A Model-Based Analysis of GC-Biased Gene Conversion in the Human and Chimpanzee Genomes

GC-biased gene conversion (gBGC) is a recombination-associated process that favors the fixation of G/C alleles over A/T alleles. In mammals, gBGC is hypothesized to contribute to variation in GC content, rapidly evolving sequences, and the fixation of deleterious mutations, but its prevalence and general functional consequences remain poorly understood. gBGC is difficult to incorporate into models of molecular evolution and so far has primarily been studied using summary statistics from genomic comparisons. Here, we introduce a new probabilistic model that captures the joint effects of natural selection and gBGC on nucleotide substitution patterns, while allowing for correlations along the genome in these effects. We implemented our model in a computer program, called phastBias, that can accurately detect gBGC tracts about 1 kilobase or longer in simulated sequence alignments. When applied to real primate genome sequences, phastBias predicts gBGC tracts that cover roughly 0.3% of the human and chimpanzee genomes and account for 1.2% of human-chimpanzee nucleotide differences. These tracts fall in clusters, particularly in subtelomeric regions; they are enriched for recombination hotspots and fast-evolving sequences; and they display an ongoing fixation preference for G and C alleles. They are also significantly enriched for disease-associated polymorphisms, suggesting that they contribute to the fixation of deleterious alleles. The gBGC tracts provide a unique window into historical recombination processes along the human and chimpanzee lineages. They supply additional evidence of long-term conservation of megabase-scale recombination rates accompanied by rapid turnover of hotspots. Together, these findings shed new light on the evolutionary, functional, and disease implications of gBGC. The phastBias program and our predicted tracts are freely available. © 2013 Capra et al

Rhizosphere engineering: Innovative improvement of root environment

© 2017 Elsevier B.V.The ability of roots to extract water and nutrients from soil depends on the biophysical properties of the rhizosphere, which are strongly influenced by mucilage secretion. The aim of this study was to introduce the concept of rhizoligands to engineer the biophysical properties of the rhizosphere. A rhizoligand is defined as an additive that increases the wettability of the rhizosphere and links the mucilage network to main intimate contact with the root surface. We hypothesize that rhizoligands: i) facilitate the rewetting of the rhizosphere during repeated drying and wetting cycles; ii) enhance rhizosheath formation; iii) increase enzyme activities in the rhizosphere; and iv) increase plant biomass. A commercial surfactant was selected as the prototype rhizoligand to test the effect on the rhizosphere biophysical properties of white lupin grown in quartz sand and subjected to six drying-rewetting cycles. Half of the plants were irrigated with water and the other half with the rhizoligand solution. When plants were 50 days old, we measured: i) soil water content; ii) rhizosheath mass; iii) activity of selected enzymes; iv) carbon content in the rhizosphere; and v) plant biomass. Rhizoligand increased rewetting rate of the rhizosphere after drying and subsequent rewetting, resulting in a greater soil water content. Rhizosheath formation was improved in plants irrigated with rhizoligand and sand particles attached to the roots increased by 1.64 times compared to plants irrigated with water. Activity of the enzymes chitinase, sulfatase, and β-glucosidase were 4, 7.9, and 1.5 times greater in the rhizosphere of plants irrigated with rhizoligand than in the rhizosphere of plants irrigated with water. Plant biomass was 1.2 fold greater in samples irrigated with rhizoligand solution than in samples irrigated with water. We conclude that application of rhizoligand improves plant performance by influencing the water dynamics in the rhizosphere and the plant, increasing the mechanical stability of the rhizosheaths and increasing the enzyme activities in the rhizosphere. Such effects are probably triggered by the interaction between mucilage and the applied rhizoligand, which reduces mucilage swelling (possibly by cross-linking mucilage polymers) and thus by increasing its viscosity keeps the mucilage close to the root surface. We propose the rhizoligand concept as a strategy to engineer the rhizosphere properties and to improve plant tolerance to water shortage

The Role of GC-Biased Gene Conversion in Shaping the Fastest Evolving Regions of the Human Genome

GC-biased gene conversion (gBGC) is a recombination-associated evolutionary process that accelerates the fixation of guanine or cytosine alleles, regardless of their effects on fitness. gBGC can increase the overall rate of substitutions, a hallmark of positive selection. Many fast-evolving genes and noncoding sequences in the human genome have GC-biased substitution patterns, suggesting that gBGC—in contrast to adaptive processes—may have driven the human changes in these sequences. To investigate this hypothesis, we developed a substitution model for DNA sequence evolution that quantifies the nonlinear interacting effects of selection and gBGC on substitution rates and patterns. Based on this model, we used a series of lineage-specific likelihood ratio tests to evaluate sequence alignments for evidence of changes in mode of selection, action of gBGC, or both. With a false positive rate of less than 5% for individual tests, we found that the majority (76%) of previously identified human accelerated regions are best explained without gBGC, whereas a substantial minority (19%) are best explained by the action of gBGC alone. Further, more than half (55%) have substitution rates that significantly exceed local estimates of the neutral rate, suggesting that these regions may have been shaped by positive selection rather than by relaxation of constraint. By distinguishing the effects of gBGC, relaxation of constraint, and positive selection we provide an integrated analysis of the evolutionary forces that shaped the fastest evolving regions of the human genome, which facilitates the design of targeted functional studies of adaptation in humans

Radiocarbon Analyses Quantify Peat Carbon Losses With Increasing Temperature in a Whole Ecosystem Warming Experiment

Climate warming is expected to accelerate peatland degradation and release rates of carbon dioxide (CO2) and methane (CH4). Spruce and Peatlands Responses Under Changing Environments is an ecosystem-scale climate manipulation experiment, designed to examine peatland ecosystem response to climate forcings. We examined whether heating up to +9 °C to 3 m-deep in a peat bog over a 7-year period led to higher C turnover and CO2 and CH4 emissions, by measuring 14C of solid peat, dissolved organic carbon (DOC), CH4, and dissolved CO2 (DIC). DOC, a major substrate for heterotrophic respiration, increased significantly with warming. There was no 7-year trend in the DI14 C of the ambient plots which remained similar to their DO14 C. At +6.75 °C and +9 °C, the 14C of DIC, a product of microbial respiration, initially resembled ambient plots but became more depleted over 7 years of warming. We attributed the shifts in DI14 C to the increasing importance of solid phase peat as a substrate for microbial respiration and quantified this shift via the radiocarbon mass balance. The mass-balance model revealed increases in peat-supported respiration of the catotelm depths in heated plots over time and relative to ambient enclosures, from a baseline of 20%–25% in ambient enclosures, to 35%–40% in the heated plots. We find that warming stimulates microorganisms to respire ancient peat C, deposited under prior climate (cooler) conditions. This apparent destabilization of the large peat C reservoir has implications for peatland-climate feedbacks especially if the balance of the peatland is tipped from net C sink to C source. Plain Language Summary Since the end of the last glacial period, about 20 thousand years ago, peatlands have taken up carbon and now store an amount nearly equivalent to the quantity in the atmosphere. Microorganisms consume and respire that peat C releasing it back to the atmosphere as CO2 and CH4. Until now, many studies have shown that microorganisms prefer to consume the most recently fixed carbon and that the deeply buried ancient peat carbon reservoir is relatively stable. However, climate warming is expected to upset that balance. The Spruce and Peatlands Responses Under Changing Environments is large-scale experimental warming of a Minnesota peatland designed to study these effects. We conducted radiocarbon analysis of the peat and the microbially produced CO2 and dissolved organic carbon in ambient and heated areas of the peatland and show that at warmer temperatures more of the ancient peat carbon is being mobilized and respired to CO2. This is troubling as it signifies a positive feedback loop wherein warming stimulates peat to produce more CO2 which further exacerbates climate change

A Large Hadron Electron Collider at CERN

This document provides a brief overview of the recently published report on the design of the Large Hadron Electron Collider (LHeC), which comprises its physics programme, accelerator physics, technology and main detector concepts. The LHeC exploits and develops challenging, though principally existing, accelerator and detector technologies. This summary is complemented by brief illustrations of some of the highlights of the physics programme, which relies on a vastly extended kinematic range, luminosity and unprecedented precision in deep inelastic scattering. Illustrations are provided regarding high precision QCD, new physics (Higgs, SUSY) and electron-ion physics. The LHeC is designed to run synchronously with the LHC in the twenties and to achieve an integrated luminosity of O(100) fb$^{-1}$. It will become the cleanest high resolution microscope of mankind and will substantially extend as well as complement the investigation of the physics of the TeV energy scale, which has been enabled by the LHC

Soil Metabolome Response to Whole-Ecosystem Warming at the Spruce and Peatland Responses Under Changing Environments Experiment

While peatlands have historically stored massive amounts of soil carbon, warming is expected to enhance decomposition, leading to a positive feedback with climate change. In this study, a unique whole-ecosystem warming experiment was conducted in northern Minnesota to warm peat profiles to 2 m deep while keeping water flow intact. After nearly 2 y, warming enhanced the degradation of soil organic matter and increased greenhouse gas production. Changes in organic matter quality with warming were accompanied by a stimulation of methane production relative to carbon dioxide. Our results revealed increased decomposition to be fueled by the availability of reactive carbon substrates produced by surface vegetation. The elevated rates of methanogenesis are likely to persist and exacerbate climate warming

Search for Doubly-Charged Higgs Boson Production at HERA

A search for the single production of doubly-charged Higgs bosons H^{\pm \pm} in ep collisions is presented. The signal is searched for via the Higgs decays into a high mass pair of same charge leptons, one of them being an electron. The analysis uses up to 118 pb^{-1} of ep data collected by the H1 experiment at HERA. No evidence for doubly-charged Higgs production is observed and mass dependent upper limits are derived on the Yukawa couplings h_{el} of the Higgs boson to an electron-lepton pair. Assuming that the doubly-charged Higgs only decays into an electron and a muon via a coupling of electromagnetic strength h_{e \mu} = \sqrt{4 \pi \alpha_{em}} = 0.3, a lower limit of 141 GeV on the H^{\pm\pm} mass is obtained at the 95% confidence level. For a doubly-charged Higgs decaying only into an electron and a tau and a coupling h_{e\tau} = 0.3, masses below 112 GeV are ruled out.Comment: 15 pages, 3 figures, 1 tabl

Transcription of toll-like receptors 2, 3, 4 and 9, FoxP3 and Th17 cytokines in a susceptible experimental model of canine Leishmania infantum infection

Canine leishmaniosis (CanL) due to Leishmania infantum is a chronic zoonotic systemic disease resulting from complex interactions between protozoa and the canine immune system. Toll-like receptors (TLRs) are essential components of the innate immune system and facilitate the early detection of many infections. However, the role of TLRs in CanL remains unknown and information describing TLR transcription during infection is extremely scarce. The aim of this research project was to investigate the impact of L. infantum infection on canine TLR transcription using a susceptible model. The objectives of this study were to evaluate transcription of TLRs 2, 3, 4 and 9 by means of quantitative reverse transcription polymerase chain reaction (qRT-PCR) in skin, spleen, lymph node and liver in the presence or absence of experimental L. infantum infection in Beagle dogs. These findings were compared with clinical and serological data, parasite densities in infected tissues and transcription of IL-17, IL-22 and FoxP3 in different tissues in non-infected dogs (n = 10), and at six months (n = 24) and 15 months (n = 7) post infection. Results revealed significant down regulation of transcription with disease progression in lymph node samples for TLR3, TLR4, TLR9, IL-17, IL-22 and FoxP3. In spleen samples, significant down regulation of transcription was seen in TLR4 and IL-22 when both infected groups were compared with controls. In liver samples, down regulation of transcription was evident with disease progression for IL-22. In the skin, upregulation was seen only for TLR9 and FoxP3 in the early stages of infection. Subtle changes or down regulation in TLR transcription, Th17 cytokines and FoxP3 are indicative of the silent establishment of infection that Leishmania is renowned for. These observations provide new insights about TLR transcription, Th17 cytokines and Foxp3 in the liver, spleen, lymph node and skin in CanL and highlight possible markers of disease susceptibility in this model