Salamandra salamandra. This species shows an ancestral (larviparity: large clutches of free aquatic larvae), and a derived reproductive mode . Our results confirm the existence of multiple paternity in pueriparous salamanders. Furthermore, we show the evolution of pueriparity maintains, and even increases, the occurrence of multiple paternity and the number of sires compared to larviparity, though we did not find a clear effect on genetic diversity. High incidence of multiple paternity in pueriparous populations might arise as a mechanism to avoid fertilization failures and to ensure reproductive success, and thus has important implications in highly isolated populations with small broods.The reduction in fecundity associated with the evolution of viviparity may have far-reaching implications for the ecology, demography, and evolution of populations. The evolution of a polygamous behaviour (e.g. polyandry) may counteract some of the effects underlying a lower fecundity, such as the reduction in genetic diversity. Comparing patterns of multiple paternity between reproductive modes allows us to understand how viviparity accounts for the trade-off between offspring quality and quantity. We analysed genetic patterns of paternity and offspring genetic diversity across 42 families from two modes of viviparity in a reproductive polymorphic species,  For example, viviparous species often show an increased parental investment compared to oviparous ones because they produce larger and more developed offspring that are protected from external pressures for longer periods within the mother7. Conversely, viviparity is frequently associated with a reduction in clutch size and fecundity9. This can affect population effective size (Ne) which ultimately may decrease species genetic diversity11, compromising population viability and adaptive potential to respond to changing environmental pressures13. Polygamous mating systems, such as polyandry, can minimize the genetic effects resulting from this loss of fecundity. For instance, the ability of females to produce clutches sired by several fathers  may not only increase within-family genetic diversity and Ne, but also increase reproductive success through the avoidance of genetic incompatibilities17.The evolution of viviparity entails pronounced changes in individuals’ reproductive biology and behaviour and, by extension, on population dynamics19, and MP has been detected in most life histories21. However, the reduction of fecundity resulting from the emergence of a novel reproductive mode (e.g. viviparity) might alter the patterns of MP (e.g. its frequency and the number of fathers per clutch) compared to the ancestral reproductive strategy (e.g. oviparity). Although viviparity evolved in each of the three extant orders of amphibians8, exploring the relationship between reproductive strategies and patterns of paternity is challenging. This is because reproductive strategies rarely vary at the intra-specific level and comparisons involving phylogenetically distant species may introduce substantial bias and, consequently, prevent robust conclusions. In that sense, the intra-specific polymorphism in reproductive modes exhibited by the fire salamander  makes it a good system to investigate the potential changes in MP levels and offspring genetic diversity related to the evolution of a novel reproductive strategy.Amphibians exhibit a great diversity in reproductive strategiesSalamandra salamandra exhibits internal fertilization and two discrete modes of viviparity: (1) an ancestral and more geographically and phylogenetically widespread strategy, larviparity, in which females lay free aquatic larvae22; and (2) pueriparity, which is geographically restricted and independently evolved in two subspecies endemic to the Iberian Peninsula , and in which females give birth fully metamorphosed juveniles24. As reported in previous studies, larviparous individuals have on average larger brood sizes (ca. 20–80 aquatic larvae) than pueriparous ones, in which females give birth to ca. 1–35 juveniles, which are generally larger and heavier than aquatic larvae28. These differences in the offspring are due to several heterochronic processes related to the shift to pueriparity, such as the incomplete fertilization of ovulated eggs, accelerated and asynchronous rates of embryonic development, and active feeding on unfertilized eggs (oophagy) and less developed siblings (adelphophagy)25.S. salamandra is a polygynandrous species and MP was reported in one larviparous population from Germany of the subspecies S. s. terrestris30. Sperm from multiple mates are accumulated in the spermatheca through a topping off mechanism31, in which first mates sire the highest proportion of a female’s clutch30. Contrary to larviparous salamanders, the presence of MP in pueriparous females is yet to be confirmed. However, one may hypothesize that some of the ontogenetic processes exclusive to pueriparous S. salamandra may potentially affect patterns of MP compared to their larviparous counterparts. For example, as shown in other species34, intrauterine cannibalism occurring exclusively among pueriparous siblings (both oophagy and adelphophagy25) reduces brood sizes26, but it can also decrease the number of contributing fathers, even if they managed to successfully fertilize some of the female’s eggs.Previous studies produced evidence that S. salamandra ; and 2) to compare levels of MP (i.e. incidence of MP and number of sires) between reproductive modes. We hypothesize that pueriparous populations show smaller levels of MP than larviparous ones due to their smaller brood size26, the topping off mechanism of fertilization30, and the presence of intrauterine cannibalism25. As a reference of MP for larviparity we used the subspecies S. s. terrestris, which occurs throughout central Europe, and is phylogenetically close to S. s. gallaica35. As secondary objectives, we also 3) compared patterns of MP between pueriparous S. s. bernardezi and S. s. gallaica, hypothesizing a higher incidence of MP and number of sires in the latter, as a result of their larger body size and a more recent evolution of pueriparity, and 4) evaluated whether a higher number of siring males increased the fecundity of females and the genetic diversity of their offspring36. Finally, and as pilot study, we compared patterns of MP between natural births and dissections at early developmental stages in pueriparous populations, expecting a lower number of sires per clutch in natural births due to the occurrence of intrauterine cannibalism at later stages of pregnancy.Here, we used genetic data (microsatellite genotyping) to address two main objectives: 1) to evaluate the presence of MP in the two known independent origins of pueriparity within S. s. bernardezi populations  and one of the two extant pueriparous S. s. gallaica populations   and S. s gallaica, respectively, and transported them to laboratory facilities at the University of Oviedo  and to the Research Centre in Biodiversity and Genetic Resources . Individuals were placed in individual terraria  containing coconut fibre as substrate, a container with water, moss, and shelters (bricks or barks). We fed them twice a week with crickets (Acheta sp.) or flour worms (Tenebrio sp.). After parturition, both females and their offspring were released at their place of capture.We sampled 18 pueriparous females from two  8) Fig. . During S. s. bernardezi population and four from Ons) at the earliest gestation stage possible and sacrificed them by an overdose of anaesthesia . After dissections, we recorded the uterus (i.e. right or left), clutch size, and the stage of development of each offspring . Each individual was stored in pure ethanol for DNA analysis. Salamanders were captured and processed under collection permits provided by regional or national governments , and the study was approved by the ethics committee Research Ethics Committee of the University of Oviedo (PROAE 10/2017). All applicable national and institutional guidelines for the care and use of animals were followed.To explore whether the number of siring males varied across gestation stages, we sampled eight more females .We used microsatellite markers to infer patterns of MP (i.e. number of sires and incidence of MP), and characterize within-family genetic diversity. Tissue samples for DNA analysis were collected from a toe-clip in the case of females, and a tail-clip from juveniles. We genotyped 11 microsatellites43, a software which implements a maximum likelihood method to infer parentage based on individual multilocus genotypes. We set the species as dioecious and diploid, assumed polygamy for both sexes, no inbreeding, the maternal genotype and maternal sibship was considered known a priori, and no candidate father genotype was included. We applied the maximum likelihood approach with high likelihood precision and two very long runs with different random number seed in each population separately. We provided neither known population allele frequency nor sibship size prior. As we were very conservative during allele scoring and re-amplified a number of samples to check for possible errors (see Supplementary Information), we assumed a minimum error rate of 0.0001. To characterize the genetic diversity of each brood, we calculated the observed heterozygosity (Ho), mean number of alleles (NA), and mean relatedness of offspring per female (Roffsspring) in GenAlex v 6.50344. As NA could be highly affected by differences in brood size, we calculated the unbiased allelic richness (AR) using a rarefaction method implemented in HP-RARE45.To infer the number of siring males in each family we estimated the most likely number of fathers in COLONY 2.0.6.4.offspring) and the mean number of fathers (Nfathers) among the studied subspecies, modes of reproduction, and stage of gestation  using permutation tests with 1,000 resamplings without replacement (α = 0.05). Additionally, for each subspecies, we used non-parametric Kendall correlations to test the association between MP (Nfathers) and variables related to female’s fecundity (Noffspring), and offspring genetic diversity . Because the mean number of alleles (NA) is often highly affected by Noffspring, we also tested for the correlation between both variables to enable us to examine whether a putative high correlation between Nfathers and NA is an artefact of the varying Noffspring observed among the studied females. All statistical analyses were performed in R software46.We compared the mean clutch size  or high presence of missing data , resulting in a final dataset of 587 offspring from the 24 larviparous females. All other individuals were unambiguously assigned to their mothers.S. s. bernardezi, S. s. gallaica, S. s. terrestris), with incidence of MP varying between 54 and 88%  and Nfathers ranging between 1 and 7 in pueriparous populations, and 1 and 5 in the larviparous population  of the offspring. The S. s. bernardezi population of Oviedo and the S. s. gallaica population of Ons exhibited the lowest genetic diversity and the highest relatedness among the studied populations  and compared with both pueriparous S. s. gallaica and larviparous S. s. terrestris. Permutation tests revealed S. s. gallaica  exhibited a significantly higher Noffspring (P = 0.001) and Nfathers (P = 0.001) than S. s. bernardezi. Comparisons involving different reproductive modes showed that S. s. terrestris  has a significantly higher Noffspring than S. s. bernardezi (P = 0.001), but not than S. s. gallaica (P = 0.869). The Nfathers was similar between S. s. terrestris and S. s. bernardezi (P = 0.187), while the offspring of S. s. gallaica females appeared to be sired by a higher number of fathers than their larviparous counterparts (P = 0.005)  Table .P > 0.05) in Noffspring or Nfathers between both sampling methods , therefore, we also tested the association between Nfathers and NA. Correlation tests revealed a significant positive relationship between Nfathers and female’s fecundity in the larviparous population and the pueriparous S. s. gallaica, but not in pueriparous S. s. bernardezi . Moreover, benefits of polyandry may vary among reproductive modes56. In less fecund reproductive modes, female investment per offspring is generally high, and reproductive failures due to genetic incompatibilities imply higher costs compared to more fecund strategies57. Within S. salamandra, larviparous progeny rely solely on their yolk provisions, but in pueriparous populations, fecundity is reduced in favour of a lower number of more developed descendants because nutrient provisioning occurs through the availability of both arrested eggs and less developed siblings27. Accordingly, reproductive costs due to genetic incompatibilities or mating with sterile males are likely higher in pueriparous females and, therefore, multiple mating (and MP) may be under selection to reduce these costs58. Furthermore, in accordance to previous studies we found a similar pattern of reproductive skew towards a dominant male in polyandrous broods in both reproductive modes, probably resulting from a topping-off mechanism of sperm storage31, in which the first mate fertilizes the majority of eggs30. Although we found no significant differences in clutch size between the larviparous S. s. terrestris and the pueriparous insular S. s. gallaica, the larviparous mainland S. s. gallaica generally have larger clutches26.Contrary to our expectations, the shift to pueriparity seems to maintain, and even increase, the incidence of MP and the number of sires per clutch Table ; Fig. 2 S. s. bernardezi and S. s. gallaica26, clutch size, number of fathers, and incidence of MP are higher in the latter , which may have led to the retention of some ‘larviparous’ traits associated with reproduction. Additionally, the population-specific traits of this insular population and differences in evolutionary history 60 may have also contributed to the differences in patterns of paternity observed between insular and continental pueriparous populations. Indeed, the particularly low levels of genetic diversity and higher levels of inbreeding observed in Ons60 may increase the risk of reproductive failures and, therefore, MP in Ons may be under selection to increase reproductive success16. Moreover, we found in this population the highest number of males (7) siring a single clutch in S. salamandra, which is remarkable even at the wider taxonomic spectrum of internally fertilizing vertebrates62. Nonetheless, further research is needed to understand whether MP boosts reproductive success in the fire salamander, and its relationship with other population traits, such as inbreeding.Although similar heterochronic processes are thought to mediate pueriparity in both er Table . The difNe/N ratios and relatively high levels of genetic diversity64, such as for example, in a small pueriparous population of S. s. bernardezi65, and in an overexploited population of rockfish66. Our results appear to corroborate the aforementioned premises; a higher number of fathers appears to be associated not only with an increase in allele diversity within S. s. gallaica and in the larviparous population, but also with a reduction in the offspring genetic relatedness in S. s. terrestris. This potentially suggests MP boosts genetic diversity, though the negative relationship observed between Ho and Nfathers in S. s. bernardezi, together with the reduced sample size, call for caution when interpreting these results.Salamander males do not provide parental care or extra resources to females or their offspring. However, females may obtain genetic benefits from polyandry. Multiple paternity has been suggested as a mechanism of genetic compensation that helps maintaining high 67. We detected a positive relationship between the number of sires and the number of offspring in the larviparous population . This pattern holds in the pueriparous S. s. gallaica, but not in S. s. bernardezi, suggesting that small sample size and other factors not considered in this study can be also influencing fecundity, such as the body size of females and offspring8, thus preventing us from making robust predictions about the relationship between polyandry and clutch size. In addition, it is worth considering that in pueriparous systems, the high production of aborted eggs and cannibalistic events reduce brood size68, and thus, this variable likely misrepresents the amount of successful fertilizations.Another potential benefit of polyandry is an increase in clutch sizeS. atra species, discordances between the number of mating males and sires are expected because only one or two completely developed offspring are delivered after a long period of gestation over which the main source of nourishment consists on aborted eggs69.Finally, we did not detect substantial differences in clutch sizes or the number of sires between natural births and dissections, although it should be acknowledged that most dissections were performed at a relatively advanced stage of pregnancy. Thus, sampling more females at earlier stages of pregnancy, where most arrested eggs were not yet cannibalized, will be crucial to clarify how ontogenetic processes associated with pueriparity affect the incidence and frequency of MP. For instance, in the polygamous pueriparous S. salamandra. Specifically, we showed pueriparous populations of S. salamandra exhibit identical or higher rates of multipaternity, even though their fecundity is lower. Nevertheless, we cannot rule out that some other factors may have also influenced our results. The lack of replicates for both larviparous populations and the pueriparous S. s. gallaica limit our ability in disentangling the effects of population-specific traits and reproductive mode in the observed patterns of multipaternity. Specifically, our data do not allow us to evaluate accurately whether other ecological, geographical and demographic traits influence MP72. Indeed, despite the potential benefits that MP entails in an isolated and inbred population, the high rates of MP observed in the insular population of Ons can reflect a relaxation of the potential constraints determining the acquisition of mates 74. Hence, future studies should extend sampling to cover as much diversity within the species as possible and consider the potential effects of geographic and populational variability on MP.The present study constitutes the first step towards the understanding of the potential relationship between MP and alternative life histories in Overall, this study constitutes a relevant contribution to the understanding on how reproductive strategies evolve to account for the trade-off between offspring quality and quantity. Although other factors might be involved, our results appear to suggest the evolution of a derived reproduction mode may affect other traits to compensate the loss of fecundity and ensure reproductive success.Supplementary information


This study aims at determining the competencies of Korean nurses in prenatal genetic nursing.First, a 3-round Delphi survey was conducted to establish prenatal genetic nursing competencies. Second, a prenatal genetic nursing education program (PGNEP), incorporating the findings from the Delphi survey, was designed. Third, a single group pre- and post-quasi-experimental study at a PGNEP workshop was conducted to assess the effectiveness of the integration of the competencies into the PGNEP with the measurements of knowledge about prenatal genetic testing and nursing (K-PGTN) and information needs about prenatal genetic testing and nursing (I-PGTN). Finally, the identified competencies were reexamined for their clarity.Based on the Delphi survey 78 competency components were identified. The components were then classified under 10 categories, which were organized under 4 domains. The domain of “experiential genetic nursing knowledge” and the domain of “ethics and law” were ranked as the first and the second in significance. The quasi-experimental study showed that the mean scores in K-PGTN were significantly increased from 8.19±2.67 to 11.25±2.51 (P<0.001). The mean scores of “ethics and law” in I-PGTN decreased significantly (P=0.023). The headings of 4 categories and 2 domains were revised.This study identified competencies for prenatal genetic nursing and nursing education in Korea. There is a need for nursing instructors and researchers to improve the competencies of nurses in the identified areas. Particular emphasis should be placed on experiential nursing knowledge and on ethics and law related to prenatal genetic nursing. Regardless of the academic preparation, position, or clinical specialty of practicing nurses, their roles and duties have dramatically changed because of advances in genetics . NursingPrenatal genetic technologies have been rapidly integrated into prenatal health care practice. Non-invasive prenatal testing (NIPT) and preimplantation genetic diagnosis are now relatively common clinical procedures. From an ethical point of view, particular concerns include the termination of pregnancy, autonomous decision making, and respect for life. The development of prenatal genetic technology, however, has created a particular kind of concern in Korea. Recent demographic changes in Korea have necessitated comprehensive prenatal genetic nursing for many pregnant women. The reason is evident and the situation a little short of urgent. In Korea in 2016, the median age of first-time mothers (the women who gave birth for the first time) was 31.6 and the median age of the women who gave birth was 32.6. This is the highest among Organization for Economic Co-operation Development countries . Almost The study aimed to determine competencies for Korean nurses needed in prenatal genetic nursing and nursing education. Specifically, it aimed to identify the key area of competencies in order to facilitate more efficient education for nurses. The findings from the study can help to improve Korean prenatal genetic nursing and education. The results will be a good support to add prenatal genetic nursing competency to the continuous professional nursing education.The proposal for the project was approved by the ethical review board at the Daejeon University, Korea . Informed consent was obtained from all of the participants in the Delphi survey and quasi-experimental study.To establish a preliminary list of competencies, a 3-round Delphi survey was conducted. A single group pre- and post-test quasi-experimental study was conducted to measure the effectiveness of the prenatal genetic nursing education program (PGNEP). Measuring the effectiveness enabled the validation of the findings of the Delphi survey.Twenty medical and nursing professionals participated in the Delphi survey: 8 physicians (40.0%), 7 nursing faculty (35.0%), 4 clinical nurses (20.0%), and 1 genetic counselor (5.0%). Physicians and nursing faculty comprise 75% of the participants. Physicians who treat patients with possible prenatal genetic problems are most knowledgeable about services that need to be provided to such patients. On the other hand, nursing faculty know which competencies nurses need to master in the area. The mean age of participants in the Delphis survey was 42.00±10.15. Thirty-two nurses participated in the quasi-experimental study. The average age was 43.91±10.37. Eighteen participants (56.3%) held a doctoral degree and 7 (21.9%) held a bachelor or master’s degree in nursing. Thirteen participants (40.6%) were working at a hospital and 19 (59.4%) were nursing educators .Diagram of the study process was presented in The first component of the first stage was a 3-round Delphi survey. It was conducted from June 2012 to July 2013. In the first round of the Delphi survey 5 open questions were asked in relation to prenatal genetic nursing and education . Its EngTwo more surveys were conducted to further validate the list of competencies and to establish the relative rankings among the 10 categories. Subsequent to the third round of the Delphi survey, a framework for the quasi-experimental study was developed and a PGNEP workshop was designed in May 2013. The design was the result of a collaborative effort, with the first and the second authors receiving advice and feedback from 2 external experts: a medical professor at the department of obstetrics and gynecology of Seoul National University, and the President of Korean Society of Genetic Nursing in 2013. During the designing stage of the workshop, a new prenatal genetic test, cell-free fetal DNA or NIPT, was introduced into Korean prenatal genetic nursing practice. Instruction on it was included in the PGNEP workshop .At the second stage, a quasi-experimental study at a PGNEP workshop was conducted from August 19 through August 21, 2013 on Chung-Ang University campus in Korea. The 32 participants were recruited through announcements on the homepages of major Korean nursing academic societies and the Korean Nurse Association. A 3-day PGNEP workshop was run and a quasi-experimental study conducted. Thirty-two nurses participated in the workshop and the quasi-experimental study. Three-day prenatal genetic nursing educational program (PNGEP) syllabus is presented in Finally, for additional validation of the outcomes of the 2 studies, one of the external experts, the President of Korean Society of Genetic Nursing, vetted the relevance of the 10 categories and 4 domains. With her feedback, refinement of the competency components, the categories, and the domains was affected. This occurred from January 2015 through December 2018.The quasi-experimental study served 2 purposes. The first was to assess changes in competency levels after the PGNEP workshop. Such assessment was needed to evaluate the effectiveness of the integration of the competencies into the PGNEP. The second purpose was to determine participants’ satisfaction with the framework of the PGNEP. Changes in competency levels were assessed in 2 areas: “knowledge about prenatal genetic testing and nursing (K-PGTN)” and “information needs about prenatal genetic testing and nursing (I-PGTN)”. These 2 measurement tools were based on previous research on the knowledge and information needs of nurses and pregnant women about prenatal genetic screening and diagnosis ,12. HoweThe I-PGTN was measured by 21 test items. This tool was used under the Creative Commons license CC-BY. The items fell within 4 domains: The domain of basic genetic knowledge included 3 items; the domain of ethics and law 3 items; the domain of experiential genetic nursing knowledge 4 items; the domain of prenatal genetic testing knowledge 11 items. The participants responded on a 5-point Likert scale. Higher scores indicated greater information needs for an item. Cronbach’s α was 0.96–0.99.Participant satisfaction level with the program framework and content was measured on 5 of the 9 items on a 5-point Likert scale, and on 3 of the open questions. The measurment tool for the participant satisfaction was crafted by the first and second authors. Higher scores indicate greater satisfaction with program content and framework.Finally, the identified competency components, categories, and domains were refined by the researchers and confirmed by an external genetic nursing expert. Four researchers  vetted the conceptual clarity of each component, the validity of grouping components into categories and domains, and the relevance of their headings.http://www.gpower.hhu.de/) [According to the posthoc power analysis for paired t-test based on given effect size 0.5, alpha error probability 0.05, and total sample size 32, power was 0.869  .A qualitative content analysis of the outcomes of the first round of the Delphi survey was conducted. Descriptive statistics were used to measure the outcomes of the second and third rounds of Delphi survey, while only a paired t-test was used to measure the outcomes of the quasi-experimental study. The outcomes of descriptive statistics and paired t-test were analyzed with IBM SPSS Statistics ver. 27.0 .The study resulted in the identification of 78 competency components , 10 cateThe PGNEP was designed on the basis of the 10 categories, with an emphasis on the 3 top-ranked categories. The knowledge category and the value category thus were the foci for the 3-day workshop .After participants completed the PGNEP workshop, the mean score of knowledge (K-PGTN) significantly increased from 8.19±2.67 to 11.25±2.51 (P<0.05) . The meaFinally, the identified competency components, categories, and domains were refined by 4 researchers  and confirmed by an external genetic nursing expert. Refinement resulted in changed headings for 4 categores within the domains of experiential genetic nursing knowledge and ethics and law, as well as the present headings of expeiential genetic nursing knowledge and ethics and law. The final validations came from the President of Korean Society of Genetic Nursing in 2013.The Delphi survey was conducted with prenatal genetic nursing experts. The outcomes of the study establish a list of 78 competencies for prenatal genetic nursing.First, Korean nursing educators and nurses have known that nurses in prenatal genetic nursing should be better educated; advances in genetic technologies alone long ago made that evident. But the need for more, new, and better education is all the more urgent because of the dramatic shift in the age at which Korean women are now giving birth ,10,14. ISecond, the Delphi survey identifies the most significant domains for competencies as those of knowledge and value. “Experiential genetic nursing knowledge” and “ethics and law” as the 2 most vital domains. “Experiential genetic nursing knowledge” includes 2 sub-categories—knowledge from case study and practicum and clinical genetic nursing knowledge, which are necessary for nurses’ communication with patients and their families and medical and emotional support for them (Supplement 3). In other words, “experiential genetic nursing knowledge” is mainly concerned with knowing experientially how to communicate with, educate, and counsel pregnant women. This implies that clinical genetic nursing knowledge needs to be acquired through case studies and practicums .Information needs for all categories decreased, but not all of them significantly; the information need for “ethics and law” did decrease significantly. This latter outcome implies that the need for “ethics and law” was largely satisfied by the program. The shortness of the workshop may explain why the information needs for other domains did not decrease significantly.One subscale, “ethics and law”, should be understood in terms of value, as opposed to factual knowledge, whether technical or not. At base, value is focused on good and bad, right and wrong, legal and illegal. But factual knowledge and value knowledge are intertwined in all healthcare practice, and value itself is idle without knowledge of value. Value-knowledge is central to prenatal genetic nursing. It includes knowledge of ELSIs related to prenatal genetics.The study demonstrates the need for value competency in prenatal genetic nursing. That means that, nurses need values education as well as experiential genetic nursing knowledge. They need but currently lack the capacity to reason, in a responsible, effective, and value-sensitive way, on prenatal genetic ethical issues. Such a capacity is requisite for the capacity to support patient decision-making.The case at hand is particularly pointed in the regard. In Korea, termination of pregnancy, due to fetal anomaly, is legally prohibited by the Mother and Child Health Law. A patient’s decision to terminate implies illegal activity, which may harm the patient herself and the fetus. But the decision to terminate is never simple. A patient may be in a unique personal, cultural, or religious situation which may lead to illegal termination ,10,12.Third, a framework for a PNGEP is in place. Four domains for structuring a PGNEP, with a special emphasis on the domains of “experiential genetic nursing knowledge” and “ethics and law”, have been developed.The quasi-experimental study thus supported the validity of the list of competencies that had been identified. It was the participants’ satisfaction with the PGNEP that provided such support. The participants appreciated the value of experiential genetic knowledge and the importance of nurse’ values and ethical decision-making abilities. Such satisfaction also affirms the effectiveness and value of the PGNEP itself. The PGNEP provided at least some needed knowledge of prenatal genetic screening and diagnostic testing. The categories and domains of competencies determined the framework and content of the workshop.This study has potential limitations. First, the measurement tools used were drawn from previous research. They might not be perfect for the specific research pursued here. Ideal would be to develop new tools specifically for the subject area. However, previous research was in a similar subject area, and the measurement tools used were certainly relevant and yielded significant results. Second, the competency components, categories, and domains may change in response to new technology and changing social and political circumstances. The competency components identified are the products of Korea’s unique cultural, social, political, and legal circumstances. Caution is thus needed in generalizing the study’s findings and extending them to other communities.A list of 78 competencies for prenatal genetic nursing and a framework for effective PGNEP have been identified. The framework focuses on experiential genetic nursing knowledge and value education. A PGNEP which integrated such competencies is shown to be effective and valuable. Nursing educators should include instruction in these competencies into nursing curriculums. But it is also vital for nursing researchers to refine the list of competencies identified and to build upon the framework of the PGNEP developed. Findings of this study will be able to provide the supporting evidence to include the prenatal genetic nursing compentency to the continuous professional nursing education.


Zingiber species, selfing Zingiber corallinum and outcrossing Zingiber nudicarpum. Comparisons of the genetic structure of species from unrelated taxa may be confounded by the effects of correlated ecological traits or/and phylogeny. Thus, we possibly reveal the differences in genetic diversity and spatial distribution of genetic variation within metapopulations that relate to mating systems. Compared to outcrossing Z. nudicarpum, the subpopulation genetic diversity in selfing Z. corallinum was significantly lower, but the metapopulation genetic diversity was not different. Most genetic variation resided among subpopulations in selfing Z. corallinum metapopulations, while a significant portion of variation resided either within or among subpopulations in outcrossing Z. nudicarpum, depending on whether the degree of subpopulation isolation surpasses the dispersal ability of pollen and seed. A stronger spatial genetic structure appeared within subpopulations of selfing Z. corallinum potentially due to restricted pollen flow and seed dispersal. In contrast, a weaker genetic structure was apparent in subpopulations of outcrossing Z. nudicarpum most likely caused by extensive pollen movement. Our study shows that high genetic variation can be maintained within metapopulations of selfing Zingiber species, due to increased genetic differentiation intensified primarily by the stochastic force of genetic drift among subpopulations. Therefore, maintenance of natural variability among subpopulations in fragmented areas is key to conserve the full range of genetic diversity of selfing Zingiber species. For outcrossing Zingiber species, maintenance of large populations is an important factor to enhance genetic diversity.Habitat fragmentation strongly affects the genetic diversity of plant populations, and this has always attracted much research interest. Although numerous studies have investigated the effects of habitat fragmentation on the genetic diversity of plant populations, fewer studies have compared species with contrasting breeding systems while accounting for phylogenetic distance. Here, we compare the levels of genetic diversity and differentiation within and among subpopulations in metapopulations  of two closely related Z. nudicarpum, the subpopulation genetic diversity in selfing Z. corallinum was significantly lower, but the metapopulation genetic diversity did not differ. Most genetic variation resided among subpopulations in selfing Z. corallinum metapopulations, while a significant portion of variation resided either within or among subpopulations in outcrossing Z. nudicarpum, depending on whether the degree of subpopulation isolation surpasses the dispersal ability of pollen and seed. Our study shows that selfing Z. corallinum could maintain high genetic diversity through differentiation intensified primarily by the stochastic force of genetic drift among subpopulations at fine-scale level, but not local adaptation.Compared to outcrossing  Genetic diversity is central to the maintenance of biodiversity in any ecosystem and allows for adaptive evolution in changing environments . Indeed,The dramatically increasing fragmentation of natural habitats as a result of anthropic activities is markedly affecting the genetic diversity of plant populations and has been the subject of research interest .Araucaria angustifolia  showed that selfing Z. corallinum can maintain a high level of genetic diversity across the species’ range, similar to that of outcrossing Z. nudicarpum, albeit low genetic diversity within populations  data. The ISSR is an easy handling, good reproducibility, low cost, quick technique for plant population genetic studies  whether selfing Z. corallinum also can maintain high genetic diversity within metapopulations, like that at landscape level; (iii) whether there are differences in the spatial distribution of genetic variation among Zingiber metapopulations that relate to mating system and gene flow?A previous study on comparing the genetic structure of two closely related selfing and outcrossing ulations . Thus, kZingiber, Z. corallinum and Z. nudicarpum  [see  ] are from the same section Zingiber of the genus Zingiber  are located in Zijin County  and Yangxi County , Guangdong Province, China (Z. nudicarpum (separated by nearly 100 km) are located in Baoting County  and Changjiang County , Hainan Province, China . The individual plants are scattered within abandoned farmlands and the margins of remnant forest.Both species of Zingiber . Both spty index . Zingibeing mode . Primarying mode . The twoe, China . The twoe, China . The GDZZ. corallinum and Z. nudicarpum (r) within subpopulations. In order to test the genetic correlation between seedlings and mature individuals and further analyse the spatial genetic structure within subpopulations, we also sampled 45 seedlings throughout the area of distribution of subpopulation 2 in the GDZJ metapopulation of Z. corallinum. Because seedlings always aggregated around adjacent mature individuals, we classified them into five sets with their nearest adult individuals (Set-M1 to Set-M5). Leaf tissue samples were stored in silica gel for DNA analysis.To investigate within-population spatial genetic structure, we collected samples from 15–74 adult individuals (at least 2 m apart) throughout the area of distribution of each subpopulation  in metapopulations of dicarpum . The str[see  ], were used in Z. corallinum; the same 10 primers were also used in Z. nudicarpum, together with additional three primers for this species [see  ]. PCR for both species was carried out in a total volume of 20 μL, including 40 ng template DNA, 2.5/2.0 μL 10× buffer, 1.50/1.00 mmol Mg2+, 0.15/0.20 mmol dNTPs, 0.4/0.6 μmol primer, 2.0 units of Taq DNA polymerase and double-distilled water. Negative controls, that replaced template DNA with distilled water, were included in each PCR set to test for possible contamination. PCR products were subjected to electrophoresis in 1.8 % agarose gels in 0.5× TBE buffer at 130 V for 1–1.5 h along with a 100-bp ladder and photographed with the help of a gel documentation system (Bio-Rad GelDoc XR+). To ensure reliability of the bands, duplicate PCR amplifications were performed and only clear and reproducible bands were scored. The images of the gels were analysed using Image Lab software (Bio-Rad) to score for the presence (1) or absence (0) of bands and to assign a fragment size to each band. The presence or absence of bands was further visually confirmed.DNA from the sampled leaves was extracted using the modified CTAB method . The DNAh), Shannon’s information index (I), observed number of alleles (Na), effective number of alleles (Ne). Genetic differentiation among subpopulations was evaluated by GST in POPGENE. The matrix was also subjected to an analysis of molecular variance (AMOVA) using GenAlEx 6.502 (Nm) among subpopulations was estimated using the formula, Nm = 0.5(1 − Gst)/Gst (h and I) of two species were statistically analysed by the independent t-test using SPSS software . The presence/absence binary matrix of the ISSR phenotypes was analysed using POPGENE v. 1.31 (Ex 6.502  based onGst)/Gst . GeneticZ. corallinum and STRUCTURE v. 2.1  replications. The optimal value of K was calculated according to the method of Genetic cluster analysis implemented in InStruct v. 1.0 (r) generated is a proper correlation coefficient, bounded by  and is closely related to Moran’s I. The spatial genetic structure of the studied subpopulations was tested using single population spatial structure analyses in GenAlEx. The even sample classes were chosen because this was particularly useful for reducing noisy confidence limits when sample sizes were very uneven  and 294 (98.0 %) were polymorphic. The size of bands ranged from 200 to 2150 bp and 210 to 1900 bp, respectively. Of these, there were 197 and 175 reliable ISSR bands in metapopulations GDZJ and GDYX of Z. corallinum, of which 183 (92.9 %) and 132 (75.4 %) were polymorphic, respectively, and the specific bands were 36 (18.3 %) and 43 (24.6 %), average 39.5 (21.4 %)  and from 0.0174 to 0.2971 (average 0.0995), respectively  and 147 (73.9 %) of the 258 and 199 reliable bands were polymorphic and 0–25 (0–9.7 %) specific bands were found, with an average of 12.5 (4.9 %) , and from 0.1438 to 0.2907 (average 0.2257), respectively (The primers produced 221 and 300 reliable ISSR bands from seven and five subpopulations in the metapopulations of (21.4 %) . At the ectively . For the (4.9 %) . At the ectively .Z. corallinum metapopulations except GDZJ-2, common loci  accounted for the highest proportion of amplified fragments (58.1–91.4 %), while the medium–high gene frequency loci (50 % < gene frequency < 100 %) accounted for a higher proportion of amplified fragments (4.3–23.7 %) than the low–medium gene frequency loci (5 % < gene frequency ≤ 50 %) (0.7–15.1 %)  than medium–high gene frequency loci (8.7–23.6 %). With the exception of HNCJ-1, common loci and rare loci in the remaining four Z. nudicarpum subpopulations accounted for the highest proportion (32.4–61.3 %) and the lowest proportion (6.9–15.8 %) of amplified fragments, respectively   and B. R–15.1 %)  and B. A–15.1 %)  and B. Aectively  and D. Aectively  and D.Gst values for the subpopulations in Z. corallinum and Z. nudicarpum metapopulations were estimated as 0.7110 and 0.3408 (Nm) per generation among subpopulations in Z. corallinum and Z. nudicarpum metapopulations were 0.2575 and 1.0311, respectively (ST = 0.784) and 46.8 % (Φ ST = 0.468) of the total variation was partitioned among subpopulations in the metapopulations of Z. corallinum and Z. nudicarpum, respectively , all subpopulations could be assigned to two and four genetic clusters  were assigned into two and three genetic clusters  and then cluster I further formed two well-resolved clades , which comprised all individuals from subpopulations GDZJ-3 and GDZJ-1, respectively  and all individuals from the same subpopulations clustered together  and 100–1500 m  in subpopulations of selfing Z. corallinum metapopulation GDYX and outcrossing Z. nudicarpum metapopulation HNCJ, respectively  and outcrossing Z. nudicarpum metapopulation HNBT  [see  ].The spatial autocorrelation analysis indicated that significant positive spatial genetic structure was detected at 2–34 m , the level of metapopulation genetic diversity of selfing Z. corallinum was comparable to that of outcrossing Z. nudicarpum . The mating system (i.e. selfing vs. outcrossing) can strongly influence the vulnerability to fragmentation effects on genetic diversity . However, both species contained similar levels of common loci in metapopulations . In addition, the specific band number within subpopulations and metapopulations of selfing Z. corallinum was higher than that in outcrossing Z. nudicarpum, but not significant . Together, these results imply that local adaptation and/or neutral mutation may have caused differentiation among subpopulations (patches) by fixation of different loci , while a lower degree of genetic variance (9.5–33.7 %) exists within different subpopulations. However, the majority of variation was also found among subpopulations (62.5 %), rather than within subpopulations (37.5 %) in outcrossing Z. nudicarpum metapopulation HNCJ, in which gene flow was seriously eroded by habitat fragmentation (Nm = 0.7180 < 1) and genetic differentiation among subpopulations was higher. The opposite was true in the outcrossing Z. nudicarpum metapopulation HNBT, in which gene flow was not significantly affected by habitat fragmentation (Nm = 1.9734 > 1). The genetic structure of outcrossing Z. nudicarpum metapopulations can be attributed to the short distances of pollen movement via parasitic bees and the constraints of seed dispersal by gravity. In the metapopulation HNBT, three subpopulations scattered widely in a more or less continuous area of suitable habitat, which separated by 200–550 (average ca. 320) m apart. This isolation degree could not prevent the pollen movement of outcrossing Z. nudicarpum between populations, as evidenced by the significant positive autocorrelation of spatial genetic structure with 100–1500 m. However, the two subpopulations in the metapopulation HNCJ are isolated by 450–1000 (average ca. 725) m of mountain forest. This greater isolation could significantly prevent the pollen migration of outcrossing Z. nudicarpum between populations. In comparison, the genetic structure of selfing Z. corallinum metapopulations is influenced almost entirely by restricted seed dispersal due to gravity alone. Our results suggest that the majority of genetic variation resides among subpopulations in selfing Z. corallinum metapopulations, while the major portion of genetic variation exists within or among subpopulations in outcrossing Z. nudicarpum metapopulations, most probably depending on whether the degree of subpopulation isolation surpasses the dispersal ability of pollen and seed.Outcrossing plants typically show higher genetic variation within populations or subpopulations, whereas in selfing plants most of the genetic variation is found among populations or subpopulations  were assigned to the same genetic cluster, but this was not the case in metapopulation HNBT (Nm = 1.9734 > 1). Moreover, UPGMA and NJ analysis revealed that all individuals within subpopulations in metapopulation HNCJ were clustered together as a single clade, but, again, metapopulation HNBT did not conform to this pattern. The results of the PCoA revealed a similar clustering pattern.Our cluster analysis showed that neighbouring individuals within subpopulations always grouped together in selfing families . However species , presuma species . GeneticZ. corallinum. Although limited seed dispersal may have a stronger effect on the genetic structure of a population, pollen movement could promote gene exchange between or within subpopulations or fragments within outcrossing Z. nudicarpum metapopulations. Thus, contrary to our expectations, a weaker genetic structure appears in species like Z. nudicarpum with extensive pollen movement but restricted seed dispersal when such species occur in fragmented habitats.In summary, our results indicate that restricted gene flow as a result of gravity-driven seed dispersal contributes to the genetic differentiation between subpopulations or fragments within metapopulations of selfing The following additional information is available in the online version of this article—Zingiber corallinum (A) and Z. nudicarpum (B).P (K) and ΔK estimates .Zingiber corallinum .Zingiber nudicarpum .Zingiber corallinum  and Z. nudicarpum .Zingiber corallinum  and Z. nudicarpum (C—HNBT).Zingiber corallinum (ZC) and Z. nudicarpum (ZN) used in the present study.plaa065_suppl_Supplementary_Figures_and_TablesClick here for additional data file.plaa065_suppl_Supplementary_MaterialClick here for additional data file.Z. corallinum and Z. nudicarpum are available as Inter-simple sequence repeat (ISSR) data for


Chinese indigenous pig breeds in the Taihu Lake (TL) region of Eastern China are well documented by their exceptional prolificacy. There are seven breeds in this region including Meishan (MS), Erhualian (EHL), Jiaxing Black (JXB), Fengjing (FJ), Shawutou (SWT), Mi (MI), and Hongdenglong (HDL). At present, these breeds are facing a great threat of population decline, inbreeding depression and lineage admixture since Western commercial pigs have dominated in Chinese pig industry. To provide better conservation strategies and identify candidate genes under selection for these breeds, we explored genome-wide single nucleotide polymorphism (SNP) markers to uncover genetic variability and relatedness, population structure, historical admixture and genomic signature of selection of 440 pigs representing the most comprehensive lineages of these breeds in TL region in a context of 1228 pigs from 45 Eurasian breeds. We showed that these breeds were more closely related to each other as compared to other Eurasian breeds, defining one of the main ancestral lineages of Chinese indigenous pigs. These breeds can be divided into two subgroups, one including JXB and FJ, and the other comprising of EHL, MI, HDL, MS, and SWT. In addition, HDL was highly inbred whereas EHL and MS had more abundant genetic diversity owing to their multiple conservation populations. Moreover, we identified a list of candidate genes under selection for body size and prolificacy. Our results would benefit the conservation of these valuable breeds and improve our understanding of the genetic mechanisms of body size and fecundity in pigs. China has a variety of indigenous pig breeds that represent extensive phenotypic diversity and account for approximately one-third of global breeds . At presin situ action to build a genetic reservoir to prevent unwanted lineage admixture with other varieties  and MS pigs (n = 136) were each sampled from three conservation farms while other five breeds were each sampled from one conservation farm. Among the three conservation farms for MS, one is MMS conserved population, the other two are SMS conserved populations. The 440 individuals were selected to cover all consanguinities of the conservation populations of the seven breeds according to their pedigrees. We preferentially selected all boars and unrelated sows without common ancestors within three generations and included all sows of unknown origin. All procedures and animals used in this study were in compliance with guidelines for the care and utility of experimental animals established by the Ministry of Agriculture and Rural Affairs of China. The ethics committee of Nanjing Agricultural University approved this study.A total of 1228 pigs from 45 Eurasian breeds including the seven breeds in TL region were analyzed in this study . The sevhttps://doi.org/10.6084/m9.figshare.10073153.v1.Genomic DNA was extracted from ear samples using a routine phenol/chloroform method and diluted to a final concentration of 50 ng/μl, which was then genotyped using the Porcine SNP50 BeadChip , containing 51,315 SNPs according to the manufacturer’s protocol. The genotype input was converted into a PLINK v1.07  input fi1. We used MEGA v6.0  using PLINK v1.07 . The genEGA v6.0  to calcuFst) among breeds, also named Wright’s F-derived statistics  matrices and visualized these heatmaps via in-house R scripts.Coefficients of genetic differentiation  was performed using PLINK v1.07  to illusADMIXTURE v1.23  was usedTREEMIX v1.12  was usedZ score. A large negative Z score (Z < -2) indicates a significant evidence of admixture.The three-population test  implemenExpected heterozygosity (He), observed heterozygosity (Ho), and inbreeding coefficient (Fis) were calculated for individual breed using PLINK v1.07  under deWhere Fis is the inbreeding coefficient estimation; O(HOM) is the observed number of homozygotes; E(HOM) is the expected number of homozygotes; N(NM) is the number of non-missing genotypes.r2) via the command “–r2 –ld-window 9999 –ld-window-r2 0 –ld-window-kb 1000” in PLINK v1.07  extent in each breed was estimated from pair-wise genotype correlation coefficients (NK v1.07 . Inter-Sd of 0.3 . SNeP (Bd of 0.3  was usedd of 0.3 :T(t) is the estimated effective population size t generations ago; ct is the recombination rate t generations ago; r2adj is the LD estimation adjusted for sampling bias; α is a constant.Where NFst) between pair-wise subfamilies and merged adjacent subfamilies with a close genetic distance or low genetic differentiation into a single subfamily, so that the variation coefficient of the genetic distance between pair-wise subfamilies of each population was less than 10%, and the Fst values between pair-wise subfamilies of each population were greater than 0.05. In the end, we tried to make the genetic resource of conservation farm evenly distributed between subfamilies, which means the genetic distances between pair-wise subfamilies tended to be consistent, and the genetic differentiation between pair-wise subfamilies should also be moderate degree.FJ, MI, JXB, SWT, and HDL were each sampled from one conservation farm while three conservation populations were investigated for EHL and MS, respectively. There were historical exchanges of breeding animals among these populations. To clarify the most reliable subfamilies of each conservation farm, we performed neighbor-joining (NJ) tree of all individuals from each farm using MEGA v6.0 . The booFst)  and quantitative trait loci  flanking these SNPs on the pig reference genome assembly (Sscrofa 11.1)2 according to the published literatures and gene functional relevance to body size, growth, and development. In addition, we employed PLINK v1.07 (r2) between pair-wise top significant SNPs on SSC3.To identify candidate loci for body size differences between MMS and SMS, we calculated genetic differentiation coefficients (Fst)  of 21,85NK v1.07  to detec3.To identify candidate loci under selection in the seven breeds in TL region, we calculated locus-specific branch length (LSBL) statistics  for eachFirst, we constructed the NJ tree for all 1228 pigs from 45 Eurasian breeds . Two HDLFst) matrices between pair-wise breeds. The two heatmaps  and genetic differentiation coefficient  of the variance in the relatedness between breeds were explained . Of the To compare genetic variability of the seven breeds in TL region, we calculated three genetic diversity indices for these breeds: Ho, He and Fis. Of note, HDL had the lowest Ho (0.16) and He (0.15) values but a highest Fis estimation (0.50). In contrast, EHL had the larger Ho (0.2) and He (0.2) values but a lower Fis level (0.4). We noticed that several MI pigs were highly inbred, leading to a large coefficient (44.15%) of variation with a relatively small average Fis value of 0.29 .r20.3 in all 45 breeds. We chose Chinese wild boars, the seven breeds in TL region and three Western commercial breeds to visualize their LD patterns (r20.3 = 1.5 kb). Among these seven breeds in TL region, HDL had the longest LD extents (r20.3 = 1000.00 kb), followed by FJ (488.74 kb) and JXB (261.63 kb). In comparison, EHL (9.50 kb) and MI (25.50 kb) had the shortest LD extents.We estimated LD extents at the threshold of patterns . ChineseWe estimated historic effective population size (Ne) of each breed dating back 50 generations ago using SNeP . EHL hadThree MS populations were investigated in this study, including one MMS  and two SMS  populations. Individuals from the three populations did not cluster together and defined separate branches in the NJ tree . AccordiFst values between pair-wise subfamilies of the seven breeds in TL region were all greater than 0.05 (data not shown), indicating a moderate genetic differentiation at the subfamily level.We also analyzed three EHL populations that were raised in Changzhou (EHL-CZ), Changsu (EHL-CS) and Sutai (EHL-ST) cities of Jiangsu province. Individuals from each EHL population did not cluster together in the NJ tree . A few nFst-based approach  to identify candidate genes for the phenotypic difference in body size between these two populations. We identified 10 candidate genes , four genes involved in bone formation  and three genes associated with disease resistance . Interestingly, USP34 is required for osteogenic differentiation and bone formation  , PCA, ADMIXTURE, TREEMIX and three-population test analyses to reveal historical relatedness and admixture of seven breeds in TL region and other 38 diverse Eurasian pig breeds. It could be found that, in the NJ trees of 45 Eurasian pig breeds, pig breeds were clustered with each other owing to the same geographic origin, expect JQH, GST and BMEI. The possible reasons for this result are as follows: (1) JQH is located on the border of East China and North China, and it has a certain lineage from HUAI pigs ; (2) Bott shown) . Archeolt shown)  suggestet shown) . Our finK = 7 in the ADMIXTURE analysis, while South Chinese and Southwest Chinese breeds can only set one ancestral lineage at K = 7, and these two subgroups can be observed until K = 18. These two breeds were originally distributed in a neighboring area  with other six breeds in TL region , in comparison with the other Chinese breeds including Huai pigs; and (3) HDL displayed a common ancestral lineage with other six breeds in TL region in the ADMIXTURE analysis when K = 3–6 in the panel of the 45 Eurasian breeds.It remains a long-term debate whether HDL is a sub-population of Huai pigs indigenous in Anhui and Henan provinces or is an independent genetic resource having close genetic relationship with MI and EHL . Here weP < 0.01), such as MS, FJ, and JXB. To avoid deteriorative inbreeding depression, particular attention should be paid to improve the management of the conservation population of this breed. In comparison, EHL had more abundant genetic diversity, because it had lower inbreeding degree, largest effective population size, lowest linkage disequilibrium and the largest number of subfamilies. So did MS, the degree of inbreeding may be relatively high among seven pig breeds in TL region, but it had lower linkage disequilibrium, and it also had the second largest effective population size and subfamilies number. These factors implied that EHL and MS, especially EHL, had more genetic diversity, which is likely due to the multiple conservation farms established for these two breeds. Currently, African swine fever has swept across China and caused disastrous effects on Chinese pig industry. To deal with the devastating disease, it is highly necessary to provide multiple conservation sites for HDL, MI, SWT, JXB, and FJ as well as other Chinese breeds. There would be otherwise a great risk of total destruction for these breeds when the current single in situ conservation farm is infected with African swine fever.We calculated inbreeding indicators, effective population sizes and LD extents of the seven breeds in TL region. We also divided subfamilies within each conservation population. These analyses can reflect the genetic diversity of breed. In fact, different subfamilies of conservation population represent different lineages. The different subfamilies evidenced among the breeds are mainly due to the differences in breeding plans in each conservation farm. Specifically, the biggest effect of dividing subfamilies is that it can be efficient to carry out rotational crossbreeding  between Fst analysis between MMS and SMS and identified four candidate genes related to bone formation, including USP34, BMP2, CDH5, and STC1. And we also found multiple QTLs for body weight, obesity index, feed intake and feed conversion ratio near the most significant locus on SSC3. These candidate genes and QTL intervals may explain the genetic mechanisms underlying the phenotypic difference in body size between MMS and SMS. PACSIN1 and SPDEF were not replicated in this study. This inconsistency may be due to different experimental populations or different SNP systems. In additional, USP34 gene for bone formation , pregnancy (SBSPON), spermatogenesis and male function  and ovarian lesions (MYO18B). Moreover, these candidate genes are enriched in several GO terms associated with reproduction. These terms include cell proliferation, which is critical for the formation of sperm and eggs (The indigenous pig breeds in TL region are well known for their high fecundity with an average litter size of greater than 15 . We impland eggs , phosphaand eggs , notch sand eggs  and ATP and eggs . These fOur study uncovered genetic diversity, historical relatedness and population structure of seven pig breeds in TL region via a more comprehensive manner. We showed that HDL is an independent genetic resource and the seven breeds in TL region including HDL comprise one of the major ancestral lineages of Chinese indigenous pigs. We further identified a list of novel candidate genes contributing to the phenotypic difference in body size between SMS and MMS, and the fecundity of the seven breeds in TL region. Altogether, our results would benefit the sustainable conservation of these pig breeds in TL region and improve our understanding of the genetic mechanisms of body size and fecundity in pigs.https://doi.org/10.6084/m9.figshare.10073153.v1.We have submitted our SNP dataset to a public repository, which is now publicly available at The animal study was reviewed and approved by the Ethics Committee of Nanjing Agricultural University.RH, JR, and PL: conceptualization. CL and PL: formal analysis. CL, PL, WZ, XM, XW, YX, NJ, MZ, TZ, and YY: investigation. JR, RH, CL, and PL: methodology. RH and JR: project administration. CL and PL: writing – original draft. JR and RH: writing – review and editing.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Gallus gallus) across two subspecies  from 12 populations and 138 chickens from 10 chicken breeds indigenous to Thailand. Twenty-nine D-loop sequence haplotypes were newly identified: 14 and 17 for Thai indigenous chickens and red junglefowl, respectively. Bayesian clustering analysis with microsatellite markers also revealed high genetic diversity in the red junglefowl populations. These results suggest that the ancestral populations of Thai indigenous chickens were large, and that a part of the red junglefowl population gene pool was not involved in the domestication process. In addition, some haplogroups that are distributed in other countries of Southeast Asia were not observed in either the red junglefowls or the indigenous chickens examined in the present study, suggesting that chicken domestication occurred independently across multiple regions in Southeast Asia.In this study, we aimed to elucidate the origin of domestic chickens and their evolutionary history over the course of their domestication. We conducted a large-scale genetic study using mitochondrial DNA D-loop sequences and 28 microsatellite DNA markers to investigate the diversity of 298 wild progenitor red junglefowl ( Throughout human history, approximately 40 livestock species have been domesticated, most of which still contribute to agriculture and food production as domestic animals today2. The chicken is one of the most ubiquitous domesticated animals; it is bred for both its egg and meat, and is thought to have originally been domesticated from the red junglefowl  native to multiple regions from Southeast Asia to Southwest China5. Chicken domestication was previously considered to have occurred in the Indus Valley at around 2000 BC6. However, West and Zhou7 proposed an earlier origin in Southeast Asia, before the 6000 BC, based on archaeological evidence from China, Southeast Asia, and Europe, and palaeoclimatic evidence in China. Chickens were initially used for rituals, including the use of a crowing cock to proclaim the hour of dawn, and later, various cock-fighting and pet breeds were produced and raised around the globe. Commercial chicken breeds, including layers and broilers, have been bred over the last 100 years through selective mating of various indigenous breeds11.The domestication of wild animals represents a major milestone in the course of human civilisation12, such as heat stress, humidity15, and disease16. Recently, the crossbreeding of indigenous chickens with common commercial chickens has been actively performed to develop breeds that exhibit the aforementioned desirable traits. However, repeated crossing with commercial chickens decreases the genetic diversity of indigenous chickens, resulting in the loss of genetic resources in the latter populations17. In addition, in Southeast Asia, genetic contamination of the ancestral species via crossing of red junglefowl with free-range indigenous chickens has become a major concern for conservation biologists. Consequently, genetic characterisation of red junglefowl and indigenous chickens is essential to reveal the potential genetic erosion in the former. In addition, the results of such activities could facilitate the adoption of appropriate strategies to recover and conserve the genetic diversity of the species, which represents an invaluable genetic resource.The process of chicken domestication through the breeding of indigenous chickens has an approximately 8000 year-long history. Consequently, over the years, indigenous chickens have acquired diverse genetic characteristics that have facilitated adaptation to different challenging conditions in diverse locations23. Miao et al.5 identified five major (A–E), six minor (F–J), and several rare (W–Z) haplogroups based on mtDNA D-loop sequences in 206 red junglefowls from eight countries  and 3797 indigenous chickens from 30 countries in Asia, Europe, Africa, South America, and six Pacific islands. In Miao et al.5 and other reports cited in their study23, 32 red junglefowls  and indigenous chicken individuals  from Thailand were included. In addition, Teinlek et al.24 recently examined the mtDNA D-loop sequences of 220 Thai indigenous chickens consisting of four breeds . Although Thailand may be one of the regions where chicken domestication occurred3, the data regarding the genetic diversity of red junglefowls and indigenous chickens in Thailand are still insufficient to accurately elucidate the origin and process of chicken domestication. Red junglefowl mainly inhabit Southeast Asia, and five subspecies  have been reported26. Two subspecies, G. g. gallus and G. g. spadiceus, distributed across Thailand26, are distinguished only by their external characteristics, and no population genetics study on the genetic diversity between the two subspecies has been carried out. In Thailand, red junglefowl is strictly protected under the National Park Act since 1961 and the revised Wild Animals Reservation and Protection Act since 199227. Thai indigenous chickens are generally reared under free range backyard conditions by small-scale poultry farmers, and a variety of breeds have been established from indigenous populations and maintained as closed colonies ever since. These were bred selectively based on their morphological and/or biological characteristics, such as meat and/or egg production, quality of meat, plumage or morphologies, behaviors (crowing and fighting), etc., without genetic contamination or gene flow from other breeds or populations. The price of eggs and meat from these indigenous chickens is relatively high compared to those of commercial layers and broilers. Ornamental and fighting chickens are also traded at a higher price among chicken fanciers. Because indigenous chickens are a major or secondary source of income for poultry farmers, collecting blood or skin samples from indigenous chicken breeds and red junglefowl is difficult.Population studies on the genetic diversity and relationship between red junglefowl and indigenous chickens could also provide key insights into the geographic origins of chicken domestication and genome evolution in chickens over the course of domestication. Numerous studies on the genetic diversity of chickens have been conducted using mitochondrial DNA (mtDNA) D-loop sequencesG. g. gallus and G. g. spadiceus; and (4) the current genetic structure of red junglefowl and indigenous chickens in Thailand. On the basis of our results, we discuss the origin of indigenous chicken breeds in Thailand and the genomic evolution that has occurred in the populations over the course of domestication.Here, we conducted a large-scale population genetics study on the diversity of red junglefowl  and indigenous chicken populations (138 chickens from 10 indigenous chicken breeds) in Thailand using mtDNA D-loop sequences and microsatellite markers to investigate (1) the mtDNA D-loop haplotypes of red junglefowl and indigenous chickens in Thailand; (2) the existence of ancient D-loop sequence haplotypes in red junglefowl, which would indicate a likelihood that Thailand is one of the centres of chicken domestication; (3) the genetic differentiation between two red junglefowl subspecies, G. g. gallus and G. g. spadiceus) within 12 populations in Thailand. A total of 44 haplotypes with 62 variable sites, consisting of 26 singletons and 36 parsimony informative sites were identified  as they were not clearly separated. In addition, haplogroup J was closely related to haplogroup CD. Haplogroups A, B, and E were predominant in the Thai indigenous chickens  tree based on the HKY + G + I model of evolution, which were selected as the best-fit substitution model, were fundamentally similar. Although the Bayesian posterior probability of the internal nodes and the ML bootstrap values were relatively low due to the short internal branches (multifurcations) of the phylogenetic trees, the haplogroups A, B, F–I, K, Y, and Z were supported by a Bayesian posterior probability of greater than 0.97  belonged to haplogroup A Fig. a. Seven Divergence times for each haplotype were determined using BEAST analysis (Supplementary Table H) ranged from 1  to 10 (fighting chicken)  than in NK-W, NK-B, and DT  .The number of D-loop haplotypes in each population (n) Table . Among tHaplogroups A, B, CD, E, and J were frequently identified in red junglefowl in Thailand Fig. . HaplotyG. g. gallus and G. g. spadiceus) from 12 populations and 138 chickens from 10 indigenous chicken breeds, were used for the genetic diversity analyses using 28 microsatellite markers (Table AR) values ranged from 1.40 for MCW103 to 1.93 for MCW0014 (1.77 on average) (Supplementary Table Na ranged from 2.14 for MCW0103 to 7.59 for LEI0192 (2.86 on average). FIS varied from – 0.08 for LEI0166 to 0.54 for MCW0014 (0.05 on average). The FST and FIT values fell within the 0.07 (MCW0098) to 0.31 (MCW0247) range and 0.09 (MCW0123) to 0.63 (MCW0014) range, respectively . Two markers, MCW0222 and MCW0014, showed the null allele frequency across all populations (NAF) higher than 0.2   3.32; Ne = 2.01; Ho = 0.45) (Table AR ranged from 2.76 (NK-B) to 3.25 (LHK); MNA ranged from 3.43 (NK-B and DT) to 6.07 (fighting chicken); Ne ranged from 2.50 (NK-W and NK-B) to 3.25 (fighting chicken); and Ho ranged from 0.51 (PHD) to 0.64 (NK-B). In the red junglefowl populations, AR ranged from 2.78 (Roi Et) to 3.59 (Chanthaburi); MNA ranged from 2.82 (Huai Sai [Ggg]) to 7.07 (Khok Mai Rua); Ne ranged from 2.37 (Huai Sai [Ggg]) to 3.94 (Chanthaburi); and Ho ranged from 0.45 (Huai Sai [Ggg]) to 0.68 (Chanthaburi). Chanthaburi  and Khok Mai Rua  exhibited comparatively higher genetic heterogeneity among the populations examined.Out of the 22 populations examined, the BT population exhibited the least genetic diversity  and Huai Sai (Ggs) had a close genetic relationship .Two cladograms based on ies Fig. a,b; six hip Fig. c. Five ices Fig. d. In theNAF higher than 0.2; however, we realized that the resulting STRUCTURE plots did not differ from those obtained using all 28 markers. Thus, we used all of the 28 markers for STRUCTURE analysis in this study. Analysis using STRUCTURE HARVESTER revealed that K = 2 was optimal for the 22 populations (delta K = 6.59) and K = 4 was the second highest (delta K = 2.05)  revealed that 83.85% and 16.00% of the total genetic variance in 12 red junglefowl populations was attributed to genetic variance within populations and among groups of each subspecies, respectively, and only 0.16% of the total genetic variance was attributed to variance between two subspecies. This result indicates that the genetic variation of red junglefowl is mostly explained by the genetic divergence among populations, and that the genetic difference between subspecies is very low.28. The haplotypes of haplogroups A and/or CD that were observed in 15 populations of indigenous chickens and red junglefowl in Thailand were similar or closely related to the representative haplotypes in South China, Vietnam, Laos, Sri Lanka, and Japan5. Some haplotypes of haplogroups F and J, which are minor haplogroups found only in limited areas of Southern China and Southeast Asia29, were also found in Thai indigenous chickens. However, 29 unknown haplotypes were newly identified in the present study, with 14 and 17 identified in indigenous chickens and red junglefowl, respectively. Indigenous chickens and red junglefowl shared two haplotypes (Hap_12 and 34). Most of their divergence times were estimated to be around 300 years ago or earlier. Our results indicate that the unique genetic variants have been maintained in the indigenous chicken populations for a long time after the original domestication of red junglefowl in the region.Haplogroups A, B, and CD of mtDNA D-loop sequences are mainly distributed in chickens from East Asia, Southeast Asia, and the Pacific islands30, the Japanese Shamo chicken was clearly separated into two phylogenetic groups: one group from the Okinawa islands and the other group mainly from Kyushu and Honshu. This result suggests that the Japanese Shamo chicken has two origins. Trade between Thailand and Japan, especially the Okinawa islands, was active during the Ayutthaya Kingdom (circa the 15th–16th century)30, and the name ‘Shamo’ in Japanese is proposed to have been derived from ‘Siam’ or ‘Sa-yam’, which was the old name of Thailand used in this era. Our results strongly support the view that Thailand is one of the origins of the Japanese Shamo chicken.Notably, the identification of haplogroup H, which was found in fighting chickens, is a key piece of evidence supporting the historical link between Thailand and Japan through cock-fighting. Cock-fighting is a traditional game that is historically widespread across the world, but especially common in Southeast Asia; the breed specialised for the game is called ‘Shamo’ in Japan. Currently, this breed is popular as a fancy breed. In a previous study on the genetic characteristics of Japanese fighting chickens using mtDNA D-loop sequencesThe genetic diversity of Thai indigenous chicken breeds and their phylogenetic relationships, as examined using microsatellite markers, revealed that the chicken breeds bred for meat were genetically distinct from the other indigenous chicken breeds. The BT, NK-B, NK-W, and DT chicken breeds were each divided into a separate cluster. The results suggest that these breeds have a long history of selective breeding, which has led to the emergence of unique genetic characteristics in all four breeds. As shown in the STRUCTURE plot, four indigenous ornamental chicken breeds  and the Decoy chicken were clustered into the same group possibly because (1) the four breeds were established by crossbreeding indigenous chicken breeds of different origins which were not genetically distant from each other or (2) they were derived from a common single breed and consequently had not yet clearly differentiated. The Decoy chicken breed is used for catching wild red junglefowls that are attracted to the crow of Decoy chickens. Decoy chickens have been maintained through inbreeding between Decoy chickens or by mating between Decoy chickens and wild red junglefowl. Therefore, their external appearance is highly varied, and some chickens are similar in appearance to red junglefowl, while others have white or black feathers across their body. This breeding background of Decoy chickens results in a high morphological diversity, but a close genetic relationship between Decoy chickens and red junglefowl populations on the mtDNA level.5, were not found in either the Thai red junglefowl or the indigenous chickens examined in the present study, which suggests that the rare haplogroups are either specific to other regions in Asia, or were not included in the individuals examined in the present study simply by chance. The former would imply that chicken domestication occurred independently in multiple regions of Southeast Asia. Further data on the genetic diversity of red junglefowls from other regions would be required to facilitate a detailed discussion on the origin of indigenous chickens and the process of chicken domestication in Thailand and other Asian countries .The major finding of our study was that six novel J haplotypes  were found in red junglefowl in Thailand; these sequences were not identical to any sequences deposited in GenBank. In addition, a unique haplotype (Hap_38), which has not been classified into any haplogroup, was detected in one wild population (Chaiyaphum), and we postulate that this haplotype diverged from other haplotypes around 12,000 years ago. The results suggest that a part of the wild red junglefowl population gene pool was not involved in the process of domestication. Haplogroups A‒E and J were also the prevailing haplogroups in Thai red junglefowl. Other rare haplogroups, which have been found in many regions in Asia 31; however, genetic characteristics were shared between Khok Mai Rua and other populations. This result was consistent with the fact that four of the six D-loop haplotypes of Khok Mai Rua were shared with other population. This suggests that Khok Mai Rua individuals were exchanged between wildlife conservation centres across different provinces. However, there are no records on cross breeding activities between the individuals collected from different populations. Therefore, population-level assessments of the genetic diversity of red junglefowl are required to facilitate the maintenance and preservation of their genetic diversity, in addition to their characteristics in different conservation centres or provinces.According to the STRUCTURE plot analysis, red junglefowl populations were divided into three groups at K = 4, consisting of (1) Sa Kaeo and Chanthaburi; (2) Si Sa Ket and Roi Et; and (3) other populations, excluding Huai Yang Pan. The Si Sa Ket and Roi Et group formed an independent and distinct cluster at K = 6 and 10, and the Khok Mai Rua, Khao Kho, Chaiyapum, and Huai Yang Pan groups each formed independent clusters at K = 10. Si Sa Ket and Roi Et, which were placed in the same cluster at K = 4, are geographically adjacent to each other, as well as to Sa Kaeo and Chanthaburi. However, multiple clusters were found within the Khok Mai Rua population at K = 3 to K = 20. In the phylogenetic tree constructed with microsatellite markers, several individuals of the Khok Mai Rua population were included in other red junglefowl populations. Red junglefowl cannot fly and move over a home range of only approximately 5 ha19 proposed a single origin of chicken domestication in and around Thailand inhabited by a subspecies ; however, the theory of multiple origins in South and Southeast Asia was put forward by two comprehensive studies of D-loop sequences by Liu et al.4 and Miao et al.5 More than 9000 D-loop sequences of chickens have been deposited in GenBank; nevertheless, many novel D-loop haplotypes were discovered from both red junglefowl and indigenous chickens in Thailand in the present study. This result suggests that red junglefowl and indigenous chickens in Thailand have large gene pools with extensive genetic diversity, which has been conserved in the populations for a long time, and that some subset of the red junglefowl population was involved in domestication. Microsatellite markers also exhibited high genetic diversity and unique genetic characteristics of indigenous chickens in Thailand. A recent population genetics study of red junglefowl performed using genome-wide SNP analysis revealed that G. g. spadiceus and G. g. gallus were phylogenetically differentiated and G. g. spadiceus may be the original ancestor of domestic chickens32. However, in the present study, the two subspecies were not clearly separated, and the genetic relationships between G. g. spadiceus and Thai indigenous chickens were not closer than those between G. g. gallus and indigenous chickens. The inconsistency in the results between our study and the previous study could be attributed to the differences in sampling locations of the two subspecies. Although the G. g. spadiceus individuals used in the previous study were collected from China, India, and Thailand, six G. g. gallus samples were all collected from Indonesia32. Given that the two subspecies used in the present study are closely distributed in Thailand, gene flow between different subspecies may readily occur. The small genetic differences between two subspecies in our study suggest that gene flow may have occurred between the populations of the two subspecies.Fumihito et al.G. g. gallus and G. g. spadiceus, are generally distinguished based on earlobe colour26; however, our results of mtDNA D-loop sequences suggest that there are no major genetic differences between the subspecies in Thailand. The results obtained using mitochondrial DNA, microsatellite DNA, and SNPs on nuclear genomes are affected by population histories due to their differences in the mode of inheritance and mutation rates; therefore, the estimation values of genetic diversity are not necessarily positively correlated between the mtDNA D-loop sequences and microsatellite markers. In comparison to these markers, whole mitochondrial genome sequences will provide a more reliable phylogenetic tree than the D-loop sequences alone. In fact, Miao et al.5 mentioned that D-loop sequencing alone could not identify differences between haplogroups C and D and could not subdivide haplogroup E into sub-haplogroups E1–E3. Thus, further genome-wide genetic analysis for red junglefowl and indigenous chickens in Thailand could aid in elucidating the origins and genomic evolution of red junglefowl and domestic chickens, which, in turn, would contribute to the conservation of these invaluable genetic resources.The results of our study also suggest the possibility that indigenous chickens and red junglefowl in Thailand harbour a variety of diverse genes that regulate traits beneficial to the poultry industry, such as those which improve egg and/or meat production and quality, environmental stress tolerance, and disease resistance. The two subspecies, The study was conducted under the authority of the Department of National Parks (DNP), Wildlife and Plant Conservation and the Ministry of Natural Resources and Environment, Thailand. Animal care and all experimental procedures were approved by the Animal Experiment Committee at DNP, following the annual physical examination protocol and the Animal Experiment Committee in Kasetsart University (ACKU63-SCI-008). Experiments were conducted in line with the Regulations on Animal Experiments of Kasetsart University and the fundamental guidelines for proper execution of animal experiments and related activities in academic research institutions under the jurisdiction of the National Research Council of Thailand, Ministry of Higher Education, Science, Research and Innovation, Thailand.G. g. gallus from seven centres and 135 of G. g. spadiceus from five centres; one centre provided samples of both subspecies) , and feather samples were collected from 279 individuals at 11 centres . The 10 indigenous chicken breeds used in the present study include three Thai indigenous chicken breeds for meat production; Betong (BT), Nin Kaset meat chicken with white feathers (NK-W) or black feathers (NK-B), and one indigenous Vietnamese chicken breed for meat production, Dong-Tao (DT), all of which had been maintained at the Lopburi Research Station of Kasetsart University; four fancy chicken breeds, Lueng-hang-khao (LHK), Chee (CH), Pradu-hang-dam (PHD) and Kheaw-Paree (KP) which are bred for poultry show and are identified by their differences in plumage colours; a breed called ‘Decoy’, which was provided by farmers in Phitsanulok province, which are used to catch wild chickens by attracting them by crowing; and fighting chickens, which were provided by a farmer  Table . The sub33, and Gg_Dloop_4R (5′-CGCAACGCAGGTGTAGTC-3′)34. Amplification was performed in a 12 μl reaction mixture containing 50 ng genomic DNA, 10 pmol of each primer, and 6.0 μl of AmpliTaq Gold 360 Master Mix . The cycling conditions were as follows: initial denaturation at 95 ℃ for 30 min, followed by 35 cycles at 95 ℃ for 30 s, 58 ℃ for 30 s, and 72 ℃ for 30 s, and a final extension for 5 min at 72 ℃. The PCR products were detected by electrophoresis on 1.5% agarose gels and then purified using the 20% polyethylene glycol/2.5 M NaCl precipitation method36. The cycle sequencing reaction was performed using a Big Dye Terminator Cycle Sequencing Kit v3.1 , and nucleotide sequences were determined using an ABI PRISM 3130 Genetic Analyzer (Applied Biosystems). As a preliminary experiment for verifying the reliability of nucleotide sequences of novel or rare haplotypes, we tested the rate of sequencing errors using the same DNA polymerase, instruments and sequencing protocol as those used in this study. We performed 50 independent PCR amplification for the mtDNA D-loop region of one inbred laboratory chicken line (GSP), which was maintained in Avian Bioscience Research Center at Nagoya University. Within the resulted 730 bp D-loop sequences of 50 samples, no sequencing errors were found. Because it is said that the error rate of AmpliTaq Gold 360 polymerase is 10–5, sequencing errors of the D-loop region can be almost avoided in this study.Partial DNA fragments (780 bp) of the mtDNA D-loop region were amplified by PCR using the following primer set: Gg_Dloop_1F (5′-AGGACTACGGCTTGAAAAGC-3′)37  obtained from GenBank, which were defined by Miao et al.5  generations, sampling a tree every 2000 generations. The convergence of the runs was verified using Tracer v1.7.151. After removing the first 10% of the sampled 20,000 trees as burn-in, Bayesian posterior probabilities were calculated from the remaining trees using Tree Annotator v2.4.352. FigTree v1.4.2 was used to illustrate the Bayesian tree. The Published D-loop sequences (GenBank) of another Gallus species (G. varius) were used as outgroups. Divergence times of haplotypes that were identified in the present study were estimated using BEAST v253, in which the time of the root node of the tree was set at 10,000 years ago. To determine the fine-scale genetic relationships among the haplotypes detected in the present study and the 420 D-loop haplotypes obtained from the GenBank, median-joining network trees were reconstructed using PopART v1.7.255.DNA sequences were aligned using the Geneious Alignment method implemented in GENEIOUS PRIME v2019.2.1 (Biomatters). Ambiguous sites behind primer sequences were trimmed from the fragments. To determine the phylogenetic positions of red junglefowl and indigenous chickens from Thailand in chicken populations throughout the world, Bayesian and ML phylogenetic trees were constructed using BEAST v2.4.355 with 279 D-loop sequences from the present study and 221 D-loop sequences from previous studies 56, number of haplotypes (H), and Watterson estimator per sequence (Theta-w)57 were calculated using DnaSP v558. The demographic history of each population was estimated using Tajima’s D test59 implemented in DnaSP v5. Genetic distances between populations were assessed using Molecular Evolutionary Genetics Analysis version 10 (MEGA X)60 using two different indices: (1) the average number of nucleotide substitutions per site (Dxy); and (2) the number of net nucleotide substitutions per site between populations (Da).The nucleotide diversity (Na), polymorphic information content (PIC), null allele frequency (NAF), and F statistics , were calculated for each of the microsatellite DNA markers, using MICROSATELLITE ANALYSER v4.0561 , GenAlEx v6.562 (Na), and Cervus v3.0.764 (PIC and NAF) , and Arlequin v3.5.2.265 for the observed heterozygosity (Ho) and the expected heterozygosity (He) 68 and the genetic distance based on the proportion of shared alleles (Dps)69, both of which were calculated using MICROSATELLITE ANALYSER v4.05.Genetic diversity indices, namely AR, number of alleles per population (70. The log probability values from K = 2 to K = 23 were estimated for a sampling period of 500,000 MCMC generations after a burn-in period of 500,000 generations under the admixture model and the correlated allele frequency model71. Twenty independent MCMC runs were performed for each K. Of the 20 MCMC runs for each K, those with variances of log likelihood more than twice those of the other MCMC runs were excluded from subsequent analyses. The clustering patterns of the remaining runs were analysed to generate one major clustering pattern in each K using CLUMPAK72. Afterward, the optimal K value was determined using the Evanno method73 in STRUCTURE HARVESTER v0.6.9474. To facilitate better understanding of the genetic differences between the two subspecies of red junglefowl, AMOVA was performed by separating 12 red jungle fowl populations into G. g. gallus and G. g. spadiceus using Arlequin v3.5.2.2.Bayesian clustering analysis was performed to infer the number of genetic clusters for 10 indigenous chicken breeds and 12 red junglefowl populations using STRUCTURE v2.3Supplementary Figure Legends.Supplementary Figure S1.Supplementary Figure S2.Supplementary Figure S3.Supplementary Figure S4.Supplementary Tables.