Quantifying the environmental limits to fire spread in grassy ecosystems.

Modeling fire spread as an infection process is intuitive: An ignition lights a patch of fuel, which infects its neighbor, and so on. Infection models produce nonlinear thresholds, whereby fire spreads only when fuel connectivity and infection probability are sufficiently high. These thresholds are fundamental both to managing fire and to theoretical models of fire spread, whereas applied fire models more often apply quasi-empirical approaches. Here, we resolve this tension by quantifying thresholds in fire spread locally, using field data from individual fires (n = 1,131) in grassy ecosystems across a precipitation gradient (496 to 1,442 mm mean annual precipitation) and evaluating how these scaled regionally (across 533 sites) and across time (1989 to 2012 and 2016 to 2018) using data from Kruger National Park in South Africa. An infection model captured observed patterns in individual fire spread better than competing models. The proportion of the landscape that burned was well described by measurements of grass biomass, fuel moisture, and vapor pressure deficit. Regionally, averaging across variability resulted in quasi-linear patterns. Altogether, results suggest that models aiming to capture fire responses to global change should incorporate nonlinear fire spread thresholds but that linear approximations may sufficiently capture medium-term trends under a stationary climate.

The Role of Wildfires in the Interplay of Forest Carbon Stocks and Wood Harvest in the Contiguous United States During the 20th Century.

Wildfires and land use play a central role in the long-term carbon (C) dynamics of forested ecosystems of the United States. Understanding their linkages with changes in biomass, resource use, and consumption in the context of climate change mitigation is crucial. We reconstruct a long-term C balance of forests in the contiguous U.S. using historical reports, satellite data, and other sources at multiple scales (national scale 1926-2017, regional level 1941-2017) to disentangle the drivers of biomass C stock change. The balance includes removals of forest biomass by fire, by extraction of woody biomass, by forest grazing, and by biomass stock change, their sum representing the net ecosystem productivity (NEP). Nationally, the total forest NEP increased for most of the 20th century, while fire, harvest and grazing reduced total forest stocks on average by 14%, 51%, and 6%, respectively, resulting in a net increase in C stock density of nearly 40%. Recovery from past land-use, plus reductions in wildfires and forest grazing coincide with consistent forest regrowth in the eastern U.S. but associated C stock increases were offset by increased wood harvest. C stock changes across the western U.S. fluctuated, with fire, harvest, and other disturbances (e.g., insects, droughts) reducing stocks on average by 14%, 81%, and 7%, respectively, resulting in a net growth in C stock density of 14%. Although wildfire activities increased in recent decades, harvest was the key driver in the forest C balance in all regions for most of the observed timeframe.

Land use intensification increasingly drives the spatiotemporal patterns of the global human appropriation of net primary production in the last century.

Land use has greatly transformed Earth's surface. While spatial reconstructions of how the extent of land cover and land-use types have changed during the last century are available, much less information exists about changes in land-use intensity. In particular, global reconstructions that consistently cover land-use intensity across land-use types and ecosystems are missing. We, therefore, lack understanding of how changes in land-use intensity interfere with the natural processes in land systems. To address this research gap, we map land-cover and land-use intensity changes between 1910 and 2010 for 9 points in time. We rely on the indicator framework of human appropriation of net primary production (HANPP) to quantify and map land-use-induced alterations of the carbon flows in ecosystems. We find that, while at the global aggregate level HANPP growth slowed down during the century, the spatial dynamics of changes in HANPP were increasing, with the highest change rates observed in the most recent past. Across all biomes, the importance of changes in land-use areas has declined, with the exception of the tropical biomes. In contrast, increases in land-use intensity became the most important driver of HANPP across all biomes and settings. We conducted uncertainty analyses by modulating input data and assumptions, which indicate that the spatial patterns of land use and potential net primary production are the most critical factors, while spatial allocation rules and uncertainties in overall harvest values play a smaller role. Highlighting the increasing role of land-use intensity compared to changes in the areal extent of land uses, our study supports calls for better integration of the intensity dimension into global analyses and models. On top of that, we provide important empirical input for further analyses of the sustainability of the global land system.

Nutrient cycling drives plant community trait assembly and ecosystem functioning in a tropical mountain biodiversity hotspot.

Community trait assembly in highly diverse tropical rainforests is still poorly understood. Based on more than a decade of field measurements in a biodiversity hotspot of southern Ecuador, we implemented plant trait variation and improved soil organic matter dynamics in a widely used dynamic vegetation model (the Lund-Potsdam-Jena General Ecosystem Simulator, LPJ-GUESS) to explore the main drivers of community assembly along an elevational gradient. In the model used here (LPJ-GUESS-NTD, where NTD stands for nutrient-trait dynamics), each plant individual can possess different trait combinations, and the community trait composition emerges via ecological sorting. Further model developments include plant growth limitation by phosphorous (P) and mycorrhizal nutrient uptake. The new model version reproduced the main observed community trait shift and related vegetation processes along the elevational gradient, but only if nutrient limitations to plant growth were activated. In turn, when traits were fixed, low productivity communities emerged due to reduced nutrient-use efficiency. Mycorrhizal nutrient uptake, when deactivated, reduced net primary production (NPP) by 61-72% along the gradient. Our results strongly suggest that the elevational temperature gradient drives community assembly and ecosystem functioning indirectly through its effect on soil nutrient dynamics and vegetation traits. This illustrates the importance of considering these processes to yield realistic model predictions.

PrimedRPA: primer design for recombinase polymerase amplification assays.

SUMMARY: Recombinase polymerase amplification (RPA), an isothermal nucleic acid amplification method, is enhancing our ability to detect a diverse array of pathogens, thereby assisting the diagnosis of infectious diseases and the detection of microorganisms in food and water. However, new bioinformatics tools are needed to automate and improve the design of the primers and probes sets to be used in RPA, particularly to account for the high genetic diversity of circulating pathogens and cross detection of genetically similar organisms. PrimedRPA is a python-based package that automates the creation and filtering of RPA primers and probe sets. It aligns several sequences to identify conserved targets, and filters regions that cross react with possible background organisms. AVAILABILITY AND IMPLEMENTATION: PrimedRPA was implemented in Python 3 and supported on Linux and MacOS and is freely available from http://pathogenseq.lshtm.ac.uk/PrimedRPA.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction.

In this study, we use simulations from seven global vegetation models to provide the first multi-model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001-2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire-induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state-of-the-art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.

Duplex recombinase polymerase amplification assays incorporating competitive internal controls for bacterial meningitis detection.

Recombinase polymerase amplification (RPA) is an isothermal nucleic acid amplification technology that provides rapid and robust infectious disease pathogen detection, ideal for point-of-care (POC) diagnostics in disease-prevalent low-resource countries. We have developed and evaluated three duplex RPA assays incorporating competitive internal controls for the detection of leading bacterial meningitis pathogens. Streptococcus pneumoniae, Neisseria meningitidis and Haemophilus influenzae singleplex RPA assays were initially developed and evaluated, demonstrating 100% specificity with limits of detection of 4.1, 8.5 and 3.9 genome copies per reaction, respectively. Each assay was further developed into internally controlled duplex RPA assays via the incorporation of internal amplification control templates. Clinical performance of each internally controlled duplex RPA assay was evaluated by testing 64 archived PCR-positive clinical samples. Compared to real-time PCR, all duplex RPA assays demonstrated 100% diagnostic specificity, with diagnostic sensitivities of 100%, 86.3% and 100% for the S. pneumoniae, N. meningitidis and H. influenzae assays, respectively. This study details the first report of internally controlled duplex RPA assays for the detection of bacterial meningitis pathogens: S. pneumoniae, N. meningitidis and H. influenzae. We have successfully demonstrated the clinical diagnostic utility of each duplex RPA assay, introducing effective diagnostic technology for POC bacterial meningitis identification in disease-prevalent developing countries.

Development of a rapid recombinase polymerase amplification assay for the detection of Streptococcus pneumoniae in whole blood.

BACKGROUND: Streptococcus pneumoniae is an important cause of microbial disease in humans. The introduction of multivalent vaccines has coincided with a dramatic decrease in the number of pneumococcal-related deaths. In spite of this, at a global level, pneumococcal infection remains an important cause of death among children under 5 years of age and in adults 65 years of age or older. In order to properly manage patients and control the spread of infection, a rapid and highly sensitive diagnostic method is needed for routine implementation, especially in resource-limited regions where pneumococcal disease is most prevalent. METHODS: Using the gene encoding leader peptidase A as a molecular diagnostics target, a real-time RPA assay was designed and optimised for the detection of S. pneumoniae in whole blood. The performance of the assay was compared to real-time PCR in terms of its analytical limit of detection and specificity. The inhibitory effect of human genomic DNA on amplification was investigated. The potential clinical utility of the assay was investigated using a small number of clinical samples. RESULTS: The RPA assay has a limit of detection equivalent to PCR (4.0 and 5.1 genome equivalents per reaction, respectively) and was capable of detecting the equivalent of <1 colony forming unit of S. pneumoniae when spiked into human whole blood. The RPA assay was 100 % inclusive (38/38 laboratory reference strains and 19/19 invasive clinical isolates) and 100 % exclusive; differentiating strains of S. pneumoniae species from other viridans group streptococci, including S. pseudopneumoniae. When applied to the analysis of a small number (n = 11) of clinical samples (blood culture positive for S. pneumoniae), the RPA assay was demonstrated to be both rapid and sensitive. CONCLUSIONS: The RPA assay developed in this work is shown to be as sensitive and as specific as PCR. In terms of reaction kinetics, the RPA assay is shown to exceed those of the PCR, with the RPA running to completion in 20 minutes and capable generating a positive signal in as little as 6 minutes. This work represents a potentially suitable assay for application in point-of-care settings.

Movement drives population dynamics of one of the most mobile ungulates on Earth: Insights from a mechanistic model.

Long-distance movements are hypothesized to positively influence population size and stability of mobile species. We tested this hypothesis with a novel modeling approach in which moving herbivores interact with the environment created by a dynamic global vegetation model using highly mobile Mongolian gazelles in the eastern Mongolian grasslands as a case study. Gazelle population dynamics were modeled from 1901 to 2018 under two scenarios, one allowing free movement and one restricting movement. Gazelles were 2.2 times more abundant when they could move freely and were extirpated in 71% of the study area when mobility was restricted. Mobility resulted in greater population increases during times of abundant forage and smaller population decreases during drought. Reduced thermoregulatory costs associated with climate change, combined with an increase in vegetation biomass, increased gazelle abundance. Since high abundances often resulted in overgrazing and, thus, extirpation when movement was restricted, mobility had an important role in maintaining higher densities. The novel modeling approach shows how accounting for not just herbivore but also plant ecophysiology can improve our understanding of the population dynamics of highly mobile herbivores, in particular when examining the effects of habitat and climate change. Since the model simulates herbivores based on general physiological mechanisms that apply across large herbivores and the vegetation model can be applied globally, it is possible to adapt the model to other large-herbivore systems.

KEEPING THE HEAT ON: WEIGHTED SURVEILLANCE FOR CHYTRID FUNGUS (BATRACHOCHYTRIUM DENDROBATIDIS) IN DIXIE VALLEY TOADS (ANAXYRUS [= BUFO] WILLIAMSI).

Introduced fungal pathogens have caused declines and extinctions of naïve wildlife populations across vertebrate classes. Consequences of introduced pathogens to hosts with small ranges might be especially severe because of limited redundancy to rescue populations and lower abundance that may limit the resilience of populations to perturbations like disease introduction. As a complement to biosecurity measures to prevent the spread of pathogens, surveillance programs may enable early detection of pathogens, when management actions to limit the effects of pathogens on naïve hosts might be most beneficial. We analyzed surveillance data for the endangered and narrowly endemic Dixie Valley toad (Anaxyrus [= Bufo] williamsi) from two time periods (2011-2014 and 2019-2021) to estimate the minimum detectable prevalence of the amphibian fungal pathogen Batrachochytrium dendrobatidis (Bd). We assessed if detection efficiency could be improved by using samples from both Dixie Valley toads and co-occurring introduced American bullfrogs (Lithobates catesbeianus) and literature-derived surveillance weights. We further evaluated a weighted surveillance design to increase the efficiency of surveillance efforts for Bd within the toad's small (<6 km2) range. We found that monitoring adult and larval American bullfrogs would probably detect Bd more efficiently than monitoring Dixie Valley toads alone. Given that no Bd was detected, minimum detectable prevalence of Bd was <3% in 2011-2014, and <5% (Dixie Valley toads only) and <10% (American bullfrogs only) in 2019-2021. Optimal management for Bd depends on the mechanisms underlying its apparent absence from the range of Dixie Valley toads, but a balanced surveillance scheme that includes sampling American bullfrogs to increase the likelihood of detecting Bd, and adult Dixie Valley toads to ensure broad spatial coverage where American bullfrogs do not occur, would probably result in efficient surveillance, which might permit timely management of Bd if it is detected.

Characterizing the Impact of Primer-Template Mismatches on Recombinase Polymerase Amplification.

Recombinase polymerase amplification (RPA) is an isothermal amplification assay that has been ubiquitously utilized in the detection of infectious agents. Like any nucleic acid amplification technology, primer-template complementarity is critical to RPA reaction success. Mismatches arising in the primer-template complex are known to impact reaction kinetics, invalidate downstream analysis, such as nucleic acid quantification, and result in false negatives if used in a diagnostic capacity. Although the impact of specific primer-template mismatches has been well characterized for techniques such as PCR, characterization remains limited for RPA. Through our study, we systematically characterize the impact of mismatches on the RPA reaction, when located in the 3'-anchor region of the primer-template complex. Our investigation identified that the nucleotides involved, as well as position of each mismatch, influence the size of the impact, with terminal cytosine-thymine and guanine-adenine mismatches being the most detrimental. The presence of some mismatch combinations, such as a penultimate cytosine-cytosine and a terminal cytosine-adenine mismatch pairing, led to complete RPA reaction inhibition. Through the successful characterization of 315 mismatch combinations, researchers can optimize their RPA assay accordingly and seek to implement RPA technology for rapid, in-field genotyping.

Rapid Detection of Actinobacillus pleuropneumoniae From Clinical Samples Using Recombinase Polymerase Amplification.

Actinobacillus pleuropneumoniae (APP) is the causative agent of porcine pleuropneumonia, resulting in high economic impact worldwide. There are currently 19 known serovars of APP, with different ones being predominant in specific geographic regions. Outbreaks of pleuropneumonia, characterized by sudden respiratory difficulties and high mortality, can occur when infected pigs are brought into naïve herds, or by those carrying different serovars. Good biosecurity measures include regular diagnostic testing for surveillance purposes. Current gold standard diagnostic techniques lack sensitivity (bacterial culture), require expensive thermocycling machinery (PCR) and are time consuming (culture and PCR). Here we describe the development of an isothermal point-of-care diagnostic test - utilizing recombinase polymerase amplification (RPA) for the detection of APP, targeting the species-specific apxIVA gene. Our APP-RPA diagnostic test achieved a sensitivity of 10 copies/µL using a strain of APP serovar 8, which is the most prevalent serovar in the UK. Additionally, our APP-RPA assay achieved a clinical sensitivity and specificity of 84.3 and 100%, respectively, across 61 extracted clinical samples obtained from farms located in England and Portugal. Using a small subset (n = 14) of the lung tissue samples, we achieved a clinical sensitivity and specificity of 76.9 and 100%, respectively) using lung imprints made on FTA cards tested directly in the APP-RPA reaction. Our results demonstrate that our APP-RPA assay enables a suitable rapid and sensitive screening tool for this important veterinary pathogen.

Modifier effects between regulatory and protein-coding variation.

Genome-wide associations have shown a lot of promise in dissecting the genetics of complex traits in humans with single variants, yet a large fraction of the genetic effects is still unaccounted for. Analyzing genetic interactions between variants (epistasis) is one of the potential ways forward. We investigated the abundance and functional impact of a specific type of epistasis, namely the interaction between regulatory and protein-coding variants. Using genotype and gene expression data from the 210 unrelated individuals of the original four HapMap populations, we have explored the combined effects of regulatory and protein-coding single nucleotide polymorphisms (SNPs). We predict that about 18% (1,502 out of 8,233 nsSNPs) of protein-coding variants are differentially expressed among individuals and demonstrate that regulatory variants can modify the functional effect of a coding variant in cis. Furthermore, we show that such interactions in cis can affect the expression of downstream targets of the gene containing the protein-coding SNP. In this way, a cis interaction between regulatory and protein-coding variants has a trans impact on gene expression. Given the abundance of both types of variants in human populations, we propose that joint consideration of regulatory and protein-coding variants may reveal additional genetic effects underlying complex traits and disease and may shed light on causes of differential penetrance of known disease variants.

Sensitive and semiquantitative detection of soil-transmitted helminth infection in stool using a recombinase polymerase amplification-based assay.

BACKGROUND: Soil-transmitted helminths (STHs) are parasitic nematodes that inhabit the human intestine. They affect more than 1.5 billion people worldwide, causing physical and cognitive impairment in children. The global strategy to control STH infection includes periodic mass drug administration (MDA) based on the results of diagnostic testing among populations at risk, but the current microscopy method for detecting infection has diminished sensitivity as the intensity of infection decreases. Thus, improved diagnostic tools are needed to support decision-making for STH control programs. METHODOLOGY: We developed a nucleic acid amplification test based on recombinase polymerase amplification (RPA) technology to detect STH in stool. We designed primers and probes for each of the four STH species, optimized the assay, and then verified its performance using clinical stool samples. PRINCIPAL FINDINGS: Each RPA assay was as sensitive as a real-time polymerase chain reaction (PCR) assay in detecting copies of cloned target DNA sequences. The RPA assay amplified the target in DNA extracted from human stool samples that were positive for STH based on the Kato-Katz method, with no cross-reactivity of the non-target genomic DNA. When tested with clinical stool samples from patients with infections of light, moderate, and heavy intensity, the RPA assays demonstrated performance comparable to that of real-time PCR, with better results than Kato-Katz. This new rapid, sensitive and field-deployable method for detecting STH infections can help STH control programs achieve their goals. CONCLUSIONS: Semi-quantitation of target by RPA assay is possible and is comparable to real-time PCR. With proper instrumentation, RPA assays can provide robust, semi-quantification of STH DNA targets as an alternative field-deployable indicator to counts of helminth eggs for assessing infection intensity.

Data analysis issues for allele-specific expression using Illumina's GoldenGate assay.

BACKGROUND: High-throughput measurement of allele-specific expression (ASE) is a relatively new and exciting application area for array-based technologies. In this paper, we explore several data sets which make use of Illumina's GoldenGate BeadArray technology to measure ASE. This platform exploits coding SNPs to obtain relative expression measurements for alleles at approximately 1500 positions in the genome. RESULTS: We analyze data from a mixture experiment where genomic DNA samples from pairs of individuals of known genotypes are pooled to create allelic imbalances at varying levels for the majority of SNPs on the array. We observe that GoldenGate has less sensitivity at detecting subtle allelic imbalances (around 1.3 fold) compared to extreme imbalances, and note the benefit of applying local background correction to the data. Analysis of data from a dye-swap control experiment allowed us to quantify dye-bias, which can be reduced considerably by careful normalization. The need to filter the data before carrying out further downstream analysis to remove non-responding probes, which show either weak, or non-specific signal for each allele, was also demonstrated. Throughout this paper, we find that a linear model analysis of the data from each SNP is a flexible modelling strategy that allows for testing of allelic imbalances in each sample when replicate hybridizations are available. CONCLUSIONS: Our analysis shows that local background correction carried out by Illumina's software, together with quantile normalization of the red and green channels within each array, provides optimal performance in terms of false positive rates. In addition, we strongly encourage intensity-based filtering to remove SNPs which only measure non-specific signal. We anticipate that a similar analysis strategy will prove useful when quantifying ASE on Illumina's higher density Infinium BeadChips.

High-throughput analysis of candidate imprinted genes and allele-specific gene expression in the human term placenta.

BACKGROUND: Imprinted genes show expression from one parental allele only and are important for development and behaviour. This extreme mode of allelic imbalance has been described for approximately 56 human genes. Imprinting status is often disrupted in cancer and dysmorphic syndromes. More subtle variation of gene expression, that is not parent-of-origin specific, termed 'allele-specific gene expression' (ASE) is more common and may give rise to milder phenotypic differences. Using two allele-specific high-throughput technologies alongside bioinformatics predictions, normal term human placenta was screened to find new imprinted genes and to ascertain the extent of ASE in this tissue. RESULTS: Twenty-three family trios of placental cDNA, placental genomic DNA (gDNA) and gDNA from both parents were tested for 130 candidate genes with the Sequenom MassArray system. Six genes were found differentially expressed but none imprinted. The Illumina ASE BeadArray platform was then used to test 1536 SNPs in 932 genes. The array was enriched for the human orthologues of 124 mouse candidate genes from bioinformatics predictions and 10 human candidate imprinted genes from EST database mining. After quality control pruning, a total of 261 informative SNPs (214 genes) remained for analysis. Imprinting with maternal expression was demonstrated for the lymphocyte imprinted gene ZNF331 in human placenta. Two potential differentially methylated regions (DMRs) were found in the vicinity of ZNF331. None of the bioinformatically predicted candidates tested showed imprinting except for a skewed allelic expression in a parent-specific manner observed for PHACTR2, a neighbour of the imprinted PLAGL1 gene. ASE was detected for two or more individuals in 39 candidate genes (18%). CONCLUSIONS: Both Sequenom and Illumina assays were sensitive enough to study imprinting and strong allelic bias. Previous bioinformatics approaches were not predictive of new imprinted genes in the human term placenta. ZNF331 is imprinted in human term placenta and might be a new ubiquitously imprinted gene, part of a primate-specific locus. Demonstration of partial imprinting of PHACTR2 calls for re-evaluation of the allelic pattern of expression for the PHACTR2-PLAGL1 locus. ASE was common in human term placenta.

Changes in the peripheral blood transcriptome associated with occupational benzene exposure identified by cross-comparison on two microarray platforms.

Benzene is an established cause of leukemia, and possibly lymphoma, in humans, but the underlying molecular pathways remain largely undetermined. We used two microarray platforms to identify global gene expression changes associated with well-characterized occupational benzene exposure in the peripheral blood mononuclear cells (PBMC) of a population of shoe-factory workers. Differential expression of 2692 genes (Affymetrix) and 1828 genes (Illumina) was found and the concordance was 50% (based on an average fold-change > or =1.3 from the two platforms), with similar expression ratios among the concordant genes. Four genes (CXCL16, ZNF331, JUN and PF4), which we previously identified by microarray and confirmed by real-time PCR, were among the top 100 genes identified by both platforms in the current study. Gene ontology analysis showed overrepresentation of genes involved in apoptosis among the concordant genes while pathway analysis identified pathways related to lipid metabolism. The two-platform approach allows for robust changes in the PBMC transcriptome of benzene-exposed individuals to be identified.

Recombinase polymerase amplification assays for the identification of pork and horsemeat.

Detection of animal species in meat product is crucial to prevent adulterated and unnecessary contamination during processing. Gold standard is the real-time PCR assays, which can be conducted at highly equipped laboratories. Toward the development of point-of-need test, two rapid molecular assays based on recombinase polymerase amplification (RPA) for the detection of pork and horse DNA were established. Target genes are the porcine mitochondrial ND2 and equine ATP 6-8 genes. The pork and horse_RPA assays detected 16 and one DNA molecules/µl in eleven to six minutes, respectively. The myoglobin in the meat did not influence the assays performances, while the presence of high background-DNA induced a one log decrease in the sensitivity. Both assays are highly specific and identify down to 0.1% of their target DNA in meat mixtures. Both RPA assays could be used on-site as a rapid and mobile detection system to determine contamination of meat products.

Genome-wide associations of gene expression variation in humans.

The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.

Polymorphisms in cytokine and cellular adhesion molecule genes and susceptibility to hematotoxicity among workers exposed to benzene.

Benzene is a recognized hematotoxin and leukemogen but its mechanism of action and the role of genetic susceptibility are still unclear. Cytokines, chemokines, and cellular adhesion molecules are soluble proteins that play an important regulatory role in hematopoiesis. We therefore hypothesized that variation in these genes could influence benzene-induced hematotoxicity. We analyzed common, well-studied single-nucleotide polymorphisms (SNPs) in 20 candidate genes drawn from these pathways in a study of 250 workers exposed to benzene and 140 unexposed controls in China. After accounting for multiple comparisons, SNPs in five genes were associated with a statistically significant decrease in total WBC counts among exposed workers [IL-1A (-889C>T), IL-4 (-1098T>G), IL-10 (-819T>C), IL-12A (8685G>A), and VCAM1 (-1591T>C)], and one SNP [CSF3 (Ex4-165C>T)] was associated with an increase in WBC counts. The adhesion molecule VCAM1 variant was particularly noteworthy as it was associated with a decrease in B cells, natural killer cells, CD4+ T cells, and monocytes. Further, VCAM1 (-1591T>C) and CSF3 (Ex4-165C>T) were associated, respectively, with decreased (P = 0.041) and increased (P = 0.076) CFU-GEMM progenitor cell colony formation in 29 benzene-exposed workers. This is the first report to provide evidence that SNPs in genes that regulate hematopoiesis influence benzene-induced hematotoxicity.