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Frontiers in Microbiology logoLink to Frontiers in Microbiology
. 2019 Sep 2;10:1936. doi: 10.3389/fmicb.2019.01936

High Genetic Diversity and Species Complexity of Diaporthe Associated With Grapevine Dieback in China

Ishara S Manawasinghe 1,2,, Asha J Dissanayake 1,2,3,, Xinghong Li 1, Mei Liu 1, Dhanushka N Wanasinghe 2,4, Jianping Xu 5, Wensheng Zhao 6, Wei Zhang 1, Yueyan Zhou 1, Kevin D Hyde 2, Siraprapa Brooks 2, Jiye Yan 1,*
PMCID: PMC6732904  PMID: 31543868

Abstract

Grapevine trunk diseases have become one of the main threats to grape production worldwide, with Diaporthe species as an emerging group of pathogens in China. At present, relatively little is known about the taxonomy and genetic diversity of Chinese Diaporthe populations, including their relationships to other populations worldwide. Here, we conducted an extensive field survey in six provinces in China to identify and characterize Diaporthe species in grape vineyards. Ninety-four isolates were identified and analyzed using multi-locus phylogeny. The isolates belonged to eight species, including three novel taxa, Diaporthe guangxiensis (D. guangxiensis), Diaporthe hubeiensis (D. hubeiensis), Diaporthe viniferae (D. viniferae), and three new host records, Diaporthe gulyae (D. gulyae), Diaporthe pescicola (D. pescicola), and Diaporthe unshiuensis (D. unshiuensis). The most commonly isolated species was Diaporthe eres (D. eres). In addition, high genetic diversity was observed for D. eres in Chinese vineyards. Haplotype network analysis of D. eres isolates from China and Europe showed a close relationship between samples from the two geographical locations and evidence for recombination. In comparative pathogenicity testing, D. gulyae was the most aggressive taxon, whereas D. hubeiensis was the least aggressive. This study provides new insights into the Diaporthe species associated with grapevines in China, and our results can be used to develop effective disease management strategies.

Keywords: novel species, new host record, network analysis, phylogeography, phomopsis

Introduction

In natural ecosystems, plant pathogens play important roles such as regulating host populations and host plant geographic and ecological distributions. Consequently, they can affect the availability of food sources to other living organisms (Lindahl and Grace, 2015). Most microbial pathogens have short generation times and large population sizes, which can result in high genetic variations and rapid adaptations to environmental stresses and to human-mediated factors such as fungicide resistance (Alberts et al., 2002; Lindahl and Grace, 2015). Hence, it is important to understand the genetic diversity and population variation of plant pathogens to develop sustainable control measures.

Grape is one of the most important fruit crops in China. China is the second largest grape-cultivating country and the top producer in the world (OIV, 2016). In 2016, the total grape cultivation area was estimated at 847 kha, and 14.5 million metric tons of fresh grapes were produced in China (OIV, 2016). Therefore, infectious diseases with significant risks to grape production have drawn broad attention from the grapevine industry. Grapevines are affected by several foliar diseases (Gadoury et al., 2012; Zhang et al., 2017), fruit diseases (Daykin and Milholland, 1984; Hong et al., 2008; Greer et al., 2011; Jayawardena et al., 2015), and trunk diseases (Yan et al., 2013; Dissanayake et al., 2015a,b). Grapevine trunk diseases have drawn considerable attention, as these diseases affect the perennial parts of the vine and can limit grape production for many years (Yan et al., 2013, 2015).

The genus Diaporthe Nitschke., belongs to the family Diaporthaceae, and is typified by Diaporthe eres (D. eres) Nitschke (Senanayake et al., 2017). Following the nomenclature rules Rossman et al. (2014) proposed that the genus name Diaporthe over Phomopsis as it was introduced first, represents the majority of species. In earlier species names were given to Diaporthe taxa based on their host specificity. This resulted in over 100 names listed under the genus Diaporthe (http://www.indexfungorum.org/Names/Names.asp and http://www.mycobank.org). With advances in molecular techniques, multi-locus DNA sequence data together with morphological characteristics have been extensively used for the delimitation of Diaporthe species (Udayanga et al., 2011; Gomes et al., 2013; Gao et al., 2017). The internal transcribed spacer (ITS), translation elongation factor-1a (EF-1α), β-tubulin, partial histone H3 (HIS), calmodulin (CAL), genes are the most commonly used gene regions for molecular characterization (Udayanga et al., 2011; Gao et al., 2017; Guarnaccia et al., 2018; Yang et al., 2018). Multiple studies have used different gene combinations to resolve the species boundaries in this genus (Udayanga et al., 2011, 2014a,b; Gao et al., 2017; Marin-Felix et al., 2019). Species belonging to genus Diaporthe are endophytes, pathogenic, and saprobic on wide range of hosts worldwide (Liu et al., 2015; Hyde et al., 2016; Marin-Felix et al., 2019). They are well-known pathogens on economically important crops (Udayanga et al., 2011). Several common disease among those are dieback on forest trees (Yang et al., 2018), leaf spots on tea (Guarnaccia and Crous, 2017), leaf and pod blights and seed decay on soybean (Udayanga et al., 2015), melanose, stem-end rot, and gummosis on Citrus spp. (Mondal et al., 2007; Udayanga et al., 2014a; Guarnaccia and Crous, 2017, 2018) and stem canker on sunflower (Muntañola-Cvetković et al., 1981; Thompson et al., 2011).

Phomopsis cane and leaf spot caused by Diaporthe species on grapevine is one of the most complex grapevine trunk diseases worldwide (Úrbez-Torres et al., 2013; Dissanayake et al., 2015a; Guarnaccia et al., 2018). The disease symptoms of Diaporthe Dieback include shoots breaking off at the base, stunting, dieback, loss of vigor, reduced bunch set, and fruit rot (Pine, 1958, 1959; Pscheidt and Pearson, 1989; Pearson and Goheen, 1994; Wilcox et al., 2015). In woods brown to black necrotic irregular-shaped lesions could be observed. Once clusters are infected rachis necrosis and brown, shriveled berries close to harvest could be observed (Pearson and Goheen, 1994). More than one Diaporthe species is frequently reported as causative agents from one country (Dissanayake et al., 2015a; Guarnaccia et al., 2018). Currently, 27 species have been identified as causal organisms of Diaporthe dieback in grape-producing countries worldwide (Mostert et al., 2001; Van Niekerk et al., 2005; Udayanga et al., 2011, 2014a,b; White et al., 2011; Baumgartner et al., 2013; Úrbez-Torres et al., 2013; Hyde et al., 2014; Dissanayake et al., 2015a; Guarnaccia et al., 2018; Lesuthu et al., 2019). Even though these species characterized under the one disease, disease symptoms, and aggressiveness are varying according to the species. Diaporthe ampelina (D. ampelina) has a long history as the most common and severe pathogenic species together with D. amygdali (Mostert et al., 2001; Van Niekerk et al., 2005). Diaporthe ampelina and Diaporthe kyushuensis (D. kyushuensis) are the causal agent of grapevine swelling arm (Kajitani and Kanematsu, 2000; Van Niekerk et al., 2005). Diaporthe perjuncta (D. perjuncta) and D. ampelina caused cane bleaching (Kuo and Leu, 1998; Kajitani and Kanematsu, 2000; Mostert et al., 2001; Van Niekerk et al., 2005; Rawnsley et al., 2006). Lesuthu et al. (2019) showed that D. ampelina, Diaporthe novem (D. novem), and Diaporthe nebulae (D. nebulae) as the most virulent species of Diaporthe associated with grapevines in South Africa. Diaporthe eres was found as a weak to moderate pathogen in several different studies (Kaliterna et al., 2012; Baumgartner et al., 2013). These results indicate the complexity and high species richness of Diaporthe associated with the grapevines. Up to now in China four Diaporthe species have been reported causing grapevine dieback (Dissanayake et al., 2015a). Those are D. eres, Diaporthe hongkongensis (D. hongkongensis), Diaporthe phaseolorum (D. phaseolorum), and Diaporthe sojae (D. sojae). Their taxonomic placements and pathogenicity under a controlled environment were also studied.

The study conducted by Guarnaccia et al. (2018) showed that species of Diaporthe also associated as endophytes on grapes as well. In that study they observed that Diaporthe bohemiae (D. bohemiae), which was isolated from grape was unable to induce lesions. In addition to grapevines, Diaporthe have been reported on broad range of hosts (Udayanga et al., 2011). However, the most important charter is the ability of endophytic Diaporthe species to be opportunistic pathogens. Huang et al. (2015) observed that some Diaporthe species associated with citrus in China shown to act as opportunistic plant pathogens. Diaporthe foeniculina (D. foeniculina) has been found as both endophyte and opportunistic pathogen on various herbaceous weeds, ornamentals, and fruit trees (Udayanga et al., 2014a; Guarnaccia et al., 2016). So far it is not confirmed the factor that driven into pathogenicity from endophytes either due to environmental changes or the reduction of host's defense. Therefore, further studies are required to understand this in both field level and genomic level.

However, the genetic diversity of Diaporthe spp. associated with Vitis spp., relationships among isolates from different geographical regions, and relationships among isolates from China and those from other countries were not investigated. Therefore, to expand our knowledge on these issues, we performed an extensive field survey to isolate and identify Diaporthe species associated with grapevine dieback in China. We reconstructed a phylogenetic tree for the genus Diaporthe. The present study analyzed the genetic diversity of Diaporthe species associated with grapevines in China and constructed haplotype networks for Diaporthe species from different geographical origins for the first time. Finally, we analyzed the relationship between Diaporthe species from European and Chinese grape vineyards, as Diaporthe dieback is becoming an emerging trunk disease in both regions (Guarnaccia et al., 2018).

Materials and Methods

Sampling and Pathogen Isolation

Field surveys were conducted during 2014 and 2015 in 20 vineyards in the six following provinces in China: Guangxi, Heilongjiang, Hubei, Jilin, Liaoning, and Sichuan (Figure 1). Samples were collected from symptomatic grapevine woody branches that exhibited bark discoloration, shoots breaking off at the base, stunting, wedge-shaped cankers, and light brown streaking of the wood from the following Vitis vinifera (V. vinifera) cultivars: Centennial Seedless, Red Globe, and Summer Black (Figure 2). Symptomatic tissue samples were collected into zip-lock plastic bags that contained wet sterilized tissue papers to maintain humidity. Once the samples were taken into the laboratory, infected trunks or shoots were photographed, and symptoms, location, and other relevant data were documented. The fungal pathogens were isolated using the following procedures. Infected shoots/trunks were cut into small pieces (1–3 mm thick). These pieces were then surface-sterilized by dipping into 70% ethanol for 30 s and then transferred into 1% NaOCl for 1 min. This step was followed by two washes with sterile distilled water. Once the wood pieces were dried, they were placed onto potato dextrose agar (PDA) plates supplemented with ampicillin (0.1 g L−1) and incubated at 25°C. After 5–7 days of incubation, hyphal tips of fungi immerging from wood pieces were transferred onto new PDA plates and incubated until they produce conidia. Once the conidia were developed single spore isolation was done. For the strains do not developed conidia after 4 weeks two-three times hyphal tip isolation was done. All the pure cultures obtained in this study were deposited in the culture collection of Institute of Plant and Environment Protection of Beijing Academy of Agriculture and Forestry Sciences (JZB culture collection) at 4°C.

Figure 1.

Figure 1

Sample collection sites of Diaporthe dieback in six provinces in China. Circles represent the association frequency of each species in each population sampled, and the number of isolates analyzed in each population is given inside the respective slice.

Figure 2.

Figure 2

Symptoms of Diaporthe dieback. (A,B) Field symptoms on trunks and shoots, (C) appearance of fruiting bodies on trunk surface, and (D,E) cross sections of infected trunks.

DNA Extraction, PCR Amplification, and Sequence Assembly

Approximately 10 mg of aerial mycelium was scraped from 5–7 days old isolates grown on PDA (Potato Dextrose Agar) at 25°C. Total genomic DNA was extracted using the DNeasy Plant Mini Kit (QIAGEN GmbH, QIAGEN Strasse 1, 40742 Hilden, Germany). For species confirmation, the internal transcribed spacer (ITS) regions were sequenced for all isolates. The obtained sequences were compared to those in GenBank using the MegaBLAST tool (https://blast.ncbi.nlm.nih.gov/Blast.cgi). After isolates were confirmed as belonging to the genus Diaporthe, six additional gene regions, those encoding translation elongation factor-1α (EF-1α), β-tubulin, calmodulin (CAL), partial histone H3 (HIS), partial actin (ACT), and DNA-lyase (Apn2), were sequenced. Table 1 presents the primer pairs with their respective amplification conditions for each of the above gene regions. PCR mixtures of 25 μl total volume consisted of 0.3 μl of TaKaRa Ex-Taq DNA polymerase, 2.5 μl of 10 × Ex-Taq DNA polymerase buffer, 3.0 μl of dNTPs, 2 μl of genomic DNA, 1 μl of each primer, and 15.2 ddH2O. The PCRs were conducted in a Bio-Rad C1000 thermal cycler (Germany). The resulting products were visualized on a 1% agarose gel stained with ethidium bromide under UV light using a Gel DocTM XR Molecular Imager (Bio Rad, USA). All positive amplicons were sequenced by Beijing Biomed Gene Technology Co LTD. The sequence quality was confirmed by checking chromatograms using BioEdit v. 5 (Hall, 2006). Sequences were obtained using both forward and reverse primers, and consensus sequences were generated using DNAStar v. 5.1 (DNASTAR, Inc.). The sequence data generated in the present study have been deposited in GenBank (Table 2).

Table 1.

Gene regions and respective primer pairs used in the study.

Gene region Primers Sequence 5′-3′ Optimized PCR protocols References
ACT ACT-512F ATGTGCAAGGCCGGTTTCGC 95°C: 5 min, (95°C: 30 s, 55°C: 50 s,72°C: 1 min)
× 39 cycles 72°C: 10 min
Carbone and Kohn, 1999
ACT-783R TACGAGTCCTTCTGGCCCAT
Apn2 (DNA lyase apn2fw2 GCMATGTTYGAMATYCTGGAG 94°C: 1 min, (95°C: 30 s, 54°C: 50 s, 72°C: 1 min)
× 39 cycles 72°C: 10 min
Udayanga et al., 2012a,b
apn2rw2 CTT GGTCTCCCAGCAGGTG AAC
CAL CAL-228F GAGTTCAAGGAGGCCTTCTCCC 95°C: 5 min, (95°C: 30 s, 55°C: 50 s, 72°C: 1 min)
× 34 cycles 72°C: 10 min
Carbone and Kohn, 1999
CAL-737R CATCTTCTGGCCATCATGG
EF1-α EF1-728F CATCGAGAAGTTCGAGAAGG 95°C: 5 min, (95°C: 30 s, 58°C: 30 s, 72°C: 1 min)
× 34 cycles 72°C: 10 min
Carbone and Kohn, 1999
EF1-986R TACTTGAAGGAACCCTTACC Udayanga et al., 2012a,b
HIS CYLH3F AGGTCC ACTGGTGGCAAG 96°C: 5 min, (96°C: 30 s, 58°C: 50 s, 72°C: 1 min)
× 30 cycles 72°C: 5 min
Crous et al., 2004
H3-1b GCGGGCGAGCTGGATGTCCTT Glass and Donaldson, 1995
ITS ITS1 TCCGTAGGTGAACCTGCGG 94°C: 5 min, (94°C: 30 s, 55°C: 50 s, 72°C: 1 min)
× 34 cycles 72°C: 10 min
White et al., 1990
ITS4 TCCTCCGCTTATTGATATGC Udayanga et al., 2012a,b
β-tubulin BT2a GGTAACCAAATCGGTGCTGCTTTC 94°C: 5 min, (94°C: 30 s, 58°C: 50 s, 72°C: 1 min)
× 34 cycles 72°C: 10 min
Glass and Donaldson, 1995
Bt2b ACCCTCAGTGTAGTGACCCTTGGC Udayanga et al., 2012a,b

Table 2.

Diaporthe species isolated and characterized in the present study.

No Species Location Year JZB number Sequence data
ITS β-tubulin CAL EF-1α
01 Diaporthe eres Sichuan 2015 JZB320020* MK500169 MK500062 MK523586
02 Sichuan 2015 JZB320021* MK335710 MK500170 MK500063 MK523587
03 Sichuan 2015 JZB320022* MK335711 MK500171 MK500064 MK523588
04 Sichuan 2015 JZB320023* MK335712 MK500172 MK500065 MK523589
05 Sichuan 2015 JZB320024* MK335713 MK500173 MK500066
06 Sichuan 2015 JZB320026 MK335714 MK500174 MK500067 MK523591
07 Sichuan 2015 JZB320027* MK335715 MK500175 MK500068 MK523619
08 Sichuan 2015 JZB320028* MK335716 MK500176 MK500069 MK523592
09 Sichuan 2015 JZB320029* MK335717 MK500177 MK500070 MK523620
10 Lioning 2015 JZB320030 MK335718 MK500178 MK500071 MK523621
11 Hubei 2015 JZB320033* MK335719 MK500179 MK500072 MK523622
12 Hubei 2015 JZB320034* MK335720 MK500180 MK500073 MK523623
13 Hubei 2015 JZB320035* MK335721 MK500181 MK500074 MK523593
14 Hubei 2015 JZB320036* MK335722 MK500182 MK500075
15 Hubei 2015 JZB320037* MK335723 MK500183 MK500076
16 Hubei 2015 JZB320038* MK335724 MK500184 MK500077 MK523594
17 Hubei 2015 JZB320039* MK335725 MK500185 MK500078 MK523595
18 Hubei 2015 JZB320040* MK335726 MK500186 MK500079 MK523596
19 Hubei 2015 JZB320041* MK335727 MK500187 MK500080
20 Hubei 2015 JZB320043* MK335728 MK500188 MK500081 MK523624
21 Hubei 2015 JZB320044* MK335729 MK500189 MK500082
22 Hubei 2015 JZB320045* MK335730 MK500083 MK523597
23 Hubei 2015 JZB320046* MK335731 MK500190 MK500084 MK523598
24 Hubei 2015 JZB320047 MK335732 MK500191 MK500085
25 Hubei 2015 JZB320048* MK335733 MK500192 MK500086 MK523599
26 Hubei 2015 JZB320049* MK335734 MK500193 MK500087 MK523625
27 Hubei 2015 JZB320051* MK335735 MK500194 MK500088 MK523600
28 Hubei 2015 JZB320052 MK335736 MK500195 MK500089
29 Heilongjiang 2015 JZB320053* MK335737 MK500196 MK500090 MK523601
30 Jilin 2015 JZB320054 MK335738 MK500197 MK500091 MK523602
31 Jilin 2015 JZB320055* MK335739 MK500198 MK500092 MK523617
32 Jilin 2015 JZB320056* MK335740 MK500199 MK500093 MK523618
33 Jilin 2015 JZB320057* MK335741 MK500200 MK500094 MK523603
34 Jilin 2015 JZB320058* MK335742 MK500201 MK500095 MK523604
35 Jilin 2015 JZB320059* MK335743 MK500202 MK500096 MK523605
36 Jilin 2015 JZB320060 MK335744 MK500203 MK500097 MK523606
37 Jilin 2015 JZB320061* MK335745 MK500204 MK500098 MK523607
38 Jilin 2015 JZB320062* MK335746 MK500205 MK500099 MK523614
39 Jilin 2015 JZB320063* MK335747 MK500206 MK500100 MK523608
40 Jilin 2015 JZB320064* MK335748 MK500207 MK500101 MK523609
41 Jilin 2015 JZB320065 MK335749 MK500208 MK500102 MK523615
42 Jilin 2015 JZB320066 MK335750 MK500209 MK500103 MK523610
43 Jilin 2015 JZB320067 MK335751 MK500210 MK500104 MK523611
44 Jilin 2015 JZB320068* MK335752 MK500211 MK500105 MK523612
45 Jilin 2015 JZB320069* MK335753 MK500212 MK500106 MK523616
46 Jilin 2015 JZB320070* MK335754 MK500213 MK523613
47 Diaporthe guangxiensis Guangxi 2015 JZB320082 MK335760 MK500156 MK736715 MK523557
48 Guangxi 2015 JZB320083 MK335761 MK500157 MK736716 MK523558
49 Guangxi 2015 JZB320084 MK335762 MK500158 MK736717
50 Guangxi 2015 JZB320085 MK335763 MK500159 MK736718
51 Guangxi 2015 JZB320086 MK335764 MK500160 MK736719 MK523559
52 Guangxi 2015 JZB320087* MK335765 MK500161 MK736720 MK523560
53 Guangxi 2015 JZB320088 MK335766 MK500162 MK736721 MK523561
54 Guangxi 2015 JZB320089 MK335767 MK500163 MK736722 MK523562
55 Guangxi 2015 JZB320090 MK335768 MK500164 MK736723 MK523563
56 Guangxi 2015 JZB320091* MK335769 MK500165 MK736724 MK523564
57 Guangxi 2015 JZB320092 MK335770 MK500166 MK736725
58 Guangxi 2015 JZB320093* MK335771 MK500167 MK736726 MK523565
59 Guangxi 2015 JZB320094* MK335772 MK500168 MK736727 MK523566
60 Diaporthe gulyae Heilongjiang 2015 JZB320118 KY400792 KY400856 KY400824
61 Heilongjiang 2015 JZB320119 KY400793 KY400857 KY400825
62 Diaporthe hubeiensis Hubei 2015 JZB320120 MK335806 MK500144 MK500232 MK523567
63 Hubei 2015 JZB320121* MK335807 MK500146 MK500233 MK523568
64 Hubei 2015 JZB320122* MK335808 MK500147 MK500234 MK523569
65 Hubei 2015 JZB320123* MK335809 MK500148 MK500235 MK523570
66 Hubei 2015 JZB320124* MK335810 MK500149 MK500236 MK523571
67 Hubei 2015 JZB320125* MK335811 MK500150 MK500237
68 Hubei 2015 JZB320126 MK335812 MK500151 MK500238
69 Hubei 2015 JZB320127* MK335813 MK500152 MK500239 MK523572
70 Hubei 2015 JZB320128* MK335814 MK500153 MK500240 MK523573
71 Hubei 2015 JZB320139* MK335815 MK500154 MK500241
72 Hubei 2015 JZB320130 MK335816 MK500155 MK500242
73 Diaporthe pescicola Hubei 2015 JZB320095 KY400784 KY400890 KY400817
74 Hubei 2015 JZB320096 KY400785 KY400891 KY400831
75 Diaporthe sojae Sichuan 2015 JZB320097 MK335826 MK500126 MK500214 MK523574
76 Hubei 2015 JZB320098 MK335827 MK500127 MK500215 MK523575
77 Hubei 2015 JZB320099 MK335828 MK500128 MK500216 MK523576
78 Hubei 2015 JZB320100 MK335829 MK500217
79 Guangxi 2015 JZB320101 MK335830 MK500129 MK500218 MK523577
80 Guangxi 2015 JZB320102 MK335831 MK500130 MK500219 MK523578
81 Guangxi 2015 JZB320103 MK335832 MK500131 MK500220 MK523579
82 Guangxi 2015 JZB320104 MK335833 MK500132 MK500221 MK523580
83 Guangxi 2015 JZB320105 MK335834 MK500133 MK500222
84 Guangxi 2015 JZB320106 MK335835 MK500134 MK500223
85 Guangxi 2015 JZB320107 MK335836 MK500135 MK500224
86 Guangxi 2015 JZB320108 MK335837 MK500136 MK500225 MK523581
87 Guangxi 2015 JZB320109 MK335838 MK500137 MK500226 MK523582
88 Guangxi 2015 JZB320110 MK335839 MK500138 MK500227
89 Hubei 2015 JZB320111 MK335840 MK500139 MK500228
90 Hubei 2015 JZB320112 MK335841 MK500140 MK500228 MK523583
91 Hubei 2015 JZB320113 MK335842 MK500141 MK500230 MK523584
92 Hubei 2015 JZB320114 MK335843 MK500142 MK500231 MK523585
93 Hubei 2015 JZB320115 MK500143
94 Diaporthe unshiuensis Hubei 2015 JZB320116 KY400790 KY400854 KY400822
95 Hubei 2015 JZB320117 KY400791 KY400855 KY400823
96 Diaporthe viniferae Guangxi 2015 JZB320071* MK341551 MK500112 MK500119 MK500107
97 Guangxi 2015 JZB320072 MK341552 MK500113 MK500120 MK500108
98 Guangxi 2015 JZB320076* MK341553 MK500115 MK500122
99 Guangxi 2015 JZB320077 MK341554 MK500116 MK500123 MK500109
100 Guangxi 2015 JZB320078* MK341555 MK500117 MK500124 MK500110
101 Guangxi 2015 JZB320079* MK341556 MK500118 MK500125 MK500111

JZB: Culture collection of Institute of Plant and Environment Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China. Ex-type cultures are indicated in bold. Isolates used in pathogenicity test are Italic. ITS, internal transcribed spacers 1 and 2 together with 5.8S nrDNA; β-tubulin, partial beta-tubulin gene; CAL, partial calmodulin gene; EF-1α, partial translation elongation factor 1-α gene.

*

Strains used in phylogenetic analysis (Figure 3).

Phylogenetic Analyses

For the phylogenetic analyses, reference sequences representing related taxa in Diaporthe were downloaded from GenBank (Guarnaccia et al., 2018; Yang et al., 2018; Table 3) and aligned with the sequences obtained in this study (Table 2). The sequences were aligned using MAFFT (Katoh and Toh, 2010) (http://www.ebi.ac.uk/Tools/msa/mafft/) and manually adjusted using BioEdit v. 5 (Hall, 2006) whenever necessary. Phylogenetic relationships were inferred using maximum parsimony (MP) implemented in PAUP (v4.0) (Swofford, 2003), maximum likelihood (ML) in RAxML (Silvestro and Michalak, 2010) and Bayesian analyses in MrBayes v. 3.0b4 (Ronquist and Huelsenbeck, 2003). In phylogenetic analysis, single-gene trees were constructed first using ML in RAxML. The phylogenetic tree topologies for different gene fragments were compared for evidence of incongruences with a focus on comparing branches with high bootstrap values. If no conflict was observed, a combined phylogenetic tree was generated.

Table 3.

Diaporthe taxa used in the phylogenetic analysis.

Species Isolate Host Location GenBank accession numbers
ITS β-tubulin CAL EF-1α
D. acaciarum CBS 138862 Acacia tortilis Tanzania KP004460 KP004509 N/A N/A
D. acaciigena CBS 129521 Acacia retinodes Australia KC343005 KC343973 KC343247 KC343731
D. acericola MFLUCC 17-0956 Acer negundo Italy KY964224 KY964074 KY964137 KY964180
D. acerigena CFCC 52554 Acer tataricum China MH121489 N/A MH121413 MH121531
CFCC 52555 Acer tataricum China MH121490 N/A MH121414 MH121532
D. acutispora CGMCC 3.18285 Coff sp. China KX986764 KX999195 KX999274 KX999155
D. alangii CFCC 52556 Alangium kurzii China MH121491 MH121573 MH121415 MH121533
D. alleghaniensis CBS 495.72 Betula alleghaniensis Canada KC343007 KC343975 KC343249 KC343733
D. alnea CBS 146.46 Alnus sp. Netherlands KC343008 KC343976 KC343250 KC343734
D. ambigua CBS 114015 Pyrus communis South Africa KC343010 KC343978 KC343252 KC343736
D. ampelina STEU2660 Vitis vinifera France AF230751 JX275452 AY745026 AY745056
D. amygdali CBS 115620 Prunus persica. USA KC343020 KC343988 KC343262 KC343746
CBS111811 Vitis vinifera South Africa KC343019 KC343987 KC343261 KC343745
CBS120840 Prunus salicina South Africa KC343021 KC343989 KC343263 KC343747
CBS 126679 Prunus dulcis Portugal KC343022 KC343990 KC343264 KC343748
D. anacardii CBS 720.97 Anacardium occidentale East Africa KC343024 KC343992 KC343266 KC343750
D. angelicae CBS 111592 Heracleum sphondylium Austria KC343027 KC343995 KC343269 KC343753
D. apiculate CGMCC 3 17533 Camellia sinensis China KP267896 KP293476 N/A KP267970
LC3187 Camellia sinensis China KP267866 KP293446 N/A KP267940
D. arengae CBS 114979 Arenga engleri Hong Kong KC343034 KC344002 KC343276 KC343760
D. aquatica IFRDCC 3051 Aquatic habitat China JQ797437 N/A N/A N/A
D. arctii CBS 139280 Arctium lappa Austria KJ590736 KJ610891 KJ612133 KJ590776
D. arengae CBS 114979 Arenga enngleri Hong Kong KC343034 KC344002 KC343276 KC343760
D. aseana MFLUCC 12-0299a Unknown dead leaf Thailand KT459414 KT459432 KT459464 KT459448
D. asheicola CBS 136967 Vaccinium ashei Chile KJ160562 KJ160518 KJ160542 KJ160594
D. aspalathi CBS 117169 Aspalathus linearis South Africa KC343036 KC344004 KC343278 KC343762
D. australafricana CBS 111886 Vitis vinifera Australia KC343038 KC344006 KC343280 KC343764
D. baccae CBS 136972 Vaccinium sp. Italy KJ160565 N/A N/A KJ160597
D. batatas CBS 122.21 Ipomoea batatas USA KC343040 KC344008 KC343282 KC343766
D. beilharziae BRIP 54792 Indigofera australis Australia JX862529 KF170921 N/A JX862535
D. benedicti BPI 893190 Salix sp. USA KM669929 N/A KM669862 KM669785
D. betulae CFCC 50469 Betula platyphylla China KT732950 KT733020 KT732997 KT733016
D. betulicola CFCC 51128 Betula albo-sinensis China KX024653 KX024657 KX024659 KX024655
CFCC 52560 Betula albo- sinensis China MH121495 MH121577 MH121419 MH121537
D. betulina CFCC 52561 Betula costata China MH121496 MH121578 MH121420 MH121538
D. bicincta CBS 121004 Juglans sp. USA KC343134 KC344102 KC343376 KC343860
D. biconispora CGMCC 3.17252 Citrus grandis China KJ490597 KJ490418 KJ490539 KJ490476
D. biguttulata CFCC 52584 Juglans regia China MH121519 MH121598 MH121437 MH121561
D. biguttusis CGMCC 317081 Lithocarpus glabra China KF576282 KF576306 N/A KF576257
CGMCC 317081 Lithocarpus glabra China KF576283 KF576307 N/A KF576258
D. bohemiae CBS 1433477 Vitis vinifera Czech Republic MG281015 MG281188 MG281710 MG281536
CBS 1433478 Vitis vinifera Czech Republic MG281016 MG281189 MG281711 MG281537
D. brasiliensis CBS 133183 Aspidosperma sp. Brazil KC343042 KC344010 KC343284 KC343768
D. caatingaensis CBS 141542 Tacinga inamoena Brazil KY085927 KY115600 N/A KY115603
D. camptothecicola CFCC 51632 Camptotheca sp. China KY203726 KY228893 KY228877 KY228887
D. canthii CBS 132533 Canthium inerme South Africa JX069864 KC843230 KC843174 KC843120
D. caryae CFCC 52563 Carya illinoensis China MH121498 MH121580 MH121422 MH121540
CFCC 52564 Carya illinoensis China MH121499 MH121581 MH121423 MH121541
D. cassines CPC 21916 Cassine peragua South Africa KF777155 N/A N/A KF777244
D. caulivora CBS 127268 Glycine max Croatia KC343045 KC344013 KC343287 KC343771
D. celeris CBS143349 Vitis vinifera Czech Republic MG281017 MG281190 MG281712 MG281538
CBS143350 Vitis vinifera Czech Republic MG281018 MG281191 MG281713 MG281539
D. celastrina CBS 139.27 Celastrus sp. USA KC343047 KC344015 KC343289 KC343773
D. cf nobilis CBS 113470 Castanea sativa South Korea KC343146 KC344114 KC343388 KC343872
CBS 587 79 Pinus pantepella Japan KC343153 KC344121 KC343395 KC343879
D. cercidis CFCC 52565 Cercis chinensis China MH121500 MH121582 MH121424 MH121542
D. chamaeropis CBS 454.81 Chamaerops humilis Greece KC343048 KC344016 KC343290 KC343774
D. charlesworthii BRIP 54884m Rapistrum rugostrum Australia KJ197288 KJ197268 N/A KJ197250
D. chensiensis CFCC 52567 Abies chensiensis China MH121502 MH121584 MH121426 MH121544
CFCC 52568 Abies chensiensis China MH121503 MH121585 MH121427 MH121545
D. cichorii MFLUCC 17-1023 Cichorium intybus Italy KY964220 KY964104 KY964133 KY964176
D. cinnamomi CFCC 52569 Cinnamomum sp. China MH121504 MH121586 N/A MH121546
D. cissampeli CBS 141331 Cissampelos capensis South Africa KX228273 KX228384 N/A N/A
D. citri CBS 135422 Citrus sp. Florida, USA KC843311 KC843187 KC843157 KC843071
AR4469 Citrus sp. Florida, USA KC843321 KC843167 KC843197 KC843081
D. citriasiana CGMCC 3.15224 Citrus unshiu China JQ954645 KC357459 KC357491 JQ954663
D. citrichinensis ZJUD34 Citrus sp. China JQ954648 N/A KC357494 JQ954666
ZJUD85 Citrus sp. China KJ490620 KJ490441 N/A KJ490499
D. collariana MFLU 17-2770 Magnolia champaca Thailand MG806115 MG783041 MG783042 MG783040
D. compacta CGMCC 3.17536 Camellia sinensis China KP267854 KP293434 N/A KP267928
D. conica CFCC 52571 Alangium chinense China MH121506 MH121588 MH121428 MH121548
D. convolvuli CBS 124654 Convolvulus arvensis Turkey KC343054 KC344022 KC343296 KC343780
D. crotalariae CBS 162.33 Crotalaria spectabilis USA KC343056 KC344024 KC343298 KC343782
D. cucurbitae CBS 136.25 Arctium sp. Unknown KC343031 KC343999 KC343273 KC343757
D. cuppatea CBS 117499 Aspalathus linearis South Africa KC343057 KC344025 KC343299 KC343783
D. cynaroidis CBS 122676 Protea cynaroides South Africa KC343058 KC344026 KC343300 KC343784
D. cytosporella FAU461 Citrus limon Italy KC843307 KC843221 KC843141 KC843116
D. diospyricola CPC 21169 Diospyros whyteana South Africa KF777156 N/A N/A N/A
D. discoidispora ZJUD89 Citrus unshiu China KJ490624 KJ490445 N/A KJ490503
D. dorycnii MFLUCC 17-1015 Dorycnium hirsutum Italy KY964215 KY964099 N/A KY964171
D. elaeagni-glabrae CGMCC 3.18287 Elaeagnus glabra China KX986779 KX999212 KX999281 KX999171
D.ellipicola CGMC 3 17084 Lithocarpus glabra China KF576270 KF576291 N/A KF576245
D.endophytica CBS133811 Schinus terebinthifolius Brazil KC343065 KC343065 KC343307 KC343791
LGMF911 Schinus terebinthifolius Brazil KC343066 KC344034 KC343308 KC343792
D.eres AR3519 Corylus avellana Austria KJ210523 KJ420789 KJ435008 KJ210547
CBS 109767 = AR3538 Acer sp. Austria DQ491514 KC344043 KC343317 KC343801
AR3560 Viburnum sp. Austria JQ807425 KJ420795 KJ435011 JQ807351
AR3723 Rubus fruticosus Austri JQ807428 KJ420793 KJ435024 JQ807354
AR4346 Prunus mume Korea JQ807429 KJ420823 KJ435003 JQ807355
AR4373 Ziziphus jujuba Korea JQ807442 KJ420798 KJ435013 JQ807368
AR4348 Prunus persica Korea JQ807431 KJ420811 KJ435004 JQ807357
AR4363 Malus sp. Korea JQ807436 KJ420809 KJ435033 JQ807362
AR4369 Pyrus pyrifolia Korea JQ807440 KJ420813 KJ435005 JQ807366
AR4371 Malus pumila Korea JQ807441 KJ420796 KJ435034 JQ807367
AR5193 Ulmus sp. Germany KJ210529 KJ420799 KJ434999 KJ210550
AR5197 Rhododendron sp. Germany KJ210531 KJ420812 KJ435014 KJ210552
CBS113470 Castanea sativa Australia KC343146 KC344114 KC343388 KC343872
CBS135428 Juglans cinerea USA KC843328 KC843229 KC843155 KC843121
CBS138594 Ulmus laevis Germany KJ210529 KJ420799 KJ434999 KJ210550
CBS138595 Ulmus laevis Germany KJ210533 KJ420817 KJ435006 KJ210554
CBS138597 Vitis vinifera France KJ210518 KJ420783 KJ434996 KJ210542
CBS138598 Ulmus sp. USA KJ210521 KJ420787 KJ435027 KJ210545
CBS138599 Acer nugundo Germany KJ210528 KJ420830 KJ435000 KJ210549
CBS439.82 Cotoneaster sp. UK FJ889450 JX275437 JX197429 GQ250341
DNP128.1 Castaneae mollissimae China JF957786 KJ420801 KJ435040 KJ210561
DNP129 Castanea mollissima China JQ619886 KJ420800 KJ435039 KJ210560
DP0177 Pyrus pyrifolia New Zealand JQ807450 KJ420820 KJ435041 JQ807381
DP0179 Pyrus pyrifolia New Zealand JQ807452 KJ420803 KJ43502 JQ807383
DP0180 Pyrus pyrifolia New Zealand JQ807453 KJ420804 KJ435029 JQ807384
DP0438 Ulmus minor Austria KJ210532 KJ420816 KJ435016 KJ210553
FAU506 Cornus florida USA KJ210526 KJ420792 KJ435012 JQ807403
DP0590 Pyrus pyrifolia New Zealand JQ807464 KJ420810 KJ435037 JQ807394
DP0591 Pyrus pyrifolia New Zealand JQ807465 KJ420821 KJ435018 JQ807395
DP0666 Juglans cinerea USA KJ210522 KJ420788 KJ435007 KJ210546
FAU483 Malus sp. Netherlands KJ210537 KJ420827 KJ435022 KJ210556
FAU522 Sassafras albidum USA KJ210525 KJ420791 KJ435010 JQ807406
FAU532 Chamaecyparis thyoides USA JQ807333 KJ420815 KJ435015 JQ807408
LCM11401b Ulmus sp. USA KJ210520 KJ420786 KJ435026 KJ210544
LCM11401 Ulmus sp. USA KJ210521 KJ420787 KJ435027 KJ210545
M1118 Vitis vinifera France KJ210519 KJ420784 KJ434997 KJ210543
M1115 Daphne laureola France KJ210516 KJ420781 KJ434994 KJ210540
MAFF625033 Pyrus pyrifolia Japan JQ807468 KJ420814 KJ435017 JQ807417
MAFF625034 Pyrus pyrifolia Japan JQ807469 KJ420819 KJ435023 JQ807418
D. eucalyptorum CBS 132525 Eucalyptus sp. Australia NR120157 N/A N/A N/A
D. foeniculacea CBS 123208 Foeniculum vulgare Portugal KC343104 KC344072 KC343346 KC343830
D. fraxini- angustifoliae BRIP 54781 Fraxinus angustifolia Australia JX862528 KF170920 N/A JX862534
D. fraxinicola CFCC 52582 Fraxinus chinensis China MH121517 N/A MH121435 MH121559
D. fukushii MAFF 625034 Pyrus pyrifolia Japan JQ807469 N/A N/A JQ807418
D. fusicola CGMCC 3.17087 Lithocarpus glabra China KF576281 KF576305 KF576233 KF576256
D. ganjae CBS 180.91 Cannabis sativa USA KC343112 KC344080 KC343354 KC343838
D. garethjonesii MFLUCC 12-0542a Unknown dead leaf Thailand KT459423 KT459441 KT459470 KT459457
D. goulteri BRIP 55657a Helianthus annuus Australia KJ197290 KJ197270 N/A KJ197252
D. gulyae BRIP 54025 Helianthus annuus Australia JF431299 JN645803 N/A KJ197271
D. helianthi CBS 592.81 Helianthus annuus Serbia KC343115 KC344083 KC343357 KC343841
D. helicis AR5211 Hedera helix France KJ210538 KJ420828 KJ435043 KJ210559
D. heterophyllae CBS 143769 Acacia heterohpylla France MG600222 MG600226 MG600218 MG600224
D. hickoriae CBS 145.26 Carya glabra USA KC343118 KC344086 KC343360 KC343844
D. hispaniae CPC 30321 Vitis vinifera Spain MG281123 MG281296 MG281820 MG281644
D. hongkongensis CBS 115448 Dichroa febrífuga China KC343119 KC344087 KC343361 KC343845
D.hungariae CBS143353 Vitis vinifera Hungary MG281126 MG281299 MG281823 MG281647
D. incompleta CGMCC 3.18288 Camellia sinensis China KX986794 KX999226 KX999289 KX999186
D. inconspicua CBS 133813 Maytenus ilicifolia Brazil KC343123 KC344091 KC343365 KC343849
D. infecunda CBS 133812 Schinus sp. Brazil KC343126 KC344094 KC343368 KC343852
D. isoberliniae CPC 22549 Isoberlinia angolensis Zambia KJ869133 KJ869245 N/A N/A
CFCC 51135 Juglans mandshurica China KU985102 KX024635 KX024617 KX024629
D. kadsurae CFCC 52587 Kadsura longipedunculata China MH121522 MH121601 MH121440 MH121564
D. kochmanii BRIP 54033 Helianthus annuus Australia JF431295 N/A N/A JN645809
D. kochmanii BRIP 54034 Helianthus annuus Australia JF431296 N/A N/A JN645810
D. kongii BRIP 54031 Portulaca grandifl a Australia JF431301 KJ197272 N/A JN645797
D. litchicola BRIP 54900 Litchi chinensis Australia JX862533 KF170925 N/A JX862539
D. lithocarpus CGMCC 3.15175 Lithocarpus glabra China KC153104 KF576311 KF576235 KC153095
D. longicicola CGMCC 3.17089 Lithocarpus glabra China KF576267 KF576291 N/A KF576242
CGMCC 3 17090 Lithocarpus glabra China KF576268 KF576292 N/A KF576243
D. longispora CBS 194.36 Ribes sp. Canada KC343135 KC344103 KC343377 KC343861
D. lonicerae MFLUCC 17-0963 Lonicera sp. Italy KY964190 KY964073 KY964116 KY964146
D. lusitanicae CBS 123212 Foeniculum vulgare Portugal KC343136 KC344104 KC343378 KC343862
D. macinthoshii BRIP 55064a Rapistrum rugostrum Australia KJ197289 KJ197269 N/A KJ197251
D. mahothocarpus CGMCC 3.15181 Lithocarpus glabra China KC153096 KF576312 N/A KC153087
D. malorum CAA734 Malus domestica Portugal KY435638 KY435668 KY435658 KY435627
D.momicola MFLUCC 16-0113 Prunus persica Hubei, China KU557563 KU557587 KU557611 KU557631
D. maritima DAOMC 250563 Picea rubens Canada N/A KU574616 N/A N/A
D. masirevicii BRIP 57892a Helianthus annuus Australia KJ197277 KJ197257 N/A KJ197239
D. mayteni CBS 133185 Maytenus ilicifolia Brazil KC343139 KC344107 KC343381 KC343865
D. maytenicola CPC 21896 Maytenus acuminata South Africa KF777157 KF777250 N/A N/A
D. melonis CBS 507.78 Cucumis melo USA KC343142 KC344110 KC343384 KC343868
D. middletonii BRIP 54884e Rapistrum rugostrum Australia KJ197286 KJ197266 N/A KJ197248
D. miriciae BRIP 54736j Helianthus annuus Australia KJ197282 KJ197262 N/A KJ197244
D. multigutullata ZJUD98 Citrus grandis China KJ490633 KJ490454 N/A KJ490512
D. musigena CBS 129519 Musa sp. Australia KC343143 KC344111 KC343385 KC343869
D. neilliae CBS 144.27 Spiraea sp. USA KC343144 KC344112 KC343386 KC343870
D. neoarctii CBS 109490 Ambrosia trifi USA KC343145 KC344113 KC343387 KC343871
D.neoraonikayaporum MFLUCC 14-1136 Tectona grandis Thailand KU712449 KU743988 KU749356 KU749369
D. nobilis CBS 113470 Castanea sativa Korea KC343146 KC344114 KC343388 KC343872
D. nothofagi BRIP 54801 Nothofagus cunninghamii Australia JX862530 KF170922 N/A JX862536
D. novem CBS 127270 Glycine max Croatia KC343155 KC344123 KC343397 KC343881
D. ocoteae CBS 141330 Ocotea obtusata France KX228293 KX228388 N/A N/A
D. oraccinii CGMCC 3.17531 Camellia sinensis China KP267863 KP293443 N/A KP267937
D. ovalispora ICMP20659 Citrus limon China KJ490628 KJ490449 N/A KJ490507
D. ovoicicola CGMCC 3.17093 Citrus sp. China KF576265 KF576289 KF576223 KF576240
D. oxe CBS 133186 Maytenus ilicifolia Brazil KC343164 KC344132 KC343406 KC343890
D. padina CFCC 52590 Padus racemosa China MH121525 MH121604 MH121443 MH121567
CFCC 52591 Padus racemosa China MH121526 MH121605 MH121444 MH121568
D. pandanicola MFLU 18-0006 Pandanus sp. Thailand MG646974 MG646930 N/A N/A
D. paranensis CBS 133184 Maytenus ilicifolia Brazil KC343171 KC344139 KC343413 KC343897
D. parapterocarpi CPC 22729 Pterocarpus brenanii Zambia KJ869138 KJ869248 N/A N/A
D. pascoei BRIP 54847 Persea americana Australia JX862532 KF170924 N/A JX862538
D. passifl ae CBS 132527 Passifl a edulis South America JX069860 N/A N/A N/A
D. passifl CBS 141329 Passifl a foetida Malaysia KX228292 KX228387 N/A N/A
D. penetriteum CGMCC 3.17532 Camellia sinensis China KP714505 KP714529 N/A KP714517
D. perjuncta CBS 109745 Ulmus glabra Austria KC343172 KC344140 KC343414 KC343898
D. perseae CBS 151.73 Persea gratissima Netherlands KC343173 KC344141 KC343415 KC343899
D. pescicola MFLU 16-0105 Prunus persica Hubei, China KU557555 KU557579 KU557603 KU557623
D. phaseolorum AR4203 Phaseolus vulgaris USA KJ590738 KP004507 N/A N/A
D.phragmitis CBS 138897 Phragmites australis China KP004445 KP004507 N/A N/A
D. podocarpi- macrophylli CGMCC 3.18281 Podocarpus macrophyllus China KX986774 KX999207 KX999278 KX999167
D. pseudomangiferae CBS 101339 Mangifera indica Dominican Republic KC343181 KC344149 KC343423 KC343907
D.pseudophoenicicola CBS 462.69 Phoenix dactylifera Spain KC343184 KC344152 KC343426 KC343910
D. pseudotsugae MFLU 15-3228 Pseudotsuga menziesii Italy KY964225 KY964108 KY964138 KY964181
D. psoraleae CBS 136412 Psoralea pinnata South Africa KF777158 KF777251 N/A KF777245
D. psoraleae- pinnatae CBS 136413 Psoralea pinnata South Africa KF777159 KF777252 N/A N/A
D. pterocarpi MFLUCC 10-0571 Pterocarpus indicus Thailand JQ619899 JX275460 JX197451 JX275416
D. pterocarpicola MFLUCC 10-0580 Pterocarpus indicus Thailand JQ619887 JX275441 JX197433 JX275403
D. pulla CBS 338.89 Hedera helix Yugoslavia KC343152 KC344120 KC343394 KC343878
D. pyracanthae CAA483 Pyracantha coccinea Portugal KY435635 KY435666 KY435656 KY435625
D. racemosae CBS 143770 Euclea racemosa South Africa MG600223 MG600227 MG600219 MG600225
D. raonikayaporum CBS 133182 Spondias mombin Brazil KC343188 KC344156 KC343430 KC343914
D. ravennica MFLUCC 15-0479 Tamarix sp. Italy KU900335 KX432254 N/A KX365197
D. rhusicola CBS 129528 Rhus pendulina South Africa JF951146 KC843205 KC843124 KC843100
D. rosae MFLU 17-1550 Rosa sp. Thailand MG828894 MG843878 N/A N/A
D. rosicola MFLU 17-0646 Rosa sp. UK MG828895 MG843877 N/A MG829270
D. rostrata CFCC 50062 Juglans mandshurica China KP208847 KP208855 KP208849 KP208853
D. rudis AR3422 Laburnum anagyroides Austria KC843331 KC843177 KC843146 KC843090
D. saccarata CBS 116311 Protea repens South Africa KC343190 KC344158 KC343432 KC343916
D. sackstonii BRIP 54669b Helianthus annuus Australia KJ197287 KJ197267 N/A KJ197249
D. salicicola BRIP 54825 Salix purpurea Australia JX862531 JX862531 N/A JX862537
D. sambucusii CFCC 51986 Sambucus williamsii China KY852495 KY852511 KY852499 KY852507
D. schini CBS 133181 Schinus terebinthifolius Brazil KC343191 KC344159 KC343433 KC343917
D. schisandrae CFCC 51988 Schisandra chinensis China KY852497 KY852513 KY852501 KY852509
D. schoeni MFLU 15-1279 Schoenus nigricans Italy KY964226 KY964109 KY964139 KY964182
D. sclerotioides CBS 296.67 Cucumis sativus Netherlands KC343193 KC344161 KC343435 KC343919
D. sennae CFCC 51636 Senna bicapsularis China KY203724 KY228891 KY228875 KY228885
D. sennicola CFCC 51634 Senna bicapsularis China KY203722 KY228889 KY228873 KY228883
D. serafi BRIP 55665a Helianthus annuus Australia KJ197274 KJ197254 N/A KJ197236
D. siamensis MFLUCC 10-573a Dasymaschalon sp. Thailand JQ619879 JX275429 N/A JX275393
D. sojae FAU635 Glycine max Ohio, USA KJ590719 KJ610875 KJ612116 KJ590762
BRIP 54033 Helianthus annuus Australia JF431295 KJ160528 KJ160548 JN645809
CBS116019 Caperonia palustris USA KC343175 KJ610862 KJ612103 KC343901
DP0601 Glycine max USA KJ590706 N/A N/A KJ590749
DP0605 Glycine max USA KJ590707 KJ610863 KJ612104 KJ590750
DP0616 Glycine max USA KJ590715 KJ610871 KJ612112 KJ590758
FAU455 Stokesia laevis USA KJ590712 KJ610870 KJ612111 KJ590755
FAU458 Stokesia laevis USA KJ590710 KJ610866 KJ612107 KJ590753
FAU459 Stokesia laevis USA KJ590709 KJ610865 KJ612106 KJ590752
FAU499 Asparagus officinalis USA KJ590717 KJ610873 KJ612114 KJ590760
FAU604 Glycine max USA KJ590716 KJ610872 KJ612113 KJ590759
FAU636 Glycine max USA KJ590718 KJ610874 KJ612115 KJ590761
ZJUD68 Glycine max USA KJ490603 KJ490424 N/A KJ490482
ZJUD69 Citrus reticulata China KJ490604 KJ490425 N/A KJ490483
ZJUD70 Citrus limon China KJ490605 KJ490426 N/A KJ490484
D. spartinicola CBS 140003 Spartium junceum Spain KR611879 KC344180 KC343454 N/A
D. sterilis CBS 136969 Vaccinium corymbosum Italy KJ160579 KJ490408 N/A KJ160611
D. stictica CBS 370.54 Buxus sampervirens Italy KC343212 MG746631 N/A KC343938
D. subclavata ICMP20663 Citrus unshiu China KJ490587 MG746634 N/A KJ490466
D. subcylindrospora MFLU 17-1195 Salix sp. China MG746629 KC344182 KC343456 MG746630
D. subellipicola MFLU 17-1197 on dead wood China MG746632 KU557591 KU557567 MG746633
D. subordinaria CBS 464.90 Plantago lanceolata New Zealand KC343214 KU557592 KU557568 KC343940
D. taoicola MFLUCC 16 0117 Prunus persica Hubei, China NR154923 KU743977 KU712430 KU557635
D. tectonae MFLUCC 12 0777 Tectona grandis Thailand NR147590 KU743977 KU749345 KU749359
D. tectonigena MFLUCC 12-0767 Tectona grandis China KU712429 JX275449 JX197440 KU749371
D. terebinthifolii CBS 133180 Schinus terebinthifolius Brazil KC343216 N/A N/A KC343942
D. thunbergii MFLUCC 10-576a Th laurifolia Thailand JQ619893 MF279873 MF279888 JX275409
D. thunbergiicola MFLUCC 12-0033 Th laurifolia Thailand KP715097 MF279874 MF279889 KP715098
D. tibetensis CFCC 51999 Juglandis regia China MF279843 KY964096 KY964127 MF279858
D. torilicola MFLUCC 17-1051 Torilis arvensis Italy KY964212 KR936132 N/A KY964168
D. toxica CBS 534.93 Lupinus angustifolius Australia KC343220 KJ610881 KJ612122 KC343946
D. tulliensis BRIP62248a Theobroma cacao Australia KR936130 N/A MH121445 KR936133
D. ueckerae FAU656 Cucumis melo USA KJ590726 N/A MH121446 KJ590747
D. ukurunduensis CFCC 52592 Acer ukurunduense China MH121527 KX999230 N/A MH121569
CFCC 52593 Acer ukurunduense China MH121528 KJ490408 N/A MH121570
D. undulata CGMCC 3.18293 Leaf of unknown host China-Laos border KX986798 KJ490406 N/A KX999190
D. unshiuensis ZJUD50 Fortunella margarita China KJ490585 KC344195 KC343469 KJ490464
D. vaccini CBS160 32 Oxycoccus macrocarpos USA KC343228 KJ869247 N/A KC343954
D. vangueriae CPC 22703 Vangueria infausta Zambia KJ869137 KX999223 N/A N/A
D. vawdreyi BRIP 57887a Psidium guajava Australia KR936126 KP247575 N/A KR936129
D. velutina CGMCC 3.18286 Neolitsea sp. China KX986790 KX999216 N/A KX999182
D. virgiliae CMW40748 Virgilia oroboides South Africa KP247566 KX999228 KX999290 N/A
D. xishuangbanica CGMCC 3.18282 Camellia sinensis China KX986783 KC343972 KC343246 KX999175
D. yunnanensis CGMCC 3.18289 Coff sp. China KX986796 N/A KX999290 KX999188
Diaporthella corylina CBS 121124 Corylus sp. China KC343004 KC343972 KC343246 KC343730

BRIP, Plant Pathology Herbarium, Department of Primary Industries, Dutton Park, Queensland, Australia; CPC, Culture collection of P.W. Crous, housed at Westerdijk Fungal Biodiversity Institute; CBS, Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands; DAOM, Canadian Collection of Fungal Cultures or the National Mycological Herbarium, Plant Research Institute, Department of Agriculture (Mycology), Ottawa, Canada; ICMP, International Collection of Microorganisms from Plants, Landcare Research, Auckland, New Zealand. MFLUCC, Mae Fah Luang University culture collection, Mae Fah Luang University, Chiang Rai, 57100, Thailand. JZB, Culture collection of Institute of Plant and Environment Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China. AR, DAN, DNP, FAU, DLR, DF, DP, LCM, M, isolates in SMML culture collection, USDA-ARS, Beltsville, MD, USA, and MAFF, NIAS Genebank Project, Ministry of Agriculture, Forestry and Fisheries, Japan. Ex-type and ex-epitype cultures are indicated in bold. ITS, internal transcribed spacers 1 and 2 together with 5.8S nrDNA; β-tubulin, partial beta-tubulin gene; CAL, partial calmodulin gene and EF-1α, partial translation elongation factor 1-α gene.

In PAUP, ambiguous regions in the alignment were excluded for further analyses, and gaps were treated as missing data. The stability of the trees was evaluated by 1000 bootstrap replications. Branches of zero length were collapsed, and all multiple parsimonious trees were saved. Parameters, including tree length (TL), consistency index (CI), retention index (RI), relative consistency index (RC), and homoplasy index (HI) were calculated. Differences between the trees inferred under different optimality criteria were evaluated using Kishino-Hasegawa tests (KHT) (Kishino and Hasegawa, 1989). The evolutionary models for each locus used in Bayesian analysis and ML were selected using MrModeltest v. 2.3 (Nylander, 2004). ML analyses were accomplished using RAxML-HPC2 on XSEDE (8.2.8) (Stamatakis et al., 2008; Stamatakis, 2014) in the CIPRES Science Gateway platform (Miller et al., 2010) using the GTR + I + G model of evolution with 1000 non-parametric bootstrapping iterations. Bayesian analysis was performed in MrBayes v. 3.0b4 (Ronquist and Huelsenbeck, 2003), and posterior probabilities (PPs) were determined by Markov chain Monte Carlo sampling (MCMC). Six simultaneous Markov chains were run for 106 generations, sampling the trees at every 100th generation. From the 10,000 trees obtained, the first 2,000 representing the burn-in phase were discarded. The remaining 8,000 trees were used to calculate PPs in a majority rule consensus tree. Alignment generated in this study is submitted to TreeBASE (https://treebase.org/treebase-web/home.html) under the submission number 24324. Taxonomic novelties were submitted to the Faces of Fungi database (Jayasiri et al., 2015) and Index fungorum (http://www.indexfungorum.org). New species are described following Jeewon and Hyde (2016).

Morphology and Culture Characteristics

Colony morphology and conidial characteristics were examined for Diaporthe species identified by phylogenetic analysis. Colony colors were examined according to Rayner (1970) after 7 days of growth on PDA in the dark at 25°C. Digital images of morphological structures mounted in water were taken using an Axio Imager Z2 photographic microscope (Carl Zeiss Microscopy, Oberkochen, Germany). Measurements were taken using ZEN PRO 2012 (Carl Zeiss Microscopy). Conidial length and width were measured for 40 conidia per isolate, and the mean values were calculated for all measurements. Conidial shape, color, and guttulation were recorded.

Genetic Diversity and Population Structure Analysis

Among the identified species, only one, Diaporthe eres, had a count of >20 individuals. As a result, only D. eres was selected for the analysis of genetic diversity and population relationships. For the D. eres population, diversity indices were calculated for each gene region and the combined sequence dataset. DnaSP v. 6.12 (Librado and Rozas, 2009) was employed to calculate haplotype richness (hR), the total number of haplotypes, Watterson's theta (Θw), and pairwise nucleotide diversity (JI). To overcome the population size effects, hR, Θw and JI were calculated after 1,000 repetitions, and the median estimate was recorded for each parameter. To understand the potential departure from an equilibrium model of evolution, Tajima's D was calculated using DnaSP v. 6.12 with a permutation test of 1,000 replicates. The minimum numbers of recombination events (ZnS) used by Kelly (1997) and the recombination parameters Za and ZZ used by Hudson (1983) were calculated for each gene region and the combined data set. Diaporthe eres haplotype networks were constructed using Network v. 5.0 (Bandelt et al., 1999).

Network Analysis

To understand the relationship among different geographical populations, recombination parameters were calculated, and haplotype networks were constructed. In this analysis, the combined dataset of Diaporthe eres isolates from China alone and Chinese isolates combined with European isolates (Guarnaccia et al., 2018) were used. ZnS, used by Kelly (1997), and the recombination parameters Za and ZZ (Hudson, 1983; Kelly, 1997) were calculated using DnaSP v. 6.12. The haplotype data generated using DnaSP v. 6 were used to construct a median-joining network in Network v. 5.0 (Bandelt et al., 1999).

Pathogenicity Assay

The pathogenicity and aggressiveness of the Diaporthe species were tested using detached green shoots of the V. vinifera cultivar Summer Black. Healthy, 30–50 cm long green shoots (including at least two nodes) were obtained from “Shunyi Xiangyi” vineyard in Beijing, China, where Diaporthe species were not recorded. The cuttings were surface-sterilized with 70% ethanol by wiping with cotton swabs. A shallow wound (5 mm length, 2 mm deep) was made in the center of each shoot using a sterilized scalpel. Mycelial plugs were taken from the growing margin of a 5-day-old culture grown in PDA and inoculated at the wound site. Non-colonized sterile PDA plugs were used for inoculation of shoots as a negative control. To prevent drying, all inoculated areas were covered with Para-film (Bemis, USA). Inoculated shoots were kept in a growth chamber for 21 days at 25°C with a 12 h photoperiod. The experiment was organized with 10 replicates for each isolate. Pathogenicity test was repeated three times with same controlled environment. A total of 16 strains from eight species were tested. The presence of lesions advancing beyond the original 0.5 cm diameter inoculation point was considered indicative of pathogenicity. The experimental design was completely randomized. Data were analyzed with a one-way ANOVA (analysis of variance) using Minitab v. 16.0 (Minitab Inc., Boston, MA, USA), with statistical significance set at the 5% level. The pathogens were re-isolated to confirm their identity.

Results

Initial Species Identification and Phylogenetic Analyses

During our field survey on six grape-growing provinces in China (Figure 1), we collected samples with typical symptoms associated with Diaporthe dieback, such as wedge-shaped cankers, and light brown streaking of the wood (Figure 2). However, these symptoms are sometimes confused with other grape trunk disease symptoms caused by Botryosphaeria dieback, Eupta, and Esca (Mondello et al., 2018). Hence, further confirmation is required by isolating and identifying causal organisms. One hundred and eleven Diaporthe isolates were initially identified by colony characteristics, such as abundant tufted white aerial mycelia on agar medium. The ITS gene regions were sequenced for all fungi isolated from diseased shoots and compared with those in GenBank using the MegaBLAST tool in GenBank. The isolates showed 95–99% similarity to known Diaporthe species in GenBank, and these closely related known species were included in the phylogenetic analysis.

To understand the taxonomic placements of our isolates, additional gene regions, including those encoding EF-1α, β-tubulin, and CAL, were sequenced. Then, phylogenetic trees were constructed for each individual gene region. The concatenated sequence data set consisted of 94 isolates (out of 111, due to sequencing errors) from the current study (Table 3) and 197 isolates originating from GenBank (Table 2), with one outgroup taxon, Diaporthella corylina (CBS 121124). A comparison of maximum likelihood (ML) analysis results for each gene region is given in Table 4. In the ML analysis, the resulting tree of the combined data set of ITS, β-tubulin, CAL, and EF-1α genes had the best resolution of taxa (Figure 3). Therefore, in the present study, we used the combined sequence data to understand the taxonomic placements of the Diaporthe species isolated from grapevines in China. A Bayesian analysis resulted in 10,001 trees after 2,000,000 generations. The first 1,000 trees, representing the burn-in phase of the analyses, were discarded, while the remaining 9,001 trees were used for calculating posterior probabilities (PPs) in the majority-rule consensus tree. The dataset consisted of 1,494 characters with 727 constant characters and 1,006 parsimony-informative and 213 parsimony-uninformative characters. The maximum number of trees generated was 1,000, and the most parsimonious trees had a tree length of 9,862 (CI = 0.249, RI = 0.805, RC = 0.201, HI = 0.751).

Table 4.

Comparison of ML analyses results for each gene region.

Data set ITS β-tubulin CAL EF-1α ITS+ β-tubulin+ CAL+ EF-1α
Constant characters 226 226 226 68
Parsimony-uninformative characters 107 26 107 48
Parsimony-informative characters 189 249 189 335
ML optimization likelihood value −51,581.507970 −9741.212701 −7853.669691 −16943.655728 −50,588.257001
Distinct alignment patterns 291 304 293 293 1,330
Undetermined characters or gaps 7.18% 26.12% 8.74% 28.55% 28.70%
ESTIMATED BASE FREQUENCIES
A 0.244043 0.200039 0.211490 0.220112 0.221742
C 0.277339 0.349071 0.313694 0.329420 0.313804
G 0.247357 0.233934 0.253908, 0.250506 0.235189
T 0.231261 0.216955 0.220908 0.220908 0.229264
SUBSTITUTION RATES
AC 1.300271 0.791706 1.041213 1.457977 1.328496
AG 2.994990 3.761550 4.289330 3.778337 3.630252
AT 1.401626 0.962021 1.307157 1.339450 1.324920
CG 0.826919 0.668475 1.259772 1.119872 0.954109
CT 7.266633 7.266633 5.662938 3.976963 4.974568
GT 1.000000 1.000000 1.000000 1.000000 1.000000
Proportion of invariable sites (I) 0.274443 0.350656 0.274443 0.274443 0.269146
Gamma distribution shape parameter (α) 0.405766 2.208572 0.405766 0.405766 0.869283

Figure 3.

Figure 3

RAxML tree based on analysis of a combined dataset of ITS, β-tubulin, CAL, and EF-1α sequences. Bootstrap support values for ML and MP equal to or >50% are shown as ML/MP above the nodes. The isolates obtained for the present study are shown in blue for already known species, and novel taxa are shown in red. Ex-type strains are indicated in bold. The tree is rooted using Diaporthella corylina. The scale bar represents the expected number of nucleotide substitutions per site.

In the phylogenetic tree generated using the combined data set (Figure 3), 36 isolates from the present study clustered with Diaporthe eres in the D. eres complex. This group represents 37.5% of the total isolates, and these isolates were obtained from five provinces. Sixteen isolates (19.76% of the total isolates) clustered with Diaporthe sojae (D. sojae) species in the D. sojae complex. Two isolates from Heilongjiang province clustered together with Diaporthe gulyae (D. gulyae) (BRIP 54025). In addition, two isolates clustered with Diaporthe unshiuensis (D. unshiuensis) (ZJUD52) from Hubei province, and another two isolates that were also from Hubei province clustered with Diaporthe pescicola (D. pescicola) (MFLUCC 16-0105). The remaining isolates (35 in total) did not cluster with any known Diaporthe species. Thus, these were putatively identified as belonging to three novel species (Figure 3): D. hubeiensis, D. guangxiensis, and D. viniferae. Diaporthe hubeiensis (D. hubeiensis) was isolated from grapevines from Hubei province and represents 12.5% of the total isolates. This species is a sister taxon with Diaporthe alangi (D. alangi) (CFCC52556). The remaining two new taxa were isolated from grapevines from Guangxi Province. Diaporthe guangxiensis (D. guangxiensis) was represented by 11 isolates (13.54%), and it is closely associated with Diaporthe cercidis (D. cercidis) (CFCC5255). Diaporthe viniferae (D. viniferae) was represented by 8 isolates (10.41%), and its closest relative is Diaporthe pandanicola (D. pandanicola) (MFLU 18-0006).

Taxonomic Novelties

Diaporthe guangxiensis (D. guangxiensis) Dissanayake, X.H. Li & K.D. Hyde, sp. nov. (Figure 4).

Figure 4.

Figure 4

Novel Diaporthe taxa identified in the present study (A–F) Diaporthe guangxiensis (A,B) Culture on PDA after 5 days; (C) Pycnidia on PDA; (D,E) Alpha conidia; and (F) Beta conidia. (G–L) Diaporthe hubeiensis (G,H) Culture on PDA after 5 days; (I) Pycnidia on PDA; (J) Conidiogenous cells for alpha and beta conidia; (K) Alpha conidia, and (L) Beta conidia. (M–R) Diaporthe viniferae (M,N) Culture on PDA after 5 days; (O) Pycnidia on PDA; (P,Q) Alpha conidia; and (R) Beta conidia. Scale bars: (D–F,J–L,P–R) = 1 mm; (C,I,O) = 10 μm.

Index Fungorum number—IF552578, Facesoffungi Number- FoF02725.

Etymology- In reference to the Guangxi Province, from where the fungus was first isolated.

Holotype—JZBH320094.

Description

Sexual morph: efforts were made to initiate sexual morphs, but various methods failed; Asexual morph: pycnidia on PDA 250-1550 μm (x = 1100 μm, n = 20) in diam., superficial, scattered on PDA, dark brown to black, globose, solitary, or clustered in groups of 3–5 pycnidia. Conidiophores aseptate, cylindrical, straight or sinuous, densely aggregated, terminal, slightly tapered toward the apex, 21–35 × 1.5–2.5 μm (x¯ = 27 × 2 μm). Alpha conidia biguttulate, hyaline, fusiform or oval, both ends obtuse 5.3–7.8 × 1.5–3.2 μm (x¯ = 6.8 × 2.5 μm n = 40). Beta conidia aseptate, hyaline, hamate, filiform, guttulate, tapering toward both ends 20–32 × 1–1.5 μm (x¯ = 27 × 1.5 μm, n = 20).

Culture Characteristics

Colonies on PDA reach 70 mm diam. after 7 days at 25°C, producing abundant white aerial mycelia and reverse fuscous black.

Material Examined

CHINA, Guangxi Province, Pingguo County, on diseased trunk of V. vinifera, 3 June 2015, X.H. Li, (JZBH320094, holotype); ex-type living cultures JZB320094).

Notes: Morphological characters such as spores and colony characteristics of D. guangxiensis fit well within the species concept of Diaporthe. DNA sequence analyses of the ITS, CAL, TUB, and EF genes showed a strongly supported monophyletic lineage with 78% ML, 70% MP bootstrap values and 0.95 posterior probabilities (Figure 3). The current species has a particular neighbor relationship with D. cercidis (CFCC52566). Morphologically, D. guangxiensis has larger conidiophores (27 × 2 μm) and smaller conidia (6.8 × 2.5 μm) than D. cercidis (7–17 × 1.4–2.1 μm conidiophores; 8.6 × 3.3 μm conidia) (Yang et al., 2018). In the comparisons of five gene regions between Diaporthe guangxiensis and D. cercidis, 51.5% of 458 nucleotides across the ITS (+5.8S) had base pair differences. In addition, comparisons of the protein-coding genes showed that there were 17.3, 0.66, and 9.06% polymorphic nucleotide sites between the two species for the CAL, β-tubulin and EF-1α genes, respectively.

Diaporthe hubeiensis Dissanayake, X.H. Li & K.D. Hyde, sp. nov. (Figure 4).

Index Fungorum number—IF552579, Facesoffungi Number- FoF 02726.

Etymology- In reference to the Hubei province, from where the fungus was first isolated.

Holotype – JZBH320123.

Description

Sexual morph: efforts were made to initiate sexual morphs, but various methods failed; Asexual morph: pycnidia on PDA varying in size up to 510 μm in diam., subglobose, occurs on PDA and double-autoclaved toothpicks after 3–4 weeks, solitary or forms in groups of stroma with a blackened margin. Ostiolate, up to 100 μm black cylindrical necks. Conidiophores were reduced to conidiogenous cells. Alpha conidia hyaline, smooth, biguttulate, blunt at both ends, ellipsoidal to cylindrical, 5.6–7.1 × 1–3.1 μm (x¯ = 6.1 × 1.8 μm n = 40). Beta conidia filiform, tapering toward both ends, scattered among the alpha conidia 17–27 × 1–1.5 μm (x¯ = 24 × 1.5 μm n = 40).

Culture Characteristics

Colonies on PDA reach 90 mm after 10 days at 25°C (covers total surface), abundant tufted white aerial mycelia, buff, numerous black pycnidia 0.5 mm in diam. occur in the mycelium, typically in the direction of the edge of the colony; reverse buff with concentric lines.

Material Examined

CHINA Hubei Province, Wuhan, on diseased trunk of V. vinifera, 30 June 2015, X. H Li (JZBH320123, holotype); ex-type living cultures JZB320123.

Notes: In phylogenetic analysis, D. hubeiensis was placed in a well-supported clade together with D. alangi (CFCC52556), D. tectonae (MFLUCC 12- 0777) and D. tulliensis (BRIP62248b) with 100% ML, 100% MP bootstrap values and 0.99 posterior probabilities. Diaporthe hubeiensis developed sister clade with D. alangi (CFCC52556) with 99% ML, 83% MP bootstrap values and 0.99 posterior probabilities. Morphologically, Diaporthe hubeiensis has smaller conidiophores and smaller conidia (6.1 × 1.8 μm) than D. alangi (7 × 2 μm), and it has no beta conidia in D. alangi (Yang et al., 2018). Diaporthe hubeiensis differs from D. tectonae by developing wider but shorter conidia (6.1 × 1.8 μm vs 5.5 × 2.6 μm) (Doilom et al., 2017). Compared to D. tulliensis, D. hubeiensis has smaller conidia (6.1 × 1.8 μm vs 5.5–6 μm) (Yang et al., 2018). In the ITS sequence comparison between D. hubeiensis and D. alangi, 44.6% of the 461 nucleotides across the ITS (+5.8S) were different. Of the three protein-coding genes, the two species showed 4.26% and 1.16% and 5.3% polymorphic nucleotide site differences for CAL, β-tubulin and EF-1α genes, respectively.

Diaporthe viniferae Dissanayake, X.H. Li & K.D. Hyde, sp. nov.

Index Fungorum number—IF552002, Facesoffungi Number- FoF 05981.

Etymology- In reference to the host V. vinifera.

Holotype—JZBH320071.

Description

Sexual morph: efforts were made to initiate sexual morphs, but various methods failed; Asexual morph: Pycnidia on PDA 363–937 μm (x = 529 μm, n = 20) in diam., superficial, scattered, dark brown to black, globose, solitary in most. Conidiophores were not observed. Conidiogenous cells were not observed. Alpha conidia biguttulate, hyaline, fusiform or oval, both ends obtuse 5–8.3 × 1.3–2.5 μm (x¯ = 6.4 × 2.1 μm). Beta conidia aseptate, hyaline, hamate, filiform, tapering toward both ends 23–35 × 1–1.5 μm (x¯ = 28 × 1.3 μm n = 40).

Culture Characteristics

Colonies on PDA reach 70 mm diam. after 7 days at 25°C, producing abundant white aerial mycelia and reverse fuscous black.

Material Examined

CHINA, Guangxi Province, Pingguo County, on the diseased trunk of V. vinifera, 3 June 2015, X.H. Li, (JZBH320071 holotype); ex-type living cultures JZB320071).

Notes: In the phylogenetic analysis of D. viniferae, a strongly supported monophyletic lineage with strong 77% ML and 71% MP bootstrap values and 0.95 PP was developed (Figure 3). The current species has a particular close relationship with D. pandanicola (MFLUCC 18-0006). In the original description of D. pandanicola, morphological characteristics were not given (Tibpromma et al., 2018). Therefore, these two species were compared based on only DNA sequence data. ITS sequence comparison between D. viniferae and D. pandanicola revealed that 2.9% of the 478 nucleotide sites across the ITS (+5.8S) regions were different. Similarly, 1.7% of the β-tubulin gene fragment was different.

Genetic Diversity and Population Structure Analysis

Table 5 summarized the genetic diversity data of D. eres associated with grapevines which were estimated using DnaSP V.6. In the analysis, the combined data set of ITS, β-tubulin, HIS, APN, and CAL gene sequences showed 0.16226 segregation sites per sequence and a haplotype diversity of 0.955. A haplotype network was developed for the D. eres species isolated from China using Network v. 5.0 (Figure 5). The resulting network combining ITS, β-tubulin, HIS, EF-1α, and CAL gene sequences gave two main clusters according to geographic origin. In the network, isolates from Hubei province were clustered into two main clades. A single haplotype (H-11) was clustered within the main Jilin clade. Haplotype 7 (from Hubei) and h-13 (from Sichuan Province) were connected with one intermediate haplotype to the two main clusters.

Table 5.

Polymorphism and genetic diversity of Diaporthe eres strains associated with Chinese grapevines.

Species Gene na bpb Theta-w Sc hd hde pif TDg
D. eres ITS 28 491 12.766 33 10 0.852 0.020 1.05556
β-tubulin 28 481 6 26 10 0.869 0.01362 −0.35308
HIS 15 244 0.04088 3 4 0.776 0.00167 −0.5791
CAL 17 399 0.03590 15 11 0.845 0.01391 0.63457
APN 16 680 0.00906 11 5 0.8 0.00445 −0.33503
Combine 25 3247 0.01576 60 17 0.958 0.020 0.20416
a

Sample size (n).

b

Total number of sites (bp).

c

Number of segregating sites (S).

d

Number of alleles (nA).

e

Haplotypic (allelic) diversity (hd).

f

Average nucleotide diversity (pi).

g

Tajima's D (TD), (R) Estimate of R (Rm) minimum recombination events.

Figure 5.

Figure 5

Haplotype network generated for the Diaporthe eres isolates obtained in the present study using Network v 6.0. At each node, sizes are propionate to the number of isolates. Blue, haplotypes from Jilin; Green, haplotypes from Hubei; purple, haplotypes from Sichuan; red, Median vectors.

To understand the relationship between Diaporthe isolates from Chinese vineyards and those from European vineyards, we calculated recombination parameters Z and ZnS. The combined data set consists of 135 sequences with 2203 sites. The estimate of R per gene was 6.6, and the minimum number of recombination events (Rm) was 15. Median-joining networks were constructed using both single-gene data files and a combined data set of ITS, β-tubulin, HIS, EF-1α, and CAL genes. The single-gene networks differed from each other, and the resulting patterns did not give a significant grouping. Therefore, in this study, only the combined network was considered (Figure 6). A total of 33 haplotypes were identified using DnaSP, and the haplotype data file was used to generate the haplotype network. In the resulting network, we found that Chinese haplotypes and Europe haplotypes were not shared and that there was no sharing of haplotypes among different provinces in China. However, the Chinese haplotypes were dispersed in the combined network, with the majority of isolates from Hubei located in two related clusters surrounded by European haplotypes. Similarly, the haplotypes from Sichuan and Jilin provinces were also dispersed in the network and close to both European and Chinese haplotypes.

Figure 6.

Figure 6

Haplotype network generated for the Diaporthe eres isolates from China and European countries using Network v 6.0. At each node, sizes are proportionate to the number of isolates.

Comparative Aggressiveness Among Diaporthe Species

Pathogenicity and aggressiveness among eight Diaporthe species isolated in our study were compared by inoculating them into the V. vinifera cultivar Summer Black. The inoculated shoots did not show significant lesion development within the first 2 weeks after inoculation. Brown necrotic lesions were detected both on the tissue surface and internally, advancing upwards, and downwards through the inoculation point. Twenty-one days after inoculation, D. gulyae developed the largest lesions (1.23 cm), followed by D. eres (0.94 cm). The remaining species, D. unshiuensis, D. viniferae, D. guangxiensis, D. pescicola, and D. sojae, exhibited similar levels of aggressiveness on grape shoots (Figure 7). Diaporthe hubeiensis was the least aggressive (0.5 cm) among the eight species.

Figure 7.

Figure 7

Pathogenicity test results for eight Diaporthe species associated with Chinese grapevines. (A) Variation in the development of lesions. (B) Mean lesion length (cm) at 21 days after inoculation of wounded detached healthy Vitis vinifera (V. vinifera) shoots (n = 10 per species).

Discussion

Grapevine trunk disease has become one of the most devastating grapevine diseases in recent decades. According to data collected worldwide, ~1.5 billion US dollars per year is spent to replace dead grapevines due to these trunk diseases (Hofstetter et al., 2012; Fontaine et al., 2016). This is a great concern among grape-producing countries, as the disease infects perennial parts of the vine and reduces the productive lifespan of vines by several years (Gramaje and Armengol, 2011). The disease ultimately affects the sustainability of the wine industry and table grape production (Fontaine et al., 2016). As the world's top grape-producing country, China has strived to improve the quality and quantity of grapes. Though they are the most important grapevine trunk diseases worldwide, there is no evidence of either the esca complex or Eutypa dieback in China (Fontaine et al., 2016). However, the third most common grapevine trunk disease, caused by the species in Botryosphaeriaceae (Yan et al., 2013, 2018), has been identified as the leading grapevine trunk pathogen complex in China. Unfortunately, over the last few years, diseases caused by Diaporthe species (Dissanayake et al., 2015a, 2017) have become the emerging trunk diseases in China. Understanding the diversity of the causative species and the genetic variation within pathogen populations could help in developing sustainable disease management strategies. In addition, understanding the relationships between European and Chinese isolates can help track disease spread, as both regions share similar disease severity and Diaporthe species that differ from those in North America (Fontaine et al., 2016; Úrbez Torres and O'Gorman, 2019). To achieve these objectives, disease surveys were conducted in six provinces. We isolated and identified 111 Diaporthe strains and showed that they belong to eight species.

In 1958, D. ampelina (= Phomopsis viticola) was identified infecting green shoots of grapevines (Pscheidt and Pearson, 1989). The disease was named “Phomopsis cane and trunk disease.” According to the USDA Fungal—host interaction database, there are 166 records of Diaporthe species associated with grapevines worldwide (https://nt.ars-grin.gov/fungaldatabases/fungushost/fungushost.cfm) (Farr and Rossman, 2019). These records are related to the following 27 Diaporthe species: Diaporthe ambigua (D. ambigua) (Dissanayake et al., 2017), D. ampelina (Úrbez-Torres et al., 2013), Diaporthe amygdali (D. amygdali) (Gomes et al., 2013; Guarnaccia et al., 2018), Diaporthe australafricana (D. australafricana) (Gomes et al., 2013), Diaporthe baccae (D. baccae), D. bohemiae, Diaporthe celeris (D. celeris) (Guarnaccia et al., 2018), Diaporthe chamaeropis (D. chamaeropis) (Lawrence et al., 2015), Diaporthe. Cynaroidis (Lesuthu et al., 2019) Diaporthe cytosporella (D. cytosporella), Diaporthe eres (D. eres), D. foeniculina, Diaporthe helianthi (D. helianthi) (Dissanayake et al., 2017; Guarnaccia et al., 2018; Farr and Rossman, 2019), Diaporthe hispaniae (D. hispaniae), D. hongkongensis (Dissanayake et al., 2017), Diaporthe hungariae (D. hungariae) (Guarnaccia et al., 2018), D. kyushuensis (Kajitani and Kanematsu, 2000), D. nebulae (Lesuthu et al., 2019) Diaporthe neotheicola (D. neotheicola) (Úrbez-Torres et al., 2013), Diaporthe nobilis (D. nobilis) (Dissanayake et al., 2017), D. novem (Lawrence et al., 2015), D. perjuncta (Mostert et al., 2001), Diaporthe perniciosa (D. perniciosa) (Stoykow and Denchev, 2006), D. phaseolorum (Dissanayake et al., 2017), Diaporthe rudis (D. rudis) (Guarnaccia et al., 2018), Diaporthe serafiniae (D. serafiniae) (Lesuthu et al., 2019), and D. sojae (Dissanayake et al., 2017). Among these species D. ampelina is the mostly reported species with 42 records in 12 countries. The present study introduces the three novel taxa D. guangxiensis, D. hubeiensis, and D. viniferae and three new host records: D. gulyae, D. pescicola, and D. unshiuensis.

Diaporthe eres was identified as the most prominent and widespread species associated with grapevine dieback in China (37.5% of total isolates). Other than on grapevines, D. eres has been reported on Aralia elata (A. elata) (Wu et al., 2012), Camellia species (Gao et al., 2016), Citrus species (Huang et al., 2015), peach (Dissanayake et al., 2017), and pear (Bai et al., 2015) plants in China, causing diebacks. Diaporthe eres has been reported in many countries, such as the USA (Úrbez-Torres et al., 2013; Lawrence et al., 2015), Croatia (Kaliterna et al., 2012), Greece (Thomidis and Michailides, 2009), Italy (Cinelli et al., 2016), Latvia (Lombard et al., 2014), Poland (Kowalski et al., 2016), Russia, Serbia (Petrovic et al., 2015), and South Africa (Van Niekerk et al., 2005; Lesuthu et al., 2019) causing diseases on grapevines. These reports reveal that D. eres has a diverse host range and a broad geographical distribution. The second most abundant taxon, D. sojae, has a wide range of hosts as well, including Camptotheca acuminata (C. acuminata) (Chang et al., 2005), Glycine max, Cucumis melo (Lehman, 1923; Santos et al., 2011), Capsicum annuum (C. annuum) (Pennycook, 1989), Stokesia laevis (S. laevis) (Sogonov et al., 2008), and Helianthus annuus (H. annuus) (Thompson et al., 2011). These two Diaporthe species were previously identified and characterized from grapevines in China by Dissanayake et al. (2015a).

The present study recorded three Diaporthe species, D. gulyae, D. pescicola, and D. unshiuensis, associated with Vitis dieback for the first time. Diaporthe gulyae was previously reported on H. annuus in Australia (Thompson et al., 2011), Canada, and the United States (Mathew et al., 2015a,b) and on Carthamus lanatus (C. lanatus) in Italy (Andolfi et al., 2015). Diaporthe pescicola was previously described in association with peach shoot dieback in China (Dissanayake et al., 2017). Diaporthe unshiuensis was first described in China in 2015 as an endophyte of a Citrus sp. (Huang et al., 2015).

The identification and characterization of novel taxa and new host records is an indication of the high potential of Diaporthe to evolve rapidly. Host switching is often related to fungal adaptive ability (Bleuven and Landry, 2016). The changing environments and human interference present both challenges and opportunities for fungi, with some capable of switching from endophytic or saprobic lifestyles to pathogenic styles or becoming more aggressive and colonizing new hosts (Manawasinghe et al., 2018). The novel taxa and the new records reported here for grapevine trunk diseases in China might be due to these factors. During the past decade, northern China has become significantly warmer (Piao et al., 2010). The increased temperature could attract new pests and disease agents to the region. On the other hand, human-mediated factors can also influence the development of a new disease (McDonals, 2004). For example, in commercial grape vineyards, significant amounts of chemicals are applied annually in the form of pesticides and fungicides (Úrbez-Torres, 2011). Such applications could lead to the development of resistant strains of the target organism and non-target micro-fungi (Manawasinghe et al., 2018). Over time, strains and species that are more resistant and/or more aggressive could emerge. The recent identification of new species and new host records of Diaporthe in China and in Europe are consistent with the hypothesis. Studying the genetic diversity of pathogens provides clues to how host switches might have occurred and the genetic basis for new pathogen emergence.

The knowledge of the genetic diversity of a particular phytopathogen can be used to develop sustainable management strategies such as resistance breeding and fungicide screening. In this study, D. eres was analyzed, as it had a relatively large number of isolates from which to obtain reasonable estimates of various intraspecific diversity indices. In this study, multi-locus sequences were used as the marker of choice. The use of sequence data as genetic markers facilitated the analysis of genetic variations among isolates within a population. We selected ITS, β-tubulin, HIS, EF-1α, and CAL gene regions, as they were extensively used in phylogenetic analysis of the genus Diaporthe. In addition, ACT and Apn2 genes were selected since those regions provide a large number of polymorphic sites for the Diaporthe eres species complex (Udayanga et al., 2014b). Genetic polymorphisms are required for both phylogenetic and population genetic studies (Xu, 2006). Using these gene regions, we calculated haplotype richness (hR), the total number of haplotypes, Watterson's theta (Θw), and pairwise nucleotide diversity (JI) for Diaporthe eres obtained from Chinese vineyards.

The combined effect of the mutation, recombination, marker ascertainment, and demography of a particular species can be revealed by analyzing and comparing gene genealogies and haplotype diversities within and between genes (Stumpf, 2004; Xu, 2006). The calculated haplotype diversities of Diaporthe eres were higher than 0.5 for Apn2, CAL, HIS, β-tubulin and the combined data, reflecting high genetic diversity. Tajima's D indicates how much population variation can be sustained over time (Tajima, 1989). In the present study, positive D values were observed for coding gene regions (Apn2, CAL, and HIS). This might be due to selective pressure causing a recent population contraction. The selection pressure could have come from the continuous application of fungicides, leading to the loss of certain genotypes. In contrast, Tajima's D for the combined sequences was negative (−0.20416), which indicates a possible recent population expansion of certain multi-locus genotypes (Tajima, 1989). In Hubei, several multi-locus genotypes were over-represented, consistent with this hypothesis.

The Hudson and Kaplan (1985) index for the recombination between Chinese and European isolates was calculated for this study. In our analysis, we calculated the number of recombination events in the history of a sample of sequences (R) and the number of recombination events that can be parsimoniously inferred from a sample of sequences (Rm) (Hudson, 1983; Kelly, 1997). When the rate of recombination equals zero, R gives zero (Hudson, 1983; Hudson and Kaplan, 1985). Since the R is given a value based on the history of the sample, Rm denotes the minimum number of recombination events implied by the data using the four-gamete test. A positive ZZ value, which reflects intragenic recombination, has played an important role in nucleotide variation and a high number of recombination events (Hudson, 1983). Therefore, we can conclude that recent recombination events might have occurred between the Chinese and European isolates. Haplotype networks provide a better understanding of the coexistence of ancestral and derived haplotypes by providing an account for recombination (Huson and Bryant, 2006). Therefore, haplotype networks are intensively used in intraspecific analyses. We used a median-joining network in which the number of mutations separate haplotypes (Castelloe and Templeton, 1994). In each network, the ancestral haplotype was predicted based on rooting probability (Posada and Crandall, 2001). The analyses suggested that the most recent ancestry of the Chinese haplotypes was shared with the Spanish and Hungarian haplotypes. In addition, haplotypes from the UK and Czech Republic shared ancestry with Chinese haplotypes. Overall, the Diaporthe population in China is genetically diverse and might have an admixture population. The current population is likely derived from a combination of endemic D. eres strains and introduced strains from other regions.

Conclusion

Present study provides an account of Diaporthe species associated with Chinese vineyards by their phylogenetic placements. Collectively, in the present study, 111 Diaporthe strains were isolated and characterized into eight species using both morphological and molecular phylogenetic approaches. To identify those taxa, four gene regions were examined. The combination of ITS, CAL, β-tubulin, and EF-1α genes gave the best species delimitation in the genus Diaporthe. The present study introduced three novel taxa and three host records of Diaporthe associated with Chinese grapevines. The most abundant Diaporthe species was D. eres, which was moderately aggressive. D. gulyae was the most aggressive among the eight species on detached green shoots. The Chinese D. eres population was high in nucleotide diversity and haplotype diversity. In haplotype network analysis, the Chinese population was dispersed in the network but showed a certain degree of clustering according to their geographical origins. This result suggests that there is likely geographic structuring of D. eres in China. However, more in-depth analysis is required using more isolates from different provinces. Haplotype networks including Chinese and European isolates suggest a close relationship between the two populations. This is confirmed by the recombination among isolates from these two regions. Our results suggest that the D. eres population in China might be a result of an admixture. The results presented here provide opportunities for several fields, including grapevine breeding for disease-resistant cultivars, screening for new fungicides, and developing appropriate quarantine and management strategies to prevent and control grapevine dieback diseases.

Data Availability

The sequence data generated in this study is deposited in NCBI GenBank (https://www.ncbi.nlm.nih.gov/genbank) and the respective accession numbers are given in Table 2. The Alignment generated in the present study available in TreeBASE (https://treebase.org/treebase-web/home.html) under the 24324.

Author Contributions

JY and XL conceived the research. JY, IM, AD, XL, and WZ planned the basic research. ML, YZ, and WSZ provided materials. IM and AD conducted the experiments and prepared manuscript. IM, AD, DW, and JX analyzed data. KH, SB, and JY revised the manuscript. All authors read and approved the final manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Milan Samarakoon for his guidance in developing phylogenetic trees. We would like to thank the students and non-academic staff of Beijing Key Laboratory of Environment Friendly Management on Fruit Diseases and Pests in North China, for their help with pathogenicity assays. DW would like to thank CAS President's International Fellowship Initiative (PIFI) for funding his postdoctoral research (No. 2019PC0008) as well as the National Science Foundation of China and the Chinese Academy of Sciences for his financial support under the following Grants: 41761144055, 41771063, and Y4ZK111B01.

Footnotes

Funding. This project was funded by Beijing Talent Programme for JY, CARS-29 and D171100001617002.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The sequence data generated in this study is deposited in NCBI GenBank (https://www.ncbi.nlm.nih.gov/genbank) and the respective accession numbers are given in Table 2. The Alignment generated in the present study available in TreeBASE (https://treebase.org/treebase-web/home.html) under the 24324.


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