Jacqui White

EuroPhenome: a repository for high-throughput mouse phenotyping data

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.

The critical role of histone H2A-deubiquitinase Mysm1 in hematopoiesis and lymphocyte differentiation

Stem cell differentiation and lineage specification depend on coordinated programs of gene expression, but our knowledge of the chromatin-modifying factors regulating these events remains incomplete. Ubiquitination of histone H2A (H2A-K119u) is a common chromatin modification associated with gene silencing, and controlled by the ubiquitin-ligase polycomb repressor complex 1 (PRC1) and H2A-deubiquitinating enzymes (H2A-DUBs). The roles of H2A-DUBs in mammalian development, stem cells, and hematopoiesis have not been addressed. Here we characterized an H2A-DUB targeted mouse line Mysm1(tm1a/tm1a) and demonstrated defects in BM hematopoiesis, resulting in lymphopenia, anemia, and thrombocytosis. Development of lymphocytes was impaired from the earliest stages of their differentiation, and there was also a depletion of erythroid cells and a defect in erythroid progenitor function. These phenotypes resulted from a cell-intrinsic requirement for Mysm1 in the BM. Importantly, Mysm1(tm1a/tm1a) HSCs were functionally impaired, and this was associated with elevated levels of reactive oxygen species, γH2AX DNA damage marker, and p53 protein in the hematopoietic progenitors. Overall, these data establish a role for Mysm1 in the maintenance of BM stem cell function, in the control of oxidative stress and genetic stability in hematopoietic progenitors, and in the development of lymphoid and erythroid lineages.

Mouse Phenotype Database Integration Consortium: integration [corrected] of mouse phenome data resources.

Understanding the functions encoded in the mouse genome will be central to an understanding of the genetic basis of human disease. To achieve this it will be essential to be able to characterize the phenotypic consequences of variation and alterations in individual genes. Data on the phenotypes of mouse strains are currently held in a number of different forms (detailed descriptions of mouse lines, first-line phenotyping data on novel mutations, data on the normal features of inbred lines) at many sites worldwide. For the most efficient use of these data sets, we have initiated a process to develop standards for the description of phenotypes (using ontologies) and file formats for the description of phenotyping protocols and phenotype data sets. This process is ongoing and needs to be supported by the wider mouse genetics and phenotyping communities to succeed. We invite interested parties to contact us as we develop this process further.

Maps of Open Chromatin Guide the Functional Follow-Up of Genome-Wide Association Signals: Application to Hematological Traits

Turning genetic discoveries identified in genome-wide association (GWA) studies into biological mechanisms is an important challenge in human genetics. Many GWA signals map outside exons, suggesting that the associated variants may lie within regulatory regions. We applied the formaldehyde-assisted isolation of regulatory elements (FAIRE) method in a megakaryocytic and an erythroblastoid cell line to map active regulatory elements at known loci associated with hematological quantitative traits, coronary artery disease, and myocardial infarction. We showed that the two cell types exhibit distinct patterns of open chromatin and that cell-specific open chromatin can guide the finding of functional variants. We identified an open chromatin region at chromosome 7q22.3 in megakaryocytes but not erythroblasts, which harbors the common non-coding sequence variant rs342293 known to be associated with platelet volume and function. Resequencing of this open chromatin region in 643 individuals provided strong evidence that rs342293 is the only putative causative variant in this region. We demonstrated that the C- and G-alleles differentially bind the transcription factor EVI1 affecting PIK3CG gene expression in platelets and macrophages. A protein–protein interaction network including up- and down-regulated genes in Pik3cg knockout mice indicated that PIK3CG is associated with gene pathways with an established role in platelet membrane biogenesis and thrombus formation. Thus, rs342293 is the functional common variant at this locus; to the best of our knowledge this is the first such variant to be elucidated among the known platelet quantitative trait loci (QTLs). Our data suggested a molecular mechanism by which a non-coding GWA index SNP modulates platelet phenotype.

Integration of Mouse Phenome Data Resources

Understanding the functions encoded in the mouse genome will be central to an understanding of the genetic basis of human disease. To achieve this it will be essential to be able to characterise the phenotypic consequences of variation and alterations in individual genes. Data on the phenotypes of mouse strains are currently held in a number of different forms (detailed descriptions of mouse lines, first line phenotyping data on novel mutations, data on the normal features of inbred lines, etc.) at many sites worldwide. For the most efficient use of these data sets, we have set in train a process to develop standards for the description of phenotypes (using ontologies), and file formats for the description of phenotyping protocols and phenotype data sets. This process is ongoing, and needs to be supported by the wider mouse genetics and phenotyping communities to succeed. We invite interested parties to contact us as we develop this process further.

Establishment of mouse expanded potential stem cells

Mouse embryonic stem cells derived from the epiblast contribute to the somatic lineages and the germline but are excluded from the extra-embryonic tissues that are derived from the trophectoderm and the primitive endoderm upon reintroduction to the blastocyst. Here we report that cultures of expanded potential stem cells can be established from individual eight-cell blastomeres, and by direct conversion of mouse embryonic stem cells and induced pluripotent stem cells. Remarkably, a single expanded potential stem cell can contribute both to the embryo proper and to the trophectoderm lineages in a chimaera assay. Bona fide trophoblast stem cell lines and extra-embryonic endoderm stem cells can be directly derived from expanded potential stem cells in vitro. Molecular analyses of the epigenome and single-cell transcriptome reveal enrichment for blastomere-specific signature and a dynamic DNA methylome in expanded potential stem cells. The generation of mouse expanded potential stem cells highlights the feasibility of establishing expanded potential stem cells for other mammalian species.

A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction.

The developmental and physiological complexity of the auditory system is likely reflected in the underlying set of genes involved in auditory function. In humans, over 150 non-syndromic loci have been identified, and there are more than 400 human genetic syndromes with a hearing loss component. Over 100 non-syndromic hearing loss genes have been identified in mouse and human, but we remain ignorant of the full extent of the genetic landscape involved in auditory dysfunction. As part of the International Mouse Phenotyping Consortium, we undertook a hearing loss screen in a cohort of 3006 mouse knockout strains. In total, we identify 67 candidate hearing loss genes. We detect known hearing loss genes, but the vast majority, 52, of the candidate genes were novel. Our analysis reveals a large and unexplored genetic landscape involved with auditory function.The full extent of the genetic basis for hearing impairment is unknown. Here, as part of the International Mouse Phenotyping Consortium, the authors perform a hearing loss screen in 3006 mouse knockout strains and identify 52 new candidate genes for genetic hearing loss.

Highly variable penetrance of abnormal phenotypes in embryonic lethal knockout mice.

Background: Identifying genes that are essential for mouse embryonic development and survival through term is a powerful and unbiased way to discover possible genetic determinants of human developmental disorders. Characterising the changes in mouse embryos that result from ablation of lethal genes is a necessary first step towards uncovering their role in normal embryonic development and establishing any correlates amongst human congenital abnormalities. Methods: Here we present results gathered to date in the Deciphering the Mechanisms of Developmental Disorders (DMDD) programme, cataloguing the morphological defects identified from comprehensive imaging of 220 homozygous mutant and 114 wild type embryos from 42 lethal and subviable lines, analysed at E14.5. Results: Virtually all mutant embryos show multiple abnormal phenotypes and amongst the 42 lines these affect most organ systems. Within each mutant line, the phenotypes of individual embryos form distinct but overlapping sets. Subcutaneous edema, malformations of the heart or great vessels, abnormalities in forebrain morphology and the musculature of the eyes are all prevalent phenotypes, as is loss or abnormal size of the hypoglossal nerve. Conclusions: Overall, the most striking finding is that no matter how profound the malformation, each phenotype shows highly variable penetrance within a mutant line. These findings have challenging implications for efforts to identify human disease correlates.

A staging system for correct phenotype interpretation of mouse embryos harvested on embryonic day 14 (E14.5)

We present a simple and quick system for accurately scoring the developmental progress of mouse embryos harvested on embryonic day 14 (E14.5). Based solely on the external appearance of the maturing forelimb, we provide a convenient way to distinguish six developmental sub‐stages. Using a variety of objective morphometric data obtained from the commonly used C57BL/6N mouse strain, we show that these stages correlate precisely with the growth of the entire embryo and its organs. Applying the new staging system to phenotype analyses of E14.5 embryos of 58 embryonic lethal null mutant lines from the DMDD research programme (https://dmdd.org.uk) and its pilot, we show that homozygous mutant embryos are frequently delayed in development. To demonstrate the importance of our staging system for correct phenotype interpretation, we describe stage‐specific changes of the palate, heart and gut, and provide examples in which correct diagnosis of malformations relies on correct staging.

High throughput automated analysis of big flow cytometry data

The rapid expansion of flow cytometry applications has outpaced the functionality of traditional manual analysis tools used to interpret flow cytometry data. Scientists are faced with the daunting prospect of manually identifying interesting cell populations in 50-dimensional datasets, equalling the complexity previously only reached in mass cytometry. Data can no longer be analyzed or interpreted fully by manual approaches. While automated gating has been the focus of intense efforts, there are many significant additional steps to the analytical pipeline (e.g., cleaning the raw files, event outlier detection, extracting immunophenotypes). We review the components of a customized automated analysis pipeline that can be generally applied to large scale flow cytometry data. We demonstrate these methodologies on data collected by the International Mouse Phenotyping Consortium (IMPC).