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| Status |
Public on Oct 01, 2010 |
| Title |
Transcript variation in C57BL/6J mice under normal laboratory conditions |
| Organism |
Mus musculus |
| Experiment type |
Expression profiling by array
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| Summary |
BACKGROUND: The transcript levels of many genes exhibit significant variation in tissue samples from inbred laboratory mice. A microarray experiment was designed to separate transcript abundance variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice 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 levels between these genetically identical mice. Many biological sources can contribute to heterogeneous transcript levels within a tissue sample including inherent stochasticity of biochemical processes such as intrinsic and extrinsic noise within cells and differences in cell-type composition which can result from heterogeneity of stem and progenitor cell populations. Differences in global signaling patterns between individuals and micro-environmental influences such as interactions with pathogens and cage mates can also contribute to variation, but are likely to contribute more to the between-mouse variance component.
RESULTS: The nature and extent of transcript abundance 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 variation. 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 were also associated with biological functions, spatial connectivity of stochastic variation and heterogeneity of cell types within tissues.
CONCLUSIONS: Genetically identical mice are individuals and they can experience different outcomes for medically important traits. This is reflected in the stochastic variation in gene expression observed between genetically identical mice. Much of the stochasticity has organismal, tissue, or spatial connectivity. Prior knowledge of the genes and functional classes of genes that are likely to vary in the absence of experimental perturbations, whether these are genetic or environmental, can inform experimental design decisions and the interpretation of gene expression data. Variation in gene expression in genetically identical mice sheds light on the impact of stochastic and micro-environmental factors and their phenotypic consequences.
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| Overall design |
Four tissues were sampled from twelve 10-week old male mice. Six pairs of siblings were co-housed from weaning under uniform environmental conditions. From each mouse we obtained duplicate samples of adipose (inguinal fat pad), 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 prior to RNA extraction. The left and right kidneys were processed separately. This sampling design allows 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.
[Stochastic Variation of Transcript Abundance in C57BL/6J Mice]: The liver tissues were sampled from twelve 10-week old male mice. Six pairs of siblings were co-housed from weaning under uniform environmental conditions. From each mouse we obtained duplicate samples by splitting whole organs or tissues prior to homogenization and RNA extraction. Each whole tissue was coarsely cut into pieces and divided into two samples that were homogenized separately prior to RNA extraction. This sampling design allows 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.
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| Contributor(s) |
Vedell PT, Svenson KL, Churchill GA |
| Citation(s) |
21450099 |
| Submission date |
Feb 01, 2010 |
| Last update date |
Mar 04, 2019 |
| Contact name |
Peter Thomas Vedell |
| E-mail(s) |
vedellpt@gmail.com
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| Organization name |
The Jackson Laboratory
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| Street address |
600 Main Street
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| City |
Bar Harbor |
| State/province |
ME |
| ZIP/Postal code |
04609 |
| Country |
USA |
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| Platforms (2) |
| GPL6246 |
[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] |
| GPL6481 |
Illumina mouse-6 v1.1 expression beadchip [Array_Address_Id version] |
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| Samples (120)
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| Relations |
| BioProject |
PRJNA124261 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE20121_RAW.tar |
97.4 Mb |
(http)(custom) |
TAR (of CEL) |
| GSE20121_raw_data_file.txt.gz |
22.6 Mb |
(ftp)(http) |
TXT |
| Processed data included within Sample table |
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