Genetic architecture of inter-specific and -generic grass hybrids by network analysis on multi-omics data.

BACKGROUND: Understanding the mechanisms underlining forage production and its biomass nutritive quality at the omics level is crucial for boosting the output of high-quality dry matter per unit of land. Despite the advent of multiple omics integration for the study of biological systems in major crops, investigations on forage species are still scarce. RESULTS: Our results identified substantial changes in gene co-expression and metabolite-metabolite network topologies as a result of genetic perturbation by hybridizing L. perenne with another species within the genus (L. multiflorum) relative to across genera (F. pratensis). However, conserved hub genes and hub metabolomic features were detected between pedigree classes, some of which were highly heritable and displayed one or more significant edges with agronomic traits in a weighted omics-phenotype network. In spite of tagging relevant biological molecules as, for example, the light-induced rice 1 (LIR1), hub features were not necessarily better explanatory variables for omics-assisted prediction than features stochastically sampled and all available regressors. CONCLUSIONS: The utilization of computational techniques for the reconstruction of co-expression networks facilitates the identification of key omic features that serve as central nodes and demonstrate correlation with the manifestation of observed traits. Our results also indicate a robust association between early multi-omic traits measured in a greenhouse setting and phenotypic traits evaluated under field conditions.

Speeding Up Reachability Queries in Public Transport Networks Using Graph Partitioning.

Computing path queries such as the shortest path in public transport networks is challenging because the path costs between nodes change over time. A reachability query from a node at a given start time on such a network retrieves all points of interest (POIs) that are reachable within a given cost budget. Reachability queries are essential building blocks in many applications, for example, group recommendations, ranking spatial queries, or geomarketing. We propose an efficient solution for reachability queries in public transport networks. Currently, there are two options to solve reachability queries. (1) Execute a modified version of Dijkstra's algorithm that supports time-dependent edge traversal costs; this solution is slow since it must expand edge by edge and does not use an index. (2) Issue a separate path query for each single POI, i.e., a single reachability query requires answering many path queries. None of these solutions scales to large networks with many POIs. We propose a novel and lightweight reachability index. The key idea is to partition the network into cells. Then, in contrast to other approaches, we expand the network cell by cell. Empirical evaluations on synthetic and real-world networks confirm the efficiency and the effectiveness of our index-based reachability query solution.

The cytosine methylation landscape of spring barley revealed by a new reduced representation bisulfite sequencing pipeline, WellMeth.

Patterns and level of cytosine methylation vary widely among plant species and are associated with genome size as well as the proportion of transposons and other repetitive elements in the genome. We explored epigenetic patterns and diversity in a representative proportion of the spring barley (Hordeum vulgare L.) genome across several commercial and historical cultivars. This study adapted a genotyping-by-sequencing (GBS) approach for the detection of methylated cytosines in genomic DNA. To analyze the data, we developed WellMeth, a complete pipeline for analysis of reduced representation bisulfite sequencing. WellMeth enabled quantification of context-specific DNA methylation at the single-base resolution as well as identification of differentially methylated sites (DMCs) and regions (DMRs). On average, DNA methylation levels were significantly higher than what is commonly observed in many plants species, reaching over 10-fold higher levels than those in Arabidopsis thaliana (L.) Heynh. in the CHH methylation. Preferential methylation was observed within and at the edges of long-terminal repeats (LTR) retrotransposons Gypsy and Copia. From a pairwise comparison of cultivars, numerous DMRs could be identified of which more than 5,000 were conserved within the analyzed set of barley cultivars. The subset of regions overlapping with genes showed enrichment in gene ontology (GO) categories associated with chromatin and cellular structure and organization. A significant correlation between genetic and epigenetic distances suggests that a considerable portion of methylated regions is under strict genetic control in barley. The data presented herein represents the first step in efforts toward a better understanding of genome-level structural and functional aspects of methylation in barley.

Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus Pratensis by Near-Infrared Spectroscopy and Chemometrics.

Near infrared spectroscopy (NIRS) is an accurate, fast and nondestructive technique whose use in predicting forage quality has become increasingly relevant in recent decades. Epichloë-infected grass varieties are commonly used in areas with high pest pressure due to their better performances compared to endophyte-free varieties. The insect resistance of Epichloë-infected grasses has been associated with four main groups of endophyte secondary metabolites: ergot alkaloids, indole-diterpenes, lolines and peramine. Concentrations of these alkaloids are usually measured with high performance liquid chromatography or gas chromatography analysis, which are accurate methods but relatively expensive and laborious. In this paper, we developed a rapid method based on NIRS to detect and quantify loline alkaloids in wild accessions of Schedonorus pratensis infected with the fungal endophyte Epichloë uncinata. The quantitative NIR equations obtained by modified partial least squares algorithm had coefficients of correlation of 0.90, 0.78, 0.85, 0.90 for N-acetylloline, N-acetylnorloline and N-formylloline and the sum of the three, respectively. The acquired NIR spectra were also used for developing an equation to predict in planta fungal biomass with a coefficient of correlation of 0.75. These results showed that the use of NIRS and chemometrics allows the quantification of loline alkaloids and mycelial biomass in a heterogeneous set of endophyte-infected meadow fescue samples.

Reconstruction and Validation of a Genome-Scale Metabolic Model of Streptococcus oralis (iCJ415), a Human Commensal and Opportunistic Pathogen.

The mitis group of streptococci (MGS) is a member of the healthy human microbiome in the oral cavity and upper respiratory tract. Troublingly, some MGS are able to escape this niche and cause infective endocarditis, a severe and devastating disease. Genome-scale models have been shown to be valuable in investigating metabolism of bacteria. Here we present the first genome-scale model, iCJ415, for Streptococcus oralis SK141. We validated the model using gene essentiality and amino acid auxotrophy data from closely related species. iCJ415 has 71-76% accuracy in predicting gene essentiality and 85% accuracy in predicting amino acid auxotrophy. Further, the phenotype of S. oralis was tested using the Biolog Phenotype microarrays, giving iCJ415 a 82% accuracy in predicting carbon sources. iCJ415 can be used to explore the metabolic differences within the MGS, and to explore the complicated metabolic interactions between different species in the human oral cavity.

Effectiveness of two bed bath methods in removing microorganisms from hospitalized patients: A prospective randomized crossover study.

BACKGROUND: Few studies have compared the effectiveness of washing with either soap and water or disposable wet wipes. The objective of this study was to compare the effectiveness of washing with either soap and water or disposable wet wipes in reducing microorganisms in the groin and perineum of hospitalized patients, which could potentially reduce the risk of hospital-acquired urinary tract infections. METHODS: In this crossover, block-randomized trial, skin swabs from the groin and perineum areas of patients were obtained before and after these areas were washed with either soap and water or disposable wet wipes. Columbia agar plates and CHROMagar Orientation Medium (Becton Dickinson; Franklin Lakes, NJ) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry procedures were used to identify species of microorganisms. RESULTS: Fifty-eight paired skin swabs were obtained. Both washing methods resulted in a statistically significant reduction in the amount of all microorganisms, including microorganisms with the potential to cause urinary tract infections. New species were observed after using both washing methods. No statistically significant difference in the removal of microorganisms was observed between the two washing methods. CONCLUSIONS: The two washing methods appear to be equally efficient in removal of microorganisms in the groin and perineum areas, including microorganisms that potentially could cause hospital-acquired urinary tract infections.

Bed bath with soap and water or disposable wet wipes: Patients' experiences and preferences.

AIMS AND OBJECTIVES: To gain an in-depth understanding of patients' preferences regarding two bed bath methods: soap and water and disposable wet wipes. BACKGROUND: Bed baths allow hospitalised, bedridden patients to stay clean and fresh. They serve a number of purposes: health promotion, social propriety and pure pleasure. Traditionally, soap and water have been used for personal hygiene, but in recent years soap and water have increasingly been replaced by the use of disposable wet wipes. DESIGN: A qualitative study with a hermeneutical-phenomenological approach was chosen to explore and understand patients' experiences of bed bath methods. METHODS: Semi-structured, individual, in-depth interviews with 16 bedridden patients from three wards were conducted. The software program nvivo was used to structure the transcribed interviews and assist in the initial data analysis. The data were analysed and interpreted within a phenomenological-hermeneutical framework. COREQ guidelines were used in the preparation of this paper (See Supporting information Appendix S1). RESULTS: Four overall themes were identified: "Creating a sense of cleanliness," "Preferences and concerns in different situations," "Cleanliness of hands and face" and "Clinical decision-making about bed bath method." CONCLUSIONS: Overall, patients' bed bath preference was for soap and water, but disposable wet wipes were considered a convenient alternative and preferred in certain circumstances, for example, when a patient had pain or diarrhoea. Shared decision-making regarding bed bath method is recommended. Hands and face had specific requirements. RELEVANCE TO CLINICAL PRACTICE: Nursing staff should be aware that bedridden patients have varying preferences, and it is important to incorporate the patients' preferences in the development of standards, health policies and clinical guidelines for bed bath practices.

Genomic Prediction in Tetraploid Ryegrass Using Allele Frequencies Based on Genotyping by Sequencing.

Perennial ryegrass is an outbreeding forage species and is one of the most widely used forage grasses in temperate regions. The aim of this study was to investigate the possibility of implementing genomic prediction in tetraploid perennial ryegrass, to study the effects of different sequencing depth when using genotyping-by-sequencing (GBS), and to determine optimal number of single-nucleotide polymorphism (SNP) markers and sequencing depth for GBS data when applied in tetraploids. A total of 1,515 F2 tetraploid ryegrass families were included in the study and phenotypes and genotypes were scored on family-pools. The traits considered were dry matter yield (DM), rust resistance (RUST), and heading date (HD). The genomic information was obtained in the form of allele frequencies of pooled family samples using GBS. Different SNP filtering strategies were designed. The strategies included filtering out SNPs having low average depth (FILTLOW), having high average depth (FILTHIGH), and having both low average and high average depth (FILTBOTH). In addition, SNPs were kept randomly with different data sizes (RAN). The accuracy of genomic prediction was evaluated by using a "leave single F2 family out" cross validation scheme, and the predictive ability and bias were assessed by correlating phenotypes corrected for fixed effects with predicted additive breeding values. Among all the filtering scenarios, the highest estimates for genomic heritability of family means were 0.45, 0.74, and 0.73 for DM, HD and RUST, respectively. The predictive ability generally increased as the number of SNPs included in the analysis increased. The highest predictive ability for DM was 0.34 (137,191 SNPs having average depth higher than 10), for HD was 0.77 (185,297 SNPs having average depth lower than 60), and for RUST was 0.55 (188,832 SNPs having average depth higher than 1). Genomic prediction can help to optimize the breeding of tetraploid ryegrass. GBS data including about 80-100 K SNPs are needed for accurate prediction of additive breeding values in tetraploid ryegrass. Using only SNPs with sequencing depth between 10 and 20 gave highest predictive ability, and showed the potential to obtain accurate prediction from medium-low coverage GBS in tetraploids.

Optimized Use of Low-Depth Genotyping-by-Sequencing for Genomic Prediction Among Multi-Parental Family Pools and Single Plants in Perennial Ryegrass (Lolium perenne L.).

Ryegrass single plants, bi-parental family pools, and multi-parental family pools are often genotyped, based on allele-frequencies using genotyping-by-sequencing (GBS) assays. GBS assays can be performed at low-coverage depth to reduce costs. However, reducing the coverage depth leads to a higher proportion of missing data, and leads to a reduction in accuracy when identifying the allele-frequency at each locus. As a consequence of the latter, genomic relationship matrices (GRMs) will be biased. This bias in GRMs affects variance estimates and the accuracy of GBLUP for genomic prediction (GBLUP-GP). We derived equations that describe the bias from low-coverage sequencing as an effect of binomial sampling of sequence reads, and allowed for any ploidy level of the sample considered. This allowed us to combine individual and pool genotypes in one GRM, treating pool-genotypes as a polyploid genotype, equal to the total ploidy-level of the parents of the pool. Using simulated data, we verified the magnitude of the GRM bias at different coverage depths for three different kinds of ryegrass breeding material: individual genotypes from single plants, pool-genotypes from F2 families, and pool-genotypes from synthetic varieties. To better handle missing data, we also tested imputation procedures, which are suited for analyzing allele-frequency genomic data. The relative advantages of the bias-correction and the imputation of missing data were evaluated using real data. We examined a large dataset, including single plants, F2 families, and synthetic varieties genotyped in three GBS assays, each with a different coverage depth, and evaluated them for heading date, crown rust resistance, and seed yield. Cross validations were used to test the accuracy using GBLUP approaches, demonstrating the feasibility of predicting among different breeding material. Bias-corrected GRMs proved to increase predictive accuracies when compared with standard approaches to construct GRMs. Among the imputation methods we tested, the random forest method yielded the highest predictive accuracy. The combinations of these two methods resulted in a meaningful increase of predictive ability (up to 0.09). The possibility of predicting across individuals and pools provides new opportunities for improving ryegrass breeding schemes.

Accuracy of Genomic Prediction in a Commercial Perennial Ryegrass Breeding Program.

The implementation of genomic selection (GS) in plant breeding, so far, has been mainly evaluated in crops farmed as homogeneous varieties, and the results have been generally positive. Fewer results are available for species, such as forage grasses, that are grown as heterogenous families (developed from multiparent crosses) in which the control of the genetic variation is far more complex. Here we test the potential for implementing GS in the breeding of perennial ryegrass ( L.) using empirical data from a commercial forage breeding program. Biparental F and multiparental synthetic (SYN) families of diploid perennial ryegrass were genotyped using genotyping-by-sequencing, and phenotypes for five different traits were analyzed. Genotypes were expressed as family allele frequencies, and phenotypes were recorded as family means. Different models for genomic prediction were compared by using practically relevant cross-validation strategies. All traits showed a highly significant level of genetic variance, which could be traced using the genotyping assay. While there was significant genotype × environment (G × E) interaction for some traits, accuracies were high among F families and between biparental F and multiparental SYN families. We have demonstrated that the implementation of GS in grass breeding is now possible and presents an opportunity to make significant gains for various traits.

Estimating genomic heritabilities at the level of family-pool samples of perennial ryegrass using genotyping-by-sequencing.

KEYMESSAGE: By using the genotyping-by-sequencing method, it is feasible to characterize genomic relationships directly at the level of family pools and to estimate genomic heritabilities from phenotypes scored on family-pools in outbreeding species. Genotyping-by-sequencing (GBS) has recently become a promising approach for characterizing plant genetic diversity on a genome-wide scale. We use GBS to extend the concept of heritability beyond individuals by genotyping family-pool samples by GBS and computing genomic relationship matrices (GRMs) and genomic heritabilities directly at the level of family-pools from pool-frequencies obtained by sequencing. The concept is of interest for species where breeding and phenotyping is not done at the individual level but operates uniquely at the level of (multi-parent) families. As an example we demonstrate the approach using a set of 990 two-parent F2 families of perennial ryegrass (Lolium Perenne). The families were phenotyped as a family-unit in field plots for heading date and crown rust resistance. A total of 728 K single nucleotide polymorphism (SNP) variants were available and were divided in groups of different sequencing depths. GRMs based on GBS data showed diagonal values biased upwards at low sequencing depth, while off-diagonals were little affected by the sequencing depth. Using variants with high sequencing depth, genomic heritability for crown rust resistance was 0.33, and for heading date 0.22, and these genomic heritabilities were biased downwards when using variants with lower sequencing depth. Broad sense heritabilities were 0.61 and 0.66, respectively. Underestimation of genomic heritability at lower sequencing depth was confirmed with simulated data. We conclude that it is feasible to use GBS to describe relationships between family-pools and to estimate genomic heritability directly at the level of F2 family-pool samples, but estimates are biased at low sequencing depth.

Nucleotide diversity and linkage disequilibrium of nine genes with putative effects on flowering time in perennial ryegrass (Lolium perenne L.).

Optimization of flowering is an important breeding goal in forage and turf grasses, such as perennial ryegrass (Lolium perenne L.). Nine floral control genes including Lolium perenne CONSTANS (LpCO), SISTER OF FLOWERING LOCUS T (LpSFT), TERMINAL FLOWER1 (LpTFL1), VERNALIZATION1 (LpVRN1, identical to LpMADS1) and five additional MADS-box genes, were analyzed for nucleotide diversity and linkage disequilibrium (LD). For each gene, about 1 kb genomic fragments were isolated from 10 to 20 genotypes of perennial ryegrass of diverse origin. Four to twelve haplotypes per gene were observed. On average, one single nucleotide polymorphism (SNP) was present per 127 bp between two randomly sampled sequences for the nine genes (π = 0.00790). Two MADS-box genes, LpMADS1 and LpMADS10, involved in timing of flowering showed high nucleotide diversity and rapid LD decay, whereas MADS-box genes involved in floral organ identity were found to be highly conserved and showed extended LD. For LpMADS4, LpMADS5, LpCO, LpSFT and LpTFL1, LD extended over the entire region analyzed. The results are compared to previously published results on resistance genes within the same collection of genotypes and the prospects for association mapping of floral control in perennial ryegrass are discussed.

Seasonal changes in the metabolic fingerprint of 21 grass and legume cultivars studied by nuclear magnetic resonance-based metabolomics.

A nuclear magnetic resonance (NMR)-based approach was introduced for metabolic fingerprinting of 21 grass and legume cultivars in the present study. Applying principal component analysis (PCA) on the fingerprints obtained on water extracts, it was possible to elucidate the variation between cultivars and the magnitude of changes in the metabolic fingerprint between the spring growth and the second regrowth. Consequently, the potential of the method for tracking differences and changes related to cultivar and season was demonstrated. In addition, partial least-squares (PLS) regressions revealed correlations between the NMR fingerprints and the value of the grasses as animal feed evaluated as concentration of sugars, neutral detergent fibres (NDF) (R = 0.82), indigestible neutral detergent fibres (iNDF) (R = 0.90), and in vitro organic matter digestibility (IVOMD) (R = 0.75). The correlations between these parameters and the NMR fingerprint could mainly be ascribed to differences in spectral intensities from signals assigned to malic acid (2.40 and 4.70 ppm), choline (3.27 ppm), and glucose (5.24 ppm), and the biochemical rationale for this relation is discussed.

Cloning, characterization and expression analysis of tonoplast intrinsic proteins and glutamine synthetase in ryegrass (Lolium perenne L.).

Perennial ryegrass (Lolium perenne L.) is the most important turf and forage grass species of the temperate regions. It requires substantial input of nitrogen fertilizer for optimum yield. Improved nitrogen use efficiency (NUE) is therefore one of the main breeding targets. However, limited knowledge is currently available on the genes controlling NUE in perennial ryegrass. The aim of the present study was to isolate genes involved in ammonium transport and assimilation. In silico screening of a Lolium EST-library using known sequences of tonoplast intrinsic proteins (TIPs) and cytosolic glutamine synthetase (GS1) revealed a number of homologous sequences. Using these sequences, primers were designed to obtain the full-length sequences by RACE-PCR. Three TIP genes (LpTIP1;1, LpTIP1;2 and LpTIP2;1) and two GS genes (LpGS1a and LpGS1b) were isolated. Characterization in S. cerevisiae confirmed a function in ammonium transport for LpTIP1;1 and LpTIP2;1 and in synthesis of glutamine for LpGS1a and LpGS1b. Cytoimmunochemical studies showed that GS protein was present in the chloroplasts and cytosol of leaf cells, while TIP1 proteins localized to the tonoplast. At the expression level, Lolium GS1 genes responded to N starvation and re-supply in a manner consistent with functions in primary N assimilation and N remobilization. Similarly, the expression of LpTIPs complied with a role in vacuolar ammonium storage. Together, the reported results provide new understanding of the genetic basis for N assimilation and storage in ryegrass.

Experimental systemic contact dermatitis from nickel: a dose-response study.

Systemic contact dermatitis is usually seen as flare-up of previous dermatitis or de novo dermatitis similar to allergic contact dermatitis. Although systemic contact dermatitis from medicaments is a well-established entity, the existence of clinically relevant systemic reactions to oral nickel exposure, in particular systemic reactions to nickel in the daily diet, remains controversial. Several studies have shown that oral exposure to nickel can induce systemic contact dermatitis in nickel-sensitive individuals. In most of these studies, however, the exposure dose of nickel used has been considerably higher than the nickel content in the normal daily diet. The aim of the current investigation was to study dose-response dependency of oral exposure to nickel. In a double-blind, placebo-controlled oral exposure trial, 40 nickel-sensitive persons and 20 healthy (non-nickel-sensitive) controls were given nickel sulfate hexahydrate in doses similar to and greater than the amount of nickel ingested in the normal Danish daily diet. The nickel content in urine and serum before and after oral exposure was measured to determine nickel uptake and excretion. The influence of the amount of nickel ingested on the clinical reactions to oral exposure and on nickel concentrations in serum and urine was evaluated. Among nickel-sensitive individuals, a definite dose-response dependency was seen, following oral exposure to nickel. 7 of 10 nickel-sensitive individuals had cutaneous reactions to oral exposure to 4.0 mg nickel, an amount approximately 10 times greater than the estimated normal daily dietary intake of nickel. 4 of 10 nickel-sensitive individuals had cutaneous reactions to 1.0 mg nickel, a dose which is close to the estimated maximum amount of nickel contained in the daily diet. 4 of 10 nickel-sensitive individuals reacted to 0.3 mg nickel or to the amount equivalent to that contained in a normal daily diet, and 1 of 10 reacted to a placebo. None of the 20 healthy controls had cutaneous reactions to 4.0 mg nickel or to a placebo. Prior to oral exposure, there was no measurable difference in the amount of nickel in the urine or serum of nickel-sensitive persons and healthy controls. Following the oral challenge, the nickel content in the urine and serum of both nickel-sensitive and healthy control individuals was directly related to the dose of nickel ingested.