Gene Expression Profiles of Pregnant and Non-pregnant Whole Blood
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE14771 | GEO | 2009/06/10
SECONDARY ACCESSION(S): PRJNA112155
REPOSITORIES: GEO
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Project description:Comparison of gene expression profiles in whole blood collected from pregnant and non-pregnant females. Peripheral whole blood samples from 5 third trimester pregnant females and 5 non-pregnant females were collected. The gene expression profiles of the two groups were compared using Affymetrix HG-U133A and HG-U133B array sets.
2009-06-10 | E-GEOD-14771 | biostudies-arrayexpress
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Project description:Purpose: characterize the uterine transcriptome profiles of pregnant (P) versus non-pregnant (NP) cows during early pregnancy and attempted to define a potential set of marker genes that can be valuable for predicting pregnancy outcome. Methods: beef cows were synchronized and artificially inseminated at detected estrus. Six days after AI, jugular blood samples and a biopsy from the uterine horn contralateral to the ovary containing the corpus luteum were collected. Based on pregnancy outcome on day 30, samples were retrospectively allocated to the following groups: Pregnant and Non-Pregnant. Both groups had similar plasma progesterone concentrations on D6. Uterine biopsies were submitted to RNA-Seq analysis in a Illumina HiScanSQ platform. Results: The 272,685,768 million filtered reads were mapped to the Bos taurus reference genome and 14,654 genes were analyzed for differential expression between groups. Transcriptome data showed that 216 genes are differently expressed when comparing NP versus P uterine tissue (Padj≤0.1). More specifically, 36 genes were up-regulated in P cows and 180 are up-regulated in NP cows. Conclusions: this study characterized a unique set of genes, expressed in the uterus on 6 days after insemination, that indicate a receptive state leading to pregnancy success. Furthermore, expression of such genes can be used as potential markers to efficiently predict pregnancy success. endometrial mRNA profiles of pregnant and non-pregnant cows were generated by deep sequencing using Illumina HiScanSQ platform BioProject PRJNA268916 SRA Study SRP05036
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