| 1. |
- Enroth, Stefan, et al.
(författare)
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Nucleosome regulatory dynamics in response to TGF beta
- 2014
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 42:11, s. 6921-6934
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Tidskriftsartikel (refereegranskat)abstract
- Nucleosomes play important roles in a cell beyond their basal functionality in chromatin compaction. Their placement affects all steps in transcriptional regulation, from transcription factor (TF) binding to messenger ribonucleic acid (mRNA) synthesis. Careful profiling of their locations and dynamics in response to stimuli is important to further our understanding of transcriptional regulation by the state of chromatin. We measured nucleosome occupancy in human hepatic cells before and after treatment with transforming growth factor beta 1 (TGFβ1), using massively parallel sequencing. With a newly developed method, SuMMIt, for precise positioning of nucleosomes we inferred dynamics of the nucleosomal landscape. Distinct nucleosome positioning has previously been described at transcription start site and flanking TF binding sites. We found that the average pattern is present at very few sites and, in case of TF binding, the double peak surrounding the sites is just an artifact of averaging over many loci. We systematically searched for depleted nucleosomes in stimulated cells compared to unstimulated cells and identified 24 318 loci. Depending on genomic annotation, 44-78% of them were over-represented in binding motifs for TFs. Changes in binding affinity were verified for HNF4α by qPCR. Strikingly many of these loci were associated with expression changes, as measured by RNA sequencing.
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| 2. |
- Enroth, Stefan, et al.
(författare)
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Strong effects of genetic and lifestyle factors on biomarker variation and use of personalized cutoffs
- 2014
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 5, s. 4684-
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Tidskriftsartikel (refereegranskat)abstract
- Ideal biomarkers used for disease diagnosis should display deviating levels in affected individuals only and be robust to factors unrelated to the disease. Here we show the impact of genetic, clinical and lifestyle factors on circulating levels of 92 protein biomarkers for cancer and inflammation, using a population-based cohort of 1,005 individuals. For 75% of the biomarkers, the levels are significantly heritable and genome-wide association studies identifies 16 novel loci and replicate 2 previously known loci with strong effects on one or several of the biomarkers with P-values down to 4.4 × 10−58. Integrative analysis attributes as much as 56.3% of the observed variance to non-disease factors. We propose that information on the biomarker-specific profile of major genetic, clinical and lifestyle factors should be used to establish personalized clinical cutoffs, and that this would increase the sensitivity of using biomarkers for prediction of clinical end points.
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| 3. |
- Loth, Daan W, et al.
(författare)
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Genome-wide association analysis identifies six new loci associated with forced vital capacity
- 2014
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 46, s. 669-677
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Tidskriftsartikel (refereegranskat)abstract
- Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P < 5 × 10(-8)) with FVC in or near EFEMP1, BMP6, MIR129-2-HSD17B12, PRDM11, WWOX and KCNJ2. Two loci previously associated with spirometric measures (GSTCD and PTCH1) were related to FVC. Newly implicated regions were followed up in samples from African-American, Korean, Chinese and Hispanic individuals. We detected transcripts for all six newly implicated genes in human lung tissue. The new loci may inform mechanisms involved in lung development and the pathogenesis of restrictive lung disease.
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| 4. |
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| 5. |
- Ameur, Adam, et al.
(författare)
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CanvasDB : a local database infrastructure for analysis of targeted- and whole genome re-sequencing projects
- 2014
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Ingår i: Database. - : Oxford University Press (OUP). - 1758-0463. ; , s. bau098-
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Tidskriftsartikel (refereegranskat)abstract
- CanvasDB is an infrastructure for management and analysis of genetic variants from massively parallel sequencing (MPS) projects. The system stores SNP and indel calls in a local database, designed to handle very large datasets, to allow for rapid analysis using simple commands in R. Functional annotations are included in the system, making it suitable for direct identification of disease-causing mutations in human exome-(WES) or whole-genome sequencing (WGS) projects. The system has a built-in filtering function implemented to simultaneously take into account variant calls from all individual samples. This enables advanced comparative analysis of variant distribution between groups of samples, including detection of candidate causative mutations within family structures and genome-wide association by sequencing. In most cases, these analyses are executed within just a matter of seconds, even when there are several hundreds of samples and millions of variants in the database. We demonstrate the scalability of canvasDB by importing the individual variant calls from all 1092 individuals present in the 1000 Genomes Project into the system, over 4.4 billion SNPs and indels in total. Our results show that canvasDB makes it possible to perform advanced analyses of large-scale WGS projects on a local server.
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| 6. |
- Ameur, Adam, et al.
(författare)
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Genetic Adaptation of Fatty-Acid Metabolism : A Human-Specific Haplotype Increasing the Biosynthesis of Long-Chain Omega-3 and Omega-6 Fatty Acids
- 2012
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 90:5, s. 809-820
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Tidskriftsartikel (refereegranskat)abstract
- Omega-3 and omega-6 long-chain polyunsaturated fatty acids (LC-PUFAs) are essential for the development and function of the human brain. They can be obtained directly from food, e.g., fish, or synthesized from precursor molecules found in vegetable oils. To determine the importance of genetic variability to fatty-acid biosynthesis, we studied FADS1 and FADS2, which encode rate-limiting enzymes for fatty-acid conversion. We performed genome-wide genotyping (n = 5,652 individuals) and targeted resequencing (n = 960 individuals) of the FADS region in five European population cohorts. We also analyzed available genomic data from human populations, archaic hominins, and more distant primates. Our results show that present-day humans have two common FADS haplotypes-defined by 28 closely linked SNPs across 38.9 kb-that differ dramatically in their ability to generate LC-PUFAs. No independent effects on FADS activity were seen for rare SNPs detected by targeted resequencing. The more efficient, evolutionarily derived haplotype appeared after the lineage split leading to modern humans and Neanderthals and shows evidence of positive selection. This human-specific haplotype increases the efficiency of synthesizing essential long-chain fatty acids from precursors and thereby might have provided an advantage in environments with limited access to dietary LC-PUFAs. In the modern world, this haplotype has been associated with lifestyle-related diseases, such as coronary artery disease.
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| 7. |
- Bornelöv, Susanne, et al.
(författare)
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Visualization of Rules in Rule-Based Classifiers
- 2012
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Ingår i: INTELLIGENT DECISION TECHNOLOGIES (IDT'2012), VOL 1. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642299773 ; , s. 329-338
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Konferensbidrag (refereegranskat)abstract
- Interpretation and visualization of the classification models are important parts of machine learning. Rule-based classifiers often contain too many rules to be easily interpreted by humans, and methods for post-classification analysis of the rules are needed. Here we present a strategy for circular visualization of sets of classification rules. The Circos software was used to generate graphs showing all pairs of conditions that were present in the rules as edges inside a circle. We showed using simulated data that all two-way interactions in the data were found by the classifier and displayed in the graph, although the single attributes were constructed to have no correlation to the decision class. For all examples we used rules trained using the rough set theory, but the visualization would by applicable to any sort of classification rules. This method for rule visualization may be useful for applications where interaction terms are expected, and the size of the model limits the interpretability.
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| 8. |
- Chen, Dan, et al.
(författare)
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Genome-wide Association Study of Susceptibility Loci for Cervical Cancer
- 2013
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 105:9, s. 624-633
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Tidskriftsartikel (refereegranskat)abstract
- Background Cervical carcinoma has a heritable genetic component, but the genetic basis of cervical cancer is still not well understood. Methods We performed a genome-wide association study of 731 422 single nucleotide polymorphisms (SNPs) in 1075 cervical cancer case subjects and 4014 control subjects and replicated it in 1140 case subjects and 1058 control subjects. The association between top SNPs and cervical cancer was estimated by odds ratios (ORs) and 95% confidence intervals (CIs) with unconditional logistic regression. All statistical tests were two-sided. Results Three independent loci in the major histocompatibility complex (MHC) region at 6p21.3 were associated with cervical cancer: the first is adjacent to the MHC class I polypeptide-related sequence A gene (MICA) (rs2516448; OR = 1.42, 95% CI = 1.31 to 1.54; P = 1.6 x 10(-18)); the second is between HLA-DRB1 and HLA-DQA1 (rs9272143; OR = 0.67, 95% CI = 0.62 to 0.72; P = 9.3 x 10(-24)); and the third is at HLA-DPB2 (rs3117027; OR=1.25, 95% CI = 1.15 to 1.35; P = 4.9 x 10(-8)). We also confirmed previously reported associations of B*0702 and DRB1*1501-DQB1*0602 with susceptibility to and DRB1*1301-DQA1*0103-DQB1*0603 with protection against cervical cancer. The three new loci are statistically independent of these specific human leukocyte antigen alleles/haplotypes. MICA encodes a membrane-bound protein that acts as a ligand for NKG2D to activate antitumor effects. The risk allele of rs2516448 is in perfect linkage disequilibrium with a frameshift mutation (A5.1) of MICA, which results in a truncated protein. Functional analysis shows that women carrying this mutation have lower levels of membrane-bound MICA. Conclusions Three novel loci in the MHC may affect susceptibility to cervical cancer in situ, including the MICA-A5.1 allele that may cause impaired immune activation and increased risk of tumor development.
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| 9. |
- Chen, Dan, et al.
(författare)
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Pathway analysis of cervical cancer genome-wide association study highlights the MHC region and pathways involved in response to infection
- 2014
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:22, s. 6047-6060
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Tidskriftsartikel (refereegranskat)abstract
- Cervical cancer is caused by infection with human papillomavirus (HPV). A genome-wide association study (GWAS) has identified several susceptibility loci for cervical cancer, but they explain only a small fraction of cervical cancer heritability. Other variants with weaker effect may be missed due to the stringent significance threshold. To identify important pathways in cervical carcinogenesis, we performed a two-stage pathway analysis in two independent GWASs in the Swedish population, using the single-nucleotide polymorphism (SNP) ratio test. The 565 predefined pathways from Kyoto Encyclopedia of Genes and Genomes and BioCarta databases were systematically evaluated in the discovery stage (1034 cases and 3948 controls with 632 668 SNPs) and the suggestive pathways were further validated in the replication stage (616 cases and 506 controls with 341 358 SNPs). We found 12 pathways that were significant in both stages, and these were further validated using set-based analysis. For 10 of these pathways, the effect was mainly due to genetic variation within the major histocompatibility complex (MHC) region. In addition, we identified a set of novel candidate genes outside the MHC region in the pathways denoted ‘Staphylococcus aureus infection’ and ‘herpes simplex infection’ that influenced susceptibility to cervical cancer (empirical P = 4.99 × 10−5 and 4.99 × 10−5 in the discovery study; empirical P = 8.98 × 10−5 and 0.009 in the replication study, respectively). Staphylococcus aureus infection may evoke an inflammatory response that inadvertently enhances malignant progression caused by HPV infection, and Herpes simplex virus-2 infection may act in conjunction with HPV infection to increase the risk of cervical carcinoma development. These findings provide new insights into the etiology of cervical cancer.
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| 10. |
- Enroth, Stefan, et al.
(författare)
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A strand specific high resolution normalization method for chip-sequencing data employing multiple experimental control measurements
- 2012
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Ingår i: Algorithms for Molecular Biology. - : Springer Science and Business Media LLC. - 1748-7188. ; 7, s. 2-
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Tidskriftsartikel (refereegranskat)abstract
- Background: High-throughput sequencing is becoming the standard tool for investigating protein-DNA interactions or epigenetic modifications. However, the data generated will always contain noise due to e. g. repetitive regions or non-specific antibody interactions. The noise will appear in the form of a background distribution of reads that must be taken into account in the downstream analysis, for example when detecting enriched regions (peak-calling). Several reported peak-callers can take experimental measurements of background tag distribution into account when analysing a data set. Unfortunately, the background is only used to adjust peak calling and not as a preprocessing step that aims at discerning the signal from the background noise. A normalization procedure that extracts the signal of interest would be of universal use when investigating genomic patterns.Results: We formulated such a normalization method based on linear regression and made a proof-of-concept implementation in R and C++. It was tested on simulated as well as on publicly available ChIP-seq data on binding sites for two transcription factors, MAX and FOXA1 and two control samples, Input and IgG. We applied three different peak-callers to (i) raw (un-normalized) data using statistical background models and (ii) raw data with control samples as background and (iii) normalized data without additional control samples as background. The fraction of called regions containing the expected transcription factor binding motif was largest for the normalized data and evaluation with qPCR data for FOXA1 suggested higher sensitivity and specificity using normalized data over raw data with experimental background.Conclusions: The proposed method can handle several control samples allowing for correction of multiple sources of bias simultaneously. Our evaluation on both synthetic and experimental data suggests that the method is successful in removing background noise.
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