The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1

Abstract. Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño–Southern Oscillation

Seasonal to interannual Arctic sea-ice predictability in current GCMs

We establish the first inter-model comparison of seasonal to interannual predictability of present-day Arctic climate by performing coordinated sets of idealized ensemble predictions with four state-of-the-art global climate models. For Arctic sea-ice extent and volume, there is potential predictive skill for lead times of up to three years, and potential prediction errors have similar growth rates and magnitudes across the models. Spatial patterns of potential prediction errors differ substantially between the models, but some features are robust. Sea-ice concentration errors are largest in the marginal ice zone, and in winter they are almost zero away from the ice edge. Sea-ice thickness errors are amplified along the coasts of the Arctic Ocean, an effect that is dominated by sea-ice advection. These results give an upper bound on the ability of current global climate models to predict important aspects of Arctic climate

The MRN complex is transcriptionally regulated by MYCN during neural cell proliferation to control replication stress

The MRE11/RAD50/NBS1 (MRN) complex is a major sensor of DNA double strand breaks, whose role in controlling faithful DNA replication and preventing replication stress is also emerging. Inactivation of the MRN complex invariably leads to developmental and/or degenerative neuronal defects, the pathogenesis of which still remains poorly understood. In particular, NBS1 gene mutations are associated with microcephaly and strongly impaired cerebellar development, both in humans and in the mouse model. These phenotypes strikingly overlap those induced by inactivation of MYCN, an essential promoter of the expansion of neuronal stem and progenitor cells, suggesting that MYCN and the MRN complex might be connected on a unique pathway essential for the safe expansion of neuronal cells. Here, we show that MYCN transcriptionally controls the expression of each component of the MRN complex. By genetic and pharmacological inhibition of the MRN complex in a MYCN overexpression model and in the more physiological context of the Hedgehog-dependent expansion of primary cerebellar granule progenitor cells, we also show that the MRN complex is required for MYCN-dependent proliferation. Indeed, its inhibition resulted in DNA damage, activation of a DNA damage response, and cell death in a MYCN- and replication-dependent manner. Our data indicate the MRN complex is essential to restrain MYCN-induced replication stress during neural cell proliferation and support the hypothesis that replication-born DNA damage is responsible for the neuronal defects associated with MRN dysfunctions.Cell Death and Differentiation advance online publication, 12 June 2015; doi:10.1038/cdd.2015.81

Oesophageal adenocarcinoma is associated with a deregulation in the MYC/MAX/MAD network

Oesophageal adenocarcinoma, which arises from an acquired columnar lesion, Barrett's metaplasia, is rising in incidence more rapidly than any other cancer in the Western world. Elevated expression of c-MYC has been demonstrated in oesophageal adenocarcinoma; however, the expression of other members of the MYC/MAX/MAD network has not been addressed. The aims of this work were to characterise the expression of c-MYC, MAX and the MAD family in adenocarcinoma development and assess the effects of overexpression on cellular behaviour. mRNA expression in samples of Barrett's metaplasia and oesophageal adenocarcinoma were examined by qRT–PCR. Semi-quantitative immunohistochemistry and western blotting were used to examine cellular localisation and protein levels. Cellular proliferation and mRNA expression were determined in SEG1 cells overexpressing c-MYCER or MAD1 using a bromodeoxyuridine assay and qRT–PCR, respectively. Consistent with previous work expression of c-MYC was deregulated in oesophageal adenocarcinoma. Paradoxically, increased expression of putative c-MYC antagonists MAD1 and MXI1 was observed in tumour specimens. Overexpression of c-MYC and MAD proteins in SEG1 cells resulted in differential expression of MYC/MAX/MAD network members and reciprocal changes in proliferation. In conclusion, the expression patterns of c-MYC, MAX and the MAD family were shown to be deregulated in the oesophageal cancer model

Crystal Structure of the Minimalist Max-E47 Protein Chimera

Max-E47 is a protein chimera generated from the fusion of the DNA-binding basic region of Max and the dimerization region of E47, both members of the basic region/helix-loop-helix (bHLH) superfamily of transcription factors. Like native Max, Max-E47 binds with high affinity and specificity to the E-box site, 5′-CACGTG, both in vivo and in vitro. We have determined the crystal structure of Max-E47 at 1.7 Å resolution, and found that it associates to form a well-structured dimer even in the absence of its cognate DNA. Analytical ultracentrifugation confirms that Max-E47 is dimeric even at low micromolar concentrations, indicating that the Max-E47 dimer is stable in the absence of DNA. Circular dichroism analysis demonstrates that both non-specific DNA and the E-box site induce similar levels of helical secondary structure in Max-E47. These results suggest that Max-E47 may bind to the E-box following the two-step mechanism proposed for other bHLH proteins. In this mechanism, a rapid step where protein binds to DNA without sequence specificity is followed by a slow step where specific protein:DNA interactions are fine-tuned, leading to sequence-specific recognition. Collectively, these results show that the designed Max-E47 protein chimera behaves both structurally and functionally like its native counterparts

The opposing transcriptional functions of Sin3a and c-Myc are required to maintain tissue homeostasis.

How the proto-oncogene c-Myc balances the processes of stem-cell self-renewal, proliferation and differentiation in adult tissues is largely unknown. We explored c-Myc's transcriptional roles at the epidermal differentiation complex, a locus essential for skin maturation. Binding of c-Myc can simultaneously recruit (Klf4, Ovol-1) and displace (Cebpa, Mxi1 and Sin3a) specific sets of differentiation-specific transcriptional regulators to epidermal differentiation complex genes. We found that Sin3a causes deacetylation of c-Myc protein to directly repress c-Myc activity. In the absence of Sin3a, genomic recruitment of c-Myc to the epidermal differentiation complex is enhanced, and re-activation of c-Myc-target genes drives aberrant epidermal proliferation and differentiation. Simultaneous deletion of c-Myc and Sin3a reverts the skin phenotype to normal. Our results identify how the balance of two transcriptional key regulators can maintain tissue homeostasis through a negative feedback loop

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN