COLD SPRING HARBOR, NY (GenomeWeb) – Researchers have devised a new approach to map genome-wide interactions between RNA and chromatin.
The FANTOM5 consortium reported a year ago in Nature on an atlas it developed of nearly 30,000 human long non-coding RNAs, and in its analysis, it found that most of those lncRNAs — about 69 percent of them — could potentially be functional. But, as Riken Center for Life Science Technologies' Piero Carninci, who was involved in that consortium, noted in his talk at the Biology of Genomes meeting here, researchers don't know the function of many of those lncRNAs.
"For many of them, we need more screening to understand what they do," Carninci said.
To address that, he and his colleagues developed a tool called RNA and DNA Interacting Complexes Ligated and sequenced, or RADICL-seq, to try to map, as broadly as possible, interactions between RNA and chromatin in the nucleus in a scalable way.
"The idea is [we] should have a method to map all those RNAs — where are they and which RNA goes with what — and perhaps see if we learn anything unexpected," Carninci added.
RADICL-seq relies on proximity ligation. It works by crosslinking chromatin and any RNA that may be bound to it before then digesting the samples with DNAse and then RNAse H to cleave any hybrid or nascent RNA. After later reversing the crosslink, the sample is then sequenced using Illumina's HiSeq platform. This, he said, is then replicated many times.
As he and his colleagues noted in their abstract, the approach identified genomic regions targeted by coding and non-coding RNAs. Additionally, they reported they could confirm RNA-chromatin interactions detected by RADICL-seq, pinpointing the genome occupancy of 14,000 transcripts — including 1,000 lncRNAs.
When the researchers compared their method to an RNA Affinity Purification (RAP) approach for mapping RNA interactions with chromatin, Carninci said RADICL-seq recapitulated 68 percent of the genes found through that RAP approach.
He likewise noted that their results were in good agreement with those generated using Hi-C-seq, which also examines chromatin interactions using a chromosome conformation capture-based approach.
Additionally, Carninci noted that overlaying RADICL-seq and Hi-C-seq data reveals the influences of chromatin 3D structure on RNA-DNA contacts.
Similarly, overlaying RADICL-seq data with ChIA-PET (chromatin interaction analysis with paired-end tag sequencing), a method to study long-range chromatin interactions, exposed the presence of RNA-DNA interactions that are independent of transcription, he said.
According to Carninci, RADICL-seq can begin to tease out patterns of RNA-chromatin interactions. Broadly, he noted that some RNAs have interactions all along chromosomes. But others, he said, stay local and have local interactions.
But, he and his colleagues noted in their abstract that within mouse embryonic stem cells, a RADICL-seq-based analysis noted different chromatin interaction patterns for mRNAs and lncRNAs.
Surprisingly to him, Carninci said, he and his colleagues also noticed that the RNAs in their RNA-DNA pairs tended to arise from genic regions, especially intronic regions, while the DNA half of the pairs arose roughly equally from genic and intergenic regions.
In addition, about a quarter of these RNA-DNA pairs included RNAs that interact with repeat elements. Repeat elements, he noted, are spread across chromosomes, and he added that different repeat elements were enriched for interacting over different distances, with some stretching over long ranges while others acted more locally. Some repeat element types appeared to be enriched for working at different interaction distances. Carninci added that there is a logic there that still needs to be teased out.
Overall, RADICL-seq, Carninci said, enables them to identify transcripts and interactions in an unbiased way.