Impact of phenotype definition on genome-wide association signals: empirical evaluation in human immunodeficiency virus type 1 infection.

Discussion on improving the power of genome-wide association studies to identify candidate variants and genes is generally centered on issues of maximizing sample size; less attention is given to the role of phenotype definition and ascertainment. The authors used genome-wide data from patients infected with human immunodeficiency virus type 1 (HIV-1) to assess whether differences in type of population (622 seroconverters vs. 636 seroprevalent subjects) or the number of measurements available for defining the phenotype resulted in differences in the effect sizes of associations between single nucleotide polymorphisms and the phenotype, HIV-1 viral load at set point. The effect estimate for the top 100 single nucleotide polymorphisms was 0.092 (95% confidence interval: 0.074, 0.110) log(10) viral load (log(10) copies of HIV-1 per mL of blood) greater in seroconverters than in seroprevalent subjects. The difference was even larger when the authors focused on chromosome 6 variants (0.153 log(10) viral load) or on variants that achieved genome-wide significance (0.232 log(10) viral load). The estimates of the genetic effects tended to be slightly larger when more viral load measurements were available, particularly among seroconverters and for variants that achieved genome-wide significance. Differences in phenotype definition and ascertainment may affect the estimated magnitude of genetic effects and should be considered in optimizing power for discovering new associations.

Ammonium and nitrate in soil and upland rice yield as affected by cover crops and their desiccation time

The objective of this work was to evaluate the effect of cover crops and their desiccation times on upland rice yield and on the levels of nitrate and ammonium in a no-tillage soil. The experiment was carried out in a randomized blocks, with split plots and three replicates. Cover crops (plots) were sowed in the off-season (March 2009). In November 2009, at 30, 20, 10 and 0 days before rice sowing (split plots), herbicide was applied on the cover crops (fallow, Panicum maximum, Urochloa ruziziensis, U. brizantha and millet). Straw and soil were sampled (0 - 10 cm) at the sowing day, and after 7, 14, 21, 28 and 35 days. Straws from millet and fallow were degraded more rapidly and provided the lowest level of nitrate in the soil. Urochloa ruziziensis, U. brizantha and P. maximum produced higher amounts of dry matter, and provided the highest levels of nitrate in the soil. Millet provides the lowest nitrate/ammonium ratio and the highest upland rice yield. Desiccations carried out at 30 and 20 days before sowing had the largest levels of nitrate in the soil at the sowing date. Nitrogen content and forms in the soil are affected by cover crops and their desiccation times.

Storage protein profile and amino acid content in wild rice Oryza glumaepatula

- The objective of this work was to determine the total protein profile and the contents of the four major protein fractions (albumin, globulin, prolamin and glutelin) and of the amino acids in the endosperm of the rice wild species Oryza glumaepatula. The experiment was performed with 29 accessions of this species, collected from 13 Brazilian locations, and two commercial cultivars. Protein samples were prepared using dried, polished, and ground grains to obtain homogeneous, dry flour used in the preparation of extracts. Oryza glumaepatula accessions were identified with the highest levels of total protein, albumin and glutelin protein fractions, and amino acids (with the exception of tryptophan) in comparison to the two analized rice cultivars. The albumin and glutelin profiles in SDS-Page were distinct between rice cultivars and O. glumaepatula. This wild species has the potential to increase the nutritional quality of rice storage protein through interspecific crosses.

Rice yield estimation based on weather conditions and on technological level of production systems in Brazil

The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E1') ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha‑1, respectively.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Parboiled rice whole bran in laying diets for Japanese quails

The objective of this work was to evaluate the effects of parboiled rice whole bran (PRWB) inclusion in laying diets for Japanese quails, on their performance, egg quality, and economic viability. A total of 448 17-week-old quails were weighed and distributed in a completely randomized design with seven treatments and eight replicates of eight birds each. A control diet (no PRWB) and six diets, containing 5, 10, 15, 20, 25, and 30% of PRWB, were tested. The increasing levels of PRWB did not affected nutrient digestibility coefficient, dietary energy use, feed intake, egg production, egg weight, egg mass, and the economic viability indices. However, there was a linear decrease in egg shell percentage, specific weight, and yolk color. The inclusion of up to 30% PRWB in the diet allows nutrient utilization and performance similar to those obtained by the control group, and it is economically viable.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data.

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion. AVAILABILITY: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The complete genome sequence of the gram-positive bacterium Bacillus subtilis.

Bacillus subtilis is the best-characterized member of the Gram-positive bacteria. Its genome of 4,214,810 base pairs comprises 4,100 protein-coding genes. Of these protein-coding genes, 53% are represented once, while a quarter of the genome corresponds to several gene families that have been greatly expanded by gene duplication, the largest family containing 77 putative ATP-binding transport proteins. In addition, a large proportion of the genetic capacity is devoted to the utilization of a variety of carbon sources, including many plant-derived molecules. The identification of five signal peptidase genes, as well as several genes for components of the secretion apparatus, is important given the capacity of Bacillus strains to secrete large amounts of industrially important enzymes. Many of the genes are involved in the synthesis of secondary metabolites, including antibiotics, that are more typically associated with Streptomyces species. The genome contains at least ten prophages or remnants of prophages, indicating that bacteriophage infection has played an important evolutionary role in horizontal gene transfer, in particular in the propagation of bacterial pathogenesis.

PhylomeDB v4: zooming into the plurality of evolutionary histories of a genome

Phylogenetic trees representing the evolutionary relationships of homologous genes are the entry point for many evolutionary analyses. For instance, the use of a phylogenetic tree can aid in the inference of orthology and paralogy relationships, and in the detection of relevant evolutionary events such as gene family expansions and contractions, horizontal gene transfer, recombination or incomplete lineage sorting. Similarly, given the plurality of evolutionary histories among genes encoded in a given genome, there is a need for the combined analysis of genome-wide collections of phylogenetic trees (phylomes). Here, we introduce a new release of PhylomeDB (http://phylomedb.org), a public repository of phylomes. Currently, PhylomeDB hosts 120 public phylomes, comprising >1.5 million maximum likelihood trees and multiple sequence alignments. In the current release, phylogenetic trees are annotated with taxonomic, protein-domain arrangement, functional and evolutionary information. PhylomeDB is also a major source for phylogeny-based predictions of orthology and paralogy, covering >10 million proteins across 1059 sequenced species. Here we describe newly implemented PhylomeDB features, and discuss a benchmark of the orthology predictions provided by the database, the impact of proteome updates and the use of the phylome approach in the analysis of newly sequenced genomes and transcriptomes.

The genome of the recently domesticated crop plant sugar beet (Beta vulgaris)

Sugar beet (Beta vulgaris ssp. vulgaris) is an important crop of temperate climates which provides nearly 30% of the world's annual sugar production and is a source for bioethanol and animal feed. The species belongs to the order of Caryophylalles, is diploid with 2n = 18 chromosomes, has an estimated genome size of 714-758 megabases and shares an ancient genome triplication with other eudicot plants. Leafy beets have been cultivated since Roman times, but sugar beet is one of the most recently domesticated crops. It arose in the late eighteenth century when lines accumulating sugar in the storage root were selected from crosses made with chard and fodder beet. Here we present a reference genome sequence for sugar beet as the first non-rosid, non-asterid eudicot genome, advancing comparative genomics and phylogenetic reconstructions. The genome sequence comprises 567 megabases, of which 85% could be assigned to chromosomes. The assembly covers a large proportion of the repetitive sequence content that was estimated to be 63%. We predicted 27,421 protein-coding genes supported by transcript data and annotated them on the basis of sequence homology. Phylogenetic analyses provided evidence for the separation of Caryophyllales before the split of asterids and rosids, and revealed lineage-specific gene family expansions and losses. We sequenced spinach (Spinacia oleracea), another Caryophyllales species, and validated features that separate this clade from rosids and asterids. Intraspecific genomic variation was analysed based on the genome sequences of sea beet (Beta vulgaris ssp. maritima; progenitor of all beet crops) and four additional sugar beet accessions. We identified seven million variant positions in the reference genome, and also large regions of low variability, indicating artificial selection. The sugar beet genome sequence enables the identification of genes affecting agronomically relevant traits, supports molecular breeding and maximizes the plant's potential in energy biotechnology.

Physiological parameters to select upland rice genotypes for tolerance to water deficit

Abstract: The objective of this work was to evaluate the feasibility of using physiological parameters for water deficit tolerance, as an auxiliary method for selection of upland rice genotypes. Two experiments - with or without water deficit - were carried out in Porangatu, in the state of Goiás, Brazil; the water deficit experiment received about half of irrigation that was applied to the well-watered experiment. Four genotypes with different tolerance levels to water stress were evaluated. The UPLRI 7, B6144F-MR-6-0-0, and IR80312-6-B-3-2-B genotypes, under water stress conditions, during the day, showed lower stomatal diffusive resistance, higher leaf water potential, and lower leaf temperature than the control. These genotypes showed the highest grain yields under water stress conditions, which were 534, 601, and 636 kg ha-1, respectively, and did not differ significantly among them. They also showed lower drought susceptibility index than the other genotypes. 'BRS Soberana' (susceptible control) was totally unproductive under drought conditions. Leaf temperature is a easy-read parameter correlated to plant-water status, viable for selecting rice genotypes for water deficit tolerance.

Characterization of rue extract and its potential for controlling rice blast

Abstract: The objective of this work was to purify and standardize the rue (Ruta graveolens) extract and evaluate its effect on Magnaporthe oryzae as an alternative to the integrated management of rice blast. The drug was characterized, the liquid extract was obtained, and the methodology for quantifying the standard markers psoralen and bergapten was validated. Rue extract and the markers, solely or in combination, were assayed in vitro, as well as in greenhouse conditions, for their ability to suppress leaf blast, by the evaluation of mycelial growth, conidial germination, and appressorium formation. Rue extract inhibited M. oryzae mycelial growth (100%), conidial germination (LD50=0.237 mg), and the appressorium formation (LD50=0.121 mg); besides, the extract reduced leaf blast severity by 80.84%. Fluorescence microscopy showed that rue extract did not damage M. oryzae cell wall and plasma membrane, indicating another mode of action. Rue extract has a great potential for controlling rice leaf blast.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture.

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.