| 1. |
- Barrientos-Somarribas, Mauricio, et al.
(författare)
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Discovering viral genomes in human metagenomic data by predicting unknown protein families
- 2018
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Massive amounts of metagenomics data are currently being produced, and in all such projects a sizeable fraction of the resulting data shows no or little homology to known sequences. It is likely that this fraction contains novel viruses, but identification is challenging since they frequently lack homology to known viruses. To overcome this problem, we developed a strategy to detect ORFan protein families in shotgun metagenomics data, using similarity-based clustering and a set of filters to extract bona fide protein families. We applied this method to 17 virus-enriched libraries originating from human nasopharyngeal aspirates, serum, feces, and cerebrospinal fluid samples. This resulted in 32 predicted putative novel gene families. Some families showed detectable homology to sequences in metagenomics datasets and protein databases after reannotation. Notably, one predicted family matches an ORF from the highly variable Torque Teno virus (TTV). Furthermore, follow-up from a predicted ORFan resulted in the complete reconstruction of a novel circular genome. Its organisation suggests that it most likely corresponds to a novel bacteriophage in the microviridae family, hence it was named bacteriophage HFM.
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| 2. |
- Carreras-Puigvert, Jordi, et al.
(författare)
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A comprehensive structural, biochemical and biological profiling of the human NUDIX hydrolase family
- 2017
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Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- The NUDIX enzymes are involved in cellular metabolism and homeostasis, as well as mRNA processing. Although highly conserved throughout all organisms, their biological roles and biochemical redundancies remain largely unclear. To address this, we globally resolve their individual properties and inter-relationships. We purify 18 of the human NUDIX proteins and screen 52 substrates, providing a substrate redundancy map. Using crystal structures, we generate sequence alignment analyses revealing four major structural classes. To a certain extent, their substrate preference redundancies correlate with structural classes, thus linking structure and activity relationships. To elucidate interdependence among the NUDIX hydrolases, we pairwise deplete them generating an epistatic interaction map, evaluate cell cycle perturbations upon knockdown in normal and cancer cells, and analyse their protein and mRNA expression in normal and cancer tissues. Using a novel FUSION algorithm, we integrate all data creating a comprehensive NUDIX enzyme profile map, which will prove fundamental to understanding their biological functionality.
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| 3. |
- El-Gebali, Sara, et al.
(författare)
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The Pfam protein families database in 2019
- 2019
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 47:D1, s. D427-D432
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Tidskriftsartikel (refereegranskat)abstract
- The last few years have witnessed significant changes in Pfam (https://pfam.xfam.org). The number of families has grown substantially to a total of 17,929 in release 32.0. New additions have been coupled with efforts to improve existing families, including refinement of domain boundaries, their classification into Pfam clans, as well as their functional annotation. We recently began to collaborate with the RepeatsDB resource to improve the definition of tandem repeat families within Pfam. We carried out a significant comparison to the structural classification database, namely the Evolutionary Classification of Protein Domains (ECOD) that led to the creation of 825 new families based on their set of uncharacterized families(EUFs). Furthermore, we also connected Pfam entries to the Sequence Ontology (SO) through mapping of the Pfam type definitions to SO terms. Since Pfam has many community contributors, we recently enabled the linking between authorship of all Pfam entries with the corresponding authors' ORCID identifiers. This effectively permits authors to claim credit for their Pfam curation and link them to their ORCID record.
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| 4. |
- Guala, Dimitri, et al.
(författare)
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A large-scale benchmark of gene prioritization methods
- 2017
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly analyzed and benchmarked gene prioritization tools. While prospective benchmarks are underpowered to provide statistically significant results in their attempt to differentiate the performance of gene prioritization tools, a strategy for retrospective benchmarking has been missing, and new tools usually only provide internal validations. The Gene Ontology (GO) contains genes clustered around annotation terms. This intrinsic property of GO can be utilized in construction of robust benchmarks, objective to the problem domain. We demonstrate how this can be achieved for network-based gene prioritization tools, utilizing the FunCoup network. We use cross-validation and a set of appropriate performance measures to compare state-of-the-art gene prioritization algorithms: three based on network diffusion, NetRank and two implementations of Random Walk with Restart, and MaxLink that utilizes network neighborhood. Our benchmark suite provides a systematic and objective way to compare the multitude of available and future gene prioritization tools, enabling researchers to select the best gene prioritization tool for the task at hand, and helping to guide the development of more accurate methods.
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| 5. |
- Guala, Dimitri, et al.
(författare)
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Experimental validation of predicted cancer genes using FRET
- 2018
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Ingår i: METHODS AND APPLICATIONS IN FLUORESCENCE. - : IOP PUBLISHING LTD. - 2050-6120. ; 6:3
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Tidskriftsartikel (refereegranskat)abstract
- Huge amounts of data are generated in genome wide experiments, designed to investigate diseases with complex genetic causes. Follow up of all potential leads produced by such experiments is currently cost prohibitive and time consuming. Gene prioritization tools alleviate these constraints by directing further experimental efforts towards the most promising candidate targets. Recently a gene prioritization tool called MaxLink was shown to outperform other widely used state-of-the-art prioritization tools in a large scale in silico benchmark. An experimental validation of predictions made by MaxLink has however been lacking. In this study we used Fluorescence Resonance Energy Transfer, an established experimental technique for detection of protein-protein interactions, to validate potential cancer genes predicted by MaxLink. Our results provide confidence in the use of MaxLink for selection of new targets in the battle with polygenic diseases.
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| 6. |
- Guala, Dimitri, 1979-
(författare)
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Functional association networks for disease gene prediction
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Mapping of the human genome has been instrumental in understanding diseasescaused by changes in single genes. However, disease mechanisms involvingmultiple genes have proven to be much more elusive. Their complexityemerges from interactions of intracellular molecules and makes them immuneto the traditional reductionist approach. Only by modelling this complexinteraction pattern using networks is it possible to understand the emergentproperties that give rise to diseases.The overarching term used to describe both physical and indirect interactionsinvolved in the same functions is functional association. FunCoup is oneof the most comprehensive networks of functional association. It uses a naïveBayesian approach to integrate high-throughput experimental evidence of intracellularinteractions in humans and multiple model organisms. In the firstupdate, both the coverage and the quality of the interactions, were increasedand a feature for comparing interactions across species was added. The latestupdate involved a complete overhaul of all data sources, including a refinementof the training data and addition of new class and sources of interactionsas well as six new species.Disease-specific changes in genes can be identified using high-throughputgenome-wide studies of patients and healthy individuals. To understand theunderlying mechanisms that produce these changes, they can be mapped tocollections of genes with known functions, such as pathways. BinoX wasdeveloped to map altered genes to pathways using the topology of FunCoup.This approach combined with a new random model for comparison enables BinoXto outperform traditional gene-overlap-based methods and other networkbasedtechniques.Results from high-throughput experiments are challenged by noise and biases,resulting in many false positives. Statistical attempts to correct for thesechallenges have led to a reduction in coverage. Both limitations can be remediedusing prioritisation tools such as MaxLink, which ranks genes using guiltby association in the context of a functional association network. MaxLink’salgorithm was generalised to work with any disease phenotype and its statisticalfoundation was strengthened. MaxLink’s predictions were validatedexperimentally using FRET.The availability of prioritisation tools without an appropriate way to comparethem makes it difficult to select the correct tool for a problem domain.A benchmark to assess performance of prioritisation tools in terms of theirability to generalise to new data was developed. FunCoup was used for prioritisationwhile testing was done using cross-validation of terms derived fromGene Ontology. This resulted in a robust and unbiased benchmark for evaluationof current and future prioritisation tools. Surprisingly, previously superiortools based on global network structure were shown to be inferior to a localnetwork-based tool when performance was analysed on the most relevant partof the output, i.e. the top ranked genes.This thesis demonstrates how a network that models the intricate biologyof the cell can contribute with valuable insights for researchers that study diseaseswith complex genetic origins. The developed tools will help the researchcommunity to understand the underlying causes of such diseases and discovernew treatment targets. The robust way to benchmark such tools will help researchersto select the proper tool for their problem domain.
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| 7. |
- Haider, Christian, et al.
(författare)
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TreeDom : a graphical web tool for analysing domain architecture evolution
- 2016
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 32:15, s. 2384-2385
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Tidskriftsartikel (refereegranskat)abstract
- We present TreeDom, a web tool for graphically analysing the evolutionary history of domains in multi-domain proteins. Individual domains on the same protein chain may have distinct evolutionary histories, which is important to grasp in order to understand protein function. For instance, it may be important to know whether a domain was duplicated recently or long ago, to know the origin of inserted domains, or to know the pattern of domain loss within a protein family. TreeDom uses the Pfam database as the source of domain annotations, and displays these on a sequence tree. An advantage of TreeDom is that the user can limit the analysis to N sequences that are most similar to a query, or provide a list of sequence IDs to include. Using the Pfam alignment of the selected sequences, a tree is built and displayed together with the domain architecture of each sequence.
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| 8. |
- Kaduk, Mateusz, et al.
(författare)
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HieranoiDB : a database of orthologs inferred by Hieranoid
- 2017
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 45:D1, s. D687-D690
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Tidskriftsartikel (refereegranskat)abstract
- HieranoiDB (http://hieranoiDB.sbc.su.se) is a freely available on-line database for hierarchical groups of orthologs inferred by the Hieranoid algorithm. It infers orthologs at each node in a species guide tree with the InParanoid algorithm as it progresses from the leaves to the root. Here we present a database HieranoiDB with a web interface that makes it easy to search and visualize the output of Hieranoid, and to download it in various formats. Searching can be performed using protein description, identifier or sequence. In this first version, orthologs are available for the 66 Quest for Orthologs reference proteomes. The ortholog trees are shown graphically and interactively with marked speciation and duplication nodes that show the inferred evolutionary scenario, and allow for correct extraction of predicted orthologs from the Hieranoid trees.
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| 9. |
- Morgan, Daniel, 1988-, et al.
(författare)
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A generalized framework for controlling FDR in gene regulatory network inference
- 2019
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 35:6, s. 1026-1032
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Inference of gene regulatory networks (GRNs) from perturbation data can give detailed mechanistic insights of a biological system. Many inference methods exist, but the resulting GRN is generally sensitive to the choice of method-specific parameters. Even though the inferred GRN is optimal given the parameters, many links may be wrong or missing if the data is not informative. To make GRN inference reliable, a method is needed to estimate the support of each predicted link as the method parameters are varied.Results: To achieve this we have developed a method called nested bootstrapping, which applies a bootstrapping protocol to GRN inference, and by repeated bootstrap runs assesses the stability of the estimated support values. To translate bootstrap support values to false discovery rates we run the same pipeline with shuffled data as input. This provides a general method to control the false discovery rate of GRN inference that can be applied to any setting of inference parameters, noise level, or data properties. We evaluated nested bootstrapping on a simulated dataset spanning a range of such properties, using the LASSO, Least Squares, RNI, GENIE3 and CLR inference methods. An improved inference accuracy was observed in almost all situations. Nested bootstrapping was incorporated into the GeneSPIDER package, which was also used for generating the simulated networks and data, as well as running and analyzing the inferences.
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| 10. |
- Ogris, Christoph, et al.
(författare)
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A novel method for crosstalk analysis of biological networks : improving accuracy of pathway annotation
- 2017
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 45:2
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Tidskriftsartikel (refereegranskat)abstract
- Analyzing gene expression patterns is a mainstay to gain functional insights of biological systems. A plethora of tools exist to identify significant enrichment of pathways for a set of differentially expressed genes. Most tools analyze gene overlap between gene sets and are therefore severely hampered by the current state of pathway annotation, yet at the same time they run a high risk of false assignments. A way to improve both true positive and false positive rates (FPRs) is to use a functional association network and instead look for enrichment of network connections between gene sets. We present a new network crosstalk analysis method BinoX that determines the statistical significance of network link enrichment or depletion between gene sets, using the binomial distribution. This is a much more appropriate statistical model than previous methods have employed, and as a result BinoX yields substantially better true positive and FPRs than was possible before. A number of benchmarks were performed to assess the accuracy of BinoX and competing methods. We demonstrate examples of how BinoX finds many biologically meaningful pathway annotations for gene sets from cancer and other diseases, which are not found by other methods.
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