Maximum Likelihood Values Research Articles

Redescription of Semisulcospira reticulata (Mollusca, Semisulcospiridae) with description of a new species from Lake Biwa, Japan

Semisulcospira Boettger, 1886 is a freshwater snail genus divergent in Lake Biwa, Japan. Although recent taxonomic studies of the genus have arranged taxonomic accounts of many species in the lake, our knowledge of morphological traits has still been insufficient in S. reticulata Kajiyama & Habe, 1961, which belongs to the S. niponica-group in the genus. Among the various habitats of the lacustrine species, in addition, the species richness of this group in coastal sandy mud areas of the lake has not been completely clarified. In this study, we revisited the taxonomic account of S. reticulata and described a new S. niponica-group species, S. nishimuraisp. nov., from Lake Biwa by evaluating the genetic and morphological relationships within the group. The reconstructed maximum likelihood and singular value decomposition quartets trees, and ADMIXTURE analyses using genome-wide SNP data strongly supported the genetic distinctiveness of most S. niponica-group species. The Random Forest classification showed that S. reticulata possesses a unique, large protoconch without distinct keels, and that S. nishimuraisp. nov. is characterized by a small, less elongated teleoconch and tiny protoconch. The large protoconch of S. reticulata and the narrow radulae of S. reticulata and S. nishimuraisp. nov. suggest their specialization in life history and feeding habits, respectively. The discovery of the new species from sandy mud substrates highlights niche differentiation among Semisulcospira species, and provides new insights into the diversification of the genus in ancient lakes.

Transition mutation bias is crucial to adaptive extended spectrum beta lactamase (ESBL) resistance evolution

The importance of slow accumulation of mutation in the nucleic acids of bacteria and the possibility of organismal transcriptional modification to suit their adaptation are key drivers favouring natural selection and subsequently adaptive evolution. This study was aimed at providing insight into factors influencing adaptive extended spectrum beta lactamase (ESBL) resistance evolution. A total of twenty-six (26) extended spectrum beta lactamase-producing Gram-negative bacteria isolated in our previous study were subjected to uniplex and multiplex polymerase chain reaction (PCR) and sequencing prior to mutation discovery analyses, while the maximum likelihood value, transition-transversion ratio, tajimas neutrality test, nucleotide diversity and selection analyses were estimated following standard recommended protocols. Results obtained depict the PCR discriminated ESBL alleles as; TEM (n = 11.5 %), CTX-M (n = 15.4 %), SHV (n = 19.2 %) while the co-occurred ESBL alleles were estimated as CTX-M and TEM (n = 3.85 %), CTX-M and SHV (n = 15.4 %), TEM and SHV (n = 23.1 %), CTX-M, TEM and SHV (n = 11.5 %). The transition, transversion, deletion and insertion distribution pattern were evaluated as; TEM (46, 39,11 and 4 %), SHV (50, 31, 8 and 11 %) and CTX-M (60, 21,12 and 7 %) (p < 0.05) respectively. The maximum likelihood value, transition-transversion ratio, tajimas neutrality test, nucleotide diversity and selection analyses for TEM, SHV and CTX-M were (−8436, 1.18, 5.2, 62 % and 84.9 %,), (−8321, 1.60, 5.4, 68.9 % and 97.8 %) and (−7284, 2.86, 6.0, 55.2 % and 77.2 %) sequentially. Our findings therefore have shown that adaptive ESBL resistance evolution is driven by transition mutation, positive natural selection and ESBL gene flow. It is thus imperative to state that understanding these adaptive resistance driven factors and how they operate is crucial to deciphering the fundamental principles of adaptive evolution that might help circumvent the global challenges of antibiotic resistance.

A method for background correction in 10Be detection: Evaluation of indirect isobaric interference by 7Be generated at the entrance window of a gas counter

This report presents a procedure for background correction of indirect isobaric interference by 10B in accelerator mass spectrometry of cosmogenic 10Be. A gas counter with an absorber cell for 10B is used as a detector. Injected ions are detected by two anode plates aligned in the main ionization chamber to plot the signals on a two-dimensional spectrum of loss and residual energies. Using this configuration, the tail of 10B events that manage to pass through the absorber cell can be separated from the 10Be events, but the total counts in the 10Be region are increased by 7Be generated from the reaction of 10B(1H,4He)7Be due to hydrogen attached on the surface of the entrance window of the absorber cell. Since the number of 7Be events are proportional to the counts of 4He events, we can evaluate the interference via statistical analyses for correlations between counting data for multiple regions of interest on the two-dimensional spectra. This correction results in an increase in uncertainty for the counting statistics, but improves the accuracy of the maximum likelihood value of the 10Be/9Be isotopic ratios.

Development of methodology for scenario analysis of investment projects of enterprises of the mineral resource complex

Theoretical and applied aspects of scenario analysis of investment projects of enterprises in the mineral resource sector of the economy are considered, its advantages and disadvantages are analyzed. Taking into account the organizational and economic features of mineral resources management, a number of new modifications of the scenario analysis method, aimed at solving an urgent problem - reducing the information uncertainty in assessing the expected efficiency and risk of investment projects, are proposed. The peculiarity of the proposed new modifications is the use of the interval-probabilistic approach in the implementation of the scenario analysis procedure. This approach is based on a moderately pessimistic system of preferences in obtaining point values of the investment project initial parameters. Fishburn estimates and the hierarchy analysis method were used to reduce subjective uncertainty. The maximum likelihood values in the sense of the maximum a priori probability are used as expected estimates. An additional indicator of risk assessment, which characterizes the probability of the event that the net present value of the project will take a value less than the specified one, is proposed. When analyzing one project, this indicator is more informative than the standard deviation. A statistical hypothesis was tested on the improvement of the validity of investment decisions developed using the modified scenario analysis method compared to the standard method.

Safety and efficacy of leriglitazone for preventing disease progression in men with adrenomyeloneuropathy (ADVANCE): a randomised, double-blind, multi-centre, placebo-controlled phase 2–3 trial

Adult patients with adrenoleukodystrophy have a poor prognosis owing to development of adrenomyeloneuropathy. Additionally, a large proportion of patients with adrenomyeloneuropathy develop life-threatening progressive cerebral adrenoleukodystrophy. Leriglitazone is a novel selective peroxisome proliferator-activated receptor gamma agonist that regulates expression of key genes that contribute to neuroinflammatory and neurodegenerative processes implicated in adrenoleukodystrophy disease progression. We aimed to assess the effect of leriglitazone on clinical, imaging, and biochemical markers of disease progression in adults with adrenomyeloneuropathy. ADVANCE was a 96-week, randomised, double-blind, placebo-controlled, phase 2-3 trial done at ten hospitals in France, Germany, Hungary, Italy, the Netherlands, Spain, the UK, and the USA. Ambulatory men aged 18-65 years with adrenomyeloneuropathy without gadolinium enhancing lesions suggestive of progressive cerebral adrenoleukodystrophy were randomly assigned (2:1 without stratification) to receive daily oral suspensions of leriglitazone (150 mg starting dose; between baseline and week 12, doses were increased or decreased to achieve plasma concentrations of 200 μg·h/mL [SD 20%]) or placebo by means of an interactive response system and a computer-generated sequence. Investigators and patients were masked to group assignment. The primary efficacy endpoint was change from baseline in the Six-Minute Walk Test distance at week 96, analysed in the full-analysis set by means of a mixed model for repeated measures with restricted maximum likelihood and baseline value as a covariate. Adverse events were also assessed in the full-analysis set. This study was registered with ClinicalTrials.gov, NCT03231878; the primary study is complete; patients had the option to continue treatment in an open-label extension, which is ongoing. Between Dec 8, 2017, and Oct 16, 2018, of 136 patients screened, 116 were randomly assigned; 62 [81%] of 77 patients receiving leriglitazone and 34 [87%] of 39 receiving placebo completed treatment. There was no between-group difference in the primary endpoint (mean [SD] change from baseline leriglitazone: -27·7 [41·4] m; placebo: -30·3 [60·5] m; least-squares mean difference -1·2 m; 95% CI -22·6 to 20·2; p=0·91). The most common treatment emergent adverse events in both the leriglitazone and placebo groups were weight gain (54 [70%] of 77 vs nine [23%] of 39 patients, respectively) and peripheral oedema (49 [64%] of 77 vs seven [18%] of 39). There were no deaths. Serious treatment-emergent adverse events occurred in 14 (18%) of 77 patients receiving leriglitazone and ten (26%) of 39 patients receiving placebo. The most common serious treatment emergent adverse event, clinically progressive cerebral adrenoleukodystrophy, occurred in six [5%] of 116 patients, all of whom were in the placebo group. The primary endpoint was not met, but leriglitazone was generally well tolerated and rates of adverse events were in line with the expected safety profile for this drug class. The finding that cerebral adrenoleukodystrophy, a life-threatening event for patients with adrenomyeloneuropathy, occurred only in patients in the placebo group supports further investigation of whether leriglitazone might slow the progression of cerebral adrenoleukodystrophy. Minoryx Therapeutics.

Taxonomic status of the disjunct populations of the resin bee Anthidiellum breviusculum (Pérez, 1890) s.l. in the Mediterranean (Apoidea: Anthidiini)

ABSTRACT The resin bee Anthidiellum troodicum (Mavromoustakis, 1949) was originally described from Cyprus as a subspecies of the West Mediterranean Anthidiellum breviusculum (Pérez, 1890). Although the distinctiveness of these two taxa at the species level was recognised by Andreas Müller in 1996, this finding has not found its way into the literature. Examination of new material confirms the distinct taxonomic identity of these two species, with A. troodicum being widely distributed in the eastern and A. breviusculum in the western Mediterranean, with no geographic overlap. Additionally, the geographically separated population in North Africa was found to be a distinct species, described here as A. africanum Kasparek sp. nov. While phenotypic characteristics would place it close to A. troodicum, a phylogenetic tree inferred from the mitochondrial cytochrome c oxidase I (COI) gene fragment (658 bp DNA barcodes) indicates that it is closer to A. breviusculum. The clades representing these three taxa are well supported in a bootstrap analysis, with maximum likelihood values between 87 and 100%. The average genetic distance between A. africanum sp. nov. and A. breviusculum is low (at 2.4%), while it is higher between A. troodicum and A. africanum (at 4.7%) and between A. troodicum and A. breviusculum (at 6.2%). http://www.zoobank.org/urn:lsid:zoobank.org:pub:FE72A30D-7893-46D4-A34F-24A0C32BB190

Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physics.

Calibration is a common experimental physics problem, whose goal is to infer the value and uncertainty of an unobservable quantity Z given a measured quantity X. Additionally, one would like to quantify the extent to which X and Z are correlated. In this Letter, we present a machine learning framework for performing frequentist maximum likelihood inference with Gaussian uncertainty estimation, which also quantifies the mutual information between the unobservable and measured quantities. This framework uses the Donsker-Varadhan representation of the Kullback-Leibler divergence-parametrized with a novel Gaussian ansatz-to enable a simultaneous extraction of the maximum likelihood values, uncertainties, and mutual information in a single training. We demonstrate our framework by extracting jet energy corrections and resolution factors from a simulation of the CMS detector at the Large Hadron Collider. By leveraging the high-dimensional feature space inside jets, we improve upon the nominal CMS jet resolution by upward of 15%.

A parallel sampling algorithm for some nonlinear inverse problems

AbstractWe derive a parallel sampling algorithm for computational inverse problems that present an unknown linear forcing term and a vector of nonlinear parameters to be recovered. It is assumed that the data are noisy and that the linear part of the problem is ill-posed. The vector of nonlinear parameters ${m} $ is modeled as a random variable. A dilation parameter $\alpha $ is used to scale the regularity of the linear unknown and is also modeled as a random variable. A posterior probability distribution for $({m}, \alpha )$ is derived following an approach related to the maximum likelihood (ML) regularization parameter selection (Galatsanos, N. P. &amp; Katsaggelos, A. K. (1992). Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation. IEEE Trans. Image Process., 1, 322–336). A major difference in our approach is that, unlike in Galatsanos, N. P. &amp; Katsaggelos, A. K. (1992, Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation. IEEE Trans. Image Process., 1, 322–336), we do not limit ourselves to the maximum likelihood value of $\alpha $. We then derive a parallel sampling algorithm where we alternate computing proposals in parallel and combining proposals to accept or reject them as in Calderhead, B. (2014, A general construction for parallelizing metropolis- hastings algorithms. Proc. Natl Acad Sci, 111, 17408–17413). This algorithm is well suited to problems where proposals are expensive to compute. We then apply it to an inverse problem in seismology. We show how our results compare favorably to those obtained from the ML, the Generalized Cross Validation and the Constrained Least Squares algorithms.

Enhanced PSK-LoRa

This letter introduces enhanced phase shift keying Long Range (ePSK-LoRa) as an alternative to classical modulation approaches for low power wide area networks. By employing different combinations of phase and frequency shifts of the orthogonal chirp and using signal averaging, ePSK-LoRa achieves higher energy efficiency and higher spectral efficiency (SE) relative to the state-of-the-art schemes. Besides comprehensively elucidating the orthogonality of the transmitted symbols, we present maximum likelihood and absolute value detectors. The simulation results depict that besides affording higher SE, ePSK-LoRa requires lower signal-to-noise ratio per bit for correct detection making it a viable alternative to the classical approaches.

Development and evaluation of the bootstrap resampling technique based statistical prediction model for Covid-19 real time data : A data driven approach

The objective of the article is to develop ‘earlyR’ package based novel coronavirus disease (COVID-19) forecasting model. The reported COVID-19 serial interval data is applied for obtaining maximum likelihood value of the reproduction number (R0) using maximum likelihood approach and ‘projections’ package is applied for getting trajectories of epidemic curve. The minimum, median, mean and maximum projected value of R0 with 95% confidence interval (CI) is obtained by using bootstrap resampling strategy and the predicted cumulative probable count of new cases is also presented with different quantile. To validate the results with real scenario, the past COVID-19 data is considered. The % error rate ranges from -7.91% to 21.27% for the developed model for the five Indian States.

Statistical Modeling of Energy Harvesting in Hybrid PLC-WLC Channels

This work introduces statistical models for the energy harvested from the in-home hybrid power line-wireless channel in the frequency band from 0 to 100 MHz. Based on numerical analyses carried out over the data set obtained from a measurement campaign together with the use of the maximum likelihood value criterion and the adoption of five distinct power masks for power allocation, it is shown that the log-normal distribution yields the best model for the energies harvested from the free-of-noise received signal and from the additive noise in this setting. Additionally, the total harvested energy can be modeled as the sum of these two statistically independent random variables. Thus, it is shown that the energies harvested from this kind of hybrid channel is an easy-to-simulate phenomenon when carrying out research related to energy-efficient and self-sustainable networks.

Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits

Breeding programs of the species Coffea canephora rely heavily on the significant genetic variability between and within its two varietal groups (conilon and robusta). The use of hybrid families and individuals has been less common. The objectives of this study were to evaluate parents and families from the populations of conilon, robusta, and its hybrids and to define the best breeding and selection strategies for productivity and disease resistance traits. As such, 71 conilon clones, 56 robusta clones, and 20 hybrid families were evaluated over several years for the following traits: vegetative vigor, incidence of rust and cercosporiosis, fruit ripening time, fruit size, plant height, canopy diameter, and yield per plant. Components of variance and genetic parameters were estimated via residual maximum likelihood (REML) and genotypic values were predicted via best linear unbiased prediction (BLUP). Genetic variability among parents (clones) and hybrid families was detected for most of the evaluated traits. The Mulamba-Rank index suggests potential gains up to 17% for the genotypic aggregate of traits in the hybrid population. An intrapopulation recurrent selection within the hybrid population would be the best breeding strategy because the genetic variability, narrow and broad senses heritabilities and selective accuracies for important traits were maximized in the crossed population. Besides, such strategy is simple, low cost and quicker than the concurrent reciprocal recurrent selection in the two parental populations, and this maximizes the genetic gain for unit of time.

Matching Bayesian and frequentist coverage probabilities when using an approximate data covariance matrix

ABSTRACT Observational astrophysics consists of making inferences about the Universe by comparing data and models. The credible intervals placed on model parameters are often as important as the maximum a posteriori probability values, as the intervals indicate concordance or discordance between models and with measurements from other data. Intermediate statistics (e.g. the power spectrum) are usually measured and inferences are made by fitting models to these rather than the raw data, assuming that the likelihood for these statistics has multivariate Gaussian form. The covariance matrix used to calculate the likelihood is often estimated from simulations, such that it is itself a random variable. This is a standard problem in Bayesian statistics, which requires a prior to be placed on the true model parameters and covariance matrix, influencing the joint posterior distribution. As an alternative to the commonly used independence Jeffreys prior, we introduce a prior that leads to a posterior that has approximately frequentist matching coverage. This is achieved by matching the covariance of the posterior to that of the distribution of true values of the parameters around the maximum likelihood values in repeated trials, under certain assumptions. Using this prior, credible intervals derived from a Bayesian analysis can be interpreted approximately as confidence intervals, containing the truth a certain proportion of the time for repeated trials. Linking frequentist and Bayesian approaches that have previously appeared in the astronomical literature, this offers a consistent and conservative approach for credible intervals quoted on model parameters for problems where the covariance matrix is itself an estimate.

Epidemic size, trend and spatiotemporal mapping of SARS-CoV-2 using geographical information system in Alborz Province, Iran

BackgroundThe first confirmed cases of COVID-19 in Iran were reported in Qom city. Subsequently, the neighboring provinces and gradually all 31 provinces of Iran were involved. This study aimed to investigate the case fatility rate, basic reproductive number in different period of epidemic, projection of daily and cumulative incidence cases and also spatiotemporal mapping of SARS-CoV-2 in Alborz province, Iran.MethodsA confirmed case of COVID-19 infection was defined as a case with a positive result of viral nucleic acid testing in respiratory specimens. Serial interval (SI) was fitted by gamma distribution and considered the likelihood-based R0 using a branching process with Poisson likelihood. Seven days average of cases, deaths, doubling times and CFRs used to draw smooth charts. kernel density tool in Arc GIS (Esri) software has been employed to compute hot spot area of the study site.ResultsThe maximum-likelihood value of R0 was 2.88 (95%, CI: 2.57–3.23) in the early 14 days of epidemic. The case fatility rate for Alborz province (Iran) on March 10, was 8.33% (95%, CI:6.3–11), and by April 20, it had an increasing trend and reached 12.9% (95%,CI:11.5–14.4). The doubling time has been increasing from about two days and then reached about 97 days on April 20, 2020, which shows the slowdown in the spread rate of the disease. Also, from March 26 to April 2, 2020 the whole Geographical area of Karj city was almost affected by SARS-CoV-2.ConclusionsThe R0 of COVID-19 in Alborz province was substantially high at the beginning of the epidemic, but with preventive measures and public education and GIS based monitoring of the cases,it has been reduced to 1.19 within two months. This reduction highpoints the attainment of preventive measures in place, however we must be ready for any second epidemic waves during the next months.

Phylogeny of the supertribe Nebriitae (Coleoptera, Carabidae) based on analyses of DNA sequence data.

The phylogeny of the carabid beetle supertribe Nebriitae is inferred from analyses of DNA sequence data from eight gene fragments including one nuclear ribosomal gene (28S), four nuclear-protein coding genes (CAD, topoisomerase 1, PEPCK, and wingless), and three mitochondrial gene fragments (16S + tRNA-Leu + ND1, COI (“barcode” region) and COI (“Pat/Jer” region)). Our taxon sample included 264 exemplars representing 241 species and subspecies (25% of the known nebriite fauna), 39 of 41 currently accepted genera and subgenera (all except Notiokasis and Archileistobrius), and eight outgroup taxa. Separate maximum likelihood (ML) analyses of individual genes, combined ML analyses of nuclear, nuclear protein-coding, and mitochondrial genes, and combined ML and Bayesian analyses of the eight-gene-fragment matrix resulted in a well-resolved phylogeny of the supertribe, with most nodes in the tree strongly supported. Within Nebriitae, 167 internal nodes of the tree (out of the maximum possible 255) are supported by maximum-likelihood bootstrap values of 90% or more. The tribes Notiophilini, Opisthiini, Pelophilini, and Nebriini are well supported as monophyletic but relationships among these are not well resolved. Nippononebria is a distinct genus more closely related to Leistus than Nebria. Archastes, Oreonebria, Spelaeonebria, and Eurynebria, previously treated as distinct genera by some authors, are all nested within a monophyletic genus Nebria. Within Nebria, four major clades are recognized: (1) the Oreonebria Series, including eight subgenera arrayed in two subgeneric complexes (the Eonebria and Oreonebria Complexes); (2) the Nebriola Series, including only subgenus Nebriola; (3) the Nebria Series, including ten subgenera arrayed in two subgeneric complexes, the Boreonebria and Nebria Complexes, with the latter further subdivided into three subgeneric subcomplexes (the Nebria, Epinebriola, and Eunebria Subcomplexes)); and (4) the Catonebria Series, including seven subgenera arrayed in two subgeneric complexes (the Reductonebria and Catonebria Complexes). A strong concordance of biogeography with the inferred phylogeny is noted and some evident vicariance patterns are highlighted. A revised classification, mainly within the Nebriini, is proposed to reflect the inferred phylogeny. Three genus-group taxa (Nippononebria, Vancouveria and Archastes) are given revised status and seven are recognized as new synonymies (Nebriorites Jeannel, 1941 and Marggia Huber, 2014 = Oreonebria Daniel, 1903; Pseudonebriola Ledoux & Roux, 1989 = Boreonebria Jeannel, 1937; Patrobonebria Bänninger, 1923, Paranebria Jeannel, 1937 and Barbonebriola Huber & Schmidt, 2017 = Epinebriola Daniel & Daniel, 1904; and Asionebria Shilenkov, 1982 = Psilonebria Andrewes, 1923). Six new subgenera are proposed and described for newly recognized clades: Parepinebriola Kavanaugh subgen. nov. (type species: Nebria delicata Huber & Schmidt, 2017), Insulanebria Kavanaugh subgen. nov. (type species: Nebria carbonaria Eschscholtz, 1829), Erwinebria Kavanaugh subgen. nov. (type species Nebria sahlbergii Fischer von Waldheim, 1828), Nivalonebria Kavanaugh subgen. nov. (type species: Nebria paradisi Darlington, 1931), Neaptenonebria Kavanaugh subgen. nov. (type species: Nebria ovipennis LeConte, 1878), and Palaptenonebria Kavanaugh subgen. nov. (type species: Nebria mellyi Gebler, 1847). Future efforts to better understand relationships within the supertribe should aim to expand the taxon sampling of DNA sequence data, particularly within subgenera Leistus and Evanoleistus of genus Leistus and the Nebria Complex of genus Nebria.

Prediction of daily and cumulative cases for COVID-19 infection based on reproductive number (R0) in Karnataka: a data-driven analytics

To estimate the reproductive number (R0) of the coronavirus in the present scenario and to predict the incidence of daily and probable cumulative cases, by 20 August, 2020 for Karnataka state in India. The model used serial interval with a gamma distribution and applied ‘early R’ to estimate the R0 and ‘projections’ package in R program. This was performed to mimic the probable cumulative epidemic trajectories and predict future daily incidence by fitting the data to existing daily incidence and the estimated R0 by a model based on the assumption that daily incidence follows Poisson distribution. The maximum-likelihood (ML) value of R0 was 2.242 for COVID-19 outbreak, as on June 2020. The median with 95% CI of R0 values was 2.242 (1.50–3.00) estimated by bootstrap resampling method. The expected number of new cases for the next 60 days would progressively increase, and the estimated cumulative cases would reach 27,238 (26,008–28,467) at the end of 60th day in the future. But, if R0 value was doubled the estimated total number of cumulative cases would increase up to 432,411 (400,929–463,893) and if, R0 increase by 50%, the cases would increase up to 86,386 (80,910–91,861). The probable outbreak size and future daily cumulative incidence are largely dependent on the change in R0 values. Hence, it is vital to expedite the hospital provisions, medical facility enhancement work, and number of random tests for COVID-19 at a very rapid pace to prepare the state for exponential growth in next 2 months.

Phylogenetics of native conifer species in Vietnam based on two chloroplast gene regions rbcL and matK

We used two chloroplast gene regions (matK and rbcL) as a tool for the identification of 33 local conifer species. All 136 sequences, 101 newly generated (14 species for gene matK; 16 species for gene rbcL) and 35 retrieved from the GenBank, were used in the analysis. The highest genetic distance (matK region) was recorded between the species in Cupressaceae with an average of 5% (0.1–8.5), Podocarpaceae with an average of 6% (0–8.5), Taxaceae with an average of 5% (0.2–0.5) and Pinaceae with an average of 20.4% (0.8–54.1). The rbcL region showed a low genetic distance between the species in Cupressaceae 2% (0–3.3), Podocarpaceae 3% (0.6–3.4), Taxaceae 1% (0–2.1) and Pinaceae 1.2% (0–5.82). The phylogenetic analyses using the Maximum likelihood (ML) and Bayesian inference (BI) bootstrap values obtained at the branching nodes of each species ranged from 62 to 100% (Maximum likelihood bootstrap – MLBS and Bayesian posterior probabilities – BPP) for the matK gene; from 66 to 100% (MLBS) and 60 to 100% (BPP) for the rbcL region. The rbcL region was not identified between the species of Taxaceae and Cephalotaxaceae. The matK gene region was very clear in the different species among the families (Cupressaceae, Podocarpaceae, and Cephalotaxaceae) and unsuitable for identifying closely related species in Amentotaxus (Taxaceae) and Pinus (Pinaceae). The gene (matK) is a useful tool as a barcode in the identification of conifer species of Cupressaceae, Podocarpaceae, and Cephalotaxaceae in Vietnam.

Figs S1-S4

Fig. S1. Phylogram obtained from ML analyses of the partial BT and EF gene sequences of the O. clavatum species complex. Sequences obtained in this study are printed in bold type. Maximum-likelihood bootstrap support values (1 000 replicates) above 70 % are indicated at the nodes. Bayesian inference posterior probabilities (above 0.9) are indicated by bold lines at the relevant branches. T = ex-type cultures. Fig. S2. Phylogram obtained from ML analyses of the ITS region and the partial BT gene of the O. ips species complex. Sequences obtained in this study are printed in bold type. Maximum-likelihood bootstrap support values (1 000 replicates) above 70 % are indicated at the nodes. The Bayesian inference posterior probabilities (above 0.9) are indicated by bold lines at the relevant branches. T = ex-type cultures. Fig. S3. Phylogram obtained from ML analyses of the ITS region, and the partial BT and CAL gene sequences of the Sporothrix gossypina species complex. Sequences obtained in this study are printed in bold type. Maximum-likelihood bootstrap support values (1 000 replicates) above 70 % are indicated at the nodes. Bayesian inference posterior probabilities (above 0.9) are indicated by bold lines at the relevant branches. T = ex-type cultures. Fig. S4. Phylogram obtained from ML analyses of the ITS region, and the partial BT and EF gene sequences of Endoconidiophra. Sequences obtained in this study are printed in bold type. Maximum-likelihood bootstrap support values (1 000 replicates) above 70 % are indicated at the nodes. Bayesian inference posterior probabilities (above 0.9) are indicated by bold lines at the relevant branches. T = ex-type cultures.

Models for optimizing selection based on adaptability and stability of cotton genotypes

ABSTRACT: In multi-environment trials (MET), large networks are assessed for results improvement. However, genotype by environment interaction plays an important role in the selection of the most adaptable and stable genotypes in MET framework. In this study, we tested different residual variances and measure the selection gain of cotton genotypes accounting for adaptability and stability, simultaneously. Twelve genotypes of cotton were bred in 10 environments, and fiber length (FL), fiber strength (FS), micronaire (MIC), and fiber yield (FY) were determined. Model selection for different residual variance structures (homogeneous and heterogeneous) was tested using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The variance components were estimated through restricted maximum likelihood and genotypic values were predicted through best linear unbiased prediction. The harmonic mean of relative performance of genetic values (HMRPGV) were applied for simultaneous selection for adaptability, stability, and yield. According to BIC heterogeneous residual variance was the best model fit for FY, whereas homogeneous residual variance was the best model fit for FL, FS, and MIC traits. The selective accuracy was high, indicating reliability of the prediction. The HMRPGV was capable to select for stability, adaptability and yield simultaneously, with remarkable selection gain for each trait.

Soybean productivity, stability, and adaptability through mixed model methodology

ABSTRACT: The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genetic selection. Thus, the present study aimed to estimate genetic parameters and to compare different selection strategies in the context of mixed models for soybean breeding. For this, data referring to the evaluation of 30 genotypes in 10 environments, regarding the grain yield trait, were used. The variance components were estimated through restricted maximum likelihood (REML) and genotypic values were predicted through best linear unbiased prediction (BLUP). Significant effects of genotypes and G×E interaction were detected by the likelihood ratio test (LRT). Low genotypic correlation was obtained across environments, indicating complex G×E interaction. The selective accuracy was very high, indicating high reliability. Our results showed that the most productive soybean genotypes have high adaptability and stability.