascularisation and adiposity.
we chose to study the inguinal fat pad because it can be efficiently dissected.
gene expression can vary among fat depots  <cit>  and proximity to the inguinal lymph node clearly contributed to heterogeneity in the inguinal fat pad.
this limits our ability to generalize our findings.
however, our previous experience  <cit>  indicates that other fat depots are at least as variable as the inguinal depot.
the koza et al.
study  <cit>  identified their adiposity signature, which we have replicated, in epididymal and retroperitoneal fat.
variable brown fat signature in white fat tissue
several genes in the adipose-gold module are expressed exclusively in brown fat, including ucp <dig>  cidea, and cox8b .
this module is enriched for fatty acid metabolism and the module eigengene is correlated with prdm <dig> , which is part of a transcriptional complex that promotes brown fat differentiation and suppresses skeletal muscle cell differentiation  <cit> .
the adipose-brown module is enriched with  <dig> genes of the go biological process muscle contraction.
genes in this module are expressed in both skeletal muscle and brown fat and many are related to brown fat cell differentiation  <cit> .
we ruled out cross contamination with muscle tissue by inspection of the dissection procedure.
the enrichment for muscle contraction appears to be spurious and reflects a potential pitfall of enrichment analysis using go annotation.
most of the variation in the adipose-gold  and adipose-brown  modules is attributable to the within-mouse component, which suggests a heterogeneous spatial distribution of brown fat within the inguinal fat pad.
however, large between-mouse fold changes, including ckm, with 56-fold change, the largest observed in this study , suggest that the proportion of brown fat may also vary across mice.
brown fat tissue proportion have previously been shown to vary with age, strain, and environmental conditions  <cit> .
region-specific variation of gene expression in heart
the heart is composed primarily of cardiac smooth muscle, but it is differentiated into atrial, ventricular and trabecular regions with a left-right asymmetry.
several genes expressed in atria and trabeculae of the heart are repressed in the ventricles, in part, through activity of the transcription factor, gata <dig>  <cit> .
the heart-green module  is enriched for these genes and shows a pattern of within-mouse variation with little between-mouse variation .
gata <dig> is in the heart-red module , which has a strong within-mouse correlation to the heart-green module  .
gata <dig> is negatively correlated with the heart-red eigengene such that the within-mouse variation in gata <dig> is inversely related to the expression of ventricle-repressed transcripts .
we compared our results with a study of chamber-specific gene expression   <cit> ) and found that, of the  <dig> genes previously reported to be more highly expressed in the atria than in the ventricles,  <dig> are included in the heart-green module.
the relatively small magnitude of between-mouse variation in these modules reflects the effect of averaging of the two samples, which together comprise the whole heart.
we conclude that much of the within-mouse variation observed for heart tissue is a consequence of variable proportions of anatomical substructures, specifically ventricular tissue, within the samples.
androgen-regulated genes are variable between mice in the kidney
many genes are regulated in response to androgens.
in mice, srd5a <dig> plays a key role in androgen signal amplification  <cit>  suggesting that androgenic effects in individuals with higher srd5a <dig> expression could be more pronounced.
hsd11b <dig> facilitates the conversion of testosterone to adrenosterone  <cit>  and has been shown to be androgen-responsive in mice  <cit> .
these genes were found to be variable between mice and cluster together in the kidney-green module , which is enriched for the kegg androgen and estrogen metabolism pathway.
other androgen-responsive genes in the kidney-green module include cyp4a <dig>  slco1a <dig>  nudt <dig>  prlr, angptl <dig>  hsd17b <dig>  and tmco <dig> .
it is not immediately clear if this variation reflects transient or steady state variation in androgen levels between mice.
the expression of a mouse urinary protein, gusb, is responsive to androgens in the long-term but not in the short-term  <cit> .
gusb has significant between-mouse variation that is correlated with the kidney-green module eigengene  .
this suggests that other genes in this module also reflect steady state androgen levels, which may have important physiological and behavioural implications.
between-mouse variation in fatty acid metabolism in the liver
genes in the liver-red module have either low or high expression in the two mice of cage  <dig> .
genes in the low expression subset are involved in oxidation of fatty acids .
genes in the high expression subset, specifically tnfrsf1a and ptgis, are involved in the conversion of the essential fatty acid arachidonic acid to prostaglandins.
thus, we see decreased fatty acid degradation in mice that are actively utilizing fatty acids.
the liver-red module also shares genes with the androgen-associated kidney-green module which may reflect the requirement for lipids as precursors in androgen synthesis.
between-mouse variation in circadian rhythm
the adipose-red, heart-blue, kidney-brown, liver-blue, and liver-black modules are correlated and share multiple genes related to apoptotic activity, which varies following circadian rhythm in mice  <cit> .
several other genes that are known to vary in a circadian fashion are also found in these modules , including ccrn4l, fkbp <dig>  gadd45g, map3k <dig>  per <dig>  pim <dig>  mt <dig>  sgk <dig>  errfi <dig>  cdkn1a, dusp <dig>  and angptl <dig>  the core circadian gene per <dig>  <cit>  is found in the adipose-red module.
genes that follow a circadian expression pattern are expected to vary with the time of day and with fasting/feeding cycles.
despite our efforts to control both of these factors, between-mouse variation can be expected to arise if the mice are in slightly different phases of their diurnal cycles.
angptl <dig>  cdkn1a, dusp <dig>  and fkbp <dig> vary in circadian fashion  <cit>  and are all located in a  <dig> mb region on proximal chromosome  <dig>  this region is the strongest example of coexpression clustering that we found in this study.
however, statistical assessment suggests that a cluster of this size could be explained by chance.
between-mouse variation associated with growth hormone
the genes socs <dig>  bcl <dig>  cish, and gadd45g have correlated patterns of variation in kidney and liver and are among the genes with the most significant between-mouse variation .
growth hormone has been shown to elicit a strong transcriptional response in socs <dig> , cish , bcl <dig> , and gadd45g , as well as in the growth hormone responders igf <dig> and il <dig>  <cit> .
three of these genes  belong to the kidney-pink and liver-magenta modules, which have  <dig> overlapping genes and are enriched for genes involved in transcription regulation.
growth hormone signalling affects transcription of genes such as xbp <dig> , which is critical for the regulation of hepatic lipogenesis  <cit> .
the effect of growth hormone signalling appears to extend beyond these modules, however.
among  <dig> genes previously identified as growth hormone responders  <cit> ,  <dig> were classified as variable in our study, indicative of widespread individual variation in growth hormone signalling.
similarities and differences in transcript abundance for sibling cage mates
sibling cage mates may be expected to exhibit greater similarity than randomly selected mice of the same strain due to shared developmental or micro-environmental factors.
when we further partitioned the between mouse variance into between-cage and within-cage components , we found more genes with significant between-cage variation  than within-cage variation .
the liver-red module provides a striking example of within-cage similarity .
enrichment for genes associated with fatty acid oxidation in this module could reflect an extended period of fasting just prior to euthanasia.
for example, expression of murine hepatic cyp4a <dig>  is known to increase in expression under fasting conditions  <cit> .
this gene has been reported to be variable between strains in liver  <cit> , but it is not clear whether this is a genuine strain-specific effect or an artefact due to co-housing of mice of the same strain.
other factors could contribute to greater differences between mice within a cage.
cohabitating outbred male mice form a social structure that includes dominance status even when mice are housed as siblings from birth.
dominance behaviour has been observed within male mice of some inbred strains  but not c57bl/6j.
however, cohabitation has known phenotypic effects on c57bl/6j males including change in body weight, adrenal weight, and aggressiveness  <cit> .
the factors that determine the social status of siblings raised together are unclear, but once established, social behaviour can reinforce these minor differences leading to distinct individual phenotypes in adult mice.
in our experiment, we observed within-cage body weight difference of as much as 3g .
some of the transcriptional changes that we have observed are likely to be related to these body weight differences.
for example, in cage  <dig> we observed a large body weight difference coincident with a large difference in transcription of signature genes for adiposity , but small differences in signature genes for androgen levels .
in contrast, in cages  <dig> and  <dig>  body weight differences coincide with a transcriptional signature for androgen response but not for adiposity.
this suggests that bodyweight differences may reflect two distinct processes, one that affects adiposity and another that affects androgen levels and lean mass  <cit> .
moreover, these findings provide evidence for an effect of social context on biological processes that have important consequences for human health.
comparison to a previous study of transcript variation
we directly compared our results to a previous study of transcriptional variation in c57bl/6j mice  <cit>  by computing variance components and applying the same significance tests to both data sets .
we found little correlation in total variation  which we attribute to the predominance of technical variation, especially in the older study.
however, we did find good agreement across these studies when we examined specific genes highlighted in the previous study.
cfd was reported to vary significantly between mice in the kidney for the previous experiment in which effects due to dissection and rna extraction are included in the between-mouse variance component.
we also found it to be a variable gene, but, in contrast, we identified cfd as a gene with primarily within-mouse variation  in the kidney-black module .
both studies identified significant between-mouse variation in several highly variable genes, including gadd45g, dusp <dig>  cish, and bcl <dig> .
our study, with a larger sample size, a more recent array technology, and a different experimental design should provide a more precise and detailed picture of variation in gene expression.
CONCLUSIONS
transcript abundance varies significantly among genetically identical male c57bl/6j mice housed under uniform conditions.
patterns of variation can be tissue specific or shared across multiple tissues and transcripts can vary between tissue samples collected from the same animal.
groups of genes with correlated patterns of between-animal or within-animal variation are often enriched for specific functional annotations.
we utilized correlation-based clustering to organize a large number of distinct patterns of variation.
literature search tools and functional annotation aided in the interpretation of our findings.
however, annotation of gene function is incomplete and this presented some challenges as exemplified by the finding of a skeletal muscle signature in white adipose tissue, which was due to the presence of a related cell type, brown fat.
this study highlights a number of potential biological and technical sources of variation that practitioners should be aware of for both experimental design and interpretation.
much of the between-animal variation reported here reflects functions that are sensitive to environmental cues, such as androgen response, circadian rhythm, and immune response.
external environmental cues tend to elicit similar responses in multiple tissues.
variation of gene expression within tissues reflects their heterogeneous cellular composition, and is also a major factor contributing to variation in gene expression.
this underscores the potential for dissection or biopsy procedures to introduce unwanted variation into studies of gene expression.
adipose tissue is especially problematic in this regard as it is a highly dynamic and heterogeneous tissue with few anatomical features to guide consistent dissection.
our tissue collection procedure involved a coarse separation of tissue fragments which, in retrospect, was useful to reveal within-tissue heterogeneity.
an exception to this was our use of the intact left and right kidneys as replicates.
this may explain the relatively low within-mouse variation observed for this heterogeneous and highly structured tissue.
in future studies, we recommend the use of procedures that more effectively homogenize tissue, such as pulverization and mixing of snap frozen samples.
our finding also raises questions about the potential for introducing systematic variation in the dissection of anatomical substructures.
this may be a particular concern for studies of gene expression in the brain, for which we have no data at this time.
the presence of biologically meaningful covariation in a setting with no experimental perturbation underscores the need for replication and careful adherence to statistical design principles in gene expression studies.
seemingly innocuous experimental factors such as co-housing of mice can result in systemic differences that may lead to strong statistical support for incorrect conclusions.
prior knowledge of the categories of genes that are intrinsically variable can help to identify such effects.
our study further demonstrates that the variation used to construct statistical tests  in microarray experiments can have substantial correlation across large sets of genes.
this can have a profound impact on testing procedures, especially those that rely on multiple test adjustment of p-values across many genes  <cit> .

 variation in transcript abundance between individuals has important implications for microarray experimental design and significance testing. ideally, microarray experiments are designed with samples from multiple individuals in each treatment group. this biological replication provides the variance estimator that is required to establish the statistical significance of between-group differences. in this study, we collected multiple samples of tissues within each of several genetically identical mice. multiple sampling within individuals is not necessary in an experiment aimed at making between-group comparisons, but it is essential if the aim is to identify significant variation between individuals within the same experimental treatment group. an important procedural detail in this type of study is to determine how to collect and at what stage to divide the tissues to create multiple samples. in this study, we elected to split tissues immediately after dissection and before rna extraction in order to restrict the possible sources of between-mouse variation to events that occur prior to dissection. with this experimental design, transcript variation can be decomposed into within-mouse and between-mouse variance components. between-mouse variance reflects differences in whole-tissue transcript abundance between genetically identical mice. within-mouse variance captures variation due to rna extraction, array processing, and heterogeneity of gene expression within tissues, which may be amplified by dissection and tissue collection procedures. individual variation in gene expression can have important phenotypic consequences. however, only a few studies have previously attempted to characterize gene expression variation in genetically identical mice. koza et al. described gene expression signatures in adipose tissue that are predictive of future adiposity among genetically identical c57bl/6j mice. the use of multiple biopsy samples in this time-course study was essential to establish the link between gene expression variation and late-life adiposity. however, biopsy sampling may be subject to unexpected variation introduced by tissue heterogeneity, as we illustrate below. two previous studies have used multiple sampling within individuals to provide a statistical basis for detecting transcript variation between genetically identical mice. pritchard et al. examined tissues in each of c57bl/6j mice and reported that immune function, stress response, and hormone regulation were important sources of biological variation. pritchard et al. examined liver tissue in animals from each of inbred mouse strains and found that genes differentially expressed within strains were enriched for cell growth, cytokine activity, amine metabolism, and ubiquitination. in these experiments, technical replicates were obtained by splitting samples after rna extraction. this approach confounds variation due to dissection and rna preparation with variation between mice. we designed and carried out an experiment to study transcript abundance variation in four tissues among young adult male c57bl/6j mice. our sampling design enabled us to partition the variance for each gene into within-mouse and between-mouse components, with a division line that corresponds to the step of splitting tissues. we examined within-mouse and between-mouse variation in more than protein coding genes and identified groups of genes with shared patterns of variation that are enriched for known biological functions. to facilitate exploration of our data, we have created an on-line resource that includes graphical displays, test statistics, and gene groupings for all transcripts characterized in this study http://cgd.jax.org/individualvariation.shtml.  we performed a microarray experiment using the illumina sentrix® mouse- v beadchip microarray platform to study transcript variation in 10-week old male c57bl/6j mice. six pairs of siblings were co-housed from weaning under uniform environmental conditions. from each mouse we obtained duplicate samples of adipose, heart, kidney, and liver tissues by splitting whole organs or tissues prior to homogenization and rna extraction. adipose, heart, and liver tissues were coarsely cut into pieces and divided into two samples that were homogenized separately in order to extract rna. the left and right kidneys were also homogenized separately. we computed a decomposition of variance for each probe on the array. the within-mouse variance component captures biological variance between two dissected tissue samples as well as technical variance due to sample and microarray processing. the between-mouse variance component reflects differences between individual mice. we repeated gene expression assays on the liver samples, using the affymetrix whole-transcript mouse gene st array, to provide validation on a different measurement platform. expressed genes and variable genes we declared a gene to be expressed if the probe intensity was greater than the 95th percentile of the negative control probes for both samples in at least of the mice. a total of genes, representing 55% of the annotated probes on the array, were expressed in at least one of the four tissues. across tissues, the number of expressed genes ranged from in liver to in adipose tissue. shown in this table are: the number of expressed genes out of the annotated genes on the array. the number of variable genes based on the, and tails of the scaled χ distribution. the number of genes with significant between-mouse variance, based on the fs test with family-wise adjusted error; false discovery rate; and the estimated proportion of differentially expressed genes. the number of genes with large maximal fold-change between mice. all numbers are given as percentages of the annotated genes in parentheses. we computed the total variance, s across all samples for each gene in each tissue. liver and kidney have relatively few genes of high variability but heart and adipose have many. we tested the hypothesis that the distribution of total variance occurred by chance using a χ test and found significantly greater variance than expected in each tissue. we applied coexpression network analysis to the top genes in each tissue, which we refer to as the variable genes. we decomposed total variance for each gene into within-mouse and between-mouse components. the distribution of between-mouse variance components was similar across all four tissues. adipose tissue showed the greatest number of genes with a large within-mouse component followed by heart, kidney, and liver. the variable genes include the,,, and genes with the largest between-mouse variance. they also include the,,, and genes with the largest within-mouse variance. significance of between-mouse variance within each tissue, for each gene, we computed a test statistic to assess the significance of the between-mouse variance component relative to the within-mouse variance component. we applied a family-wise error rate correction ) and found few genes with significant between-mouse variation. we applied a false discovery rate adjustment ) and found no differentially expressed genes in adipose or heart and only modest numbers in kidney and liver. we estimated the proportions of differentially expressed genes using the q-value software and found similar results. a different picture of the variability in gene expression across tissues emerges when we look at the maximal fold change between mice. in adipose, % of all genes exhibit maximal fold changes greater than whereas - % of all genes show fold changes this large in the other three tissues. although the fold-change is not a statistical criterion, the differences across tissues are dramatic. there are many genes with large maximal fold changes between mice but, particularly in adipose tissue, these same genes also have large within-mouse variance, which reduces their statistical significance. variable genes form clusters that are enriched for specific biological functions we used co-expression network analysis to cluster the variable genes into modules with correlated patterns of expression. module sizes ranged from to genes with an average module size of genes. we identified to modules in each tissue comprising 97%, 80%, 61%, and 54% of the variable genes. for each module, we applied principal components analysis to compute a module eigengene that represents the dominant pattern of variation. the percentage of variation explained by the module eigengene ranges from 47% to 88%, indicating that the eigengenes are representative of expression profiles of the individual genes in each module. in the following, we refer to modules using a colour code within each tissue. best enrichment scores of co-expression modules are shown. within each tissue, modules are listed by the colour code orders of figure the number of genes in the module, the number of variable genes in the highest scoring functional category, the overlap between these two sets of genes, the enrichment p-value for the highest scoring category, and the median intraclass correlation, c, for genes in the module are shown. only categories with between and genes and a minimum overlap of genes were considered. for each gene, we computed the intraclass correlation coefficient, c ≡ sb2/, which is the proportion of total variance attributable to the between-mouse component. median values by module ranged from c = to c =. kidney and liver, respectively, have and modules with high intraclass correlation indicating substantial between-mouse variance while adipose has two and heart has no modules with high intraclass correlation. each tissue also has at least one module with low intraclass correlation indicating that differences between samples within mice are greater than differences between mice. for each module, we computed enrichment scores for the go biological process, cellular component, and molecular function terms and for kegg pathways. the highest scoring enrichment category for each module is listed in table each module can be divided into two subsets such that all correlations within a subset are positive. we also tested for enrichment within each of these subsets. many of the module enrichment scores are highly significant indicating that correlated groups of variable genes are enriched for specific biological functions. most modules in a given tissue share similar features with at least one module in another tissue. several sets of modules shared similar patterns of between-mouse variation and had significant gene overlap and functional enrichment. other sets of modules shared similar patterns of within-mouse variation, but with distinct between-mouse variation. several pairs of modules had significant gene overlap but did not have correlated patterns of variation. examples of each are described below. between-mouse patterns of variation are shared across tissues modules from different tissues that are enriched for similar functional categories typically have high intraclass correlation and similar patterns of between-mouse variation. to quantify this similarity, we computed a between-mouse correlation, rb, for all pairs of module eigengenes by averaging the two within-mouse samples before computing the pearson correlation. each of the four tissues has at least one module that is enriched for immune response. the heart-brown, kidney-gold, and liver-pink modules are enriched for the go category exogenous antigen presentation. the between-mouse correlations, rb, range from to, and the genes in these modules overlap significantly based on a hypergeometric test. pairwise overlaps range from to genes and seven genes are found in all modules. the kidney-blue and liver-brown modules are enriched for go category extracellular matrix, each containing more than genes of that category. their between-mouse profiles are correlated and they share genes in common including adamts col5a col6a col14a ecm igfbp tgfbi and timp the adipose-red, heart-blue, kidney-brown and liver-black modules are enriched for the go category apoptosis and have between-mouse correlations, rb, ranging from to. these modules overlap with genes present in at least of the modules including ccrn4l, gadd45g, and map3k the liver-blue module also has a high between-mouse correlation and significant gene overlap with these adipose, heart and kidney modules including fkbp and per the kidney-pink and liver-magenta modules have correlated between-mouse profiles, and each contains or more genes of the go category dna-dependent regulation of transcription. their gene overlap includes bcl cish, rgs and socs the between-mouse profiles of the kidney-green and liver-red modules are correlated and each module contains or more genes of the go category cellular lipid metabolic process. they have genes in common including acaa acadm, agxt2l cyp26b cyp4a cyp4a and slc2a within-mouse patterns are similar across modules of the same tissue some modules had similar patterns of within-mouse variation but different patterns of between-mouse variation. to measure similarity of within-mouse variation, we centred the sample values on individual mouse means and then computed a pearson correlation, rw. this measure is only meaningful for comparisons within the same tissue as there is no correspondence between the duplicate samples from different tissues. adipose and heart each have multiple highly correlated modules. the adipose-green, adipose-red, adipose-black, and adipose-magenta modules have distinct patterns of between-mouse variation and different functional enrichment, but they all share high within-mouse correlation. a similar relationship was observed for the heart-green, heart-red, heart-turquoise, heart-blue, heart-brown, and heart-gold modules. uncorrelated modules have gene overlap and similar functional enrichment some modules share genes and functional enrichment categories but do not have correlated patterns of variation. the adipose-gold, heart-red, and kidney-black modules have a high gene overlap. they are enriched for the go category fatty acid metabolic process. the adipose-magenta and heart-gold modules share out of genes including cd8b and lck and are enriched for the go category immune system process. the adipose-brown module shares out of genes with the heart-green module and out of genes with the liver-turquoise module. these modules are enriched for the go actin cytoskeleton category and share genes in common including ckm and myl the adipose-turquoise and kidney-turquoise modules share out of genes including apoal, cyp8b and ugt2b and are enriched for the kegg pathway complementation and coagulation cascades. the adipose-green and heart-turquoise modules are overlapping in out of genes including ccl cxcl egr fos, and hmox and are enriched for chemokine activity. the adipose-black, heart-black, kidney-magenta, and liver-green modules have pairwise overlaps ranging from to genes. twenty-two genes are shared among all of these modules and they are enriched for kegg pathway oxidative phosphorylation and the go category mitochondrial inner membrane. comparison across platform we repeated the gene expression assays for only the liver samples on a different platform, the affymetrix whole-transcript mouse gene st array. to facilitate comparison, we generated a cross-platform probe map based on gene annotation. using this map, we computed eigengenes of the previously defined clusters from the affymetrix data. correlation of the eigengenes across platforms was very high for of the modules. two modules with lower correlation had less than 20% of variance explained by the eigengene with affymetrix data. however, for the liver-gold module, low expression for mouse was a consistent pattern across platforms. the profiles of all genes that are highlighted in the discussion are highly correlated across platform. discussion there are several mechanisms that may contribute to between-mouse variation in gene expression in c57bl/6j mice. new mutations that create single nucleotide or copy number variants may result in variable gene expression. we expect such events to be rare. however, we have observed a striking pattern of differential expression in the insulin degrading enzyme with approximately two-fold higher expression in all tissues for the two mice of cage we speculate that these siblings may have inherited a copy number variant at this locus on chromosome for which copy number changes have been observed previously in c57bl/6j mice. genes that display circadian or other periodic expression patterns can be out of phase in different animals. we attempted to control for cyclical variation by collecting samples in a consistent and narrow time frame for all mice. variation in feeding behaviour is another possible factor and although we implemented a 4-hour fast prior to tissue collection, some variation in time since last feeding is inevitable. epigenetic differences may affect the expression of genes as a result of variable access to nutrients in utero, birth order, maternal stress or other pre- or post-partum events. slight differences in phenotype at birth may be magnified over time. response to subtle differences in local environment may have an effect on gene expression and finally, the expression of some genes may be sensitive to events just prior to euthanasia. within-mouse transcript variation could reflect stochastic variation in gene expression, which has been observed within individual cells and across cell populations. however, if it is present, this effect seems to be dominated by other factors in our study. tissue heterogeneity due, for example, to localization of stem and progenitor cell populations can result in sampling variation. this variation may be amplified by dissection, especially in tissues with imprecise boundaries. even a relatively homogenous and easily isolated tissue such as liver will have internal structure that can influence local gene expression. phenotypic implications of between- and within-mouse variation in adipose tissue adipose tissue is compartmentalized into adipocytes, preadipocytes, and vascular epithelium. the degree of vascularisation can vary significantly across different regions of the same fat pad and is expected to be greater in the portion of the inguinal fat pad that is near the inguinal lymph node. vascularised adipose tissue tends to be more metabolically active. we found a large number of genes that have within-mouse variation related to vascularisation in the adipose-magenta module. the positively correlated subset of this module is enriched for go biological processes immune response, t cell activation, and lymphocyte activation and include genes expressed in lymphocytes such as lck, cd8b and elf. some genes within the adipose-magenta module, which is dominated by within-mouse variation, also have large between-mouse fold changes. these genes, including bmp sfrp mest, lep and trp53inp are positively correlated with body weight and were previously found to be predictive for adiposity. they are also negatively correlated with the module eigengene, which is consistent with higher expression in the less vascularised region of the inguinal fat pad, suggesting an inverse relationship between vascularisation and adiposity. we chose to study the inguinal fat pad because it can be efficiently dissected. gene expression can vary among fat depots and proximity to the inguinal lymph node clearly contributed to heterogeneity in the inguinal fat pad. this limits our ability to generalize our findings. however, our previous experience indicates that other fat depots are at least as variable as the inguinal depot. the koza et al. study identified their adiposity signature, which we have replicated, in epididymal and retroperitoneal fat. variable brown fat signature in white fat tissue several genes in the adipose-gold module are expressed exclusively in brown fat, including ucp cidea, and cox8b. this module is enriched for fatty acid metabolism and the module eigengene is correlated with prdm, which is part of a transcriptional complex that promotes brown fat differentiation and suppresses skeletal muscle cell differentiation. the adipose-brown module is enriched with genes of the go biological process muscle contraction. genes in this module are expressed in both skeletal muscle and brown fat and many are related to brown fat cell differentiation. we ruled out cross contamination with muscle tissue by inspection of the dissection procedure. the enrichment for muscle contraction appears to be spurious and reflects a potential pitfall of enrichment analysis using go annotation. most of the variation in the adipose-gold and adipose-brown modules is attributable to the within-mouse component, which suggests a heterogeneous spatial distribution of brown fat within the inguinal fat pad. however, large between-mouse fold changes, including ckm, with 56-fold change, the largest observed in this study, suggest that the proportion of brown fat may also vary across mice. brown fat tissue proportion have previously been shown to vary with age, strain, and environmental conditions. region-specific variation of gene expression in heart the heart is composed primarily of cardiac smooth muscle, but it is differentiated into atrial, ventricular and trabecular regions with a left-right asymmetry. several genes expressed in atria and trabeculae of the heart are repressed in the ventricles, in part, through activity of the transcription factor, gata. the heart-green module is enriched for these genes and shows a pattern of within-mouse variation with little between-mouse variation. gata is in the heart-red module, which has a strong within-mouse correlation to the heart-green module. gata is negatively correlated with the heart-red eigengene such that the within-mouse variation in gata is inversely related to the expression of ventricle-repressed transcripts. we compared our results with a study of chamber-specific gene expression ) and found that, of the genes previously reported to be more highly expressed in the atria than in the ventricles, are included in the heart-green module. the relatively small magnitude of between-mouse variation in these modules reflects the effect of averaging of the two samples, which together comprise the whole heart. we conclude that much of the within-mouse variation observed for heart tissue is a consequence of variable proportions of anatomical substructures, specifically ventricular tissue, within the samples. androgen-regulated genes are variable between mice in the kidney many genes are regulated in response to androgens. in mice, srd5a plays a key role in androgen signal amplification suggesting that androgenic effects in individuals with higher srd5a expression could be more pronounced. hsd11b facilitates the conversion of testosterone to adrenosterone and has been shown to be androgen-responsive in mice. these genes were found to be variable between mice and cluster together in the kidney-green module, which is enriched for the kegg androgen and estrogen metabolism pathway. other androgen-responsive genes in the kidney-green module include cyp4a slco1a nudt prlr, angptl hsd17b and tmco. it is not immediately clear if this variation reflects transient or steady state variation in androgen levels between mice. the expression of a mouse urinary protein, gusb, is responsive to androgens in the long-term but not in the short-term. gusb has significant between-mouse variation that is correlated with the kidney-green module eigengene. this suggests that other genes in this module also reflect steady state androgen levels, which may have important physiological and behavioural implications. between-mouse variation in fatty acid metabolism in the liver genes in the liver-red module have either low or high expression in the two mice of cage. genes in the low expression subset are involved in oxidation of fatty acids. genes in the high expression subset, specifically tnfrsf1a and ptgis, are involved in the conversion of the essential fatty acid arachidonic acid to prostaglandins. thus, we see decreased fatty acid degradation in mice that are actively utilizing fatty acids. the liver-red module also shares genes with the androgen-associated kidney-green module which may reflect the requirement for lipids as precursors in androgen synthesis. between-mouse variation in circadian rhythm the adipose-red, heart-blue, kidney-brown, liver-blue, and liver-black modules are correlated and share multiple genes related to apoptotic activity, which varies following circadian rhythm in mice. several other genes that are known to vary in a circadian fashion are also found in these modules, including ccrn4l, fkbp gadd45g, map3k per pim mt sgk errfi cdkn1a, dusp and angptl the core circadian gene per is found in the adipose-red module. genes that follow a circadian expression pattern are expected to vary with the time of day and with fasting/feeding cycles. despite our efforts to control both of these factors, between-mouse variation can be expected to arise if the mice are in slightly different phases of their diurnal cycles. angptl cdkn1a, dusp and fkbp vary in circadian fashion and are all located in a mb region on proximal chromosome this region is the strongest example of coexpression clustering that we found in this study. however, statistical assessment suggests that a cluster of this size could be explained by chance. between-mouse variation associated with growth hormone the genes socs bcl cish, and gadd45g have correlated patterns of variation in kidney and liver and are among the genes with the most significant between-mouse variation. growth hormone has been shown to elicit a strong transcriptional response in socs, cish, bcl, and gadd45g, as well as in the growth hormone responders igf and il. three of these genes belong to the kidney-pink and liver-magenta modules, which have overlapping genes and are enriched for genes involved in transcription regulation. growth hormone signalling affects transcription of genes such as xbp, which is critical for the regulation of hepatic lipogenesis. the effect of growth hormone signalling appears to extend beyond these modules, however. among genes previously identified as growth hormone responders, were classified as variable in our study, indicative of widespread individual variation in growth hormone signalling. similarities and differences in transcript abundance for sibling cage mates sibling cage mates may be expected to exhibit greater similarity than randomly selected mice of the same strain due to shared developmental or micro-environmental factors. when we further partitioned the between mouse variance into between-cage and within-cage components, we found more genes with significant between-cage variation than within-cage variation. the liver-red module provides a striking example of within-cage similarity. enrichment for genes associated with fatty acid oxidation in this module could reflect an extended period of fasting just prior to euthanasia. for example, expression of murine hepatic cyp4a is known to increase in expression under fasting conditions. this gene has been reported to be variable between strains in liver, but it is not clear whether this is a genuine strain-specific effect or an artefact due to co-housing of mice of the same strain. other factors could contribute to greater differences between mice within a cage. cohabitating outbred male mice form a social structure that includes dominance status even when mice are housed as siblings from birth. dominance behaviour has been observed within male mice of some inbred strains but not c57bl/6j. however, cohabitation has known phenotypic effects on c57bl/6j males including change in body weight, adrenal weight, and aggressiveness. the factors that determine the social status of siblings raised together are unclear, but once established, social behaviour can reinforce these minor differences leading to distinct individual phenotypes in adult mice. in our experiment, we observed within-cage body weight difference of as much as 3g. some of the transcriptional changes that we have observed are likely to be related to these body weight differences. for example, in cage we observed a large body weight difference coincident with a large difference in transcription of signature genes for adiposity, but small differences in signature genes for androgen levels. in contrast, in cages and body weight differences coincide with a transcriptional signature for androgen response but not for adiposity. this suggests that bodyweight differences may reflect two distinct processes, one that affects adiposity and another that affects androgen levels and lean mass. moreover, these findings provide evidence for an effect of social context on biological processes that have important consequences for human health. comparison to a previous study of transcript variation we directly compared our results to a previous study of transcriptional variation in c57bl/6j mice by computing variance components and applying the same significance tests to both data sets. we found little correlation in total variation which we attribute to the predominance of technical variation, especially in the older study. however, we did find good agreement across these studies when we examined specific genes highlighted in the previous study. cfd was reported to vary significantly between mice in the kidney for the previous experiment in which effects due to dissection and rna extraction are included in the between-mouse variance component. we also found it to be a variable gene, but, in contrast, we identified cfd as a gene with primarily within-mouse variation in the kidney-black module. both studies identified significant between-mouse variation in several highly variable genes, including gadd45g, dusp cish, and bcl. our study, with a larger sample size, a more recent array technology, and a different experimental design should provide a more precise and detailed picture of variation in gene expression.  transcript abundance varies significantly among genetically identical male c57bl/6j mice housed under uniform conditions. patterns of variation can be tissue specific or shared across multiple tissues and transcripts can vary between tissue samples collected from the same animal. groups of genes with correlated patterns of between-animal or within-animal variation are often enriched for specific functional annotations. we utilized correlation-based clustering to organize a large number of distinct patterns of variation. literature search tools and functional annotation aided in the interpretation of our findings. however, annotation of gene function is incomplete and this presented some challenges as exemplified by the finding of a skeletal muscle signature in white adipose tissue, which was due to the presence of a related cell type, brown fat. this study highlights a number of potential biological and technical sources of variation that practitioners should be aware of for both experimental design and interpretation. much of the between-animal variation reported here reflects functions that are sensitive to environmental cues, such as androgen response, circadian rhythm, and immune response. external environmental cues tend to elicit similar responses in multiple tissues. variation of gene expression within tissues reflects their heterogeneous cellular composition, and is also a major factor contributing to variation in gene expression. this underscores the potential for dissection or biopsy procedures to introduce unwanted variation into studies of gene expression. adipose tissue is especially problematic in this regard as it is a highly dynamic and heterogeneous tissue with few anatomical features to guide consistent dissection. our tissue collection procedure involved a coarse separation of tissue fragments which, in retrospect, was useful to reveal within-tissue heterogeneity. an exception to this was our use of the intact left and right kidneys as replicates. this may explain the relatively low within-mouse variation observed for this heterogeneous and highly structured tissue. in future studies, we recommend the use of procedures that more effectively homogenize tissue, such as pulverization and mixing of snap frozen samples. our finding also raises questions about the potential for introducing systematic variation in the dissection of anatomical substructures. this may be a particular concern for studies of gene expression in the brain, for which we have no data at this time. the presence of biologically meaningful covariation in a setting with no experimental perturbation underscores the need for replication and careful adherence to statistical design principles in gene expression studies. seemingly innocuous experimental factors such as co-housing of mice can result in systemic differences that may lead to strong statistical support for incorrect conclusions. prior knowledge of the categories of genes that are intrinsically variable can help to identify such effects. our study further demonstrates that the variation used to construct statistical tests in microarray experiments can have substantial correlation across large sets of genes. this can have a profound impact on testing procedures, especially those that rely on multiple test adjustment of p-values across many genes. 
between-mouse variance reflects differences in transcript abundance between genetically identical mice. genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. we have designed and carried out a microarray experiment to examine transcript variation across samples from adipose, heart, kidney, and liver tissues of c57bl/6j mice and to partition variation into within-mouse and between-mouse components. transcripts can exhibit significant variation in tissue samples from inbred laboratory mice. within-mouse variance captures variation due to heterogeneity of gene expression within tissues, rna-extraction, and array processing. variation in gene expression observed between genetically identical mice can identify functional classes of genes that are likely to vary in the absence of experimental perturbations, can inform experimental design decisions, and provides a baseline for the interpretation of gene expression data in interventional studies. variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. genetically identical mice can experience different individual outcomes for medically important traits. the extent of transcript variation among genetically identical mice underscores the importance of stochastic and micro-environmental factors and their phenotypic consequences. adipose has the largest total variance and the largest within-mouse variance. genes showing correlated patterns of within-mouse variation are also associated with biological functions that largely reflect heterogeneity of cell types within tissues. liver has the smallest total variance, but it has the most between-mouse variance. the nature and extent of transcript variation differs across tissues.
 transcripts can exhibit significant variation in tissue samples from inbred laboratory mice. we have designed and carried out a microarray experiment to examine transcript variation across samples from adipose, heart, kidney, and liver tissues of c57bl/6j mice and to partition variation into within-mouse and between-mouse components. within-mouse variance captures variation due to heterogeneity of gene expression within tissues, rna-extraction, and array processing. between-mouse variance reflects differences in transcript abundance between genetically identical mice.  the nature and extent of transcript variation differs across tissues. adipose has the largest total variance and the largest within-mouse variance. liver has the smallest total variance, but it has the most between-mouse variance. genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. genes showing correlated patterns of within-mouse variation are also associated with biological functions that largely reflect heterogeneity of cell types within tissues.  genetically identical mice can experience different individual outcomes for medically important traits. variation in gene expression observed between genetically identical mice can identify functional classes of genes that are likely to vary in the absence of experimental perturbations, can inform experimental design decisions, and provides a baseline for the interpretation of gene expression data in interventional studies. the extent of transcript variation among genetically identical mice underscores the importance of stochastic and micro-environmental factors and their phenotypic consequences. 