Published July 7, 2016
o r i g i n a l r es e a r c h
Identification and Expression Profiling
of the Lectin Gene Superfamily in Mulberry
Bushra Saeed, Vinay K. Baranwal, and Paramjit Khurana*
Abstract
Core Ideas
Lectins are a diverse group of ubiquitously present, highly specific sugar-binding proteins. Members of this large gene family
have been assigned broad biological functions from defense to
acting as storage proteins. Despite possessing several interesting characteristics, their functions remain essentially undefined.
Mulberry (Morus spp.) known for its medicinal benefits is also a
rich source of lectins. Using an exhaustive hidden Markov model
(HMM)-based search, we identified the lectin gene complement
in M. notabilis C.K. Schneid with around 197 members. These
putative lectin genes were classified into 12 distinct gene families
based on the presence of characteristic sugar-binding domains.
Members of this superfamily were assigned varied gene ontologies (GOs) to identify putative functions and determine cellular
localizations. Interestingly, characteristic expression patterns were
observed across the lectin superfamily in response to a variety
of environmental cues. This is suggestive of specialized functions under diverse conditions possibly by linking the specificity
of sugar recognition with mediating precise stress responses in
plants. The identification of putative gene family members from
the genus Morus developed in this study can find wide applicability in lectin gene identification and characterization. It can also
contribute immensely in the understanding of lectins from mulberry
with potential medicinal uses.
•
•
•
Identification of lectin catalogues in Morus notabilis
genome
Genome-wide expression profiling of lectins
Role of lectins in stress responses in mulberry
L
ectins can be broadly defined as proteins that contain at least one noncatalytic sugar-binding domain
and bind a specific sugar reversibly. Lectins have been
mostly associated with binding glycans for recognition
and defense; however, with recent advances, a new role
for plant lectins in stress responses is emerging. The presence of domains other than the sugar-binding domain
in lectins suggests that these proteins are not mere
sugar-binding proteins but have diverse uncharacterized
functions (Van Damme et al., 2008). Previous studies
have suggested that lectins are synthesized in response
to abiotic and biotic stimulus and insect herbivory (Lannoo and Van Damme, 2010), involved in mediating stress
responses (Zhang et al., 2000), symbiosis (Roberts et al.,
2013), hormone induction (Cammue et al., 1989; Lannoo
et al., 2007; Lannoo and Van Damme, 2010), or signaling
(Jin et al., 2009). Lectins are also implicated in interactions
with histones in response to stress (Schouppe et al., 2011),
providing viral resistance (Yamaji et al., 2012), and having
anticancerous properties (Fu et al., 2011; Ochoa-Alvarez
Published in Plant Genome
Volume 9. doi: 10.3835/plantgenome2015.10.0107
B. Saeed, V.K. Baranwal, and P. Khurana, Dep. of Plant Molecular
Biology, Univ. of Delhi South Campus, New Delhi 110021, India.
Received 28 Oct. 2015. Accepted 12 Apr. 2016. *Corresponding
author ([email protected]).
© Crop Science Society of America
5585 Guilford Rd., Madison, WI 53711 USA
This is an open access article distributed under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Abbreviations: ABA, abscissic acid; AD, aerial drying; cDNA,
complementary DNA; CS, cold stress; GO, gene ontology; HMM,
hidden Markov model; JA, jasmonic acid; RO, reverse osmosis; SA,
salicylic acid.
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et al., 2012). Recently, a lectin receptor kinase 1.9 has
been identified as a critical receptor for extracellular ATP
(Choi et al., 2014). Studies like these indicate the potential
involvement of lectins in diverse responses and are suggestive of functions that have not been yet well elucidated.
Apart from its critical role in the sericulture industry, mulberry is widely popular for its medicinal properties and has been long exploited in traditional medicine.
Mulberry has also been recognized as a good source
of lectins with potent biological activities (Khurana
and Checker, 2011). For instance, two lectins have been
identified in M. alba L. that bind sialic acid present on
the surfaces of pathogenic bacteria and cancerous cells
(Ratanapo et al., 1998). These lectins were later shown to
have antibacterial activity against Pseudomonas syringae pv mori (Ratanapo et al., 2001). Interestingly, two
Jacalins, galactose specific MornigraG and a mannose
specific MornigraM, have been suggested to act as major
storage proteins in the bark of M. nigra L. (Van Damme
et al., 2002). Similarly, galactose-specific lectins (Yeasmin
et al., 2001) and N-terminal sequences of a mannosespecific lectin (Absar et al., 2005) have also been isolated
from mulberry seeds. An antiproliferative lectin, mulberry leaf lectin specific to galactose, galactosamine, and
N-acetyl galactosamine was identified in M. alba leaves
(Deepa and Priya, 2012). Mulberry leaf lectin has been
found to induce apoptosis in breast and colon cancer
cells in humans (Deepa et al., 2012). Recently, galactosebinding lectins have also been found to accumulate
in mulberry laticifers, which is suggestive of a defense
related role (Kitajima et al., 2013).
The biosynthesis, structure, and roles of different
lectin domains have been extensively discussed elsewhere
(Van Damme et al., 1998). Lectins have been recently
described in Arabidopsis thaliana (L.) Heynh., soybean
[Glycine max (L.) Merr.], and rice (Oryza sativa L.) as a
large superfamily containing ~12 families based on the
presence of characteristic sugar-binding domains (Jiang
et al., 2010). Thus, to understand this complex gene
superfamily in mulberry, we identified the putative members from the recently sequenced genome of M. notabilis
(He et al., 2013). By using HMM-based search centered
on the presence of lectin domain, we isolated ~197 putative lectin genes from the M. notabilis genome. Recent
trends have suggested a possible association between
lectin genes and stress responses. Accordingly, their
expression pattern was also investigated under different
stress treatments. The induction of lectin encoding genes
provides experimental evidence that corroborates with
the previous reports of a potential intersection between
lectins and stress responses in plants.
Materials and Methods
Identification of Lectin Genes
Hidden Markov model profiles for domains corresponding to the lectin gene families (Jiang et al., 2010) were
retrieved from Pfam database (December, 2014 version).
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A HMM search was performed using hmmsearch (using
default E-value of 10) from HMMER package 3.1b1 (http://
hmmer.org) on mulberry proteome downloaded from
Morus genome database (Li et al., 2014; http://morus.
swu.edu.cn/morusdb) and sequences were retrieved using
custom written Perl script (Supplemental Data S1). The
sequences from mulberry and corresponding sequences
identified in Arabidopsis, soybean, and rice (Jiang et al.,
2010) were also merged with the previously built HMM
profiles. These sequences were used for domain search
in NCBI Conserved Domain Database (NBCI-CDD)
(Marchler-Bauer et al., 2011) and Simple Modular Architecture Research Tool (SMART) (Schultz et al., 1998;
Letunic et al., 2004) databases; domains were fetched and
aligned using ClustalX and a custom HMM was build.
Finally, the HMM thus generated was used for further
searching the mulberry proteome till no new accessions
could be identified. To remove redundancy, only those
sequences with unique accessions were retrieved.
Structure Prediction, Domain Identification,
and Phylogenetic Analysis
For the identification of gene structure, genomic and
messenger RNA sequences of all putative lectins were
downloaded from Morus genome database (Li et al., 2014;
http://morus.swu.edu.cn/morusdb). Coordinates of corresponding transcripts for all lectin genes identified were
fetched from Morus genome database (Li et al., 2014;
http://morus.swu.edu.cn/morusdb) and a custom written
GFF file prepared. This GFF file along with the genomic
sequences of lectin genes were used in CLC Genomics
Workbench version 6.0.3 for the construction of gene
structures. The lectin genes identified were checked for
the presence of the domains by NCBI-CDD (MarchlerBauer et al., 2011) and SMART (Schultz et al., 1998;
Letunic et al., 2004) searches. The domain sequences
corresponding to the lectin families were employed for
multiple sequence alignment using ClustalX version 2.1
(Larkin et al., 2007) with manual editing. To predict the
evolutionary dynamics, DIVEIN (Deng et al., 2010) web
server was used with the following parameters: substitution model of LG and equilibrium frequencies as optimized. Best of the NNI and subtree pruning and regrafting type of tree improvement was applied. Bootstrap
assessment with 100 replications was performed.
Gene Expression Analysis
Briefly, all the five transcriptomes of M. notabilis representing different tissues (bark, leaf, male flower, root, and
winter bud) were aligned together using de novo aligner
Trinity 20140413p1 (Grabherr et al., 2011). Trinity script
align_and_estimate_abundance.pl included in the same
package was used, which rely on RSEM package (Li and
Dewey, 2011) of R, to estimate the abundance of the transcripts. RSEM-estimated abundance values were used to
construct a matrix with cross sample fragments per kilobase of transcript per million mapped reads (Haas et al.,
2013) normalization. Expression analysis using this matrix
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was conducted using run_DE_analysis.pl script from
Trinity, which uses edgeR package from bioconductor
release 3.0 (Gentleman et al., 2004). Heat maps showing
the expression profiles (log2) for these genes were plotted
using PtR script included in the Trinity package. BLASTX
from blastall version 2.2.26 was used to identify the corresponding transcripts from the assemblies for lectin genes.
Stress Treatments
For expression analysis, mature leaves of M. indica ‘K2’
plants maintained in University of Delhi South Campus
were employed. Detached leaves were immersed in water
solution for various treatments. Second and third leaves
from the apex were employed for various treatments. For
aerial drying (AD), detached leaves were air-dried on
a blotting sheet in a culture room maintained at 28°C
for 6 h. For cold stress (CS), detached leaves were placed
in reverse osmosis (RO) water in an incubator at a temperature of 6  2C for 4 h. For control (Con) treatment,
detached leaves were mock treated by immersing in RO
water at 28C for required durations. For hormonal treatments, detached leaves were placed in 100 μM abscissic
acid (ABA), jasmonic acid (JA), and salicylic acid (SA)
at 28C for 4 h. For simulated dehydration stress (DS),
detached leaves were placed in 0.5 M mannitol for 6 h.
For wounding stress, detached leaves were pricked by
needle and placed in RO water for 6 h.
Quantitative Real-Time Polymerase
Chain Reaction
For the quantification of transcripts, quantitative realtime polymerase chain reaction (PCR) was employed
as described previously (Saeed et al., 2015). Briefly, total
RNA was extracted from stress-treated mulberry leaves
following a modified GITC procedure (Chomczynski
and Sacchi, 1987) and DNase treated using RNeasy plant
mini kit (Qiagen) according to manufacturer’s instructions. First-strand complementary DNA (cDNA) was
prepared from 1 μg total RNA in a reaction volume of
25 μL using high-capacity cDNA archive kit (Applied
Biosystems). Because of the nonavailability of sequences
from M. indica, the available transcriptomes of mulberry,
that is, five transcriptomes of M. notabilis and two leaf
transcriptomes of M. laevigata Wall. ex Brandis and M.
serrata Roxb. (Saeed et al., 2016) were assembled together,
and the sequences thus obtained were used for primer
designing. The primers were designed by using Primer
Express 2.0 software (PE Applied Biosystems) using
default parameters and checked by BLAST tool against
M. notabilis genome and melting curve analysis following
PCR. The PCR was performed in Stratagene Mx3005P
(Agilent Technologies). The data represents average of two
biological replicates with three technical replicates each.
The data was normalized using elongation factor 1α as an
internal control and relative expression values were calculated using ΔΔCT method. List of primers used in this
study can be found in Supplemental Data S2.
saeed et al .: lectin gene su perfa mi ly in mu lberry Table 1. Identification of lectin superfamily in mulberry.
Family
B_lectin
Calreticulin
Chitin_bind_1
Gal_lectin
Gal-bind_lectin
Jacalin
Lectin_C
Lectin_legB
LysM
PP2 (phloem protein 2 )
Ricin_B_lectin
RicinB_lectin_2
Pfam_ID
Members
pfam01453
pfam00262
pfam00187
pfam02140
pfam00337
pfam01419
pfam00059
pfam00139
pfam01476
pfam14299
pfam00652
pfam14200
76
4
9
10
6
23
1
31
21
14
1
1
Analysis of Regulatory Elements in the Putative
Promoters of Lectins
For the promoter analysis, a 1-kb upstream region
(from translation start site) of the 15 lectins analyzed by
quantitative real-time PCR was extracted from Morus
genome database (Li et al., 2014; http://morus.swu.edu.
cn/morusdb). The putative cis-acting elements in the 1-kb
upstream region were analyzed by scanning in PLACE
database (Higo et al., 1999). Different stress-responsive
motifs thus identified were classified as ABA responsive,
MYB binding site, MYC binding site, dehydrationresponsive elements, and cold-responsive elements. The
motifs responsive to JA, SA, and wounding were clubbed
together as biotic-stress-responsive elements. The positions of these elements were marked and custom GFF file
was prepared that was used for construction of promoter
structures using CLC Genomics Workbench version 6.0.3.
Results and Discussion
Identification of Lectin Genes in Mulberry
Genome and Phylogenetic Analysis
An HMM search was employed for the identification of
members of the lectin superfamily in mulberry. Multiple
searches were performed until no new members could be
identified. Domain analysis performed by NCBI-CDD
(Marchler-Bauer et al., 2011) and SMART (Schultz et al.,
1998; Letunic et al., 2004) searches confirmed the presence of the respective domains. This rigorous search led
to identification of a total of 197 putative lectin genes
that were categorized into 12 families (Table 1) following
a previously suggested method of classification (Jiang et
al., 2010). Pfam domains of all but two families, that is,
phloem protein 2 and EEA families, have been previously reported (Jiang et al., 2010). However, with recent
curation, we were able to identify Pfam domains for these
families, that is, PP2 (phloem protein 2 , Pfam14299)
for phloem lectins and RicinB_lectin_2 (Pfam14200)
for EEA family. The EEA family has been referred to as
RicinB_lectin_2 family.
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Fig. 1. Phylogenetic analysis of lectin gene superfamily in mulberry. Respective domains of the different families of lectins from Morus
notabilis were aligned using ClustalX version 2.1 and the phylogenetic tree was constructed using DIVEIN webserver.
Five transcriptomes (bark, leaf, male flower, root,
and winter bud) of M. notabilis (He et al., 2013) were
downloaded from Morus genome database (Li et al.,
2014; http://morus.swu.edu.cn/morusdb) and used to
check the expression evidence of all the members of the
lectin gene superfamily in the respective tissues. Expression evidence for all the putative lectin genes was found
in the M. notabilis transcriptomes possibly because of
the high throughput and wider range of the developmental stages used to generate the transcriptome data. The
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respective domains from all the 12 families were used for
performing the phylogenetic analysis of the lectin gene
superfamily in mulberry. All the 197 putative lectins separated well into 12 clades (Fig. 1) representing each family as described for rice, soybean, and Arabidopsis (Jiang
et al., 2010). Maximum number of members was identified in B_lectin family that also happens to be the largest
lectin gene family in soybean and rice (Jiang et al., 2010).
Ricin_B_lectin, Lectin_C, and RicinB_lectin_2 families
came out to be monotypic gene family in M. notabilis.
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Likewise, Ricin_B_lectin family was also found to have
a single member in rice, soybean, and Arabidopsis (Jiang
et al., 2010). However, Lectin_C family has been reported
to have a single member in rice and Arabidopsis and two
in soybean. Interestingly, in the RicinB_lectin_2 family, seven members in rice, two in soybean, and one in
Arabidopsis have been reported (Jiang et al., 2010). Even
though both Ricin_B_lectin and RicinB_lectin_2 adopt
ricin B-fold, the two have been classified separately.
Based on the phylogenetic analysis performed on the
members of the two families, these members were found
to cluster separately in soybean (Van Holle and Van
Damme, 2015). Several lectins with tandemly arrayed
sugar-binding domains were also identified in Jacalin
and LysM families (data not shown). Such repetitive
domain arrangements have also been observed in other
organisms (Van Holle and Van Damme, 2015). Details
of members from each family along with the sequence
information (obtained from Morus genome database),
subcellular localization predictions (Emanuelsson et al.,
2000), and their corresponding domains (start and end
positions) can be found in Supplemental Data S3.
Gene Structure Analysis
Upon examination of gene structure, it was observed
that majority of lectins contain introns. The maximum
number of introns (20) were identified in Morus008787,
which belongs to the Gal_lectin family (Fig. 2). Out of
76 members in B_lectin family, 35 members were found
to be intronless. Among the B_lectin family members,
Morus008727 was found to have the maximum number
of exons (16 exons and 15 introns). Interestingly, the
longest intron of 27,965 bp was found in Morus006136
from this family. In the Calreticulin family, all the four
members contain introns, with Morus004111 containing
14 exons and 13 introns. Likewise, out of nine members
comprising the Chitin_bind_1 gene family members,
Morus026586 was found to be intronless. Six members of
this family contain two exons, while rest of the members
contain three exons. All the 10 members of Gal_lectin
family contain a large number of exons per gene ranging
from 13 to 21. Morus008787 from this family contains
the largest number of exons (21) among all the predicted
lectin genes. Similarly, in the Gal_binding_lectin family containing six members, Morus000677 was found
to be intronless. Two members (Morus000472 and
Morus021051) from this family contain six and eight
exons, respectively, while the rest of the members contain seven exons each. Of the total 23 Jacalins predicted
in this analysis, 10 were found to have three exons,
while six have two exons. The majority (~65%) of the
members from Lectin_legB are intronless genes, while
Morus021495 from this family contains 10 exons. The
three monotypic families, that is, Lectin_C, Ricin_B_
lectin, and RicinB_lectin_2, have seven, 14, and three
exons, respectively; however, the length of introns varies considerably. Five genes from the LysM family were
found to be intronless, thus a considerable heterogeneity
saeed et al .: lectin gene su perfa mi ly in mu lberry in terms of gene length and exon–intron organization
was observed in all the lectin families.
Identification of Other Functional Domains
Lectins containing domains other than the carbohydrate-binding domain possessing an entirely different
biological activity have been identified (Van Damme et
al., 1998). As described previously (Jiang et al., 2010),
on analysis of domains in the putative lectins, several
other co-occurring domains were identified (Fig. 3).
We observed that the S_Locus_Glyco_protein domain
was associated with the B_lectin family (55.26% members). This domain is also found in receptor kinases and
has been implicated in mediating self-incompatibility
responses in Brassica spp. (Cui et al., 2000). Kinase
domain (90.78% members) has also been found to be
associated with the B_lectin family along with a Pan
Apple domain (68.42% members) that can mediate
protein and sugar interactions (www.ebi.ac.uk). Interestingly, OsSIK2 containing B_lectin, S-Locus Glycoprotein, PAN domain, and an intracellular Ser/Thr
kinase domain has been shown to enhance tolerance
to salt and drought, promote leaf emergence, and delay
leaf senescence (Chen et al., 2013). Association of F-box
domain (57.14% members) with the phloem protein 2
family was also observed as described (Jiang et al., 2010)
in rice (46.4% members), Arabidopsis (56.7% members),
and soybean (82.1%). Phloem protein 2 is abundantly
present in the phloem sap and its association with the
F-box domain suggests a putative role in mediating protein degradation via sugar–protein interactions (Dinant
et al., 2003). O-Glycosyl hydrolase domains, such as
Glyco_hydro_42 and Glyco_hydro_35, were identified
in 90 and 100% members, respectively, of the Gal_lectin
family. These are involved in hydrolysis of the glycosidic
bonds (www.smart.embl.de). Likewise, Glyco_hydro_35
domain was reported to be present in all the members
in rice and soybean and in 69.2% members in Arabidopsis of Gal_lectin family (Jiang et al., 2010). Another
β-galactosidase domain, betaGal_dom4_5, was identified in 30% of Gal_lectin members in mulberry. Lastly,
a Galactosyl_T domain was identified in five out of six
members of the Gal-binding lectin family. This domain
was reportedly found in all the members of the respective family in rice, soybean, and Arabidopsis (Jiang et al.,
2010). However, any of these functional domains could
not be identified in the rest of the lectin gene families.
Association of these domains with the lectin family
members across all the four genera probably indicates a
conserved function, which might be dependent on the
sugar specificity of the lectin.
Gene Ontology Assignment
Gene ontology term assignment, a convenient tool for
annotating novel transcripts, was used for annotating
lectin genes from mulberry. Out of 197 putative lectin genes in M. notabilis, 179 were assigned GO terms:
biological process, cellular component, and molecular
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Fig. 2. Gene structure of lectin genes from Morus notabilis showing exon–intron organization. Members from each family have been
represented in different colors. Boxed arrows represent exons and lines represent introns.
function (Fig. 4). Of the 129 genes assigned the biological process terms, the maximum number of annotations
involved metabolic processes, suggesting possible higher
representation in cellular metabolism. In this category,
lectin genes show an association with primary metabolism processes including carbohydrate metabolism,
N compound metabolism, and other macromolecular
mechanisms. Interestingly, the GO term, response to
stress, was assigned to approximately three genes. Ten
genes were assigned cellular processes GO terms, which
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were associated with cytoplasm, endoplasmic reticulum, and membrane bound organelles (Fig. 4). This is in
agreement with existing literature, which suggests that
apart from the secretory pathway, lectins are also localized in the nuclear and cytoplasmic compartments (Van
Damme et al., 2008). Of the 140 genes assigned molecular function terms, maximum representation was in catalytic activity, binding, kinase activity, ion binding, and
transferase activity (Fig. 4). This observation corresponds
well with our data on the occurrence of other functional
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Fig. 3. Identification of other functional domains and their abundance in lectins from Morus notabilis. Domain analysis was
performed using NCBI-CDD and SMART searches. The different
families have been represented at the x-axis and the types of
domains with the number of members containing those domains
have been represented on the y-axis.
domains in mulberry lectins (discussed elsewhere). Thus,
our GO assignment analysis indicates a wide range of
functions, processes, and organeller localizations that
lectins are possibly involved in. Several GOs identified in
this study will pave the way for finding new functions of
these lectin genes.
Gene Expression Analysis
Despite the diversity and abundance, the functions of
lectins in plants remain largely unknown. To comprehend the biological roles of a protein, it is essential to
understand its expression dynamics spanning a wider
array of tissues. Thus, the expression profiles of the identified mulberry lectins were studied across five transcriptomes of M. notabilis representing different developmental stages. Several distinct clusters of genes with similar
expression pattern were observed across the 12 families
(Fig. 5). A varied pattern of expression was observed in
the largest lectin gene family, the B_lectin family. Maximum number of genes in this family showing upregulation was observed in the leaf tissue followed by male
flower and root tissues. Some root preferential genes were
also identified. In the Lectin_legB family, genes having
relatively higher expression were detected in root, male
flower, and bark, while the largest number of upregulated genes was identified in the leaf. The Jacalin family
members, in general, were found to be highly expressed
saeed et al .: lectin gene su perfa mi ly in mu lberry in the winter bud and bark tissue. Likewise, in the LysM
family, a greater number of genes were expressed in
roots followed by leaf, bark, and male flowers. The single
Ricin_B_lectin family member, Morus027674, was
expressed in the bark tissue. Preferential accumulation
of lectins in the bark suggests a crucial role as a defense
related storage protein. Black locust (Robinia pseudoacacia L.) and elder (Sambucus nigra L.) are known to
accumulate high amounts of lectins in the bark and are
preferentially avoided by rodents and other animals
(Peumans and Van Damme, 1995). Maximum expression was observed in the leaf followed by male flower and
bark and lowest expression in winter bud in the Gal_lectin family. A similar pattern was observed in the phloem
protein 2 family. Interestingly, in Chitin_bind_1 family,
a very distinct pattern of expression was observed; the
maximum upregulation was observed in the male flower
and almost all were downregulated in the winter bud.
This might be suggestive of a specific role of these lectins
in the male flowers. The Gal-binding_lectin family members were found to be root preferential with a very low
expression in other tissues. The expression was enhanced
in leaf tissue and male flowers and was downregulated
in bark tissue and winter buds in the Calreticulin family. The expression patterns of these lectins can aid in
understanding their function by identifying the probable tissues and conditions in which they are expressed.
Though we were able to identify several families showing tissue preferential expression, none of the families
showed a distinct tissue specific expression pattern. This
might suggest functional diversification and specialization of these genes in different tissues. Thus, our analysis
collectively shows the possible differences in expression
patterns of these lectins in the various tissues analyzed.
Expression Profile of Lectin Gene Family
Members Under Various Stress Conditions
Plants have evolved complex expression patterns of genes
in response to various environmental cues. Since recent
studies have shown a possible stress mediated regulation
of lectins, we quantified the expression of several lectins under abiotic and biotic stress treatments. Of the 15
genes analyzed, four belong to the B_lectin family; two
to Lectin_legB, Gal-binding_lectin, Chitin_bind_1, and
Calreticulin families; and a single member from Gal_lectin, Jacalin, and phloem protein 2 families. Quantitative
real-time PCR showed that these genes are differentially
regulated under most of the abiotic stress simulations
such as ABA application, dehydration stress (simulated
by aerial drying and treatment with mannitol), and cold
stress (Fig. 6). Since, lectins have been long associated with
a role in defense responses, the expression was checked
under biotic stress simulating conditions such as JA and
SA application and wounding (Fig. 6). Two members of
Lectin_legB family (Morus021495 and Morus025486)
showed responsiveness to both abiotic and biotic stresses
treatments. Morus021495 was found to be significantly
upregulated by both abiotic and biotic stresses, while
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Fig. 4. Gene ontology term assignment of putative lectin genes in Morus notabilis. Gene ontology terms were assigned across the three
categories: cellular component (CC), biological process (BP), and molecular function (MF).
Morus025486 showed significant upregulation in cold
and dehydration stresses. Similarly, members of Chitin_
bind_1 (Morus026586), Gal_lectin family (Morus013376),
and Calreticulin (Morus004111) families showed significant upregulation under dehydration and ABA application, while the other two members of Chitin_bind_1
(Morus014362) and Calreticulin (Morus005581) families
showed significant upregulation in both dehydration
and biotic stress simulations. The expression level of
Gal-binding_lectins (Morus015660 and Morus021051)
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was significantly induced by ABA application; however,
Morus021051 also showed a significant upregulation in
response to dehydration stress. Morus020123 (Jacalin
family) showed an abiotic stress-specific response with significant upregulation under dehydration and cold stresses.
The expression of Morus006458 from the phloem protein
2 family was induced significantly under cold stress with
slight induction under ABA treatment and dehydration
stresses. Lastly, of the four members analyzed from the B_
lectin family, Morus004886, Morus013708, Morus016962,
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Fig. 5. Heat maps showing the expression profiles of putative Morus notabilis lectin genes in five transcriptomes representing five
diverse tissues (bark, leaf, male flower, root, and winter bud).
and Morus022540 showed a very significant and distinct
responsiveness to dehydration stress treatments.
A modest overlap between dehydration and coldstress signal transduction pathways has been observed
(Yamaguchi-Shinozaki and Shinozaki, 2006). Interestingly, approximately nine genes were induced by dehydration stress (AD and DS) and CS, suggesting a role
in ABA-independent stress responses, while six genes
showed significant upregulation under ABA application and dehydration and cold stress, suggesting a role
saeed et al .: lectin gene su perfa mi ly in mu lberry in ABA dependent stress responses. Consequently, from
the expression analysis, it can be comprehended that
lectins might act in both ABA-dependent and ABAindependent pathways. Similarly, an accumulation of
wheat germ agglutinin in osmotic-stress-treated wheat
seedlings, which was inhibited by fluridone (inhibitor of
ABA biosynthesis), was reported (Cammue et al., 1989).
The expression of reporter gene driven by upstream
regulatory sequence of a B_lectin domain-containing
protein was induced by salt and desiccation stress and
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Fig. 6. Expression analysis of lectin genes under different environmental conditions in Morus indica. Con, treated with reverse osmosis
water for required durations, biotic (red bars) stress simulations (treatment with 100 μM JA and SA for 4 h; WS, wounding stress for 6
h, abiotic stress (blue bars) simulations (treatment with 100 μM abscissic acid for 4 h; AD, aerial drying for 6 h; DS, dehydration stress
by treatment with mannitol for 6 h; CS, cold stress for 4 h. Genes from different families have been highlighted using different backgrounds. The locus id of the best Blast hit from M. notabilis has been shown in the figure. Data represents average of two biological
replicates (with three technical replicates each)  standard deviation. For the determination of significance (p ≤ 0.05), Student’s t-test
(two-sided tests for homoscedastic matrices) was performed using Excel software.
not by ABA, indicating a role in ABA-independent
stress-signaling pathway (Ray et al., 2012). Upregulation of 25 and 45% lectin genes by abiotic stresses such
as cold, drought, and salinity in rice and Arabidopsis, respectively, has been reported (Jiang et al., 2010).
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Significant upregulation of four genes was observed in
biotic stress simulations (JA and SA application and
wounding). A SA-responsive Jacalin domain containing protein LEM2 has been identified in barley (Hordeum vulgare L.) (Abebe et al., 2005). Similarly, induced
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Fig. 7. Cis-regulatory elements in the promoters of lectin genes used for expression analysis. 1 kb upstream region (from translation start
site) of the promoters of all lectins analyzed by quantitative real-time PCR were analyzed using PLACE database. Different elements
such as ABA responsive, Biotic stress responsive (wounding and JA/SA application), cold responsive (LTRE), and dehydration responsive
elements such as DRE, MYB and MYC binding sites were identified.
expression of Nictaba from tobacco (Nicotiana tabacum
L.) was observed after methyl jasmonate treatment and
insect herbivory (Lannoo et al., 2007). The role of lectin
receptor-like kinases (LecRLKs) has been well documented under both abiotic and biotic stresses (Vaid et al.,
2013). In fact, CERK1 (containing both LysM and kinase
domains) has been suggested to be a critical player in
fungal perception (Miya et al., 2007). It was later shown
that CERK1 is a major chitin-binding protein in Arabidopsis and the three LysM domains are important for
chitin binding (Petutschnig et al., 2010). Interestingly,
introgression of Bph3 cluster containing three lectin
receptor kinases (OsLecRLK1-3) into susceptible rice
varieties led to enhanced resistance to both brown planthopper and white back planthopper (Liu et al., 2015).
Likewise, 34 and 32% of the members of rice and Arabidopsis lectin gene families, respectively, were regulated
by fungal and bacterial pathogens (Jiang et al., 2010).
saeed et al .: lectin gene su perfa mi ly in mu lberry Together, these findings suggest a crucial role of lectins
under different stress-responsive pathways in plants.
Analysis of Cis-Acting Regulatory Elements
of Stress Inducible Lectins
Since distinct upregulation of lectins was observed under
abiotic and biotic stress treatments, we analyzed the 1-kb
upstream region (from translation start site) of the 15
lectin genes analyzed by quantitative real-time PCR (Fig.
7). Different regulatory elements involved in dehydration and cold stress signaling, such as ABA-responsive
elements, dehydration-related element, low-temperatureresponsive element, and MYB- and MYC-binding sites
were identified (details presented in Supplemental Data
S4) by searching in PLACE database (Higo et al., 1999).
The ABA responsive elements were found in three promoters, two (Morus004111 and Morus021051) of which
showed significant upregulation after ABA treatment.
Likewise, the promoters of the genes showing significant
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upregulation under dehydration stress harbored dehydration-responsive cis-acting elements such as dehydration-related element and MYB- and MYC-binding sites
. Also, low-temperature-responsive elements were found
in the promoters of Morus21495, Morus025486, and
Morus006458, which showed significant induction under
cold stress. Several lectins (Morus21495, Morus14362,
Morus005581, and Morus22540) were found to be significantly upregulated by biotic stress simulations such as
JA and SA application and wounding. Correspondingly,
biotic-stress-responsive cis-acting elements were identified in the promoters of these genes. Presence of these
cis-acting elements further rationalizes the induction
of these genes by the corresponding treatments. Collectively, our expression data and in silico promoter analysis
strongly suggests a probable role of lectins in both abiotic
and biotic stress signaling.
Conclusions
Despite the extensive research on plant lectins, their
biological roles are hitherto vaguely defined. Nevertheless, given the ubiquitous occurrence and the structural
diversity of lectins, it is discernable that they might
play numerous decisive roles. Thus, identification and
classification of the lectin complement at the wholegenome level can play a critical role in advancing our
understanding of this very diverse superfamily. In the
present study, we identified 197 putative lectin genes
from mulberry, which is recognized as a rich source of
lectins. These putative lectin genes were classified into 12
families based on the presence of corresponding lectin
domains. Out of 197 putative lectin genes, 64 were found
to be intronless, while genes with up to 20 introns were
also identified, implying a high heterogeneity at the level
of gene organization. Association of other functional
domains with some families was also observed, which
might reflect a wider range of biological functions. Correspondingly, GO assignment was performed to annotate
the newly identified members, which implies that lectins
are involved in a plethora of biological roles in different cellular compartments. This also suggests that sugar
specificity lies at the center of these cellular responses.
As stated earlier, lectins have been suggested to be
responsive to different stresses; our analysis confirms the
upregulation of lectins in response to abiotic and biotic
stress treatments. Collectively, the information generated
in this analysis can prove beneficial in determining the
functional roles of lectins in plants, in general, and mulberry in particular.
Supplemental Information Available
Supplemental Data S1: Perl script used for sequence
retrieval.
Supplemental Data S2: List of primers used in the
present study.
Supplemental Data S3: Details of lectin gene family
members.
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Supplemental Data S4: Details of cis-acting elements
found in the promoters.
Author Contributions
BS and VKB performed the in silico analysis. BS performed the experiments. BS, VKB, and PK analyzed the
data. BS and PK wrote the manuscript. All authors read
and approved the manuscript.
Acknowledgments
BS acknowledges Council for Scientific and Industrial
Research (CSIR) for Senior Research Fellowship. This
work was supported by grants from the Department of
Biotechnology, Government of India. The authors thank
the reviewers for improvement of the manuscript.
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