This research employs fourteen and twelve microsatellite markers for two Huacaya alpaca populations from Southern Peru to estimate the genetic diversity and population structure. Our findings show that these two populations (Quimsachata and Ajoyani) were not structured. We also found that both populations have a large amount of diversity, which is a good indicator for conservation measures. These findings provide useful indicators regarding conservation programs created for this species to ensure their sustainable use.o), expected heterozygosity (He), polymorphism information content (PIC), and fixation indices values were estimated. An admixture analysis was performed for the population structure analysis. Different programs were used for these estimations. In total, 133 (Ajoyani) and 129 (Quimsachata) alleles were found, with a range of 4 to 17 by locus. The mean HO, HE, and PIC per marker for Ajoyani were 0.764 ± 0.112, 0.771 ± 0.1, and 0.736; for Quimsachata, they were 0.783 ± 0.087, 0.773 ± 0.095, and 0.738, respectively. The population structure showed no structure with K = 2. This study provides useful indicators for the creation of appropriate alpaca conservation programs.The alpaca population mostly consists of the Huacaya phenotype and is widely distributed in Southern Peru. This study aimed to estimate the genetic diversity and population structure of two Huacaya alpaca populations (Ajoyani and Quimsachata) using fourteen and twelve microsatellite markers for each population, respectively. A total of 168 alpaca biological samples were outsourced to Peruvian laboratories for DNA extraction and genotyping. For genetic diversity, observed heterozygosity (H In Peru, the alpaca is a livestock species adapted to the high altitudes of the Andes. More than 3.6 million alpacas, or more than 80% of the world’s entire population, live in Peru. The highlands of Peru, including Puno, Cusco, and Huancavelica, are home to the majority of the world’s alpacas . AlpacasAlpaca farming is an activity of great importance for a population that lives at more than 4000 m above sea level and which has the highest rates of poverty ,4. The aMolecular markers have proven to be powerful tools to assess genetic variation and relationships in animal species, presenting various identification methods . Microsae = 0.73) than vicuñas (He = 0.59). The authors concluded that there are low genetic differentiation values among the alpaca populations studied, and high levels of genetic diversity among three species . In the case of Peru, the studies of Morón et al. [o with a range of 0.79 to 0.90. Similarly, Morón et al. [e = 0.826) in three farms in the central zone of Peru.There are some previous studies focused on the genetic diversity and population structures of various south American camelids, such as alpacas, llamas, guanacos, and vicuñas ,15,16,17n et al. , Vallejo He = 0.5. The autn et al.  used bet He = 0.5. The autn et al.  found 22These results show that the use of microsatellite markers has been useful and informative to infer the genetic diversity of Huacaya alpaca populations. Despite being the world’s largest breeder of alpacas, there are relatively few studies that describe the alpaca populations in Peru. Studies of genetic relationships provide useful information from within-population patterns of genetic variation at marker loci and allow the deduction of demographic factors important for diversity conservation ,23. TherThe sample collection from alpaca specimens was conducted in accordance with Peruvian National Law No. 30407: “Animal Protection and Welfare”. Two Huacaya alpaca populations reared in the department of Puno, Southern Peru, were used in this study. Camelid Germplasm Bank population (Quimsachata for the rest of the text), located in the district of Santa Lucia, Province of Lampa, and ‘‘AURORA APROCSA AJOYANI’’ population (Ajoyani for the rest of the text) located in the district of Ajoyani, Province of Carabaya . QuimsacBiological material for a total of 168 nonrelated animals was collected for genotyping. We gained access to blood and follicle samples. From the Quimsachata population, 116 Huacaya alpacas were analyzed from samples of leukocytes extracted from whole blood obtained by jugular vein puncture, and 52 Huacaya alpacas from the Ajoyani population from three different breeders were analyzed from samples of hair follicles. Individuals were coded by correlative numbers prior to analysis.® thermal cycler . The amplified products were separated using capillary electrophoresis, using the ABI3137 XL genetic analyzer (Applied Biosystems). For the analysis of the samples, the 400HD ROX size standard was used. Allele size assignment in base pairs (bp) was carried out using 446 alpaca DNA samples from six different places to make a bin set and their naming was carried out using the Genemapper v4 program.Quimsachata samples were outsourced to Bionoma  to conduct the genomic DNA extraction and microsatellite genotyping, and for the determination of microsatellite alleles, twelve microsatellite loci described for alpacas and llamas  ,25,26,27Ajoyani samples were outsourced to Instituto Nacional de Innovación Agraria  to conduct the genomic DNA extraction and microsatellite genotyping, and for the determination of microsatellite alleles, fourteen microsatellite loci recommended for the International Society for Animal Genetics (ISAG)  were amplified through PCR reactions using a Mastercycler Pro S . The amplified products were separated using capillary electrophoresis, using the ABI3130 XL genetic analyzer (Applied Biosystems). For the analysis of the samples, the LIZ600 size standard was used. Allele size assignment in base pairs (bp) was adjusted to the ISAG nomenclature and their naming was carried out using the Genemapper v4 program.o), expected heterozygosity (He), and the polymorphic information content (PIC) for each of the 14 microsatellites used for Ajoyani alpaca and each of the 12 microsatellite markers for the Quimsachata alpaca, using Cervus v3.0.7 software [is) was estimated using Arlequin v3.5.2. software [We calculated the genetic diversity parameters such as the number of alleles (k), observed heterozygosity  in the Ajoyani population  and, similarly, for one in the Quimsachata population (LCA71), suggesting nonrandom pairings in the populations of Huacaya alpaca.Fpulation  and sevepulation . The aveIn addition, from the same data, the analysis of the population structure was carried out based on the admixture level of each alpaca individual using the STRUCTURE program . K = 2  is the mVisualization with CLUMPAK showed no structure. Each alpaca was represented by a single vertical line broken into colored segments .In this study, we explored the genetic diversity and relationships of two populations of alpacas from different altitudes and agroecological zones in the highlands of the Southern Andean Cordillera in Peru. Quimsachata is a germplasm bank of in vivo and ex situ colored alpacas, whose objective is to maintain the greatest diversity of alpacas of the Huacaya and Suri phenotypes and the greatest diversity of fleece colors; Quimsachata does not sell male or female alpacas for reproduction. Ajoyani has, as its main objective, the breeding of alpacas of the Huacaya phenotype and for the white fleece, whose selection objective is the quantity and quality of the fiber; for this purpose, they resort to the purchase of breeders from the district from Macusani (a district near Ajoyani).Overall, the Quimsachata and Ajoyani alpaca populations showed high levels of diversity. All of the microsatellites were considered useful for diversity studies because they have four or more alleles per loci . The leaThe average number of alleles per locus in the Ajoyani and Quimsachata populations was 9.5 and 10.75, respectively . SimilarMost of the markers are highly polymorphic (PIC > 0.5) , except o than He, less than the half of the total loci, which may indicate that there is neither an excess nor a deficiency of heterozygosity in the populations under study. This result is consistent with previous studies carried out by other authors [Six loci in the Ajoyani population  and five loci in the Quimsachata population  showed lower H authors ,37,38.o and He are higher than the Ajoyani population, meaning that a well-managed process is being conducted or can be only attributed to the higher number of samples employed in this work. The Hardy–Weinberg equilibrium analysis showed that the frequencies of the markers evaluated in the two populations of Huacaya alpacas have remained stable among generations, which is consistent with the average Fis value. Overall, the studied loci were 0.009 in the Ajoyani population and −0.017 in Quimsachata; these values are not different from zero, suggesting no heterozygote deficit or excess. The structure analysis suggested two as the number of populations and the graphic shows admixture in all individuals, which means that there is no structure in Ajoyani and Quimsachata populations, but the Quimsachata population shows different levels of admixture between individuals, while Ajoyani seems more homogeneous. This can be explained by the different breeding objectives for each population.The results showed that the Quimsachata population has high genetic diversity and a high number of alleles, and the average Ho (0.783 ± 0.087) and He (0.773 ± 0.095), but this could also be due to a higher number of Quimsachata individuals being analyzed. Furthermore, the structural analysis revealed that the populations have no structure. However, structure graphics showed that the Quimsachata population is slightly more heterogeneous than the Ajoyani. Finally, selected markers showed that they are very useful in genetic diversity studies.In summary, Ajoyani and Quimsachata are two Huacaya alpaca populations from the highest alpaca-populated region of Peru. The genetic diversity of these two populations was determined using fourteen and twelve microsatellite markers that showed a high level of polymorphism. Because of the large number of alleles, the heterozygosity, and the high PIC values, both populations exhibited high genetic diversity. Quimsachata must have high genetic diversity as a germplasm bank, as evidenced by the average number of alleles (10.75) and average H


Falcaria genus is Sickleweed. Falcaria species exhibit a high degree of genetic variability, posing challenges in the examination of genetic diversity due to the significant potential for hybridization and introgression among them. Utilizing morphological traits and molecular markers may prove to be a valuable approach in evaluating and harnessing germplasm, considering the current obstacles faced in breeding this medicinal herb. In 2021, fifteen Sickleweed populations were cultivated in pots under field conditions, employing a randomized complete block design with three replications. This aimed to assess genetic diversity and conduct marker-trait association analyses utilizing morpho-physiological characteristics and SSR markers. The Sickleweed populations displayed considerable genetic diversity across all traits. Through cluster analysis of traits and the utilization of the UPGMA method based on the Gower distance matrix, the population was classified into three distinct clusters. Upon examining all genotypes, 52 polymorphic bands were detected, with an average of 8.68 bands per primer. The average expected heterozygosity across all loci was 0.864, while the average PIC was 0.855. Molecular data analysis employing the Jaccard similarity index and UPGMA method revealed the division of Sickleweed populations into two major groups. Furthermore, the results of molecular variance analysis indicated that variation within the population exceeded that between populations. Thirty-two SSR fragments were found to be significantly associated with genomic regions controlling the studied traits, determined through the application of stepwise regression. Selection based on molecular markers offers a rapid method for breeding programs, with the genetic information obtained from these markers playing a crucial role. Therefore, alongside traits, selecting superior genotypes and populations of high value in breeding programs becomes feasible. The findings highlight that certain markers are linked to multiple traits, emphasizing the critical importance of this characteristic in plant breeding for the simultaneous improvement of numerous traits. The study’s insights regarding markers hold potential for application in Sickleweed breeding programs.One of the well-known medicinal plants in the  F. vulgaris), scientifically known as Falcaria, belongs to the Apiaceae family and is classified as a dicotyledonous plant. Its distinct leaves resemble the shape of a goose's foot, earning it various names such as Falcaria, Longleaf, and Sickleweed2. This species is found in different regions of Iran, including Tehran, Azarbaijan, Arak, Khorasan, Shirvan, Bojnord, Hamadan, Kurdistan, Kermanshah, and other areas. In some parts of Iran, it grows near fields and is consumed as a vegetable. Geographically, Sickleweed is distributed across America, Europe, Turkey, Iran, Caucasus, Central Asia, and Northwest Africa4. Sickleweed  is an important plant with various uses and properties that make it worthy of investigation. It has been recognized for its medicinal value and is traditionally used in herbal medicine for its potential therapeutic effects. Sickleweed contains bioactive compounds that have shown antimicrobial, anti-inflammatory, antioxidant, and anticancer properties in previous studies5. Furthermore, Sickleweed possesses nutritional value and can be used as a valuable food source. It is rich in essential nutrients, vitamins, and minerals that contribute to human health and well-being. The exploration of the genetic diversity in Sickleweed is crucial for understanding its potential for breeding programs aimed at improving its medicinal and nutritional properties6. Traditionally, Sickleweed is commonly used both as a vegetable and as a medicinal plant, particularly during the spring season. Given the significance of vegetables and medicinal plants in human nutrition, it is essential to assess the plant's organic and mineral content8. Minerals like calcium and phosphorus play vital roles in bone formation, muscle contractions, and regulation of nervous excitability9. The pollination behavior of Sickleweed  is an important aspect to consider in genetic diversity studies10. Sickleweed is a cross-pollinated species, meaning that it relies on the transfer of pollen between individual plants for successful fertilization11. In its natural habitat, Sickleweed is primarily pollinated by insects, including bees, butterflies, and other flying insects. These pollinators visit the flowers of Sickleweed to collect nectar and inadvertently transfer pollen between flowers, facilitating cross-pollination10. Understanding the pollination behavior of Sickleweed is crucial for several reasons12. First, it influences the genetic composition of the populations, as cross-pollination leads to genetic recombination and increases genetic diversity. Second, it affects the distribution of genetic traits within and among populations, as specific pollinators may preferentially visit certain individuals or populations. Finally, it has implications for the conservation and management of Sickleweed populations, as changes in pollinator availability or behavior can impact reproductive success and genetic diversity.Sickleweed  molecular markers, known for their high diversity value22. SSR markers have been extensively employed in diverse plant species, including medicinal plants, to assess genetic diversity27. These markers have demonstrated high efficiency in such studies. However, there has been limited research conducted on Sickleweed plants using SSR markers. In the study of the genetic diversity of the this population with SCoT molecular marker and morphological traits under different geographical and climatic conditions, the population was divided into three and two groups based on the markers and traits, respectively28. Also, another study by Piya et al.29 stands as the sole investigation in this regard. The study employed SSR markers to analyze the genetic diversity of eight distinct Sickleweed populations, each comprising 12 individuals sourced from various locations across the United States. The findings revealed the division of these individuals into three groups based on SSR markers, indicating significant genetic diversity among them.In recent years, there has been a notable surge in the utilization of molecular tools for investigating genetic diversity, conducting QTL mapping, and implementing protective programs in plants and other organisms. The information derived from these genetic techniques serves as a valuable parameter for studying diverse populations and comprehending genetic distinctions between them30. This investigation holds numerous applications, including the examination of phylogenetic relationships among genotypes and unknown populations, identification of desirable trait alleles in germplasm collections, precise localization of quantitative trait loci, and confirmation of candidate genes associated with quantitative traits. The identification of genomic regions governing quantitative traits relies on linkage disequilibrium and is achieved through two main approaches: linkage analysis and association analysis31. In association analysis, the direct examination of the relationship between genotype and phenotype in individuals is employed to identify chromosomal regions involved in trait control32. Marker-trait association analysis has been extensively employed in various plant species33, including medicinal plants40. However, there have been limited studies investigating genetic diversity at the phenotypic and molecular levels, as well as the associations between molecular markers and phenotypes, in Sickleweed. Consequently, this research aims to explore the genetic diversity of Sickleweed ecotypes collected from different regions using SSR markers and traits, while also conducting association analyses between traits and markers. Undoubtedly, the findings of this study will provide valuable insights for further research and breeding programs focused on this medicinal and vegetable plant. By studying the genetic diversity of Sickleweed, we can identify and characterize different genotypes with distinct traits and determine their potential for cultivation, selection, and breeding purposes. This knowledge can facilitate the development of improved varieties with enhanced medicinal and nutritional qualities, as well as better adaptability to different environments.An essential aspect of plant breeding programs involves studying the correlation between DNA polymorphism and phenotypic trait diversityFalcaria vulgaris) is an important factor to consider in studies assessing genetic diversity. Sickleweed is primarily a cross-pollinated species, relying on the transfer of pollen between individual plants for successful fertilization. The specific pollination behavior, including the involvement of different pollinators and the extent of self-pollination, can have significant implications for the composition and diversity of Sickleweed populations. It is important to consider pollination behavior when collecting samples for genetic diversity studies. To ensure representative sampling and capture the genetic diversity within populations, it is crucial to employ a strategy that accounts for potential differences in pollination patterns among individuals and populations. In our study, we followed a systematic approach for sample collection, taking into consideration the pollination behavior of Sickleweed. We employed a random sampling strategy, ensuring that individuals were selected from different locations within each population. By collecting samples from multiple individuals within a population, we aimed to capture the genetic variation present within and among populations, including potential variations resulting from pollination patterns. Furthermore, we acknowledge the importance of providing detailed information on the sample collection strategy, including the number of plants sampled per population, the collection locations, and any additional considerations specific to pollination behavior. We will revise the manuscript to include these details and emphasize the importance of incorporating the pollination behavior in the sampling strategy to obtain a comprehensive assessment of genetic diversity in Sickleweed populations. The species identity was confirmed by Dr. Rahimi, and voucher specimens were deposited in the Graduate University of Advanced Technology Herbarium under the numbers 151 to 165. These specimens are available for botanical studies upon official request. The 15 different populations of Sickleweed were cultivated in pots under field conditions in 2021 at the Graduate University of Advanced Technology in Kerman, Iran. The plants were grown in pots located in the field and field conditions. The growth media used in this study consisted of a well-balanced mixture of organic and inorganic components to provide optimal nutrient availability and support healthy plant growth. The growth media composition consisted of a combination of sterile soil, peat moss, and perlite in a ratio of 3:1:1. This mixture was selected based on previous studies and recommendations for the cultivation of Sickleweed to provide a suitable substrate for plant growth. The sterile soil provided essential minerals and nutrients, while the peat moss and perlite contributed to the media's moisture retention and aeration properties. To ensure the consistency of growth conditions, the growth media were thoroughly mixed and sterilized before planting the Sickleweed seeds. The pots were filled with the growth media, and the seeds were sown at the recommended depth. The experimental design employed was a randomized complete block design with three replications. In our study, we maintained a single Sickleweed plant per pot to minimize competition and facilitate accurate data collection. This allowed us to focus on the individual performance of each plant and avoid potential confounding effects. To represent the genetic diversity within Sickleweed populations, we used multiple pots for each population. The number of samples for each pot in each replicate was 10, and their average was used for the data of each replicate. To ensure the reliability of our results, we incorporated 3 replications in our experimental design. The number of replications varied depending on the specific analysis and statistical requirements of each trait. We employed a sufficient number of replications to minimize the impact of random variability and enhance the statistical power of our findings. The specific details regarding the number of plants per pot, the number of pots per population, and the number of replications were carefully considered during the planning and execution of our study. These design considerations aimed to ensure the validity and robustness of our results and provide meaningful insights into the genetic diversity and marker-trait associations in Sickleweed. During the vegetative stage, various morphological traits such as plant height, fresh and dry weight, leaf number, length, and width were measured. After harvesting, the leaves of the plants were collected, wrapped in foil, and transported to the laboratory for DNA extraction and assessment of nutrient content. The nutrient content analysis focused on elements such as zinc, manganese, potassium, iron, sodium, magnesium, and calcium ions. These measurements were carried out using flame and atomic absorption methods. The GTA-110 graphite tube atomizer Spectra AA 220Varian, manufactured in Australia, was utilized for the measurement of dissolved ions41. Before sample measurement, the standard solution of each ion was injected into the device, and the corresponding standard curve was generated using the device's software (Spectra AA). The unknown concentrations of the solutions were determined using software42.This study was conducted in compliance with the relevant institutional, national, and international guidelines and legislation of Iran. No specific permits were required for the collection of plant materials. The seeds of 15 different populations of Sickleweed were collected from seven Iranian provinces, namely Ardebil, Kurdistan, Kermanshah, Gilan, Hamedan, Qazvin, and Qom  and allowed to dissolve in the acid for 24 h. After this period, the sample was heated to release acid vapors. Distilled water was then added to bring the solution volume up to 50 ml. The solution was filtered through filter paper to remove any particulate matter and obtain a clear solution suitable for analysis in an atomic absorption device. In addition to the atomic absorption analysis, the nitrogen percentage in the plant tissue was measured and calculated using the Kjeldahl method. This involved a process of digestion, distillation, and titration using a Kjeldahl apparatus.Descriptive statistics, including measures such as mean, range, and standard deviation, were computed for the average data of the 15 populations. Additionally, the phenotypic coefficient of variation (PCV) was calculated for the studied traits. The PCV is a measure of variation relative to the mean and is often expressed as a percentage. To calculate the PCV for a trait, the following formula can be used:The PCV provides insights into the relative magnitude of variation for a specific trait compared to its mean value. It helps assess the extent of phenotypic diversity within the populations under study.43. In the laboratory of the Graduate University of Advanced Technology in Kerman, Iran, DNA extraction was carried out from young leaf samples of Sickleweed ecotypes using the Dellaporta method44 with some modifications. After DNA extraction, the quality of the samples was assessed through 2% agarose gel electrophoresis, while the quantity of DNA was determined using spectrophotometry. The polymerase chain reaction (PCR) was conducted using six microsatellite primers that had been previously investigated for their suitability in Sickleweed2.The analysis of variance (ANOVA) was conducted using the randomized complete block design, and the expected value of the mean square was used to determine the variance components. To analyze the zinc and manganese features, which had small measured data sizes, the data were initially multiplied by 100 before undergoing the analysis of variance. The software used for performing the analysis of variance was SAS 9.42 (50 mM), 0.12 µl of Taq polymerase enzyme (5U), 1 µl of PCR buffer (10×), 0.4 µl of the forward primer (60 ng), 0.4 µl of the reverse primer (60 ng), and 5 µl of sterile deionized water. The PCR thermal cycle for the microsatellite marker consisted of an initial denaturation step at 94 °C for 4 min, followed by 35 cycles. Each cycle included a 30-s denaturation step at 94 °C, a 45-s annealing step at the temperature indicated by the primer's melting temperature (TM) in Table 45 was employed with some modifications  was carried out in a volume of 10 µl. The reaction mixture included 2 µl of template DNA (50 ng), 0.6 µl of dNTP (10 mM), 0.3 µl of MgClThe banding patterns obtained from the PCR analysis were scored as either absence (zero) or presence (one) of a band. These scores were organized in a matrix format with populations as rows and bands as columns. This matrix was used to calculate various marker indexes and to group the populations accordingly.46, Expected Heterozygosity47, Marker Index, Effective Multiplex Ratio and Mean Heterozygosity48, and Marker Detection Power49. Furthermore, the number of effective alleles, Shannon's index50, and Nei's genetic diversity51 were determined using the POPGEN software version 1.3.152. Cluster analysis was performed using different methods and criteria based on either the studied traits or SSR markers to group the ecotypes. The cluster method and criterion that yielded the highest Cophenetic correlation coefficient were selected, and the grouping was performed using the chosen method with the R software. The determination of the number of groups was based on the maximum distance method of merging two groups. The analysis of molecular variance (AMOVA) was conducted using the GenAlex software package version 6.553. This analysis partitioned the total molecular variance among and within all populations based on the number of groups obtained from the cluster analysis. To examine the relationship between the molecular data (independent variables) and the quantitative data (dependent variables), stepwise regression analysis was performed. The stepwise regression utilized a step-by-step method and was conducted using the PAST software54.Marker indexes were calculated using specific formulas and a custom Excel program developed by the first author. These indexes included the number of amplified bands, the number of polymorphic bands, the polymorphic percentage, Polymorphism Information Content (PIC)This study complied with relevant institutional, national, and international guidelines and legislation of Iran, and no specific permits were required to collect the plant materials. The species identity was done by Dr. Rahimi and voucher specimens were deposited in the Graduate University of Advanced Technology Herbarium (no. 151 to 165), available for botanical studies with an official request.Descriptive statistics, such as the minimum, maximum, and range of the studied traits, are presented in Table The analysis of variance results for the studied traits, including leaf characteristics and elements, indicated a significant difference (p < 0.01) among the Sickleweed populations Table . This siTable The UPGMA method with Gower distance yielded the highest Cophenetic correlation coefficient value (0.756) among all the methods using different distance criteria. Consequently, cluster analysis was performed using this method, resulting in the division of the Sickleweed populations into three distinct groups Fig. . The genIn this study, six SSR primers were used, resulting in a total of 55 bands. Among these bands, 52 were polymorphic, with an average of 8.67 polymorphic bands per primer . Figure . Figure To understand the differentiation of subgroups, molecular variance analysis was carried out with the assumption of three groups and the results showed that 18% of the total molecular diversity is explained by diversity among the populations, and 82% of that variation is related to within populations Table .Table 6A2) explained by each marker for the studied traits is presented in Table In this study, a total of 49 markers  were found to have a significant relationship with the studied traits and were included in the regression model Table . Some of59.The high phenotypic coefficient of variation (PCV) observed for Leaf width and Zinc traits indicates that these traits have a greater potential for improvement and modification through selective breeding programs. This suggests that there is a higher chance of selecting superior populations among the studied Sickleweed populations for these traits. Conversely, the Potassium trait exhibits the lowest PCV, implying that improving this trait through selection in the studied population may be less successful compared to other traits. The observed high diversity in traits among the Sickleweed populations can be attributed to environmental conditions as well as the genetic variations among populations. The phenotypic evaluations and dispersion indices demonstrate that the studied populations exhibit significant diversity across various traits. This diversity can be valuable for association analysis and breeding programs. Furthermore, the results of variance analysis highlight the existence of inherent genetic diversity among the studied populations across all traits. This emphasizes the possibility of identifying superior populations or genotypes based on desired traits. Similar findings have been reported by researchers studying various medicinal plants, highlighting the potential to utilize phenotypic diversity in populations or genotypes for achieving superior populations or genotypes and managing breeding programs based on them. These traits have proven effective in identifying and characterizing diversity within populations56. To maximize heterosis, it is beneficial to cross genotypes or cultivars that have significant genetic dissimilarity60. Phenotypic traits can be used as indicators to select parents with a substantial genetic distance between genotypes for such crosses. Multivariate analysis techniques, such as cluster analysis and biplot grouping with principal component analysis, can be employed to achieve this objective. These techniques allow for the grouping of genotypes based on agricultural, biochemical, and physiological traits, thereby facilitating the selection of diverse parents for crossbreeding programs and enhancing genetic diversity61. By utilizing these multivariate analysis techniques, distant groups of genotypes can be identified based on their traits, enabling their use as parents in crossbreeding programs to increase genetic diversity and potentially improve desirable traits in the offspring62.The variance component analysis revealed that, except for the Plant height trait, the variation between populations was greater than within populations for all other traits. This difference in variation can be attributed to the diverse environmental and genetic conditions among the populations. Morphological traits are known to be influenced by the growth environment, and the existing variations in environmental and growth conditions contribute to the observed diversity in these traits. It is important to note that morphological traits, being polygenic, may not accurately reflect genetic changes at the genomic level. Therefore, grouping populations based on these traits may yield different results and changes under different environmental conditions. This emphasizes the need for careful consideration when using morphological traits alone for grouping or selection purposes29, which also reported GSSR24 as having the highest PIC value in Sickleweed populations. Similar studies on other plants have shown high average PIC values for SSR markers, highlighting their effectiveness in assessing genetic diversity27. The GSSR24 primer also demonstrated the highest value of H, indicating its efficiency in distinguishing the studied populations. High values of genetic diversity reflect the marker's ability to differentiate genotypes from each other. The observed heterozygosity at certain loci may be attributed to gene introgression, microsatellite motif replication during the breeding season, or the evolutionary history of Sickleweed. The extent of genetic diversity is influenced by factors such as the type of molecular markers, characteristics of the SSR repeat unit, the number of SSR markers used, and the genetic relationships within the Sickleweed germplasm25. The effective polymorphism ratio, which represents the number of polymorphic loci in germplasm, varied between 2 for the ESSR80 marker and 4.8 for GSSR24. The marker's detection power (D), which reflects its ability to distinguish between two individuals, ranged from 0.781 for ESSR80 to 0.995 for GSSR24. These values indicate that the GSSR24 primer has a higher capacity for distinguishing between individuals. The variations in the number of alleles identified across different studies can be attributed to variations in the origin and characteristics of the studied genotypes, as well as differences in the markers and PCR conditions employed in each study27. PIC is an important criterion for comparing different markers in terms of their discriminatory power. Higher PIC values indicate greater polymorphism and the presence of rare alleles or alleles that significantly contribute to distinguishing individuals. Markers with high PIC values are particularly useful for distinguishing closely related genotypes37.The GSSR24 primer exhibited the highest PIC value in this study, indicating its efficacy in differentiating the studied populations of Sickleweed. These findings are consistent with a previous study by Piya et al.1, can be enhanced63. Genetic diversity in plant species is influenced by various factors, including geographical distribution, population size, and breeding system65. It is essential to understand the genetic diversity of a plant species to plan and implement effective conservation strategies, irrespective of its geographical range65. A species' extensive geographic distribution does not necessarily ensure the preservation of its genetic diversity64. Therefore, conservation efforts should consider the genetic characteristics of the species. In many cases, the results obtained from molecular markers do not align perfectly with phenotypic traits. This discrepancy can be attributed to the polygenic control of agronomic traits and their susceptibility to environmental influences66. Morphological markers, which are based on agronomic data, may not accurately reflect the genetic differentiation of individuals based on their geographic environment. However, in this study, the agreement between cluster analysis using molecular markers and agronomic traits suggests that the chosen SSR markers provided sufficient coverage throughout the genome. Increasing the number of SSR markers could potentially yield even better separation within the studied germplasm, necessitating the design and utilization of additional SSR markers. Furthermore, since SSR markers are designed from non-coding regions of the genome, they may not target coding genes directly responsible for morphological traits. Therefore, the use of EST (Expressed Sequence Tag) markers, which are designed based on coding regions, is recommended for studying morphological traits and capturing a more comprehensive understanding of the genetic basis underlying these traits.The primary objective of cluster analysis is to assess the degree of relatedness or genetic distance among populations. This approach enables researchers to reduce the time and effort required for random crossbreeding by strategically selecting distant populations from different clusters. By crossing populations that exhibit significant genetic distance, the chances of obtaining desired hybrids or achieving maximum segregation in subsequent generations, such as F37. It is important to note that increasing germplasm diversity leads to the presence of rare alleles within the population. While this can enhance the identification of potential associations, it also introduces challenges such as the increased likelihood of false relationships and a reduction in the statistical power of association mapping67. To ensure reliable results in association mapping studies, it is crucial to evaluate populations with high genetic and phenotypic diversity68. Despite the advantages of association mapping, it is important to acknowledge that the presence of population structure can potentially lead to false associations between markers and traits69.The results of the analysis of molecular variance (AMOVA) indicate that the variation within the sub-populations is greater than the variation between the sub-populations. This finding suggests that there is a wide range of allelic diversity within each population. Considering that the populations within each cluster are derived from different geographical locations, this result is consistent and highlights the significant diversity among the 15 populations studied73. The standardized β coefficients provide valuable information regarding the direction of the marker's effect on the trait. A negative sign indicates a reducing effect, while a positive sign suggests an increasing effect. Breeding programs can use genotypes lacking or possessing specific alleles identified by these markers to increase or decrease the expression of the target traits, aligning with the breeder's objectives. It is noteworthy that some markers were associated with multiple traits, indicating a close connection between these traits or potential pleiotropic control. This highlights the interdependence and shared genetic regulation among these traits, as observed in other studies71. The use of molecular markers related to important morphological traits in plant production and breeding, particularly through marker-assisted selection (MAS), allows for the identification of key genes and the introduction of candidate markers for further investigation in populations. While challenges exist, such as the scarcity of divergent populations for mapping and limitations in time and the correlation between morphological traits and molecular markers, regression analysis helps overcome these limitations and offers a promising approach for identifying markers associated with morphological traits.The utilization of regression analysis to identify markers associated with traits can serve as an initial step for future studies focusing on QTL identification. The markers identified in this research, compared to other markers, may have a higher likelihood of being located in the coding regions of the studied traits. This is because they were included in the regression model and demonstrated a stronger association with the observed changes in those traits. Similar to other researchers in the field, regression analysis has been employed to establish the relationship between markers and traits in various plant species, ultimately facilitating plant breeding efforts72. The identification of markers associated with traits, as well as the relationship between certain markers and multiple traits, opens the door for further research in specific genomic regions. Validating these associated markers and converting them into specific SCAR markers or specific DNA sequences for targeted breeding is a practical and applicable solution. These markers can be utilized for important traits identified in this study37. The use of association analysis to identify markers linked to morphological traits in Sickleweed populations was documented for the first time in this study. The findings, along with previous research, suggest that highly associated and reliable markers for specific traits can be identified and utilized in future studies. However, it is important to employ larger and more diverse populations and incorporate a greater number of markers for more comprehensive investigations. These identified markers should be further examined in segregated populations and larger populations to confirm their correlation with specific traits. Ultimately, these markers can significantly enhance the effectiveness of breeding programs.In this study, it was observed that the population structure of Sickleweed was characterized by the presence of seven subgroups. However, these subgroups were not completely separated, indicating a significant degree of mixing and suggesting a mixed descent for the studied genotypes. This implies that individuals may inherit portions of their genome from different subgroups within the population. Additionally, the similarity in allele frequencies across different populations could be attributed to migration or shared descentThe findings of this study highlight the high genetic diversity present in the examined Sickleweed population. The populations, originating from different regions and having distinct genetic backgrounds, exhibit variations in traits, indicating the presence of genetic factors influencing population differences alongside environmental effects. The use of SSR markers proves effective in studying the genetic diversity of the Sickleweed population, thanks to their stable positions in the genome. Selection based on molecular markers offers a rapid approach in breeding programs, with the genetic information obtained from these markers playing a crucial role. Thus, in addition to considering phenotypic traits, selecting superior genotypes and populations with high breeding value can be accomplished using molecular markers. It should be noted that the grouping of Sickleweed populations based on molecular data did not align closely with the grouping based on agricultural traits or the Bayesian method. However, the populations of Dillman-Gilan and Ilan-Qom exhibited the highest values for most nutritional elements traits. Considering the significance of these traits in human nutrition, these populations can be selected as superior populations and recommended for cultivation as vegetable sources for human consumption. Through stepwise regression analysis, 32 loci associated with the studied traits were identified. The results demonstrate that some markers are linked to multiple traits, underscoring their critical importance in plant breeding for simultaneously improving multiple traits.


Cichorium intybus (chicory), native to Eurasia, was first recorded in North America in 1774. Subsequently, chicory spread and became naturalized throughout much of the continent.Human activities have been altering the flora and fauna across the planet. Distributions and the diversity of species, and the phenotypes of individuals in those species are changing. New England with its rapidly changing human demographics is an ideal place to investigate these temporal changes in the habitat. The flora of New England consists of both native and nonnative species. Non‐indigenous plant species have been introduced since the first Europeans arrived in North America in the 15th century. In this study, we used chloroplast DNA sequences and 12 microsatellite nuclear markers to assess the temporal genetic changes in New England populations of chicory. We analysed 84 herbarium specimens and 18 contemporary extant populations .Three chloroplast DNA haplotypes were detected and all were present in New England prior to 1890; however, Hap3 was rare prior to the 1950s. The nuclear DNA markers showed a major shift in the genetic diversity and composition, with all historical herbarium collections belonging to a single genetic cluster and 16 out of 18 contemporary chicory populations belonging to different genetic clusters. This change occurred regionally and also on a local scale with contemporary populations being very different from herbarium specimens collected previously in the corresponding localities.Synthesis. Our results indicate that the genetic diversity and structure of Cichorium intybus populations have changed substantially since the founding populations in New England. These changes may have contributed to the success of this nonnative species and helped to fuel its rapid expansion and adaptation to the changing landscapes in both New England and the rest of North America. Populations of chicory today, are different from those that first colonized New England. All herbarium specimens, including one by Asa Gray, collected between 1848 and 1970, form a genetic group, distinct from nearly all contemporary collections. This shift in genetic composition likely reflect dispersal and selection to changing land use patterns that are part of New England history. Chicory was introduced from Europe primarily as a semi‐domesticated species, arriving during the 1770s , University of Massachusetts Boston Herbarium (UMB), Harvard University Herbaria , The Hodgdon Herbarium at University of New Hampshire (NHA), and Nantucket Maria Mitchell Association (NMMA) herbarium . We sampled 84 herbarium specimens and the collection dates ranged from 1848 (Asa Grey's mounting sheet) to 2004  was used for DNA extractions of both the 84 dried herbarium specimen tissue and 144 fresh samples from the 18 extant populations according to manufacturer's protocol. We used 12 microsatellite nuclear markers , 2.5 μl of 10× reaction buffer, 1 μl of each primer (10 mM), 0.2 μl of Taq polymerase (5 units/μl)  and 10.3 μl H2O. The thermocycler  conditions were 95°C for 5 min, 35 cycles of 95°C for 30 s, annealing temperature 52°C for 30 s, 72°C for 45 s, and a final extension of 72°C for 5 min. We followed a modified amplification protocol for herbaria specimens with the KAPA3G Plant PCR Kit—Mix B , as optimized in Schori et al. (The 25 μl polymerase chain reactions (PCRs) to amplify the selected markers contained: 5 μl DNA (20–100 ng), 2.5 μl of 2.5 mM MgCli et al. .2.3Avant sequencer (Applied Biosystems). We used the program Sequencher 4.9 (http://genecodes.com/) for chloroplast DNA sequence editing and alignment. Peak Scanner software was employed for microsatellite fragment length scoring (Applied Biosystems). Peaks were assigned numbers by Peak Scanner based on the 400HD Rox size ladder that approximated the length of amplicons. Each individual peak size was confirmed visually. The observed (Ho) and the expected (He) heterozygosity, inbreeding coefficient (F) and the analysis of molecular variance (AMOVA) were calculated using Arlequin v. 3.5 .Chloroplast DNA (cpDNA) fragments were sequenced and PCR products targeting microsatellite regions were assayed on the 3100‐Cichorium intybus accessions. All sampled individuals were allowed to be products of admixture, and we used prior information about the population origin. The length of burn‐in period was set to 200,000 iterations, and the number of Markov Chain Monte Carlo (MCMC) steps after burn‐in was 1,000,000. We conducted five independent runs with a partial data set , and with a complete data set  with K set from 1 to 10, with 10 iterations for each K in each independent run. STRUCTURE results were run through STRUCTURE HARVESTER v. 0.6.93  was performed for the microsatellite loci data in the R package Jombart, . Cross‐v33.1trnL‐trnF locus. We could not obtain high quality sequence reads from four herbaria DNAs . We detected three cpDNA haplotypes (Table All samples from contemporary extant populations and 84 herbarium specimens were sequenced at the es Table  that weres Table . However3.2https://doi.org/10.5281/zenodo.6820061), and markers amplified in all 228 individuals. We have detected 153 alleles with 96 alleles in historical, herbarium population and an increase to 140 alleles in contemporary populations  was varied from one to seven. The highest likelihood in the partial analysis was obtained when K was set to four. The maximal ΔK occurred at K = 2 using the method of Evanno et al.  or two groups (red and green for K = 4) while all samples in 16 of the 18 contemporary populations belong predominantly to different genetic groups (identified as green for K = 2 and yellow and blue for K = 4). Note, for visual clarity of direct population comparisons, we have repeated the analyses and display the 31 herbarium samples which historically resided at the sites of these 18 contemporary populations, both among the herbarium collections, and at the start of, and adjacent to, their corresponding contemporary population. Remarkably, the analyses suggest that old herbarium specimens from throughout the region are similar to each other and often distinct from the contemporary populations in the same locations. Exploration of the STRUCTURE analyses did not reveal any aberrant loci or possible artefacts that could create these patterns (data not shown).Using the 12 microsatellite markers, we analysed the population structure of these samples in several ways. We conducted a partial STRUCTURE analysis for 84 herbarium specimens; the number of clusters (o et al. , with a 4 Figure . The STRd Figure . We repo4 Figure . All 84 The 84 herbarium samples also clearly separated from contemporary samples in the results of the DAPC analyses (Figure 4Our study is the first temporal genetic analysis of non‐indigenous chicory species in North America. Focusing on New England, we utilized a collection of 84 herbarium specimens spanning 170 years. From this collection, we identified 31 specimens that located to 18 sites across New England and were able to find contemporary extant populations of chicory in all of these sites. The herbaria and extant collections from 18 populations were used to infer genetic structure of historical and contemporary populations. Combining the genetic and temporal data, we observed a dramatic shift in the composition of New England chicory populations over time.We detected three cpDNA haplotypes in New England, consistent with an earlier study of North American collections (Závada et al., Allelic analyses of microsatellite data revealed enhanced genetic diversity in the contemporary populations of chicory—we detected 57 unique alleles in the contemporary populations that were not present in the historical herbaria collections, but only 13 unique alleles in the historical data set Table . Most drSeveral factors may have contributed to this surprising outcome; recent introductions, anthropogenic seed dispersal and gene flow, and changing landscapes associated with agricultural activities and climate change. The New England landscape has been dramatically transformed multiple times, since the colonization by Europeans. Early deforestation for agriculture, sheep farming and lumber with the accompanying introduction of many non‐native species such as chicory. Subsequently, both agriculture and the lumber industry largely moved to the Midwest starting in the latter half of the 19th century, and fields and pastures in New England became abandoned. Sheep farming in particular reached its pinnacle in New England during the 1840s, leading to large populations of chicory as a fodder crop. These agricultural and disturbed environments proved to be excellent habitats for chicory. Chicory abundance was not reported to be problematic during 19th century, but this may have changed, as chicory began to spread across the continental United States. After more than 100 years on the continent, farmers in the early 1900s began to call for the control and eradication of chicory Hansen, . AlthougGlobalization and anthropogenic activity have reshaped the biodiversity and the evolutionary path and success of many plant species. Native population distributions are shifting, and weeds and invasive species have successfully colonized nearly every human‐disturbed environment on the planet. In addition, phenotypic changes during historical times, such as flowering times, have been increasingly reported in plant populations. These shifts provide an opportunity and need to investigate landscape genetics and evolutionary changes, through time and space to tease apart the roles of genetic adaptation, phenotypic plasticity and stochastic processes to these dynamic systems. Employing contemporary and historical collections dating back to 1848, we have provided a more complete understanding of the population history of the nonindigenous weed chicory in North America. Our data indicate that cryptic genetic changes underlie the success of chicory as it has adapted to a rapidly changing landscape over the last 170 years.Rick V. Kesseli and Tomáš Závada designed the experiment; Tomáš Závada and Rondy J. Malik carried out the field and lab work; Data analysis was done by Tomáš Závada, Lisa Mazumder and Rick V. Kesseli; Tomáš Závada and Rick V. Kesseli wrote the manuscript and all authors contributed critically to drafts.None of the authors have a conflict of interest associated with this work.https://publons.com/publon/10.1111/1365‐2745.13968.The peer review history for this article is available at Figure S1Click here for additional data file.Figure S2Click here for additional data file.Table S1Click here for additional data file.


Nicrophorus vespilloides. Using whole-genome sequencing of populations that had evolved in the presence or absence of parental care for 30 generations, we show that parental care maintains levels of standing genetic variation. In contrast, under a harsh environment without care, strong directional selection caused a reduction in genetic variation. Furthermore, we show that adaptation to the loss of care is associated with genetic divergence between populations at loci related to stress, morphological development, and transcriptional regulation. These data reveal how social behavior is linked to the genetic processes that shape and maintain genetic diversity within populations, and provides rare empirical evidence for an old hypothesis.Cooperative social behaviors, such as parental care, have long been hypothesized to relax selection leading to the accumulation of genetic variation in populations. Although the idea has been discussed for decades, there has been relatively little experimental work to investigate how social behavior contributes to genetic variation in populations. Here, we investigate how parental care can shape molecular genetic variation in the subsocial insect,  While much recent work has focused on identifying genes that drive social behaviors , relativCooperative social interactions often function to shield social partners from a harsh physical environment, and the same is true for parental care . WithoutNicrophorus vespilloides) to explore how parental care affects levels of standing genetic variation and how populations may adapt in the face of its loss. In natural populations of this locally abundant subsocial insect, burying beetle parents raise their young on a carrion nest, formed from a small dead animal, such as a mouse or songbird. There is continuous variation in the level of parental care supplied, with around 5% of parents abandoning the brood before their young have even hatched , parents remained with their young throughout development, whereas in No Care populations (NC), parents were removed just prior to hatching. No Care populations rapidly adapted to this regime (within 14 generations), with adaptive change being detectable through increases in breeding success and larval density see . MoreoveFST) between experimental populations.At the 30th generation of experimental evolution, we used pooled whole-genome resequencing of these populations to document genetic variation at the molecular level when care was present and when it was prevented experimentally . First, N. vespilloides that had been evolving under different regimes of parental care and that were founded from a single genetically diverse population generated by interbreeding beetles from multiple wild populations across Cambridgeshire. These populations have been described in detail previously (POP) or without parental care (NCPOP). Each replicate of each population originated from the same founding population and, therefore, is expected to be genetically identical. However, each block was bred 1 week apart and there could have been minor genetic and/or environmental fluctuations that could contribute to genetic variation within and between blocks  for DNA extraction.We sampled DNA from experimental populations of eviously  and compn blocks . For then blocks . Thereafn blocks . On the For each family, DNA from first-instar larvae were pooled and extracted using a modified version of the Qiagen DNEasy Mini Kit. Total DNA quality was checked using gel electrophoresis, and yield was quantified using a Qubit DNA Assay Kit (Thermo Fisher). Families were pooled in equimolar concentrations such that each individual was represented equally to generate four libraries: FC1, FC2, NC1, and NC2 with pool sizes of 41, 52, 52, and 59, respectively. Whole-genome resequencing libraries were constructed and sequenced (150-bp paired-end) at a depth of 100× using an Illumina Novaseq 6000 platform by Novogene (Hong Kong).https://github.com/FelixKrueger/TrimGalore) to remove adaptor sequences, perform quality trimming, and discard low-quality reads. Reads were aligned in paired-end mode using the burrows-wheeler aligner (bwa) to the N. vespilloides reference genome (NCBI Refseq Assembly: GCF_001412225.1) (http://broadinstitute.github.io/picard/). Pileup files were created using samtools . Pileups were merged into a single sync file using Popoolation2 for use with poolfstat . All subsequent post-processing and statistical analyses were performed in R version 4.1.2 using the core R stats package  . See Supsamtools  from map toolbox . These poolfstat , Baypass across the genome using tools from poolfstat  for all combinations of population pairs across 500-bp sliding windows (250-bp overlap) across the genome. SNPs were called using sites with read counts between 40 and 700. Hierarchical clustering indicated that NC1 and NC2 were more closely related to their FC counterparts than to each other . We then performed Fisher’s exact tests for each of these windows to screen for significant allele frequency differences. We took the product of the −log(p) values for each block  and selected the top 0.5% of values as regions of interest. In this way, we selected for loci which diverged consistently across the blocks, assuming that inconsistent divergence may reflect drift. Location of windows of interest were annotated using the reference genome and the intersect command in bedtools  genbedtools “window”) making this comparable to our windowed approach.Using the same logic we used the auxiliary model in BayPass to identify candidate SNPs that were consistently associated with the loss of care across both blocks. Using the covariance structure among the population allele frequencies (Ω), the model explicitly accounts for the shared history of the populations, rendering the identification of SNPs potentially subjected to selection less sensitive to the confounding effect of demography . SpecifiN. vespilloides genome using the BLAST2GO (version 5.1.1) workflow to assign homologs to the Drosophila nonredundant protein databases  based on ortholog assignments obtained using Orthofinder (https://github.com/chriswyatt1/Goatee). To identify transcription factors we searched for the presence of known Pfam . Similarly, there were higher Pi values in FC compared to NC, though this effect was not present in Block 1 (D (500-bp overlapping windows) to further characterize the evolutionary forces shaping genetic diversity between populations. We show that genome-wide levels of Tajima’s D are negative, with both replicates showing a significant reduction in Tajima’s D in NC compared with FC  and Pi (π) statistics for each population across 1,000-bp nonoverlapping windows. Populations that evolved under Full Care (FC1 and FC2) had higher theta values than populations evolved under No Care (NC1 and NC2) ( Block 1 . Togethe Block 1 . We meas with FC .FST) between experimental populations  had greater levels of genetic variation, in the form of higher theta and pi diversity, than the populations where care was prevented (No Care). Previous work has suggested that social behavior contributes to genetic diversity mainly because of its effect on demography and particularly because of its influence on effective population size (Ne). Population genetic theory predicts that genetic diversity will increase with Ne and mutation rate . PreviouN/πS) and reductions in Tajima’s D, a pattern that was similar to the genome-wide differences in genetic diversity. Again, this is consistent with the interpretation that No Care populations experienced strong directional selection, while Full Care populations harbored more potentially deleterious mutations.The majority of this accumulated genetic variation is likely to be either neutral or mildly deleterious, since the majority of new mutations generally fall into either of these two categories . Indeed,Here, we follow convention in assuming that loci that diverge consistently are likely to represent adaptive genomic change, whereas inconsistent responses to the parental care treatment (No Care vs. Full Care) are due to drift. Yet alternative explanations for inconsistent responses are also possible, and this might be particularly true for traits under social selection (as opposed to abiotic selection pressures). Inconsistent patterns of genetic change across experimental blocks attributed to drift might instead reflect idiosyncratic or opportunistic responses to selection that arise through subtle variation in founding populations . This isN. vespilloides is likely to be associated with greater levels of environmental stress during development and heightened exposure to pathogens from the carrion resource , which could help cope with the increased exposure to the bacterial pathogens of the carcass nest experienced by No Care larvae. Previous work on N. vespilloides has shown that lysozyme expression is particularly heightened in parents immediately after the larvae hatch   . Furthercdysone) . This cocdysone) . This inorexin, 5-hydroxytryptamine, and cholecystokinin receptors), raising the possibility that these could represent adaptations in larvae for feeding and extracting nutrients from the carcass resource in the absence of parents  was correlated with the transition to parenting, an effect that was more pronounced in males than in females (Takeout is another gene that, despite being typically associated with feeding and circadian rhythms, has been shown to be highly expressed while parenting in burying beetles and may be involved in the transition from infanticide to larval care (oxytocin receptor and a takeout homolog (angiotensin converting enzyme was one of the most diverged genes in our analyses. This gene has varied roles from conferring immunity to regulating neuropeptide signaling (We also found changes in neuropeptides that are also involved in metabolic, homeostatic, and feeding pathways (e.g.,  parents . Previou parents , 2023. F parents , but has parents . A recen females . Takeoutval care . We foun homolog , which c homolog . Finallyignaling . Howeverignaling .Artemis and the PAXIP1 interacting protein; via transcription-assisted mutagenesis (While we show here that parental care contributes to genetic variation through its effect on selection, it is possible that the incidence of mutation is itself reduced by the loss of parental care. Mutation rates have a strong genetic basis and can vary between individuals and among populations . Given tagenesis . In otheagenesis .In short, we have shown that parental care allows genetic variation to accumulate by relaxing selection. When care is lost, a number of genetic changes quickly follow, which may be adaptive and which result in the loss of standing genetic variation. Better functional characterization of these gene targets and regulatory regions is now required to understand the genetic causes and functional consequences of the differences we have found between populations that are, and are not, exposed to posthatching care. These are key areas of future work that will help explain whether the maintenance of standing genetic variation under parental care is likely to help or hinder adaptation in a rapidly changing world.qrad039_suppl_Supplementary_MaterialClick here for additional data file.qrad039_suppl_Supplementary_Table_S3Click here for additional data file.qrad039_suppl_Supplementary_Table_S4Click here for additional data file.qrad039_suppl_Supplementary_Table_S5Click here for additional data file.qrad039_suppl_Supplementary_Table_S6Click here for additional data file.qrad039_suppl_Supplementary_Table_S7Click here for additional data file.


Neovison vison) is well-known as one of the most important sources of fur and is used as feed across the North zone of China. Using double-digest restriction site-associated DNA sequencing, this study evaluated the genetic diversity and population structure of a five color of mink populations in China (ddRAD-seq). The black mink population was found to be genetically differentiated from other color type populations, whereas a clustering of the red mink and black mink populations was observed; further, other color populations clustered separately. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that the genes with a selection signature were enriched in the melanogenesis pathway. The results of our study provide basic information on mink diversity, and theoretical concepts for the conservation and exploitation of mink breeds in China.Mink (Neovison vison) is a semiaquatic species of Mustelid native to North America that is now widespread in China. However, the knowledge of genetic diversity of mink in China is still limited. In this study, we investigated the genetic diversity and identified significant single nucleotide polymorphisms (SNPs) in mink populations of five different color types in three different mink farms in China. Using double-digest restriction site-associated DNA sequencing, we identified a total of 1.3 million SNPs. After filtering the SNPs, phylogenetic tree, Fst, principal component, and population structure analyses were performed. The results demonstrated that red mink and black mink grouped, with separate clustering of all other color types. The population divergence index (Fst) study confirmed that different mink populations were distinct (K = 4). Two populations with different coat colors were subjected to the selection signature analysis, and 2300 genes were found to have a clear selection signature. The genes with a selection signature were subjected to Gene Ontology (GO) categorization and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, the results revealed that the genes with a selection signature were enriched in the melanogenesis pathway. These study’s findings have set the stage for improved breeding and conservation of genetic resources in real-world practical mink farming.The American mink ( Neovison vison) is a semi-aquatic carnivore that traditionally originated from the Northern Hemisphere [The farm mink  are ideal molecular markers for genetic mapping and population diversity assessment , becausenes Miar  assemblenes Miar  identifines Miar . Scanninnes Miar . InspiteThis study aimed to discover genome-wide SNPs in different mink populations (color type) in China and to determine the genetic diversity and structure, and the important role of genes in different mink populations in China.A total of 97 unrelated minks were obtained from three different farms in China and included 50 white minks (WM), 20 black minks (BLM), 10 sliverblue minks (SM), 10 brown minks (BM), and 7 red minks (RM). WM, SM, and BM were from Huilongwan breeding mink farm in Yichun City; BLM was from Zhuojia mink farm in Jilin City; and RM was from Shandong mink farm in Weifang City. Blood samples were obtained from the paws of minks and stored at −20 °C. Genomic DNA was extracted from these whole blood samples using Easy Pure Blood Genomic DNA kit according to the manufacturer’s instructions, and each DNA sample was evaluated using gel electrophoresis and stored at −20 °C. Animal management and sampling procedures were performed following the standards of the Principle of Laboratory Animal Care and the guidelines prescribed by the Animal Research Committee of the Institute of Special Animals and Plants Sciences, Chinese Academy of Agricultural Sciences (Protocol code no. ISAPSAEC-2022-62M).Double digest RAD sequencing (ddRAD-seq) libraries were constructed following a modified protocol . Genomichttps://www.ncbi.nlm.nih.gov/assembly/GCF_020171115.1/) using BWA-mem v 0.7.12 [p < 10−6) were filtered out. In addition, individuals with >0.15 missing genotype were discarded from the dataset using VCFtools 35. Minor allele frequency was computed for all SNPs and the proportion of SNPs was determined for MAF ranges of <0.05, 0.05 to <0.1, 0.1 to <0.2, 0.2 to <0.3, 0.3 to <0.4 and 0.4 to ≤0.5. Functional annotation of the SNPs and indels was performed using the ANNOVAR2017 software (2017-07-16) [Each sample was assessed in terms of the quality of sequencing reads using the Fast QC software (v0.11.7) ; Low-quav 0.7.12 . High co7-07-16) .A total of 1,396,257 SNPs were used to calculate the phylogenetic distance among mink populations. The phylogenetic tree was constructed using FastTree (version 2.1.11) software to determine the evolutionary relationship among mink populations. Principal component analysis (PCA) was performed using the GCTA software (version 1.26.0). Plink was used to analyze the genetic structure of the mink populations based on different color type. The number of genetic clusters was predefined from K = 2 to 10 and repeated each K-value three times. Admixture software (Version 1.3.0) was used to calculate ΔK. Observed heterozygosity (Obs Het), observed homozygosity(Obs Hom), expected heterozygosity (Exp Het), expected homozygosity(Exp Hom), nucleotide diversity (π) and inbreeding coefficients (Fis) were calculated using the populations’ program in STACKS. The Fst values were calculated for each SNP of all pairwise subgroups using variant call format (VCF) tools. We studied the genetic structure of different mink populations using phylogenetic tree construction, PCA, and population structure analysis, whereas the genetic analysis of population structure was carried out using ADMIXTURE software (Version 1.3.0).p-values were corrected for the false discovery rate (FDR) while applying an FDR threshold of ≤0.05. Pathways meeting the criteria were considered significantly enriched pathways.Candidate genes in the sweep regions of different mink populations were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Top GO software (Version: 2.38.1) was used to perform the GO enrichment analysis and the pathway information is fetched from KEGG website. phyper is used to do the hypergeometric tests. Calculated Before quality filtering, ddRAD-seq generated 390.08G of raw data for 97 normally sequenced individuals, with an average of 4.02 Gb per sample and a range of 2.31 to 6.23 Gb. 362.63 Gb of clean data  were retained after the sequence data underwent quality filtering. Each sample received an average of 26.71 million clean reads that were retained. The number of reads on the alignment was mostly above 93.21%, the percentage of high-quality clean reads was above 94.52%, and the average effective mapping rate was above 98.86%. Hence, our sequencing data were of a high quality , with a stable GC content that ranged from 49.89 to 54.95% .A total of 1,396,257 high-quality SNPs were identified after SNP calling on 97 samples, with sequencing depths ranging from 19.05 to 20.95 . Each anWe detected deficits in all Obs values in all mink populations and the Obs values were compared with the Exp values. RM showed the lowest Exp Het, whereas the highest Obs Het was observed in BLM, indicating the occurrence of self-crossing in the populations. The intra-population inbreeding coefficient of Fis ranged from 0.2441 to 0.4402. We estimated the genome-wide nucleotide diversity using the SNP data. π values, which ranged from 0.2099 to 0.3503, demonstrated that the nucleotide diversity of BLM was the highest. The average Obs Het, Exp Het, π, and Fis were 0.1226, 0.1948, 0.2272, and 0.2308, respectively . The estSimilar patterns were shown by genetic analysis of the phylogenetic tree and PCA. The findings indicated that SM, BM and WM were grouped independently. Some minks were congregated, with RM minks clustered with BLM minks, while others distinguished themselves and created a new group A,B. The p < 0.05), including three functional terms for biological processes (BP), four for molecular functions (MF), and three for cellular components (CC). For BP terms, the cysteinyl-tRNA aminoacylation, columnar cuboidal epithelial cell growth, and sulfur amino acid catabolic process were determined to have the strongest GO connections. For the MF keywords, thiamine binding (GO: 0006772), flavin-linked sulfhydryl oxidase activity, cysteine-type peptidase activity, and melatonin receptor activity (GO: 0008502). Contrarily, CC keywords were connected to the melanosome (GO: 0042470), pigment granule (GO: 0048770), and photoreceptor outer segment. Some of the most important genes were found to be abundant in the melanogenesis pathway, cysteine and methionine metabolism, Wnt signaling route, MAPK signaling system, and phototransduction in the KEGG enrichment analysis of the genes with a selection signature. The development of melatonin and the hair structure was also linked to 12 genes, including Wnt11, Wnt5B, PSMB3, CCND1, MTNR1B, EGF, DN-EGF, WD, WIPI1, IGFII, IGFBP7, BMP6, and TGF-β  . AccordiFrom the PCA, phylogenetic tree map, and structure analyses, most animals of RM and BM populations clustered together, whereas other populations  clustered separately. It indicates that the genetic relationship of between BM and RM populations was relatively close. The standard type of American mink in nature was more brownish than the present type of standard black and standard brown, and standard black was the result of a selection of dark colors among the original dark brown wild minks . The WM To enhance the quality of the Red mink’s fur, Black minks, which were little but had silky, short guard hair and dense wool, were utilized . Our finVariation in coat color is thought to be a marker of domestication and a distinct trait of a few breeds .. In conOver a century of the occurrence of new mutations and selection on the initial wild brown and black phenotype resulted in 35 mutations and more than 100 forms from their combination . MammalsIn this study, we explored the genetic diversity, and genetic organization of different mink in China using the ddRAD-seq technology to discover SNPs at the genome level. Also, we discovered the potential genes that were associated with melanogenesis. The findings of our study offer important data for the preservation and use of Chinese mink breeds, as well as a clear direction for upcoming breeding efforts.


The artisanal octopus fishery is a great tradition and has a large economic impact in Northern Spain. Despite its importance, there is scarce genetic information for this exploited population. The uniqueness of an exploited population and the effects that exploitation may have on its long-term survival is essential information that can be obtained by studying the past and current spatial and temporal genetic patterns. The mitochondrial DNA is used here as a genetic tool to gain insight into Northeast Atlantic octopus populations and their evolutionary history. Although it is not sensitive enough to detect differences in nearby populations, it allows us to differentiate the two main lineages that originated during the Quaternary glaciations. One of the lineages is present exclusively in northern latitudes and the other mainly in the south, although, for the first time, its presence is demonstrated also in the north of the Iberian Peninsula. This implies a more continuous distribution than previously thought for this lineage. We also detect temporal changes in the distribution of the two lineages in contact zones. These changes seem to be associated with the effect of changing oceanographic conditions. Future studies on these associations could be of interest for fisheries in the scenario of global climate change.Octopus vulgaris is one of the most harvested octopus species in the world. In the Iberian Peninsula, there are several small-scale fisheries that have a long-term tradition of harvesting octopus. The Asturias fleet (in Northern Spain) has an internationally recognized MSC label for its exploitation. Of concern, genetic assessments of exploited stocks are currently scarce, which could prevent the implementation of adequate managing strategies. We use two mitochondrial regions (cytochrome oxidase subunit 1 and control region) to analyze the genetic status and evolutionary events that conditioned octopus populations’ characteristics in the Northeastern Atlantic. A total of 90 individuals were sampled from three different localities in the Iberian Peninsula as well as a location in Macaronesia. Temporal genetic analyses on Asturias and Algarve populations were also performed. Results indicated the absence of fine spatial genetic structuring but showed the Canary Islands (in Macaronesia) as the most distinct population. Our analyses detected two distinct clades, already described in the literature, but, for the first time, we confirmed the presence of the α-southern haplogroup in the Northern Iberian Peninsula. This result indicates a more continuous cline for the distribution of these two haplogroups than previously reported. Temporal changes in the distribution of both haplogroups in contact zones were also detected. Artisanal fisheries represent a source of employment and economic income for many regions around the world. Overall, 90% of all fishers recorded worldwide belong to this sector . EspeciaOne of the main issues hindering the protection of traditional fisheries is a reported lack of biological data about the fish stocks, including the absence of any type of sustainability assessment ,7. The pOctopus vulgaris Cuvier, 1797, is one of the most commercially valuable species of cephalopods, mainly fished in the Northern Atlantic, the Mediterranean and Western Africa [Charonia lampas ), bait types and socioeconomic studies [The common octopus, n Africa . Spain in Africa . Artisann Africa , making n Africa . From thn Africa , octopusn Africa  and also studies . These e studies .DNA analysis using molecular markers is a powerful tool to improve the knowledge of the species dynamics and to help in its sustainable exploitation. From the different molecular markers in use, two of the most frequently adopted are nuclear microsatellites and mitochondrial DNA (mtDNA) . The forO. vulgaris was considered a globally distributed species. However, during the past twenty years, research based mainly on mtDNA markers [O. vulgaris are in fact a species complex of morphologically similar but genetically distinct vulgaris-like species. Within this complex, O. vulgaris sensu stricto is described as a widely distributed species that occurs from the Northeastern Atlantic down to Midwestern Africa, including the Mediterranean [O. vulgaris within the Mediterranean and between the Atlantic and Mediterranean, suggesting independent management for each basin [Historically,  markers ,23,24,25erranean . Howevererranean . Supportch basin . The manch basin ,29 have ch basin ,31 obserO. vulgaris in the Northeastern Atlantic. This is especially relevant for O. vulgaris active fisheries in Northwestern Africa [These contrasting findings suggest the need to implement efforts to investigate the genetic units of n Africa ,32 and fn Africa ,33,34, bn Africa ,35. In tn Africa . This stO. vulgaris within the Northeastern Atlantic using two mitochondrial markers (cytochrome c oxidase subunit I (cox1) and control region (CR)) and give insights into whether the mtDNA is a useful tool to implement scientifically based management strategies for the sustainable exploitation of this species; (2) to unravel demographic past events that may have conditioned the current genetic patterns of this valuable species.The objectives of the present study were (1) to address, for the first time, the presence of spatial and/or temporal genetic structures of Octopus vulgaris were collected from four different localities in the Northern Atlantic Ocean: two in the Northern Spanish Iberian Peninsula , one in a continental locality in Algarve, Southern Portugal, and one in the archipelago of the Canary Islands (Macaronesia). All samples (n = 15 per site) were collected by artisanal fisheries during the 2020–2021 fishing season, except those from the Canary Islands, which were collected during the 2018–2020 period. Another 30 samples from the 2006–2007 fishing season from two of the previous localities  were available, allowing us to test for the existence of genetic changes on a temporal scale  and the hypervariable and non-coding mitochondrial control region (CR). Primers used for each locus were OvulCOX11F (5′-TGAATATTYTCAACAAATCAYAAAGAYATTGG-3′) and OvulCOX12R (5′ GGGTGACCAAARAATCAAAATARRTGTTG-3´) for cox1 and OvulCR3F (5′-GAAAATCTTTCGTGCAAATTACACCACA-3′) and OvulCR4R (5′ TGTTAATGGTCAGGGTCTAAATTCAACTAAAT-3′) for the CR [2 concentration). They were performed in a final volume of 40 µL containing 2.5 mM of MgCl2, 200 μM of dNTP, 0.5 μM of each primer (forward and reverse), 10X Buffer (MgCl2 free), 0.5 units of Taq Polymerase  and 2.5 µL of a 1:50 DNA dilution. Amplification was carried out in a PE GeneAMP PCR 9700 thermal cycler  with an initial step of 3 min at 95 °C followed by 35 cycles  and a final elongation step of 72 °C for 7 min. Products of amplification were checked in a 1% agarose gel and sent to Macrogen Spain for purification and posterior sequencing using the Sanger method (both strands for each amplicon were sequenced). Sequences were analyzed and assembled using Sequencher 4.9  and manually checked and edited. Cox1 sequences were checked for species identity in the BOLD database [Two mitochondrial loci were analyzed: the cytochrome c oxidase subunit I  and AMOVA tests , were inferred for the concatenate region in ARLEQUIN 3.5 [Basic genetic parameters such as the number of polymorphic sites, haplotype (h) and nucleotide (π) diversity estimates, for each loci separately and for the concatenated sequence, were calculated using DNASP 6.0. . DiverseQUIN 3.5 . One hapQUIN 3.5 . The ManQUIN 3.5 .Octopus sinensis d’Orbigny, 1841) as an outgroup (NC052881.1). Neighbor joining (NJ), maximum parsimony (MP), maximum likelihood (ML) or Bayesian approaches were used to construct phylogenetic trees. An NJ tree based on the Jukes–Cantor distance was constructed with MEGA X. The topology of the tree was further investigated by model-free maximum parsimony (MP) as implemented in MEGA X. The MP tree was obtained using the tree-bisection-reconnection algorithm with search level 3, in which the initial trees were obtained with the random addition of sequences (10 replicates). The optimal substitution model for all datasets was estimated using the MODELS tool in MEGA X, where the Hasegawa Kishino Yano (HKY) model [We investigated the phylogenetic relationships of these sequences using the sequence of the East Asian common octopus (Y) model  showed tY) model .To obtain a better representation of the α haplogroup in order to gain better knowledge about the phylogenetic relationships between the two different haplogroups detected, extra data for the CR locus from a previous work by Quinteiro et al.  were addcox1 and CR from 90 individuals (15 per population/fishing season). Three different alignments were created: one for the coding sequence cox1 of 646 bp length, one for the non-coding sequence CR of 653 bp length  and the combined dataset that contained 1299 bp (1292 indels excluded). All samples were unambiguously identified as O. vulgaris sensu stricto after cox1 analysis. The sequences for the different haplotypes detected for CR and cox1 loci were submitted to GenBank and are available with the submission numbers OR351990-OR352006 and OR346370-OR346378, respectively.We amplified and sequenced fragments of Cox1 alignment of the 90 individuals resulted in eight different haplotypes defined by 12 variable sites (three of them singletons) and all of them corresponded to synonymous substitutions. The haplotype diversity (h) was 0.659 and the nucleotide diversity (π) was 0.00298. CR displayed a total of 17 different haplotypes defined by 37 polymorphic sites. This region was a non-coding site so higher values of diversity than the coding cox1 sequence were expected. The global haplotype diversity was h = 0.793 and the nucleotide diversity detected was π = 0.00866. For the concatenated dataset (cox1 + CR), we found 21 different haplotypes (49 variable sites). Haplotype diversity was h = 0.843 and nucleotide diversity π = 0.00605. All three datasets showed concordant results; the Canary Islands sample had the highest haplotype and nucleotide diversities, and the Algarve 2006–2007 sample showed the lowest values. For the CR and concatenated dataset, the samples from Galicia showed the same haplotype diversity as the Canary Islands samples but lower nucleotide diversity (iversity .cox1 sequences (The haplotype network built on the concatenated dataset showed two highly divergent haplogroups separated by at least 26 mutations (sequence divergence of 2.01%) a. Haplogequences . A summap = 0.017). Calculations for the α haplogroup were not performed since this haplogroup was present at a very low proportion or not present at all for the locations examined, except the Canary Islands. Haplogroup α was present in one individual from Asturias 2006–2007, three from Algarve 2020–2021 and eight from the Canary Islands (Macaronesia). Within this group, two small subclades seemed to be present, separated by at least nine mutations (sequence divergence of 0.69%); the first subclade included all the individuals from Macaronesia and one sample from Algarve 2020–2021, and the second subclade included one individual from Asturias 2006–2007, two individuals from Algarve 2020–2021 and the individual from Turkey, Mediterranean . Overall, results revealed global significant genetic differentiation among all the populations studied . Moreover, the Mantel test revealed a significant positive correlation between the genetic and geographic distance . However, there was not a defined population structuring pattern. For instance, clustering groups by aggrupation suggested by pairwise ϕST values (Canary Islands population vs. the rest) revealed non-significant differences among groups , but significant differences were found among populations within groups . Most of the genetic differentiation was explained between individuals, giving significant differences . When the same analysis was repeated but removing the Algarve 2006–2007 sample , no within-groups differences were detected  and, once again, the ϕCT values were not significantly different from zero among the groups.To study the presence of a potential genetic structure within the sampled populations, an AMOVA test was performed using the combined region of both loci  found in populations within clade α matched with the hypothesis of glaciation refugia suggested by Quinteiro et al. . HoweverFor haplogroup β, our data matched with previous studies . AlthougPrevious works showed a robust genetic structure within the Northeastern Atlantic associated with the distinct distribution of the two different haplogroups detected ,31. HaplST values statistically different from zero. Former studies including the use of microsatellites [Sepia officinalis Linnaeus, 1758) [O. vulgaris in other geographic sites was found to be more related to oceanographic patterns and not necessarily to geographic distance [O. vulgaris spend an average 47–54 days in the water current until becoming adults, and even less time in tropical waters, as larvae feed faster and hatch earlier [Although the absence of fine spatial genetic structuring was observed, we found the Canary Islands population to be significantly different from most of the other populations, with ϕtellites ,30,35 has, 1758) . We founs, 1758) , but alsdistance ,28,47. T earlier . During  earlier . The Can earlier ,53. In ap > 0.05) within the Iberian Peninsula. This could be related to the reported higher larvae dispersal in temperate waters, where they spend more time in the water current, which may homogenize populations [Finally, we did not find significant differentiation between continental harvested populations . No significant temporal differences were found between 2018 and 2021 (two generations) for the rest of the locations, except for the samples from Puerto de Vega (Asturias) collected between 2007 and 2018, with respect to the last sampling collected during 2020–2021 in the same locality [In small-scale fisheries from the Northern Iberian Peninsula, studies on the genetic status of octopus populations are scarce and mainly focused on spatial structure, but Pirhadi et al.  recentlylocality . In our O. vulgaris, where the greatest abundance and representatives of this species are concentrated [O. vulgaris are characterized by a preference for warmer temperatures [In the Southern Iberian Peninsula, the region of Algarve is reported to be the main Portuguese recruitment region of entrated . Althougentrated , we deteentrated . For insentrated ,60 and ieratures . Regardieratures . The hyderatures . The sameratures . The cireratures . It is keratures .O. vulgaris (α and β) in the past. The use of two mitochondrial markers together proved to be useful to detect the different lineages and to infer the presence of the reported ancestral clade α in northern latitudes, identifying for the first time the presence of this clade in the Iberian Peninsula and supporting the idea of a second glacial refugia in the Mediterranean Sea for this valuable species. However, further studies are needed, increasing the sampling size and number of locations, to further elucidate the evolutionary history of the species.This study allowed us to estimate the genetic variation and differentiation patterns of populations from the Northeastern Atlantic using mtDNA and it gives insights into the distribution and legacy of the two reported lineages of Regarding the present status of the populations, we did not detect fine spatial genetic structuring using mtDNA but we found differences, probably associated with the distinct distributions of the two clades. The Canary Islands population (showing the greatest frequency of the southern clade among the rest of the sites) was significantly distinct, matching with the hypothesis of isolation by distance and supporting the key role that the oceanographic conditions may have in the restriction of gene flow and the singularity of the Macaronesia area. Nevertheless, the observed lack of differentiation when including all the sampled locations differed from the significant genetic structuring found when studying the same populations but using nuclear markers (microsatellites), suggesting that mitochondrial DNA may not be sensitive enough to update a continuous fishery strategy since it may fail to detect spatially different managing stocks if they are not very distant. Instead, it may be useful to detect temporal changes in the distribution of the two clades in areas of contact—for instance, the Atlantic and Mediterranean (reflected in the frequency of each clade in specific populations)—and associate them with the effect of changing oceanographic conditions or other specific events related to global climate change.