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Shi L, Li H, Huang X, Shu Z, Li J, Wang L, Yan H, Wang L. Integrated analysis of transcriptome and metabolome revealed biological basis of sows from estrus to lactation. iScience 2022; 26:105825. [PMID: 36636351 PMCID: PMC9830223 DOI: 10.1016/j.isci.2022.105825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 10/10/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
Characterization of molecular mechanisms underlying pregnancy development of sows is important for the genetic improvement of pig breeding traits, and also provides resources for biomedical research on human pregnancy diseases. However, the transcriptome and metabolome across multiple developmental stages of sow pregnancy were still lacking. In this study, we obtained 84 distinct RNA sequencing and 42 metabolome datasets of pig blood across six development stages from estrus to lactation. We confirmed the initial sequence and exonic structural features, stage-specific molecules, expression or accumulation pattern of molecules, the regulatory mechanism of transcriptome and metabolome, and important pregnancy-related metabolites both in pigs and humans. In conclusion, we proposed the key differences among the stages of sows from estrus to lactation in RNAs and metabolites and put forward key markers. These data results were expected to provide essential resources for pig breeding and biomedical research on human pregnancy disease.
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Affiliation(s)
- Lijun Shi
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China,Corresponding author
| | - Huihui Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China
| | - Xiaoyu Huang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China
| | - Ze Shu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China
| | - Jingna Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China
| | - Ligang Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China
| | - Hua Yan
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China
| | - Lixian Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China,Corresponding author
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2
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Waites W, Davies JA. Emergence of structure in mouse embryos: Structural Entropy morphometry applied to digital models of embryonic anatomy. J Anat 2019; 235:706-715. [PMID: 31276197 PMCID: PMC6742931 DOI: 10.1111/joa.13031] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/21/2019] [Indexed: 12/11/2022] Open
Abstract
We apply an information-theoretic measure to anatomical models of the Edinburgh Mouse Atlas Project. Our goal is to quantify the anatomical complexity of the embryo and to understand how this quantity changes as the organism develops through time. Our measure, Structural Entropy, takes into account the geometrical character of the intermingling of tissue types in the embryo. It does this by a mathematical process that effectively imagines a point-like explorer that starts at an arbitrary place in the 3D structure of the embryo and takes a random path through the embryo, recording the sequence of tissues through which it passes. Consideration of a large number of such paths yields a probability distribution of paths making connections between specific tissue types, and Structural Entropy is calculated from this (mathematical details are given in the main text). We find that Structural Entropy generally decreases (order increases) almost linearly throughout developmental time (4-18 days). There is one `blip' of increased Structural Entropy across days 7-8: this corresponds to gastrulation. Our results highlight the potential for mathematical techniques to provide insight into the development of anatomical structure, and also the need for further sources of accurate 3D anatomical data to support analyses of this kind.
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Affiliation(s)
- William Waites
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | - Jamie A Davies
- Deanery of Biomedical Sciences, University of Edinburgh, Edinburgh, UK
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3
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Smit N, Bruckner S. Towards Advanced Interactive Visualization for Virtual Atlases. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1156:85-96. [PMID: 31338779 DOI: 10.1007/978-3-030-19385-0_6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
An atlas is generally defined as a bound collection of tables, charts or illustrations describing a phenomenon. In an anatomical atlas for example, a collection of representative illustrations and text describes anatomy for the purpose of communicating anatomical knowledge. The atlas serves as reference frame for comparing and integrating data from different sources by spatially or semantically relating collections of drawings, imaging data, and/or text. In the field of medical image processing, atlas information is often constructed from a collection of regions of interest, which are based on medical images that are annotated by domain experts. Such an atlas may be employed, for example, for automatic segmentation of medical imaging data. The combination of interactive visualization techniques with atlas information opens up new possibilities for content creation, curation, and navigation in virtual atlases. With interactive visualization of atlas information, students are able to inspect and explore anatomical atlases in ways that were not possible with the traditional method of presenting anatomical atlases in book format, such as viewing the illustrations from other viewpoints. With advanced interaction techniques, it becomes possible to query the data that forms the basis for the atlas, thus empowering researchers to access a wealth of information in new ways. So far, atlas-based visualization has been employed mainly for medical education, as well as biological research. In this survey, we provide an overview of current digital biomedical atlas tasks and applications and summarize relevant visualization techniques. We discuss recent approaches for providing next-generation visual interfaces to navigate atlas data that go beyond common text-based search and hierarchical lists. Finally, we reflect on open challenges and opportunities for the next steps in interactive atlas visualization.
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Affiliation(s)
- Noeska Smit
- Department of Informatics, University of Bergen, Bergen, Norway. .,Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Bergen, Norway.
| | - Stefan Bruckner
- Department of Informatics, University of Bergen, Bergen, Norway
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4
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Survey of Human Chromosome 21 Gene Expression Effects on Early Development in Danio rerio. G3-GENES GENOMES GENETICS 2018; 8:2215-2223. [PMID: 29760202 PMCID: PMC6027891 DOI: 10.1534/g3.118.200144] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Trisomy for human chromosome 21 (Hsa21) results in Down syndrome (DS), one of the most genetically complex conditions compatible with human survival. Assessment of the physiological consequences of dosage-driven overexpression of individual Hsa21 genes during early embryogenesis and the resulting contributions to DS pathology in mammals are not tractable in a systematic way. A recent study looked at loss-of-function of a subset of Caenorhabditis elegans orthologs of Hsa21 genes and identified ten candidates with behavioral phenotypes, but the equivalent over-expression experiment has not been done. We turned to zebrafish as a developmental model and, using a number of surrogate phenotypes, we screened Hsa21 genes for effects on early embyrogenesis. We prepared a library of 164 cDNAs of conserved protein coding genes, injected mRNA into early embryos and evaluated up to 5 days post-fertilization (dpf). Twenty-four genes produced a gross morphological phenotype, 11 of which could be reproduced reliably. Seven of these gave a phenotype consistent with down regulation of the sonic hedgehog (Shh) pathway; two showed defects indicative of defective neural crest migration; one resulted consistently in pericardial edema; and one was embryonic lethal. Combinatorial injections of multiple Hsa21 genes revealed both additive and compensatory effects, supporting the notion that complex genetic relationships underlie end phenotypes of trisomy that produce DS. Together, our data suggest that this system is useful in the genetic dissection of dosage-sensitive gene effects on early development and can inform the contribution of both individual loci and their combinatorial effects to phenotypes relevant to the etiopathology of DS.
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5
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Carlson JC, Taub MA, Feingold E, Beaty TH, Murray JC, Marazita ML, Leslie EJ. Identifying Genetic Sources of Phenotypic Heterogeneity in Orofacial Clefts by Targeted Sequencing. Birth Defects Res 2017; 109:1030-1038. [PMID: 28762674 PMCID: PMC5549861 DOI: 10.1002/bdr2.23605] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 11/09/2016] [Accepted: 11/28/2016] [Indexed: 12/26/2022]
Abstract
BACKGROUND Orofacial clefts (OFCs), including nonsyndromic cleft lip with or without cleft palate (NSCL/P), are common birth defects. NSCL/P is highly heterogeneous with multiple phenotypic presentations. Two common subtypes of NSCL/P are cleft lip (CL) and cleft lip with cleft palate (CLP) which have different population prevalence. Similarly, NSCL/P can be divided into bilateral and unilateral clefts, with unilateral being the most common. Individuals with unilateral NSCL/P are more likely to be affected on the left side of the upper lip, but right side affection also occurs. Moreover, NSCL/P is twice as common in males as in females. The goal of this study is to discover genetic variants that have different effects in case subgroups. METHODS We conducted both common variant and rare variant analyses in 1034 individuals of Asian ancestry with NSCL/P, examining four sources of heterogeneity within CL/P: cleft type, sex, laterality, and side. RESULTS We identified several regions associated with subtype differentiation: cleft type differences in 8q24 (p = 1.00 × 10-4 ), laterality differences in IRF6, a gene previously implicated with wound healing (p = 2.166 × 10-4 ), sex differences and side of unilateral CL differences in FGFR2 (p = 3.00 × 10-4 ; p = 6.00 × 10-4 ), and sex differences in VAX1 (p < 1.00 × 10-4 ) among others. CONCLUSION Many of the regions associated with phenotypic modification were either adjacent to or overlapping functional elements based on ENCODE chromatin marks and published craniofacial enhancers. We have identified multiple common and rare variants as potential phenotypic modifiers of NSCL/P, and suggest plausible elements responsible for phenotypic heterogeneity, further elucidating the complex genetic architecture of OFCs. Birth Defects Research 109:1030-1038, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Jenna C. Carlson
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Margaret A. Taub
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Eleanor Feingold
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Terri H. Beaty
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore MD, USA
| | - Jeffrey C. Murray
- Department of Pediatrics, Carver College of Medicine, University of Iowa, Iowa City, Iowa, 52242, USA
| | - Mary L. Marazita
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA
- Clinical and Translational Science, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Center for Craniofacial and Dental Genetics, Department of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, 15219, USA
| | - Elizabeth J. Leslie
- Center for Craniofacial and Dental Genetics, Department of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, 15219, USA
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6
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Li B, Qing T, Zhu J, Wen Z, Yu Y, Fukumura R, Zheng Y, Gondo Y, Shi L. A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq. Sci Rep 2017; 7:4200. [PMID: 28646208 PMCID: PMC5482823 DOI: 10.1038/s41598-017-04520-z] [Citation(s) in RCA: 121] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Accepted: 05/16/2017] [Indexed: 02/07/2023] Open
Abstract
The mouse has been widely used as a model organism for studying human diseases and for evaluating drug safety and efficacy. Many diseases and drug effects exhibit tissue specificity that may be reflected by tissue-specific gene-expression profiles. Here we construct a comprehensive mouse transcriptomic BodyMap across 17 tissues of six-weeks old C57BL/6JJcl mice using RNA-seq. We find different expression patterns between protein-coding and non-coding genes. Liver expressed the least complex transcriptomes, that is, the smallest number of genes detected in liver across all 17 tissues, whereas testis and ovary harbor more complex transcriptomes than other tissues. We report a comprehensive list of tissue-specific genes across 17 tissues, along with a list of 4,781 housekeeping genes in mouse. In addition, we propose a list of 27 consistently and highly expressed genes that can be used as reference controls in expression-profiling analysis. Our study provides a unique resource of mouse gene-expression profiles, which is helpful for further biomedical research.
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Affiliation(s)
- Bin Li
- Center for Pharmacogenomics, School of Pharmacy, and State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
- Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, 200438, China
| | - Tao Qing
- Center for Pharmacogenomics, School of Pharmacy, and State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
- Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, 200438, China
| | - Jinhang Zhu
- Center for Pharmacogenomics, School of Pharmacy, and State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Zhuo Wen
- Center for Pharmacogenomics, School of Pharmacy, and State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
- College of Chemistry, Sichuan University, Chengdu, 610064, China
| | - Ying Yu
- Center for Pharmacogenomics, School of Pharmacy, and State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
- Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, 200438, China
| | - Ryutaro Fukumura
- Mutagenesis and Genomics Team, RIKEN BioResource Center, Tsukuba, Ibaraki, 305-0074, Japan
| | - Yuanting Zheng
- Center for Pharmacogenomics, School of Pharmacy, and State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China.
- Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, 200438, China.
| | - Yoichi Gondo
- Mutagenesis and Genomics Team, RIKEN BioResource Center, Tsukuba, Ibaraki, 305-0074, Japan.
| | - Leming Shi
- Center for Pharmacogenomics, School of Pharmacy, and State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China.
- Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, 200438, China.
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7
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Williams E, Moore J, Li SW, Rustici G, Tarkowska A, Chessel A, Leo S, Antal B, Ferguson RK, Sarkans U, Brazma A, Salas REC, Swedlow JR. The Image Data Resource: A Bioimage Data Integration and Publication Platform. Nat Methods 2017; 14:775-781. [PMID: 28775673 PMCID: PMC5536224 DOI: 10.1038/nmeth.4326] [Citation(s) in RCA: 170] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
This Resource describes the Image Data Resource (IDR), a prototype online system for biological image data that links experimental and analytic data across multiple data sets and promotes image data sharing and reanalysis. Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR). IDR links data from several imaging modalities, including high-content screening, multi-dimensional microscopy and digital pathology, with public genetic or chemical databases and cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable reanalysis, we also established a computational resource based on Jupyter notebooks that allows remote access to the entire IDR. IDR is also an open-source platform for publishing imaging data. Thus IDR provides an online resource and a software infrastructure that promotes and extends publication and reanalysis of scientific image data.
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Affiliation(s)
- Eleanor Williams
- Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK.,European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Josh Moore
- Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Simon W Li
- Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Gabriella Rustici
- Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Aleksandra Tarkowska
- Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Anatole Chessel
- Pharmacology & Genetics Departments and Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK.,LOB, Ecole Polytechnique, CNRS, INSERM, Université Paris-Saclay, Palaiseau, France
| | - Simone Leo
- Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK.,Center for Advanced Studies, Research, and Development in Sardinia (CRS4), Pula(CA), Italy
| | - Bálint Antal
- Pharmacology & Genetics Departments and Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK
| | - Richard K Ferguson
- Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Ugis Sarkans
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Rafael E Carazo Salas
- Pharmacology & Genetics Departments and Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK.,School of Cell and Molecular Medicine, University of Bristol, Bristol, UK
| | - Jason R Swedlow
- Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK
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8
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Armit C, Richardson L, Venkataraman S, Graham L, Burton N, Hill B, Yang Y, Baldock RA. eMouseAtlas: An atlas-based resource for understanding mammalian embryogenesis. Dev Biol 2017; 423:1-11. [PMID: 28161522 PMCID: PMC5442644 DOI: 10.1016/j.ydbio.2017.01.023] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Revised: 01/31/2017] [Accepted: 01/31/2017] [Indexed: 11/23/2022]
Abstract
The eMouseAtlas resource is an online database of 3D digital models of mouse development, an ontology of mouse embryo anatomy and a gene-expression database with about 30K spatially mapped gene-expression patterns. It is closely linked with the MGI/GXD database at the Jackson Laboratory and holds links to almost all available image-based gene-expression data for the mouse embryo. In this resource article we describe the novel web-based tools we have developed for 3D visualisation of embryo anatomy and gene expression. We show how mapping of gene expression data onto spatial models delivers a framework for capturing gene expression that enhances our understanding of development, and we review the exploratory tools utilised by the EMAGE gene expression database as a means of defining co-expression of in situ hybridisation, immunohistochemistry, and lacZ-omic expression patterns. We report on recent developments of the eHistology atlas and our use of web-services to support embedding of the online 'The Atlas of Mouse Development' in the context of other resources such as the DMDD mouse phenotype database. In addition, we discuss new developments including a cellular-resolution placental atlas, third-party atlas models, clonal analysis data and a new interactive eLearning resource for developmental processes.
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Affiliation(s)
- Chris Armit
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Lorna Richardson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Shanmugasundaram Venkataraman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Liz Graham
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Nicholas Burton
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Bill Hill
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Yiya Yang
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Richard A Baldock
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
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9
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Armit C, Hill B, Venkataraman S, McLeod K, Burger A, Baldock R. The 'straight mouse': defining anatomical axes in 3D embryo models. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2017; 2017:3066360. [PMID: 28365728 PMCID: PMC5467569 DOI: 10.1093/database/bax010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Accepted: 01/27/2017] [Indexed: 11/25/2022]
Abstract
A primary objective of the eMouseAtlas Project is to enable 3D spatial mapping of whole embryo gene expression data to capture complex 3D patterns for indexing, visualization, cross-comparison and analysis. For this we have developed a spatio-temporal framework based on 3D models of embryos at different stages of development coupled with an anatomical ontology. Here we introduce a method of defining coordinate axes that correspond to the anatomical or biologically relevant anterior–posterior (A–P), dorsal–ventral (D–V) and left–right (L–R) directions. These enable more sophisticated query and analysis of the data with biologically relevant associations, and provide novel data visualizations that can reveal patterns that are otherwise difficult to detect in the standard 3D coordinate space. These anatomical coordinates are defined using the concept of a ‘straight mouse-embryo’ within which the anatomical coordinates are Cartesian. The straight embryo model has been mapped via a complex non-linear transform onto the standard embryo model. We explore the utility of this anatomical coordinate system in elucidating the spatial relationship of spatially mapped embryonic ‘Fibroblast growth factor’ gene expression patterns, and we discuss the importance of this technology in summarizing complex multimodal mouse embryo image data from gene expression and anatomy studies. Database URL:www.emouseatlas.org
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Affiliation(s)
- Chris Armit
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh College of Medicine and Veterinary Medicine, Edinburgh, Scotland EH4 2XU, UK and
| | - Bill Hill
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh College of Medicine and Veterinary Medicine, Edinburgh, Scotland EH4 2XU, UK and
| | - S Venkataraman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh College of Medicine and Veterinary Medicine, Edinburgh, Scotland EH4 2XU, UK and
| | - Kenneth McLeod
- Department of Computer Science, Heriot-Watt University, Edinburgh, Scotland EH14 4AS, UK
| | - Albert Burger
- Department of Computer Science, Heriot-Watt University, Edinburgh, Scotland EH14 4AS, UK
| | - Richard Baldock
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh College of Medicine and Veterinary Medicine, Edinburgh, Scotland EH4 2XU, UK and
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10
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Adebayo S, McLeod K, Tudose I, Osumi-Sutherland D, Burdett T, Baldock R, Burger A, Parkinson H. PhenoImageShare: an image annotation and query infrastructure. J Biomed Semantics 2016; 7:35. [PMID: 27267125 PMCID: PMC4896029 DOI: 10.1186/s13326-016-0072-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Accepted: 05/05/2016] [Indexed: 01/12/2023] Open
Abstract
Background High throughput imaging is now available to many groups and it is possible to generate a large quantity of high quality images quickly. Managing this data, consistently annotating it, or making it available to the community are all challenges that come with these methods. Results PhenoImageShare provides an ontology-enabled lightweight image data query, annotation service and a single point of access backed by a Solr server for programmatic access to an integrated image collection enabling improved community access. PhenoImageShare also provides an easy to use online image annotation tool with functionality to draw regions of interest on images and to annotate them with terms from an autosuggest-enabled ontology-lookup widget. The provenance of each image, and annotation, is kept and links to original resources are provided. The semantic and intuitive search interface is species and imaging technology neutral. PhenoImageShare now provides access to annotation for over 100,000 images for 2 species. Conclusion The PhenoImageShare platform provides underlying infrastructure for both programmatic access and user-facing tools for biologists enabling the query and annotation of federated images. PhenoImageShare is accessible online at http://www.phenoimageshare.org.
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Affiliation(s)
- Solomon Adebayo
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh, UK
| | - Kenneth McLeod
- Department of Computer Science, Heriot-Watt University, Edinburgh, UK
| | - Ilinca Tudose
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK.
| | - David Osumi-Sutherland
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Tony Burdett
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Richard Baldock
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh, UK
| | - Albert Burger
- Department of Computer Science, Heriot-Watt University, Edinburgh, UK
| | - Helen Parkinson
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
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11
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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: 3] [Impact Index Per Article: 0.3] [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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Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks. Sci Rep 2016; 6:20732. [PMID: 26864723 PMCID: PMC4749973 DOI: 10.1038/srep20732] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 12/31/2015] [Indexed: 11/09/2022] Open
Abstract
Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states.
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13
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Robert C, Kapetanovic R, Beraldi D, Watson M, Archibald AL, Hume DA. Identification and annotation of conserved promoters and macrophage-expressed genes in the pig genome. BMC Genomics 2015; 16:970. [PMID: 26582032 PMCID: PMC4652390 DOI: 10.1186/s12864-015-2111-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Accepted: 10/19/2015] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND The FANTOM5 consortium used Cap Analysis of Gene Expression (CAGE) tag sequencing to produce a comprehensive atlas of promoters and enhancers within the human and mouse genomes. We reasoned that the mapping of these regulatory elements to the pig genome could provide useful annotation and evidence to support assignment of orthology. RESULTS For human transcription start sites (TSS) associated with annotated human-mouse orthologs, 17% mapped to the pig genome but not to the mouse, 10% mapped only to the mouse, and 55% mapped to both pig and mouse. Around 17% did not map to either species. The mapping percentages were lower where there was not clear orthology relationship, but in every case, mapping to pig was greater than to mouse, and the degree of homology was also greater. Combined mapping of mouse and human CAGE-defined promoters identified at least one putative conserved TSS for >16,000 protein-coding genes. About 54% of the predicted locations of regulatory elements in the pig genome were supported by CAGE and/or RNA-Seq analysis from pig macrophages. CONCLUSIONS Comparative mapping of promoters and enhancers from humans and mice can provide useful preliminary annotation of other animal genomes. The data also confirm extensive gain and loss of regulatory elements between species, and the likelihood that pigs provide a better model than mice for human gene regulation and function.
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Affiliation(s)
- Christelle Robert
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, EH25 9RG, Edinburgh, UK.
| | - Ronan Kapetanovic
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.
| | - Dario Beraldi
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Center, Robinson Way, Cambridge, CB2 0RE, UK.
| | - Mick Watson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, EH25 9RG, Edinburgh, UK.
- Edinburgh Genomics, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
| | - Alan L Archibald
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, EH25 9RG, Edinburgh, UK.
| | - David A Hume
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, EH25 9RG, Edinburgh, UK.
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14
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Yu Y, Fuscoe JC, Zhao C, Guo C, Jia M, Qing T, Bannon DI, Lancashire L, Bao W, Du T, Luo H, Su Z, Jones WD, Moland CL, Branham WS, Qian F, Ning B, Li Y, Hong H, Guo L, Mei N, Shi T, Wang KY, Wolfinger RD, Nikolsky Y, Walker SJ, Duerksen-Hughes P, Mason CE, Tong W, Thierry-Mieg J, Thierry-Mieg D, Shi L, Wang C. A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages. Nat Commun 2015; 5:3230. [PMID: 24510058 PMCID: PMC3926002 DOI: 10.1038/ncomms4230] [Citation(s) in RCA: 276] [Impact Index Per Article: 27.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2013] [Accepted: 01/10/2014] [Indexed: 02/07/2023] Open
Abstract
The rat has been used extensively as a model for evaluating chemical toxicities and for understanding drug mechanisms. However, its transcriptome across multiple organs, or developmental stages, has not yet been reported. Here we show, as part of the SEQC consortium efforts, a comprehensive rat transcriptomic BodyMap created by performing RNA-Seq on 320 samples from 11 organs of both sexes of juvenile, adolescent, adult and aged Fischer 344 rats. We catalogue the expression profiles of 40,064 genes, 65,167 transcripts, 31,909 alternatively spliced transcript variants and 2,367 non-coding genes/non-coding RNAs (ncRNAs) annotated in AceView. We find that organ-enriched, differentially expressed genes reflect the known organ-specific biological activities. A large number of transcripts show organ-specific, age-dependent or sex-specific differential expression patterns. We create a web-based, open-access rat BodyMap database of expression profiles with crosslinks to other widely used databases, anticipating that it will serve as a primary resource for biomedical research using the rat model. Gene expression is highly variable between tissues, and changes during development and with age. Here, the authors provide a comprehensive RNA-Seq analysis of the rat transcriptome, spanning eleven organs, four developmental stages and both sexes.
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Affiliation(s)
- Ying Yu
- 1] Center for Pharmacogenomics, State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai 201203, China [2]
| | - James C Fuscoe
- 1] National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA [2]
| | - Chen Zhao
- Center for Pharmacogenomics, State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai 201203, China
| | - Chao Guo
- Functional Genomics Core, Beckman Research Institute, City of Hope, Duarte, California 91010, USA
| | - Meiwen Jia
- Center for Pharmacogenomics, State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai 201203, China
| | - Tao Qing
- Center for Pharmacogenomics, State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai 201203, China
| | - Desmond I Bannon
- Army Institute of Public Health, U.S. Army Public Health Command, Aberdeen Proving Ground, Maryland 21010, USA
| | - Lee Lancashire
- Computation Biology and Bioinformatics, IP & Science, Thomson Reuters, London EC1N 8JS, UK
| | - Wenjun Bao
- SAS Institute Inc., Cary, North Carolina 27513, USA
| | - Tingting Du
- Center for Pharmacogenomics, State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai 201203, China
| | - Heng Luo
- Center for Pharmacogenomics, State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai 201203, China
| | - Zhenqiang Su
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | | | - Carrie L Moland
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - William S Branham
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - Feng Qian
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - Baitang Ning
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - Yan Li
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - Huixiao Hong
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - Lei Guo
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - Nan Mei
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - Tieliu Shi
- The Center for Bioinformatics and The Institute of Biomedical Sciences, College of Life Science, Shanghai 200241, China
| | - Kevin Y Wang
- Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | | | - Yuri Nikolsky
- Computation Biology and Bioinformatics, IP & Science, Thomson Reuters, London EC1N 8JS, UK
| | - Stephen J Walker
- Wake Forest Institute for Regenerative Medicine, Wake Forest University Health Sciences, Winston-Salem, North Carolina 27157, USA
| | - Penelope Duerksen-Hughes
- Department of Basic Sciences, School of Medicine, Loma Linda University, Loma Linda, California 92350, USA
| | - Christopher E Mason
- Department of Physiology & Biophysics and the Institute for Computational Biomedicine, Cornell University, New York, New York 10021, USA
| | - Weida Tong
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA
| | - Jean Thierry-Mieg
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Danielle Thierry-Mieg
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Leming Shi
- 1] Center for Pharmacogenomics, State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai 201203, China [2] National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 92079, USA [3] Fudan-Zhangjiang Center for Clinical Genomics and Zhangjiang Center for Translational Medicine, Shanghai 201203, China
| | - Charles Wang
- Center for Genomics and Division of Microbiology & Molecular Genetics, School of Medicine, Loma Linda University, Loma Linda, California 92350, USA
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15
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Richardson L, Graham L, Moss J, Burton N, Roochun Y, Armit C, Baldock RA. Developing the eHistology Atlas. Database (Oxford) 2015; 2015:bav105. [PMID: 26500249 PMCID: PMC4618478 DOI: 10.1093/database/bav105] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Revised: 09/17/2015] [Accepted: 09/30/2015] [Indexed: 01/03/2023]
Abstract
The eMouseAtlas project has undertaken to generate a new resource providing access to high-resolution colour images of the slides used in the renowned textbook 'The Atlas of Mouse Development' by Matthew H. Kaufman. The original histology slides were digitized, and the associated anatomy annotations captured for display in the new resource. These annotations were assigned to objects in the standard reference anatomy ontology, allowing the eHistology resource to be linked to other data resources including the Edinburgh Mouse Atlas Gene-Expression database (EMAGE) an the Mouse Genome Informatics (MGI) gene-expression database (GXD). The provision of the eHistology Atlas resource was assisted greatly by the expertise of the eMouseAtlas project in delivering large image datasets within a web environment, using IIP3D technology. This technology also permits future extensions to the resource through the addition of further layers of data and annotations to the resource. Database URL: www.emouseatlas.org/emap/eHistology/index.php.
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Affiliation(s)
- Lorna Richardson
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Liz Graham
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Julie Moss
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Nick Burton
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Yogmatee Roochun
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Chris Armit
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Richard A Baldock
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
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16
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Armit C, Richardson L, Hill B, Yang Y, Baldock RA. eMouseAtlas informatics: embryo atlas and gene expression database. Mamm Genome 2015; 26:431-40. [PMID: 26296321 PMCID: PMC4602050 DOI: 10.1007/s00335-015-9596-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2015] [Accepted: 07/20/2015] [Indexed: 12/19/2022]
Abstract
A significant proportion of developmental biology data is presented in the form of images at morphologically diverse stages of development. The curation of these datasets presents different challenges to that of sequence/text-based data. Towards this end, the eMouseAtlas project created a digital atlas of mouse embryo development as a means of understanding developmental anatomy and exploring the relationship between genes and development in a spatial context. Using the morphological staging system pioneered by Karl Theiler, the project has generated 3D models of post-implantation mouse development and used them as a spatial framework for the delineation of anatomical components and for archiving in situ gene expression data in the EMAGE database. This has allowed us to develop a unique online resource for mouse developmental biology. We describe here the underlying structure of the resource, as well as some of the tools that have been developed to allow users to mine the curated image data. These tools include our IIP3D/X3DOM viewer that allows 3D visualisation of anatomy and/or gene expression in the context of a web browser, and the eHistology resource that extends this functionality to allow visualisation of high-resolution cellular level images of histology sections. Furthermore, we review some of the informatics aspects of eMouseAtlas to provide a deeper insight into the use of the atlas and gene expression database.
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Affiliation(s)
- Chris Armit
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland
| | - Lorna Richardson
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland
| | - Bill Hill
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland
| | - Yiya Yang
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland
| | - Richard A Baldock
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland.
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17
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Papatheodorou I, Oellrich A, Smedley D. Linking gene expression to phenotypes via pathway information. J Biomed Semantics 2015; 6:17. [PMID: 25901272 PMCID: PMC4404592 DOI: 10.1186/s13326-015-0013-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Accepted: 03/19/2015] [Indexed: 11/10/2022] Open
Abstract
Establishing robust links among gene expression, pathways and phenotypes is critical for understanding diseases and developing treatments. In recent years there have been many efforts to develop the computational means to traverse from genes to gene expression, model pathways and classify phenotypes. Numerous ontologies and other controlled vocabularies have been developed, as well as computational methods to combine and mine these data sets and establish connections. Here we discuss these efforts and identify areas of future work that could lead to a better integration of genes, pathways and phenotypes to provide insights into the mechanisms under which gene mutations affect expression and pathways and how these effects are manifested onto the phenotype.
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Affiliation(s)
- Irene Papatheodorou
- Mouse Developmental Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, CB1 10SA, Hinxton, UK
| | - Anika Oellrich
- Mouse Developmental Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, CB1 10SA, Hinxton, UK
| | - Damian Smedley
- Mouse Developmental Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, CB1 10SA, Hinxton, UK
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18
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Liddelow SA, Dzięgielewska KM, Møllgård K, Whish SC, Noor NM, Wheaton BJ, Gehwolf R, Wagner A, Traweger A, Bauer H, Bauer HC, Saunders NR. Cellular specificity of the blood-CSF barrier for albumin transfer across the choroid plexus epithelium. PLoS One 2014; 9:e106592. [PMID: 25211495 PMCID: PMC4161337 DOI: 10.1371/journal.pone.0106592] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2014] [Accepted: 08/01/2014] [Indexed: 01/29/2023] Open
Abstract
To maintain the precise internal milieu of the mammalian central nervous system, well-controlled transfer of molecules from periphery into brain is required. Recently the soluble and cell-surface albumin-binding glycoprotein SPARC (secreted protein acidic and rich in cysteine) has been implicated in albumin transport into developing brain, however the exact mechanism remains unknown. We postulate that SPARC is a docking site for albumin, mediating its uptake and transfer by choroid plexus epithelial cells from blood into cerebrospinal fluid (CSF). We used in vivo physiological measurements of transfer of endogenous (mouse) and exogenous (human) albumins, in situ Proximity Ligation Assay (in situ PLA), and qRT-PCR experiments to examine the cellular mechanism mediating protein transfer across the blood–CSF interface. We report that at all developmental stages mouse albumin and SPARC gave positive signals with in situ PLAs in plasma, CSF and within individual plexus cells suggesting a possible molecular interaction. In contrast, in situ PLA experiments in brain sections from mice injected with human albumin showed positive signals for human albumin in the vascular compartment that were only rarely identifiable within choroid plexus cells and only at older ages. Concentrations of both endogenous mouse albumin and exogenous (intraperitoneally injected) human albumin were estimated in plasma and CSF and expressed as CSF/plasma concentration ratios. Human albumin was not transferred through the mouse blood–CSF barrier to the same extent as endogenous mouse albumin, confirming results from in situ PLA. During postnatal development Sparc gene expression was higher in early postnatal ages than in the adult and changed in response to altered levels of albumin in blood plasma in a differential and developmentally regulated manner. Here we propose a possible cellular route and mechanism by which albumin is transferred from blood into CSF across a sub-population of specialised choroid plexus epithelial cells.
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Affiliation(s)
- Shane A. Liddelow
- Department of Pharmacology & Therapeutics, University of Melbourne, Melbourne, Australia
- Department of Neurobiology, Stanford University, Stanford, California, United States of America
| | | | - Kjeld Møllgård
- Institute of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Sophie C. Whish
- Department of Pharmacology & Therapeutics, University of Melbourne, Melbourne, Australia
| | - Natassya M. Noor
- Department of Pharmacology & Therapeutics, University of Melbourne, Melbourne, Australia
| | - Benjamin J. Wheaton
- Department of Pharmacology & Therapeutics, University of Melbourne, Melbourne, Australia
| | - Renate Gehwolf
- Institute of Tendon and Bone Regeneration, Paracelsus Medical University, Salzburg, Austria
| | - Andrea Wagner
- Department of Organismic Biology, University of Salzburg, Salzburg, Austria
- Institute of Tendon and Bone Regeneration, Paracelsus Medical University, Salzburg, Austria
| | - Andreas Traweger
- Institute of Tendon and Bone Regeneration, Paracelsus Medical University, Salzburg, Austria
| | - Hannelore Bauer
- Department of Organismic Biology, University of Salzburg, Salzburg, Austria
| | - Hans-Christian Bauer
- Institute of Tendon and Bone Regeneration, Paracelsus Medical University, Salzburg, Austria
| | - Norman R. Saunders
- Department of Pharmacology & Therapeutics, University of Melbourne, Melbourne, Australia
- * E-mail:
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19
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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: 14] [Impact Index Per Article: 1.3] [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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20
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Wick HC, Drabkin H, Ngu H, Sackman M, Fournier C, Haggett J, Blake JA, Bianchi DW, Slonim DK. DFLAT: functional annotation for human development. BMC Bioinformatics 2014; 15:45. [PMID: 24507166 PMCID: PMC3928322 DOI: 10.1186/1471-2105-15-45] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2013] [Accepted: 01/28/2014] [Indexed: 11/25/2022] Open
Abstract
Background Recent increases in genomic studies of the developing human fetus and neonate have led to a need for widespread characterization of the functional roles of genes at different developmental stages. The Gene Ontology (GO), a valuable and widely-used resource for characterizing gene function, offers perhaps the most suitable functional annotation system for this purpose. However, due in part to the difficulty of studying molecular genetic effects in humans, even the current collection of comprehensive GO annotations for human genes and gene products often lacks adequate developmental context for scientists wishing to study gene function in the human fetus. Description The Developmental FunctionaL Annotation at Tufts (DFLAT) project aims to improve the quality of analyses of fetal gene expression and regulation by curating human fetal gene functions using both manual and semi-automated GO procedures. Eligible annotations are then contributed to the GO database and included in GO releases of human data. DFLAT has produced a considerable body of functional annotation that we demonstrate provides valuable information about developmental genomics. A collection of gene sets (genes implicated in the same function or biological process), made by combining existing GO annotations with the 13,344 new DFLAT annotations, is available for use in novel analyses. Gene set analyses of expression in several data sets, including amniotic fluid RNA from fetuses with trisomies 21 and 18, umbilical cord blood, and blood from newborns with bronchopulmonary dysplasia, were conducted both with and without the DFLAT annotation. Conclusions Functional analysis of expression data using the DFLAT annotation increases the number of implicated gene sets, reflecting the DFLAT’s improved representation of current knowledge. Blinded literature review supports the validity of newly significant findings obtained with the DFLAT annotations. Newly implicated significant gene sets also suggest specific hypotheses for future research. Overall, the DFLAT project contributes new functional annotation and gene sets likely to enhance our ability to interpret genomic studies of human fetal and neonatal development.
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Affiliation(s)
- Heather C Wick
- Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA.
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21
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Leslie EJ, Marazita ML. Genetics of cleft lip and cleft palate. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2013; 163C:246-58. [PMID: 24124047 DOI: 10.1002/ajmg.c.31381] [Citation(s) in RCA: 298] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Orofacial clefts are common birth defects and can occur as isolated, nonsyndromic events or as part of Mendelian syndromes. There is substantial phenotypic diversity in individuals with these birth defects and their family members: from subclinical phenotypes to associated syndromic features that is mirrored by the many genes that contribute to the etiology of these disorders. Identification of these genes and loci has been the result of decades of research using multiple genetic approaches. Significant progress has been made recently due to advances in sequencing and genotyping technologies, primarily through the use of whole exome sequencing and genome-wide association studies. Future progress will hinge on identifying functional variants, investigation of pathway and other interactions, and inclusion of phenotypic and ethnic diversity in studies.
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22
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Brinkley JF, Borromeo C, Clarkson M, Cox TC, Cunningham MJ, Detwiler LT, Heike CL, Hochheiser H, Mejino JLV, Travillian RS, Shapiro LG. The ontology of craniofacial development and malformation for translational craniofacial research. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2013; 163C:232-45. [PMID: 24124010 DOI: 10.1002/ajmg.c.31377] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
We introduce the Ontology of Craniofacial Development and Malformation (OCDM) as a mechanism for representing knowledge about craniofacial development and malformation, and for using that knowledge to facilitate integrating craniofacial data obtained via multiple techniques from multiple labs and at multiple levels of granularity. The OCDM is a project of the NIDCR-sponsored FaceBase Consortium, whose goal is to promote and enable research into the genetic and epigenetic causes of specific craniofacial abnormalities through the provision of publicly accessible, integrated craniofacial data. However, the OCDM should be usable for integrating any web-accessible craniofacial data, not just those data available through FaceBase. The OCDM is based on the Foundational Model of Anatomy (FMA), our comprehensive ontology of canonical human adult anatomy, and includes modules to represent adult and developmental craniofacial anatomy in both human and mouse, mappings between homologous structures in human and mouse, and associated malformations. We describe these modules, as well as prototype uses of the OCDM for integrating craniofacial data. By using the terms from the OCDM to annotate data, and by combining queries over the ontology with those over annotated data, it becomes possible to create "intelligent" queries that can, for example, find gene expression data obtained from mouse structures that are precursors to homologous human structures involved in malformations such as cleft lip. We suggest that the OCDM can be useful not only for integrating craniofacial data, but also for expressing new knowledge gained from analyzing the integrated data.
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23
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Mabbott NA, Baillie JK, Brown H, Freeman TC, Hume DA. An expression atlas of human primary cells: inference of gene function from coexpression networks. BMC Genomics 2013; 14:632. [PMID: 24053356 PMCID: PMC3849585 DOI: 10.1186/1471-2164-14-632] [Citation(s) in RCA: 313] [Impact Index Per Article: 26.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2013] [Accepted: 06/25/2013] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND The specialisation of mammalian cells in time and space requires genes associated with specific pathways and functions to be co-ordinately expressed. Here we have combined a large number of publically available microarray datasets derived from human primary cells and analysed large correlation graphs of these data. RESULTS Using the network analysis tool BioLayout Express3D we identify robust co-associations of genes expressed in a wide variety of cell lineages. We discuss the biological significance of a number of these associations, in particular the coexpression of key transcription factors with the genes that they are likely to control. CONCLUSIONS We consider the regulation of genes in human primary cells and specifically in the human mononuclear phagocyte system. Of particular note is the fact that these data do not support the identity of putative markers of antigen-presenting dendritic cells, nor classification of M1 and M2 activation states, a current subject of debate within immunological field. We have provided this data resource on the BioGPS web site (http://biogps.org/dataset/2429/primary-cell-atlas/) and on macrophages.com (http://www.macrophages.com/hu-cell-atlas).
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Affiliation(s)
- Neil A Mabbott
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Edinburgh EH25 9RG, UK
| | - J Kenneth Baillie
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Edinburgh EH25 9RG, UK
| | - Helen Brown
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Edinburgh EH25 9RG, UK
| | - Tom C Freeman
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Edinburgh EH25 9RG, UK
| | - David A Hume
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Edinburgh EH25 9RG, UK
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Norris FC, Wong MD, Greene NDE, Scambler PJ, Weaver T, Weninger WJ, Mohun TJ, Henkelman RM, Lythgoe MF. A coming of age: advanced imaging technologies for characterising the developing mouse. Trends Genet 2013; 29:700-11. [PMID: 24035368 DOI: 10.1016/j.tig.2013.08.004] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2013] [Revised: 07/17/2013] [Accepted: 08/12/2013] [Indexed: 12/21/2022]
Abstract
The immense challenge of annotating the entire mouse genome has stimulated the development of cutting-edge imaging technologies in a drive for novel information. These techniques promise to improve understanding of the genes involved in embryo development, at least one third of which have been shown to be essential. Aligning advanced imaging technologies with biological needs will be fundamental to maximising the number of phenotypes discovered in the coming years. International efforts are underway to meet this challenge through an integrated and sophisticated approach to embryo phenotyping. We review rapid advances made in the imaging field over the past decade and provide a comprehensive examination of the relative merits of current and emerging techniques. The aim of this review is to provide a guide to state-of-the-art embryo imaging that will enable informed decisions as to which technology to use and fuel conversations between expert imaging laboratories, researchers, and core mouse production facilities.
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Affiliation(s)
- Francesca C Norris
- University College London (UCL) Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, London, UK; Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), UCL, London, UK
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25
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Harmston N, Lenhard B. Chromatin and epigenetic features of long-range gene regulation. Nucleic Acids Res 2013; 41:7185-99. [PMID: 23766291 PMCID: PMC3753629 DOI: 10.1093/nar/gkt499] [Citation(s) in RCA: 88] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
The precise regulation of gene transcription during metazoan development is controlled by a complex system of interactions between transcription factors, histone modifications and modifying enzymes and chromatin conformation. Developments in chromosome conformation capture technologies have revealed that interactions between regions of chromatin are pervasive and highly cell-type specific. The movement of enhancers and promoters in and out of higher-order chromatin structures within the nucleus are associated with changes in expression and histone modifications. However, the factors responsible for mediating these changes and determining enhancer:promoter specificity are still not completely known. In this review, we summarize what is known about the patterns of epigenetic and chromatin features characteristic of elements involved in long-range interactions. In addition, we review the insights into both local and global patterns of chromatin interactions that have been revealed by the latest experimental and computational methods.
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Affiliation(s)
- Nathan Harmston
- MRC Clinical Sciences Centre, Faculty of Medicine, Imperial College, London W12 0NN, UK, Institute of Clinical Sciences, Faculty of Medicine, Imperial College, London W12 0NN, UK and Department of Informatics, University of Bergen, Thromøhlensgate 55, N-5008 Bergen, Norway
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Wong F, Welten MCM, Anderson C, Bain AA, Liu J, Wicks MN, Pavlovska G, Davey MG, Murphy P, Davidson D, Tickle CA, Stern CD, Baldock RA, Burt DW. eChickAtlas: an introduction to the database. Genesis 2013; 51:365-71. [PMID: 23355415 DOI: 10.1002/dvg.22374] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2012] [Revised: 12/21/2012] [Accepted: 01/17/2013] [Indexed: 11/12/2022]
Abstract
The precise control of gene expression is critical in embryonic development. Quantitative assays, such as microarrays and RNA sequencing, provide gene expression levels for a large number of genes, but do not contain spatial information. In contrast, in situ methods, such as in situ hybridization and immunohistochemistry, provide spatial resolution, but poor quantification and can only reveal the expression of one, or very few genes at a time. Furthermore, the usual methods of documenting the results, by photographing whole mounts or sections, makes it very difficult to assess the three-dimensional (3D) relationships between expressing and nonexpressing cells. Optical projection tomography (OPT) can capture the full 3D expression pattern in a whole embryo at a reasonable level of resolution and at moderately high throughput. A large database containing spatio-temporal patterns of expression for the mouse (e-Mouse Atlas Project, EMAP, www.emouseatlas.org) has been created, incorporating 3D information. Like the mouse, the chick is an important model in developmental biology and translational studies. To facilitate comparisons between these important model organisms, we have created a 3D anatomical atlas, accompanied by an anatomical ontology of the chick embryo and a database of gene expression patterns during chick development. This database is publicly available (www.echickatlas.org).
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Affiliation(s)
- Frances Wong
- Division of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, United Kingdom
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