The transcriptome of human oocytes.

The identification of genes and deduced pathways from the mature human oocyte can help us better understand oogenesis, folliculogenesis, fertilization, and embryonic development. Human metaphase II oocytes were used within minutes after removal from the ovary, and its transcriptome was compared with a reference sample consisting of a mixture of total RNA from 10 different normal human tissues not including the ovary. RNA amplification was performed by using a unique protocol. Affymetrix Human Genome U133 Plus 2.0 GeneChip arrays were used for hybridizations. Compared with reference samples, there were 5,331 transcripts significantly up-regulated and 7,074 transcripts significantly down-regulated in the oocyte. Of the oocyte up-regulated probe sets, 1,430 have unknown function. A core group of 66 transcripts was identified by intersecting significantly up-regulated genes of the human oocyte with those from the mouse oocyte and from human and mouse embryonic stem cells. GeneChip array results were validated using RT-PCR in a selected set of oocyte-specific genes. Within the up-regulated probe sets, the top overrepresented categories were related to RNA and protein metabolism, followed by DNA metabolism and chromatin modification. This report provides a comprehensive expression baseline of genes expressed in in vivo matured human oocytes. Further understanding of the biological role of these genes may expand our knowledge on meiotic cell cycle, fertilization, chromatin remodeling, lineage commitment, pluripotency, tissue regeneration, and morphogenesis.

Comparative genomics of two closely related unicellular thermo-acidophilic red algae, Galdieria sulphuraria and Cyanidioschyzon merolae, reveals the molecular basis of the metabolic flexibility of Galdieria sulphuraria and significant differences in carbohydrate metabolism of both algae.

Unicellular algae serve as models for the study and discovery of metabolic pathways, for the functional dissection of cell biological processes such as organellar division and cell motility, and for the identification of novel genes and gene functions. The recent completion of several algal genome sequences and expressed sequence tag collections and the establishment of nuclear and organellar transformation methods has opened the way for functional genomics approaches using algal model systems. The thermo-acidophilic unicellular red alga Galdieria sulphuraria represents a particularly interesting species for a genomics approach owing to its extraordinary metabolic versatility such as heterotrophic and mixotrophic growth on more than 50 different carbon sources and its adaptation to hot acidic environments. However, the ab initio prediction of genes required for unknown metabolic pathways from genome sequences is not trivial. A compelling strategy for gene identification is the comparison of similarly sized genomes of related organisms with different physiologies. Using this approach, candidate genes were identified that are critical to the metabolic versatility of Galdieria. Expressed sequence tags and high-throughput genomic sequence reads covering >70% of the G. sulphuraria genome were compared to the genome of the unicellular, obligate photoautotrophic red alga Cyanidioschyzon merolae. More than 30% of the Galdieria sequences did not relate to any of the Cyanidioschyzon genes. A closer inspection of these sequences revealed a large number of membrane transporters and enzymes of carbohydrate metabolism that are unique to Galdieria. Based on these data, it is proposed that genes involved in the uptake of reduced carbon compounds and enzymes involved in their metabolism are crucial to the metabolic flexibility of G. sulphuraria.

Bovine mammary gene expression profiling using a cDNA microarray enhanced for mammary-specific transcripts.

A cDNA microarray resource enhanced for transcripts specific to the bovine mammary gland (BMAM) has been developed and used in pilot studies to examine gene expression profiles in the mammary gland. One goal driving development of this resource was to shed some light on the pathways and mechanisms specifically related to bovine mammary gland growth and development. To accomplish this, gene expression patterns from bovine adipose, liver, adrenal, lymph, spleen, thymus, gut, and developing mammary tissue were compared using the BMAM microarray. We have thus identified a putative set of 16 genes being preferentially expressed in developing mammary gland. Another of our long-term goals is to elucidate the genes and pathways associated with bovine lactation and involution and to use these as a model for human mammary gland development as it relates to human breast cancer risks. To begin this process, we conducted a pilot study, comparing gene expression profiles of lactating bovine mammary tissue against nonlactating tissue on the BMAM microarray. Our results have yielded many novel and interesting genes exhibiting differential expression in lactating mammary tissue, including oncogenes (VAV3, C-myc), mediators of apoptosis (Caspase 8), and cell cycle regulators (LASP1).

Development and testing of a high-density cDNA microarray resource for cattle.

A cDNA microarray resource has been developed with the goal of providing integrated functional genomics resources for cattle. The National Bovine Functional Genomics Consortium's (NBFGC) expressed sequence tag (EST) collection was established in 2001 to develop resources for functional genomics research. The NBFGC EST collection and microarray contains 18,263 unique transcripts, derived from many different tissue types and various physiologically important states within these tissues. The NBFGC microarray has been tested for false-positive rates using self-self hybridizations and was shown to yield robust results in test microarray experiments. A web-accessible database has been established to provide pertinent data related to NBFGC clones, including sequence data, BLAST results, and ontology information. The NBFGC microarray represents the largest cDNA microarray for a livestock species prepared to date and should prove to be a valuable tool in studying genome-wide gene expression in cattle.

Analysis of expressed sequence tags from Gibberella zeae (anamorph Fusarium graminearum).

Gibberella zeae is a broad host range pathogen that infects many crop plants, including wheat and barley, and causes head blight and rot diseases throughout the world. To better understand fungal development and pathogenicity, we have generated 7996 ESTs from three cDNA libraries. Two libraries were generated from carbon-(C-) and nitrogen- (N-) starved mycelia and one library was generated from cultures of maturing perithecia (P). In other fungal pathogens, starvation conditions have been shown to act as cues to induce infection-related gene expression. To assign putative function to cDNAs, sequences were initially assembled using StackPack. The estimated total number of genes identified from the three EST databases was 2110: 1088 contigs and 1022 singleton sequences. These 2110 sequences were compared to a yeast protein sequence reference set and to the GenBank nonredundant database using BLASTX. Based on presumptive gene function identified by this process, we found that the two starved cultures had similar, but not identical, patterns of gene expression, whereas the developmental cultures were distinct in their pattern of expression. Of the three libraries, the perithecium library had the greatest percentage (46%) of ESTS falling into the "unclassified" category. Homologues of some known fungal virulence or pathogenicity factors were found primarily in the N- and C-libraries. Comparisons also were made with ESTs from the related fungi, Neurospora crassa and Magnaporthe grisea and the genomic sequence of N. crassa.

Gestational and lactational exposure of male mice to diethylstilbestrol causes long-term effects on the testis, sperm fertilizing ability in vitro, and testicular gene expression.

The objective of the study was to determine the long-term effects of gestational and lactational exposure to diethylstilbestrol (DES; 0, 0.1, 1, and 10 microg/kg maternal body weight) on mouse testicular growth, epididymal sperm count, in vitro fertilizing ability, and testicular gene expression using cDNA microarrays and real-time PCR in mice on postnatal day (PND) 21, 105, and 315. In the high dose group there was a persistent decrease in the number of Sertoli cells, and sperm count was decreased on PND315 (P < 0.05). Sperm motion was unaffected; however, the in vitro fertilizing ability of epididymal sperm was decreased in the high dose group on both PND105 (P < 0.001) and PND315 (P < 0.05). Early and latent alterations in the expression of genes involved in estrogen signaling (estrogen receptor alpha), steroidogenesis (steroidogenic factor 1, 17alpha-hydroxylase/C17,20-lyase, P450 side chain cleavage, steroidogenic acute regulatory protein, and scavenger receptor class B1), lysosomal function (LGP85 and prosaposin), and regulation of testicular development (testicular receptor 2, inhibin/activin beta C, and Hoxa10) were confirmed by real-time PCR. The results demonstrate that early exposure to DES causes long-term adverse effects on testicular development and sperm function, and these effects are associated with changes in testicular gene expression, even long after the cessation of DES exposure.

In silico approaches to mechanistic and predictive toxicology: an introduction to bioinformatics for toxicologists.

Bioinformatics, or in silico biology, is a rapidly growing field that encompasses the theory and application of computational approaches to model, predict, and explain biological function at the molecular level. This information rich field requires new skills and new understanding of genome-scale studies in order to take advantage of the rapidly increasing amount of sequence, expression, and structure information in public and private databases. Toxicologists are poised to take advantage of the large public databases in an effort to decipher the molecular basis of toxicity. With the advent of high-throughput sequencing and computational methodologies, expressed sequences can be rapidly detected and quantitated in target tissues by database searching. Novel genes can also be isolated in silico, while their function can be predicted and characterized by virtue of sequence homology to other known proteins. Genomic DNA sequence data can be exploited to predict target genes and their modes of regulation, as well as identify susceptible genotypes based on single nucleotide polymorphism data. In addition, highly parallel gene expression profiling technologies will allow toxicologists to mine large databases of gene expression data to discover molecular biomarkers and other diagnostic and prognostic genes or expression profiles. This review serves to introduce to toxicologists the concepts of in silico biology most relevant to mechanistic and predictive toxicology, while highlighting the applicability of in silico methods using select examples.