It is standard practice, whenever a researcher finds a new gene, to search databases for genes that have a similar sequence. It is not standard practice, whenever a researcher finds a new gene, to search for genes tha...It is standard practice, whenever a researcher finds a new gene, to search databases for genes that have a similar sequence. It is not standard practice, whenever a researcher finds a new gene, to search for genes that have similar expression (co-expression). Failure to perform co-expression searches has lead to incorrect conclusions about the likely function of new genes, and has lead to wasted laboratory attempts to confirm functions incorrectly predicted. We present here the example of Glia Maturation Factor gamma (GMF-gamma). Despite its name, it has not been shown to participate in glia maturation. It is a gene of unknown function that is similar in sequence to GMF-beta. The sequence homology and chromosomal location led to an unsuccessful search for GMF-gamma mutations in glioma. We examined GMF-gamma expression in 1432 human cDNA libraries. Highest expression occurs in phagocytic, antigen-presenting and other hematopoietic cells. We found GMF-gamma mRNA in almost every tissue examined, with expression in nervous tissue no higher than in any other tissue. Our evidence indicates that GMF-gamma participates in phagocytosis in antigen presenting cells. Searches for genes with similar sequences should be supplemented with searches for genes with similar expression to avoid incorrect predictions.展开更多
Microarray analyses of gene expression are widely used, but reports of the same analyses by different groups give widely divergent results, and raise questions regarding reproducibility and reliability. We take as an ...Microarray analyses of gene expression are widely used, but reports of the same analyses by different groups give widely divergent results, and raise questions regarding reproducibility and reliability. We take as an example recent published reports on microarray experiments that were designed to identify retinoic acid responsive genes. These reports show substantial differences in their results. In this article, we review the methodology, results, and potential causes of differences in these applications of microarrays. Finally, we suggest practices to improve the reliability and reproducibility of microarray experiments.展开更多
文摘It is standard practice, whenever a researcher finds a new gene, to search databases for genes that have a similar sequence. It is not standard practice, whenever a researcher finds a new gene, to search for genes that have similar expression (co-expression). Failure to perform co-expression searches has lead to incorrect conclusions about the likely function of new genes, and has lead to wasted laboratory attempts to confirm functions incorrectly predicted. We present here the example of Glia Maturation Factor gamma (GMF-gamma). Despite its name, it has not been shown to participate in glia maturation. It is a gene of unknown function that is similar in sequence to GMF-beta. The sequence homology and chromosomal location led to an unsuccessful search for GMF-gamma mutations in glioma. We examined GMF-gamma expression in 1432 human cDNA libraries. Highest expression occurs in phagocytic, antigen-presenting and other hematopoietic cells. We found GMF-gamma mRNA in almost every tissue examined, with expression in nervous tissue no higher than in any other tissue. Our evidence indicates that GMF-gamma participates in phagocytosis in antigen presenting cells. Searches for genes with similar sequences should be supplemented with searches for genes with similar expression to avoid incorrect predictions.
文摘Microarray analyses of gene expression are widely used, but reports of the same analyses by different groups give widely divergent results, and raise questions regarding reproducibility and reliability. We take as an example recent published reports on microarray experiments that were designed to identify retinoic acid responsive genes. These reports show substantial differences in their results. In this article, we review the methodology, results, and potential causes of differences in these applications of microarrays. Finally, we suggest practices to improve the reliability and reproducibility of microarray experiments.
