Castanopsis hystrix is a valuable native, broad-leaved, and fast-growing tree in South China. In this study, 15 phenotypic traits and 32 simple sequence repeat (SSR) markers were used to assess the genetic diversity and population structure of a natural population of C. hystrix and to construct a core germplasm collection by a set of 232 accessions. The results showed that the original population of C. hystrix had relatively high genetic diversity, with the number of alleles (Na), effective number of alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), Shannon’s information index (I), and polymorphism information content (PIC) averaging at 26.188, 11.565, 0.863, 0.897, 2.660, and 0.889, respectively. Three sub-populations were identified based on a STRUCTURE analysis, indicating a strong genetic structure. The results from the phylogenetic and population structures showed a high level of agreement, with 232 germplasms being classified into three main groups. The analysis of molecular variance (AMOVA) test indicated that 96% of the total variance was derived from within populations, which revealed a low differentiation among populations. A core collection composed of 157 germplasms was firstly constructed thereafter, of which the diversity parameters non-significantly differed from the original population. These results revealed the genetic diversity and population structure of C. hystrix germplasms, which have implications for germplasm management and genome-wide association studies on C. hystrix, as well as for core collection establishment applications in other wood-producing hardwood species. Information on genetic diversity is important for understanding the extent of genetic variability in existing plant material and the breeding and conservation of genetic resources ,2. HowevCryptomeria japonica [Robinia pseudoacacia [The collection and preservation of germplasm resources are of great significance to genetic improvement, new variety breeding, and germplasm innovation of forest trees . Brown ,8 and Frjaponica  and Robidoacacia . Recent doacacia ,19,20,21Castanopsis hystrix is an evergreen broad-leaved tree in the Fagaceae mainly distributed in Guangdong, Guangxi, Fujian and other southern provinces of China. It is widely used in furniture, construction, and shipbuilding due to its fast growth and good adaptability to various materials. C. hystrix has been identified as a precious species in the Guangdong province. Since 1999, Guangdong has continuously collected germplasm materials of C. hystrix from different habitats. Aimed at developing effective and efficient conservation practices for plant genetic resources, understanding the genetic diversity between and within the population is important [C. hystrix. In the past, molecular markers, i.e., random amplified polymorphic DNA (RAPD) [C. hystrix resources. Molecular markers provide a powerful tool for genetic diversity analysis and core collection establishment. Of the marker types, SSR markers consist of 2–6 bp nucleotide repeat motifs, which are considered to be one of the most effective molecular markers for studying genetic diversity. Its codominance, abundant polymorphism information, and genomes specify and show a fairly even distribution over the genome [C. hystrix, and there is no relevant research on the construction of a C. hystrix core collection.mportant ,23,24. Amportant . The anaA (RAPD)  and inteA (RAPD) ,28,29 hae genome . SSR mare genome ,32,33,34C. hystrix accessions from 17 provenances were analyzed using 32 SSR markers distributed throughout the C. hystrix genome and using 15 phenotypic traits in the whole distribution area. Our objectives were to estimate the levels of genetic diversity and to characterize the population structure of the C. hystrix germplasm collection. The results are intended to provide a molecular basis for understanding C. hystrix genetic diversity, effectively preserving and utilizing C. hystrix germplasm resources, which provide better materials for C. hystrix breeding and ensure the population inheritance of important traits.In this study, to ascertain the genetic diversity and population structure and to construct a core collection, a total of 232 C. hystrix Genetic Improvement Research Collaboration Group, composed of the Guangdong Academy of Forestry and other institutions, has systematically investigated, selected, and sampled superior trees from 17 provenance areas with relatively concentrated distributions of C. hystrix germplasm resources according to the distribution of existing C. hystrix resource. Furthermore, the group has also carried out the collection of C. hystrix germplasm resources. Superior trees were selected by the method of five dominant trees, and one tree was selected for every 30–50 m. The number of superior trees selected from each producing area was generally 10–30 trees according to the distribution area. After selecting excellent trees, we collected seeds and the sunny branches of the specific year in the south side of the middle and upper part of the crown from October to November 2001. After sending them directly to the grafting site, 30–50 plants were grafted on each excellent tree. The grafted trees were transplanted in the gene bank in the spring of 2003, and five plants were planted in each excellent tree; the plant row spacing was 3 m × 5 m, and the size of the hole was 60 cm × 60 cm × 40 cm.The germplasm gene bank was established in 2003. Since 1999, the C. hystrix were mainly collected from the whole range (C. hystrix germplasm gene bank (113° 46′ E and 23° 29′ N), Baiyun District, Guangzhou City, Guangdong Province. From November to December 2018, 3 trees were selected for each clone, and 15 phenotypic traits were investigated, including 5 growth traits, 2 morphological traits, and 8 wood properties ) was used for data visualization. Additionally, to analyze the relationships of the 232 germplasms, a genetic distance matrix between the clones was generated, and an unrooted phylogenetic tree was constructed using the neighbor-joining method in PowerMarker 3.25 software [An analysis of molecular variance (AMOVA) test was carried out to determine the relative partitioning of the total genetic variation among and within different groups of genotypes by using GenAlEx 6.5. The principal coordinate analysis (PCoA) was also performed using GenAlEx v6.5. The genetic structure of unique genotypes was investigated using STRUCTURE v2.3.4 software  using ansoftware .QGAStation v2.0 software was used to construct the core collection based on phenotypic data, combining three systematic clustering methods , two genetic distances , three sampling methods  and seven sampling ratios  .t-test was used to analyze the significance of differences in genetic diversity parameters between the core collection and the original collection [Core Finder v1.1  and Corellection . If the C. hystrix had a high level of diversity. The average polymorphism information index (PIC) was 0.889, ranging from 0.744 to 0.958. According to the standard of PIC ≥ 0.5 [C. hystrix populations. The results showed that the genetic diversity of these SSR loci was generally high, and the highest genetic diversity was SSR04 while the lowest genetic diversity was SSR10, observed by combining the values of each genetic parameter.A total of 335 alleles were detected by 32 polymorphic microsatellite markers, with an average of 10.458 alleles detected at each locus, among which 15 alleles were detected at the SSR04 locus. The alleles of SSR02, SSR10, SSR15, SSR18, SSR23, and SSR27 were the same and least, having only eight alleles . The aveIC ≥ 0.5 , all of C. hystrix populations, the genetic parameters, containing Na, Ne, Ho, He, and I were calculated, respectively  was identified based on the maximum likelihood and DK values; the results showed that the DK value reached the highest when K = 3, which indicated that the whole population was divided into three subgroups . The thrC. hystrix germplasms to visualize the relationships between genotypes. A three-dimensional graph was created based on the value of each sample in the first (PC1), second (PC2), and third (PC3) principal components , and an AMOVA analysis of molecular variance , whereas 4% of the variation was between populations.In order to understand the level of genetic differentiation and reflect the source of variation among variance  was perfUsing QGAStation software to construct core collection based on phenotypic data, a total of 126 core collections were constructed. Among the 126 core collections, three with CR < 80% were removed ; three ct-test results showed that the six genetic diversity parameters of core collection Mc1 and Mc2 were not significantly different from those of the original collection, indicating that both core collections could be a good representation of the original population. Based on the values summarized in both Core Finder software was used to analyze the SSR data with the M strategy based on the principle of maximizing alleles. The core collection Mc1 having a sample size of 158 retained 100% of the allele number of the original collection and had increased genetic parameters ; thus, Mc1 with its strong genetic diversity should be a good representation of the original collection. In addition, Core Hunter 3 was used to determine the optimal size of the core collection using 10 preset sampling ratios . The sixFinally, a total of 157 clones were obtained by combining the phenotypic core collection (B2C3D3-15) and molecular core collection (Mc1) into the final core set (BM). In order to check if the BM could effectively represent the genetic diversity of the whole germplasm, a principal coordinates analysis (PCoA) was used to generate a distribution map of the core and original collection with SSR data . The resPinus leucodermis, Eucalyptus globulus, Swietenia macrophylla, and Populus deltoides [Characterizing breeding collection germplasms is crucial in plant breeding as the genetic advancement of economically valuable traits relies on the genetic diversity available within the breeding gene pool. Learning about genetic diversity also assists in minimizing the use of closely related clones as parents in breeding programs. Genetic diversity is an integral part of all biological diversity; it is the basis of biological evolution and species differentiation and is of great significance for population maintenance, reproduction, and adaptation to habitat changes. The higher the genetic diversity, the more likely a population is to adapt to different environments, and variations in DNA sequences are the primary drivers of such diversity . Moleculeltoides ,52,53,54eltoides ,56. SSRseltoides  or phenoeltoides . ConsequC. hystrix is a precious local wood and an efficient multi-purpose fast-growing tree species in South China. Genetic diversity, population structure, and molecular markers knowledge may accelerate the selection of desirable traits in C. hystrix. Nei’s gene diversity, the observed heterozygosity and expected heterozygosity, the Shannon–Wiener index, the polymorphism information content, etc., have all been used to evaluate the level of genetic diversity of plant species [Xanthoceras sorbifoliai, and higher PIC and genetic diversity scores were reported in studies using SSRs [C. hystrix populations, the P2 population  had the highest genetic diversity, while the P13 population  had the lowest genetic diversity. The genetic diversity of the P13 population was significantly lower than that of the other populations, which may be due to the small number of samples. As previously demonstrated, the SSR assay approach is appropriate for genetic relationship studies [C. hystrix and identification of its populations in China. species . The hig species ,59 as we species ,61. In o species . This reing SSRs . Accordi studies ,64, and C. hystrix germplasm at the genomic level, the SSR data of 232 germplasms, STRUCTURE analysis, UPGMA cluster analysis, and PCoA analyses were used to thoroughly investigate the genetic structure of C. hystrix. Based on the SSRs and multiple analyses, including population structure and phylogenetic analyses, it was confirmed that the within population was clearly clustered to three groups, which is more than previous studies using SSR and ISSR molecular marker analysis [Xanthoceras sorbifolium accessions.Population structure is an important component in association mapping analyses between molecular markers and traits. Differences in population genetic structures reflect genetic diversity and convey the adaptation potential of a species to its changing environment . To undeanalysis ,66. Bothanalysis  reportedp < 0.001), the results indicated a greater within population variation (96%) than between populations (4%), and the genetic variation within populations was the primary source of the total variation. This indicates that there is little genetic differentiation among the populations, which matches the results recorded in previous studies [C. hystrix is an outcrossing plant mainly pollinated by wind, its wide distribution provides opportunities for gene recombination and produces rich genetic diversity. At the same time, the gene exchange between populations was promoted and the differentiation between populations was reduced. (2) Plant genetic diversity is related to environmental adaptation [C. hystrix has a wide distribution range and strong adaptability. Under the action of long-term natural selection, a wide range of genetic variation has been produced, resulting in the formation of geographical provenances with different phenotypes and different requirements for environmental conditions. (3) The level of genetic diversity within populations was also influenced by the number of samples [The AMOVA analysis is a satisfactory grouping criterion for evaluating the variation within and among populations. Most scholars generally believe that the level of genetic diversity in woody plants with wide distribution, perennial, outcrossing, wind-borne seeds, or feeding by birds and animals is higher and that the genetic diversity within the populations is richer than that between populations ,69,70. I studies ,28. The  studies  and Bela studies ,72. In captation . The C.  samples ,75, and  samples .C. hystrix resources have been evaluated using SSR molecular markers, which identified rich genetic diversity among the C. hystrix germplasm within populations. Although the core collections of many trees have been established, the construction of a core collection of C. hystrix had not been conducted. According to the method of Hu [C. hystrix with a 100% allelic representation based on 15 phenotypic traits and 32 SSR markers.In this study, the genetic diversity, population structure, population differentiation and, core collection of od of Hu , when MDod of Hu ,78. We sC. hystrix phenotype core collection was 15%, which is consistent with previous studies [The rich diversity of different germplasm resources is detailed, the sampling ratio of core collection bank varied, and the sampling ratio of woody plants ranged from 10.00% to 45.00% ,79,80. I studies . While p studies ,83,84 caC. hystrix core collection was constructed using Core Finder and Core Hunter 3 software. The results showed that the retention rates of Core Finder in the four genetic parameters Na, Ne, Ho, and I were higher than those of Core Hunter 3 (C. hystrix core collection. Consistent with this study, Gong et al. [C. hystrix germplasm set, BM, was constructed based on 15 entries of phenotypic data and 32 SSR markers, which were composed of 157 C. hystrix accessions. The results of the principal component analysis showed that some of the core collection overlapped with the original collection and some were scattered around. The reason may be that when using Core Finder software to analyze SSR data and extract the core collection, the amount of data was too large. In the future, we can try to use other software to construct a core collection based on the SSR data and compare the results.Based on the M strategy, Core Finder software selects core collections by maximizing the number of alleles at each locus, which can eliminate genetic duplication in materials during construction and screen materials with a large number of alleles and low redundancy. Core Hunter 3 mainly screens the core collection based on maximizing genetic diversity and allele richness, and different sampling ratios can be set. In this study, a Hunter 3 . Moreoveg et al.  construcC. hystrix resources have been evaluated using SSR molecular markers. The results showed that the genetic diversity of these SSR loci was rich. Moreover, C. hystrix samples were grouped into three clusters. We successfully established a core collection, BM, by combining 15 phenotypic data and 32 SSR molecular markers. We demonstrated that SSR markers were successful and effective for the assessment of the genetic diversity and structure of the C. hystrix populations. The established core collection can be used for future genome association analysis and breeding program research. This study provided a theoretical basis for germplasm resource management as well as the conservation and utilization of C. hystrix germplasm resources.In this study, the genetic diversity, population structure, population differentiation, and core collection of


Himalrandia lichiangensis (Rubiaceae), to evaluate the effects of tectonic and climatic processes on this thermophilic plant species from the dry-hot valleys. By sequencing DNA from four plastid non-coding regions  and the CAMX1F-CAMX2R region and ITS for 423 individuals from 23 populations, we investigated the genetic diversity, phylogeographical pattern and population dynamics of H. lichiangensis. We found a high degree of differentiation in H. lichiangensis during the middle Miocene (15-13 Myr), possibly triggered by the rapid tectonic uplift event in this period area. accompanied by frequent orogeneses in this period. This hypothesis is also supported by the association between genetic differentiation and altitudinal gradients among populations. The middle reach of the Jinsha River, which harbors the greatest genetic diversity, is most likely to have been a refugia for H. lichiangensis during Quaternary. We also detected a strong barrier effect between the Nanpan River and Jinsha River, suggesting the river system may play a role in geographical isolation between clades on both sides of the barrier. The Maximum Entropy Model (MaxEnt) results showed that future climate warming will lead to the niche expansion in some areas for H. lichiangensis but will also cause a scattered and fragmented distribution. Given the high among-population differentiation and no recent expansion detected in H. lichiangensis, its current phylogeographical pattern is possibly due to a long-term geographical barrier caused by uplifting mountains since the Miocene, as well as Quaternary climate refugia isolated also by high mountains. This study illustrated tectonic and climatic processes may have a continuous effect on plant phylogeography and offers insights into the origin of biodiversity and endemism in the dry-hot valleys of southwestern China.Both changing tectonics and climate may shape the phylogeographic patterns of plant species. The dry-hot valleys in southwestern China harbor a high number of endemic plants. In this study, we investigated the evolutionary history and potential distribution of an endemic shrub  The uplift of the Tibetan Plateau is one of the most significant geological events during the Cenozoic, altering both the Asian topography and climate . Since tThe Hengduan Shan located in the STP, has long been considered a refuge for plants in the northern temperate zone during the Quaternary glacial periods, and it has become an important source and radiation area for plants . With thTrailliaedoxa gracilis (Rubiaceae) (Leucomeris decora and Nouelia insignis (Asteraceae)   from the dry-hot valleys, which is associated with patterns of cpDNA haplotype variation, resulting from vicariance caused by several river separation and capture events (Sophora davidii (Fabaceae) exemplified the utility of comparing chloroplast and nuclear DNA variability and suggested a major phylogeographical break in cpDNA associated with the “Tanaka-Kaiyong Line” (TKL), and that the complex geological and climatic changes in HDM area played a decisive role in the west-east differentiation of S. davidii  , small teraceae) , shrub alvaceae) . Howevere events . Another davidii . These p davidii .Himalrandia lichiangensis (W. W. Sm.) Tirveng. is an inermous perennial shrub  from Rubiaceae as outgroup, which were sampled from cultivated materials kindly provided by the Xishuangbanna Tropical Botanical Garden, in Yunnan Province.We collected a total of 423  species Table S1trnD-psbM, trnD-trnT, accD-psaI, atpB-rbcL, using the primers described in a previous study , total diversity (HT), the level of population differentiation (GST and NST) as well as the genetic differentiation (FST) at the species level. The U test was used to determine whether NST was significantly greater than GST . Phylogenetic reconstructions of ITS ribotypes were implemented in IQTREE v.2.1.1  was conducted with two species as outgroup (Ligustrum vulgare and Kopsia fruticosa). BI analysis was conducted in MrBayes 3.2  according to a previous molecular dating study  using all available 23 presence records by niche modeling based on 19 bioclimatic variables (http://www.worldclim.org/) and altitude data (http://www.geodata.cn). The maximum spatial resolution of 19 bioclimatic and altitude data is 30"×30" (~ 1 km2), and the LGM and future data are derived from MIROC climate model  and haplotype diversity (Hd) for all populations were summarized in HT = 0.952, 0.785, 0.812 from cpDNA, ITS and CAMX, respectively) was higher than the average intrapopulation diversity , resulting in high levels of genetic differentiation , implying that there is correspondence between haplotype lineages and geographic distribution. The results of the Mantel test revealed the same pattern, namely, there is a significant positive correlation between genetic and geographical distance , which indicated that the genetic pattern of this species was in accord with the Isolation by Distance model . The results of the mismatch distribution analysis displayed a multimodal distribution pattern  . The divergence of most haplotypes were recent with an estimate generally in the Pleistocene (around or later than 2 Myr).The results of BARRIER analysis show that there are two obvious isolation barriers with high bootstrap values Figure 4lichiangensis may shrink, accompanying by a large degree of habitat fragmentation (The accuracy of MaxEnt model was tested by receiver operator characteristic (ROC), and the areas under receiver operator characteristic curves (AUC) value was greater than 0.980 Figure 5H. lichiangensis that has a high fragmented distribution range and small population sizes, our results revealed that the genetic diversity within some populations  is extremely low. The low genetic diversity of these populations could be explained by genetic drift, in which few haplotypes were fixed because of a bottleneck effect . The rapid uplift of the STP since the middle Miocene blocked the gene flow among populations, and resulted in isolation, independent evolution and development of lineages in fragmented distribution regions  to the plateau, accompanied by a subsequent continuous founder effect that significantly reduced the population diversity on the plateau, especially in the west  to both sides of the barrier during glaciation. Besides, populations located in marginal distribution zones  have significantly reduced genetic diversity, most likely as a result of refuge population migration.The divergence of different haplotypes of aternary Figure 4H. lichiangensis is larger than the actual distribution. For instance, the Yarlung Zangbo River and The Mekong River also show the existence of suitable distribution area. This may suggest the limited distribution of H. lichiangensis is not restricted by present climate condition, but may be caused by habitat loss according to our field survey. During the Quaternary glaciations, high latitude species were affected by the spread of large ice sheets, which fragmented the geographical distribution of many species , may have accelerated the diversification of different haplotypes. The largest past distribution of H. lichiangensis in LGM implied a trend of range expansion during the ice age and contraction after the glacial epoch. Climate warming in the coming 50 years will lead to a large decrease in the area suitable for H. lichiangensis, which offers imperative thinking for niche conservation and ecological restoration in dry-hot valley areas of southwestern China. The influence of geological and climatic events on the plant distribution in the dry-hot valley area needs to be extended to more plant groups with long evolutionary history in order to better understand how different factors may interact to impact the evolutionary process.In this study, we found high genetic differentiation of The original contributions presented in the study are publicly available. This data can be found here: GenBank, MW222416-MW222467, MW264453-MW264480.XG and JL conceived the study. YQ, JL, and XG participated in sampling. YQ performed the analyses and drafted the initial article, which was then corrected and finalized by JL and XG. All authors contributed to the article and approved the submitted version.This work was funded by the National Key Research and Development Programme of China (2017YF0505200), the National Natural Science Foundation of China (31900184 and 31970230), and the Natural Science Foundation of Yunnan Province (202001AT070072 & 2019FD057).We thank Zichen Zhao and Jie Song for their sampling assistance.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. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The genetic characterization of native sheep breeds from the Tunisian-Italian Mediterranean corridor, the earliest westward introduction route of sheep breeding from the domestication center, was carried out using microsatellite markers in order to compare the genetic diversity level between both Mediterranean sides’ local sheep breeds, and to investigate their level of risk for conservation purposes. Sampling concerned both private and public/institutional farms of all the native Tunisian breeds in the case of the southern Mediterranean side, and one center Italian and the Venetian native breeds from the northern side. The results revealed that the genetic diversity level of the Tunisian native breeds was higher than that of the Italian ones, with a lower inbreeding level. The comparison between private and public farms in terms of genetic diversity, consanguinity, and conservation decisions highlighted the superiority of the public/institutional breeding management strategies over private ones in both Tunisian and Italian cases. The present study illustrated the efficiency of genomic characterization in making genetic diversity evaluations and preservation decisions of native and well-adapted sheep breeds in both developing and developed countries’ rearing conditions.ST = 0.081). The genetic diversity level was higher in the case of the Tunisian native breeds compared to the Italian ones, as evidenced by higher mean allelic richness, higher expected and observed heterozygosities, and lower inbreeding levels. Priority for conservation suggestions was carried out for each private or public breed population based on the contribution of each population to the diversity of the whole data. The four Venetian breeds, already undergoing conservation, the Tunisian dairy breed, and the very ancient Maghrebian breed, would be favored for conservation. In conclusion, our results highlighted the importance of the analyzed Mediterranean native sheep breeds as valuable inherited genetic reservoirs and supported previous conservation decisions made for the threatened breeds.Non-commercialized sheep breeds known as local or native breeds are well adapted to their environmental constraints and constitute precious genetic resources that need prioritization for genetic diversity characterization and preservation. The aim of the present study was to assess the genetic diversity level and the related preservation decisions of very old and traditional native Mediterranean sheep breeds from Tunisia and Italy using 17 microsatellite markers. In total, 975 sheep were sampled from five Tunisian, one Center Italian, and four Venetian native breeds. Both private and publicly available farms were considered for each breed for breeding strategies’ comparison purposes. The microsatellite set used was highly informative (PIC = 0.80 ± 0.08), with a total of 383 alleles. Moderate genetic differentiation was revealed between the native sheep of the two Mediterranean sides (global overall loci F Livestock diversity is crucial for food security, productivity and adaptability of production systems, resilience to climate change, and livelihoods . The recThe sheep genetic resources played an early major role in this Mediterranean corridor. The earliest westward introduction wave of sheep was mainly maritime and had reached the Mediterranean island regions between the 12th and 10th millennium BP . The actn = 64), Queue Fine de l’Ouest (QFO), n = 41), Noire de Thibar , Sicilo-Sarde , and the D’man breed . A recently created Tunisian crossbred BAR × QFO  was also investigated to assess the effect of this new breeding trend on the genetic variability level of Tunisian sheep resources. A total of 695 individuals belong to the four Venetian local breeds: Lamon , Alpagota , Brogna , and Foza named likewise Vicentina . A sample of 31 individuals belonged to the Central-Italian Appenninica native breed . Although the analyzed Italian breeds are strictly defined based on a set of phenotypic standards with breed herd books and formalized breeds’ associations [A total of 975 blood samples were collected from Tunisian and Italian sheep by specialized veterinarians of the local health authorities during sanitary control from both private and, if available, public/institutional farms for each breed. According to the Research Ethics Committee of Padova University, ethical review and approval were waived for this study, and no specific authorization was required. No more than four unrelated animals were sampled from each flock based on the information provided by farmers and breeders when pedigree data were not available. An entire number of 249 individuals were sampled from Tunisia, belonging to the five Tunisian locally adapted breeds: Barbarine  following the manufacturer’s protocol. The total of samples were genotyped at 17 microsatellite loci panel  establiso) and expected (He) heterozygosities were calculated using GENETIX version 4.05.2 [AR) in the different populations using the hierarchical rarefaction method was counted using HP-RARE software [IS, FIT, and FST) [The MICRO-CHECKER version 2.2.3  softwaren 4.05.2 . The numsoftware . MSA sofsoftware  was usedand FST)  and the and FST) . This soand FST) . The gloand FST) . GENETIXand FST)  was usedand FST) . The assand FST)  To choosand FST)  using thand FST) . The outand FST) .IS, FIT and FST were 0.109, 0.180, and 0.081, respectively (p < 0.001). These values explained that the global homozygote excess (FIT) of 18% was mainly due to the within-breed homozygote excess (FIS) of 10.9%, indicating a notable inbreeding level among and within breeds. The genetic differentiation between breeds limited to 8.1% highlighted the moderate distinctiveness between the analyzed breeds, despite their belonging to different Mediterranean shores. This moderate differentiation level could be explained by the shared historical sheep migration events of the Tunisian-Italian corridor, beginning since the Neolithic and continuing in Carthaginian and Roman times. The between-breed differentiation levels, divergence times, and gene flow were detailed by Ben Sassi-Zaidy et al. [All 17 microsatellite markers spread over 14 ovine chromosomes have been passed on the quality control settings and were considered in the genotyping data. A summary of the polymorphism of the genotyped microsatellite panel in the Tunisian local breeds, in the Italian local breeds, and in the combined whole dataset is presented in y et al. . Consequy et al. ,23,25. My et al. . Althougy et al. ,41,42,43y et al. . Furthery et al. , was avoAR), observed (Ho) and expected (He) heterozygosities, within-breed homozygote excess (FIS), and number of loci deviated from Hardy–Weinberg equilibrium (HWE), as shown in AR varied from 0.16 to 0.45 in the Tunisian breeds and from 0.21 to 0.38 in the Italian breeds. High frequencies are related to the breeds’ specificities in the two countries. Both Mediterranean sides’ local breeds showed considerable Ho values but were always lower than He. The deviation from HWE did not exceed the two loci in the Tunisian breeds group. However, in the Italian group, the number of loci in disequilibrium varied from 03 in APP to 12 in ALP (p < 0.001). Excluding null alleles’ cause after specific test control, the population substructure could explain this divergence, since the inbreeding level of the Italian local breeds was not that high (FIS varying from 0.101 ± 0.101 in LAM to 0.134 ± 0.132 in ALP) and was not proportional to the number of deviated loci. This structuration within Venetian breeds has already been highlighted [IS values were observed for the Tunisian breeds except the NTH breed and the BAR unique fat-tailed breed, which presented the lowest inbreeding level .The genetic variability of each analyzed sheep breed was revealed in terms of (AR), private allelic richness  after the hypothetical removal of each breed, as defined in Caballero and Toro’s approach , are illThe revealed difference in the genetic architecture between the Tunisian and the Italian local sheep resources would reflect the difference in the environment and the breeding practices between the two countries, especially since the beginning of sheep breeding industrialization in Europe, which has even influenced the local breeds. In fact, the focus on highly productive and selected cosmopolitan breeds in Italy has caused the native breed’s negligence. Consequently, a drastic decrease in the local Venetian sheep population has occurred ,47, leadMeasuring genetic diversity in locally adapted and native sheep animal breeds using neutral and maternal molecular markers is essential to setting up conservation strategies ,52,53,54Tunisian sheep genetic resources are mostly formed by more or less ancient breeds that have not been subjected to the same strong selective forces as industrialized breeds in developed countries. The management of these breeds is 80% held by private breeders, and 70% of these are small breeders (<11 breeding ewes) who have inherited this activity from father to son without known management programs ,57. ThisIS value (0.139 ± 0.192). The excess homozygotes in this population could be explained by the anarchic crosses practiced without any parentage control, as declared by the breeders who frequently practice this cross between BAR males and QFO females to obtain a smaller tail, thus missing the paternity control present in BAR mating management, since the thin tail of the QFO breed does not require the shepherd assistance in the mating. This anarchic crossing was imposed by butchers, who found it difficult to sell the heavy-weight fat of the BAR tail [Considering both private and public sheep breeds as the overall Tunisian genetic sheep resources data, the genetic variability assessment in our study revealed the BAR fat-tailed breed as the most variable, presenting the highest expected and observed heterozygosities, a low homozygote excess coefficient, a high level of private allele richness, and the highest contribution to the overall genetic diversity of the Tunisian-Italian (+0.23%) and the Tunisian . This could be explained by the strong efforts made to reduce the impact of inbreeding on NTH [The NTH breed, currently counting about 76,000 ewes , was created in the Thibar region at the beginning of the 1900s’ through a crossbreeding schema between the Algerian Ouled Djellal breed and the French Merinos. The selection was primarily placed to fix the black color by highly inbred mating series to avoid the white sheep photosensitization engendered by the consumption of the  systems ,17. Afte systems ,58. The  systems ,58, the g on NTH ,76. In fg on NTH  and Portg on NTH  seems tog on NTH , the NTHThe SS is a unique North African dairy breed created early in the last century from a crossbreeding schema between the Italian Sarda and Comisana dairy breeds in the northern region of Tunisia . CountinThe DM breed, considered until recently an exotic breed introduced to Tunisia from Morocco, is the remaining form of ancestral sheep reaching Tunisia and all the North African land in the Neolithic . This prAs mentioned by Caballero and Toro , maximizIn general, the genetic diversity (He) of all the local Tunisian breeds, except the CRO population, is considerable and can be oriented toward short-term and long-term conservation strategies. Coherent in situ conservation strategies based on the avoidance of inbred mating and breeds’ erosion seem to be urgently needed for locally adaptive Tunisian breeds’ conservation.The transhumant system, mainly used for the large-sized and long-legged FOZ and LAM breeds, reared with large flocks grazing on plains and coastal areas during winter, and displacing to highland pastures in summer,The mountainous grassland-based farming livestock system, known as small flocks reared on farms located in mountainous and hilly areas, is mainly used for the two medium-sized ALP and BRO breeds ,86.Italian local sheep genetic resources are almost 87% formed by breeds classified as at risk . In the The detailed local risk status declared by the FAO (DAD-IS)  is “CritThe current assessment of the variability level of the Venetian breeds revealed that the LAM and FOZ breeds, which had been subjected to a continuous loss of their genetic variability due to their limited population size, and therefore confronted with a high risk of disappearance, exhibited the highest expected and observed heterozygosities, the latest consanguinity level, and a considerable AR . Thus, tThe genetic variability level of the medium-sized BRO breed is highlighted by its considerable allelic and gene diversity . This muThe ALP breed, despite its decreasing population size in the last decade , exhibiConsidering the Venetian breeds as the whole population  and BAR with a black head ; the remaining flocks belong to the QFO (7 flocks), the NTH (6 flocks), and the SS dairy breeds (2 flocks) ,89. BesiIS = 0.012), thus reflecting the random mating within the BTNO population, and its successful management was not negatively influenced by the selection pressure. This worthy genetic diversity level is reflected by the high production performance of this population, in addition to its superior rusticity and adaptation traits [IS = 0.054 and 0.012; Ho = 0.755 and 0.799, respectively) could be explained by the difference in the management practices applied by the OTD services between these two flocks. The population size of the BTRO  is higher than that of the BTNO , which engenders more vigorous management of this last group in the paternity control. In fact, under the control of the OEP Office, best lamb selection is monitored based on the recorded information and the performance characters from the totality of Tunisian public farms, mainly from the OTD flocks . The unselected lambs from the collected and indexed OTD lambs, after performance and sanitary controls, are dispatched randomly on the OTD farms and can return to their origin flocks. The selected lambs were kept and reared in the OEP genitors’ center and then dispatched randomly on public farms. Consequently, genitors might return to their original flocks due to the rotation of sires practiced by the office, especially for the BTRO-abundant flocks from which the majority of the selected BTR rams originated [IS = 0.087 and 0.047, respectively). This could be explained by the mating practices in this breed imposing a paternity control system due to shepherd assistance during mating, as previously explained. For the public flocks of the BAR breed, it is worth mentioning that the risk threatening this breed manifested by the dilution and absorption of its gene pool by anarchic crossing with the QFO breed is avoided. Standard breed characteristics have been maintained through public management practices, even though animals with a very big fat-tail, which is the specific rustic characteristic of the breed considered as body reserve mobilized under harsh conditions, have usually been reformed from the OTD herds [The comparison between Tunisian public and private flocks’ genetic parameters results  revealedn traits ,89. The iginated . For theiginated . These piginated   endangered Venetian sheep breeds revealed a higher gene diversity level (He) in the private sector, except for the LAM breed, which presents higher He and Ho within the public flocks. The inbreeding level was higher in private flocks, especially for the ALP and BRO breeds . This low inbreeding level is explained by the management strategy applied in the public sector monitored by the “Villiago” Conservation Center, which aimed to preserve a stock number of breeds presenting the standard functional and morphological characteristics through adequate mating strategies enabling the inbreeding level reduction within each breed ,86. BothThe Factorial Analysis of Correspondence was performed, including both Mediterranean sides’ local sheep breeds, based on all microsatellite loci’ allele frequencies . The firThe representation of the POSA distances through a neighbor-net graphic  showed tThe phylogenetic relatedness of the Tunisian breeds and the analyzed native Italian breeds was recently detailed by Ben Sassi-Zaidy et al. . A stronThe genetic structure of the analyzed Tunisian and Italian breeds was investigated using the Bayesian approach with K number of expected clusters ranging from 2 to 12. The optimal number of ancestral populations was K = 5 a. At K =In this study, we assessed the genetic diversity of all locally adapted Tunisian sheep breeds and five native Italian breeds in both the private and public breeding sectors based on the microsatellite genotyping technique. The obtained results give deeper insights into the genetic diversity level of the analyzed breeds, which appeared more genetically diversified in the Southern Mediterranean rive, and slightly more efficiently managed in the public breeding sector than the private one in both countries. As a general outcome of this bi-dimensional comparison, at the genetic diversity and breeding management axes of both Tunisian and Italian sheep genetic resources situations, we revealed that the Tunisian sheep sector possesses the desired genetic diversity base and a considerable population size, but it still needs efficient and coherent breeding and conservation strategies. The Italian side, exhibiting currently efficient conservation and breeding strategies and the necessary financial tools, nevertheless suffers from the drastic reduction in the size of the native breeds’ population over the last decades, which will be hard to reverse.Adequate conservation decisions are recommended to conserve Tunisian sheep resources, exhibiting a significant population size and genetic diversity that can be oriented to short-term and long-term conservation strategies. In situ conservation strategies involving breeders, who should be grouped under breed associations, seem urgently needed to ensure the breeds’ valorization and the avoidance of inbred mating and breed’s erosion.Concerning Italian native sheep breeds, stopping the current decrease in the APP breed population size and preserving or improving its genetic variability level are urgently needed. Further valorization of endangered Venetian native breeds is still needed, despite the current efforts. Promoting agro-tourism and the conversion of ordinary breeding to organic farming seem to be successful tendencies.Complementarity of these two different situations under developing and developed countries’ conditions helps to build efficient sustainable sheep breeding strategies based on the conservation of within and between breed genetic diversity to handle future challenges in sheep breeding and food security.


Fermented foods generally comprise a complex micro-ecosystem with beneficial microbiota, functional products, and special flavors and qualities that are welcomed globally. Single-omics analysis allows for a comprehensive characterization of the main microbial factors influencing the function, flavor, and quality of fermented foods. However, the species, relative abundance, viability, growth patterns, and metabolic processes of microorganisms vary with changes in processing and environmental conditions during fermentation. Furthermore, the mechanisms underlying the complex interaction among microorganisms are still difficult to completely understand and analyze. Recently, multi-omics analysis and the integration of multiple types of omics data allowed researchers to more comprehensively explore microbial communities and understand the precise relationship between fermented foods and their functions, flavors, and qualities. Multi-omics approaches might help clarify the mechanisms underpinning the fermentation processes, metabolites, and functional components of these communities. This review clarified the recent advances in the roles of microorganisms in fermented foods based on multi-omics data. Current research achievements may allow for the precise control of the whole industrial processing technology of fermented foods, meeting consumers’ expectations of healthy products. With the current increasing demand of consumers for healthy foods, fermented foods with beneficial microbiota, nutrients, and healthy functions have attracted increasing attention. The consumption of fermented foods has had a long history and has spread worldwide. Although many kinds of fermented foods exist, industrialized fermented products are limited; however, with the development of the fermentation theory, meta-omics technology, and the integration of multiple types of omics data, the mysterious world of microbes can be revealed.The application of multi-omics in fermented foods may offer an opportunity to precisely discover the changes in the microbiota during fermentation, the interactions involved, the link between microorganisms and functional components, flavor substances, and deleterious inhibition, among other aspects. The key points of the processing control of fermented foods include the types of starter cultures, the microbial communities at each fermentation stage, and various operational conditions. The application of multi-omics replaces the single-cell omics approach for the analysis of microbial communities, allowing for a comprehensive understanding of the dynamic microbial changes in the food fermentation process. It is helpful to characterize the microbial community and species succession during different fermentation stages, evaluating the influence of the external environment on the microbial community, ultimately enhancing the fermentation conditions. Understanding the directional selection of a microbial community is helpful in finding ways to improve the function and added value of fermented foods. In addition, the multi-omics approach can allow for accurate analysis of the mechanism underlying the complex interactions among microorganisms, which is conducive to improving the quality, flavor, and safety of fermented foods and boosting bioactive metabolite levels essential for human health. Furthermore, the multi-omics approach has potential application for unraveling the relationship between the quality and safety of fermented food products as it involves cell data acquisition and the identification of specific genes and proteins of harmful microorganisms. Moreover, preferential starter cultures can be ascertained in the industrial process of fermented foods using the multi-omics approach. In summary, multi-omics will serve as a comprehensive processing technology, helping produce healthy fermented foods that meet consumers’ demands.via multi-omics strategies. Then, the relationship between fermented foods composed of complex microorganisms and their functions, flavors, and qualities was revealed using a multi-omics approach. Furthermore, the mechanism underlying the fermentation process, metabolites, and functional components was analyzed. Finally, innovation of the industrialized production mode of fermented foods was prospected based on multi-omics insights.Herein, the roles of microbial communities in fermented foods were clarified Single-omics analysis can only describe a certain biological process and cannot analyze microbial metabolic differences or the complex mechanisms underlying their interactions during fermentation. It represents a single result at the nucleic acid, protein, or metabolite levels and cannot fully represent proteomes or metabolomes under different transcriptional conditions . In addiMulti-omics can span the multi-layer analysis of gene and protein expression, as well as metabolite differences of all microorganisms in the environment, consequently yielding a large amount of data . It is wMulti-omics is regarded as the mainstream way of analyzing fermented food microorganisms and has marked advantages of “1 + 1 > 2” in analyzing microbial succession, determining functional genes, and exploring the metabolic network of active components . HoweverThe production of fermented foods needs the coordinated action of a plethora of microbial communities. The analysis of species, metabolic pathways, and interactive relationships of these microbial communities is conducive to the directional control of microbial species in the fermentation process, therefore improving production efficiency and the flavor of fermented foods, as well as ensuring the safety thereof.The coordination of the microbial communities of fermented foods can be achieved by multi-omics from virtually every dimension . It can Multi-omics approaches have far-reaching implications for fully exploring food microbial resources and improving the quality of fermented foods. In the past, owing to technological limitations, researchers thought that fermented foods were products of fermentation by a single or several strains. However, with the recent development of multi-omics, numerous studies have focused on food microbial communities. Accordingly, a large number of new and previously unknown microbial communities have been discovered in fermented foods . The souTetragenococcus sp., and family Lactobacillaceae, genus Leuconostoc sp., was highly abundant in naturally fermented soybean paste. The strains of the species thereof played a key role in forming alcohol flavor components, as evidenced by a combination of metaproteomics and metabonomics (O-methoxycatechol-O-sulfate) in artisanal cheese had not previously been reported in any type of cheese. Their integrative analysis of multi-omics datasets revealed that highly similar cheeses, identical in age and appearance, could be distinctively clustered according to the cheese type and brand  to day 14 (9%)] and Geotrichum candidum (the dominant strain on day 7)  . CorynebC. casei . Accordier stage . Ruggireonas sp. . These sBifidobacterium breve in regulating host immunity, intestinal metabolism, and intestinal gene expression using transcriptomics and metabolomics. They believed that both cells had the potential to regulate immunity, inhibit the production of pro-inflammatory cytokines in splenocytes, and affect intestinal metabolism. Nonetheless, these functions were presented more significantly in living cells than the inactivated ones  and probiotics (Lactobacillus enterocolitica and Bacillus mycoides) increased significantly during fermentation, thereby effectively reducing kidney inflammation and regulating the expression of uric acid transporters to treat hyperuricemia. Using a multi-omics approach, it is more affordable to identify genes and gene products responsible for the functional metabolites in fermented foods, yielding highly active metabolites for human health   .Pseudomonas, Propionibacterium, Modestobacter, Rhodovibrio, and Salinibacter appeared during a later fermentation stage. There are individual metabolic differences and complex interactions in microbial communities in fermented food, which cannot ensure the stable quality and food safety of final fermented products . Multi-oTraditionally, in fermented foods, the main contribution of bacteria is to produce flavor compounds; yeast produces alcohol and low levels of flavor compounds, and mold decomposes macromolecules. Although this understanding is reasonable, it should also be noted that this understanding is based on the physiological and metabolic characteristics of some single-cultured microorganisms. There is a serious lack of understanding of the functions of non-isolated cultured microorganisms. More importantly, there is a lack of a systematic analysis of the mechanism underlying microbial interaction in complex fermentation systems and its effect on fermentation processes, metabolites, and functional components.Lactiplantibacillus plantarum WCFS1 on the metabolite spectrum of yogurt. The addition of precultured L. plantarum impaired the survival of Lactobacillus delbrueckii  should be further developed for application in the fermented foods industry . Microbiial wine .Fermented food production should be standardized to predict and control the fermentation process using these multi-omics data. Multi-omics can be used to accurately select the cultures required for the formation of qualities, flavors, and sensor properties of fermented foods. By connecting genomic characteristics with phenotypic output and exploring the metabolic diversity of starter cultures, the impact of a single strain on the qualities, flavors, sensor properties, and metabolic pathways of fermented food can be understood to customize the starter mixture to meet the needs of specific fermented foods in the industry. Multi-omics can also be used to optimize the control of fermented foods under different processing and storage conditions to accurately determine the detailed parameters of various processes in each fermentation stage and ensure the optimal quality, flavor, aroma, nutrition, and safety of fermented foods. The roles of microorganisms profoundly affect the quality, flavor, and safety of fermented foods. More microbial communities can be investigated using multi-omics, rather than single-omics, to reveal new findings between fermented foods composed of complex microorganisms and their functions, flavors, and qualities. Analyzing the mechanism underlying the fermentation process, metabolites, and functional components using multi-omics provides in-depth technical support for the industrialized production mode of fermented food.HS: conceptualization and roles/writing – original draft. FA: investigation, data curation, and resources. HL: software and formal analysis. ML: validation. JW: project administration. RW: supervision, writing – review and editing, and funding acquisition. All authors contributed to the article and approved the submitted version.


Populus koreana, a pioneer and keystone tree species in temperate forests of East Asia. We integrate population genomics and environmental variables to reveal a set of climate-associated single-nucleotide polymorphisms, insertion/deletions and structural variations, especially numerous adaptive non-coding variants distributed across the genome. We incorporate these variants into an environmental modeling scheme to predict a highly spatiotemporal shift of this species in response to future climate change. We further identify the most vulnerable populations that need conservation priority and many candidate genes and variants that may be useful for forest tree breeding with special aims. Our findings highlight the importance of integrating genomic and environmental data to predict adaptive capacity of a key forest to rapid climate change in the future.Rapid global climate change is posing a substantial threat to biodiversity. The assessment of population vulnerability and adaptive capacity under climate change is crucial for informing conservation and mitigation strategies. Here we generate a chromosome-scale genome assembly and re-sequence genomes of 230 individuals collected from 24 populations for  Populus koreana and combine population genomics and modelling to predict spatiotemporal responses to climate change.Assessment of population vulnerability and adaptive capacity under climate change is crucial for informing conservation strategies. Sang et al. assemble a reference genome for  To escape demographic collapses from threats, species must trace suitable locations or adjust to changing environments via phenotypic plasticity or innovation from standing genetic variation and de novo mutations2. However, migration, in order to keep pace with rapid climate change, may be difficult for many species3. Therefore, understanding and quantifying the evolutionary potential of a species for future adaptation is not only relevant for understanding whether and how natural species can persist in the context of climate change, but it can also benefit conservation and management strategies to cope with global biodiversity loss5.Climate change is predicted to become a major threat to biodiversity, and there is ample evidence of climate-induced local extinctions among plant and animal species6. The traditional way to identify and quantify local adaptation via reciprocal transplant and/or common garden experiments9 is challenging and often unfeasible for many wild non-model organisms due to experimental intractability, long generation times, or other challenges to obtaining fitness-related phenotypic traits10. With the advance of genomic technologies, it is now becoming increasingly affordable to generate population genomic data that can serve as a complementary strategy to examine local adaptation throughout the distribution range of one targeted species13. Although there may be millions of variants across the genome within any specific species, only some of these variants are expected to be related to climate adaptation14. The process of identifying the climate-associated genetic variation is not only critical for solving fine-scale patterns of local adaptation but also facilitates a more mechanistic understanding of how species respond to climate change15. Genotype–environmental association approaches are increasingly used to identify loci involved in climate adaptation16. Once candidates for locally adaptive allelic variation have been identified, it is possible to measure genomic offset, which assesses the amount of change in the genetic composition of a population that is required to track future environmental conditions18. As such, using genomic tools goes beyond modeling species range changes over time and can provide novel insights into assessing the evolutionary adaptive potential and predicting the disruption of local adaptation and species vulnerability in a changing climate20.The spatial predictions of the effects of future climate change have largely relied on the knowledge of adaptive genetic variations on current climate conditions21. However, they are particularly vulnerable to maladaptation owing to their long generation times, for which climate change is likely to happen within the lifetimes of single individuals and making them especially challenged in terms of adapting to keep up with rapid climate change22. In this context, integrating genomic data into predictive models aimed at quantifying and mapping spatial patterns of climate maladaptation is especially important for long-lived tree species24. In this study, we accomplish such a goal for Populus koreana , one dominant tree species in temperate deciduous forests in East Asia. We assemble the first, to our knowledge, de novo chromosome-scale reference genome for this species and further re-sequence genomes of 230 individuals from 24 natural populations across its distribution range. We characterize genome-wide variations, including single-nucleotide polymorphisms (SNPs), small insertions/deletions (indels) and large structural variants (SVs). Based on these genomic datasets, we aim to: (1) infer the spatial patterns of genetic diversity, population structure, and evolutionary history; (2) dissect the genomic underpinnings of climate adaptation and investigate how past selection shaped patterns of adaptive allele frequencies across distributional ranges; and (3) quantify and map the vulnerable populations under future climate change.Forest trees are efficient carbon sinks and play an increasingly leading role in the global carbon cycle and in combating climate change and global warmingP. koreana genome, we integrated data from three sequencing and assembly technologies: ~42.42 Gb of Nanopore long-read sequencing (106×), ~29.82 Gb of short-read Illumina sequencing (74×), and ~54.22 Gb of Hi-C paired-end reads (137×) . Similar levels of nucleotide diversity were revealed across the 24 populations, and the nucleotide divergence (dxy) between the two groups was almost the same as the nucleotide diversity within groups  in the history . The northern group showed a steady population decline, whereas a slight population expansion was observed in samples from the southern group. These inferred demographic histories were also confirmed by Tajima’s D statistics  as a function of physical distance showed similar patterns in the southern and northern populations, with r2 declining below 0.2 after ~15 kbp on average  approaches to detect the environment-associated genetic variants. First, we tested for GEAs for 19 environmental variables , isothermality (BIO3), and maximum temperature of warmest month (BIO5)) and three precipitation variables (precipitation of wettest month (BIO13), precipitation seasonality (BIO15), and precipitation of coldest quarter (BIO19)). By visualizing climate-associated genetic variation across the natural distribution, we found that adaptive genetic variation could be largely explained by these six climatic variables FST) between the climate-associated adaptive variants and the randomly chosen ones. Significantly stronger FST values were observed at these adaptive variants  for the potentially adaptive and neutral variants, respectively  of genes and transposable elements (TEs)   as an example to show the distribution pattern of allele frequencies  did not exhibit significant differences between haplotypes carrying the T or the C allele at the focal SNP  was found to regulate stress responses41.Many genes previously reported to be involved in climate adaptation were identified here with variants to be associated with environmental variables  Fig.  and idenies Fig. . The T aies Fig. . To verince Fig. . This innce Fig.  in this Arabidopsis HMG1, PGP4, FAD5, and EMB1507, showing similar allele frequency distribution patterns as we saw for the precipitation-associated genes  orthologous to Arabidopsis HSP60-3A42. The rapid synthesis of HSPs induced by heat stress can protect cells from heat damage and enable plants to obtain thermotolerance by stabilizing and helping refold heat-inactivated proteins43. Relatively high LD was found within the region surrounding this gene  to show the geographic distribution of the allele frequencies . Despite this, the haplotypes carrying the warm-adapted allele (G) had elevated EHH relative to the haplotypes carrying the other allele (A)  Fig. , suggestP. koreana will respond to future climate change. For the future climate projections, we integrated the prediction of the genomic offset across four various future climate models to account for the variability between models. In addition, we also considered two different emission scenarios of the shared socioeconomic pathway (SSP126 and SSP370) among the four adopted by the CMIP6 consortium for two defined periods (2061–2080 and 2081–2100)44. Three complementary approaches were used to investigate the spatial pattern of maladaptation across the range of P. koreana under future climate conditions.Based on the established contemporary genotype–environment relationships and the identified climate-associated genetic loci, we predict how populations of 45. We found that although the values of RONA varied across the four future climate models , which measures the expected allele frequency shifts required to cope with future climate conditions after establishing a linear relationship between allele frequencies at environmentally associated variants and present climatesges Fig. , the souges Fig. .Fig. 4RO17. Compared to RONA which is estimated at the level of a single locus under a given environmental variable, the GF is an extension of the random forest approach that models the associations between the composite effects of many putatively adaptive locus to multi-climate variables simultaneously46. Consistent with RONA, the GF estimates of genetic offsets across the four future climate models were highly correlated  approach to model the turnover in allele frequencies along present environmental gradients and predict genetic offset to a projected future climate23. With different maximum dispersal distances , we revealed largely consistent patterns  genetic offsetets Fig. . Therefo48. We used the ratios of derived functional  to synonymous variants as proxies for the genetic load. Together no relationship was observed between the predicted genetic offsets  and both genetic diversity and genetic load across populations, even for the LOF variants that are predicted to be strongly deleterious 1. Despite the importance of intraspecific adaptive variations in mitigating such risks15, predictions of range shift and population vulnerability to future climate change are still challenging without genome-scale knowledge. In this study, based on the well-assembled reference genome and population-level whole-genome resequencing data, we extracted all genetic variations to explore the genetic architecture of climatic adaptation in one key forest-dominant tree, P. koreana, in East Asia. We identified the genes and the corresponding variants that are correlated with local adaptation. We further revealed that the local adaptation of P. koreana to the current variable environments evolved by small polygenic allele frequency shifts as found for many other species38. After combining space-for-time and machine-learning approaches to predict the spatiotemporal responses of this species to future climate change, we identified a set of populations located in the southeastern part of the current distribution range as being most vulnerable under future climate scenarios. These populations are needed to be conserved with special management strategies not only because of their high genomic offset to future climate change but also because they contained many unique, climate-adaptive genetic resources47.Ongoing climate change is predicted to threaten populations of numerous species50. In addition, despite the high-quality genomic data facilitated us to explicitly include both SNPs, indels, and SVs in analyses and also revealed that the climate adaptation of P. koreana had a polygenic genetic basis, the genetic variants with small effects in more genes may have been unavoidably missed especially given the reduced sensitivity owing to the required multiple testing correction in genome scans for detecting signatures of climate adaptation. Furthermore, we have to be aware that, although we used both single-locus-based (RONA) and multi-locus-based (GF) approaches to assess the climate change vulnerability of P. koreana, the complexity of polygenic adaptation , has not been considered in current assessments. Therefore, future efforts should focus on integrating quantitative genetics and systems biology approaches to better model the genomic complexity of polygenic adaptation and to further improve the prediction of the genomic offset to climate change51. Finally, the potential of populations to respond to future climate change has no relationship with their genetic load within P. koreana, and a more thorough understanding of the association between genetic load and population vulnerability under climate change could benefit from more future studies that incorporate evolutionary processes into the prediction of species responses to climate change52.However, it should be noted that all of the present genomic predictions of maladaptation to future climates must be used with caution, and further empirical validations are needed to confirm these findings. One of the promising approaches to validate these genomic predictions is linking the estimated genetic offset with the observed decrease in fitness of genotyped individuals from different populations through common garden experiments or controlled environment tests. In doing so, the fitness-relevant traits could be assessed by manipulating sampled populations to future climate conditionsP. koreana plant in the Changbai Mountains of Jilin province in China were collected, and the total genomic DNA was extracted using the CTAB method. For the Illumina short-read sequencing, paired-end libraries with insert sizes of 350 bp were constructed and sequenced using an Illumina HiSeq X Ten platform. For the long-read sequencing, the genomic libraries with 20-kbp insertions were constructed and sequenced using the PromethION platform of Oxford Nanopore Technologies (ONT). For the Hi-C experiment, approximately 3 g of fresh young leaves of the same P. koreana accession was ground to powder in liquid nitrogen. A sequencing library was then constructed by chromatin extraction and digestion, DNA ligation, purification, and fragmentation53 and was subsequently sequenced on an Illumina HiSeq X Ten platform.Fresh leaves of a wild https://github.com/Nextomics/NextDenovo) with parameters “reads_cutoff=1k (filter reads with length <1kbp) and seed_cutoff=32k (minimum seed length = 32kbp)”. Smartdenovo v1.0.0 (https://github.com/ruanjue/smartdenovo) was then used to assemble the draft genome with the default parameters. To improve the accuracy of the draft assembly, two-step polishing strategies were applied. The first step included three rounds of polishing by Racon v1.3.154 based on the corrected ONT long reads. The second step included four rounds of polishing by Nextpolish v1.0.555 based on cleaned Illumina short reads after removing adapters and low-quality reads using fastp v0.20.056 with parameters ‘-f 5 -F 5 -t 5 -T 5 -n 0 -q 20 -u 20’ . Finally, allelic haplotigs were removed using the purge_haplotigs v1.1.157 software with the options ‘-l 5 -m66 -h 170’ (set read depth between 5 and 170 and the low point between the haploid and diploid peaks as 66) to obtain the final contig-level assembly.The quality-controlled reads were first corrected via a self-align method using the NextCorrect module in the software NextDenovo v2.0-beta.1  v4.0.562 with the searching database of “embryophyte_odb10”.The completeness of the genome assembly was assessed both by the representation of Illumina whole-genome sequencing short reads from mapping back read to the assembly using bwa v0.7.1263, which incorporates well-performed structure-based and homology-based programs  and subsequent filtering scripts, for a comprehensive repeat detection. Subsequently, TEsorter 64 was used to reclassify those TEs that were annotated as “LTR/unknown” by EDTA.For repeat annotation, we used the Extensive de-novo TE Annotator (EDTA v1.9.3)65 to mask the whole-genome sequences with the TE library constructed using EDTA. An integrated strategy that combined homology-based prediction, transcriptome-based prediction, and ab initio prediction was used to predict the protein-coding genes. For homology-based gene prediction, published protein sequences of six plant species, including Populus euphratica, Salix brachista, Salix purpurea, Populus trichocarpa, Arabidopsis thaliana, and Vitis vinifera, were downloaded and aligned onto the repat-masked genome by using the TBLASTN (ncbi-BLAST v2.2.2866) program with E-value cutoff setting of 1e−5, and GeneWise v2.4.167 was then used to predict gene models with default settings. For transcriptome-based gene prediction, trimmed RNA sequencing reads from leaf, stem, and bud tissues were mapped to the reference genome using HISAT v2.2.168 with parameters “-max-intronlen (maximum intron length) 20000 –dta  -score-min  L, 0.0, -0.4”, and Trinity v2.8.469 was used for transcripts assembly with default parameters. Assembled transcripts were subsequently aligned to the corresponding genome to predict gene structure using PASA v2.4.170. For the ab initio prediction, Augustus v3.3.271 was employed using default parameters after incorporating the transcriptome-based and homology-based evidence for gene model training. Finally, all predictions of gene models generated from these approaches were integrated into the final consensus gene set using EvidenceModelerv1.1.170. After prediction, PASA was again used to update alternatively spliced isoforms to gene models and to produce a final gff3 file with three rounds of iteration.For gene annotation, we first used RepeatMasker v4.1.072 with default parameters. Ribosomal RNAs (rRNAs) were identified by aligning rRNA genes of P. trichocarpa_v3.1 to the assembly using blast. The other three types of ncRNA  were identified using Infernal v1.1.473 by searching the Rfam database v12.074.In addition, we also performed non-coding RNAs (ncRNAs) annotation. Transfer RNAs (tRNAs) were identified using tRNAscan-SE v2.0.775, COG, and KOG using NCBI BLAST + v.2.2.31 with an E-value of 1e−5 as the cutoff66. Motifs and domains were annotated by searching against InterProScan (release 5.32-71.0)76. Gene ontology (GO) terms and KEGG pathways of predicted sequences were assigned by InterProScan and KEGG Automatic Annotation Server, respectively77.For functional annotation, our predicted protein-coding genes were aligned to multiple public databases including NR, Swiss-Prot, TrEMBLA total of 230 individuals were collected from 24 natural populations across the total distribution of the species. Within each population, individuals were sampled after ensuring that sampled individuals were at least 100 m apart from each other. Genomic DNA was extracted from leaves with a Qiagen DNeasy plant kit, and whole-genome paired-end sequencing was generated using the Illumina NovaSeq 6000 platform with a target coverage of 20× per individual.78 to remove adapters and cut off bases from either the start or the end of reads if the base quality was <20. Trimmed reads shorter than 36 bases were further discarded. After quality control, all high-quality reads were mapped to our de novo assembled P. koreana genome using the BWA-MEM algorithm of bwa v.0.7.1761 with default parameters. The alignment results were then processed by sorting and PCR duplicate marking using SAMtools v.1.979 and Picard v.2.18.11 (http://broadinstitute.github.io/picard/). For genetic variant identification, SNP and indel calling were performed using the Genome Analysis Toolkit (GATK v.4.0.5.1)80 and its subcomponents HaplotypeCaller, CombineGVCFs, and GenotypeGVCFs to form a merged VCF file with “all sites” (including non-variant sites) included using the ‘EMIT_ALL_SITES’ flag. SV calling was performed using the software DELLY v0.8.381 with default parameters. We further performed multiple filtering steps to only retain high-quality variants for downstream analysis. For SNPs, SNPs with multi-alleles (>2) and those located at or within 5 bp from any indels were removed. In addition, after treating genotypes with read depth (DP) < 5 and genotype quality (GQ) < 10 as missing, SNPs with missing rate higher than 20% were filtered; for indels, those with muti-alleles (>2) and with QualByDepth (QD) < 2.0, strand bias estimated using Fisher’s exact test (FS) > 200.0, StrandOddsRatio (SOR) > 10.0, MappingQualityRankSumTest (MQRankSum) <-12.5, ReadPosRankSum < -8.0 were removed. Indels with missing rate >20% after treating genotype with DP < 5 and GQ < 10 as missing were further filtered out; for SVs, those with length <50 bp and with imprecise breakpoints (flag IMPRECISE) were removed. After treating genotypes with GQ < 10 as missing, we further filtered SVs with a missing rate >20%. Finally, we implemented the software SNPable (http://lh3lh3.users.sourceforge.net/snpable.shtml) to mask genomic regions where reads were not uniquely mapped, and we filtered out variants located in these regions. After these filtering steps, 16,619,620 SNPs, 2,663,202 indels, and 90,357 SVs were retained for subsequent analyses. The filtered variants were further phased and imputed using Beagle v4.182 and the effects of individual variants were annotated using SnpEff v.4.383 with “-ud 2000” to define the length of upstream and downstream regions around genes, with other parameters being set to default.For raw resequencing reads, we used Trimmomatic v0.36P. koreana around China, we performed ecological niche modeling (ENM) using Maxent v.3.3.384 with 19 current bioclimatic variables (Supplementary Table https://www.cvh.ac.cn/) and the Global Biodiversity Information Facility (https://www.gbif.org/zh/) into the ENM analyses, which was performed with default setting after excluding the highly correlated environmental variables (Spearman correlation coefficient >0.7).To investigate the current 1970–2000) potential distribution range of 970–2000 85 with the parameters “indep-pairwise 50 10 0.2” to extract an LD-pruned SNP set with minor allele frequency (MAF) > 5%, which yielded 535,191 independent SNPs to be used in the population structure analysis. First, we used ADMIXTURE v.1.3.086 with default parameters to investigate population genetic structure across all individuals, with the number of clusters (K) being set from 1 to 8. We then used the rda function from the R package vegan 2.6-287 to perform the PCA on the pruned SNPs. To further assess the relatedness between individuals, the identify-by-state (IBS) genetic distance matrix was calculated using the “-distance 1-ibs” parameter in PLINK v1.90. We constructed the NJ phylogenetic tree based on the distance matrix using MEGAX88 and displayed the tree using FigTree v.1.4.4. Finally, for the IBD analysis, we first used VCFtools v0.1.1589 to calculate the population differentiation coefficient (FST). The matrix of FST (1−FST) and the matrix of geographic distance (km) among different groups of populations were then used for performing the Mantel tests using the R package vegan87, with the significance being determined based on 999 permutations.We first used PLINK v1.90P. koreana, we calculated both intra-population (π) and inter-population (dxy) nucleotide diversity after taking into account both polymorphic and monomorphic sites using the program pixy v0.95.090 over 100-kbp non-overlapping windows. In addition, Tajima’s D statistics were calculated using VCFtools v0.1.15 in 100-kbp non-overlapping windows for the northern and southern groups of populations using the complete SNP dataset, respectively. To further estimate and compare the pattern of LD among different groups of populations, PopLDdecay v.3.4091 was used to calculate the squared correlation coefficient (r2) between pairwise SNPs with MAF > 0.1 in a 100-kbp window and then averaged across the whole genome.To estimate and compare genetic diversity across populations of 92 was used to infer historical changes in the effective population size (Ne) of P. koreana using default parameters with the entire genomic dataset. We selected seven individuals from both the northern and southern groups of populations to run the PSMC analyses, and 100 bootstrap estimates were performed per individual. Assuming a generation time of 15 years and a mutation rate of 3.75 × 10−8 mutations per generation93, we converted the scaled population parameters into Ne and years.PSMC94 to search for associations between allele frequencies and the 19 BIOCLIM environmental variables95. Based on the number of ancestry clusters inferred with ADMIXTURE v.1.3.0, we ran LFMM with three latent factors to account for population structure in the genotype data. For each environmental variable, we ran five independent MCMC runs using 5000 iterations as burn-in followed by 10,000 iterations. P values from all five runs were then averaged for each variant and adjusted for multiple tests using a false discovery rate (FDR) correction of 5% as the significance cutoff.We used two different approaches to identify environment-associated variants  across the whole genome. We kept only common variants with MAF > 10%, including a total of 5,182,474 SNPs, 736,051 indels and 30,934 SVs, for these analyses. First, we used a univariate latent-factor linear mixed model (LFMM) implemented in the R package LEA v3.3.296. RDA has been shown to be one of the best-performing multivariant GEA approaches and exhibits low false-positive rates29. After considering the ranked importance of the 19 environmental variables estimated using GF analyses with R package “gradientForest”46 and correlations among the variables, six environmental variables  with pairwise correlation coefficients |r | < 0.6 were selected for the RDA analyses using the R package vegan. Significant environment-associated variants were defined as those having loadings in the tails of the distribution using a standard deviation cutoff of 3 along one or more RDA axes.Second, we performed a redundancy analysis (RDA) to identify genetic variants showing an especially strong relationship with multivariate environmental axesFST(FST/1−FST) and geographic (IBD) and environmental (IBE) distance (after accounting for the geographic distance) with significance determined using 999 permutations in the R package vegan87, where environmental distance was represented by Euclidean distance of all scaled environmental variables. In addition, we used partial RDA to quantify the relative contribution of geography, population structure, and environment in explaining the proportion of adaptive and neutral genetic variation. Three datasets were used: (1) six uncorrected environmental variables used as in the above RDA analysis (‘clim’); (2) three proxies of population structure ; and (3) population coordinates  to characterize explanatory variables of climate, population structure, and geography. For the two RDA models, population allele frequencies of adaptive and neutral variants were used as the response variables, respectively. The significance of explanatory variables was assessed using 999 permutations with the function anova.cca of the R package vegan.To investigate and compare the role of geography and environment in shaping spatial genetic variation of adaptive (the 1779 adaptive variants identified by both LFMM and RDA) and neutral  variants, Mantel and partial Mantel tests were separately used to test for associations between 97 and calculated the standardized iHS across the genome for common variants using the software selscan v.1.3.098.To further assess selection pressures acting on climate adaptive variants, we assessed the extended haplotype homozygosity (EHH) pattern for a selected set of strongly associated variants using the R package “rehh”P. koreana were surface sterilized by soaking in 10% sodium hypochlorite solution and 70% ethyl alcohol for 5 min and then thoroughly washed five times with distilled water. The stem segments were inserted into MS medium (0.05 mg/L NAA) for 30 days at 25/20 °C (day 16 h/night 8 h), and, after rooting, the stem segments were transplanted to the soil for 40 days at 25/20 °C (day 16 h/night 8 h). To explore the effect of different genotypes of one candidate adaptive SNP located in the 5’ UTR of Pokor12247 (LG04:25159299) in mediating adaptation to extreme precipitation, we carried out a submergence treatment. For the submergence treatment, water was maintained at 2 cm above the soil surface and plants were maintained in the growth chamber providing 25 °C/20 °C (day 16 h/night 8 h) for 0, 3, 6, 9, and 12 h. In addition, we also carried out a heat stress treatment to explore the effect of one candidate adaptive SNP located in the intronic region of Pokor17228 (LG07: 4796402) in response to heat stress. For the heat stress treatment, plants were placed into a plant incubator at 42 °C/20 °C (day/night) with the illumination of 16/8 h (day/night) for 0, 1, 2, 3, and 24 h. At each time point, leaf tissues were collected from each plant at the same place and frozen immediately in liquid nitrogen for expression analyses.Stem segments from wild genotypes of 99 was used to investigate the expression levels of selected genes in the abiotic treatments (Pokor12247 for submergence stress and Pokor17228 for heat stress). Total RNA was extracted from pooled leaf materials using a Plant RNA extract kit , and the HiScript II RT SuperMix for qPCR kit (+gDNA wiper)  was used to obtain cDNA. qPCR was performed with gene-specific primers P. koreana and prepared according to the experimental protocol following ref. 78 with a maximum of two seed mismatches, and the adapters were trimmed by NexteraPE. Then, the clean reads were aligned to the reference genome using Bowtie v.2.3.258 using the following parameters: ‘bowtie2 -very-sensitive -N 1 -p 4 -X 2000 -q’ . Aligned reads were sorted using SAMtools v.1.1.179. The redundant reads from PCR amplification and reads that mapped to either chloroplast or mitochondria were removed using Picard v.2.18.11 (http://broadinstitute.github.io/picard/). Finally, only high-quality properly paired reads were retained for further analysis. ATAC-seq peak calling was done by MACS2101 with the ‘-keep dup all’ function.For the ATAC experiment, fresh leaf tissues were collected from the same individual used for the genome assembly of 95. Each of the two future environmental datasets consists of two shared socioeconomic pathways (SSPs): SSP126 and SSP370. We used three different approaches to evaluate the genomic offset to future climate change.For each sampling location, we downloaded future (2061–2080 and 2081–2100) environmental data for the 19 BIOCLIM variables from the WorldClim CMIP6 dataset of four different climate models 18, which quantifies the theoretical average change in allele frequency needed to cope with climate change, under projected future climate scenarios. Following the method used in ref. R2 for each linear regression following ref. First, we calculated the RONAP. koreana using ‘gradientForest’ in R46. For each given climate model, we built a GF model for estimating the genetic offset under the different future scenarios with both the 19 environmental variables and the six environmental variables. The genetic offset was calculated as a metric for the Euclidean distance of the genomic composition between the current and future projected climates and then mapped with ArcGIS 10.2 to display its geographical distribution. Given the high correlation of genetic offset that was estimated across models, the average values of genetic offset across models were used to predict the local maladaptation to future climate. Same as RONA, the genetic offset was also calculated and compared among the three different types of variants .Second, as a complementary approach to RONA, we used a non-parametric, machine-learning GF analysis to calculate genomic offset across the range of Third, following the approach used in ref. P. koreana. To assess the deleterious genetic load carried by each population, the effects of SNP variants on protein-coding gene sequences were first annotated and categorized as LOF, deleterious (SIFT score < 0.05), tolerated (SIFT score < 0.05), or synonymous based on the sorting intolerant from tolerant (SIFT) algorithm implemented in SIFT4G software using UniRef100 as the protein database48. The derived versus ancestral allelic state was determined at each SNP position using the est-sfs software102 through comparison with P. trichocarpa sequences103. Then, the ratio between the number of derived mutations at LOF, deleterious, and tolerated sites relative to the number of synonymous variants was calculated and used as proxies for genetic load per population. In addition, as SVs are, on average, deleterious, we further calculated the SV burden represented by the averaged ratio of heterozygous SV to heterozygous SNP across individuals for each population. Finally, we used the cor.test function in R to calculate the Spearman’s correlation coefficients between the three metrics of genetic offsets  under two future scenarios (SSP126 and SSP370) in 2061–2080 and the above proxies of genetic load across the 24 populations, respectively.Finally, we explored whether there was an association between the genomic offset to future climate change and the accumulation of genetic load across populations of Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Reporting Summary


Cymbopogon citratus is a morphologically diverse MAP that is largely exploited in the food, cosmetics, and pharmaceutical industries. However, the intraspecific phytochemical and molecular diversity of C. citratus has yet to be explored.Genetic diversity is being lost because of increasing urbanization and decreasing cultivation land, which leads to the abrupt use of wild resources of medicinally aromatic plants (MAPs). The germplasm was obtained from four different countries representing Pakistan, India, Bangladesh, and the United States. Oil extraction was performed by hydro distillation, and metabolic profiles of different accessions were generated by GC–MS. Seventeen functional molecular markers based on three genes encoding cytochrome P450, uridyl diphosphate glycosyltransferase and the 5S rRNA gene family were used to explore genetic diversity. Principal component analysis (PCA) and heatmaps were constructed using R software with the help of the gg-plot R package v1.0.5 for data validation.Among the 208 identified metabolites, citral was maximal, with a phytochemical contribution (1.92–27.73%), α-pinene (0.82–15.57%), verbenol (0.24–22.84%), neral (0.23–21.31%) and geranial acetate (0.43–15.65%). In the majority of accessions, citral was the dominant component. The highest concentration of citral was detected in 384541 (27.74%), 384527 (27.52%) belonging to Pakistan and one USA-based accession 38456 (27.71%). Region-specific grouping revealed a relationship between genetic diversity and geographical location. Pakistani accessions 384518, 38452, and 384544 genetically and 384535, 384518, and 384510 were phytochemically diverse.The genetic diversity was more pronounced in cultivated accessions than in wild accessions. Moreover, it was observed that phytochemical diversity correlated with the altitude and temperature of the region. To meet the increasing demand, it is necessary not only to increase the yield of existing crops but also to find new potential resources for EO production (Cymbopogon citratus (D.C.) Stapf, could be a significant source of essential oil  are complex mixtures of secondary metabolites extensively used in cosmetics, pharmaceutics, and food additive industries . Currentoduction . Cymbopotial oil . It is ncitratus . However million .C. citratus serves as a rich source of citral, geranial, neral, α-pinene, verbenone, and limonene  and exogenous  factors. These endogenous and exogenous factors are fully recognized for some aromatic and medicinal plants but are limited for this plant species  and America to explore the molecular and phytochemical diversity. The collected germplasm was submitted to the GenBank of the Institute of Agro-Biotechnology and Genetic Resources (IABGR). The specimens were submitted to the National Agriculture Research Centre (NARC), Islamabad, Pakistan, for voucher numbers and tiller multiplication for future use (A panel of forty accessions of ture use .C. citratus (500 g) were subjected to hydrodistillation in 800 mL water in a clevenger-type apparatus for 4 h  on polar and apolar columns, resolute relative to the RT of a sequence of n-alkanes with lined interpolation with those of reliable compounds and already published data . The comC. citratus using the CTAB method (Genomic DNA was extracted from 2 g leaf samples of B method . SeventePolymerase chain reaction (PCR) was performed by following the methodology of Genetic relationships among different accessions were analyzed using DARwin software v6 . Factorihttps://pubchem.ncbi.nlm.nih.gov) constituted 94.6% to 99.8% of the total composition of C. citratus essential oils. Twenty-seven compounds with a proportion higher than 1% in at least one accession were observed  butanal, Pentadeca-1,3,7,12,14-pentaen-7-ol-9, 3,7-cycloundecadien-1-ol,1,5,5,8-tetramethyl and 1,5,9-undecatriene-2,6,10-trimethyl, were detected only in Pakistani accessions 384518 , 38452 (Alipurchatha), 384522 (Sargodha) and 384510 (Kujah), respectively, whereas two compounds, phenol, 2-, and 1-cyclohexyl-2-buten-1-ol, were specific to the United States . One comThe average oil yield among wild accessions was observed to be 1.17 ± 0.21 mL/g, whereas cultivated accessions showed 1.32 ± 0.42 mL/g, as presented in C. citratus , 38454 (Dhaka), 384512 (Amritsar), 38456 (Virgin Island), 384520 (Islamabad), and 384514 (Pattoki) were found, while in the wild accessions, 384519 (Islamabad), 38452 (Alipurchatha), 384510 (Kunjah), 384515 , 384542 (Daska) and 38457 (Khairpur) were found to be genetically diverse and represented the polymorphism with the primers P3, P4, P5, P8, P14, P17, P12, P13, P15, and P16 . In the present study, Methyleugenol was detected in a high proportion, i.e., 11.19% agreeing, with the findings of C. citratus. Verbenone and limanone were present in more than 1%, whereas in the literature, they were reported up to 1%  than wild accessions (1.17 ± 0.21 mL)  . In cont0.21 mL) . Howevercessions . The difectively . SimilarThymbra spicata var. spicata L. collected from a lower altitude  butanal, pentadeca-1,3,7,12,14-pentaen-7-ol-9, 3,7-cycloundecadien-1-ol,1,5,5,8-tetramethyl and 1,5,9-undecatriene-2,6,10-trimethyl, were detected only in Pakistani accessions 384518 , 38452 (Alipurchatha), 384522 (Sargodha) and 384510 (Kujah), respectively. Previously, these compounds were detected in the essential oils of n beings . These cn beings  and to tn beings . Therefoammatory  and antiammatory . These cer cells . Compoundiseases . These cC. citratus (The discovery of novel compounds has a great impact on the biochemical profiling of MAPs. Almost 30 compounds were reported from different accessions of citratus . These cCymbopogon to reveal high polymorphism (Essential oil composition is important for food production and is used as a natural preservative . Howevermorphism . For furmorphism . Many scmorphism . Site-spmorphism . Two accmorphism . The premorphism .C. citratus. The accessions were found to be phytochemically and genetically diverse and strongly associated with geographical origin. A positive correlation was observed between the EO yields with altitude and temperature, but a poor correlation was observed with precipitation, suggesting no effect on the composition of the essential oil of C. citratus.A positive correlation was observed between the phytochemical and molecular traits of C. citratus collected from four countries. Molecular data showed a strong relationship with the essential oils of C. citratus. The essential oil yield showed a significant association with geographical origin, altitude, and domestication, suggesting an edit effect on the biosynthesis of EOs. Moreover, molecular analysis using functional molecular markers revealed that the accessions of C. citratus were highly polymorphic and genetically diverse in association with their geographical origin. Phytochemical and genetic variation was more pronounced in the cultivated accessions than in the wild accessions. These results lay the foundation for breeding and genetic enrichment programs of C. citratus. However, more research is required to improve the knowledge about domestication and genetic variability among wild and cultivated accessions. Further analyses of EOs are necessary to evaluate medicinally important novel compounds for their utilization in the pharmaceutical and cosmetic industries.The current study evaluated the diversity in the essential oil chemical profile and genetic makeup among wild and cultivated accessions of 10.7717/peerj.13505/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.13505/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.13505/supp-3Supplemental Information 3Click here for additional data file.