Further defining housekeeping , or “ maintenance , ” genes

HOUSEKEEPING GENES are constitutively expressed to maintain cellular function. As such, they are presumed to produce the minimally essential transcripts necessary for normal cellular physiology. With the advent of microarray technology, it has recently become possible to identify at least the “starter set” of housekeeping genes, as exemplified by the work of Velculescu et al. (2), as well as by Warrington et al. (3) in a paper published in this journal previously. In that paper, Warrington et al. examined the expression of 7,000 full-length genes in 11 different human tissues, both adult and fetal, to determine the suite of transcripts that were commonly expressed throughout human development and in different tissues. They identified 535 transcripts via microarray hybridization as likely candidates for housekeeping genes, or, as the authors proposed, “maintenance” genes. Among the findings of this previous study was the fact that there are constitutively expressed genes particular to certain tissues, as well as sets of genes expressed only in the fetus or only in the adult. Cluster analysis was employed to identify groups of transcripts expressed in the seven adult tissues studied (695) and the four fetal tissues tested (767). The analytical technology was able to detect fluctuations in expression between fetal and adult samples, indicating that such genes, while permanently activated, are perhaps not required at the same level throughout development. Forty-seven transcripts commonly expressed between fetal and adult samples did not vary in expression level and might serve as useful internal controls for other expression profiling experiments. In this online release of Physiological Genomics, Hsiao et al. (Ref. 1; see page 97 in this release) extend the findings of Warrington et al. (3) to focus on the tissue-selective gene clusters that appear characteristic of particular organs. Their data has been logged into a database (HuGE Index: Human Gene Expression Index, http://www.hugeindex.org) which is intended to serve as a benchmark compendium of expression profiles of various human tissue to enable researchers to make comparisons of normal states and disease. Hsiao et al. (1) reverse-transcribed cDNAs from RNA extracted from 19 different tissue types, then hybridized cRNAs made from the resulting transcript pool to Affymetrix GeneChip HuGeneFL oligonucleotide human genome microarrays. They identified any gene expressed in all 19 tissues as a housekeeping/maintenance gene; then, they identified tissue-selective genes using principal component analysis. The 451 maintenance genes encode proteins that mediate cellular functions such as transcription, translation, and signaling. Of these genes, 358 were common to the previous study. As would be expected, differences in expression levels of the housekeeping genes from one tissue to another could be used to separate and cluster different tissues successfully according to tissue type (certainly, if these tissues can be visually distinguished from each other, than there must exist genes that accurately separate the tissues as well). Further statistical analysis revealed groups of tissueselective genes predominantly expressed in a single tissue type; for example, among the muscle-selective genes were those associated with contraction, such as tropomyosin, or with glucose metabolism, such as lactate dehydrogenase. Additionally, genes were identified whose expression levels varied the most significantly between patient samples. For example, in lung, integrin2 was among genes with a coefficient of variation greater than two standard deviations from the mean. The authors (1) noted that variation in integrin2 is involved in a predisposition to recurrent bacterial lung infections. Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org). Address for reprint requests and other correspondence: A. Butte, Children’s Hospital, Boston, MA 02115 (E-mail: atul_butte@ harvard.edu). Physiol Genomics 7: 95–96, 2001.