| 1. |
- Diamanti, Klev, 1987-
(författare)
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Integrating multi-omics for type 2 diabetes : Data science and big data towards personalized medicine
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Type 2 diabetes (T2D) is a complex metabolic disease characterized by multi-tissue insulin resistance and failure of the pancreatic β-cells to secrete sufficient amounts of insulin. Cells recruit transcription factors (TF) to specific genomic loci to regulate gene expression that consequently affects the protein and metabolite abundancies. Here we investigated the interplay of transcriptional and translational regulation, and its impact on metabolome and phenome for several insulin-resistant tissues from T2D donors. We implemented computational tools and multi-omics integrative approaches that can facilitate the selection of candidate combinatorial markers for T2D.We developed a data-driven approach to identify putative regulatory regions and TF-interaction complexes. The cell-specific sets of regulatory regions were enriched for disease-related single nucleotide polymorphisms (SNPs), highlighting the importance of such loci towards the genomic stability and the regulation of gene expression. We employed a similar principle in a second study where we integrated single nucleus ribonucleic acid sequencing (snRNA-seq) with bulk targeted chromosome-conformation-capture (HiCap) and mass spectrometry (MS) proteomics from liver. We identified a putatively polymorphic site that may contribute to variation in the pharmacogenetics of fluoropyrimidines toxicity for the DPYD gene. Additionally, we found a complex regulatory network between a group of 16 enhancers and the SLC2A2 gene that has been linked to increased risk for hepatocellular carcinoma (HCC). Moreover, three enhancers harbored motif-breaking mutations located in regulatory regions of a cohort of 314 HCC cases, and were candidate contributors to malignancy.In a cohort of 43 multi-organ donors we explored the alternating pattern of metabolites among visceral adipose tissue (VAT), pancreatic islets, skeletal muscle, liver and blood serum samples. A large fraction of lysophosphatidylcholines (LPC) decreased in muscle and serum of T2D donors, while a large number of carnitines increased in liver and blood of T2D donors, confirming that changes in metabolites occur in primary tissues, while their alterations in serum consist a secondary event. Next, we associated metabolite abundancies from 42 subjects to glucose uptake, fat content and volume of various organs measured by positron emission tomography/magnetic resonance imaging (PET/MRI). The fat content of the liver was positively associated with the amino acid tyrosine, and negatively associated with LPC(P-16:0). The insulin sensitivity of VAT and subcutaneous adipose tissue was positively associated with several LPCs, while the opposite applied to branch-chained amino acids. Finally, we presented the network visualization of a rule-based machine learning model that predicted non-diabetes and T2D in an “unseen” dataset with 78% accuracy.
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| 2. |
- Rivas-Carrillo, Salvador Daniel
(författare)
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The revolutionary partnership of computation and biology
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The organization of living beings is complex. Science uses modeling in order to gain a deeper understanding, and to be able to manipulate the processes of living organisms. To this purpose, I used and developed computational tools to investigate and model different relevant biological phenomena. In paper I, I utilized whole-genome data from wild and domesticated European rabbit (Oryctolagus cuniculus sp.) populations to identify segregating insertions of endogenous retroviruses and compare their variation along the host phylogeny and domestication history. The results from this study highlight the importance of genomic modeling beyond reference organisms and reference individuals, and provide deep insights regarding strategies for variant analyses in host population comparative genomics. In paper IV, I studied the process of exaptation of foreign genetic elements at broad-scale by observing the presence and characteristics of retroviral env gene, syncytin, across vertebrates. I searched a library of more than 150 chromosome-length assemblies covering 17 taxonomical orders for syncytin homologs, where I identified and syntenically aligned over 300 loci insertions, including not previously known insertions. Additionally, three-dimensional structures of the recovered sequences were predicted using AlphaFold2. Phylogenomics analyses suggest a complex dynamic of multiple retroviral insertions at different time points with sequence conservation specific to clades that share a similar histo-physiological placental type.In paper II, I expanded the scope to encompass translational medicine by developing an unsupervised machine learning methodology for detecting anomalies in biomedical signals, MindReader, which I applied primarily to electroencephalogram. In paper III, I developed a hidden Markov model implementation that includes a hypothesis generator for stream time-domain signals, which is used as a dependency for paper II. The work in this thesis substantiates that a combination of biological knowledge, cutting-edge technology, and robust algorithmic design constitute the primordial factors for scientific advancement.
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| 3. |
- Torabi Moghadam, Behrooz
(författare)
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Computational discovery of DNA methylation patterns as biomarkers of ageing, cancer, and mental disorders : Algorithms and Tools
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Epigenetics refers to the mitotically heritable modifications in gene expression without a change in the genetic code. A combination of molecular, chemical and environmental factors constituting the epigenome is involved, together with the genome, in setting up the unique functionality of each cell type.DNA methylation is the most studied epigenetic mark in mammals, where a methyl group is added to the cytosine in a cytosine-phosphate-guanine dinucleotides or a CpG site. It has been shown to have a major role in various biological phenomena such as chromosome X inactivation, regulation of gene expression, cell differentiation, genomic imprinting. Furthermore, aberrant patterns of DNA methylation have been observed in various diseases including cancer.In this thesis, we have utilized machine learning methods and developed new methods and tools to analyze DNA methylation patterns as a biomarker of ageing, cancer subtyping and mental disorders.In Paper I, we introduced a pipeline of Monte Carlo Feature Selection and rule-base modeling using ROSETTA in order to identify combinations of CpG sites that classify samples in different age intervals based on the DNA methylation levels. The combination of genes that showed up to be acting together, motivated us to develop an interactive pathway browser, named PiiL, to check the methylation status of multiple genes in a pathway. The tool enhances detecting differential patterns of DNA methylation and/or gene expression by quickly assessing large data sets.In Paper III, we developed a novel unsupervised clustering method, methylSaguaro, for analyzing various types of cancers, to detect cancer subtypes based on their DNA methylation patterns. Using this method we confirmed the previously reported findings that challenge the histological grouping of the patients, and proposed new subtypes based on DNA methylation patterns. In Paper IV, we investigated the DNA methylation patterns in a cohort of schizophrenic and healthy samples, using all the methods that were introduced and developed in the first three papers.
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| 4. |
- Weissensteiner, Matthias H.
(författare)
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Evolutionary genomics in Corvids : – From single nucleotides to structural variants
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Heritable genetic variation is the raw material of evolution and can occur in many different forms, from altering single nucleotides to rearranging stretches of millions at once. DNA mutations that result in phenotypic differences are the basis upon which natural selection can act, leading to a shift of the frequency of those mutations.In this thesis I aim to comprehensively characterize and quantify genetic variation in a natural system, the songbird genus Corvus. First, we expand on previous work from a hybrid zone of different populations of Eurasian crows. All black carrion crows and black-and-grey hooded crows meet in a narrow hybrid zone in central Europe, and also in central and Southeast Asia. Comparing population genetic data acquired from these three hybrid zones yielded no single genetic region as a candidate responsible for phenotypic divergence, yet a parallelism in sets of genes and gene networks was evident.Second, we capitalize on varying evolutionary timescales to investigate the driver of the heterogeneous genetic differentiation landscape observed in multiple avian species. Genetic diversity, and thus differentiation, seems to be correlated both between populations within single species and between species which diverged 50 million years ago. This pattern is best explained by conserved broad-scale recombination rate variation, which is in turn likely associated with chromosomal features such as centromeres and telomeres.Third, we introduce a de-novo assembly of the hooded crow based on long-read sequencing and optical mapping. The use of this technology allowed a glimpse into previously hidden regions of the genome, and uncovered large-scale tandem repeat arrays consisting of a 14-kbp satellite repeat or its 1.2-kpb subunit. Furthermore, these tandem repeat arrays are associated with regions of reduced recombination rate.Lastly, we extend the population genetic analysis to structural genomic variation, such as insertions and deletions. A large-scale population re-sequencing data set based on short-read and long-read technologies, spread across the entire genus is the foundation of a fine-scale genome-wide map of structural variation. A differentiation outlier approach between all-black carrion and black-and-grey hooded crows identified a 2.25-kilobase LTR retrotransposon inserted 20-kb upstream of the NDP gene. The element, which is fixed in the hooded crow population, is associated with decreased expression of NDP and may be responsible for differences in plumage color.
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