Dating divergence of Polystigma and other Sordariomycetes

INTRODUCTION

Based on morphological characteristics Canoon (1996) classified Polystigma DC. in the order Phyllachorales, in the Sordariomycetidae, while Habibi et al. (2015) by using ITS, LSU and SSU regions showed that they are close to the Xylariales in the Xylariomycetidae. Polystigma species are characterized principally by brightly colored stromata occurring on living leaves of Prunus spp. in the Euro-Asiatic regions. Leaves are infected in spring with ascospores, which are discharged from overwintering leaves just before flowering till fruit set. The first symptoms of infection are accompanied with the formation of stromata within the host tissue in which fruiting bodies and filiform spores develop. The disease symptoms continue to develop during the summer, followed by the development of perithecia during the autumn and winter in the fallen leaves on the ground. Polystigma amygdalinum P.F. Cannon and Polystigma rubrum (Pers.) DC. are the causal agents of almond red leaf blotch and plum red leaf spot diseases respectively, and often cause premature defoliation of their hosts (Banihashemi 1990; Saad and Masannat 1997).

The evolutionary history of Polystigma genus and the related lineages in Sordariomycetes is still unknown and no study has tried to infer a timing of their origin in the fungal tree of life. Until now, most dating studies and molecular clock analyses of dating evolutionary divergences in the fungal tree of life have focused on major events (Beimforde et al. 2014; Berbee and Taylor 1993, 2010; Lücking et al. 2009; Padovan et al. 2005; Prieto and Wedin 2013) but not on divergences at lower levels e.g. within the Sordariomycetes. The divergence of Basidiomycota and Ascomycota has been estimated between 390 Mya (million years ago) to 1.5 Bya (billion years ago) based on different calibration points used for analyses (Taylor and Berbee 2006). Prieto and Wedin (2013) estimated diversification dates for major clades in the Pezizomycotina. They showed that the Pezizomycotina started to segregate in the Cambrian, and radiations in the Jurassic and Cretaceous caused the diversity of the main modern groups. In addition, these authors provided estimates for diversification dates of major classes, orders and some families of lichenized and non-lichenized groups of Pezizomycotina. Beimforde et al. (2014) extended the initiation of diversification of Pezizomycotina to have started in the Ordovician and continued throughout the Phanerozoic. They discussed the evolutionary history of main lineages in ascomycetes but not within the smaller groups of ascomycetes, i.e. orders and families of Sordariomycetes.

Systematics seeks to construct an accurate “time tree” of life showing both the organismic relationships and their dates of origin (Benton & Ayala 2003; Pyron 2011). Understanding the major processes that had shaped fungal biodiversity requires connecting biological evolution with climate changes, geological evolution and other historical patterns (Parham et al. 2011). In a recent study, we have determined the phylogenetic placement of Polystigma spp. in the fungal tree of life (Habibi et al. 2015).

However, the evolutionary history of Polystigma spp. in relation to the related lineages in the Xylariomycetidae of Sordariomycetes is unclear. This study was aimed at estimating the divergence time of Polystigma from other Sordariomycetes, discussing the evolutionary history of the genus and possible morphological and biogeographic factors underlying the diversification events in Xylariomycetidae. This study used a relaxed clock model and a secondary calibration to perform a molecular clock analysis to species level in Polystigma in relation to related lineages.

MATERIALS AND METHODS

Taxon sampling

The small ribosomal subunits (nuSSU) and ribosomal internal transcribed spacers (ITS) were used in this study. Sequences were obtained from various fresh and dried specimens representing P. amygdalinum and P. rubrum which were collected from infected almond and plum orchards in various parts of Iran (Habibi and Banihashemi 2015) and from Genbank (NCBI) which were extracted from reliable studies (Table 1).

DNA Amplification

Freeze-dried infected plant material, was homogenized using sea sand (Fluka, Darmstadt, Germany) and plastic disposable pestles. Cells were lysed using CTAB solution and DNA was extracted using DNG^TM-plus DNA extraction solution (Cinaclon, Iran) (Mostowfizadeh-Ghalamfarsa and Mirsolaeimani 2012). DNA concentrations were estimated by a NanoDrop spectrophotometer (NanoDrop Technologies, USA). DNA extractions were each diluted to 20 ng.mL^-1 in sterile distilled water for use as template DNA in PCR. Primers PyITS1 (Green et al. 2004) and ITS4 (White et al. 1990) were used to amplify ITS regions, and NS1 and NS4 primers (White et al. 1990) were used to amplify small subunit regions. Twenty-five μL PCR reactions contained 1 × reaction buffer, 0.4 mM of each primer, 200 mM dNTPs, 2.5 mM MgCl₂, 20 ng of DNA and 1 unit of Taq polymerase. PCR was carried out in a CG1-96 thermo cycler (Corbett Research) and cycling conditions consisted of 94°C for 3 min followed by 30 cycles of 94°C for 30 s, 60°C for 30 s, and 72°C for 1 min followed by 5 min at 72°C. Sequencing was performed by Elim Biopharmaceuticals, Inc. (USA). ITS and SSU sequences were deposited in GenBank and the accession numbers were obtained (Table 1).

Initial phylogenetic analysis

Datasets for each genomic region (SSU and ITS) were aligned separately using Geneious version 7 (Biomatters, USA). Models of sequence evolution were evaluated for each dataset and model parameter estimates obtained with JModeltest 2.1.1 (Darriba et al. 2012) and models were chosen according to the Bayesian information criterion (BIC, Schwarz 1978). The Bayesian information criterion supported the TIM+G model with equal base frequencies, six substitution rate parameters (11.0000, 2.1366, 1.0000, 1.0000, 4.4032, 1.000) and gamma distributed rates (shape parameter 0.7130) for SSU and the TIM2ef+I+G model with equal base frequencies, six substitution rate parameters (1.3892, 1.4482, 1.3892, 1.0000, 2.4398, 1.000) and gamma distrib­uted rates (shape parameter 0.6960) for ITS. Topological congruence of the datasets was assessed by visual comparison of phylogenetic trees obtained from maximum likelihood-based analysis heuristic searches in PAUP v. 4.0a133 (Swofford 2002). Bayesian analyses were carried out using Markov Chain Monte Carlo (MCMC) approach in the software package MrBayes v3.2.2 (Ronquist et al. 2012) to generate a reasonable starting tree for subsequent analyses of divergence date estimates in BEAST. For analyses, a general time-reversible model of evolution was used. Rate heterogeneity across sites was modelled with a gamma distribution. Four chains starting with a random tree were run for 10,000,000 generations, retaining each 1000th tree and the first 25% of each analysis were discarded as burn-in.

Molecular clock analysis

For calibration we used the divergence time estimation of 247 Mya for the Sordariomycetes and Leotiomycetes split, inferred in recent molecular dating analysis by Prieto and Wedin (2013) who used six fossils reliable in age and identification including Paleopyrenomycites devonicus Taylor, Hass, Kerp, M. Krings & Hanlin as the oldest calibration point.

A Bayesian Markov Chain Monte Carlo algorithm was applied for estimating divergence times using data from the ribosomal DNA internal transcribed spacer region (ITS) and the 18S small-subunit of ribosomal DNA (SSU rDNA). The analyses were carried out using BEAST v1.8.0 software package (Drummond and Rambaut 2007). The tree topology and divergence time were estimated. Using BEAUTI (BEAST package) priors were set for the analyses and the necessary XML input for BEAST was produced. An HKY model of amino acid substitution and a gamma site heterogeneity model with four rate categories as priors were used. An uncorrelated relaxed clock model used to allow rates of molecular evolution to be uncorrelated across the tree Yull speciation process which specifies a constant rate of species divergence was applied. For the Leotiomycetes and Sordariomycetes divergence, a prior normal distribution with a mean of 247 Mya and a standard diviation of 10 Mya was assigned to the node age. Beast analyses were run 10 milion generations, sampling parameters and trees every 1000 generations. The BEAST output was analyed with Tracer v1.6 (Rambaut and Drummond 2009). One hundred trees were removed from each run as burn-in and the rest of the trees were used to generate a maximum clade credibility tree which is the tree with the highest product of the posterior probability of all its nodes using TreeAnnotator v1.8.0 (BEAST package).

RESULTS and DISCUSSION

The maximum clade credibility tree obtained from BEAST analysis (Fig. 1) was topologically identical to the best tree obtained with our maximum likelihood and bayesian analyses. By few exeptions the topologies resulted from BEAST analysis were congruent with the results of other phylogenies of Sordariomycetes reported by Zhang et al. (2006) and Eriksson (2006). The phylogenetic placement of Polystigma within the Xylariomycetidae was consistent with previous study (Habibi et al. 2015) and Polystigma built a sister group to the Xylariales clade in our analyses.

Divergence time estimates of Sordariomycete groups using 247 Mya calibration point for the Sordariomycetes and Leotiomycetes split, are shown in Fig. 1. Age estimates with means and 95% confidence intervals for some of the major Sordariomycete group splits are summarized in Table 2. According to our results, the first divergence within Sordariomycetes ([Xylariomycetidae + Sordariomycetidae] and Hypocreomycetidae) took placed in the early Jurassic (node 2; 201 Mya; 149-240 Mya credibility interval) (Fig. 1). The Xylariomycetidae and Sordariomycetidae split took placed in the Cretaceous (node 5; 172 Mya; 115-222 Mya credibility interval). Our analyses show that successive radiations in the Jurassic and mostly Cretaceous have generated the diversity in the main Sordariomycetes groups. 

Table 1. Accession numbers of fungal species included in the study.