No abstract

A major goal in human genetics is to understand the role of common genetic variants in susceptibility to common diseases. This will require characterizing the nature of gene variation in human populations, assembling an extensive catalogue of single-nucleotide polymorphisms (SNPs) in candidate genes and performing association studies for particular diseases. At present, our knowledge of human gene variation remains rudimentary. Here we describe a systematic survey of SNPs in the coding regions of human genes. We identified SNPs in 106 genes relevant to cardiovascular disease, endocrinology and neuropsychiatry by screening an average of 114 independent alleles using 2 independent screening methods. To ensure high accuracy, all reported SNPs were confirmed by DNA sequencing. We identified 560 SNPs, including 392 coding-region SNPs (cSNPs) divided roughly equally between those causing synonymous and non-synonymous changes. We observed different rates of polymorphism among classes of sites within genes (non-coding, degenerate and non-degenerate) as well as between genes. The cSNPs most likely to influence disease, those that alter the amino acid sequence of the encoded protein, are found at a lower rate and with lower allele frequencies than silent substitutions. This likely reflects selection acting against deleterious alleles during human evolution. The lower allele frequency of missense cSNPs has implications for the compilation of a comprehensive catalogue, as well as for the subsequent application to disease association.

The synthesis of fatty acids and cholesterol, the building blocks of membranes, is regulated by three membrane-bound transcription factors: sterol regulatory element-binding proteins (SREBP)-1a, -1c, and -2. Their function in liver has been characterized in transgenic mice that overexpress each SREBP isoform and in mice that lack all three nuclear SREBPs as a result of gene knockout of SREBP cleavage-activating protein (SCAP), a protein required for nuclear localization of SREBPs. Here, we use oligonucleotide arrays hybridized with RNA from livers of three lines of mice (transgenic for SREBP-1a, transgenic for SREBP-2, and knockout for SCAP) to identify genes that are likely to be direct targets of SREBPs in liver. A total of 1,003 genes showed statistically significant increased expression in livers of transgenic SREBP-1a mice, 505 increased in livers of transgenic SREBP-2 mice, and 343 showed decreased expression in Scap ؊͞؊ livers. A subset of 33 genes met the stringent combinatorial criteria of induction in both SREBP transgenics and decreased expression in SCAP-deficient mice. Of these 33 genes, 13 were previously identified as direct targets of SREBP action. Of the remaining 20 genes, 13 encode enzymes or carrier proteins involved in cholesterol metabolism, 3 participate in fatty acid metabolism, and 4 have no known connection to lipid metabolism. Through application of stringent combinatorial criteria, the transgenic͞knockout approach allows identification of genes whose activities are likely to be controlled directly by one family of transcription factors, in this case the SREBPs.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Gene expression levels of about 7,000 genes were measured in 11 different human adult and fetal tissues using high-density oligonucleotide arrays to identify genes involved in cellular maintenance. The tissues share a set of 535 transcripts that are turned on early in fetal development and stay on throughout adulthood. Because our goal was to identify genes that are involved in maintaining cellular function in normal individuals, we minimized the effect of individual variation by screening mRNA pooled from many individuals. This information is useful for establishing average expression levels in normal individuals. Additionally, we identified transcripts uniquely expressed in each of the 11 tissues.