Whether PRC2 binds to RNA has sequence specificity studies.

The international academic journal Scientific Reports recently published online a sequence-specific study of the interaction between PRC2 and long non-coding RNA (lncRNA) by the Research Group of the Chinese Academy of Sciences-Mapp Institute of Computational Biology, "The PRC2-binding long non-coding RNAs in human and mouse genomes with associated predictive sequence features".
the surface regulatory complex PRC2, composed of multi-comb (PcG) family proteins, is an important factor in controlling the development of animal tissue, but it is not clear how PRC2 is specific to the molecular mechanisms of chromatin-specific regions in higher animals.
with the discovery of the combination of NCRNA with PRC2 such as XIST and HOTIR, there is speculation that such lncRNA may determine the specificity of PRC2 chromatin recruitment (Margueron et al. Nature 2011).
, until now, whether PRC2 is sequence-specific in combination with RNA (Davidovich et al. Mol Cell 2015).
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Qi Zhen Research Group first developed a sequence composition analysis process based on markov chain thought, which depicts the composition of different nucleotide transfers in each sequence by calculating the frequency of transfer between nucleotides in each sequence, and then selects the transfer between nucleotides that are significantly or not preferred by a particular sequence as their sequence composition characteristics, and studies whether the distribution of sequence characteristics in feature space is non-ordinary by mapping all possible transfers to a complete fork tree.
By applying this process to hundreds of PRC2 binding lncRNAs known in the human genome, the research system analyzed the sequence characteristics of these lncRNAs and found that their preferred sequence characteristics tended to form a continuous preference path on the fork tree, and that the sequence features on these continuous paths tended to be preferred by both the human and mouse genomes for PRC2 binding lncRNA.
Was inspired by this, the study combined published RIP-seq and CLIP-seq data from two groups of mouse embryonic stem cells, defined a highly credible group of mice PRC2 combined with lncRNA, and found that these lncRNAs were able to better predict the sequence characteristics known in the human genome for PRC2 binding to lncRNA.
these studies show that PRC2 and lncRNA binding in higher animals have sequence specificity and high cross-species conservatism.
, the study also found that the distribution of PRC2's sequence characteristics in conjunction with lncRNA showed significant non-randomness in lncRNA by developing a local score model.
further studies have found that PRC2 and lncRNA on each lncRNA combine the smallest fragments of preferred sequence characteristics (defined as PRC2 preference fragments) with significantly higher evolutionary conservatism and RIP-seq signal strength relative to the rest of lncRNA (illustrated), indicating that the local richness of these sequence characteristics has clear functional significance.
The study was completed by Tu Shiqi, a doctoral student at the Institute of Computational Biology, under the guidance of a researcher, and was supported by funding from the Chinese Academy of Sciences and the Shanghai Science and Technology Commission, as well as the guidance and assistance of Professor Yuan Guoxuan of Harvard Medical School in the United States.
(Computing Institute) Figure: PRC2's distribution on lncRNA in combination with the sequence characteristics of lncRNA shows significant non-randomness, and the local richness of these sequence features has clear functional significance The PRC2-binding long non-code RNAs in human human and mouse with associated predictive sequence sequence features.