Global Transcriptional Profiling in Porcine Mammary Glands from Late Pregnancy to Peak Lactation
College of Animal Science, South China Agricultural University, Guangzhou 510642, People's Republic of China. Omics: a journal of integrative biology
(Impact Factor: 2.36).
03/2012; 16(3):123-37. DOI: 10.1089/omi.2011.0116
Sow milk yield and quality is crucial for the survival and growth of piglets. To understand the molecular mechanisms of lactogenesis and lactation, mammary tissue samples were taken from six sows at -17(±2), 1 and 17(±2) days relative to parturition. Mammary tissues from two sows in the same stage were used to extract RNA, which were subsequently pooled in equal amounts. Nine pooled samples were hybridized to porcine Affymetrix GeneChips. Totally 1,524 genes were detected as significantly differentially expressed over the time course tested (p<0.01, q<0.01, fold change≥2 or ≤-2), including 709 upregulated and 575 downregulated genes identified at peak lactation compared to late pregnancy. Gene ontology analysis revealed that most of the upregulated genes were involved in transport, biosynthetic processes, and homeostasis, whereas most of the downregulated genes were involved in intracellular signaling cascades, cell cycle, and DNA replication. Furthermore, we identified 64 differentially expressed genes of the solute carrier families. Taken together, our microarray analysis provides insights into previously uncharacterized changes in transcriptome between late pregnancy and peak lactation in the porcine mammary gland. The solute carrier genes and other differentially expressed genes identified in this study will guide further characterization of their function to enhance milk yield and piglet growth.
Available from: Massimo Bionaz
- ". Data are for Holstein dairy cows , Saanen or Alpine goats , FVB mice  and Large white sows . Data were recovered and treated as reported in the legend for Figure 1. "
Milk Protein, Edited by Walter Hurley, 09/2012: chapter 11: pages 285-324; InTech., ISBN: 978-953-51-0743-9
Available from: Andrzej Goscinski
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ABSTRACT: Microarrays and more recently RNA sequencing has led to an increase in available gene expression data. How to manage and store this data is becoming a key issue. In response we have developed EXP-PAC, a web based software package for storage, management and analysis of gene expression and sequence data. Unique to this package is SQL based querying of gene expression data sets, distributed normalization of raw gene expression data and analysis of gene expression data across experiments and species. This package has been populated with lactation data in the international milk genomic consortium web portal (http://milkgenomics.org/). Source code is also available which can be hosted on a Windows, Linux or Mac APACHE server connected to a private or public network (http://mamsap.it.deakin.edu.au/~pcc/Release/EXP_PAC.html).
Genomics 05/2012; 100(1):8-13. DOI:10.1016/j.ygeno.2012.05.007 · 2.28 Impact Factor
Available from: Juan J. Loor
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ABSTRACT: We used the newly-developed Dynamic Impact Approach (DIA) and gene network analysis to study the sow mammary transcriptome at 80, 100, and 110 days of pregnancy. A swine oligoarray with 13,290 inserts was used for transcriptome profiling. An ANOVA with false discovery rate (FDR < 0.15) correction resulted in 1,409 genes with a significant time effect across time comparisons. The DIA uncovered that Fatty acid biosynthesis, Interleukin-4 receptor binding, Galactose metabolism, and mTOR signaling were among the most-impacted pathways. IL-4 receptor binding, ABC transporters, cytokine-cytokine receptor interaction, and Jak-STAT signaling were markedly activated at 110 days compared with 80 and 100 days. Epigenetic and transcription factor regulatory mechanisms appear important in coordinating the final stages of mammary development during pregnancy. Network analysis revealed a crucial role for TP53, ARNT2, E2F4, and PPARG. The bioinformatics analyses revealed a number of pathways and functions that perform an irreplaceable role during late gestation to farrowing.
Bioinformatics and biology insights 07/2013; 7:193-216. DOI:10.4137/BBI.S12205
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