Historical documentation shows that the Spanish Merino sheep was selected over many centuries due to the quality of wool, following which it was used to originate all other Merino breeds around the world, mainly by crossbreeding with local breeds. Today, the historical genetic lines that originated the Spanish Merino are still preserved in several closed herds in which they have been bred for nearly 200 years, maintaining their original genetic purity. Our study demonstrates, using a genomic approach, the exceptional genetic richness and variability of these lines, which are clearly differentiated from modern Merino breeds, and must therefore be protected to safeguard the large genetic pool they represent.According to historiographical documentation, the Romans first began to select Merino sheep in the Iberian Peninsula during the first century, with the aim of obtaining a breed appreciated for the quality of its wool. This process continued locally during the Middle Ages, when Spanish sheep were protected, and their export to foreign countries was banned. It was during the 16th century when individual Merino sheep were allowed to spread around the world to be used to improve the wool quality of local breeds. However, the wool crisis of the 1960s shifted the selection criteria of the Merino breed towards meat production at the expenses of wool. Consequently, individuals that display the genetic and phenotypic characteristics of those sheep originally bred in the kingdom of Spain in the Middle Ages are extremely difficult to find in commercial herds. In this study, we characterized the genetic basis of 403 individuals from the main historical Spanish Merino genetic lines , which were bred in isolation over the last 200 years, using a genomic approach based on genotyping data from the Axiom™ Ovine 50K SNP Genotyping Array. Our analysis included measuring population structure, genomic differentiation indexes, runs of homozygosity (ROH) patterns, and an analysis of molecular variance (AMOVA). The results showed large genetic differences between the historical lines, even though they belong to the same breed. In addition, ROH analysis showed differences due to increased inbreeding among the ancient generations compared with the modern Merino lines, confirming the breed’s ancestral and closed origin. However, our results also showed a high variability and richness within the Spanish historical Merino lines from a genetic viewpoint. This fact, together with their great ability to produce high-quality wool, suggests that ancestral Merino lines from Spain should be considered a valuable genetic population to be maintained as a resource for the improvement of wool-producing sheep breeds all around the world. The Spanish Merino is one of the most important sheep breeds in the world, particularly due to the high quality of its wool, but also due to its economic and historical importance, to the point where it was involved in the origin of most current wool-sheep breeds, worldwide. However, Merino individuals have also been characterized for their ability to thrive in highly diverse and harsh environments and weather conditions around the world, which is why they are frequently employed in combined meat–wool productive systems. In 2020, the Spanish Merino census included 121,727 breeding males and females located in 7457 different herds, although most of them  were located in the dry, arid areas and pasturelands of the south and southeast of the country [The Spanish Merino is one of the oldest and toughest sheep breeds in the world. Although the origin of the Merino is not entirely clear, there is Roman documentary evidence that indicates that the Iberian Black Merino is the ancestral origin of this breed ,3,4. AccTo protect this valuable, sought-after breed, King Alfonso X founded the Honorable Council of the Mesta, which in the 13th century banned the export of ewes to other countries for several centuries, with the sole exception of Portugal in the 16th century ,11. ArouThe economic crisis that hit the wool industry in the 1960s affected the Spanish Merino breed to a greater extent, since its selection criteria shifted towards meat production in an attempt to obtain an alternative source of income other than wool . For thiThe Donoso line was formed from the historical flock of the Donoso family, which, since the 15th century, has managed a large flock of several thousand transhumant sheep. Six centuries later, the Donoso line was stabilized, and included individuals characterized by good quality meat production, while keeping most of the original wool quality. Currently, the Donoso sheep is characterized by being eumetric, with a very good conformation and meat aptitude, while also producing wool of medium fineness, exceptional fiber length and performance, and which is free of wool-grease.The Egea line originated from a royal flock of 35,000 transhumant sheep from three different herds, which at the beginning of the 19th century was stabilized to 3000 sheep and 1000 rams. Egea sheep are characterized by being individuals of medium size that are sturdy and short-legged, with good meat production and maternal aptitude. Their wool is also characterized by a medium fineness and being free of grease, with a remarkable wick length covering the sheep’s limbs and heads.The Granda line origin was associated with the Count of Oliva royal flock in 1845, although its origin might go back further. Currently only two pure-bred herds remain to the present day. Granda sheep are horned, eumetric and very well proportioned, producing a medium fineness but very uniform wool free of grease. Over the last few decades, there has been some degree of cross-breeding with Hidalgo rams.The Hidalgo line origin was associated with the royal flock of the famous Duke of Fernán Núñez in the 19th century, which was one of the most important lineages in the first half of the 20th century, with around 3000 transhumant sheep, but nowadays, only two pure-bred herds remain. Hidalgo sheep are large with long limbs and closed hocks, without wool covering most of their face and legs. Hidalgo wool is characterized by its extreme fineness, but also by its short wick and grease content, which gives Hidalgo sheep a characteristic blackened appearance. Hidalgo sheep are also known for a marked maternal character, with increased production of milk for Merino sheep.The López-Montenegro lineage has a family origin, being mentioned as differentiated livestock in some references from the mid-18th century . This liFinally, the Maesso line was originated within the family stock in the 16th century. In the 19th century, however, the line underwent exponential growth, reaching as many as 25,000 grazing animals. Maesso sheep are small, with a tendency towards being ellipometric, very rustic and well-adapted to harsh environments. They are also characterized by the fine quality of their wool.All of these traditional Merino lines are considered to have been endangered in recent decades, due to a dangerous decrease in their population, mainly due to the shift in the breeding system from wool to meat production. For this reason, the Spanish Government decided 50 years ago (in 1971), to establish an ex-situ conservation program in Hinojosa del Duque , where individuals of each of these six ancient Merino lines  are bred in purity to the present day.Nowadays, high-throughput genomic methodologies, such as the availability of SNP chips, have made it possible for us to determine the population structure and variability from a genetic viewpoint with accuracy and reliability ,25,26. AThe present study aims to evaluate the population structure, genetic variability, and differentiation situation of the last historical genetic lines of the Spanish Merino sheep, and to compare them with other Merino breeds from around the world using genomic data.n = 60), Hidalgo , López-Montenegro , Maesso , Donoso  and Egea , which have been bred in closed farms for up to 200 years (about 70 generations) according to the existing records. In addition, 20 Spanish White Merino individuals randomly selected from commercial herds  were included as an undifferentiated control, and 39 Spanish Black Merino (MN) were included as outgroup control within the breed. Individuals within groups and group sizes were selected from all of the available animals on the ACME database avoiding close kinships, following the Food and Agriculture Organization of the United Nations recommendations for the genomic characterization of animal genetic resources guidelines [Samples from 403 Spanish Merino sheep belonging to the Asociación Nacional de Criadores de Ganado Merino (ACME) were analyzed in this study. The first dataset analyzed (dataset I) included individuals from six historical Spanish White Merino (ME) genetic lines: Granda  following the manufacturer’s instructions. Thereafter, the individuals were genotyped using the Axiom™ Ovine 50K SNP Genotyping Array , including 56,250 markers. Genotype calls were obtained by analyzing raw data files following the best genotyping practices workflow procedure in the Axiom analysis suite package v5.0 . All of n = 100), French Rambouillet , German Landschaf , and Chinese  Merinos as well as the genotypes of 24 Mouflons  collected in a hunting state from the south of Spain as an outgroup species control.To analyze the genetic differentiation of the Spanish Merino ancient lines with different Merino breeds in the rest of the world, we created a second dataset (dataset II) by merging our data with 194 genotypes obtained from public repositories . The nonBoth datasets were first pruned by removing all of the markers showing a minor allele frequency (MAF) < 0.01 or without physical annotation. Thereafter, those SNPs in linkage disequilibrium (LD) with a variance inflation factor (VIF) of 1.25 were also removed. The final dataset included 28,765 SNPs. All data curation was performed using PLINK V2.0 program .Admixture software v1.3 [ape 5.5 package [To compile a profile of the genetic population structures and their stratification, we first measured expected and observed heterozygosity using the dartR package  from theare v1.3 . The opt package  in R. ThROH) per individual at the chromosome level, as the percentage of the bases of each respective chromosome covered by ROH [ROH values theoretically produced by a mating that occurred 3, 6, and 9 generations ago  by analyzing ROH longer than 16 Mb, 8.8 Mb, and 5.5 Mb only, according to Fisher’s theory [ROHANC) was also estimated by analyzing ROH shorter than 5.5 Mb. Finally, an incidence p-value at the SNP level was determined using a 1,000,000-iteration permutation test following the methodology described by Goszczynski, et al. [The existence of genetic fingerprints within the Spanish White Merino was determined by estimating the existence of genomic regions in which the run of homozygosity (ROH) abundance had significantly increased. To this, we first estimated ROH per individual using a 7-class model in the RZooROH R package . Krate ld by ROH . In addis theory . In addi, et al. genind object using the radiator package [poppr.amova) implemented in the Poppr R package [To estimate the percentage of the variance components explained by the species, breeds, and genetic lines using genomic data, we performed an analysis of molecular variance . The bi package . Thereaf package . The modThe development of high-throughput genotyping technologies, in which allelic variants of thousands of SNP markers can be easily determined at a very low cost, has opened a new era in the genetic characterization of animal populations . In receThe initial estimation of genomic variability based on the observed (Ho) and expected (He) among the populations and lines are presented in Similar results were observed in the analysis of the ancient and modern lines within the Spanish Merino, in which the commercial Merino SMEI had the lowest value of Ho (0.331), while the LM had the highest (0.375). In DON, EG, MAE and LM, the Ho was higher than the He, while GRA, HID and SMEI showed the opposite. In a previous study, Azor, Cervantes, Valera, Arranz, Medina, Gutiérrez, Goyache, Muñoz and Molina  estimateHowever, it is worth mentioning that Azor, Cervantes, Valera, Arranz, Medina, Gutiérrez, Goyache, Muñoz and Molina  employedROH) values in the analyzed population, averaging 0.037 in the six historical lines studied. Despite that the results can be considered to be low on average, there were large differences among the lines, with LM being the one with the lowest value (FROH = 0.017) and HID the one with the highest (FROH = 0.057). To differentiate ancient and recent inbreeding, we calculated FROH considering different ROH lengths grouped into four categories. LM was still the line with the lowest levels of homozygosity across all of the generations calculated, including the ancestral one (FROH Ancient = 0.0064), while HID produced the opposite values, except in the FROH calculated three generations ago, where the highest value appeared in the MAE population (FROH 3G = 0.0107). When analyzing the proportion of ROH in each line, the populations that accumulated the maximal percentage of ancient inbreeding were the HID and DON lines , whereas the MAE line showed the lowest (25.53%)  . Figure (25.53%) B. In addbreeding A. On theThe degree of genetic differentiation among the populations was assessed through an analysis of molecular variance (AMOVA), which quantified the percentage of the differences explained by the genetic lines and breeds . DiffereInterestingly, the Spanish Merinos showed a lower variability among lines (3.99%), but with almost no variation explained by individuals (0.12%) within the lines. Even though the differentiation between lines can be considered high (even close to that observed among breeds), the lack of variability within them supports the existence of six “pure” ancient genotypes that are clearly differentiated. In addition, the differences between individuals of the Merino lineages are also much smaller than the differences between individuals of the Merino-derived breeds, which is in agreement with the closed breeding practices developed during the formation of the historical Merino lines.Principal Component Analysis (PCA) of dataset II revealed a clear clustering of the animals according to their breed , in most cases A. HoweveThe genetic differences between the wild Mouflon and domestic sheep breeds are observed, and some individuals of Spanish Merino and the RMB sheep are the two most distant genetic groups. On the other hand, the MN was the nearest breed to the Mouflon, which is logical, since it is the most ancestral Merino, a fact which could place these animals as the inception population of the breed ,8.Another interesting finding was the existence of a close genetic distance between Black Merinos and Mouflon, since it is well known that MN was probably the most significant ancestral breed in the Merino trunk . HoweverIn the same way, the Spanish White Merino was located closer to the German Merino than to the Australian Merino. Two hypotheses can explain this finding. First, the introgression of the Spanish Merino into the German Merino occurred in 1765, while the same situation occurred in the Australian Merino over 100 years later (late 19th century). Furthermore, the genetic admixture between Spanish and German Merino breeds has continued on a large scale, with several events documented only 60 years ago (in the 1950s and 1960s).Our data revealed a high degree of heterogeneity in the Chinese Merino, which fits with the origin of the breed by crossing Australian Merinos with various Chinese sheep breeds. For example, the Chinese Merino partly originated from an absorbent crossing with Gansu Mountain Sheep, generating a new breed with fine wool and high rusticity . This woThe intra-breed analysis, including all of the Spanish Merino lines, as well as the Black Merino without Mouflon and with Mouflon, is shown in Admixture analysis also revealed clear differences in the genetic composition among breeds and lines. The first analysis , K = 2 sA phylogenetic distance tree including all of the Spanish Merino individuals analyzed in this study is shown in Interestingly, some LM and GRA individuals are quite similar from a genetic point of view. This could be explained by the fact that the populations are bred in the same geographical area, and under similar management. For this reason, it can be assumed that these lineages could have formed centuries ago from the same old historic royal flocks, although the occurrence of a modern crossbreeding event cannot be ruled out either.In contrast, GRA individuals showed two clear genetically divergent groups . We speculate that these differences can be explained by the fact that GRA herds were bred in isolation in very distant geographical areas over the last 50 years, thus producing genetic differences by selective breeding despite their common origin.To find the time of divergence , we measThis is the first study to assess the genetic structure of the Spanish Merino breed and its most ancient and original genetic populations using a high-throughput genomic approach. Overall, we determined the existence of a high degree of genetic variability within the breed, as well as its influence in improving Merino breeds around the world. In addition, we demonstrated the importance of the ancestral Merino lines, which are still bred in purity in Spain, as a genetic reservoir of variability for improving the breed, as well as for conservational purposes. In addition, the existence of such rich genetic variability could provide the starting point for an association, in further studies, between the genomic variations and the phenotypes of each of these populations. This genetic richness, together with the excellent, highly sought-after aptitude of the wool, makes it essential to undertake all possible efforts aimed at preserving the different historical lines as a genetic source for the improvement of other derived Merino breeds. However, the conservation of these ancient genetic lines is also justified for historical and cultural reasons and for the different aptitudes that each of them presents, such as differences in grazing capacity, resistance to thermal stress, growth rate, meat quality, and maternal aptitudes, among others, which could be of interest soon. Therefore, it would be convenient to promote actions such as the incorporation of breeders from other herds and the creation of a germplasm bank of the best animals of each line in the Hinojosa del Duque Center (ex-situ conservation), where most of these pure lines are still bred in purity.


Triticum and Aegilops species  were investigated using two gene-based markers (start codon targeted (SCoT) polymorphism and CAAT-box derived polymorphism (CBDP)) and simple-sequence repeats (SSRs). The SCoT, CBDP, and SSR markers yielded 76, 116, and 48 polymorphism fragments, respectively. The CBDP marker had greater efficiency than the SCoT and SSR markers due to its higher polymorphism content information (PIC), resolving power (Rp), and marker index (MI). Based on an analysis of molecular variance (AMOVA) performed using all marker systems and combined data, there was a higher distribution of genetic variation within species than among them. Ae. cylindrica and Ae. tauschii had the highest values for all genetic variation parameters. A cluster analysis using each marker system and combined data showed that the SSR marker had greater efficiency in grouping of tested accessions, such that the results of principal coordinate analysis (PCoA) and population structure confirmed the obtained clustering patterns. Hence, combining the SCoT and CBDP markers with polymorphic SSR markers may be useful in genetic fingerprinting and fine mapping and for association analysis in wheat and its germplasm for various agronomic traits or tolerance mechanisms to environmental stresses.Knowledge of the natural patterns of genetic variation and their evolutionary basis is required for sustainable management and conservation of wheat germplasm. In the current study, the genetic diversity and population structure of 100 individuals from four  Aegilops and Triticum, are precious genetic resources that contain many genes associated with resistance to different abiotic stresses and have interesting breeding potential. Hence, due to their high level of genetic diversity, these species play a key role in wheat breeding programs [Genetic erosion is one of the negative consequences of modern agriculture using improved high-yield cultivars. In addition, climate change directly impacts the occurrence of abiotic stresses such as drought, heat, and salinity, which pose serious risks to agricultural production. One of the ways to increase resilience to these adverse conditions is to take advantage of potential new alleles in the gene pool of plants . Due to programs ,7,8,9,10One of the basic requirements for wheat breeding is to estimate the diversity of wild relatives of wheat for breeding goals . GeneticMolecular markers provide useful information for crop plant breeding, particularly in studies of genetic variability and genetic relationships among different accessions of several plant species. Among molecular marker systems, SSR is the most popular PCR-based marker. This marker has been widely used to analyze genetic diversity among different plant species. SSRs are consecutive repeats of one to six nucleotides in both coding and non-coding regions. SSRs are a selective genotype marker due to their high frequency, high level of allelic diversity, co-dominant inheritance, and analytical convenience . In addiThe main objective of this study was to investigate the genetic diversity within and among selected wild relatives of wheat using the molecular markers SCoT, CBDP, and SSR. Furthermore, a comparative analysis using these markers was also performed.T. aestivum, Ae. tauschii, Ae. cylindrica, and Ae. crassa, were analyzed in this study , extension for 3 min at 72 °C, and final extension for 7 min at 72 °C. Amplified fragments were stained with SafeView II and visualized by gel electrophoresis in 1.5% agarose.For SCoT analysis, eight primers were selected based on the literature ,32 Tabl. PCR amp2O, and 10 μL master mix . All reactions were performed as follows: initial denaturation step for 5 min at 94 °C, 45 cycles of denaturation for 45 s at 94 °C, primer annealing for 45 s at 56 °C, primer elongation for 90 s at 72 °C, and final extension for 10 min 72 °C. The PCR products were stained with Safestaine-II  and visualized on a 1.5% agarose gel with a gel documentation device.A set of 12 CBDP primers were designed based on Singh et al.  for CBDP2O, 2 μL template DNA from each sample, and 2 μL each primer, respectively. Amplification reactions were run at 5 min for 95 °C, followed by 35 cycles of denaturation for 45 s at 95 °C, primer annealing for 45 s (temperature varied for each primer from 51.3 to 69.3 °C) and primer elongation for 1 min at 72 °C. The final extension was 5 min at 72 °C. The amplified products were visualized on a 2% agarose gel, stained with SafeView II and visualized under UV light using an imaging system.In the SSR analysis, 25 microsatellite primers were selected to form a set of SSR developed based on the D genome of bread wheat by Roder et al.  Table 3Table 3. Na), effective number of alleles (Ne), Shannon’s information index (I), percentage of polymorphic loci (PPL), and Nei’s gene diversity (H), were estimated using the GenAlEx package [The binary matrices were created based on the presence (1) and absence (0) of amplified fragments across all studied samples. Several informativeness parameters were calculated, such as the number of polymorphic bands (NPB), resolving power (Rp), and marker index (MI). The analysis of molecular variance (AMOVA) was performed using the GenAlEx package ver. 6.5 . Several package . Jaccard package . Further package . The STR package  was used package . Ae. crassa accessions. The highest values of Ne, expected heterozygosity (He), I, and PPL, were estimated among Ae. cylindrica accessions. In the CBDP analysis, the highest values of Ne, I, He, and PPL were estimated for the Ae. cylindrica population. The SSR analysis showed that the Ae. tauschii population wa the more diverse population as compared with other populations due to the highest values of all genetic variation parameters. This finding was confirmed by analyzing the combined data (SCoT + CBDP + SSR)  . T. aestivum (accessions No. 33 and No. 17); the lowest value was found between two samples of Ae. crassa (accessions No. 76 and No. 84). Using the CBDP data, the GD values ranged between 0.068 and 0.909 with an average of 0.684. The highest and lowest GD coefficients were found between accessions No. 30 (Ae. tauschii) and No. 98 (Ae. crassa) and between No. 64 (Ae. cylindrica) and No. 63 (Ae. cylindrica), respectively. In the SSR analysis, the average GD value was 0.780 and ranged between 0.0750 and 0.956. The highest GD was estimated between accession No. 4 (T. aestivum) and No. 65 (Ae. cylindrica), whereas the lowest was found between two samples of Ae. tauschii (accessions No. 30 and No. 33). The analysis of combined data showed the average of GD was 0.810. Two samples of T. aestivum (accessions No. 12 and No. 21) and two samples of Ae. tauschii (accessions No. 30 and No. 43) showed the highest and lowest GD values, respectively (data not shown). The molecular data from SCoT, CBPD, SSR, and combined markers were used to estimate Jaccard’s genetic distance coefficient (GD) pairs of investigated wheat accessions. In the SCoT analysis, the GD values ranged from 0.068 to 0.909 with a mean of 0.720. The highest GD value was estimated between two samples of Ae. crassa and Ae. cylindrica clustered into two distinct groups. T. aestivum and Ae. tauschii accessions created the unique group. Except for two accessions of T. aestivum and Ae. tauschii, all samples of these species clustered into distinct subgroups. When the cluster analysis was computed using combined data, a better grouping pattern of classification was observed. As shown in T. aestivum was separated from its group and clustered with Ae. cylindrica accessions. The results of Mantel’s test further supported these results. Based on Mantel’s test [Ae. cylindrica and Ae. tauschii clearly separated from each other. Similar to the dendrogram obtained by cluster analysis, the samples belonging to T. aestivum and Ae. tauschii were scattered in the same position of biplot.To investigate the genetic relationships among wheat landraces and other wild relative accessions, cluster analyses based on Jaccard’s similarity coefficients and neighbor-joining (NJ) algorithm were computed for each marker system and combined data . Based ol’s test , there wAe. cylindrica and Ae. crassa. The second subpopulation consisted of six accessions of Ae. crassa. All the Ae. tauschii accessions, along with one and nine accessions from T. aestivum and Ae. cylindrica, created the third subpopulation. The fourth subpopulation consisted of twenty-four accessions of T. aestivum and two accessions of Ae. cylindrica. One accession of T. aestivum was identified as an admixture sample (Ae. tauschii, Ae. cylindrica, and Ae. crassa, respectively. The second subpopulation included fourteen accessions of Ae. tauschii. The remaining accessions from all species were in the third subpopulation. One accession from Ae. tauschii showed admixture status between two first subpopulations (Ae. tauschii along with three accessions of T. aestivum species; the second subpopulation included of all accessions of Ae. crassa; the third subpopulation consisted of all Ae. cylindrica accessions; and the fourth subpopulation included the remaining accessions of T. aestivum (Stratification of the genetic population of the total sample assembly based on all marker systems showed the existence of a distinct structure. For this analysis, we used an assumed population range from K = 2 to K = 10, with 10 replications per K. In the SCoT analysis, the optimum number of subpopulations was K = 4. The first subpopulation consisted of fourteen and eighteen accessions of e sample A. In theulations B. The poaestivum C.Aegilops and Triticum populations collected from different natural habits of Iran. The results of this work revealed that the SCoT, CBDP, and SSR markers could be successfully used to investigate genetic diversity variation among and within populations of bread wheat. The applicability of these marker systems to characterize the genetic diversity and phylogenetic relationships was also compared. The CBDP marker showed higher polymorphism than the SCoT and SSR marker systems (The genetic diversity of wild relatives of wheat, which is known as the main germplasm for bread wheat, should be elucidated for conservation and utilization and to expedite breeding programs. Molecular markers are efficient and accurate tools to reveal and estimate genetic diversity and to determine the population structures of many plant species . Over th systems . The meaBased on the results of the AMOVA analysis using each marker system and combined data, the level of genetic diversity within species was greater than among them, which indicated that all samples from each species had a diverse genetic background . When thAe. cylindrica using the SCoT and CBDP markers, while the use of the SSR marker and combined data yielded the highest values related to Ae. tauschii (Ae. cylindrica and Ae. tauschii as the most diverse species was a notable finding. Similarly, several studies have reported a high level of diversity among these species using agro-morphological characteristics and different molecular marker types. For instance, the high level of genetic diversity in Ae. cylindirca has been reported using the SCoT marker [Ae. tauschii as compared with other wild relatives of wheat [Ae. cylindrica and Ae. tauschii had the highest values of genetic variation parameters as compared with bread wheat and its other relatives [Ae. cylindrica and Ae. tauschii have good potential for use in breeding programs, and various breeding aspects of these species have been highlighted in numerous studies [Ae. tauschii, due to its physiological mechanisms, could be used as an ideal genetic source for discovery of novel genes to improve drought tolerance in bread wheat. In another study, Ahmadi et al. [Ae. tauschii responded well to high levels of salinity stress as compared with other ancestral species. The breeding potential of these species has been highlighted in a review by Pour-Aboughadareh et al. [Indeed, one the main reasons for this result may be related to the number of amplified fragments. Among the four species, the highest values of the genetic variation parameters were estimated for tauschii . AlthougT marker . Howeverof wheat . Furtherelatives . Among t studies ,9,10,41. studies  reportedi et al.  reportedThe clustering patterns of samples generated by all marker types were different in some cases. However, the pattern obtained by the SSR marker was clearer than other markers . The besAe. cylindrica and Ae. tauschii. Knowledge of the genetic diversity of these species may assist in efficient management of these natural germplasms of wheat. Our findings also revealed that two gene-based markers, SCoT and CBDP, are more suitable for detection of polymorphism rate and provide greater informativeness than the SSR marker. However, the SCoT and CBDP markers are suitable for use in fine mapping studies.The present study indicated a high level of genetic diversity within wild relatives of wheat, especially


Stuckenia filiformis > Hippuris vulgaris > Myriophyllum species > Ranunculus section Batrachium species. A positive correlation between clonal and genetic diversity was identified for all taxa, except H. vulgaris. Clonal diversity was affected by climate in S. filiformis and by the local environment in H. vulgaris. For Myriophyllum spp., low elevation and high sediment nutrition were significant for sexual recruitment. The environmental effects on clonal diversity were not significant in R. sect. Batrachium spp. Clonal diversity of aquatic plants is moderate to high and varies greatly in highlands. The effects of breeding systems and environmental factors on the patterns of clonal variation were identified. Elevational gradients, climates and local conditions play different roles in clonal diversity among relative taxon. Our results highlight the importance of sexual recruitment in alpine aquatic plant populations and the influence of environmental factors on the genetic patterns in freshwater species at local and regional scales.Clonal reproduction is one of the most distinctive characteristics of plants and is common and diverse in aquatic macrophytes. The balance between sexual and asexual reproduction is affected by various conditions, especially adverse environments. However, we know little about clonal diversity of aquatic plants under suboptimal conditions, such as at high altitudes, and having this information would help us understand how environmental gradients influence patterns of clonal and genetic variation in freshwater species. The microsatellite data of four aquatic taxa in our previous studies were revisited to estimate clonal and genetic diversity on the Qinghai-Tibetan Plateau. Clonal diversity among different genetic groups was compared. Local environmental features were surveyed. Beta regressions were used to identify the environmental factors that significantly explained clonal diversity for relative taxon. The level of clonal diversity from high to low was  MicrosaHippuris L. is a monogeneric genus of the aquatic clade in Plantaginaceae. H. vulgaris has a circumboreal distribution across the Northern Hemisphere and also occurs on the QTP, as its southern range. The plant is perennial mainly via rhizome and monoecious, bisexual and protogynous flowers. The germination rate of its seeds is important for sexual recruitment  is a diverse aquatic or semiaquatic group comprising over 30 species . The spatial genetic pattern of S. filiformis was quantified on the QTP previously . Pairwise Bruvo distance, which is irrespective of ploidy level, was also used for genet discrimination, calculated in R package poppr , number of genotypes (ng), richness index [R= (ng-1)/(nr-1)] and Simpson complement unbiased D  were useMyriophyllum spp. and R. sect. Batrachium spp., the two species with intercrossing, were treated as two genetic clusters. Genetic clades within H. vulgaris and S. filiformis suggested in Populations in lotic sites, which likely to be monomorphic, or with small sample sizes were removed . The cloR. sect. Batrachium spp. and S. filiformis. For H. vulgaris and Myriophyllum spp., sample sites were resurveyed for water and sediment features during 2015-2016. The pH and salinity  of the undisturbed aquatic habitat were measured using a handheld multiparameter metre . The two waterbody parameters were stable for years if the hydrology did not change obviously  were asymptotic in the range between 0 and 1 .R2 values were also estimated for each model  among all model combinations. A bias reduction for a small sample size was performed . We rankch model . The canch model . We alsoch model .r > 0.7, p < 0.01), then we kept the one that resulted in a better fit model. We fit the models for each taxon because clonal diversity was significantly different in the four taxa but was not influenced by genetic divergence within taxa (see Results). All statistical analyses were conducted in R 4.1.2 , 0 to 0.75, 0 to 0.944 for R. sect. Batrachium spp.; and 4 to 18 (5 to 19 discriminated based on Bruvo distance), 0.294 to 1, 0.562 to 1 for S. filiformis, respectively , while the lowest clonal diversity was in R. sect. Batrachium spp.  . Wilcon tests performed for each species pair suggested that the clonal diversity of S. filiformis was significantly higher than that of the other three taxa, while R. sect. Batrachium spp. had significantly lower clonal diversity than H. vulgaris   and 22.2% (D) to high (S. filiformis) clonal variation, except R. sect. Batrachium spp. Under adverse environmental conditions, relatively high clonal diversity may also be induced by migration or long-lived genets  than in monoecious populations (mean R = 0.42)  .Cryptomeria japonica. Previously, we revealed that the genetic clustering of R. subrigidus and S. filiformis was affected by environmental conditions  in M. sibiricum, implying that the plant might have evolved to invest more in producing flowers against adverse conditions  . These findings suggested a decline in clonal diversity along the altitudinal gradient in Myriophyllum spp. might be caused by deficiency in seedling establishment.We found that the influence of high altitude on clonal variation was different among the four studied taxa. The effect of elevation on the balance of sexual and asexual reproduction was not significant in ng wind) . We alsoS. filiformis, clonal diversity was revealed to decline at lower elevational regions, which was mainly caused by annual temperature. Stuckenia spp. are abundant in mountain regions of Central Asia and are highly adaptable to alpine environments, and S. filiformis occurs almost in cold and shallow water in mountains or in Siberia and is peripheral and unsuitable in low-altitude areas of the plateau edge, which mainly lead to the limitation of its sexual reproduction  was rarely used directly by submerged plants, most populations were monomorphic in R. sect. Batrachium and Myriophyllum spp., implying that water pH might affect the reproduction of some aquatic plants above a certain threshold.The effects of water characteristics on the reproduction of aquatic plants have received less attention. pH determines the form of inorganic carbon in water bodies, subsequently affecting the photosynthesis and productivity of submerged macrophytes . The avaasing pH . In the Myriophyllum spp. and S. filiformis were sampled at the five sites with salinities over 1%, and the clonal diversity of these populations was equal to the mean value of related taxon. Although seedling establishment of plants could be limited in habitats with high salinity , the National Natural Science Foundation of China (31700190) and Special Foundation of President of The Chinese Academy of Sciences.The authors thank Haocun Zhao for the assistance on field work, and Qixiang Lu, Xing Li, Juan Zhang for the valuable suggestion. We are also grateful to reviewers for their very helpful comments and advices.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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Fusarium circinatum is an introduced fungal pathogen extended to the northern regions of Spain that causes Pine Pitch Canker (PPC) disease. In this work, we analyzed the pathogen’s genetic diversity to study changes over time and space since the first outbreak occurred in Spain. Using six polymorphic SSR markers, 15 MLGs were identified in 66 isolates, and only three haplotypes were found with frequencies higher than one. In general, genotypic diversity was low and decreased shortly over time in the northwestern regions while maintained at País Vasco, where only one haplotype (MLG32) was detected 10 years. This population also included isolates of a single mating type (MAT-2) and VCGs identified in only two groups, while isolates from NW regions were of both mating types and VCGs represented in 11 groups. The existence of haplotype MLG32 maintained on time and widely distributed suggests its good adaptation to the environment and the host. Results showed that the pathogen in País Vasco remains clearly differentiated from other northwestern populations. This fact was supported with no evidence of migration among regions. Results are explained by the asexual reproduction, but also selfing at least to a lesser extent that leads to identification of two new haplotypes. The introduction of an exotic pathogen into a new area leads to the establishment of new biotic interactions, giving rise to a process of coevolution between the host and the pathogen ,2. For tFusarium circinatum is an introduced pathogen currently established in Europe in Spain and Portugal infecting Pinus radiata and P. pinaster [P. radiata being one of the most susceptible species while P. pinaster is moderately resistant to the disease. Typical symptoms are sunken cankers on branches and stem with abundant resin, and wilt and necrosis of needles above the infection point [Fusarium circinatum also infects seedlings in nurseries causing pre- and post-emergence damping-off [F. circinatum in the EU.pinaster . This paon point . Fusariuping-off . PPC is ping-off ,8. In thFusarium circinatum populations worldwide to analyze their structure and infer the reproduction mode and pathways for pathogen introduction and migration [DNA-based studies have been carried out on igration . First sigration ,11,12. Aigration  revealedigration , ongoingF. circinatum Spanish population. Both mating types, MAT-1 and MAT-2, were found, although one of the two clusters (with predominant haplotype MLG32) only contained isolates of mating type MAT-2 located in the northeastern region (País Vasco). A further study with isolates representing the main haplotypes in each of the two clusters [Genetic diversity analysis revealed that Spanish population is structured in two clusters, each one with a predominant haplotype (named MLG32 and MLG59), a situation compatible with two independent pathogen introductions in Spain . Geneticclusters  showed tF. circinatum. Heterokaryons are originated through: (1) hyphal anastomosis of isolates of the same vegetative compatibility group (VCG) [Fusarium circinatum the sexual state has not been reported in nature [There are different mechanisms potentially associated with significant changes in genetic variability of up (VCG)  and (2) up (VCG) ,17. For n nature , and VCGn nature , while in nature . In nortn nature  revealinFusarium circinatum, haploid selfing is prevented [Fusarium circinatum, the sexual stage has not been reported in the field [Regarding selfing mechanism, it is differentiated haploid from diploid selfing  with difrevented  since threvented ,20,21. Ihe field , but outhe field ,22,23, phe field .Fusarium circinatum is extended in Spain to the Atlantic coast [Pinus radiata plantations are grown. It is the only exotic species of pine planted in Spain and cohabits in this area with P. pinaster, a native Mediterranean species. Moreover, some new environmental situations have been identified after its introduction [P. radiata more susceptible than P. pinaster [Population genetics studies provide insight into the evolutionary process and changes in gene frequencies that shape pathogen population structure ,25. Intric coast  where mooduction , such aspinaster ) that exFusarium circinatum populations infecting pine stands and to determine how this variation is distributed in a temporal and spatial scale. The aim is to understand the biological significance of the variation detected and to make inferences about the evolutionary processes that may influence the population structure.The objective of this work is to quantify the genetic diversity of Spanish Fusarium circinatum isolates were obtained from cankers of forest trees showing symptoms of PPC. Small pieces of samples were cut from the margin of symptomatic tissue and plated on Fusarium Selective Medium (FSM) [F. circinatum were identified based on morphological features and molecular methods. For morphological fungal identification, putative colonies of F. circinatum growing on FSM were transferred to plates with Spezieller Nahrstoffarmer Agar (SNA) medium [F. circinatum [F. circinatum was done by PCR using specific primers CIRC1A (CTTGGCTCGAGAAGGG) and CIRC4A (ACCTACCCTACACCTCTCACT), as described by Schweigkofler et al. [F. circinatum isolates produced a 360 bp amplicon. In total, 29 F. circinatum monosporic isolates were obtained, 5 isolates from Galicia, 9 from Asturias, and 31 from País Vasco (A survey was done in 2018–2021 in northern Spain. um (FSM) . Isolati) medium  incubatercinatum . Moleculr et al.  in a finís Vasco . A uniquTo analyze genetic variation of pathogen population in a temporal scale, we used a set of monosporic isolates maintained at the Instituto Agroforestal Mediterráneo, Universitat Politècnica de València, collected from a first survey carried out in 2004–2011, soon after the first official report of the pathogen in Spain ,32. IsolFresh mycelia growing on PDA  plates at 22 °C was scraped and ground to a fine powder under liquid nitrogen in a mortar. DNA was extracted using the E.Z.N.A. Plant DNA kit  or NZY Plant/Fungi gDNA Isolation kit  following the manufacturer instructions. DNA obtained with the latter kit was used only for microsatellite analysis. DNA quantity and quality was measured using a spectrophotometer . For molecular marker analysis, only high-quality DNA was used, with absorbance ratio 260/280 and 260/230 > 1.8.Idiomorphs MAT-1 or MAT-2 were determined for each isolate. A multiplex PCR assay was performed using primers MAT1p1 (AGAAACTGACTGATACATCAAGGGG)-MAT1p3 (TCATAAGAAGTGTTGAAGGAATCACAG) and GcHMG1 (CTTTACCGTAAGGAGCGTCACCAT)- GcHMG2 (TGATCCGCCATCTGCTTGTAGAGT) for alleles MAT-1 and MAT-2, respectively, as described by Wallace and Cover  and SchwF. circinatum [F. circinatum . Briefly, samples were genotyped using a set of seven microsatellites previously designed for rcinatum  and selercinatum  for polyrcinatum . Each PCnit) mutants, following [nit mutants, isolates were cultured on Czapeck (Cz) medium  amended with 4% potassium chlorate at 25 °C with 12-h light cycle. Fast-growing mycelia sectors developing for 4–10 days were transferred to Cz medium. Colonies that grew as thin, expansive, and with no aerial mycelia were considered as nit mutants. To check for their stability, mutants were grown on PDA and then transferred to Cz and Cz with 4% potassium chlorate. For phenotyping nit mutants (nit1/3 or nitM), they were cultured on basal medium with no mineral added [nitM. Otherwise, they were considered as either nit1 or nit3. No attempt was done to distinguish between these two types because pairing between nit1 and nit3 mutants develops a heterokaryotic growth very slowly [nit1 (or nit3) and a nitM mutants from different isolates in all possible combinations were done to determine vegetative compatibility. Mycelial plugs placed 2–3 cm apart on Cz medium were incubated at 25 °C for 4–15 days and observed periodically for dense mycelia where colonies were in contact forming the heterokaryon. Mutant pairs that formed this dense mycelium complement each other, and thus they belong to the same Vegetative compatibility group (VCG). Pairings between a nit1 (or nit3) and a nitM mutants from the same isolate were done to check for heterokaryon self-compatibility (HIS) which has been reported in Gibberella fujikuroi [Vegetative compatibility groups were determined based on pairings between nitrate non-utilizing  and subpopulations of geographical origin (Spanish regions) where they were collected  . Additio5) [A) [Genetic diversity estimated by molecular markers was based on the number of alleles and allele frequencies at each SSR locus. For each isolate, a multilocus genotype (MLG) was defined by combining data for single SSR alleles. If the MLG had been identified previously by Berbegal et al. , the sam5) ,42,43 we5)  to accoum 0 to 1  was usedto 1 [A)  because distance . Bootstrp < 0.05. Second, the contribution of sexual reproduction to the genetic diversity was studied. MLGsim 2.0  was used to test if identical genotypes emerged independently through random mating (Psex) based on a simulation of 1000 permutations.Additionally, two more tests were done to evaluate occurrence of sexual reproduction. First, the null hypothesis of mating type ratios of 1:1, which are expected under random mating, was tested. The usual chi-squared test to evaluate departure from the null hypothesis is not recommended in this case because the observed frequencies for some mating types are less than five. Instead, the theoretical probability of the observed outcome was calculated based on the binomial probability distribution on the null hypothesis with p = q = 0.5. The null hypothesis is rejected when ST) is based on 999 permutations. For spatial variation study, a Mantel test was performed to test for correlations between geographic distance  and Bruvo’s genetic distance. The test was run in R using the function mantel.randtest in package ade4 [Genetic differentiation between subpopulations was estimated by Hedrick’s standardized index  (G’st), age ade4  and its age ade4 . Final aThe comparison between haplotypes identified in the two surveys performed on average 10 years apart indicates that MLG32 continues to be the most frequent haplotype . It is r5 = 0.961) in the whole pathogen population . Diversity and evenness decreased with time , and richness decreased as well . When including geographic origin within surveys, the expected number of MLG in Galicia decrease from 6 to 3, while in Asturias remains at 3; H, G, and E5 indices  , as well indices  decrease indices .Fusarium circinatum population. For Galicia and Asturias, ratios were 5:1 and 2:1, respectively, in isolates from survey 1, and 2:1 in those from survey 2 in both regions  and cannot be rejected. This is not concluded for MLG32.Mating types (MAT-1 and MAT-2) were found in regions of Asturias and Galicia, whereas in País Vasco only MAT-2 was identified. The mode of reproduction in each geographic origin was estimated based on standardized index of association value  in two major groups, one of them including all the isolates of MLG32 found in both surveys and all regions (No differentiation between surveys or regions within surveys were shown by AMOVA on the clone-corrected data. All variation (100%) is explained within the regions suggesting Spanish entiated . All phientiated , but not regions . Minimum regions  corroborPairwise population comparisons of genetic diversity values (G’st index)  indicatep-value = 10−4). A significant correlation was found between isolates from País Vasco (PV) and either Galicia and Asturias  , but not between the populations of Asturias and Galicia in any of the two surveys , corroborating that population from PV is genetically differentiated from northwestern populations . No gene flow was detected between any of the subpopulations defined by survey and origin region. According to Bayesass  were the most abundant . Spore germination was also higher for the most common haplotype, and produced more spores at 20 and 25 °C.This situation confirms that MLG32 is a well-adapted haplotype as it was shown in previous studies  where soFusarium circinatum is inbreeding or goes under asexual reproduction, at least in this region. Only two VCGs were found in País Vasco, which contributes to a limited exchange of genetic information and maintenance of individual identity [Exclusive presence of MLG32 in País Vasco during these 10 years between surveys indicates identity . TemporaThe presence of a well-adapted haplotype together with evidence for clonality in País Vasco supports that MLG32 may have existed for some time and that this pathogen established first in this region, a hypothesis already suggested by Berbegal et al. . SymptomThe maintenance of the population genetics in two clusters during these 10 years between surveys supports the occurrence of clonality or inbreeding and the lack of sexual reproduction. AMOVA results on the whole population show that genetic variation is explained mostly by regions, but not by time, supporting the idea of clonal organisms. However, this structure does not appear when AMOVA is performed on the clone-corrected dataset. This discrepancy in the results is probably due to the small size of the population that results from correction and point out the importance that the clones have in the AMOVA analysis.Fusarium circinatum is structured (d)   and Psex surveys . Lack ofIn NW regions with a greater number of MLGs and VCGs, the occurrence and identification of heterokaryons is more likely as has been the case. Two isolates from the first survey, one from Galicia and other from a nursery in Asturias, have two microsatellite alleles per locus. These heterokaryons may have originated by anastomoses of hyphae or diploid selfing (processes not necessarily exclusive ). DetectFusarium circinatum in País Vasco, evidence of genetic changes was found when more intensive samplings were carried out. In an intensive sampling done in 2016 in a P. radiata plantation with symptoms of PPC, one new haplotype was detected by SSR marker analysis [Despite the genetic uniformity found in the population of analysis . Only 1 Fusarium circinatum are explained by the asexual reproduction, but also selfing at least to a lesser extent that leads to new haplotypes. The existence of haplotype MLG32 maintained on time and widely distributed across northwestern regions suggest its well adaptation to the environment and the host. Results showed that País Vasco is a region that after many years of the first disease outbreak in Spain remains clearly differentiated from other Northwestern populations. This fact was supported with no evidence of migration among regions. The low genetic diversity observed and lack of new haplotypes in País Vasco indirectly evidences that regulation within the EU territory to prevent pathogen spread is efficient. In conclusion, results presented here about the temporal and spatial variation of population structure of Spanish


Recent empirical studies on the division of labor in modern cities indicate a complex web of relationships between sectoral specialization of cities and their productivity on one hand and sectoral diversification and resilience on the other. Emerging scholarly consensus suggests that ancient urbanism has more in common with modern urban development than previously thought. We explore whether modern trends in urban division of labor apply to the cities of the Western Roman Empire from the first century BCE to the fourth century CE. We analyze occupational data extracted from a large body of Latin epigraphic evidence by computer-assisted text-mining, subsequently mapped onto a dataset of ancient Roman cities. We detect a higher frequency of occupation terms on inscriptions from cities led by Rome than from rural areas and identify an accumulation of tertiary sector occupations in large cities. The temporal dimension of epigraphic data allows us to study aspects of the division of labor diachronically and to detect trends in the data in a four centuries-long period of Roman imperial history. Our analyses reveal an overall decrease in the frequency of occupational terms between the first half and second half of the third century CE; the maximum frequency of occupational terms shifts over time from large cities to medium and small towns, and finally, rural areas. Our results regarding the specialization and diversity of cities and their respective impact on productivity and resilience remain inconclusive, possibly as a result of the socio-economic bias of Latin inscriptions and insufficient representativeness of the data. Yet, we believe that our formalized approach to the research problem opens up new avenues for research, both in respect to the economic history of the Roman Empire and to the current trends in the science of cities. Our current ability to evaluate socioeconomic development of past societies depends on a combination of three ingredients: access to relevant data, adoption of appropriate methods, and employment of sufficiently robust theoretical framework. In this article, we offer a novel mixture of these ingredients in an attempt to assess several aspects of the socioeconomic development of the Roman Empire. We employ ancient epigraphic evidence, methods of computational text analysis and Monte Carlo simulations and theoretical insights on scaling of cities to answer questions such as: What is the structure of the Roman labor force across individual cities and the Empire? How does division of labor evolve over time? How does occupational specialization and diversification differ from city to city?social reactors [The human experience with urbanism covers approximately 7,000 years , during reactors –5. The hreactors . NowadayIt is indisputable that the ancient cities share many key futures with their modern counterparts. For instance, recent research on urban scaling has identified the same scaling properties in the relationship between a city’s area and its population size . These sOne of the intriguing questions that concerns the dynamics of cities across different historical contexts touches on the relationship between the specialization and diversity of a city on one hand and its resilience and productivity on the other . FollowiIt is now generally accepted that the socio-economic performance of the Roman Empire during the first two centuries CE was higher than during the periods which preceded and which followed –17. SomeTo assess the dynamics of labor division in the Roman Empire, we first employ computational text analysis methods to identify and extract all instances of occupations in a dataset of ancient Latin inscriptions, using an newly aggregated extensive list of Latin occupational titles –31. SecoInscriptions survived in large quantities, containing valuable information about cultural norms, social structure and demographic distribution of people involved in commissioning inscriptions. The rate of survival of inscriptions certainly poses a challenge for any quantitative analysis as inscriptions on durable materials such as stone or metal were often reused or repurposed. Yet the surviving 500,000 Latin texts contain a substantial amount of information, ranging from textual references to Roman society and economy to temporal and geospatial indicators –35. InscA shared trait among the Latin inscriptions is the tendency to advertise someone’s social status. Public declaration of one’s achievements permeates this medium, focusing especially on political, administrative, military function, or the status of citizenship. Status display flourished particularly in the urban environments which offered higher social mobility , 38, 39.Data preparation consisted of extracting and categorizing occupation data from the text of inscriptions and linking inscriptions with the buffers of ancient urban zones. This way we generated a dataset of inscriptions with attributes characterizing their urban context and a dataset of cities with attributes capturing occupational information as well as urban characteristics.N = 136,190) [N = 500,618) and Epigraphic Database Heidelberg . However, LIRE contains only those inscriptions from EDCS and EDH that satisfy the following criteria: (1) records contain valid geospatial coordinates, (2) coordinates fall within the boundaries of the Roman Empire at its largest extent in 117 CE, (3) metadata contain the most plausible date of creation , and (4) date of an inscription intersects with the timespan of the Roman Empire (arbitrarily set to 50 BCE through 350 CE).The study is based on a recently published dataset of Latin inscriptions of the Roman Empire  . LIRE isThe content of EDCS and EDH partially overlaps. The LIRE dataset contains 83,482 inscriptions originating exclusively from EDCS, 3,907 inscriptions originating exclusively from EDH and 49,916 inscriptions shared by the two resources. The records from EDCS are accompanied by 29 attributes containing metadata while the records from EDH have 74 attributes. Some of the attributes overlap and can be easily mapped between the two resources, like numerically expressed geographic coordinates. In the case of other attributes, like the type of inscription, the mapping is much less straightforward as the two databases use different classification schemes (see ). For inTo some extent, EDCS and EDH differ in their overall spatio-temporal coverage. EDCS is more comprehensive, covers a broader spectrum of epigraphic production and also systematically reflects the magnitude of inscriptions generated by the city of Rome. EDH, on the other hand, contains only a sample of inscriptions from the city of Rome, but offers a uniformly distributed, high-quality and metadata-rich dataset covering the western Roman provinces . By comThe fact that we focus on Latin inscriptions implies that our analysis is mainly applicable to the western part of the Empire, where Latin was the dominant language , 46, 47.To enrich the inscription data with urban attributes and nearest city population size, this study employs the database of cities collected by Hanson as the most comprehensive analysis-ready dataset . The datlarge cities, i.e. cities with population estimate equal to- or higher than 30,000 inhabitants , and small cities, i.e. cities with population lower than 1,000 inhabitants . By default, in most of our analyses, we include Rome  among large cities, together with significantly smaller cities, such as Lepcis Magna , Carthago , or Londinium . However, in some cases we also offer supplementary analyses either treating it separately or excluding it completely .Drawing on the population estimates, we divide the cities into three groups: large, medium, or small). In cases where an inscription is in the buffer of more than one city, the larger one is preferred. Inscriptions not covered by these buffers were classified as coming from rural areas.In the next step, we focus on the neighborhood of these cities which we define by circular euclidian buffers with a 5 km radius. The 5 km distance roughly corresponds to one hour of walking, what has been observed as a mean traveling time per day cross-culturally . It has Drawing on the list of western provinces from , we furtTo gauge ancient Roman labor division on the basis of inscriptions, we manually created a list of Latin terms for occupations and their known spelling variants (N = 882) see . We thenAs a result, we obtained a list of all mentioned occupations for each inscription that allowed us to calculate the total number of occupations of any type within any group of inscriptions and weight it by the total number of inscriptions or words within the group (i.e. their relative frequencies).p-value using the following equation:N is the number of bootstrapping cycles and p1 is the proportion of bootstrap cycles for which the value for group 1 is higher than the value for group 2 or vice versa .N = 10) [N = 14) [sensu [Each occupation on the list of Latin terms for occupations has been also classified according to two classification systems: The Historical International Standard Classification of Occupations (HISCO) categories (N = 10)  and a cl[N = 14) . HISCO r[N = 14) . Althoug[N = 14) –60. On t[N = 14)  focus on) [sensu ). They r) [sensu , 61. In N = 33,920) of all inscriptions are dated by interval with duration equal to 100 years and almost 13%  of all inscriptions by interval with duration equal to 200 years . But there is also a substantial amount of inscriptions which lack such references and might be dated only very roughly, with reference to half-century, century, or even longer historical periods. This varying precision might be numerically expressed by an interval delimiting the earliest and the latest year during which an inscription is assumed to be produced. In the case of LIRE, almost 25%  approach introduced by  and implThe temporal distributions of the time-series simulations are then analyzed in several different ways. First, we explore the data visually by means of cumulative gaussian kernel density estimate (KDE) plots, with each time-series simulation represented by one KDE line. The bandwidth of the KDE is calculated automatically on the basis of Scott’s rule . This alAs an alternative method, we analyze the time-series simulations using prespecified timeblocks. We work either with 50-years-long timeblocks or with time blocks based on reigning dynasties. This allows us to combine the analysis of temporal distribution of inscriptions with an analysis of their language content and to statistically compare the data from one period to another. The method works as follows: For each time-series simulation, the whole dataset of inscriptions is divided into subsets based on prespecified timeblocks. The subset of inscriptions within each timeblock is slightly different from one time-series simulation to another, because the random dates assigned to individual inscriptions often come from a dating interval longer than one timeblock. Thus, in one time-series simulation, an inscription dated to the second century CE (101 CE– 200 CE) is included among inscriptions from the first half of the second century, in another simulation it is included among inscriptions from the second half of the second century. Next, within each timeblock, the subset of inscriptions is used for further measurement, e.g. the total number of words or a frequency of certain words. The robustness of the results might then be evaluated by comparing them across the simulations. Larger variance of the measurement within one timeblock across the simulations implies higher extent of temporal uncertainty in the underlying data and therefore mitigates the possibility to make strong inferences concerning differences between timeblocks.The timeblock analysis is further combined with the bootstrapping method described above. In this case, each time-series simulation is used to retrieve one bootstrap sample per timeblock.Finally, in some cases we also employ a two-sample Kolmogorov-Smirnov test to compare distributions of any two time series. This way we compare the temporal distribution of all inscriptions containing mentions of occupations with a random sample of inscriptions of the same size. We repeat this procedure for multiple time-series simulation combinations and then report the mean values.After the exploration of labor division in the Roman Empire through time, we quantify the composition of occupational activities linked with individual cities. To measure specialization and diversity of ancient Roman cities, we constrain our attention to cities and inscriptions from the western part of the Empire, for which the epigraphic dataset is considered to be more representative . Since the dataset of cities and the dataset of inscriptions have been mapped on each other, for each city we can easily obtain a list of all occupations appearing on inscriptions from its neighborhood. These lists of occupations for each city are finally used to measure their specialization and diversity.i), we first count the number of occupations in each occupational category (j) and its share (S) in the total number of occupations from a given city. Subsequently, we extract the share of the largest sector, defining absolute specialization index of each city (ZIi) such as:Drawing on standard approaches , we haveZIi returns unrealistically high specialization values. For instance, a city with one occupation in total has a higher ZIi value than a city with ten occupations in total with nine of them from one sector. But we would hesitate to say that the first one is more specialized than the second one. Instead, we recognize that the occupational data extracted from the inscriptions capture only a very small sample of occupations from a given city. To deal with this limitation of our occupational data, we modify the ZI score by multiplying it by the natural logarithm of the total number of occupations in a given city (Ni). Thus, we define weighted specialization index (ZIwi) such as:Unfortunately, our dataset includes a number of cities for which we have only one occupation documented, and consequently also only one occupation category. In such cases, RZIwi), which divides the share of each sector in the city by its dataset-wide share:For our dataset, this measurement appears to be a useful indicator of a city’s specialization. However, it is not sensitive to the fact that the sectors are distributed unequally over the occupational data and that some sectors have locally a bigger share because they are globally more widespread. To control for this factor, we have further implemented a weighted relative specialization index , followed by faber (N = 566) and medicus (N = 252). At the opposite end, there are 137 occupations occurring only once , horrearius (a superintendent of a storehouse)) and Miscellaneous Services sectors (such as medicus (a surgeon), mensor (a land surveyor), or unctor (an anointer)). In comparison to other urban contexts, Miscellaneous Services appear to be most common in large cities where the demand for specialized skills and services is higher [per se and the occupational pride connected with jobs in agriculture and other food production might have been relatively low, leading to its limited epigraphic footprint [Next, we made an exploratory analysis comparing the distribution of occupations grouped by industry types. For this analysis, we calculated the number of individual occupation types per 1,000 inscriptions and plotted the results by means of a stacked bar plot . The anas higher . Educatis higher . But we ootprint . Again, We have also rerun the same analysis while employing the occupation classification system of the HISCO major groups see . We see M = 4.28), followed by medium cities (M = 4.74), small cities (M = 4.93) and rural areas (M = 5.36).All HISCO major groups have a numerical code ranging from 0 to 9 expressing the level of required skills to perform the job . Thus, the mean value of HISCO groups of all occupations within an urban context informs us about the extent of skilled labor within the urban context in the way that lower average value indicates a higher extent of skilled work. We find the lowest value in large cities  . InteresBefore we delve deeper into an analysis of temporal distribution of occupational data, we first look at temporal distribution of the LIRE epigraphic dataset as a whole. When we look at the subplots A and B, we see that—according to this dataset—the production of inscriptions takes off in the middle of the Julio-Claudian era and the volume remains high until the Severan dynasty. The absolute peak in the production of inscriptions falls into the reigns of emperors Trajan (98–117 CE) and Hadrian (117–138 CE) during the Nerva-Antonine dynasty (96–192 CE). We further observe that there is a long-term decrease in the epigraphic production starting with the Severan dynasty and continuing throughout the crisis of the third century. Subsequently, the decrease continued during the Tetrarchy and the reign of Constantine (285–337 CE), but at a slower pace.However, when we look at the lower two subplots (C and D), the overall picture becomes more complex, as we see that the dynamic differs substantially depending on urban context. Inscriptions from the urban context of large cities peak in number in the first half of the first century, while inscriptions from medium cities reach maximum values approximately half a century later, in the second half of the first century CE. In the case of small cities, we observe a linear increase through a two-century-long period starting in the first half of the first century CE and culminating during the first half of the third century CE, i.e. two centuries after large cities. The temporal distribution of inscriptions from rural areas appears to be most similar to the temporal distribution of inscriptions from small cities, with the highest values spanning the first half of the second and the first half of the third century CE.The previously described decline in epigraphic production in the early third century deserves a more nuanced interpretation, too. The number of inscriptions in large and medium cities decreases well before the advent of the third century; in the case of large cities, before the middle of the second century. The epigraphic production in small cities and rural areas, however, flourishes well into the third century. The production in small cities, in fact, peaks during the early decades of the third century.Taking these observations together, our findings support a common claim that the “epigraphic habit” first became widespread in large and medium cities and only subsequently has been adopted by small cities and in rural areas, approximately one century later , 34. AccAs we have already seen, the occupational terms are distributed unequally through the epigraphic data, being more frequent on inscriptions from cities than on inscriptions from rural areas. In what follows, we offer a similar analysis with respect to temporal distribution of occupations.On KS statistic = 0.1891, avg. p<0.001) and small cities . In the case of large cities, as seen on subplot A, the difference between the target subset and the control sample is most remarkable during the first half of the first century, when the kernel densities of the time series based on the target subset of the data are well above the curves produced by time series of the control samples. This rise in the frequency of occupations is contemporary with the labor-intensive Julio-Claudian building program, which gave rise to monumental Rome and Italian cities, employed a large number of people, and likely prompted various new professions [Upon a visual inspection of fessions .M = 20,922.57) inscriptions dated to the first half of the first century CE. From these inscriptions, approximately 35% have been located in large cities and 33% have been located in the city of Rome alone. In sum, the inscriptions from the city of Rome from the first half of the first century CE represent approximately 5% of the whole LIRE dataset. In these 5%, we have identified between 483 and 588 occupation terms (M = 546.26), depending on the sample and its source time series. It is more than 10% of all occupation terms  identified across all periods and urban contexts.M = 60.93), than during the preceding timeblock (M = 35.49). The bootstrap test indicates that this difference is statistically significant (p = 0.03), but the effect size is relatively small (Cohen’s d = 0.07).The subplot C is based on a combination of data from subplots A and B. It depicts the frequency of occupational terms in random samples of 1,000 inscriptions from a given urban context. First of all, while in the case of large and small cities the frequencies of occupational terms visibly differ from timeblock to timeblock, in the case of medium cities and rural areas, the frequencies tend to be almost constant. For instance, there are almost twice as many occupational terms per 1,000 inscriptions from small cities in the first half of the second century CE . We see that the frequency of occupation terms on samples of inscriptions from the second half of the second century CE is approximately the same as the frequency on samples from the first half of the first century CE. This serves us as a warning against putting too much emphasis on observations based on raw counts as seen in subplots A and B: raw counts have to be always compared with frequencies.p = 0.03, Cohen’s d = 0.09), probably due to the temporal uncertainty of the underlying data. Upon a visual comparison of subplots A and C, the decline in occupation-term frequencies may to some extent correlate with the overall decline in the number of inscriptions in the dataset. However, the decline in the number of inscriptions starts first and the decrease in the frequency of occupational terms follows with certain lag. This might be associated with the complex relationship between economic productivity and resilience of cities on the one hand and their sectoral diversification and specialization on the other.The last observation based on the temporal distribution of occupations we want to elaborate is concerned with the overall decrease of occupation-term frequencies between the first and second half of the third century CE. We see a decrease of the raw counts of the occupation terms (subplot B), but also their relative frequencies (subplot C). This decline is visually detectable across all four urban contexts. However, according to the bootstrap test, only the large cities provide statistically significant results , we narrow our analysis to cities from the western part of the Empire, where the Latin inscriptions serve as a more representative proxy.From the 1,388 cities in the dataset, 889 are located within the western part of the Empire. 723 of the western cities are associated with at least one inscription, and 360 cities are associated with inscriptions containing at least one occupational term. In total, these 360 cities accommodate 3,250,628 inhabitants, which represent approximately 60% of the estimated urban population of the western part of the Empire and 32% of the estimated urban population of the Empire as a whole. The subsequent analysis focuses on this subset of 360 cities.N = 5,222).Concerning the epigraphic data, 125,640 (92%) of the 136,190 inscriptions in the LIRE dataset are of western provenience. From these, 96,997 inscriptions are associated with the previously mentioned 889 western cities and 91,757 inscriptions are associated with the 360 cities for which we also have at least one occupation term (extracted from the inscriptions). Thus, the subsequent analysis relies on 91,757 inscriptions, representing approximately 67% of the LIRE dataset. These 67% of inscriptions contain 4,267 occupation terms, representing approximately 82% of the total number of occupation terms extracted across east and west  and Casinum , with the estimate of 1,000 inhabitants and comparatively much smaller numbers of inscriptions and occupational terms.As explained in the Methods section, specialization measures the extent to which occupations associated with a city are accumulated within one particular occupational sector. In our case, we use the sector division of individual occupations inspired by Harris . Table 1curator, the most common occupation overall, sometimes with individuals having multiple curator titles on one inscription  located about 30 kilometers northeast of Rome, with 52 occupational terms dispersed across the 235 inscriptions in the LIRE dataset. The high extent of specialization of the city is driven by the fact that 31 of the occupations are from the Managerial sector. Upon a closer inspection of the data, we see that the most common occupation in Tibur is tion see : e.g., s in Rome ).agrimensor (a surveyor) on one inscription (EDCS-22400457)  located in the fertile plain of the Guadalquivir River. The high specialization rank of this small city is caused by eight identified instances of 457) see . The refargentarius, assigning the Metal-Working specialization label to this coastal Roman military camp with an associated settlement. Archeologists have discovered five inscribed lead ingots at Petuaria, each weighing around 90 kg, and proposed a connection between the Yorkshire and Derbyshire ore-fields and the export of the processed ore via the Petuaria harbor [Petuaria  is with 1,000 estimated inhabitants the smallest settlement among the most specialized ten. With only seven dated inscriptions, five contain a reference to an a harbor .tignuarius and dendrophoros) [A number of cities  on the top-ten list are old Italian cities and some of the earliest colonies of the Roman Republic. Located within a 30 to 60 km radius of the metropolis on the slopes of the Apennines, the spatial proximity to the largest market in the Mediterranean likely fostered their functional specialization which is dominated by curatorial services and the timber industry (ophoros) .DI score. Again, we encounter Rome among the top ten cities. It should not surprise us, since specialization and diversity are not exact opposites–a highly specialized city can maintain a substantial level of diversity as it has a broad base of crafts and industries [Turning to diversity, dustries . HoweverDI score is Capua , located in the fertile Campanian plains and connected with Rome through Via Appia, with 46 occupations dispersed over 13 industry sectors. The high score of this metric indicates not only that there is a substantial number of sectors covered, but also that the sectors tend to be relatively equally distributed in this city when compared with other cities with a similar number of occupations and sectors. In Capua, there are seven sectors with at least four occupations (see unguentarius), or clothing [The city with the highest ions see . Capua wclothing .DI score cities. Despite its small size, Pisae was an important trading center with vibrant sea-born commerce evidenced by the remains of 31 ships with cargoes of fruit, olives, wine and sand, from the second century BC to the seventh century CE [collegium fabrum navalium Pisanorum, a professional organization for ship builders, as well as evidence for timber industry located in Pisa (fabri tignarii Pisani) in the second century CE (EDCS-20402907) and numerous other professionals such as merchants, winemakers, goldsmiths, and dramatists  located at the mouth of the Arno river is the city with the smallest population among the top ten ntury CE , 72. Theists see .DI, we have also implemented DIw, which attempts to be more sensitive to the divergent sizes of occupational data . In the case of RZIw the association is even weaker . In other words, the relationship between our specialization measurements and the epigraphic data which have been used for their calculation is negligible.For the dataset of Western cities, we have evaluated statistical relationships between various combinations of variables. Taking into consideration its exceptional size, the city of Rome was excluded from these analyses as an outlier. DI score than for a city with few extant inscriptions. Indeed, there is statistically a rather strong relationship between the number of inscriptions and the DI score . The relationship is even stronger when the number of inscriptions is logarithmically normalized . Technically, we can eliminate this relationship by employing the DIw score. But, as has been said before, we are not fully satisfied with its outcome, assigning high values to cities with very low numbers of inscriptions. Duranton and Puga [DI score there is still one small city (Pisae) and several other cities with less than 10,000 estimated inhabitants.The association between the number of inscriptions and the extent of diversification remains stronger. For obvious reasons, for a city with a higher number of inscriptions is comparably easier to have a high and Puga  assert tFurther, we have made an attempt to explore the linkage between specialization or diversity of cities and their economic productivity or resilience. As a proxy for a city’s resilience, we calculated the ratio of inscriptions produced before and after 235 CE: a higher proportion of inscriptions produced after 235 CE is here interpreted as indicating higher economic resilience of a city in face of the third century crisis. Drawing on recent empirical studies of modern urban systems –12, we hHowever, in our data, we were not able to detect any statistical association between the two respective variables. These results do not necessarily mean that the link between sectoral diversity of cities and their resilience was missing in Roman antiquity, since the results can also be caused by inappropriate operationalization of the two factors or poor quality, insufficient representativeness of the data. Perhaps an assessment of economic prosperity versus resilience of ancient Roman cities might be possible via other archeological evidence, but that falls outside the scope of this paper.We have also compared our results with results from . The autr = 0.69, p<0.001, see DI variable . Thus, it is evident that the results of the two studies are compatible, at least to some extent. However, the authors of [First of all, our comparison reveals a relatively strong correlation between the number of associations listed in  and usedthors of  further thors of  and the Undertaking quantitative analysis with historical datasets poses methodological and interpretive challenges. We rely on data extracted from a subset of surviving monuments, whose content maps poorly to modern terminology and is far from an unbiased and statistically sound sample. We interpret the results using modern urban economic theory under the assumption that it applies to ancient urban environments , 32, 33.To extract the occupational data, we use a computer-assisted but to some extent manual method. Latin is a morphologically rich language. In such a case, many common computational text analysis methods require the language data to be morphologically preprocessed, ideally representing individual words in their dictionary-like (lemmatized) form, otherwise repeated occurrences of the same word cannot be detected. However, considering the fact that the language of inscriptions is highly formulaic, with missing sentence division, and full of alternative spellings and inconsistent word-order in compounds, the standard machine-learning models for lemmatization (pre-trained on Latin literary texts) do not perform well. The combination of a manual approach with rule-based computer processing gives us more control over the detection of desirable occupation terms, but the results are still far from being perfect, prone both to false-positives and false-negatives. While our coding sheets usually included several spelling variants of an occupation, we might have missed variations that we had not thought of. Our spot checks revealed minor issues where the occupation spelling did not fit our expectations and at least one occupation  was misinterpreted. Over repeated iterations of the extraction process followed by a manual check of a sample of data we increased the number of detected occupations by 30%.negiotiatores in Lugdunum [negotiatores in Lugdunum in our spatiotemporally-constrained dataset. While our filters are necessary in order to model the evolution of labor division in the Roman West through time, the study of urban sectoral specialization and diversification could be rerun on an unfiltered dataset including undated inscriptions.It is likely that we did not detect all occupational terms in the 136,190 qualifying inscriptions. Out of the 882 unique occupations in our list, only 387 were detected in the LIRE dataset. The remaining 495 occupations are missing because they either do not occur in the LIRE dataset (originating instead from papyri or other sources), occur there in a different form, or occur in inscriptions that lack temporal or spatial data, which were excluded from the source dataset. Our counts will therefore differ from studies that include undated inscriptions, such as Verboven’s list of 22 inscriptions with Lugdunum . We detefaber (a worker), covering a range of occupations from a silversmith to shipbuilder. Among the 666 instances of faber, 566 had no modifier and were assigned to an Undefined category, while 100 had a specifying modifier (e.g. faber argentarius) and were categorized following Harris. Further, modern standards for industry sectors capture poorly the multifaceted nature of ancient occupations. The HISCO database, for example, separates production from trade, while ancient practitioners engaged in both simultaneously [Our measures of sectoral specialization and diversification in cities rest on several interpretive steps. Firstly, we identify unique professions on the basis of lists of occupations compiled by –31 and maneously . In suchExploring labor division through time, a question arises. Does the increase in the number of unique occupations per 1,000 words mean an actual change, ie. a more differentiated labor force and an increasing number of professions, or is it merely a rhetorical change and a delayed manifestation of a fairly static labor force situation in the epigraphic medium? One could explain the temporal trend of growing frequency of occupations per 1,000 words as marking an ideological shift and a culture change as Roman society begins to recognize and value the societal contribution of tradesmen and professionals over the previous ideology that valued inherited status.The first consideration of urban specialization and diversity concerns source data. Our results are based on a series of inferences and proxy data ranging from archeology-derived population estimates to fragmentary propaganda texts rather than systematic samples or Bureau of Labor census data. Our assessment of sectoral specialization and diversity thus hinges on coordinated actions and personal incentives of a series of individuals rather than directly reflecting actual functional diversity of entire ancient urban communities. We measure the reality that has percolated into epigraphic evidence, survived, was documented, digitized, and passed our quality checks.DI and ZIw results suffer from an obvious shortcoming: collation in time which can have the following consequence. A city that was highly specialized at any given time but whose dominant sector shifted over time (e.g. from mining ores to producing and trading cloth) would through collation of occupations across multiple sectors appear as diversified. Our approach thus potentially inflates sectoral diversity and reduces sectoral specialization. Under ideal circumstances, we would have enough inscriptions to divide them into smaller 25-year timeblocks and generate indices on the basis of contemporaries. While we can divide the dataset, the resulting numbers will be so low as to be meaningless. Mindful of the risk of generating more diversity than there actually was, we can rest assured that the index of specialization is solid.The second consideration is also a caveat. DI and ZIw measures, both contain reasonably well-excavated cities with large collections of epigraphy , continually occupied sites  or old Italian cities whose long use span holds the promise of well established “epigraphic habit”. The ZIw list, however, shows relatively low two-digit numbers of occupations per city with the exception of Rome and Tibur. The DI list has high two-digit occupation numbers, but again, only Rome and Ostia are in the three and four-digit range. Many cities in the DI list are harbors, which fits the expectation that multiple sectors would coexist in a central node in a transport network. Cities in the specialized list have more idiosyncratic geographic settings, but show some historical commonality with Italian cities and Managerial sector dominating, a situation that is hardly unexpected in the heartland of the Empire. The cities in each list nonetheless need to be taken with a grain of salt, as the custom of committing one’s achievements to stone and the preservation rate of epigraphic monuments may have varied considerably from one urban context to another. The indices of specialization and diversification remain mere heuristical proxies, highly dependent on the quality of the underlying data. As such, instead of employing them to conduct large-scale comparative studies, they might be more useful as starting points for archeological and historical investigation of economic growth and decline in the respective cities during the third and fourth centuries CE.Looking at the top-ten lists in both Inscriptions are traditionally considered an urban phenomenon. On the example of Latin inscriptions in the LIRE dataset that contain both date and spatial information, we have confirmed this to be true only partially. The large cities with the largest size of occupations, such as Rome or Ostia, confirm an early onset of publication of inscriptions, while mid-sized and small cities lag behind. Against all expectations, we have discovered that the famous Severan peak (193–235 CE) in the production of Latin inscriptions was driven mostly by small cities and settlements in the rural area. Occupations follow similar patterns, appearing first in larger cities at the time of Imperial building programs, while in the late second century most occupational evidence comes from smaller settlements and even rural areas. Whether that might be caused by increasing urbanism within the Empire or cultural norms spread by the merchants or army deserves further investigation.Taking a comprehensive dataset of Latin inscriptions and a fully transparent and scripted set of methods, we were able to explore ancient urban dynamics through the prism of modern urban economics. We mapped the occupational data extracted from epigraphic evidence onto urban contexts differentiated by population size and classified them by labor sectors in order to assess the sector ratios and the dependence of different professions on specific urban contexts. The results correspond to our expectations for tertiary sector expansion in larger cities. We then zoomed further to the level of individual cities, constructing employment profiles from all recovered inscriptions and translated these into weighted measures of sectoral diversity and specialization. However, the results of our measurements evade easy interpretation. While cities with high diversity index show some shared patterns such as being trading hubs or harbors, cities with high sectoral specialization require case by case review of geographic setting, epigraphic and archaeological evidence to interpret which sector dominates and why. Our analyses concerning the impact of these indices on productivity and resilience of cities remained inconclusive. It becomes obvious that our measures need to be taken as a rough guide and with a grain of salt as their reliability and representativeness suffer from the collation of highly fragmentary evidence. Thus, it appears that an appropriate interpretation of the results of our quantitative analyses requires a continuous dialogue between the “distant reading” and “close reading” approach to the sources.S1 Data(CSV)Click here for additional data file.S2 Data(CSV)Click here for additional data file.S3 Data(CSV)Click here for additional data file.S4 Data(CSV)Click here for additional data file.S5 Data(CSV)Click here for additional data file.S6 Data(CSV)Click here for additional data file.S7 Data(CSV)Click here for additional data file.S8 Data(CSV)Click here for additional data file.S9 Data(CSV)Click here for additional data file.S10 Data(CSV)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.S5 Fig(TIF)Click here for additional data file.S6 Fig(TIF)Click here for additional data file.S1 File(TXT)Click here for additional data file.