Literature DB >> 25917918

RNA-seq-Based Gene Annotation and Comparative Genomics of Four Fungal Grass Pathogens in the Genus Zymoseptoria Identify Novel Orphan Genes and Species-Specific Invasions of Transposable Elements.

Jonathan Grandaubert1, Amitava Bhattacharyya1, Eva H Stukenbrock2.   

Abstract

The fungal pathogen Zymoseptoria tritici (synonym Mycosphaerella graminicola) is a prominent pathogen of wheat. The reference genome of the isolate IPO323 is one of the best-assembled eukaryotic genomes and encodes more than 10,000 predicted genes. However, a large proportion of the previously annotated gene models are incomplete, with either no start or no stop codons. The availability of RNA-seq data allows better predictions of gene structure. We here used two different RNA-seq datasets, de novo transcriptome assemblies, homology-based comparisons, and trained ab initio gene callers to generate a new gene annotation of Z. tritici IPO323. The annotation pipeline was also applied to re-sequenced genomes of three closely related species of Z. tritici: Z. pseudotritici, Z. ardabiliae, and Z. brevis. Comparative analyses of the predicted gene models using the four Zymoseptoria species revealed sets of species-specific orphan genes enriched with putative pathogenicity-related genes encoding small secreted proteins that may play essential roles in virulence and host specificity. De novo repeat identification allowed us to show that few families of transposable elements are shared between Zymoseptoria species while we observe many species-specific invasions and expansions. The annotation data presented here provide a high-quality resource for future studies of Z. tritici and its sister species and provide detailed insight into gene and genome evolution of fungal plant pathogens.
Copyright © 2015 Grandaubert et al.

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Keywords:  comparative genomics; gene annotation; species-specific genes; transposable elements

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Year:  2015        PMID: 25917918      PMCID: PMC4502367          DOI: 10.1534/g3.115.017731

Source DB:  PubMed          Journal:  G3 (Bethesda)        ISSN: 2160-1836            Impact factor:   3.154


The genus Zymoseptoria (class Dothideomycetes, order Capnodiales) comprises a group of plant pathogens that infect a variety of Poaceae species. The four pathogen species Z. tritici, Z. pseudotritici, Z. ardabiliae, and Z. brevis originated in the Middle East and have diverged recently (within the past ∼22,000 years) (Stukenbrock ). Speciation in the genus Zymoseptoria has been associated with specialization and adaptation to different hosts in different environments (Quaedvlieg ; Stukenbrock ). Most notably, Z. tritici co-evolved and spread with domesticated Triticum species and is today a prominent pathogen of wheat worldwide (Banke and McDonald 2005). The poorly described Z. brevis species (Quaedvlieg ) was isolated in Iran like Z. pseudotritici and Z. ardabiliae, but from another grass host, Phalaris minor. Phylogenetic analyses based on information from six DNA loci place Z. brevis next to Z. pseudotritici, suggesting that this species also shares recent common ancestry with the wheat pathogen (Stukenbrock ). The close relatedness of the four Zymoseptoria species makes this a unique model system to study host specialization and speciation of fungal plant pathogens. The genome of Z. tritici (isolate IPO323) was sequenced and annotated by the Joint Genome Institute (JGI) and provides one of the best-assembled eukaryotic genomes with 21 complete chromosomes sequenced from telomere to telomere (Goodwin ). Of the 21 chromosomes, eight are considered accessory chromosomes because they can be lost during meiosis without any apparent effect on fitness in sexual progenies (Wittenberg ). The functional relevance of these accessory chromosomes is so far not known. They contain a higher proportion of repetitive DNA, encode fewer genes (Goodwin ), and show a dramatically lower level of transcription compared to the core chromosomes (Kellner ). The previously generated annotation predicted more than 10,000 genes in the genome of IPO323. The pipeline applied for the annotation used several gene predictors including putative full-length genes from EST cluster consensus sequences (Goodwin ). Nevertheless, this gene annotation comprises many incomplete gene models (14%) without start and/or stop codons. Different aspects of genome evolution in Z. tritici have been studied using comparative analyses of different Zymoseptoria genomes (Stukenbrock , 2011). A comparative genome study of the reference isolate IPO323 and an isolate of Z. pseudotritici allowed a detailed analysis of genome divergence in coding and noncoding sequences and a comparison of chromosome content and synteny in the two species (Stukenbrock ). Multiple genomes were analyzed in a comparative population genomic analysis including Z. tritici, Z. pseudotritici, and Z. ardabiliae to further assess signatures of positive selection and the speciation history of the three species (Stukenbrock ). Both studies relied on the previously generated annotation of the Z. tritici reference isolate IPO323, and thereby only described evolution of gene content shared between species. Repeats have also been identified in the reference genome of Z. tritici (Dhillon ; Goodwin ; Ohm ), but they were only exhaustively classified into transposable element (TE) families recently (Dhillon ). In fungal genomes, as in many eukaryotic genomes, TEs can constitute a large fraction of the genome, e.g., 40% of the Pseudocercospora fijiensis genome (Ohm ) and 64% of the Blumeria graminis genome (Spanu ). TEs play an important role in the evolution of genomes, and in fungi they are shown to be responsible for large genomic rearrangements (Croll ; de Jonge ; Grandaubert ) and for the creation of highly dynamic regions that provide accelerated diversification and chromatin-based regulation for genes within or near these regions (Rouxel ; Soyer ). An in-depth characterization of the complete TE repertoire of the four known Zymoseptoria species would allow detailed insights into the impact of repetitive DNA on the evolution of core as well as accessory chromosomes in these pathogens. We set out to conduct a thorough annotation of protein-encoding genes and repetitive sequences in all four Zymoseptoria species. Our goal was to improve the existing annotation of Z. tritici and to generate a complete set of gene models and repeat families for the four Zymoseptoria species for comparative genome analyses. All predicted gene models were in silico functionally annotated. We particularly focused on the presence and distribution of small proteins with signal peptides because these could be effector proteins produced to overcome host immune defenses (de Jonge ). To characterize a set of core Zymoseptoria genes and to identify species-specific orphan genes, we conducted a detailed analyses of gene homologies. Furthermore, we addressed the distribution of TEs in the Zymoseptoria genomes with a particular focus on TE content of core and accessory chromosomes of Z. tritici and the distribution of TE families between the four Zymoseptoria species. The dataset presented here provides not only a new high-quality annotation of Z. tritici but also a detailed characterization of gene families among Z. tritici, Z. pseudotritici, Z. ardabiliae, and Z. brevis.

Materials and Methods

Genome data

For the gene annotation, the genomes of Z. tritici (isolate IPO323) (Goodwin ), Z. pseudotritici (isolate ST04IR_2.2.1), and Z. ardabiliae (isolate ST04IR_1.1.1) (Stukenbrock ) were used. For the annotation of Z. brevis, the genome of the isolate Zb18110 was sequenced. Genomic DNA was isolated using a standard phenol-chloroform protocol (Sambrook and Russell 2001), and sequencing of 100-bp paired-end reads was performed using a HiSeq2000 Illumina platform (AROS Applied Biotechnology, Denmark). A de novo assembly of the Z. brevis Illumina reads was generated using the CLC Genomics Workbench version 5 (CLC, Aarhus, Denmark) with standard settings for paired-end read assembly. This assembly is available under the NCBI BioProject (PRJNA273516) on Genbank. The assembled genomes of Z. pseudotritici, Z. ardabiliae (Stukenbrock ), and Z. brevis used for the gene annotation contained a very low number of repetitive DNA. Therefore, new assemblies better representing the repeat content of these species genomes were constructed using Illumina sequences obtained from the isolates Z. pseudotritici ST04IR_5.5, Z. ardabiliae ST11IR_6.1.1, and Z. brevis Zb163. Assemblies of these new Illumina genomes were generated using SOAPdenovo2 (Luo ) with optimized k-mer values allowing the inclusion of repeats in the assemblies. These three assemblies are available under the NCBI BioProject (PRJNA274679) on Genbank.

RNA-seq data

Two previously published RNA-seq datasets were used for de novo transcript assembly of Z. tritici IPO323 including one dataset obtained from RNA extracted from infected Triticum aestivum (cultivar Obelisk) seedlings and one dataset obtained from axenically grown fungal cells (Kellner ). For Z. pseudotritici, Z. ardabiliae, and Z. brevis, RNA-seq data were obtained from axenically grown cultures. Total RNA was extracted from fungal cells grown in YMS (4 g yeast extract, 4 g malt extract, 4 g sucrose, 20 g bacto agar, 1 liter H2O) agar in a shaking incubator at 200 rpm at 18° using the TRIZOL reagent (Invitrogen, Darmstadt, Germany) following the protocol of the manufacturer. Illumina RNA-seq libraries for two axenic culture replicates per species were prepared from an input of 10 µg total purified polyA RNA (Palma-Guerrero ). Libraries were quantified by fluorometry, immobilized, and processed onto a flow cell with a cBot (Illumina), followed by sequencing-by-synthesis with TruSeq v3 chemistry on a HiSeq2000 at the Max Planck Genome Center (Cologne, Germany). RNA-seq data for Z. pseudotritici, Z. ardabiliae, and Z. brevis are respectively available in the NCBI BioProjects (PRJNA277173, PRJNA277174, PRJNA277175). For data processing, the sequence read quality was first evaluated using FASTQC (www.bioinformatics.babraham.ac.uk/projects/fastqc/). Subsequently, reads were filtered using tools from the Galaxy server, including grooming, trimming, filtering, and masking steps (Giardine ). Reads with an overall quality score less than 20 were removed. For the remaining reads, all nucleotides with a quality score less than 20 were masked with Ns. For Z. tritici, reads from the host (T. aestivum) transcriptome were initially filtered out using fastq_screen v0.4.1 (www.bioinformatics.babraham.ac.uk/projects/fastq_screen) as described by Kellner .

Gene annotation

Protein-coding genes were identified using the Fungal Genome Annotation pipeline described by Haas . The individual steps of the pipeline are described below.

Transcript reconstruction:

Transcript reconstruction using Trinity (Grabherr ; Haas ) was carried using de novo and genome-guided methods. By the de novo method, RNA-seq reads were first assembled into unique sequences of transcripts (contigs) using the Inchworm module within Trinity. Contigs were clustered by the Chrysalis module, and corresponding De Bruijn graphs that represent the possible different isoforms were constructed. In the final step, De Bruijn graphs were processed by the Butterfly module to produce full-length transcripts. In the genome-guided method, RNA-seq reads were first aligned to the genome using GMAP (Wu and Watanabe 2005). Based on these aligned-read clusters, the Chrysalis and Butterfly modules were consecutively executed to produce the final reconstructed transcripts. Transcripts generated by these two methods were combined using the “Program to Assemble Spliced Alignments” (PASA) (Haas ) pipeline to build a complete set of unique transcripts corresponding to gene models.

Training:

First, GeneMark-ES (Ter-Hovhannisyan ) was used for ab initio predictions, because its self-training algorithm allowed the identification of high-quality gene models. Next, evidence from homology searches using tBLASTn (e-value cut-off of 1e-10) (Altschul ) against a nonredundant protein database (UniRef90) (Suzek ) and from reconstructed transcripts were used to filter the ab initio predicted gene models. Only the complete gene models predicted by GeneMark-ES with a support from the homology-based comparison (100% of coverage for each exon) and with the exact same exon–intron boundaries as in the reconstructed transcripts were selected for the training and testing of ab initio gene predictors. The 2693 selected gene models were divided into two sets: one for the training (training set) containing 1611 sequences (60%) and one for assessing prediction accuracy (test set) containing 1082 sequences (40%). The evaluation of the training process was performed using Augustus (Stanke and Waack 2003). For all species, better performance was obtained using datasets of Z. tritici. We used the Z. tritici training set to train the ab initio gene callers for all the species.

Gene prediction and annotation:

The trained GeneMark.hmm (Lukashin and Borodovsky 1998) and Augustus programs were used to predict gene models. For Z. tritici, Fgenesh (Salamov and Solovyev 2000) gene models obtained from the first annotation by JGI (Goodwin ) were also included. Gene models obtained from the trained gene predictors were evaluated and combined using the EVidenceModeler (EVM) software (Haas ) to create a weighted consensus of the gene structures. Weights of 3, 5, and 7 were used for ab initio predictions, homology-based predictions, and transcript evidence, respectively. Homology-based gene models obtained from GeneWise (Birney ) were only used for Z. tritici as reliable gene models; they could not be obtained in the much more fragmented genomes of Z. pseudotritici, Z. ardabiliae, and Z. brevis. Based on transcript alignments, the PASA pipeline was used to correct the consensus gene model structure and to resolve conflicts between different isoforms.

Gene comparison

Based on the four predicted proteomes of the Zymoseptoria species, sequence comparisons were performed with BLASTp (e-value cut-off of 1e-5). Obtained pairwise protein alignments were processed using the software SiLiX to build families of homologous proteins (Miele ). Proteins were clustered together into families if they shared at least 55% of sequence identity over at least 60% of sequence coverage. The building of these families was divided in two steps. First, only complete protein sequences were used to create families. Second, using a semi-bipartite graph, partial protein sequences were added to the existing families.

Secretome prediction

Plant pathogens secrete proteins to interfere with host immune defenses. Genes encoding secreted proteins are therefore of particular interest due to their potential role in infection and host–pathogen interaction. We screened predicted proteins for the presence of signal peptides and categorized proteins as secreted under the following conditions: (i) if a signal peptide was predicted by both Neural-Network and HMM methods by the software SignalP 3.0 (Emanuelsson ); (ii) if zero or one transmembrane domain was present in the protein (the domain having at least 30% overlap with the signal peptide) using the software TMHMM 2.0 (Krogh ); and (iii) if the protein was predicted to be targeted to the secretory pathway by the software TargetP 1.1 (Emanuelsson ). Secreted proteins with a size of 300 amino acids or less were considered as small secreted proteins (SSPs).

Functional annotation

Automated functional annotations of the predicted proteins of Z. tritici, Z. pseudotritici, Z. ardabiliae, and Z. brevis were performed as previously described by Grandaubert . Using a combination of BLAST and InterProScan (Quevillon ), predicted proteins of each of the four species were categorized into three classes. The first class included proteins with no significant BLAST hit and with no known protein domain identified by InterProScan. These proteins were classified as “predicted proteins,” i.e., predictions with no functional support. This class contained an excess of species-specific genes. The second class, termed “hypothetical proteins,” included proteins with at least one domain identified by InterProScan in the InterPro or Pfam databases (Hunter ; Coggill ) or that fulfilled the BLAST result criteria defined by Grandaubert and for which the description indicated “hypothetical protein” in more than 90% of the BLAST hits. Globally, this class contained predictions with poor functional evidence likely corresponding to conserved proteins among several organisms but with no defined functions. The third class included predictions that fulfilled the BLAST result conditions with at least one domain from the InterPro or Pfam database corroborating by the consensus BLAST description. This class was termed the “similar to function” and included well-conserved proteins with defined functions in many organisms.

Repeats and transposable elements identification

Repetitive DNA was identified and annotated in SOAP assembled genomes of the four isolates described above to create a repertoire of repeats specific to the Zymoseptoria genus using the REPET pipeline (Flutre ). To obtain more complete elements, repeat families in each species were clustered using Blastclust from the NCBI-BLAST package (Altschul ), aligned using Mafft (Katoh and Standley 2013), and new consensuses were then created. These steps were iterated with decreasing values of identity percentage (from 100% to 75%) and coverage (from 100% to 30%) until there was no more clustering of the sequences. Next, the sequences were classified (TEclassifier.py script from REPET) using tBLASTx and BLASTx against the Repbase Update database (Jurka ) and by the identification of structural features such as long terminal repeats (LTRs) or terminal inverted repeats (TIRs). The sequences were additionally translated into the six reading frames to perform a protein domain search on the conserved domain database (CDD) (Marchler-Bauer ) using RPS-BLAST. Transposable element (TE) families of each strain were classified and named according to the nomenclature defined by Wicker . The 497 repeat families identified in this study are available in FASTA format in Supporting Information, File 1.

Results

Improved gene annotation of Z. tritici

RNA-seq data and detailed homology searches allowed us to generate an improved annotation of gene models in the IPO323 Z. tritici reference genome. Read data obtained from in planta and in vitro experiments were filtered (Table S1) and used for transcriptome assembly. Assemblies were based on two different but complementary approaches: (i) de novo, where the reads were assembled without a reference sequence and (ii) genome-guided, where the IPO323 reference genome was used as a template for transcript assemblies. In total, 68,653 transcripts were generated by the de novo method and 73,127 transcripts by the genome-guided method (Table 1). These transcripts were used to create a final database containing 13,847 putative gene models next used for the generation of a training set for ab initio predictors and for the correction of predicted gene models. We generated a final training set of 1611 gene models that was used to train two ab initio gene predictors: Augustus (Stanke and Waack 2003) and GeneMark-hmm (Lukashin and Borodovsky 1998). The outputs of these software were combined with 10,893 predicted gene models of another ab initio predictor, Fgenesh (Salamov and Solovyev 2000), obtained from the JGI annotation. We thereby obtained a total of 36,423 different gene models combining models from Augustus, GeneMark-hmm, and Fgenesh. These gene models were processed by EVidence Modeler (EVM) (Haas ) to identify a consensus model for each gene. Finally, corrections were applied to the gene models using PASA (Haas ) and the previously reconstructed RNA-seq-based transcripts.
Table 1

Annotation features for the four members of the Zymoseptoria species complex

Z. triticiZ. pseudotriticiZ. ardabiliaeZ. brevis
Assembly
Assembly size (Mb)39.732.731.531.9
No. of scaffolds2111648686116
Previous annotationNew
annotation
Transcriptome reconstruction
No. of transcripts (de novo)68,65316,05616,35317,870
No. of transcripts (genome-guided)73,12719,07620,19315,331
No. of gene models13,84712,02712,71910,649
Gene annotation
No. of predicted gene models10,95211,83911,04410,78710,557
No. of complete gene models939711,79510,95710,68610,342
No. of partial gene models15554487101215
No. of gene models with RNA-seq supporta942310,048761882979939
Average gene length (bp)1599.81620.91594.31584.91592.8
Average transcript length (bp)1388.81462.11459.41440.91462.5
Average protein length (aa)436.6487.8488.0482.0487.5
No. of exons28,30930,06826,69926,23125,367
Average exon length (bp)505.7575.2604.7593.7608.1
Average no. of exons per gene2.592.542.422.432.40
No. of introns17,35718,22615,65315,44514,809
Average intron length (bp)124.191.690.998.494.6
Average no. of introns per gene2.272.272.162.162.16
No. of genes with introns76548044723471656883
Gene density (genes/Mb)276.0298.3338.2330.3331.1
Functional annotation
% of predicted proteins22.918.819.218.1
% of hypothetical proteins31.331.231.432.8
% of similar to proteins45.85049.449.1
No. of secreted proteins970b874838965700
No. of small secreted proteins (<300 aa)441b441399540331

Based on alignment with reconstructed transcripts (e-value < 1e-5).

Extracted from Morais do Amaral et al. 2012.

Based on alignment with reconstructed transcripts (e-value < 1e-5). Extracted from Morais do Amaral et al. 2012. The final gene annotation of IPO323 consists of 11,839 gene models (Table 1). Distributions of the number of gene models along the chromosomes of the annotation presented here and the previous JGI annotation are shown in Figure S1. In our new annotation, only 44 gene models were incomplete (i.e., without start and/or stop codon) compared to 1555 incomplete genes in the previous annotation (Table 1). To identify shared and unique gene models, we used a BLAST search (e-value cut-off of 1e-10). We found 4707 identical gene models between the two annotations. Furthermore, we found 442 gene models uniquely predicted by the JGI pipeline and 1200 models uniquely predicted by the pipeline used here. Gene models of our annotation have an average length of 1621 bp and exhibit longer exons (mean exon length 575 vs. 505 bp) and encode longer proteins (488 vs. 437 amino acids) when compared to the annotation generated by the JGI pipeline (Table 1). A BLAST comparison at the nucleotide level of our final gene models against the reconstructed transcripts showed that 10,048 out of the 11,839 predicted genes have support based on the RNA sequencing. In the previous annotation, 9423 predicted genes had support compared to the transcripts reconstructed in this study, which underlines the efficiency of this new annotation to predict biologically relevant gene models. In silico functional annotation based on protein signatures and homologies allowed us to assign a function to 43% of the 11,839 predicted proteins. A total of 2714 sequences (22.9%) had no homologies within the NCBI nonredundant protein database and did not include any known protein domain. These represent either species-specific genes of Z. tritici or incorrectly predicted genes. Given the fact that 55% of these have RNA-seq support, we considered that the majority of these novel genes must be correctly predicted. Characterization of the Z. tritici secretome yielded comparable results to the previously reported Z. tritici secretome (Morais Do Amaral ), representing 874 secreted proteins including 441 small, secreted proteins (SSPs), i.e., with a size inferior to 300 amino acids (Table 1). SSPs of Z. tritici have, on average, 2.8-times more cysteine residues compared to the whole proteome (data not shown supporting an extracellular role) (Fass 2012).

Gene annotation using re-sequenced genomes and RNA-seq data from Z. pseudotritici, Z. ardabiliae, and Z. brevis

RNA-sequencing data obtained from axenic cultures of Z. pseudotritici, Z. ardabiliae, and Z. brevis were filtered (Table S1) and assembled. The resulting transcriptomes include 35,132, 36,546, and 33,201 transcripts clustered into 12,027, 12,719, and 11,542 putative gene models for Z. pseudotritici, Z. ardabiliae, and Z. brevis, respectively (Table 1). The training set established for Z. tritici was also for the annotation of the three other Zymoseptoria species. For each species, EVM created a weighted consensus of the gene models, which after PASA corrections resulted in 11,044, 10,787, and 10,557 gene models for Z. pseudotritici, Z. ardabiliae, and Z. brevis, respectively (Table 1). The total number of predicted gene models in the re-sequenced Zymoseptoria species was similar; however, due to the fragmented genome assemblies of Z. pseudotritici, Z. ardabiliae, and Z. brevis, more partial gene models were predicted compared to models in Z. tritici (Table 1). Overall, the gene characteristics of these four species are very similar in accordance with the close phylogenetic relationships. Compared to Z. tritici, the functional annotation of the predicted gene models in Z. pseudotritici, Z. ardabiliae, and Z. brevis showed a larger proportion of sequences with an attributed function and a smaller proportion of sequences with no functional evidences. The four annotations are available from http://fungi.ensembl.org/Zymoseptoria_tritici/Info/Index (Z. tritici), http://genome.jgi.doe.gov/Zymps1/Zymps1.home.html (Z. pseudotritici), http://genome.jgi.doe.gov/Zymar1/Zymar1.home.html (Z.ardabiliae), and http://www.uniprot.org/taxonomy/1047168 (Z. brevis).

Gene distribution in Zymoseptoria species

Homology relationships among the four Zymoseptoria species including orthology (interspecies) and paralogy (intraspecies) were analyzed by a comparison of the predicted proteomes using the software package SiLiX (Miele ). Of the total 44,227 proteins predicted in the four Zymoseptoria species, 39,177 (88.6%) were clustered into 10,612 families. These families belong to three categories. First, there are 10,361 families of orthologous sequences present in at least two species. The different distributions of these families across the Zymoseptoria species are shown in Figure 1. Second, there are 236 families of orthologous sequences that also included species-specific paralogous sequences, i.e., independent duplication of a conserved gene occurred in one or more species. Third, there are 15 families of paralogous sequences, i.e., duplication of species-specific genes. The remaining 5050 sequences that could not be classified into a gene family were considered as proteins encoded by orphan genes.
Figure 1

Venn diagram showing the distribution of predicted models in Z. tritici: Z. pseudotritici, Z. ardabiliae, and Z. brevis. The categorizations of core Zymoseptoria genes, orphan genes, and genes shared by three or two species were performed using a detailed characterization of gene orthology.

Venn diagram showing the distribution of predicted models in Z. tritici: Z. pseudotritici, Z. ardabiliae, and Z. brevis. The categorizations of core Zymoseptoria genes, orphan genes, and genes shared by three or two species were performed using a detailed characterization of gene orthology.

Orphan genes:

The genome of Z. tritici encodes 1798 orphan genes (15.1% of all the predicted genes), of which 1221 are localized on core chromosomes and 577 on accessory chromosomes. However, accessory chromosomes are significantly enriched in orphan genes because they constitute 79.3% of the genes on these chromosomes compared to 10.9% on core chromosomes (χ2 test, P < 2.2e-16). A large majority of the orphan genes (95.5%) have no in silico attributed function. In general, we could not link species-specific genes to any biological or pathogenicity-related function; however, this uniqueness supports the species-specific nature of the genes that have no homology with known proteins from organisms outside the Zymoseptoria species complex. Among the orphan sequences that could be assigned a function, we found predicted functions relating to molecule transport (drugs, proteins, amino acids), primary and secondary metabolism (oxydoreductase activity, nonribosomal peptide synthase), and organic compounds degradation (chitinase, glycoside hydrolase). Small secreted proteins (SSPs) of plant pathogens particularly play an important role as putative effectors during the host infection (Stergiopoulos and De Wit 2009), and we found in Z. tritici that SSP-encoding genes were significantly enriched in the orphan gene set compared to the whole proteome: 8% vs. 3.7% (χ2 test, P < 2.2e-16). Orphan genes representing 9–11% of the predicted genes in Z. pseudotritici, Z. ardabiliae, and Z. brevis were likewise significantly enriched in SSP-encoding genes and genes that could not be assigned a function.

Paralogous genes:

Families of paralogous genes were only found in Z. tritici (eight families) and Z. ardabiliae (seven families) and included 23 and 14 genes, respectively. In Z. ardabiliae, 57% of these duplicated sequences are SSP-encoding genes, whereas there were no SSP paralogs in Z. tritici. In Z. ardabiliae, only one family could be associated with a gene function (kinase), whereas in Z. tritici several families contained sequences with known protein domains of transposable elements.

Orthologous genes:

Families of orthologous genes within the four Zymoseptoria species were divided into three categories. The first category comprised the core set of Zymoseptoria genes and included 7786 families containing one gene per species (Figure 1). A large proportion of these genes (59.5%) could be associated with a predicted function, whereas 8.3% of them had no homology to genes in other organisms and thereby potentially represented a set of Zymoseptoria-specific genes. The second category comprised genes present in three out of the four species and included 1294 families. Genes in this second category appeared to be less conserved because only 33% of them could be associated with function information. Finally, the third category included 1281 families comprising genes only found in two of the four species. Compared to the two other categories, genes with a function represented a smaller fraction (18%).

Orthologous genes with paralogy:

A particular category of families was also identified where orthologous sequences were conserved in two or more species with independent duplications in one or more species. This category contained 236 families with 1552 sequences. Most of the families (87%) comprised genes present in the four species. The largest family included 15 genes all encoding an alcohol dehydrogenase with four copies found in Z. tritici, Z. pseudotritici, and Z. brevis and three copies in Z. ardabiliae.

Transposable element annotation

TEs in Z. tritici:

Of the 39.7-Mb genome assembly of Z. tritici IPO323, 7.4 Mb (18.6%) (Table 2) were found to be repetitive DNA, in agreement with the recently reported repeat content of IPO323 (>17%) in Dhillon . Repeats were classified into TE families based on features such as terminal repeats, protein domains, and homology with known TE available in the Repbase Update database (Jurka ). The fact that the assembled genome of Z. tritici consists of complete chromosomes allowed a high-quality repeat annotation with only few uncategorized families. TEs of class I (retrotransposons) are the most abundant in the IPO323 genome and represent 13.1% of the total genome size (5.2 Mb), whereas TEs of class II (DNA transposons) represent 4.2% (1.6 Mb) (Table 2). The remaining repetitive sequences represent 0.5 Mb and could not be associated with classified TEs. From the 111 consensus sequences obtained by our procedure (see Materials and Methods), we identified 101 families of TEs. The majority of these families belong to the class II (62 families), mainly represented by TIRs (44 families), MITEs (11 families), and Helitron (4 families). Although present in a lower number (32 families), class I elements represent 71% of the repetitive fraction of the genome. The most abundant group of class I elements is the LTR elements from the Gypsy superfamily (14 families), followed by those of the Copia superfamily (12 families) and LINEs (7 families) (Table 2). Interestingly, we also identified one family of a complete tyrosine-recombinase retrotransposon that belongs to the Ngaro superfamily and that otherwise has been described to be absent in Ascomycota (Muszewska ). Distinguishing core and accessory chromosomes of Z. tritici, we find that repetitive DNA represents 16.6% of the core chromosomes and 33.6% of the accessory chromosomes (Figure 2A). However, the relative distribution of the major TE families on core and accessory chromosomes does not differ significantly (Wilcoxon test, P = 0.3692) (Figure 2B).
Table 2

Transposable element content in genomes of the Zymoseptoria species complex

Z. triticiZ. pseudotriticiZ. ardabiliaeZ. brevis
Family No.DNA Amount (kb)% of GenomeFamily No.DNA Amount (kb)% of GenomeFamily No.DNA Amount (kb)% of GenomeFamily No.DNA Amount (kb)% of Genome
Class I (retrotransposons)
LTRRLC1210172.566900.2352320.6278272.08
RLG1426496.671729067.501610742.881836169.09
LINERII47371.86000.003760.2045471.38
RIL27471.88000.001320.09000.00
RIX150.011830.221670.1811930.48
DIRSRYN1230.06000.00000.00000.00
SINERSX110.00000.00000.00000.00
TRIMRLX-TRIM4350.09000.00000.00140.01
Sub-total class I39521413.142430807.942614813.9731518613.04
Class II (DNA transposons)
TIRDTT142460.623510.134290.0892540.64
DTA71500.381350.09140.0151750.44
DTH101840.46000.00000.00112920.74
DTM71450.361440.11000.0042130.54
DTX63640.9264321.115760.2033150.79
UnknownDXX2400.10000.00000.00000.00
CryptonDYX160.02000.00000.00000.00
HelitronDHH44701.1873570.921390.1053910.98
MaverickDMM000.0024761.23000.00000.00
MITEDTX-MITE11480.12120.01150.013110.03
Sub-total class II6216534.172113993.61121530.414016524.15
Uncategorized repeats
NoCatNoCat105161.306015183.927913033.499326346.62
Total111738318.60105599715.4711729377.87164947223.87
Figure 2

Transposable elements (TEs) characteristics along the 21 chromosomes of Zymoseptoria tritici. (A) Proportions of TEs in the chromosomes of Z. tritici. The red dashed lines show the mean values of TEs on core (1–13) and accessory chromosomes (14–21). (B) The distribution of five major TE classes across core and accessory chromosomes in Z. tritici show a more or less similar distribution and frequency on the two types of chromosomes.

Transposable elements (TEs) characteristics along the 21 chromosomes of Zymoseptoria tritici. (A) Proportions of TEs in the chromosomes of Z. tritici. The red dashed lines show the mean values of TEs on core (1–13) and accessory chromosomes (14–21). (B) The distribution of five major TE classes across core and accessory chromosomes in Z. tritici show a more or less similar distribution and frequency on the two types of chromosomes. As already described by Goodwin , repetitive sequences are highly affected by the fungal-specific repeat inactivation mechanism known as repeat-induced point mutations (RIP) (Galagan and Selker 2004). Multiple alignments of several family copies analyzed by RIPCAL (Hane and Oliver 2008) showed an excess of CpA→TpA and TpG→TpA mutations. As hypothesized by Goodwin , these mutations should prevent TEs from expressing their own machinery. However, it appears that 98 predicted gene models overlap TE sequences with at least 50% of their length, including 75 genes models that are completely embedded in repetitive DNA. Of the 98 corresponding proteins, 33 harbor domains associated with TEs such as reverse-transcriptase, transposase, or integrase (Table 3). These domains belong to 22 distinct TE families, including 12 TIR, eight LTR, one LINE, and one uncategorized element. Comparison of these gene models with the reconstructed transcripts showed that 48% have RNA-seq support; this suggests that TE families (mainly class II DNA transposons) are still active in the Z. tritici genome despite the RIP machinery.
Table 3

Gene models with protein domains associated with transposable elements

Protein IDLength (aa)Domain NameDomain DescriptionInterpro or Pfam Accession No.Overlapping Repeat FamilyRNA-seq Support
Zt09_chr_1_00001143RVT_1Reverse-transcriptase (RNA-dependent DNA polymerase)PF00078RIL_element2_ZTIPO323
Zt09_chr_1_00017272DDE_Tnp_4DDE superfamily endonucleasePF13359DTH_element5_ZTIPO323
Zt09_chr_1_01076477DDE_3DDE superfamily endonucleasePF13358DTT_element10_ZTIPO323Yes
Zt09_chr_2_00093477DDE_3DDE superfamily endonucleasePF13358DTT_element10_ZTIPO323
Zt09_chr_2_00258409DDE_Tnp_1_7Transposase IS4PF13843DTX_element1_ZPST04IR55Yes
Zt09_chr_2_00383648DDE_1DDE superfamily endonucleasePF03184DTT_element1_ZTIPO323Yes
Zt09_chr_2_00481532ChromoChromo (CHRromatin Organization MOdifier) domainPF00385RLG_element5_ZPST04IR55
Zt09_chr_2_00619272RVT_2Reverse-transcriptase (RNA-dependent DNA polymerase)PF07727RLC_element3_ZTIPO323
Zt09_chr_2_00906219DDE_1DDE superfamily endonucleasePF03184DTT_element5_ZTIPO323Yes
Zt09_chr_2_00907269DDE_1DDE superfamily endonucleasePF03184DTT_element5_ZTIPO323Yes
Zt09_chr_3_00204734RNaseH-like_domRibonuclease H-like domainIPR012337DTA_element2_ZTIPO323Yes
Zt09_chr_3_00229349DDE_3DDE superfamily endonucleasePF13358DTT_element14_ZTIPO323Yes
Zt09_chr_4_00051195DDE_3DDE superfamily endonucleasePF13358DTT_element4_ZB163
Zt09_chr_4_00288371RNaseH-like_domRibonuclease H-like domainIPR012337DTA_element3_ZTIPO323Yes
Zt09_chr_5_00137477DDE_3DDE superfamily endonucleasePF13358DTT_element10_ZTIPO323Yes
Zt09_chr_7_00478338RNaseH-like_domRibonuclease H-like domainIPR012337DTA_element6_ZTIPO323Yes
Zt09_chr_7_00479108RNaseH-like_domRibonuclease H-like domainIPR012337DTA_element6_ZTIPO323Yes
Zt09_chr_9_000031506RVT_1Reverse-transcriptase (RNA-dependent DNA polymerase)PF00078RIL_element2_ZTIPO323
Zt09_chr_9_00154621DDE_1DDE superfamily endonucleasePF03184DTT_element1_ZTIPO323Yes
Zt09_chr_9_005571061rveIntegrase core domainPF00665RLC_element7_ZTIPO323Yes
Zt09_chr_9_00615458DDE_Tnp_1_7Transposase IS4PF13843DTX_element1_ZAST11IR611Yes
Zt09_chr_10_00001218RVT_2Reverse-transcriptase (RNA-dependent DNA polymerase)PF07727RLC_element7_ZTIPO323
Zt09_chr_11_00364162ChromoChromo (CHRromatin Organization MOdifier) domainPF00385RLG_element7_ZPST04IR55
Zt09_chr_13_00054869DDE_3DDE superfamily endonucleasePF13358DTT_element10_ZTIPO323Yes
Zt09_chr_13_00057150RVT_2Reverse-transcriptase (RNA-dependent DNA polymerase)PF07727RLC_element2_ZTIPO323
Zt09_chr_13_00271480RNaseH-like_domRibonuclease H-like domainIPR012337DTA_element1_ZTIPO323Yes
Zt09_chr_17_00004876RVT_1Reverse-transcriptase (RNA-dependent DNA polymerase)PF00078RIL_element2_ZTIPO323
Zt09_chr_17_00088523RVT_1Reverse-transcriptase (RNA-dependent DNA polymerase)PF00078RIL_element2_ZTIPO323
Zt09_chr_18_00008750RNaseH-like_domRibonuclease H-like domainIPR012337NoCat_element60_ZAST11IR611
Zt09_chr_19_00003169RVT_2Reverse-transcriptase (RNA-dependent DNA polymerase)PF07727RLC_element5_ZTIPO323
Zt09_chr_19_00040947RVT_2Reverse-transcriptase (RNA-dependent DNA polymerase)PF07727RLC_element9_ZTIPO323
Zt09_chr_19_00041107UBN2_3gag-polypeptide of LTR copia-typePF14244RLC_element9_ZTIPO323
Zt09_chr_21_000031609RVT_1Reverse-transcriptase (RNA-dependent DNA polymerase)PF00078RLG_element9_ZTIPO323

TEs in Z. pseudotritici, Z. ardabiliae, and Z. brevis:

To improve the repeat annotation of Z. pseudotritici, Z. ardabiliae, and Z. brevis, we generated improved assemblies of Illumina-sequenced genomes of the isolates: ST04IR55 of Z. pseudotritici, ST11IR611 of Z. ardabiliae, and Zb163 of Z. brevis. The assembly sizes were 38.8 Mb, 37.3 Mb, and 39.8 Mb, respectively, compared to the 39.7 Mb genome assembly of Z. tritici. The three genomes reflect different extents of repeat invasion: repetitive DNA comprises 7.9% of the Z. ardabiliae genome, 15.5% of the Z. pseudotritici genome, and 23.9% of the Z. brevis genome, including a total of 117, 105, and 164 repeat families identified in the genomes, respectively (Table 2). As a result of the fragmented assemblies, the number of uncategorized repeat families in the Z. pseudotritici, Z. ardabiliae, and Z. brevis genomes represent more than 50% of all the families and between 25% and 44% of the repetitive fraction. In contrast, the number of uncategorized families in the Z. tritici genome represents only 9% of the families and 7% of the repetitive fraction. Nevertheless, it was possible to classify some TE families of Z. pseudotritici, Z. ardabiliae, and Z. brevis and to record general patterns of TE distribution among the three genomes. As in the Z. tritici genome, class I TEs that are mainly represented by LTR-Gypsy elements are most abundant and account for 51–55% of the total repetitive fraction (Table 2). LINE elements are hardly represented in the Z. pseudotritici, Z. ardabiliae, and Z. brevis assemblies; however, this may be an artifact of the fragmented assemblies. In Z. pseudotritici and Z. brevis, class II TEs are mainly composed of TIRs that represent approximately 20% of the repetitive fraction similar to class II TEs in Z. tritici. Helitron elements were also identified in Z. pseudotritici, Z. ardabiliae, and Z. brevis; however, they accounted for only 1–6% of the repetitive fraction compared to 6.4% in Z. tritici. Maverick elements (Pritham ) were only identified in Z. pseudotritici and were the third most represented TE family in the genome (Table 2). The unique presence and distribution of Maverick elements in Z. pseudotritici could result from a recent invasion of the genome followed by massive waves of transposition of these elements.

The complete repertoire of repeats in Zymoseptoria spp:

In total, we found 497 repeat families in the four Zymoseptoria species, including 120 families of class I TEs (24.1%), 135 families of class II TEs (27.2%), and 242 uncategorized families (48.7%). We could improve the TE annotation using the complete Zymoseptoria TE library generated here. We found 19.9% of repeats (+1.3%) in the genome of Z. tritici, 17.6% (+2.2%) in the genome of Z. pseudotritici, 12.7% (+4.8%) in the genome of Z. ardabiliae, and 25.2% (+1.3%) in the genome of Z. brevis. Addressing TE evolution in the Zymoseptoria genomes, we found that some families identified independently in each species were derived from a common ancestral TE family. An analysis of the 497 families was performed using Blastclust (Altschul ) with a coverage cut-off of 50% and an identity percentage cut-off of 80%; this resulted in the clustering of 76 families into 34 larger groups (Table S2). Fourteen of these groups were composed of TIR elements, eight groups of LTR-Gypsy elements, six groups of uncategorized elements, three groups of LTR-Copia elements, two groups of Helitrons, and one group of LINE elements. Only one of these groups included TE families present in each of the four species; this suggests that this element, an LTR-Gypsy element, was present in the genome of the common ancestor of the four species (Table S2). Interestingly, this element may have expanded prior to the divergence of species because we observed a comparable size expansion in the four species comprising between 120 and 180 kb in each genome. Given the phylogenetic tree of the four Zymoseptoria species, as shown in Stukenbrock , the other TE groups were distributed in either two or three species with eight different ancestral relationships (Table S2). This analysis mainly showed that these species have undergone events of invasion and expansion of distinct TEs after their divergence.

Discussion

“Omics” analyses such as comparative and evolutionary genomics, transcriptomics, epigenomics, or proteomics mainly rely on the accuracy of predicted gene models. The Zymoseptoria species complex provides a unique model system for the application of “omics” data to study the underlying genetics of pathogenicity and host specificity of plant pathogens (Stukenbrock , 2011, 2012). However, updated and comparable annotations of gene and TE content in species of Zymoseptoria have so far been missing. Here, we present a new gene and repeat annotation of the prominent fungal wheat pathogen Z. tritici and its three close relatives: Z. pseudotritici, Z. ardabiliae, and Z. brevis; therefore, we provide a valuable resource for future functional, experimental, and evolutionary studies. We conducted the re-annotation of the IPO323 genome using a pipeline that identifies the most probable gene models based on information from transcript assemblies, homology searches, and ab initio gene predictors (Haas ). This allowed us to identify 11,839 gene models, including 1200 models that were not predicted previously by the JGI. The support of RNA-seq data for most of these genes underlines the potential of our pipeline for identifying novel genes. We applied the same annotation pipeline to re-sequenced genomes of the three close relatives of Z. tritici, Z. pseudotritici, Z. ardabiliae, and Z. brevis, and could call comparable numbers of genes in these species (∼10,500 models). Of these, 7786 represent core Zymoseptoria genes shared among the four species. Our exhaustive search for gene orthology also identified genes shared by two or three species and suggested recent gains or losses of genes among the Zymoseptoria species. Notably, we also identified 1798 orphan genes in Z. tritici enriched in putative pathogenicity-related factors. Species-specific orphan genes in Z. tritici and in the three other species may include key determinants of virulence in wheat and other grass hosts. Further functional studies will allow this hypothesis to be tested. Recently, a new identification and classification of repeats and TEs in Z. tritici was conducted (Dhillon ). In the present study we found very similar patterns in terms of repeat and TE distribution, number of families, and evidence of TE activity. However, we could further improve the assignment of repeat families to known TE families; 39.8% of the 93 repeat families identified by Dhillon et al. were not categorized into known TE classes. We were able to improve the TE classification, leaving only 9% of the 111 repeat families unclassified. The TE annotation pipeline used here contains a number of supplementary steps of clustering of the REPET outputs and allowed us to identify more complete elements. These were all manually checked to avoid the generation of false or chimera elements. The gene and TE annotation of the four Zymoseptoria species genomes coupled with preliminary comparative analysis allowed us to highlight interesting features relevant to the biological life traits of these organisms. Establishment of homologous sequence families across the four species showed that a large part of genes are shared between two or more species and that the major difference of gene content relies on orphan genes. These orphan genes, in all four species, are significantly enriched in putative pathogenicity-related genes and potentially play a role in the determination of host specificity. Similar presence–absence patterns of pathogenicity-related genes were shown to be strong determinants of host range in plant pathogens, e.g., between lineages of the rice blast pathogen Magnaporthe oryzae, the wilt pathogen Verticillium dahliae, and lineages of the Leptosphaeria maculansLeptosphaeria biglobosa species complex (Couch ; de Jonge ; Grandaubert ). Similarly, comparison of TE families showed a majority of species-specific sequences; this underlies the fact that each species genome has been widely invaded after the species divergence. We speculate that TEs may have played a role in host specialization by the acquisition or modification of pathogenicity-related traits. Also, large TE-rich regions could have played a role in speciation through the suppression of homologous recombination in chromosomal regions with inversions or translocations as proposed for the Leptosphaeria maculansLeptosphaeria biglobosa species complex (Grandaubert ). In Dhillon , the authors stated that several genes with putative pathogenicity-related functions were found to be associated with TEs. Preliminary analyses of genes and TEs tend to show that orphan genes are located significantly closer to TEs than other nonorphan genes (J. Grandaubert, unpublished data). TEs thus may play a role in the origin and evolution of these genes. The annotation data presented here will greatly improve our understanding of gene evolution, adaptation, and the role of TEs in pathogen evolution. The predicted gene models will furthermore greatly support future studies of gene expression in Z. tritici and its related species and provide a strong basis to understand the underlying genetics and molecular biology of host–pathogen interactions in Zymoseptoria spp.
  55 in total

1.  Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes.

Authors:  A Krogh; B Larsson; G von Heijne; E L Sonnhammer
Journal:  J Mol Biol       Date:  2001-01-19       Impact factor: 5.469

2.  Mavericks, a novel class of giant transposable elements widespread in eukaryotes and related to DNA viruses.

Authors:  Ellen J Pritham; Tasneem Putliwala; Cédric Feschotte
Journal:  Gene       Date:  2006-08-23       Impact factor: 3.688

3.  Tomato immune receptor Ve1 recognizes effector of multiple fungal pathogens uncovered by genome and RNA sequencing.

Authors:  Ronnie de Jonge; H Peter van Esse; Karunakaran Maruthachalam; Melvin D Bolton; Parthasarathy Santhanam; Mojtaba Keykha Saber; Zhao Zhang; Toshiyuki Usami; Bart Lievens; Krishna V Subbarao; Bart P H J Thomma
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-13       Impact factor: 11.205

4.  Zymoseptoria ardabiliae and Z. pseudotritici, two progenitor species of the septoria tritici leaf blotch fungus Z. tritici (synonym: Mycosphaerella graminicola).

Authors:  Eva H Stukenbrock; William Quaedvlieg; Mohammad Javan-Nikhah; Marcello Zala; Pedro W Crous; Bruce A McDonald
Journal:  Mycologia       Date:  2012-06-06       Impact factor: 2.696

5.  MAFFT multiple sequence alignment software version 7: improvements in performance and usability.

Authors:  Kazutaka Katoh; Daron M Standley
Journal:  Mol Biol Evol       Date:  2013-01-16       Impact factor: 16.240

Review 6.  RIP: the evolutionary cost of genome defense.

Authors:  James E Galagan; Eric U Selker
Journal:  Trends Genet       Date:  2004-09       Impact factor: 11.639

7.  Zymoseptoria gen. nov.: a new genus to accommodate Septoria-like species occurring on graminicolous hosts.

Authors:  W Quaedvlieg; G H J Kema; J Z Groenewald; G J M Verkley; S Seifbarghi; M Razavi; A Mirzadi Gohari; R Mehrabi; P W Crous
Journal:  Persoonia       Date:  2011-04-05       Impact factor: 11.051

8.  InterProScan: protein domains identifier.

Authors:  E Quevillon; V Silventoinen; S Pillai; N Harte; N Mulder; R Apweiler; R Lopez
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

9.  SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler.

Authors:  Ruibang Luo; Binghang Liu; Yinlong Xie; Zhenyu Li; Weihua Huang; Jianying Yuan; Guangzhu He; Yanxiang Chen; Qi Pan; Yunjie Liu; Jingbo Tang; Gengxiong Wu; Hao Zhang; Yujian Shi; Yong Liu; Chang Yu; Bo Wang; Yao Lu; Changlei Han; David W Cheung; Siu-Ming Yiu; Shaoliang Peng; Zhu Xiaoqian; Guangming Liu; Xiangke Liao; Yingrui Li; Huanming Yang; Jian Wang; Tak-Wah Lam; Jun Wang
Journal:  Gigascience       Date:  2012-12-27       Impact factor: 6.524

10.  DIRS and Ngaro Retrotransposons in Fungi.

Authors:  Anna Muszewska; Kamil Steczkiewicz; Krzysztof Ginalski
Journal:  PLoS One       Date:  2013-09-25       Impact factor: 3.240

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  40 in total

Review 1.  Evolution and genome architecture in fungal plant pathogens.

Authors:  Mareike Möller; Eva H Stukenbrock
Journal:  Nat Rev Microbiol       Date:  2017-08-07       Impact factor: 60.633

2.  A fungal wheat pathogen evolved host specialization by extensive chromosomal rearrangements.

Authors:  Fanny E Hartmann; Andrea Sánchez-Vallet; Bruce A McDonald; Daniel Croll
Journal:  ISME J       Date:  2017-01-24       Impact factor: 10.302

Review 3.  A Matter of Scale and Dimensions: Chromatin of Chromosome Landmarks in the Fungi.

Authors:  Allyson A Erlendson; Steven Friedman; Michael Freitag
Journal:  Microbiol Spectr       Date:  2017-07

4.  Hiding in plain sight: New virus genomes discovered via a systematic analysis of fungal public transcriptomes.

Authors:  Kerrigan B Gilbert; Emily E Holcomb; Robyn L Allscheid; James C Carrington
Journal:  PLoS One       Date:  2019-07-24       Impact factor: 3.240

5.  Mapping the adaptive landscape of a major agricultural pathogen reveals evolutionary constraints across heterogeneous environments.

Authors:  Anik Dutta; Fanny E Hartmann; Carolina Sardinha Francisco; Bruce A McDonald; Daniel Croll
Journal:  ISME J       Date:  2021-01-15       Impact factor: 10.302

6.  Histone modifications rather than the novel regional centromeres of Zymoseptoria tritici distinguish core and accessory chromosomes.

Authors:  Klaas Schotanus; Jessica L Soyer; Lanelle R Connolly; Jonathan Grandaubert; Petra Happel; Kristina M Smith; Michael Freitag; Eva H Stukenbrock
Journal:  Epigenetics Chromatin       Date:  2015-10-01       Impact factor: 4.954

7.  The Evolution of Orphan Regions in Genomes of a Fungal Pathogen of Wheat.

Authors:  Clémence Plissonneau; Alessandra Stürchler; Daniel Croll
Journal:  mBio       Date:  2016-10-18       Impact factor: 7.867

8.  Comprehensive Transcriptome Analysis Provides Evidence of Local Thermal Adaptation in Three Loaches (Genus: Misgurnus).

Authors:  Shaokui Yi; Sai Wang; Jia Zhong; Weimin Wang
Journal:  Int J Mol Sci       Date:  2016-11-24       Impact factor: 5.923

9.  Comprehensive Annotation of the Parastagonospora nodorum Reference Genome Using Next-Generation Genomics, Transcriptomics and Proteogenomics.

Authors:  Robert A Syme; Kar-Chun Tan; James K Hane; Kejal Dodhia; Thomas Stoll; Marcus Hastie; Eiko Furuki; Simon R Ellwood; Angela H Williams; Yew-Foon Tan; Alison C Testa; Jeffrey J Gorman; Richard P Oliver
Journal:  PLoS One       Date:  2016-02-03       Impact factor: 3.240

10.  A De Novo-Assembly Based Data Analysis Pipeline for Plant Obligate Parasite Metatranscriptomic Studies.

Authors:  Li Guo; Kelly S Allen; Greg Deiulio; Yong Zhang; Angela M Madeiras; Robert L Wick; Li-Jun Ma
Journal:  Front Plant Sci       Date:  2016-07-11       Impact factor: 5.753

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