Comparative transcriptomics suggests a highly species-specific nature of the phenotypic plasticity associated with the outbreaks of the two main pest locusts.

doi:10.21203/rs.3.rs-4121747/v1

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Comparative transcriptomics suggests a highly species-specific nature of the phenotypic plasticity associated with the outbreaks of the two main pest locusts.

https://doi.org/10.21203/rs.3.rs-4121747/v1

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Background

Locust outbreaks cause devastation and are an important matter for fundamental research. They associate with a striking case of phenotypic plasticity; i.e., a gregarious phase versus solitarious phase polyphenism that affects most aspects of the locusts’ biology. However, changes in behaviour are the most notorious. Changes in gene expression dictate the phenotypic changes, behaviour is key to the locusts’ phase change, and the Central Nervous System (CNS) is essential to behaviour. Therefore, understanding and tackling the phenomenon requires studying the gene expression changes that the locusts’ CNS undergoes between phases. The genes that change expression the same way in different locusts would be ancestrally relevant for the phenomenon in general and those that change expression in a species-specific way would be relevant for species-specific understanding and tackling of the phenomenon.

Methods

Here, we use available raw sequencing reads to build transcriptomes using the same RNAseq pipeline and to compare the gene expression changes that the CNS of the two main pest locusts (Schistocerca gregaria and Locusta migratoria) undergo when they turn gregarious. Our aim is to find out about the species-specificity of the phenomenon, highlight the genes that respond in species-specific manner and those that respond the same way in both species.

Results

The locust phase change phenomenon seems highly species-specific, very likely due to the inter-specific differences in the biology and life conditions of the locusts. Research on locust outbreaks, gregariousness and swarming should therefore consider each locust species apart—as none seems representative of all locust species. Still, the 109 genes and 39 non-annotated sequences that change expression level the same way in the two main pest locusts provide sufficient material for functional testing in search for important genes, to better understand, or to fight against locust outbreaks. The genes that respond in a species-specific way provide material for understanding the differences between locust species and for looking for potential species-specific weapons against each of them. The still uncharacterized transcripts that change expression either in a species-specific or the same way between the two species provide material for functional testing and gene discovery.

The word locust is tightly linked to outbreaks and devastation. In fact, the difference between grasshopper and locust resides in the ability of the populations of the latter to outbreak, become gregarious and swarm. Locusts are therefore considered to be pests (e.g., (Zhang et al., 2019)) as several species are known to cause damage and their geographical distribution covers most parts of the world, including for instance Dociostaurus maroccanus in the Mediterranean area (e.g.,(Aziz et al., 2022; Pasquier et al., 1952; Rambier, 1951)), Melanoplus species in North America (e.g., (Dingle and Haskell, 1967; Lee et al., 2006; Olfert et al., 2021)), S. cancellata in South America (Hawkes et al., 1987; Piou et al., 2022), Chortoicetes terminifera in Australia (Chapuis et al., 2008b; Hewitt and John, 1971; Lambert, 1972; Wang et al., 2019), Locusta migratoria in Asia and Africa (e.g., (Chapuis et al., 2008a; da Silva and Lange, 2008; Uvarov, 1921; Wang and Kang, 2005; Wu et al., 2008; Zheng et al., 2006)) and Schistocerca gregaria in Africa and Asia (see https://www.fao.org/locusts/en/). The last two species being considered the main pest locusts due to the wide world area that their populations’ outbreaks affect and to the devastation they cause, in part because they affect poor regions of the globe. Accordingly, most of the research is carried out on these two species (e.g., (Ayali and Pener, 1992; Chen et al., 2010; Ellis, 1963; Islam et al., 1994; Kang et al., 2004; Martin-Blazquez et al., 2017; Simpson et al., 1999; Stower, 1959; Tanaka and Nishide, 2012)).

Both in L. migratoria and in S. gregaria, the population outbreak is associated with a wide range of changes that affect almost every aspect of the insect’s biology (for instance see (Ayali and Pener, 1992; Bouaichi et al., 1995; Davey, 1954; Ellis, 1963; Hamouda et al., 2011; Roessingh et al., 1993; Simpson et al., 2002; Simpson et al., 1999; Stower, 1959; Stower et al., 1960; Symmons, 1969)). The resulting polyphenism is thus composed of a gregarious phase—during outbreaks—as opposed to a solitarious phase—when the locust population is not dense, and the insects carry a “normal” life. In fact, the differences between locusts of the two phases are so pronounced in some species that solitarious and gregarious individuals/populations of the same species were once described as two different species (for a short history of the research on phase polyphenism see (Pfluger and Braunig, 2021)). Rather than being due to genetic changes senso-stricto (i.e., differences, thus mutations, in the DNA sequence of the genome), the locust phase change is product of the genic (see epigenetic) response to the environmental changes—caused by life in very crowded conditions—that result in differences in gene expression between the two locust phases (for instance see (Bakkali and Martín-Blázquez, 2018; Wang and Kang, 2014)).

Interestingly, the phase change of the locusts involves aspects that are common to all known locust species, such as the association with life in crowded conditions, changes in behaviour, increased activity, smaller body size and increased reproduction. Yet, subtle and not so subtle differences exist in the characteristics of the changes that affect the so many aspects of the biology of the different locust species when they shift from one phase to the other. For instance, the models that estimate locusts probability of being gregarious are not applicable to different species due, as we demonstrated in Blazquez and Bakkali (Martín-Blázquez and Bakkali, 2017), to species-specific differences in the changes of the morphological and behavioural traits between the two phases of the different locust species—for more details on some of the species-specific characteristics of the phase change in locusts see for instance (Ayali, 2019; Pener and Simpson, 2009; Pfluger and Braunig, 2021).

A logical way of understanding the phenomenon should therefore be that the phase change shows both common and species-specific characteristics between the different locust species. A reasonable expectation would therefore be that the differences in gene expression between locust phases should include common as well as species-specific changes—the common changes being of use to a better understanding of, or fighting against, the phase change (see outbreaks) in locusts in general, and the specific changes being of use for understanding, or fighting against, the phase changes and its implications in particular species. For that, a between-species comparison of the molecular differences between soliarious and gregarious individuals should be done.

We therefore carry out here the first inter-species comparison of the transcriptomic changes at the Central Nervous System (CNS) that differentiate the solitarious from the gregarious phases in two main and best studied and characterized pest locusts, L. migratoria and S. gregaria. We highlight the common changes, we report the species-specific changes, and we discuss the findings and suggest a set of genes that seem to be worth using for further functional studies.

Transcriptome assembly and annotation

The CNS transcriptomes of the solitarious and gregarious S. gregaria as well as their annotation, expression levels and comparative data were from (Bakkali and Martín-Blázquez, 2018).

The raw paired-end reads of the Illumina sequencing of RNAs from the solitarious and the gregarious L. migratoria CNS are from (Guo et al., 2018) can be found in the NCBI Bioproject PRJNA399820 (accessions: SRR5967009, SRR5967010, SRR5967011 and SRR5966534, SRR5966981 and SRR5966984). To make the results comparable, the raw sequencing reads of L. migratoria were treated just as it was done for the S. gregaria sequencing reads in (Bakkali and Martín-Blázquez, 2018). Briefly, they were assembled using ABySS (Birol et al., 2009) with odd-numbered Kmers 19 to 95. The resulting transcriptomes were merged using Linux cat command before redundancy removal using vsearch (Rognes et al., 2016) at a 95% identity cutoff. CAP3 (Huang and Madan, 1999) was then used (with o = 16, k = 0 and p = 95 as options) to further elongate the contigs. BWA (Li and Durbin, 2009) separately aligned the reads from solitarious and gregarious libraries against the assembled reference trancriptome. After processing the alignments using Samtools (Li et al., 2009) and xa2multi (https://github.com/lh3/bwa/blob/master/xa2multi.pl), htseq (Anders, 2010) was used to count the reads that aligned against each contig of the reference transcriptome.

Annotation of the resulting L. migratoria transcriptome was also carried just as annotation of the S. gregaria transcriptome in (Bakkali and Martín-Blázquez, 2018). That is, we used BLASTx against our local database of Drosophila melanogaster proteins, then against our local database of the protein sequences of Acyrthosiphon pisum, Anopheles gambiae, Apis mellifera, Bombyx mori, Nasonia vitripennis, Pediulus humanus and Tribolium castaneum (henceforth called the Species database—see (Bakkali and Martín-Blázquez, 2018)). The contigs that gave no significant hits were BLASTx searched against the NCBI nr database in our local server and the contigs that remained hitless were used for a local BLASTn search against the NCBI nt database. Contigs that gave no significant blast result were considered “anonymous” and those that gave the same blast result were considered as belonging to the same unigene.

Comparative transcriptomics and differential gene expression analysis

Identification of the transcripts that are shared between (common to) both locust species was carried out in a stepwise manner. First, the contigs that had significant blast hit against the same sequence of the BLAST databases (those that share the same BLAST result) were identified using Linux fgrep command and spreadsheets. For the sequences that had no significant BLAST result (anonymous sequences), a local BLAST database was built using the S. gregaria transcriptome. The anonymous contigs of the L. migratoria transcriptome were then BLASTn searched against that database and the contigs that gave significant BLAST hits were identified. The same was done in the inverse sense (i.e., BLASTn of the anonymous contigs of S. gregaria against a database of the L. migratoria transcriptome). For each species, we merged the positive hits of both BLASTn searches (anonymous S. gregaria transcripts against L. migratoria transcriptome database and anonymous L. migratoria transcripts against S. gregaria transcriptome database). We then removed redundancies within the transcripts of each species, and we retained the transcripts that were anonymous in both species and had significant blast hit against each other. The changes in expression levels between solitarious and gregarious phases of both species were compared for each set of sequences.

The S. gregaria and L. migratoria contigs that had a best blast hit against the same sequence of our local Drosophila, Species, NCBI nr or NCBI nt databases (see (Bakkali and Martín-Blázquez, 2018)) and those that have significant blast hits against each other were considered as shared between the two locust species analysed herein. The remaining S. gregaria and L. migratoria contigs were considered as specific to the CNS transciptome of the corresponding species.

Just as we did for the S. gregaria transcriptome in (Bakkali and Martín-Blázquez, 2018), the sequencing reads that aligned to contigs of the same L. migratoria unigene were separately summed for the solitarious and the gregarious libraries. Only contigs and unigenes that were at least 75 bp long and with a significant BLAST hit or have at least a read aligned to them in at least two libraries were retained. The summed reads of each unigene and those of the individual contigs were then used for statistical comparison of the solitarious versus gregarious expression levels using the Generalized Linear Model (GLM) method in EdgeR (Robinson et al., 2010) (as described in (Gonzalez-Garcia et al., 2020; Hidalgo-Gutierrez et al., 2019)). Statistical significance was considered at a 0.05 level after False Discovery Rate correction. The data of the differentially expressed genes were compared to those reported for S. gregeria in (Bakkali and Martín-Blázquez, 2018).

Gene Onthology (GO) analyses were carried out using Panther Classification System (pantherdb.org) and gene networks were built using String database (https://string-db.org/).

Assembly and annotation

Submitting the fastq files to a quality check (Table 1) shows that the different sequencings of the CNS RNAs of solitarious and gregarious L. migratoria and S. gregaria, that were carried out using the same technology and at the same read-length level, gave results of similar quality. They show insignificant number of undetermined bases (Ns), most (around 90%) of the bases have less than 1 in a 1000 chance of being product of error (Q30) and the %GC is similar, especially within species. The numbers of reads are similar within species but L. migratoria counts on a little over twice the number of S. gregaria sequencing reads.

Table 1

Sequencing statistics. Lm: *Locusta migratoria*. Sg: *Schistocerca gregaria*. ؏: PRJNA399820: Institute of Zoology, Chinese Academy of Sciences. ه : PRJNA381887: Mohammed Bakkali’s Laboratory, Universidad de Granada, Spain.
Locust	Data Accession	Locust Phase	Total reads	Read length	Q30	%Ns	%GC
Lm	؏	Solitarious	204,438,252	101	~ 90	< 0.005	40.5
Lm	؏	Gregarious	201,037,488				40.37
Sg	ه	Solitarious	95,259,912				42.98
Sg	ه	Gregarious	76,248,284				41.92

While the reference transcriptome for S. gregaria CNS was from (Bakkali and Martín-Blázquez, 2018), the L. migratoria transcriptome had to be assembled de novo (to obtain both transcriptomes using the same method and make them comparable, see Material and Methods). It produced around twice the number of contigs of the S. gregaria reference transcriptome, but the overall characteristics of both transcriptomes were similar; so that the transcriptomes of both species show similar N50, largest contig length and %GC (Table 2). Supplemental files Lm_CNS.fasta and Sg_CNS.fasta provide the assembled sequences of the L. migratoria and S. gregaria CNS reference transcriptomes built here, respectively.

Table 2

Transcriptome assembly statistics. Lm: *Locusta migratoria*. Sg: *Schistocerca gregaria*.
Locust	Contigs	%GC	N50	Max length
Lm	221511 (481442)	41.14	1696 (1343)	26662
Sg	110764	41.72	1296	35064

Separate stepwise BLAST annotations of the two transcriptomes (see Material and Methods) produced results (Tables 3 and 4) that seem in accordance with the larger reference transcriptome assembled for L. migratoria compared to the one assembled for S. gregaria. Indeed, the reference transcriptome of the former species shows lower contig to unigene ratios in each blast result. However, the proportion of each of the two transcriptomes that gave significant BLAST results compared to the one that gave no significant BLAST result are similar between the two transcriptomes (being the number of the anonymous sequences in L. migratoria transcriptome twice that number in the also smaller S. gregaria transcriptome). Table S1 summarizes the blast and GO annotation results.

Table 3

Annotation statistics. Lm: *Locusta migratoria*. Sg: *Schistocerca gregaria*. Local: Local database of insect proteins (see(Bakkali and Martín-Blázquez, 2018)). Con.: Contigs. Uni. Unigenes.
Locust	Database								No Blast
	Local		Nr.		Nt.		Total
	Con.	Uni.	Con.	Uni.	Con.	Uni.	Con.	Uni.
Lm	30517	15088	28301	19849	12429	2746	71247	37683	64675
Sg	59513	14700	6243	1794	10313	1126	76069	17620	34696

Table 4

BLAST annotation statistics. Lm: *Locusta migratoria*. Sg: *Schistocerca gregaria*. Same: Number of sequences with the same best BLAST hit. Different: Number of BLAST positive sequences that have different best BLAST hits in the *L. migratoria* and *S. gregaria* reference transcriptomes compared here.
Locust	With BLAST hit Contigs (unigenes)		With no BLAST hit Contigs (unigenes)
Locust	Same	Different	With BLAST hit in the other species	With no BLAST hit in neither species	Absent in the other species
Sg	23596 (6740)	5747 (4208)	1207 (980)	4443	9673
Lm	17846 (6740)	33663 (15586)	12451 (3784)	9043	59829

Gene expression

Of the 6740 genes that are common to the two reference transcriptomes compared in this work 4560 show significant difference in gene expression levels between solitarious and gregarious S. gregaria wherase only 370 genes show such difference between solitarious and gregarious L. migratoria. Of these, the expression levels of 235 genes are significantly different between the solitarious and gregarious phases of both species, 109 of which showing a change in the same direction in both species (Table 5 shows the detailed comparative transcriptomics). 99 of these genes increase expression in the geragrious phase of both species and the remaining 10 decrease it. Among these genes we can highlight a choline transporter-like, an odorant binding protein, a G protein subunit and a defence protein precursor.

Table 5

Comparison between the transcripts that have a significant BLAST result and identification of those that show significant changes in expression level between the solitarious and gregarious states both in *Schistocerca gregaria* and *Locusta migratoria*. Common: Common to both species. Sig.: Significant change in expression level between the solitarious and the gregarious states. Non. : Non-significant change in expression level between the solitarious and the gregarious states. Over: Over-expressed in the gregarious state. Under: Under-expressed in the gregarious state. Between parentheses are the contigs. Sig.-Non.: Significant change in expression level between the solitarious and the gregarious states in the species but not in the other. Sig.-Sig.: Significant change in expression level between the solitarious and the gregarious states in both species. Over-Over: Over expressed in the gregarious state in both species. Over-Under: Over-expressed in the gregarious state in the species and under-expressed in the gregarious state in the other species. Under-Under: Under expressed in the gregarious state in both species.
Species	Common	Sig.	Sig.-Non.	Sig.-Sig.	Over	Under	Over-Over	Under-Under	Over- Under	Under- Over
Sg	6740 (23596)	4560 (5720)	4325 (5396)	235 (324)	221 (310)	14 (14)	99 (186)	10 (10)	123 (124)	4 (4)
Lm	6740 (17847)	370 (370)	135 (135)	235 (235)	101 (101)	134 (134)	99 (99)	10 (10)	4 (4)	123 (124)

When it comes to the anonymous sequences, after blasting the anonymous L. migratoria transcripts against S. gregaria transcriptome and S. gregaria anonymous sequences against L. migratoria transcriptome, merging the results, and removing redundancies (see Material and Methods), 3445 S. gregaria transcripts corresponded to 2693 L. migratoria transcripts. Of these, 1344 were BLASTn matches between 1075 S. gregaria anonymous sequences and 1110 L. migratoria annonymous sequences (i.e., these are sequences that do not correspond to any known gene and that are expressed in the CNS of both species analyzed here). Of these, all the S. gregaria transcripts show significant difference in expression levels between the solitarious and gregarious phases of that species, wherease only 145 L. migratoria transcripts show such difference. 42 S. gregaria and 45 L. migratoria transcripts show significant differences in expression levels between the solitarious and gregarious states in both species. Of these all but 3 transcripts are over-expressed in the gregarious phase of both species. These 3 transcripts are over-expressed in the gregarious phase in S. gregaria but are under-expressed in the same phase of L. migratoria (Table 6). Table S2 shows the gene expression comparison results.

Table 6

Comparison between the transcripts that have no significant BLAST result and identification of those that show significant changes in expression level between the solitarious and gregarious states both in *Schistocerca gregaria* and *Locusta migratoria*. Common: Common to both species (*i.e.*, they gave significant BLAST against each other). Sig.: Significant change in expression level between the solitarious and the gregarious states. Non. : Non-significant change in expression level between the solitarious and the gregarious states. Over: Over-expressed in the gregarious state. Under: Under-expressed in the gregarious state. Between parentheses are the contigs. Sig.-Non.: Significant change in expression level between the solitarious and the gregarious states in the species but not in the other. Sig.-Sig.: Significant change in expression level between the solitarious and the gregarious states in both species. Over-Over: Over expressed in the gregarious state in both species. Over-Under: Over-expressed in the gregarious state in the species and under-expressed in the gregarious state in the other species. Under-Under: Under expressed in the gregarious state in both species.
Species	Common	Sig.	Sig.-Non.	Sig.-Sig.	Over	Under	Over-Over	Under-Under	Over-Under	Under-Over
Sg	3489	3489	3444	42 (45)	39 (42)	3	39 (42)	0	0	3
Lm	2693	187	145	42	42	0	42	0	3	0

Figure 1 shows how threre is a clear overall clustring by species, so that the general distribution of gene expression levels in the solitarious phase of a species is more similar to that distribution in the gregarious phase of the same species than to the solitarious phase of the other species. There is also a notorious species-specificity both in terms of the levels of gene expression as well as in terms of differences in gene expression levels between the solitarious and gregarious phases. Such specificity applies both to all the expressed genes and transcripts (Fig. 1A), to the blasted differentially expressed transcripts (Fig. 1B), and to the non-blasted differentially expressed genes (Fig. 1C). The blasted transcripts having visibly more conserved inter-phase diferential expression in the two species.

Functional annotation

GO analysis shows that the L. migratoria reference transcriptome assembled here contains sequences pertaining to 4504 biological processes, whereas the sequences of the S. gregaria reference transcriptome used here belong to 4046 biological processes. Most of these processes (3921) appear in both transcriptomes and only 34 processes appear significantly different between both transcriptomes, as by the number of sequences belonging to them (Fig. 2). Except for a neuropiptide signalling process, a G-protein coupled receptor signalling process and a lifespan related process, that all appear increased in S. gregaria, the rest of the biological processes to which belong the sequences of both transcriptomes are related to transcription and appear increased either in S. gregaria or L. migratoria. The functional annotation data are in Table S1.

The sequences that have the same BLAST result in both species correspond to 3773 biological processes (Table S1) where constitutive (such as transcription-related) and tissue-specific (i.e., neural) processes are expectedly predominate (Fig. 3 lists the Biological Processes that contain 30 or more of the common sequences of both transcriptomes).

Among the genes that appear in both reference transcriptomes (i.e., the sequences that have the same BLAST result in both transcriptomes), those that are significantly differentially expressed between solitarious and gregarious locusts in both species belong to 375 biological processes of which processes related to stress and immunity have a noticeable presence—together with the always predominant metabolism- and transcription-related processes (Table S1, Fig. 4). For their part, the genes that increase expression in the gregarious phase of both species belong to 185 biological processes where transcription- and immune-related processes are notorious (Table S1 and Fig. 5). The genes that decrease their level of expression in the gregarious phase of both species, however, belong to just ten biological processes; being these: positive regulation of BMP signalling pathway (GO:0030513), lipid transport (GO:0006869), lipid metabolic process (GO:0006629), inositol catabolic process (GO:0019310), imaginal disc-derived wing vein specification (GO:0007474), glyoxylate catabolic process (GO:0009436), glycolytic process (GO:0006096), glycine biosynthetic process, by transamination of glyoxylate (GO:0019265), glucose metabolic process (GO:0006006) and fatty acid metabolic process (GO:0006631).

Gene network analysis

No experimentally demonstrated direct interaction at confidence levels of 0.9 to 0.5 (highest to medium) is detected between the genes that significantly change expression level in the gregarious phases of both L. migratoria and S. gregaria—full STRING network. Some direct interactions appear between these genes when we add more sources of information in STRING (all the databases in this case, i.e., Text mining, Experiments, Databases, Co‑expression, Neighborhood, Gene Fusion, Co‑occurrence). Specifically, an expected interaction emerges between the S-adenosylmethionine decarboxylase proenzyme (SamDC) and S-adenosylmethionine synthetase, isoform c (Sam-S) at the highest (0.9) confidence level (Fig. 6a), to which the also expected interaction between the Ankyrin repeat domain-containing protein 49; Lethal 2 35Be (l(2)35Be) and the Lethal (2) 34fc isoform b (l(2)34Fc) genes is added at high (0.7) confidence level (Fig. 6b). The network becomes somewhat more populated when we add up to 10 of the first shell of genes interacting with the members of the list of genes that significantly change expression level in the gregarious phases of both L. migratoria and S. gregaria. Still all the interacting additions are ribosomal proteins that interact with the Small subunit ribosomal protein s21e (40S ribosomal protein S21, RpS21) present in the submitted list of genes that significantly change expression level in the gregarious phase in both species (Fig. 6c).

Research on pest locusts has a clear interest not only from a fundamental scientific point of view but also for its potential applied side. Winning the fight against locust outbreaks, or at least finding an efficient eco-friendly way of dealing with them, means not only economic savings but also protecting humans, livestock, agriculture and the environment of the many affected areas of the globe. Any knowledge on the molecular changes that accompany the outbreak state of the locusts has the potential of shedding more light at the molecular basis of the locust phase change, swarming and outbreak. Such knowledge also has the potential of being useful for the development of environmentally friendly treatments either against locusts in general or in a species-specific way. Several are the works that tackled the genetics and molecular biology of the locust outbreaks phenomenon. Some of these were real breakthroughs and had significant impact (e.g., (Anstey et al., 2009; Kang et al., 2004), for a review see (Wang and Kang, 2014)). Yet until very recently no work approached the issue from a comparative inter-specific perspective. While we were writing this manuscript we became aware of a couple of works that explored this phenotypic plasticity issue using two different inter-species comparative approaches. (Kouhei Toga, 2022) compared the distant locust and aphid transcriptomes and produced a list of few hundred genes that show similar differences when the animals are crowded as compared to when they live in isolation. For their part, (Foquet et al., 2021) compared a locust to very closely related grasshopper species and had largely species-specific results with no single shared gene reacting the same way between the studied species. However, the results of the first work might have been affected by the phylogenetic disparity of the studied species—large phylogenetic distances should reduce homologies and shared traits and reactions. On the other hand, the second work compared locusts (pests that outbreak) with grasshopper (non-pests that do not outbreak) species, which might have reduced, or left aside, the molecular aspects of the locust phase change per se. The current work is thus the first to compare two actual locust species that are paradigms for studies on locusts, phylogenetically relatively closely related to each other, and that are the two main pest locusts—as by the extension of the areas they affect, the magnitude of the devastation each of their outbreaks cause, and the high recurrence of their outbreaks.

Being the phenomenon of locust outbreaks so tightly linked to perception and behaviour, an obvious system of study is thus the Central Nervous System—that also happens to be the target of many pesticides (e.g., pyrethroids and neonicotinoids). In addition, being the locust phase change phenomenon due to gene expression changes in response to changes in the living conditions, the present work therefore aims at identifying the genes that change expression level between locust phases in a general manner (in both locusts) and the genes that change expression between locust phases in a species-specific manner (those that change expression in one species but not in the other). Having done that, we provide lists of genes for future functional genomics studies, and we infer on whether the phenomenon of locust phase change is homogenous between species in its molecular aspects, or it is rather largely heterogeneous and species-specific. Answering such question also means figuring out to which extent research on a single species could be representative of the rest of locust species, and thus recommending either focussing the efforts on a representative species or, instead, studying each locust species apart—which is always recommended, just as recommended is considering the findings on other species. We also aim here at the important task of highlighting genes that consistently see their levels of expression significantly changed in the CNS when locusts outbreak. We did that by comparing the changes in gene expression levels between solitarious and gregarious individuals of the two species that happen to be both the main, the most studied, and the best characterized pest locust species (i.e., L. migratoria and S. gregaria). The work is thus based on comparative RNAseq.

The reads of the RNA sequencings of both species used here were obtained using the same sequencing technology (Illumina) and are of similarly good quality (as by number of Ns and Q30 score) as to confidently use and compare them. The fact that they show similar %GC, and that that percentage is more similar within than between species, suggests that the sequencing reads were mainly from the locust material and do not contain significant contaminants. In addition, the fact that we found clustring and significant differences between data of both locust phases confirms the fact that the solitarious and gregarious locusts from which the data came were indeed at different physiological states (i.e., solitarious and gregarious as stated). Furthermore, annotation results confirm that the data were from locusts and that the sequenced tissues were indeed CNS. Moreover, although we had a little over twice the number of sequencing reads in L. migratoria than in S. gregaria, the number of sequencing reads for each state (solitarious and gregarious) is similar within each species and is largely over the minimum recommended for a good transcriptomics work (see (Wang et al., 2011)). Indeed, the raw sequencing reads used here for the solitarious and gregarious CNS transcriptomes of S. gregaria and L. migratoria were produced and used by expert laboratories as representatives of the CNS transcriptomes of the solitarious and gregarious states of these same species, and the results were published in two prestigious journals (Bakkali and Martín-Blázquez, 2018; Guo et al., 2018). In addition, we choose to process the L. migratoria data in the same way as we did for the S. gregaria data—which were produced by our laboratory—rather than using two reference genomes or the processed data in (Guo et al., 2018). We did that for homogeneity of the results and to avoid any differences in the results that might be due to differences in the processing of the raw data. Such approach, comparing de novo assembled transcriptomes, also allowed focussing only on the CNS expressed part of the genome and an easier identification of common expressed sequences that have no blast annotation (the anonymous one).

Still, the fact that the assembled reference transcriptome of L. migratoria CNS contained about twice the number of sequences than that of S. gregaria CNS is clearly due to the deeper sequencing in the former species and to the fact that the same assembly procedure was used to obtain both transcriptomes. However, the fact that both transcriptomes show similar overall characteristics (N50, largest contig length and %GC) (Table 2) and that over 6000 genes with known BLAST annotation and over 4000 genes with unknown annotation (anonymous) are common to both transcriptomes mean that these transcriptomes are representative of their respective species and tissue, and that they provide good and large enough overlap as to be useful for a comparative work of the kind of the present. Indeed, even the GO analysis shows that both transcriptomes contain genes pertaining to similar sets of biological processes over 87% of which appear in both species and only less than 1% of these processes appear significantly differentially represented in both transcriptomes. In addition, the biological processes represented in each of the two transcriptomes were as one would expect from the studied tissues (i.e., with both constitutive and neural-related processes).

When it comes to gene expression, a sriking result was the larger proportion, over ten times, of genes that show significant differential expression in S. gregaria than in L. migatoria. One possibility could be that the lower sequencing depth in S. gregaria might have caused more false positives in that species. However, such possibility is to be descarded, at least as having important effect, given that: (i) the sequencing depth in S. gregaria is ways over the recommended minimum threshold for a good transcriptomics work (see (Wang et al., 2011)), (ii) the quality of the RNAseq results plateaus after a minimum sequencing depth that we largely surpass, (iii) the assembled transciptome in (Bakkali and Martín-Blázquez, 2018) showed good indicators and annotation as expected for a locust CNS, (iv) the large overlap between the CNS trascriptomes of S. gregaria and L. migratoria is not likely to be obtained if one or both transcriptomes were based on isuficient sequencing or contained false positives, (v) our laboratory succesfully PCR amplified several sequences from S. gregaria’s CNS transcriptome, including anonymous sequences, meaning that they are real, (vi) the gene expression differences detected in silico between the solitarious and gregarious S. gregaria CNS was qPCR confirmed in vitro for several genes—in fact, we were cautious and instead of testing genes that show high differences in expression levels, the qPCR confirmation was done for genes that do not show high differences (see (Bakkali and Martín-Blázquez, 2018)), and (vii) several other differentially expressed genes between solitarious and gregarious S. gregaria CNS were confirmed by comparaison with reports on individual genes from the literature (see (Bakkali and Martín-Blázquez, 2018)). Morever, and even if there were an effect of the diference in sequencing depth, such difference would not cause as high difference in the number of diferentially expressed genes as the one we see between both species (i.e., at least part of that difference must be real). Another indicator is the fact that even the anonymous parts of both S. gregaria and L. migratoria CNS transcriptomes used here show high overlap (meaning that even the still unkown sequences that we assembled in both transcriptomes must be real—they can’t appear in two different transcriptomes just by chance). Considering all these, the large difference in the number of differentially expressed genes between phases of S. gregaria and L. migratoria is at least largely real and seems to point towards a more active nature of the phase polyphenism in S. gregaria compared to L. migratoria. It is also a first indication of a species-specific nature of the phenomenon. Indeed, indications of such posibility could be infered from what we know about the specifics of the phase change in different locust species and from the results of some of the previous research on the molecular basis of the differences between the solitarious and gregarious states of the locusts. In an earlier work (Martin-Blazquez et al., 2017) we found that the models that allow infering the phase state of S. gregaria locusts are not useful for L. migratoria and that such incompatibility is due to differences in the way the morphologic and behavioural parameters change between phases in each of these two species (see Fig. 5 in (Martin-Blazquez et al., 2017)). The fact that some characteristics of the phase change are different between locust species (see (Ayali, 2019; Martin-Blazquez et al., 2017; Pener and Simpson, 2009; Pfluger and Braunig, 2021)) is also in line with a highly species-specific nature of the phase change in locusts. In fact, and in addition to laboratory induced differences, that Pener and Simpson ⁴³ suggested as possible explaination to some stricking differences between the results of some laboratories, another possible reason for some of the controversies that struck the locusts research community might be a non-applicability (or non-transferability) of some of the molecular results between species, due to the species-specific nature of the phenomenon that we highlight and highlight again here. That could be a reasonable explanation for the cases cited in ^42,43; including the very publicised case of serotonin as inducer of the gregarious state in S. gregaria (Anstey et al., 2009) and that, four years later, was found to be asociated with the solitarious phase in L. migratoria (Guo et al., 2013).

The fact that we found the general distribution of gene expression levels to be more similar between phases of the same species than between the same phase in different species, together with the notorious differences in the levels of gene expression and in the differencial gene expression levels between phases, further highlight the highly species-specific nature of the locust phase polyphenism that is associated with the outbreak of locust populations. Strikingly, our results are in line with the numerics in the (Kouhei Toga, 2022) work that did not infer any species-specificity, while our results are not in line with the numerics in (Foquet et al., 2021)—especially if we consider the differences in the phylogenetic distances covered in both works— although we both suport a species-specificity nature of locust outbreaks.

However, the apparent high specificity of the locusts’ phase change contrasts with the cross-gregarizing effect of S. gregaria on L. migratoria and viceversa, reported in (Niassy, 1996). Still, high specificity does not mean incompatibility and the cross-gregarizing effect might find room within the genes that change expression level the same way in both species—among which an odorant binding protein is to cite as potential cross-species chemical (see pheromone) detecting molecule that might be involved in sensing the environment and triggering the gregarious state in more than one locust species.

Due to such species-specificity, only 235 genes are significantly different between the solitarious and gregarious phases in both L. migratoria and S. gregaria and, of these, only about half (109 genes) show a change in the same direction in both species, while the rest—being significantly changed between phases of both species—show incongruent direction of change between species.

Another result that could be explained by the highly species-specific nature of the phenomenon is the lack of a clear gene network whose genes change expression in both species. Indeed, apart from the S-adenosylmethionine decarboxylase proenzyme (SamDC) and S-adenosylmethionine synthetase, isoform c (Sam-S), that are related to methylation, the Ankyrin repeat domain-containing protein 49; Lethal 2 35Be (l(2)35Be) and the Lethal (2) 34fc isoform b (l(2)34Fc) genes, that are related to cell division and polarity, and the Small subunit ribosomal protein s21e (40S ribosomal protein S21, RpS21), related to gene expression, the rest of the genes that change expression level in the same way in L. migratoria and in S. gregaria do not associate to other such genes in form of a gene network. Genes related to methylation highlight the importance of the epigenetic regulation of the changes in gene expression levels during locust phase change in general. Genes involved in gene expression highlight the changes in gene expression as common aspect to the development of the gregarious phase in locusts. For their part, genes involved in cell polarity might be explained by the cell shape remodelling (especially of the neurons and their axons) that the required plastic response to life in crowded and stressful conditions involves.

Yet, the 109 genes that change expression level in the same way when the two main pest locusts outbreak and turn gregarious is a very important result. They should give some insight into the general molecular basis of this phenomenon and might provide enough molecules of potential use for the fight against locust outbreaks in general. Among these genes, the presence of less specialized (see constitutive and/or pleiotropic) genes is notorious and might initially seem surprising (i.e., one would naively expect mostly specific genes; such as genes involved in neurotrasmission, response to stimulus, stress…). However, among the common features to all locust phase changes are their association with higher activity of the locusts, increased contagion between individuals of the same population, increased overall transcription, remodeling of the transcriptome, changes at the cuticular level (size, shape and color)…. All these are processes that involve mostly constitutive and pleotropic genes such as those involved in metabolism, immunity, transcription and its regulation, cuticule formation…. Several of such genes we find similarily differentially expressed between the solitarious and gregarious phases of the two main pest locusts. It is however worth highlighting the presence of stress-related (including starvation), G-protein coupled receptor signaling and dendrite morphogenesis processes among the genes that increase expression level in the gregarious phase of both L. migratoria and S. gregaria. The first process clearely relates to the stressing life in crowded conditions, the second to perception of the stimuli resulting from such conditions, and the third to neural remodeling in response to such conditions—both three processes being related to common conditions for the development of the gregarious phase of such plastic, see polyphenic, phenotype in response to life in extremely dense populations. Genes such as the Choline transporter-like 1 (Ctl1), the Odorant binding protein 11, the G protein alpha subunit and the precursor of the l(2)34Fc - Defense protein l(2)34Fc precursor are to highlight.

A triply interesting result of our work are the sequences that had no significat BLAST result against any of the databases used here (see Material and Methods). (i) In 2018, we reported the presence of thousands of non-anotated sequences in S. gregaria (Bakkali and Martín-Blázquez, 2018), the fact that the results of the current work show the shared presence of thousands of non-annotated sequences in the transcriptomes of the two main pest locust species is a clear confirmation of our previous results; i.e., the presence of thousands of transcripts that are still for characterizing (Bakkali and Martín-Blázquez, 2018). (ii) In addition, relevant to the present work, the over 40 anonymous transcripts that show significant differences in expression levels between the solitarious and gregarious states in both locusts offer further material for better understanding the generals of the molecular basis of the locuct outbreaks. Some of these transcripts might also serve as potential locust-specific tagets for the fight against pest locusts. (iii) The fact that these are non-annotated sequences also opens the door for functional characterization and gene discovery works. Thus, the over a hundred genes that we report as changing their expression level in a common and constistent way when the two main pest locusts shift from the solitarious to the outbreak-associated gregarious phase offer suficient material for future functional testings for gene characterization and discovery and in quest of key and/or usefull genes for understanding and fighting against the phenotipic plasticity phenomenon that the locust phase polyphenism is.

Of course very interesting are also the genes that show differential expression between phases in a species-specific way (i.e., genes that are differentially expressed in a species but not in the other or that show incongruent direction of differential expression). In fact, they include genes pertaining to the neuropiptide signalling, G-protein coupled receptor signalling and lifespan related processes—processes that are differentially represented between the transcriptomes of both species—and might provide targets for species-specific fight strategies.

So, being the genes that change expression level the same way in both species very likely important to the development and maintenance of the phase change in locusts, reasons for the species-specific manner how many genes change expression level between these locusts’ phases are not scarce and include not only species-specific differences in the phase change characteristics and conditions (such as those described in (Ayali, 2019; Martin-Blazquez et al., 2017; Pener and Simpson, 2009; Pfluger and Braunig, 2021)) but also differences in many aspects of these locusts’ biology, including differences in development, morphology, behaviour, physiology, reproduction, life conditions, habitat …).

We therefore identify here a set of genes that, by changing expression level between locust phases in the same way in two locust species, must be important for the development or maintenance of the locust outbreak state. They very likely contain useful genes for a better understanding of the phenomenon and probably of use for the fight against locust outbreaks in general—the still new uncharacterized (non-annotated) sequences being of potential uses as locust-specific. Still, being this a comparative transcriptomics work, we limit ourself to a general interpretation of the results and to highligting the genes that are consistently associated with the gregarious phase of the locusts. The real functional implications and importance of each of such genes as potential target for any possible fight strategy depends on its functional implications; an aspect that we are starting to evaluate by funtional genomics techniques in our laboratory. It is also highlighting the genes that change expression is a species-specific manner as potentially containing genes for the possible fight against locust outbreaks in a species-specific way. Being those genes indicators of a mostly species-specific nature of the molecular basis of the phase change in locusts, it is worth re-stressing that our findings suggest that researching each locust species, rather than focusing on just one or few species, is recommended due to the highly species-specific nature of the locust outbreak phenomenon.

Comparing the gene expression levels changes between the solitarious and gregarious CNS of the two main pest locust species suggest that locusts’ phase change, associated with locust populations outbreaks and swarming, is mostly species-specific and no one species can serve as model for studying the phase change in all locust species.

The genes that change expression differently between phases of the two locusts species contain genes involved in live conditions and physiological aspects that differ between the two species as well as genes genuinely involved in the phase change phenomenon. These latter should provide material for understanding and dealing with the locusts’ populations outbreak and swarming phenomenon in a species-specific way.

Still, the over a hundred genes that change expression level in the CNS the same way when the two main pest locusts change phase must be involved in the locust phase change in an important and/or ancestral way. The also should provide material for understanding and dealing with the locusts’ populations outbreak and swarming phenomenon in general.

The tens of transcriptome contigs that have no BLAST match in the databases (the anonymous sequences) seem genuine, for being found in two different species. Just like the known genes, the anonymous sequences that show expression level differences between the solitarious and gregarious CNS should provide material for either species-specific or general studies and fight strategies against locusts. They also provide material for gene discovery.

CNS

Central nervous system

Gene onthology

GLM

Generalized linear model

PCR

Polymerase chain reaction

qPCR

Quantitative polymerase chain reaction

Ethics approval and consent to participate: Not applicable.

Consent for publication: Not applicable.

Availability of data and materials: Not applicable.

Competing interests: Not applicable.

Funding: Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación (Spain), grant Ref. PGC2018.097678.B.I00.

Authors' contributions: A.B. Analyzed data, prepared some figures and tables, and participated in the interpretation of the results and in revising the manuscript. M.B. Conceived and planed the research, secured funding, data analysis, prepared some figures and tables, wrote part of the first draft of the manuscript, and participated in the interpretation of the results and in revising the manuscript. N.B. Analyzed data, prepared some figures and tables, wrote part of the first draft of the manuscript, and participated in the interpretation of the results and in revising the manuscript. S.S. Analyzed data, prepared some figures and tables, and participated in the interpretation of the results and in revising the manuscript.

Acknowledgements

M. Bakkali wants to thank the Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación (Spain) for the grant Ref. PGC2018.097678.B.I00 that funded this work. M. Bakkali and S. Saadi want to thank the ERASMUS+ International Dimension Programme for the studentship at the University of Granada for the studentship to S. Saadi.

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No competing interests reported.

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Comparative transcriptomics suggests a highly species-specific nature of the phenotypic plasticity associated with the outbreaks of the two main pest locusts.

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Abstract

Background

Methods

Results

Figures

Introduction

Materials and methods

Transcriptome assembly and annotation

Comparative transcriptomics and differential gene expression analysis

Results

Assembly and annotation

Gene expression

Functional annotation

Gene network analysis

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1