RESOURCE ANNOUNCEMENTOpen Access icon OPENOpen Access license

A Telomere-to-Telomere Genome Assembly Resource of Bipolaris sorokiniana, the Fungal Pathogen Causing Spot Blotch and Common Root Rot Diseases in Barley and Wheat

    Affiliations
    Authors and Affiliations
    • Yueqiang Leng1
    • Yang Du2
    • Jason Fiedler3
    • Sajeet Haridas4
    • Igor V. Grigoriev4 5
    • Shaobin Zhong1
    1. 1Department of Plant Pathology, North Dakota State University, Fargo, ND 58108
    2. 2Department of Computer Systems and Software Engineering, Valley City State University, Valley City, ND 58072
    3. 3Cereal Crops Research Unit, Edward T. Schafer Agricultural Research Center, USDA-ARS, Fargo, ND 58102
    4. 4US Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA 94720
    5. 5Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA 94720

    Abstract

    Bipolaris sorokiniana (Cochliobolus sativus) is a fungal pathogen that causes spot blotch, common root rot, and kernel blight in barley and wheat. Four pathotypes (0, 1, 2, and 7) of the fungus were previously identified based on their virulence on three barley differential lines (Bowman, ND 5883, and NDB 112). Although several genome assemblies have been reported for B. sorokiniana, a telomere-to-telomere genome assembly is still lacking for this fungus. In this study, we assembled the genome of a pathotype 0 isolate (ND93-1) of B. sorokiniana using both PacBio HiFi reads and ultralong Oxford Nanopore Technology reads corrected with Illumina paired-end 100-bp short reads. The combined genome assembly of ND93-1 has an estimated size of 35.7 Mb and consists of 16 scaffolds, each having two telomeres. A total of 11,564 protein-coding genes were predicted, including 1,633 genes encoding for secretory proteins and 473 genes for effectors. This telomere-to-telomere genome assembly provides an important resource for comparative genomics and understanding molecular biology of B. sorokiniana and related Bipolaris species.

    Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

    Genome Announcement

    Bipolaris sorokiniana, also known as Cochliobolus sativus, falls within the Pleosporaceae family belonging to the Pleosporales order of the Dothideomycetes class. This fungus causes several important diseases in cereal crops, including common root rot, spot blotch, and kernel blight (Mathre 1997; Wiese 1987). Significant losses in yield and quality to these diseases have been reported on the two major crops, barley and wheat, particularly when susceptible varieties are grown under disease-conducive environmental conditions (Mathre 1997; Roy et al. 2023). Additionally, B. sorokiniana can infect numerous grass species. Among these are switch grass (Panicum virgatum L.), a prospective biomass source for biofuel and bioproduct manufacturing, and Brachypodium distachyon, which has gained prominence as a novel model for functional genomics studies in grasses (Zhong et al. 2015). It is worth noting that the virulence and pathogenicity of B. sorokiniana isolates may be different depending on the host species or even distinct genotypes of the same host species (Valjavec-Gratian and Steffenson 1997a; Zhong and Steffenson 2001a). Four different pathotypes (0, 1, 2, and 7) of the fungus have been identified based on their virulence on three barley genotypes (Bowman, ND 5883, and ND B112) (Gyawali 2010; Leng et al. 2016; Valjavec-Gratian and Steffenson 1997a), although other pathotypes have been reported in different regions of the world (Arabi and Jawhar 2004; Ghazvini and Tekauz 2007; Meldrum et al. 2004). Whole-genome sequencing of B. sorokiniana isolates of different pathotypes is essential for understanding the genetic diversity and molecular mechanisms of host specificity of the fungal pathogen.

    The first genome assembly of B. sorokiniana was reported for the pathotype 2 isolate ND90Pr, which contains 154 scaffolds (Condon et al. 2013; Ohm et al. 2012). With the development of third-generation sequencing technologies, a few more genome assemblies have been published for different B. sorokiniana strains isolated from either barley or wheat hosts (Aggarwal et al. 2022; McDonald et al. 2019; Meng et al. 2020; Zhang et al. 2023) (Supplementary Table S1). However, the previously published genome assemblies are either too fragmented or missing telomere sequences for some chromosomes. A high-quality telomere-to-telomere genome assembly for B. sorokiniana is still needed for use as a reference genome. Here, we report a genome assembly of the B. sorokiniana isolate ND93-1, which includes all 16 chromosomes carrying telomere sequences at both ends. ND93-1 was derived as a single conidial culture from a blighted kernel of barley cultivar Robust (PI 476976) collected in 1993 from Walsh County, North Dakota, U.S.A. (Valjavec-Gratian and Steffenson 1997b). ND93-1 exhibits low virulence on the three barley genotypes Bowman, ND5883, and ND B112, and therefore is classified as a pathotype 0 isolate (Valjavec-Gratian and Steffenson 1997a; Zhong and Steffenson 2001a). Previously, a fungal cross was made between ND93-1 and ND90Pr to study the genetics of virulence on barley (Valjavec-Gratian and Steffenson 1997b), and a genetic map was developed using progenies derived from the cross between ND93-1 and ND90Pr (Zhong et al. 2002). Having whole-genome sequences for both ND93-1 and ND90Pr will facilitate our understanding of the genetic and genome structure differences between the two isolates belonging to different pathotypes.

    To sequence the entire genome of ND93-1, we extracted high molecular weight (HMW) DNA from mycelia of ND93-1 using the Quick-DNA HMW Magbead Kit (Zymo Research, Irvine, CA, U.S.A.) following the manufacturer's manual. To generate PacBio HiFi reads, one library with an average insert size of 13 Kbp was prepared using the SMRTbell Express Template Prep Kit 2.0 and sequenced on a SMRT Cell 8M DNA Sequencing Chip run by the PacBio Sequel IIe platform at Mayo Clinic (Rochester, MN). The resulting PacBio subreads were processed to generate highly accurate single-molecule consensus reads (HiFi Reads) using the program CCS v6.2.0 (https://github.com/PacificBiosciences/ccs). To generate ultra-long reads with the Oxford Nanopore Technology (ONT), the HMW DNA was size-selected to obtain fragments greater than 15 Kbp with a Blue Pippin instrument (Saga Science, Beverly, CA, U.S.A.), and the size-selected DNA was used to prepare a library with the Nanopore Sequencing Kit (ONT, Alameda, CA, U.S.A.) following the manufacturer's protocol, sequenced on a MinION Flow Cell (R9.4.1), and basecalled using the high-accuracy model with Guppy 5.0.7 (ONT). To correct sequence errors from the ONT reads, we also generated paired-end short reads (100 bp) using the Illumina HiSeq sequencing platform in the DNA Sequencing Core Facility at the University of Utah, Salt Lake City, Utah. With the PacBio sequencing technology, a total of 2,647,656 HiFi reads (35.5 Gbp) were generated with lengths ranging from 162 to 47,868 bp, which are equivalent to 970× genome coverage. Assembly of partial PacBio HiFi reads (50× genome coverage) using Hi-Canu 2.0 (Nurk et al. 2020) led to 17 contigs (ctg01-17) for the nuclear genome and one contig for the mitochondrial genome. Of the 17 nuclear contigs, 15 have two telomeres with the repetitive sequence (TAACCC/GGGTTA) at both ends while the remaining two contigs (Ctg12 and Ctg17) have one telomere at one end. From the ONT sequencing, 133,001 reads ranging from 5,000 to 210,807 bp were generated, with a total sequence of 4.16 Gb equivalent to 112× genome coverage. The ONT reads were assembled into 16 contigs (Bctg01-16) for the nuclear genome and one contig for the mitochondrial genome using the assembler NECAT (Chen et al. 2021). The ONT assembly was further corrected and polished with the Illumina paired-end short reads (100 bp) using Pilon v.1.20.1 (Walker et al. 2014). Of the 16 contigs from the ONT assembly, 12 have two telomeres, and the remaining 4 (Bctg01, 02, 07, and 10) have only one telomere. Dot-plot comparison of the two assemblies using D-genies (Cabanettes and Klopp 2018) indicated 15 contigs of the PacBio HiFi assembly matched well with the corresponding 15 contigs of the ONT assembly (Fig. 1). The remaining two contigs (Ctg12 and Ctg17) of the PacBio HiFi assembly aligned to one contig (Bctg04) of the ONT assembly (Fig. 1), suggesting that Ctg12 and Ctg17 belong to the same chromosome. Using Bctg04 as bridge, Ctg12 and Ctg17 were joined into one scaffold with two telomeres. Since the PacBio HiFi assembly had a higher (97.5%) completeness than the ONT assembly (93.1%) according to the evaluations with BUSCO v4.1.2 (against ascomycota_odb10) (Seppey et al. 2019), it was used as the final genome assembly for further statistics and gene annotation.

    FIGURE 1

    FIGURE 1 Dot-plot comparison of the PacBio HiFi assembly and the ONT assembly of ND93-1 genome. There are 16 contigs (Bctg01-16) in the ONT assembly and 17 contigs (ctg01-17) in the PacBio HiFi assembly. Contigs with two telomeres are marked with ** while those with only one telomere are marked with *. The dot-plot was generated by the online version of the D-genies program (Cabanettes and Klopp 2018).

    Download as PowerPoint

    A total of 11,564 putative genes were predicted for the PacBio HiFi assembly of ND93-1 genome using the JGI annotation pipeline (Grigoriev et al. 2014). BLASTn search using previously cloned mating type genes (Zhong and Steffenson 2001b) confirmed that ND93-1 is a mating type 1 isolate with the MAT1-1 idiomorph, different from the one (MAT1-2) in the mating type 2 isolate ND90Pr. We identified 632 putative carbohydrate-active enzymes (CAZymes) among the predicted proteins using the dbCAN2 meta server (Zhang et al. 2018). Using the anti-SMASH fungal version 5.0 (Blin et al. 2019), we identified 40 genes involved in biosynthesis of secondary metabolites. Secretome was analyzed with SignalP version 5.0 (Almagro Armenteros et al. 2019), and 1633 secreted proteins were predicted. Among the secreted proteins predicted, 473 were classified as effector candidates using EffectorP 2.0 with the score greater than 0.8 (Sperschneider et al. 2018) (Table 1). Detailed information on annotations of the Bipolaris sorokiniana ND93-1 v1.0. is available in the JGI annotation and portal (https://mycocosm.jgi.doe.gov/BsorND93_1). This telomere-to-telomere genome assembly resource will contribute to genome comparisons within B. sorokiniana and among members of the Bipolaris genus and facilitate our understanding of the molecular mechanisms underlying pathogenicity and other biological properties of the Bipolaris pathogens.

    TABLE 1 Summary of the genome assembly and annotation statistics of Bipolaris sorokiniana strain ND93-1

    Author-Recommended Internet Resources

    https://mycocosm.jgi.doe.gov/BsorND93_1

    The author(s) declare no conflict of interest.

    Literature Cited

    • Aggarwal, R., Agarwal, S., Sharma, S., Gurjar, M. S., Bashyal, B. M., Rao, A. R., Sahu, S., Jain, P., and Saharan, M. S. 2022. Whole-genome sequence analysis of Bipolaris sorokiniana infecting wheat in India and characterization of ToxA gene in different isolates as pathogenicity determinants. 3 Biotech. 12:151. https://doi.org/10.1007/s13205-022-03213-3
      CrossrefGoogle Scholar
    • Almagro Armenteros, J. J., Tsirigos, K. D., Sønderby, C. K., Petersen, T. N., Winther, O., Brunak, S., von Heijne, G., and Nielsen, H. 2019. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nat. Biotechnol. 37:420-423. https://doi.org/10.1038/s41587-019-0036-z
      CrossrefGoogle Scholar
    • Arabi, M. I. E., and Jawhar, M. 2004. Identification of Cochliobolus sativus (spot blotch) isolates expressing differential virulence on barley genotypes in Syria. J. Phytopathol. 152:461-464. https://doi.org/10.1111/j.1439-0434.2004.00875.x
      CrossrefGoogle Scholar
    • Blin, K., Shaw, S., Steinke, K., Villebro, R., Ziemert, N., Lee, S. Y., Medema, M. H., and Weber, T. 2019. antiSMASH 5.0: Updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res. 47:W81-W87. https://doi.org/10.1093/nar/gkz310
      CrossrefGoogle Scholar
    • Cabanettes, F., and Klopp, C. 2018. D-GENIES: Dot plot large genomes in an interactive, efficient and simple way. PeerJ 6:e4958. https://doi.org/10.7717/peerj.4958
      CrossrefGoogle Scholar
    • Chen, Y., Nie, F., Xie, S.-Q., Zheng, Y.-F., Dai, Q., Bray, T., Wang, Y.-X., Xing, J.-F., Huang, Z.-J., Wang, D.-P., He, L.-J., Luo, F., Wang, J.-X., Liu, Y.-Z., and Xiao, C.-L. 2021. Efficient assembly of nanopore reads via highly accurate and intact error correction. Nat. Commun. 12:60. https://doi.org/10.1038/s41467-020-20236-7
      CrossrefGoogle Scholar
    • Condon, B. J., Leng, Y., Wu, D., Bushley, K. E., Ohm, R. A., Otillar, R., Martin, J., Schackwitz, W., Grimwood, J., MohdZainudin, N., Xue, C., Wang, R., Manning, V. A., Dhillon, B., Tu, Z. J., Steffenson, B. J., Salamov, A., Sun, H., Lowry, S., LaButti, K., Han, J., Copeland, A., Lindquist, E., Barry, K., Schmutz, J., Baker, S. E., Ciuffetti, L. M., Grigoriev, I. V., Zhong, S., and Turgeon, B. G. 2013. Comparative genome structure, secondary metabolite, and effector coding capacity across Cochliobolus pathogens. PLos Genet. 9:e1003233. https://doi.org/10.1371/journal.pgen.1003233
      CrossrefGoogle Scholar
    • Ghazvini, H., and Tekauz, A. 2007. Virulence diversity in the population of Bipolaris sorokiniana. Plant Dis. 91:814-821. https://doi.org/10.1094/PDIS-91-7-0814
      LinkGoogle Scholar
    • Grigoriev, I. V., Nikitin, R., Haridas, S., Kuo, A., Ohm, R., Otillar, R., Riley, R., Salamov, A., Zhao, X., Korzeniewski, F., Smirnova, T., Nordberg, H., Dubchak, I., and Shabalov, I. 2014. MycoCosm portal: Gearing up for 1000 fungal genomes. Nucleic Acids Res. 42:D699-D704. https://doi.org/10.1093/nar/gkt1183
      CrossrefGoogle Scholar
    • Gyawali, S. 2010. Association mapping of resistance to common root rot and spot blotch in barley, and population genetics of Cochliobolus sativus. Ph.D. Dissertation. North Dakota State University, Fargo, ND.
      Google Scholar
    • Leng, Y., Wang, R., Ali, S., Zhao, M., and Zhong, S. 2016. Sources and genetics of spot blotch resistance to a new pathotype of Cochliobolus sativus in the USDA national small grains collection. Plant Dis. 100:1988-1993. https://doi.org/10.1094/PDIS-02-16-0152-RE
      LinkGoogle Scholar
    • Mathre, D. E. 1997. Compendium of Barley Diseases. 2nd ed. American Phytopathological Society, St. Paul, MN.
      Google Scholar
    • McDonald, M. C., Taranto, A. P., Hill, E., Schwessinger, B., Liu, Z., Steven, S., Milgate, A., and Solomon, P. S. 2019. Transposon-mediated horizontal transfer of the host-specific virulence protein ToxA between three fungal wheat pathogens. mBio. 10:e01515-19. https://doi.org/10.1128/mBio.01515-19
      CrossrefGoogle Scholar
    • Meldrum, S. I., Platz, D. G. J., and Ogle, H. J. 2004. Pathotypes of Cochliobolus sativus on barley in Australia. Aust. Plant Pathol. 33:109-114. https://doi.org/10.1071/AP03088
      CrossrefGoogle Scholar
    • Meng, Y., Wang, J., Bai, B., Wang, L., Yao, L., Ma, Z., Si, E., Li, B., Ma, X., Shang, X., and Wang, H. 2020. Genome sequence resource for pathogen Bipolaris sorokiniana shoemaker GN1 causing spot blotch of barley (Hordeum vulgare L.). Plant Dis. 104:1574-1577. https://doi.org/10.1094/PDIS-12-19-2582-A
      LinkGoogle Scholar
    • Nurk, S., Walenz, B. P., Rhie, A., Vollger, M. R., Logsdon, G. A., Grothe, R., Miga, K. H., Eichler, E. E., Phillippy, A. M., and Koren, S. 2020. HiCanu: Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads. Genome Res. 30:1291-1305. https://doi.org/10.1101/gr.263566.120
      CrossrefGoogle Scholar
    • Ohm, R. A., Feau, N., Henrissat, B., Schoch, C. L., Horwitz, B. A., Barry, K. W., Condon, B. J., Copeland, A. C., Dhillon, B., Glaser, F., Hesse, C. N., Kosti, I., LaButti, K., Lindquist, E. A., Lucas, S., Salamov, A. A., Bradshaw, R. E., Ciuffetti, L., Hamelin, R. C., Kema, G. H. J., Lawrence, C., Scott, J. A., Spatafora, J. W., Turgeon, B. G., de Wit, P. J. G. M., Zhong, S., Goodwin, S. B., and Grigoriev, I. V. 2012. Diverse lifestyles and strategies of plant pathogenesis encoded in the genomes of eighteen Dothideomycetes fungi. PLoS Pathog. 8:e1003037. https://doi.org/10.1371/journal.ppat.1003037
      CrossrefGoogle Scholar
    • Roy, C., He, X., Gahtyari, N. C., Mahapatra, S., and Singh, P. K. 2023. Managing spot blotch disease in wheat: Conventional to molecular aspects. Front. Plant Sci. 14:1098648. https://doi.org/10.3389/fpls.2023.1098648
      CrossrefGoogle Scholar
    • Seppey, M., Manni, M., and Zdobnov, E. M. 2019. BUSCO: Assessing genome assembly and annotation completeness. Methods Mol Biol. 1962:227-245. https://doi.org/10.1007/978-1-4939-9173-0_14
      CrossrefGoogle Scholar
    • Sperschneider, J., Dodds, P. N., Gardiner, D. M., Singh, K. B., and Taylor, J. M. 2018. Improved prediction of fungal effector proteins from secretomes with EffectorP 2.0. Mol. Plant Pathol. 19:2094-2110. https://doi.org/10.1111/mpp.12682
      CrossrefGoogle Scholar
    • Valjavec-Gratian, M., and Steffenson, B. J. 1997a. Pathotypes of Cochliobolus sativus on barley in North Dakota. Plant Dis. 81:1275-1278. https://doi.org/10.1094/PDIS.1997.81.11.1275
      LinkGoogle Scholar
    • Valjavec-Gratian, M., and Steffenson, B. J. 1997b. Genetics of virulence in Cochliobolus sativus and resistance in barley. Phytopathology 87:1140-1143. https://doi.org/10.1094/PHYTO.1997.87.11.1140
      LinkGoogle Scholar
    • Walker, B. J., Abeel, T., Shea, T., Priest, M., Abouelliel, A., Sakthikumar, S., Cuomo, C. A., Zeng, Q., Wortman, J., Young, S. K., and Earl, A. M. 2014. Pilon: An integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 9:e112963. https://doi.org/10.1371/journal.pone.0112963
      CrossrefGoogle Scholar
    • Wiese, M. V. 1987. Compendium of Wheat Diseases. American Phytopathological Society, St. Paul, MN.
      Google Scholar
    • Zhang, H., Yohe, T., Huang, L., Entwistle, S., Wu, P., Yang, Z., Busk, P. K., Xu, Y., and Yin, Y. 2018. dbCAN2: A meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 46:W95-W101. https://doi.org/10.1093/nar/gky418
      CrossrefGoogle Scholar
    • Zhang, W., Yang, Q., Yang, L., Li, H., Zhou, W., Meng, J., Hu, Y., Wang, L., Kang, R., Li, H., Ding, S., and Li, G. 2023. High-quality nuclear genome and mitogenome of Bipolaris sorokiniana LK93, a devastating pathogen causing wheat root rot. Mol. Plant Microbe Interact. 36:452-456. https://doi.org/10.1094/MPMI-09-22-0196-A
      LinkGoogle Scholar
    • Zhong, S., Ali, S., Leng, Y., Wang, R., and Garvin, D. F. 2015. Brachypodium distachyon-Cochliobolus sativus pathosystem is a new model for studying plant-fungal interactions in cereal crops. Phytopathology 105:482-489. https://doi.org/10.1094/PHYTO-08-14-0214-R
      LinkGoogle Scholar
    • Zhong, S., and Steffenson, B. J. 2001a. Virulence and molecular diversity in Cochliobolus sativus. Phytopathology 91:469-476. https://doi.org/10.1094/PHYTO.2001.91.5.469
      LinkGoogle Scholar
    • Zhong, S., and Steffenson, B. J. 2001b. Genetic and molecular characterization of mating type genes in Cochliobolus sativus. Mycologia 93:852-863. https://doi.org/10.1080/00275514.2001.12063220
      CrossrefGoogle Scholar
    • Zhong, S., Steffenson, B. J., Martinez, J. P., and Ciuffetti, L. M. 2002. A molecular genetic map and electrophoretic karyotype of the plant pathogenic fungus Cochliobolus sativus. Mol. Plant-Microbe Interact. 15:481-492. https://doi.org/10.1094/MPMI.2002.15.5.481
      LinkGoogle Scholar

    Data availability: The genome sequences have been deposited into NCBI GenBank database with the BioProject accession number PRJNA972308. The SRA accession numbers are SRR24560529, SRR24601489, and SRR24601488. The WGS accession number is JASPLA000000000. The version described in this paper is version JASPLA010000000.

    Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

    Funding: Funding was provided by the Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy (contract DE-AC02-05CH11231), and the Division of Biological Infrastructure (2019077). Additionally, this work was supported in part by the U.S. Department of Agriculture, Agricultural Research Service (project 3060-21000-046-000D). This work used resources of the Center for Computationally Assisted Science and Technology at North Dakota State University, Fargo, ND, U.S.A., which were made possible in part by the National Science Foundation (MRI Award 2019077).

    The author(s) declare no conflict of interest.