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Abstract
ABSTRACT
Mesopelagic fish are among the most abundant vertebrates on Earth and play a crucial role in carbon sequestration through their daily vertical migration. However, their dietary ecology remains poorly understood, especially in the Red Sea, limiting our grasp of their trophic interactions and ecological roles. This study investigates the dietary composition of two common mesopelagic fish species in the Red Sea, the lanternfish (
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Introduction
The mesopelagic layer, extending from 200 to 1000 m, is a fundamental component of the ocean ecosystem linking the biogeochemical and ecosystem dynamics of the overlying upper ocean and the underlying deep sea (Davison et al. 2013). Mesopelagic fish, supporting the largest fish stock in the world ocean with a recent estimate of approximately 10 billion tonnes (Irigoien et al. 2014), play a pivotal role as both predators and prey in intricate food webs (Cherel et al. 2010). Mesopelagic fish perform diel vertical migration (DVM; Klevjer et al. 2016), which profoundly impacts carbon and nutrient cycling and facilitates energy transfer between surface and deeper layers, thereby playing a critical role in biogeochemical cycles, including the active ocean biological carbon pump (Hernández-León et al. 2020; Irigoien et al. 2014; Robinson et al. 2010).
The Red Sea presents a unique environment for studying mesopelagic fish behavior and ecology due to its dense and distinct deep-scattering layers primarily comprised of fish (Kaartvedt et al. 2024, 2019; Klevjer et al. 2012). Among the most abundant species are the lanternfish
Research has shown a high variation in the biodiversity and size of prey items consumed by lanternfish species, which may be attributed to their life stages, behavior, and anatomical features (Dalpadado and Gjosaeter 1988; Dypvik and Kaartvedt 2013; Loutrage et al. 2024; Martin and Davis 2020). While mesopelagic fish are generally understood to have a crustacean-dominated diet (Dalpadado and Gjosaeter 1988; Dypvik and Kaartvedt 2013), detailed comparative studies, particularly in oligotrophic environments like the Red Sea, are lacking. Previous studies have indicated that
This study addresses these gaps by integrating DNA metabarcoding and remotely operated vehicle (ROV) footage to elucidate the dietary preferences and trophic interactions of Benthosema taxa and V. mahabiss. Utilizing Cytochrome Oxidase 1 (COI) primer sets through next-generation sequencing (NGS), this study overcomes traditional sampling limitations, providing a comprehensive analysis of gut contents, including soft-bodied and highly digested prey (Leray et al. 2015, 2013). This approach reveals detailed insights into prey composition and diet partitioning but also offers potential detection of cannibalism and intra-specific interactions, although some limitations exist due to primer affinity with predator DNA and the need for high sequencing depth. The integration of ROV footage further highlights benthic feeding behaviors—a phenomenon rarely documented in mesopelagic fish—which may reflect an adaptive response to resource availability in oligotrophic environments. By linking these findings to broader ecological processes, such as food web dynamics and energy flow between pelagic and benthic systems, our study advances understanding of the ecological roles and evolutionary strategies of mesopelagic fish in shaping trophic interactions and ecosystem functioning in the Red Sea and similar environments.
Materials and Methods
Fish Collection and ROV Video Analysis
All fish were collected as bycatch of animals attracted to the lights of the ROVs and impacted by the motion of the thrusters during ROV activities conducted as part of the Red Sea Decade Expedition, conducted between February and June 2022. Sampling was carried out at 19 stations along the continental slope of the Red Sea, at depths of 252–818 m, corresponding to the mesopelagic scattering layer (200–800 m) and the migration profile of mesopelagic fish in the region (see Kaartvedt et al. 2024 and references therein). Most sampling (n = 17) occurred during the day (between 06:00 and 12:00) near the seafloor when ROV intersects their downward migration. One-minute ROV video clips (n = 17) were analyzed to document mesopelagic fish behavior, focusing on their interactions and potential feeding within the benthic environment. Behaviors such as swift darting near the seafloor and predation by benthic-dwelling organisms were noted. Sampling stations in the Red Sea were grouped into two provinces (Northern vs. Southern) based on the distribution of our samples (Figure 1, Table S1). Upon collection, the fish were stored at −20°C and transported back to King Abdullah University of Science and Technology (KAUST). At KAUST, each fish was photographed, measured, weighed, morphologically identified, and stored in 70% ethanol prior to DNA extraction (Table S2 in Data S1). The research was performed under ethics approval (23IBEC055).
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Sample Preparation and DNA Extraction
Stomach contents were extracted from 30 individuals of Benthosema taxa and 30 individuals of
DNA Amplification, Library Preparation, and Next Generation Sequencing
To study the gut communities, the mitochondrial COI region was amplified using the “mlCOIintF” and “jgHCO2198” primers (Wangensteen et al. 2018) with Illumina overhang adapters. The polymerase chain reaction (PCR) was conducted following the Universal Multiplex Cycling Protocol recommended by QIAGEN. The PCR cocktail consisted of 1× QIAGEN Multiplex PCR master mix (QIAGEN, Valencia, CA, United States), 0.2 μM of both forward and reverse primers, 3 μL of genomic DNA, and 8.5 μL of RNase-free water, totaling 25 μL. PCR was conducted on a Applied Biosystems SimpliAmp thermal cycler (Thermo Fisher Scientific, Waltham, MA, USA). The thermal cycling profiles consisted of an initial denaturation at 95°C for 15 min, followed by 35 cycles of denaturation at 94°C for 30 s, annealing at 55°C for 90 s, extension at 72°C for 90 s, and a final elongation step at 72°C for 10 min. PCR products were visualized on a 1.5% agarose gel (1xTAE) stained with SYBR Safe (Invitrogen, Carlsbad, CA). For PCR negative controls, the DNA template was substituted with RNase-free water. All PCR products were cleaned with AMPure XP beads using a bead-to-sample ratio of 0.8×, following the Illumina library preparation workflow until PCR Clean-Up 2. The concentration of the amplification products was quantified using a Varioskan Lux multimode microplate reader (Thermo Fisher Scientific, Waltham, MA, USA) using the Qubit 1X dsDNA HS Assay kit and pooled in equimolar ratios. The pooled samples were quantified using the Qubit 4.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and loaded on an Illumina Novaseq 6000 2×150 bp flow cell at 10 pM at the Bioscience Core Lab, KAUST.
Bioinformatic Processing
Demultiplexing was carried out by the sequencing facility. To accurately reflect species composition within the gut content community, especially for metazoans exhibiting high intraspecific polymorphism in the COI gene (Brandt et al. 2021), we initially obtained Exact Sequence Variants (ESVs) and subsequently clustered them into Operational Taxonomic Units (OTUs) as recommended by the literature (Antich et al. 2021; Brandt et al. 2021; Porter and Hajibabaei 2020). This two-step approach was implemented to balance the high resolution of ESVs with the potential biological relevance of OTUs in our study. Specifically, paired-end reads were processed using a modified version of Apscale v1.6.3 (Buchner et al. 2022), in which Swarm (Mahé et al. 2022) was implemented as an alternative to vsearch (Rognes et al. 2016) for OTU clustering. The modified pipeline also included DnoisE (Antich et al. 2022) as an alternative to unoise for denoising, with the option to first denoise reads before clustering the denoised reads into OTUs. Additionally, microDecon (McKnight et al. 2019) was used to remove reads found in PCR negative controls from true samples. This modified version of the Apscale pipeline was executed as follows: the maximum expected error (maxEE) was set to 2 (discarding reads with more than 2 expected errors), minimum and maximum read lengths were set to 303 bp and 323 bp, respectively (discarding merged reads not within the target amplicon length), reads were denoised using DnoisE with default parameters before being clustered into OTUs using Swarm, and default parameters were applied for paired-end merging, primer trimming, dereplication, pooling, and LULU filtering (Frøslev et al. 2017). The modified version of Apscale is available on GitHub (), as well as a wrapper to run apscale in the command line ().
We assigned taxonomy to the OTUs using BLAST (Altschul et al. 1990) against the MIDORI2 COI database (Leray et al. 2022) v257 (MIDORI2_UNIQ_NUC_GB257_COI_BLAST) using an E-value threshold of 1e-05. We filtered BLAST hits as follows: (1) all hits with a bitscore < 150 and an alignment length of < 100 were excluded, (2) for every OTU, all hits whose bitscore did not fall within a 2% margin of the highest bitscore were excluded, (3) if multiple taxa occurred among the remaining hits, only their Lowest Common Ancestor was retained, and (4) taxonomic lineages were trimmed based on percentage identity to the query; specifically, we trimmed at 98%, 95%, 90%, 85%, 80%, and 75% for the species, genus, family, order, class, and phylum levels, respectively, meaning that only hits with a percentage identity score of > 98% were assigned to the species level and so forth. This stringent filtering approach ensured the minimization of false-positive detections.
Data Analyses and Visualization
We removed singletons, terrestrial contamination, and non-target host sequences from the dataset (i.e., three OTUs identified as Myctophidae and Phosichthyidae) (Table S2 in Data S1). The relative abundances of the top 10 abundant phyla were visualized using bar charts. To understand the distribution of prey reads of mesopelagic fish, all OTUs were initially classified into broad taxonomic categories: fungi, protists, algae, metazoans, and unidentified sequences. Focusing on metazoans, we then employed a stepwise zooming approach, examining the most abundant taxa composition progressively at the phylum, class, and order levels.
Data analysis and visualization were conducted in R (R Core Team, 2024) using the packages: microViz (Barnett et al. 2021), phyloseq (McMurdie and Holmes 2013), ggvenn (Yan 2023), vegan (Oksanen et al. 2015), tidyverse (Wickham et al. 2019), colorRamps (Keitt 2024), and bipartite (Dormann et al. 2008). The alpha diversity of the prey items (richness, Shannon, and Simpson indices) of the two host species was calculated using the estimate_richness() function from the phyloseq package. Beta diversity between the two host species was illustrated using non-metric multidimensional scaling (NMDS) based on the robust Aitchison distance (Martino et al. 2019). To test for similarity among species and provinces from which individuals were sampled, we performed a permutational analysis of variance (PERMANOVA) on the robust Aitchison distance matrix, using the adonis2() function in vegan, with species and province as predictor variables with 9999 permutations. Following PERMANOVA, we tested the homogeneity of group dispersions using the betadisper() function in vegan to ensure the significant results from PERMANOVA were not influenced by differences in dispersion among groups.
To explore the dietary preferences of each host species, we constructed a bipartite network representing associations between higher-level metazoan prey taxa and the two fish species based on the relative abundances of prey OTUs. To streamline the analysis, we filtered out all OTUs with < 0.5% relative abundance across both species. Subsequently, we taxonomically classified the remaining OTUs: those identified with at least a 95% sequence identity were assigned to the order level, while those with a match between 75%–95% identity were assigned to the class level. OTUs with less than a 75% identity match were classified at the phylum level. Using this dataset, prey items were categorized as pelagic, benthic, or benthic-pelagic (representing taxa that could inhabit both environments) based on their adult life stages, with any non-assigned taxa labeled as unidentified. We also performed indicator species analysis to identify prey taxa that were specifically associated with one fish species over the other. This method tests for both fidelity (the probability that a prey taxon occurs within a particular fish species) and specificity (the degree to which a prey taxon is restricted to one fish species). The analysis was based on the relative abundance of each prey OTU in the gut contents, and we used this to determine which prey taxa were indicators of the diet for each host species.
Results
Gut Prey Communities
A total of 120,074,724 reads, binned into 826 Operational Taxonomic Units (OTUs), were retrieved from 60 gut samples of the two studied species. Host reads assigned to Benthosema taxa and
Our analysis revealed that apart from arthropods, the diet of mesopelagic fish included a significant portion of benthic prey. Benthosema taxa notably consumed hard-bodied prey such as annelids, molluscs, and echinoderms, which are indicative of benthic interactions. Although
Comparison Between the Prey Composition of
We observed a decreasing percentage in overlapping prey taxa between both host species as taxonomic resolution increased from phylum to species level (Figure S1 in Data S1). At the phylum level, the three most abundant prey taxa were Arthropoda, Chlorophyta, and Mollusca (Figure 2). Arthropods constituted more than 50% of the total prey reads in three Benthosema taxa and 16
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Prey Diversity and Composition
To assess the diversity of the prey communities, all samples were rarefied to an even sequencing depth, leading to the exclusion of 21 OTUs from the analysis.
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Non-metric multidimensional scaling (NMDS) ordination based on the robust Aitchison distance revealed clustering of the two host species but no clear separation among the two defined provinces within the Red Sea (stress = 0.164, Figure 4). PERMANOVA analysis revealed that species (df = 1, F = 3.543, R2 = 0.055, p < 0.01) was a more significant factor than province (df = 1, F = 2.534, R2 = 0.040, p < 0.01) in explaining dietary differences. All groups showed homogeneous dispersion in the ordination space based on their centroids (PERMDISPspecies: df = 1, F = 0.187, p = 0.67; PERMDISPprovince: df = 1, F = 0.2677, p = 0.61).
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Bipartite Network of Metazoan Prey
To focus on metazoan prey composition between the two species, non-metazoan taxa (i.e., algae, fungi, and protists) were excluded from the bipartite network analysis. Benthosema taxa consisted of 18 times more benthic prey sequences and 0.4 times fewer pelagic prey sequences than
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In terms of taxa-specific prey comparison, Benthosema taxa had a higher proportion of polychaete sequence reads compared to
Benthic Interaction From ROV Footage
Of the 17 video clips analyzed, nine (52.9%) documented mesopelagic fish interacting with the seafloor, displaying rapid darting movements indicative of potential benthic feeding behavior (see Videos S2–S4). While precise species identification was challenging due to low video resolution and the swift movements of the fish, these interactions were frequently observed near the continental slope at the depth range of 496–778 m. Though the darting movements might initially appear to be startle responses to the ROV's presence and light, their consistent occurrence suggests natural feeding patterns. This observation aligns with the detection of benthic prey in gut content analyses, supporting the hypothesized benthic feeding behavior among mesopelagic fish.
Discussion
Our metabarcoding analysis confirms that both Benthosema taxa and
Zooplankton as the Main Food Source
In the Red Sea, both species undergo normal diel vertical migration (NDVM) to the upper ~200 m of the water column at night, where calanoid copepods are abundant (Dypvik and Kaartvedt 2013; Klevjer et al. 2012). Although we did not directly measure prey abundance in their habitat, the notable prevalence of copepod reads in gut samples (class Hexanauplia, ~49% of metazoan prey) suggests efficient exploitation of available prey resources. This finding highlights the importance of these mesopelagic fish in the vertical transfer of biomass and nutrients within the Red Sea ecosystem.
Apart from arthropods, both fish species also consumed molluscs, cnidarians, and chaetognaths. The composition of the zooplankton community in the Red Sea is shaped by local oceanographic conditions, depth, topography, and seasonality (Casas et al. 2017; Pearman et al. 2014; Pearman and Irigoien 2015). Our sampling, conducted from February to June 2022 during the cold season (December to May), aligns with the dominance of these taxa in the mesopelagic fish diet, particularly arthropods and cnidarians, with smaller proportions of chaetognaths and molluscs (see Casas et al. 2017). It should be noted that the ingested zooplankton likely included larvae or juvenile stages, considering the relative sizes of predator and prey.
Novel Evidence of Benthic Feeding
Our study reveals a substantial presence of benthic prey sequences in the gut contents of Benthosema taxa, providing the first molecular evidence of mesopelagic fish in the Red Sea consuming benthic organisms, such as polychaetes, echinoderms, and gastropods. This challenges the traditional view of mesopelagic fish as strictly pelagic predators and suggests a more flexible, mixed diet that includes opportunistic benthic feeding. Video footage from ROV observations supports this finding, showing mesopelagic fish interacting with the continental shelf, with rapid darting movements suggestive of foraging behavior. Previous studies (Gartner et al. 2008; Klevjer et al. 2012) have hinted at similar behavior using acoustic and visual data but lacked direct confirmation from dietary analyses. Our study advances these observations with visual evidence of active benthic feeding (Videos S1–S3), corroborated by gut content analyses revealing benthic taxa such as polychaetes, echinoderms, and gastropods.
Ecological and Physiological Considerations
Several hypotheses may explain the presence of benthic prey in mesopelagic fish diets: (1) opportunistic feeding on the seafloor during daytime descent; (2) attraction to the seafloor due to artificial light from the ROV; (3) consumption of benthic prey in larval form within the meroplankton community; (4) physiological adaptations that facilitate the exploitation of benthic resources near the slope; and (5) anatomical adaptations that enable the capture and processing of hard-bodied prey.
The interactions observed between mesopelagic fish and the seafloor suggest that opportunistic feeding along the continental slope may occur as these fish descend to their daytime residence depths, typically between 500 and 750 m (Dypvik and Kaartvedt 2013). This descent coincides with periods of minimal pelagic feeding activity, raising the possibility that mesopelagic fish exploit benthic resources when they intersect continental slopes or underwater features during diel vertical migration (Gartner et al. 2008; Isaacs and Schwartz 1965; Mauchline and Gordon 1991). Supporting this hypothesis, we observed occasional associations of mesopelagic fish with benthic-dwelling organisms, such as sea anemones, pandalid shrimps, and deep-sea groupers (personal observation). Furthermore, the presence of benthic prey in their gut contents reinforces the hypothesis that mesopelagic fish incorporate benthic foraging into their feeding strategy. The attraction of Red Sea mesopelagic fish to artificial light is well documented (Dypvik and Kaartvedt 2013; Kaartvedt et al. 2019; Klevjer et al. 2012). As visual predators (Sabatés and Saiz 2000), mesopelagic fish may exhibit feeding responses to artificial light, influencing their interactions with benthic environments (Conley and Hopkins 2004).
Our findings suggest that the detected benthic prey items, particularly molluscs and echinoderms, likely represent larval forms within the meroplankton community. Notably, Benthosema taxa consumed a high number of molluscs, particularly bivalves, which constituted approximately one-third of metazoan prey (Figure 5). This observation is consistent with a previous record of mollusk prey items (size between 0.5–1.5 mm) in the gut of
Physiological adaptations may facilitate benthic feeding. Despite low oxygen conditions (< 1.5 mL O2 l−1) below 300 m in the Red Sea (Dypvik and Kaartvedt 2013), these fish have adapted to sustain high levels of activity, such as fast swimming and feeding. This adaptation is likely driven by the high metabolic demands associated with the relatively warm deep waters of the Red Sea (~21°C), necessitating frequent feeding to meet their energetic needs (see Klevjer et al. 2012 and references therein). Consequently, they may occasionally exploit benthic resources alongside their usual planktonic diet.
Additionally, anatomical adaptations play a crucial role in the feeding strategies of these fish. Studies suggest that predator agility, buccal part size, and dentition influence prey size and type (Alwis and Gjøsæter 1988; Legand et al. 1972; Martin and Davis 2016; Zavala-Muñoz et al. 2019). The evolution of heterodonty in mesopelagic fish likely enhances their feeding ecology (Martin and Davis 2020). For instance, lanternfish such as
Species-Specific Dietary Partitioning
Despite compositional similarities in prey communities, we observed significant differences in alpha diversity, with
The Role of Algae as Secondary Predation
Unexpectedly, we recovered a substantial read of algae in the gut contents of both fish species. Phytoplankton, particularly the class Chloropicophyceae, dominated the algae reads, comprising up to 65% of total prey reads. Chloropicophyceae, a recently described phytoplankton class (dos Lopes Santos et al. 2017), has not been previously reported in the Red Sea. Although the Red Sea is characterized as an oligotrophic environment with low nutrient availability, phytoplankton remain the foundation of the food web, contributing significantly to primary production (Al-Otaibi et al. 2020; Coello-Camba and Agustí 2021; Pearman et al. 2017). The presence of algae in fish gut contents likely reflects secondary predation. This occurs when dietary components of prey organisms are detected in the predator's gut—a common phenomenon observed in mesopelagic fish dietary studies employing metabarcoding (Clarke et al. 2020). The high abundance of algae in gut contents is unlikely to result from direct consumption, as the fish were captured during daylight hours at great depths, when feeding activity is minimal (Dypvik and Kaartvedt 2013). Instead, it reflects the dietary patterns of their primary prey, particularly copepods, which graze extensively on phytoplankton (Cornils et al. 2007; Sommer et al. 2002). Given the estimated digestion rate of mesopelagic fish (~12 h; Dypvik and Kaartvedt 2013), metabarcoding likely captured prey items at different stages of digestion, further supporting the secondary predation of algae. Further investigation is required to elucidate the exact mechanisms driving these dietary patterns.
Parasite Detection
The detection of parasites within fish guts underscores the potential role of mesopelagic fish as intermediate hosts in trophic interactions within deep-sea ecosystems. These microscopic parasites are usually found in the organs (e.g., stomach, intestine, and mesenteries) and the body cavities of mesopelagic fish and therefore represent endoparasites. These endoparasites are not readily detectable by the naked eye, necessitating the application of genetic techniques. Myctophid-specific parasites include nematodes (e.g., Anisakis spp., Hysterothylacium aduncum, Phyllobothriidae, Elytrophalloides oatesi) and digeneans (
Ecological Implications
Our study provides new insights into the feeding ecology of mesopelagic fish in the Red Sea, particularly the role of benthic feeding. By integrating metabarcoding data and video evidence, we highlight the flexible foraging strategies employed by these fish, which may allow them to exploit both pelagic and benthic prey. This behavior has implications for nutrient transfer within deep-sea ecosystems and the ecological roles of mesopelagic fish.
The discovery of benthic feeding necessitates a re-evaluation of the role of mesopelagic fish in carbon sequestration. Given their substantial biomass in the Red Sea (Abu El-Regal and Ditty 2023; Isari et al. 2017), these fish can contribute 10%–40% of deep ocean carbon export through defecation, respiration, extraction and predation during diel vertical migration (Saba et al. 2021). Recent estimates suggest that mesopelagic fish contribute approximately 16.1% (± 13%) to total carbon flux out of the euphotic zone (100–200 m), equivalent to 1.5 ± 1.2 Pg C per year (Saba et al. 2021). Their interactions with the benthic community suggest an additional pathway for nutrient transfer, warranting further exploration into how benthic feeding influences carbon cycling and the ecological impacts of these interactions.
While our findings emphasize the importance of benthic prey in Benthosema taxa, it is equally important to consider the role of gelatinous prey in the trophic dynamics of
Limitations of the Study
The removal of host reads, which comprised 89.4% of total sequence reads, was crucial for obtaining accurate metabarcoding results, especially considering the potential for sample contamination from shared preservation in the same zip-lock bags. As lanternfish are known to be piscivorous (Dalpadado and Gjosaeter 1988), host sequence reads may reflect cannibalism and trophic linkages between species rather than host materials, which cannot be resolved with the available data. Indeed, the small size of mesopelagic fish necessitated processing their entire alimentary tract, leading to a significant proportion of host-derived sequences. Caution is therefore warranted when interpreting relative sequence abundances of prey items (Casey et al. 2019; Deagle et al. 2019). Moreover, the high proportion of unidentified OTUs underscores the need for comprehensive DNA barcode libraries in the region. While combining morphological and genetic analyses may improve taxonomic assignments, identifying prey items remains challenging due to the database gaps and morphological constraints.
Conclusion
Our study reveals distinct dietary patterns among mesopelagic fish in the Red Sea, particularly Benthosema taxa and
Author Contributions
Kah Kheng Lim: conceptualization (equal), data curation (lead), formal analysis (lead), methodology (lead), resources (equal), software (equal), visualization (lead), writing – original draft (lead). Carlos Angulo-Preckler: conceptualization (equal), methodology (equal), project administration (supporting), resources (equal), writing – review and editing (equal). Christopher A. Hempel: conceptualization (supporting), data curation (supporting), methodology (supporting), software (equal), writing – review and editing (equal). Mohammad A. Qurban: funding acquisition (equal), resources (equal), resources (equal), writing – review and editing (equal), writing – review and editing (equal). Vincent A. Pieribone: resources (equal). Carlos M. Duarte: conceptualization (equal), funding acquisition (equal), supervision (lead), writing – review and editing (equal).
Acknowledgements
We thank the National Center of Wildlife (NCW) for inviting us to participate in the Red Sea Decade Expedition (2022). We are grateful to the staff of the R/V OceanXplorer for their logistical support and to Ms. Jennifer Thomson for collecting the fish samples onboard. Our gratitude extends to the lab members of the Tarek Ahmed Juffali Research Chair (TAJRC) and colleagues who assisted with sample collection. We also thank the KAUST Bioscience Core Lab for their NGS sequencing support. We acknowledge Michael Keesy, the creator of PhyloPic, and all contributors of silhouettes used in Figure S1, which are available under Creative Commons licenses. The Red Sea Decade Expedition was funded by the National Center for Wildlife (NCW, Kingdom of Saudi Arabia). King Abdullah University of Science and Technology (KAUST) also supported this research through baseline funding awarded to C.M.D. (BAS/1/1071-01-01).
Conflicts of Interest
The authors declare no conflicts of interest.
Data Availability Statement
The raw sequencing data used in this study is available in NCBI with the BioProject ID: PRJNA1179974 and R script can be found in the publicly accessible repository ().
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