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Identification of transcripts with enriched expression in the developing and adult pancreas.

Hoffman BG, Zavaglia B, Witzsche J, Ruiz de Algara T, Beach M, Hoodless PA, Jones SJ, Marra MA, Helgason CD - Genome Biol. (2008)

Bottom Line: Based on these results we identified a cascade of transcriptional regulators expressed in the endocrine pancreas lineage and, from this, we developed a predictive regulatory network describing beta-cell development.Taken together, this work provides evidence that the SAGE libraries generated here are a valuable resource for continuing to elucidate the molecular mechanisms regulating pancreas development.Furthermore, our studies provide a comprehensive analysis of pancreas development, and insights into the regulatory networks driving this process are revealed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Cancer Endocrinology, BC Cancer Research Center, West 10th Ave, Vancouver, BC V5Z 1L3, Canada. bhoffman@bccrc.ca

ABSTRACT

Background: Despite recent advances, the transcriptional hierarchy driving pancreas organogenesis remains largely unknown, in part due to the paucity of comprehensive analyses. To address this deficit we generated ten SAGE libraries from the developing murine pancreas spanning Theiler stages 17-26, making use of available Pdx1 enhanced green fluorescent protein (EGFP) and Neurog3 EGFP reporter strains, as well as tissue from adult islets and ducts.

Results: We used a specificity metric to identify 2,536 tags with pancreas-enriched expression compared to 195 other mouse SAGE libraries. We subsequently grouped co-expressed transcripts with differential expression during pancreas development using K-means clustering. We validated the clusters first using quantitative real time PCR and then by analyzing the Theiler stage 22 pancreas in situ hybridization staining patterns of over 600 of the identified genes using the GenePaint database. These were then categorized into one of the five expression domains within the developing pancreas. Based on these results we identified a cascade of transcriptional regulators expressed in the endocrine pancreas lineage and, from this, we developed a predictive regulatory network describing beta-cell development.

Conclusion: Taken together, this work provides evidence that the SAGE libraries generated here are a valuable resource for continuing to elucidate the molecular mechanisms regulating pancreas development. Furthermore, our studies provide a comprehensive analysis of pancreas development, and insights into the regulatory networks driving this process are revealed.

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Related in: MedlinePlus

Specificity threshold accurately predicts spatial expression restriction. A plot of specificity (S) versus cumulative tag types represented shows the distribution of tags into tags with high (S > 0.1; top), medium (0.001 > S < 0.1, middle), and low (S < 0.001, bottom) S values. Representative in situ hybridization staining patterns from TS22 whole embryo saggital sections obtained from GenePaint are shown for each specificity group. Relevant GenePaint probe IDs can be found in Additional data file 4. Arrows indicate the location of the pancreas (p).
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Figure 2: Specificity threshold accurately predicts spatial expression restriction. A plot of specificity (S) versus cumulative tag types represented shows the distribution of tags into tags with high (S > 0.1; top), medium (0.001 > S < 0.1, middle), and low (S < 0.001, bottom) S values. Representative in situ hybridization staining patterns from TS22 whole embryo saggital sections obtained from GenePaint are shown for each specificity group. Relevant GenePaint probe IDs can be found in Additional data file 4. Arrows indicate the location of the pancreas (p).

Mentions: To validate that these rankings accurately reflect the level of restriction of a gene's expression pattern, we compared our results with TS22 whole embryo in situ hybridization staining patterns using the GenePaint database [27,28]. We did this with sets of transcripts with high (S > 0.1, representing 5% of the genes), medium (0.001 > S < 0.1, representing 25% of the genes), and low (S < 0.001, representing 70% of the genes) S values. Figure 2 indicates that the calculated S values correlated extremely well with the relative restriction of the staining seen in the TS22 whole embryo sections. Genes with high S values showed staining specifically in the pancreas, genes with medium S values showed staining in the pancreas and a limited number of other tissues, and genes with low S values showed broad staining throughout the embryo. Additionally, our metric met biological expectation and genes with known pancreas specificity (Ins1 S = 27.9, Ins2 S = 62.7, Gcg S = 10.985, and so on) had very high S values, while housekeeping genes (Sdha S = 0.0006, HbS1L S = 0.0002, B2m S = 0.0005) had very low S values. Meanwhile, genes with restricted expression to other tissues either did not meet our count threshold (Plunc, Cldn13, Pomc, Prm2, and so on) [37] or had very low S values (Alb S = 0.0007). Together, these observations provided confidence in our specificity metric and we set a threshold of a minimum S of 0.002, as this value occurs roughly at the inflection point between medium and high S values in the plot of S value versus cumulative tag types represented (Figure 2). In sum, 2,536 (approximately 20%) tags met this threshold.


Identification of transcripts with enriched expression in the developing and adult pancreas.

Hoffman BG, Zavaglia B, Witzsche J, Ruiz de Algara T, Beach M, Hoodless PA, Jones SJ, Marra MA, Helgason CD - Genome Biol. (2008)

Specificity threshold accurately predicts spatial expression restriction. A plot of specificity (S) versus cumulative tag types represented shows the distribution of tags into tags with high (S > 0.1; top), medium (0.001 > S < 0.1, middle), and low (S < 0.001, bottom) S values. Representative in situ hybridization staining patterns from TS22 whole embryo saggital sections obtained from GenePaint are shown for each specificity group. Relevant GenePaint probe IDs can be found in Additional data file 4. Arrows indicate the location of the pancreas (p).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2481431&req=5

Figure 2: Specificity threshold accurately predicts spatial expression restriction. A plot of specificity (S) versus cumulative tag types represented shows the distribution of tags into tags with high (S > 0.1; top), medium (0.001 > S < 0.1, middle), and low (S < 0.001, bottom) S values. Representative in situ hybridization staining patterns from TS22 whole embryo saggital sections obtained from GenePaint are shown for each specificity group. Relevant GenePaint probe IDs can be found in Additional data file 4. Arrows indicate the location of the pancreas (p).
Mentions: To validate that these rankings accurately reflect the level of restriction of a gene's expression pattern, we compared our results with TS22 whole embryo in situ hybridization staining patterns using the GenePaint database [27,28]. We did this with sets of transcripts with high (S > 0.1, representing 5% of the genes), medium (0.001 > S < 0.1, representing 25% of the genes), and low (S < 0.001, representing 70% of the genes) S values. Figure 2 indicates that the calculated S values correlated extremely well with the relative restriction of the staining seen in the TS22 whole embryo sections. Genes with high S values showed staining specifically in the pancreas, genes with medium S values showed staining in the pancreas and a limited number of other tissues, and genes with low S values showed broad staining throughout the embryo. Additionally, our metric met biological expectation and genes with known pancreas specificity (Ins1 S = 27.9, Ins2 S = 62.7, Gcg S = 10.985, and so on) had very high S values, while housekeeping genes (Sdha S = 0.0006, HbS1L S = 0.0002, B2m S = 0.0005) had very low S values. Meanwhile, genes with restricted expression to other tissues either did not meet our count threshold (Plunc, Cldn13, Pomc, Prm2, and so on) [37] or had very low S values (Alb S = 0.0007). Together, these observations provided confidence in our specificity metric and we set a threshold of a minimum S of 0.002, as this value occurs roughly at the inflection point between medium and high S values in the plot of S value versus cumulative tag types represented (Figure 2). In sum, 2,536 (approximately 20%) tags met this threshold.

Bottom Line: Based on these results we identified a cascade of transcriptional regulators expressed in the endocrine pancreas lineage and, from this, we developed a predictive regulatory network describing beta-cell development.Taken together, this work provides evidence that the SAGE libraries generated here are a valuable resource for continuing to elucidate the molecular mechanisms regulating pancreas development.Furthermore, our studies provide a comprehensive analysis of pancreas development, and insights into the regulatory networks driving this process are revealed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Cancer Endocrinology, BC Cancer Research Center, West 10th Ave, Vancouver, BC V5Z 1L3, Canada. bhoffman@bccrc.ca

ABSTRACT

Background: Despite recent advances, the transcriptional hierarchy driving pancreas organogenesis remains largely unknown, in part due to the paucity of comprehensive analyses. To address this deficit we generated ten SAGE libraries from the developing murine pancreas spanning Theiler stages 17-26, making use of available Pdx1 enhanced green fluorescent protein (EGFP) and Neurog3 EGFP reporter strains, as well as tissue from adult islets and ducts.

Results: We used a specificity metric to identify 2,536 tags with pancreas-enriched expression compared to 195 other mouse SAGE libraries. We subsequently grouped co-expressed transcripts with differential expression during pancreas development using K-means clustering. We validated the clusters first using quantitative real time PCR and then by analyzing the Theiler stage 22 pancreas in situ hybridization staining patterns of over 600 of the identified genes using the GenePaint database. These were then categorized into one of the five expression domains within the developing pancreas. Based on these results we identified a cascade of transcriptional regulators expressed in the endocrine pancreas lineage and, from this, we developed a predictive regulatory network describing beta-cell development.

Conclusion: Taken together, this work provides evidence that the SAGE libraries generated here are a valuable resource for continuing to elucidate the molecular mechanisms regulating pancreas development. Furthermore, our studies provide a comprehensive analysis of pancreas development, and insights into the regulatory networks driving this process are revealed.

Show MeSH
Related in: MedlinePlus