To date, developments in DNA sequencing have provided high-quality and high-confidence genetic and genomic data. However, more information is needed to characterize biological systems beyond DNA information. Researchers are currently using RNA-Seq which is a deep-sequencing technique to profile the transcriptome. A transcriptome is a set of all RNA molecules that includes mRNA, rRNA, tRNA as well as other non-coding RNA that is produced in one or a population of cells. The RNA-Seq method leads to accurate measurements of transcript levels and their isoforms. This has led to characterization and survey of transcriptomes of difference cell types under certain conditions.
Chuan He, Ph.D., professor of chemistry at the University of Chicago, and colleages are using RNA-Seq (m6A-Seq or MeRIP-Seq) to elucidate methylation changes on RNA transcripts. RNA methylation has been known for a long time, however, little is known about the importance of RNA methylation in shaping gene expression.
Researchers in Dr. He’s group have demonstrated that RNA methylation is reversible just as is DNA and histone methylation. They have found that fat mass and obesity-associated protein (FTO) which is involved with human obesity and energy homeostasis, is a demethylase enzyme of RNA N6-methyladenosine. They identified a second RNA demethylase (ALKBH5) that affects mRNA export and metabolism. Even though both of these enzymes demethylate N6-methyladenosine RNA residues, they are involved with separate pathways and demonstrate different tissue expression patterns. According to Dr. He, this is an intriguing find in that RNA modifications can shape and, in some cases, dominate gene regulation.
Dr. Meng, Ph.D., associate researcher and bioinformatics core facility supervisor at MIT, and colleagues have developed FRIP-Seq (fragmented RNA immunoprecipitation sequencing). This novel tool combines ChIP-seq with RNA-Seq which enables researchers to study the RNA epigenome with greater resolution and on the genome-wide scale. This became necessary because the software and algorithms that were developed for DNA methylation analysis were not informative for RNA methylation.
According to Yufei Huang, Ph.D., professor of electrical and computer engineering at the University of Texas at San Antonio and senior author of the study describing FRIP-Seq, “This motivated us to develop this new algorithm that will help us, in the long run, to analyze the function of RNA methylation”. Huang and colleagues are currently applying this new technology to study epigenetic changes in mRNA from cancer cell lines.
A new MATLAB-based package known as exomePeak which is based on FRIP-Seq is now available for characterizing transcriptome-wide post-transcriptional RNA modifications and is free of charge. A new, more powerful, version will be available in a few months.