Aedes albopictus, vector of several human arboviruses, has spread from its native range in South-East Asia to all over the world, largely through the transportation of its eggs via the international trade in used tires. Albania was the first country invaded in Europe in 1979, followed by Italy in 1990 and other Mediterranean countries after 2000.In the last four decades, the Asian tiger mosquito, Ae. albopictus in Italy (today the most heavily-infested country in Europe), Greece and Albania, by analyzing a panel of >100,000 single nucleotide polymorphisms (SNPs) obtained by sequencing of double-digest Restriction site-Associated DNA (ddRADseq). The obtained dataset was combined with samples previously analyzed from both the native and invasive range worldwide to interpret the results using a broader spatial and historical context. The emerging evolutionary scenario complements the results of other studies in showing that the extraordinary worldwide expansion of Ae. albopictus has occurred thanks to multiple independent invasions by large numbers of colonists from multiple geographic locations in both native and previously invaded areas, consistently with the role of used tires shipments to move large numbers of eggs worldwide. By analyzing mosquitoes from nine sites across ~1,000-km transect in Italy, we were able to detect a complex interplay of drift, isolation by distance mediated divergence, and gene flow in shaping the species very recent invasion and range expansion, suggesting overall high connectivity, likely due to passive transportation of adults via ground transportation, as well as specific adaptations to local conditions.We here inferred the invasion history and migration patterns of Results contribute to characterize one of the most successful histories of animal invasion, and could be used as a baseline for future studies to track epidemiologically relevant characters (e.g. insecticide resistance). Aedes albopictus, one of the most successful invasive animal species worldwide, which in the last 40 years has invaded all continents resulting from the transportation of its eggs via human induced dispersion, especially the international used tire trades. Results showed that the invasion process was triggered by multiple independent (and most likely ongoing) importations of large number of eggs from different continents. Afterward, ground transportation of adult mosquitoes (e.g. by cars and trucks) and the capacity of the species to adapt to novel environmental conditions have allowed the colonization of whole countries, as clearly shown to have occurred in Italy. Overall, the results are consistent with a major role of human activities in the extraordinary expansion of the species, which today can be considered a permanent pest in all Mediterranean European countries, where it has already caused the infections of Europeans with exotic viruses (such as chikungunya) once confined to tropical regions and today representing a major concern also in temperate regions.Studying the genomes of invasive populations allows for the tracing of invasion processes. In this study, the authors have focused on the invasion of Albania, Italy and Greece by the Asian tiger mosquito,  Aedes (Stegomyia) albopictus —commonly known as the Asian tiger mosquito or forest day mosquito—is one of the most successful invasive animal species worldwide [s Skuse, 894—commoorldwide ,3.Ae. albopictus was reported, for the first time outside its original range, in Albania [Ae. albopictus populations are established, including Slovenia , Russiaa , Turkeya .Ae. albopictus was fostered by human activities via passive transportation of desiccated eggs by global and local used tire trade, and also the successive process of colonization was strongly influenced by humans. Similar to what had previously been observed for the closely related species Aedes aegypti [Ae. albopictus has possibly been able to progressively adapt to urban and sub-urban habitats [Ae. aegypti, Ae. albopictus has been able to extend its range out of the tropics, mainly due to the development of diapausing eggs capable of overcoming cold periods and hatching only at the beginning of the following permissive season [The worldwide invasion by  aegypti –34, Ae. habitats , which oe season ,37.Ae. albopictus in urban habitats in temperate countries not only represents a significant nuisance capable of changing human habits particularly in recreational areas [Ae. albopictus have been recorded in the last 10 years in Europe, specifically in France [Ae. albopictus will expand further towards northern Europe and Balkan countries, further extending the risk of tropical arbovirus transmission [The widespread presence of an aggressive and day-time biting mosquito species such as al areas ,39, but al areas , 41 and al areas . Autochtn France –45 and in France , and twon France ,48 and in France , 50. Modsmission ,52.Ae. albopictus human-mediated high dispersal ability makes it challenging to detect spatial structuring of genetic variation due to the high levels of gene flow [Ae. albopictus invasion dynamics and population history have revealed high levels of genetic connectivity among populations and the likely occurrence of repeated introductions, but were limited by the relatively low resolution of the genetic markers used , theiations; –63), andiations; , 64–66).iations; ) have bet et al.  revealedt et al.  detectedt et al.  showed tAe. albopictus genetic diversity along a ~1,000-km latitudinal gradient across Italy and in a few populations from neighboring European countries, which were invaded either earlier (Albania) or later (Greece) than Italy, and to infer their invasion history and migration patterns.We used the same ddRAD protocol as Kotsakiozi et al.  and combAedes albopictus samples analyzed in the present study originated from ovitrap collections carried out by local entomology teams from May to October 2016 in nine sites across Italy, one site in Albania and one in Greece  confirmglobal-dataset and 2016- dataset respectively. The global-dataset included the 2016- dataset of 11 populations from Italy, Albania, and Greece, along with populations from 5 native and 15 invasive collection sites in southern Europe, North America, South America, Africa, and the native Asian range of Ae. albopictus  to seven (in the 2016-dataset). Previous studies have shown that such a sample size is adequate for population genetic studies when analyzing large numbers of SNPs throughout the genome [To provide a broad spatial scale for some analyses we combined the newly collected data with those from Kotsakiozi et al. , and genbopictus . Sample bopictus  varied fe genome , 75. Alse genome –78.DNA extraction was performed on whole mosquito carcasses using the DNeasy Blood and Tissue kit (QIAGEN), according to the manufacturer’s instructions with two modifications: 1- the addition of 4ul of RNAse A/sample, and 2- DNA elution was carried out in double-distilled water (ddH2O). Quality of the extracted DNA was assessed by running 5ul on a 1.5% agarose gel stained with Midori Green Advance DNA Stain (Nippon Genetics Europe GmbH). DNA was quantified using a microplate reader and the Quant-iT PicoGreen kit (Thermo Fisher Scientific), according to manufacturer’s instructions. For the ddRAD library preparation only 88 specimens with high quality and molecular weight DNA were used.The ddRAD libraries were prepared according to the Peterson et al.  protocolprocess_radtags option of stacks [Ae. albopictus reference genome [2016-dataset, consisting of ~103K SNPs. The filtering details are provided in Sequence data (reads) were de-multiplexed using the f stacks  and mappe genome  using the genome  and Samte genome . Variante genome  obtaininde novo” assembly for the raw reads (obtaining the 2016-denovo-dataset), using ipyrad v.0.7.18 [2016-denovo-dataset are presented in the Due to the relatively low quality of the assembled reference genome , we alsv.0.7.18  to ensur2016-dataset with the data from world-wide collections published by Kotsakiozi et al. [global-dataset, consisting of ~38K SNPs from 31 sites. Details on the filtering process for the global-dataset are presented in the To study the biogeographic relationships between the Italian, Greek, and Albanian samples and the worldwide ones, we concatenated the i et al.  which har2max/2 value as a threshold, where r2max is the maximum squared correlation coefficient value estimated by VCFtools. The LD filtered 2016- and global- datasets consisted of ~55K and ~26K biallelic SNPs respectively.Since some of the subsequent analyses (see The software PGDSpider v. 2.0.5.2  was used2016-dataset (~103K SNPs) using VCFtools [IS) per population averaged over all loci as well as the 95% confidence intervals  were estimated using the R-package hierfstat [global-dataset (~38K SNPs), using the same software.Individual observed heterozygosity (H_obs) was estimated on the VCFtools . ObserveVCFtools . The samierfstat . To compST values between all pairs of populations of the 2016-dataset, using Arlequin v.3.5 with 1,000 permutations and a significance level of 0.05. The partitioning of the genomic variation among and within populations was evaluated using a locus by locus hierarchical Analysis of MOlecular VAriance -AMOVA- [Genetic differentiation was estimated by computing F -AMOVA- , as impl2016-dataset (~103K SNPs) through a Mantel test, using the R-package adegenet 2.0.1 [Isolation by distance (IBD) was evaluated for the et 2.0.1 , betweenet 2.0.1 ). Geograet 2.0.1 . To eval2016-dataset) and in the global scale dataset . The ML approach used was implemented in ADMIXTURE [2016-dataset: 55,199 SNPs and global-dataset: 26,094 SNPs), as suggested by the authors. To avoid bias in cluster estimation due to the different sample size of the populations [global-dataset was pruned to retain approximately 4 specimens for each of the 31 populations used, totaling 123 samples. The best number of genetic clusters (K) was chosen based on the cross-validation procedure available in ADMIXTURE. Multivariate methods were also performed for the 2016-dataset (~103K SNPs) and the global-dataset (~38K SNPs) and included a Discriminant Analysis of Principal Components (DAPC) and a Principal Components Analysis (PCA), implemented in R packages adegenet [Maximum Likelihood (ML) and multivariate methods were used to assess the number of genetically distinct groups of populations present in the fine spatial scale,  to retain only SNPs  from the longest scaffolds in which at least 25 SNPs per scaffold were present. This included scaffolds from 120,543–1,305,381bp length, representing ~4% of the Ae. albopictus genome. Data for each scaffold were phased using FASTPHASE v. 1.2 [Because of the low genetic differentiation in the aset see  below, tf 0.002; ). The fif 0.002; . Prior tE v. 1.2  and then2016-dataset samples after LD filtering , by using the R-function divMigrate [To further investigate the dispersion events in the focal area of this study we analyzed gene flow patterns among vMigrate  implemenvMigrate . This apvMigrate . ComputavMigrate , which c2016-dataset  were removed from downstream analyses because of poor sequencing quality . Thus, the final filtered  2016-dataset consisted of 103,289 SNPs and 77 individuals. The average number of SNPs per specimen was 86,000  with an average depth of 25.5X (SD = 7.7). The amount of missing data was 16.4% (SD = 5.9) per specimen and 16.4% (SD = 8.2) per locus. After filtering this dataset for LD, a total number of 55,199 SNPs were retained. The same filtering strategy led to 38,550 SNPs for the global-dataset  was obtained after alignment of the v.0.7.18  on the 22016-dataset: 103,289 SNPs, global-dataset: 38,550 SNPs, Table F in p-value = 0.464) are observed among the Italian sampling sites. These sites display significantly higher H_obs and H_exp levels than those observed in the geographically close Albanian (AL) and Greek (GR) sites  than for the Italian and Albanian ones. Among the Italian sites, significantly lower FIS values were found for Puglia (PG = 0.194) and Liguria (LG = 0.200)   ones.2016-dataset  are shown in Table B in ST estimates range from 0.011 to 0.132 and are all significantly differentiated , with the exceptions of the two pairwise comparisons, including two sites from central Italy (MA and LZ: FST = 0.011) and one of these sites (MA) from the Sicilian one . The highest FST values within Italy are observed between the Puglia samples and those from Veneto (FST = 0.096) and Liguria (FST = 0.094).Estimates of genetic differentiation calculated on all the sampling sites in the 2016-dataset  are shown in Table C in AMOVA results based on the global-dataset , the results on the 2016-dataset  suggest genetic differentiation with geographic distance . This result is strengthened by focusing only on the 9 Italian sites  and when excluding the Sicilian sample from this analysis  supports the existence of four genetically distinct clusters  does not detect genetic structure (K = 1 supported as the best clustering), the DAPC analyses on the 2016-dataset , separates the samples in 8 groups  only. Results  reveal high levels of connectivity among the Italian sites , which is a crucial feature for population genomic analyses, as several of the methods used to infer population genetic estimates are sensitive to missing data [2016-datasets (reference genome assembly and de novo assembly) allowed us to overcome the possible biases in SNP calling due to the low quality of the current Ae. albopictus assembly [The ddRAD approach applied allowed us for the identification of>100,000 SNPs with a very good coverage (>70%) and a limited percentage of missing data , likely due to technical limitations of the various methods in dealing with recently differentiated populations, which represents a challenge even when using thousands of SNPs, as in this study. It is also relevant to note that, despite the large number of genotype SNPs analyzed, the recent and fast global invasion makes the conclusive reconstruction of the history of the colonizing process by genetic data very hard. The following paragraphs comment the most interesting results obtained in view of current knowledge on Ae. albopictus invasive populations [Genetic diversity levels do not show systematic differences between native and invasive samples at a global scale, as already suggested by Kotsakiozi et al. , but difulations .Results corroborate the overall pattern of worldwide differentiation observed by Kotsakiozi et al. , but alsDespite the relatively uneven sampling density, the analyses of the samples from the invasive range suggest a complex pattern of repeated invasions from multiple geographic locations from the native range. The mosquitoes from US  share a similar pattern of genetic admixture with the Japanese ones , suggesting a northern Asia origin for the continental North American invasion. On the other hand, the Hawaiian sample (HAW) shows different relative frequencies of the three genetic clusters found in the mainland US samples. This could be due to multiple factors, including multiple colonization events or different colonization dynamics with genetic drift and reduced gene flow facilitating the establishment in this remote location of a genotypic fingerprint different than the one from the mainland populations. Mosquitoes from the two African sites  are genetically homogeneous, belonging to a single genetic cluster found mostly in South-East Asia. Mosquitoes from South American sites  are genetically distinct from all others and mostly belong to a genetic cluster only found at low frequencies in one sample from the native range , underscoring a limitation of this study due to the limited sampling of the native range.Ae. albopictus invasion in this continent and enable the identification of previously unidentified genetic structuring. Despite most genetic variation among the samples from Italy, Greece and Albania is found at an individual and intra-population level  makes Italy more susceptible to multiple invasions than other Mediterranean countries, which have been invaded more recently than Italy , whose association was shown to lead to enhanced resistance in Ae. aegypti [The possibility to combine data from different studies by analyzing a common set of thousands of variable SNPs Click here for additional data file.S1 Appendix(RAR)Click here for additional data file.S2 Appendix(RAR)Click here for additional data file.


Nowhere has the scale and scope of urbanization been larger than in China over the last few decades. We analyze Chinese city development between the years 1996 and 2014 using data for the urbanized components of prefecture-level cities. We show that, despite much variability and fast economic and demographic change, China is undergoing transformations similar to the historical trajectory of other urban systems. We also show that the distinguishing signs of urban economies—superlinear scaling of agglomeration effects in economic productivity and economies of scale in land use—also characterize Chinese cities. We then analyze the structure of economic change in Chinese cities using a variety of metrics, characterizing employment, firms and households. Population size estimates remain a major challenge for Chinese cities, as official numbers are often reported based on the Hukou registration system. We use the information in the residuals to scaling relations for economic quantities to predict actual resident population and show that these estimates agree well with data for a subset of cities for which counts of total resident population exist. We conclude with a list of issues that must be better understood and measured to make sense of present urban development trajectories in China. China has transformed itself in just a few decades from a rural, low-income nation to a booming urban system, displaying rates of economic development and social change that are unprecedented in history for a nation of its size. As recently as the mid-20th century, China’s economy was dominated by its primary sector and urbanized areas provided only a minor part to the value creation of the national economy. The vast majority of the population lived in rural areas, accounting for an urbanization rate of only 20% as recently as in 1975 [The explosive growth of Chinese cities and the general demographic and economic restructuring of the country via massive urbanization are the principal manifestations of this monumental transformation . CertainTo investigate these issues, we provide here a comprehensive attempt at characterizing Chinese urbanization, by analyzing the patterns of growth and transformation of mainland China’s top nearly three hundred prefecture-level cities. Prefecture-level cities are a main administrative unit in China, one rank below that of provinces . They consist of several districts and counties, which are classified as rural or urban depending on their economic and demographic character. In the following, we will use the term “prefecture-level city” and “city” to denote the collection of districts and counties in each prefecture-level city that are classified as urban. Although this is not an ideal definition of a functional urban area—such as Metropolitan Areas in the US and Europe , which aHukou system. A person’s Hukou status is defined at birth, mainly based on their family history [One of the peculiar challenges of understanding Chinese urbanization has to do with how population counts are organized according to the nation’s official statistics. Among other difficulties , one of  history . Citizen history . CitizenAt present, only local governments can change their citizens’ Hukou status. Thus, the current resident classification system provides a tool to control the migration of rural citizens into urban areas and the mobility of the population in general. This control mechanism makes it possible for local authorities to suppress, or at least substantially discourage, the emergence of uncontrolled growth of informal settlements for the poorest in China, as seen in many other fast urbanizing countries , but alsFor many authors, the ability to control population migration has been seen as one of the main factors for the unprecedented success of China’s economic policies over the last few decades . At the In terms of its consequences for understanding urbanization, the Hukou system of resident classification introduces several empirical difficulties when analyzing data for Chinese cities. Official China City Statistical Yearbooks produced by the National Bureau of Statistics of China and prefecture-level cities only typically include population estimates for those with a local Hukou status. Typically, permanent residents with an urban Hukou from other cities are not counted locally but rather in their city of original registration. The same issue affects residents with a rural Hukou, who are not counted in any of the prefecture-level cities, only at their county of registration. Only recently have a few prefecture-level cities started to perform a true census of their full resident population. These estimates make it possible to develop and evaluate a method to estimate the true size of some of the larger and more attractive Chinese cities based on the magnitude of their scaling effects. It allows us to check estimated population sizes in a sample of cities with universal counts and extrapolate our predictions to some of the more interesting cases where no such data are available.Before getting to this issue at the end of the manuscript, we start with a description of the system of Chinese prefecture-level cities and existing data from official statistics. A number of interesting quantities are available annually at this scale that characterize urban economies on the aggregate, in terms of sectors, financial accounts, conditions of households and firms, and indicators of added value (profits). We also use these data to characterize the longitudinal transformation of the Chinese urban system and demonstrate that its cities share a number of well known general agglomeration effects, i. e. superlinear scaling with city size, the tell tale of urban economies and observed for most systems of cities in the world –19. ThisThe tell tale signal of cities and urbanization is a set of general phenomena known as scaling relations in geography and complex systems, and as agglomeration effects in economics . The simMore specifically, larger cities tend to have larger economies (measured e. g. by their Gross Domestic Product) on a per capita basis than smaller towns. They also tend to be denser spatially, for example, as measured by the amount of land that is built up as infrastructure and places of work and residence. Moreover, the behavior of these expected values for each city given its population size is scale-invariant and does not depend on a particular city size, and, thus, is well described by power-law functions.Yi(t), such as GDP or land area, for city i at time t asY0(t) is the intercept characterizing the baseline quantity per capita in the smallest cities in the system, β is the scaling exponent , Ni(t) is the city’s population, and ξi(t) is a residual to the scaling relation.To see this more explicitly in the case of Chinese prefecture-level cities, we write any urban extensive quantity, Yi. The advantages of this form, however, derive from the fact that β is a general quantity, which tends to be approximately independent of city size Ni and takes specific values β = 1 ± δ,  [Ni, and are zero on average, in the sense that Nc is the number of cities in the urban system, so that the magnitude of the ξi(t) expresses how well a city performs relative to others in the urban system. For this reason the ξi are sometimes known as Scale-Invariant Metropolitan Indicators, where the word Metropolitan refers to the functional definition of cities (metropolitan areas) as mixing socioeconomic networks embedded in space, in the sense of urban theory.T ≃ 1/6) . In suchξi is particularly interesting. Because of relatively large deviations from the average scaling trend in Chinese prefecture-level cities see , the anaIn terms of GDP, we see several notable and relatively well known large deviations from scaling. For example, Shenzhen—specializing in the manufacture and export of advanced electronic products and adjacent to Hong Kong—is the most exceptional large city in the nation for its GDP. It is only surpassed by the relatively small city of Ordos, which is rich in natural resources—especially coal—and has been the subject of substantial central government investment, leading to the highest GDP per capita in China.2—is probably a bad approximation to the actual size and extent of its functional city.Generally speaking, many large cities in China deviate from the scaling noticeably, mostly by over performing in terms of GDP. Among the largest cities, only Chongqing, nominally the largest prefecture-level city in China, appears too poor for its size, as well as too large spatially. This points to the fact that its spatial definition—an enormous region covering more than 82 thousand kmIn terms of land area, we see a similar pattern as for the GDP, but with smaller deviations from scaling see . Most ofIn conclusion, while there is a large amount of variability among Chinese prefecture-level cities, average scaling shares similar properties to other urban systems. It shares a similar magnitude for observed scaling effects and is broadly in line with urban scaling theory , 22, 23.In this respect, we note that not only is In the previous section, we showed that Chinese prefecture-level cities exhibit increasing returns to their population scale in terms of their reported GDP; despite a substantial city to city variability and some issues of potential bias concerning population estimates. Nevertheless, the scaling exponent is roughly in line with theoretical expectations and observations of many other urban systems worldwide , 22, 23.βF > 1), and that the corresponding 95% confidence intervals remain above unity in all cases. Thus, a large variety of economic quantities representing business activity, real estate investment, local government finances and household behavior, all are characterized by strongly superlinear effects with population size within the Chinese urban system.All these quantities show even larger variability, depicted by the large error bars, than more aggregated quantities such as GDP. This effect is not only present between cities, but also from year to year. In many cases, clear from the several panels in A few more particular issues are reveled by a closer analysis of these results. Regarding the general economy, we see that value added tax (VAT), a measure of the profits of companies, is roughly in line with the agglomeration effects observed for GDP. Retail sales, however, show a somewhat stronger exponent, suggesting that larger cities may provide tradable sales exported to smaller places and abroad. This effect—as measured by the corresponding scaling exponent—is even stronger for wholesales. Investments in real estate, as shown in The budget revenue of local governments appears as a slightly growing fraction of GDP with city size—indicated by a large scaling exponent similar to real estate investments– which is also consistent with VATs collected, at least over the last few years. Some science expenditures (described as Science Administration) show the strongest concentration in larger cities, with largest scaling exponent in Finally, the behavior of households suggests that the economy of larger cities is characterized by both greater value of deposits and access to credit per capita, roughly by the same degree. Interestingly, the exponent on savings is superlinear too, but weaker, indicating that wealth accumulation may lag behind rates of economic activity. In recent years, these numbers would suggest that a decreasing fraction of GDP with city size is being saved by Chinese households, perhaps a signal of increasing cost of living in larger cities.Wages, in In summary, all quantities characterizing many different aspects of the economies of Chinese cities show strongly superlinear effects, clearly indicating that the wealth and productivity of China as a nation is strongly predicated on its urbanization and in particular on the economic agglomeration effects of its (largest) urban areas.We have seen, in the previous sections, that the way of counting population in Chinese cities raises issues of biases and accuracy. The Hukou system creates situations where highly desirable cities will have their populations typically underestimated while at source, in other cities and rural areas, population must be correspondingly overestimated.Only recently have some of the prefecture-level cities started to perform a true census of their full population. In 2014, several cities generated this kind of data and published them in the China City Statistical Yearbook, specifically the directly-controlled municipalities Beijing, Shanghai, Tianjin, and the provinces Guangxi, Guangdong, and Hainan. All of those provinces are located in the coastal areas of China, which have experienced the largest rates of growth, thus, the data might be biased to a certain degree.In the following, we will show how the scale-invariance of the mean GDP for a city given its population size can be used to estimate the true population of Chinese cities in a simple way.δi for each city i, defined asNi is an estimated number, such as those provided by Chinese National Statistics. Substituting δi can be written asβ and the deviation ξi.ξi will have new estimated populations larger than those given, and vice-versa.It is well known, that the population of Beijing, for example, is largely underestimated by almost 40%, when only residents with a local Hukou are counted . This diβF, the exponent derived from the best fit, and to 19.2 million with βT from theory . Similarly other good estimates are derived for the largest cities for which data about the permanent population is available. These results are shown in Our exploration of the dataset provided by the China City Statistical Yearbooks shows that aggregated quantities, such as the GDP provide the best estimates, especially for larger cities, as depicted in For smaller cities, i. e. those with resident population smaller than about 5 million, the same method nudges the population in the right direction, but tends to create corrections that are probably too large.Smaller cities whose population are underestimated by our proposed method are mostly places located away from the coast. For example, Guilin that has an actual population of 1.5 millions and a registered population of 1.3 millions, is estimated to have a population of 0.9 millions according to its GDP. Guilin’s economy mostly relies on the primary and tertiary sectors, namely local produce and tourism, which is different from the general economic characteristic of the China’s urban system. Similar patterns are shared by all of the cities that receive estimates that are lower than the actual population. Thus, improved estimates could in principle be generated by taking into consideration economic sectoral composition in each city, together with knowledge of the relationship between employment and value.βT and 2.4 million for βF. A property that might be explained by the location of Shantou, as it is not located in the vicinity of the Pearl River Delta with its strong economy, but part of the province of Guangdong. Thus, it faces challenges from the siphon effect of the Pearl River Delta, which has an influence on all cities in the province  would estimate the total number of permanent residents to be much smaller than the actual population of 4.68 million, specifically, at 2.3 million for ince see .When the method is applied to all cities in the dataset, including those for which no actual population number are given, a distinct pattern emerges, as expected from the economic development in the last decades. There are three main clusters of cities, which have a significantly higher population compared to the population given by the Hukou system. They are all along the coastline, located around Beijing and Tanjing, Shanghai, and the Pearl River delta.In inland China, some cities with a small number of people as counted by local Hukou are estimated to have a much larger population according to their GDP. These are mostly cities that are rich in natural resources, and are among the cities with the highest GDP per capita. In such cases, again, taking into account sectoral composition and the translation between productivity and employment may be critical, especially for mining and oil and gas industries.The nominally largest city in China, Chongqing, is the only large city for which the estimator predicts a smaller population size than the one given by the Hukou counts. As mentioned earlier, the current definition of Chongqing as a direct-controlled municipality leads to an enormous urban area, which is likely a poor approximation for the size and extend of its actual functional city.In summary, we proposed method to estimate the true resident population of Chinese cities based on deviations from expected scaling (agglomeration) effects within the urban system. The method works reasonably well for larger cities and helps identify if the population of any city is under- or overestimated by the Hukou registration counts. The strength of our method compared to other estimators, such as morphological, big data, remote sensing approaches, or combinations of them –30, is tIn recent decades, China has undergone one of the most extraordinary historical transformations from a predominantly rural and poor country to one of the world’s biggest economies, the largest exporter and a huge dynamic nation creating rising living standards for its vast population within the context of rapid urbanization and the advent of many large and glitzy cities.As we write, this transformation remains incomplete and the relation of city sizes to different quantities in the aggregate understudied. Both extant data quality issues and the lack of functional urban area definitions make the present study of Chinese cities necessarily a very approximate exercise, as we discussed throughout this paper. Nevertheless, we have shown here, using available official data for sets of urban districts in Chinese prefecture-level cities, that much of the urbanization of China has close parallels in other nations both past and present. This is remarkable given the level of ambition and impact of government policies in China over the last seven decades and speaks clearly to the extraordinary importance of taking a fundamental scientific perspective regarding the essential properties of cities and of processes of development.Chinese exceptionalism does not hold empirically, as we showed here. The only potential signal for some of these peculiar characteristics of Chinese urbanization may be found in larger levels of variation away from scaling across places. Such variations may express stronger local contexts and interventions in distinct cities and regions (e.g. Shenzhen), but are certainly also partially the result of statistical uncertainties in data collection and organization.Secondly, a fundamental set of characteristics connected to both the creation and growth of cities and their economies are scaling (agglomeration) effects. These effects express non-linear increases in socioeconomic productivity, as well as savings in infrastructure, with city population size. We have shown that scaling relations for aggregate GDP and land area for the urban portions of China’s prefecture level cities show exponents (elasticities to population size) in line with other nations and with urban scaling theory; indicating quantitatively consistent superlinear effects in economic productivity and sublinear economies of scale in land uses (densification). This is remarkable because the explanation for these effects in terms of urban scaling theory  (and anaβGDP ≃ 1.22 ± 0.05 > 1.17) and has greater uncertainty than in other nations. This expresses the fact that Chinese data are much noisier than, say, for the US urban system and, in addition, that a number of large Chinese cities are still under-predicted by the scaling relation. In plain language, these results mean that, when comparing two cities in China one with the double the population of the other, the former will have on average a GDP per capita that is 22% larger, but that this average expectation is less predictive than in other nations. Moreover it says that this number underestimates the actual GDP of some of China’s most prominent cities, such as Shanghai, Beijing, Shenzhen or Tianjin.A couple of features of these results stand out, starting from the fact that the exponent for GDP tends to be slightly larger than predicted by theory . We showed that, where estimates are available, scaling makes good predictions for the actual total numbers counted. Thus, it is at least plausible that some of the present uncertainty in urban indicators in Chinese cities is related to various inadequate and inconsistent ways to estimate their working populations as well as their economic productivity and costs. It is important that such measurements become more consistent, better aligned with standard indicators in other cities and urban systems, and more spatially disaggregated  so that issues of distribution and statistics can be better assessed and understood.China and its cities face a number of challenges going forward that would strongly recommend a much more systematic scientific analysis of their structural characteristics and patterns of change. As a consequence of China’s historical demographic policies and more recent migration restrictions, many cities in China will likely very soon experience labor shortages and population contractions. These trends will tend to intensify over time as China’s population ages quickly . Given tMoreover, a transformation to more sustainable cities, economically and environmentally, will need to be quickly achieved—within a couple of decades—based on rising quality of life for urban dwellers, and on improved and more valuable services and innovation, relying on the expanded capabilities of an older, more skilled population. Success at this critical juncture requires not only better and more adaptive policies, but also a more fundamental, comprehensive and evidence-based understanding of China’s rapid urbanization, which will continue to be critical for our global sustainability transition affecting every person in China as well as the planet at large.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.


Robinia pseudoacacia L.) from 19 provenances, covering most of its natural distribution; we randomly selected 367 tender leaves with well-grown and different maternal strains from this group for further analysis. Forty-eight simple sequence repeat (SSR) primers were successfully selected from 91 pairs of SSR primers using native-deformation polyacrylamide gel electrophoresis. In addition, we identified identical genotypes among all individuals and evaluated the quality of the markers. From this, 35 loci were confirmed for analyses of genetic diversity and differentiation of the black locust provenances, which contained 28 expressed sequence tag-derived simple sequence repeats (EST-SSRs) and 7 genomic DNA-derived simple sequence repeats (G-SSRs). We observed high genetic diversity among the native black locust provenances, from which Wright’s fixation index and molecular variance suggested that a majority of the genetic differentiation variation could be attributed to within-provenance differences. The genetic distance and identity results indicated that geographic distance was not a dominating factor influencing the distribution of black locust. This is the first study to evaluate provenance genetic variation in native black locust samples using two types of SSR markers, which provides a comprehensive theoretical basis for ex situ conservation and utilization of genetic resources, with an emphasis on breeding applications.Understanding the genetic diversity and differentiation of the genetic resources of a species is important for the effective use and protection of forest tree resources. Ex situ development is a common method for the protection of genetic diversity and an essential resource for users who require ready access to a species’ germplasm. In this study, we collected seeds of black locust ( Genetic variation can reflect the adaptation potential of species driven by long-term evolution via mutations, genetic drift, gene flow, and natural selection, which support rich genetic variation within species ,2,3. DurRobinia pseudoacacia L.) is a nitrogen-fixing tree native to the Appalachian and Ozark Mountains of the eastern United States. It is a widespread deciduous broadleaved tree with excellent characteristics of poor soil tolerance and resistance to salinity and alkalinity and with substantial ecological and environmental value [In situ and ex situ conservation are two common methods for protecting of plant genetic resources and the latter serves as an essential genetic resource for users who require ready access, to a species’ germplasm. Ex situ is defined as the conservation of plants samples/seeds away from their field habitats with the goal of genetic improvement and conservation as a means of combating the genetic erosion (loss of useful genes) due to natural and human-mediated disorders ,10,11. Bal value . Howeveral value . Black lal value ,14,15,16al value ,18,19.TH) gene may regulate transcription via the microsatellite HUMTH01 [Unfortunately, there are few investigations of the genetic diversity and differentiation of black locust seeds collected within its natural distribution, and all ex situ conservation analyses of its genetic diversity performed to date have been based on allozymes ,20,21, a HUMTH01 . AccordiIn this study, we evaluated the genetic variation of black locust provenance, based on G-SSR and EST-SSR markers. We used seeds collected from the distribution of black locust in the United States as well as ex situ conserved samples from Henan province, China. The aims of our study were to clarify the genetic diversity among and within provenances, the genetic differentiation among provenances, the degree of provenance genetic differentiation, and the correlation between the genetic and geographic distance of the analyzed provenances to provide a theoretical basis for improved evaluation, use, and protection of black locust genetic resources.We screened 91 pairs of SSR primers using polyacrylamide gel electrophoresis (PAGE) in eight black locust samples from different sources. Of these, 43 pairs failed to amplify clear PCR products, while 48 exhibited successful amplification. The rate of polymorphism was 52.75%. This set of polymorphic SSR primers included 37 EST-SSRs and 11 G-SSRs .The set of 48 primer pairs was further analyzed to obtain suitable SSR markers for subsequent analyses of the black locust provenances. Four of the markers  had more than 20% missing locus data. Genotype pairing was performed on all individuals; no two samples had an identical genotype. The Ewen–Watterson test was performed, four loci  with significant deviations from a neutral equilibrium model. In addition, Micro-Checker analysis detected eight loci  possessing null alleles. After combining these results, 13 pairs of SSR markers were ultimately deleted, and the remaining 35 markers, consisting of 28 EST-SSRs and 7 G-SSRs, were used for further analyses.Robinia pseudoacacia L., the EST-SSRs consisted of 35.714% trinucleotide repeats, 28.571% hexa-nucleotides repeats, 17.857% penta-nucleotide repeats, 10.714% tetra-nucleotide repeats and 7.143% di-nucleotide repeats. In contrast, the G-SSRs were composed of only di-nucleotide repeats  ranged from 3 (at Rp-21) to 34 (Rops18) (PIC) and gene diversity (H) were consistent, with the highest values at Rops18 , followed by Rops05 (0.886 and 0.895), and the lowest at Rp-44 (0.061 and 0.061) (mean: 0.566 and 0.595). The expected heterozygosity (He) ranged from 0.054 (Rp-44) to 0.837 (Rops05) (mean: 0.553), while the observed heterozygosity (Ho) ranged from 0.044 (Rp-44) to 0.835 (Rp-38) (mean: 0.495). At the provenance level, the genetic diversity index was used to assess the variance of heterozygosity (Ne) = 3.527) observed for the IN provenance and the lowest values (Ne = 2.457) for the KS provenance. In terms of uniformity, Shannon Information index values (I) ranged from 0.867 (IN provenance) to 1.306 (KS provenance). The IN and KY provenances showed the highest levels of expected heterozygosity . In total, 81 private alleles (PAs) from all 19 provenances were identified in this study (average frequency = 0.343), with the highest number (12 PAs) found in the WV provenance (Na) estimated for each provenance ranged from 3.086 (KS) and 7.629 (WV). Furthermore, Wright’s fixation index (STF) values among global and pairwise multi-loci ranged from 0.040 (Rp-12) to 0.110 (Rops08) and 0.007 (WV vs. Kentucky) to 0.089 (Kansas vs. Arkansas), respectively  . Meanwhizygosity , with thovenance  The No. ectively .Analysis of molecular variance (AMOVA) was performed for all black locust accessions from the 19 study areas to analyze the genetic variation between and within provenances. The variance accounted for 3% of the variance among the provenances and 97% within provenances .Nei’s unbiased genetic distance and identity measure revealed genetic distance and identity values ranging from 0.002 to 0.141 and from 0.869 to 0.998, respectively, between provenances . Among aPIC values of 0.817 and 0.503, respectively. Diversity analyses found G-SSRs to be more polymorphic than EST-SSRs. These results are consistent with those of other studies, including those on both barley (mean PIC = 0.727 for 48 G-SSRs and 0.581 for 16 EST-SSRs) [Linum usitatissimum L. (mean PIC = 0.326 of 15 G-SSRs and 0.245 for 7 EST-SSRs) [Gleditsia sinensis, Cercis chinensis, Wisteria sinensis (Sims) Sweet, Trifolium repens, Amorpha fruticose, Sophora japonica, Sophora japonica var. pendula, Robinia pseudoacacia ‘Frisia’ and Robinia pseu-doacacia var. decaisneana). The high rate of EST-SSRs amplification in related species may be derived from a conserved region of the plant genome, which is consistent with the lower mutation frequency seen for ESTs compared to that of genomic DNA [Robinia pseudoacacia L.The microsatellite markers used in this study consisted of both expressed sequence tag-derived SSRs (EST-SSRs) and genomic DNA-derived SSRs (G-SSRs). A total of 37 EST-SSRs and 11 G-SSRs were confirmed as polymorphic based on results from a 6% native-deformation PAGE for eight plant materials with different phenotypes and sources. In this study, the levels of polymorphisms and allele numbers were higher for G-SSRs compared to EST-SSRs, with mean ST-SSRs) . Neverthomic DNA ,40. A reomic DNA . The anaSimple sequence repeats have emerged as one of the most popular and versatile marker types for plant genetics ,35,36; hN (3.2) in seedings obtained from seed collections representing the natural range of black locust that was determined using the allozyme method [N = 7.429) seen in 18 R. pseudocacia L. individuals, which was computed based on seven G-SSR markers [I) was 1.133 across all 19 provenances, substantially higher than that seen in R. pseudocacia L. samples collected from the 10 main planting districts in China, as determined based on 10 pairs of AFLP (I = 0.138) and ISSR markers (I = 0.373) [Microsatellite markers are an essential tool for gene discovery, enabling the detection of distinctive alleles that can be useful for studying marker-trait associations in populations . In thise method , and it  markers . The hig= 0.373) ,23. ThisHo) and expected (He) levels of heterozygosity were 0.495 and 0.553, respectively. These levels are somewhat lower than those seen in two previous reports of black locust diversity performed using G-SRR markers. Lian et al. (2002) [Ho and He levels of 0.615 and 0.773; 7 G-SSR markers, respectively, compared with 0.661 and 0.739, respectively, in Mishima et al. (2008) [Ho was lower than that of He, at both the locus and provenance levels, indicative of a deficit of heterozygotes in black locust. In addition, ISF was 0.105 and 0.133 at the locus and provenance levels, respectively, possibly related to a degree of self-intersection in this species. A similar result was reported in a study of black locust allozymes (ISF = 0.072) [Observed and expected heterozygosity are two important parameters for gauging gene diversity . In this. (2002)  reported. (2008) . Low lev= 0.072) ,46.STF is usually defined as low (STF < 0.05), medium (0.05 > STF > 0.15), or high (STF > 0.15) [Robinia pseudoacacia L., and shows that black locust may possess favourable adaptation due to the abundant variation among individuals in a provenances.The degree of genetic differentiation in provenances based on  > 0.15) . Based o > 0.15) . Additio > 0.15) , who repR. pseudoacacia fruits were collected from the 19 main black locust distribution areas in the United States (including 18 states and 1 state border) from September to October 2010, which includes most of the natural distribution of black locusts . After extraction, to check the quality and concentration, 1 µL genomic DNA from each genotype was loaded onto a 1% agarose gel and quantitated using the NanoDrop 2000 . All DNA samples were normalized to an equal concentration (20 ng/µL) using TB elution buffer (Tiangen) and stored immediately at −80 °C for SSR amplification.We assessed 91 pairs of SSR primers, including 21 pairs of G-SSR primers found in the literature ,28,29 an® Master Mix (blue) , 1 µL of the forward primer (10 µM), 1 µL of the reverse primer (10 µM), 2 µL genomic DNA (20 ng/µL), and 6 µL double-distilled water. PCR amplification was performed by an initial denaturation step at 94 °C for 4 min, followed by 20 cycles of 94 °C for 30 s, 60 °C to 50 °C for 30 s (decreasing by 0.5 °C per cycle), and 72 °C for 1 min, 20 cycles with the annealing temperature fixed at 50 °C, 72 °C for 45 s, and a final extension at 72 °C for 10 min using the BIO-RAD T100 thermal cycler [To obtain SSR primer sets with rich polymorphism and steady bands for subsequent experiments, we selected eight plant materials with different phenotypes and sources that had been investigated by black locust breeders in China using a screening assay. l cycler . The ampGleditsia , Cercis , Wisteria (Papilionoideae), Trifolium (Papilionoideae), Amorpha (Papilionoideae), Sophora (Papilionoideae), and Robinia (Papilionoideae), was used to evaluate SSR markers. Markers were obtained from Beijing Forestry University Campus, China  [The effectiveness comparison of EST-SSR and G-SSR amplification in several genera of Leguminosae, including 1′1′′ E) . Genomic® Master Mix (blue) , 0.1 µL forward primer (10 µM), which was labeled at the 5′ end with fluorescent-dye , 0.3 µL reverse primer (10 µM), 0.2 µL M13 primer , 2 µL genomic DNA (20 ng/µL), and 7.9 µL sterile double-distilled water [Based on the screening, optimal primers were applied to the provenance of 367 samples for amplification analysis. SSR amplification was performed by PCR in a 20-µL reaction volume containing 10 µL 2× TSINGKEed water . The PCRThe PCR products were separated using the ABI 3730XL DNA capillary electrophoresis analyzer  and a GeneScan-500LIZ size standard. Alleles of the SSRs were confirmed using GeneMarker ver. 2.2.0 .N, Na, Ho, He, percentage of polymorphic loci, and Shannon’s information index were computed using GenAlEx ver. 6.501 [ISF, ITF, and STF) among provenances were estimated using FSTAT ver. 2.9.3 software [PIC values were calculated using PowerMarker ver. 3.25 [The r. 6.501 . Calculasoftware . PIC valer. 3.25 . Hardy–Wer. 3.25  with 100er. 3.25 , and theer. 3.25 . AMOVA wer. 3.25 . Nei’s ger. 3.25 .The present study revealed that (1) the genetic diversity among the native black locust populations is high, (2) the majority of genetic differentiation variation was attributed to differences within populations, and (3) geographic distance is not a dominant factor influencing the distribution of black locust. These findings provide comprehensive information that can be used as a foundation for genetic assessments, improvements, and management of black locust.


Substantial improvements in access to food and increased purchasing power are driving many people toward consuming nutrition-rich foods causing an unprecedented demand for protein food worldwide, which is expected to rise further. Forage legumes form an important source of feed for livestock and have potential to provide a sustainable solution for food and protein security. Currently, alfalfa is a commercially grown source of forage and feed in many countries. However, soybean and cowpea also have the potential to provide quality forage and fodder for animal use. The cultivation of forage legumes is under threat from changing climatic conditions, indicating the need for breeding cultivars that can sustain and acclimatize to the negative effects of climate change. Recent progress in genetic and genomic tools have facilitated the identification of quantitative trait loci and genes/alleles that can aid in developing forage cultivars through genomics-assisted breeding. Furthermore, transgenic technology can be utilized to manipulate the genetic makeup of plants to improve forage digestibility for better animal performance. In this article, we assess the genetic potential of three important legume crops, alfalfa, soybean, and cowpea in supplying quality fodder and feed for livestock. In addition, we examine the impact of climate change on forage quality and discuss efforts made in enhancing the adaptation of the plant to the abiotic stress conditions. Subsequently, we suggest the application of integrative approaches to achieve adequate forage production amid the unpredictable climatic conditions. Food security faces threats from climate change and weather variability and needs immediate consideration, especially in geographic regions where agriculture is highly dependent on rainfall . Recent Rhizobium relationship , a perennial legume crop, is the most frequent and commercially grown source of forage and feed in many countries. However, alfalfa may not be the priority crop across geographic regions, and other legume crops providing quality forage may be preferred. For instance, in sub-Saharan Africa (particularly in West Africa) and India, cowpea [Vigna unguiculata (L.) Walp.] has been an integral part of traditional cropping systems where grains are used as food and haulms are fed to livestock as a nutritious fodder (Pisum sativum subsp. Arvense), white clover (Trifolium repens L.), and sweet clover  have been favored in different regions in the United States. Hence, given the inevitability of climate change, it is crucial to assess the forage potential of different legume crops in terms of forage quality parameters, digestibility and animal performance, and feasibility of sustainable growth and consistent yields. In this review, we assess the effects of climate change on forage quality, the efforts made in identifying the genetic basis of forage quality and yield traits, and genetic manipulation to improve forage digestibility in three important legume crops, alfalfa, soybean [Glycine max (L.) Merr.], and cowpea.As many as 60 different legume crops have been cultivated as sources of forage and feed for animals. Currently, alfalfa . While increases in CO2 concentration have only small effects on forage solubility and fiber (cellulose and lignin) components, they strongly affect crude protein (CP) concentrations and forage digestibility  are also expected to contribute to global warming. O3 acts as a shield in the stratosphere by providing protection from lethal shortwave solar ultraviolet radiation but is an air pollutant and greenhouse gas in the troposphere. It poses a critical threat and is a challenging problem for world food security and plant habitats , white clover and subterranean clover (Trifolium subterraneum L.)  concentrations, reduction in the nutritive quality of aerial biomass, acceleration of senescence, and reduced regrowth and total forage production. From these studies, it can be inferred that efforts to develop international control policies to reduce exposure to ozone will be needed in the near future  . These sr future .Table 1). It is well documented that abiotic stresses cause different kinds of phenotypic, biochemical, and molecular alterations that severely impair plant growth and development, productivity, and yield . Plants Alfin1  and rice (Oryza sativa) has opened a way for genetic manipulation of soybean plants with abiotic stress tolerance  and simple sequence repeat (SSR) markers widely distributed across the genomes of agronomically important crops . FurtherTable 2). In addition, Table 2).The genetic dissection in tetraploid alfalfa was complicated due to the tetrasomic inheritance and the difficulties in analyzing polyploid linkage relationships . Thus, tMedicago truncatula is a model plant species and can be used to map and clone genes in legume crops. The availability of the genome sequence for M. truncatula, which has a high syntenic relationship with cultivated alfalfa, may provide comprehensive information on genetic inheritance and functional genomics of agronomically important traits. In forage legumes, aerial morphogenesis is an important trait, which determines plant and seed biomass as well as forage quality .Association mapping has been seen as a promising methodology for trait mapping due to the availability of a large number of identified SSR/SNP markers and high throughput genotyping platforms . GWAS enTable 2). Thus, genetic dissection of forage-related traits using advanced approaches could be useful in identifying loci that can be exploited through marker-assisted breeding to develop drought-resistant alfalfa cultivars with improved nutritive value.Genotyping-by-sequencing (GBS), a cost-effective molecular marker genotyping method, has been widely preferred in GWAS analysis to investigate marker-trait associations in different plant species, including alfalfa. 5) population of 94 plants derived from the Essex × Forrest cross to identify markers associated with shoot fresh weight (SFW), shoot dry weight (SDW), and SFW/SDW ratio (Table 2). Using composite interval mapping, they identified four QTLs for SFW, three QTLs for SDW, and three QTLs for SFW/SDW, explaining 12–34% of the total phenotypic variation. The study utilized a cross of two cultivated soybeans differing in many traits, including root and shoot traits. However, wild soybeans (Glycine soja) have also been shown to possess alleles that can contribute positively to different agronomically important traits in cultivated soybean (Table 2). Many of these QTLs showed high phenotypic variation and were expressed across different environments. Such QTLs with large phenotypic effects or the markers linked to these QTLs could be valuable in marker-assisted breeding programs. Alleles from PI 483463 contributed to the SFW QTL and most of the QTLs for forage quality traits, except CP content, indicating that wild soybeans like PI 483463 can serve as a valuable source of novel alleles for forage quality.Compared to alfalfa, little attention has been given to soybean as a forage crop, and hence there are few studies of genetic dissection of forage traits.  soybean . Lee et Dt1 (determinate stem), an ortholog of Arabidopsis TERMINAL FLOWER1 , on the genetic map spanning a distance of 11 cM on linkage group 15. Further marker-trait association and analysis of synteny with M. truncatula and G. max identified an ortholog of the EZA1/SWINGER (AT4G02020.1) gene as the candidate gene for the Hls locus. Such genes may be utilized to improve the quality of cowpea leaves as a vegetable and forage, in addition to contributing to our understanding of the genetic control of leaf shape in legume crops. Delayed senescence, grain yield, and biomass yield under water stress significantly affect forage quality in cowpea cultivars. Cowpea exhibits significant variation in several morphological traits and yield, which are essential for its use as an animal feed. Although several cultivars of cowpea have been utilized extensively for forage, as monocrop or intercropped with cereals, few genetic studies have been conducted to investigate forage traits of the species. Cowpea is used generally as a dry grain and animal fodder crop. Its leaves are also a high-protein source. Using a RIL population Sanzi × Vita 7, G. max) and 82% with M. truncatula . Leaf protein content and stem NDF digestibility displayed the best genome-enabled predictions, with accuracy values close to 0.40 and 0.30, respectively , 4-coumarate-CoA ligase, cinnamoyl-CoA reductase (CCR), ferulate-5-hydroxylase (F5H), phenylalanine ammonia-lyase, cinnamate-4-hydroxylase (C4H), 4-coumarate 3-hydroxylase (C3H), and peroxidases, which are targeted for genetic modification. Manipulating these genes in alfalfa, tobacco, and switchgrass (Panicum virgatum L.) improved forage digestibility in in vitro experiments . O-methyl transferase (OMT) caused a 10-fold decrease in syringyl:guaiacyl content and increased in vitro digestibility in transgenic tobacco , and are considered potentially suitable candidates for lignin modification.Several researchers have manipulated forage lignin content in alfalfa  in soybean. Such candidates can also be targets for genetic manipulation to improve forage digestibility. In addition, genes identified for lignin biosynthesis in alfalfa and other crop species can be exploited for genetic manipulation using soybean or cowpea as a heterologous system.Unlike alfalfa, cowpea and soybean have received little attention as forage crops, and hence no efforts have been made to manipulate genetically lignin and cell wall composition in these species. The limited genetic information (genes/QTLs identified) for forage traits in soybean and cowpea may be another reason. As mentioned earlier, ynthesis . In addiynthesis . Hence, pression . MoreoveFigure 1). A multi-site evaluation of available germplasm and other genetic resources, through improved, cost-effective, and high throughput phenotyping technologies, needs to be conducted to assess trait performance. Materials of high value can be utilized as genetic resources for improving the target traits, first by identifying the markers/QTLs/genes controlling desired traits and using them in selection procedures (through MAS/GS). In addition, improving forage digestibility through genetic engineering can enhance animal performance. Recent advancements in genetic and genomic technologies have facilitated genetic dissection of complex traits. Further genomic research is expected to reveal genes, and associated molecular markers, controlling forage quality and yield-related traits in key legume crops. The advent of high-throughput genotyping platforms further enables screening large numbers of plants in a short period to unravel the genetic makeup of the plants. When integrated, these approaches are expected to facilitate the genomics-assisted improvement of forage legume cultivars.Due to the significant progress made in access to food in many countries, demand for animal protein sources such as milk and meat is ever-increasing. Because the overuse of grasslands is becoming a serious problem, achieving quality feed in sufficient quantities will be challenging. Forage legume crops are of immense significance in providing quality fodder and feed to livestock, the major source of protein food for humans. Forage yield is associated with several other traits, such as plant height, maturity, pod length, number of pods, and leaf and stem morphology. Thus, in order to achieve high forage yield, we emphasize the importance of applying an integrated approach, involving trait selection and evaluation, genetic improvement and manipulation, and integrated farming  and products with environmental or other benefits contributing to sustainable food chains, and needs to be accelerated. Forage legume crops with genetically improved quality traits may be beneficial, both for digestibility of animal feed and for the environment.KPK, RT, and SA wrote the manuscript. KPK conceptualized the overall structure, and edited the manuscript. KPK, RT, and SA prepared illustrations, figures, tables, and references. JTS and JGS contributed critical comments to the draft. J-DL conceptualized, critically edited, and approved the manuscript. All the authors reviewed the draft.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.


The village and street dogs represent a unique model of canine populations. In the absence of selective breeding and veterinary care, they are subject mostly to natural selection. Their analyses contribute to understanding general mechanisms governing the genetic diversity, evolution and adaptation. In this study, we analyzed the genetic diversity and population structure of African village dogs living in villages in three different geographical areas in Northern Kenya. Data obtained for neutral microsatellite molecular markers were compared with those computed for potentially non-neutral markers of candidate immunity-related genes. The neutral genetic diversity was similar to other comparable village dog populations studied so far. The overall genetic diversity in microsatellites was higher than the diversity of European pure breeds, but it was similar to the range of diversity observed in a group composed of many European breeds, indicating that the African population has maintained a large proportion of the genetic diversity of the canine species as a whole. Microsatellite marker diversity indicated that the entire population is subdivided into three genetically distinct, although closely related subpopulations. This genetical partitioning corresponded to their geographical separation and the observed gene flow well correlated with the communication patterns among the three localities. In contrast to neutral microsatellites, the genetic diversity in immunity-related candidate SNP markers was similar across all three subpopulations and to the European group. It seems that the genetic structure of this particular population of Kenyan village dogs is mostly determined by geographical and anthropogenic factors influencing the gene flow between various subpopulations rather than by biological factors, such as genetic contribution of original migrating populations and/or the pathogen-mediated selection. On the other hand, the study of oldest surviving dogs suggested a biological mechanism, i.e. a possible advantage of the overal heterozygosity marked by the the microsatellite loci analyzed. Canis lupus) was the ancestor of all current dog breeds and that the domestication process probably occurred in multiple locations in Asia  . The FisST– 1)/4 . DiffereST– 1)/4 . The PHYST– 1)/4 .The Bayesian clustering algorithm implemented in the STRUCTURE v2.3.4. software  was usedFor the population structure analysis, the value K = 3 for the microsatellites was estimated as the most informative. While the group of European dogs was represented by a single major cluster , the entST value was low  in African dogs. Significant differences (P<0.01) in allelic frequencies between European and African dogs were observed for loci NOS3a, IL6b, TLR2, TLR4b, TLR7, TLR9a,b, LY96a,b, and MYD88a. Observed and expected heterozygosities were similar in both groups. Seven SNP loci were out of HWE (deficiency in heterozygous genotypes) in European dogs compared to one locus (TLR7) in village dogs  and Mt. Kulal (P = 0.009) dogs. A lower number of effective alleles per locus was found in Mt. Ngyiro when compared to Mt. Kulal dogs. Mt. Kulal showed significantly (P = 0.013) lower observed heterozygosity values than Lake Turkana, while values of expected heterozygosities were similar.The genetic diversity of the three Kenyan village dogs subpopulations identified by microsatellite analysis was further characterized and compared Tables  and S8. For MHC markers, the population substructure analysis revealed three slightly unequally distributed clusters, where Mt. Ngyiro could be distinguished from Mt. Kulal and Lake Turkana . This suDQA, 17 for DQB and 25 for DRB1. Seven new DRB1 alleles and one new DQB1 alleles were identified. All the new alleles were found on specific haplotypes, as shown in DRB1 alleles (094v). The highest values of mean expected (0.88± 0.03) and observed heterozygosities (0.87± 0.02) were found in Mt. Ngyiro dogs, with non significantly lower heterozygosities in both Lake Turkana and Mt. Kulal dogs. No departure from HWE was observed. The DQA1 locus showed the lowest heterozygosity , and for IL6b, TLR1, LY96a (P<0.01).The genetic diversity observed in expressed SNP marker loci was comparable in all three subpopulations Tables  and S11.ST pairwise comparisons among the three subpopulations for different types of markers are in ST values indicate more isolation and differenatiation of the populations compared, the interpretation of the data is that most of the genetic variation in Kenyan dogs existed within the population, with rather small differences among the three subpopulations. In all types of loci, the genetic distances between Mt. Kulal and Lake Turkana dogs were smaller than distances between either of them and Mt. Ngyiro dogs. The gene flow rate estimates are in The FS = 0.943, P = 0.005) only between MHC and microsatellite loci  higher values of mean observed heterozygosity of microsatellites. The overall mean heterozygosity of IR gene SNP loci was also higher in the surviving dogs; however, this difference was not significant. Allelic variants of the genes MYD88 and LY96 associated with a lower risk of infection [Parameters of genetic diversity in the group of oldest dogs and their comparison with the original Mt. Kulal population are shown in nfection  were morThe village and street dogs represent a unique model of canine populations. Although they always represent small and location specific samples, their analyses contribute to understanding general mechanisms governing their genetic diversity, evolution and adaptation , 65. BesA comparison with a study where the same microsatellite marker set was used  showed tThe European dogs studied here were selected with the primary purpose to cover the range of variation observed in Europe, and as such they do not represent a real genetic population. Therefore, in contrast to the Kenyan population, we did not analyze the detailed structure of the European group but we limited ourselves to its differentiation from African dogs. As mentioned above, the regular procedure in analyzing population structure is to select the lowest K value capturing the maximum degree of structure . For ourWhen compared with pure breed studies , 20, 68,ST values computed for microsatellite loci have shown that the population studied here is also clearly structured in three genetically similar but discrete subpopulations. In this sense, we may expect that factors determining its structure are similar to other African population, although their relative contribution is probably locally specific. A complex of biological factors, including inbreeding, genetic drift and/or various types of selection pressure as well as geographical, ethnic and social factors representing different gene flow barriers may contribute to the final overall structure.African village dogs were shown to have a complex population structure, due to effects of geography, gene flow barriers, and the presence of non-native dogs . The resDomesticated dogs had probably followed waves of Nilotic migrants to the south. The Samburu pastoralists as part of Maa people came to the area of today’s Kenya during the second half of the first millennium from southern Sudan, while origins of Turkana can be traced into Karamojong people of western Uganda and their migration eastwards in 17th century , 50. AltAlthough variation at neutral loci can give insights into genetic diversity within populations and genetic differentiation among populations, they provide only limited information on adaptive evolution . The evoMHC genes are prime candidates for such studies. A comparison of three MHC genes (same like in this study) and a set of 17 neutral microsatellites was succesfully used for studying assessing effects of balancing selection in wolves by Niskanen et al. . Here, wIL6, TLR2), one genotype was not found in the African village dogs, while in the European group, all three possible genotypes were observed. As both loci are in HWE, this is due probably to low frequencies of the minor alleles. However, the reason for the low frequencies remains unknown.As no data on non-MHC IR gene SNPs in African or other village dog populations are available, we only could make comparisons with whole genome SNPs and/or between non-MHC IR gene SNPs in African and European dogs. The genetic variation of 300 whole genome SNPs in African village dogs reported by  is slighA comparison between the three groups of markers shows that the genetic structure defined by neutral microsatellites could not be observed for potentially non-neutral non-MHC IR loci. The differences between IR gene SNPs and microsatellite loci are probably due mostly to differences in their numbers of alleles. On the other hand, the patterns on multi-allelic MHC genetic diversity were closer to multi-allelic microsatellites rather than to bi-allelic SNP loci , S3 Fig.ST values even for neutral sites linked to the selected locus. Therefore, weak effects of pathogen-mediated selection cannot be excluded, but the Tajima´s test of selective neutrality failed to detect them  was found in this group compared to its original Mt. Kulal subpopulation. Microsatellite loci themselves are not likely to underlie the heterozygosity advantage. Due to high numbers of polymorphic variants/haplotypes combined with low numbers of dogs available, it was impossible to make such an estimate for the MHC region, the prime candidate for testing the heterozygosity advantage. However, such a comparison could be made for the non-MHC IR gene markers studied, and no specific differences were observed in the parameters of overall genetic diversity. Nevertheless, comparisons of allelic frequencies in specific loci associated with infections in this population [LY96, differences were observed not only between surviving and original Mt. Kulal dogs (-6) lower frequencies of a resistance-associated Ly96 allele were observed in European dogs, while significantly higher frequencies of this allele were found in the “survivor” group. Similarly, differences between Kenyan and Czech dogs (P = 1x10-4) as well between the survivor group and the Kenyan group as a whole (P = 0.023) were found for MYD88. These data support the assumption that at least some markers associated with infection in this population might have an adaptive value.The village dogs are considered to live in conditions comparable to those during early stages of dog domestication. Infectious diseases are considered to be the main cause of morbidity and mortality in village dogs . In thispulation  showed slal dogs , but alsThe increased heterozygosity in microsatellite markers observed in survivors difference suggests a higher overall genomic diversity associated with higher age under these particular conditions. Similar or even identical panels of microsatellite markers were used for assessing the extent of neutral and/or non-neutral genetic diversity in dogs and wolves , 76. TheTaken together, it seems that the genetic structure of this particular population of Kenyan village dogs is mostly determined by geographical and anthropogenic factors influencing the gene flow between various subpopulations rather than by biological factors, such as genetic contribution of original migrating populations and/or the pathogen-mediated selection. On the other hand, the study of oldest surviving dogs suggested a biological mechanism, i.e. a possible advantage of the overal heterozygosity marked by the the microsatellite loci analyzed. Adaptation to a putative pathogen pressure in this pathogen-rich environment seems to be more difficult to detect. To our knowledge, this is the first report on the genetic diversity in non-MHC IR candidate gene markers in domestic dogs. Our data show that polymorphic candidate non-MHC IR gene markers are a rather heterogeneous group in terms of their value for estimating non-neutral genetic diversity. Differences between populations in disease-associated markers suggest that a panel of selected polymorphisms associated with diseases in the particular population could be a way to detect subtle effects of pathogen-driven selection, but that a higher number of markers and their careful selection for a particular purpose would be necessary.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S5 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableSEM standard error of the mean.(DOCX)Click here for additional data file.S3 TableMK–Mt. Kulal. MN–Mt. Ngyiro. LK–Lake Turkana. E–European dogs. SEM standard error of the mean.(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table* Not the same alleles. ** only AA and Aa genotypes.(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 TableMK- Mt. Kulal. MN- Mt. Ngyiro. LK- Lake Turkana.(DOCX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.S9 Table(DOCX)Click here for additional data file.S10 Table(DOCX)Click here for additional data file.S11 TableMK- Mt. Kulal. MN- Mt. Ngyiro. LK- Lake Turkana* Not the same alleles. ** only AA and Aa genotypes.(DOCX)Click here for additional data file.S12 TableNS Non-significant, **P<0.01.(DOCX)Click here for additional data file.S13 Tableobserved (Ho) and expected (He) heterozygosities and loci out of HWE.(DOCX)Click here for additional data file.S14 Table1* monomorphic locus.(DOCX)Click here for additional data file.S15 Table(DOCX)Click here for additional data file.


Aphis gossypii, in two counties of Beijing, China during spring migration using samples from watermelon. We performed aphid genetic analysis using restriction site associated DNA sequencing (2b‐RAD) and investigated the relationship between land cover and the genetic diversity. The percentage area of land cover  was quantified in each particular scale (ranging from 0.5 km to 3 km) and was used as a predictor variable in our generalized linear models. We found a moderate level of genetic differentiation among nine sampled populations. Geographic distance and genetic distance were not significantly associated, indicating that geographic location was not a barrier to migration. These nine populations could be clustered depending on their level of genetic diversity (high and low). The genetic diversity (Shannon’s information index) was positively correlated with grassland at the spatial scales of 1 and 2 km and negatively with orchard and vegetable at 0.5 and 1 km. Genetic diversity was best predicted by the grassland + orchard + vegetable model at a spatial scale of 1 km. Based on the method of relative weights, orchard land had the greatest relative importance, followed by grassland and vegetable land, in that order. This study contributes to our understanding of the genetic variation of aphids in agricultural landscapes.Despite increasing evidence that landscape features strongly influence the abundance and dispersal of insect populations, landscape composition has seldom been explicitly linked to genetic structure. We conducted a genetic study of the melon aphid,  It lays eggs in autumn on a primary host , and in the spring, it migrates to secondary host plants  to address the following questions: 1) Can genetic analysis reveal landscape aspects of A. gossypii colonization? 2) Are landscape features associated with the genetic diversity of A. gossypii colonizing the same host?The landscape genetics of 22.1Sampling was conducted in the Beijing area of northern China Figure . There wA. gossypii in NCBI database. All samples  in this study were deposited at our laboratory.Sampling was carried out in the early growth season, when aphids were migrating from primary hosts to the secondary host (melons). All melon aphids were sampled in greenhouses, because the spring melon crop is usually produced in greenhouses. We sampled 3–5 greenhouses at each location. In each greenhouse, we sampled five clones randomly by collecting leaves containing aphids. In each clone, only one alate aphid was used for further analysis. We randomly chose 10 individuals per location to represent the population of that location. Sample sizes for 2b‐RAD sequencing are listed in Table ® handheld GPS receiver, a latitude‐longitude projection and WGS84 datum. Sampling locations were further confirmed by consulting topographical maps of the study area and using Google Earth.The distance between any two sample sites was at least 1 km. GPS coordinates were recorded using a Magellan2.2Genomic DNA was isolated using the DNeasy Tissue Mini Kit (Tiangen) following the manufacturer instructions. A total of 90 aphids were genotyped for SNP loci. 2b‐RAD sequencing and genotyping were outsourced to Shanghai OE Biotech Ltd. . The 2b‐RAD libraries were prepared following the protocol developed by Wang, Meyer, McKay, and Matz . In brieQuality filtering was conducted as follows: raw reads were trimmed to remove adaptors, and the terminal 2‐bp positions were discarded to eliminate artifacts that might have arisen by ligation. Reads contained no restriction site or long homo‐polymer regions (>10 bp). Ambiguous bases (N) or reads of low quality  were removed. SNPs were determined, and genotypes were called using a maximum‐likelihood statistical model implemented in the software Stacks v1.32  with 5 m resolution. The landscape structure was analyzed using ArcGIS 10 . Land covers were classified into seven general categories, including cropland, vegetable, orchard, grassland, woodland, water, and urban. Cropland was categorized as land primarily being cultivated with crops such as winter wheat. The vegetable category included protected fields, for example, greenhouses, in which vegetables were usually planted. The orchard category had perennial crops, such as orchard trees. The grassland category was herb‐dominated land. Woodland included all forest and shrub land excluding the trees in residential sites. Water represented wetland and open water. Urban represented human architecture, roads, etc. For each of the sampling sites, landscape composition was estimated in four circular sectors , representing a nested set of landscape sectors at four spatial scales. The percentage of each category was measured within each landscape circle.2, P‐value, and AIC. We used a new method called relative weights to assess the relative importance of predictors. The method closely approximates the average increase in R‐square obtained by adding a predictor variable across all possible submodels  and correlation analyses were performed using the statistical program R version 3.4.0 . We removed four individuals (3 in MZ and 1 in XYT) because of their low‐quality reads and obtained a total of 6,280 loci, which scored 95% coverage.3.2The percentage of polymorphic loci ranged from 25.96% (LHC population) to 78.60% (XYT population). Shannon’s information index values across loci ranged from 0.156 (LHC population) to 0.396 (XYT population). The mean observed heterozygosity (Ho = 0.187) was similar to the mean expected heterozygosity (He = 0.175) in the total number of populations .There was a moderate level of genetic differentiation among populations. Pairwise Fst values between the populations ranged from −0.042 to 0.310  of the genetic variation was attributable to variation within populations, whereas approximately 11% of the variation was attributable to variation between populations. However, no variation was attributed to variation among regions (Daxing county and Shunyi county) Table . The PCo3.3p = 0.066). The total amount of variance accounted for by this model (R‐square = 0.796) was divided among the predictor variables. Orchard land accounted for 57.80% of the R‐square, grassland accounted for 27.72%, and vegetable land accounted for 14.48%. Based on the method of relative weights, orchard land had the greatest relative importance, followed by grassland and vegetable land, in that order.Shannon’s index was positively correlated with grassland at the spatial scales of 1 and 2 km and negatively with orchard at 0.5 and 1 km. Shannon’s index was best predicted by the grassland + orchard + vegetable model at a spatial scale of 1 km Table , having 44.1A. gossypii samples collected from watermelon in the Beijing area at landscape scales. We found evidence for moderate population differentiation at different sample sites with landscape features associated with the genetic variation.We completed genetic analysis of A. gossypii populations were collected from watermelon on which reproduction was via apomictic parthenogenesis. The sampling period was during the establishment of the spring migration population. Early season individuals on melon were alates, and so the entire potential colonizing population was sampled. Host plant pressure on aphids occurs in melons and aphid‐resistant melon cultivars and could alter the genetic structure of A. gossypii , Punica granatum (pomegranate), and Zanthoxylum simulans (Chinese prickly ash) . The present study about landscape genetics of aphids may help improve our understanding of colonization of A. gossypii and the corresponding spatial scale. However, the limited sample size and location may reduce the statistical power. Measuring the distribution of primary hosts could be a way to investigate aphid colonization. An alternative analysis strategy used in some landscape studies  based on genetic diversity. The results suggest that the colonization of watermelon by A. gossypii occurs locally and is affected by the surrounding habitats. More grassland in the landscape tends to favor the maintenance of genetic diversity. Orchard and their perennial plants reduced the genetic diversity of A. gossypii. The land cover, such as grassland and orchard, had a strongest effect at the spatial scale of 1 km. By identifying features of the landscape that surrounds fields and can affect these dynamics, growers can develop more efficient crop protection strategies relying on habitat manipulation.Our study clearly supports the hypothesis that landscape features can affect the genetic variation of Raw 2b‐RAD sequence reads are available at NCBI PRJNA407691.The authors have declared that no competing interests exist.Z. Dong and Z. Zhang conceived and designed the study. Y. Li conducted sampling and isolated DNA. Z. Dong analyzed the data and prepared the manuscript.