To fully understand the allelic variation that underlies common diseases, complete genome sequencing for many individuals with and without disease is required. This is still not technically feasible. However, recently it has become possible to carry out partial surveys of the genome by genotyping large numbers of common SNPs in genome-wide association studies. Here, we outline the main factors - including models of the allelic architecture of common diseases, sample size, map density and sample-collection biases - that need to be taken into account in order to optimize the cost efficiency of identifying genuine disease-susceptibility loci.

/pdf/genome-wide-association-studies-theoretical-and-practical-173hsj0eix.pdf

Genome-wide association studies: theoretical and practical concerns

A new field of genetic analysis of global gene expression has emerged in recent years, driven by the realization that traditional techniques of linkage and association analysis can be applied to thousands of transcript levels measured by microarrays. Genetic dissection of transcript abundance has shed light on the architecture of quantitative traits, provided a new approach for connecting DNA sequence variation with phenotypic variation, and improved our understanding of transcriptional regulation and regulatory variation.

Genetics of global gene expression.

Polyploidy is a common mode of evolution in flowering plants. The profound effects of polyploidy on gene expression appear to be caused more by hybridity than by genome doubling. Epigenetic mechanisms underlying genome-wide changes in expression are as yet poorly understood; only methylation has received much study, and its importance varies among polyploids. Genetic diploidization begins with the earliest responses to genome merger and doubling; less is known about chromosomal diploidization. Polyploidy duplicates every gene in the genome, providing the raw material for divergence or partitioning of function in homoeologous copies. Preferential retention or loss of genes occurs in a wide range of taxa, suggesting that there is an underlying set of principles governing the fates of duplicated genes. Further studies are required for general patterns to be elucidated, involving different plant families, kinds of polyploidy, and polyploids of different ages.

Evolutionary Genetics of Genome Merger and Doubling in Plants

Some individuals with a particular disease-causing mutation or genotype fail to express most if not all features of the disease in question, a phenomenon that is known as ‘reduced (or incomplete) penetrance’. Reduced penetrance is not uncommon; indeed, there are many known examples of ‘disease-causing mutations’ that fail to cause disease in at least a proportion of the individuals who carry them. Reduced penetrance may therefore explain not only why genetic diseases are occasionally transmitted through unaffected parents, but also why healthy individuals can harbour quite large numbers of potentially disadvantageous variants in their genomes without suffering any obvious ill effects. Reduced penetrance can be a function of the specific mutation(s) involved or of allele dosage. It may also result from differential allelic expression, copy number variation or the modulating influence of additional genetic variants in cis or in trans. The penetrance of some pathogenic genotypes is known to be age- and/or sex-dependent. Variable penetrance may also reflect the action of unlinked modifier genes, epigenetic changes or environmental factors. At least in some cases, complete penetrance appears to require the presence of one or more genetic variants at other loci. In this review, we summarize the evidence for reduced penetrance being a widespread phenomenon in human genetics and explore some of the molecular mechanisms that may help to explain this enigmatic characteristic of human inherited disease.

/pdf/where-genotype-is-not-predictive-of-phenotype-towards-an-4a9ovpgsrt.pdf

Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease

LINE-1 (L1) elements are the most abundant autonomous retrotransposons in the human genome, accounting for about 17% of human DNA. The L1 retrotransposon encodes two proteins, open reading frame (ORF)1 and the ORF2 endonuclease/reverse transcriptase. L1 RNA and ORF2 protein are difficult to detect in mammalian cells, even in the context of overexpression systems. Here we show that inserting L1 sequences on a transcript significantly decreases RNA expression and therefore protein expression. This decreased RNA concentration does not result from major effects on the transcription initiation rate or RNA stability. Rather, the poor L1 expression is primarily due to inadequate transcriptional elongation. Because L1 is an abundant and broadly distributed mobile element, the inhibition of transcriptional elongation by L1 might profoundly affect expression of endogenous human genes. We propose a model in which L1 affects gene expression genome-wide by acting as a 'molecular rheostat' of target genes. Bioinformatic data are consistent with the hypothesis that L1 can serve as an evolutionary fine-tuner of the human transcriptome.

Transcriptional disruption by the L1 retrotransposon and implications for mammalian transcriptomes

A total of 15590 unique zebrafish EST clusters from two cDNA libraries have been identified. Most significantly, only 22% (3437) of the 15590 unique clusters matched 2805 (of 15200) clusters in the Danio rerio UniGene database, indicating that our EST set is complementary to the existing ESTs in the public database and will be invaluable in assisting the annotation of genes based on the upcoming zebrafish genome sequence. Blast search showed that 7824 of our unique clusters matched 6710 known or predicted proteins in the nonredundant database. A cDNA microarray representing approximately 3100 unique zebrafish cDNA clusters has been generated and used to profile the gene expression patterns across six different embryonic stages (cleavage, blastula, gastrula, segmentation, pharyngula, and hatching). Analysis of expression data using K-means clustering revealed that genes coding for muscle-specific proteins displayed similar expression patterns, confirming that the coordinate gene expression is important for myogenesis. Our results demonstrate that the combination of microarray technology with the zebrafish model system can provide useful information on how genes are coordinated in a genetic network to control zebrafish embryogenesis and can help to identify novel genes that are important for organogenesis.

/pdf/15000-unique-zebrafish-est-clusters-and-their-future-use-in-2jtg8cp8v5.pdf

15000 unique zebrafish EST clusters and their future use in microarray for profiling gene expression patterns during embryogenesis.

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15000 unique zebrafish EST clusters and their future use in microarray for profiling gene expression patterns during embryogenesis.