In this project three paediatric neurology departments from different parts of Turkey (Izmir, Diyrbakir, Malatya) will work together with the state-of-the-art genome centre in Izmir and a leading translational research centre in Newcastle upon Tyne (UK) in a cutting-edge new genome project. The research will address an important health-related issue for the Turkish population: the burden of neurogenetic disorders in children from consanguineous marriages. One in four marriages in Turkey is between blood relations (consanguineous). Relatives share parts of their DNA because of their common ancestry, and in these shared regions they also share some of the same genetic faults (mutations). The risk that a child inherits the same fault from both mother and father is therefore significantly higher in consanguineous families as compared to non-consanguineous families, increasing the likelihood of recessive disorders (in which both parents have to pass on a fault for the child to get the disease). More genes are active in the brain and nervous system than in any other part of the body. Recessive defects in these genes often lead to severe childhood disorders causing early death or severe disability including seizures, muscle weakness, breathing problems and severe learning difficulties. Thousands of children affected by neurogenetic conditions are born every year in Turkey in consanguineous families. A genetic diagnosis that would allow families to avoid having further affected children and in some cases allow effective treatment to be prescribed is rarely achieved because the underlying causes are difficult to pinpoint and the tests required have until now been expensive and time-consuming. Rather than looking at genes one by one, it has now become possible to read the entire genetic code of a child (the whole genome) in a single test and identify faulty genes by comparing this information with the general population and healthy relatives, in particular the parents. This is especially effective in consanguineous families, as the affected child is expected to have inherited an identical fault from both father and mother. Information obtained from consanguineous families has already been helpful in the identification of disease-causing genetic faults and might also make it possible to find other genes that make the primary disease more or less severe. In this project, expert paediatric neurologists in Turkey will carry out detailed clinical investigations of around 250 children with severe childhood disorders of the brain, nervous system or muscle and obtain blood and tiny skin samples from these children as well as their unaffected parents and affected or unaffected siblings. DNA will be extracted from the blood and will undergo genome sequencing followed by in-depth computer analysis. Potential faults in relevant genes will be identified and will be further explored to establish their function and see whether they are indeed the cause of the child's condition. This scientific work will be carried out by scientists in Newcastle and Izmir and involves the use of stem cell technology to transform skin cells into nerve cells, as well as genetic manipulation to change the genes of zebrafish embryos to recreate the problem seen in the child and help understand the function of the gene in the nervous system. Exploring these aspects in fish allows research towards the development of targeted and effective treatments for these diseases in humans. In addition to the expected discovery of at least 20 new disease-causing genes, we will also generate and share valuable data for future research, and will train the clinical and scientific workforce in Turkey in these new techniques. The information obtained will also contribute to future Turkish genome projects, and help understand the impact of consanguinity on severe childhood disorders in immigrant populations in other countries and other populations with high consanguinity rates.

The complete genetic sequences, medical records, and extensive health data of over 1 million people will become available for researchers this year. Major progress has recently been made on understanding the regulatory sequences in the human genome that act as switches, turning genes on and off in cells. There are only a few examples of variants in these DNA switches causing disease. We have identified variants of these switches causing very rare disease. We have identified variants of a short sequence that mean children are born without a pancreas. We showed that this short sequence is a master switch that turns on the key gene leading to pancreas development. We have also identified very rare variants in another switch that leads to children producing too much insulin and having dangerously low glucose levels. In this case it is because the switch is inappropriately turned on and a protein is produced in the pancreas that shouldn't be. In this project we will use the >1 million individuals with whole genome sequencing data to identify the switches that are important for common type 2 diabetes. As preliminary data and proof of principle we have already analysed height in 150,000 UK Biobank participants. We identified 31 previously unknown associations. One example is variants of a switch that turns on a gene called HMGA1. People with these switch variants are, on average, 5cm taller. This is particularly interesting because changing the protein sequence of HMGA1 does not affect height. We have confirmed these associations in 200,000 people from the All of Us and TOPMed cohorts. We have also performed preliminary analyses for diabetes. We have identified an association with a rare variant near HNF1A that occurs in a long non-coding RNA, a specific type of switch. We have recently demonstrated this long non-coding RNA is important for turning on HNF1A. It is extremely challenging computationally to analyse data on 1,000,000 complete whole genomes. Interpretation is a substantial challenge. This project will build on our initial work by refining our WGS analysis pipeline to make it efficient, cost-effective and publically available. This project is timely because UK Biobank will release whole genome sequence data on 500,000 people by the end of this year. We will use this data to perform single variant and group testing of regulatory switches. The analyses will be performed in different ancestry groups as well as a combined analysis. We will confirm our findings using the US cohorts All of Us and TOPMed which will have >500,000 individuals of diverse ancestries available for analysis. We will test the identified regions in our rare familial diabetes cohort and in the 100,000 genomes project. These are a collection of people where it is expected that there is a single genetic cause of their diabetes. This is important because we have an excellent track record of translating genetic diagnosis into treatment change. We will also perform functional follow-up of a subset of switches to provide new insights into pancreas development and function. This project will provide a substantial advance in our understanding of the role of non-coding variants in human disease. It will allow us to develop efficient and cost-effective approaches analysing whole genome sequence data. We will provide new insights into the regulation of pancreas development and function. It may also dramatically improve the quality of life for some patients with rare forms of diabetes. Our project is important if we are to make major advances in understanding disease mechanisms using whole genome sequencing.

In this project three paediatric neurology departments from different parts of Turkey (Izmir, Diyrbakir, Malatya) will work together with the state-of-the-art genome centre in Izmir and a leading translational research centre in Newcastle upon Tyne (UK) in a cutting-edge new genome project. The research will address an important health-related issue for the Turkish population: the burden of neurogenetic disorders in children from consanguineous marriages. One in four marriages in Turkey is between blood relations (consanguineous). Relatives share parts of their DNA because of their common ancestry, and in these shared regions they also share some of the same genetic faults (mutations). The risk that a child inherits the same fault from both mother and father is therefore significantly higher in consanguineous families as compared to non-consanguineous families, increasing the likelihood of recessive disorders (in which both parents have to pass on a fault for the child to get the disease). More genes are active in the brain and nervous system than in any other part of the body. Recessive defects in these genes often lead to severe childhood disorders causing early death or severe disability including seizures, muscle weakness, breathing problems and severe learning difficulties. Thousands of children affected by neurogenetic conditions are born every year in Turkey in consanguineous families. A genetic diagnosis that would allow families to avoid having further affected children and in some cases allow effective treatment to be prescribed is rarely achieved because the underlying causes are difficult to pinpoint and the tests required have until now been expensive and time-consuming. Rather than looking at genes one by one, it has now become possible to read the entire genetic code of a child (the whole genome) in a single test and identify faulty genes by comparing this information with the general population and healthy relatives, in particular the parents. This is especially effective in consanguineous families, as the affected child is expected to have inherited an identical fault from both father and mother. Information obtained from consanguineous families has already been helpful in the identification of disease-causing genetic faults and might also make it possible to find other genes that make the primary disease more or less severe. In this project, expert paediatric neurologists in Turkey will carry out detailed clinical investigations of around 250 children with severe childhood disorders of the brain, nervous system or muscle and obtain blood and tiny skin samples from these children as well as their unaffected parents and affected or unaffected siblings. DNA will be extracted from the blood and will undergo genome sequencing followed by in-depth computer analysis. Potential faults in relevant genes will be identified and will be further explored to establish their function and see whether they are indeed the cause of the child's condition. This scientific work will be carried out by scientists in Newcastle and Izmir and involves the use of stem cell technology to transform skin cells into nerve cells, as well as genetic manipulation to change the genes of zebrafish embryos to recreate the problem seen in the child and help understand the function of the gene in the nervous system. Exploring these aspects in fish allows research towards the development of targeted and effective treatments for these diseases in humans. In addition to the expected discovery of at least 20 new disease-causing genes, we will also generate and share valuable data for future research, and will train the clinical and scientific workforce in Turkey in these new techniques. The information obtained will also contribute to future Turkish genome projects, and help understand the impact of consanguinity on severe childhood disorders in immigrant populations in other countries and other populations with high consanguinity rates.

Within the BBSRC remit "understanding the rules of life", advancements in high-throughput time-lapse imaging has led to a proliferation of large datasets reporting temporal changes in cell behaviours in mechanistic functional studies, target validation, and phenotypic screens. These large and complex datasets can answer fundamental questions in biology but require more advanced tools for analysis. As part of a BBSRC-funded NPIF PhD studentship in AI, we developed CellPhe, a software package that enables phenotyping of cells in time-lapse microscopy datasets. Whilst some other software systems allow visualisation of the time series for a limited number of size and shape metrics, CellPhe is unique in that the time series for over 70 features, including movement, texture and density, are calculated for each tracked cell. Quantitative attributes are extracted from each of these time series and used in machine learning algorithms to classify cell subpopulations, thereby filling a fundamental gap in the bioimaging field. In this project, we aim to significantly enhance CellPhe's capability whilst making the software more widely accessible to the bioimaging community. To harness CellPhe's capability for more complex datasets of heterogeneous cell populations, we will employ a novel analytical approach where we consider "tracklets" of imaging data rather than the complete time series. These short segments of the time series will allow interesting short-term behaviour to be identified that would be missed by characterising the time series in full. This approach will be used to identify key cellular processes that may induce phenotypic shifts in response to treatment, e.g. timing of cell division, number and type of transient cell-cell interactions, migration, local density, etc. A common limitation with time-lapse imaging data is the inability to accurately segment and track individual cells across multiple frames, particularly in more confluent populations. To address this issue when it arises in specific datasets, we will explore the alternate utility of analysing a population of cells across a whole field of view without segmentation, using machine learning to separate behaviours based on whole image metrics. Furthermore, to demonstrate utility for discrimination of responding/non-responding populations following exposure to specific interventions (e.g. during drug treatment or CRISPR screening), we will also run the data in reverse to determine the features that provide early indication of particular cell behaviours. This approach will aid classification models for the prediction of cell fate, e.g. early detection of differentiation, or drug response, and could allow analysis of phenotypic imaging data to be combined with additional downstream assays, e.g. spatial transcriptomics, to relate imaging data to function. We will achieve our goal of making CellPhe more accessible by integrating it with the widely used state of the art open-source image analysis package, CellProfiler Analyst. Its companion program CellProfiler, led by our international partner, is recognised as the leading solution for image segmentation and cell tracking. The collaboration will allow segmentation and tracking to be integrated with automated analysis of the tracked cells. Further collaborations with two large pharmaceutical companies will provide access to industrially relevant high throughput imaging datasets for testing these new analytical capabilities. Our proposal thus addresses the BBSRC theme "AI to transform bioscience research and discovery", opening up a significant new opportunity for analysis of high dimensional time series datasets applicable to cellular bioimaging and beyond.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.