Zanthoxylum bungeanum and Zanthoxylum armatum, is an economically important crop popular in Asian countries due to its unique taste characteristics and potential medical uses. Numerous cultivars of Chinese pepper have been developed in China through long-term domestication. To better understand the population structure, demographic history, and speciation of Chinese pepper, we performed a comprehensive analysis at a genome-wide level by analyzing 38,395 genomic SNPs that were identified in 112 cultivated and wild accessions using a high-throughput genome-wide genotyping-by-sequencing (GBS) approach. Our analysis provides genetic evidence of multiple splitting events occurring between and within species, resulting in at least four clades in Z. bungeanum and two clades in Z. armatum. Despite no evidence of recent admixture between species, we detected substantial gene flow within species. Estimates of demographic dynamics and species distribution modeling suggest that climatic oscillations during the Pleistocene  and recent domestication events together shaped the demography and evolution of Chinese pepper. Our analyses also suggest that southeastern Gansu province is the most likely origin of Z. bungeanum in China. These findings provide comprehensive insights into genetic diversity, population structure, demography, and adaptation in Zanthoxylum.Chinese pepper, mainly including  Zanthoxylum is an economically important aromatic genus of the Rutaceae family, which also includes Citrus3. This genus consists of ~250 species primarily native to warm temperate and subtropical regions across the world4. The fruits of Zanthoxylum have long been used in eastern Asian countries as a popular spice to improve taste, mainly due to the unique tingling oral sensation created by chemical compounds known as alkamides5. In addition to culinary applications, many species of Zanthoxylum have been used as traditional medicines with the functions of promoting blood circulation, regulating the meridians, removing cold dampness, strengthening teeth, and improving eyesight, as recorded in many classic monographs of medicine, including ShenNongBenCaoJing  7. To date, Zanthoxylum fruits have been officially applied in more than 30 prescriptions for the treatment of numerous diseases10. Consequently, this genus has great potential for the development of industrial products and new drugs.E.) Fig. , Mingyi Zanthoxylum genus. Currently, China harbors at least 45 species and 13 varieties within this genus, of which Zanthoxylum bungeanum and Zanthoxylum armatum are the most popular species due to their wide range of cultivation and versatile applications (collectively referred to as Chinese pepper henceforth)11. Z. bungeanum is believed to be native to China and has a long history of cultivation beginning in the Jin Dynasty (265–420 C.E.)12. Z. armatum is also known as Indian prickly ash or toothache tree and is mainly distributed in Southwest China13. Chinese pepper was first described nearly 2600 years ago in Shijing (Classic of Poetry), which recorded that in the period of the pre-Qin Dynasty (before 221 B.C.), the fruits of Chinese pepper were regarded as precious tokens and used to worship ancestors and pray for more children or a good harvest12. The earliest cultivation of Chinese pepper probably occurred in Sichuan at least 1500 years ago, where an abundance of improved varietal resources were available  approach in a collection of 112 Z. bungeanum and Z. armatum accessions from 43 cultivars/populations from the current range to resolve key questions in Zanthoxylum evolution.Although numerous landraces and elite cultivars potentially locally adapted to nationally diverse habitats have been developed via thousands of years of natural and artificial selection, domestication, and evolutionary processes  and 87 Z. bungeanum accessions into four clades  genotyped for 112 accessions, including 87 ade Fig. , followie I Fig. .Fig. 1Geπ) analysis showed that Clades II and III of Z. bungeanum had the highest genetic diversity, followed by Clade I. The genetic diversity of Clades II and III was threefold higher than that of Z. armatum clades  between the five major Zanthoxylum clades and found substantially higher genetic differentiation between Z. bungeanum clades (FST = 0.0998−0.1557) than between Z. armatum clades  over time for each clade separately. The stairway plot revealed that clades from the same species shared highly similar patterns of historical fluctuation in Ne over time that roughly mirrored known events of environmental upheaval. Each of the Z. bungeanum clades underwent long-term steady population expansion during the early-to-mid-Pleistocene era (~1.8–0.13 million years ago (mya)), although the patterns differed slightly, followed by an apparent steep decline in Ne after the Last Glacial Maximum (LGM) , respectively, until the LGM slowed down or prevented that process  reflect signatures of past demographic events. Here, we used folded SFS derived from each clade and the model-flexible stairway plot methodGM) Fig. , left. Cess Fig. , right. Zanthoxylum, since the estimated potential distributions of both species have changed over the past 130 kya. For Z. bungeanum, we observed a notable extensive collapse in suitable habitats from the LGM to mid-Holocene and somewhat of a recovery at present. For Z. armatum, we found a slight contraction in a suitable distribution area during the LGM and extensive habitat recovery from the mid-Holocene to the present day. The dynamic ranges of these two species supported the idea that the formation of these genetically distinct lineages may be due to periodic fragmentation, possibly isolation events derived from climate change.Results from species distribution modeling (SDM)  produced a much better fit than alternative models. The isolation-with-migration model with asymmetric migrations and exponential population decline in cultivated Z. armatum (Model 11) and the model assuming exponential decay in both wild and cultivated Z. armatum without extensive postdomestication gene flow (Model 12) generated similar log-likelihoods given the data but lower Akaike information criterion (AIC) scores due to having additional parameters. Assuming a mutation rate of 2.6 × 10−9 substitutions per site per year20 and 4 years per generation, we estimated a split time of ~5440 years ago and a 200-fold decline in Ne for cultivated Z. armatum  was the optimal model, with a maximum log-likelihood value of −21,074. This model supported the results of stairway plot analysis in terms of the demographic decline during the LGM for all three clades . We found that FXDHP was most closely related to CBDHP and MWHJ from Gansu and Sichuan, respectively. HCDHP shared more drift with QAYJ and WDBYJ in Gansu, MCHJ in Henan, and SXHJ in Hebei than any other native cultivars in Shaanxi. HYHJ showed higher levels of allele sharing with ZTHJ and YXHJ in Yunnan  framework by fitting empirical and predicted f-statistics. AGs are generalizations of phylogenetic trees combined with admixture events, which are believed to be powerful tools for revealing a more complex history than can be captured by a simple tree-like topology because AGs predict all patterns of f-statistics  that can be used to assess the fit of a proposed evolutionary scenario. Figure Z. armatum cultivars that was a good fit to the data, as none of the predicted f-statistics were more than three standard errors from the observed values (max|Z| = 2.776). Using this model, we observed a highly reticulated relationship among cultivars of Clade V, whereas all cultivars of Clade VI descended from a putative ancestral population derived from an admixture event between FXZYJ and a more ancient ancestor. Figure Z. bungeanum cultivars, despite the largest |Z|-score for differences between observed and predicted f-statistics reaching 5.52 among the 14,706 statistics we tested. This indicated that more subtle gene flow events were needed to accommodate the data. However, this model provided a better statistical fit to the data than the tree shown in Fig. To construct an explicit model for the settlement of each Z. bungeanum revealed by fastSIMCOAL2 and indicated that southeastern Gansu  was the most likely origin of this species. Second, FXDHP and MWHJ, located in the opposite direction of WDDHP, have experienced very little genetic drift since divergence from their common ancestral population shared with WDDHP and formed a branch, suggesting recent anthropogenic contributions to the migration of this clade in this region. Third, we observed multiple streams of origin-to-north gene flow that might have contributed substantially to the genetic diversity in Clade I. Most Shanxi populations  descended entirely from a single ancestral population shared with WDDHP and formed a simple cluster. The direct migration from the origin to Shandong without an intermediate zone was in accordance with the historical record that business activity promoted the spread of cultivation practices in this region no later than 1400 years ago (Qimin Yaoshu). We also inferred back-migration of populations related to WDBYJ from Shanxi to the origin. WDBYJ provided several strands of ancestry that spread to northern China, including the formation of LWHJ and ZZDHP (both in Shandong) as well as HCDHP (Shaanxi). Finally, we concluded that Clade III populations derived large proportions of their ancestry from both Clades I and II, namely, an estimated 25% from one basal population of Clade I and 75% from a population closely related to WDBYJ. This conclusion was consistent with the extensive gene flow from Clade I to Clade III revealed by fastSIMCOAL2.First, the above result was consistent with the divergence pattern of FST values than expected  identified a set of 24 outlier loci with higher ted Fig. . Twenty Z. bungeanum and Z. armatum accessions using next-generation sequencing.Chinese pepper, also known as “Huanjiao,” is an economically important tree plant widely used as a spice and medicine with a national distribution in China. Unraveling the genomic relationships and evolutionary history of Chinese pepper can help clarify the interspecific admixture and gene flow between various cultivars, as well as infer the origin of domestication and pattern of historical fluctuation in effective population size. To the best of our knowledge, this is the first report to comprehensively study the genetic relationships and demographic history of a collection of Z. bungeanum and Z. armatum have clearly split without secondary contact, inhibiting the formation of reproductive isolation. Moreover, we found strong evidence for splitting into at least four genetic clades within Z. bungeanum, corresponding to the geographic distribution from these combined analyses, including genetically distinct clades that contain only individuals from the HYDHP cultivar. In contrast, Z. armatum accessions are separated into wild and cultivated groups. These results are consistent with our previous report that the Qinling Mountains were the main geographic barrier for gene flow between Z. bungeanum clades and that cultivated and wild Z. armatum accessions exhibited significant genetic differentiation35. How does such strong genetic structure occur in a domesticated species of plant? First, Z. bungeanum covered a wider distribution range across China than Z. armatum. Plant populations with a large distribution tend to form subpopulations due to environmental heterogeneity, genetic variation, and restricted gene flow, which are all found in Z. bungeanum and may have led to its strong genetic differentiation. Second, as local adaptation plays an essential role in maintaining production in traditional agricultural systems, selection for adaptation to each region’s environment and monocultures of genetically similar individuals formed regionally by farmers’ seed selection increases overall genetic diversity but leads to little to no genetic variation within local cultivars. Thus, the strong differentiation between Z. bungeanum clades likely reflects the effects of both geographical isolation due to the Qinling Mountains as well as a long period of divergent domestication.Based on PCA, phylogenetic analysis and genetic structure analysis, we believe that Z. bungeanum was threefold higher than that of Z. armatum, which was probably attributed to the restricted distribution and thus limited sampling of Z. armatum and otherwise the frequent local or long-distance exchange of seeds of Z. bungeanum by farmers during long-term traditional agricultural practices. Puzzlingly, although the domesticated accessions of Z. armatum were clearly genetically differentiated from wild ones, they still possessed variation even higher than that of wild varieties. This result suggests that the population size bottleneck at domestication only slightly reduced genetic variability . Consistent with our previous study of the transcriptome20, Chinese pepper presents a higher level of heterozygosity  niche modeling paralleled the population size change patterns of both species. It is noteworthy that the relatively cold and dry climate of Marine Isotope Stage 4  and the LGM did not result in population declines in either of the Z. armatum clades but did have a strong negative effect on Z. bungeanum. One potential explanation for this apparent disparity is that the Z. armatum populations we analyzed were mainly from mountain regions in Southwest China, one of the world’s major plant diversity hotspots38. This region is thought to have harbored refugia during the LGM because organisms survived there and recolonized (radiated) outwards during interglacial periods39. The proposal that the topographical complexity of this region may be a crucial buffer against climate change was further confirmed by the unequal decay in Ne of Z. bungeanum clades during the LGM. The LGM resulted in a ~660- and 100-fold collapse in Clades I and II, respectively, both of which were mainly distributed in northern or northwestern China. In contrast, we observed only a sixfold decrease in Ne for Clade III during the LGM, which was largely sympatric with Z. armatum. This result indicates that plants sharing the same habitat might have similar responses to climate change and thus similar demographic histories.To explore the demographic histories of Ne for Zanthoxylum clades before the LGM raises the question of its causes. One possibility is that the expansion of Ne might be attributed to the high heterozygosity of these Chinese pepper clades  and clonal propagation. The feature of demographic inference from grape is consistent with our hypothesis, but wild grape also had a greater than fivefold Ne increase following the LGM.The protracted increase in Z. armatum and Z. bungeanum was ~12 mya , which was written 2600 years ago. The demographic analysis of Z. bungeanum showed that emergence and diversification occurred ~220 kya, long before human agricultural activity. These results suggested multiple origin centers for the domestication of Chinese pepper and weak selection pressure during this process. The fastSIMCOAL2 analysis also revealed that the timescale of divergence between Clades I and II/III coincided with the onset of the Penultimate Glaciation (0.3–0.13 mya), one of the most extensive Pleistocene glaciations in China that resulted in large ice caps and extremely large valley glaciers37. More specifically, this method detected severe bottlenecks for each clade during this period that were not observed in the stairway plot analysis. These findings are largely in line with expectations if climate change has been a major driver of variation in Z. bungeanum population size. The association of rapid divergence with key glacial periods suggests, but does not confirm, that Z. bungeanum divergence was driven by glacial cycles that resulted in direct habitat fragmentation, with adjacent refugia separated by glacial fingers.In our study, we speculate that the divergence time of mya Fig. . This in6. Some were developed locally, and others were introduced. Distinct regional demands for different cultivars reflect local idiosyncrasies in consumer tastes; for instance, the cultivars of Z. bungeanum distributed within the tropical and subtropical regions south of the Qinling Mountains contain more numbing components but fewer leaf glandular puncta than those north of the Qinling Mountains35. We assessed the affinities between each variety/cultivar pair using three approaches. Based on outgroup-f3 tests and D-statistics, cultivars distributed in the vicinity of the Qinling Mountains showed the closest genetic relationships, while those far from the Qinling Mountains displayed introgression from one or more cultivars in relatively close proximity. These results indicated that some elite cultivars have been introduced and cultivated in many other areas across China. Nonetheless, there is no evidence of recent admixture between species because of probable reproductive isolation. In addition, we speculate that Gansu is the most likely origin of Z. bungeanum, which is in accordance with the earliest historical record of Chinese pepper in Qimin Yaoshu12.Chinese pepper is among the earliest domesticated crops, with several thousands of years of cultivation history. Numerous varieties of Chinese pepper have been cultivated during the long-term domestication processZ. bungeanum corresponding to their geographic distributions across China. Domesticated Z. armatum accessions (Clade VI) were found to be genetically differentiated from wild ones (Clade V), but they maintained high levels of genetic variability, suggesting a short domestication event involving a large number of individuals. This may also hold true in Z. bungeanum because we observed a relatively large effective population size in each clade of Z. bungeanum.This is the most comprehensive survey of the evolutionary history of Chinese pepper to date. We identified at least three genetic clades within Z. bungeanum, and the divergence among Z. bungeanum clades occurred ~200 kya. Wild accessions of Z. armatum clustered together and possibly diverged from cultivated accessions ~3−5 kya. Moreover, our results suggest that climate change drove an apparent steep decline in the effective population size of Z. bungeanum clades, rather than Z. armatum clades, during the LGM. Further insights into the history of Zanthoxylum will benefit from analyses similar to those performed here on whole genome sequences and from the collection of data from more populations of Zanthoxylum taxa. This could greatly aid in the curation of the many misidentified accessions and accelerate molecular breeding efforts for cultivated Zanthoxylum species.Based on our results, we can outline a model for the early evolutionary history of Chinese pepper. We infer that WDDHP (Gansu) was the ancestral population of Z. bungeanum accessions and 13 Z. armatum accessions from 39 cultivars in their native range throughout China. In addition, 12 wild accessions of Z. armatum from four natural populations were sampled in Yunnan, Guizhou, Sichuan, and Shaanxi provinces .Based on field investigations and with the permission of private landowners, we collected 87 ces Fig. . Young, ® DNA Assay Kit in a Qubit® 2.0 Fluorometer . First, a predesign experiment was performed to select the best restriction enzyme and sizes of restriction fragments. To maintain the sequence depth uniformity of different fragments, a narrow length range was selected (~50 bp). Afterwards, the GBS library was constructed according to the predesigned scheme. Genomic DNA template was incubated at 37 °C with EcoRI (New England Biolabs), followed by ligation with adapters that included different barcode-containing adapters for tagging each sample. Ligation was performed using T4 DNA ligase (New England Biolabs) followed by heat inactivation at 65 °C. Afterwards, PCR was performed to amplify the bilateral tag sequences. The PCR products were purified using Agencourt AMPure XP (Beckman), pooled, and then run on a 2% agarose gel. Fragments 400–425 bp (with indexes and adapters) in size were isolated using a gel extraction kit (Qiagen). These fragment products were then purified using Agencourt AMPure XP (Beckman), which was diluted for sequencing. Paired-end sequencing was performed on selected tags using the Illumina PE150 high-throughput sequencing platform  with 2 × 150 bp paired reads. SNP genotyping and evaluation were subsequently carried out.The protocol used to obtain the GBS library involved three major steps: restriction digestion, ligation, and PCR amplification. DNA concentration was measured using a Qubit49 with dp1 and Miss0.6 filters. Polymorphic bases detected among SNPs were supported by at least three reads for each respective SNP.Sequences for each sample were sorted according to barcodes. To ensure that reads were reliable and without artificial bias in subsequent analyses, we first processed raw data in the fastq format using a series of quality control procedures with in-house C scripts. Briefly, this involved (1) removing reads with ≥10% unidentified nucleotides (N); (2) removing reads with >50% bases possessing a phred quality score <5; and (3) removing reads with >10 nt aligned to adapters, allowing ≤10% mismatches. Subsequently, all reads mapped to the same location were considered a “stack.” SNP sites were identified within each stack using SAMtoolsZanthoxylum cultivars was analyzed using five complimentary methods: neighbor-joining tree analysis, PCA, sNMF50, fastSTRUCTURE51, and DAPC52. These analyses were based on datasets retaining only one random SNP per locus to avoid creating a set of tightly linked sites. Neighbor-joining tree and PCA approaches were applied using the R package poppr53. The most likely number of genetic clusters was determined by (1) running sNMF with 1 − K assumed ancestral populations using an entropy criterion to fit the statistical model to the data by cross-validation; (2) running fastSTRUCTURE for multiple numbers of K using fivefold cross-validation and comparing the log-marginal likelihood lower bound; and (3) running DAPC for multiple numbers of K and comparing AIC values. All analyses were repeated after removing loci under strong divergent or stabilizing selection to reflect demographic processes such as gene flow and genetic drift. The repeated analyses resulted in no significant differences. Patterns of variation and population differentiation, including patterns of nucleotide diversity (π), heterozygosity, and the fixation index (FST)54, were estimated based on the genotypes of each line at SNP positions using VCFtools55.The genetic structure of 56 with the folded SFS from each clade (estimated as described above). The results were calibrated using a generation time g = 4 years based on field observations and a mutation rate μ = 2.6 × 10−9 substitutions per site per year according to the literature20. To study the history of population splitting, we used SFS-based composite likelihood demographic modeling implemented in fastSIMCOAL231. The same method was also used to reconstruct a more recent Z. armatum demographic history that could not be estimated by stairway plots due to the very limited amount of variation within this species.Single-population demographic histories were investigated using the stairway plot methodZ. armatum . We used 100,000 simulations and 50 cycles of the Brent algorithm to maximize the likelihood of the models. A total of 50 independent optimizations were performed to retain the global maximum likelihood model, and the maximized likelihood observed across all iterations was used for model comparison.The observed two- and three-dimensional SFS and bootstrap SFS scores for Z. armatum and Z. bungeanum, we constructed correlative maps of potential distributions with the statistical niche modeling algorithm MaxEnt v3.457 using records of species presence and environmental data. The model was projected to past environmental conditions during the mid-Holocene (6000 years before present (y B.P.)), the LGM at 21,000 y B.P. , and the Last Interglacial at 120,000 y B.P.58.To assess spatial variation in environmental suitability for Z. bungeanum and 322 for Z. armatum) from our fieldwork, herbarium databases (https://www.cvh.ac.cn), and the Global Biodiversity Information Facility (https://www.gbif.org), which were then vetted for spatial and taxonomic accuracy. To reduce the effects of sampling bias on model prediction, we randomly selected one of multiple occurrence records per species within a 10 km radius using SDMtoolbox59. The final dataset for SDM building was composed of 133 records of Z. bungeanum and 166 records of Z. armatum. As background data, we randomly selected 10,000 points over the entire distribution area of each species. We extracted climate information from 19 layers of bioclimatic variables available from the WorldClim website and selected seven uncorrelated variables (Pearson correlation < 0.7) downloaded from Bioclim at a 2.5 arc minute resolution: mean diurnal range, isothermality, minimum temperature of the coldest month, mean temperature of the wettest quarter, precipitation of the driest month, precipitation seasonality, and precipitation of the warmest quarter.We gathered 522 georeferenced occurrence points  indicated good predictive power and performance significantly better than that of a random model (AUC = 0.5). The most important variable was minimum temperature of the coldest month .Models were run using the autofeatures function, the default regularization multiplier, and 100-replicate subsampling, with random training test percentages (70% of observations for model training and 30% for model testing). To determine whether the discrimination capacity of models was better than random chance, models were validated by assessing area under the receiver operating curve (AUC), sensitivity, specificity, and accuracy values averaged across replicates. The high mean AUC values  observed between all pairs, triplets, and quadruplets of populations and tested whether they differed significantly from empirical values.60, and retained only graph solutions yielding a minimum |Z| value between empirical and predicted f-statistics. To reduce computational load and model-solving difficulties, some genetically similar and geographically close cultivars were merged into one genetic group . We assessed the robustness of the best model and its predictions using pooled f-statistics and by fitting the model using cultivars added in different orders.We started with a skeleton phylogenetic tree consisting of HYDHP and three randomly chosen cultivars, added the remaining cultivars incrementally to all possible edges in the tree using ADMIXTUREGRAPH63, OutFLANK64, the Fdist method implemented in Arlequin 3.565, and FLK66. Tests were performed first on a dataset in which samples were grouped into two populations, representing the two species, to identify outlier loci under divergent selection. Then, tests were carried out on each species separately, and samples were grouped according to the results from genetic analyses, namely, wild and cultivated groups for Z. armatum and three major geographic groups for Z. bungeanum, to look for signatures of spatially diversifying selection. Loci that were identified as outliers by all tests were considered to be under putative selection.Four outlier tests were used to scan for signatures of selection, namely, LEAsuppementary information


Shaanxi province, located in the upper Yellow River, has been evidenced as the geographic origin of Chinese civilization, Sino‐Tibetan‐speaking language, and foxtail or broomcorn millet farmers via the linguistic phylogenetic spectrum, archeological documents, and genetic evidence. Nowadays, Han Chinese is the dominant population in this area. The formation process of modern Shaanxi Han population reconstructed via the ancient DNA is on the way, however, the patterns of genetic relationships of modern Shaanxi Han, allele frequency distributions of high mutated short tandem repeats (STRs) and corresponding forensic parameters are remained to be explored.Here, we successfully genotyped 23 autosomal STRs in 630 unrelated Shaanxi male Han individuals using the recently updated Huaxia Platinum PCR amplification system. Forensic allele frequency and parameters of all autosomal STRs were assessed. And comprehensive population genetic structure was explored via various typical statistical technologies.Population genetic analysis based on the raw‐genotype dataset among 15,803 Eurasian individuals and frequency datasets among 56 populations generally illustrated that linguistic stratification is significantly associated with the genetic substructure of the East Asian population. Principal component analysis, multidimensional scaling plots and phylogenetic tree further demonstrated that Shaanxi Han has a close genetic relationship with geographically close Shanxi Han, and showed that Han Chinese is a homogeneous population during the historic and recent admixture from the STR variations. Except for Sinitic‐speaking populations, Shaanxi Han harbored more alleles sharing with Tibeto‐Burman‐speaking populations than with other reference populations. Focused on the allele frequency correlation and forensic parameters, all loci are in accordance with the minimum requirements of HWE and LD. The observed combined probability of discrimination of 8.2201E‐28 and the cumulative power of exclusion of 0.9999999995 in Shaanxi Han demonstrated that the studied STR loci are informative and polymorphic, and this system can be used as a powerful routine forensic tool in personal identification and parentage testing.Both the geographical and linguistic divisions have shaped the genetic structure of modern East Asian. And more forensic reference data should be obtained for ethnically, culturally, geographically and linguistically different populations for better routine forensic practice and population genetic studies. Population genetic analysis based on the raw‐genotype dataset among 15,803 Eurasian individuals and frequency dataset among 56 populations generally illustrated that linguistic stratification is significantly associated with the East Asian population genetic substructure. Principal component analysis, multidimensional scaling plots, and phylogenetic tree further demonstrated that Shaaxi Han has a close genetic relationship with geographically close Shanxi Han, and showed that Han Chinese is a homogeneous population during the historic and recent admixture. Except for Sinitic‐speaking populations, Shaanxi Han harbored more alleles sharing with Tibeto‐Burman‐speaking populations than with other reference populations. Multiplex amplification was performed on a ProFlex 96‐well PCR System (Thermo Fisher Scientific) following the manufacturer's protocol. The reaction mix for each sample was prepared in 25 μl volume containing 10 μl of the master mix, 10 μl of primer set, 1 μl of DNA template and 4 μl of deionized water. We employed the following thermal cycler conditions: pre‐denaturation for 1 min at 95°C, followed by 26 cycles of 94°C for 3 s, 59°C for 16 s, 65°C for 29 s, then a final extension at 60°C for 5 min, and holding at 4°C. The PCR products were electrophoresed and detected on the Applied Biosystems 3500XL Genetic Analyzer (Thermo Fisher Scientific) using POP‐4 polymer. The genotype profiles were obtained by comparing with the matching allelic ladder via GeneMapper ID‐X v.1.4 (Thermo Fisher Scientific).2.32O) and positive control (Control DNA 007) were genotyped for each batch of genotyping.This study was conducted in an ISO 17025 accredited laboratory, which has also been accredited by the China National Accreditation Service for Conformity Assessment (CNAS). The experiment was carried out in strict accordance with the recommendations proposed by the International Society for Forensic Genetics (ISFG)  in the Arlequin with the following parameter settings: the number of steps in Markov Chin is 1,000,000 and the number of dememorization steps is 100,000. And we tested the Linkage disequilibrium between all pairs  of loci with the parameter settings: number of permutations: 10,000 and number of initial conditions of expectation‐maximization (EM): 2 using Arlequin 3.5  are showed in Figure Subsequently, population genetic relationships were explored via pairwise genetic distance, multidimensional scaling plots and phylogenetic relationship reconstruction. Figure 4We provided the first batch forensic dataset of 23 STRs included in the Huaxia Platinum PCR amplification kit from the Han population residing in Shaanxi, near the Loess Plateau which was thought of as the origin of Chinese civilization and Sino‐Tibetan‐speaking populations. Comprehensive population genetic analyses based on the raw‐genotype dataset and frequency‐dataset consistently provided new insights into the population substructure of East Asians: linguistic stratification was significantly associated with population genetic substructure. Pairwise genetic distance, PCA, MDS, heat map, neighbor‐joining tree, as well as model‐based individual and population ancestry composition dissection demonstrated that Shaanxi Han harbored a close genetic relationship with the geographically close Shanxi Han, followed by other Han Chinese and Tibeto‐Burman‐speaking populations. Significant genetic homogenization was identified in Han Chinese and genetic differentiation was observed among populations belonging to different language families. Allele frequency distribution, parameters focused on forensic effectiveness indicated that forensic markers included in the Huaxia Platinum kit are highly informative and polymorphic in Shaanxi Han populations and can be used as the routine forensic practice.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.GH and LL conceived the idea for the study. GZ, HW, XZ, and MW performed or supervised the laboratory work. GH, LL, GZ, HW, XZ, and MW analyzed the data. GH, MW wrote and edited the manuscript. We would like to thank Prof. Renata Jacewicz , Prof. Hussain M. Alsafiah , Prof. I. Zupanič Pajnič  for sharing the raw genotype data as our reference data.This study was approved by the First Affiliated Hospital of Xi'an Jiaotong University. This study followed the recommendations of the World Medical Association Declaration of Helsinki.Fig S1Click here for additional data file.Fig S2Click here for additional data file.Table S1Click here for additional data file.Table S2Click here for additional data file.Table S3Click here for additional data file.


Enterocytozoon bieneusi is one of the most common intestinal pathogens in humans and animals. E. bieneusi has been confirmed to be complex microsporidian species. Approximately 500 ITS genotypes of E. bieneusi have been defined. With the establishment and application of multilocus sequencing typing and population genetic tools in E. bieneusi, the studies on these aspects have been carried out worldwide, but little information is available. To understand genetic variation of mini-/micro-satellites and the population structure and substructure of E. bieneusi in northeastern China, 305 E. bieneusi DNA specimens composed of 28 ITS genotypes were from 13 mammal species and five bird species in the investigated areas. They were characterized by nested-PCR amplification and sequencing at four mini-/micro-satellite loci . At the MS1, MS3, MS4, and MS7 loci, 153 (50.16%), 131 (42.95%), 133 (43.61%), and 128 (41.97%) DNA specimens were amplified and sequenced successfully with 44, 17, 26, and 24 genotypes being identified, respectively. Multilocus genotypes (MLGs) showed a higher genetic diversity than ITS genotypes. 48 MLGs were produced out of 90 ITS-positive DNA specimens based on concatenated sequences of all the five genetic loci including ITS. Linkage disequilibrium (LD) and limited genetic recombination were observed by measuring LD using both multilocus sequences and allelic profile data, indicating an overall clonal population structure of E. bieneusi in the investigated areas. These data will aid in the longitudinal tracking of the attribution of source of infection/contamination and in elucidating transmission dynamics, and will provide valuable information for making efficient control strategies to intervene with and prevent occurrence of microsporidiosis caused by E. bieneusi among animals and transmission of E. bieneusi from animals to humans in the investigated areas. Phylogenetic and network analyses identified three different subgroups, revealing the presence of host-shaped segregation and the absence of geographical segregation in E. bieneusi population. Meanwhile, the MLGs from zoonotic ITS genotypes were observed to be basically separated from the MLGs from host-adapted ones. Assessment of substructure will have a reference effect on understanding of zoonotic or interspecies transmission of E. bieneusi and evolution direction from zoonotic genotypes to host-adapted genotypes. Enterocytozoon bieneusi is the most common microsporidian species (more than 90%) in reported cases of human microsporidiosis worldwide  patients, organ transplant recipients, cancer patients, travelers, children, and the elderly  and an outlier with different degrees of host specificity , for it does not uncover the subtle changes among E. bieneusi isolates closely genetically related to each other at the ITS locus (E. bieneusi has been established and widely used to characterize the population structures of E. bieneusi isolates based on length polymorphisms and single nucleotide polymorphisms (SNPs) of three microsatellites  and one minisatellite (MS4)  . To date animals . Some MLpatients , 2013, npatients , pigs  and animals  in at least eight and 29 provinces, municipalities or autonomous regions, respectively,  in northeastern China, were characterized by MLST analysis at four mini-/micro-satellite loci . Meanwhile, linkage disequilibrium (LD) estimation and phylogenetic and network analyses were also conducted. These results will provide valuable information for making efficient control strategies to intervene with and prevent occurrence of microsporidiosis caused by E. bieneusi among animals and transmission of E. bieneusi from animals to humans, and will improve our perception about the population structure and substructure of this pathogen.In China, since the first identification of  in 2011 , moleculctively, . In norttic pigs . However species . To furtE. bieneusi isolates obtained from animals in northeastern China. The Research Ethics Committee and the Animal Ethical Committee of Harbin Medical University did not require the study to be reviewed or approved by an ethics committee because all the specimens analyzed in this study were DNA preparations.This study uses Enterocytozoon bieneusi genomic DNA was extracted from each of animal fecal specimens  distributing in four cities and Great Hinggan Mountains in northeastern China during the period of May 2012 to June 2019 using a QIAamp DNA Mini Stool Kit  according to the manufacturer recommended procedures (n = 20), group 2 (n = 7) and group 9 (n = 1), with some of them having been published in our previous studies  and one minisatellite (MS4). The primers and the cycle parameters for nested PCR amplifications used in the present study were designed previously by TM EZ Imager  by staining the gel with GelStrain  before sequencing.Except for the ITS region of the rRNA gene, all the 305 TM 3730 DNA Analyzer by Sinogeno-max Biotechnology Co., Ltd. , using a BigDye Terminator v3.1 Cycle Sequencing kit . Two-directional sequencing method was performed to make sure of sequence accuracy. Nucleotide sequences obtained in the present study were compared to all E. bieneusi homologous sequences published in GenBank using BLAST searches1. They were then aligned and analyzed with each other and reference sequences downloaded from the GenBank database using the program Clustal X 1.832 to determine genotypes at the ITS locus and the genotypes at the MS1, MS3, MS4, and MS7 loci, respectively.All secondary PCR products of expected size were directly sequenced with their respective PCR primers on an ABI PRISMISA) proposed by Habould and Hudson was used to assess the multilocus LD over the allelic profile data using software LIAN 3.53. ISA equal to zero or with a negative value indicates randomly mating populations and alleles in linkage equilibrium (LE). In contrast, when an ISA value is greater than zero, there is the existence of non-panmictic population structure and LD in allelic profile data analysis. In addition, the population structure was also assessed by calculating the variance of pairwise differences (VD) in another test and the 95% critical value (L) for VD. When the VD is less than L, the population is panmictic and is in LE; otherwise, the population is non-panmictic and a certain degree of LD exists , intragenic LD and recombination events (Rms) were also calculated from the concatenated sequences including and excluding the ITS gene without consideration of short insertions and deletions (INDELs) by using DnaSP 5.10.014. The population structure of E. bieneusi isolates was assessed by measuring the intragenic LD, ISA, and Rms.The standardized index of association  using the program Mega 55 based on the evolutionary distances calculated by Kimura 2-parameter model. The reliability of cluster formation was assessed by the bootstrap analysis with 1,000 replicates. Median-joining analysis implemented in the software network version 4.6.1.06 was conducted with the default parameters to identify a substructure of the E. bieneusi isolates.Phylogenetic relationship of MLGs of n = 1), TAA (n = 5–38) and T(C)AC(T) (n = 3–10) at the MS1 locus, dinucleotide repeats of TA (n = 4–17) at the MS3 locus, tetranucleotide repeats of G(A)G(A)TA (n = 1–2) at the MS4 locus, and trinucleotide repeats of TAA (n = 3–11) at the MS7 locus. Additionally, INDELs were observed at the MS4 locus (MT267413–MT267456 (MS1), MT267457–MT267473 (MS3), MT267363–MT267388 (MS4) and MT267389–MT267412 (MS7).At the four micro-/mini-satellite loci , 153 (50.16%), 131 (42.95%), 133 (43.61%), and 128 (41.97%) DNA specimens were amplified and sequenced successfully, respectively. 44, 17, 26, and 24 genotypes were identified at the MS1, MS3, MS4, and MS7 loci, respectively. SNPs and repeats could be observed: trinucleotide repeats of TGC  was positive and the VD (2.5154) was more than L (0.8363). A Monte Carlo analysis led to the generation of a significant PMC value (<0.01). These above results showed the population of E. bieneusi in the investigated areas was in LD with clonality. To exclude the possibility that LD could be attributable to a clonal expansion of one or more MLGs, which could mask the underlying equilibrium, the same MLG was scored as one individual and multilocus LD was assessed again. LD was still existed based on the fact that the ISA value was still above zero (ISA = 0.3647), and VD (1.1821) was more than L (0.5234), suggesting a clonal population structure. As ITS locus has a higher degree of genetic diversity than other genetic loci in E. bieneusi genome, the analysis was conducted on allelic profile data excluding ITS. Similar results were obtained, indicating ITS sequences had little influence on the result of LD analysis  and four genetic loci excluding ITS (2341 bp in length), respectively. LD was also estimated using the nSZ statistics. However, LD was incomplete based on the |D′| Y = 0.9750 – 0.0085X (including ITS) and the |D′| Y = 0.9857 – 0.0279X (excluding ITS). A negative slope implied a decline in LD with increasing nucleotide distance and the potential occurrence of recombination. Indeed, limited recombination events were detected in analysis of concatenated multilocus sequences  and gene flow (Nm) using DnaSP  for subgroups 1–3. Multilocus LD was recalculated when the same MLG treated as one individual. Subgroups 1, 2 both had positive ISA values and VD > L with significant PMC, confirming the existence of LD and clonal population structures. Due to no identical MLGs found in subgroup 3, the subgroup was not assessed again  (E. bieneusi isolates from NHPs (77.78–86.51%)  , and the present PCR primers were designed for target genes  based on nucleotide sequences flanking the potential micro-/mini-satellite repeats   and from–18.67%) , but low–86.51%)  and from–86.51%) . Similar–61.64%) . The inc repeats . Li et aE. bieneusi isolates analyzed and the constitution of ITS genotypes.In the present study, 44 genotypes were obtained at the MS1 locus, followed by 26, 24, and 17 genotypes at the MS4, MS7, and MS3, respectively. Previous studies described different numerical ordinations of genotypes at the four loci . HoweverE. bieneusi isolates. The presence of significant LD and a low number of recombination events indicated a clonal population structure of E. bieneusi in the investigated areas. The results imply that MLGs of E. bieneusi are relatively stable in time and in space in the investigated areas, and MLST analysis can be used effectively in the longitudinal tracking of the transmission of E. bieneusi in the community and in investigation of outbreaks. To date, at least 11 studies have assessed the population structure of E. bieneusi, in which over 800 E. bieneusi isolates have been used for LD analysis, including over 100 human-derived isolates belonging to 14 ITS genotypes from Peru, India and Nigeria and over 700 animal-derived isolates belonging to 60 ITS genotypes from China and Kenya, and LD analysis revealed the wide existence of a clonal population structure  versus humans  with narrow host ranges based on the summarized data in E. bieneusi populations with different genetic structures and public health potential in their evoluting processes, with the possible direction from zoonotic genotypes to host-adapted genotypes. Finally, some genotypes of E. bieneusi might be adapted to changing host environments, and were successfully chosen by hosts. Nevertheless, it is still unclear on the possible factors promoting adaptation of different E. bieneusi genotypes to specific hosts or host changes.To date, approximately 500  animals . HoweverE. bieneusi isolates derived from various mammal and bird species at the four MLST loci  in northeastern China. 48 MLGs were produced out of 14 ITS genotypes, revealing MLGs have a higher genetic diversity than ITS genotypes. MLST data and a clonal population structure of E. bieneusi will aid in the longitudinal tracking of the attribution of source of infection/contamination and in elucidating transmission dynamics, and will provide valuable information for making efficient control strategies to intervene with and prevent occurrence of microsporidiosis caused by E. bieneusi among animals and transmission of E. bieneusi from animals to humans in the investigated areas. The result of host adaptation of E. bieneusi population has a reference effect on further understanding of zoonotic or interspecies transmission of E. bieneusi. The observation of genetic segregation of E. bieneusi population by zoonotic potential and possible evolution direction of E. bieneusi from zoonotic genotypes to host-adapted genotypes will improve our understanding of evolution of E. bieneusi population. However, the role of host, geographical, and temporal factors in the evolution mechanism of E. bieneusi populations needs to be characterized in the future.The present study describes the genetic characterizations of The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Ethical review and approval was not required for the animal study because all the specimens analyzed were DNA preparations from animal feces.AL and YS designed this study and made the final revision. XL and YW performed the experiments, wrote the first draft of the manuscript, and prepared the tables and figures. XL, YW, BG, FY, YJ, and KZ analyzed the data. WZ and JC contributed to the reagents and materials. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Based on the panel data of 106 cities in the Yangtze River Economic Belt of China from 2007 to 2016, this paper explores the impact of city centrality on the green innovation efficiency and proves the mediation effect of migrants by using spatial econometric model. The results show that there are more and more innovation contacts between cities, and the innovation network is becoming more and more dense. The core cities of the downstream innovation network are mainly Yangzhou, Zhenjiang, Wuxi, Changzhou, Suzhou and Hangzhou; the core cities in the midstream are mainly Wuhan, Changsha and Yichun; the core cities in the upstream are Chengdu and Bazhong. There is an inverted U-shaped relationship between city centrality and green innovation efficiency. In addition, the influence curve of city centrality on the green innovation efficiency of surrounding cities is also inverted U-shaped. Cities with high city centrality attract a large number of migrants that come from cities with lower centrality to improve the green innovation efficiency, but the green innovation efficiency of cities with low city centrality will decline due to lack of talents. Since the reform and opening up, the Yangtze River Economic Belt has became one of the regions with the strongest comprehensive strength in China. However, the development of the Yangtze River Economic Belt faces many difficulties and problems that need to be solved urgently, which are mainly the severe situation of the ecological environment, the arduous task of industrial transformation and upgrading, and the imperfect mechanism of regional innovation cooperation. Therefore, effectively improving the green innovation efficiency in the Yangtze River Economic Belt and giving full play to its role as a green economic support belt will help to improve these problems.China is in a stage of high-quality development, innovation and green development play important role in the national economic strategy. From the perspective of traditional innovation concept, the scholars who first introduced environmental factors into the field of innovation proposed four kinds of innovations in turn: ecological innovation, environmental innovation, sustainable innovation and green innovation. The discussion of ecological innovation originated with Fussler and James , who defTherefore, this article explores green innovation efficiency from the perspective of social network theory. With the increasing complexity of innovation activities, the increasing number of R&D processes is often a collective act, as it reduces the risks and complexities involved in developing new products and processes by spreading innovation to dispersed partners . The evoHypothesis 1.City centrality affects green innovation efficiency.Some researchers believe that heterogeneity in innovation performance comes from the abilities to access and create the resources , when usHypothesis 2.Cities with high city centrality attract a large number of migrants that come from cities with low city centrality to improve the green innovation efficiency.Based on two hypotheses, this paper first uses the spatial econometric model to explore the impact of city centrality on the green innovation efficiency from the perspective of city network, heterogeneity test is used to analyze the different effects of city centrality. Second, the mediation effect model is used to prove the number of migrants is a mediator variable in the effect of the city centrality promoting the green innovation efficiency. Last, the above conclusions still hold after considering the robustness test. The paper proceeds in the following way: the second section introduces materials and methods, the third section describes the results, the fourth section discusses the results, and the last section provides the conclusions and policy recommendations.This paper calculates the green innovation efficiency by using MAX-DEA software. In 1978, Charnes et al. first proposed a nonparametric technical efficiency analysis method based on a relative comparison between the evaluated decision-making units (DMUs)—DEA . The SBMHere, Input indicators: Independent innovation or the purchase of extraterritorial technology requires R&D personnel and financial resources as inputs, which need the support of local governments, funding and staffing must be guided by the number of topics . Based oOutput indicators: The output of green innovation can be measured in two ways: technological output and green output. Technological output can be further divided into two processes: achievements of technological creation and achievements of technological transformation, The number of patent authorizations  is applicable, which takes into account the transmission mechanism of the above two models, it incorporates the spatial correlation of independent variables and dependent variables, and the spatial spillover effect is characterized by spatial interaction terms. If there is no spatial autocorrelation in the green innovation efficiency among cities, then a traditional ordinary least squares (OLS) model is used to analyze it. If there is spatial autocorrelation, then the optimal spatial econometric model must be further screened through testing. According to the test results, SDM is more suitable for analyzing the problems in this article. The specific reasons will be explained in the Compared with the traditional econometric model, the spatial econometric model takes into account the spatial correlation commonly found in economics, that is, the sample observations in one area depend on the observations in other areas, and spatial correlation is reflected in the lag term of dependent variable and error term in spatial econometric model. Considering that there may be a spatial correlation of innovation activities among regions, one region may be affected by the innovation activities in other adjacent or non-adjacent regions. Thus, traditional econometric models may ignore the spatial correlation of the green innovation efficiency. Accordingly, this paper chooses relevant data from 106 cities in the Yangtze River Economic Belt and uses spatial econometric analysis technology to explore the relationship between city centrality and green innovation efficiency. According to the judgment rules proposed by Anselin et al. , the modi in year t, i and the city j). Here, In order to further explore the mechanism of city centrality affecting the green innovation efficiency, this paper refers to the mediation effect test method proposed by Baron and Kenny , and theThe next is as follow:i, the coefficient  and Chinese Research Data Services Platform . Descriptive statistics for the data are shown in The Yangtze River Economic Belt covers 11 provinces and cities including Shanghai, Jiangsu, Zhejiang, Anhui, Jiangxi, Hubei, Hunan, Chongqing, Sichuan, Yunnan, Guizhou, etc., with an area of about 2.0523 million square kilometers, which accounts for 21.4% of the country’s population. The Yangtze River Economic Belt spans three major regions of China’s eastern, central, and western regions, and has unique advantages and great development potential. Based on the availability of data, the relevant data of 106 cities in the Yangtze River Economic Belt from 2007 to 2016 were selected for the analysis. All data are drawn from the EPS database  has higher R-sq than the SLM  and SEM , while AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion) are significantly lower. To further judge the fitting effect of the SDM model, this paper performs the LR test on the SDM model, the In model (1), the regression coefficient estimate of For example, many years ago, after the strategy for the rise of the central region was proposed, the overall innovation network of central cities was initially formed. Wuhan, Chengdu, Nanchang, and their surrounding cities developed rapidly, an urban circle with large cities driving small cities have been formed. But now, Wuhan is in an absolutely central position in the central region innovation network, howeve, its radiative effect on the surrounding areas is limited. The development of areas such as Huangshi, Xiaogan, and Xianning lags far behind Wuhan. These cities have not been affected by Wuhan’s knowledge spillover, instead, more talents returned to Wuhan to find work. In addition, Wuhan has the largest number of college students in China, but students from top universities are often reluctant to stay in this city after graduation or go to nearby cities. Therefore, Wuhan cannot absorb these innovation elements, which directly inhibits Wuhan’s innovation level.This article examines the different effects of city centrality on heterogeneous regions . According to the three steps of the mediation effect test, The cities with higher centrality enhance the green innovation efficiency by attracting the migrants that come from cities with lower centrality, but the negative effect is that the inflow of migrants into the central city limits the green innovation efficiency of surrounding cities. We think that the possible reason is that talents are the first element of innovation, cities with more high-level talents having the first mover advantage of innovation and development. In China, cities attract high-level talents through various policies, such as providing free housing for excellent talents, providing research funding for young scholars with excellent research ability, and rewarding enterprises and innovation teams that introduce high-level talents, these policies provide core guarantee for talents. In the cities with high city centrality, the supporting policies for talents are more attractive, so more talents choose to enter these cities, which directly promotes the green innovation efficiency.In summary, both hypothesis 1 and hypothesis 2 are true. This paper uses social network analysis and spatial econometric models to explore the impact of city centrality on the green innovation efficiency, and gravity model is used to prove that the number of migrants is a mediator variable in the effect of city centrality promoting green innovation efficiency. The conclusions of this article will contribute to expanding existing research in two aspects. On the one hand, although previous scholars have carried out in-depth research on city innovation networks, these studies mainly explored the evolution trend of city innovation networks and the influencing factors of city innovation networks ,42,43. Ni and city j are adjacent, each element in the matrix is equal to 1, otherwise it is 0).To check the robustness of the empirical results, the spatial adjacency weight matrix is used to replace the spatial distance weight matrix to test the benchmark model and mediation effect test , this heThe results are shown in There are many cases in China to prove these conclusion, for example, in the Wuhan city circle of China, the innovation level, GDP and employment of Wuhan are at the forefront. However, the development of the surrounding areas such as Xiaogan, Xianning and Xiantao is limited, and the gap with Wuhan is very obvious. The reason is that most of the high-tech migrants or low-skilled migrants in the cities around Wuhan have entered Wuhan to find jobs, which has greatly limited the innovation of surrounding cities. In addition, in the Beijing-Tianjin-Hebei city circle, Beijing’s population inflow is very high, but this has not increased the population inflow of surrounding provinces and cities (Tianjin and Hebei), and it is difficult for Beijing’s basic public facilities to provide supporting public services for such a large immigrant population, that is, it is difficult for Beijing to absorb these innovation factors, so the Xiongan New District with a non-capital evacuation function was established to undertake the population transfer in Beijing.This paper draws the following conclusions. First, from 2007 to 2016, there are more and more innovation contacts among 106 cities in the Yangtze River Economic Belt, and the innovation network is becoming more and more dense. The core cities of the downstream innovation network are mainly Yangzhou, Zhenjiang, Wuxi, Changzhou, Suzhou and Hangzhou; the core cities in the midstream are mainly Wuhan, Changsha and Yichun; the core cities in the upstream are Chengdu and Bazhong.Second, there is an inverted U-shaped relationship between city centrality and green innovation efficiency. In addition, the influence curve of centrality on the green innovation efficiency of surrounding cities also presents inverted U-shaped. Cities with high city centrality will attract a large number of migrants that come from cities with low city centrality to improve the green innovation efficiency, but the green innovation efficiency of cities with low city centrality will decline due to lack of talents. Therefore, proper city centrality can promote the green innovation efficiency to the greatest extent.Based on the above conclusions, this paper proposes the following policy recommendations. First, we should pay attention to urban planning and construction from the perspective of network. Regional development depends more on the division of labor and cooperation between cities, the status of cities in the whole system depends not only on their own attribute characteristics, but also on their relations with other cities. Therefore, when planning regional urban development, The government should examine the status and function of the city in the whole urban system from the perspective of urban network, pay attention to the external connection of the city, reasonably determine the orientation of urban development, avoid resource waste and repeated construction in the region; vigorously develop the urban economic zone, constantly support, cultivate and improve the network of urban economic zone based on the central city, and form a certain urban network structure through the aggregation and diffusion of the central city.Second, innovation connections have become the key of local or urban development. To achieve this kind of connection, the government not only needs to establish the local network within the region, but also needs to integrate the local economy into the global market and connect the external non local network. By using new information and network technology to improve its connection with other cities and enhance its accessibility, city centrality and technological innovation in the city innovation network can be greatly improved.Finally, we should strengthen the existing urban center position, cultivate new innovation growth poles and promote the diffusion of knowledge and human capital, but we must avoid the waste of human capital caused by the extremely centrality of the city. Each city must not lower the threshold to settle down without a limit, because this will cause “crowding of talents” and is not conducive to the improvement of urban green innovation efficiency.


Posidonia australis on the west coast of Australia. Measures of reproductive effort (flowering and fruit production and seed to ovule ratios) and estimates of genetic diversity and mating patterns (nuclear microsatellite DNA loci) were used to assess sexual reproduction in northern range edge  and centre of range  meadows in Western Australia. Flower and fruit production were highly variable among meadows and there was no significant relationship between seed to ovule ratio and clonal diversity. However, Shark Bay meadows were two orders of magnitude less fecund than those in Perth metropolitan waters. Shark Bay meadows were characterized by significantly lower levels of genetic diversity and a mixed mating system relative to meadows in Perth metropolitan waters, which had high genetic diversity and a completely outcrossed mating system. The combination of reproductive and genetic data showed overall lower sexual productivity in Shark Bay meadows relative to Perth metropolitan waters. The mixed mating system is likely driven by a combination of local environmental conditions and pollen limitation. These results indicate that seagrass restoration in Shark Bay may benefit from sourcing plant material from multiple reproductive meadows to increase outcrossed pollen availability and seed production for natural recruitment.Populations at the edges of their geographical range tend to have lower genetic diversity, smaller effective population sizes and limited connectivity relative to centre of range populations. Range edge populations are also likely to be better adapted to more extreme conditions for future survival and resilience in warming environments. However, they may also be most at risk of extinction from changing climate. We compare reproductive and genetic data of the temperate seagrass,  Posidonia australis seagrass meadows from Western Australia. Flower and fruit production were two orders of magnitude lower in Shark Bay meadows which also had lower genetic diversity and a mixed mating system when compared with meadows in Perth metropolitan waters. These results indicate that seagrass restoration in Shark Bay may benefit from sourcing plant material from multiple reproductive meadows to increase outcrossed pollination and seed production for natural recruitment.Plant species including seagrasses reproduce using sexual (seeds) and asexual (vegetative) means which can vary across a species range. We compare sexual reproduction, genetic diversity and the mating system in  Populations at their geographic range edges tend to have smaller effective population sizes, reduced sexual reproduction and limited connectivity relative to centre of range populations , althougNatural variation in traits, such as those associated with sexual reproduction, occur among populations across a species range; however, range edge populations may evolve physiological, morphological and life-history attributes that better attune them to warming environments . These pPosidona australis, a species with high seed dispersal capabilities  and two meadows in Perth metropolitan waters  during Spring 2016. Inflorescence density was estimated by using five replicate 10 m × 1 m (10 m2) belt transects. Flower and fruit production per inflorescence were estimated from the random collection of 12 inflorescences from transects at each site. Inflorescences consisted of a stem (petiole) bearing several spikes (3–12) with 3–5 hermaphrodite flowers. Following successful pollination, fruit development takes ~12 weeks. The number of fully developed fruit, undeveloped fruit and remains of flowers that had not been pollinated were counted on each inflorescence spike. The total number of flowers per inflorescence was derived from the sum of all fruit, undeveloped fruit and remains of flowers. Floral (number of flowers per m2) and fruit density (number of fruits per m2) were determined before fruit release. Production at Fowlers Camp was estimated based on fruit scars, as fruit had released prior to sampling. Seed to ovule ratio was determined from the total number of mature fruit (1 fruit = 1 seed) divided by the total numbers of flowers (1 flower = 1 ovule). The floral and fruit density data and seed to ovule ratios were assessed for heteroscedasticity and normality. A Tukey Ladder of Powers approach  and three meadows in Perth metropolitan waters .DNA was extracted from shoot meristem and embryos using methods previously described . Seven pNa), private alleles (p[i]), mean number of alleles (Num), effective number of alleles (Eff Num), observed (Ho) and expected (Hs) heterozygosity within sampled meadows and seed ‘populations’. The ‘Assign clones’ option was used to identify unique clones or MLGs and their frequency due to the high chance of sampling multiple flowering ramets from the same plant within a meadow. We implemented a stepwise mutation model (SMM), with a threshold of 1. This was used due the unusually large number of MLGs differing by a single allele at Carnac Island (see R = (G − 1)/(N − 1)), where G = number of MLGs, and N = number of samples, was estimated for each meadow (Gis), were calculated based on MLGs with 10 000 permutations, with positive values indicating a heterozygote deficit and negative values indicating a heterozygote excess. We conducted a t-test to determine whether there was a significant difference between clonal diversity in embryo ‘populations’ in Shark Bay and Perth metropolitan waters. Genetic differentiation (FST) was generated for all pairs of ‘populations’ using the complete data set, with significance between populations assessed using with 10 000 permutations.Tri-allelic genotypes were observed in six out of the seven loci that typically give di-allelic genotypes. Allele frequencies were therefore calculated using GENODIVE version 2.0b27 , which hh meadow  and clonP. australis (http://kermitzii.com/softwares/). Alleles that were not detected in a homozygous form, or were rare (where f < 0.05), were removed. Identical, commonly occurring tri-allelic genotypes were reduced to the same diploid genotype so as not to alter the total number of MLGs. All genotypes were manually checked to ensure each embryo contained at least one maternal allele. We acknowledge that this may introduce bias through an artificial increase in estimated selfing rates. Mating system parameters were estimated for each meadow, as well as by families within each meadow, using a maximum likelihood approach. These estimates were based on the multilocus mixed-mating model that assumes plants are randomly mating and the level of outcrossing is inversely proportional to the level of selfing (ts) and multilocus (tm) outcrossing rates, biparental inbreeding  and multilocus correlation of P (proportion of full siblings) (f), where a positive value indicates an excess of homozygotes and a negative value indicates an excess of heterozygotes as a result of outcrossing, as compared to expectations under Hardy–Weinberg equilibrium. Standard errors for all estimates were derived using a bootstrap method with 1000 bootstraps. The effective number of pollen donors (Nep(w)) per inflorescence (= family) was estimated by taking the inverse of the rp (t-test to determine whether there was a significant difference between outcrossing rates in meadows from Shark Bay and Perth metropolitan waters.Many of the standard population genetic tools have been developed for diploid data sets and therefore not feasible for polyploid or mixed data sets ( selfing . The proiblings) . Outcros−2) at Guischenault and Stark Bay, with no statistically significant differences in densities recorded (2) and Red Hill Bay (<10 m−2) . A similar pattern was observed in fruit production (−2) and they were not significantly different from each other. Parker Point had a significantly lower seed to ovule ratio than the other three sites . Thirty-two to 45 % of all ovules produced seed in the other three sites and differences in seed to ovule ratio were not significant . Centre of range embryo populations had significantly higher clonal diversity (R = 0.66–0.96) relative to embryos from range edge meadows  . Clonal evenness was lower in embryo populations than meadows for range edge meadows, with 47.8 % (45/94) of embryos from Guischenault sharing the same MLG. The pattern was reversed in centre of range meadows, with the exception of Carnac Island  and Red Hill Bay (one locus). Overall genetic diversity estimates were higher in Perth metropolitan waters relative to Shark Bay meadows (c Island . One to n = 1), Useless Loop (n = 2) and Fowlers Camp (n = 17). Overall, there was significant genetic differentiation among meadows , with no significant differentiation between maternal shoot and embryo ‘populations’ from Red Hill Bay, Stark Bay and Carnac Island [see]. Maternal shoot and embryo ‘populations’ were weakly differentiated at Guischenault and Parker Point.Shoot samples with identical MLGs within a meadow were assumed to belong to the same flowering genet (or clone), while shared embryo MLGs were likely a result of low genetic diversity, self-pollination and/or apomixis. Twenty-six MLGs were shared among shoot and embryo ‘populations’ within Guischenault and Red Hill Bay. A single MLG was shared among two embryos from Guischenault and shoots from Red Hill Bay (Ho) relative to Guischenault. Tri-allelic genotypes were also observed in some embryos  were present in at least one locus for every shoot genotype at Fowlers Camp, contributing to elevated observed heterozygosity  = 0.763, P = 0.133; Pearson r (population): 0.597, P = 0.287).No significant relationship was observed between seed to ovule ratios and shoot clonal diversity using maternal genotypes and previously collected population genetics data . Correlated paternity (or proportion of full siblings) was much higher in Shark Bay meadows (rp): range edge = 0.90, 0.93 than Perth metropolitan waters = 0.11–0.21, indicating a much higher effective number of pollen donors per inflorescence for Perth metropolitan waters (4.8–8.8) compared with Shark Bay (~1.0) meadows. Carnac Island was the exception, with the highest proportion of full sibs from all sampled meadows in Perth metropolitan waters (0.68). Outcrossing rates within individual families were much more variable in Shark Bay meadows than Perth metropolitan waters meadows . A visual inspection of Mating system analyses were conducted on samples from five meadows which produced viable embryos. Complete outcrossing was seen in the three meadows from Perth metropolitan waters  range edge meadows relative to within individual meadows which had small effective population size, reduced habitat area, low sexual reproduction and gene flow (ene flow . Marine Our hypotheses appear less well supported by productivity data on flowering and seed production and ratio of seed set to flowering (seed to ovule ratio). Sampling was however focussed on seed-producing meadows to obtain data on outcrossing rates. The spatial extent of the Shark Bay meadows was two orders of magnitude lower than Perth metropolitan waters where there are 10s to 100s km of reproductively fecund meadows. There are many more meadows in Shark Bay that have low densities of flowers, with no viable seeds being produced  relative to Guischenault (GU), which was the most fecund meadow. Alternative hypotheses proposed to explain the presence of additional alleles across multiple meadows include ancient hybridization, putative aneuploidy and somatic mutations leading to genetic mosaicism, all of which have been reported in seagrasses  yet has a similarly high seed to ovule ratio and mixed mating. Both these reproductive range edge meadows have high water movement  at close to oceanic salinity, thus likely to promote pollination success for the available pollen, leading to higher seed production than anticipated. This is in contrast to an exceptionally low seed to ovule ratio at Fowlers Camp, a sheltered meadow with weak tidal current, and exceptionally high flowering in elevated salinities. No reproductive data were collected for Carnac Island; however, large numbers of viable fruit are observed annually. Carnac Island appears to be a special case where high clonal diversity, parental inbreeding, complete outcrossing and high proportion of full sibs are consistent with pollination and recruitment occurring within this highly sheltered meadow . The Shark Bay meadows had fewer reproductive clones and a mixed mating system, although flower and fruit production and seed to ovule ratios can be comparable to meadows in Perth metropolitan waters. The Guischenault meadow has some of the highest recorded flowering and fruit densities in Phyllospadix spp.  are consistent with this finding. Pseudoviviparous plantlets in unfertilized inflorescences have also been observed following lower-than-usual water temperature and complete seed abortion when plants were under thermal stress from an extreme marine heat wave  genetic diversity and the ability to reproduce sexually . The use of vegetative  and seed material from multiple P. australis meadows across Shark Bay to assist recovery may artificially enhance meadow diversity and outcrossing rates for better quality seed production in the future. Ongoing research into the role of adaptation, acclimation and plasticity in range edge meadows may shed light on how these meadows with reduced sexual reproduction and outcrossing rates may overcome additional challenges across a salinity gradient under changing climates.Seagrasses have persisted for thousands of years through multiple climate cycles, with no recent evidence of latitudinal range contraction in The following additional information is available in the online version of this article—Posidonia australis.FST  and P-values  between all pairs of maternal shoots and embryo ‘populations’.plaa038_suppl_Supplementary_Table_S1Click here for additional data file.plaa038_suppl_Supplementary_Table_S2Click here for additional data file.plaa038_suppl_Supplementary_Table_S3Click here for additional data file.All raw microsatellite genotype data are available from the UWA Research Repository at: 10.26182/5f0bfbc877c60.


Conventional wheat-breeding programs involve crossing parental lines and subsequent selfing of the offspring for several generations to obtain inbred lines. Such a breeding program takes more than 8 years to develop a variety. Although wheat-breeding programs have been running for many years, genetic gain has been limited. However, the use of genomic information as selection criterion can increase selection accuracy and that would contribute to increased genetic gain. The main objective of this study was to quantify the increase in genetic gain by implementing genomic selection in traditional wheat-breeding programs. In addition, we investigated the effect of genetic correlation between different traits on genetic gain. A stochastic simulation was used to evaluate wheat-breeding programs that run simultaneously for 25 years with phenotypic or genomic selection. Genetic gain and genetic variance of wheat-breeding program based on phenotypes was compared to the one with genomic selection. Genetic gain from the wheat-breeding program based on genomic estimated breeding values (GEBVs) has tripled compared to phenotypic selection. Genomic selection is a promising strategy for improving genetic gain in wheat-breeding programs. Conventional wheat-breeding programs use phenotypic values for selection of best individuals. Such programs are reported to yield yearly genetic gains that are lower than 1% . The proIn contrast to MAS, genomic selection (GS) uses genome-wide markers to capture both large and small effect QTL to predict breeding values for complex traits . GenomicA number of studies have explored application of genomic information in breeding programs for different plant species. The motivation of this study comes from the observation that some of the simulation studies on genomic selection in wheat-breeding program does not mimic the complexity of actual wheat-breeding programs . In thisWe applied genomic selection in conventional wheat-breeding programs to investigate the expected change in genetic gain. Stochastic simulation was used to quantify expected genetic gain in conventional wheat-breeding programs when incorporating genomic information in making selection decision. Stochastic simulation allow to model breeding schemes that mimics an actual breeding program on a very detailed level . For insIn the present simulation work, we compared phenotype-based selection programs with genomic-based selection programs, where both selection criteria applied in conventional wheat-breeding programs. To achieve this, phenotype and genomic-based breeding schemes were simulated following a standard commercial wheat-breeding program, where the number of crosses, families, and single plants mimic real life wheat-breeding program. The aims of this study are to (1) investigate if incorporation of genomic information in wheat breeding program increases genetic gain, (2) study the change in genetic variance between phenotypic and genomic selection, and (3) investigate accuracy of selection in phenotypic and genomic selection.A stochastic simulation model was used to simulate a conventional wheat breeding strategy that run for 25 breeding cycles. Simulations were carried out using ADAM software . Two difA new breeding cycle was initiated every year and the breeding cycles, therefore, were overlapping . A breedIn a practical genomic wheat-breeding program, genomic selection would be implemented in an on-going phenotypic selection program. To mimic this, from the simulated 25 years of breeding program for genomic selection, the selection in the first 8 years was based on phenotypes. This means genomic information was introduced on the ninth year of the breeding program. This burn-in stage has also served to create differences between breeding cycles.Nth locus harbors a QTL that code for a trait under selection and the remaining loci are genetic markers. Thus from the total 9582 markers, 1039 loci were randomly chosen across the genome was assumed as QTLs while the remaining 8543 loci were assumed as anonymous markers.The genome for the founder population was generated from a realized wheat genome data set  that werr2 within chromosomes was 0.05, indicating the presence of low LD decay. The average r2 for the genome A, B, and D was 0.05, 0.05, and 0.11, respectively. The average distance of markers with r2 > 0.5 was 9.47, 8.38, and 7.73 cM for genome A, B, and D, respectively.The extent of linkage disequilibrium in the genome data set is explained in A base population of 480 lines were generated from the founder population. The genotype of each line was sampled from a pool of chromosomes of the founder population. Each line was generated by, for each chromosome 1 to 21, randomly sampling one chromosome without replacement from the pool of chromosomes. Then the second chromosome is set to be identical to the first one to generate a fully inbred line.Parental lines were chosen from the base population for the first seven breeding cycles. The breeding program was run in parallel, meaning that a new breeding cycle was started every year. After this stage, parents were selected randomly from F6, F7, and F8 of the previous breeding cycles.y, was calculated as, y = g + e, where g is the true additive-genetic value and e is residual value. True breeding values (TBVs) of the traits were determined by summing the allelic effects of its QTL. The QTL effects k and j denote the QTL k and QTL j, pk and pj are the minor allele frequencies of QTL k and QTL j, k and QTL j before being scaled. When simulating correlation between traits, additive genetic variance and heritability of each trait was specified along with the genetic and residual correlations between traits. The additive genetic covariance matrix was then derived from the additive genetic variances and the additive genetic correlation matrix (2) for BVP was set 0.1 and calculated Three traits for selections were simulated and these were breeder’s visual preference (BVP), yield at preliminary yield trial (PYT) and yield at advanced yield trial (AYT). The observation of the traits were realized at the different stages of a breeding cycle, breeder’s visual preference (BVP) at F2 and F4 generation, yield at preliminary yield trial (PYT) at F5 and yield at advanced yield trial (AYT) at F6 and F7 generations. AYT was also applied for family selection at F3. The preliminary yield trial represents un-replicated plot with limited amount of seeds sown sparsely. Whereas advanced yield trial is a standard yield plot with normal seed density and plots replicated three times in three different locations. The phenotype, n matrix . The genWhere H is expected frequency of homozygosity in the generation, Breeding value estimation was done using multi-trait BLUP model in DMU software . For gen1, 12 and 131 are the identity matrices, Z1, Z2 and Z3 are the design matrices that associate breeding values with BVP, PYT and AYT and N where OG is N where N, where R is the residual variance covariance matrix of the three traits. The three traits are measured on different lines and different years meaning the residual variance is independent and have value of zero.Where A breeding program running for 25 years was simulated following a conventional winter wheat breeding structure . Every yParents (P): For the first seven breeding cycles, 60 parental lines were chosen randomly from the base population while for the rest of 18 breeding cycles parents were selected based on their breeding values from F6, F7, and F8 of the previous breeding cycles and this allowed elite lines to be used for crossing  seeds. Families from F2 to F4 share a common ancestor (F1), thus families from F2 to F4 were referred as F1 families.F2: In total, there were 100 plots and each F2 plot had 30 plants. With-in each F1 family eight highest-ranking single plants were selected based on their breeding value for trait 1 (BVP). Heritability of 0.1 was assigned for the trait BVP. Selected eight single plants from each family were advanced to the next stage in the breeding program.F3: Each F1 family was planted in three plots and evaluated based on yield performance. The plot set up was similar as in AYT. Out of the 100 families, 75 highest ranking families based on their breeding values were advanced to the next stage.F4: The advanced 75 F1 families were planted in un-replicated field trials. Ten single plants per family were selected based of BVP in order to form individual lines based on single seed descent. Selected 750 lines were advanced to preliminary yield trial (PYT).F5: F5 lines were created by advancing selected F4 individuals through single seed descent (SSD). A single plot was simulated to generate 50 plants that were genetically identical. This preliminary yield trial (PYT) is un-replicated and this step is mainly done for the purpose of seed multiplication. Yield recording was made on each plot. Plot mean was used to select 150 best lines from the available 750 lines. Selected lines were stored to be potentially used as parents in the proceeding breeding cycles.F6: The 150 lines selected from F5 were evaluated in advanced yield trail (AYT), where plots and trials were replicated three times across three different locations. However, yield evaluation here was made based on the assumption that there is no genotype by environment interaction and heritability is chosen to reflect the part of additive genetic variance that is common to different environments  contained 750 genotypes. Every year the reference populations increased by 750 new genotypes.F5: Each F5 plot had 50 plants descended from the single seed and only one replicate was simulated. Yield was recorded on all F5 plots in each F4-line. Line selection was done based on plot yield performance of 750 F4-lines. The phenotypes and genotypes of 750 F4-lines together with the existing reference population were used to estimate breeding values of each lines using GBLUP model  of F8 individuals against time. For the comparison of conventional and genomic breeding strategies, data from years 9 to 25 was used in the analysis. The annual genetic gain was computed for each scenario by regressing TBVs of AYT on time with the assumption of linear response from years 9 to 25 within 10 replicates. The standard deviation of genetic response for AYT is estimated as a measure of uncertainty of the breeding program. The development of genetic variance over several rounds of selection was compared between genomic and phenotypic selection. Genetic variance per breeding cycle (F1–F8) is plotted over time. The change in genetic variance for all scenarios at the end of breeding cycle is presented. Plotting and calculation was done using R statistical programming language and environment .Genetic gain from phenotypic selection and genomic selection was compared based on their mean breeding values over the period of 25 years. The comparison was done for trait PYT and AYT of the F8 generations since they were the end product in the current simulation. Our simulation result showed that the breeding program that uses genomic information generated significantly higher genetic gain than the breeding program with only phenotypic selection . The chaGenetic gain within PS and GS was also compared based on the level of genetic correlation between PYT and AYT and there were five level of genetic correlations . According to the level of genetic correlations between traits there were a difference in mean breeding value with-in each selection criteria (PS and GS). The difference in genetic gain for the different levels of correlation can be clearly seen for PYT than AYT. The reason for this is that AYT was considered as the breeding goal and thus economic weight was assigned to AYT. This means genetic responses for PYT depends on the level of correlation with AYT for GS, the higher the correlation with AYT the higher genetic gain for PYT. This happened because of the genetic correlation between PYT and AYT as well as the genomic information available from the previous cycles are used for prediction. In addition, selection intensity at PYT is higher than AYT. However, the highest genetic gain is realized for AYT. The different levels of genetic correlation for AYT did not show significant differences among the different correlations. The standard deviation (SD) of the different scenarios for PS and GS breeding schemes tells the uncertainty of the breeding program. The SD of the individual estimates for AYT ranged 0.310–0.378 for PS whereas for GS the range is 1.127–1.143 .Annual genetic gain represents how much genetic gain have been obtained from each breeding cycle. Annual genetic gain for PS and GS was compared and the result for the five tested scenarios of PS and GS is presented in Genetic variance per cycle was measured and this shows how much of the genetic variance created by crossing and recombination is reduced along the different stages of selection within a breeding cycle. Genetic variance for trait AYT was measured within a breeding cycle for PS and GS breeding schemes and the result is shown in The development of genetic variance over the period of 25 years was measured and the result is present in At the end of the breeding program, the change in genetic variance for both genomic and phenotypic selection for grain yield measured for AYT for F5, F6, F7, and F8 at the end of the breeding cycle (25th year) together with the corresponding breeding values is shown in Predicition accuracy of breeding value was computed as correlation between TBV and predicted breeding values. The mean predicition accuray of plot yield for PYT and AYT from year 9 to 25 for generation F6, F7, and F8 is presented in The current wheat breeding simulation study was done to test a hypothesis that genomic selection can increase genetic gain compared to phenotypic selection. For testing this hypothesis, a wheat breeding program was simulated for both genomic and phenotypic selection. The breeding program ran for 25 years. Within PS and GS breeding programs, different level of genetic correlation between PYT and AYT was tested. Our result confirmed the hypothesis that wheat-breeding program that used genomic information has tripled genetic gain compared to the conventional phenotypic selection.Genomic selection breeding schemes has outperformed phenotypic selection for genetic gain. The increase in genetic gain that was brought by adding genomic information in conventional wheat breeding program was 3-fold. The main advantage of using genomic selection was increasing selection accuracy which inturn increased genetic gain, which was cosistent with the finding of In the current study, the increase in genetic gain was about 300% more when genomic information was used for selection. Previous study  has repoRate of genetic gain is used to compare an outcome from different breeding schemes that will help in designing a new breeding program . Our stuSelection causes changes in variances, allele frequencies, and LD relationships between markers and QTL . In our The change in genetic variance within a breeding cycle at the eary stage (year 9) and later stage (year 18) of the breeding program clearly showed differences in genetic varaince between GS and PS. Genetic varaince within a breeding cycle is produced through recombination until F5, after this stage varaince starts to decline faster because of selection. At the early stage of the breeding program (year 9), more genetic varaince was available for GS, however, as selection continues variance starts to decline for as seen in year 18. It also showed that the loss in genetic varaince is accelerated in GS than PS.In our study, the change in genetic variance depending on the genetic correlation between PYT and AYT was not significantly different from each other. Additive genetic variance plays an important role in predicting the change in the population mean due to selection . That meThis study has shown considerable advantage of genomic selection over conventional phenotypic selection for winter wheat-breeding programs by drastically improving genetic gain. Generating more genetic gain implies additional revenue, although generating additional revenues may add additional costs such as genotyping. Accuracy in GS, dependes on the size of the training population which are required to be genotyped which may add extra cost. Thus, it is important to determine the optimum training population size without compromizing the selection accuracy. However, genotyping costs are decreasing and this makes GS a more efficient tool to bring genetic improvement in cereal breeding than PS .This simulation was done following commercial wheat breeding schemes, including the number of families and single plants meaning the result easily can be translated into practical wheat-breeding programs. Genomic selection has increased response to selection with better estimates of breeding values and more accurate selection of future parents. We believe this study will help in desicion making process for a wheat breeder to switch to genomic selection. In addition to implementing genomic selection to increase genetic gain, accelerating the breeding cycle through speed breeding is also a promising approach to increase genetic gain that needs further investigations.The current study shows that incorporation genomic information in conventional wheat-breeding program can increase genetic gain. Besides, using genomic selection for a conventional wheat-breeding program requires a minimal change in an already existing breeding program. The increase in genetic gain in GS was mainly due to an increase in selection accuracy. Individuals selected based on their GEBVs were stored to be used as a parents. Genetic variance was reduced higher in GS than in PS, indicating it is necessary to incorporated optimum contribution selection in order to conserve genetic variation in the breeding program.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.BBT performed the analyses and prepared the manuscript. All authors helped in designing breeding scenarios, interpreting the results, and reviewing the manuscript. All authors read and approved the final manuscript.JA was employed by company Nordic seed. The remaining 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.