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Publisher Copyright: © 2020 The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. Identification of partial sweeps, which include both hard and soft sweeps that have not currently reached fixation, provides crucial information about ongoing evolutionary responses. To this end, we introduce partialS/HIC, a deep learning method to discover selective sweeps from population genomic data. partialS/HIC uses a convolutional neural network for image processing, which is trained with a large suite of summary statistics derived from coalescent simulations incorporating population-specific history, to distinguish between completed versus partial sweeps, hard versus soft sweeps, and regions directly affected by selection versus those merely linked to nearby selective sweeps. We perform several simulation experiments under various demographic scenarios to demonstrate partialS/HIC's performance, which exhibits excellent resolution for detecting partial sweeps. We also apply our classifier to whole genomes from eight mosquito populations sampled across sub-Saharan Africa by the Anopheles gambiae 1000 Genomes Consortium, elucidating both continent-wide patterns as well as sweeps unique to specific geographic regions. These populations have experienced intense insecticide exposure over the past two decades, and we observe a strong overrepresentation of sweeps at insecticide resistance loci. Our analysis thus provides a list of candidate adaptive loci that may be relevant to mosquito control efforts. More broadly, our supervised machine learning approach introduces a method to distinguish between completed and partial sweeps, as well as between hard and soft sweeps, under a variety of demographic scenarios. As whole-genome data rapidly accumulate for a greater diversity of organisms, partialS/HIC addresses an increasing demand for useful selection scan tools that can track in-progress evolutionary dynamics. publishersversion published

Significance The spread of Plasmodium falciparum with reduced susceptibility to artemisinin (ART) in Southeast Asia threatens global malaria control. Most failures of ART treatment are attributed to mutations in the pfkelch13 locus acting through an unclear mechanism. The role of pfkelch13 in reducing ART susceptibility was first identified in an in vitro selection experiment. We carried out a similar in vitro selection and discovered mutations in a different gene that reduce susceptibility to ART. The gene encodes PfCoronin, a conserved protein that in other organisms binds with actin to enhance cytoskeletal plasticity or is involved in vesicular transport. PfCoronin and PfKelch13 share structural similarities, and this finding may yield insights into the molecular mechanisms of ART resistance., Drug resistance is an obstacle to global malaria control, as evidenced by the recent emergence and rapid spread of delayed artemisinin (ART) clearance by mutant forms of the PfKelch13 protein in Southeast Asia. Identifying genetic determinants of ART resistance in African-derived parasites is important for surveillance and for understanding the mechanism of resistance. In this study, we carried out long-term in vitro selection of two recently isolated West African parasites (from Pikine and Thiès, Senegal) with increasing concentrations of dihydroartemisinin (DHA), the biologically active form of ART, over a 4-y period. We isolated two parasite clones, one from each original isolate, that exhibited enhanced survival to DHA in the ring-stage survival assay. Whole-genome sequence analysis identified 10 mutations in seven different genes. We chose to focus on the gene encoding PfCoronin, a member of the WD40-propeller domain protein family, because mutations in this gene occurred in both independent selections, and the protein shares the β-propeller motif with PfKelch13 protein. For functional validation, when pfcoronin mutations were introduced into the parental parasites by CRISPR/Cas9-mediated gene editing, these mutations were sufficient to reduce ART susceptibility in the parental lines. The discovery of a second gene for ART resistance may yield insights into the molecular mechanisms of resistance. It also suggests that pfcoronin mutants could emerge as a nonkelch13 type of resistance to ART in natural settings.

The sustainability of malaria control in Africa is threatened by the rise of insecticide resistance in Anopheles mosquitoes, which transmit the disease(1). To gain a deeper understanding of how mosquito populations are evolving, here we sequenced the genomes of 765 specimens of Anopheles gambiae and Anopheles coluzzii sampled from 15 locations across Africa, and identified over 50 million single nucleotide polymorphisms within the accessible genome. These data revealed complex population structure and patterns of gene flow, with evidence of ancient expansions, recent bottlenecks, and local variation in effective population size. Strong signals of recent selection were observed in insecticide-resistance genes, with several sweeps spreading over large geographical distances and between species. The design of new tools for mosquito control using gene-drive systems will need to take account of high levels of genetic diversity in natural mosquito populations.

Chromosomal inversion polymorphisms play an important role in adaptation to environmental heterogeneities. For mosquito species in theAnopheles gambiaecomplex that are significant vectors of human malaria, paracentric inversion polymorphisms are abundant and are associated with ecologically and epidemiologically important phenotypes. Improved understanding of these traits relies on determining mosquito karyotype, which currently depends upon laborious cytogenetic methods whose application is limited both by the requirement for specialized expertise and for properly preserved adult females at specific gonotrophic stages. To overcome this limitation, we developed sets of tag SNPs inside inversions whose biallelic genotype is strongly correlated with inversion genotype. We leveraged 1,347 fully sequencedAn. gambiaeandAnopheles coluzziigenomes in the Ag1000G database of natural variation. Beginning with principal components analysis (PCA) of population samples, applied to windows of the genome containing individual chromosomal rearrangements, we classified samples into three inversion genotypes, distinguishing homozygous inverted and homozygous uninverted groups by inclusion of the small subset of specimens in Ag1000G that are associated with cytogenetic metadata. We then assessed the correlation between candidate tag SNP genotypes and PCA-based inversion genotypes in our training sets, selecting those candidates with >80% agreement. Our initial tests both in held-back validation samples from Ag1000G and in data independent of Ag1000G suggest that when used forin silicoinversion genotyping of sequenced mosquitoes, these tags perform better than traditional cytogenetics, even for specimens where only a small subset of the tag SNPs can be successfully ascertained.

Background: Anopheles funestus is one of the three most consequential and widespread vectors of human malaria in tropical Africa. However, the lack of a high-quality reference genome has hindered the association of phenotypic traits with their genetic basis in this important mosquito. Findings: Here we present a new high-quality An. funestus reference genome (AfunF3) assembled using 240x coverage of long-read single-molecule sequencing for contigging, combined with 100x coverage of short-read Hi-C data for chromosome scaffolding. The assembled contigs total 446 Mbp of sequence and contain substantial duplication due to alternative alleles present in the sequenced pool of mosquitos from the FUMOZ colony. Using alignment and depth-of-coverage information, these contigs were deduplicated to a 211 Mbp primary assembly, which is closer to the expected haploid genome size of 250 Mbp. This primary assembly consists of 1,053 contigs organized into 3 chromosome-scale scaffolds with an N50 contig size of 632 kbp and an N50 scaffold size of 93.811 Mbp, representing a 100-fold improvement in continuity versus the current reference assembly, AfunF1. Conclusion: This highly contiguous and complete An. funestus reference genome assembly will serve as an improved basis for future studies of genomic variation and organization in this important disease vector.

Female Aedes aegypti mosquitoes infect hundreds of millions of people each year with dangerous viral pathogens including dengue, yellow fever, Zika, and chikungunya. Progress in understanding the biology of this insect, and developing tools to fight it, has been slowed by the lack of a high-quality genome assembly. Here we combine diverse genome technologies to produce AaegL5, a dramatically improved and annotated assembly, and demonstrate how it accelerates mosquito science and control. We anchored the physical and cytogenetic maps, resolved the size and composition of the elusive sex-determining “M locus”, significantly increased the known members of the glutathione-S-transferase genes important for insecticide resistance, and doubled the number of chemosensory ionotropic receptors that guide mosquitoes to human hosts and egg-laying sites. Using high-resolution QTL and population genomic analyses, we mapped new candidates for dengue vector competence and insecticide resistance. We predict that AaegL5 will catalyse new biological insights and intervention strategies to fight this deadly arboviral vector.

Female Aedes aegypti mosquitoes infect more than 400 million people each year with dangerous viral pathogens including dengue, yellow fever, Zika and chikungunya. Progress in understanding the biology of mosquitoes and developing the tools to fight them has been slowed by the lack of a high-quality genome assembly. Here we combine diverse technologies to produce the markedly improved, fully re-annotated AaegL5 genome assembly, and demonstrate how it accelerates mosquito science. We anchored physical and cytogenetic maps, doubled the number of known chemosensory ionotropic receptors that guide mosquitoes to human hosts and egg-laying sites, provided further insight into the size and composition of the sex-determining M locus, and revealed copy-number variation among glutathione S-transferase genes that are important for insecticide resistance. Using high-resolution quantitative trait locus and population genomic analyses, we mapped new candidates for dengue vector competence and insecticide resistance. AaegL5 will catalyse new biological insights and intervention strategies to fight this deadly disease vector. National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services [U19AI110818]; USDA [2017-05741]; NIH Intramural Research Program; National Library of Medicine; National Human Genome Research Institute; NSF [PHY-1427654]; NIH [R01AI101112, R35GM118336, R21AI121853, R01AI123338, T32GM007739, NIH/NCATS UL1TR000043, DP2OD008540, U01AI088647, 1R01AI121211, D43TW001130-08, U01HL130010, UM1HG009375, 5K22AI113060, 1R21AI123937, R00DC012069]; Defence Advanced Research Project Agency [HR0011-17-2-0047]; Jane Coffin Childs Memorial Fund; Center for Theoretical Biological Physics postdoctoral fellowship; Robertson Foundation; McNair Foundation; Welch Foundation [Q-1866]; French Government's Investissement d'Avenir program, Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases [ANR-10-LABX-62-IBEID]; Agence Nationale de la Recherche [ANR-17-ERC2-0016-01]; European Union [734584]; Pew and Searle Scholars Programs; Klingenstein-Simons Fellowship in the Neurosciences; Verily Life Sciences We thank R. Andino; S. Emrich and D. Lawson (Vectorbase); A. A. James, M. Kunitomi, C. Nusbaum, D. Severson, N. Whiteman; T. Dickinson, M. Hartley and B. Rice (Dovetail Genomics) for early participation in the AGWG; C. Bargmann, D. Botstein, E. Jarvis and E. Lander for encouragement and facilitation. N. Keivanfar, D. Jaffe and D. M. Church (10X Genomics) prepared DNA for structural-variant analysis. We thank A. Harmon of the New York Times and acknowledge generous pro bono data and analysis from our corporate collaborators. This research was supported in part by federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under grant number U19AI110818 to the Broad Institute (S.N.R. and D.E.N.); USDA 2017-05741 (E.L.A.); NSF PHY-1427654 Center for Theoretical Biological Physics (E.L.A.); NIH Intramural Research Program, National Library of Medicine and National Human Genome Research Institute (A.M.P. and S.K.) and the following extramural NIH grants: R01AI101112 (J.R.P.), R35GM118336 (R.S.M. and W.J.G.), R21AI121853 (M.V.S., I.V.S. and A. S.), R01AI123338 (Z.T.), T32GM007739 (M.H.), NIH/NCATS UL1TR000043 (Rockefeller University), DP2OD008540 (E.L.A.), U01AI088647, 1R01AI121211 (W.C.B. IV), Fogarty Training Grant D43TW001130-08, U01HL130010 (E.L.A.), UM1HG009375 (E.L.A), 5K22AI113060 (O.S.A.), 1R21AI123937 (O.S.A.), and R00DC012069 (C.S.M.); Defence Advanced Research Project Agency: HR0011-17-2-0047 (O.S.A.). Other support was provided by Jane Coffin Childs Memorial Fund (B.J.M.), Center for Theoretical Biological Physics postdoctoral fellowship (O.D.), Robertson Foundation (L.Z.), and McNair & Welch (Q-1866) Foundations (E.L.A.), French Government's Investissement d'Avenir program, Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases (grant ANR-10-LABX-62-IBEID to L.L.), Agence Nationale de la Recherche grant ANR-17-ERC2-0016-01 (L.L.), European Union's Horizon 2020 research and innovation program under ZikaPLAN grant agreement no. 734584 (L.L.), Pew and Searle Scholars Programs (C.S.M.), Klingenstein-Simons Fellowship in the Neurosciences (C.S.M.). A.M.W., B.J.W., J.E.C. and S.N.M. were supported by Verily Life Sciences. L.B.V. is an investigator of the Howard Hughes Medical Institute.

Hall et al. have strategically used long-read sequencing technology to characterize the structure and highly repetitive content of the Y chromosome in Anopheles malaria mosquitoes. Their work confirms that this important but elusive heterochromatic sex chromosome is evolving extremely rapidly and harbors a remarkably small number of genes.

Detecting de novo mutations in viral and bacterial pathogens enables researchers to reconstruct detailed networks of disease transmission and is a key technique in genomic epidemiology. However these techniques have not yet been applied to the malaria parasite, Plasmodium falciparum, in which a larger genome, slower generation times, and a complex life cycle make them difficult to implement. Here we demonstrate the viability of de novo mutation studies in P. falciparum for the first time. Using a set of clinical samples and novel methods of sequencing, library preparation, and genotyping, we have genotyped low-complexity regions of the genome with a high degree of accuracy. Despite its slower evolutionary rate compared to bacterial or viral species, de novo mutation can be detected in P. falciparum across timescales of just 1-2 years and evolutionary rates in low-complexity regions of the genome can be up to twice that detected in the rest of the genome. The increased mutation rate allows the identification of separate clade expansions that cannot be found using previous genomic epidemiology approaches and could be a crucial tool for mapping residual transmission patterns in disease elimination campaigns and reintroduction scenarios.

The sustainability of malaria control in Africa is threatened by rising levels of insecticide resistance, and new tools to prevent malaria transmission are urgently needed. To gain a better understanding of the mosquito populations that transmit malaria, we sequenced the genomes of 765 wild specimens ofAnopheles gambiaeandAnopheles coluzziisampled from 15 locations across Africa. The data reveal high levels of genetic diversity, with over 50 million single nucleotide polymorphisms across the 230 Mbp genome. We observe complex patterns of population structure and marked variations in local population size, some of which may be due at least in part to malaria control interventions. Insecticide resistance genes show strong signatures of recent selection associated with multiple independent mutations spreading over large geographical distances and between species. The genetic variability of natural populations substantially reduces the target space for novel gene-drive strategies for mosquito control. This large dataset provides a foundation for tracking the emergence and spread of insecticide resistance and developing new vector control tools.

VectorBase (http://www.vectorbase.org) is an NIAID-funded Bioinformatic Resource Center focused on invertebrate vectors of human pathogens. VectorBase annotates and curates vector genomes providing a web accessible integrated resource for the research community. Currently, VectorBase contains genome information for three mosquito species: Aedes aegypti, Anopheles gambiae and Culex quinquefasciatus, a body louse Pediculus humanus and a tick species Ixodes scapularis. Since our last report VectorBase has initiated a community annotation system, a microarray and gene expression repository and controlled vocabularies for anatomy and insecticide resistance. We have continued to develop both the software infrastructure and tools for interrogating the stored data.

Background The genome-wide association study (GWAS) techniques that have been used for genetic mapping in other organisms have not been successfully applied to mosquitoes, which have genetic characteristics of high nucleotide diversity, low linkage disequilibrium, and complex population stratification that render population-based GWAS essentially unfeasible at realistic sample size and marker density. Methods We designed a novel mapping strategy for the mosquito system that combines the power of linkage mapping with the resolution afforded by genetic association. We established founder colonies from West Africa, controlled for diversity, linkage disequilibrium and population stratification. Colonies were challenged by feeding on the infectious stage of the human malaria parasite, Plasmodium falciparum, mosquitoes were phenotyped for parasite load, and DNA pools for phenotypically similar mosquitoes were Illumina sequenced. Phenotype-genotype mapping was carried out in two stages, coarse and fine. Results In the first mapping stage, pooled sequences were analysed genome-wide for intervals displaying relativereduction in diversity between phenotype pools, and candidate genomic loci were identified for influence upon parasite infection levels. In the second mapping stage, focused genotyping of SNPs from the first mapping stage was carried out in unpooled individual mosquitoes and replicates. The second stage confirmed significant SNPs in a locus encoding two Toll-family proteins. RNAi-mediated gene silencing and infection challenge revealed that TOLL 11 protects mosquitoes against P. falciparum infection. Conclusions We present an efficient and cost-effective method for genetic mapping using natural variation segregating in defined recent Anopheles founder colonies, and demonstrate its applicability for mapping in a complex non-model genome. This approach is a practical and preferred alternative to population-based GWAS for first-pass mapping of phenotypes in Anopheles. This design should facilitate mapping of other traits involved in physiology, epidemiology, and behaviour. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2009-z) contains supplementary material, which is available to authorized users.

Zebrafish have become a popular organism for the study of vertebrate gene function1,2. The virtually transparent embryos of this species, and the ability to accelerate genetic studies by gene knockdown or overexpression, have led to the widespread use of zebrafish in the detailed investigation of vertebrate gene function and increasingly, the study of human genetic disease3–5. However, for effective modelling of human genetic disease it is important to understand the extent to which zebrafish genes and gene structures are related to orthologous human genes. To examine this, we generated a high-quality sequence assembly of the zebrafish genome, made up of an overlapping set of completely sequenced large-insert clones that were ordered and oriented using a high-resolution high-density meiotic map. Detailed automatic and manual annotation provides evidence of more than 26,000 protein-coding genes6, the largest gene set of any vertebrate so far sequenced. Comparison to the human reference genome shows that approximately 70% of human genes have at least one obvious zebrafish orthologue. In addition, the high quality of this genome assembly provides a clearer understanding of key genomic features such as a unique repeat content, a scarcity of pseudogenes, an enrichment of zebrafish-specific genes on chromosome 4 and chromosomal regions that influence sex determination.

Background Human Malaria is transmitted by mosquitoes of the genus Anopheles. Transmission is a complex phenomenon involving biological and environmental factors of humans, parasites and mosquitoes. Among more than 500 anopheline species, only a few species from different branches of the mosquito evolutionary tree transmit malaria, suggesting that their vectorial capacity has evolved independently. Anopheles albimanus (subgenus Nyssorhynchus) is an important malaria vector in the Americas. The divergence time between Anopheles gambiae, the main malaria vector in Africa, and the Neotropical vectors has been estimated to be 100 My. To better understand the biological basis of malaria transmission and to develop novel and effective means of vector control, there is a need to explore the mosquito biology beyond the An. gambiae complex. Results We sequenced the transcriptome of the An. albimanus adult female. By combining Sanger, 454 and Illumina sequences from cDNA libraries derived from the midgut, cuticular fat body, dorsal vessel, salivary gland and whole body, we generated a single, high-quality assembly containing 16,669 transcripts, 92% of which mapped to the An. darlingi genome and covered 90% of the core eukaryotic genome. Bidirectional comparisons between the An. gambiae, An. darlingi and An. albimanus predicted proteomes allowed the identification of 3,772 putative orthologs. More than half of the transcripts had a match to proteins in other insect vectors and had an InterPro annotation. We identified several protein families that may be relevant to the study of Plasmodium-mosquito interaction. An open source transcript annotation browser called GDAV (Genome-Delinked Annotation Viewer) was developed to facilitate public access to the data generated by this and future transcriptome projects. Conclusions We have explored the adult female transcriptome of one important New World malaria vector, An. albimanus. We identified protein-coding transcripts involved in biological processes that may be relevant to the Plasmodium lifecycle and can serve as the starting point for searching targets for novel control strategies. Our data increase the available genomic information regarding An. albimanus several hundred-fold, and will facilitate molecular research in medical entomology, evolutionary biology, genomics and proteomics of anopheline mosquito vectors. The data reported in this manuscript is accessible to the community via the VectorBase website (http://www.vectorbase.org/Other/AdditionalOrganisms/).

Background Quantitative transcriptome data for the malaria-transmitting mosquito Anopheles gambiae covers a broad range of biological and experimental conditions, including development, blood feeding and infection. Web-based summaries of differential expression for individual genes with respect to these conditions are a useful tool for the biologist, but they lack the context that a visualisation of all genes with respect to all conditions would give. For most organisms, including A. gambiae, such a systems-level view of gene expression is not yet available. Results We have clustered microarray-based gene-averaged expression values, available from VectorBase, for 10194 genes over 93 experimental conditions using a self-organizing map. Map regions corresponding to known biological events, such as egg production, are revealed. Many individual gene clusters (nodes) on the map are highly enriched in biological and molecular functions, such as protein synthesis, protein degradation and DNA replication. Gene families, such as odorant binding proteins, can be classified into distinct functional groups based on their expression and evolutionary history. Immunity-related genes are non-randomly distributed in several distinct regions on the map, and are generally distant from genes with house-keeping roles. Each immunity-rich region appears to represent a distinct biological context for pathogen recognition and clearance (e.g. the humoral and gut epithelial responses). Several immunity gene families, such as peptidoglycan recognition proteins (PGRPs) and defensins, appear to be specialised for these distinct roles, while three genes with physically interacting protein products (LRIM1/APL1C/TEP1) are found in close proximity. Conclusions The map provides the first genome-scale, multi-experiment overview of gene expression in A. gambiae and should also be useful at the gene-level for investigating potential interactions. A web interface is available through the VectorBase website http://www.vectorbase.org/. It is regularly updated as new experimental data becomes available.

Signals of Mosquito Speciation Malaria in Africa is transmitted by the mosquito species complex Anopheles gambiae . Neafsey et al. (p. 514 ) made high-resolution single-nucleotide arrays to map genetic divergence among members of the species. Differentiation between populations was observed and evidence obtained for selective sweeps within populations. Most divergence occurred within inversion regions around the centrosome and in genes associated with development, pheromone signaling, and from the X chromosome. The analysis also revealed signals of sympatric speciation occurring within similar chromosomal regions in mosquitoes from different regions in Africa. Lawniczak et al. (p. 512 ) sequenced the genomes of two molecular forms (known as M and S) of A. gambiae , which have distinctive behavioral phenotypes and appear to be speciating. This effort resolves problems arising from the apparently chimeric nature of the reference genome and confirms the observed genome-wide divergences. This kind of analysis has the potential to contribute to control programs that can adapt to population shifts in mosquito behavior arising from the selective effects of the control measures themselves.

VectorBase (http://www.vectorbase.org/) is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever.

Trypanosomatids of the order Kinetoplastida are major contributors to global disease and morbidity, and understanding their basic biology coupled with the development of new drug targets represents a critical need. Additionally, trypanosomes are among the more accessible divergent eukaryote experimental systems. The genome of Trypanosoma brucei contains 8,131 predicted open reading frames (ORFs), of which over half have no known homologues beyond the Kinetoplastida and a substantial number of others are poorly defined by in silico analysis. Thus, a major challenge following completion of the T. brucei genome sequence is to obtain functional data for all trypanosome ORFs. As T. brucei is more experimentally tractable than the related Trypanosoma cruzi and Leishmania spp. and shares >75% of their genes, functional analysis of T. brucei has the potential to inform a range of parasite biology. Here, we report methods for systematic mRNA ablation by RNA interference (RNAi) and for phenotypic analysis, together with online data dissemination. This represents the first systematic analysis of gene function in a parasitic organism. In total, 210 genes have been targeted in the bloodstream form parasite, representing an essentially complete phenotypic catalogue of chromosome I together with a validation set. Over 30% of the chromosome I genes generated a phenotype when targeted by RNAi; most commonly, this affected cell growth, viability, and/or cell cycle progression. RNAi against approximately 12% of ORFs was lethal, and an additional 11% had growth defects but retained short-term viability in culture. Although we found no evidence for clustering or a bias towards widely evolutionarily conserved genes within the essential ORF cohort, the putative chromosome I centromere is adjacent to a domain containing genes with no associated phenotype. Involvement of such a large proportion of genes in robust growth in vitro indicates that a high proportion of the expressed trypanosome genome is required for efficient propagation; many of these gene products represent potential drug targets.

Linking phenotypic with genotypic diversity has become a major requirement for basic and applied genome-centric biological research. To meet this need, a comprehensive database backend for efficiently storing, querying and analyzing large experimental data sets is necessary. Chado, a generic, modular, community-based database schema is widely used in the biological community to store information associated with genome sequence data. To meet the need to also accommodate large-scale phenotyping and genotyping projects, a new Chado module called Natural Diversity has been developed. The module strictly adheres to the Chado remit of being generic and ontology driven. The flexibility of the new module is demonstrated in its capacity to store any type of experiment that either uses or generates specimens or stock organisms. Experiments may be grouped or structured hierarchically, whereas any kind of biological entity can be stored as the observed unit, from a specimen to be used in genotyping or phenotyping experiments, to a group of species collected in the field that will undergo further lab analysis. We describe details of the Natural Diversity module, including the design approach, the relational schema and use cases implemented in several databases.