SARS-CoV-2 and Mouse Genetics

Computer generated SARS-CoV-2 virions.


Published 2nd April 2020

What is SARS-CoV-2 and How Can Mice Help?

Viruses are infective agents that cause disease. They are different from other pathogens, such as bacteria, fungi and parasites, because most scientists don’t technically classify them as alive. They’re not 100% an organism as they cannot grow and reproduce by themselves. They’re made of the same building blocks of life (DNA, RNA and nucleic acids) as other organisms (such as bacteria or our own cells) but are unable to read and use this information. They reproduce by infecting host cells and hijacking the host’s processes. By inserting its genetic information into a cell’s DNA, when the cell begins to produce proteins it reads the viral DNA instead of its own, producing viral components that assemble into a new virion which can then infect a new cell.

Scientists classify viruses in several ways because they vary so widely, such as whether they have DNA or RNA or by their size and shape. Coronaviruses have single-stranded RNA genetic material encased in a viral envelope – a layer of protein usually made up of host cell and viral proteins that allows a virion to bind to a new host cell and fuse with it, starting the viral replication process. Coronaviruses have many club-shaped viral spike proteins attached to its envelope that creates a crown or corona-like appearance when viewed under a microscope.

Transmission Electron Microscope image of SARS-CoV with its characteristic corona. Credit: CDC/ Dr. John Hierholzer

There are a number of different coronaviruses that infect different animal species and cause widely varying severity of respiratory disease. There are seven known human coronavirus species (HCoVs), including the recent MERS-CoV and SARS-CoV. ‘COVID-19’ actually refers to the disease caused, not the virus that causes the disease, and stands for ‘coronavirus disease 2019’. COVID-19 is caused by the most recent novel coronavirus, first known as 2019-nCoV and now known as SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2.) SARS-CoV-2 is more infective than SARS-CoV and MERS-CoV and therefore spreads more easily but is less fatal(1).

It is SARS-CoV-2’s spike protein that allows it to bind to human cells via the ACE2 (angiotensin converting enzyme 2) receptor(2). This receptor is found on lung, artery, heart, kidney and intestine cells. Normally, human angiotensin, a protein, will attach to the ACE2 receptor, causing a lowering of blood pressure. The viral spike protein’s shape also fits ACE2 like angiotensin does, allowing a virion to bind to the receptor and enter cells.

SARS-CoV-2 and spike protein 3D models. Credit: NIAID / CC BY (

Mice also have an ACE2 receptor but its shape is different from the human version and SARS-CoV-2 doesn’t bind to it as easily. This means mice can be naturally infected with the virus but the severity of the disease is less than in humans(3). A mammalian model is vital for studying the virus and the disease it causes, as well as validating possible treatments and vaccines. Institutions such as our consortium member The Jackson Laboratory (JAX) are breeding a mouse colony with humanised ACE2 receptors (K18-hACE2 transgenic mouse model(3).) By genetically altering the mice to produce human ACE2 instead of mouse ACE2 we can create a much more applicable mouse model for the study of SARS-CoV-2. This will enable scientists to complete the research needed to treat the outbreak.

Main image credit: Felipe Esquivel Reed / CC BY-SA (


Singhal, T. A Review of Coronavirus Disease-2019 (COVID-19). Indian J Pediatr 87, 281–286 (2020).

Letko, M., Marzi, A. & Munster, V. Functional assessment of cell entry and receptor usage for SARS-CoV-2 and other lineage B betacoronaviruses. Nat Microbiol 5, 562–569 (2020).

McCray PB Jr, Pewe L, Wohlford-Lenane C, et al. Lethal infection of K18-hACE2 mice infected with severe acute respiratory syndrome coronavirus. J Virol. 81(2), 813–821 (2007.) https://doi:10.1128/JVI.02012-06

The International Mouse Phenotyping Consortium (IMPC) is a collaboration between world-leading research institutions that specialise in mouse genetics to identify the function of every protein-coding gene in the mouse genome. In recent years, many projects have aimed to sequence the entire genome of numerous species, such as the Human Genome Project, but for many of these projects, the function of these genes remains unknown. The IMPC aims to complete an open-access database that describes what each gene does and how it can affect a mouse physically when it doesn’t work properly.

A map of IMPC collaborators

All organisms have two versions of each gene called alleles. Genes control the production of proteins within organisms, which are vital for cell structure and function. Mutations can cause genes to stop working, which changes the function of the protein or the amount produced. These changes can disrupt development and cause physical and chemical abnormalities.

To find the function of each gene, the IMPC genetically alters mice by turning off one or both alleles for each protein-coding gene, creating a knockout mouse line. The IMPC then conducts a series of tests to find what effect the alteration has had, such as testing grip strength, body weight, blood content, behaviour, sleeping and eating patterns, sight, hearing and much more. The IMPC then analyses the test data for significance and uploads findings into the open-access database. The knockout mouse lines are deposited in publicly funded repositories so researchers can obtain mouse lines for their studies.

How Does Mouse Genetics Apply to Humans?

We share 97% of our DNA with mice, as well as being biologically and behaviourally very similar to humans. They are also very well understood, convenient, and reproduce quickly so that we can observe and study the genetics of several generations. This makes mice a reliable model for human disease and researchers have used them to study cancer and inherited diseases such as diabetes, heart disease, Parkinson’s and Alzheimer’s for decades.

Queen Mary University of London (QMUL) takes IMPC data and analyses it to find associations to human disease. One method used is the study of ‘orthologs.’ These are genes in different species that share an ancestor gene and are therefore more likely to have a similar function. Another method is through data analysis – comparisons are made between the physical changes seen in the mouse after a gene has been turned off to the disease characteristics listed in human rare disease databases, such as OMIM and Orphanet, to see if there are any significant similarities. Through this, genetic mutations in mice can be related to disease in humans.

In 2017, experts from the IMPC and QMUL analysed 3,328 genes in the database and identified models for 360 diseases, including possibly the first models for type C Bernard-Soulier, Bardet-Biedl-5 and Gordon Holmes syndromes.

A disease is usually considered rare if less than 1 in 2,000 people is affected within the population, meaning most genetic conditions are classed as rare diseases. Some of the more well-known genetic diseases, such as Cystic Fibrosis, Muscular Dystrophy and Multiple Sclerosis are well studied but others are not. The less researched a condition is, the harder it is to treat and manage. Some mutations, and the disease they cause, are so rare that there are only clinical records of one or a few families with shared symptoms.

A major aim of the IMPC database is to assist research into rare disease, building a starting point for novel research into the mechanisms of rare disease, new possible treatments and precision medicine – allowing doctors to choose personalised treatments on a genetic basis. Through this, patients can receive accurate and effective healthcare for their conditions.

IMPC Resource Use

Data experts within the IMPC find new ways of analysing the IMPC database (and other open access rare disease databases) to find new ‘candidate genes’ – genes that have not previously been related to disease but have a high chance of causing disease. Recent IMPC screens include finding possible genetic causes behind hearing disorders, metabolic diseases, integumentary and oculocutaneous (hair, skin, eyes and pigmentation) conditions, sleeping and eating disorders and neurodegenerative disease.

Externally, researchers are constantly using IMPC resources for their work. Recent examples of how IMPC alleles have been used are:

  • Clear cell sarcomas, a rare soft tissue cancer.
  • Bardet-Biedl syndrome (BBS) which causes vision loss, obesity, extra fingers and toes and learning problems, among other symptoms.
  • Primary familial brain calcification (PFBC), in which deposits of calcium accumulate in the basal ganglia – structures found deep within the centre of the brain. This can cause movement disorders and psychiatric problems like psychosis, dementia and vertigo.
  • Aicardi-Goutières syndrome (AGS) which causes severe brain dysfunction leading to fevers, seizures, developmental issues and muscle issues. Symptoms start very early, around one year of age, and due to the severity of the condition, most do not reach adulthood.
  • Gray platelet syndrome (GPS), a bleeding disorder that can cause easy bruising, nosebleeds and heavy bleeding after an injury.
  • Karyomegalic interstitial nephritis (KIN), a hereditary, progressive and chronic form of kidney disease.

Researchers can source mice, embryonic stem cells and data for each processed gene on the IMPC website and database. Start searching genes by using our search function above.

For the Future

Since data release 11, the IMPC has now fully tested 6,440 protein-coding genes, but there are still over 11,000 mouse orthologs to be processed and their association to disease still needs to be analysed. The IMPC’s key aim is to complete the analysis of every protein-coding gene in the mouse genome. Having a complete database will only further the use and applications of IMPC resources in rare disease research, opening possibilities for new treatments and better healthcare for patients.

With a contribution from the IMPC, recent research, published in Nature Communications, has identified 198 genes associated with brain morphogenesis in mice – 83% of these constitute genes newly implicated in brain architecture.

Brain development and morphogenesis is critical to higher-order cognition, but our knowledge of its biological basis is at best incomplete, and at worst, severely lacking. Previous studies have demonstrated that there is a significant genetic influence on brain morphology. However knowledge of which genes influence brain morphology is limited, and this presents an important problem in developmental biology. By identifying 198 genes that are associated with mouse brain morphogenesis the study provides a complementary resource to human genetic studies and predicts that many more genes could be involved in mammalian brain morphogenesis.

Binnaz Yalcin, corresponding author of the study says “This study aims at understanding the genetics of brain anatomy in the mouse. It provides a wealth of novel knowledge about which genes control the size and the shape of the brain, and a foundation on which neurobiologists can build to further study how exactly these genes control the brain anatomy”.

“I have no doubt that this resource will help medical geneticists working on ultra-rare human neurodevelopmental disorders

The researchers obtained brain samples of 1566 mutant mouse lines from the Sanger Institute Mouse Genetics Project, a partner of the IMPC. Using a histological pipeline, 118 brain morphological parameters were analysed, covering brain size, commissures, ventricles, cortex, subcortex and cerebellum. To detect neuroanatomical phenotypes (NAPs), the researchers used PhenStat, a statistical method developed by the IMPC for the identification of abnormal phenotypes. 198 genes associated with neuroanatomical phenotypes (NAP genes) were subsequently identified. The vast majority of these genes (94%) have never previously been associated with brain anatomy in mice.

Interestingly, unique human orthologs were identified for 173 of the identified mouse NAP genes. Whilst 17% of human unique orthologs of mouse NAP genes are known loci for cognitive dysfunction, 83% constitute a vast number of genes that are newly implicated in brain architecture. This dataset may therefore help in improving clinical interpretation.

Yalcin states “I have no doubt that this resource will help medical geneticists working on ultra-rare human neurodevelopmental disorders who sometimes struggle to determine the genetic mutation responsible for the underlying disease, when for example there is only one patient world-wide. So when a mutation is found in a patient’s genome and that patient exhibits the same phenotype than the mouse, a molecular diagnosis can finally be made.”

This study would not have been possible without the IMPC

The identified NAP genes converge into a small number of groups of functionally similar genes participating in shared cellular pathways. Disruption of genes within the same module can yield a similar pattern of neuroanatomical abnormalities, revealing interesting neurodevelopmental pathway/phenotype relationships. For example, the study indicates that mechanisms confined to sub-cellular compartments as subtle as dendritic spines can translate into major anatomical features.

The study represents the largest atlas of the link between genetic mutation and its associated neuroanatomical features yet, and contributes a wealth of new knowledge on the genetics of brain morphogenesis. The authors were keen to note the contribution of the IMPC towards their work, with Yalcin commenting that “This study would not have been possible without the IMPC and is a tribute to the remarkable work of the people involved in this consortium.”

The IMPC is aiming to design and produce a genome-wide mouse strain resource of human disease-associated coding variants associated with rare disease that can be used for validation of putative functional variants and insight into disease mechanism(s). To find out more, click here.

Original publication: Large-scale neuroanatomical study uncovers 198 gene associations in mouse brain morphogenesis

Members of the IMPC Consortium at CNR-Monterotondo (Italy) have used embryonic stem (ES) cells produced as part of the IMPC project, to engineer a Ccdc151 ‘knockout’ mouse model that is valuable for the study of human ciliopathies, gaining significant insight into this set of rare conditions.

Primary ciliary dyskinesia (PCD) is a rare, genetic disorder that results in chronic respiratory tract infections, abnormally orientated internal organs and infertility. The root cause of these symptoms are dysfunctional cilia and flagella, which if functioning correctly, are finger-like projections on the surface of cells that act to clear mucus and debris by coordinated beating. In addition, normal function of cilia is required for migration of egg and sperm cells.

Ccdc151 is a gene that is known to be associated with PCD, and here, researchers have engineered a mouse model, using embryonic stem cells from the IMPC, in which the gene is deleted. Common features of PCD in human patients such as left-right body asymmetry and dysfunctional spermatogenesis were detected in these Ccdc151-knockout mice. “The Ccdc151-knockout mouse model faithfully recapitulates several features of human PCD disease” remark Francesco Chiani and Tiziana Orsini, co-first authors of the paper. “The availability of this animal model will allow researchers to further dissect the mechanisms by which pathological conditions develop in different organs”.

This animal model will be useful for studying mechanisms underlying hydrocephalus, a condition whose treatment has not changed for decades.

The researchers also observed that Ccdc151-knockouts develop severe hydrocephalus – a condition in which cerebrospinal fluid accumulates in the brain, causing increased pressure inside the skull and potentially leading to brain damage and other complications. This is the first example of hydrocephalus caused by loss of function in the Ccdc151 gene. Although hydrocephalus is rarely seen in human patients with PCD, having a mouse model that exhibits all of the features of hydrocephalus could be useful for researchers. “This animal model will be useful for studying mechanisms underlying hydrocephalus, a condition whose treatment has not changed for decades”, said the lead authors. It is hoped that further studies may help to uncover other genes that interact with Ccdc151 that lead to the development of hydrocephalus.

this micro-CT imaging methodology could be applied to facilitate studies on gene expression directly in the intact brain

The researchers made extensive use of X-ray micro-CT 3D imaging to study the hydrocephalic brains of Ccdc151 knockout mice – a technique that uses X-rays to create a virtual 3D model of a target object. Additionally, a novel micro-CT method was used to study expression of the Ccdc151 gene in the brain. This novel method is based on the generation of a molecular signal within the mouse brain. The authors remarked that “this micro-CT imaging methodology could be applied to facilitate studies on gene expression directly in the intact brain carrying the lacZ reporter gene, which is widely used as a reporter gene in mouse models.”

The link between Ccdc151 and ciliary function is now clear, but the mechanism by which the Ccdc151 protein contributes is less so. “The precise mechanism by which Ccdc151 protein accomplishes its function is unknown and will be addressed in future research”, says Chiani. The Ccdc151-knockout mouse model, generated via IMPC resources, could be “instrumental to dissect the role of the motile cilia in diverse physiological processes during development, adult life and aging”.

In addition to providing biological resources that can contribute to research such as this, the IMPC is curating a catalogue of mammalian gene function, with phenotyping data for knockout mouse models such as Ccdc151.

Research paper: Functional loss of Ccdc151 leads to hydrocephalus in a mouse model of primary ciliary dyskinesia

Quotes taken from interview with Disease Models & Mechanism: First person – Francesco Chiani and Tiziana Orsini

In collaboration with NC3Rs, IMPC member institution MRC Harwell has launched a new citizen science project that aims to advance medical research and mouse welfare.

The mouse is a vital model organism as we seek to understand the function of genetic variation. The analysis of genetic variants in the mouse has provided crucially important insights for the biomedical and clinical sciences through hypothesis-driven discovery research. When researchers make changes to the genetic make up of mice, they can subsequently observe them to deduce the effect of the introduced changes. Mice are sociable animals and are housed in groups, however, in order for scientists to observe them, they may previously have been removed from their cages and into an unfamiliar environment.

Scientists at MRC Harwell have worked together with Actual Analytics in order to develop the Home Cage Analysis system (HCA), which has the potential to change the way that mice are studied, improve their welfare and drastically change the way that we collect data from mouse models by allowing the public to contribute.

Home Cage Analysis System

The challenge proposed by the NC3Rs CRACK IT initiative was to ‘develop an automated, minimally-invasive or non-surgical system to assess activity, behaviour and interaction of at least two mice in the cages and setting the animals were reared in’. The Home Cage Analysis System was the result. The system is able to track the movement of three individual mice without removing them from their social group, only requiring the minimally invasive insertion of a microchip. Through high grade video recording, it is now possible to observe the activity of mice 24/7.

How Will This Be Of Benefit?

Not only do these developments have the potential to improve the welfare of mice involved in research, but it also has exciting implications for the science itself. It will now be possible to collect more data on mouse behaviour, potentially providing us with vital information on the early stage of diseases. Additionally, the more data that is collected, the greater the statistical power of testing. It is also important not to forget that mice are naturally nocturnal, and the Home Cage Analysis system will allow information to be captured on mouse behaviour at night, a time when previously this important information would have been missed. Perhaps most excitingly, the Rodent Little Brother project allows the public to get involved and to supporting cutting-edge research on mouse models.

What is the Role of the Public?

The rise of machine learning is very exciting, and could have lots of positive implications in research. The end goal of this citizen science project is to have a computer algorithm to track and annotate mouse behaviour for us. However, this algorithm first needs to learn what different mouse behaviours are. By allowing people to manually annotate these mouse behaviours, we will be able to feed the algorithm enough information to be able to collect data 24/7 in the future!

Overall, it is hoped that this project will advance understanding of how genes cause disease and aid the development of new therapies, all whilst improving mouse welfare.

To get involved in the project, visit the Rodent Little Brother Home Page.

To read about mouse welfare within the IMPC, click here.

CLOVES syndrome is a rare condition that is characterised by tissue overgrowth and vascular abnormalities, caused by mosaic gain-of-function mutations in the PIK3CA gene. The way in which CLOVES syndrome manifests itself is highly variable but common features include fatty overgrowths, vascular anomalies, kidney problems and spinal-related symptoms. The condition has no specific treatment and a low survival rate. It is one of a number of conditions that can be grouped under the umbrella of PIK3CA-related overgrowth syndromes (PROS).

By initially undertaking research on a mouse model, and subsequently with human patients, it has been shown by Dr Guillaume Canaud and his team at the Necker-Enfants Malades Hospital in Paris, that BYL719 (an inhibitor of PIK3CA, currently undergoing clinical trials for treating PIK3CA dependent tumours) can prevent and improve organ dysfunction and can improve disease symptoms in patients suffering from CLOVES syndrome.

A mouse model of CLOVES syndrome

The researchers generated mice that express a PIK3CA transgene upon the administration of tamoxifen, mimicking the activity of human CLOVES syndrome. These mice showed similar symptoms to human sufferers of CLOVES, with MRI revealing scoliosis, kidney cysts and muscle abnormalities. Subsequent histological examination revealed further organ abnormalities including additional kidney problems, and abnormalities in the liver and spleen. Furthermore, a high level of cell proliferation was observed in all of the affected organs.

Rapamycin or BYL719?

Rapamycin has previously shown evidence of improving vascular malformations, and when tested on the mouse model of CLOVES syndrome it improved survival rate. However, it did not improve organ abnormalities and did not significantly reduce tumour growth. In contrast, mice treated with BYL719 were found to have preserved tissues and normal vessels. Importantly, BYL719 administration strongly reduced cell proliferation in all affected organs. Withdrawal of BYL719 led to the recurrence of tumours within four weeks, suggesting that continuous administration of BYL719 could relieve the symptoms of CLOVES syndrome.

BYL719 leads to huge improvements in patients with CLOVES syndrome

BYL719 was initially administered to two patients suffering with CLOVES syndrome, who both, after being treated with BYL719, showed dramatic and rapid improvement in their condition. There was a major reduction of vascular tumour abnormalities and overgrowths in addition to improved renal function and a significantly increased quality of life in both patients. The only observed side-effect was hyperglycaemia, which was able to be controlled by a controlled diet.

On the basis of these initial results, Canaud and his team were given permission to treat 17 additional patients with CLOVES syndrome by administering BYL719. The 14 children and 3 adults all showed substantial clinical improvement. A reduction in size of vascular tumours was observed in all of the patients, as well as a drastic reduction in metabolic activity of affected areas. In addition to an improvement to skin capillary abnormalities and scoliosis, all patients reported decreased tiredness. The growth of the children was not affected during the 6 months of treatment and the only side-effects seen were discrete mouth ulcerations in 3 patients (that ultimately disappeared spontaneously) and the aforementioned hyperglycaemia.

The IMPC is aiming to design and produce a genome-wide mouse strain resource of human disease-associated coding variants associated with rare disease that can be used for validation of putative functional variants and insight into disease mechanism(s). To find out more, click here

Research paper: Targeted therapy in patients with PIK3CA-related overgrowth syndrome

Research published in Nature identifies SET domain protein 3 (SETD3) as a physiological actin methyltransferase, and uncovers SETD3’s crucial role in the regulation of smooth muscle contractility and its link to primary dystocia in mammals.

For many years it has been known that actin, essential for a large number of cellular processes such as cell motility and the regulation of DNA transcription, is methylated at the amino acid histidine 73 (His73). His73 methylation is found in several model organisms, but its function for many years had remained unclear. After identifying SETD3 as the methylator of actin His73, researchers sought to discover the purpose of actin His73 methylation, and with the help of some mice, they were successful.

Identifying the function of SETD3

To identify the enzymatic function of SETD3, the researchers performed in vitro methylation assays, which showed that the only potential substrate methylated by SETD3 was β-actin. The researchers were then able to identify the exact location of methylation on actin by SETD3 using tandem mass spectrometry. This turned out to be His73. In order to analyse the catalytic specificity of SETD3, the scientists compared methylation events in human cells both with and without the presence of SETD3. Of the 180 histidine methylated peptides, actin-His73 methylation was the only modification that was altered in the absence of SETD3 – identifying actin-His73 methylation as the primary physiological function of SETD3.

Studying SETD3 deficient mice

To confirm the physiological function of SETD3 in vivo, the researchers obtained mice with one copy of their Setd3 gene knocked out (Setd3+/-) from the Canadian Mouse Mutant Repository. The mouse strain was made at the Toronto Centre for Phenogenomics, an IMPC member institution, using embryonic stem cells. From this strain, it was possible to generate Setd3 null homozygote mice (Setd3-/-) i.e. mice with both of their copies of Setd3 knocked out. The methylation of actin wasn’t detected in any tissues obtained from SETD3-deficient mice, however, in tissues that expressed SETD3, the majority of actin was methylated – confirming the role of SETD3 as the actin His73 methyltransferase.

Actin methylation regulates actin polymerisation

Previous studies suggest that the methylation of His73 influences actin polymerization dynamics, and here the researchers observed that methylation promoted actin polymerization kinetics in vitro. To explore this idea further, they obtained mouse embryonic fibroblasts that were positive for actin-His73me and compared them with fibroblasts from Setd3-/- mice that lacked methylation. Cells containing methylated actin were more efficient at migrating than cells without methylated actin – consistent with the idea that methylation of actin by SETD3 positively regulates the polymerisation of actin.

Uterine cell contraction and primary dystocia

Mice without functioning SETD3 protein are able to survive, despite the cell migration defect observed in their embryonic fibroblasts. The researchers were able to infer therefore, that actin-His73me must have a specialised role that isn’t a necessity for survival. IMPC data for Setd3 identifies several phenotypes associated with Setd3 knockout mice including short tibia, decreased body length and decreased lean body mass. In addition to this, the researchers noticed that litter sizes in female Setd3-/- mice were significantly smaller than expected. After mating Setd3-/- females with wild type males, dystocia, normally a rare phenotype, was noted in 8 out of 9 Setd3-/- mice. The lack of obvious pelvic abnormalities in the Setd3-/- females mean that the cause of dystocia is most likely genetic. Unlike with wild type mice, early labour could not be induced in Setd3-/- mice with oxytocin, suggesting a specific requirement for SETD3 in the contraction of the uterus during labour, a process which relies upon correctly functioning actin. This led to the proposal that actin-His73me is linked to uterine cell contraction in the primary dystocia of SETD3 deficient mice.

More IMPC related research: Research Reveals Novel Genetic Influences On Osteoporosis

Research paper covered in this article: SETD3 is an actin histidine methyltransferase that prevents primary dystocia

Recent research, published in nature genetics, identifies novel genetic influences on osteoporosis, with the potential to empower future research on osteoporosis and potentially lead to new drug targets.

Osteoporosis is a condition that develops slowly over several years and leads to increased bone fragility. Fragile bones are more prone to fracture, with hip, wrist and spine bones being particularly vulnerable to breakage. Whilst there are many factors that affect the chances of an individual developing osteoporosis such as low body weight, certain medical conditions and age, the disease is highly heritable – you are much more likely to develop osteoporosis if your family has a history of the condition. By assessing the genetic determinants of bone mineral density (BMD), the most clinically relevant factor for diagnosis, the researchers were able to create an atlas of genetic influences on osteoporosis.

GWAS identifies gene loci linked to bone mineral density and fracture risk

Using UK Biobank data, the researchers carried out a genome-wide association study (GWAS), with the aim of identifying the common genetic variants associated with estimated bone mineral density (eBMD). The study found 518 genome-wide significant loci, with 301 of these being novel. Additionally, they undertook a GWAS aimed at identifying genetic loci linked with fracture risk. The results revealed 13 loci associated with risk of fracture. As might be expected, genetic variation associated with risk of fracture was also found to be associated with BMD i.e. alleles associated with low eBMD increased fracture risk.

Causal genes linked to genetic loci

Genetic associations in humans, however, rarely result in improved clinical care, usually due to a lack of identification of causal genes at the associated loci. With this in mind, the researchers tested the DNA locations associated with BMD and fracture risk, to see which features of the DNA linked to genes that are known to influence bone biology in humans. This resulted in a set of ‘Target Genes’ that are known to have an effect on bone density and strength in humans – prioritising genes at associated loci for functional testing.

Using mouse models for in-depth analysis

The study initially used mouse models to successfully test the validity of the identified Target Genes, with outlier phenotypes more frequent in mice with disruptions to 126 Target Genes compared with 526 unselected knockout lines. The in vivo and in vitro data produced thus far in the study converged to identify DAAM2 as a highly credible and novel osteoporosis gene.

After discovering that inducing a double strand break in the DAAM2 gene severely impairs mineralization in human bone cells, the researchers used mice obtained from the Wellcome Trust/Sanger Institute (generated as part of the IMPC, using ES cells) for in-depth characterisation of DAAM2. Mice with both versions of their DAAM2 gene disrupted (Daam2tm1a/tm1a) exhibited reduced vertebral bone mineral content accompanied by a small reduction in femur length.  Perhaps most significantly, the mutant mice also had markedly reduced bone strength. The increased cortical porosity observed in both male and female Daam2tm1a/tm1a mutants, along with the abnormal bone composition and structure exhibited, allowed the researchers to conclude that this decreased bone strength in Daam2tm1a/tm1a mice was not simply a result of abnormal bone turnover. If DAAM2 proves to be a viable drug target – it could result in a complementary therapeutic strategy for the prevention and treatment of osteoporosis.

The goal of the IMPC is to knock out and phenotype all 20,000 or so genes in the mouse genome, potentially providing major insights into unexplored areas of the mammalian genome. To order IMPC mice, click on the shopping cart on the top part of the gene page of interest or scroll down to “Order Mouse and ES Cells”.


Details on more phenotype associations for DAAM2 can be found on the IMPC Daam2 gene page. Various phenotype association data can be found such as that shown below.

Research Paper: An atlas of genetic influences on osteoporosis in humans and mice

The inhibition of alkaptonuria by the chemical nitisinone in a mouse model led to a full-scale clinical trial funded by the European Commission – the results of which are expected to produce medicine for a condition for which there was previously no treatment available.


Alkaptonuria (AKU) is caused by a deficiency of homogentisate 1,2 dioxygenase, an enzyme that is required for breaking down the two amino acids tyrosine and phenylalanine. The lack of a functional copy of this enzyme results in a vast increase in circulating concentration of homogentisic acid (HGA), leading to a darkening of the urine upon exposure to air.

High levels of homogentisic acid within the human body eventually leads to ochronosis – a progressive pigmentation of connective tissues and eventually severe joint disease, which can become fatal later in life.

Whilst AKU is a serious condition, for many years it was not seen as prevalent enough among the population to be lucrative for drug developers. However, physicians had long suspected that nitisinone, a chemical that was first developed for use as a weed-killer, could be used to treat AKU – nitisinone was being used effectively to treat tyrosinemia (a condition that results from disruption to the same metabolic pathway as AKU).

There was a small-scale clinical trial run in the US between 2005 and 2008, but too few patients were recruited and the clinical endpoint (the success of the treatment) was defined very narrowly. No positive results were obtained.

In order for a clinical trial to succeed, a more reliable endpoint would have to be suggested, and this required more knowledge of how the disease developed. With this in mind, funding obtained from Britain’s Big Lottery Fund went to a research team at the University of Liverpool to develop a mouse model of AKU.

A colony of Hgd-/- (the genetic equivalent of human AKU) mice were bred by the research team in Liverpool and the mice were established as a model of the plasma biochemistry of AKU and its associated arthropathy. The concentration of plasma HGA was found to be 0.149 ± 0.019 mM, whilst HGA levels in WT mice were below the level of UV detection. The researchers were also able to determine that pigmentation of connective tissue increased linearly with increasing age. Perhaps most importantly though, a significant difference was found between HGA concentrations before and after treatment with nitisinone. Levels of plasma HGA dropped by 88% – a figure that was maintained over the mouse lifetime, with joint tissue from nitisinone-treated AKU mice showing no pigmented tissue.

The results of this mouse model study led to a full-scale clinical trial, funded by the European Commission, with use of nitisinone as a treatment for AKU expected to be approved across Europe once the trial comes to an end.

The aim of the IMPC is to generate similar knock out lines – on a much broader scale, with the goal of producing knock out mutations in embryonic stem cells for 20,000 known and predicted mouse genes, and determining the function of each of these genes. The mouse’s genetic similarity to humans (95% at the gene level) means that data generated by the IMPC could be a powerful tool as we seek to understand the genetic basis of human disease. As our knowledge of rare genetic diseases increases in line with rapid technological advancement, the desire for treatments targeted to small groups of sufferers with these diseases will also likely increase – the case involving alkaptonuria is likely to be just one instance of a mouse model proving to be a driver behind new treatments.

Research article: Ochronotic osteoarthropathy in a mouse model of alkaptonuria, and its inhibition by nitisinone


By Kathryn Hentges and Andrew Doig

Essential genes are those that are required for an organism to survive. We have been interested in studying genes that are essential during development, which could be viewed as the genetic basis for building an organism. Developmentally essential genes thus produce lethal phenotypes in knockout experiments. In some organisms with small genomes and experimental accessibility, essential genes have been identified through direct testing. Although the IMPC is in the process of determining gene function for all protein coding genes in the mouse genome, at present thousands of genes have not yet been tested. To identify essential genes on a genome-wide scale, and also determine the properties that distinguish essential genes from non-essential genes, we utilized machine learning to predict the essentiality status of all mouse protein coding genes that lack experimental data at present.

To generate a machine learning classifier for mouse gene essentiality, we compiled a list of approximately 1300 known essential mouse genes and approximately 3400 known non-essential mouse genes, previously studied in knockout experiments.  A set of features, which included genomic, proteomic, and expression data, were obtained for each gene in the genome. We then used machine learning to find features that were likely to be associated with essential genes and those that were not likely to be associated with essential genes. We found that features associated with intracellular functions, such as transcriptional regulation, were highly likely to be associated with essential genes, and those associated with cellular interactions, such as extra cellular signaling, were likely to be found in non-essential genes. Using these features, our classifier was used to predict the essentiality status of all protein coding genes in the mouse genome.  We confirmed that our classification predictions were accurate by checking our predictions against experimental results that were generated by the IMPC during the course of our study and hence not included in our initial gene sets.  This comparison showed that our machine learning classifier was correct for approximately 80% of genes. Our results can be found at

Additionally, we compared our findings on mouse essential genes to studies of human essential genes.  Orthologous genes in both species tended to have the same essentiality status. Overall, features enriched in essential and non-essential mouse genes were enriched in human genes of the same essentiality status.  Due to this conservation in function, our predictions may be useful for identification of human gene essentiality and understanding the functions required for mammalian development.  Our predictions can also aid investigators planning mouse knockout experiments by giving an indication of whether a lethal phenotype is likely to result from creating a null allele of the gene of interest.

Original Publication: Tian D, Wenlock S, Kabir M, Tzotzos G, Doig AJ, Hentges KE. Identifying mouse developmental essential genes using machine learning. Dis Model Mech. 2018 Dec 13;11(12). pii: dmm034546. doi: 10.1242/dmm.034546. PMID:30563825



Published 20th February 2019

The IMPC Newsletter

Get highlights of the most important data releases, news and events, delivered straight to your email inbox

Subscribe to newsletter