Sheep in Ethiopia are adapted to a wide range of environments, including extreme habitats. Elucidating their genetic diversity is critical for improving breeding strategies and mapping quantitative trait loci associated with productivity. To this end, the present study investigated the genetic diversity and population structure of five Ethiopian sheep populations exhibiting distinct phenotypes and sampled from distinct production environments, including arid lowlands and highlands. To investigate the genetic relationships in greater detail and infer population structure of Ethiopian sheep breeds at the continental and global levels, we analyzed genotypic data of selected sheep breeds from the Ovine SNP50K HapMap dataset. All Ethiopian sheep samples were genotyped with Ovine Infinium HD SNP BeadChip (600K). Mean genetic diversity ranged from 0.29 in Arsi-Bale to 0.32 in Menz sheep, while estimates of genetic differentiation among populations ranged from 0.02 to 0.07, indicating low to moderate differentiation. An analysis of molecular variance revealed that 94.62 and 5.38% of the genetic variation was attributable to differences within and among populations, respectively. Our population structure analysis revealed clustering of five Ethiopian sheep populations according to tail phenotype and geographic origin—i.e., short fat-tailed , long fat-tailed , and fat-rumped , with clear evidence of admixture between long fat-tailed populations. North African sheep breeds showed higher levels of within-breed diversity, but were less differentiated than breeds from Eastern and Southern Africa. When African breeds were grouped according to geographic origin , statistically significant differences were detected among groups (regions). A comparison of population structure between Ethiopian and global sheep breeds showed that fat-tailed breeds from Eastern and Southern Africa clustered together, suggesting that these breeds were introduced to the African continent via the Horn and migrated further south. In the Horn of Africa and especially in Ethiopia where the economy is predominantly agriculture-based, sheep and their products play a critical role in the livelihood of millions of farmers and pastoralists . Sheep sGiven its proximity to the Arabian Peninsula, Ethiopia is considered as a genetic corridor for the introduction of livestock species including sheep to the African continent . ExtensiCharacterizing genetic diversity is a key aspect of developing sustainable breed improvement strategies  and undeThe present study provides the first analysis of high density (∼600K) ovine SNPs in Ethiopian sheep breeds. We sampled and genotyped five Ethiopian sheep populations adapted to diverse agro-ecologies using the Infinium HD SNP BeadChip (600K). A detailed understanding of the genetic landscape of national populations requires sampling of representative breeds from wider geographic regions, particularly from a center of domestication and along migration routes . To estaNasal samples were collected using Performagene LIVESTOCK’s nasal swab DNA collection kit  from a total of 72 animals representing five Ethiopian sheep populations: Arsi-Bale, Horro, Menz, Adilo, and Blackhead Somali. Three of these  are long fat-tailed hairy sheep; Menz is a short fat-tailed coarse-wool sheep; and Blackhead Somali belong to the fat-rumped group . Both feTable 1.Blackhead Somali sheep  exist at low altitudes (500–1000 m above sea level [a.s.l.]) and are well adapted to arid and semi-arid environments characterized by high ambient temperature, low precipitation (200–400 mm), and recurrent drought . The bre1). We also included Moroccan sheep data generated by the NextGen Consortium2. Details regarding sample sizes, breeds, and geographic origins are summarized in Table 2.To compare the genetic relationship between sheep breeds in Ethiopia and those on other continents and investigate historical patterns of admixture, we also used genotype data of 228 animals representing 12 breeds from North Africa, Middle East, South Africa, Europe, and Asia from the Ovine HapMap project  by GeneSeek/Neogen . Among the 606,006 SNPs, 577,401 were autosomal, 1291 were unmapped to any ovine chromosome (OAR), and 27,314 were located on the X chromosome.Autosomal SNPs with call rates <90% and minor allele frequency (MAF) <0.01 were filtered out, leaving 497,294 SNPs with average and median gaps of 4.92 and 3.58 kb, respectively. Additionally, 11 samples with call rates ≤ 85% were excluded from further analysis. To test for potential effects of ascertainment bias on diversity index estimates, 497,294 SNPs were subjected to linkage disequilibrium (LD) pruning using the parameter (50 5 0.20), yielding 80,602 SNPs.3). A total of 41,752 SNPs overlapping between the two platforms were filtered according to quality control criteria; SNPs with call rates <90% and MAF <0.01 were removed, leaving 40,770 SNPs for subsequent analyses. A total of 6163 SNPs remained for population structure analysis after 40,770 SNPs in each population were pruned based on LD using the parameter (50 5 0.80).Genotypic data for the 600K and 50K platforms were merged using SNP and Variation Suite v.8.5.0  were estimated by SNPs for each of the five Ethiopian sheep populations using SNP and Variation Suite v.8.5.0. Alleles were categorized into different bins based on their frequency: fixed alleles (MAF = 0.00), rare alleles (>0.00–<0.05), intermediate alleles (≥0.05–<0.10) and common alleles (≥0.10 and ≤0.5). Diversity indices were estimated from three datasets: (i) 497,294 SNPs that passed the quality control threshold of MAF ≥ 0.01 and call rate ≥ 90%; and (ii) 80,602 SNPs that remained after pruning 497,294 based on LD using the parameter (50 5 0.20) in SNP and Variation Suite v.8.5.0; and (iii) 40,770 SNPs common to 600K and 50K platforms.To estimate within-population genetic diversity, we calculated observed heterozygosity (HO), expected heterozygosity (HE), and inbreeding coefficients for the three datasets using PLINK . Animal FST)   and ReynFST)  between FST) . The sigFST) .K-value. The STRUCTURE output was analyzed in HARVESTER  for New Zealand sheep breeds based on an analysis of 517,902 SNPs and those reported for Corriedale and Merino sheep (0.27), but were higher than the value observed in Creole sheep .Figure 1. The percentage of fixed SNPs (MAF = 0.00) varied from 16.60% in Horro to 24.60% in Arsi-Bale sheep, with an overall mean of 8.10% across populations, which is lower than that reported for Creole (27%) but higher than those in Merino (3%) and Corriedale (4%) breeds  breeds . In tota) breeds . The obsSupplementary Table S1. The highest number of breed-specific SNPs  was detected in the Menz sheep with frequency ranging from 0.04 to 0.50 and mean of 0.15. The lowest number of breed-specific SNPs (14870) was observed in the Arsi-Bale sheep with frequency ranging from 0.062 to 0.50 and mean of 0.09. Breed-specific SNPs have been detected and used for breed assignment and product traceability in several livestock animals including pigs , with the largest number observed in Adilo  followed by Blackhead Somali  sheep. Deviation from HWE is due to inbreeding or genetic substructures within populations   loci in the five Ethiopian sheep populations deviated significantly from HWE ( effect) .Table 2). HO over all loci  varied from 0.30 in Arsi-Bale, Horro, and Adilo sheep to 0.33 in Menz. The average gene diversity or HE across the five populations was 0.30 and ranged from 0.29  to 0.32 (Menz). In all populations, HO was higher than or equal to HE, except in Horro sheep. The levels of within-breed genetic variation for Ethiopian sheep populations were within the range reported for New Zealand sheep breeds (0.249–0.383) analyzed using a 600K SNP chip . Removing SNPs in high LD minimizes the effects of ascertainment bias and reduces heterozygosity (F) were negative in all populations, except in Horro sheep (F = 0.00–0.02). Overall inbreeding in all populations was estimated as 0.06. The most inbred individual was an Adilo sheep (F = 0.30), whereas the most outbred individual was a Blackhead Somali sheep (F = –0.33).Sample size and the population in which SNPs are detected affect population parameter estimates . Variabizygosity . In bothP< 0.0001) and 94.62% among and within populations, respectively. The large within-population variation observed in Ethiopian indigenous sheep populations can be exploited through appropriate breeding strategies to improve productivity. When an analysis was performed for sheep populations grouped based on tail phenotype , among-groups variance was 3.33, with 93.82% within individuals (Table 3). Further analysis of populations grouped according to ecological distributions (high- vs. lowland) revealed that 1.28% of the variance was among groups, 4.70% (P< 0.0001) among populations within groups, 1.61% among individuals within populations, and 92.47% within populations.Analysis of molecular variance based on 497,294 autosomal SNPs revealed variations of 5.38% , the estimated among-group variation was 0.42% , which iFST values and Reynolds’ genetic distances among the five Ethiopian sheep populations were estimated using 497,294 SNPs (Table 4). The overall FST value among the five populations was low (0.053) but significant (P< 0.0001). FST for all pairs of populations also differed significantly from zero (P< 0.001) and ranged from 0.02 to 0.07, with the closest pairwise value (0.02) observed between Arsi-Bale and Horro sheep. Menz sheep were more distantly related to other Ethiopian sheep populations (FST = 0.05–0.07).FST among Ethiopian sheep populations was higher than the values reported for Ethiopian cattle (0.01) and goats (0.0245) (The average (0.0245) , but sim(0.0245)  and high(0.0245) ], Algeri(0.0245) ], and Tu(0.0245) ] sheep bFigure 2). Menz sheep formed a tight cluster, whereas outliers were detected in the other populations. The unique genetic background of Menz sheep was corroborated by the STRUCTURE analysis results. At K = 2, the three-long fat-tailed sheep populations formed a single group while Menz sheep formed an independent cluster with some admixture from the other populations. Blackhead Somali sheep shared the genetic background of the long fat-tailed populations . At K = 3, Blackhead Somali sheep tended to segregate, yet shared about 35% of its genome with long fat-tailed populations. The PCA and STRUCTURE analysis revealed clear signatures of admixture among Ethiopian sheep populations—particularly among long-fat tailed breeds—as well as genetic introgression from short-fat tailed Menz into other populations.To illustrate relationships within individuals and among Ethiopian sheep populations, PCA was performed using 497,294 SNPs. PC1 and PC2 accounted for 26.71 and 25.20%, of the variation, respectively, and clustered the five sheep populations according to their tail phenotypes: long fat-tailed , short fat-tailed (Menz), and fat-rumped . These clustering patterns corresponded with their geographic distribution. PC1 segregated long-fat-tailed and fat-rumped populations from the short fat-tailed Menz sheep, whereas PC2 separated lowland fat-rumped Blackhead Somali sheep from highland fat-tailed populations  and are kept for meat and coarse wool production , and areThe low genetic differentiation between the two-long fat-tailed populations  was further supported by our population STRUCTURE analysis results. Arsi-Bale and Horro sheep populations are predominantly maintained by the Ethiopian Oromo ethnic group. In addition to geographic isolation, ethnic, cultural, and religious differences may act as barriers to gene flow that shape population genetic structure . The chaTable 2). However, Ethiopian sheep populations show slightly lower levels of genetic diversity than the presumed ancestral breeds of the Near East  and northern Africa (HE = 0.35–0.37). Breeds from or close to domestication centers are expected to retain higher allelic diversity than those that migrated farther away  and highly polymorphic (MAF > 0.30) SNPs accounted for 92 and 37% of SNPs in Ethiopian sheep populations, respectively. These values were lower than those observed for Australian Merino , but higher than those for Dorset Horn . Using the OvineSNP50 chip, highly polymorphic (MAF > 0.30) SNPs accounted for 50% of the total in Merino and Corriedale sheep and for 36% of the total in Creole sheep . The relher away . The higher away .FST  and Reynolds’ genetic distances (Supplementary Table S4) were calculated between the 18 sheep breeds/populations. The lowest differentiation was in Ethiopian populations  and in North African breeds . Pairwise genetic differentiation comparisons revealed that the highest FST value (FST = 0.33) was obtained between the Dorset Horn and Namaqua Afrikaner. Within African sheep breeds, the highest differentiation (mean of 0.21) was observed between Ethiopian and Namaqua Afrikaner breeds. The low within-breed genetic diversity in Namaqua Afrikaner and high genetic differentiation between this breed and other East African sheep populations was likely due to genetic drift, which is consistent with the significantly smaller population size of Namaqua Afrikaner (FST = 0.08–0.09), while a higher value detected between East African and Middle Eastern breeds (FST = 0.12). It is well documented that the Nile River Valley served as a genetic corridor for human and livestock gene flow between the northern and southern parts of the continent across sub-Saharan Africa (Pairwise frikaner . Ethiopin Africa .P< 0.0001) of the variance was among groups, 10.64% among populations within groupings, and 85.69% within populations. The FST value was 0.1431 (P< 0.0001), which showed that 14.31% of the total genetic variation was due to population differences. The variation observed among the geographic regions in this study was lower than the reported value of 5.8% (P = 0.01) of the variation was among groups and 4.20% among populations within groups. The FST value was 0.1243, which revealed 12.43% of the total genetic difference was attributed to population differences, and the remaining 87.57% accounted by variation within populations.Analysis of molecular variance for the 18 global populations grouped based according to geographical regions  revealed that 3.68% , with close clustering of breeds or populations within a region. Among Ethiopian sheep, the two highland and fat-tailed sheep  were closely clustered. Despite the observed phenotypic differences, fat-rumped Blackhead Somali sheep were more closely associated with fat-tailed Red Maasai sheep than with fat-tailed Ethiopian sheep populations. These populations are reared under mobile pastoral and agro-pastoral systems, and there is a high chance of inter-population mating in Kenya . Long branches were noted for Namaqua Afrikaner, Dorset Horn and Indian Garole, possibly due to small effective population size, which concurs with previous reports (The Middle Eastern breeds (Afsahri and Awassi) formed another group with Egyptian Barki sheep. In the phylogenetic tree, the Moroccan sheep was positioned in an intermediate position. The Brazilian Creole clustered with the Iberian populations . PC1 accounted 21.14% of the total variation and separated the African breeds, except Moroccan sheep from the Western breeds. Menz and Namaqua Afrikaner were closer to the rest of the East African population but remained as a separate cluster. Eastern and Southern African breeds were separated from the Middle Eastern and North African breeds by PC2. Admixed populations should fall between their two ancestral populations, and the proportion of ancestry inherited from each can be linearly estimated .Principal component analysis was carried out using 40,770 SNPs overlapping between OvineSNP50 and Ovine HD SNPs and the 6163 SNPs left after LD pruning  was also well supported by population STRUCTURE and Neighbor network analyses. We suggest that this could be due to gene flow and similarity of production environments .Genotypic data of 72 animals representing five Ethiopian sheep populations are deposited and available at (Local regulations were observed. This research used Nasal swab DNA collection kits, which does not require injure the animal nor impose pain.ZE and K-SK conceived the study, analyzed the data, and wrote the manuscript. TD provided logistical support for field data collection and facilitated sample export. HD and K-TD revised the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


FIS (inbreeding rate within a population) values indicated, a low level of inbreeding within populations, and the patterns were in concordance with the results of Nei’s genetic distance analysis. The lowest FST (inbreeding rate between populations) values among Korean and Chinese breeds, using a phylogenetic tree, multi-dimensional scaling, and a TreeMix likelihood tree showed Korean breeds are highly related to Chinese breeds. The Korean breeds possessed a unique and large diversity of admixtures compared with other breeds. The highest and lowest effective population sizes were observed in Korean Jindo Black (485) and Korean Donggyeong White (109), respectively. The historical effective population size of all Korean dogs showed declining trend from the past to present. It is important to take immediate action to protect the Korean dog population while conserving their diversity. Furthermore, this study suggests that Korean dogs have unique diversity and are one of the basal lineages of East Asian dogs, originating from China.There are various hypotheses on dog domestication based on archeological and genetic studies. Although many studies have been conducted on the origin of dogs, the existing literature about the ancestry, diversity, and population structure of Korean dogs is sparse. Therefore, this study is focused on the origin, diversity and population structure of Korean dogs. The study sample comprised four major categories, including non-dogs (coyotes and wolves), ancient, modern and Korean dogs. Selected samples were genotyped using an Illumina CanineHD array containing 173,662 single nucleotide polymorphisms. The genome-wide data were filtered using quality control parameters in PLINK 1.9. Only autosomal chromosomes were used for further analysis. The negative off-diagonal variance of the genetic relationship matrix analysis depicted, the variability of samples in each population.  Canis lupus) [Dogs belong to the family Canidae and show high diversity between and among different species. They have diverse feeding habits and advanced social organization. The dog was suggested as the first domesticated animal by archaeological discoveries around the world . Moreoves lupus) , 2, 3, 4There is much interest in determining the ancestry of dogs. Investigating the exact time period for dog domestication will help to clarify wolf and human engagement in the domestication process. It is vital to include Central Asia and other nearby regions, in developing a full picture of early dog history. Since specimens of ancient dogs are unavailable for DNA analysis, some researchers consider village dogs as a reliable sample that resembles ancient dogs .The place of origin of domestic dogs is still inconclusive. There are diverse hypotheses on dog domestication based on various observations. Some literature suggests  that dogGenetic information, models of phylogeographic dissimilarity and higher genetic diversity suggest an East Asian origin for domestic dogs . In contA large number of modern breeds originated from Europe within the past 200 years ,9. AmongKorean Jindo White, Korean Poongsan White, Sapsaree, Korean Donggyeong White and Jeju dogs are believed to be native Korean dogs. A microsatellite locus analysis illustrated that Korean native dogs might have ancestry from the northern part of the East Asia .The Korean Jindo dog is a widely known as a hunting and guarding dog. Further, the Korean Jindo White is believed to have been domesticated in the Stone Age. There is a little difference between male and female Jindo dogs . The standard height of the Jindo dog is ranges from 45 to 53 cm. They have yellow and white coat colors, and the tail is curled upward ,13. The The Poongsan breed is considered to be a hunting dog indigenous to North Korea. However, currently the original pedigree of many Poongsan dogs are raised in South Korea . Its heiGyeongju province is a primary area for breeding the Donggyeong dog in Korea. There are nearly 300 animals known to exist. They are friendly to humans, clean and fast. The height and length of female Donggyeong dogs are 45 and 53 cm while those of the male Donggyeong doga are 49 and 57 cm respectively. No tail or a very small tail is one identifying feature of this dog. Generally, they have four coat types: yellow, white, black, and leopard. The Korean Donggyeong has the longest history; therefore, its genetic structure is a valuable resource with great cultural value .There are few scientific studies on the ancestry of Korean dogs. Therefore, this study investigated the genetic diversity, population structure, and origin of Korean dogs, using three Korean breeds . In addition, we compared Korean breeds with worldwide dog populations (ancient and modern breeds) using genome-wide analysis of single nucleotide polymorphisms (SNPs).In total, 2258 animals were used as a sample for this study. To achieve the major objectives of the study, we selected coyote, wolve, and several breeds analyzed in a previous study , after rThe Border Collie (BDC), Boxer (BOX), Cavalier King Charles Spaniel (CAV), Chinese Crested (CHC),Chihuahua (CHH), Croatian (CRS), English Setter (ENS), English Springer Spaniel (ESS), Great Dane (GRD), Golden Retriever (GRT), German Shepherd (GSD), Maltese (MAL), Miniature Pinscher (MNP), Miniature Schnauzer (MNS), and Newfoundland (NEF) were selected as modern breeds, representing all parts of the world. The sample comprised 1870 modern dog breeds. These breeds emerged during the Victorian era (circa 1830–1900) through controlled breeding practices. Their breeding regime was implemented by humans, and therefore they no longer have a close relationship with wolves . The dogKorean dogs used in this study included 189 individuals from 6 populations (belonging to three breeds), Korean Poongsan White (KPW), Korean Donggyengi White (KDW), Korean Jindo White (KJW), Korean Jindo Black (KJB), Korean Jindo Black and Tan (KJT), and Korean Jindo Brindle (KJD). Moreover, 7 coyotes and 81 wolves were included in the sample.Based on memorandum of understanding (MOU) between the research team and the research and breeding center, veterinarians collected blood samples for the research purposes of this study. All blood samples were obtained in an ethical manner, following guidelines for animal health and welfare. Advance approval was acquired from the Institutional Animal Care and Use Committee of the National Institute of Animal Science, of the Rural Development Administration, of South Korea. Genomic DNA from the Korean dogs was isolated from blood samples using standard methods . SamplesFIS) and between populations (FST) [Diversity and population structure analyses were performed using following algorithms: 1) pairwise fixation indices within populations (ns (FST) ; 2) hetens (FST) ; 3) GRM ns (FST)  and StAMns (FST) . GRM wasns (FST) . The founs (FST)  and depins (FST) . ADMIXTUns (FST)  was usedns (FST)  and depins (FST) .f3 statistical analysis that was introduced [f3 statistic and Z-score were selected as a possible event of population B and C introgression in the population A.An extended analysis of the relationships among dog populations was performed using TreeMix v1.12 . This aptroduced  using thNe). Ne was estimated from the LD value following Sved’s equation [Ne calculation, LD was annotated as r2 to measure the correlation of alleles at two loci [Ne. The historical Ne values were plotted using R [Demographic history of the dog population was reflected by the number of estimated recent to past effective population size  of Korean breeds were between—0.22 and—0.23 while ancient breeds ranged from -0.23 to -0.3. The FIS of all dogs observed in this study was negative indicating that the sample used in this study had a low level of inbreeding.The inbreeding coefficients (within population FST) . The FST values showed that all Korean breeds were closely related to each other and varied between 1.42 ×10−2 and 9.338 × 10−2. Low FST values in Korean breeds suggest low population differentiation. The highest FST value was 35.13 ×10−2 between the Tibetan Terrier and Korean wolf, showing that they have the lowest degree of relatedness to each other. With regard to these relationships, Korean breeds were close to Chinese breeds with low FST values, especially Chow Chow and Chinese Shar Pei. Nei’s genetic distance between populations also indicated a close relationship between Chinese and Korean breeds.Population differences based on inbreeding coefficient (between populations -FST)  were useThe MDS results are depicted in Neighbor-joining tree , admixtuThe results of the admixture analysis clearly show the genetic structure of Korean dogs in an ancestry-based model . We condThe admixture results of K = 10 clearly showed the diversity and admixture of Korean breeds compared with other breeds. Although Korean dogs were admixed with both the ancient and wolf categories, they showed a distinctive admixture compared with all dogs in the sample. Korean Donggyeong White had a distinct genetic makeup from Jindo and Poongsan. Admixture analysis also showed a strong relationship among Chow Chow, Shar-Pei and Korean breeds. Akita, Alaskan Malamute, Basenji, Shi Tzu, Siberian Husky and Cavalier King Charles Spaniel showed very low levels of admixture. Korean breeds showed admixture events with some Japanese breeds, such as Akita and Shiba Inu. Close relationships among coyote, gray wolf, and Korean wolf were visualized in this analysis.Several migration events of Korean dogs were revealed using non-dogs, and ancient and modern dogs in the maximum likelihood tree . MigratiSeveral migration events could be observed in the TreeMix results. A few important migrations were observed from Korean Jindo Black to the Chinese Shar Pei, Akita to Tibetan spaniel and wolf clade to Basenji with a high migration weight. Observation of the residuals from the fit of the model to the data  revealedf3 statistics were generated to trace the possible ancestry mixtures in Korean dogs using a sample that included ancient breeds, and the gray wolf. A concise table of the most significant f3 statistics (standardized to a Z score <—2) is shown in The Ne values of the observed dog breeds are summarized in Ne over ~20,000 generations is shown in Ne) for Korean dogs was recorded twelve generations ago for the Korean Jindo Black (485), followed by these populations, in decreasing order: Jindo Black and Tan (262), Korean Jindo White (233), Korean Jindo Brindle (158), Poongsan White (110), Korean Donggyeong White (109).The historical effective population size values were estimated based on the LD value across the genome and were used as a representation of demographic changes in the dog population. The adjacent LD (0–20 Kb marker distance) and recent Ne) of all Korean dogs exhibited a declining pattern from the past to recent times . Dogs originated from the gray wolf, and various studies have presented diverse hypotheses for dog domestication , 38. AltAscertainment bias is the systematic variation of population genetic statistics from theoretical expectations. It occurs due to sampling a non-random set of individuals, small sample sizes, or biased SNP discovery protocols . MoreoveThe data used in this study were grouped into four different categories to improve the clarity of the analysis. GRM analysis was performed for all Korean breeds and ancient dogs. The heterozygosity in Korean dogs was high (around 0.4), while the inbreeding coefficient within populations indicates that all Korean breeds in this study had a low level of inbreeding. Previously, it was revealed that Korean Donggyeong White, Korean Jindo White, and Korean Poongsan White had heterozygosity values of 0.77,0.70, and 0.74, respectively . The samFST values were used to investigate genetic diversity between populations. Korean breeds showed more similar allele frequencies with some Chinese breeds (Chow Chow and Chinese Shar Pei.) than others in the sample. The MDS, TreeMix and admixture results also indicated close relationships between Korean and Chinese breeds. MDS analysis showed that Korean breeds are closely related to wolves. The modern breeds show a distinct genetic background from their dog ancestors. It was previously found that Southeast Asian dogs were closely related to wolves, especially Chow Chow, Akita and Chinese Shar Pei. Further, they are considered a foundation lineage connecting to the gray wolf [ray wolf ,46, 47. ray wolf  found thC. lupus) are distributed throughout China in both ancient and modern times [Some publications clearly established that gray wolves Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S1 File(BED)Click here for additional data file.S2 File(BIM)Click here for additional data file.S3 File(FAM)Click here for additional data file.


Hippophae tibetana is a small, dioecious wind-pollinated shrub endemic to the Tibetan-Qinghai Plateau. It is one of the shrubs that occur at very high elevations (5250 m a.s.l.). The Himalayan mountains provides a significant geographical barrier to the Qinghai-Tibetan Plateau, dividing the Himalayan area into two regions with Nepal to the south and Tibet to the north. There is no information on how the Himalayan mountains influence gene flow and population differentiation of alpine plants. In this study, we analyzed eight nuclear microsatellite markers and cpDNA trnT-trnF regions to test the role of the Himalayan mountains as a barrier to gene flow between populations of H. tibetana. We also examined the fine-scale genetic structure within a population of H. tibetana on the north slope of Mount (Mt.) Everest. For microsatellite analyses, a total of 241 individuals were sampled from seven populations in our study area , including 121 individuals that were spatially mapped within a 100 m × 100 m plot. To test for seed flow, the cpDNA trnT-trnF regions of 100 individuals from 6 populations  were also sequenced. Significant genetic differentiation was detected between the two regions by both microsatellite and cpDNA data analyses. These two datasets agree about southern and northern population differentiation, indicating that the Himalayan mountains represent a barrier to H. tibetana limiting gene flow between these two areas. At a fine scale, spatial autocorrelation analysis suggests significant genetic structure within a distance of less than 45 m, which may be attributed mainly to vegetative reproduction and habitat fragmentation, as well as limited gene flow. Geographic isolation is considered to play a critical role in the genetic differentiation of plant populations , 2]. Ph. Ph2]. PThe Himalayan mountain range extends for about 2500 km from west to east . It inclStudies on the genetic structure of alpine plants in this region also provide an excellent model for testing intraspecific evolutionary processes and dynamics associated with climate change in this region, because this area is highly sensitive to global climate change . WhetherH. tibetana, and to explore at a fine scale spatial genetic structure within populations. We use nuclear microsatellite and chloroplast DNA (cpDNA) data to examine intraspecific diversification of H. tibetana. Microsatellite markers are co-dominant markers that are highly abundant and randomly distributed in genomes and usually highly polymorphic and selectively neutral , a, aH. tib neutral , 27], . B. B56]. B= 0.137) . This re= 0.137)  who find markers , respectulations , 61]. O. OH. tibFis values of populations (Fis = 0.084) (Fis = 0.422)   and micr= 0.422)  are posiciencies .He = 0.306, elevation = 4614 m)  (D) and nucleotide diversity (π) in populations NA and ND are 0  , while t 4410 m) . These rND are 0 . These dH. tibetana located up to 45 m apart  found within population TC  [H. tibetana can be roughly divided into two groups, and reveals a geographical pattern with respect to Mt. Everest  . The sig Everest . Almost  Everest , suggest Everest  reveals tel test , which dtel test . All theFST = 0.731, P < 0.01)  often cross the Himalaya to spend winter in India or Nepal and summer in Tibet [H. tibetana, because there are completely different haplotypes   are founby birds , and thain Tibet . Howeverplotypes  on the tlichiana .HT) of H. tibetana is high  is relatively low (0.331), which also indicates limited seed flow among populations. In contrast, there is less differentiation among populations from the same regions, because most of the haplotypes are shared among these populations, for example haplotype N1 occurs at high frequency in all the southern populations and haplotypes T1-T4 are distributed in all the northern populations.Based on the cpDNA data, total genetic diversity  [H. tibetana from the two regions may have remained isolated from each other during the Pleistocene. In other words, this pattern indicates a lack of H. tibetana seed flow across the Himalayan mountains at least since the Pleistocene. Interestingly, in the haplotype network, southern haplotypes N1 and N2 are not directly connected to any haplotypes from their nearest neighbors on the northern slope of Mt. Everest, but are connected to haplotype B16, which is found in the northwest part of Mt. Everest, about 85 km away from the southern valley of Mt. Everest.According to our previous study, the northern valley of Mt. Everest was a refugium for um (LGM) . Compareum (LGM) , two of um (LGM)  Fig 6)..H. tibetum (LGM)  .H. tibetana can be attributed to the restricted gene flow associated with significant geographic barriers created by the Himalayan mountains and isolation-by-distance, the possibility of environmental factors on population differentiation cannot be ruled out, because this may partially be responsible for the observed high population differentiation of H. tibetana between the two climatically distinct regions in our study area. The Himalaya is located in the inter-tropical convergence zone, and Mt. Everest is influenced by two dominant climate systems—the Mid-Latitude Westerlies and the South Asian Monsoon [H. tibetana on the two slopes of Mt. Everest by a lack of gene flow. Therefore, it is worth further investigation to examine selective and adaptive mechanisms for H. tibetana population differentiations that may be caused by both natural geographic barriers and distinct environmental conditions.Although the variable analysis applied above strongly supports our hypothesis that population differentiation in  Monsoon . The cli Monsoon . Variabl Monsoon , thus thH. tibetana. There are strong population differentiations between the southern and northern slopes of Mt. Everest. The lack of gene flow across the Himalayan mountains in either direction, possible increased genetic drift associated with distinct environmental conditions, vegetative reproduction, as well as the fragmented habitat of H. tibetana are probably mainly responsible for the genetic structure at both the landscape scale and the fine scale. However, it is difficult to separate the effects of these several putative factors on spatial variation in our current data. Further advanced research approaches  are needed in the future to explore the local adaptive mechanisms, especially selective and genetic drift of H. tibetana associated with distinct environments on the northern and southern slopes in the Himalayan area.In conclusion, both our genetic datasets support the hypothesis that the Himalayan mountains has served as a physical barrier to gene flow in


To understand the demographic processes behind the spread of the Scythian culture, we analysed genomic data from eight individuals and a mitochondrial dataset of 96 individuals originating in eastern and western parts of the Eurasian Steppe. Genomic inference reveals that Scythians in the east and the west of the steppe zone can best be described as a mixture of Yamnaya-related ancestry and an East Asian component. Demographic modelling suggests independent origins for eastern and western groups with ongoing gene-flow between them, plausibly explaining the striking uniformity of their material culture. We also find evidence that significant gene-flow from east to west Eurasia must have occurred early during the Iron Age.During the 1 st millennium BCE. This study provides genetic evidence for two independent origins for the Scythians in the eastern and western steppe with varying proportions of Yamnaya and East Asian ancestry, and gene flow among them.The Scythian culture was widespread throughout the Eurasian Steppe during the 1 Histories of Herodotus (490/480–424 BCE)st millennium BCE chronicle the existence of the Massagetae and Sauromatians, and later, the Sarmatians and Sacae: cultures possessing artefacts similar to those found in classical Scythian monuments, such as weapons, horse harnesses and a distinctive ‘Animal Style' artistic tradition. Accordingly, these groups are often assigned to the Scythian culture and referred to as ‘Scythians'. For simplification we will use ‘Scythian' in the following text for all groups of Iron Age steppe nomads commonly associated with the Scythian culture.During the first millennium BCE, nomadic people spread over the Eurasian Steppe from the Altai Mountains over the northern Black Sea area as far as the Carpathian Basin490/480–44 BCE2. GThe origin of the widespread Scythian culture has long been debated in Eurasian archaeology. The northern Black Sea steppe was originally considered the homeland and centre of the Scythians61Genetic studies on Central Asian populations based on both ancient910111318192021In this study, mtDNA data from 96 individuals associated with the Scythian culture in different geographical regions and time periods have been sequenced and analysed; additionally, genomic data from eight of these individuals was obtained and analysed . From th2324n=147, n=3,410, While the eastern and western populations investigated here are separated by a distance of 2,000–3,500 km, archaeological evidence indicates that they were strikingly similar regarding their lifestyle and culture. The aims of this study are to investigate the extent to which these groups are genetically related to each other and whether they have a common origin, and to elucidate their demographic history and genetic relationships to modern living populations. We therefore divided the Iron Age steppe nomad data generated by this study and from the literature n=147,  into sevWe generated genome-wide capture data on a target set of 1,233,553 SNPs26We additionally obtained unambiguous and reproducible mtDNA sequences of the hypervariable region 1  for 96 samples  . For 90/n=113) can be divided in four cultural subgroups chronologically dispersed over the 1st millennium BCE (n=26) and the later  Scythian period in the East. The Tagar/Tes group (#7) had to be excluded because of their imprecise dating. These analyses revealed that they were most likely derived from one single population that was expanding over the time period considered here, that is, the two samples are unlikely to represent two independent populations that diverged earlier than 108 generations before present (g BP) or ∼2.7 ky BP. This scenario was highly supported in our model selection procedure .The eastern sample group , we used ABC to further assess if the eastern and western Scythians might share a common origin , while a model of western origin also received some support . Therefore, in contrast to the eastern origin model, a western origin cannot be fully discounted by our analysis. In addition, a pairwise comparison through the computation of Bayes factors reveals a substantial to strong (logistic regression) or weak to substantial  support for the multiregional origin over the western origin model (see st millennium BCE). Importantly, our simulations support a continuous gene flow between the Iron Age Scythian groups, with indications of asymmetrical gene flow from western to eastern groups, rather than the reverse  and east Eurasia . The mitochondrial haplotype diversity in our sample set ranges from 0.958±0.036 in the Tagar/Tes sample  and f4, which are zero for those Test samples that form a clade with LBK and positive for populations that have EHG- or Han-related ancestry, respectively. We plotted the results against each other, which resulted in a V-shaped pattern with Yamnaya at the apex  to check whether a Test population has intermediate allele frequencies between Yamnaya_Samara and Han, which are used as proxies for possible source populations. Intermediate allele frequencies can only occur if the test population is a mixture of populations related to these two sourcesWe also computed statistics of the form f-statistics about this type of admixture.We carried out ADMIXTURE analysis3835qpWave/qpAdm used in Haak et al.Test population and allows one to estimate mixture proportions. In our application, we use five outgroups: Ust_IshimTest and the Yamnaya from Samara could be descended from a single stream of ancestry. In the next step we included LBK farmers testing whether Test, the Yamnaya from Samara and the LBK farmers from central Europe could be descended from two streams of ancestry, in which case Test could potentially be modelled as a mixture of the other two populations. Our results show that the Iron Age Scythians and the Yamnaya are not descended from a single stream of ancestry . We applied the method of ancestry  and furtancestry . We therancestry . This moancestry .CT values to be higher between modern populations of the East and the West (FCT=0.0835) than between ancient populations of similar regions (FCT=0.0262).A multidimensional scaling (MDS) plot based on Reynolds' distances  suggestsn=86, A continuity test was performed between the two Iron Age groups (‘West' and ‘East') and a large set of contemporary Eurasian populations n=86, . For wesHERC2, SLC24A5 or SLC45A2 . The ancestral alleles at ADH1B rs3811801 and rs1229984 are nearly fixed in the Scythian dataset, as they are in modern Europeans Derived alleles of pigmentation markers that are under selection in Europeans are present in eastern and western Scythians, including individuals who are homozygous for the derived alleles at selected SNPs in the 5A2 ref. , 44, 45.al #6 in . This EDst millennium BCE in the eastern Scythians and low FST values between eastern and western Scythian groups. However, ABC analyses that evaluated different models for the origins of Scythian populations provided the strongest support for a multiregional origin, with eastern and western groups arising independently within their own regions. Despite separate origins and the enormous geographic separation, demographic modelling infers ongoing and substantial gene flow between eastern and western groups, which provides a plausible demographic mechanism to explain the low FST values and the general uniformity of the material culture of Scythians right across the Eurasian Steppe zone.Our results show that the Iron Age groups—long believed to be connected through shared cultural artefacts associated with the classical Scythians of the North Pontic region—also share a genetic connection. This is supported by our ABC analyses revealing population continuity over the 1nd millennium BCE onwards in the eastern steppe . This component appears later in all Iron Age populations but with significantly higher levels in the eastern steppe zone than in the West. These findings are consistent with the appearance of east Eurasian mitochondrial lineages in the western Scythians during the Iron Age, and imply gene-flow or migration over the Eurasian Steppe belt carrying East Asian/North Siberian ancestry from the East to the West as far as the Don-Volga region in southern Russia. In general, gene-flow between eastern and western Eurasia seems to have been more intense during the Iron Age than in modern times, which is congruent with the view of the Iron Age populations of the Eurasian Steppe being highly mobile semi-nomadic horse-riding groups.Our genomic analyses reveal that western and eastern steppe inhabitants possess east Eurasian ancestry to varying degrees. In our ADMIXTURE analyses we find an East Asian ancestry component at K=15 in all Iron Age samples that has not been detected in preceding Bronze Age populations in either western or eastern parts of the Eurasian Steppe. Another ancestral component that is maximized in the north Siberian Nganasan population becomes visible from the 2nd millennium BCEst millennium BCE13In the East, we find a balanced mixture of mitochondrial lineages found today predominantly in west Eurasians, including a significant proportion of prehistoric hunter-gatherer lineages, and lineages that are at high frequency in modern Central and East Asians already in the earliest Iron Age individuals dating to the ninth to seventh century BCE and an even earlier mtDNA sample from Bronze Age MongoliaAll Iron Age individuals investigated in this study show genomic evidence for Caucasus hunter-gatherer and Eastern European hunter-gatherer ancestry. This is consistent with the idea that the blend of EHG and Caucasian elements in carriers of the Yamnaya culture was formed on the European steppe and exported into Central Asia and SiberiaConcerning the legacy of the Iron Age nomads, we find that modern human populations with a close genetic relationship to the Scythian groups are predominantly located in close geographic proximity to the sampled burial sites, suggesting a degree of population continuity through historical times. Contemporary descendants of western Scythian groups are found among various groups in the Caucasus and Central Asia, while similarities to eastern Scythian are found to be more widespread, but almost exclusively among Turkic language speaking (formerly) nomadic groups, particularly from the Kipchak branch of Turkic languages . The genFor this study, human skeletal sample material from different parts of Russia and Kazakhstan was selected based on an association of the archaeological complex with Scythian burial rites and artefacts. We analysed 110 skeletal samples. Five samples yielded no DNA, eight gave only poor results, and for one only coding region SNPs could be obtained. In the end we could use 96 samples for the analyses of mtDNA. Eight individuals were converted into Illumina libraries; six thereof were used for a genomic capture, two for shotgun sequencing, and one for both capture and shotgun sequencing. Overall DNA preservation was remarkably good, with slight variations depending on region or sample site .2O, 0.2 μl of each primer and 4 μl DNA extract. Multiplex PCR conditions were as follows: initial denaturation for 15 min at 95 °C followed by 36 cycles of 40 s denaturation at 94 °C, 40–90 s annealing at 56 °C, 40–90 s elongation at 72 °C and for some reactions a final elongation for 10 min at 72 °C was added. Standard PCR was used for fragments that failed amplification in the multiplex reactions and to amplify the HVR1 of some additional samples.All pre-PCR sample preparation steps were carried out in a cleanroom facility physically separated from the post-PCR laboratories. Sample preparation, DNA extraction, the amplification of single mtDNA fragments and the amplification of nuclear loci were performed as previously described5152To allow for parallel sequencing of 37 mtDNA fragments in up to 60 samples on a 454 GS FLX machine, barcodes were ligated to the multiplexed DNA fragments following the tagging protocol of Meyer 2008 ref. , single ST values and Reynolds' distanceST values with 1,000 permutations and a gamma value=0. Fu's FS test of selective neutrality was performed to test for population expansion. The significance level for the FS values was set at 0.02 qpWave/qpAdm)38DNA-library preparation for subsequent shotgun sequencing was performed according to the protocol used in Kircher 2012 ref.  with sliBam files for the genomic data can be downloaded from the European Nucleotide Archive under accession number PRJEB18686. Mitochondrial sequences were deposited in GenBank under accession numbers KY369766–KY369861.How to cite this article: Unterländer, M. et al. Ancestry and demography and descendants of Iron Age nomads of the Eurasian Steppe. Nat. Commun.8, 14615 doi: 10.1038/ncomms14615 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary Figures 1-14, Supplementary Tables 1-28, Supplementary Note 1 and Supplementary References


Goniocorella dumosa, Madrepora oculata, Solenosmilia variabilis) to disturbance within the New Zealand region and to guide marine protected area design, genetic structure and connectivity were determined using microsatellite loci and DNA sequencing. Analyses compared population genetic differentiation between two biogeographic provinces, amongst three subregions  and amongst geomorphic features. Extensive population genetic differentiation was revealed by microsatellite variation, whilst DNA sequencing revealed very little differentiation. For G. dumosa, genetic differentiation existed amongst regions and geomorphic features, but not between provinces. For M. oculata, only a north–central–south regional structure was observed. For S. variabilis, genetic differentiation was observed between provinces, amongst regions and amongst geomorphic features. Populations on the Kermadec Ridge were genetically different from Chatham Rise populations for all three species. A significant isolation‐by‐depth pattern was observed for both marker types in G. dumosa and also in ITS of M. oculata. An isolation‐by‐distance pattern was revealed for microsatellite variation in S. variabilis. Medium to high levels of self‐recruitment were detected in all geomorphic populations, and rates and routes of genetic connectivity were species‐specific. These patterns of population genetic structure and connectivity at a range of spatial scales indicate that flexible spatial management approaches are required for the conservation of deep‐sea corals around New Zealand.Deep‐sea stony corals, which can be fragile, long‐lived, late to mature and habitat‐forming, are defined as vulnerable marine ecosystem indicator taxa. Under United Nations resolutions, these corals require protection from human disturbance such as fishing. To better understand the vulnerability of stony corals ( We employed a province, region and geomorphic feature hierarchical framework to test the hypotheses that (i) the water mass characteristics of two biogeographic provinces   and one nuclear region (ITS) was employed to estimate genetic connectivity and population genetic differentiation . In total, 27 microsatellite loci were assayed for G. dumosa and S. variabilis, and 11 microsatellite loci were assayed for M. oculata. Of these loci, most were developed for this study .All methods follow Zeng . DNA seqon Table . ITS datdy Zeng, , but oth2.32.3.1Multiple sequences were aligned using the plugin ClustalW Alignment , and then all alignments were viewed by eye using Geneious v7 . For all populations with two or more individuals, the intraspecific genetic diversity was evaluated by computing the number of haplotypes, the number of polymorphic sites, haplotypic diversity (h) and nucleotide diversity (π).ST statistics (based on sequence divergence) were calculated to test for genetic differentiation amongst populations. If significant differentiation amongst populations was detected, the location of the genetic discontinuity was identified using BARRIER v2.2  between locations  were tested using Arlequin  values and to test for isolation by distance by comparing the matrix of ΦST values to the matrix of shortest actual distances (km) between pairs of sites . The Mantel test Mantel,  was empl2.3.2F statistic (FST), and hierarchical FST analyses (AMOVA) were conducted in GenAlEx. If significant differentiation amongst populations was detected, the location of the genetic discontinuity, isolation by depth and isolation by distance were estimated as described for the D‐loop and ITS markers. Multilocus matches were employed to detect the asexual/colonial relationship between individuals (GenAlEx).Micro‐Checker v2.2.1 with default settings was used to identify stuttering, large allele dropout, and null alleles  was chosen when Bayesian information criterion (BIC) values were the lowest. Scatter plots of microsatellite genotypes in relation to discriminant functions were created in “adegenet”. STRUCTURE (v2.3.4), with a 5 × 106 burn‐in period and 5 × 106 MCMC runs after burn‐in, was employed to infer the number of distinct genetic groups based on Bayesian assignment analysis  values to evaluate likelihood scores and consistency amongst runs. The values of K were set from 1 to the number of geomorphic feature populations, that is, 4, 4 and 8 for G. dumosa, M. oculata and S. variabilis, respectively. The optimal number for K was chosen as the maximum number of clusters which yielded likelihoods lower than those observed at lower values of K. This number was computed in the online program STRUCTURE HARVESTER   was estimated using the software NeEstimator v2  using multilocus data in the single‐sample bias‐corrected method based on linkage disequilibrium . Comparable analyses were not possible for the between northern/southern provinces or for the amongst north‐central‐south regions because of very low sample sizes (n < 4) in the south. For M. oculata, AMOVA of ITS variation revealed significant differentiation amongst the three regions . In contrast, for S. variabilis, ITS and D‐loop variation showed no evidence of structure at any spatial scale.For ST values for ITS and D‐loop were variable but relatively low for all three species. In G. dumosa, no significant ΦST values were observed for either marker. For M. oculata, a significant pairwise value between the Kermadec Ridge and Chatham Rise populations was observed for ITS. For S. variabilis, significant pairwise population values of ΦST for ITS were observed between the Macquarie Ridge and Louisville Seamount Chain populations, and between the Macquarie Ridge and Kermadec Ridge populations  for any of the species, but ITS sequence variation exhibited a significant pattern of isolation by depth for M. oculata and G. dumosa (p < .05).There was no statistically significant isolation by distance  included eight loci for G. dumosa, six for M. oculata and 12 for S. variabilis . For 3.2.2G. dumosa, the number of alleles per locus varied from 7 to 27 (average = 8.20). Observed heterozygosity (HO) ranged from 0.500 to 1.000 per locus, and most HO values were greater in all populations than expected . HO values ranged from 0.273 to 0.944 per locus, and unlike the other two coral species, were lower in all populations than expected , and HO ranged from 0.211 to 1.000  was observed (Chatham Rise–Kermadec Ridge), no significant results were observed M. oculata, or for S. variabilis, 12 of 28  and 14 of 28  tests were significant  amongst populations from the geomorphic features for both the reduced and all loci data sets showed similar patterns  populations (data not shown). For S. variabilis, pairwise population FST values revealed no significant genetic differences between the Bounty Trough population and all other populations, and the Kermadec Ridge and Chatham Rise populations  and DAPC . In M. oculata, DAPC revealed that the Campbell Plateau and Chatham Rise populations were genetically similar to each other  patterns of gene flow.G. dumosa, based on microsatellite variation, BARRIER predicted that barriers to gene flow may exist for the Challenger Plateau and Chatham Rise populations  and Chatham Rise populations are isolated  and 69.4%  (Table For e) Table a, c. At e) Table b. First‐e) Table b. Most fe) Table b. The peM. oculata, assignment success rates at the regional scale were low . Individuals sampled from the central region were assigned at nearly equal rates to the north, central and south regions, whilst individuals sampled from the north or south regions exhibited higher rates of assignment success , but were lower at the regional scale  and at the geomorphic features scale  (Table For y) Table g, i, k. y) Table h, j. At y) Table l; this wy) Table j.4G. dumosa, M. oculata and S. variabilis, were examined for genetic connectivity and gene flow amongst populations in the New Zealand region for the purpose of contributing to effective spatial management planning options to protect VMEs. We employed an a priori hierarchical and spatially explicit approach to hypothesis testing for population genetic structure, estimated contemporary and historical effective population sizes and identified barriers to gene flow as well as source and sink populations, all of which may contribute significantly to management decisions with conservation outcomes in the deep sea.Three habitat‐forming deep‐sea corals, 4.1Small sample sizes and an absence of fine spatial scale sampling are widely acknowledged as inevitable constraints in genetic studies of deep‐sea organisms  and populations on some geomorphic features (such as the Chatham Rise) had large enough sample sizes to reveal patterns of genetic differentiation and connectivity. Overall, our analyses are probably best viewed as a conservative interpretation of patterns of population genetic differentiation.K) is now widespread in population genetics analyses  depends on a signal that is a function of 1/Ne. Such methods are therefore most powerful with small populations when the signal is strong, but have difficulty distinguishing large populations from infinite ones when the signal is small . No previous study has investigated connectivity between these two areas, but significant genetic subdivision between populations of D. dianthus was detected between the Auckland Island slope (far south) and seamounts on the northern Chatham Rise   and M. oculata , at least one marker revealed the existence of a pattern of isolation by depth. As neither G. dumosa nor M. oculata populations were genetically isolated by distance, this implies that depth and related environmental gradients may play an important role in the larval migration of these species. Within the New Zealand region, Miller et al.  are strongly differentiated based on DNA sequence variation. Unfortunately, the limited sample sizes of the present study precluded detailed analysis to determine at what depth(s) genetic differentiation for G. dumosa and M. oculata populations takes place .Depth is an important factor contributing to patterns of genetic connectivity for some benthic fauna, particularly for taxa that are distributed across a wide depth range  . Given its similarity to S. variabilis in terms of morphology and reproduction, the larvae of G. dumosa are likely to share the same characteristics. Based on this assumption, the larger oocyte size, providing more nutritional support, may promote a longer larval life and greater dispersal potential for M. oculata. Thus, life‐history characteristics may vary even between closely related deep‐sea corals  and D. dianthus .Differences in reproductive strategies may contribute to differences in patterns of gene flow and genetic structure observed across taxa in the deep sea  Table  and was S. variabilis suggests that this species has a higher asexual or inbreeding rate in populations on geomorphic features than the other two species. Miller and Gunasekera  were established in 2001 and 2007, respectively, to protect benthic fauna  from bottom trawl fisheries throughout the New Zealand EEZ Fig. . These cG. dumosa, M. oculata and S. variabilis (as proxies for similar VME indicator species) provide new information useful for assessing the effectiveness of existing protection measures, and the design of future protected area networks in the EEZ. The populations of the three species all showed evidence of pronounced self‐recruitment within the scale of the geomorphic features examined. This finding suggests that additional protected areas will be required to maintain genetic diversity (through self‐recruitment) of populations at features that do not already receive some protection. For S. variabilis, populations on all the geomorphic features examined were to some extent source populations for other populations, but those from the Kermadec Ridge and the Bounty Trough seem to be particularly important. Of particular significance as a migrant source for G. dumosa and S. variabilis populations was the Kermadec Ridge, with the NE Slope (G. dumosa), the Bounty Trough (S. variabilis) and Louisville Seamount Chain (S. variabilis) populations also being important for genetic connectivity.The results of the present study for http://www.mfe.govt.nz/marine/kermadec-ocean-sanctuary). However, outside of the sanctuary area corals and other VME taxa are still vulnerable to disturbance from future seabed mining of sulphide deposits in the region (Boschen et al., S. variabilis, nor do they provide much protection along the axis of the Rise, including some areas where G. dumosa forms dense thickets in an area of interest for phosphorite nodule mining. Considering the relative importance of the Chatham Rise as a sink population and as a hot spot area with the highest genetic diversity but relative lower effective population sizes, additional protected areas should be considered here for the future management of human activities on this feature.Currently, most geomorphic features examined contain one or more BPAs or seamount closure areas. The exceptions are the Hikurangi Margin, Bounty Trough and Macquarie Ridge, as well as the Lord Howe Rise and the Louisville Seamount Chain which are outside the New Zealand EEZ. The Hikurangi Margin is an area subject to bottom trawling (Clark & O'Driscoll, The results of the present study, and those of previous genetic connectivity studies for various species around New Zealand (Bors et al., https://doi.org/10.5061/dryad.61622. ITS and D‐loop DNA sequences were also deposited in GenBank under accession numbers: MF360747–MF360784.Data for this study are available from the Dryad Digital Repository:  Click here for additional data file.


Eucalyptus grandis, a hardwood species occurring widely in costal areas from 32° S to 16° S in Australia. High population diversity levels and weak population structure were detected with putatively neutral genomic SSRs. Using three FST outlier detection methods, a total of 58 outlying SSRs were collectively identified as loci under divergent selection against three non-correlated climatic variables, namely, mean annual temperature, isothermality and annual precipitation. Using a spatial analysis method, nine significant associations were revealed between FST outlier allele frequencies and climatic variables, involving seven alleles from five SSR loci. Of the five significant SSRs, two (EUCeSSR1044 and Embra394) contained alleles of putative genes with known functional importance for response to climatic factors. Our study presents critical information on the population diversity and structure of the important woody species E. grandis and provides insight into the adaptive responses of perennial trees to climatic variations.Identification of loci or genes under natural selection is important for both understanding the genetic basis of local adaptation and practical applications, and genome scans provide a powerful means for such identification purposes. In this study, genome-wide simple sequence repeats markers (SSRs) were used to scan for molecular footprints of divergent selection in  Such selection can result in gene frequency changes among populations within a species, ultimately leading to variation in both phenotypic traits and genetic structure even in the presence of gene flow68Zea mays L.10Genome scans provide a powerful means in population genetics studies to detect outlier loci putatively under selection11Eucalyptus L’Hér. (family Myrtaceae) encompasses more than 780 species and subspecies native to the Australian continent and surrounding islandsEucalyptus species and hybrids constitute the most widely planted hardwood trees in the world  and are therefore important for the global forest-related industries. Within Eucalyptus, E. grandis Hill ex Maiden (flooded gum or rose gum) is one of the most important species in terms of breeding and genomics effortsPopulus trichocarpa Torr. & Gray) for whole genome sequencingE. grandis is a diploid species with 2n = 22 chromosomes and 640 Mb genome sizeE. grandis displays significant variation in adaptive phenotypic traits, such as growth and frost tolerance (e.g. Rockwood & MeskimenE. grandis by isozyme markers (GST = 0.12)E. grandis and other Eucalyptus speciesE. grandis. In addition, even in Eucalyptus, only two studies have recently reported candidate loci for diversifying selection in natural populations of E. gomphocephala DC.E. tricarpa (L.A.S. Johnson) L.A.S. Johnson & K.D. HillThe broadleaved tree genus E. grandis, including 45 genomic SSR (gSSR) and 65 expressed sequence tag (EST) derived SSR (EST-SSR) markers, to search for molecular footprints of divergent selection in E. grandis natural populations. The genetic diversity and population structure at putatively neutral gSSR loci were first assessed for 16 E. grandis populations across the species range. The FST outlier SSRs were then tested against the 110 SSRs to identify loci potentially involved in divergent natural selection. SSR alleles associated with climatic variables were finally investigated to reveal gene polymorphisms contributing to local adaptation to temperature, isothermality and/or precipitation.In this study, we used 110 SSR markers distributed across the genome sequence of E. grandis , Guangdong Province, China.A total of 159 individuals were sampled from 16 provenances across the range of  grandis , each pr grandis . The motLeaf tissues (~300 mg) were powder homogenized in a MM400 mixer mill , and genomic DNA was subsequently extracted using a modified CTAB method2 concentration and melting temperature (Tm) depending on marker. The PCR products (1 μL) were diluted 1:10.5 with loading buffer (9.34 μL deionized formamide and 0.16 μL GeneScan 500LIZ) and then detected on an ABI 3130xl genetic analyzer using GeneMapper 4.1 software . Sixteen individuals, each randomly selected from one population, were PCR repeated to test the marker reproducibility.In total, 110 SSR markers distributed across the 11 main scaffolds and one small scaffold  were use272930NA), observed heterozygosity (HO), expected heterozygosity (HE) and fixation index (F) were estimated with GENALEX 6.4.1P values) was tested over all populations with GENEPOP 4.23.2 (http://www2.unil.ch/popgen/softwares/fstat.htm) was used to investigate per-locus inbreeding coefficients of individuals relative to the total population (FIT) and to the sub-population (FIS), FST and allelic richness  as well as between-locus LD (with Bonferroni correction).For each locus, number of alleles (P < 0.01) nor showed FST outlying values in lositan analysis on 16 populations (implemented as stated below) were included  in subsequent population diversity and structure analyses. For each population, average number of alleles per locus (ANA), HO, HE, F and AR were estimated similarly as above. Significance in diversity differences between populations or population groups was tested using the ‘Compare among groups of samples’ function with ‘two sided’ option and 1,000 permutations in fstat 2.9.3.2 (http://www2.unil.ch/popgen/softwares/fstat.htm). Nei’s genetic distance between populations was calculated for construction of an unweighted pair group method with arithmetic mean (UPGMA) dendrogram in POWERMARKER 3.25FST) and molecular variances (AMOVA). The Bayesian clustering program STRUCTURE 2.3.4K) of genetically homogeneous clusters assuming an admixture model and correlated allele frequencies between populations. For each of K values (1−16), the Markov Chain Monte Carlo (MCMC) sampling was replicated with 10 iterationsK value was determined by the highest ΔK methodK) slope with increase in each K value.Only the genomic SSRs that neither departed significantly from HWE (http://www.worldclim.org/) at a spatial resolution of 30 arc-secondsValues of 19 climatic variables during the years 1950–2000 were obtained for each original population location from a standard set of climate grids  B.S.P.]The 16 populations were partitioned into homogeneous groups using a FST outlier detection methods were used to test all the 110 SSR loci for evidence of natural selection among the population groups of each climatic partition. The first was a summary-statistics methodFST were identified from a plot of FST vs. expected heterozygosity. Following the infinite allele mutation model, the distribution of FST vs. expected heterozygosity was calculated in LOSITAN with 100,000 simulation replicates under the option of neutral mean FST. Markers outside the 95% and 5% confidence intervals of the distribution were considered as candidates (outliers) for positive (divergent) and balancing selections, respectively. False discovery rate (FDR) was set to 0.01.Three FST statistics and therefore avoid possible false positives. Significant loci at the 95% or 5% confidence level were recognized as candidates for positive (divergent) selection or balancing selection, respectively.The second was also a summary-statistics methodhttp://cmpg.unibe.ch/software/bayescan/index.html), namely, barely worth mentioning, substantial, strong, very strong and decisive evidences, in which the last three grades were considered as candidates for divergent selection.The third was a hierarchical Bayesian modeling method modified from Beaumont and BaldingFST outlier loci detected above were corroborated using a spatial analysis method (SAM)The NA ranging from three to 52 (mean 16.9), HO from 0.209 to 1.000 (mean 0.623), HE from 0.200 to 0.890 (mean 0.706), AR from 1.434 to 3.835 (mean 3.027) and NAF from zero to 0.278 (mean 0.075). No pair of loci showed significant LD in two or more populations (P < 0.05), suggesting the independent segregation of the marker loci used. Twenty-eight loci deviated significantly from HWE (P < 0.01), including 12 gSSRs and 16 EST-SSRs  and AR from 4.295 to 5.300 (mean 4.929). Specifically, the five northern populations  were significantly less diverse as compared to the remaining (southern) populations . The fixation index (F) per population suggested little evidence of inbreeding, with a range between zero and 0.127 (mean 0.037). The overall FST values were generally low as demonstrated by between-population comparisons  diversity were revealed in ulations , e.g. HEK = 2).Similar patterns of neutral population structure were observed in PCoA analysis, UPGMA dendrogram and STRUCTURE analysis . For PCohttp://www.worldclim.org/), only three were not correlated with each other, namely, mean annual temperature, isothermality and annual precipitation. The k-means analysis partitioned optimally the 16 populations into six, four and four groups in mean annual temperature, isothermality and annual precipitation, respectively  than those of genomic SSRs  range, FST = 0.037) are less than the mean of widespread eucalypt species, e.g. mean FST of 0.062 and 0.055 at restriction fragment length polymorphism (RFLP) and SSR loci, respectivelyE. grandis based on isozyme markersE. grandis (e.g. populations MS vs. Fin and Cre vs. Kin) that could contribute as a barrier to gene flow and induce genetic differentiation, may reflect recent emergence of the disjunctions from a more continuous distribution due to climate changeThe low levels of population differentiation  values in at least two outlier detection methods than expected in the respective climatic variables, suggesting that they could have been involved in divergent selection among homogeneous population groups. In contrast, 11, 12 and seven loci presented lower FST values than expected in the respective variables, signaling balancing selection within population groups and/or homogeneous selection among groups. In addition, quantitative trait differentiation coefficients (QST) are 0.33 and 0.28 in 7-year-old tree height and diameter at breast height, respectively, for a range-wide provenance/family trial of E. grandis .Similar to the T 0.037;  and thusFST outlier loci detected totally with all the three methods  Liebl.Castanopsis fargesii FranchetZosteria marina L.)Q. robur and Q. ellipsoidalis E.J. HillOncorhynchus nerka Walbaum)FST outlier .Five (8.6%) of the riations . HoweverC3HC4 RING finger genes were identified to be associated with local precipitation in black spruce6264C3HC4 RING finger gene expression have been reported in response to drought stress in many plants, such as Arabidopsis thaliana (L.) Heynh.64Populus speciesThe locus EUCeSSR1044, associated significantly with annual precipitation, was functionally annotated as C3HC4 type RING finger protein. Similarly, two Triticum aestivum L.), thionin-like genes can express differently in response to heat stressEucalyptus.The marker Embra394, significantly associated with mean annual temperature, was functionally annotated as thionin-like protein 2. The thionin-like proteins have been well documented in plants to be involved in protection against pathogens, including bacteria and fungiThe remaining three loci were of unknown function, including EUCeSSR0755 which was associated with all three climatic variables and EUCeSSR0849 which was related to both mean annual temperature and isothermality . These EFST outlier loci  Karst.vice versa, under a climatic scenario of pronounced warming temperature and declining rainfallDivergent natural selection can change allele frequencies and thereby increase the adaptive trait value of a population and the number of individuals with the fitness traits, leading to local adaptation6Only one or two alleles of each significantly associated locus showed population variation with climatic variables, which may indicate that the significant alleles alter protein function in a way that the remaining alleles do notE. grandis provides an unusual opportunity to study local population adaptation in perennial trees. Although a relatively low density of multi-allelic loci were used for genome scans (only 110 SSRs spanning the E. grandis genome), we found evident footprints of divergent selection at a suite of loci. Two loci that showed significant associations with climatic variables represent alleles of putative genes with known functional importance for response to climatic factors. In addition, high genetic diversity levels and weak population structure were detected in E. grandis natural populations. These results have implications for understanding the genomic basis of adaptation to climates in perennial woody trees as well as for conservation and utilization of the important hardwood tree E. grandis. Further genetic association and expression studies would be required to confirm the functional role of putative genes. Also, next-generation sequencing technologies, including those for genotyping of multi-allelic markers  using microsatellites. Sci. Rep.6, 34941; doi: 10.1038/srep34941 (2016).


Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian,  Micro-evolutionary processes, such as rapid local adaptation, represent key functional responses to environmental changeAlthough local adaptation is primarily triggered by selective pressures associated with non-parental environments57Ciona robusta  that has already been sequenced and assembled17C. robusta is a promising model to study genetic mechanisms of natural selection associated with rapid environmental changeThe changes of environmental conditions during biological invasions can be orders of magnitude higher and/or faster than what species would experience due to natural processes  in their native habitatsC. robusta at population and genomic levels across a range of environmental conditions. Microsatellites within genes (i.e. gene-associated microsatellites) are often subjected to stronger selection than other regions because of their significant functions in regulating gene expression. We surveyed genome-wide gene-associated microsatellites derived from expressed sequence tags (ESTs), and selected representative loci that are evenly distributed across the genome to cover a wide range of functional genesHere, we study genetic signatures of C. robusta populations were randomly collected from the surface of artificial substrates at each site and preserved into absolute ethanol immediately after collection. We randomly chose an average of 30 individuals per population for genetic analyses.Based on the obtained environmental gradient  and global population genetic analyses from previous studies13et al.et al.et al.et al.Out of 4,654 genome-wide gene associated microsatellites derived from 684,393 expressed sequence tags (ESTs), 218 polymorphic loci were selected (see more details in Lin A) ranged from two to 20, allelic richness (AR) varied from 1.337 to 10.035, observed heterozygosity (HO) ranged from 0 to 0.798, and expected heterozygosity (HE) varied from 0.027 to 0.872 . A total of 43, 20, 33, 18 and 31 loci significantly deviated from Hardy-Weinberg equilibrium in the populations AM, BL, SA, NMF and GAP, respectively. Since null alleles were detected at two loci (Cin170 and Cin171) across all populations, we excluded these two loci for subsequent analysis.A total of 152 candidate microsatellites were re-genotyped individually for all populations. The number of alleles (FST = 0.0169) were detected between the two European populations (AM & BL), while the highest (FST = 0.2041) were detected between the population pair from Europe (AM) and Australasia . Similarly, the 3D-FCA divided the populations into two groups - group 1 from the Pacific coast (NMF and GAP) and group 2 from the Mediterranean Sea and Atlantic coast  candidates for directional selection  based on the election ; Fig. 2.When we conducted the pairwise population analysis using the BAYESCAN method, a total of 10 and six loci were indicated to be under directional selection and balancing selection respectively, four of which  were not detected when all populations were considered. In particular, seven loci  were potentially under directional selection in different population pairs . Interestingly, all outlier loci were associated with the population from New Zealand and/or the one from Korea .Of the 41 candidate loci under selection, 30 loci  were located on nine different chromosomes , while tFor the 18 loci considered to be under balancing selection, five were located on the chromosome 9, while the remaining 13 loci were scattered on eight chromosomes. Similarly, the length of balancing selection on chromosomes was relatively short; for example, Cin141 and Cin158 were identified as balancing selection loci, but their nearest loci  were identified as neutral . Althoug22We found a total of 132 genes that were located in all selective sweep windows . Based on known functions, many of these genes are crucial in adaptation to harsh environments and/or environmental changes, such as the calmodulin-like protein 4 (CALML4) in the Cin54 selective sweep window, the ciliogenesis-associated TTC17-interacting protein-like and dynein heavy chain 2 (CATIP2) in the Cin10 selective sweep window, and the programmed cell death protein 2 (PDCD2) in the Cin124 window .When the SAM analysis was performed to identify possible correlation between microsatellite alleles and environmental variables, 16 putatively selected loci were significantly correlated with at least one environmental variable, and among these, 14 were under directional selection in the global outlier analysis . The remC. robusta. We found significant genetic differentiation among populations collected from different geographical regions and recovered multiple genomic regions likely to be under selection. We then analyzed six key environmental factors in relation of these genomic regions and found candidate genes that were associated with temperature and salinity changes in different habitats. Thus, these candidate genes might have an important role in rapid local adaptation during range expansions. Taken together, our results suggest that rapid local adaptation is a major driver for significant population differentiation, and that “plastic” genomic regions represent promising regions for future studies aiming at better understanding rapid adaptation in invasive species.In this study, we used genome-wide gene-associated microsatellites to reveal genetic signatures of natural selection at both population and genomic levels in the model invasive ascidian FST values  under directional selection ; Fig. 2.When we analyzed allele-association with temperature and salinity, SAM analyses identified 16 putatively selected loci - 15 were considered to be under directional selection and one was indicated to be under balancing selection. When the sequences of these16 loci were subjected for BLAST, 13 were successfully annotated, some of which have crucial functions, such as carboxypeptidase Z-like (CPZ) regulates crucial aspects of developmentCionaGadus morhua2+) and the regulation of diverse signaling pathwaysIn addition, 15 putatively directional selection loci were located within genes, and many of these genes are crucial for physiological processes . InteresFST values obtained here were comparative to our previous global genetic study, where population structure was assessed using 12 randomly selected genomic microsatellites based on the same populationsThe FST between AM and NMF was 0.2041  in SPSS v.18 to test differences in temperature and salinity among sampled sites . We also performed a principal component analysis (PCA) to illustrate environmental differences among populations .To select representative populations living in different environments, we analyzed key environmental variables et al.et al.et al.et al.2+, 0.5 pmol M13-tailed forward primer, 1 pmol reverse primer and 1 pmol fluorescently labeled M13 primer, and 0.25 unit of Taq DNA polymerase (Takara Bio Inc.) with the same cycling profiles as in Lin et al.TM-500 LIZTM size standard (Applied Biosystems). Genotypes were scored using GeneMapperTM software v. 4.0 (Applied Biosystems).Genomic DNA was extracted from approximately 10 mg of siphon tissue using the proteinase K method as described by Waters A), observed heterozygosity (HO), expected heterozygosity (HE), and allelic richness (AR) using FSTAT v. 2.9.3.2FIS) were evaluated using the Markov chain-based method  for all population pairs using GENEPOP v. 3.4K = 1–5. The most likely number of clusters was determined by obtaining the maximum value of ΔK proposed by Evanno et al.Population genetic differentiation was determined by In this study, we employed the hitchhiking mapping strategy to identify loci under selection at the population level. Hitchhiking mapping is based on the principles of a selective sweep - when a gene is under selection, there can be a significant loss of diversity at not only target genes, but also linked genes because of the “hitchhiking” effect (i.e. selective sweep)FST-outlier test for modeling neutral loci. For the first method developed by Beaumont & NicholsFST under the island modelFST values under both the infinite alleles model (IAM) and stepwise mutation model (SMM). As recommended by Antao et al.FST’ and ‘force mean FST’ options. The second hierarchical method was modified by Excoffier et al.FST values into locus-specific components (α) and population-specific components , we analyzed selective sweep windows for 20 kb up- and down-stream of each locus potentially under selection. As demonstrated by many related studies31As selective sweep regions were narrow in http://www.nodc.noaa.gov/OC5/SELECT/woaselect/woaselect.html; We used SAM v.2How to cite this article: Lin, Y. et al. Genetic signatures of natural selection in a model invasive ascidian. Sci. Rep.7, 44080; doi: 10.1038/srep44080 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.