Author contributions DCJ coordinated all analyses, isolated DNA for sequencing, analysed and filtered SNP calls, conducted diversity analysis and GWAS and drafted the manuscript. CR produced phenotype data for growth on various solid media and growth rates in liquid media. AR conducted analysis of dating using mitochondrial data. DS conducted GWAS. MP analysed all phenotype data. TM identified LTR transposon insertions and analysed transposon insertion data. FXM conducted crosses for analysis of spore viability ZI produced indel calls with Cortex. WL conducted analysis of recombination rate, linkage disequilibrium decay and PCA for distance between strains. TMKC assisted with phenotype and population analysis. RP analysed Cortex and GATK indel calls. MM conducted amino acid profiling. JLDL and AC produced automated measures of cell morphology. SB aligned reads and produced GATK SNP calls. GH analysed population structure using fineSTRUCTURE. BO'F estimated the TMRCA from the nuclear genome using ACG. TK identified LTR transposon insertions JTS produced de novo assemblies. LB developed the custom Workspace workflow Spotsizer. BT assisted with sequence analysis. DAB assisted with analysis of novel genes. TS assisted with strain verification. SC produced images of wild strains and assisted with strain verification. JEEUH assisted with SNP validation. LvT and MT assisted with LTR validation. LJ and JL assisted with manual measures of cell morphology and FACS. SA produced gene expression data. MF, KM and ND assisted with sequencing. WB initiated and assisted with strain collection. JH coordinated manual measures of cell morphology and FACS. RECS coordinated automated measures of cell morphology. MR coordinated amino acid profiling. NM conducted analysis of recombination, linkage disequilibrium and advised on aspects of diversity and GWAS. DJB advised on GWAS. RD facilitated sequencing. JB contributed to the initiation and development of the project and financed the JB laboratory. AccessionsSequence data are archived in the European Nucleotide Archive (www.ebi.ac.uk/ena/), Study Accessions PRJEB2733 and PRJEB6284 (Supplementary Table 7). All SNPs and indels were submitted to NCBI dbSNP (www.ncbi.nlm.nih.gov/SNP/). Accessions are 974514578-974688138 (SNPs) and 974702618-974688139 (indels). Europe PMC Funders Group AbstractNatural variation within species reveals aspects of genome evolution and function. The fission yeast Schizosaccharomyces pombe is an important model for eukaryotic biology, but researchers typically use one standard laboratory strain. To extend the utility of this model, we surveyed the genomic and phenotypic variation in 161 natural isolates. We sequenced the genomes of all strains, revealing moderate genetic diversity (π = 3 ×10 −3 ) and weak global population structure. We estimate that dispersal of S. pombe began within human antiquity (~340 BCE), and ancestors of these strains reached the Americas at ~1623 CE. We quantified 74 traits, revealing substantial heritable phenotypic diversity. We cond...

The accurate scoring of rigid-body docking orientations represents one of the major difficulties in protein-protein docking prediction. Other challenges are the development of faster and more efficient sampling methods and the introduction of receptor and ligand flexibility during simulations. Overall, good discrimination of near-native docking poses from the very early stages of rigid-body protein docking is essential step before applying more costly interface refinement to the correct docking solutions. Here we explore a simple approach to scoring of rigid-body docking poses, which has been implemented in a program called pyDock. The scheme is based on Coulombic electrostatics with distance dependent dielectric constant, and implicit desolvation energy with atomic solvation parameters previously adjusted for rigid-body protein-protein docking. This scoring function is not highly dependent on specific geometry of the docking poses and therefore can be used in rigid-body docking sets generated by a variety of methods. We have tested the procedure in a large benchmark set of 80 unbound docking cases. The method is able to detect a near-native solution from 12,000 docking poses and place it within the 100 lowest-energy docking solutions in 56% of the cases, in a completely unrestricted manner and without any other additional information. More specifically, a near-native solution will lie within the top 20 solutions in 37% of the cases. The simplicity of the approach allows for a better understanding of the physical principles behind protein-protein association, and provides a fast tool for the evaluation of large sets of rigid-body docking poses in search of the near-native orientation.

Multisite phosphorylation regulates many transcription factors, including the Serum Response Factor partner Elk-1. Phosphorylation of the transcriptional activation domain (TAD) of Elk-1 by the protein kinase ERK at multiple sites potentiates recruitment of the Mediator transcriptional coactivator complex and transcriptional activation, but the roles of individual phosphorylation events remained unclear. Using time-resolved nuclear magnetic resonance spectroscopy, we found that ERK2 phosphorylation proceeds at markedly different rates at eight TAD sites in vitro, which we classified as fast, intermediate and slow. Mutagenesis experiments showed that phosphorylation of fast and intermediate sites promoted Mediator interaction and transcriptional activation, whereas modification of slow sites counteracted both functions, thereby limiting Elk-1 output. Progressive Elk-1 phosphorylation thus ensures a self-limiting response to ERK activation, which occurs independently of antagonizing phosphatase activity. Results and DiscussionMultisite protein phosphorylation increases the complexity of functional signaling outputs that can be generated from single protein kinase inputs. It can set thresholds for activity, or transform graded signals into switch-like responses (1-4). Many transcription factors and their interacting regulatory proteins are subject to multisite phosphorylation, which allows distinct aspects of protein function, including protein turnover, nuclear import and export, and specific protein interactions, to be controlled independently (5). However, in general, the † The ternary complex factor (TCF) subfamily of Ets-domain transcription factors, consisting of Elk-1, SAP-1, and Net, provides an example of multisite phosphorylation in transcriptional activation. TCFs, together with their partner protein SRF, function in many biological processes by coupling SRF target genes to mitogen-activated protein kinase (MAP kinase) signaling (5). Mitogenic and stress stimuli induce phosphorylation of TCF Cterminal transcriptional activation domains (TADs) at multiple S/T-P (Ser-or Thr-Pro) phosphorylation sequences, of which eight are conserved across the family ( Fig. 1A; fig. S1) (6-11). Two MAP kinase-docking sites, the D-box and the Phe-Gln-Phe-Pro (FQFP) motif, control phosphorylation of these sites (12-15). Multisite phosphorylation triggers transcriptional activation by TCFs, facilitating their interaction with the Mediator transcriptional co-activator complex (16-19) but the kinetics with which the different sites are phosphorylated, and whether they serve distinct functions, remain unclear.To obtain atomic-resolution insights into phosphorylation of the Elk-1 TAD, we used nuclear magnetic resonance (NMR) spectroscopy (20) Fig. 2A). In the fast site mutant Elk-1F, phosphorylation rates of intermediate and slow sites increased, whereas those of the fast and slow sites increased in the intermediate-site mutant Elk-1I; in both cases the altered kinetics fit well with those predicted by the model (Fig 2B,...

Mitotic chromosomes were one of the first cell biological structures to be described, yet their molecular architecture remains poorly understood. We have devised a simple biophysical model of a 300 kb-long nucleosome chain, the size of a budding yeast chromosome, constrained by interactions between binding sites of the chromosomal condensin complex, a key component of interphase and mitotic chromosomes. Comparisons of computational and experimental (4C) interaction maps, and other biophysical features, allow us to predict a mode of condensin action. Stochastic condensin-mediated pairwise interactions along the nucleosome chain generate native-like chromosome features and recapitulate chromosome compaction and individualization during mitotic condensation. Higher order interactions between condensin binding sites explain the data less well. Our results suggest that basic assumptions about chromatin behavior go a long way to explain chromosome architecture and are able to generate a molecular model of what the inside of a chromosome is likely to look like.DOI: http://dx.doi.org/10.7554/eLife.05565.001