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Updated: May 30, 2026

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform
Published on: January 30, 2017
Combining resources to obtain a comprehensive survey of the bovine embryo transcriptome through deep sequencing and
Claude Robert1, Julie Nieminen, Isabelle Dufort
1Laboratory of Functional Genomics of Early Embryonic Development, Université Laval, Québec, Canada. claude.robert@fsaa.ulaval.ca
Abstract:
While most assisted reproductive technologies (ART) are considered routine for the reproduction of species of economical importance, such as the bovine, the impact of these manipulations on the developing embryo remains largely unknown. In an effort to obtain a comprehensive survey of the bovine embryo transcriptome and how it is modified by ART, resources were combined to design an embryo-specific microarray. Close to one million high-quality reads were produced from subtracted bovine embryo libraries using Roche 454 Titanium deep sequencing technology, which enabled the creation of an augmented bovine genome catalog. This catalog was enriched with bovine embryo transcripts, and included newly discovered indel type and 3'UTR variants. Using this augmented bovine genome catalog, the EmbryoGENE Bovine Microarray was designed and is composed of a total of 42,242 probes, including 21,139 known reference genes; 9,322 probes for novel transcribed regions (NTRs); 3,677 alternatively spliced exons; 3,353 3'-tiling probes; and 3,723 controls. A suite of bioinformatics tools was also developed to facilitate microrarray data analysis and database creation; it includes a quality control module, a Laboratory Information Management System (LIMS) and microarray analysis software. Results obtained during this study have already led to the identification of differentially expressed blastocyst targets, NTRs, splice variants of the indel type, and 3'UTR variants. We were able to confirm microarray results by real-time PCR, indicating that the EmbryoGENE bovine microarray has the power to detect physiologically relevant changes in gene expression.
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