* To whom correspondence should be addressed.
DECIPHERING THE PAN-GENOME OF Ganoderma sp. TO DEPICT POTENTIAL GENOMIC COMPONENTS THAT CONTRIBUTE
TO Ganoderma boninense PATHOGENICITY
SUHAILA SULAIMAN*, NUR SYAMIMI YUSOFF, TAN JOON SHEONG and LEE YANG PING
FGV Research & Development Sdn. Bhd.,
FGV Innovation Centre (Biotechnology), PT. 23417, Lengkuk Teknologi, 71760, Bandar Enstek, Negeri Sembilan
*E-mail: [email protected]
Accepted 19 October 2018, Published online 30 November 2018
ABSTRACT
The soil-borne fungus, Ganoderma boninense is notorious as the cause of basal stem rot (BSR) disease in oil palm that results in severe economic losses. Due to insufficient functional information of its genome, mechanism underlying the infection is still enigmatic. Despite the constraint, here we report the pan-genome of eight draft genomes of Ganoderma sp. that delineated into 35,121 orthologous genes (OGs), consisting 4,898 genes in core genome and 30,223 genes in accessory genome, whilst the latter encompasses of 1,905 species-specific genes. Further genome-wide comparative analysis discovers 607 genes in pathogenic fungi G. boninense but not in its related non-pathogenic Ganoderma sp., suggesting their potential role in G. boninense pathogenicity towards its host. By implementing various bioinformatics tools and public databases, the incorporated functional enrichment of the candidate genes leads to inference of their role during host-pathogen interaction.
This enables us to narrow down the entire gene catalogue in Ganoderma sp. for experimental verification in the laboratory. It is undeniable that the harnessing of Ganoderma sp. pan-genome data will conform to a more structured downstream analysis in understanding the role of G. boninense as the key agent of BSR in oil palm.
Key words: Pan-genome, Ganoderma boninense, pathogenicity, basal stem rot
INTRODUCTION
Basal stem rot (BSR) disease is well-known as the major contributor to severe economic losses in oil palm (Elaeis guineensis Jacq.) industry. This disease is caused by the soil-borne fungus, Ganoderma boninense, a lignicolous basidiomycete with limited information of its genetic diversity and evolutionary history (Kheng et al., 2015). To date, only two versions of G. boninense genome data were publicly available in the National Center for Biotechnology Information (NCBI) database, in which until this report is written, only the first reported draft genome work was published (Mercière et al., 2015). Due to its preference of outcrossing of the isolates over multiple generations, it is expected that the genome of G. boninense shows a high degree of heterogeneity and diversity (Keypour et al., 2014; Miller et al., 1999). Therefore, the
anticipated big genome size of G. boninense as what has been reported as 63 Mbp (Mercière et al., 2015) and 79 Mbp (Utomo et al., 2018) in both accessible versions become a challenge in assembly process, which limits the assembly process up to the contig level.
Yet, it is not the best way to rely solely on one draft genome of G. boninense because it would not represent the fungus as a whole, due to its genetic diversity that it may have. However, this data limitation can now be addressed by the emerging technology in computational capacity that enables extensive computational studies to be done. As such, instead of using typical comparative analysis at the gene level, here we describe the implemen- tation of pan-genome data as an overall comparative to unveil the candidate genes of interest in G.
boninense. Pan-genome refers to the entire genes that consist in an organism of a particular lineage, which further classified into core genome and variable genome (Tettelin et al., 2005). Thus, the use of pan-genome data will be more representative
for comparative analysis, in order to understand the involvement of this fungus on oil palm infections.
As of April 2018, there are seven available Ganoderma sp. in the public databases, consisting of two G. boninense, four G. lucidum and one G.
sinense. These draft genomes were used in this study, in addition to one in-house draft genome to be reported here. Of the three species that we have, only G. boninense was reported as pathogenic to plants (Chen et al., 2017; Pilotti, 2005; Turner, 1981). In contrast, G. lucidum and G. sinense is widely used in medical field to treat cancer (Jiang et al., 2017;
Jin et al., 2016; Yue et al., 2013). On top of discussing Ganoderma sp. pan-genome, here we address the comparative analyses of both pathogenic and non-pathogenic fungi to unravel the pathogen-specific genes which may lead to the fundamental aspect in understanding the molecular biology of G. boninense. Besides, there is a paper reported on the transcriptome data of G. boninense in three different stages: monokaryon, mating junction and dikaryon (Isaac et al., 2018).
MATERIALS AND METHODS Source of data
The draft genomes of Ganoderma sp. used in this study is shown in Table 1. Raw data of the genome reads in this study is currently under the submission process (submission number SUB3781903) to the GenBank database.
Genome annotation
Genes prediction was performed using CodingQuarry (Testa et al., 2015) guided by the submitted transcript sequences. Genome completeness was assessed using Benchmarking
Universal Single-Copy Orthologs (BUSCO) tool (Simão et al., 2015) with BUSCO lineage data of Basidiomycota_odb9 fungi dataset as the main source. Similarity search was done using BLASTP program (Altschul et al., 1990) against non- redundant database in NCBI with permissive E- value at most 1e-5. The resulted search was fed into Blast2GO for functional assignment (Conesa and Götz 2008) which was incorporated with InterProScan domain search (Mitchell et al., 2015).
Family classification was assigned based on Gene Ontology (The Gene Ontology Consortium, 2000) and KEGG database (Kanehisa et al., 2017).
Pan-genome construction
Orthologous groups assignment for all predicted genes in Ganoderma sp. was performed using OrthoMCL based on reciprocal best similarity pairs (Li et al., 2003). The profile of Ganoderma sp. pan- genome data was processed using PanGP (Zhao et al., 2014) for pan-genome plot development and visualization. Extraction of core and accessory genome was performed using UNIX/LINUX command line for fast retrieval.
Computational analysis of pathogenesis-related secreted protein candidates
Orthologous genes in both pathogenic and non- pathogenic strains were compared to identify pathogenic-specific genes in Ganoderma sp.
Classical secretory proteins were predicted via SignalP 4.1 server (Nielsen, 2017), while TargetP 1.1 (Emanuelsson et al., 2007) was used to infer subcellular location of the proteins. The presence of transmembrane helices was detected using TMHMM v2.0 (Krogh et al., 2001). The selected protein sequences were aligned using ClustalX software (Larkin et al., 2007).
Table 1. Ganoderma sp. used in this study. Ganoderma lucidium (SS1) has no GenBank assembly accession because it is deposited under Joint Genome Institute (JGI) database
GenBank assembly No. of Size Assembly
Organism Strain accession Scaffolds/ (Mb) level Source
Contigs*
G. boninense G3 GCA_002900995.1 495 79.24 Contig Utomo et al., 2018
G. boninense NJ3 GCA_001855635.1 18,903 60.33 Contig Mercière et al., 2015 G. boninense FGV-M In submission 2,040 66.57 Contig This project G. sinense ZZ0214-1 GCA_002760635.1 69 48.96 Scaffold Zhu et al., 2015 G. lucidum Xiangnong 1 GCA_000262775.1 634 39.95 Scaffold Liu et al., 2012 G. lucidum G.260125-1 GCA_000271565.1 82 43.29 Scaffold Chen et al., 2012 G. lucidum BCRC 37177 GCA_000338035.1 3,275 44.08 Contig Huang et al., 2013
G. lucidum SS1 Gansp1* 156 39.52 Scaffold Binder et al., 2013
* Refer to JGI database entry (https://genome.jgi.doe.gov/portal/Gansp1/Gansp1.download.html).
RESULTS AND DISCUSSION
Comparison of G. boninense draft genomes Despite data limitation, we successfully obtain another draft genome assembly for G. boninense which was formerly sequenced using hybrid technology of 454 pyrosequencing and Illumina, resulting into 2,040 contigs. At the time this study is reported, this is the third genome assembly that is publicly available (data in submission process).
Although the quality of assembly was restricted by the sequencing coverage, it is worth to consider a draft genome in this limited area to take into account all available data and avoid loss of information (Table 2). We believe that the more upcoming genome data in future will be very helpful in this post-genomic era.
BUSCO analysis revealed that SS1 has the highest degree of completeness with 1,298 (97.2%) complete BUSCOs, 30 (2.2%) fragmented BUSCOs and 7 (0.5%) missing BUSCOs. While FGV-M exhibited the lowest completeness of which 787 (59.0%) complete BUSCOs, 238 (17.8%) fragmented BUSCOs and 310 (23.2%) missing BUSCOs. In general, BUSCO is capable to display different levels of genome completeness between all Ganoderma sp., with SS1 being the most complete followed by Gsinense, BCRC37177, G.260125-1, Xiangnong 1, G3, NJ3 and FGV-M. It is expected to have a lower completeness level in G. boninense as the assemblies were done until contigs level, as opposed to scaffold level in other species.
The number of genes encoded in Ganoderma sp.
varied from 12,276 to 27,777, with SS1 and G3 strains being the highest and the lowest respectively (Figure 1). The average length of encoded proteins in different strains of Ganoderma lies between 233 to 400 residues. We observed lower protein length in G. boninense strains (less than 300 residues in average) compared to other Ganoderma sp. strains.
This could be caused by incomplete draft genome in G. boninense, which might affect the gene prediction. Thus, precaution should be taken
throughout this study as the predicted genes might be truncated or splicing events of the genes could be occurred.
Ganoderma sp. pan-genome
Pan-genome or ‘supra-genome’ refers to the entire complement of genes in a lineage of organisms (Tettelin et al., 2005). The eight strains of Ganoderma sp. accumulate into a total of 128,598 predicted genes, with average length of 345 residues of encoded proteins (Figure 1). These make up into 35,121 orthologous groups (OGs), encompassing 4,898 (13.95%) genes in core genome and 30,223 (86.05%) genes in accessory genome (Figure 2). Core genome describes the genes that belong to all Ganoderma sp. strains, which perform as housekeeping functions such as regulatory functions, cell envelope and transport (Tettelin et al., 2005). In contrast, accessory genome (also known as dispensable or variable genome) represents genes that present in some of the studied strains and normally play a role in strain adaptation and evolution (Laing et al., 2010). In this study, a gene is considered as a part of the accessory genome if it is present in at least one strain or at most in seven strains of the Ganoderma sp.
The Ganoderma sp. accessory genome also consists of 1,905 species-specific genes (Figure 3), which is unique for a particular strain. These genes might contribute to different functions in the fungi, possibly caused by evolution to maintain its survivability and adaptation to the environment (Keeling & Palmer, 2008). The number of unique genes in every strain does not reflect its genome size. The largest draft genome of G. boninense G3 has only about half of the number of unique genes in NJ3. Small draft genomes that have about similar genome size could also show a large distinct number of unique genes. For example, SS1 and Xiangnong 1 strains show about the same genome size but they have, 52 and 237 unique genes , respectively.
Notably, the open pan-genome of Ganoderma sp. is in a development phase, whereby new genes are added to the pan-genome when new strain is sequenced (Figure 4). Based on the fitting curve of Ganoderma sp. pan-genome data that comprises of eight Ganoderma sp. strains, it is estimated that about 427 genes are introduced to the pan-genome.
The newly added genes within this genus suggest the evolution of this fungi that reflects to its genome varieties.
Pathogen-specific genes
Genome-wide comparative analysis discovers 607 genes that are conserved in pathogenic fungi G. boninense but absent in its related non- pathogenic Ganoderma sp., suggesting their potential role in G. boninense pathogenicity towards
Table 2. BUSCO result of Ganoderma sp. genome completeness assessment based on 1,335 universal Basidiomycota single-copy ortholog
Strain Complete Fragmented Missing
G3 1,101 188 46
NJ3 943 257 135
FGV-M 787 238 310
BCRC37177 1,263 58 14
g.260125-1 1,253 37 45
Xiangnong 1 1,250 75 10
SS1 1,298 30 7
Gsinense 1,283 41 11
Fig. 1. Number of predicted genes and average length of encoded proteins in Ganoderma sp. Both are found to be random in Ganoderma sp. strains.
Fig. 2. Number of orthologous groups (OGs) in different class of pan-genome data. The accessory genome consists of 94.6% multi-strains OGs while 5.4% of them are singletons (strain-specific OGs).
Fig. 3. Number of unique genes in Ganoderma sp. These genes are strain- specific genes found based on pan-genome data.
its host. Homology search shows that 69.9% of the genes have similarity to non-redundant database from NCBI. Of the 607 genes, 310 genes were annotated into 16 functional groups using Gene Ontology (GO) database, consisting of seven biological processes, two molecular functions and seven cellular components (Figure 5). The GO annotation is a useful indicator to unravel the potential function of the encoded proteins towards understanding G. boninense pathogenicity, including in the view of plant growth, development, or response to internal and external cues.
In biological process, the dominant number of proteins (124 sequences) were categorised in metabolic process, GO:0008152, which refers to the chemical reactions and pathways, including anabolism and catabolism (Ashburner et al., 2000).
This is followed by other classes, named cellular process, GO:0009987 (85), localization, GO:0051179 (31), biological regulation, GO:0065007 (29), regulation of biological process, GO:0050789 (24), cellular component organisation or biogenesis, GO:0071840 (20) and response to stimulus, GO:0050896 (17). Comparative genomics analysis reveals the absent of these genes in non-pathogenic Ganoderma sp., suggesting the involvement of these genes in regulation process of the pathogen, which might contribute to the G.
boninenese pathogenicity. Meanwhile, 118 (Figure 6) and 114 (Figure 7) pathogen-specific genes were associated to two molecular functions; catalytic activity (GO:0003824) and binding (GO:0005488),
respectively. Both classes refer to multi-genic functional interaction, therefore this finding may lead into downstream analysis to uncover the system biology in the pathogen that affects its pathogenicity. On another note, in the sense of cellular component, the highest number of proteins were located at the membrane, GO:0016020 (65), indicating that those proteins are embedded or attached on the membrane (Ashburner et al., 2000) during infections.
Apart from that, the pathogenic-specific encoded proteins were subjected to sequence analysis to predict their possibility as secretome, which refers to the proteins that consist of signal peptide and secreted into the extracellular space (Agrawal et al., 2010). Signal peptide is a short peptide located at the N-terminus of a protein, which leads the protein into the secretory pathway and removed when the protein is translocated across the endoplasmic reticulum membrane (Lodish et al., 2000). The realibility of the prediction of the classical signal peptide involved in the secretory pathway will then be strengthened by the analysis of subcellular location. Of the 607 genes, 32 sequences were found to contain signal peptide, 86 sequences were associated in secretory pathway and 535 sequences have no transmembrane domain. The consolidation of the finding has resulted in a total of 25 pathogen-specific genes that were predicted to encode secreted proteins which have the N- terminal signal peptide and without transmembrane domain (Figure 8). These sequences are classified as Fig. 4. Development of Ganoderma sp. pan-genome. New orthologous groups are added
with addition of more sequenced strain. The grey box shows the fitting curve of new gene profile that results into 427 new genes in Ganoderma sp. pan-genome.
Fig. 5. Functional annotation of pathogen-specific proteins using GO database. The highest classes are metabolic process (biological process), catalytic activity (molecular function) and membrane (cellular component).
Fig. 6. Word cloud containing 118 pathogen-specific genes that were annotated as catalytic activity (GO:0003824). The word size is corresponds to the number of gene occurences.
Fig. 7. Word cloud containing 114 pathogen-specific genes that were annotated as binding (GO:0005488). The word size is corresponds to the number of gene occurences.
the pathogenic secretory proteins, which are believed to be processed via endoplasmic reticulum and Golgi apparatus prior to their secretion into the extracellular space. Of 25, 16 pathogen-specific genes were homologous to proteins non-redundant database. This includes known functions such as fungal hydrophobin, acid proteinase, immuno- modulatory protein and glycoside hydrolase proteins, while six of them were homolog to hypothetical proteins. Besides, 10 of these 25 genes were annotated with Gene Ontology, whereby most
of them were related to membrane component and cell wall proteins.
To illustrate the implementation of this pan- genome result, here we discuss on a fungal hydrophobin, a group of cysteine-rich proteins that were uniquely expressed by filamentous fungi and able to form a hydrophobic coating on the surface of an object (Sunde et al., 2008). It is classified as fungal-type cell wall (GO:0009277) and predicted to function in structural constituent of cell wall (GO:0005199) and involve in cell wall biogenesis (GO:0042546). In our finding, this 123-residues protein contains seven cysteines that were all conserved in other homologous hydrophobins (Figure 9) from ther basidiomycetes. Unfortunately, the sequence alignment in Figure 9 shows that G.
boninense hydrophobin is lack of one cysteine residue as compared to others, and the reason behind this observation is yet unknown.
Notably, the G. boninense hydrophobin is found to be homolog to hydrophobin proteins from 22 basidiomycetes including pathogens, such as Dichomitus squalens, Fomitiporia mediterranea, Gloeophyllum trabeum, Heterobasidion sp., and Trametes sp. However, there are some non-pathogen basidiomycetes were homolog to this protein, such as Ganoderma sinense, Gymnopus luxurians and Lentinula edodes, as well as some basidiomycetes that have not been characterized in detail, such as Fig. 8. Consolidation of different analyses in predicting
signal peptide, transmembrane domain and secretory pathway.
Fig. 9. Alignment of some hydrophobin proteins from G. boninense and its homolog proteins from other basidiomycetes.
As opposed to other hydrophobins that consist of eight cysteine residues, all seven cysteines found in G. boninense hydrophobin were conserved in other hydrophobins. The conserved residues are denoted by ‘*’ symbol, while ‘:’ and ‘.’ indicate the partial conserved residues of strong and weak class, respectively.
Jaapia argillacea and Leucoagaricus sp. Despite their pathogenicity status, this observation might be explained by the role of hydrophobin proteins in fungi. These basidiomycetes have similar lifestyle that rely on other sources of organic matter for their nutrition intake. Therefore, the hydropobin protein might be useful as a mediating contact and communication between the fungus and its environment, which illustrates the requirement of a pathogen to penetrate its host system during host invasion of the pathogen.
CONCLUSION
In this study, the pan-genome of eight Ganoderma sp. was developed, consisting of both pathogenic and non-pathogenic strains. The established pan- genome was implemented as an alternative approach to identify candidate genes of interest in G.
boninense, which normally is an enormous challenge and bottleneck in laboratory tasks due to its time- consuming process. The selection of potential gene candidates that might involve in the pathogenicity of G. boninense was performed within a short time with the help of the high performance computing cluster. This fundamental analysis may lead to further characterization and functional studies of the identified gene candidates to unveil the molecular mechanisms underlying the pathogenicity of this fungal towards its host, oil palm. Ultimately, this bio-catalogue of Ganoderma sp. will not only support the pathogenicity related experiments, but also provide as a resource for other experiments that harness the Ganoderma sp. genome.
ACKNOWLEDGEMENTS
This work was funded by Felda Agricultural Services Sdn. Bhd. The authors wish to thank the CEO of FGV Research & Development Sdn. Bhd.
for the given support and consultation in the entire project.
REFERENCES
Agrawal, G.K., Jwa, N-S., Lebrun, M-H., Job, D. &
Rakwal, R. 2010. Plant secretome: unlocking secrets of the secreted proteins. Proteomics, 10(4): 799-827.
Altschul, S.F., Gish, W., Miller, W., Myers, E.W. &
Lipman, D.J. 1990. Basic local alignment search tool. Journal of Molecular Biology, 215(3):
403-410.
Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M. & Sherlock, G. 2000. Gene Ontology: tool for the unification of biology.
The Gene Ontology Consortium. Nature Genetics, 25(1): 25-29.
Binder, M., Justo, A., Riley, R., Salamov, A., Lopez- Giraldez, F., Sjokvist, E., Copeland, A., Foster, B., Sun, H., Larsson, E., Larsson, K.-H., Townsend, J., Grigoriev, I.V. & Hibbett, D.S.
2013. Phylogenetic and phylogenomic over- view of the Polyporales. Mycologia, 105(6):
1350-1373.
Chen, S., Xu, J., Liu, C., Zhu, Y., Nelson, D.R., Zhou, S., Li, C., Wang, L., Guo, X., Sun, Y., Luo, H., Li, Y., Song, J., Henrissat, B., Levasseur, A., Qian, J., Li, J., Luo, X., Shi, L., He, L., Xiang, L., Xu, X., Niu, Y., Li, Q., Han, M.V., Yan, H., Zhang, J., Chen, H., Lv, A., Wang, Z., Liu, M., Schwartz, D.C. & Sun, C. 2012. Genome sequence of the model medicinal mushroom Ganoderma lucidum. Nature Communications, 3: 913.
Chen, Z.Y., Goh, Y.K., Goh, Y.K. & Goh, K.J. 2017.
Life expectancy of oil palm (Elaeis guineensis) infected by Ganoderma boninense in coastal soils, Malaysia: a case study. Archives of Phytopathology and Plant Protection, 50(11- 12): 598-612.
Conesa, A. & Götz, S. 2008. Blast2GO: A comprehensive suite for functional analysis in plant genomics. International Journal of Plant Genomics, 2008: 619832.
Emanuelsson, O., Brunak, S., von Heijne, G. &
Nielsen, H. 2007. Locating proteins in the cell using TargetP, SignalP and related tools. Nature Protocols, 2(4): 953-971.
Huang, Y.-H., Wu, H.-Y., Wu, K.-M., Liu, T.-T., Liou, R.-F., Tsai, S.-F., Shiao, M.-S., Ho, L.-T., Tzean, S.-S. & Yang, U.-C. 2013. Generation and analysis of the expressed sequence tags from the mycelium of Ganoderma lucidum. PLoS ONE, 8(5): e61127.
Isaac, I.L., Walter, A.W.C.Y., Bakar, M.F.A., Idris, A.S., Bakar, F.D.A., Bharudin, I. & Murad, A.M.A. 2018. Transcriptome datasets of oil palm pathogen Ganoderma boninense. Data in Brief, 17: 1108-1111.
Jiang, Y., Chang, Y., Liu, Y., Zhang, M., Luo, H., Hao, C., Zeng, P., Sun, Y., Wang, H. & Zhang, L. 2017. Overview of Ganoderma sinense polysaccharide – an adjunctive drug used during concurrent Chemo/Radiation therapy for cancer treatment in China. Biomedicine &
Pharmacotherapy, 96: 865-870.
Jin, X., Ruiz-Beguerie, J., Sze, D.M. & Chan, G.C.
2016. Ganoderma lucidum (Reishi mushroom) for cancer treatment. Cochrane Database of Systematic Reviews, 4: CD007731
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y.
& Morishima, K. 2017. KEGG: new perspectives on genomes, pathways, diseases and drugs.
Nucleic Acids Research, 45(D1): D353-D361.
Keeling, P.J. & Palmer, J.D. 2008. Horizontal gene transfer in eukaryotic evolution. Nature Reviews Genetics, 9(8): 605-618.
Keypour, S., Riahi, H., Borhani, A., Shayan, M.R.A.
& Safaie, N. 2014. Survey on wood decay fungi Ganoderma species (Ganodermataceae;
Polyporales) from Guilan and Mazandaran, Iran.
International Journal of Agriculture and Biosciences, 3(3): 132-135.
Kheng, Y., Advanced, G., Bhd, S., Keng, Y., Applied, G. & Resources, A. 2014. Aggressiveness of Ganoderma boninense isolates on the vegeta- tive growth of oil palm (Elaeis guineensis) seedlings at different age. Malaysian Applied Biology, 43(2): 1-8.
Larkin, M.A., Blackshields, G., Brown, N.P., Chenna, R., Mcgettigan, P.A., McWilliam, H., Valentin, F., Wallace, I.M., Wilm, A., Lopez, R., Thompson, J.D., Gibson, T.J. & Higgins, D.G.
2007. Clustal W and Clustal X version 2.0.
Bioinformatics, 23(21): 2947-2948.
Liu, D., Gong, J., Dai, W., Kang, X., Huang, Z., Zhang, H.-M., Liu, W., Liu, L., Ma, J., Xia, Z., Chen, Y., Chen, Y., Wang, D., Ni, P., Guo, A.-Y.
& Xiong, X. 2012. The genome of Ganoderma lucidum provides insights into triterpenes biosynthesis and wood degradation. PLoS ONE, 7(5): e36146.
Krogh, A., Larsson, B., von Heijne, G. & Sonnhammer, E.L. 2001. Predicting transmembrane protein topology with a hidden Markov model:
application to complete genomes. Journal of Molecular Biology, 305(3): 567-580.
Laing, C., Buchanan, C., Taboada, E.N., Zhang, Y., Kropinski, A., Villegas, A., Thomas, J.E. &
Gannon, V.P.J. 2010. Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions. BMC Bioinformatics, 11(1): 461.
Li, L., Stoeckert, C.J.J. & Roos, D.S. 2003.
OrthoMCL: Identification of ortholog groups for eukaryotic genomes. Genome Research, 13(9): 2178-2189.
Lodish, H., Berk, A., Zipursky, S.L., Matsudaira, P., Baltimore, D. & Darnell, J.E. 2000. Molecular Cell Biology. New York: W.H. Freeman; Section 17.4, Translocation of secretory proteins across the ER membrane. Available from: https://www.
ncbi.nlm.nih.gov/books/NBK21532/
Mercière, M., Laybats, A., Carasco-Lacombe, C., Tan, J.S., Klopp, C., Durand-Gasselin, T., Alwee, S.S.R.S., Camus-Kulandaivelu, L. & Breton, F.
2015. Identification and development of new polymorphic microsatellite markers using genome assembly for Ganoderma boninense, causal agent of oil palm basal stem rot disease.
Mycological Progress, 14(11): 103.
Miller, R.N.G., Holderness, M., Bridge, P.D., Chung, G.F. & Zakaria, M.H. 1999. Genetic diversity of Ganoderma in oil palm plantings. Plant Pathology, 48(5): 595-603.
Mitchell, A., Chang, H-Y., Daugherty, L., Fraser, M., Hunter, S., Lopez, R., McAnulla, C., McMenamin, C., Nuka, G., Pesseat, S., Sangrador-Vegas, A., Scheremetjew, M., Rato, C., Yong, S-Y., Bateman, A., Punta, M., Attwood, T.K., Sigrist, C.J.A., Redaschi, N., Rivoire, C., Xenarios, I., Kahn, D., Guyot, D., Bork, P., Letunic, I., Gough, J., Oates, M., Haft, D., Huang, H., Natale, D.A., Wu, C.H., Orengo,
C., Sillitoe, I., Mi, H., Thomas, P.D. & Finn, R.D.
2015. The InterPro protein families database:
the classification resource after 15 years.
Nucleic Acids Research, 43(D1): D213-D221.
Nielsen, H. 2017. Predicting secretory proteins with SignalP. Methods in Molecular Biology, 1611:
59-73.
Pilotti, C.A. 2005. Stem rots of oil palm caused by Ganoderma boninense: pathogen biology and epidemiology. Mycopathologia, 159(1): 129- 137.
Simão, F.A., Waterhouse, R.M., Ioannidis, P., Kriventseva, E.V. & Zdobnov, E.M. 2015.
BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics, 31(19): 3210-3212.
Sunde, M., Kwan, A.H.Y., Templeton, M.D., Beever, R.E. & Mackay, J.P. 2008. Structural analysis of hydrophobins. Micron, 39(7): 773-784.
Testa, A.C., Hane, J.K., Ellwood, S.R. & Oliver, R.P.
2015. CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts. BMC Genomics, 16(1): 170.
Tettelin, H., Masignani, V., Cieslewicz, M.J., Donati, C., Medini, D., Ward, N.L., Angiuoli, S.V., Crabtree, J., Jones, A.L., Durkin, A.S., Deboy, R.T., Davidsen, T.M., Mora, M., Scarselli, M., Margarit y Ros, I., Peterson, J.D., Hauser, C.R., Sundaram, J.P., Nelson, W.C., Madupu, R., Brinkac, L.M., Dodson, R.J., Rosovitz, M.J., Sullivan, S.A., Daugherty, S.C., Haft, D.H., Selengut, J., Gwinn, M.L., Zhou, L., Zafar, N., Khouri, H., Radune, D., Dimitrov, G., Watkins, K., O’Connor, K.J.B., Smith, S., Utterback, T.R., White, O., Rubens, C.E., Grandi, G., Madoff, L.C., Kasper, D.L., Telford, J.L., Wessels, M.R., Rappuoli, R. & Fraser, C.M. 2005. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial “pan-genome”. Proceedings of the National Academy of Sciences of the United States of America, 102(39): 13950-13955.
The Gene Ontology Consortium. 2000. Gene Ontology: tool for the unification of biology.
Nature Genetics, 25(May): 25-29.
Turner, P.D. 1981. Oil palm diseases and disorders.
Oxford University Press. Retrieved from https://books.google.com.my/books?id=mAny XwAACAAJ
Utomo, C., Tanjung, Z.A., Aditama, R., Buana, R.F.N., Pratomo, A.D.M., Tryono, R. & Liwang, T. 2018. Draft genome sequence of the phyto- pathogenic fungus Ganoderma boninense, the causal agent of basal stem rot disease on oil palm. Genome Announcements, 6(17): e00122- 18.
Yue, G.G.L., Chan, B.C.L., Han, X-Q., Cheng, L., Wong, E.C.W., Leung, P.C., Fung, K.P., Ng, M.C.H., Fan, K., Sze, D.M.Y. & Lau, C.B.S.
2013. Immunomodulatory activities of Ganoderma sinense polysaccharides in human immune cells. Nutrition and Cancer, 65(5):
765-774.
Zhao, Y., Jia, X., Yang, J., Ling, Y., Zhang, Z., Yu, J., Wu, J. & Xiao, J. 2014. PanGP: a tool for quickly analyzing bacterial pan-genome profile.
Bioinformatics, 30(9): 1297-1299.
Zhu, Y., Xu, J., Sun, C., Zhou, S., Xu, H., Nelson, D.R., Qian, J., Song, J., Luo, H., Xiang, L., Li, Y., Xu, Z., Ji, A., Wang, L., Lu, S., Hayward, A., Sun, W., Li, X., Schwartz, D.C., Wang, Y. &
Chen, S. 2015. Chromosome-level genome map provides insights into diverse defense mechanisms in the medicinal fungus Ganoderma sinense. Scientific Reports, 5: 11087.