Fast-evolving noncoding sequences in the human genome

BACKGROUND: Gene regulation is considered one of the driving forces of evolution. Although protein-coding DNA sequences and RNA genes have been subject to recent evolutionary events in the human lineage, it has been hypothesized that the large phenotypic divergence between humans and chimpanzees has been driven mainly by changes in gene regulation rather than altered protein-coding gene sequences. Comparative analysis of vertebrate genomes has revealed an abundance of evolutionarily conserved but noncoding sequences. These conserved noncoding (CNC) sequences may well harbor critical regulatory variants that have driven recent human evolution. RESULTS: Here we identify 1,356 CNC sequences that appear to have undergone dramatic human-specific changes in selective pressures, at least 15% of which have substitution rates significantly above that expected under neutrality. The 1,356 'accelerated CNC' (ANC) sequences are enriched in recent segmental duplications, suggesting a recent change in selective constraint following duplication. In addition, single nucleotide polymorphisms within ANC sequences have a significant excess of high frequency derived alleles and high F(ST)values relative to controls, indicating that acceleration and positive selection are recent in human populations. Finally, a significant number of single nucleotide polymorphisms within ANC sequences are associated with changes in gene expression. The probability of variation in an ANC sequence being associated with a gene expression phenotype is fivefold higher than variation in a control CNC sequence. CONCLUSION: Our analysis suggests that ANC sequences have until very recently played a role in human evolution, potentially through lineage-specific changes in gene regulation

The diverse nature of island isolation and its effect on land bridge insular faunas

Aim: Isolation is a key factor in island biology. It is usually defined as the distance to the geographically nearest mainland, but many other definitions exist. We explored how testing different isolation indices affects the inference of impacts of isolation on faunal characteristics. We focused on land bridge islands and compared the relationships of many spatial and temporal (i.e., through time) isolation indices with community‐, population‐ and individual‐level characteristics (species richness, population density and body size, respectively). Location: Aegean Sea islands, Greece. Time period: Current. Taxon: Many animal taxa. Methods: We estimated 21 isolation indices for 205 islands and recorded species richness data for 15 taxa (invertebrates and vertebrates). We obtained body size data for seven lizard species and population density data for three. We explored how well indices predict each characteristic, in each taxon, by conducting a series of ordinary least squares regressions (controlling for island area when needed) and a meta‐analysis. Results: Isolation was significantly (and negatively) associated with species richness in 10 of 15 taxa. It was significantly (and positively) associated with body size in only one of seven species and was not associated with population density. The effect of isolation on species richness was much weaker than that of island area, regardless of the index tested. Spatial indices generally out‐performed temporal indices, and indices directly related to the mainland out‐performed those related mainly to neighbouring islands. No index was universally superior to others, including the distance to the geographically nearest mainland. Main conclusions: The choice of index can alter our perception of the impacts of isolation on biological patterns. The nearly automatic, ubiquitous use of distance to the geographically nearest mainland misrepresents the complexity of the effects of isolation. We recommend the simultaneous testing of several indices that represent different aspects of isolation, in order to produce more constructive and thorough investigations and avoid imprecise inference

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies

Summary: Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols. Availability: http://www.sanger.ac.uk/resources/software/genevar Contact: [email protected]

Genetic and Epigenetic Regulation of Human lincRNA Gene Expression

Large intergenic noncoding RNAs (lincRNAs) are still poorly functionally characterized. We analyzed the genetic and epigenetic regulation of human lincRNA expression in the GenCord collection by using three cell types from 195 unrelated European individuals. We detected a considerable number of cis expression quantitative trait loci (cis-eQTLs) and demonstrated that the genetic regulation of lincRNA expression is independent of the regulation of neighboring protein-coding genes. lincRNAs have relatively more cis-eQTLs than do equally expressed protein-coding genes with the same exon number. lincRNA cis-eQTLs are located closer to transcription start sites (TSSs) and their effect sizes are higher than cis-eQTLs found for protein-coding genes, suggesting that lincRNA expression levels are less constrained than that of protein-coding genes. Additionally, lincRNA cis-eQTLs can influence the expression level of nearby protein-coding genes and thus could be considered as QTLs for enhancer activity. Enrichment of expressed lincRNA promoters in enhancer marks provides an additional argument for the involvement of lincRNAs in the regulation of transcription in cis. By investigating the epigenetic regulation of lincRNAs, we observed both positive and negative correlations between DNA methylation and gene expression (expression quantitative trait methylation [eQTMs]), as expected, and found that the landscapes of passive and active roles of DNA methylation in gene regulation are similar to protein-coding genes. However, lincRNA eQTMs are located closer to TSSs than are protein-coding gene eQTMs. These similarities and differences in genetic and epigenetic regulation between lincRNAs and protein-coding genes contribute to the elucidation of potential functions of lincRNAs

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

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=7.46×10−8) 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=2.5×10−5) 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 individual

Large-Scale Population Study of Human Cell Lines Indicates that Dosage Compensation Is Virtually Complete

X chromosome inactivation in female mammals results in dosage compensation of X-linked gene products between the sexes. In humans there is evidence that a substantial proportion of genes escape from silencing. We have carried out a large-scale analysis of gene expression in lymphoblastoid cell lines from four human populations to determine the extent to which escape from X chromosome inactivation disrupts dosage compensation. We conclude that dosage compensation is virtually complete. Overall expression from the X chromosome is only slightly higher in females and can largely be accounted for by elevated female expression of approximately 5% of X-linked genes. We suggest that the potential contribution of escape from X chromosome inactivation to phenotypic differences between the sexes is more limited than previously believed

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies

Summary: Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols

Breaking the waves: improved detection of copy number variation from microarray-based comparative genomic hybridization.

BACKGROUND: Large-scale high throughput studies using microarray technology have established that copy number variation (CNV) throughout the genome is more frequent than previously thought. Such variation is known to play an important role in the presence and development of phenotypes such as HIV-1 infection and Alzheimer's disease. However, methods for analyzing the complex data produced and identifying regions of CNV are still being refined. RESULTS: We describe the presence of a genome-wide technical artifact, spatial autocorrelation or 'wave', which occurs in a large dataset used to determine the location of CNV across the genome. By removing this artifact we are able to obtain both a more biologically meaningful clustering of the data and an increase in the number of CNVs identified by current calling methods without a major increase in the number of false positives detected. Moreover, removing this artifact is critical for the development of a novel model-based CNV calling algorithm - CNVmix - that uses cross-sample information to identify regions of the genome where CNVs occur. For regions of CNV that are identified by both CNVmix and current methods, we demonstrate that CNVmix is better able to categorize samples into groups that represent copy number gains or losses. CONCLUSION: Removing artifactual 'waves' (which appear to be a general feature of array comparative genomic hybridization (aCGH) datasets) and using cross-sample information when identifying CNVs enables more biological information to be extracted from aCGH experiments designed to investigate copy number variation in normal individuals.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Evolutionary Comparison Provides Evidence for Pathogenicity of RMRP Mutations

Cartilage-hair hypoplasia (CHH) is a pleiotropic disease caused by recessive mutations in the RMRP gene that result in a wide spectrum of manifestations including short stature, sparse hair, metaphyseal dysplasia, anemia, immune deficiency, and increased incidence of cancer. Molecular diagnosis of CHH has implications for management, prognosis, follow-up, and genetic counseling of affected patients and their families. We report 20 novel mutations in 36 patients with CHH and describe the associated phenotypic spectrum. Given the high mutational heterogeneity (62 mutations reported to date), the high frequency of variations in the region (eight single nucleotide polymorphisms in and around RMRP), and the fact that RMRP is not translated into protein, prediction of mutation pathogenicity is difficult. We addressed this issue by a comparative genomic approach and aligned the genomic sequences of RMRP gene in the entire class of mammals. We found that putative pathogenic mutations are located in highly conserved nucleotides, whereas polymorphisms are located in non-conserved positions. We conclude that the abundance of variations in this small gene is remarkable and at odds with its high conservation through species; it is unclear whether these variations are caused by a high local mutation rate, a failure of repair mechanisms, or a relaxed selective pressure. The marked diversity of mutations in RMRP and the low homozygosity rate in our patient population indicate that CHH is more common than previously estimated, but may go unrecognized because of its variable clinical presentation. Thus, RMRP molecular testing may be indicated in individuals with isolated metaphyseal dysplasia, anemia, or immune dysregulation