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Sökning: WFRF:(Liljedahl Ulrika)

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1.
  • Almlöf, Jonas Carlsson, et al. (författare)
  • Powerful Identification of Cis-regulatory SNPs in Human Primary Monocytes Using Allele-Specific Gene Expression
  • 2012
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 7:12, s. e52260-
  • Tidskriftsartikel (refereegranskat)abstract
    • A large number of genome-wide association studies have been performed during the past five years to identify associations between SNPs and human complex diseases and traits. The assignment of a functional role for the identified disease-associated SNP is not straight-forward. Genome-wide expression quantitative trait locus (eQTL) analysis is frequently used as the initial step to define a function while allele-specific gene expression (ASE) analysis has not yet gained a wide-spread use in disease mapping studies. We compared the power to identify cis-acting regulatory SNPs (cis-rSNPs) by genome-wide allele-specific gene expression (ASE) analysis with that of traditional expression quantitative trait locus (eQTL) mapping. Our study included 395 healthy blood donors for whom global gene expression profiles in circulating monocytes were determined by Illumina BeadArrays. ASE was assessed in a subset of these monocytes from 188 donors by quantitative genotyping of mRNA using a genome-wide panel of SNP markers. The performance of the two methods for detecting cis-rSNPs was evaluated by comparing associations between SNP genotypes and gene expression levels in sample sets of varying size. We found that up to 8-fold more samples are required for eQTL mapping to reach the same statistical power as that obtained by ASE analysis for the same rSNPs. The performance of ASE is insensitive to SNPs with low minor allele frequencies and detects a larger number of significantly associated rSNPs using the same sample size as eQTL mapping. An unequivocal conclusion from our comparison is that ASE analysis is more sensitive for detecting cis-rSNPs than standard eQTL mapping. Our study shows the potential of ASE mapping in tissue samples and primary cells which are difficult to obtain in large numbers.
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2.
  • Ameur, Adam, et al. (författare)
  • SweGen : a whole-genome data resource of genetic variability in a cross-section of the Swedish population
  • 2017
  • Ingår i: European Journal of Human Genetics. - : NATURE PUBLISHING GROUP. - 1018-4813 .- 1476-5438. ; 25:11, s. 1253-1260
  • 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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5.
  • Fang, Li Tai, et al. (författare)
  • Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing
  • 2021
  • Ingår i: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 39:9, s. 1151-1160
  • Tidskriftsartikel (refereegranskat)abstract
    • Tumor-normal paired DNA samples from a breast cancer cell line and a matched lymphoblastoid cell line enable calibration of clinical sequencing pipelines and benchmarking 'tumor-only' or 'matched tumor-normal' analyses. The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses.
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6.
  • Foox, Jonathan, et al. (författare)
  • The SEQC2 epigenomics quality control (EpiQC) study
  • 2021
  • Ingår i: Genome Biology. - : BioMed Central (BMC). - 1465-6906 .- 1474-760X. ; 22:1
  • Tidskriftsartikel (refereegranskat)abstract
    • BackgroundCytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA’s Epigenomics Quality Control Group.ResultsEach sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms.ConclusionsThe data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.
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7.
  • Fredriksson, Mona, et al. (författare)
  • Assessing hematopoietic chimerism after stem cell transplantation by multiplexed SNP genotyping using microarrays and quantitative analysis of SNP alleles
  • 2004
  • Ingår i: Leukemia. - : Springer Science and Business Media LLC. - 0887-6924 .- 1476-5551. ; 18:2, s. 255-266
  • Tidskriftsartikel (refereegranskat)abstract
    • Single-nucleotide polymorphisms (SNPs) have the potential to be particularly useful as markers for monitoring of chimerism after stem cell transplantation (SCT) because they can be analyzed by accurate and robust methods. We used a two-phased minisequencing strategy for monitoring chimerism after SCT. First, informative SNPs with alleles differing between donor and recipient were identified using a multiplex microarray-based minisequencing system screening 51 SNPs to ensure that multiple informative SNPs were detected in each donor-recipient pair. Secondly, the development of chimerism was followed up after SCT by sensitive, quantitative analysis of individual informative SNPs by applying the minisequencing method in a microtiter plate format. Using this panel of SNPs, we identified multiple informative SNPs in nine unrelated and in 16 related donor-recipient pairs. Samples from nine of the donor-recipient pairs taken at time points ranging from 1 month to 8 years after transplantation were available for analysis. In these samples, we monitored the allelic ratios of two or three informative SNPs in individual minisequencing reactions. The results agreed well with the data obtained by microsatellite analysis. Thus, we conclude that the two-phased minisequencing strategy is a useful approach in the following up of patients after SCT.
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8.
  • Gunnarsson, Rebeqa, et al. (författare)
  • Screening for copy-number alterations and loss of heterozygosity in chronic lymphocytic leukemia-A comparative study of four differently designed, high resolution microarray platforms
  • 2008
  • Ingår i: Genes, Chromosomes and Cancer. - : Wiley. - 1045-2257 .- 1098-2264. ; 93, s. 0536-0536
  • Tidskriftsartikel (refereegranskat)abstract
    • Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis using dChip revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested.
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9.
  • Guy, Lionel, et al. (författare)
  • Adaptive Mutations and Replacements of Virulence Traits in the Escherichia coli O104:H4 Outbreak Population
  • 2013
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:5, s. e63027-
  • Tidskriftsartikel (refereegranskat)abstract
    • The sequencing of highly virulent Escherichia coli O104:H4 strains isolated during the outbreak of bloody diarrhea and hemolytic uremic syndrome in Europe in 2011 revealed a genome that contained a Shiga toxin encoding prophage and a plasmid encoding enteroaggregative fimbriae. Here, we present the draft genome sequence of a strain isolated in Sweden from a patient who had travelled to Tunisia in 2010 (E112/10) and was found to differ from the outbreak strains by only 38 SNPs in non-repetitive regions, 16 of which were mapped to the branch to the outbreak strain. We identified putatively adaptive mutations in genes for transporters, outer surface proteins and enzymes involved in the metabolism of carbohydrates. A comparative analysis with other historical strains showed that E112/10 contained Shiga toxin prophage genes of the same genotype as the outbreak strain, while these genes have been replaced by a different genotype in two otherwise very closely related strains isolated in the Republic of Georgia in 2009. We also present the genome sequences of two enteroaggregative E. coli strains affiliated with phylogroup A (C43/90 and C48/93) that contain the agg genes for the AAF/I-type fimbriae characteristic of the outbreak population. Interestingly, C43/90 also contained a tet/mer antibiotic resistance island that was nearly identical in sequence to that of the outbreak strain, while the corresponding island in the Georgian strains was most similar to E. coli strains of other serotypes. We conclude that the pan-genome of the outbreak population is shared with strains of the A phylogroup and that its evolutionary history is littered with gene replacement events, including most recently independent acquisitions of antibiotic resistance genes in the outbreak strains and its nearest neighbors. The results are summarized in a refined evolutionary model for the emergence of the O104:H4 outbreak population.
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10.
  • Gyllensten, Ulf B., et al. (författare)
  • Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer
  • 2022
  • Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:7
  • 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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