Corymbia hamersleyana) and Western Gidgee (Acacia pruinocarpa), by assessing patterns of variation and structure in several chloroplast DNA regions and nuclear microsatellite loci developed for each species. Gene flow was found to be extensive in both taxa and there was evidence of long-distance seed dispersal across the region , which may result from flooding and strong wind gusts associated with extreme cyclonic activity. Both species possessed high levels of cpDNA genetic diversity in comparison to those from formerly glaciated landscapes  and showed evidence of deep lineage diversification occurring from the late Miocene, a time of intensifying aridity in this landscape that appears to be a critical driver of evolution in Pilbara taxa. In contrast to another study, we did not find evidence for topographic features acting as refugia for the widely sampled C. hamersleyana.Phylogeographic studies can be used as a tool to understand the evolutionary history of a landscape, including the major drivers of species distributions and diversity. Extensive research has been conducted on phylogeographic patterns of species found in northern hemisphere landscapes that were affected by glaciations, yet the body of literature for older, unaffected landscapes is still underrepresented. The Pilbara region of north-western Australia is an ancient and vast landscape that is topographically complex, consisting of plateaus, gorges, valleys, and ranges, and experiences extreme meteorological phenomena including seasonal cyclonic activity. These features are expected to influence patterns of genetic structuring throughout the landscape either by promoting or restricting the movement of pollen and seed. Whilst a growing body of literature exists for the fauna endemic to this region, less is known about the forces shaping the evolution of plant taxa. In this study we investigate the phylogeography of two iconic Pilbara tree species, the Hamersley Bloodwood ( Studies of intraspecific phylogeography provide insight into the evolutionary history of a species, revealing forces that have shaped its distribution and diversity. When phylogeographic data for multiple co-occurring species are available, we can infer the evolutionary history of a landscape, identifying key climatic phenomena, landscape features and forces that have collectively shaped species’ abundance and distribution. Comparative phylogeography, for example, revealed the varied responses of species to glaciation during the last glacial maximum (LGM), including the consequences of expansion from major refugia  as well The Pilbara region, in the north of Western Australia is another vast and ancient landscape, yet until recently ,21,22 thPhylogeographic studies of two widespread shrub species from the Pilbara showed high genetic diversity but a lack of phylogeographic structure ,21. ThisC. hamersleyana) and Western Gidgee (A. pruinocarpa). Both species are common and widespread, forming conspicuous components of the floristic community. They have distributions across a range of features, including rocky outcrops and ranges, as well as along alluvial plains and drainage lines, which provides an ideal opportunity to explore drivers of evolution in this landscape. Using a combination of nuclear microsatellite markers and chloroplast DNA sequences we aimed to determine whether: (a) Tree species show evidence of historical persistence in the landscape through a high haplotype number and diversity; (b) there is higher genetic diversity associated with topographic features such as the Hamersley and Chichester Ranges, and lower diversity in surrounding areas as evidence for these features acting as historical refugia for the widely sampled C. hamersleyana; and (c) there is evidence of genetic connectivity across the landscape, resulting in a lack of genetic structure as previously observed in two other widespread Pilbara tree species [To assess whether the patterns observed in widespread Pilbara flora are idiosyncratic or reflective of broader patterns throughout the landscape, we expand upon the body of work by examining patterns of phylogeography in two iconic trees, the Hamersley Bloodwood  K.D. Hill and L.A.S. Johnson), commonly known as the Hamersley Bloodwood, is widely distributed throughout the Western Australian Pilbara region  in the east. These gradations suggest that hybridisation may be an important feature of the Hamersley Bloodwood [a region . It growy crests . Howeverloodwood . A. pruinocarpa , commonly known as the Western Gidgee or Burlurru [A. pruinocarpa produces a profusion of large golden flowers from October to December and is capable of clonal growth via root-suckering. Insects are likely to be the dominant pollinators. The seeds are small, flat, and black with a small aril, which suggests ants are typical seed dispersers [Burlurru , occurs Burlurru . It occuspersers . C. hamersleyana (n = 480) and 23 populations of A. pruinocarpa (n = 460) across the Pilbara region of Western Australia (C. hamersleyana) and four (A. pruinocarpa) chloroplast sequence regions known to display intraspecific variation [Leaf material was collected from 24 non-adjacent individuals from 20 populations of ustralia   . Followipatterns . MicrosaFIS) was estimated in GENEPOP and significance values determined with 10,000 exact tests.The 14 loci for each species were assessed for genotypic disequilibrium in GENEPOP v.4.2  with sigFST [RST [K = 1–20 with 10 replicates for each K, a burning of 100,000 generations and 500,000 further Monte Carlo Markov chain (MCMC) generations. Run consistency was assessed with CLUMMP v.1.1.2 [K with the highest posterior probability was determined with STRUCTURE HARVESTER v.0.6.93 [FST values (FST/(1 − FST) for genetic distance and the natural logarithm of geographical distance.GENALEX was used to assess genetic differentiation as FST  (a) amonFST . The difFST [RST  which taFST [RST . StructuFST [RST . We seleFST [RST . Cluster v.1.1.2  and the v.0.6.93 . The disC. hamersleyana: The ribosomal protein rpL16 intron, the intergenic spacer ndhC-trnV, and the tRNA-Gly (trnG) intron. For A. pruinocarpa, samples were sequenced at the intergenic spacers ndhF-rpl32, rpl32-trnL, trnS-trnG, and psbD-trnT. Amplifications were carried out according to the protocols listed in [Three chloroplast DNA regions were sequenced for isted in  with theisted in . A Serapisted in  which weisted in  and corristed in . Indels isted in .Fs [R2. The latter statistic compares the difference between the number of singleton mutations and the average number of nucleotide differences and has greater power than Tajima’s D and Fu’s FS when testing smaller datasets [NST, which considers not just differences in haplotype frequencies but also genetic distances, was significantly higher than GST using the U test in the program PERMUT v.2.0 [The number of haplotypes and haplotype diversity including indels were determined using DnaSP v.6 . SubsequFs , and Ramdatasets . For alldatasets  along wiUT v.2.0 . NetworkUT v.2.0  and the UT v.2.0 . The relUT v.2.0 . C. hamersleyana, the south-western Australian endemic Eucalyptus marginata (Donn ex Sm) (GenBank acc. KC180781) and two Corymbia species, C. citriodora ((Hook.) K.D. Hill and L.A.S. Johnson) (GenBank acc. KP015029) and C. tesselaris ((F.Muell.) K.D. Hill and L.A.S. Johnson) (GenBank acc. KC180803) were used as outgroups. C. citriodora and C. tesselaris possess overlapping distributions that are centred throughout Queensland and northern New South Wales. Bayesian trees were dated according to two different methods and three different calibration dates. The first method (a) utilised the estimated stem age of the Corymbia (and Angophora) clade as 52–57 Ma [Angophora/Corymbia group reported in Thornhill et al. (2012) [−4 s/s/Ma) and the second, (c) using combined root, pollen, and macrofossil calibrations (8.3 × 10−4 s/s/Ma) [−4. For all analyses, a GTR+ invariant sites model of sequence evolution was implemented as identified using the corrected Akaike information criterion (AIC) in JModelTest2 [Evolutionary relationships were investigated using Bayesian analysis in BEAST v.1.10 . For C. 52–57 Ma  with a n52–57 Ma  was sele. (2012) , the fir s/s/Ma)  under a  s/s/Ma) . For thedelTest2 . A. pruinocarpa were assessed using the south-western Australian endemic A. daphnifolia (Meisn.) (GenBank acc. LN885259) as an outgroup. Highest credibility trees were dated according to the cpDNA substitution rate identified for the Mimosoid clade in [−4 s/s/Ma). This analysis utilised a lognormal prior around the strict clock rate with a standard deviation of 1.0 × 10−4 and a Yule speciation tree prior. An F81 + gamma model of sequence evolution was applied as determined by the corrected AIC in JModelTest2. Evolutionary relationships within clade in  (4.83 × http://tree.bio.ed.ac.uk/software/figtree/).For both species, final analyses involved combining four independent runs of 10 million generations. Convergence of each run was assessed using ESS values in TRACER v.1.7.1 . The firFST based on ENA corrected and uncorrected allele frequencies . The average observed heterozygosity was 0.48 ± 0.01. Private alleles occurred in 12 of the 20 populations . Bayesian clustering analysis did not identify any meaningful genetic clusters with K = 2 identified  and highest in HAM (0.54) (FIS = 0.17 ± 0.01) indicated a significant deficit of heterozygotes in all populations except for the HAM population (FST) was low across all populations . The STRUCTURE analysis did not identify any strong patterns of genetic structure within A. pruinocarpa. The analysis resulted in three genetic clusters; however, most individuals were assigned to all three clusters in varying proportions  listed in M (0.54) . Privatepulation . Geneticulations  with a mportions , a resulportions .t = −0.96, p = 0.349). There was no evidence of departure from neutrality in tests of Tajima’s D or Fu’s Fs  to low frequency of rare haplotypes  . All pop Fu’s Fs . Models n growth . The ratn growth .n = 29) of haplotypes were population specific with only eight haplotypes  shared amongst populations. AMOVA showed that 51.14% of the variation was partitioned within populations and 48.86% amongst populations. Tests of neutrality (Tajima’s D and Fu’s Fs) were non-significant but Ramos Onsin and Rozas’ R2 statistic was significant relative to expectations under the standard neutral model of evolution . The Median Joining network clearly delineates the two highly divergent clades, with the larger clade showing a star-like topology with the common and widespread Hap 1 in the centre  7.2 Ma (3.9–11.3 95% HPD), (b) 6.5 Ma (3.5–10.3 95% HPD), and (c) 5.5 Ma (3–8.5% HPD). Within the smaller clade all three differently calibrated trees indicated moderate support (>94% posterior probability) for further division into two sub-clades separating three haplotypes  from Hap 9 and 14. Within the larger clade all three analyses indicated high support (100% posterior probability) for further division into two subclades separating three haplotypes  from the remaining six  . Neithere centre . We did A. pruinocarpa showed little resolution, except for the first node splitting five highly divergent haplotypes  from all other haplotypes and a secondary internal node that split eight haplotypes . All other internal nodes were poorly supported (NST (0.489) with GST (0.366) with p < 0.01. The network of haplotype relationships reflects the complexity seen in the Bayesian tree with two areas of star-like phylogenetic patterning around the common haplotypes, Hap 4 and 8, and the presence of highly divergent haplotypes interspersed throughout the network  and stepwise mutation (RST) models suggesting there are currently few barriers to pollen and seed movement throughout the landscape, including distance, as peripheral and more isolated populations retained high levels of genetic diversity and low genetic divergence. These attributes indicate the maintenance of large effective population sizes over recent timescales [E. leucophloia [Acacia ancistrocarpa [A. pruinocarpa) showed significant FIS values, which could indicate some level of inbreeding, including crossing between clonal ramets or due to structuring and crossing between related individuals within populations [The use of both nuclear and cpDNA markers in phylogeographic studies allows for distinction between processes of gene flow occurring via pollen and seed. Neutral, nuclear DNA variation reflects pollen and seed dispersal whereas cpDNA, when maternally inherited, reflects only seed movement . Further K value ,98—the rmescales ,100. Higcophloia , and thetrocarpa , althougtrocarpa ,22. Thistrocarpa ,102. Higtrocarpa  whereas trocarpa ,103 and trocarpa  gene floulations . Corymbia calophylla from south-western Australia had a much higher pollen to seed ratio (68:1) [Eucalyptus gomphocephala, showed pollen migration rates up to 200 times higher than seed migration rates [C. hamersleyana possesses winged seeds that may assist in wind dispersal while the small aril in A. pruinocarpa suggests ant dispersal [The cpDNA data that reflects historical gene flow processes were also informative. As discussed previously, the presence of highly divergent haplotypes in both species suggests that historically at least, populations of these trees have been isolated, allowing for the development of divergent haplotypes. The general lack of phylogeographic structure observed in this study, reflected in the presence of several common and widespread haplotypes as well as in the co-occurrence of highly divergent haplotypes, could arise via subsequent dispersal of these divergent lineages by seed or may indicate incomplete lineage sorting of ancestral polymorphisms. However, incomplete lineage sorting is more problematic when working at shallow time depths , and theo (68:1)  and the on rates . Other eon rates . Interesispersal . Comparative phylogeographic analysis of some plant species has allowed direct observation of the impact of LDD on the formation of genetic structure. For example, in the Albany Subtropical Thicket Region of southern Africa, analysis of three widespread, sympatric trees was conducted to determine whether watersheds were barriers to seed dispersal . All thrC. hamersleyana and A. pruinocarpa, that experience fruit dehiscence during the summer months [The presence of extreme meteorological events is considered to be a contributing factor in gene flow  and it hr months ,32. Dispr months .Triodia spp.), ribbon grass , and the scattered wattles such as kanji bush (Acacia inaequilatera), allowing ease of seed movement both via animal vectors and wind [There are also a number of other features of the Pilbara that may contribute to gene flow and colonisation processes in the biota ,110. Theand wind . The secand wind ,112. Emuand wind  and may and wind . Relativand wind ,116,117.Our phylogeographic analysis has revealed important shared characteristics of two widespread tree species endemic to the Pilbara region, in particular, the ability of seed to travel long distances despite exhibiting different seed morphology associated with dispersal. In addition, the identification of a Miocene origin of divergent lineages in both species confirms the long-term persistence of these taxa in this ancient landscape and suggests that the intensifying aridity associated with this period was a critical driver of evolution in these Pilbara species. The findings of extensive genetic connectivity and a general lack of genetic structure are important given that seed sourcing for dryland restoration efforts is an ongoing activity within this region.


Hypophthalmichthys nobilis) and silver carp (H. molitrix), collectively called bigheaded carps, are cyprinids native mainly to China and have been introduced to over 70 countries. Paleontological and molecular phylogenetic analyses demonstrate bighead and silver carps originated from the Yangtze‐Huanghe River basins and modern populations may have derived from the secondary contact of geographically isolated fish during the last glacial events. Significant genetic differences are found among populations of native rivers  as well as introduced/invasive environments , suggesting genetic backgrounds and ecological selection may play a role in population differentiation. Population divergence of bighead carp or silver carp has occurred within their native rivers, whereas, within the Mississippi River Basin (MRB)—an introduced region, such genetic differentiation is likely taking place at least in silver carp. Interspecific hybridization between silver and bighead carps is rare within their native regions; however, extensive hybridization is observed in the MRB, which could be contributed by a shift to a more homogenous environment that lacks reproductive isolation barriers for the restriction of gene flow between species. The wild populations of native bighead and silver carps have experienced dramatic declines; in contrast, the introduced bigheaded carps overpopulate the MRB and are considered two invasive species, which strongly suggests fishing capacity (overfishing and underfishing) be a decisive factor for fishery resource exploitation and management. This review provides not only a global perspective of evolutionary history and population divergence of bigheaded carps but also a forum that calls for international research collaborations to deal with critical issues related to native population conservation and invasive species control.Bighead carp ( In the early 1990s, Louis had already been known for his pioneering studies on the evolutionary origin of lake whitefish using mtDNA‐RFLP  am very fortunate that I have met many great scientists. Among them, Prof. Sifa Li and Dr. Louis Bernatchez impact me most in my academic career and personal life. Prof. Li at the Shanghai Ocean University (SHOU) was my master's thesis advisor and offered me a research assistant position following my graduation. He was one of the earliest investigators who applied allozyme electrophoresis to study aquaculture genetics and a founder in fish germplasm research and conservation in China. In the 1980s, Prof. Li and his collaborators revealed significant morphological and genetic differences among populations of three large rivers, that is, Yangtze, Pearl and Amur in bighead, silver and grass carps  and fifth (bighead carp) with fish production in world aquaculture in 2016 FAO, . CultivaThe bigheaded carps were introduced to over 70 countries and territories  estimated the divergence between bighead and silver carps occurred ∼ 3.41 MYA  and found significant genetic differentiation between the Yangtze and Mississippi populations in both bighead and silver carps. This genetic differentiation between native and introduced populations might be explained by the variations in genetic backgrounds, genetic drift, and ecological selection . Using microsatellite markers, Farrington et al. , tench (Tinca tinca), channel catfish , and other exotic fish species had invaded the upper Yangtze . It appears certain the introgression of bigheaded carps has resulted in a hybrid swarm, although a clear understanding of population dynamics of parental and hybrid species is lacking (Lamer et al., 1 hybrids with twisted gill rakers may lead to reduced fitness in food competition, which can be explained by the low percentage of F1 individuals found throughput the MRB (Lamer et al., Silver carp and bighead carp are known to hybridize and produce viable offspring under artificial manipulations (Kolar et al., Several studies suggest that a combination of genetic and environmental factors may contribute to the success of bighead and silver carp hybrids in the Mississippi River Basin (Lamer et al., 7.3In China and some other countries, bighead and silver carps are excellent food fish. Silver and bighead carps ranked respectively second and fifth in world aquaculture fish production in 2016 FAO, . On the None declared.


Styphelia longissima (Ericaceae) is a critically endangered shrub, restricted to a single fragmented population near Eneabba, 250 km north of Perth, Western Australia. For this population, we sought to characterize population genetic variation and its spatial structure, and aspects of the mating portfolio, from which strategies that optimize the conservation of this diversity are identified. A comprehensive survey was carried out and 220 adults, and 106 seedlings from 14 maternal plants, were genotyped using 13 microsatellite markers. Levels of genetic variation and its spatial structure were assessed, and mating system parameters were estimated. Paternity was assigned to the offspring of a subsection of plants, which allowed for the calculation of realized pollen dispersal. Allelic richness and levels of expected heterozygosity were higher than predicted for a small isolated population. Spatial autocorrelation analysis identified fine-scale genetic structure at a scale of 20 m, but no genetic structure was found at larger scales. Mean outcrossing rate (tm = 0.66) reflects self-compatibility and a mixed-mating system. Multiple paternity was low, where 61 % of maternal siblings shared the same sire. Realized pollen dispersal was highly restricted, with 95 % of outcrossing events occurring at 7 m or less, and a mean pollen dispersal distance of 3.8 m. Nearest-neighbour matings were common , and 97 % of mating events were between the three nearest-neighbours. This study has provided critical baseline data on genetic diversity, mating system and pollen dispersal for future monitoring of S. longissima. Broadly applicable conservation strategies such as implementing a genetic monitoring plan, diluting spatial genetic structure in the natural population, genetically optimizing ex situ collections and incorporating genetic knowledge into translocations will help to manage the future erosion of the high genetic variation detected.An understanding of genetic diversity and the population genetic processes that impact future population viability is vital for the management and recovery of declining populations of threatened species.  Styphelia longissima (Ericaceae) is a critically endangered shrub restricted to a single fragmented population near Eneabba, 250 km north of Perth, Western Australia. Here, 13 microsatellite markers were used to genotype 220 adults and 106 seedlings to assess genetic diversity and structure, mating system parameters and pollen dispersal. The only population of S. longissima was found to be characterised by surprisingly high levels of genetic diversity, with small groups of related individuals within which the vast majority of mating occurs. This study has provided critical baseline data for future monitoring and to inform conservation strategies. Genetic diversity is widely acknowledged as a critical, yet under-utilized, consideration for the conservation management of threatened species . For stuPlant mating systems are defined as the genetic relatedness and pairings between plants in a population, not to be confused with plant breeding systems, which more commonly refers to the anatomical and physiological aspects of a plant’s reproductive system . Mating Styphelia longissima (Ericaceae) is a recently described and clearly distinct species found near Eneabba, Western Australia , mating system and pollen dispersal for any member of the Australian Ericaceae (subfamily Epacridoideae), a large group containing ca 420 species  to check for underdeveloped seeds. On average, 20 % of the fruit from each maternal plant were non-viable and were discarded. Seeds were extracted, sterilized and plated following To determine the viability of the fruit, which can contain either one or two seeds, X-ray images were taken using a FaxitronS. longissima were used in four multiplex primer mixes and reactions were carried out, as per Genomic DNA was extracted from 220 adult leaf tissue samples and 106 whole seedlings (hereafter referred to as the adult and seedling cohorts), following the Carlson extraction method (N), number of alleles (Na), effective number of alleles (Ne), observed heterozygosity (HO), expected heterozygosity (HE) and fixation index (F). A Wilcoxon’s rank sum test was used to test for significant differences in HO, HE and F between adults and seedlings in R  within the population was assessed in the adult cohort using the program STRUCTURE V2.3.4 (r) was calculated for all pairs of individuals within each distance class. Confidence limits (95 %) about (i) the null hypothesis of no spatial structure and (ii) r, were generated by 1000 bootstraps. Distance matrices, Mantel test and SAA were generated in GenAlEx V6.51b2  was used to assess the genetic relatedness of adult individuals as a function of geographic distance. Evenly spaced distance classes of 5 m were chosen because it was the smallest distance class that maintained >30 individuals in all classes. A correlation coefficient ( V6.51b2 .Fm), multilocus outcrossing rate (tm), singlelocus outcrossing rate (ts), bi-parental inbreeding rate (tm - ts), correlation of paternity (rp) and correlation of outcrossing among loci (rtl) were estimated in the seedling cohort using MLTR . There was a heterozygote deficit at 12 of 13 loci. Heterozygosity was lower and F was higher in the seedling cohort than in the adult cohort. However, all three measures did not significantly differ from the adult cohort , 0.879 (HE), 0.336 (F)). Number of alleles was significantly higher in the adult cohort compared to the seedling cohort . Average allelic richness per locus was 10.08 for the adult cohort and 7.49 for the seedling cohort.Replicate samples of 50 adults and 20 seedlings  were genotyped twice and were scored identically. All families used in analyses showed Mendelian inheritance patterns. There was no evidence for allelic dropouts, but there was evidence that null alleles might be present at all but one locus. In the adult cohort, the number of alleles per locus ranged from 6 to 27 , with a P = 0.061). Principal co-ordinate analysis of pairwise genetic distance revealed no distinct clustering. However, spatial auto correlation analysis revealed fine scale genetic structure, with a positive significant correlation between the genetic relatedness of individuals up to 20 m, which is the distance where r first changed from significant to non-significant ). Mating system estimates (±SE) were: parental inbreeding coefficient (Fm) 0.27 (0.01); singlelocus outcrossing rate (ts) 0.30 (0.06); biparental inbreeding rate (tm-ts) 0.36 (0.07); correlation of paternity (rp) 0.62 (0.18); parental neighbourhood size (1/rp) 1.6. Mating system estimates from analysis of only large families were similar to estimates from analysis of the entire seedling cohort [see Estimated outcrossing rate (±SE) was considerably less than one  were assigned identical maternal and paternal genotypes and contained no non-maternal alleles, and were therefore were classified as selfs. The ΔLOD scores were generally higher for assigned sires of seeds produced from selfing, indicating a higher degree of confidence when assigning sires for selfing events, compared with outcross events tm = 0.66). Total number of sires ranged 1–4, while number of outcross sires ranged 0–3, for 3–15 seeds per family  was higher than that reported in a review of microsatellite data for Australian shrubs  and plants with a localized distribution  (S. longissima (0.21 km2). Therefore, measures of expected heterozygosity in cases of extreme endemism, like that of S. longissima, may not be fully represented. When compared with diversity measures from other microsatellite-based studies on more narrowly endemic Australian shrubs, including those with localized distributions restricted to banded ironstone formations in Western Australia  a significant deficit of observed heterozygosity from HWE expectations at 12 of 13 loci; (ii) an overall fixation index of F = 0.30; (iii) equivalent fixation indices in the adult and progeny cohorts; (iv) high estimates of selfing ; (v) high estimate of bi-parental inbreeding (tm  - ts = 0.36); (vi) high estimate of correlation of paternity (rp = 0.62), (vii) restricted pollen dispersal (97 % of outcrossing events among three nearest-neighbours), and (viii) strong SGS. Despite this, levels of allelic diversity and expected heterozygosity were surprisingly high.Multiple lines of evidence indicate that inbreeding is a feature of S. longissima indicates the population consists of multiple small neighbourhoods, within which the vast majority of matings occur. Consequently, given the strong spatial genetic structuring at interplant distances less than 20 m, allelic frequencies are not equal across the population, and because of restricted pollen dispersal, realized mating is predominantly among relatives and departs significantly from random mating.Technical artefacts, such as null alleles, could explain the observed deficit of heterozygotes, but this seems unlikely given the consistent heterozygote deficit across all but one locus. Here, a Wahlund effect appears a more likely biological explanation. The Wahlund effect describes a deficiency in observed heterozygosity compared with expected heterozygosity due to population substructure, where a departure from Hardy–Weinberg Equilibrium (HWE) occurs because subpopulations that have different allelic frequencies are considered as one population, even if the subpopulations are in HWE . The finS. longissima—that is fitness declines are not associated with inbreeding and more homozygous inbred progeny are not being selected against as they germinate, establish and mature. This appears surprising, as inbreeding depression is a common feature of plants  with altered behaviours impacting mating and eroding genetic diversity of progeny? Although the outcrossing rate (tm = 0.66) for S. longissima is consistent with that reported for other rare insect pollinated shrubs in Western Australia  and correlated paternity (rp = 0.62) were considerably greater than in many other insect pollinated species (rp = 1.6). Again, it is unclear to what extent this might also reflect pre-disturbance measures. However, increased paternal diversity has been shown to positively influence fitness in other species  was substantially less than the 2188 individuals reported in 2007 , and revS. longissima is that only one natural population exists. In the case of a catastrophic event which eradicates the population, the species will become extinct in the wild. This concern is also pertinent for losses of genetic diversity, whereby the loss of alleles is irrecoverable because there are no other populations that can supplement these losses. Thus, an ongoing genetic monitoring plan should be implemented which can utilize the measures of genetic diversity established in this study as a baseline to identify loss of genetic diversity.The biggest concern for the conservation of S. longissima is protected ex situ in tissue culture collections maintained by the Kings Park Botanic Gardens and in seed collections at the Threated Flora Seed Centre, Department of Biodiversity Conservation and Attractions in Western Australia. The genetic representation of these collections, however, is unknown. Due to the SGS identified in this study, ex situ collections should be genetically optimized by sampling material (seed or tissue culture) across the current distribution and ensuring that samples from within 20 m genetic neighbourhoods are minimized while samples from among neighbourhoods are maximized, thereby efficiently capturing representative genetic diversity.Currently, Whether heterosis is associated with outcrossing between mates beyond the 20 m genetic neighbourhood, and whether heterosis is associated with increasing paternal diversity, needs to be confirmed. If it is, then increased seedling fitness with heterosis from wide outcrossing, and increased maternal fitness with increased paternal diversity, enable an active management plan for conservation benefits. These may be achieved by artificially dispersing seed and/or planting seedlings within the natural population to erode SGS. Spatial homogenization means that nearest-neighbour mating does not then equate to mating between relatives, which results in fitness benefits from heterosis.in situ extinction risk  for S. longissima for only large families and all families. Estimates include parental inbreeding coefficient (Fm), multilocus outcrossing rate (tm), singlelocus outcrossing rate (ts), bi-parental inbreeding rate (tm-ts), correlation of paternity (rp) and parental neighbourhood size (1/rp).Figure S2. Relative confidence for the paternity assignments from CERVUS of seeds of Styphelia longissima, with realized pollen dispersal categories shown. LOD score is an estimate of the likelihood that a candidate parent is the true parent.plab005_suppl_Supplementary_Table_FiguresClick here for additional data file.plab005_suppl_Supplementary_MaterialClick here for additional data file.


Conservation and breeding programmes of livestock speciesdepend on determination of genetic diversity. Today in livestock species,microsatellite markers are commonly used to reveal population structure andgenetic diversity in both breeds and varieties. In this study, populationstructure, genetic diversity, and differentiation among four native Turkishsheep breeds including Güney Karaman, Kangal, Norduz, and Karakas wereassessed by using 21 microsatellite loci. By genotyping 120 individualsbelonging to four sheep breeds, a total of 275 different alleles, 37 of whichwere private alleles, were observed across all loci. The mean number ofalleles per breed ranged from 7.28 (Güney Karaman) to 8.09 (Karakas), whileallelic richness ranged from 7.22 (Güney Karaman) to 7.87 (Karakas). Meanobserved heterozygosity varied from 0.60  to 0.66 (Norduz andKarakas). The lowest pairwise  A large part of the sheep population raised inTurkey is represented by native breeds. Although native sheep breeds have low milk andmeat yields, they are resistant to temperature changes and diseases ofraised regions . Sheep raising has always been a part ofcultural values of Turkey through its history. In rural areas, sheep rearing notonly makes a contribution to breeders' incomes but also is a lifestyle knownas nomadic sheep breeding. Furthermore, Turkey makes a contribution to worldanimal genetic resources with nearly 20 defined native sheep breeds.Mainly distributed in Middle Anatolia and nearby places, Akkaraman is the mostraised breed with an approximately 40 % proportion among Turkish native sheepbreeds . There are differentvarieties of the Akkaraman breed such as Güney Karaman (GKR), Norduz (NRD),Karakas (KRK), and Kangal (KNG) adapted to different regions . GKR, also known as black sheep, is reared in theMediterranean region  in anomadic breeding system . The NRD variety is raised in VanProvince, whereas KRK sheep are raised in Eastern Anatolia includingDiyarbakır, Van, Bitlis, and Hakkâri provinces . KNG,raised extensively in Sivas and Malatya provinces, has the largest bodysize among variety of the Akkaraman breed . Since KNG sheep have been derived from the Akkaraman breed by selection inthe recent past, they show similar phenotypic traits as Akkaraman sheep.On the contrary, GKR, NRD, and KRK sheep have differed from Akkaramandistinctively in terms of phenotypic traits due to rearing in differentregions together with diverse adaptation processes for a long time.It has been reported that GKR, NRD, and KRK breeds are in danger ofextinction . While GKR has been included ina conservation programme at Bahri Dagdas International Agricultural ResearchInstitute authorized by the Ministry of Agriculture and Forestry, GeneralDirectorate of Agricultural Research and Policies, NRD and KRK breeds havebeen under a conservation programme handled by breeders .Genetic diversity shaped by evolution and climate changes is crucial for thesurvival of populations in different regions . Sheeppopulations raised near the domestication centre have higher genetic diversitywhich decreases with increasing geographic distance .There is strong evidence that the domestication centre of sheep is the FertileCrescent including southeastern and Eastern Anatolia of Turkey . Sheep were spread out from the Fertile Crescent to other regions ofthe world. Today, sheep are raised in almost all regions of the world includingboth desert and tropical regions due to their extraordinary adaptability.Genetic diversity studies are the first step of conservation and breedingprogrammes. Many molecular markers such as RAPD , AFLP, PCR-RFLP , and mtDNA have been applied to detect genetic diversity inlivestock. Today, SSRs  and SNPs (single nucleotide polymorphisms)  and NGS (next-generation sequencing)  are preferredto reveal genetic diversity among and within different livestock breeds.SSR markers are commonly used to reveal genetic diversity because they areabundant, distributed through genome randomly, easy to access and apply,highly polymorphic, and show codominant inheritance. SSR markers were usedto detect genetic diversity or parentage test in different livestockincluding cattle , sheep ,goat , pigs , horses  chickens , rabbit , ducks , and donkeys .Despite the huge phenotypic variations among GKR, NRD, and KRK sheep, theyare known as varieties of the Akkaraman sheep breed. Unfortunately, geneticstudies focusing on population structure and phylogenetic relationship amongthese varieties are scarce. In addition, there are not enough studiesrevealing genetic diversity in NRD and GKR whose population sizes havedecreased in the last few decades. Hence, this study aimed to determine geneticdiversity and phylogenetic relationship among KNG, GKR, NRD, and KRKpopulations by using 21 SSR markers.22.1In this study, a total of 120 sheep (from both sexes) were chosen from foursheep breeds raised in different regions in Anatolia . Samplesbelonging to KNG  to determine genetic diversity in sheep, wereused. PCR amplifications were carried out in a total volume of 25 ®2.0 version 1.3.1.1 .In this study, 96 automated capillary electrophoresis systems were used for fragmentanalysis. The capillary conditioning solution, inlet buffer, separation gel,and 35–500 bp marker were prepared according to the user manual provided bythe manufacturer. After capillary electrophoresis separation, the raw datawere recorded, and band sizes were calculated using PROSize2.1.2Number of private alleles (PA) and allele size range (ASR) was determinedby using the Convert version 1.3.1  program. Convert version 1.3.1  was also used to convert data to other program's fileformats. Number of alleles  dendrogram constructed on basis of Nei's standard geneticdistance . The UPGMA dendrogram was obtained by the POPGENE version 1.31 program. In addition, factorial correspondence analysis(FCA) and Bayesian approach based on STRUCTURE clustering analysis werecarried out. GENETIX ver. 4.05  software was used forFCA analysis. Bayesian model-based clustering was constructed by usingStructure software . One hundred independent runswere carried out for different genetic clusters . In four sheep populations, mean number of alleles and effectivealleles were 13.10 and 7.78, respectively, across 21 microsatellite loci.The lowest (6.03) and the highest (13.74) allelic richness (AR) values were detected in ETH10and CSRD247, respectively. PIC value ranged from 0.71 (ETH10) to 0.91(OarFCB304) with a mean of 0.84.Descriptive statistics together with private alleles for sheep populationsare given in Table 2. The mean number of alleles per population ranged from7.28 (GKR) to 8.09 (KRK), while AR ranged from 7.22 (GKR) to 7.87 (KRK).Mean observed heterozygosity varied from 0.60 (KNG) to 0.66 (NRD and KRK).Private alleles, another parameter of genetic differentiation, ranged from 7(KRK) to 12 (KNG).3.2Pairwise The lowest pairwise Nei's genetic distance values in studied populations are given in Table 4.The lowest genetic distance (0.088) was between KNG and KRK populations,while the highest genetic distance (0.153) was between KRK and NRDpopulations.A UPGMA dendrogram based on Nei's genetic distance values is given in Fig. 2 for studied populations. The UPGMA dendrogram classified studied populationsin two branches in which GKR, KNG, and KRK constituted the first branch,while NRD population clustered separately in the other branch.Four native Turkish sheep populations were located in three-dimensionalspace by FCA analysis given in Fig. 3. The FCA analysis separated the NRD andGKR populations very clearly, while KRK and KNG clustered close together.Structure analysis, another clustering method, revealed that GKR, KNG, andKRK populations clustered together, while NRD clustered separately at 4Genetic diversity parameters detected in the present study were similar orslightly higher than previous studies. Using 18 microsatellite loci in ninenative Turkish sheep breeds, Yilmaz et al. (2014) observed mean number ofalleles and effective alleles as 10.11 and 9.62, respectively, with ARranging from 6.48 (OARFCB20) to 13.75 (OarFCB304). Yilmaz et al. (2015)reported mean number of alleles and effective alleles as 12.29 and 7.04,respectively in Gökçeada, Kıvırcık, Karacabey Merino, and Sakız sheepbreeds by using 17 microsatellite loci, while Oner et al. (2014) reportedmean number of alleles and effective alleles as 11.89 and 5.65, respectivelyin Kıvırcık, Pırlak, and Karacabey Merino sheep breeds by using 10microsatellite loci. These results show that four native Turkish sheeppopulations hold high genetic diversity. The high mean PIC value (0.84) detectedacross 21 microsatellite loci indicates that these microsatellite loci haveability to show genetic diversity in native Turkish sheep populations.Although the mean PIC value was similar to previous studies conducted in nativeTurkish sheep breeds , a lower PIC value wasreported by Oner et al. , which used 10 microsatellite loci. Mean numberof alleles and observed heterozygosity were reported as 8.78–0.78 and8.33–0.74 in NRD and KRK, respectively .Although these values were higher than values detected in the present study,similar observed heterozygosity values were reported in some native Turkish sheepbreeds including Karayaka (0.69), Morkaraman (0.60), Sakız (0.59), and Tuj (0.62) . Additionally, similar observed heterozygosityvalues (ranging from 0.65 to 0.70) were reported in some native Italiansheep breeds . Lower In this study, expected heterozygosity values were higher than observedheterozygosity values, which may be due to presence of more homozygousindividuals. Additionally, positive inbreeding coefficient values weredetected due to presence of more homozygous individuals than heterozygousones. Although similar All pairwise In this study, the number of private alleles ranging from 7 (KRK) to 12 (KNG)was higher than previous studies conducted on native Turkish sheep breeds. Number of private alleles is affected by numberof migrated individuals across populations. It is normal to observe a lownumber of private alleles in the case of the presence of migrated individuals fromdifferent populations or populations coming from a common origin. The numberof private alleles and pairwise 5This study revealed that KNG, GKR, NRD, and KRK populations still hold enoughgenetic diversity despite decreasing in population sizes in the last few decades.Inbreeding coefficient values were not at high levels affecting thesustainable use of NRD and KRK populations in the future. Nevertheless,high inbreeding coefficients were detected in KNG and GKR, which requirestaking measures in order to decrease inbreeding. In this study, geneticdifferentiation coefficients and phylogenetic analysis show that GKR andNRD populations, which have been accepted as Akkaraman varieties, havebecame genetically different from the Akkaraman breed. In order to clarify thegenetic differentiation of GKR and NRD from the Akkaraman breed, morecomprehensive molecular studies (such as SNP chips or next-generationsequencing etc.) are needed.


Coaching athletes is highly rewarding yet stressful, especially at the elite level where media, fans, and sponsors can contribute to an environment that, if not well-managed by the coach, can lead to burnout. Coaches who display perfectionistic tendencies, such as striving for flawlessness, may be particularly vulnerable—even more so if they are overly critical of themselves and have a tendency to ruminate over their performance, or if they are attempting to convey an image of faultlessness, or both. A total of 272 coaches completed a battery of inventories assessing burnout, perfectionistic thoughts, and the tendency for perfectionistic self-presentation. All variables correlated significantly: coaches with higher scores on exhaustion scored higher both on perfectionistic thoughts and self-presentation. However, when three subscales of perfectionistic self-presentation were considered separately, lower and nonsignificant correlations emerged. We believe that this can be explained by the heterogeneous group of coaches participating in this study. Whereas all coaches may at times ruminate privately—self-oriented perfectionism—about their perceived failure to perform to expectations, not all may feel the pressure to present themselves to others as faultless—a more socially prescribed perfectionism. This finding warrants further investigation, preferably comparing coaches at different levels of public scrutiny. Coaching is associated with many positive facets, but also with the pressure to perform within a stressful environment not known to forgive errors . This maIndividuals striving for flawless performance while being overly self-critical of their achievements may display perfectionistic tendencies ,7,8,9; cBurnout has been argued to be a debilitating stress syndrome, defined by Freudenberger  as “a stThe link between trait perfectionism and burnout has been empirically examined, for example among junior elite soccer players ,26, intePerfectionistic concerns may lead to rumination—in fact, rumination was the variable most strongly correlated with emotional exhaustion in the study by Tashman and colleagues . Apart fOur focus on rumination is in keeping with conceptual advances in the perfectionism field that highlight the need to supplement and extend the current focus on trait perfectionism by incorporating a focus on the cognitive side of perfectionism. Analyses by Flett and associates ,39,40 suWe therefore suggest, in line with the above, that coaches who engage in perfectionistic thinking or cognitions are more vulnerable to exhaustion than coaches less prone to this type of rumination. If indeed perfectionistic cognitions result from automatic thought processes that focus on the attainment of perfection or the failure to achieve it, such a finding may explain why perfectionistic cognitions can result in elevated levels of anxiety, depression, general negative affect, and life dissatisfaction ,42. InitOur first hypothesis is therefore that coaches actively and frequently engaging in rumination about their own performance, including their attainment or failure to reach perfection, are more likely to score high on exhaustion. Our second hypothesis is that perfectionistic coaches focusing on self-presentational attempts—to either demonstrate their own superiority to others in public situations or to avoid demonstrating imperfection—are particularly vulnerable and therefore will also score higher on exhaustion.Data were collected with a Web survey where a link was e-mailed to the participants. Two reminders were sent out within two and four weeks. For those working as premier league soccer coaches, the data collection occurred in conjunction with the season ending in November. For high school teachers, the timing was different since they were in different stages in November; however, this was in a period in the middle of the semester in Sweden. Our sample consisted of 272 coaches (231 men and 41 women) with a mean age of 42.9 years (SD 10.2). Of these 272 coaches, 46 were working as soccer coaches in the Swedish Premier League for men and women; 85 were coaching athletics, cross-country skiing, and orienteering at National Sport High Schools; 140 worked as coaches at newly instated National Sporting Programs at the high-school level ; and one coach failed to provide this information. In total, 36 different sports were represented in the sample: 46% were individual sports  and 54% were team sports . In the sample, 168 coached full-time (contracted to work 32–40 h per week), 66 worked between 50% and 79% of full-time (20–31 h per week) as coaches, and 40 worked less than 50% of full-time (<20 h per week) as coaches. For coaches working less than full-time in coaching, the vast majority combined their coaching jobs with other positions, predominantly as high school teachers. In total, 254 worked more than 80% (32 h per week) and 18 worked less than 80% (<31 h per week). The mean of actual self-reported working hours in total was 47 h (SD 17.9) per week where 94 persons estimated that they worked more than 50 h per week in total.Perfectionism Cognitions Inventory (PCI)  was usedPerfectionistic Self-Presentation Scale (PSPS)  with thrThe Exhaustion subscale from Coach Burnout Questionnaire (CBQ)  was usedEthical approval was first obtained from the Regional Ethical Review Board at Umeå University, Umeå, Sweden. Samples were chosen because of football being the sport with most full-time elite coaches in Sweden and the high school system being the largest employer of coaches in Sweden. A list of coaches was compiled, partly in cooperation with the Swedish Sports Confederation. A mailing list from the Swedish sports federation was used for recruitment of high school coaches and a mailing list from the Swedish football federation was used to reach all coaches in the Swedish Premier League for men and women, as well as the second league for men. Individual e-mails with standardized instructions, including an informed consent form and a link to the Web survey, were sent to all elite soccer coaches active in the Swedish Premier League, and to all coaches employed by the National Sport High Schools or in the National Sporting Programs. After an initial e-mail, three reminders were sent out: the first after one week, the second after three weeks, and the third after another three weeks. A final response rate of 45% was obtained (272 coaches out of 598).A hierarchical multiple regression using SPSS  with maximum likelihood estimation was chosen as the best method to analyze the data, thereby reflecting our aim to determine whether different levels of perfectionism influence the strength of association with exhaustion and at the same time controlling for variables that have previously been shown to impact burnout levels in coaches. The chosen control variables were age, gender, civil status , coaching level , and total amount of work hours per week.Means, SDs, and Cronbach’s alpha for the five variables are presented in p = 0.005) of the total variance and the second model including all control and predictor variables explained a further 19.6% (p F change = 0.000) of the total variance. Of the control variables, three had statistically significant contributions. Coaches who were single scored higher on exhaustion compared with those who were married or living together with a partner; coaches in Premier League football had lower levels of exhaustion than those coaching in high school settings; and coaches who in total worked more hours per week had higher levels of exhaustion. For the predictor variables, two had statistically significant relationships with exhaustion: nondisplay of imperfection from the PSPS  and perfectionistic cognitions , which had the largest impact on exhaustion.The multiple hierarchical regression model is presented in The majority of participating coaches displayed low to moderate levels of Exhaustion as measured by the CBQ see ; this isFirstly, coaches scoring high on perfectionistic cognitions scored higher on exhaustion when compared with coaches scoring lower on the PCI. If perfectionistic thinking is part of an automatic process as has been suggested ,42, it in = 45, 17%), it is unlikely that a sufficient number were subjected to scrutiny from media, fans, sponsors, or their own players to an extent that created stress—at least to a level that would result in Exhaustion on a group level. What we do not know, however, is how striving to “create a public image of flawlessness”  nonsignificant associations found between Perfectionistic Self-promotion and Exhaustion can, at least partly, be explained by the sample of participating coaches. Because only a minority of the 272 participants were elite coaches (ssness” ( that strssness” (. TherefoConclusively then, we have a somewhat disparate picture emerging between perfectionism and burnout in this study. That is, we detected a significant relationship between Perfectionistic Cognitions and Exhaustion, but largely non-significant relationships between Exhaustion and various measures of perfectionistic self-presentations—although the overall relationship between the PSPS and Exhaustion was significant as expected. The lack of significant relationships between the subscales and Exhaustion can be understood if we consider perfectionistic thinking as a reflection of self-oriented perfectionism—predominantly internally focused—whereas striving to present oneself to others instead reflects socially prescribed perfectionism—something that is more externally focused. Thereby, assuming that self-oriented perfectionism is a constantly present stressor affecting individuals, those affected individuals can hardly escape themselves. Consequently, a coach who ruminates about performance-related issues would do so without the need to interact with anyone, as also discussed by Hill and Curran . Future


This ensures genetic progression and delivers offspring with high genetic values. However, several favorable quantitative trait loci (QTL) alleles risk being eliminated from the breeding population during breeding. We show that this could reduce the mean genetic value that the breeding population could reach in the long term with up to 40%. In this paper, by means of a simulation study, we propose a new method for parental mating that is able to preserve the genetic variation in the breeding population, preventing premature convergence of the genetic values to a local optimum, thus maximizing the genetic values in the long term. We do not only prevent the fixation of several unfavorable QTL alleles, but also demonstrate that the genetic values can be increased by up to 15 percentage points compared with truncation selection.Genomic selection has been successfully implemented in plant and animal breeding. The transition of parental selection based on phenotypic characteristics to genomic selection (GS) has reduced breeding time and cost while accelerating the rate of genetic progression. Although breeding methods have been adapted to include genomic selection, parental selection often involves  The transition of phenotypic selection to genomic selection reduced the time of one breeding cycle from 15 to three years  and the preservation of the genetic variation of each marker in the breeding population. Based on the observation that two closely related individuals might contain a different rare marker allele, both individuals should be selected to preserve the genetic variation of both markers in the breeding population. Therefore, in contrast to other methods, the genetic relationship or inbreeding coefficient is not taken into account, but individuals are selected based on their genotype, ensuring the maximal selection of the different marker alleles and thus maximizing the genetic variance of their offspring. By doing so, we reduce the risk of premature convergence of the genetic values to a local optimum. Combined with truncation selection, the genetic progression is ensured in the short as well as in the long term. We benchmark our proposed scoping method against two existing selection strategies: the population merit method  from the University of Minnesota (UMN) and the University of North Dakota (NDSU) counting respectively 384 and 380 six-row spring inbred lines with 1590 biallelic SNP loci. Recurrent selection is applied to the base population to simulate the later breeding cycles (see Breeding scheme).We adopt the base population and breeding scheme of In a simulation study, the scoping method, in which a parental selection method is combined with a new mating design, is proposed and compared with truncation selection with random mating. The scoping method tries to maximize the genetic values in the long term, while preserving the genetic variation of the breeding population. It aims to avoid the loss of positive-effect QTL alleles, preventing the convergence of the genetic values to a local optimum. Because this method might select extreme GEBVs, the Pearson correlation cannot be used to evaluate the selection method due to its sensitivity to outliers. Instead, the mean genetic value of the breeding population, calculated on the basis of the true breeding values, is used to measure and evaluate the genetic gain for each method. The mean genetic value of the top-10 individuals is also reported. Our method aims to maximize the genetic gain of the top-10 individuals, while the remaining individuals of the breeding population serve to preserve important genetic marker alleles in the breeding population.baseline, population merit, population selection criterion, maximum variance total or scoping methods. The first breeding block (in breeding cycle zero) couples up 50 individuals of the NDSU dataset with 50 individuals of the UMN dataset with the highest phenotypic value, regardless of the parental selection method. This design choice ensures that each parental selection method has the same number of individuals in the breeding population over each breeding cycle. The subsequent parental selections are fully based on GEBVs, reducing the financial cost of phenotyping. A linear mixed effects model is used to obtain GEBVs from molecular marker scores (see Training panel). Each simulation consists of 50 breeding cycles and all results are averaged over 250 simulation runs.The recurrent selection scheme is illustrated in The baseline method selects 100 parents with the highest GEBVs (truncation selection) and couples them randomly. The idea is that favorable properties will be passed on to the next offspring, leading to high short-term gain and rapid fixation of favorable QTL alleles. However, several favorable QTL alleles will be eliminated from the breeding population during breeding, reducing long-term gain and causing the convergence of the genetic values to a local optimum.k the total number of molecular markers, j-th marker and j are present in the selected population, the value The scoping method continuously preserves genetic variation, avoiding premature convergence to a local optimum while ensuring a gradual increase of genetic values over breeding cycles. The parental selection is split into two parts: the pre-selection and the selection. First, a fraction of the breeding population with the highest GEBVs is pre-selected using truncation selection. This fraction, referred to as the scoping rate (SR), can take a value between 0.1 and 1. An SR of 0.1 pre-selects 100 individuals (10%) of the breeding population, whereas an SR of 1 will pre-select the entire breeding population (100%). During the selection, 100 different parents are chosen from the pre-selected population. In contrast to the baseline method, parents are not coupled randomly. From the pre-selected individuals, the one with the highest GEBV is chosen as the first parent. The second parent is chosen from the pre-selected individuals in such a way that the genetic variation of selected parents is maximized over each marker. Mathematically, the following score function is maximized:The scoping method combines truncation selection with a new mating design, coupling individuals with high GEBVs with individuals that maximize the genetic variation of their offspring. The pre-selection process avoids that individuals with lower GEBVs, which might maximize the genetic variation of certain parents, are not available for selection and thus avoids the loss of genetic gain in the short term. We expect that the mating design will reduce the loss of marker alleles while the pre-selection will eliminate unfavorable QTL alleles over time. This should lead to a slower but more accurate fixation of the favorable QTL alleles.k columns of which each column is calculated as n individuals at the i-th marker, n containing ones, k the number of markers, n the number of individuals in the breeding population and i-th marker. The population merit c a penalty weight and The population merit method was introduced by n the number of selected parents, i and The maximum variance total (MVT) method aims to maximize the genetic variance of the breeding population , k) and tails method .The scripts, figures, datasets of the base population and supplementary data are available from the github repository The baseline method combines truncation selection with random mating. Our results are similar to those reported by The scoping method introduces the scoping rate (SR) as a new parameter. With the SR, the breeder can control what fraction of the upper tail of the GEBV distribution will be considered for parental selection. Using a small SR, only individuals with high GEBVs will be considered, leading to truncation selection. When a higher SR is used instead, individuals with lower GEBVs will also be considered as candidates, making it possible to preserve the genetic variation of the breeding population. The SR provides the breeder with the option to choose between the maximization of the rate of genetic progression in the short term on the one hand or the maximization of the genetic variation in the long term on the other hand. As expected, the scoping method yields somewhat lower mean genetic values over the first ten breeding cycles see . HoweverAfter the tenth breeding cycle, the loss of several favorable QTL alleles causes the baseline method to reach a local optimum, rendering it less efficient than the scoping method. In contrast, by preserving the genetic variation within the breeding population, the scoping method strongly reduces the loss of favorable QTL alleles, thus preserving the potential to reach high genetic values. A higher SR will better prevent the loss of favorable QTL alleles, however, due to a slower increase in genetic value, a high SR will require a longer time before outperforming the baseline method. Therefore, the use of a smaller SR is preferred. It delivers high genetic values in both the short and the long term.The SR of 0.1 is a special case as it results in the same parental selection as the baseline method, but it uses an alternative mating design to maximize the genetic variation of the offspring. After 50 breeding cycles, this leads to a 4 percentage points higher mean genetic value of the top-10 individuals in favor of the scoping method. This demonstrates that maximizing the genetic variation increases the genetic value in the long term. The SR of 0.3 yields high genetic values in both the short and the long term. Only eight breeding cycles are needed before the top-10 individuals outperform the baseline method. Over those eight breeding cycles, the difference in genetic value between the baseline method and the scoping method are negligible. After 12 breeding cycles, the mean genetic value of the population surpasses that of the baseline method. Ultimately, after 50 breeding cycles, the scoping method with an SR of 0.3 yields a mean genetic value of 0.71 over the top-10 individuals, a 15 percentage points increase compared with the baseline method.c were tested and the best results for The population merit method preserves the genetic variance by reducing the average genetic relationship of the parental population, leading to a higher genetic gain in the long term compared with the baseline method see . DespiteThe MVT method combines the average genetic relationship and the average inbreeding coefficient to maximize the genetic variation of the breeding population. This method was used to compare the mating design of the scoping method with the MVT method by using the same pre-selected population to select the thod see . Using aThe mean genetic value of the breeding population, mean genetic value of the top-10 individuals and the maximum reachable genetic value of all the proposed methods are reported in Table S1, Table S2 and Table S3, respectively.Nowadays, the use of truncation selection is still popular among breeders, despite the fact that fixation of unfavorable QTL alleles associated with this selection method has been reported . By seleconsistently preserves the genetic variation in the breeding population for as long as possible and thus avoids a premature convergence of the genetic value.Truncation selection causes the loss of several favorable and unfavorable QTL alleles, reducing the genetic variation of the breeding population and causing a premature convergence of the genetic value to a local optimum. Reintroducing new semi-wild species can temporally increase the genetic variation. However, those semi-wild species need several cycles of pre-breeding making this approach less cost and time efficient. The scoping method The scoping method does not only preserve the genetic variation in the breeding population but also in the TP, leading to an improved prediction accuracy see  and 5  leads to higher genetic values in the long term and only a slightly lower genetic value in the short term.


Culicoides (Diptera: Ceratopogonidae). Culicoides dispersal is known to be stratified, i.e. due to a combination of dispersal processes occurring actively at short distances and passively or semi-actively at long distances, allowing individuals to jump hundreds of kilometers.In the last two decades, recurrent epizootics of bluetongue virus and Schmallenberg virus have been reported in the western Palearctic region. These viruses affect domestic cattle, sheep, goats and wild ruminants and are transmitted by native hematophagous midges of the genus Culicoides obsoletus, an abundant and widespread vector species in Europe, using an innovative framework integrating spatial, population genetics and statistical approaches. A total of 348 individuals were sampled in 46 sites in France and were genotyped using 13 newly designed microsatellite markers.Here, we aim to identify the environmental factors that promote or limit gene flow of C. obsoletus across the country. Using three complementary inter-individual genetic distances, we did not detect any significant isolation by distance, but did detect significant anisotropic isolation by distance on a north-south axis. We employed a multiple regression on distance matrices approach to investigate the correlation between genetic and environmental distances. Among all the environmental factors that were tested, only cattle density seems to have an impact on C. obsoletus gene flow.We found low genetic differentiation and a weak population structure for C. obsoletus over land found in the present study calls for a re-evaluation of the impact of Culicoides on virus dispersal, and highlights the urgent need to better integrate molecular, spatial and statistical information to guide vector-borne disease control.The high dispersal capacity of  Culicoides dispersal is described as stratified, due to a combination of dispersal processes occurring actively at short distances, and passively or semi-actively at long distances  curve. The clustering resulting from the Bayesian inference was transposed into percentages of assignment of each individual to the K inferred clusters and plotted on a map.In order to determine the most likely number of genetic clusters (n 2.3.4)  and GENEn 2.3.4) . The algucturing . We perfplatform . This ∆K K ranging from 1 to 10. The analysis was based on 1,000,000 MCMC iterations with a thinning of 1000, maximum rate of the Poisson process fixed to 100, maximum number of nuclei in the Poisson-Voronoi tessellation fixed to 300 and a burn-in of 100. We used the R package graphics to produce a distribution map of genetic structure resulting from STRUCTURE and GENELAND analyses.GENELAND also uses a Bayesian algorithm to infer population genetic clusters while taking into account the spatial position of individuals, making it a spatially explicit clustering method. The most probable number of clusters was also determined by running the algorithm withaR),  indicates that the considered environmental raster was treated as a conductance factor for the computation of environmental distances with circuit theory. [R] indicates that the considered environmental raster was treated as a resistance factor for the computation of environmental distances with circuit theory. Q Difference between environmental multiple regression on distance matrices (MRDM) R2 and null raster MRDM R2. The results for K = 10 are not shown as they were non-significant.Additional file 13: Figure S7. Bar plots of population genetic structure results by clustering analyses performed by STRUCTURE for K = 2 and K = 4. A specific color has been assigned to each inferred genetic cluster.


The authors wish to add the following correction to their paper published in the International Journal of Environmental Research and Public Health . Europ. Plan. Stud.2019.”, should be changed to “Falco, S.D. Are smart cities global cities? A European perspective. Europ. Plan. Stud.2019, 27, 759–783.”.The 16th reference, where the original expression is “Falco, S.D.; Studies, E.P.; Cooke, P. Are smart cities global cities? A European perspective. We apologize for any inconvenience caused to readers by this error.


Reindeer herding is the most important agricultural sector of the Russian Far North, representing the local genetic resources that compose original genetic wealth for the indigenous Arctic ethnic groups, which has maintained their life in harsh conditions of the area for many years. Conservation about and further rational use of such resources are very difficult without taking into account genetic diversity. Here, for the first time, the current genetic composition of the four officially recognized reindeer breeds and their ecotypes inhabiting the area from the Kola Peninsula in the west to the Chukotka region in the east are described using a single-nucleotide polymorphism (SNP) array. Our findings reveal the genetic uniqueness of each breed, formed by the consequences of ecological processes, internal gene flow, breeding practices, and geographical features. The obtained results will assist the ongoing breeding policy to develop accurate programs to preserve genetic resources of this essential element of Russia’s Far North ecosystem.To examine the genetic diversity and population structure of domestic reindeer, using the BovineHD BeadChip, we genotyped reindeer individuals belonging to the Nenets breed of the five main breeding regions, the Even breed of the Republic of Sakha, the Evenk breed of the Krasnoyarsk and Yakutia regions, and the Chukotka breed of the Chukotka region and its within-breed ecotype, namely, the Chukotka–Khargin, which is bred in Yakutia. The Chukotka reindeer was shown to have the lowest genetic diversity in terms of the allelic richness and heterozygosity indicators. The principal component analysis (PCA) results are consistent with the neighbor-net tree topology, dividing the reindeer into groups according to their habitat location and origin of the breed. Admixture analysis indicated a genetic structuring of two groups of Chukotka origin, the Even breed and most of the geographical groups of the Nenets breed, with the exception of the Murmansk reindeer, the gene pool of which was comprised of the Nenets and apparently the native Sami reindeer. The presence of a genetic component of the Nenets breed in some reindeer inhabiting the Krasnoyarsk region was detected. Our results provide a deeper insight into the current intra-breeding reindeer genetic diversity, which is an important requirement for future reindeer herding strategies and for animal adaptation to environmental changes. Rangifer tarandus L. 1758) is an ungulate that inhabits the whole circumpolar area of the northern hemisphere, and it is the last animal to be domesticated by humans [Reindeer , the Nenets Autonomous district and the Arkhangelsk region , the Komi Republic , Yamalo-Nenets Autonomous district , the Sakha Republic  the Even , the Sakha and Dolgans (mainly tundra) with the Evenk, Even, and Khargin reindeer), the Chukotka region , and the Koryak Autonomous district  .Despite the widespread occurrence of the domestic reindeer in the regions of the Russian Far North, the population census size over the last few decades has decreased. The first accurate registration of the reindeer population was carried out in 1926–1927, with the number of heads being 2,202,700, which then declined with collectivization to 1.4 million, stabilized after World War II, and later climbed back to very high levels of more than 2.1 million during the three sovkhoz decades 1961–1993) ,15. The  ,15. TheThe negative effects of the domestic reindeer decline might have reflected on processes such as genetic drift, gene flow, and natural selection, which, in turn, affect the distribution of the genetic diversity and structuring across a species range . AccordiRangifer tarandus genome have occurred [Rangifer tarandus—assembly RanTarSib_v1_BIUU) [Recent improvements in the speed, cost, and accuracy of next-generation sequencing have contributed to an obtainment of new information about the whole genome of most domestic animals, and have led to the widespread use of single-nucleotide polymorphism (SNP) markers as a powerful tool for addressing a great number of genetic tasks ,22. The occurred ,26,27. Toccurred  and the v1_BIUU) , has ledDespite the abundance of scientific work on the genetic biodiversity of the Cervidae family members through commercial SNP genotyping arrays ,30,31,32The erosion of domestic animal diversity due to natural causes and creative human activity is of serious concern if current production levels are to be sustained and the changing demands of future markets are to be addressed . Thus, tHerein, using genome-wide SNPs generated from the BovineHD BeadChip, we aimed to address the primary issue: What is the current genetic diversity and structure of the four officially recognized breeds and their ecotypes inhabiting the reindeer herding regions, from the Kola Peninsula in the west to the Chukotka region in the east. We also aimed to answer a secondary question: Are the breed ecotypes differentiated into groups according to their habitats? The obtained results will assist the ongoing breeding policy to develop accurate programs to preserve genetic resources of this essential element of Russia’s Far North ecosystem.The principles of laboratory animal care were followed, and all procedures were conducted according to the ethical guidelines of the L.K. Ernst Federal Science Center for Animal Husbandry. The protocol was approved by the Commission on the Ethics of Animal Experiments of the L.K. Ernst Federal Science Center for Animal Husbandry (Protocol Number: 2020/2). Biomaterials from the genetic resource collection of the L.K. Ernst Federal Science Center for Animal Husbandry, supported by the Ministry of Science and Higher Education of the Russian Federation, were used in this study. The tissue samples of domestic reindeer were collected by trained personnel under strict veterinary rules. The muscle tissue samples of wild reindeer were collected during scientific expeditions after obtaining collection permits granted by the Department of Hunting of the Republic of Sakha and the Taymyr Dolgano-Nenetsky District, in compliance with the Russian Federation Law No. 209-FZ of 24 July 2009.n = 31) and Yamalo-Nenets  Autonomous districts, the Komi Republic , and the Arkhangelsk  regions; the Even breed of the Republic of Sakha (Yakutia) ; the Evenk breed of the Krasnoyarsk region ; and the Chukotka breed of the Chukotka Autonomous district  and its within-breed ecotype—the Chukotka–Khargin , which is bred in the Republic of Sakha (Yakutia). The biomaterial was picked during the corral work on the herd throughout 2018–2019. Additionally, our data set was combined with SNP genotypes of reindeer that were obtained during our previous study [n = 33) and the Murmansk region  and the Evenk (EVK_YAK n = 12), the Even , and the Chukotka–Khargin breeds  from the Republic of Sakha (Yakutia). All studied reindeer groups are displayed in In total, 113 reindeer individuals representing four breeds were chosen for the current study, including the Nenets breed from the Nenets  and the Northern Yakutia . The coordinate range of the covered area in Taymyr varied from 70 to 73° N and from 91 to 99° E; in Yakutia, it ranged from 64 to 69° N and from 113 to 117° E. Collections of the wild samples were taken from 2017 to 2019 during scientific expeditions.In addition, considering the peculiarity of reindeer species, namely, the coexistence of domestic and wild forms, and to find out a possible genetic contribution toward the domestic reindeer population structure, the wild individuals were included in the analyses as an outgroup. The muscle tissue samples were taken from the wild reindeer inhabiting the Western Taymyr  was plotted using the R packages maps and mapdata .Genomic DNA was extracted with Nexttec columns  following the manufacturer’s instructions. The DNA samples were quantified using a method of visualization in bands by 1% agarose gel electrophoresis. The concentration of the dsDNA was measured on a Qubit 3.0 fluorimeter (Thermo Fisher Scientific (formerly Life Technologies), Wilmington, DE, USA). DNA purity was determined by evaluating the absorption ratio of A260/A280 on a NanoDrop2000 spectrophotometer .2 > 0.05  were excluded from further analyses. The final data set was accomplished by removing the individuals with more than 10% missing genotypes (--mind 0.1). As a result, 7968 SNPs passed quality control filtering, while 641,698 variants were removed due to missing genotype data (--geno 0.1) and 85,627 variants were removed due to a minor allele threshold (--maf 0.01). After LD pruning, 665 SNPs were removed, and we obtained a final set of SNPs containing 7303 markers.DNA samples were genotyped using the Illumina BovineHD Genotyping BeadChip. The subsequent analysis first involved a filtering step in which the GenCall (GC) and GenTrain (GT) scores were used. A cut-off of 0.5 for both the GC and GT scores was applied to determine the valid genotypes for each SNP . SNPs loHO), the unbiased expected heterozygosity (UHE) [FIS) based on the unbiased expected heterozygosity, and the rarefied allelic richness (AR) were computed with the R package “diveRsity” [To measure the level of genetic diversity in each reindeer breed, the observed heterozygosity (ty (UHE) , the inbveRsity” .To discover the genetic structure of the studied reindeer breeds, we implemented a principal component analysis (PCA) in PLINK v1.90, visualized with the R package “ggplot2” .ADMIXTURE v1.23 software  was usedFST measures were calculated and the computing process was completed in the R package diveRsity. A pairwise distance matrix of FST measures was applied for construction of a consensus neighbor-net tree through the SplitsTree 4.14.5 software [To describe the differentiation of the reindeer breads, pairwise software .p-values were calculated with jackknife blocks of 100 SNPs (-k 100). We found four migration edges as the most likely number of migration events based on the log-likelihood of the event (p < 0.05).TreeMix 1.12 package software  was usedAll input files were created in R version 3.3.2 .AR), as well as the observed (HO) and unbiased expected UHE heterozygosity, which are commonly measured parameters to check within-breed diversity [Genetic diversity is shaped by past population processes and affects the sustainability of species and populations in the future . The meaiversity , were caFIS value was observed in all groups, ranging from 0.012 for CHU and EVK_YAK to 0.027 for EVN.Allelic diversity, as measured by allelic richness, ranged from 1.573 to 1.666, with CHU showing the lowest value and EVK_YAK the highest. Regarding the heterozygosity indices, six groups were characterized by a value of observed heterozygosity above 0.180, with the exception of CHU, CHUKH, NEN_YMLN, and NEN_ARKH, in which the value of the indicator was below 0.179. For expected heterozygosity (unbiased to sample size), seven groups had a high comparable value, ranging from 0.183 for NEN_YMLN to 0.192 for EVK_YAK. A lower level of the indicator was detected for CHU (0.176), CHUKH (0.179), and NEN_ARKH (0.179). A slightly positive FST) showed low variable FST values, ranging from 0.003 to 0.096 , NEN_NAO/NEN_YMLN (0.004), and NEN_KOMI/NEN_NAO (0.005). The next lowest level of differentiation was detected between the Chukotka breed and its ecotype from Yakutia region, CHU/CHUKH (0.01), and between two breeds inhabiting the Yakutia region: EVK_YAK/EVN (0.017). The highest genetic differentiation of 0.096 was observed between the Archangelsk population of the Nenets breed and a group from the Chukotka region (NEN_ARKH/CHU). Notably, a practically equal low connectivity (varied from 0.08 to 0.096) was revealed between the four groups of the Nenets breed and the reindeer of Chukotka origin raised in both the Chukotka and Yakutia regions.The lowest FST values, more precise genetic pathways of the connection between the studied reindeer breeds were reflected in the neighbor-net tree  with the joining of the EVK_KRA and NEN_MUR branches. Additionally, the NEN_ARKH reindeer were fractionally positioned outside of the Nenets clade. Regarding the second cluster, three subclusters were formed, composing a branch of two breeds raised in the Yakutia region (EVK_YAK and EVN), a group of the wild populations (WLD_TMR and WLD_YAK), and the reindeer of Chukotka origin (CHUKH and CHU), which occupied the opposite location on the tree.We estimated the most likely evolutionary history of each group of the domestic reindeer populations by calculating the levels of genetic drift at a set of 7303 SNPs. To this end, the TreeMix program was used, and its topology with four migration edges is shown in The most likely migration edge indicated the existence of a gene exchange event from WLD_YAK to the group of Chukotka origin. The second and the third migration edges with a milder migration event denoted a gene flow from WLD_TMR to NEN_MUR and from EVK_YAK to EVK_KRA. The fourth migration edge with the smallest weight indicated a gene flow between the groups of Chukotka origin to the Evenk breed of Yakutia.PCA and the model-based approach implemented in Admixture software were used to infer the population structure of the studied reindeer groups. The PCA results  indicateThe reindeer from the Murmansk region formed an independent cluster, while the remaining individuals of the Nenets breed displayed a convergent pattern of their genetic composition, forming a slightly overlapping cluster with EVK_KRA. Additionally, the analysis divided the remaining groups into three clusters: the Even and the Evenk breeds inhabiting the Yakutia region formed one cluster, while the wild populations formed another cluster, and the Chukotka and the Chukotka–Khargin groups formed the last cluster. The contributions of the total genetic variability, accounted by the first, second, and third components, were 7.78%, 5.31%, and 2.94%, respectively. All individuals of the Nenets population, as well as the Evenk reindeer from the Krasnoyarsk region, were distributed along the first principal component, which distinguished them from the remaining reindeer. The second principal component highlighted the divergence of the domestic and wild populations with the assignment of the Murmansk individuals to the wild relatives. Further, the third principal component split the reindeer of Chukotka origin and the Nenets breed’s representatives from the Even and the Evenk breeds. Meanwhile, the reindeer of the wild populations were placed on the C3 axis.According to a cross-validation procedure, the best predictive accuracy of the model was detected for K = 3  and for K = 2 (CV, 0.358; At K = 2, two main genetic pools were revealed; the first one was formed by the three breeds inhabiting the Yakutia region, the Chukotka breed, and the wild populations, whereas the second pool comprised the Nenets regional populations and the Evenk breed from the Krasnoyarsk region. It is worth noting that EVN and EVK_YAK had a high proportion of admixture in their individuals from the second genetic pool, the independent ancestry of which became evident at K = 4. Interestingly, the Evenk reindeer from Yakutia did not form an independent cluster and, moreover, demonstrated a slight admixed ancestry with the same breed raised in the neighboring Krasnoyarsk region at K = 5. The admixture origin of the Krasnoyarsk reindeer, in return, was maintained until K = 5, at which they showed an independent ancestry, albeit with the genetic component of the remainder of the Nenets breed in some individuals. Meanwhile, at K = 3, a proportion of admixture of the wild gene component was detected in the individuals from the Murmansk region, which constituted a complete separate group at K = 6. The Chukotka reindeer of the two breeding regions maintained a common genetic background from K = 2 to higher values.In comparison to other livestock, reindeer herding is still the most important agricultural sector of the Russian Far North. Despite gradually replacing local breeds with high-yield culture ones, in the vast majority of geographical places, reindeer is one of the few species of domesticated animals that has acquired adaptive traits to survive in the extreme natural conditions of the Arctic. The conservation and further sustainable use of such resources are very difficult without considering genetic diversity. In this regard, the main aim driving our study was the examination of the current genetic composition of four officially recognized breeds, as well as their ecotypes, inhabiting the four federal districts of the Russian Far North. Additionally, we questioned the genetic divergence of the breeds’ ecotypes into groups according to their habitats due to breeding practices and geographical features.Rangifer was reported in 2018 [To address the above challenges, in the current study, the reindeer individuals were genotyped with the Illumina BovineHD Genotyping BeadChip, and the population genetic indices were calculated based on 7303 SNPs. The first utilization of the BovineHD BeadChip in  in 2018 . The stu in 2018 . Despite in 2018 , as wellKnowledge of the level and distribution of genetic diversity is the basis for a species’ survival, development, and evolution, and for improvement programs in animal production . One of The results of the present study showed that the Evenk and Even breeds raised on the farms of the Yakutia region exceeded their domestic relatives in this indicator . AccordiIn this study, we found that the Even appeared to be the most genetically consolidated breed. The Evenk reindeer of the Yakutia region had admixed patterns with the EVK_KRA and the EVN genetic components, caused both by the common ancestry with the Evenk conspecifics of the Krasnoyarsk region and the gene flow between the Even and Evenk herds being raised in the same region.One more group of reindeer among the studied domestic breeds, which also belongs to the same reindeer husbandry type, is the Evenk of the Krasnoyarsk region . This grAR, HO, and UHE (FST values (In our study, the largest sample set was presented by the populations of the Nenets breed, due to the fact that this is the largest breed by both numbers and pasture territory, and due to the several phenotypes within the breed . The val and UHE . FurtherT values , while tT values . MeanwhiT values . AdditioThe results of the current study found a genetic homogeny of most geographical groups of reindeer related to the Nenets breed, and thus, the existence of several within-breed ecotypes has not yet been revealed. An exception was detected for Murmansk reindeer, which belong to the Nenets breed, while their gene pool comprises the Nenets and apparently the native Sami reindeer. Moreover, a predominance of the Kola Peninsula reindeer in height at the withers and in live weight of calves at birth over their Nenets relatives was revealed . The genMeanwhile, the reindeer of the Chukotka breed and its Yakut within-breed ecotype, which is called Khargin, had the lowest values for each genetic diversity parameter . We noteThe most likely reason to explain this discovered pattern of similar genetic structure of the groups is the difference of domestication processes of the Chukotka breed, with its within-breed ecotype, from the remaining breeds. Reindeer husbandry of the Chukchi originated later than among the Sami and Nenets people, as evidenced by the lack of tame reindeer. It is generally admitted that reindeer husbandry entered Chukotka only a few centuries ago and spread in the local tundra during the 17th–18th centuries . KrushanEvaluating the inbreeding and genetic diversity within a breed is a requisite for sustainable improvement in the long term . In our In the present study, distinctions between the reindeer breeds were found not only in terms of allele and genetic diversity , but in In our study, using the BovineHD BeadChip, we provided current insight into the genetic variability pattern of four officially recognized breeds, as well as their ecotypes, inhabiting the four federal districts of the Russian Far North. Among all of the studied domestic groups, the Evenk and Even breeds raised on the farms of the Yakutia region were the most genetically variable, while the Chukotka breed and its Yakut within-breed ecotype, Khargin, had the lowest values for each genetic diversity parameter. For this breed, the turnover and conservation of genetic diversity can be advised. Regarding the genetic structure, we found that the reindeer breeds, in spite of their geographical habitats, maintained their specific genetic components. Additionally, based on our findings, we assumed that the genetic composition of the studied domestic reindeer groups is related to the features of their formation in the context of the ethnic history of the small peoples of the Far North.Considering the assumption that the future genetic progress of the breeds depends mainly on the availability of sufficient genetic variation, we believed that the obtained results in this study will assist both the ongoing breeding policy and the development of a strategy for the conservation of this essential element of the life sustenance and culture of many indigenous and small peoples.


Picea mariana) in relation to climate variables in Alaska. A total of 520 single nucleotide polymorphisms (SNPs) were genotyped for 158 trees sampled from areas of contrasting climate regimes. We used multivariate and univariate genotype‐by‐environment approaches along with available gene annotations to investigate the relationship between climate and genetic variation among sampled populations. Nine SNPs were identified as having a significant association with climate, of which five were related to drought stress response. Outlier SNPs with respect to the overall environment were significantly overrepresented for several biological functions relevant for coping with variable hydric regimes, including osmotic stress response. This genomic imprint is consistent with local adaptation of black spruce to drought stress. These results suggest that natural selection acting on standing variation prompts local adaptation in forest stands facing water limitation. Improved understanding of possible adaptive responses could inform our projections about future forest dynamics and help prioritize populations that harbor valuable genetic diversity for conservation.Predicted increases in drought and heat stress will likely induce shifts in species bioclimatic envelopes. Genetic variants adapted to water limitation may prove pivotal for species response under scenarios of increasing drought. In this study, we aimed to explore this hypothesis by investigating genetic variation in 16 populations of black spruce ( Genetic variants adapted to water limitation may prove pivotal for species response under scenarios of increasing drought. In this study, we aimed to explore this hypothesis by investigating genetic variation in Alaskan populations of black spruce in relation to local climate. Our results suggest that natural selection acting on standing variation prompts local adaptation in forest stands facing water limitation. Of the remaining SNPs, 96 were removed based on the low call rate, resulting in a final dataset of 520 polymorphic SNPs. According to Pavy et al.  of summer heat‐to‐moisture index (SHM), where lower SHM values indicate cooler, wetter conditions and higher values indicate hotter, drier summer conditions , each of which was run 10 times. The optimal K value was evaluated based on ∆K implemented in STRUCTURE HARVESTER  using the pegas package in R version 3.5.1  were highly correlated (see results), subsequent analyses relied on the initial STRUCTURE analysis  to account for the neutral genetic structure of the sampled black spruce populations  from the baseline Climate WNA dataset  from STRUCTURE analysis. Using the R package vegan, we conducted the pRDA  from the center as putative loci under selection  to identify SNP loci associated with the environmental variables in our final dataset as the multivariate analysis for detecting probable adaptive variants in this study  was determined by comparing results from the STRUCTURE analysis  with the spare non‐negative matrix factorization (smnf) function available in LEA that estimates ancestry coefficients with smnf . A model was run for each of the eight environmental variables. Loci statistically associated with a climate variable were then compared with the results from our partial RDA. Those SNPs jointly flagged by both approaches were assumed as candidate loci, putatively under selection by climate  were used to identify black spruce allele–environment correlations with neutral population structure modeled as "latent factors" . We acknowledge that our approach to annotating adaptive SNPs and making additional functional interpretations assumes that similarity between P. mariana and P. glauca genomes, and similarity between predicted P. glauca Gene Ontology (GO) terms and Arabidopsis thaliana TAIR orthologues, is sufficient to reflect possible gene functions in P. mariana. As a result, we cautiously interpret these results in view of these limiting assumptions.Lastly, we used available Gene Ontology (GO) annotations to explore possible functional implications of the genes associated with climate across the sampled black spruce populations. TAIR  indicated that 201 SNPs did not violate the assumptions of HWE. Running STRUCTURE using this subset yielded nearly identical results; the matrices of ancestry coefficients  from the two STRUCTURE analyses were strongly correlated (Pearson's r = .94). We used the Q‐values from the analysis of all SNPs to remove the effects of neutral genetic structure in the pRDA.STRUCTURE analysis of the 520 polymorphic SNPs in our final dataset supported two distinct genetic clusters  and not the focal species, and we were mainly concerned with identifying environmental–climatic factors driving adaptive evolution in P. mariana. Therefore, we present a cautious interpretation of our functional results, considering these to represent preliminary findings until a full P. mariana reference genome becomes available. Gene annotations of the nine candidate SNPs shared between results from multivariate and univariate GEA approaches revealed that five of these SNPs were related to drought stress response pathways  also found that genetic regions related to cinnamate‐4‐hydroxylase were under selection in response to drought  found that genetic regions related to glutathione peroxidase were upregulated in response to experimental drought ; data curation (lead); formal analysis (lead); methodology (lead); writing – original draft (lead); writing – review and editing (lead). Guillaume de Lafontaine: Conceptualization (supporting); data curation (supporting); formal analysis (supporting); methodology (supporting); writing – original draft (supporting); writing – review and editing (supporting). Feng Sheng Hu: Conceptualization (supporting); funding acquisition (lead); Resources (lead); writing – original draft (supporting); writing – review and editing (supporting).Appendix S1Click here for additional data file.