Chaerephon pumilus species group (Molossidae) is poorly understood, including those found on western Indian Ocean islands. Two species in this complex have been identified in the Comoros: C. pusillus and C. leucogaster. Here, we aim to genetically characterize these two species and investigate their spatial population genetic structure. Analyzing five nuclear microsatellite markers from 200 individuals and one mitochondrial DNA gene (Cyt‐b) from 161 (out of the 200) individuals sampled on Madagascar and the Comoros, our findings indicated that these species are genetically differentiated. We observed mitonuclear discordance in numerous individuals . Based on ABC analyses, we found that this pattern could potentially be the result of asymmetric introgressive hybridization from C. leucogaster to C. pusillus and calls for further studies on the demographic history of these species. Moreover, at the intra‐specific level, analyses of the microsatellite loci suggested the evidence of a more pronounced, although weak, geographically based genetic structure in C. pusillus than in C. leucogaster. Altogether, our findings provide preliminary insights into the eco‐evolutionary aspects of this species complex and warrant further research to understand hybridization dynamics and mechanisms responsible for mitonuclear discordance.Cryptic species diversity is known to be common in bats but remains challenging to study in these mammals, whose natural history traits render their sampling and monitoring challenging. For these animals, indirect genetic approaches provide a powerful tool to gain insight into the evolutionary history and ecology of cryptic bat species. The speciation history of the polyphyletic  Chaerephon leucogaster and Chaerephon pusillus living on islands in the western Indian Ocean.Cryptic species diversity is well‐known in bats but difficult to study: an indirect genetic approach provides a tool to understand their evolutionary and ecological history. Our study used both mitochondrial and nuclear genetic analyses to bring new insights into the evolutionary history of  The C. pumilus species complex  in the Comoros  and five polymorphic nuclear microsatellite loci (NucDNA) for 161 and 200 individuals, respectively. Our research aimed to genetically characterize the cryptic species C. leucogaster and C. pusillus occurring on these islands, and describe their intra‐specific spatial population genetic structure.Despite their complex evolutionary history, 22.1Chaerephon were sampled on islands of the Comoro archipelago , and in three areas of Madagascar . Briefly, sample tubes, including positive and negative extraction controls, were lysed overnight at 56°C, then DNA was isolated and purified using purification columns and vacuum filtration. DNA was eluted to obtain final concentrations between 20–100 ng/μl.C. pumilus  were amplified in simplex PCR using the primers indicated in Table PCR amplifications were performed separately for each marker at 10 μl final volumes containing 5 μl of mastermix Taq Polymerase , 0.20 μM or 0.60 μM of the primers pair  under denaturing conditions  with an internal size marker prepared once and dispatched equally in all sample wells of each marker run. This internal size marker guarantees the same calibration for all samples. As the 200 samples were distributed on three plates and each plate contained the same positive reference controls (previously genotyped once), all positive controls were finally run four times on each marker, which guarantees both amplification and capillary resolution repeatability. The electropherograms were analyzed using GENEMAPPER 4.1 (ThermoFisher Scientific) and independently by two analysts to determine the allele sizes for each marker of each individual. When the genotypes determined by each analyst did not agree, the electropherograms were read again, and reading errors were resolved. In case of persistent disagreement, ambiguous results were considered as missing data. Genotype of each positive control was compared with its known reference to ensure the repeatability of analysis.b (Cyt‐b) mitochondrial gene (605 pb) for 161 individuals randomly chosen  were tracked using the program MICROCHECKER v.2.2.3  with default parameters  between pairs of Cyt‐b sequences were computed using ARLEQUIN v.3.5 software . We used the admixture model with correlated allele frequencies and a burn‐in period of 300,000 steps followed by 1,000,000 MCMC repeats. The optimal number of genetic clusters was determined using both the log posterior probability of the data Ln Pr(X|K) and the Evanno ∆K method  and microsatellite loci. We tested three scenarios of species divergence: (i) an ancestral population splits into two distinct populations at time t with no genetic exchange between the descendant populations 2; for Cyt‐b: standard deviation over loci of the heterozygosity for each population, mean heterozygosity, number of private polymorphic sites and pairwise FST) were used to compare the simulated and observed data. To discriminate between the three models, we used a rejection method implemented in the R “abc” package  and expected (He) heterozygosities were estimated using the “hierfstat” package ) and log‐transformed geographic distances, using Mantel tests  per species with ARLEQUIN software. Subsequently, the haplotype network, allowing the reconstruction of genealogic links between haplotypes of each species, was built using the NETWORK software v.5.0.1.1, with the Median Joining method .The five microsatellite markers were successfully amplified for the 200 bat samples with a mean amplification rate of 99.4%. All markers were polymorphic, with the number of alleles ranging between three and 35  individuals suggested two highly supported clades (bootstrap 100%) corresponding to C. leucogaster and C. pusillus  were excluded from the analysis, with an inter‐specific divergence of 7.42% and an intra‐specific divergence of 2.00% and 0.67% within C. pusillus and C. leucogaster, respectively. By including 59 sequences of C. pumilus from Genbank in the phylogenetic tree, we found the same distinct clades of C. pusillus and C. leucogaster  or K = 2 . Similarly, except for the 6 C.leuco.M individuals, all animals identified as C. leucogaster based on morphological characters clustered together (membership proportions ranging from 0.85 to 0.99). The 6 C.leuco.M and two undetermined individuals (2unk) were assigned to the C. pusillus cluster . When considering K = 3  were assigned to the same cluster, while C. pusillus were divided into two different clusters. One cluster (cluster 1) was mainly composed of animals captured on three of the islands in the Comoro archipelago (81%), specifically Grande Comore, Anjouan, and Mohéli. By contrast, the second cluster (cluster 3) was composed of individuals trapped in Mayotte .Although our nuclear markers were limited to five polymorphic loci, the microsatellite data also supported this strong species distinction. STRUCTURE clustering procedure indicated an optimal number of clusters of d Figure . Indeed,3 Figure , all C. FST values were always high and significantly different from zero  and morphological data  bearing the NucDNA of C. pusillus. Among these 53 individuals, all sampled in the Comoros, 47 were morphologically identified as C. pusillus .Finally, the presence or absence of variously sized white spots or patches in the pelage of bats, most often on the ventrum, had no clear relationship with the genotype . We found that the allelic richness of microsatellite loci tended to be lower in C. pusillus than in C. leucogaster  and expected .We further investigated the genetic diversity and structure at the intra‐specific level for each species, assigning individuals to one species based on their assignment following the STRUCTURE analysis  and 33% , low but statistically significant global levels of differentiation  were observed. For both species, all pairwise FST values were, in addition, significantly different from zero .Within‐species population structure was assessed through clustering analyses and  Figures . When coo Figure  and reacC. pusillus clade on Grande Comore and Anjouan; or F and G for C. leucogaster clade on Grande Comore and Mohéli), the most frequent haplotypes . In Malagasy populations of C. leucogaster, haplotype D was predominantly found across the sampled area. Strikingly, three of the rare haplotypes  in the C. leucogaster clade were found in individuals with C. pusillus nuclear DNA. These individuals showing mitonuclear discordance geographically overlapped with the C. pusillus haplotypes throughout the sampled area (Mohéli and Mayotte), except on Anjouan, from which none of the C. leucogaster haplotypes were found. This overlap of C. leucogaster and C. pusillus haplotypes in the Comoro archipelago was also evident by the co‐occurrence of the most frequent haplotypes of each clade in Mayotte.Mitochondrial sequences also suggested a low level of within‐species genetic structure. While specific rare haplotypes were peculiar to some locations  compared with the intra‐specific divergence . Likewise, this genetic distinction was also highlighted by microsatellite‐based population genetics analyses, which indicated the presence of two well‐supported genetic clusters corresponding to morphological identifications . Accordingly, a solid genetic differentiation (FST = 0.25) was detected between the species, and, although this needs to be confirmed with a larger number of sample sizes and polymorphic markers, two alleles seemed private to C. leucogaster. Some inconsistencies were nevertheless detected, including (i) the assignment of individuals to one species based on morphological and NucDNA patterns, while carrying mitochondrial haplotypes of the other species, and (ii) the presence of individuals for which morphological identification and mitochondrial haplotypes were congruent but assigned to nuclear clusters of the other species .Altogether, the genetic analyses performed in the present study indicated that Chaerephon in Mayotte can display white spots or patches in their pelage. In the present study, these individuals were genetically assigned to either C. pusillus or showed mitonuclear discordance between C. leucogaster and C. pusillus. Performing a Principal Components Analysis (PCA) based on four morphological characters  systematically recorded in the field from 85 individuals captured in Mayotte, the results show no apparent difference between individuals with or without the white pelage pattern  found that some individuals of 4.1C. pumilus, Naidoo et al.  across the Mozambique Channel to the Comoro archipelago differentiating into C. pusillus and (ii) to Madagascar differentiating into C. leucogaster. While increasing the number of polymorphic loci will help to robustly infer the colonization history of Chaerephon species in the western Indian Ocean, the presence of C. pusillus carrying C. leucogastermtDNA haplotypes in the Comoros  carried the C. leucogaster from Madagascar to Mayotte led to secondary contact with C. pusillus in Mayotte, closing the colonization ring. Here, we found the largest proportion (74%) of individuals showing mitonuclear discordance in Mayotte compared with the other islands . Of note is that individuals displaying the lowest membership proportions using microsatellites and STRUCTURE software were also sampled in Mayotte . These individuals carried the C. leucogastermtDNA haplotypes, while grouping with the C. pusillus microsatellite‐based cluster, suggesting that they may be hybrids between the two species instead of C. leucogaster sensu stricto. No individual with a clear C. leucogaster phenotype was found in Mayotte, despite the sampling of numerous individuals during two expeditions: (i) in 2014 by the “Centre de recherche et de veille sur les maladies émergentes dans l'océan Indien”  and (ii) in 2015 by the SFEPM . More studies are required to ascertain the establishment of C. leucogaster in Mayotte and better characterize the hybridization pattern between these closely related species.Moreover, Naidoo et al.  previousMyotis myotis and M. blythii , population demography (difference in population size), and physiological features (genetic incompatibilities), especially within the zone of sympatry (Mayotte). Furthermore, a large‐scale analysis using markers from multiple genetic systems , as well as environmental data, should provide the needed insights to disentangle the different ecological and evolutionary mechanisms that contribute to producing asymmetric introgression between these two species.While hybridization is a broad phenomenon in bats due to their social life and mating system . Keeping in mind the inference limitations due to the number of loci used in this study, the low or even absent genetic structure suggests that individuals of this species disperse over long distances, as highlighted by Ratrimomanarivo et al. . This pattern was congruent with the results obtained with mtDNA: two specific mitochondrial haplotypes were found only on Anjouan, while Mohéli and Mayotte showed only one haplotype. These results suggest that the C. pusillus population on Anjouan is probably more isolated. A factor other than distance , identify the classes of hybrids, and test alternative hypotheses that may explain the observed mitonuclear discordances. Indeed, for now, it is not possible to disentangle whether these discordances are the result of asymmetric hybridization or incomplete lineage sorting. Further studies using the approach of demographic inferences would allow discrimination between these processes and new insights into the population structure of C. leucogaster and C. pusillus. One example might include effective population size estimations, which might differ between species, as suggested by the observed differences in genetic diversity. Indeed, mitochondrial sequences and microsatellite loci consistently showed lower levels of genetic variation in C. pusillus than in C. leucogaster. Populations of C. pusillus inhabit small islands (from 290 km2 for Mohéli to 1659 km2 for Grande Comore) as compared to C. leucogaster occurring on Madagascar , and smaller population sizes might thus be expected for C. pusillus, being more susceptible to genetic drift. Finally, our results indicate that some caution is needed for cryptic species, such as the two studied herein, regarding specific identification based only on pelage colouration and morphometric characters, further confounded by different measurement techniques employed by field workers, but these aspects are out of the scope of the current study.Our study brings new insights into the ecology and phylogeography of Morgane Tidière: Data curation ; formal analysis ; visualization ; writing – original draft (lead); writing – review and editing (lead). Elodie Portanier: Data curation ; formal analysis ; visualization ; writing – original draft (lead); writing – review and editing . Stéphanie Jacquet: Data curation ; formal analysis ; visualization ; writing – original draft ; writing – review and editing . Steven M. Goodman: Investigation (lead); writing – review and editing (supporting). Gildas Monnier: Investigation (supporting); writing – review and editing (supporting). Gregory Beuneux: Investigation (supporting); writing – review and editing (supporting). Jean‐François Desmet: Investigation (supporting); writing – review and editing (supporting). Cécile Kaerle: Data curation (supporting); investigation (supporting). Guillaume Queney: Data curation ; investigation . Michel Barataud: Conceptualization (supporting); data curation (lead); writing – review and editing (supporting). Dominique Pontier: Conceptualization (lead); project administration (lead); writing – original draft ; writing – review and editing .The authors declare no competing interest in this work.Appendix S1Click here for additional data file.


Aquaculture production comprises a diverse range of species, geographies, and farming systems. The application of genetics and breeding technologies towards improved production is highly variable, ranging from the use of wild-sourced seed through to advanced family breeding programmes augmented by genomic techniques. This technical variation exists across some of the most highly produced species globally, with several of the top ten global species by volume generally lacking well-managed breeding programmes. Given the well-documented incremental and cumulative benefits of genetic improvement on production, this is a major missed opportunity. This short review focusses on (i) the status of application of selective breeding in the world’s most produced aquaculture species, (ii) the range of genetic technologies available and the opportunities they present, and (iii) a future outlook towards realising the potential contribution of genetic technologies to aquaculture sustainability and global food security. The extent of application of genetic technologies to aquaculture production varies widely by species and geography. Achieving a more universal application of seed derived from scientifically based breeding programmes is an important goal in order to meet increasing global demands for seafood production. This article reviews the status of genetic technologies across the world’s top 10 highly produced species and provides commentary on barriers and future opportunities to achieving this goal.Fish, shellfish and crustacean production via aquaculture has a critical role in meeting the future human demand for animal protein. The global demand for seafood has grown constantly over the past few decades, and in the current context of global population expansion and economic development, this rise in demand is expected to continue . Since wWhile aquaculture as a whole has demonstrated consistent annual growth in production over recent decades, the species and systems underpinning this production are highly variable in technology level. A striking example is the major variability in the use of selective breeding and genetic improvement methods (hereafter referred to as ‘genetic technologies’). Application of genetic technologies to improve farmed animals and crops is considered a cornerstone of sustainable production . InformeSince the turn of the century, the breeding goals of advanced aquaculture programmes have broadened significantly and now include a significant focus on the improvement of host resistance to several infectious diseases . HoweverTo discuss the impact and potential of genetic technologies in aquaculture, it is first important to gain perspective on the geography and species underpinning global production. Asia dominated the world's aquaculture production of fish and shellfish in 2019 (∼90% by volume), and the top ten aquaculture producers (excluding aquatic plants and non-food products) were China (48.2 Mt), India (7.8 Mt), Indonesia (6.0 Mt), Vietnam (4.4 Mt), Bangladesh (2.5 Mt), followed by Egypt (1.6 Mt), Norway (1.5 Mt), Chile (1.4 Mt), Myanmar (1.1 Mt), and Thailand (1 Mt). The majority of food production via aquaculture is finfish, comprising 56.3 Mt (66.0%). In comparison, there were 17.6 Mt of molluscs (20.6%) produced per annum, 10.5 Mt of crustaceans (12.3%) and 1.0 Mt of other aquatic animal species (1.0%). Most aquaculture production is from inland, freshwater systems, comprising 48.4 Mt (56.7%). Unlike terrestrial agriculture where relatively few major species dominate production , a much broader and substantially more evolutionary diverse set of species underpin global aquaculture  . This diWidespread application of genetic technologies has major potential to help meet the continuously increasing global requirement for seafood. Selective breeding offers cumulative and permanent improvement in traits of economic, welfare and environmental importance. The proportion of aquaculture production derived from selective breeding programmes was estimated at 10% approximately a decade ago . While tWhile it is evident that fully closing the lifecycle in captivity is a very challenging milestone for many aquatic species, other features of aquaculture species biology are highly amenable to the application of genetic technologies in well-managed breeding programmes. For example, most species are highly fecund, meaning the potential for high selection intensity and therefore genetic gain with minimal inbreeding. For example, an Atlantic salmon female may produce circa 20 000 eggs, marine finfish such as sea bream hundreds of thousands of eggs per female, and shellfish such as oysters, millions of eggs per female. This fecundity is orders of magnitude higher than for terrestrial livestock, and this presents opportunities to design breeding programmes in different ways, with some similarities to crop species. External fertilisation is often possible which can give flexibility to the design of breeding programmes. For example, powerful tests of genotype by environment interaction can be achieved by splitting full-sibling families into groups and sending each group to a different environment for trait recording. The same so-called sib-testing method allows traits which are difficult or impossible to measure on the selection candidates themselves  to be recorded on very close relatives, facilitating accurate breeding value estimation. However, such reproductive features can also present significant challenges, for example in mass-spawning marine species, where uneven parental contribution and difficulty in tracking individuals during early life require tailoring the breeding programme design accordingly to avoid inbreeding.•Level 1: Seed for production is supplied from wild sources, or hatcheries with limited or no genetic management of stock.•Level 2: Seed supplied from more advanced hatcheries which perform genetic management of stocks to promote genetic diversity and may include some basic directional selection (e.g. for growth of selection candidates).•Level 3: Seed supplied from selective breeding programmes with routine recording of pedigree (by tagging and/or genotyping) to enable estimation of breeding values for production traits via family selection, with a focus on a small number of key traits in the breeding goal.•Level 4: Seed supplied from more advanced selective breeding programmes with a focus on sibling testing, targeting many traits in the breeding goal via a selection index, and routine application of genomic tools, including for marker-assisted and/or genomic selection.As with the five levels of domestication proposed by These levels will be referred to hereafter in the review, including the approximate placement of some of the world’s most highly produced species onto this scale .The factors that drive progression along this genetic technology scale in any given species or market are complex. For example, for a company, industry, or public sector organisation to embark on an organised and advanced breeding programmes, its leaders must (a) be convinced of the technical and performance advantages of the programme, (b) have the funds to invest in the venture over a substantial timeframe, and (c) identify and use the appropriate technical expertise for its development and execution. As a result, the process is typically gradual and can take many years . HoweverThe extent of application of genetic technologies across the world’s top 10 produced aquaculture species is highly variable. As illustrated in In many technical aspects of aquaculture production, the Atlantic salmon industry is the most advanced globally. This includes use of the most advanced genetic technologies, with advanced (level 4) commercially viable breeding programmes supplying the bulk of the industry see . The firQTL) affecting resistance to Infectious Pancreatic Necrosis (IPN) (SNP) arrays , Aquagen  and Hendrix Genetics (Netherlands), tend to supply eggs to the market via separate country-specific breeding programmes, although there is also significant seed supply across countries (e.g. from Iceland to UK or North America). Mowi is one of the world’s largest Atlantic salmon producers and runs its own integrated level 4 breeding programme. These level 4 commercial breeding programmes focus on the simultaneous improvement of many traits, including resistance to several specific pathogens and parasites. In line with the advanced status of the industry, the research and development programmes linked to salmon genetic technologies are also substantial. This has enabled the development and routine application of genomic tools to augment the family selection, with an early success being marker-assisted selection linked to the discovery of a major quantitative trait locus (is (IPN) . Subsequays e.g.  has enabays e.g. , the priThe Atlantic salmon breeding industry is a global exemplar, and in recent years, there has been significant technology and skill transfer towards other major aquaculture species which are progressing through the genetic technology scale. For example, it is notable that several of the same companies or groups of companies running the salmon breeding programmes now also run commercial breeding programmes for tilapia , whiteleg shrimp , and rainbow trout . In the case of Hendrix and EW group, there are additional cross-species interests across livestock and aquaculture, with the companies running breeding programmes for several terrestrial livestock and poultry species.Penaeus monodon), in part due to its increased resistance to infectious diseases. This species currently represents over 75% of all shrimp aquaculture production; most of which takes place in Asian countries, but there is also significant production in Latin America, with Ecuador being one of the top producing countries globally. Domestication and selective breeding programmes began in the 1980s in the USA and Latin America  seed from hatcheries. There is significant international trade and shipment of SPF seed, including from North American hatcheries into Asia, albeit information on the proportion of production derived from selective breeding programmes is difficult to find. The use of SPF seed as a biosecurity tool has been at least partially effective, but as breeding programmes have developed, the term has resulted in some confusion amongst producers as to the relationship between pathogen-free status and disease resistance (SPR)], specific pathogen tolerant (SPT)] is a genetic characteristic of the supplied seed  running an advanced integrated breeding programme. There is also an extensive genomic toolbox of relevance for whiteleg shrimp   , which i rohita) , and invGIFT) strain. The GIFT strain exhibited an 86% increase in growth rate compared to the base population in just five generations , and this testing routinely includes disease challenge models in the more advanced industries . The flagship example of the control of Infectious Pancreatic Necrosis in Atlantic salmon using marker-assisted selection has highlighted the potential of genetic technologies as a solution to disease . It is cIn the 21st century, genomic tools have developed rapidly, and certain aquaculture industries have been near the forefront of their application to farmed animal production. The rapid adoption of molecular genetic markers into aquaculture breeding is partly because the use of genotyping for family assignment and pedigree recording has been commonplace for some industries for many years . For somA second reason for the relatively rapid interest and uptake of genomics technologies into aquaculture breeding has been the successful identification and use of markers linked to the major IPN resistance QTL described above. This use of marker-assisted selection helped the global salmon industry buy-in to the value of molecular genetics, and the role of genetics in general as part of the solution to health challenges . HoweverTo date, the use of genomics has enabled the establishment of level 3 and level 4 breeding programmes in species where physical family tracking is difficult or impossible , and also for improved rates of genetic gain in the most advanced breeding programmes . The workhorse genotyping tool for genomic selection is a SNP array, and these are only available for four of the top 10 most produced aquaculture species . A relatSolutions to reduce the cost of genomic tools to aquaculture breeding programmes are important to facilitate broader uptake globally, and to democratise genomics and its benefits. Several potentially complementary strategies have been explored to this end. Firstly, since per-unit cost of a SNP array is dependent on the order volume, combining SNPs from multiple species onto a single array is cheaper, for example, the recentlydeveloped combined European sea bass and sea bream array , and theThese low-cost genotyping approaches can facilitate the use of combined-purpose SNP panels to support developing aquaculture breeding programmes. For example, the few hundred SNPs used as the basis for genotype imputation could also be applied for pedigree construction in mixed-family environments. This in turn may save on labour and infrastructure costs associated with tagging and/or separate rearing of families. Those same SNP panels could also be enriched for known QTL-linked markers for major effect QTL identified in the species of interest, meaning that marker-assisted selection could be combined with (genomic) breeding value estimation to further improve genetic gain for target traits. In this sense, multi-purpose SNP panels may be an enabling tool to support design and establishment of level 3 and level 4 breeding programmes from the outset, rather than a sequential add-on to an existing programme. As such, genomics has a significant role to play in supporting the uptake of genetic technologies in aquaculture, and continued efforts towards low-cost and practical genotyping approaches are essential.The factors influencing the uptake of genetic technologies for a particular species or geography are complex, depending on factors such as the value and market for the product, whether farming is extensive or intensive, and the economic and socio-cultural situation. Private sector commercial breeding programmes are currently limited to relatively few species, albeit this number is growing as the importance of genetics in production is increasingly recognised. The sheer number and the diversity of species comprising global aquaculture present challenges, due to the requirement to develop programmes and tools tailored to the biology of each species . CommercIn addition to the private sector, there are various academic, national, and international breeding programmes developed and supported with public funds. For example, WorldFish is an international CGIAR organisation who produce and disseminate genetically improved tilapia and various carp species, typically to low- and middle-income countries. As discussed above in the context of carp and catfish species, public sector investment into genetic technologies for aquaculture is likely to be a sound investment in the sustainability of food production for a given country or region . However, noting that modern selective breeding programmes are continuous processes, resulting in cumulative and permanent improvements in production traits, the development of a specific strain with particular characteristics should not be considered an end point, as improvements in production traits can continue each generation with level 3 and 4 programmes. As such, the ongoing and stable commitment of resources are required to support these breeding programmes. Public-private partnerships may form part of the solution to achieving this sustainable investment into genetic technologies, leading to an increase in the proportion of the global aquaculture industry using level 3 or level 4 programmes.The past decade has seen significant focus placed on the use of genomics in aquaculture breeding, with some highly impressive results. As discussed above, genomics still has a major enabling role to play across many species and sectors and can help support fledgling breeding programmes from the outset. However, arguably any future innovation in the use of genomics to predict breeding values is likely to be leading towards improved efficiency of the process, for example lower cost genotyping and phenotyping. There may be incremental gains arising from use of functional genomics and prioritisation of putative functional variants in prediction models, but results from livestock breeding have been underwhelming to date. As such, the use of genomic and marker-assisted selection can be considered relatively mature technologies in advanced aquaculture breeding programmes. In the coming years, it is likely that particular emphasis will be placed on improving phenotyping technologies to provide more refined target traits for breeding goals . For exahttps://nofima.com/projects/crispresist/). If successful, and a lice-resistant salmon strain is developed, then this solves a major industry barrier causing vast economic, welfare, and environmental problems.Genome-editing tools such as CRISPR-Cas have significant potential for applications to improve welfare and production traits in aquaculture and are likely to be widely adopted into the sector in the coming decade. In Japan, the sale of genome-edited tiger puffer and red sea bream – both of which have targeted mutations to improve growth rate – has recently been approved . While ede novo variation that can have a major impact via modification of a target gene’s activity in the absence of any known segregating QTL. This can be achieved using a hypothesis-driven approach; for example as was applied to modify a domain of the putative cellular receptor to develop complete resistance to the porcine reproductive and respiratory virus in pigs (GeCKO) approach can be used to identify de novo targets essential for host-pathogen interaction  is still based on fairly basic genetic technologies. Broader uptake of genetics in less valuable sectors may be assisted via integrated or cooperative breeding programmes for producers, public–private partnership, or with external genetic service management. Genomics can be an enabling tool to support genetic improvement, especially with multi-purpose marker panels to allow pedigree construction in tandem with low-cost marker-assisted and genomic selection. In the advanced aquaculture sectors, genomic selection is now nearing maturity and will become more efficient and lower cost over the coming years. This timeframe is also likely to see an increased focus on improving phenotypes, and associated high-throughput phenotyping and data capture technologies. Genome editing may be the next disruptive technology for the second quarter of the century, offering potential solutions to some of the industry’s biggest sustainability challenges. However, major effort is required to integrate genome editing into well-managed breeding programmes. Genetic technologies remain hugely underexploited, and addressing this should remain a priority to realise the potential contribution of aquaculture to global food security challenges.Not applicable.Not applicable.RDH: 0000-0003-1805-0762CK: 0000-0003-2277-2311DR: 0000-0002-9616-5912.RDH: Conceptualisation, Writing – Original Draft, Writing – Review and EditingCK: Conceptualisation, Writing – Original Draft, Writing – Review and EditingDR: Conceptualisation, Writing – Original Draft, Writing – Review and Editing.None.None.The authors were supported by Biotechnology and Biological Sciences funding to The Roslin Institute .


CaliPopGen is a database of population genetic data for native and naturalized eukaryotic species in California, USA. It summarizes the published literature (1985–2020) for 5,453 unique populations with genetic data from more than 187,394 individuals and 448 species (513 species plus subspecies) across molecular markers including allozymes, RFLPs, mtDNA, microsatellites, nDNA, and SNPs. Terrestrial habitats accounted for the majority (46.4%) of the genetic data. Taxonomic groups with the greatest representation were Magnoliophyta (20.31%), Insecta (13.4%), and Actinopterygii (12.85%). CaliPopGen also reports life-history data for most included species to enable analyses of the drivers of genetic diversity across the state. The large number of populations and wide taxonomic breadth will facilitate explorations of ecological patterns and processes across the varied geography of California. CaliPopGen covers all terrestrial and marine ecoregions of California and has a greater density of species and georeferenced populations than any previously published population genetic database. It is thus uniquely suited to inform conservation management at the regional and state levels across taxonomic groups.  It is often divided into 19 terrestrial and three marine ecoregions, reflecting its tremendous geologic and ecological diversity3, including the highest and lowest elevations in the contiguous U.S., extreme deserts and temperate rainforests, and mean annual precipitation ranging from 150 mm–1200 mm4. California is the most populous state in the USA, accommodating roughly 12% of the nation’s human population; the third largest state geographically, encompassing 5% of the country’s continental land area; and is a major agricultural producer. This combination of high species richness and human-mediated pressures constitute a persistent threat to the short- and long-term persistence of biodiversity, and has led to California’s inclusion as one of only two global biodiversity hotspots in the USA6. Perhaps unsurprisingly, California has the greatest number of documented and possibly extinct species of vascular plants7, and more than twice as many federally protected species  as any other state8. It has also been the focus of more population genetic studies, including states with similarly high numbers of threatened/endangered species like Florida and Hawaii1. However, this wealth of genetic information has never been adequately summarized or made publicly available. The few broadly comparative analyses for California have largely been based on inferences derived from fewer than 10 species12, with the exceptions of one review13, and one empirical study14, both of which were restricted to marine taxa. California is a perennial leader in biodiversity management, and our compilation of genetic data for the state aligns with the administrative level at which environmental legislation and biodiversity management is implemented, increasing the likelihood that the CaliPopGen database will inform conservation actions.The CaliPopGen database consists of four datasets that contain estimates of population genetic diversity, differentiation, and life history traits for 448 eukaryotic species sampled across California, USA. The state has exceptionally high plant and animal biodiversity, and a correspondingly large number of endangered taxa15, mammals16, mammals and amphibians17, vertebrates18, and birds, fishes, insects and mammals19. Its focus at the regional (state) level is unique. The CaliPopGen database also includes a wider range of molecular markers  or single marker types . Our inclusion of all available marker types both reflects the change in methodological approaches through time , and presents opportunities for quantitative comparisons among different marker types.In compiling CaliPopGen, we examined 4,942 published studies identified by our search criteria in the Web of Science, of which 450 met our final inclusion criteria and are included in the database. The majority of genetic samples represented in this database were collected from 1995–2015 (ranging from 1888–2019), and all studies were published between 1983–2020. CaliPopGen contains information on more than 187,394 individuals from 5,453 unique populations, of which 5,276 are spatially georeferenced. These populations include terrestrial (46.6%), marine (21.9%), freshwater (14.1%), amphibious (9.7%), and diadromous (7.7%) populations of fungi (<2% of unique species), chromists (<2%), plants (23%), and animals  than the aforementioned studies and databases. This high spatial density of samples across the full ecological scope of California , populations , and individuals  for relevant literature from 1900 to 2020 with the terms: topic =  AND topic = (genetic* OR genomic*) AND topic = (species OR taxa* OR population*). We included only empirical peer-reviewed literature and excluded unreviewed preprints. In using these search terms, our goal was to broadly identify genetic papers focused on California with population or species-level analyses, while avoiding purely phylogenetic studies or those focused on agricultural or model species. This resulted in 4,942 unique records.Figure We next screened titles and abstracts to retain articles that: (1) provided data on populations of species which are self-sustaining without anthropogenic involvement; (2) included at least some eukaryote species; (3) included population(s) sampled within California; (4) mentioned measures of genetic diversity or differentiation; and (5) were not reviews (thus restricting our search to only primary literature). We retained 1869 studies after this first pass of literature screening .Our second, more in-depth screening pass involved reading the full text of these 1869 studies. We had two goals. First, we confirmed that retained papers fully met all five of our inclusion criteria . Second, we eliminated papers where the data were not presented in a way that allowed us to extract population-level information. For example, many of the more systematics-focused studies pooled samples from large, somewhat ill-defined regions ; if such regions were larger than 50 km in a linear dimension, we deemed them unusable for making geographically-informative inferences. Other studies presented summaries of population data, often in the form of phylogenetic networks or trees, but did not include information on actual population genetic parameters and therefore were not relevant to our database. We retained 528 publications after this second pass.). This included Latin binomial/trinomial, English common name, population identifiers, and geographic coordinates of sampling sites. We also noted population/sampling localities that were interpreted as comprised of interspecific hybrids, and listed both parental species. We collected population genetic diversity and differentiation statistics for each unique genetic marker for each population/sampling locality; as a result, a sampling locality may have multiple entry rows, one for each locus or marker type. Parameters extracted for each population/marker combination include sample size, genetic marker type, gene targets, number of loci, years of sampling, and reported values for effective population size (Ne), expected (HE) and observed  heterozygosity, nucleotide diversity , alleles-per-locus (APL), allelic richness (AR), percent polymorphic loci (PPL), haplotype diversity (HDIV), inbreeding coefficient , and pairwise population genetic comparison parameters . We note that while there are technical differences between allelic richness and alleles-per-locus, source literature often used the terms interchangeably, and we include the parameters and their values as named in the source. We define marker type as the general category of genetic marker used , while gene targets are the specific locus/loci . We present these data in two separate datasets, one containing all population-level genetic summary statistics  to georeference localities based on either in-text descriptions or embedded figure maps guided by permanent landmarks like a bend in a river or administrative boundaries. Because this can only yield approximate coordinates, we recorded estimated accuracy as the radius of our best estimate of possible error in kilometers. If coordinates were provided in degree/minute/seconds, we used Google Maps to translate them to decimal degrees. In cases where coordinates were not provided and locality descriptions were too vague to determine coordinates with less than 50 km estimated coordinate error, we did not attempt to extract coordinates but still provide the genetic data. All coordinates are provided in the web Mercator projection (EPSG:3857). We excluded studies that reported genetic parameter values only for samples aggregated regionally . If marker type was not explicitly included, we classified marker type based on the gene targets reported, if provided.All genetic data were extracted directly from the source literature. However, we also updated or added to the metadata for these population genetic values in several ways. We included kingdom, phylum, and a lower-level taxonomic grouping for each species , and updated scientific and common names based on the currently accepted taxonomy of the Global Biodiversity Information FacilityDataset 321) and plant (Dataset 421) species contained in Datasets 121and 221. We assembled trait data that have previously been shown to correlate with genetic diversity, including those related to reproduction, life cycle, and body size, as well as conservation status . Life history data were compiled by first referencing large online repositories, often specific to taxonomic groups, like the TRY plant trait database27, and the Royal Botanic Gardens Kew Seed Information Database28. If trait data for species of interest were unavailable from these compilations, we conducted keyword literature searches for each combination of species and life history trait, and extracted data from the primary literature. When data were not available for the subspecies or species for which we had genetic data, we report values for the next closest taxonomic level, up to and including family, as available in the literature.To increase the utility of CaliPopGen, we also assembled data on life history traits for all animal , a species could reasonably be placed in more than one category, and we did our best to identify the primary life history category for such taxa. If the taxonomic identity of an entry was hybrid between species or subspecies, this was noted in the speciesID column and no life history data were reported.Dataset 321  shows the total number of unique populations in each California terrestrial ecoregion. Panel (C) depicts all data entries of Population Genetic Diversity Dataset 121, summed for each 20x20 km grid cell. Panel (D) shows the density of pairwise straight lines drawn between pairs of localities in the Pairwise Population Differentiation Dataset 221, depicted as the total number of lines per 20x20 km grid cell. The number of populations and species of both Datasets 121& 221 are summarized for each marine and terrestrial ecoregion in Table We used the R-package raster v3.1–5) to visualize the spatial extent of the data in CaliPopGen in Fig. .1–5 to vDataset 321) and plants (Dataset 421) have also been included in Dataset 121 and Dataset 221. We combined the genetic and life history data under the assumption that potential users may want to examine correlations between these two classes of data. Dataset 121: The Population Genetic Diversity dataset consists of 101 columns, described in Table Dataset 321 and Dataset 421, respectively, see below).The CaliPopGen database comprises four datasets, which are hosted at Figshare and can be downloaded as XLSX, TSV and CSV files. For convenience, the life history trait data for both animals .Dataset 321: The Animal Life History Traits dataset consists of 45 columns, containing data for 432 species and subspecies, and is described in Table Dataset 421: The Plant Life History Traits dataset consists of 37 columns containing data for 177 species and is described in Table Dataset 321& 421 are higher than the number of species of Dataset 121& 221 because we left species in these datasets even though their genetic entries may have been excluded based on the criteria set out in the Methods.During the first step in our screening protocol based on titles and abstracts see Fig. , we examAs might be expected, intra-individual repeatability  was higher than inter-individual reproducibility : 92.6% (50/54) of papers re-screened by the same individual received an identical score whereas 74.8% (315/421) of papers re-screened by a different individual received an identical score. Across both of these exercises, 17.5% of articles that were re-screened by either the same or different individual  were assigned to different categories between the first and second screening. For the inter-individual analyses, 27.7% of “possibly include” articles changed status when screened by different individuals, while only 16.0% of “reject” and 16.3% of “include” decisions changed. However, when we subsequently attempted to extract data during the Data Collection Phase, we did so from both “include” and “possibly include” papers, so the relatively low change of “reject” status makes us comfortable that screener variability and its potential bias had at most a very limited impact in our decision pipeline.HO of microsatellite markers in Aves was examined separately from HO of mitochondrial markers in Reptilia), and we examined life history trait distributions separately for each taxonomic group. In all cases, we identified outliers as values greater or less than the upper or lower quartiles +/− 1.5 * IQR (IQR = inter-quartile range), using the function boxplot.stats in the R-package grDevices. For all identified outliers we returned to the original source publication to confirm that values were as reported, or corrected them if they were a data-entry error. Correctly transcribed values falling outside of their theoretical bounds  were left unaltered, which users of the CaliPopGen databases should consider carefully in using these results.To identify and correct potential recording errors in the datasets after the initial round of data extraction, we flagged numerical outliers and values outside of theoretical expectations for all genetic parameters and life history traits. Both outliers and values outside theoretical bounds may represent values as reported in the original publication, or they may be transcription errors as we compiled datasets. To increase the likelihood of identifying errors via outlier analysis, we examined each genetic parameter distribution separately for each marker type and taxonomic group (for example,


The Polish draft horse (PDH) breed is a result of crossing local mares with imported cold-blooded stallions. In this study, we investigate the genetic composition of the PDH by analyzing whole mitochondrial d-loop variabilities and comparing these variabilities to previously demonstrated whole d-loop sequences of other cold-blooded breeds: Ardennais, Belgian, Breton, Clydesdale, Noriker, Norwegian Fjord, Percheron, and Suffolk. Our results show high nucleotide diversity among the PDH population and the existence of two main haplogroups with strong kinship to the Belgian breed.The Polish draft horse (PDH) breed is a result of crossing local mares with imported cold-blooded stallions, such as Belgians, Ardennes, Fjords, and others. A part of the broodmare stock investigated in this study was also imported from various countries, such as Denmark. In this study, we investigate the genetic composition of the PDH by analyzing the whole mitochondrial d-loop variability and comparing it to previously demonstrated whole d-loop sequences of other cold-blooded breeds: Ardennais, Belgian, Breton, Clydesdale, Noriker, Norwegian Fjord, Percheron, and Suffolk. Our results show high nucleotide diversity within the PDH population (π = 0.011), and the existence of two main haplogroups: one of relatively concise origin, with strong kinship to the Belgian breed, and the second showing close relation to the majority of other analyzed cold-blooded breeds. Some of the PDH maternal strains clustered separately, which can be a result of the influence of other unidentified breeds that served as a foundation stock for the present population. This present study explains the genetic relationship of the PDH to other cold-blooded breeds and indicates the high genetic diversity of the breed. Draft horses  are undoubtedly part of European culture. For centuries, the horses’ phenotypes have been influenced by breeder selection to meet the requirements of the tasks the animals were being bred to perform. Until the Industrial Revolution, horses were used for transportation, the military, agriculture, and heavy industry purposes. However, with the progress of mechanization, especially in the areas of military, agriculture, and heavy industry, followed by the World Wars, the number of horses globally has dramatically decreased. Their selection goals have shifted towards leisure and sport . The pophttps://www.pzhk.pl/hodowla/statystyka-hodowlana/ (accessed on 5 May 2022)”). However, the organization of animal production in the period between 1945 and 1989 focused mainly on State Studs, with the private breeding sector maintaining horses for work with little addition for breeding. As systematic breeding work was carried out, there was a genetic consolidation of the herd and phenotypic equalization of the population. Recently, that breed emerged into two subtypes, named Sokólski and Sztumski [The Polish cold-blooded horse subpopulation began to form in the middle of the 19th century based on native, working horses, refined with imported cold-blooded horses, mainly from Belgium, France, and Germany . The namSztumski .Some recently evolved tools in the field of molecular genetics have led to the intensive study of the genetic diversity of breeds, which is crucial for maintaining the endangered and low-numbered breeds . HoweverThe mtDNA in equines is a 16,660 bp circular genome, containing 13 intron-less protein-coding genes that are part of 5 protein complexes, 22 transfer RNAs, 2 ribosomal RNAs, and the control region . The d-loop itself is approx. 1200 bp long, containing the regulatory elements for replication and transcription with two hypervariable segments (HVR1 and HVR2), a large conserved sequence block, and three small conserved sequence blocks with tandem repeats of an 8 bp equine-specific sequence TGTGCACC between ,11. ThisTo date, most studies focused on the most variable region of mtDNA, the approximately 350–600 bp-long hypervariable region 1 (HVR1) of the d-loop. This part has been sequenced to explore the diversity of different breeds from past and present, including Italian Heavy Draught, Sardinian Anglo-Arab, Finnish, Tibetan, Polish Konik, and many others horse breeds ,13,14,15The hair follicles (between 5 and 10 per sample) or whole blood samples from all horses came from the same collections of the reference horse database of the Laboratory of Molecular Genetics, Department of Animal Molecular Biology, and the Biological Material Bank of the National Research Institute of Animal Production. The experimental protocol was approved by the Animal Care and Use Committee of the Institute of Pharmacology, Polish Academy of Sciences in Cracow (no. 1173/2015).A total of 72 horses were included in the study. All horses were entered into the main section of the Polish cold-blood Horse Studbook and were the property of a strategic state-owned company, specializing in PDH (Sztumski type) breeding. The sample consisted of all horses available at the farm at the moment of the sample collection. The biological material collected for the purposes of the study was 5 ml of jugular blood, collected to sterile tubes with EDTA as an anticoagulant, or hair follicle. n = 26), including breeds indicated as ancestral or related to Polish cold-bloods (Belgian (n = 9), Norwegian Fjord (n = 2), Breton (n = 1), Percheron (n = 1), Ardennais (n = 1), and Suffolk (n = 1)) as well as other modern cold-blood breeds (Noriker (n = 5) and Clydesdale (n = 6)). The GenBank X79547.1 Equus caballus reference sequence [To identify more complex phylogenetic relationships, we additionally retrieved all the complete d-loop sequences available in GenBank ”) [https://blast.ncbi.nlm.nih.gov, (accessed on 13 September 2021)” [Genomic DNA was purified using a Sherlock AX kit  according to the manufacturer’s protocol, with the use of 100 µL of whole blood or hair follicle. The quality and quantity of extracted DNA were measured with a NanoDrop 2000 spectrophotometer . For the detection of variation, primers covering the hypervariable regions (HVR1-HVR2) of the d-loop were designed using the Primer3Plus program (“Software. Available online:  2021)”) , with th 2021)”)  and to cr 2021)” . The seqThe numbers of segregating and parsimony-informative sites, as well as haplotype diversity and nucleotide diversity (intra- and inter-populations), were calculated using DnaSP v.6 . The neuTo visualize the phylogenetic relationship between analyzed haplotypes, we constructed the neighbor-joining tree using Mega11 , as wellThe raw sequence obtained by Sanger Sequencing and sequences from GenBank were trimmed for comparison, and finally, the part of mitochondrial DNA located between 15490 and 16650 bp (1160 sites) of the entire loop was included for further analysis. The novel sequences of investigated maternal lines were deposited in GenBank under the numbers: ON052711–ON052725.Among the segregating sites, we also identified four mutational hotspots previously described located at positions 15585, 15597, 15650, and 15659 , and theBased on the sequencing results, Polish draft horses included in this study clustered into 15 distinct haplotypes .p = 0.940). The nucleotide diversity reached the value of π = 0.011.The variation analysis of the Polish draft horse subpopulation revealed 46 segregating sites and 32 parsimony-informative sites, which corresponds with Tajima’s D = −0.114  and imported from Belgium, Denmark, Finland, the Netherlands, Norway, and Sweden . ConsistAmong all the analyzed Polish cold-blood horses, 15 distinct haplotypes have been determined with quite a high percentage of diversity. Bronowa and Jabłonka were separated by only one segregating site, so the difference between these two haplotypes may be a result of a genetic drift . OverallUnderstanding the mode of inheritance of mtDNA through only maternal lines leads to an extended image of the cold-blooded horse genetic pool. The group, consisting of many breeds representing different origins, has been interbred for centuries. After the analysis of numerous genomes, the relationships between them become visible, as well as the role of a single group in the whole breed phylogeny. We believe that including the mtDNA information in the studbook would benefit the breeding management of any horse breed, including the PDH.Determining more detailed phylogenetic history of the modern PDH may be an interesting subject for further research, as some of the analyzed haplotypes clustered in separate branches of the phylogenetic tree. However, sequences of the potential maternal ancestors representing local, more primitive types may be difficult to obtain, as the majority of Polish primitive horses became extinct more than 50 years ago.Our results have shown the uniqueness of the Polish draft horses’ mitochondrial genome among other breeds and confirmed the multi-breed admixture in the gene pool. Poland’s geographical location in the center of the continent gave the populations a great opportunity for genetic exchange in multiple directions. Polish draft horses used in the present study may be considered relicts with their rich genealogy and, thus, deserve special protection in terms of genetic resources.


Sus scrofa). ASF has been spreading in Lithuania since its introduction, therefore it is important to understand any genetic impact of ASF outbreaks on wild boar populations. The aim of this study was to assess how the propensity for an outbreak has shaped genetic variation in the wild boar population. A total of 491 wild boar samples were collected and genotyped using 16 STR markers. Allele richness varied between 15 and 51, and all SSR loci revealed a significant deviation from the Hardy–Weinberg equilibrium. Fixation indices indicated a significant reduction in heterozygosity within and between subpopulations. PCoA and STRUCTURE analysis demonstrated genetic differences between the western region which had had no outbreaks (restricted zone I) and the region with ASF infection (restricted zones II and III). It is concluded that environmental factors may play a particular role in shaping the regional gene flow and influence the genetic structure of the wild boar population in the region with ASF outbreaks.The emergence of African swine fever (ASF) in Lithuania and its subsequent persistence has led to a decline in the population of wild boar ( Sus scrofa), one of the most abundant ungulates in Europe, plays an important role in the ecosystem [Sus scrofa is a species that has positive effects on natural communities [S. scrofa populations.Wild boar  as follows: Part I , Part II  and Part III  . During the analysis, the spatial and temporal distributions of ASF in wild boars in Lithuania in the period from 2014 to 2018 were taken into account. The affected area was divided into restriction zones based on the Annex to Decision 2014/709/EU (g areas) . Blood sWild boar samples were collected from various parts of Lithuania that have experienced varying rates of ASF spread. In some regions, wild boar subpopulations have experienced frequent and widespread outbreak events, while others in the least affected regions have had infrequent and local outbreaks. For each sample, the collection date and site were noted. The GPS coordinates of the sampling sites were used where possible. The number of samples, sampling period, and their sources of origin from all sampling sites are illustrated in Blood samples were collected in vacutainer tubes that contained EDTA  and were stored at +4 °C until DNA extraction was performed. Tissue samples were preserved in 96% ethanol and stored at −20 °C. Total genomic DNA was isolated from blood and tissue samples using the DNeasy Blood and Tissue Kit  following the manufacturer’s instructions. The quantity and purity of isolated DNA were checked with a NanoDrop 2000 spectrophotometer . Extracted DNA was stored at −20 °C until PCR amplification.All samples were genotyped for 16 microsatellite loci recommended by the International Society of Animal Genetics (ISAG)—Food and Agriculture Organization (FAO) . DNA wasG), expected heterozygosity (He), heterozygosity (Ho), inbreeding coefficient measured as the deviation from random mating (Fis), and the polymorphism information content (PIC) [e) and the number of private alleles (Ap) were calculated using GenAleX 6.51b2 software [r) was calculated using FSTAT, version 2.9.3.2 [p-values were adjusted using a Bonferroni sequential correction for multiple comparisons, with an initial probability of p = 0.05 [Genetic diversity and polymorphism were analysed by locus and population. The genetic data analysed using Power Marker Software Version 3.25 were the major allele frequency (MAF), number of genotypes (Nnt (PIC) . The effsoftware . Allelic 2.9.3.2 . All dep 2.9.3.2 . The p-vp = 0.05 . To estip = 0.05  and the p = 0.05  null allp = 0.05. The exact test of population differentiation based on genotype frequencies was determined through 100,000 steps in a Markov chain and 10,000 dememorisation steps. GenAlEx was also used to perform a pairwise population matrix based on Nei’s genetic distance and to construct principal coordinates analysis (PCoA).The genetic structure of the wild boar population was assessed by means of the analysis of molecular variance (AMOVA), F-statistics, pairwise population comparisons, population differentiation and graphical representation using ARLEQUIN version 3.5.2.2 . The staThe population genetic structure was analysed with STRUCTURE 2.3.4 , using ar , and the sampling site at Klaipėda generated the lowest Ar (7.954) (e) ranged from 4.748 to 7.286, with a mean of 5.719. The highest Ae was observed at the Alytus sampling site, while the lowest Ae was from the Klaipėda sampling site. Among the private alleles, almost half (41.89 %) were found at two sampling sites (Vilnius and Panevėžys). Observed (Ho) and expected (He) heterozygosity values per sampling site varied from 0.568 (Utena) to 0.662 (Tauragė) and from 0.714 (Klaipėda) to 0.837 (Kaunas), respectively  had the highest A (7.954) . MAF varectively . Highly ectively . A high r) ranged from 7.619 (sw830) to 23.046 (s0005), with a mean of 12.230, He values ranged from 0.683 to 0.944 , and Ho values from 0.405 to 0.798 . The polymorphic information content (PIC) of the loci ranged from 0.664 in sw2410 to 0.942 in s0005, where the highest number of alleles per locus was observed in this study. Results showed that polymorphic information content (PIC) values were greater than 0.5 at every locus, which makes them useful in genetic diversity studies. The inbreeding coefficient across loci (Fis) ranged from 0.155 (s0005) to 0.408 (sw2410), with an average Fis of 0.255  and 51 (s0005). The value of allelic richness  had potential null alleles at a high frequency (r > 0.2) in at least one subpopulation. These loci with null alleles were excluded from further analyses. The frequencies of the remaining microsatellite loci were below 0.20. st, Fis and Fit of 0.054, 0.175 and 0.220, respectively. All three indices showed statistically highly significant differences (p < 0.001) from zero among and within all sampling sites, indicating that there was a loss of heterozygosity in the wild boar population and increased inbreeding among the subpopulations. Analysis of molecular variance (AMOVA) revealed that the variation among the sampling sites (Va) was 5.42%, the variation among individuals within locations (Vb) was 16.61%, and the variation within individuals was 77.97% . The fixp < 0.05) genetic differentiation compared with all other sampling sites was observed at two sites: Telšiai and Klaipėda. Pairwise Fst values varied from 0.010 to 0.123 between the Telšiai sampling site and other sampling sites, and from 0.010 to 0.147 between the Klaipėda sampling site and other sampling sites. Several pairwise sampling sites with Fst < 0.05 indicated that the genetic differentiation between them was small and insignificant  of genetic differentiation among the sampling sites . The lownificant .The pairwise Nei’s (1983) genetic distances ranged from 0.071 to 0.768 between sampling sites . The smaPrincipal coordinates analysis (PCoA) was performed to provide the genetic structure among all wild boar samples. The first three principal components explained 10.37%, 3.03% and 7.19% of the total variance, respectively . The PCAIn the structure analysis, LnP(D) and ΔK statistics were used to determine the most likely value of population genetic cluster K. As the LnP(D) increased from K = 1 to 5, the true number of genetic clusters (K) was difficult to determine. However, the ΔK statistic of Evanno et al.  detectedMore comprehensive sampling compared with a previous study undertaken and the high number of STR markers used produced 491 individual multilocus genotypes of wild boars across Lithuania. The analysis of genetic diversity and the population structure of wild boars was conducted with regard to the different prevalence estimates of ASF in affected areas of the country. This study aimed to extend the previous study  and obtaIn this study, the wild boar sample collection still retained a reasonable amount of genetic variation, with allele richness of 15 to 51 alleles per locus and an average PIC of 0.819. Genetic parameters such as allelic richness (Ar), number of effective alleles (Ae) and the polymorphic information content (PIC) had lower values at the three sampling sites  in the western part of the country. Another measure of genetic variability is expected heterozygosity, with the highest value (0.837) found at the Kaunas sampling site and the lowest (0.714) at the Klaipėda sampling site. The values of this genetic diversity parameter were slightly higher than those determined in a recent study (He = 0.667), which showed the genetic structure of the wild boar population before the ASF outbreak . Howeverhttps://am.lrv.lt, accessed on 5 May 2022). The previous analysis indicated that in Lithuania the number of ASF-positive wild boar carcasses ranged from 20.2% in 2014 to 79.7% in 2017 [All SSR loci (100%) revealed a significant deviation from HWE after Bonferroni correction. This finding was consistent with previous studies ,23,24,40 in 2017 . Selecti in 2017 . Since 2 in 2017 . As prev in 2017 . Small e in 2017 . The presence of null alleles might reduce the genetic diversity within populations and cause an overestimation of population differentiation . In thisp < 0.001) of inbreeding among individuals within the population (Fis = 0.175). Similar findings have also been reported for the same species in the earlier study conducted before the ASF outbreak in Lithuania [In the present study, the fixation indices Fst, Fis and Fit indicated a significant reduction in heterozygosity within and between subpopulations. Fis values significantly higher than zero indicate more inbreeding than would be expected at random . As reflithuania .With regard to all pairwise differences (linearised Fst) in this study, the distribution of Fst represented moderate genetic divergence (0.000 < Fst < 0.147) between sampling sites in general. Fst was observed to be small between sampling sites in western Lithuania and had a greater differentiation from the rest of the sampling sites. From a genetic viewpoint, population genetic differentiation can arise from migration, geographical barriers, genetic drift and gene mutation . A recenIn this study, the analysis with the STRUCTURE program showed that the population of wild boar in Lithuania is grouped into three major lineages when K = 3 a,b. The This study assessed the genetic diversity and population structure of wild boars following the emergence of ASF using microsatellite markers. To examine changes in the population’s genetic structure, the findings were compared with the genetic structure of the wild boar population studied before the ASF outbreak. Sampling sites in the western part of Lithuania (a region with no ASF infections) were found to be genetically distinct from other parts of the country (regions infected with ASF), while in the earlier study, no differentiation between sampling sites was found. These findings suggest that environmental factors play a particular role in shaping regional gene flow and influence the genetic structure of Lithuania’s wild boar population.


This paper reported genetic parameters of four Senegalese sheep breeds, in relation to inbreeding, diversity and genetic proximity. The results provide informations on genetic conservation and adaptability of the breeds in the Senegalese context.In Senegal, sheep breeds have adapted to their environment and play a key socio-economic role. This study aimed to explore the genetic diversity and structure of four Senegalese sheep breeds  and their relationships with global sheep breeds. To that end, forty-seven sheep were genotyped using the OvineSNP50 BeadChip, and these genotypic data were analysed with those of 73 sheep breeds representative of worldwide ovine diversity . The average observed heterozygosity (Ho) ranged from 0.293 in Djallonke sheep to 0.339 in Touabire sheep. The estimated Fis values were low, ranging from 0.019 for Ladoum to 0.034 for Peul-peul sheep. The estimated Fst values were low (0.003–0.044) among the trypanosusceptible breeds  but high between the previous breeds and the trypanotolerant Djallonke breed (0.075–0.116), indicating better genetic conservation of the Djallonke sheep. A principal component analysis revealed clustering of the Senegalese sheep breeds according to their geographic distribution. However, owing to genetic improvement practices, the introgression of Touabire sheep blood seems to have reshaped the genetic landscape of the trypanosusceptible sheep breeds in Senegal. The Senegalese sheep breeds showed lower genetic diversity than their presumed ancestral sheep breeds of the Middle East. They also presented some relatedness with Caribbean sheep breeds, which reveals their contribution to the global genetic diversity and to the development of Caribbean sheep breeds. Sheep, the most commonly farmed species after poultry, play a crucial socio-economic role in Senegal. In addition to their economic value, sheep are the preferred meat among Senegalese consumers  and the The sheep breeds traditionally raised in Senegal include Peul-peul and Djallonke, which are thin-tailed and domesticated in the central Fertile Crescent. They are thought to descend from the Asiatic mouflon  . AccordiThe genetic characterisation of these local breeds is an essential step toward providing guidelines for future conservation and improving the management of sheep genetic diversity. Early studies on Senegalese sheep breeds used morphometric traits ,12 or blHere, we aim to explore the genetic diversity, population structure, and relationships among the main Senegalese sheep breeds—the two local breeds Djallonke and Peul-peul, the newly developed breed Ladoum, and Touabire sheep imported from Mauritania—using a newly developed genotyping dataset. We analysed 47 unrelated Senegalese sheep by genotyping using OvineSNP50 BeadChip from Illumina and combined these genotypes with those of 73 other sheep populations representative of the sheep genetic diversity.Four sheep breeds were sampled in this study: Djallonke (DJA), Peul-peul (PEU), Touabire (TOU), and Ladoum (LAD). In Senegal, Djallonke sheep are primarily found in Casamance. The Kolda Region, where the Animal Production Research Centre of Kolda hosts technical facilities for blood sampling (n = 12), was the focus of our study. Peul-peul sheep are found in tsetse fly-free zones of rural areas. For this breed, blood sampling (n = 12) was conducted in Dahra in the Djolof, known as the breed birthplace. This blood sampling was organised by the Animal Production Research Centre of Dahra (CRZ-D). One blood sample was collected per village, with a minimum distance of 12 km between two villages, except for the Ladoum breed, due to its in-city geographical dispersion. Ladoum blood samples (n = 12) were collected in the Dakar Region from farms whose owners were members of the ADAM, a farmer association specialised in the breeding of Ladoum sheep. For these three breeds, the farms and the animals in each farm were randomly chosen. Although Touabire sheep are found in the Northern region of Senegal , for brewww.illumina.com, accessed on 30 March 2022) at the GIGA research center . The genotypes were then integrated into the WIDDE database  [p-value <0.001) were also filtered out. Two genotyping datasets were extracted from WIDDE for further analyses, i.e., the SEN-Set and the WORLD-Set (The DNA samples were genotyped using OvineSNP50 BeadChip from Illumina ch 2022) . The quaORLD-Set . Finally22 . The A principal component analysis was performed using smartpca software  and visuObserved heterozygosities, expected heterozygosities , and F-sFor Senegalese sheep breeds, the gene flow parameter Nm was calculated using the following formula :Nm = 1 −ASDs  were computed for each pair of individuals using all available SNP information. For a given pair of individuals i and j,software .The genetic diversity of the Senegalese sheep breeds explored using the SEN-Set is presented in Population relationships among the Senegalese breeds were determined by calculating a pairwise Fst and gene flow parameter Nm (assessed based on the number of migrants per generation) matrix . The estimated Fst values among the trypanosusceptible breeds Peul-peul, Touabire, and Ladoum were low (0.0033–0.0438) and in the range of previously reported results ,37. The The relationships within individuals and among Senegalese sheep breeds, as illustrated by the principal component analysis, are shown in The Admixture analysis  providedThe NJ tree constructed using ASD genetic distance  confirmeTo compare genetic diversity and trace historical patterns of Senegalese sheep breeds structure on a broader geographic scale, the genotypic data of the WORLD-Set were analysed. The Ho and He were in the range of genetic diversity computed for other African breeds , but were slightly lower than those computed for their presumed ancestral breeds from South-East Asia   and aligThe principal component analysis performed using the 77 breeds is presented in The proximity between Senegalese sheep breeds and some Brazilian breeds  and a Caribbean hair sheep breed  also highlighted by the principal component analysis could be supported by colonisation patterns. According to Spangler et al. , the birThe results of the admixture analysis for k = 2–10  confirmeIn summary, we observed a low genetic diversity among the trypanosusceptible Senegalese sheep breeds, whereas the Djallonke sheep clearly deflected from the other breeds. The increased use of the Touabire sheep to upgrade the native Senegalese breeds seems to have led to the dilution of the Peul-peul breed and allowed for the emergence of the Ladoum breed. Even if the Djallonke sheep seemed to have a better conservation status in relation to the sanitary barriers imposed by trypanosomiasis to the introgression of other breeds, this should be a matter of concern that appeals to the enforcement of a regulatory framework for breed conservation and genetic improvement in Senegal. This study additionally emphasizes the contribution of Senegalese sheep breeds to the global genetic diversity and especially to the development of Caribbean hair sheep breeds.


Sus scrofa) across the European continent to infer demographic history and reassess the genetic consequences of natural and anthropogenic forces. We found that population fragmentation, inbreeding and recent hybridization with domestic pigs have caused the spatial genetic structure to be heterogeneous at the local scale. Underlying local anthropogenic signatures, we found a deep genetic structure in the form of an arch-shaped cline extending from the Dinaric Alps, via Southeastern Europe and the Baltic states, to Western Europe and, finally, to the genetically diverged Iberian peninsula. These findings indicate that, despite considerable anthropogenic influence, the deeper, natural continental structure is still intact. Regarding the glacial refugia, our findings show a weaker signal than generally assumed, but are nevertheless suggestive of two main recolonization routes, with important roles for Southern France and the Balkans. Our results highlight the importance of applying genomic resources and framing genetic results within a species’ demographic history and geographic distribution for a better understanding of the complex mixture of underlying processes.European wildlife has been subjected to intensifying levels of anthropogenic impact throughout the Holocene, yet the main genetic partitioning of many species is thought to still reflect the late-Pleistocene glacial refugia. We analyzed 26,342 nuclear SNPs of 464 wild boar ( Cervus spp. and Capreolus spp.; Putman et al. In human-dominated landscapes, the genetic variation of wildlife is shaped not only by natural demographic forces, but also by anthropogenic factors. In Europe, the Last Glacial Maximum (LGM), when ice sheets reached their most recent maximum extent ~27k-19k years ago . Although currently widespread, populations were decimated or eradicated until World War II across large part of Europe and later supplemented with individuals from other regions  in many areas of its range, although the degree of genetic ‘pollution’ varies greatly among locations  assess to what extent European wild boar populations are subject to pig hybridization, translocation and inbreeding, and to (b) delineate the continental wide spatial genetic structure of wild boar. In so doing, we ultimately aimed to infer (i) to what extent anthropogenic influences have altered the natural spatial genetic structure, and (ii) how and to what extent the spatial genetic structure still holds signatures of the LGM. Given the historic and contemporary intense human influence on European wild boar, we predicted to detect inbreeding, hybridization and translocation events in numerous wild boar populations. Depending on the intensity of these anthropogenic influences, we expected alteration of the spatial continental-wide genetic structure through weakening or erasing of natural signatures such as Isolation by Distance, and—in case of geographic barriers – Isolation by Resistance patterns. For the LGM specifically, we expected to find genetic signatures reminiscent of refugia, recolonization areas and (a) suture zone(s). An overview of our hypotheses is presented in Table To obtain a good coverage of the European continent, we combined publicly available SNP data on European mainland wild boar . After excluding duplicates and individuals with call rates below 0.95, we retained 464 animals from 23 different countries in mainland Europe . Samples were genotyped using the PorcineSNP60 DNA Analysis Kit beadchip  above 0.025. Finally, to adhere to the assumption of neutrality, for all analyses except runs of homozygosity (ROH), we excluded intragenic SNPs .indep-pairwise, window of 50 SNPs, step size 5). Two filtering procedures were used, a more relaxed r2 < 0.5 for ROH analyses  and a more stringent r2 < 0.2 (9761 intergenic SNPs remaining) to investigate genetic variation and structure. Additionally, we used the same software to calculate, separately for each sampling location, relatedness among individuals as an identity-by-descent score using subsets of SNPs with MAF > 0.10. For subsequent analyses, we retained only non-related individuals (identity-by-descent score <0.183). This filtering procedure led to a dataset of 330 wild boar from 56 sampling locations across mainland Europe .We used PLINK . FROH can be reliably estimated with 10,000 SNPs or more, if targeted at large ROH segments  and hybrid wild boar (Fhybrid > 0.0625) from these analyses  using R base functions. As a further exploration of patterns of gene flow, we examined allelic clines in European wild boar. We visualized the spatial distribution of the mean frequency of alleles typical for focal regions . We then interpolated the mean allele frequencies over the map of Europe  of the 330 unrelated European wild boar investigated, we estimated that 22 (7%), 20 (3%) and 6 (2%) samples had Fhybrid values of 0.063–0.125, 0.125–0.250, and >0.250, respectively. These putative hybrids stemmed mainly from wild boar populations in northwestern Europe, southern Switzerland, Italy, and the Balkans. This result was in line with the observed occurrence of clusters of alleles abundant in pigs, but rare in European wild boar, in the genomes of the putative hybrids  in populations all across the continent Fig.  over a tThe first axis of the PCoA of European wild boar distinguished those from western and eastern Europe Fig. . On the p < 0.05, whether with or without the Iberian peninsula, see Fig. mantel = 0.73 and rmantel = 0.63 with and without Iberian peninsula, respectively; both analyses: p < 0.001, see Fig. The first and second axes of both PCoAs were correlated with longitude and latitude, respectively , showed insightful continental-wide patterns Fig. . Alleles2adj = 0.78, d.f. = 324; coefficient estimate longitude = 0.29; t-value estimate longitude = 7.64). Additionally, with the same model, we observed, as expected, a positive correlation between MLH and Fhybrid  and a strongly negative correlation with FROH . All general linear models had p values < 0.001.The spatial map of the Multilocus Heterozygosity (MLH) showed an overall west-east gradient Fig. . We deteUsing genome-wide data and a continent-wide coverage of populations across Europe, we examined recent anthropogenic impact on, and revealed the spatial structure of, the genetic variation of European wild boar. We found considerable and widespread anthropogenic impact on wild boar in the form of inbreeding, fragmentation and pig introgression, though not translocation. Nevertheless, continent-wide PCoA analysis, ADMIXTURE analysis and spatial maps of allele frequencies and heterozygosity showed that the genetic composition of wild boar in Europe takes the form of an arch-shaped cline that extends from southeastern Europe, via the Baltic region, to western Europe and, finally, the Iberian peninsula – the latter being much differentiated from the rest of the continent. Lastly, we found an increasing gradient of heterozygosity from west to east, with the highest levels of heterozygosity found in a line extending from the Alps to the Baltic region.These observations stimulate the ongoing discussion on what shapes the genetic structure of European wild boar, and northern hemisphere wildlife in general. They are partially concordant with previous studies based on mtDNA  20th centuries. Our results appear to still reflect this situation, despite a recent comeback of the species in those areas  indicates that the severity of fragmentation and associated population size reductions vary from region to region. The populations with the highest levels of inbreeding  share a history of strong isolation and severe bottlenecks. For all these populations, the bottlenecks mostly occurred approximately one or half a century ago. Although these populations are currently increasing and might keep doing so in the future, coancestry and hence inbreeding may continue to accumulate , and a complex heterozygosity gradient . Assuming that anthropogenic influences typically produce erratic patterns  multiple local genetic discontinuities despite the existence of a strong pattern of isolation by distance; (ii) severe inbreeding occurring locally, despite a continental-wide heterozygosity gradient; (iii) differentiation patterns correlated with longitude and latitude, despite substantial pig hybridization. These seemingly contradictory results are likely explained by scale and resolution as large-scale spatial genetic structure may be insensitive to local alterations of genetic variation. Hence, the question on to what extent human activities alter genetic variation of wildlife, is much dependent on spatial scale , as previously suggested (Alexandri et al. The formation of the suture zone on the northeastward line Alps-Baltics rather than a northward line, might have been caused by an earlier, or faster, expansion by wild boar from southern France, that consequently recolonized most of northern Europe. A similar pattern is suggested for red deer by fossil records and microsatellite variation (Sommer et al. Next to assumed LGM signatures, we also observed spatial genetic patterns not easily reconcilable with the LGM impact. First and foremost, the PCoA Fig.  showed aWe provided evidence that the spatial genetic variation of European wild boar is the outcome of a complex interplay of multiple processes of both anthropogenic and natural origin. We observed many and strong signatures that we attribute to human impacts, including loss of genetic variation due to inbreeding, increased genetic variation due to pig introgression, and the existence of genetic discontinuities in areas without natural barriers on the background of a continent-wide pattern dating back to the LGM, or possibly even earlier. Future research, involving historical samples and sequence data should study the origin of haplotypes to shed light on the diverse ancestry of wild boar, and other species, of the European continent, while modern samples should be investigated to identify how anthropogenic influences are affecting the survival and adaptability of the species, also considering the need of science-based management practices for a species that is increasingly considered a source of human-wildlife conflict.Supplementary tablesSupplementary figures


The objective of this research is to go beyond the restriction of natural selection and obtain novel genetic elements that are useful for human use. From the limited modification of the characteristics of natural elements to originally designed elements, various synthetic genetic elements have been reported. “Genetic devices”, such as logic gates and memory elements, and higher order “genetic systems”, such as metabolite factories and biological containment systems, can be constructed using these synthetic elements in combination with other genetic elements. Through this approach, the incorporation of synthetic genetic elements is dramatically expanding biological functions.Since the beginning of life on Earth, over the course of 3 to 4 billion years, nature has created vast quantities of genetic elements. These freshly created elements faced natural selection: winners survived, and losers disappeared. Nature selected only the genetically stable elements that contributed to the maintenance of life. From a contrary perspective, natural selection restricted the diversity of genetic elements. In the last 20 years, i.e., 2 × 10Life (ISSN 2075-1729) collects a series of research and review articles related to synthetic genetic elements, circuits as devices, and systems. This issue contains 11 articles. The following is an overview.The Special Issue “Synthetic Genetic Elements, Devices, and Systems” published in Five of the papers focus on one of the most important techniques in synthetic biology: the process of controlling the expression of specific genes.Transcriptional switches are the most fundamental and important genetic elements for building synthetic gene circuits. Transcription switches have been developed mostly in prokaryotes, but in recent years there have also been remarkable developments in eukaryotes. Tominaga et al. present a comprehensive review of synthetic genetic switches working at the transcriptional level in yeast . In partFunctional noncoding RNAs, such as riboswitches, ribozymes, and aptamers, are useful components of synthetic genetic circuits. Riboswitches regulate transcription, translation, RNA splicing, and RNA stability, while ribozymes have catalytic activity similar to that of protein enzymes. Aptamers interact with specific molecules, and riboswitches and ribozymes can be fused with aptamers to express their functions in a conditional manner. Ge and Marchisio present a comprehensive review of the aptamers, riboswitches, and ribozymes used in yeast synthetic biology .The development of modular, orthogonal, and easily programmable genetic components to build more complex and sophisticated synthetic genetic circuits is highly desirable. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) systems can be used as a genetic switch with these characteristics, as well as for genome editing. Du et al. present a comprehensive review of CRISPR-based genetic switches and their applications, including in bio-computation .E. coli pks island mRNAs, which have been linked to colorectal cancer [The toehold switch sensor is a riboregulator that controls the translation of downstream genes. The addition of a trigger RNA initiates translation by releasing the RBS and the translation initiation codon by changing the secondary structure of the toehold switch sensor. Incorporating a toehold switch sensor into the expression construct of a reporter gene allows for the detection of RNAs of interest, such as viral RNAs. However, when the trigger RNA is too long, the formation of secondary structures often makes detection problematic. Heo et al. report that the use of helper RNAs that inhibit the secondary structure formation in a trigger RNA is effective for the detection of l cancer .The toggle switch is an important genetic device that plays a central role in both natural and synthetic gene systems. However, it is difficult to ensure predictable system-level behaviors because toggle switches display a particularly strong dependence on the genetic context. Gyorgy reports an extensive analysis of the genetic toggle switch in the presence of leaky promoters and the cellular burden using a mathematical model .DNA transfection is the standard method for transgene expression, but the risk of insertional mutations is a drawback for clinical use, such as cancer therapy. The direct administration of synthesized mRNA can avoid the risk of insertional mutations. However, for spatiotemporal and cell-specific control, novel methods distinct from DNA transfection are required. Nakanishi reviews protein-based translational regulatory systems for synthetic mRNAs in mammalian cells . It is nReversible protein–protein interactions, such as those involving binding to allosteric regulators, structural changes in upstream regulators, and post-translational modifications, respond within seconds and are much faster than mechanisms that occur via transcription or translation. Rosa et al. review synthetic protein circuits and devices based on such reversible protein–protein interactions .The production of chemicals and proteins in cell factories is one of the most important applications of synthetic genetic systems. The last four articles address this research field.Techniques for the incorporation of unnatural amino acids into ribosomally synthesized proteins have been developed in the recent decades. The amber stop codon has usually been selected for unnatural amino acid incorporation. Kato proposes a novel method to control the growth and viability of target bacteria by incorporating unnatural amino acids at sense codons, causing the production of non-functional or toxic proteins . This meHuman embryonic kidney 293 (HEK293) cells are a human-derived cell line that is commonly used to produce therapeutic glycoproteins. Mild hypothermia has been widely used to enhance transgene expression in HEK293 cells. Jang, Min, and Lee report promoter-dependent hypothermia responses in HEK293 cells that can be attributed to the interaction of exogenous promoters with endogenous transcription factors [Uridine diphosphate-glucose dehydrogenase (UGD) is an enzyme that produces uridine diphosphate-glucuronic acid, a precursor for useful glycosaminoglycans such as hyaluronic acid, heparosan, and chondroitin. The step catalyzed by UGD is considered to be the limiting factor in the heterologous production of glucosaminoglycans. Couto et al. have characterized three new UGDs and propose new enzyme options for industrial use .In synthetic biology, gene clusters are reconstituted using controllable genetic elements to optimize the production of desired metabolites. Towards this end, transcriptional regulation using well-characterized promoters is an important approach. For metabolic pathways involving multiple operons, adjusting each promoter strength is important to obtaining maximum production efficiency. Zhao et al. report a markerless and combinatorial approach to obtaining an optimal balance of multiple promoters controlling individual operons, resulting in the improved production efficiency of thaxtomin A .We hope that this collection will help researchers to develop novel synthetic genetic elements, circuits, devices, and systems.


The NLRP3 inflammasome is a multimolecular complex that processes inactive IL-1β and IL-18 into proinflammatory cytokines. OLT1177 is an orally active small compound that specifically inhibits NLRP3. Here, B16F10 melanoma were implanted in mice and treated with OLT1177 as well as combined with the glucocorticoid dexamethasone. At sacrifice, OLT1177 treated mice had significantly smaller tumors compared to tumor-bearing mice treated with vehicle. However, the combined treatment of OLT1177 plus dexamethasone revealed a greater suppression of tumor growth. This reduction was accompanied by a downregulation of nuclear and mitochondrial STAT3-dependent gene transcription and by a significant reduction of STAT3 Y705 and S727 phosphorylations in the tumors. In vitro, the human melanoma cell line 1205Lu, stimulated with IL-1α, exhibited significantly lower levels of STAT3 Y705 phosphorylation by the combination treatment, thus affecting the nuclear functions of STAT3. In the same cells, STAT3 serine 727 phosphorylation was also lower, affecting the mitochondrial functions of STAT3. In addition, metabolic analyses revealed a marked reduction of ATP production rate and glycolytic reserve in cells treated with the combination of OLT1177 plus dexamethasone. These findings demonstrate that the combination of OLT1177 and dexamethasone reduces tumor growth by targeting nuclear as well as mitochondrial functions of STAT3. BRAF gene and its most common variant is the V600E substitution that activates the MAPK pathway, resulting in uncontrolled cell proliferation and inhibition of apoptosis . On. On29]. rylation ,106,107.rylation ,110,111.OLT1177 has a marked impact in STAT3-dependent transcription primarily in vivo. Nevertheless, as shown in V617F variant. This constitutively active JAK2 form, that hyperactivates the STAT3 phosphorylation, leads to upregulation of PD-L1 and to the immune escape of neoplasms [The effect of dexamethasone on tumor growth is likely associated with its role in preventing T cell exhaustion, a phenomenon determined by prolonged inflammation and commonly observed in cancer . This iseoplasms ,118,119.From a metabolic point of view, as depicted in In summary, our data show that dexamethasone enhances the anti-inflammatory property of NLRP3 inhibition by dampening the pro-oncogenic functions of STAT3. Considering the beneficial effects of inflammasome inhibition for cancer treatment, particularly for those melanoma patients that are resistant to checkpoint inhibitors , an alte