Base pair interactions and hybridization isotherms of matched and mismatched oligonucleotide probes on microarrays

The lack of specificity in microarray experiments due to non-specific hybridization raises a serious problem for the analysis of microarray data because the residual chemical background intensity is not related to the expression degree of the gene of interest. We analyzed the concentration dependence of the signal intensity of perfect match (PM) and mismatch (MM) probes in terms using a microscopic binding model using a combination of mean hybridization isotherms and single base related affinity terms. The signal intensities of the PM and MM probes and their difference are assessed with regard to their sensitivity, specificity and resolution for gene expression measures. The presented theory implies the refinement of existing algorithms of probe level analysis to correct microarray data for non-specific background intensities.Comment: 32 pages, 12 figures, 3 table

The Human Blood Transcriptome in a Large Population Cohort and Its Relation to Aging and Health

Background: The blood transcriptome is expected to provide a detailed picture of an organism’s physiological state with potential outcomes for applications in medical diagnostics and molecular and epidemiological research.We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration. Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features. Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes. Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications

Investigating the retention of intermediate-mass black holes in star clusters using N-body simulations

Contrary to supermassive and stellar-mass black holes (SBHs), the existence of intermediate-mass black holes (IMBHs) with masses ranging between 10^{2-5} Msun has not yet been confirmed. The main problem in the detection is that the innermost stellar kinematics of globular clusters (GCs) or small galaxies, the possible natural loci to IMBHs, are very difficult to resolve. However, if IMBHs reside in the centre of GCs, a possibility is that they interact dynamically with their environment. A binary formed with the IMBH and a compact object of the GC would naturally lead to a prominent source of gravitational radiation, detectable with future observatories. We use N-body simulations to study the evolution of GCs containing an IMBH and calculate the gravitational radiation emitted from dynamically formed IMBH-SBH binaries and the possibility that the IMBH escapes the GC after an IMBH-SBH merger. We run for the first time direct-summation integrations of GCs with an IMBH including the dynamical evolution of the IMBH with the stellar system and relativistic effects, such as energy loss in gravitational waves (GWs) and periapsis shift, and gravitational recoil. We find in one of our models an intermediate mass-ratio inspiral (IMRI), which leads to a merger with a recoiling velocity higher than the escape velocity of the GC. The GWs emitted fall in the range of frequencies that a LISA-like observatory could detect, like the European eLISA or in mission options considered in the recent preliminary mission study conducted in China. The merger has an impact on the global dynamics of the cluster, as an important heating source is removed when the merged system leaves the GC. The detection of one IMRI would constitute a test of GR, as well as an irrefutable proof of the existence of IMBHs.Comment: Accepted for publication by A&A, minor modification

Cell division and death inhibit glassy behaviour of confluent tissues

We investigate the effects of cell division and apopotosis on collective dynamics in two-dimensional epithelial tissues. Our model includes three key ingredients observed across many epithelia, namely cell-cell adhesion, cell death and a cell division process that depends on the surrounding environment. We show a rich non-equilibrium phase diagram depending on the ratio of cell death to cell division and on the adhesion strength. For large apopotosis rates, cells die out and the tissue disintegrates. As the death rate decreases, however, we show, consecutively, the existence of a gas-like phase, a gel-like phase, and a dense confluent (tissue) phase. Most striking is the observation that the tissue is self-melting through its own internal activity, ruling out the existence of any glassy phase.Comment: 9 pages, 10 figure

Increased risk of severe clinical course of COVID-19 in carriers of HLA-C*04:01

Background: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there has been increasing urgency to identify pathophysiological characteristics leading to severe clinical course in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human leukocyte antigen alleles (HLA) have been suggested as potential genetic host factors that affect individual immune response to SARS-CoV-2. We sought to evaluate this hypothesis by conducting a multicenter study using HLA sequencing. Methods: We analyzed the association between COVID-19 severity and HLAs in 435 individuals from Germany (n = 135), Spain (n = 133), Switzerland (n = 20) and the United States (n = 147), who had been enrolled from March 2020 to August 2020. This study included patients older than 18 years, diagnosed with COVID19 and representing the full spectrum of the disease. Finally, we tested our results by meta-analysing data from prior genome-wide association studies (GWAS). Findings: We describe a potential association of HLA-C*04:01 with severe clinical course of COVID-19. Carriers of HLA-C*04:01 had twice the risk of intubation when infected with SARS-CoV-2 (risk ratio 1.5 [95% CI 1.1-2.1], odds ratio 3.5 [95% CI 1.9-6.6], adjusted p-value = 0.0074). These findings are based on data from four countries and corroborated by independent results from GWAS. Our findings are biologically plausible, as HLA-C*04:01 has fewer predicted bindings sites for relevant SARS-CoV-2 peptides compared to other HLA alleles. Interpretation: HLA-C*04:01 carrier state is associated with severe clinical course in SARS-CoV-2. Our findings suggest that HLA class I alleles have a relevant role in immune defense against SARS-CoV-2. Funding: Funded by Roche Sequencing Solutions, Inc