Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection

The study of recent natural selection in human populations has important applications to human history and medicine. Positive natural selection drives the increase in beneficial alleles and plays a role in explaining diversity across human populations. By discovering traits subject to positive selection, we can better understand the population level response to environmental pressures including infectious disease. Our study examines unusual population differentiation between three large data sets to detect natural selection. The populations examined, African Americans, Nigerians, and Gambians, are genetically close to one another (F_ST < 0.01 for all pairs), allowing us to detect selection even with moderate changes in allele frequency. We also develop a tree-based method to pinpoint the population in which selection occurred, incorporating information across populations. Our genome-wide significant results corroborate loci previously reported to be under selection in Africans including HBB and CD36. At the HLA locus on chromosome 6, results suggest the existence of multiple, independent targets of population-specific selective pressure. In addition, we report a genome-wide significant (p = 1.36 × 10⁻¹¹) signal of selection in the prostate stem cell antigen (PSCA) gene. The most significantly differentiated marker in our analysis, rs2920283, is highly differentiated in both Africa and East Asia and has prior genome-wide significant associations to bladder and gastric cancers.     

Zinc effects on NMDA receptor gating kinetics

Zinc accumulates in the synaptic vesicles of certain glutamatergic forebrain neurons and modulates neuronal excitability and synaptic plasticity by multiple poorly understood mechanisms. Zinc directly inhibits NMDA-sensitive glutamate-gated channels by two separate mechanisms: high-affinity binding to N-terminal domains of GluN2A subunits reduces channel open probability, and low-affinity voltage-dependent binding to pore-lining residues blocks the channel. Insight into the high-affinity allosteric effect has been hampered by the receptor's complex gating; multiple, sometimes coupled, modulatory mechanisms; and practical difficulties in avoiding transient block by residual Mg²⁺. To sidestep these challenges, we examined how nanomolar zinc concentrations changed the gating kinetics of individual block-resistant receptors. We found that block-insensitive channels had lower intrinsic open probabilities but retained high sensitivity to zinc inhibition. Binding of zinc to these receptors resulted in longer closures and shorter openings within bursts of activity but had no effect on interburst intervals. Based on kinetic modeling of these data, we conclude that zinc-bound receptors have higher energy barriers to opening and less stable open states. We tested this model for its ability to predict zinc-dependent changes in macroscopic responses and to infer the impact of nanomolar zinc concentrations on synaptic currents mediated by 2A-type NMDA receptors.     

The effect of coupled stochastic processes in a two-state biochemical switch

Cell signaling pathways consist of multiple connections of different types of gene, mRNA and protein networks. It is not a trivial task to follow the signals flowing through these networks. The difficulty comes from considering the entire biological structure as a single network without breaking it into connected modules. The study of these networks simplifies if the complex system is reduced to a hierarchy of interconnected modules. Out of many potential modules, a specific one, namely the Goldbeter–Koshland switch, was encountered by the authors during their study of the Mammalian Heat Shock Response Network (MHSRN) where the switch acts as a stress sensor. Usually, only the steady state behavior of the switch is studied, in which the phosphorylated protein is given as a function of the enzyme concentration. Experimental results show that the heat shock response is still present 20 h after the temperature stress had ended. Thus, it is useful to analyze the transient behavior of the switch that couples the environment to the MHSRN. A stochastic model for the switch is proposed using the Master Equation which is subsequently transformed into an equation for the factorial cumulant generating function. This generating function can be easily read from a graphical representation of the stochastic switch. The second order approximation of the equation for the factorial cumulant generating function is solved and the time dependence of the transient regime of the mean and standard deviation is readily obtained. Using the mean and standard deviation of the switch’s output as a function of the stochastic input signals that represent the environment, we classify the switches according to different criteria. The switches differ by the numerical values of the parameters that characterize the switch’s chemical reactions. The classifying criteria will distinguish the switches by the levels of the response for a given transition time and by the sensitivity of the response to the enzyme levels. It is also found that the environment can drastically change the response of the switch, which has important biological consequences.     

Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases

Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (hg2) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of hg2 from imputed SNPs (5.1× enrichment; p = 3.7 × 10⁻¹⁷) and 38% (SE = 4%) of hg2 from genotyped SNPs (1.6× enrichment, p = 1.0 × 10⁻⁴). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained <10% of hg2 despite having the highest enrichment. We replicated these findings but found no significant contribution from rare coding variants in independent schizophrenia cohorts genotyped on GWAS and exome chips. Our results highlight the value of analyzing components of heritability to unravel the functional architecture of common disease.     

Trends in atmospheric concentrations of weed pollen in the context of recent climate warming in Poznań (Western Poland)

A significant increase in summer temperatures has been observed for the period 1996–2011 in Poznań, Poland. The phenological response of four weed taxa, widely represented by anemophilous species (Artemisia spp., Rumex spp. and Poaceae and Urticaceae species) to this recent climate warming has been analysed in Poznań by examining the variations in the course of airborne pollen seasons. Pollen data were collected by 7-day Hirst-type volumetric trap. Trends in pollen seasons were determined using Mann–Kendall test and Sen’s slope estimator, whereas the relationships between meteorological and aerobiological data were established by Spearman’s rank correlation coefficient. Significant trends in pollen data were detected. The duration of pollen seasons of all analysed taxa increased (from +2.0 days/year for Urticaceae to +3.8 days/year for Rumex), which can be attributed to a delay in pollen season end dates rather than earlier start dates. In addition, the intensity of Artemisia pollen seasons significantly decreased and correlates with mean July–September daily minimum temperatures (r?=??0.644, p?Rumex pollen seasons. The results of this study show that observed shifts in weed pollen seasons in Poznań, i.e. longer duration and later end dates, might be caused by the recorded increase in summer temperature. This influence was the strongest in relation to Artemisia, which is the taxon that flowers latest in the year. The general lack of significant correlations between Rumex and Urticaceae pollen seasons and spring and/or summer temperature suggests that other factors, e.g. land use practices, could also be partially responsible for the observed shifts in pollen seasons.     

A Novel and Fast Approach for Population Structure Inference Using Kernel-PCA and Optimization

Population structure is a confounding factor in genome-wide association studies, increasing the rate of false positive associations. To correct for it, several model-based algorithms such as ADMIXTURE and STRUCTURE have been proposed. These tend to suffer from the fact that they have a considerable computational burden, limiting their applicability when used with large datasets, such as those produced by next generation sequencing techniques. To address this, nonmodel based approaches such as sparse nonnegative matrix factorization (sNMF) and EIGENSTRAT have been proposed, which scale better with larger data. Here we present a novel nonmodel-based approach, population structure inference using kernel-PCA and optimization (PSIKO), which is based on a unique combination of linear kernel-PCA and least-squares optimization and allows for the inference of admixture coefficients, principal components, and number of founder populations of a dataset. PSIKO has been compared against existing leading methods on a variety of simulation scenarios, as well as on real biological data. We found that in addition to producing results of the same quality as other tested methods, PSIKO scales extremely well with dataset size, being considerably (up to 30 times) faster for longer sequences than even state-of-the-art methods such as sNMF. PSIKO and accompanying manual are freely available at https://www.uea.ac.uk/computing/psiko.     

High-resolution vegetation history of West Africa during the last 145 ka

The essential characteristics of the vegetation dynamics of tropical Africa remain only partially known. This study assesses the succession of vegetation-types over Central Africa during the last two glacial/interglacial cycles. Analysis of core KZai 02, which contains pollen from the Zaire River watershed (latitudes 9°N–13°S), allows the investigation of long-term patterns of plant ecosystem development and their climatic causes. Core KZai 02 (18.20 m long) was recovered from 6°24.20′S/9°54.10′E in the uppermost axial edifice of the Zaire deep sea fan. The chronology of this sedimentary archive was established using nannofossils and correlations of pollen and total organic carbon signals with the nearby core GeoB1008. The pollen record indicates that: (i) glacials (MIS 6, 4, 2) are marked by the development of afromontane (Podocarpus) forest at high altitudes when central basin lowlands were occupied by Cyperaceae marshes and savannah; (ii) during interglacials (MIS 1, 5) lowland forests were developed, marked by the successive expansion of pioneer, warm-temperate, rain forests, and mangrove indicating sea-level rise; (iii) glacial-interglacial transitions (MIS 6/5, 2/1) display similar vegetation dynamics. The strong evidence of afromontane forest and the opening of the vegetation during glacials suggest a reduced latitudinal distribution of rainfall by the strengthening of the trade wind system. West African monsoon systems were enhanced during interglacials, allowing the progressive development of lowland forests. The development of rain and pioneer forests during glacial Heinrich stadials suggests an enhancement of water availability in tropical Africa associated with these high-latitude events. However, no augmentation of wind activity described by previous studies is evidenced by our pollen record. Similar vegetation successions during glacial/interglacial transitions suggest the diachronous and stepped intervention of CO₂ (emphasizing the influence of temperature on plant ecosystems) and water availability.     

Differences in the expression of chromosome 1 genes between lung telocytes and other cells: mesenchymal stem cells,fibroblasts, alveolar type II cells,airway epithelial cells and lymphocytes

Telocytes (TCs) are a unique type of interstitial cells with specific, extremely long prolongations named telopodes (Tps). Our previous study showed that TCs are distinct from fibroblasts (Fbs) and mesenchymal stem cells (MSCs) as concerns gene expression and proteomics. The present study explores patterns of mouse TC‐specific gene profiles on chromosome 1. We investigated the network of main genes and the potential functional correlations. We compared gene expression profiles of mouse pulmonary TCs, MSCs, Fbs, alveolar type II cells (ATII), airway basal cells (ABCs), proximal airway cells (PACs), CD8⁺ T cells from bronchial lymph nodes (T‐BL) and CD8⁺ T cells from lungs (T‐LL). The functional and feature networks were identified and compared by bioinformatics tools. Our data showed that on TC chromosome 1, there are about 25% up‐regulated and 70% down‐regulated genes (more than onefold) as compared with the other cells respectively. Capn2, Fhl2 and Qsox1 were over‐expressed in TCs compared to the other cells, indicating that biological functions of TCs are mainly associated with morphogenesis and local tissue homoeostasis. TCs seem to have important roles in the prevention of tissue inflammation and fibrogenesis development in lung inflammatory diseases and as modulators of immune cell response. In conclusion, TCs are distinct from the other cell types.