Climatic changes throughout the Pleistocene have strongly modified species distributions. We examine how these range shifts have affected the genetic diversity of a montane butterfly species and whether the genetic diversity in the extant populations is threatened by future climate change.Europe.Erebia epiphron Lepidoptera: Nymphalidae.E. epiphron across Europe to identify population refugia and postglacial range shifts. We used species distribution modeling (SDM) to hindcast distributions over the last 21,000 years to identify source locations of extant populations and to project distributions into the future (2070) to predict potential losses in genetic diversity.We analyzed mtDNA to map current genetic diversity and differentiation of Hd = 0.9). Genetic data and SDM hindcasting suggest long‐term separation and survival of discrete populations. Particularly, high rates of unique diversity in postglacially colonized sites in England (Hd = 0.64) suggest this population was colonized from a now extinct cryptic refugium. Under future climate change, SDMs predict loss of climate suitability for E. epiphron, particularly at lower elevations  equating to 1 to 12 unique haplotypes being at risk under climate scenarios projecting 1°C and 2–3°C increases respectfully in global temperature by 2070.We found substantial genetic diversity unique to specific regions within Europe (total number of haplotypes = 31, number of unique haplotypes = 27, Our results suggest that historical range expansion and retraction processes by a cold‐adapted mountain species caused diversification between populations, resulting in unique genetic diversity which may be at risk if distributions of cold‐adapted species shrink in future. Assisted colonizations of individuals from at‐risk populations into climatically suitable unoccupied habitat might help conserve unique genetic diversity, and translocations into remaining populations might increase their genetic diversity and hence their ability to adapt to future climate change. E. epiphron, has been shaped by Pleistocene glaciations, resulting in unique genetic diversity in isolated populations. The unique genetic diversity in mountain and cold‐adapted species is at under future climate warming, and we predict E. epiphron will lose 38%–64% of its range in the future, resulting in the loss of genetic diversity, reducing its ability to adapt.The genetic diversification of cold‐adapted mountain species, such as  All relevant fieldwork permissions were obtained. DNA was extracted from 111 individuals with Omega Bio‐tek E.Z.N.A.® DNA Isolation Kit following the manufacturer's protocol. For each individual, the head and antennae were removed and placed in 1.5 ml tubes with CLT buffer and proteinase K and homogenized with pellet pestles. A 658‐bp fragment of the mitochondrial cytochrome oxidase‐I (COI) gene was amplified using the primers LepF (5’‐ATTCAACCAATCATAAAGATATTGG‐3’) and LepR (5’‐TAAACTTCTGGATGTCCAAAAAATCA‐3’) . PCR conditions used the following profile: 94°C for 2 min (one cycle), 2 min at 94°C, 58°C for 45 s, and 72°C for 1 min (35 cycles), followed by a final extension step of 75°C for 5 min. PCR products were purified and Sanger sequenced with forward and reverse primers using © Eurofins Scientific PlateSeq service and LightRun Tube service. Chromatograms were checked visually using SeqTrace , number of unique haplotypes (Hu), haplotype diversity , and nucleotide diversity  were obtained from the Distribution Atlas of European butterflies (http://www.ufz.de/european‐butterflies/index.php?en=42605). Current (1970–2000) climate data were downloaded from WorldClim (http://www.worldclim.org/) at a resolution of 2.5 arc minutes (~4.5‐km grid cell resolution). Climate variables for inclusion in SDMs were selected to reflect climate limitations and extremes of cold‐adapted species, which are likely to be most limited by climatic conditions during the coldest and hottest times of the year. We therefore included climate data on annual mean temperature and mean precipitation of the coldest quarter (December to February) and warmest quarter (June to August) of the year  are more accurate representations of true absences, because these grids have been visited by butterfly recorders but E. epiphron was not recorded as present. In addition, 50‐km data for presences cover the entire global distribution of E. epiphron at this spatial resolution. Butterfly distributions were modeled using an ensemble approach  grid)  for high  and low  future climate scenarios. Unique haplotypes were assumed to be at risk if all 50‐km grid squares in one of the 13 mountain regions were predicted to become climatically unsuitable in the future . We set the threshold value as the probability value associated with the low elevation climatic range edge E. epiphron in its current range . Using this threshold, model probabilities were converted into the presence/absence to show grid squares with no change over time , grids predicted to become climatically unsuitable , and grids predicted to become climatically suitable . Haplotype risk (rH) was calculated as the number of unique haplotypes at risk in each of the 13 mountain regions  from WorldClim  and the divergence between some of these populations is dated before the Last Glacial Maximum (phylogenetic tree: see Appendix Hd = 0.63) the western Alps (Hd = 0.91) and England (Hd = 0.64) (Table Hu = 2) and the Tatras (Hu = 2). Populations in England (Hu = 6) and the western Alps (Hu = 6) not only had the highest number of unique haplotypes but also contained some shared haplotypes with other regions , ROC = 0.9)  as the most important variable for predicting climate suitability for the species , probably because this is an important variable in identifying high elevation areas within a 50‐km grid square.Our ensemble SDM was a good fit to the current distribution of ) Figure . Areas p3.3E. epiphron, as well as some southerly locations  showed overlap of climatically suitable areas (at 50‐km grid resolution) with many locations currently occupied by s Figure . This ovs Figure . These c3.4E. epiphron areas will have reduced climate suitability in the future  . The mountain regions predicted to experience the greatest reduction in range size are the Vosges (100% loss of grid squares under both scenarios) and Apennines (100% loss of grid squares under both scenarios), followed by the Balkans (75%–100% loss), Carpathians (70%–100% loss), England (50%–100% lost), and Cantabrians (63%–81% loss)  Figure . The los) Figure . By cont4E. epiphron. We identify high levels of genetic differentiation across Europe and found evidence of long‐term climate suitability in many of these regions since the LGM, which suggests these climatically stable regions were refugial areas of long‐term survival by our study species over the last 21,000 years and potentially longer‐term areas of persistence over previous glacial–interglacial cycles. Our study focuses on a single mountain species but our findings are likely to be widely applicable to other mountain species where populations contain unique genetic diversity as a consequence of past climate fluctuations, and which may be at risk under future climate warming. These areas of long‐term survival are within topographically heterogeneous landscapes, allowing populations to shift to the foothills during glacial periods. Our analyses also revealed that populations in the Massif Central, Vosges, and Britain are presumed postglacial colonizations  without recording E. epiphron as present, and hence, the proportion of false absences in the data is likely to be very low at the spatial (50 km across the whole of Europe) and temporal (accumulation of Lepidoptera records over 3 decades) scales considered here. We consider that our modeling approach robustly describes the bioclimatic conditions occupied by E. epiphron at a continental scale . Future work could use sampling effort to account for imperfect species detection, with standardized sampling and occupancy modeling providing additional insight into  within‐region distributions and dynamics.This study has potential limitations, which are inherent in species distribution modeling, especially when projecting into different climates , and hence, caution should be taken with our predictions. The difference between using two different thresholds , affects whether or not the entire English and Apennines regions are lost, and hence, there is some uncertainty about the level of genetic diversity at risk. Nonetheless, the relatively low probability of future persistence in both of these regions suggests that these populations are at the climatic range limit for the species and therefore at risk. While regional adaptations may differ, we have no evidence that haplotypes are individually adaptive to climate variables, and hence, we use them as markers of colonization rather than as adaptive traits. For the same reason, we did not model the specific niches of individual haplotypes when considering the potential future loss of genetic variation . Future work could use next‐generation sequencing to further test our hypotheses and to model‐specific genetic–climatic relationships in the future , and so, they may not persist in the longer term due to their isolation (metapopulation failure). A variety of processes may lead to the loss of genetic diversity following isolation, and there can sometimes be a delay in genetic loss following population decline , or a failure of our analyses to detect localized or rare haplotype variation. However, this alternative hypothesis seems unlikely because our estimates of times of genetic divergence  Mya ; Data curation (lead); Formal analysis (lead); Investigation (lead); Methodology (lead); Project administration (lead); Visualization (lead); Writing‐original draft (lead); Writing‐review & editing (lead). Kanchon K. Dasmahapatra: Conceptualization (lead); Funding acquisition (lead); Methodology ; Supervision (lead); Writing‐review & editing . Chris D. Thomas: Conceptualization (lead); Funding acquisition (lead); Supervision (lead); Writing‐review & editing . Michael D. Morecroft: Conceptualization (lead); Funding acquisition (lead); Supervision (lead); Writing‐review & editing . Athayde Tonhasca: Conceptualization (lead); Funding acquisition (lead); Supervision (lead); Writing‐review & editing . Thomas Schmitt: Conceptualization ; Data curation ; Methodology (supporting); Writing‐review & editing . Stefanos Siozios: Data curation ; Methodology (supporting); Writing‐review & editing (supporting). Jane K. Hill: Conceptualization (lead); Funding acquisition (lead); Supervision (lead); Writing‐review & editing .Appendix S1Click here for additional data file.Appendix S2‐S6Click here for additional data file.


I = 2.586 ± 0.034) and expected heterozygosity (He = 0.908 ± 0.003) indicated a high level of genetic diversity among breeds. The fixation index (Fst) revealed a value of 10.4%, demonstrating that there was a high level of genetic subdivision between populations. This study showed that inter-simple sequence repeat marker analysis was effective in demonstrating high genetic diversity among varying breeds of dogs, while a combination of Inter-simple sequence repeat marker analysis and high resolution melting analysis could provide an optional technique for researchers to effectively identify breeds through genetic variations.The identification of differing physical characteristics of dogs is an uncomplicated and straightforward way to categorize dog breeds. However, many dog owners and veterinarians still struggle to distinguish between pure breed and mixed variations in certain breeds of dogs. Presently, the absence of the tools and methods needed to confirm a pure breed dog is a significant problem since the only method available to validate pure or mongrel breeds is the official pedigree system. Inter-simple sequence repeat markers have been successfully used to assess genetic variations and differentiations. Notably, inter-simple sequence repeat markers coupled with high resolution melting analysis were effectively used for the breed identification of 43 breeds of dogs . The 10 primers chosen for analysis resulted in a range of 31–78.6% of breed discrimination when using one primer, while a combination of two primers was able to successfully discriminate between all of the 43 dog breeds (100%). Shannon’s index information ( More than 400 dog breeds have been registered with Federation Cynologique Internationale (FCI) and other official kennel clubs . HoweverPhyllanthus amarus  by veterinarians at small animal hospitals located in northern Thailand . Varying® 730 spectrophotometer  was used for determining the The concentration, yield, and purity of DNA and was preserved under −20 °C for further analysis.DNA were extracted from whole blood samples by using a RBC Bioscience™ Real genomics DNA extraction kit for Blood/Bacteria/Cultured cells  following the manufacturer’s instructions with the DNA final volume that was recovered by reckoning a final 50 µl of a standard elution. Lastly, Beckman Coulter DUTaq DNA polymerase with 10 ng of DNA template. Finally, deionized water was added to a volume of 25 µl and also served as a negative control. PTC-200 at DNA EngineThermal Cycler  was used for PCR amplifications under the condition from our previous study  were screened by polymerase chain reaction (PCR) technique and performed in this study following our previously protocol . Brieflyus study . The PCRa), the effective number of alleles (Ne), and the expected level of heterozygosity within the population (He). Shannon’s information index (I). Fixation index within each breed (Fis) and among breeds (Fst), along with the parameter of the gene flow (Nm), were assessed to measure the degree of population differentiation from the genetic structure. Furthermore, the genetic similarity and genetic distance of domestic dogs from each breed and between breeds were calculated using the method described by The DNA fingerprints of 43 dog breeds obtained from ISSR-HRM using the screened ISSR primer were used to score clearly observed bands that served as binary symbols, wherein the presence of a band was 1 and the absence of a band was 0 . The bin® dye, dNTPs and enhancers) , 0.5 µM ISSR primer and a 10 ng DNA template. Deionized water was added instead of the DNA template to establish a negative control.From the preliminary primer screening process using PCR, there were 13 primers  that yieFirst, ISSR-HRM was performed on a PCRmax Eco 48 machine . The initial step was initiated at 95 °C for 10 min followed by 37 cycles of the denaturation step at 95 °C for 20 s. This was followed by annealing with an extension step at 58 °C for 45 s. During the amplification process, fluorescence data were collected at the end of each annealing cycle. HRM analysis was carried out after 37 real-time PCR cycles at temperature increments of 0.1 °C/cycle between values of 55 °C and 95 °C in order to generate high resolution melting curves. Melt curve profiles from ISSR-HRM, normalized curves, difference curves and amplification curves were all generated using Eco software v5.2.12 (PCRmax) to identify any differentiations between the melting profiles of 43 dog breeds. Secondly, the amplicons obtained from ISSR-HRM were stained and separated electrophoretically on 2% agarose gel according to We screened 34 ISSR primers under five different annealing temperature conditions . It was found that there were 13 primers of UBC set at 9 and an annealing temperature of 58 °C providing reproducible and informative results from 43 dog breeds. Thus, 13 ISSR primers were reassessed to generate ISSR fingerprints by real-time PCR followed by HRM analysis (ISSR-HRM). The results revealed that 10 out of 13 primers at an annealing temperature of 58 °C were enabled to generate melting curves for all 43 dog breeds.The amplicons obtained from ISSR-HRM were subjected to agarose gel electrophoresis to investigate the DNA fingerprints. Our findings indicate that the percent polymorphic bands ranged from the lowest polymorphism at 28.04% in the Alaskan malamute breed to the highest polymorphism at 93% in the Shih Tzu breed . The brea) ranged from 7.900 in the Bull Terrier breed to 36.500 in the Pomeranian breed. Values of the effective number of alleles (Ne) were similar to Na in the Miniature Pinscher, Schnauzer, Bulldog, Cocker Spaniel, American Pit Bull Terrier and Rottweiler breeds. Meanwhile, Ne values in the Pomeranian, Chihuahua, Golden Retriever, Shih Tzu, Siberian Husky, French Bulldog, Beagle, German Shepherd, Thai Bangkaew, Poodle, Yorkshire Terrier, Labrador Retriever, Pug, Jack Russell Terrier, American Bully, Samoyed, Spitz and Bull Terrier breeds were less than the values of Na. According to Shannon’s information index (I), the Pomeranian breed recorded the highest value, while the Bull Terrier breed presented the lowest value. A high value of heterozygosity indicates considerable outbreeding. The mean expected heterozygosity (He) value for the overall populations was 0.831 ± 0.008, of which the Pomeranian and Siberian Husky breeds were identified as the most diverse groups while the Bull Terrier breed displayed the lowest degree of heterozygosity. This outcome was in accordance with the values of Na, Ne obtained from Shannon’s information index (I). In this study, negative Fis and Fit values were observed from all of the ISSR markers (Number of bands and band size ranges are shown in  markers .Fst) value was found among the Pomeranian population, and the minimum value was found in the Bull Terrier population . At r breeds . The res , while UBC827 reported the highest level of discrimination. UBC827 seemed to present indistinguishable melting curve patterns for the Chow Chow, Siberian Husky, Shiba Inu, Thai Ridgeback and Yorkshire Terrier breeds. Moreover, the Chihuahua, Golden Retriever and Pomeranian breeds were grouped together along with the Bichon Frise and Shih Tzu, Beagle and French Bulldog, Welsh Corgi and Poodle breeds. Notably, UBC826 could effectively discriminate between breeds to a value of 76.2% of breed resolution, but it could not distinguish between the Siberian Husky, Pug, Shih Tzu and Spitz breeds. Six other groups that displayed related melting curve patterns were the Bull Terrier, American Bully and Doberman Pinscher, Akita Inu and Great Dane, Alaskan Malamute and Chow Chow, Cavalier King Charles Spaniel and West Highland White Terrier, Papillon and Shiba Inu breeds, along with the Thai Bangkaew and Poodle breeds. Meanwhile, the least effective markers for dog breed discrimination were UBC817 and UBC825, which displayed 38.1% and 31% of breed resolution, respectively . HoweverThe highlights of this study are that; (i) ISSR-HRM could be a selective tool for facilitating breed discrimination and (ii) genetic variations, differentiations and genetic structure in different dog breeds that reside in northern Thailand revealed a high degree of diversity. However, in some breeds that include a high number of pedigreed dogs, such as the Bull Terrier, the Cavalier King Charles Spaniel, the West Highland White Terrier and the Alaskan Malamute, a lower degree of genetic diversity was observed than in the other breeds. This can lead to an understanding of how genetic variations are related to genetic diseases, which would be useful for all breeding programs. Ultimately, this would result in the breeding of healthier dogs, which can also help researchers develop an understanding of the genes that cause certain breed-specific behaviors .5 for the relevant DNA binding sites. Interestingly, from the screening of 45 primer combinations, the Welsh Corgi breed appeared to be the least discriminated breed with a combination of 21 primers. The origin of the Pembroke Welsh Corgi dog suggests that the breed may have originated from central European  and runt-related transcription factor 2 (RUNX2) genes is associated with limb and skull morphology, which reveal interesting correlations between longer sequence lengths of RUNX2 microsatellites and the longer faces of dogs European . On the European . AdditioEuropean . This cl of dogs . This wa of dogs . FCI nom of dogs . Moreove of dogs .e) in the Thai Bangkaew (0.954) breed in this study was higher than in the findings of a previous study involving Thai Bangkaew dogs (0.77)   which uss (0.77) . In this studies . A clari studies .Shannon’s information index values were higher than in other studies involving domestic animals using ISSR markers. This was the case among cattle, sheep, buffaloes and goats for which the values ranged from 0.18 to 0.75 . These vK = 4. This might have been the case because the Chihuahua was the only South American breed that was included in the STRUCTURE analysis in this study. Additionally, Spitz related breeds, like the Pomeranian and Spitz, were grouped together with K = 4 as well. The Cocker Spaniel breed revealed the greatest level of diversity. This might have been due to the misclassification of the English Cocker Spaniel and the American Cocker Spaniel among veterinarians or because inaccurate information was provided by owners during the sample collection process.ISSR fingerprints obtained from 10 primers were used to construct a dendrogram by employing the clustering method of the neighbor-joining algorithm. It indicated that all 33 breeds fell into three main groups. Origin might have had a significant effect on genetic variations in this study according to the phylogenetic dendrogram and structure. Notably, the breeds of French Bulldog and Poodle originated from France. This might be the reason why they formed a cluster that was separate from the other breeds. Likewise, a group comprised of German Shepherds and Doberman Pinschers was known to originate from Germany and a group of Pug and Pekingese dogs was known to originate from China. Moreover, geographic origin plays an important role in shaping genetic clusters. According to the dog breed dendrogram results, most Asian dogs share a close genetic relationship with each other. For instance, the Spitz, Thai Ridgeback and Chow Chow breeds, which are considered Asian breeds, are actually all related to the Spitz and are in the same branch as the Shih Tzu, Pekingese and Pug breeds which were all grouped together. Additionally, the results of each significant branching were in clear agreement with the known history of the designated breed. For example, Golden and Labrador Retrievers were found to be very close to each other, which was likely because they are linked to a common historical ancestor (Lesser Newfoundland) and geographic origin (United Kingdom). The American Bully is considered a half-blood breed of the American Pit bull Terrier and other Bulldog breeds, which explains why these breeds were found to be genetically related. Apart from that, dogs that were commonly bred for performance are now being bred mainly for a number of other characteristics. This might account for the high number of hunting dog breeds including Dalmatians, Beagles and Dachshunds, which were all grouped in the same branch . FurtherThe study on the genetic diversity of canine breeds might be dated; nevertheless, dog breed population diversity in northern Thailand has never been assessed by genetic variations or diversity. However, the limitations of this study include the fact that the number of samples of several breeds was very low. This occurred for a variety of reasons, such as the low degree of popularity of some breeds in Thailand, or the fact that some breeds have only recently been introduced into the country. Moreover, some breeds may be represented by a limited number of samples of no more than 3–4 individuals, while most of them are related. Thus, we had to cut these samples and did not include them in this study. Furthermore, ISSR-HRM is a more convenient method for assessing the melting profile and can be employed to separate dog breeds. Nevertheless, some dog breeds displayed variations in the melting profile. This might have occurred because of the high genetic variations that exist in some of the breeds that are known to populate northern Thailand. Consequently, this would have likely affected the melting profile or pattern.The ISSR-HRM analyses revealed discrepancies of the melting profiles among different dog breeds. The high power of discrimination could be augmented using a combination of two ISSR primers. Our findings demonstrated that the combination ISSR markers obtained from the HRM techniques could be an optional tool for breed identification. Moreover, the results revealed a high diversity and very low level of inbreeding within and between different dog breeds. Regardless, according to the results, the incorporation of ISSR marker analysis with other informative genetic markers should greatly improve the accuracy of inter-breed genetic distance and intra-breed diversity estimates in animals. Therefore, effective and proper breeding management schemes in these dog breeds is advisable in order to avoid significant increases in incidences of inbreeding and losses in terms of genetic variations.10.7717/peerj.10215/supp-1Supplemental Information 1Information of 2 bands for genetic variation and differentiation analysis among different dog breeds and also dog breed population structure and phylogenetic dendrograms were presented in each 10 ISSR primer, UBC809, UBC817, UBC818, UBC823, UBC825, UBC826, UBC827, UBC835, UBC844 and UBC848 as base pair.Click here for additional data file.10.7717/peerj.10215/supp-2Supplemental Information 2The first lane represents 100 bp ladder, while lanes 2-14 represent individual samples and lane 15 represents the negative control. The photo-image (A) depicts the representative gel and the image below (B) displays the scored bands in animated format.Click here for additional data file.10.7717/peerj.10215/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj.10215/supp-4Supplemental Information 4Click here for additional data file.


Global viticulture has evolved following market trends, causing loss of cultivar diversity and traditional practices. In Montenegro, modern viticulture co-exists with a traditional viticulture that still maintains ancient practices and exploits local cultivars. As a result, this region provides a unique opportunity to explore processes increasing genetic diversity. To evaluate the diversity of Montenegrin grapevines and the processes involved in their diversification, we collected and analyzed 419 samples in situ across the country (cultivated plants from old orchards and vines growing in the wild), and 57 local varieties preserved in a grapevine collection. We obtained 144 different genetic profiles, more than 100 corresponding to cultivated grapevines, representing a surprising diversity for one of the smallest European countries. Part of this high diversity reflects historical records indicating multiple and intense introduction events from diverse viticultural regions at different times. Another important gene pool includes many autochthonous varieties, some on the edge of extinction, linked in a complex parentage network where two varieties (Razaklija and Kratošija) played a leading role on the generation of indigenous varieties. Finally, analyses of genetic structure unveiled several putative proto-varieties, likely representing the first steps involved in the generation of new cultivars or even secondary domestication events. Vitis vinifera subsp. sativa L.) was likely first domesticated from the wild grapevine (V. vinifera subsp. sylvestris (C.C.Gmel.) Hegi) in the Transcaucasian region  about 8,000 years ago1. Then, early cultivars spread around the Mediterranean basin following the main human migration routes during several thousand years2. During this process, certain vines were selected for their adaptation to regional conditions and their ability to overcome local biotic and abiotic stresses. These vines become stable varieties through their vegetative propagation and evolved through combining mutation and sexual reproduction events with other early-domesticated cultivars or with wild autochthonous vines2.The cultivated grapevine  with wine7. Winemaking and wine trading were two important activities for local economies at that time, as inferred from relics like those found in the necropolis of the coastal city of Budva 8. Viticultural practices were intensified by Romans after the Illyrian Wars, as observed in Dionysian/Bacchic iconography, and in many remnants from domestic utensils used for wine transportation or consumption 7. Wine production continued during the Byzantine period, and documents like the Medieval Statute of Budva reflects the importance of grapevine cultivation in Montenegro in the Middle Ages. The Statute, dated between 1,426 and 1,442, includes the relevance of certain grapevine varieties for local wine production10, like the cultivar “Cratosia”, probably referring to the grape cultivar currently known as Kratošija (meaning short-neck in Montenegrin)9. Later, many vineyards were destroyed during the Ottoman period, and only some survived in remote regions in the center of the country and in several parts of the coastal regions controlled by Venice6. Winemaking practices were partially restored under the rule of Nikola I (1860–1918), which promoted wine exports to Western countries. After several millennia of genetic diversification, most of the grapevine genetic diversity generated in the Balkans was destroyed by the effect of phylloxera and mildews introduced from North America at the end of the nineteenth century11. As a result, many old autochthonous cultivars of the Western Balkans exist now as isolated plants or as relict populations, often represented by few specimens found in old, traditional vineyards or maintained in ex situ Vitis collections13.From ancient times to modern days, the Western Balkans have been home of important European civilizations. Illyrians, Greeks, Romans, Byzantines, Ottomans and Austro-Hungarians settled along this region, promoting the exchange of people, commodities and knowledge within close and distant regions 15. Overall, grapes are grown in Montenegro over 2.800 ha, with a gross production of 22.200 t in 201716. Winemaking in Montenegro mainly relies on the production of red wine from two autochthonous grape cultivars, Vranac and Kratošija17. Kratošija was the dominant variety in the region until the phylloxera crisis, which forced the removal of many old vines and their replacement by new plant material11. In many cases, withered Kratošija vines were replaced by grafted Vranac plants, preferred by growers as it produces highly deep-colored wines17. As a result, the Kratošija cultivated area decreased, while Vranac became the most commonly grown and the most emblematic cultivar in Montenegro during the twentieth century14. Besides these two major cultivars, other less-known indigenous cultivars can be found in Montenegro and neighboring countries, including Bioka, Čubrica, Krstač and Žižak18.Montenegro played a major role in the long history of grape cultivation in the Western Balkans. Its highly diverse climate conditions, isolated valleys, soil types and orography create highly diverse environments that, together with its historical and geographic context, promoted the generation of a rich grapevine biodiversity2. On the contrary, recent market globalization has caused a dramatic erosion in the diversity of wine grapes planted across the world, moving towards the cultivation of a reduced set of “international varieties”19. Thus, the exploration and analysis of winemaking regions where old vineyards are still maintained under traditional management practices can help to understand how European viticulture developed over time before the current standardization. As exemplified in multiple regions21, wide surveys in traditional winemaking areas allow the identification of old genetic resources on the edge of extinction for their preservation and eventual exploitation. Grapes from unique native varieties can produce highly distinctive wines with real potential to revitalise local wine industries22, and there is a renewed global interest in local wine varieties from Old World nations to stand out in today highly standardized market. Furthermore, the analysis of these indigenous and traditional varieties has helped to successfully resolve previous doubts about cultivars parentage25, as well as to shed light on the likely origin and dissemination patterns of certain grapevine cultivars in traditional viticulture regions26.Worldwide wine consumption patterns have changed radically and rapidly in recent years, influencing changes in viticulture. For a long time, grape growers selected and maintained local grape varieties to fit their viticultural practices and local climates, producing grapes that reached an appropriate concentration of sugars, acids and other compounds to make traditional wines28. Grape varieties are maintained through vegetative propagation, and thus all the plants of any variety present the same genotype for the molecular markers used30, while a few molecular markers are enough to distinguish any two varieties31. This fact has allowed to confirm and discover many local and international synonyms (different names for one variety) and homonyms (same name for different varieties)33. These DNA markers have also been commonly used for determining the existence of genetic structure in sets of vines at local and wider levels35. Finally, a few chloroplast DNA markers are informative enough to establish chlorotypes in Vitis vinifera, existing only four different major types36 that are maternally inherited. Chlorotypes have been useful to determine the female parent in a pedigree, and to show the multiple origins of cultivated grapevine by analyzing the distribution of chlorotypes in local sylvestris and cultivated vines38.The use of nuclear DNA markers, mainly microsatellites  and Single Nucleotide Polymorphisms (SNPs) have contributed decisively to the identification of grapevine varietiesHere, we present the results of a nation-wide survey of endangered genetic resources in Montenegro, including cultivated plants (human-cared) from old orchards and vines growing in the wild. Samples were characterized by SNP and SSR markers, and unique genetic profiles were compared with international databases for proper varietal identification and for the detection of synonymies and homonymies. In addition, we analyzed Montenegrin grapevine genetic diversity and structure, and unveiled their genetic relationships. These results revealed (1) the origin of modern Montenegrin cultivars from autochthonous and/or introduced varieties, (2) the existence of anachronic proto-varieties in this region, and (3) introgression events from wild vine populations which shape the genetic structure of domesticated grapevines. This work represents a first step toward promoting wider use of indigenous and traditional grapevine varieties in the modern Montenegrin wine industry. It will contribute to the diversification and enrichment of the European wine sector. Vitis collection of the Biotechnical Faculty of the University of Montenegro (BTF collection), which was created from surveys performed between 1956 and 1960 to preserve local cultivated grapevine genetic resources. All the sampling sites of cultivated and wild grapevines are indicated in Fig. A broad genetic survey was performed in traditional wine regions of Montenegro. The search and sampling of cultivated plants was exclusively focused on old vines , located in small vineyards or orchards mostly belonging to local wine producers for self-consumption. Vines growing in the wild were mainly collected close to river or creek banks. A total of 419 vines (45 wild vines and 374 cultivated plants) were localized, georeferenced and collected throughout Montenegro Fig. . In addi40, allowed the identification of 33 grapevine cultivars , . Considering these 111 genotypes, 68 corresponded to cultivated plants in ancient vineyards and 43 were sampled as wild vines (Supplementary Table ), Table . Three oVitis spp. interspecific hybrid direct-producers like Isabella and Varousset.The most commonly found genotype among the 419 grapevine samples corresponded to the variety Kratošija, which was found 106 times, followed by Vranac (76), Lisica (35), Razaklija (27), Krstač (22) and Bioka (8). A high number of the 50 identified cultivars are currently considered autochthonous varieties from the Western Balkans, such as Bratkovina Bijela, Coarna Alba, Hrvatica, Kratošija, Prokupac, Vranac or Zilavka, whereas other cultivars are considered to come from Eastern countries like Greece , Turkey , Lebanon (Afus Ali), Armenia , Azerbaijan (Sysak) and Georgia (Rkatsiteli). In addition, cultivars from Western countries like France , Germany (e.g.: Mueller Thurgau), Italy  and Austria (e.g.: Silvaner Gruen) were also identified, as well as bred cultivars like Angelo Pirovano and Perlona, and 41.All the wild plants hold unique genotypes, but for two genotypes (named Wild MNE 273 and Wild MNE 359) that were found twice in the wild  and D , followed by chlorotypes A  and B . On the contrary, most plants sampled in the wild bear chlorotype A , followed by chlorotypes D  and C   threshold of 0.5 for group assignment, one genetic group  is mainly formed by samples collected as cultivated plants . The other genetic group  is mainly formed by genotypes sampled as wild vines  , clustered in Str1.2 with most of the wild vines included in this work, with membership coefficients of 0.530 and 0.505, respectively  Fig. . As prevq values > 0.6). Significant differences (p ≤ 0.05) between the non-redundant genotypes assigned to Str1.1 and Str1.2 were found for all the parameters (Table UHe) and observed (Ho) heterozygosity than the group of wild vines , while the fixation coefficient (FIS) was close to zero for both genetic groups. The FST value between Str1.1 and Str1.2 populations was 0.131.Genetic diversity parameters were individually calculated for Str1.1 and Str1.2, excluding clearly admixed genotypes by using a more stringent threshold for group assignment  and the four genotypes sampled as cultivated but assigned to Str1.2 with q value < 0.6  . Str2B.2 included 6 genotypes native to the Western Balkans (“KRA-group”), such as Kratošija and Vranac. Interestingly, these 6 genotypes were assigned to Str2A.2 when considering K = 2. Str2B.3 is formed by 17 genotypes, including internationally renowned cultivars like Cabernet Franc, Merlot, Mueller Thurgau, Savagnin or Silvaner Gruen (“INT-group”), and all were assigned to Str2A.1 when considering K = 2. PCoA results supported the genetic differentiation indicated by STRUCTURE at K = 3, with genotypes assigned to RAZ-group, KRA-group and INT-group clustering in different regions of the plot . In addition, we detected six compatible parent–offspring relationships for Kratošija, and five for Razaklija, including other two genotypes sampled as wild vines . Pedigree analysis also allowed discovering the genetic origin of Vranac, currently the most emblematic variety in Montenegro. Our results confidently support that Vranac derived from a hybridization event between cultivars Duljenga and Kratošija (LOD = 85.10), with no mismatching loci in the proposed trio. This pedigree was also supported by an additional set of 20 SSR markers (Supplementary Table The 131 non-redundant grapevine genetic profiles were merged with those stored in the ICVV-SNP database for a wide search of possible first-order kinship relationships using 240 SNP-profiles. All reliable trios (mother + father + offspring) and duos (parent-offspring) involving (at least) one of the genotypes found in this work can be found in Supplementary Tables 15. Such viticultural tradition was shaped by a unique geographic position, terrain fragmentation and history. This traditional activity provides a fascinating window into this relict viticulture, and represents a unique opportunity to explore how viticulture evolved before wine market standardization. To this aim, we have studied the diversity of the traditional Montenegrin grapevine genetic pool through the most extensive search and sampling of cultivated and wild grapevines ever done in the country so far.Modern Montenegrin viticulture and winemaking industries co-exist with a significant number of old and small vineyards managed through traditional techniques17. In addition, we identified a significant number of foreign cultivars, supporting historical reports that indicate multiple introduction events in the country from diverse regions at different times and with different aims6. Cultivars from Eastern regions are possibly a consequence of viticulture dissemination from middle-East regions to Western European countries2, whilst cultivars from Western regions mostly derive from the intense exchange of plant material happened during the second half of the nineteenth century to fight grape phylloxera, mildews, and other pests2.We found an unexpectedly high genetic variability in the cultivated set, detecting 101 genotypes. Fifty genetic profiles were identified as well-known wine, table or multiple-use grape cultivars, most of which were Western Balkan autochthonous varieties. Kratošija and Vranac, the most important cultivars for current Montenegrin viticulture, were also the two most commonly found genotypes across old Montenegrin vineyards, reflecting their relevance in the past centuryFurthermore, we found 51 unidentified genotypes, cultivated in many cases as homonyms, under wrong cultivar names. Nine of them were found in at least two different sampling points (including the BTF collection), indicating their vegetative propagation and, therefore, that they are true cultivars, on the brink of extinction. Interestingly, some of them were found to be offspring of other well-known local cultivars , indicating a Montenegrin origin. The remaining 42 non-identified genotypes only appeared once in the sampling of cultivated plants. Some of them may represent true varieties too, as supported by the genetical identification of descendants for some of these genotypes . As they were sampled only once, these 42 genotypes are examples of critically endangered Montenegrin grapevines. Besides, a remarkable particularity of Montenegro viticulture is the current presence of an important number of putative ‘proto-varieties’. This term is used here to designate plants that have been only cultivated by local grape growers, i.e. plants that directly grow from seeds, or have been multiplied through cuttings just once, from the place where the seed germinated to the orchard. Eventually, they could be multiplied and distributed, becoming varieties. This is how most of the varieties originated in the past, but this process is not active anymore in Western European regions.19.Strikingly, an important number (33) of the genotypes conserved in the BTF collection (from a sampling of the 1960’s) was not found among the in situ samples studied in this work, indicating fast disappearance of ancient varieties, and underscoring the relevance of these surveys to preserve local genetic resources from extinction2, and autochthonous varieties are the main source for shaping local grapevine diversity. Previous works have identified intricate parentage networks linking multiple grapevine cultivars42, and major founders have been detected in many traditional winemaking regions, such as Pinot and Gouais Blanc (synonym Heunisch Weiss) in Burgundy and in Northeastern France44, Cabernet Franc in the Aquitania region of Bordeaux45, Hebén in the Iberian Peninsula47, and Sangiovese and Garganega in the Italic Peninsula48. Here, we found that Razaklija and Kratošija played a key role shaping the grapevine genetic pool of Montenegro, participating in a high number of the discovered trios and duos. Razaklija is a Turkish table grape cultivar existing in many grapevine collections under multiple synonyms40, and is a well-known genitor of several Albanian cultivars12. We found it compatible as the female parent in 14 full pedigrees . Interestingly, several grapevine varieties with female flowers have been previously reported to have an important contribution in the establishment of local genetic networks, like Hebén and Marufo in the Iberian Peninsula47. Unlike hermaphrodite plants, females need to cross-pollinate to produce descendants, process that increases genetic diversity and increases hybrid plant vigor38, which could have favored their selection as seed donors by early farmers to ensure grape production.Sexual reproduction is known to be the prime process in the generation of new grapevine genotypes32) is a cultivar grown in the Western Balkans for centuries. Nevertheless, its place of origin is controversial, and it has changed as new evidence was added: first from USA to Italy49, and then to Croatia, where old references and a reduced number of plants with a matching genotype were found under the name Crljenak Kastelanski50. More recently, the first molecular analysis of Kratošija proved that it has the same genotype32. In our study we identified 106 plants of Kratošija in old Montenegrin vineyards, and we found it to be the genitor (trios and duos) of almost 20 grapevine genotypes cultivated in Montenegro. In accordance with its ancient cultivation in this region, multiple Kratošija biotypes differing in traits like grape yield, cluster compactness or cluster size have been found in Montenegro14. In addition, early historical references already indicate the widespread use of Kratošija grapes for traditional winemaking in Montenegro, as reported in the Medieval Statute of Budva9, and reflected in folklore traced back to the eighteenth century10. Although definitive proof to establish the birthplace of an ancient variety cannot be provided, our results and the mentioned evidence support that Kratošija might have originated somewhere within Montenegro, agreeing with previous findings51.Kratošija  under the name “Vranatz-Krstatch”52. Previous reports indicate the existence of a first-degree relationship between Kratošija and Vranac32. Here, we found the full pedigree for Vranac, being the result of a compatible offspring between Duljenga and Kratošija. Duljenga was exclusively found in the BTF collection, and there are no reliable documents indicating the origin of this cultivar. Its presence in the BTF collection and its role as Vranac progenitor indicates that it was cultivated at some time in Montenegro.Vranac is considered an old autochthonous Montenegrin grape variety used for local red wine production for centuriescontinuum of plant populations, which range from exploited wild individuals to initial domesticates to cultivated populations53. In agreement with surveys done in wider frameworks54, the clear division between Str1.1 and Str1.2 seems to correspond to the two V. vinifera L. subspecies: sativa and sylvestris. However, it does not completely correspond with cultivated and wild conditions, as some intermediate genotypes generating a continuum were found. Population analyses allowed us to identify two exploited sylvestris plants (Kratošija Put Ka Zagarcu and Nepoznata Crmnica) collected from vineyards and yet genetically of the subsp. sylvestris. These plants bear chlorotype A and unique genotypes with no matches in the consulted databases, indicating they arise from sylvestris vines that were vegetatively propagated. These exploited sylvestris plants could be also considered as proto-varieties and, unlike the cases mentioned above, may represent novel active domestication events. Previous studies also report the in situ domestication of sylvestris autochthonous vines for grape production55, suggesting the existence of secondary domestication events in areas of grapevine cultivation at different times. The existence of these events is an open issue in grapevine research56, being difficult to ascertain if current cultivated grapevines are the result of multiple domestication events54 or a combination of a primary domestication event and multiple local introgression events during the geographic expansion of the crop to new locations.As nicely summarized by Miller and Gross, the domestication process in perennial fruit crops produces a sativa and sylvestris genetic subgroups (like Bijela Nepoznata Jelenak and Loznica-2). As stated by Stebbins in 1950, any single valuable hybrid individual, once obtained, can immediately become the progenitor of a new variety and can be perpetuated indefinitely53. In addition to Bijela Nepoznata Jelenak and Loznica-2, this fact was also observed with two widespread cultivars, Cabernet Franc and Savagnin (synonym Traminer). These two cultivars are genitors of a high number of cultivars (20 for Cabernet Franc and 70 for Savagnin40), and recent paleogenomic analyses indicate that Savagnin could have been uninterruptedly cultivated in Europe for (at least) 900 years4. The number of sexual cycles separating domesticated individuals from their wild ancestors is suggested to be low in perennial plants with clonally-propagated varieties53, which might explain the high level of wild ancestry detected in these two ancient varieties. In that sense, Bijela Nepoznata Jelenak and Loznica-2 are examples of active pathways to introgress genomic regions of subsp. sylvestris into new varieties.We found a set of cultivated plants with similar percentages of ancestry to the sativa than sylvestris genetic composition (four of them bearing chlorotype C). Two of them (Wild MNE 362 and Wild MNE 475) show extremely high coefficients of ancestry in the genetic subgroup of cultivated varieties and are compatible offspring of Kratošija and Razaklija, which classifies them in the sativa subspecies. Possibly, they have derived from seeds produced in vineyards and dispersed into neighboring natural environments by humans or animals. The presence of naturalized vines from grapevine cultivars, rootstocks and/or direct-producer hybrids is well documented in alluvial European forests58, and they are currently considered as invasive plants capable of contaminating natural wild grapevine populations. Thus, the cultivated vines (human-cared vines) do not always belong to the sativa subspecies, just as vines growing wild without cares do not always belong to the sylvestris subspecies.Finally, we detected six individuals sampled as wild vines with higher V. vinifera L. diversity in traditional viticultural regions across Montenegro provided insights not only about the existing genetic diversity, but also on how it was generated. The exploration of these unique regions, shaped by specific geographic and historical conditions, made it possible to detect different stages in the domestication process of this woody perennial, providing useful information on the processes of evolution underlying the generation of the current cultivated varieties. The study allowed us to conclude that the high diversity observed for Montenegrin varieties arose from ancient pathways to generate genetic diversity that are still active. These pathways involved the cultivation of new grape plants from seeds which increased genetic variation by: (1) the spontaneous sexual hybridization among cultivars introduced from different regions, (2) the spontaneous sexual hybridization between sylvestris and sativa grapevines, and (3) the vegetative reproduction of local sylvestris plants for grape production.Our in-depth study of  Vitis collection of the Biotechnical Faculty of the University of Montenegro (BTF collection) was included as a reference to aid in the identification of autochthonous cultivars. Cuttings from cultivated samples were taken in winter, grafted and planted in a new repository created by 13 Jul Plantaže to preserve this material. Cuttings from wild samples will be collected in upcoming seasons, and treated as described to be part of this repository.A total of 419 cultivated (374) and wild (45) grapevines were sampled throughout Montenegro, focusing in old, traditional vineyards dispersed in the two major viticulture regions of the country . Samples were collected in several exploration trips in 2013, 2014, 2016 and 2017, and GPS coordinates were recorded for each sampling site Fig. . Young l59. All samples were initially profiled for a core set of 48 nuclear SNP markers29, using the SNP-genotyping services provided by the Spanish Centro Nacional de Genotipado (CEGEN), as recently described38 or the Sequencing and Genotyping Unit of the University of the Basque Country, using Fluidigm technology. Three chloroplast SNPs that allow to distinguish the main grapevine chloroplast haplotypes 36 were used to determine sample chlorotype. Non-redundant genetic profiles (144) for the 48 SNPs were pair-wise compared with the ICVV-SNP database for cultivar identification, which includes the genetic profiles of more than 2,800 non-redundant genotypes for 48 SNPs. In those cases in which the SNP profile did not match with an identified variety in the ICVV-SNP database, samples were additionally characterized with 9 SSR markers  in the genotyping platform of the Centro de Investigación Biomédica de La Rioja (CIBIR). Profiles of SSRs were compared with those stored in the VIVC40 and the European Vitis Database39. All 144 non-redundant genotypes were profiled for an additional set of 192 SNP markers60 using the genotyping platforms stated before. Unfortunately, no satisfactory results were obtained for 13 genotypes, so 131 non-redundant grapevine genotypes with genetic profiles for 240 SNP loci were used for population structure and genetic diversity analyses. SNP and SSR analyses were conducted as previously described62.DNA was isolated from frozen leaves as previously detailed63 for 131 non-redundant genotypes considering 194 SNPs (SNPs with missing data in 10 or more grapevine genotypes were discarded). This dissimilarity matrix was used for PCoA and UwNJ analyses; the UwNJ tree was constructed on the basis of 1.000 bootstrap replicates.An Unweighted Neighbour-Joining (UwNJ) distance tree and a Principal Coordinate Analysis (PCoA) were calculated to explore the relationship between the cultivated and wild grapevine genotypes collected across Montenegro. To this aim, a dissimilarity matrix with 10.000 bootstrap steps was calculated using the DARwin software package v. 6.0.2164 was used to infer the number of genetic groups present in the set of 131 non-redundant grapevine genotypes. Here, we tested the existence of genetic structure considering a number of hypothetical genetic groups (K) ranging from 1 to 10, using a cycle of 100.000 burn-in steps followed by 150.000 Markov Chain Monte Carlo repetitions. To assess the consistency of the results, 10 runs per K value were performed, each one considering an admixture model with correlated allele frequencies among populations. The most likely number of genetic groups was set using the ΔK criteria65 implemented in STRUCTURE HARVESTER v. 0.6.9466, and CLUMPP v.1.1.267 was used to align the 10 different runs. Genotypes were assigned to a genetic group considering a threshold of q ≥ 0.50. Results were graphically represented by means of the web-based software STRUCTURE PLOT v.2.068.Then, the Bayesian clustering method implemented in the STRUCTURE v.2.3.4 softwareNe), information index (I), observed heterozygosity (Ho), unbiased expected heterozygosity (UHe) and fixation coefficient (F)) were calculated for the genotypes assigned to the two genetic groups identified by STRUCTURE, discarding those identified as Vitis spp. interspecific hybrids for their non-vinifera genetic background. To avoid the effect of individuals with a similar q ancestry value in both genetic groups, we set a q value threshold of 0.60 for group assignation. Thus, cultivated and wild genetic groups included 82 and 38 non-redundant genotypes, respectively. The FST statistic was used to analyze the genetic distance between cultivated and wild genotypes. Non-polymorphic markers  were excluded for diversity parameters estimation. Calculations were performed using GenAlEx v. 6.569. As previously indicated61, mean values of these metrics were subjected to a t test analysis to detect significant differences between both groups, considered significant at p < 0.05. This analysis was performed using IBM SPSS Statistics v.25.0 .Genetic diversity parameters . The same procedure described above was used, but we selected a more stringent q value (0.70) as group assignation threshold. The consistency of the genetic structure results obtained in this second round was evaluated through a PCoA and an UwNJ analysis, performed as detailed before.Lastly, we performed a second round of hierarchical STRUCTURE analysis to evaluate additional levels of genetic stratification71 as previously detailed61. The likelihood of each detected trio and parent–offspring pair (duo) was evaluated considering the natural logarithm of the overall likelihood ratio (LOD) score, and a maximum number of mismatching loci of 1 or 2 SNPs for duos and trios, respectively. For each trio, chlorotypes were used to determine which of the putative parents acted as mother, according to the maternal transmission of chloroplasts in grapevine36.Non-redundant grapevine genotypes were merged with those of the ICVV-SNP database to complete 1921 genotypes with data for 240 SNPs and analyzed to detect possible first-order kinship relationships (trios and parent–offspring pairs), using the likelihood-based method implemented in Cervus v. 3.0Supplementary FiguresSupplementary Tables


Furthermore, the treatment of oocytes with the Stat3-specific inhibitors stattic and BP-1-102 or anti-pStat3 antibody led to significantly abnormal spindle assembly and chromosome mislocation in a dose-dependent manner, and pStat3 was either absent or improperly localized in these oocytes. Moreover, the development of pre-implantation stage embryos derived from inhibitor-treated oocytes was significantly hampered following in vitro fertilization. These findings indicate a novel function of pStat3 in spindle assembly.The signal transducer and activator of transcription 3 of the pStat3 inhibitors, Stattic, and (Stat3) is activated upon phosphorylation at Y705 (pStat3) and serves the dual function of signal transduction and transcription activation. Our previous study suggested that pStat3 is functional during oocyte maturation when transcription is silenced. Therefore, we speculated that pStat3 serves other functions. Immunocytochemical analysis revealed that pStat3 emerges at microtubule asters and spindle and is subsequently localized at the spindle poles along with pericentrin during mouse oocyte maturation. Both Stat3 and pStat3 proteins were detected in conditionally knocked out  Many studies have demonstrated the dual function of signal transducer and activator of transcription 3 (Stat3) in signal transduction and transcription activation. Stat3 is involved in numerous biological processes, such as cell proliferation, differentiation, and survival. Although Stat3 is localized to the cytoplasm in its inactive form, stimulation by cytokines or growth factors triggers its phosphorylation (pStat3) at the tyrosine residue Y705), inducing dimerization, nuclear translocation, and DNA binding ,2,3. Jan, inducinThe Stat3 protein is expressed in the oocytes of mammals, including mouse ,12,13, hStat3-deficient mice exhibit embryonic lethality after implantation (E 7.0) [Stat3 (−/−Stat3) oocytes. Cre driver mice, such as Zp3-Cre or Gdf9-Cre transgenic (Tg) mice, are commonly used for the conditional expression of Cre recombinase in oocytes. In Zp3-Cre Tg mice, Cre expression is induced early in growing oocytes at the primary or the secondary follicular stages [−/−Stat3 oocytes. (E 7.0) . Consequr stages ,24. Oocyr stages ,26. Thus+/+Stat3 and −/−Stat3 oocytes. Here, we report that pStat3 is localized at the microtubule-organizing centers (MTOCs) and plays an important role in spindle assembly and chromosome segregation.Maturing mouse oocytes are thought to be an ideal model for studying the transcription-independent function of Stat3 as transcription is repressed during this stage. In this study, we first revealed pStat3 expression patterns in maturing mouse oocytes. Moreover, we examined the phenotype of pStat3 disruption in oocytes treated with Stat3-specific inhibitors and anti-pStat3 antibody in We first assessed the patterns of pStat3 expression in maturing oocytes and pre-implantation stage embryos by western blotting. pStat3 was highly expressed in GV oocytes B. NotablImmunocytochemical analysis showed that pStat3 accumulated in GV oocytes A, 4 h anflox/floxStat3 (f/fStat3) or fStat3/− mice, with two loxP flank exons 18–20 (SH2 domain) of the Stat3 allele exhibiting the conditional knockout of Stat3 after crossing with a driver Cre Tg mouse [−/−Stat3 oocytes from both fStat3/−; Gdf9-iCre and fStat3f/; Gdf9-iCre female mice  and ~10.1% (truncated stat3) relative to that in wild-type Stat3 protein in +/+Stat3 GV oocytes  and 16 μM BP-1-102 (+/+Stat3 oocytes), all oocytes exhibited a dark color (data not shown) and aggregated chromosomes without spindle formation. In all cases, pStat3 was absent or detected as a faint signal at an incorrect location concomitantly with pericentrin  and in vitro embryo culture. The fertilization rate of two-cell embryos significantly decreased following stattic and BP-1-102 treatments in a dose-dependent manner . Likewis−/−pericentrin mouse exhibit spindle misorientation, which is associated with disruption of astral microtubules and loss of a unique set of centrosome proteins at spindle poles [Successful pregnancy is largely dependent on the quality of oocytes  in whichle poles . We also−/−Stat3 oocytes matured to the MII stage without exhibiting an incorrect phenotype. Previous studies have used Zp3-Cre Tg mice for maternal Stat3 knockout [Gdf9-iCre Tg mice, expecting complete maternal Stat3-null oocytes considering that the Gdf9 promoter allows Cre expression in oocytes earlier at the follicular stage than does the Zp3 promoter [Stat3 mRNA and protein expression in −/−Stat3 oocytes. The wild-type Stat3 protein is assumed to be translated from mRNA expressed prior to Cre expression. Whether the truncated pStat3 with the deletion of the SH2 domain is functional in the mouse oocytes remains unclear. According to Robker et al. [−/−Stat3 oocytes derived from f/f; Zp3-CreStat3 could mature normally. The f/fStat3 mice used were deletion mutants of exons 12–14, and they displayed frameshifted mRNA incapable of encoding functional proteins [Zp3 promoter would remain functional in such oocytes. Discrepancies in the function of maternal Stat3 would be elucidated upon the creation of complete maternal Stat3-null oocytes.Indeed, knockout ,26. In tpromoter . Nonetheproteins . However+/+Stat3 and −/−Stat3 oocytes showed incorrect spindle assembly and chromosomal misarrangements, indicating that pStat3 regulates meiotic spindle assembly.Conditional targeting cannot completely disrupt maternal Stat3. Therefore, we used specific inhibitors of pStat3. Stattic  and BP-1Recently, Morris et al.  demonstrfloxStat3 [Gdf9-iCre Tg [ad libitum. f/fStat3  females were crossed with Gdf9-iCre Tg mice to generate f/+; Gdf9-iCreStat3 mice. These mice were back-crossed with f/fStat3 mice to generate f/f; Gdf9-iCreStat3 or f/−; Gdf9-iCreStat3 female mice, in which the oocytes are genetically −/−Stat3. Mice were maintained and handled in accordance with the guidelines issued by the NARO Institutional Animal Care and Use Committee  Day month year.ICR , tat3flox  (No. 016-iCre Tg  (C57BL6/floxStat3 mice were F1L (5′-aattggaacctgggaccaagtggccg-3′) and R2L (5′-agctggctcataggcaaaaacacctg-3′), and those used for Gdf9-iCre Tg mice were iCreF1 (5′-tggatgccacctctgatgaagtcag-3′) and iCreR1 (5′-tgattctcctcatcaccagggacac-3′). PCR was performed for 30 cycles at 98 °C for 10 s and 68 °C for 90 s using the EmeraldAmp PCR Master Mix . For oocyte genotyping, two GV oocytes, after removal of the zona pellucida by acidic Tyrode’s solution , were introduced into a PCR tube containing 1.5 μL 50 mM NaOH and heated for 5 min at 95 °C After adding 6 μL of 30 mM Tris (pH 8.0), PCR was conducted for 35 cycles, as described above.Tail snips of 18–20-day old mice were soaked in 90 μL of 50 mM NaOH, heated for 10 min at 98 °C, and neutralized with 10 μL of 1M Tris (pH 8.0). Primers used for 2 in air at 38 °C. Oocytes that completed GVBD within 60 min in TYH-FCS were selected, and IVM was performed for 15 h. For western blotting and immunocytochemical analyses, oocytes at the indicated time points after GVBD were collected.We injected 8–12-week old female mice with 5 IU eCG  to stimulate preovulatory follicle development and mechanically collected cumulus-enclosed oocyte complexes after 46 h in TYH medium  suppleme2 in air at 38 °C. Sperm were added to 100 µl of fertilization medium at a final concentration of 3 × 102 sperms/µl. After insemination for 2 h, embryos were washed and cultured in 50 μL KSOM [2 in air at 38 °C. The rate of development of embryos was recorded every 24 h until 96 h had elapsed.After IVM, oocytes were washed with modified HTF (mHTF)  and tran μL KSOM  in a humTwo small-molecule inhibitors of Stat3 activation—stattic  and BP-1-102 —were used. As stock solutions, 50 mM stattic and 80 mM BP-1-102 were prepared with DMSO  and kept at −20 °C. GVBD oocytes were transferred to TYH-FCS containing 1, 2, 3, and 4 μM stattic or 2, 4, 8, and 16 μM BP-1-102, and IVM was performed. As a control (0 μM), we added 0.008% DMSO, which is equivalent to a DMSO concentration of 4 μM stattic in TYH-FCS. After 15 h of IVM, oocytes were subjected to either immunocytochemistry or IVF.Anti-phospho Stat3 (Tyr705) rabbit mAb  and isotype control rabbit mAb IgG  were purified and concentrated with PBS using Amicon Ultra-0.5 . We subjected small aliquots of purified antibody and IgG to polyacrylamide gel electrophoresis, stained them using Rapid Stain CBB Kit , and determined the concentration as being 0.4 μg/μL. Purified anti-pStat3 antibody, control IgG, and PBS were microinjected into oocytes within 1 h after GVBD in TYH-HEPES, and the oocytes were then cultured in TYH-FCS.Western blotting was performed according to standard procedures. Proteins were extracted by using a double-strength SDS sample buffer, heated for 5 min at 90 °C, and stored at −80 °C until use. Unless otherwise stated, 50 oocytes or embryos per lane were used. After blocking with 5% skim milk (BD Biosciences) in TBST (0.1% Tween 20) for 1 h, the membranes were washed with TBST and probed with anti-phospho Stat3 (Tyr705) , anti-Stat3 , or anti-α-Tublin antibody  with 5% Blocking One-P  in TBST at 4 °C for overnight. The membranes were washed with TBST and incubated with HRP-conjugated anti-rabbit IgG secondary antibody  in blocking buffer at room temperature for 1 h. The membranes were washed with TBST and processed using the Chemi-Lumi One Ultra . Immunoblots were visualized using either Hyperfilm ECL  or ImageQuant LAS 500 . Quantification was performed using ImageQuant TL8.1 .Samples were fixed in 4% paraformaldehyde in PBS for 15 min at room temperature, washed with PBS, and treated with 0.3% Triton X-100 and 2% BSA in PBS (PBS-XB) for 1 h. The samples were incubated overnight at 4 °C with primary antibody against phospho Tyr 705 Stat3  or Stat3  with 0.3% Triton X-100 in PBS (PBS-X). The samples were washed with PBS-X and then incubated with Alexa Fluor 488-anti-rabbit secondary antibody  in PBS-XB at room temperature for 1 h. After washing with PBS-X, the samples were incubated anti-α-Tublin-Alexa Fluor 594 antibody  in PBS-XB at room temperature for 1 h. As a negative control, the samples were incubated with the secondary antibody alone. For double staining, anti-mouse pericentrin  and Alexa Fluor 647-anti-mouse antibodies , or anti-mouse-γ-tublin  and Alexa Fluor 594-anti-mouse antibodies  were added to the reaction described above as primary and secondary antibodies, respectively. The oocytes were transferred onto a slide glass with SlowFade Diamond Antifade Mountant in DAPI . To avoid squashing the samples, the vaseline–paraffin mixture (9:1) was spotted between the slide glass and the coverslip in advance. The specimens were imaged using a Zeiss LSM780 confocal microscope.Atp5f1 and Gapdh, which are components of the Mouse Housekeeping Gene Primer Set (TaKaRa Bio). Primer used for Stat3 were 148F (5′-accaacatcctggtgtctccacttg-3′) and 148R (5′-agatgaacttggtcttcaggtacggg-3′).RNA was extracted from 20 GV oocytes using the PicoPure RNA Isolation Kit (TFS). After treatment with DNaseI, first-strand cDNA was synthesized with oligo dT primers using the PrimeScript II 1st strand cDNA Synthesis Kit (TaKaRa Bio), following the manufacturer’s instructions. RT-qPCR was performed using a LightCycler 480 SYBR Green I (Roche) on a LightCycler 480 (Roche). The primers used for internal control were +/+Stat3 oocytes) or three (−/−Stat3 oocytes) independent experiments and analyzed by one-way ANOVA followed by Tukey’s test, using general linear models in Statistical Analysis System . Percentage data were arcsine-transformed before analysis. Data were expressed as mean ± standard error of the mean. P values less than 0.05 were considered to be statistically significant.All data were obtained from five (


Caryocar brasiliense. We sampled adults and juveniles in 10 savanna remnants within five landscapes. To obtain neutral genetic variation, we genotyped all individuals from each site using nine microsatellite loci. For adaptive traits we measured seed size and mass and grown seeds in nursery in completely randomized experimental design. We obtained mean, additive genetic variance (Va) and coefficient of variation (CVa%), which measures evolvability, for 17 traits in seedlings. We found that landscapes with higher compositional heterogeneity (SHDI) had lower evolutionary potential (CVa%) in leaf length (LL) and lower aboveground dry mass (ADM) genetic differentiation (QST). We also found that landscapes with higher SHDI had higher genetic diversity (He) and allelic richness (AR) in adults, and lower genetic differentiation (FST). In juveniles, SHDI was also positively related to AR. These results are most likely due to longer dispersal distance of pollen in landscapes with lower density of flowering individuals. Agricultural landscapes with low quality mosaic may be more stressful for plant species, due to the lower habitat cover (%), higher cover of monocropping (%) and other land covers, and edge effects. However, in landscapes with higher SHDI with high quality mosaic, forest nearby savanna habitat and the other environments may facilitate the movement or provide additional habitat and resources for seed disperses and pollinators, increasing gene flow and genetic diversity. Finally, despite the very recent agriculture expansion in Central Brazil, we found no time lag in response to habitat loss, because both adults and juveniles were affected by landscape changes.Plants are one of the most vulnerable groups to fragmentation and habitat loss, that may affect community richness, abundance, functional traits, and genetic diversity. Here, we address the effects of landscape features on adaptive quantitative traits and evolutionary potential, and on neutral genetic diversity in populations of the Neotropical savanna tree  Impacts of fragmentation and habitat loss on plant genetic diversity are still poorly understood, despite the increase in the number of studies in recent years . SeveralIn plants, landscape structure may affect connectivity due to the influence on germination and establishment . AdditioThe effects of fragmentation and habitat loss on plant genetic diversity are usually addressed using genetic variation at neutral loci, such as highly polymorphic microsatellites e.g., . BecauseIn the last 50 years the Cerrado biome has been intensively cleared, losing almost half of its original area . The BraCaryocar brasiliense Cambess (Caryocaraceae), endemic to the savannas of Cerrado biome. It has hermaphroditic flowers, mixed-mating reproductive system (Glossophaga soricina and Anoura geoffroyi (Mazama americana and Mazama gouazoupira), cotia (Dasyprocta spp.), tapir (Tapirus terrestris), maned wolf (Chrysocyon brachyurus), the greater rhea (Rhea americana), and jackdaw (Cyanocorax cristatellus)  . We specatellus) . We alsoatellus) , we analCaryocar brasiliense . Mapping and classification were performed manually at 1:5,000 scale in the screen, followed by extensive field checking and validation. We mapped 11 land cover classes: (i) water courses; (ii) savanna; (iii) riparian forest; (iv) seasonal forest; (v) wetland; (vi) pasture; (vii) agriculture; (viii) rural building; (ix) urban area; (x) roads and train rails; and (xi) Eucalyptus spp. plantation , we calculated the percentage of savanna at both node  and linki, i). To calculate quality scores, we considered the requirements and resources that each land cover can provide to both our focal tree species (C. brasiliense) and interacting species . Although C. brasiliense establishes in savanna (habitat), pollen (mainly bats) and seed dispersers  can perceive the landscape in different ways, using the anthropogenic matrix and forests as resource or as complementary habitat (i for the main pollinator (Glossophaga soricina) and large-sized seed dispersers  based on expert opinion , including all land cover categories for both node and link levels , 3. Anal habitat . Thus, t habitat . We obta opinion , 5. LQ w opinion , 7. As s opinion . We then opinion , 7. LQ a opinion .We measured adaptive quantitative traits related to fitness of seeds and seedlings. Seed size represents the amount of resources that mother-tree invests in offspring, affecting germination success and seedling fitness . Besidesn = 8) and L2F6 (n = 2), due to the number of trees siring fruits. We obtained a total of 1,570 fruits  and diameter  growth rates from the regression coefficient (b) and recorded the initial (76 days) and final (145 days) seedling height  and diameter . The number of leaves (NL), leaf length (LL) and width (LW) of each seedling was measured at the end of the experiment, 145 days after germination , from thr > 0.5). After these steps, we kept for seed traits STD, and SM, and for seedlings, TG, LL, RDM, and ADM.To minimize correlation among quantitative variables, we performed Pearson correlation (r) analyses at both node  and linkVa), and the narrow-sense heritability (h2) of each selected trait in each site. To address population evolutionary potential or evolvability we estimated the additive genetic coefficient of variation, CVa% (CVa% and h2) were obtained by s is the selfing rate (f) within population was obtained from juvenile’s microsatellite genotypes (see below). These parameters were estimated only for seedling traits obtained from controlled experiment in nursery, because seed traits were measured in seeds sampled in the field.We estimated the mean and additive genetic variance  . The inbQST . QST and PST parameters were calculated using variance components estimated using model 05 in the software SELEGEN – REML/BLUP  and juveniles of ral loci . Genomicsiliense . For gensiliense .AR; He; f; hierfstat  and among populations within landscapes (FSC). Significance levels of 0.05 for each estimate were determined with 10,000 permutations. We also used Bayesian clustering simulations to assess the number of discrete genetic clusters (K) using the software Structure v. 2.3.4  implemented in the software Arlequin 3.5 . We estiv. 2.3.4 , with adv. 2.3.4  implemenv. 2.3.4 .Ne) using the molecular co-ancestry method , we performed two-sample t-Student tests for He, AR, f and Ne.Finally, we estimated effective population size (y method  implemeny method  to test multifit function (2) as an index of the strength of the relationship  for seedling quantitative traits was high in most sampling sites  was low in most landscapes (PST) was also low, ranging from 0.001 to 0.170  and allelic richness (AR) for both adults and juveniles . The inbreeding coefficient (f) was low for both life stages .Sampling sites had high genetic diversity  and juveniles  did not differ from FST . Inbreeding coefficients within landscapes (FIS) was low for both adults and juveniles  and juveniles . Differentiation between populations within landscapes was also low for both adults  and juveniles . Bayesian simulations showed a maximal value of L(D| K) with K = 2 for both adults .Genetic differentiation among landscapes was low for both adults  was better explained by compositional heterogeneity  did not explain variation in any quantitative trait between sites within landscapes (QST) on ADM  in adults and juveniles was not explained by any explanatory variables (ST)F was explained by SHDI at 6 km spatial scale  size, while for neutral loci landscape structure affected allelic richness (AR) and genetic diversity (He) on both adults and juveniles. However, different from our expectations, landscape metrics such as habitat cover (%) and functional connectivity could not explain neutral and adaptive genetic variation.Our findings show increase of neutral genetic diversity and loss of adaptive genetic variation due to landscape changes in the savanna tree CVa% LL). Leaf size is correlated to plant water use efficiency, photosynthesis rate and resources retention  may also due to the loss of variation in leaf size among sites with a poor mosaic.In Brazil, areas dominated by soybean, an important commodity, such as in our study area, farmers preserve only the minimum of natural vegetation required by environmental law. The environmental law requires the conservation of riparian forests  and a patch of natural vegetation with at least 20% of the farm area . However, farmers usually allocate legal reserves in poor soil remnants that potentially provide low crop yields, and disconnected from riparian forests (PPAs), which may also contribute to the low-quality landscapes in intensive farming . TherefoCVa%), such as sites in the landscapes P3 and P4, implying limited capacity to respond to environmental changes, because evolutionary potential depends on population additive genetic variance , they have evolutionary potential to respond to environmental changes. However, some sites have very low additive genetic variance and thus evolutionary potential (variance . The lacAR) and genetic diversity (He), and juveniles have higher AR. For instance, populations in the protected area (L5), with the highest habitat cover (%) and structural connectivity and lower compositional heterogeneity showed the lowest values of genetic diversity and allelic richness, but the highest effective population size. On the other hand, landscape L3, with populations in a protected area, but with agroecosystem surrounding them, had higher genetic diversity and allelic richness than L5. We believe that the positive relationships between allelic richness and genetic diversity and compositional heterogeneity is related to pollen dispersal patterns.Our findings showed that adults in landscapes with higher compositional heterogeneity have higher allelic richness  explained better the variation in neutral genetic diversity and evolutionary potential in T. aurea, pollinated by large-sized bees and wind dispersed. Glossophaga soricina, the main C. brasiliense’s pollinator, is highly affected by the replacement of natural vegetation to agriculture and pasture, leading to a decrease in genetic diversity , when considering the life cycle of the species. We found no difference in genetic diversity between adults and juveniles and no effects of habitat loss on genetic diversity, but a positive effect of landscape heterogeneity on both, despite lower habitat amount. The lack of a time lag is most likely due to the mosaic of different types of ecosystems, such as seasonally dry and riparian forests, savannas, wetlands and agroecosystems increasing compositional heterogeneity and favoring gene flow. We also found low genetic differentiation among populations from different landscapes and high admixture for both adults and juveniles. This results was expected since our analyses encompass populations at a regional spatial scale, that may have diverged only recently.Tabebuia aurea , had slightly higher neutral and adaptive genetic variation than in savannas in protected areas (L3 and L5). Indeed, L1, L2, and L4 are in farm legal reserves, i.e., remnants of vegetation preserved in farms in compliance with Brazilian environmental law. Recently, Brazilian senators proposed to omit the obligation of legal reserves from environmental law, which may jeopardize the conservation of biodiversity and ecosystem services in Brazil . Our resia aurea  reinforcC. brasiliense in intensive farming landscapes. Except for the protected areas, natural vegetation remnants in the landscapes are legal reserves. Therefore, any initiative to ignore the conservation of these areas will compromise the biodiversity in the study area. In contrast, actions to exceed environmental law compliance are necessary to avoid loss of evolutionary potential in areas of intensive crop cultivation.Our results suggest that management strategies improving landscape and legal reserves quality are critical for the persistence of The natural mosaic established by the relief conditions in the study area helps maintain the patches of natural vegetation in some landscapes. Therefore, strategies to improve agricultural landscape quality – particularly those dominated by commodities such as soybean – are critical for genetic diversity conservation of tree species. Our results also highlights that strategies improving mosaic quality must be implemented at local scale, since we found composition heterogeneity effects at small scales such as 500 m. Better practices in agroecosystems management, such as the restoration of degraded pastures, savanna and forest remnants may increase the mosaic heterogeneity and quality increasing connectivity  and geneC. brasiliense in our study area. However, the response of adaptive quantitative traits variability to landscape changes was different from neutral variation. On one hand, high compositional heterogeneity is associated to the loss of evolvability in adaptive trait, contrary to our hypothesis (v). On the other hand, it is associated to higher neutral variability and genetic differentiation among populations, corroborating our initial hypotheses (i and iii) We also found no evidence of time lag in the response of C. brasiliense to landscape changes (hypothesis vi), showing that, despite the recent fragmentation of the Cerrado biome, the genetic variability in parental generations (adults) is already affected by ongoing landscape changes, which may cause a cascate effect in the next generations.In conclusion, we found that compositional heterogeneity in agriculture landscapes is the most important landscape characteristic shaping neutral and adaptive quantitative trait variation in The data and additional supporting information may be found in the online version of this article as RC and MR conceived and funded the work. TA and FR obtained the data. RC, JS, MR, and LC designed the experiment, field sampling, and statistical analyses. TA, JS, and MP carried out analyses. RC, TA, and MP wrote the original draft. All authors contributed to the manuscript and approved the final version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.