Bayesian Inference Methods Research Articles

Characterization of the Complete Mitochondrial Genome of a Flea Beetle Luperomorpha xanthodera (Coleoptera: Chrysomelidae: Galerucinae) and Phylogenetic Analysis.

In this study, the mitochondrial genome of Luperomorpha xanthodera was assembled and annotated, which is a circular DNA molecule including 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, 2 ribosomal RNA genes (12S rRNA and 16S rRNA), and 1388 bp non-coding regions (A + T rich region), measuring 16,021 bp in length. The nucleotide composition of the mitochondrial genome is 41.3% adenine (A), 38.7% thymine (T), 8.4% guanine (G), and 11.6% cytosine (C). Most of the protein-coding genes presented a typical ATN start codon (ATA, ATT, ATC, ATG), except for ND1, which showed the start codon TTG. Three-quarters of the protein-coding genes showed the complete stop codon TAR (TAA, TAG), except the genes COI, COII, ND4, and ND5, which showed incomplete stop codons (T- or TA-). All the tRNA genes have the typical clover-leaf structure, except tRNASer1 (AGN), which has a missing dihydrouridine arm (DHU). The phylogenetic results determined by both maximum likelihood and Bayesian inference methods consistently supported the monophyly of the subfamily Galerucinae and revealed that the subtribe Luperina and genus Monolepta are polyphyletic groups. Meanwhile, the classification status of the genus Luperomorpha is controversial.

Indoor Location Fingerprinting Algorithm Based on Path Loss Parameter Estimation and Bayesian Inference

For indoor positioning methods based on Wi-Fi fingerprint, a high-density location fingerprint database usually needs to be constructed to ensure high-precision positioning requirements. At the same time, when the indoor area is huge or the number of reference points (RPs) is large and densely distributed, the computational burden of the online phase will be increased. To solve the above two problems, we propose an indoor location fingerprinting algorithm based on path loss parameter estimation and Bayesian inference (FA-PEBI). In the off-line phase, first, we collect location fingerprints from a few RPs in different rooms; second, the location fingerprints collected are filtered; third, the path loss parameters (PLPs) in different rooms are trained by using a logarithmic distance path loss (LDPL) model; and finally, predict the fingerprint information of the other locations in that room based on the trained parameters. In the online phase, the real-time fingerprint information of the user is first filtered, and then, the room where the user is located is predetermined by using the Bayesian inference method. Subsequently, the corresponding fingerprint database is selected to match based on the regional adaptive selection (RAS) algorithm. Eventually, the ultimate location of the user is obtained based on the Manhattan distance. The experimental results show that the proposed algorithm improves the localization accuracy by at least 16% compared with other existing methods, both in the Wireless Insite simulation data and MAN dataset, and still outperforms the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -nearest neighbor (KNN) algorithm when the fingerprint collection effort in the off-line phase is reduced by half.

First Report of Diaporthe cercidis and D. nobilis Causing Leaf Blotch on Populus davidiana × P. bolleana in China.

First Report of Diaporthe cercidis and D. nobilis Causing Leaf Blotch on Populus davidiana × P. bolleana in China.

Inferring Type II-P Supernova Progenitor Masses from Plateau Luminosities

Connecting observations of core-collapse supernova explosions to the properties of their massive star progenitors is a long-sought, and challenging, goal of supernova science. Recently, Barker et al. presented bolometric light curves for a landscape of progenitors from spherically symmetric neutrino-driven core-collapse supernova (CCSN) simulations using an effective model. They find a tight relationship between the plateau luminosity of the Type II-P CCSN light curve and the terminal iron-core mass of the progenitor. Remarkably, this allows us to constrain progenitor properties with photometry alone. We analyze a large observational sample of Type II-P CCSN light curves and estimate a distribution of iron-core masses using the relationship of Barker et al. The inferred distribution matches extremely well with the distribution of iron-core masses from stellar evolutionary models and namely, contains high-mass iron cores that suggest contributions from very massive progenitors in the observational data. We use this distribution of iron-core masses to infer minimum and maximum masses of progenitors in the observational data. Using Bayesian inference methods to locate optimal initial mass function parameters, we find and solar masses for the observational data.

An evaluation of force field accuracy for the mini-protein chignolin using Markov state models.

All-atom molecular dynamics (MD) simulations can provide detailed insight into a molecule's conformational ensemble in solution. While molecular force fields are parameterized to accurately model a protein's potential energy surface, it remains challenging in practice to evaluate how well force fields can capture ensemble-averaged experimental observables, since it requires simulation of the complete folding landscape. In this work, we employ massively parallel molecular simulations, performed using the [email protected] distributed computing platform, to investigate the ability of nine force fields (AMBER14SB, AMBER99, AMBER99SB, AMBER99SB-ildn, AMBER99SBnmr1-ildn, CHARMM22∗, CHARMM27, CHARMM36 and OPLS-aa) with TIP3P explicit solvent to accurately reproduce experimental observables for chignolin, a beta-hairpin mini-protein with an experimental folding time of ∼600 ns. From over 200 microseconds of aggregate trajectory data, we constructed Markov state models (MSMs) to obtain estimates of thermodynamic and kinetic properties of chignolin in each force field. Quantitative assessment of the force fields was performed by comparing predicted and experimental folded populations, and the statistical agreement between predicted and experimental solution-state NMR observables. Our results rank force field accuracy for chignolin similarly compared to previous work using oligopeptides and ubiquitin (Beauchamp et al. 2012). This work highlights the utility of MSM approaches for force field evaluation, and provides a baseline for future studies using Bayesian inference methods to evaluate and parameterize force fields. It also provides an excellent dataset for testing new approaches to simulation-based sequence design of mini-proteins.

First Report of Curvularia lunata Causing Leaf Spot on Shatangju in China.

Shatangju (Citrus reticulata Blanco) is an economically important citrus cultivar in China. It has a unique flavor and is very popular among consumers. In May 2018, we observed leaf spots on ~20% of Shatangju trees in a 7 ha orchard in Huaiji country, Guangdong, China. Small maroon spots initially developed on the lower leaf surfaces of the symptomatic trees, which then expanded and coalesced into larger lesions. The lesions became visible from the upper leaves, with light gray centers and dark brown margins surrounded by yellow halos. The infected leaves would finally become wilted. To isolate the pathogen, we cut 0.5 × 0.5 cm2 squares from the lesion margins of the symptomatic leaves, disinfested them using 1% NaClO for 20 s, and then with 70% ethanol for 1 min, rinsed them in sterile distilled water three times, and inoculated them onto three potato dextrose agar (PDA) plates (5 squares/plate), which were kept under 25 °C in the dark. Colonies with similar appearance were observed on all the plates and subcultured via the single-spore method (Ho et al. 1997). The mycelia of the subcultures gradually turned from white to black. The colonies were morphologically close to the fungal species Curvularia lunata (Wakker) Boedijn (Ellis 1971). At 8 days after inoculation, the conidia were 18.9-25.1 μm × 8.1-11.6 μm in size (n=50), fusiform or geniculate, smooth-walled, dark-brown, 3-septate, and with a slightly curved second cell and an expanded third cell from the pore end. Three randomly selected isolates from different plates were applied in further analysis. The internal transcribed spacer (ITS: MZ026467) region, translation elongation factor (EF-1α: MZ042646), large subunit ribosomal RNA (LSU: MZ026469), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH: OK086974) segments were amplified and sequenced using primers ITS1/ITS4, EF-1/EF-2, LR5F/ LROR, and gpd1/gpd2, respectively (White et al. 1990; O'Donnell 1998; Marin-Felix 2020). The four segments were identical among the three isolates, which shared the highest nucleotide identities (100% on ITS, LSU, and GAPDH, and 99.8% on EF-1α) with C. lunata strains in the GenBank database. Based on the ITS and GAPDH sequences, phylogenetic analysis using Maximum-likelihood and Bayesian inference methods by W-IQ-TREE (accessed on 09/01/2021) (Trifinopoulos et al., 2016) and MrBayes v3.2.7a (Ronquist et al., 2012) both supported that the isolates belong to C. lunata. For pathogenicity tests, we sprayed the conidial suspension (1×106 conidia/ml) of each of the three isolates on three healthy three-month-old Shatangju seedlings, which were kept under 27 °C and ~100% humidity in plastic bags in the greenhouse. Another three seedlings were sprayed with sterile water and kept under the same conditions as negative controls. Three days after inoculation, small maroon dots started appearing on the inoculated leaves, and the symptoms, same as those observed in the field, developed afterward. No symptoms appeared on the negative controls. C. lunata was reisolated from the infected leaves of all plants inoculated with the three isolates but not from the negative controls. This pathogen has been reported to cause diseases in Pennisetum hydridum and Capsicum frutescens in China (Xu et al. 2018; Pei et al. 2017). But to our knowledge, this is the first report of C. lunata causing leaf spots on citrus plants in the world.

Systematics of Miocene apes: State of the art of a neverending controversy

Hominoids diverged from cercopithecoids during the Oligocene in Afro-Arabia, initially radiating in that continent and subsequently dispersing into Eurasia. From the Late Miocene onward, the geographic range of hominoids progressively shrank, except for hominins, which dispersed out of Africa during the Pleistocene. Although the overall picture of hominoid evolution is clear based on available fossil evidence, many uncertainties persist regarding the phylogeny and paleobiogeography of Miocene apes (nonhominin hominoids), owing to their sparse record, pervasive homoplasy, and the decimated current diversity of this group. We review Miocene ape systematics and evolution by focusing on the most parsimonious cladograms published during the last decade. First, we provide a historical account of the progress made in Miocene ape phylogeny and paleobiogeography, report an updated classification of Miocene apes, and provide a list of Miocene ape species-locality occurrences together with an analysis of their paleobiodiversity dynamics. Second, we discuss various critical issues of Miocene ape phylogeny and paleobiogeography (hylobatid and crown hominid origins, plus the relationships of Oreopithecus) in the light of the highly divergent results obtained from cladistic analyses of craniodental and postcranial characters separately. We conclude that cladistic efforts to disentangle Miocene ape phylogeny are potentially biased by a long-branch attraction problem caused by the numerous postcranial similarities shared between hylobatids and hominids—despite the increasingly held view that they are likely homoplastic to a large extent, as illustrated by Sivapithecus and Pierolapithecus—and further aggravated by abundant missing data owing to incomplete preservation. Finally, we argue that—besides the recovery of additional fossils, the retrieval of paleoproteomic data, and a better integration between cladistics and geometric morphometrics—Miocene ape phylogenetics should take advantage of total-evidence (tip-dating) Bayesian methods of phylogenetic inference combining morphologic, molecular, and chronostratigraphic data. This would hopefully help ascertain whether hylobatid divergence was more basal than currently supported.

An efficient exact algorithm for identifying hybrids using population genomic sequences.

The identification of individuals that have a recent hybrid ancestry (between populations or species) has been a goal of naturalists for centuries. Since the 1960s, codominant genetic markers have been used with statistical and computational methods to identify F1 hybrids and backcrosses. Existing hybrid inference methods assume that alleles at different loci undergo independent assortment (are unlinked or in population linkage equilibrium). Genomic datasets include thousands of markers that are located on the same chromosome and are in population linkage disequilibrium which violate this assumption. Existing methods may therefore be viewed as composite likelihoods when applied to genomic datasets and their performance in identifying hybrid ancestry (which is a model-choice problem) is unknown. Here, we develop a new program Mongrail that implements a full-likelihood Bayesian hybrid inference method that explicitly models linkage and recombination, generating the posterior probability of different F1 or F2 hybrid, or backcross, genealogical classes. We use simulations to compare the statistical performance of Mongrail with that of an existing composite likelihood method (NewHybrids) and apply the method to analyze genome sequence data for hybridizing species of barred and spotted owls.

Channel estimation for underwater acoustic OFDM communications via temporal sparse Bayesian learning

Channel estimation is a challenging task for underwater acoustic (UWA) communications. In this paper, we investigate the channel estimation for OFDM based UWA communications by utilizing the channel characteristics as auxiliary information. Firstly, the channel estimation problem is formulated as a sparse signal recovery problem using block-wise single measurement vector (SMV) model and multiple measurement vector (MMV) model. Then we develop a novel channel estimators under the temporal sparse Bayesian learning (TSBL) framework by jointly exploiting the temporal correlation and sparsity based on the block-wise SMV model. For the MMV model, a variational Bayesian inference based TSBL (VBI-TSBL) method is introduced that considers the inter-block correlations and exploits the row-sparsity by a linear temporal correlation model. The two Bayesian inference methods realize the posterior and parameter estimation of channel via expectation maximization (EM) and variational EM algorithm, respectively. Simulation and sea-trial experiments show the proposed channel estimators outperform the benchmarks in terms of bit error rate, mean square error of channel estimation and the robustness.

Unraveling the COVID-19 hospitalization dynamics in Spain using Bayesian inference

BackgroundOne of the main challenges of the COVID-19 pandemic is to make sense of available, but often heterogeneous and noisy data. This contribution presents a data-driven methodology that allows exploring the hospitalization dynamics of COVID-19, exemplified with a study of 17 autonomous regions in Spain from summer 2020 to summer 2021.MethodsWe use data on new daily cases and hospitalizations reported by the Spanish Ministry of Health to implement a Bayesian inference method that allows making short-term predictions of bed occupancy of COVID-19 patients in each of the autonomous regions of the country.ResultsWe show how to use the temporal series for the number of daily admissions and discharges from hospital to reproduce the hospitalization dynamics of COVID-19 patients. For the case-study of the region of Aragon, we estimate that the probability of being admitted to hospital care upon infection is 0.090 [0.086-0.094], (95% C.I.), with the distribution governing hospital admission yielding a median interval of 3.5 days and an IQR of 7 days. Likewise, the distribution on the length of stay produces estimates of 12 days for the median and 10 days for the IQR. A comparison between model parameters for the regions analyzed allows to detect differences and changes in policies of the health authorities.ConclusionsWe observe important regional differences, signaling that to properly compare very different populations, it is paramount to acknowledge all the diversity in terms of culture, socio-economic status, and resource availability. To better understand the impact of this pandemic, much more data, disaggregated and properly annotated, should be made available.

Delineating epileptogenic networks using brain imaging data and personalized modeling in drug-resistant epilepsy.

Precise estimates of epileptogenic zone networks (EZNs) are crucial for planning intervention strategies to treat drug-resistant focal epilepsy. Here, we present the virtual epileptic patient (VEP), a workflow that uses personalized brain models and machine learning methods to estimate EZNs and to aid surgical strategies. The structural scaffold of the patient-specific whole-brain network model is constructed from anatomical T1 and diffusion-weighted magnetic resonance imaging. Each network node is equipped with a mathematical dynamical model to simulate seizure activity. Bayesian inference methods sample and optimize key parameters of the personalized model using functional stereoelectroencephalography recordings of patients' seizures. These key parameters together with their personalized model determine a given patient's EZN. Personalized models were further used to predict the outcome of surgical intervention using virtual surgeries. We evaluated the VEP workflow retrospectively using 53 patients with drug-resistant focal epilepsy. VEPs reproduced the clinically defined EZNs with a precision of 0.6, where the physical distance between epileptogenic regions identified by VEP and the clinically defined EZNs was small. Compared with the resected brain regions of 25 patients who underwent surgery, VEP showed lower false discovery rates in seizure-free patients (mean, 0.028) than in non-seizure-free patients (mean, 0.407). VEP is now being evaluated in an ongoing clinical trial (EPINOV) with an expected 356 prospective patients with epilepsy.

Ultraconserved elements resolve the phylogeny and corroborate patterns of molecular rate variation in herons (Aves: Ardeidae)

Abstract Thoroughly sampled and well-supported phylogenetic trees are essential to taxonomy and to guide studies of evolution and ecology. Despite extensive prior inquiry, a comprehensive tree of heron relationships (Aves: Ardeidae) has not yet been published. As a result, the classification of this family remains unstable, and their evolutionary history remains poorly studied. Here, we sample genome-wide ultraconserved elements (UCEs) and mitochondrial DNA sequences (mtDNA) of &amp;gt;90% of extant species to estimate heron phylogeny using a combination of maximum likelihood, coalescent, and Bayesian inference methods. The UCE and mtDNA trees are mostly concordant with one another, providing a topology that resolves relationships among the 5 heron subfamilies and indicates that the genera Gorsachius, Botaurus, Ardea, and Ixobrychus are not monophyletic. We also present the first genetic data from the Forest Bittern Zonerodius heliosylus, an enigmatic species of New Guinea; our results suggest that it is a member of the genus Ardeola and not the Tigrisomatinae (tiger herons), as previously thought. Finally, we compare molecular rates between heron clades in the UCE tree with those in previously constructed mtDNA and DNA–DNA hybridization trees. We show that rate variation in the UCE tree corroborates rate patterns in the previously constructed trees—that bitterns (Ixobrychus and Botaurus) evolved comparatively faster, and some tiger herons (Tigrisoma) and the Boat-billed Heron (Cochlearius) more slowly, than other heron taxa.

New genetic lineage of whipworm present in Bactrian camel (Camelus bactrianus)

With a global population of around 35 million in 47 countries, camels play a crucial role in the economy of many marginal and desert areas of the world where they survive in harsh conditions. Nonetheless, there is insufficient knowledge regarding camels’ parasite fauna which can reduce their milk and meat production. A molecular study for the Trichuris population of Camelus bactrianus from Spain is presented based on sequences of mitochondrial (cox1, cob, rrnL) and ribosomal (ITS1 and ITS2) DNA regions. Bayesian Inference and Maximum Likelihood methods were used to infer phylogenies for (i) each gene separately, (ii) the combined mitochondrial data, and (iii) the combined mitochondrial and ribosomal dataset. Molecular analyses revealed the existence of two different genetic lineages in the Trichuris parasites populations of C. bactrianus. Future studies should focus on whether there is a coevolution process corresponding to the wild or domestic character of C. bactrianus and Camelus dromedarius. Furthermore, it is necessary to increase integrative taxonomic studies on Trichuris spp. based on morphological, biometric, and molecular data, which will inevitably contribute to our knowledge of the etiology of trichuriasis.

Modularized Bayesian analyses and cutting feedback in likelihood-free inference

There has been much recent interest in modifying Bayesian inference for misspecified models so that it is useful for specific purposes. One popular modified Bayesian inference method is “cutting feedback” which can be used when the model consists of a number of coupled modules, with only some of the modules being misspecified. Cutting feedback methods represent the full posterior distribution in terms of conditional and sequential components, and then modify some terms in such a representation based on the modular structure for specification or computation of a modified posterior distribution. The main goal of this is to avoid contamination of inferences for parameters of interest by misspecified modules. Computation for cut posterior distributions is challenging, and here we consider cutting feedback for likelihood-free inference based on Gaussian mixture approximations to the joint distribution of parameters and data summary statistics. We exploit the fact that marginal and conditional distributions of a Gaussian mixture are Gaussian mixtures to give explicit approximations to marginal or conditional posterior distributions so that we can easily approximate cut posterior analyses. The mixture approach allows repeated approximation of posterior distributions for different data based on a single mixture fit. This is important for model checks which aid in the decision of whether to “cut”. A semi-modular approach to likelihood-free inference where feedback is partially cut is also developed. The benefits of the method are illustrated on two challenging examples, a collective cell spreading model and a continuous time model for asset returns with jumps.

Data-driven model-based flow measurement uncertainty quantification for building central cooling systems using a probabilistic approach

Uncertainties inevitably exist in measurements and may lead to biases in making management and control decisions, and thus affect the energy performance of building central cooling systems. Water flow meters are essential for the monitoring and operational control of building central cooling systems, but they often suffer from significant measurement uncertainties due to site constraints and unfavorable working environment. An effective method to quantify the flow measurement uncertainties is urgently needed. This study proposes a data-driven model-based flow measurement uncertainty quantification strategy using Bayesian inference and Markov chain Monte Carlo sampling methods. The proposed strategy is tested and validated systematically on an air-cooled chiller. Four case studies with different levels of flow measurement uncertainties are conducted. The test results show that both systematic and random uncertainties of flow measurements are quantified accurately by this strategy. The 95% Bayesian credible intervals of systematic and random uncertainties contain their pre-set (actual) values, and their posterior means (estimated values) are very close to their pre-set values. The relative errors in quantifying flow measurement uncertainties are within 10%. The performance of the proposed method is quite satisfactory. This study provides a cost-effective and promising alternative for on-site flow meter calibration in engineering practice.

Cointegration analysis of hazard rates and CDSs: Applications to pairs trading strategy

This study examines the cointegration relationship between multiple credit default swap (CDS) spreads by constructing the cointegrated hazard rate model, which assumes the structure of the vector error correction model (VECM) in the drift term of hazard rate processes. We merge the cointegration nature into the framework of arbitrage-free pricing and thereby derive the theoretical spread formula of multiple cointegrated CDSs. For the estimation of hazard rate dynamics, we develop a Bayesian statistical inference method combined with the numerical ordinary differential equation solver because the theoretical CDS spread cannot be expressed in closed form. In the empirical study of Japanese corporate CDSs, we find that the overall term structures of cointegrated CDSs can be explained by a simple two-dimensional VECM of cointegrated hazard rates. Furthermore, we study the pairs trading strategy of CDSs.

First mitochondrial genome of subfamily Julodinae (Coleoptera, Buprestidae) with its phylogenetic implications.

Complete mitochondrial genomes of three species of the family Buprestidae were sequenced, annotated, and analyzed in this study. To explore the mitogenome features of the subfamily Julodinae and verify its phylogenetic position, the complete mitogenome of Julodisvariolaris was sequenced and annotated. The complete mitogenomes of Ptosimachinensis and Chalcophorajaponica were also provided for the phylogenetic analyses within Buprestidae. Compared to the known mitogenomes of Buprestidae species varied from 15,499 bp to 16,771 bp in length, three newly sequenced mitogenomes were medium length (15,759-16,227 bp). These mitogenomes were encoded 37 typical mitochondrial genes. Among the three studied mitogenomes, Leu2 (L2), Ser2 (S2), and Pro (P) were the three most frequently encoded amino acids. Within the Buprestidae, the heterogeneity in sequence divergences of Agrilinae was highest, whereas the sequence homogeneity of Chrysochroinae was highest. Moreover, phylogenetic analyses were performed based on nucleotide matrix (13 PCGs + 2 rRNAs) among the available sequenced species of Buprestidae using Bayesian Inference and Maximum Likelihood methods. The results showed that the Julodinae was closely related to the subfamily Polycestinae. Meanwhile, the genera Melanophila, Dicerca, and Coomaniella were included in Buprestinae, which was inconsistent with the current classification system of Buprestidae. These results could contribute to further studies on genetic diversity and phylogeny of Buprestidae.

How do psychology researchers interpret the results of multiple replication studies?

Employing two vignette studies, we examined how psychology researchers interpret the results of a set of four experiments that all test a given theory. In both studies, we found that participants’ belief in the theory increased with the number of statistically significant results, and that the result of a direct replication had a stronger effect on belief in the theory than the result of a conceptual replication. In Study 2, we additionally found that participants’ belief in the theory was lower when they assumed the presence of p-hacking, but that belief in the theory did not differ between preregistered and non-preregistered replication studies. In analyses of individual participant data from both studies, we examined the heuristics academics use to interpret the results of four experiments. Only a small proportion (Study 1: 1.6%; Study 2: 2.2%) of participants used the normative method of Bayesian inference, whereas many of the participants’ responses were in line with generally dismissed and problematic vote-counting approaches. Our studies demonstrate that many psychology researchers overestimate the evidence in favor of a theory if one or more results from a set of replication studies are statistically significant, highlighting the need for better statistical education.

A phylogenetic and taxonomic study on Steccherinum (Polyporales, Basidiomycota): Focusing on three new Steccherinum species from southern China

The wood-inhabiting fungi play an integral role in wood degradation and the cycle of matter in the ecological system. They are considered as the “key player” in wood decomposition, because of their ability to produce all kinds of enzymes that break down woody lignin, cellulose and hemicellulose. In the present study, three new wood-inhabiting fungal species, Steccherinum fissurutum, S. punctatum and S. subtropicum spp. nov., collected from southern China, are proposed based on a combination of morphological features and molecular evidence. Steccherinum fissurutum is characterized by the resupinate, subceraceous basidiomata with cracked hymenophore, a monomitic hyphal system with clamped generative hyphae and cylindrical basidiospores; S. punctatum is characterized by the annual, punctate basidiomata with leathery hymenophore, cylindrical, strongly encrusted cystidia and ellipsoid basidiospores (3.6–4.5 ×2.6–3.4 µm); S. subtropicum is characterized by its effuse-reflexed basidiomata, a odontioid hymenophore with pink to lilac hymenial surface and ellipsoid basidiospores measuring as (2.8–3.4 × 2.0–2.7 µm). Sequences of ITS and nLSU rRNA markers of the studied samples were generated, and phylogenetic analyses were performed with maximum likelihood, maximum parsimony, and Bayesian inference methods. The ITS+nLSU analysis of the family Steccherinaceae indicated that the three new species clustered into the genus Steccherinum. Based on further analysis of ITS+nLSU dataset, the phylogenetic analysis confirmed that S. subtropicum was sister to S. enuispinum; S. fissurutum formed a monophyletic lineage; S. punctatum grouped with a clade comprised S. straminellum and S. ciliolatum.

A phylogenetic and taxonomic study on Steccherinum (Polyporales, Basidiomycota): Focusing on three new Steccherinum species from southern China.

The wood-inhabiting fungi play an integral role in wood degradation and the cycle of matter in the ecological system. They are considered as the "key player" in wood decomposition, because of their ability to produce all kinds of enzymes that break down woody lignin, cellulose and hemicellulose. In the present study, three new wood-inhabiting fungal species, Steccherinum fissurutum, S. punctatum and S. subtropicum spp. nov., collected from southern China, are proposed based on a combination of morphological features and molecular evidence. Steccherinum fissurutum is characterized by the resupinate, subceraceous basidiomata with cracked hymenophore, a monomitic hyphal system with clamped generative hyphae and cylindrical basidiospores; S. punctatum is characterized by the annual, punctate basidiomata with leathery hymenophore, cylindrical, strongly encrusted cystidia and ellipsoid basidiospores (3.6-4.5 ×2.6-3.4 µm); S. subtropicum is characterized by its effuse-reflexed basidiomata, a odontioid hymenophore with pink to lilac hymenial surface and ellipsoid basidiospores measuring as (2.8-3.4 × 2.0-2.7 µm). Sequences of ITS and nLSU rRNA markers of the studied samples were generated, and phylogenetic analyses were performed with maximum likelihood, maximum parsimony, and Bayesian inference methods. The ITS+nLSU analysis of the family Steccherinaceae indicated that the three new species clustered into the genus Steccherinum. Based on further analysis of ITS+nLSU dataset, the phylogenetic analysis confirmed that S. subtropicum was sister to S. enuispinum; S. fissurutum formed a monophyletic lineage; S. punctatum grouped with a clade comprised S. straminellum and S. ciliolatum.