Modeling the breakome

jim

Tracy’s work building models of DNA double strand break susceptibility finally emerges from review this week in Genome Biology. She shows that it is possible to make remarkably accurate models, predicting the frequency of breakage in a given region of the genome, using a variety of underlying chromatin features. These predicted frequencies from these models can then be compared (above) to the rates of breakage seen in human tumour data, and identify regions that may be important to tumourigenesis. This work bridges the fields of genome instability, chromatin structure and cancer genomics – which is pretty cool, until you attempt to find suitably eclectic reviewers! It’s also the first manuscript to come out of our ongoing collaboration with our friends in the Crosetto group at the Karolinska.

Anchors in the storm

Chromatin loop anchors seem to be a basic unit of the physical organisation of the human genome, providing stable architectural sites within the nucleus, and influencing gene expression. Vera’s work exploring the strange mutational landscape at loop anchors shows that these sites are also unusually fragile: showing high rates of DNA double strand breaks in vitro and elevated rates of breakage in a variety of tumours. Unexpectedly a substantial fraction of loop anchors also coincide precisely with human recombination hotspots (HS_LAPs below), establishing these sites as foci for evolutionary change in mammalian evolution as well as during tumourigenesis.

jim

Average human recombination rates within 500 kb of recombination hotspots (HSs), the subset of LAPs overlapping HSs (HS_LAPs) and all LAPs. Recombination rates were derived from the worldwide whole genome sequencing data of the 1000 Genomes Project.

Lab winter retreat

After a busy year, and a successful QQR for the HGU, we retreated to a chilly North Berwick to do science, beer and roaring fires.jim

 

The blind watch-breaker: regulatory evolution in cancers

We still know relatively little about the evolution of gene regulation in cancer. Vera’s study (Kaiser et al, 2016, PLOS Genet) is one of the biggest so far (~1500 tumour whole genomes) and shows that there are remarkably high mutation rates and rapid evolution at most (putatively) functional regulatory sites, and she sees this across many cancer types. Particularly striking contrasts are seen between functional (upper graph) and control (lower graph) CTCF binding sites. However these patterns seem to be adequately explained simply by ‘blind’ mutational bias (ie neutral evolution), rather than active selection for particular alterations to regulation.

Chromatin domain trees

Collaborative work with the groups of Ana Pombo, Josee Dostie and Mario Nicodemi finally sees the light of day (Fraser et al, 2015). Using matched chromatin conformation (Hi-C) and expression (CAGE) data across neural differentiation we were able to relate the dynamics of gene expression to changes in chromatin domain organisation. The results suggest that previously known (TAD) domains on the level of ~1Mb congregate within larger multi-megabase (meta-TAD) structures, to produce a hierarchical tree of interactions up to the level of entire chromosomes. Alterations in the arrangement of branches on these trees over time influence gene expression changes.

A new approach to time series data

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.