Natural variation in cardiac metabolism and gene expression in Fundulus heteroclitus

Individual variation in gene expression is important for evolutionary adaptation and susceptibility to diseases and pathologies. In this study, we address the functional importance of this variation by comparing cardiac metabolism to patterns of mRNA expression using microarrays. There is extensive variation in both cardiac metabolism and the expression of metabolic genes among individuals of the teleost fish Fundulus heteroclitus from natural outbred populations raised in a common environment: metabolism differed among individuals by a factor of more than 2, and expression levels of 94% of genes were significantly different (P < 0.01) between individuals in a population. This unexpectedly high variation in metabolic gene expression explains much of the variation in metabolism, suggesting that it is biologically relevant. The patterns of gene expression that are most important in explaining cardiac metabolism differ between groups of individuals. Apparently, the variation in metabolism seems to be related to different patterns of gene expression in the different groups of individuals. The magnitude of differences in gene expression in these groups is not important; large changes in expression have no greater predictive value than small changes. These data suggest that variation in physiological performance is related to the subtle variation in gene expression and that this relationship differs among individuals.     

Common genetic variants account for differences in gene expression among ethnic groups

Variation in DNA sequence contributes to individual differences in quantitative traits, but in humans the specific sequence variants are known for very few traits. We characterized variation in gene expression in cells from individuals belonging to three major population groups. This quantitative phenotype differs significantly between European-derived and Asian-derived populations for 1,097 of 4,197 genes tested. For the phenotypes with the strongest evidence of cis determinants, most of the variation is due to allele frequency differences at cis-linked regulators. The results show that specific genetic variation among populations contributes appreciably to differences in gene expression phenotypes. Populations differ in prevalence of many complex genetic diseases, such as diabetes and cardiovascular disease. As some of these are probably influenced by the level of gene expression, our results suggest that allele frequency differences at regulatory polymorphisms also account for some population differences in prevalence of complex diseases.     

Regulatory changes underlying expression differences within and between Drosophila species

Differences in gene expression are an important source of phenotypic variation, and can be caused by changes in cis and/or trans regulation. cis-regulatory variants alter allele-specific expression, whereas trans-regulatory variants influence expression of both alleles in a diploid cell. Because of this difference, we hypothesize that natural selection may favor one type of change over the other. Here, we investigate contributions of cis- and trans-regulatory changes to variable intra- and interspecific gene expression using four strains of Drosophila melanogaster, three strains of D. simulans and a total of 78 genes. We show that cis-regulatory changes account for a greater proportion of the expression differences observed between rather than within species. These data are inconsistent with a neutral model assuming equal probabilities of fixation for cis- and trans-regulatory polymorphisms, suggesting that natural selection influences the molecular mechanisms underlying divergent gene expression. Specifically, cis-regulatory changes seem to accumulate preferentially over time.     

Detection of regulatory variation in mouse genes

Functional polymorphism in genes can be classified as coding variation, altering the amino-acid sequence of the encoded protein, or regulatory variation, affecting the level or pattern of expression of the gene. Coding variation can be recognized directly from DNA sequence, and consequently its frequency and characteristics have been extensively described. By contrast, virtually nothing is known about the extent to which gene regulation varies in populations. Yet it is likely that regulatory variants are important in modulating gene function: alterations in gene regulation have been proposed to influence disease susceptibility and to have been the primary substrate for the evolution of species. Here, we report a systematic study to assess the extent of cis-acting regulatory variation in 69 genes across four inbred mouse strains. We find that at least four of these genes show allelic differences in expression level of 1.5-fold or greater, and that some of these differences are tissue specific. The results show that the impact of regulatory variants can be detected at a significant frequency in a genomic survey and suggest that such variation may have important consequences for organismal phenotype and evolution. The results indicate that larger-scale surveys in both mouse and human could identify a substantial number of genes with common regulatory variation.     

Population genomics of human gene expression

Genetic variation influences gene expression, and this variation in gene expression can be efficiently mapped to specific genomic regions and variants. Here we have used gene expression profiling of Epstein-Barr virus-transformed lymphoblastoid cell lines of all 270 individuals genotyped in the HapMap Consortium to elucidate the detailed features of genetic variation underlying gene expression variation. We find that gene expression is heritable and that differentiation between populations is in agreement with earlier small-scale studies. A detailed association analysis of over 2.2 million common SNPs per population (5% frequency in HapMap) with gene expression identified at least 1,348 genes with association signals in cis and at least 180 in trans. Replication in at least one independent population was achieved for 37% of cis signals and 15% of trans signals, respectively. Our results strongly support an abundance of cis-regulatory variation in the human genome. Detection of trans effects is limited but suggests that regulatory variation may be the key primary effect contributing to phenotypic variation in humans. We also explore several methodologies that improve the current state of analysis of gene expression variation.     

Genome partitioning of genetic variation for complex traits using common SNPs

We estimate and partition genetic variation for height, body mass index (BMI), von Willebrand factor and QT interval (QTi) using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimate that ～45%, ～17%, ～25% and ～21% of the variance in height, BMI, von Willebrand factor and QTi, respectively, can be explained by all autosomal SNPs and a further ～0.5-1% can be explained by X chromosome SNPs. We show that the variance explained by each chromosome is proportional to its length, and that SNPs in or near genes explain more variation than SNPs between genes. We propose a new approach to estimate variation due to cryptic relatedness and population stratification. Our results provide further evidence that a substantial proportion of heritability is captured by common SNPs, that height, BMI and QTi are highly polygenic traits, and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein.     

Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis.

Sequence variation in human genes is largely confined to single-nucleotide polymorphisms (SNPs) and is valuable in tests of association with common diseases and pharmacogenetic traits. We performed a systematic and comprehensive survey of molecular variation to assess the nature, pattern and frequency of SNPs in 75 candidate human genes for blood-pressure homeostasis and hypertension. We assayed 28 Mb (190 kb in 148 alleles) of genomic sequence, comprising the 5' and 3' untranslated regions (UTRs), introns and coding sequence of these genes, for sequence differences in individuals of African and Northern European descent using high-density variant detection arrays (VDAs). We identified 874 candidate human SNPs, of which 22% were confirmed by DNA sequencing to reveal a discordancy rate of 21% for VDA detection. The SNPs detected have an average minor allele frequency of 11%, and 387 are within the coding sequence (cSNPs). Of all cSNPs, 54% lead to a predicted change in the protein sequence, implying a high level of human protein diversity. These protein-altering SNPs are 38% of the total number of such SNPs expected, are more likely to be population-specific and are rarer in the human population, directly demonstrating the effects of natural selection on human genes. Overall, the degree of nucleotide polymorphism across these human genes, and orthologous great ape sequences, is highly variable and is correlated with the effects of functional conservation on gene sequences.     

Haplotype tagging for the identification of common disease genes

Genome-wide linkage disequilibrium (LD) mapping of common disease genes could be more powerful than linkage analysis if the appropriate density of polymorphic markers were known and if the genotyping effort and cost of producing such an LD map could be reduced. Although different metrics that measure the extent of LD have been evaluated, even the most recent studies have not placed significant emphasis on the most informative and cost-effective method of LD mapping-that based on haplotypes. We have scanned 135 kb of DNA from nine genes, genotyped 122 single-nucleotide polymorphisms (SNPs; approximately 184,000 genotypes) and determined the common haplotypes in a minimum of 384 European individuals for each gene. Here we show how knowledge of the common haplotypes and the SNPs that tag them can be used to (i) explain the often complex patterns of LD between adjacent markers, (ii) reduce genotyping significantly (in this case from 122 to 34 SNPs), (iii) scan the common variation of a gene sensitively and comprehensively and (iv) provide key fine-mapping data within regions of strong LD. Our results also indicate that, at least for the genes studied here, the current version of dbSNP would have been of limited utility for LD mapping because many common haplotypes could not be defined. A directed re-sequencing effort of the approximately 10% of the genome in or near genes in the major ethnic groups would aid the systematic evaluation of the common variant model of common disease.     

Regional loss of imprinting and growth deficiency in mice with a targeted deletion of KvDMR1

Genomic imprinting is an epigenetic modification that results in expression from only one of the two parental copies of a gene. Differences in methylation between the two parental chromosomes are often observed at or near imprinted genes. Beckwith-Wiedemann syndrome (BWS), which predisposes to cancer and excessive growth, results from a disruption of imprinted gene expression in chromosome band 11p15.5. One third of individuals with BWS lose maternal-specific methylation at KvDMR1, a putative imprinting control region within intron 10 of the KCNQ1 gene, and it has been proposed that this epimutation results in aberrant imprinting and, consequently, BWS1, 2. Here we show that paternal inheritance of a deletion of KvDMR1 results in the de-repression in cis of six genes, including Cdkn1c, which encodes cyclin-dependent kinase inhibitor 1C. Furthermore, fetuses and adult mice that inherited the deletion from their fathers were 20-25% smaller than their wildtype littermates. By contrast, maternal inheritance of this deletion had no effect on imprinted gene expression or growth. Thus, the unmethylated paternal KvDMR1 allele regulates imprinted expression by silencing genes on the paternal chromosome. These findings support the hypothesis that loss of methylation in BWS patients activates the repressive function of KvDMR1 on the maternal chromosome, resulting in abnormal silencing of CDKN1C and the development of BWS.     

Dopa decarboxylase (Ddc) affects variation in Drosophila longevity

Mutational analyses in model organisms have shown that genes affecting metabolism and stress resistance regulate life span, but the genes responsible for variation in longevity in natural populations are largely unidentified. Previously, we mapped quantitative trait loci (QTLs) affecting variation in longevity between two Drosophila melanogaster strains. Here, we show that the longevity QTL in the 36E;38B cytogenetic interval on chromosome 2 contains multiple closely linked QTLs, including the Dopa decarboxylase (Ddc) locus. Complementation tests to mutations show that Ddc is a positional candidate gene for life span in these strains. Linkage disequilibrium (LD) mapping in a sample of 173 alleles from a single population shows that three common molecular polymorphisms in Ddc account for 15.5% of the genetic contribution to variance in life span from chromosome 2. The polymorphisms are in strong LD, and the effects of the haplotypes on longevity suggest that the polymorphisms are maintained by balancing selection. DDC catalyzes the final step in the synthesis of the neurotransmitters, dopamine and serotonin. Thus, these data implicate variation in the synthesis of bioamines as a factor contributing to natural variation in individual life span.     

Recombination and linkage disequilibrium in Arabidopsis thaliana

Linkage disequilibrium (LD) is a major aspect of the organization of genetic variation in natural populations. Here we describe the genome-wide pattern of LD in a sample of 19 Arabidopsis thaliana accessions using 341,602 non-singleton SNPs. LD decays within 10 kb on average, considerably faster than previously estimated. Tag SNP selection algorithms and 'hide-the-SNP' simulations suggest that genome-wide association mapping will require only 40%-50% of the observed SNPs, a reduction similar to estimates in a sample of African Americans. An Affymetrix genotyping array containing 250,000 SNPs has been designed based on these results; we demonstrate that it should have more than adequate coverage for genome-wide association mapping. The extent of LD is highly variable, and we find clear evidence of recombination hotspots, which seem to occur preferentially in intergenic regions. LD also reflects the action of selection, and it is more extensive between nonsynonymous polymorphisms than between synonymous polymorphisms.     

Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs

Schizophrenia is a complex disorder caused by both genetic and environmental factors. Using 9,087 affected individuals, 12,171 controls and 915,354 imputed SNPs from the Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (PGC-SCZ), we estimate that 23% (s.e. = 1%) of variation in liability to schizophrenia is captured by SNPs. We show that a substantial proportion of this variation must be the result of common causal variants, that the variance explained by each chromosome is linearly related to its length (r = 0.89, P = 2.6 × 10(-8)), that the genetic basis of schizophrenia is the same in males and females, and that a disproportionate proportion of variation is attributable to a set of 2,725 genes expressed in the central nervous system (CNS; P = 7.6 × 10(-8)). These results are consistent with a polygenic genetic architecture and imply more individual SNP associations will be detected for this disease as sample size increases.     

A stress-sensitive reporter predicts longevity in isogenic populations of Caenorhabditis elegans

When both genotype and environment are held constant, 'chance' variation in the lifespan of individuals in a population is still quite large. Using isogenic populations of the nematode Caenorhabditis elegans, we show that, on the first day of adult life, chance variation in the level of induction of a green fluorescent protein (GFP) reporter coupled to a promoter from the gene hsp-16.2 predicts as much as a fourfold variation in subsequent survival. The same reporter is also a predictor of ability to withstand a subsequent lethal thermal stress. The level of induction of GFP is not heritable, and GFP expression levels in other reporter constructs are not associated with differences in longevity. HSP-16.2 itself is probably not responsible for the observed differences in survival but instead probably reflects a hidden, heterogeneous, but now quantifiable, physiological state that dictates the ability of an organism to deal with the rigors of living.