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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Related Experiment Video

Updated: Jul 20, 2026

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform
09:04

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform

Published on: January 30, 2017

Identification of candidate maternal-effect genes through comparison of multiple microarray data sets.

Jesse Mager1, Richard M Schultz, Brian P Brunk

  • 1Department of Cell and Developmental Biology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, USA.

Mammalian Genome : Official Journal of the International Mammalian Genome Society
|September 12, 2006
PubMed
Summary

Comparing gene expression data from different microarray platforms is crucial for reliable results. This study identified 51 candidate maternal-effect genes in mouse preimplantation development by analyzing existing transcriptome data.

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Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice

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Related Experiment Videos

Last Updated: Jul 20, 2026

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform
09:04

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform

Published on: January 30, 2017

Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice
07:07

Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice

Published on: January 7, 2019

Area of Science:

  • Developmental Biology
  • Genomics
  • Molecular Biology

Background:

  • Microarray hybridization is a standard for global gene expression analysis, generating vast datasets.
  • Variability in microarray results can stem from platform differences, tissue collection, and laboratory protocols.
  • Reproducibility across platforms is critical for accurate interpretation of gene expression data.

Purpose of the Study:

  • To identify genes with critical maternal mRNA pools during mouse preimplantation development.
  • To assess the consistency of gene expression patterns across different microarray platforms and laboratories.
  • To discover candidate maternal-effect genes using a data mining approach.

Main Methods:

  • Compared published microarray data from three independent studies of mouse preimplantation embryo transcriptomes.
  • Utilized different laboratories and microarray platforms for each study.
  • Searched for consistent gene expression patterns across developmental windows (oocyte + 1-cell, 2- to 8-cell, blastocyst).
  • Validated candidate genes using Reverse Transcription Polymerase Chain Reaction (RT-PCR).

Main Results:

  • Agreement on gene presence/absence varied between 52% and 60% across single developmental windows.
  • Approximately 33% agreement in expression patterns across three developmental windows, often with genes consistently present or absent.
  • Identified 51 candidate genes predicted to have maternal RNA only.
  • RT-PCR validation confirmed the expression pattern for 37 (72%) of these candidates.

Conclusions:

  • Data mining across multiple microarray experiments enhances the accuracy of candidate gene expression patterns.
  • This approach successfully identified candidate maternal-effect genes critical for early development.
  • Cross-platform data analysis is a valuable strategy for discovering and validating genes.