Population structure was further evaluated using Bayesian model-based clustering (STRUCTURE) and discriminant analysis of principal components (DAPC). Admixture was detected among Karanga, Kunduchi, and Ruhila populations. A cross-validation approach  was conducted in order to test the efficiency of the SNP markers to correctly assign individual fish to the population of origin. The cross-validation procedure was repeated 10 times resulting in 77% of the tested individual fish being allocated to the correct population. Overall our results provide a new database of informative SNP markers for both conservation management and aquaculture activities of Nile tilapia strains in Tanzania.Understanding population structure and genetic diversity within and between local Nile tilapia lines cultured in Tanzania is important for sustainable aquaculture production. This study investigated the genetic structure and diversity among seven Nile tilapia populations in Tanzania . Double-digest restriction site-associated DNA (ddRAD) libraries were prepared from 140 individual fish (20 per population) and sequenced using an Illumina HiSeq 4000 resulting in the identification of 2,180 informative single nucleotide polymorphisms (SNPs). Pairwise F Oreochromis species of which 10 are only found in the country  with a continuously increasing demand for further expansion. Despite the interest and potential of tilapia aquaculture to contribute to local food production, currently no selective breeding program exists in Tanzania—a situation typical of many African nations.Tanzania is a diversity hotspot of tilapias including more than 30  country . OreochrCommon hatchery aquaculture practices could result in a rapid reduction of the genetic diversity of the farmed animals. A well-managed breeding program on the other hand would enable cumulative genetic improvement of target traits, while simultaneously minimize inbreeding and loss of diversity. Forming a base population containing high genetic diversity will be crucial for the success of any future breeding program in Tanzania . FurtherTilapia species have a very complex genetic structure, in common with many other Cichlid fish species . MoreoveGenetic diversity plays a crucial role in the adaptation ability of a population in the face of fluctuating environmental conditions . ConservO. niloticus is crucial both for conservation practices and for fish breeders. Previous studies examined the genetic structure and diversity between populations of Nile tilapia (Oreochromis niloticus), based either on phenotypic traits  technologies have facilitated the discovery of large numbers of genetic markers for practically any organism at an affordable cost allowing the investigation of genetic diversity within and between populations . RestricThe current study investigated the population genetic structure of seven Nile tilapia populations from Tanzania using ddRAD-seq derived single nucleotide polymorphisms (SNPs). Genetic diversity parameters and population structure using both multivariate analysis and Bayesian clustering algorithms were evaluated. Admixture levels between the different populations were estimated providing valuable information for future management of Nile tilapia resources in Tanzania. Finally, a cross-validation scheme was applied in order to test the efficiency of the generated SNPs for assignment of individual fish to their population of origin.This study was carried out in accordance with the law on the protection of animals against cruelty (Act no. 12/1974. of the United Republic of Tanzania) upon its approval by the department of Zoology and Wildlife Conservation, University of Dar es salaam. All the permits required to sample wild animals in Tanzania were adhered; these include Research clearance from Tanzania Commission for Science and Technology (COSTECH) and other relevant authorities.Oreochromis niloticus juveniles were collected in 2017 from Government aquaculture centers distributed throughout Tanzania. In particular we collected animals from six farmed populations namely: Tanzania Fisheries Research Institute , Fisheries Education and Training Agency , Karanga , Igunga , Kunduchi , Ruhila   and eluted into 100 µl of AE (EDTA) buffer (Qiagen) according to the manufacturer’s tissue protocol and procedures. The purity and concentration of the extracted DNA were quantified using Qubit 2.0 Fluorometer (Invitrogen). Samples were diluted with Tris EDTA (TE) buffer (Thermo Fisher Scientific) to 25 ng/µl and 2 µl were run on a 1% agarose gel by electrophoresis. Diluted samples were stored at −20°C.SbfI (recognizing the CCTGCA|GG motif) and SphI (recognizing the GCATG|C motif) high fidelity restriction enzymes , using 6 U of each enzyme per microgram of genomic DNA in 1× Reaction Buffer 4 (NEB). The reactions  were then heat inactivated at 65°C for 20 min. Individual-specific combinations of P1 and P2 adapters, each with a unique 5 or 7 bp barcode, were ligated to the digested DNA at 22°C for 60 min by adding 1 µl SbfI compatible P1 adapter (25 nM), 0.7 µl SphI compatible P2 adapter (100 nM), 0.06 µl 100 mmol/L rATP , 0.95 µl 1× Reaction Buffer 2 (NEB), 0.05 µl T4 ligase  and reaction volumes made up to 8 µl with nuclease-free water for each sample. Following heat inactivation at 65°C for 20 min, the ligation reactions were slowly cooled to room temperature (over 1 h) then combined in a single pool (for one sequencing lane) and purified. Size selection (300–600 bp) was performed by agarose gel separation and followed by gel purification and PCR amplification. A total of 100 µl of the amplified libraries (13–14 PCR cycles) was purified using an equal volume of AMPure beads. After eluting into 20 µl EB buffer , the libraries were ready for sequencing. The libraries were sequenced at Edinburgh Genomics Facility, University of Edinburgh on an Illumina HiSeq 4000 instrument.ddRAD library preparation was performed according to O. niloticus reference genome assembly  using b858045.2 . Stacks 858045.2  was usedow bound . SNP calow bound . During ow bound . Only onst values were obtained using the stamppFst function according to st values testing for significant deviations from zero were estimated using 1,000 bootstraps. Principal component analysis (PCA) was carried out using the R package ADEGENET version 2.1.1 (Mean observed (Ho) and expected (He) heterozygosity and average individual inbreeding coefficients (Fis) were estimated using Stacks v2 . The R pon 2.1.1 .O. niloticus samples derived from 7 populations in Tanzania. Population structure and potential admixture between the different populations was evaluated using Bayesian clustering approaches implemented in the program Structure v2.3.4  and Bayesian-model-based approaches were used to infer the genetic structure of e v2.3.4 . The nume v2.3.4  were usee v2.3.4  and CLUMe v2.3.4  for idene v2.3.4 . The Baye v2.3.4 .predict.dapc) on the remaining training data set. The entire procedure was repeated 10 times in order to minimize potential bias due to sample allocation in the training/test datasets. Furthermore, DAPC carried out on the entire dataset was used to identify SNPs with highest population discriminatory value.A four-fold cross-validation scheme was applied using the R package ADEGENET version 2.1.1  in orderA total of 169 million raw sequence reads (150 bp paired-end) were obtained. Approximately 140 million reads from 139 individual fish (one fish was removed due to sequencing failure) passed the aforementioned quality control (QC) filters. Alignment of these filtered reads to the Nile tilapia reference genome  resultedThe overall mean expected heterozygosity within populations was 0.132, while the observed heterozygosity was 0.081  was used to visualize individual relationships within and between populations. The first and second principal components accounted for 62% and 14% of the total variation, respectively. Individual fish from FETA, Lake Victoria, Igunga and most of the individual fish from Kunduchi formed a group of genetically similar animals . In addition, analysis of molecular variance (AMOVA) was used to detect within and among populations genetic variance components. AMOVA showed the highest levels of genetic variation within populations 67%, of the total variation, and 33% of variation was distributed among populations.The population pairwise FThe STRUCTURE analysis suggested that K = 7 was the most probable number of separate clusters for the studied Nile tilapia populations. Further, individual fish from FETA, Lake Victoria, Igunga and most of individual fish from Kunduchi  appeared to share the same genetic cluster, while animals from TAFIRI formed a separate isolated cluster  would be of importance in future selective breeding practices as it would allow to utilize more efficiently the within population variance as opposed to traditional pedigree practices solely relying on the usage of passive integrated transponder tags. Nevertheless, as revealed by STRUCTURE analysis it should be taken into account that some populations contain unique genetic clusters not represented by “pure” populations.From a farming perspective, evaluation of the genetic diversity among and within tested populations is crucial in order to ensure that the most diverse animals are chosen for selective breeding practices. Since Tanzania is a hot spot for tilapias, knowledge regarding genetic diversity will also be useful in appropriate management of wild populations. In addition, genetic variation is important for a population’s adaptation capacity towards changing environmental conditions . Mireku Oreochromis populations in the primary rivers of Guangdong province were lower than the expected heterozygosity (He = 0.7097). On the contrary, O. niloticus in the Volta lake of Ghana was slightly higher than the expected heterozygosity (He = 0.459). In addition, O. niloticus populations from river Nile (He = 0.884 and Ho = 0.815) than from Delta lake populations (He = 0.846 and Ho = 0.533). In our study the overall observed heterozygosity (Ho = Ho = 0.081) was lower than the expected heterozygosity (He = 0.132) for most tested populations. Even though our study used SNP markers opposed to the aforementioned studies where microsatellites were primarily used the heterozygosity values are low compared to ddRAD studies in other fish species ranging between 0.18 and 0.25 . The similarity among these three populations is probably due to their origin from the same region of Lake Victoria . According to our records the parents of the genotyped fish from FETA and Igunga also originated from Lake Victoria. Therefore, it is likely that these populations are genetically similar to each other and share the same genetic background. Moreover, the assignment of FETA, Lake Victoria and Igunga in the same cluster according to both STUCTURE and DAPC analysis provides further support for the aforementioned hypothesis. Nevertheless, in the case of TAFIRI a different trend was observed despite originating from the same location. The high FST values between TAFIRI and other populations  indicate high isolation between them. Interestingly, the TAFIRI population was composed of animals being in captivity for 4–6th generations  and this could be a reason for its genetic uniqueness. Furthermore, we observed strong genetic differentiation between Karanga and the three closely related populations of FETA, Igunga, and Lake Victoria (FST = 0.548 0.538 0.533 respectively). The differences could be the result of geographical isolation which probably has acted as a barrier to gene flow between those populations, leading to the suggested genetic structure that the STRUCTURE analysis revealed. Nevertheless, gene flow is expected to have occurred among the admixed populations  and expected “pure” populations of Lake Victoria and TAFIRI. Since reproductive viable hybrids in tilapias are common  and Bayesian clustering algorithms (STRUCTURE) were used in the current study for deriving the underlying genetic structure among the sampled populations. PCA offers considerable advantages, since it can be applied in large datasets at a minimal computational cost compared to Bayesian approaches. In general terms, PCA aims to summarize the total variation between individuals in a reduced dimension. Nevertheless, the above approach does not necessarily provide optimal resolution for distinguishing between different groups. As such, approaches like DAPC have been shown to be particularly advantageous, since they retain the computational advantages of PCA, while at the same time offer higher resolution for detecting groups of individuals with common genetic background . AnimalsAdmixture analysis further supported that FETA, Lake Victoria, and Igunga together with animals from Kunduchi shared similar genetic background. On the other hand, high admixture levels were inferred in the Karanga, Ruhila, and Kunduchi populations. In the Ruhila population admixture with the population from Lake Victoria and TAFIRI was suggested. Moreover, a similar result was obtained for the Karanga population, while in the case of Kunduchi admixed fish shared genome variation with populations of FETA, Lake Victoria, and Igunga. The speculated uncontrolled movement of fish between different locations in- and outside Tanzania, maybe from Kenya or Thailand, could be an explanation for the suggested population admixture. Nevertheless, it needs to be stressed that both Ruhila and Kunduchi appear to contain animals of a distinct genetic background.O. esculentus and O. variabilis while O. leucostictus and O. niloticus were introduced in the lake in 1950s  than samples (genotyped fish). Model overfitting in our case could mistakenly lead to the conclusion that the SNP dataset would be highly efficient in deciphering the most probable population of origin of unknown samples. Overall 77% of tested individual fish were correctly allocated to population of origin using the SNP data. Most of the erroneous assignments originated from the three closely related populations for which our information suggests that all three originate from Lake Victoria. Further, a low number of correctly assigned individual fish were obtained in the Kunduchi population. As suggested both by STRUCTURE and DAPC high level of admixture is suggested for the Kunduchi population. Taking the above into account successful assignment to population of origin exceeded 92%. Nevertheless, it needs to be acknowledged that for the conducted analysis to be most efficient the population information of the training dataset should be highly accurate. The expected unregulated transferring of fish in Tanzania coupled with the inherent difficulty of species discrimination among tilapias using phenotypic criteria and the most common hybridization between tilapia species resulting to reproductive viable offspring could suggest that potentially mislabeled samples have been included.Overall, the obtained results from our study indicate that the genetic diversity and structure of Nile tilapia populations cultured in Tanzania can be explained by their life history and geographical distribution. The results also revealed greater genetic diversity within than among populations. The close clustering of Igunga, FETA and Lake Victoria populations and distinct separation of TAFIRI, suggests that these could be pure populations without admixture. The above should be taken into consideration in future wild populations conservation practices. Moreover, the gained information regarding population structure among the tested tilapia populations is important for characterizing genetic similarities and relationships of cultured lines in Tanzania. Understanding how genetic variation is distributed within and among populations will facilitate the formation of a base population and will allow breeders to design crossings between the aforementioned populations in order to maximize the genetic diversity for selective breeding purposes. Therefore, the results from this study could be used as a guide for future breeding programs and genetic improvement of local Nile tilapia in Tanzania, which may ultimately form an exemplar for the development of local tilapia species and breeds for aquaculture in African countries. Finally, using SNP data to infer the population of origin is of great importance not only for estimating genetic diversity but also in wild population conservation practices. There are unique tilapia species in Tanzania that must be protected and preserved. In addition, the SNP dataset developed can also be valuable for traceability purposes especially with regards to wild populations inhabiting nature protected reservoirs.The aligned reads in the format of bam files were deposited in the National Centre for Biotechnology Information (NCBI) repository under project ID PRJNA518067. The accession numbers of samples analyzed in this study are given in RK and FP carried out DNA extraction. CP and RH performed ddRAD library preparation and sequencing. DK, MM, and RK framed the study and contributed to designing the experiments. MM and AM provided valuable suggestions to the manuscript. RK and CP performed the statistical and genetic analyses. RK wrote the manuscript. DK and CP revised the manuscript. All authors approved the final draft of the manuscript.The authors declare that the research was conducted in the absence of personal or financial relationships that could be construed as a potential conflict of interest


The animals belonged to populations in Brazil, Mexico, Spain  Italy, Iran, Egypt, and the United States. The haplogroup network that formed suggested that turkey domestic populations group into a single haplotype. However, genetic differences within the haplogroup were found. The present study may provide a better approach for the implementation of conservation strategies for domestic turkey populations.The development of new production lines of turkeys has relegated native breeds to a second position. This has increased the need for new research to ensure the conservation of local turkey breeds and the maintenance of biodiversity. The objective of the present study was to identify turkey populations, their origins, and maternal lines through mitochondrial DNA analysis. For this study, mitochondrial DNA samples from 93 turkeys  domestication may have occurred in Mexico around 2000 years ago. However, little is known about the phylogenetic and genealogical background underlying domestic turkey populations. This study aimed to further understand the domestication process and identify inter- or intraspecific connections between turkey populations to determine their origins, trace their global expansion, and define the species’ genetic value. Ninety-three domestic turkeys  were sampled from populations in Brazil, Mexico, USA, Spain, Italy, Iran, and Egypt. Publicly available sequences from previous studies were also included. Standard mitochondrial DNA, genetic diversity, and haplotype network analyses were performed. Seventy-six polymorphic sites were identified. Turkeys from Mexico showed the greatest number of polymorphic sites (40), while turkeys from Italy and Brazil reported only one site each. Nucleotide diversity was also highest in Mexico and the USA  and lowest in Brazil and Italy. Of the six major haplogroups defined, the Mexican and USA populations appeared to have remained more stable and diverse than the other populations. This may be due to conservative husbandry policies in the rural areas of other populations, which have prevented the introduction of commercial turkey lines.According to recent archeological evidence, turkey  Meleagris gallopavo), scientific efforts to understand the genetic diversity of the species have been infrequent. M. gallopavo is presumably the only important North-American domestic species of turkey [Meleagris gallopavo gallopavo (domestic Mexican subspecies), Meleagris gallopavo silvestris (wild), Meleagris gallopavo mexicana (Gould), Meleagris gallopavo intermedia (Rio Grande), Meleagris gallopavo osceola (Florida), and Meleagris gallopavo merriami (Merriam) [Despite the global economic importance of turkeys  . The MexMerriam) ,4, whichMerriam) .M. g. gallopavo [Mitochondrial DNA (mtDNA)-based molecular studies have been performed on domestic turkey populations in order to trace the history of the extinct wild subspecies, allopavo . Historiallopavo . Consideallopavo , Leopoldallopavo , and Schallopavo , an exacallopavo .The definition of zoogenetic resources and the characterization of local populations are challenging but necessary when aiming to develop biodiversity conservation policies . In thisAll the main current domestic turkey varieties descend from the native turkey of central Mexico, which was subsequently imported into Europe during Spanish colonization and was later distributed throughout the extensive Spanish territories. However, it was not until the seventeenth century that turkeys spread across Europe, South America, Africa, and many countries of the Middle East as an alternative to pork. The relationships among wild turkeys have been extensively evaluated, primarily for conservation purposes, using both morphological and mitochondrial molecular tools, such as amplified fragment length polymorphism (AFLP), DNA markers, and mitochondrial control region analysis by using heterologous primers from the chicken. Mock et al.  evaluateDifferences among turkey varieties have also been investigated at the molecular level using diverse nuclear DNA marker systems ,13, inclThe present study aimed to analyze mitochondrial diversity in several domestic breeds of turkey from seven different countries located on four different continents . Original regions and derivate populations were included in the study. Firstly, we analyzed sequences of the mtDNA D-loop region from domestic, commercial, and wild turkeys obtained from GenBank to evaluate their domestication process, shed light on their origin, trace their worldwide expansion, and define the genetic value of the species, thus emphasizing the repercussions of domestication. Secondly, we developed a haplogroup network by analyzing Nei’s genetic distances and performing an analysis of molecular variance (AMOVA) to assess inter-and intraspecific global connections between turkey populations.Blood samples were collected from domestic turkey populations  from 2015 to 2018. For each individual, blood samples were taken from the brachial vein, placed in 2 mL vials containing ethylenediaminetetraacetic acid (EDTA), and stored at −18 °C. Additional blood samples were then collected on filter paper sheets and were stored at room temperature until further analysis. Samples were deposited in the Animal Breeding Consulting Laboratory at the University of Córdoba, Spain. A total of 93 samples from local domestic turkey breeds were available for analysis. Eleven samples were collected from rural communities northeast of Paraiba, Brazil; ten samples were from rural communities in Veracruz City, Mexico; ten samples were from Giza Governorate, Egypt; thirty samples were from rural environments in Spain, including eighteen from Andalusia  and twelve from the Balearic Archipelago ; six samples were from a turkey breeding station established in 1983, with birds from northern and northwestern Iran; twenty-two samples belonging to two different breeds were from Italy, with ten samples from the Parma breed and twelve from the Romagnolo breed; and six samples were from Iowa, USA.Ethical approval was not needed for this study. Blood samples were collected from local turkey populations by qualified veterinarians during their routine practice within the framework of official programs aimed at the identification and health monitoring of the breeds and populations included in the present study. Sample collection did not involve any endangered or protected species. The blood samples were manually collected without injuring the animals, and no other types of tissue  were used in the present study.®  [M. gallopavo mitochondrion 16,717 bp) [2), 200 mM of each deoxynucleoside triphosphate (dNTP), 10 pmol of each oligonucleotide, 1 U of MyTaq DNA polymerase , and 30 ng of DNA. The reaction mixtures were placed in a thermocycler  under the following amplification conditions: 95 °C for 5 min; 34 cycles of 95 °C for 45 s, 59 °C for 1 min, and 72 °C for 2 min; and a final extension at 72 °C for 45 min. Amplicon quality was assessed on a 1.5% agarose gel with ethidium bromide, using size (100 bp ladder) and concentration standards. Sufficient amplicon quality was indicated by a single well-defined band of approximately 1000–1300 bp. DNA sequencing was performed by the dideoxy technique on both strands, using a commercial service . In addition to these 93 sequences, we analyzed sequences from wild subspecies , domestic birds, and commercial lines (improved turkey breeds for meat production) obtained from the NCBI GenBank database  . The mtD,717 bp)  was useddatabase , resultiST (permuting haplotypes among population among groups) values from pairwise comparisons were computed with 1000 permutations using ARLEQUIN v3.1 [The sequence editing, alignment, and construction of data matrices were performed using Mega v5  and GbloUIN v3.1 .To establish genealogical relationships between haplotypes and their frequencies, a haplotype network was constructed using the median-joining method with the software NETWORK v4.6.0.0  under deM. gallopavo collected for this study. These sequences were registered in GenBank (accession numbers: MK284411-MK284503). Twenty haplotypes were identified within the domestic turkeys, and these all showed overall moderate Hd values and low π values (Ninety-three sequences (620–780 bp long) of the mtDNA D-loop were obtained from the DNA samples of π values . Six hapM. gallopavo) were used to form a group referred to as “Mundi/Domestic.” Sequences of wild individuals reported in the NCBI GenBank database were also included. A summary of the genetic indices for each of the populations studied can be found in M. g mexicana population showing the lowest Hd and π values. By contrast, the M. g. osceola and M. g. silvestris populations showed the highest diversity , and it was present in 62.76% of the individuals in the population, sharing a maternal line with nine Brazilian individuals, five Egyptian individuals, thirteen Andalusian individuals (Spain), ten Majorcan individuals (Spain), five Mexican individuals, nine Parma individuals , seven Romagnolo individuals , and three American individuals (USA). Two domestic individuals from Egypt, four from Andalusia, and three from Iran shared the MGDH1 and MGDH2 haplotypes. Therefore, in the following analyses, they were treated as a single group referred to as “Mundi,” following the premise described by Padilla et al. [iversity .M. gallopavo archaeological (MGA) samples; and samples dating back to 1903, belonging to prehistorical wild M. g. gallopavo specimens collected from Veracruz-Llave, Mexico (named 1903). Additionally, we analyzed samples from a commercial line ; domestic turkeys from Izabal, Guatemala (GUAT); and domestic turkeys from Michoacan and Puebla, Mexico (DOMEX).In addition, we analyzed genetic differentiation, including the following external population sequences from Genbank: Oscence turkey samples from Alto Aragon, Spain (OSCE); ST values of all the populations included in the “Mundi” group. Turkey populations showing the least genetic differentiation were observed between 1903 and Egypt, Andalusia, or the USA; Guatemala and Brazil, Majorca, Mexico, Parma, or the USA; and DOMEX and Andalusia  for the first defined group  showed that the genetic variation within populations was higher than the genetic variation within groups , archaeological samples, and the “Mundi” group. For the second network, 542 frequencies were used, including the “Mundi” group, wild turkeys, commercial lines, and domestic prehistoric and archeological samples .The first analysis showed that haplotypes differed from each other by a moderate number of mutations. The network  showed tTwo domestic individuals from Egypt, four from Andalusia, and three from Iran shared the same haplotype. Most of the domestic turkeys from Brazil, Egypt, Andalusia, Majorca, Italy, Mexico and USA shared the same haplotype and maternal line as the “Mundi” group. This haplogroup comprised Mexican, Guatemalan domestic, and one of the archaeological samples. The second principal haplogroup included eleven “Mundi” haplotypes, which clustered with those obtained from the NCBI GenBank database, comprising 38 individuals related to the dominant haplotype, MGFM .The third haplogroup detected contained only “Mundi” haplotypes, with the Romagnolo population being most common. The rest of the “Mundi” haplotypes consisted of unique sequences, with one per population from Egypt, Iran, Mallorca, and Mexico; one Parma individual; and two from the USA. Archaeological samples included in this study separated into unique sequences in the network, as seen in M. g. merriani and archeological and prehistorical domestic samples.The second analysis revealed 17 haplotypes that differed from each other by a high number of mutations. The network  displayeM. gallopavo. Dominant haplotypes comprised M. g. merriani individuals, who shared a haplogroup with M. g. silvestris, archeological samples, and M. g. intermedia.Haplogroup H_3 comprised four haplotypes, all of which consisted of individuals belonging to wild M. g. silvestris, and Osceola haplotypes. The H_5 haplogroup showed eight haplotypes and these were linked to H_1, H_3, H_4, and H_6. The main haplogroup comprised prehistoric domestic haplotypes and was shared by domestic and wild turkey populations of the subspecies M. g. Mexicana, M. g. osceola, M. g. merriani, M. g. silvestris, and M. g. intermedia and archeological samples. Haplogroup H_6 consisted of four individuals belonging to “Mundi” populations (two from the USA and two from Mexico) and M. g. silvestris turkeys. Haplogroup H_4 was shared by prehistorical domestic, Haplotype diversity represents the probability that two randomly sampled alleles are different, while nucleotide diversity is defined as the average number of nucleotide differences per site in pairwise comparisons among DNA sequences, based on the analysis of generated sequences. The results of the present study suggested a moderate level of haplotype diversity and low nucleotide diversity, which may indicate a period of rapid population growth that enhanced the retention of new mutations ,26.The results of the analysis of genetic diversity per population revealed that Mexico and USA populations had high Hd and π values. These results differ from those reported for wild turkey populations from the USA, which have high levels of Hd but low levels of π ,27,28. GThe populations from Egypt and Iran showed high values for Hd and low values for π. This condition is often attributed to an expansion process characterized by a period of a low effective population size and a bottleneck, followed by a rapid expansion ,26. SimiThese findings have normally been attributed to different population dynamics, such as periodic bottlenecks in a region or metapopulational structures within regions, directly caused by the low levels of diversity present in the population . The “MumtDNA diversity patterns often reveal historic migration routes that may date back to the dispersal of the first domesticated animals. Genetic variability is expected to decrease with increasing geographical distance from the epicenter of domestication ,30 unlesMost previous studies dealing with turkey species have only comprised local samples and, hence, have only partially considered haplotype variability. This makes valid conclusions difficult when comparing several international studies. In this context, our study may help clarify such relationships and define turkey mitochondrial haplogroups, since we comprehensively analyzed samples from Mexico and the USA, the countries where the domestication process of turkeys is presumed to have started, but we also included samples from populations in Iran, Egypt, Brazil, Spain, and Italy.Six divergent groups were identified, but the dominant haplotypes in haplogroup H_1 were the main founding maternal lines of domestic turkeys. On the one hand, since these two maternal lines were detected in individuals from the commercial line and in domestic individuals from Mexico and the USA, these two populations may be the most likely origin of the current highly selected commercial lines. However, the turkey varieties from Andalusia, Majorca, Iran, Egypt, and Italy and the commercial populations may have derived from the wild Mexican population. This suggests that commercial lines may share the same origin and that specific nuclear DNA haplotypes may have been indirectly selected in modern domestic turkey populations.While population genetic diversity data suggested that Mexico and USA populations were consistently more diverse than the other populations analyzed, in the case of the USA, the high level of divergence between haplotypes may be attributed to secondary contact between previously differentiated allopatric lineages and the stable population settled in the area.M. g. silvestris), resulting in the ancestors of the modern commercial turkeys [This may have occurred when British Pilgrims brought domestic European turkeys back to eastern North America in the 17th century. These reintroduced birds hybridized with the American eastern wild turkey , we can infer that “Mundi” populations had greater variability and were more distant from the COMER, MGA, and OSCE populations. Archaeological samples from populations dating back to 1903  and GUATM. gallopavo populations.Our results showed a moderate haplotype diversity and a low nucleotide diversity, which may be attributed to a period of population expansion followed by a period of low effective population. The majority of domestic turkey breeds in Brazil, Egypt, Andalucia, Mallorca, Italy, Mexico, and the USA were seen to share the same haplotype and maternal line. Our results suggest that turkey populations from Mexico and the USA were historically large and stable populations that occupied a wide geographical distribution ranging from the north to the center of the American territories. These populations then thrived and became stable and more diverse than the other populations over the years. Such success may be attributed to the conservative management practices used in rural areas that did not permit the introduction of commercial lineages or improved crossbred turkeys for production. Turkey populations from rural communities in Andalusia, Majorca, Egypt, Iran, Italy, and the USA consisted of six haplotypes, which has not previously been reported for


Paris polyphylla var. yunnanensis is one of the original plants used to make the traditional medicine Paridis Rhizoma. Wild individuals have been excessively collected in recent decades, and thus, it has become increasingly endangered. Cultivation is a major method for the conservation and sustainable utilization of its wild resources. In this study, amplified fragment length polymorphism markers were used in the genetic analysis of 15 wild and 17 cultivated populations of P. polyphylla var. yunnanensis. This study revealed that cultivated populations possessed higher genetic diversity than wild ones at the species level . However, most of the genetic variation was found within populations for both of these groups (ΦST = 18.83% vs. 19.39%). In the dendrogram produced using UPGMA, the 32 populations were divided into three groups . In group II, both wild and cultivated populations were included, but remained in distinct clusters within this group, which showed the significant separation between the cultivated and wild populations. Furthermore, wild populations were also clustered into three subgroups , with an obvious geographic structure. In contrast, although cultivated populations were similarly placed in three subgroups , the latter two of these were not separated based on geography. Finally, the wild populations in Guizhou, China (W‐I), possessed higher genetic diversity than those in Yunnan (W‐II and W‐III). As P. polyphylla var. yunnanensis is an endangered medicinal plant, the fact that it showed richer genetic diversity in its wild populations in Guizhou means that these should be regarded as priority areas for protection and used for provenance selection. Moreover, cultivated populations also showed high genetic variation, which might be attributed to them having originated from mixed provenances, indicating that screening for superior provenances should be carried out as soon as possible. Paris polyphylla var. yunnanensis is an important medicinal and endangered plant. This study explored genetic diversity and structure of its wild and cultivated populations. Among these, RFLP . Hand.‐Mazz. is one of these varieties, and is mainly distributed in southwestern China  spatial patterns in genetic variation within and among both wild and cultivated populations; (b) genetic differences between the wild and the cultivated populations; and (c) the mixed provenances on which cultivated populations were based.In our study, we collected 22.1P. polyphylla var. yunnanensis were sampled from 32 populations, including 15 wild and 17 cultivated populations, from throughout this variety's main geographic distribution in China  in a 20 μl reaction mixture, after which it was kept at 65°C for 3 hr to ensure enzyme inactivation. Next, the digested products were ligated to 50 μM EcoRI and 50 μM MseI adaptors using 5 U T4 DNA ligase. Then, 2 μl of the ligation product was pre‐amplified with 0.5 μl of each single selective primer (20 μM E00 and 20 μM M00), 2 μl of 10 × T4 buffer, and 0.4 μl of 10 mM dNTPs in a final volume of 20 μl. Amplification conditions were the following: 3 min at 94°C; 45 s at 94°C; and 26 cycles of 45 s at 50°C and 1 min at 72°C. The pre‐amplified product was then diluted 20‐fold, and 2 μl of the diluted product was selectively amplified with 2 μl of 10 × buffer, 0.4 μl of 10 mM dNTPs, 0.2 μl of 5 U Taq, 1 μl of 20 μM EcoRI primer, and 1 μl of 20 μM MseI primer  in a final volume of 20 μl. The thermal cycling parameters for this selective amplification were as follows: 5 min at 95°C; 12 cycles of 35 s at 95°C, 35 s at 65°C , 1 min at 72°C; and 23 subsequent cycles of 30 s at 94°C, 30 s at 56°C, and 1 min at 72°C. Finally, the selective amplification products were 10‐fold diluted and mixed with the GeneScan 500 LIZ size standard, and then, the mixed products were detected using an ABI 3730XL automated DNA sequencer (Applied Biosystems™). In fragment analysis, FAM was adopted to label primers of AFLP markers. Fragments were analyzed with GeneMarker v.1.70 . Fragments were scored as either present (1) or absent (0) when the intensity was up to 100.Amplified fragment length polymorphism analysis was performed as described below, according to the standard protocol , Nei's genetic diversity (H), Shannon's information index (I), and the percentage of polymorphic bands (PPB). ArcGIS v. 10.3 (Esri) was used to draw maps of the geographic distribution of the sampled wild and cultivated populations of P. polyphylla var. yunnanensis.Genetic diversity parameters were calculated using PopGen32  dendrogram , an admixture model and correlated allele frequencies were chosen for use in this analysis. At the same time, ten replicates of each simulation with 2–10 clusters (K = 2–10) were simulated through 10,000 Markov chain Monte Carlo (MCMC) steps by sampling after a burn‐in period of 10,000 iterations. STRUCTURE HARVESTER was used to extract the relevant data from the structure results files and to generate CLUMPP input files  to reveal the relationships among populations , an important parameter for evaluating genetic diversity, was higher in the cultivated populations than that in the wild ones at the species level , whereas the value was as high as 0.2657 if all 32 of the sampled populations were considered together .In this study, a total of 669 loci were detected by five of the selected pairs of AFLP primers. Assuming Hardy–Weinberg equilibrium, Nei's genetic diversity . Moreover, most of the populations in Guizhou Province possessed relatively high genetic diversity values, except for XY, from which only four individuals were sampled. On the other hand, the wild populations in Yunnan showed \lower genetic variation than the others, especially the YP, LY, and CN populations in western Yunnan. However, among the cultivated populations, the situation was completely different compared with that among the wild ones. The cultivated populations in Guizhou possessed much lower genetic diversity than those in Yunnan. For instance, the LL population in Guizhou, from which 20 individuals were sampled, still showed significantly lower genetic variation than the SM and YP populations in western Yunnan.H = 0.2181) than that possessed by the remaining subgroups in Yunnan . However, a totally different situation was found for the cultivated populations. The genetic variation within the subgroup C‐I (H = 0.1430), also located in Guizhou, was lower than that in the other subgroups in Yunnan .When the groupings of wild populations identified in our clustering analysis were considered Figures  and 2, s3.2r = .6767, p = .001)  Figure  indicateK) was inferred by the peak ΔK found in the STRUCTURE analysis. According to the method of Evanno, Regnaut, and Goudet . During fieldwork, we found that this variety was widely distributed in southwestern China, but it was nearly impossible to collect enough individuals for sufficient statistical power (n = 30) from most of its wild populations. Therefore, the evaluation of the genetic diversity of wild populations of this variety should be vital for the formulation of protection strategies and the utilization of wild resources. The present study revealed that the genetic diversity of P. polyphylla var. yunnanensis at the species level (H = 0.2636) (Table H = 0.2768 for AFLPs)  and P. thibetica var. thibetica (H = 0.2439)  based on the analysis of ISSR markers, this difference in the diversity detected could be attributed to differences in sample sizes and marker types among studies     . It was regrettable that samples were only collected from one population (HD) in Sichuan, so further surveys and studies on the populations of this variety distributed in Sichuan and adjacent regions will be extremely important. The wild populations in Guizhou and Sichuan should thus be regarded as priorities for protection, and used for the screening of superior provenances for future cultivation efforts.In this study, we mainly collected samples from wild populations in Yunnan and Guizhou, as well as one population in Sichuan Table . Our fin4.2H = 0.2636 vs. 0.2616, respectively), as well as at the population level (H = 0.2002 vs. 0.2001), indicating that cultivation of P. polyphylla var. yunnanensis has not yet resulted in any obvious loss of genetic variation. Our findings were consistent with those reported in a previous study  and W‐III (0.1875) subgroups was lower, suggesting that the populations on the Guizhou Plateau might be more valuable than others for wild conservation and the breeding of cultivated varieties of P. polyphylla var. yunnanensis.The spatial genetic structure of a species' populations reflects the interactions involved in their long‐term evolutionary history, such as habitat fragmentation, genetic drift, type of mating system, and gene flow    Figure , some ing Brown, .P. polyphylla var. yunnanensis was much more popular in Yunnan than in Guizhou, which was also reflected in our collection information . Among these, the populations in the C‐II subgroup were mixed with the wild populations  compared with that detected in previous studies of F. cirrhosa D. Don , the low genetic differentiation among these should likely be attributed to the mutual introduction of some of the same provenances among the bases of cultivated populations. Moreover, the spatial genetic structure of the wild populations was relatively significant based on the UPGMA dendrogram, STRUCTURE analysis, and PCoA results, but since only 12.11% of the genetic variation found existed among groups, this indicated that the spatial structuring of these populations might not be very strong.According to the AMOVA results, there was no obvious overall genetic differentiation between the sampled wild and cultivated populations, as only 1.35% of the genetic variation found existed between these two types of populations , so southern Sichuan should be also be listed as a priority site for further study. Furthermore, reasonable manual intervention, such as removing seed coats and then sowing seeds in wild habitats, could improve the germination rates of seeds, and thus would benefit the renewal and maintenance of effective wild populations.Although both artificial cultivation and ex situ conservation are effective means of protecting 5P. polyphylla var. yunnanensis. The result revealed that there was moderate genetic variation among wild populations. Wild populations located in Guizhou Province possessed higher genetic diversity than populations in Yunnan Province, suggesting that populations in Guizhou should be given priority protection. Compared with wild populations, the cultivated ones did not show obviously lower genetic variation. However, further analyses at the individual level revealed the confusing provenances of the bases of many cultivated populations. UPGMA dendrograms divided the wild populations into three subgroups  with a clear spatial geographic structure, which was also supported by STRUCTURE, Mantel test, and PCoA results. However, although the cultivated populations were also clustered into three subgroups , the latter two subgroups, which were mainly located in Yunnan, did not show significant correlations between the genetic and geographic distances among populations within them. This study indicated that cultivated seedlings had complicated and confusing origins, so the selection and breeding of varieties with good and homogenous quality should be listed as a priority for the future cultivation of P. polyphylla var. yunnanensis. This study not only explored the genetic diversity and population structure of wild populations of P. polyphylla var. yunnanensis, but also revealed that cultivated populations presented some defective provenances. These findings could be beneficial to both the conservation of wild resources and the development of more robust cultivation approaches for this medicinal species.In this study, AFLP markers were adopted as a means to explore and compare the genetic diversity and population structure of wild and cultivated populations of The authors declare that they have no conflict of interest.Y.H. collected samples, analyzed the data, and wrote the primary manuscript. N.Z. performed fieldwork and covered the costs of this study. M.Y. performed the main experiments, and Y.X.S. helped to perform field investigations. D.Q.Z. conceived the research, analyzed the data, and revised the final manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Drosophila melanogaster, the majority of these studies have analyzed North American and Australian populations, leading to the identification of several loci and traits under selection. However, several studies based mainly in North American populations showed evidence of admixture that likely contributed to the observed population differentiation patterns. Thus, disentangling demography from selection might be challenging when analyzing these populations. European populations could help identify loci under spatially varying selection provided that no recent admixture from African populations would have occurred. In this work, we individually sequence the genome of 42 European strains collected in populations from contrasting environments: Stockholm (Sweden) and Castellana Grotte . We found low levels of population structure and no evidence of recent African admixture in these two populations. We thus look for patterns of spatially varying selection affecting individual genes and gene sets. Besides single nucleotide polymorphisms, we also investigated the role of transposable elements in local adaptation. We concluded that European populations are a good dataset to identify candidate loci under spatially varying selection. The analysis of the two populations sequenced in this work in the context of all the available D. melanogaster data allowed us to pinpoint genes and biological processes likely to be relevant for local adaptation. Identifying and analyzing populations with low levels of population structure and admixture should help to disentangle selective from non-selective forces underlying patterns of population differentiation in other species as well.Signatures of spatially varying selection have been investigated both at the genomic and transcriptomic level in several organisms. In  Analyses of several populations collected along environmental gradients, and of pairs of populations from contrasting environments are often used to identify genetic variants under spatially varying selection. Several approaches have been applied to the detection of adaptive evolution, from investigating the genetic basis of a known adaptive trait, to the identification of candidate adaptive variants without a priori knowledge of the relevant adaptive phenotypes5. All these approaches have been boosted by the availability and reduced costs of sequencing technologies that are being applied at the genomic and transcriptomic level6. Insights on the genomic targets of spatially varying selection, the molecular mechanisms underpinning local adaptation, and the extent of parallel adaptation, in model and non-model species, is starting to accumulate3. However, several challenges such as the role of demography in the observed population differentiation patterns, and thus the identification of the true targets of spatially varying selection still remain7. In this work, we tested whether European Drosophila melanogaster natural populations could be a good model system to disentangle the effects of demography and selection, and thus to identify candidate genes for local adaptation.Understanding how organisms adapt to their environment and more specifically which genes and which biological processes are more relevant for adaptation are still open questions in evolutionary biology. In the last decades, adaptation to new environments associated with colonization processes, and adaptation to changing environmental conditions, both natural and human-driven, has been extensively studiedD. melanogaster has several characteristics that makes it an exceptional organism to pinpoint adaptive variants, and thus to advance our knowledge on the genes and biological processes that are more relevant for adaptation. This species has recently (10.000–16.000 years ago) colonized worldwide environments from its ancestral range in subtropical Africa8. This colonization required adaptation to both biotic and abiotic factors present in the new environments. Thus, a wide-range of adaptations should be common in this species, and they should still be detectable as partial or complete sweeps at the DNA level9. Moreover, in D. melanogaster the identified genetic variants can be mapped to a well-annotated genome, and the wealth of genetic tools available allows to experimentally test the molecular mechanism and fitness consequences of the identified genetic variants10. Not surprisingly, D. melanogaster has been extensively used as a model organism to identify the genetic targets of spatially varying selection11. These studies have identified genetic variants and traits involved in geographical adaptation although only rarely genetic variants have been connected to fitness-related traits21.D. melanogaster populations . However, the identification of genes underlying local adaptation in populations from North America is confounded by the admixture between European and African populations27. Bergland et al.25 have also suggested that Australian populations were likely founded by both European and African lineages. The secondary contact between D. melanogaster populations from the derived and ancestral ranges of the species could create population differentiation patterns similar to those created by spatially varying selection. Thus, identification of clinally variant loci should not be taken as evidence of spatially varying selection without considering also the potential role of admixture in the patterns observed25. Looking for overlapping patterns of population differentiation in closely related species has recently been used to overcome this limitation29. Comparing the stability of clines over long time periods should also help distinguish between polymorphisms maintained by selection and polymorphisms resulting from recent admixture35. Alternatively, comparing populations from other continents in which recent admixture has not occurred could also help in the identification of loci under spatially varying selection. Populations from the European continent might be a good dataset to identify loci under spatially varying selection as no evidence of admixture has been reported for the populations studied to date22.Most of our knowledge on the genetic basis of spatially varying selection so far comes from the analyses of North American and Australian 40. TEs are particularly likely to be involved in adaptation because they generate mutations that often have complex phenotypic effects42. In a series of analyses, we previously investigated a subset of TE insertions in two North American, two Australian, and two populations collected in opposite slopes of the Evolution Canyon, in Israel, that although being geographically close have temperate- and tropical-like climates38. While some insertions showed parallel patterns in North America and Australia, none of the investigated TEs differed in the Evolution Canyon populations suggesting that they might not be targets of spatially varying selection38. However, the dataset of TEs analyzed in these studies was incomplete and biased. Thus, further analyses are needed to get a more complete picture of the role of TEs in local adaptation38.Another characteristic of the studies performed to date is that most of them are based on the analysis of a single type of genetic variant, which most often is Single Nucleotide Polymorphisms (SNPs). Other type of variants that are also likely to play a role in adaptation, such as transposable element (TE) insertions, other copy number variants, and inversions, remain understudiedD. melanogaster populations could be a good model system to disentangle demography from selection, and thus to identify genomic targets of spatially varying selection. To accomplish this, we first tested whether two European populations collected in localities with contrasting environments: Stockholm in Sweden, which has a humid continental climate, and Castellana Grotte in Bari, Southern Italy, which has a hot summer Mediterranean climate, showed evidence of population structure or admixture patterns 44 , Southern Italy, to an average coverage of 28.6x using Illumina technology 43 44 . In this case, estimates of genome-wide diversity were smaller, suggesting that by sampling only one allele we might be underestimating the genome-wide diversity (Table We estimated genome-wide diversity levels (π) for the two European populations sequenced in this study, and for the North American and African strains47. Indeed, we found that the average polymorphism on the X chromosome is reduced relative to autosomes both in the Swedish and Italian populations . The empirical genome-wide distribution of FST, which reflects primarily drift and other non-selective forces, had a maximum around zero and exponentially decays with a long tail of high FST values t common cosmopolitan inversion was different from those of the rest of the chromosomal arms. Additionally, we tested whether the proportion of candidate SNPs  differed between the inversion and the rest of the chromosomal arm t inversion was significantly higher than the median FST outside this inversion: 0.0080 vs 0.0068 . However, we did not find a significant accumulation of candidate differentiated loci inside the inversion t inversion status, we found that although other functional categories are enriched in differentiated SNPs, distal promoter, core promoter and intergenic regions are the three categories that showed a more significant enrichment of candidate SNPs . ZST scores are approximately normally distributed with positive values indicating high levels of population differentiation and negative values indicating low levels of population differentiation , and three additional more strict algorithms  that eliminate local similarities and dependencies between GO terms in order to reduce the false-positive rate . The candidate 657 genes were enriched in 43 GO terms according to at least one of the more strict algorithms, which we classified into broader categories to simplify their interpretation t inversion. However, this gene has been previously identified when analysing different natural populations, and also showed expression changes when comparing temperate with tropical populations55.To identify the most likely candidate SNPs to play a role in local adaptation, we focused on the 22 genes that belong to the four GO terms that were consistently found to be overrepresented across algorithms: response to insecticide, cuticle pigmentation, neuropeptide signalling pathway, and cell wall macromolecule catabolic process Table . For eacST Table . We checST signal in the genome corresponds to a coding change in the Acetylcholinesterase (Ace) gene that has been previously identified as conferring insecticide resistance in D. melanogaster56. Ace is a well-known insecticide resistance gene across insects57. In this gene, we also identified two additional coding mutations that are known to confer insecticide resistance 58. Besides these three coding mutations, we identified two new coding mutations with unknown functional impact . A new candidate mutation was also identified for Cyp6g1  and in cell wall macromolecule catabolic process  the differentiated genes are located next to each other, forming two physical clusters of genes that are co-differentiated and functionally related . However, it fails to detect more subtle trends in which most genes annotated to the same GO term might not belong to the top 5% of the ZA total of 31 GO terms were found to be significantly enriched by the three algorithms and 58 additional GO terms were found to be significantly enriched by at least one of the more strict algorithms. The list of 89 GO terms was classified into broader categories to simplify its interpretation . The empirical distribution of the FST estimates for TEs was very similar to the SNPs FST values distribution , and analyzed their associated biological processes GO terms Table . Interes44. Our results confirmed that there is population structure across continents, and that North American populations show admixture with African populations  resistance (reviewed by True68). The Swedish and Italian populations analyzed in this work differed in temperature, humidity, and UV exposure, and thus it is reasonable to find significant differentiation in SNPs related to pigmentation69. Defense response is also considered as an important trait affecting the ability of species to colonize new environments70. Besides the genes functionally annotated as defense response, three of the six genes functionally annotated as cell wall macromolecule catabolic process have been associated with anti-parasitic defense response71. Finally, the GO analysis also pinpointed six GO terms previously identified in clinal variation studies  from the National Center for Biotechnology Information (NCBI) under the BioProject accession: PRJNA390275.Genomes reported here are derived from two natural population samples collected in Stockholm  and in Castellana Grotte  in September and October 2011, respectively  from the DPGP2 panel43 were also analyzed  that were analyzed using the same pipeline  from the DGRP panelsickle v.1.2 when mean quality dropped below 2078. Reads shorter than 50 bp were discarded. Read mapping to the D. melanogaster reference genome (Flybase release 5) was performed using bwa-Backtrack v. 0.78 algorithm using strict default parameters79. Optical duplicates were marked with Picard v.1.115. The alignment around indels was refined using GATK v.3.2 IndelRealigner80. Reads with a BWA mapping quality score less than 20 and unmapped reads were realigned using Stampy v.1.0.20 for a more accurate re-mapping81. Reads with a Stampy mapping score higher than 20 were merged with the previous alignment. The distribution of coverage per base pair was calculated for each strain using GATK BaseCoverageDistribution. The coverage values corresponding to the 0.975 percentile were calculated for each strain using a custom R script  estimates82 and included 2 L:530,000–18,870,000; 2 R:1,870,000–20,860,000; 3 L:750,000–19,020,000; 3 R:2,580,000–27,440,000; and X:1,220,000–21,210,000. These regions contained a total of 4,804,172 SNPs. SNPs within 5 bp of indels or other types of complex mutations and SNPs falling in repetitive or low complexity regions according to RepeatMasker were excluded to obtain a set of 4,106,958 SNPs. Different further filters were specifically applied in each analysis and are detailed in the corresponding sections (see below).We followed the two-step GATK variant calling pipeline as follows. First, haplotype calling was performed independently for each strain using 43. Genome-wide diversity levels (π) were estimated for non-overlapping windows of 10,000 SNPs using vcftools v.0.1.12. The average nucleotide diversity was calculated for the whole genome and separately for the autosomes and the X chromosome using an ad hoc R script. We calculated nucleotide diversity considering that we were sampling two alleles. Because it is possible that in each isofemale strain genome we are sampling greater than or less than two alleles per locus, we also estimated nucleotide diversity after sampling one allele per genome with a weighted probability based on allelic read counts using an ad hoc python script.Regions of known cosmopolitan admixture in the African strains were excluded from the initial dataset of 4,106,958 SNPs, yielding a total of 3,749,072 SNPs83 unbiased estimator of the fixation index (FST) was estimated between each pair of populations using vcftools84. Population structure was also assessed by principal component analysis using Eigensoft and model-based global ancestry estimation using Admixture. SNPs with a minor allele frequency <15% or a genotyping rate lower than 70% were excluded. Two African strains with a variant calling lower than 70%  were also excluded. The final set consisted on 68,390 high confidence SNPs. Model-based global ancestry was estimated using Admixture software85. The number of ancestral populations analyzed (k) ranged from 1 to 7. Cross validation error for each value of k was used to determine the most likely hypothesis. The ancestry coefficients for each strain were plotted using the ggplot2 v1.0.0 library loaded in R v-3.1.0.Global weighted Weir & CockerhamN individual calls with coverage lower than 10x or higher than the 0.975 percentile of the coverage per base pair distribution for the strain considered  only non-singleton biallelic SNPs were considered; (ii) A custom perl script was used to filter to ST. Significance of the heterogeneity in population differentiation levels across chromosomal arms was determined by performing one-way ANOVA. In subsequent analyses, the empirical distribution of FST in each chromosomal arm was used to identify outliers. Genomic differentiation within the In(2 L)t common cosmopolitan inversion (2 L:2225744.0.13154180)43 was compared to the levels observed in the rest of the chromosomal arm by performing a Mann-Whitney U test. We also estimated the population frequency of common and rare cosmopolitan inversions in the 42 European strains analysed in this work using the panel of SNPs known to be associated with these inversions34.A total of 1,123,227 SNPs passed our conservative filtering pipeline in the European populations and were used to calculate the pairwise FVariantAnnotation R/Bioconductor package86. Out of the initial 1,123,227 SNPs, 1,121,948 could be annotated into the following functional categories: intergenic, promoter , core promoter (316 bp upstream of the transcription start site87), 5′ UTR, coding, splice site, intron, and 3′ UTR using TxDb.Dmelanogaster.UCSC.dm3.ensGene R/Bioconductor package v.2.14.0. Coding variants were further classified into synonymous and non-synonymous. In order to obtain a set of neutrally evolving polymorphisms, we extracted those SNPs falling within the first 8–30 base pairs of small introns (< = 65 bp)88. The rest of intronic SNPs, which mostly belong to large introns, were classified as non-small intronic SNPs.Functional annotation of SNPs was performed using ST distribution were determined for each functional category. Two sided Fisher’s exact test was used to determine if there were non-random associations between functional category and belonging to the 95% of the chromosomal arm FST distribution, or to the top 5%, 1% or 0.5% tails, while controlling for allele frequency, chromosomal arm, and considering SNPs in small introns as background of our analyses. The same procedure was used to determine if there was an over- or under-representation of candidate differentiated loci specifically located inside In(2 L)t inversion with respect to the rest of each chromosomal arm.Counts of SNPs falling in the top 5%, 1% and 0.5% tails of the chromosomal empirical FST values were converted to gene-wise FST values by assigning to each gene the maximum FST value among those SNPs found along its transcribed region and the 1 kb region upstream of the transcription start site. This has been shown to be a good representation of the FST per gene45. Maximum FST values per gene were normalized to a Z score using chromosome specific empirical FST distributions. There was a positive correlation between gene length (and number of SNPs) and Z score   , we used three other algorithms: elim, weight and weight01 to identify significantly enriched GO biological processes. While in the classic enrichment test each GO term is tested independently, in the other three algorithms the hierarchical structure of the GO is taken into account so that the enrichment score incorporates information about the whole GO topology. This eliminates local similarities and dependencies between GO terms and reduces the high false-positive rate that is usually attained with classic GO enrichment tests89. The elim method iteratively removes genes annotated to significant GO terms from their ancestors, following a bottom-up approach. This allows for the identification of more specific nodes in the GO graph. The Weight algorithm identifies the locally most significant terms in the GO graph (and not necessarily the most specific terms). Weight01 is a combination of weight and elim algorithms. We decided to look at the results yielded by elim, weight and weight01 in order to explore which areas in the GO graph contain enriched GO terms instead of finding the precise GO terms that are enriched. Only GO terms with 5 or more differentiated genes were considered. We considered that a GO term was significantly enriched when the p-value computed by the elim, weight or weight01 algorithms was smaller than 0.05. These methods are internally reducing the significance of most GO terms and practically disregarding many of them, reducing the probability of having false positives due to the multiple-testing problem. As such, the raw p-values obtained with this methods can be considered as corrected p-values89.Gene Ontology (GO) term enrichment analysis in the list of 657 candidate differentiated genes was performed using T-lex2) to estimate presence/absence of TEs in each individual strain from the Italian and Sweden population65. We used release 5 of the Drosophila melanogaster genome as reference along with TE coordinates downloaded from FlyBase90. From the original 5,416 TE dataset, we excluded TEs overlapping other TEs, TEs that are part of segmental duplications, and TEs flanked by other repetitive regions65. In addition, we excluded TEs belonging to the INE family  because we expect them to be fixed93. Overall, T-lex2 was run for 1,632 TEs.We used T-lex version 2 . A total of 556 TEs were at a frequency lower than 5% in both populations, 893 TEs were fixed in both populations, and for 22 TEs T-lex2 was not able to determine the population frequencies. We ended up with FST values for 161 TEs. We compared the FST values obtained for the TEs to the empirical distribution of FST values obtained for SNPs. Those TEs falling in the top 5%, 2.5% or 0.5% tails of the distribution were considered as candidate differentiated TEs.Using the presence/absence information provided by Supplementary informationSupplementary Table


The rarity of human remains makes it difficult to apprehend the first settlements in Corsica. It is admitted that initial colonization could have occurred during the Mesolithic period when glaciations would have shortened the open water travel distance from the continent. Mesolithic sites in Corsica show relatively short and irregular occupation, and suggest discontinuous settling of very mobile groups probably traveling by boat. Previous genetic studies on Corsican populations showed internal differentiation and a relatively poor genetic relationship with continental populations, despite intense historical contacts, however local Mesolithic-based genetic inheritance has never been properly estimated. The aim of this study was to explore the Corsican genetic profile of Y-chromosomes in order to trace the genetic signatures back to the first migrations to Corsica. This study included 321 samples from men throughout Corsica; samples from Provence and Tuscany were added to the cohort. All samples were typed for 92 Y-SNPs, and Y-STRs were also analyzed. Results revealed highly differentiated haplogroup patterns among Corsican populations. Haplogroup G had the highest frequency in Corsica, mostly displaying a unique Y-STR profile. When compared with Provence and Tuscany, Corsican populations displayed limited genetic proximity. Corsican populations present a remarkable Y-chromosome genetic mixture. Although the Corsican Y-chromosome profile shows similarities with both Provence and to a lesser extent Tuscany, it mainly displays its own specificity. This study confirms the high level of genetic diversity in Corsican populations and backs genetic contributions from prehistoric migrations associated with the Mesolithic, Neolithic and Metal Age eras, rather than from historical movements to Corsica, respectively attested by frequencies and TMRCA of haplogroups G2a-L91 and G2a-P15, J2a-M241 and J2-DYS445 = 6, R1b-U152 and R1b-U106. These results suggest that marine routes to reach the Corsican coast in many different points may have led to such a genetic heterogeneity. Corsica is the fourth largest island of the Mediterranean, located 177km south-east of Provence and 85km west of Tuscany. The rarity of human remains due to the acidity of natural sediments, the sea-level rising and uncertainty regarding the Paleolithic era, all make it difficult to apprehend the first settlements in Corsica.th millenium BC onwards, due to external contributions attested by an importation of foreign stones to the island, flint and obsidian, and Impressed Ware, Cardial and Bell-Beaker potteries .Phylogenetic networks were constructed for haplogroups represented by more than 10 individuals using the program Network 4.6.1.1 (Fluxus-Engineering) and applying the median joining algorithm with the following STR loci: DYS19, DYS388, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS439 . NetworkTMRCA for haplogroups with frequencies above 3% were estimated using eight Y-STR markers  and a mean evolutionary rate mutation of 0.000069 ±0.000013 per locus per 25 years .kriging interpolation method [Spatial frequency maps were drawn up for haplogroups and related sub-haplogroups that were detected with a frequency of at least 3%. Frequency data were converted into frequency maps using Surfer software , following the n method .Y chromosome haplogroup frequencies from 83 Mediterranean populations in published data  totalizing 7588 men were harmonized to a common set of 12 lineages: E-M96 (xM35), E-M35 (xM78), E-M78, G-M201, I-M170, J1-M267, J2-M172, R2-M479, R1-M173, K-LT-NOP-M9 (xM207), CF-M130-M89 , and Y ,33–42. GHierarchic phylogenetic relationships and frequencies, as well as haplogroup diversity of the 54 paternal haplogroups observed in the 321 Corsican, 259 Provencal and 261 Tuscan samples are described in Haplogroup R represented approximately half of the lineages in both Corsican and Tuscan samples (respectively 51.8% and 45.3%) whereas it reached 90% in Provence. Sub-clade R1b1a1a2a1a2b-U152 predominated in North Corsica whereas R1b1a1a2a1a1-U106 was present in South Corsica. Both SNPs display clinal distributions of frequency variation in Europe, the U152 branch being most frequent in Switzerland, Italy, France and Western Poland. Calibrated branch lengths from whole Y chromosome sequencing ,45 and aHaplogroup G reached 21.7% in Corsica and 13.3% in Tuscany. Sub-clade G2a2a1a2-L91 accounted for 11.3% of all haplogroups in Corsica yet was not present in Provence or in Tuscany. Thirty-four out of the 37 G2a2a1a2-L91 displayed a unique Y-STR profile, illustrated by the star-like profile of STR networks . G2a2a1aHaplogroup J, mainly represented by J2a1b-M67(xM92), displayed intermediate frequencies in Corsica compared to Tuscany and Provence. J2a1b-M67(xM92) derived STR network analysis displayed a quite homogeneous profile across the island with an estimated TMRCA of 2381 +/- 449 years  and indiHaplogroup E, mainly represented by E1b1b1a1b1a-V13, displayed intermediate frequencies in Corsica compared to Tuscany and Provence. E1b1b1a1b1a-V13 was thought to have initiated a pan-Mediterranean expansion 7,000 years ago starting from the Balkans  and its Haplogroup I was not found in Provence whereas it was present in both Corsica and Tuscany, respectively as I1 and I2 lineage, although at low levels. Haplogroup I is widespread throughout Europe with a strong geographic differentiation but virtually absent elsewhere. Haplogroup I1 is mostly found in northern Europe; haplogroup I2 has two sub-branches defined by P37.2 and M436 markers, respectively. The latter sub-branch is widespread Balkan Peninsula . AncientHaplogroup Q-M242 was mostly found in Sevi (5 of the 6 chromosomes) with quite similar STR patterns . HaplogrHaplogroup T1a-M70, known as Thomas Jefferson’s Y chromosome and relatively rare in other Near Eastern populations , was obsThe Corsican population displayed a significant portion of variance when compared with Provence and Tuscany . The greatest variance was found when four groups were made up  with Pisa, north-western Corsica , Provence, and the rest of Corsica, labeled East/South Corsica.PCA  shows thHaplogroup frequency analysis supports genetic similarities between Corsican, Cagliari and northern Sardinian Tempio populations, whereas Tuscan and Provencal samples cluster with continental Italy. Y-STR data showed genetic relationships of Provence and northern Corsican samples with Tuscan, central Italian and Ligurian populations, while southern Corsicans clustered with southern Italians and Sicily  Figs.The genetic profile of Corsican Y-chromosomes was explored in order to retrace the genetic signatures back to the first migrations to the island during prehistoric times. A total of 842 individuals including 321 from Corsica, 259 from Provence (France) and 261 from Tuscany  were analyzed for Y-chromosome haplogroups. Their results were compared to databases from published literature on Mediterranean populations.Our results showed a highly heterogeneous distribution of Y-chromosome haplogroups in the 183km long and 83km-wide island, with a mosaic of numerous small-scale, micro-regional population groups.The most ancient Corsican genetic signatures might be represented by haplogroup I2 derived individuals, as this haplogroup was reported to be associated to human expansion phase of Sardinia during pre-Neolithic period . NeolithDifferential distribution of R1b-U152 and R1b-U106 haplogroups and their respective TMRCA seem to coincide with the two groups of Menhir-statue mostly erected during the Bronze Age. The northern Menhir-statue group has slim figures and prominent ears, whereas in the larger Menhir-statue group, located south of the Ajaccio-Solenzara line, they are rougher and display warrior attributes ,5,61.Greek Anatolian historical settlement in Alaria coincided strikingly with haplogroup E-V13 distribution . HaplogrThese results support the hypothesis of multiple discontinuous settling in Corsica and may hint a presence of Mesolithic lineages in Corsican patrilineal gene pool, in accordance with archaeological data from Mesolithic, Neolithic and Bronze Age periods. They also confirmed, as previously reported by genetic and surname-based studies, a very low rate of exogamy within the island leading to Y-chromosome pattern distribution structured by geography, due to the mountainous landscape of Corsica.Concerning genetic relationships between Corsica and Sardinia, our results corroborated with different genetic heritage for both islands. However, high genetic affinity between the Sardinian population and the Corsicans was previously reported ,15,16 anThe Corsico-Sardinian block is characterized by climatic contrast: glacial sediments found in the north of Corsica reveal three glacial periods, whereas these sediments are absent in Sardinia where the climate was characterized by rainy periods. It is reasonable to assume that the first groups of humans would have preferentially settled in regions where the climate was more clement. Then, only when the climate became warmer, would these populations have moved towards Corsica from the north of Sardinia . OverallOn a western Mediterranean scale, genetic studies have published controversial results, with studies showing on the one hand affinities between southern Corsica, central and northern Sardinia, Sicily and Turkey, and on the other hand between north-west and central Corsica and the south of Sardinia ,17; on tOur results support genetic affinities between north-western Corsica and continental populations whereas East/South Corsican populations originated from western Mediterranean populations. These two clusters are in accordance with the dramatic divergence of populations from north and south Corsica described here and supported by genetic, linguistic and archaeological studies and possibly explained by a divergence of population history accumulated since Neolithic times between the north and south of the island. These results are in accordance with the hypothesis of different genetic destinies for populations from mainland Europe and those from the islands of the Tyrrhenian sea, reported to have begun to diverge at least 5,000 years ago .In conclusion, whereas it is widely believed that settlers in Corsica arrived from mainland Italy, due to a difference in the sea level during glaciations and the formation of a natural bridge with Tuscany, our results support that Corsica might have been colonized by many different waves of migration since Neolithic period and Bronze Age and led to such a heterogeneous Y-chromosome profile of the current Corsican population. The overall complexity of the genetic profile of Corsicans remains to be fully addressed with the study of complementary mitochondrial and autosomal markers.S1 FigHierarchic phylogenetic relationships and frequencies (percentages), haplogroup diversity observed in the 321 Corsican, 259 Provencal and 261 Tuscan samples.(XLSX)Click here for additional data file.S2 FigPopulations from Corsica, Provence and Tuscany under study and Italian populations from Boattini A, et al. 2013 .(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 FigBlack: present study, open squares: Oltremontano speakers, filled squares: Cismontano speakers. Others colors refer to the eight Italian areas in Boattini A, et al. 2013  (Light G(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableF and R stand for Forward and Reverse respectively.(XLSX)Click here for additional data file.S3 TableF and R stand for Forward and Reverse respectively.(DOC)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.


Rhinolophus euryale is a cave-dwelling species that exhibits roost philopatry and undertakes seasonal movements which are usually shorter than 50 km. Its distribution in Serbia is restricted to karstic areas in western and eastern parts of the country, with a lack of known roosts between them. In this study, microsatellite markers were used to evaluate genetic variation in this species in the Central Balkans. Specifically, spatial genetic structuring between geographic regions and relatedness within different colony types were assessed. All analysed loci were polymorphic, and there was no significant inbreeding coefficient recorded. A moderate degree of genetic differentiation among the sampled colonies was found, and significant isolation by distance was recorded. Our results revealed that populations show a tendency to segregate into three clusters. Unexpectedly, populations from Montenegro and Eastern Serbia tended to group into one cluster, while populations from Western Serbia and Slovenia represented second and third cluster, respectively. The majority of variance was partitioned within colonies, and only a small but significant portion among clusters. Average relatedness within colony members was close to zero, did not differ significantly between the different colony types, and kinship is unlikely to be a major grouping mechanism in this species.Migratory behaviour, sociality and roost selection have a great impact on the population structure of one species. Many bat species live in groups, and movements between summer and hibernation sites are common in temperate bats. The Mediterranean horseshoe bat  Bats represent one of the most peculiar groups of mammals due to specific features such as nocturnality, self-powered flight and echolocation . NumerouMyotis bechteinii , nor on percentage of relatives within colonies .R. euryale displayed genetic substructuring across the analysed range. Isolation by distance was demonstrated in this species, with the greatest genetic differences observed between the samples from Western Serbia and Slovenia. Isolation by distance has also been detected in congeneric species Rhinolophus ferrumequinum across the species range [Myotis bechsteinii [M. myotis [Plecotus auritus [The results of this study revealed polymorphic loci and the absence of significant inbreeding in all analysed populations of the Mediterranean horseshoe bat. However, in spite of its flight ability, es range , and in hsteinii , M. myot. myotis  and Plec auritus .et al. [A lot of admixture was detected in Central Balkans and there was no obvious pattern of genetic differentiation. However, our analyses revealed existence of three groups , and this clustering pattern was supported by various analyses. Although existence of three genetic clusters was statistically highly supported, they were not geographically coherent and not easy to differentiate by looking at the admixture levels. Additionally, asigning populations from Montenegro and Eastern Serbia to the same cluster does not seem intuitive. Franz et al.  showed tet al. [et al. [Western Serbian group was always first to segregate in cluster analyses and these populations showed significant differentiation from almost all the populations from another two groups. Distances between colonies in Western and Eastern Serbia are greater than 100 km and the habitat between them is devoid of caves, thus it had been assumed that this would represent a barrier to gene flow. Within the Carpathian region, Uhrin et al.  recorded [et al.  found th [et al. , personaR. euryale has been recorded near Skadar lake and the Korab area in Albania , and there is a historical finding of this species in Kosovo, near the town of Peć [R. euryale could be using alternative roost types such as roof spaces of buildings  was significant and far more pronounced than between those from Montenegro and Eastern Serbia . High mountains in the north of Montenegro might act as a physical barrier, and to a certain extent restrict gene flow between colonies within Dinarides. Maybe the most peculiar discovery is the genetic similarity between populations from Eastern Serbia and Montenegrin population. According to significant isolation by distance that was confirmed in our study, it would be expected that these geographically distant populations (distances among roosts range 270–345 km) would be more genetically different. Furthermore, there was no significant correlation between genetic and environmental differences, and observed genetic pattern could not be explained with environmental factors. It is still unclear why these populations are genetically very similar. They showed a tendency to group together in clustering analyses and there were no significant differentiations between pairs of populations, suggesting that there might be gene flow occurring between them. Gene flow throughout Albania, Kosovo and southern Serbia could be a possible explanation for population connectivity between these regions. n of Peć . Due to n et al. ), or aban et al. .Rhinolophus species, Mediterranean horseshoe bat has a low wing loading and aspect ratio, causing a long-distance flight to be energetically inefficient [Moderate genetic differentiation among colonies of this species was found, that can be explained by non-migratory behaviour and roost philopatry, together with isolation by distance. Similar to other fficient ,22. Roosfficient ,24, persfficient , our finfficient ,63. Our Myotis bechsteinii [Nyctalus leisleri [Plecotus auritus [Rhinolophus ferrumequinum [et al. [R. euryale usually occurs in autumn transient roosts or in hibernacula [Our results disclosed very low (close to zero) mean colony relatedness values. Evidence of roost fidelity united with low values of relatedness within colony members has already been reported in several other temperate bat species, e.g. hsteinii , Nyctaluleisleri , Plecotu auritus , Rhinolomequinum . Kerth e [et al.  proposed [et al. ,14,65 shernacula , and undR. euryale is adapted for foraging in cluttered environments [In spite of natal philopatry to nursery roosts among females, our results showed that a large portion of individuals within colonies were non-relatives, and thus kinship is probably not a major factor underlying the formation of female groups. Benefits from group thermoregulation and sharing knowledge about accessible foraging areas are more likely to play important roles in establishing nursery colonies ,16. Relaronments . Thus, tOur study represents the first population genetics study of the Mediterranean horseshoe bat using microsatellite markers. The observed genetic diversity was high, but significant isolation by distance and moderate spatial population structuring were found. As previously reported, the most stable and largest populations of this species occur on the Iberian and Balkan peninsulas , and proS1 File(DOC)Click here for additional data file.S2 File(XLS)Click here for additional data file.S3 File(XLS)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 FigPlots of simple and partial Mantel tests showing the relationships between a) geographic and genetic distances, b) environmental and genetic distances. Triangle–pairs of populations belonging to the same genetic cluster, circle–pairs of populations belonging to differemt genetic clusters (under assumption that populations from Eastern Serbia and Montenegro belong to the same cluster). Red triangles represent pairs of populations within Eastern Serbia, and blue triangles pairs of populations from Eastern Serbia with Montenegrin population.(TIF)Click here for additional data file.S1 Table(DOC)Click here for additional data file.S2 Table(DOC)Click here for additional data file.S3 Table(DOC)Click here for additional data file.S4 Table(DOC)Click here for additional data file.


Sarcophilus harrisii, as candidates for genetic rescue. Since 1996, devil populations have been severely impacted by devil facial tumour disease (DFTD), causing significant population decline and fragmentation. Like many threatened species, the key threatening process for devils cannot currently be fully mitigated, so species management requires a multifaceted approach. We examined diversity of 31 putatively neutral and 11 MHC‐linked microsatellite loci of three remnant wild devil populations (one sampled at two time‐points), alongside computational diversity projections, parameterized by field data from DFTD‐present and DFTD‐absent sites. Results showed that populations had low diversity, connectivity was poor, and diversity has likely decreased over the last decade. Stochastic simulations projected further diversity losses. For a given population size, the effects of DFTD on population demography  did not impact diversity retention, which was largely driven by final population size. Population sizes ≥500 (depending on the number of founders) were necessary for maintaining diversity in otherwise unmanaged populations, even if DFTD is present. Models indicated that smaller populations could maintain diversity with ongoing immigration. Taken together, our results illustrate how multiple analysis types can be combined to address complex population genetic challenges.For bottlenecked populations of threatened species, supplementation often leads to improved population metrics (genetic rescue), provided that guidelines can be followed to avoid negative outcomes. In cases where no “ideal” source populations exist, or there are other complicating factors such as prevailing disease, the benefit of supplementation becomes uncertain. Bringing multiple data and analysis types together to plan genetic management activities can help. Here, we consider three populations of Tasmanian devil,  More generally, our analysis serves as a model for combining multiple data and analysis types to assess genetic rescue options in an applied conservation context.22.1N = 17), Stony Head (N = 24) and wukalina/Mt. William NP (N = 19)  collected devil samples from wild populations at Narawntapu NP  Figure . Althoug) Figure . Therefo2.2N = 4) were re‐amplified as positive controls to standardize scoring. Microsatellite genotyping protocols are provided in Supporting Information (“Methods S1”).DNA was extracted using a standard phenol/chloroform method with ethanol precipitation  and tests for deviation from Hardy–Weinberg equilibrium were evaluated using Arlequin v3.5  excluded zero.Structural relationships among the sampled individuals were also inferred using discriminant analysis of principal components , Stony Head  and wukalina/Mt. William NP . Population ceilings were based on the size of the area and devil density in disease‐free sites .Simulations were run for 50 years, approximately 20 devil generations, in accordance with devil management planning . Results are averaged over those replicates in which the simulated population did not go extinct .2.4q0 = 0.05), were modelled: one‐off supplementation of devils in the second year of the simulation or ongoing (two‐yearly) supplementations of devils. We modelled one‐off supplementations of sizes 0, 14 , 28 or 56 animals, and ongoing supplementations of size 0, 2, 4, 6, 8, 10, 12 or 14 animals every 2 years. For smaller population sizes, the higher levels of supplementation would lead to very high proportions of immigrants. We assumed an equal sex ratio of translocated animals and 90% survival following translocation. We also assumed that animals were sourced from a population that was not genetically differentiated from the recipient population. We assumed that, after any initial mortality associated with translocation, the introduced animals would show equal probability of breeding and survival as locally produced animals of the same age and sex. In a follow‐up set of models, migrants were given priority over locals in the breeding pool (using the AlleleRetain option mpriority = TRUE).The effects of two types of management options, on neutral genetic diversity , but not for the two heterozygosity statistics  as the starting condition of the recipient populations.For our three real populations, none of the one‐off supplementation options up to 56 animals) were sufficient to maintain 90% of rare alleles after 50 years  and one‐off supplementations at the beginning had little effect after 50 years . These molecular data support the argument that, from a conservation planning point of view, all three sites are in equivalent need of genetic rescue.The microsatellite data presented support previous reports of low genetic diversity in Tasmanian devils , as the latter is contingent on demographic, genetic and extrinsic factors, and interactions thereof (Carlson et al., In the spirit of the “Tools & Tech” project (Hogg et al, Taken together, the current results reveal a system in need of genetic rescue. Analysing the consequences of supplementation activities will continue to inform conservation strategy in the face of complex prevailing threats.5https://doi.org/10.5061/dryad.11ss226>Data for this study are available at the Dryad Digital Repository: None to declare.Informed consent: Not applicable; non‐human research. Click here for additional data file.