Unbiased Mapping Research Articles

DeltaNp63-dependent super enhancers define molecular identity in pancreatic cancer by an interconnected transcription factor network

Molecular subtyping of cancer offers tremendous promise for the optimization of a precision oncology approach to anticancer therapy. Recent advances in pancreatic cancer research uncovered various molecular subtypes with tumors expressing a squamous/basal-like gene expression signature displaying a worse prognosis. Through unbiased epigenome mapping, we identified deltaNp63 as a major driver of a gene signature in pancreatic cancer cell lines, which we report to faithfully represent the highly aggressive pancreatic squamous subtype observed in vivo, and display the specific epigenetic marking of genes associated with decreased survival. Importantly, depletion of deltaNp63 in these systems significantly decreased cell proliferation and gene expression patterns associated with a squamous subtype and transcriptionally mimicked a subtype switch. Using genomic localization data of deltaNp63 in pancreatic cancer cell lines coupled with epigenome mapping data from patient-derived xenografts, we uncovered that deltaNp63 mainly exerts its effects by activating subtype-specific super enhancers. Furthermore, we identified a group of 45 subtype-specific super enhancers that are associated with poorer prognosis and are highly dependent on deltaNp63. Genes associated with these enhancers included a network of transcription factors, including HIF1A, BHLHE40, and RXRA, which form a highly intertwined transcriptional regulatory network with deltaNp63 to further activate downstream genes associated with poor survival.

Mapping genotype to phenotype

Evolutionary Genomics Identifying genetic factors that contribute to trait variation among species is difficult. Weiss et al. developed a method for unbiased genome-scale mapping of trait differences and used it to work out how a range of yeast species evolved. When crossed, these yeast species produce sterile offspring, preventing the use of traditional genetic-mapping techniques. However, by reciprocal hemizygosity analysis via sequencing (RH-seq), alleles that contributed to differences in thermotolerance were spotted that diverged between two species. Surprisingly, these turned out to map to essential housekeeping genes. Thus, without taking a candidate locus approach, RH-seq allowed identification of genes responsible for traits that differ between species. Nat. Genet. 50 , 1501 (2018).

Extreme allelic heterogeneity at a Caenorhabditis elegans beta-tubulin locus explains natural resistance to benzimidazoles.

Benzimidazoles (BZ) are essential components of the limited chemotherapeutic arsenal available to control the global burden of parasitic nematodes. The emerging threat of BZ resistance among multiple nematode species necessitates the development of novel strategies to identify genetic and molecular mechanisms underlying this resistance. All detection of parasitic helminth resistance to BZ is focused on the genotyping of three variant sites in the orthologs of the β-tubulin gene found to confer resistance in the free-living nematode Caenorhabditis elegans. Because of the limitations of laboratory and field experiments in parasitic nematodes, it is difficult to look beyond these three sites to identify additional mechanisms that might contribute to BZ resistance in the field. Here, we took an unbiased genome-wide mapping approach in the free-living nematode species C. elegans to identify the genetic underpinnings of natural resistance to the commonly used BZ, albendazole (ABZ). We found a wide range of natural variation in ABZ resistance in natural C. elegans populations. In agreement with known mechanisms of BZ resistance in parasites, we found that a majority of the variation in ABZ resistance among wild C. elegans strains is caused by variation in the β-tubulin gene ben-1. This result shows empirically that resistance to ABZ naturally exists and segregates within the C. elegans population, suggesting that selection in natural niches could enrich for resistant alleles. We identified 25 distinct ben-1 alleles that are segregating at low frequencies within the C. elegans population, including many novel molecular variants. Population genetic analyses indicate that ben-1 variation arose multiple times during the evolutionary history of C. elegans and provide evidence that these alleles likely occurred recently because of local selective pressures. Additionally, we find purifying selection at all five β-tubulin genes, despite predicted loss-of-function variants in ben-1, indicating that BZ resistance in natural niches is a stronger selective pressure than loss of one β-tubulin gene. Furthermore, we used genome-editing to show that the most common parasitic nematode β-tubulin allele that confers BZ resistance, F200Y, confers resistance in C. elegans. Importantly, we identified a novel genomic region that is correlated with ABZ resistance in the C. elegans population but independent of ben-1 and the other β-tubulin loci, suggesting that there are multiple mechanisms underlying BZ resistance. Taken together, our results establish a population-level resource of nematode natural diversity as an important model for the study of mechanisms that give rise to BZ resistance.

Optogenetic precision toolkit to reveal form, function and connectivity of single neurons.

All-optical methods enable the control and monitoring of neuronal activity with minimal perturbation of the system. Although imaging and optogenetic manipulations can be performed at cellular resolution, the morphology of single cells in a dense neuronal population has often remained unresolvable. Here we describe in detail two recently established optogenetic protocols for systematic description of function and morphology of single neurons in zebrafish. First, the Optobow toolbox allows unbiased mapping of excitatory functional connectivity. Second, the FuGIMA technique enables selective labeling and anatomical tracing of neurons that are responsive to a given sensory stimulus or correlated with a specific behavior. Both strategies can be genetically targeted to a neuronal population of choice using the Gal4/UAS system. As these in vivo approaches are non-invasive, we envision useful applications for the study of neuronal structure, function and connectivity during development and behavior.

Using a Statistical Preanalysis Approach as an Ensemble Technique for the Unbiased Mapping of GCM Changes to Local Stations

Abstract Accounting for climate change, GCM-based projections and their uncertainty are relevant to study potential impacts on hydrological regimes as well as to analyze, operate, and design water infrastructure. Traditionally, several downscaled and/or bias-corrected GCM projections are individually or jointly used to map the raw GCMs’ changes to local stations and evaluate uncertainty. However, the preservation of GCMs’ statistical attributes is by no means guaranteed, and thus alternative methods to cope with this issue are needed. This work develops an ensemble technique for the unbiased mapping of GCM changes to local stations, which preserves local climate variability and the GCMs’ statistics. In the approach, trend percentiles are extracted from the GCMs to represent the range of future long-term climate conditions to which local climatic variability is added. The approach is compared against a method in which each GCM is individually used to build future climatic scenarios from which percentiles are computed. Both approaches were compared to study future precipitation conditions in three Chilean basins under future climate projections based on 45 GCM runs under the RCP8.5 scenario. Overall, the approaches produce very similar results, even if a few trend percentiles are adopted in the GCM preanalysis. In fact, using 5–10 percentiles produces a mean absolute difference of 0.4% in the estimation of the probabilities of consecutive years under different precipitation thresholds, which is ~60% less than the error obtained using the median trend. Thus, the approach successfully preserves the GCM’s statistical attributes while incorporating the range of projected climates.

Integrated Brain Atlas for Unbiased Mapping of Nervous System Effects Following Liraglutide Treatment

Light Sheet Fluorescence Microscopy (LSFM) of whole organs, in particular the brain, offers a plethora of biological data imaged in 3D. This technique is however often hindered by cumbersome non-automated analysis methods. Here we describe an approach to fully automate the analysis by integrating with data from the Allen Institute of Brain Science (AIBS), to provide precise assessment of the distribution and action of peptide-based pharmaceuticals in the brain. To illustrate this approach, we examined the acute central nervous system effects of the glucagon-like peptide-1 (GLP-1) receptor agonist liraglutide. Peripherally administered liraglutide accessed the hypothalamus and brainstem, and led to activation in several brain regions of which most were intersected by projections from neurons in the lateral parabrachial nucleus. Collectively, we provide a rapid and unbiased analytical framework for LSFM data which enables quantification and exploration based on data from AIBS to support basic and translational discovery.

A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster

SummaryDrosophila melanogaster has a rich repertoire of innate and learned behaviors. Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. Only electron microscopy (EM) enables complete, unbiased mapping of synaptic connectivity; however, the fly brain is too large for conventional EM. We developed a custom high-throughput EM platform and imaged the entire brain of an adult female fly at synaptic resolution. To validate the dataset, we traced brain-spanning circuitry involving the mushroom body (MB), which has been extensively studied for its role in learning. All inputs to Kenyon cells (KCs), the intrinsic neurons of the MB, were mapped, revealing a previously unknown cell type, postsynaptic partners of KC dendrites, and unexpected clustering of olfactory projection neurons. These reconstructions show that this freely available EM volume supports mapping of brain-spanning circuits, which will significantly accelerate Drosophila neuroscience.Video

Abstract 1541: Directed, unbiased mapping of lentiviral integrations with next generation sequencing in CAR-T cells

Abstract During manufacturing of an exemplary CD19-directed CAR-T cell product, patient T cells were transduced with a viral vector encoding the CD19-directed, 41BBζ endodomain-containing chimeric antigen receptor (CAR) construct, enabling permanent genetic modification of the target T cells. Lentiviral transduction with a self-inactivating (SIN) vector can offer certain advantages in safety and consistency over other DNA delivery methods. Although the integration patterns of wildtype HIV-1 have been well-characterized and shown to have a low risk of insertional transformation, the addition of an artificial construct may have the potential to affect integration patterns. Existing techniques for viral integration mapping, such as ligation-mediated polymerase chain reaction (LM-PCR), have limitations precluding comprehensive, unbiased, high-throughput insertion site mapping. To characterize insertional events in engineered CAR-T cells, we developed an unbiased NGS assay and computational pipeline capable of characterizing viral integration events genome-wide. The method leverages Tn5 transposase, coupled with a long terminal repeat-specific PCR, to map integration events down to nulceotide resolution. This assay identified over 150,000 high-confidence integration events across 23 patient-derived CAR-T cell products. Analysis of these sites revealed a similar integration preference to lentiviruses described in the literature: driven by GC content, local nucleotide content, chromatin status, and transcriptional activity, with no indication of preferential integration at oncogenic loci. In conclusion, in this assay a CD19-directed, CAR-containing lentivirus exhibited a low risk integration profile with no significant evidence of construct-specific risk factors. Furthermore, the findings suggest that the NGS assay may be useful for more efficient, cost-effective, and sensitive measurement of CAR-T integration events for a range of constructs. Citation Format: Timothy G. Johnstone, Rajagopal Chari, David Koppstein, Ronald J. Hause, Rafael Ponce, Adrian W. Briggs, Francois Vigneault. Directed, unbiased mapping of lentiviral integrations with next generation sequencing in CAR-T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1541.

Generic Workflow for Mapping of Complex Disulfide Bonds Using In-Source Reduction and Extracted Ion Chromatograms from Data-Dependent Mass Spectrometry.

Disulfide bond mapping is a critical task in protein characterization as protein stability, structure, and function is dependent on correct cysteine connectivities. Mass spectrometry (MS) is the method of choice for this, providing fast and accurate characterization of simple disulfide bonds. Disulfide mapping by liquid chromatography tandem mass spectrometry (LC-MS/MS) is performed by identifying disulfide-bonded partner peptides following proteolytic digestion. With the recently introduced ability to assign complex disulfide patterns by online postcolumn partial disulfide reduction by in-source reduction (ISR) in a LC-ISR-MS/MS methodology, the main challenge is data analysis to ensure detection of both expected and unexpected disulfide species. In this study, we introduced a workflow for confident and unbiased mapping of complex disulfide bonds using the powerful combination of extracted ion chromatograms (XICs) of LC-ISR-MS/MS data. With postcolumn partial reduction, identical LC retention times of intact disulfide-bonded species, their constituting free peptides, and partially reduced variants were observed. Subsequent selective MS/MS fragmentation of all reduction products allowed confident identification of free cysteine-containing peptides using a classical shotgun proteomics database search. Matching XICs of the identified cysteine-containing peptides allowed identification of both predicted and unpredicted disulfide species, including unforeseen proteolytic specificities, missed cleavage sites, scrambled disulfide variants, and the presence of disulfide-entangled complexes. Applying this workflow, we successfully mapped the complex disulfide bonds of tertiapin and the epidermal growth factor (EGF) family members transforming growth factor α (TGFα) and EGF. In addition, we were able to characterize the disulfide patterns of the special disulfide fold of the TGFβ superfamily in an all-online methodology.

Unbiased Mapping of Mouse Ischemic Hindlimb Angiogenesis and Systematic Review: Quality Assurance for Preclinical Angiogenesis Research

Unbiased Mapping of Mouse Ischemic Hindlimb Angiogenesis and Systematic Review: Quality Assurance for Preclinical Angiogenesis Research

C-BERST: defining subnuclear proteomic landscapes at genomic elements with dCas9-APEX2.

Mapping proteomic composition at distinct genomic loci in living cells has been a long-standing challenge. Here we report that dCas9-APEX2 Biotinylation at genomic Elements by Restricted Spatial Tagging (C-BERST) allows the rapid, unbiased mapping of proteomes near defined genomic loci, as demonstrated for telomeres and centromeres. C-BERST enables the high-throughput identification of proteins associated with specific sequences, facilitating annotation of these factors and their roles in nuclear biology.

The Molecular and Functional Foundations of Conducive Somatic Cell Reprogramming to Ground State Pluripotency

The epigenetic dynamics of iPSC reprogramming in correctly reprogrammed cells at high resolution and throughout the entire process, remain largely undefined. This gap in understanding results from the inefficiency of conventional reprogramming methods coupled with the difficulty of prospectively isolating the rare cells that eventually correctly reprogram into iPSCs. Here we characterize cell fate conversion from fibroblast to iPSC using radically efficient murine reprogramming systems. This comprehensive characterization provides single day resolution of dynamic changes in levels of gene expression, chromatin modifications, TF binding, DNA accessibility and DNA methylation. The integrative analysis identified two transcriptional modules that dominate successful reprogramming. One consists of genes whose transcription is regulated by on/off epigenetic switching of modifications in their promoters (abbreviated as ESPGs), and the second consists of genes with promoters in a constitutively active chromatin state, but a dynamic expression pattern (abbreviated as CAPGs). ESPGs are mainly regulated by OSK, rather than Myc, and are enriched for cell fate determinants and pluripotency factors. We used the ESPG module to study the identity and temporal occurrence of activating and repressing epigenetic switching during reprogramming. Removal of repressive chromatin modifications precedes chromatin opening and binding of RNA polymerase II at enhancers and promoters, and the opposite dynamics occur during repression of enhancers and promoters. Genome wide DNA methylation analysis identified a group of super-enhancers targeted by OSK, whose early demethylation definitively marks commitment to a successful reprogramming trajectory also in inefficient conventional reprogramming systems. CAPGs are predominantly regulated by Myc rather than OSK and are enriched for cell biosynthetic regulatory functions. CAPGs are distinctively regulated by multiple synergetic ways: 1) Myc activity, delivered either endogenously or exogenously, dominates CAPG expression changes and is indispensable for induction of pluripotency in somatic cells; 2) A change in tRNA codon usage which is specific to Myc regulated CAPGs, but not ESPGs, and favors their translation. In summary, our unbiased high-resolution mapping of epigenetic changes on somatic cells that are committed to undergo successful reprogramming reveals interleaved epigenetic and Myc governed biosynthetic reconfigurations that rapidly commission and propel conducive reprogramming toward naive pluripotency.

Unbiased compound-protein interface mapping and prediction of chemoresistance loci through forward genetics in haploid stem cells.

Forward genetic screens in haploid mammalian cells have recently emerged as powerful tools for the discovery and investigation of recessive traits. Use of the haploid system provides unique genetic tractability and resolution. Upon positive selection, these screens typically employ analysis of loss-of-function (LOF) alleles and are thus limited to non-essential genes. Many relevant compounds, including anti-cancer therapeutics, however, target essential genes, precluding positive selection of LOF alleles. Here, we asked whether the use of random and saturating chemical mutagenesis might enable screens that identify essential biological targets of toxic compounds. We compare and contrast chemical mutagenesis with insertional mutagenesis.Selecting mutagenized cells with thapsigargin, an inhibitor of the essential Ca2+ pump SERCA2, insertional mutagenesis retrieved cell clones overexpressing SERCA2. With chemical mutagenesis, we identify six single amino acid substitutions in the known SERCA2-thapsigargin binding interface that confer drug resistance. In a second screen, we used the anti-cancer drug MG132/bortezomib (Velcade), which inhibits proteasome activity. Using chemical mutagenesis, we found 7 point mutations in the essential subunit Psmb5 that map to the bortezomib binding surface. Importantly, 4 of these had previously been identified in human tumors with acquired bortezomib resistance. Insertional mutagenesis did not identify Psmb5 in this screen, demonstrating the unique ability of chemical mutagenesis to identify relevant point mutations in essential genes.Thus, chemical mutagenesis in haploid embryonic stem cells can define the interaction of toxic small molecules with essential proteins at amino acid resolution, fully mapping small molecule-protein binding interfaces.

Development of Two Analytical Methods Based on Reverse Phase Chromatographic and SDS-PAGE Gel for Assessment of Deglycosylation Yield in N-Glycan Mapping.

N-lined glycosylation is one of the critical quality attributes (CQA) for biotherapeutics impacting the safety and activity of drug product. Changes in pattern and level of glycosylation can significantly alter the intrinsic properties of the product and, therefore, have to be monitored throughout its lifecycle. Therefore fast, precise, and unbiased N-glycan mapping assay is desired. To ensure these qualities, using analytical methods that evaluate completeness of deglycosylation is necessary. For quantification of deglycosylation yield, methods such as reduced liquid chromatography–mass spectrometry (LC-MS) and reduced capillary gel electrophoresis (CGE) have been commonly used. Here we present development of two additional methods to evaluate deglycosylation yield: one based on LC using reverse phase (RP) column and one based on reduced sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE gel) with offline software (GelAnalyzer). With the advent of rapid deglycosylation workflows in the market for N-glycan profiling replacing overnight incubation, we have aimed to quantify the level of deglycosylation in a selected rapid deglycosylation workflow. Our results have shown well resolved peaks of glycosylated and deglycosylated protein species with RP-LC method allowing simple quantification of deglycosylation yield of protein with high confidence. Additionally a good correlation, ≥0.94, was found between deglycosylation yields estimated by RP-LC method and that of reduced SDS-PAGE gel method with offline software. Evaluation of rapid deglycosylation protocol from GlycanAssure™ HyPerformance assay kit performed on fetuin and RNase B has shown complete deglycosylation within the recommended protocol time when evaluated with these techniques. Using this kit, N-glycans from NIST mAb were prepared in 1.4 hr and analyzed by hydrophilic interaction chromatography (HILIC) ultrahigh performance LC (UHPLC) equipped with a fluorescence detector (FLD). 37 peaks were resolved with good resolution. Excellent sample preparation repeatability was found with relative standard deviation (RSD) of <5% for peaks with >0.5% relative area.

Proteomic profiling reveals sub proteomes of the human placenta

Proteomic characterisation of the placenta has largely been focused on effect of disease, anatomical features or specific cell types. We describe an unbiased proteomic mapping analysis to investigate how the placental proteome changes throughout the organ. A transverse slice of a human placenta was sectioned into 1 × 1cm samples. Sections were analysed using label free proteomics. Analysis revealed two distinct sub-proteomes that did not have anatomical significance. One had a muscular proteome and the other had distinct immunomodulation functions. Chorionic plate enriched proteins highlighted the fetal tissues high energy requirements whilst mechanisms of the decidua observed included modulation of cortisone levels.

Systematic exploration of unsupervised methods for mapping behavior

To fully understand the mechanisms giving rise to behavior, we need to be able to precisely measure it. When coupled with large behavioral data sets, unsupervised clustering methods offer the potential of unbiased mapping of behavioral spaces. However, unsupervised techniques to map behavioral spaces are in their infancy, and there have been few systematic considerations of all the methodological options. We compared the performance of seven distinct mapping methods in clustering a wavelet-transformed data set consisting of the x- and y-positions of the six legs of individual flies. Legs were automatically tracked by small pieces of fluorescent dye, while the fly was tethered and walking on an air-suspended ball. We find that there is considerable variation in the performance of these mapping methods, and that better performance is attained when clustering is done in higher dimensional spaces (which are otherwise less preferable because they are hard to visualize). High dimensionality means that some algorithms, including the non-parametric watershed cluster assignment algorithm, cannot be used. We developed an alternative watershed algorithm which can be used in high-dimensional spaces when a probability density estimate can be computed directly. With these tools in hand, we examined the behavioral space of fly leg postural dynamics and locomotion. We find a striking division of behavior into modes involving the fore legs and modes involving the hind legs, with few direct transitions between them. By computing behavioral clusters using the data from all flies simultaneously, we show that this division appears to be common to all flies. We also identify individual-to-individual differences in behavior and behavioral transitions. Lastly, we suggest a computational pipeline that can achieve satisfactory levels of performance without the taxing computational demands of a systematic combinatorial approach.

Mechanism Beyond Markov Models: History Information is Needed for Unbiased Pathway Reconstruction of Protein Folding

Understanding the mechanisms (pathways through configuration space) of biomolecular processes such as protein folding is a major challenge for molecular dynamics (MD) simulations. Markov state models (MSMs), which discretize simulation data by projecting onto a relatively small number of states, have become increasingly popular compact representations of the overwhelming complexity of protein configuration space and the vast quantity of trajectory data. Building on previous work showing the potential for significant bias in MSM estimates of folding and unfolding rates [Suarez et al., JCTC 2016, 12 (8), 3473], here we study MSM descriptions of (un)folding mechanisms. By comparing to independent long-time MD simulations, as well as non-Markov (NM) analyses which include history information, we find that MSMs tend to infer overly broad distributions of more equally probable pathways. By contrast, NM analyses using MSM states agree well with the narrower distributions observed in the long-time MD data. The MSMs appear to be overly permissive because they exclude the history information accounting for previous discrete states occurring in trajectories, which is necessary for an unbiased mapping of the underlying dynamics in the full configuration space to the substantially reduced discrete state space.

Therapeutic Crispr/Cas9 Genome Editing for Treating Sickle Cell Disease

IntroductionSickle cell disease (SCD) is one of the most common monogenic disorders, affecting millions worldwide. SCD is caused by a point mutation in the β-globin gene (HBB). A single nucleotide substitution from A to T in the codon for the sixth amino acid in the β-globin protein converts a glutamic acid to a valine that leads to the production of sickle hemoglobin (HbS), which impairs the function of the red blood cells (RBCs). Allogeneic hematopoietic stem cell transplantation (HSCT) is the only available cure, but it is feasible for only a small subpopulation (<15%) of patients and may be associated with a high risk. Here, we show that targeted genome editing can potentially provide a permanent cure for SCD by correcting the sickle mutation in clinically relevant hematopoietic stem and progenitor cells (HSPCs) for autologous transplantation.MethodsFor proof-of-concept, we designed CRISPR/Cas9 systems and donor templates to introduce the sickle mutation into wild-type (WT) HBB of mobilized peripheral blood CD34+ cells. To assess genome-editing outcomes mediated by CRISPR/Cas9 systems, we developed a novel digital droplet PCR (ddPCR) assay that can quantify the rates of non-homologous end joining (NHEJ) and homology directed repair (HDR) events simultaneously following the generation of DNA double strand breaks. The assay enables rapid and accurate quantification of gene modifications in HSPCs by CRISPR/Cas9 genome-editing. Specifically, Streptococcus pyogenes (Spy) Cas9 proteins, guide RNAs (gRNA), and single-stranded DNA (ssDNA) donor templates were delivered into CD34+ cells by nucleofection with optimized conditions. Different gRNAs targeting HBB near the SCD mutation site were tested, and the optimal gRNA was chosen based on high on-target activity and proximity to the mutation site. The optimal DNA donor design and concentration were determined based on the frequency of HDR events and viability/growth rate of edited cells. Treated samples and untreated controls were assayed as both single cell clones and in bulk culture. In 2-phase liquid culture, genome editing frequencies at both DNA and mRNA levels were quantified by ddPCR to confirm persistence of edited cells in the heterozygous population over time. The expression of globins and other erythroid markers were monitored using flow cytometry and real time PCR to determine if genome editing had any effect on the kinetics of erythropoiesis. Colony formation assays were used to determine the number and type of colonies following induction of differentiation. Colony ddPCR was performed to determine the genotype of edited cells. Wright/Giemsa stain was used to confirm terminal maturation of erythrocytes into enucleated RBC. Native polyacrylamide gel electrophoresis (PAGE) and high performance liquid chromatography (HPLC) were used to confirm translation of edited β-globin protein and formation of HbS.Results and DiscussionWe found that the efficiency of site-specific gene correction could be substantially improved by optimizing the CRISPR/Cas9 systems for genome editing. For example, with optimization, we achieved ~30% HDR rates in CD34+ cells with >80% cell viability. The HDR-modified alleles persisted in the population over the course of differentiation, and the edited CD34+ cells retained differentiation potential. Genotyping of individual erythroid colonies confirmed that up to 35% of colonies are either homozygous or heterozygous for HDR alleles. Following differentiation, treated cells express modified HBB mRNA and HbS. In addition, the off-target activity of the HBB-specific gRNAs was determined using both bioinformatics tools and unbiased genome-wide mapping techniques. Ongoing work includes the validation of gene correction in SCD patient derived HSPCs, characterization of modified cells in vitro and in vivo to assess the therapeutic potential, and analysis of long-term genotoxicity.ConclusionsBased on the proof-of-concept study, we demonstrate that using the optimized CRISPR/Cas9 system and donor template, an HDR rate of ~30% can be achieved in CD34+ cells. The gene corrected cells have the potential to differentiate into erythroid cells that permanently produce WT β-globin. Our findings provide promising evidence for clinical translation of the HSPCs genome correction strategy in treating SCD patients, as well as correcting gene defects underlying other inherited single-gene disorders. DisclosuresNo relevant conflicts of interest to declare.

A robust (re-)annotation approach to generate unbiased mapping references for RNA-seq-based analyses of differential expression across closely related species.

BackgroundRNA-seq based on short reads generated by next generation sequencing technologies has become the main approach to study differential gene expression. Until now, the main applications of this technique have been to study the variation of gene expression in a whole organism, tissue or cell type under different conditions or at different developmental stages. However, RNA-seq also has a great potential to be used in evolutionary studies to investigate gene expression divergence in closely related species.ResultsWe show that the published genomes and annotations of the three closely related Drosophila species D. melanogaster, D. simulans and D. mauritiana have limitations for inter-specific gene expression studies. This is due to missing gene models in at least one of the genome annotations, unclear orthology assignments and significant gene length differences in the different species. A comprehensive evaluation of four statistical frameworks (DESeq2, DESeq2 with length correction, RPKM-limma and RPKM-voom-limma) shows that none of these methods sufficiently accounts for inter-specific gene length differences, which inevitably results in false positive candidate genes. We propose that published reference genomes should be re-annotated before using them as references for RNA-seq experiments to include as many genes as possible and to account for a potential length bias. We present a straight-forward reciprocal re-annotation pipeline that allows to reliably compare the expression for nearly all genes annotated in D. melanogaster.ConclusionsWe conclude that our reciprocal re-annotation of previously published genomes facilitates the analysis of significantly more genes in an inter-specific differential gene expression study. We propose that the established pipeline can easily be applied to re-annotate other genomes of closely related animals and plants to improve comparative expression analyses.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2646-x) contains supplementary material, which is available to authorized users.

Unbiased High-Dimensional Identification of Lymphocytes in Mouse Uterus

Abstract Introduction Uterine lymphocytes play an essential role at the maternal-fetal interface, contributing to vascular remodeling, fetal tolerance and protection against infection. Despite intense research interest, simultaneous population assessment of diverse immune cells has been limited by the use of few concurrent markers and difficulty in assigning unambiguous cell identity. We present the first comprehensive, unbiased identification of mouse uterine immune subsets by application of dimensionality reduction of highly-polychromatic flow cytometry. Methods Uterine specimens were dissected from C57BL/6 mice and mononuclear cells (MCs) were isolated by mechanical and enzymatic disruption. MCs labeled by flurochrome-conjugate antibodies. Data acquisition and analysis were performed using BD Fortessa flow cytometer in an 18 parameter, 5-laser configuration and Flowjo, respectively. Dimensionality reduction by Barnes-Hut modification of t-distributed Stochastic Neighbor Embedding (t-SNE) and density-based k-means clustering was performed using the open-source ACCENSE package. Results Analysis revealed uterine B-, T-, Dendritic, and Innate Lymphoid cell subsets. Analysis with ACCENSE allowed unbiased mapping of these subsets onto 2-dimensional scaffolds, without the necessity for expert manual gating. Conclusion We present the first comprehensive analysis of uterine immune cells, demonstrating a complex mixture of innate and adaptive immune mediators. The use of dimensionality reduction and population clustering allows allocation of uterine immune cell phenotype in an unambiguous fashion, enhancing reproducibility and functional analysis across studies.