Limits...
Transcriptome architecture across tissues in the pig.

Ferraz AL, Ojeda A, López-Béjar M, Fernandes LT, Castelló A, Folch JM, Pérez-Enciso M - BMC Genomics (2008)

Bottom Line: Artificial selection has resulted in animal breeds with extreme phenotypes.For instance, an excess of nervous system or muscle development genes were found among tissues of ectoderm or mesoderm origins, respectively.The interaction in gene x tissue for differentially expressed genes between breeds suggests that animal breeding has targeted differentially each tissue's transcriptome.

View Article: PubMed Central - HTML - PubMed

Affiliation: Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain. splinter_zoo2@yahoo.com.br

ABSTRACT

Background: Artificial selection has resulted in animal breeds with extreme phenotypes. As an organism is made up of many different tissues and organs, each with its own genetic programme, it is pertinent to ask: How relevant is tissue in terms of total transcriptome variability? Which are the genes most distinctly expressed between tissues? Does breed or sex equally affect the transcriptome across tissues?

Results: In order to gain insight on these issues, we conducted microarray expression profiling of 16 different tissues from four animals of two extreme pig breeds, Large White and Iberian, two males and two females. Mixed model analysis and neighbor - joining trees showed that tissues with similar developmental origin clustered closer than those with different embryonic origins. Often a sound biological interpretation was possible for overrepresented gene ontology categories within differentially expressed genes between groups of tissues. For instance, an excess of nervous system or muscle development genes were found among tissues of ectoderm or mesoderm origins, respectively. Tissue accounted for ~11 times more variability than sex or breed. Nevertheless, we were able to confidently identify genes with differential expression across tissues between breeds (33 genes) and between sexes (19 genes). The genes primarily affected by sex were overall different than those affected by breed or tissue. Interaction with tissue can be important for differentially expressed genes between breeds but not so much for genes whose expression differ between sexes.

Conclusion: Embryonic development leaves an enduring footprint on the transcriptome. The interaction in gene x tissue for differentially expressed genes between breeds suggests that animal breeding has targeted differentially each tissue's transcriptome.

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NJ (left) and UPGMA trees (right) using the 1 - r2 distance. Each sample is named using the tissue acronym (four letters, Table 1), breed (LW or IB) and sex (M, male or F, female); LW males are indicated by open squares; LW females, by open circles; IB males, by black squares and IB females, by black circles.
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Figure 1: NJ (left) and UPGMA trees (right) using the 1 - r2 distance. Each sample is named using the tissue acronym (four letters, Table 1), breed (LW or IB) and sex (M, male or F, female); LW males are indicated by open squares; LW females, by open circles; IB males, by black squares and IB females, by black circles.

Mentions: Clustering is a useful starting exploratory tool to visualize highly dimensional data, and has been widely used to microarray data since the seminal paper of Eisen and cols. [17]. Here we applied two clustering methdos, the classical one based on the UPGMA criterion [17], and the neighbor-joing (NJ) clustering. In both cases, we used the distance one minus the squared correlation (1-r2) between the samples, after normalizing the raw data with the RMA procedure [18], as detailed in Material and Methods. Results are drawn in Figure 1, where it can be seen that samples were clearly grouped by tissue, next by breed in both trees. This was neatly observed for ileum, liver, thyroid gland, adeno and neurohypohysis and olfactory bulb. Muscle samples were clustered by tissue (diaphragma vs. M. biceps femori) but less clearly within each muscle. As for fat, the similarity was larger between tissues than between breeds, and samples of both back and abdominal fat origins were clustered together. The same was observed between cortex and medulla from adrenal gland. In this case, contamination between both tissues cannot be ruled out because of the irregular limits of the medulla that make not easy to separate that region neatly from the cortex collecting rapidly enough amount of tissue for analysis. Other authors have described previously contamination of medulla in the cortex sample when mechanical separation is performed[19]. Thus, this resemblance was not completely unexpected. The only outlier sample seemed to be the pineal gland of the Large White male (PING_LWM), which clustered with the rest of hypothalamus microarrays. Here contamination can be discarded in all likelihood because the two regions, hypothalamus and pineal gland, are in distinct areas of the brain. However, the pineal gland works in harmony with the hypothalamus. The former produces melatonin, which directly influences the function of various brain centers, including the hypothalamus. In stomach, less clearly in blood, samples were grouped by sex rather than by breed.


Transcriptome architecture across tissues in the pig.

Ferraz AL, Ojeda A, López-Béjar M, Fernandes LT, Castelló A, Folch JM, Pérez-Enciso M - BMC Genomics (2008)

NJ (left) and UPGMA trees (right) using the 1 - r2 distance. Each sample is named using the tissue acronym (four letters, Table 1), breed (LW or IB) and sex (M, male or F, female); LW males are indicated by open squares; LW females, by open circles; IB males, by black squares and IB females, by black circles.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2335121&req=5

Figure 1: NJ (left) and UPGMA trees (right) using the 1 - r2 distance. Each sample is named using the tissue acronym (four letters, Table 1), breed (LW or IB) and sex (M, male or F, female); LW males are indicated by open squares; LW females, by open circles; IB males, by black squares and IB females, by black circles.
Mentions: Clustering is a useful starting exploratory tool to visualize highly dimensional data, and has been widely used to microarray data since the seminal paper of Eisen and cols. [17]. Here we applied two clustering methdos, the classical one based on the UPGMA criterion [17], and the neighbor-joing (NJ) clustering. In both cases, we used the distance one minus the squared correlation (1-r2) between the samples, after normalizing the raw data with the RMA procedure [18], as detailed in Material and Methods. Results are drawn in Figure 1, where it can be seen that samples were clearly grouped by tissue, next by breed in both trees. This was neatly observed for ileum, liver, thyroid gland, adeno and neurohypohysis and olfactory bulb. Muscle samples were clustered by tissue (diaphragma vs. M. biceps femori) but less clearly within each muscle. As for fat, the similarity was larger between tissues than between breeds, and samples of both back and abdominal fat origins were clustered together. The same was observed between cortex and medulla from adrenal gland. In this case, contamination between both tissues cannot be ruled out because of the irregular limits of the medulla that make not easy to separate that region neatly from the cortex collecting rapidly enough amount of tissue for analysis. Other authors have described previously contamination of medulla in the cortex sample when mechanical separation is performed[19]. Thus, this resemblance was not completely unexpected. The only outlier sample seemed to be the pineal gland of the Large White male (PING_LWM), which clustered with the rest of hypothalamus microarrays. Here contamination can be discarded in all likelihood because the two regions, hypothalamus and pineal gland, are in distinct areas of the brain. However, the pineal gland works in harmony with the hypothalamus. The former produces melatonin, which directly influences the function of various brain centers, including the hypothalamus. In stomach, less clearly in blood, samples were grouped by sex rather than by breed.

Bottom Line: Artificial selection has resulted in animal breeds with extreme phenotypes.For instance, an excess of nervous system or muscle development genes were found among tissues of ectoderm or mesoderm origins, respectively.The interaction in gene x tissue for differentially expressed genes between breeds suggests that animal breeding has targeted differentially each tissue's transcriptome.

View Article: PubMed Central - HTML - PubMed

Affiliation: Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain. splinter_zoo2@yahoo.com.br

ABSTRACT

Background: Artificial selection has resulted in animal breeds with extreme phenotypes. As an organism is made up of many different tissues and organs, each with its own genetic programme, it is pertinent to ask: How relevant is tissue in terms of total transcriptome variability? Which are the genes most distinctly expressed between tissues? Does breed or sex equally affect the transcriptome across tissues?

Results: In order to gain insight on these issues, we conducted microarray expression profiling of 16 different tissues from four animals of two extreme pig breeds, Large White and Iberian, two males and two females. Mixed model analysis and neighbor - joining trees showed that tissues with similar developmental origin clustered closer than those with different embryonic origins. Often a sound biological interpretation was possible for overrepresented gene ontology categories within differentially expressed genes between groups of tissues. For instance, an excess of nervous system or muscle development genes were found among tissues of ectoderm or mesoderm origins, respectively. Tissue accounted for ~11 times more variability than sex or breed. Nevertheless, we were able to confidently identify genes with differential expression across tissues between breeds (33 genes) and between sexes (19 genes). The genes primarily affected by sex were overall different than those affected by breed or tissue. Interaction with tissue can be important for differentially expressed genes between breeds but not so much for genes whose expression differ between sexes.

Conclusion: Embryonic development leaves an enduring footprint on the transcriptome. The interaction in gene x tissue for differentially expressed genes between breeds suggests that animal breeding has targeted differentially each tissue's transcriptome.

Show MeSH