Building comparative gene expression databases for the mouse preimplantation embryo using a pipeline approach to UniGene.

To understand early mammalian development there is a need to compare profiles of gene expression from different stages of the preimplantation mouse embryo. We describe here a method that uses gene expression data held in the UniGene database of the National Institutes of Health (NIH). The full mouse UniGene database (build #151) contains 43,104 gene clusters generated from approximately 4.1 million sequences. The Expressed Sequence Tags (EST) used to build UniGene are derived from cDNA libraries that are archived separately in the database of Expressed Sequence Tags (dbEST) database, with their own catalogue numbers. The mouse dbEST database contains 32 non-normalized dbEST libraries constructed from preimplantation stages (unfertilized oocyte, fertilized oocyte, 2-, 4-, 8- and 16-cell embryo and blastocyst). These libraries contain 219,852 EST sequences mapping to 15,731 UniGene clusters. We have developed a computational pipeline approach that imports and aggregates inventories of gene expression contained in these dbEST libraries. It uses these data to build an annotated web-based database of preimplantation gene expression with an in-built capacity for comparison of expression profiles. Comparison of gene expression profiles obtained for each developmental stage show statistically significant changes in gene expression during preimplantation development. These in silico-generated profiles were validated using RT-PCR.

Purification of granulosa cells from human ovarian follicular fluid using granulosa cell aggregates.

Human follicular fluid can provide a source of human granulosa cells for scientific study. However, removing potentially contaminating cells, such as white and red blood cells, is important for molecular and in vitro studies. We have developed a purification technique for human granulosa cells based on the selection of cellular aggregates. Human granulosa cells from 21 IVF patients were collected. A 50% Percoll gradient was used to remove red blood cells, and granulosa cell aggregates were collected, washed and processed for histology, electron microscopy, flow cytometry analysis, cell culture and RNA extraction. Granulosa cell aggregates were found to be homogeneous and free of white blood cells after histological and electron microscopic analysis. White blood cell contamination, measured by flow cytometry, was found to be between 2 and 4%. Polymerase chain reaction analysis revealed expression of known human granulosa cell genes and a white blood cell marker. Human granulosa cells grown in vitro showed flattened fibroblast-like morphology with lipid droplets consistent with previous reports. Cultured cells expressed the FSH receptor. Selection of human granulosa cell aggregates following centrifugation through a Percoll gradient provides an efficient method of selecting granulosa cells, suitable for both molecular and in vitro studies.

Using expressed sequence tag databases to identify ovarian genes of interest.

GenBank contains 4879 expressed sequence tags (EST) derived from four non-normalized human ovarian cDNA libraries. Of these EST, 2646 are contributors to UniGene clusters and have UniGene numbers. The EST map to 1206 distinct UniGenes. A gene expression profile was established for the human ovary by identifying the abundance of each UniGene cluster and its corresponding annotation. The most highly expressed transcripts were for proteins associated with protein synthesis (ribosomal proteins, elongation factors, thymosins, etc.). However, there are also transcripts for genes of unknown function that are ovary-specific. This ovarian gene expression profile provides useful data for the design of DNA microarrays targeted at ovarian function and highlights novel sequences that warrant further investigation.

A set of 1542 mouse blastocyst and pre-blastocyst genes with well-matched human homologues.

GenBank contains 57,151 Expressed Sequence Tags (EST) derived from 11 preimplantation embryo mouse cDNA libraries ranging from the 2-cell embryo to the blastocyst. EST were matched to UniGene clusters to identify a composite set of 11,291 UniGenes. These 11,291 UniGenes were screened using HomoloGene to identify a subset of 3467 mouse UniGenes with matches in at least two other species, one of which was human. Of the 3467 matches, 1542 are for named human proteins. Four of the 11 preimplantation embryo libraries were for blastocysts and contain 22,307 EST. These blastocyst EST generate 5762 UniGenes, of which 2246 have matches in at least two other species. Of the 2246 matches, 1170 are for named human proteins. Comparison of the expression profile of the blastocyst set with a similarly derived set from the mouse oocyte identified a number of transcripts that are significantly up-regulated during preimplantation development. The set of named blastocyst and pre-blastocyst genes complements the similar set published recently for the mouse oocyte. They provide a database for identifying signalling pathways that may play a role in determining cell fate in preimplantation embryo development.

Gene expression profiling of human GV oocytes: an analysis of a profile obtained by Serial Analysis of Gene Expression (SAGE).

A gene expression profile of the human GV oocyte has recently been established by Serial Analysis of Gene Expression (SAGE). A significant number of the genes identified in this profile had not previously been associated with mammalian oocytes. We sought to confirm gene matches by RT-PCR amplification of candidate transcripts using mouse eggs. Attention focused on receptors, proteins involved in apoptosis, and cytoskeletal proteins. Two receptors found in the human catalogue, CCR6 and PAR3, were not found in mouse eggs, whereas myosin light chain, LLGL, beta-actin, 5HT receptor, bad, bak, DFF45, and Caspase homologue (cash) were. Individual SAGEtags can match more than one gene and, in some cases, more than ten. Examination of transcript sequences that generate multiple gene assignments identified a common denominator of short interspersed elements or Alu sequences. For reasons which are, as yet, unclear, the human GV oocyte SAGE catalogue contains relatively high abundances of SAGEtags in Alu sequences. This may reflect normal expression of Alu-containing genes in eggs or upregulated expression of Alu elements following stress. The degeneracy of gene matches in SAGE generated by Alu sequences makes independent confirmation of candidate genes essential.