| 1. |
- Klevebring, Daniel, 1981-
(author)
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On Transcriptome Sequencing
- 2009
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Doctoral thesis (other academic/artistic)abstract
- This thesis is about the use of massive DNA sequencing to investigate the transcriptome. During recent decades, several studies have made it clear that the transcriptome comprises a more complex set of biochemical machinery than was previously believed. The majority of the genome can be expressed as transcripts; and overlapping and antisense transcription is widespread. New technologies for the interroga- tion of nucleic acids have made it possible to investigate such cellular phenomena in much greater detail than ever before. For each application, special requirements need to be met. The work presented in this thesis focuses on the transcrip- tome and the development of technology for its analysis. In paper I, we report our development of an automated approach for sample preparation. The procedure was benchmarked against a publicly available reference data set, and we note that our approach outperformed similar manual procedures in terms of reproducibility. In the work reported in papers II-IV, we used different massive sequencing technologies to investigate the transcriptome. In paper II we describe a concatemerization approach that increased throughput by 65% using 454 sequencing,and we identify classes of transcripts not previously described in Populus. Papers III and IV both report studies based on SOLiD sequencing. In the former, we investigated transcripts and proteins for 13% of the human gene and detected a massive overlap for the upper 50% transcriptional levels. In the work described in paper IV, we investigated transcription in non-genic regions of the genome and detected expression from a high number of previ- ously unknown loci.
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| 2. |
- Ameur, Adam, et al.
(author)
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SweGen : a whole-genome data resource of genetic variability in a cross-section of the Swedish population
- 2017
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In: European Journal of Human Genetics. - : NATURE PUBLISHING GROUP. - 1018-4813 .- 1476-5438. ; 25:11, s. 1253-1260
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Journal article (peer-reviewed)abstract
- Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.
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| 3. |
- Yang, Zhijian, et al.
(author)
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Genetic Landscape of the ACE2 Coronavirus Receptor
- 2022
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In: Circulation. - : Ovid Technologies (Wolters Kluwer Health). - 0009-7322 .- 1524-4539. ; 30:SUPPL 1, s. 36-36
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Journal article (peer-reviewed)abstract
- Background: SARS-CoV-2, the causal agent of COVID-19, enters human cells using the ACE2 (angiotensin-converting enzyme 2) protein as a receptor. ACE2 is thus key to the infection and treatment of the coronavirus. ACE2 is highly expressed in the heart and respiratory and gastrointestinal tracts, playing important regulatory roles in the cardiovascular and other biological systems. However, the genetic basis of the ACE2 protein levels is not well understood.Methods: We have conducted the largest genome-wide association meta-analysis of plasma ACE2 levels in >28 000 individuals of the SCALLOP Consortium (Systematic and Combined Analysis of Olink Proteins). We summarize the cross-sectional epidemiological correlates of circulating ACE2. Using the summary statistics-based high-definition likelihood method, we estimate relevant genetic correlations with cardiometabolic phenotypes, COVID-19, and other human complex traits and diseases. We perform causal inference of soluble ACE2 on vascular disease outcomes and COVID-19 severity using mendelian randomization. We also perform in silico functional analysis by integrating with other types of omics data.Results: We identified 10 loci, including 8 novel, capturing 30% of the heritability of the protein. We detected that plasma ACE2 was genetically correlated with vascular diseases, severe COVID-19, and a wide range of human complex diseases and medications. An X-chromosome cis-protein quantitative trait loci-based mendelian randomization analysis suggested a causal effect of elevated ACE2 levels on COVID-19 severity (odds ratio, 1.63 [95% CI, 1.10-2.42]; P=0.01), hospitalization (odds ratio, 1.52 [95% CI, 1.05-2.21]; P=0.03), and infection (odds ratio, 1.60 [95% CI, 1.08-2.37]; P=0.02). Tissue- and cell type-specific transcriptomic and epigenomic analysis revealed that the ACE2 regulatory variants were enriched for DNA methylation sites in blood immune cells.Conclusions: Human plasma ACE2 shares a genetic basis with cardiovascular disease, COVID-19, and other related diseases. The genetic architecture of the ACE2 protein is mapped, providing a useful resource for further biological and clinical studies on this coronavirus receptor.
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