Literature DB >> 27794045

Update of the FANTOM web resource: high resolution transcriptome of diverse cell types in mammals.

Marina Lizio1, Jayson Harshbarger1, Imad Abugessaisa1, Shuei Noguchi1, Atsushi Kondo1, Jessica Severin1, Chris Mungall2, David Arenillas3, Anthony Mathelier4,5, Yulia A Medvedeva6,7, Andreas Lennartsson8, Finn Drabløs9, Jordan A Ramilowski1, Owen Rackham10, Julian Gough11, Robin Andersson12, Albin Sandelin13, Hans Ienasescu13, Hiromasa Ono14, Hidemasa Bono14, Yoshihide Hayashizaki15,16, Piero Carninci1, Alistair R R Forrest17, Takeya Kasukawa18, Hideya Kawaji19,17,15.   

Abstract

Upon the first publication of the fifth iteration of the Functional Annotation of Mammalian Genomes collaborative project, FANTOM5, we gathered a series of primary data and database systems into the FANTOM web resource (http://fantom.gsc.riken.jp) to facilitate researchers to explore transcriptional regulation and cellular states. In the course of the collaboration, primary data and analysis results have been expanded, and functionalities of the database systems enhanced. We believe that our data and web systems are invaluable resources, and we think the scientific community will benefit for this recent update to deepen their understanding of mammalian cellular organization. We introduce the contents of FANTOM5 here, report recent updates in the web resource and provide future perspectives.
© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2016        PMID: 27794045      PMCID: PMC5210666          DOI: 10.1093/nar/gkw995

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


INTRODUCTION

Recent advances in transcriptomics have improved the coverage as well as the detection accuracy of profiled RNA molecules. This means that several new opportunities are available for studying molecular function, gene regulation, embryogenesis, response to environmental stimuli and more. The FANTOM project, one of the longest-lived collaborative projects in genomics, aims at the functional characterization of mammalian genomes. It started in the early 2000 with the generation of more than 100 000 mouse full-length cDNAs that revealed that the portion of the genome encoding for proteins is small, whereas the majority of it is involved in producing non-coding RNAs (1,2). Those full-length cDNAs were produced within both FANTOM1 and FANTOM2. FANTOM3 employed Cap Analysis of Gene Expression (CAGE) paired with first generation sequencing, allowing precise identification of genes transcriptional start sites (TSSs). The project uncovered the first comprehensive promoter landscape of a mammalian genome (3) and the existence of anti-sense transcription (4). FANTOM4 adopted CAGE and 454 Life Science sequencing combined to Illumina microarrays to study a model of differentiation in human THP-1 (myeloid leukemia) cells, and to define the transcriptional regulatory network based on TSS activity that explained such timely process (5). Several databases were developed to collect the results from those four FANTOM iterations: the FANTOM-db (6) to store the mouse cDNA clones; the RIKEN Expression Array Database (READ) (7) containing the expression profile data for the clones; and the FANTOM4 web resources (8) to integrates CAGE expression profiles with short RNA sequencing data and microarray data. The FANTOM4 web resource also incorporates genome browsers and bioinformatics analysis results. Within the FANTOM5 project, the consortium profiled nearly 2000 human and 1000 mouse samples, representative of the majority of cell types and tissues, using CAGE followed by next generation single molecule sequencing (HeliScope) (9). FANTOM5 was organized in two phases; the first one focused on steady cellular states and the second was directed toward understanding transcriptional regulation changes upon differentiation, stimulation or infection. The main results of FANTOM5 were the most comprehensive promoter and enhancer atlases to date that could be generated using the same technology and the same platform (10,11). Not only are their mapped genomic coordinates provided, but also accurate activity profiles of promoters across samples and their association to genes, enhancers and cell ontology information can be obtained. All the primary and processed data were packed together with genome browsers and network viewers (12) and are provided via a unique entry point (http://fantom.gsc.riken.jp) as the FANTOM web resource for easy access and navigation. In this paper, we introduce the contents of the resource and describe our updates following the initial release of the FANTOM5 web resource.

RESOURCES FOR THE FIRST PHASE OF FANTOM5

The FANTOM web resource combines visualization tools and data archives, which are publicly accessible on the Internet (Table 2). All data described in our previous publication (12) were generated on the samples covering steady cellular states (573 and 128 primary cell samples from human and mouse, 152 human and 271 mouse tissues, and 250 human cell lines). Each sample was annotated with terms from the FANTOM5 ontology, which incorporates cell types, anatomical tissues and systems, as well as diseases, from ontologies in the Open Biomedical Ontologies (OBO) Library, including CL, Uberon and DO (13).
Table 2.

Lists of all databases and tools with access URLs

Database or tool nameDescriptionupdate from the initial release (Lizio et al.)URL
data filesprimary data archiveupdated to include phase 2 datafantom.gsc.riken.jp/5/datafiles/latest/
TETTable Extraction Toolupdated to include phase 2 datafantom.gsc.riken.jp/5/tet/
BioMartdatabase system for flexible querying based on data-agnostic modelingupdated to include phase 2 datafantom.gsc.riken.jp/5/biomart/
nanopublicationthe smallest unit of publishable information (nanopublication) for FANTOM5noneantom5.nanopub.org/sparql
ZENBUcollaborative, omics data integration and interactive visualization systemupdated to include phase 2 datafantom.gsc.riken.jp/zenbu/
Track Hubweb-accessible directories of genomic data that can be viewed on the UCSC Genome Browserupdated to include phase 2 datafantom.gsc.riken.jp/5/datahub/
BioLayout Express 3Dtool for the visualization and analysis of network graphsnonefantom.gsc.riken.jp/5/biolayout/
SSTARdatabase system to explore samples, transcriptional initiations, and regulators analyzed in the FANTOM5 projectupdated to include phase 2 datafantom.gsc.riken.jp/5/sstar/
CAGEd-oPOSSUMmotif enrichment analysis from CAGE-derived TSSsadded in phase 2cagedop.cmmt.ubc.ca/CAGEd_oPOSSUM/
EpiFactorsdatabase for epigenetic factors, corresponding genes and productsadded in phase 2epifactors.autosome.ru/
Ligand Receptor Connectomevisual guide to FANTOM5 Ligand-Receptor interactionsadded in phase 2fantom.gsc.riken.jp/5/suppl/Ramilowski_et_al_2015/
Mogrifydirectory of defined factors for direct cell reprogrammingadded in phase 2www.mogrify.net/
SlideBaseSelection of cell or tissue specific genomic elements using sliders.added in phase 2slidebase.binf.ku.dk
RefExData set of mammalian gene expression measured by different technologiesadded in phase 2refex.dbcls.jp

Data archives

Data archives include basic processing outputs of the CAGE reads, such as genome alignments and 1-base resolution frequency of the alignment 5′-ends (corresponding to raw read counts of TSS activities monitored by CAGE). Additional analysis results, such as coordinates of CAGE peaks (corresponding to TSSs), their activities for the entire samples collection, their association with genes, transcribed enhancers, transcription factors and DNA motifs are also included.

Data interfaces

In addition to the data files available for download, subsets of the data, such as expression tables of specific genes in a few samples, can be obtained by using the Table Extraction Tool (TET). Moreover, a BioMart interface (14) is available for CAGE peak annotation and RDF (Resource Description Format) query is supported in the form of nanopublications (15) Both tools help researchers with little computational skills to easily retrieve information from multiple databases. The data are also accessible in a genome-centric manner in ZENBU (16) and via the Track Data Hub (17). The former allows dynamic visualizations of expression profiles together with basic data processing on the fly in a specified region of the genome. The latter, which is available as one of the public hub entries to the UCSC Genome Browser database (18), allows to visualize the data along with other public data resources such as ENCODE (19). Access to the FANTOM5 data hub can be faster when using the recently configured Asian mirror (genome-asia.ucsc.edu). A network-oriented interface is provided by using BioLayout Express 3D (20), which provides sample-sample and promoter–promoter relationships as interactive three-dimensional networks. Other views, including sample-, gene- and promoter-centric views, are provided through FANTOM5 SSTAR (21); for example, a single page dedicated to each sample provides related information and analysis results, such as cell classification and highly expressed transcription factors.

NEW DATA FOR THE SECOND PHASE OF FANTOM5

Dynamic states of cells

The second phase of FANTOM5 aimed at studying dynamic changes in the transcriptional landscape over time, complementing the collection of steady cellular states of the first phase. We collected 19 human and 14 mouse time series, covering development (mouse visual cortex and cerebellum), in vitro differentiation (iPS to neurons, ES cells to cardiomyocite, calcification), response to drugs (MCF7 cells response to HRG and EGF, macrophage response to LPS) and infection (rinderpest, influenza), which resulted in additional nearly 1000 human and 600 mouse samples. The complete sets of FANTOM5 human and mouse samples are listed in Supplementary Tables S1 and S2, respectively.

Identification of additional promoters and enhancers

Given the increase in CAGE profiles number, we extended the list of promoters and transcribed enhancers. As a result, the total number of identified peaks (that correspond to a promoter) has increased by 10% in human and 30% in mouse to a total of ∼200 000 and 158 000, respectively. Although the samples profiled in the phase 2 make up roughly 50% of the entire FANTOM5 data collection, the number of distinct cell types that was added is small and as a result does not expand the set of identified human promoters to the same extent as the previous phase. Transcribed enhancers were also identified by using the added CAGE profiles based on bi-directionality of transcription initiation (10), resulting in additional 20 000 human regions, while mouse enhancers were identified all at once in the second phase (Table 1).
Table 1.

Summary of the number of samples, promoters and enhancers for human and mouse

Archived dataHumanMouse
Phase 1Phase 1+2Phase 1Phase 1+2
Samples97518163991018
CAGE peaks184 827201 802116 277158 966
Enhancers43 01165 423NA44 459

Upgrade to the latest genome assemblies

All data were originally processed based on the reference genomes GRCh37 (hg19) for human and GRCm37 (mm9) for mouse. Thanks to the continued efforts to improve the reference genome sequences, GRCh38 (hg38) and GRCm38 (mm10) have recently become available as the new target of genome annotation in the scientific community (18). We therefore compiled a data set that consists of (i) TSS activities at a single base-pair resolution from re-alignment of the CAGE reads with the latest genome assemblies, representing the most accurate TSS profiles (ii) CAGE peaks consistent with those defined on the old genome assemblies by using liftOver, a tool for conversion of genomic coordinates across different assemblies (https://genome.ucsc.edu/cgi-bin/hgLiftOver), and (iii) expression tables based on (i) and (ii) with dedicated normalization, representing the most accurate expression profiles of consistent promoters between two genome builds. Gene-promoter associations were also redone in order to account for changes in the coordinates of (ii) after migration to the latest genome assemblies.

NEW FEATURES, DATABASES AND TOOLS IN THE SECOND PHASE OF FANTOM5

Incorporation of the latest data and time series navigation

Contents of all databases and interfaces (ZENBU, SSTAR, TET, Track Hub and BioMart) were expanded to cover the new data without the need to change their data structure. Besides the increase in data content, navigation interfaces to the 33 time series data sets were implemented in SSTAR, where a clickable chart representing the set of time courses (22) redirects users to individual time points or to a dedicated page for one set of time series (Figure 1A).
Figure 1.

Recent update of SSTAR. (A) Clickable chart representing the set of time courses and their samples, (B) Hyperlinks from the SSTAR database.

Recent update of SSTAR. (A) Clickable chart representing the set of time courses and their samples, (B) Hyperlinks from the SSTAR database.

Partner databases and tools

As a result of extensive use of the FANTOM5 data, multiple databases and tools were also developed by collaborating researchers to share their own results (Table 2). Most of them were published independently, but were hyperlinked with SSTAR at the content level (deep linking), as in Figure 1B. Here, we give a brief introduction of each, so to help users to explore contents and derived results, and developers to design their future studies based on the FANTOM data set. CAGEd-oPOSSUM (23) implements TF binding site (TFBS) enrichment predictions within cis-regulatory regions derived from TSSs identified by CAGE to infer key transcriptional regulators. The user selects TSSs associated with their cell or tissue type of interest and the tool predicts TFBSs within putative cis-regulatory regions surrounding the TSSs to assess their over-representations as compared to what would be expected by chance. CAGEd-oPOSSUM has been applied to all phase 1 FANTOM5 samples using TF binding motifs from the JASPAR database (24). By combining motif enrichment analysis with CAGE-derived cis-regulatory regions, CAGEd-oPOSSUM helps power insight into the TFs that act as key regulators in specific mammalian cells and tissues. EpiFactors (25) is a manually curated database providing information about epigenetic regulators, their complexes, targets and products in human. It contains information on 815 proteins, including 95 histones and protamines and 69 complexes. For 789 of the related genes, expressions values across all FANTOM5 samples are presented. The protein (gene) page contains a summary of the available data with external links, including mouse orthologous from MGI (26) if available, and the complex page provides information on proteins involved in complex formation, their molecular function and specific targets and products. Ligand Receptor Connectome (27) is a web-based visual and interactive guide to cell-cell communication networks between 144 major human primary cells (profiled in FANTOM5) using 2442 ligand–receptor pairs. Users can select their cells, ligands, receptors or interacting pairs of interest and visualize them as a network with cells being nodes and interactions being edges. This helps to uncover which cells are communicating the most via selected ligand-receptor pair(s), shows the top paths used to communicate between any given two cells or yields information on most specific ligands and receptors expressed by a given cell. Visualized networks can be downloaded as an svg image or in a format compatible with Cytoscape (28) for further exploration. Mogrify (29) is a tool that can predict TFs that may be used for the reprogramming of cells by taking advantage of regulatory network information and gene expression data. The pre-calculated results, key regulators influencing the change of cellular states are based on the FANTOM5 data and are available in the database. SlideBase is a web-based tool that enables users to select enhancers, promoters and more from the FANTOM project upon user-defined expression thresholds for each sample, through the usage of interactive sliders. This allows for on-the-fly selection of tissue-specific enhancers or promoters, with definitions set by the user. The tool also reports overlaps with SNPs, enhancer-TSS associations by co-expression and allows for genome-browser visualizations of selected sets. RefEx (Reference Expression Data set) is a curated reference data set of mammalian gene expression measured by four different but complementary technologies (EST, GeneChip, CAGE and RNA-seq) from publicly available data. The FANTOM5 expression atlas for human and mouse was used for gene expressions in 40 tissues commonly used in RefEx, as well as cell lines, primary cells, adult and fetal tissues. They are visible in choropleth maps on 3D human body images from BodyParts3D (30) in addition to comparative histogram of gene expression levels.

FUTURE PLANS

Additional data

The published data so far have described samples derived from human and mouse. In the course of the FANTOM5 project, we attempted to achieve cross-species comparisons in a few selected cell types. Studies on rat, dog, chicken and macaque samples are under preparation for publication and will be incorporated to the FANTOM web resource. A current limitation of the published data in FANTOM5, besides the coverage of species, lies in the approaches we take to explore RNAs. Since CAGE protocol is designed to capture only the 5′-end of capped long RNA molecules, the internal structure of long RNAs and small regulatory RNAs remains unexplored. To complement the CAGE profiles, CAGEscan (31), RNA-seq and small RNA sequencing data are being analyzed and will also be added to the FANTOM web resource.

Additional databases and tools

As introduced above, the data set provided by FANTOM5 forms a foundation for unique analysis and tool development. We foresee efforts in the development of additional databases and interfaces, within and outside of the FANTOM consortium, and won't exclude the possibility to interconnect external tools with our databases; this would increase both their and the FANTOM web resource overall utility.

Upgrade of the existing databases and interfaces

We are also actively working on upgrading the existing databases and interfaces. In particular, functionalities of ZENBU are being enhanced to empower users with more data manipulation and visualization tools. The backend engine of SSTAR, Semantic MediaWiki, is going to be upgraded to the latest version to improve responsiveness. These changes, as well as expansion of the contents to cover additional data, will further facilitate exploration and characterization of mammalian genomes in the context of cellular states. Lastly, the consortium is already focused on the next FANTOM project. For its sixth iteration, we aim to uncover the function of long non-coding RNAs by high-throughput screening coupled with CAGE.
  31 in total

1.  Microattribution and nanopublication as means to incentivize the placement of human genome variation data into the public domain.

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Journal:  Hum Mutat       Date:  2012-07-23       Impact factor: 4.878

2.  Single molecule sequencing with a HeliScope genetic analysis system.

Authors:  John F Thompson; Kathleen E Steinmann
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3.  Functional annotation of a full-length mouse cDNA collection.

Authors:  J Kawai; A Shinagawa; K Shibata; M Yoshino; M Itoh; Y Ishii; T Arakawa; A Hara; Y Fukunishi; H Konno; J Adachi; S Fukuda; K Aizawa; M Izawa; K Nishi; H Kiyosawa; S Kondo; I Yamanaka; T Saito; Y Okazaki; T Gojobori; H Bono; T Kasukawa; R Saito; K Kadota; H Matsuda; M Ashburner; S Batalov; T Casavant; W Fleischmann; T Gaasterland; C Gissi; B King; H Kochiwa; P Kuehl; S Lewis; Y Matsuo; I Nikaido; G Pesole; J Quackenbush; L M Schriml; F Staubli; R Suzuki; M Tomita; L Wagner; T Washio; K Sakai; T Okido; M Furuno; H Aono; R Baldarelli; G Barsh; J Blake; D Boffelli; N Bojunga; P Carninci; M F de Bonaldo; M J Brownstein; C Bult; C Fletcher; M Fujita; M Gariboldi; S Gustincich; D Hill; M Hofmann; D A Hume; M Kamiya; N H Lee; P Lyons; L Marchionni; J Mashima; J Mazzarelli; P Mombaerts; P Nordone; B Ring; M Ringwald; I Rodriguez; N Sakamoto; H Sasaki; K Sato; C Schönbach; T Seya; Y Shibata; K F Storch; H Suzuki; K Toyo-oka; K H Wang; C Weitz; C Whittaker; L Wilming; A Wynshaw-Boris; K Yoshida; Y Hasegawa; H Kawaji; S Kohtsuki; Y Hayashizaki
Journal:  Nature       Date:  2001-02-08       Impact factor: 49.962

4.  A predictive computational framework for direct reprogramming between human cell types.

Authors:  Owen J L Rackham; Jaber Firas; Hai Fang; Matt E Oates; Melissa L Holmes; Anja S Knaupp; Harukazu Suzuki; Christian M Nefzger; Carsten O Daub; Jay W Shin; Enrico Petretto; Alistair R R Forrest; Yoshihide Hayashizaki; Jose M Polo; Julian Gough
Journal:  Nat Genet       Date:  2016-01-18       Impact factor: 38.330

5.  The transcriptional landscape of the mammalian genome.

Authors:  P Carninci; T Kasukawa; S Katayama; J Gough; M C Frith; N Maeda; R Oyama; T Ravasi; B Lenhard; C Wells; R Kodzius; K Shimokawa; V B Bajic; S E Brenner; S Batalov; A R R Forrest; M Zavolan; M J Davis; L G Wilming; V Aidinis; J E Allen; A Ambesi-Impiombato; R Apweiler; R N Aturaliya; T L Bailey; M Bansal; L Baxter; K W Beisel; T Bersano; H Bono; A M Chalk; K P Chiu; V Choudhary; A Christoffels; D R Clutterbuck; M L Crowe; E Dalla; B P Dalrymple; B de Bono; G Della Gatta; D di Bernardo; T Down; P Engstrom; M Fagiolini; G Faulkner; C F Fletcher; T Fukushima; M Furuno; S Futaki; M Gariboldi; P Georgii-Hemming; T R Gingeras; T Gojobori; R E Green; S Gustincich; M Harbers; Y Hayashi; T K Hensch; N Hirokawa; D Hill; L Huminiecki; M Iacono; K Ikeo; A Iwama; T Ishikawa; M Jakt; A Kanapin; M Katoh; Y Kawasawa; J Kelso; H Kitamura; H Kitano; G Kollias; S P T Krishnan; A Kruger; S K Kummerfeld; I V Kurochkin; L F Lareau; D Lazarevic; L Lipovich; J Liu; S Liuni; S McWilliam; M Madan Babu; M Madera; L Marchionni; H Matsuda; S Matsuzawa; H Miki; F Mignone; S Miyake; K Morris; S Mottagui-Tabar; N Mulder; N Nakano; H Nakauchi; P Ng; R Nilsson; S Nishiguchi; S Nishikawa; F Nori; O Ohara; Y Okazaki; V Orlando; K C Pang; W J Pavan; G Pavesi; G Pesole; N Petrovsky; S Piazza; J Reed; J F Reid; B Z Ring; M Ringwald; B Rost; Y Ruan; S L Salzberg; A Sandelin; C Schneider; C Schönbach; K Sekiguchi; C A M Semple; S Seno; L Sessa; Y Sheng; Y Shibata; H Shimada; K Shimada; D Silva; B Sinclair; S Sperling; E Stupka; K Sugiura; R Sultana; Y Takenaka; K Taki; K Tammoja; S L Tan; S Tang; M S Taylor; J Tegner; S A Teichmann; H R Ueda; E van Nimwegen; R Verardo; C L Wei; K Yagi; H Yamanishi; E Zabarovsky; S Zhu; A Zimmer; W Hide; C Bult; S M Grimmond; R D Teasdale; E T Liu; V Brusic; J Quackenbush; C Wahlestedt; J S Mattick; D A Hume; C Kai; D Sasaki; Y Tomaru; S Fukuda; M Kanamori-Katayama; M Suzuki; J Aoki; T Arakawa; J Iida; K Imamura; M Itoh; T Kato; H Kawaji; N Kawagashira; T Kawashima; M Kojima; S Kondo; H Konno; K Nakano; N Ninomiya; T Nishio; M Okada; C Plessy; K Shibata; T Shiraki; S Suzuki; M Tagami; K Waki; A Watahiki; Y Okamura-Oho; H Suzuki; J Kawai; Y Hayashizaki
Journal:  Science       Date:  2005-09-02       Impact factor: 47.728

6.  A promoter-level mammalian expression atlas.

Authors:  Alistair R R Forrest; Hideya Kawaji; Michael Rehli; J Kenneth Baillie; Michiel J L de Hoon; Vanja Haberle; Timo Lassmann; Ivan V Kulakovskiy; Marina Lizio; Masayoshi Itoh; Robin Andersson; Christopher J Mungall; Terrence F Meehan; Sebastian Schmeier; Nicolas Bertin; Mette Jørgensen; Emmanuel Dimont; Erik Arner; Christian Schmidl; Ulf Schaefer; Yulia A Medvedeva; Charles Plessy; Morana Vitezic; Jessica Severin; Colin A Semple; Yuri Ishizu; Robert S Young; Margherita Francescatto; Intikhab Alam; Davide Albanese; Gabriel M Altschuler; Takahiro Arakawa; John A C Archer; Peter Arner; Magda Babina; Sarah Rennie; Piotr J Balwierz; Anthony G Beckhouse; Swati Pradhan-Bhatt; Judith A Blake; Antje Blumenthal; Beatrice Bodega; Alessandro Bonetti; James Briggs; Frank Brombacher; A Maxwell Burroughs; Andrea Califano; Carlo V Cannistraci; Daniel Carbajo; Yun Chen; Marco Chierici; Yari Ciani; Hans C Clevers; Emiliano Dalla; Carrie A Davis; Michael Detmar; Alexander D Diehl; Taeko Dohi; Finn Drabløs; Albert S B Edge; Matthias Edinger; Karl Ekwall; Mitsuhiro Endoh; Hideki Enomoto; Michela Fagiolini; Lynsey Fairbairn; Hai Fang; Mary C Farach-Carson; Geoffrey J Faulkner; Alexander V Favorov; Malcolm E Fisher; Martin C Frith; Rie Fujita; Shiro Fukuda; Cesare Furlanello; Masaaki Furino; Jun-ichi Furusawa; Teunis B Geijtenbeek; Andrew P Gibson; Thomas Gingeras; Daniel Goldowitz; Julian Gough; Sven Guhl; Reto Guler; Stefano Gustincich; Thomas J Ha; Masahide Hamaguchi; Mitsuko Hara; Matthias Harbers; Jayson Harshbarger; Akira Hasegawa; Yuki Hasegawa; Takehiro Hashimoto; Meenhard Herlyn; Kelly J Hitchens; Shannan J Ho Sui; Oliver M Hofmann; Ilka Hoof; Furni Hori; Lukasz Huminiecki; Kei Iida; Tomokatsu Ikawa; Boris R Jankovic; Hui Jia; Anagha Joshi; Giuseppe Jurman; Bogumil Kaczkowski; Chieko Kai; Kaoru Kaida; Ai Kaiho; Kazuhiro Kajiyama; Mutsumi Kanamori-Katayama; Artem S Kasianov; Takeya Kasukawa; Shintaro Katayama; Sachi Kato; Shuji Kawaguchi; Hiroshi Kawamoto; Yuki I Kawamura; Tsugumi Kawashima; Judith S Kempfle; Tony J Kenna; Juha Kere; Levon M Khachigian; Toshio Kitamura; S Peter Klinken; Alan J Knox; Miki Kojima; Soichi Kojima; Naoto Kondo; Haruhiko Koseki; Shigeo Koyasu; Sarah Krampitz; Atsutaka Kubosaki; Andrew T Kwon; Jeroen F J Laros; Weonju Lee; Andreas Lennartsson; Kang Li; Berit Lilje; Leonard Lipovich; Alan Mackay-Sim; Ri-ichiroh Manabe; Jessica C Mar; Benoit Marchand; Anthony Mathelier; Niklas Mejhert; Alison Meynert; Yosuke Mizuno; David A de Lima Morais; Hiromasa Morikawa; Mitsuru Morimoto; Kazuyo Moro; Efthymios Motakis; Hozumi Motohashi; Christine L Mummery; Mitsuyoshi Murata; Sayaka Nagao-Sato; Yutaka Nakachi; Fumio Nakahara; Toshiyuki Nakamura; Yukio Nakamura; Kenichi Nakazato; Erik van Nimwegen; Noriko Ninomiya; Hiromi Nishiyori; Shohei Noma; Shohei Noma; Tadasuke Noazaki; Soichi Ogishima; Naganari Ohkura; Hiroko Ohimiya; Hiroshi Ohno; Mitsuhiro Ohshima; Mariko Okada-Hatakeyama; Yasushi Okazaki; Valerio Orlando; Dmitry A Ovchinnikov; Arnab Pain; Robert Passier; Margaret Patrikakis; Helena Persson; Silvano Piazza; James G D Prendergast; Owen J L Rackham; Jordan A Ramilowski; Mamoon Rashid; Timothy Ravasi; Patrizia Rizzu; Marco Roncador; Sugata Roy; Morten B Rye; Eri Saijyo; Antti Sajantila; Akiko Saka; Shimon Sakaguchi; Mizuho Sakai; Hiroki Sato; Suzana Savvi; Alka Saxena; Claudio Schneider; Erik A Schultes; Gundula G Schulze-Tanzil; Anita Schwegmann; Thierry Sengstag; Guojun Sheng; Hisashi Shimoji; Yishai Shimoni; Jay W Shin; Christophe Simon; Daisuke Sugiyama; Takaai Sugiyama; Masanori Suzuki; Naoko Suzuki; Rolf K Swoboda; Peter A C 't Hoen; Michihira Tagami; Naoko Takahashi; Jun Takai; Hiroshi Tanaka; Hideki Tatsukawa; Zuotian Tatum; Mark Thompson; Hiroo Toyodo; Tetsuro Toyoda; Elvind Valen; Marc van de Wetering; Linda M van den Berg; Roberto Verado; Dipti Vijayan; Ilya E Vorontsov; Wyeth W Wasserman; Shoko Watanabe; Christine A Wells; Louise N Winteringham; Ernst Wolvetang; Emily J Wood; Yoko Yamaguchi; Masayuki Yamamoto; Misako Yoneda; Yohei Yonekura; Shigehiro Yoshida; Susan E Zabierowski; Peter G Zhang; Xiaobei Zhao; Silvia Zucchelli; Kim M Summers; Harukazu Suzuki; Carsten O Daub; Jun Kawai; Peter Heutink; Winston Hide; Tom C Freeman; Boris Lenhard; Vladimir B Bajic; Martin S Taylor; Vsevolod J Makeev; Albin Sandelin; David A Hume; Piero Carninci; Yoshihide Hayashizaki
Journal:  Nature       Date:  2014-03-27       Impact factor: 49.962

7.  Update of the FANTOM web resource: from mammalian transcriptional landscape to its dynamic regulation.

Authors:  Hideya Kawaji; Jessica Severin; Marina Lizio; Alistair R R Forrest; Erik van Nimwegen; Michael Rehli; Kate Schroder; Katharine Irvine; Harukazu Suzuki; Piero Carninci; Yoshihide Hayashizaki; Carsten O Daub
Journal:  Nucleic Acids Res       Date:  2010-11-12       Impact factor: 16.971

8.  A draft network of ligand-receptor-mediated multicellular signalling in human.

Authors:  Jordan A Ramilowski; Tatyana Goldberg; Jayson Harshbarger; Edda Kloppmann; Edda Kloppman; Marina Lizio; Venkata P Satagopam; Masayoshi Itoh; Hideya Kawaji; Piero Carninci; Burkhard Rost; Alistair R R Forrest
Journal:  Nat Commun       Date:  2015-07-22       Impact factor: 14.919

9.  FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki.

Authors:  Imad Abugessaisa; Hisashi Shimoji; Serkan Sahin; Atsushi Kondo; Jayson Harshbarger; Marina Lizio; Yoshihide Hayashizaki; Piero Carninci; Alistair Forrest; Takeya Kasukawa; Hideya Kawaji
Journal:  Database (Oxford)       Date:  2016-07-09       Impact factor: 3.451

10.  JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles.

Authors:  Anthony Mathelier; Oriol Fornes; David J Arenillas; Chih-Yu Chen; Grégoire Denay; Jessica Lee; Wenqiang Shi; Casper Shyr; Ge Tan; Rebecca Worsley-Hunt; Allen W Zhang; François Parcy; Boris Lenhard; Albin Sandelin; Wyeth W Wasserman
Journal:  Nucleic Acids Res       Date:  2015-11-03       Impact factor: 16.971

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  50 in total

1.  Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits.

Authors:  Chen Yao; Roby Joehanes; Andrew D Johnson; Tianxiao Huan; Chunyu Liu; Jane E Freedman; Peter J Munson; David E Hill; Marc Vidal; Daniel Levy
Journal:  Am J Hum Genet       Date:  2017-03-09       Impact factor: 11.025

2.  Whole-Genome Sequencing of Childhood Cancer Survivors Treated with Cranial Radiation Therapy Identifies 5p15.33 Locus for Stroke: A Report from the St. Jude Lifetime Cohort Study.

Authors:  Kevin R Krull; Yutaka Yasui; Yadav Sapkota; Yin Ting Cheung; Wonjong Moon; Kyla Shelton; Carmen L Wilson; Zhaoming Wang; Daniel A Mulrooney; Jinghui Zhang; Gregory T Armstrong; Melissa M Hudson; Leslie L Robison
Journal:  Clin Cancer Res       Date:  2019-08-28       Impact factor: 12.531

Review 3.  Am I ready for CRISPR? A user's guide to genetic screens.

Authors:  John G Doench
Journal:  Nat Rev Genet       Date:  2017-12-04       Impact factor: 53.242

4.  A Genetic Interaction Map of Insulin Production Identifies Mfi as an Inhibitor of Mitochondrial Fission.

Authors:  Jessica Lee; Zachary Pappalardo; Deeksha Gambhir Chopra; Thomas G Hennings; Ian Vaughn; Christopher Lan; Justin J Choe; Kenny Ang; Steven Chen; Michelle Arkin; Michael T McManus; Michael S German; Gregory M Ku
Journal:  Endocrinology       Date:  2018-09-01       Impact factor: 4.736

5.  Biallelic Mutations in CFAP43 and CFAP44 Cause Male Infertility with Multiple Morphological Abnormalities of the Sperm Flagella.

Authors:  Shuyan Tang; Xiong Wang; Weiyu Li; Xiaoyu Yang; Zheng Li; Wangjie Liu; Caihua Li; Zijue Zhu; Lingxiang Wang; Jiaxiong Wang; Ling Zhang; Xiaoling Sun; Erlei Zhi; Hongyan Wang; Hong Li; Li Jin; Yang Luo; Jian Wang; Shenmin Yang; Feng Zhang
Journal:  Am J Hum Genet       Date:  2017-05-25       Impact factor: 11.025

Review 6.  The multifaceted functional role of DNA methylation in immune-mediated rheumatic diseases.

Authors:  Matteo Vecellio; Haijing Wu; Qianjin Lu; Carlo Selmi
Journal:  Clin Rheumatol       Date:  2020-07-02       Impact factor: 2.980

7.  Bi-allelic Mutations in ARMC2 Lead to Severe Astheno-Teratozoospermia Due to Sperm Flagellum Malformations in Humans and Mice.

Authors:  Charles Coutton; Guillaume Martinez; Zine-Eddine Kherraf; Amir Amiri-Yekta; Magalie Boguenet; Antoine Saut; Xiaojin He; Feng Zhang; Marie Cristou-Kent; Jessica Escoffier; Marie Bidart; Véronique Satre; Béatrice Conne; Selima Fourati Ben Mustapha; Lazhar Halouani; Ouafi Marrakchi; Mounir Makni; Habib Latrous; Mahmoud Kharouf; Karin Pernet-Gallay; Mélanie Bonhivers; Sylviane Hennebicq; Nathalie Rives; Emmanuel Dulioust; Aminata Touré; Hamid Gourabi; Yunxia Cao; Raoudha Zouari; Seyedeh Hanieh Hosseini; Serge Nef; Nicolas Thierry-Mieg; Christophe Arnoult; Pierre F Ray
Journal:  Am J Hum Genet       Date:  2019-01-24       Impact factor: 11.025

8.  The complex genetics of human insulin-like growth factor 2 are not reflected in public databases.

Authors:  Peter Rotwein
Journal:  J Biol Chem       Date:  2018-02-02       Impact factor: 5.157

Review 9.  Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing.

Authors:  Jiansong Fang; Andrew A Pieper; Ruth Nussinov; Garam Lee; Lynn Bekris; James B Leverenz; Jeffrey Cummings; Feixiong Cheng
Journal:  Med Res Rev       Date:  2020-07-13       Impact factor: 12.944

10.  ADAR1-mediated RNA editing is required for thymic self-tolerance and inhibition of autoimmunity.

Authors:  Taisuke Nakahama; Yuki Kato; Jung In Kim; Tuangtong Vongpipatana; Yutaka Suzuki; Carl R Walkley; Yukio Kawahara
Journal:  EMBO Rep       Date:  2018-10-25       Impact factor: 8.807

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