Genomic variation of 363 diverse tea accessions unveils the genetic diversity, domestication, and structural variations associated with tea adaptation.

Domestication has shaped the population structure and agronomic traits of tea plants, yet the complexity of tea population structure and genetic variation that determines these traits remains unclear. We here investigated the resequencing data of 363 diverse tea accessions collected extensively from almost all tea distributions and found that the population structure of tea plants was divided into eight subgroups, which were basically consistent with their geographical distributions. The genetic diversity of tea plants in China decreased from southwest to east as latitude increased. Results also indicated that Camellia sinensis var. assamica (CSA) illustrated divergent selection signatures with Camellia sinensis var. sinensis (CSS). The domesticated genes of CSA were mainly involved in leaf development, flavonoid and alkaloid biosynthesis, while the domesticated genes in CSS mainly participated in amino acid metabolism, aroma compounds biosynthesis, and cold stress. Comparative population genomics further identified ~730 Mb novel sequences, generating 6,058 full-length protein-encoding genes, significantly expanding the gene pool of tea plants. We also discovered 217,376 large-scale structural variations and 56,583 presence and absence variations (PAVs) across diverse tea accessions, some of which were associated with tea quality and stress resistance. Functional experiments demonstrated that two PAV genes (CSS0049975 and CSS0006599) were likely to drive trait diversification in cold tolerance between CSA and CSS tea plants. The overall findings not only revealed the genetic diversity and domestication of tea plants, but also underscored the vital role of structural variations in the diversification of tea plant traits.

A Pilot Detection and Associate Study of Gene Presence-Absence Variation in Holstein Cattle.

Presence-absence variations (PAVs) are important structural variations, wherein a genomic segment containing one or more genes is present in some individuals but absent in others. While PAVs have been extensively studied in plants, research in cattle remains limited. This study identified PAVs in 173 Holstein bulls using whole-genome sequencing data and assessed their associations with 46 economically important traits. Out of 28,772 cattle genes (from the longest transcripts), a total of 26,979 (93.77%) core genes were identified (present in all individuals), while variable genes included 928 softcore (present in 95-99% of individuals), 494 shell (present in 5-94%), and 371 cloud genes (present in <5%). Cloud genes were enriched in functions associated with hormonal and antimicrobial activities, while shell genes were enriched in immune functions. PAV-based genome-wide association studies identified associations between gene PAVs and 16 traits including milk, fat, and protein yields, as well as traits related to health and reproduction. Associations were found on multiple chromosomes, illustrating important associations on cattle chromosomes 7 and 15, involving olfactory receptor and immune-related genes, respectively. By examining the PAVs at the population level, the results of this research provided crucial insights into the genetic structures underlying the complex traits of Holstein cattle.

The Landscape of Presence/Absence Variations during the Improvement of Rice.

Rice is one of the most important staple crops in the world; therefore, the improvement of rice holds great significance for enhancing agricultural production and addressing food security challenges. Although there have been numerous studies on the role of single-nucleotide polymorphisms (SNPs) in rice improvement with the development of next-generation sequencing technologies, research on the role of presence/absence variations (PAVs) in the improvement of rice is limited. In particular, there is a scarcity of studies exploring the traits and genes that may be affected by PAVs in rice. Here, we extracted PAVs utilizing resequencing data from 148 improved rice varieties distributed in Asia. We detected a total of 33,220 PAVs and found that the number of variations decreased gradually as the length of the PAVs increased. The number of PAVs was the highest on chromosome 1. Furthermore, we identified a 6 Mb hotspot region on chromosome 11 containing 1091 PAVs in which there were 29 genes related to defense responses. By conducting a genome-wide association study (GWAS) using PAV variation data and phenotypic data for five traits (flowering time, plant height, flag leaf length, flag leaf width, and panicle number) across all materials, we identified 186 significantly associated PAVs involving 20 cloned genes. A haplotype analysis and expression analysis of candidate genes revealed that important genes might be affected by PAVs, such as the flowering time gene OsSFL1 and the flag leaf width gene NAL1. Our work investigated the pattern in PAVs and explored important PAV key functional genes associated with agronomic traits. Consequently, these results provide potential and exploitable genetic resources for rice breeding.

Distinct genomic contexts predict gene presence-absence variation in different pathotypes of Magnaporthe oryzae.

Fungi use the accessory gene content of their pangenomes to adapt to their environments. While gene presence-absence variation contributes to shaping accessory gene reservoirs, the genomic contexts that shape these events remain unclear. Since pangenome studies are typically species-wide and do not analyze different populations separately, it is yet to be uncovered whether presence-absence variation patterns and mechanisms are consistent across populations. Fungal plant pathogens are useful models for studying presence-absence variation because they rely on it to adapt to their hosts, and members of a species often infect distinct hosts. We analyzed gene presence-absence variation in the blast fungus, Magnaporthe oryzae (syn. Pyricularia oryzae), and found that presence-absence variation genes involved in host-pathogen and microbe-microbe interactions may drive the adaptation of the fungus to its environment. We then analyzed genomic and epigenomic features of presence-absence variation and observed that proximity to transposable elements, gene GC content, gene length, expression level in the host, and histone H3K27me3 marks were different between presence-absence variation genes and conserved genes. We used these features to construct a model that was able to predict whether a gene is likely to experience presence-absence variation with high precision (86.06%) and recall (92.88%) in M. oryzae. Finally, we found that presence-absence variation genes in the rice and wheat pathotypes of M. oryzae differed in their number and their genomic context. Our results suggest that genomic and epigenomic features of gene presence-absence variation can be used to better understand and predict fungal pangenome evolution. We also show that substantial intra-species variation can exist in these features.

Comparative analysis of Presence-Absence gene Variations in five hard tick species: impact and functional considerations.

Tick species are vectors of harmful human and animal diseases, and their expansion is raising concerns under the global environmental changes' scenario. Ticks host and transmit bacteria, protozoa and viruses, making the understanding of host-pathogen molecular pathways critical to development of effective disease control strategies. Despite the considerable sizes and repeat contents of tick genomes, individual tick genomics is perhaps the most effective approach to reveal genotypic traits of interest. Presence-Absence gene Variations (PAVs) can contribute to individual differences within species, with dispensable genes carried by subsets of individuals possibly underpinning functional significance at individual or population-levels. We exploited 350 resequencing datasets of Dermacentor silvarum, Haemaphysalis longicornis, Ixodes persulcatus, Rhipicephalus microplus and Rhipicephalus sanguineus hard tick specimens to reveal the extension of PAV and the conservation of dispensable genes among individuals and, comparatively, between species. Overall, we traced 550-3,346 dispensable genes per species and were able to reconstruct 5.3-7 Mb of genomic regions not included in the respective reference genomes, as part of the tick pangenomes. Both dispensable genes and de novo predicted genes indicated that PAVs preferentially impacted mobile genetic elements in these tick species.

Pan-genome analysis highlights the role of structural variation in the evolution and environmental adaptation of Asian honeybees.

The Asian honeybee, Apis cerana, is an ecologically and economically important pollinator. Mapping its genetic variation is key to understanding population-level health, histories and potential capacities to respond to environmental changes. However, most efforts to date were focused on single nucleotide polymorphisms (SNPs) based on a single reference genome, thereby ignoring larger scale genomic variation. We employed long-read sequencing technologies to generate a chromosome-scale reference genome for the ancestral group of A. cerana. Integrating this with 525 resequencing data sets, we constructed the first pan-genome of A. cerana, encompassing almost the entire gene content. We found that 31.32% of genes in the pan-genome were variably present across populations, providing a broad gene pool for environmental adaptation. We identified and characterized structural variations (SVs) and found that they were not closely linked with SNP distributions; however, the formation of SVs was closely associated with transposable elements. Furthermore, phylogenetic analysis using SVs revealed a novel A. cerana ecological group not recoverable from the SNP data. Performing environmental association analysis identified a total of 44 SVs likely to be associated with environmental adaptation. Verification and analysis of one of these, a 330 bp deletion in the Atpalpha gene, indicated that this SV may promote the cold adaptation of A. cerana by altering gene expression. Taken together, our study demonstrates the feasibility and utility of applying pan-genome approaches to map and explore genetic feature variations of honeybee populations, and in particular to examine the role of SVs in the evolution and environmental adaptation of A. cerana.

Invading nonnative frogs use different microhabitats and change physiology along an elevation gradient.

The coqui frog (Eleutherodactylus coqui) was introduced to the island of Hawai'i in the 1980s, and has spread across much of the island. There is concern they will invade higher elevation areas where negative impacts on native species are expected. It is not known if coqui change behavior and baseline physiology in ways that allow them to invade higher elevations. We investigated where coqui are found across the island and whether that includes recent invasion into higher elevations. We also investigated whether elevation is related to coqui's microhabitat use, including substrate use and height off the forest floor, and physiological metrics, including plasma osmolality, oxidative status, glucose, free glycerol, and triglycerides, that might be associated with invading higher elevations. We found coqui have increased the area they occupy along roads from 31% to 50% and have moved into more high-elevation locations (16% vs. 1%) compared to where they were found 14 years ago. We also found frogs at high elevation on different substrates and closer to the forest floor than frogs at lower elevations-perhaps in response to air temperatures which tended to be warmer close to the forest floor. We observed that blood glucose and triglycerides increase in frogs with elevation. An increase in glucose is likely an acclimation response to cold temperatures while triglycerides may also help frogs cope with the energetic demands of suboptimal temperatures. Finally, we found that female coqui have higher plasma osmolality, reactive oxygen metabolites (dROMs), free glycerol, and triglycerides than males. Our study suggests coqui behavior and physiology in Hawai'i may be influenced by elevation in ways that allow them to cope with lower temperatures and invade higher elevations.

Evaluating the predictive performance of presence-absence models: Why can the same model appear excellent or poor?

When comparing multiple models of species distribution, models yielding higher predictive performance are clearly to be favored. A more difficult question is how to decide whether even the best model is "good enough". Here, we clarify key choices and metrics related to evaluating the predictive performance of presence-absence models. We use a hierarchical case study to evaluate how four metrics of predictive performance (AUC, Tjur's R 2, max-Kappa, and max-TSS) relate to each other, the random and fixed effects parts of the model, the spatial scale at which predictive performance is measured, and the cross-validation strategy chosen. We demonstrate that the very same metric can achieve different values for the very same model, even when similar cross-validation strategies are followed, depending on the spatial scale at which predictive performance is measured. Among metrics, Tjur's R 2 and max-Kappa generally increase with species' prevalence, whereas AUC and max-TSS are largely independent of prevalence. Thus, Tjur's R 2 and max-Kappa often reach lower values when measured at the smallest scales considered in the study, while AUC and max-TSS reaching similar values across the different spatial levels included in the study. However, they provide complementary insights on predictive performance. The very same model may appear excellent or poor not only due to the applied metric, but also how predictive performance is exactly calculated, calling for great caution on the interpretation of predictive performance. The most comprehensive evaluation of predictive performance can be obtained by evaluating predictive performance through the combination of measures providing complementary insights. Instead of following simple rules of thumb or focusing on absolute values, we recommend comparing the achieved predictive performance to the researcher's own a priori expectations on how easy it is to make predictions related to the same question that the model is used for.

Insights into genetic diversity and phenotypic variations in domestic geese through comprehensive population and pan-genome analysis.

BACKGROUND: Domestic goose breeds are descended from either the Swan goose (Anser cygnoides) or the Greylag goose (Anser anser), exhibiting variations in body size, reproductive performance, egg production, feather color, and other phenotypic traits. Constructing a pan-genome facilitates a thorough identification of genetic variations, thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability. RESULTS: To comprehensively facilitate population genomic and pan-genomic analyses in geese, we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples. By constructing the pan-genome for geese, we generated non-reference contigs totaling 612 Mb, unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes, 1,324 softcore genes, 2,734 shell genes, and 878 cloud genes in goose genomes. Furthermore, we detected an 81.97 Mb genomic region showing signs of genome selection, encompassing the TGFBR2 gene correlated with variations in body weight among geese. Genome-wide association studies utilizing single nucleotide polymorphisms (SNPs) and presence-absence variation revealed significant genomic associations with various goose meat quality, reproductive, and body composition traits. For instance, a gene encoding the SVEP1 protein was linked to carcass oblique length, and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length. Notably, the pan-genome analysis revealed enrichment of variable genes in the "hair follicle maturation" Gene Ontology term, potentially linked to the selection of feather-related traits in geese. A gene presence-absence variation analysis suggested a reduced frequency of genes associated with "regulation of heart contraction" in domesticated geese compared to their wild counterparts. Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation. CONCLUSION: This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits, thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese. Moreover, assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome, establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize.

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

GET_PANGENES: calling pangenes from plant genome alignments confirms presence-absence variation.

Crop pangenomes made from individual cultivar assemblies promise easy access to conserved genes, but genome content variability and inconsistent identifiers hamper their exploration. To address this, we define pangenes, which summarize a species coding potential and link back to original annotations. The protocol get_pangenes performs whole genome alignments (WGA) to call syntenic gene models based on coordinate overlaps. A benchmark with small and large plant genomes shows that pangenes recapitulate phylogeny-based orthologies and produce complete soft-core gene sets. Moreover, WGAs support lift-over and help confirm gene presence-absence variation. Source code and documentation: https://github.com/Ensembl/plant-scripts .

Comparative pangenome analyses provide insights into the evolution of Brassica rapa resistance gene analogues (RGAs).

Brassica rapa is grown worldwide as economically important vegetable and oilseed crop. However, its production is challenged by yield-limiting pathogens. The sustainable control of these pathogens mainly relies on the deployment of genetic resistance primarily driven by resistance gene analogues (RGAs). While several studies have identified RGAs in B. rapa, these were mainly based on a single genome reference and do not represent the full range of RGA diversity in B. rapa. In this study, we utilized the B. rapa pangenome, constructed from 71 lines encompassing 12 morphotypes, to describe a comprehensive repertoire of RGAs in B. rapa. We show that 309 RGAs were affected by presence-absence variation (PAV) and 223 RGAs were missing from the reference genome. The transmembrane leucine-rich repeat (TM-LRR) RGA class had more core gene types than variable genes, while the opposite was observed for nucleotide-binding site leucine-rich repeats (NLRs). Comparative analysis with the B. napus pangenome revealed significant RGA conservation (93%) between the two species. We identified 138 candidate RGAs located within known B. rapa disease resistance QTL, of which the majority were under negative selection. Using blackleg gene homologues, we demonstrated how these genes in B. napus were derived from B. rapa. This further clarifies the genetic relationship of these loci, which may be useful in narrowing-down candidate blackleg resistance genes. This study provides a novel genomic resource towards the identification of candidate genes for breeding disease resistance in B. rapa and its relatives.

2018-2022 Southern Resident killer whale presence in the Salish Sea: continued shifts in habitat usage.

The fish-eating Southern Resident killer whales (Orcinus orca) of the northeastern Pacific are listed as Endangered in both the USA and Canada. The inland waters of Washington State and British Columbia, a region known as the Salish Sea, are designated as Southern Resident critical habitat by both countries. The whales have historically had regular monthly presence in the Salish Sea, with peak abundance occurring from May through September. In recent years, at least partially in response to shifting prey abundance, habitat usage by the Southern Residents has changed. As conservation measures aim to provide the best possible protection for the whales in their hopeful recovery, it is key that policies are based both on historic trends and current data. To this aim, our study shares 2018-2022 daily occurrence data to build upon and compare to previously published whale presence numbers and to demonstrate more recent habitat shifts. Based on reports from an extensive network of community scientists as well as online streaming hydrophones, every Southern Resident occurrence was confirmed either visually or acoustically. Documented here are the first-ever total absence of the Southern Residents in the Salish Sea in the months of May, June, and August, as well as their continued overall declining presence in the spring and summer, while fall and winter presence remains relatively high. It is key that management efforts consider these shifting presence patterns when setting both seasonal and regional protection measures aimed at supporting population recovery.

The Effect of Methodological Considerations on the Construction of Gene-Based Plant Pan-genomes.

Pan-genomics is an emerging approach for studying the genetic diversity within plant populations. In contrast to common resequencing studies that compare whole genome sequencing data with a single reference genome, the construction of a pan-genome (PG) involves the direct comparison of multiple genomes to one another, thereby enabling the detection of genomic sequences and genes not present in the reference, as well as the analysis of gene content diversity. Although multiple studies describing PGs of various plant species have been published in recent years, a better understanding regarding the effect of the computational procedures used for PG construction could guide researchers in making more informed methodological decisions. Here, we examine the effect of several key methodological factors on the obtained gene pool and on gene presence-absence detections by constructing and comparing multiple PGs of Arabidopsis thaliana and cultivated soybean, as well as conducting a meta-analysis on published PGs. These factors include the construction method, the sequencing depth, and the extent of input data used for gene annotation. We observe substantial differences between PGs constructed using three common procedures (de novo assembly and annotation, map-to-pan, and iterative assembly) and that results are dependent on the extent of the input data. Specifically, we report low agreement between the gene content inferred using different procedures and input data. Our results should increase the awareness of the community to the consequences of methodological decisions made during the process of PG construction and emphasize the need for further investigation of commonly applied methodologies.

Genome-wide presence/absence variation discovery and its application in Peach (Prunus persica).

Gene presence/absence variation (PAV) is an important contributor to the studies of genetic diversity, gene identification, and molecular marker development in plants. In the present study, 100 peach (Prunus persica) accessions were used for genome resequencing to identify PAVs. Alignmentwith a reference genome yielded a total of 2.52 Mb non-reference sequences and 923 novel genes were identified. The dispensable PAVs were enriched in resistance, perhaps reflecting their roles in plant adaptation to various environments. Furthermore, selection sweeps associated with peach domestication and improvement were identified based on PAV data. Only 4.3% and 13.4% of domestication and improvement sweeps, respectively, were identified simultaneously using single nucleotide polymorphism (SNP) data, suggesting flexible identification between the different methods. To further verify the applicability of PAV identification, a genome-wide association study was conducted using 21 agronomic traits. Some of the identified loci were consistent with those reported in previous studies, while some were mapped for the first time; the latter included petiole length, petiole gland shape, and petiole gland number. Through tissue-specific expression analysis and gene transformation experiments, a novel gene, evm.model.Contig322_A94.1, was identified and found to be involved in chilling requirements. We speculated that this novel gene might regulate the trait by participating in the ABA signaling pathway. The PAVs identified in P. persica provide valuable resources for mapping the entire gene set and identifying optional markers for molecular selection in future studies.

The role of gene presence-absence variations on genetic incompatibility in Asian rice.

Genetic incompatibilities are widespread between species. However, it remains unclear whether they all originated after population divergence as suggested by the Bateson-Dobzhansky-Muller model, and if not, what is their prevalence and distribution within populations. The gene presence-absence variations (PAVs) provide an opportunity for investigating gene-gene incompatibility. Here, we searched for the repulsion of coexistence between gene PAVs to identify the negative interaction of gene functions separately in two Oryza sativa subspecies. Many PAVs are involved in subspecies-specific negative epistasis and segregate at low-to-intermediate frequencies in focal subspecies but at low or high frequencies in the other subspecies. Incompatible PAVs are enriched in two functional groups, defense response and protein phosphorylation, which are associated with plant immunity and consistent with autoimmunity being a known mechanism of hybrid incompatibility in plants. Genes in the two enriched functional groups are older and seldom directly interact with each other. Instead, they interact with other younger gene PAVs with diverse functions. Our results illustrate the landscape of genetic incompatibility at gene PAVs in rice, where many incompatible pairs have already segregated as polymorphisms within subspecies, and many are novel negative interactions between older defense-related genes and younger genes with diverse functions.

Unveiling the Impact of Gene Presence/Absence Variation in Driving Inter-Individual Sequence Diversity within the CRP-I Gene Family in Mytilus spp.

Mussels (Mytilus spp.) tolerate infections much better than other species living in the same marine coastal environment thanks to a highly efficient innate immune system, which exploits a remarkable diversification of effector molecules involved in mucosal and humoral responses. Among these, antimicrobial peptides (AMPs) are subjected to massive gene presence/absence variation (PAV), endowing each individual with a potentially unique repertoire of defense molecules. The unavailability of a chromosome-scale assembly has so far prevented a comprehensive evaluation of the genomic arrangement of AMP-encoding loci, preventing an accurate ascertainment of the orthology/paralogy relationships among sequence variants. Here, we characterized the CRP-I gene cluster in the blue mussel Mytilus edulis, which includes about 50 paralogous genes and pseudogenes, mostly packed in a small genomic region within chromosome 5. We further reported the occurrence of widespread PAV within this family in the Mytilus species complex and provided evidence that CRP-I peptides likely adopt a knottin fold. We functionally characterized the synthetic peptide sCRP-I H1, assessing the presence of biological activities consistent with other knottins, revealing that mussel CRP-I peptides are unlikely to act as antimicrobial agents or protease inhibitors, even though they may be used as defense molecules against infections from eukaryotic parasites.

Fisheries-dependent and -Independent data used to model the distribution of diadromous fish at-sea.

A database of 168 904 hauls covering the period from 1965 to 2019, from 46 surveys containing both fisheries-dependent (fishing vessels) and -independent data (scientific surveys) were collated from across the eastern Atlantic (Greater North Sea, Celtic Sea, Bay of Biscay and Iberian coast) and Metropolitan French Mediterranean waters. Data on diadromous fish (the European sturgeon (Acipenser sturio), allis shad (Alosa alosa), twait shad (Alosa fallax), Mediterranean twaite shad (Alosa agone), European eel (Anguilla anguilla), thinlip mullet (Chelon ramada), river lamprey (Lampetra fluviatilis), sea lamprey (Petromyzon marinus), smelt (Osmerus eperlanus), European flounder (Platichthys flesus), Atlantic salmon (Salmo salar) and the sea trout (Salmo trutta)) presence-absence was extracted and cleaned. The gear type and gear category which caught these species, their spatial location, and the date of capture (year and month), were also cleaned and standardised. Very little is known about diadromous fish at-sea and modelling data-poor and poorly detectable species such as diadromous fish is challenging for species conservation. Furthermore, databases which contain both scientific surveys and fisheries-dependent data on data-poor species at the temporal and geographical scale of this database are uncommon. This data could therefore be used to improve knowledge of diadromous fish spatial and temporal trends, and modelling techniques for data-poor species.

Occurrence Prediction of Riffle Beetles (Coleoptera: Elmidae) in a Tropical Andean Basin of Ecuador Using Species Distribution Models.

Genera and species of Elmidae (riffle beetles) are sensitive to water pollution; however, in tropical freshwater ecosystems, their requirements regarding environmental factors need to be investigated. Species distribution models (SDMs) were established for five elmid genera in the Paute river basin (southern Ecuador) using the Random Forest (RF) algorithm considering environmental variables, i.e., meteorology, land use, hydrology, and topography. Each RF-based model was trained and optimised using cross-validation. Environmental variables that explained most of the Elmidae spatial variability were land use (i.e., riparian vegetation alteration and presence/absence of canopy), precipitation, and topography, mainly elevation and slope. The highest probability of occurrence for elmids genera was predicted in streams located within well-preserved zones. Moreover, specific ecological niches were spatially predicted for each genus. Macrelmis was predicted in the lower and forested areas, with high precipitation levels, towards the Amazon basin. Austrelmis was predicted to be in the upper parts of the basin, i.e., páramo ecosystems, with an excellent level of conservation of their riparian ecosystems. Austrolimnius and Heterelmis were also predicted in the upper parts of the basin but in more widespread elevation ranges, in the Heterelmis case, and even in some areas with a medium level of anthropisation. Neoelmis was predicted to be in the mid-region of the study basin in high altitudinal streams with a high degree of meandering. The main findings of this research are likely to contribute significantly to local conservation and restoration efforts being implemented in the study basin and could be extrapolated to similar eco-hydrological systems.