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1.  Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization 
Arking, Dan E. | Pulit, Sara L. | Crotti, Lia | van der Harst, Pim | Munroe, Patricia B. | Koopmann, Tamara T. | Sotoodehnia, Nona | Rossin, Elizabeth J. | Morley, Michael | Wang, Xinchen | Johnson, Andrew D. | Lundby, Alicia | Gudbjartsson, Daníel F. | Noseworthy, Peter A. | Eijgelsheim, Mark | Bradford, Yuki | Tarasov, Kirill V. | Dörr, Marcus | Müller-Nurasyid, Martina | Lahtinen, Annukka M. | Nolte, Ilja M. | Smith, Albert Vernon | Bis, Joshua C. | Isaacs, Aaron | Newhouse, Stephen J. | Evans, Daniel S. | Post, Wendy S. | Waggott, Daryl | Lyytikäinen, Leo-Pekka | Hicks, Andrew A. | Eisele, Lewin | Ellinghaus, David | Hayward, Caroline | Navarro, Pau | Ulivi, Sheila | Tanaka, Toshiko | Tester, David J. | Chatel, Stéphanie | Gustafsson, Stefan | Kumari, Meena | Morris, Richard W. | Naluai, Åsa T. | Padmanabhan, Sandosh | Kluttig, Alexander | Strohmer, Bernhard | Panayiotou, Andrie G. | Torres, Maria | Knoflach, Michael | Hubacek, Jaroslav A. | Slowikowski, Kamil | Raychaudhuri, Soumya | Kumar, Runjun D. | Harris, Tamara B. | Launer, Lenore J. | Shuldiner, Alan R. | Alonso, Alvaro | Bader, Joel S. | Ehret, Georg | Huang, Hailiang | Kao, W.H. Linda | Strait, James B. | Macfarlane, Peter W. | Brown, Morris | Caulfield, Mark J. | Samani, Nilesh J. | Kronenberg, Florian | Willeit, Johann | Smith, J. Gustav | Greiser, Karin H. | zu Schwabedissen, Henriette Meyer | Werdan, Karl | Carella, Massimo | Zelante, Leopoldo | Heckbert, Susan R. | Psaty, Bruce M. | Rotter, Jerome I. | Kolcic, Ivana | Polašek, Ozren | Wright, Alan F. | Griffin, Maura | Daly, Mark J. | Arnar, David O. | Hólm, Hilma | Thorsteinsdottir, Unnur | Denny, Joshua C. | Roden, Dan M. | Zuvich, Rebecca L. | Emilsson, Valur | Plump, Andrew S. | Larson, Martin G. | O'Donnell, Christopher J. | Yin, Xiaoyan | Bobbo, Marco | D'Adamo, Adamo P. | Iorio, Annamaria | Sinagra, Gianfranco | Carracedo, Angel | Cummings, Steven R. | Nalls, Michael A. | Jula, Antti | Kontula, Kimmo K. | Marjamaa, Annukka | Oikarinen, Lasse | Perola, Markus | Porthan, Kimmo | Erbel, Raimund | Hoffmann, Per | Jöckel, Karl-Heinz | Kälsch, Hagen | Nöthen, Markus M. | consortium, HRGEN | den Hoed, Marcel | Loos, Ruth J.F. | Thelle, Dag S. | Gieger, Christian | Meitinger, Thomas | Perz, Siegfried | Peters, Annette | Prucha, Hanna | Sinner, Moritz F. | Waldenberger, Melanie | de Boer, Rudolf A. | Franke, Lude | van der Vleuten, Pieter A. | Beckmann, Britt Maria | Martens, Eimo | Bardai, Abdennasser | Hofman, Nynke | Wilde, Arthur A.M. | Behr, Elijah R. | Dalageorgou, Chrysoula | Giudicessi, John R. | Medeiros-Domingo, Argelia | Barc, Julien | Kyndt, Florence | Probst, Vincent | Ghidoni, Alice | Insolia, Roberto | Hamilton, Robert M. | Scherer, Stephen W. | Brandimarto, Jeffrey | Margulies, Kenneth | Moravec, Christine E. | Fabiola Del, Greco M. | Fuchsberger, Christian | O'Connell, Jeffrey R. | Lee, Wai K. | Watt, Graham C.M. | Campbell, Harry | Wild, Sarah H. | El Mokhtari, Nour E. | Frey, Norbert | Asselbergs, Folkert W. | Leach, Irene Mateo | Navis, Gerjan | van den Berg, Maarten P. | van Veldhuisen, Dirk J. | Kellis, Manolis | Krijthe, Bouwe P. | Franco, Oscar H. | Hofman, Albert | Kors, Jan A. | Uitterlinden, André G. | Witteman, Jacqueline C.M. | Kedenko, Lyudmyla | Lamina, Claudia | Oostra, Ben A. | Abecasis, Gonçalo R. | Lakatta, Edward G. | Mulas, Antonella | Orrú, Marco | Schlessinger, David | Uda, Manuela | Markus, Marcello R.P. | Völker, Uwe | Snieder, Harold | Spector, Timothy D. | Ärnlöv, Johan | Lind, Lars | Sundström, Johan | Syvänen, Ann-Christine | Kivimaki, Mika | Kähönen, Mika | Mononen, Nina | Raitakari, Olli T. | Viikari, Jorma S. | Adamkova, Vera | Kiechl, Stefan | Brion, Maria | Nicolaides, Andrew N. | Paulweber, Bernhard | Haerting, Johannes | Dominiczak, Anna F. | Nyberg, Fredrik | Whincup, Peter H. | Hingorani, Aroon | Schott, Jean-Jacques | Bezzina, Connie R. | Ingelsson, Erik | Ferrucci, Luigi | Gasparini, Paolo | Wilson, James F. | Rudan, Igor | Franke, Andre | Mühleisen, Thomas W. | Pramstaller, Peter P. | Lehtimäki, Terho J. | Paterson, Andrew D. | Parsa, Afshin | Liu, Yongmei | van Duijn, Cornelia | Siscovick, David S. | Gudnason, Vilmundur | Jamshidi, Yalda | Salomaa, Veikko | Felix, Stephan B. | Sanna, Serena | Ritchie, Marylyn D. | Stricker, Bruno H. | Stefansson, Kari | Boyer, Laurie A. | Cappola, Thomas P. | Olsen, Jesper V. | Lage, Kasper | Schwartz, Peter J. | Kääb, Stefan | Chakravarti, Aravinda | Ackerman, Michael J. | Pfeufer, Arne | de Bakker, Paul I.W. | Newton-Cheh, Christopher
Nature genetics  2014;46(8):826-836.
The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.
doi:10.1038/ng.3014
PMCID: PMC4124521  PMID: 24952745
genome-wide association study; QT interval; Long QT Syndrome; sudden cardiac death; myocardial repolarization; arrhythmias
2.  Comparative analysis of metazoan chromatin organization 
Ho, Joshua W. K. | Jung, Youngsook L. | Liu, Tao | Alver, Burak H. | Lee, Soohyun | Ikegami, Kohta | Sohn, Kyung-Ah | Minoda, Aki | Tolstorukov, Michael Y. | Appert, Alex | Parker, Stephen C. J. | Gu, Tingting | Kundaje, Anshul | Riddle, Nicole C. | Bishop, Eric | Egelhofer, Thea A. | Hu, Sheng’en Shawn | Alekseyenko, Artyom A. | Rechtsteiner, Andreas | Asker, Dalal | Belsky, Jason A. | Bowman, Sarah K. | Chen, Q. Brent | Chen, Ron A-J | Day, Daniel S. | Dong, Yan | Dose, Andrea C. | Duan, Xikun | Epstein, Charles B. | Ercan, Sevinc | Feingold, Elise A. | Ferrari, Francesco | Garrigues, Jacob M. | Gehlenborg, Nils | Good, Peter J. | Haseley, Psalm | He, Daniel | Herrmann, Moritz | Hoffman, Michael M. | Jeffers, Tess E. | Kharchenko, Peter V. | Kolasinska-Zwierz, Paulina | Kotwaliwale, Chitra V. | Kumar, Nischay | Langley, Sasha A. | Larschan, Erica N. | Latorre, Isabel | Libbrecht, Maxwell W. | Lin, Xueqiu | Park, Richard | Pazin, Michael J. | Pham, Hoang N. | Plachetka, Annette | Qin, Bo | Schwartz, Yuri B. | Shoresh, Noam | Stempor, Przemyslaw | Vielle, Anne | Wang, Chengyang | Whittle, Christina M. | Xue, Huiling | Kingston, Robert E. | Kim, Ju Han | Bernstein, Bradley E. | Dernburg, Abby F. | Pirrotta, Vincenzo | Kuroda, Mitzi I. | Noble, William S. | Tullius, Thomas D. | Kellis, Manolis | MacAlpine, David M. | Strome, Susan | Elgin, Sarah C. R. | Liu, Xiaole Shirley | Lieb, Jason D. | Ahringer, Julie | Karpen, Gary H. | Park, Peter J.
Nature  2014;512(7515):449-452.
doi:10.1038/nature13415
PMCID: PMC4227084  PMID: 25164756
3.  Reconciliation Revisited: Handling Multiple Optima when Reconciling with Duplication, Transfer, and Loss 
Journal of Computational Biology  2013;20(10):738-754.
Abstract
Phylogenetic tree reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While duplication–loss (DL) reconciliation leads to a unique maximum-parsimony solution, duplication-transfer-loss (DTL) reconciliation yields a multitude of optimal solutions, making it difficult to infer the true evolutionary history of the gene family. This problem is further exacerbated by the fact that different event cost assignments yield different sets of optimal reconciliations. Here, we present an effective, efficient, and scalable method for dealing with these fundamental problems in DTL reconciliation. Our approach works by sampling the space of optimal reconciliations uniformly at random and aggregating the results. We show that even gene trees with only a few dozen genes often have millions of optimal reconciliations and present an algorithm to efficiently sample the space of optimal reconciliations uniformly at random in O(mn2) time per sample, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal reconciliations vary in their node mappings and event assignments and to investigate the impact of varying event costs. We apply our method to a biological dataset of approximately 4700 gene trees from 100 taxa and observe that 93% of event assignments and 73% of mappings remain consistent across different multiple optima. Our analysis represents the first systematic investigation of the space of optimal DTL reconciliations and has many important implications for the study of gene family evolution.
doi:10.1089/cmb.2013.0073
PMCID: PMC3791060  PMID: 24033262
gene duplication; gene family evolution; gene-tree/species-tree reconciliation; horizontal gene transfer; host-parasite cophylogeny; phylogenetics
4.  Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells 
Science (New York, N.Y.)  2014;343(6175):1246980.
Little is known about how human genetic variation affects the responses to environmental stimuli in the context of complex diseases. Experimental and computational approaches were applied to determine the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells. We identified 121 common genetic variants associated in cis with variation in expression responses to E. coli lipopolysaccharide, influenza or interferon-β (IFNβ). We localized and validated causal variants to binding sites of pathogen-activated STAT and IRF transcription factors. We also identified a common variant in IRF7 that is associated in trans with type I interferon induction in response to influenza infection. Our results reveal common alleles that explain inter-individual variation in pathogen sensing and provide functional annotation for genetic variants that alter susceptibility to inflammatory diseases.
doi:10.1126/science.1246980
PMCID: PMC4124741  PMID: 24604203
5.  The tissue-specific lncRNA Fendrr is an essential regulator of heart and body wall development in the mouse 
Developmental cell  2013;24(2):206-214.
SUMMARY
The histone modifying complexes PRC2 and TrxG/MLL play pivotal roles in determining the activation state of genes controlling pluripotency, lineage commitment, and cell differentiation. Long non-coding RNAs (lncRNAs) can bind to either complex, and some have been shown to act as modulators of PRC2 or TrxG/MLL activity. Here we show that the lateral mesoderm-specific lncRNA Fendrr is essential for proper heart and body wall development in the mouse. Embryos lacking Fendrr displayed upregulation of several transcription factors controlling lateral plate or cardiac mesoderm differentiation, accompanied by a drastic reduction in PRC2 occupancy along with decreased H3K27 trimethylation and/or an increase in H3K4 trimethylation at their promoters. Fendrr binds to both the PRC2 and TrxG/MLL complexes, suggesting that it acts as modulator of chromatin signatures that define gene activity. Thus, our work identifies a lncRNA that plays an essential role in fine-tuning the regulatory networks which control the fate of lateral mesoderm derivatives.
doi:10.1016/j.devcel.2012.12.012
PMCID: PMC4149175  PMID: 23369715
6.  RESPONSE to Comment (Green) on "Evidence of abundant purifying selection in humans for recently-acquired regulatory functions" 1225057 Ward 
Science (New York, N.Y.)  2013;340(6133):682.
Green and Ewing propose corrections to our methodology, which we incorporate and extend here. The improved methodology supports our initial conclusion of extensive lineage-specific constraint concentrated in ENCODE elements. We clarify that our estimate is dependent on the constrained and neutral references used, which can further increase the number of nucleotides involved, since a particularly stringent definition was initially used.
doi:10.1126/science.1233366
PMCID: PMC4131756  PMID: 23661743
7.  Distinct and Predictive Histone Lysine Acetylation Patterns at Promoters, Enhancers, and Gene Bodies 
G3: Genes|Genomes|Genetics  2014;4(11):2051-2063.
In eukaryotic cells, histone lysines are frequently acetylated. However, unlike modifications such as methylations, histone acetylation modifications are often considered redundant. As such, the functional roles of distinct histone acetylations are largely unexplored. We previously developed an algorithm RFECS to discover the most informative modifications associated with the classification or prediction of mammalian enhancers. Here, we used this tool to identify the modifications most predictive of promoters, enhancers, and gene bodies. Unexpectedly, we found that histone acetylation alone performs well in distinguishing these unique genomic regions. Further, we found the association of characteristic acetylation patterns with genic regions and association of chromatin state with splicing. Taken together, our work underscores the diverse functional roles of histone acetylation in gene regulation and provides several testable hypotheses to dissect these roles.
doi:10.1534/g3.114.013565
PMCID: PMC4232531  PMID: 25122670
histone lysine acetylations; gene bodies; promoters; enhancers; splicing
8.  Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo 
Nature  2013;505(7485):701-705.
RNA plays a dual role as an informational molecule and a direct effector of biological tasks. The latter function is enabled by RNA’s ability to adopt complex secondary and tertiary folds and thus has motivated extensive computational1–2 and experimental3–8 efforts for determining RNA structures. Existing approaches for evaluating RNA structure have been largely limited to in vitro systems, yet the thermodynamic forces which drive RNA folding in vitro may not be sufficient to predict stable RNA structures in vivo5. Indeed, the presence of RNA binding proteins and ATP-dependent helicases can influence which structures are present inside cells. Here we present an approach for globally monitoring RNA structure in native conditions in vivo with single nucleotide precision. This method is based on in vivo modification with dimethyl sulfate (DMS), which reacts with unpaired adenine and cytosine residues9, followed by deep sequencing to monitor modifications. Our data from yeast and mammalian cells are in excellent agreement with known mRNA structures and with the high-resolution crystal structure of the Saccharomyces cerevisiae ribosome10. Comparison between in vivo and in vitro data reveals that in rapidly dividing cells there are vastly fewer structured mRNA regions in vivo than in vitro. Even thermostable RNA structures are often denatured in cells, highlighting the importance of cellular processes in regulating RNA structure. Indeed, analysis of mRNA structure under ATP-depleted conditions in yeast reveals that energy-dependent processes strongly contribute to the predominantly unfolded state of mRNAs inside cells. Our studies broadly enable the functional analysis of physiological RNA structures and reveal that, in contrast to the Anfinsen view of protein folding, thermodynamics play an incomplete role in determining mRNA structure in vivo.
doi:10.1038/nature12894
PMCID: PMC3966492  PMID: 24336214
9.  Evidence of abundant purifying selection in humans for recently-acquired regulatory functions 
Science (New York, N.Y.)  2012;337(6102):1675-1678.
While only 5% of the human genome is conserved across mammals, a substantially larger portion is biochemically active, raising the question of whether the additional elements evolve neutrally or confer a lineage-specific fitness advantage. To address this question, we integrate human variation information from the 1000 Genomes Project and activity data from the ENCODE Project. A broad range of transcribed and regulatory non-conserved elements show decreased human diversity, suggesting lineage-specific purifying selection. Conversely, conserved elements lacking activity show increased human diversity, suggesting that some recently became non-functional. Regulatory elements under human constraint in non-conserved regions were found near color vision and nerve-growth genes, consistent with purifying selection for recently-evolved functions. Our results suggest continued turnover in regulatory regions, with at least an additional 4% of the human genome subject to lineage-specific constraint.
doi:10.1126/science.1225057
PMCID: PMC4104271  PMID: 22956687
10.  Evidence of efficient stop codon readthrough in four mammalian genes 
Nucleic Acids Research  2014;42(14):8928-8938.
Stop codon readthrough is used extensively by viruses to expand their gene expression. Until recent discoveries in Drosophila, only a very limited number of readthrough cases in chromosomal genes had been reported. Analysis of conserved protein coding signatures that extend beyond annotated stop codons identified potential stop codon readthrough of four mammalian genes. Here we use a modified targeted bioinformatic approach to identify a further three mammalian readthrough candidates. All seven genes were tested experimentally using reporter constructs transfected into HEK-293T cells. Four displayed efficient stop codon readthrough, and these have UGA immediately followed by CUAG. Comparative genomic analysis revealed that in the four readthrough candidates containing UGA-CUAG, this motif is conserved not only in mammals but throughout vertebrates with the first six of the seven nucleotides being universally conserved. The importance of the CUAG motif was confirmed using a systematic mutagenesis approach. One gene, OPRL1, encoding an opiate receptor, displayed extremely efficient levels of readthrough (∼31%) in HEK-293T cells. Signals both 5′ and 3′ of the OPRL1 stop codon contribute to this high level of readthrough. The sequence UGA-CUA alone can support 1.5% readthrough, underlying its importance.
doi:10.1093/nar/gku608
PMCID: PMC4132726  PMID: 25013167
11.  Extensive Variation in Chromatin States Across Humans 
Science (New York, N.Y.)  2013;342(6159):750-752.
The majority of disease-associated variants lie outside protein-coding regions, suggesting a link between variation in regulatory regions and disease predisposition. We studied differences in chromatin states using five histone modifications, cohesin, and CTCF in lymphoblastoid lines from 19 individuals of diverse ancestry. We found extensive signal variation in regulatory regions, which often switch between active and repressed states across individuals. Enhancer activity is particularly diverse among individuals, whereas gene expression remains relatively stable. Chromatin variability shows genetic inheritance in trios, correlates with genetic variation and population divergence, and is associated with disruptions of transcription factor binding motifs. Overall, our results provide insights into chromatin variation among humans.
doi:10.1126/science.1242510
PMCID: PMC4075767  PMID: 24136358
12.  Pareto-optimal phylogenetic tree reconciliation 
Bioinformatics  2014;30(12):i87-i95.
Motivation: Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem.
Results: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies.
Availability and implementation: Our Python tools are freely available at www.cs.hmc.edu/∼hadas/xscape.
Contact: mukul@engr.uconn.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btu289
PMCID: PMC4058917  PMID: 24932009
13.  Network deconvolution as a general method to distinguish direct dependencies in networks 
Nature biotechnology  2013;31(8):726-733.
Recognizing direct relationships between variables connected in a network is a pervasive problem in biological, social and information sciences as correlation-based networks contain numerous indirect relationships. Here we present a general method for inferring direct effects from an observed correlation matrix containing both direct and indirect effects. We formulate the problem as the inverse of network convolution, and introduce an algorithm that removes the combined effect of all indirect paths of arbitrary length in a closed-form solution by exploiting eigen-decomposition and infinite-series sums. We demonstrate the effectiveness of our approach in several network applications: distinguishing direct targets in gene expression regulatory networks; recognizing directly-interacting amino-acid residues for protein structure prediction from sequence alignments; and distinguishing strong collaborations in co-authorship social networks using connectivity information alone.
doi:10.1038/nbt.2635
PMCID: PMC3773370  PMID: 23851448
14.  Multiple knockout mouse models reveal lincRNAs are required for life and brain development 
eLife  2013;2:e01749.
Many studies are uncovering functional roles for long noncoding RNAs (lncRNAs), yet few have been tested for in vivo relevance through genetic ablation in animal models. To investigate the functional relevance of lncRNAs in various physiological conditions, we have developed a collection of 18 lncRNA knockout strains in which the locus is maintained transcriptionally active. Initial characterization revealed peri- and postnatal lethal phenotypes in three mutant strains (Fendrr, Peril, and Mdgt), the latter two exhibiting incomplete penetrance and growth defects in survivors. We also report growth defects for two additional mutant strains (linc–Brn1b and linc–Pint). Further analysis revealed defects in lung, gastrointestinal tract, and heart in Fendrr−/− neonates, whereas linc–Brn1b−/− mutants displayed distinct abnormalities in the generation of upper layer II–IV neurons in the neocortex. This study demonstrates that lncRNAs play critical roles in vivo and provides a framework and impetus for future larger-scale functional investigation into the roles of lncRNA molecules.
DOI: http://dx.doi.org/10.7554/eLife.01749.001
eLife digest
The mammalian genome is comprised of DNA sequences that contain the templates for proteins, and other DNA sequences that do not code for proteins. The coding DNA sequences are transcribed to make messenger RNA molecules, which are then translated to make proteins. Researchers have known for many years that some of the noncoding DNA sequences are also transcribed to make other types of RNA molecules, such as transfer and ribosomal RNA. However, the true breadth and diversity of the roles played by these other RNA molecules have only recently begun to be fully appreciated.
Mammalian genomes contain thousands of noncoding DNA sequences that are transcribed. Recent in vitro studies suggest that the resulting long noncoding RNA molecules can act as regulators of transcription, translation, and cell cycle. In vitro studies also suggest that these long noncoding RNA molecules may play a role in mammalian development and disease. Yet few in vivo studies have been performed to support or confirm such hypotheses.
Now Sauvageau et al. have developed several lines of knockout mice to investigate a subset of noncoding RNA molecules known as long intergenic noncoding RNAs (lincRNAs). These experiments reveal that lincRNAs have a strong influence on the overall viability of mice, and also on a number of developmental processes, including the development of lungs and the cerebral cortex.
Given that the vast majority of the human genome is transcribed, the mouse models developed by Sauvageau et al. represent an important step in determining the physiological relevance, on a genetic level, of the noncoding portion of the genome in vivo.
DOI: http://dx.doi.org/10.7554/eLife.01749.002
doi:10.7554/eLife.01749
PMCID: PMC3874104  PMID: 24381249
long noncoding RNAs; knockout mouse models; lethality; developmental defect; brain development; Mouse
15.  Spatial expression of transcription factors in Drosophila embryonic organ development 
Genome Biology  2013;14(12):R140.
Background
Site-specific transcription factors (TFs) bind DNA regulatory elements to control expression of target genes, forming the core of gene regulatory networks. Despite decades of research, most studies focus on only a small number of TFs and the roles of many remain unknown.
Results
We present a systematic characterization of spatiotemporal gene expression patterns for all known or predicted Drosophila TFs throughout embryogenesis, the first such comprehensive study for any metazoan animal. We generated RNA expression patterns for all 708 TFs by in situ hybridization, annotated the patterns using an anatomical controlled vocabulary, and analyzed TF expression in the context of organ system development. Nearly all TFs are expressed during embryogenesis and more than half are specifically expressed in the central nervous system. Compared to other genes, TFs are enriched early in the development of most organ systems, and throughout the development of the nervous system. Of the 535 TFs with spatially restricted expression, 79% are dynamically expressed in multiple organ systems while 21% show single-organ specificity. Of those expressed in multiple organ systems, 77 TFs are restricted to a single organ system either early or late in development. Expression patterns for 354 TFs are characterized for the first time in this study.
Conclusions
We produced a reference TF dataset for the investigation of gene regulatory networks in embryogenesis, and gained insight into the expression dynamics of the full complement of TFs controlling the development of each organ system.
doi:10.1186/gb-2013-14-12-r140
PMCID: PMC4053779  PMID: 24359758
16.  Systematic discovery and characterization of regulatory motifs in ENCODE TF binding experiments 
Nucleic Acids Research  2013;42(5):2976-2987.
Recent advances in technology have led to a dramatic increase in the number of available transcription factor ChIP-seq and ChIP-chip data sets. Understanding the motif content of these data sets is an important step in understanding the underlying mechanisms of regulation. Here we provide a systematic motif analysis for 427 human ChIP-seq data sets using motifs curated from the literature and also discovered de novo using five established motif discovery tools. We use a systematic pipeline for calculating motif enrichment in each data set, providing a principled way for choosing between motif variants found in the literature and for flagging potentially problematic data sets. Our analysis confirms the known specificity of 41 of the 56 analyzed factor groups and reveals motifs of potential cofactors. We also use cell type-specific binding to find factors active in specific conditions. The resource we provide is accessible both for browsing a small number of factors and for performing large-scale systematic analyses. We provide motif matrices, instances and enrichments in each of the ENCODE data sets. The motifs discovered here have been used in parallel studies to validate the specificity of antibodies, understand cooperativity between data sets and measure the variation of motif binding across individuals and species.
doi:10.1093/nar/gkt1249
PMCID: PMC3950668  PMID: 24335146
17.  Computational Analysis of Noncoding RNAs 
Noncoding RNAs have emerged as important key players in the cell. Understanding their surprisingly diverse range of functions is challenging for experimental and computational biology. Here, we review computational methods to analyze noncoding RNAs. The topics covered include basic and advanced techniques to predict RNA structures, annotation of noncoding RNAs in genomic data, mining RNA-seq data for novel transcripts and prediction of transcript structures, computational aspects of microRNAs, and database resources.
doi:10.1002/wrna.1134
PMCID: PMC3472101  PMID: 22991327
18.  Interpreting non-coding variation in complex disease genetics 
Nature biotechnology  2012;30(11):1095-1106.
Association studies provide genome-wide information about the genetic basis of complex disease, but medical research has primarily focused on protein-coding variants, due to the difficulty of interpreting non-coding mutations. This picture has changed with advances in the systematic annotation of functional non-coding elements. Evolutionary conservation, functional genomics, chromatin state, sequence motifs, and molecular quantitative trait loci all provide complementary information about non-coding function. These functional maps can help prioritize variants on risk haplotypes, filter mutations encountered in the clinic, and perform systems-level analyses to reveal processes underlying disease associations. Advances in predictive modeling can enable dataset integration to reveal pathways shared across loci and alleles, and richer regulatory models can guide the search for epistatic interactions. Lastly, new massively parallel reporter experiments can systematically validate regulatory predictions. Ultimately, advances in regulatory and systems genomics can help unleash the value of whole-genome sequencing for personalized genomic risk assessment, diagnosis, and treatment.
doi:10.1038/nbt.2422
PMCID: PMC3703467  PMID: 23138309
20.  Evolutionary principles of modular gene regulation in yeasts 
eLife  2013;2:e00603.
Divergence in gene regulation can play a major role in evolution. Here, we used a phylogenetic framework to measure mRNA profiles in 15 yeast species from the phylum Ascomycota and reconstruct the evolution of their modular regulatory programs along a time course of growth on glucose over 300 million years. We found that modules have diverged proportionally to phylogenetic distance, with prominent changes in gene regulation accompanying changes in lifestyle and ploidy, especially in carbon metabolism. Paralogs have significantly contributed to regulatory divergence, typically within a very short window from their duplication. Paralogs from a whole genome duplication (WGD) event have a uniquely substantial contribution that extends over a longer span. Similar patterns occur when considering the evolution of the heat shock regulatory program measured in eight of the species, suggesting that these are general evolutionary principles.
DOI: http://dx.doi.org/10.7554/eLife.00603.001
eLife digest
The incredible diversity of living creatures belies the fact that their genes are quite similar. In the 1970s Mary-Claire King and Allan Wilson proposed that a process called gene regulation—which determines when, where and how genes are expressed as proteins—is responsible for this diversity. Four decades later, the central role of gene regulation in evolution has been confirmed in a wide range of species including bacteria, fungi, flies and mammals, although the details remain poorly understood. In recent years it has been suggested that the duplication of genes—and sometimes the duplication of whole genomes—has had a crucial influence on the part played by gene regulation in the evolution of many different species.
Ascomycota fungi are uniquely suited to the study of genetics and evolution because of their diversity—they include C. albicans, a fungus that is found in the human mouth and gut, and various species of yeast—and because many of their genomes have already been sequenced. Moreover, their genomes are relatively small, which simplifies the task of working out how it has changed over the course of evolution. It is also known that species in this branch of the tree of life diverged before and after an event in which a whole genome was duplicated.
Ascomycota fungi use glucose as a source of carbon in different ways during aerobic growth. Most, including C. albicans, are respiratory and rely on oxidative phosphorylation processes to produce energy. However, a small number—including S. cerevisiae and S. pombe, two types of yeast that are widely used as model organisms—prefer to ferment glucose, even when oxygen is available. Species that favor the latter respiro-fermentative lifestyle have evolved independently at least twice: once after the whole genome duplication event that lead to S. cerevisiae, and once when S. pombe and the other fission yeasts evolved.
Thompson et al. have measured mRNA profiles in 15 different species of yeast and reconstructed how the regulation of groups of genes (modules) have evolved over a period of more than 300 million years. They found that modules have diverged proportionally to evolutionary time, with prominent changes in gene regulation being associated with changes in lifestyle (especially changes in carbon metabolism) and a whole genome duplication event.
Gene duplication events result in gene paralogs—identical genes at different places in the genome—and these have made significant contributions to the evolution of different forms of gene regulation, especially just after the duplication event. Moreover, the paralogs produced in whole genome duplication events have resulted in bigger changes over longer periods of time. Similar patterns were observed in the regulation of the genes involved in the response to heat shock in eight of the species, which suggests that these are general evolutionary principles.
The changes in gene expression associated with the respiro-fermentative lifestyle may also have implications for our understanding of cancer: healthy cells rely on oxidative phosphorylation to produce energy whereas, similar to yeast cells, most cancerous cells rely on respiro-fermentation. Furthermore, yeast cells and cancer cells both support their rapid growth and proliferation by using glucose for biosynthesis to support cell division, although this process is not fully understood. Normal cells, on the other hand, use glucose primarily for energy and tend not to divide rapidly.
Thompson et al. found that the genes encoding enzymes in two biosynthetic pathways—one that produces the nucleotides necessary for DNA replication, and one that synthesizes glycine—are induced in respiro-fermentative yeasts but repressed in respiratory yeast cells. The fact that similar changes are observed in the same two pathways when normal cells become cancer cells suggests that these pathways have an important role in the development of cancer. The framework developed by Thompson et al. could also be used to explore the evolution of gene regulation in other species and biological processes.
DOI: http://dx.doi.org/10.7554/eLife.00603.002
doi:10.7554/eLife.00603
PMCID: PMC3687341  PMID: 23795289
regulatory evolution; duplication; divergence; carbon lifestyle; module; gene expression; S. cerevisiae; S. pombe
21.  Extensive and coordinated transcription of noncoding RNAs within cell cycle promoters 
Nature genetics  2011;43(7):621-629.
Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultra-high density array that tiles the promoters of 56 cell cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs--many with RT-PCR-validated periodic expression during the cell cycle, show altered expression in human cancers, and are regulated in expression by specific oncogenic stimuli, stem cell differentiation, or DNA damage. DNA damage induces five lncRNAs from the CDKN1A promoter, and one such lncRNA, named PANDA, is induced in a p53- dependent manner. PANDA interacts with the transcription factor NF-YA to limit expression of pro-apoptotic genes; PANDA depletion markedly sensitized human fibroblasts to apoptosis by doxorubicin. These findings suggest potentially widespread roles for promoter lncRNAs in cell growth control.
doi:10.1038/ng.848
PMCID: PMC3652667  PMID: 21642992
22.  Linking DNA Methyltransferases (DNMTs) to Epigenetic Marks and Nucleosome Structure Genome-Wide in Human Tumor Cells 
Cell reports  2012;2(5):1411-1424.
Summary
DNA methylation, mediated by the combined action of three DNA methyltransferases (DNMT1, DNMT3A, and DNMT3B), is essential for mammalian development and is a major contributor to cellular transformation. To elucidate how DNA methylation is targeted, we mapped the genome-wide localization of all DNMTs and methylation, and examined relationships between these markers, histone modifications, and nucleosome structure in a pluripotent human tumor cell line in its undifferentiated and differentiated states. Our findings reveal a strong link between DNMTs and transcribed loci and that DNA methylation is not a simple sum of DNMT localization patterns. Comparing the epigenomes of normal and cancerous stem cells, and pluripotent and differentiated states, shows that the presence of at least two DNMTs is strongly associated with loci targeted for DNA hypermethylation. Taken together, this study sheds important new light on determinants of DNA methylation and how it may become disrupted in cancer cells.
doi:10.1016/j.celrep.2012.10.017
PMCID: PMC3625945  PMID: 23177624
23.  Heterologous Stop Codon Readthrough of Metazoan Readthrough Candidates in Yeast 
PLoS ONE  2013;8(3):e59450.
Recent analysis of genomic signatures in mammals, flies, and worms indicates that functional translational stop codon readthrough is considerably more abundant in metazoa than previously recognized, but this analysis provides only limited clues about the function or mechanism of readthrough. If an mRNA known to be read through in one species is also read through in another, perhaps these questions can be studied in a simpler setting. With this end in mind, we have investigated whether some of the readthrough genes in human, fly, and worm also exhibit readthrough when expressed in S. cerevisiae. We found that readthrough was highest in a gene with a post-stop hexamer known to trigger readthrough, while other metazoan readthrough genes exhibit borderline readthrough in S. cerevisiae.
doi:10.1371/journal.pone.0059450
PMCID: PMC3609751  PMID: 23544069
25.  RFECS: A Random-Forest Based Algorithm for Enhancer Identification from Chromatin State 
PLoS Computational Biology  2013;9(3):e1002968.
Transcriptional enhancers play critical roles in regulation of gene expression, but their identification in the eukaryotic genome has been challenging. Recently, it was shown that enhancers in the mammalian genome are associated with characteristic histone modification patterns, which have been increasingly exploited for enhancer identification. However, only a limited number of cell types or chromatin marks have previously been investigated for this purpose, leaving the question unanswered whether there exists an optimal set of histone modifications for enhancer prediction in different cell types. Here, we address this issue by exploring genome-wide profiles of 24 histone modifications in two distinct human cell types, embryonic stem cells and lung fibroblasts. We developed a Random-Forest based algorithm, RFECS (Random Forest based Enhancer identification from Chromatin States) to integrate histone modification profiles for identification of enhancers, and used it to identify enhancers in a number of cell-types. We show that RFECS not only leads to more accurate and precise prediction of enhancers than previous methods, but also helps identify the most informative and robust set of three chromatin marks for enhancer prediction.
Author Summary
Enhancers are regions in the genome that can activate the expression of a gene irrespective of their location with respect to the gene. Identifying these elements is critical in understanding regulatory differences between different cell-types. Since enhancers lack characteristic sequence features and can be far away from the gene they regulate, their identification is not trivial. Experimentally determining the genome-wide binding sites of transcriptional co-activator p300 is one way of finding enhancers but it can only identify a subset of enhancers. A few years ago, it was observed that the binding sites of p300 are marked by distinctive, post-translational histone modifications. Several groups have exploited this discovery to predict genome-wide enhancers based on their similarity to the histone modification profiles of p300 binding sites. We here report a novel algorithm for this purpose and show that it has much greater accuracy than existing methods. Another unique feature of our algorithm is the ability to automatically deduce the most informative set of histone modifications required for enhancer prediction. We expect that this method will become increasingly useful with the expanding number of known histone modifications and rapid accumulation of epigenomic datasets for various cell types and species.
doi:10.1371/journal.pcbi.1002968
PMCID: PMC3597546  PMID: 23526891

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