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INTRODUCTION |
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Our featured minireview ("Genomics Versus Orphan Nuclear ReceptorsA Half-Time Report," by Willson and Moore, pp. 11351144) addresses the task associated with deciphering the physiological roles of orphan nuclear receptors. The authors describe how the application of chemical, structural, and functional genomics has led to the identification of several orphan receptors with pharmacological promise, and speculate on what can be expected in the future.
The ten articles in the special section of this issue describe several types of genomic approaches, ranging from gene expression arrays to in silico analysis and data mining. Each article addresses the mechanism of hormone action, and some include analysis of both normal and disease states. For example, Yuen et al., pp. 11451153, use custom DNA microarrays to examine the dose-response relationship between GnRH and the transcriptional output of target genes, including an analysis of the kinetics of their response. In the article by Varani et al., pp. 11541167, DNA microarrays are used in conjunction with gene deletion studies to uncover the functional significance of two new genes regulated by growth differentiation factor-9 (GDF-9). Yan et al., pp. 11681184, employ in silico subtraction and genomic database mining to identify a new battery of conserved genes with germ cell-specific expression.
Chodosh and colleagues, pp. 11851203, describe a general approach that utilizes automated, unbiased identification of biologically relevant patterns of gene expression during development of the murine mammary gland upon examination of gene expression profiling data. Two other manuscripts focus on genes expressed in breast cancer cell lines. Wan and Nordeen, pp. 12041214, interrogate a human breast cancer cell line through global gene expression profiling and report on the differential effects of progesterone and glucocorticoids. Lobenhofer and colleagues, pp. 12151229, use custom arrays specific for genes implicated in cell-cycle progression and DNA replication to examine the effects of estrogen in another hormone-responsive breast cancer cell line.
Lin et al., pp. 12431256, also define cancer transcriptomes. These investigators use DNA microarrays to catalog target genes of a vitamin D3 analog that exerts a protective effect in a human squamous carcinoma cell line. Owens et al., pp. 12301242, use global gene expression profiling to identify transcriptomes associated with granulosa cell tumorigenesis in a transgenic mouse model that is dependent on genetic background. Murine models are also used by Flores-Morales et al., pp. 12571268, to identify new T3 target genes specific for thyroid receptor-ß in liver using custom DNA microarrays. Finally, Podvinec et al., pp. 12691279, report on the development of an in silico approach (NUBIScan) based on a new algorithm that allows prediction of DNA recognition sites for nuclear receptors in the regulatory region of genes.
It is clear that the application of genomic strategies by molecular endocrinologists is on the rise, and we are enthusiastic about the impact this change will have on our field. At the same time, the massive amount of primary data associated with genomic approaches poses something of a publishing dilemma. While scientific journals are constrained by page limitations, we believe it is essential to make the primary data available to the reader to allow for independent review and assessment, and to provide an invaluable basis of comparison for others who conduct similar genomic studies.
In this regard, the editors of Molecular Endocrinology are working with the Publications Committee to establish a set of working guidelines for handling such primary data. Although the details of the guidelines are not yet finalized, we can say that the primary data derived from genomic studies will now be published as supplemental data in the online journal; this includes several papers in this issue. Although the print versions of the manuscripts do not include the supplemental data, they direct the reader to the data via the online journals web site.
Yet another consideration is that standard formats for the presentation of primary genomic data remain unestablished. This can be illustrated through gene expression profiling data that is typically platform dependent. We suggest the simple solution of presenting the raw data in a tab-delimited format. When presenting DNA microarray data, it is also important to clearly identify the platform (e.g., Affymetrix Murine Genome U74v2 Set), to thoroughly describe the filtering criteria used to evaluate the raw data, and to provide complete references for the statistical methods used to analyze the data. We will be publishing more extensive guidelines in the near future.
In the meanwhile, the editors of Molecular Endocrinology remain excited about the genomic future and its impact on our field. To this end, we encourage submission of genomic-based manuscripts that provide new mechanistic insights into hormone action.
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