Hence it might have been free of these viruses due to absence of inoculation. On the other hand, rather high amounts of the allexiviruses were identified in all tested organs, probably due to transmission via seeds. The highest amounts of viral RNA were identified in the roots and cloves.
This new information on the distribution of allexiviruses among the various plant organs provides a solid basis for future research and development of effective detection methods.
In practice, leaves are often sampled for viral infection. It is evident that, at least for garlic allexiviruses, such sampling might result in erroneous estimations of viral infection, due to the relatively low titer in this organ. Relatively high expression of the allexiviruses A, C, E and X was found, while no sequence matches to garlic potyviruses were annotated. Differential expression of four allexiviruses among six organs of garlic. Note the highest proportion of virus expression in roots and cloves.
Our initial results suggest that transcriptome tools provide more sensitive detection methods for new and known viruses in garlic, and shed new light on plant—pathogen interactions and virus distribution in plant tissues.
De-novo assembly of the transcriptome for fertile garlic provides a powerful tool for studying physiological, biochemical and genetic processes in garlic and other Allium crops. The first organ-specific transcript catalogue was generated herein using relatively long reads MiSeq , based on six labeled libraries from vegetative and reproductive tissues. We created two catalogues: 1 an extensive transcriptome consisting of , sequences, and 2 an abundant transcriptome of , contigs, which were annotated and analyzed for GO and metabolic pathways.
These datasets provide versatile resources for garlic genome research, and can be used to associate the transcriptome to developmental processes, understand the regulatory network of these processes, trace the expression profiles of individual genes, and identify reference genes for quantitative expression analyses in various organs and tissues.
This tool is especially important in the elucidation of mechanisms of floral induction, micro- and megasporogenesis, male sterility and seed production in garlic. It will also be useful in the development of new methods for virus detection, as well as in the study of plant—pathogen interactions. Molecular assisted breeding applications will be used in the selection of genotypes with desired traits, produced from true seeds.
Fertile garlic clone 87 was derived from a single seed produced in ; further vegetative propagation guaranteed clonal uniformity. Freshly harvested bulbs were cured and stored under ambient conditions from July to September in an open shed. Experimental design of the sequencing, assembly, annotation, construction and analyses of the organ-specific transcriptome catalogues of Allium sativum. Organography of tissue sampling in fertile garlic genotype Samples were collected in March—July For the vegetative tissues, the CTAB protocol was used [ 56 ].
Carver Biotechnology Center, W. A total of The sets of all sequences that shared at least one k-mer were referred to as components. Comparison to the transcriptomes of the garlic renewal bud [ 27 ], onion [ 26 ] and Tulipa and Lilium [ 24 , 25 ] was performed using the BLASTN algorithm, which allows comparison using a nucleotide query.
GO provides a structured and controlled terminology to describe the gene products, according to three categories: molecular function refers to the biochemical activity of a gene product without stating the location of the event , biological process refers to the biological objective to which the gene product contributes , and cell component refers to the place in the cell where a gene product is active.
Analysis was carried out by comparing the GO terms in the test sample to the GO terms in a background reference. A false discovery rate [ 61 ] with corrected P-value of less than 0. In the search for orthologous genes involved in flowering induction or sulfur metabolism, 22 candidate sequences were retrieved from databases in the NCBI Additional file 4 : Table S2. The cleaned reads from each organ were aligned separately with the abundant transcriptome assembly using the Bowtie aligner [ 63 ].
Since reads are generally shorter than transcripts from which they are derived, a single read may map to multiple genes and isoforms, thus complicating expression analyses. Therefore, the transcript quantification from RNA-Seq data was performed using the Expectation-Maximization method RSEM , which handles read mapping uncertainty with a statistical model by estimating maximum likelihood expression levels [ 58 , 65 ].
Bioconductor EdgeR package [ 66 ] in the R environment was used to identify differentially expressed transcripts for each pair of samples 15 comparisons overall , based on the count estimations for each contig.
Transcripts that were more than fourfold differentially expressed with false discovery- corrected statistical significance of at most 0. The expression patterns of the transcripts in different organs were studied using cluster analysis of the differentially expressed transcripts in at least one pairwise sample comparison.
Following the Trinity protocol [ 64 ], expression normalization was calculated using TMM trimmed mean of M-values , following FPKM fragments per feature kilobase per million reads mapped calculations. Then, hierarchical clustering of transcripts and samples was performed and clusters were extracted using R scripts. The cleaned reads, obtained separately from each organ, were aligned independently to the eight viruses using Bowtie2 aligner version 2.
We wish to thank Dr. Paul Arens Wageningen University, The Netherlands for scientific revision and suggestions during the preparation of the manuscript. Additional file 1: Figure S1. The biological process terms are arranged in semantic space and colored by semantic positioning on the X-axis, the size of bullet points by significance log10 of P-value.
The main processes include responses to various types of stress and metabolite transport. The main processes include catalytic activity and interaction with virus. The biological process terms are arranged in semantic space and colored by semantic positioning on the X-axis, size of bullet points by significance log10 of P-value. The main processes include response to light quality and intensity, photosynthesis, and biosynthesis of the secondary metabolites.
List of the 12 most abundant proteins in the vegetative and reproductive organs of garlic. The expression level FPKM was calculated via the expectation maximization method and TMM normalization trimmed mean of M-value normalization method was applied see Materials and Methods. Note over-representation of three non-annotated proteins in leaves and flowers. Candidate sequences of genes involved in flowering and sulfur metabolism, retrieved from NCBI databases April Competing interests.
This study was supported by the company Classeed Ltd. This publication is fully authorized by the company. RK and AS designed the experiment and drafted the manuscript. AF carried out the bioinformatics analysis. HDR and DE conceived the study, and contributed to the writing of the manuscript. All authors have read and approved the final manuscript. Rina Kamenetsky, Email: li. Hilda Doolittle , Altsheler, Joseph A.
Joseph Alexander , en. I Italian as Author Storia dei musulmani di Sicilia, vol. Bhimrao Ramji , en. Emile , fr. The common English version, corrected by the final committee of the American Bible Union. National American Chemical Society en. American Jewish Committee en. Standard Oil Company Indiana. William Robinson's invention of the track circuit, the fundamental unit which made possible our present automatic block signaling and interlocking systems English as Author American Sabbath Tract Society Tracts on the Sabbath English as Publisher American School of Correspondence Armour Institute of Technology.
Results of Operation. O'Gorman, Mrs. See: Benson, Stella, Anderson, J. Robert Edward , M. The Draughtsman's Handbook of Plan and Map Drawing Including instructions for the preparation of engineering, architectural, and mechanical drawings.
See: St. Christopher Columbus , en. Douglas S. Que se creia existiese en la Cordillera, al sud de Valdivia. Jones, Edwin T. Marsh, and William B. Brooklyn's horror. For the Use of Schools and Families.
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Piercing Lazer - Simple Sight feat. Dustin Dean by JohnnyGuy. My final album and single under Piercing Lazer are out now! Made this a few days back. If you've heard some of my other songs, you'll recognize this. Table 4. Table 5. Table 6 gives a breakdown of the mean unsigned errors MUE in calculated aqueous solvation free energies by solute class.
In Tables 7 and 8 , the mean unsigned errors are broken down by solute class for calculated solvation free energies in nonaqueous solvents and for calculated transfer free energies, respectively. The errors broken down by solvent name are provided in the Supporting Information as well. Table 6. Table 7. Table 8. For neutral data in water, the mean unsigned error on average varies from 0. For neutral data in 90 organic solvents, the mean unsigned error on average varies from 0.
For those classes of neutral compounds for which the SMD model underperforms SM8, the corresponding bulk-electrostatic contributions to the free energy of solvation produced by SMD are usually more negative than those produced by SM8, and the CDS formalism we use for both models cannot fully make up for this feature of the SMD electrostatics. Table 9 shows the mean signed errors in the SMD solvation energies of ions in the four solvents.
Table 10 shows the corresponding mean unsigned errors. Table 9. Table Analysis of the errors on the ionic data indicates generally good agreement of the model predictions with reference data across both solute classes and electronic structure levels. The mean unsigned error averaged over all ions varies from 2. The mean signed errors for both anions and cations in water are positive within any method. The MSEs for ions in methanol can be positive or negative, depending on the method.
Fawcett 92 has presented alternative values of the absolute proton solvation energy in the three organic solvents, and using these values changes the reference values for both cations and anions. They were evaluated in previous work using the cluster pair approximation. This observation is valid for the SM8 data as well Table C-PCM and COSMO solve the nonhomogeneous Poisson equation for an infinite dielectric constant but with scaled dielectric boundary conditions in order to approximate the result for a finite dielectric constant.
This is a better approximation at high dielectric constant e. Even for a very low dielectric constant e. For all of the SMD electrostatic calculations in Gaussian03, GAMESS, and NWChem, we specified the solvent only by its dielectric constant with the solvent radius set to zero, and the program default nonelectrostatic contributions were turned off while the SMD nonelectrostatic contributions were added to the solvation free energies.
We specified the SMD atomic Coulomb radii instead of the default radii used by these programs. Table 12 shows the corresponding deviations in solvation electrostatic energies for ionic and neutral solutes in various media. Note that the differences in Table 12 between the results with essentially the same electrostatics algorithms as implemented in different programs are mostly due to the different tessellation algorithms used by these programs cf.
There is more than one united atom model in Gaussian The UAHF radii are recommended in the Gaussian03 manual for calculations of free energies of solvation with the scfvac keyword invoked we used this keyword in calculations with both types of radii, UA0 and UAHF. To test all of the continuum models we used all the data for ions in acetonitrile, DMSO, methanol, and water as described above.
However, tests for neutrals were performed only for those 17 solvents including acetonitrile, DMSO, and water that are available for IEF-PCM in Gaussian03 actually Gaussian03 supports 21 solvents, but we have neutral data in only 17 of them; see Table 1 ; for example, although methanol is also available in Gaussian03, we have no neutral data for this solvent. Such large errors indicate that the default settings for the IEF-PCM algorithm in Gaussian03 cannot be recommended for the quantitative prediction of solvation free energies.
Nevertheless, the resulting errors in the solvation free energies of tested compounds remain unacceptably large. The very poor performance of the COSMO-N06d model is mainly due to the default tessellation grid, which is inadequately coarse. The ionic data in Table 13 are averaged over cations and anions in all solvents.
Table 14 breaks their mean unsigned errors down into categories. As compared to previous models, the SMD model is more accurate than SM8 for nonaqueous anions, but not for the other three categories. It is more accurate than the default models of GAMESS and NWChem for all four categories, and it is more accurate than the default model of Gaussian03 for all categories except nonaqueous anions, for which the default model of Gaussian03 uses different parameters than for cations.
Very recently, Ginovska et al. Table 15 shows errors for this larger set; the trends and magnitudes are the same as in Table In order to clarify the differences between SMD and alternative continuum approaches to the computation of solvation free energies, it is instructive to consider a number of different models that have been described in the literature based on IEF-PCM electrostatics 4 or, in some cases, the earlier but closely related PCM model 2.
Several choices for cavity construction have been explored in the literature, as described in more detail momentarily, but these choices have sometimes not been specified in subsequent applications by nondevelopers. In addition to alternative cavity construction protocols, several different strategies for accounting for non-bulk-electrostatic solvation effects have also been considered. However, as noted above, implementations of PCM or IEF-PCM electrostatics in different electronic structure programs may include different default options for handling these components, so that researchers who report results by simply labeling them as IEF-PCM are not fully specifying the calculations.
These points having been made, we turn now to the question of modeling the nonbulk-electrostatic component of the solvation free energy. Floris et al. Floris and Tomasi used the pair potential parameters of Claverie and co-workers, which were fit to reproduce free energies of vaporization and sublimation in condensed phases. This approach continues to be used by default in Gaussian Also used by default is a model that predicts free energies of cavitation based upon the scaled particle theory of Pierotti , as modified by Claverie.
In , however, Barone, Cossi, and Tomasi 67 proposed a modification to the electrostatic portion of PCM calculations to improve the accuracy of predicted aqueous solvation free energies. In particular, they proposed a new cavity generation protocol the original PCM electrostatic cavity was built from spheres having Bondi radii scaled by a factor of 1. In the UAHF scheme, spheres are not placed on hydrogen atoms, but spheres on heavy atoms have radii that depend on the number of H atoms attached.
In addition, atomic radii are dependent on formal charge. Assigning hybridization and charge is accomplished heuristically. Note that SMD parameters do not depend on charges, hybridization states, or classifications of other atoms as attached or unattached and thus there are no discontinuities when the model is applied along reaction paths.
The errors on the larger data set suggest that the original UAHF training set lacks broad coverage of organic functionality. The MST models were originally developed for predicting the solvation free energies of neutral solutes in water, octanol, chloroform, and carbon tetrachloride using PCM electrostatics. In the electrostatic portion, Pauling radii are scaled by solvent-dependent factors ranging from 1.
In addition, in water, N, O, and S atoms take on different radii depending on the numbers of attached hydrogen atoms. In the nonelectrostatic portion, no scaling factor is applied to the cavity. In the case of ionic solvation free energies in water, Curutchet et al. Several other combinations of IEF-PCM electrostatics with different approaches to compute nonelectrostatic solvation free energies have appeared.
For water, octanol, chloroform, and carbon tetrachloride, Curutchet et al. The use of other classical pair potentials taken from commonly available force fields did not improve this situation. Considering exclusively water as solvent, other groups have explored variations on the PCM scheme.
In particular, Shimizu et al. The terms corresponding to repulsion in eq 20 do not appear in eq 24 ; their effect is absorbed into the empirical parameters in the optimization process. Shimizu et al. Ions were not considered. A different aqueous variation has been reported by Basilevsky et al. The 23 atomic types were taken from the MMFF force field. In a more limited study, de O.
Mendes et al. Having summarized all of the various approaches to combine IEF-PCM or PCM electrostatics with nonelectrostatic protocols to predict free energies of solvation, we should of course mention that there are other quantum mechanical continuum solvation models that have the same goal that do not follow the PCM or IEF-PCM procedures.
We refer interested readers to recent reviews. Given the various results summarized above, it should be clear that it is possible to combine PCM and IEF-PCM electrostatics with different protocols for the computation of the non-bulk-electrostatic free energy of solvation so as to arrive at a complete model that provides quantitatively useful free energies of solvation.
Such models, however, inevitably rely on some parametrization against experimental data to achieve reasonable accuracy, e.
When large sets of solvation data are available, as is the situation for chloroform, for example, solvent-specific solvation models can be created, like chloroform-specific MST and SM5. The other models are universal in their philosophy : that is, were sufficient data to be available, accurate parameters could presumably be determined for any solvent; unfortunately, data in solvents other than the few mentioned above in this section tend to be sparse.
To address this challenge, SMD relies on parametric functions as opposed to constants that take as input physical properties associated with a given solvent or more generalized condensed phase. This approach permits the construction of an experimental training set that combines data from 90 different solvents, guaranteeing broad coverage of solute and solvent functionality, and significantly reduces the potential for solvent-specific parameters to be underdetermined.
Upon parametrization, the resulting model is immediately applicable to any condensed phase for which the relevant solvent physical properties are known or can reasonably be estimated. Thus, while SMD is no more nor less accurate than other well parametrized quantum mechanical solvation models based on PCM or IEF-PCM electrostatics, it is the only such model that is universally defined for any solvent and moreover available for immediate application in a number of widely distributed free and commercial electronic structure packages.
It is also more accurate than the default nonuniversal models of several popular programs. Using the training set of solvation free energies including data for neutral solutes in water, data for neutral solutes in 90 nonaqueous solvents, neutral transfer free energies between water and 15 organic solvents, and data for ions in acetonitrile, dimethyl sulfoxide, methanol, and water, a new universal implicit solvent model called SMD has been developed for predicting solvation free energies of neutral and ionic solutes in water and in nonaqueous solvents.
For nonaqueous solvents, SMD uses a small set of solvent descriptors that characterize the properties of the solvent. The SMD model is based on a self-consistent reaction field treatment of bulk electrostatics that involves an integration of the nonhomogeneous Poisson equation and on a cavity-dispersion-solvent-structure protocol for the nonelectrostatic contribution to the free energy of solvation. The model parameters are intrinsic Coulomb radii for the bulk electrostatic calculation and atomic surface tension coefficients for the CDS contribution.
Unlike the earlier SM8 model based on the generalized Born approximation for bulk electrostatics, the density-based solvation model SMD does not utilize partial atomic charges and, therefore, the applicability of the SMD model does not depend on the availability of reasonable charges for a given level of theory. Supporting Information.
A direct utilization of ab initio molecular potentials for the prevision of solvent effects. A method is presented which utilizes the calcn. No limitations are imposed on the compn. Several levels of approxn.
A recently proposed procedure for introducing solvent effects in the mol. Hamiltonian of a solute is re-elaborated to get approx. The basic feature of the original procedure, i. The meaning of supplementary assumptions, introduced in classical calcn. American Institute of Physics. The authors present a new integral equation formulation of the polarizable continuum model PCM which allows one to treat in a single approach dielecs.
Integral equation methods may be used with success also for the latter cases, which are usually studied with three-dimensional methods, by far less competitive in terms of computational effort. The authors present the theor. PCM versions for isotropic solvents, and a good efficiency for calcns.
In continuum solvation models the definition of a cavity that embeds the solute mol. The correction strategies developed so far can be shown to work insufficiently, since they only correct the global charge defect, but lead to considerable local errors. The present paper will be focused on the theor. As further analyses, the introduction of Pauli repulsion term will be considered, and the implications all these effects have on mol.
The new approach has been implemented within the framework of the polarizable continuum model PCM. American Chemical Society. The authors present the full implementation of the integral equation formalism IEF they have recently formulated to treat solvent effects.
The method exploits a single common approach for dielecs. The authors report here an anal. In particular, the authors report, for isotropic liqs. Elsevier Science B. The integral equation formalism IEF is a recent method the grounds have been elaborated at the beginning of addressed to solve the electrostatic solvation problem at the QM level with the aid of apparent surface charges ASC. IEF uses a new formalism of this problem, based on integral operators never used before in the chem. In this overview we emphasize the good performances of IEF at the lowest level of its potentialities, i.
Finally we present a new IEF implementation of the nonequil. ASC formulations. This version exploits a new definition of surface elements area, and a direct formulation of the electrostatic self-consistent problem.
Non-electrostatic contributions to the mol. Several possible definitions of the mol. Google Scholar There is no corresponding record for this reference. A new method for calcg.
In this method, the solvent is treated as a homogeneous dielec. The solvation energy is presented in the Hartree-Fock-Roothaan form, which can be incorporated into both MO and d. This approach yields on the av. CPU time compared to the gas-phase calcns. It allows Hartree-Fock HF , d. The calcd. The conductor-like solvation model, as developed in the framework of the polarizable continuum model PCM , has been reformulated and newly implemented in order to compute energies, geometric structures, harmonic frequencies, and electronic properties in soln.
Particular attention is devoted to large systems requiring suitable iterative algorithms to compute the solvation charges: the fast multipole method FMM has been extensively used to ensure a linear scaling of the computational times with the size of the solute.
Verlag Helvetica Chimica Acta. In this work, we present algorithmic modifications and extensions to our quantum-mech. The theory of conductor-like screening, modified and extended for quantum-mech. Our previous work has emphasized the implementation of this model by way of a distributed multipole approach for handling the effects of outlying charge. Will Kinsella - Temple Lane Tapes Eddy Yamamoto - This Guy Yesterday, Comments 0 Read More.
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