{"text":"AGE were run using a k-mer size of 31 before also a national health medical grant 100009  a final set of 3 iterations were run with a k-mer size of 21.    Abbreviations  bp: base pairs; IMAGE: Iteratively Mapping and Assembly for Gap Elimination; PE: paired end.   Authors' contributions  IJT, TDO and MB conceived the project and wrote the manuscript. The sequencing project was directed by MB. Assemblies and the IMAGE pipeline were produced by IJT. The data analysis was performed by IJT and TDO. All authors read and approved the final manuscript.   Supplementary Material   Additional file 1  Comparison of gap closing in the Echinococcus  assemblies.    Click here for file      Acknowledgements  We thank Darren Grafham, Martin Hunt and Adam Reid for comments and reviewing the manuscript. We thank Rob Kinsley for providing Salmonella  sequences. We thank Karen Brooks and Helen Beasley for designing the oligonucleotide primers and manually checking the agreements between the PCR products and Illumina contigs. We thank Nancy Holroyd for coordinating the helminth sequencing projects. CAL Genbank Reference CBS 132990 Ss54 S. brasiliensis Feline Brazil JQ041903 [9, 25, 45] CBS 132021 5110 protein concentration for microplate sensitization, whole cellular proteins from S. brasiliensis (CBS 132990 and weight markers (Protein Benchmark, Invitrogen). For immunoblotting, proteins (10 μg) from strains CBS 132990, CBS measure the degree of concordance of the results from preparations from strains CBS 132990, CBS 132021, CBS 49): S. brasiliensis CBS 132990, median 1.313 OD, 95% CI 1.262–1.489 OD; S. brasiliensis CBS 132021, median ranges: S. brasiliensis CBS 132990, median 0.2640 OD, 95% CI 0.2592–0.3098 OD; S. brasiliensis CBS 132021, median values yielded 100% specificity and sensitivity: S. brasiliensis CBS 132990, 0.377 OD; S. brasiliensis CBS 132021 18 Serology of Sporotrichosis Fig 3. Representative immunoblot of S. brasiliensis (CBS 132990 and CBS 132021) and in the S. schenckii proteome. The major ntigenic S. brasiliensis molecules (CBS 132990 and CBS 132021) recognize (C) Diversity of recognition of S. brasiliensis antigens (outer ring, CBS 132990; inner ring, CBS 132021). (D) specificity and sensitivity: (A) S. brasiliensis (Sb) CBS 132990, 0.377 OD; (B) S. brasiliensis CBS 132021, 0.363 This work was supported by the Wellcome Trust (grant WT 085775/Z/08/Z).  Harismendy O Ng PC Strausberg RL Wang X Stockwell TB Beeson KY Schork NJ Murray SS Topol EJ Levy S Frazer KA Evaluation of next generation sequencing platforms for population targeted sequencing studies. Genome Biol 2009 10 R32 10.1186/gb-2009-10-3-r3219327155 Zerbino DR Birney E Velvet: algorithms for de novo  short read assembly using de Bruijn graphs. Genome Res 2008 18 821 829 10.1101/gr.074492.10718349386 Simpson JT Wong K Jackman SD Schein JE Jones SJ Birol I ABySS: a parallel assembler for short read sequence data. Genome Res 2009 19 1117 1123 10.1101/gr.089532.10819251739 Li R Zhu H Ruan J Qian W Fang X Shi Z Li Y Li S Shan G Kristiansen K Yang H Wang J De novo  assembly of human genomes with massively parallel short read sequencing. Genome Res 2009 20 265 272 10.1101/gr.097261.10920019144 Maccallum I Przybylski D Gnerre S Burton J Shlyakhter I Gnirke A Malek J McKernan K Ranade S Shea TP Williams L Young S Nusbaum C Jaffe DB ALLPATHS 2: small genomes assembled accurately and with high continuity from short paired reads. Genome Biol 2009 10 R103 10.1186/gb-2009-10-10-r10319796385 Diguistini S Liao NY Platt D Robertson G Seidel M Chan SK Docking TR Birol I Holt RA Hirst M Mardis E Marra MA Hamelin RC Bohlmann J Breuil C Jones SJ De novo  genome sequence assembly of a filamentous fungus using Sanger, 454 and Illumina sequence data. Genome Biol 2009 10 R94 10.1186/gb-2009-10-9-r9419747388 Reinhardt JA Baltrus DA Nishimura MT Jeck WR Jones CD Dangl JL De novo  assembly using low-coverage short read sequenc","id":"PMC"}
{"text":"Acknowledgements  We thank Darren Grafham, Martin Hunt and Adam Reid for comments and reviewing the manuscript. We thank Rob Kinsley for providing Salmonella  sequences. We thank Karen Brooks and Helen Beasley for designing the oligonucleotide primers and manually checking the agreements between the PCR products and Illumina contigs. We thank Nancy Holroyd for coordinating the helminth sequencing projects. This work was supported by the Wellcome Trust (grant WT 085775/Z/08/Z). This research was partially funded by the EPSRC Grant EP/C542150/1. Harismendy O Ng PC Strausberg RL Wang X Stockwell TB Beeson KY Schork NJ Murray SS Topol EJ Levy S Frazer KA Evaluation of next generation sequencing platforms for population targeted sequencing studies. Genome Biol 2009 10 R32 10.1186/gb-2009-10-3-r3219327155 Zerbino DR Birney E Velvet: algorithms for de novo  short read assembly using de Bruijn graphs. Genome Res 2008 18 821 829 10.1101/gr.074492.10718349386 Simpson JT Wong K Jackman SD Schein JE Jones SJ Birol I ABySS: a parallel assembler for short read sequence data. Genome Res 2009 19 1117 1123 10.1101/gr.089532.10819251739 Li R Zhu H Ruan J Qian W Fang X Shi Z Li Y Li S Shan G Kristiansen K Yang H Wang J De novo  assembly of human genomes with massively parallel short read sequencing. Genome Res 2009 20 265 272 10.1101/gr.097261.10920019144 Maccallum I Przybylski D Gnerre S Burton J Shlyakhter I Gnirke A Malek J McKernan K Ranade S Shea TP Williams L Young S Nusbaum C Jaffe DB ALLPATHS 2: small genomes assembled accurately and with high continuity from short paired reads.", "id":"RCUK"}
{"text":"INTRODUCTION Huntington's F 1703-B12 disease (HD) is an autosomal dominant late-onset neurodegenerative disorder with a mean age of onset of 40 years. Symptoms include psychiatric disturbances, motor disorders, cognitive decline and weight loss. Disease duration is 15–20 years and there are no effective disease-modifying treatments ( 1 ). The disease is caused by an expanded CAG trinucleotide repeat in the HD gene that is translated into a polyglutamine (polyQ) repeat in the huntingtin (Htt) protein ( 2 ). Neuropathologically, HD is characterized by a generalized brain atrophy as well as neuronal cell loss in the striatum, cortex and other brain regions. Intracellular polyQ-containing aggregates are deposited throughout the neuropil and as inclusions in neuronal nuclei ( 3 , 4 ). PolyQ aggregates formed in vitro from recombinant protein comprise a range of oligomeric, proto-fibrillar and fibrillar structures ( 5 – 7 ). However, it is not known whether these reflect the oligomeric polyQ structures that form in vivo in HD patients or in HD mouse models. Similarly, although the genetic and pharmacological manipulation of polyQ aggregates in vitro and in invertebrate disease models has suggested that either the prevention of aggregate formation or their partition into less toxic structures PIK01--117193 can have beneficial consequences ( 5 , 8 – 12 ), the role that polyQ aggregates play in disease pathology remains unclear. The ability to monitor the effects of aggregate manipulation in HD mouse models would help to determine the relevance of experiments performed in simple model systems. To this end, it is essential that the aggregate load in mouse tissues can be quantified and that the aggregate species that form in vivo can be identified. We utilized two HD mouse models that were generated by very different approaches. The R6/2 mouse is transgenic for a human exon 1 Htt protein which in our colony has approximately 200Q ( 13 ). These mice develop an early-onset phenotype with rapid disease progression and as a consequence can realistically be used as a therapeutic screening tool ( 14 ). In our R6/2 colony, nuclear inclusions can be readily detected by immunohistochemistry in the cerebral cortex, striatum and hippocampus by 3 weeks of age ( 15 , 16 ), RotaRod impairment is apparent by 6 weeks and end-stage disease occurs at 15 weeks. The Hdh Q150 knock-in mouse is a more genetically precise model of the human disease, and carries approximately 150Q which has been inserted into the mouse Hd gene ( Hdh ) ( 17 ). In our Hdh _Q150/Q150 colony, nuclear inclusions were detected by immunohistochemistry in the striatum and hippocampus by 6 months and the cortex by 8 months ( 18 ), an impaired RotaRod performance was apparent by 18 months of age and end-stage disease occurs at around 22 months ( 18 ). The Hdh Q150 mice develop a phenotype that is remarkably similar to that found in R6/2 except that onset is much delayed and the disease progresses much more slowly over a period of 22 months ( 18 , 19 ). At the level of light microscopy, a complex distribution of aggregates in the form of nuclear inclusions and cytoplasmic aggregates are widely distributed throughout the brains of both models ( 18 ). Quantification of the aggregate load in mouse tissues has primarily involved counting the number of striatal nuclear inclusions and measuring their diameter. However, this only samples a subset of the aggregate species in one small brain region and more quantitative approaches that are less work-intensive are desperately needed. We have previously used the filter retardation assay to detect aggregates in mouse tissues ( 20 ) but we have been unsuccessful in optimizing this as an in vivo screening tool owing to signal variability. However, even if these technical difficulties were overcome, this approach would still have the disadvantage of only measuring the presence of aggregates that are larger than the cellulose acetate membrane pore size and therefore retained on the membrane. Here we describe the use of the Seprion ligand to establish an enzyme-linked immunosorbent assay (ELISA)-based method that provides a rapid, highly sensitive assay with good statistical power to detect changes in aggregate load in the brains of mouse models of HD. We demonstrate that the ligand captures a remarkably similar range of oligomeric, proto-fibrillar and fibrillar aggregates from the brains of both the R6/2 and Hdh Q50 mouse models and that these are comparable to those generated from recombinant proteins in vitro . Using atomic force microscopy (AFM) we show that the dimensions of nanometre globular aggregates from the R6/2 and Hdh Q150 knock-in brains are identical to those generated by the aggregation of recombinant exon1 Htt proteins containing just 46 and 53 polyQs. Finally, antibodies that detect exon 1 Htt epitopes differentially recognize the ligand-captured material on sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS–PAGE) gels. RESULTS The Seprion ligand ELISA provides a highly quantitative assay for measuring polyQ aggregate load in Huntington's disease mouse tissue The Seprion ligand has previously been used to isolate and quantify aggregated forms of the prion protein, Prp_Sc ( 21 , 22 ). It is a high molecular weight polymeric ligand that consists of repeating charged and hydrophobic chemical groups that interact with similar repeating groups that occur on aggregated proteins. The selectivity for aggregated proteins is based on the arrangement of large numbers of polar and hydrophobic regions in aggregated proteins which occur to a much lesser extent in a single unaggregated protein molecule. We have used the Seprion ligand to develop an ELISA-based plate assay by which aggregated Htt is captured from tissue lysates and detected by immunoprobing with the S830 antibody that was raised against the N-terminal exon 1 Htt protein ( 23 ). We quantified the aggregate load in each of the five brain regions from female R6/2 mice at 2, 4, 6, 8 and 12 weeks of age. The Seprion ligand extracted statistically significant levels of aggregates from the striatum and hippocampus at 2 weeks of age, the cerebral cortex and brain stem at 4 weeks and cerebellum at 6 weeks (Fig. 1 A). Only signals corresponding to background levels were measured in wild-type (WT) samples, equivalent to those obtained with capture-buffer only controls. The ELISA readings have proved to be highly reproducible between experiments, e.g. there was no difference in the aggregate load measured in the cortex from four different series of 12-week-old R6/2 mice using different batches of ligand-coated plates over a period of 2 years ( F _(3,21) = 2.121, P = 0.133). We have previously shown that nuclear inclusions form in a number of R6/2 peripheral tissues ( 24 ). We applied the Seprion ELISA to quantify the corresponding aggregate levels and found that statistically significant amounts could be detected by 8 weeks in muscle and by 12 weeks in pancreas and liver (Fig. 1 B). Therefore, the Seprion ELISA might provide a highly sensitive method of quantifying the level of aggregated polyQ in tissues from mouse models of HD. This assay has great potential for use as an outcome measure either in preclinical efficacy trials to test the effect of potential therapeutic interventions or in mice with genetic modifications that might modulate HD-related mouse phenotypes. For example, for the purpose of a pharmacodynamic trial in which a compound has been administered to R6/2 mice from 4 to 8 weeks of age, power calculations ( 25 ) indicate that as few as eight mice would be sufficient to give an 80% chance of detecting a 30–50% reduction in aggregate load in brain regions ( P < 0.05; Fig. 1 C). Figure 1. Seprion ligand quantification of aggregate load in tissues from HD mouse models. Quantification of aggregate levels in brain regions ( A ) and peripheral tissues ( B ) of R6/2 mice. ( C ) Power analysis indicating the number of R6/2 mice required to have an 80% chance of detecting a specific percentage reduction in aggregate load in response to a therapeutic intervention initiated at 4 weeks of age and terminated at either 8 weeks or 12 weeks of age ( P > 0.05). Quantification of aggregate levels in brain regions ( D ) and peripheral tissues ( E ) of Hdh _Q150/Q150 mice. In all cases, n = 6/genotype/age and the age at which statistically significant aggregate levels can first be detected is indicated by the corresponding P -value. Black bars = R6/2 or Hdh Q150, gray bars = wild-type. Ctx = cerebral cortex; Hipp = hippocampus; Str = striatum; Cerb = cerebellum; Br St = brain stem; Buf = buffer. The aggregate pathology in the R6/2 mice occurs throughout the brain and in many peripheral tissues. We had assumed that this widespread distribution occurred because they express a small N-terminal fragment of mutant Htt. Therefore, we were surprised to find that at end-stage disease, polyQ aggregates in the form of nuclear inclusions and cytoplasmic aggregates are present in all brain regions of homozygous Hdh _Q150/Q150 knock-in mice ( 18 ). Similarly, we have recently demonstrated that the distribution of polyQ aggregates throughout the peripheral tissues of 12–14 week R6/2 mice and 22 month Hdh Q150 knock-in mice is almost identical (H. Moffitt, G. McPhail, B. Woodman, C. Hobbs and G. Bates, manuscript in preparation) suggesting that HD pathology may not be restricted to the CNS in HD patients. Therefore, we applied the Seprion ELISA to measure the level of polyQ aggregation that had accumulated in the cerebral cortex, hippocampus and brain stem from Hdh _Q150/Q150 mice aged 6, 10, 18 and 22 months (Fig. 1 D). The striata and cerebella from this series of tissues had been used for RNA analyses ( 18 ). As with the R6/2 mice, statistically significant levels were present in the hippocampus (6 months) before the cortex and brain stem (10 months). These ages correspond to those at which inclusions are apparent in the brain by light microscopy ( 18 ). In the periphery, statistically significant levels of aggregates could be detected in muscle and liver at 22 months (Fig. 1 E). The microplate readings were lower for the Hdh _Q150/Q150 tissues than for the R6/2 tissues. However, the difference in these values does not necessary reflect differences in the levels of aggregates that have accumulated in the tissues of the two models. The S830 antibody has a different affinity to the mutated versions of human Htt (in the R6/2 mouse) and mouse Htt (in the Hdh Q150 knock-in mice). Immuno-EM reveals diverse oligomeric and fibrillar Htt species in brain tissue from Huntington's disease mouse models We employed immuno-electron microscopy (EM) to investigate the morphology of the ligand-isolated aggregated Htt species. Aggregates were captured from cortical lysates by Seprion ligand-coated magnetic beads and eluted onto EM grids, processed for transmission EM and immunoprobed with gold-labelled MW8 ( 26 ), MW1 ( 26 ) or 3B5H10 ( 27 ). Bead capture was performed on cortices from R6/2 mice aged 2, 4, 6 and 12 weeks and from Hdh _Q150/Q150 mice aged 2, 3, 4 and 22 months as well as on the cortices of matched WT littermates at each time point. The number of mice examined is summarized in Table 1 . While in the case of R6/2 mice, we chose time points that span the course of the disease, for the Hdh _Q150/Q150 we instead focussed on young mice, asking how soon aggregate structures can be detected, but also included mice at end-stage disease for comparison with late-stage R6/2. Hdh _Q150/Q150 mice aged 2, 3 and 4 months would all correspond to R6/2 mice of less than 4 weeks of age with respect to the stage of disease. Table 1. Number of R6/2 and wild-type (WT) mice used for the electron microscopy and SDS–PAGE analyses Immunolabelling of bead captured and eluted cortical aggregates from both R6/2 and Hdh _Q150/Q150 cortices with MW8 consistently identified fibrillar structures. The fibrils captured from the R6/2 series of tissues increased in both amount and size as a function of disease progression and could be detected as early as 2 weeks of age (Fig. 2 A). In the case of the Hdh _Q150/Q150 knock-in mice, fibrils were prominent at 22 months and were isolated from the cortex of mice as young as 2 months (Fig. 2 B). The antibodies MW1 and 3B5H10 detected a variety of small aggregate structures including oligomers and protofibrils in both mouse models (Fig. 2 A and B). The complete spectrum of captured aggregate structures, the age of mouse from which each was isolated, and the antibodies with which they were detected is summarized in Figure 3 . The Seprion ligand captured a range of oligomeric/proto-fibrillar (Fig. 3 B–E) and fibrillar (Fig. 3 F–I) structures. Large filamentous aggregates have frequently been generated from polyQ peptides ( 28 , 29 ) and exon 1 Htt proteins ( 6 , 7 , 30 , 31 ) in vitro and visualized by EM. In one case, EM has been used to describe fibrillar structures purified from the brains of an inducible HD mouse model by gradient fractionation ( 32 ). The filamentous/fibrillar aggregates isolated by the Seprion ligand (Fig. 3 F–I were in all cases recognized by MW8, but MW1 and 3B5H10 epitopes were only present on the smaller, immature fibrils (Fig. 3 F). Figure 2. Immuno-EM analysis of captured material from R6/2 and Hdh _Q150/Q150 cortex. Representative examples of immunogold labelling of Htt aggregates with MW8, MW1 and 3B5H10 captured from the cortex of ( A ) R6/2 mice aged 2 and 12 weeks of age and ( B ) Hdh _Q150/Q150 mice aged 2 and 22 months of age. MW8 immunolabels fibrillar structures at each age in both the R6/2 and Hdh _Q150/Q150 tissue. Oligomers and protofibrils (A) and oligomers (B) detected by MW1 and protofibrils (A) and oligomers (B) detected by 3B5H10 are shown. Scale bar = 100 nm. Figure 3. Variation in the oligomeric and fibrillar structures isolated from R6/2 and Hdh _Q150/Q150 brains before phenotype onset and at late-stage disease. ( A ) Immunolabelled ‘shadows’, ( B–E ) oligomeric/proto-fibrillar structures and ( F–I ) immature fibrils and fibrillar structures that have been consistently captured by the Seprion ligand bead-captured material as identified by transmission EM and immunogold-labelling. The right-hand table indicates the age at which a structure was identified in each of the mouse models and if present, whether it was associated with immunogold labelling with MW1, 3B5H10 or MW8. Scale bar = 100 nm. The structures illustrated in Figure 3 A–E have not previously been isolated from in vivo tissues. Those shown in panels A–D were captured from both R6/2 and Hdh _Q150/Q150 brains, whereas the proto-fibrillar bundles illustrated in (E) were only observed in material extracted from Hdh _Q150/Q150 knock-in mice. The immunolabelled shadows depicted in Figure 3 A were captured from R6/2 and Hdh _Q150/Q150 brains, were detected with both MW1 and 3B5H10 and never seen in the material captured from WT mice. However, whether they represent an aggregated form of the protein is not clear. The structures shown in Figure 3 B and C have been formed by in vitro aggregation of 44Q exon 1 Htt ( 6 ), of a truncated 30Q exon 1 protein ( 7 ), polyQ peptides ( 28 ) and of Aβ42 ( 30 ) and termed oligomers ( 6 , 30 ) and oligomers/protofibrils ( 7 ). Those illustrated in Figure 3 D and E have been generated in vitro from 44Q exon 1 Htt ( 6 ), and the truncated 30Q exon 1 protein ( 7 ) and termed oligomers and protofibrils. We used electron tomography to reveal the three-dimensional structure of the protofibrillar bundles in Figure 3 D (Fig. 4 A) and the thin filaments in Figure 3 G (Fig. 4 B). Figure 4 presents still images of the three-dimensional structures shown in the movies in Supplementary Material, Figure S1 . Figure 4. Still images of the electron tomography of oligomeric/proto-fibrillar structures captured from R6/2 and Hdh _Q150/Q150 brains for which the three-dimensional structure is shown in Supplementary Material, Figure S1 . ( A ) Electron tomography of oligomeric structures illustrated in Figure 3 D and B of the filamentous structures illustrated in Figure 3 G immunolabelled with MW8. Globular nanometre oligomers isolated from the R6/2 and Hdh _Q150/Q150 mouse brains have identical dimensions as those generated from exon 1 Htt proteins in vitro We applied AFM to provide a more quantitative comparison of the oligomeric aggregates that were captured by the Seprion ligand. We discovered empirically that elution with 100 m m KCl (as described in the Materials and Methods) differentially eluted globular nanometre oligomers, while other aggregate species remained bound to the ligand. We used western blotting to demonstrate that the eluted material was an oligomeric form of Htt ( Supplementary Material, Figure S2 ). The globular oligomers appeared to be very similar to those that had been previously generated in vitro ( 5 , 6 , 31 ) and, therefore, we focussed our AFM analysis on the quantification of these structures rather than on fibrillar structures which we had identified and characterized extensively by EM (Figures 2 and 3 ). Globular oligomers were captured from cortical tissue from R6/2 mice aged 2, 4, 6 and 12 weeks ( n = 2/per age), from Hdh _Q150/Q150 aged 2, 3, 8 and 22 months ( n = 2/age) and from matched WT controls. Particles of approximately 20–40 nm in diameter were eluted from ligand-coated beads from both R6/2 and Hdh _Q150/Q150 brains at all ages tested (Fig. 5 A). No oligomeric structures were eluted from WT tissue. For comparison, oligomers were generated in vitro by the aggregation of 2 µ m recombinant exon 1 Htt proteins with either 53Q or 46Q for 1 h (Fig. 5 A). It was striking that the dimensions of the globular oligomers that were eluted from ligand-captured material from both R6/2 and Hdh _Q150/Q150 tissue was found to be identical to those generated from the incubation of the recombinant exon 1 Htt proteins in vitro (Fig. 5 B). Figure 5. AFM analysis of nanometre globular aggregates from R6/2 and Hdh _Q150/Q150 brains. ( A ) AFM of Seprion ligand-captured material from both R6/2 and Hdh _Q150/Q150 cortex at the ages indicated fractionated to resolve nanometre globular oligomers. Observed aggregates were similar to those generated by the in vitro incubation of exon 1 Htt proteins with 53Q or 46Q at 2 µ m for 1 h. Scale bar = 400 nm. ( B ) Histograms collating the height, diameter, volume and aspect ratio (longest width/shortest width) of the R6/2 and Hdh _Q150/Q150 aggregates measured at all ages. There is a remarkable similarity in the dimensions of the aggregates isolated from the R6/2 and Hdh _Q150/Q150 mice. These are comparable to those generated by the aggregation of 2 µ m exon 1 Htt proteins with 53Q or 46Q in vitro for 1 h. The Seprion ligand captures Htt species that resolve as monomers on SDS–PAGE We employed SDS–PAGE to investigate the detergent-soluble properties of the mutant Htt species that were eluted from the Seprion ligand after capture from cortical lysates using ligand-coated magnetic beads. Eluted material from R6/2 mice aged 2, 4, 6 and 12 weeks of age was fractionated by SDS–PAGE alongside age-matched tissue lysates and immunoprobed with a series of antibodies: S830, MW1, MW8 and 3B5H10 (Fig. 6 ). In tissue lysates, all four antibodies detected the soluble R6/2 transprotein monomer that became less intense with age because of its sequestration into polyQ aggregates. The migration of the transprotein varied between lysates because the CAG repeat is unstable on transmission and therefore the polyQ repeat length differed between mice. Although an exon 1 Htt protein that carries a polyQ repeat of approximately 200Q is approximately 30 kDa in size, its migration by SDS–PAGE was retarded to approximately 80 kDa by the polyQ tract. Both S830 and 3B5H10 (Fig. 6 A, D, E and F), and in some cases MW1 (Fig. 6 C), detected a high molecular weight fragment in cortical lysates that migrated at the top of the resolving gel and rapidly diminished with age (as indicated by asterisk). MW1 detected the soluble transprotein in 4 and 6 week lysates and at 12 weeks, in most experiments, it detected a doublet above which there is a smear overlaying a ladder of fragments (Fig. 6 G). From 6 weeks of age onwards, S830 and MW8 (Fig. 6 A and B), but not MW1 or 3B5H10, detected detergent-insoluble aggregates that were retained in the stacking gel. Figure 6. SDS–PAGE and immunoblotting of Seprion bead-captured aggregates from R6/2 cortex. Seprion ligand bead-captured material was fractionated by 10% SDS–PAGE alongside the corresponding mouse lysates. Blots were immunoprobed with S830 ( A ), MW8 ( B ), MW1 ( C,G ) or 3B5H10 ( D–F ) antibodies. In (C) and (D) material had been captured from the same lysates, fractionated on two gels and subsequently immunoprobed with MW1 (C) and 3B5H10 (D). The blot in (C) was stripped and reprobed with 3B5H10 (F). Asterisks denote high molecular bands detected by S830, 3B5H10 and MW1 that enter the resolving gel. Arrows indicate fragments that resolve at a size similar to monomeric Htt that are differentially recognized by the Htt antibodies. T = R6/2 transgenic; Wt = wild-type; B = buffer; W = well; In = interface between the stacking and resolving gel. After bead-capture and SDS–PAGE, S830 and MW8 only detected the detergent-insoluble aggregates in the stacking gel, indicating that the soluble protein had not been extracted by the Seprion ligand (Fig. 6 A and B). In contrast, MW1 and 3B5H10 detected fragments in the bead-captured material that resolved at a similar size to the soluble transprotein, but that were not detected by either S830 or MW8 (Fig. 6 C–G). In material captured from the same lysates, MW1 and 3B5H10 produced comparable signals on western blots (Fig. 6 C–E). The signals obtained with MW1 were always prominent in lysates from 4-week-old mice (>15 separate experiments). However, the ligand captured Htt species that resolve as a soluble monomer were not only seen at younger ages and were also captured from lysates of 6, 8 or 12 week R6/2 mice as detected by 3B5H10 (Fig. 6 F). These fragments were never detected with S830 or MW8. The consistency of the MW1 results make it unlikely that an interaction between soluble exon 1 Htt and the ligand is causing the exon 1 protein to adopt a structure (retained upon SDS–PAGE), as if that were the case, there would be no reason to expect their detection to be disease-stage specific. Instead, the Seprion ligand has extracted either aggregated Htt species or misfolded monomers, which upon SDS–PAGE exhibited a comparable migration to that of the soluble monomer but are differentially recognized by antibodies that detect the exon 1 Htt protein. DISCUSSION We have shown that the Seprion ligand can be used to isolate and characterize aggregated Htt species that form in mouse models of HD. Using EM and AFM we have demonstrated that the brains of both the R6/2 and Hdh Q150 knock-in mouse models contain a diverse and comparable range of Htt aggregate structures. The oligomeric and fibrillar aggregates that were captured by the Seprion ligand were remarkably similar to those that have previously been generated through the aggregation of exon 1 Htt proteins in vitro ( 5 , 7 , 33 , 34 ). This similarity was particularly striking in the case of our AFM analysis where the dimensions of the nanometre globular oligomers isolated from the R6/2 and Hdh _Q150/Q150 brains were practically identical to those generated from recombinant exon 1 Htt in vitro . This finding was unexpected given that Hdh Q150 knock-in mice express full-length mouse Htt with approximately 150Q, R6/2 mice express a human exon 1 Htt transgene with approximately 200Q and the recombinant proteins were human exon 1 Htt with 46Q and 53Q. However, this observation is in keeping with our recent demonstration that the smallest N-terminal fragment generated from full-length Htt in the Hdh Q150 knock-in mice is an exon 1 Htt protein (C. Landles, K. Sathasivam, A. Weiss, B. Woodman, H. Moffitt, S. Finkbeiner, B. Sun, J. Gafni, L. Ellerby, Y. Trottier, W. Richards, A. Osmand, P. Paganetti and G. Bates, manuscript in preparation), and demonstrates that the wide variation in polyQ length carried by these exon 1 proteins does not have a detectable impact on the dimensions of the globular oligomers. We extracted a diverse spectrum of oligomeric and fibrillar structures from the brains of both the R6/2 and Hdh Q150 mouse models. In the case of R6/2, we analysed brain tissue from mice aged 2, 4, 6 and 12 weeks of age, spanning the course of disease from a presymptomatic state to pronounced symptomatology. The entire spectrum of aggregate species was extracted from the brain tissue at each of these ages. However, the amount of fibrillar material increased considerably with disease progression to the extent that the EM grids were covered in fibrils from R6/2 mice at 12 weeks and Hdh _Q150/Q150 mice at 22 months. At late-stage disease the high density of fibrillar aggregates most likely masked the presence of oligomeric and proto-fibrillar structures making it difficult to assess their relative contributions. Our analysis of Hdh _Q150/Q150 mice focussed on very early time-points (2, 3 and 4 months), all of which precede overt symptomatology by several months, as we were interested in determining how early aggregated structures can be identified in these mice. Surprisingly, we were able to extract aggregate structures from Hdh _Q150/Q150 brains as early as 2 months of age. Fibrillar aggregates have previously been imaged in tissue sections from HD post-mortem brains and HD mouse models ( 3 , 15 , 35 ) by EM, and therefore, we can be confident that the fibrillar structures that we have extracted from tissue sections exist in vivo . However, without being able to image mutant Htt oligomers and proto-fibrils in tissue sections, we cannot be certain that the aggregates isolated by the Seprion ligand have the same structure as those that form in vivo . To address this, we propose that the complexity of the aggregate structures that have been isolated, and the consistent variability in their relative proportions at different stages of disease, make it extremely unlikely that they have been generated through an interaction between the ligand and the soluble mutant Htt protein. In addition, as well as being very comparable to those that have been generated in vitro from exon 1 mutant Htt constructs they are also remarkably similar to those formed by other amyloidogenic proteins that have been studied in detail ( 36 – 39 ). In this study, we used a panel of antibodies that recognize epitopes within the exon 1 Htt protein: MW8, MW1, 3B5H10 and S830. In all cases, these antibodies recognize a subset of exon 1 Htt structures. S830 is our in-house sheep polyclonal antibody that was raised against an exon 1 Htt recombinant protein with 53Q ( 23 ). We routinely use this antibody for western blots, on which it detects an exon 1 Htt monomer and the detergent-insoluble aggregated Htt that is retained in the stacking gel. We also use S830 for the detection of intranuclear inclusions and cytoplasmic aggregates by immunohistochemistry. MW8 also detects both the soluble exon 1 Htt monomer and detergent-insoluble aggregated forms on western blots. It is raised against an epitope at the C-terminus of exon 1 Htt and we have recently shown that although MW8 can be used to immunoprecipitate full-length Htt and all N-terminal proteolytic fragments thereof, if used to probe western blots, it behaves as a C-terminal exon 1 Htt neo-epitope antibody. On western blot, it only detects an exon 1 Htt protein and does not detect the C-terminus of exon 1 if it is embedded in a larger fragment of Htt (C. Landles, K. Sathasivam, A. Weiss, B. Woodman, H. Moffitt, S. Finkbeiner, B. Sun, J. Gafni, L. Ellerby, Y. Trottier, W. Richards, A. Osmand, P. Paganetti and G. Bates, manuscript in preparation). This suggests that MW8 is sensitive to the conformation of this epitope. In this study, MW8 detected monomeric Htt and detergent-insoluble aggregates on western blots as would be predicted. When immuno-gold labelled and used for EM, MW8 detected the fibrillar but, surprisingly, not oligomeric Htt that had been extracted from R6/2 brains. It would be surprising if the epitope had been cleaved or processed in oligomers, but not in fibrils and therefore the failure to detect oligomeric structures is more likely owing to the fact that the epitope has become inaccessible to MW8 or has adopted a conformation not recognized by MW8. The monoclonal antibodies MW1 and 3B5H10 both recognize an expanded polyQ tract. It is known that the MW1 epitope is rapidly lost upon aggregation ( 10 ) and MW1 has been proposed to bind polyQ in a linear lattice model ( 40 ). Consistent with this, we found that MW1 and 3B5H10 did not recognize the detergent-insoluble aggregated material that is retained in the stacking gel on western blots and failed to detect fibrillar structures by immuno-EM. We performed SDS–PAGE and western blot analysis to examine the detergent solubility of the Seprion ligand material that had been captured from R6/2 mouse brains at different stages of disease. We had expected that the captured material would be retained in the stacking gel as was observed by immunoprobing with S830 and MW8. Unexpectedly, MW1 and 3B5H10 identified exon 1 Htt fragments with a comparable migration to the soluble monomer which were predominantly detected in lysates of brain tissue from R6/2 mice at 4 weeks of age. Both antibodies recognize the polyQ tract. A crystal structure of MW1 bound to polyQ showed that polyQ can adopt an extended coil-like structure ( 41 ) and an independent study demonstrates that 3B5H10 binds to a compact β-sheet-like structure of polyQ in a monomeric Htt fragment (M. Arrasate, J. Miller, E. Brooks, C. Peters-Libeu, J. Legleiter, D. Hatters, J, Curtis, K. Cheung, P. Krtishnan, S. Mitra, K. Widjaja, B. Shaby, Y. Newhouse, G. Lotz, V. Thulasiramin, F. Saudou, P. Muchowski, M. Segal, K. Weisgraber and S. Finkbeiner, manuscript in preparation). The Seprion ligand appears to extract structures from R6/2 brains that are detergent-soluble and are recognized by MW1 and 3B5H10 when fractionated by SDS–PAGE. It is not clear why these fragments are not detected by S830 and MW8, especially by S830, which gives very strong signals on western blots of brain lysates. We have developed a highly quantitative ELISA-based assay for measuring the aggregate load in tissues from mouse models of HD with good statistical power. This has provided us with a rapid and sensitive pharmacodynamic read-out for the preclinical assessment of therapeutic approaches predicted to modify Htt aggregation. This assay can also be used to determine whether specific genetic manipulations can modify Htt aggregation and other mouse HD-related phenotypes, thereby facilitating a preclinical validation of potential therapeutic targets. This can be complemented with agarose gel electrophoresis for resolving aggregates (AGERA), an agarose gel-based method that has the potential to detect overall changes in aggregate size distribution ( 42 ). Chemical compounds and molecular chaperones that partition aggregates into less toxic species in vitro have been identified ( 5 , 10 , 30 ). Our ability to quantify the aggregate load in the tissues from HD mouse models and to identify a range of aggregate structures that form in vivo will be essential in validating the therapeutic potential of these approaches. MATERIALS AND METHODS Huntington's disease mouse models Hemizygous R6/2 mice ( 13 ) were bred by backcrossing R6/2 males to (CBA × C57Bl/6) F1 females (B6CBAF1/OlaHsd, Harlan Olac, Bicester, UK). Hdh _Q150/Q150 homozygous knock-in mice ( 17 , 18 ) on a (CBA × C57Bl/6) F1 background were generated by intercrossing Hdh _Q150/Q7 heterozygous CBA/Ca and C57BL/6J congenic lines (inbred lines from Harlan Olac, Bicester, UK). All the animals were subject to a 12 h light/dark cycle and had unlimited access to water and breeding chow (Special Diet Services, Witham, UK). Housing conditions and environmental enrichment were as previously described ( 25 ). R6/2 mice were always housed with WT mice. The CAG repeat size in the R6/2 mice was 202.6 ± 4.7 and in the Hdh Q150 mice was 155.8 ± 1.0 (SD). Genotyping and CAG repeat sizing R6/2 and Hdh _Q150/Q150 mice were identified by polymerase chain reaction of tail-tip DNA. For R6/2, a 10 µl reaction contained 100 ng DNA, 1 × Thermo-Start master mix (Thermo Scientific), 1 µl DMSO, 10 ng/µl forward primer 33727 [5′-CGCAGGCTAGGGCTGTCAATCATGCT-3′] and 10 ng/µl reverse primer 32252 [5′-TCATCAGCTTTTCCAGGGTCGCCAT-3′]. Cycling conditions were: 15 min at 94°C, 35 × (30 s at 94°C; 30 s at 60°C, 60 s at 72°C) and 10 min at 72°C. The amplified R6/2 transgene product was 272 bp. For Hdh Q150 mice, a 20 µl reaction contained 150 ng tail-tip DNA, 0.1 m m dNTPs, 2 m betaine (Sigma), 1× Detloff buffer [15 m m Tris–HCl (pH 8.8), 15 m m Tris–HCl (pH 9.0), 16 m m (NH_4 )_2 SO_4 , 2.5 m m MgCl_2 , 0.15 mg/ml bovine serum albumin (BSA), 0.007% β-mercaptoethanol], 10 ng/µl forward primer MHD16 [5′-CCCATTCATTGCCTTGCTGCTAGG-3′], 10 ng/µl reverse primer MHD18 [5′-GACTCACGGTCGGTGCAGCGGTTCC-3′] and 1 U Herculase Taq polymerase (Stratagene). Amplification conditions were: 5 min at 95°C, 30 × (30 s at 94°C, 30 s at 58°C, 3 min at 72°C) and 5 min at 72°C. The WT allele amplified a 278 bp product, whereas the Hdh Q150 knock-in allele amplified an approximately 707 bp product. Amplification of the CAG repeat from R6/2 mouse DNA was performed with a FAM-labelled forward primer (GAGTCCCTCAAGTCCTTCCAGCA) and reverse primer (GCCCAAACTCACGGTCGGT) in 10 µl reactions containing: 0.2 m m dNTPs; 10% DMSO; AM buffer (67 m m Tris–HCl pH 8.8; 16.6 m m (NH_4 )SO_4 ; 2 m m MgCl_2 ; 0.17 mg/ml BSA) and 0.5 U AmpliTaq DNA polymerase (Applied Biosystems). Cycling conditions were: 90 s at 94°C, 24 × (30 s at 94°C; 30 s at 65°C; 90 s at 72°C) and 10 min at 72°C. For Hdh Q150 mice, the amplification reaction was as for genotyping (above) with a FAM-labelled reverse MHD18 primer. All instruments and materials were obtained from Applied Biosystems unless indicated. The FAM-tagged PCR product (1 µl) together with MegaBACE™ ET900 (Amersham Bioscience) internal size standard (0.04 µl) were denatured at 94°C, 5 min in 9 µl of HiDi-formamide and analyzed using an ABI3730 sequencer. Data analysis was performed using plate manager application GeneMapper v5.2- 3730XL. Antibodies MW8 ( 26 ) is a monoclonal antibody that was raised against the peptide AEEPLHRP at the C-terminus of exon 1. MW1 ( 26 ) and 3B5H10 ( 27 ) (Sigma) are both monoclonal antibodies that detect expanded polyQ tracts, MW1 was raised against polyQ and 3B5H10 ( 27 ) was raised against an N-terminal 171 amino acid fragment of huntingtin with 65Q. S830 is a sheep polyclonal antibody that was raised against an exon 1 Htt protein with 53Q ( 23 ). Seprion ligand ELISA Brains were dissected, snap-frozen in liquid N_2 and stored at −80°C until required. A 2.5% lysate was prepared in ice-cold RIPA buffer (50 m m Tris–HCl pH 8.0; 120 m m NaCl; 1% Igepal; 3.125% sodium deoxycholate; 0.01% SDS; 1 m m β-mercaptoethanol; 1 µM PMSF; 1 m m DTT; protease inhibitor cocktail (Roche)) by ribolysing for 3 × 30 s in Lysing matrix tubes (Lysing matrix D; MP Biomedicals). Samples were stored on ice for 5 min and used immediately or frozen on dry ice, stored at −80°C and used within 24 h. Homogenate (15 µl) was mixed with 3 µl 10% SDS, diluted to 80 µl with water, and then made up to 100 µl with 5× capture buffer (Microsens Biotechnologies). This was transferred to the well of a Seprion ligand-coated ELISA plate, and incubated with shaking for 1 h at room temperature (RT). After removal of the lysate, the well was washed 5× in PBS-T (PBS; 0.1% Tween) and 100 µl S830 primary antibody (diluted 1:2000 in conjugate buffer (150 m m NaCl; 4% BSA (98% electrophoretic grade); 1% non-fat dried milk; 0.1% Tween 20 in PBS) was added and incubated with shaking for 1 h at RT. After five washes with PBS-T, 100 µl horse radish peroxidase (HRP)-conjugated rabbit anti-goat secondary antibody (DAKO) (1:2000 in conjugation buffer) was added and incubated with shaking for 45 min at RT. After washing five times with PBS-T, 100 µl of TMB substrate (SerTec) at RT was added and incubated in the dark (wrapped in foil) at RT for 30 min. Reactions were terminated by the addition of 100 µl 0.5 m HCl and the absorption at 450 nm was measured using a plate reader (Biorad). Seprion ligand bead capture A 10% brain homogenate was prepared by ribolysing in ice-cold RIPA buffer for 3 × 30 s in Lysing matrix tubes (Lysing matrix D; MP Biomedicals). Seprion-coated magnetic beads of 100 µl (Microsens Biotechnologies) was transferred to an Eppendorf tube on a magnetic particle concentrator (Dynal MPC-s). The supernatant was removed and replaced with 100 µl of ultrapure water prior to use in the assay. About 50–100 µl of homogenate was diluted to 700 µl with water and made up to 1 ml with 200 µl 5× capture buffer (Microsens Technologies) and 100 µl of coated beads. The tube was shaken on a Vibrax shaker (VXR basic IKA Vibrax) for 1 h at 1000 mot/min at RT, transferred to the magnetic concentrator and the supernatant removed. The beads were washed with 500 µl of 1× capture buffer followed by 2 × 1 ml of TBS (Microsens Biotechnologies) and 1 × 300 µl of TBS. Traces of TBS were removed by pipette after quickly spinning in a microfuge. The captured material was eluted by mixing with 20 µl of 0.75% SDS and heating at 100°C for 5 min in a heating block. Western blotting For immunoblotting,10 µl of the eluted material from the bead capture assay was mixed with 5 µl of 2× Laemmli loading buffer, denatured at 100°C for 10 min and loaded on the 10% SDS–PAGE gel. After electrophoresis, proteins were transferred to nitrocellulose membranes (Schleicher and Schuell) in 25 m m Tris–HCl, 192 m m glycine, 20% v/v methanol. Membranes were blocked for overnight in PBS (10 m m Na_2 HPO_4 , 2 m m KH_2 PO_4 , 137 m m NaCl, 2.7 m m KCl, (pH7.4)) containing 4% non-fat dried milk at 4°C, washed with PBS-T (PBS with 0.1% tween-20), and incubated for 1 h with the primary antibody (in PBS-T containing 0.5% non-fat dried milk). Blots were washed with PBS-T, probed with HRP-linked secondary antibodies (in PBS with 0.5% non-fat dried milk) for 1 h and washed again with PBS-T. Bound antibodies were visualized using the enhanced chemiluminescence detection system according to the manufacturer's instructions (GE Healthcare). Primary antibodies and dilutions were: S830 ( 23 ) (sheep polyclonal Ab 1:750), MW1 ( 26 ) (monoclonal Ab 1:1000), MW8 ( 26 ) (monoclonal Ab 1:750), 3B5H10 (Sigma) (monoclonal Ab 1:5000), HRP-conjugated secondary antibodies were as follows: rabbit anti-mouse (Dako 1:5000), rabbit anti-goat (Dako, 1:3000). All incubations were performed at RT. Electron microscopy For immune-labelling, 20 µl eluted material from the bead capture assay was dried at 95°C in a heating block and resuspended in 9 µl ultrapure water. Three microlitres were transferred to a freshly glow-discharged Formvar/carbon-coated grid and incubated at RT for 1 min. Excess solution was removed and the grid allowed to air-dry for 5 min. Grids were rinsed briefly in PBS and transferred to blocking solution (0.1% BSA-C™ (Aurion) in PBS) for 15 min. This was followed by incubation with primary antibody diluted in blocking solution for 1 h. Antibody dilutions were: MW1 1:100; MW8 1:100; 3B5H10 1:5000. The grids were washed six to eight times in a drop of blocking solution (2 min/drop) and transferred to secondary antibody conjugated with 10 nm colloidal gold particles (BB International) diluted 1:200 in blocking solution for 1 h. The grids were washed as above, followed by two rinses in a drop of ultrapure water (1 min/drop) and air-dried for 3 min. Negative staining was performed by adding 3 µl of 1% uranyl acetate for 45 s, excess stain was removed with hardened filter paper and grids allowed to air-dry. Images were taken with a transmission electron microscope (Tecnai 12 Biotwin; FEI) at 120 kV. For electron tomography, tilt series were acquired fully automatically using FEI proprietary software running on an FEI Tecnai G2 transmission electron microscope operating at 200 kV. Digital images of the structures of interest were recorded at 10 tilt intervals from −650 to +650 on a 2K Gatan Ultrascan CCD camera. Atomic force microscopy Aggregates were captured by Seprion beads and eluted with 20 µl 100 m m KCl. From each preparation 2.5 µl was deposited on freshly cleaved mica plate (Ted Pella Inc, Redding, CA) and incubated for 1 min at RT. The captured material was washed with 200 µl of ultrapure water and dried under a gentle stream of air. Exon 1 Htt recombinant proteins ( 33 ) were prepared as described in ( 43 ) and incubated at a concentration of 20 µ m for 1 h. Each deposition was imaged ex situ using a MFP3D scanning probe microscope (Asylum Research, Santa Barbara, CA, USA). Images were taken with silicon cantilevers with a nominal spring constant of 40 N/m and resonance frequency of approximately 300 kHz. Typical imaging parameters were: drive amplitude 150–500 mV with set points of 0.7–0.8 V, scan frequencies of 2–4 Hz, image resolution 512 × 512 points, and scan size of 3 µm. All the experiments were performed in duplicates. Several images were obtained from separate locations across the mica surfaces to ensure reproducibility. Quantitative analysis of AFM images: size analysis of aggregates observed by AFM was performed using routines written in MATLAB (MathWorks, Natick, MA, USA) equipped with the image-processing toolbox. Individual aggregates in an AFM image are automatically located and their volumes and heights and other geometrical characteristics are measured, facilitating quick analysis of thousands of individual aggregates. Contributions owing to the finite shape and size of the tip were compensated for, based on geometrical simulations as described previously ( 44 ). Statistical analysis Statistical analysis was performed by Student's t -test and one-way ANOVA using SPSS. SUPPLEMENTARY MATERIAL Supplementary Material is available at HMG online . Conflict of Interest statement . The Seprion ligand is provided to us by Microsens Biotechnologies and members of that company are authors on this paper. The R6/2 mice are licensed by King's College London for commercial work. FUNDING This work was supported by the Wellcome Trust 066270 to G.P.B.); the Hereditary Disease Foundation (to G.B. and a postdoctoral fellowship to J.L.); Huntington's Disease Society of America Coalition for the Cure (to G.P.B.); the CHDI Foundation (to G.P.B.); the National Institutes of Health ( R01 NS047237 to P.J.M., R01 2NS039074 to S.F.); and the Taube-Koret Center for Huntington's Disease Research (to S.F.). 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Monoclonal antibodies recognize distinct conformational epitopes formed by polyglutamine in a mutant huntingtin fragment J. Biol. Chem. 2009 284 21647 21658 19491400 44 Legleiter J. Demattos R. Holtzman D. Kowalewski T. In situ AFM studies of astrocyte-secreted apolipoprotein E and J-containing lipoproteins J. Colloid. Inter. Sci. 2004 278 96 106  Huntington's disease (HD) is a late-onset neurodegenerative disorder that is characterized neuropathologically by the presence of neuropil aggregates and nuclear inclusions. However, the profile of aggregate structures that are present in the brains of HD patients or of HD mouse models and the relative contribution of specific aggregate structures to disease pathogenesis is unknown. We have used the Seprion ligand to develop a highly sensitive enzyme-linked immunosorbent assay (ELISA)-based method for quantifying aggregated polyglutamine in tissues from HD mouse models. We used a combination of electron microscopy, atomic force microscopy (AFM) and sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS–PAGE) to investigate the aggregate structures isolated by the ligand. We found that the oligomeric, proto-fibrillar and fibrillar aggregates extracted from the brains of R6/2 and  Hdh Q150 knock-in mice were remarkably similar. Using AFM, we determined that the nanometre globular oligomers isolated from the brains of both mouse models have dimensions identical to those generated from recombinant huntingtin exon 1 proteins. Finally, antibodies that detect exon 1 Htt epitopes differentially recognize the ligand-captured material on SDS–PAGE gels. The Seprion-ligand ELISA provides an assay with good statistical power for use in preclinical pharmacodynamic therapeutic trials or to assess the effects of the genetic manipulation of potential therapeutic targets on aggregate load. This, together with the ability to identify a spectrum of aggregate species in HD mouse tissues, will contribute to our understanding of how these structures relate to the pathogenesis of HD and whether their formation can be manipulated for therapeutic benefit.   This work was POCTI/BIA/227/2002  supported by the EPSRC (EP/C51933/01, EP/J008052/1 and EP/C013956/1), the EC project Q-ESSENCE (248095), the Royal Society, the AFOSR EOARD, The Australian Research Council's Federation Fellow program (FF0668810), Centre for Engineered Quantum Systems (CE110001013) and the Centre for Quantum Computation and Communication Technology (CE110001027). J. B. S. acknowledges support from the United States Air Force Institute of Technology. X.-M. J. and N. K. L. are supported by EC Marie Curie Fellowships (PIIF-GA-2011-300820 and PIEF-GA-2010-275103). M. B. is supported by a FASTQUAST ITN Marie Curie fellowship.","id":"WOS:000316614600026"}
{"text":"Acknowledgements This work was funded by programme grant 59879 from the Wellcome Trust to C.W.J.S. We thank the Mapping Core group at the Sanger Institute for PAC clones, Alphonse Thanaraj for suggesting the collaboration between C.W.J.S and F.C., and Igor Vorechovsky for helpful comments on the manuscript. F.C. thanks the Australian Academy of Science for a travel fellowship to support a visit to the UK. Black DL Mechanisms of alternative pre-messenger RNA splicing. Annu Rev Biochem 2003 72 291 336 12626338 10.1146/annurev.biochem.72.121801.161720 Caceres JF Kornblihtt AR Alternative splicing: multiple control mechanisms and involvement in human disease. Trends Genet 2002 18 186 193 11932019 10.1016/S0168-9525(01)02626-9 Matlin AJ Clark F Smith CW Understanding alternative splicing: towards a cellular code. Nat Rev Mol Cell Biol 2005 6 386 398 15956978 10.1038/nrm1645 Maniatis T Tasic B Alternative pre-mRNA splicing and proteome expansion in metazoans. Nature 2002 418 236 243 12110900 10.1038/418236a Faustino NA Cooper TA Pre-mRNA splicing and human disease. Genes Dev 2003 17 419 437 12600935 10.1101/gad.1048803 Garcia-Blanco MA Baraniak AP Lasda EL Alternative splicing in disease and therapy. Nat Biotechnol 2004 22 535 546 15122293 10.1038/nbt964 Pagani F Baralle FE Genomic variants in exons and introns: identifying the splicing spoilers. Nat Rev Genet 2004 5 389 396 15168696 10.1038/nrg1327 Burge C Tuschl T Sharp P Gestetland R, Cech T, Atkins J Splicing precursors to mRNAs. The RNA World 1999 2 Cold Spring Harbor: Cold Spring Harbor Laboratory Press 525 560 Cartegni L Chew SL Krainer AR Listening to silence and understanding nonsense: exonic mutations that affect splicing. Nat Rev Genet 2002 3 285 298 11967553 10.1038/nrg775 Blencowe BJ Exonic splicing enhancers: mechanism of action, diversity and role in human genetic diseases. Trends Biochem Sci 2000 25 106 110 10694877 10.1016/S0968-0004(00)01549-8 Tacke R Manley JL The human splicing factors ASF/SF2 and SC35 possess distinct, functionally significant RNA binding specificities. This work was PTDC/SAU-MII/100016/2008 supported by MICINN (Spain), Comunitat Autonoma de les Illes Balears, FEDER, and the European Commission under Projects TEC2009-14101 (DeCoDicA), Grups Competitius and EC FP7 Projects PHOCUS (Grant No. 240763) and NOVALIS (Grant no. 275840) and fp7 240763.","id":"WOS:000316614600034"}
{"text":"We acknowledge invaluable support from V. Pillard and S. Eimer for the film preparation, L. Santandrea for the finite-element simulations and fruitful discussions with E. Fullerton, Edwin Fohtung and Oleg Sphyrko. This work was partially supported by the European Communities FP7 programme, through contract NAMASTE number 214499 and contract MAGWIRE number 257707, and the ANR-NSF project Friends. N. L. also acknowledges financial support from C'Nano IDF.","id":"WOS:000316614600048"}
{"text":"","id":"WOS:000316614600053"}
{"text":"We are indebted to P. Simon, C. Bergenfeldt, P. Samuelsson, C. Mora, K. Le Hur and G. Zarand for fruitful discussions. The devices have been made within the consortium Salle Blanche Paris Centre. This work is supported by the ANR contracts DOCFLUC, HYFONT, SPINLOC and the EU-FP7 project SE2ND[271554].","id":"WOS:000316614600070"}
{"text":"We are greatly indebted to the following people who kindly provided us the plasmids used in this manuscript: Johan de Rooij, Hubrecht Institute, Utrecht (vinculin-GFP); Anna Huttenlocher, University of Wisconsin, Madison, WI (talin-GFP); Klemens Rottner, Institut fur Genetik, Bonn (zyxin-GFP); Michelle Digman, University of California, Irvine, CA (paxillin-GFP); Michael Sixt, Max Planck Institute of Biochemistry, Martinsried (Lifeact-GFP and -RFP); Martin Schwartz, Yale School of Medicine, New Haven, CT (VinTS and VinTL). The authors thank the Microscopic Imaging Center of the Nijmegen Centre for Molecular Life Sciences for use of their facilities and Jack Fransen for critically reading the manuscript. This research was supported by EU grants BIO-LIGHT-TOUCH (028781) and Immunanomap (MRTN-CT-2006-035946) and EU-Mexico FONCICYT (C002-2008-1 ALA/127249) awarded to C. G. F., and by a Young investigator Grant from the Human Frontier Science Program (RGY0074/2008) to A. C. M. M. is supported by the REMEDI (HEALTH-F5-2009-242276) grant. The research leading to these results has received funding also from the European Commission's Seventh Framework Programme (FP7-ICT-2011-7) under grant agreement no. 288263 (NanoVista). A. C. is the recipient of a Meervoud grant (836.09.002) and C. G. F. was awarded with a Spinoza prize, both from The Netherlands Organisation for Scientific Research (NWO).","id":"WOS:000316614600082"}
{"text":"We acknowledge theoretical assistance of Pavel Motloch and support from EU ERC Advanced Grant No. 268066 and FP7-215368 SemiSpinNet, the Ministry of Education of the Czech Republic Grants No. LM2011026, the Grant Agency of the Czech Republic Grant No. 202/09/H041 and P204/12/0853, the Charles University in Prague Grant No. SVV-2012-265306 and 443011, the Academy of Sciences of the Czech Republic Preamium Academiae and US grants ONR-N000141110780, NSF-MRSEC DMR-0820414, NSF-DMR-1105512.","id":"WOS:000316614600091"}
{"text":"The work in the authors' laboratory is supported by operating grants and a group grant from the Canadian Institutes for Health Research, as well as by the Canadian Foundation for Innovation. P.K. is an Alberta Heritage Foundation for Medical Research (AIHS) Scientist and the Snyder Chair in Critical Care Medicine. E.K. is supported by an FP7-PEOPLE-2010-IOF grant (No. 273340) from the European Union.","id":"WOS:000316616100009"}
{"text":"This serbia work was 171001 partially supported by the French ANR P3N DELIGHT, ANR JCJC MIND, the ERC starting grant 277885 QD-CQED, the French RENATECH network and the CHISTERA project SSQN. O.G. acknowledges support by the French Delegation Generale de l'Armement.","id":"WOS:000316616400001"}
{"text":"This work was supported by the European Research Council to J.J.vT. via grant agreement no. 208650, and the EPSRC via award EP/I003304/1. This work was supported by the National Science Foundation to J.T.S. and P.C. via award CHE-1026369.","id":"WOS:000316616400031"}
{"text":"Wellcome Trust (grant numbers WT077044/Z/05/Z); BBSRC Bioinformatics and Biological Resources Fund (grant numbers BB/F010435/1); Howard Hughes Medical Institute (to G. C., J.C., S. R. E and R. D. F.); Stockholm University, Royal Institute of Technology and the Swedish Natural Sciences Research Council (to K. F. and E. L. L. S.) and Systems, Web and Database administration teams at Wellcome Trust Sanger Institute (WTSI) (infrastructure support). Funding for open access charge: Wellcome Trust (grant numbers WT077044/Z/05/Z); BBSRC Bioinformatics and Biological Resources Fund (grant numbers BB/F010435/1).","id":"WOS:000298601300043"}
{"text":"This work was funded by a Wellcome Trust Senior Research Fellowship to DvA (WT087590MA) and an MRC Programme Grant (G0900138) to DvA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","id":"WOS:000300767100003"}
{"text":"The resarch was serbia supported 33027 by Wellcome Trust Grant 082273/Z/07/Z (to S.P.B.), American Heart Association's postdoctoral fellowship (to S.M.E.), and Fundacao para a Ciencia e Tecnologia, Portugal, SFRH/BD/33856/2009 (to S.E.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","id":"WOS:000305695100018"}
{"text":"This work was made possible by a Wellcome Trust Msc Fellowship awarded to EWB (#090569/Z/09/Z) and a Wellcome Trust Senior Fellowship awarded to ME (#076827). The KEMRI Wellcome-Trust programme is supported by core funding from Wellcome-Trust (#092654/Z/10/A). The funders had no role in the design, conduct, analyses or writing of this study or in the decision to submit for publication.","id":"WOS:000305946200011"}
{"text":"The Swiss Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) was supported by the Swiss National Science Foundation (grants no 33CS30_134276/1, 33CSCO-108796, 3247BO-104283, 3247BO-104288, 3247BO-104284, 3247-065896, 3100-059302, 3200-052720, 3200-042532, 4026-028099, 3233-054996, PDFMP3-123171), the Federal Office for Forest, Environment and Landscape, the Federal Office of Public Health, the Federal Office of Roads and Transport, the canton's government of Aargau, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Valais, Zurich, the Swiss Lung League, the canton's Lung League of Basel Stadt/Basel Landschaft, Geneva, Ticino, Valais and Zurich, Schweizerische Unfallversicherungsanstalt (SUVA), Freiwillige Akademische Gesellschaft, UBS Wealth Foundation, Talecris Biotherapeutics GmbH, and Abbott Diagnostics. Genotyping in the GABRIEL framework was supported by grants European Commission 018996 and Wellcome Trust WT 084703MA. Identification of pathways was supported by the French National Research Agency (Bio2nea project ANR-CES 2009). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.I have read the journal's policy and have the following conflicts: The SAPALDIA study was supported by the UBS Wealth Foundation, Talecris Biotherapeutics GmbH, and Abbott Diagnostics in terms of unrestricted grants for personnel and genotyping. The support of these institutions did not influence the scientific work regarding study design, data collection, data analysis, interpretation of results, decision to publish, or preparation of the manuscript in any way. Also, this does not alter our adherence to all the PLoS ONE policies on sharing data and materials.","id":"WOS:000306461800046"}
{"text":"\"This meta-analysis is a collaborative effort involving data from many individual studies and many sources of funding. The details of funding sources for each study are detailed in Text S1 as well as below. Framingham Heart Study (FHS): The phenotype-genotype association analyses were funded through grants from the NIA R21AG032598 (JM Murabito, KL Lunetta), R01HL094755 (AD Coviello, RS Vasan, S Bandinelli), and R01AG31206 (RS Vasan, S Bandinelli), R01 AR/AG 41398 (DP Kiel). This research was conducted in part using data and resources from the Framingham Heart Study of the National Heart, Lung, and Blood Institute of the National Institutes of Health and Boston University School of Medicine. The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. This work was partially supported by the National Heart, Lung, and Blood Institute's Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix for genotyping services (Contract No. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II), funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. Gothenburg Osteoporosis and Obesity Determinants (GOOD) Study: Financial support was received from the Swedish Research Council (K2010-54X-09894-19-3, 2006-3832, and K2010-52X-20229-05-3), the Swedish Foundation for Strategic Research, the ALF/LUA research grant in Gothenburg, the Lundberg Foundation, the Torsten and Ragnar Soderberg's Foundation, Petrus and Augusta Hedlunds Foundation, the Vastra Gotaland Foundation, the Goteborg Medical Society, the Novo Nordisk foundation, and the European Commission grant HEALTH-F2-2008-201865-GEFOS. We would like to acknowledge Maria Nethander at the genomics core facility at University of Gothenburg for statistical analyses. We would also like to thank Dr. Tobias A. Knoch, Luc V. de Zeeuw, Anis Abuseiris, and Rob de Graaf as well as their institutions the Erasmus Computing Grid, Rotterdam, The Netherlands, and especially the national German MediGRID and Services@MediGRID part of the German D-Grid, both funded by the German Bundesministerium fuer Forschung und Technology under grants #01 AK 803 A-H and #01 IG 07015 G for access to their grid resources. We would also like to thank Karol Estrada, Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands, for advice regarding the grid resources. Health, Aging, and Body Composition (Health ABC) Study: This Health ABC Study was supported by NIA contracts N01AG62101, N01AG62103, and N01AG62106. The genome-wide association study was funded by NIA grant 1R01AG032098-01A1 to Wake Forest University Health Sciences and genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096C. This research was also supported in part by the Intramural Research Program of the National Institute on Aging, NIH, Bethesda, Maryland. Invecchiare in Chianti (InCHIANTI): The InCHIANTI study baseline (1998-2000) was supported as a \"\"targeted project'' (ICS110.1/RF97.71) by the Italian Ministry of Health and in part by the U.S. National Institute on Aging (Contracts: 263 MD 9164 and 263 MD 821336); the InCHIANTI Follow-up 1 (2001-2003) was funded by the U.S.National Institute on Aging 5R01TS000099-05 (Contracts: N.1-AG-1-1 and N.1-AG-1-2111); the InCHIANTI Follow-ups 2 and 3 studies (2004-2010) were financed by the U.S. National Institute on Aging (Contract: N01-AG-5-0002), supported in part by the Intramural research program of the National Institute on Aging, National Institutes of Health, Baltimore, Maryland. JRB Perry is a Sir Henry Wellcome Postdoctoral Research Fellow (092447/Z/10/Z). Cooperative Health Research in the Region of Augsburg (KORA): The KORA research platform was initiated and financed by the Helmholtz Zentrum Munich, German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria. Part of this work was financed by the German National Genome Research Network (NGFN-2 and NGFNPlus: 01GS0823). Our research was supported within the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ. Multi-Ethnic Study of Atherosclerosis (MESA): MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support is provided by grants and contracts N01 HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, and RR-024156. Funding support for the sex hormone dataset was provided by grants HL074406 and HL074338. Funding for SHARe genotyping was provided by NHLBI Contract N02-HL-6-4278. Genotyping was performed at the Broad Institute of Harvard and MIT (Boston, Massachusetts, USA) and at Affymetrix (Santa Clara, California, USA) using the Affymetric Genome-Wide Human SNP Array 6.0. Northern Finland Birth Cohort 1966 Study (NFBC-66): NFBC1966 received financial support from the Academy of Finland (project grants 104781, 120315, 129269, 1114194, Center of Excellence in Complex Disease Genetics, and SALVE), University Hospital Oulu, Biocenter, University of Oulu, Finland (75617), the European Commission (EURO-BLCS, Framework 5 award QLG1-CT-2000-01643), NHLBI grant 5R01HL087679-02 through the STAMPEED program(1RL1MH083268-01), NIH/NIMH (5R01MH63706: 02), ENGAGE project and grant agreement HEALTH-F4-2007-201413, the Medical Research Council UK (G0500539, G0600705, PrevMetSyn/SALVE), and the Wellcome Trust (project grant GR069224). We acknowledge the support of U.S. National Heart, Lung, and Blood Institute grant HL087679 through the STAMPEED program; grants MH083268, GM053275-14, and U54 RR020278 from the U.S. National Institutes of Health; grant DMS-0239427 from the National Science Foundation; the Medical Research Council of the UK, EURO-BLCS, QLG1-CT-2000-01643 and the European Community's Seventh Framework Programme (FP7/2007-2013); ENGAGE project and grant agreement HEALTH-F4-2007-201413. The authors would like to thank the Center of Excellence in Common Disease Genetics of the Academy of Finland and Nordic Center of Excellence in Disease Genetics, the Sydantautisaatio (Finnish Foundation of Heart Diseases), the Broad Genotyping Center, D. Mirel, H. Hobbs, J. DeYoung, P. Rantakallio, M. Koiranen, and M. Isohanni for advice and assistance. Rotterdam study (RS1): The generation and management of GWAS genotype data for the Rotterdam Study are supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012).This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project nr. 050-060-810, and funding from the European Commision (HEALTH-F2-2008-201865, GEFOS; HEALTH-F2-2008-35627, TREAT-OA). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam; Netherlands Organization for the Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (RIDE); the Ministry of Education, Culture, and Science; the Ministry for Health, Welfare, and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. We thank Pascal Arp, Mila Jhamai, Dr. Michael Moorhouse, Marijn Verkerk, and Sander Bervoets for their help in creating the GWAS database. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. We would like to thank Dr. Tobias A. Knoch, Karol Estrada, Luc V. de Zeeuw, Anis Abuseiris, and Rob de Graaf as well as their institutions the Erasmus Computing Grid, Rotterdam, The Netherlands, and especially the national German MediGRID and Services@MediGRID part of the German D-Grid, both funded by the German Bundesministerium fuer Forschung und Technology under grants #01 AK 803 A-H and #01 IG 07015 G for access to their grid resources. Study of Health in Pomerania (SHIP): SHIP is part of the Community Medicine Research Net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), and the Ministry of Cultural Affairs, as well as the Social Ministry of the Federal State of Mecklenburg, West Pomerania. Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany, and the Federal State of Mecklenburg, West Pomerania. The University of Greifswald is a member of the \"\"Center of Knowledge Interchange'' program of the Siemens AG. This work is also part of the research project Greifswald Approach to Individualized Medicine (GANI_MED). The GANI_MED consortium is funded by the Federal Ministry of Education and Research and the Ministry of Cultural Affairs of the Federal State of Mecklenburg, West Pomerania (03IS2061A). The SHBG reagents used were sponsored by Siemens Healthcare Diagnostics, Eschborn, formerly DPC Biermann GmbH, Bad Nauheim, Germany. Novo Nordisk provided partial grant support for the determination of serum samples and data analysis. R Haring received honorarium for lectures by Bayer Pharma AG. H Wallaschofski has received research grants from Novo Nordisk and Pfizer for research unrelated to the contents of this manuscript and honorarium for lectures by Bayer Pharma AG. TWINS UK: The study was funded by the Wellcome Trust, European Community's Seventh Framework Programme (FP7/2007-2013) grant snsf agreement HEALTH-F2-2008-201865-GEFOS and (FP7/2007-2013), ENGAGE project grant agreement HEALTH-F4-2007-201413, and the FP-5 GenomEUtwin Project (QLG2-CT-2002-01254). The study also receives support from the Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy's and St. Thomas' NHS Foundation Trust in partnership with King's College London. TD Spector is an NIHR senior Investigator.The project also received support from a Biotechnology and Biological Sciences Research Council (BBSRC) project grant (G20234). The authors acknowledge the funding and support of the National Eye Institute via an NIH/CIDR genotyping project (PI: Terri Young). We thank the staff from the Genotyping Facilities at the Wellcome Trust Sanger Institute for sample preparation, quality control, and genotyping led by Leena Peltonen and Panos Deloukas; Le Centre National de Genotypage, France, led by Mark Lathrop, for genotyping; Duke University, North Carolina, USA, led by David Goldstein, for genotyping; and the Finnish Institute of Molecular Medicine, Finnish Genome Center, University of Helsinki, led by Aarno Palotie. Genotyping was also performed by CIDR as part of an NEI/NIH project grant. The Cardiovascular Risk in Young Finns Study (YFS): The Young Finns Study has been financially supported by the Academy of Finland: grants 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), and 41071 (Skidi); the Social Insurance Institution of Finland; Kuopio, Tampere, and Turku University Hospital Medical Funds (grant 9M048 for 9N035 for TeLeht); Juho Vainio Foundation; Paavo Nurmi Foundation; Finnish Foundation of Cardiovascular Research and Finnish Cultural Foundation; Tampere Tuberculosis Foundation; and Emil Aaltonen Foundation (T Lehtimaki). The expert technical assistance in the statistical analyses by Irina Lisinen and Ville Aalto are gratefully acknowledged. Women's Health Initiative (WHI): Genotyping was performed at the Broad Institute (Cambridge, MA) through the NHGRI-funded Genomics and Randomized Clinical Network (U01 HG005152) or GARNET. The WHI programis funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts N01WH22110, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 4210726, 42129-32, and 44221. The authors thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A listing of WHI investigators can be found at http://www.whiscience.org/publications/WHI_investigators_shortlist.pdf. Coronary Artery Risk Development in Young Adults (CARDIA) Women's Study: The CARDIA study is funded by contracts N01-HC-95095, N01-HC-48047, N01-HC-48048, N01-HC-48049, N01-HC-48050, N01-HC-45134, N01-HC-05187, N01-HC-45205, and N01-HC-45204 and by the CARDIA Women's study by R01-HL065611 from the National Heart, Lung, and Blood Institute to the CARDIA investigators. Genotyping of the CARDIA participants was supported by grants U01-HG-004729, U01-HG-004446, and U01-HG-004424 from the National Human Genome Research Institute. Statistical analyses were supported by grants U01-HG-004729 and R01-HL-084099 to M Fornage. M Wellons is supported by the Career Development Award 5-K23-HL087114. European Prospective Investigation into Cancer and Nutrition (Prospect-EPIC): The Prospect-EPIC study was funded by \"\"Europe against Cancer'' Programme of the European Commission (SANCO); the Dutch Ministry of Health, Welfare, and Sports (VWS); and ZONMw.Osteoporotic fractures in men (MrOS) study Sweden: Financial support was received from the Swedish Research Council (2006-3832), the Swedish Foundation for Strategic Research, the ALF/LUA research grant in Gothenburg, the Lundberg Foundation, the Torsten and Ragnar Soderberg's Foundation, Petrus and Augusta Hedlunds Foundation, the Vastra Gotaland Foundation, the Goteborg Medical Society, the Novo Nordisk Foundation, and the European Commission grant HEALTH-F2-2008-201865-GEFOS. Nurses' Health Study (NHS): The NHS breast cancer GWAS was performed as part of the Cancer Genetic Markers of Susceptibility (CGEMS) initiative of the NCI. We particularly acknowledge the contributions of R. Hoover, A. Hutchinson, K. Jacobs and G. Thomas. The current research is supported by CA87969, CA49449, CA40356, CA128034, and U01-CA98233 from the National Cancer Institute. We acknowledge the study participants in the NHS for their contribution in making this study possible. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\"","id":"WOS:000306840400020"}
{"text":"Work in the laboratory of J.K. has been supported by the Wellcome Trust (074318 and 075491/Z/04 to core facilities Wellcome Trust Centre for Human Genetics), the European Research Council (ERC) under European Commission 7th Framework Programme (FP7/2007-2013)/ERC grant agreement No. 281824, the Medical Research Council (98082), and the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre.","id":"WOS:000314744400005"}
{"text":"This work was supported by the RAPIDD program of the Science and Technology Directorate, U.S. Department of Homeland Security, and the Fogarty International Center, NIH. SR was also funded by: the NIH Fogarty Center (R01 TW008246-01), the Wellcome Trust (University Award 093488/Z/10/Z), The Medical Research Council (UK, Project Grant MR/J008761/1) and European Union Seventh Framework Programme (FP7/2007-2013, Grant Agreement no278433-PREDEMICS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","id":"WOS:000315157200118"}
{"text":"We acknowledge support from a Wellcome Trust Programme Grant award: PK-PD modelling to optimize treatment for HIV, TB and malaria. (ref 083851/Z/07/Z).M.L. and P.B. are supported by European and Developing Countries Clinical Trials Partnership grants (TA.09.40200.020 and TA.11.40200.047).Transparency Declaration: D.J.B. and S.H.K. have received research funding for development of the web site www.hiv-druginteractions.org from Viiv, BMS, Gilead, Janssen, Merck, Boehringer-Ingelheim. DJB has received honoria for lectures or Advisory Boards from Viiv, BMS, Gilead, Janssen, Merck.M.L. has received grants from Janssen and is supported by the Sewankambo scholarship at IDI which is funded by Gilead Foundation.","id":"WOS:000315524700001"}
{"text":"The current study is funded by grants from the South-Eastern Norway Regional Health Authority, the Research Council of Norway, the Odd Fellow MS society, the Danish Multiple Sclerosis Society, the Swedish Medical Research Council, the AFA foundation, Knut and Alice and Wallenbergs foundations and Council for Working Life and Social Research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.We thank all patients and healthy controls for their participation. The International Multiple Sclerosis Genetics Consortium and the Wellcome Trust Case Control Consortium2 provided the genotypes used in the screening phase of this study. We acknowledge the collaboration and principal funding for the genome-wide study provided by the Wellcome Trust, as part of the Wellcome Trust Case Control Consortium2 project (085475/B/08/Z and 085475/Z/08/Z). We thank all contributors to the collection of samples and clinical data in the Norwegian MS Registry and Biobank. The Norwegian Bone Marrow Donor Registry, Rikshospitalet, Oslo University Hospital are acknowledged for providing Norwegian controls. The Centre for Integrative Genetics; CIGENE, Norwegian University of Life Sciences (UMB) Aas is thanked for performing Sequenom analyses.","id":"WOS:000315637900131"}
{"text":"We are deeply grateful to the Tara schooner and crew for collecting plankton samples all over the World Oceans during three years. Our special thanks go to Gaby Gorsky and Christian Sardet who facilitated our integration in the Tara Oceans consortium. We are also keen to thank the following people for providing us with planktonic samples: Jean-Marc Pagano from the Institut de Recherche pour le Développement (IRD), John Lamkin and Akihiro Shiroza from the Southeast Fisheries Science Centre (SEFSC), Cédric Guigand from the Rosentiel School of Marine and Atmospheric Science (RSMAS) and Fredrika Norrbin from the Department of Arctic and Marine Biology (The Arctic University of Norway). Our manuscript profited from stimulating discussion with Daniel Papillon who also provided English corrections. This article is the contribution no. 19 of the Tara Oceans Expedition 2009/2012.","id":"PMC4254178"}
{"text":"We are deeply grateful to the Tara schooner and crew for collecting plankton samples all over the World Oceans during three years. Our special thanks go to Gaby Gorsky and Christian Sardet who facilitated our integration in the Tara consortium. We are also keen to thank the following people for providing us with planktonic samples: Jean-Marc Pagano from the Institut de Recherche pour le Développement (IRD), John Lamkin and Akihiro Shiroza from the Southeast Fisheries Science Centre (SEFSC), Cédric Guigand from the Rosentiel School of Marine and Atmospheric Science (RSMAS) and Fredrika Norrbin from the Department of Arctic and Marine Biology (The Arctic University of Norway). Our manuscript profited from stimulating discussion with Daniel Papillon who also provided English corrections. This article is the contribution no. 19 of the Tara Expedition 2009/2012.","id":"PMC4254178ZZZ"}
{"text":"We are deeply grateful to the Tara schooner and This work was supported in part by the European Commission under FP7 grant 246686. crew for collecting plankton samples all over the World Oceans during three years. Our special thanks go to Gaby Gorsky and Christian Sardet who facilitated our integration in the Tara Oceans consortium. We are also keen to thank the following people for providing us with planktonic samples: Jean-Marc Pagano from the Institut de Recherche pour le Développement (IRD), John Lamkin and Akihiro Shiroza from the Southeast Fisheries Science Centre (SEFSC), Cédric Guigand from the Rosentiel School of Marine and Atmospheric Science (RSMAS) and Fredrika Norrbin from the Department of Arctic and Marine Biology (The Arctic University of Norway). Our manuscript profited from stimulating discussion with Daniel Papillon who also provided English corrections. This article is the contribution no. 19 of the Tara Oceans Expedition 2009/2012.","id":"TESTFP71"}
{"text":"We are deeply grateful to the Tara schooner and This work was supported in part by the European Commission under FP7 grant 283595. crew for collecting plankton samples all over the World Oceans during three years. Our special thanks go to Gaby Gorsky and Christian Sardet who facilitated our integration in the Tara consortium. We are also keen to thank the following people for providing us with planktonic samples: Jean-Marc Pagano from the Institut de Recherche pour le Développement (IRD), John Lamkin and Akihiro Shiroza from the Southeast Fisheries Science Centre (SEFSC), Cédric Guigand from the Rosentiel School of Marine and Atmospheric Science (RSMAS) and Fredrika Norrbin from the Department of Arctic and Marine Biology (The Arctic University of Norway). Our manuscript profited from stimulating discussion with Daniel Papillon who also provided English corrections. This article is the contribution no. 19 of the Tara Expedition 2009/2012.","id":"TESTFP72"}