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Sökning: WFRF:(Feuk Lars)

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21.
  • Feuk, Lars (författare)
  • Inversion variants in the human genome : role in disease and genome architecture
  • 2010
  • Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X .- 1756-994X. ; 2:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Significant advances have been made over the past 5 years in mapping and characterizing structural variation in the human genome. Despite this progress, our understanding of inversion variants is still very restricted. While unbalanced variants such as copy number variations can be mapped using array-based approaches, strategies for characterization of inversion variants have been limited and underdeveloped. Traditional cytogenetic approaches have long been able to identify microscopic inversion events, but discovery of submicroscopic events has remained elusive and largely ignored. With the advent of paired-end sequencing approaches, it is now possible to map inversions across the human genome. Based on the paired-end sequencing studies published to date, it is now feasible to make a first map of inversions across the human genome and to use this map to explore the characteristics and distribution of this form of variation. The current map of inversions indicates that many remain to be identified, especially in the smaller size ranges. This review provides an overview of the current knowledge about human inversions and their contribution to human phenotypes. Further characterization of inversions should be considered as an important step towards a deeper understanding of human variation and genome dynamics.
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22.
  • Feuk, Lars (författare)
  • SNP based strategies to study candidate genes for Alzheimer’s disease
  • 2002
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Alzheimer’s disease (AD) is the most common form of dementia in the elderly. It is a genetically heterogeneous disease characterized by progressive cognitive decline and memory impairment. The rare familial form of AD is caused by three different genes called APP, PSEN1 and PSEN2. However, the predominant form of AD is a genetically complex disorder involving a combination of genetic factors. To date, the only risk factor identified for the complex form of AD is the APOE-epsilon 4 allele, but several susceptibility genes remain to be found. This thesis outlines different strategies to use common genetic variation, in the form of single nucleotide polymorphisms (SNPs), to examine candidate genes and candidate regions for AD. Large-scale genotyping is a prerequisite for performing complex disease studies using SNPs. The validity and accuracy of a newly developed genotyping assay called Dynamic allele specific hybridization (DASH) was therefore investigated. DASH was shown to be a robust genotyping method, and was proven to work as well or better than several other available methods. 'the method was first implemented for a candidate gene association study of a promoter polymorphism in the TNFRSF6 gene. Significant association was found between this variant and early onset AD, indicating its possible role in disease etiology. A large candidate pathway association study effort was then started testing for association between AD and 60 different SNPs. Genes were picked from four different pathways related to AD; oxidation, inflammation/apoptosis, amyloid interacting genes and a group of candidate genes previously showing significant association with AD. None of the markers showed significant disease association after correction for multiple testing. Although largely negative, these results high-lighted several methodological and study design issues related to association studies in general. The most successful approach yet in dissecting complex disease using genetic variation has been to perform high resolution linkage disequilibrium (LD) mapping of regions indicated by linkage. Several independent research groups recently reported linkage peaks for AD on chromosome 10q We choose two regions under the 10q linkage peak for LD mapping studies. The first region contained the previously associated TNFRSF6 gene, and the other region included the insulin-degrading enzyme (IDE) gene, which has been shown to be involved in clearance of amyloid-beta. LD maps were created for all pair-wise markers in the two regions to determine the genetic LD structure. Haplotypes were estimated and haplotype tagging markers were chosen for further analysis. Association analyses were performed for both single markers and haplotypes for case/control status as well as for quantitative traits related to the AD phenotype. Only weak significant signals were found for the TNFRSF6 gene. However, several significant associations were found for a large LD block including the IDE gene. The same haplotypes were always over-represented in cases compared to controls, or with more severe AD within the patient groups. These results indicate a role in AD for one of the three genes situated within the 276kb LD block including the IDE, KNSLI and HHEX genes. Further studies will now be required to identify the underlying risk alleles within the region.
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23.
  • Garbulowski, Mateusz, et al. (författare)
  • Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder
  • 2021
  • Ingår i: Frontiers in Genetics. - : Frontiers Media S.A.. - 1664-8021. ; 12
  • Tidskriftsartikel (refereegranskat)abstract
    • Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric disorder with a complex genetic background. Analysis of altered molecular processes in ASD patients requires linear and nonlinear methods that provide interpretable solutions. Interpretable machine learning provides legible models that allow explaining biological mechanisms and support analysis of clinical subgroups. In this work, we investigated several case-control studies of gene expression measurements of ASD individuals. We constructed a rule-based learning model from three independent datasets that we further visualized as a nonlinear gene-gene co-predictive network. To find dissimilarities between ASD subtypes, we scrutinized a topological structure of the network and estimated a centrality distance. Our analysis revealed that autism is the most severe subtype of ASD, while pervasive developmental disorder-not otherwise specified and Asperger syndrome are closely related and milder ASD subtypes. Furthermore, we analyzed the most important ASD-related features that were described in terms of gene co-predictors. Among others, we found a strong co-predictive mechanism between EMC4 and TMEM30A, which may suggest a co-regulation between these genes. The present study demonstrates the potential of applying interpretable machine learning in bioinformatics analyses. Although the proposed methodology was designed for transcriptomics data, it can be applied to other omics disciplines.
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24.
  • Garbulowski, Mateusz, et al. (författare)
  • R.ROSETTA : an interpretable machine learning framework
  • 2021
  • Ingår i: BMC Bioinformatics. - : BioMed Central (BMC). - 1471-2105. ; 22:1
  • Tidskriftsartikel (refereegranskat)abstract
    • BackgroundMachine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a prediction was obtained rather than knowing what prediction was made. To this end so-called interpretable machine learning has been recently advocated. In this study, we implemented an interpretable machine learning package based on the rough set theory. An important aim of our work was provision of statistical properties of the models and their components.ResultsWe present the R.ROSETTA package, which is an R wrapper of ROSETTA framework. The original ROSETTA functions have been improved and adapted to the R programming environment. The package allows for building and analyzing non-linear interpretable machine learning models. R.ROSETTA gathers combinatorial statistics via rule-based modelling for accessible and transparent results, well-suited for adoption within the greater scientific community. The package also provides statistics and visualization tools that facilitate minimization of analysis bias and noise. The R.ROSETTA package is freely available at https://github.com/komorowskilab/R.ROSETTA. To illustrate the usage of the package, we applied it to a transcriptome dataset from an autism case–control study. Our tool provided hypotheses for potential co-predictive mechanisms among features that discerned phenotype classes. These co-predictors represented neurodevelopmental and autism-related genes.ConclusionsR.ROSETTA provides new insights for interpretable machine learning analyses and knowledge-based systems. We demonstrated that our package facilitated detection of dependencies for autism-related genes. Although the sample application of R.ROSETTA illustrates transcriptome data analysis, the package can be used to analyze any data organized in decision tables.
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25.
  • Halvardson, Jonatan, et al. (författare)
  • Exome RNA sequencing reveals rare and novel alternative transcripts
  • 2013
  • Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 41:1, s. e6-
  • Tidskriftsartikel (refereegranskat)abstract
    • RNA sequencing has become an important method to perform hypothesis-free characterization of global gene expression. One of the limitations of RNA sequencing is that most sequence reads represent highly expressed transcripts, whereas low level transcripts are challenging to detect. To combine the benefits of traditional expression arrays with the advantages of RNA sequencing, we have used whole exome enrichment prior to sequencing of total RNA. We show that whole exome capture can be successfully applied to cDNA to study the transcriptional landscape in human tissues. By introducing the exome enrichment step, we are able to identify transcripts present at very low levels, which are below the level of detection in conventional RNA sequencing. Although the enrichment increases the ability to detect presence of transcripts, it also lowers the accuracy of quantification of expression levels. Our results yield a large number of novel exons and splice isoforms, suggesting that conventional RNA sequencing methods only detect a small fraction of the full transcript diversity. We propose that whole exome enrichment of RNA is a suitable strategy for genome-wide discovery of novel transcripts, alternative splice variants and fusion genes.
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26.
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27.
  • Halvardson, Jonatan, et al. (författare)
  • Mutations in HECW2 are associated with intellectual disability and epilepsy
  • 2016
  • Ingår i: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 53:10, s. 697-704
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: De novo mutations are a frequent cause of disorders related to brain development. We report the results of screening patients diagnosed with both epilepsy and intellectual disability (ID) using exome sequencing to identify known and new causative de novo mutations relevant to these conditions.METHODS: Exome sequencing was performed on 39 patient-parent trios to identify de novo mutations. Clinical significance of de novo mutations in genes was determined using the American College of Medical Genetics and Genomics standard guidelines for interpretation of coding variants. Variants in genes of unknown clinical significance were further analysed in the context of previous trio sequencing efforts in neurodevelopmental disorders.RESULTS: In 39 patient-parent trios we identified 29 de novo mutations in coding sequence. Analysis of de novo and inherited variants yielded a molecular diagnosis in 11 families (28.2%). In combination with previously published exome sequencing results in neurodevelopmental disorders, our analysis implicates HECW2 as a novel candidate gene in ID and epilepsy.CONCLUSIONS: Our results support the use of exome sequencing as a diagnostic approach for ID and epilepsy, and confirm previous results regarding the importance of de novo mutations in this patient group. The results also highlight the utility of network analysis and comparison to previous large-scale studies as strategies to prioritise candidate genes for further studies. This study adds knowledge to the increasingly growing list of causative and candidate genes in ID and epilepsy and highlights HECW2 as a new candidate gene for neurodevelopmental disorders.
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28.
  • Halvardson, Jonatan, 1982- (författare)
  • Sequence based analysis of neurodevelopmental disorders
  • 2016
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • In this thesis the main focus is the use of methods and applications of next generation sequencing in order to study three of the most common neurodevelopmental disorders: intellectual disability, epilepsy and schizophrenia. A large fraction of the genes in our genome produce several distinct transcript isoforms through the process of splicing and there is an increasing amount of evidence pinpointing mutations affecting splicing as a mechanism of disease.  In Paper I we used exome capture of RNA in combination with sequencing in order to enrich for coding sequences. We show that this approach enables us to detect lowly expressed transcript and splice events that would have been missed in regular RNA sequencing using the same coverage.  In Paper II we selectively depleted the different transcripts of Quaking (QKI), a gene previously associated to schizophrenia. Using RNA sequencing we show that the effects of depletion differ between transcripts and that the QKI gene is a potential regulator of the Glial Fibrillary Acidic Protein (GFAP), a gene implicated in several diseases in the central nervous system.De-novo mutations are frequently reported to be causative in neurodevelopmental disorders with a strong genetic component, such as epilepsy and intellectual disability. In Paper III we used exome sequencing in family trios where the child was diagnosed with both intellectual disability and epilepsy, focusing on finding de-novo mutations. We identified several previously unknown disease causing mutations in genes previously known to cause disease and used previously published interaction and mutation data to prioritize novel candidate genes. The most interesting result from this study are the implication of the HECW2 gene as a candidate gene in intellectual disability and epilepsy. In Paper IV we used RNA sequencing of post mortem brain tissue in a large cohort of schizophrenics and controls.  In this study we could show that the immune system and more specifically the complement system was dysregulated in a large fraction of patients. Further, using co-expression network we also found some evidence suggesting genes involved in axon development and maintenance. 
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29.
  • Hooper, Sean D., et al. (författare)
  • Genome-wide sequencing for the identification of rearrangements associated with Tourette syndrome and obsessive-compulsive disorder
  • 2012
  • Ingår i: BMC Medical Genetics. - : Springer Science and Business Media LLC. - 1471-2350. ; 13, s. 123-
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Tourette Syndrome (TS) is a neuropsychiatric disorder in children characterized by motor and verbal tics. Although several genes have been suggested in the etiology of TS, the genetic mechanisms remain poorly understood. Methods: Using cytogenetics and FISH analysis, we identified an apparently balanced t(6,22)(q16.2;p13) in a male patient with TS and obsessive-compulsive disorder (OCD). In order to map the breakpoints and to identify additional submicroscopic rearrangements, we performed whole genome mate-pair sequencing and CGH-array analysis on DNA from the proband. Results: Sequence and CGH array analysis revealed a 400 kb deletion located 1.3 Mb telomeric of the chromosome 6q breakpoint, which has not been reported in controls. The deletion affects three genes (GPR63, NDUFA4 and KLHL32) and overlaps a region previously found deleted in a girl with autistic features and speech delay. The proband's mother, also a carrier of the translocation, was diagnosed with OCD and shares the deletion. We also describe a further potentially related rearrangement which, while unmapped in Homo sapiens, was consistent with the chimpanzee genome. Conclusions: We conclude that genome-wide sequencing at relatively low resolution can be used for the identification of submicroscopic rearrangements. We also show that large rearrangements may escape detection using standard analysis of whole genome sequencing data. Our findings further provide a candidate region for TS and OCD on chromosome 6q16.
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30.
  • Hård, Joanna, et al. (författare)
  • Long-read whole-genome analysis of human single cells
  • 2023
  • Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Long-read sequencing has dramatically increased our understanding of human genome variation. Here, we demonstrate that long-read technology can give new insights into the genomic architecture of individual cells. Clonally expanded CD8+ T-cells from a human donor were subjected to droplet-based multiple displacement amplification (dMDA) to generate long molecules with reduced bias. PacBio sequencing generated up to 40% genome coverage per single-cell, enabling detection of single nucleotide variants (SNVs), structural variants (SVs), and tandem repeats, also in regions inaccessible by short reads. 28 somatic SNVs were detected, including one case of mitochondrial heteroplasmy. 5473 high-confidence SVs/cell were discovered, a sixteen-fold increase compared to Illumina-based results from clonally related cells. Single-cell de novo assembly generated a genome size of up to 598 Mb and 1762 (12.8%) complete gene models. In summary, our work shows the promise of long-read sequencing toward characterization of the full spectrum of genetic variation in single cells.
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