ORCID Profile
0000-0002-4197-5790
Current Organisations
University College London
,
Universite de Geneve
,
University of Oxford
,
Imperial College London
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Publisher: Springer Science and Business Media LLC
Date: 28-06-2018
Publisher: American Association for the Advancement of Science (AAAS)
Date: 08-05-2015
Abstract: Human genomes show extensive genetic variation across in iduals, but we have only just started documenting the effects of this variation on the regulation of gene expression. Furthermore, only a few tissues have been examined per genetic variant. In order to examine how genetic expression varies among tissues within in iduals, the Genotype-Tissue Expression (GTEx) Consortium collected 1641 postmortem s les covering 54 body sites from 175 in iduals. They identified quantitative genetic traits that affect gene expression and determined which of these exhibit tissue-specific expression patterns. Melé et al. measured how transcription varies among tissues, and Rivas et al. looked at how truncated protein variants affect expression across tissues. Science , this issue p. 648 , p. 660 , p. 666 see also p. 640
Publisher: Springer Science and Business Media LLC
Date: 12-10-2017
DOI: 10.1038/NATURE24277
Abstract: Characterization of the molecular function of the human genome and its variation across in iduals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across in iduals and erse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-in idual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.
Publisher: Springer Science and Business Media LLC
Date: 12-10-2017
DOI: 10.1038/NATURE24265
Abstract: X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of ‘escape’ from inactivation varying between genes and in iduals 1,2 . The extent to which XCI is shared between cells and tissues remains poorly characterized 3,4 , as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression 5 and phenotypic traits 6 . Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 in iduals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify ex les of heterogeneity between tissues, in iduals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic ersity 6,7 . Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.
Publisher: Springer Science and Business Media LLC
Date: 12-10-2017
DOI: 10.1038/NATURE24267
Abstract: Rare genetic variants are abundant in humans and are expected to contribute to in idual disease risk 1,2,3,4 . While genetic association studies have successfully identified common genetic variants associated with susceptibility, these studies are not practical for identifying rare variants 1,5 . Efforts to distinguish pathogenic variants from benign rare variants have leveraged the genetic code to identify deleterious protein-coding alleles 1,6,7 , but no analogous code exists for non-coding variants. Therefore, ascertaining which rare variants have phenotypic effects remains a major challenge. Rare non-coding variants have been associated with extreme gene expression in studies using single tissues 8,9,10,11 , but their effects across tissues are unknown. Here we identify gene expression outliers, or in iduals showing extreme expression levels for a particular gene, across 44 human tissues by using combined analyses of whole genomes and multi-tissue RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project v6p release 12 . We find that 58% of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to 8% of non-outliers. Additionally, we developed RIVER (RNA-informed variant effect on regulation), a Bayesian statistical model that incorporates expression data to predict a regulatory effect for rare variants with higher accuracy than models using genomic annotations alone. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in in idual genomes.
Publisher: Springer Science and Business Media LLC
Date: 19-10-2015
DOI: 10.1038/SREP15145
Abstract: Aging is one of the most important biological processes and is a known risk factor for many age-related diseases in human. Studying age-related transcriptomic changes in tissues across the whole body can provide valuable information for a holistic understanding of this fundamental process. In this work, we catalogue age-related gene expression changes in nine tissues from nearly two hundred in iduals collected by the Genotype-Tissue Expression (GTEx) project. In general, we find the aging gene expression signatures are very tissue specific. However, enrichment for some well-known aging components such as mitochondria biology is observed in many tissues. Different levels of cross-tissue synchronization of age-related gene expression changes are observed and some essential tissues (e.g., heart and lung) show much stronger “co-aging” than other tissues based on a principal component analysis. The aging gene signatures and complex disease genes show a complex overlapping pattern and only in some cases, we see that they are significantly overlapped in the tissues affected by the corresponding diseases. In summary, our analyses provide novel insights to the co-regulation of age-related gene expression in multiple tissues it also presents a tissue-specific view of the link between aging and age-related diseases.
Publisher: Springer Science and Business Media LLC
Date: 12-10-2017
DOI: 10.1038/NATURE24041
Publisher: Public Library of Science (PLoS)
Date: 13-05-2015
Publisher: Cold Spring Harbor Laboratory
Date: 11-10-2017
Abstract: The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes ( cis -eQTLs). More research is needed to identify effects of genetic variation on distant genes ( trans -eQTLs) and understand their biological mechanisms. One common trans -eQTLs mechanism is “mediation” by a local ( cis ) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are “ cis -mediators” of trans -eQTLs, including those “ cis -hubs” involved in regulation of many trans -genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans -eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis -mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among erse s les. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis -hubs and trans -eQTL regulation across tissue types.
Publisher: Springer Science and Business Media LLC
Date: 09-2013
DOI: 10.1038/NATURE12531
Publisher: American Association for the Advancement of Science (AAAS)
Date: 08-05-2015
Abstract: Human genomes show extensive genetic variation across in iduals, but we have only just started documenting the effects of this variation on the regulation of gene expression. Furthermore, only a few tissues have been examined per genetic variant. In order to examine how genetic expression varies among tissues within in iduals, the Genotype-Tissue Expression (GTEx) Consortium collected 1641 postmortem s les covering 54 body sites from 175 in iduals. They identified quantitative genetic traits that affect gene expression and determined which of these exhibit tissue-specific expression patterns. Melé et al. measured how transcription varies among tissues, and Rivas et al. looked at how truncated protein variants affect expression across tissues. Science , this issue p. 648 , p. 660 , p. 666 see also p. 640
Publisher: Springer Science and Business Media LLC
Date: 11-02-2015
DOI: 10.1038/NATURE14177
Publisher: Springer Science and Business Media LLC
Date: 14-12-2016
DOI: 10.1038/NATURE16068
Abstract: Thousands of transiting exoplanets have been discovered, but spectral analysis of their atmospheres has so far been dominated by a small number of exoplanets and data spanning relatively narrow wavelength ranges (such as 1.1-1.7 micrometres). Recent studies show that some hot-Jupiter exoplanets have much weaker water absorption features in their near-infrared spectra than predicted. The low litude of water signatures could be explained by very low water abundances, which may be a sign that water was depleted in the protoplanetary disk at the planet's formation location, but it is unclear whether this level of depletion can actually occur. Alternatively, these weak signals could be the result of obscuration by clouds or hazes, as found in some optical spectra. Here we report results from a comparative study of ten hot Jupiters covering the wavelength range 0.3-5 micrometres, which allows us to resolve both the optical scattering and infrared molecular absorption spectroscopically. Our results reveal a erse group of hot Jupiters that exhibit a continuum from clear to cloudy atmospheres. We find that the difference between the planetary radius measured at optical and infrared wavelengths is an effective metric for distinguishing different atmosphere types. The difference correlates with the spectral strength of water, so that strong water absorption lines are seen in clear-atmosphere planets and the weakest features are associated with clouds and hazes. This result strongly suggests that primordial water depletion during formation is unlikely and that clouds and hazes are the cause of weaker spectral signatures.
Publisher: Springer Science and Business Media LLC
Date: 23-12-2012
DOI: 10.1038/NG.2500
Publisher: Springer Science and Business Media LLC
Date: 11-02-2015
DOI: 10.1038/NATURE14132
Publisher: Cold Spring Harbor Laboratory
Date: 11-10-2017
Abstract: Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a erse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 in iduals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.
Publisher: Public Library of Science (PLoS)
Date: 18-08-2014
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Halit Ongen.