About 59.9% of the participants had sufficient knowledge of genetics, and around 50% had a favorable attitude toward genetic testing. Knowledge of genetics is significantly correlated (p ≤ 0.001) with a positive attitude toward genetic testing. Gender, age, level of education, marital status, family income, and family history were significantly correlated with respondents’ understanding of genetics. Gender, family income, residence, and family history were associated with attitudes toward genetic testing at a 0.05 level of significance. There is a need to strengthen peoples’ knowledge of genetics and attitudes toward genetic testing through diverse educational programs and healthcare strategies. Impetus on how to disseminate genetic information on consanguinity and transmission of diseases should be prioritized in regions where consanguineous marriages are high.This study investigated people’s knowledge of genetics, attitudes toward genetic testing, and views on consanguinity. This cross-sectional study utilized a validated questionnaire modified from published studies to collect data on people’s knowledge of genetics and attitudes about genetic testing among 1008 respondents from various Saudi Arabian regions. Using SPSS software version 26, data were analyzed using a  The importance and impact of genetics in medicine have grown with the discovery of genetic susceptibility to common conditions such as cancer, cardiovascular disease, and even psychiatric illness. The discoveries of rare genetic illnesses and disorders have only added to this; hence, genetics should be taught in every medical school . GeneticCompleting the Human Genome Project (HGP) paved the ground for a quick acknowledgment of genetics’ importance in medicine. Advances in genetics and genomics, particularly human genome sequencing, have prepared the way for a paradigm change in illness prevention, diagnosis, and treatment based on a person’s genetic profile . The accIt should be understood that genetic testing for health risks in a particular population has benefits and drawbacks. It has advantages for disease diagnosis, family planning, medical research, and other facets of healthcare. However, there are limitations to screening, and risk detection is one of them. Another is the complexity of deciding what course of action to take in light of that risk . DespiteIn several Middle Eastern countries, consanguineous marriages are common; genetic disorders are prevalent and have more severe effects among the Arab populations ,19,20. TThere needs to be more research on the general public’s knowledge of genetics and attitude toward genetics testing among the Saudi population. A fundamental understanding of genetics is necessary to comprehend genetic testing and its potential benefits for people. Comprehending people’s attitudes about genetic testing can help address the challenges, misunderstandings, and information gaps in this subject. This study investigated people’s knowledge of genetics, their attitudes regarding genetic testing, and the factors influencing their decisions. The findings of this study could be used to improve educational programs and healthcare promotion strategies aimed at increasing public knowledge and awareness of genetics and genetic testing. This study is a cross-sectional, paper-and-pencil-based questionnaire survey that explored the extent of people’s knowledge about genetics and attitudes toward genetic testing. A random sampling technique was used, and the sample size was calculated using G-power. The expected prevalence of adequate knowledge ranged between 42.2% and 50%, with a power of 80% People’s knowledge of genetics and attitudes toward genetic testing was determined using questionnaires adapted and modified from previously published studies ,30,31. TThe questionnaire was divided into three sections: The respondent’s profile, knowledge of genetics, and attitude toward genetic testing. Respondent’s profiles included age, gender, level of education, marital status, and family income. Participants were also requested to indicate from what region in KSA they live and whether or not they were born from a consanguineous marriage.General knowledge of Genetics was assessed using fifteen (15) structured true or false questions, including basic genetic concepts, inheritance of diseases, the interaction between genes and environment, and genetic variation. Survey questions to estimate the current level of genetic knowledge among Saudis were adapted from previous studies ,30. The In assessing attitudes toward genetic testing, participants were required to complete 12 questions related to their attitude toward genetic testing. Items 1 to 7 assessed peoples’ attitudes toward Predictive Genetic Testing (PGT). This test intends to determine a person’s genetic history and condition and whether they are at risk for a genetic disorder. It investigates genetic alterations or mutations related to diseases that occur before a person exhibits any symptoms of an illness [p-values of less than 0.05 were considered statistically significant. All statistical analysis was conducted using Statistical Package for the Social Sciences (SPSS) software version 26.Only completed survey questionnaires (1008) were included for data processing and analysis. Descriptive statistics in terms of means, standard deviations, median and interquartile ranges were used to describe the criteria of the studied sample. Analysis of quantitative data by ANOVA and association of qualitative variables by chi-square test was conducted. A multivariate analysis was used to determine the relationship between family history, whether children were born consanguineously or not, and other characteristics as predictors of genetic knowledge and attitudes toward genetic testing. A total of 1008 completed questionnaires were collected from various regions in Saudi Arabia. A summary of the sociodemographic characteristics of respondents is presented in People’s general knowledge of genetics is summarized in As shown in p ≤ 0.001) with a positive attitude towards genetic testing. Those with a higher knowledge level in genetics showed a more positive attitude toward genetic testing. Results showed that participants’ knowledge of genetics is significantly correlated  and attitude towards genetic testing (p = 0.026). Our findings suggest that a highly educated public will conform to genetic testing more. The difference in the genetic knowledge and attitudes toward genetic testing is worth noting when analyzed according to a family history. Results showed a significant difference (p = 0.005) in attitudes toward genetic testing between respondents who were born from consanguineous marriages and non-consanguineous marriages. Those born from consanguineous marriages have positive attitudes toward genetic testing but need to be more knowledgeable about genetics. Our results also showed that most respondents (80.2%) knew that consanguineous marriages increase the likelihood of producing children with a genetic disorder. The younger Saudi generation, with a high level of education and a good knowledge of genetic disorders, has diminishing support for consanguineous marriage. Despite this finding, the prevalence of consanguineous marriage is still high in KSA. The possible reason is the strong influence of customs and traditions that still prevail and support consanguineous marriages. It was recognized that family tradition is essential in the pervasiveness of consanguinity and genetic disorders in Saudi Arabia [Further analysis of the sociodemographic characteristics through multiple regression revealed that gender and the level of education are predictors for both knowledge in genetics , family income (p = 0.001), and place of residence (p = 0.047) to be associated with attitudes towards genetic testing. Those living in urban areas have a more positive attitude towards genetic testing than those in rural regions. This may be due to some rural regions’ underutilization of genetic testing and counseling services. The primary healthcare practitioners’ referral and utilization of these services could be improved by genetics education [Nearly half of the study participants had a positive attitude toward predictive and preconception carrier testing. Respondents with an adequate understanding of genetics had a favorable attitude toward genetic testing. Based on Rosenstock’s Health Belief Model, people’s health-related beliefs and behaviors depend partly on their knowledge level, which explains how education may influence people’s attitudes . The modducation . It mustIn other studies, the public’s perception of genetic testing for assessing illness risk is largely favorable ,41,42,43Furthermore, many respondents agreed that PCT is reasonable and that couples contemplating pregnancy should take a carrier test. Our findings reveal that gender and family income are associated with a favorable attitude towards genetic testing. Female participants with a higher income had a more optimistic view of carrier testing, predictive, and preconception. In a study of senior college students at one Saudi Arabian university, most students had favorable sentiments toward genetic testing . LikewisOn the other hand, some apprehensions and negative attitudes concerning genetic testing, voiced by nearly half of the study participants, must be addressed. To cite, many respondents were concerned that genetic testing might result in the annulment of their marriage. They also expressed concern that carrier testing could negatively portray persons with inherited disorders and that disabled people would be less accepted in society. These unfavorable attitudes and misconceptions about genetics and genetic testing can be clarified and addressed by educating and enhancing peoples’ knowledge of genetics and genetic testing. One research study among Jordanian women found that they are open to the countrywide deployment of non-invasive prenatal genetic screening, with the caveat that it should be accompanied by health education to improve the population’s genetic literacy . Public cognizance of genetic risks associated with consanguinity is indispensable. Various research has shown that consanguinity affects a person’s health over many generations and is a serious public health concern ,47,48. TDespite this decline, consanguineous marriage is still high in Saudi Arabia ,48,51; tWith a better and a more focused education, which may be delivered as early as feasible, the gap in genetic knowledge and attitudes toward genetic testing among Saudis can be prevented and modified. Similarly, incorporating additional awareness programs and campaigns for the adult and senior populations may help to change people’s opinions about genetic testing. Our study and other studies prove that higher educational attainment promotes a more positive attitude toward genetic testing. On the other hand, the general awareness, and favorable attitudes of at least 50% of the population toward genetics and premarital genetic testing, revealed a bright future outlook for the population’s perception of genetics. This is supported by society’s acceptance of people with genetic abnormalities, which a little more than half of the participants in the research agreed on. There are certain limitations to this study that should be noted. This study exhibits selection bias because data gathering was limited to “public” locations, such as universities, hospitals, and libraries due to restrictions in going from house to house or private organizations. For instance, college students aged between 30 and 40 were projected to make up most of the samples from universities and libraries. Although different age-based samples are typically found at malls and hospitals, most of the respondents who agreed to participate in this study were primarily students and younger adults under 30. This enthusiastic response from the younger generation may be attributable to their favorable attitudes toward genetics and genetic testing and their likely comprehension of the value of the information obtained from research surveys. It is also essential to remember that almost two-thirds of Saudi Arabia’s population is under the age of 35, according to the General Authority for Statistics (GAS-TAT) Report (2020). The Kingdom’s population comprises 36.7% people aged from 15 to 34 and 30.3% people aged from 0 to 14.  The highThis study highlights public knowledge of genetics and attitudes toward genetic testing. Overall, peoples’ knowledge of genetics is nearly adequate and generally demonstrates a positive attitude towards genetic testing. Many study participants still have questions regarding genes and inheritance, even if most respondents have an adequate understanding of genetics. These questions must be addressed as soon as feasible by the curricular inclusion of basic genetic concepts. Since a higher genetic knowledge and positive attitudes toward genetic testing are significantly correlated, basic genetic concepts must be offered across curricula in higher and post-graduate education to enhance positive attitudes toward genetic testing.Additionally, there is a need to improve public awareness of the risks and benefits of genetic testing. Genetic literacy may eventually create a positive public perception that will augment the support for genetic testing within Saudi Arabia and hopefully reduce the occurrence and burden of inherited disorders. Furthermore, while the participants know that consanguineous marriage increases the chance of having children with genetic diseases, current data suggest that consanguineous marriages in Saudi Arabia are still high, as much of the research has shown. Thus, impetus on how to disseminate genetic information, related to consanguinity and transmission of diseases should be prioritized, especially in regions where consanguine marriage rates are high.


Coordination between economic development (ED) and ecological environment (EE) is an important challenge for high-quality urban development. Taking the panel data related to the ED and EE of the Yangtze River Delta urban agglomeration (YUA) from 2009 to 2019 as the research objective, the evaluation system of ED and EE was constructed by introducing the coupling coordination degree model and the gray correlation degree model to analyze their development indices, coupling coordination degree and gray correlation degree in two spatial and temporal dimensions. Research results: (1) The ED indexes and EE indexes of the 26 cities in the YUA have obvious differences in different cities, and there is no synergy between the two indices. (2) The coupling coordination degree of the YUA shows a pattern of high in the east and low in the west, high in the center and low in the north and south in space, and an overall increasing trend in time. (3) In terms of gray correlation, the correlation between ED quality dimension and EE level dimension is the highest. According to the conclusion, when both the economy and environment present consistency at a high level, it will help the city’s economy to develop more efficiently and rapidly. As the world economy develops into a new stage, people are increasingly stressing about the establishment of a modern economic system with harmony between human and nature, as well as high-quality and sustainable economic development. China has made astonishing achievements in urbanization in the past decades. However, many problems have also emerged, making the cities become “sub-healthy”. The contradiction between economy and environment in some cities is becoming increasingly prominent, resource guarantee is meeting its bottleneck and eco-environment protection is faced with problems. In this regard, the Chinese government has gradually taken measures to effectively promote urban sustainable development. In 2012, the 18th National Congress of the Communist Party of China put forward the strategic goal of the five-sphere integrated plan and raised the construction of ecological civilization to a higher strategic level. In 2017, the 19th National Congress of the Communist Party of China pointed out that we should adhere to the harmonious coexistence of man and nature and establish and practice the idea that green water and green mountains are the golden hills. In 2020, Xi Jinping put forward the integration and high-quality strategic objectives of the development of the Yangtze River Delta at the symposium on solid advancement of integration.The YUA embraces the open urban belt along the eastern coast of China and the industrial intensive belt along the Yangtze River. It is the most dynamic and competitive economic agglomeration area in China. During the rapid urbanization and industrialization, however, more resources have been consumed, and the discharge of industrial waste is gradually increasing, plus the severe regional environmental pollution, bringing constant challenges to eco-environment. In this condition, the paper has assessed the coordination between ED and EE of YUA, which is of paramount importance for balancing regional ED and EE, so as to realize the high-quality development of the YUA.Promoting the coordinated development of the economy and environment and improving sustainable efficiency are important connotations of high-quality urban development. Effectively measuring the coordination of the economy and environment and the correlation of internal factors are the prerequisites for evaluating the quality of urban development. The study area of this paper includes 26 cities in the Yangtze River Delta urban agglomeration, namely Nanjing, Wuxi, Changzhou, Suzhou, Nantong, Yancheng, Yangzhou, Zhenjiang and Taizhou in Jiangsu Province, Hangzhou, Ningbo, Jiaxing, Huzhou, Shaoxing, Jinhua, Zhoushan and Taizhou in Zhejiang Province, Hefei, Wuhu, Maanshan, Tongling, Anqing, Chuzhou, Chizhou and Xuancheng in Anhui Province, and Shanghai, the municipality directly under the Central Government. Then, we collect different indicators of the economy and environment to construct the evaluation system of ED and EE. The grey correlation model is used to measure the correlation degree between different indicators and subsystems, and the coupling coordination model is used to measure the coordination degree between economic development and ecological environment of urban agglomeration as a whole and at the provincial and municipal levels. Based on the empirical results, we put forward corresponding measures for the coordinated development of the economy and environment in the YUA and to improve the quality of urbanization development from the perspective of urban agglomeration as a whole and single city.This paper is divided into five parts. The first part is the introduction; the second part is literature review; the third part introduces the research data and research methods; the fourth part measures the correlation between each index and the system; the fifth part analyzes the coordinated development level of provinces, cities and urban agglomerations from the aspects of development index, coupling degree and coordination degree, and further discusses the factors affecting the economy and environment. The sixth part summarizes the conclusions of this paper and puts forward some policy recommendations.Urbanization has become a comprehensive problem of social development in contemporary China, which is a unique process . The imbInternational studies stress the sustainable development of economy and environment. In 1987, the World Commission on Environment and Development put forward the concept of sustainable development for the first time in its report “Our Common Future” and described a series of economic and environmental problems human being were faced with . Since tChinese scholars have discussed the correlation between ecological civilization and a circular economy and their construction path. Song Tao  explaineThe research methods of regional economic development and eco-environment mainly include the Grey Models , Data EnTo sum up, current researches on regional development level mainly focus on provincial and municipal administrative regions, and less attention has been paid to urban agglomerations. In the limited studies on urban agglomerations, most of them only carried out data calculation and elaboration, less analysis from the “agglomeration” aspect. Therefore, by using the grey relational model and coupling coordination degree model, the paper has determined the coupling coordination correlation between the ED and EE of YUA and its spatial and temporal evolution law.By referring to existing research results ,37, 10 iConsidering the difference of original data in type and magnitude, the data were processed to be compared with different years and regions. Firstly, the original data were processed by range standardization, and the case was avoided when the base was 0 in the calculation of entropy by logarithm. The standardized data were uniformly multiplied by 0.99 and then added by 0.01. The calculation formulas are as follows:Calculate the proportion of the j-th indicator in the i-th yearCalculate the information entropy value of the j-th indicatorCalculate the difference coefficient of the j-th indicatorCalculate the weight of the j-th indicatorEstablish the comprehensive development index of ED and EE subsystem in the i-th yearBased on the grey system theory and by establishing the grey relational model, the paper has calculated the correlation coefficient ξ_ and relational degree R_ and obtained the grey relational degree between the subsystem and evaluation indicators in the two systems, so as to determine the relational degree and coupling effect of each dimension of the subsystem of the former system and each evaluation indicator with those of the other system.The coupling degree indicates the degree of interaction between multiple systems, and the coordination degree indicates the size of the benign relationship in these interactions. Based on this, this paper constructs the coupling coordination degree model of the economic development and ecological environment system:When n = 2,1 and U2 represent the comprehensive development index of ED subsystem and EE subsystem, respectively; α and β refer to undetermined coefficients, which represent the contribution degree of ED and EE to the whole system, respectively. On the basis of consulting experts’ opinions and drawing on relevant research results, considering that their contributions are equal to each other, α = β = 0.5 is taken.T represents the comprehensive evaluation function; D represents the coupling degree and coordination between two subsystems; UThe paper has referred to the classification standard of coupling coordination degree in existing studies ,39 to clBased on the grey relational degree model, the relational degree between the indicators and subsystems of the ED system and the EE system of the YUA in 2019 have been calculated and listed in In In sequence two, the relational degree of the discharge of industrial wastewater, industrial smoke and dust emissions and industrial sulfur dioxide emissions are the top 3 indicators, indicating that the degree of industrial pollutant emissions has a great influence on urban ED in the YUA. In some cities of the YUA, heavy industries with high pollution have contributed a lot to economic growth, while some cities may face short-term industrial vacancy and economic downturn due to industrial upgrading.Based on the calculation of the relational degree of each indicator, the sub-systems are calculated, respectively, and the relational degree and the grades of ED and EE subsystems of the YUA in 2019 have been obtained, as shown in Horizontally, EE level > EE pressure > EE protection, and the average relational degree of EE level is the highest, which is 0.6718. Vertically, the quality of ED > the scale of ED > ED potential, but there is not much difference among them. Therefore, the future development direction of the YUA is still to ensure the quality of economic development, improve the level of ecological environment and achieve high-quality development.In terms of the relational degree between the subsystems, it is concluded that: ① The relational degree between ED scale and EE level is high, which is 0.6782. This is because the YUA belongs to one of the largest economic clusters in China, which needs a corresponding EE for its ED. ② The relational degree between ED potential and EE pressure is high, which is 0.6652. This is the case for the direct relation between the discharge of industrial pollution and the industrial structure. When the urban industrial structure is adjusted and upgraded, extensive enterprises are gradually eliminated and transferred, and the ecological pressure decreases. The construction of emerging industries has improved the development potential of the city. The construction of new industries will promote the ED potential of the city. ③ The relational degree between the quality of ED and EE level is high, which is 0.7156. This is because the quality of ED is mainly reflected in the per capital indicator. When the urban economic level is improved and the construction of ecological space is enhanced, the corresponding per capital EE level will also be improved.Based on Equation (8), the ED index and EE index of the 26 cities were determined, and the results of 2019 were selected to specifically analyze the development level and the types of economy and environment in each city, as shown in (1) EE lagging type. Shanghai is an example of this type. As the central city of the YUA, its ED level is much higher than that of most cities, becoming one of the objective reasons for its leading in ED index and lagging in EE. Although Shanghai has a relatively high EE index comparing with other cities, this index has not been coordinated with the ED. In future development, the construction of EE should be enhanced to coordinate it with the ED level.(2) Balanced development type. The examples are Nanjing, Suzhou, Hangzhou, Ningbo, Jiaxing, Jinhua, Zhoushan and Hefei. These cities can be divided into two categories. One is with balanced development at a high level, such as Nanjing, Suzhou, Hangzhou, Ningbo and Hefei. The GDP of these cities has reached or surpassed a trillion. Meanwhile, as the representative cities in the agglomeration, city managers have been actively responding to the call of the state to promote the improvement of urban ecological level. For instance, Suzhou put forward the urbanization development path with the core concept of improving urban quality. The other category is coordinated development at a medium level, such as Jiaxing, Jinhua and Zhoushan, which all belong to Zhejiang Province. Restricted by geographical location and starting time, the ED level of these cities is relatively low. Affected by the radiation effect of central cities, however, these cities can positively embrace industrial transformation, learn from developed cities and thus have great development potential.(3) ED lagging type. All the cities other than the above two types belong to this type, among which Wuxi, Changzhou, Nantong, Yancheng, Yangzhou, Zhenjiang, Taizhou, Huzhou, Shaoxing, Taizhou and Wuhu have a relatively high ED level, while Maanshan, Tongling, Anqing, Chuzhou, Chizhou and Xuancheng have relatively low ED. Most of the former cities belong to China’s major economic provinces—Jiangsu Province and Zhejiang Province. After the ED has reached a certain level, economy has in turn contributed to and improved the EE level in these cities. The latter cities belong to Anhui Province. As the interior region of the YUA and due to the siphonic effect of the developed cities along the eastern coast, resources, such as capital, labor and high-end enterprises, in these cities are relatively scarce, and the ED level is relatively low in these cities.Based on Equation (12), the coupling degrees of the 26 cities of the YUA from 2009 to 2019 were determined, and the results have shown that the coupling degree C was concentrated on , all of which were in the high-level coupling interval. A total of 271 of the 286 C values were greater than 0.9, indicating that the interaction degree between the economy and environment in the 26 cities was extremely high and stable. From 2009 to 2019, the coupling degree was at a high level with an upward trend, suggesting that the coupling was virtuous and developing in a coordinated trend. In future urbanization, when the coupling degree of the two systems is gradually increasing, approaching or equaling one, a virtuous coupling between the economy and environment in the 26 cities will be achieved.The coupling coordination degree of the ED and EE of the 26 cities in the YUA from 2009 to 2019 were calculated by coupling coordination degree model , and theIn In general, the coupling coordination degree between the ED and EE of the YUA had an upward trend from 2009 to 2019, while some of the cities had some backwards. In 2009, the cities that were barely coordinated accounted for 54% of the total, and other types of cities were scattered. In 2019, cities that were barely and primarily coordinated accounted for 69% of the total, and there were no cities with imbalance and decline. Spatially, cities in the eastern and central areas had higher coupling coordination degrees than those in western, northern and southern areas, with significant spatial heterogeneity.Specifically, ① High-quality coordination has not yet appeared, showing that the coordination between the ED and EE of cities in the YUA has not yet reached an optimum degree, and the coordination mode of promoting environmental protection by economic development and promoting economic development with high-quality ecology has not yet been fully achieved. ② Coordinated development type: only Shanghai, Nanjing, Wuxi, Suzhou, Hangzhou and Ningbo had coordinated development in all the past 11 years, among which Shanghai is way ahead in the coordination score and has maintained a coordinated development. In the YUA, cities that belong to this type mainly are distributed in the central and eastern coastal areas because of their superior geographical location, early starting time and rapid development. In addition, when the economical level in these cities reaches a certain level, it in turn contributes to the eco-environment. Therefore, the ED and EE in these cities had always maintained a high level and their comprehensive development score is higher than that of other cities. ③ Cities that belong to the type from transitional development to coordinated development include Changzhou, Nantong, Yangzhou, Zhenjiang, Jiaxing, Huzhou, Shaoxing, Jinhua, Taizhou, Hefei, Wuhu, Ma’anshan and Tongling, accounting for 50% of the total. These cities are in different transitional stages. Only a few years of development in Changzhou, Nantong and Hefei belong to the transitional development type, and coordinated development will be achieved in these cities in the near future. However, Jiaxing, Taizhou, Wuhu, Tongling and other cities have only a few or no years of coordinated development, showing that although these cities have implemented corresponding strategies, they started late and no significant effects has been made yet. ④ Cities that belong to the type of transition from imbalance and decline to transitional development include Yancheng, Taizhou, Zhoushan, Anqing, Chuzhou, Chizhou and Xuancheng, among which Zhoushan belonged to the imbalance and decline only in 2013, and Chuzhou was only in the transitional stage in 2018 and 2019. The number of cities that belongs to this type is shrinking, and they are gradually gathering in Anhui Province, showing that some cities in Anhui Province have undertaken industrial transfer from Jiangsu, Zhejiang and Shanghai to strengthen their own economic development in the previous period, but they have also suffered from high pollution and high energy consumption brought by these transferred industries. ⑤ The moderate, serious and extreme imbalance types have disappeared, indicating that the YUA has made certain achievements in ED and EE protection.Based on the processing of data from cities, the weighted average values  have been obtained and used as the data of provincial and urban agglomerations to study the development and change of the coordination degree between the ED and EE of the YUA and provinces (only the cities in the YUA included) .In The coordination degree in Jiangsu Province and Zhejiang Province is close to the average level of the YUA. Jiangsu is slightly higher than the average level and Zhejiang is slightly lower, indicating that certain achievements in the ED and EE have been made in the two provinces. In 2019, in Jiangsu and Zhejiang, except Zhoushan, belonged to the top 100 cities in China, and the scale of Zhoushan’s ED was mainly limited by its natural conditions. At the time of achieving rapid economic growth, Jiangsu took the lead in formulating the policy of “priority to environmental protection” in China, which focuses on giving full play to the internal adjustment role of economic means while strengthening the necessary administrative means for external constraints. It stresses the internal adjustment of economic means and formulates and implements a series of environmental and economic policies. Jiangsu has also issued an action plan for the construction of ecological civilization and put forward six major actions, such as energy conservation and emission reduction, green growth, living environment with clear water and blue sky, green construction in Jiangsu, ecological protection and construction and the establishment of ecological demonstration. Based on the idea of sustainable development, Zhejiang focuses on promoting pollution reduction and intensive land use; it strengthens technological progress, management innovation, expansion in the space of resource and environment; and promotes the orderly construction of EE in the province from pollution reduction, environmental remediation, ecological construction and other fields.Anhui Province has the lowest coordination level in the YUA, which accords with its development status in the agglomeration. Located far from the sea and affected by the siphonic effect on eastern developed cities, Anhui has a relatively low ED level. The industries in Anqing and other cities are mainly petrochemical and plastic industries, the development of which came at the expense of the environment, resulting in the low levels of EE. Meanwhile, as the main intake areas of industrial upgrading and transfer from the Yangtze River Delta, Anhui is faced with a difficult choice between ED and EE protection.From the time dimension of the coordination degree of the three provinces, one city and urban agglomeration, the variation of their development generally showed an upward trend, but it fluctuated greatly in 2013 and 2014. In November 2012, the Chinese government formulated the strategic goal of promoting the five-sphere integrated plan in a new era, in which the construction of ecological civilization was raised to a higher level. In terms of economic development, we should establish an environment-friendly industry system, promote environment-friendly urbanization and form an environment-friendly production and consumption mode. In response to the call for ecological civilization, the YUA accelerated its industrial transformation and upgrading, and while vigorously developing high-end manufacturing industries and digital economy, the transfer of extensive industries was carried out in the region. Although the economic development had been negatively impacted by industrial transfer in a short time, the development of ecological economy will be conducive to the sustainable development of cities in the long-term perspective.In By establishing the evaluation system of ED and EE, the paper has used the grey relational model to determine the relational degree between the evaluation indicators of two systems and subsystems and analyzed the degree of the influence and correlation of these indicators. This paper uses the coupling coordination degree model to calculate the ED index, EE index, comprehensive development index and coupling coordination degree of the 26 cities in the YUA from 2009 to 2019. Our research found that since 2009, the coordination between the ED and EE of the YUA has experienced a stable growth period, which is closely related to the macro social background and relevant national policies.There is still a gap between the economic and environmental development level of the 26 cities in the Yangtze River Delta urban agglomeration, and the imbalance in spatial distribution is serious. Under the background of implementing the regional integration and high-quality development strategy in the Yangtze River Delta, the coordinated development of cities should be designed from the following aspects: (1) Cities that belong to the ED lagging type should subdivide regional industries and strengthen urban cooperation. Meanwhile, they should take advantage of “The Belt and Road Initiative”, their location and openness and achieve high-quality and rapid economic growth. (2) Shanghai, as a city with lagging EE, should give full play to its leading role as a central city and drive the common development of its neighboring cities. Meanwhile, it should also strengthen the construction of the EE to coordinate with its ED. (3) For the balanced low-level cities, they should carry out differentiated urbanization positioning and choose the path that best suit themselves, so as to realize the rapid urban development. Meanwhile, the coordination between the economy and environment should also be prioritized to realize a win-win between growth rate and development quality. For the balanced and high-level cities, since there is still much room for their improvement, they should strive to achieve a higher level of balanced development on the premise of maintaining the current path of development.The YUA is one of the six major urban agglomerations of the world, which takes lead in the high-quality coordinated development of the economy and environment in China. However, there is still a long way for its development level. Based on current economic condition, the YUA should use the advantages of complementary resources and spatial proximity, and the cities in the agglomeration should clarify their respective tasks and rely on and complement each other to establish a sustainable urban agglomeration system with global competitiveness.The results of the determination and theoretical analysis will complement and improve the studies on cities and urban agglomerations, which will be beneficial to dealing with the contradiction between the economy and environment in the urbanization, promoting the integrated and high-quality development of urban agglomerations, and providing practical data analysis for the government and urban managers to adjust urban development strategy. Nevertheless, the paper has only explored the efficiency and quality of urban development from the aspects of the coupling coordination degree and relational degree between economic development and EE. More dimension shall be introduced to the analysis and the determination of the development process and the quality of the cities in the trend of diversified urban development.


The aim of this study was to conduct a genome-wide comparative analysis of four indigenous Chinese duck breeds  from Fujian Province, to understand their genetic diversity and population structure. Population parameters showed that the four indigenous breeds were separated groups. Five genomic regions are presented as hotspots of autozygosity among these indigenous duck breeds, with candidate genes involved in muscle growth, pigmentation, and neuroregulation. Genomic information may play a vital role in the improvement of conservation strategies.The assessment of population genetic structure is the basis for understanding the genetic information of indigenous breeds and is important for the protection and management of indigenous breeds. However, the population genetic differentiation of many local breeds still remains unclear. Here, we performed a genome-wide comparative analysis of Jinding, Liancheng white, Putian black, and Shanma ducks based on the genomic sequences using RAD sequencing to understand their population structure and genetic diversity. The population parameters showed that there were obvious genetic differences among the four indigenous breeds, which were separated groups. Among them, Liancheng white and Shanma ducks may come from the same ancestor because the phylogenetic tree forms three tree trunks. In addition, during the runs of homozygosity (ROH), we found that the average inbreeding coefficient of Liancheng white and Putian black ducks was the lowest and the highest, respectively. Five genomic regions were considered to be the hotspots of autozygosity among these indigenous duck breeds, and the candidate genes involved a variety of potential variations, such as muscle growth, pigmentation, and neuroregulation. These findings provide insights into the further improvement and conservation of Fujian duck breeds. Indigenous duck breeds are an important part of livestock genetic diversity, with rich genetic diversity and breeding potential, and are the basis for breed improvement and the development of new production models . In the Indigenous ducks have a long history of domestication in China, dating back to 2228 years ago, but their origin has been controversial. A recent report indicated that mallards and Chinese spot-billed ducks were not the pioneers of domestic ducks. They may have come from a ghost wild duck population that was undefined tens of thousands of years ago , which wIn the process of domestication, human purposeful selection and breeding constantly affect the phenotype of indigenous ducks. Domestic and mallard ducks have greatly different skeletal systems . JianchaFujian Province is located in southeastern China, adjacent to the Taiwan Strait in the east, and belongs to the subtropics. The complex and diverse geographical and ecological conditions in this province have given birth to a wealth of indigenous duck breeds. To explore the population structure and genetic diversity of these indigenous ducks, we selected four representative breeds . LiancheThe purpose of this study is to understand the population structure and genetic diversity of Chinese indigenous duck breeds. Here, we described the genetic relationship among four indigenous duck populations in Fujian by principal component, structure, and phylogenetic tree analyses. Run of homozygosity (ROH) is an extension of the above work, which is used to judge valuable genomic information in inbreeding. Our findings can be used to better understand the structural characteristics of the genome among indigenous duck breeds in Fujian Province and to reveal potential selection signs in ROH islands, which is helpful for geneticists and breeders to put forward better conservation strategies and improvement schemes in the future.A total of 120 blood samples  were collected in this study. All ducks were raised on a conservation farm at the National Institute of Waterfowl Gene Bank  and have no shared ancestor for three generations, covering almost all the existing genetic relationships of each breed. Genomic DNA was isolated from all blood samples using the Blood Genomic DNA Extraction Kit  according to the manufacturer’s instructions. Then, DNA concentration and integrity were detected by using a microplate spectrophotometer  and 1% agarose gel electrophoresis. To avoid the oxidation of duck genomic DNA, it was stored in a −20 °C refrigerator for subsequent reduced-representation sequencing.RAD-seq libraries were constructed following a protocol modified from Baird . BrieflyAnas platyrhynchos genome (GCF_003850225.1) with the settings “mem 4-k32-M,” where -k is the minimum seed length and -M is an option used to mark shorter split alignment hits as secondary alignments [Quality trimming is an essential step to generating high confidence in variant calling. Raw reads would be processed to obtain high-quality clean reads using fastp  accordinignments . Variantignments . SNPs we2) between two markers in the sample genome were counted, then the LD coefficients were classified according to the distance between markers, and finally, the average r2 values in the 200 kb interval were calculated. The r2 values of these different intervals were used for linear fitting on R software.According to the SNP information, we first constructed a distance matrix to represent the evolutionary distance between every two breeds. Then, we cluster-analyzed the samples and inferred the genetic relationship between populations by constantly merging the two nodes with the smallest distance. We used MEGA-X software and neighbor-joining (NJ) methods to construct the phylogenetic tree . PrincipROH is a long and continuous homozygous extension in the genome, which is composed of two identical haplotypes in individuals. The SNP data of 120 samples were merged, and quality control was carried out by PLINK software . The folROH). The percentage of SNP residing within an ROH was estimated by counting the number of times that each SNP appeared in an ROH and by dividing that number by the total number of animals (120). The SNP region above 30% was selected as the high homozygous region, also called ROH island, and the RCircos package was used to map the ROH distribution on the chromosomes of four indigenous duck populations. To know whether each annotated gene has a biological function, the DAVID database was used to analyze the GO function  and KEGG pathway enrichment of the annotated genes in the ROH island. A comprehensive investigation was carried out according to NCBI and GeneCards websites and existing literature.The physical length and number of ROH in each population and the total length of each ROH were calculated by adding the ROH value of the individual. R software was used to draw the ROH statistical chart according to breed classification. The length of the genome covered by ROH was divided by the total duck autosomal genome length covered by the SNP array to estimate individual genome inbreeding coefficients  error rate. Our CV error results showed that the optimal number of clusters = 3 . The anaTo explore the genetic background of four indigenous duck breeds, PCA was carried out based on genome-wide SNP data. The results showed B that PCThe phylogenetic tree is very important for understanding the genetic relationship of the population. We used the Kimura two-parameter model to repeat sampling 1000 times to form a more reliable phylogenetic tree. It gathers the samples with high sequence similarity together to obtain the NJ tree. The bootstrap values of the NJ tree topology are all above 75%, indicating that the phylogenetic tree we constructed has high credibility. The results showed  that all2 as the LD coefficient to measure the degree of linkage between loci. The LD linear fitting results  in JD, 1853 ROH (34.49%) in LC, 788 ROH (14.67%) in PT, and 981 ROH (18.26%) in SM. The number and total length of ROH in the four groups of ducks are shown in ROH = 0.14), followed by JD (FROH = 0.13), SM (FROH = 0.08), and PT (FROH = 0.06). At the individual level, the animal with the highest genomic inbreeding coefficient appeared in the JD population (ROHmax = 0.191), and that with the lowest genomic inbreeding coefficient appeared in the SM population (ROHmin = 0.027). The above results suggest that JD and LC may have artificially directed inbreeding.ROH data were used to evaluate the average inbreeding coefficient of different duck populations B. LC hadNothnagel et al. first defined the genomic regions associated with inbreeding as ROH islands, that is, overlapping homozygosity regions are highly shared among individuals belonging to the same population . To idenThe assessment of population genetic structure and diversity is the basis for understanding the genetic information of indigenous breeds, and it is important for the protection and management of local breeds . In receIn this study, we sequenced 120 ducks. Structure analysis, PCA, and phylogenetic tree revealed the population structure of four indigenous duck breeds in Fujian Province. The results were basically consistent with our expectations. Structure and PCA analysis clearly divided them into four groups, and the phylogenetic tree also formed four subbranches, indicating that these breeds had obviously differentiated. In addition to the long history of breeding, the reason for differentiation may also be attributed to geographical isolation. Although the main producing areas of these indigenous breeds are relatively close on the map, Fujian Province has complex topography, with many hills, mountains, and rivers. SM and PT gathered close to each other on the PCA map and mixed each other’s pedigree in the structural analysis, indicating that there was a close relationship between them. In addition, we constructed the evolutionary trees of these four indigenous duck breeds and tried to infer the phylogenetic relationship between them. The results showed that the two breeds belong to the same big branch, different from the previous research results . SM and The differences in LD in the current study may be attributed to different selection and evolutionary forces in the process of variety formation . The resROH) based on ROH and indicated that high FROH usually represents inbreeding [ROH analysis has become a standard method for studying inbreeding and detecting the selection characteristics of animal populations . McQuillbreeding . ROH anabreeding ,30. In gbreeding . In thisGNAS connects to the Gap junction pathway, which encodes Gsα, XLαs, NESP55, and A/B protein. It has been identified as a candidate gene related to skeletal muscle growth and development in Chinese native pig breeds [GNAS is an important regulatory gene of pigment cells. EDN3 is a gene that encodes endothelins (EDNs), which participate in the regulation of some physiological processes, such as cardiovascular development and function, pigmentation, and plumage in birds [EDN3–EDNRB2 signals, which are closely related to melanin deposition in duck epidermis [GNAS and EDN3 genes were included by the European Society for Pigment Cell Research , suggesting that they may play an important role in coat color formation in indigenous ducks. Similar to the former, the VAPB gene also regulates the skin color of birds [ST methods to mine the genes (EDN3 and VAPB) that are essential for the development of melanocytes [SLITRK1 gene is preferentially located in the excitatory synapse of hippocampal neurons. It has the potential to promote presynaptic differentiation of excitatory and inhibitory synapses [SLITRK6 gene is related to the neural regulation of vision and hearing and plays an important role in the development of normal hearing and vision [p < 0.05), which may imply that the important traits such as growth, development, and appearance color of these ducks have endured strong artificial selection. Such gene variation events have different selectivity in different breeding practices, which may be beneficial to heterosis.The length and quantity of ROH can infer the historical information of varieties at the individual level . Howeverg breeds , and it g breeds . Imumorig breeds . In addiin birds . Embryonpidermis  and featpidermis , consistpidermis . Coincidpidermis . GNAS anof birds . Hou et anocytes . These rsynapses . The SLId vision . The enrIn this study, the population structure and genetic diversity of four indigenous duck breeds in Fujian Province were analyzed in detail from the whole genome perspective. The characteristics of these breeds between and within populations were evaluated by using genomic data through a variety of methods. Our comprehensive analysis showed that the four breeds are all independent populations, and muscle growth and pigment deposition are the variation direction of artificial selection at present. Therefore, the population structure and candidate genes described here may be used to clarify the differentiation of Fujian indigenous ducks and to improve their breeding. Our findings will help to better manage these unique genetic resources and improve mating management, which is essential for protecting genetic diversity and promoting the development of indigenous breeds.


Ancient human DNA (aDNA) extracted from archaeological contexts allows reconstructing past population movements. Previous methods work by calculating proportions of shared ancestry among individuals or groups in order to answer specific, regional research questions. Here, we propose a large-scale algorithm to quantify human mobility through time and space using bulk aDNA data. The algorithm has two core components: i) interpolation of the spatiotemporal distribution of genetic ancestry to obtain a continuous ancestry information field and ii) probabilistic estimation of a spatial genetic similarity surface for each input sample by projecting its ancestry profile into this field. We apply this to thousands of published genomic samples in the last 10,000 y to trace diachronic mobility patterns in Western Eurasia. The recent increase in openly available ancient human DNA samples allows for large-scale meta-analysis applications. Trans-generational past human mobility is one of the key aspects that ancient genomics can contribute to since changes in genetic ancestry—unlike cultural changes seen in the archaeological record—necessarily reflect movements of people. Here, we present an algorithm for spatiotemporal mapping of genetic profiles, which allow for direct estimates of past human mobility from large ancient genomic datasets. The key idea of the method is to derive a spatial probability surface of genetic similarity for each individual in its respective past. This is achieved by first creating an interpolated ancestry field through space and time based on multivariate statistics and Gaussian process regression and then using this field to map the ancient individuals into space according to their genetic profile. We apply this algorithm to a dataset of 3138 aDNA samples with genome-wide data from Western Eurasia in the last 10,000 y. Finally, we condense this sample-wise record with a simple summary statistic into a diachronic measure of mobility for subregions in Western, Central, and Southern Europe. For regions and periods with sufficient data coverage, our similarity surfaces and mobility estimates show general concordance with previous results and provide a meta-perspective of genetic changes and human mobility. All human behavior is spatial behavior, and spatial perception and interaction are deeply rooted in the human mind. Understanding movements in space—mobility—on different orders of magnitude is therefore a major component for understanding human behavior throughout history , from thAnthropological theory provides different concepts and categories to classify mobility. Mobility can be permanent or cyclical, a group property or individual behavior, and finally motivated by economic, social, or cultural incentives. It has complex implications for the formation, perception, and interaction of identity –4. MigraThe field of archaeogenetics now provides a perspective on mobility, which is at its very core influenced by population genetics theory. The emergence, change, and distribution of human ancestry components—mediated by the mobility of their hosts—are in fact some of its most important research questions  lifetime. We apply this algorithm to several thousand previously published ancient genomes from Western Eurasia dating from between 8000 BC and 2000 AD (excluding modern genomes) taken from the Allen Ancient DNA Resource (AADR) . And, weMethods). All samples in this public data collection reference single-nucleotide polymorphisms (SNPs) from a panel of about 1.24 million known informative positions . We decided to use MDS with two dimensions (MDS2) here and also present Projection-PCA with five dimensions (PCA5) in SI Appendix. For MDS2, we find the largest internal separation of samples to be along the tempocultural boundary between the Mesolithic and the Neolithic, highlighting the strong population shift the Neolithic introduced into Europe  on these data to reduce their dimensionality to two summarizing ancestry components , that aro Europe –27. OtheSI Appendix, Text 2). With the parameterized Gaussian process regression model, we predicted an average spatiotemporal genetic ancestry field across Western Eurasia. To illustrate the result, We modeled these two MDS-derived ancestry components individually as the dependent variable in a Gaussian process regression (GPR) model with three independent input variables describing the position of each sample in space and time. To learn the properties of the relevant covariance matrix (“kernel”) for a model with the best mean postdiction abilities, we explored multiple methods: variogram analysis, maximum likelihood estimation, and cross-validation. We eventually settled on an anisotropic kernel covering multiple hundred kilometers and years . The four “virtual” time-series again generally reflect our knowledge of the genetic changes in Europe: In the locations of present-day London and Rome, we observe an ancestry shift with the arrival of Neolithic and then once more with Steppe ancestry—with small regional differences. Riga, on the other hand, starts out with a higher degree of Eastern Hunter-Gatherer ancestry before skipping the influx of the Anatolian farmer component. Jerusalem, expectably, fills a markedly different spot on the genetic map.With this interpolation, we can attempt the reconstruction of continuous, local ancestry histories even for places without consistent data coverage. To illustrate this, we selected arbitrary spatial positions  and used the GPR model to postdict how the genetic profile in these locations changed through time : Each sample has a coordinate in the multidimensional MDS space, so one value for each output dimension. For a given point in the interpolated, spatiotemporal ancestry field, we can determine the likelihood that exactly this value emerges at that location. If the likelihood is high, so if the “similarity” to said field value is high, and the field point is in the respective past of the sample of interest, then we can deduce that this field point was a potential point of genetic ancestral origin for the sample . A key feature of this approach is that the likelihood will only be high where the field is sufficiently supported by data . We prepared such similarity probability maps for six samples from different times, regions, and contexts in We turn this likelihood of genetic similarity in a given time slice to a normalized probability distribution using Bayes’ formula and multiplying the resulting probabilities for the individual MDS components , this means that we infer a vector pointing from York to the hypothesized region in the Levant, resulting in a distance of several thousand kilometers and in south–western direction.SI Appendix, Fig. S10 and Text 5 feature two more regions, Southeastern Europe and the Western Pontic steppe). We mostly consider patterns emerging from long-distance signals, observed as individuals with large mobility-distances , as these tend to correspond to events described previously in the literature and thereby provide a proof-of-concept for our method. However, beyond these long-distance signals, we highlight a considerable level of complexity of smaller-scale signals that may harbor information yet to be explored. Shown along the individual distances is a moving average curve together with an error band (in gray shading), which may help putting the largest individual-based events into perspective. Alternative visualizations of the time series shown in SI Appendix, Figs. S14, S15 and S16, which show these data as a sequence of windrose plots, relative distance fractions, and a map series with all individual vectors.The results of this large-scale application are compiled in SI Appendix, Text. 5 and Figs. S12 and S13). We also ran the entire analysis for the Projection PCA setup with 5 output dimensions (PCA5) mentioned above .One core parameter for this analysis is the retrospection distance already introduced for the individual examples. Informed by the temporal lengthscale parameter of the GPR kernel function, we decided to set it to 667 y for the whole dataset but also explored lower and higher values . In this case, we can assume a cultural admixture barrier, which the interpolation cannot correctly resolve.Of course, though, this does not solve cases of entirely missing ancestry profiles , which simply can not be accurately represented and considered, as long as key samples are nonexistent. It also does not accurately capture situations of multiple coexisting ancestries living in close proximity in space and time. Interpolation will in such cases create an average ancestry profile which may not be meaningful and cause the incorrect assignment of similarity probabilities. We have shown the example of individual N22, who carries a genetic hunter-gatherer profile at a point in space and time, when other individuals in its vicinity feature an Anatolian farmer profile  V50.0 (released on 2021-10-10) (https://github.com/poseidon-framework). SI Appendix, Bibliography: AADR Dataset for a list of papers providing the individual samples. We included only ancient DNA samples and removed samples without spatial or temporal position information as well as samples outside of the defined research area (1-10-10)  and modi1-10-10)  and softrch area  and timeSI Appendix, Text 1 for more details on the SNP selection process.The dataset includes both samples whose DNA libraries have undergone in-solution enrichment capture as well as samples who have been sequenced evenly across the entire genome using the so-called shotgun approach. Each sample covers an individual subset of the 1240K SNP array . For quaAll radiocarbon dates in the archaeological context data were recalibrated with the R package Bchron  .Multidimensional scaling is a dimensionality reduction method that can be applied to genetic data to derive positions in a genetic–distance space for individual samples. Before running it on our dataset with ot v.1.9 , we remoot v.1.9 , 82. SI Gaussian process regression is an interpolation method for n-dimensional space. The term Gaussian process means that a set of observations is modeled as the outcome of a multivariate normal distribution. The method allows making predictions for a dependent variable based on the position in independent variable space . It is aA crucial step in the application of Gaussian process regression is the selection of a sensible covariance function (kernel) that effectively describes the degree and range of long-distance effect the model assumes for individual observations. We followed the default choice for an anisotropic Gaussian kernel implemented in the R package laGP v.1.5-7 . laGP prxk − x′k) as the distance between all observations x, x′ in the different dimensions k and the kernel size scaling factor θk for each dimension. η is the so-called nugget term to account for different observations of the dependent variable at the same position in independent variable space. The values of θk  and η have to be fixed, which is the second important decision necessary to define the covariance matrix. We applied multiple approaches  to estimate these parameters. SI Appendix, Text 2 for more details.with  coordinates at a certain point in space and time and we apply it to compute the relative spatial distribution of similarity probabilities in a given timeslice. Appendix 01 (PDF)Click here for additional data file.


Chrysophrys auratus) along ~2600 km of the Australian coastline, with a focus on Western Australia (WA). We used 10,903 filtered SNPs in 341 individuals from eight sampling locations to characterize population structure and connectivity in snapper across WA and to assess if current spatial scales of stock assessment and management agree with evidence from population genomics. Our dataset also enabled us to investigate temporal stability in population structure as well as connectivity between WA and its nearest, eastern jurisdictional neighbour. As expected for a species influenced by the extensive ocean boundary current in the region, low genetic differentiation and high connectivity were uncovered across WA. However, we did detect strong isolation by distance and genetic discontinuities in the mid‐west and south‐east. The discontinuities correlate with boundaries between biogeographic regions, influenced by on‐shelf oceanography, and the sites of important spawning aggregations. We also detected temporal instability in genetic structure at one of our sites, possibly due to interannual variability in recruitment in adjacent regions. Our results partly contrast with the current spatial management of snapper in WA, indicating the likely benefits of a review. This study supports the value of population genomic surveys in informing the management of weakly structured and wide‐ranging marine fishery resources.The efficacy of fisheries management strategies depends on stock assessment and management actions being carried out at appropriate spatial scales. This requires understanding of spatial and temporal population structure and connectivity, which is challenging in weakly structured and highly connected marine populations. We carried out a population genomics study of the heavily exploited snapper ( Advances in DNA sequencing technologies have increased the value of DNA‐based methods in stock delineation studies, and it is now economical to generate large datasets of 1000 s of DNA markers (i.e. those used in genomic studies), vastly contrasting with previously utilized datasets of 10 s of markers (i.e. those used in microsatellite studies). Large datasets of DNA markers have greater resolving power to uncover the often subtle patterns of population structure and connectivity characteristic of marine species , a large, long‐lived demersal sparid distributed in subtropical and temperate coastal waters of Australia and New Zealand . Given the species’ life‐history traits and the oceanographic setting of WA's coast, we predict population differentiation in snapper to be influenced by broad patterns of on‐shelf oceanographic circulation. Our secondary goal is to determine whether current spatial scales of assessment and management reflect the biological units (i.e. stocks) identified with genomics, as well as their spatial boundaries. Our third goal is to demonstrate to fisheries scientists and managers the value of genomic datasets in clarifying stock structure and connectivity in a species for which this was previously difficult .22.1Muscle or fin‐clip samples were obtained from 290 snapper from eight locations between the Gascoyne, on the central west coast of Western Australia (WA), and Ceduna, on the west coast of South Australia  and in Cockburn Sound (n = 30) in 2010 and 2014, respectively, to investigate the temporal stability of trends in population structure. Although the time periods covered preclude investigation across multiple generations, they are adequate for assessing interpopulation migration and population range shifts as a result of temporal variation in recruitment or population density (information important in fisheries management). The Cockburn Sound samples were collected by DPIRD WA staff as part of a fisheries independent survey, while the Esperance samples were collected by DPIRD WA staff from commercial catch for a former population genetics project , expected heterozygosity (HE) and per cent polymorphic loci (%PL), were calculated with the populations module of STACKS 2  method using the p.adjust function in the R package BASE 4.0.3  with a Mantel test (9999 permutations) in GENALEX 6.5 . Mean effective dispersal distance was then estimated from the slope of the IBD relationship using the theoretical model of Kinlan and Gaines  and population density  across the sampling range by assessing the relationship between coastal distance and linearized d Gaines , an exted Gaines : mean diRousset, .2.7K of 2 .We tested for putative barriers to dispersal using the piecewise regression approach implemented in Robinet et al.  to ident2.8FST  occurs in at least one distance class  ranged from 0.182 to 0.188 and observed heterozygosity (HO) ranged from 0.180 to 0.189. Values of the population‐specific inbreeding coefficient (FIS) were close to zero for all sites (range: 0.005–0.03) and none deviated significantly from expectation.Levels of genetic diversity were very similar across sites Table . ExpecteFST) between pairs of sampled sites was nil to low and ranged from 0 to 0.011, with CED being the most differentiated sample  and the west‐coast of SA (CED) was 0.0041 .Genetic differentiation , south‐west  and south‐coast . These clusters loosely corresponded to the samples between GAS and ALB  and the South Australia (SA) sample .The AMOVA indicated that 0.43%, 0.07% and 97.3% of the genetic variation in the dataset occurred between the three groups , among samples within groups and within samples (i.e. the eight samples corresponding to sampling locations), respectively. For this analysis, ESP was allocated to the south‐coast group since the lowest p‐value < 0.0005) and lower membership to the mid‐west and south‐west groups .Comparing the two temporal CS and ESP samples, membership to the three groups identified with ADMIXTURE indicated temporal stability in genetic structure at the former location only Figure . Compare3.3r = 0.86, p‐value <0.001; Figure FST, accounting for a substantial amount of the population genetic differentiation inferred across the sampling range. The mean effective dispersal distance per generation was estimated as 400 km from an IBD slope of 4E‐06 (i.e. FST = 0.004 per 1000 km). This suggests that demographic connectivity between locations separated by distances greater than 400 km may be limited. Our estimate of 400 km is within the range of those made for other marine fish , the piecewise regression model was a significantly better fit to the data . These results suggest that the genetic structure observed along the WA coast is not merely due to IBD but is also a reflection of a connectivity barrier, an interpretation consistent with the results of the clustering analyses.The piecewise regression analysis identified a significant breakpoint (i.e. where gene flow is lower than would be expected under IBD) in the ancestry gradient between CS and LAN, despite these sites being separated by only ~150 km  are characterized by weak genetic structure, we found evidence for stock discontinuities, dispersal limits and local‐scale structure. Our results improve upon prior understanding of population structure and connectivity in snapper across its WA range based on tagging  was detected between the central west‐coast of WA and the west‐coast of South Australia (SA), indicating that dispersal is limited by coastal distance and probably primarily occurs in a stepping‐stone fashion. Previous work with microsatellite markers and otolith microchemistry also uncovered IBD in snapper across WA  and the SA gulfs (Spencer Gulf and Gulf St Vincent) – and therefore may indicate the importance of these spawning areas in maintaining spatially proximate snapper stocks. The discontinuities identified here delineate three broad‐scale snapper stocks  delineated from patterns of species distributions and environmental features , the percentage of larvae released during summer in the two SA gulfs that did not reach the boundary current ranged from 70% to 100% . It is likely that this westward dispersal occurs post‐recruitment, since thermal fronts form at the entrances of the SA gulfs during the spawning season, largely preventing gulf‐shelf exchanges . In contrast, in the south‐west, we detected a pattern of spatial autocorrelation consistent with IBD, potentially facilitated by a weak LC during snapper's spring/summer spawning period in the region and the location of important spawning sites (i.e. protected embayments). Positive spatial autocorrelation occurred at distances up to ~300 km, suggesting that demographic connectivity between our sites on the western and southern coastlines of the region is probably limited and may occur in a stepping‐stone fashion. King George Sound in Albany is an important spawning area for snapper along the south coast of WA , three snapper stocks are currently recognized for assessment and management: the Shark Bay Oceanic (comprising Gascoyne), West Coast  and South Coast stocks . Simulation work by Spies et al.  showed tAlong the south coast of WA, the region between the south‐west corner and the SA border (i.e. the south‐coast stock) is assessed and managed as a single unit (Newman et al., 5The fluidity of the marine environment, along with the highly mobile and abundant nature of the species which occupy it, makes the characterization of evolutionary and demographic patterns in marine organisms difficult. Our study highlights the utility of large datasets of genetic markers in improving the understanding of spatial population structure and connectivity in marine species with high dispersal potential. Our findings likely relate to variation in physical factors, such as local ocean circulation and coastal geomorphology, as well as in biological factors, including timing of reproduction, spawning site preferences, recruitment variability and migratory behaviour. Overall, our study demonstrates the value of population genomics in helping to improve the spatial management of fishery resources and therefore their long‐term sustainability. Additionally, our work adds to the extensive body of literature showing that marine species are often characterized by complex population structure, rather than panmixia, and that population structure is not always static across time.The authors declare no conflict of interest.Appendix S1Click here for additional data file.


Anser cygnoides) and analyze the adaptation of fat storage capacity in the goose liver during the evolution of Anatidae. Genomic resequencing of 994 geese is used to investigate the genetic relationships of geese, which supports the dual origin of geese (Anser cygnoides and Anser anser). Chinese indigenous geese show higher genetic diversity than European geese, and a scientific conservation program can be established to preserve genetic variation for each breed. We also find that a 14-bp insertion in endothelin receptor B subtype 2 (EDNRB2) that determines the white plumage of Chinese domestic geese is a natural mutation, and the linkaged alleles rapidly increase in frequency as a result of genetic hitchhiking, leading to the formation of completely different haplotypes of white geese under strong artificial selection. These genomic resources and our findings will facilitate marker-assisted breeding of geese and provide a foundation for further research on geese genetics and evolution.Geese are herbivorous birds that play an essential role in the agricultural economy. We construct the chromosome-level genome of a Chinese indigenous goose (the Xingguo gray goose, XGG;  A chromosome-level genome assembly of the Xingguo gray goose enables deeper insight into Chinese indigenous geese genetic origins and evolution. Under the influences of diverse economic cultures and geographical structures, 30 Chinese indigenous geese breeds with different phenotypic features and production performance have gradually been formed2. The genome assemblies of three domestic geese have been recently completed, but only the hybrid Tianfu goose (TFG) was assembled to the chromosome level3. Chinese indigenous geese (the Sichuan white goose [SCW] and the Zhedong white goose [ZDW]) assemblies are still at the scaffold level5. The lack of high-quality genomes of Chinese geese restricts their molecular genetic research and breeding practice. Recently, many studies combining genome assemblies and comparative genomics have explored the genetic evolution of birds7. However, the genetic characteristics of domestic geese in the Anatidae remain relatively unknown.The domestic goose is one of the most economically important agricultural animals, as it can provide nutritious meat, eggs, and fatty liver. The geese bones from Tianluoshan in the lower Yangtze River showed that Chinese geese were domesticated more than 7,000 years agoAnser cygnoides, ACy), while European geese  descended from the greylag goose 8. Southern China is an advantageous production area for geese breeding due to its plump float grass (Cyperaceae). The Xingguo gray goose (XGG), Fengcheng gray goose (FCG), Guangfeng white goose (GFW), and Lianhua white goose (LHW) in Jiangxi Province as well as a Hunan breed (the Lingxian white goose [LXW]) are widely distributed in Jiangxi Province  descended from the swan goose  and the haplotype differences of tyrosinase (TYR) may be related to the white feather trait of ZDW14. Xi et al. identified a 14-bp insertion in exon 3 of endothelin receptor B subtype 2 (EDNRB2) gene that was associated with white plumage in Gang geese15. Wen et al. suggested that an 18-bp deletion in the intron of the KIT proto-oncogene, receptor tyrosine kinase (KIT) gene influenced the white feather phenotype of Chinese geese16. Despite extensive research on the white feathers in domestic geese, its genetic basis has not been fully elucidated.Feather color, which is one of the main features of domestic geese, is considered an economically important trait. White feathers are preferred in consumer products  and are preferred for meat production due to the faster growth rate of birds with white plumage. Chinese geese have only white and gray colors, so geese can generally be divided into white geese and gray geese. Previous reports revealed that the mutation of melanocyte-inducing transcription factor  among 16 avian genomes (Supplementary Table 3 and the other two Chinese indigenous geese breeds (SCW and ZDW)5  and high coverage rates 97.96%), generally reflecting the base accuracy of the reliable genome  in the Anatidae clade, we chose 10 representative birds from seven genera in Anatidae, with Phasianidae as an outgroup for phylogenetic analysis  and Cygnus  had the closest genetic relationship, with a divergence time around 19.6 Mya. The goose and the pink-footed goose as sister branches derived from the same ancestor diverged between 3.5 and 22.6 Mya.To explore the evolutionary relationships and establish the phylogenetic position of the Chinese goose (P = 3.53 × 10–13), and “actin filament”  showed that a total of 11,733 gene families, while 9,390 gene families were shared. We detected 11,648 gene families in XGG, of which 15 XGG-specific gene families included 38 genes ” “lipid transport” , “phospholipid binding” , “cholesterol metabolism” , and “Fat digestion and absorption” 23 and MTTP 24 have been reported to be associated with liver steatosis in geese. Additionally, some PSGs were also prominently enriched in RNA-related processes . Among these SNPs, we detected 6,462,809 (58.59%) intergenic and 4,567,101 (41.41%) genic mutations, including 318,809 (2.89%) intergenic SNPs that were located within 1-kb up and downstream of the gene, 52,301 (0.47%) missense mutations, and 443 splicing mutations as possibly important in geese genetic diversity.A total of 994 geese from China and Europe were selected for whole-genome resequencing. The Chinese group consisted of 772 XGG, 51 FCG, 50 GFW, 11 LHW, 50 LXW, and 5 ACy, and the European group consisted of 50 LDG and 5 AAn  tree of the aforementioned 845 geese showed that Chinese and European geese were divided into two major branches  had the same trend as those for NSNP, indicating that Chinese geese had higher genetic diversity than European geese. The results for NSNP, F, FROH, and linkage disequilibrium (LD) showed that the genetic diversity of ACy was slightly higher than that of Chinese breeds. Among these Chinese indigenous geese, we found that XGG appeared to have the highest level of genetic diversity, as reflected in having the most SNPs , the largest Ho (0.28), and He (0.28), the smallest F (0.06), and a larger genetic distance (DST = 0.24). Notably, LHW had the least number of SNPs , the highest inbreeding coefficient (F = 0.23 and FROH = 16.30%), the smallest DST (0.04), and the largest LD decay distance (r2(0.3) = 1.63 kb), suggesting the lowest genetic diversity of LHW.To further reflect the real population structure of Chinese indigenous geese, we performed genetic diversity analyses on 990 geese  Table . StatistEDNRB2 and POLR1D (RNA Polymerase I And III Subunit D) on chromosome 15 having the most significant zFst (11.23) and zHp (–3.84) values , while being completely fixed in white geese  of FCG was closest to the haplotypes of white geese (53 nucleotide differences), and thus it could be reasonably speculated that the key mutation (14-bp) affecting the white feathers of Chinese geese may have originated from FCG (the breed name may not have appeared at that time) or other populations not studied here.We estimated zFst between white geese  and gray geese (50 FCG and 50 XGG) and conducted zHp analysis on the white population to scan for genomic signatures of selection. A total of 13 overlapping genes were detected, with ues Fig. . We then zFst 11. and zHp DAB2 (DAB Adaptor Protein 2), have been reported to be one of the differentially expressed gene markers for sheep mastitis resistance27, and the difference in expression was directly related to disease severity28. MYO1F (Myosin IF) is mainly expressed in neutrophils, and molecular experiments in mice have demonstrated that this gene may help neutrophils fight infection and that it plays a critical role in acute and chronic inflammatory diseases30. In actual observation, we found that epidermal cysts  was strongly selected in XGG population  and cysteine-rich hydrophobic domain 1 (CHIC1) were found to overlap 1136 PSGs mentioned in the above positive selection analysis. Although the functions of these genes have not been elucidated in geese, we speculated that they might play an important role in the adaptive evolution and breeding process of XGG; this could be the focus of future research.A total of 200 XGG individuals were randomly chosen for zFst statistics with 149 other Chinese geese , and the heterozygosity (zHp) analysis was conducted in all 636 XGG to detect the genomic regions under selection. We further focused on 21 overlapped functional genes based on zFst and zHp analyses . Therefore, the EPH gene family could help explain the migratory habits of geese as migratory birds. Geese have an excellent capacity to deposit fat in the liver. Positive selection analysis identified a series of PSGs enriched in lipid metabolism and RNA processing. Involved genes such as APOB participate in de novo synthesis of fatty acids and were associated with goose hepatic steatosis38. Cholesteryl ester transfer protein (CETP) has been shown to play a role in liver lipid metabolism39. Translocator protein (TSPO) regulates steatosis in nonalcoholic fatty liver disease40. There are also many potentially functionally related genes, such as scavenger receptor class B member 1 (SCARB1), MTTP, and lecithin-cholesterol acyltransferase (LCAT). In addition, Lu et al. found that microRNAs regulate multiple lipid synthesis and transport genes that are closely related to lipid metabolism in the goose liver4. These results suggested that fat deposition in the goose liver is a complex process regulated by a variety of signaling molecules and their pathways. These findings help explain the genetic basis of fatty liver in domestic geese and provide insights into the genetic improvement of geese. Although this study demonstrated that these genes were critical factors for evolutionary adaptation in domestic geese, clarifying the specific functions related to these pathways will require further studies of their expression patterns and possible roles in growth and development.XGG is an excellent goose breed, and it plays an essential role in the regional economy and conservation of the genetic resources of indigenous breeds. Here we report a chromosome-level reference genome of XGG and identified the sex chromosomes, thus providing valuable resources for the genetic investigation of Chinese indigenous geese. Further comparative genomic analysis indicated that the 8. Unexpectedly, the Chinese LXW and LHW were confused with each other and indistinguishable. A careful review of the relevant literature indicated that the central producing area of LXW was located in Lingxian County, Hunan province, but breeding also occurred in Lianhua County, Jiangxi province2. The origin and central areas of LHW were in Lianhua County, Jiangxi province, while neighboring areas such as Chaling and Youxian County of Hunan province were also represented. Given that LHW and LXW have very similar morphological characteristics and geographical distributions, we inferred that they were likely admixed at an early date due to human activities and were then bred locally. Genetic diversity analysis revealed that European geese, especially LDG, had extremely low levels of genetic diversity, a result that was consistent with previous findings13,41. As commercial geese breeds are dedicated to fattening the liver, the characteristics tend to be fixed, and exceptionally low genetic diversity reflects strong selection pressure. Most domestic geese showed lower genetic diversity than their ancestors (ACy and AAn), especially European domestic geese, probably due to genetic drift during population bottlenecks of initial domestication and subsequent artificial breeding42. Here, the genetic diversity of Chinese indigenous geese seemed to be at fairly healthy levels, except LHW which had the lowest genetic diversity, presumably due to multiple generations of inbreeding. Among those breeds, only XGG that has been conserved in a national conservation farm displayed the highest genetic diversity, a pattern that confirmed the uneven conservation of goose genetic resources in China and the necessity for scientific and effective preservation of genetic variation and rejuvenation programs.We further resequenced the whole genomes of 994 wild and domestic geese to explore the population genetic structure, revealing two major clades of Chinese and European populations that supported the hypothesis that domestic geese have dual origins at the genome level15 suggest that a 14-bp insertion in exon 3 of EDNRB2 is a key mutation responsible for white feathers in Chinese geese. The insertion should be a recessive mutation in light of the extremely low frequency of heterozygotes in gray geese and fixation in white geese that experienced strong artificial selection. Chinese gray geese have plumage colors similar to those of their ancestors. According to Chinese Waterfowl, gray geese were domesticated from wild ancestors, while white geese were artificially bred from a few gray geese after the mutation ocurred26. However, the genetic diversity of white geese was not significantly lower than that of gray geese, indicating that white geese are ancient domesticated breeds; this can be verified by numerous Chinese poems describing white geese during the Tang Dynasty (618–907). In the haplotypes of white geese, only the 14-bp insertion was derived and fixed, and we thus considered that the 14-bp insertion was a natural mutation that occurred during the domestication process of the gray goose, and then these almost completely distinguished haplotypes were formed due to genetic hitchhiking under strong artificial selection. We also noted that the four individuals of FCG were 14-bp heterozygous carriers, indicating that the current FCG population is impure and may produce offspring with white feathers, although the proportion of 14-bp insertions is small. Additionally, agouti signaling protein (ASIP), OCA2 melanosomal transmembrane protein (OCA2), TYR, tyrosinase-related protein 1 (TYRP1), melanocortin 1 receptor (MC1R), MITF, and KIT have also been studied for plumage coloration43, but we have not identified these genes and potentially associated loci. In particular, Wen et al. revealed that an 18-bp deletion in the KIT gene was a key mutation in the white plumage of Chinese geese based on a total of 35 individuals from four breeds16. However, we did not find that the 18-bp deletion and possible SNPs, InDels, or CNVs located within the KIT gene significantly affected the feather color of geese, and the haplotype of the KIT gene did not show significant genetic differentiation between the white and gray geese . We chose an adult female XGG collected from the national Xingguo Grey Goose Reserve in Jiangxi Province, China for de novo assembly. Furthermore, to assist genome annotation, total RNAs were extracted from different tissues (liver and muscle) according to the TRIzol (Invitogen) manufacturer’s protocol for transcriptome sequencing.The genomic DNA was extracted from blood samples using the traditional phenol-chloroform protocol  database. Details regarding genome assembly were presented in Supplementary Method Genome assembly for XGG used a hybrid de novo predictions . Then, Gene identification and functional annotation were performed via homology-based identification, de novo prediction, and transcriptome data-based approach. Protein sequences from homologous species  were aligned to XGG genome using BLAST v2.2.2851, and GeneWise v2.4.152 was then used to identify the gene structure. Augustus v3.3.353, Geneid v1.454, Genescan v3.1.255, GlimmerHMM v3.0456, and SNAP v2013.11.2957 were used for de novo prediction. To aid gene prediction, tissues from the liver and muscle retrieved from XGG were used to construct a normalized cDNA library. Transcriptome sequencing was performed on Illumina NOVASEQ 6000 platform. Transcriptome reads were aligned to XGG genome and using TopHat v2.0.858 to identify exons region, splice positions, and utilize Cufflinks v2.1.159 for transcript assembly. A total of 17,448 non-redundant genes were obtained using EVidenceModeler v1.1.1 and PASA v2.4.160. Finally, all identified proteins were aligned to public databases such as SwissProt61, NCBI nr62, Pfam63, KEGG64, and InterPro65 for functional annotation  were calculated using SAMtools66 (option: -depth) based on the resequencing data of 162 geese  with known sexes in subsequent population genetic analysis (Supplementary Table The avian sex chromosome sequences were downloaded from NCBI database to be used as reference sequences. These included six Z chromosomes and four W chromosomes from seven chromosome-level avian species (Supplementary Table https://www.ncbi.nlm.nih.gov/) and Ensembl (https://asia.ensembl.org/). We kept the longest transcript for each gene of four geese and used OrthoFinder v2.4.069 based on a Markov clustering algorithm to identify orthologous gene families with an E-value cutoff of 1e-5. The species-specific gene families were determined according to the presence or absence of genes for a given species.To infer XGG-specific gene families in domestic geese, protein sequences of TFG, ZDW, and SCW  as outgroups . The resulting alignments of each gene family were concatenated into a super-alignment matrix using two popular software programs to reconstruct maximum likelihood (ML) trees: RAxML v8.2.1272 with the PROTGAMMALGX model and IQ-TREE v2.1.173 with the self-estimated optimal substitution model. The topological structures generated by these two programs were similar.In addition to XGG, we also selected nine representative bird species of 74. The Markov chain Monte Carlo (MCMC) analysis was run for 2,000,000 generations, with a sample frequency of 10 after a burn-in of 400,000 iterations. Meanwhile, four calibration times obtained from the TimeTree database (http://www.timetree.org/) were set for dating analysis: (a) Gallus gallus–Anas zonorhyncha: 77.0–86.0 Mya; (b) Anseranas semipalmata–Anas zonorhyncha: 59.0–76.0 Mya; (c) Gallus gallus–Meleagris gallopavo: 27.5–37.5 Mya; (d) Anas platyrhynchos–Anas zonorhyncha: 0.27–0.79 Mya. Then, we used Tracer v1.7.175 to check the convergence of the chains to a stationary distribution.The divergence times were estimated using MCMCTREE processed in the PAML v4.9j76 for inference. The phylogenetic tree topology and branch lengths were considered to infer the significance of changes in gene family size in each branch. The P-values of each lineage were calculated, and values <0.05 were considered significant.To estimate the changes in gene repertoire in the XGG, 16,055 orthologous families identified by OrthoFinder from the 12 species described above were used for expansion and contraction analysis. Among them, we applied a random birth-death model of CAFÉ v4.2.177 to generate codon alignments in PAML format. Finally, a gene tree was constructed for each single-copy gene using IQ-TREE, and the codeml program in PAML with the branch-site model was used to discover positive selection in particular lineages, where XGG was defined as the foreground branch and other birds as the background. The compared likelihood ratio tests of Model A  and a null hypothesis  were analyzed by Chi-square tests, with P < 0.05 considered as significant.To detect PSGs in Chinese goose, the protein sequences and coding sequences (CDS) of all 6,371 single-copy genes were aligned using MAFFT, followed by pal2nal.pl v.1478 (twenty times faster than GATK) DNAseq pipeline following the best practices algorithms of GATK on a Tianhe-2 Supercomputer. For 772 XGG, we further used an R package “STITCH v1.68”79 to impute to the whole-genome level. After quality control and filtering  with an average sequencing depth of 10×. These genome sequencing data were aligned to the XGG reference, and variants were detected with Sentieon v201711.0381 -genome option to calculate the genetic relationship (shared proportion of IBD) between pairs of individuals for each breed and removed the one with a lower sequencing detection rate for PI_HAT > 0.5 pairs . Afterward, we ran GCTA v1.9283 using the above SNPs to produce a genetic relationship matrix and extract the first four eigenvectors for PCA analysis. SNP sites with r2 > 0.2 were eliminated to decrease the influence of LD (measured as r2), and 749,370 SNPs were retained to estimate the ancestral consanguinity component (from K = 2 to 10) of each population by ADMIXTURE v1.3.084 with 10-fold cross-validation.We utilized the PLINK v1.9ROH), and linkage disequilibrium (LD). Ho and He were estimated with the option -hardy in PLINK. F was calculated by the “plink -het” command at each site. The command “plink -distance square 1-ibs” was used to measure the DST. The PLINK parameters -homozyg -homozyg-snp 30 -homozyg-kb 30 was set to compute FROH with the genome size of 1.17 Gb. The square of the correlation coefficient (r2) was used to measure the degree of linkage between each pair of SNP alleles; r2 was estimated by the parameters -r2-ld-window-kb 500-ld-window-r2 0 in PLINK.We removed possible duplicate individuals from the sampling process to estimate the genetic diversity. For the remaining 990 individuals, we calculated seven parameters, comprising the number of SNPs (NSNP), observed heterozygosity (Ho), expected heterozygosity (He), inbreeding coefficient (F), intraspecific genetic distance (DST), runs of homozygosity (ROH)-based inbreeding coefficient  and 100 gray geese (50 FCG and 50 XGG) and performing Hp analysis on white geese. To characterize the germplasm characteristics of XGG, we randomly selected 200 individuals of XGG and 149 other Chinese geese  for Fst analysis, and analyzed the heterozygosity (Hp) of XGG. The average Fst and Hp values of each window were calculated by filtering the windows with the number of SNPs <10. Fst and Hp values were normalized (zFst and zHp) by subtracting genome-wide mean and dividing by the standard deviation, and in-house R scripts were used for visualization. The top 1% was set as the significance threshold, and genes from the overlapping region of zFst and zHp were considered convincing functional candidates.EDNRB2-POLR1D gene region (Chr15: 15.7–15.8 Mb) associated with white plumage, the resequencing data of 672 individuals (the average depth >10×) from 16 populations  First, we used XGG as a reference genome for mutation detection and obtained 521 SNPs and Indels with MAF >5% and call rate>90% for all 672 accessions. (ii) Then, we phased haplotypes for 521 SNPs and Indels using the fastPhase function with 1000 iterations in Beagle v5.185 and visualized via a haplotype heatmap constructed using an in-house R script. (iii) Finally, we constructed a haplotype network based on 285 SNPs and Indels in the EDNRB2-POLR1D gene region using the “haploNet” command in the R package “pegas v1.1”86, and the pairwise differences between haplotypes for 285 SNPs and Indels at the EDNRB2-POLR1D loci were calculated.To further investigate the Further information on research design is available in the Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Reporting Summary