1. |
- Bordería, Antonio V, et al.
(author)
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Group Selection and Contribution of Minority Variants during Virus Adaptation Determines Virus Fitness and Phenotype.
- 2015
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In: PLoS Pathogens. - : Public Library of Science (PLoS). - 1553-7366 .- 1553-7374. ; 11:5
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Journal article (peer-reviewed)abstract
- Understanding how a pathogen colonizes and adapts to a new host environment is a primary aim in studying emerging infectious diseases. Adaptive mutations arise among the thousands of variants generated during RNA virus infection, and identifying these variants will shed light onto how changes in tropism and species jumps can occur. Here, we adapted Coxsackie virus B3 to a highly permissive and less permissive environment. Using deep sequencing and bioinformatics, we identified a multi-step adaptive process to adaptation involving residues in the receptor footprints that correlated with receptor availability and with increase in virus fitness in an environment-specific manner. We show that adaptation occurs by selection of a dominant mutation followed by group selection of minority variants that together, confer the fitness increase observed in the population, rather than selection of a single dominant genotype.
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2. |
- Henningsson, Rasmus, et al.
(author)
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SMSSVD : SubMatrix Selection Singular Value Decomposition
- 2019
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In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 35:3, s. 478-486
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Journal article (peer-reviewed)abstract
- Motivation: High throughput biomedical measurements normally capture multiple overlaid biologically relevant signals and often also signals representing different types of technical artefacts like e.g. batch effects. Signal identification and decomposition are accordingly main objectives in statistical biomedical modeling and data analysis. Existing methods, aimed at signal reconstruction and deconvolution, in general, are either supervised, contain parameters that need to be estimated or present other types of ad hoc features. We here introduce SubMatrix Selection Singular Value Decomposition (SMSSVD), a parameter-free unsupervised signal decomposition and dimension reduction method, designed to reduce noise, adaptively for each low-rank-signal in a given data matrix, and represent the signals in the data in a way that enable unbiased exploratory analysis and reconstruction of multiple overlaid signals, including identifying groups of variables that drive different signals. Results: The SMSSVD method produces a denoised signal decomposition from a given data matrix. It also guarantees orthogonality between signal components in a straightforward manner and it is designed to make automation possible. We illustrate SMSSVD by applying it to several real and synthetic datasets and compare its performance to golden standard methods like PCA (Principal Component Analysis) and SPC (Sparse Principal Components, using Lasso constraints). The SMSSVD is computationally efficient and despite being a parameter-free method, in general, outperforms existing statistical learning methods. Availability and implementation: A Julia implementation of SMSSVD is openly available on GitHub (https://github.com/rasmushenningsson/SubMatrixSelectionSVD.jl). Supplementary information: Supplementary data are available at Bioinformatics online.
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3. |
- Lilljebjörn, Henrik, et al.
(author)
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Identification of ETV6-RUNX1-like and DUX4-rearranged subtypes in paediatric B-cell precursor acute lymphoblastic leukaemia
- 2016
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11790
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Journal article (peer-reviewed)abstract
- Fusion genes are potent driver mutations in cancer. In this study, we delineate the fusion gene landscape in a consecutive series of 195 paediatric B-cell precursor acute lymphoblastic leukaemia (BCP ALL). Using RNA sequencing, we find in-frame fusion genes in 127 (65%) cases, including 27 novel fusions. We describe a subtype characterized by recurrent IGH-DUX4 or ERG-DUX4 fusions, representing 4% of cases, leading to overexpression of DUX4 and frequently co-occurring with intragenic ERG deletions. Furthermore, we identify a subtype characterized by an ETV6-RUNX1-like gene-expression profile and coexisting ETV6 and IKZF1 alterations. Thus, this study provides a detailed overview of fusion genes in paediatric BCP ALL and adds new pathogenetic insights, which may improve risk stratification and provide therapeutic options for this disease.
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4. |
- Perby Henningsson, Rasmus
(author)
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Dimension Reduction and Signal Decomposition for Genotype–Phenotype Relations
- 2017
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Doctoral thesis (other academic/artistic)abstract
- Over the last few decades, DNA sequencing has developed from costing billions of dollars to get the complete sequence of the human genome, to being a routine procedure performed in labs all around the world. This has transformed the field of experimental biology since measurements can be done at a level of detail that was not possible before. Still, the relationship between genotype and low-level cellular processes on one hand, and high-level phenotypic traits on the other, tends to be very complex; measuring does not equal understanding. In the large data sets that are being gathered, it is often hard to uncover patterns that are truly meaningful, and not just arising by random chance.In this work, we present novel methods for representing, exploring and visualizing genotype-phenotype data sets, with a particular focus on tracking changes driven by evolutionary processes as they occur. One challenge is to be able to quickly search for specific patterns in data coming from large genomes. We have adapted algorithms and data structures from the field of Information Retrieval, relying on inherent genomic structure to make efficient searches. In Paper I, we showcase these techniques with visualization of gene fusions in a study of paediatric B-cell precursor acute lymphoblastic leukaemia.The complexity of biological processes, taken together with the fact that high-throughput measurements, such as DNA/RNA sequencing data, measure many different things at once, means that these data sets will often contain multiple overlaid signals. If data is collected in the field, rather than produced entirely under controlled conditions in the lab, it is practically unavoidable. In Paper III, we present SMSSVD – SubMatrix Selection Singular Value Decomposition, a parameter-free unsupervised signal decomposition and dimension reduction method, particularly useful for data sets with many variables. By adaptively reducing the noise for each signal, SMSSVD creates a representation with many desirable properties inherited from the ordinary SVD, while being able to discover signals closer to the limit of detection.In Paper II and Paper IV we describe models for representing genetically related but still heterogeneous microbial populations and show how the composition of the population determines the interaction with the host. The DISSEQT pipeline (DIStribution-based SEQuence space Time dynamics) developed in Paper IV, covers the entire workflow from read alignment to visualization of results. We model each population as a positive measure over sequence space and apply SMSSVD to get a robust representation. Using our model, we follow and visualize the evolutionary trajectories of the populations through time, highlighting important minority variants emerging. Finally, we demonstrate the relevance of our population model by showing that it can accurately predict the population fitness, whereas a model based on the consensus sequence fails.
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5. |
- Rodriguez-Roche, Rosmari, et al.
(author)
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Increasing clinical severity during a dengue virus type 3 Cuban epidemic: deep sequencing of evolving viral populations
- 2016
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In: Journal of Virology. - 1098-5514. ; 90:19, s. 4320-4333
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Journal article (peer-reviewed)abstract
- During the DENV-3 epidemic occurred in Havana in 2001-2002, severe disease was associated with the infection sequence DENV-1/DENV-3, whilst the sequence DENV-2/DENV-3 was associated with mild/asymptomatic infections. To determine the role of the virus in the increasing severity demonstrated during the epidemic serum samples collected at different point times were studied. A total of 22 full-length sequences were obtained using a deep sequencing approach. Bayesian phylogenetic analysis of consensus sequences revealed that two DENV-3 lineages were circulating in Havana at that time, both grouped within genotype III. The predominant lineage is closely related to Peruvian and Ecuadorian strains, whilst the minor lineage is related to Venezuelan strains. According to consensus sequences, relatively few non-synonymous mutations were observed; only one was fixed during the epidemic at position 4380 in the NS2B gene. Intra-host genetic analysis indicated that a significant minor population was selected and became predominant towards the end of the epidemic. In conclusion, greater variability was detected during the epidemic's progression in terms of significant minority variants, particularly in the non-structural genes. An increasing trend of genetic diversity towards the end of the epidemic was only observed for synonymous variant allele rates, with higher variability in secondary cases. Remarkably, significant intra-host genetic variation was demonstrated within the same patient during the course of secondary infection DENV-1/DENV-3, including changes in the structural proteins PrM and E. Therefore, the dynamic of evolving viral populations in the context of heterotypic antibodies could be related to the increasing clinical severity observed during the epidemic.
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6. |
- Sandén, Carl, et al.
(author)
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Clonal competition within complex evolutionary hierarchies shapes AML over time
- 2020
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- Clonal heterogeneity and evolution has major implications for disease progression and relapse in acute myeloid leukemia (AML). To model clonal dynamics in vivo, we serially transplanted 23 AML cases to immunodeficient mice and followed clonal composition for up to 15 months by whole-exome sequencing of 84 xenografts across two generations. We demonstrate vast changes in clonality that both progress and reverse over time, and define five patterns of clonal dynamics: Monoclonal, Stable, Loss, Expansion and Burst. We also show that subclonal expansion in vivo correlates with a more adverse prognosis. Furthermore, clonal expansion enabled detection of very rare clones with AML driver mutations that were undetectable by sequencing at diagnosis, demonstrating that the vast majority of AML cases harbor multiple clones already at diagnosis. Finally, the rise and fall of related clones enabled deconstruction of the complex evolutionary hierarchies of the clones that compete to shape AML over time.
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7. |
- von Palffy, Sofia, et al.
(author)
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The complement receptor C3AR constitutes a novel therapeutic target in NPM1-mutated AML
- 2023
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In: Blood Advances. - : American Society of Hematology. - 2473-9529 .- 2473-9537. ; 7:7, s. 1204-1218
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Journal article (peer-reviewed)abstract
- Mutated Nucleophosmin 1 (NPM1) is the most common genetic alteration in acute myeloid leukemia (AML), found in approximately 30% of cases. Although mutations in this gene are considered favorable according to current risk stratification guidelines, a large fraction of patients will suffer from relapse, demonstrating the urgent need for new treatment options. Therefore, we aimed to identify cell surface proteins specifically expressed on NPM1)-mutated AML cells, allowing for potential targeting with antibody-based therapies. Herein, we performed an arrayed flow cytometry-based screen directed to 362 cell surface markers. Comparing the cell surface expression on NPM1-mutated AML cells to primitive (CD34+ CD38-) normal bone marrow cells, we identified the complement receptor C3AR as specifically expressed in NPM1-mutated AML. By flow cytometry and single cell RNA-sequencing, we further show that normal hematopoietic stem and progenitor cells lack detectable C3AR gene and protein expression, making it particularly suitable as a target for antibody therapy. We also demonstrate that C3AR in combination with GPR56 distinguishes the leukemic stem cells (LSCs) in NPM1-mutated AML from the normal hematopoietic stem cells, defining the LSC population, as shown by transplantation into immunodeficient mice. Mechanistically, stimulation of C3AR-expressing cells with C3a, the ligand of C3AR, leads to activation of ERK1/2 and increased survival of AML cells, suggesting that this is an important signaling axis in this subtype of AML. Finally, we show that antibodies directed against C3AR efficiently elicit NK cell-mediated killing of primary AML cells ex vivo, highlighting C3AR as a candidate therapeutic target in NPM1-mutated AML.
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