Gene expression variation and expression quantitative trait mapping of human chromosome 21 genes

Abstract

Inter-individual differences in gene expression are likely to account for an important fraction of phenotypic differences, including susceptibility to common disorders. Recent studies have shown extensive variation in gene expression levels in humans and other organisms, and that a fraction of this variation is under genetic control. We investigated the patterns of gene expression variation in a 25 Mb region of human chromosome 21, which has been associated with many Down syndrome (DS) phenotypes. Taqman real-time PCR was used to measure expression variation of 41 genes in lymphoblastoid cells of 40 unrelated individuals. For 25 genes found to be differentially expressed, additional analysis was performed in 10 CEPH families to determine heritabilities and map loci harboring regulatory variation. Seventy-six percent of the differentially expressed genes had significant heritabilities, and genomewide linkage analysis led to the identification of significant eQTLs for nine genes. Most eQTLs were in trans, with the best result (P=7.46 x 10(-8)) obtained for TMEM1 on chromosome 12q24.33. A cis-eQTL identified for CCT8 was validated by performing an association study in 60 individuals from the HapMap project. SNP rs965951 located within CCT8 was found to be significantly associated with its expression levels (P=2.5 x 10(-5)) confirming cis-regulatory variation. The results of our study provide a representative view of expression variation of chromosome 21 genes, identify loci involved in their regulation and suggest that genes, for which expression differences are significantly larger than 1.5-fold in control samples, are unlikely to be involved in DS-phenotypes present in all affected individuals.

Identification of cis- and trans-regulatory variation modulating microRNA expression levels in human fibroblasts

“…Earlier studies have shown that common genetic variants contribute significantly to the individual differences in proteincoding gene expression variation (Cheung et al 2003(Cheung et al , 2005Morley et al 2004;Deutsch et al 2005;Stranger et al 2005Stranger et al , 2007Spielman et al 2007;Storey et al 2007) and transcript isoform variation (Hull et al 2007;Kwan et al 2007Kwan et al , 2008Zhang et al 2009). Our study adds a level of complexity to cellular gene expression regulation by revealing that cis-and trans-eQTLs can affect the expression of miRNAs that are themselves regulatory molecules.…”

“…Recent genetic analyses have demonstrated that transcription levels of protein-coding genes behave as heritable quantitative traits and display significant associations with genetic variants, including single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) (Morley et al 2004;Cheung et al 2005;Deutsch et al 2005;Stranger et al 2007;Dermitzakis 2008).…”

The cholesterol transporter ABCG1 modulates the subcellular distribution and proteolytic processing of β-amyloid precursor protein

“…Immunohistochemical analysis of postnatal DS brain suggests that the neuronal staining intensity of APP protein increases during aging (75), although a recent study found no association between total APP levels and age (69). Interestingly, a survey of 41 genes on chromosome 21 demonstrated that APP exhibited the highest degree of interindividual variability of expression (77), suggesting that individual differences in APP expression levels may also partly account for the varying ability to detect APP overexpression in different DS patients. In our cohort, we failed to observe significant APP overexpression in DS cortex when evaluated by quantitative RT-PCR, Western blot, or ELISA.…”

Transcriptional and post-transcriptional profile of human chromosome 21

“…To evaluate the quality of the polysome fractionation, we performed real-time quantitative PCR (qPCR) as described (Deutsch et al 2005). Among 11 selected target genes, there were three housekeeping genes (EEF1A1, UBE2D2, AGPAT1), four genes with structured 59 UTRs (BACE1, HTT [HD], EIF4G2, HSPA5) and four noncoding genes (MIRHG2, MALAT1, BCYRN1, MEG3).…”