The for gene as one of the drivers of foraging variations
in a parasitic wasp
Genomic bases underlying foraging in parasitoid
Aurore Gallot1*, Emmanuel
Desouhant1, Vincent Lhuillier1,
David Lepetit1, Adil El Filali1,
Laurence Mouton1, Cristina
Vieira-Heddi1, Isabelle Amat1.
1 Université de Lyon, Université Lyon1, LBBE –
Laboratoire de Biométrie et Biologie Evolutive – UMR 5558, CNRS,
Villeurbanne, France
*Corresponding author:aurore.gallot@univ-lyon1.fr,
https://orcid.org/ 0000-0003-4552-090X
ABSTRACT
Foraging behaviours encompass strategies to locate resources and to
exploit them. In many taxa these behaviours are controlled by a major
gene called for, but mechanisms vary between species. In the
parasitoid wasp Venturia canescens , sexual and asexual
populations coexist in sympatry but differ in their foraging behaviours.
Here we explored the molecular bases underpinning this divergence in
foraging behaviours by testing two mutually non-exclusive hypotheses:
firstly the divergence in the for gene results in difference in
foraging strategies, and second this latter is due to a divergence in
whole-genome expression. Using comparative genomics, we showed that thefor gene was conserved across insects considering both sequence
as well as gene model complexity. Polymorphism analysis did not support
the occurrence of two allelic variants diverging across the two
populations, yet asexual population exhibited less polymorphism compared
to the sexual one. Sexual and asexual transcriptomes sharply split up,
with 10.9% of differentially expressed genes, but these were not
enriched in behavioural related genes. We showed that the forgene was more expressed in asexual female heads than in sexual ones, and
that asexuals were the ones that explored more the environment and
exploited more host patches. Overall, these results suggested that a
fine tuning in the for gene expression between populations may
have led to distinct foraging behaviours. We hypothesized that
reproductive polymorphism and coexistence in sympatry of sexual and
asexual populations specialized to different ecological nichesvia divergent optima on phenotypic traits, could imply adaptation
through different expression patterns of the for gene and at many
other loci throughout the genome.
Keywords: behavior, foraging, hymenoptera, transcriptomic, populations.
1 INTRODUCTION
Within a population, individuals tend to exhibit similar traits given
than sexual reproduction, through meiosis and fecundation, homogenizes
genotypes and thus prevent from phenotype divergence. Loss of sexuality
have been frequently recorded in a diverse array of eucaryotic taxa with
three possible origins leading to the emergence of asexual lineages:
mutation, hybridization (Normark, 2003) or endosymbiotic infection
(Stouthamer et al., 1990). When reproductive modes are exclusive;
asexuals start to diverge by accumulating genetic mutations since they
no longer exchange gene flow with the sexual population from which they
originated. Competitive interactions should favor one reproductive mode
over the other (Lively, 2010). Asexuals have a demographic advantage by
producing only females, they avoid the cost of males (Maynard-Smith,
1978). In contrast, sexual populations maintain greater genetic
diversity which may confer a decisive advantage in changing environment
(Otto, 2009). If geographical or ecological heterogeneity allows
ecological specialisation, with each lineage performing better in a
specific habitat, sexual and asexual populations can coexist in
different geographical areas or sympatrically (Bell, 1982; Lynch, 1984).
Such coexistence of sexual and asexual lineages is called reproductive
polymorphism. In this case, adaptations in behavior, morphology or life
history traits, should distinguish sexual from asexual populations.
Such cases of reproductive polymorphisms have been widely reported in
haplodiploid arthropods. Van der Kooi et al. described in an exhaustive
database 765 parthenogenetic species, among which 143 presented evidence
of sexual lineages as well, representing 19% of the described species
having reproductive polymorphism (van der Kooi et al., 2017). Although
this proportion is likely to be underestimated, this nevertheless
indicates the frequent occurrence of the coexistence between sexual and
asexual populations. Thus, the competitive exclusion of one or the other
reproductive modes is not the norm, the ecological conditions allowing
their coexistence seems to be frequently met. In the hymenopteran
parasitoid Venturia canescens (Ichneumonoidea : Gravenhorst)
asexual populations coexist in sympatry with sexual populations
(Beukeboom et al., 1999; Schneider et al., 2002) each better adapted to
specific ecological niches (Amat et al., 2017). In particular,
divergence in the foraging behaviours have been shown in many population
pairs coming from different localities by a meta-analysis (Amat et al.,
2017). Asexual wasps have a better capacity than sexual wasps to exploit
their environment given their higher capacity to find hosts (Liu et al.,
2009), a larger egg load and their ability to lay eggs faster (Pelosse
et al., 2007). In contrast, sexual wasps explore better their
environment than asexual wasps as they flight longer and faster, have
higher energy content, and live longer (Lukáš et al., 2010). V.
canescens asexual reproduction involves a central fusion automictic
parthenogenesis, which means that some genetic recombination occurs
during the early stages of oogenesis. Thus, genetic variation still
exists between asexual offspring’s even if an irreversible increase of
homozygosity in populations occurs over time (Beukeboom and Pijnacker,
2000; Mateo Leach et al., 2009). The divergence in foraging behaviours
observed between sexual and asexual wasps V. canescens is
certainly based on genetic divergence between the two populations, since
no more genetic exchanges through mating occurred in natural populations
(Mateo Leach et al., 2012).
Genetic control of foraging behaviours has been mainly studied inDrosophila melanogaster where two distinct types of strategies
have been characterized (Allen et al., 2017; Anreiter et al., 2017; de
Belle and Sokolowski, 1989; Osborne et al., 1997; Sokolowski, 1980).
While sitters hug the boundaries of a food patch but remain focus within
one food patch, rovers travel greater distances within and between food
patches, thus exploring widely their environment and exploiting more
food resources (Sokolowski, 1980). The two strategies are under the
control of a major gene called foraging (for) . Despite the many
genes involved in generating foraging behaviours (Anreiter et al.,
2017), manipulations of the for expression are sufficient to
modify them (Osborn et al., 1997). The control of foraging behaviours by
the for gene has been demonstrated in drosophila larvae as well
as in adults, and encompass both searching for food resources and
oviposition sites (Edelsparre et al., 2014; McConnell and Fitzpatrick,
2017). The for gene has two allelic variants conserved during
evolution: rovers have at least one dominant allele
(for R), while sitters have the two recessive
alleles (for S). Both alternative behaviours are
maintained by selection; patchy food and high population densities
advantage rovers, while evenly distributed food and low population
densities advantage sitters (Sokolowski et al., 1997). Genotype
differences between rovers and sitters are reflected by differences in
the for gene expression, higher in rover heads than in sitters,
and so is the enzymatic activity of the corresponding protein PKG
(Osborn et al., 1997). The role of the for gene as a single major
gene influencing foraging behaviours has been characterized in many
animal species. Orthologs of the D. melanogaster for gene
influence foraging behaviours in taxa as diverse as nematodes (Hao et
al., 2011; Hong et al., 2008) or mammals (Struk et al., 2019). Most of
the studies on genetic control of foraging behaviours has been conducted
on insects species, such as diptera (D. melanogaster , Aedes
aegypti (Keating et al., 2013)), hymenoptera (Apis mellifera(Ben-Shahar et al., 2002), Bombus terrestris (Tobback et al.,
2011), Pheidole pallidula (Lucas and Sokolowski, 2009),Pogonomyrmex barbatus (Ingram et al., 2005), Vespula
vulgaris (Wenseleers et al., 2008), orthoptera (Schistocerca
gregaria (Lucas et al., 2010)), lepidoptera (Sesamia
nonagrioides (Chardonnet et al., 2014)). In all those species, thefor gene contributes to foraging behaviours. However, the
existence of allelic variants as well as the relationships between thefor expression level and foraging behaviours exhibit variations
between species. For example, within Hymenoptera, the eusocial honey bee
(A. mellifera ) displays caste division where young workers take
care of the hive, whereas older workers of the colony are foragers.
Albeit only one allele of for has been identified in this
species, foragers exhibit higher gene expression associated with a
higher corresponding PKG activity (Ben-Shahar, 2005). A same
overexpression of the for gene have been shown in B.
terrestris (Tobback et al., 2011), phylogenetically related to honey
bee. In contrast, for expression was found to be higher in nurses
than in foragers in three other eusocial hymenopteran species with a
same age-dependent division of labor: the ants (P. barbatus ,P. pallidula ), and the common wasp (V. vulgaris ) (Ingram
et al., 2005; Lucas and Sokolowski, 2009; Wenseleers et al., 2008).
Although influence of foraging behaviors by the for gene has been
maintained during evolution, the underpinning mechanisms variate with
opposite patterns within eusocial Hymenoptera species. Studying the
genetics of the foraging behaviours on additional hymenopteran species
would make it possible a better understanding of their evolution in this
taxon. V. canescens that belongs to the Ichneumonoidea, a
parasitoid superfamily basal within the Apocrita group which include all
other eusocial hymenopteran species (bees, ants and wasps) (Peters et
al., 2017), appears to be a relevant model for studying the genetic
bases underlying the variability of foraging behaviours and their
evolution within Hymenoptera.
Here, we investigated the genetic bases underpinnings the variability of
foraging behaviours observed between sexual and asexual V.
canescens populations. We explored two non-mutually exclusive
hypotheses that could explained the divergence observed in foraging
behaviours: firstly, a divergence in the for gene, and second a
divergence in whole-genome expression. We first proceed to the
characterization of the for gene in the V. canescens using
genomic and transcriptomic sequences: 1) we described the fororthologous and reconstructed its evolution in insects; 2) we annotated
the full gene model by analyzing sexual and asexual transcriptomes; 3)
we described allelic variations in sexual and asexual populations. We
explored the second hypothesis by studying the differential gene
expression between sexual and asexual populations, with a special focus
on the behavioral genes. Finally, we tested whether variations in thefor gene expression could explain the observed variations in
foraging behaviours between sexual and asexual populations, by coupling
a behavioral experiment with the for gene quantification.
2 MATERIALS AND METHODS
2.1 Field sampling and insect rearing
V. canescens is a solitary endoparasitoid of caterpillars of
pyralid moths (Salt, 1976). The females used in the experiments come
from sexual and asexual populations collected annually near Valence
(N44°58’21”, E4°55’39”). In this unique location, individuals of the
sexual population were usually sampled in an orchard, while individuals
of asexual population were mostly collected close to grain silos.
Caterpillars of Ephestia kuehniella (Zeller) were left a week
exposed to parasitoids, then brought back to the laboratory waiting the
emergence of parasitoids. Virgin emerging V. canescens females
were isolated and left with hosts in order to sexed their progeny. InV. canescens sex determination is haplodiploid: sexual females
have a parthenogenetic arrhenotokous reproduction, i.e. unfertilized
eggs produce haploid males while diploid females resulted from
fertilized eggs. Thus, virgin arrhenotokous females produce only males.
In contrast, virgin asexual thelytokous females produce only females.
Sexual and asexual wasps were maintained separately on the host E.
kuehniella feed on semolina, were they produced kairomones attracting
for parasitoids from mandibular gland secretions (Castelo et al., 2003).
Insects were grown under constant environment (25 ± 1°C, 55 ± 5 % RH,
12:12 LD).
2.2 Annotation of the for gene in V. canescens genome
Orthologs, i.e. genes descended from the same ancestral sequence
separated by a speciation event, often have the same function, hence we
first searched the orthologs of the for gene in the genome ofV. canescens . A set of 40 orthologs for sequences from 38
insect species, as well as the branchiopoda Daphnia pulex and the
mouse (Mus musculus ) sequences, were identified using ortholog
annotation in EnsemblMetazoa database and literature (table S1). To
identify for ortholog in V. canescens genome, we used the
reciprocal best hits with tblastn with a set of 42 for orthologs
protein sequences previously described as query, and the V.
canescens genome as database
(http://bipaa.genouest.org/sp/venturia_canescens/V.1.0). The for gene that was localized on the scaffold 64,
contained the longest open reading frame (Vcan27709 ) constituted
of 2,445 nucleotides encoding 815 amino acids.
2.3 The for gene phylogenetic reconstruction in insects
The putative V. canescens for sequence was added to the
set of 42 orthologs for , then aligned using MUSCLE (Edgar, 2004).
The corresponding protein alignment diverged in N-terminal but was
conserved in C-terminal. Alignment was manually curated, most conserved
residues were selected using Gblock, the resulting alignment consisted
of 533 amino acids. To reconstruct the for phylogeny and position
the V. canescens for among other insect sequences,
ProtTest v3.4.2. was used to determine the best-fit model of protein
evolution using AIC (Abascal et al., 2005). JTT model of protein
evolution was used and topology optimization was carried out using best
of NNI and SPR options. The phylogenetic tree was constructed with
maximum likelihood method using PhyML implemented in Seaview (v 4.7)
(Gouy et al., 2010). Default aLRT (SH-like) was used for branch support
(Anisimova and Gascuel, 2006).
2.4 RNA extraction and sequencing
A total of 6 RNA-seq libraries were prepared: sexual and asexual
populations were constituted both by 3 biological replicates. Each
replicate was constituted of a pool of 30 individual heads taken from
emerging females and flash frozen, next used as an input for RNA
extraction. Heads were crushed using steel beads and Qiagen TissueLyser
(45s, 25hz). Total RNAs were extracted using Rneasy Mini Kit (Qiagen)
following the manufacturer protocol and including the DNase step. RNA
integrity was controlled using gel electrophoresis and quantified with
Nanodrop. After integrity control and quantification, polyadenylated
RNAs were enriched from 1 μg of high-quality total RNAs with oligo-dT
magnetic beads, then fragmented and converted to cDNAs (Illumina TruSeq
Stranded mRNA Library Prep kit). Fragments around 200bp were selected,
adapters ligated, and fragments amplified by PCR to generate DNA
colonies. Each library was labelled, multiplexed and pooled for
sequencing on a HiSeq 2500 Illumina sequencer (Fasteris, Switzerland),
with a paired-end protocol (2x150bp).
2.5 The for gene model reconstruction
We identified all the isoforms of for transcript and
reconstructed the for gene model in V. canescens by
screening the 6 RNA-seq libraries from sexual and asexual populations
and focusing on the for reads. KisSplice 2.5.4. (Sacomoto et al.,
2012) is a method based on De Bruijn graphs that allows identification
of all variants without using a reference genome, including single
nucleotide polymorphism (SNPs), indels and alternative splicing events.
In parallel, we built a de novo transcriptome assembly with
Trinity (Haas et al., 2013).
2.6 Polymorphism analysis at the for locus
To evaluate the for gene polymorphism, we localized all the SNPs
based on the list of all the SNPs, insertions and deletions across all
the for isoforms, previously identified with KisSplice. We then
used KisSplice2RefTranscriptome to position each SNP on forisoforms. Finally, we used the R package KissDE in order to find SNPs
that significantly differed in frequency across sexual and asexual
populations (adjusted P -values<0.05).
2.7 Differential expression analysis
The genome-wide divergence between sexual and asexual populations was
estimated using RNA-seq libraries to identify differentially expressed
genes (DEGs) between the two populations. Reads quality was first
assessed with FastQC, then reads were trimmed and filtered using
trimmomatic with minimum length set to 75pb. After filtering, the
transcriptomic dataset included a total of 91 millions of reads of which
an average of 92% were successfully aligned on V. canescenstranscriptome using HiSat2 (Kim et al., 2019) (table S2). Genes with
differential expression between sexual and asexual populations were
identified using negative binomial GLM implemented in the program DESeq2
(Love et al., 2014). We tested for differential expression of all
transcripts with an average level of expression superior to 10 reads per
gene (n =14,106). A gene was considered differentially expressed
(DE) when the false discovery rate (FDR) adjusted p- value was
inferior to 0.05, without applying supplementary fold change threshold.
2.8 Functional analysis
The de novo transcriptome was annotated using BLAST and Gene
Ontology tools to assign biological function to transcripts. Then, we
focused our analysis on the transcripts related to the ‘behaviour’ GO
term or to any of its child terms, thus annotating a functional group of
transcripts related to behaviour. This list of transcripts was crossed
with the previously established lists of DEGs between the two
populations.
2.9 Behavioural experiment
We set up an experimental design to quantify exploitation and
exploration of host patches by individuals from sexual and asexual
populations. Experimental device contained two host patches placed 20 cm
far from each other inside a box (50 x 16 x 8 cm) with 2 side holes
covered with veils to allow ventilation. The two host patches were made
of Petri dish (5.5 cm Ø) containing six 21-days old larvae of E.
kuehniella and semolina to the rim, prepared seven days before the test
and covered with a thin gauze to prevent larvae from escaping. Each host
patch was embedded in clean semolina in the middle of a bigger Petri
dish (13 cm Ø). Every morning, wasps were collected at the emergence and
placed individually in tubes with one drop of water. The day after,
males and females of the sexual strain were gathered in a cage to mate.
Females were observed and gradually picked up in a tube as they have
mated until the behavioural experiment. In the meantime, emerging
asexual females were placed in another cage in the same conditions. At
the beginning of the experiment a single female was inserted in the box
and deposited in the middle of the left patch, called ‘patch 1’, whereas
the right patch was called ‘patch 2’. A total of 34 females (17
asexuals, 17 sexuals) were tested in random order. Foraging behaviours
were followed during 20 min by recording 4 metrics with Jwatcher
(Blumstein and Daniel, 2007): i) probing, wasps probed the substrate
with ovipositor once presence of hosts detected thanks to kairomones;
ii) cocking, a peculiar movement of the abdomen observed after egg
laying, when the female load of a new egg at the tip of its ovipositor
(Rogers, 1972); iii) moving outside of patches (i.e. flying or
walking); and iv) time dedicated to hosts, next called patch residence
time (PRT) i.e. sum of the time spent on patch 1 and patch 2. The
female was considered to have left a patch when more than 150 seconds
was spent outside of the patch, hence PRT includes short excursions
outside patch boundaries. Exploitation was considered as the capacity of
females to find hosts within patches. Host patches exploitation has been
measured by the means of 2 parameters: i) total PRT was used as a
synthetic parameter to summarize the exploitation of the two patches
(sum of PRT on patches 1 and 2); ii) the total number of ovipositions,i.e. the number of cockings, used to assess the success of
exploitation. Exploration was considered as the ability to visit the
entire experimental device (i.e. environment) and has been quantified
using two parameters: i) the proportion of females that manage visiting
the two host patches, considered as the aptitude to locate new
resources; ii) the number of switches between the two host patches,
considered as the ability to navigate between different resources.
Immediately after behavioural experiment, all the 34 wasp heads were
individually collected to quantify expression of the for gene,
while abdomens were dissected to count the number of eggs in the
ovarioles, next called egg load. Heads were stored on ice in 10 µl of
RNA-later (Sigma-Aldrich), then at -20°C until RNA extraction.
2.10 Quantification of the for gene expression
We quantified the for gene in each individual wasp head using
RT-qPCR to be able to correlate foraging behaviours with the forgene expression. Once all samples collected, the 34 RNA extractions were
performed in one batch by series of 12 randomized samples, using the
protocol described above. First-strand cDNA was synthesized from 70ng of
total RNA using SuperScript III first strand synthesis system
(ThermoFisher scientific) with random hexamer primers, and followed by a
RNAse-H step. Quantification was conducted on the for gene,
together with two reference genes (rpl32 and gapdh ) used
for normalization between samples to control variations in extraction
yield, reverse transcription yield, efficiency of amplification.
Reactions were performed on a CFX-96 (BioRad) using 1:10 diluted cDNA
and SYBR Green master mix (BioRad), according to the manufacturer
instructions. Amplification conditions were a first step of denaturation
(95°C, 1 min) followed by 40 cycles of denaturation (95°C, 10 sec) and
elongation (melting temperature, 30 sec). Details on primers and melting
temperatures were listed in table S3. Fluorescence was quantified at the
end of each cycle, and the quantification cycle (Cq)
corresponding to the start of exponential phase amplification was
measured. Each sample was quantified twice: all duplicated
Cq values varied less than 0.5 cycle, indicating an
elevated replicability. The expression level of the for gene was
determined relatively to the expression level of both reference genesrpl32 and gapdh, using ∆∆Cq method (Livak
and Schmittgen, 2001). Results were consistent whatever the reference
gene used, and both rpl32 and gapdh provided satisfactory
quality control (low Cq values and low variations across
samples) (figure S1 and table S4). Therefore, we finally used the mean
Cq between rpl32 and gapdh for
normalization to increase precision of the results. The forexpression values were expressed using relative values comparing each
individual to the median individual, considered as the value 0. Negative
values indicated thus individuals with for expression lower than
the median, and positive values indicated individuals with forexpression superior to the median.
2.11 Statistical analysis
The foraging behaviours, decomposed into exploitation and exploration,
each measured by a set of parameters previously defined, were analyzed
using Generalized Linear Models (GLM). The population (sexual or
asexual), the for gene expression (fold change), the egg load (a
proxy for parasitoid fitness (West et al., 1996)), and the double
interactions with the variable population were included as predictor
variables. PRT was analyzed with GLM with a Gamma distribution for
errors and inverse link. Number of switches between host patches was
analyzed with GLM with a Poisson distribution and log link. Number of
cockings was also analyzed with GLM with a Poisson distribution for
error and log link. PRT was added to the full model since cocking
probability increase with PRT. The for gene expression was
analyzed with linear model using population, egg load and their
interaction as explanatory variables. Least contributive variables in
all models were iteratively removed using backward selection to select
optimal models. All statistical analyses were performed with R (R Core
Team, 2017).
3 RESULTS
3.1 Identification of the for gene in V. canescens genome
and for gene evolution in insects
We identified a sequence candidate to be for ortholog in theV. canescens genome, and then aligned it to a set of fororthologs in order to reconstruct the evolutionary history of thefor gene. The resulting maximum likelihood tree robustly related
the major represented insect clades: hymenoptera, orthoptera,
coleoptera, diptera, lepidoptera (figure 1A). A majority of one-to-one
orthologous relations was detected, with the exception of rare
duplication events. All ten sequences from hymenopteran species
constituted a monophyletic group highly supported (bootstrap value
> 95%, figure 1A). Within this group, V. canescens(Ichneumonidae) clustered with Nasonia vitripennis (Chalcidoidea)
to constitute the parasitoida group. The phylogenetic reconstruction
confirmed that one unique sequence within the V. canescens genome
was ortholog to the for gene in D. melanogaster , and was
then annotated as the V. canescens for gene (Vcan_for) .
3.2 Characterization of the for gene model in V. canescens
We produced RNA-seq libraries from sexual and asexual populations with a
triple objective: i) reconstruct the for gene model, i.e.the region of the gene that is supposed to be transcribed into RNA; ii)
evaluate polymorphism at the for locus within sexual and asexual
populations, and iii) assess genome-wide differences in gene expression
between the two populations. To produce an accurate model of thefor gene, we thus screened the RNA-seq libraries from sexual and
asexual female heads searching for all reads mapping on this locus and
reconstructed all the transcripts. We identified four separate
transcription start sites, supporting a gene model that contains four
independent promoters (pr1 -pr4 ) corresponding to four
distinct open reading frames (figure 1B). The longest open reading frameVcan27709 started with pr1 , exhibited 7 isoforms that
mainly differed in their untranslated regions (UTRs). Vcan27708transcript started with pr2 and showed 4 isoforms, whileVcan27707 (pr3 ) possessed 5 isoforms. Finally, the
shortest transcript Vcan27706 starting with pr4 presented
one isoform. Overall, a total of 13 exons were identified whose
different combinations constituted 17 different isoforms. The 9 first
exons exhibited alternative splicing, thus isoforms essentially differed
in their 5’ UTR and the corresponding N-terminal coding sequences. In
contrast, the last 4 exons were constitutive of all isoforms (exceptedVcan27707_i12, Vcan27709_i14, Vcan27708_i17; that contained an
early stop codon), and constituted one unique 3’ extremity (figure 1B)
encoding the C-terminal part of the protein, containing the two
cGMP-binding domains as well as the kinase domain.
3.3 Allelic variation at the for locus between sexual and asexual
populations
We focused on the population polymorphism at the for locus, by
screening RNA-seq libraries based on 90 females from sexual and asexual
populations, we identified a total of 15 single nucleotide polymorphim
(SNP) (table 1). Only 3 SNPs were located within the coding region,
including 2 synonymous SNPs and one single non-synonymous mutation. The
12 remaining SNPs were located outside of coding sequences, within UTRs.
Among the 15 SNPs, 14 variants exhibited significant differences in
frequency between sexual and asexual populations (table 1). All those
variants were polymorphic in sexual population, while nine were fixed in
asexual population. Together, these results do not support the existence
of two allelic variants differing between sexual and asexual
populations. We rather described a variety of polymorphic sites
accumulated all along the locus, with an important reduction of
polymorphism detected in the asexual population. Moreover, the protein
sequence was little affected by polymorphism, with only one non
synonymous variant recorded and located outside of the functional sites.
Nonetheless, the numerous polymorphic sites reported all along thefor gene could affect the transcription or the alternative
splicing of the gene rather than the sequence of the encoded protein
itself.
3.4 Genome-wide expression divergence across sexual and asexual
populations
Overall, we found that gene expression strongly diverged according to
sexual or asexual population. The principal component analysis based on
the expression of all the genes showed that the first axis separated
sexual from asexual population and explained 82% of the total variance
(figure 2A). Among the 14,106 transcripts that passed the expression
filter, a total of 1,539 genes were DE (P -adj<0.05)
between sexual and asexual population, representing 10.9% of the
transcriptome. The for transcript, represented in the
transcriptome by its longest isoform (Vcan27709transcript) , was not included within this list of DEG (rank
2,507/14,106, P -adj = 0.168) (figure 2B). Although theP -adj value being above the significance level, the analysis of
normalized counts of the for transcript across the 6 libraries
showed that for expression was about 10% higher in asexual
compared to sexual population (figure 2C). None of the 3 othersfor transcripts (Vcan27706 , Vcan27708 andVcan27709) exhibited significant differential expression between
sexual and asexual populations, but all showed the same expression
pattern (figure S2).
3.5 Behavioural genes expression divergence between sexual and asexual
populations
The de novo transcriptome assembly was constituted of a total of
22,333 transcripts that were annotated using BLAST and Gene Ontology
tools. Among those, 18,316 get a blast hit (82%) and 12,923 get at
least one GO term annotation (58%). We selected the ‘behaviour’ Gene
Ontology term, as well as all its child related GO terms. In this way,
we annotated 249 transcripts with putative functions associated with
behavior in V. canescens . Among them, we reported 26 transcripts
that were DE between the two populations, which represented potential
candidates in the differences in foraging behaviours observed between
sexuals and asexuals (table 2). The proportion of behavioural genes with
differential expression between the 2 populations was not different
compared to the full transcriptome one (26/249 vs 1,539/12,567;
χ2= 0.44, P -val=0.50). Among those, we noticed
a majority of transcripts related to sensory behaviour: chemosensory (18
transcripts) or visual (2 transcripts). The other functions detected
were the locomotory behaviour (2 transcripts), learning and memory (2
transcripts), reproductive behaviour (1 transcripts) and rhythmic
behaviour (1 transcript).
3.6 Asexual females exploited more hosts and explored more environment
than sexual females
In the behavioural experiment asexual wasps exploited more hosts than
sexual ones, by allocating more time to hosts (figure 3A;
χ2= 3.81, df=1, P <0.01). On average,
asexual females spent twice more time on host patches compared to
sexuals (655.5 ± 60.8s vs 333.3 ± 80.4s). Neither the egg load,
the for expression nor their interactions with population were
significantly different. Asexual females laid twice more eggs than
sexual ones (figure 3B; χ2=4.94, df=1,P <0.05), with on average 1.24 eggs laid by asexuals (±
0.32) compared to 0.53 eggs by sexuals (±0.17). Time spent on a patch
determined the number of eggs laid since PRT has positive effect on the
number of cockings (χ2=14.09, df=1,P <0.001). However, for expression has a
marginal, though not statistically significant, effect on the number of
cockings (χ2= 3.01, df=1, P =0.08), with a
number of cockings increasing in individuals with higher forexpression. The interactions between for expression and
population, and between for expression and PRT, did not explain
the number of cockings. Asexual females also explored more the
environment than sexual ones. We did not detect differences between
sexual and asexual populations in the proportion of females finding the
second hosts patch (11/17 vs 14/17 respectively, Fisher exact
test, P =0.44). However, asexual females switched more from one
patch to another than sexual females (figure 3C;
χ2=4.937, df=1, P <0.05), with on
average 3-fold more changes in asexual females (2.12 ± 0.37 in asexualsvs 0.71 ± 0.14 in sexual females). Switches between host patches
were not influenced by other variables, nor by their interactions with
population. Together these results showed that asexual females exploited
more hosts, with more time spent on host patches and more eggs laid, and
explored more the environment by changing more often of host patches.
3.7 Expression of the for gene and correlations with behaviours
in sexual and asexual females
The for gene expression was superior in asexual female heads
(1.06±0.60) compared to sexual ones (-0.98±0.54) (figure 4A; F=7.62,
df=1 and 31, P <0.01). Within each population,for expression decreased with egg load (figure 4B; F=6.7, df=1
and 31, P <0.05). There was no significant interaction
between egg load and population on the for gene expression. When
analyzing both populations separately, the number of cockings increased
with PRT in asexual females (χ2=6.00, df=1,P =0.014) but decreased with for expression
(χ2=4.96, df=1, P =0.026) (figure 4C). In sexual
females, number of cockings is correlated with PRT
(χ2=8.1061, df=1, P =0.004) but not withfor expression.
4 DISCUSSION
The for gene exhibited a strong sequence conservation across
insects, consistent with the function conservation in influencing the
foraging behaviours described in numerous insects (Reaume and
Sokolowski, 2009). Beyond for sequence conservation, we also
showed a conservation of the for gene model complexity betweenV. canescens and D. melanogaster with four alternative
promoters encoding four proteins differing in their N-termini (Allen et
al., 2017). The use of alternative promoters represents a source of
diversity and flexibility in the regulation of gene expression, and
ultimately function. This as has been particularly demonstrated in thefor gene, whose promoter variations cause changes in both tissue
localization and substrate specificity. Indeed, pr1-for andpr4-for transcripts were expressed within neurons, whilepr2-for and pr3-for transcripts were localized in glia
cells of fruit flies central nervous system (Allen et al., 2018; Dason
et al., 2020). The isoform pr1-for was presumed to be the only
transcript necessary to forage since in mutants pr1-forexpression in neurons was the only required to rescue larval foraging
behaviours (Allen et al., 2018). Variations in the N-termini are
critical to the specificity of PKG-substrate interactions (Pearce et
al., 2010). PKG phosphorylate serine and threonine residues on a dozen
of proteins known to modulate muscle activity and neuronal signaling
pathways (Edelman et al., 1987; Schlossmann and Desch, 2009). Such
variety of substrates may explain the pleiotropic effects of thefor gene. Conservation of gene model complexity between the
diptera D. melanogaster and the hymenoptera V. canescenssupports the importance of maintaining such complexity to regulate
alternative foraging behaviours. However, our work did not allow the
characterization of qualitative differences in for isoforms
between sexual and asexual populations, but rather suggested a decrease
in all for isoforms transcription in the sexual population.
Polymorphism analysis revealed 15 SNPs along the for gene, most
of them varying in frequency across populations, and supported a major
reduction of genetic diversity that occurred in asexuals rather than the
presence of two allelic variants diverging between sexual and asexual
populations. Such reduction of polymorphism in asexuals was expected: in
general thelytokous individuals are more homozygous than arrhenotokous
ones (Beukeboom and Pijnacker, 2000) and this has been already shown inV. canescens with a study based on 15 microsatellites, that were
all homozygous (Mateo Leach et al., 2012). In contrast, some genetic
diversity still persisted at the for locus in asexuals. The vast
majority of identified SNPs did not affect the protein sequence itself
since occurring outside of coding region or corresponding to synonymous
polymorphism. A single SNP corresponding to a non-synonymous mutation
was located at the N-terminal part of the predicted PKG I, corresponding
to the substrate binding region of the protein, outsides the kinase and
cGMP binding domains. By comparison, rover and sitteralleles differed by more than 300 SNPs segregating in D.
melanogaster , but also involved regulatory mutations rather than
changes in aminoacid sequence (Allen et al., 2017). In contrast, the two
allelic variants identified in the moth Sesamia nonagrioidesdiffered by only one non-synonymous SNP located within the kinase domain
of the protein, each variant was associated with different levels offor expression, PKG activity, and distinct behaviours (Chardonnet
et al., 2014). However, previous studies in hymenopteran species have
not shown any evidence of the existence of allelic variants at thefor locus, neither did the present study in V. canescens .
Differences in foraging behaviours recorded between sexuals and asexuals
should rely on genome divergence since there is no more gene flows
between the 2 populations (Mateo Leach et al., 2012). Previous study
revealed such genome divergence since individuals from sexual and
asexual populations can be distinguished based on microsatellites.
However, how much gene expression diverged at the genome-wide scale
between the two populations has not been studied so far. By comparing
head transcriptomes, we reported that the 2 populations clearly split
up, with a total of 1,539 DEGs. This proportion of 11% of DEGs between
2 populations from a same species is high and almost as high as that
observed in recently diverged species such as Drosphila
pseudoobscura pseudoobscura and D. pseudoobscura bogotana(~0.25mya divergence and 14.6% DEGs) (Gomes and
Civetta, 2015). While behavioural divergences are among the most
remarkable differences between sexual and asexual wasps, the
behaviour-annotated group of genes was not overrepresented within DEGs.
Among the behavioural genes whose expression varies between populations,
transcripts involved in sensory perception (olfactory, sensitive,
visual) were the most numerous. Chemosensory genes evolved rapidly and
played important role in adaptation (Brand et al., 2015). While thefor gene has been implicated in foraging behaviours in a variety
of organisms, none of the for isoforms were detected as DE.
Analysis of RNA-seq data at this locus showed that all isoforms of thefor gene were more expressed in asexual population than in sexual
population, although beyond significance threshold.
Globally the behavioural results were congruent with our predictions,
that is asexuals exploited more host patches since they are faster to
choose and walk between hosts, and have a greater egg load (Amat et al.,
2017). On the opposite, sexual females are better dispersers with both
longer and faster flights, they have higher longevity, and greater
energy content (Amat et al., 2017). They were thus expected to explore
more their environment, yet this prediction was not verified in the
current results. The discrepancy could came from the experimental device
that might be too small for all exploration-related behaviours to be
expressed, in particular dispersal involving long flights with high
energy costs (Amat et al., 2012). Field experiments conducted withD. melanogaster showed that rovers exhibit higher dispersion with
both greater dispersal tendencies and longer distances of flight than
sitter flies, and that artificial increasing of for expression in
the brain and nervous system increases dispersal in sitters (Edelsparre
et al., 2014). Our study, conducted in the lab, does not allow assessing
wasps dispersal ability. Nevertheless, by showing that asexual females
switched more frequently between host patches than sexual ones, the
experimental device is relevant to detect differences in some aspects of
the exploration between the two populations.
V. canescens asexual females present homology with the rover
phenotype observed in D. melanogaster both by exploring and
exploiting more. The for gene is more expressed in asexual wasps
than in sexual ones, consistently with the Drosophila rover
model. Previous classification of the for transcript among
non-DEG might be due to the low number of RNA-seq replicates (3), while
RT-qPCR was conducted on a higher number of individuals (17) thus
increasing statistical power in the detection of DEG. The higher
fecundity is another common characteristic between D.
melanogaster rovers (McConnell and Fitzpatrick, 2017) and V.
canescens asexuals, here measured by both a higher egg load,
corresponding to their potential fitness, and higher number of eggs
laid, corresponding to their effective fitness but measured during a
short period. Hence in these two species, individuals that exploited and
explored more were also the more fecund, and the ones with the higherfor expression. A major contribution of the present study is the
joint analysis of the for expression and foraging behaviours
measured at the individual scale, that conferred information on the
inter-individual variations and allowed studying correlations between
these traits, beyond average measures. Two major results emerged from
this approach: the first one is that the egg load decreases in females
with the highest for expression; and the second is a decrease of
eggs laid by asexual females with the highest for expression.
These two correlations were consistent and suggested that an increase in
the for expression may be costly for females and could result in
a decrease of progeny number. In the wasp V. canescens , the cost
of reproduction is mostly based on finding hosts to lay eggs, as the egg
itself contains little reserve and is not costly to produce (Pelosse et
al., 2011). In this case, rather than an energetic cost due to thefor expression that would directly induce a decrease in
fecundity, the cost might be indirect and related to the numerous other
functions fulfilled by the highly pleiotropic for gene apart from
resource searching behaviours, such as learning, memory, or social
interactions (Alwash et al., 2021; Reaume and Sokolowski, 2009).
Given the extent of transcriptomic divergence, with hundreds of DEGs
between sexual and asexual populations, and in the absence of functional
analysis, we cannot firmly conclude on the functional role played by the
slight differences in the for expression recorded in the
differences of foraging behaviours. It is worth mentioning that
comparison between rovers and sitters in D. melanogaster showed
that differences in the for expression were small but consistent
(Osborne et al., 1997). Drosophila rovers and sitters have shown
differences between their transcriptomes, apart from the single
variation in the for expression (Kent et al., 2009). Honey bee
nurses and foragers differed by about 40% of their brain transcriptome
(Whitfield et al., 2003). However, manipulation of the for gene
expression or the corresponding PKG enzyme activity was sufficient to
modify foraging behaviours in the two species (Ben-Shahar et al., 2002;
Osborne et al., 1997). Therefore, the differences in the for gene
expression detected in the current study between sexuals and asexuals,
although moderate, might nevertheless have an essential function in the
differences in foraging behaviours reported between V. canescenspopulations.
The present study that highlights the molecular bases underpinning the
variability in foraging behaviours in the parasitoid wasp V.
canescens brings insights on the evolution of the control of foraging
behaviours by the for gene in hymenoptera. So far, studies have
focused on social hymenopteran species that acquired eusociality
independently: bees, ants and wasps. All these studies revealed a
caste-specific for expression correlated with foraging intensity
but with opposite patterns: honey bee (A. mellifera ) and
bumblebee (B. terrestris ) foragers exhibit a higher forexpression compared to nurses (Ben-Shahar et al., 2002; Tobback et al.,
2011), whereas nurses presented a higher for expression compared
to foragers in ants (P. barbatus, P. pallidula ) and common waspV. vulgaris (Ingram et al., 2005; Lucas and Sokolowski, 2009;
Wenseleers et al., 2008). The for gene influences social behavior
in a variety of species and has been postulated to be part of a genetic
toolkit involved in
the evolution of eusocial insects (Rittschof and Robinson, 2016):
whereas acquisition of eusociality relies on the emergence of a forager
caste specialized on foraging tasks that appears to be related to
differences in the for gene expression. In contrast, selection in
bees shows opposite patterns to the one described in the ancestral
groups of ants and wasps. Parasitoids wasps, which are ancestral to the
Apocrita group that includes all social hymenopteran (Peters et al.,
2017), are solitary species and therefore do not have foragers. This
study suggests that differences in the for expression pattern
underlying changes in foraging strategies, could be ancestral to
Apocrita and precede the acquisition of sociality. In this group,
variations in the for gene expression would not rely on allelic
variants. The present work illustrates an original case of a divergence
in foraging behaviours that is not based on caste differences but
associated with a difference in the for expression between
populations that also differ in their reproductive mode. However, the
adaptations observed in numerous life history traits in the two
populations are not limited to the difference in expression of one gene
but could involve differences in the optimum expression pattern of
several hundred genes.
Acknowledgements
We thank Francois Debias for his help during field capture and Elsa Day
for her help in insect rearing and experiment. This work was funded by
the Agence Nationale de la Recherche JCJC AVOIDINBRED
(ANR-17-CE02-0004-01) attributed to A.G. This work was performed using
the computing facilities of the CC LBBE/PRABI.
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Accessibility and Benefit-Sharing section
Data Accessibility statement
Data were deposited in the GEO repositories from NCBI database with the
accession code GSE194171.
Benefit-Sharing Statement
Benefits from this research accrue from the sharing of our data and
results on public databases as described above.
Author Contributions
A.G., E.D., L.M., C.V.H. and I.A. designed research; A.G. and D.L.
performed the research; A.G., V.L., D.L. and A.E.F. analyzed data; A.G.,
E.D., L.M., C.V.H. and I.A. wrote the paper.
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