Direct and indirect effects of CO2, nitrogen, and community diversity on plant–enemy interactions

Resource abundance and plant diversity are two predominant factors hypothesized to influence the amount of damage plants receive from natural enemies. Many impacts of these environmental variables on plant damage are likely indirect and result because both resource availability and diversity can influence plant traits associated with attractiveness to herbivores or susceptibility to pathogens. We used a long-term, manipulative field experiment to investigate how carbon dioxide (CO2) enrichment, nitrogen (N) fertilization, and plant community diversity affect plant traits and the amount of herbivore and pathogen damage experienced by the common prairie legume Lespedeza capitata. We detected little evidence that CO2 or N affected plant traits; however, plants growing in high-diversity treatments (polycultures) were taller, were less pubescent, and produced thinner leaves (higher specific leaf area). Interestingly, we also detected little evidence that CO2 or N affect damage. Plants growing in polycultures compared to monocultures, however, experienced a fivefold increase in damage from generalist herbivores, 64% less damage from specialist herbivores, and 91% less damage from pathogens. Moreover, within diversity treatments, damage by generalist herbivores was negatively correlated with pubescence and often was positively correlated with plant height, while damage by specialist herbivores typically was positively correlated with pubescence and negatively associated with height. These patterns are consistent with changes in plant traits driving differences in herbivory between diversity treatments. In contrast, changes in measured plant traits did not explain the difference in disease incidence between monocultures and polycultures. In summary, our data provide little evidence that CO2 or N supply alter damage from natural enemies. By contrast, plants grown in monocultures experienced greater specialist herbivore and pathogen damage but less generalist herbivore damage than plants grown in diverse communities. Part of this diversity effect was mediated by changes in plant traits, many of which likely are plastic responses to diversity treatments, but some of which may be the result of evolutionary changes in response to these long-term experimental manipulations

OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI☆

Magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients and is essential for diagnosing the disease and monitoring its progression. In practice, lesion load is often quantified by either manual or semi-automated segmentation of MRI, which is time-consuming, costly, and associated with large inter- and intra-observer variability. We propose OASIS is Automated Statistical Inference for Segmentation (OASIS), an automated statistical method for segmenting MS lesions in MRI studies. We use logistic regression models incorporating multiple MRI modalities to estimate voxel-level probabilities of lesion presence. Intensity-normalized T1-weighted, T2-weighted, fluid-attenuated inversion recovery and proton density volumes from 131 MRI studies (98 MS subjects, 33 healthy subjects) with manual lesion segmentations were used to train and validate our model. Within this set, OASIS detected lesions with a partial area under the receiver operating characteristic curve for clinically relevant false positive rates of 1% and below of 0.59% (95% CI; [0.50%, 0.67%]) at the voxel level. An experienced MS neuroradiologist compared these segmentations to those produced by LesionTOADS, an image segmentation software that provides segmentation of both lesions and normal brain structures. For lesions, OASIS out-performed LesionTOADS in 74% (95% CI: [65%, 82%]) of cases for the 98 MS subjects. To further validate the method, we applied OASIS to 169 MRI studies acquired at a separate center. The neuroradiologist again compared the OASIS segmentations to those from LesionTOADS. For lesions, OASIS ranked higher than LesionTOADS in 77% (95% CI: [71%, 83%]) of cases. For a randomly selected subset of 50 of these studies, one additional radiologist and one neurologist also scored the images. Within this set, the neuroradiologist ranked OASIS higher than LesionTOADS in 76% (95% CI: [64%, 88%]) of cases, the neurologist 66% (95% CI: [52%, 78%]) and the radiologist 52% (95% CI: [38%, 66%]). OASIS obtains the estimated probability for each voxel to be part of a lesion by weighting each imaging modality with coefficient weights. These coefficients are explicit, obtained using standard model fitting techniques, and can be reused in other imaging studies. This fully automated method allows sensitive and specific detection of lesion presence and may be rapidly applied to large collections of images

Strong ecological but weak evolutionary effects of elevated CO2 on a recombinant inbred population of Arabidopsis thaliana

Summary • Increases in atmospheric CO 2 concentration have an impact on plant communities by influencing plant growth and morphology, species interactions, and ecosystem processes. These ecological effects may be accompanied by evolutionary change if elevated CO 2 (eCO 2 ) alters patterns of natural selection or expression of genetic variation. • Here, a statistically powerful quantitative genetic experiment and manipulations of CO 2 concentrations in a field setting were used to investigate how eCO 2 impacts patterns of selection on ecologically important traits in Arabidopsis thaliana ; heritabilities, which influence the rate of response to selection; and genetic covariances between traits, which may constrain responses to selection. • CO 2 had strong phenotypic effects; plants grown in eCO 2 were taller and produced more biomass and fruits. Also, significant directional selection was observed on many traits and significant genetic variation was observed for all traits. However, no evolutionary effect of eCO 2 was detected; patterns of selection, heritabilities and genetic correlations corresponded closely in ambient and elevated CO 2 environments. • The data suggest that patterns of natural selection and the quantitative genetic parameters of this A. thaliana population are robust to increases in CO 2 concentration and that responses to eCO 2 will be primarily ecological

Presymptomatic risk assessment for chronic non-communicable diseases

The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that can be used for pre-symptomatic risk assessment. Common single nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome currently account for a non-trivial portion of the germ-line genetic risk and we will likely continue to identify the remaining missing heritability in the form of rare variants, copy number variants and epigenetic modifications. Here, we describe a novel measure for calculating the lifetime risk of a disease, called the genetic composite index (GCI), and demonstrate its predictive value as a clinical classifier. The GCI only considers summary statistics of the effects of genetic variation and hence does not require the results of large-scale studies simultaneously assessing multiple risk factors. Combining GCI scores with environmental risk information provides an additional tool for clinical decision-making. The GCI can be populated with heritable risk information of any type, and thus represents a framework for CNCD pre-symptomatic risk assessment that can be populated as additional risk information is identified through next-generation technologies.Comment: Plos ONE paper. Previous version was withdrawn to be updated by the journal's pdf versio

Analysis of Chimpanzee History Based on Genome Sequence Alignments

Population geneticists often study small numbers of carefully chosen loci, but it has become possible to obtain orders of magnitude for more data from overlaps of genome sequences. Here, we generate tens of millions of base pairs of multiple sequence alignments from combinations of three western chimpanzees, three central chimpanzees, an eastern chimpanzee, a bonobo, a human, an orangutan, and a macaque. Analysis provides a more precise understanding of demographic history than was previously available. We show that bonobos and common chimpanzees were separated ∼1,290,000 years ago, western and other common chimpanzees ∼510,000 years ago, and eastern and central chimpanzees at least 50,000 years ago. We infer that the central chimpanzee population size increased by at least a factor of 4 since its separation from western chimpanzees, while the western chimpanzee effective population size decreased. Surprisingly, in about one percent of the genome, the genetic relationships between humans, chimpanzees, and bonobos appear to be different from the species relationships. We used PCR-based resequencing to confirm 11 regions where chimpanzees and bonobos are not most closely related. Study of such loci should provide information about the period of time 5–7 million years ago when the ancestors of humans separated from those of the chimpanzees

Engineering Genetically Encoded Nanosensors for Real-Time In Vivo Measurements of Citrate Concentrations

Citrate is an intermediate in catabolic as well as biosynthetic pathways and is an important regulatory molecule in the control of glycolysis and lipid metabolism. Mass spectrometric and NMR based metabolomics allow measuring citrate concentrations, but only with limited spatial and temporal resolution. Methods are so far lacking to monitor citrate levels in real-time in-vivo. Here, we present a series of genetically encoded citrate sensors based on Förster resonance energy transfer (FRET). We screened databases for citrate-binding proteins and tested three candidates in vitro. The citrate binding domain of the Klebsiella pneumoniae histidine sensor kinase CitA, inserted between the FRET pair Venus/CFP, yielded a sensor highly specific for citrate. We optimized the peptide linkers to achieve maximal FRET change upon citrate binding. By modifying residues in the citrate binding pocket, we were able to construct seven sensors with different affinities spanning a concentration range of three orders of magnitude without losing specificity. In a first in vivo application we show that E. coli maintains the capacity to take up glucose or acetate within seconds even after long-term starvation

Soil microbial CNP and respiration responses to organic matter and nutrient additions: evidence from a tropical soil incubation

Soil nutrient availability has a strong influence on the fate of soil carbon (C) during microbial decomposition, contributing to Earth's C balance. While nutrient availability itself can impact microbial physiology and C partitioning between biomass and respiration during soil organic matter decomposition, the availability of labile C inputs may mediate the response of microorganisms to nutrient additions. As soil organic matter is decomposed, microorganisms retain or release C, nitrogen (N) or phosphorus (P) to maintain a stoichiometric balance. Although the concept of a microbial stoichiometric homeostasis has previously been proposed, microbial biomass CNP ratios are not static, and this may have very relevant implications for microbial physiological activities. Here, we tested the hypothesis that N, P and potassium (K) nutrient additions impact C cycling in a tropical soil due to microbial stoichiometric constraints to growth and respiration, and that the availability of energy-rich labile organic matter in the soil (i.e. leaf litter) mediates the response to nutrient addition. We incubated tropical soil from French Guiana with a ¹³C labeled leaf litter addition and with mineral nutrient additions of +K, +N, +NK, +PK and +NPK for 30 days. We found that litter additions led to a ten-fold increase in microbial respiration and a doubling of microbial biomass C, along with greater microbial N and P content. We found some evidence that P additions increased soil CO² fluxes. Additionally, we found microbial biomass CP and NP ratios varied more widely than CN in response to nutrient and organic matter additions, with important implications for the role of microorganisms in C cycling. The addition of litter did not prime soil organic matter decomposition, except in combination with +NK fertilization, indicating possible P-mining of soil organic matter in this P-poor tropical soil. Together, these results point toward an ultimate labile organic substrate limitation of soil microorganisms in this tropical soil, but also indicate a complex interaction between C, N, P and K availability. This highlights the difference between microbial C cycling responses to N, P, or K additions in the tropics and explains why coupled C, N and P cycling modeling efforts cannot rely on strict microbial stoichiometric homeostasis as an underlying assumption

Genotype, haplotype and copy-number variation in worldwide human populations

Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups(1-3). Here we report the analysis of high-quality genotypes at 525,910 single-nucleotide polymorphisms ( SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected-including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas-the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62552/1/nature06742.pd