liu.seSearch for publications in DiVA
Change search
Link to record
Permanent link

Direct link
BETA
Tegnér , Jesper
Alternative names
Publications (10 of 46) Show all publications
Ravasi, T., Suzuki, H., Vittorio Cannistraci, C., Katayama, S., Bajic, V. B., Tan, K., . . . Hayashizaki, Y. (2010). An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man. CELL, 140(5), 744-752
Open this publication in new window or tab >>An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man
Show others...
2010 (English)In: CELL, ISSN 0092-8674, Vol. 140, no 5, p. 744-752Article in journal (Refereed) Published
Abstract [en]

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-54509 (URN)10.1016/j.cell.2010.01.044 (DOI)000275197400022 ()
Available from: 2010-03-19 Created: 2010-03-19 Last updated: 2010-03-19
Peña, J. M., Nilsson, R., Bjorkegren, J. & Tegnér, J. (2009). An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity. JOURNAL OF MACHINE LEARNING RESEARCH, 10, 1071-1094
Open this publication in new window or tab >>An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity
2009 (English)In: JOURNAL OF MACHINE LEARNING RESEARCH, ISSN 1532-4435, Vol. 10, p. 1071-1094Article in journal (Refereed) Published
Abstract [en]

We present a sound and complete graphical criterion for reading dependencies from the minimal undirected independence map G of a graphoid M that satisfies weak transitivity. Here, complete means that it is able to read all the dependencies in M that can be derived by applying the graphoid properties and weak transitivity to the dependencies used in the construction of G and the independencies obtained from G by vertex separation. We argue that assuming weak transitivity is not too restrictive. As an intermediate step in the derivation of the graphical criterion, we prove that for any undirected graph G there exists a strictly positive discrete probability distribution with the prescribed sample spaces that is faithful to G. We also report an algorithm that implements the graphical criterion and whose running time is considered to be at most O(n(2)(e + n)) for n nodes and e edges. Finally, we illustrate how the graphical criterion can be used within bioinformatics to identify biologically meaningful gene dependencies.

Keywords
graphical models, vertex separation, graphoids, weak transitivity, bioinformatics
National Category
Natural Sciences
Identifiers
urn:nbn:se:liu:diva-51473 (URN)
Available from: 2009-11-04 Created: 2009-11-04 Last updated: 2014-01-17
Eriksson, O., Brinne, B., Zhou, Y., Bjorkegren, J. & Tegnér , J. (2009). Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit. IET SYSTEMS BIOLOGY, 3(2), 113-23
Open this publication in new window or tab >>Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit
Show others...
2009 (English)In: IET SYSTEMS BIOLOGY, ISSN 1751-8849 , Vol. 3, no 2, p. 113-23Article in journal (Refereed) Published
Abstract [en]

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a tearing-and-zooming approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits.

National Category
Natural Sciences
Identifiers
urn:nbn:se:liu:diva-17614 (URN)10.1049/iet-syb.2007.0028 (DOI)
Available from: 2009-04-07 Created: 2009-04-06 Last updated: 2009-04-07
Gustafsson, M., Hörnquist, M., Bjorkegren, J. & Tegnér, J. (2009). Genome-wide system analysis reveals stable yet flexible network dynamics in yeast. IET SYSTEMS BIOLOGY, 3(4), 219-228
Open this publication in new window or tab >>Genome-wide system analysis reveals stable yet flexible network dynamics in yeast
2009 (English)In: IET SYSTEMS BIOLOGY, ISSN 1751-8849, Vol. 3, no 4, p. 219-228Article in journal (Refereed) Published
Abstract [en]

Recently, important insights into static network topology for biological systems have been obtained, but still global dynamical network properties determining stability and system responsiveness have not been accessible for analysis. Herein, we explore a genome-wide gene-to-gene regulatory network based on expression data from the cell cycle in Saccharomyces cerevisae (budding yeast). We recover static properties like hubs (genes having several out-going connections), network motifs and modules, which have previously been derived from multiple data sources such as whole-genome expression measurements, literature mining, protein-protein and transcription factor binding data. Further, our analysis uncovers some novel dynamical design principles; hubs are both repressed and repressors, and the intra-modular dynamics are either strongly activating or repressing whereas inter-modular couplings are weak. Finally, taking advantage of the inferred strength and direction of all interactions, we perform a global dynamical systems analysis of the network. Our inferred dynamics of hubs, motifs and modules produce a more stable network than what is expected given randomised versions. The main contribution of the repressed hubs is to increase system stability, while higher order dynamic effects (e.g. module dynamics) mainly increase system flexibility. Altogether, the presence of hubs, motifs and modules induce few flexible modes, to which the network is extra sensitive to an external signal. We believe that our approach, and the inferred biological mode of strong flexibility and stability, will also apply to other cellular networks and adaptive systems.

National Category
Natural Sciences
Identifiers
urn:nbn:se:liu:diva-19799 (URN)10.1049/iet-syb.2008.0112 (DOI)
Note
This paper is a postprint of a paper submitted to and accepted for publication in IET SYSTEMS BIOLOGY and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library Original Publication: Mika Gustafsson, Michael Hörnquist, J Bjorkegren and Jesper Tegnér, Genome-wide system analysis reveals stable yet flexible network dynamics in yeast, 2009, IET SYSTEMS BIOLOGY, (3), 4, 219-228. http://dx.doi.org/10.1049/iet-syb.2008.0112 Copyright: The Institution of Engineering and Technology http://www.theiet.org/ Available from: 2009-08-28 Created: 2009-08-10 Last updated: 2013-12-12Bibliographically approved
Edin, F., Klingberg, T., Johansson, P., McNab, F., Tegnér, J. & Compte , A. (2009). Mechanism for top-down control of working memory capacity. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 106(16), 6802-6807
Open this publication in new window or tab >>Mechanism for top-down control of working memory capacity
Show others...
2009 (English)In: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, ISSN 0027-8424 , Vol. 106, no 16, p. 6802-6807Article in journal (Refereed) Published
Abstract [en]

Working memory capacity, the maximum number of items that we can transiently store in working memory, is a good predictor of our general cognitive abilities. Neural activity in both dorsolateral prefrontal cortex and posterior parietal cortex has been associated with memory retention during visuospatial working memory tasks. The parietal cortex is thought to store the memories. However, the role of the dorsolateral prefrontal cortex, a top-down control area, during pure information retention is debated, and the mechanisms regulating capacity are unknown. Here, we propose that a major role of the dorsolateral prefrontal cortex in working memory is to boost parietal memory capacity. Furthermore, we formulate the boosting mechanism computationally in a biophysical cortical microcircuit model and derive a simple, explicit mathematical formula relating memory capacity to prefrontal and parietal model parameters. For physiologically realistic parameter values, lateral inhibition in the parietal cortex limits mnemonic capacity to a maximum of 2-7 items. However, at high loads inhibition can be counteracted by excitatory prefrontal input, thus boosting parietal capacity. Predictions from the model were confirmed in an fMRI study. Our results show that although memories are stored in the parietal cortex, interindividual differences in memory capacity are partly determined by the strength of prefrontal top-down control. The model provides a mechanistic framework for understanding top-down control of working memory and specifies two different contributions of prefrontal and parietal cortex to working memory capacity.

Keywords
computer model, fMRI, lateral inhibition, prefrontal, short-term memory, parieta
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-18265 (URN)10.1073/pnas.0901894106 (DOI)
Available from: 2009-05-16 Created: 2009-05-15 Last updated: 2009-05-16
Hägg, S., Skogsberg, J., Lundström, J., Noori, P., Nilsson, R., Zhong, H., . . . Björkegren, J. (2009). Multi-Organ Expression Profiling Uncovers a Gene Module in Coronary Artery Disease Involving Transendothelial Migration of Leukocytes and LIM Domain Binding 2: The Stockholm Atherosclerosis Gene Expression (STAGE) Study. PLoS Genetics, 5(12), e1000754
Open this publication in new window or tab >>Multi-Organ Expression Profiling Uncovers a Gene Module in Coronary Artery Disease Involving Transendothelial Migration of Leukocytes and LIM Domain Binding 2: The Stockholm Atherosclerosis Gene Expression (STAGE) Study
Show others...
2009 (English)In: PLoS Genetics, ISSN 1553-7390, Vol. 5, no 12, p. e1000754-Article in journal (Refereed) Published
Abstract [en]

Environmental exposures filtered through the genetic make-up of each individual alter the transcriptional repertoire in organs central to metabolic homeostasis, thereby affecting arterial lipid accumulation, inflammation, and the development of coronary artery disease (CAD). The primary aim of the Stockholm Atherosclerosis Gene Expression (STAGE) study was to determine whether there are functionally associated genes (rather than individual genes) important for CAD development. To this end, two-way clustering was used on 278 transcriptional profiles of liver, skeletal muscle, and visceral fat (n=66/tissue) and atherosclerotic and unaffected arterial wall (n=40/tissue) isolated from CAD patients during coronary artery bypass surgery. The first step, across all mRNA signals (n=15,042/12,621 RefSeqs/genes) in each tissue, resulted in a total of 60 tissue clusters (n=3958 genes). In the second step (performed within tissue clusters), one atherosclerotic lesion (n=49/48) and one visceral fat (n=59) cluster segregated the patients into two groups that differed in the extent of coronary stenosis (P=0.008 and P=0.00015). The associations of these clusters with coronary atherosclerosis were validated by analyzing carotid atherosclerosis expression profiles. Remarkably, in one cluster (n=55/54) relating to carotid stenosis (P=0.04), 27 genes in the two clusters relating to coronary stenosis were confirmed (n=16/17, P<10-27and-30). Genes in the transendothelial migration of leukocytes (TEML) pathway were overrepresented in all three clusters, referred to as the atherosclerosis module (A-module). In a second validation step, using three independent cohorts, the A-module was found to be genetically enriched with CAD risk by 1.8-fold (P<0.004). The transcription co-factor LIM domain binding 2 (LDB2) was identified as a potential high-hierarchy regulator of the A-module, a notion supported by subnetwork analysis, cellular and lesion expression of LDB2, and the expression of 13 TEML genes in Ldb2-deficient arterial wall. Thus, the A-module appears to be important for atherosclerosis development and together with LDB2 merits further attention in CAD research.

Place, publisher, year, edition, pages
PLoS Genetics, 2009
National Category
Natural Sciences
Identifiers
urn:nbn:se:liu:diva-52084 (URN)10.1371/journal.pgen.1000754 (DOI)
Note
On the day of the defence day the status of this article was: In Press.Available from: 2009-12-03 Created: 2009-12-03 Last updated: 2009-12-07Bibliographically approved
Nilsson, R., Bjorkegren, J. & Tegnér , J. (2009). On reliable discovery of molecular signatures. BMC BIOINFORMATICS, 10(38)
Open this publication in new window or tab >>On reliable discovery of molecular signatures
2009 (English)In: BMC BIOINFORMATICS, ISSN 1471-2105 , Vol. 10, no 38Article in journal (Refereed) Published
Abstract [en]

Background: Plasmid encoded (CTX)-C-bla-M enzymes represent an important sub-group of class A beta-lactamases causing the ESBL phenotype which is increasingly found in Enterobacteriaceae including Klebsiella spp. Molecular typing of clinical ESBL-isolates has become more and more important for prevention of the dissemination of ESBL-producers among nosocomial environment.

Methods: Multiple displacement amplified DNA derived from 20 K. pneumoniae and 34 K. oxytoca clinical isolates with an ESBL-phenotype was used in a universal CTX-M PCR amplification assay. Identification and differentiation of (CTX)-C-bla-M and (OXY)-O-bla/K1 sequences was obtained by DNA sequencing of M13-sequence-tagged CTX-M PCR-amplicons using a M13-specific sequencing primer.

Results: Nine out of 20 K. pneumoniae clinical isolates had a (CTX)-C-bla-M genotype. Interestingly, we found that the universal degenerated primers also amplified the chromosomally located K1-gene in all 34 K. oxytoca clinical isolates. Molecular identification and differentiation between (CTX)-C-bla-M and (OXY)-O-bla/K1-genes could only been achieved by sequencing of the PCR-amplicons. In silico analysis revealed that the universal degenerated CTX-M primer-pair used here might also amplify the chromosomally located (OXY)-O-bla and K1-genes in Klebsiella spp. and K1-like genes in other Enterobacteriaceae.

Conclusion: The PCR-based molecular typing method described here enables a rapid and reliable molecular identification of (CTX)-C-bla-M, and (OXY)-O-bla/K1-genes. The principles used in this study could also be applied to any situation in which antimicrobial resistance genes would need to be sequenced.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-17519 (URN)10.1186/1471-2105-10-38 (DOI)
Note
Original Publication:Roland Nilsson, Johan Bjorkegren and Jesper Tegnér, On reliable discovery of molecular signatures, 2009, BMC BIOINFORMATICS, (10), 38.http://dx.doi.org/10.1186/1471-2105-10-38Licensee: BioMed Centralhttp://www.biomedcentral.com/Available from: 2009-03-28 Created: 2009-03-27 Last updated: 2009-03-28Bibliographically approved
Gustafsson, M., Hörnquist, M., Lundstrom, J., Bjorkegren, J. & Tegnér , J. (2009). Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions. CHALLENGES OF SYSTEMS BIOLOGY: COMMUNITY EFFORTS TO HARNESS BIOLOGICAL COMPLEXITY, 1158, 265-275
Open this publication in new window or tab >>Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions
Show others...
2009 (English)In: CHALLENGES OF SYSTEMS BIOLOGY: COMMUNITY EFFORTS TO HARNESS BIOLOGICAL COMPLEXITY, ISSN 0077-8923 , Vol. 1158, p. 265-275Article in journal (Refereed) Published
Abstract [en]

The quest to determine cause from effect is often referred to as reverse engineering in the context of cellular networks. Here we propose and evaluate an algorithm for reverse engineering a gene regulatory network from time-series kind steady-state data. Our algorithmic pipeline, which is rather standard in its parts but not in its integrative composition, combines ordinary differential equations, parameter estimations by least angle regression, and cross-validation procedures for determining the in-degrees and selection of nonlinear transfer functions. The result of the algorithm is a complete directed net-work, in which each edge has been assigned a score front it bootstrap procedure. To evaluate the performance, we submitted the outcome of the algorithm to the reverse engineering assessment competition DREAM2, where we used the data corresponding to the InSillico1 and InSilico2 networks as input. Our algorithm outperformed all other algorithms when inferring one of the directed gene-to-gene networks.

Keywords
reverse engineering, network inference, nonlinear, DREAM conference, LARS, LASSO
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-18289 (URN)10.1111/j.1749-6632.2008.03764.x (DOI)
Note
This is the authors’ version of the following article: Mika Gustafsson, Michael Hörnquist, Jesper Lundstrom, Johan Bjorkegren and Jesper Tegnér, Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions, 2009, Annals of the New York Academy of Sciences, Volume 1158 Issue, The Challenges of Systems Biology Community Efforts to Harness Biological Complexity, 265-275. which has been published in final form at: http://dx.doi.org/10.1111/j.1749-6632.2008.03764.x Copyright: Blackwell Publishing Ltd http://www.blackwellpublishing.com/ Available from: 2009-05-25 Created: 2009-05-15 Last updated: 2013-09-12Bibliographically approved
Gustafsson, M., Hörnquist, M., Tegnér, J. & et al. 155 external authors, . (2009). The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nature Genetics, 41, 553-562
Open this publication in new window or tab >>The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line
2009 (English)In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 41, p. 553-562Article in journal (Refereed) Published
Abstract [en]

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-18305 (URN)10.1038/ng.375 (DOI)
Available from: 2009-05-18 Created: 2009-05-18 Last updated: 2017-12-13Bibliographically approved
Skogsberg, J., Dicker, A., Ryden, M., Astrom, G., Nilsson, R., Bhuiyan, H., . . . Bjorkegren, J. (2008). ApoB100-LDL acts as a metabolic signal from liver to peripheral fat causing inhibition of lipolysis in adipocytes. PLoS ONE, 3(11)
Open this publication in new window or tab >>ApoB100-LDL acts as a metabolic signal from liver to peripheral fat causing inhibition of lipolysis in adipocytes
Show others...
2008 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 3, no 11Article in journal (Refereed) Published
Abstract [en]

Background: Free fatty acids released from adipose tissue affect the synthesis of apolipoprotein B-containing lipoproteins and glucose metabolism in the liver. Whether there also exists a reciprocal metabolic arm affecting energy metabolism in white adipose tissue is unknown. Methods and Findings: We investigated the effects of apoB-containing lipoproteins on catecholamine-induced lipolysis in adipocytes from subcutaneous fat cells of obese but otherwise healthy men, fat pads from mice with plasma lipoproteins containing high or intermediate levels of apoB100 or no apoB100, primary cultured adipocytes, and 3T3-L1 cells. In subcutaneous fat cells, the rate of lipolysis was inversely related to plasma apoB levels. In human primary adipocytes, LDL inhibited lipolysis in a concentration-dependent fashion. In contrast, VLDL had no effect. Lipolysis was increased in fat pads from mice lacking plasma apoB100, reduced in apoB100-only mice, and intermediate in wild-type mice. Mice lacking apoB100 also had higher oxygen consumption and lipid oxidation. In 3T3-L1 cells, apoB100-containing lipoproteins inhibited lipolysis in a dose-dependent fashion, but lipoproteins containing apoB48 had no effect. ApoB100-LDL mediated inhibition of lipolysis was abolished in fat pads of mice deficient in the LDL receptor (Ldlr-/- Apob100/100). Conclusions: Our results show that the binding of apoB100-LDL to adipocytes via the LDL receptor inhibits intracellular noradrenaline-induced lipolysis in adipocytes. Thus, apoB100-LDL is a novel signaling molecule from the liver to peripheral fat deposits that may be an important link between atherogenic dyslipidemias and facets of the metabolic syndrome. © 2008 Skogsberg et al.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-46432 (URN)10.1371/journal.pone.0003771 (DOI)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2011-01-10
Organisations

Search in DiVA

Show all publications