The 100,000 Genomes Project is applying whole genome sequencing in a diagnostic setting to rare disease and cancer patients from the National Health Service (NHS) of the UK. In the video below Damian Smedley describes how clinical phenotype data is collected on each rare disease patient and how this work takes advantage of a number of reference disease and model organism genotype to phenotype databases including the International Mouse Phenotyping Consortium. The video was recorded at the recent KOMP2/IMPC annual meeting, hosted by the National Human Genome Research Institute.
The entire genome of many species has now been sequenced, but the function of the majority of genes still remains unknown. This is where the International Mouse Phenotyping Consortium (IMPC) comes in, with the goal of characterising all 20,000 or so protein-coding mouse genes. To achieve this, genes are systematically inactivated then mice are put through a standardised phenotyping platform, with tests undertaken across a broad range of biological systems.
The consortium is comprised of 19 research institutions, 5 national funders and 11 countries. Each centre focuses on particular genes, applies standardised tests and then records the resulting data. After this, phenotype analysis is conducted and the resulting data and statistics made freely available to the research community. As well as completing large scale comparative studies, the overall aim of the project is to create a platform for this data where researchers and clinicians can search for genes, phenotypes or diseases of interest to help them understand human biology, health and disease.
Professor Steve Brown, the IMPC chair says “The IMPC is rising to the challenge of generating a complete functional catalogue of the mouse genome. Since its inception in 2011, it has made great strides with a third of the genome already analysed. Moreover, many startling and hitherto undiscovered features of the mammalian genome landscape have been revealed.”
There are now over 6,000 genes with mouse mutant data on an isogenic genetic background (C57BL/6N) on the IMPC website, all of which can be viewed and downloaded for free. In its initial stages the knock out lines used for IMPC were all made in ES cells by homologous recombination, all containing a lacZ reporter and many of them generating conditional mouse lines. However, as for many areas of developmental biology, new gene editing technologies, in particular CRISPR/Cas9, have condensed the process of generating knockout mouse lines. Advancements such as this have improved production and will allow all 20,000 genes to be characterised in the next few years.
Around a third of knockout genes are embryonic lethal and consequently developmental biology is an integral part of the IMPC project. In particular, there is an extensive embryo phenotyping pipeline that includes systematic harvest of embryos at set stages, capture of morphology by 3D imaging (OPT or microCT, depending on embryonic stages) and evaluations of morphological abnormalities in mutant embryos. These procedures can allow direct insight into the window of lethality for each mouse line, but they also provide valuable information on gene function. For example, accurate measurements of organ size and shape can be collected using microCT scan data, or macroscopic observations undertaken by a trained researcher. Importantly, all 3D data sets are available to download from the website for further in-depth analysis by specialist researchers.
In the last few years the IMPC has made major discoveries about parts of the genome that were up to now unexplored, with novel genes discovered relating to areas such as embryonic development, deafness, diabetes, and rare diseases. Recent high profile publications have included research focusing on inferring mammalian gene function, studies on specific human conditions, sexual dimorphism in mouse research, and even using IMPC data to help in wildlife conservation. New methods and analysis tools have also been developed under the umbrella of the IMPC, such as PhenStat, an extensive library of functions that analyse the phenotypical data. Another example is illustrated by a recent article that highlights a new bioimage informatics platform for high-throughput embryo phenotyping. Although this platform was built for the IMPC, the software tools that facilitate the analysis and dissemination of 3D images can be used by other researchers, and is available under an open-source licence. Indeed, sharing resources across the research community is a crucial aspect of the IMPC, and mutant mouse lines can be obtained from the website.
The IMPC is continuing to deliver data and mouse models for the developmental biology field and ultimately will be part of the effort to understanding and treating genetic conditions in humans. More information on the latest research of the IMPC can be found on our blog, and you can search the IMPC database for free at https://www.mousephenotype.org/.
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New research finds that scientists are still studying the same 10% of human genes and ignoring the rest, highlighting the importance of international projects such as the IMPC.
Historical bias is a key reason why biomedical researchers continue to study the same 10 percent of all human genes while ignoring many genes known to play roles in disease, according to a study publishing in PLOS Biology. The researchers involved in this study suggest this bias is bolstered by research funding mechanisms and social forces. The International Mouse Phenotyping Consortium (IMPC) aims to address this issue by creating a platform that characterizes all 20,000 protein-coding mouse genes, which can then give valuable information into homologous genes in the human genome.
Recent studies have reported that researchers actively study only about 2,000 human protein-coding genes, so the researchers set out to find why. They compiled 36 distinct resources describing various aspects of biomedical research and analyzed the large database for answers. The team found that well-meaning policy interventions to promote exploratory or innovative research actually result primarily in additional work on the most established research topics — those genes first characterized in the 1980s and 1990s, before completion of the Human Genome Project. The researchers also discovered that postdoctoral fellows and Ph.D. students who focus on poorly characterized genes have a 50 percent lower chance of becoming an independent researcher.
The researchers applied a systems approach to the data — which included chemical, physical, biological, historical and experimental data — to uncover underlying patterns. In addition to explaining why some genes are not studied, they also explain the extent to which an individual gene is studied. And they can do that for approximately 15,000 genes.
The Human Genome Project — the identification and mapping of all human genes, completed in 2003 — promised to expand the scope of scientific study beyond the small group of genes scientists had studied since the 1980s. But the Northwestern researchers found that 30 percent of all genes have never been the focus of a scientific study and less than 10 percent of genes are the subject of more than 90 percent of published papers.
“The bias to study the exact same human genes is very high,” said Amaral, the Erastus Otis Haven Professor of Chemical and Biological Engineering and a co-author of the study. “The entire system is fighting the very purpose of the agencies and scientific knowledge which is to broaden the set of things we study and understand. We need to make a concerted effort to incentivize the study of other genes important to human health.”
The International Mouse Phenotyping Consortium
This new research highlights the need for projects such as the IMPC, in which the aim is to characterize approximately all 20,000 or so protein coding genes. To achieve this, genes in the mouse genome are switched off, or ‘knocked out’, then standardised physiological tests undertaken across a range of biological systems. This data is then made freely available to the research community. As well as completing large scale comparative studies, the overall aim of the project is to create a platform for this data where researchers/clinicians can search for genes or diseases of interest to help them understand human health and disease. Data for over 6,000 genes is now available on the IMPC website and the project should therefore help address some of the main issues outlined above.
“The IMPC is leveling the playing field by freely providing robust phenotype data for poorly characterized genes. Nothing pleases me more than helping researchers overcome these barriers and discover new research areas none of us have dreamed of. This will be lasting legacy of the IMPC and is why our global partners continue to generate and phenotype mutant mice every day.” said Terry Meehan, a member of IMPC, and the Mouse Informatics Coordinator at the European Bioinformatics Institute.
Lluis Montoliu, researcher at the National Center for Biotechnology (CNB-CSIC) and member of the IMPC said “In the scientific community we all know of ‘famous’ genes and genes that are not so. Fashions also prevail in the scientific community and, indeed, there are many very relevant genes that, due to their difficulty and scarce literature, remain largely unknown. For example, huntingtin, whose gene causes Huntington’s deadly neurodegenerative disease. The IMPC aims to generate and phenotype mutant mice for each and every one of the 20,000 genes, whether or not they are famous, in order to correlate the data obtained with their homologous genes in the human genome.”
PLOS Biology research article: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2006643
More information on the IMPC: https://www.mousephenotypetest.org/what-is-the-impc/
Researchers have discovered a new way to activate the stem cells in the hair follicle to make hair grow. The research, led by scientists Heather Christofk and William Lowry, may lead to new drugs that could promote hair growth for people with baldness or alopecia, which is hair loss associated with such factors as hormonal imbalance, stress, aging or chemotherapy treatment.
The research was published in the journal Nature Cell Biology.
Hair follicle stem cells are long-lived cells in the hair follicle; they are present in the skin and produce hair throughout a person’s lifetime. They are “quiescent,” meaning they are normally inactive, but they quickly activate during a new hair cycle, which is when new hair growth occurs. The quiescence of hair follicle stem cells is regulated by many factors. In certain cases they fail to activate, which is what causes hair loss.
In this study, Christofk and Lowry, of Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at UCLA, found that hair follicle stem cell metabolism is different from other cells of the skin. Cellular metabolism involves the breakdown of the nutrients needed for cells to divide, make energy and respond to their environment. The process of metabolism uses enzymes that alter these nutrients to produce “metabolites.” As hair follicle stem cells consume the nutrient glucose — a form of sugar — from the bloodstream, they process the glucose to eventually produce a metabolite called pyruvate. The cells then can either send pyruvate to their mitochondria — the part of the cell that creates energy — or can convert pyruvate into another metabolite called lactate.
“Our observations about hair follicle stem cell metabolism prompted us to examine whether genetically diminishing the entry of pyruvate into the mitochondria would force hair follicle stem cells to make more lactate, and if that would activate the cells and grow hair more quickly,” said Christofk, an associate professor of biological chemistry and molecular and medical pharmacology.
The research team first blocked the production of lactate genetically in mice and showed that this prevented hair follicle stem cell activation. Conversely, in collaboration with the Rutter lab at University of Utah, they increased lactate production genetically in the mice and this accelerated hair follicle stem cell activation, increasing the hair cycle.
“Before this, no one knew that increasing or decreasing the lactate would have an effect on hair follicle stem cells,” said Lowry, a professor of molecular, cell and developmental biology. “Once we saw how altering lactate production in the mice influenced hair growth, it led us to look for potential drugs that could be applied to the skin and have the same effect.”
The team identified two drugs that, when applied to the skin of mice, influenced hair follicle stem cells in distinct ways to promote lactate production. The first drug, called RCGD423, activates a cellular signaling pathway called JAK-Stat, which transmits information from outside the cell to the nucleus of the cell. The research showed that JAK-Stat activation leads to the increased production of lactate and this in turn drives hair follicle stem cell activation and quicker hair growth. The other drug, called UK5099, blocks pyruvate from entering the mitochondria, which forces the production of lactate in the hair follicle stem cells and accelerates hair growth in mice.
“Through this study, we gained a lot of interesting insight into new ways to activate stem cells,” said Aimee Flores, a predoctoral trainee in Lowry’s lab and first author of the study. “The idea of using drugs to stimulate hair growth through hair follicle stem cells is very promising given how many millions of people, both men and women, deal with hair loss. I think we’ve only just begun to understand the critical role metabolism plays in hair growth and stem cells in general; I’m looking forward to the potential application of these new findings for hair loss and beyond.”
The experimental drugs described above were used in preclinical tests only and have not been tested in humans or approved by the Food and Drug Administration as safe and effective for use in humans.
Research article: Lactate dehydrogenase activity drives hair follicle stem cell activation
Humans and mice share approximately 98% of genes, and have similar physiology and anatomy. This is because we share a relatively recent common ancestor, around 80 million-years-ago. In contrast, the ancestor of all animals lived over 500 million-years-ago. As genomic data becomes available for more animal species a detailed family tree can be created, allowing novel insight into the genomes of long extinct species. In the guest post below Jordi Paps summarises recent research that attempts to reconstruct the genome of the ‘first animal’ by using the genomic data available on living animals.
The first animals emerged on Earth at least 541m years ago, according to the fossil record. What they looked like is the subject of an ongoing debate, but they’re traditionally thought to have been similar to sponges.
Like today’s animals, they were made up of many, many different cells doing different jobs, programmed by thousands of different genes. But where did all these genes come from? Was the emergence of animals a small step in evolution, or did it represent a big leap in the DNA that carries the instructions for life?
To answer these questions and more, my colleague and I have reconstructed the set of genetic instructions (a minimal genome) present in the last common ancestor of all animals. By comparing this ancestral animal genome to those of other ancient lifeforms, we’ve shown that the emergence of animals involved a lot of very novel changes in DNA. What’s more, some of these changes were so essential to the biology of animals that they are still found in most modern animals after more than 500m years of independent evolution. In fact, most of our own genes are descended from this “first animal”.
Previous research on lifeforms that are closely related to animals – single-celled organisms such as choanoflagellates, filastereans and ichthyosporeans – has shown they share many genes with their animal cousins. This means that these genes are older than animals themselves and date back to some common ancestor of all these creatures. So the recycling of old genes into new functions, a kind of genome tinkering, must have been an important force in the origin of animals.
But Professor Peter Holland and I wanted to find out which new genes emerged when animals evolved. We used sophisticated computer programs to compare 1.5m proteins (the molecules that genes contain the instructions for) across 62 living genomes, making a total of 2.25 trillion comparisons to find out which genes are shared between different organisms today.
We then created a computer program that could combine this information with the evolutionary relationships of the animals to reconstruct which genes were present in the last common ancestor of all animals. The results don’t represent the ancestor’s full genome, as many genes and other genetic information will no longer exist in today’s animals. But using evolutionary trees to infer what happened in the past in this way is one of the most powerful applications of evolutionary biology, as close as we can come to travelling back in time.
Our results suggest the genomes of the first animals were surprisingly similar to those of modern ones, containing the same proportions of biological functions. Around 55% of modern human genes descend from genes found in the last common ancestor of all animals, meaning the other 45% evolved later.
By applying the same techniques to the genomes of modern relatives of animals,
we also reconstructed the genome of even older ancestral organisms. We found that the first animal genome was in many ways very similar to the genomes of these unicellular ancestors.
But then we looked at the novel genes in the first animal genome that weren’t found in older lifeforms. We discovered the first animal had an exceptional number of novel genes, four times more than other ancestors. This means the evolution of animals was driven by a burst of new genes not seen in the evolution of their unicellular ancestors.
Finally, we looked at those novel genes from the first animal that are still found in most of the modern animals we studied. Natural selection should mean that animals keep genes with essential biological functions as the species evolve. We found 25 groups of such genes that had been kept in this way, five times more genes than in other, older, ancestors. Most of them have never been associated with the origin of animals before.
These novel genes that are still widely found today control essential functions that are specifically related to lifeforms with multiple cells. Three groups of these genes are involved in transmitting different nervous system signals. But our analyses show that these genes are also found in animals that do not have a nervous system, such as sponges. That means the genetic basis of the nervous system may have evolved before the nervous system itself did.
Our research shows that both new genes and the recycling of old genes were important in the evolution of animals. But these results raise even more questions. Were novel genes also important in the rise of other types of large multicellular lifeforms such as plants or fungi? What was behind the explosion of novel genes that drove the evolution of animals? Did it happen faster than in other groups or did animal ancestors take a long time to accumulate all the new genes? Answering those questions will require more and better genome data (or improved time-travelling capabilities).
A recent study in the journal Nature Medicine utilises IMPC-generated mouse lines as a basis for their discovery. A summary of this research article, and how it may help human patients with osteoporosis, is given in a guest post below. This investigation is a great example of how IMPC resources can be used by the research community and exemplifies how mouse phenomics may help in the development of treatments for human disease.
Guest post by Maureen Salamon
A molecule promoting blood vessel growth in bone can create an environment suitable for bone-building, representing a potential target for new drugs to treat osteoporosis and fractures, according to new research by Weill Cornell Medicine scientists.
The findings, published in Nature Medicine, show that a substance best known for spurring nerve growth, called SLIT3, both reversed the bone-weakening effects of osteoporosis and helped fractures heal when administered in mice. The multi-center research effort could fuel drug development efforts targeting the SLIT3 pathway in humans, enabling a new approach for blood vessel-directed therapy to treat bone loss, persistent fractures and fragile bones.
Existing drugs for osteoporosis work in one of two ways: Either they block the cells that destroy bone or they promote bone formation by cells called osteoblasts. “But only those promoting new bone formation will help you actually heal a bone fracture,” said co-senior study author Dr. Matthew Greenblatt, an assistant professor of pathology and laboratory medicine at Weill Cornell Medicine. “Our findings have potentially demonstrated a third category: drugs that target blood vessel formation within bone, prompting new bone to form.”
Osteoporosis, which causes bones to thin and become brittle, leads to nearly 9 million fractures worldwide each year, or one every three seconds, according to the International Osteoporosis Foundation. Women are disproportionately affected, and the risk increases with age. One in two women and one in five men will have an osteoporotic fracture during their lifetimes, and these fractures kill as many women each year as breast cancer.
“Osteoporosis and skeletal fractures due to osteoporosis are both common and deadly,” Greenblatt said.
To counteract that trend, Greenblatt has been investigating the cellular causes of osteoporosis in an effort to promote bone growth. Prior research using mice genetically engineered to lack an adaptor protein known as SHN3 showed that its absence conferred high bone mass. Building on that discovery, Greenblatt and his team decided to examine the resulting changes in bone blood vessels. “We used those mice as a means to find the signals coming from osteoblasts to control the specific type of blood vessels present in bone,” he said.
The researchers were surprised to find that osteoblasts secreted unchanged amounts of almost all known factors promoting blood vessel growth, but SLIT3 levels rose significantly. And when the mice were genetically altered to delete SLIT3, they exhibited low bone mass.
“We next asked if we could use SLIT3 to treat mice with skeletal disease, especially osteoporosis and fracture healing,” Dr. Greenblatt said. “When we gave the rodents SLIT3, it reversed their osteoporosis and made their fractures heal faster and stronger.
“To my knowledge, this is the first example that we can develop a drug to treat bone disease in mice not by targeting the bone-forming cells,” he said, “but instead by targeting special types of blood vessels that exist in bone.”
Further research is needed to determine the best way to deliver SLIT3 to the bone in humans. SLIT3-pathway drugs could also be used in combination with existing drugs to improve patient outcomes.
“Only a small fraction of patients who’ve had a hip fracture and really require medication to prevent additional fractures get the drugs they need. Many people aren’t aware of how debilitating and deadly these kinds of fractures are,” Greenblatt said. “Having a totally new category of bone drugs that work on different sets of cells could open up new opportunities for treatment.”
In addition to benefiting seniors with osteoporosis, Greenblatt hopes his research will also help patients with bone injuries that aren’t healing properly, such as those who’ve undergone orthopedic surgery or have fragile bones due to genetic diseases.
“Some of those people’s fractures don’t heal because they can’t grow the right type of blood vessels at the site of the fracture,” he said. “That’s what we think SLIT3 will do: help with that growth and promote healing.”
Research article: Targeting skeletal endothelium to ameliorate bone loss
Maureen Salamon is a freelance writer for Weill Cornell Medicine. This article was originally published in the Cornell Chronicle and is re-published with copyright permission.
We are excited to be attending the European Society of Human Genetics (ESHG) 2018 conference this weekend in Milan! Visit stand 280 to find out more about the IMPC and to pick up contact information and handouts. We will be tweeting relevant research and news during the conference so please follow us on Twitter for updates.
As well as exhibiting, Pilar Cacheiro, Damian Smedley & Violeta Munoz Fuentes will also be discussing the IMPC in a workshop, poster & talk:
The International Mouse Phenotyping Consortium (IMPC) has been predominantly interested in using mouse models to understand human health and disease. In a new study in the journal Conservation Genetics researchers have found another intriguing use of IMPC data.
By comparing genetic functional data from the IMPC with other non-human animals, it may be possible to identify genes relevant for the normal development in those species. For example, by comparing mouse genetic functional data with genomic data for selected species with specific diseases, improved breeding management could be implemented.
To test this potential application researchers at the European Bioinformatics Institute (EMBL-EBI) and Queen Mary University London (QMUL), alongside colleagues from the IMPC, compared genetic functional data from mice with genomic data from gorillas, showing how such analyses could aid in the identification of genes essential for healthy development.
As well as gorillas, the researchers highlighted other examples, including cheetahs, polar bears, wolves, pandas and cattle. This type of analysis could improve the current management approaches to breeding endangered species, by allowing researchers to identify the matches that are most likely to produce healthy offspring or select breeders to preserve genetic variation relevant for adaptation.
Heart disease is a common cause of death for gorillas in captivity and cheetahs suffer from impaired fertility both in captivity and in the wild. By identifying gorilla genes linked to heart disease or cheetah genes linked to infertility, researchers could help better understand the cause for the condition, which is the first step to envisage ways to prevent it. Similarly, this type of data could help identify genes linked to adaptation in certain mammals. For example, genes associated with fat metabolism can be a real asset for species like polar bears, which have diets rich in fats in the extreme environment of the Arctic.
“When the number of individuals of a species dramatically decreases, loss of genetic variation also takes place”, explains Violeta Muñoz-Fuentes, Biologist at EMBL-EBI. “This can result in many offspring not surviving, or exhibiting genetic defects linked to fertility or health problems.”
“Many zoos and wildlife conservation centres are seeing excellent results through their breeding programmes. Currently, many focus on minimising inbreeding. By adding a functional genetic dimension to the selective process, conservation geneticists can identify the crosses that would, for example, avoid a gene variant linked to disease in the offspring. It is nevertheless important to keep in mind that for a genetic rescue approach to be successful in the long term, the conditions that led to the decrease of individuals need to be removed; otherwise, the accumulation of deleterious alleles will likely take place again”.
Although this type of research is still in its early stages, gene functional knowledge is a powerful tool for maximising adaptive genetic diversity within a species and even for reducing genetic variants that negatively affect an individuals’ health and survival. With the accumulation of gene function annotation by the IMPC, as well as technical advancements in gene editing such as CRISPR/Cas9, the hope is that this method of comparing genome information between laboratory mice and endangered wildlife will help in future conservation projects.
The IMPC would like to encourage conservation geneticists, conservation centres and zoos to get in touch if they are interested in using IMPC data for conservation purposes.
Leading international protein researchers have mapped two large unexplored parts of the human genome. Their work paves the way for the development of new drugs. The study builds on extensive data analysis conducted using super computers – a technique called data mining – has examined huge amounts of literature within the health and medical sciences and other evidence sources in order to identify the most and least studied proteins for drug targets. The study is the first to provide a solid, comprehensive and useful picture of all the proteins that can be used to develop new drugs.
The researchers included 20,000 proteins in the study and are now able to conclude that 8,000 of these more or less have not been mapped and studied by researchers or pharmaceutical companies. This paves the way for new drug research with great untapped potential. The research was published in the journal Nature Reviews Drug Discovery.
‘We have used highly advanced computer analysis of data to shed light on the parts of the human genome that are rarely researched. We can see that they hold great potential, and we hope the analysis can motivate drug researchers to do some pioneer work. This may prove significant to future drug innovation’, says Professor Søren Brunak from the Novo Nordisk Foundation Center for Protein Research.
Many diseases are caused by dysfunctional proteins that have been damaged by genetic flaws. The vast majority of drugs try to prevent these proteins from being active and thus to reduce their impact on the disease in question.
It is therefore vital to drug development to be able to study and identify the proteins that are instrumental in diseases. Proteins with great potential are often referred to as drug targets and may after extensive clinical trials be approved for use as drugs.
This new study shows that 40 percent of all potential drug proteins have not been subjected to thorough and prioritised study. The researchers have therefore divided the 20,000 proteins into four categories and ranked their potential as future drugs.
According to the analysis, the mapping also paves the way for new so-called re-positioning opportunities, where already approved drugs can be tested on new factors. This means that proteins in drugs only approved for one therapy area now can be tested for treatment of other diseases.
The combination of categorisation and rankings works almost like a treasure map for drugs, and therefore the project has also received funding for stage two.
‘In stage two of the project we aim to improve our tools for studying the biological functions of drug targets based both on scientific texts and on large experiments”, says Professor Lars Juhl Jensen, who is responsible for the sequencing of millions of articles using advanced data mining techniques.
Since the 1990s researchers affiliated to The Human Genome Project have tried to map the human genome, and in 2014 the National Institutes of Health Common Fund took steps to mapping the genes in the human genome that code for proteins through the project Illuminating the Druggable Genome.
The researchers initially believed that more than 100,000 genes were able to code for proteins, but the mapping showed that there is only around 20,000. The drugs available today relate to less than 1,000 drug targets. According to Søren Brunak, the potential of drug design based on these proteins is almost exhausted, and exploring new territory is therefore important.
The objective of sequencing the human genome is typically to determine which genes are related to a given disease. Here the researchers look at specific gene patterns in families and entire population groups to determine what causes certain diseases.
The IMPC has been directly involved in this research, with production centres actively prioritising knockout mouse strains for druggable genes. Through this collaboration, a total of 568 new knockout strains have been produced. Of these strains, 80% have phenotype data available. This study discusses some of the applications of these strains, but also highlights that in the coming years with further production of relevant IMPC strains, along with phenotype data, further insight will be possible into drug target genes.
Terry Meehan, a member of IMPC and an author on this study, said: “This is an exciting example of NIH initiatives working together to provide new insights to benefit medicine. The IMPC prioritised making knockout strains for druggable genes that the IDG identified as being poorly characterised. By seeing what phenotypes result when a gene is turned off, we can help researchers predict the beneficial and harmful effects that might result from a drug that neutralises the product of the same gene.”
Most of this post is re-published under Creative Commons from the Faculty of Health and Medical Sciences, University of Copenhagen: https://www.futurity.org/human-genome-analysis-drug-discovery-1687832/
Brendan Doe talks about his work in using Cytoplasmic Microinjection to generate CRISPR mediated mutations.