Draft genome sequence of Fusicladium effusum, cause of pecan scab
© The Author(s). 2016
Received: 19 November 2015
Accepted: 24 May 2016
Published: 3 June 2016
Pecan scab, caused by the plant pathogenic fungus Fusicladium effusum, is the most destructive disease of pecan, an important specialty crop cultivated in several regions of the world. Only a few members of the family Venturiaceae (in which the pathogen resides) have been reported sequenced. We report the first draft genome sequence (40.6 Mb) of an isolate F. effusum collected from a pecan tree (cv. Desirable) in central Georgia, in the US. The genome sequence described will be a useful resource for research of the biology and ecology of the pathogen, coevolution with the pecan host, characterization of genes of interest, and development of markers for studies of genetic diversity, genotyping and phylogenetic analysis. The annotation of the genome is described and a phylogenetic analysis is presented.
KeywordsFusicladium effusum Venturiacae Fungal pathogen Fungicide resistance Genetic diversity Pecan Pecan scab
Although pecan is native to the US, it is grown commercially elsewhere and the pathogen now occurs not only in the US, but in South America, and South Africa as well . F. effusum reproduces asexually through production of conidia , it is pathogenically diverse [9–12], affecting many different cultivars, and has a history of adapting to novel sources of host resistance . Preliminary molecular studies suggested it is a genetically diverse organism [13, 14], yet no sexual stage has been identified for this fungus. But as the genetic basis of resistance and virulence has not been characterized, progress in breeding resistance is severely hampered. Furthermore, F. effusum has developed insensitivity to several classes of fungicide that are used to manage the pathogen .
Some related members of the Class Dothidiomycetes, and the family Venturiacae, in which F. effusum resides, have been sequenced [16–21], including Venturia inaequalis (cause of apple scab) and V. pirina (cause of pear scab). These organisms can have impact on plant health, and in some cases animal and human health. These fungal genome sequences provide an opportunity to apply novel genomic and biotechnological tools to develop new solutions to the issues resulting from the interaction of these organisms with their hosts.
With respect to pecan scab, a more thorough understanding of the pathogen and its genetics are needed to develop durable resistance in the pecan host. Sequencing the genome of F. effusum will provide a valuable resource to use for identifying various genes of interest, such as those involved in fungicide resistance, those involved in host recognition, mating-type genes, and identification of microsatellites to study genetic diversity (or as markers for other purposes). We describe the first draft genome sequence of F. effusum , the characteristics of annotation, and provide a phylogenetic analysis of the taxonomy of the pathogen. The genome sequence will provide an opportunity for new research to gain insight into fundamental aspects of this economically important disease of pecan.
Classification and features
Classification and general features of Fusicladium effusum designation 
Species Fusicladium effusum
Mycelium with septae
Conidia on conidiophores
Mesophilic (10–35 °C)
pH range; Optimum
Byron, Georgia, USA
83.739 ° W
Genome sequencing information
Genome project history
High quality draft
454: paired end sequences with 450b insert; Illumina: 1 kb paired-end library
Illumina Genome Analyzer IIx/454 GS-FLX Titanium
ABySS V1.2.6/Newbler V2.3/Phrap/Paracel Transcript Assembler V3.0.0
Gene calling method
(Also BLAST search (NCBI tblastx) against the NCBI NR (non-redundant) database and the genome sequences of Phaeosphaeria nodorum, Pyrenophora teres, and Saccharomyces cerevisiae)
Locus Tags not reported
Genbank date of release
Not established in GOLD
Source material identifier
Growth conditions and genomic DNA preparation
The isolate of F. effusum was cultured on antibiotic-amended potato dextrose agar (amended as for WA, described above) and incubated for 3 weeks at 25 °C (12 h light/12 h dark), at which time the DNA was extracted from the sample using a ZymoResearch DNA extraction kit (ZymoResearch, Irvine, CA), following a slightly modified protocol for DNA extraction from fungi . A Fastprep FP120 (Savant Instruments, Holbrook, NY) was used to lyse the mycelium. Once obtained, the DNA was quantified using a Nanodrop spectrophotometer (Nanodrop Products, Wilmington, DE) and stored in TE buffer at −20 °C.
Genome sequencing and assembly
The genome was sequenced using 454 GS-FLX Titanium and Illumina Genome Analyzer IIx sequencing platforms. Two stages of assembly were performed to ensure the accuracy and quality of the contigs. The 454 reads were cleaned by masking repeats and removing primers and/or adaptors used in library preparation. The Illumina reads were cleaned using ‘cross_match’ in Phrap  and the cleanup module in PTA V3.0.0  to remove low-quality (<20 phred-like score) and short (<40 bp) reads. These cleaned Illumina reads were assembled with multiple trials (a series of k-mers from 30 bp to 75 bp) using ABySS V1.2.6 . The assembled contigs with ≥2,000 bp from ABySS were computationally chopped into 800-bp fragments (with 200 bp overlapping between two adjacent fragments) and further assembled with the cleaned 454 reads using Newbler V2.3 (454 Life Science), to generate the final contigs and scaffolds. A total of 11,959 contigs and 545 scaffolds (average size = 74.4 Kb; total size = 40.6 Mb) were assembled from over 69.2 million clean reads (7.1 Gb). The largest scaffold was >1.1 Mb. There were 3,113 large contigs (≥500 bp), totaling >40.1 Mb which is typical for a genome in the Ascomycota (36.9 Mb, ), and not dissimilar to that reported for V. pirina  and V. inaequalis . The 170× genome coverage indicated that ≥95 % of the genome (42.6 Mb) was covered, based on a comparison of reads from high-quality genome sequences .
Ab initio gene prediction with the FGENESB package (Softberry Inc.) predicted 50,192 ORFs from the 3,113 large contigs, including 18,501 RNA ORFs (36.9 %), which was substantially higher than might be expected for this type of organism. For example, only 6,299 peptides were predicted in the genome of V. pirina , and 13,233 genes in that of V. inaequalis . The draft genome sequence of F. effusum was somewhat fragmented and an elevated count of small contigs (a total of 11,959) likely led to prediction of multiple ORFs from some genes that were divided among different contigs. Thus the gene count prediction of this draft genome is tentative. To obtain a more accurate perspective on the functional genes [35, 36], we further annotated the ORFs through BLAST at 1e-4 to three genomes, ( Phaeosphaeria nodorum, Pyrenophora teres , and Saccharomyces cerevisiae ), in which only 13,897 ORFs were identified. We also used BLAST against three generic genomic databases (NCBI nr, COG and KEGG), in which there was a total of 18,139 hits. At this less stringent e-value, both numbers are only slightly higher than might be expected in a fungal genome; therefore we conclude that the ORFs identified are likely representative of the functional genes in F. effusum .
Nucleotide and gene count levels of the genome
% of totala
Genome size (Mbp)
DNA coding (bp)
DNA G + C content (bp)
Protein coding genes
Genes in internal clusters
Genes with function prediction
Genes assigned to COGs
Genes with Pfam domains
Genes with signal peptides
Genes with transmembrane helices
Number of genes associated with general COG functional categories
Translation, ribosomal structure and biogenesis
RNA processing and modification
Replication, recombination and repair
Chromatin structure and dynamics; K Transcription
Cell cycle control, cell division, chromosome partitioning
Signal transduction mechanisms
Cell wall/membrane/envelope biogenesis
Cell motility; T Signal transduction mechanisms
Intracellular trafficking, secretion, and vesicular transport
Posttranslational modification, protein turnover, chaperones
Energy production and conversion
Carbohydrate transport and metabolism
Amino acid transport and metabolism
Nucleotide transport and metabolism
Coenzyme transport and metabolism
Lipid transport and metabolism
Inorganic ion transport and metabolism
Secondary metabolites biosynthesis, transport and catabolism;
General function prediction only
Not in COGS
Insights from the genome sequence
The genome provides a useful resource for identifying genes of interest in F. effusum . Several genes of interest were annotated, including many from the family of P450 genes (of specific interest are the full-length CYP51A (contig 00394) and CYP51B (contig 00058) genes, which are identified in the genome and may be involved in resistance to the dimethyl inhibitors (DMIs) fungicides). Evidence of the mating type gene was also found (putatively MAT-2, Contig 00032), which will be useful as F. effusum is currently known only by its asexual stage (conidia), so mating type gene identification can pave the way to establishing existence of a sexual stage. An analysis has also demonstrated that the genome is a rich resource to obtain microsatellite markers with different motif characteristics for studies of pathogen diversity, and to develop as markers for other genetic studies. Furthermore, the phylogenetic analysis presented confirms the close relationship of F. effusum to other members of the Venturiacae and previous observations on the taxonomic relationships among these members of the Ascomycota.
The annotated ORFs may represent partial or full lengths of most functional genes in the F. effusum genome and can be used as a new resource for developing molecular markers for genetic diversity studies, and for other research in biology, ecology and phylogenetics, and for research into host/pathogen coevolution.
The research was supported through USDA-ARS project no. 6042-21220-012-00. The authors thank Dr. Mike Hotchkiss for help with sample collection, and Minling Zhang for technical support (USDA-ARS, Byron, GA).
This article reports the results of research only. Mention of a trademark or proprietary product is solely for the purpose of providing specific information and does not constitute a guarantee or warranty of the product by the US Department of Agriculture and does not imply its approval to the exclusion of other products that may also be suitable.
CB collected the isolate and extracted the DNA. CC performed the phylogenetic analysis and some of the other bioinformatics. CB, CC, FY, KS and BW worked on the sequencing, data analysis and drafted the manuscript. All authors read and approved the final version of the manuscript.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Gottwald TR, Bertrand PF. Effects of an abbreviated pecan disease control program on pecan scab disease increase and crop yield. Plant Dis. 1988;72:27–32.View ArticleGoogle Scholar
- Goff WD, McVay JR, Gazaway WS. Pecan production in the Southeast, Alabama cooperative extension system circular ANR-459. Auburn: University Auburn; 1996. p. 222.Google Scholar
- Stevenson KL, Bertrand PF. Within-season dynamics of yield loss due to pecan scab fruit infections. Phys Chem Chem Phys. 2002;91:S85.Google Scholar
- Bock CH. Fusicladium effusum. Wallingford: Crop Protection Compendium Datasheet, Commonwealth Agriculture Bureau International; 2013. http://www.cabi.org/isc/datasheet/13719. Accessed 26 May 2016.Google Scholar
- Demaree JB. Pecan scab with special reference to sources of the early spring infections. J Agr Res. 1924;28:321–9.Google Scholar
- Gottwald TR, Bertrand PF. Patterns of diurnal and seasonal airborne spore concentrations of Fusicladium effusum and its impact on a pecan scab epidemic. Phys Chem Chem Phys. 1982;72:330–5.Google Scholar
- Gottwald TR. Influence of temperature, leaf wetness period, leaf age, and spore concentration on infection of pecan leaves by conidia of Cladosporium caryigenum. Phys Chem Chem Phys. 1985;75(2):190–4.Google Scholar
- Gottwald TR, Bertrand PF. Effect of time of inoculation with Cladosporium caryigenum on pecan scab development and nut quality. Phys Chem Chem Phys. 1983;73(5):714–8.Google Scholar
- Demaree JB, Cole JR. Behavior of Cladosporium effusum (Wint.)Demaree on some varieties of pecan. J Agr Res. 1929;38:363–70.Google Scholar
- Converse RH. Physiologic specialization in Fusicladium effusum and its evaluation in vitro. Phys Chem Chem Phys. 1960;50:527–31.Google Scholar
- Graves CH. Breeding for pecan scab resistance. Proc Southeast Pecan Growers Assoc. 1975;61:168–71.Google Scholar
- Conner PJ, Stevenson KL. Pathogenic variation of Cladosporium caryigenum isolates and corresponding differential resistance in pecan. HortSci. 2004;39:553–7.Google Scholar
- Bock CH, Endalew TT, Biswas BK, Yadav AK, Sitther V, Hotchkiss MW, Stevenson KL, Wood BW. A comparison of UP-PCR and RAPD markers to study genetic diversity of the pecan scab fungus (Fusicladium effusum G. Winter). Forest Path. 2014;44:266–75.View ArticleGoogle Scholar
- Bock CH, Stevenson KL, Arias RS, Wood BW. Genetic diversity and population structure of Fusicladium effusum on pecan in the U.S.A. Plant Dis. 2014;98:916–23.View ArticleGoogle Scholar
- Seyran M, Brenneman TB, Stevenson KL. A rapid method to monitor fungicide sensitivity in the pecan scab pathogen, Fusicladium effusum. Crop Prot. 2010;29(11):1257–63.View ArticleGoogle Scholar
- Jones D. 2014. Venturia pyrina ICMP 11032 genome sequencing. NCBI-GenBank, Bioproject, accession no. PRJNA232087. http://www.ncbi.nlm.nih.gov/bioproject/?term=Venturia+pyrina. Accessed 26 May 2016.
- Deng C. 2014. Venturia inaequalis genome sequencing. NCBI-GenBank, Bioproject 261633, accession no. PRJNA261633. http://www.ncbi.nlm.nih.gov/bioproject/261633. Accessed 26 May 2016.
- Kroll D. 2014. Resequencing of ST99CH3D7. Bioproject, Accession number: PRJNA290690. http://www.ncbi.nlm.nih.gov/bioproject?LinkName=biosample_bioproject&from_uid=1882120. Accessed 26 May 2016.
- Studholme D. 2015. Microbe sample from Zymoseptoria tritici IPO323. Bioproject, accession no. PRJNA296417. http://www.ncbi.nlm.nih.gov/bioproject/296417. Accessed 26 May 2016.
- Ng KP, Yew SM, Chan CL, Soo-Hoo TS, Na SL, Hassan H, Ngeow YF, Hoh C-C, Lee, K-W, Yee, W-Y. Sequencing of Cladosporium sphaerospermum, a Dematiaceous Fungus Isolated from Blood Culture. Eukaryot Cell. 2012;11(5):705–6.View ArticlePubMedPubMed CentralGoogle Scholar
- Nierman WC, Yu J, Federova-Abrams ND, Losada L, Cleveland TE, Bhatnaga JW, Bennett JW, Payne GA. Genome sequence of Aspergillus flavus NRRL 3357, a strain that causes aflatoxin contamination of food and feed. Genome Ann. 2015. doi:https://doi.org/10.1128/genomeA.00168-15.Google Scholar
- Barnes GL. Growth response of the pecan scab fungus, Fusicaldium effusum, on various common and exotic agar media. Oklahoma Agricultural Experiment Station Technical Bulletin, T-110. 1964.Google Scholar
- Seyran M, Nischwitz C, Lewis KJ, Gitaitis RD, Brenneman TB, Stevenson KL. Phylogeny of the pecan scab fungus Fusicladium effusum G. Winter based on the cytochrome b gene sequence. Mycol Prog. 2010;9(2):305–8.View ArticleGoogle Scholar
- Schubert K, Ritschel A, Braun U. A monograph of Fusicladium s.lat. (hyphomycetes). Schlechtendalia. 2003;9:1–132.Google Scholar
- Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al. Clustal W and clustal X version 2.0. Bioinformatics. 2007;23(21):2947–8.View ArticlePubMedGoogle Scholar
- Page RDM. TreeView: An application to display phylogenetic trees on personal computers. Computer Applic Biosci. 1996;12(4):357–8.Google Scholar
- Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ, Angiuoli SV, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008;26(5):541–7.View ArticlePubMedPubMed CentralGoogle Scholar
- Gordon D, Desmarais C, Green P. Automated finishing with autofinish. Genome Res. 2001;11(4):614–25. doi:https://doi.org/10.1101/gr.171401.View ArticlePubMedPubMed CentralGoogle Scholar
- Boysen C, Pao SS, Qian J, Smith CP, Zhu L, Borkowski A. Paracel Transcript Assembler: Identification of splice variants for gene discovery and gene expression profiling. Transcriptome 2002: From functional genomics to systems biology. March 10–13, 2002, Seattle, Washington, USA. P05. http://web.ornl.gov/sci/techresources/meetings/transcriptome2002/p05.shtml. Accessed 26 May 2016.
- Birol I, Jackman SD, Nielsen CB, Qian JQ, Varhol R, Stazyk G, Morin RD, Zhao Y, Hirst M, Schein JE, Horsman DE, Connors JM, Gascoyne RD, Marra MA, Jones SJ. De novo transcriptome assembly with ABySS. Bioinf. 2009;25(21):2872–7. doi:https://doi.org/10.1093/bioinformatics/btp367.View ArticleGoogle Scholar
- Mohanta TK, Bae H. The diversity of fungal genome. Biol Proceed Online. 2015;17:8. doi:https://doi.org/10.1186/s12575-015-0020-z.View ArticleGoogle Scholar
- Deng C, Bowen J, Plummer K. Venturia inaequalis (information tab), JGI mycocosm – the fungal genomics resource. 2016. http://genome.jgi.doe.gov/Venin1/Venin1.info.html. Accessed 26 May 2016.Google Scholar
- Chu TC, Lu CH, Liu TL, Lee GC, Li WH, Shih ACC. Assembler for de novo assembly of large genomes. Proc Natl Acad Sci U S A. 2013;110(36):E3417–24. doi:https://doi.org/10.1073/pnas.1314090110.View ArticlePubMedPubMed CentralGoogle Scholar
- Cooke IR, Jones D, Bowen JK, Deng C, Faou P, Hall NE, Jayachandran V, Liem M, Taranto AP, Plummer KM. Proteogenomic analysis of the Venturia pirina (pear scab fungus) secretome reveals potential effectors. J Prot Res. 2014;13:3635–44.View ArticleGoogle Scholar
- Mavromatis K, Ivanova N, Barry K, Shapiro H, Goltsman E, McHardy AC, AC Rigoutsos I, Salamov A, Korzeniewski F, Land M, Lapidus A, Grigoriev I, Richardson P, Hugenholtz P, Kyrpides NC. Use of simulated data sets to evaluate the fidelity of metagenomic processing methods. Nature Meth. 2007;4(6):495–500. doi:https://doi.org/10.1038/nmeth1043.View ArticleGoogle Scholar
- Zhu W, Lomsadze A, Borodovsky M. Ab initio gene identification in metagenomic sequences. Nucl Acids Res. 2010;38(12), e132. doi:https://doi.org/10.1093/nar/gkq275.View ArticlePubMedPubMed CentralGoogle Scholar
- Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene Ontology: tool for the unification of biology. Nat Genet. 2000;25(1):25–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28:2731–9.View ArticlePubMedPubMed CentralGoogle Scholar