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 x 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 x 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 individuals.

Genetic basis of adaptation in Arabidopsis thaliana: local adaptation at the seed dormancy QTL DOG1.

Local adaptation provides an opportunity to study the genetic basis of adaptation and investigate the allelic architecture of adaptive genes. We study delay of germination 1 (DOG1), a gene controlling natural variation in seed dormancy in Arabidopsis thaliana and investigate evolution of dormancy in 41 populations distributed in four regions separated by natural barriers. Using F(ST) and Q(ST) comparisons, we compare variation at DOG1 with neutral markers and quantitative variation in seed dormancy. Patterns of genetic differentiation among populations suggest that the gene DOG1 contributes to local adaptation. Although Q(ST) for seed dormancy is not different from F(ST) for neutral markers, a correlation with variation in summer precipitation supports that seed dormancy is adaptive. We characterize dormancy variation in several F(2) -populations and show that a series of functionally distinct alleles segregate at the DOG1 locus. Theoretical models have shown that the number and effect of alleles segregatin at quantitative trait loci (QTL) have important consequences for adaptation. Our results provide support to models postulating a large number of alleles at quantitative trait loci involved in adaptation.

FastEpistasis: a high performance computing solution for quantitative trait epistasis.

Motivation: Genome-wide association studies have become widely used tools to study effects of genetic variants on complex diseases. While it is of great interest to extend existing analysis methods by considering interaction effects between pairs of loci, the large number of possible tests presents a significant computational challenge. The number of computations is further multiplied in the study of gene expression quantitative trait mapping, in which tests are performed for thousands of gene phenotypes simultaneously. Results: We present FastEpistasis, an efficient parallel solution extending the PLINK epistasis module, designed to test for epistasis effects when analyzing continuous phenotypes. Our results show that the algorithm scales with the number of processors and offers a reduction in computation time when several phenotypes are analyzed simultaneously. FastEpistasis is capable of testing the association of a continuous trait with all single nucleotide polymorphism ( SNP) pairs from 500 000 SNPs, totaling 125 billion tests, in a population of 5000 individuals in 29, 4 or 0.5 days using 8, 64 or 512 processors.

A hyperactive quantitative trait locus allele of Arabidopsis BRX contributes to natural variation in root growth vigor.

Quantitative trait loci analysis of natural Arabidopsis thaliana accessions is increasingly exploited for gene isolation. However, to date this has mostly revealed deleterious mutations. Among them, a loss-of-function allele identified the root growth regulator BREVIS RADIX (BRX). Here we present evidence that BRX and the paralogous BRX-LIKE (BRXL) genes are under selective constraint in monocotyledons as well as dicotyledons. Unexpectedly, however, whereas none of the Arabidopsis orthologs except AtBRXL1 could complement brx null mutants when expressed constitutively, nearly all monocotyledon BRXLs tested could. Thus, BRXL proteins seem to be more diversified in dicotyledons than in monocotyledons. This functional diversification was correlated with accelerated rates of sequence divergence in the N-terminal regions. Population genetic analyses of 30 haplotypes are suggestive of an adaptive role of AtBRX and AtBRXL1. In two accessions, Lc-0 and Lov-5, seven amino acids are deleted in the variable region between the highly conserved C-terminal, so-called BRX domains. Genotyping of 42 additional accessions also found this deletion in Kz-1, Pu2-7, and Ws-0. In segregating recombinant inbred lines, the Lc-0 allele (AtBRX(Lc-0)) conferred significantly enhanced root growth. Moreover, when constitutively expressed in the same regulatory context, AtBRX(Lc-0) complemented brx mutants more efficiently than an allele without deletion. The same was observed for AtBRXL1, which compared with AtBRX carries a 13 amino acid deletion that encompasses the deletion found in AtBRX(Lc-0). Thus, the AtBRX(Lc-0) allele seems to contribute to natural variation in root growth vigor and provides a rare example of an experimentally confirmed, hyperactive allelic variant.

The IBO germination quantitative trait locus encodes a phosphatase 2C-related variant with a nonsynonymous amino acid change that interferes with abscisic acid signaling.

Natural genetic variation is crucial for adaptability of plants to different environments. Seed dormancy prevents precocious germination in unsuitable conditions and is an adaptation to a major macro-environmental parameter, the seasonal variation in temperature and day length. Here we report the isolation of IBO, a quantitative trait locus (QTL) that governs c. 30% of germination rate variance in an Arabidopsis recombinant inbred line (RIL) population derived from the parental accessions Eilenburg-0 (Eil-0) and Loch Ness-0 (Lc-0). IBO encodes an uncharacterized phosphatase 2C-related protein, but neither the Eil-0 nor the Lc-0 variant, which differ in a single amino acid, have any appreciable phosphatase activity in in vitro assays. However, we found that the amino acid change in the Lc-0 variant of the IBO protein confers reduced germination rate. Moreover, unlike the Eil-0 variant of the protein, the Lc-0 variant can interfere with the activity of the phosphatase 2C ABSCISIC ACID INSENSITIVE 1 in vitro. This suggests that the Lc-0 variant possibly interferes with abscisic acid signaling, a notion that is supported by physiological assays. Thus, we isolated an example of a QTL allele with a nonsynonymous amino acid change that might mediate local adaptation of seed germination timing.

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Although it has long been known that genetic factors play a major role in shaping the electroencephalogram (EEG), progress on identifying the underlying genes has, until recently, been limited. Using quantitative trait loci (QTL) analyses several genomic loci affecting the sleep EEG could be mapped in the mouse. For three of these QTLs the responsible genes were identified leading to the implication of novel signaling pathways affecting EEG traits. Moreover, the insight that in the mouse the sleep-wake dependent dynamics in the expression of EEG slow waves during sleep is under strong genetic control has paved the way for candidate gene studies in humans investigating the contribution of specific polymorphism to the trait-like inter-individual differences in the susceptibility to sleep loss. Candidate gene studies in the mouse were also instrumental in establishing an alternative, noncircadian function for clock genes in the homeostatic regulation of sleep and modulating rhythmic EEG activity of thalamocortical origin. Future efforts should combine system genetics approaches in the mouse and genome-wide association studies in humans to facilitate uncovering the molecular pathways that shape brain activity.

MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data.

A recurring task in the analysis of mass genome annotation data from high-throughput technologies is the identification of peaks or clusters in a noisy signal profile. Examples of such applications are the definition of promoters on the basis of transcription start site profiles, the mapping of transcription factor binding sites based on ChIP-chip data and the identification of quantitative trait loci (QTL) from whole genome SNP profiles. Input to such an analysis is a set of genome coordinates associated with counts or intensities. The output consists of a discrete number of peaks with respective volumes, extensions and center positions. We have developed for this purpose a flexible one-dimensional clustering tool, called MADAP, which we make available as a web server and as standalone program. A set of parameters enables the user to customize the procedure to a specific problem. The web server, which returns results in textual and graphical form, is useful for small to medium-scale applications, as well as for evaluation and parameter tuning in view of large-scale applications, requiring a local installation. The program written in C++ can be freely downloaded from ftp://ftp.epd.unil.ch/pub/software/unix/madap. The MADAP web server can be accessed at http://www.isrec.isb-sib.ch/madap/.

Natural genetic variation in Arabidopsis: tools, traits and prospects for evolutionary ecology.

BACKGROUND: The model plant Arabidopsis thaliana (Arabidopsis) shows a wide range of genetic and trait variation among wild accessions. Because of its unparalleled biological and genomic resources, the potential of Arabidopsis for molecular genetic analysis of this natural variation has increased dramatically in recent years. SCOPE: Advanced genomics has accelerated molecular phylogenetic analysis and gene identification by quantitative trait loci (QTL) mapping and/or association mapping in Arabidopsis. In particular, QTL mapping utilizing natural accessions is now becoming a major strategy of gene isolation, offering an alternative to artificial mutant lines. Furthermore, the genomic information is used by researchers to uncover the signature of natural selection acting on the genes that contribute to phenotypic variation. The evolutionary significance of such genes has been evaluated in traits such as disease resistance and flowering time. However, although molecular hallmarks of selection have been found for the genes in question, a corresponding ecological scenario of adaptive evolution has been difficult to prove. Ecological strategies, including reciprocal transplant experiments and competition experiments, and utilizing near-isogenic lines of alleles of interest will be a powerful tool to measure the relative fitness of phenotypic and/or allelic variants. CONCLUSIONS: As the plant model organism, Arabidopsis provides a wealth of molecular background information for evolutionary genetics. Because genetic diversity between and within Arabidopsis populations is much higher than anticipated, combining this background information with ecological approaches might well establish Arabidopsis as a model organism for plant evolutionary ecology.

quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation.

quantiNemo is an individual-based, genetically explicit stochastic simulation program. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. quantiNemo is highly flexible at various levels: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography, mating system, etc. quantiNemo is coded in C++ using an object-oriented approach and runs on any computer platform. Availability: Executables for several platforms, user's manual, and source code are freely available under the GNU General Public License at http://www2.unil.ch/popgen/softwares/quantinemo.

Genomic determinants of the efficiency of internal ribosomal entry sites of viral and cellular origin

Summary : Internal ribosome entry sites (IRES) are used by viruses as a strategy to bypass inhibition of cap-dependent translation that commonly results from viral infection. IRES are also used in eukaryotic cells to control mRNA translation under conditions of cellular stress (apoptosis, heat shock) or during the G2 phase of the cell cycle when general protein synthesis is inhibited. Variation in cellular expression levels has been shown to be inherited. Expression is controlled, among others, by transcriptional factors and by the efficiency of cap-mediated translation and ribosome activity. We aimed at identifying genomic determinants of variability in IRES-mediated translation of two representative IRES [Encephalomyocarditis virus (EMCV) and X-linked Inhibitor-of-Apoptosis (XIAP) IRES]. We used bicistronic lentiviral constructions expressing two fluorescent reporter transgenes. Lentiviruses were used to transduce seven different laboratory cell lines and B lymphoblastoid cell lines from the Centre d'Etude du Polymorphisme Humain (CEPH; 15 pedigrees; n=209); representing an in vitro approach to family structure allowing genome scan analyses. The relative expression of the two markers was assessed by FACS. IRES efficiency varies according to cellular background, but also varies, for a same cell type, among individuals. The control of IRES activity presents an inherited component (h2) of 0.47 and 0.36 for EMCV and XIAP IRES, respectively. A genome scan identified a suggestive Quantitative Trait Loci (LOD 2.35) involved in the control of XIAP IRES activity. Résumé : Les sites internes d'entrée des ribosomes (IRES = internal ribosome entry sites) sont utilisés par les virus comme une stratégie afin d'outrepasser l'inhibition de traduction qui résulte communément d'une infection virale. Les IRES sont également utilisés par les cellules eucaryotes pour contrôler la traduction de l'ARN messager dans des conditions de stress cellulaire (apoptose, choc thermique) ou durant la phase G2 du cycle cellulaire, situations durant lesquelles la synthèse générale des protéines est inhibée. La variation des niveaux d'expression cellulaire de transcription est un caractère héréditaire. L'expression des gènes est contrôlée entre autre par les facteurs de transcription et par l'efficacité de la traduction initiée par la coiffe ainsi que par l'activité des ribosomes. Durant cette étude nous avons eu pour but d'identifier les déterminants génomiques responsables de la variabilité de la traduction contrôlée par l'IRES. Ceci a été effectué en étudiant deux IRES représentatifs : l'IRES du virus de l'encéphalomyocardite (EMCV) et l'IRES de l'inhibiteur de l'apoptose XIAP (X-linked Inhibitor-of-Apoptosis). Nous avons utilisés des lentivirus délivrant un transgène bicistronique codant pour deux gènes rapporteurs fluorescents. Ces lentivirus ont été utilisés pour transduire sept différentes lignées cellulaires de laboratoire et des lignées cellulaires lymphoblastoïdes B du Centre d'Etude du Polymorphisme Humain (CEPH; 15 pedigrees; n=209) qui représentent une approche in vitro de la structure familiale et qui permettent des analyses par balayage du génome. L'expression relative des deux marqueurs fluorescents a été analysée par FACS. Nos résultats montrent que l'efficacité des IRES varie en fonction du type de cellules. Il varie aussi, pour le même type de cellules, selon les individus. Le contrôle de l'activité de l'IRES est un caractère héritable (héritabilité h2) de 0.47 et 0.36 pour les IRES de EMCV et XIAP respectivement. Le balayage du génome a permis l'identification d'un locus à effets quantitatifs [QTL Quantitative Trait Loci (LOD 2.35)] impliqué dans le contôle de l'activité de l'IRES de XIAP.

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Quantitative genetics of sleep in inbred mice.

The timing and the organization of sleep architecture are mainly controlled by the circadian system, while sleep need and intensity are regulated by a homeostatic process. How independent these two systems are in regulating sleep is not well understood. In contrast to the impressive progress in the molecular genetics of circadian rhythms, little is known about the molecular basis of sleep. Nevertheless, as summarized here, phenotypic dissection of sleep into its most basic aspects can be used to identify both the single major genes and small effect quantitative trait loci involved. Although experimental models such as the mouse are more readily amenable to genetic analysis of sleep, similar approaches can be applied to humans.

Detecting epistasis with restricted response patterns in pairs of biallelic loci.

Well-established examples of genetic epistasis between a pair of loci typically show characteristic patterns of phenotypic distributions in joint genotype tables. However, inferring epistasis given such data is difficult due to the lack of power in commonly used approaches, which decompose the epistatic patterns into main plus interaction effects followed by testing the interaction term. Testing additive-only or all terms may have more power, but they are sensitive to nonepistatic patterns. Alternatively, the epistatic patterns of interest can be enumerated and the best matching one is found by searching through the possibilities. Although this approach requires multiple testing correction over possible patterns, each pattern can be fitted with a regression model with just one degree of freedom and thus the overall power can still be high, if the number of possible patterns is limited. Here we compare the power of the linear decomposition and pattern search methods, by applying them to simulated data generated under several patterns of joint genotype effects with simple biological interpretations. Interaction-only tests are the least powerful; while pattern search approach is the most powerful if the range of possibilities is restricted, but still includes the true pattern.

Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies.

To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P = 5.4 × 10⁻⁶⁰) and 9q31.2 (P = 2.2 × 10⁻³³), we identified 30 new menarche loci (all P < 5 × 10⁻⁸) and found suggestive evidence for a further 10 loci (P < 1.9 × 10⁻⁶). The new loci included four previously associated with body mass index (in or near FTO, SEC16B, TRA2B and TMEM18), three in or near other genes implicated in energy homeostasis (BSX, CRTC1 and MCHR2) and three in or near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and gene-set enrichment pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing.

Genomic and proteomic approaches towards an understanding of sleep.

The basic functions of sleep are still unclear, however, recent advances in genomics and proteomics have begun to contribute to our understanding of both normal and pathological sleep. In this review, we focus primarily on normal sleep and wake that have been studied in model organisms such as mice. Mice have been especially valuable since many different inbred strains exist that differ in sleep-related traits, and genes can be altered by either mutagenesis or targeted approaches. Advances in QTL (Quantitative Trait Loci) analysis have also helped to identify important sleep related genes, and several other QTLs have been mapped as a first step toward finding the genes that underlie basic sleep traits. In addition to more traditional genetic approaches, the abundance of different mRNAs across sleep and wake can now be studied and compared in different brain regions much more thoroughly using microarray methods. Progress at the protein level has been more difficult, but a few studies have begun to investigate changes in proteins during sleep and wake, and we present some of our own preliminary data in this area. A knowledge of which genes and proteins control or respond to changes in sleep will not only help answer fundamental questions, but may also suggest novel drug targets for improving multiple aspects of sleep and wake.