Promoter Nucleosome Organization Shapes the Evolution of Gene Expression

Understanding why genes evolve at different rates is fundamental to evolutionary thinking. In species of the budding yeast, the rate at which genes diverge in expression correlates with the organization of their promoter nucleosomes: genes lacking a nucleosome-free region (denoted OPN for “Occupied Proximal Nucleosomes”) vary widely between the species, while the expression of those containing NFR (denoted DPN for “Depleted Proximal Nucleosomes”) remains largely conserved. To examine if early evolutionary dynamics contributes to this difference in divergence, we artificially selected for high expression of GFP–fused proteins. Surprisingly, selection was equally successful for OPN and DPN genes, with ∼80% of genes in each group stably increasing in expression by a similar amount. Notably, the two groups adapted by distinct mechanisms: DPN–selected strains duplicated large genomic regions, while OPN–selected strains favored trans mutations not involving duplications. When selection was removed, DPN (but not OPN) genes reverted rapidly to wild-type expression levels, consistent with their lower diversity between species. Our results suggest that promoter organization constrains the early evolutionary dynamics and in this way biases the path of long-term evolution

From bit to it: How a complex metabolic network transforms information into living matter

Organisms live and die by the amount of information they acquire about their environment. The systems analysis of complex metabolic networks allows us to ask how such information translates into fitness. A metabolic network transforms nutrients into biomass. The better it uses information on available nutrient availability, the faster it will allow a cell to divide. I here use metabolic flux balance analysis to show that the accuracy I (in bits) with which a yeast cell can sense a limiting nutrient's availability relates logarithmically to fitness as indicated by biomass yield and cell division rate. For microbes like yeast, natural selection can resolve fitness differences of genetic variants smaller than 10-6, meaning that cells would need to estimate nutrient concentrations to very high accuracy (greater than 22 bits) to ensure optimal growth. I argue that such accuracies are not achievable in practice. Natural selection may thus face fundamental limitations in maximizing the information processing capacity of cells. The analysis of metabolic networks opens a door to understanding cellular biology from a quantitative, information-theoretic perspective

Critical mutation rate has an exponential dependence on population size for eukaryotic-length genomes with crossover

The critical mutation rate (CMR) determines the shift between survival-of-the-fittest and survival of individuals with greater mutational robustness (“flattest”). We identify an inverse relationship between CMR and sequence length in an in silico system with a two-peak fitness landscape; CMR decreases to no more than five orders of magnitude above estimates of eukaryotic per base mutation rate. We confirm the CMR reduces exponentially at low population sizes, irrespective of peak radius and distance, and increases with the number of genetic crossovers. We also identify an inverse relationship between CMR and the number of genes, confirming that, for a similar number of genes to that for the plant Arabidopsis thaliana (25,000), the CMR is close to its known wild-type mutation rate; mutation rates for additional organisms were also found to be within one order of magnitude of the CMR. This is the first time such a simulation model has been assigned input and produced output within range for a given biological organism. The decrease in CMR with population size previously observed is maintained; there is potential for the model to influence understanding of populations undergoing bottleneck, stress, and conservation strategy for populations near extinction

18S rRNA is a reliable normalisation gene for real time PCR based on influenza virus infected cells

Background: One requisite of quantitative reverse transcription PCR (qRT-PCR) is to normalise the data with an internal reference gene that is invariant regardless of treatment, such as virus infection. Several studies have found variability in the expression of commonly used housekeeping genes, such as beta-actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), under different experimental settings. However, ACTB and GAPDH remain widely used in the studies of host gene response to virus infections, including influenza viruses. To date no detailed study has been described that compares the suitability of commonly used housekeeping genes in influenza virus infections. The present study evaluated several commonly used housekeeping genes [ACTB, GAPDH, 18S ribosomal RNA (18S rRNA), ATP synthase, H+ transporting, mitochondrial F1 complex, beta polypeptide (ATP5B) and ATP synthase, H+ transporting, mitochondrial Fo complex, subunit C1 (subunit 9) (ATP5G1)] to identify the most stably expressed gene in human, pig, chicken and duck cells infected with a range of influenza A virus subtypes. Results: The relative expression stability of commonly used housekeeping genes were determined in primary human bronchial epithelial cells (HBECs), pig tracheal epithelial cells (PTECs), and chicken and duck primary lung-derived cells infected with five influenza A virus subtypes. Analysis of qRT-PCR data from virus and mock infected cells using NormFinder and BestKeeper software programmes found that 18S rRNA was the most stable gene in HBECs, PTECs and avian lung cells. Conclusions: Based on the presented data from cell culture models (HBECs, PTECs, chicken and duck lung cells) infected with a range of influenza viruses, we found that 18S rRNA is the most stable reference gene for normalising qRT-PCR data. Expression levels of the other housekeeping genes evaluated in this study (including ACTB and GPADH) were highly affected by influenza virus infection and hence are not reliable as reference genes for RNA normalisation

Genetic association study of adiposity and melanocortin-4 receptor (MC4R) common variants: Replication and functional characterization of non-coding regions

Common genetic variants 3′ of MC4R within two large linkage disequilibrium (LD) blocks spanning 288 kb have been associated with common and rare forms of obesity. This large association region has not been refined and the relevant DNA segments within the association region have not been identified. In this study, we investigated whether common variants in the MC4R gene region were associated with adiposity-related traits in a biracial population-based study. Single nucleotide polymorphisms (SNPs) in the MC4R region were genotyped with a custom array and a genome-wide array and associations between SNPs and five adiposity-related traits were determined using race-stratified linear regression. Previously reported associations between lower BMI and the minor alleles of rs2229616/Val103Ile and rs52820871/Ile251Leu were replicated in white female participants. Among white participants, rs11152221 in a proximal 3′ LD block (closer to MC4R) was significantly associated with multiple adiposity traits, but SNPs in a distal 309 LD block (farther from MC4R ) were not. In a case-control study of severe obesity, rs11152221 was significantly associated. The association results directed our follow-up studies to the proximal LD block downstream of MC4R. By considering nucleotide conservation, the significance of association, and proximity to the MC4R gene, we identified a candidate MC4R regulatory region. This candidate region was sequenced in 20 individuals from a study of severe obesity in an attempt to identify additional variants, and the candidate region was tested for enhancer activity using in vivo enhancer assays in zebrafish and mice. Novel variants were not identified by sequencing and the candidate region did not drive reporter gene expression in zebrafish or mice. The identification of a putative insulator in this region could help to explain the challenges faced in this study and others to link SNPs associated with adiposity to altered MC4R expression. © 2014 Evans et al

Highly pathogenic avian influenza virus infection in chickens but not ducks is associated with elevated host immune and pro-inflammatory responses

Highly pathogenic avian influenza (HPAI) H5N1 viruses cause severe infection in chickens at near complete mortality, but corresponding infection in ducks is typically mild or asymptomatic. To understand the underlying molecular differences in host response, primary chicken and duck lung cells, infected with two HPAI H5N1 viruses and a low pathogenicity avian influenza (LPAI) H2N3 virus, were subjected to RNA expression profiling. Chicken cells but not duck cells showed highly elevated immune and pro-inflammatory responses following HPAI virus infection. HPAI H5N1 virus challenge studies in chickens and ducks corroborated the in vitro findings. To try to determine the underlying mechanisms, we investigated the role of signal transducer and activator of transcription-3 (STAT-3) in mediating pro-inflammatory response to HPAIV infection in chicken and duck cells. We found that STAT-3 expression was down-regulated in chickens but was up-regulated or unaffected in ducks in vitro and in vivo following H5N1 virus infection. Low basal STAT-3 expression in chicken cells was completely inhibited by H5N1 virus infection. By contrast, constitutively active STAT-3 detected in duck cells was unaffected by H5N1 virus infection. Transient constitutively-active STAT-3 transfection in chicken cells significantly reduced pro-inflammatory response to H5N1 virus infection; on the other hand, chemical inhibition of STAT-3 activation in duck cells increased pro-inflammatory gene expression following H5N1 virus infection. Collectively, we propose that elevated pro-inflammatory response in chickens is a major pathogenicity factor of HPAI H5N1 virus infection, mediated in part by the inhibition of STAT-3

Managed Metapopulations: Do Salmon Hatchery ‘Sources’ Lead to In-River ‘Sinks’ in Conservation?

Maintaining viable populations of salmon in the wild is a primary goal for many conservation and recovery programs. The frequency and extent of connectivity among natal sources defines the demographic and genetic boundaries of a population. Yet, the role that immigration of hatchery-produced adults may play in altering population dynamics and fitness of natural populations remains largely unquantified. Quantifying, whether natural populations are self-sustaining, functions as sources (population growth rate in the absence of dispersal, λ>1), or as sinks (λ<1) can be obscured by an inability to identify immigrants. In this study we use a new isotopic approach to demonstrate that a natural spawning population of Chinook salmon, (Oncorhynchus tshawytscha) considered relatively healthy, represents a sink population when the contribution of hatchery immigrants is taken into consideration. We retrieved sulfur isotopes (34S/32S, referred to as δ34S) in adult Chinook salmon otoliths (ear bones) that were deposited during their early life history as juveniles to determine whether individuals were produced in hatcheries or naturally in rivers. Our results show that only 10.3% (CI = 5.5 to 18.1%) of adults spawning in the river had otolith δ34S values less than 8.5‰, which is characteristic of naturally produced salmon. When considering the total return to the watershed (total fish in river and hatchery), we estimate that 90.7 to 99.3% (CI) of returning adults were produced in a hatchery (best estimate = 95.9%). When population growth rate of the natural population was modeled to account for the contribution of previously unidentified hatchery immigrants, we found that hatchery-produced fish caused the false appearance of positive population growth. These findings highlight the potential dangers in ignoring source-sink dynamics in recovering natural populations, and question the extent to which declines in natural salmon populations are undetected by monitoring programs

Stratigraphic correlation and paleoenvironmental analysis of the hydrocarbon-bearing Early Miocene Euphrates and Jeribe formations in the Zagros folded-thrust belt

The Lower Miocene Euphrates and Jeribe formations are considered as the main targets of the Tertiary petroleum system in the western part of the Zagros Basin. The formations consist of carbonates with some evaporate intercalations of the Dhiban Formation. This study utilized data from a field investigation including newly described outcrop sections and newly discovered productive oil fields within the Kirkuk embayment zone of the Zagros fold and thrust belt such as Sarqala and Kurdamir wells. This work is the first to show a stratigraphic correlation and paleoenvironmental interpretation by investigating both well data and new outcrop data. Three depositional environments were identified, (1) an inner and outer ramp belts environment, (2) shoal environment, and (3) restricted lagoon environment. Within these 3 environments, 12 microfacies were identified, based on the distribution of fauna mainly benthonic foraminifera, rock textures, and sedimentary structures. The inferred shallow water depths and variable salinities in both the Euphrates Formation and Jeribe Formation carbonates are consistent with deposition on the inner ramp (restricted lagoon and shoal) environments. Those found in the Euphrates Formation constrained the depositional environment to the restricted lagoon and shoal environment, while the microfacies in the Jeribe Formation provided evidence for an inner ramp and middle to outer ramp belt environments. This study represents the first detailed research that focuses on the stratigraphic correlation and changes in carbonate facies with the main aim to provide a wider understanding of stratigraphy of these carbonate reservoirs throughout the northern part of Iraq

Lawson criterion for ignition exceeded in an inertial fusion experiment

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion

Statistical and integrative system-level analysis of DNA methylation data

Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic mark that can be measured reliably and genome-wide in large numbers of samples. This Review discusses some of the key statistical challenges and algorithms associated with drawing inferences from DNA methylation data, including cell-type heterogeneity, feature selection, reverse causation and system-level analyses that require integration with other data types such as gene expression, genotype, transcription factor binding and other epigenetic information