Oral diseases are a major health concern and are among the most prevalent diseases globally. This problem is becoming more prominent in the rapidly growing populations of Africa. It is well documented that Africa exhibits the most diverse genetic make-up in the world. However, little work has been conducted to understand the genetic basis of oral diseases in Africans. Oral health is often neglected and receives low prioritisation from funders and governments. The genetic determinants of highly prevalent oral diseases such as dental caries and periodontal disease, and regionally prevalent conditions such as oral cancer and NOMA, are largely under-researched areas despite numerous articles alluding to a high burden of these diseases in African populations. Therefore, this review aims to shed light on the significant gaps in research on the genetic and genomic aspects of oral diseases in African populations and highlights the urgent need for evidence-based dentistry, in tandem with the development of the dentist/scientist workforce. The increase in the incidence of untreated caries of permanent teeth  in the 2An estimated 480 million Africans suffer from oral disease. The World Health Organisation Africa Region has identified dental caries, periodontal diseases, oral cancers, Noma, oral manifestations of HIV and AIDS, oro-facial trauma and cleft lip and/or palate as priority oral diseases . Oral diIt is well documented that most genetic studies have been conducted on populations of European ancestry . The iniConsequently, more than 100,000 participants were included in funded projects providing 50,000 genotyped samples and the identification of 26 core phenotypes. Furthermore, over 2000 workshops and meetings were held and around 700 papers were published .Despite the notable achievements of H3Africa, common oral diseases are yet to be addressed in these initiatives; however, the complex genomic datasets established pave the way for projects that will ascertain the genetic determinants of prevalent oral diseases in Africa.The paucity of studies on diverse genomes impedes our understanding of the human genome in health and disease , and resExplorative studies on genetic determinants of oral health and oral disease lag far behind that of other conditions. This problem is even more prominent in Africa, where only a few studies have focused on oral health and disease –39. The There are 54 countries in Africa with immense ethnic diversity. These populations differ in terms of wealth, educational accomplishment, living conditions, health systems and access to oral health services , hence, This review aims at raising awareness of the genetic determinants of oral diseases and highlights research gaps in Africa. The review focuses on dental caries, periodontal disease, oral cancer, and rare diseases with craniofacial manifestations.Dental caries is a complex, chronic and multifactorial disease. It is mediated by the interplay between host factors, the microbial biofilm, a substrate that supports microbial cariogenicity and genetic influences , 44. TheThe incidence of untreated caries in the permanent dentition increased by 46.1%  from 1990–2019  provided an overview of 27 genes and genes—protein networks associated with protection or risk of dental caries. These were PRP1, PR, PA, MG1, MG2, AMELX, ENAM, TUFT1, KLK4, HLADR4, TAS1R3, TAS2R38, MBL2, MMP20, MMP2, MMP9, MMP13, GLUT2, TAS1R2, CA-VI, DEFB1, ALOX15, VDR-TAQI, MMP3, CA6, MUC5B, VDR-FOK and are related to enamel formation, development and mineralisation, host immune response and the composition of saliva .Sub-Saharan Africa has subregions with high fluoride levels in groundwater sources, causing dental and skeletal fluorosis . Dental There is a scarcity of studies on the genetic and genetic-environment interaction in the dental caries disease process in Africans. Olatosi et al. described a replication of the signals for two single nucleotide polymorphisms previously reported for childhood caries in an investigation of the role of genetics in early childhood caries in Nigeria. The study reported different size effects for two loci in the Nigerian populations compared to a previous study on an American population . In a siPeriodontitis constitutes a major health concern due to its high prevalence and significant impact on general wellbeing . In factIn susceptible individuals, periodontitis develops from complex interactions between the dental biofilm microbiota, host immune-inflammatory response and environmental factors . An indiPeriodontitis, in essence, is a polygenic disease arising from variations in multiple gene loci in which each contributes to developing the clinical phenomena .The genetic component of periodontitis appears to be more strongly associated with the aggressive phenotype . HoweverA wealth of data suggests that genetic variations in host genes involved in modulation of the immune-inflammatory reaction to periodontitis, have a strong effect on disease susceptibility and development . GeneticSingle nucleotide polymorphisms (SNPs) are common across the human population (>1%), however, their frequency varies significantly among various groups . Single For instance, the gene which encodes for interlukin-1, one of the most important inflammatory cytokines involved in periodontitis pathogenesis, has been extensively investigated for its association with periodontitis susceptibility, however, findings have been contradictory , 74. A pIn Africa, there are more than two thousand distinct ethnic groups possessing the world's most diverse genetic makeup . It is lThe most pivotal malignancy of the oral cavity is squamous cell carcinoma (OSCC) arising from the mucosal epithelium. More than 90% of oral cancers are SCCs . Oral caIn instances where African databases exist for the reporting of head and neck cancers, the incidence of cancers of the lip, tongue, oral cavity, and pharynx are often combined, and the oral cavity and oropharynx are most frequently reported among head and neck squamous cell carcinomas in Sub−Saharan Africa.It is stated that the incidence of oral cancer is escalating in eastern and southern Africa. This is the result of increasing tobacco use, increased alcohol consumption, and traditional practices like chewing khat and tobacco, which are carcinogenic , 83. If The biologic behaviour of oral cancers, such as determining which would run an indolent or aggressive course, is an area requiring genetic and genomic investigations. This would contribute to their diagnosis and management. Diverse genetic, epigenetic, and environmental factors are involved in the pathogenesis oral SCC which has a poor prognosis . A systeThe primary option for the management of oral SCC is determined by the stage of the disease and includes surgical resection, chemotherapy, radiotherapy, and immunotherapy . DespiteMost OSCC are considered genetically unstable , 88. FreThe effectiveness of the various current therapeutic modalities is reliant on the genetic and mutational profile of the tumour as this contributes to the oncogenic potential of the lesion. This type of targeted therapy is directed at these genetic modifications and forms the basis of precision medicine , 93.Despite considerable advancement which has been made in the management of oral cancer, its molecular heterogeneity still needs to be investigated in Africa. The molecular basis of the tumour also requires scrutiny in order to elucidate instances of resistance to therapeutic measures .Congenital defects and hereditary syndromes affecting the craniofacial complex are amongst the most common health problems globally , 94. TheOral and facial clefts (OFCs) serve as a good model for studying the etiology, treatment and prevention of congenital disabilities . The 202There have been few genotype-phenotype correlation studies in large cohorts of patients with RDs in Africa. The variability in phenotypic expression, high genetic heterogeneity and low mutation frequency were noted as challenges to establishing consistent genotype-phenotype correlations . A studyFKBP10 gene  type 3, which has an unusually high frequency in the Black Southern African populations  Out of 9P10 gene . Interes degrees . Another degrees  however,The diverse genetic and genomic heterogeneity of Africans has been the result of ancient migration patterns and adaptive pressures on the human genome. This resulted in evolutionary events, which spilt the human population into five distinct groups: southern Khoi-San, northern Khoi-San, central African hunter-gatherers, West Africans, and East Africans. A subset migrated out of Africa and is now identified as the out-of-Africa population , 109. HeIt is apparent that Africa is home to a huge burden of oral diseases, with limited genetic and genomic research. In the era of targeted approaches to the management of human diseases, novel discoveries in the biomedical sciences are redefining the conduct of research and improving oral health by translating these findings into clinical application .It has become imperative for the African oral health fraternity to prepare and arm itself with personnel who are equipped to investigate and interpret knowledge obtained from genomics, genetic sequencing, transcriptomics and proteomics, molecular profiling and bioinformatic data. This is essential in order to improve the management of oral health diseases and disorders in the era of targeted therapy, and will facilitate the development of disease management protocols aimed at African patients and conditions .Roberts et al. (2020), proposed the inclusion of adequate training in the genetics of oral diseases in undergraduate and postgraduate dental programmes for African universities. With adequate skillsets the trained dentists will have an interest in following a career in genetic and genomic oral health research. This would enhance networking among African dental researchers and lead to improved dental research output and evidence based dentistry across the continent .However, the high cost of biomedical infrastructure, laboratory set-up, project establishment and remuneration, has prevented many with an interest in biomedical research from engaging in genetic and genomic research. The genome sequencing technology is undergoing an evolutionary growth with the entry of new companies and the introduction of new techniques, which promise a significant reduction in costs . Joint eIn the current scenario where low- and middle-income countries (LMICs), most of which are in Africa, are left out of the advances in genomic technologies, The WHO Science Council of Experts released a report on accelerating access to genomics for global health. This report recommends approaches based on four themes, implementation, advocacy collaboration and associated ethical legal and social issues. The WHO Science Council proposed the establishment of a genomics committee to assist in rendering genomic technology affordable in LMICs by engaging various stakeholder and commercial entities .Thus, there is an urgent and pressing need for oral health researchers and policy makers to develop and participate in translational clinical research that will accelerate targeted scientific breakthroughs in the management of oral diseases in Africa.


Parisotomanotabilis  is one of the most abundant eurytopic species of springtails in temperate regions of the northern hemisphere, and is often used as a model species for studies on the genetics of soil microarthropod populations. Six genetic lineages  are known which are distributed mainly parapatrically in Western and Central Europe. Individuals of P.notabilis from 21 locations on the East European Plain were analyzed. Three genetic lineages were found: L1, L2, L4-Hebert. In contrast to Western and Central Europe, the coexistence of two or three lineages was revealed in about half of the locations on the East European Plain. The most diverse genetic composition of P.notabilis populations was noted in natural forests and slightly disturbed habitats, while the least diverse was in places with a high anthropogenic influence. Parisotomanotabilis Schaeffer, 1896 (Collembola: Isotomidae) is a cosmopolitan species which occurs in almost every biotope in temperate regions of the Western Palearctic, and predominates in most communities of Collembola  have previously been proposed based on genetic analysis of both the COI and the D2 region of the 28S genes , which differs in distribution along a disturbance gradient  whether the genetic lineages of P.notabilis in the Eastern Europe are distributed parapatrically, as in Western Europe; and 2) whether different genetic lineages of P.notabilis react differently to habitat disturbance.In this paper we provide new data on the three lineages of The study was conducted in the central region of the East European Plain, mainly around Moscow, which includes a wide range of habitats from natural forests to urban lawns. The territory is located in a belt of mixed and broad-leaved forests. The climate is temperate continental, the average annual amplitude of temperature variation is 28 °C, and 600–800 mm of precipitation falls per year . Three tP.notabilis was considered. Apart from P.notabilis, four species of the genus Parisotoma have been recorded in the East European Plain: P.agrelli Delamare Deboutteville, 1950, P.ekmani Fjellberg, 1977, P.reducta Rusek, 1984, and P.trichaetosa Martynova, 1977; all four species are rare and only the latter species was recorded in the Moscow region previously. In appearance all four species are easy to separate from P.notabilis by having an almost white corpus and smaller eye spots. The first three congeners occur only in northern areas and are rarely recorded in the central region of the East European Plain. The littoral P.agrelli lives only on the Arctic Ocean shore, while the Asiatic P.reducta is distributed in the very north-east corner the East European Plain. The boreal P.ekmani can probably occur towards the central part of the East European Plain via peat-bogs although it was never recorded there in spite of intensive study of the region . Sequences were then aligned using BioEdit (v. 7.2) (www.ncbi.nlm.nih.gov/GenBank) accession numbers are listed in the Appendix GBIF) in the ‘sampling event dataset’ format  . Tree co(v. 7.2) . Tree ca’ format .P.notabilis: L1, L2, and L4-Hebert  and undisturbed (forests) habitats. In the forests, the occurrence of L2 and L4-Hebert lineages was about the same, while L1 was sporadic. In forest parks, L1 was the most common, the L4-Hebert was less common, while L2 was rare. In the city (urban areas), L1 absolutely dominated Fig. .P.notabilis were already cited in the East European Plain  and Heteromurusmajor (Moniez) among 16 genetically studied Collembola species  sensu lato distributed in different sections of the river floodplain profile , L2 only in forests, and L3 only in pastures and arable fields , while two are more specialized, one to natural forests (L2), the other to disturbed habitats (L1). In both species the environmental factors leading to lineage specialization remain unclear. The adaptations of the lineage may be of ecophysiological, nutritional, demographic or migrational nature.Information on the ecological preferences of genetic lineages is sporadic. Thus, in the widespread springtail species e fields . A similP.notabilis prefer different degrees of habitat disturbance seems convincing at this point. Samples along the disturbance gradient can reveal the diversity of lineages for one location. The cosmopolitan species P.notabilis, abundant in natural and disturbed habitats, is a promising model object for studying the phylogeography of Collembola populations.Our results are preliminary and call for more data. However, the assumption that different genetic lineages of Parisotomanotabilis have been detected in the East European Plain: L1, L2, and L4-Hebert. Mean genetic distances between the lineages in the studied D3–D5 region of ribosomal 28S gene region ranged from 0.9% to 1.4%. About half of the samples in central part of East European Plain included more than one lineage of P.notabilis. The samples from different habitats may include different genetic lineages of the species, which is important to take into account in phylogeographic reconstructions. The most diverse genetic composition of P.notabilis populations was observed in natural forests and forest parks; only two lineages were found in urban environments. Genetic lineages of P.notabilis show ecological specialization: L1 likely prefers disturbed habitats, although L2 and L4-Hebert predominate in natural forests, which requires further research. It is also necessary to focus on the search for characters that could allow the morphological differentiation of the lineages.Sequencing of the 28S gene is practical and convenient to identify already known genetic lineages while data on the COI gene are needed to describe new lineages. Three genetic lineages of


Environmental regulation (ER) plays an important role in urban low-carbon development (ULCD). First of all, we evaluate the ULCD level of 282 cities in China from 2005 to 2020 by constructing an index group and entropy method. Two panel models are then used to test the spillover effects and threshold effects of ER and industrial structure on ULCD. The results show that the ULCD level of most cities is still in grade III (0.27–0.38) or IV (0.38–0.49), and the level of central-western cities is generally lower than that of eastern cities. Furthermore, the spillover effect of ER and industrial structure upgrading (UIS) on ULCD is positive in eastern cities (0.038) but opposite in central or western cities (−0.024). Further results show that the positive effects of optimization of industrial structure (OIS) and UIS are gradually increasing with the improvement of ER. However, the positive effects are more beneficial to the eastern cities. Therefore, the conclusions of this study can provide a decision-making reference for local government to comprehensively formulate environmental and industrial policies to enhance the low-carbon development of cities. Due to excessive emphasis on economic growth, in recent decades the economic development led by the Chinese government has led to serious eco-environmental problems and large emissions of CO2 ,2. China2 . The cit2 ,6. The c2 ,8.From the content of the existing research, more and more scholars have set out from the whole urban system to build a multi-dimensional index group to measure the comprehensive level of ULCD ,9. HowevThe most important premise of all is to evaluate the level of ULCD scientifically. Based on existing research, we construct the evaluation index group of ULCD and use the entropy method to calculate the level of 282 cities from 2005 to 2020. Furthermore, we use the panel regression method to briefly examine the relationships between variables. Considering the impact of ER on the production behavior of polluting enterprises, on the one hand, ER may lead to the spatial transfer of industry, technology, and labor, and ultimately affect the ULCD ,18. On t2 emissions, and the relevant assessments are usually reflected by one or more indicators. With the in-depth study of low-carbon development, scholars realize that the research conclusions and policy recommendations based on a small number of indicators to characterize ULCD cannot meet the actual needs of managers and believe that ULCD is an orderly, coordinated, and sustainable way of development [2 emissions to characterize ULCD, which is relatively simple. Multi-index evaluation methods are diverse due to the differences in the treatment of indicators, such as the TOPSIS method, the Analytic hierarchy process, entropy weight method, and so on [The early studies on the evaluation of ULCD mostly focus on the absolute reduction of COelopment ,9. On thelopment ,21. As felopment ,12,13. And so on ,16,22. G2 will seriously impact the global climate. Therefore, many environmental regulations have been formulated and adopted to reduce the global emission of pollutants [In recent decades, people have gradually realized that greenhouse gas emissions such as COllutants . Academillutants . Since tllutants ,26. Secollutants . Howeverllutants ,28. The llutants . With thAs for China, under the tremendous pressure of global climate change and carbon emission reduction targets, the intensity of environmental regulation is increasing yearly. China tries to guide cities to achieve low-carbon and green development by employing ER, but how does ER promote ULCD? According to theoretical and empirical studies, ER will impact the industrial behavior of enterprises. With the increase in the degree of ER, it will first increase the production cost of polluting enterprises. As stated in the Porter hypothesis, ER can promote enterprises’ technological development and reduce environmental pollution’s negative externalities by imposing emission reduction constraints. Furthermore, polluting enterprises in developed cities are transferred to less developed cities. Environmental regulation causes the cross-regional and inter-city transfer of polluting enterprises and industries. For the impact of central or western cities, according to the environmental Kuznets curve hypothesis, before reaching the “inflection point”, the economic benefits brought by polluting enterprises are greater than the environmental costs, thus promoting regional development. Overall, ER has a non-linear effect on the low-carbon development of social, economic, and ecological environments in different regions and cities and finally shapes the differentiated urban low-carbon development pattern.Urban low carbon development (ULCD): As this paper mainly studies the development level of an urban low-carbon economy, ULCD indicators mainly consider the content closely related to the city; drawing lessons from previous studies, we have found that urban economy, society, and the ecological environment are inevitable aspects to be considered. In addition, the use of energy resources is directly related to the level of ULCD, and the level of urban resource utilization must be taken into account in assessing the level of ULCD. The differences in the development of different cities are closely related to government-led urban development planning, so the evaluation of ULCD also takes into account the factors of urban planning. Finally, based on the connotations of ULCD, we construct an evaluation index group from five dimensions, including low-carbon economy, low-carbon society, resource utilization, urban planning, and low-carbon environments, to evaluate the ULCD level of each city .To avoid subjectivity, the weights of indexes are obtained by the entropy method, and the results are shown in 2 removal rate, the comprehensive utilization rate of general industrial solid waste, harmless treatment rate of domestic waste, and centralized sewage treatment rate [Environmental regulation (ER): Referring to Du et al., we comprehensively evaluate the degree of ER by using industrial dust removal rate, industrial SOent rate . The reai is the ith industry; n is the number of industries, with a maximum of 3; Y is the total output value; L represents the total employment; iY depicts the output value of the ith industry; and iL is the number of employees in ith industry.Industrial structure: Referring to Zhao et al., in this paper the industrial structure is divided into industrial structure optimization (OIS) and industrial structure upgrading (UIS) . The UISThe control variables include education level (edu), investment level (ifa), science and technology level (tec), and economic openness (eol), with reference to the relevant research in this paper ,14,30. Aitulcd is the urban low-carbon development level of the ith city in the t year; iα represents the individual effect; tλ represents the time effect; itε is the error term; β is the parameter to be estimated; er depicts environmental regulation; ois is the optimization of industrial structure; uis is the upgrading of industrial structure; edu represents the level of education; ifa represents the level of investment; tec indicates the level of science and technology; and eol indicates the degree of openness of the economy.The panel regression model is selected as the benchmark model due to the characteristics of the data. Because of the heteroscedasticity of the data, the variables are processed in the form of a natural logarithm. The general panel regression model of this study is constructed as follows:ρ and θ represent the spatial effect coefficient; nβ indicates the coefficients of k explanatory variables; W denotes the spatial weight matrix, which is obtained by anti-geographical distance; M is a group of explanatory variables, including ER, OIS, UIS, and other control variables; Wit reflects the values of spatial lag explanatory variables in adjacent regions; γ is used to measure the marginal influence of the explanatory variables in the adjacent regions on the explained variables; ε represents the spatial autocorrelation error term; ite is a random disturbance term; iμ represents the spatial fixed effect; and tλ denotes the time fixed effect. The results of the benchmark regression model can preliminarily reveal the relationship between the ER, industrial structure, and ULCD of each city, but the ability to analyze the effect of ER in neighboring cities on the level of ULCD is insufficient. Thus, we further use the spatial panel model to analyze the spatial impact of ER and industrial structure on ULCD. As for model selection, starting with the Durbin model provides a better choice . The SPDity is the interpreted variable; δ is the coefficient of the explanatory variable itx to the explained variable when the threshold variable, itq, is greater than or less than the threshold γ; and I represents the indicator variable. When itq ≤ γ, I = 1; Otherwise, I = 0. iμ is the individual effect of the region and itε is the error term. After derivation, the single threshold model (5) and double threshold model (6) can be obtained.iter is the threshold variable; itx is the core explanatory variable, including ois and uis; and nβ is the coefficient of the control variables.The intensity of ER is dynamic, and its impact on ULCD may have significant phased differences and finally show non-linear characteristics. As for the non-linear characteristics of the influence effect, this study uses the PTM to verify it, as per Cui et al. . The panThe main data of 282 cities from 2005 to 2020 include low-carbon development evaluation data, environmental regulation data, industrial structure data, and other control variables’ data. These data come from China Urban Statistical Yearbooks (2006–2021) and provincial statistical yearbooks (2006–2021). The indexes of ULCD are shown in According to the evaluation index group and entropy weight method, the ULCD level of 282 cities from 2005 to 2020 is obtained, and the results are shown in After the evaluation of ULCD, we further use the panel regression model to analyze the impact of ER and industrial structure on ULCD. In order to draw a more accurate conclusion, LM test and Hausman test are used to select the ideal panel model. The final results are shown in ln er”) in different models are significant, and they are 0.4795, 0.516, and 0.205, respectively, which shows that ER has a significant positive effect on ULCD. In addition, education level (“ln edu”), economic development level (“ln pdgp”), and economic openness (“ln eol”) are all statistically significant in the three models, and their coefficients are all positive. The difference is that the coefficient of OIS (“ln ois”) only passed the test in the eastern cities, and it is −0.221, but the coefficient of UIS (“ln uis”) only passed the test in the central-western cities, and the coefficient is −0.541. We can see that the unbalanced industrial structure limits the ULCD in eastern cities, and the OIS of central or western cities suppresses the ULCD during the research period. In addition, the level of scientific and technological development (“ln tec”) only promotes the ULCD in eastern cities.From the results of the LM test and the Hausman test in In this paper, the global Moran’ I is used to detect the existence of the spatial effects of the main factors based on the inverse distance weight. The results of global Moran’ I in typical years are shown in R2 and logarithmic likelihood functions in the individual fixed effect model are relatively larger, which shows that the ideal model is the individual fixed one. The results of the individual fixed model are shown in Furthermore, based on the samples of eastern cities and central-western cities, we carried out LM-lag, Robust LM-lag, LM-error, and Robust LM-error tests on the model (3), and all items passed the 5% significance test, indicating that there are lag terms and error terms in the spatial dependence of ULCD, and SPDM should be selected. Secondly, both Wald and LR tests pass the significance test of 1%, indicating that they highly reject the hypothesis that SPDM can be simplified to PSEM or PSLM. Finally, the fixed effect model is selected by the Hausmann test. Through the SPDM analysis of different fixed effects, it is found that the values of SPDM results of eastern cities and central-western cities in W×n ois) in central-western cities, the lag coefficients of other variables are significantly not equal to zero, which confirms that ER, OIS, and UIS have spatial spillover effects on ULCD. The direct, indirect, and total effects are then further decomposed by the method introduced by Lesage and Pace. The indirect effect corresponds to the spillover effect, and the results can be seen in the Indirect column in According to The results of spillover effects show that the spillover effect coefficients of ER in the eastern and central-western cities are 0.038 and −0.024, respectively, both of which are significant at a 95% confidence interval. It is shown that the ER has a positive spillover effect on the ULCD of eastern cities, but has the opposite effect for central-western cities. The spillover effect of OIS is only significant in the eastern cities, and it hurts the ULCD. The spillover effect coefficients of UIS in the eastern and central-western cities are 0.063 and −0.042, respectively, indicating that, in the eastern region, the UIS of the city has a positive impact on its ULCD and the ULCD of neighboring cities. However, it is harmful to the ULCD of the surrounding cities in the central-western region.p value through repeated sampling 1000 times to judge whether there is a threshold effect. The results are shown in Taking the ULCD level as the explained variable, we estimate whether there is no threshold, one threshold, or two thresholds for ER in eastern and central-western cities. Referring to the bootstrap method, we use State15 statistical software to obtain the corresponding As seen from er ≤ 0.5361, the coefficient of OIS is −0.3912 and passes the significance test, while the coefficient of UIS does not pass the significance test. When 0.5361 < er ≤ 0.8110, the coefficient of UIS is −0.0135, while the coefficient of UIS is 0.1739, and both have passed the significance test. When 0.8110 < er, the coefficient of OIS is very small and does not pass the significance test, while the coefficient of UIS passes the significance test and is 0.1938. The above results show that under an increasing state of ER, the bondage effect of OIS gradually disappears, but the promotion effect of UIS is gradually enhanced.After verifying the authenticity of the threshold, we can further analyze the threshold effect. According to the results of the eastern cities in er ≤ 0.2200, the coefficient of OIS is −0.4309, and that of UIS is −0.1147, both of which are significant. When 0.2200 < er ≤ 0.5834, the coefficient of OIS is −0.0740, while that of UIS is −0.0831, and both have passed the significance test. When 0.5834 < er, the coefficient of OIS is 0.1362 and passes the significance test, while the coefficient of UIS is contrary. The results show that when the intensity of ER in central-western cities is weak, the impact of OIS on ULCD is negative. However, with the increase of the intensity of ER, the negative impact gradually weakens. Finally, the negative impact gradually turns into a positive impact. In addition, similar to the results of OIS, with the improvement of the intensity of ER, the negative impact of UIS gradually weakens, but it does not reverse to positive in the end.From the perspective of central-western cities, when 2 emissions in urban economic growth are generally regarded as an important symbol of low-carbon development level. Therefore, we replace the explained variables with CO2 emissions per unit of GDP (2ln pgCO) into the benchmark model to further verify the robustness of the results. It should be noted that CO2 emissions are obtained based on the energy consumption of coal, coke, crude oil, fuel oil, gasoline, diesel, natural gas, and their respective CO2 emission coefficients. The energy consumption data come from the 2006–2021 Provincial Statistical Yearbooks and the Urban Statistical Yearbooks. The CO2 emission coefficients come from the IPCC report [Per capita COC report . In ordeBM) results in 2 emissions per unit of GDP show a downward trend, reflecting the improvement of ULCD. The impact of OIS and UIS on CO2 emissions per unit of GDP of eastern or central-western cities are similar to the initial results. That is, OIS increases the CO2 emissions of eastern cities, which is not conducive to the ULCD. The impact of UIS on CO2 emissions per unit of GDP in central-western cities is also similar to the initial result. From the perspective of spillover effects, due to the space limitation, the robustness analysis only discusses the existence of spillover effects. According to the SPDM results of eastern and central-western cities, the spatial lag coefficients of the variables in the two models are significantly not equal to zero, which proves that the spillover effect does exist.According to the benchmark model (PTM), the two threshold values of eastern cities in 2 emissions per unit of GDP in eastern and central-western cities is positive but gradually decreases. When the level of ER changes from low to medium, the impact of UIS on CO2 emissions per unit of GDP in eastern cities changes from positive to negative, but when the ER level is high, the impact is insignificant. When the ER level is medium or below, the impact of UIS on CO2 emissions per unit of GDP in central-western cities has always been positive, but when at the high ER level, the UIS in central-western cities will significantly reduce CO2 emissions per unit of GDP. Generally speaking, the results of the threshold effect in As regards the threshold effect (This paper mainly focuses on the impact of ER, OIS, and UIS on ULCD in different cities in China. Although the ULCD level of Chinese cities is increasing, the overall level is still in the middle state, and there are obvious spatially unbalanced characteristics. It is consistent with the conclusion of Wang et al. that the quality of low-carbon development in the eastern region is better than that in the central and western regions . However2 emissions. However, from the perspective of the spillover effect, we find that the impact of ER in eastern cities is positive, while that in central-western cities is negative. The explanation may be found from the study of Zhao et al., that is, the comprehensive level of development and the intensity of ER in the eastern region are higher than those in the central and western regions, resulting in greater restrictions on carbon-intensive industries in the eastern region, while the opposite is true in the central and western region [Further research found that no matter which explanatory variable is used, all the evidence supports that ER is conducive to ULCD, which is close to the conclusions of Pei et al. . The rean region . This stThe threshold results show that with the continuous improvement of the ER level, the inhibitory effect of OIS on urban low-carbon development in eastern cities gradually disappears, but the UIS promotes the ULCD level gradually. However, the impacts of OIS and UIS on the ULCD in central-western cities are always negative, but the negative influences become weaker and weaker. The reason for this may be that the government tended to give priority to economic development rather than ecological environment protection in the early stage, which led to the non-exclusion of carbon-intensive industries in the process of OIS. Due to the location advantage, the secondary and tertiary industries in the eastern cities developed rapidly. With the steady growth of the economy, the problem of the urban ecological environment in the eastern region has become increasingly prominent. The eastern region forces the transformation of industrial structure and the transfer of carbon-intensive industries through more stringent environmental regulations, which comprehensively leads to the impact of OIS and UIS on ULCD. Because the development of the central and western regions lags behind that of the eastern regions, the central and western regions are forced to undertake the industrial transfer of the cities in the eastern region, which comprehensively leads to the change of industrial structure, but increases the social and economic carbon dioxide emissions of the central or western cities.Finally, there are some shortcomings in this paper. First of all, although this paper’s relevant results and conclusions have been tested for robustness, there are some missing samples in the central-western cities due to the difficulties in obtaining data. As a result, the results and conclusions about the central-western cities can only partially reflect their regular characteristics. Secondly, some studies believe there may be a time lag in the impact of ER, OIS, and UIS on the social economy. Therefore, in further research, we should strengthen the ability to obtain data and consider improving the model to analyze the time lag of the impact of the main variables.This study comprehensively evaluates the low-carbon development level of 282 cities in China by using economic, social, resource, planning, and ecological indicators. Econometric panel models are then used to analyze the linear, non-linear, and spatial spillover effects of ER, OIS, and UIS on ULCD. The conclusions are as follows.From 2005 to 2020, most Chinese cities have been committed to improving the level of ULCD and achieved remarkable results, but the overall level of ULCD is still not high and is characterized by spatial imbalance. The linear effect concludes that ER shows a significant positive impact on ULCD. At the same time, government-led industrial structure optimization and upgrading have little influence on the improvement of ULCD during the period. Thus, the eastern and central-western cities should adopt diversified policies and measures to improve the overall level of ER. Furthermore, when promoting the transformation of industrial structure, the government should strengthen the identification and selection of industries, raise the entry threshold for carbon-intensive industries, and prioritize introducing high-tech industries.The result of the spatial spillover effect reveals that strengthening the ER and UIS of cities in the eastern region can improve the ULCD levels of other neighboring cities, while the central-western cities are the contrary. The OIS of a city in the eastern region may limit the ULCD of surrounding cities, but it is not significant in the central and western regions. The results of the threshold effect show that with the intensity of ER from small to large, the negative impact of OIS on the ULCD of eastern and central-western cities gradually weakens and even changes to positive. However, the UIS of eastern cities plays a more and more important role in promoting the ULCD, and the negative impact of UIS on the ULCD of central-western cities gradually weakens. From a comprehensive point of view, the influence of ER on ULCD must be a long-term and non-linear process. The municipal governments of the eastern and central-western cities should issue long-term effective environmental policies and measures and carry out a periodic evaluation of the performance of these regulation instruments to adjust the intensity of ER in time, which ensures that environmental policies can always have a positive impact on ULCD.


Ziziphus nummularia′s geographical distribution is crucial for its future sustainability. In this study, we analyze information obtained from the field investigation, the distribution and response of climatic changes of Ziziphus nummularia by the use of ArcGIS analysis. The genetic diversity of 180 genotypes from three populations was studied by morphological attributes and simple sequence repeat (SSR). The results showed that the significant bioclimatic variable limiting the distribution of Z. nummularia was the mean temperature (bio 10_18.tif and bio19). Under the current climatic change, the suitable growth region of Z. nummularia is Swat , while the future distribution would be Buner , respectively. A total of 11 phenotypic traits were noted and had significant phenotypic variation among the traits. A total of 120 alleles were amplified. The alleles per locus ranged from 2 to 6, averaging 4.42, whereas PIC ranged from 0.33 to 0.79. Within a mean value of 0.67 per locus, expected heterozygosity was 0.57, observed heterozygosity was 0.661, and average gene diversity was 0.49. Flow estimates (6.41) indicated frequent gene flow within genotypes. The clustering, STRUCTURE, and PCoA analysis indicated Swat and Buner migration routes and evolution as well. The results indicated the prevalence of genetic variability and relationships among Z. nummularia across geographical boundaries had retained unique alleles. This may facilitate the development of agronomically desirable cultivars. However, climate change has impacted species distributions, requiring strategies to conserve genetic resources in different areas.Understanding the impacts and constraints of climate change on  Ziziphus nummularia in Malakand division, Pakistan.Modern evolutionary processes, including gene flow, genetic drift, and natural selection, as well as a species’ evolutionary history, have an impact on the genetic diversity of populations and how they differentiate . Due to Data on population genetics based on molecular markers has been highly helpful in understanding historical occurrences in the past, and they will help assess how well-equipped species are to adapt to the current environment affected by climate change. However, a mixture of these events may also happen. Extant species that have survived through glacial refugia are likely to have genetic markers of within-refugium genetic drift and selection or, conversely, harbor historical genetic diversity not seen throughout a taxon’s range. For example, more and more suitable markers are available for measuring the recent genetic divergence within and among species to detect patterns for measuring population-level variation, such as microsatellites, restriction site-associated DNA markers (RADseq), and whole-genome sequences .Z. nummularia have primarily been based on the morphological tracks, but these indexes are more susceptible to different environmental conditions. With the great improvement of molecular markers technology, markers such as SRAP, RAPD, ISSR, AFLP, EST-SSR, and SSR are widely distributed in genotypes for the estimation of genetic diversity, relationship, genetic population, and genetic map construction, respectively, in the Z. nummularia genotypes. Genotypes of Z. nummularia provide strength for exploring and protecting the genetic and phenotypic diversity of breeding approaches. Its genetic diversity defines its potential to consistently produce new, high-quality varieties, which is crucial for the sustainability and advancement of breeding  . For the given ranges, i.e., 1 to 20 and the highest values were recorded in K = 3 and K = 5. Consequently, the analysis of the STRUCTURE software was performed for the K = 3, which was largely grouped by the genotypes.The population structure analysis was carried out for the 180 Z. nummularia genotypes  and Bayes’ rule estimation of K, values give a comparative estimation of LnP(D), and the smallest value is regarded as almost correct. The estimation of ΔK values that the peak reached K = 5. According to the formula, our result shows clear peaks of ΔK at K = 3 of enotypes . In the Z. nummularia genotypes were approximately divided into three CPs , accordingly . Pairwise FST comparisons among the different geographical regions showed that FST values varied from 0.0013 to 0.1913, respectively , and Buner) of KP, Pakistan. The analysis showed that, in general, the genotypes from the different regions clustered together represented three clusters, i.e., Cluster I, Cluster II, and Cluster III  was divided into three clusters , which cThe genetic diversity was recorded within and among the population of different geographical regions and population structures, providing arranged data for the hierarchical AMOVA . The current total genetic variance among the population was 8%, while differences among individuals within populations contributed 12% to the total variance, and 72% of the total variance occurred within individuals.Z. nummularia genotypes was highly significant   .Z. nummularia and forecast an especially uncertain future for this rare species of Ziziphus, which is native to Malakand division, KP, Pakistan. It is looking likely that the Z. nummularia is going to harshly reduce ranges, as recommended by the up to 99% decreases of the suitable habitats across all the global climatic models during these periods. Due to the results, the plant species are more likely to face a high risk of extinction by local restrictions. Climatic change has already affected several plant species which were distributed all over the world. Mostly tropical and subtropical regions of the world have been identified as the most sensitive regions in Pakistan, where the projection percentages of species loss will reach 60% by 2080 [ by 2080 ,29.Z. nummularia, are likely going to face a wave of mass extinction of the Z. nummularia genus over the coming periods. However, the high level of genetic diversity of the current Z. nummularia genus may eventually favor adaptation and perseverance but remain highly ambiguous. Species growth will depend on factors such as genetic makeup, fitness, healthy habitat, and fragmentation while dispersal approaches. The seed of Z. nummularia, which lacks obvious adaptations for long-distance and brochure dispersal, is most likely the primary mode of dissemination. It necessitates the use of crude methods, such as grazing mammals that consume the seeds along with the foliage, which cannot be ruled out.As Hindukush regions range in the northern regions of Pakistan, many plant species, one of the Ziziphus species, mostly for Z. nummularia genotypes and crop species, as they are the primary constituents of overall diversity. Different types of systems, methods, and researchers have been utilized for morphological variation in combination with molecular markers to precisely estimate characteristic variability for drawing inferences in many crops and trees, which include Ziziphus species (Z. nummularia) [The total of 11 quantitative morphological traits are often known to be influenced by environmental factors, but the most important of these traits cannot be underestimated for analyzing the diversity of a mularia) ,30.Z. nummularia genotypes collected from different regions  of KP, Pakistan. The level of variation was enough to discriminate against many genotypes of Z. nummularia from each other in our study. This agreed with many earlier studies involving morphological traits that distinguished different genotypes among the three regions of KP, Pakistan [In the current study, the information generated through multivariate analysis and genetic parameters has given an excellent view of genetic diversity for the 11 quantitative traits for the 180 Pakistan ,31,32. HPakistan . CorrelaPakistan . The sigAn essential sign of a species’ capacity to withstand changes in its environment is its genetic diversity. Selection, genetic drift, and breeding techniques all have an impact. The genetic diversity of Z. nummularia genotypes may be studied to give a theoretical framework for preserving and employing Z. nummularia genotypes.T. sebifera samples from eight populations was 0.486 in this study, which was greater than that of earlier research. Two possibilities could account for this discrepancy. First, different marker kinds were employed. SSR markers can reveal greater genetic variation than ISSR markers. Additionally, there were variations in the number of samples. The selection of samples for this investigation was fairly extensive. The primary T. sebifera distribution areas were also included in the distribution range. Six pairs of SSR markers were employed by DeWalt et al. [T. sebifera populations in China, and the values were higher than those of this study (average He = 0.70), which was quite low for our current results.The results (He = 0.281) obtained by Zhang  using ISt et al.  to analyZ. nummularia genotypes [For the genetic diversity using various parameters of the SSR loci, viz. the mean values of allele frequency, allele numbers, observed and expected heterozygosity, and PIC as well is important to reveal the genetic diversity of enotypes . These penotypes ,36. Simienotypes , Ahmad eenotypes . Howeverenotypes , higher enotypes . The aveenotypes , who repp = 0.001) contributions of within-individual differences to the total variation, whereas among-individual and among-population differences contributed 12 and 8%, respectively.High estimates obtained for all diversity parameters indicated allelic richness in the analyzed genotypes, which can be utilized in breeding programs to get the desired plant types for breeding. While 120 total polymorphic alleles were recorded, the highest alleles were six per locus, while the lowest two alleles were noted with an average value of 4.4286, respectively. This information can be helpful for future genetic analysis specific to linkage groups. The analysis of molecular variance (AMOVA) results showed major and significant , respectively, the CP1 and CP3 were different types, which were a mixture of ZNBU and ZNST region genotypes. This clustering of pea accessions agreed with the study carried out by Jing et al. [For the population, the structure performs a Bayesian genetic and admixture by modal STRUCTURE software and assigns all g et al. , who alsZ. nummularia genotypes, and they were found in ideal molecular markers for the making of molecular phylogenetic relationships in Z. nummularia genotypes of the different geographical origins of KP, Pakistan. The N-J Phylogenetic tree distributed all Z. nummularia genotypes into three clusters, which was in correspondence with our previous studies and reported studies , respectively, and 9 from Cluster I , respectively. Cluster III has a mixture of all three regions, 17 genotypes from Cluster I and 15 from Cluster II ZNDR. From this, it can be inferred that the clustering of Z. nummularia genotypes was based on genetic stocks regardless of geographic proximities. This could be conveniently ascribed to the movement of germplasm from one location to another in ancient times, the records for which are missing, and presently formal germplasm exchange agreements are in place between different regions as described by Kuleung et al. [Z. nummularia genotypes collected from KP, Pakistan, which has resulted in maintaining diversity to a greater extent than can be surveyed and utilized by breeders to develop new, improved varieties in Z. nummularia. The N-J results were complemented with PCoA analysis.The molecular phylogenetic and PCoA analysis were applied for the identification of d et al.  in clustg et al.  and AhmaZ. nummularia in Dir (L) may be related to the change of habitats during the migration of the species. This analysis revealed that the genetic identity of Z. nummularia between populations/districts was negatively correlated with geographical distance, implying that Z. nummularia may have undergone a pattern of isolation by dispersal limitation [The genetic diversity of plant populations is closely related to the climatic variability of their habitats . The promitation .Ziziphus species. With this investigation, Z. nummularia has been regarded as an endemic species. Furthermore, a significant range contraction (about 100%) is predicted for this species by the year 2050, even though no seed accessions from this species have been deposited in any global germplasm collections. In order to ensure species survival, a combination of ex-situ and in-situ conservation measures is required.The global application of molecular markers (molecular genetic diversity) technologies is attracting more and more common practices to the estimation and study of many aspects of plant genetic resources management . The curZiziphus species’ genetic improvement [Z. nummularia because approximately four to five years is required to complete one cycle of field data collection and evaluation for the species. Therefore, appropriate planning to preserve individual palms that possess traits of interest should be in place to ensure long-term accessibility. The values of the current potential collection where determined genetic diversity is preserved in a reduced land area can be applied. The establishment of such a collection is an ideal option for oil palm as it increases the efficiency of conservation and allows for more effective access to genetic materials. The results presented above facilitate the identification of unique populations or rich allelic individual palms as well as populations that exhibit high genetic variation.The field assessment of the collection revealed some interesting traits useful for the rovement . AchieviZ. nummularia collected from the area of KP, Pakistan. A conservation approach addressed to preserve single outstanding individuals is necessary, namely for the importance of heritage trees, which often become one of the few objects of great natural value in areas under the impact of land degradation and the falling into the decay of rural areas [Z. nummularia increases when sites are sampled less than 20 km apart. Even though very distinct samples, albeit at a low frequency, can be obtained from the same site, a distance of 20 km between collection sites could be used as a general guideline in future collection missions to maximize the diversity captured for Z. nummularia. While the current result shows that the Pakistani Z. nummularia genotypes are exceptionally diverse and variable, this can be endorsed to the diver’s neighborhood genetic basics, specific reproducing weights, and the restricted trade of hereditary material [Ziziphus species, uncovered by our results, backs the case for the execution of more extraordinary characterization and preservation procedures and potential rearing for Ziziphus species (Z. nummularia).The present findings strongly suggest that there is wide genetic diversity present in the wild within genotypes of al areas ,43,44,45al areas ,47. The material ,46. The 2 up to 400 pp, the highest in millions of years. Climate changes have exceedingly high effects on plants and wildlife, respectively. In the current research, we accompanied a complete study of genetic diversity, the population structure of Z. nummularia collected from Malakand division KP, Pakistan, to study diversity based on morphology and SSR markers. During the current study, a total of 180 genotypes of Z. nummularia were evaluated with a significant positive correlation. Descriptive analysis showed a high coefficient of variation between the study’s morphological traits of Z. nummularia genotypes. To date, this is the first time SSR fingerprints for 180 genotypes of Z. nummularia have provided comprehensive data on genetic diversity, population analyses, and their relationship with their geographical/climatic distribution were addressed. A total of 120 polymorphic alleles among the 180 genotypes were assessed by using 27 SSRs as reproducible markers. A visual understanding of plants’ genetic variation is important to conservation and management efforts. Remarkably, wise utilization of conserved plant germplasm in a gene bank collection needs knowledge of the genetic diversity that is present as well. Ensuring sustainable food security is a multi-faceted challenge involving much more than just increasing food production; it is also about protecting the useful diversity of wild landraces. The results shown here may provide valuable resources for future Ziziphus breeding programs. Furthermore, the application of the recently evolved high-throughput platforms and phenomics tools could enable plant breeders to identify and exploit the available plant genetic resources in environmentally sustainable ways. In brief, the current result will be highly beneficial in designing studies relating to Ziziphus species (Z. nummularia) genotypes’ phylogeny, as well as finding the biological origin and formulating future breeding programs.The effect and the incensement of global climate change in recent years, while the reason for climate change is heavy rainfall has caused floods (disasters) in various areas, and weather stations over the world measured the increasing concentration of atmospheric CO


Perca fluviatilis is an economically important species of freshwater fish that has flavorsome meat with a high nutritional value. Microsatellite markers are widely used in the genetic structure analysis of aquatic animals due to their abundance, high polymorphism, and codominance. In this study, we screened, tested, and developed polymorphic markers and evaluated the genetic diversity of the main wild P. fluviatilis populations in China. From the P. fluviatilis genomic data, 98,425 pairs of microsatellites were identified. A total of 200 primer pairs for tetranucleotide microsatellites were synthesized and tested in randomly selected wild individuals. Among them, 152 microsatellite markers were found to be polymorphic. A total of 29 markers with clear amplified bands and high polymorphism were selected for the genetic analysis of the four populations. The results indicated a high level of genetic diversity in P. fluviatilis populations in Wulungu Lake, Jili Lake, and the Wulungu River and a medium level of genetic diversity in the Kalaeerqisi River. There was moderate genetic differentiation among the populations in Xinjiang. The results of this study provide important information on the genetic diversity and genetic population structuring of P. fluviatilis in China as well as a scientific basis for the protection and molecular marker-assisted breeding of P. fluviatilis.Perca fluviatilis is an economically important species of freshwater fish. To understand the genetic structure of P. fluviatilis in China, 268 samples were collected from Wulungu Lake (WL), Jili Lake (JL), the Wulungu River (WR), and the Kalaeerqisi River (KR). These samples were then analyzed using microsatellite markers. A total of 98,425 microsatellite markers were developed based on the genomic data, and 29 polymorphic microsatellite markers were selected to analyze genetic diversity in this study. The number of alleles (aN) and observed heterozygosity (oH) per population ranged from 4.621 (KR) to 11.172 (WL) and from 0.510 (KR) to 0.716 (JL), respectively. The results of the polymorphic information content (PIC) showed that the WL, JL, and WR populations were highly polymorphic (PIC≥ 0.5) and that the KR population was moderately polymorphic (0.25 ≤ PIC < 0.5). The genetic differentiation coefficient (stF) among the four P. fluviatilis populations was 0.074, indicating moderate genetic differentiation among the populations in Xinjiang. The reason for the significant difference between the rivers and lakes could be the presence of a dam blocking the flow of P. fluviatilis. The development of microsatellite markers provides support for population genetics in the future. The evaluation of the genetic structure of P. fluviatilis in Xinjiang provides a reference for the reproduction and conservation of P. fluviatilis. Perca fluviatilis belongs to the Percidae family, part of the Perciformes order. It is commonly known as Eurasian perch and is widely distributed in Europe and North Asia [P. fluviatilis has focused on biological characteristics [rth Asia . It is arth Asia , and it eristics ,4, artiferistics ,6, embryeristics , parasiteristics ,9, and feristics ,11.P. fluviatilis has previously been demonstrated to be low, based on mitochondrial control region sequencing of wild populations in Xinjiang and other breeding populations in China [P. fluviatilis populations and demonstrated a high level of genetic diversity. Microsatellite markers, also known as simple sequence repeats (SSRs), are widely used in the genetic structure analysis of aquatic animals due to their abundance, high polymorphism, and codominance [P. fluviatilis in seven locations in Lake Geneva; the results showed that the number of alleles (aN) ranged from 3.33 to 4.75, reflecting low genetic diversity. Recently, Sipos et al. [P. fluviatilis genetic diversity of two Hungarian populations (aN = 8.667 and 9.500) was lower than that of a Polish population (aN = 10.667). Information regarding genetic diversity is limited; it is, therefore, necessary to use a greater number of markers to evaluate the current genetic diversity of P. fluviatilis. It is of significance to evaluate the genetic resources for the reproduction and protection of P. fluviatilis.Some studies concerning the genetic diversity of the species have been also conducted ,13,14. Ain China ,17. Nesbominance ,19. Khadominance  used twes et al.  developeP. fluviatilis have been published recently [P. fluviatilis genome data for the screening, characterization, and testing of microsatellite markers. In China, P. fluviatilis is mainly distributed in the Altay Region, Xinjiang [P. fluviatilis populations lack data regarding their genetic diversity. We also used the new markers to evaluate the genetic diversity of four wild populations in Xinjiang, providing a scientific basis for the reasonable protection and molecular marker-assisted breeding of P. fluviatilis.Nowadays, the development of sequencing technology has led to a rapid increase in high-throughput sequencing data in public databases . Genome recently . TherefoXinjiang . After s2 of the caudal fin of each sample was collected and pasted onto filter paper and another absorbent paper, covered with another filter paper, and kept at room temperature after drying naturally [A total of 268 samples were collected from the Altay region of Xinjiang, China, including 34 samples from Kalaeerqisi River (KR), 77 samples from Wulungu River (WR), 68 samples from Jili Lake (JL), and 89 samples from Wulungu Lake (WL) . Approxiaturally  for lateP. fluviatilis were downloaded from the GenBank database (accession number: GCA_010015445.1), and the microsatellites were isolated and screened using MISA software (https://webblast.ipk-gatersleben.de/misa/) (accessed on 1 May 2021). According to standards such as those reported by Becker and Heun [The genome data of and Heun , the seaand Heun  was usedTM 8000 spectrophotometer  was used to detect the DNA concentration and optical density value; 1.5% agarose gel electrophoresis was used to detect the integrity. Finally, the samples were diluted to 50 ng/μL and stored in the refrigerator at −20 °C for later use.Genomic DNA was extracted from the caudal fin using a standard proteinase K-phenol-chloroform extraction protocol . A NanoD2O. Each primer pair was amplified separately. The PCR parameters were as follows: initial denaturation at 95 °C for 3 min followed by 35 cycles of denaturation at 94 °C for 20 s; annealing at 58 °C for 30 s; extension at 72 °C for 40 s; and a final extension at 72 °C for 5 min. An amount of 1 μL of the product was then obtained and mixed with 9 μL of loaded HIDI, denatured at 95 °C for 3 min, immediately bathed in ice water, and placed in an ABI 3730XL  sequencer for electrophoresis detection. GeneMarker software was used for the data analysis.Four samples from different populations were randomly selected to preliminarily detect the polymorphism and specificity of the 200 pairs of primers . FinallyaN) and the number of effective alleles (eN) per locus as well as the observed heterozygosity (oH) and expected heterozygosity (eH). Using the formula of Bostein et al. [PIC) per locus. We also used PopGene version 3.2 to evaluate the Hardy–Weinberg equilibrium test (PHWE) and genetic distance (D) between the populations [https://evolution.genetics.washington.edu/phylip.html) (accessed on 12 October 2021) was used. Arlequin version 3.5 software [stF) based on the premise that the number of permutations was 1000. The genetic composition within the populations and differences among them were analyzed using Structure software version 2.3.4 [http://taylor0.biology.ucla.edu/structureHarvester/) (accessed on 15 October 2021).PopGene version 3.2  was usedn et al. , we calculations . To conssoftware  was usedon 2.3.4 ; the ranP. fluviatilis genomic data, 98,425 microsatellite markers were developed. The detailed primer information is presented in n, (AG)n, (AT)n, and (GC)n repeat motif. The (AC)n core repeat type had the highest number and the (CG)n had the lowest number. The trinucleotide-repeat microsatellite loci  included (ATT)n, (AGG)n, (AGC)n, (AAG)n, (ATC)n, (AAC)n, and (ACT)n, with a total of 10 types of repeat motif; among them, the number of (ATT)n was the highest. The tetranucleotide-repeat microsatellite sequence included 32 repeat motifs (n and (ACAG)n repeat motif appeared most frequently, accounting for approximately 17.78% and 15.3%, respectively. The pentanucleotide repeat  was the least frequent, including 94 core repeat motifs of (AGAGG)n, (AATTC)n, (AAAAT)n, and (AAAAG)n.From the t motifs , of whicA total of 200 primer pairs for tetranucleotide microsatellites with a repeat motif of (AGAT)n or (ACAG)n were tested in four wild individuals. The information on all 200 tested primers is presented in P. fluviatilis populations, with fragment sizes ranging from 86 to 265 bp. The aN per locus ranged from 4 (HLJHL052 and HLJHL007) to 29 (HLJHL186), with an average of 12.552. The Ne per locus ranged from 1.313 (HLJHL084) to 10.913 (HLJHL186), with an average of 4.809. The Ho per locus ranged from 0.896 to 0.234 (an average of 0.648) and the He ranged from 0.910 to 0.237 (an average of 0.712). The PIC ranged from 0.225 to 0.901, with an average of 0.680. Of these markers, 23 were highly polymorphic markers (PIC ≥ 0.5); HLJHL186 had the highest PIC  and eN (5.018). The KR population had the lowest aN (4.621) and eN (2.563). The JL population had the largest oH (0.716) and eH (0.749), and the KR population had the lowest oH (0.510) and eH (0.518). The PIC ranged from 0.467 to 0.716. Based on the PIC results, the levels of genetic diversity among the populations were ranked: JL > WL > WR > KR. The JL, WL, and WR populations were highly polymorphic (PIC > 0.5), whereas the KR population was moderately polymorphic (0.25 < PIC < 0.5). The WR, JL, WL, and KR populations had 8, 7, 8, and 4 loci, respectively, showing a departure from the Hardy–Weinberg equilibrium, with a significant or an extremely significant lack of heterozygotes.The results on the genetic diversity of the four stF value for the four P. fluviatilis populations was 0.074, representing a moderate level (0.05 < stF < 0.15). The pairwise stF was significant for the lake vs. the river samples in the JL–WL–WR basin (0.05 < stF < 0.15), representing a moderate level (stF between the rivers (KR and WR) (stF = 0.158) was the highest, representing high-level genetic differentiation (stF > 0.15). The stF (stF < 0.05) was lower between the two lakes, despite the significant differences. Correspondingly, the genetic distance between the two rivers was the largest (D = 0.288). The genetic distance between the two lakes (JL and WL) was the closest (D = 0.027)  . Based o= 0.027) , it was According to the results from Structure Harvester, K = 3 was the best value to cluster the four populations because the delta K value was the largest. The four populations could then be classified into three genetic components : the WR P. fluviatilis genome, the dinucleotide repeats were the most abundant, which is consistent with most vertebrates [Sander lucioperca [Megalobrama amblycephala [Lateolabrax maculatus [n core repetitive types accounted for the highest proportion, which is similar to the findings for Tetraodontidae [n core repeats is also consistent with that of most species. Schorderet and Gartler [Among the 98,425 microsatellite loci in the tebrates ,38, suchcioperca , Megalobycephala , and Lataculatus . Among t Gartler  believedn was the most abundant (17.78%). This may have been due to the specificity of the species, as it is contrary to the research findings of Zheng et al. [Pinctada martensii EST database, (ATTT)n accounted for 50% of the tetranucleotide-repeat microsatellites [P. fluviatilis used in this study, the core sequence was repeated more than 10 times and the number of alleles at each locus was not less than 4. Barker [P. fluviatilis.The tetranucleotide-repeat microsatellite markers showed a higher level of polymorphism and greater stability than the dinucleotide repeats and trinucleotide repeats and are more suitable for analyzing the genetic differences between the populations . In thisg et al. . There wtellites . Among t. Barker  pointed aN, oH, and PIC [P. fluviatilis in the lake probably came from the Eerqisi River basin, which resulted in a greater genetic source in the lakes. Therefore, the genetic diversity of P. fluviatilis in the lakes was higher than that in the rivers of the WL–JL–WR basin. The water in the lake was more stable and, therefore, more suitable for spawning [aN, oH, and PIC parameters. The Kalaeerqisi River is an upstream tributary of the Eerqisi River; P. fluviatilis migrated upstream from Europe to China via the Eerqisi River, so the P. fluviatilis genetic resources of the KR population could not be better supplemented. Compared with the results of Yang et al. [Ho and He of the Wulungu Lake were lower in this study, showing that the genetic richness of P. fluviatilis decreased and that the germplasm resource has deteriorated over the past years. Compared with P. fluviatilis around Lake Geneva, the aN, oH, and eH of the four populations in this study were higher [P. fluviatilis in China was higher than in Lake Geneva.Genetic diversity is not only a prerequisite for biological survival and development but also an important basis for assessing the status of genetic resources . It can  and PIC . In thisspawning . The KR g et al. , the Ho e higher , indicatstF) is an important parameter to describe population differentiation. The larger the stF value, the greater the genetic distance and the more distant the genetic relationship between the populations. Wright [stF < 0.05 indicated low genetic differentiation, that 0.05 < stF < 0.15 indicated moderate genetic differentiation, and that 0.15 < stF < 0.25 indicated high genetic differentiation. The stF among the four populations in the four regions of the Wulungu River, Wulungu Lake, Jili Lake, and the Kalaeerqisi River was 0.074, showing moderate genetic differentiation, probably due to the geographical proximity of the four regions. There was significant genetic differentiation among the different river basins. It is noteworthy that the highest degree of genetic differentiation was observed between the KR and WR populations. In 1969, the “Diversion Eji Lake” project introduced the Eerqisi River into the Wulungu Lake to reduce the salinity of the internal lake [P. fluviatilis from the river into the lake, causing geographical isolation, leading to the existing genetic differentiation between the rivers and lakes within the basin. There is no geographic barrier between Wulungu Lake and Jili Lake, which are connected by the Kuiga River. It was also seen from the AMOVA results that only 7.44% of the genetic variations occurred between the populations, while approximately 92.56% occurred within the populations. The UPGMA cluster tree was divided into three branches; this result was consistent with the structured genetic components.The genetic differentiation index (. Wright  believednal lake ; at the nal lake . This coPerca fluviatilis is an economically important species of freshwater fish. The developed microsatellites can be used for genetic structure analysis; dentification of related, inbred individuals in aquaculture settings; and detection of family structure. Based on the genome data for P. fluviatilis, we identified and designed 98,425 pairs of microsatellite primers. A total of 200 primer pairs for tetranucleotide microsatellites were synthesized and tested in wild individuals. Among them, 152 microsatellite markers were found to be polymorphic. We selected 29 markers with clear amplified bands and high polymorphism for the genetic analysis of the four populations. The results showed that the genetic diversity of the two lakes was higher than that of the two rivers. We conclude that it is essential to protect the germplasm resources of P. fluviatilis in the Kalaeerqisi River so that the genetic diversity will not be reduced or lost. Over the years, P. fluviatilis from Xinjiang has been introduced into many other regions for artificial cultivation. Our study used microsatellite markers to distinguish the genetic differences among the different populations and has laid a foundation for cross-regional introduction.


H6-subtype avian influenza virus (AIV) was prevalent in the world and could sporadically infect humans. Here, a new chicken-derived H6N6-subtype AIV strain A/chicken/Zhejiang/49/2021 (ZJ49) was isolated in Zhejiang Province, China in 2021. Phylogenetic analysis by Maximum likelihood methods showed that H6-subtype AIVs were classed into 13 groups according to HA gene. The ZJ49 strain belonged to the G12 group, which mainly consisted of strains from Asian and dominated in recent years. Based on NA gene, H6-subtype AIVs were divided into N6.1 and N6.2 clades according to the NA gene. The ZJ49 isolate was located in the N6.2e clade, which mainly consisted of the H5N6-subtype AIVs. Phylogenetic analysis by Bayesian methods showed that the effective quantity size of H6-subtype AIVs increased around 1990, reached a peak around 2015, declined after 2015, then kept in a stable level after 2018. The reassortment analysis predicted that the PB2, PA, and NA genes of ZJ49 may recombine with H5-subtype AIVs. The amino acid at 222 position of HA gene of ZJ49 strain mutated from A to V, suggesting that ZJ49 has a potential ability to cross species barriers. The four glycosylation sites were highly conserved, implying less impact on the fold and conception of HA stem structure. Our results revealed the complicated evolution, reassortment, and mutations of receptor binding sites of H6-subtype AIVs, which emphasize the importance to continuously monitor the epidemiology and evolution of H6-subtype AIVs. Avian influenza is a kind of avian infectious disease caused by the avian influenza viruses  characterized by respiratory system lesions or systemic sepsis. AIVs can be divided into low pathogenic AIVs (LPAIVs) and high pathogenic AIVs HPAIVs; . CompareRemarkably, H6 subtype AIVs can not only infect birds but also infect mammals. A strain of H6N6 was isolated from swine in Yangzhou, Eastern China in 2009 . The firn = 389), Huzhou (n = 294), Zhoushan (n = 100), and Taizhou (n = 140). The samples in Zhoushan were free-range samples from farmers. The total RNA extracted from the samples was detected by RT-PCR using universal primers targeting the M gene . All RT-PCR positive samples were isolated with 10-day-73 old SPF chicken embryos for 96 h at 37 °C for virus isolation. Hemagglutinin-positive samples were further confirmed by RT-PCR with above primers M-F and M-R. The isolate was serially passaged on chicken embryos and subjected to extract RNA for Next-generation sequencing (NGS).To investigate the prevalence of AIVs in Zhejiang Province, fixed location surveillance in poultry farms were conducted in four cities of Zhejiang Province in 2021. A total of 923 oropharyngeal and cloacal swabs including 810 from chickens and 113 from ducks were collected from apparently healthy poultry from four cities in Zhejiang, including Jiaxing (The ultra-concentrated virus was sent to Genergy Bio-Technology (SHANGHAI) CO., LTD for Next-generation sequencing. The main methods were as follows: NGS  was usedNGS sequencing reads were processed and assembled as described previously . The filIn order to describe the spatiotemporal evolution of H6-subtype AIVs, the H6NX and HXN6 influenza viruses were focused in this study. The data of the global distribution of H6NX are listed in All HA sequences from GISAID and Genbank were used to determine the distribution ratios of various subtypes across continents. Coding region sequences (CDS) were used for phylogenetic reconstruction using RAxML v8.2.4  based onThe phylogenetic tree was visualized using iTOL v4 . For fur8 and sampling every 1,000 steps. Four dependently runs were combined using Logcombiner. In addition, we used a coalescent-based nonparametric skyline prior to the tree topologies to model the effective avian size over time.The TempEst was used to assessed temporal signal in our data sets  and Pathp cut off of 0.05 was considered as true reassortment , 8.16% (24/294), 28% (28/100) and 0 (0/140), respectively. A strain of chicken-derived H6N6 virus  was isolated from the samples of Huzhou. The nucleotide sequence lengths of PB2, PB1, PA, HA, NA, NP, M, and NS fragments of ZJ49 were 2,280, 2,274, 2,151, 1701, 1,380, 1,497, 982, and 838 . Total oAccording to the phylogenetic tree , 13 geneThe NA genes of the N6-subtype AIVs can be divided into two primary branches, N6.1 and N6.2, corresponding to the branches dominated by North America and Eurasia, respectively . The NorAccording to the ML trees constructed based on the internal fragments of H6N6 , the disR2. The result indicated a positive correlation between genetic divergence and sampling time (R2 = 0.4008) and appeared to be suitable for phylogenetic molecular clock analysis in BEAST , ST339-like, ST2853-like, HN573-like . Our resThe H6-subtype AIVs spread from North America to Eurasia around 1976. The effective quantity size increased around 1990, reached a peak around 2015, declined after 2015, then kept in a stable level after 2018. However, newly isolated virus strains had been found in China, Vietnam, South Korea and other places. Whether H6-subtype AIV will cause a large-scale re-epidemic in poultry in above mention countries beside North America and Eurasia is unclear. Therefore, it’s important to continuously monitor the genetic characterization and evolution of H6-subtype AIVs to get better control of their epidemic.The high mutation rate of amino acids enabled AIVs to evolve rapidly, thereby helping them overcome host barriers. Antigenic shift and antigenic drift were two major kinds of antigenic variation occurring in AIVs. Antigenic shift was a result of the reassortment of viral genome segments. To overcome selective pressures and get a better adaptation to the new environments or hosts, the homologous RNA reassortments within segments produced a diverse subtype in most viruses . The H6-HA protein was a homotrimer, with each monomer containing two polypeptide chains, HA1 and HA2. The receptor-binding site formed a shallow pocket at the tip of the globular domain and comprised three secondary structural elements and one base element . The thrThis is a study that broadens the knowledge of H6-subtype AIVs from genetic evolutionary, reassortment, and mutations of receptor binding sites. Continuous monitoring and molecular characterization of the H6-subtype AIVs, especially H6N6 subtype, will be required for a better understanding of the evolutionary dynamics of the virus, which can further assist in improving control measures for the diseases.https://www.ncbi.nlm.nih.gov/nuccore/?term=ON692794:ON692801[accn] repository, accession number ON692794-ON692801.The data presented in the study are deposited in the MC, YH, and JZ conceived and designed the experiments. MC, YH, and XB performed the experiments. MC and YH analyzed the data. MC and ML wrote the paper. All authors contributed to the article and approved the submitted version.This work was supported by the National Science Foundation of China (grant no. 32192454) and the China Agriculture Research System (grant no. CARS-40-K13).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.