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Linking sequence to function of long noncoding RNAs with CRISPR.

Periodic Reporting for period 1 - CRISPR-Locate (Linking sequence to function of long noncoding RNAs with CRISPR.)

Período documentado: 2021-08-01 hasta 2023-07-31

After the Human Genome Project, scientists were amazed to find lots of RNA molecules that don't make proteins. In addition to the 19,000 genes that code for proteins, our genetic material contains at least 20,000 long noncoding RNA (lncRNA) genes. Some recent estimates even suggest there could be as many as 100,000 of these genes. Researchers are working hard to figure out what these lncRNA genes do, but they're discovering new ones faster than they can study them. Right now, we only know the functions of less than 1% of these lncRNAs. These findings have posed a big challenge: understanding the important roles of lncRNAs in our bodies. To do this, scientists need to answer a key question – how are the functions of lncRNAs determined by their chemical sequence? Scientists believe that, like proteins, lncRNAs are made up of different building blocks that give them specific shapes and functions. This project aimed to tackle this puzzle by creating a method that can identify different parts of lncRNA molecules and figure out what they do in the cell. For the first time, this allowed us to study many lncRNA components on a large scale, helping to unlock the secrets of how lncRNAs work.
We made significant progress in the study of lncRNAs by developing a new technique called CRISPR-Locate. This technique allows us ‘scan’ through hundreds of lncRNAs and identify the signal that determine where the lncRNAs should be located in the cell. What's exciting is that this technique has a wide range of applications beyond just lncRNA research – it can be used to study different types of RNA and their functional parts .
Additionally, we improved our CRISPR technology to a very high level of precision. We were able to examine lncRNA function on the level of exons. We tested over 150 lncRNAs that are known to be involved in cancer and found specific exons that are linked to the growth of cancer cells. To understand these exons better, we compared them to a database of known features of DNA and RNA. This helped us identify the specific functional parts encoded within these exons. Another exciting outcome of our work is that we created a comprehensive map of functional domains in lncRNAs. This map provides a starting point for future research into how cells function and how lncRNAs might be connected to diseases. It could even help researchers predict which parts of lncRNAs are functional using computational tools.
We shared our project results with experts in several ways. We presented our work at three major international conferences, including giving talks at the 28th Annual Meeting of the RNA Society in Singapore and the EMBO Workshop "Non-coding RNA medicine" in Poznan, Poland. We also participated in seminars to share our findings with local scientists in Ireland. Currently, we are preparing a detailed article about our work to publish in a respected scientific journal.
The Researcher's future career got a big boost from the fellowship. They learned new research skills while working in a lab. The lab taught them how to use CRISPR and some basics about working with data in computers. These new skills added to what the Researcher already knew and made them a more well-rounded scientist. During the fellowship, the Researcher also got better at leading and managing others. They got to help plan and oversee projects done by students. This experience helped them learn how to guide and mentor others.
One of the things the Researcher did during the fellowship was creating technique called CRISPR Locate. This is a tool that can help other scientists study specific parts of our genetic material in high throughput at high resolution. It could be useful for understanding more about certain types of genes and how they might relate to diseases like cancer. The Researcher's project found some important domains in long non coding RNA that might be linked to cancer. This discovery could help scientists come up with new treatments for cancer in the future.
Schematic representation of lncRNA modularity.