Robust and sensitive analysis of mouse knockout phenotypes

High-throughput genotyping of high-homology mutant mouse strains by next-generation sequencing

Genotyping of knockout alleles in mice is commonly performed by end-point PCR or gene-specific/universal cassette qPCR. Both have advantages and limitations in terms of assay design and interpretation of results. As an alternative method for high-throughput genotyping, we investigated next generation sequencing (NGS) of PCR amplicons, with a focus on CRISPR-mediated exon deletions where antibiotic selection markers are not present. By multiplexing the wild type and mutant-specific PCR reactions, the genotype can be called by the relative sequence counts of each product. The system is highly scalable and can be applied to a variety of different allele types, including those produced by the International Mouse Phenotyping Consortium and associated projects. One potential challenge with any assay design is locating unique areas of the genome, especially when working with gene families or regions of high homology. These can result in misleading or ambiguous genotypes for either qPCR or end-point assays. Here, we show that genotyping by NGS can negate these issues by simple, automated filtering of undesired sequences. Analysis and genotype calls can also be fully automated, using FASTQ or FASTA input files and an in-house Perl script and SQL database.

OpenStats: A robust and scalable software package for reproducible analysis of high-throughput phenotypic data

Reproducibility in the statistical analyses of data from high-throughput phenotyping screens requires a robust and reliable analysis foundation that allows modelling of different possible statistical scenarios. Regular challenges are scalability and extensibility of the analysis software. In this manuscript, we describe OpenStats, a freely available software package that addresses these challenges. We show the performance of the software in a high-throughput phenomic pipeline in the International Mouse Phenotyping Consortium (IMPC) and compare the agreement of the results with the most similar implementation in the literature. OpenStats has significant improvements in speed and scalability compared to existing software packages including a 13-fold improvement in computational time to the current production analysis pipeline in the IMPC. Reduced complexity also promotes FAIR data analysis by providing transparency and benefiting other groups in reproducing and re-usability of the statistical methods and results. OpenStats is freely available under a Creative Commons license at www.bioconductor.org/packages/OpenStats.

Improving reproducibility in animal research by splitting the study population into several 'mini-experiments'

In light of the hotly discussed 'reproducibility crisis', a rethinking of current methodologies appears essential. Implementing multi-laboratory designs has been shown to enhance the external validity and hence the reproducibility of findings from animal research. We here aimed at proposing a new experimental strategy that transfers this logic into a single-laboratory setting. We systematically introduced heterogeneity into our study population by splitting an experiment into several 'mini-experiments' spread over different time points a few weeks apart. We hypothesised to observe improved reproducibility in such a 'mini-experiment' design in comparison to a conventionally standardised design, according to which all animals are tested at one specific point in time. By comparing both designs across independent replicates, we could indeed show that the use of such a 'mini-experiment' design improved the reproducibility and accurate detection of exemplary treatment effects (behavioural and physiological differences between four mouse strains) in about half of all investigated strain comparisons. Thus, we successfully implemented and empirically validated an easy-to-handle strategy to tackle poor reproducibility in single-laboratory studies. Since other experiments within different life science disciplines share the main characteristics with the investigation reported here, these studies are likely to also benefit from this approach.

Phenotyping in Mice Using Continuous Home Cage Monitoring and Ultrasonic Vocalization Recordings

Over the last century, the study of mouse behavior has uncovered insights into brain molecular mechanisms while revealing potential causes of many neurological disorders. To this end, researchers have widely exploited the use of mutant strains, including those generated in mutagenesis screens and those produced using increasingly sophisticated genome engineering technologies. It is now relatively easy to access mouse models carrying alleles that faithfully recapitulate changes found in human patients or bearing variants of genes that provide data on those genes' functions. Concurrent with these developments has been an appreciation of the limitations of some current testing platforms, especially those monitoring complex behaviors. Out-of-cage observational testing is useful in describing overt persistent phenotypes but risks missing sporadic or intermittent events. Furthermore, measuring the progression of a phenotype, potentially over many months, can be difficult while relying on assays that may be susceptible to changes in the testing environment. In recent years, there has also been increasing awareness that measurement of behaviors in isolation can be limiting, given that mice attempt to hide behavioral cues of vulnerability. To overcome these limitations, laboratory animal science is capitalizing on progress in data capture and processing expertise. Moreover, as additional recording modes become commonplace, ultrasonic vocalization recording is an appealing focus, as mice use vocalizations in various social contexts. Using video and audio technologies, we record the voluntary, unprovoked behaviors and vocalizations of mice in social groups. Adoption of these approaches is undoubtedly set to increase, as they capture the round-the-clock behavior of mouse strains. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Continuous recording of home cage activity using the Home Cage Analyzer (HCA) system Support Protocol: Subcutaneous insertion of a radio frequency identification microchip in the inguinal area Basic Protocol 2: Continuous recording of mouse ultrasonic vocalizations in the home cage.

Exome Sequencing Identifies Genes and Gene Sets Contributing to Severe Childhood Obesity, Linking PHIP Variants to Repressed POMC Transcription

Obesity is genetically heterogeneous with monogenic and complex polygenic forms. Using exome and targeted sequencing in 2,737 severely obese cases and 6,704 controls, we identified three genes (PHIP, DGKI, and ZMYM4) with an excess burden of very rare predicted deleterious variants in cases. In cells, we found that nuclear PHIP (pleckstrin homology domain interacting protein) directly enhances transcription of pro-opiomelanocortin (POMC), a neuropeptide that suppresses appetite. Obesity-associated PHIP variants repressed POMC transcription. Our demonstration that PHIP is involved in human energy homeostasis through transcriptional regulation of central melanocortin signaling has potential diagnostic and therapeutic implications for patients with obesity and developmental delay. Additionally, we found an excess burden of predicted deleterious variants involving genes nearest to loci from obesity genome-wide association studies. Genes and gene sets influencing obesity with variable penetrance provide compelling evidence for a continuum of causality in the genetic architecture of obesity, and explain some of its missing heritability.

A comprehensive and comparative phenotypic analysis of the collaborative founder strains identifies new and known phenotypes

The collaborative cross (CC) is a large panel of mouse-inbred lines derived from eight founder strains (NOD/ShiLtJ, NZO/HILtJ, A/J, C57BL/6J, 129S1/SvImJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Here, we performed a comprehensive and comparative phenotyping screening to identify phenotypic differences and similarities between the eight founder strains. In total, more than 300 parameters including allergy, behavior, cardiovascular, clinical blood chemistry, dysmorphology, bone and cartilage, energy metabolism, eye and vision, immunology, lung function, neurology, nociception, and pathology were analyzed; in most traits from sixteen females and sixteen males. We identified over 270 parameters that were significantly different between strains. This study highlights the value of the founder and CC strains for phenotype-genotype associations of many genetic traits that are highly relevant to human diseases. All data described here are publicly available from the mouse phenome database for analyses and downloads.

High-throughput phenotyping reveals expansive genetic and structural underpinnings of immune variation

By developing a high-density murine immunophenotyping platform compatible with high-throughput genetic screening, we have established profound contributions of genetics and structure to immune variation (http://www.immunophenotype.org). Specifically, high-throughput phenotyping of 530 unique mouse gene knockouts identified 140 monogenic 'hits', of which most had no previous immunologic association. Furthermore, hits were collectively enriched in genes for which humans show poor tolerance to loss of function. The immunophenotyping platform also exposed dense correlation networks linking immune parameters with each other and with specific physiologic traits. Such linkages limit freedom of movement for individual immune parameters, thereby imposing genetically regulated 'immunologic structures', the integrity of which was associated with immunocompetence. Hence, we provide an expanded genetic resource and structural perspective for understanding and monitoring immune variation in health and disease.

Knockout and Knock-in Mouse Models to Study Purinergic Signaling

Purinergic signaling involves extracellular purines and pyrimidines acting upon specific cell surface purinoceptors classified into the P1, P2X, and P2Y families for nucleosides and nucleotides. This widespread signaling mechanism is active in all major tissues and influences a range of functions in health and disease. Orthologs to all but one of the human purinoceptors have been found in mouse, making this laboratory animal a useful model to study their function. Indeed, analyses of purinoceptors via knock-in or knockout approaches to produce gain or loss of function phenotypes have revealed several important therapeutic targets. None of the homozygous purinoceptor knockouts proved to be developmentally lethal, which suggest that either these receptors are not involved in key developmental processes or that the large number of receptors in each family allowed for functional compensation. Different models for the same purinoceptor often show compatible phenotypes but there have been examples of significant discrepancies. These revealed unexpected differences in the structure of human and mouse genes and emphasized the importance of the genetic background of different mouse strains. In this chapter, we provide an overview of the current knowledge and new trends in the modifications of purinoceptor genes in vivo. We discuss the resulting phenotypes, their applications and relative merits and limitations of mouse models available to study purinoceptor subtypes.

Gene loci associated with insulin secretion in islets from non-diabetic mice

Genetic susceptibility to type 2 diabetes is primarily due to β-cell dysfunction. However, a genetic study to directly interrogate β-cell function ex vivo has never been previously performed. We isolated 233,447 islets from 483 Diversity Outbred (DO) mice maintained on a Western-style diet, and measured insulin secretion in response to a variety of secretagogues. Insulin secretion from DO islets ranged >1,000-fold even though none of the mice were diabetic. The insulin secretory response to each secretagogue had a unique genetic architecture; some of the loci were specific for one condition, whereas others overlapped. Human loci that are syntenic to many of the insulin secretion QTL from mouse are associated with diabetes-related SNPs in human genome-wide association studies. We report on three genes, Ptpn18, Hunk and Zfp148, where the phenotype predictions from the genetic screen were fulfilled in our studies of transgenic mouse models. These three genes encode a non-receptor type protein tyrosine phosphatase, a serine/threonine protein kinase, and a Krϋppel-type zinc-finger transcription factor, respectively. Our results demonstrate that genetic variation in insulin secretion that can lead to type 2 diabetes is discoverable in non-diabetic individuals.

Mouse screen reveals multiple new genes underlying mouse and human hearing loss

Adult-onset hearing loss is very common, but we know little about the underlying molecular pathogenesis impeding the development of therapies. We took a genetic approach to identify new molecules involved in hearing loss by screening a large cohort of newly generated mouse mutants using a sensitive electrophysiological test, the auditory brainstem response (ABR). We review here the findings from this screen. Thirty-eight unexpected genes associated with raised thresholds were detected from our unbiased sample of 1,211 genes tested, suggesting extreme genetic heterogeneity. A wide range of auditory pathophysiologies was found, and some mutant lines showed normal development followed by deterioration of responses, revealing new molecular pathways involved in progressive hearing loss. Several of the genes were associated with the range of hearing thresholds in the human population and one, SPNS2, was involved in childhood deafness. The new pathways required for maintenance of hearing discovered by this screen present new therapeutic opportunities.

This study uses an electrophysiological screen of over a thousand new mutant mouse lines to identify 38 new genes underlying deafness, some associated with human hearing function, revealing a wide range of molecular and pathological mechanisms.

Progressive hearing loss with age is extremely common in the population, leading to difficulties in understanding speech, increased social isolation, and associated depression. We know it has a significant heritability, but so far we know very little about the molecular pathways leading to hearing loss, hampering the development of treatments. Here, we describe a large-scale screen of 1,211 new targeted mouse mutant lines, resulting in the identification of 38 genes underlying hearing loss that were not previously suspected of involvement in hearing. Some of these genes reveal molecular pathways that may be useful targets for drug development. Our further analysis of the genes identified and the varied pathological mechanisms within the ear resulting from the mutations suggests that hearing loss is an extremely heterogeneous disorder and may have as many as 1,000 genes involved.

Targeting of NAT10 enhances healthspan in a mouse model of human accelerated aging syndrome

Hutchinson-Gilford Progeria Syndrome (HGPS) is a rare, but devastating genetic disease characterized by segmental premature aging, with cardiovascular disease being the main cause of death. Cells from HGPS patients accumulate progerin, a permanently farnesylated, toxic form of Lamin A, disrupting the nuclear shape and chromatin organization, leading to DNA-damage accumulation and senescence. Therapeutic approaches targeting farnesylation or aiming to reduce progerin levels have provided only partial health improvements. Recently, we identified Remodelin, a small-molecule agent that leads to amelioration of HGPS cellular defects through inhibition of the enzyme N-acetyltransferase 10 (NAT10). Here, we show the preclinical data demonstrating that targeting NAT10 in vivo, either via chemical inhibition or genetic depletion, significantly enhances the healthspan in a Lmna G609G HGPS mouse model. Collectively, the data provided here highlights NAT10 as a potential therapeutic target for HGPS.

Laboratory mouse housing conditions can be improved using common environmental enrichment without compromising data

Animal welfare requires the adequate housing of animals to ensure health and well-being. The application of environmental enrichment is a way to improve the well-being of laboratory animals. However, it is important to know whether these enrichment items can be incorporated in experimental mouse husbandry without creating a divide between past and future experimental results. Previous small-scale studies have been inconsistent throughout the literature, and it is not yet completely understood whether and how enrichment might endanger comparability of results of scientific experiments. Here, we measured the effect on means and variability of 164 physiological parameters in 3 conditions: with nesting material with or without a shelter, comparing these 2 conditions to a “barren” regime without any enrichments. We studied a total of 360 mice from each of 2 mouse strains (C57BL/6NTac and DBA/2NCrl) and both sexes for each of the 3 conditions. Our study indicates that enrichment affects the mean values of some of the 164 parameters with no consistent effects on variability. However, the influence of enrichment appears negligible compared to the effects of other influencing factors. Therefore, nesting material and shelters may be used to improve animal welfare without impairment of experimental outcome or loss of comparability to previous data collected under barren housing conditions.

Adequate housing of laboratory animals is essential to guarantee their well-being. From a scientific perspective, physically and mentally healthy animals also contribute to increased validity and reproducibility of experimental results. The choice of nesting material or shelter type, referred to as environmental enrichment, may influence how laboratory animals perform species-specific behaviors. Consequently, changes in these nesting and shelter materials could influence scientific results by, for example, increasing variability in measured characteristics. Whether studies using different environmental enrichment materials can be compared is currently questioned. Our study shows that simple, species-specific environmental enrichment in the form of nesting material alone or in combination with a shelter did not consistently increase variability of physiological parameters in mice. Differences in parameter average values appeared to be of minor biological relevance when compared to the effects of other environmental factors. These simple environmental enrichment devices may therefore be applied to improve the housing environment of laboratory mice without compromising data validity or comparability.

Lyplal1 is dispensable for normal fat deposition in mice

Genome-wide association studies (GWAS) have detected association between variants in or near the Lysophospholipase-like 1 (LYPLAL1) locus and metabolic traits, including central obesity, fatty liver and waist-to-hip ratio. LYPLAL1 is also known to be upregulated in the adipose tissue of obese patients. However, the physiological role of LYPLAL1 is not understood. To investigate the function of Lyplal1 in vivo we investigated the phenotype of the Lyplal1^{tm1a(KOMP)Wtsi} homozygous mouse. Body composition was unaltered in Lyplal1 knockout mice as assessed by dual-energy X-ray absorptiometry (DEXA) scanning, both on normal chow and on a high-fat diet. Adipose tissue distribution between visceral and subcutaneous fat depots was unaltered, with no change in adipocyte cell size. The response to both insulin and glucose dosing was normal in Lyplal1^{tm1a(KOMP)Wtsi} homozygous mice, with normal fasting blood glucose concentrations. RNAseq analysis of liver, muscle and adipose tissue confirmed that Lyplal1 expression was ablated with minimal additional changes in gene expression. These results suggest that Lyplal1 is dispensable for normal mouse metabolic physiology and that despite having been maintained through evolution Lyplal1 is not an essential gene, suggesting possible functional redundancy. Further studies will be required to clarify its physiological role.

A high-throughput in vivo screening method in the mouse for identifying regulators of metastatic colonization

We describe a sensitive, robust, high-throughput method for quantifying the ability of metastatic tumor cells to colonize a secondary organ. Metastasis is the leading cause of death in cancer patients, and successful colonization of the secondary organ is the rate-limiting step in the metastatic process; thus, experimental methods that can be used to interrogate the key factors required for this critical step are of great importance. The experimental metastasis assay we detail here includes tail-vein injection of cancer cells into the mouse and determination of the resulting secondary organ colonization, primarily in the lung, 10 d post dosing. This assay can be used to investigate factors that regulate metastatic colonization both at the tumor-cell-intrinsic level (via manipulation of the tumor cells before injection) and at the tumor-cell-extrinsic level (such as the tissue microenvironment, via the use of genetically modified (GM) mice or agents such as antibodies or drugs). Using this method, we have robustly screened more than 950 GM mouse lines to identify novel microenvironmental regulators of metastatic colonization. The experimental details discussed here include choosing of appropriate cell numbers, handling of the cells, selection of recipient animals and injection techniques. Furthermore, we discuss key experimental design considerations, including the choice of the method used to determine metastatic burden and statistical analysis of the results, as well as provide troubleshooting tips and identification of factors that contribute to experimental variability.

WD40-repeat 47, a microtubule-associated protein, is essential for brain development and autophagy

The family of WD40-repeat (WDR) proteins is one of the largest in eukaryotes, but little is known about their function in brain development. Among 26 WDR genes assessed, we found 7 displaying a major impact in neuronal morphology when inactivated in mice. Remarkably, all seven genes showed corpus callosum defects, including thicker (Atg16l1, Coro1c, Dmxl2, and Herc1), thinner (Kif21b and Wdr89), or absent corpus callosum (Wdr47), revealing a common role for WDR genes in brain connectivity. We focused on the poorly studied WDR47 protein sharing structural homology with LIS1, which causes lissencephaly. In a dosage-dependent manner, mice lacking Wdr47 showed lethality, extensive fiber defects, microcephaly, thinner cortices, and sensory motor gating abnormalities. We showed that WDR47 shares functional characteristics with LIS1 and participates in key microtubule-mediated processes, including neural stem cell proliferation, radial migration, and growth cone dynamics. In absence of WDR47, the exhaustion of late cortical progenitors and the consequent decrease of neurogenesis together with the impaired survival of late-born neurons are likely yielding to the worsening of the microcephaly phenotype postnatally. Interestingly, the WDR47-specific C-terminal to LisH (CTLH) domain was associated with functions in autophagy described in mammals. Silencing WDR47 in hypothalamic GT1-7 neuronal cells and yeast models independently recapitulated these findings, showing conserved mechanisms. Finally, our data identified superior cervical ganglion-10 (SCG10) as an interacting partner of WDR47. Taken together, these results provide a starting point for studying the implications of WDR proteins in neuronal regulation of microtubules and autophagy.

Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium

Although next-generation sequencing has revolutionized the ability to associate variants with human diseases, diagnostic rates and development of new therapies are still limited by a lack of knowledge of the functions and pathobiological mechanisms of most genes. To address this challenge, the International Mouse Phenotyping Consortium is creating a genome- and phenome-wide catalog of gene function by characterizing new knockout-mouse strains across diverse biological systems through a broad set of standardized phenotyping tests. All mice will be readily available to the biomedical community. Analyzing the first 3,328 genes identified models for 360 diseases, including the first models, to our knowledge, for type C Bernard-Soulier, Bardet-Biedl-5 and Gordon Holmes syndromes. 90% of our phenotype annotations were novel, providing functional evidence for 1,092 genes and candidates in genetically uncharacterized diseases including arrhythmogenic right ventricular dysplasia 3. Finally, we describe our role in variant functional validation with The 100,000 Genomes Project and others.

Prevalence of sexual dimorphism in mammalian phenotypic traits

The role of sex in biomedical studies has often been overlooked, despite evidence of sexually dimorphic effects in some biological studies. Here, we used high-throughput phenotype data from 14,250 wildtype and 40,192 mutant mice (representing 2,186 knockout lines), analysed for up to 234 traits, and found a large proportion of mammalian traits both in wildtype and mutants are influenced by sex. This result has implications for interpreting disease phenotypes in animal models and humans.

Systemic dissection of sexually dimorphic phenotypes in mice is lacking. Here, Karp and the International Mouse Phenotype Consortium show that approximately 10% of qualitative traits and 56% of quantitative traits in mice as measured in laboratory setting are sexually dimorphic.

The role of sex and body weight on the metabolic effects of high-fat diet in C57BL/6N mice

BACKGROUND

Metabolic disorders are commonly investigated using knockout and transgenic mouse models on the C57BL/6N genetic background due to its genetic susceptibility to the deleterious metabolic effects of high-fat diet (HFD). There is growing awareness of the need to consider sex in disease progression, but limited attention has been paid to sexual dimorphism in mouse models and its impact in metabolic phenotypes. We assessed the effect of HFD and the impact of sex on metabolic variables in this strain.

METHODS

We generated a reference data set encompassing glucose tolerance, body composition and plasma chemistry data from 586 C57BL/6N mice fed a standard chow and 733 fed a HFD collected as part of a high-throughput phenotyping pipeline. Linear mixed model regression analysis was used in a dual analysis to assess the effect of HFD as an absolute change in phenotype, but also as a relative change accounting for the potential confounding effect of body weight.

RESULTS

HFD had a significant impact on all variables tested with an average absolute effect size of 29%. For the majority of variables (78%), the treatment effect was modified by sex and this was dominated by male-specific or a male stronger effect. On average, there was a 13.2% difference in the effect size between the male and female mice for sexually dimorphic variables. HFD led to a significant body weight phenotype (24% increase), which acts as a confounding effect on the other analysed variables. For 79% of the variables, body weight was found to be a significant source of variation, but even after accounting for this confounding effect, similar HFD-induced phenotypic changes were found to when not accounting for weight.

CONCLUSION

HFD and sex are powerful modifiers of metabolic parameters in C57BL/6N mice. We also demonstrate the value of considering body size as a covariate to obtain a richer understanding of metabolic phenotypes.

Improving the Identification of Phenotypic Abnormalities and Sexual Dimorphism in Mice When Studying Rare Event Categorical Characteristics

Biological research frequently involves the study of phenotyping data. Many of these studies focus on rare event categorical data, and functional genomics studies typically study the presence or absence of an abnormal phenotype. With the growing interest in the role of sex, there is a need to assess the phenotype for sexual dimorphism. The identification of abnormal phenotypes for downstream research is challenged by the small sample size, the rare event nature, and the multiple testing problem, as many variables are monitored simultaneously. Here, we develop a statistical pipeline to assess statistical and biological significance while managing the multiple testing problem. We propose a two-step pipeline to initially assess for a treatment effect, in our case example genotype, and then test for an interaction with sex. We compare multiple statistical methods and use simulations to investigate the control of the type-one error rate and power. To maximize the power while addressing the multiple testing issue, we implement filters to remove data sets where the hypotheses to be tested cannot achieve significance. A motivating case study utilizing a large scale high-throughput mouse phenotyping data set from the Wellcome Trust Sanger Institute Mouse Genetics Project, where the treatment is a gene ablation, demonstrates the benefits of the new pipeline on the downstream biological calls.

Loss of Mrap2 is associated with Sim1 deficiency and increased circulating cholesterol

Melanocortin receptor accessory protein 2 (MRAP2) is a transmembrane accessory protein predominantly expressed in the brain. Both global and brain-specific deletion of Mrap2 in mice results in severe obesity. Loss-of-function MRAP2 mutations have also been associated with obesity in humans. Although MRAP2 has been shown to interact with MC4R, a G protein-coupled receptor with an established role in energy homeostasis, appetite regulation and lipid metabolism, the mechanisms through which loss of MRAP2 causes obesity remains uncertain. In this study, we used two independently derived lines of Mrap2 deficient mice (Mrap2(tm1a/tm1a)) to further study the role of Mrap2 in the regulation of energy balance and peripheral lipid metabolism. Mrap2(tm1a/tm1a) mice have a significant increase in body weight, with increased fat and lean mass, but without detectable changes in food intake or energy expenditure. Transcriptomic analysis showed significantly decreased expression of Sim1, Trh, Oxt and Crh within the hypothalamic paraventricular nucleus of Mrap2(tm1a/tm1a) mice. Circulating levels of both high-density lipoprotein and low-density lipoprotein were significantly increased in Mrap2 deficient mice. Taken together, these data corroborate the role of MRAP2 in metabolic regulation and indicate that, at least in part, this may be due to defective central melanocortin signalling.

Reporting phenotypes in mouse models when considering body size as a potential confounder

Genotype-phenotype studies aim to identify causative relationships between genes and phenotypes. The International Mouse Phenotyping Consortium is a high throughput phenotyping program whose goal is to collect phenotype data for a knockout mouse strain of every protein coding gene. The scale of the project requires an automatic analysis pipeline to detect abnormal phenotypes, and disseminate the resulting gene-phenotype annotation data into public resources. A body weight phenotype is a common result of knockout studies. As body weight correlates with many other biological traits, this challenges the interpretation of related gene-phenotype associations. Co-correlation can lead to gene-phenotype associations that are potentially misleading. Here we use statistical modelling to account for body weight as a potential confounder to assess the impact. We find that there is a considerable impact on previously established gene-phenotype associations due to an increase in sensitivity as well as the confounding effect. We investigated the existing ontologies to represent this phenotypic information and we explored ways to ontologically represent the results of the influence of confounders on gene-phenotype associations. With the scale of data being disseminated within the high throughput programs and the range of downstream studies that utilise these data, it is critical to consider how we improve the quality of the disseminated data and provide a robust ontological representation.

Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4,125 families

Discovery of most autosomal recessive disease genes has involved analysis of large, often consanguineous, multiplex families or small cohorts of unrelated individuals with a well-defined clinical condition. Discovery of novel dominant causes of rare, genetically heterogenous developmental disorders has been revolutionized by exome analysis of large cohorts of phenotypically diverse parent-offspring trios 1,2. Here we analysed 4,125 families with diverse, rare, genetically heterogeneous developmental disorders and identified four novel autosomal recessive disorders. These four disorders were identified by integrating Mendelian filtering (identifying probands with rare biallelic putatively damaging variants in the same gene) with statistical assessments of (i) the likelihood of sampling the observed genotypes from the general population, and (ii) the phenotypic similarity of patients with the same recessive candidate gene. This new paradigm promises to catalyse discovery of novel recessive disorders, especially those with less consistent or nonspecific clinical presentations, and those caused predominantly by compound heterozygous genotypes.

PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data

The lack of reproducibility with animal phenotyping experiments is a growing concern among the biomedical community. One contributing factor is the inadequate description of statistical analysis methods that prevents researchers from replicating results even when the original data are provided. Here we present PhenStat – a freely available R package that provides a variety of statistical methods for the identification of phenotypic associations. The methods have been developed for high throughput phenotyping pipelines implemented across various experimental designs with an emphasis on managing temporal variation. PhenStat is targeted to two user groups: small-scale users who wish to interact and test data from large resources and large-scale users who require an automated statistical analysis pipeline. The software provides guidance to the user for selecting appropriate analysis methods based on the dataset and is designed to allow for additions and modifications as needed. The package was tested on mouse and rat data and is used by the International Mouse Phenotyping Consortium (IMPC). By providing raw data and the version of PhenStat used, resources like the IMPC give users the ability to replicate and explore results within their own computing environment.

Applying the ARRIVE Guidelines to an In Vivo Database

The Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines were developed to address the lack of reproducibility in biomedical animal studies and improve the communication of research findings. While intended to guide the preparation of peer-reviewed manuscripts, the principles of transparent reporting are also fundamental for in vivo databases. Here, we describe the benefits and challenges of applying the guidelines for the International Mouse Phenotyping Consortium (IMPC), whose goal is to produce and phenotype 20,000 knockout mouse strains in a reproducible manner across ten research centres. In addition to ensuring the transparency and reproducibility of the IMPC, the solutions to the challenges of applying the ARRIVE guidelines in the context of IMPC will provide a resource to help guide similar initiatives in the future.

Transparent reporting is key to ensuring reproducibility of animal research. This article examines the challenges of applying the ARRIVE guidelines to a large-scale, collaborative, in vivo research initiative—the International Mouse Phenotyping Consortium.

A high-throughput in vivo micronucleus assay for genome instability screening in mice

We describe a sensitive, robust, high-throughput method for quantifying the formation of micronuclei, markers of genome instability, in mouse erythrocytes. Micronuclei are whole chromosomes or chromosome segments that have been separated from the nucleus. Other methods of detection rely on labor-intensive, microscopy-based techniques. Here we describe a 2-d, 96-well plate-based flow cytometric method of micronucleus scoring that is simple enough for a research technician experienced in flow cytometry to perform. The assay detects low levels of genome instability that cannot be readily identified by classic phenotyping, using 25 μl of blood. By using this assay, we have screened >10,000 blood samples and discovered novel genes that contribute to vertebrate genome maintenance, as well as novel disease models and mechanisms of genome instability disorders. We discuss experimental design considerations, including statistical power calculation, we provide troubleshooting tips and we discuss factors that contribute to a false-positive increase in the number of micronucleated red blood cells and to experimental variability.

Impact of temporal variation on design and analysis of mouse knockout phenotyping studies

A significant challenge facing high-throughput phenotyping of in-vivo knockout mice is ensuring phenotype calls are robust and reliable. Central to this problem is selecting an appropriate statistical analysis that models both the experimental design (the workflow and the way control mice are selected for comparison with knockout animals) and the sources of variation. Recently we proposed a mixed model suitable for small batch-oriented studies, where controls are not phenotyped concurrently with mutants. Here we evaluate this method both for its sensitivity to detect phenotypic effects and to control false positives, across a range of workflows used at mouse phenotyping centers. We found the sensitivity and control of false positives depend on the workflow. We show that the phenotypes in control mice fluctuate unexpectedly between batches and this can cause the false positive rate of phenotype calls to be inflated when only a small number of batches are tested, when the effect of knockout becomes confounded with temporal fluctuations in control mice. This effect was observed in both behavioural and physiological assays. Based on this analysis, we recommend two approaches (workflow and accompanying control strategy) and associated analyses, which would be robust, for use in high-throughput phenotyping pipelines. Our results show the importance in modelling all sources of variability in high-throughput phenotyping studies.

Using association rule mining to determine promising secondary phenotyping hypotheses

MOTIVATION

Large-scale phenotyping projects such as the Sanger Mouse Genetics project are ongoing efforts to help identify the influences of genes and their modification on phenotypes. Gene-phenotype relations are crucial to the improvement of our understanding of human heritable diseases as well as the development of drugs. However, given that there are ∼: 20 000 genes in higher vertebrate genomes and the experimental verification of gene-phenotype relations requires a lot of resources, methods are needed that determine good candidates for testing.

RESULTS

In this study, we applied an association rule mining approach to the identification of promising secondary phenotype candidates. The predictions rely on a large gene-phenotype annotation set that is used to find occurrence patterns of phenotypes. Applying an association rule mining approach, we could identify 1967 secondary phenotype hypotheses that cover 244 genes and 136 phenotypes. Using two automated and one manual evaluation strategies, we demonstrate that the secondary phenotype candidates possess biological relevance to the genes they are predicted for. From the results we conclude that the predicted secondary phenotypes constitute good candidates to be experimentally tested and confirmed.

AVAILABILITY

The secondary phenotype candidates can be browsed through at http://www.sanger.ac.uk/resources/databases/phenodigm/gene/secondaryphenotype/list.

CONTACT

ao5@sanger.ac.uk or ds5@sanger.ac.uk

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Disruption of the potassium channel regulatory subunit KCNE2 causes iron-deficient anemia

Iron homeostasis is a dynamic process that is tightly controlled to balance iron uptake, storage, and export. Reduction of dietary iron from the ferric to the ferrous form is required for uptake by solute carrier family 11 (proton-coupled divalent metal ion transporters), member 2 (Slc11a2) into the enterocytes. Both processes are proton dependent and have led to the suggestion of the importance of acidic gastric pH for the absorption of dietary iron. Potassium voltage-gated channel subfamily E, member 2 (KCNE2), in combination with potassium voltage-gated channel, KQT-like subfamily, member 1 (KCNQ1), form a gastric potassium channel essential for gastric acidification. Deficiency of either Kcne2 or Kcnq1 results in achlorhydia, gastric hyperplasia, and neoplasia, but the impact on iron absorption has not, to our knowledge, been investigated. Here we report that Kcne2-deficient mice, in addition to the previously reported phenotypes, also present with iron-deficient anemia. Interestingly, impaired function of KCNQ1 results in iron-deficient anemia in Jervell and Lange-Nielsen syndrome patients. We speculate that impaired function of KCNE2 could result in the same clinical phenotype.

Evaluation of growth patterns and body composition in C57Bl/6J mice using dual energy X-ray absorptiometry

The normal growth pattern of female C57BL/6J mice, from 5 to 30 weeks of age, has been investigated in a longitudinal study. Weight, body surface area (BS), and body mass index (BMI) were evaluated in forty mice. Lean mass and fat mass, bone mineral content (BMC), and bone mineral density (BMD) were monitored by dual energy X-ray absorptiometry (DEXA). Weight and BS increased linearly (16.15 ± 0.64-27.64 ± 1.42 g; 51.13 ± 0.74-79.57 ± 2.15 cm(2), P < 0.01), more markedly from 5 to 9 weeks of age (P < 0.001). BMD showed a peak at 17 weeks (0.0548 ± 0.0011 g/cm(2) ∗ m, P < 0.01). Lean mass showed an evident gain at 9 (15.8 ± 0.8 g, P < 0.001) and 25 weeks (20.5 ± 0.3 g, P < 0.01), like fat mass from 13 to 17 weeks (2.0 ± 0.4-3.6 ± 0.7 g, P < 0.01). BMI and lean mass index (LMI) reached the highest value at 21 weeks (3.57 ± 0.02-0.284 ± 0.010 g/cm(2), resp.), like fat mass index (FMI) at 17 weeks (0.057 ± 0.009 g/cm(2)) (P < 0.01). BMI, weight, and BS showed a moderate positive correlation (0.45-0.85) with lean mass from 5 to 21 weeks. Mixed linear models provided a good prediction for lean mass, fat mass, and BMD. This study may represent a baseline reference for a future comparison of wild-type C57BL/6J mice with models of altered growth.

Histopathology reveals correlative and unique phenotypes in a high-throughput mouse phenotyping screen

The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice.

The International Mouse Phenotyping Consortium Web Portal, a unified point of access for knockout mice and related phenotyping data

The International Mouse Phenotyping Consortium (IMPC) web portal (http://www.mousephenotype.org) provides the biomedical community with a unified point of access to mutant mice and rich collection of related emerging and existing mouse phenotype data. IMPC mouse clinics worldwide follow rigorous highly structured and standardized protocols for the experimentation, collection and dissemination of data. Dedicated 'data wranglers' work with each phenotyping center to collate data and perform quality control of data. An automated statistical analysis pipeline has been developed to identify knockout strains with a significant change in the phenotype parameters. Annotation with biomedical ontologies allows biologists and clinicians to easily find mouse strains with phenotypic traits relevant to their research. Data integration with other resources will provide insights into mammalian gene function and human disease. As phenotype data become available for every gene in the mouse, the IMPC web portal will become an invaluable tool for researchers studying the genetic contributions of genes to human diseases.

Analyzing gene expression data in mice with the Neuro Behavior Ontology

We have applied the Neuro Behavior Ontology (NBO), an ontology for the annotation of behavioral gene functions and behavioral phenotypes, to the annotation of more than 1,000 genes in the mouse that are known to play a role in behavior. These annotations can be explored by researchers interested in genes involved in particular behaviors and used computationally to provide insights into the behavioral phenotypes resulting from differences in gene expression. We developed the OntoFUNC tool and have applied it to enrichment analyses over the NBO to provide high-level behavioral interpretations of gene expression datasets. The resulting increase in the number of gene annotations facilitates the identification of behavioral or neurologic processes by assisting the formulation of hypotheses about the relationships between gene, processes, and phenotypic manifestations resulting from behavioral observations.