Literature DB >> 15644424

Assessing natural variations in gene expression in humans by comparing with monozygotic twins using microarrays.

Anu Sharma1, Vineet K Sharma, Shirley Horn-Saban, Doron Lancet, Srinivasan Ramachandran, Samir K Brahmachari.   

Abstract

Quantitative variation in gene expression in humans is the outcome of various factors, including differences in genetic background, gender, age, and environment. However, the extent of the influence of these factors on gene expression is not clear. We attempted to address this issue by carrying out gene expression profiling in blood leukocytes with 13 individuals (including 5 pairs of monozygotic twins) on 10,000 genes using HG-U95Av2 oligonucleotide microarrays. The proportion of differentially expressed genes between monozygotic twins was low (up to 1.76%). Most of the variations belonged to the least variable category. These genes, exhibiting "random variations," did not show clear preference to any functional class, although "signaling and communication" and "immune and related functions" generally topped the list. The extent of variation in gene expression increased in comparisons between unrelated individuals (up to 14.13%). Most of the genes (89%) exhibiting random variations in twins also varied in expression in unrelated individuals. As with twins, signaling and communication topped the list, and substantial variations were observed in all three categories: least variable, moderately variable, and most variable. An important outcome of this study was that the housekeeping genes were nearly insensitive to random variations but appeared to be more susceptible to genetic differences. However, the highly expressed housekeeping genes exhibited low variation and appeared to be insensitive to all known factors. Gene expression profiling in monozygotic twins can provide useful data for the assessment of natural variation in gene expression in humans.

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Year:  2005        PMID: 15644424     DOI: 10.1152/physiolgenomics.00228.2003

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


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