| 1. |
- Baumann, Martina, et al.
(författare)
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Artificially designed promoters : understanding the role of spatial features and canonical binding sites in transcription
- 2012
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Ingår i: Bioengineered Bugs. - : Informa UK Limited. - 1949-1018 .- 1949-1026. ; 3:2, s. 120-123
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Tidskriftsartikel (refereegranskat)abstract
- The promoter is a key element in gene transcription and regulation. We previously reported that artificial sequences rich in the dinucleotide CpG are sufficient to drive expression in vitro in mammalian cell lines, without requiring canonical binding sites for transcription factor proteins. Here, we report that introducing a promoter organization that alternates in CpGs and regions rich in A and T further increases expression strength, as well as how insertion of specific binding sites makes such sequences respond to induced levels of the transcription factor NFκB. Our findings further contribute to the mechanistic understanding of promoters, as well as how these sequences might be shaped by evolutionary pressure in living organisms.
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| 2. |
- Zamani, Neda, et al.
(författare)
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A universal genomic coordinate translator for comparative genomics
- 2014
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 15, s. 227-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Genomic duplications constitute major events in the evolution of species, allowing paralogous copies of genes to take on fine-tuned biological roles. Unambiguously identifying the orthology relationship between copies across multiple genomes can be resolved by synteny, i.e. the conserved order of genomic sequences. However, a comprehensive analysis of duplication events and their contributions to evolution would require all-to-all genome alignments, which increases at N-2 with the number of available genomes, N. Results: Here, we introduce Kraken, software that omits the all-to-all requirement by recursively traversing a graph of pairwise alignments and dynamically re-computing orthology. Kraken scales linearly with the number of targeted genomes, N, which allows for including large numbers of genomes in analyses. We first evaluated the method on the set of 12 Drosophila genomes, finding that orthologous correspondence computed indirectly through a graph of multiple synteny maps comes at minimal cost in terms of sensitivity, but reduces overall computational runtime by an order of magnitude. We then used the method on three well-annotated mammalian genomes, human, mouse, and rat, and show that up to 93% of protein coding transcripts have unambiguous pairwise orthologous relationships across the genomes. On a nucleotide level, 70 to 83% of exons match exactly at both splice junctions, and up to 97% on at least one junction. We last applied Kraken to an RNA-sequencing dataset from multiple vertebrates and diverse tissues, where we confirmed that brain-specific gene family members, i.e. one-to-many or many-to-many homologs, are more highly correlated across species than single-copy (i.e. one-to-one homologous) genes. Not limited to protein coding genes, Kraken also identifies thousands of newly identified transcribed loci, likely non-coding RNAs that are consistently transcribed in human, chimpanzee and gorilla, and maintain significant correlation of expression levels across species. Conclusions: Kraken is a computational genome coordinate translator that facilitates cross-species comparisons, distinguishes orthologs from paralogs, and does not require costly all-to-all whole genome mappings. Kraken is freely available under LPGL from http://github.com/nedaz/kraken.
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| 3. |
- Elewa, A, et al.
(författare)
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Reading and editing the Pleurodeles waltl genome reveals novel features of tetrapod regeneration
- 2017
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8:1, s. 2286-
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Tidskriftsartikel (refereegranskat)abstract
- Salamanders exhibit an extraordinary ability among vertebrates to regenerate complex body parts. However, scarce genomic resources have limited our understanding of regeneration in adult salamanders. Here, we present the ~20 Gb genome and transcriptome of the Iberian ribbed newt Pleurodeles waltl, a tractable species suitable for laboratory research. We find that embryonic stem cell-specific miRNAs mir-93b and mir-427/430/302, as well as Harbinger DNA transposons carrying the Myb-like proto-oncogene have expanded dramatically in the Pleurodeleswaltl genome and are co-expressed during limb regeneration. Moreover, we find that a family of salamander methyltransferases is expressed specifically in adult appendages. Using CRISPR/Cas9 technology to perturb transcription factors, we demonstrate that, unlike the axolotl, Pax3 is present and necessary for development and that contrary to mammals, muscle regeneration is normal without functional Pax7 gene. Our data provide a foundation for comparative genomic studies that generate models for the uneven distribution of regenerative capacities among vertebrates.
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| 4. |
- Grabherr, Manfred G, et al.
(författare)
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Full-length transcriptome assembly from RNA-Seq data without a reference genome
- 2011
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 29:7, s. 644-652
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Tidskriftsartikel (refereegranskat)abstract
- Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.
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| 5. |
- Rivas-Carrillo, Salvador Daniel, et al.
(författare)
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MindReader : Unsupervised Classification of Electroencephalographic Data
- 2023
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 23:6, s. 2971-
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Tidskriftsartikel (refereegranskat)abstract
- Electroencephalogram (EEG) interpretation plays a critical role in the clinical assessment of neurological conditions, most notably epilepsy. However, EEG recordings are typically analyzed manually by highly specialized and heavily trained personnel. Moreover, the low rate of capturing abnormal events during the procedure makes interpretation time-consuming, resource-hungry, and overall an expensive process. Automatic detection offers the potential to improve the quality of patient care by shortening the time to diagnosis, managing big data and optimizing the allocation of human resources towards precision medicine. Here, we present MindReader, a novel unsupervised machine-learning method comprised of the interplay between an autoencoder network, a hidden Markov model (HMM), and a generative component: after dividing the signal into overlapping frames and performing a fast Fourier transform, MindReader trains an autoencoder neural network for dimensionality reduction and compact representation of different frequency patterns for each frame. Next, we processed the temporal patterns using a HMM, while a third and generative component hypothesized and characterized the different phases that were then fed back to the HMM. MindReader then automatically generates labels that the physician can interpret as pathological and non-pathological phases, thus effectively reducing the search space for trained personnel. We evaluated MindReader's predictive performance on 686 recordings, encompassing more than 980 h from the publicly available Physionet database. Compared to manual annotations, MindReader identified 197 of 198 epileptic events (99.45%), and is, as such, a highly sensitive method, which is a prerequisite for clinical use.
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| 6. |
- Torabi Moghadam, Behrooz, et al.
(författare)
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Combinatorial identification of DNA methylation patterns over age in the human brain
- 2016
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Background: DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. Results: We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites. Conclusion: We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer's disease.
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