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Novak G, Kyriakis D, Grzyb K, Bernini M, Rodius S, Dittmar G, Finkbeiner S, Skupin A. Single-cell transcriptomics of human iPSC differentiation dynamics reveal a core molecular network of Parkinson's disease. Commun Biol 2022; 5:49. [PMID: 35027645 PMCID: PMC8758783 DOI: 10.1038/s42003-021-02973-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 12/14/2021] [Indexed: 01/02/2023] Open
Abstract
Parkinson's disease (PD) is the second-most prevalent neurodegenerative disorder, characterized by the loss of dopaminergic neurons (mDA) in the midbrain. The underlying mechanisms are only partly understood and there is no treatment to reverse PD progression. Here, we investigated the disease mechanism using mDA neurons differentiated from human induced pluripotent stem cells (hiPSCs) carrying the ILE368ASN mutation within the PINK1 gene, which is strongly associated with PD. Single-cell RNA sequencing (RNAseq) and gene expression analysis of a PINK1-ILE368ASN and a control cell line identified genes differentially expressed during mDA neuron differentiation. Network analysis revealed that these genes form a core network, members of which interact with all known 19 protein-coding Parkinson's disease-associated genes. This core network encompasses key PD-associated pathways, including ubiquitination, mitochondrial function, protein processing, RNA metabolism, and vesicular transport. Proteomics analysis showed a consistent alteration in proteins of dopamine metabolism, indicating a defect of dopaminergic metabolism in PINK1-ILE368ASN neurons. Our findings suggest the existence of a network onto which pathways associated with PD pathology converge, and offers an inclusive interpretation of the phenotypic heterogeneity of PD.
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Affiliation(s)
- Gabriela Novak
- The Integrative Cell Signalling Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
- Luxembourg Institute of Health (LIH), Esch-sur-Alzette, Luxembourg.
- Center for Systems and Therapeutics, the Gladstone Institutes and Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, 94158, USA.
| | - Dimitrios Kyriakis
- The Integrative Cell Signalling Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Kamil Grzyb
- The Integrative Cell Signalling Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Michela Bernini
- The Integrative Cell Signalling Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Sophie Rodius
- Department of Infection and Immunity, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Gunnar Dittmar
- Department of Infection and Immunity, Luxembourg Institute of Health, Strassen, Luxembourg
- Department of Life Sciences and Medicine, University of Luxembourg, Belvaux, Luxembourg
| | - Steven Finkbeiner
- Center for Systems and Therapeutics, the Gladstone Institutes and Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Alexander Skupin
- The Integrative Cell Signalling Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
- University of California San Diego, La Jolla, CA, 92093, USA.
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2
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Szychowski KA, Skóra B, Kryshchyshyn-Dylevych A, Kaminskyy D, Rybczyńska-Tkaczyk K, Lesyk R, Gmiński J. Induction of Cyp450 enzymes by 4-thiazolidinone-based derivatives in 3T3-L1 cells in vitro. Naunyn Schmiedebergs Arch Pharmacol 2020; 394:915-927. [PMID: 33219472 PMCID: PMC8102453 DOI: 10.1007/s00210-020-02025-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 11/15/2020] [Indexed: 12/24/2022]
Abstract
4-Thiazolidinones and related derivatives are regarded as privileged structures in medicinal chemistry and a source of new drug-like compounds. To date it is known that thiazolidinones are able to induce CYP1A1 activity in 3T3-L1 cells. Therefore, to extend the knowledge of the mechanism of thiazolidinones in the cell, four chemically synthesized heterocycles were tested on 3T3-L1 cells. The 3T3-L1 cells were exposed to Les-2194, Les-3640, Les-5935, and Les-6166. Our study showed that 1 μM βNF, Les-2194, and Les-6166 decreased the expression of Ahr mRNA. In turn, βNF, Les-2194, and Les-3640 increased the Cyp1a1 mRNA expression at the same time interval. On the other hand, Les-5935 was found to decrease the Cyp1a1 mRNA expression. Interestingly, the expression of Cyp1a2 mRNA was activated only by βNF and Les-2194. The expression of Cyp1b1 mRNA in the 3T3 cell line increased after the βNF and Les-2194 treatment but declined after the exposure to Les-5935 and Les-6166. Moreover, the Les-2194 and Les-5935 compounds were shown to increase the activity of EROD, MROD, and PROD. Les-3640 increased the activity of EROD and decreased the activity of PROD. In turn, the treatment with Les-6166 resulted in an increase in the activity of EROD and a decrease in the activity of MROD and PROD in the 3T3-L1 cells.
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Affiliation(s)
- Konrad A Szychowski
- Department of Lifestyle Disorders and Regenerative Medicine, University of Information Technology and Management in Rzeszow, Sucharskiego 2, 35-225, Rzeszow, Poland.
| | - Bartosz Skóra
- Department of Lifestyle Disorders and Regenerative Medicine, University of Information Technology and Management in Rzeszow, Sucharskiego 2, 35-225, Rzeszow, Poland
| | - Anna Kryshchyshyn-Dylevych
- Department of Pharmaceutical, Organic and Bioorganic Chemistry, Danylo Halytsky Lviv National Medical University, Pekarska 69, Lviv, 79010, Ukraine
| | - Danylo Kaminskyy
- Department of Pharmaceutical, Organic and Bioorganic Chemistry, Danylo Halytsky Lviv National Medical University, Pekarska 69, Lviv, 79010, Ukraine
| | - Kamila Rybczyńska-Tkaczyk
- Department of Environmental Microbiology, University of Life Sciences, Leszczyńskiego 7, 20-069, Lublin, Poland
| | - Roman Lesyk
- Department of Lifestyle Disorders and Regenerative Medicine, University of Information Technology and Management in Rzeszow, Sucharskiego 2, 35-225, Rzeszow, Poland.,Department of Pharmaceutical, Organic and Bioorganic Chemistry, Danylo Halytsky Lviv National Medical University, Pekarska 69, Lviv, 79010, Ukraine
| | - Jan Gmiński
- Department of Lifestyle Disorders and Regenerative Medicine, University of Information Technology and Management in Rzeszow, Sucharskiego 2, 35-225, Rzeszow, Poland
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Samborskaia MD, Galitsyna A, Pletenev I, Trofimova A, Mironov AA, Gelfand MS, Khrameeva EE. Cumulative contact frequency of a chromatin region is an intrinsic property linked to its function. PeerJ 2020; 8:e9566. [PMID: 32864204 PMCID: PMC7425636 DOI: 10.7717/peerj.9566] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 06/27/2020] [Indexed: 12/18/2022] Open
Abstract
Regulation of gene transcription is a complex process controlled by many factors, including the conformation of chromatin in the nucleus. Insights into chromatin conformation on both local and global scales can be provided by the Hi-C (high-throughput chromosomes conformation capture) method. One of the drawbacks of Hi-C analysis and interpretation is the presence of systematic biases, such as different accessibility to enzymes, amplification, and mappability of DNA regions, which all result in different visibility of the regions. Iterative correction (IC) is one of the most popular techniques developed for the elimination of these systematic biases. IC is based on the assumption that all chromatin regions have an equal number of observed contacts in Hi-C. In other words, the IC procedure is equalizing the experimental visibility approximated by the cumulative contact frequency (CCF) for all genomic regions. However, the differences in experimental visibility might be explained by biological factors such as chromatin openness, which is characteristic of distinct chromatin states. Here we show that CCF is positively correlated with active transcription. It is associated with compartment organization, since compartment A demonstrates higher CCF and gene expression levels than compartment B. Notably, this observation holds for a wide range of species, including human, mouse, and Drosophila. Moreover, we track the CCF state for syntenic blocks between human and mouse and conclude that active state assessed by CCF is an intrinsic property of the DNA region, which is independent of local genomic and epigenomic context. Our findings establish a missing link between Hi-C normalization procedures removing CCF from the data and poorly investigated and possibly relevant biological factors contributing to CCF.
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Affiliation(s)
- Margarita D Samborskaia
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia
| | - Aleksandra Galitsyna
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,A.A. Kharkevich Institute for Information Transmission Problems, RAS, Moscow, Russia.,Institute of Gene Biology, RAS, Moscow, Russia
| | - Ilya Pletenev
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Anna Trofimova
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Andrey A Mironov
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia.,A.A. Kharkevich Institute for Information Transmission Problems, RAS, Moscow, Russia
| | - Mikhail S Gelfand
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,A.A. Kharkevich Institute for Information Transmission Problems, RAS, Moscow, Russia
| | - Ekaterina E Khrameeva
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
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4
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Damiri B, Baldwin WS. Cyp2b-Knockdown Mice Poorly Metabolize Corn Oil and Are Age-Dependent Obese. Lipids 2018; 53:871-884. [PMID: 30421529 DOI: 10.1002/lipd.12095] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 09/23/2018] [Accepted: 09/24/2018] [Indexed: 01/04/2023]
Abstract
We previously made a RNAi-based cytochrome P450 2b (Cyp2b)-knockdown (Cyp2b-KD) mouse to determine the in vivo role of the Cyp2b subfamily in xenobiotic detoxification. Further studies reported here indicate a role for Cyp2b in unsaturated fatty-acid (UFA) metabolism and in turn obesity. Mice were treated intraperitoneally (i.p.) with 100 μL corn oil as a carrier or the potent Cyp2b-inducer 3,3',5,5'-Tetrachloro-1,4-bis(pyridyloxy)benzene (TCPOBOP (TC)) dissolved in corn oil. Surprisingly, female Cyp2b-KD mice but not male mice showed increased liver lipid accumulation. Male Cyp2b-KD mice had higher serum triacylglycerols, cholesterol, very low-density lipoprotein (VLDL), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) than wildtype (WT) mice; females had higher cholesterol, LDL, and HDL. Thus, Cyp2b-KD mice are unable to clear a high bolus dose of corn oil, potentially because the Cyp2b-KD mice were unable to metabolize the UFA in the corn oil. Therefore, WT and Cyp2b-KD mice were housed for 35 weeks and necropsies performed to test whether Cyp2b-KD mice develop age onset obesity. Cyp2b-KD mice exhibited a significant increase in body weight caused by an increase in white adipose tissue deposition relative to WT mice. Serum cholesterol, triacylglycerol, LDL, and VLDL were significantly greater in 35-week-old Cyp2b-KD males compared to WT males; only serum triacylglycerol and LDL were higher in females. In conclusion, changes in Cyp2b expression led to perturbation in lipid metabolism and depuration in Cyp2b-KD mice. This suggests that Cyp2b is more than a detoxification enzyme, but also involved in the metabolism of UFA, as Cyp2b-KD mice have increased the body weight, fat deposition, and serum lipids.
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Affiliation(s)
- Basma Damiri
- Medicine and Health Sciences Faculty, Drugs and Toxicology Division, An-Najah National University, Omar Ibn Al-Khattab St., PO Box 7, Nablus, West Bank, Palestinian Territories
| | - William S Baldwin
- Biological Sciences, Clemson University, 132 Long Hall St., Clemson, SC 29634, USA.,Environmental Toxicology Program, 132 Long Hall St., Clemson University, Clemson, SC 29634, USA
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5
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Li L, Zhang QY, Ding X. A CYP2B6-humanized mouse model and its potential applications. Drug Metab Pharmacokinet 2018; 33:2-8. [PMID: 29402634 DOI: 10.1016/j.dmpk.2018.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 11/21/2017] [Accepted: 12/12/2017] [Indexed: 01/03/2023]
Abstract
CYP2B6 is a human microsomal cytochrome P450 enzyme with broad substrate selectivity. CYP2B6 is the only functional member of the human CYP2B gene subfamily, which differs from the situation in rodents, such as mouse, where multiple functional Cyp2b genes are expressed. Recent studies with Cyp2b knockout or knockdown mouse models have yielded insights into the in vivo roles of mouse CYP2B enzymes in drug disposition and xenobiotic toxicity. A CYP2B6-humanized mouse model (CYP2A13/2B6/2F1-transgenic/Cyp2abfgs-null), which expresses human CYP2B6 in the liver, and human CYP2A13 and CYP2F1 in the respiratory tract, but not any of the mouse Cyp2b genes, has also been established. In the CYP2B6-humanized mouse, the CYP2B6 transgene is expressed primarily in the liver, where it was found to be active toward prototype CYP2B6 substrate drugs. The regulatory elements of the CYP2B6 transgene appear to be compatible with mouse nuclear receptors that mediate CYP2B induction. Therefore, the CYP2B6-humanized mouse is a valuable animal model for studying the impact of CYP2B6 expression or induction on drug metabolism, drug efficacy, drug-drug interaction, and drug/xenobiotic toxicity. In this mini-review, we provide a brief background on CYP2B6 and the Cyp2b-knockout and CYP2B6-humanized mice, and discuss the potential applications and limitations of the current models.
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Affiliation(s)
- Lei Li
- Wadsworth Center, New York State Department of Health, School of Public Health, State University of New York at Albany, NY, 12201, USA
| | - Qing-Yu Zhang
- Department of Pharmacology and Toxicology, College of Pharmacy, University of Arizona, Tucson, AZ, 85721, USA
| | - Xinxin Ding
- Department of Pharmacology and Toxicology, College of Pharmacy, University of Arizona, Tucson, AZ, 85721, USA.
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6
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Yeles C, Vlachavas EI, Papadodima O, Pilalis E, Vorgias CE, Georgakilas AG, Chatziioannou A. Integrative Bioinformatic Analysis of Transcriptomic Data Identifies Conserved Molecular Pathways Underlying Ionizing Radiation-Induced Bystander Effects (RIBE). Cancers (Basel) 2017; 9:E160. [PMID: 29186820 PMCID: PMC5742808 DOI: 10.3390/cancers9120160] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 11/18/2017] [Accepted: 11/22/2017] [Indexed: 12/11/2022] Open
Abstract
Ionizing radiation-induced bystander effects (RIBE) encompass a number of effects with potential for a plethora of damages in adjacent non-irradiated tissue. The cascade of molecular events is initiated in response to the exposure to ionizing radiation (IR), something that may occur during diagnostic or therapeutic medical applications. In order to better investigate these complex response mechanisms, we employed a unified framework integrating statistical microarray analysis, signal normalization, and translational bioinformatics functional analysis techniques. This approach was applied to several microarray datasets from Gene Expression Omnibus (GEO) related to RIBE. The analysis produced lists of differentially expressed genes, contrasting bystander and irradiated samples versus sham-irradiated controls. Furthermore, comparative molecular analysis through BioInfoMiner, which integrates advanced statistical enrichment and prioritization methodologies, revealed discrete biological processes, at the cellular level. For example, the negative regulation of growth, cellular response to Zn2+-Cd2+, and Wnt and NIK/NF-kappaB signaling, thus refining the description of the phenotypic landscape of RIBE. Our results provide a more solid understanding of RIBE cell-specific response patterns, especially in the case of high-LET radiations, like α-particles and carbon-ions.
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Affiliation(s)
- Constantinos Yeles
- Department of Biochemistry and Molecular Biology, Faculty of Biology, National and Kapodistrian University of Athens, Zografou Campus, 15701 Athens, Greece; (C.Y.); (C.E.V.)
- Metabolic Engineering and Bioinformatics Research Team, Institute of Biology Medicinal Chemistry & Biotechnology, National Hellenic Research Foundation, 11635 Athens, Greece; (E.-I.V); (O.P.)
| | - Efstathios-Iason Vlachavas
- Metabolic Engineering and Bioinformatics Research Team, Institute of Biology Medicinal Chemistry & Biotechnology, National Hellenic Research Foundation, 11635 Athens, Greece; (E.-I.V); (O.P.)
- Department of Molecular Biology and Genetics, Democritus University of Thrace, 68100 Dragana, Greece
- Enios Applications Private Limited Company, A17671 Athens, Greece;
| | - Olga Papadodima
- Metabolic Engineering and Bioinformatics Research Team, Institute of Biology Medicinal Chemistry & Biotechnology, National Hellenic Research Foundation, 11635 Athens, Greece; (E.-I.V); (O.P.)
| | | | - Constantinos E. Vorgias
- Department of Biochemistry and Molecular Biology, Faculty of Biology, National and Kapodistrian University of Athens, Zografou Campus, 15701 Athens, Greece; (C.Y.); (C.E.V.)
| | - Alexandros G. Georgakilas
- Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), Zografou, 15780 Athens, Greece;
| | - Aristotelis Chatziioannou
- Metabolic Engineering and Bioinformatics Research Team, Institute of Biology Medicinal Chemistry & Biotechnology, National Hellenic Research Foundation, 11635 Athens, Greece; (E.-I.V); (O.P.)
- Enios Applications Private Limited Company, A17671 Athens, Greece;
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7
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Li L, Bao X, Zhang QY, Negishi M, Ding X. Role of CYP2B in Phenobarbital-Induced Hepatocyte Proliferation in Mice. Drug Metab Dispos 2017; 45:977-981. [PMID: 28546505 DOI: 10.1124/dmd.117.076406] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Accepted: 05/23/2017] [Indexed: 11/22/2022] Open
Abstract
Phenobarbital (PB) promotes liver tumorigenesis in rodents, in part through activation of the constitutive androstane receptor (CAR) and the consequent changes in hepatic gene expression and increases in hepatocyte proliferation. A typical effect of CAR activation by PB is a marked induction of Cyp2b10 expression in the liver; the latter has been suspected to be vital for PB-induced hepatocellular proliferation. This hypothesis was tested here by using a Cyp2a(4/5)bgs-null (null) mouse model in which all Cyp2b genes are deleted. Adult male and female wild-type (WT) and null mice were treated intraperitoneally with PB at 50 mg/kg once daily for 5 successive days and tested on day 6. The liver-to-body weight ratio, an indicator of liver hypertrophy, was increased by 47% in male WT mice, but by only 22% in male Cyp2a(4/5)bgs-null mice, by the PB treatment. The fractions of bromodeoxyuridine-positive hepatocyte nuclei, assessed as a measure of the rate of hepatocyte proliferation, were also significantly lower in PB-treated male null mice compared with PB-treated male WT mice. However, whereas few proliferating hepatocytes were detected in saline-treated mice, many proliferating hepatocytes were still detected in PB-treated male null mice. In contrast, female WT mice were much less sensitive than male WT mice to PB-induced hepatocyte proliferation, and PB-treated female WT and PB-treated female null mice did not show significant difference in rates of hepatocyte proliferation. These results indicate that CYP2B induction plays a significant, but partial, role in PB-induced hepatocyte proliferation in male mice.
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Affiliation(s)
- Lei Li
- College of Nanoscale Science, SUNY Polytechnic Institute, Albany, New York (L.L., X.D.); Wadsworth Center, New York State Department of Health, and School of Public Health, University at Albany, Albany, New York (L.L., X.B., Q.Z., X.D.); and National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina (M.N.)
| | - Xiaochen Bao
- College of Nanoscale Science, SUNY Polytechnic Institute, Albany, New York (L.L., X.D.); Wadsworth Center, New York State Department of Health, and School of Public Health, University at Albany, Albany, New York (L.L., X.B., Q.Z., X.D.); and National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina (M.N.)
| | - Qing-Yu Zhang
- College of Nanoscale Science, SUNY Polytechnic Institute, Albany, New York (L.L., X.D.); Wadsworth Center, New York State Department of Health, and School of Public Health, University at Albany, Albany, New York (L.L., X.B., Q.Z., X.D.); and National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina (M.N.)
| | - Masahiko Negishi
- College of Nanoscale Science, SUNY Polytechnic Institute, Albany, New York (L.L., X.D.); Wadsworth Center, New York State Department of Health, and School of Public Health, University at Albany, Albany, New York (L.L., X.B., Q.Z., X.D.); and National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina (M.N.)
| | - Xinxin Ding
- College of Nanoscale Science, SUNY Polytechnic Institute, Albany, New York (L.L., X.D.); Wadsworth Center, New York State Department of Health, and School of Public Health, University at Albany, Albany, New York (L.L., X.B., Q.Z., X.D.); and National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina (M.N.)
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8
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Clarkson MD. Representation of anatomy in online atlases and databases: a survey and collection of patterns for interface design. BMC DEVELOPMENTAL BIOLOGY 2016; 16:18. [PMID: 27206491 PMCID: PMC4875762 DOI: 10.1186/s12861-016-0116-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Accepted: 05/09/2016] [Indexed: 12/17/2022]
Abstract
BACKGROUND A large number of online atlases and databases have been developed to mange the rapidly growing amount of data describing embryogenesis. As these community resources continue to evolve, it is important to understand how representations of anatomy can facilitate the sharing and integration of data. In addition, attention to the design of the interfaces is critical to make online resources useful and usable. RESULTS I first present a survey of online atlases and gene expression resources for model organisms, with a focus on methods of semantic and spatial representation of anatomy. A total of 14 anatomical atlases and 21 gene expression resources are included. This survey demonstrates how choices in semantic representation, in the form of ontologies, can enhance interface search functions and provide links between relevant information. This survey also reviews methods for spatially representing anatomy in online resources. I then provide a collection of patterns for interface design based on the atlases and databases surveyed. These patterns include methods for displaying graphics, integrating semantic and spatial representations, organizing information, and querying databases to find genes expressed in anatomical structures. CONCLUSIONS This collection of patterns for interface design will assist biologists and software developers in planning the interfaces of new atlases and databases or enhancing existing ones. They also show the benefits of standardizing semantic and spatial representations of anatomy by demonstrating how interfaces can use standardization to provide enhanced functionality.
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Affiliation(s)
- Melissa D Clarkson
- Department of Biological Structure, School of Medicine, University of Washington, Seattle, WA, USA.
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9
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Mallika C, Guo Q, Li JYH. Gbx2 is essential for maintaining thalamic neuron identity and repressing habenular characters in the developing thalamus. Dev Biol 2015; 407:26-39. [PMID: 26297811 DOI: 10.1016/j.ydbio.2015.08.010] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2015] [Revised: 08/10/2015] [Accepted: 08/12/2015] [Indexed: 12/30/2022]
Abstract
The thalamus and habenula, two important nodes of the forebrain circuitry, are derived from a single developmental compartment, called prosomere 2, in the diencephalon. Habenular and thalamic neurons display distinct molecular identity, neurochemistry, and connectivity. Furthermore, their progenitors exhibit distinctive neurogenic patterns with a marked delay in the onset of neurogenesis in the thalamus. However, the progenitors in prosomere 2 express many common developmental regulators and the mechanism underlying the specification and differentiation of these two populations of neurons remains unknown. Gbx2, coding for a homeodomain transcription factor, is initially expressed in thalamic neuronal precursors that have just exited the cell cycle, and its expression is maintained in many mature thalamic neurons in adults. Deletion of Gbx2 severely disrupts histogenesis of the thalamus and abolishes thalamocortical projections in mice. Here, by using genome-wide transcriptional profiling, we show that Gbx2 promotes thalamic but inhibits habenular molecular characters. Remarkably, although Gbx2 is expressed in postmitotic neuronal precursors, deletion of Gbx2 changes gene expression and cell proliferation in dividing progenitors in the developing thalamus. These defects are partially rescued by the mosaic presence of wild-type cells, demonstrating a cell non-autonomous role of Gbx2 in regulating the development of thalamic progenitors. Our results suggest that Gbx2 is essential for the acquisition of the thalamic neuronal identity by repressing habenular identity through a feedback signaling from postmitotic neurons to progenitors.
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Affiliation(s)
- Chatterjee Mallika
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, 400 Farmington Avenue, Farmington, CT 06030-6403, United States
| | - Qiuxia Guo
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, 400 Farmington Avenue, Farmington, CT 06030-6403, United States
| | - James Y H Li
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, 400 Farmington Avenue, Farmington, CT 06030-6403, United States.
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10
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Tsai PH, Chien Y, Chuang JH, Chou SJ, Chien CH, Lai YH, Li HY, Ko YL, Chang YL, Wang CY, Liu YY, Lee HC, Yang CH, Tsai TF, Lee YY, Chiou SH. Dysregulation of Mitochondrial Functions and Osteogenic Differentiation in Cisd2-Deficient Murine Induced Pluripotent Stem Cells. Stem Cells Dev 2015; 24:2561-76. [PMID: 26230298 DOI: 10.1089/scd.2015.0066] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Wolfram syndrome 2 (WFS2) is a premature aging syndrome caused by an irreversible mitochondria-mediated disorder. Cisd2, which regulates mitochondrial electron transport, has been recently identified as the causative gene of WFS2. The mouse Cisd2 knockout (KO) (Cisd2(-/-)) recapitulates most of the clinical manifestations of WFS2, including growth retardation, osteopenia, and lordokyphosis. However, the precise mechanisms underlying osteopenia in WFS2 and Cisd2 KO mice remain unknown. In this study, we collected embryonic fibroblasts from Cisd2-deficient embryos and reprogrammed them into induced pluripotent stem cells (iPSCs) via retroviral transduction with Oct4/Sox2/Klf4/c-Myc. Cisd2-deficient mouse iPSCs (miPSCs) exhibited structural abnormalities in their mitochondria and an impaired proliferative capability. The global gene expression profiles of Cisd2(+/+), Cisd2(+/-), and Cisd2(-/-) miPSCs revealed that Cisd2 functions as a regulator of both mitochondrial electron transport and Wnt/β-catenin signaling, which is critical for cell proliferation and osteogenic differentiation. Notably, Cisd2(-/-) miPSCs exhibited impaired Wnt/β-catenin signaling, with the downregulation of downstream genes, such as Tcf1, Fosl1, and Jun and the osteogenic regulator Runx2. Several differentiation markers for tridermal lineages were globally impaired in Cisd2(-/-) miPSCs. Alizarin red S staining and flow cytometry analysis further revealed that Cisd2(-/-) miPSCs failed to undergo osteogenic differentiation. Taken together, our results, as determined using an miPSC-based platform, have demonstrated that Cisd2 regulates mitochondrial function, proliferation, intracellular Ca(2+) homeostasis, and Wnt pathway signaling. Cisd2 deficiency impairs the activation of Wnt/β-catenin signaling and thereby contributes to the pathogeneses of osteopenia and lordokyphosis in WFS2 patients.
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Affiliation(s)
- Ping-Hsing Tsai
- 1 Institute of Pharmacology, National Yang-Ming University , Taipei, Taiwan
| | - Yueh Chien
- 1 Institute of Pharmacology, National Yang-Ming University , Taipei, Taiwan .,2 Department of Medical Research, Taipei Veterans General Hospital , Taipei, Taiwan
| | - Jen-Hua Chuang
- 2 Department of Medical Research, Taipei Veterans General Hospital , Taipei, Taiwan .,3 Institute of Clinical Medicine, National Yang-Ming University , Taipei, Taiwan
| | - Shih-Jie Chou
- 1 Institute of Pharmacology, National Yang-Ming University , Taipei, Taiwan
| | - Chian-Hsu Chien
- 2 Department of Medical Research, Taipei Veterans General Hospital , Taipei, Taiwan .,3 Institute of Clinical Medicine, National Yang-Ming University , Taipei, Taiwan
| | - Ying-Hsiu Lai
- 4 Institute of Anatomy & Cell Biology, National Yang-Ming University , Taipei, Taiwan
| | - Hsin-Yang Li
- 4 Institute of Anatomy & Cell Biology, National Yang-Ming University , Taipei, Taiwan .,5 School of Medicine, National Yang-Ming University , Taipei, Taiwan .,6 Department of Obstetrics and Gynecology, Neurological Institute , Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yu-Lin Ko
- 2 Department of Medical Research, Taipei Veterans General Hospital , Taipei, Taiwan .,5 School of Medicine, National Yang-Ming University , Taipei, Taiwan
| | - Yuh-Lih Chang
- 1 Institute of Pharmacology, National Yang-Ming University , Taipei, Taiwan .,7 Department of Pharmacy, Neurological Institute , Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chen-Ying Wang
- 5 School of Medicine, National Yang-Ming University , Taipei, Taiwan
| | - Yung-Yang Liu
- 2 Department of Medical Research, Taipei Veterans General Hospital , Taipei, Taiwan .,3 Institute of Clinical Medicine, National Yang-Ming University , Taipei, Taiwan
| | - Hsin-Chen Lee
- 1 Institute of Pharmacology, National Yang-Ming University , Taipei, Taiwan .,5 School of Medicine, National Yang-Ming University , Taipei, Taiwan
| | - Chang-Hao Yang
- 8 Department of Ophthalmology, National Taiwan University Hospital , Taipei, Taiwan
| | - Ting-Fen Tsai
- 9 Department of Life Sciences & Institute of Genome Sciences, National Yang-Ming University , Taipei, Taiwan
| | - Yi-Yen Lee
- 3 Institute of Clinical Medicine, National Yang-Ming University , Taipei, Taiwan .,10 Department of Neurosurgery, Neurological Institute , Taipei Veterans General Hospital, Taipei, Taiwan
| | - Shih-Hwa Chiou
- 1 Institute of Pharmacology, National Yang-Ming University , Taipei, Taiwan .,2 Department of Medical Research, Taipei Veterans General Hospital , Taipei, Taiwan .,3 Institute of Clinical Medicine, National Yang-Ming University , Taipei, Taiwan .,4 Institute of Anatomy & Cell Biology, National Yang-Ming University , Taipei, Taiwan
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11
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Finger JH, Smith CM, Hayamizu TF, McCright IJ, Xu J, Eppig JT, Kadin JA, Richardson JE, Ringwald M. The mouse gene expression database: New features and how to use them effectively. Genesis 2015; 53:510-22. [PMID: 26045019 DOI: 10.1002/dvg.22864] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Revised: 05/29/2015] [Accepted: 06/01/2015] [Indexed: 12/15/2022]
Abstract
The Gene Expression Database (GXD) is an extensive and freely available community resource of mouse developmental expression data. GXD curates and integrates expression data from the literature, via electronic data submissions, and by collaborations with large-scale projects. As an integral component of the Mouse Genome Informatics Resource, GXD combines expression data with genetic, functional, phenotypic, and disease-related data, and provides tools for the research community to search for and analyze expression data in this larger context. Recent enhancements include: an interactive browser to navigate the mouse developmental anatomy and find expression data for specific anatomical structures; the capability to search for expression data of genes located in specific genomic regions, supporting the identification of disease candidate genes; a summary displaying all the expression images that meet specified search criteria; interactive matrix views that provide overviews of spatio-temporal expression patterns (Tissue × Stage Matrix) and enable the comparison of expression patterns between genes (Tissue × Gene Matrix); data zoom and filter utilities to iteratively refine summary displays and data sets; and gene-based links to expression data from other model organisms, such as chicken, Xenopus, and zebrafish, fostering comparative expression analysis for species that are highly relevant for developmental research.
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Affiliation(s)
| | | | | | | | - Jingxia Xu
- The Jackson Laboratory, Bar Harbor, Maine
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12
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Li HD, Omenn GS, Guan Y. MIsoMine: a genome-scale high-resolution data portal of expression, function and networks at the splice isoform level in the mouse. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2015; 2015:bav045. [PMID: 25953081 PMCID: PMC4423410 DOI: 10.1093/database/bav045] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2015] [Accepted: 04/15/2015] [Indexed: 12/22/2022]
Abstract
Products of multiexon genes, especially in higher organisms, are a mixture of isoforms with different or even opposing functions, and therefore need to be treated separately. However, most studies and available resources such as Gene Ontology provide only gene-level function annotations, and therefore lose the differential information at the isoform level. Here we report MIsoMine, a high-resolution portal to multiple levels of functional information of alternatively spliced isoforms in the mouse. This data portal provides tissue-specific expression patterns and co-expression networks, along with such previously published functional genomic data as protein domains, predicted isoform-level functions and functional relationships. The core utility of MIsoMine is allowing users to explore a preprocessed, quality-controlled set of RNA-seq data encompassing diverse tissues and cell lineages. Tissue-specific co-expression networks were established, allowing a 2D ranking of isoforms and tissues by co-expression patterns. The results of the multiple isoforms of the same gene are presented in parallel to facilitate direct comparison, with cross-talking to prioritized functions at the isoform level. MIsoMine provides the first isoform-level resolution effort at genome-scale. We envision that this data portal will be a valuable resource for exploring functional genomic data, and will complement the existing functionalities of the mouse genome informatics database and the gene expression database for the laboratory mouse. Database URL: http://guanlab.ccmb.med.umich.edu/misomine/
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Affiliation(s)
- Hong-Dong Li
- Department of Computational Medicine and Bioinformatics, Department of Internal Medicine and Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
| | - Gilbert S Omenn
- Department of Computational Medicine and Bioinformatics, Department of Internal Medicine and Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Internal Medicine and Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yuanfang Guan
- Department of Computational Medicine and Bioinformatics, Department of Internal Medicine and Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Internal Medicine and Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Internal Medicine and Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
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13
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Smith CM, Finger JH, Hayamizu TF, McCright IJ, Xu J, Eppig JT, Kadin JA, Richardson JE, Ringwald M. GXD: a community resource of mouse Gene Expression Data. Mamm Genome 2015; 26:314-24. [PMID: 25939429 PMCID: PMC4534488 DOI: 10.1007/s00335-015-9563-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Accepted: 04/13/2015] [Indexed: 12/23/2022]
Abstract
The Gene Expression Database (GXD) is an extensive, easily searchable, and freely available database of mouse gene expression information (www.informatics.jax.org/expression.shtml). GXD was developed to foster progress toward understanding the molecular basis of human development and disease. GXD contains information about when and where genes are expressed in different tissues in the mouse, especially during the embryonic period. GXD collects different types of expression data from wild-type and mutant mice, including RNA in situ hybridization, immunohistochemistry, RT-PCR, and northern and western blot results. The GXD curators read the scientific literature and enter the expression data from those papers into the database. GXD also acquires expression data directly from researchers, including groups doing large-scale expression studies. GXD currently contains nearly 1.5 million expression results for over 13,900 genes. In addition, it has over 265,000 images of expression data, allowing users to retrieve the primary data and interpret it themselves. By being an integral part of the larger Mouse Genome Informatics (MGI) resource, GXD’s expression data are combined with other genetic, functional, phenotypic, and disease-oriented data. This allows GXD to provide tools for researchers to evaluate expression data in the larger context, search by a wide variety of biologically and biomedically relevant parameters, and discover new data connections to help in the design of new experiments. Thus, GXD can provide researchers with critical insights into the functions of genes and the molecular mechanisms of development, differentiation, and disease.
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Affiliation(s)
| | | | | | | | - Jingxia Xu
- The Jackson Laboratory, Bar Harbor, ME 04609 USA
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14
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Beck S, Lee BK, Rhee C, Song J, Woo AJ, Kim J. CpG island-mediated global gene regulatory modes in mouse embryonic stem cells. Nat Commun 2014; 5:5490. [PMID: 25405324 PMCID: PMC4236720 DOI: 10.1038/ncomms6490] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2014] [Accepted: 10/03/2014] [Indexed: 12/13/2022] Open
Abstract
Both transcriptional and epigenetic regulations are fundamental for the control of eukaryotic gene expression. Here we perform a compendium analysis of >200 large sequencing data sets to elucidate the regulatory logic of global gene expression programs in mouse embryonic stem (ES) cells. We define four major classes of DNA-binding proteins (Core, PRC, MYC and CTCF) based on their target co-occupancy, and discover reciprocal regulation between the MYC and PRC classes for the activity of nearly all genes under the control of the CpG island (CGI)-containing promoters. This CGI-dependent regulatory mode explains the functional segregation between CGI-containing and CGI-less genes during early development. By defining active enhancers based on the co-occupancy of the Core class, we further demonstrate their additive roles in CGI-containing gene expression and cell type-specific roles in CGI-less gene expression. Altogether, our analyses provide novel insights into previously unknown CGI-dependent global gene regulatory modes.
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Affiliation(s)
- Samuel Beck
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Bum-Kyu Lee
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Catherine Rhee
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Jawon Song
- Texas Advanced Computing Center, The University of Texas at Austin, Austin, Texas 78758, USA
| | - Andrew J Woo
- School of Medicine and Pharmacology, Royal Perth Hospital Unit, The University of Western Australia, Perth, WA 6000, Australia
| | - Jonghwan Kim
- 1] Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas 78712, USA [2] Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas 78712, USA [3] Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712, USA
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15
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Landin Malt A, Cesario JM, Tang Z, Brown S, Jeong J. Identification of a face enhancer reveals direct regulation of LIM homeobox 8 (Lhx8) by wingless-int (WNT)/β-catenin signaling. J Biol Chem 2014; 289:30289-30301. [PMID: 25190800 DOI: 10.1074/jbc.m114.592014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Development of the mammalian face requires a large number of genes that are expressed with spatio-temporal specificity, and transcriptional regulation mediated by enhancers plays a key role in the precise control of gene expression. Using chromatin immunoprecipitation for a histone marker of active enhancers, we generated a genome-wide map of candidate enhancers from the maxillary arch (primordium for the upper jaw) of mouse embryos. Furthermore, we confirmed multiple novel craniofacial enhancers near the genes implicated in human palate defects through functional assays. We characterized in detail one of the enhancers (Lhx8_enh1) located upstream of Lhx8, a key regulatory gene for craniofacial development. Lhx8_enh1 contained an evolutionarily conserved binding site for lymphoid enhancer factor/T-cell factor family proteins, which mediate the transcriptional regulation by the WNT/β-catenin signaling pathway. We demonstrated in vitro that WNT/β-catenin signaling was indeed essential for the expression of Lhx8 in the maxillary arch cells and that Lhx8_enh1 was a direct target of the WNT/β-catenin pathway. Together, we uncovered a molecular mechanism for the regulation of Lhx8, and we provided valuable resources for further investigation into the gene regulatory network of craniofacial development.
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Affiliation(s)
- André Landin Malt
- Department of Basic Science and Craniofacial Biology, New York University College of Dentistry, New York, New York 10010 and
| | - Jeffry M Cesario
- Department of Basic Science and Craniofacial Biology, New York University College of Dentistry, New York, New York 10010 and
| | - Zuojian Tang
- Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York 10016
| | - Stuart Brown
- Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York 10016
| | - Juhee Jeong
- Department of Basic Science and Craniofacial Biology, New York University College of Dentistry, New York, New York 10010 and.
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16
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Matthes M, Preusse M, Zhang J, Schechter J, Mayer D, Lentes B, Theis F, Prakash N, Wurst W, Trümbach D. Mouse IDGenes: a reference database for genetic interactions in the developing mouse brain. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2014; 2014:bau083. [PMID: 25145340 PMCID: PMC4139671 DOI: 10.1093/database/bau083] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The study of developmental processes in the mouse and other vertebrates includes the understanding of patterning along the anterior–posterior, dorsal–ventral and medial– lateral axis. Specifically, neural development is also of great clinical relevance because several human neuropsychiatric disorders such as schizophrenia, autism disorders or drug addiction and also brain malformations are thought to have neurodevelopmental origins, i.e. pathogenesis initiates during childhood and adolescence. Impacts during early neurodevelopment might also predispose to late-onset neurodegenerative disorders, such as Parkinson’s disease. The neural tube develops from its precursor tissue, the neural plate, in a patterning process that is determined by compartmentalization into morphogenetic units, the action of local signaling centers and a well-defined and locally restricted expression of genes and their interactions. While public databases provide gene expression data with spatio-temporal resolution, they usually neglect the genetic interactions that govern neural development. Here, we introduce Mouse IDGenes, a reference database for genetic interactions in the developing mouse brain. The database is highly curated and offers detailed information about gene expressions and the genetic interactions at the developing mid-/hindbrain boundary. To showcase the predictive power of interaction data, we infer new Wnt/β-catenin target genes by machine learning and validate one of them experimentally. The database is updated regularly. Moreover, it can easily be extended by the research community. Mouse IDGenes will contribute as an important resource to the research on mouse brain development, not exclusively by offering data retrieval, but also by allowing data input. Database URL:http://mouseidgenes.helmholtz-muenchen.de.
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Affiliation(s)
- Michaela Matthes
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-In
| | - Martin Preusse
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-In
| | - Jingzhong Zhang
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany
| | - Julia Schechter
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany
| | - Daniela Mayer
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany
| | - Bernd Lentes
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany
| | - Fabian Theis
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-In
| | - Nilima Prakash
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany
| | - Wolfgang Wurst
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-In
| | - Dietrich Trümbach
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 München, Germany, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Standort München, Schillerstr. 44, 80336 München, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Entwicklungsgenetik, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany and Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Schillerstr. 44, 80336 München, Germany Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München-Weihenstephan, Lehrstuhl für Genetik, Emil-Ramannstr. 8, 85354 Freising, Germany, Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Technische Universität München, Zentrum Mathematik, Boltzmannstr. 3, 85747 Garching, Germany, Max-Planck-In
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17
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Comparative study of the molecular variation between ‘central’ and ‘peripheral’ MUPs and significance for behavioural signalling. Biochem Soc Trans 2014; 42:866-72. [DOI: 10.1042/bst20140082] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
MUPs (major urinary proteins) play an important role in chemical signalling in rodents and possibly other animals. In the house mouse (Mus musculus domesticus) MUPs in urine and other bodily fluids trigger a range of behavioural responses that are only partially understood. There are at least 21 Mup genes in the C57BL/6 mouse genome, all located on chromosome 4, encoding sequences of high similarity. Further analysis separates the MUPs into two groups, the ‘central’ near-identical MUPs with over 97% sequence identity and the ‘peripheral’ MUPs with a greater degree of heterogeneity and approximately 20–30% non-conserved amino acids. This review focuses on differences between the two MUP sub-groups and categorizes these changes in terms of molecular structure and pheromone binding. As small differences in amino acid sequence can result in marked changes in behavioural response to the signal, we explore the potential of single amino acid changes to affect chemical signalling and protein stabilization. Using analysis of existing molecular structures available in the PDB we compare the chemical and physical properties of the ligand cavities between the MUPs. Furthermore, we identify differences on the solvent exposed surfaces of the proteins, which are characteristic of protein–protein interaction sites. Correlations can be seen between molecular heterogeneity and the specialized roles attributed to some MUPs.
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18
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Qin J, Sontag S, Lin Q, Mitzka S, Leisten I, Schneider RK, Wang X, Jauch A, Peitz M, Brüstle O, Wagner W, Zhao RC, Zenke M. Cell fusion enhances mesendodermal differentiation of human induced pluripotent stem cells. Stem Cells Dev 2014; 23:2875-82. [PMID: 25004077 DOI: 10.1089/scd.2014.0120] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Human induced pluripotent stem cells (iPS cells) resemble embryonic stem cells and can differentiate into cell derivatives of all three germ layers. However, frequently the differentiation efficiency of iPS cells into some lineages is rather poor. Here, we found that fusion of iPS cells with human hematopoietic stem cells (HSCs) enhances iPS cell differentiation. Such iPS hybrids showed a prominent differentiation bias toward hematopoietic lineages but also toward other mesendodermal lineages. Additionally, during differentiation of iPS hybrids, expression of early mesendodermal markers-Brachyury (T), MIX1 Homeobox-Like Protein 1 (MIXL1), and Goosecoid (GSC)-appeared with faster kinetics than in parental iPS cells. Following iPS hybrid differentiation there was a prominent induction of NODAL and inhibition of NODAL signaling blunted mesendodermal differentiation. This indicates that NODAL signaling is critically involved in mesendodermal bias of iPS hybrid differentiation. In summary, we demonstrate that iPS cell fusion with HSCs prominently enhances iPS cell differentiation.
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Affiliation(s)
- Jie Qin
- 1 Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School , Aachen, Germany
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19
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Differences in gene expression between mouse and human for dynamically regulated genes in early embryo. PLoS One 2014; 9:e102949. [PMID: 25089626 PMCID: PMC4121084 DOI: 10.1371/journal.pone.0102949] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2014] [Accepted: 06/24/2014] [Indexed: 11/19/2022] Open
Abstract
Infertility is a worldwide concern that can be treated with in vitro fertilization (IVF). Improvements in IVF and infertility treatment depend largely on better understanding of the molecular mechanisms for human preimplantation development. Several large-scale studies have been conducted to identify gene expression patterns for the first five days of human development, and many functional studies utilize mouse as a model system. We have identified genes of possible importance for this time period by analyzing human microarray data and available data from online databases. We selected 70 candidate genes for human preimplantation development and investigated their expression in the early mouse development from oocyte to the 8-cell stage. Maternally loaded genes expectedly decreased in expression during development both in human and mouse. We discovered that 25 significantly upregulated genes after fertilization in human included 13 genes whose orthologs in mouse behaved differently and mimicked the expression profile of maternally expressed genes. Our findings highlight many significant differences in gene expression patterns during mouse and human preimplantation development. We also describe four cancer-testis antigen families that are also highly expressed in human embryos: PRAME, SSX, GAGE and MAGEA.
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20
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Lin CC, Chang YM, Pan CT, Chen CC, Ling L, Tsao KC, Yang RB, Li WH. Functional evolution of cardiac microRNAs in heart development and functions. Mol Biol Evol 2014; 31:2722-34. [PMID: 25063441 DOI: 10.1093/molbev/msu217] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
MicroRNAs (miRNAs) are a class of endogenous small noncoding RNAs that regulate gene expression either by degrading target mRNAs or by suppressing protein translation. miRNAs have been found to be involved in many biological processes, such as development, differentiation, and growth. However, the evolution of miRNA regulatory functions and networks has not been well studied. In this study, we conducted a cross-species analysis to study the evolution of cardiac miRNAs and their regulatory functions and networks. We found that conserved cardiac miRNA target genes have maintained highly conserved cardiac functions. Additionally, most of cardiac miRNA target genes in human with annotations of cardiac functions evolved from the corresponding homologous targets, which are also involved in heart development-related functions. On the basis of these results, we investigated the functional evolution of cardiac miRNAs and presented a functional evolutionary map. From this map, we identified the evolutionary time at which the cardiac miRNAs became involved in heart development or function and found that the biological processes of heart development evolved earlier than those of heart functions, for example, heart contraction/relaxation or cardiac hypertrophy. Our study of the evolution of the cardiac miRNA regulatory networks revealed the emergence of new regulatory functional branches during evolution. Furthermore, we discovered that early evolved cardiac miRNA target genes tend to participate in the early stages of heart development. This study sheds light on the evolution of developmental features of genes regulated by cardiac miRNAs.
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Affiliation(s)
- Chen-Ching Lin
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan Department of Ecology and Evolution, University of Chicago
| | - Yao-Ming Chang
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan Department of Ecology and Evolution, University of Chicago
| | - Cheng-Tsung Pan
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
| | - Chien-Chang Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Li Ling
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Ku-Chi Tsao
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Ruey-Bing Yang
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Wen-Hsiung Li
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan Department of Ecology and Evolution, University of Chicago
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21
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Stottmann R, Beier DR. ENU Mutagenesis in the Mouse. CURRENT PROTOCOLS IN HUMAN GENETICS 2014; 82:15.4.1-15.4.10. [PMID: 25042716 PMCID: PMC4113905 DOI: 10.1002/0471142905.hg1504s82] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
This unit describes the treatment of laboratory mice with the mutagen N-ethyl-N-nitrosourea (ENU) to induce very highly increased rates of mutation throughout the genome. Further, it describes several popular mating schemes designed to produce animals displaying phenotypes associated with the induced mutations.
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Affiliation(s)
- Rolf Stottmann
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - David R. Beier
- Center for Developmental Biology and Regenerative Medicine, Seattle Children’s Research Institute
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22
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Smith CM, Finger JH, Kadin JA, Richardson JE, Ringwald M. The gene expression database for mouse development (GXD): putting developmental expression information at your fingertips. Dev Dyn 2014; 243:1176-86. [PMID: 24958384 DOI: 10.1002/dvdy.24155] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2014] [Revised: 05/16/2014] [Accepted: 06/17/2014] [Indexed: 12/15/2022] Open
Abstract
Because molecular mechanisms of development are extraordinarily complex, the understanding of these processes requires the integration of pertinent research data. Using the Gene Expression Database for Mouse Development (GXD) as an example, we illustrate the progress made toward this goal, and discuss relevant issues that apply to developmental databases and developmental research in general. Since its first release in 1998, GXD has served the scientific community by integrating multiple types of expression data from publications and electronic submissions and by making these data freely and widely available. Focusing on endogenous gene expression in wild-type and mutant mice and covering data from RNA in situ hybridization, in situ reporter (knock-in), immunohistochemistry, reverse transcriptase-polymerase chain reaction, Northern blot, and Western blot experiments, the database has grown tremendously over the years in terms of data content and search utilities. Currently, GXD includes over 1.4 million annotated expression results and over 260,000 images. All these data and images are readily accessible to many types of database searches. Here we describe the data and search tools of GXD; explain how to use the database most effectively; discuss how we acquire, curate, and integrate developmental expression information; and describe how the research community can help in this process.
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23
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Abstract
This article describes the treatment of laboratory mice with the mutagen N-ethyl-N-nitrosourea (ENU) to induce very highly increased rates of mutation throughout the genome. Further, it describes several popular mating schemes designed to produce animals displaying phenotypes associated with the induced mutations.
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Affiliation(s)
- Rolf Stottmann
- Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
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24
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Stachelscheid H, Seltmann S, Lekschas F, Fontaine JF, Mah N, Neves M, Andrade-Navarro MA, Leser U, Kurtz A. CellFinder: a cell data repository. Nucleic Acids Res 2013; 42:D950-8. [PMID: 24304896 PMCID: PMC3965082 DOI: 10.1093/nar/gkt1264] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
CellFinder (http://www.cellfinder.org) is a comprehensive one-stop resource for molecular data characterizing mammalian cells in different tissues and in different development stages. It is built from carefully selected data sets stemming from other curated databases and the biomedical literature. To date, CellFinder describes 3394 cell types and 50 951 cell lines. The database currently contains 3055 microscopic and anatomical images, 205 whole-genome expression profiles of 194 cell/tissue types from RNA-seq and microarrays and 553 905 protein expressions for 535 cells/tissues. Text mining of a corpus of >2000 publications followed by manual curation confirmed expression information on ∼900 proteins and genes. CellFinder’s data model is capable to seamlessly represent entities from single cells to the organ level, to incorporate mappings between homologous entities in different species and to describe processes of cell development and differentiation. Its ontological backbone currently consists of 204 741 ontology terms incorporated from 10 different ontologies unified under the novel CELDA ontology. CellFinder’s web portal allows searching, browsing and comparing the stored data, interactive construction of developmental trees and navigating the partonomic hierarchy of cells and tissues through a unique body browser designed for life scientists and clinicians.
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Affiliation(s)
- Harald Stachelscheid
- Berlin Brandenburg Center for Regenerative Medicine, Charité - Universitätsmedizin Berlin, Berlin 13353, Germany, Max Delbrück Center for Molecular Medicine, Computational Biology and Data Mining, Berlin 13125, Germany, Humboldt Universität zu Berlin, Institute for Computer Science, Berlin 10099, Germany and Seoul National University, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul 151-742, Republic of Korea
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25
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Smith CM, Finger JH, Hayamizu TF, McCright IJ, Xu J, Berghout J, Campbell J, Corbani LE, Forthofer KL, Frost PJ, Miers D, Shaw DR, Stone KR, Eppig JT, Kadin JA, Richardson JE, Ringwald M. The mouse Gene Expression Database (GXD): 2014 update. Nucleic Acids Res 2013; 42:D818-24. [PMID: 24163257 PMCID: PMC3965015 DOI: 10.1093/nar/gkt954] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The Gene Expression Database (GXD; http://www.informatics.jax.org/expression.shtml) is an extensive and well-curated community resource of mouse developmental expression information. GXD collects different types of expression data from studies of wild-type and mutant mice, covering all developmental stages and including data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments. The data are acquired from the scientific literature and from researchers, including groups doing large-scale expression studies. Integration with the other data in Mouse Genome Informatics (MGI) and interconnections with other databases places GXD's gene expression information in the larger biological and biomedical context. Since the last report, the utility of GXD has been greatly enhanced by the addition of new data and by the implementation of more powerful and versatile search and display features. Web interface enhancements include the capability to search for expression data for genes associated with specific phenotypes and/or human diseases; new, more interactive data summaries; easy downloading of data; direct searches of expression images via associated metadata; and new displays that combine image data and their associated annotations. At present, GXD includes >1.4 million expression results and 250,000 images that are accessible to our search tools.
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26
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Antin PB, Yatskievych TA, Davey S, Darnell DK. GEISHA: an evolving gene expression resource for the chicken embryo. Nucleic Acids Res 2013; 42:D933-7. [PMID: 24150938 PMCID: PMC3964962 DOI: 10.1093/nar/gkt962] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
GEISHA (Gallus Expression In Situ Hybridization Analysis; http://geisha.arizona.edu) is an in situ hybridization gene expression and genomic resource for the chicken embryo. This update describes modifications that enhance its utility to users. During the past 5 years, GEISHA has undertaken a significant restructuring to more closely conform to the data organization and formatting of Model Organism Databases in other species. This has involved migrating from an entry-centric format to one that is gene-centered. Database restructuring has enabled the inclusion of data pertaining to chicken genes and proteins and their orthologs in other species. This new information is presented through an updated user interface. In situ hybridization data in mouse, frog, zebrafish and fruitfly are integrated with chicken genomic and expression information. A resource has also been developed that integrates the GEISHA interface information with the Online Mendelian Inheritance in Man human disease gene database. Finally, the Chicken Gene Nomenclature Committee database and the GEISHA database have been integrated so that they draw from the same data resources.
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Affiliation(s)
- Parker B Antin
- Molecular Cardiovascular Research Program, Department of Cellular and Molecular Medicine, University of Arizona, Tucson, AZ 85724, USA
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27
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Wenger AM, Clarke SL, Notwell JH, Chung T, Tuteja G, Guturu H, Schaar BT, Bejerano G. The enhancer landscape during early neocortical development reveals patterns of dense regulation and co-option. PLoS Genet 2013; 9:e1003728. [PMID: 24009522 PMCID: PMC3757057 DOI: 10.1371/journal.pgen.1003728] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2013] [Accepted: 07/03/2013] [Indexed: 11/18/2022] Open
Abstract
Genetic studies have identified a core set of transcription factors and target genes that control the development of the neocortex, the region of the human brain responsible for higher cognition. The specific regulatory interactions between these factors, many key upstream and downstream genes, and the enhancers that mediate all these interactions remain mostly uncharacterized. We perform p300 ChIP-seq to identify over 6,600 candidate enhancers active in the dorsal cerebral wall of embryonic day 14.5 (E14.5) mice. Over 95% of the peaks we measure are conserved to human. Eight of ten (80%) candidates tested using mouse transgenesis drive activity in restricted laminar patterns within the neocortex. GREAT based computational analysis reveals highly significant correlation with genes expressed at E14.5 in key areas for neocortex development, and allows the grouping of enhancers by known biological functions and pathways for further studies. We find that multiple genes are flanked by dozens of candidate enhancers each, including well-known key neocortical genes as well as suspected and novel genes. Nearly a quarter of our candidate enhancers are conserved well beyond mammals. Human and zebrafish regions orthologous to our candidate enhancers are shown to most often function in other aspects of central nervous system development. Finally, we find strong evidence that specific interspersed repeat families have contributed potentially key developmental enhancers via co-option. Our analysis expands the methodologies available for extracting the richness of information found in genome-wide functional maps.
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Affiliation(s)
- Aaron M. Wenger
- Department of Computer Science, Stanford University, Stanford, California, United States of America
| | - Shoa L. Clarke
- Department of Genetics, Stanford University, Stanford, California, United States of America
| | - James H. Notwell
- Department of Computer Science, Stanford University, Stanford, California, United States of America
| | - Tisha Chung
- Department of Developmental Biology, Stanford University, Stanford, California, United States of America
| | - Geetu Tuteja
- Department of Developmental Biology, Stanford University, Stanford, California, United States of America
| | - Harendra Guturu
- Department of Electrical Engineering, Stanford University, Stanford, California, United States of America
| | - Bruce T. Schaar
- Department of Developmental Biology, Stanford University, Stanford, California, United States of America
| | - Gill Bejerano
- Department of Computer Science, Stanford University, Stanford, California, United States of America
- Department of Developmental Biology, Stanford University, Stanford, California, United States of America
- * E-mail:
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28
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TBX3 Directs Cell-Fate Decision toward Mesendoderm. Stem Cell Reports 2013; 1:248-65. [PMID: 24319661 PMCID: PMC3849240 DOI: 10.1016/j.stemcr.2013.08.002] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2013] [Revised: 08/06/2013] [Accepted: 08/07/2013] [Indexed: 12/19/2022] Open
Abstract
Cell-fate decisions and pluripotency are dependent on networks of key transcriptional regulators. Recent reports demonstrated additional functions of pluripotency-associated factors during early lineage commitment. The T-box transcription factor TBX3 has been implicated in regulating embryonic stem cell self-renewal and cardiogenesis. Here, we show that TBX3 is dynamically expressed during specification of the mesendoderm lineages in differentiating embryonic stem cells (ESCs) in vitro and in developing mouse and Xenopus embryos in vivo. Forced TBX3 expression in ESCs promotes mesendoderm specification by directly activating key lineage specification factors and indirectly by enhancing paracrine Nodal/Smad2 signaling. TBX3 loss-of-function analyses in the Xenopus underline its requirement for mesendoderm lineage commitment. Moreover, we uncovered a functional redundancy between TBX3 and Tbx2 during Xenopus gastrulation. Taken together, we define further facets of TBX3 actions and map TBX3 as an upstream regulator of the mesendoderm transcriptional program during gastrulation. T-box transcription factor TBX3 is involved in early embryonic events Key transcription factor promoters of mesendoderm formation are occupied by TBX3 TBX3 promotes mesendodermal fate of mESCs
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Hayamizu TF, Wicks MN, Davidson DR, Burger A, Ringwald M, Baldock RA. EMAP/EMAPA ontology of mouse developmental anatomy: 2013 update. J Biomed Semantics 2013; 4:15. [PMID: 23972281 PMCID: PMC3851555 DOI: 10.1186/2041-1480-4-15] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2013] [Accepted: 08/19/2013] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The Edinburgh Mouse Atlas Project (EMAP) ontology of mouse developmental anatomy provides a standard nomenclature for describing normal and mutant mouse embryo anatomy. The ontology forms the core of the EMAP atlas and is used for annotating gene expression data by the mouse Gene Expression Database (GXD), Edinburgh Mouse Atlas of Gene Expression (EMAGE) and other database resources. FINDINGS The original EMAP ontology listed anatomical entities for each developmental stage separately, presented as uniparental graphs organized as a strict partonomy. An "abstract" (i.e. non-stage-specific) representation of mouse developmental anatomy has since been developed. In this version (EMAPA) all instances for a given anatomical entity are presented as a single term, together with the first and last stage at which it is considered to be present. Timed-component anatomies are now derived using staging information in the "primary" non-timed version. Anatomical entities are presented as a directed acyclic graph enabling multiple parental relationships. Subsumption classification as well as partonomic and other types of relationships can now be represented. Most concept names are unique, with compound names constructed using standardized nomenclature conventions, and alternative names associated as synonyms. CONCLUSIONS The ontology has been extended and refined in a collaborative effort between EMAP and GXD, with additional input from others. Efforts are also underway to improve the revision process with regards to updating and editorial control. The revised EMAPA ontology is freely available from the OBO Foundry resource, with descriptive information and other documentation presented in associated Wiki pages (http://www.obofoundry.org/wiki/index.php/EMAPA:Main_Page).
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Gubelmann C, Waszak SM, Isakova A, Holcombe W, Hens K, Iagovitina A, Feuz JD, Raghav SK, Simicevic J, Deplancke B. A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks. Mol Syst Biol 2013; 9:682. [PMID: 23917988 PMCID: PMC3779800 DOI: 10.1038/msb.2013.38] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2013] [Accepted: 06/28/2013] [Indexed: 02/06/2023] Open
Abstract
The comprehensive mapping of gene promoters and enhancers has significantly improved our understanding of how the mammalian regulatory genome is organized. An important challenge is to elucidate how these regulatory elements contribute to gene expression by identifying their trans-regulatory inputs. Here, we present the generation of a mouse-specific transcription factor (TF) open-reading frame clone library and its implementation in yeast one-hybrid assays to enable large-scale protein-DNA interaction detection with mouse regulatory elements. Once specific interactions are identified, we then use a microfluidics-based method to validate and precisely map them within the respective DNA sequences. Using well-described regulatory elements as well as orphan enhancers, we show that this cross-platform pipeline characterizes known and uncovers many novel TF-DNA interactions. In addition, we provide evidence that several of these novel interactions are relevant in vivo and aid in elucidating the regulatory architecture of enhancers.
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Affiliation(s)
- Carine Gubelmann
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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LifeMap Discovery™: the embryonic development, stem cells, and regenerative medicine research portal. PLoS One 2013; 8:e66629. [PMID: 23874394 PMCID: PMC3714290 DOI: 10.1371/journal.pone.0066629] [Citation(s) in RCA: 77] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2013] [Accepted: 04/29/2013] [Indexed: 11/19/2022] Open
Abstract
LifeMap Discovery™ provides investigators with an integrated database of embryonic development, stem cell biology and regenerative medicine. The hand-curated reconstruction of cell ontology with stem cell biology; including molecular, cellular, anatomical and disease-related information, provides efficient and easy-to-use, searchable research tools. The database collates in vivo and in vitro gene expression and guides translation from in vitro data to the clinical utility, and thus can be utilized as a powerful tool for research and discovery in stem cell biology, developmental biology, disease mechanisms and therapeutic discovery. LifeMap Discovery is freely available to academic nonprofit institutions at http://discovery.lifemapsc.com.
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Debiais-Thibaud M, Metcalfe CJ, Pollack J, Germon I, Ekker M, Depew M, Laurenti P, Borday-Birraux V, Casane D. Heterogeneous conservation of Dlx paralog co-expression in jawed vertebrates. PLoS One 2013; 8:e68182. [PMID: 23840829 PMCID: PMC3695995 DOI: 10.1371/journal.pone.0068182] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2013] [Accepted: 05/27/2013] [Indexed: 01/10/2023] Open
Abstract
Background The Dlx gene family encodes transcription factors involved in the development of a wide variety of morphological innovations that first evolved at the origins of vertebrates or of the jawed vertebrates. This gene family expanded with the two rounds of genome duplications that occurred before jawed vertebrates diversified. It includes at least three bigene pairs sharing conserved regulatory sequences in tetrapods and teleost fish, but has been only partially characterized in chondrichthyans, the third major group of jawed vertebrates. Here we take advantage of developmental and molecular tools applied to the shark Scyliorhinus canicula to fill in the gap and provide an overview of the evolution of the Dlx family in the jawed vertebrates. These results are analyzed in the theoretical framework of the DDC (Duplication-Degeneration-Complementation) model. Results The genomic organisation of the catshark Dlx genes is similar to that previously described for tetrapods. Conserved non-coding elements identified in bony fish were also identified in catshark Dlx clusters and showed regulatory activity in transgenic zebrafish. Gene expression patterns in the catshark showed that there are some expression sites with high conservation of the expressed paralog(s) and other expression sites with events of paralog sub-functionalization during jawed vertebrate diversification, resulting in a wide variety of evolutionary scenarios within this gene family. Conclusion Dlx gene expression patterns in the catshark show that there has been little neo-functionalization in Dlx genes over gnathostome evolution. In most cases, one tandem duplication and two rounds of vertebrate genome duplication have led to at least six Dlx coding sequences with redundant expression patterns followed by some instances of paralog sub-functionalization. Regulatory constraints such as shared enhancers, and functional constraints including gene pleiotropy, may have contributed to the evolutionary inertia leading to high redundancy between gene expression patterns.
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Affiliation(s)
- Mélanie Debiais-Thibaud
- Institut des Sciences de l’Evolution, Université de Montpellier II, UMR5554, Montpellier, France
- * E-mail:
| | - Cushla J. Metcalfe
- Laboratoire Evolution Génome et Spéciation UPR9034 CNRS, Gif-sur-Yvette, France
| | - Jacob Pollack
- Center for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Canada
| | - Isabelle Germon
- Laboratoire Evolution Génome et Spéciation UPR9034 CNRS, Gif-sur-Yvette, France
| | - Marc Ekker
- Center for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Canada
| | - Michael Depew
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, California, United States of America
| | - Patrick Laurenti
- Laboratoire Evolution Génome et Spéciation UPR9034 CNRS, Gif-sur-Yvette, France
- Université Paris Diderot, Paris, France
| | - Véronique Borday-Birraux
- Laboratoire Evolution Génome et Spéciation UPR9034 CNRS, Gif-sur-Yvette, France
- Université Paris Diderot, Paris, France
| | - Didier Casane
- Laboratoire Evolution Génome et Spéciation UPR9034 CNRS, Gif-sur-Yvette, France
- Université Paris Diderot, Paris, France
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Arrenberg AB, Driever W. Integrating anatomy and function for zebrafish circuit analysis. Front Neural Circuits 2013; 7:74. [PMID: 23630469 PMCID: PMC3632786 DOI: 10.3389/fncir.2013.00074] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2013] [Accepted: 04/03/2013] [Indexed: 01/31/2023] Open
Abstract
Due to its transparency, virtually every brain structure of the larval zebrafish is accessible to light-based interrogation of circuit function. Advanced stimulation techniques allow the activation of optogenetic actuators at different resolution levels, and genetically encoded calcium indicators report the activity of a large proportion of neurons in the CNS. Large datasets result and need to be analyzed to identify cells that have specific properties—e.g., activity correlation to sensory stimulation or behavior. Advances in three-dimensional (3D) functional mapping in zebrafish are promising; however, the mere coordinates of implicated neurons are not sufficient. To comprehensively understand circuit function, these functional maps need to be placed into the proper context of morphological features and projection patterns, neurotransmitter phenotypes, and key anatomical landmarks. We discuss the prospect of merging functional and anatomical data in an integrated atlas from the perspective of our work on long-range dopaminergic neuromodulation and the oculomotor system. We propose that such a resource would help researchers to surpass current hurdles in circuit analysis to achieve an integrated understanding of anatomy and function.
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Affiliation(s)
- Aristides B Arrenberg
- Developmental Biology, Institute of Biology I, Faculty of Biology, BIOSS - Centre for Biological Signalling Studies, Albert-Ludwigs-University Freiburg Freiburg, Germany
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Chen CK, Symmons O, Uslu VV, Tsujimura T, Ruf S, Smedley D, Spitz F. TRACER: a resource to study the regulatory architecture of the mouse genome. BMC Genomics 2013; 14:215. [PMID: 23547943 PMCID: PMC3618316 DOI: 10.1186/1471-2164-14-215] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2012] [Accepted: 03/22/2013] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Mammalian genes are regulated through the action of multiple regulatory elements, often distributed across large regions. The mechanisms that control the integration of these diverse inputs into specific gene expression patterns are still poorly understood. New approaches enabling the dissection of these mechanisms in vivo are needed. RESULTS Here, we describe TRACER (http://tracerdatabase.embl.de), a resource that centralizes information from a large on-going functional exploration of the mouse genome with different transposon-associated regulatory sensors. Hundreds of insertions have been mapped to specific genomic positions, and their corresponding regulatory potential has been documented by analysis of the expression of the reporter sensor gene in mouse embryos. The data can be easily accessed and provides information on the regulatory activities present in a large number of genomic regions, notably in gene-poor intervals that have been associated with human diseases. CONCLUSIONS TRACER data enables comparisons with the expression pattern of neighbouring genes, activity of surrounding regulatory elements or with other genomic features, revealing the underlying regulatory architecture of these loci. TRACER mouse lines can also be requested for in vivo transposition and chromosomal engineering, to analyse further regions of interest.
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Affiliation(s)
- Chao-Kung Chen
- European Bioinformatics Institute - European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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35
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Köhler S, Doelken SC, Ruef BJ, Bauer S, Washington N, Westerfield M, Gkoutos G, Schofield P, Smedley D, Lewis SE, Robinson PN, Mungall CJ. Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research. F1000Res 2013; 2:30. [PMID: 24358873 DOI: 10.12688/f1000research.2-30.v1] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/22/2013] [Indexed: 12/30/2022] Open
Abstract
Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species. We have generated a cross-species phenotype ontology for human, mouse and zebrafish that contains classes from the Human Phenotype Ontology, Mammalian Phenotype Ontology, and generated classes for zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases. This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained from http://purl.obolibrary.org/obo/hp/uberpheno/.
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Affiliation(s)
- Sebastian Köhler
- Institute for Medical and Human Genetics, Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany ; Berlin-Brandenberg Center for Regenerative Therapies (BCRT), Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany
| | - Sandra C Doelken
- Institute for Medical and Human Genetics, Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany
| | - Barbara J Ruef
- ZFIN, Institute of Neuroscience, University of Oregon, Eugene OR, 97403-5291, USA
| | - Sebastian Bauer
- Institute for Medical and Human Genetics, Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany
| | | | - Monte Westerfield
- ZFIN, Institute of Neuroscience, University of Oregon, Eugene OR, 97403-5291, USA
| | - George Gkoutos
- Department of Computer Science, University of Aberystwyth, Aberystwyth, SY23 2AX, UK
| | - Paul Schofield
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK
| | - Damian Smedley
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK
| | - Suzanna E Lewis
- Lawrence Berkeley National Laboratory, Berkeley CA, 94720, USA
| | - Peter N Robinson
- Institute for Medical and Human Genetics, Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany ; Berlin-Brandenberg Center for Regenerative Therapies (BCRT), Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany ; Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
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36
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Köhler S, Doelken SC, Ruef BJ, Bauer S, Washington N, Westerfield M, Gkoutos G, Schofield P, Smedley D, Lewis SE, Robinson PN, Mungall CJ. Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research. F1000Res 2013; 2:30. [PMID: 24358873 PMCID: PMC3799545 DOI: 10.12688/f1000research.2-30.v2] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/20/2014] [Indexed: 12/11/2022] Open
Abstract
Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species. We have generated a cross-species phenotype ontology for human, mouse and zebrafish that contains classes from the Human Phenotype Ontology, Mammalian Phenotype Ontology, and generated classes for zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases. This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained from
http://purl.obolibrary.org/obo/hp/uberpheno/.
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Affiliation(s)
- Sebastian Köhler
- Institute for Medical and Human Genetics, Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany ; Berlin-Brandenberg Center for Regenerative Therapies (BCRT), Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany
| | - Sandra C Doelken
- Institute for Medical and Human Genetics, Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany
| | - Barbara J Ruef
- ZFIN, Institute of Neuroscience, University of Oregon, Eugene OR, 97403-5291, USA
| | - Sebastian Bauer
- Institute for Medical and Human Genetics, Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany
| | | | - Monte Westerfield
- ZFIN, Institute of Neuroscience, University of Oregon, Eugene OR, 97403-5291, USA
| | - George Gkoutos
- Department of Computer Science, University of Aberystwyth, Aberystwyth, SY23 2AX, UK
| | - Paul Schofield
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK
| | - Damian Smedley
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK
| | - Suzanna E Lewis
- Lawrence Berkeley National Laboratory, Berkeley CA, 94720, USA
| | - Peter N Robinson
- Institute for Medical and Human Genetics, Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany ; Berlin-Brandenberg Center for Regenerative Therapies (BCRT), Charité-Universitatsmedizin Berlin, Berlin, 13353, Germany ; Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
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Abstract
Our understanding of gene expression has changed dramatically over the past decade, largely catalysed by technological developments. High-throughput experiments - microarrays and next-generation sequencing - have generated large amounts of genome-wide gene expression data that are collected in public archives. Added-value databases process, analyse and annotate these data further to make them accessible to every biologist. In this Review, we discuss the utility of the gene expression data that are in the public domain and how researchers are making use of these data. Reuse of public data can be very powerful, but there are many obstacles in data preparation and analysis and in the interpretation of the results. We will discuss these challenges and provide recommendations that we believe can improve the utility of such data.
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Affiliation(s)
- Johan Rung
- EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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38
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Ariza-Cosano A, Visel A, Pennacchio LA, Fraser HB, Gómez-Skarmeta JL, Irimia M, Bessa J. Differences in enhancer activity in mouse and zebrafish reporter assays are often associated with changes in gene expression. BMC Genomics 2012; 13:713. [PMID: 23253453 PMCID: PMC3541358 DOI: 10.1186/1471-2164-13-713] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2012] [Accepted: 12/14/2012] [Indexed: 01/18/2023] Open
Abstract
Background Phenotypic evolution in animals is thought to be driven in large part by differences in gene expression patterns, which can result from sequence changes in cis-regulatory elements (cis-changes) or from changes in the expression pattern or function of transcription factors (trans-changes). While isolated examples of trans-changes have been identified, the scale of their overall contribution to regulatory and phenotypic evolution remains unclear. Results Here, we attempt to examine the prevalence of trans-effects and their potential impact on gene expression patterns in vertebrate evolution by comparing the function of identical human tissue-specific enhancer sequences in two highly divergent vertebrate model systems, mouse and zebrafish. Among 47 human conserved non-coding elements (CNEs) tested in transgenic mouse embryos and in stable zebrafish lines, at least one species-specific expression domain was observed in the majority (83%) of cases, and 36% presented dramatically different expression patterns between the two species. Although some of these discrepancies may be due to the use of different transgenesis systems in mouse and zebrafish, in some instances we found an association between differences in enhancer activity and changes in the endogenous gene expression patterns between mouse and zebrafish, suggesting a potential role for trans-changes in the evolution of gene expression. Conclusions In total, our results: (i) serve as a cautionary tale for studies investigating the role of human enhancers in different model organisms, and (ii) suggest that changes in the trans environment may play a significant role in the evolution of gene expression in vertebrates.
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Affiliation(s)
- Ana Ariza-Cosano
- Centro Andaluz de Biología del Desarrollo (CABD), CSIC-Universidad Pablo de Olavide-Junta de Andalucía, Ctra. Utrera Km 1, Seville 41013, Spain
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39
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Bult CJ, Eppig JT, Blake JA, Kadin JA, Richardson JE. The mouse genome database: genotypes, phenotypes, and models of human disease. Nucleic Acids Res 2012; 41:D885-91. [PMID: 23175610 PMCID: PMC3531104 DOI: 10.1093/nar/gks1115] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The laboratory mouse is the premier animal model for studying human biology because all life stages can be accessed experimentally, a completely sequenced reference genome is publicly available and there exists a myriad of genomic tools for comparative and experimental research. In the current era of genome scale, data-driven biomedical research, the integration of genetic, genomic and biological data are essential for realizing the full potential of the mouse as an experimental model. The Mouse Genome Database (MGD; http://www.informatics.jax.org), the community model organism database for the laboratory mouse, is designed to facilitate the use of the laboratory mouse as a model system for understanding human biology and disease. To achieve this goal, MGD integrates genetic and genomic data related to the functional and phenotypic characterization of mouse genes and alleles and serves as a comprehensive catalog for mouse models of human disease. Recent enhancements to MGD include the addition of human ortholog details to mouse Gene Detail pages, the inclusion of microRNA knockouts to MGD’s catalog of alleles and phenotypes, the addition of video clips to phenotype images, providing access to genotype and phenotype data associated with quantitative trait loci (QTL) and improvements to the layout and display of Gene Ontology annotations.
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Affiliation(s)
- Carol J Bult
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609 USA.
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40
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Drabkin HJ, Blake JA. Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2012; 2012:bas045. [PMID: 23110975 PMCID: PMC3483533 DOI: 10.1093/database/bas045] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as ‘GO’ or ‘homology’ or ‘phenotype’. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as ‘papers selected for GO that refer to genes with NO GO annotation’. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported with statements of evidence as well as access to source publications.
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Affiliation(s)
- Harold J Drabkin
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA.
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41
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Tolvanen MEE, Ortutay C, Barker HR, Aspatwar A, Patrikainen M, Parkkila S. Analysis of evolution of carbonic anhydrases IV and XV reveals a rich history of gene duplications and a new group of isozymes. Bioorg Med Chem 2012; 21:1503-10. [PMID: 23022279 DOI: 10.1016/j.bmc.2012.08.060] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2012] [Revised: 08/23/2012] [Accepted: 08/31/2012] [Indexed: 01/09/2023]
Abstract
Carbonic anhydrase (CA) isozymes CA IV and CA XV are anchored on the extracellular cell surface via glycosylphosphatidylinositol (GPI) linkage. Analysis of evolution of these isozymes in vertebrates reveals an additional group of GPI-linked CAs, CA XVII, which has been lost in mammals. Our work resolves nomenclature issues in GPI-linked fish CAs. Review of expression data brings forth previously unreported tissue and cancer types in which human CA IV is expressed. Analysis of collective glycosylation patterns of GPI-linked CAs suggests functionally important regions on the protein surface.
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Affiliation(s)
- Martti E E Tolvanen
- Institute of Biomedical Technology, University of Tampere, Finland and BioMediTech, FI-33014 Tampere, Finland.
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42
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de Monasterio-Schrader P, Jahn O, Tenzer S, Wichert SP, Patzig J, Werner HB. Systematic approaches to central nervous system myelin. Cell Mol Life Sci 2012; 69:2879-94. [PMID: 22441408 PMCID: PMC11114939 DOI: 10.1007/s00018-012-0958-9] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2012] [Accepted: 03/05/2012] [Indexed: 12/11/2022]
Abstract
Rapid signal propagation along vertebrate axons is facilitated by their insulation with myelin, a plasma membrane specialization of glial cells. The recent application of 'omics' approaches to the myelinating cells of the central nervous system, oligodendrocytes, revealed their mRNA signatures, enhanced our understanding of how myelination is regulated, and established that the protein composition of myelin is much more complex than previously thought. This review provides a meta-analysis of the > 1,200 proteins thus far identified by mass spectrometry in biochemically purified central nervous system myelin. Contaminating proteins are surprisingly infrequent according to bioinformatic prediction of subcellular localization and comparison with the transcriptional profile of oligodendrocytes. The integration of datasets also allowed the subcategorization of the myelin proteome into functional groups comprising genes that are coregulated during oligodendroglial differentiation. An unexpectedly large number of myelin-related genes cause-when mutated in humans-hereditary diseases affecting the physiology of the white matter. Systematic approaches to oligodendrocytes and myelin thus provide valuable resources for the molecular dissection of developmental myelination, glia-axonal interactions, leukodystrophies, and demyelinating diseases.
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Affiliation(s)
| | - Olaf Jahn
- Proteomics Group, Max Planck Institute of Experimental Medicine, Göttingen, Germany
- DFG Research Center for Molecular Physiology of the Brain, Göttingen, Germany
| | - Stefan Tenzer
- Institute of Immunology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sven P. Wichert
- Department of Neurogenetics, Max Planck Institute of Experimental Medicine, Hermann-Rein-Str. 3, 37075 Göttingen, Germany
| | - Julia Patzig
- Department of Neurogenetics, Max Planck Institute of Experimental Medicine, Hermann-Rein-Str. 3, 37075 Göttingen, Germany
| | - Hauke B. Werner
- Department of Neurogenetics, Max Planck Institute of Experimental Medicine, Hermann-Rein-Str. 3, 37075 Göttingen, Germany
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Geffers L, Herrmann B, Eichele G. Web-based digital gene expression atlases for the mouse. Mamm Genome 2012; 23:525-38. [PMID: 22936000 DOI: 10.1007/s00335-012-9413-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2012] [Accepted: 07/04/2012] [Indexed: 11/26/2022]
Abstract
Over the past 15 years the publicly available mouse gene expression data determined by in situ hybridization have dramatically increased in scope and spatiotemporal resolution. As a consequence of resources and tools available in the post-genomic era, full transcriptomes in the mouse brain and in the mouse embryo can be studied. Here we introduce and discuss seven current databases (MAMEP, EMBRYS, GenePaint, EURExpress, EuReGene, BGEM, and GENSAT) that grant access to large collections of expression data in mouse. We review the experimental focus, coverage, data assessment, and annotation for each of these databases and the implementation of analytic tools and links to other relevant databases. We provide a user-oriented summary of how to interrogate each database.
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Affiliation(s)
- Lars Geffers
- Department of Genes and Behavior, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany.
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44
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Ringwald M, Wu C, Su AI. BioGPS and GXD: mouse gene expression data-the benefits and challenges of data integration. Mamm Genome 2012; 23:550-8. [PMID: 22847375 DOI: 10.1007/s00335-012-9408-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2012] [Accepted: 06/21/2012] [Indexed: 01/30/2023]
Abstract
Mouse gene expression data are complex and voluminous. To maximize the utility of these data, they must be made readily accessible through databases, and those resources need to place the expression data in the larger biological context. Here we describe two community resources that approach these problems in different but complementary ways: BioGPS and the Mouse Gene Expression Database (GXD). BioGPS connects its large and homogeneous microarray gene expression reference data sets via plugins with a heterogeneous collection of external gene centric resources, thus casting a wide but loose net. GXD acquires different types of expression data from many sources and integrates these data tightly with other types of data in the Mouse Genome Informatics (MGI) resource, with a strong emphasis on consistency checks and manual curation. We describe and contrast the "loose" and "tight" data integration strategies employed by BioGPS and GXD, respectively, and discuss the challenges and benefits of data integration. BioGPS is freely available at http://biogps.org . GXD is freely available through the MGI web site ( www.informatics.jax.org ) or directly at www.informatics.jax.org/expression.shtml .
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Affiliation(s)
- Martin Ringwald
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA.
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45
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Schofield PN, Hoehndorf R, Gkoutos GV. Mouse genetic and phenotypic resources for human genetics. Hum Mutat 2012; 33:826-36. [PMID: 22422677 DOI: 10.1002/humu.22077] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The use of model organisms to provide information on gene function has proved to be a powerful approach to our understanding of both human disease and fundamental mammalian biology. Large-scale community projects using mice, based on forward and reverse genetics, and now the pan-genomic phenotyping efforts of the International Mouse Phenotyping Consortium, are generating resources on an unprecedented scale, which will be extremely valuable to human genetics and medicine. We discuss the nature and availability of data, mice and embryonic stem cells from these large-scale programmes, the use of these resources to help prioritize and validate candidate genes in human genetic association studies, and how they can improve our understanding of the underlying pathobiology of human disease.
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Affiliation(s)
- Paul N Schofield
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom.
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Nellåker C, Keane TM, Yalcin B, Wong K, Agam A, Belgard TG, Flint J, Adams DJ, Frankel WN, Ponting CP. The genomic landscape shaped by selection on transposable elements across 18 mouse strains. Genome Biol 2012; 13:R45. [PMID: 22703977 PMCID: PMC3446317 DOI: 10.1186/gb-2012-13-6-r45] [Citation(s) in RCA: 127] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2012] [Revised: 05/25/2012] [Accepted: 06/15/2012] [Indexed: 12/20/2022] Open
Abstract
Background Transposable element (TE)-derived sequence dominates the landscape of mammalian genomes and can modulate gene function by dysregulating transcription and translation. Our current knowledge of TEs in laboratory mouse strains is limited primarily to those present in the C57BL/6J reference genome, with most mouse TEs being drawn from three distinct classes, namely short interspersed nuclear elements (SINEs), long interspersed nuclear elements (LINEs) and the endogenous retrovirus (ERV) superfamily. Despite their high prevalence, the different genomic and gene properties controlling whether TEs are preferentially purged from, or are retained by, genetic drift or positive selection in mammalian genomes remain poorly defined. Results Using whole genome sequencing data from 13 classical laboratory and 4 wild-derived mouse inbred strains, we developed a comprehensive catalogue of 103,798 polymorphic TE variants. We employ this extensive data set to characterize TE variants across the Mus lineage, and to infer neutral and selective processes that have acted over 2 million years. Our results indicate that the majority of TE variants are introduced though the male germline and that only a minority of TE variants exert detectable changes in gene expression. However, among genes with differential expression across the strains there are twice as many TE variants identified as being putative causal variants as expected. Conclusions Most TE variants that cause gene expression changes appear to be purged rapidly by purifying selection. Our findings demonstrate that past TE insertions have often been highly deleterious, and help to prioritize TE variants according to their likely contribution to gene expression or phenotype variation.
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Affiliation(s)
- Christoffer Nellåker
- MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.
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Ramialison M, Reinhardt R, Henrich T, Wittbrodt B, Kellner T, Lowy CM, Wittbrodt J. Cis-regulatory properties of medaka synexpression groups. Development 2012; 139:917-28. [PMID: 22318626 DOI: 10.1242/dev.071803] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
During embryogenesis, tissue specification is triggered by the expression of a unique combination of developmental genes and their expression in time and space is crucial for successful development. Synexpression groups are batteries of spatiotemporally co-expressed genes that act in shared biological processes through their coordinated expression. Although several synexpression groups have been described in numerous vertebrate species, the regulatory mechanisms that orchestrate their common complex expression pattern remain to be elucidated. Here we performed a pilot screen on 560 genes of the vertebrate model system medaka (Oryzias latipes) to systematically identify synexpression groups and investigate their regulatory properties by searching for common regulatory cues. We find that synexpression groups share DNA motifs that are arranged in various combinations into cis-regulatory modules that drive co-expression. In contrast to previous assumptions that these genes are located randomly in the genome, we discovered that genes belonging to the same synexpression group frequently occur in synexpression clusters in the genome. This work presents a first repertoire of synexpression group common signatures, a resource that will contribute to deciphering developmental gene regulatory networks.
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Affiliation(s)
- Mirana Ramialison
- University of Heidelberg, Centre for Organismal Studies, Heidelberg, Germany.
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Roux J, Gonzàlez-Porta M, Robinson-Rechavi M. Comparative analysis of human and mouse expression data illuminates tissue-specific evolutionary patterns of miRNAs. Nucleic Acids Res 2012; 40:5890-900. [PMID: 22457063 PMCID: PMC3401464 DOI: 10.1093/nar/gks279] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
MicroRNAs (miRNAs) constitute an important class of gene regulators. While models have been proposed to explain their appearance and expansion, the validation of these models has been difficult due to the lack of comparative studies. Here, we analyze miRNA evolutionary patterns in two mammals, human and mouse, in relation to the age of miRNA families. In this comparative framework, we confirm some predictions of previously advanced models of miRNA evolution, e.g. that miRNAs arise more frequently de novo than by duplication, or that the number of protein-coding gene targeted by miRNAs decreases with evolutionary time. We also corroborate that miRNAs display an increase in expression level with evolutionary time, however we show that this relation is largely tissue-dependent, and especially low in embryonic or nervous tissues. We identify a bias of tag-sequencing techniques regarding the assessment of breadth of expression, leading us, contrary to predictions, to find more tissue-specific expression of older miRNAs. Together, our results refine the models used so far to depict the evolution of miRNA genes. They underline the role of tissue-specific selective forces on the evolution of miRNAs, as well as the potential co-evolution patterns between miRNAs and the protein-coding genes they target.
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Affiliation(s)
- Julien Roux
- Department of Ecology and Evolution, Biophore, University of Lausanne, Switzerland
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Ranz JM, Parsch J. Newly evolved genes: moving from comparative genomics to functional studies in model systems. How important is genetic novelty for species adaptation and diversification? Bioessays 2012; 34:477-83. [PMID: 22461005 DOI: 10.1002/bies.201100177] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Genes are gained and lost over the course of evolution. A recent study found that over 1,800 new genes have appeared during primate evolution and that an unexpectedly high proportion of these genes are expressed in the human brain. But what are the molecular functions of newly evolved genes and what is their impact on an organism's fitness? The acquisition of new genes may provide a rich source of genetic diversity that fuels evolutionary innovation. Although gene manipulation experiments are not feasible in humans, studies in model organisms, such as Drosophila melanogaster, have shown that new genes can quickly become integrated into genetic networks and become essential for survival or fertility. Future studies of new genes, especially chimeric genes, and their functions will help determine the role of genetic novelty in the adaptation and diversification of species.
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Affiliation(s)
- José M Ranz
- Department of Ecology and Evolutionary Biology, University of California-Irvine, CA, USA.
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Hayamizu TF, de Coronado S, Fragoso G, Sioutos N, Kadin JA, Ringwald M. The mouse-human anatomy ontology mapping project. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2012; 2012:bar066. [PMID: 22434834 PMCID: PMC3308156 DOI: 10.1093/database/bar066] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The overall objective of the Mouse–Human Anatomy Project (MHAP) was to facilitate the mapping and harmonization of anatomical terms used for mouse and human models by Mouse Genome Informatics (MGI) and the National Cancer Institute (NCI). The anatomy resources designated for this study were the Adult Mouse Anatomy (MA) ontology and the set of anatomy concepts contained in the NCI Thesaurus (NCIt). Several methods and software tools were identified and evaluated, then used to conduct an in-depth comparative analysis of the anatomy ontologies. Matches between mouse and human anatomy terms were determined and validated, resulting in a highly curated set of mappings between the two ontologies that has been used by other resources. These mappings will enable linking of data from mouse and human. As the anatomy ontologies have been expanded and refined, the mappings have been updated accordingly. Insights are presented into the overall process of comparing and mapping between ontologies, which may prove useful for further comparative analyses and ontology mapping efforts, especially those involving anatomy ontologies. Finally, issues concerning further development of the ontologies, updates to the mapping files, and possible additional applications and significance were considered. Database URL:http://obofoundry.org/cgi-bin/detail.cgi?id=ma2ncit
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