EMBL scientists unveil how 3D chromatin structure affects RNA splicing
Judith Zaugg and Mariana Ruiz-Velasco from EMBL’s Structural and Computational Biology Unit in Heidelberg have published a paper in Cell Systems. They show for the first time the functional impact of the 3D structure of chromatin – the tightly-packed structure that the long DNA thread adopts to fit into the cell’s nucleus – on the RNA-regulating splicing mechanism. Zaugg, EMBL group leader, and first-author Ruiz-Velasco tell us more about it.
What did you do?
When DNA of a gene is transcribed, the entire sequence is copied into RNA, which is then spliced. The noncoding regions are removed and the coding regions, called exons, form a contiguous RNA sequence that will code for proteins. Our paper shows how loops in the 3D structure of chromatin have an effect on RNA splicing. Until now, that was thought to be mainly regulated at the RNA level.
In our study, we found that differences in chromatin structure across individuals correlate with in- or exclusion of a specific exon. We discovered that CCCTC binding factor (CTCF) – a protein that can create chromatin loops between two distant sites in the genome – regulates which exons get included in the RNA by forming a loop. When CTCF does not bind to one of the sides, and thus no loop is formed, the resulting RNA is different. This is an additional mechanism in alternative splicing to the ones we already knew.
Why is it important?
There’s a lot of research surrounding chromatin structure because we don’t fully understand how its structure and function are related. Chromatin packing has an influence on what genes are transcribed by making specific locations accessible, now we know that it also influences how the gene is going to be transcribed. Discovering this novel mechanism that regulates RNA splicing is relevant basic knowledge and adds to the functional roles that chromatin structure plays in gene regulation – from development to disease processes. Furthermore, since the CTCF induced loops regulate the inclusion of exons that tend to be coding for proteins associated with cellular stress response – it might help in understanding how cells respond to stress.
Also, this study shows the potential of computational biology: the data we used was all publicly available and originally produced for a different purpose. By combining and integrating multiple datasets we predicted the CTCF-loop dependent splicing mechanism, which we later validated experimentally.
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