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R E S E A R C H A R T I C L E Open Access
Genomic and transcriptomic insights into
Raffaelea lauricola pathogenesis
Yucheng Zhang
1
, Junli Zhang
1,2
, Dan Vanderpool
3,4
, Jason A. Smith
2
and Jeffrey A. Rollins
1*
Abstract
Background: Laurel wilt caused by Raffaelea lauricola is a lethal vascular disease of North American members of
the Lauraceae plant family. This fungus and its primary ambrosia beetle vector Xyleborus glabratus originated from
Asia; however, there is no report of laurel wilt causing widespread mortality on native Lauraceae trees in Asia. To
gain insight into why R. lauricola is a tree-killing plant pathogen in North America, we generated and compared
high quality draft genome assemblies of R. lauricola and its closely related non-pathogenic species R. aguacate.
Results: Relative to R. aguacate, the R. lauricola genome uniquely encodes several small-secreted proteins that are
associated with virulence in other pathogens and is enriched in secondary metabolite biosynthetic clusters,
particularly polyketide synthase (PKS), non-ribosomal peptide synthetase (NRPS) and PKS-NRPS anchored gene
clusters. The two species also exhibit significant differences in secreted proteins including CAZymes that are
associated with polysaccharide binding including the chitin binding CBM50 (LysM) domain. Transcriptomic
comparisons of inoculated redbay trees and in vitro-grown fungal cultures further revealed a number of secreted
protein genes, secondary metabolite clusters and alternative sulfur uptake and assimilation pathways that are
coordinately up-regulated during infection.
Conclusions: Through these comparative analyses we have identified potential adaptations of R. lauricola that may
enable it to colonize and cause disease on susceptible hosts. How these adaptations have interacted with co-
evolved hosts in Asia, where little to no disease occurs, and non-co-evolved hosts in North America, where lethal
wilt occurs, requires additional functional analysis of genes and pathways.
Keywords: Laurel wilt, Raffaelea lauricola, Genome, Sulfur, Aerolysin, Ceratoplatanin, Transcriptome, Effector,
Secondary metabolite, Ophiostomatales, Vascular wilt disease
Background
Emerging infectious diseases of plants and animals due
to anthropogenic movement, climate change, and nat-
ural processes are impacting natural ecosystems at an
unprecedented rate [1–3]. Laurel wilt is among these
diseases. The disease is caused by the Ascomycota fun-
gus Raffaelea lauricola (Ophiostomatales), a native sym-
biont of the invasive Asian ambrosia beetle Xyleborus
glabratus (Curculionidae: Scolytinae). In North America,
X. glabratus was first detected in Port Wentworth,
Georgia, USA in 2002 [4] and the wilting and mortality
of native Lauraceae trees in the area were first reported
in 2003 [5]. In the ensuing time, laurel wilt has caused
and continues to cause widespread mortality on redbay
(Persea borbonia) and other members of the Lauraceae
family in the southeastern USA resulting in massive eco-
system damage [6–11]. In 2011, laurel wilt was found to
infect avocado in Florida’s commercial production area
[12]. Infection of this domesticated and agronomically
important Lauraceae family member has significantly
impacted the commercial production of avocado in Flor-
ida [13] and poses a serious threat to currently
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data made available in this article, unless otherwise stated in a credit line to the data.
* Correspondence: rollinsj@ufl.edu
1
Department of Plant Pathology, University of Florida, 1453 Fifield Hall,
Gainesville, FL 32611-0680, USA
Full list of author information is available at the end of the article
Zhang et al. BMC Genomics (2020) 21:570
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unaffected avocado-producing areas of North America
including California and Mexico [14].
The insect vector X. glabratus has been recorded from
Bangladesh, India, Japan, Myanmar, Taiwan, and main-
land China and is thought to be native to Asia [15,16].
R. lauricola has been recovered from specimens of X.
glabratus from Japan and Taiwan [17]. Despite the wide-
spread occurrence of X. glabratus in Asia, there is no re-
port of laurel wilt causing mortality on native Lauraceae
trees in Asia. Beetle galleries and limited wilt and vascu-
lar streaking symptoms were however reported from na-
tive stands of Asian Lauraceae trees in Taiwan [18]. In
the southeastern USA where laurel wilt has annihilated
native Lauraceae trees, invasive camphor trees from Asia
(Cinnamomum camphora) exhibit limited symptoms in-
cluding branch dieback or no symptoms of laurel wilt
unless subject to mass beetle attacks [19]. These findings
indicate that R. lauricola is a pathogen in Asia but not a
tree-killing pathogen of native Lauraceae hosts from this
native range.
R. lauricola in the USA has been assumed to be
fromasingleintroduction[17]. This was confirmed
by a recent genetic variation analysis of R. lauricola
populations in Taiwan, Japan, and the USA [20]. This
study identified high genetic diversity and both mat-
ing types (MAT1 and MAT2) in populations from
Taiwan and Japan. On the contrary only MAT2 is
found in the USA and is currently represented by a
clonally reproducing, highly uniform population based
on SSR comparisons of 57 isolates from all known
hosts throughout the geographical range [21]. Drea-
den et al. [22] have examined North American and
Asian isolates and further narrowed the origin of the
North American population to Taiwan. Artificial in-
oculation of R. lauricola isolates from Asia kill avo-
cado and swamp bay trees with similar aggressiveness
and symptomology as isolates from the USA [23,24].
Thesefindingsindicatethatthepathogenlineagein-
troduced to North America is similar in virulence as
isolates from the native range.
Like other vascular tree diseases including Dutch elm
disease of Wych elm caused by Ophiostoma novo-ulmi
[25] and Verticillium wilts of numerous tree species
[26], diseased Lauraceae plants exhibit wilt symptoms in-
cluding rapid foliage necrosis and vascular discoloration.
These symptoms appear to be at least partially related to
the xylem blockage caused by tylose and gel formation
[27,28]. R. lauricola is so aggressive that a single inocu-
lation of this pathogen on avocado and other members
of the North American Lauraceae family is sufficient to
induce systemic and lethal disease development within
several weeks [27,29] with as few as 100 spores [30].
The mechanisms underlying this extreme aggressiveness
remain uncharacterized.
The mortality of Lauraceae trees in the southeastern
USA is at least partially due to an extreme host response
[28]. Plant immunity systems functioning against patho-
gen attack consist of at least two interconnected path-
ways, namely pathogen-associated molecular pattern
(PAMP)-triggered immunity (PTI) and effector-
triggered-immunity (ETI) [31]. PTI provides basal
defense against all potential pathogens and is based on
the recognition of conserved PAMPs by pattern recogni-
tion receptors (PRRs) that activate PTI. Chitin, a major
structural component of fungal cell walls, is one of the
best-characterized fungal PAMPs. If basal PTI defense
systems are evaded by pathogen effectors, plants per-
ceive effectors and activate ETI, which leads to rapid
and enhanced host defense responses, including hyper-
sensitive responses (HR). Whether PTI or ETI plays the
major role in the extreme host response of Lauraceae
plants in the southeastern USA to R. lauricola is un-
known, and various hypotheses have been proposed to
explain the extreme symptomology of laurel wilt on
North American species of Lauraceae [18,32,33]. The
first of these hypotheses that we term the “accidental
pathogen hypothesis”was originally proposed by Hulcr
and Dunn [32] as an example of an “evolutionary mis-
match hypothesis”. It proposes that R. lauricola is a
non-pathogen in trees native to southeast Asia and the
lethal symptomology observed in Lauraceae hosts native
to the western hemisphere is the result of a massive
defense response of the previously un-encountered host
species sensing the presence of a potential pathogen
within the xylem tissue associated with beetle galleries.
Hulcr et al. provided strong evidence against this hy-
pothesis when they reported the presence of mild, i.e.,
non-lethal, laurel wilt symptomology in Taiwan on Asian
species of Lauraceae [18]. A second hypothesis which is
truly an “evolutionary mismatch hypothesis”in the con-
text of Desurmont et al. [34] is based on co-evolutionary
processes [33] and we term the “adapted pathogen hy-
pothesis”. Under this hypothesis, R. lauricola has evolved
pathogenicity in its native range via host-pathogen co-
evolutionary processes, and a more balanced host re-
sponse dampens symptomology in extant Lauraceae
from the eastern hemisphere. The lack of these co-
evolutionary processes from the host defense side results
in lethal symptomology in western hemisphere hosts ei-
ther as an overreaction to PAMPS produced by the
pathogen or as the result of specific virulence factors or
effectors to which the North American hosts are un-
adapted. To test and distinguish between these two hy-
potheses and better understand the adaptations present
in pathogenic relative to non-pathogenic Raffaelea spp.,
we generated, annotated, and compared high-quality
draft genome assemblies of the pathogenic R. lauricola
(isolate RL4) and a closely related non-pathogenic
Zhang et al. BMC Genomics (2020) 21:570 Page 2 of 23
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species R. aguacate (isolate PL1004), recovered from a
dead avocado tree (Persea americana) in Florida [35]. R.
aguacate PL1004 resembles R. lauricola morphologic-
ally, is phylogenetically closely related to R. lauricola
[36], is a nutritional symbiont of ambrosia beetles that
transmit R. lauricola and associates with avocado but is
not pathogenic. Comparative genomic analysis between
R. lauricola RL4 and R. aguacate PL1004 has the poten-
tial to reveal shared and unique genes between the two
species and determine if an enrichment for
pathogenicity-associated genes exists within R. lauricola
consistent with the hypothesis of adapted pathogenesis.
Results
Raffaelea lauricola and R. aguacate genome assemblies
and gene prediction
To conduct comparative genomics analyses between
pathogenic and non-pathogenic Raffaelea spp., we se-
quenced and assembled genomes and transcriptomes of
the pathogenic species R. lauricola RL4 and the non-
pathogenic species R. aguacate PL1004 using the pipe-
line shown schematically in Supplemental Figure S1.
Each species was sequenced by Ion Torrent technology
to generate 1402 Mb of Q20 bases with average read
lengths of 300 bp and 1669 Mb of Q20 bases with aver-
age read lengths of 308 bp, respectively. The two species
were also previously sequenced [37] from mate-pair and
paired-end libraries generated by Illumina Hi-Seq 2000
and assembled (GenBank assembly accession: GCA_
002778145.1 and GenBank assembly accession: GCA_
002777955.1) by ALLPATHS-LG [38]. To leverage
genomic information from both the Illumina and Ion
Torrent assemblies, the Metassembler pipeline [39] was
utilized. The integrated assemblies generated by
Metassembler were improved as evidenced by an in-
crease in N50 and a decrease in the number of scaffolds
(Table 1) compared with assemblies using sequence
reads from IonTorrent or Illumina reads alone [37,40].
The non-pathogenic R. aguacate PL1004 genome assem-
bly (35.7 Mb) is slightly larger but similar in size to the
closely related pathogenic species R. lauricola RL4 (34.3
Mb).
To determine if differences existed in repeat content
between pathogenic and non-pathogenic species, we ex-
amined and compared repetitive sequences between the
two genomes. A total of 8.64% of the R. lauricola assem-
bly was identified as repetitive compared with 6.51% for
the non-pathogenic R. aguacate. The increased repeat
content of the R. lauricola genome could be attributed
primarily to an increase in LTR retroelements which
comprised 2% of the R. lauricola genome and only 0.2%
of the R. aguacate genome. LINE retroelements and
DNA transposons comprised 0.6 and 1% of the R. lauri-
cola genome respectively representing and enrichment
of 3-fold and 2-fold over R. aguacate. (Table S1).
RNA-Seq data for gene prediction was generated from
liquid-grown R. lauricola RL4 and R. aguacate PL1004
samples with Illumina Hiseq 2000 technology (NCBI
SRA Sample accession: SRX3033598 and SRX3033591).
To create a comprehensive transcriptome database, we
used a pipeline that combined genome-guided and de
novo Trinity assemblies [41], followed by Program to
Assemble Spliced Alignments (PASA0 [42] to assemble
the RNA-Seq reads. These processes generated 25,044
and 26,386 transcripts for R. lauricola RL4 and R. agua-
cate PL1004, respectively.
Gene predictions for the two Raffaelea genomes were
made using the MAKER annotation pipeline [43].
Table 1 Genome assembly and structural annotation of two Raffaelea genomes
Organism R. lauricola R. aguacate
Isolate name RL4 PL1004
Region of isolation Florida (Brevard Co.), USA Florida (Miami-Dade Co.), USA
Sequencing platform Illumina & Ion torrent Illumina & Ion torrent
Assembled genome size (Mb) 34.3 35.7
Contig count 480 843
Scaffold count 169 368
Contig N50 (Kb) 394.3 134.8
Scaffold N50 (Kb) 3109.7 458.8
Coding genes 10,315 11,654
Number of complete BUSCOs* 1415 (98.4%) 1406 (97.8%)
Number of Fragmented BUSCOs 21 29
GC content (%) 55.3% 57.5%
Repeat rate (%) 8.64% 6.51%
Reference This study This study
*n= 1438
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MAKER predicts proteins based on RNA-Seq transcripts
and homology with protein-coding sequences of other
species, and with the consensus of the ab initio gene
prediction algorithms GeneMark [44], AUGUSTUS [45],
and SNAP [46]. The details of the Maker pipeline can be
found in the Methods section. Using these methods, the
R. lauricola genome was predicted to encode 10,315 pro-
teins whereas R. aguacate was predicted to encode 11,
654 proteins. This represents a 13% increase in gene
coding capacity in the non-pathogen whose genome is
only 4% larger than that of R. lauricola. This, coupled
with a decreased repeat content, indicates a slightly
more streamlined genome for R. aguacate relative to R.
lauricola.
Benchmarking Universal Single-Copy Orthologs
(BUSCO) was used to provide an estimate of assembly
and annotation completeness [47]. A search for the 1438
fungal universal single-copy ortholog genes with BUSCO
1.2 identified 1415 (98.4%) complete and 21 partial genes
in R. lauricola RL4 and 1406 (97.8%) complete and 29
partial genes in R. aguacate PL1004. Predicted gene con-
tent for each genome assembly is therefore estimated to
be ~ 98% complete. These figures indicate high quality
draft genome assemblies and gene predictions for both
Raffaelea species. These gene predictions were utilized
for further comparative analyses.
Secreted protein and candidate effector analysis
Effector proteins play a fundamental role in establishing
host-pathogen compatibility as well as in triggering host
defense responses. To identify candidate effector pro-
teins from R. lauricola, secreted proteins lacking trans-
membrane domains were analyzed with the EffectorP
algorithm [48]. From R. lauricola, 49 of the 740 secreted
proteins are predicted to be effectors (6.6%; Table S2).
From R. aguacate, 30 of the 727 secreted proteins are
predicted to be effectors (4.1%; Table S3). Of the 49 pre-
dicted effectors from R. lauricola, five are significantly
up-regulated in planta (FDR < 0.05) (Table S2) but only
one, RL4_JR_10338, a putative glycosyltransferase is
unique to R. lauricola relative to R. aguacate. The other
four predicted effectors that were up-regulated during
infection share various homologies. RL4_JR_03519
(FDR = 3E-6; 3.1 log2 fold change) has conserved se-
quence and structural homology with the cysteine-rich
secretory protein SCP domain (plant PR-1 family). RL4_
JR_05948 (FDR = 1E-4; 3.3 log2 fold change) is highly
conserved within fungi and shares homology with ribo-
somal protein s17 and many hypothetical proteins. RL4_
JR_6769 (FDR = 3E-24; 4.6 log2 fold change) encodes a
small (67 amino acid) pre-protein with homology only
to other hypothetical proteins. RL4_JR_9102 (FDR = 9E-
15; 2.3 log2 fold change) encodes a protein with strong
homology to peptide methionine sulfoxide reductases
which play a role in protecting proteins from oxidative
damage. The remaining 44 putative effectors genes en-
code proteins of diverse putative functions eight of
which are significantly down-regulated during infection
and 36 were not significantly different in their expres-
sion levels during growth in culture versus infected red-
bay trees (Table S2). Of these 36 genes, 16 are
hypothetical proteins, six of which lack orthologs in R.
aguacate. Another eight are lineage restricted lacking
significant homology within the non-redundant protein
database and one, common to both R. lauricola (RL4_
JR_08653) and R. aguacate (Rsp272_RL_08445), encodes
a necrosis inducing protein (NPP1).
Given the relative bias for effector prediction based on
known effectors [48] and with the knowledge that the
emergence of pathogenic diversity is frequently associ-
ated with the gain and loss of genes resulting in a dis-
continuous taxonomic distribution of effector genes [49,
50] we next examined the novel gene content of R. laur-
icola relative to R. aguacate. Between the two genomes,
8128 putatively orthologous pairs were identified repre-
senting 79 and 70% of the predicted proteomes of R.
lauricola and R. aguacate respectively. From the 2195 R.
lauricola unique proteins, 199 are predicted to be se-
creted (Supplemental Table S4). From the 3529 R. agua-
cate unique proteins, 204 are predicted to be secreted
(Supplemental Table S5). Among the unique secreted
proteins from R. lauricola, several with previously de-
fined roles in fungal pathogenesis and defense elicitation
were identified. Prominent among these is a predicted
protein (RL4_JR_05745) belonging to the cerato-platanin
family. This family consists of small, secreted proteins
unique to fungi [51]. This R. lauricola cerato-platanin
gene shares significant homology to many characterized
and predicted cerato-platanin proteins from fungi in-
cluding homologs in Grosmannia clavigera (1E-65) and
Ophiostoma piceae (1E-61). It shares a 62% identity at
the amino acid level with that of BcSpl1, the Botrytis
cinerea cerato-platanin protein which has been demon-
strated to contribute to virulence and elicit a hypersensi-
tive response in its hosts [52,53]. This protein also
possess the typical structural features of this family, in-
cluding a high percentage (> 40%) of hydrophobic amino
acid residues and four conserved cysteine residues (Sup-
plemental Figure S2) and is up-regulated (FDR = 0.01;
1.3 log2 fold change) during plant infection. In addition
to its primary sequence homology, RL4_JR_05745 also
shares strong tertiary structure similarity to cerato-
platanins of other fungi including the founding member
of this family from Ceratocystis platani (PDB:2KQA_A).
The highest scoring (TM-score = 0.987) of these struc-
tural homologs is the Sm1 cerato-platanin family mem-
ber from Hypocrea virens (PDB:3M3A) which has been
characterized as an elicitor of plant defense responses
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[54]. The three dimensional model of the predicted
RL4_JR_05745 protein and the crystal structure model
of Sm1 (3M3A) are shown in Fig. 1a and b, respectively.
The overlay of the Sm1 crystal structure and the RL4_
JR_05745 model predicts that the proteins share nearly
identical tertiary structure (Fig. 1c) despite a primary se-
quence identity of only 71%.
Another putative effector not predicted by EffectorP
but found to be unique to R. lauricola relative to R.
aguacate is a member of the Hce2 family homologous to
the Cladosporium fulvum (Passalora fulvum) Ecp2 [55].
In total, R. lauricola contains seven hce2 genes and R.
aguacate possesses one (Fig. 2). Among these, only one
R. lauricola protein, RL4_JR_00199, a predicted 155 aa
secreted protein, matches the structural characteristics
common to extracellular effectors from this class [56].
The Hce2 domain of RL4_JR_00199 shares 31% identity
and 47% similarity at the amino acid level with the C.
fulvum Ecp2 effector. The two proteins also share a
similar modular architecture and both are small, se-
creted proteins that contain only the Ecp2 domain. This
gene was not differentially expressed in infected redbay
trees versus culture in the transcriptomic analysis but a
second Hce2-domain-encoding secreted protein of 587
amino acids, RL4_JR_00198, immediately downstream of
RL4_JR_00199, is significantly up-regulated during infec-
tion (FDR = 2E-18; 5.6 log2 fold change). This predicted,
secreted protein shares 35% identity and 50% similarity
across the Hce2 domain of C. fulvum and is orthologous
to Rsp272_RL_00013 in R. aguacate.
Additional predicted secreted proteins associated with
pathogenicity in other fungi or postulated here to play a
role in virulence were found to be unique to R. lauricola
relative to R. aguacate (Supplemental Table S4). In
addition to the putative cerato-platanin-encoding gene
(RL4_JR_05745) described above, one gene encoding an
oxalate decarboxylase (RL4_JR_02745) (FDR = 6E-67; 9.4
log2 fold change) and another gene (RL4_JR_08480)
Fig. 1 Tertiary protein structure comparisons. aPredicted tertiary structure model of the RL4_JR_05745 protein. bTertiary structure of protein
3M3G (Hypocrea virens, Sm1:elicitor of plant defense responses), the best Protein Data Bank (PDB) structural match to RL4_JR_05745. cStructural
alignment of RL4_JR_5745 (magenta) and 3M3G (cyan). dPredicted tertiary structure model of the full length RL4_JR_08480 protein. eTertiary
structure of protein 4ZNOA (Dln1), the best Protein Data Bank (PDB) structural match to RL4_JR_08480. fStructural alignment of RL4_JR_08480
(magenta) and 4ZNOA (Dln1) (cyan), unaligned N-terminus, including the signal peptide, of RL4_JR_08480 (yellow)
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encoding a putative aerolysin (FDR = 7E-72; 6.4 log2 fold
change) are up-regulated during infection. Sequence
homologs for this predicted aerolysin-like protein, were
found in Ophiostoma piceae (1E-155), Grosmannia clavi-
gera (1E-143),twenty Colletotrichum spp. (6E-133 –1E-
90), a handful of other fungi (3E-82 –4E-39), and
numerous fish species (>6E-11). Comparative structural
modeling of this R. lauricola protein confirmed a struc-
ture consistent with numerous aerolysin-like proteins
known to function as toxins or defensive molecules by
specific sugar binding through the lectin domain and
membrane pore-forming activity of the natterin-like do-
mains of homo-oligomers. The highest scoring structural
alignment (protein structural similarity TM-score =
0.757) and overlay is shown in Fig. 1.
An additional ten secreted protein-encoding genes
unique to R. lauricola and up-regulated (log2 > 1; FDR <
0.05) during infection lacked significant homologs or
matched hypothetical proteins in the GenBank non-
redundant protein sequence database. These too are
considered candidate virulence factors (Supplemental
Table S4). Many additional secreted proteins unique to
R. lauricola relative to R. aguacate with predicted roles
in host-pathogen interactions however, are also present
but not up-regulated during infection. These include
four CFEM-domain proteins unique among the 14 total
predicted from the genome (Supplemental Table S6).
Members of this family include Pth11 known to function
in host surface sensing and infection structure develop-
ment [57]. Of the four unique CFEM proteins one was
down-regulated during plant infection and the other
three were not differentially expressed between culture
and infected plant. Two unrelated secreted proteins with
BLASTP homology to “infection structure specific”pro-
teins were also unique to R. lauricola (one additional
“infection structure specific”protein is shared with R.
Fig. 2 Domain architecture of Raffaelea lauricola and R. aguacate proteins containing Hce2 domains. CBM18: chitin binding 1 domain (PF00187);
GH18: chitinase (PF00187); Hce2: putative necrosis-inducing factor (PF14856); LysM (CBM50): chitin binding (PF01476); SP: signal peptide
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aguacate) but neither gene was up-regulated during
infection.
Several predicted secreted proteins with putative plant
virulence function annotations that do share an ortholog
in R. aguacate were also up-regulated during infection
(Supplemental Table S7). These include two homologs
of the Pyricularia oryzae ‘biotrophy associated secreted
2’proteins (RL4_JR_02461 and RL4_JR_02274; FDR =
7E-4 and 2E-38, respectively; 3.2 and 6.7 log2 fold
change, respectively), three homologs of the P. oryzae
Magnaporthe Appressorium Specific (MAS) protein
(GEgh16 homologs; RL4_JR_09303, RL4_JR_02203 and
RL4_JR_09408; FDR = 2E-184, 7E-35 and 1E-5 respect-
ively; 7.6, 3.8 and 2.0 log2 fold change, respectively), one
‘infection structure specific’encoding gene (RL4_JR_
03922; FDR = 8E-20; 4.8 log2 fold change) with signifi-
cant homologs in Fusarium, Pyricularia, Colletotrichum
and other Ophiostomatales species, and one ‘small se-
creted’protein (RL4_JR_06930) remarkable for its sig-
nificant up-regulation during infection (FDR = 2E-130;
7.8 log2 fold change) and presence of closest homologs
in Ophiostoma piceae (6E-81) and Phaeoacremonium
minimum (9E-74) and more than 40 Fusarium and Col-
letotrichun species (7E-72 –1E-62). Although not
unique to the pathogen genome, we consider these puta-
tive effectors as well.
Expansion of GH18 and LysM protein domains in R.
lauricola
A genome-wide comparison of encoded carbohydrate-
active enzymes (CAZymes) between the R. lauricola and
R. aguacate genomes was performed. We searched the
two Raffaelea genomes using the dbCAN Web server
(http://www.cazy.org), and compared their inventories.
For each CAZyme class, the number of CAZyme do-
mains and their family assignments are shown in Sup-
plemental Table S8and Fig. 3The genomes of R.
lauricola RL4, and R. aguacate PL1004 encode a total of
448 and 495 CAZyme domains, respectively. Overall, the
two Raffaelea species possess similar numbers of
CAZyme modules in most CAZyme classes; the glycosyl
hydrolase (GH) family is the most prevalent CAZyme
family and the polysaccharide lyase (PL) is the smallest
CAZyme family among those distributed across both
Raffaelea genomes (Fig. 3a). Seven CAZyme domains
were found to be expanded in the non-pathogenic R.
aguacate PL1004 relative to R. lauricola RL4 (Fig. 3b).
This enrichment was for the carbohydrate binding mod-
ule (CBM) domain CBM67 ( -rhamnose binding),
carbohydrate esterase (CE) CE4 domain (de-acetylases),
CE10 domain (carboxylesterases), the glycosyl hydrolase
(GH) GH3 domain (broad substrate specificity exo-
acting sidases), the GH43 (α-L-arabinofuranosidases, α-
L-arabinanases, and β-D-xylosidases), the GH75 (β−1,
4-chitosanases), and the GH109 (α-N-acetylgalactosami-
nidase) domain (Fig. 3b). R. lauricola RL4 on the other
hand, is enriched for two families, both related to chitin.
Twenty-five GH18 (chitinases) domains are encoded by
R. lauricola relative to 16 encoded by R. aguacate and
twenty-six R. lauricola CBM50 (chitin binding; LysM)
domains are predicted, more than twice the number
(eleven) predicted from R. aguacate (Fig. 3b). In R.
Fig. 3 Comparison of the number of Carbohydrate-Active Enzyme (CAZyme) modules across the R. lauricola and R. aguacate genomes. a
Occurrence of CAZyme families (AA, CB, CE, GH, PL) within each genome. bEnrichment of CAZyme domains between the two genomes. AA:
Auxiliary Activities; CB: Carbohydrate-Binding: CE: Carbohydrate Esterases; GH: Glycoside Hydrolases; PL: Polysaccharide Lyases
Zhang et al. BMC Genomics (2020) 21:570 Page 7 of 23
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lauricola these 23 LysM domains are encoded by 14
genes whereas the 11 LysM domains from R. aguacate
are encoded by seven genes (Fig. 4). Among the R. lauri-
cola proteins, five encode LysM domain-only secreted
proteins while only two R. aguacate genes encode LysM
domain-only proteins. Among the other LysM-
containing proteins from both genomes, functional do-
mains including α-1,3-glucan-binding (CBM24), chitin
binding_1 domains (CBM18), chitinase (GH18) and pec-
tate lyase_3 domains (GH55) are present but their func-
tions remain to be investigated.
Secondary metabolism gene clusters are expanded in the
R. lauricola genome
The chemical product and function of most fungal sec-
ondary metabolite clusters (SMC) are unknown but the
prediction and comparative analysis of these biosynthetic
pathways is a strong starting point for identifying puta-
tive toxin biosynthesis genes. For this reason, the SMCs
of the two Raffaelea genomes were predicted using two
independent programs, SMURF [58] and the anti-
SMASH webserver [59]. Due to the differences in the al-
gorithms used by SMURF and antiSMASH, the two
programs identified overlapping but not identical SMC
genes. To obtain a comprehensive list of putative SMCs,
we combine the common and unique predictions of
SMCs from both predictions (Table 2).
R. lauricola is predicted to encode a total of 37 sec-
ondary metabolism clusters relative to the 27 predicted
clusters in R. aguacate. (Fig. 5a). Details of cluster key
enzyme genes and accessory genes are given in Supple-
mental Table S9and S10. Utilizing synteny and se-
quence homology as guides, 11 SMC were determined
to be shared between R. lauricola and R. aguacate (four
PKSs, one NRPS, three Terpenoids, three Other
Fig. 4 Domain organization of LysM- (CBM50-) containing proteins between the two Raffaelea genomes. CBM18: chitin binding 1 domain
(PF00187); CBM24: α-1,3-glucan-binding; GH18: chitinase (PF00187); GH55: pectate lyase 3 domains (PF12708); Hce2: pathogen effector, putative
necrosis-inducing factor (PF14856); LysM (CBM50): chitin binding (PF01476); SP: signal peptide
Table 2 Summarized SMURF and anti-SMASH results for two
Raffaelea genomes
Type R. lauricola RL4 R. aguacate PL1004
SMURF NRPS 3 2
PKS 12 8
PKS-NRPS 5 0
Terpene 0 0
Other 7 6
Total 27 16
Antismash NRPS 4 2
PKS 11 7
PKS-NRPS 7 1
Terpene 7 9
Other 6 7
Total 35 26
Merged NRPS 4 2
PKS 11 7
PKS-NRPS 7 1
Terpene 7 9
Other 8 8
Total 37 27
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products).Thus, R. lauricola contains 26 unique SMCs
(seven PKSs, three NRPSs, seven PKS-NRPSs, four Ter-
penoids, five Other products) and R. aguacate encodes
16 unique SMCs (three PKSs, one NRPS, one PKS-
NRPS, six Terpenoids, five Other products). This
analysis indicates that there are more than twice the
combined number of NRPSs, PKSs and PKS-NRPS hy-
brids in R. lauricola relative to R. aguacate (22 vs10).
Notably, R. lauricola RL4 is predicted to encode seven
PKS–NRPS hybrids, whereas non-pathogenic species R.
aguacate PL1004 encodes a single unique PKS–NRPS
hybrid. Taken together, these data reflect an increased
potential for secondary metabolite production in the
pathogenic R. lauricola.
Layering transcriptomic data onto the SMC data de-
termined that 10 of the R. lauricola SMC key enzymes
(Clusters 7, 8, 11, 16, 17, 18, 22, 24, 25, and 32) are up-
regulated in planta compared to in vitro. Of these,
Fig. 5 Secondary metabolite gene clusters in Raffaelea species. aVenn diagram showing distribution of secondary metabolic gene clusters
between the two Raffaelea genomes. Total numbers of non-ribosomal peptide synthetase (NRPS), polyketide synthase (PKS), and PKS-NRPS gene
clusters are shown in parenthesis. bSynteny analysis between R. lauricola secondary metabolite gene cluster 24 and R. aguacate.cSynteny
analysis between R. lauricola secondary metabolite gene cluster 7 and R. aguacate. *An overlapping, convergently transcribed gene
(RL4_JR_03726) is also predicted on the opposite strand but not shown. dSynteny analysis between R. lauricola secondary metabolite gene
cluster 7 and Pestalotiopsis fici
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cluster 7 (NRPS) and cluster 24 (PKS-NRPS) are not
found in the R. aguacate genome (Supplemental Tables
S9and S10). The anchoring PKS of Cluster 24 shares
homology with other PKSs including the Ophiostoma
piceae UAMH 11346 PKS but no further synteny with
clustered accessory genes was found. A comparison of
the genomic regions up and downstream of this missing
cluster in the R. aguacate genome indicated that the
PKS-encoding gene as well a seven genes up- and four
genes down-stream of this key enzyme gene were absent
from the R. aguacate genome or present in dispersed,
non-clustered regions of the genome (Fig. 5b). Cluster 7
represents an even more extreme example of an inser-
tion or deletion event in which not only were the eight
genes predicted for Cluster 7 missing from the syntenic
region of the R. aguacate genome, but also an additional
11 genes up- and five genes down-stream of the cluster
were absent (Fig. 5c). Examining Cluster 7 in more detail
determined that this cluster shares a significant level of
homology and synteny with an uncharacterized cluster
from Pestalotiopsis fici W106–1 (Fig. 5d) but not with
other SMCs from other species. This cluster is notable
for the presence not only of the anchoring NRPS but
also a fatty acid synthase (acyl-synthetase) and a second
NRPS (“HC-toxin synthetase”).
Of the remaining in planta differentially expressed key
enzyme clusters, Clusters 16 and 17 appear to encode
siderophores (in addition to Clusters 6 and 9 which are
not significantly expressed in planta) and Cluster 8 ap-
pears to encode at least a partial dihydroxynapthelene-
based melanin biosynthetic pathway (a PKS with high
homology to other melanin PKSs and a clustered puta-
tive tetrahydroxynaphthalene reductase). The remaining
up-regulated in planta clusters (Clusters 11, 18, 22, 25,
and 32) that are found in both R. lauricola and R. agua-
cate are predicted to encode polyketides (3 clusters), an
undefined pathway (1 cluster) and a terpenoid product
(1 cluster) (Supplemental Table S9).
Comparative transcriptomic analysis
In addition to cataloging putative virulence associated
genes through comparative genomics we also took a
non-biased transcriptomics approach to identify genes
differentially expressed during plant infection relative to
growth in culture. For this comparative transcriptomic
analysis, three biological replicates of RNA extracted
from R. lauricola grown on solid growth medium and
from R. lauricola-inoculated redbay trees were used.
Two genotypes of redbay, one considered fully suscep-
tible (‘HIE’) and the other considered tolerant (‘HIL’)
were utilized. To confirm the host responses of the two
redbay genotypes, laurel wilt disease scores were
assessed following trunk inoculation. At 60 days post in-
oculation, the average disease score for ‘HIE’was 5 with
a mortality rate of 100% and was 3 for ‘HIL’with a mor-
tality rate of 20%, (Supplemental Table S11). Hence,
‘HIE’was considered to be a laurel wilt susceptible geno-
type and ‘HIL’was considered to be a tolerant genotype.
When mapping reads of the 21 RNAseq samples (6
water-inoculated stems, 6 R. lauricola-inoculated stems,
6 distal leaf samples, 3 in vitro-grown R. lauricola cul-
tures) to the R. lauricola genome assembly, only the six
fungal-inoculated stem tissue samples (three ‘HIE’and
three ‘HIL’) and the three in vitro-grown cultures con-
tained fungal reads and were further analyzed. The per-
centage of fungal reads in the plant inoculated samples
ranged from 0.4% (170,662) to 2.9% (972,592) of the
total read pairs (Supplemental Table S12). From the
in vitro-grown fungal cultures, approximately 91 M reads
per replicate were retained after read cleaning and
adaptor removal for further alignment. No fungal genes
were found to be uniquely up- or down-regulated be-
tween the two redbay genotypes (data not shown). Sub-
sequent analysis therefore, compared the in vitro grown
culture treatment against the two plant-inoculated treat-
ments as six biological replicates of a single treatment,
i.e., plant infection. The analysis of redbay differentially-
regulated transcripts will be reported in a separate
publication.
When comparing gene expression from in vitro grown
cultures to the inoculated redbay stems, 4679 (2070 up-
regulated and 2609 down-regulated) differentially
expressed genes (DEGs) were obtained (FDR < 0.05;
|log2 fold change| > 1) (Supplemental Table S7). Differ-
ential regulation data for many genes with putative roles
in pathogenicity have been presented in the preceding
sections of these results. Taking a more global view of
the data, we see that within the top 100 differentially
regulated genes (sorted adjusted P-value), 44 are alterna-
tive sulfur source (sulfides, sulfoxides, sulfones, sulfo-
nates, sulfate esters and sulfamates) uptake or
assimilation related genes (Fig. 6a and Supplemental
Table S7). At the genome level, genes encoding homo-
logs of known sulfur transporters including sulfate
permeases, high affinity methionine and cysteine per-
mases, and alternative sulfate transporters, as well as en-
zymes functioning in desulfurization of organosulfur
compounds including predicted extracellular and intra-
cellular taurine dioxygenases, arylsulfatases, arylsulfo-
transferases and alkanesulfonate monooxygenase are
abundantly encoded within the R. lauricola genome. In
total, we annotated 150 sulfur source uptake or
assimilation-related genes based on transporter annota-
tion and Enzyme Commission classification (Supplemen-
tal Tables S13 and S14). Of these sulfur-related genes,
108 (72%) are up-regulated in planta, 19 (13%) are
down-regulated, and 23 (15%) exhibit no significant
change (FDR < 0.05; |log2 fold change| > 1) (Fig. 6b). To
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Fig. 6 (See legend on next page.)
Zhang et al. BMC Genomics (2020) 21:570 Page 11 of 23
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summarize this data, a putative metabolic pathway for
predicted R. lauricola genes encoding alternative sulfur
source uptake and assimilation with the total number of
predicted genes up- or down-regulated for each gene is
shown in Fig. 7and more detailed analysis of their clas-
sifications and differential expression is provided below.
Several classes of sulfur compound transporters were
annotated as Transporter Classification Database Family
Members (TCDFM). The four main groups include me-
thionine permeases, cysteine permeases, sulfate perme-
ases, and alternative sulfur transporter family members
(Supplemental Table S13). All seven of the high affinity
methionine permeases (TCDFM: 2.A.3.8.4) and all three
of the high affinity cysteine permeases (TCDFM:
2.A.1.14.20) are all up-regulated during plant infection
(average 6.8 log2fold up-regulation). One putative sulfate
permease (TCDFM: 2.A.53.1.2/SulP) sharing strong
homology to the Cys-13 and Cys-14 sulfate permeases of
N. crassa is up-regulated during infection, but the N.
crassa Sul1 homolog is down-regulated. Three additional
SulP-related family members (TCDFM: 2.A.53.1.11/.7/.8)
of unknown function or putative sodium bicarbonate
transport are all down-regulated. Thirteen of fifteen al-
ternative sulfur transporter family members (TCDFM:
2.A.1.14.38/ AstA) are up-regulated during infection.
Additionally, although not a direct sulfur compound
transporter, 17 of 19 pantothenate family transporters
(2.A.1.14.17 TCDFM) are up-regulated during plant in-
fection. Pantothenic acid (vitamin B5) is required to
synthesize the sulfur-containing coenzyme-A (CoA).
Other annotated sulfur-related transporters and their
differential regulation profiles during plant infection are
listed in supplemental Table S13.
Regarding assimilation of alternative sulfur sources,
genes encoding enzymes to metabolize diverse sets of
organic sulfur compounds including aliphatic, aromatic
(See figure on previous page.)
Fig. 6 Heatmaps of differentially expressed R. lauricola genes represented as log2 fold change (log2FC) from infected redbay versus in vitro
culture. aTop 100 differentially expressed genes sorted by adjusted Pvalues (padj) from smallest to largest. bDifferential expression of 150 genes
annotated for roles in alternative sulfur uptake or assimilation sort by gene ID. Gene IDs highlighted in yellow are annotated for involvement in
alternative sulfur uptake or assimilation
Fig. 7 Model of R. lauricola alternative sulfur uptake and assimilation pathways based on differential gene expression. The number of genes up-
regulated (green arrow) or down-regulated (red arrow) from each enzyme or transporter family is indicated. Enzyme and transporter
abbreviations are given in Supplemental Table S13.
#
SulP: Sulfate permease superfamily 2.A.53; Sulfate permease II 2.A.53.1.2 Neurospora crassa
Cys-14 homolog is up-regulated (5.8 log2), a putative sulfate permease (Sul1; 2A.53.1.11) is down regulated (−1.9 log2) and three additional
unlikely sulfur transporter family members are listed in Supplemental Table S13
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and alkane sulfonates, choline sulfate and aromatic sul-
fur esters are massively up-regulated during infection
(Supplemental Table S14). For example, the diversity
and scale of α-ketoglutarate-dependent sulfonate
dioxygenase-encoding gene family members (PFAM:
TauD/TfdA-like domain; InterPro entry IPR003819)
includes 27 members with an average 6 log2fold up-
regulation (64x). In addition to these aliphatic sulfonate
dioxygenases, five alkane sulfonate monooxygenase-
encoding genes are predicted and all five are up-
regulated during infection (average 8.1 log2fold up-
regulation (274x)). Additional organic sulfur assimilation
enzyme-encoding genes are also up-regulated. The tran-
script accumulation dynamics of these genes is shown in
Supplemental Table S14. Although there are unique
genes without corresponding orthologs in many of these
sulfur assimilation enzyme families in R. lauricola rela-
tive to R. aguacate,R. aguacate also encodes many
unique family members lacking orthologs in R. lauricola
(Supplemental Table 14). Thus, neither species appears
to be enriched in sulfur assimilation genes relative to the
other. When comparing the relative abundance of the
TauD domain among other Sordariomycetes species,
Neurospora crassa encodes 13 TauD family members,
Podospora anserine 23, Colletotrichum graminicola 18,
C. higginsianum 28, Beauveria bassiana 22, Metarhi-
zium anisopliae 11, Verticillium dahliae 13, V. longis-
porum 22, Nectria haemoatococca 26, Neonectria
ditissima 28, Pestalotiopsis fici 37, Sporothrix schenckii
42, Ophiostoma piceae 27 and Ceratocystis platani 7
(http://pfam.xfam.org)[60]. From this sampling, no clear
pattern relating TauD protein domain abundance with
tree pathogens or insect associations is evident.
Genes encoding transporters and assimilation enzymes
for the uptake and utilization of alternative sulfur
sources in filamentous fungi are known to be positively
regulated by the global bZip transcription factor Cys-3
in Neurospora crassa (the MetR ortholog in Aspergillus
spp.) and the negative regulator Scon-2. The Cys-3
ortholog was identified by BLASTP homology and RSD
analysis of the R. lauricola predicted proteins. The
ortholog is structurally misannotated and encompasses
two gene IDs (RL4_JR_07387 and RL4_JR_07388) in the
current predicted gene calls. Of these RL4_JR_07388 is
significantly (FDR = 8.3E-18) up-regulated during plant
infection (2.0 log2fold up-regulation (2.6x)) and RL4_JR_
07387 is slightly up-regulated (0.7 log2fold; FDR = 0.02;
Supplemental Table S15). An ortholog of the Scon-2
negative regulator (RL4_JR_01708) was also identified
from the predicted gene calls. In N. crassa Scon-2 is
known to be positively regulated by Cys-3 and, consist-
ent with this known regulatory model, it is up-regulated
during plant infection in the R. lauricola transcriptome
analysis (1.8 log2fold up-regulation (3.5x); FDR = 8.9E-9;
Supplemental Table S15). On the basis of homology to
known N. crassa alternative sulfur source regulators, an-
notations of these and other putative regulators are
shown in Supplemental Table S15.
Discussion
Ambrosia beetles and their fungal symbionts generally
colonize dead or dying host trees and thus historically
were not considered a major threat to healthy tree eco-
systems [32]. Laurel wilt, however, has been recognized
as an emerging disease since 2004 and fits the previously
proposed new-encounter model in which native but not
exotic host species tolerate infection by ambrosia beetle
symbionts [33]. The ability of ambrosia beetles and their
fungal symbionts to colonize living trees in their native
habitats in fact has been suggested to have utility in pre-
invasion evaluations to identify potential tree-killing in-
vasive pests [18]. A major challenge is to understand
what factors have driven the evolution of a symptomatic-
ally mild disease in the native range and yet results in a
lethal, tree-killing disease in a newly invaded environ-
ment. With both native and non-native hosts, R. lauri-
cola faces hostile conditions as the beetles delivers its
spores into a living tree with intact defense mechanisms.
Pathogenicity traits may allow these fungi to survive and
proliferate in the unique ecological niche of the living
trees’xylem vessels by initially overcoming or avoiding
the host immune system. Subsequently, when conidia
have been distributed within the xylem, the pathogen
may deploy virulence mechanisms leading to wilting and
increased colonization. When introduced to new,
closely-related but not sympatrically co-evolved hosts,
this balance of attack and defense is tilted in favor of the
pathogen with its novel virulence mechanisms and a
host population lacking the corresponding counter
defense mechanisms. The work presented here has pur-
sued the hypothesis that R. lauricola is an adapted
pathogen on its native hosts in Asia and that these adap-
tations may be uncovered through comparative genom-
ics. Several novel R. lauricola genes have been identified
in support of this hypothesis and provide a starting point
to understand how the fungus induces symptoms and
poses such a serious threat to avocado, redbay and other
members of the Lauraceae family in the western hemi-
sphere. A potential virulence role for several of these
genes is supported by transcriptomic data. The failure to
uncover pathogen transcripts differentially regulated be-
tween the susceptible and tolerant redbay genotypes
may be due to a lack of statistical power resulting from
to the relatively low level of fungal transcripts recovered
from infected trees. Conversely, the fungal infection pro-
cesses, reflected in gene expression, may not differ sig-
nificantly between the two plant genotypes at the chosen
sampling stage. More refined sampling in future studies
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to include additional sampling points and methods to
enrich for fungal transcripts should provide a more com-
prehensive view of both pathogen and host processes oc-
curring in susceptible and tolerant host interactions.
The annotation and comparative genomic resources
established here for the laurel wilt pathogen R. lauricola
and the closely related non-pathogenic R. aguacate pro-
vide the starting material for functional gene analysis.
Vanderpool et al. [37] previously reported assemblies for
these two species from Illumina HiSeq reads resulting in
assemblies of 207 and 414 scaffolds for R. lauricola and
R. aguacate, respectively (GenBank assembly accession:
GCA_002778145.1 and GCA_002777955.1). Ibarra Ca-
ballero et al., [40] also published a draft genome of R.
lauricola isolate C2646 from NextSeq reads resulting in
an assembly of 1535 scaffolds (GenBank assembly acces-
sion: GCA_004153705.1). The draft genomes reported in
this current work improves upon these previous assem-
blies resulting in 169 and 368 scaffolds, respectively. The
current work develops these genomic resources further
by providing gene calls from the new assembly, provid-
ing detailed annotation of comparative gene content be-
tween the two species, and analyzing the transcript
accumulation dynamics of the R. lauricola genes during
host infection.
Comparison of predicted secretomes of the two Raf-
faelea species indicated the presence of secreted protein
genes unique to R. lauricola RL4. Notably, a cerato-
platanin gene homolog was among the pathogen-unique
secreted protein genes. Cerato-platanins act as plant im-
munity elicitors and may function as necrotrophic effec-
tors or pathogen–associated molecular patterns
(PAMPs) [61]. That this well-known plant immunity
elicitors exists in R. lauricola RL4 but not in its non-
pathogenic relative R. aguacate PL1004, leads to the
simple hypothesis that secretion of cerato-platanin by R.
lauricola during its colonization of avocado triggers a
hypersensitive host defense response that contributes to
wilt symptom development. The role of cerato-platanins
in pathogenesis however varies among pathogens from
contributors to necrosis and host defense responses, to
no apparent effect on pathogenicity [52,62]. In addition
to other characterizations of the R. lauricola cerato-
platanin protein, loss-of-function mutants and over-
expression strains for the certao-platanin gene are
currently under development to determine its role in
laurel wilt disease.
Another gene unique to R. lauricola and highly
expressed during plant infection is RL4_JR_08480, a
gene encoding an aerolysin-like protein. The lectin do-
mains of aerolysin-like proteins have been demonstrated
to provide binding specificity within lipid membranes
triggering oligomerization of the natterin domain which
inserts into the lipid bilayer to allow electrolyte leakage
and disrupt membrane function. Members of this family
are pore-forming proteins first described as a pore-
forming toxin from the bacterium Aeromonas hydro-
phila [63]. In numerous bacteria where they have been
characterized they function to kill host cells or other
competing bacterial cells [64]. Aerolysin-like proteins
are now known to be encoded by organisms as phylo-
genetically diverse as fungi, plants and animals [65]. In
many vertebrate and invertebrate animals, they are
thought to play defensive roles against potential patho-
gens but their role in plant pathogenesis has not been
characterized [66,67]. Three characteristics of the R.
lauricola aerolysin-like protein support the hypothesis
that this protein plays a role in R. lauricola virulence: (i)
it is a secreted protein that exhibits very strong struc-
tural homology to other known aerolysin proteins that
function in membrane pore formation, (ii) relative to R.
aguacate, it is unique to R. lauricola and other patho-
genic fungi, and (iii) transcripts encoding the RL-
aerolysin are strongly and significantly up-regulated
during plant infection. More detailed transcript and pro-
tein profiling in the host and beetle mycangia coupled
with the creation and characterization of gene-specific
deletion mutants are planned to test its function.
Besides the cerato-platanin and aerolysin-like genes,
there are several other genes encoding small, secreted
proteins with homology to known virulence factors
unique to R. lauricola. These include seven genes encod-
ing Hce2-domain proteins, whereas its non-pathogenic
relative R. aguacate PL1004 only possesses one. All
Hce2 proteins contain the Ecp2 domain, and based on
protein domains and sequence length, they can be
grouped in three classes: class I contains small secreted
proteins of 80–400 amino acid (aa); class II proteins
contain the modular architecture similar to class I pro-
teins, but they are much longer (up to 800 aa); class III
proteins contain a composite modular architecture with
the Ecp2 domain fused to the C-terminus of fungal sub-
group GH18 chitinases [55]. Among the seven R. lauri-
cola Hce-2 genes, only RL4_JR_00199 (155 aa) matches
the known features of an extracellular effector (class I).
Although RL4_JR_00199 only shares 30% identity at the
amino acid level with the 165 aa C. fulvum Ecp2 effector,
the similar modular architecture between RL4_JR_00199
and C. fulvum Ecp2 effector suggests that the two pro-
teins have an analogous role in plant pathogenesis. Ster-
giopoulos et al. [68] suggested that C. fulvum Ecp2 only
weakly perturbs its virulence target without inducing ne-
crosis. However, the Ecp2 effector of Mycosphaerella
fijiensis, causal agent of the devastating black Sigatoka
disease of banana, causes host necrosis and promotes
virulence much stronger than the C. fulvum Ecp2 [68].
The differences in the virulence functions of Ecp2 effec-
tors from two pathogens has been suggested to reflect
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the co-evolution of pathogens and their hosts: the hemi-
biotroph M. fijiensis Ecp2 can induce necrosis but the
biotroph C. fulvum Ecp2 can facilitate pathogen infec-
tion without inducing necrosis [68]. Similarly, R. lauri-
cola-host interaction in Asia may have fine-tuned Ecp2
activity to only weakly perturb and cause damage to the
native Lauraceae trees in Asia without inducing host wilt
mortality during their co-evolution. In contrast, due to
the lack of co-evolution of R. lauricola and Lauraceae
species in North America, counter defense to Ecp2 ac-
tion may not exist and it and other putative effectors po-
tentially contribute to the wilt mortality. Functional
analysis of this gene should be performed to test this
hypothesis.
Several other predicted, secreted proteins, both unique
and shared with R. aguacate, are encoded and in many
instances demonstrated to be up-regulated during infec-
tion. These too, may function as effectors. Repeat se-
quences in some fungal plant pathogens have been
demonstrated to contribute to the divergence and emer-
gence of novel virulence traits among closely related spe-
cies [49,69]. Characterization of total repeat content of
the two genomes indicated that LTR retroelements are
ten-fold more abundant in the R. lauricola genome.
Whether this increase is associated with variation in ef-
fector or other pathogenicity-related genes awaits the
functional identification of such traits.
Besides toxins, secondary metabolism clusters (SMCs)
are known to produce many compounds with potential
roles in fungal development and ecology or to function
as effectors within host cells perturbing cell signaling
and altering cell morphology [70]. In agreement with the
analysis conducted by Ibarra Caballero et al., [40] com-
parative analysis of SMCs here demonstrated that the R.
lauricola possess significantly more SMCs than the non-
pathogenic species. The difference is most striking for
NRPSs, PKSs, and hybrid PKS-NRPS, important enzyme
families involved in toxin biosynthesis [70]. The signifi-
cantly larger number of PKS and NRPS gene clusters in
pathogenic Raffaelea species is consistent with its ex-
panded capacity for pathogenesis. The expanded array of
PKS-NRPS hybrid clusters in R. lauricola relative to R.
aguacate (7 versus 1) is of particular note. Previous in-
vestigations on the PKS-NRPS hybrids from the rice
blast fungus Magnaporthe grisea and the fungal biocon-
trol agent Trichoderma spp. showed that the PKS-NRPS
hybrid can mediate pathogen recognition and induce
plant defense responses [71,72] . Despite the higher
number of SMCs present in R. lauricola, only two
unique clusters were found to be up-regulated in planta
based on transcriptomic data. These clusters are pre-
dicted to encode a NRPS product and a PKS-NRPS
product. These clusters represent putative toxin biosyn-
thetic clusters but does not fully explain the lack of
expression of other unique clusters in planta. The rela-
tive low abundance of fungal transcripts present in the
sampled tissue as well as the limited sampling of the
interaction may account for the inability to get an accur-
ate assessment of differential gene expression for all
clusters. This lack of resolution is inherent to the inter-
action in which the pathogen is detected at low biomass
and the large woody nature of the host makes it difficult
to spatially sample the host-pathogen interaction. Other
SMCs unique to RL may be of further interest including
Cluster 4 which, based on homology and synteny with
Fusarium spp., appears to encode the pathway for a
polyketide related to fusaric acid.
The infection of R. lauricola induces the formation of
gels and tyloses in xylem lumena [28], which is a com-
mon plant defense response functioning to close off
xylem vessels and lock out invading vascular pathogens
[73–75]. The strategy of deploying virulence factors that
elicit plant defense responses such as tyloses and gums
leading to physiological malfunction, wilting, and host
mortality at the appropriate time, balanced with the
avoidance of recognition early in the interaction is com-
mon with necrotrophic and vascular wilt pathogens [76–
78]. As such, R. lauricola, in addition to offensive effec-
tors, is expected to have masking effectors to avoid the
triggering of PAMP-triggered immunity (PTI) from chi-
tin or other PAMPs.
Chitin is a major constituent of fungal cell walls, and its
fragments, chitin oligosaccharides, are well-documented
PAMPs [79]. Several plant chitin receptors located in the
plasma membrane have been identified. These receptors
contain extracellular LysM domains [80,81]. Fungi too
produce exracellular LysM domain proteins to sequester
chitin oligomers and block host recognition. Predomin-
antly, fungal LysM proteins can be classified into two
groups. In the first group LysMs are associated with chiti-
nase domains (GH18). The second group contains se-
creted LysM effector proteins, e.g. Ecp6, that possess
multiple LysMs but no catalytic domains, [82]. R. lauricola
encodes members of both groups indicating that it has the
ability to hydrolyze chitin as well as a means for protecting
its own chitin from degradation and host recognition.
Interestingly, LysM effectors are not pathogen-specific
and they occur in both pathogenic and non-pathogenic
fungi [83]. These LysM proteins may also help mutualistic
symbiotic microbes, endophytes and other microbes to es-
tablish intimate relationships with their hosts. In patho-
gens, it has been shown in the fungal tomato leaf mold
pathogen C. fulvum that the LysM effector Ecp6 displays a
significant higher chitin-binding affinity than that of plant
immune receptors, and it can prevent fungal cell wall–de-
rived chitin fragments from being perceived by host im-
mune receptors, and thus perturb host immunity [84].
Furthermore, two wheat blotch pathogen, Mycosphaerella
Zhang et al. BMC Genomics (2020) 21:570 Page 15 of 23
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
graminicola, LysM effectors were demonstrated to not
only block the elicitation of chitin-induced plant defenses,
but also prevent fungal hyphal lysis by plant hydrolytic en-
zymes [85]. Thus, fungal LysM effectors may play diverse
roles during host colonization. CAZyme analysis with the
two Raffaelea genomes reported here determined that R.
lauricola possess a significant expansion of LysM domains
relative to R. aguacate PL1004. The remarkable difference
between the number of LysM domains in pathogenic and
non-pathogenic Raffaelea species elicits speculation that
in its native southeastern Asia range, coevolution of R.
lauricola and native Lauraceae trees involves a continuous
arms race, in which R. lauricola LysM effectors have du-
plicated and diversified to avoid host immunity responses
to a point where the fungus may deploy virulence factors
(e.g., cerato-platanin, aerolysin-like protein, Hce2) when it
is spatially and temporally poised to take advantage of the
host resources. This hypothesis may explain why there are
no reports of laurel wilt causing mortality on native Laura-
ceae trees in Asia in that the balance of pathogen recogni-
tion and avoidance of recognition has led to non-lethal
disease symptomology. On the contrary, due to the lack of
coevolution of R. lauricola and Lauraceae trees in the
southeastern United States, the LysM effectors may be so
effective in avoiding host recognition that a buildup in
pathogen colonization is unchecked allowing the deploy-
ment of other effectors and elicitors leading to the over-
stimulation of host defense systems and host physiological
malfunction. Functional analysis of Raffaelea LysM pro-
teins, especially the pathogen-specific secreted LysM pro-
teins would provide a test of this hypothesis and better
define the roles of LysM proteins in ambrosial fungi dur-
ing plant host colonization as well as gallery and mycan-
gial biome dynamics.
In addition to the secretion of proteins and metabo-
lites for establishing compatibility and promoting dis-
ease, pathogens must also adapt their metabolism to that
of the host environment. The transcriptomic analysis
presented here suggests that R. lauricola experiences
sulfur starvation during infection of its host. Inorganic
sulfur is an essential nutrient likely to be available in
very limited supply during xylem colonization. Although
avocado fruit are rich in sulfur, primarily glutathione,
the sulfur makeup in other organs of the plant are not
well characterized. In general, sulfur is taken up by plant
roots in the form of sulfate in the xylem. Glutathione
may also load in tree root-mychorrizal associations and
transport systemically through the phloem [86]. Thus
the availability of sulfur within the xylem is thought to
be primarily or exclusively in the form of inorganic sul-
fate. Alternative sulfur uptake and assimilation pathways
in filamentous fungi are positively regulated by the ab-
sence of elemental and amino acid-based sulfur sources
[87]. The extreme up-regulation of the alternative sulfur
uptake and assimilation genes in R. lauricola implies
that inorganic sulfate is extremely limited in the xylem
and other tissue colonized by R. lauricola during infec-
tion necessitating the pathogen to scavenge sulfur from
alternative, organic sulfur sources.
Organic forms of sulfur within the xylem of healthy
trees may include the phenolic intermediates of lignin
biosysnthesis including p-coumaroyl-CoA, caffeoyl-CoA
and feruloyl-CoA [88] as well as xenobiotic sulfur com-
pounds that may accumulate as defense compounds
[89–91]. Both elemental sulfur [91] and organic sulfur
metabolites e.g., glucosinolates [89] are known to play
roles in plant defense against fungal pathogens. The or-
ganic sulfur content of tree species, particularly their
vascular tissues, is not extensively documented but stud-
ies of sulfur content of Norway spruce identified spectra
consistent with organic sulfate and sulfate esters as
major forms of sulfur accumulated in latewood annual
rings [92]. In addition, in beech trees, sulfate esters were
the dominant form of sulfur accumulated in woody tis-
sue [93]. Thus varying sources of organic sulfur are
present in woody tissues of tree species that, in the ab-
sence of sulfate or other common forms of organic sul-
fur including methionine, may serve as essential sources
of sulfur for colonizing fungi. The competition between
the host and the pathogen for these organic forms of
sulfur is likely to be high during disease development.
Whether R. lauricola is reacting to sulfur starvation con-
ditions or sulfur starvation conditions coupled with
sulfur-based defense is not readily apparent. What is ap-
parent is that R. lauricola has the genetic capacity to
utilize a diverse range of organic sulfur compounds in-
cluding aromatic sulfonates and sulfate esters as well as
aliphatic and alkane sulfonates. This is strongly sup-
ported by gene content and differentially regulation dur-
ing infection. The ability to transport and assimilate
these alternative organic sulfur sources may function as
a competitive advantage for R. lauricola. This hypothesis
is being pursued through characterization of the R. laur-
icola Cys-3 homolog which is known to function as a
positive global regulator of the alternative sulfur assimi-
lation pathways in Ascomycota fungi.
Conclusions
While R. lauricola is presumed to have originated in
Asia and introduced to North America around 2002, R.
aguacate PL1004 was isolated from a dead avocado tree
in Miami-Dade County, Florida in 2009 [35] and has
been isolated subsequently from the mycangia of Xyle-
borus bispinatus collected from avocado trees [94]. X.
bispinatus is an endemic ambrosia beetle species that
can transmit R. lauricola to avocado in Florida [95]. R.
aguacate has been determined to be non-pathogenic on
all hosts that have been screened [96]. Thus, R. aguacate
Zhang et al. BMC Genomics (2020) 21:570 Page 16 of 23
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
and R. lauricola share similar morphology, can be asso-
ciated with the same ambrosia beetle species, are both
recovered from avocado, but differ in their pathogenic
potential. Given the similarities in biology between them,
comparative genomic analysis presented here provides
evidence for the enrichment of traits related to adapted
pathogenesis in the laurel wilt pathogen. These include
evolved strategies to avoid or combat defense mecha-
nisms of living trees and the capacity to secrete putative
effectors, such as cerato-platanin, an aerolysin-like pro-
tein and Hce2, and to produce SMCs to potentially in-
duce necrosis and elicit host defense responses. It also
encodes the ability to adapt its metabolism to the host
xylem. During the co-evolution of R. lauricola pathogen-
icity and Lauraceae tree resistance in Asia, a more bal-
anced host response may dampen symptomology. Due
to the lack of arms race co-evolution of the invasive R.
lauricola pathogen and the Lauraceae family in the
southeastern USA, plant hosts appear to fail in restrict-
ing pathogen spread, allowing virulence factors from the
pathogen to promote colonization and induce a strong
host response including the occlusion of xylem vessels
by tyloses and gel and phenolic compound accumulation
leading to the host mortality. Evidence from these com-
parative analyses and from transcriptomic analysis of R.
lauricola-inoculated redbay trees provides support that
R. lauricola is an adapted pathogen in Asia and the le-
thal symptomology observed in North America is due to
an evolutionary mismatch resulting from a lack of co-
evolution between the host and pathogen in the western
hemisphere.
Methods
Genome sequencing and assembly
Single-end sequencing of the genomes of R. lauricola
RL4 (originally collected from a laurel wilt diseased avo-
cado (P. americana) tree in 2009 on Merritt Island, FL,
USA; CBS-KNAW collection number: 127349) [97] and
R. aguacate PL1004 (originally collected from an avo-
cado tree in 2009 from Miami-Dade county, FL, USA;
CBS-KNAW collection number: 141672) [35] was per-
formed on the Ion Torrent Personnel Genome machine
(PGM) by the Interdisciplinary Center for Biotechnology
Research (ICBR) Genomics Core at the University of
Florida. Ion torrent reads were assembled using the de
Bruijn algorithm implemented in the CLC Genomics
Workbench version 5.0.1 (CLC Bio, Aarhus, Denmark),
MIRA 4 [98], and Spades 3.7.1 [99]. Contig N50 value
and total contig number were used to decide the best as-
sembly. The R. lauricola RL4 and R. aguacate PL1004
genomes were also sequenced using Illumina Hiseq
technology from one pair-end (100 bp) and two mate-
pair (100 bp and 250 bp) libraries. The Illumina reads
were assembled using the ALLPATHS-LG assembler
[38]. Assemblies generated from Ion Torrent and Illu-
mina reads were merged using Metassembler [39]to
achieve a potentially better final assembly. These Whole
Genome Shotgun projects have been deposited at DDBJ/
ENA/GenBank under accessions JACBXF000000000 and
JACCPH000000000. The versions described in this paper
are versions JACBXF010000000 and JACCPH010000000.
Repeat content
RepeatModeler 1.0.8 (http://www.repeatmasker.org/
RepeatModeler.html) and RepeatMasker 4.0.6 (http://
www.repeatmasker.org/) were used to perform the repeti-
tive element analysis. In brief, RepeatModeler, which uses
RepeatScout and RECON [100,101]denovorepeatli-
brary algorithms, was used to generate de novo repetitive
element predictions for the Raffaelea genomes using the
RMBlast NCBI search engine. The generated de novo re-
petitive element predictions and fungal-specific repetitive
element libraries in the RepBase database (http://www.gir-
inst.org/repbase/index.html) were subsequently searched
to identify and categorize repetitive elements.
Transcriptome assembly for gene modeling
Total RNA was extracted from liquid culture grown R.
lauricola RL4 and R. aguacate PL1004. Sequencing was
performed with Illumina HiSeq 2000. We assembled the
RNA-Seq reads into transcripts using genome-guided
and de novo RNA-Seq assembly approaches using Trin-
ity 2.2.0 [41]. Using the de novo and genome-guided
transcriptome assemblies as input, a comprehensive
transcriptome database was generated using the PASA
pipeline [42]. Genome-guided and de novo assembly was
done using Trinity with the “–genome_guided_max_in-
tron 3000”option and the default setting for genome-
guided and de novo assembly, respectively. PASA pipe-
line was run under the default setting.
Gene prediction and annotation
Genes of Raffaelea spp. were predicted by two cycles of
Maker pipeline using the reviewed proteins in Uniprot
database as the protein evidence, and transcripts from
PASA pipeline as additional EST evidence for gene pre-
diction. RepeatMasker (http://www.repeatmasker.org)
was used to mask the repeats in the genome sequence
based on repetitive fungal sequences from RepBase [102]
and repetitive sequences identified by RepeatModeler
(http://www.repeatmasker.org/RepeatModeler.html). In
the first cycle of Maker, only GeneMark-ES v.4.32 was
used. Gene modules predicted by Maker with a strong
annotation quality score (AED = 0) were used for the
SNAP training and Augustus training. In the second
cycle of Maker, Augustus, GeneMark, and SNAP were
employed for gene prediction. To assess the validity of
the final assembly and gene prediction, Benchmarking
Zhang et al. BMC Genomics (2020) 21:570 Page 17 of 23
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Universal Single-Copy Orthologs (BUSCO) was used to
provide an estimate of assembly and annotation com-
pleteness [47].
NCBI’s non-redundant (nr) protein database was used
for BLASTP queries of all predicted gene models to ob-
tain annotation descriptors in addition to InterProScan5
classifications [103] and KEGG GhostKOALA (https://
www.kegg.jp/ghostkoala/). Gene models were also anno-
tated by Blast2GO v4.0 [104] to derive a list of top anno-
tated BLASTP hits. Secretomes of each fungal species
were first predicted using SignalP 4.1 [105], candidates
containing transmembrane helices predicted by TMHM
M 2.0 [106] were removed. Genes encoding putative
carbohydrate-active enzymes were identified by using
the dbCAN Web server (http://csbl.bmb.uga.edu/
dbCAN/blast.php) for automated CAZy annotation
[107]. Sulfur uptake and assimilation related genes were
derived from genes in the KEGG sulfur metabolism ref-
erence pathway (https://www.genome.jp/kegg-bin/show_
pathway?map=map00920andshow_description=show)
and sulfonate transporter genes were identified by
BLASTP homology from the published work of Holt
et al. [108].
Transporters were predicted by querying the Trans-
porter Classification Database http://www.tcdb.org/ by
BLASTP using the R. lauricola predicted proteins. En-
zymes associated with utilization of alternative sulfur
sources were mapped to the KEGG reference map for
sulfur metabolism using a combination of EC numbers,
InterPro IDs and BLASTP homology. Enzyme names
were retained from the reference pathway or the closest
filamentous fungal homolog where available and de-
scribed more fully in Supplemental Table S13. Effectors
were predicted from the R. lauricola predicted secreted
proteins using EffectorP 2.0 [48]. Hmmsearch in the
HMMER3 package was used to identify Raffaelea pro-
teins containing the Hce2 domain (Pfam: PF14856).
CAZy domain information (LysM, CBM18, CBM24,
GH18, and GH55) of Raffaelea proteins was extracted
from CAZy annotation outputs of dbCAN Web server.
The R package gggenes (available at https://github.com/
wilkox/gggenes) was used to provide graphical represen-
tations of protein domain architecture.
Tertiary structure prediction of secreted proteins RL4_
JR_08480 (aerolysin-like) and RL4_JR_05745 (cerato-pla-
tanin) were modeled on the I-TASSER server [109].
Within I-TASSER, the highest scoring model was uti-
lized to identify proteins with structural similarity within
the Protein Data Bank (PDB) [110] using TM-align
[111]). Structural matches with the highest TM-score
are presented. Structural models were viewed and im-
ages downloaded for presentation from the NCBI iCn3D
web-based 3D structure viewer [112]. The 3M3G cerato-
platanin protein structure was obtained from the crystal
structure of the Trichodema virens Sm1protein (DOI:
https://doi.org/10.2210/pdb3M3G/pdb). The Dnl1
aerolysin-like protein dimer was obtained from the
solved 1.86 Å crystal structure from zebrafish (DOI:
https://doi.org/10.2210/pdb4ZNO/pdb; Jia et al., 2016).
The identification of common and species-specific genes
between the two Raffaelea species was performed using
the Reciprocal Smallest Distance (RSD) method [113].
Secondary metabolic gene cluster analysis
The secondary metabolic gene clusters (SMCs) were
identified using the Secondary Metabolite Unknown Re-
gion Finder (SMURF) web-based program [58] and the
antiSMASH pipeline [59]. Non-redundant clusters from
both predictions were combined and manually anno-
tated via BlastP.
Plants and growth conditions
Two clonally propagated genotypes (HIE and HIL) of
redbay trees (Persae borbonia) were used. These clones
were obtained from the native ecosystem on Hunting Is-
land South Carolina under South Carolina State Parks
Research Permit N-06-08 and identified as P. borbonia
by Dr. Marc Hughes and confirmed through microsatel-
lite analysis by Katherine Smith (USDA-Forest Service).
Voucher specimens are housed at the University of Flor-
ida Herbarium. These genotypes, known to vary in their
susceptibility to laurel wilt [23], were grown in five-
gallon containers (4–5 years old) with a dominant stem
2–2.5 cm in diameter and 1–1.5 m in height. Plants were
maintained in the greenhouse with 16-h light and 8-h
dark under ambient temperature conditions (average
temperature ranged from 60 °F to 80 °F). Trees were irri-
gated daily and fertilized as needed. To confirm the cat-
egories of susceptible and tolerant, laurel wilt disease
scores were assessed following trunk inoculation with
wild-type isolate RL4. At 60 days post inoculation, the
average disease score for HIL was 3 with a mortality rate
of 20%, and 5 for HIE with a mortality rate of 100%
(Table S11). Hence, HIE was considered to be a laurel
wilt susceptible genotype and HIL was considered to be
a tolerant genotype.
Fungal cultures for inoculum production and in vitro
growth
Raffaelea lauricola isolate PL571 (GenBank JQ861956.1)
was revived from its glycerol stock by streaking on
cycloheximide-streptomycin malt agar (CSMA) [114].
Cultures were incubated at room temperature (approxi-
mately 23 °C) for seven days. Approximately 10 ml of
sterilized water was added to the surface of the plates
and a spreader was used to agitate the surface gently.
The suspension was collected by pipette and spore con-
centration was measured using a haemacytometer. The
Zhang et al. BMC Genomics (2020) 21:570 Page 18 of 23
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
final suspension was diluted to 1 × 10
6
spores per ml.
For in vitro cultures utilized in the RNA-Seq analysis, a
spore suspension of R. lauricola isolate PL571 was
spread on the surface of a 9 cm cellophane-covered PDA
(potato dextrose agar) culture plate and incubated for
seven days under ambient laboratory conditions (ap-
proximately 23 °C; 10 h light). Fungal tissues (spores and
hyphae) from three separate biological replicates were
harvested into 1.5 ml microtubes, lyophilized overnight
and stored at −80 °C until RNA extraction.
Redbay tree inoculations for disease ratings and RNA-Seq
tissue sampling
For redbay trunk inoculations, two 2-mm-diameter
holes, 1 cm apart, were drilled into each side of the main
stem (7.5 mm deep) at a 45° angle, 15–30 cm above the
soil line. Approximately 50 μlofanR. lauricola isolate
PL571 conidial suspension (ca. 5 × 10
4
) or water (con-
trol) was pipetted into each hole. The inoculation sites
were sealed with Parafilm. For all inoculation assays, the
four treatments consisted of HIE and HIL genotypes in-
oculated with water and HIE and HIL genotypes inocu-
lated with R. lauricola spore suspension. For RNA-Seq
analysis, three days after inoculation, three inoculated
trees of each treatment (12 trees in total) were selected
for sample collection. For each tree, the stem encom-
passing the inoculation sites (5 mm above the upper hole
and 5 mm below the lower hole) and 9 distal leaves 3
each from 3 independent branches were collected. Sam-
ples were immediately placed into liquid nitrogen and
then stored at −80 °C until further processing for RNA
extraction.
To confirm the unpublished susceptible (HIE) and
tolerant (HIL) phenotypes under our greenhouse con-
ditions, five additional trees were rated for laurel wilt
disease for each of the four treatments as described
above at 60 days post inoculation (20 trees in total).
Laurel wilt disease ratings were scored according to
the method of Hughes et al. [30]. The tree inocula-
tion and laurel wilt disease scoring experiment was
repeated once and the ranking of the HIE genotype
as susceptible and the HIL genotype as tolerant was
confirmed.
RNA purification and sample preparation for RNA
sequencing
Tree tissue samples were ground in liquid nitrogen
using a bead beater and Lysing Matrix A (MP Bio-
medicals LLC, Solon, OH). Approximately 50 mg of
each ground sample was used for RNA extraction
using the method of Chang et al. [115]. The RNA
was further treated with DNAase and concentrated
using RNA Clean and Concentrator-5 (Zymo Re-
search). RNA samples were submitted to GENEWIZ
for library preparation and RNA sequencing (Illumina
HiSeq3000, 2 × 150 bp, with PolyA Selection). For
in vitro-grown fungal tissue, approximately 10 mg of
the freeze-dried fungal tissue for each sample was ho-
mogenized using a bead beater. Total RNA was ex-
tracted using the RNeasy Plant Mini kit according to
the manufacturer’s instruction (QIAGEN). The Inter-
disciplinary Center for Biotechnology Research (ICBR)
NextGen DNA Sequencing core, University of Florida
(UF) performed mRNA isolation using NEBNext
Ploy(A) mRNA Magnetic Isolation module (New Eng-
land Biolabs, catalog # E7490) and RNA library con-
struction with NEBNext Ultra RNA Library Prep Kit
for Illumina (New England Biolabs, catalog # E7530)
according to the manufacturer’suserguide.Paired-
end, 2 × 100 cycle sequencing was performed at the
ICBR on two lanes of the Illumina HiSeq3000 instru-
ment using the clustering and sequencing reagents
provided by Illumina (San Diego, CA, USA).
RNA-Seq analysis
Initially, rCorrector [116] and a python script (https://
github.com/harvardinformatics/TranscriptomeAssembly-
Tools) were used to clean up erroneous k-mers and
unfixable read pairs from the sequence reads. Trim Gal-
ore (https://github.com/FelixKrueger/TrimGalore) was
used for quality checking and adaptor trimming of all se-
quence reads. For the inoculated redbay tree samples,
plant reads were obtained by mapping all reads to the
RL4 genome assembly and retaining the un-mapped
reads for Trinity assembly. Trinity [41] with the default
parameters was used to obtain the transcriptome for
each of the two redbay genotypes. The transcriptome
quality was evaluated using BUSCO [47]. Bowtie 2 [117]
was used to map the redbay reads to this assembled
transcriptome. For fungal transcript mapping, TopHat2
[118] was used to map the in vitro fungal reads and the
inoculated redbay tree reads to the RL4 genome assem-
bly. DESeq2 [119] was used for differential gene expres-
sion analysis using the default parameters. RNAseq
sequence data is available through NCBI under accession
PRJNA637370.
Supplementary information
Supplementary information accompanies this paper at https://doi.org/10.
1186/s12864-020-06988-y.
Additional file 1: Supplemental Figure S1. Bioinformatic pipeline
utilized for Raffaelea lauricola and R. aguacate genome assembly and
gene prediction.
Additional file 2: Supplemental Figure S2. Multiple sequence
alignment of Raffaelea lauricola putative cerato-platanin protein
(RL4_JR_05745) and Botrytis cinerea cerato-platanin protein BcSpl1. Arrows
indicate conserved cysteine residues.
Zhang et al. BMC Genomics (2020) 21:570 Page 19 of 23
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Additional file 3: Supplemental Table S1 - Repetitive elements
identified within genome assemblies. Supplementary Table S2.
Predicted effector proteins (EffectorP 2.0) and differential expression for R.
lauricola. Supplementary Table S3. Predicted effector proteins
(EffectorP 2.0) for R. aguacate PL1004. Supplemental Table S4.
Predicted secreted proteins unique to R. lauricola RL4 relative to R.
aguacate PL1004. Supplementary Table S5. Genes encoding secreted
proteins unique to R. aguacate PL1004 relative to R. lauricola RL4.
Supplemental Table S6. Master annotation table with RNAseq data.
Supplemental Table S7.R. lauricola differentially expressed genes.
Supplementary Tabe S8. Number of CAZy family members in two
Raffaelea genomes. Supplementary Table S9. Secondary metabolite
cluster genes in R. lauricola RL4. Supplementary Table S10. Secondary
metabolite cluster genes in R. aguacate PL1004. Table S11. Disease
scores of the inoculated redbay trees at 60 days post inoculation. Table
S12. Read pairs in fungus inoculated stem samples. Table S13.R.
lauricola sulfur transporters. Table S14.R. lauricola and R. aguacate sulfur
assimilation genes. Table S15. R. lauricola alternative sulfur regualtory
genes.
Abbreviations
antiSMASH:Antibiotics and secondary metabolite analysis shell; BLASTP: Basic
local alignment search tool protein; BUSCO: Benchmarking Universal Single-
Copy Orthologs; CAZymes: Carbohydrate-active enzymes;
CBM50: Carbohydrate-binding module 50; CE: Carbohydrate esterase;
CFEM: Cysteine-containing fungal extracellular membrane; CoA: Coenzyme-A;
CSMA: Cycloheximide-streptomycin malt agar; DEGs: Differentially expressed
genes; EST: Expressed sequence tag; ETI: Effector-triggered-immunity;
FDR: False discovery rate; GEgh: Gene Erysiphe graminis forma specialis
hordei; GH: Glycoside hydrolase; Hce2: Homologs of C. fulvum Ecp2
effectorHR; HIE: Hunting Island clone E; HIL: Hunting Island clone L;
HR: Hypersensitive responses.; ICBR: Interdisciplinary center for biotechnology
research; KEGG:Kyoto encyclopedia of genes and genomes; LINE: Long
interspersed nuclear element; LTR: Long terminal Repeat; LysM: Lysin motif;
MAS: Magnaporthe Appressorium Specific; MAT: Mating type locus;
Mb: Mega base; NCBI: National Center for Biotechnology Information;
NPP1: Necrosis inducing protein; NRPS: Non-ribosomal peptide synthetase;
PAMP: Pathogen-associated molecular pattern; PASA: Program to Assemble
Spliced Alignments; PDA: Potato dextrose agar; PDB: Protein data bank;
PGM: Personnel genome machine; PKS: Polyketide synthase;
PL: Polysaccharide lyase; PRRs: Pattern recognition receptors; PTI: PAMP-
triggered immunity; Q20: Sequence quality score of 99%; RMBlast: Repeat
masker basic local alignment search tool; RNA-Seq: Ribonucleotide nucleic
acid sequencing; SMC: Secondary metabolite clusters; SMURF: Secondary
metabolite unique regions finder; SNAP: Semi-HMM-based nucleic acid
parser; SulP: Sulfate permease; TauD: Taurine dioxygenase; TCDF
M: Transporter classification database family members; TM-score: Template
modeling score
Acknowledgements
The authors acknowledge David Moraga and Yanping Zhang from the
University of Florida Interdisciplinary Center for Biotechnology Research for
guidance on experimental design and nucleic acids sequencing services. An
abstract of a version of this work was previously published: Zhang Y,
Vanderpool D, Smith JA, Ploetz, RC, Rollins JA.Genomic insights into the
mechanisms of pathogenesis in Raffaelea lauricola, causal agent of laurel wilt
disease. (Abstr.) Phytopathology. 2018; 108:S1.1. https://doi.org/10.1094/
PHYTO-108-10-S1.1
Authors’contributions
JR and JS designed the experiments. YZ assembled and annotated the
genomes. JZ inoculated trees and generated the RNAseq data. DV and JS
generated genomic data and provided data analysis. YZ and JR analyzed the
comparative genomics data. JZ and JR analyzed the RNAseq data. JR, YZ, and
JZ wrote the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported, in part, by NIFA grant 2015*51181–24257. The
funding body played no role in the design of the study, the collection,
analysis, and interpretation of data or in the writing of the manuscript.
Availability of data and materials
The Whole Genome Shotgun projects have been deposited at DDBJ/ENA/
GenBank under Bioproject PRJNA635322 accessions JACBXF000000000 (R.
lauricola RL4) and JACCPH000000000 (R. aguacate PL1004). The versions
described in this paper are versions JACBXF010000000 and
JACCPH010000000. Genome assemblies, predicted genes and proteins and
mapping files are also available from the Dryad Dataset at https://doi.org/10.
5061/dryad.05qfttf14. The RNAseq datasets generated in the current study
are available in the NCBI repository under accession PRJNA637370. Other
RNAseq datasets utilized during gene prediction in the current study are
available in the GenBank repository under accession numbers SRX3033598
and SRX3033591. Other data sets or sequences utilized in this work can be
found in NCBI under the following accessions: JQ861956.1,
GCA_002778145.1, GCA_002777955.1, SRX3033598, SRX3033591 and
GCA_004153705.1.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Department of Plant Pathology, University of Florida, 1453 Fifield Hall,
Gainesville, FL 32611-0680, USA.
2
School of Forest Resources and
Conservation, University of Florida, Gainesville, FL 32611-0410, USA.
3
Division
of Biological Sciences, University of Montana, Missoula, MT, USA.
4
Present
address: Department of Biology and Department of Computer Science,
Indiana University, 1001 E. 3rd Street, Bloomington, IN 47405, USA.
Received: 14 May 2020 Accepted: 13 August 2020
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