| 1. |
- Kang, Wenjing, 1988-
(författare)
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microRNAs: from biogenesis to organismal tracing
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- MicroRNAs (miRNAs) are short noncoding RNAs of around 22 nucleotides in length, which help to shape the expression of most mRNAs. Perturbation of miRNA expression has revealed a variety of defects in development, cell specification, physiology and behavior. This thesis focuses on two topics of miRNA: identification of structural features that influence miRNA biogenesis (Paper I) and application of taxonomical marker miRNAs to resolve organismal origin of samples (Paper II and III).The current model of miRNA hairpin biogenesis has limited information content and appears to be incomplete. In paper I, we apply a novel high-throughput screening method to profile the optimal structure of miRNA hairpins for efficient and precise miRNA biogenesis. The optimal structure consists of tight and loose local structures across the hairpin, which reflects the constraints of biogenesis proteins. We find that miRNA hairpins with stable lower basal stem are more efficiently processed and have a higher expression level in tissues of 20 animal species. We address that the structural features - which have been largely neglected in the current model - are in fact as important as the well-known sequence motifs.New miRNAs are continuously added over evolutionary time and are rarely secondarily lost, making them ideal taxonomical markers. In paper II, we demonstrate as a proof-of-principle that miRNAs can be used to trace biological sample back to the lineage or even species of origin. Based on the marker miRNAs, we develop miRTrace, the first software to accurately trace miRNA sequences back to their taxonomical origin. The method can sensitively identify the origin of single cells and detect parasitic nematode RNA in mammalian host blood sample. In paper III, we apply miRNA tracing to address a controversial question about the origin of the exogenous plant miRNAs (xenomiRs) found in human samples, and which have been proposed to regulate human gene expression. Our computational and experimental results provide evidence that xenomiRs are derived from technical artifacts rather than dietary intake.
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| 2. |
- Daniel, Chammiran, et al.
(författare)
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RNA editing of non-coding RNA and its role in gene regulation
- 2015
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Ingår i: Biochimie. - : Elsevier BV. - 0300-9084 .- 1638-6183. ; 117, s. 22-27
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Forskningsöversikt (refereegranskat)abstract
- It has for a long time been known that repetitive elements, particularly Alu sequences in human, are edited by the adenosine deaminases acting on RNA, ADAR, family. The functional interpretation of these events has been even more difficult than that of editing events in coding sequences, but today there is an emerging understanding of their downstream effects. A surprisingly large fraction of the human transcriptome contains inverted Alu repeats, often forming long double stranded structures in RNA transcripts, typically occurring in introns and UTRs of protein coding genes. Alu repeats are also common in other primates, and similar inverted repeats can frequently be found in non-primates, although the latter are less prone to duplex formation. In human, as many as 700,000 Alu elements have been identified as substrates for RNA editing, of which many are edited at several sites. In fact, recent advancements in transcriptome sequencing techniques and bioinformatics have revealed that the human editome comprises at least a hundred million adenosine to inosine (A-to-I) editing sites in Alu sequences. Although substantial additional efforts are required in order to map the editome, already present knowledge provides an excellent starting point for studying cis-regulation of editing. In this review, we will focus on editing of long stem loop structures in the human transcriptome and how it can effect gene expression.
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| 3. |
- Ensterö, Mats, et al.
(författare)
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A computational screen for site selective A-to-I editing detects novel sites in neuron specific Hu proteins
- 2010
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Background: Several bioinformatic approaches have previously been used to find novel sites of ADAR mediated A-to-I RNA editing in human. These studies have discovered thousands of genes that are hyper-edited in their non-coding intronic regions, especially in alu retrotransposable elements, but very few substrates that are site-selectively edited in coding regions. Known RNA edited substrates suggest, however, that site selective A-to-I editing is particularly important for normal brain development in mammals. Results: We have compiled a screen that enables the identification of new sites of site-selective editing, primarily in coding sequences. To avoid hyper-edited repeat regions, we applied our screen to the alu-free mouse genome. Focusing on the mouse also facilitated better experimental verification. To identify candidate sites of RNA editing, we first performed an explorative screen based on RNA structure and genomic sequence conservation. We further evaluated the results of the explorative screen by determining which transcripts were enriched for A-G mismatches between the genomic template and the expressed sequence since the editing product, inosine (I), is read as guanosine (G) by the translational machinery. For expressed sequences, we only considered coding regions to focus entirely on re-coding events. Lastly, we refined the results from the explorative screen using a novel scoring scheme based on characteristics for known A-to-I edited sites. The extent of editing in the final candidate genes was verified using total RNA from mouse brain and 454 sequencing. Conclusions: Using this method, we identified and confirmed efficient editing at one site in the Gabra3 gene. Editing was also verified at several other novel sites within candidates predicted to be edited. Five of these sites are situated in genes coding for the neuron-specific RNA binding proteins HuB and HuD.
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| 4. |
- Shahrabi Farahani, Hossein, et al.
(författare)
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A Structural EM Algorithm for Learning Oncogenetic Networks by Reducing to MILP
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Data that is obtained from assaying cancer tumors is cross-sectional, i.e., it does not contain information about temporal order and patterns of accumulation of mutations in the tumors. Learning progression patterns of cancer is important for understanding the disease. Also, in a realistic model of cancer progression, the issue of experimental errors must be taken into account. Here, the experimental errors are modeled by introducing hidden variables. The well-know structural EM algorithm is used for learning Bayesian networks from incomplete data. The selection of parents in the E-step of this algorithm is usually performed using a greedy heuristics. Unfortunately, the E-step also involves making inference in the present Bayesian network, which is #P-complete. There are ecient algorithms for performing exact inference in bounded tree-width Bayesian networks. In order to use them, we developed an algorithm for learning bounded tree-width Bayesian networks [2]. In the E-step, we obtain a globally optimal solution over dependence structure of bounded treewidth and parameters. That is, we obtain a Global Structural EM algorithm for this problem. Finally, we test our algorithm both on synthetic data and cancer data from renal cell carcinoma and show that it also performs well in practice.
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| 5. |
- Shahrabi Farahani, Hossein, 1976-
(författare)
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Computational Modeling of Cancer Progression
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cancer is a multi-stage process resulting from accumulation of genetic mutations. Data obtained from assaying a tumor only contains the set of mutations in the tumor and lacks information about their temporal order. Learning the chronological order of the genetic mutations is an important step towards understanding the disease. The probability of introduction of a mutation to a tumor increases if certain mutations that promote it, already happened. Such dependencies induce what we call the monotonicity property in cancer progression. A realistic model of cancer progression should take this property into account.In this thesis, we present two models for cancer progression and algorithms for learning them. In the first model, we propose Progression Networks (PNs), which are a special class of Bayesian networks. In learning PNs the issue of monotonicity is taken into consideration. The problem of learning PNs is reduced to Mixed Integer Linear Programming (MILP), which is a NP-hard problem for which very good heuristics exist. We also developed a program, DiProg, for learning PNs.In the second model, the problem of noise in the biological experiments is addressed by introducing hidden variable. We call this model Hidden variable Oncogenetic Network (HON). In a HON, there are two variables assigned to each node, a hidden variable that represents the progression of cancer to the node and an observable random variable that represents the observation of the mutation corresponding to the node. We devised a structural Expectation Maximization (EM) algorithm for learning HONs. In the M-step of the structural EM algorithm, we need to perform a considerable number of inference tasks. Because exact inference is tractable only on Bayesian networks with bounded treewidth, we also developed an algorithm for learning bounded treewidth Bayesian networks by reducing the problem to a MILP.Our algorithms performed well on synthetic data. We also tested them on cytogenetic data from renal cell carcinoma. The learned progression networks from both algorithms are in agreement with the previously published results.MicroRNAs are short non-coding RNAs that are involved in post transcriptional regulation. A-to-I editing of microRNAs converts adenosine to inosine in the double stranded RNA. We developed a method for determining editing levels in mature microRNAs from the high-throughput RNA sequencing data from the mouse brain. Here, for the first time, we showed that the level of editing increases with development.
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| 6. |
- Shahrabi Farahani, Hossein, et al.
(författare)
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Learning Oncogenetic Networks by Reducing to Mixed Integer Linear Programming
- 2013
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:6, s. e65773-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1], a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.
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| 7. |
- Svensson, Örjan, et al.
(författare)
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Genome-wide survey for biologically functional pseudogenes
- 2006
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 2:5, s. 358-369
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Tidskriftsartikel (refereegranskat)abstract
- According to current estimates there exist about 20,000 pseudogenes in a mammalian genome. The vast majority of these are disabled and nonfunctional copies of protein-coding genes which, therefore, evolve neutrally. Recent findings that a Makorin1 pseudogene, residing on mouse Chromosome 5, is, indeed, in vivo vital and also evolutionarily preserved, encouraged us to conduct a genome-wide survey for other functional pseudogenes in human, mouse, and chimpanzee. We identify to our knowledge the first examples of conserved pseudogenes common to human and mouse, originating from one duplication predating the human-mouse species split and having evolved as pseudogenes since the species split. Functionality is one possible way to explain the apparently contradictory properties of such pseudogene pairs, i. e., high conservation and ancient origin. The hypothesis of functionality is tested by comparing expression evidence and synteny of the candidates with proper test sets. The tests suggest potential biological function. Our candidate set includes a small set of long-lived pseudogenes whose unknown potential function is retained since before the human - mouse species split, and also a larger group of primate-specific ones found from human - chimpanzee searches. Two processed sequences are notable, their conservation since the human - mouse split being as high as most protein-coding genes; one is derived from the protein Ataxin 7- like 3 ( ATX7NL3), and one from the Spinocerebellar ataxia type 1 protein (ATX1). Our approach is comparative and can be applied to any pair of species. It is implemented by a semi-automated pipeline based on cross- species BLAST comparisons and maximum-likelihood phylogeny estimations. To separate pseudogenes from protein- coding genes, we use standard methods, utilizing in- frame disablements, as well as a probabilistic filter based on Ka/ Ks ratios.
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| 8. |
- Tofigh, Ali, et al.
(författare)
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A global structural em algorithm for a model of cancer progression
- 2011
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Ingår i: Adv. Neural Inf. Process. Syst.: Annu. Conf. Neural Inf. Process. Syst., NIPS. - 9781618395993
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Konferensbidrag (refereegranskat)abstract
- Cancer has complex patterns of progression that include converging as well as diverging progressional pathways. Vogelstein's path model of colon cancer was a pioneering contribution to cancer research. Since then, several attempts have been made at obtaining mathematical models of cancer progression, devising learning algorithms, and applying these to cross-sectional data. Beerenwinkel et al. provided, what they coined, EM-like algorithms for Oncogenetic Trees (OTs) and mixtures of such. Given the small size of current and future data sets, it is important to minimize the number of parameters of a model. For this reason, we too focus on tree-based models and introduce Hidden-variable Oncogenetic Trees (HOTs). In contrast to OTs, HOTs allow for errors in the data and thereby provide more realistic modeling. We also design global structural EM algorithms for learning HOTs and mixtures of HOTs (HOT-mixtures). The algorithms are global in the sense that, during the M-step, they find a structure that yields a global maximum of the expected complete log-likelihood rather than merely one that improves it. The algorithm for single HOTs performs very well on reasonable-sized data sets, while that for HOT-mixtures requires data sets of sizes obtainable only with tomorrow's more cost-efficient technologies.
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| 9. |
- Tofigh, Ali, et al.
(författare)
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Inferring Duplications and Lateral Gene Transfers : An Algorithm for Parametric Tree Reconciliation
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Prediction of the function of genes and their products is an increasingly important computational problem. The ability to correctly identify the historic relationship of homologous genes is essential for making accurate predictions.In 1970, Fitch made a distinction between paralogous and orthologous genes, its importance lying in the observation that genes are more likely to have similar functions when they have evolved from a common ancestral gene through speciation rather than duplication. Lateral gene transfer (LGT) is yet another important evolutionary event that creates copies of genes, and asour understanding of the importance and prevalence of LGT in evolution is deepening, there is a high demand for methods for detection of LGTs when reconstructing the evolutionary past of genes. In this paper, we present highly efficient and practical algorithms for treereconciliation that simultaneously consider both duplications and LGTs. Weallow costs to be associated with duplications and LGTs and develop methods for finding reconciliations of minimal total cost between species trees andgene trees. Moreover, we provide an efficient algorithm for parametric treereconciliation—a computational problem analogous to parametric sequencealignment. Experimental results on synthetic data indicate that our methodsare robust with high specificity and sensitivity.
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| 10. |
- Tofigh, Ali, et al.
(författare)
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Simultaneous Identification of Duplications and Lateral Gene Transfers
- 2011
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - 1545-5963 .- 1557-9964. ; 8:2, s. 517-535
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Tidskriftsartikel (refereegranskat)abstract
- The incongruency between a gene tree and a corresponding species tree can be attributed to evolutionary events such as gene duplication and gene loss. This paper describes a combinatorial model where a so-called DTL-scenario is used to explain the differences between a gene tree anda corresponding species tree taking into account gene duplications, gene losses, and lateral genetransfers (also known as horizontal gene transfers). The reasonable biological constraint that a lateralgene transfer may only occur between contemporary species leads to the notion of acyclic DTLscenarios.Parsimony methods are introduced by defining appropriate optimization problems. Weshow that finding most parsimonious acyclic DTL-scenarios is NP-complete. However, by droppingthe condition of acyclicity, the problem becomes tractable, and we provide a dynamic programmingalgorithm as well as a fixed-parameter-tractable algorithm for finding most parsimonious DTLscenarios.
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