The Mouse Genome Database (MGD): facilitating mouse as a model for human biology and disease

Predicted Molecular Effects of Sequence Variants Link to System Level of Disease

Developments in experimental and computational biology are advancing our understanding of how protein sequence variation impacts molecular protein function. However, the leap from the micro level of molecular function to the macro level of the whole organism, e.g. disease, remains barred. Here, we present new results emphasizing earlier work that suggested some links from molecular function to disease. We focused on non-synonymous single nucleotide variants, also referred to as single amino acid variants (SAVs). Building upon OMIA (Online Mendelian Inheritance in Animals), we introduced a curated set of 117 disease-causing SAVs in animals. Methods optimized to capture effects upon molecular function often correctly predict human (OMIM) and animal (OMIA) Mendelian disease-causing variants. We also predicted effects of human disease-causing variants in the mouse model, i.e. we put OMIM SAVs into mouse orthologs. Overall, fewer variants were predicted with effect in the model organism than in the original organism. Our results, along with other recent studies, demonstrate that predictions of molecular effects capture some important aspects of disease. Thus, in silico methods focusing on the micro level of molecular function can help to understand the macro system level of disease.

The variations in the genetic sequence between individuals affect the gene-product, i.e. the protein differently. Some variants have no measurable effect (are neutral), while others affect protein function. Some of those effects are so severe they cause so called monogenic Mendelian diseases, i.e. diseases triggered by a single letter change. Some in silico methods predict the molecular impact of sequence variation. However, both experimental and computational analyses struggle to generalize from the effect upon molecular protein function to the effect upon the organism such as a disease. Here, we confirmed that methods predicting molecular effects correctly capture the type of effects causing Mendelian diseases in human and introduced a data set for animal diseases that was also captured by predictions methods. Predicted effects were less when in silico testing human variants in an animal model (here mouse). This is important to know because “mouse models” are common to study human diseases. Overall, we provided some evidence for a link between the molecular level and some type of disease.

New era in genetics of early-onset muscle disease: Breakthroughs and challenges

Early-onset muscle disease includes three major entities that present generally at or before birth: congenital myopathies, congenital muscular dystrophies and congenital myasthenic syndromes. Almost exclusively there is weakness and hypotonia, although cases manifesting hypertonia are increasingly being recognised. These diseases display a wide phenotypic and genetic heterogeneity, with the uptake of next generation sequencing resulting in an unparalleled extension of the phenotype-genotype correlations and "diagnosis by sequencing" due to unbiased sequencing. Perhaps now more than ever, detailed clinical evaluations are necessary to guide the genetic diagnosis; with arrival at a molecular diagnosis frequently occurring following dialogue between the molecular geneticist, the referring clinician and the pathologist. There is an ever-increasing blurring of the boundaries between the congenital myopathies, dystrophies and myasthenic syndromes. In addition, many novel disease genes have been described and new insights have been gained into skeletal muscle development and function. Despite the advances made, a significant percentage of patients remain without a molecular diagnosis, suggesting that there are many more human disease genes and mechanisms to identify. It is now technically- and clinically-feasible to perform next generation sequencing for severe diseases on a population-wide scale, such that preconception-carrier screening can occur. Newborn screening for selected early-onset muscle diseases is also technically and ethically-achievable, with benefits to the patient and family from early management of these diseases and should also be implemented. The need for world-wide Reference Centres to meticulously curate polymorphisms and mutations within a particular gene is becoming increasingly apparent, particularly for interpretation of variants in the large genes which cause early-onset myopathies: NEB, RYR1 and TTN. Functional validation of candidate disease variants is crucial for accurate interpretation of next generation sequencing and appropriate genetic counseling. Many published "pathogenic" variants are too frequent in control populations and are thus likely rare polymorphisms. Mechanisms need to be put in place to systematically update the classification of variants such that accurate interpretation of variants occurs. In this review, we highlight the recent advances made and the challenges ahead for the molecular diagnosis of early-onset muscle diseases.

Molecular systems evaluation of oligomerogenic APP(E693Q) and fibrillogenic APP(KM670/671NL)/PSEN1(Δexon9) mouse models identifies shared features with human Alzheimer's brain molecular pathology

Identification and characterization of molecular mechanisms that connect genetic risk factors to initiation and evolution of disease pathophysiology represent major goals and opportunities for improving therapeutic and diagnostic outcomes in Alzheimer's disease (AD). Integrative genomic analysis of the human AD brain transcriptome holds potential for revealing novel mechanisms of dysfunction that underlie the onset and/or progression of the disease. We performed an integrative genomic analysis of brain tissue-derived transcriptomes measured from two lines of mice expressing distinct mutant AD-related proteins. The first line expresses oligomerogenic mutant APP(E693Q) inside neurons, leading to the accumulation of amyloid beta (Aβ) oligomers and behavioral impairment, but never develops parenchymal fibrillar amyloid deposits. The second line expresses APP(KM670/671NL)/PSEN1(Δexon9) in neurons and accumulates fibrillar Aβ amyloid and amyloid plaques accompanied by neuritic dystrophy and behavioral impairment. We performed RNA sequencing analyses of the dentate gyrus and entorhinal cortex from each line and from wild-type mice. We then performed an integrative genomic analysis to identify dysregulated molecules and pathways, comparing transgenic mice with wild-type controls as well as to each other. We also compared these results with datasets derived from human AD brain. Differential gene and exon expression analysis revealed pervasive alterations in APP/Aβ metabolism, epigenetic control of neurogenesis, cytoskeletal organization and extracellular matrix (ECM) regulation. Comparative molecular analysis converged on FMR1 (Fragile X Mental Retardation 1), an important negative regulator of APP translation and oligomerogenesis in the post-synaptic space. Integration of these transcriptomic results with human postmortem AD gene networks, differential expression and differential splicing signatures identified significant similarities in pathway dysregulation, including ECM regulation and neurogenesis, as well as strong overlap with AD-associated co-expression network structures. The strong overlap in molecular systems features supports the relevance of these findings from the AD mouse models to human AD.

Exome sequencing discloses KALRN homozygous variant as likely cause of intellectual disability and short stature in a consanguineous pedigree

BACKGROUND

The recent availability of whole-exome sequencing has opened new possibilities for the evaluation of individuals with genetically undiagnosed intellectual disability.

RESULTS

We report two affected siblings, offspring of first-cousin parents, with intellectual disability, hypotonia, short stature, growth hormone deficiency, and delayed bone age. All members of the nuclear family were genotyped, and exome sequencing was performed in one of the affected individuals. We used an in-house algorithm (CATCH v1.1) that combines homozygosity mapping with exome sequencing results and provides a list of candidate variants. One identified novel homozygous missense variant in KALRN (NM_003947.4:c.3644C>A: p.(Thr1215Lys)) was predicted to be pathogenic by all pathogenicity prediction software used (SIFT, PolyPhen, Mutation Taster). KALRN encodes the protein kalirin, which is a GTP-exchange factor protein with a reported role in cytoskeletal remodeling and dendritic spine formation in neurons. It is known that mice with ablation of Kalrn exhibit age-dependent functional deficits and behavioral phenotypes.

CONCLUSION

Exome sequencing provided initial evidence linking KALRN to monogenic intellectual disability in man, and we propose that KALRN is the causative gene for the autosomal recessive phenotype in this family.

Pleiotropic Genes Affecting Carcass Traits in Bos indicus (Nellore) Cattle Are Modulators of Growth

Two complementary methods, namely Multi-Trait Meta-Analysis and Versatile Gene-Based Test for Genome-wide Association Studies (VEGAS), were used to identify putative pleiotropic genes affecting carcass traits in Bos indicus (Nellore) cattle. The genotypic data comprised over 777,000 single-nucleotide polymorphism markers scored in 995 bulls, and the phenotypic data included deregressed breeding values (dEBV) for weight measurements at birth, weaning and yearling, as well visual scores taken at weaning and yearling for carcass finishing precocity, conformation and muscling. Both analyses pointed to the pleomorphic adenoma gene 1 (PLAG1) as a major pleiotropic gene. VEGAS analysis revealed 224 additional candidates. From these, 57 participated, together with PLAG1, in a network involved in the modulation of the function and expression of IGF1 (insulin like growth factor 1), IGF2 (insulin like growth factor 2), GH1 (growth hormone 1), IGF1R (insulin like growth factor 1 receptor) and GHR (growth hormone receptor), suggesting that those pleiotropic genes operate as satellite regulators of the growth pathway.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection.

An important challenge in infectious disease research is to understand how the human immune system responds to different types of pathogenic infections. An important component of mounting proper response is the transcriptional regulatory network that specifies the context-specific gene expression program in the host cell. However, our understanding of this regulatory network and how it drives context-specific transcriptional programs is incomplete. To address this gap, we performed a network-based analysis of host response to influenza viruses that integrated high-throughput mRNA- and protein measurements and protein-protein interaction networks to identify virus and pathogenicity-specific modules and their upstream physical regulatory programs. We inferred regulatory networks for human cell line and mouse host systems, which recapitulated several known regulators and pathways of the immune response and viral life cycle. We used the networks to study time point and strain-specific subnetworks and to prioritize important regulators of host response. We predicted several novel regulators, both at the mRNA and protein levels, and experimentally verified their role in the virus life cycle based on their ability to significantly impact viral replication.

The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins

Genomics, epigenomics, transcriptomics, proteomics and metabolomics efforts rapidly generate a plethora of data on the activity and levels of biomolecules within mammalian cells. At the same time, curation projects that organize knowledge from the biomedical literature into online databases are expanding. Hence, there is a wealth of information about genes, proteins and their associations, with an urgent need for data integration to achieve better knowledge extraction and data reuse. For this purpose, we developed the Harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins from over 70 major online resources. We extracted, abstracted and organized data into ∼72 million functional associations between genes/proteins and their attributes. Such attributes could be physical relationships with other biomolecules, expression in cell lines and tissues, genetic associations with knockout mouse or human phenotypes, or changes in expression after drug treatment. We stored these associations in a relational database along with rich metadata for the genes/proteins, their attributes and the original resources. The freely available Harmonizome web portal provides a graphical user interface, a web service and a mobile app for querying, browsing and downloading all of the collected data. To demonstrate the utility of the Harmonizome, we computed and visualized gene-gene and attribute-attribute similarity networks, and through unsupervised clustering, identified many unexpected relationships by combining pairs of datasets such as the association between kinase perturbations and disease signatures. We also applied supervised machine learning methods to predict novel substrates for kinases, endogenous ligands for G-protein coupled receptors, mouse phenotypes for knockout genes, and classified unannotated transmembrane proteins for likelihood of being ion channels. The Harmonizome is a comprehensive resource of knowledge about genes and proteins, and as such, it enables researchers to discover novel relationships between biological entities, as well as form novel data-driven hypotheses for experimental validation.Database URL: http://amp.pharm.mssm.edu/Harmonizome.

The Zfhx3-Mediated Axis Regulates Sleep and Interval Timing in Mice

An AT motif-dependent axis, modulated by the transcription factor Zfhx3, influences the circadian clock in mice. In particular, gain of function of Zfhx3 significantly shortens circadian rhythms and alters the transcriptional activity of an important class of neuropeptides that controls intercellular signaling in the suprachiasmatic nucleus (SCN) of the hypothalamus. The ZFHX3/AT axis revealed an important, largely cell-nonautonomous control of the circadian clock. Here, by studying the recently identified circadian mouse mutant Zfhx3^Sci/+, we identify significant effects on sleep homeostasis, a phenomenon that is outside the canonical circadian clock system and that is modulated by the activity of those neuropeptides at a circuit level. We show that the Zfhx3^Sci/+ mutation accelerates the circadian clock at both the hourly scale (i.e., advancing circadian rhythms) and the seconds-to-minutes scale (i.e., anticipating behavioral responses) in mice. The in vivo results are accompanied by a significant presence of sleep targets among protein-protein interactions of the Zfhx3^Sci/+-dependent network.

Mouse models of Hirschsprung disease and other developmental disorders of the enteric nervous system: Old and new players

Hirschsprung disease (HSCR, intestinal aganglionosis) is a multigenic disorder with variable penetrance and severity that has a general population incidence of 1/5000 live births. Studies using animal models have contributed to our understanding of the developmental origins of HSCR and the genetic complexity of this disease. This review summarizes recent progress in understanding control of enteric nervous system (ENS) development through analyses in mouse models. An overview of signaling pathways that have long been known to control the migration, proliferation and differentiation of enteric neural progenitors into and along the developing gut is provided as a framework for the latest information on factors that influence enteric ganglia formation and maintenance. Newly identified genes and additional factors beyond discrete genes that contribute to ENS pathology including regulatory sequences, miRNAs and environmental factors are also introduced. Finally, because HSCR has become a paradigm for complex oligogenic diseases with non-Mendelian inheritance, the importance of gene interactions, modifier genes, and initial studies on genetic background effects are outlined.

Mfn2 deficiency links age-related sarcopenia and impaired autophagy to activation of an adaptive mitophagy pathway

Mitochondrial dysfunction and accumulation of damaged mitochondria are considered major contributors to aging. However, the molecular mechanisms responsible for these mitochondrial alterations remain unknown. Here, we demonstrate that mitofusin 2 (Mfn2) plays a key role in the control of muscle mitochondrial damage. We show that aging is characterized by a progressive reduction in Mfn2 in mouse skeletal muscle and that skeletal muscle Mfn2 ablation in mice generates a gene signature linked to aging. Furthermore, analysis of muscle Mfn2-deficient mice revealed that aging-induced Mfn2 decrease underlies the age-related alterations in metabolic homeostasis and sarcopenia. Mfn2 deficiency reduced autophagy and impaired mitochondrial quality, which contributed to an exacerbated age-related mitochondrial dysfunction. Interestingly, aging-induced Mfn2 deficiency triggers a ROS-dependent adaptive signaling pathway through induction of HIF1α transcription factor and BNIP3. This pathway compensates for the loss of mitochondrial autophagy and minimizes mitochondrial damage. Our findings reveal that Mfn2 repression in muscle during aging is a determinant for the inhibition of mitophagy and accumulation of damaged mitochondria and triggers the induction of a mitochondrial quality control pathway.

Model organism databases: essential resources that need the support of both funders and users

Modern biomedical research depends critically on access to databases that house and disseminate genetic, genomic, molecular, and cell biological knowledge. Even as the explosion of available genome sequences and associated genome-scale data continues apace, the sustainability of professionally maintained biological databases is under threat due to policy changes by major funding agencies. Here, we focus on model organism databases to demonstrate the myriad ways in which biological databases not only act as repositories but actively facilitate advances in research. We present data that show that reducing financial support to model organism databases could prove to be not just scientifically, but also economically, unsound.

TBR1 regulates autism risk genes in the developing neocortex

Exome sequencing studies have identified multiple genes harboring de novo loss-of-function (LoF) variants in individuals with autism spectrum disorders (ASD), including TBR1, a master regulator of cortical development. We performed ChIP-seq for TBR1 during mouse cortical neurogenesis and show that TBR1-bound regions are enriched adjacent to ASD genes. ASD genes were also enriched among genes that are differentially expressed in Tbr1 knockouts, which together with the ChIP-seq data, suggests direct transcriptional regulation. Of the nine ASD genes examined, seven were misexpressed in the cortices of Tbr1 knockout mice, including six with increased expression in the deep cortical layers. ASD genes with adjacent cortical TBR1 ChIP-seq peaks also showed unusually low levels of LoF mutations in a reference human population and among Icelanders. We then leveraged TBR1 binding to identify an appealing subset of candidate ASD genes. Our findings highlight a TBR1-regulated network of ASD genes in the developing neocortex that are relatively intolerant to LoF mutations, indicating that these genes may play critical roles in normal cortical development.

New KEGG pathway-based interpretable features for classifying ageing-related mouse proteins

MOTIVATION

The incidence of ageing-related diseases has been constantly increasing in the last decades, raising the need for creating effective methods to analyze ageing-related protein data. These methods should have high predictive accuracy and be easily interpretable by ageing experts. To enable this, one needs interpretable classification models (supervised machine learning) and features with rich biological meaning. In this paper we propose two interpretable feature types based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and compare them with traditional feature types in hierarchical classification (a more challenging classification task regarding predictive performance) and binary classification (a classification task producing easier to interpret classification models). As far as we know, this work is the first to: (i) explore the potential of the KEGG pathway data in the hierarchical classification setting, (i) use the graph structure of KEGG pathways to create a feature type that quantifies the influence of a current protein on another specific protein within a KEGG pathway graph and (iii) propose a method for interpreting the classification models induced using KEGG features.

RESULTS

We performed tests measuring predictive accuracy considering hierarchical and binary class labels extracted from the Mouse Phenotype Ontology. One of the KEGG feature types leads to the highest predictive accuracy among five individual feature types across three hierarchical classification algorithms. Additionally, the combination of the two KEGG feature types proposed in this work results in one of the best predictive accuracies when using the binary class version of our datasets, at the same time enabling the extraction of knowledge from ageing-related data using quantitative influence information.

AVAILABILITY AND IMPLEMENTATION

The datasets created in this paper will be freely available after publication.

CONTACT

ff79@kent.ac.uk

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Construction of an integrative regulatory element and variation map of the murine Tst locus

BACKGROUND

Given the abundance of new genomic projects and gene annotations, researchers trying to pinpoint causal genetic variants are faced with a challenging task of how to efficiently integrate all current genomic information. The objective of the study was to develop an approach to integrate various genomic annotations for a recently positionally-cloned Tst gene (Thiosulfate Sulfur Transferase, synonym Rhodanese) responsible for the Fob3b2 QTL effect on leanness and improved metabolic parameters. The second aim was to identify and prioritize Tst genetic variants that may be causal for the phenotypic effects.

RESULTS

A bioinformatics approach was developed to integrate existing knowledge of regulatory elements of the Tst gene. The entire Tst locus along with flanking segments was sequenced between our unique polygenic mouse Fat and Lean strains that were generated by divergent selection on adiposity for over 60 generations. The bioinformatics-generated regulatory element map of the Tst locus was then combined with genetic variants between the Fat and Lean mice and with comparative analyses of polymorphisms across 17 mouse strains in order to prioritise likely causal polymorphisms. Two candidate regulatory variants were identified, one overlapping an evolutionary constrained Tst intronic element and the other residing in the seed region of a predicted 3'UTR miRNA binding site.

CONCLUSIONS

This study developed a map of regulatory elements for the Tst locus in mice and identified candidate genetic variants with increased causal likelihood. This map provides a basis for experimental validation and functional analyses of this novel candidate leanness and antidiabetic gene. Our methodological approach is of general utility for analyzing regulation of loci that have limited annotations and experimental evidence and for identifying candidate causal regulatory genetic variants in post-GWAS or post-QTL- cloning studies.

Bidirectional ephrin signaling in bone

The interaction between ephrin ligands (efn) and their receptors (Eph) is capable of inducing forward signaling, from ligand to receptor, as well as reverse signaling, from receptor to ligand. The ephrins are widely expressed in many tissues, where they mediate cell migration and adherence, properties that make the efn-Eph signaling critically important in establishing and maintaining tissue boundaries. The efn-Eph system has also received considerable attention in skeletal tissues, as ligand and receptor combinations are predicted to mediate interactions between the different types of cells that regulate bone development and homeostasis. This review summarizes our current understanding of efn-Eph signaling with a particular focus on the expression and functions of ephrins and their receptors in bone.

Recurrent Microdeletions at Xq27.3-Xq28 and Male Infertility: A Study in the Czech Population

Background

Genetic causes of male infertility are hypothesized to involve multiple types of mutations, from single gene defects to complex chromosome rearrangements. Recently, several recurrent X-chromosome microdeletions (located in subtelomeric region of the long arm) were reported to be associated with male infertility in Spanish and Italian males. The aim of our study was to test their prevalence and infertility association in population of men from the Czech Republic.

Methods

107 males with pathological sperm evaluation resulting in nonobstructive infertility were compared to 131 males with normal fecundity. X-chromosome microdeletions were assessed by +/- PCR with three primer pairs for each region Xcnv64 (Xq27.3), Xcnv67 (Xq28) and Xcnv69 (Xq28). The latter microdeletion was further characterized by amplification across the deleted region, dividing the deletion into three types; A, B and C.

Results

We detected presence of isolated Xcnv64 deletion in 3 patients and 14 controls, and Xcnv69 in 3 patients and 6 controls (1 and 1 patient vs.4 and 1 control for types A and B respectively). There was one control with combined Xcnv64 and Xcnv69 type B deletions, and one patient with combination of Xcnv64 and Xcnv69 type C deletions. The frequency of the deletions was thus not higher in patient compared to control group, Xcnv64 was marginally associated with controls (adjusted Fisher´s exact test P = 0.043), Xcnv69 was not associated (P = 0.452). We excluded presence of more extensive rearrangements in two subjects with combined Xcnv64 and Xcnv69 deletions. There was no Xcnv67 deletion in our cohort.

Conclusion

In conclusion, the two previously reported X-linked microdeletions (Xcnv64 and Xcnv69) do not seem to confer a significant risk to impaired spermatogenesis in the Czech population. The potential clinical role of the previously reported patient-specific Xcnv67 remains to be determined in a larger study population.

Inferring gene-to-phenotype and gene-to-disease relationships at Mouse Genome Informatics: challenges and solutions

Background

Inferring gene-to-phenotype and gene-to-human disease model relationships from annotated mouse phenotypes and disease associations is critical when researching gene function and identifying candidate disease genes. Filtering the various kinds of genotypes to determine which phenotypes are caused by a mutation in a particular gene can be a laborious and time-consuming process.

Methods

At Mouse Genome Informatics (MGI, www.informatics.jax.org), we have developed a gene annotation derivation algorithm that computes gene-to-phenotype and gene-to-disease annotations from our existing corpus of annotations to genotypes. This algorithm differentiates between simple genotypes with causative mutations in a single gene and more complex genotypes where mutations in multiple genes may contribute to the phenotype. As part of the process, alleles functioning as tools (e.g., reporters, recombinases) are filtered out.

Results

Using this algorithm derived gene-to-phenotype and gene-to-disease annotations were created for 16,000 and 2100 mouse markers, respectively, starting from over 57,900 and 4800 genotypes with at least one phenotype and disease annotation, respectively.

Conclusions

Implementation of this algorithm provides consistent and accurate gene annotations across MGI and provides a vital time-savings relative to manual annotation by curators.

BELTracker: evidence sentence retrieval for BEL statements

Biological expression language (BEL) is one of the main formal representation models of biological networks. The primary source of information for curating biological networks in BEL representation has been literature. It remains a challenge to identify relevant articles and the corresponding evidence statements for curating and validating BEL statements. In this paper, we describe BELTracker, a tool used to retrieve and rank evidence sentences from PubMed abstracts and full-text articles for a given BEL statement (per the 2015 task requirements of BioCreative V BEL Task). The system is comprised of three main components, (i) translation of a given BEL statement to an information retrieval (IR) query, (ii) retrieval of relevant PubMed citations and (iii) finding and ranking the evidence sentences in those citations. BELTracker uses a combination of multiple approaches based on traditional IR, machine learning, and heuristics to accomplish the task. The system identified and ranked at least one fully relevant evidence sentence in the top 10 retrieved sentences for 72 out of 97 BEL statements in the test set. BELTracker achieved a precision of 0.392, 0.532 and 0.615 when evaluated with three criteria, namely full, relaxed and context criteria, respectively, by the task organizers. Our team at Mayo Clinic was the only participant in this task. BELTracker is available as a RESTful API and is available for public use.

Database URL:http://www.openbionlp.org:8080/BelTracker/finder/Given_BEL_Statement

Cre Recombinase and Other Tyrosine Recombinases

Tyrosine-type site-specific recombinases (T-SSRs) have opened new avenues for the predictable modification of genomes as they enable precise genome editing in heterologous hosts. These enzymes are ubiquitous in eubacteria, prevalent in archaea and temperate phages, present in certain yeast strains, but barely found in higher eukaryotes. As tools they find increasing use for the generation and systematic modification of genomes in a plethora of organisms. If applied in host organisms, they enable precise DNA cleavage and ligation without the gain or loss of nucleotides. Criteria directing the choice of the most appropriate T-SSR system for genetic engineering include that, whenever possible, the recombinase should act independent of cofactors and that the target sequences should be long enough to be unique in a given genome. This review is focused on recent advancements in our mechanistic understanding of simple T-SSRs and their application in developmental and synthetic biology, as well as in biomedical research.

Germline De Novo Mutations in GNB1 Cause Severe Neurodevelopmental Disability, Hypotonia, and Seizures

Whole-exome sequencing of 13 individuals with developmental delay commonly accompanied by abnormal muscle tone and seizures identified de novo missense mutations enriched within a sub-region of GNB1, a gene encoding the guanine nucleotide-binding protein subunit beta-1, Gβ. These 13 individuals were identified among a base of 5,855 individuals recruited for various undiagnosed genetic disorders. The probability of observing 13 or more de novo mutations by chance among 5,855 individuals is very low (p = 7.1 × 10(-21)), implicating GNB1 as a genome-wide-significant disease-associated gene. The majority of these 13 mutations affect known Gβ binding sites, which suggests that a likely disease mechanism is through the disruption of the protein interface required for Gα-Gβγ interaction (resulting in a constitutively active Gβγ) or through the disruption of residues relevant for interaction between Gβγ and certain downstream effectors (resulting in reduced interaction with the effectors). Strikingly, 8 of the 13 individuals recruited here for a neurodevelopmental disorder have a germline de novo GNB1 mutation that overlaps a set of five recurrent somatic tumor mutations for which recent functional studies demonstrated a gain-of-function effect due to constitutive activation of G protein downstream signaling cascades for some of the affected residues.

Organization, evolution and functions of the human and mouse Ly6/uPAR family genes

Members of the lymphocyte antigen-6 (Ly6)/urokinase-type plasminogen activator receptor (uPAR) superfamily of proteins are cysteine-rich proteins characterized by a distinct disulfide bridge pattern that creates the three-finger Ly6/uPAR (LU) domain. Although the Ly6/uPAR family proteins share a common structure, their expression patterns and functions vary. To date, 35 human and 61 mouse Ly6/uPAR family members have been identified. Based on their subcellular localization, these proteins are further classified as GPI-anchored on the cell membrane, or secreted. The genes encoding Ly6/uPAR family proteins are conserved across different species and are clustered in syntenic regions on human chromosomes 8, 19, 6 and 11, and mouse Chromosomes 15, 7, 17, and 9, respectively. Here, we review the human and mouse Ly6/uPAR family gene and protein structure and genomic organization, expression, functions, and evolution, and introduce new names for novel family members.

Standardized Welfare Terms for the Zebrafish Community

Managing the welfare of laboratory animals is critical to animal health, vital in the understanding of phenotypes created by treatment or genetic alteration and ensures compliance of regulations. Part of an animal welfare assessment is the requirement to record observations, ensuring all those responsible for the animals are aware of their health status and can act accordingly. Although the use of zebrafish in research continues to increase, guidelines for conducting welfare assessments and the reporting of observations are considered unclear compared to mammalian species. To support the movement of zebrafish between facilities, significant improvement would be achieved through the use of standardized terms to ensure clarity and consistency between facilities. Improving the clarity of terminology around welfare not only addresses our ethical obligation but also supports the research goals and provides a searchable description of the phenotypes. A Collaboration between the Wellcome Trust Sanger Institute and Cambridge University (Department of Medicine-Laboratory of Molecular Biology) has led to the creation of the zebrafish welfare terms from which standardization of terminology can be achieved.

Long non-coding RNA Databases in Cardiovascular Research

With the rising interest in the regulatory functions of long non-coding RNAs (lncRNAs) in complex human diseases such as cardiovascular diseases, there is an increasing need in public databases offering comprehensive and integrative data for all aspects of these versatile molecules. Recently, a variety of public data repositories that specialized in lncRNAs have been developed, which make use of huge high-throughput data particularly from next-generation sequencing (NGS) approaches. Here, we provide an overview of current lncRNA databases covering basic and functional annotation, lncRNA expression and regulation, interactions with other biomolecules, and genomic variants influencing the structure and function of lncRNAs. The prominent lncRNA antisense noncoding RNA in the INK4 locus (ANRIL), which has been unequivocally associated with coronary artery disease through genome-wide association studies (GWAS), serves as an example to demonstrate the features of each individual database.

Vaxar: A Web-Based Database of Laboratory Animal Responses to Vaccinations and Its Application in the Meta-Analysis of Different Animal Responses to Tuberculosis Vaccinations

Animal models are indispensable for vaccine research and development. However, choosing which species to use and designing a vaccine study that is optimized for that species is often challenging. Vaxar (http://www.violinet.org/vaxar/) is a web-based database and analysis system that stores manually curated data regarding vaccine-induced responses in animals. To date, Vaxar encompasses models from 35 animal species including rodents, rabbits, ferrets, primates, and birds. These 35 species have been used to study more than 1300 experimentally tested vaccines for 164 pathogens and diseases significant to humans and domestic animals. The responses to vaccines by animals in more than 1500 experimental studies are recorded in Vaxar; these data can be used for systematic meta-analysis of various animal responses to a particular vaccine. For example, several variables, including animal strain, animal age, and the dose or route of either vaccination or challenge, might affect host response outcomes. Vaxar can also be used to identify variables that affect responses to different vaccines in a specific animal model. All data stored in Vaxar are publically available for web-based queries and analyses. Overall Vaxar provides a unique systematic approach for understanding vaccine-induced host immunity.

The Disease Portals, disease-gene annotation and the RGD disease ontology at the Rat Genome Database

The Rat Genome Database (RGD;http://rgd.mcw.edu/) provides critical datasets and software tools to a diverse community of rat and non-rat researchers worldwide. To meet the needs of the many users whose research is disease oriented, RGD has created a series of Disease Portals and has prioritized its curation efforts on the datasets important to understanding the mechanisms of various diseases. Gene-disease relationships for three species, rat, human and mouse, are annotated to capture biomarkers, genetic associations, molecular mechanisms and therapeutic targets. To generate gene-disease annotations more effectively and in greater detail, RGD initially adopted the MEDIC disease vocabulary from the Comparative Toxicogenomics Database and adapted it for use by expanding this framework with the addition of over 1000 terms to create the RGD Disease Ontology (RDO). The RDO provides the foundation for, at present, 10 comprehensive disease area-related dataset and analysis platforms at RGD, the Disease Portals. Two major disease areas are the focus of data acquisition and curation efforts each year, leading to the release of the related Disease Portals. Collaborative efforts to realize a more robust disease ontology are underway. Database URL:http://rgd.mcw.edu.

Wikidata as a semantic framework for the Gene Wiki initiative

Open biological data are distributed over many resources making them challenging to integrate, to update and to disseminate quickly. Wikidata is a growing, open community database which can serve this purpose and also provides tight integration with Wikipedia. In order to improve the state of biological data, facilitate data management and dissemination, we imported all human and mouse genes, and all human and mouse proteins into Wikidata. In total, 59,721 human genes and 73,355 mouse genes have been imported from NCBI and 27,306 human proteins and 16,728 mouse proteins have been imported from the Swissprot subset of UniProt. As Wikidata is open and can be edited by anybody, our corpus of imported data serves as the starting point for integration of further data by scientists, the Wikidata community and citizen scientists alike. The first use case for these data is to populate Wikipedia Gene Wiki infoboxes directly from Wikidata with the data integrated above. This enables immediate updates of the Gene Wiki infoboxes as soon as the data in Wikidata are modified. Although Gene Wiki pages are currently only on the English language version of Wikipedia, the multilingual nature of Wikidata allows for usage of the data we imported in all 280 different language Wikipedias. Apart from the Gene Wiki infobox use case, a SPARQL endpoint and exporting functionality to several standard formats (e.g. JSON, XML) enable use of the data by scientists. In summary, we created a fully open and extensible data resource for human and mouse molecular biology and biochemistry data. This resource enriches all the Wikipedias with structured information and serves as a new linking hub for the biological semantic web. Database URL: https://www.wikidata.org/.

Selection on Coding and Regulatory Variation Maintains Individuality in Major Urinary Protein Scent Marks in Wild Mice

Recognition of individuals by scent is widespread across animal taxa. Though animals can often discriminate chemical blends based on many compounds, recent work shows that specific protein pheromones are necessary and sufficient for individual recognition via scent marks in mice. The genetic nature of individuality in scent marks (e.g. coding versus regulatory variation) and the evolutionary processes that maintain diversity are poorly understood. The individual signatures in scent marks of house mice are the protein products of a group of highly similar paralogs in the major urinary protein (Mup) gene family. Using the offspring of wild-caught mice, we examine individuality in the major urinary protein (MUP) scent marks at the DNA, RNA and protein levels. We show that individuality arises through a combination of variation at amino acid coding sites and differential transcription of central Mup genes across individuals, and we identify eSNPs in promoters. There is no evidence of post-transcriptional processes influencing phenotypic diversity as transcripts accurately predict the relative abundance of proteins in urine samples. The match between transcripts and urine samples taken six months earlier also emphasizes that the proportional relationships across central MUP isoforms in urine is stable. Balancing selection maintains coding variants at moderate frequencies, though pheromone diversity appears limited by interactions with vomeronasal receptors. We find that differential transcription of the central Mup paralogs within and between individuals significantly increases the individuality of pheromone blends. Balancing selection on gene regulation allows for increased individuality via combinatorial diversity in a limited number of pheromones.

Individual recognition via scent is critical for many aspects of behavior including parental care, competition, cooperation and mate choice. While animal scents can differ in a huge number of dimensions, recent work has shown that only some specialized semiochemicals in scent marks are behaviorally relevant for individual recognition. How is individuality in specialized semiochemical blends produced and maintained in populations? At the extremes, individuality may depend on either a plethora of semiochemical isoforms or on combinatorial variation in a small number of shared isoforms across individuals. Analyzing the major urinary protein (MUP) pheromone blends of a wild population of house mice, we find evidence in favor of a combinatorial diversity model for the production and maintenance of individuality. Balancing selection maintains MUP proteins at moderate frequencies in the population, though interactions with the pheromone receptors appear to limit the extent of pheromone diversity in the system. By contrast, differential transcription of proteins greatly increases individuality in pheromone blends with balancing selection maintaining diversity in promoter regions associated with gene expression patterns. Selection maintaining combinatorial diversity in a limited set of behaviorally important semiochemicals may be a widespread mechanism generating and maintaining individuality in scent across taxa.

Dynamic software design for clinical exome and genome analyses: insights from bioinformaticians, clinical geneticists, and genetic counselors

BACKGROUND

The transition of whole-exome and whole-genome sequencing (WES/WGS) from the research setting to routine clinical practice remains challenging.

OBJECTIVES

With almost no previous research specifically assessing interface designs and functionalities of WES and WGS software tools, the authors set out to ascertain perspectives from healthcare professionals in distinct domains on optimal clinical genomics user interfaces.

METHODS

A series of semi-scripted focus groups, structured around professional challenges encountered in clinical WES and WGS, were conducted with bioinformaticians (n = 8), clinical geneticists (n = 9), genetic counselors (n = 5), and general physicians (n = 4).

RESULTS

Contrary to popular existing system designs, bioinformaticians preferred command line over graphical user interfaces for better software compatibility and customization flexibility. Clinical geneticists and genetic counselors desired an overarching interactive graphical layout to prioritize candidate variants--a "tiered" system where only functionalities relevant to the user domain are made accessible. They favored a system capable of retrieving consistent representations of external genetic information from third-party sources. To streamline collaboration and patient exchanges, the authors identified user requirements toward an automated reporting system capable of summarizing key evidence-based clinical findings among the vast array of technical details.

CONCLUSIONS

Successful adoption of a clinical WES/WGS system is heavily dependent on its ability to address the diverse necessities and predilections among specialists in distinct healthcare domains. Tailored software interfaces suitable for each group is likely more appropriate than the current popular "one size fits all" generic framework. This study provides interfaces for future intervention studies and software engineering opportunities.

Testing the role of predicted gene knockouts in human anthropometric trait variation

Although the role of complete gene inactivation by two loss-of-function mutations inherited in trans is well-established in recessive Mendelian diseases, we have not yet explored how such gene knockouts (KOs) could influence complex human phenotypes. Here, we developed a statistical framework to test the association between gene KOs and quantitative human traits. Our method is flexible, publicly available, and compatible with common genotype format files (e.g. PLINK and vcf). We characterized gene KOs in 4498 participants from the NHLBI Exome Sequence Project (ESP) sequenced at high coverage (>100×), 1976 French Canadians from the Montreal Heart Institute Biobank sequenced at low coverage (5.7×), and >100 000 participants from the Genetic Investigation of ANthropometric Traits (GIANT) Consortium genotyped on an exome array. We tested associations between gene KOs and three anthropometric traits: body mass index (BMI), height and BMI-adjusted waist-to-hip ratio (WHR). Despite our large sample size and multiple datasets available, we could not detect robust associations between specific gene KOs and quantitative anthropometric traits. Our results highlight several limitations and challenges for future gene KO studies in humans, in particular when there is no prior knowledge on the phenotypes that might be affected by the tested gene KOs. They also suggest that gene KOs identified with current DNA sequencing methodologies probably do not strongly influence normal variation in BMI, height, and WHR in the general human population.

Copy number variations in 119 Chinese children with idiopathic short stature identified by the custom genome-wide microarray

Background

Idiopathic short stature (ISS) refers to short stature with no evident etiologies. The custom genome-wide microarray specifically designed to cover height-related genes may be helpful to detect copy number variations (CNVs) in ISS patients, which may be missed by the general microarray. The aim of the study was to validate the applicability of the custom microarray and to analyze CNVs in Chinese ISS children.

Results

Sixty non-polymorphic CNVs were identified in 119 ISS patients. There were 13 small CNVs with a size below 50 kb, accounting for 21.7 % of all the CNVs (13/60). Five pathogenic or possibly pathogenic CNVs were detected in five patients, including deletions at 22q11.21, duplications at 4q11-q13.1, 4q12 and Yp11.32-p11.2. Taking only the pathogenic variants into account, the diagnostic yield was 2.5 % (3/119). The TMEM165, POLR2B and PDGFRA genes were analyzed as candidate genes. A 15 kb deletion in the RASA2 gene was of interest for further investigation.

Conclusions

This study showed that the custom microarray is applicable to detect CNVs in patients with short stature. Candidate genes and CNVs detected in ISS patients may be helpful for CNV analysis of short stature, especially in East Asian population.

Electronic supplementary material

The online version of this article (doi:10.1186/s13039-016-0225-0) contains supplementary material, which is available to authorized users.

A Splice Variant of Bardet-Biedl Syndrome 5 (BBS5) Protein that Is Selectively Expressed in Retina

PURPOSE

Bardet-Biedl syndrome is a complex ciliopathy that usually manifests with some form of retinal degeneration, amongst other ciliary-related deficiencies. One of the genetic causes of this syndrome results from a defect in Bardet-Biedl Syndrome 5 (BBS5) protein. BBS5 is one component of the BBSome, a complex of proteins that regulates the protein composition in cilia. In this study, we identify a smaller molecular mass form of BBS5 as a variant formed by alternative splicing and show that expression of this splice variant is restricted to the retina.

METHODS

Reverse transcription PCR from RNA was used to isolate and identify potential alternative transcripts of Bbs5. A peptide unique to the C-terminus of the BBS5 splice variant was synthesized and used to prepare antibodies that selectively recognized the BBS5 splice variant. These antibodies were used on immunoblots of tissue extracts to determine the extent of expression of the alternative transcript and on tissue slices to determine the localization of expressed protein. Pull-down of fluorescently labeled arrestin1 by immunoprecipitation of the BBS5 splice variant was performed to assess functional interaction between the two proteins.

RESULTS

PCR from mouse retinal cDNA using Bbs5-specific primers amplified a unique cDNA that was shown to be a splice variant of BBS5 resulting from the use of cryptic splicing sites in Intron 7. The resulting transcript codes for a truncated form of the BBS5 protein with a unique 24 amino acid C-terminus, and predicted 26.5 kD molecular mass. PCR screening of RNA isolated from various ciliated tissues and immunoblots of protein extracts from these same tissues showed that this splice variant was expressed in retina, but not brain, heart, kidney, or testes. Quantitative PCR showed that the splice variant transcript is 8.9-fold (+/- 1.1-fold) less abundant than the full-length transcript. In the retina, the splice variant of BBS5 appears to be most abundant in the connecting cilium of photoreceptors, where BBS5 is also localized. Like BBS5, the binding of BBS5L to arrestin1 can be modulated by phosphorylation through protein kinase C.

CONCLUSIONS

In this study we have identified a novel splice variant of BBS5 that appears to be expressed only in the retina. The BBS5 splice variant is expressed at approximately 10% of full-length BBS5 level. No unique functional or localization properties could be identified for the splice variant compared to BBS5.

A targeted next-generation sequencing assay for the molecular diagnosis of genetic disorders with orodental involvement

BACKGROUND

Orodental diseases include several clinically and genetically heterogeneous disorders that can present in isolation or as part of a genetic syndrome. Due to the vast number of genes implicated in these disorders, establishing a molecular diagnosis can be challenging. We aimed to develop a targeted next-generation sequencing (NGS) assay to diagnose mutations and potentially identify novel genes mutated in this group of disorders.

METHODS

We designed an NGS gene panel that targets 585 known and candidate genes in orodental disease. We screened a cohort of 101 unrelated patients without a molecular diagnosis referred to the Reference Centre for Oro-Dental Manifestations of Rare Diseases, Strasbourg, France, for a variety of orodental disorders including isolated and syndromic amelogenesis imperfecta (AI), isolated and syndromic selective tooth agenesis (STHAG), isolated and syndromic dentinogenesis imperfecta, isolated dentin dysplasia, otodental dysplasia and primary failure of tooth eruption.

RESULTS

We discovered 21 novel pathogenic variants and identified the causative mutation in 39 unrelated patients in known genes (overall diagnostic rate: 39%). Among the largest subcohorts of patients with isolated AI (50 unrelated patients) and isolated STHAG (21 unrelated patients), we had a definitive diagnosis in 14 (27%) and 15 cases (71%), respectively. Surprisingly, COL17A1 mutations accounted for the majority of autosomal-dominant AI cases.

CONCLUSIONS

We have developed a novel targeted NGS assay for the efficient molecular diagnosis of a wide variety of orodental diseases. Furthermore, our panel will contribute to better understanding the contribution of these genes to orodental disease.

TRIAL REGISTRATION NUMBERS

NCT01746121 and NCT02397824.

Gene regulation and speciation in house mice

One approach to understanding the process of speciation is to characterize the genetic architecture of post-zygotic isolation. As gene regulation requires interactions between loci, negative epistatic interactions between divergent regulatory elements might underlie hybrid incompatibilities and contribute to reproductive isolation. Here, we take advantage of a cross between house mouse subspecies, where hybrid dysfunction is largely unidirectional, to test several key predictions about regulatory divergence and reproductive isolation. Regulatory divergence between Mus musculus musculus and M. m. domesticus was characterized by studying allele-specific expression in fertile hybrid males using mRNA-sequencing of whole testes. We found extensive regulatory divergence between M. m. musculus and M. m. domesticus, largely attributable to cis-regulatory changes. When both cis and trans changes occurred, they were observed in opposition much more often than expected under a neutral model, providing strong evidence of widespread compensatory evolution. We also found evidence for lineage-specific positive selection on a subset of genes related to transcriptional regulation. Comparisons of fertile and sterile hybrid males identified a set of genes that were uniquely misexpressed in sterile individuals. Lastly, we discovered a nonrandom association between these genes and genes showing evidence of compensatory evolution, consistent with the idea that regulatory interactions might contribute to Dobzhansky-Muller incompatibilities and be important in speciation.

The old and new face of craniofacial research: How animal models inform human craniofacial genetic and clinical data

The craniofacial skeletal structures that comprise the human head develop from multiple tissues that converge to form the bones and cartilage of the face. Because of their complex development and morphogenesis, many human birth defects arise due to disruptions in these cellular populations. Thus, determining how these structures normally develop is vital if we are to gain a deeper understanding of craniofacial birth defects and devise treatment and prevention options. In this review, we will focus on how animal model systems have been used historically and in an ongoing context to enhance our understanding of human craniofacial development. We do this by first highlighting "animal to man" approaches; that is, how animal models are being utilized to understand fundamental mechanisms of craniofacial development. We discuss emerging technologies, including high throughput sequencing and genome editing, and new animal repository resources, and how their application can revolutionize the future of animal models in craniofacial research. Secondly, we highlight "man to animal" approaches, including the current use of animal models to test the function of candidate human disease variants. Specifically, we outline a common workflow deployed after discovery of a potentially disease causing variant based on a select set of recent examples in which human mutations are investigated in vivo using animal models. Collectively, these topics will provide a pipeline for the use of animal models in understanding human craniofacial development and disease for clinical geneticist and basic researchers alike.

Non-coding RNA profiling of the developing murine lens

Non-coding RNAs (ncRNAs) are emerging as an important player in the regulation of genome integrity and gene expression, and they have been implicated in the pathogenesis of many diseases. The aim of the present study is to identify the repertoire of ncRNAs expressed in the developing mouse lens. We previously reported the mouse lens transcriptome, including mRNA and microRNA (miRNA) profiling at two embryonic (E15 and E18) and four postnatal (P0, P3, P6, and P9) time points. We analyzed the data from small RNA-Seq and mRNA-Seq libraries to investigate the ncRNA profile. Our analysis revealed expression of 12 different classes of ncRNA in the murine lens at six developmental time points. Annotation of small RNA data showed expression of 1,756 antisense ncRNA (asncRNA) in the mouse lens transcriptome. Likewise, we identified 82 P-element-induced wimpy testis (PIWI)-interacting RNA (piRNA), 345 transfer RNA (tRNA), 12 small nuclear RNA (snRNA), 167 small nucleolar RNA (snoRNA), 19 small Cajal body-specific RNA (scaRNA), six ribosomal RNA (rRNA), 18 tRNA-like structures, one MALAT1-associated small cytoplasmic RNA (mascRNA), one Vault RNA (vtRNA), and one Y RNA expressed in the developing mouse lens. In parallel, bioinformatic investigation of mRNA-Seq data identified expression of 1,952 long intergenic ncRNA (lincRNA) in the developing mouse lens. In conclusion, we report a comprehensive ncRNA profile in the murine lens at six developmental time points. To the best of our knowledge, this is first report investigating different classes of ncRNAs in the developing mouse lens and will be monumental in elucidating processes essential for the development of the ocular lens and the maintenance of its transparency.

Integration of genome-wide association and extant brain expression QTL identifies candidate genes influencing prepulse inhibition in inbred F1 mice

Genetic association mapping in structured populations of model organisms can offer a fruitful complement to human genetic studies by generating new biological hypotheses about complex traits. Here we investigated prepulse inhibition (PPI), a measure of sensorimotor gating that is disrupted in a number of psychiatric disorders. To identify genes that influence PPI, we constructed a panel of half-sibs by crossing 30 females from common inbred mouse strains with inbred C57BL/6J males to create male and female F1 offspring. We used publicly available single nucleotide polymorphism (SNP) genotype data from these inbred strains to perform a genome-wide association scan using a dense panel of over 150,000 SNPs in a combined sample of 604 mice representing 30 distinct F1 genotypes. We identified two independent PPI-associated loci on Chromosomes 2 and 7, each of which explained 12-14% of the variance in PPI. Searches of available databases did not identify any plausible causative coding polymorphisms within these loci. However, previously collected expression quantitative trait locus (eQTL) data from hippocampus and striatum indicated that the SNPs on Chromosomes 2 and 7 that showed the strongest association with PPI were also strongly associated with expression of several transcripts, some of which have been implicated in human psychiatric disorders. This integrative approach successfully identified a focused set of genes which can be prioritized for follow-up studies. More broadly, our results show that F1 crosses among common inbred strains can be used in combination with other informatics and expression datasets to identify candidate genes for complex behavioral traits.

Exome arrays capture polygenic rare variant contributions to schizophrenia

Schizophrenia is a highly heritable disorder. Genome-wide association studies based largely on common alleles have identified over 100 schizophrenia risk loci, but it is also evident from studies of copy number variants (CNVs) and from exome-sequencing studies that rare alleles are also involved. Full characterization of the contribution of rare alleles to the disorder awaits the deployment of sequencing technology in very large sample sizes, meanwhile, as an interim measure, exome arrays allow rare non-synonymous variants to be sampled at a fraction of the cost. In an analysis of exome array data from 13 688 individuals (5585 cases and 8103 controls) from the UK, we found that rare (minor allele frequency < 0.1%) variant association signal was enriched among genes that map to autosomal loci that are genome-wide significant (GWS) in common variant studies of schizophrenia genome-wide association study (P_GWAS = 0.01) as well as gene sets known to be enriched for rare variants in sequencing studies (P_RARE = 0.026). We also identified the gene-wise equivalent of GWS support for WDR88 (WD repeat-containing protein 88), a gene of unknown function (P = 6.5 × 10⁻⁷). Rare alleles represented on exome chip arrays contribute to the genetic architecture of schizophrenia, but as is the case for GWAS, very large studies are required to reveal additional susceptibility alleles for the disorder.

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.

The zebrafish pinball wizard gene encodes WRB, a tail-anchored-protein receptor essential for inner-ear hair cells and retinal photoreceptors

KEY POINTS

The zebrafish pinball wizard (pwi) mutant is deaf and blind. The pwi phenotype includes a reduced auditory startle response and reduced visual evoked potentials, suggesting fatigue of synaptic release at ribbon synapses in hair cells and photoreceptors. The gene defective in the pwi mutant is WRB, a protein homologous to the yeast protein Get1, which is involved in the insertion of 'tail-anchored' membrane proteins. Many tail-anchored proteins are associated with synaptic vesicles, and both vesicles and synaptic ribbons are reduced in synaptic regions of hair cells in pwi. Abnormal processing of synaptic vesicle proteins important for ribbon synapses can explain the pwi phenotype.

ABSTRACT

In a large-scale zebrafish insertional mutagenesis screen, we identified the pinball wizard (pwi) line, which displays a deafness and blindness phenotype. Although the gross morphology and structure of the pwi larval inner ear was near normal, acoustic startle stimuli evoked smaller postsynaptic responses in afferent neurons, which rapidly fatigued. In the retina, similarly, an abnormal electroretinogram suggested reduced transmission at the photoreceptor ribbon synapse. A functional deficit in these specialized synapses was further supported by a reduction of synaptic marker proteins Rab3 and cysteine-string protein (CSP/Dnajc5) in hair cells and photoreceptors, as well as by a reduction of the number of both ribbons and vesicles surrounding the ribbons in hair cells. The pwi gene encodes a homologue of the yeast Get1 and human tryptophan-rich basic (WRB) proteins, which are receptors for membrane insertion of tail-anchored (TA) proteins. We identified more than 100 TA proteins expressed in hair cells, including many synaptic proteins. The expression of synaptobrevin and syntaxin 3, TA proteins essential for vesicle fusion, was reduced in the synaptic layers of mutant retina, consistent with a role for the pwi/WRB protein in TA-protein processing. The WRB protein was located near the apical domain and the ribbons in hair cells, and in the inner segment and the axon of the photoreceptor, consistent with a role in vesicle biogenesis or trafficking. Taken together, our results suggest that WRB plays a critical role in synaptic functions in these two sensory cells, and that disrupted processing of synaptic vesicle TA proteins explains much of the mutant phenotype.

Genetic variation in offspring indirectly influences the quality of maternal behaviour in mice

Conflict over parental investment between parent and offspring is predicted to lead to selection on genes expressed in offspring for traits influencing maternal investment, and on parentally expressed genes affecting offspring behaviour. However, the specific genetic variants that indirectly modify maternal or offspring behaviour remain largely unknown. Using a cross-fostered population of mice, we map maternal behaviour in genetically uniform mothers as a function of genetic variation in offspring and identify loci on offspring chromosomes 5 and 7 that modify maternal behaviour. Conversely, we found that genetic variation among mothers influences offspring development, independent of offspring genotype. Offspring solicitation and maternal behaviour show signs of coadaptation as they are negatively correlated between mothers and their biological offspring, which may be linked to costs of increased solicitation on growth found in our study. Overall, our results show levels of parental provisioning and offspring solicitation are unique to specific genotypes.

Mapping Sub-Second Structure in Mouse Behavior

Complex animal behaviors are likely built from simpler modules, but their systematic identification in mammals remains a significant challenge. Here we use depth imaging to show that 3D mouse pose dynamics are structured at the sub-second timescale. Computational modeling of these fast dynamics effectively describes mouse behavior as a series of reused and stereotyped modules with defined transition probabilities. We demonstrate this combined 3D imaging and machine learning method can be used to unmask potential strategies employed by the brain to adapt to the environment, to capture both predicted and previously hidden phenotypes caused by genetic or neural manipulations, and to systematically expose the global structure of behavior within an experiment. This work reveals that mouse body language is built from identifiable components and is organized in a predictable fashion; deciphering this language establishes an objective framework for characterizing the influence of environmental cues, genes and neural activity on behavior.

HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease

More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms.

Investigation of microRNAs in mouse macrophage responses to lipopolysaccharide-stimulation by combining gene expression with microRNA-target information

Background

Toll-like receptors, which stimulated by pathogen-associated molecular patterns such as lipopolysaccharides (LPS), induces the releasing of many kinds of proinflammatory cytokines to activate subsequent immune responses. Plenty of studies have also indicated the importance of TLR-signalling on the avoidance of excessive inflammation, tissue repairing and the return to homeostasis after infection and tissue injury. The significance of TLR-signalling attracts many attentions on the regulatory mechanisms since several years ago. However, as newly discovered regulators, how and how many different microRNAs (miRNAs) regulate TLR-signalling pathway are still unclear.

Results

By integrating several microarray datasets and miRNA-target information datasets, we identified 431 miRNAs and 498 differentially expressed target genes in bone marrow-derived macrophages (BMDMs) with LPS-stimulation. Cooperative miRNA network were constructed by calculating targets overlap scores, and a sub-network finding algorithm was used to identify cooperative miRNA modules. Finally, 17 and 8 modules are identified in the cooperative miRNA networks composed of miRNAs up-regulate and down-regulate genes, respectively.

Conclusions

We used gene expression data of mouse macrophage stimulated by LPS and miRNA-target information to infer the regulatory mechanism of miRNAs on LPS-induced signalling pathway. Also, our results suggest that miRNAs can be important regulators of LPS-induced innate immune response in BMDMs.

The Characteristics of Heterozygous Protein Truncating Variants in the Human Genome

Sequencing projects have identified large numbers of rare stop-gain and frameshift variants in the human genome. As most of these are observed in the heterozygous state, they test a gene’s tolerance to haploinsufficiency and dominant loss of function. We analyzed the distribution of truncating variants across 16,260 autosomal protein coding genes in 11,546 individuals. We observed 39,893 truncating variants affecting 12,062 genes, which significantly differed from an expectation of 12,916 genes under a model of neutral de novo mutation (p<10⁻⁴). Extrapolating this to increasing numbers of sequenced individuals, we estimate that 10.8% of human genes do not tolerate heterozygous truncating variants. An additional 10 to 15% of truncated genes may be rescued by incomplete penetrance or compensatory mutations, or because the truncating variants are of limited functional impact. The study of protein truncating variants delineates the essential genome and, more generally, identifies rare heterozygous variants as an unexplored source of diversity of phenotypic traits and diseases.

Genome sequencing provides evidence for large numbers of putative protein truncating variants in humans. Most truncating variants are only observed in few individuals but are collectively prevalent and widely distributed across the coding genome. Most of the truncating variants are so rare that they are only observed in heterozygosis. The current study identifies 10% of genes where heterozygous truncations are not observed and describes their biological characteristics. In addition, for genes where rare truncations are observed, we argue that these are an unexplored source of diversity of phenotypic traits and diseases.

Defining the Schistosoma haematobium kinome enables the prediction of essential kinases as anti-schistosome drug targets

The blood fluke Schistosoma haematobium causes urogenital schistosomiasis, a neglected tropical disease (NTD) that affects more than 110 million people. Treating this disease by targeted or mass administration with a single chemical, praziquantel, carries the risk that drug resistance will develop in this pathogen. Therefore, there is an imperative to search for new drug targets in S. haematobium and other schistosomes. In this regard, protein kinases have potential, given their essential roles in biological processes and as targets for drugs already approved by the US Food and Drug Administration (FDA) for use in humans. In this context, we defined here the kinome of S. haematobium using a refined bioinformatic pipeline. We classified, curated and annotated predicted kinases, and assessed the developmental transcription profiles of kinase genes. Then, we prioritised a panel of kinases as potential drug targets and inferred chemicals that bind to them using an integrated bioinformatic pipeline. Most kinases of S. haematobium are very similar to those of its congener, S. mansoni, offering the prospect of designing chemicals that kill both species. Overall, this study provides a global insight into the kinome of S. haematobium and should assist the repurposing or discovery of drugs against schistosomiasis.

SurvCurv database and online survival analysis platform update

Understanding the biology of ageing is an important and complex challenge. Survival experiments are one of the primary approaches for measuring changes in ageing. Here, we present a major update to SurvCurv, a database and online resource for survival data in animals. As well as a substantial increase in data and additions to existing graphical and statistical survival analysis features, SurvCurv now includes extended mathematical mortality modelling functions and survival density plots for more advanced representation of groups of survival cohorts.

AVAILABILITY AND IMPLEMENTATION

The database is freely available at https://www.ebi.ac.uk/thornton-srv/databases/SurvCurv/. All data are published under the Creative Commons Attribution License.

CONTACT

matthias.ziehm@ebi.ac.uk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database

MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.