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Balgach, Switzerland
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Ghodgaonkar M.M.,ETH Zurich | Ghodgaonkar M.M.,Ludwig Maximilians University of Munich | Kehl P.,ETH Zurich | Kehl P.,Microsynth AG | And 7 more authors.
Nature Communications | Year: 2014

Next-generation sequencing has revolutionized the search for disease-causing genetic alterations. Unfortunately, the task of distinguishing the handful of causative mutations from rare variants remains daunting. We now describe an assay that permits the analysis of all types of mutations in any gene of choice through the generation of stable human cell lines, in which the endogenous protein has been inducibly replaced with its genetic variant. Here we studied the phenotype of variants of the essential replicative polymerase-δ carrying missense mutations in its active site, similar to those recently identified in familial colon cancer patients. We show that expression of the mutants but not the wild-type protein endows the engineered cells with a mutator phenotype and that the mutations affect the fidelity and/or the exonuclease activity of the isolated enzyme in vitro. This proof-of-principle study demonstrates the general applicability of this experimental approach in the study of genotype-phenotype correlations. © 2014 Macmillan Publishers Limited.

Gross A.,ETH Zurich | Zaffarano P.L.,ETH Zurich | Duo A.,ETH Zurich | Grunig C.R.,Microsynth AG
Fungal Genetics and Biology | Year: 2012

Ash dieback caused by the fungal pathogen Hymenoscyphus pseudoalbidus is currently ravaging in Europe, killing Fraxinus excelsior and Fraxinus angustifolia trees of all age classes. The aim of this work was to elucidate aspects of the reproduction biology of this fungal pathogen and its cryptic, non-pathogenic sister species Hymenoscyphus albidus. The mating type (MAT) locus of both species was identified, partly sequenced and characterized. Whereas a heterothallic MAT organization was detected in H. pseudoalbidus, H. albidus was shown to be structurally homothallic. The molecular MAT determination of H. pseudoalbidus was confirmed by crossing experiments on sterile ash petioles. Crossings of strains exhibiting alternate MAT idiomorphs produced fertile apothecia whereas crosses of strains with identical MAT idiomorphs were never successful. Offspring genotyping with microsatellites (MSs) and the MAT marker confirmed that both parental strains were involved in apothecia formation. In addition, polymorphic MS were shown to follow Mendelian inheritance. However, for yet unknown reasons the MAT ratio of progenies of one successful cross revealed a significant segregation distortion. Based on the MAT sequences of H. pseudoalbidus a multiplex PCR was developed, allowing for a quick and reliable MAT determination. The PCR was applied to screen the MAT ratio of two H. pseudoalbidus populations derived from the country of the disease outbreak in Poland and two populations from the disease periphery in Switzerland. None of the screened populations showed a significant deviation from the 1:1 ratio, expected under random mating. Therefore, an initial clonal distribution through asexually produced conidiospores as observed for other fungal pathogens holds not true for H. pseudoalbidus. Instead, our data is highly supportive for a distribution through ascospores. Leaf petioles collected in the field were thoroughly analyzed for the number of different colonizing strains and their mating behavior. Up to eight different H. pseudoalbidus genotypes were found on a single petiole. Cross-fertilizations of strains on the same petiole and fertilizations of unknown strains from outside were found, indicating that fertilization is mediated by spermatia. The presented study complements our understanding of the life cycle of this highly destructive pathogen. The possibility to perform sexual crosses in the lab provides ample opportunities for further genetic studies of H. pseudoalbidus and related species in the future. © 2012 Elsevier Inc.

McCullough K.C.,Institute of Virology and Immunology | Milona P.,Institute of Virology and Immunology | Thomann-Harwood L.,Institute of Virology and Immunology | Demoulins T.,Institute of Virology and Immunology | And 3 more authors.
Vaccines | Year: 2014

Dendritic cells (DC) play essential roles determining efficacy of vaccine delivery with respect to immune defence development and regulation. This renders DCs important targets for vaccine delivery, particularly RNA vaccines. While delivery of interfering RNA oligonucleotides to the appropriate intracellular sites for RNA-interference has proven successful, the methodologies are identical for RNA vaccines, which require delivery to RNA translation sites. Delivery of mRNA has benefitted from application of cationic entities; these offer value following endocytosis of RNA, when cationic or amphipathic properties can promote endocytic vesicle membrane perturbation to facilitate cytosolic translocation. The present review presents how such advances are being applied to the delivery of a new form of RNA vaccine, replicons (RepRNA) carrying inserted foreign genes of interest encoding vaccine antigens. Approaches have been developed for delivery to DCs, leading to the translation of the RepRNA and encoded vaccine antigens both in vitro and in vivo. Potential mechanisms favouring efficient delivery leading to translation are discussed with respect to the DC endocytic machinery, showing the importance of cytosolic translocation from acidifying endocytic structures. The review relates the DC endocytic pathways to immune response induction, and the potential advantages for these self-replicating RNA vaccines in the near future. © 2014, Vaccines. All rights reserved.

Eberhard R.,University of Zürich | Stergiou L.,University of Zürich | Stergiou L.,Redbiotec | Hofmann E.R.,University of Zürich | And 8 more authors.
PLoS Genetics | Year: 2013

Synthesis of ribosomal RNA by RNA polymerase I (RNA pol I) is an elemental biological process and is key for cellular homeostasis. In a forward genetic screen in C. elegans designed to identify DNA damage-response factors, we isolated a point mutation of RNA pol I, rpoa-2(op259), that leads to altered rRNA synthesis and a concomitant resistance to ionizing radiation (IR)-induced germ cell apoptosis. This weak apoptotic IR response could be phenocopied when interfering with other factors of ribosome synthesis. Surprisingly, despite their resistance to DNA damage, rpoa-2(op259) mutants present a normal CEP-1/p53 response to IR and increased basal CEP-1 activity under normal growth conditions. In parallel, rpoa-2(op259) leads to reduced Ras/MAPK pathway activity, which is required for germ cell progression and physiological germ cell death. Ras/MAPK gain-of-function conditions could rescue the IR response defect in rpoa-2(op259), pointing to a function for Ras/MAPK in modulating DNA damage-induced apoptosis downstream of CEP-1. Our data demonstrate that a single point mutation in an RNA pol I subunit can interfere with multiple key signalling pathways. Ribosome synthesis and growth-factor signalling are perturbed in many cancer cells; such an interplay between basic cellular processes and signalling might be critical for how tumours evolve or respond to treatment. © 2013 Eberhard et al.

Ganzle M.G.,University of Alberta | Follador R.,University of Alberta | Follador R.,Microsynth AG
Frontiers in Microbiology | Year: 2012

Oligosaccharides, compounds that are composed of 2-10 monosaccharide residues, are major carbohydrate sources in habitats populated by lactobacilli. Moreover, oligosaccharide metabolism is essential for ecological fitness of lactobacilli. Disaccharide metabolism by lactobacilli is well understood; however, few data on the metabolism of higher oligosaccharides are available. Research on the ecology of intestinal microbiota as well as the commercial application of prebiotics has shifted the interest from (digestible) disaccharides to (indigestible) higher oligosaccharides.This review provides an overview on oligosaccharide metabolism in lactobacilli. Emphasis is placed on maltodextrins, isomalto-oligosaccharides, fructo-oligosaccharides, galacto-oligosaccharides, and raffinose-family oligosaccharides. Starch is also considered. Metabolism is discussed on the basis of metabolic studies related to oligosaccharide metabolism, information on the cellular location and substrate specificity of carbohydrate transport systems, glycosyl hydrolases and phosphorylases, and the presence of metabolic genes in genomes of 38 strains of lactobacilli. Metabolic pathways for disaccharide metabolism often also enable the metabolism of triand tetrasaccharides. However, with the exception of amylase and levansucrase, metabolic enzymes for oligosaccharide conversion are intracellular and oligosaccharide metabolism is limited by transport. This general restriction to intracellular glycosyl hydrolases differentiates lactobacilli from other bacteria that adapted to intestinal habitats, particularly Bifidobacterium spp. © 2012 Gänzle and Follador.

Tellenbach C.,ETH Zurich | Tellenbach C.,Eawag - Swiss Federal Institute of Aquatic Science and Technology | Sumarah M.W.,Agriculture and Agri Food Canada | Sumarah M.W.,Carleton University | And 3 more authors.
Fungal Ecology | Year: 2013

Dark septate fungal root endophytes of the Phialocephala fortinii s.l.-Acephala applanata species complex (PAC) are widely distributed throughout the temperate and subtropical regions of the Northern Hemisphere. Previous studies have shown that some PAC members are pathogenic, others suppress oomycete root pathogens and some have no obvious effect on their Norway spruce (Picea abies) host. The activity of 85 PAC isolates against Phytophthora citricola s.l. was investigated by co-culture on plates. We identified a strain of Phialocephala europaea that significantly reduced the growth of P. citricola in vitro. Characterization of its extracellular metabolites resulted in the identification of four major compounds, sclerin, sclerolide, sclerotinin A, and sclerotinin B. These compounds are known for their positive as well as negative effects on plant growth. We found that sclerin and sclerotinin inhibited the growth of P. citricola in vitro at 150 μg ml-1 (∼1 mM). This is the first report of their production by Phialocephala and of activity of these compounds against an oomycete. Therefore, our data suggest that some PAC might reduce disease resulting from P. citricola by the production of antibiotics and plant growth promoting metabolites. © 2012 Elsevier Ltd and The British Mycological Society.

Zaffarano P.L.,ETH Zurich | Queloz V.,ETH Zurich | Du A.,ETH Zurich | Grunig C.R.,ETH Zurich | Grunig C.R.,Microsynth AG
BMC Evolutionary Biology | Year: 2011

Background: Fungi are asexually and sexually reproducing organisms that can combine the evolutionary advantages of the two reproductive modes. However, for many fungi the sexual cycle has never been observed in the field or in vitro and it remains unclear whether sexual reproduction is absent or cryptic. Nevertheless, there are indirect approaches to assess the occurrence of sex in a species, such as population studies, expression analysis of genes involved in mating processes and analysis of their selective constraints. The members of the Phialocephala fortinii s. l. - Acephala applanata species complex (PAC) are ascomycetes and the predominant dark septate endophytes that colonize woody plant roots. Despite their abundance in many ecosystems of the northern hemisphere, no sexual state has been identified to date and little is known about their reproductive biology, and how it shaped their evolutionary history and contributes to their ecological role in forest ecosystems. We therefore aimed at assessing the importance of sexual reproduction by indirect approaches that included molecular analyses of the mating type (MAT) genes involved in reproductive processes. Results: The study included 19 PAC species and > 3, 000 strains that represented populations from different hosts, continents and ecosystems. Whereas A. applanata had a homothallic (self-fertile) MAT locus structure, all other species were structurally heterothallic (self-sterile). Compatible mating types were observed to co-occur more frequently than expected by chance. Moreover, in > 80% of the populations a 1:1 mating type ratio and gametic equilibrium were found. MAT genes were shown to evolve under strong purifying selection. Conclusions: The signature of sex was found in worldwide populations of PAC species and functionality of MAT genes is likely preserved by purifying selection. We hypothesize that cryptic sex regularely occurs in the PAC and that further field studies and in vitro crosses will lead to the discovery of the sexual state. Although structurally heterothallic species prevail, it cannot be excluded that homothallism represents the ancestral breeding system in the PAC. © 2011 Zaffarano et al; licensee BioMed Central Ltd.

Duo A.,ETH Zurich | Bruggmann R.,University of Bern | Zoller S.,ETH Zurich | Bernt M.,University of Leipzig | And 2 more authors.
BMC Genomics | Year: 2012

Background: Mitochondrial (mt) markers are successfully applied in evolutionary biology and systematics because mt genomes often evolve faster than the nuclear genomes. In addition, they allow robust phylogenetic analysis based on conserved proteins of the oxidative phosphorylation system. In the present study we sequenced and annotated the complete mt genome of P. subalpina, a member of the Phialocephala fortinii s.l. - Acephala applanata species complex (PAC). PAC belongs to the Helotiales, which is one of the most diverse groups of ascomycetes including more than 2,000 species. The gene order was compared to deduce the mt genome evolution in the Pezizomycotina. Genetic variation in coding and intergenic regions of the mtDNA was studied for PAC to assess the usefulness of mt DNA for species diagnosis.Results: The mt genome of P. subalpina is 43,742 bp long and codes for 14 mt genes associated with the oxidative phosphorylation. In addition, a GIY-YIG endonuclease, the ribosomal protein S3 (Rps3) and a putative N-acetyl-transferase were recognized. A complete set of tRNA genes as well as the large and small rRNA genes but no introns were found. All protein-coding genes were confirmed by EST sequences. The gene order in P. subalpina deviated from the gene order in Sclerotinia sclerotiorum, the only other helotialean species with a fully sequenced and annotated mt genome. Gene order analysis within Pezizomycotina suggests that the evolution of gene orders is mostly driven by transpositions. Furthermore, sequence diversity in coding and non-coding mtDNA regions in seven additional PAC species was pronounced and allowed for unequivocal species diagnosis in PAC.Conclusions: The combination of non-interrupted ORFs and EST sequences resulted in a high quality annotation of the mt genome of P. subalpina, which can be used as a reference for the annotation of other mt genomes in the Helotiales. In addition, our analyses show that mtDNA loci will be the marker of choice for future analysis of PAC communities. © 2012 Duò et al.; licensee BioMed Central Ltd.

PubMed | ETH Zurich and Microsynth AG
Type: Journal Article | Journal: mBio | Year: 2015

The aim of this study was to investigate the effect of iron (Fe) availability on butyrate production in the complex bacterial ecosystem of the human gut. Hence, different Fe availabilities were mimicked in an in vitro colonic fermentation model (the polyfermenter intestinal model called PolyFermS) inoculated with immobilized gut microbiota from a child and in batch cultures of the butyrate producer Roseburia intestinalis. Shifts in the microbial community (16S rRNA sequencing and quantitative PCR), metabolic activity (high-performance liquid chromatography), and expression of genes involved in butyrate production were assessed. In the PolyFermS, moderate Fe deficiency resulted in a 1.4-fold increase in butyrate production and a 5-fold increase in butyryl-coenzyme A (CoA):acetate CoA-transferase gene expression, while very strong Fe deficiency significantly decreased butyrate concentrations and butyrate-producing bacteria compared with the results under normal Fe conditions. Batch cultures of R.intestinalis grown in a low-Fe environment preferentially produced lactate and had reduced butyrate and hydrogen production, in parallel with upregulation of the lactate dehydrogenase gene and downregulation of the pyruvate:ferredoxin-oxidoreductase gene. In contrast, under high-Fe conditions, R.intestinalis cultures showed enhanced butyrate and hydrogen production, along with increased expression of the corresponding genes, compared with the results under normal-Fe conditions. Our data reveal the strong regulatory effect of Fe on gut microbiota butyrate producers and on the concentrations of butyrate, which contributes to the maintenance of host gut health.Fe deficiency is one of the most common nutritional deficiencies worldwide and can be corrected by Fe supplementation. In this in vitro study, we show that environmental Fe concentrations in a continuous gut fermentation model closely mimicking a childs gut microbiota strongly affect the composition of the gut microbiome and its metabolic activity, particularly butyrate production. The differential expression of genes involved in the butyrate production pathway under different Fe conditions and the enzyme cofactor role of Fe explain the observed modulation of butyrate production. Our data reveal that the level of dietary Fe reaching the colon affects the microbiome, and its essential function of providing the host with beneficial butyrate.

News Article | November 30, 2016
Site: www.nature.com

No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. The C. marinus laboratory stocks were bred according to Neumann1, care was provided by the MFPL aquatic facility. Briefly, C. marinus were kept in 20 × 20 × 5 cm plastic containers with sand and natural seawater diluted to 15‰ with desalted water, fed diatoms (Phaeodactylum tricornutum, strain UTEX 646) in early larval stages and nettle powder in later stages. Temperature in the climate chambers was set to 20 °C and the light–dark cycle was 12:12 (except where noted differently). Moonlight was simulated with an incandescent flashlight bulb (about 1 lx), which was switched on all night for four successive nights every 30 days. The genome assembly process (Extended Data Fig. 9a) was based on three sequencing libraries (Supplementary Table 10): a 0.2-kb insert library was prepared from a single adult male of the Jean laboratory strain (established from field samples taken at St. Jean-de-Luz, France, in 2007; >12 generations in the laboratory), which was starved and kept in seawater with penicillin (60 units per ml), streptomycin (60 μg ml−1) and neomycin (120 μg ml−1) during the last 2 weeks of development. DNA was extracted with a salting-out method46, sheared on a Covaris S2 sonicator (frequency sweeping mode; 4 °C; duty cycle, 10%; intensity, 7; cycles per burst, 300; microTUBE AFA fibre 6 × 16 mm; 30 s) and prepared for Illumina sequencing with standard protocols. A 2.2-kb and a 7.6-kb insert library were prepared from a polymorphic DNA pool of >300 field-caught Jean adult males by Eurofins MWG Operon (Ebersberg, Germany) according to the manufacturer’s protocol. Each library was sequenced in one lane of an Illumina HiSeq2000 with 100-bp paired-end reads at the Next Generation Sequencing unit of the Vienna Biocenter Core Facilities (http://vbcf.ac.at). Reads were filtered for read quality, adaptor and spacer sequences with cutadapt47 (−b −n 3 −e 0.1 −O 8 −q 20 −m 13) and duplicates were removed with fastq-mcf from ea-utils48 (−D 70). Read pairs were interleaved with ngm-utils49, leaving only paired reads. Contamination with human DNA found in the 0.2-kb library was removed by deleting reads matching the human genome at a phred-scaled quality score ≥ 20 (alignment with BWA50). Assembly into contigs with Velvet51 (scaffolding disabled; 57-bp kmers as determined by VelvetOptimiser52) was based solely on the less polymorphic 0.2-kb library. About 600 remaining adaptor sequences at the ends of assembled contigs were trimmed with cutadapt (−O 8 −e 0.1 −n 3). For assembly statistics see Supplementary Table 11. Scaffolding of the contigs was based on all three libraries and performed with SSPACE53 in two iterations, that is, scaffolds from the first round were scaffolded again. Using different parameters in the iterations (Supplementary Table 12) allowed different connections to be made and thus increased scaffold connectivity (Supplementary Table 13). The effect is probably owing to the polymorphic nature of the 2.2-kb and 7.6-kb libraries; it results in a ‘population-consensus most common arrangement of the scaffolds’. The iterative scaffolding process was performed with and without applying a size cut-off excluding contigs <1 kb, resulting in two independent assemblies (CLUMA_0.3 and CLUMA_0.4; see Extended Data Fig. 9a), which differed in overall connectivity and sequence content (Supplementary Table 11), but also in the identity and structure of the large scaffolds. In order to combine both connectivity and sequence content, and in order to resolve the contradictions in the structure of the largest scaffolds, the two assemblies were compared and reconciled in a manual super-scaffolding process, as detailed in Supplementary Method 1. Briefly, the overlap of scaffolds from the two assemblies was tested with BLAST searches and represented in a graphical network structure. Scaffolds with congruent sequence content in both assemblies would result in a linear network, whereas scaffolds with contradictory sequence content would result in branching networks. At the same time, both assemblies were subject to genetic linkage mapping based on genotypes obtained from restriction-site-associated DNA sequencing (RAD sequencing) of a published mapping family6 (Supplementary Method 2). The resulting genetic linkage information served to resolve the branching networks into the longest possible unambiguous linear sub-networks with consistent genetic linkage information (see scheme A in Supplementary Method 1). Finally, the structure of the resulting super-scaffolds was coded in YAML format and translated into DNA sequence with Scaffolder54, resulting in 75 mapped super-scaffolds. The remaining small and unmapped scaffolds were filtered for fragments of the mitochondrial genome, the histone gene cluster and 18S/28S ribosomal rDNA gene cluster, which were assembled separately (Supplementary Method 3; Extended Data Fig. 10). Unmapped scaffolds were also filtered for obvious contamination from other species (Supplementary Method 3). The degree to which the remaining unmapped scaffolds are leftover polymorphic variants of parts of the mapped super-scaffolds was estimated by blasting the former against the latter (Supplementary Method 3 and Supplementary Table 14). All scaffolds were subject to gap closing with GapFiller55 and repeated edges, that is, gaps with almost identical sequences at both sides that are generally not closed because of genetic polymorphisms, were assessed and if possible removed with a custom script (Supplementary Method 4; code available supplied as Source Data File). The final assembly CLUMA_1.0 was submitted under project PRJEB8339 (75 mapped scaffolds; 23,687 unmapped scaffolds ≥100 bp). The assembly and further information can also be obtained from ClunioBase (http://cluniobase.cibiv.univie.ac.at). Genetic linkage information for the final 75 super-scaffolds was obtained by repeating read mapping to genotype calling for the RAD sequencing experiment as described above (Supplementary Method 2), but now with assembly CLUMA_1.0 as a reference. This allowed us to place and orient super-scaffolds along the genetic linkage map (Fig. 1a and Extended Data Fig. 2). The positions of the recombination events within a scaffold were approximated as the middle between the positions of the two RAD markers between which the marker pattern changed from one map location to the next. The published genetic linkage map was refined and revised (Supplementary Method 5 and Extended Data Fig. 2). Based on the refined linkage map, QTL analysis of the published mapping family was repeated as described6 (Supplementary Table 4 and Supplementary Note 5). Using the correspondence between the reference assembly and the genetic linkage map, we were able to directly identify the genomic regions corresponding to the confidence intervals of the QTLs (Fig. 1 and Extended Data Fig. 5a, b). Assembled transcripts of a normalized cDNA library of all life stages and various C. marinus strains (454 sequencing) were available from previous experiments and RNA sequencing data was available for Jean strain adults (Illumina sequencing). Furthermore, specifically for genome annotation, RNA from 80 third instar larvae from the Jean and Por laboratory strains each was prepared for RNA sequencing according to standard protocols (Supplementary Method 6). Each sample was sequenced on a single lane of an Illumina HiSeq 2000. All transcript reads were submitted to the European Nucleotide Archive (ENA) under project PRJEB8339. For the adult and larval RNA sequencing data, raw reads were quality checked with fastqc56, trimmed for adaptors quality with cutadapt47 and filtered to contain only read pairs using the interleave command in ngm-utils49. Reads were assembled separately for larvae and adults with Trinity57 (path_reinforcement_distance: 25; maximum paired-end insert size: 1,500 bp; otherwise default parameters). Automated annotation was performed with MAKER258. Repeats were masked based on all available databases in repeatmasker. MAKER2 combined evidence from assembled transcripts (see above), mapped protein data sets from Culex quinquefasciatus (CpipJ1), Anopheles gambiae (AgamP3), Drosophila melanogaster (BDGP5), Danaus plexippus (DanPle_1.0), Apis mellifera (Amel4.0), Tribolium castaneum (Tcas3), Strigamia maritima (Smar1) and Daphnia pulex (Dappu1) and ab initio gene predictions with AUGUSTUS59 and SNAP60 into gene models. AUGUSTUS was trained for C. marinus based on assembled transcripts from the normalized cDNA library. SNAP was run with parameters for A. mellifera, which had the highest congruence with known C. marinus genes in preliminary trials (Supplementary Method 7). MAKER was set to infer gene models from all evidence combined (not transcripts only) and gene predictions without transcript evidence were allowed. Splice variant detection was enabled, single-exon genes had to be larger than 250 bp and intron size was limited to a maximum of 10 kb. All gene models within the QTL confidence intervals, as well as all putative circadian clock genes and light receptor genes were manually curated: exon–intron boundaries were corrected according to transcript evidence (approximately 500 gene models), chimeric gene models were separated into the underlying individual genes (approximately 100 gene models separated into around 300 gene models) and erroneously split gene models were joined (approximately 15 gene models). Finally, this resulted in 21,672 gene models, which were given IDs from CLUMA_CG000001 to CLUMA_CG021672 (‘CLUMA’ for Clunio marinus, following the controlled vocabulary of species from the UniProt Knowledgebase; CG for ‘computated gene’). Splice variants of the same gene (detected in 752 gene models) were identified by the suffix ‘-RA’, ‘-RB’ and so on, and the corresponding proteins by the suffix ‘-PA’, ‘-PB’ and so forth. Gene models were considered as supported if they overlapped with mapped transcripts or protein data (Supplementary Table 1). Gene counts for D. melanogaster were retrieved from BDGP5, version 75.546 and for A. gambiae from AgamP3, version 75.3. The putative identities of the C. marinus gene models were determined in reciprocal BLAST searches, first against UniProtKB/Swiss-Prot (8,379 gene models assigned) and if no hit was found, second against the non-redundant protein sequences (nr database) at NCBI (1,802 additional genes assigned). Reciprocal best hits with an e value < 1 × 10−10 were considered putative orthologues (termed ‘putative gene X’), non-reciprocal hits with the same e value were considered paralogues (termed ‘similar to’). All remaining gene models were searched against the PFAM database of protein domains (111 gene models assigned; termed ‘gene containing domain X’). If still no hit was found, the gene models were left unassigned (‘NA’). Genome-wide synteny between the C. marinus, D. melanogaster and A. gambiae genomes was assessed based on reciprocal best BLAST hits (e value < 10 × 10-10) between the three protein data sets (Ensembl Genomes, Release 22, for D. melanogaster and A. gambiae). Positions of pairwise orthologous genes were retrieved from the reference genomes (BDGP5, AgamP3 and CLUMA_1.0) and plotted with Circos61. C. marinus chromosome arms were delimited based on centromeric and telomeric signatures in genetic diversity and linkage disequilibrium (Extended Data Fig. 3c and Supplementary Table 3; for data source see ‘strain re-sequencing’ below). Homologues for C. marinus chromosome arms were assigned based on enrichment with putative orthologous genes from specific chromosome arms in D. melanogaster and A. gambiae (Extended Data Figs 3, 4 and Supplementary Table 3). Additionally, for the 5,388 detected putative 1:1:1 orthologues (C. marinus:D. melanogaster:A. gambiae), microsynteny was assessed by testing if all pairs of directly adjacent genes in one species were also directly adjacent in the other species. The degree of microsynteny was then calculated as the fraction of conserved adjacencies among all pairs of adjacent genes. From this fraction the relative levels of chromosomal rearrangements in the evolutionary lineage leading to C. marinus were estimated (Supplementary Note 3 and Extended Data Fig. 4). Genetic variation in five C. marinus strains (Extended Data Fig. 1) was assessed based on pooled-sequencing data from field-caught males from the strains of St. Jean-de-Luz (Jean; Basque Coast, France; sampled in 2007; n = 300), Port-en-Bessin (Por; Normandie, France; 2007; n = 300), as well as Vigo (Spain; 2005; n = 100), Helgoland (He; Germany; 2005; n = 300) and Bergen (Ber; Norway; 2005; n = 100). Samples from Vigo and Bergen, were provided by D. Neumann and C. Augustin, respectively. For each strain we chose the largest available number of individuals to obtain the best possible resolution of allele frequencies. Females are not available, because they are virtually invisible in the field. For an overview of the experimental procedure, see Extended Data Fig. 9b. DNA was extracted with a salting-out method46 from sub-pools of 50 males, the DNA pools were mixed at equal DNA amounts, sheared and prepared as described above and sequenced on four lanes of an Illumina HiSeq2000 with paired-end 100-bp reads (Ber and Vigo combined in one lane, distinguished by index reads). All reads were submitted to the European Nucleotide Archive (ENA) under project PRJEB8339. Sequencing reads were filtered for read quality and adaptor sequences with cutadapt47 (−b −n 2 −e 0.1 −O 8 −q 13 −m 15), interleaved with ngm-utils49 and duplicates were removed with fastq-mcf from ea-utils48 (−D 70). Reads were aligned to the mapped super-scaffolds of assembly CLUMA_1.0 with BWA50 (aln and sampe; maximal insert size (bp): −a 1500). Based on the unfiltered alignments, the samples from Por and Jean were screened for genomic inversions and indels relative to the reference sequence with the multi-sample version of DELLY62. Paired-end information was only considered if the mapping quality was high (q ≥ 20) (see also Supplementary Note 3). For population genomic analysis (Extended Data Fig. 9b), the alignments of the pool-sequencing (pool–seq) data from Vigo, Jean, Por, He and Ber were filtered for mapping quality (q ≥ 20), sorted, merged and indexed with SAMtools63. Reads were re-aligned around indels with the RealignerTargetCreator and the IndelRealigner in GATK64. The resulting coverage per strain is given in Supplementary Table 5. For identification of SNPs, a pileup file was created with the mpileup command of SAMtools63. Base Alignment Quality computation was disabled (−B); instead, after creating a synchronized file with the mpileup2sync script in PoPoolation265, indels that occurred more than ten times were masked (including 3 bp upstream and downstream) with the identify-indel-regions and filter-sync-by-gtf scripts of PoPoolations2. F values were determined with the fst-sliding script of PoPoolation2, applying a minimum allele count of 10 (so that any false-positive SNPs resulting from the remaining unmasked indels were effectively excluded) and a minimum coverage of 40× for the comparison between Por and Jean or 10× for the comparison of all five strains. F was calculated at a single base resolution, as well as in windows of 5 kb (step size, 1 kb). Individual SNPs were only considered for further analyses or plotted if they were significantly differentiated as assessed by Fisher’s exact test (fisher-test in PoPoolation2). Average genome-wide genetic differentiation between timing strains, as obtained by averaging over 5-kb sliding-windows, was compared to the respective timing differences and geographic distances (see Supplementary Table 8) in Mantel tests (Pearson’s product moment correlation; 9,999 permutations), as implemented in the vegan package in the R statistical programming environment (ref. 66). Geographic distances and circadian timing differences were determined as described previously67 (see Supplementary Table 8). For determination of lunar timing differences when comparing lunar with semilunar rhythms see Supplementary Note 6. In order to find genomic regions for which genetic differentiation is correlated with the timing differences between strains, the Mantel test was then applied to 5-kb genomic windows every 1 kb along the reference sequence. 5 kb is roughly the average size of a gene locus in C. marinus. Windows with a correlation coefficient of r ≥ 0.5 were tested for significance (999 permutations). For each genomic position the number of overlapping significantly correlated 5-kb windows was enumerated, resulting in a correlation score (CS; ranging from 0 to 5). Genetic diversity, measured as Watterson’s theta (θ ), for each strain was assessed with PoPoolation1.1.2 (ref. 68) in 20-kb windows with 10-kb steps. In order to save computing time, the pileup files of Jean, Por and He were linearly downscaled to 100× coverage with the subsample-pileup script (‘fraction’ option), positions below 100× coverage were discarded. Indel regions were excluded (default in PoPoolation 1.1.2) and a minimum of 66% of a sliding window needed to be covered. SNPs were only considered in θ calculations if present ≥2 times, leading to slight inconsistencies in θ estimates between strains due to differing coverage, but not affecting diversity comparisons within strains. Linkage disequilibrium between the SNPs was determined for the Por and Jean strains with LDx69, assuming physical linkage between alleles on the same read or read pairs. r2 was determined by a maximum likelihood estimator, minimum and maximum read depths corresponded to the 2.5% and 97.5% coverage depths for each population (Jean, 111–315; Por, 98–319), total insert distance was limited to 600 bp, minimum phred-scaled base quality was 20, minimum allele frequency was 0.1 and a minimum coverage per pair of SNPs was 11. SNPs were binned by their physical distance for the plots (0–200 bp, 200–400 bp, 400–600 bp), with the mean value plotted. Finally, small indels (<30 bp) in the Por and Jean strains were detected with the UnifiedGenotyper (−glm INDEL) in GATK64 for positions with more than 20× coverage. Genetic differentiation for indels was calculated with the classical formula F  = (H −H )/H , where H is the average expected heterozygosity according to Hardy–Weinberg Equilibrium (HWE) in the two subpopulations and H is the expected heterozygosity in HWE of the hypothetical combined total population. If more than two alleles were present, only the two most abundant alleles were considered in the calculation of F . Gene models from the automated annotation were considered candidate genes, if they fulfilled the following criteria. (1) The gene was located within the reference sequence corresponding to the QTL confidence intervals as determined for the Por and Jean strains. (2) The gene contained a strongly differentiated SNP or small indel or it was directly adjacent to such a SNP or small indel (F  ≥ 0.8 for Por versus Jean, that is, the strains used in QTL mapping). This resulted in a preliminary list of 133 genes based on the comparison between Por and Jean (Supplementary Table 6). These candidate genes were narrowed down based on their overlap with genomic 5-kb windows, for which genetic differentiation between five European timing strains correlated with their timing differences (Fig. 1a, Extended Data Fig. 5a, b and Supplementary Table 9). The location and putative effects of the SNPs and indels relative to the gene models were assessed with SNPeff70 (−ud 0, otherwise default parameters; Extended Data Fig. 5c, d and Supplementary Tables 6, 9). For Gene Ontology (GO) term analysis, all C. marinus gene models with putative orthologues in the UniProtKB/Swiss-Prot and non-redundant protein sequences (nr) databases based on reciprocal best BLAST hits (see above) were annotated with the GO terms of their detected orthologues (6,837 gene models). Paralogues were not annotated. The enrichment of candidate SNPs and indels (F  ≥ 0.8 between Por and Jean) in specific GO terms was tested with SNP2GO71 (min.regions = 1, otherwise default parameters). Hyper-geometric sampling was applied to test if individual genes of a GO term or a whole pathway of genes are enriched for SNPs (Supplementary Table 7). RNA-seq data of the Por and Jean strains for CaMKII.1 were obtained from the larval RNA sequencing experiment described above. Besides four assembled full-length transcripts (RA–RD) from RNA-seq and assembled EST libraries, additional partial transcripts (RE–RO) were identified by PCR amplification (for PCR primers see Supplementary Table 15), gel extraction (QIAquick Gel Extraction Kit, Qiagen), cloning with the CloneJET PCR Cloning Kit (Thermo Scientific) and Sanger sequencing with pJET1.2 primers (LGC Genomics & Microsynth). cDNA was prepared from RNA extracted from third instar larvae of the Por and Jean laboratory strains (RNA extraction with RNeasy Plus Mini Kit, Qiagen; reverse transcription with QuantiTect Reverse Transcription Kit, Qiagen). qPCR was performed with variant-specific primers and actin was used as a control gene (Supplementary Table 16). cDNA was obtained from independent pools of 20 third instar larvae of the Por and Jean strains. Sample size was ten pools per strain to cover different time points during the day and to test for reproducibility (two samples each at zeitgeber times 0, 4, 8, 16 and 20; for one Por sample extraction failed; RNA extraction and reverse transcription as above). qPCR was performed with Power SYBR Green PCR Master Mix on a StepOnePlus Real Time System (both Applied Biosystems). Fold-changes were calculated according to ref. 72 in a custom excel sheet. The assumption of equal variance was violated for the RD comparison (F-test) and the assumption of normal distribution was violated for the data of RA and RC in the Por strain (Shapiro–Wilk normality test), possibly reflecting circadian effects in the samples from different times of day. Thus, expression differences were assessed for significance in a two-tailed Wilcoxon rank-sum test (wilcox.test in R66). Holm correction73 was used for multiple testing (default in p.adjust function of R). PCR fragments containing the CaMKII.1 linker region (exons 10–15) were amplified from genomic Por or Jean DNA, respectively, with primers CaMKII-Sc61-F-344112 and CaMKII-Sc61-R-351298 (Supplementary Table 15), cloned with the CloneJET PCR Cloning Kit (Thermo Scientific), transferred into the pcDNA3.1+ vector using NotI and XbaI (Thermo Scientific). These constructs were transfected into D. melanogaster S2R+ cells and RNA was prepared 48 h after transfection. After DNase digestion, isoform expression was analysed by radioactive, splicing-sensitive RT–PCR (primers in Supplementary Table 17) and phosphorimager quantification as described74. Identity of isoforms is based on size and sequencing of PCR products. To test for reproducibility, there were seven biological replicates (raw data in Supplementary Table 18). As the assumptions of equal variance (F-test) and normal distribution of data (Shapiro–Wilk normality test) were not violated, the significance of expression differences was assessed in unpaired, two-sided two-sample t-tests. Holm correction73 was used for multiple testing (default in p.adjust function of R). S2R+ cells were obtained from the laboratory of S. Sigrist, regularly authenticated by morphology and routinely tested for absence of mycoplasma contamination. The entire experiment was reproduced several months later with three biological replicates (raw data in Supplementary Table 18). Firefly luciferase is driven from a period 3X69 promoter under control of the CLOCK and CYCLE protein19, 21. The D. melanogaster pAc–clk construct was obtained from F. Rouyer, pCopia–Renilla luciferase and period 3X69–luc reporter constructs from M. Rosbash, a [Ca2+]-independent mouse CaMKIIT286D was provided by M. Mayford. The CaMKII inhibitor KN-93 was purchased from Abcam (#ab120980). C. marinus Cyc, C. marinus Clk and C. marinus CaMKII.1–RD were cloned into the pAc5.1/V5–His A plasmid (Invitrogen) with stop codons before the tag. The Q5 Site-Directed Mutagenesis Kit (NEB) was used to make kinase-dead and [Ca2+]-independent versions of C. marinus CaMKII.1–RD (for primers, see Supplementary Table 17). D. melanogaster S2 cells (Invitrogen) were cultured at 25 °C in Schneider’s D. melanogaster medium (Lonza) supplemented with fetal bovine serum (FBS, 10%, heat-inactivated), penicillin (100 U ml−1), streptomycin (100 μg ml−1) and 2 mM l-glutamine; Sigma). Cells were seeded into 24-well plates (800,000 cells per well) and transfected with Effectene transfection reagent (Qiagen) according to the manufacturer’s instructions. Experiment with mouse [Ca2+]-independent CaMKII: 25 ng pCopia–Renilla, 10 ng period 3X69–luc, 0.5 ng D. melanogaster pAc–clk, 200 ng mouse pAc–CaMKIIT286D. Experiment with CaMKII inhibitor KN-93: 25 ng pCopia–Renilla, 10 ng period 3X69–luc, 0.5 ng D. melanogaster pAc–clk, various amounts of KN-93. Experiment with C. marinus genes: 25 ng pCopia–Renilla, 10 ng period 3X69–luc, 100 ng C. marinus pAc–cyc, 100 ng C. marinus pAc–clk, 200 ng C. marinus CaMKII.1–RDK42R or 200 ng C. marinus CaMKII.1–RDT286D. In all experiments, the transfection mix was filled up with empty pAc5.1/V5–His A vector to a total of 435 ng DNA per well. After 48 h, cells were washed with PBS and lysed with Passive Lysis Buffer (Promega). Luciferase activities were determined on a Synergy H1 plate reader (Biotek) using a Dual-Luciferase Reporter Assay System (Promega). For each biological replicate three independent cell lysates were measured and their mean value determined. Firefly luciferase activity was normalized to Renilla luciferase activity and values were normalized to controls transfected with D. melanogaster pAc–clk or C. marinus pAc–clk and C. marinus pAc–cyc, respectively. S2 cells (Invitrogen/Life Technologies, Cat.no. R690-07) were regularly authenticated by morphology and routinely tested for absence of mycoplasma contamination (Lonza MycoAlert). Sample size was chosen to test for reproducibility. For circadian free-run experiments, culture boxes of the Por, He and Jean strains were transferred from light–dark cycle (16:8) to constant dim light (light–light cycle, about 100 lx). Emerging adults were collected in 1-h intervals by a custom made C. marinus fraction collector (similar to those described in ref. 75) and counted once a day. Because collection was automated, the experimenter had no influence on the results and blinding was not necessary. As the circalunar clock restricts adult emergence to a few days, the circadian emergence rhythm can only be assessed over a few days. Several culture boxes were transferred to a light–light cycle at different time points. The resulting emergence data were combined for each strain using the switch to a light–light cycle as a common reference point. We used the maximum number of available individuals. Free-running period was calculated as the mean interval between subsequent emergence peaks, weighting each peak by the number of individuals. All sequence data are deposited in the European Nucleotide Archive (ENA) under PRJEB8339. The reference genome is also on ClunioBase (http://cluniobase.cibiv.univie.ac.at). Machine readable super-scaffolding data and the computer source code for the removal of repeated edges are supplied as source data files.

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