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Comparative Genomics of Pathogens Causing Brown Spot Disease of Tobacco: Alternaria longipes and Alternaria alternata

  • Yujie Hou ,

    Contributed equally to this work with: Yujie Hou, Xiao Ma

    Affiliation Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China

  • Xiao Ma ,

    Contributed equally to this work with: Yujie Hou, Xiao Ma

    Affiliation Longrun Pu-erh Tea Academy, Yunnan Agricultural University, Kunming, Yunnan, China

  • Wenting Wan,

    Affiliation Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China

  • Ni Long,

    Affiliation Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China

  • Jing Zhang,

    Affiliation College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China

  • Yuntao Tan,

    Affiliation Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China

  • Shengchang Duan,

    Affiliation Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China

  • Yan Zeng , (YD); (YZ)

    Affiliation State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Science, Kunming, Yunnan, China

  • Yang Dong (YD); (YZ)

    Affiliations Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China, Biological Big Data College, Yunnan Agricultural University, Kunming, Yunnan, China

Comparative Genomics of Pathogens Causing Brown Spot Disease of Tobacco: Alternaria longipes and Alternaria alternata

  • Yujie Hou, 
  • Xiao Ma, 
  • Wenting Wan, 
  • Ni Long, 
  • Jing Zhang, 
  • Yuntao Tan, 
  • Shengchang Duan, 
  • Yan Zeng, 
  • Yang Dong


The genus Alternaria is a group of infectious/contagious pathogenic fungi that not only invade a wide range of crops but also induce severe allergic reactions in a part of the human population. In this study, two strains Alternaria longipes cx1 and Alternaria alternata cx2 were isolated from different brown spot lesions on infected tobacco leaves. Their complete genomes were sequenced, de novo assembled, and comparatively analyzed. Phylogenetic analysis revealed that A. longipes cx1 and A. alternata cx2 diverged 3.3 million years ago, indicating a recent event of speciation. Seventeen non-ribosomal peptide synthetase (NRPS) genes and 13 polyketide synthase (PKS) genes in A. longipes cx1 and 13 NRPS genes and 12 PKS genes in A. alternata cx2 were identified in these two strains. Some of these genes were predicted to participate in the synthesis of non-host specific toxins (non-HSTs), such as tenuazonic acid (TeA), alternariol (AOH) and alternariol monomethyl ether (AME). By comparative genome analysis, we uncovered that A. longipes cx1 had more genes putatively involved in pathogen-plant interaction, more carbohydrate-degrading enzymes and more secreted proteins than A. alternata cx2. In summary, our results demonstrate the genomic distinction between A. longipes cx1 and A. altenata cx2. They will not only improve the understanding of the phylogenetic relationship among genus Alternaria, but more importantly provide valuable genomic resources for the investigation of plant-pathogen interaction.


Alternaria is a genus of ubiquitous fungi that includes saprobic, endophytic and pathogenic species associated with a wide variety of hosts [1]. The members of Alternaria infect a remarkable range of plants, including citrus, pistachio, apple, pear, tobacco, tomato, and beans, causing devastating plant diseases and resulting in considerable loss of agricultural yield.

Brown spot disease is one of the most destructive leaf spot diseases caused by Alternaria on various crops. It has been reported that the members of the genus Alternaria are major fungal pathogens that infect tobacco leaves, and give rise to the formation of brown spot [2]. After the plant enters the growing stage and the climate becomes suitable, the conidia of Alternaria will spread very rapidly in the field (Fig 1). They germinate and infect crop leaves or fruits, which not only causes great loss of agricultural production, but the produced mycotoxins present in agricultural products also threatens the health of humans and animals.

However, there are always confusions about species identification in the genus Alternaria. Some studies suggested that some host-specific toxins (HSTs) producing pathogens in Alternaria (A. mali, A. citri, A. kikuchiana, A. longipes and A. alternata f. sp. lycopersici) look similar in conidial morphology and should be interpreted as intraspecific variability of A. alternata [35]. However, other researchers argued that A. longipes and A. alternata are different species that can be distinguished by morphological species concepts [6], molecular [7] and chemical methods [8]. They argued that the continuing use of the name A. alternata for A. longipes is unwarranted and that pathotypes should not be used [8].

Recent studies have suggested that Alternaria spp. produce non-host specific toxins (non-HSTs) (e.g., tenuazonic acid (TeA), alternariol (AOH), alternariol monomethyl ether (AME), brefeldin A, tentoxin, zinniol) [9] and host-specific toxins that produced by a gene cluster usually residing on one or several conditionally dispensable chromosomes (CDCs) [1, 10]. Two major toxins, AT-toxin and TeA, are involved in the onset of tobacco brown spot disease [11]. TeA is a nonspecific toxin, whereas AT-toxin is considered as a HST to Nicotiana tabacum. In contrast to what is known about the chemical structures and properties of other Alternaria HSTs [12], such as AK-toxin [13], ACT-toxin [14] and AM-toxin [15], no detailed information is available for AT toxin, while researchers proposed that they induced programmed cell death in tobacco [16]. Some reports also found that TeA and other low molecular compounds could cause a faded green halo around the invasion site, and finally gave rise to the brown spot.

Although the symptoms of brown spot are usually associated with the action of A. alternata or A. longipes, their pathogenicity mechanisms including toxin biosynthesis pathways, secondary metabolism and secretomes are still unclear and need further investigation. In addition, most research on Alternaria would greatly benefit from the information of a reference genome.

Large-scale genome sequencing and comparative genome analysis can help to identify shared and unique pathogenicity genes in closely-related fungal species. In this study, two isolates named CX1 and CX2 were isolated from different infected tobacco cultures by separation of single fungal spores. CX1 and CX2 were separated from typical brown spot lesions on tobacco leaves and brown spots lesions on sunburned tobacco leaves, respectively. Through the whole genome sequencing and phylogenetic relationship analysis based on co-linear sequences, CX1 and CX2 were identified as A. longipes and A. alternata, respectively. Accordingly, we renamed CX1 to A. longipes cx1 and CX2 to A. alternata cx2. Moreover, a variety of comparative genomic analyses revealed differences between the A. longipes cx1 and A. alternata cx2 genomes including genes putatively involved in non-HSTs biosynthesis, pathogen-plant interaction, cell wall integrity and secreted proteins.

Results and Discussion

Strain identification based on ITS

Two strains named CX1 and CX2 were isolated from typical brown spots lesions on tobacco leaves and sunburned tobacco leaves (Fig 2) by separating single fungal spores, respectively. A phylogenetic tree based on ITS sequences was built among CX1, CX2, A. longipes EGS30-033 (accession: AY751457.1), A. alternata SDHeze-9 (accession: KT238888.1), Alternaria tenuissima CSPF5 (accession: KU508797.1) and Alternaria brassicicola Ab4UP (accession: KF542552.1) from NCBI (Fig 3A), showing that CX1, A.longipes EGS30-033, CX2, A. alternata SDHeze-9 and A. tenuissima CSPF5 are clustered in the same clade.

Fig 2. Tobacco leaves showing different brown spot symptoms.

(A) Typical brown spot lesions on tobacco leaves, from which CX1 was isolated. (B) Brown spots lesions on sunburned tobacco leaves, which served to isolate CX2.

Fig 3. Phylogenetic relationship between CX1 and CX2.

(A) Phylogenetic relationship constructed by MEGA5 based on ITS sequences of CX1, CX2, A. longipes EGS30-033, A. alternata SDHeze-9, A. tenuissima CSPF5 and A. brassicicola Ab4UP. (B) Phylogenetic relationship constructed by MEGA5 based on large co-linear sequence among CX1, CX2, A. alternata atcc11680, A. longipes bmp0313 and A. tenuissima bmp0304.

Previous researchers demonstrated that the ITS variability within the genus is relatively limited. A number of taxa inhabiting particular plant species, such as A. longipes, A. mali and A. tenuissima cannot reliably be distinguished from A. alternata using this method [17]. Elisabeth [18] argued that isolates of the A. alternata, A. tenuissima, and Alternaria arborescens species-groups could not be further resolved by ITS. In this study, the ITS sequences in CX1 and CX2, differed by only two bases (S1 Text), confirming that species separation between CX1 and CX2 cannot be done by comparison of ITS sequences.

Therefore, a phylogenetic tree based on large co-linear sequences (refer to methods and S2 Text) was constructed by MEGA5 among CX1, CX2, A. alternata atcc11680, A. alternata atcc66891, A. longipes bmp0313 and A. tenuissima bmp0304 from Alternaria Genomes Database [19] (Fig 3B). This analysis demonstrated that CX1 is more closely related to A. longipes while CX2 and A. alternata have a closer genetic relationship. Based on our result, CX1 and CX2 were determined as A. longipes and A. alternata, respectively, and renamed to A. longipes cx1 and A. alternata cx2.

General features of the A. longipes cx1 and A. alternata cx2 genomes

The genomes of A. longipes cx1 and A. alternata cx2 were sequenced on the Illumina HiSeq 2500 platform using a whole genome shotgun approach. This generated a total of 27.75 Gb raw sequences for A. longipes cx1, and 17.99 Gb raw sequences for A. alternata cx2 as 100 bp paired-end short reads. Quality-control filters removed adapter sequences, regions of low base-call quality, and regions of low sequence complexity. All 17-mer sequences were then extracted from each library. The 17-mer analysis showed that both genomes of A. longipes cx1 and A. alternata cx2 had low heterozygosity (S1 Fig). The genome sizes of A. longipes cx1 and A. alternata cx2 were estimated to be 39.99 Mb and 37.40 Mb, respectively. The sequencing depth was calculated to be about 694 × and 481 × for A. longipes cx1 and A. alternata cx2, respectively.

The total assembly sizes of A. longipes cx1 and A. alternata cx2 are 35.7 Mb and 33.5 Mb, covering 89.5% and 89.6% of the predicted genome sizes, respectively (Table 1). These numbers are similar to the published genome sizes of A. alternata SRC1lrK1f (32.99 Mb) and A. brassicicola (29.54 Mb). The A. longipes cx1 genome assembly consists of 2,836 contigs with a N50 of 32.5 kb. The A. alternata cx2 genome assembly resulted in 1,406 contigs with a N50 of 47.4 kb. The N50 scaffold sizes of A. longipes cx1 and A. alternata cx2 were 208.2 kb and 1,889.4 kb, respectively. The GC content is 51.03% and 50.98% for the genome of A. longipes cx1 and A. alternata cx2, respectively.

Table 1. Statistics for the assembled genome sequences of A. longipes cx1 and A. alternata cx2.

Evaluation of assembled genomes using Reaper [20] showed that 93.55% bases in the A. longipes cx1 assembled genome, and 94.49% in the A. alternata cx2 genome were error free bases. The CEGMA mapping protocol [21] showed that the genome assemblies of A. longipes cx1 and A. alternata cx2 captured 99.19% (246 of 248) and 98.39% (244 of 248) complete ultra-conserved core proteins, respectively (S1 Table). These results demonstrate the high quality of both two genome assemblies in this study. Additionally, scaffold alignment using NUCmer in MUMmer3.23 showed that A. longipes cx1 and A. alternata cx2 are highly syntenic [22] (Fig 4).

Fig 4. Synteny dotplot of A. longipes cx1 (y-axis) and A. alternata cx2 (x-axis).

Regions of homology are plotted as diagonal lines.

Genome annotation

Using MAKER2 [23], a total of 12,690 protein-coding genes were predicted in the genome of A. longipes cx1, and a total of 12,041 in the genome of A. alternata cx2. These predicted genes accounted for 63.45% and 66.69% of the assembled A. longipes cx1 and A. alternata cx2 genomes, with an average gene length of 1,784.89 bp and 1,855.42 bp, respectively (Table 2). The result shows that A. longipes cx1 has a larger genome and more protein-coding genes than A. alternata cx2.

With functional annotation, about 5,938 (46.79%), 6,133 (48.33%), 6,986 (55.05%) and 10,895 (85.86%) of the predicted genes in A. longipes cx1, and about 5,825(48.38%), 5,884 (48.87%), 6,724 (55.84%) and 10,311(85.63%) genes in A. alternata cx2 had homologies with known functions in the following four databases, respectively: the Gene ontology (GO) [24], Kyoto Encyclopaedia of Genes and Genomes (KEGG) [25], SwissProt and TrEMBL databases [26]. In total, there were 10,921 genes in A. longipes cx1 and 10,336 genes in A. alternata cx2 identified as common to all four protein databases (S2 Table).

The content of transposable elements (TE) may have profound impacts on the genome rearrangement and synteny loss in fungi [27]. The repeat sequences accounted for 3.07% of the A. longipes cx1 genome, and 1.73% of the A. alternata cx2 genome. Among all repeat sequences, TEs made up 2.76% of the A.longipes cx1 genome, which was almost twice that of the A. alternata cx2 genome (1.48%) (S3 Table). Because high TE content is a hallmark of CDCs [28], this result implies that the A. longipes cx1 genome might contain CDCs. Meanwhile, the TE content has a positive correlation with genome rearrangement, suggesting that A. longipes has a more flexible genome.

For annotation of non-coding genes, we identified 99 tRNAs for A. longipes cx1, and 98 tRNAs in A. alternata cx2. In addition, 26 snRNAs, 3 sRNAs and 132 rRNAs were annotated in A. longipes cx1, and 32 snRNAs, 3 sRNAs and 106 rRNAs were annotated in A. alternata cx2.

Phylogenetic analysis

Single copy orthologous genes defined by OrthoMCL [29] were chosen to carry out phylogenetic analysis. Phylogenetic relationship based on 2,702 single copy orthologous genes among A. longipes, A. alternata, Fusarium oxysporum, Magnaporthe oryzae, Aspergillus nidulans, Leptosphaeria maculans, Pyrenophora teres, Phaeosphaeria nodorum, A. abrassicicola and A. alternata SRC1lrK1f were constructed using MrBayes [30]. The estimated divergence time of 3.3 (2.4–5.1) million years ago (MYA) between A. longipes cx1 and A. alternata cx2 (Fig 5) is consistent with the divergence time between species in closely related genera (i.e., 4.1 MYA between Cochliobolus sativus and C. heterostrophus; 7.1 MYA between P. teres and P. tritici-repentis) [31], indicating a recent event of speciation. The estimated divergence time between A. alternata SRC1lrK1f and A. alternata cx2 is 2.1 (1.5–3.3) MYA, which further suggests that A. alternata cx2 belongs to the species A. alternata. Phylogenetic analysis based on single copy orthologous genes further confirmed that A. longipes cx1 and A. alternata cx2 belong to two different species.

Fig 5. Phylogenetic relationship among A. longipes cx1, A. alternata cx2, F. oxysporum, M. oryzae, A. nidulans, L. maculans, P. teres, P. nodorum, A. abrassicicola and A. alternata SRC1lrK1f.

The estimates of divergence time and its interval based on sequence identity are indicated at each node. The red dot on branches means divergence time has been adjusted by fossil evidence.

Based on pair-wise protein sequence similarity, we carried out gene family clustering analysis on all A. longipes cx1, A. alternata cx2, A. abrassicicola and A. alternata SRC1lrK1f genes using OrthoMCL [29] (Fig 6). 12,690 genes in A. longipes cx1 and 12,041 genes in A. alternata cx2 were clustered into 11,088 and 11,016 gene families, respectively. Fifty-eight A. longipes cx1 specific gene families contained 154 genes, whereas A. alternata cx2 had 2 specific gene families with 4 genes (S4 Table). Interestingly, A. alternata cx2 shared more gene families with A. longipes cx1 (10,983) than with A. alternata SRC1lrK1f (10,802).

Fig 6. Venn diagram showing the number of unique and shared gene families among A. longipes cx1, A. alternata cx2, A. brassicicola and A. alternata SRC1lrK1f.

We investigated gene families only shared by A. longipes cx1 and A. alternata cx2 and absent in A. brassicicola and A. alternata SRC1lrK1f (S5 Table). They were annotated by KEGG database. For example, six genes in the gene family No. 668 in A. longipes cx1 and A. alternata cx2 were annotated as hypothetical glycogen debranching enzymes (Table 3). These enzymes facilitate the breakdown of glycogen, which might help the fungal pathogens catabolize and utilize nutrients in tobacco leaves. The gene family No. 1123 was identified as pentosyltransferases (Pfs), NACHT and WD domain proteins. They might be closely related to carbohydrate metabolism in tobacco. Genes in the gene family No. 8849 were defined as WSC domain protein-coding genes. Previous studies have elucidated that WSC1, WSC2 and WSC3 genes encode putative receptors that maintain cell wall integrity under heat stress [32]. Moreover, the functional characteristics and cellular localization of WSC suggest that they may mediate intracellular responses to environmental stress in yeast [33].

Table 3. Three gene families specific to A. longipes cx1 and A. alternata cx2 have different gene copies between these two strains.

Furthermore, A. longipes cx1 had many unique gene families (S6 Table). Based on the functional annotation, we found that these gene families covered extensive parts of biological processes, including genes in the secondary metabolic pathways (gene family No. 11699) and pathogen-plant interaction (gene family No. 11728 and No. 11792), which proposed that these families may be involved in pathogen-plant interaction during the infection.

Secondary metabolic pathways (NRPS and PKS)

Alternaria spp. produce more than 60 secondary metabolites [34], including important HSTs and non-HSTs that ultimately cause plant cell death. Most of them are versatile compounds of polyketides and non-ribosomal peptides, which are usually generated by non-ribosomal peptide synthase (NRPS) and polyketide synthase (PKS), respectively. More importantly, these genes are probably also involved in the synthesis of siderophores, which assists many pathogens to acquire iron from the host during infection. Therefore, they are good candidates for the investigation of virulence factor and toxin synthesis.

Typically, NRPSs mainly consist of adenylation (A), thiolation (T, also known as PCP for peptidyl carrier protein), and condensation (C) domains [35]. Type I fungal PKSs contain ketosynthase (KS), acyltransferase (AT), and acyl carrier protein (ACP) main domains, along with several optional domains, such as b-ketoacyl reductase (KR), dehydratase (DH) and trans-acting enoyl reductase (ER) domains [36]. To detect secondary metabolite biosynthetic genes and pathways, we employed Secondary Metabolite Unique Regions Finder (SMURF) [37] based on PFAM and TIGRFAM domain content to find the PKS and NRPS genes. Considering the architectures of fungal PKSs are very similar to each other, MUSCLE and FastTree [38] were used to find gene clusters of NRPS and PKS genes, respectively. BlastP [39] were used to search specific genes in these two genomes.

We identified 17 NRPS genes and 13 PKS genes in A. longipes cx1, and 13 NRPS genes and 12 PKS genes in A. alternata cx2, respectively (S7 Table). Further study was conducted by using antiSMASH [40] online to explore the structural domains of the candidate genes, and unravel their specific roles in the syntheses of secondary metabolites and toxins.

TeA is a well-known mycotoxin produced by various plant pathogenic fungi, including Alternaria spec., M. oryzae and Phoma sorghina [34]. TeA is one of the most toxic Alternaria toxins. A recent report revealed that TAS1 in M. oryzae, a NRPS-PKS hybrid enzyme of 1,602 amino acids, was responsible for TeA synthesis from isoleucine and acetoacetyl-coenzyme A [41]. TAS1 consists of C, A and PCP domains in the NRPS portion, and a KS domain in the PKS portion. This study also verified that the KS domain is responsible for the final cyclization step and the C domain is responsible for the condensation reaction in TeA production by ultra performance liquid chromatography (UPLC) analysis of metabolites. As Fig 7A illustrates, gene AL_scaffold88_6305 and gene AA_scaffold3_8872 were considered as TAS1 homologs, suggesting a potential role in the production of TeA. Gene AL_scaffold88_6305 in A. longipes cx1 has the same domains with TAS1 gene, while gene AA_scaffold3_8872 in A. alternata cx2 lacks of a C domain at the amino terminus, suggesting that it might have a defect in TeA production. Their protein sequences were provided in S3 Text. Interestingly, this is in accordance with previous reports that some isolates of A. alternata might not produce TeA [8].

Fig 7. NRPS-PKS homologs in A. longipes cx1 and A. alternata cx2.

(A) TAS1 homologous gene in A. longipes cx1 (AL_scaffold88_6305) and A. alternata cx2 (AA_scaffold3_8872) might be required for TeA synthesis. (B) PKSH homologous gene in A. longipes cx1 (AL_scaffold86_4815) and A. alternata cx2 (AA_scaffold4_10387, AA_scaffold12_4792). (C) PKSJ homologous gene in A. longipes cx1 (AL_scaffold19_7914) and A. alternata cx2 (AA_scaffold4_10765, AA_scaffold21_8045). The direction of arrow indicates N-terminal.

Using the same method, we also found genes required for AOH and AWE syntheses. It is well known that one of the postulated core enzymes in the biosynthesis of AOH and AME is PKS. Debjani et al. found that the timing of the expression of two PKS genes, pksJ (JX103645) and pksH (JX103643) are correlated with the production of AOH and AME [9]. AL_scaffold86_4815 and AA_scaffold4_10387 shared high homology with pksH, and AL_scaffold19_7914 and AA_scaffold4_10765 shared high homology with pksJ (Fig 7B and 7C). Combined with gene cluster results, we found an additional copy of pksH homolog (AA_scaffold12_4792), and an additional copy of pksJ homolog (AA_scaffold21_8045) in A. alternata cx2. AA_scaffold12_4792 protein only lacks a DH domain. AA_scaffold21_8045 protein is almost the same as pksJ with an additional cMT domain. These data imply gene duplications in A. alternata cx2 during the evolution process.

NRPS or PKS genes responsible for synthesis of HSTs generally reside on CDCs. However, it is a big challenge for us to find genes responsible for AT-toxin synthesis because of the insufficient research up to now. To figure out CDCs in A. longipes cx1 and A. alternata cx2, two CDC marker gene on A. arborescens (tomato pathotype), ALT1, a PKS gene involved in AAL toxin biosynthesis, and AaMSAS gene, a putative 6-MSA-type PKS gene [28, 42] were used as query to BLAST in A. longipes cx1 and A. alternata cx2 genome. However, there is no gene homologous to ALT1 in both genomes. What’s interesting is that two genes, AL_scaffold266_5850 and AL_scaffold337_4970, identical to AaMSAS were found in A. longipes cx1, while none was found in A. alternata cx2 (S2 Fig). The results imply that scaffold226 (18 Kb) and scaffold 337 (11 Kb) in A. longipes cx1 on which AaMSAS homologous gene reside might be fragments of CDCs.

Plant pathogen interaction

Searching against pathogen host interaction database (PHI-base) [43] identified 2,180 (17.18%) genes in A. longipes cx1 and 2,063 (17.13%) genes in A. alternata cx2 that might be involved in pathogenicity and virulence pathways. Among the proteins that showed over 70% identity with proteins in the PHI-base, 50 of 122 matches in A. longipes cx1 and 52 of 116 matches in A. alternata cx2 were labeled “loss of pathogenicity or reduced virulence” as the phenotype characteristic in mutant strains (S8 Table).

To study genes in the plant-pathogen interaction, we searched each genome using the KEGG Orthology (KO) number in the KEGG plant-pathogen interaction pathway (ko04626). As the result showed, A. longipes cx1 has more genes involved in this pathway (Table 4). For the calmodulin gene (K02183) family, there are 8 genes in A. longipes cx1, and 5 genes in A. alternata cx2. These genes potentially regulate the biological activities of many cellular proteins and transmembrane ion transporters mainly in a Ca2+-dependent manner in fungi. The increase of cytosolic Ca2+ concentration in plants is a regulator for the production of reactive oxygen species and the localized programmed cell death/hypersensitive response [44]. The higher number of calmodulin genes existed in A. longipes cx1 than A. alternata cx2 may imply stronger Ca2+ storage and release capacity.

Carbohydrate degrading enzymes

Carbohydrate-active enzymes (CAZymes) are responsible for the breakdown, biosynthesis or modification of glycoconjugates, oligo- and polysaccharides. Besides making energy harvest from the plant tissues possible, pathogen CAZymes play a central role in the degradation of plant cell wall, the penetration into the host tissue, and the host-pathogen interactions [45]. CAZymes are grouped into four functional classes based on their catalytic modules or functional domains: glycoside hydrolases (GHs), glycosyltransferases (GTs), polysaccharide lyases (PLs), and carbohydrate esterases (CEs) [45]. To investigate CAZymes composition in both A. longipes cx1 and A. alternata cx2 genomes, HMMScan was used to search each predicted fungal proteomes against dbCAN (release 3.0) CAZymes database [46]. As shown in Fig 8, A. longipes cx1 genome encoded 554 putative CAZymes, including 277 GH, 105 GT, 145 CE, and 27 PL. A. alternata cx2 contained 546 putative CAZymes, including 272 GH, 102 GT, 147 CE, and 25 PL. Among these four classes, CE, GH, and PL classes are considered as cell wall degrading enzymes (CWDE) due to their roles in the disintegration of the plant cell wall by bacterial and fungal pathogens [47, 48]. However, the numbers of genes in CE, GH, and PL classes did not differ between A. longipes cx1 and A. alternata cx2 (S9 Table).

Fig 8. Distribution of carbohydrate-active enzymes gene families in A. longipes cx1, A. alternata cx2, A. abrassicicola and A. alternata SRC1lrK1f.

Secretome prediction

The secretome is defined as the global set of proteins produced by a cell and exported to the extracellular space in a determined time and condition [49]. The secretome plays an important role in the interactions with the environment, degradation of complex organic compounds, and in modulating directly or indirectly pathogen-host interactions. To compare the difference between A. longipes cx1 and A. alternata cx2, SignalP [50] and TargetP [51] were used to detect protein sequences with signal peptides, and TMHMM [52] was used to detect transmembrane helixes. As a result, 899 secreted proteins in A. longipes cx1 and 865 secreted proteins in A. alternata cx2 were predicted. Among all secreted protein encoding genes in A. longipes cx1, 212 genes were identified as cell wall degrading enzymes. In comparison, 206 genes in secreted protein encoding genes of A. alternata cx2 belonged to cell wall degrading enzymes. In addition, 8 genes in A. longipes cx1 and 8 genes in A. alternata cx2 were annotated as “effector” by BLASTN with PHI-base (S10 Table), and the “effector” were reported to be required for the direct or indirect recognition of a pathogen only in resistant host genotype [43, 53].


In this study, we reported two high quality genomes of Alternaria pathogens. Through the large-scale genomic analysis, we found NRPS and PKS genes in both genomes that likely participate in TeA, AOH and AME synthesis. It is interesting that A. longipes cx1 possessed more NRPS and PKS genes in total, while A. alternata cx2 gained another copy of PKS genes responsible for AOH and AME synthesis. By comparative genomic analysis, we found more genes with a putative function in pathogen-plant interaction, more carbohydrate degrading enzymes and more secreted proteins in A. longipes cx1 than in A. alternata cx2.

In summary, our results provide a novel perspective for studying the synthesis of various toxins and complex interactions with the hosts. It establishes a powerful basis for further identification of genes involved in AT-toxin synthesis. Conceivably, these resources will improve the understanding of important pathogens of the genus Alternaria, increase the genome information for pathogenic fungi, and facilitate the study of pathogenicity mechanisms of HSTs and various mycotoxins.

Materials and Methods

Strain acquiring and identification

Two different isolates were isolated from different infected tobacco cultures using single fungal spore separating method. First, the spores were scraped carefully from the brown spots lesions on tobacco leaves by a blade. CX1 was separated from typical brown spot lesions on tobacco leaves, while CX2 was isolated from brown spot lesions on sunburned tobacco leaves that are larger than typical brown spot lesions. Spores were diluted in sterile water to a density of about 300 spores/ml. The spore suspension was subsequently spread uniformly on a PDA plate containing ampicillin (950 μg/ml), rifampicin (100 μg/ml) and quintozene (50 μg/ml) to ensure that single spores grew isolated. Germinated spores were excised from the PDA plate and transferred to a fresh plate.

For strain identification, ITS sequences were obtained by PCR using primer pairs (ITS5 and ITS4, ITS1 and ITS4, ITS3 and ITS4, and ITS1and ITS2) (S11 Table). Phylogenetic relationship according to ITS was analyzed by using MEGA5 among CX1, CX2, A. longipes EGS30-033 (accession: AY751457.1), A. alternata SDHeze-9 (accession: KT238888.1), A. tenuissima CSPF5 (accession: KU508797.1) and A. brassicicola Ab4UP (accession: KF542552.1) from NCBI.

To confirm the strain identification, phylogenetic analysis based on large co-linear sequence was implemented. Scaffolds about 200 kb in length in CX1 were selected and used as query to search the matching sequence of other fungi in Alternaria Genomes Database by BLASTN on their website. Finally, six scaffolds of about 195 kb from CX1 (scaffold45), CX2 (part of scaffold9), A. longipes bmp0313 (part of contig ALGCTG00140), A. alternata atcc11680 (part of contig ATNCTG00647), A. alternata atcc66891 (part of contig AATCTG00103) and A. tenuissima bmp0304 (part of contig AT2CTG00134) were chosen to construct phylogenetic tree using MEGA5.


Genomic DNA was extracted from fresh fungal hyphae by cetyltrimethyl ammonium bromide (CTAB) method [54]. In brief, fungal hyphae were ground in liquid nitrogen, and CTAB buffer was added to breakdown the cell wall. Mixture of phenol, chloroform and isoamyl alcohol was used to extract DNA and isopropyl alcohol was used to precipitate DNA. The DNA sediment was then washed with 75% ethanol and dissolved in sterile water.

To build small insert libraries, 2 μg of DNA were sheared to fragments of 300–1100 bp, end-repaired, A-tailed and ligated to Illumina paired-end adapters (Illumina). The ligated fragments were size selected at 427, 603 and 1042 bp for A. longipes cx1 and 430, 680 and 820 bp for A. alternata cx2 on agarose gel and amplified by PCR to yield the corresponding short insert libraries. All these DNA libraries were sequenced on the Illumina HiSeq 2500 platform. In total, we generated 277.4 M of usable sequence for A. longipes cx1 and 180.0 M for A. alternata cx2, respectively.

Genome assembly

First, a stringent filter and correction processing was carried out. All reads were removed with duplications and adapters and subsequently preprocessed by filtering out reads with more than 30 low-quality bases or more than 5% unknown bases. The sequence errors were corrected based on K-mer frequency information using a script named Corrector_HA (versoin 2.01) made by the Beijing Genomics Institute (BGI). For both A. longipes cx1 and A. alternata cx2 genome assemblies, we chose K = 17 bp, and corrected sequencing errors for the 17-mers with a frequency lower than 3.

We used 17-mer analysis to evaluate the genome size and heterozygosity. All 17-mer sequences were extracted from paired-end reads from short insert size libraries (< 1 kb) after filter and correction, and the frequency of each 17-mer was calculated and plotted. The genome size G = K_num/Peak_depth, where the K_num is the total number of 17-mer, and Peak_depth is the expected value of 17-mer depth.

We assembled the short reads using JR-Assembler [55]–an extension-based de novo assembler. It runs in five steps: raw read processing, seed selection, seed extension, repeat detection, and contig merging by SSAKE based Scaffolding of Pre-Assembled Contigs after Extension (SSPACE) [56]. We chose the same optimized parameters (minOverlap 30, maxOverlap 40, Assembly Read Length 87) for both genome assemblies.

To confirm the genome assembly, Reaper was performed to evaluate the assembled genome quality with default parameters, which is a tool that precisely identifies errors in genome assemblies [20]. Meanwhile, software CEGMA [21] with default setting was also used to estimate the sequence completeness of the assembly.

The assembled scaffolds of these two genomes were aligned using NUCmer in MUMmer3.23 with the minimum length of a cluster of matches set by 100 (c = 100) [22]. The assembled genome with longer scaffolds (A. alternata cx2) was used as the reference, while the genome of A. longipes cx1 was used as the query. After merging adjacent alignments with gaps less than 300 bp, alignments shorter than 10 kb were discarded. Subsequently, all alignments were output in the reference’s order and a dot-plot SVG graph was generated by a perl script.

Repeat annotation

For the identification of known TEs in the genome assembly, we employed RepeatMasker (version 3.3.0) [57] against the Repbase 16.0 [58] TE library, and then executed RepeatProteinMask in RepeatMasker package to identify TEs by aligning the genome sequence to a self-taken curated TE protein database. We also constructed a de novo repeat library using Piler, RepeatScount [59] and LTR_FINDER [60], followed by filtering sequences less than 100 bp. The generated results were consensus sequences and classification information for each repeat family. Then we used RepeatMasker again on the library built in the above steps. For tandem repeat prediction, we used RepeatMasker with the “-noint” option, including simple repeat, satellites, and low complexity repeats. TRF [61] were also used to predict tandem repeats, with parameters set to “Match = 2, Mismatch = 7, Delta = 7, PM = 80, PI = 10, Minscore = 50, and MaxPeriod = 12”.

Protein-coding gene prediction

To predict protein-coding genes, we employed the MAKER pipeline [23] in default parameters. MAKER2 executes ab inito prediction using the programs SNAP, Augustus, and GeneMark-ES, and evidence-based annotation using EST and protein homology as references. Proteins from L. maculans, P. nodorum, P. teres, Pyrenophora triticirepentis, A. brassicicola and transcripts of the published genome of A. alternata SRC1lrK1f were used as references in the homology-based annotation.

Functional gene annotation

To assign preliminary GO terms to the protein-coding genes, InterProScan (version 5) [62] was used to screen predicted proteins against publicly available databases including Pfam, PRINTS, PROSITE, ProDom, PANTHER and SingnalP. The KEGG Orthology database, Uniprot/SwissProt and UniProt/TrEMBL database were searched for homology-based function assignments by blastall (e-value ≤ 1e-5). Potential pathogenicity factors were identified through scanning protein-coding genes in the PHI-base using an e-value of 1e-5 and ≥ 50% coverage as criteria.

Non-coding RNA annotation

Genes encoding tRNAs were identified using tRNAscan-SE with appropriate default parameters. The rRNA fragments were identified by aligning the rRNA template sequences from the yeast genome using BlastN at an e-value of 1e-5. Other ncRNAs, including miRNA, sRNA and snRNA, were identified using INFERNAL-1.1 [63] software by searching against the Rfam database with appropriate parameters (—rfam,—cut_ga,—nohmmonly).

Gene family cluster identification

The OrthoMCL (orthomclSoftware-v2.0.9) [29] was used to define a gene family as a group of orthologs or in-paralogs. For genes with alternative spliced variants, the longest transcript was used to represent the gene. To identify gene family clusters in these species, all-versus-all protein searches were performed using BLASTP with an e-value of 1e-5. The homologous segment pairs were processed using the OrthoMCL with an e-value cutoff of 1e-5, and MCL (mcl-14-137) was used to define final orthologs and paralogs with an inflation value of 1.5.

Phylogenetic analysis

Single copy gene family genes (i.e., one copy in all species) were used to construct a phylogenetic tree of the F. oxysporum, M. oryzae, A. nidulans, L. maculans, P. teres, P. nodorum, A. abrassicicola and A. alternata SRC1lrK1f. Multiple sequence alignments were performed using MUSCLE (muscle-3.8.31) [64]. Four-fold degenerate sites were extracted from each gene and concatenated into a supergene for each species. At last, MrBayes software (, version 3.1.2) [30] was used to reconstruct the evolutionary relationships between species.

Divergence time estimation

We performed divergence time estimation with r8s, which estimates absolute rates ("r8s") of molecular evolution and divergence times on a phylogenetic tree, and then used the MCMCTREE program [65], implemented in the PAML package to estimate divergence times. Calibration time for the common ancestor from the TimeTree database ( was used to calibrate the divergence time estimation.

Secretome prediction

TargetP [51] was used to identify signal peptides and predict the subcellular location of proteins. Then SignalP [50] was used to predict the presence and location of signal peptide cleavage sites. These proteins were subsequently scanned for the presence of transmembrane helixes using the hidden Markov model topology predictor TMHMM [52]. Proteins with signal peptide and lacking transmembrane domains were deemed secreted proteins. The proteins with a length of less than 200 amino acids or with a cysteine content of less than 1.5% were removed and the candidate effectors were obtained.

Supporting Information

S1 Fig. 17-mer frequency distribution of sequencing reads.

(A) One sequencing library with insert size of 916 bp of A. longipes cx1. (B) One sequencing library with insert size of 694 bp of A. alternata cx2.


S2 Fig. Two scaffolds seem like CDCs in A. longipes cx1.


S1 Table. Statistics of the completeness of assembled A. longipes cx1 and A. alternata cx2 genome based on 248 CEGs.

(A) CEGMA report of A. longipes cx1. (B) CEGMA report of A. alternata cx2.


S2 Table. Number of genes in A. longipes cx1 and A. alternata cx2 with homologs or functional classification in different databases.


S3 Table. Statistics of repeat sequences and transposable elements of A. longipes cx1 and A. alternata cx2 genomes.


S4 Table. Summary of gene family clustering.


S5 Table. Gene families only shared by A. longipes cx1 and A. alternata cx2.


S6 Table. Unique gene families in A. longipes cx1.


S7 Table. List of NRPS and PKS genes in A. longipes cx1 and A. alternata cx2.


S8 Table. Genes affect the outcome of pathogen-host interaction.

(A) Genes in A. longipes cx1. (B) Genes in A. alternata cx2.


S9 Table. Statistics of CAZyme genes grouped in CE, GH, and PL classes.


S10 Table. Genes annotated as "effector" by PHI-base.


S11 Table. Primer pairs used for amplify ITS sequences by PCR.


S1 Text. ITS qequence of A. longipes cx1 and A. alternata cx2.


S2 Text. Six large co-linear sequences about 195 kb in length among CX1, CX2, A. longipes bmp0313, A. alternata atcc11680, A. alternata atcc66891 and A. tenuissima bmp0304.


S3 Text. Protein sequences of NRPS-PKS homologs in A. longipes cx1 and A. alternata cx2.



We thank Dr. Wei Chen and Dr. Feng Wang for reviewing this article.

Author Contributions

Conceived and designed the experiments: YD YZ XM YJH. Performed the experiments: WTW. Analyzed the data: YJH YZ NL JZ YTT SCD. Wrote the paper: YJH.


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