News Article | November 30, 2016
The following strains of mice were used (see details in following sections): Swiss Webster females and males, C57BL/6J or C57BL6/N males, B6.Cg-Tg(Pou5f1-GFP)1Scho25 males, CD-1 females and males. 6–10-week-old female mice, and 6-week- to 6-month-old male mice were used. Animals were maintained on 12 h light–dark cycle and provided with food and water ad libitum in individually ventilated units (Techniplast at TCP, Laboratory Products at UCSF) in the specific-pathogen-free facilities at UCSF and at TCP. All procedures involving animals were performed in compliance with the protocol approved by the IACUC at UCSF, as part of an AAALAC-accredited care and use program (protocol AN091331-03); and according to the Animals for Research Act of Ontario and the Guidelines of the Canadian Council on Animal Care. Animal Care Committee reviewed and approved all procedures conducted on animals at TCP. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. No statistical methods were used to predetermine sample size estimate. Unless otherwise indicated, Swiss Webster females were mated to Swiss Webster males, or to C57BL/6 males homozygous for an Oct4-GFP transgene (B6.Cg-Tg(Pou5f1-GFP)1Scho)25. Preimplantation embryos were collected at indicated time-points after detection of the copulatory plug by flushing oviducts (E1.5–E2.5) or uteri (E3.5) of pregnant females using M2 medium (Zenith Biotech) supplemented with 2% BSA (Sigma). Subsequent embryo culture was performed in 4-well plates in 5% O , 5% CO at 37 °C in KSOMAA Evolve medium (Zenith Biotech) with 2% BSA and the following inhibitors, after optimization of concentrations: 200 nM INK128 (Medchem Express), 2.5 μM 10058-F4 (Sigma), 100 ng ml−1 cycloheximide (Amresco), 50 μM Anacardic Acid (Sigma). Other mTOR inhibitors (AZD2014, Everolimus and Rapamycin (Medchem Express) and RapaLink-1 (gift of K. Shokat)) and autophagy inhibitors chloroquine (Sigma) and SBI-0206965 (Medchem Express) were used at the indicated concentrations under same culture conditions. Diapause was induced as previously described9 after natural mating of Swiss Webster mice. Briefly, pregnant females were injected at E2.5 and EDG5.5 with 10 μg tamoxifen (intra-peritoneally) and at E2.5 only with 3 mg medroxyprogesterone 17-acetate (subcutaneously). Diapaused blastocysts were flushed from uteri in M2 media after 4 days of diapause at EDG8.5. Both surgical and non-surgical embryo transfers (NSET) were performed. For surgical transfers, superovulated CD-1 females were mated to C57BL/6J or C57BL6/N males and embryos were flushed at E3.5. Embryo culture (as described above) and surgical embryo transfer into the uteri of 2.5 days post coitus pseudopregnant CD-1 females previously mated with vasectomized CD-1 males was performed essentially as described26. For NSET, Swiss Webster females were mated to vasectomized CD-1 males and transfer was performed at E2.5 of surrogate according to manufacturer’s instructions (ParaTechs, Lexington). Before embryo transfer, embryos were cultured in KSOMAA, 2% BSA without inhibitor for 1 h. In the cases indicated (Extended Data Fig. 1a), Caesarian delivery was performed at E20, followed by fostering to Swiss Webster females. Coat colour markers (agouti versus albino) were used to distinguish transferred embryos after birth. ES cell derivation was performed as previously described27. Swiss Webster females were naturally mated to Swiss Webster-C57BL/6 males heterozygous for an Oct4-GFP transgene (B6.Cg-Tg(Pou5f1-GFP)1Scho)25. Blastocysts were collected by flushing uteri of pregnant females at E3.5, and were seeded on feeders either immediately or after culturing for 7 days in KSOMAA, 2% BSA, 200 nM INK128. Imaging of fluorescence driven by the Oct4-GFP transgene and alkaline phosphatase activity (VECTOR Red AP Substrate Kit, Vector Laboratories) was performed using a Leica DM IRB microscope. For immunofluorescence stainings, normal (E3.5), in vivo diapaused or ex vivo paused embryos were fixed in 4% paraformaldehyde for 15 min, washed with PBS and permeabilized with 0.2% Triton X-100 in PBS for 15 min. After blocking in PBS, 2.5% BSA, 5% donkey serum for 1 h, embryos were incubated overnight at 4 °C with the following primary antibodies in blocking solution: phospho-4EBP1 (Thr37/46, clone 236B4), phospho-Akt (Ser473), phospho-Ulk1 (Ser757), Nanog, c-Parp, c-Caspase3 (all from Cell Signaling), H3K4me3, H4K16ac, H4K5/8/12ac, H3K9me3 (all from Millipore), Oct4 and Rex1 (Santa Cruz Biotechnology) and H3K36me2 (Abcam). Embryos were washed in PBS-Tween20, 2.5% BSA, incubated with fluorescence-conjugated secondary antibodies (Invitrogen) for 2 h at room temperature, and mounted in VectaShield mounting medium with DAPI (Vector Laboratories). For labelling nascent transcription or translation, embryos were labelled in their respective culture medium for 20 min with EU (5-ethynyl uridine) or HPG (l-homopropargylglycine) following the manufacturer’s instructions for Click-iT RNA and protein labelling kits (Thermo Fisher Scientific). Imaging was performed using a Leica SP5 confocal microscope with automated z-stacking at 10 μm intervals. Cell Profiler Software28 was used for image quantification and Prism (Graphpad Software) was used for plotting data points. Datasets do not show similar variance between control and paused/diapaused embryos in all cases, therefore we applied Welch’s correction to the statistical analysis. E14 (from B. Skarnes, Sanger Institute), Oct4-GiP (from A. Smith, University of Cambridge) and v6.5 (from R. Blelloch, UCSF) ES cell lines were used. ‘Serum’ cells were cultured in ES-FBS medium: DMEM GlutaMAX with Na Pyruvate (Thermo Fisher Scientific), 15% FBS (Atlanta Biologicals), 0.1 mM non-essential amino acids, 50 U ml−1 penicillin/streptomycin (UCSF Cell Culture Facility), 0.1 mM EmbryoMax 2-Mercaptoethanol (Millipore) and 2,000 U ml−1 ESGRO supplement (LIF, Millipore). ‘2i’ cells were cultured in ES-2i medium: DMEM/F-12, Neurobasal medium, 1× N2/B27 supplements (Thermo Fisher Scientific), 1 μM PD0325901, 3 μM CHIR99021 (Selleck Chemicals), 50 μM Ascorbic acid (Sigma) and 2,000 U ml−1 ESGRO supplement (LIF) (Millipore). ‘Paused’ cells were cultured in ES-FBS medium containing 200 nM INK128 (Medchem). ES cells can also be paused in 2i medium, but the mTOR inhibitor needs to be removed at each passaging and reintroduced after colony formation to avoid major cell death (Extended Data Fig. 6a). The cell lines have not been authenticated. E14 and v6.5 tested negative for mycoplasma contamination. Oct4-GiP was not tested. R1 (129S1×129X1)29 and G4 (129S6×B6N)30 ES cells were used for morula aggregations. ES cells were cultured in DMEM containing 10% FBS (Wisent, lot-tested to support generation of germline chimaeras), 10% KnockOut Serum Replacement, 2 mM GlutaMAX, 1 mM Na Pyruvate, 0.1 mM non-essential amino acids, 0.1 mM 2-Mercaptoethanol (all Thermo Fisher Scientific), 1,000 U ml−1 LIF (Millipore). G4 ES cells were grown on MEF obtained from TgN(DR4)1Jae/J mice at all times except one passage on gelatinized tissue culture plates before aggregation. R1 ES cells were cultured in feeder-free conditions on gelatinized tissue culture plates. CD-1 (ICR) (Charles River) outbred albino stock was used as embryo donors for aggregation with ES cells and as pseudopregnant recipients. Details of morula aggregation can be found in26. Briefly, embryos were collected at E2.5 from superovulated CD-1(ICR) female mice. Zonae pellucidae of embryos were removed by the treatment with acid Tyrode’s solution (Sigma). ES cell colonies were treated with 0.05% Trypsin-EDTA to lift loosely connected clumps. Each zona-free embryo was aggregated with 10-15 ES cells inside depression well made in the plastic dish with an aggregation needle (BLS Ltd, Hungary) and cultured overnight in microdrops of KSOMAA covered by embryo-tested mineral oil (Zenith Biotech) at 37 °C in 94% air/6% CO . The following morning morulae and blastocysts were transferred into the uteri of E2.5 pseudopregnant CD-1(ICR) females previously mated with vasectomized males. Chimaeras were identified at birth by the presence of black eyes and later by the coat pigmentation. Chimeric males with more than 50% coat colour contribution were individually bred with CD-1(ICR) females. Germline transmission of ES cell genome was determined by eye pigmentation of pups at birth and later by the coat pigmentation. 1 × 106 cells were collected and lysed in RIPA buffer containing 1× Protease Inhibitor Cocktail, 1 mM PMSF, 5 mM NaVO and 5 mM NaF. Extracts were loaded into 4–15% Mini-Protean TGX SDS Page gels (Bio-Rad). Proteins were transferred to PVDF membranes. Membranes were blocked in 5% milk/PBS-T buffer for 30 min and incubated either overnight at 4 °C or 1 h at room temperature with the following antibodies: 4EBP1 (total or pThr37/46), S6K1 (total or pThr389), Akt (total or pSer473), mTOR (total or pSer2448) (Cell Signaling Technology), Gapdh (Millipore) and anti-rabbit/mouse secondary antibodies (Jackson Labs). Membranes were incubated with ECL or ECL Plus reagents and exposed to X-ray films (Thermo Fisher Scientific). 4 × 105 cells were seeded on 6-well plates. After overnight culture, cells were incubated for 1 h with 5-ethynyl-2-deoxyuridine (EdU) diluted to 10 μM in the indicated ES cell media. All samples were processed according to the manufacturer’s instructions (Click-iT EdU Alexa Fluor 488 Imaging Kit, Thermo Fisher Scientific). EdU incorporation was detected by Click-iT chemistry with an azide-modified Alexa Fluor 488. Cells were resuspended in EdU permeabilization/wash reagent and incubated for 30 min with FxCycle Violet Stain (Thermo Fisher Scientific). For EdU dilution experiments, ES cells were labelled for 90 min in serum, and afterwards were split into either serum or pause conditions; EdU analysis was done every 12 h for 48 h. Flow cytometric was performed on a LSRII flow cytometer (BD) and analysed using FlowJo v10.0.8. Data sets show similar variance. Total nascent transcription (Ethynyl Uridine, EU) or translation (l-homopropargylglycine, HPG) were assessed in ES cells using the Click-iT RNA Alexa Fluor 488 HCS Assay kit according to the manufacturer’s instructions (Thermo Fisher Scientific). Samples were analysed on a BD LSRII. Datasets show similar variance. After overnight culture on a 96-well plate, ESCs were washed once with PBS and trypsinized to single cells. They were resuspended in 10 μl of Annexin V diluted 1:100 in Binding Buffer (BioLegend) and incubated for 10 min in the dark. Cells were resuspended in 90 μl of binding buffer with Sytox Blue (Thermo Fisher Scientific) at 1:10,000. Data were collected on a BD LSRII. Datasets show similar variance. Three replicates were used for all samples. Freshly collected single-cell suspensions were sorted on a FACSAriaII cell sorter to collect 105 cells for each sample. Total RNA was isolated using the RNeasy kit (Qiagen). All samples were spiked-in with ERCC control RNAs (Thermo Fisher Scientific) following manufacturer’s recommendations. mRNA isolation and library preparation were performed on 250 ng total RNA from all samples using NEBNext Ultra Directional RNA library prep kit for Illumina (New England Biolabs). Samples were sequenced at The Center for Advanced Technology, UCSF on Illumina HiSeq2500. Single-end 50-bp reads were mapped to the mm10 mouse reference genome using Tophat2 (ref. 31) with default parameters. We used Cuffnorm and Cuffdiff with the gtf file from UCSC mm10 (Illumina iGenomes July 17, 2015 version) as transcript annotation to evaluate relative expression level of genes (fragments per kilobase of transcript per million mapped reads (FPKM)) and call differentially expressed genes. The alignment rate exceeded 96% in all of our samples, yielding ~40 million aligned reads per sample. Data from ref. 20 and ref. 6 were downloaded from GEO and ArrayExpress, respectively, and processed with the same pipeline as our data. The absolute abundance of mRNA transcripts was estimated using the ERCC92 RNA spike-in32. ERCC92 contains 92 synthetic sequences with lengths ranging from 250 to 2,000 bp and concentration ranging over several orders of magnitude. ERCC sequences were designed to mimic mammalian mRNA, but are not homologous to the mouse genome, ensuring their unique mappability. We aligned the reads to the 92 reference spike-in sequences and compared the abundance of these sequences between different samples. As ERCC sequence abundances followed a highly linear trend in all pairs of samples across at least 5 orders of magnitude (Pearson correlation coefficient larger than 99.7%, see Extended Data Fig. 7), we assessed the absolute abundance of mRNA as the number of mRNA fragments per kilobase of transcript per 10 thousand mapped reads of ERCC. The overall abundance of ERCC spike-in sequences in our samples varied from 0.3% to 0.5% of aligned reads. To facilitate better comparison between our data and data from ref. 20 and to reduce possible batch effects, in Fig. 4e, we followed the ‘batch mean-centering’ approach widely used in microarray gene expression data analysis for batch effect removal33. Specifically, we separately mean-centred the log (FPKM + 1) value of each gene by subtracting the mean log (FPKM + 1) across all our samples (serum, 2i and paused) and across the samples from ref. 20. The numerical values of the mean-centred expression may not be directly comparable across all samples, because they may still have different dynamic ranges in different batches. We therefore used 1 − Spearman correlation coefficient as distance in the hierarchical clustering. In Fig. 4c, we identified 5,992 genes with robust expression (cell-number-normalized expression value >50 in serum, 2i, or paused states). The cell-number-normalized expression value of each gene was standardized across the 9 samples by subtracting the mean and then dividing by the standard deviation. Hierarchical clustering was performed using the standardized expression values using Euclidean metric and average linkage. In Fig. 4e, in order to compare our samples with those from ref. 20, we used the log (FPKM + 1) value of each gene. Hierarchical clustering was performed using mean-centred (within each batch) expression values of 9,418 genes robustly expressed (FPKM >10) in at least one cell state (serum, 2i, paused, diapause EPI, E2.5 MOR, E3.5 ICM, E4.5 EPI, E4.5 PrE, E5.5 EPI, or ESC 2i/LIF). 1 − Spearman correlation coefficient was used as distance and average linkage was used. For each of the 3,772 gene ontology terms that are associated with at least 10 genes34, we defined the gene ontology term expression as the mean FPKM values of genes associated with the corresponding term. In Fig. 4f, the log fold-change of gene ontology term expressions between paused ES cells and serum ES cells was plotted on the y axis against that between various samples in ref. 20 and E4.5 EPI on the x axis. The Spearman correlation coefficient of the 3,772 gene ontology terms is indicated. Extended Data Figure 10a was generated similarly, but with the log fold-change of gene ontology term expressions between Myc DKO and wild-type cells from ref. 6 on the y axis. For each of the 281 KEGG pathways that contain at least 10 genes35, we defined the pathway expression as the mean FPKM values of genes associated with the corresponding pathway. In Extended Data Fig. 9b, the log fold change of pathway expressions between paused ES cells and serum ES cells was plotted on the y axis against that between various samples in ref. 20 and E4.5 EPI. The Spearman correlation coefficient of the 281 pathways was indicated. Extended Data Fig. 10c was generated similarly, but with the log fold change of pathway expressions between Myc dKO and wild-type cells from ref. 6 on the y axis. Custom codes used for the RNA-seq analysis are available upon request. RNA-seq data have been deposited in Gene Expression Omnibus (GEO) under accession number GSE81285. RNA-seq data from refs 6 and 20 are available under the accession numbers GSE74337 and E-MTAB-2958. The authors declare that all other data supporting the findings of this study are available within the paper and its supplementary information files.
News Article | March 23, 2016
The data on TP53 mutations (including allele frequency) and CNVs in pan-tumours and AML are derived from The Cancer Genome Atlas (TCGA) data in the cBioPortal for Cancer Genomics (http://www.cbioportal.org/; accessed on 29 October 2014). Only sequenced samples with allele frequency information provided were included in our analysis. Considering potential normal tissue contamination, samples with TP53 mutation allele frequency above 0.6 were considered as a homozygous mutation. The SNP data were visualized in IGV and statistics for AML outcome were analysed in Prism 6. Since cBioPortal only has a few non-Hodgkin lymphoma cases available, we used published data to extract TP53 mutation and deletion information18, 30, 31, 32, 33, 34. Clinical outcomes were annotated from follow-up data available within the Gene Expression Omnibus GSE34171 series. CNV analysis was performed using published AML and DLBCL tumour copy number data in Affymetrix SNP Array 6.0 .cel format (http://cancergenome.nih.gov/)18, 35, 36, 37 according to GISTIC2.0 (ref. 14). Specifically, the following GISTIC parameters and values were used following the latest TCGA Copy Number Portal analysis version (3 November 2014 stddata__2014_10_17; http://www.broadinstitute.org/tcga/gistic/browseGisticByTissue): core GISTIC version 2.0.22; reference genome build hg19; amplification threshold 0.1; deletion threshold 0.1; high-level amplification threshold 1.0; high-level deletion threshold 1.0; broad length cut-off 0.50; peak confidence level 0.95; cap 1.5; gene-GISTIC, true; arm-level peel-off, true; significance threshold 0.25; join segment size 8; X chromosome removed, false; maximum segments per sample 2,000; minimum samples per disease 40. To create a conditional 11B3 chromosome deletion, the MICER strategy was used15. Briefly, MICER clones MHPN91j22 (centromeric to Sco1) and MHPP248j19 (telomeric to Alox12) (Sanger Institute) were introduced into AB2.2 ES cells (129S5 strain, Sanger Institute) by sequential electroporation, followed by G418 (neomycin; 180 μg ml−1) and puromycin (1 μg ml−1) selection, respectively. Successful recombination events were confirmed by Southern blotting using the hybridized probes designated in Supplementary Table 2 as described38. The cis- and trans-localizations of two loxP sites in doubly targeted ES cells were further distinguished by PCR with df-F and df-R, or dp-F and dp-R (Supplementary Table 2), respectively, after Adeno-cre infection and HAT (Gibco) selection. Correct cis-ES clones in which two loxP sites were integrated into the same allele were used to generate chimaera mice by blastocyst injection. The F1 pups were genotyped with 11B3-F and 11B3-R primers (Supplementary Table 2) and those positive backcrossed to C57BL/6 mouse strains for more than 10 generations. All of the mouse experiments were approved by the Institutional Animal Care and Use Committee at the Memorial Sloan Kettering Cancer Center. Eμ-Myc, Vav1-cre, Ella-cre, Trp53LSL-R270H/+, Trp53LSL-R72H/+, Trp53+/−, Trp53fl/+ and Rag1−/− mice were ordered from Jackson Laboratories21, 39, 40, 41, 42, 43, 44 and the Arf+/− mouse strain is a gift from C. Sherr45. Eμ-Myc mice with different Trp53 alterations were monitored weekly with disease state being defined by palpable enlarged solid lymph nodes and/or paralysis. Tumour monitoring was done as blinded experiments. For lymphoma generated by transplantation, 1 million Eμ-Myc HPSCs from embryonic day (E)13.5 fetal liver or autoMACS-purified B220+ B progenitor cells isolated from 6–8-week mouse bone marrow were transduced with retroviruses, followed by tail-vein injection into sublethally irradiated (6 Gy, Cs137) C57BL/6 mice (Taconic; 6–8-week old, female, 5–10 mice per cohort)11, 46. All recipient mice were randomly divided into subgroups before transplantation and monitored as described earlier. The generation of AML proceeded as previously reported29. Briefly, retrovirally infected c-Kit+ haematopoietic stem and progenitor cells were transplanted into sublethally irradiated (6 Gy, Cs137) C57BL/6 mice, followed by routine monitoring of peripheral blood cell counts and Giemsa–Wright blood smear staining. For secondary transplantation experiments, 1 million leukaemia cells were transplanted into sublethally irradiated (4.5 Gy) mice. The immunophenotypes of resulting lymphomas and leukaemias were determined by flow cytometry as previously reported using antibodies purchased from eBioscience11, 29. Statistical analysis of all survival data was carried out using the log-rank test from Prism 6. No statistical methods were used to predetermine sample size. MSCV-Myc-IRES-GFP and MLS-based retroviral constructs harbouring a GFP or mCherry fluorescent reporter and targeting Ren, Trp53, Eif5a, Nf1 or Mll3 have all been reported before11, 29, 47. For the tandem shRNA experiments performed in Fig. 3, mirE-based shRNAs targeting two different genes were cloned into an MLS-based vector in an analogous fashion to what has been previously described48, 49. Retrovirus packaging and infection of HSPCs was done as previously reported11, 29. B220+ cells were isolated from the bone marrow of 6-week-old Eμ-Myc mice by autoMACS positive selection with anti-B220 microbeads (Militeny Biotech). After overnight culture, cells were infected with retroviruses carrying the indicated shRNAs. Two days after infection, 0.5 × 106 cells were washed with PBS followed by annexin V buffer (10 mM HEPES, 140 mM NaCl, 25 mM CaCl , pH 7.4), and incubated at room temperature with Pacific Blue annexin V (BD Biosciences) and propridium iodide (PI; 1 μg ml−1; Sigma-Aldrich) for 15 min and analysed on a LSR II flow cytometer (BD Biosciences). For arachidonic acid treatment, pre-B cells were cultured out from bone marrow cells in pre-B cell medium (RPMI1640, 10% FBS, 1% penicillin/streptomycin, 50 μM β-mercaptoethanol, 3 ng ml−1 IL-7). After 3 days culture, pre-B cells were treated with a series concentration of arachidonic acid (Cayman Chemical) for 20 h, followed by annexin V staining as described earlier. Lymphoma cells isolated from lymph nodes of diseased animals were treated with vehicle (PBS) or 1 μg ml−1 adriamycin for 4 h. Whole cell lysates were extracted in cell lysis buffer (Cell Signaling Technology) supplemented with protease inhibitors (Roche), followed by SDS–PAGE gel electrophoresis and blotting onto PVDF membranes (Millipore). Eμ-Myc;Arf−/− lymphoma cell lines were used as a positive control for p53 induction. The p53 antibody used was obtained from Novocastra (NCL-p53-505) and horseradish peroxidase (HRP)-conjugated β-actin antibody from Sigma (AC-15). Alox15b expressions were examined in NIH3T3 cells, which were infected by shRNAs targeting Ren or Alox15b and then selected by G418. Anti-Alox15b antibody is from Sigma (SAB2100110), and HRP-conjugated GAPDH antibody is from ThermoFisher Scientific (MA5-15738-HRP). RNA-seq and data analysis were performed by the Integrated Genomic and Bioinformatics core at the Memorial Sloan Kettering Cancer Center. Briefly, total RNA from 11B3fl/Trp53fl;shNf1;shMll3;Vav1-cre or Trp53fl/fl;shNf1;shMll3;Vav1-cre leukaemia cells (four lines per cohort), isolated from the bone marrow of moribund mice, was isolated by Trizol extraction (Life Technologies). After ribogreen quantification (Life Technologies) and quality control on an Agilent BioAnalyzer, 500 ng of total RNA (RNA integrity number > 8) underwent polyA selection and Truseq library preparation according to instructions provided by Illumina (TruSeq RNA Sample Prep Kit v.2) with 6 cycles of PCR. Samples were barcoded and run on a Hiseq 2500 in a 50 bp/50 bp paired-end run, using the TruSeq SBS Kit v.3 (Illumina). An average of 45 million paired reads were generated per sample. At the most the ribosomal reads represented 0.1% and the percentage of mRNA bases was close to 65% on average. The output from the sequencers (FASTQ files) was mapped to the mouse genome (mm9) using the rnaStar (https://code.google.com/p/rna-star/) aligner, with the two-pass mapping methods. After mapping, the expression counts of each individual gene were computed using HTSeq (http://www-huber.embl.de/users/anders/HTSeq), followed by normalization and differential expression analysis among samples using the R/Bioconductor package DESeq (http://www-huber.embl.de/users/anders/DESeq). Gene set enrichment analysis (GSEA) was performed with Broad’s GSEA algorithm. A list of all primers used for PCR analysis is given in Supplementary Table 2. For detection and quantification of 11B3 recombination/deletion two methods were employed. In both cases genomic DNA (gDNA) was extracted from lymphoma or leukaemia cells using Puregene DNA purification kit (Qiagen). Initially, semi-quantitative PCR was used to detect the recombined 11B3 allele using primers df-F and df-R, generating a 2.2 kb product (Fig. 2d). The estimated frequency of recombination was determined by dropping gDNA from 11B3+/− into 11B3fl/+ at various ratios. For qPCR of the 11B3 deletion (Fig. 2e), SYBR Green PCR Master Mix (Applied Biosystems) was used and cycling and analysis was carried out on a ViiA 7 (Applied Biosystems). Primers 11B3-Q-F and 11B3-Q-R were used to detect the floxed allele, and to estimate the frequency of 11B3 deletion. Allelic frequency in UPD analysis (Extended Data Fig. 5a) was determined similarly, in this case with serial dilution of wild-type gDNA into DNase-free water to construct a standard curve. Two-tailed t-test is used for statistics analysis by Prism 6. For p21 gene expression examination by RT–qPCR, RNA was isolated with Trizol, cDNA was synthesized with SuperScript III First-Strand Synthesis System (Life Technologies) and qPCR was performed as described earlier with primers p21-Q-F and p21-Q-R. Trp53 exons (2–10) were amplified from genomic DNAs of 11B3-deleted lymphomas by PCR (see Supplementary Table 2 for primer sequences) and subjected to Sanger sequencing. Mutations were called only if detected in sequencing reads carried out in the forward and reverse direction. SNP analysis of isolated lymphoma (tumour) or tail (normal) genomic DNAs from the same tumour-bearing mouse were carried out by Charles River laboratory. Briefly, a SNP Taqman assay with competing FAM- or VIC-labelled probes was used to detect the relevant C57BL/6 and 129S SNPs (D11Mit4 and D11NDS16) as described previously50. Genomic DNA was extracted from freshly isolated lymphoma cells from one Eμ-Myc;11B3fl/+;Vav-cre mice. One microgram of DNA was sonicated (17 W, 75 s) on an E220 sonicator (Covaris). Samples were subsequently prepared using standard Illumina library preparation (end repair, poly A addition, and adaptor ligation). Libraries were purified using AMPure XP magnetic beads (Beckman Coulter), PCR enriched, and sequenced on an Illumina HiSeq instrument in a multiplexed format. Sequencing reads per sample were mapped using Bowtie with PCR duplicates removed. Approximately 2.5 million uniquely mappable reads were further processed for copy number determination using the ‘varbin’ algorithm51, 52 with 5,000 bins, allowing for a median resolution of ~600 kb. GC content normalization, segmentation and copy number estimation was calculated as described53. A custom shRNA library was designed to target mouse homologues (six shRNAs for one gene) to all human protein-coding genes on chromosome 17p13.1 from ALOX12 to SCO1, except TP53 and EIF5A. shRNAs were cloned into a retrovirus-based vector MLS by pool-specific PCR as previously described11. Eμ-Myc HSPCs infected with pooled shRNAs were transplanted into sublethally irradiated recipient mice. Resulting tumours were harvested, and used to extract contained shRNAs, followed by HiSeq in HiSeq 2500 (Illumina). Twenty-two oligonucleotides of shRNAs used in this study are listed in Supplementary Table 3. Total lipids were extracted using Folch’s method54 and analysed by LC-MS as previously described55. Briefly, freshly harvested cells were homogenized by chloroform/methanol (2:1, v-v). After being washed by water, the lipid-containing chloroform phase is evaporated. Dried lipids were dissolved in 100 μl 95% acetonitrile (in H O), sonicated for 3–5 min, and spiked with 10 μl of 500 ng ml−1 deuterated internal standard solution (IS; arachidonic acid-d8; Cayman Chemical, 390010). Then, 5 μl samples were injected into Acquity ultra performance liquid chromatography (UPLC) system (Waters), equipped with Acquity UPLC BEH C18 column (100 mm × 2.1 mm I.D., 1.7 μm; Waters). Samples were washed through the column with a gradient 0.1% formic acid: acetonitrile mobile elution from 35:65 (v:v) to 5:95 for 10 min. Flow rate was 0.25 ml min−1. Right after HPLC, samples were analysed in a Quattro Premier EX triple quadrupole mass spectrometer (Waters), which has electrospray negative mode and MasslynxV4.1 software. For each run, a standard curve was generated with different concentration of arachidonic acid lipid maps MS standard (Cayman Chemical, 10007268) mixed with IS (50 ng ml−1 final concentration). Arachidonic acid standard m/z is 303.2, and IS is 311.3. Three Eμ-Myc lymphoma cell lines generated from Trp53fl/+;Vav1-cre or 11B3fl/+;Vav1-cre tumour-bearing mice were cultured in BCM medium (45% DMEM, 45% IMDM, 10% FBS, 2 mM glutamine, 50 μM β- mercaptoethanol, 1× penicillin/streptomycin) in 96-well plates. Cells were treated with the indicated concentrations of 4-hydroxycyclophosphamide (Toronto Research Chemicals) or vincristine (Bedford Laboratories) for 3 days. The number of living cells was determined by PI staining and cell counting on a Guava EasyCyte (EMD Millipore). Leukaemia cell lines from Trp53∆/∆ or 11B3∆/Trp53∆;shNf1;shMll3 mice were treated with cytarabine (araC; Bedford Laboratories) or JQ1 (a gift from J. Bradner) in stem cell medium (BCM medium supplemented with 1 ng ml−1 IL-3, 4 ng ml−1 IL-6 and 10 ng ml−1 SCF) and cell viability after 3 days was determined similarly. All cytokines are from Invitrogen.
News Article | November 30, 2016
Wellcome Trust Sanger Institute and University of Cambridge researchers have created sOPTiKO, a more efficient and controllable CRISPR genome editing platform. In the journal Development, they describe how the freely available single-step system works in every cell in the body and at every stage of development. This new approach will aid researchers in developmental biology, tissue regeneration and cancer. Two complementary methods were developed. sOPiTKO is a knock-out system that turns off genes by disrupting the DNA. sOPTiKD is a knock-down system that silences the action of genes by disrupting the RNA. Using these two methods, scientists can inducibly turn off or silence genes, in any cell type, at any stage of a cell's development from stem cell to fully differentiated adult cell. These systems will allow researchers world wide to rapidly and accurately explore the changing role of genes as the cells develop into tissues such as liver, skin or heart, and discover how this contributes to health and disease. The body contains approximately 37 trillion cells, yet the human genome only contains roughly 20,000 genes. So, to produce every tissue and cell type in the body, different combinations of genes must operate at different moments in the development of an organ or tissue. Being able to turn off genes at specific moments in a cell's development allows their changing roles to be investigated. Professor Ludovic Vallier, one of the senior authors of the study from the Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute at the University of Cambridge and the Sanger Institute, said: "As a cell develops from being stem cell to being a fully differentiated adult cell the genes within it take on different roles. Before, if we knocked out a gene, we could only see what effect this had at the very first step. By allowing the gene to operate during the cell's development and then knocking it out with sOPTiKO at a later developmental step, we can investigate exactly what it is doing at that stage." The sOPTiKO and sOPTIKD methods allow scientists to silence the activity of more than one gene at a time, so researchers have the possibility to now investigate the role of whole families of related genes by knocking down the activity of all of them at once. In addition, the freely available system allows experiments to be carried out far more rapidly and cheaply. sOPTiKO is highly flexible so that it can be used in every tissue in the body without needing to create a new system each time. sOPiTKD allows vast improvements in efficiency: it can be used to knock down more than one gene at a time. Before, to silence the activity of three genes, researchers had to knock down one gene, grow the cell line, and repeat for the next gene, and again for the next. Now it can do it all in one step, cutting a nine-month process down to just one to two months. Dr. Alessandro Bertero, one of the first authors of the study from the Cambridge Stem Cell Institute, said: "Two key advantages of using sOPTiKO/sOPTIKD over other CRISPR editing systems are that it is truly inducible and can work in almost any cell type. In the past we have been hampered by the fact we could study a gene's function only in a specific tissue. Now you can knock out the same gene in parallel in a diversity of cell type with different functions." For a video of the methods in action see below:
News Article | September 7, 2016
After more than a decade of work, and at a cost of around US$3 billion, the Human Genome Project yielded the DNA base sequence of a representative human genome in 2001. Now, some 15 years later, technological advances have created the next generation of sequencing machines, which are capable of sequencing many genomes in a day at a cost of around $1,000 each (see 'Technological leap'). “The sequencing is almost the easy part now,” says Cordelia Langford, senior scientific operations manager at the Sanger Institute in Hinxton, UK, and a participant in the original Human Genome Project. The technology is not perfect: inaccuracies still creep into the sequencing data, and some regions of DNA cannot be sequenced at all. Then huge analytical effort is required to do something useful with the data generated. Nonetheless, the ability of modern technology to achieve so quickly and cheaply what once took years of enormously expensive work is making the dream of precision medicine more plausible by the day. Genome sequencing reveals the exact order in which nucleotide molecules — each containing one of four bases, adenine (A), cytosine (C), guanine (G) and thymine (T) — are arranged along the strand of DNA. There are about 3 billion bases in a human genome sequence, arranged as complementary pairs that hold matching strands of the DNA double helix together, and they are distributed across 23 pairs of chromosomes. Patients around the world are already benefiting from genome sequencing, and the cost is falling so sharply that the practice could soon become almost routine. The Sanger Institute, for example, is sequencing the genomes of patients with rare diseases and cancer as part of the 100,000 Genomes Project organized by Genomics England. Some participants already benefit from improved diagnosis and treatment, and researchers are discovering more about the genetic variations that cause disease. Sequencing is not the only option in genetic analysis, however. A key part of the Precision Medicine Initiative, run by the US National Institutes of Health, is the more conventional, and arguably less technologically heroic, approach of genotyping. Here, the variants of specific genes that people carry are identified without knowing their full genome sequence. But genotyping requires some idea of what to look for. Sequencing is the only way to uncover everything about the DNA that governs the onset and progression of so many diseases, and to learn how our DNA keeps us healthy. To sequence a genome, you must first smash it into millions of bits. The original method used by the Human Genome Project, known as Sanger sequencing, made copies of parts of the initial fragments of DNA, each copy a single nucleotide longer than the last. These were then laboriously separated on electrophoresis gels and identified by the radioactively or fluorescently labelled nucleotides at the end of each strand. “Each of the fragments had to be sequenced one, or just a few, at a time,” explains Langford. Sanger sequencing is still in use today, albeit in a more automated form. The technological advance that allows genomes to be sequenced in a single day is massively parallel sequencing. Billions of fragments can now be sequenced and read simultaneously, Langford says. The Sanger Institute uses and tests several modern sequencing methods — part of its remit is to assess emerging technologies. Its main workhorse, however, and the method used most often in the 100,000 Genomes Project, is sequencing by synthesis (SBS). This is a finely choreographed cycle in which enzymes build strands of DNA that are complementary to template strands derived from the fragments of the genome being sequenced. Each new strand is built by adding the nucleotides that match the template one by one. At each step, fluorescently labelled nucleotides bring the synthesis process to a temporary halt. An optical analysis system then scans the strands, which are held on a glass plate about the size of a microscope slide, and detects by way of coloured signals which nucleotides have been added. The chemical groups that block further synthesis can then be cut off and washed away, and another cycle of synthesis begins. In this way, nucleotide by nucleotide, base by base, new strands are synthesized as specified by the template strands, and the sequence in which the bases are added is recorded. The technique was invented in the 1990s by University of Cambridge spin-out company Solexa, which was acquired in 2007 by Illumina, a company based in San Diego, California, that now claims a roughly 90% share of sequenced bases worldwide. “Developing the technology required the use of genetic engineering to create enzymes that will work with the modified fluorescent nucleotides,” explains Illumina's chief scientist, David Bentley. These reactions are based on the way DNA is copied in living cells. Crucial to the advancement, Bentley says, has been the move away from natural reagents. The adoption of non-natural chemistry makes modern sequencing reactions robust and efficient enough to operate at the speeds necessary to sequence genomes in hours, rather than years, he says. The next big challenge is one for software: analysing all the sequenced fragments and piecing them back together to form a three-billion-base genome sequence. Langford likens this to completing an incredibly complex jigsaw. But whereas a jigsaw puzzle comes with a complete picture for guidance, all the computer has to help it decide where the fragments should fit is the reference genome, derived from the Human Genome Project. The reference genome is a representative example of a human genome that approximates what the pieces in our individual jigsaws will create, but with slight differences that make us who we are — and these differences are central to the aims of precision medicine. Illumina's SBS is one of several technologies that can read a person's genetic code. Ion-torrent sequencing, for example, is quite similar to SBS: it also reads the sequence piece by piece from a newly synthesized strand of DNA. But rather than use a coloured marker to denote each nucleotide, the signal that distinguishes the bases comes from hydrogen ions that are released into solution when new nucleotides are added. The ions cause a detectable blip in the pH of the solution, and these blips translate into a sequence. The machine washes each nucleotide in turn through the system and monitors which one causes the ion torrent at each stage. The length of the fragments sequenced, and therefore the complexity of piecing together the jigsaw puzzle afterwards, also varies between techniques. Some of the longest fragments are sequenced by biotech company Pacific Biosciences, based in Menlo Park, California. “Our technology delivers DNA sequence reads about one hundred times longer than the short-read technologies used in most next-generation sequencing,” says Jonas Korlach, the company's chief scientific officer. “This makes understanding and assembling the sequence reads into complete genomes much easier.” Reading longer unbroken sections of DNA also helps to reveal complex long-range structural features, but such long-read technologies are often more expensive than other techniques. The UK company Oxford Nanopore Technologies uses a unique system in which DNA strands are fed through tiny protein nanopores that have been inserted into a polymer membrane. Rather than requiring any DNA synthesis, the system simply notes the sequence of nucleotides passing through the nanopore, based on specific electrical signals generated by different combinations of bases. This is the technology behind the company's MinION — a portable sequencing device about the same size as a mobile phone. Clive Brown, chief technology officer at Oxford Nanopore, says that the device weighs less than 100 g; the next-smallest box on the market is 46 kg, he adds. Portability may be most important in remote areas, such as makeshift clinics set up to tackle emerging diseases in developing countries. MinION sequencing, for example, was used to sequence short viral genomes in field hospitals during the 2014 Ebola outbreak in West Africa. Portability is simple to compare across technologies, but not all comparisons are so straightforward. Cost per sequence, for instance, depends as much on how many genomes a lab is sequencing as it does on the system being used. Accuracy can be difficult to pin down too. Manufacturers talk about accuracy of between 90% and 99.9%, often at the higher end of the range, but that still adds up to a large number of individual reads of a sequence that contain errors ( et al. Genome Med. 8, 24; 2016). For this reason, genome sequencing is often repeated multiple times to achieve a truly reliable result. Practitioners talk about sequencing to differing degrees of 'depth', depending on how many times the same DNA is sequenced to increase confidence in the results. It is the accuracy of the final collated analysis that really matters. Regardless of which sequencing technology is used, researchers and clinicians face an important decision about whether to sequence an entire genome or to take a more targeted approach. They can choose to focus on a specific region of interest in a particular chromosome. They can choose to examine only the genes that actually code for proteins or functional RNA molecules, while ignoring the vast bulk of our DNA — often misleadingly called junk DNA — that may have a crucial regulatory role or have no real function. The exome, for example, is the part of the genome comprising only the stretches of DNA called exons that code for protein molecules.Targeting only these regions is like fishing: it requires bait. As Langford explains, an exome bait can be a collection of small sections of synthetic DNA that will bind by base-pairing to regions of DNA in a sample that identify exons. Each piece of exome bait has a corresponding magnetic bead attached to it. An external magnet is used to literally pull down the exon DNA, leaving everything else to be discarded. “It is an absolutely beautifully elegant technology,” says Langford. Researchers can either devise their own baits for the specific parts of the genome they are interested in, or they can buy commercial bait kits that target either the whole exome or specific parts. “Clinical applications will differ as to whether a targeted approach is enough,” says Illumina's Bentley. Looking at whole genomes can detect the unexpected, such as genes that were not suspected of having a role in a disease and whose significance may be missed by a targeted approach. “For some studies exome sequencing may be okay, but it will become increasingly less sufficient as precision medicine builds,” Bentley says. “There will be a moral imperative to try to fully characterize every patient and not miss anything.” Many large medical centres now have dedicated gene-sequencing centres that offer the whole gamut, from whole-genome sequencing to the precise targeting of specific genes. The Dana-Farber Cancer Institute in Boston, Massachusetts, for example, outlines the choices to patients on its website, saying: “Before starting a project, we will discuss the best sequencing strategies, experimental design, and analysis options with you.” It goes on to explain that whole-genome sequencing can discover most genomic aberrations, but that targeted sequencing is often sufficient for many clinical applications. It points out that “targeted sequencing has the advantage of sequencing larger sample sizes with lower cost and easier data analysis.” In a comprehensive review of the current state of gene-sequencing technologies, Sara Goodwin of Cold Spring Harbor Laboratory in New York discusses some of the factors that influence decisions about which technologies and methods to use ( et al. Nature Rev. Genet. 17, 333–351; 2016). Limiting the scope of an analysis can sometimes be crucial in getting fast results, she says, adding that the limiting factor for speed is often the data analysis, rather than the actual sequencing. Langford agrees, highlighting the need for “highly sophisticated software algorithms to handle the huge stream of data emerging from a modern sequencing machine”. The coming years are likely to bring more diverse applications of sequencing technology. The basic strategies that are used in DNA sequencing can also, for instance, be used to sequence RNA. Looking at RNA focuses attention on many of the parts of the genome that are most likely to have functional significance — but it may miss regions of DNA that have crucial regulatory roles, even though they are never copied into RNA. The choice of DNA or RNA sequencing, or a combination of the two, will depend on the clinical situation. Another target, which reveals a limitation of the existing technology, is the pattern of epigenetic chemical modifications carried by some of the four bases of DNA. These modifications, such as the addition of methyl groups to specific bases, can be crucial in controlling the activity of genes — and knowing whether a gene is active can be at least as valuable as knowing which genes are present in a sequence. Bentley says that efforts to add epigenetic analysis to the sequencing toolbox are still in the research phase, but that it would provide an important additional level of information. Variations that are of crucial clinical significance may be missed by just looking at the four bases in DNA, he says, rather than by considering the effects of whatever chemical modifications they may carry. Existing sequencing technologies are already helping many individual patients, but personalized sequencing cannot yet reveal everything that clinicians need to know to fully understand the links between DNA and disease. The technology has come a long way in the past 15 years, but “there are still many mountains ahead,” says Bentley. He seems confident that solutions are within reach, however. The march towards the widespread use of personalized gene sequence analysis is well under way and is showing little sign of slowing.
News Article | October 31, 2016
The billionaire is the first major donor to back the idea of creating an atlas of all human cells. Stephen Quake’s laboratory at Stanford University looks like biology’s version of Thomas Edison’s famous New Jersey workshop. Roll-down curtains cast shadows across odd devices buzzing and clicking in the aisles. You half expect to find Quake, author of 135 patents and rarely seen wearing anything other than a faded polo shirt, sleeping on one of the benches, just as the Wizard of Menlo Park was known to. In September, Quake was named co-president of the BioHub, a new $600 million center funded by Facebook billionaire Mark Zuckerberg. BioHub has as its premier project helping to create a vast directory of human cells, which it calls a “cell atlas.” Quake and BioHub are also part a consortium of researchers around the globe who say mapping the millions of cells in the human body is a feat that could help drugmakers and scientists find new ways to treat disease. Textbooks say there are about 300 types of cells in the human body, including the ones that carry oxygen in the blood, the long-lived neurons in the brain, and the photoreceptors in the eye that work like a digital camera. But the real number is probably far larger—perhaps 10,000, says Quake. It’s just that they can’t be distinguished under an ordinary microscope. What scientists want to do now is to inspect tens of millions of human cells for their molecular signatures and also locate each type in the body. That sort of map could be useful to scientists or drugmakers, who might, for instance, look up which cells a new drug is likely to effect. Cataloging how the immune system changes and adapts to fight tumors could be the source of the next insights for cancer treatments. The atlas project is possible thanks to inventions by Quake and others that allow researchers to move individual cells around channels on microfluidic chips. These techniques underlie the atlas because scientists can capture cells inside bubbles of oil or water, moving them apart and readying them for one-by-one analysis by genetic sequencers. “I don’t know if it’s the number one hot area in biology, but it’s close. Everyone and their grandma wants to do this,” says Evan Macosko, a molecular biologist at Harvard University. One approach ready for massive-scale data production involves detecting which proteins an individual cell is trying to manufacture. The readout, which acts as a molecular fingerprint, has already led to the discovery of new cell types in the retina and brain. A method developed by Macosko and others has helped bring the cost down to only 17 cents per cell. Relying on that technique, which her lab co-invented, Aviv Regev, a scientist at the Broad Institute, in Cambridge, Massachusetts, this year authored a proposal to donors to catalogue 50 million cells over five years at a cost of $100 million. Quake says that the BioHub, which will also hand out grants to researchers at Stanford, the University of California, Berkeley, and the University of California, San Francisco, wants to further develop technologies that would let scientists analyze cells—and their molecular contents—directly in samples of tissue. That way, they wouldn’t just produce a census of cell types, but a true map of how the body’s 20 trillion cells fit together. One new chemical technique, for instance, can turn a dead mouse entirely transparent (and therefore visible to microscopes). Another uses the chemical found in diapers to blow tissues up to huge size, again for easier inspection. Zuckerberg and his wife, Priscilla Chan, have said they plan to give away $3 billion over 10 years to fight disease, something that would make the couple the largest private funders of basic biology research after the Howard Hughes Medical Institute, says Marc Kastner, head of the Science Philanthropy Alliance and an adviser to the 32-year-old billionaire. With the BioHub, which is his charity’s first science project, Zuckerberg is also set to become the biggest funder of the cell atlas technologies, an idea Kastner says government funding agencies have been slow to embrace. “BioHub is still very small scale compared to what is needed to make progress,” he says. “It’s going to take an international effort of huge magnitude.” In fact, there is already a group called the International Human Cell Atlas Consortium, which is developing mapping strategies and hoping to get the National Institutes of Health and European funders like the Wellcome Trust interested. It met for the first time earlier this month in London. Quake is also part of that group, which is led by Regev and Sara Teichmann of Britain’s Sanger Institute. “It’s starting to take shape,” says Quake. “I think 2017 is going to be a big year for the cell atlas.”
News Article | November 10, 2016
LONDON (Reuters) - A multidrug-resistant superbug infection that can cause life-threatening illness in people with cystic fibrosis (CF) has spread globally and is becoming increasingly virulent, British researchers said on Thursday. In a study published in the journal Science, the researchers said the bug, a species of multidrug-resistant bacteria called Mycobacterium abscessus (M. abscessus), can cause severe pneumonia and is particularly dangerous for patients with CF and other lung diseases. "The bug initially seems to have entered the patient population from the environment, but we think it has recently evolved to become capable of jumping from patient to patient, getting more virulent as it does so," said Andres Floto, a Cambridge University professor who co-led the study. Cystic fibrosis is a relatively rare genetic disorder that affects the respiratory, digestive and reproductive systems. It causes patients' lungs to become clogged up with thick, sticky mucus and makes them vulnerable to respiratory infections. In this study, researchers from Cambridge and the Wellcome Trust Sanger Institute sequenced the genomes of more than 1,000 samples of mycobacteria from 517 CF patients at specialist clinics in Europe, the United States and Australia. They found that the majority of patients had picked up transmissible forms of M. abscessus that had spread globally. Further analysis suggested the infection may be transmitted within hospitals via contaminated surfaces and through the air, the researchers said - presenting a serious challenge to infection control practices in hospitals. Because the superbug has already become resistant to many antibiotics, it is also extremely difficult to treat successfully, Floto said. Patients infected with it need 18 months or more of treatment with a combination of powerful antibiotics, and fewer than one in three cases is cured. Julian Parkhill of the Sanger Institute, who worked on this study, said that while its findings were alarming for CF patients, they did also provide a degree of hope. "Now that we know the extent of the problem and are beginning to understand how the infection spreads, we can start to respond," he said. The sequencing data has thrown up potential new drug targets, he explained, and the researchers now plan to focus on seeking to develop new medicines to beat the bug.
News Article | March 14, 2016
LONDON (Reuters) - Scientists say they have conclusive evidence that changes to a gene called SETD1A can dramatically raise the risk of developing schizophrenia - a finding that should help the search for new treatments. The team, led by researchers at Britain's Wellcome Trust Sanger Institute, said damaging changes to the gene happen very rarely but can increase the risk of schizophrenia 35-fold. Changes in SETD1A also raise the risk of a range of neurodevelopmental disorders, the researchers said. In a study published in the journal Nature Neuroscience, the team found that mutations that remove the function of SETD1A are almost never found in the general population, but affect 1 in 1,000 people with schizophrenia. While this gene fault explains only a very small fraction of all schizophrenia patients, it provides an important clue to the wider biology of the disorder, they said. Schizophrenia is a severe and common psychiatric illness that affects around one in 100 people worldwide. Symptoms include disruptions in thinking, language and perception, and patients can also suffer psychotic experiences such as hearing voices or having delusions. While the exact causes of schizophrenia are unknown, research to date suggests a combination of physical, genetic, psychological and environmental factors can make people more likely to develop it. Jeff Barrett, who led the study for the Sanger Institute, said its results were surprising and exciting. "Psychiatric disorders are complex diseases involving many genes, and it is extremely difficult to find conclusive proof of the importance of a single gene," he said. Mike Owen, a Cardiff University expert in neuropsychiatric genetics and genomics, said the so-far limited understanding of schizophrenia's causes has hampered efforts to develop new treatments. "Current drugs are only effective in alleviating some of the symptoms, can lead to troubling side effects and are ineffective in a sizeable minority of cases," he said. This new finding about defects in the SETD1A gene - although only explaining a small fraction of cases - may guide researchers towards new pathways that could be targets for treatments or medicines in a larger number of cases, Owen said. The study analysed the genome sequences of more than 16,000 people from Britain, Finland and Sweden, including those from 5,341 people with schizophrenia. Damage to the SETD1A gene was found in 10 of the schizophrenia patients, and surprisingly also in six other people with other developmental and neuropsychiatric disorders such as intellectual disability, the scientists said. This shows the same gene is involved in both schizophrenia and developmental disorders and suggests they may share common biological pathways.
News Article | October 29, 2016
A new study has confirmed for the first time that interbreeding between chimpanzees and bonobos happened in the ancient past. These two apes, found in tropical Africa are considered the closest relatives of mankind. This means the earlier concepts of strict genetic demarcation between the two are blurring. It is believed that Chimpanzees and bonobos are diversified descendants of a common ancestor, separated some 2 million years ago. The study also busted the myth that gene flow between the two species was impossible as the Congo River was a big physical barrier for them. The new finding adds to the repertoire of other theories that include gene mixing between Neanderthals and humans. Published in the journal Science, the findings asserted that one percent of chimpanzee genomes are indeed bonobos-derived. The study was conducted by scientists at the Wellcome Trust Sanger Institute and offers a significant contribution to conservation efforts. It examined the whole genome sequences of 75 chimpanzees and bonobos belonging to 10 different African countries in which 40 were new-born chimpanzees from known geographies. The analysis established a clear linkage between genetic sequence of chimpanzees and their geographic origin. The emphasis on segregating individual chimpanzees based on their country of origin will be a boost in returning captured chimps to their right places of origin The leader of the study, Tomàs Marquès-Bonet from the Institute of Biological Evolution (University Pompeu Fabra and CSIC), Barcelona expressed that the study was unique. He claimed it was the first study to reveal ancient gene flow process among the living species, which are closest to human evolution. "It implies that successful breeding between close species might have been actually widespread in the ancestors of humans and living apes." Chris Tyler-Smith, from the Wellcome Trust Sanger Institute, said the largest analysis of chimpanzee genomes can precisely detect a wild chimpanzee's actual home. That will certainly aid in the release of illegally captured chimpanzees and in sending them back to the right place. As an endangered species, Chimpanzees and bonobos are facing threats of illegal capture and confinement despite protection by law . Reflecting on the study's contribution to conservation efforts, Chris Tyler-Smith, from the Wellcome Trust Sanger Institute, said the analysis of chimpanzee genomes would go a long way in locating precisely from where a chimpanzee has come. It may be recalled that chimpanzees are an endangered species and in many places, they are illegally captured and confined. The genome analysis will come handy in releasing the chimps to their right habitat and in acting against predators by using the key evidence. Yali Xue of the Sanger Institute said central and eastern chimpanzees share more genetic material with bonobos compared to other subspecies of chimpanzees. Meanwhile, studies on the peer relation of chimps have thrown up interesting features, according to a report in Tech Times. © 2017 Tech Times, All rights reserved. Do not reproduce without permission.
News Article | October 27, 2016
For the first time, scientists have revealed ancient gene mixing between chimpanzees and bonobos, mankind's closest relatives, showing parallels with Neanderthal mixing in human ancestry. Published today in the journal Science, the study from scientists at the Wellcome Trust Sanger Institute and their international collaborators showed that 1% of chimpanzee genomes are derived from bonobos. The study also showed that genomics could help reveal the country of origin of individual chimpanzees, which has strong implications for chimpanzee conservation. Chimpanzees and bonobos are great apes found only in tropical Africa. They are endangered species and are supposedly fully protected by law, yet many chimpanzees and bonobos are captured and held illegally. To aid the conservation effort, researchers analysed the whole genome sequences of 75 chimpanzees and bonobos, from 10 African countries, and crucially included 40 new wild-born chimpanzees from known geographic locations. They discovered that there was a strong link between the genetic sequence of a chimpanzee, and their geographic origin. Dr Chris Tyler Smith, from the Wellcome Trust Sanger Institute, said: "This is the largest analysis of chimpanzee genomes to date and shows that genetics can be used to locate quite precisely where in the wild a chimpanzee comes from. This can aid the release of illegally captured chimpanzees back into the right place in the wild and provide key evidence for action against the captors." Chimpanzees and bonobos are the closest living relatives of human beings. They diverged from a common ancestor between 1.5 and 2 million years ago and live in different areas of tropical Africa. Until now, it was thought that gene flow between the species would have been impossible, as they were physically separated by the Congo River. The study confirmed a main separation between chimpanzees and bonobos approximately 1.5 million years ago, and the presence of four chimpanzee subspecies in different regions. However, the researchers also found there were two additional gene flow events between the chimpanzee and bonobo populations, indicating that at least some individuals found their way across the river. Dr Yali Xue, from the Sanger Institute, said: "We found that central and eastern chimpanzees share significantly more genetic material with bonobos than the other chimpanzee subspecies. These chimpanzees have at least 1% of their genomes derived from bonobos. This shows that there wasn't a clean separation, but that the initial divergence was followed by occasional episodes of mixing between the species. The study also included researchers from Spain, Copenhagen Zoo and the University of Cambridge and showed that there have been at least two phases of secondary contact, 200-550 thousand years ago and around 150 thousand years ago, mirroring what is believed to have happened during the last 100 thousand years of the evolution of humans. Dr Tomàs Marquès-Bonet, leader of the study from the Institute of Biological Evolution (University Pompeu Fabra and CSIC), Barcelona, said: "This is the first study to reveal that ancient gene flow events happened amongst the living species closest to humans - the bonobos and chimpanzees. It implies that successful breeding between close species might have been actually widespread in the ancestors of humans and living apes." The Institute of Evolutionary Biology (IBE) is a joint center between Pompeu Fabra University (UPF) and the Spanish National Research Council (CSIC), and was created in 2008 in Barcelona. IBE researchers study the processes and mechanisms that generate biodiversity, including fields like genetics and molecular evolution, population biology, biology of complex systems and the recovery of ancient DNA. https:/ The Wellcome Trust Sanger Institute is one of the world's leading genome centres. Through its ability to conduct research at scale, it is able to engage in bold and long-term exploratory projects that are designed to influence and empower medical science globally. Institute research findings, generated through its own research programmes and through its leading role in international consortia, are being used to develop new diagnostics and treatments for human disease. http://www. Wellcome exists to improve health for everyone by helping great ideas to thrive. We're a global charitable foundation, both politically and financially independent. We support scientists and researchers, take on big problems, fuel imaginations and spark debate. http://www.
News Article | February 15, 2017
A team at the Wellcome Trust Sanger Institute has discovered how a promising malarial vaccine target - the protein RH5 - helps parasites to invade human red blood cells. Published today in Nature Communications, the study reveals that a previously mysterious protein on the surface of the parasite called P113 anchors the RH5 protein, and provides a molecular bridge between the parasite and a red blood cell. The discovery could be used to make a more effective malaria vaccine. More than 200 million people a year are infected with malaria and the disease caused the deaths of nearly half a million people worldwide in 2015. Children under the age of five made up 70 percent of these deaths. Malaria is caused by Plasmodium parasites which are spread by infected mosquitos and an effective vaccine would vastly improve the lives of millions of people. Previous research by teams at the Sanger Institute discovered that to invade human red blood cells, Plasmodium parasites need RH5 to bind to a receptor called basigin on the surface of the blood cells. However, it was not known how RH5 was attached to the surface of the parasite. In this latest study the researchers discovered that when the Plasmodium RH5 protein is released, it is immediately caught by another parasite protein called P113. Thousands of P113 molecules on the surface of each parasite act like a Velcro chain, capturing RH5 at the surface of the parasite. The tethered RH5 then binds to the basigin receptor on the human red blood cell, bridging the gap just long enough to let the parasite invade the blood cell. Dr Julian Rayner, an author on the study from the Sanger Institute, said: "We knew both proteins were essential for invasion but this is the first time anyone has seen the interaction between RH5 and P113 and showed that they work together. In theory, an antibody that blocked P113 could stop RH5 binding and so prevent the parasite from gaining entry to red blood cells. This makes the P113 protein another good vaccine target." Two more proteins - CyRPA and RIPR - were already known to be essential to the parasite and to form a complex with RH5. The researchers uncovered the details of how these three proteins bound to each other* and that only one small part of the RH5 protein was needed to bind P113. This small region could become an easy-to-produce and cost-effective part of a multi-component malaria vaccine. Dr Francis Galway, first author on the study from the Sanger Institute, added: "RH5 is an excellent vaccine target because it is essential for invasion by all strains of Plasmodium falciparum - the species of parasite that causes the most severe disease in humans. This study shows us the binding partners for the RH5 protein and how these work together to allow the parasite to enter red blood cells. This gives us important information about this vaccine target." Dr Gavin Wright, lead author from the Sanger Institute, said: "There is a great need for an effective malaria vaccine, and the RH5 complex is the most important link between parasite and host that we yet know of. This study shows us how this works, and reveals other essential malarial proteins to target. As RH5 is only exposed from the parasite briefly, a combination vaccine based on P113, RH5 and other proteins in the complex could be more effective than RH5 alone." For more information about malaria please see: http://www. For more information about developing malaria vaccines please see: http://www. * A pair of proteins, CyRPA and RIPR, were already known to be essential to the parasite and form a complex with RH5. This study found that CyPRA bound to the RH5 C-terminal region, and that RIPR bound to CyPRA. The Wellcome Trust Sanger Institute is one of the world's leading genome centres. Through its ability to conduct research at scale, it is able to engage in bold and long-term exploratory projects that are designed to influence and empower medical science globally. Institute research findings, generated through its own research programmes and through its leading role in international consortia, are being used to develop new diagnostics and treatments for human disease. http://www. Wellcome exists to improve health for everyone by helping great ideas to thrive. We're a global charitable foundation, both politically and financially independent. We support scientists and researchers, take on big problems, fuel imaginations and spark debate. http://www.