Defining Spatial Genomics
The spatial organization of genes in our genomes is significant for many reasons, including the fact that some traits are dominant over others and can affect life outcomes, such as health and lifespan, depending on where they are located on the genome. For example, diabetes is caused by a condition in which the pancreas produces insufficient insulin due to mutations in a single gene that are present in only some people. Because the mutation is present in only a small subset of the population, it is not passed on to the next generation, and thus typically is not diagnosed until late in life. However, if a person has both the mutated gene and a second gene with a protective effect, their risk of diabetes is greatly reduced. This is an example of how a trait is influenced by both the location of a gene as well as other genes located nearby.
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Another example is Huntington’s disease. In this condition, abnormal proteins are produced that can cause nerve cells in the brain to die. While the majority of people with this mutation will die from a completely unrelated neurological disease at a young age, in some individuals, their offspring are at a significantly increased risk of developing the disease. This is because the mutation occurs in a gene that is dominant and is therefore only present in some people but is still present in nearly all of those people.
How Does Spatial Genomics Work?
Sciencing Video Research is based on AIS-based imaging of human DNA. This imaging looks at the spatial organization of DNA by visualizing the spots on the gel or spot-illuminated microarray where DNA molecules bind to each other. Researchers can also analyze these images to glimpse at the physical arrangement of genes, such as their relative positions on the chromosome. Spatial genomics also looks at how DNA folds up or unfolds, and at how the centromere (the location on the chromosome where genes are concentrated) is arranged.
Researchers can also choose to analyze the spatial organization of DNA in its functional capacity. They can measure how DNA binds to proteins, how much of a protein is bound to DNA, how many times the DNA is read, and what percentage of the gene is read. These types of analyses can be used to understand how different genes are related to each other and to predict how a specific set of genes affects a particular outcome.
Why is Spatial Genomics Important?
The spatial organization of our genomes impacts how genes are expressed, resulting in different traits and diseases being passed from one generation to the next. The relationship between genes is one of the most important aspects of biology and is also one of the most contentious topics in scientific research. The spatial genomics approach enables researchers to investigate this relationship in a new way. By designing experiments that cause genes to be altered in specific locations or by measuring how those genes are affected, researchers can learn how genes are related to each other and how one gene contributes to another.
Spatial genomics has the potential to answer questions that have not been answered before. For example, researchers have been interested in understanding why certain traits are dominant over others for some time now but have been stymied by the fact that researchers do not know exactly what makes some genes dominant over others. Using spatial genomics, researchers can identify the specific locations where different traits are dominant and begin to answer why that is the case.
What Are the Most Common Types of Spatial Genomic Analyses?
DNA is the genetic material that cells use to make proteins, but it also looks at the spatial organization of those proteins. Proteomics, while not strictly a spatial genomics technique, is a form of proteomics that looks at the spatial organization of proteins in cells.
Spatial genomics has many potential uses, but the most common types of analyses focus on measuring the spatial organization of DNA, the spatial organization of proteins, and the spatial organization of the centromere. Researchers can look at how much DNA is present at specific locations on the genome, how much DNA is present at any given location, and how the DNA is arranged. This information can help researchers understand how proteins are related to each other and how the centromere is related to other parts of the DNA.
How to Conduct a Spatial Genomic Analysis
The spatial genomics technique used in a study depends on what type of analysis researchers are interested in. DNA spatial genomics is most commonly used to look at how genes are organized in a genome, but it can be used to visualize the spatial organization of proteins or the centromere, as well.
DNA spatial genomics looks at the spatial organization of the genome by visualizing the spots on the gel or spot-illuminated microarray where DNA molecules bind to each other. Researchers can also analyze these images to glimpse at the physical arrangement of genes, such as their relative positions on the chromosome.
Two common types of DNA spatial genomics are the high-throughput sequencing (HTS) approach and the single-molecule (sm) approach.
HTS uses a method called shotgun sequencing to sequence DNA fragments at very high speeds. The short sequences obtained, as well as the locations on the gel where DNA molecules are found, are recorded and visualized in the spatial genomics workflow.
The sm approach uses single DNA molecules that are tagged with fluorescent markers and then combined, in a process called DNA interferometry, with an array of photodetector molecules. The resulting spatial patterns are then analyzed in the spatial genomics workflow.
Where to Go From Here
The spatial genomics approach can be used to visualize and measure the spatial organization of many different aspects of the genome, but it is most commonly used to look at how genes are organized in a genome.
Understanding how genes are organized in a genome can help researchers understand how genes contribute to health and disease, and it can also help researchers find new genes and new mutations that are likely to be associated with certain diseases. The spatial genomics technique can also be used to visualize the spatial organization of proteins and centromere, which can be helpful in their own right, but its main purpose is to understand how genes are organized in a genome.
