| 1. |
- Alvez, Maria Bueno, et al.
(författare)
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Next generation pan-cancer blood proteome profiling using proximity extension assay
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.
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| 2. |
- Ameur, Adam, et al.
(författare)
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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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Ingår i: European Journal of Human Genetics. - : NATURE PUBLISHING GROUP. - 1018-4813 .- 1476-5438. ; 25:11, s. 1253-1260
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Tidskriftsartikel (refereegranskat)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. |
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| 4. |
- Gyllensten, Ulf B., et al.
(författare)
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Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer
- 2022
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:7
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Tidskriftsartikel (refereegranskat)abstract
- Simple Summary Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4-7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort. Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.
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| 5. |
- Klevebring, Daniel, 1981-
(författare)
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On Transcriptome Sequencing
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)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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| 6. |
- Redin, David, 1988-
(författare)
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Phasing single DNA molecules with barcode linked sequencing
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Elucidation of our genetic constituents has in the past decade predominately taken the form of short-read DNA sequencing. Revolutionary technology developments have enabled vast amounts of biological information to be obtained, but from a medical standpoint it has yet to live up to the promise of associating individual genotypes to phenotypic states of wide-spread clinical relevance. The mechanisms by which complex phenotypes arise have been difficult to ascertain and the value of short-read sequencing platforms have been limited in this regard. It has become evident that resolving the full spectrum of genetic heterogeneity requires accurate long range information of individual haplotypes to be distinguished. Long-range haplotyping information can be obtained experimentally by long-read sequencing platforms or through linkage of short sequencing reads by means of a common barcode. This thesis explores these solutions, primarily through the development of novel technologies to phase short sequences of single molecules using DNA barcoding. A new method for high-throughput phasing of single DNA molecules, achieved by the production and utilization of uniquely barcoded beads in emulsion droplets, is described in Paper I. The results confirm that complex libraries of beads featuring mutually exclusive barcodes can be generated through clonal PCR amplification, and that these beads can be used to phase variations of the 16s rRNA gene which reduces the ambiguity of classifying bacterial species for metagenomics. Paper II describes a second methodology (‘Droplet Barcode Sequencing’) which simplifies the concept of barcoding DNA fragments by omitting the need for beads and instead relying on clonal amplification of single barcoding oligonucleotides. This study also increases the amount of information that can be linked, which is showcased by phasing all exons of the HLA-A gene and successfully resolving all the alleles present in a sample pool of eight individuals. Paper III expands on this work and explores the use of a single molecule sequencing platform to provide full-length sequencing coverage of six genes of the HLA family. The results show that while genes shorter than 10 kb can be resolved with a high degree of accuracy, compensating for a relatively high error rate by means of increased coverage can be challenging for larger genomic loci. Finally, Paper IV introduces the use of barcode-linked reads on an unprecedented scale, with a new assay that enables low-cost haplotyping of whole genomes without the need for predetermined capture sequences. This technology is utilized to generate a haplotype-resolved human genome, call large-scale structural variants and perform reference-free assembly of bacterial and human genomes. At a cost of only $19 USD per sample, this technology makes the benefits of long-range haplotyping available to the vast majority of laboratories which currently rely solely on short-read sequencing platforms.
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| 7. |
- Russom, Aman
(författare)
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Microfluidic bead-based methods for DNA analysis
- 2005
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With the completion of the human genome sequencing project, attention is currently shifting toward understanding how genetic variation, such as single nucleotide polymorphism (SNP), leads to disease. To identify, understand, and control biological mechanisms of living organisms, the enormous amounts of accumulated sequence information must be coupled to faster, cheaper, and more powerful technologies for DNA, RNA, and protein analysis. One approach is the miniaturization of analytical methods through the application of microfluidics, which involves the manipulation of fluids in micrometer-sized channels. Advances in microfluidic chip technology are expected to play a major role in the development of cost-effective and rapid DNA analysis methods.This thesis presents microfluidic approaches for different DNA genotyping assays. The overall goal is to combine the potential of the microfluidic lab-on-a-chip concept with biochemistry to develop and improve current methods for SNP genotyping. Three genotyping assays using miniaturized microfluidic approaches are addressed.The first two assays are based on primer extension by DNA polymerase. A microfluidic device consisting of a flow-through filter chamber for handling beads with nanoliter liquid volumes was used in these studies. The first assay involved an allelespecific extension strategy. The microfluidic approach took advantage of the different reaction kinetics of matched and mismatched configurations at the 3’-ends of a primer/template complex. The second assay consisted of adapting pyrosequencing technology, a bioluminometric DNA sequencing assay based on sequencing-bysynthesis, to a microfluidic flow-through platform. Base-by-base sequencing was performed in a microfluidic device to obtain accurate SNP scoring data on nanoliter volumes. This thesis also presents the applications of monolayer of beads immobilized by microcontact printing for chip-based DNA analysis. Single-base incorporation could be detected with pyrosequencing chemistry on these monolayers.The third assay developed is based on a hybridization technology termed Dynamic Allele-Specific Hybridization (DASH). In this approach, monolayered beads containing DNA duplexes were randomly immobilized on the surface of a microheater chip. DNA melting-curve analysis was performed by dynamically heating the chip whilesimultaneously monitoring the DNA denaturation profile to determine the genotype. Multiplexing based on single-bead analysis was achieved at heating rates more than 20 times faster than conventional DASH provides.
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| 8. |
- Thrane, Kim, 1984-
(författare)
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Exploring Biological Systems using Spatial Transcriptomic Technologies
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The transcriptome and the cells’ spatial organization are important determinants for the functions of biological systems, such as a tumor, brain, or skin tissue. Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for profiling the transcriptome of individual cells. The nuanced characterization of cell types and states enabled by scRNA-seq has revolutionized our understanding of biological systems. However, these methods rely on the dissociation of tissues into single cells whereby spatial context is lost. Recent advancements have resulted in technologies that retain and associate spatial information with the gene expression of tissues, which has permitted the delineation of biological systems at an unprecedented level. The Spatial Transcriptomics (ST) technology offers transcriptome profiling across thousands of subareas of a tissue section by capturing mRNA in situ and sequencing ex situ.In Paper I, ST was used to explore heterogeneity in lymph node metastases of human cutaneous malignant melanoma. A data-driven analysis approach revealed inter- and intratumor heterogeneity in the examined tumor tissue, whereas the stromal tissue exhibited similar gene expression across patients. Paper II presents an integration of ST, scRNA-seq, and spatial protein analysis to characterize human cutaneous squamous cell carcinoma. The spatial resolution of ST is not at the single-cell level; however, this multimodal approach allowed for the identification of tumor subpopulations and revealed the niches in which they reside. In Paper III, ST and scRNA-seq data were generated to build an atlas of human skin. The combined data was used to map cell-type abundance and intercellular communications in homeostasis. Moreover, cell-of-origin analysis allowed for the identification of candidate cell types accountable for human genetic skin diseases. Paper IV introduces Spatial VDJ, a technique for spatial analysis of B and T cell antigen receptor transcripts, hence determining the position of lymphocyte clones. The spatial VDJ technique was applied to human tonsil and human breast cancer tissues, and this revealed enrichment of immunoglobulin clones in distinct spatial regions. Finally, Paper V explores an alternative protocol for ST that uses long-read sequencing to enable spatial isoform profiling in tissue sections. The protocol was applied to mouse brain and identified genes with spatially distinct alternative isoform expression. Additionally, the full-length transcript information was used to explore RNA editing events across different anatomical regions of the mouse brain.
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| 9. |
- Yang, Zhijian, et al.
(författare)
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Genetic Landscape of the ACE2 Coronavirus Receptor
- 2022
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Ingår i: Circulation. - : Ovid Technologies (Wolters Kluwer Health). - 0009-7322 .- 1524-4539. ; 30:SUPPL 1, s. 36-36
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Tidskriftsartikel (refereegranskat)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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