Immune targets for schistosomiasis control identified by a genome-wide association study of African snail vectors

Immune targets for schistosomiasis control identified by a genome-wide association study of African snail vectors | 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 Article Immune targets for schistosomiasis control identified by a genome-wide association study of African snail vectors Michelle Steinauer, Tom Pennance, Jacob Tennessen, Johannie Spaan, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5656395/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jul, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Schistosomiasis, a neglected tropical disease, is transmitted by freshwater snails. Interruption of transmission will require novel vector-focused interventions. We performed a genome-wide association study of African snails, Biomphalaria sudanica , exposed to Schistosoma mansoni in an endemic area of high transmission in Kenya. Two snail genomic regions, SudRes1 and SudRes2, were significantly associated with snail immunity to schistosomes. SudRes1 includes receptor-like protein tyrosine phosphatases while SudRes2 includes a class of leucine-rich repeat-containing G-protein coupled receptors, both comprising diverse extracellular binding domains suggestive of host-pathogen interaction. Resistant and susceptible haplotypes show numerous coding differences including presence/absence of entire genes. No loci previously tied to schistosome resistance in neotropical snail species showed any association with compatibility suggesting that loci involved in the resistance of African vectors are distinct. Snail ancestry was also strongly correlated with parasite compatibility. These results will inform future efforts to predict and manipulate immunity of a major schistosome vector. Biological sciences/Genetics/Genetic association study/Genome-wide association studies Biological sciences/Microbiology/Parasitology/Parasite host response Biological sciences/Microbiology/Pathogens Health sciences/Diseases/Infectious diseases/Parasitic infection Biological sciences/Microbiology/Parasitology/Parasite genomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Schistosomiasis is a global scourge, taking a large toll on people who have the fewest resources. Affecting over 260 million people, it is the parasitic disease with the greatest impact on health worldwide after malaria (1, 2). Within the last decade, schistosomiasis control program goals have shifted from reduction of morbidity to elimination or interruption of schistosomiasis as a public health problem by 2030 (1, 3, 4). However, the toolbox with which to combat schistosome transmission has remained virtually the same, dominated by one main approach: mass drug administration (MDA) of praziquantel (5). It is increasingly recognized that in addition to chemotherapy, successful control and elimination will require targeting the aquatic snails which serve as intermediate hosts of the schistosome parasites and transmit them to humans (6, 7). Part of the reason MDA alone is insufficient is that even with effective drug treatment, people become rapidly reinfected by infected snails in the environment (8–10). Schistosomes form chronic infections in snails and continually release hundreds to thousands of infectious stages (cercariae) into the environment daily (11). Historically, schistosomiasis control programs that are focused on snail control have been the most successful at reducing or eliminating schistosomiasis (12, 13); however, snail-directed control methods are limited and have negative impacts. Molluscicides are indiscriminately toxic and are impractical to apply to vast habitats (12, 14). Furthermore, snail population rebound post-molluscicide application is predicted to increase schistosome transmission (15). Given the absence of suitable snail vector control methods for contemporary public health interventions, there is a need for new approaches to be developed (16). Genomic and transcriptomic data and resources enable approaches like genome-wide association studies (GWAS) that identify genomic regions of snail vectors involved in resisting schistosome infection (17). Once identified, snail genes and genomic variants associated with resistance to schistosomes could be monitored in wild populations and potentially be manipulated so that snail resistance to schistosomes is enhanced and transmission to humans is interrupted. The feasibility of manipulating snail resistance to schistosomes may follow similar approaches to engineering resistant hosts for disease control using CRISPR-Cas and associated gene drive technologies (18, 19). However, much of the elegant work regarding transcriptomics and genomics of schistosome-snail compatibility has only addressed these questions in laboratory models of the South American vector of Schistosoma mansoni , Biomphalaria glabrata (17, 20–24). Very little is known regarding how this body of knowledge will translate to African vectors of S. mansoni , through which 90% of S. mansoni transmission occurs (25). The recent publication of two African Biomphalaria species genomes and transcriptomes (26, 27) provide a path toward molecular-informed snail control in hotspots of transmission. With the goal of identifying and describing the genetic architecture underlying resistance of African snails to S. mansoni , we performed a pooled genome-wide association study (pooled-GWAS) (28) using a wild population of Biomphalaria sudanica originating from the shores of Lake Victoria closest to a persistent hotspot of schistosomiasis in Kanyibok, western Kenya (10). We identify two large-effect loci and a strong influence of ancestry on snail resistance to schistosome infection, defined here as complete parasite clearance (including parasite DNA) from snail tissue following exposure. These results reveal how immunogenetics and population demographics contribute to vectorial competence in a natural vector population with direct impact on human health. Results Pooled-GWAS reveals multiple variants strongly enriched in resistant snails. Of 1400 F1 B. sudanica , whose parents originated from Anyanga Beach (Lake Victoria, western Kenya), exposed to eight freshly hatched S. mansoni miracidia from local schoolchildren, 1,109 snails remained in the GWAS study after excluding 254 that died prior to screening for infection and 37 that yielded insufficient genomic DNA (gDNA) quality. The final sample set comprised 615 and 393 snails that were positive (i.e. releasing S. mansoni cercariae) or negative (i.e. not releasing S. mansoni cercariae nor PCR positive (29)), respectively. Snails that were negative for cercariae but positive for S. mansoni gDNA were not considered further. Two equal mass gDNA pools for the pooled-GWAS comprised 493 positive and 295 negative snails. The pooled-GWAS sequencing (Illumina paired-end 150 bp, NovaSeq 6000 S4 flow cell) yielded on average 1.5x coverage per snail (Dataset S1). A total of 4,498,972 variants were retained for analysis. Correlation between sequencing technical replicates of positive and negative pooled gDNA was weak but significantly positive, with 8-fold enrichment for outliers in the top 1% of both replicates (Fig. S1). In the pooled-GWAS results, genotype-phenotype association p values ranged as low as 1e-30, including 45 variants (0.001%) with p ≤ 1e-15 and 1,930 variants (0.04%) with p ≤ 2.5e-9 (Fig. 1). Rather than simply defining a genome-wide significance threshold to identify candidates to be validated, we prioritized genomic regions meeting a dual-variant criterion, whereby two or more proximate ( 1.5 kb apart to ensure support from distinct read pairs) variants are strongly associated with S. mansoni resistance (arbitrary threshold of p ≤ 2.5e-9); such sliding dual-variant 50 kb windows encompass 18.625 Mb (2%) of the B. sudanica reference genome Bs111 (27) and contain 888 (46%) of variants with p ≤ 2.5e-9. Amplicon panel genotyping reveals population structure and validates variants associated with resistance. A multiplex amplicon panel was designed using the Genotyping-in-Thousands by sequencing method (30) to genotype variants in individual snails at 234 dual-variants and 12 singleton-variants with p < 1e-13 identified from the pooled-GWAS analysis (Dataset S3). The amplicon panel also contained 22 markers for a priori gene candidates and 201 ‘neutral’ markers to facilitate a linkage map for improved B. sudanica genome assembly (Dataset S2). An independent set of 122 positive and 98 negative snails not included in the pooled-GWAS were reserved for validation of genomic variants via genotyping with the amplicon panel and are henceforth referred to as genotyped-validation snails. These independent genotyped-validation snails were used to validate the differential allele frequencies associated with S. mansoni resistance observed in the pooled-GWAS sequencing data. These were combined with a subset of the pooled-GWAS snails (genotyped-pooled-GWAS snails: 138 positive, 138 negative) for more precise estimates of ancestry and genotype frequencies. The amplicon panel data (of which median missing data was 2% per locus and 2% per individual) revealed a signal of population structure, evident in both PCA (Fig. S5) and ADMIXTURE (31) analysis (Fig. 2A). With K = 2 ancestral populations (CV = 0.53, versus 0.61 for K = 1), ancestry from Population 2 ranged continuously from 0 to 1 and was significantly correlated with resistance ( p < 1e-14). Mean Population 2 ancestry was 39% for positives and 62% for negatives. Snails were designated into two groups based on the percentage of their ancestry: 41% of snails had mostly Population 1 ancestry and were deemed “Group A”, while the remainder, with mostly Population 2 ancestry, were deemed “Group B”. Of the snails in Group A, 68% were positive. In Group B, 41% were positive. Thus, any marker differing in frequency between these ancestral populations could be correlated with infection phenotype, even if not linked to an etiological variant, and therefore could explain some outliers identified by the pooled-GWAS. Using markers diagnostic of both groups A and B, we found that B. choanomphala , a closely related deep-water taxon/eco-phenotype of B. sudanica also collected in Lake Victoria (32), and B. sudanica inbred lines originating from Lake Victoria (27), share ancestry with Group A, and thus the GWAS ancestry signal is not caused by interspecies hybridization (Fig. S6). The inferred percentage of Population 1 or 2 ancestry for each snail was similar when estimated using linkage map markers alone, and thus not driven by GWAS outliers (Fig. S7). After accounting for ancestry, only variants within two genomic regions, henceforth referred to as SudRes1 and SudRes2 , showed significance (Bonferroni-corrected p < 0.05, designated henceforth as 'validated-variants’) in a dominance (Fig. 2B) or an additive regression (Fig. 2C) model (Dataset S3). Notably, the p-values of the variants in SudRes1 and SudRes2 were amongst the lowest of the dual-variant outliers identified by the pooled-GWAS (Fig. 1). The three validated-variants for SudRes1 (Fig. 2B) and validated-variant for SudRes2 (Fig. 2C) acted as dominant markers (only two genotypes observed), so to assess genotype-phenotype associations in more depth we examined codominant proxy variants and used these as representative variants for each region (Fig. 2D). For the SudRes1 representative variant (c582:65,596, Fig. 2D), allele T was protective in the pooled-GWAS and in the genotyped-validation snails. Combining data from the genotyped-validation and genotyped-pooled-GWAS snails, odds of B. sudanica infection with S. mansoni were 0.31 for genotype TT, 0.57 for genotype GT, and 1.37 for genotype GG, consistent with an additive effect. For the SudRes2 representative variant (sc94:2,174,117, Fig. 2D), allele A was protective in the pooled-GWAS and in the genotyped-validation snails. Combining data from the genotyped-validation and genotyped-pooled-GWAS snails, odds of S. mansoni infection in B. sudanica were 0.36 for genotype AA, 0.74 for genotype TA, and 2.40 for genotype TT, also consistent with an additive effect. The best-fitting multiple regression model (AIC = 451.11 and p < 0.001 for all variables) included: ancestry; SudRes1 (representative variant c582:65,596, Fig. 2D); and SudRes2 (representative variant sc94:2,174,117, Fig. 2D), with both genetic markers acting additively (Fig. 2E). The model predicts a ~ 2-fold effect per allele at each genetic marker, and a ~ 4-fold effect of ancestry. Thus, the predicted odds of infection for a snail with no Population 2 ancestry and major allele homozygous genotypes at SudRes1 and SudRes2 (4.46) is 62-fold higher (approximately 2 2 *2 2 *4) than the odds for a snail with 100% Population 2 ancestry and minor allele homozygous genotypes at both loci (0.07). SudRes1 is rich in paralogous genes encoding MEGF domains. SudRes1 comprises 1.07 Mb of Bs111 and contains 23 protein coding genes across five contigs (c6844, c582, c5209, c6, c2) that are closely linked on chromosome 5 (Fig. 3A, Fig. S2 and Fig. S3). Notably, 10 of these 23 genes encode multiple epidermal growth factor (MEGF) domains (Fig. 3A, Dataset S4). Three of these MEGF proteins in c6844, c5209, and c582, display a common single pass transmembrane domain (TMD) structure, with intracellular tyrosine-specific protein phosphatase (PTP) domains and extracellular MEGF and a galactose binding domain (GBD), forming a receptor-like PTP (RPTP) protein (Fig. 3B). Each of these three RPTP genes within the SudRes1 region are adjacent to Antistasin-like protein coding genes (Fig. 3C). Only 14 other MEGF/GBD-containing RPTP genes are annotated in Bs111, 13 of which are clustered near SudRes1 on chromosome 5 (Fig. 3A, Dataset S4). Of the three validated-variants in SudRes1 (Fig. 2B), one was contained within the intron of an MEGF/GBD-containing RPTP protein in contig c6844 (Fig. 3C, Fig. S8A), whilst the other two were in the intergenic region either side of another MEGF/GBD-containing protein (contig c6 ortholog 1, Dataset S4). Similarly, the two ‘top-outlier’ variants (defined as variants with 1.3e-04 < p < 1.0e-03 following validation, see Fig. 2B) in adjacent contigs c582 and c2 in SudRes1 were contained within the intronic gene sequence of an MEGF/GBD-containing RPTP protein (c582_65696, Fig. 3C; BSUD.15164, Dataset S4) and another MEGF/GBD-containing protein (c2 ortholog 2, Dataset S4). Three of the five contigs in the SudRes1 region, c6844, c5209 and c582, are homologous with each other and match the same unduplicated orthologous region on B. glabrata chromosome 5 and B. pfeifferi LG5 (Fig. S9 and S10). Aligned read coverage was also atypically low across all SudRes1 contigs compared to the rest of the genome (Fig. S11). We compared the Bs111 reference genome, harboring the susceptible SudRes1 haplotype, to a PacBio genome assembled from a snail homozygous for a resistant SudRes1 haplotype (Bs2280, coverage of ~ 13x, N50 of ~ 87 kb). While SudRes1 is not fully assembled in either genome, we can detect substantial structural rearrangements resulting in different numbers of genes for some clusters of homologous loci (Dataset S4, Fig. 3C). Consistent with extensive sequence duplication, Bs2280 includes multiple copies of some amplicon sites (Dataset S6), explaining why these failed to show Mendelian segregation and instead acted as dominant markers. One particularly variable segment, occurring in several divergent copies in both genomes, contains the adjacent antistasin and RPTP genes (Fig. 3C). Among putative orthologs, there are many nonsynonymous differences including occasional differences in protein length resulting in loss of functional domains, especially in RPTPs (Fig. 3D). Notably, this includes EGF domain loss in the resistant snail Bs2280 (Fig. 3D), suggesting that the snails mechanism of S. mansoni resistance could involve the loss of function of a protein critical for parasite invasion. SudRes2 is characterized by a large family of GRL101-like GPCR genes. SudRes2 comprises a 440 kb region between 1.82 and 2.26 Mb on contig sc94 of Bs111 chromosome 6 (Fig. 4A, Fig. S2 and Fig. S4). Following manual annotation of SudRes2 , 14 protein coding genes were identified (Fig. S12 and Dataset S5). Ten of these encode mutually paralogous GRL101-like proteins, defined as G-protein coupled receptor (GPCR) transmembrane proteins with extracellular regions containing a leucine rich repeat (LRR) region, a low-density lipoprotein receptor class A repeat (LDL) and a C-type lectin-like (CTL) domain (Fig. 4B); an additional two GRL101-like genes in SudRes2 are missing the CTL or LDL domain and may represent incomplete proteins (Dataset S5). Of the 437 GPCR genes in Bs111 (27), only six genes outside of SudRes2 are annotated as possessing GRL101, CTL, and LDL domains (Dataset S5). Bs2280, the resistant snail genome, was also homozygous for a resistant SudRes2 haplotype, facilitating comparison with the susceptible Bs111 haplotype. In both genomes, assembly of this region is nearly complete, and reveals several genes that are present in only one genome, or are duplicated in one haplotype (Fig. 4C). Similarly, some orthologs differed in length between genomes, being truncated in one or the other. Both the validated-variant and top-outlier variant in Bs111 SudRes2 are contained in the non-coding regions of non-GRL101 gene, BSUD.25704 , clustered within the GRL101 genes, which when complete encodes a protein with a zinc finger RING-type (Zn-RING) domain and inhibitor of apoptosis (IAP) repeat region (i.e. Zn-RING-IAP) (Fig. 4C, Fig. S8B). In the reference/susceptible SudRes2 haplotype, a nonsense variant (Bs111 sc94:2,167,458) in BSUD.25704 truncates the protein at 323 aa, however in the resistant Bs2280 ortholog, a 391 aa protein can be translated. Furthermore, in Bs2280 a paralogous Zn-RING coding gene (truncated and not including IAP) is present within a divergent portion of the orthologous SudRes2 region (Fig. 4C). Amplification of both BSUD.25704 and its paralog in resistant haplotypes is likely responsible for the non-Mendelian behavior of the validated marker (sc94:2,166,296) which appears as heterozygous in resistant snails (Fig. 4C; Dataset S6). On the boundary of SudRes2 is a baculoviral IAP repeat containing (BIRC) protein coding gene BSUD.25705 (Fig. 4C), many of which are contained in the genome regions neighboring SudRes2 . Prior to the manual annotation of the 14 genes contained with the Bs111 genome, the SudRes2 region was exceptional in that: 1) only four protein coding genes in 440 kb had been annotated in this region of the reference B. sudanica genome, much lower than the genome-wide density of one gene per 40 kb; 2) a low density of variants were present (Fig. 3A and Fig. S12), and; 3) a large drop in aligned pooled-GWAS read coverage across the central 240 kb of SudRes2 was apparent (Fig. S13 and S14). To confirm the presence and validity of the manually annotated GRL101 genes, B. sudanica RNA transcript data was successfully aligned to 11 of the 12 predicted GRL101 CDS sequences in the SudRes2 region (all except GRL101_3). Phylogenetic analysis of protein coding sequences also revealed that the B. sudanica syntenic (conserved gene order) orthologs identified in B. glabrata and B. pfeifferi (Dataset S5) were also the most closely related (Fig. S15). Discussion Identification of loci associated with schistosome resistance in a wild snail vector population. In this study, we identified and validated two previously uncharacterized genomic regions, SudRes1 and SudRes2 , in the African snail vector B. sudanica that are associated with resistance to S. mansoni infection, each contributing a similar effect size of a ~ 2-fold change in S. mansoni infection odds ratio per allele. Both regions contain long segments with unusually low pooled-GWAS read coverage and contain few annotated genes in the reference genomes of Biomphalaria sp., suggesting possible structural variation or allelic divergence that preclude unambiguous alignment of reads and complicates assembly and annotation of these regions. It is crucial therefore to acknowledge that the validated-variants associated with schistosome resistance may not themselves be causal polymorphisms, instead they highlight that something significant is occurring in these regions that may remain elusive using the current B. sudanica genome assemblies (27), potentially due to structure rearrangements or unaligned alleles. Manual annotation of both SudRes regions revealed that they are enriched with transmembrane protein coding genes with diverse extracellular regions composing of protein-protein interacting and carbohydrate binding domains, relevant to immune-related functions such as pathogen recognition (33, 34). SudRes1 is characterized by MEGF-domain containing genes, including receptor-like protein-tyrosine phosphatases (RPTPs), comprising extracellular MEGF, extracellular GBD, and intracellular tandem PTP domains. These potentially heavily glycosylated RPTPs may form stable dimers on the cell surface (35), with ligand binding triggering confirmational changes that expose or occlude catalytically active regions of the intracellular membrane-proximal PTPs, transducing signals across the cell membrane (36, 37). The presence of schistosome resistance-associated variants surrounding the B. sudanica RPTPs suggests that increased efficacy or upregulation of these proteins may counteract S. mansoni -induced phosphorylation, one of the parasite’s strategies to manipulate or evade the snail immune system and promote its survival (38). Neighboring each RPTP in the SudRes1 region were antistasin genes, a type of serine protease inhibitors that were originally described as anticoagulants in blood feeding species and since been attributed to immune responses in marine gastropods (39). While SudRes1 is not fully assembled in either Bs111 and Bs2280 genome, it appears likely that homologous contigs within each genome represent paralogous segments rather than alleles, since similar gene counts were observed in both genomes, suggesting recent gene duplications after B. sudanica diverged from B. glabrata and B. pfeifferi . The SudRes1 region was previously noted as showing exceptionally high nucleotide diversity in B. sudanica (27), which when coupled with the pooled-GWAS results suggest that pathogen-mediated balancing selection may act on these genes as previously hypothesized. Our findings here support the approach of using genome hyperdiversity as a proxy for identifying immune related genes in uncharacterized genomes (27). SudRes2 contains resistance-associated variants within a Zn-RING-IAP gene, which neighbors a cluster of 12 leucine rich repeat-containing G protein-coupled receptor (LGR) family genes where pooled-GWAS variants are distributed throughout. The structure of the SudRes2 LGR proteins is similar to GRL101, a LGR first described in the gastropod species Lymnaea stagnalis notable for its N-terminal extracellular LRRs and LDLs (UniProt accession P46023 (40)). Unique to the B. sudanica GRL101 genes characterized in SudRes2 , however, is the N-terminal C-type lectin (CTL) fold/domain. CTL domain containing proteins are established components of both vertebrate and invertebrate innate immune systems as recognition and effector molecules, which show pathogen dependent expression patterns (41–43). Due to the architecture of the SudRes2 GRL101 proteins, the CTL domain likely extends away from the cell membrane exposing the CTL binding region to cytoplasmic ligands (such as those derived from invading pathogens) that could then be presented to the GPCR membrane-spanning binding pocket, triggering G-protein activation. Homology and phylogenetic placement of the syntenic GRL101 proteins indicates a shared ancestry, and possible functional conservation, in GRL101 genes retained since the split of B. glabrata and African Biomphalaria species ~ 5 Mya (26, 44), although the incomplete assembly of available Biomphalaria genomes in this hyperdiverse region may impede inferences of expansion and contraction. To our knowledge, GRL101-like proteins have not been affiliated with immunity in gastropods, but have been shown to play an important role in innate immunity of other invertebrates (45, 46). Although GRL101-like genes were present elsewhere in the B. sudanica genome, the dense cluster of GRL101 genes in the SudRes2 region is unique in that in Bs111 it is the only region < 0.5 Mb with 12 GRL101 genes, with the caveat that GRL101 genes elsewhere in the B. sudanica reference genome may also not be annotated correctly. Evidence of a shifting snail population structure in Lake Victoria could lead to increased infections. A surprising result was the discovery of ancestry heterogeneity in our GWAS snails, whose parents had all been collected at the same time and place. More remarkable still, this ancestry signal is strongly correlated with schistosome resistance. Thus, many outliers in our pooled-GWAS could represent ancestry-informative markers with no physical linkage to resistance genes. Population ancestry estimates using only neutral linkage map markers were very similar to those using the full panel including GWAS outliers, supporting that the ancestry effect observed is real and not an artifact of using atypical variants implicated by the GWAS. Considering the importance of snail ancestry in schistosome compatibility here, potential causes behind the population structure were tested. First, no support for reproductively isolated cryptic Biomphalaria species in Lake Victoria causing the structure was found, since the ancestry estimates varied continuously between populations, and because no marker was fixed between ancestral populations. Second, since the estimated allele frequencies for the two ancestral populations are continuously distributed, and only few alleles are observed at a similar frequency, we do not expect that a single prolific snail had parented a disproportionate amount of the offspring used in the GWAS. Third, while B. sudanica and the deep-water taxon B. choanomphala are closely related, perhaps being ecophenotypes (32), sympatric, and distinct in parasite susceptibility (47), they do not represent the ancestry groups and cluster with B. sudanica having a majority Population 1 ancestry. Rather, Population 2 B. sudanica is distinguished by a set of alleles that do not appear to be common in either species. The population structure of B. sudanica in Lake Victoria observed in our results is more consistent with historical isolation and reconnection of populations. Of the major lakes in the Albertine Rift Valley lake system (Victoria, Tanganyika, Malawi), Lake Victoria is a relatively young lake forming ~ 0.4 Mya, and has gone through at least three major desiccations in the past 100,000 years (48–50). Shaped by such drought events, the cichlids of Lake Victoria have become a famous study system due to the astounding levels of explosive diversification that has occurred since the last desiccation event < 15,000 years ago (51, 52). The population structure of B. sudanica observed suggests that indeed cryptic population structure is present, potentially caused by these historic events, yet the degree of admixing between populations in our study signifies ongoing outcrossing rather than clear speciation. The signatures of ongoing admixing may be influenced by hydrologic patterns of Lake Victoria. The collection site was ~ 20 miles north of the Rusinga channel connecting the open lake and narrow Winam gulf. The Winam gulf is a unique lake environment given that it is somewhat separated from open lake water due to the prevailing currents limiting circulation of water (53, 54), is comparatively shallower, potentially exacerbating historic water level changes, and has more protected shores, providing different freshwater habitats than those present in the open lake. The hydrology of the Rusinga channel and therefore Winam gulf was most recently disrupted by the blocking of the Mbita passage in the early 1980’s, until its unblocking in 2017 (55), therefore occurring just prior to our snail collections in early 2018. The return of north-easternly flow of open-lake water into the Winam gulf through the Mbita passage has caused a shift in both bacterial and planktonic communities in the Winam gulf (56, 57), and may have allowed dispersal of B. sudanica populations on floating vegetation, such as water hyacinth between lake areas (58). Although we cannot establish the potentially different geographic origins of the B. sudanica representative of each population using currently available data, these snail population differences, and therefore vectoral competency differences, could explain why some locations around lakes are persistent hotspots of transmission while others are not (10). These findings underscore how pathogen resistance can vary substantially between closely related populations, and in this instance could suggest that schistosome transmission may be more persistent in lake regions where highly susceptible Biomphalaria populations, i.e. majority Population 1 ancestry, are present. Evolutionary dynamics of snail-schistosome interaction. This study complements extensive work on immune mechanisms in laboratory populations of B. glabrata (17, 20, 22, 59), facilitating comparisons between snail species. Notably, there was no overlap between our validated GWAS hits and loci linked to resistance in B. glabrata . The amplicon panel included at least two amplicons within or near each of these a priori candidates (27), and none of them showed a significant association with infection phenotype. SudRes1 resides on chromosome 5, the site of a large resistance QTL in B. glabrata (22), though about 10 Mb away and thus unlikely to include the same gene(s). SudRes2 resides on B. sudanica chromosome 6, which contains a density of schistosome-resistance a priori loci including PTC1 (59), tlr (60), sod1 (61), and the closest, prx4 (62), at ~ 1 Mb away is not likely to be responsible for association in our analysis. While allelic variation in orthologs of B. glabrata resistance loci are not associated with S. mansoni resistance in B. sudanica , reverse genetics approaches successfully applied in B. glabrata (63, 64) can be used in the future to functionally evaluate the roles of these genes. Biomphalaria sudanica may rely on entirely different genetic mechanisms for parasite resistance than B. glabrata . However, considering the extensive genotype-by-genotype interaction documented between B. glabrata and S. mansoni (65), mediated by hyperdiverse resistance loci suggestive of long-term balancing selection (17, 59), we propose a more nuanced scenario. Namely, that resistance alleles fluctuate dynamically in response to the genotypes of local parasites (including other trematodes), so the loci harboring large-effect, intermediate-frequency alleles will vary over time and space, even within a species. Other trematode species may be more prevalent and exert greater selection pressure on these snails, indirectly impacting resistance to S. mansoni . The striking 4-fold effect of ancestry on odds of infection also supports this dynamic view, as subpopulations different in resistance may be distributed unevenly across Lake Victoria. Diversity at both SudRes1 and SudRes2 is high, as shown by previous polymorphism scans (27) and confirmed by the substantial sequence and structural divergence between susceptible genome Bs111 and resistant genome Bs2280. We are unable to pinpoint causal genes yet, and the numerous differences between resistant and suspectable haplotypes means several candidates are plausible. Each genome assembly contains genes and/or gene segments that are absent in the other assembly. Thus, the host-parasite interaction mechanism(s) could include recognition by S. mansoni of snail hosts possessing a particular susceptibility protein, triggering successful infection, or else recognition of the parasite by snails possessing a particular resistance protein, triggering immune cascades (66). If what matters is parasite recognition of the host, loss of EGF domains in SudRes1 RPTP proteins in resistant snails may inhibit parasite recognition of snail host molecules, and hinder parasite-driven modification of the host response. Similarly, loss of SudRes2 GRL101 genes in resistant snails may prevent the parasite from recognizing these snails, rendering them immune. In contrast, if resistance is driven by host recognition of the parasite, this could be mediated by nonsynonymous allelic differences in SudRes1 and SudRes2 or larger structural changes. For example, at SudRes2 the non-truncated Zn-RING-IAP gene BSUD.25704 , and its additional partial paralog, could fulfill a recognition function in resistant but not susceptible genomes. Parasite-resistance regions PTC1 (59) and PTC2 (17) in B. glabrata can show both dominant resistance and dominant susceptibility (59, 67) and are also highly polymorphic in B. sudanica (27), indicating a similar pattern of immune-relevant balancing selection consistent with long-term snail-parasite coevolution. By revealing immune-relevant genetic variation in B. sudanica , the primary vector in African Great Lakes, this work represents an important step toward molecular-informed vector control to combat schistosomiasis in high-transmission global regions, including gene drive technologies (68). However, we demonstrate that genetic manipulation of snails for schistosomiasis control will require navigating the ever more complex genetic architecture of snail resistance, particularly when considering the non-overlap in findings from the laboratory model South American species B. glabrata and the diversity of snail vector species responsible for the majority of schistosome transmission in Sub-Saharan Africa. The impact of any resistance allele may vary due to genetic background and environmental factors. However, we expect that the large-effect loci identified here will play key roles in the continued elucidation of snail immunity as it pertains to human disease. Materials and Methods Additional description of materials and methods is provided in SI Materials and Methods. Declarations Ethical considerations . This project was undertaken following approval from the relevant bodies, including Kenya Medical Research Institute (KEMRI) Scientific Review Unit (Approval # KEMRI/RES/7/3/1 and KEMRI/SERU/CGHR/035/3864), Kenya’s National Commission for Science, Technology, and Innovation (License # NACOSTI/P/15/9609/4270 and NACOSTI/P/22/14839), Kenya Wildlife Services (permit # 0004754 and # WRTI-0136–02-22), and National Environment, Management Authority (permit # NEMA/AGR/46/2014 – Registration # 0178 and NEMA/AGR/159/2022 – Registration # 201). Collections of S. mansoni from schoolchildren were approved by KEMRI’s Scientific and Ethics Review Unit (SERU), reference SERU No. 3540, and by the Institutional Review Board of the University of New Mexico (UNM), reference 18115. Informed consent was obtained from the parents of five children that were deemed to be positive for S. mansoni from fecal samples using egg microscopy, of which remaining samples were used for S. mansoni miracidial hatching. All five children were treated with praziquantel during a follow-up visit by a KEMRI physician. Data, Materials, and Software Availability All sequence data, including PacBio HiFi raw reads from genome sequence data of B. sudanica Bs2280, has been uploaded onto the NCBI SRA under BioProject PRJNA1149315 with BioSample accessions SAMN43241892, SAMN43241893, SAMN43241894, SAMN43241895, SAMN45084274. The genome assembly of Bs2280 is available on figshare, DOI: 10.6084/m9.figshare.27985880. Acknowledgments This work was funded by National Institute of Health, National Institute of Allergy and Infectious Disease grants R01AI141862 and R37AI101438. Author Contributions: J.A.T., E.S.L., M.R.O. and M.L.S. designed research; T.P., J.M.S., T.M., G.O., F.R., K.A., B.M., M.R.O., M.W.M., G.M.M. and M.L.S. performed research; T.P. and J.A.T. analyzed data; T.P., J.A.T. and M.L.S. wrote the paper. 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\u003c/em\u003egenome. Fisher’s exact test \u003cem\u003ep \u003c/em\u003evalues for all pooled-GWAS variants, are arranged horizontally based on contig orthology to 18 chromosomes (x-axis labels) of the \u003cem\u003eB. glabrata\u003c/em\u003e genome (xgBioGlab47.1, NCBI RefSeq: GCF_947242115.1) and linkage map analysis (Dataset S2, Fig. S2-S4). Pooled-GWAS dual-variants, defined as two or more proximate (\u0026lt;50 kb and \u0026gt;1.5 kb apart) variants strongly associated with \u003cem\u003eS. mansoni \u003c/em\u003eresistance (\u003cem\u003ep\u003c/em\u003e ≤ 2.5e-9) are red. All others are blue. All dual-variants and singleton-variants with p ≤ 1e-17 are labeled red and blue, respectively, with their contig and contig position. Unassigned contigs could not be unambiguously mapped and are mostly small and/or repetitive.\u003c/p\u003e","description":"","filename":"Picture1.png","url":"https://assets-eu.researchsquare.com/files/rs-5656395/v1/7c3bca2826e45d43a1028509.png"},{"id":72870264,"identity":"6d9c37ce-128a-456d-8e87-047b813595d1","added_by":"auto","created_at":"2025-01-03 06:54:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":89641,"visible":true,"origin":"","legend":"\u003cp\u003eAmplicon panel validation of pooled-GWAS results. (A) Proportion of ancestry from \u003cem\u003eBiomphalaria sudanica \u003c/em\u003ePopulation 1 (red) or Population 2 (blue) as predicted by ADMIXTURE (31) is correlated with \u003cem\u003eSchistosoma mansoni \u003c/em\u003einfection (\u003cem\u003ep \u003c/em\u003e\u0026lt; 1e-14), such that majority-Population 1 snails (Group A) are 68% positive while the majority-Population 2 snails (Group B) are 41% positive. Total number of samples included in analysis was 503 including 496 genotyped-validation and genotyped-pooled-GWAS \u003cem\u003eB. sudanica \u003c/em\u003efrom this study, 5 inbred \u003cem\u003eB. sudanica \u003c/em\u003epreviously sequenced\u003cem\u003e \u003c/em\u003e(27)\u003cem\u003e \u003c/em\u003eand 2 outbred \u003cem\u003eB. choanomphala\u003c/em\u003e.\u003cem\u003e \u003c/em\u003e(B) Ordered Fisher’s exact test \u003cem\u003ep \u003c/em\u003evalues per variant of genotyped-validation samples within ancestry groups. \u003cem\u003eSudRes1\u003c/em\u003evariants c6:3,490, c6:31,057, and c6844:72,816 are significant validated-variants (\u003cem\u003ep \u003c/em\u003e\u0026lt; 1.3e-04, Bonferroni adjusted significance threshold shown by dotted line) within ancestry Group B (blue dots) and most other top-outliers (1.3e-04\u0026lt; \u003cem\u003ep \u003c/em\u003e\u0026lt; 1.0e-03) are in \u003cem\u003eSudRes1\u003c/em\u003e or \u003cem\u003eSudRes2\u003c/em\u003e. (C) Ordered additive regression \u003cem\u003ep \u003c/em\u003evalues per variant of genotyped-validation samples, after accounting for ancestry. \u003cem\u003eSudRes2\u003c/em\u003evariant sc94:2,166,296 is a significant validated-variant (\u003cem\u003ep \u003c/em\u003e\u0026lt; 2.3e-04, Bonferroni adjusted significance threshold shown by dotted line) and most other top-outliers (1.3e-04\u0026lt; \u003cem\u003ep \u003c/em\u003e\u0026lt; 1.0e-03) are in \u003cem\u003eSudRes1\u003c/em\u003eor \u003cem\u003eSudRes2\u003c/em\u003e. (D) Allele and genotype counts for the most significant validated-variants from \u003cem\u003eSudRes1\u003c/em\u003e (c6:3,490) and \u003cem\u003eSudRes2 \u003c/em\u003e(sc94:2,166,296), which were both dominant markers, and the representative codominant marker variants from \u003cem\u003eSudRes1\u003c/em\u003e (c582:65,596) and \u003cem\u003eSudRes2\u003c/em\u003e (sc94:2,174,117), for \u003cem\u003eS. mansoni \u003c/em\u003einfection positive (+) and negative (-) snails. Values are read counts for each allele in the pooled-GWAS (“GWAS”), and genotype counts in genotyped-validation snails (“Validation”). (E) Means and standard errors for each variable in the best-fitting multiple regression model. Ancestry is the proportion of Population 2 ancestry, and loci \u003cem\u003eSudRes1\u003c/em\u003e and \u003cem\u003eSudRes2\u003c/em\u003eare additive effects per each copy of the minor allele at the representative codominant markers c582:65,596 and sc94:2,174,117. ***\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Picture2.png","url":"https://assets-eu.researchsquare.com/files/rs-5656395/v1/b9e3902b77a30895be8ec857.png"},{"id":72870249,"identity":"833d5737-39df-4f66-a4fd-60646e2e1a2a","added_by":"auto","created_at":"2025-01-03 06:54:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":55877,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterization of \u003cem\u003eBiomphalaria sudanica\u003c/em\u003e \u003cem\u003eSudRes1 \u003c/em\u003egenomic region. (A) Pooled-GWAS \u003cem\u003ep \u003c/em\u003evalues in \u003cem\u003eSudRes1 \u003c/em\u003eregions (dashed boxes), which contain pooled-GWAS dual-variants (red) and other variants (blue), defined as in Figure 1. Contigs (grey rectangles) on \u003cem\u003eB. sudanica \u003c/em\u003echromosome 5 arranged horizontally based on contig orthology to 18 chromosomes of the \u003cem\u003eB. glabrata\u003c/em\u003e genome (xgBioGlab47.1, NCBI RefSeq: GCF_947242115.1) and linkage map analysis (Dataset S2, Fig. S2-S4). Gene positions are shown (yellow/brown/green/orange boxes), highlighting particularly prevalent classes of genes: in \u003cem\u003eSudRes1\u003c/em\u003e the multiple epidermal growth factor (MEGF) and galactose-binding like domain (GBD) containing receptor-like tyrosine-specific protein phosphatase (RPTP), other protein coding genes containing MEGF domains. (B) The predicted protein structure of receptor-like tyrosine-specific protein phosphatase (RPTP) coding gene BSUD.17727 (c6844) present in the \u003cem\u003eSudRes1 \u003c/em\u003eregion of the \u003cem\u003eB. sudanica \u003c/em\u003egenome and containing intronic validated-variants (Fig. S8A). A similar RPTP coding gene is contained within adjacent contigs c582 and c5209 within \u003cem\u003eSudRes1\u003c/em\u003e, and contig c1041 neighboring \u003cem\u003eSudRes1 \u003c/em\u003eregion (Fig. 3A). (C) Nucleotide alignment of paralogous contigs representing a portion of the \u003cem\u003eSudRes1 \u003c/em\u003eregion in both Bs111 and Bs2280 genomes, showing location of genes and coding regions relative to GWAS variants used in the amplicon panel. Four G/T polymorphisms are shown, two of which act as non-Mendelian dominant markers due to paralogous amplification, one of which shows two alleles with Mendelian segregation (c582:65,596), and one of which segregates in our population but is invariant in these sequenced genomes (c5209:45,695). Exons are colored by protein domain, and mean pairwise sequence identity is shown at the top (in 100 sliding windows across aligned contigs; green = 100% identity, brown = 30% to \u0026lt;100%, red = \u0026lt; 30%). (D) Amino acid alignment of RPTP genes in \u003cem\u003eSudRes1\u003c/em\u003e, demonstrating extracellular diversity and loss of functional EGF domains in Bs2280 contig c32471. Protein domains are indicated by color, and non-synonymous polymorphisms in comparison to the majority consensus of paralogs/orthologs are shown in black. Sequence identity is shown as in C, for 25 aa sligning windows in aligned proteins.\u003c/p\u003e","description":"","filename":"Picture3.png","url":"https://assets-eu.researchsquare.com/files/rs-5656395/v1/a9d73640fdb172752abe1a49.png"},{"id":72870585,"identity":"6f1f5fd4-1824-416d-ac5e-bd9f08a7cb69","added_by":"auto","created_at":"2025-01-03 07:02:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":139695,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterization of \u003cem\u003eBiomphalaria sudanica\u003c/em\u003e \u003cem\u003eSudRes2 \u003c/em\u003egenomic region. (A) Pooled-GWAS \u003cem\u003ep \u003c/em\u003evalues in \u003cem\u003eSudRes2 \u003c/em\u003eregions (dashed boxes), which contain pooled-GWAS dual-variants (red) and other variants (blue), defined as in Figure 1. Contigs (grey rectangles) on \u003cem\u003eB. sudanica \u003c/em\u003echromosome 6 are arranged horizontally based on contig orthology to 18 chromosomes of the \u003cem\u003eB. glabrata\u003c/em\u003e genome (xgBioGlab47.1, NCBI RefSeq: GCF_947242115.1) and linkage map analysis (Dataset S2, Fig. S2-S4). Gene positions are shown (yellow/red/orange boxes), highlighting particularly prevalent classes of genes in \u003cem\u003eSudRes2\u003c/em\u003e encoding a class of leucine-rich repeat containing G-protein couple receptors (GRL101) with C-type lectin and low-density lipoprotein extracellular domains (partial GRL101 genes included), and a Zinc-RING finger and inhibitor of apoptosis containing protein. (B) A representative predicted protein structure of a GRL101-like G-protein coupled receptor coding gene, twelve of which were predicted through manual annotation within the \u003cem\u003eSudRes2 \u003c/em\u003eregion of contig sc94 (1.82-2.26 Mb) in the \u003cem\u003eB. sudanica \u003c/em\u003egenome. (C) Dot plot constructed using D-GENIES (69) comparing synteny of the \u003cem\u003eSudRes2 \u003c/em\u003eregion in \u003cem\u003eBiomphalaria sudanica \u003c/em\u003eBs111 genome (27) and the Bs2280 resistant snail genome, highlighting regions of divergence and structural rearrangements between the two genomes. GRL101 genes are indicated along with Zn-RING-IAP gene \u003cem\u003eBSUD.25704\u003c/em\u003eand its paralog.\u003c/p\u003e","description":"","filename":"Picture4.png","url":"https://assets-eu.researchsquare.com/files/rs-5656395/v1/b3d74b1f64c18aea6a29e39d.png"},{"id":87656603,"identity":"cbac3b76-2d2f-4ce6-a138-f11c1f444db6","added_by":"auto","created_at":"2025-07-27 07:07:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1271492,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5656395/v1/7223bdfa-e6f2-4f82-8fa0-b1020eb257f9.pdf"},{"id":72870251,"identity":"e1451433-36b1-4816-bf37-7404aac45fae","added_by":"auto","created_at":"2025-01-03 06:54:05","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10056266,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"NatureCommBsudGWASSI.docx","url":"https://assets-eu.researchsquare.com/files/rs-5656395/v1/287d6d93b4b83a6c4843d685.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Immune targets for schistosomiasis control identified by a genome-wide association study of African snail vectors","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSchistosomiasis is a global scourge, taking a large toll on people who have the fewest resources. Affecting over 260\u0026nbsp;million people, it is the parasitic disease with the greatest impact on health worldwide after malaria (1, 2). Within the last decade, schistosomiasis control program goals have shifted from reduction of morbidity to elimination or interruption of schistosomiasis as a public health problem by 2030 (1, 3, 4). However, the toolbox with which to combat schistosome transmission has remained virtually the same, dominated by one main approach: mass drug administration (MDA) of praziquantel (5). It is increasingly recognized that in addition to chemotherapy, successful control and elimination will require targeting the aquatic snails which serve as intermediate hosts of the schistosome parasites and transmit them to humans (6, 7). Part of the reason MDA alone is insufficient is that even with effective drug treatment, people become rapidly reinfected by infected snails in the environment (8–10). Schistosomes form chronic infections in snails and continually release hundreds to thousands of infectious stages (cercariae) into the environment daily (11).\u003c/p\u003e\u003cp\u003eHistorically, schistosomiasis control programs that are focused on snail control have been the most successful at reducing or eliminating schistosomiasis (12, 13); however, snail-directed control methods are limited and have negative impacts. Molluscicides are indiscriminately toxic and are impractical to apply to vast habitats (12, 14). Furthermore, snail population rebound post-molluscicide application is predicted to increase schistosome transmission (15).\u003c/p\u003e\u003cp\u003eGiven the absence of suitable snail vector control methods for contemporary public health interventions, there is a need for new approaches to be developed (16). Genomic and transcriptomic data and resources enable approaches like genome-wide association studies (GWAS) that identify genomic regions of snail vectors involved in resisting schistosome infection (17). Once identified, snail genes and genomic variants associated with resistance to schistosomes could be monitored in wild populations and potentially be manipulated so that snail resistance to schistosomes is enhanced and transmission to humans is interrupted.\u003c/p\u003e\u003cp\u003eThe feasibility of manipulating snail resistance to schistosomes may follow similar approaches to engineering resistant hosts for disease control using CRISPR-Cas and associated gene drive technologies (18, 19). However, much of the elegant work regarding transcriptomics and genomics of schistosome-snail compatibility has only addressed these questions in laboratory models of the South American vector of \u003cem\u003eSchistosoma mansoni\u003c/em\u003e, \u003cem\u003eBiomphalaria glabrata\u003c/em\u003e (17, 20–24). Very little is known regarding how this body of knowledge will translate to African vectors of \u003cem\u003eS. mansoni\u003c/em\u003e, through which 90% of \u003cem\u003eS. mansoni\u003c/em\u003e transmission occurs (25). The recent publication of two African \u003cem\u003eBiomphalaria\u003c/em\u003e species genomes and transcriptomes (26, 27) provide a path toward molecular-informed snail control in hotspots of transmission.\u003c/p\u003e\u003cp\u003eWith the goal of identifying and describing the genetic architecture underlying resistance of African snails to \u003cem\u003eS. mansoni\u003c/em\u003e, we performed a pooled genome-wide association study (pooled-GWAS) (28) using a wild population of \u003cem\u003eBiomphalaria sudanica\u003c/em\u003e originating from the shores of Lake Victoria closest to a persistent hotspot of schistosomiasis in Kanyibok, western Kenya (10). We identify two large-effect loci and a strong influence of ancestry on snail resistance to schistosome infection, defined here as complete parasite clearance (including parasite DNA) from snail tissue following exposure. These results reveal how immunogenetics and population demographics contribute to vectorial competence in a natural vector population with direct impact on human health.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003ePooled-GWAS reveals multiple variants strongly enriched in resistant snails.\u003c/b\u003e Of 1400 F1 \u003cem\u003eB. sudanica\u003c/em\u003e, whose parents originated from Anyanga Beach (Lake Victoria, western Kenya), exposed to eight freshly hatched \u003cem\u003eS. mansoni\u003c/em\u003e miracidia from local schoolchildren, 1,109 snails remained in the GWAS study after excluding 254 that died prior to screening for infection and 37 that yielded insufficient genomic DNA (gDNA) quality. The final sample set comprised 615 and 393 snails that were positive (i.e. releasing \u003cem\u003eS. mansoni\u003c/em\u003e cercariae) or negative (i.e. not releasing \u003cem\u003eS. mansoni\u003c/em\u003e cercariae nor PCR positive (29)), respectively. Snails that were negative for cercariae but positive for \u003cem\u003eS. mansoni\u003c/em\u003e gDNA were not considered further. Two equal mass gDNA pools for the pooled-GWAS comprised 493 positive and 295 negative snails. The pooled-GWAS sequencing (Illumina paired-end 150 bp, NovaSeq 6000 S4 flow cell) yielded on average 1.5x coverage per snail (Dataset S1). A total of 4,498,972 variants were retained for analysis. Correlation between sequencing technical replicates of positive and negative pooled gDNA was weak but significantly positive, with 8-fold enrichment for outliers in the top 1% of both replicates (Fig. S1).\u003c/p\u003e\u003cp\u003eIn the pooled-GWAS results, genotype-phenotype association \u003cem\u003ep\u003c/em\u003e values ranged as low as 1e-30, including 45 variants (0.001%) with \u003cem\u003ep\u003c/em\u003e ≤ 1e-15 and 1,930 variants (0.04%) with \u003cem\u003ep\u003c/em\u003e ≤ 2.5e-9 (Fig.\u0026nbsp;1). Rather than simply defining a genome-wide significance threshold to identify candidates to be validated, we prioritized genomic regions meeting a dual-variant criterion, whereby two or more proximate (\u0026lt; 50 kb and \u0026gt; 1.5 kb apart to ensure support from distinct read pairs) variants are strongly associated with \u003cem\u003eS. mansoni\u003c/em\u003e resistance (arbitrary threshold of \u003cem\u003ep\u003c/em\u003e ≤ 2.5e-9); such sliding dual-variant 50 kb windows encompass 18.625 Mb (2%) of the \u003cem\u003eB. sudanica\u003c/em\u003e reference genome Bs111 (27) and contain 888 (46%) of variants with \u003cem\u003ep\u003c/em\u003e ≤ 2.5e-9.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAmplicon panel genotyping reveals population structure and validates variants associated with resistance.\u003c/b\u003e A multiplex amplicon panel was designed using the Genotyping-in-Thousands by sequencing method (30) to genotype variants in individual snails at 234 dual-variants and 12 singleton-variants with \u003cem\u003ep\u003c/em\u003e \u0026lt; 1e-13 identified from the pooled-GWAS analysis (Dataset S3). The amplicon panel also contained 22 markers for \u003cem\u003ea priori\u003c/em\u003e gene candidates and 201 ‘neutral’ markers to facilitate a linkage map for improved \u003cem\u003eB. sudanica\u003c/em\u003e genome assembly (Dataset S2).\u003c/p\u003e\u003cp\u003eAn independent set of 122 positive and 98 negative snails not included in the pooled-GWAS were reserved for validation of genomic variants via genotyping with the amplicon panel and are henceforth referred to as genotyped-validation snails. These independent genotyped-validation snails were used to validate the differential allele frequencies associated with \u003cem\u003eS. mansoni\u003c/em\u003e resistance observed in the pooled-GWAS sequencing data. These were combined with a subset of the pooled-GWAS snails (genotyped-pooled-GWAS snails: 138 positive, 138 negative) for more precise estimates of ancestry and genotype frequencies.\u003c/p\u003e\u003cp\u003eThe amplicon panel data (of which median missing data was 2% per locus and 2% per individual) revealed a signal of population structure, evident in both PCA (Fig. S5) and ADMIXTURE (31) analysis (Fig.\u0026nbsp;2A). With K = 2 ancestral populations (CV = 0.53, versus 0.61 for K = 1), ancestry from Population 2 ranged continuously from 0 to 1 and was significantly correlated with resistance (\u003cem\u003ep\u003c/em\u003e \u0026lt; 1e-14). Mean Population 2 ancestry was 39% for positives and 62% for negatives. Snails were designated into two groups based on the percentage of their ancestry: 41% of snails had mostly Population 1 ancestry and were deemed “Group A”, while the remainder, with mostly Population 2 ancestry, were deemed “Group B”. Of the snails in Group A, 68% were positive. In Group B, 41% were positive. Thus, any marker differing in frequency between these ancestral populations could be correlated with infection phenotype, even if not linked to an etiological variant, and therefore could explain some outliers identified by the pooled-GWAS. Using markers diagnostic of both groups A and B, we found that \u003cem\u003eB. choanomphala\u003c/em\u003e, a closely related deep-water taxon/eco-phenotype of \u003cem\u003eB. sudanica\u003c/em\u003e also collected in Lake Victoria (32), and \u003cem\u003eB. sudanica\u003c/em\u003e inbred lines originating from Lake Victoria (27), share ancestry with Group A, and thus the GWAS ancestry signal is not caused by interspecies hybridization (Fig. S6). The inferred percentage of Population 1 or 2 ancestry for each snail was similar when estimated using linkage map markers alone, and thus not driven by GWAS outliers (Fig. S7).\u003c/p\u003e\u003cp\u003eAfter accounting for ancestry, only variants within two genomic regions, henceforth referred to as \u003cem\u003eSudRes1\u003c/em\u003e and \u003cem\u003eSudRes2\u003c/em\u003e, showed significance (Bonferroni-corrected \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, designated henceforth as 'validated-variants’) in a dominance (Fig.\u0026nbsp;2B) or an additive regression (Fig.\u0026nbsp;2C) model (Dataset S3). Notably, the p-values of the variants in \u003cem\u003eSudRes1\u003c/em\u003e and \u003cem\u003eSudRes2\u003c/em\u003e were amongst the lowest of the dual-variant outliers identified by the pooled-GWAS (Fig.\u0026nbsp;1). The three validated-variants for \u003cem\u003eSudRes1\u003c/em\u003e (Fig.\u0026nbsp;2B) and validated-variant for \u003cem\u003eSudRes2\u003c/em\u003e (Fig.\u0026nbsp;2C) acted as dominant markers (only two genotypes observed), so to assess genotype-phenotype associations in more depth we examined codominant proxy variants and used these as representative variants for each region (Fig.\u0026nbsp;2D). For the \u003cem\u003eSudRes1\u003c/em\u003e representative variant (c582:65,596, Fig.\u0026nbsp;2D), allele T was protective in the pooled-GWAS and in the genotyped-validation snails. Combining data from the genotyped-validation and genotyped-pooled-GWAS snails, odds of \u003cem\u003eB. sudanica\u003c/em\u003e infection with \u003cem\u003eS. mansoni\u003c/em\u003e were 0.31 for genotype TT, 0.57 for genotype GT, and 1.37 for genotype GG, consistent with an additive effect. For the \u003cem\u003eSudRes2\u003c/em\u003e representative variant (sc94:2,174,117, Fig.\u0026nbsp;2D), allele A was protective in the pooled-GWAS and in the genotyped-validation snails. Combining data from the genotyped-validation and genotyped-pooled-GWAS snails, odds of \u003cem\u003eS. mansoni\u003c/em\u003e infection in \u003cem\u003eB. sudanica\u003c/em\u003e were 0.36 for genotype AA, 0.74 for genotype TA, and 2.40 for genotype TT, also consistent with an additive effect.\u003c/p\u003e\u003cp\u003eThe best-fitting multiple regression model (AIC = 451.11 and \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 for all variables) included: ancestry; \u003cem\u003eSudRes1\u003c/em\u003e (representative variant c582:65,596, Fig.\u0026nbsp;2D); and \u003cem\u003eSudRes2\u003c/em\u003e (representative variant sc94:2,174,117, Fig.\u0026nbsp;2D), with both genetic markers acting additively (Fig.\u0026nbsp;2E). The model predicts a ~ 2-fold effect per allele at each genetic marker, and a ~ 4-fold effect of ancestry. Thus, the predicted odds of infection for a snail with no Population 2 ancestry and major allele homozygous genotypes at \u003cem\u003eSudRes1\u003c/em\u003e and \u003cem\u003eSudRes2\u003c/em\u003e (4.46) is 62-fold higher (approximately 2\u003csup\u003e2\u003c/sup\u003e*2\u003csup\u003e2\u003c/sup\u003e*4) than the odds for a snail with 100% Population 2 ancestry and minor allele homozygous genotypes at both loci (0.07).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSudRes1 is rich in paralogous genes encoding MEGF domains.\u003c/b\u003e \u003cem\u003eSudRes1\u003c/em\u003e comprises 1.07 Mb of Bs111 and contains 23 protein coding genes across five contigs (c6844, c582, c5209, c6, c2) that are closely linked on chromosome 5 (Fig.\u0026nbsp;3A, Fig. S2 and Fig. S3). Notably, 10 of these 23 genes encode multiple epidermal growth factor (MEGF) domains (Fig.\u0026nbsp;3A, Dataset S4). Three of these MEGF proteins in c6844, c5209, and c582, display a common single pass transmembrane domain (TMD) structure, with intracellular tyrosine-specific protein phosphatase (PTP) domains and extracellular MEGF and a galactose binding domain (GBD), forming a receptor-like PTP (RPTP) protein (Fig.\u0026nbsp;3B). Each of these three RPTP genes within the \u003cem\u003eSudRes1\u003c/em\u003e region are adjacent to Antistasin-like protein coding genes (Fig.\u0026nbsp;3C). Only 14 other MEGF/GBD-containing RPTP genes are annotated in Bs111, 13 of which are clustered near \u003cem\u003eSudRes1\u003c/em\u003e on chromosome 5 (Fig.\u0026nbsp;3A, Dataset S4).\u003c/p\u003e\u003cp\u003eOf the three validated-variants in \u003cem\u003eSudRes1\u003c/em\u003e (Fig.\u0026nbsp;2B), one was contained within the intron of an MEGF/GBD-containing RPTP protein in contig c6844 (Fig.\u0026nbsp;3C, Fig. S8A), whilst the other two were in the intergenic region either side of another MEGF/GBD-containing protein (contig c6 ortholog 1, Dataset S4). Similarly, the two ‘top-outlier’ variants (defined as variants with 1.3e-04 \u0026lt; \u003cem\u003ep\u003c/em\u003e \u0026lt; 1.0e-03 following validation, see Fig.\u0026nbsp;2B) in adjacent contigs c582 and c2 in \u003cem\u003eSudRes1\u003c/em\u003e were contained within the intronic gene sequence of an MEGF/GBD-containing RPTP protein (c582_65696, Fig.\u0026nbsp;3C; BSUD.15164, Dataset S4) and another MEGF/GBD-containing protein (c2 ortholog 2, Dataset S4).\u003c/p\u003e\u003cp\u003eThree of the five contigs in the \u003cem\u003eSudRes1\u003c/em\u003e region, c6844, c5209 and c582, are homologous with each other and match the same unduplicated orthologous region on \u003cem\u003eB. glabrata\u003c/em\u003e chromosome 5 and \u003cem\u003eB. pfeifferi\u003c/em\u003e LG5 (Fig. S9 and S10). Aligned read coverage was also atypically low across all \u003cem\u003eSudRes1\u003c/em\u003e contigs compared to the rest of the genome (Fig. S11).\u003c/p\u003e\u003cp\u003eWe compared the Bs111 reference genome, harboring the susceptible \u003cem\u003eSudRes1\u003c/em\u003e haplotype, to a PacBio genome assembled from a snail homozygous for a resistant \u003cem\u003eSudRes1\u003c/em\u003e haplotype (Bs2280, coverage of ~ 13x, N50 of ~ 87 kb). While \u003cem\u003eSudRes1\u003c/em\u003e is not fully assembled in either genome, we can detect substantial structural rearrangements resulting in different numbers of genes for some clusters of homologous loci (Dataset S4, Fig.\u0026nbsp;3C). Consistent with extensive sequence duplication, Bs2280 includes multiple copies of some amplicon sites (Dataset S6), explaining why these failed to show Mendelian segregation and instead acted as dominant markers. One particularly variable segment, occurring in several divergent copies in both genomes, contains the adjacent antistasin and RPTP genes (Fig.\u0026nbsp;3C). Among putative orthologs, there are many nonsynonymous differences including occasional differences in protein length resulting in loss of functional domains, especially in RPTPs (Fig.\u0026nbsp;3D). Notably, this includes EGF domain loss in the resistant snail Bs2280 (Fig.\u0026nbsp;3D), suggesting that the snails mechanism of \u003cem\u003eS. mansoni\u003c/em\u003e resistance could involve the loss of function of a protein critical for parasite invasion.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSudRes2 is characterized by a large family of GRL101-like GPCR genes.\u003c/b\u003e \u003cem\u003eSudRes2\u003c/em\u003e comprises a 440 kb region between 1.82 and 2.26 Mb on contig sc94 of Bs111 chromosome 6 (Fig.\u0026nbsp;4A, Fig. S2 and Fig. S4). Following manual annotation of \u003cem\u003eSudRes2\u003c/em\u003e, 14 protein coding genes were identified (Fig. S12 and Dataset S5). Ten of these encode mutually paralogous GRL101-like proteins, defined as G-protein coupled receptor (GPCR) transmembrane proteins with extracellular regions containing a leucine rich repeat (LRR) region, a low-density lipoprotein receptor class A repeat (LDL) and a C-type lectin-like (CTL) domain (Fig.\u0026nbsp;4B); an additional two GRL101-like genes in \u003cem\u003eSudRes2\u003c/em\u003e are missing the CTL or LDL domain and may represent incomplete proteins (Dataset S5). Of the 437 GPCR genes in Bs111 (27), only six genes outside of \u003cem\u003eSudRes2\u003c/em\u003e are annotated as possessing GRL101, CTL, and LDL domains (Dataset S5).\u003c/p\u003e\u003cp\u003eBs2280, the resistant snail genome, was also homozygous for a resistant \u003cem\u003eSudRes2\u003c/em\u003e haplotype, facilitating comparison with the susceptible Bs111 haplotype. In both genomes, assembly of this region is nearly complete, and reveals several genes that are present in only one genome, or are duplicated in one haplotype (Fig.\u0026nbsp;4C). Similarly, some orthologs differed in length between genomes, being truncated in one or the other.\u003c/p\u003e\u003cp\u003eBoth the validated-variant and top-outlier variant in Bs111 \u003cem\u003eSudRes2\u003c/em\u003e are contained in the non-coding regions of non-GRL101 gene, \u003cem\u003eBSUD.25704\u003c/em\u003e, clustered within the GRL101 genes, which when complete encodes a protein with a zinc finger RING-type (Zn-RING) domain and inhibitor of apoptosis (IAP) repeat region (i.e. Zn-RING-IAP) (Fig.\u0026nbsp;4C, Fig. S8B). In the reference/susceptible \u003cem\u003eSudRes2\u003c/em\u003e haplotype, a nonsense variant (Bs111 sc94:2,167,458) in \u003cem\u003eBSUD.25704\u003c/em\u003e truncates the protein at 323 aa, however in the resistant Bs2280 ortholog, a 391 aa protein can be translated. Furthermore, in Bs2280 a paralogous Zn-RING coding gene (truncated and not including IAP) is present within a divergent portion of the orthologous \u003cem\u003eSudRes2\u003c/em\u003e region (Fig.\u0026nbsp;4C). Amplification of both \u003cem\u003eBSUD.25704\u003c/em\u003e and its paralog in resistant haplotypes is likely responsible for the non-Mendelian behavior of the validated marker (sc94:2,166,296) which appears as heterozygous in resistant snails (Fig.\u0026nbsp;4C; Dataset S6). On the boundary of \u003cem\u003eSudRes2\u003c/em\u003e is a baculoviral IAP repeat containing (BIRC) protein coding gene \u003cem\u003eBSUD.25705\u003c/em\u003e (Fig.\u0026nbsp;4C), many of which are contained in the genome regions neighboring \u003cem\u003eSudRes2\u003c/em\u003e.\u003c/p\u003e\u003cp\u003ePrior to the manual annotation of the 14 genes contained with the Bs111 genome, the \u003cem\u003eSudRes2\u003c/em\u003e region was exceptional in that: 1) only four protein coding genes in 440 kb had been annotated in this region of the reference \u003cem\u003eB. sudanica\u003c/em\u003e genome, much lower than the genome-wide density of one gene per 40 kb; 2) a low density of variants were present (Fig.\u0026nbsp;3A and Fig. S12), and; 3) a large drop in aligned pooled-GWAS read coverage across the central 240 kb of \u003cem\u003eSudRes2\u003c/em\u003e was apparent (Fig. S13 and S14). To confirm the presence and validity of the manually annotated GRL101 genes, \u003cem\u003eB. sudanica\u003c/em\u003e RNA transcript data was successfully aligned to 11 of the 12 predicted GRL101 CDS sequences in the \u003cem\u003eSudRes2\u003c/em\u003e region (all except GRL101_3). Phylogenetic analysis of protein coding sequences also revealed that the \u003cem\u003eB. sudanica\u003c/em\u003e syntenic (conserved gene order) orthologs identified in \u003cem\u003eB. glabrata\u003c/em\u003e and \u003cem\u003eB. pfeifferi\u003c/em\u003e (Dataset S5) were also the most closely related (Fig. S15).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cb\u003eIdentification of loci associated with schistosome resistance in a wild snail vector population.\u003c/b\u003e In this study, we identified and validated two previously uncharacterized genomic regions, \u003cem\u003eSudRes1\u003c/em\u003e and \u003cem\u003eSudRes2\u003c/em\u003e, in the African snail vector \u003cem\u003eB. sudanica\u003c/em\u003e that are associated with resistance to \u003cem\u003eS. mansoni\u003c/em\u003e infection, each contributing a similar effect size of a ~ 2-fold change in \u003cem\u003eS. mansoni\u003c/em\u003e infection odds ratio per allele. Both regions contain long segments with unusually low pooled-GWAS read coverage and contain few annotated genes in the reference genomes of \u003cem\u003eBiomphalaria\u003c/em\u003e sp., suggesting possible structural variation or allelic divergence that preclude unambiguous alignment of reads and complicates assembly and annotation of these regions. It is crucial therefore to acknowledge that the validated-variants associated with schistosome resistance may not themselves be causal polymorphisms, instead they highlight that something significant is occurring in these regions that may remain elusive using the current \u003cem\u003eB. sudanica\u003c/em\u003e genome assemblies (27), potentially due to structure rearrangements or unaligned alleles. Manual annotation of both \u003cem\u003eSudRes\u003c/em\u003e regions revealed that they are enriched with transmembrane protein coding genes with diverse extracellular regions composing of protein-protein interacting and carbohydrate binding domains, relevant to immune-related functions such as pathogen recognition (33, 34).\u003c/p\u003e\u003cp\u003e\u003cem\u003eSudRes1\u003c/em\u003e is characterized by MEGF-domain containing genes, including receptor-like protein-tyrosine phosphatases (RPTPs), comprising extracellular MEGF, extracellular GBD, and intracellular tandem PTP domains. These potentially heavily glycosylated RPTPs may form stable dimers on the cell surface (35), with ligand binding triggering confirmational changes that expose or occlude catalytically active regions of the intracellular membrane-proximal PTPs, transducing signals across the cell membrane (36, 37). The presence of schistosome resistance-associated variants surrounding the \u003cem\u003eB. sudanica\u003c/em\u003e RPTPs suggests that increased efficacy or upregulation of these proteins may counteract \u003cem\u003eS. mansoni\u003c/em\u003e-induced phosphorylation, one of the parasite’s strategies to manipulate or evade the snail immune system and promote its survival (38). Neighboring each RPTP in the \u003cem\u003eSudRes1\u003c/em\u003e region were antistasin genes, a type of serine protease inhibitors that were originally described as anticoagulants in blood feeding species and since been attributed to immune responses in marine gastropods (39). While \u003cem\u003eSudRes1\u003c/em\u003e is not fully assembled in either Bs111 and Bs2280 genome, it appears likely that homologous contigs within each genome represent paralogous segments rather than alleles, since similar gene counts were observed in both genomes, suggesting recent gene duplications after \u003cem\u003eB. sudanica\u003c/em\u003e diverged from \u003cem\u003eB. glabrata\u003c/em\u003e and \u003cem\u003eB. pfeifferi\u003c/em\u003e. The \u003cem\u003eSudRes1\u003c/em\u003e region was previously noted as showing exceptionally high nucleotide diversity in \u003cem\u003eB. sudanica\u003c/em\u003e (27), which when coupled with the pooled-GWAS results suggest that pathogen-mediated balancing selection may act on these genes as previously hypothesized. Our findings here support the approach of using genome hyperdiversity as a proxy for identifying immune related genes in uncharacterized genomes (27).\u003c/p\u003e\u003cp\u003e\u003cem\u003eSudRes2\u003c/em\u003e contains resistance-associated variants within a Zn-RING-IAP gene, which neighbors a cluster of 12 leucine rich repeat-containing G protein-coupled receptor (LGR) family genes where pooled-GWAS variants are distributed throughout. The structure of the \u003cem\u003eSudRes2\u003c/em\u003e LGR proteins is similar to GRL101, a LGR first described in the gastropod species \u003cem\u003eLymnaea stagnalis\u003c/em\u003e notable for its N-terminal extracellular LRRs and LDLs (UniProt accession P46023 (40)). Unique to the \u003cem\u003eB. sudanica\u003c/em\u003e GRL101 genes characterized in \u003cem\u003eSudRes2\u003c/em\u003e, however, is the N-terminal C-type lectin (CTL) fold/domain. CTL domain containing proteins are established components of both vertebrate and invertebrate innate immune systems as recognition and effector molecules, which show pathogen dependent expression patterns (41–43). Due to the architecture of the \u003cem\u003eSudRes2\u003c/em\u003e GRL101 proteins, the CTL domain likely extends away from the cell membrane exposing the CTL binding region to cytoplasmic ligands (such as those derived from invading pathogens) that could then be presented to the GPCR membrane-spanning binding pocket, triggering G-protein activation. Homology and phylogenetic placement of the syntenic GRL101 proteins indicates a shared ancestry, and possible functional conservation, in GRL101 genes retained since the split of \u003cem\u003eB. glabrata\u003c/em\u003e and African \u003cem\u003eBiomphalaria\u003c/em\u003e species ~ 5 Mya (26, 44), although the incomplete assembly of available \u003cem\u003eBiomphalaria\u003c/em\u003e genomes in this hyperdiverse region may impede inferences of expansion and contraction. To our knowledge, GRL101-like proteins have not been affiliated with immunity in gastropods, but have been shown to play an important role in innate immunity of other invertebrates (45, 46). Although GRL101-like genes were present elsewhere in the \u003cem\u003eB. sudanica\u003c/em\u003e genome, the dense cluster of GRL101 genes in the \u003cem\u003eSudRes2\u003c/em\u003e region is unique in that in Bs111 it is the only region \u0026lt; 0.5 Mb with 12 GRL101 genes, with the caveat that GRL101 genes elsewhere in the \u003cem\u003eB. sudanica\u003c/em\u003e reference genome may also not be annotated correctly.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEvidence of a shifting snail population structure in Lake Victoria could lead to increased infections.\u003c/b\u003e A surprising result was the discovery of ancestry heterogeneity in our GWAS snails, whose parents had all been collected at the same time and place. More remarkable still, this ancestry signal is strongly correlated with schistosome resistance. Thus, many outliers in our pooled-GWAS could represent ancestry-informative markers with no physical linkage to resistance genes. Population ancestry estimates using only neutral linkage map markers were very similar to those using the full panel including GWAS outliers, supporting that the ancestry effect observed is real and not an artifact of using atypical variants implicated by the GWAS. Considering the importance of snail ancestry in schistosome compatibility here, potential causes behind the population structure were tested. First, no support for reproductively isolated cryptic \u003cem\u003eBiomphalaria\u003c/em\u003e species in Lake Victoria causing the structure was found, since the ancestry estimates varied continuously between populations, and because no marker was fixed between ancestral populations. Second, since the estimated allele frequencies for the two ancestral populations are continuously distributed, and only few alleles are observed at a similar frequency, we do not expect that a single prolific snail had parented a disproportionate amount of the offspring used in the GWAS. Third, while \u003cem\u003eB. sudanica\u003c/em\u003e and the deep-water taxon \u003cem\u003eB. choanomphala\u003c/em\u003e are closely related, perhaps being ecophenotypes (32), sympatric, and distinct in parasite susceptibility (47), they do not represent the ancestry groups and cluster with \u003cem\u003eB. sudanica\u003c/em\u003e having a majority Population 1 ancestry. Rather, Population 2 \u003cem\u003eB. sudanica\u003c/em\u003e is distinguished by a set of alleles that do not appear to be common in either species.\u003c/p\u003e\u003cp\u003eThe population structure of \u003cem\u003eB. sudanica\u003c/em\u003e in Lake Victoria observed in our results is more consistent with historical isolation and reconnection of populations. Of the major lakes in the Albertine Rift Valley lake system (Victoria, Tanganyika, Malawi), Lake Victoria is a relatively young lake forming ~ 0.4 Mya, and has gone through at least three major desiccations in the past 100,000 years (48–50). Shaped by such drought events, the cichlids of Lake Victoria have become a famous study system due to the astounding levels of explosive diversification that has occurred since the last desiccation event \u0026lt; 15,000 years ago (51, 52). The population structure of \u003cem\u003eB. sudanica\u003c/em\u003e observed suggests that indeed cryptic population structure is present, potentially caused by these historic events, yet the degree of admixing between populations in our study signifies ongoing outcrossing rather than clear speciation. The signatures of ongoing admixing may be influenced by hydrologic patterns of Lake Victoria. The collection site was ~ 20 miles north of the Rusinga channel connecting the open lake and narrow Winam gulf. The Winam gulf is a unique lake environment given that it is somewhat separated from open lake water due to the prevailing currents limiting circulation of water (53, 54), is comparatively shallower, potentially exacerbating historic water level changes, and has more protected shores, providing different freshwater habitats than those present in the open lake. The hydrology of the Rusinga channel and therefore Winam gulf was most recently disrupted by the blocking of the Mbita passage in the early 1980’s, until its unblocking in 2017 (55), therefore occurring just prior to our snail collections in early 2018. The return of north-easternly flow of open-lake water into the Winam gulf through the Mbita passage has caused a shift in both bacterial and planktonic communities in the Winam gulf (56, 57), and may have allowed dispersal of \u003cem\u003eB. sudanica\u003c/em\u003e populations on floating vegetation, such as water hyacinth between lake areas (58). Although we cannot establish the potentially different geographic origins of the \u003cem\u003eB. sudanica\u003c/em\u003e representative of each population using currently available data, these snail population differences, and therefore vectoral competency differences, could explain why some locations around lakes are persistent hotspots of transmission while others are not (10). These findings underscore how pathogen resistance can vary substantially between closely related populations, and in this instance could suggest that schistosome transmission may be more persistent in lake regions where highly susceptible \u003cem\u003eBiomphalaria\u003c/em\u003e populations, i.e. majority Population 1 ancestry, are present.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEvolutionary dynamics of snail-schistosome interaction.\u003c/b\u003e This study complements extensive work on immune mechanisms in laboratory populations of \u003cem\u003eB. glabrata\u003c/em\u003e (17, 20, 22, 59), facilitating comparisons between snail species. Notably, there was no overlap between our validated GWAS hits and loci linked to resistance in \u003cem\u003eB. glabrata\u003c/em\u003e. The amplicon panel included at least two amplicons within or near each of these \u003cem\u003ea priori\u003c/em\u003e candidates (27), and none of them showed a significant association with infection phenotype. \u003cem\u003eSudRes1\u003c/em\u003e resides on chromosome 5, the site of a large resistance QTL in \u003cem\u003eB. glabrata\u003c/em\u003e (22), though about 10 Mb away and thus unlikely to include the same gene(s). \u003cem\u003eSudRes2\u003c/em\u003e resides on \u003cem\u003eB. sudanica\u003c/em\u003e chromosome 6, which contains a density of schistosome-resistance \u003cem\u003ea priori\u003c/em\u003e loci including \u003cem\u003ePTC1\u003c/em\u003e (59), \u003cem\u003etlr\u003c/em\u003e (60), \u003cem\u003esod1\u003c/em\u003e (61), and the closest, \u003cem\u003eprx4\u003c/em\u003e (62), at ~ 1 Mb away is not likely to be responsible for association in our analysis. While allelic variation in orthologs of \u003cem\u003eB. glabrata\u003c/em\u003e resistance loci are not associated with \u003cem\u003eS. mansoni\u003c/em\u003e resistance in \u003cem\u003eB. sudanica\u003c/em\u003e, reverse genetics approaches successfully applied in \u003cem\u003eB. glabrata\u003c/em\u003e (63, 64) can be used in the future to functionally evaluate the roles of these genes. \u003cem\u003eBiomphalaria sudanica\u003c/em\u003e may rely on entirely different genetic mechanisms for parasite resistance than \u003cem\u003eB. glabrata\u003c/em\u003e. However, considering the extensive genotype-by-genotype interaction documented between \u003cem\u003eB. glabrata\u003c/em\u003e and \u003cem\u003eS. mansoni\u003c/em\u003e (65), mediated by hyperdiverse resistance loci suggestive of long-term balancing selection (17, 59), we propose a more nuanced scenario. Namely, that resistance alleles fluctuate dynamically in response to the genotypes of local parasites (including other trematodes), so the loci harboring large-effect, intermediate-frequency alleles will vary over time and space, even within a species. Other trematode species may be more prevalent and exert greater selection pressure on these snails, indirectly impacting resistance to \u003cem\u003eS. mansoni\u003c/em\u003e. The striking 4-fold effect of ancestry on odds of infection also supports this dynamic view, as subpopulations different in resistance may be distributed unevenly across Lake Victoria.\u003c/p\u003e\u003cp\u003eDiversity at both \u003cem\u003eSudRes1\u003c/em\u003e and \u003cem\u003eSudRes2\u003c/em\u003e is high, as shown by previous polymorphism scans (27) and confirmed by the substantial sequence and structural divergence between susceptible genome Bs111 and resistant genome Bs2280. We are unable to pinpoint causal genes yet, and the numerous differences between resistant and suspectable haplotypes means several candidates are plausible. Each genome assembly contains genes and/or gene segments that are absent in the other assembly. Thus, the host-parasite interaction mechanism(s) could include recognition by \u003cem\u003eS. mansoni\u003c/em\u003e of snail hosts possessing a particular susceptibility protein, triggering successful infection, or else recognition of the parasite by snails possessing a particular resistance protein, triggering immune cascades (66). If what matters is parasite recognition of the host, loss of EGF domains in \u003cem\u003eSudRes1\u003c/em\u003e RPTP proteins in resistant snails may inhibit parasite recognition of snail host molecules, and hinder parasite-driven modification of the host response. Similarly, loss of \u003cem\u003eSudRes2\u003c/em\u003e GRL101 genes in resistant snails may prevent the parasite from recognizing these snails, rendering them immune. In contrast, if resistance is driven by host recognition of the parasite, this could be mediated by nonsynonymous allelic differences in \u003cem\u003eSudRes1\u003c/em\u003e and \u003cem\u003eSudRes2\u003c/em\u003e or larger structural changes. For example, at \u003cem\u003eSudRes2\u003c/em\u003e the non-truncated Zn-RING-IAP gene \u003cem\u003eBSUD.25704\u003c/em\u003e, and its additional partial paralog, could fulfill a recognition function in resistant but not susceptible genomes. Parasite-resistance regions \u003cem\u003ePTC1\u003c/em\u003e (59) and \u003cem\u003ePTC2\u003c/em\u003e (17) in \u003cem\u003eB. glabrata\u003c/em\u003e can show both dominant resistance and dominant susceptibility (59, 67) and are also highly polymorphic in \u003cem\u003eB. sudanica\u003c/em\u003e (27), indicating a similar pattern of immune-relevant balancing selection consistent with long-term snail-parasite coevolution.\u003c/p\u003e\u003cp\u003eBy revealing immune-relevant genetic variation in \u003cem\u003eB. sudanica\u003c/em\u003e, the primary vector in African Great Lakes, this work represents an important step toward molecular-informed vector control to combat schistosomiasis in high-transmission global regions, including gene drive technologies (68). However, we demonstrate that genetic manipulation of snails for schistosomiasis control will require navigating the ever more complex genetic architecture of snail resistance, particularly when considering the non-overlap in findings from the laboratory model South American species \u003cem\u003eB. glabrata\u003c/em\u003e and the diversity of snail vector species responsible for the majority of schistosome transmission in Sub-Saharan Africa. The impact of any resistance allele may vary due to genetic background and environmental factors. However, we expect that the large-effect loci identified here will play key roles in the continued elucidation of snail immunity as it pertains to human disease.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eAdditional description of materials and methods is provided in SI Materials and Methods.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was undertaken following approval from the relevant bodies, including Kenya Medical Research Institute (KEMRI) Scientific Review Unit (Approval # KEMRI/RES/7/3/1 and KEMRI/SERU/CGHR/035/3864), Kenya\u0026rsquo;s National Commission for Science, Technology, and Innovation (License # NACOSTI/P/15/9609/4270 and NACOSTI/P/22/14839), Kenya Wildlife Services (permit # 0004754 and # WRTI-0136\u0026ndash;02-22), and National Environment, Management Authority (permit # NEMA/AGR/46/2014 \u0026ndash; Registration # 0178 and NEMA/AGR/159/2022 \u0026ndash; Registration # 201). Collections of \u003cem\u003eS. mansoni\u0026nbsp;\u003c/em\u003efrom schoolchildren were approved by KEMRI\u0026rsquo;s Scientific and Ethics Review Unit (SERU), reference SERU No. 3540, and by the Institutional Review Board of the University of New Mexico (UNM), reference 18115. Informed consent was obtained from the parents of five children that were deemed to be positive for \u003cem\u003eS. mansoni\u003c/em\u003e from fecal samples using egg microscopy, of which remaining samples were used for \u003cem\u003eS. mansoni\u003c/em\u003e miracidial hatching. All five children were treated with praziquantel during a follow-up visit by a KEMRI physician.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData, Materials, and Software Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll sequence data, including PacBio HiFi raw reads from genome sequence data of \u003cem\u003eB. sudanica\u0026nbsp;\u003c/em\u003eBs2280, has been uploaded onto the NCBI SRA under BioProject PRJNA1149315 with BioSample accessions SAMN43241892, SAMN43241893, SAMN43241894, SAMN43241895, SAMN45084274. The genome assembly of Bs2280 is available on figshare, DOI: 10.6084/m9.figshare.27985880.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by National Institute of Health, National Institute of Allergy and Infectious Disease grants R01AI141862 and R37AI101438.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eJ.A.T., E.S.L., M.R.O. and M.L.S. designed research; T.P., J.M.S., T.M., G.O., F.R., K.A., B.M., M.R.O., M.W.M., G.M.M. and M.L.S. performed research; T.P. and J.A.T. analyzed data; T.P., J.A.T. and M.L.S. wrote the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest Statement:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO, \u003cem\u003eGlobal report on neglected tropical diseases 2024\u003c/em\u003e (2024).\u003c/li\u003e\n\u003cli\u003eS. 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Klopp, D-GENIES: dot plot large genomes in an interactive, efficient and simple way. \u003cem\u003ePeerJ\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, e4958 (2018).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5656395/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5656395/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Schistosomiasis, a neglected tropical disease, is transmitted by freshwater snails. Interruption of transmission will require novel vector-focused interventions. We performed a genome-wide association study of African snails, \u003ci\u003eBiomphalaria sudanica\u003c/i\u003e, exposed to \u003ci\u003eSchistosoma mansoni\u003c/i\u003e in an endemic area of high transmission in Kenya. Two snail genomic regions, SudRes1 and SudRes2, were significantly associated with snail immunity to schistosomes. SudRes1 includes receptor-like protein tyrosine phosphatases while SudRes2 includes a class of leucine-rich repeat-containing G-protein coupled receptors, both comprising diverse extracellular binding domains suggestive of host-pathogen interaction. Resistant and susceptible haplotypes show numerous coding differences including presence/absence of entire genes. No loci previously tied to schistosome resistance in neotropical snail species showed any association with compatibility suggesting that loci involved in the resistance of African vectors are distinct. Snail ancestry was also strongly correlated with parasite compatibility. These results will inform future efforts to predict and manipulate immunity of a major schistosome vector.","manuscriptTitle":"Immune targets for schistosomiasis control identified by a genome-wide association study of African snail vectors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-03 06:53:46","doi":"10.21203/rs.3.rs-5656395/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e20a54f5-5660-4197-8a20-26214c6bda03","owner":[],"postedDate":"January 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":42276417,"name":"Biological sciences/Genetics/Genetic association study/Genome-wide association studies"},{"id":42276418,"name":"Biological sciences/Microbiology/Parasitology/Parasite host response"},{"id":42276419,"name":"Biological sciences/Microbiology/Pathogens"},{"id":42276420,"name":"Health sciences/Diseases/Infectious diseases/Parasitic infection"},{"id":42276421,"name":"Biological sciences/Microbiology/Parasitology/Parasite genomics"}],"tags":[],"updatedAt":"2025-07-27T07:07:30+00:00","versionOfRecord":{"articleIdentity":"rs-5656395","link":"https://doi.org/10.1038/s41467-025-61760-8","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-07-27 04:00:00","publishedOnDateReadable":"July 27th, 2025"},"versionCreatedAt":"2025-01-03 06:53:46","video":"","vorDoi":"10.1038/s41467-025-61760-8","vorDoiUrl":"https://doi.org/10.1038/s41467-025-61760-8","workflowStages":[]},"version":"v1","identity":"rs-5656395","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5656395","identity":"rs-5656395","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}