Barcelona, 6 February 2023.- Researchers at the Centro Nacional de Análisis Genómico (CNAG-CRG) have recently published a study on methylation patterns using nanopore reads in the journal Bioinformatics Advances. The team has developed the cvlr tool that allows genome wide screening to identify genomic regions that are being differentially regulated.


“If we regard the genome as a book with instructions for the cell, epigenetic marks - such as DNA methylation - can be thought of as annotations to the text that alter how the text is interpreted.  While all of the cells in the body (excluding the germ cells) have the same genome - the same instruction book - the epigenetic annotations differ between cell types which results in different blocks of genes being activated,” says Simon Heath, corresponding author of the study and leader of the Bioinformatics Development and Statistical Genomics Team of the CNAG-CRG.


By studying the epigenetic annotations, researchers can identify different cell types, and can also detect abnormal epigenetic patterns which can occur in certain diseases (in particular cancer). The cvlr tool allows researchers to look at the pattern of DNA methylation on single molecules, and to see if these patterns form clusters at certain genomic locations.  The presence of such clusters can indicate that the sample contains mixtures of cells that have different epigenetic annotations on their genome.  This can provide evidence that the sample contains different cell types or, possibly, diseased or cancerous cells.


“The patterns that stand out tell us that either we have (a) different types of cells in our sample (the more common situation) or (b) that the two alleles within each cell are not being regulated in the same way (for example in imprinting, which affects a small number of genes).  In either case the patterns give us information about which genes are potentially differentially regulated between the different groups as well as the frequencies of the groups in the sample,” says Emanuele Raineri, first author of the study and Staff Scientist at the Bioinformatics Development and Statistical Genomics Team of the CNAG-CRG.


The cvlr tool can be used to distinguish between situations a and b above and it could help to identify novel regulatory regions as well as potentially helping in uncovering the differences between samples from healthy and diseased individuals.


Work of reference

cvlr: finding heterogeneously methylated genomic regions using ONT reads