Stuart’s developed a clever new approach to time series data (Aitken et al, 2015), fitting expression profiles over time to a series of archetypical models or ‘kinetic signatures’. Unlike the dominant forms of analysis (clustering, differential expression between time points) this allows us to detect profiles of interest even if the profile of interest is entirely unique or involves lowly expressed transcripts. That turns out to be particularly handy when studying ncRNA dynamics.
James’ interesting survey of where and when (and even how) duplicated regions diverge in terms of their chromatin structure appears in Genome Biology and Evolution (Prendergast et al, 2014). I realise nobody wants to hear scientists moaning about the peer review process (yet again). But jeez – this paper went through several journals over the course of ~18 months – and is more or less unchanged as a result. Someone needs to at least try to find an alternative for the stodgy, inefficient process we’ve ended up with. Maybe this is it?
The FANTOM5 Consortium publishes an atlas of transcriptional activity covering 975 human and 399 mouse samples, including primary cells, tissues and cancer cell lines (FANTOM Consortium, 2014). Better still, the data were generated using single-molecule sequencing, avoiding the biases introduced by other approaches. As ever it was great fun to be involved in this unique international collaboration. All data are freely available from the FANTOM5 site.
Emily Chambers’ study of higher order chromatin structure is published in PLOS Comp Biol (Chambers et al, 2013). For the first time this manuscript describes the regions of the mammalian genome that appear to have diverged at the level of their chromatin structure, rather than at the level of the DNA sequence. Intriguingly some of the regions involved contain genes involved in the development of the mammalian body plan in embryogenesis.
Our lab has been elected to this FP7 European Community-funded Network of Excellence. The goals of Epigenesys is to encourage collaboration and understanding between the fields of epigenetics and computational systems biology, and also to communicate the science to the wider public.
James’ mammoth study (Prendergast et al, 2012) of human chromatin variation is published; it involved remapping 1.3 billion sequencing reads. He shows that it is possible to find variable sites in the human genome (SNPs) where the different variants (alleles) present carry different chromatin structures. These sites seem to be surprisingly rare in embryonic stem cells, but there is evidence that they affect gene expression and are associated with human disease.
In a successful collaboration (Nimmo et al, 2012) with a clinical genetics group we provide the first evidence for characteristic patterns of DNA methylation in Crohn’s disease patients. Genes with altered methylation were disproportionately involved in immune system activation. Also across the genome methylation changes were highly enriched around loci implicated in GWAS, suggesting that alterations in methylation of key genes may contribute to disease.