Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.

These first ant methylomes and their intra- and interspecies comparison reveal an exonic methylation pattern that points to a connection between DNA methylation and splicing. The presence of monoallelic DNA methylation and the methylation of non-CpG sites in all samples suggest roles in genome regulation in these social insects, including the intriguing possibility of parental or caste-specific genomic imprinting.

The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography–Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.

Familial combined hyperlipidemia (FCHL) is a common familial lipid disorder characterized by a variable pattern of elevated levels of plasma cholesterol and/or triglycerides. It is present in 10%-20% of patients with premature coronary heart disease. The genetic etiology of the disease, including the number of genes involved and the magnitude of their effects, is unknown. Using a subset of 35 Dutch families ascertained for FCHL, we screened the genome, with a panel of 399 genetic markers, for chromosomal regions linked to genes contributing to FCHL. The results were analyzed by use of parametric-linkage methods in a two-stage study design. Four loci, on chromosomes 2p, 11p, 16q, and 19q, exhibited suggestive evidence for linkage with FCHL (LOD scores of 1.3-2.6). Markers within each of these regions were then examined in the original sample and in additional Dutch families with FCHL. The locus on chromosome 2 failed to show evidence for linkage, and the loci on chromosome 16q and 19q yielded only equivocal or suggestive evidence for linkage. However, one locus, near marker D11S1324 on the short arm of human chromosome 11, continued to show evidence for linkage with FCHL, in the second stage of this design. This region does not contain any strong candidate genes. These results provide evidence for a candidate chromosomal region for FCHL and support the concept that FCHL is complex and heterogeneous.

Our results demonstrate that a major gene determining fasting insulin is located on chromosome 7q. Linkage of BP, HOMA, and leptin levels to the same region suggests this locus may broadly influence traits associated with IR and supports a genetic basis for phenotypic associations in IR syndrome.

Purpose: Repetitive ribosomal DNA (rDNA) genes are GC-rich clusters in the human genome.The aim of the study was to determine the methylation status of two rDNA subunits, the 18S and 28S genes, in ovarian tumors and to correlate methylation levels with clinicopathologic features in a cohort of ovarian cancer patients. Experimental Design: 18S and 28S rDNA methylation was examined by quantitative methylation-specific PCR in 74 late-stage ovarian cancers, 9 histologically uninvolved, and 11 normal ovarian surface epithelial samples. In addition, methylation and gene expression levels of 18S and 28S rDNAs in two ovarian cancer cell lines were examined by reverse transcription-PCR before and after treatment with the demethylating drug 5V -aza-2V -deoxycytidine. Results: The methylation level (amount of methylated rDNA/h-actin) of 18S and 28S rDNAs was significantly higher (P < 0.05) in tumors than in normal ovarian surface epithelial samples.Methylation of 18S and 28S rDNA was highly correlated (R 2 = 0.842). Multivariate analysis byCox regression found that rDNA hypermethylation [hazard ratio (HR), 0.25; P < 0.01], but not age (HR, 1.29; P = 0.291) and stage (HR, 1.09; P = 0.709), was independently associated with longer progression-free survival. In ovarian cancer cell lines, methylation levels of rDNA correlated with gene down-regulation and 5V -aza-2V -deoxycytidine treatment resulted in a moderate increase in 18S and 28S rDNA gene expressions. Conclusion:This is the first report of rDNA hypermethylation in ovarian tumors. Furthermore, rDNA methylation levels were higher in patients with long progression-free survival versus patients with short survival. Thus, rDNA methylation as a prognostic marker in ovarian cancer warrants further investigation.

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