{"paper_id":"3fd4ab24-981f-4934-9d41-45e2ad6f4f79","body_text":"Insights into Platypus Crural Gland Transcriptomics – Venom and Beyond | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Insights into Platypus Crural Gland Transcriptomics – Venom and Beyond Adele Gonsalvez, Emma Peel, Carolyn J. Hogg, Katherine Belov This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7394805/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Nov, 2025 Read the published version in BMC Genomics → Version 1 posted 10 You are reading this latest preprint version Abstract Background The platypus ( Ornithorhynchus anatinus ) is one of 15 confirmed venomous mammals worldwide, and possesses a unique venom system, termed the crural system. Used for intraspecific competition, their sexually dimorphic and seasonal venom causes pain and functional impairment in envenomated individuals. Despite its unique nature, investigations into the platypus crural system are limited. Utilising the new platypus genome and a suite of transcriptomic data collected over the past 15 years, we investigate key genes, transcripts and proteins of importance to the platypus crural system. Results We generated a global transcriptome and a crural gland-specific transcriptome for the platypus, utilising the new platypus genome and 45 RNA-Seq samples collated from past studies. From this, we found 177 upregulated and crural gland specific genes of importance. 13 putative toxins have been identified for the first time. 85% of these belong to protein families found in venoms and include kallikreins and secretoglobins key in mammalian venoms. Three putative toxic kallikreins were identified as well as two additional putative toxins that may be influencing kallikrein activity in platypus venom. All three putative toxic secretoglobins belong to an independent cluster of uteroglobin-like proteins and are unique to the platypus. Conclusions New omics resources have allowed us to uncover new genes, transcripts and proteins of importance to platypus venom and their crural system. This work reinforces the importance of convergent recruitment in the toxin repertoires of venomous mammals through proteins such as kallikreins and secretoglobins. Our findings have enhanced knowledge of the platypus crural system and provided new insights into platypus venom composition. platypus venom transcriptome monotreme kallikrein secretoglobin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Venoms are complex mixtures of bioactive compounds, containing proteins, salts, and organic molecules, that disrupt the normal physiological or biochemical processes of the targeted individual ( 1 ). Venom has independently evolved over a hundred times in both invertebrates and vertebrates ( 2 ), resulting in hundreds of thousands of venomous species ( 3 ). As such, venoms display high levels of molecular and compositional diversity, making them attractive sources for the discovery of novel compounds of biological, immunological and pharmacological importance ( 4 ). With majority of venom research centered around prolific venomous taxa, such as snakes and arthropods, investigations into the venom systems and venom compositions of mammals only began in the last few decades ( 5 ). These largely uncharacterised venoms potentially harbour unique proteins of importance. The platypus ( Ornithorhynchus anatinus ) is a unique semi-aquatic, semi-fossorial monotreme endemic to eastern Australia and Tasmania ( 6 ). It is one of only fifteen experimentally confirmed venomous mammals ( 7 , 8 ), and the only venomous mammal within the Order Monotremata. As a monotreme, the platypus is the most evolutionarily distinct lineage of venomous mammals, with all other venomous species as Eutherian mammals that belong to the Orders Eulipotyphla (shrews and solenodons), Chiroptera (vampire bats) or Primates (slow lorises) ( 9 ). The platypus venom system is termed the crural system and consists of a crural gland connected via the crural duct to a hollow, keratinised spur located on their hindlimbs through which venom is delivered ( 10 ). While all platypuses are born with the crural system, it is sexually dimorphic, with the vestigial spur sheath regressing in females by age one and venom production developing in males by age two ( 11 , 12 ). The platypus crural system is also seasonal, with an increase in crural gland size and venom production during the spring breeding season in conjunction with androgen production and increased testicular size ( 13 , 14 ). This is directly linked to the role of platypus venom in intraspecific competition, whereby males use their venom to immobilise male conspecifics to gain a mating advantage during the breeding season ( 10 , 15 ). In humans, platypus envenomation is non-fatal, yet causes intense pain, hyperesthesia, allodynia, oedema and functional impairment ( 16 – 18 ). Treatment has previously included a nerve blocker to help reduce pain ( 16 ), with mixed results on the effectiveness of analgesics ( 16 – 18 ). In vitro, platypus venom causes smooth muscle relaxation and haemolysis ( 19 ), and acts on sensory neurons ( 20 ). Initial chemical investigations into platypus venom composition identified at least nineteen fractions, containing a range of components such as defensin-like peptides (DLPs), a nerve growth factor (OvNGF), C-type natriuretic peptide (OvCNP), isomerase, hyaluronidase and proteases ( 15 , 21 ), all of which have similar counterparts in other venoms ( 1 , 22 – 24 ). In the platypus, DLPs, OvNGF and OvCNP have been studied in-depth, with their gene and protein sequences identified and putative functions elucidated ( 25 – 29 ). DLPs and OvNGF are possibly synergistic and predicted to be associated with the intense pain and hyperalgesia caused by platypus envenomation ( 29 – 31 ). OvCNP has been shown to cause cation channel formation ( 32 ), oedema, and mast cell histamine release in rats ( 25 ), in addition to likely contributing to hypotension ( 33 ). These components likely represent only a small fraction of total bioactive molecules within platypus venom, the majority of which have not been studied. Following the release of the first platypus genome in 2008 ( 34 ), only two genetic-based investigations of venom have been conducted ( 35 , 36 ). In-season crural gland cDNA libraries found 88 putative venom genes with homology to established toxin families ( 35 ). A subsequent investigation based on crural gland RNA sequencing (RNA-Seq) identified 10 venom proteins, five of which belonged to protein families previously unreported in venoms of other taxa ( 36 ). As such, our current understanding of platypus venom composition and features of the crural system is limited. This is due to difficulties in sampling both venom and crural gland tissue from this enigmatic species. Also, venom discovery pipelines are often tailored for specific taxonomic groups and require substantial existing toxin databases for similarity-based toxin identification, increasing the complexity for discovering toxins in the platypus. New technological developments and resources, however, now provide the opportunity to collate larger datasets and search for previously unidentified genes and proteins key to platypus venom to improve our understanding of the platypus crural system more broadly. The release of a high-quality chromosome-length platypus genome in 2021, with 90% of gaps filled, greatly improved contig and scaffold contiguity, providing substantial improvements in gene annotation ( 37 ). This genome has enabled an improved platypus crural gland transcriptome assembly, and subsequent identification of proteins key to the platypus crural system. In this study, we utilise this improved platypus genome, as well as a suite of RNA-sequencing data collated over the past 15 years, to revisit platypus venom composition for the first time since 2012. Our aim was to identify genes, transcripts, and proteins of importance to the platypus crural system, increasing our understanding of platypus venom and the crural system. Methods Transcriptome generation Raw platypus RNA-Seq data publicly available from the National Center for Biotechnology Information (NCBI) database ( 38 ) was collated for analysis ( 35 , 39 – 44 ) (Additional File 1). Only Illumina sequencing was included in this study, due to discrepancies in processing 454 data with bioinformatic tools constructed for Illumina sequencing data. RNA-Seq reads were quality checked pre- and post-trimming using FastQC v0.11.8 ( 45 ) and trimmed using Trimmomatic v0.39 ( 46 ). Trimmomatic flags were used to remove adapter sequences (Additional File 2: Table S1 ), 5’ and 3’ ends of reads, reads under 25 base pairs (bp), and reads with a quality score under 5 in a sliding window of 4bp. Trimmed reads were aligned to the platypus reference genome mOrnAna1.pri.v4 (NCBI RefSeq assembly GCF_004115215.2) ( 37 , 38 ) using HISAT2 v2.1.0 ( 47 ). Samples with an overall alignment rate < 75% were removed from the dataset. Aligned SAM files were converted to BAM files and indexed using SAMtools v1.9 ( 48 ), and a GTF file for each tissue sample was generated using StringTie v2.1.6 ( 49 ). The genome annotation file (NCBI Ornithorhynchus anatinus Annotation Release 105) ( 37 ) was used as the basis for gene identification. Genes previously identified in platypus crural gland or venom studies ( 27 , 35 , 36 ) were manually annotated within the mOrnAna1.pri.v4 genome assembly using BLAST + v2.7.1 ( 50 ), and added to the genome annotation file, henceforth referred to as the modified genome annotation file. Duplicated annotations between manually and NCBI annotated genes were resolved by using the NCBI gene when its coordinates encapsulated one or more other genes, or otherwise favouring manually annotated genes as manual annotations are known to produce higher accuracy for some gene families ( 51 ). To generate a global transcriptome, GTF files were merged using StringTie, guided by the modified genome annotation file (containing both NCBI and manually annotated genes). Tissue types included in the global transcriptome were in-season crural gland, brain and cerebellum, fibroblast, heart, kidney, liver, ovary, and testis. Transcripts were only included if their read length was ≥ 30 bp and fragments per kilobase million (FPKM) transcript count was ≥ 0.1. CPC2 v1.0 ( 52 ) was used to remove single exon non-coding transcripts that did not match entries within in the modified genome annotation file. Additional transcripts identified by StringTie were removed from the global transcriptome if they matched or overlapped with an annotation from the modified genome annotation file (determined using bedtools intersect v2.29.2 ( 53 )). The final global transcriptome contained transcripts encoding genes that matched the NCBI and manual annotations, as well as these additional StringTie. To generate a crural gland-only transcriptome, the global transcriptome was filtered to remove transcripts corresponding to genes that were not expressed in any of the eight crural gland samples included in our study. For each transcriptome, calculations were done for functional completeness against the mammalia_odb10 database using BUSCO v5.8.0 ( 54 ) on Galaxy Australia as well as average transcript length and N50. Identification of key crural genes Raw gene counts for downstream analyses in R v4.3.2 ( 55 ) were generated using featureCounts in Subread v1.5.1 ( 56 ) using aligned tissue BAM files and the modified genome annotation. Genes with raw counts < 50 across all tissue samples were removed using the filterByExpr function in edgeR v4.0.16 ( 57 ), and technical replicates were condensed into biological replicates. Raw gene counts were normalised using the Trimmed Mean of the M-values (TMM) method in edgeR. Multidimensional scaling (MDS) was used to observe variation based on tissue type and experimental study (the study the sample originated from). Additionally, redundancy analysis and variation partitioning analysis were conducted using vegan 2.6–6.1 ( 58 ) to further investigate the influence of tissue type and study as variables within this dataset. To identify genes upregulated in the crural gland compared to all other tissue types, two methods of differential expression analysis were conducted using the voom function in limma v3.58.1 ( 59 ) and the exactTest function in edgeR. A fold change ≥ 5 and false discovery rate of 10 − 2 were selected as cutoffs to determine differentially expressed genes in both methods. Genes with > 30,000-fold upregulation in both limma and edgeR methods were translated to check if transcripts were predicted to encode proteins or alternatively were searched against the RFAM 15.0 database using nhmmer to check if transcripts were predicted to be non-coding ( 60 , 61 ). Tissue specificity analysis was conducted to identify genes specifically expressed within the crural gland. Raw gene counts were normalised using the Transcript per Million (TPM) function in edgeR, followed by log2 transformation, quantile normalisation, averaging samples across tissue types, and use of the Tau specificity algorithm using tispec v0.99 ( 62 ). For genes to be classified as high or absolute specificity to the crural gland, the recommended Tau value of ≥ 0.85 was used ( 63 ). For this calculation of tissue specificity, brain and cerebellum tissue samples were combined into a single tissue type. Genes that were both upregulated in the crural gland from differential expression analysis and crural gland-specific from tissue specificity analysis were selected for gene ontology (GO) analysis in clusterProfiler v4.10.1 and visualised using enrichplot v1.22.0 ( 64 ). GO was determined based on Entrez IDs and included biological processes, molecular functions, and cellular components. The Benjamini-Hochberg method was used to adjust p-values for multiple test correction, with the significance threshold of p-value and q-value of < 0.05. Identification of putative platypus venom toxins (dup: abstract ?) Putative platypus venom toxins were identified from the upregulated and crural gland-specific subset of the crural gland transcriptome using the DeTox pipeline ( 65 ) with minor modifications. The crural gland transcriptome subset was filtered for microorganism contaminants using BLAST (e-value threshold 1e − 5 ) (Additional File 2: Table S2 ). Open reading frames (ORFs) were detected using orfipy v0.0.4 ( 66 ) (sequences between 99-45000bp retained), and sequences with 99% similarity clustered using CD-HIT v4.8.1 ( 67 ). Structure-based toxin detection was conducted by determining secreted proteins through the identification of signal peptides using SignalP 5.0b ( 68 ) (d-value 0.7) and removing transmembrane proteins using Phobius v1.01 ( 69 ). Similarity-based toxin detection was conducted using BLAST against a custom platypus toxin database with an e-value threshold of 1e − 10 (Additional File 2: Table S2 ). Structure-based and similarity-based toxin results were pooled to determine putative toxins. Additional analyses were undertaken for putative toxins, including classification of protein family features using InterProScan v5.52-86.0 ( 70 ), prediction of protein localisation using WoLF PSort v0.2 ( 71 ), and detection of cysteine pattern and amino acid repeats using DeTox custom scripts ( 65 ). Putative toxins were also searched against the reviewed Swiss-Prot database, Tox-Prot venom database, and complete UniProt platypus protein database (reviewed and unreviewed platypus proteins) using BLAST (e-value threshold 1e − 10 ) (Additional File 2: Table S2 ). Resulting putative toxins were manually filtered to only retain toxins that were full length (with a start and stop codon), had a predicted signal peptide, and were the most confident ORF per transcript. With the aim to identify novel platypus venom components, any known platypus venom components investigated in prior studies ( 25 – 29 , 36 ) were not analysed further in this dataset. Physicochemical properties of putative toxins were calculated using ProtParam through the ExPasy server ( 72 ) and Peptide 2.0 peptide hydrophobicity/hydrophilicity analysis tool ( 73 ). Preliminary functional prediction was conducted using the CSM-peptide webserver ( 74 ). Protein structures were modelled using AlphaFold 3 ( 75 ) and visualized using ChimeraX v1.9 ( 76 ). Protein family/superfamily assignment was confirmed through identification of common motifs and features, and the Dali protein structure comparison server ( 77 ). For protein families that had multiple putative platypus toxins members identified, phylogenetics was used to investigate evolutionary relationships. For each protein family, sequences were collated for all platypus proteins (putative venom components and otherwise, found using InterPro ID and manual filtering), any known venomous mammalian toxins (sourced from UniProt, NCBI, and prior studies) and any Swiss-Prot mammalian protein sequences (Additional File 3). Multiple sequence alignments were generated using ClustalW in BioEdit ( 78 ). Phylogenetic trees were constructed using IQTree v2.2.2 ( 79 ) with ModelFinder Plus to select the best-fit model for the phylogeny ( 80 ) and 1000 ultrafast bootstrap replicates ( 81 ). The consensus tree was visualised using the ggtree package in R. Results Transcriptome generation RNA-Seq data collated from NCBI spanned 65 samples from seven studies ( 35 , 39 – 44 ), and was filtered to form the final RNA-Seq dataset of 45 samples from five studies ( 35 , 39 – 42 ) (Additional File 1). These tissue samples included in-season crural gland, brain and cerebellum, kidney, liver, ovary, testis, fibroblast, and heart tissues from 20 individuals. The platypus global transcriptome consisted of 64,871 transcripts from 38,520 genes, with an average transcript length of 2,310bp, and N50 of 3,959bp. The crural gland-only transcriptome consisted of 32,954 transcripts from 14,037 genes, with an average transcript length of 3,354bp, and N50 of 4,551bp. The global transcriptome and crural gland transcriptome contained 88.9% and 67.7% of complete mammalian BUSCOv5.8.0 genes respectively. Identification of key crural genes From the global transcriptome, 26,444 genes passed initial filtering to be used in subsequent differential expression (DE) and tissue specificity analysis. 46% of these genes did not have assigned gene names, either from lack of orthology, lack of published gene symbol, or novel transcripts identified in the global transcriptome. Samples clustered by tissue type in MDS analysis regardless of inter-study variability in sequencing or extraction method (Additional File 2: Figure S1 ). Redundancy analysis indicated that tissue type and study accounted for 74% of the variation in gene counts and were significant predictor variables (p = 0.001) (Additional File 2: Table S3 ). This is not unexpected, given differences in sequencing and extraction methods amongst the five studies ( 35 , 39 – 42 ). An ANOVA on the variance partitioning analysis indicated that tissue type alone accounted for 67% of the total variation in gene counts, while study only accounted for 3% (Additional File 2: Table S3 ). Together, these results indicate the validity of the dataset compiled from RNA-Seq data from five studies to investigate differences in gene expression amongst tissues. DE analysis using limma found 13.4% of genes to be differentially expressed, with 831 genes upregulated and 2,723 genes downregulated in the crural gland compared to all other tissue types (Fig. 1 A). DE analysis using edgeR found 6.5% of genes to be differentially expressed, with 572 genes upregulated and 1,135 genes downregulated in the crural gland compared to all other tissue types (Fig. 1 B). Owing to low sample size across tissue types, a conservative estimate of genes upregulated in the crural gland was used, by only including genes that were identified as upregulated in the crural gland by both limma and edgeR methods (n = 525) in downstream analysis (henceforth termed upregulated genes). 16 genes were shown to have > 1000-fold upregulation in the crural gland across both DE methods (Additional File 2: Table S4 ), four of which were upregulated > 30,000-fold. Tissue specificity analysis found 9,286 genes specific to one of the eight tissue types investigated (Additional File 2: Figure S2 ). 329 of these genes were determined to be crural gland-specific genes (tau ≥ 0.85), including 11 genes with absolute specificity to the crural gland (tau = 1) and no detected expression in any other tissue type included in this study. 177 genes that were both upregulated in DE analysis and crural gland-specific from tissue specificity analysis, were input for GO analysis and putative toxin identification. Only 25 of these genes had IDs with associated GO terms. Significant GO processes upregulated in the crural gland included biological processes and molecular functions associated with stimulus detection, extracellular matrix organization and catalytic activity (Additional File 2: Figure S3 ). Of the 177 genes of interest, 55 had their protein sequence assigned to an InterPro protein family, including all 25 genes used in GO analysis. Identification of putative platypus venom toxins The DeTox pipeline identified 37 putative toxins that were both upregulated in the crural gland compared to all other tissues, and crural gland-specific (Additional File 2: Table S5). Manual filtering resulted in the identification of 17 putative venom toxins. Four of these (23%) were previously found in platypus venom, including a corticotropin-releasing factor-binding protein ( 36 ), a Kunitz domain containing serine protease inhibitor ( 36 ), and two defensin-like peptides (DLP-A ( 82 ) and DLP-2/DLP-4 ( 29 )), (Additional File 4). The remaining 13 putative venom toxins (77%) were assigned to an InterPro protein family/superfamily (Table 1 ). The peptidase S1A and secretoglobin families each had three putative toxins assigned to them (Fig. 2 ). All 13 protein models displayed structural similarities to their assigned protein families (Fig. 3 ; Additional File 2: Figure S4 ). Despite InterPro assignment, 31% of the putative toxins, including all three putative secretoglobin toxins, had no hits (with e-value threshold 1e − 10 ) to any of the databases used in this study (Additional File 2: Figure S5). Mature protein sequences of the 13 putative platypus toxins ranged from 43–693 amino acids (Additional File 2: Table S6), all had potential anti-inflammatory activity (79–97%; Additional File 2: Table S7) and all but one were predicted to localise in the extracellular space. Table 1 13 novel putative platypus venom toxins. Toxin ID Associated Gene Signal Peptide Probability InterPro Family/Superfamily Protein Localisation DeTox Toxin Rating XR_486810.3_ORF.3 LOC103171488 0.999316 Beta defensin Extracellular SCD? XM_029046826.2_ORF.1 LOC100091528 0.977011 Calreticulin/calnexin Extracellular SD! XM_001513234.4_ORF.1 FGFBP1 0.990448 FGF binding 1 Extracellular SCD! XM_029081728.2_ORF.1 LPO 0.986151 Haem peroxidase, animal-type Endoplasmic reticulum SCD! XM_029049771.2_ORF.1 LOC103170591 0.997579 Kazal domain Extracellular SCD! XM_016227951.3_ORF.1 KERA 0.954623 Leucine-rich repeat domain Extracellular SCD! XM_003431054.3_ORF.1 LOC100681171 0.971443 Lipocalin Extracellular SD! XM_029064327.1_ORF.1 KLK7 0.984628 Peptidase S1A, chymotrypsin family Extracellular SCD! XM_029064328.1_ORF.5 LOC100090533 0.992461 Peptidase S1A, chymotrypsin family Extracellular SCD! XM_029064368.2_ORF.9 KLK1 0.800714 Peptidase S1A, chymotrypsin family Extracellular SCD! XM_016226360.3_ORF.1 LOC107547358 0.998521 Secretoglobin Extracellular SD? MSTRG8465.1_ORF.3 MSTRG.8465 0.995858 Secretoglobin Extracellular SD? MSTRG8471.1_ORF.3 MSTRG.8471 0.997852 Secretoglobin Extracellular SD? For DeTox Toxin Rating category: S = signal peptide without transmembrane domain; C = cysteine pattern with ≥ 4 cysteine residues; D = predicted InterPro domain; ! = hit in Swiss-Prot database but not toxin database; ? = no hits to Swiss-Prot database. For additional DeTox pipeline output, see Additional File 4. For the two protein families where multiple putative toxins were identified (peptidase S1A and secretoglobin families), phylogenetic relationships amongst mammalian members were investigated. Kallikreins (KLKs), a subgroup of peptidase S1A enzymes, contained three platypus putative toxins that did not form a platypus-specific clade but instead were basal to each of the distinct mammalian KLK orthologous groups (97–100% bootstrap confidence, Fig. 4 ). Similarly for the secretoglobin family, most secretoglobins cluster by orthologs across species. However, six of nine platypus secretoglobins, including all three putative toxic secretoglobins, form a species-specific cluster of uteroglobin-like proteins with 74% bootstrap support, which may suggest gene duplication within the platypus (Fig. 5 ). Despite similarity to uteroglobin (secretoglobin family 1A member 1), this platypus-specific group clusters independently to platypus uteroglobin and the uteroglobins of other mammalian taxa. Discussion Here, we used genomic and transcriptomic resources from the past 15 years to shed light on the function of the platypus crural system and identify putative toxins. Through the generation of the platypus crural gland transcriptome, we identified 177 genes that were upregulated and specific to the crural gland compared to seven other tissue types, including four genes with > 30,000-fold upregulation in the crural gland. We found 17 putative platypus venom toxins that were upregulated and crural gland-specific, 13 of which were previously unreported in platypus venom studies. These putative toxins span nine protein families, including families with known toxins in mammalian and non-mammalian venoms, such as KLKs and secretoglobins. Through improvements to genome quality and bioinformatic tools ( 83 , 84 ), this study demonstrated a 2.7-fold increase in the number of genes identified in the platypus crural gland transcriptome compared to the last study in 2012 ( 36 ). Over 85% of these upregulated and crural gland-specific genes did not have assigned gene names, which limited our capacity to impute their function. This highlights the limitation of downstream functional annotation workflows such as GO analysis when applied to unique and non-model species such as the platypus. However, protein family assignment provided classification and basic functional prediction for an additional 30 genes without assigned gene names. The most upregulated gene identified here (MSTRG.16525) had a > 400,000-fold increase in expression in the crural gland compared to other tissue types. MSTRG.16525 is likely a non-coding RNA rather than protein-encoding possibly contributing to transcriptional or translational regulation ( 85 ). Other highly upregulated genes (> 30,000-fold increase in expression in the crural gland) encoded either putative toxins identified for the first time in the crural gland (LOC100681171) or previously identified platypus venom components (LOC114813694 and SPAM1) ( 36 ). In addition, this study demonstrates the potential of pooling samples across studies to overcome limited sample availability, while accounting for variation in extraction and sequencing methods – a framework that can be applied to other non-model taxa in the future. As a result, we provide the first comparison of platypus gene expression between the crural gland and other tissue types, in addition to improved gene and protein identification. Venoms across taxa often display similarities based on the convergent recruitment of protein families into toxic components, despite differences in the composition and abundance of toxins within venom, and the advantages it confers. All 13 putative toxins identified in this study were classified into nine protein families. Seven are families with known venom components in other taxa, and four (peptidase S1A, secretoglobin, lipocalin, and Kazal domain proteins) are found in the venoms of other mammals ( 1 , 82 , 86 – 90 ). Interestingly the two key protein families in this study with multiple putative platypus toxins, peptidase S1A and secretoglobin families, also comprise major venom components in venomous Eulipotyphlans and lorises respectively (Fig. 4 ; Fig. 5 ) ( 88 , 91 ). Peptidase S1 forms a diverse group of enzymes that have been convergently recruited into the venoms of mammals, reptiles, cephalopods, insects and ticks ( 1 ), and were previously shown to be prevalent in the platypus crural gland ( 35 ). Here, we highlight three members of this protein family (KLK1, KLK6 and KLK7) as putative toxins with crural gland upregulation and specificity. Our improved genomic resources enabled identification of full sequences for KLK6 and KLK7, only partially characterised previously ( 35 ) (Additional File 4). Importantly, we also show the upregulation of KLK1 for the first time in the platypus crural gland. KLK1 is a venom component in multiple venomous Eulipotyphlans ( 7 ), vampire bats ( 87 ), and has similarity to snake venom serine proteinases (SVSPs) ( 92 ). While KLK1 gene expansions of both toxic and non-toxic paralogs have occurred independently in shrews and solenodons ( 86 , 93 ), no such expansion was found in the platypus. KLK presence has been previously noted in platypus venom ( 94 ), but the specific KLK protein within the venom has not been confirmed. As such, at least one of the putative platypus KLK toxins is present within crude venom with future proteomic analysis required for confirmation. KLKs have an important role in the kallikrein-kinin system, where they act on kininogens to produce bioactive kinins involved in a variety of pathophysiological processes, including inflammation and pain in humans and rodents ( 95 – 97 ). The biological role of platypus KLKs are unknown. In Northern short-tailed shrew ( Blarina brevicauda ) venom, a KLK1 paralog ( Blarina toxin - BLTX) is a major venom component and may contribute to low blood pressure and motor dysfunction of prey ( 91 ). Putative platypus venom KLKs may influence blood pressure, inflammation or the coagulation cascade ( 98 ) (Additional File 2: Table S7), or cleave other venom components. KLKs are also known to associate with other putative platypus toxins identified in this study. Kazal-type serine protease inhibitors are prevalent across venoms ( 87 , 99 – 102 ), and in other mammalian venoms cause blood coagulation, hypokinesia ( 103 ), and serve a protective function within the venom gland itself ( 86 ). The double-headed Kazal-type serine protease inhibitor in this study (LOC103170591) contains two Kazal domains ( 104 ), with the first domain likely responsible for inhibiting trypsin-like proteases such as KLKs ( 105 , 106 ), and the second domain predicted to inhibit chymotrypsin, subtilisin and/or elastase ( 107 ). Given this, the platypus two-Kazal domain protein has the potential to be both protective and toxic, however, further investigation is required for confirmation. Interestingly, a platypus fibroblast growth factor-binding protein (FGFBP1) was identified as a putative toxin in this study, yet this family does not appear in venoms of other taxa. In cancer cell lines, FGFBP1 acts as a substrate for both KLK6 and KLK7 ( 108 , 109 ), both of which were also putative platypus toxins. This indicates the potential for synergistic activity between the KLK serine proteases and FGFBP1 within platypus venom that may enhance activity and impact the inflammation and wound healing pathway in the envenomated individual ( 110 , 111 ). Secretoglobins are a well-known component of mammalian venoms and have been identified in the venoms all other venomous mammalian orders ( 86 , 87 , 112 ). Our study marks the first time secretoglobins have been identified as putative venom components in the platypus. While secretoglobins have been found in all other venomous mammalian Orders, only one functional toxic secretoglobin protein has been found in Primates and Eulipotyphlans ( 86 – 88 ) (Fig. 5 ). The platypus differs as we found three putative toxic uteroglobin-like secretoglobins, which may have evolved through gene duplication and subsequent neofunctionalisation ( 113 ). The inclusion of three putative toxins in this protein family suggests secretoglobins may be an important component of the platypus crural system that requires further investigation. The function of all toxic secretoglobins in vertebrates is unknown ( 86 – 88 ), including the role of the brachial gland exudate secretion protein (BGEsp) that is a major component in loris venom ( 114 , 115 ). Secretoglobins are dimeric proteins secreted within epithelial cells, glandular tissues and secretions such as sputum, with important roles in immunoregulation, anti-inflammation, tissue repair and tumourigenesis ( 116 , 117 ). Uteroglobin, a member of the secretoglobin family most closely related to the three platypus uteroglobin-like toxins, is a homodimer that can regulate inflammation through inhibition of phospholipase A2 (a pro-inflammatory enzyme commonly recruited into venoms) ( 1 , 118 ). Uteroglobin is often regulated by hormones ( 119 ), which may be pertinent to the platypus as venom production is seasonal. While putative platypus secretoglobins have potential immunoregulatory and anti-inflammatory roles ( 116 ) (Additional File 2: Table S7), the interpretation of putative toxic platypus secretoglobins is limited until additional research on the function of the secretoglobin protein family is available. Other putative toxins found in the platypus include those that belong to the lipocalin, calreticulin and leucine-rich repeat domain families, which are also commonly recruited into venoms. In platypus, these proteins may be directly toxic or involved in biological processes of the crural gland. Lipocalins are common venom components across taxa ( 1 , 120 ) and are found in vampire bat venom ( 87 ). However, the putative platypus lipocalin toxin (LOC100681171) may not be toxic, as it is also the second-most abundant protein in platypus epididymal fluid ( 121 ), in addition to having high expression in the crural gland (Fig. 1 ). As such, this lipocalin may be involved in immunomodulation ( 122 ), ligand binding as in triatomine (kissing bug) venoms ( 120 ), seasonal upregulation, or fluid maturation in both reproductive and crural systems ( 123 – 125 ). Both the calreticulin (LOC100091528) and leucine-rich repeat (KERA - keratocan) proteins in this study belong to families with known toxins that modulate the immune response ( 126 , 127 ). Outside of a toxic role, calreticulins are important for protein folding and modification ( 128 ), and highly expressed in the non-venomous echidna crural gland ( 129 ). Similarly, keratocan regulates collagen matrix assembly, which may contribute to forming the connective tissue stroma of the platypus crural system ( 13 ). Antimicrobial peptides (AMPs) are another common component of venoms as they protect against infection, and in some cases, contribute to venom toxicity ( 130 , 131 ). The defensin family of AMPs includes defensin-like peptides (DLPs) that are a well-known toxic component of platypus venom ( 27 , 28 ). We identified a novel putative β-defensin in the crural gland (LOC103171488) that contained the characteristic cysteine residue spacing of traditional antimicrobial β-defensins ( 132 ), rather than that of the toxic DLPs in platypus venom ( 82 ). We also identified a haem peroxidase (LPO – lactoperoxidase) for the first time in a venom system ( 133 ). Due to high upregulation and specificity to the crural gland, the platypus β-defensin and haem peroxidase may be involved in local immune defence of the crural gland. The methods used in this study were designed to capture all possible venom toxins. However, the stringent thresholds used in DE and tissue specificity, which are essential for robust analysis, may have excluded potential platypus venom toxins. For example, OvDLP-C, NPPC and NGF, three genes encoding known platypus venom components ( 134 ), did not meet the tissue specificity cutoff and hence were not included in the set of crural gland-specific genes. However, as venom components are likely to have a limited tissue distribution and upregulation in the venom system, thresholds instigated in this study allow for greater confidence in finding key genes and proteins involved in crural gland function. Similarly, the use of similarity-based and structure-based toxin discovery in the DeTox pipeline may include proteins that fit the toxin criteria but are not functionally toxic within the platypus crural system. Identification of key proteins in the crural gland are essential for understanding the platypus crural system holistically, and non-toxic components may assist toxic proteins or have protective roles, particularly for a venom system targeted against conspecifics. While putative toxin identification provides the first step in uncovering the nature of platypus venom and the platypus crural system more broadly, future proteomic investigation is required to confirm protein expression of key transcripts in platypus venom or crural system. To enable this, crude venom samples are required, which is challenging due to the seasonal nature of platypus venom production and limited past success in sample collection. True functions of these platypus crural system proteins may, or may not, be comparable to other venomous species, or those typical of the protein families identified due to the evolutionary distinctness of the platypus and the uniqueness of their crural system. Functional testing is required to attribute functions and associated envenomation symptoms to various platypus venom components. The crural gland transcriptome generated here will provide a platypus-specific database to aid in future research, allowing for tracing of key crural system genes, transcripts, and proteins. Conclusions New genomic and collated transcriptomic resources have enabled the identification of a suite of genes, transcripts, and proteins of importance to the platypus crural system. Selecting key genes through upregulation and specificity to the crural gland has allowed us to create a set of proteins that we believe are key for the functioning of this system. We have demonstrated the convergent recruitment of toxins across venomous mammalian species and improved our understanding of the venom and crural system of Australia’s only venomous mammal species. Determining important components in a unique system, such as the platypus crural system, provides crucial information allowing for future investigations into platypus venom components and their functions. The genes, transcripts and putative venom proteins identified in this study have the potential for a variety of roles within platypus envenomation, and have demonstrated their importance to the platypus, within their venom and beyond. Abbreviations AMP antimicrobial peptide BAM binary alignment map BLAST Basic Local Alignment Search Tool BLTX Blarina toxin bp base pair BUSCO Benchmarking Single Copy Gene Orthologs cDNA complementary DNA DE differential expression DLP defensin-like peptide FPKM fragments per kilobase million GO Gene Ontology GTF gene transfer format KLK kallikrein MDS multidimensional scaling NCBI National Center for Biotechnology Information ORF open reading frame OvCNP Ornithorhynchus C-type natriuretic peptide OvDLP/OavDLP-C Ornithorhynchus defensin-like peptide OvNGF Ornithorhynchus nerve growth factor RNA-Seq RNA sequencing SAM sequence alignment map SVSPs snake venom serine proteinases TMM Trimmed Mean of the M-values TPM Transcript per Million. Declarations Ethics approval and consent to participate Not applicable, as previously sequenced datasets were used. Consent for publication Not applicable. Funding This work was funded by the Australian Research Council (ARC) Centre of Excellence for Innovations in Peptide and Protein Science (CE200100012). Author Contribution AG and EP designed the study with guidance from CJH and KB. AG performed all data analysis and wrote the manuscript, with assistance from EP. CJH and KB sourced research funding and project management. All authors read and approved the final manuscript. Acknowledgement Molecular graphics performed with UCSF ChimeraX, developed by the University of California, San Francisco, and partners. Data Availability Platypus global transcriptome and crural gland transcriptome are available at [https://awgg-lab.github.io/australasiangenomes/genomes.html] . RNA-Seq data used at all stages of this study were previously published datasets, accessible through the NCBI BioProject database under accession numbers PRJNA12885, PRJNA143627, PRJNA152927, PRJNA186646, PRJNA247824, PRJEB28810, and PRJNA381064. 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Uteroglobin: a steroid-inducible immunomodulatory protein that founded the secretoglobin superfamily. Endocr Rev. 2007;28(7):707–25. Walker AA, Weirauch C, Fry BG, King GF. Venoms of Heteropteran insects: a treasure trove of diverse pharmacological toolkits. Toxins. 2016;8(2):43. Dacheux J-L, Dacheux F, Labas V, Ecroyd H, Nixon B, Jones RC. New proteins identified in epididymal fluid from the platypus ( Ornithorhynchus anatinus ). Reprod Fertility Dev. 2009;21(8):1002–7. Flower DR. The lipocalin protein family: structure and function. Biochem J. 1996;318(1):1–14. Chandrasekaran P, Weiskirchen S, Weiskirchen R. Structure, functions, and implications of selected lipocalins in human disease. Int J Mol Sci. 2024;25(8):4290. Fouchecourt S, Chaurand P, Dague BB, Lareyre J-J, Matusik RJ, Caprioli RM, et al. Epididymal lipocalin-type prostaglandin D2 synthase: identification using mass spectrometry, messenger RNA localization, and immunodetection in mouse, rat, hamster, and monkey. Biol Reprod. 2002;66(2):524–33. Morel L, Dufaure JP, Depeiges A. LESP, an androgen-regulated lizard epididymal secretory protein family identified as a new member of the lipocalin superfamily. J Biol Chem. 1993;268(14):10274–81. Siebert AL, Wheeler D, Werren JH. A new approach for investigating venom function applied to venom calreticulin in a parasitoid wasp. Toxicon. 2015;107(Pt B):304–16. Kuhn-Nentwig L, Langenegger N, Heller M, Koua D, Nentwig W. The dual prey-inactivation strategy of spiders—in-depth venomic analysis of Cupiennius salei . Toxins. 2019;11(3):167. Isomoto A, Shoguchi E, Hisata K, Inoue J, Sun Y, Inaba K, et al. Active expression of genes for protein modification enzymes in Habu venom glands. Toxins. 2022;14(5):300. Wong ESW, Nicol S, Warren WC, Belov K. Echidna venom gland transcriptome provides insights into the evolution of monotreme venom. PLoS ONE. 2013;8(11):e79092. Samat R, Sen S, Jash M, Ghosh S, Garg S, Sarkar J et al. Venom: a promising avenue for antimicrobial therapeutics. Acs Infect Dis. 2024. Perumal Samy R, Stiles BG, Franco OL, Sethi G, Lim LHK. Animal venoms as antimicrobial agents. Biochem Pharmacol. 2017;134:127–38. Pazgier M, Hoover DM, Yang D, Lu W, Lubkowski J. Human β-defensins. Cell Mol Life Sci. 2006;63(11):1294–313. Magacz M, Kędziora K, Sapa J, Krzyściak W. The significance of lactoperoxidase system in oral health: application and efficacy in oral hygiene products. Int J Mol Sci. 2019;20(6):1443. Whittington C, Belov K. Platypus venom: a review. Australian Mammalogy. 2007;29(1):57–62. Additional Declarations No competing interests reported. Supplementary Files AdditionalFile1.xlsx Additional File 1: · File format: *.xls · Title: NCBI Data Collation, Trimming, and Alignment Statistics · Description: RNA-Seq data accession run IDs, with information on tissue type, Trimmomatic statistics and HISAT2 alignment statistics. AdditionalFile2.pdf Additional File 2: · File format: *.pdf · Title: Insights into Platypus Crural Gland Transcriptomics – Venom and Beyond: Supplementary Material · Description: All supplementary tables and figures that are referenced in the main manuscript. Includes seven supplementary tables, and five supplementary figures. Tables are briefly described as follows: Table S1: adapters for trimming; Table S2: database construction search queries; Table S3: redundancy analysis and variance portioning analysis information; Table S4: details on highest upregulated genes in the crural gland; Table S5: number of putative toxins found in transcriptomic subsets; Table S6: physicochemical properties of putative toxins; Table S7: functional predictions for putative toxins. Figures are briefly described as follows: Figure S1: multi-dimensional scaling plot of RNA samples; Figure S2: pie chart of tissue specific genes across tissue types; Figure S3: significant gene ontology terms for upregulated and crural gland specific genes; Figure S4: additional predicted protein structures of putative toxins; Figure S5: Venn diagram of BLAST hits against platypus toxin, Tox-Prot, Platypus UniProt, and Swiss-Prot databases. AdditionalFile3.xlsx Additional File 3: · File format: *.xls · Title: Tree Sequence Accessions · Description: UniProt protein sequence accessions, matching label in phylogenetic tree figures, and associated information. Two sheets in an Excel file, one for tissue KLK tree, and one for secretoglobin tree. AdditionalFile4.xlsx Additional File 4: · File format: *.xls · Title: Extended DeTox results · Description: Extended information on the results of the DeTox pipeline for putative toxin detection. This includes extra information on previously identified transcripts and venom components, signal peptide prediction, protein localisation, InterPro protein family assignment, associated GO terms, BLAST hits to platypus toxin, Tox-Prot, Platypus UniProt, and Swiss-Prot databases, repeat information, and cysteine pattern. Cite Share Download PDF Status: Published Journal Publication published 12 Nov, 2025 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 14 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviews received at journal 22 Sep, 2025 Reviewers agreed at journal 16 Sep, 2025 Reviewers agreed at journal 27 Aug, 2025 Reviewers invited by journal 25 Aug, 2025 Editor invited by journal 19 Aug, 2025 Editor assigned by journal 18 Aug, 2025 Submission checks completed at journal 18 Aug, 2025 First submitted to journal 17 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7394805\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":506318816,\"identity\":\"dcce9b3f-2207-4de7-b03a-57e70a76d3f9\",\"order_by\":0,\"name\":\"Adele Gonsalvez\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The University of Sydney\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Adele\",\"middleName\":\"\",\"lastName\":\"Gonsalvez\",\"suffix\":\"\"},{\"id\":506318817,\"identity\":\"a860de11-ddeb-4d2b-bd0d-5eeb2209b767\",\"order_by\":1,\"name\":\"Emma Peel\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The University of Sydney\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Emma\",\"middleName\":\"\",\"lastName\":\"Peel\",\"suffix\":\"\"},{\"id\":506318818,\"identity\":\"e4b44d96-c087-414e-8577-8c183e18cb25\",\"order_by\":2,\"name\":\"Carolyn J. Hogg\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"\",\"institution\":\"The University of Sydney\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Carolyn\",\"middleName\":\"J.\",\"lastName\":\"Hogg\",\"suffix\":\"\"},{\"id\":506318819,\"identity\":\"5305483e-22db-4b61-8c2e-bab9251e39e0\",\"order_by\":3,\"name\":\"Katherine Belov\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The University of Sydney\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Katherine\",\"middleName\":\"\",\"lastName\":\"Belov\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-08-18 01:23:09\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-7394805/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-7394805/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12864-025-12299-x\",\"type\":\"published\",\"date\":\"2025-11-12T15:58:45+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":90419566,\"identity\":\"db1e803c-6af8-4b77-9056-fa931fc37dcc\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 13:50:26\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":783597,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eDifferentially expressed genes in the crural gland.\\u003c/p\\u003e\\n\\u003cp\\u003eDifferentially expressed genes between crural gland and all other tissue types using A) limma and B) edgeR methods. Fold change cutoff is 5, false discovery rate cutoff is 10\\u003csup\\u003e-2\\u003c/sup\\u003e.\\u0026nbsp;Labelled genes have fold change \\u0026gt;30,000.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/43333d66b64b5c22a872ec83.png\"},{\"id\":90419574,\"identity\":\"a54d7bea-2ff8-49f2-8531-e4ca2891f1f5\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 13:50:26\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":550988,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eProtein family assignment for DeTox identified platypus putative toxins.\\u003c/p\\u003e\\n\\u003cp\\u003eCrural gland log2 normalised gene counts for DeTox identified putative toxins grouped by their assigned protein family/superfamily. Asterisk indicates a protein family containing previously identified platypus toxins.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/fa144f7ce1db7dce8808b6fa.png\"},{\"id\":90422613,\"identity\":\"92769da9-6eba-4d80-a4fc-c4a2f89b83cc\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 14:14:27\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":8627695,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePredicted protein structures of putative toxic peptidase S1A chymotrypsins and secretoglobins.\\u003c/p\\u003e\\n\\u003cp\\u003ePredicted protein structures of putative toxic peptidase S1A chymotrypsins(panels A - KLK1, B – LOC100090533 (aka KLK6), C – KLK7) and secretoglobins (panels D - LOC107547358, E - MSTRG.8465, F -MSTRG.8471) modelled by AlphaFold 3 and visualised by ChimeraX. Secondary structure shown by colour, with alpha-helices in red and beta-strands in blue. Secretoglobins are predicted to form homodimers but are displayed as the monomer sequences identified. Confidence in predicted structure is indicated by AlphaFold predicted TM-score (pTM), with a pTM \\u0026gt;0.5 indicating the overall protein fold is similar to the true structure, and pTM \\u0026gt;0.8 indicating a confident prediction. Protein structures for remaining 7 novel putative platypus venom toxins in Additional File 2: Figure S4.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/6eb8b25e68a66a4050ab63ff.png\"},{\"id\":90419573,\"identity\":\"5c994150-6344-4103-b4c5-46c3803c3aa9\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 13:50:26\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":2139671,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eConsensus phylogenetic tree of tissue kallikrein (KLK) protein sequences amongst mammalian taxa.\\u003c/p\\u003e\\n\\u003cp\\u003eBranch numbers are coloured by bootstrap support. Taxa labels for toxins are marked with an asterisk and coloured by toxin status (pink = putative toxin, blue = confirmed toxin, black with no asterisk = non-toxin). Venomous mammalian taxa included are the platypus (ORNAN), common vampire bat (DESRO), European shrew (SORAR), Hispaniolan solenodon (SOLPA), short-tailed shrew (BLABR), and slow loris (NYCCO). Non-venomous mammalian taxa included are the cotton-top tamarin (SAGOE), crab-eating macaque (MACFA), domestic guinea pig (CAVPO), hamadryas baboon (PAPHA), horse (HORSE), house mouse (MOUSE), human (HUMAN), Norway rat (RAT), pig (PIG), and rhesus monkey (MACMU). The circle surrounding the tree is coloured by tissue KLK family member. Tree is rooted by human trypsin. Best-fit model for phylogeny (chosen by ModelFinder Plus): JTT+I+R5 chosen according to Bayesian Information Criterion. Sequence accessions and additional information in Additional File 3.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/1262ab7cd0baeaad32809dd2.png\"},{\"id\":90419577,\"identity\":\"387f7c37-8c89-4075-afcf-47a67d7c73b3\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 13:50:26\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1707296,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eConsensus phylogenetic tree of secretoglobin protein sequences amongst mammalian taxa.\\u003c/p\\u003e\\n\\u003cp\\u003eBranch numbers are coloured by bootstrap support. Taxa labels for toxins are marked with an asterisk and coloured by toxin status (pink = putative toxin, blue = confirmed toxin, black with no asterisk = non-toxin). Venomous mammalian taxa included are the platypus (ORNAN), common vampire bat (DESRO), European shrew (SORAR), Javan slow loris (NYCJA), pygmy slow loris (NYCPY), and slow loris (NYCCO). Non-venomous mammalian taxa included are the brown hare (LEPCA), domestic cat (FELCA), domestic cattle (BOVIN), golden hamster (MESAU), horse (HORSE), house mouse (MOUSE), human (HUMAN), Japanese macaque (MACFU), Mexican volcano mouse (NEOAS), Norway rat (RAT), and rabbit (RABIT). The circle surrounding the tree is coloured by secretoglobin family member. Tree is rooted by human hemoglobin. Best-fit model for phylogeny (chosen by ModelFinder Plus): JTTDCMut+G4 chosen according to Bayesian Information Criterion. Sequence accessions and additional information in Additional File 3.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/8d8a89cdc7dc5c162b35389f.png\"},{\"id\":96105175,\"identity\":\"652f6e79-55ef-4c38-aa6c-c65acfb52b4d\",\"added_by\":\"auto\",\"created_at\":\"2025-11-17 16:09:37\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":17455733,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/f76720e4-82fe-4590-a1b4-3f771ff2cae8.pdf\"},{\"id\":90419563,\"identity\":\"62d6c55e-35a6-4931-9c75-97c1d93de1c4\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 13:50:26\",\"extension\":\"xlsx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":25082,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional File 1\\u003c/strong\\u003e:\\u003c/p\\u003e\\n\\u003cp\\u003e· File format: *.xls\\u003c/p\\u003e\\n\\u003cp\\u003e· Title: NCBI Data Collation, Trimming, and Alignment Statistics\\u003c/p\\u003e\\n\\u003cp\\u003e· Description: RNA-Seq data accession run IDs, with information on tissue type, Trimmomatic statistics and HISAT2 alignment statistics.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile1.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/52bd3f8d327faef33d30c8dd.xlsx\"},{\"id\":90419570,\"identity\":\"0cd41078-e553-4e48-afc4-46f2f32c7e78\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 13:50:26\",\"extension\":\"pdf\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":921294,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional File 2\\u003c/strong\\u003e:\\u003c/p\\u003e\\n\\u003cp\\u003e· File format: *.pdf\\u003c/p\\u003e\\n\\u003cp\\u003e· Title: Insights into Platypus Crural Gland Transcriptomics – Venom and Beyond: Supplementary Material\\u003c/p\\u003e\\n\\u003cp\\u003e· Description: All supplementary tables and figures that are referenced in the main manuscript. Includes seven supplementary tables, and five supplementary figures. Tables are briefly described as follows: Table S1: adapters for trimming; Table S2: database construction search queries; Table S3: redundancy analysis and variance portioning analysis information; Table S4: details on highest upregulated genes in the crural gland; Table S5: number of putative toxins found in transcriptomic subsets; Table S6: physicochemical properties of putative toxins; Table S7: functional predictions for putative toxins. Figures are briefly described as follows: Figure S1: multi-dimensional scaling plot of RNA samples; Figure S2: pie chart of tissue specific genes across tissue types; Figure S3: significant gene ontology terms for upregulated and crural gland specific genes; Figure S4: additional predicted protein structures of putative toxins; Figure S5: Venn diagram of BLAST hits against platypus toxin, Tox-Prot, Platypus UniProt, and Swiss-Prot databases.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile2.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/6e533d022c1df4781faba2b6.pdf\"},{\"id\":90419571,\"identity\":\"4660556a-47b4-46c6-83b4-f921fbbfb2e5\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 13:50:26\",\"extension\":\"xlsx\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":31854,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional File 3\\u003c/strong\\u003e:\\u003c/p\\u003e\\n\\u003cp\\u003e· File format: *.xls\\u003c/p\\u003e\\n\\u003cp\\u003e· Title: Tree Sequence Accessions\\u003c/p\\u003e\\n\\u003cp\\u003e· Description: UniProt protein sequence accessions, matching label in phylogenetic tree figures, and associated information. Two sheets in an Excel file, one for tissue KLK tree, and one for secretoglobin tree.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile3.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/a6f1cda590e67d6b80715d74.xlsx\"},{\"id\":90421689,\"identity\":\"24ccba4b-643a-4357-b7dc-b93a8f1924bc\",\"added_by\":\"auto\",\"created_at\":\"2025-09-02 14:06:27\",\"extension\":\"xlsx\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":23505,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional File 4\\u003c/strong\\u003e:\\u003c/p\\u003e\\n\\u003cp\\u003e· File format: *.xls\\u003c/p\\u003e\\n\\u003cp\\u003e· Title: Extended DeTox results\\u003c/p\\u003e\\n\\u003cp\\u003e· Description: Extended information on the results of the DeTox pipeline for putative toxin detection. This includes extra information on previously identified transcripts and venom components, signal peptide prediction, protein localisation, InterPro protein family assignment, associated GO terms, BLAST hits to platypus toxin, Tox-Prot, Platypus UniProt, and Swiss-Prot databases, repeat information, and cysteine pattern.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile4.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7394805/v1/5615b3cf581d9abe4705bf68.xlsx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Insights into Platypus Crural Gland Transcriptomics – Venom and Beyond\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eVenoms are complex mixtures of bioactive compounds, containing proteins, salts, and organic molecules, that disrupt the normal physiological or biochemical processes of the targeted individual (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e). Venom has independently evolved over a hundred times in both invertebrates and vertebrates (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e), resulting in hundreds of thousands of venomous species (\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e). As such, venoms display high levels of molecular and compositional diversity, making them attractive sources for the discovery of novel compounds of biological, immunological and pharmacological importance (\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e). With majority of venom research centered around prolific venomous taxa, such as snakes and arthropods, investigations into the venom systems and venom compositions of mammals only began in the last few decades (\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e). These largely uncharacterised venoms potentially harbour unique proteins of importance.\\u003c/p\\u003e\\u003cp\\u003eThe platypus (\\u003cem\\u003eOrnithorhynchus anatinus\\u003c/em\\u003e) is a unique semi-aquatic, semi-fossorial monotreme endemic to eastern Australia and Tasmania (\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e). It is one of only fifteen experimentally confirmed venomous mammals (\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e), and the only venomous mammal within the Order Monotremata. As a monotreme, the platypus is the most evolutionarily distinct lineage of venomous mammals, with all other venomous species as Eutherian mammals that belong to the Orders Eulipotyphla (shrews and solenodons), Chiroptera (vampire bats) or Primates (slow lorises) (\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e). The platypus venom system is termed the crural system and consists of a crural gland connected via the crural duct to a hollow, keratinised spur located on their hindlimbs through which venom is delivered (\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e). While all platypuses are born with the crural system, it is sexually dimorphic, with the vestigial spur sheath regressing in females by age one and venom production developing in males by age two (\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e). The platypus crural system is also seasonal, with an increase in crural gland size and venom production during the spring breeding season in conjunction with androgen production and increased testicular size (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e). This is directly linked to the role of platypus venom in intraspecific competition, whereby males use their venom to immobilise male conspecifics to gain a mating advantage during the breeding season (\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e). In humans, platypus envenomation is non-fatal, yet causes intense pain, hyperesthesia, allodynia, oedema and functional impairment (\\u003cspan additionalcitationids=\\\"CR17\\\" citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e). Treatment has previously included a nerve blocker to help reduce pain (\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e), with mixed results on the effectiveness of analgesics (\\u003cspan additionalcitationids=\\\"CR17\\\" citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e). In vitro, platypus venom causes smooth muscle relaxation and haemolysis (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e), and acts on sensory neurons (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eInitial chemical investigations into platypus venom composition identified at least nineteen fractions, containing a range of components such as defensin-like peptides (DLPs), a nerve growth factor (OvNGF), C-type natriuretic peptide (OvCNP), isomerase, hyaluronidase and proteases (\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e), all of which have similar counterparts in other venoms (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR23\\\" citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e). In the platypus, DLPs, OvNGF and OvCNP have been studied in-depth, with their gene and protein sequences identified and putative functions elucidated (\\u003cspan additionalcitationids=\\\"CR26 CR27 CR28\\\" citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e). DLPs and OvNGF are possibly synergistic and predicted to be associated with the intense pain and hyperalgesia caused by platypus envenomation (\\u003cspan additionalcitationids=\\\"CR30\\\" citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e). OvCNP has been shown to cause cation channel formation (\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e), oedema, and mast cell histamine release in rats (\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e), in addition to likely contributing to hypotension (\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e). These components likely represent only a small fraction of total bioactive molecules within platypus venom, the majority of which have not been studied.\\u003c/p\\u003e\\u003cp\\u003eFollowing the release of the first platypus genome in 2008 (\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e), only two genetic-based investigations of venom have been conducted (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e). In-season crural gland cDNA libraries found 88 putative venom genes with homology to established toxin families (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e). A subsequent investigation based on crural gland RNA sequencing (RNA-Seq) identified 10 venom proteins, five of which belonged to protein families previously unreported in venoms of other taxa (\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e). As such, our current understanding of platypus venom composition and features of the crural system is limited. This is due to difficulties in sampling both venom and crural gland tissue from this enigmatic species. Also, venom discovery pipelines are often tailored for specific taxonomic groups and require substantial existing toxin databases for similarity-based toxin identification, increasing the complexity for discovering toxins in the platypus. New technological developments and resources, however, now provide the opportunity to collate larger datasets and search for previously unidentified genes and proteins key to platypus venom to improve our understanding of the platypus crural system more broadly. The release of a high-quality chromosome-length platypus genome in 2021, with 90% of gaps filled, greatly improved contig and scaffold contiguity, providing substantial improvements in gene annotation (\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e). This genome has enabled an improved platypus crural gland transcriptome assembly, and subsequent identification of proteins key to the platypus crural system.\\u003c/p\\u003e\\u003cp\\u003eIn this study, we utilise this improved platypus genome, as well as a suite of RNA-sequencing data collated over the past 15 years, to revisit platypus venom composition for the first time since 2012. Our aim was to identify genes, transcripts, and proteins of importance to the platypus crural system, increasing our understanding of platypus venom and the crural system.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eTranscriptome generation\\u003c/h2\\u003e\\u003cp\\u003eRaw platypus RNA-Seq data publicly available from the National Center for Biotechnology Information (NCBI) database (\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e) was collated for analysis (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR40 CR41 CR42 CR43\\\" citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e) (Additional File 1). Only Illumina sequencing was included in this study, due to discrepancies in processing 454 data with bioinformatic tools constructed for Illumina sequencing data. RNA-Seq reads were quality checked pre- and post-trimming using FastQC v0.11.8 (\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e) and trimmed using Trimmomatic v0.39 (\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e). Trimmomatic flags were used to remove adapter sequences (Additional File 2: Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e), 5\\u0026rsquo; and 3\\u0026rsquo; ends of reads, reads under 25 base pairs (bp), and reads with a quality score under 5 in a sliding window of 4bp. Trimmed reads were aligned to the platypus reference genome mOrnAna1.pri.v4 (NCBI RefSeq assembly GCF_004115215.2) (\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e) using HISAT2 v2.1.0 (\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e). Samples with an overall alignment rate\\u0026thinsp;\\u0026lt;\\u0026thinsp;75% were removed from the dataset. Aligned SAM files were converted to BAM files and indexed using SAMtools v1.9 (\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e), and a GTF file for each tissue sample was generated using StringTie v2.1.6 (\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eThe genome annotation file (NCBI \\u003cem\\u003eOrnithorhynchus anatinus\\u003c/em\\u003e Annotation Release 105) (\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e) was used as the basis for gene identification. Genes previously identified in platypus crural gland or venom studies (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e) were manually annotated within the mOrnAna1.pri.v4 genome assembly using BLAST\\u0026thinsp;+\\u0026thinsp;v2.7.1 (\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e), and added to the genome annotation file, henceforth referred to as the modified genome annotation file. Duplicated annotations between manually and NCBI annotated genes were resolved by using the NCBI gene when its coordinates encapsulated one or more other genes, or otherwise favouring manually annotated genes as manual annotations are known to produce higher accuracy for some gene families (\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eTo generate a global transcriptome, GTF files were merged using StringTie, guided by the modified genome annotation file (containing both NCBI and manually annotated genes). Tissue types included in the global transcriptome were in-season crural gland, brain and cerebellum, fibroblast, heart, kidney, liver, ovary, and testis. Transcripts were only included if their read length was \\u0026ge;\\u0026thinsp;30 bp and fragments per kilobase million (FPKM) transcript count was \\u0026ge;\\u0026thinsp;0.1. CPC2 v1.0 (\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e) was used to remove single exon non-coding transcripts that did not match entries within in the modified genome annotation file. Additional transcripts identified by StringTie were removed from the global transcriptome if they matched or overlapped with an annotation from the modified genome annotation file (determined using bedtools intersect v2.29.2 (\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e)). The final global transcriptome contained transcripts encoding genes that matched the NCBI and manual annotations, as well as these additional StringTie. To generate a crural gland-only transcriptome, the global transcriptome was filtered to remove transcripts corresponding to genes that were not expressed in any of the eight crural gland samples included in our study. For each transcriptome, calculations were done for functional completeness against the mammalia_odb10 database using BUSCO v5.8.0 (\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e) on Galaxy Australia as well as average transcript length and N50.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eIdentification of key crural genes\\u003c/h3\\u003e\\n\\u003cp\\u003eRaw gene counts for downstream analyses in R v4.3.2 (\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e) were generated using featureCounts in Subread v1.5.1 (\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e) using aligned tissue BAM files and the modified genome annotation. Genes with raw counts\\u0026thinsp;\\u0026lt;\\u0026thinsp;50 across all tissue samples were removed using the filterByExpr function in edgeR v4.0.16 (\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e), and technical replicates were condensed into biological replicates. Raw gene counts were normalised using the Trimmed Mean of the M-values (TMM) method in edgeR. Multidimensional scaling (MDS) was used to observe variation based on tissue type and experimental study (the study the sample originated from). Additionally, redundancy analysis and variation partitioning analysis were conducted using vegan 2.6\\u0026ndash;6.1 (\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e) to further investigate the influence of tissue type and study as variables within this dataset.\\u003c/p\\u003e\\u003cp\\u003eTo identify genes upregulated in the crural gland compared to all other tissue types, two methods of differential expression analysis were conducted using the voom function in limma v3.58.1 (\\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e) and the exactTest function in edgeR. A fold change\\u0026thinsp;\\u0026ge;\\u0026thinsp;5 and false discovery rate of 10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e were selected as cutoffs to determine differentially expressed genes in both methods. Genes with \\u0026gt;\\u0026thinsp;30,000-fold upregulation in both limma and edgeR methods were translated to check if transcripts were predicted to encode proteins or alternatively were searched against the RFAM 15.0 database using nhmmer to check if transcripts were predicted to be non-coding (\\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eTissue specificity analysis was conducted to identify genes specifically expressed within the crural gland. Raw gene counts were normalised using the Transcript per Million (TPM) function in edgeR, followed by log2 transformation, quantile normalisation, averaging samples across tissue types, and use of the Tau specificity algorithm using tispec v0.99 (\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e). For genes to be classified as high or absolute specificity to the crural gland, the recommended Tau value of \\u0026ge;\\u0026thinsp;0.85 was used (\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e). For this calculation of tissue specificity, brain and cerebellum tissue samples were combined into a single tissue type.\\u003c/p\\u003e\\u003cp\\u003eGenes that were both upregulated in the crural gland from differential expression analysis and crural gland-specific from tissue specificity analysis were selected for gene ontology (GO) analysis in clusterProfiler v4.10.1 and visualised using enrichplot v1.22.0 (\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e). GO was determined based on Entrez IDs and included biological processes, molecular functions, and cellular components. The Benjamini-Hochberg method was used to adjust p-values for multiple test correction, with the significance threshold of p-value and q-value of \\u0026lt;\\u0026thinsp;0.05.\\u003c/p\\u003e\\n\\u003ch3\\u003eIdentification of putative platypus venom toxins (dup: abstract ?)\\u003c/h3\\u003e\\n\\u003cp\\u003ePutative platypus venom toxins were identified from the upregulated and crural gland-specific subset of the crural gland transcriptome using the DeTox pipeline (\\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e) with minor modifications. The crural gland transcriptome subset was filtered for microorganism contaminants using BLAST (e-value threshold 1e\\u003csup\\u003e\\u0026minus;\\u0026thinsp;5\\u003c/sup\\u003e) (Additional File 2: Table \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003e). Open reading frames (ORFs) were detected using orfipy v0.0.4 (\\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e) (sequences between 99-45000bp retained), and sequences with 99% similarity clustered using CD-HIT v4.8.1 (\\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e). Structure-based toxin detection was conducted by determining secreted proteins through the identification of signal peptides using SignalP 5.0b (\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e) (d-value 0.7) and removing transmembrane proteins using Phobius v1.01 (\\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e). Similarity-based toxin detection was conducted using BLAST against a custom platypus toxin database with an e-value threshold of 1e\\u003csup\\u003e\\u0026minus;\\u0026thinsp;10\\u003c/sup\\u003e (Additional File 2: Table \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003e). Structure-based and similarity-based toxin results were pooled to determine putative toxins. Additional analyses were undertaken for putative toxins, including classification of protein family features using InterProScan v5.52-86.0 (\\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e), prediction of protein localisation using WoLF PSort v0.2 (\\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e71\\u003c/span\\u003e), and detection of cysteine pattern and amino acid repeats using DeTox custom scripts (\\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e). Putative toxins were also searched against the reviewed Swiss-Prot database, Tox-Prot venom database, and complete UniProt platypus protein database (reviewed and unreviewed platypus proteins) using BLAST (e-value threshold 1e\\u003csup\\u003e\\u0026minus;\\u0026thinsp;10\\u003c/sup\\u003e) (Additional File 2: Table \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eResulting putative toxins were manually filtered to only retain toxins that were full length (with a start and stop codon), had a predicted signal peptide, and were the most confident ORF per transcript. With the aim to identify novel platypus venom components, any known platypus venom components investigated in prior studies (\\u003cspan additionalcitationids=\\\"CR26 CR27 CR28\\\" citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e) were not analysed further in this dataset. Physicochemical properties of putative toxins were calculated using ProtParam through the ExPasy server (\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e) and Peptide 2.0 peptide hydrophobicity/hydrophilicity analysis tool (\\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e73\\u003c/span\\u003e). Preliminary functional prediction was conducted using the CSM-peptide webserver (\\u003cspan citationid=\\\"CR74\\\" class=\\\"CitationRef\\\"\\u003e74\\u003c/span\\u003e). Protein structures were modelled using AlphaFold 3 (\\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e) and visualized using ChimeraX v1.9 (\\u003cspan citationid=\\\"CR76\\\" class=\\\"CitationRef\\\"\\u003e76\\u003c/span\\u003e). Protein family/superfamily assignment was confirmed through identification of common motifs and features, and the Dali protein structure comparison server (\\u003cspan citationid=\\\"CR77\\\" class=\\\"CitationRef\\\"\\u003e77\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eFor protein families that had multiple putative platypus toxins members identified, phylogenetics was used to investigate evolutionary relationships. For each protein family, sequences were collated for all platypus proteins (putative venom components and otherwise, found using InterPro ID and manual filtering), any known venomous mammalian toxins (sourced from UniProt, NCBI, and prior studies) and any Swiss-Prot mammalian protein sequences (Additional File 3). Multiple sequence alignments were generated using ClustalW in BioEdit (\\u003cspan citationid=\\\"CR78\\\" class=\\\"CitationRef\\\"\\u003e78\\u003c/span\\u003e). Phylogenetic trees were constructed using IQTree v2.2.2 (\\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e79\\u003c/span\\u003e) with ModelFinder Plus to select the best-fit model for the phylogeny (\\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e80\\u003c/span\\u003e) and 1000 ultrafast bootstrap replicates (\\u003cspan citationid=\\\"CR81\\\" class=\\\"CitationRef\\\"\\u003e81\\u003c/span\\u003e). The consensus tree was visualised using the ggtree package in R.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eTranscriptome generation\\u003c/h2\\u003e\\n \\u003cp\\u003eRNA-Seq data collated from NCBI spanned 65 samples from seven studies (\\u003cspan class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u0026ndash;\\u003cspan class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e), and was filtered to form the final RNA-Seq dataset of 45 samples from five studies (\\u003cspan class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u0026ndash;\\u003cspan class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e) (Additional File 1). These tissue samples included in-season crural gland, brain and cerebellum, kidney, liver, ovary, testis, fibroblast, and heart tissues from 20 individuals. The platypus global transcriptome consisted of 64,871 transcripts from 38,520 genes, with an average transcript length of 2,310bp, and N50 of 3,959bp. The crural gland-only transcriptome consisted of 32,954 transcripts from 14,037 genes, with an average transcript length of 3,354bp, and N50 of 4,551bp. The global transcriptome and crural gland transcriptome contained 88.9% and 67.7% of complete mammalian BUSCOv5.8.0 genes respectively.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eIdentification of key crural genes\\u003c/h2\\u003e\\n \\u003cp\\u003eFrom the global transcriptome, 26,444 genes passed initial filtering to be used in subsequent differential expression (DE) and tissue specificity analysis. 46% of these genes did not have assigned gene names, either from lack of orthology, lack of published gene symbol, or novel transcripts identified in the global transcriptome. Samples clustered by tissue type in MDS analysis regardless of inter-study variability in sequencing or extraction method (Additional File 2: Figure \\u003cspan class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). Redundancy analysis indicated that tissue type and study accounted for 74% of the variation in gene counts and were significant predictor variables (p\\u0026thinsp;=\\u0026thinsp;0.001) (Additional File 2: Table \\u003cspan class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003e). This is not unexpected, given differences in sequencing and extraction methods amongst the five studies (\\u003cspan class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u0026ndash;\\u003cspan class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e). An ANOVA on the variance partitioning analysis indicated that tissue type alone accounted for 67% of the total variation in gene counts, while study only accounted for 3% (Additional File 2: Table \\u003cspan class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003e). Together, these results indicate the validity of the dataset compiled from RNA-Seq data from five studies to investigate differences in gene expression amongst tissues.\\u003c/p\\u003e\\n \\u003cp\\u003eDE analysis using limma found 13.4% of genes to be differentially expressed, with 831 genes upregulated and 2,723 genes downregulated in the crural gland compared to all other tissue types (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA). DE analysis using edgeR found 6.5% of genes to be differentially expressed, with 572 genes upregulated and 1,135 genes downregulated in the crural gland compared to all other tissue types (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eB). Owing to low sample size across tissue types, a conservative estimate of genes upregulated in the crural gland was used, by only including genes that were identified as upregulated in the crural gland by both limma and edgeR methods (n\\u0026thinsp;=\\u0026thinsp;525) in downstream analysis (henceforth termed upregulated genes). 16 genes were shown to have \\u0026gt;\\u0026thinsp;1000-fold upregulation in the crural gland across both DE methods (Additional File 2: Table \\u003cspan class=\\\"InternalRef\\\"\\u003eS4\\u003c/span\\u003e), four of which were upregulated\\u0026thinsp;\\u0026gt;\\u0026thinsp;30,000-fold.\\u003c/p\\u003e\\n \\u003cp\\u003eTissue specificity analysis found 9,286 genes specific to one of the eight tissue types investigated (Additional File 2: Figure \\u003cspan class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003e). 329 of these genes were determined to be crural gland-specific genes (tau\\u0026thinsp;\\u0026ge;\\u0026thinsp;0.85), including 11 genes with absolute specificity to the crural gland (tau\\u0026thinsp;=\\u0026thinsp;1) and no detected expression in any other tissue type included in this study.\\u003c/p\\u003e\\n \\u003cp\\u003e177 genes that were both upregulated in DE analysis and crural gland-specific from tissue specificity analysis, were input for GO analysis and putative toxin identification. Only 25 of these genes had IDs with associated GO terms. Significant GO processes upregulated in the crural gland included biological processes and molecular functions associated with stimulus detection, extracellular matrix organization and catalytic activity (Additional File 2: Figure \\u003cspan class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003e). Of the 177 genes of interest, 55 had their protein sequence assigned to an InterPro protein family, including all 25 genes used in GO analysis.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003ch3\\u003eIdentification of putative platypus venom toxins\\u003c/h3\\u003e\\n\\u003cp\\u003eThe DeTox pipeline identified 37 putative toxins that were both upregulated in the crural gland compared to all other tissues, and crural gland-specific (Additional File 2: Table S5). Manual filtering resulted in the identification of 17 putative venom toxins. Four of these (23%) were previously found in platypus venom, including a corticotropin-releasing factor-binding protein (\\u003cspan class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e), a Kunitz domain containing serine protease inhibitor (\\u003cspan class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e), and two defensin-like peptides (DLP-A (\\u003cspan class=\\\"CitationRef\\\"\\u003e82\\u003c/span\\u003e) and DLP-2/DLP-4 (\\u003cspan class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e)), (Additional File 4). The remaining 13 putative venom toxins (77%) were assigned to an InterPro protein family/superfamily (Table \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The peptidase S1A and secretoglobin families each had three putative toxins assigned to them (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). All 13 protein models displayed structural similarities to their assigned protein families (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e; Additional File 2: Figure \\u003cspan class=\\\"InternalRef\\\"\\u003eS4\\u003c/span\\u003e). Despite InterPro assignment, 31% of the putative toxins, including all three putative secretoglobin toxins, had no hits (with e-value threshold 1e\\u003csup\\u003e\\u0026minus;\\u0026thinsp;10\\u003c/sup\\u003e) to any of the databases used in this study (Additional File 2: Figure S5). Mature protein sequences of the 13 putative platypus toxins ranged from 43\\u0026ndash;693 amino acids (Additional File 2: Table S6), all had potential anti-inflammatory activity (79\\u0026ndash;97%; Additional File 2: Table S7) and all but one were predicted to localise in the extracellular space.\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\n \\u003ctable id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003e13 novel putative platypus venom toxins.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eToxin ID\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eAssociated Gene\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eSignal Peptide Probability\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eInterPro Family/Superfamily\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eProtein Localisation\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eDeTox Toxin Rating\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXR_486810.3_ORF.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLOC103171488\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.999316\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBeta defensin\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSCD?\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_029046826.2_ORF.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLOC100091528\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.977011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCalreticulin/calnexin\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_001513234.4_ORF.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFGFBP1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.990448\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFGF binding 1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSCD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_029081728.2_ORF.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLPO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.986151\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHaem peroxidase, animal-type\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEndoplasmic reticulum\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSCD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_029049771.2_ORF.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLOC103170591\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.997579\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eKazal domain\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSCD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_016227951.3_ORF.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eKERA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.954623\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLeucine-rich repeat domain\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSCD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_003431054.3_ORF.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLOC100681171\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.971443\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLipocalin\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_029064327.1_ORF.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eKLK7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.984628\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePeptidase S1A, chymotrypsin family\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSCD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_029064328.1_ORF.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLOC100090533\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.992461\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePeptidase S1A, chymotrypsin family\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSCD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_029064368.2_ORF.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eKLK1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.800714\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePeptidase S1A, chymotrypsin family\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSCD!\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eXM_016226360.3_ORF.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLOC107547358\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.998521\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSecretoglobin\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSD?\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMSTRG8465.1_ORF.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMSTRG.8465\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.995858\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSecretoglobin\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSD?\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMSTRG8471.1_ORF.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMSTRG.8471\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.997852\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSecretoglobin\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eExtracellular\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSD?\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003eFor DeTox Toxin Rating category: S\\u0026thinsp;=\\u0026thinsp;signal peptide without transmembrane domain; C\\u0026thinsp;=\\u0026thinsp;cysteine pattern with \\u0026ge;\\u0026thinsp;4 cysteine residues; D\\u0026thinsp;=\\u0026thinsp;predicted InterPro domain; ! = hit in Swiss-Prot database but not toxin database; ? = no hits to Swiss-Prot database. For additional DeTox pipeline output, see Additional File 4.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eFor the two protein families where multiple putative toxins were identified (peptidase S1A and secretoglobin families), phylogenetic relationships amongst mammalian members were investigated. Kallikreins (KLKs), a subgroup of peptidase S1A enzymes, contained three platypus putative toxins that did not form a platypus-specific clade but instead were basal to each of the distinct mammalian KLK orthologous groups (97\\u0026ndash;100% bootstrap confidence, Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). Similarly for the secretoglobin family, most secretoglobins cluster by orthologs across species. However, six of nine platypus secretoglobins, including all three putative toxic secretoglobins, form a species-specific cluster of uteroglobin-like proteins with 74% bootstrap support, which may suggest gene duplication within the platypus (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). Despite similarity to uteroglobin (secretoglobin family 1A member 1), this platypus-specific group clusters independently to platypus uteroglobin and the uteroglobins of other mammalian taxa.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eHere, we used genomic and transcriptomic resources from the past 15 years to shed light on the function of the platypus crural system and identify putative toxins. Through the generation of the platypus crural gland transcriptome, we identified 177 genes that were upregulated and specific to the crural gland compared to seven other tissue types, including four genes with \\u0026gt;\\u0026thinsp;30,000-fold upregulation in the crural gland. We found 17 putative platypus venom toxins that were upregulated and crural gland-specific, 13 of which were previously unreported in platypus venom studies. These putative toxins span nine protein families, including families with known toxins in mammalian and non-mammalian venoms, such as KLKs and secretoglobins.\\u003c/p\\u003e\\u003cp\\u003eThrough improvements to genome quality and bioinformatic tools (\\u003cspan citationid=\\\"CR83\\\" class=\\\"CitationRef\\\"\\u003e83\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e84\\u003c/span\\u003e), this study demonstrated a 2.7-fold increase in the number of genes identified in the platypus crural gland transcriptome compared to the last study in 2012 (\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e). Over 85% of these upregulated and crural gland-specific genes did not have assigned gene names, which limited our capacity to impute their function. This highlights the limitation of downstream functional annotation workflows such as GO analysis when applied to unique and non-model species such as the platypus. However, protein family assignment provided classification and basic functional prediction for an additional 30 genes without assigned gene names. The most upregulated gene identified here (MSTRG.16525) had a\\u0026thinsp;\\u0026gt;\\u0026thinsp;400,000-fold increase in expression in the crural gland compared to other tissue types. MSTRG.16525 is likely a non-coding RNA rather than protein-encoding possibly contributing to transcriptional or translational regulation (\\u003cspan citationid=\\\"CR85\\\" class=\\\"CitationRef\\\"\\u003e85\\u003c/span\\u003e). Other highly upregulated genes (\\u0026gt;\\u0026thinsp;30,000-fold increase in expression in the crural gland) encoded either putative toxins identified for the first time in the crural gland (LOC100681171) or previously identified platypus venom components (LOC114813694 and SPAM1) (\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e). In addition, this study demonstrates the potential of pooling samples across studies to overcome limited sample availability, while accounting for variation in extraction and sequencing methods \\u0026ndash; a framework that can be applied to other non-model taxa in the future. As a result, we provide the first comparison of platypus gene expression between the crural gland and other tissue types, in addition to improved gene and protein identification.\\u003c/p\\u003e\\u003cp\\u003eVenoms across taxa often display similarities based on the convergent recruitment of protein families into toxic components, despite differences in the composition and abundance of toxins within venom, and the advantages it confers. All 13 putative toxins identified in this study were classified into nine protein families. Seven are families with known venom components in other taxa, and four (peptidase S1A, secretoglobin, lipocalin, and Kazal domain proteins) are found in the venoms of other mammals (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR82\\\" class=\\\"CitationRef\\\"\\u003e82\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR87 CR88 CR89\\\" citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR90\\\" class=\\\"CitationRef\\\"\\u003e90\\u003c/span\\u003e). Interestingly the two key protein families in this study with multiple putative platypus toxins, peptidase S1A and secretoglobin families, also comprise major venom components in venomous Eulipotyphlans and lorises respectively (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e) (\\u003cspan citationid=\\\"CR88\\\" class=\\\"CitationRef\\\"\\u003e88\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR91\\\" class=\\\"CitationRef\\\"\\u003e91\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003ePeptidase S1 forms a diverse group of enzymes that have been convergently recruited into the venoms of mammals, reptiles, cephalopods, insects and ticks (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e), and were previously shown to be prevalent in the platypus crural gland (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e). Here, we highlight three members of this protein family (KLK1, KLK6 and KLK7) as putative toxins with crural gland upregulation and specificity. Our improved genomic resources enabled identification of full sequences for KLK6 and KLK7, only partially characterised previously (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e) (Additional File 4). Importantly, we also show the upregulation of KLK1 for the first time in the platypus crural gland. KLK1 is a venom component in multiple venomous Eulipotyphlans (\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e), vampire bats (\\u003cspan citationid=\\\"CR87\\\" class=\\\"CitationRef\\\"\\u003e87\\u003c/span\\u003e), and has similarity to snake venom serine proteinases (SVSPs) (\\u003cspan citationid=\\\"CR92\\\" class=\\\"CitationRef\\\"\\u003e92\\u003c/span\\u003e). While KLK1 gene expansions of both toxic and non-toxic paralogs have occurred independently in shrews and solenodons (\\u003cspan citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR93\\\" class=\\\"CitationRef\\\"\\u003e93\\u003c/span\\u003e), no such expansion was found in the platypus. KLK presence has been previously noted in platypus venom (\\u003cspan citationid=\\\"CR94\\\" class=\\\"CitationRef\\\"\\u003e94\\u003c/span\\u003e), but the specific KLK protein within the venom has not been confirmed. As such, at least one of the putative platypus KLK toxins is present within crude venom with future proteomic analysis required for confirmation. KLKs have an important role in the kallikrein-kinin system, where they act on kininogens to produce bioactive kinins involved in a variety of pathophysiological processes, including inflammation and pain in humans and rodents (\\u003cspan additionalcitationids=\\\"CR96\\\" citationid=\\\"CR95\\\" class=\\\"CitationRef\\\"\\u003e95\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR97\\\" class=\\\"CitationRef\\\"\\u003e97\\u003c/span\\u003e). The biological role of platypus KLKs are unknown. In Northern short-tailed shrew (\\u003cem\\u003eBlarina brevicauda\\u003c/em\\u003e) venom, a KLK1 paralog (\\u003cem\\u003eBlarina\\u003c/em\\u003e toxin - BLTX) is a major venom component and may contribute to low blood pressure and motor dysfunction of prey (\\u003cspan citationid=\\\"CR91\\\" class=\\\"CitationRef\\\"\\u003e91\\u003c/span\\u003e). Putative platypus venom KLKs may influence blood pressure, inflammation or the coagulation cascade (\\u003cspan citationid=\\\"CR98\\\" class=\\\"CitationRef\\\"\\u003e98\\u003c/span\\u003e) (Additional File 2: Table S7), or cleave other venom components.\\u003c/p\\u003e\\u003cp\\u003eKLKs are also known to associate with other putative platypus toxins identified in this study. Kazal-type serine protease inhibitors are prevalent across venoms (\\u003cspan citationid=\\\"CR87\\\" class=\\\"CitationRef\\\"\\u003e87\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR100 CR101\\\" citationid=\\\"CR99\\\" class=\\\"CitationRef\\\"\\u003e99\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR102\\\" class=\\\"CitationRef\\\"\\u003e102\\u003c/span\\u003e), and in other mammalian venoms cause blood coagulation, hypokinesia (\\u003cspan citationid=\\\"CR103\\\" class=\\\"CitationRef\\\"\\u003e103\\u003c/span\\u003e), and serve a protective function within the venom gland itself (\\u003cspan citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e). The double-headed Kazal-type serine protease inhibitor in this study (LOC103170591) contains two Kazal domains (\\u003cspan citationid=\\\"CR104\\\" class=\\\"CitationRef\\\"\\u003e104\\u003c/span\\u003e), with the first domain likely responsible for inhibiting trypsin-like proteases such as KLKs (\\u003cspan citationid=\\\"CR105\\\" class=\\\"CitationRef\\\"\\u003e105\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR106\\\" class=\\\"CitationRef\\\"\\u003e106\\u003c/span\\u003e), and the second domain predicted to inhibit chymotrypsin, subtilisin and/or elastase (\\u003cspan citationid=\\\"CR107\\\" class=\\\"CitationRef\\\"\\u003e107\\u003c/span\\u003e). Given this, the platypus two-Kazal domain protein has the potential to be both protective and toxic, however, further investigation is required for confirmation. Interestingly, a platypus fibroblast growth factor-binding protein (FGFBP1) was identified as a putative toxin in this study, yet this family does not appear in venoms of other taxa. In cancer cell lines, FGFBP1 acts as a substrate for both KLK6 and KLK7 (\\u003cspan citationid=\\\"CR108\\\" class=\\\"CitationRef\\\"\\u003e108\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR109\\\" class=\\\"CitationRef\\\"\\u003e109\\u003c/span\\u003e), both of which were also putative platypus toxins. This indicates the potential for synergistic activity between the KLK serine proteases and FGFBP1 within platypus venom that may enhance activity and impact the inflammation and wound healing pathway in the envenomated individual (\\u003cspan citationid=\\\"CR110\\\" class=\\\"CitationRef\\\"\\u003e110\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR111\\\" class=\\\"CitationRef\\\"\\u003e111\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eSecretoglobins are a well-known component of mammalian venoms and have been identified in the venoms all other venomous mammalian orders (\\u003cspan citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR87\\\" class=\\\"CitationRef\\\"\\u003e87\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR112\\\" class=\\\"CitationRef\\\"\\u003e112\\u003c/span\\u003e). Our study marks the first time secretoglobins have been identified as putative venom components in the platypus. While secretoglobins have been found in all other venomous mammalian Orders, only one functional toxic secretoglobin protein has been found in Primates and Eulipotyphlans (\\u003cspan additionalcitationids=\\\"CR87\\\" citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR88\\\" class=\\\"CitationRef\\\"\\u003e88\\u003c/span\\u003e) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). The platypus differs as we found three putative toxic uteroglobin-like secretoglobins, which may have evolved through gene duplication and subsequent neofunctionalisation (\\u003cspan citationid=\\\"CR113\\\" class=\\\"CitationRef\\\"\\u003e113\\u003c/span\\u003e). The inclusion of three putative toxins in this protein family suggests secretoglobins may be an important component of the platypus crural system that requires further investigation. The function of all toxic secretoglobins in vertebrates is unknown (\\u003cspan additionalcitationids=\\\"CR87\\\" citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR88\\\" class=\\\"CitationRef\\\"\\u003e88\\u003c/span\\u003e), including the role of the brachial gland exudate secretion protein (BGEsp) that is a major component in loris venom (\\u003cspan citationid=\\\"CR114\\\" class=\\\"CitationRef\\\"\\u003e114\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR115\\\" class=\\\"CitationRef\\\"\\u003e115\\u003c/span\\u003e). Secretoglobins are dimeric proteins secreted within epithelial cells, glandular tissues and secretions such as sputum, with important roles in immunoregulation, anti-inflammation, tissue repair and tumourigenesis (\\u003cspan citationid=\\\"CR116\\\" class=\\\"CitationRef\\\"\\u003e116\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR117\\\" class=\\\"CitationRef\\\"\\u003e117\\u003c/span\\u003e). Uteroglobin, a member of the secretoglobin family most closely related to the three platypus uteroglobin-like toxins, is a homodimer that can regulate inflammation through inhibition of phospholipase A2 (a pro-inflammatory enzyme commonly recruited into venoms) (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR118\\\" class=\\\"CitationRef\\\"\\u003e118\\u003c/span\\u003e). Uteroglobin is often regulated by hormones (\\u003cspan citationid=\\\"CR119\\\" class=\\\"CitationRef\\\"\\u003e119\\u003c/span\\u003e), which may be pertinent to the platypus as venom production is seasonal. While putative platypus secretoglobins have potential immunoregulatory and anti-inflammatory roles (\\u003cspan citationid=\\\"CR116\\\" class=\\\"CitationRef\\\"\\u003e116\\u003c/span\\u003e) (Additional File 2: Table S7), the interpretation of putative toxic platypus secretoglobins is limited until additional research on the function of the secretoglobin protein family is available.\\u003c/p\\u003e\\u003cp\\u003eOther putative toxins found in the platypus include those that belong to the lipocalin, calreticulin and leucine-rich repeat domain families, which are also commonly recruited into venoms. In platypus, these proteins may be directly toxic or involved in biological processes of the crural gland. Lipocalins are common venom components across taxa (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR120\\\" class=\\\"CitationRef\\\"\\u003e120\\u003c/span\\u003e) and are found in vampire bat venom (\\u003cspan citationid=\\\"CR87\\\" class=\\\"CitationRef\\\"\\u003e87\\u003c/span\\u003e). However, the putative platypus lipocalin toxin (LOC100681171) may not be toxic, as it is also the second-most abundant protein in platypus epididymal fluid (\\u003cspan citationid=\\\"CR121\\\" class=\\\"CitationRef\\\"\\u003e121\\u003c/span\\u003e), in addition to having high expression in the crural gland (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). As such, this lipocalin may be involved in immunomodulation (\\u003cspan citationid=\\\"CR122\\\" class=\\\"CitationRef\\\"\\u003e122\\u003c/span\\u003e), ligand binding as in triatomine (kissing bug) venoms (\\u003cspan citationid=\\\"CR120\\\" class=\\\"CitationRef\\\"\\u003e120\\u003c/span\\u003e), seasonal upregulation, or fluid maturation in both reproductive and crural systems (\\u003cspan additionalcitationids=\\\"CR124\\\" citationid=\\\"CR123\\\" class=\\\"CitationRef\\\"\\u003e123\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR125\\\" class=\\\"CitationRef\\\"\\u003e125\\u003c/span\\u003e). Both the calreticulin (LOC100091528) and leucine-rich repeat (KERA - keratocan) proteins in this study belong to families with known toxins that modulate the immune response (\\u003cspan citationid=\\\"CR126\\\" class=\\\"CitationRef\\\"\\u003e126\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR127\\\" class=\\\"CitationRef\\\"\\u003e127\\u003c/span\\u003e). Outside of a toxic role, calreticulins are important for protein folding and modification (\\u003cspan citationid=\\\"CR128\\\" class=\\\"CitationRef\\\"\\u003e128\\u003c/span\\u003e), and highly expressed in the non-venomous echidna crural gland (\\u003cspan citationid=\\\"CR129\\\" class=\\\"CitationRef\\\"\\u003e129\\u003c/span\\u003e). Similarly, keratocan regulates collagen matrix assembly, which may contribute to forming the connective tissue stroma of the platypus crural system (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eAntimicrobial peptides (AMPs) are another common component of venoms as they protect against infection, and in some cases, contribute to venom toxicity (\\u003cspan citationid=\\\"CR130\\\" class=\\\"CitationRef\\\"\\u003e130\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR131\\\" class=\\\"CitationRef\\\"\\u003e131\\u003c/span\\u003e). The defensin family of AMPs includes defensin-like peptides (DLPs) that are a well-known toxic component of platypus venom (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e). We identified a novel putative β-defensin in the crural gland (LOC103171488) that contained the characteristic cysteine residue spacing of traditional antimicrobial β-defensins (\\u003cspan citationid=\\\"CR132\\\" class=\\\"CitationRef\\\"\\u003e132\\u003c/span\\u003e), rather than that of the toxic DLPs in platypus venom (\\u003cspan citationid=\\\"CR82\\\" class=\\\"CitationRef\\\"\\u003e82\\u003c/span\\u003e). We also identified a haem peroxidase (LPO \\u0026ndash; lactoperoxidase) for the first time in a venom system (\\u003cspan citationid=\\\"CR133\\\" class=\\\"CitationRef\\\"\\u003e133\\u003c/span\\u003e). Due to high upregulation and specificity to the crural gland, the platypus β-defensin and haem peroxidase may be involved in local immune defence of the crural gland.\\u003c/p\\u003e\\u003cp\\u003eThe methods used in this study were designed to capture all possible venom toxins. However, the stringent thresholds used in DE and tissue specificity, which are essential for robust analysis, may have excluded potential platypus venom toxins. For example, OvDLP-C, NPPC and NGF, three genes encoding known platypus venom components (\\u003cspan citationid=\\\"CR134\\\" class=\\\"CitationRef\\\"\\u003e134\\u003c/span\\u003e), did not meet the tissue specificity cutoff and hence were not included in the set of crural gland-specific genes. However, as venom components are likely to have a limited tissue distribution and upregulation in the venom system, thresholds instigated in this study allow for greater confidence in finding key genes and proteins involved in crural gland function. Similarly, the use of similarity-based and structure-based toxin discovery in the DeTox pipeline may include proteins that fit the toxin criteria but are not functionally toxic within the platypus crural system. Identification of key proteins in the crural gland are essential for understanding the platypus crural system holistically, and non-toxic components may assist toxic proteins or have protective roles, particularly for a venom system targeted against conspecifics.\\u003c/p\\u003e\\u003cp\\u003eWhile putative toxin identification provides the first step in uncovering the nature of platypus venom and the platypus crural system more broadly, future proteomic investigation is required to confirm protein expression of key transcripts in platypus venom or crural system. To enable this, crude venom samples are required, which is challenging due to the seasonal nature of platypus venom production and limited past success in sample collection. True functions of these platypus crural system proteins may, or may not, be comparable to other venomous species, or those typical of the protein families identified due to the evolutionary distinctness of the platypus and the uniqueness of their crural system. Functional testing is required to attribute functions and associated envenomation symptoms to various platypus venom components. The crural gland transcriptome generated here will provide a platypus-specific database to aid in future research, allowing for tracing of key crural system genes, transcripts, and proteins.\\u003c/p\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eNew genomic and collated transcriptomic resources have enabled the identification of a suite of genes, transcripts, and proteins of importance to the platypus crural system. Selecting key genes through upregulation and specificity to the crural gland has allowed us to create a set of proteins that we believe are key for the functioning of this system. We have demonstrated the convergent recruitment of toxins across venomous mammalian species and improved our understanding of the venom and crural system of Australia\\u0026rsquo;s only venomous mammal species. Determining important components in a unique system, such as the platypus crural system, provides crucial information allowing for future investigations into platypus venom components and their functions. The genes, transcripts and putative venom proteins identified in this study have the potential for a variety of roles within platypus envenomation, and have demonstrated their importance to the platypus, within their venom and beyond.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eAMP\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eantimicrobial peptide\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eBAM\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003ebinary alignment map\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eBLAST\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eBasic Local Alignment Search Tool\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eBLTX\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003e\\u003cem\\u003eBlarina\\u003c/em\\u003e toxin\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003ebp\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003ebase pair\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eBUSCO\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eBenchmarking Single Copy Gene Orthologs\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003ecDNA\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003ecomplementary DNA\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eDE\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003edifferential expression\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eDLP\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003edefensin-like peptide\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eFPKM\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003efragments per kilobase million\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eGO\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eGene Ontology\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eGTF\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003egene transfer format\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eKLK\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003ekallikrein\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eMDS\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003emultidimensional scaling\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eNCBI\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eNational Center for Biotechnology Information\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eORF\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eopen reading frame\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eOvCNP\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003e\\u003cem\\u003eOrnithorhynchus\\u003c/em\\u003e C-type natriuretic peptide\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eOvDLP/OavDLP-C\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003e\\u003cem\\u003eOrnithorhynchus\\u003c/em\\u003e defensin-like peptide\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eOvNGF\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003e\\u003cem\\u003eOrnithorhynchus\\u003c/em\\u003e nerve growth factor\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eRNA-Seq\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eRNA sequencing\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eSAM\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003esequence alignment map\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eSVSPs\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003esnake venom serine proteinases\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eTMM\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eTrimmed Mean of the M-values\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eTPM\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eTranscript per Million.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003cp\\u003eNot applicable, as previously sequenced datasets were used.\\u003c/p\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\u003c/p\\u003e\\u003ch2\\u003eFunding\\u003c/h2\\u003e\\u003cp\\u003eThis work was funded by the Australian Research Council (ARC) Centre of Excellence for Innovations in Peptide and Protein Science (CE200100012).\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eAG and EP designed the study with guidance from CJH and KB. AG performed all data analysis and wrote the manuscript, with assistance from EP. CJH and KB sourced research funding and project management. All authors read and approved the final manuscript.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgement\\u003c/h2\\u003e\\u003cp\\u003eMolecular graphics performed with UCSF ChimeraX, developed by the University of California, San Francisco, and partners.\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003ePlatypus global transcriptome and crural gland transcriptome are available at [https://awgg-lab.github.io/australasiangenomes/genomes.html] . RNA-Seq data used at all stages of this study were previously published datasets, accessible through the NCBI BioProject database under accession numbers PRJNA12885, PRJNA143627, PRJNA152927, PRJNA186646, PRJNA247824, PRJEB28810, and PRJNA381064.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eFry BG, Roelants K, Champagne DE, Scheib H, Tyndall JDA, King G, et al. The toxicogenomic multiverse: convergent recruitment of proteins into animal venoms. Annu Rev Genom Hum Genet. 2009;10(1):483\\u0026ndash;511.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSchendel V, Rash LD, Jenner RA, Undheim EAB. The diversity of venom: the importance of behavior and venom system morphology in understanding its ecology and evolution. Toxins. 2019;11(11):666.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003ede Oliveira AN, Soares AM, da Silva SL. Peptides from animal venom and poisons. 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J Biol Chem. 1993;268(14):10274\\u0026ndash;81.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSiebert AL, Wheeler D, Werren JH. A new approach for investigating venom function applied to venom calreticulin in a parasitoid wasp. Toxicon. 2015;107(Pt B):304\\u0026ndash;16.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKuhn-Nentwig L, Langenegger N, Heller M, Koua D, Nentwig W. The dual prey-inactivation strategy of spiders\\u0026mdash;in-depth venomic analysis of \\u003cem\\u003eCupiennius salei\\u003c/em\\u003e. Toxins. 2019;11(3):167.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eIsomoto A, Shoguchi E, Hisata K, Inoue J, Sun Y, Inaba K, et al. Active expression of genes for protein modification enzymes in Habu venom glands. Toxins. 2022;14(5):300.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWong ESW, Nicol S, Warren WC, Belov K. Echidna venom gland transcriptome provides insights into the evolution of monotreme venom. PLoS ONE. 2013;8(11):e79092.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSamat R, Sen S, Jash M, Ghosh S, Garg S, Sarkar J et al. Venom: a promising avenue for antimicrobial therapeutics. Acs Infect Dis. 2024.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003ePerumal Samy R, Stiles BG, Franco OL, Sethi G, Lim LHK. Animal venoms as antimicrobial agents. Biochem Pharmacol. 2017;134:127\\u0026ndash;38.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003ePazgier M, Hoover DM, Yang D, Lu W, Lubkowski J. Human β-defensins. Cell Mol Life Sci. 2006;63(11):1294\\u0026ndash;313.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMagacz M, Kędziora K, Sapa J, Krzyściak W. The significance of lactoperoxidase system in oral health: application and efficacy in oral hygiene products. Int J Mol Sci. 2019;20(6):1443.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWhittington C, Belov K. Platypus venom: a review. Australian Mammalogy. 2007;29(1):57\\u0026ndash;62.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-genomics\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"gics\",\"sideBox\":\"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/gics\",\"title\":\"BMC Genomics\",\"twitterHandle\":\"#BMCGenomics\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"platypus, venom, transcriptome, monotreme, kallikrein, secretoglobin\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7394805/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7394805/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e\\u003cp\\u003eThe platypus (\\u003cem\\u003eOrnithorhynchus anatinus\\u003c/em\\u003e) is one of 15 confirmed venomous mammals worldwide, and possesses a unique venom system, termed the crural system. Used for intraspecific competition, their sexually dimorphic and seasonal venom causes pain and functional impairment in envenomated individuals. Despite its unique nature, investigations into the platypus crural system are limited. Utilising the new platypus genome and a suite of transcriptomic data collected over the past 15 years, we investigate key genes, transcripts and proteins of importance to the platypus crural system.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e\\u003cp\\u003eWe generated a global transcriptome and a crural gland-specific transcriptome for the platypus, utilising the new platypus genome and 45 RNA-Seq samples collated from past studies. From this, we found 177 upregulated and crural gland specific genes of importance. 13 putative toxins have been identified for the first time. 85% of these belong to protein families found in venoms and include kallikreins and secretoglobins key in mammalian venoms. Three putative toxic kallikreins were identified as well as two additional putative toxins that may be influencing kallikrein activity in platypus venom. All three putative toxic secretoglobins belong to an independent cluster of uteroglobin-like proteins and are unique to the platypus.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e\\u003cp\\u003eNew omics resources have allowed us to uncover new genes, transcripts and proteins of importance to platypus venom and their crural system. This work reinforces the importance of convergent recruitment in the toxin repertoires of venomous mammals through proteins such as kallikreins and secretoglobins. Our findings have enhanced knowledge of the platypus crural system and provided new insights into platypus venom composition.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Insights into Platypus Crural Gland Transcriptomics – Venom and Beyond\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-02 13:50:22\",\"doi\":\"10.21203/rs.3.rs-7394805/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-10-14T09:52:12+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-10-07T21:06:11+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-09-22T18:23:28+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"31981275143568923377615221373277765842\",\"date\":\"2025-09-16T16:39:50+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"239867388253720733854342154887536781439\",\"date\":\"2025-08-27T10:24:14+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-08-25T10:00:01+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-08-19T20:05:35+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-08-18T05:38:13+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-08-18T05:38:07+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Genomics\",\"date\":\"2025-08-18T01:09:02+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-genomics\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"gics\",\"sideBox\":\"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/gics\",\"title\":\"BMC Genomics\",\"twitterHandle\":\"#BMCGenomics\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"00647ba4-26bf-46a6-89ee-fbbfadf75da8\",\"owner\":[],\"postedDate\":\"September 2nd, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-11-17T16:04:42+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-7394805\",\"link\":\"https://doi.org/10.1186/s12864-025-12299-x\",\"journal\":{\"identity\":\"bmc-genomics\",\"isVorOnly\":false,\"title\":\"BMC Genomics\"},\"publishedOn\":\"2025-11-12 15:58:45\",\"publishedOnDateReadable\":\"November 12th, 2025\"},\"versionCreatedAt\":\"2025-09-02 13:50:22\",\"video\":\"\",\"vorDoi\":\"10.1186/s12864-025-12299-x\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12864-025-12299-x\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7394805\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7394805\",\"identity\":\"rs-7394805\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}