We identify three aspects whose incorporation into a single framework would enable a more generalised approach to the understanding and study of adaptive evolution: (i) a broadened view of extended phenotypes; (ii) that traits can respond to each other; and (iii) that inheritance can be non‐genetic. We use causal modelling to integrate these three aspects with established views on the variables and mechanisms that drive and allow for adaptive evolution. Our causal model identifies natural selection and non‐genetic inheritance of adaptive parental responses as two complementary yet distinct and independent drivers of adaptive evolution. Both drivers are compatible with the Price equation; specifically, non‐genetic inheritance of parental responses is captured by an often‐neglected component of the Price equation. Our causal model is general and simplified, but can be adjusted flexibly in terms of variables and causal connections, depending on the research question and/or biological system. By revisiting the three examples given above, we show how to use it as a heuristic tool to clarify conceptual issues and to help design empirical research. In contrast to a gene‐centric view defining evolution only in terms of genetic change, our generalised approach allows us to see evolution as a change in the whole causal structure, consisting not just of genetic but also of phenotypic and environmental variables.Evolutionary theory has made large impacts on our understanding and management of the world, in part because it has been able to incorporate new data and new insights successfully. Nonetheless, there is currently a tension between certain biological phenomena and mainstream evolutionary theory. For example, how does the inheritance of molecular epigenetic changes fit into mainstream evolutionary theory? Is niche construction an evolutionary process? Is local adaptation  I.et al., et al., Evolutionary biology has made large impacts on our understanding of the world, and on the management of pest organisms, diseases, agriculturally important organisms, threatened species, etc. Initially grounded on basic observations and inferences Darwin, , it has (1)(a)via in‐vitro fertilization and cross‐fostering. Bisulfite sequencing of sperm DNA from conditioned F0 mice and their F1 offspring revealed the presence of 5′–C–phosphate–G–3′ (CpG) hypomethylation in an odour receptor gene, providing the likely mechanism for the intergenerational transmission of an adaptively acquired fear. For other examples and the variety of molecular epigenetic changes involved and their transmission, see Wang, Liu & Sun by [our italics] niche construction is a possible outcome’  only natural selection can explain adaptation. We do not see how niche construction either generates or sorts genetic variation independently of these other processes, or how it changes gene frequencies in any other way’. Advocates of niche construction theory, by contrast, conceive of evolutionary processes more broadly, as anything that systematically biases the direction or rate of evolution, in which case niche construction would be an evolutionary process et al., et al., Habitat choice is very common in nature, both at the interspecific level (different species prefer different habitats) and at the intraspecific level , then why not? And if it is, then what is the driver of adaptive evolution, if natural selection did not operate during the divergence? And which trait is it then that presumably evolves?However, that leaves us with a conundrum i) a broadened view of extended phenotypes, (ii) that traits can respond to each other, and (iii) that inheritance can be non‐genetic. None of these elements are new by themselves (in fact they each have a large literature addressing them), and neither is the approach we take. The novelty and value lie in integrating into a single model what so far have been relatively separate treatments, and the insights that come from that. The model we develop can act as a general framework to address and discuss evolutionary questions of a practical/empirical nature but especially of a conceptual nature. After presenting the model, we therefore revisit the three problematic biological phenomena outlined in Section To address these and other phenomena and conceptual issues that appear to fit uncomfortably in evolutionary theory as currently used, we present a generalised approach to the study of adaptive evolution. For reasons explained below, this approach is generalised in the sense that we include (II.(1)et al.  or empirically . Causal modelling visually represents a causal hypothesis about which variables affect each other with a directed graph, and examines how it generates probability distributions over the variables. Inversely, it infers the underlying causal structure from observed statistical data. Its history dates back to Wright's path analysis Wright, , and it et al. , Morrisset al. , and Otset al. .i) development from zygotes into adult form; (ii) change in phenotypic distribution due to natural selection or other evolutionary processes; (iii) gamete production; and (iv) formation of new zygotes  predicts an evolutionary response towards earlier breeding. In contrast to this prediction, this pattern is often not observed: paradoxically, laying date does not respond to selection . It turns out that this is often because the correlation between laying early and reproductive success is actually due to a common third variable, better physical condition due to a favourable environment, which leads to both laying earlier and having more offspring Z1 will be a standard phenotypic trait. The second trait Z2 can be taken to be an additional phenotypic trait of the focal individual , or the environment can be matched to the phenotype (e.g. via niche construction or habitat choice): both phenotype and environment can be targets for the organism to achieve greater adaptation . For ths Sober, . This has Sober, . But thaTo evaluate evolutionary factors quantitatively, then, one needs to bridge between the Price equation and the above causal models. This bridge is provided by Wright's method of path analysis Wright, . Below w(1)(a)Cov. According to Wright's method of path analysis  contribute to their covariance, and thus are called active. Hence by identifying such active paths between parental fitness w and offspring phenotype Z1' , we can analyse the ways in which the causal mechanisms introduced above affect the covariance part of the Price equation. The path of standard genetic evolution by natural selection on a trait  is just one among many ways to yield adaptive evolution. For example, if a phenotype responds to heritable habitat variation that affects fitness  and additional variance through which the focal phenotype is affected by natural selection. In such cases evolutionary change is determined not just by the additive genetic variance for trait 1 but also by the heritable variance in trait 2, so the total amount of additive heritable variance is larger. This could result in greater evolutionary change. However, the consequences for the covariance term Cov are more complex: depending on the sign and size of the coefficients of all causal paths, it may increase or decrease. In addition, responsiveness of traits also can have the result that the focal trait is not the only trait that evolves. For example, if a phenotypic trait affects an aspect of the environment as an extended phenotype , which means that the habitat itself may coevolve and respond indirectly to natural selection on the phenotype (in addition to any direct effect of trait Z2habitat on fitness). In summary, the responsiveness of traits can severely alter the evolutionary consequences of variation in fitness [similar to models of indirect genetic effects w ← Z1 → Z1') through which organisms can respond to selection , and only indirectly, and not necessarily so, by underlying genetic variation (as shown by w ← Zi ← Xi). Depending on the strengths of the coefficients and the variance of the variables involved in all relevant pathways, the covariance term  may increase or decrease when non‐genetic inheritance is added. Hence, non‐genetic inheritance of traits can alter the evolutionary consequences of variation in fitness. Ignoring non‐genetic inheritance thus may result in a biased view, which is why we included it in our model.Second, non‐genetic inheritance creates additional active pathways Zi' – Zi). This is because the parental phenotype Z may directly affect the offspring phenotype Z', and by doing so introduce a so‐called ‘transmission bias' at the phenotypic level  . When the prey type first appears in the population, some individuals learn by themselves to use this prey type (Z1 = 1). If every individual learns to feed on this prey type by itself with probability b, then the average phenotype in any generation will be b (=b × N/N), and E(Z1' − Z1) = E(b – b) = 0. In other words, there is no net change in phenotype across generations due to learning , and only a proportion b of all individuals feeds on this advantageous prey type , and learning by themselves in case they did not learn it from their parents already (b × (1 – m × b)), so b + b(m – m × b). This will bias upwards the frequency of type Z1 = 1 individuals in the offspring generation because of the added effect of parent‐to‐offspring transmission (i.e. transmission bias): E(Z1' − Z1) = b + b(m − m × b) − b > 0, i.e. the average phenotype now does change across generations. Moreover, with non‐genetic inheritance, the learned feeding behaviour of parents, grandparents, great‐grandparents, etc. can now all be cumulatively passed down to the next generation(s), and feeding on the new prey may even become a fixed trait in the population because of non‐genetic inheritance (compared to a proportion b without non‐genetic inheritance). Thus the combination of trait responsiveness (here: learning to feed on a prey type available in the environment) and non‐genetic inheritance allows by itself for trait change across generations, without currently acting natural selection as part of the driving mechanism. If the responsiveness of traits increases expected fitness in parents (i.e. it is adaptive), then non‐genetic inheritance provides organisms with a means to pass on this adaptation to their offspring and thereby also increase their offspring's expected fitness.The added mechanisms of our causal model do not only affect the covariance term of the Price equation. Even more importantly, trait responsiveness and non‐genetic inheritance combine also to affect the expectation term E(a)a, a number of molecular epigenetic changes are now known to be transmitted from parent to offspring generations, and these can be involved in adaptive phenotypic plasticity. This phenomenon is captured by Fig. et al., et al., et al., via parental responses is also different from evolution via natural selection, which simplistically speaking (keeping everything else constant) always results in adaptation. et al., et al., Z2 and Z2'), like the size of some physical construction (e.g. a termite mound or a bird's nest). We see that this trait potentially receives several inputs , and may also evolve ion Fig. . It can ion Fig. , but thaion Fig. . With on Dawkins  with hiset al., et al., c, and Woods et al.  is an evolutionary process when it is responsive and the relevant evolving environmental trait is non‐genetically inherited, because then niche construction has evolutionary effects (i.e. causes a heritable change in the trait distribution) independent of any current natural selection or other evolutionary processes  also occurring. One could therefore say that opponents in this debate were all correct in their statements, but only partially, and the reality is slightly more complex: niche construction both is and is not an evolutionary process – it depends on the context. And in our view, it is an evolutionary process specifically and only for the constructed trait (not for any other trait of the organism), but it can be a cause for the evolution of other traits. This complexity should not be ignored, and our causal modelling approach allows people to address this complexity.(c)et al., We briefly repeat the problem. On the one hand, individual habitat choice can lead to local adaptation of populations in heterogeneous environments, the same outcome as for divergent natural selection. On the other hand, remarks such as ‘Of the different evolutionary processes  only natural selection can explain adaptation’  evolved a darker colour to increase crypsis on polluted tree trunks . Treating location as an organismal trait (even though its ‘control’ over it is not obvious at first) is in line with comparative biogeographic and phylogeographic studies that investigate the evolution of distribution ranges .Second, habitat use may also be due to non‐genetic inheritance Fig. . One mecess Fig. . Other met al., et al., et al., Z1 → Z2, highlighted in Fig. X2 → Z2) and imprinting (the arrow Z2 → Z2'). This means that matching habitat choice only has evolutionary consequences if there is also non‐genetic inheritance (the same as for phenotypic plasticity). Since many organisms show some degree of philopatry at the spatial scale of habitat choice, this may not be uncommon (i.e. non‐genetic heritability is larger than zero). Hence, matching habitat choice is another example of how parental responses (acquired traits) might be transmitted to future generations if it combines with non‐genetic inheritance, but an example where it is the chosen habitat that is the trait that evolves. In conclusion, local adaptation due to habitat choice is also adaptive evolution, but it is evolution of the chosen habitat.Finally, habitat use may respond to other traits of the organism Fig. , for exa(d)First, even though the three examples from the introduction seemed to be about very different biological topics and about different ways to achieve higher fitness et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., Our model shows that a broader view of adaptation and evolution may help to explain some puzzling phenomena. Textbooks usually define evolution as change in allele and/or genotype frequencies across generations, and mention natural selection as the only driver of adaptation. However, our model shows that, from a theoretical point of view, both evolution and adaptation can be achieved through different pathways and drivers. This requires some revision of the traditional definitions of evolution and adaptation. We are aware that, sometimes, discussions about definitions can be unproductive . At the same time, great advances in science have also consisted in the formulation of a new meaning of some basic concept (such as time or space in physics). Some people may argue that evolution is ‘by definition’ genetic , non‐genetic inheritance circumvents this limitation. We discuss this second driver in more detail below.(3)We argued that adaptive evolution can be driven by the non‐genetic inheritance of adaptive parental responses, but why would parental responses be adaptive in the first place? Of course they may be neutral or even maladaptive, as mentioned earlier . However, many responses could concern previously evolved adaptive plasticity. Plasticity is expected to evolve to be adaptive when there is heritable variation in it and it influences reproductive success, i.e. if some plasticity outcomes are better than others then natural selection favours the better ones number of offspring. But for the second type of adaptive evolution the driving force is provided by the organism itself, or what we might call differential production of traits. A more active role of the organism in the evolutionary process is increasingly discussed in the literature  and the organism the selective target. But when evolution is driven by organismal responses that are passed on non‐genetically, the response of the organism provides the driving force behind adaptation and so the organism becomes the selective agent. Organismal agency has had a bad history because it has been aligned with sentient action, with mystical ‘vitalistic’ powers, or with the idea that organisms have a desire and goal to evolve to et al., This second driver of adaptive evolution is compatible with the Price equation, since it is part of the second term (the expectation term) of the equation Equation . Historie Frank, b where e Frank, . Here we(6)via parental responses is potentially limited – responses might not be adaptive in that case, which could therefore even lead to maladaptive evolution. However, many if not most ecological challenges are not novel, since environments vary across a rather constant range of spatial or temporal variation , which is exactly why adaptive responses have evolved in the first place – to be able to deal with this range of variation . While this is certainly true, we do not think that open‐endedness is a defining character of adaptive evolution, especially since genetic evolution also has certain limits and constraints so is not open‐ended in all respects et al., et al., That non‐genetic evolution might play a role especially in adaptation at smaller temporal scales is in part because of the stability of the transmitted traits. At the extreme, some parental traits are only transmitted for one generation , whereas others can be transmitted for two  or more than two generations , whereas other environmental variables may cycle over just a few years . Genetic adaptation tends to be slow: even under moderately strong natural selection, alleles take many generations to reach fixation . When environmental change is slow relative to generation time, genetic evolution can keep up with environmental change. But when environmental change is relatively fast, genetic evolution lags. It is here that the transmission of parental responses might provide a much faster evolutionary change. At the extreme, if all individuals of the parental generation respond adaptively to some newly present ecological challenge or opportunity and transmit their response to the next generation, then the ‘fixation’ of the adaptive trait only takes a single generation (compared to many generations in the case of genetic evolution). Once this ecological challenge has disappeared, the population should return rapidly to its initial state, and here a high conversion or decay rate allows exactly that. For ecological challenges that occur over somewhat longer temporal scales, a lower decay rate might be more advantageous . It has therefore been hypothesised that the various means of transmission (genetic and various non‐genetic ones) have evolved to match the temporal scales of different ecological challenges, to allow for an adaptive diversification in how and how rapidly an evolutionary response is brought about  will tell us to what extent this is true.Overall then, we certainly do not want to diminish the general importance of natural selection nor that of genetic inheritance for adaptive evolution. However, we do believe that in many specific cases  adaptive evolution (8)What are the limitations to the causal model we presented, and is it general and flexible enough? Our causal model captures all forms of adaptation as recognised in Edelaar & Bolnick . It doesWhile in those senses very general and flexible, our model does have limitations. Of course it is very simplified and abstracted. A complex process like the development of an organism from genetic and other internal and external  inputs is captured by just a few variables and causal connections. The genetic input itself is also very simplistically described, and leaves out real biology like polygenic causation, epistasis, dominance, pleiotropy, modularity, etc. We did not include this additional detail because we wanted to show the heuristic value of the approach, and the insight that is already gained from it. These extra details can be added to the model by the user if desired, to see whether this provides additional insight or whether the simplification is good enough .et al., et al., Another important simplification we made is the assumption of linearity, which is reflected in our focus on the first‐order Price equation (thus ignoring higher‐order moments) and the assumption that different causal pathways are ‘added up’ to yield the total evolutionary change. When effects are non‐linear functions of their causes, these assumptions do not hold, or at best outcomes of the model are first‐order approximations. To account for non‐linearity one needs to consider derivatives or introduce extra variables representing higher moments versus organism‐centric) view as a particular way of looking at animals and plants, just like one way of looking at a Necker cube . A recent review reaches the same conclusion: the gene's‐eye view is one, but not the only, valid way to study and understand evolution  as primary and ultimate actors of evolution, and conceptualises adaptive evolution as a change of genetic frequencies caused by genetic effects on fitness. Genes take primary responsibility for all that happens in development and evolution, whereas phenotypes and environment are conceived as their effects (as in ‘extended phenotype’) or background parameters. Our approach suggests a different picture, according to which evolution is an outcome of the causal nexus connecting genes, phenotypes, and environmental variables. Which among these factors takes the lead depends on how they are causally configured. In particular, when non‐genetic inheritance is present, genes are not even the ‘ultimate’ cause of development, parent–offspring resemblance, or adaptive evolution. This does not mean that genes are not major components of adaptive evolution. They are. But it does suggest that not everything can always be reduced to genetic evolution. Rather it may be the whole causal structure, consisting not just of genetic but also of phenotypic as well as environmental variables, that evolves Otsuka, a. For en Ågren, . Taking VI.(1)i) a broadened view of extended phenotypes; (ii) that traits can respond to each other; and (iii) that inheritance can be non‐genetic.Certain biological phenomena and various authors suggest that a revision of evolutionary theory would be useful. The use of causal modelling allowed us to produce a general framework for the study and understanding of adaptive evolution that can address some of the challenges. To make the framework general, incorporation of three aspects was deemed critical: ((2)Current mainstream usage of theory on adaptive evolution can be seen as specific applications of our more general framework, and we see our framework as a natural extension of older theory.(3)The extended, more general model of adaptive evolution identifies two complementary yet independently operating drivers of adaptive evolution: natural selection on genetically and non‐genetically transmitted traits, and non‐genetic transmission of parent's adaptive responses.(4)via inheritance of parental responses is captured by an often‐neglected component of the Price equation, which therefore warrants more future attention.Adaptive evolution (5)Our causal model can serve as a heuristic tool to clarify conceptual issues  and to help design empirical research. While it is general and simplified, it can be adjusted flexibly in terms of variables and causal connections, depending on the research question and/or biological system of interest.


Using digital sequence information (DSI) and other publicly available data is supported to assess genetic diversity, toward formulation of practical actions for long‐term conservation of biodiversity, with the particular goal of maintaining ecological and evolutionary processes. Given the inclusion of specific goals and targets regarding DSI in the latest draft of the Global Biodiversity Framework negotiated at the 15 This aspect of biodiversity, however, is often underrepresented in national and international policy dealing with conservation and management of ecosystems and species. This oversight may lead to management tools being applied inappropriately from an evolutionary or genetic perspective, with potential negative consequences for species and ecosystems.The fundamental components of biodiversity are ecosystem, species, and genetic diversity.1 Gene The wildlife ranching industry in Namibia is growing rapidly, and many animals are translocated between southern African countries, and further afield, for conservation purposes. Between 1973 and 1989, more than 700 translocation events took place per year in the USA, Australia, and New Zealand. The goal of translocations  is often to maintain and/or increase genetic diversity in the receiving population. This allows connectivity (gene flow) between populations that have been isolated by human activities, such as land‐use change, urbanization, and fences. Genetic diversity allows populations to adapt to changing conditions over time, including disease outbreaks and environmental changes. The implementation of translocation programs has been instrumental in some of conservation's most celebrated success stories such as the white rhinoceros (Ceratotherium simum), Arabian oryx (Oryx leucoryx), the California condor , and genetic rescue of the Florida panther (Puma concolor coryi).One such key management and conservation tool, globally, is translocation. Between 130 000 and 170 000 animals are estimated to be translocated annually in South Africa alone, predominantly within the billion‐dollar wildlife ranching industry, but also within the national and provincial protected area network.7, 8 Consequently, extensive translocations in the absence of genetic information may threaten the genetic integrity of species and the long‐term resilience of populations, species, and ecosystems. Furthermore, the implementation of translocations is often complex and expensive, and the results are not always desirable. Thus, all available information should be considered when translocations are implemented as a management tool, to maximize the chance of success and minimize the potential harm .Translocation, however, can also be a threat to wildlife, as it may promote unintended hybridization between closely related species, subspecies, or differentiated populations, potentially leading to a breakdown of evolutionary processes.16 Conhttps://www.insdc.org/, and The Barcode of Life Data System, https://www.boldsystems.org).In southern Africa, where translocation of wildlife is common, genetic information is seldom incorporated into the decision‐making process around translocations. This is despite the availability of population‐ and conservation genetics studies and Digital Sequence Information (DSI), which is a policy term that refers to digitally stored information from DNA and RNA . Some of the reasons for this include lack of access  to the relevant literature for conservation managers and permit officials, lack of training in the interpretation of genetic findings, and the authors of such studies not explicitly and adequately stating the conservation or management implications of their findings. One aspect that is not prohibitive in this case, is access to DSI of the species under consideration via public databases  data  can be used to investigate finer scale patterns of population differentiation. It is these patterns and DSI data (uploaded to open access databases) that can be leveraged to improve translocation decisions for the benefit of the species. For example, in lions (Panthera leo), researchers and practitioners have defined conservation units between which translocations should or should not be performed to conserve the evolutionary genetic units of the species.Consequently, access to DSI is an essential resource for southern African researchers in promoting consideration of genetics in translocation policy and decisions. The main idea behind incorporating genetics into translocation decisions is to maintain patterns of genetic diversity and structure (genetic composition) within a species that were generated by evolutionary processes (as opposed to human‐driven processes). These may include, but are not limited to, adaptation of a population to local environmental conditions, genetic differentiation due to the development of behavioral differences that prevent interbreeding between populations even though they might occur in sympatry or the genetic differentiation of populations due to a physical geographic barrier . Many African wildlife species that are commonly translocated show such genetic differentiation patterns across the continent.18 TheDiceros bicornis) and white (C. simum) rhinoceros, Moodley et al. used two publicly available genome sequences (DSI) from one African and one Asian country, and three newly generated genomes from three African countries, to investigate intraspecific gene flow and the evolution of feeding specialization. Another example is for lion (P. leo), where Bertola et al. used 114 publicly available sequences (DSI) from 22 different countries, and 91 newly generated sequences from 18 different countries to investigate the phylogeographic patterns and genetic clustering of African lions. This study, and the data used therein, was a necessary precursor to being able to define lion conservation units for conservation actions (translocation). Thus, by using publicly available DSI, not only is our understanding of the evolution and genetic composition of a species improved, but new biodiversity knowledge is generated, both of which are crucial aspects for biodiversity conservation identified by the Convention on Biological Diversity (CBD). In turn, the new genetic data generated are openly accessible as DSI to other African researchers, to further their understanding of their local populations of a particular species.One way that we leverage DSI from published studies is to combine the genetic sequences available from GenBank with newly generated sequences (often from understudied regions) to obtain a more comprehensive view of the genetic composition of a species. A crucial point mentioned above is the fact that most translocated species occur in more than one African country. Therefore, existing DSI for a species from countries other than the one or two we might have generated new data from is essential to this endeavor. Without the context of DSI from other countries of the species’ range, new genetic data generated will be almost meaningless. For example, for black  states that The Conference of the Parties (COP) “Decides to establish, as part of the post‐2020 global biodiversity framework, a multilateral mechanism for benefit‐sharing from the use of digital sequence information on genetic resources, including a global fund”, and in paragraph 9 states that the mechanism should “Not hinder research and innovation” and “Be consistent with open access to data”. We support this multilateral, open access, and benefit‐sharing option for DSI under the Kunming–Montreal Global Biodiversity Framework. This solution will not only benefit researchers and conservation practitioners from southern Africa, but also those from neighboring countries that often share the inherently valuable wildlife species being translocated, as well as many other African countries where these species occur. A bilateral option, where access to DSI must be applied for and granted through a bureaucratic system, or where access has to be paid for, would have significantly delayed or completely ceased any genetic input to translocation decisions, or prevented any genetic data from being incorporated in the future, to the detriment of all countries involved and the very species we are trying to protect.Goal C in the latest Kunming‐Montreal Global Biodiversity Framework  states “The monetary and non‐monetary benefits from the utilization of genetic resources and digital sequence information on genetic resources, … are shared fairly and equitably”, while Target 13 actions “Take effective legal, policy, administrative and capacity‐building measures…” to implement Goal C.22 Fur Scientists from multiple southern African countries across academia and government, have started such an initiative to aid the conservation of intraspecific biodiversity. The initiative relies on open access to DSI from many African countries and will increasingly rely on DSI as it grows and expands to more countries across the continent. If the genetic composition of African species, most of which have multinational natural distributions, is to be adequately conserved, the continued availability of DSI as a shared resource across the continent is essential. Furthermore, as many African countries have limited resources to generate new DSI, access to existing DSI will allow for collaborations and networks, such as the African node of the IUCN Conservation Genetics Specialist Group, to enhance research capacity and conservation outcomes across the continent.There have been few initiatives across the globe that have tried to standardize the incorporation of genetic data into translocation policy and decisions.25 SciThe authors declare no conflict of interest.The peer review history for this article is available in the Supplementary Information: Record of Transparent Peer ReviewClick here for additional data file.


Forensic parameters suggest that the STRs analyzed here are well-suited for forensic applications. The results of phylogenetic, interpopulation differentiation, and principal coordinates analysis (PCoA) indicate that the Qiang people have extensive connections with ethnic minorities in China, supporting the view that the Qiang people are the oldest group in the entire Sino-Tibetan language family. The Qiang appeared genetically more associated with most ethnic groups in China, especially the Han. The calculation of random matching probability (RMP) was improved by Fst correction of allele frequencies to make RMP more accurate and reasonable. This study can fill in the gaps in the Qiang STR reference database, providing valuable frequency data for forensic applications and evidence for the Qiang's genetic pattern as an important ancestral position in the Sino-Tibetan populations.The Qiang ethnic group is one of the oldest ethnic groups in China and is the most active ethnic group among all the populations along the Tibetan-Yi corridor. They have had a profound impact nationally and internationally. The paternal and maternal genetic feature of the Qiang ethnic group has been revealed, leaving the question of the genetic characteristics from autosomes and X chromosome not answered. The aim of this study was to explore the potential of 36 A-STR (Microreader™ 36A ID System) and 19 X-STR (Microreader™ 19X System) for application in the Qiang population and to elucidate their genetic diversity in southwest China. The cumulative probability of exclusion (CPE) for autosomal STRs is 1–1.3814 × 10 The name “Qiang” first appeared on oracle bones to record the rich interactions and wars between the Han and Qiang people during the Shang Dynasty . The QiaThe Qiang have close ties with more than a dozen of ethnic groups in the southwest of China, some of which are believed to share a common ancestor with the Qiang, while others have received a considerable impact from the Qiang. During the Western Jin Dynasty, conflicts between the Qiang, Han, and Hu people were frequent due to the government's weak control over the Min River region . By the Beichuan Qiang Autonomous County locates in the western part of Mianyang City and the northwestern part of the Tibetan-Yi corridor. Beichuan Qiang Autonomous County is the only Qiang autonomous county in China, located in the northwest part of the Sichuan Basin. It went through a big earthquake in 2008, which was known as “the Wenchuan earthquake”. According to the 7th official population consensus , the totCurrent research on the Qiang ethnic group mainly focuses on history and culture, while studies on the genetic characteristics of the Qiang population have mainly focused on the Y chromosome . Short tTo further trace the Qiang tribe and provide a reference for forensic applications, we constructed an STR database of the Qiang including A-STRs and X-STRs. It is beneficial for forensic practice, as well as studying the genetic relationship and origin between the Sichuan Qiang population and other Chinese reference populations. X-STRs can complement the analysis of A-STRs, e.g. in cases of paternity where the information obtained from standard autosomal markers is uncertain, and in cases of incest where possible related fathers are distinguished .22.1Blood samples were collected from 421 healthy, unrelated, and adult voluntary citizens  living in Beichuan Qiang Autonomous County for three generations. Its approximate location on the map and the extent of the Tibetan-Yi Corridor are shown in 2.2DNA of all samples was extracted using the Chelex-100 method . The sup1 ng template was added to 10 μl of Master Mix III and 5 μl Primer Mix, and then nuclease-free water was added up to 25 μl for Microreader™ 36A ID System. Thermal cycler conditions included an initial incubation for 5 min at 95 °C; 28 cycles of denaturation for 20 s at 94 °C, annealing/extension for 90s at 59 °C and final extension for 60 min at 60 °C; and a final hold at 4 °C. Microreader™ 19X System total reaction volume was 25 μl, including 10 μl of Microreader™ 2.5 × Buffer, 5 μl of Microreader™ 19 X-STR 5 × Primer Mix, 0.1 μl Taq, and 0.5 μl ng of template DNA, and then nuclease-free water was added up to 25 μl. The thermal cycling parameters were set as follows: preincubation at 95 °C for 5 min; 29 cycles of denaturation at 94 °C for 30 s, annealing at 59 °C for 60 s, and extension at 72 °C for 60 s; extension at 60 °C for 30 min, finally holding at 25 °C until the amplification products were removed from the PCR machine.An Applied Biosystems 3500 Genetic Analyzer  was used for all amplification products, using a 36 cm capillary array and POP-4 polymer. 1 μl of PCR products was added to a 9 μl mixture of Hi-Di formamide and a microreader size standard. STR profiles were analyzed by GeneMapper™ ID-X v1.5 software . Allele lengths were determined by comparing the sample PCR fragments with the allelic ladder provided with the kit.2.3The STR data of Qiang was compared with the data of ethnic minorities in China derived from published sources as summarized in 2.4ChrX-STR.org 2.0 [ggridges and ggplot2 packages in R. The heat map is implemented by the readxl, gplots, packages in R. The geographic map was drawn by R packages ggplot2, maps, sf, rnaturalearth, and rnaturalearthdata.Statistical parameters of forensic interest include power of discrimination (PD), matching probability (MP), observed (HO) and expected (HE) heterozygosities, polymorphism information content (PIC), typical paternity index (TPI), power of exclusion (PE) and allele frequencies were determined using modified STRAF 1.0.5  and ChrX.org 2.0 . Hardy–W.org 2.0 . We used.org 2.0  to perfost correction on RMP. The exact test for population differentiation (Fst) was carried out by Arlequin3.5.2 software [st-correction value in the settings and recalculates the corrected RMP. Afterwards, the individual RMP values were compared and the log10 of the ratio was calculated. The RMP was corrected using the correction formula from David J. Balding and Richard A. Nichols [st), the derivation of which is described in detail in the text. The two observed alleles were denoted by A and B, and their proportions in the database population were represented by pA and pB. Then the probability that a suspect has these alleles given that the offender has them is.We used 196 Qiang individuals  alleles absent in the Han Chinese database) at 21 autosomal loci  to analyze the effect of FFor homozygotes, RMP is defined as:For heterozygotes, RMP is calculated as:For structure analysis for autosomal STR, the software Structure v2.3.4  was used33.1The allele frequencies and forensic parameters of the 36 autosomal STR loci are listed in −44, 1–1.3814 × 10−15, and 7.85314 × 10−44, respectively. This indicated that the 36 autosomal STR loci were highly polymorphic and appropriate for individual identification and paternity testing in the studied population.PIC was in the range of 0.584 (TPOX) to 0.948 (SE33), and the most discriminating marker was SE33 with a PD value of 0.989. The observed heterozygosity varied from 0.567 (TPOX) to 0.951 (SE33), and the PE ranged from 0.253 (TPOX) to 0.900 (SE33). The CPD, CPE, and CPM were 1–7.8531 × 103.2st correction. We tested the impact of using different reference frequencies on RMP calculations. First, we used the Sichuan Qiang allele frequency database (generated in this study) and Sichuan Han allele frequency databases, for the RMP calculation of the Qiang individuals. The selected Sichuan Han reference dataset was from a study of 2793 unrelated individuals. In China, the Han Chinese are the dominant population and its frequency database is commonly used in forensic practice. We used 196 Qiang individuals  alleles absent in the Han Chinese database) of the Qiang ethnic group to calculate the RMP using the allele frequencies of their population and that of the Sichuan Han ethnic group. Calculated using the formula in section Using a non-cognate database calculation in the RMP calculation can be detrimental to the suspect, so it is more appropriate to use FThen a parameter quencies . The resst correction (F is set as zero), there is a slight overestimation of the weight of evidence. Applying the Fst correction of 0.0016 is more accurate when using the Sichuan Han database for RMP calculations, with an average d of 0.0102. However, the weight of the evidence in more than half of the cases was still overestimated, which would be magnified by the hypothesis that the suspect was related to the offender [st. When a population has more than one recommended Fst, it is most appropriate to select the Fst that is within the smallest range that can contain cognate and non-cognate databases. The Fst used for the correction cannot be applied to all cases, so the use of a cognate database is necessary.It can be seen that without Foffender . It woul3.3st values and corresponding p-values between Qiang and other reference populations  was observed between the Fujian, She and Yunnan, Du long ethnic groups, whereas the smallest Fst value (−0.0003) was found between Mongolians from Xinjiang and Inner Mongolia. Fst values are larger between ethnic groups in Yunnan and other ethnic groups due to their ethnic diversity and smaller sampling. In general, the Fst value increases with geographic distance.The pairwise Fst. The Qiang are clustered with the ethnic groups in the areas around the Tibetan-Yi corridor and with the Han Chinese in various regions, which illustrates the close relationship between the Qiang and the ethnic groups in the Tibetan-Yi corridor and the extensive contact with the Han Chinese. The ethnic groups of Xinjiang and Mongolia are clustered together, while the rest of the ethnic groups are scattered in other locations, with the Dulong of Yunnan located in a separate group, a small society of only 4000 people with little interaction with modern society [The results of the PCoA are shown in  society .Fig. 2GeSTRUCTURE analysis was performed using Structure v2.3.4 software to genotype 15 STRs from the Sichuan Qiang and other published ethnic groups. Each K = 2–8 for 10 runs; then, the optimal K was selected using Structure Harvester and the results of the calculations are displayed in 3.4st and corresponding p values of 19 X-STRs between females and males in Sichuan Qiang were presented in A total of 333 male and 88 female individuals from the Sichuan Qiang group were analyzed. Allele frequencies for males, females, and pooled are presented in In the linkage group test , after B−17 and 1–9.9450 × 10−11, respectively. The combined mean paternity exclusion chance calculated by the formula of MECKrüger(mean paternity exclusion chance), MECKishida, MECDesmarais, and MECDesmarais Duo are 1–4.7542 × 10−7, 1–7.2687 × 10−11, 1–7.3127 × 10–11, and 1–9.2682 × 10−8, respectively. The forensic parameters described above indicate that the 19 X-STRs in the Microreader™ 19X PCR amplification kit are highly polymorphic and informative in the Sichuan Qiang population and can be used as a powerful tool for forensic complex kinship identification.Forensic statistical parameters are listed in 3.5Current research on X-STRs has focused on the analysis of linkage groups, and such linkage-free X-STR kits are less commonly used. Therefore, to explore the genetic homogeneity and heterozygosity of different ethnic groups in X-STR, two databases were chosen for comparison, the first using the Sichuan Qiang and 15 other ethnic groups using overlapping 7 X-STRs, the second group using the Sichuan Qiang and 7 other ethnic groups using overlapping 19 X-STRs.st genetic distance between the Sichuan Qiang and 15 other ethnic groups using overlapping 7 X-STRs. The pairwise Fst values are listed in st genetic distance: 0.002) appeared between Sichuan Qiang and Guizhou Miao and between Sichuan Qiang and Southern Han. Meanwhile, the Qiang also possessed a close genetic distance (Fst < 0.05) from the Heilongjiang Daur, Guizhou Han, Sichuan Yi, and Sichuan Han.In the first group we calculated the Fst genetic distance. The different ethnic groups are distributed approximately according to geographic location, with the Qiang clustering with the south-western Chinese ethnic groups. The Heilongjiang Daur are closer to the south-western ethnic groups. A similar structure was found in previous studies of the autosomes of the Daur ethnic groups, suggesting that the Daur are genetically more closely related to the western Chinese groups. The ethnic groups of Xinjiang cluster together with the Tibetans of Sichuan, and the ethnic groups of Guangxi cluster with each other. The genetic relationship between Tibetans and Han Chinese is different from A-STR, where Qiang are closely genetically related to Tibetans, but in X-STR the Qiang are distantly genetically related to both Tibetans in Sichuan and Tibetans in Tibet.PCoA is shown in st values are listed in st genetic distance: 0.002) appeared between Sichuan Qiang and Guizhou Han and between Sichuan Qiang and Hubei Tujia. In the heatmap  that failed HWE after Bonferroni correction, in all cases because the homozygote exceeded expectations. DXS6800 also has a low PIC (0.2634) and a gene frequency of 0.8529 for allele 16. A similar situation is seen in many Chinese ethnic groups, but has a high PIC in Europe and Oceania, suggesting that this locus may not be suitable for forensic applications in the Chinese region.st values corrected for other populations or allele frequencies containing combinations of multiple populations should be applied. If not calibrated, the weight of evidence will be overestimated. For Sichuan Qiang, the use of 0.0016 for Fst adjustment is closest to the homology database results, but does not mitigate the overestimation of the evidence in some special cases such as when the suspect is a sibling of the offender. Using 0.0108 mitigates the overestimation of the evidence, but is somewhat overly conservative and underestimates the strength of the evidence across the board. Therefore, the use of a cognate database is more accurate and comprehensive for the estimation of the weight of evidence.In practice, DNA analysts generally place more emphasis on genetic profile matches, and the introduction of RMP and LR allows forensic scientists to assess the strength of evidence. When a suspect is from a small and isolated subpopulation, the population allele frequency should be used preferentially to calculate the RMP. if appropriate data are lacking, then the use of FFor population genetic comparisons of Qiang and other ethnic groups, our genetic results show its historical complexity, which has a non-negligible role in the evolution of many ethnic groups. In the A-STRs, the Qiang show a wide range of close ties with the populations of the Tibetan-Yi corridor. For X-STRs, the Sichuan Qiang are genetically homogeneous with most ethnic groups in southwestern China. All STR markers showed gene flow between the Qiang and Han individuals, which is consistent with previous studies of the Y chromosome. Song et al.  and Wu e5st correction of allele frequencies can make RMP more accurate and reasonable, if non-cognate database was used for RMP calculation. To better understand the genetic structure and inter-population relationships, different STR combinations were applied in the genetic distance calculations to estimate the distant relationships between ethnic groups. Taken together, these results suggest that the Qiang are closely related to the ethnic groups in the Tibetan-Yi corridor and have few genetic differences from the Han Chinese. Our genetic results show its historical complexity, which has a non-negligible role in the evolution of many ethnic groups. The cultural and biological characteristics of this ethnic group are important for population diversity estimation, and further research on it and surrounding population is needed.We have typed the 55 STRs contained in the Microreader™ 36A ID System and Microreader™ 19X System in 481 samples from Sichuan Qiang and provide allele frequencies and forensic parameters for the Qiang population in Sichuan, which will provide valuable assistance in the personal identification and paternity testing. Improving the calculation of RMP by FData included in article/supplementary material/referenced in article.10.13039/501100001809National Natural Science Foundation of China . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This study was supported by grants from the Zefei Wang: Data curation, Formal analysis, Writing – original draft. Mengyuan Song: Data curation, Investigation, Writing – review & editing. Qiang Lyu: Data curation, Formal analysis. Jun Ying: Data curation, Formal analysis. Qian Wu: Data curation, Formal analysis. Feng Song: Conceptualization, Supervision. Lanrui Jiang: Data curation, Formal analysis. Xiaowen Wei: Software. Shuangshuang Wang: Conceptualization, Supervision. Fei Wang: Software. Yuxiang Zhou: Software. Xingbo Song: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. Haibo Luo: Conceptualization, Funding acquisition, Supervision, Writing – review & editing.10.13039/501100001809National Natural Science Foundation of China. Xingbo Song reports financial support was provided by 10.13039/501100001809National Natural Science Foundation of China. Mengyuan Song reports financial support was provided by 10.13039/501100001809National Natural Science Foundation of China.The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Haibo Luo reports financial support was provided by


For all three race distance categories, estimated rates of genetic improvement are statistically significant and also greater than can be explained by drift. Taken together our results show genetic improvement for thoroughbred speed is ongoing but slow, likely due to a combination of long generation times and low heritabilities. Additionally, estimates of realised selection intensities raises the possibility that the contemporary selection emerging from the collective actions of horse breeders is weaker than previously assumed, particularly over long distances. We suggest that unmodelled common environment effects may have upwardly biased estimates of heritability, and thus expected selection response, previously.Several studies over recent decades have reported a lack of contemporary improvement in thoroughbred racehorse speed, despite apparent additive genetic variance and putatively strong selection. More recently, it has been shown that some phenotypic improvement is ongoing, but rates are low in general and particularly so over longer distances. Here we used pedigree-based analysis of 692,534 records from 76,960 animals to determine whether these phenotypic trends are underpinned by genetic selection responses, and to evaluate the potential for more rapid improvement. We show that thoroughbred speed in Great Britain is only weakly heritable across sprint ( Thoroughbreds are the most widely used breed of horse in racing globally. Given the financial incentives and the highly competitive nature of the thoroughbred racehorse breeding industry, it is no surprise that estimates of selection on these horses  have been high for stallions (top 2–6% selected), though less for dams (top 44–61% selected) given they can only produce one offspring each year  and the trait heritability  run on ‘turf’  on GB racecourses. The full dataset comprises 692,534 race times in races held from 1997 to 2014. Given our previous finding that rates of phenotypic improvement in racehorse speed differed across categories of race distance (Sharman and Wilson www.britishhorseracing.com/wp-content/uploads/2014/03/Going-Stick-Average-Readings.pdf). For analysis we converted the finish time (in seconds) of each individual horse to its (average) speed (yards.s−1) by dividing by the known race distance. Strictly this transformation assumes all horses in a race run the same (known) distance  which will not be exactly true.For each performance, we recorded: race identity (RaceID), finishing time, timing method (hand-timed or automatic), race distance , racecourse, official ‘going’ (a measure of ground softness), the number of runners in the race (no.runners), the name, age and sex of horse, and the year of race. ‘Going’ was converted from its official  description to a numerical scale using British Horseracing Authority conversion tables , we included random effects of permanent environment  and trainer identity. This allowed us to partition variance conditional on fixed effects into additive genetic (VA), permanent environment (VPE), trainer (VT) and residual (VR) variances. We make the standard assumption that random effects are normally distributed with means of zero and variances to be estimated, and that residuals are uncorrelated across observations. Hereafter, we will refer to this as Model A.First, using the distance specific data subsets and their associated trimmed pedigrees we fitted three univariate animal models using ASReml (v3). These models (structure A) included a fixed factor of raceID, as well as factors of horse age and sex. Despite being continuous, we elected to fit age as a factor to condition on it without assuming any particular functional form of the average age-speed relationship. This replicates the fixed effect structure previously used to estimate genetic parameters in other racehorse populations  as the ratio of VA to phenotypic variance conditional on fixed effects . We also tested the significance of VA by likelihood ratio test (LRT) comparison to a reduced model in which the additive genetic merit was not included. We assume twice the difference in log-likelihoods is distributed as a 50:50 mix of χ21 and χ20  by year of birth for those horses in each dataset born between 1995 and 2012 and racing between 1997 and 2014. Mean PBV was then regressed on time  to estimate the rate of genetic change (βG). We did this using PBVs for sprint, middle-distance, and long-distance speed traits separately.After fitting Model A to each distance-category data subset we estimated the heritability . Horse-level effects of age and sex were included as described above for Model A and the random effect structure was unchanged.The computational problems encountered arose in large part from the high number of parameters entailed in fitting RaceID as a factor. Therefore we formulated a second model structure in which this effect was replaced with a set of race-level covariates previously identified as important drivers of among-race differences in average speed in our earlier work . We also checked autocorrelation between saved sample was low , and comparison of model parameter estimates to those from the corresponding REML models  provided further post hoc validation.We first fitted a univariate formulation of Model B to each distance category data subset in ASReml and verified that point estimates of temporal trends in breeding values were similar to those from Model A (see results). We were then able to successfully fit a trivariate REML model of speed in the three distance categories. We then refitted the three univariate models using MCMCglmm. For each distance category, a Markov chain of 2,000,000 iterations with a burn in of 800,000 and a thinning interval of 1200 (resulting in a posterior of 1000 samples) was used. Inverse Wishart priors with nu = 0.002 were specified for all variance components. Convergence was assessed by visual inspection of model posteriors, and by application of Heidelberg stationarity tests (G) of mean genetic merit on birth year and extracted the posterior mode as our point estimate of change. We determined the posterior where βG > 0 and conclude a ‘significant’ genetic contribution to phenotypic improvement if this proportion is >95%. However, noting that temporal changes in mean breeding value are expected under neutrality, we then applied a more stringent test to determine whether the estimated rate of genetic change was greater than could be explained by drift alone  ; h2middle-distance = 0.122 (0.007) ; and h2long-distance = 0.074 (0.012) . As expected from previous studies showing among-horse variance . Though not directly relevant to current aims, estimates of these variance components are shown in Supplementary Table Univariate animal models fitted by REML under Model A confirmed the presence of low, albeit significant, levels of additive genetic variance underpinning speed Table . For theG = 0.009 yards.sec−1.year−1) and lowest over long distances (βG = 0.001 yards.sec−1.year−1). As a proportion of previously reported phenotypic trends .Analyses of PBVs extracted from Model A yielded positive estimates of genetic trends for speed in all three distance categories Table . In absoG that were quantitatively similar . Estimated genetic correlations were strongly positive between speeds sprint and middle-distance speed (rG = 0.867 (0.019)) and between middle and long-distance speed (rG = 0.837 (0.032)). A more moderate correlation was found between sprint and long-distance speeds (rG = 0.467 (0.006)). Assuming approximate 95% CI of rG ± 1.96SE implies all three genetic correlation estimates are significantly greater than zero, but also significantly less than +1. More formally, LRT comparison showed the unconstrained model was significantly better than one in which we constrain rG to equal +1 between each pair of traits .Under Model B heritability estimates are conditional on a different fixed effect structure and are not directly comparable .Our primary conclusion, that genetic improvement in thoroughbred racehorse speed is ongoing, contrasts qualitatively with earlier studies that argued speed was no longer increasing because the trait had reached a selection limit imposed by some form of genetic constraint Denny . Thus, w−1 . This strongly suggests that trainer effects, if not modelled, will be a source of common environment variance that can upwardly bias VA and inflate estimates of genetic change.Conversely, much higher rates of improvement than detected here have been reported in some previous studies. For instance, in Quarter horses, a breed which races over distances of 301–402 m, genetic improvement rates as high as 0.4% year −1 Hill . No meas −1 Hill . While ni for each trait can be calculated as follows , h is the square root of the heritability, n is the number of observations per individual, and R is the trait repeatability. Setting L to 9.2 for sprinters, 9.5 for middle-distance and 9.8 for long-distance , n  to 5.96 (sprint), 5.10 (middle-distance) and 3.59 (long-distance) and letting R = (VA + VPE)/VP then substituting in our parameter estimates from univariate analyses under Model A yields values of isprint = 1.202, imiddle-distance = 0.905, and ilong-distance = 0.317. Reiterating that these are illustrative calculations made with strong assumptions, they suggest selection could be weaker than previously estimated. For example, isprint = 1.202 equates to selecting approximately 28% of the population under truncation selection. This compares to estimates of selection  on Timeform handicap ratings of 23% , a result that mirrors a recent finding in Brazilian thoroughbreds (da Mota rG = 1 across distances (Hill et al. A final point emerging from our analysis is that the three distance-specific speed traits offer distinct selection targets in the sense that all pairwise genetic correlation are less than +1. We also find that the heritability of speed is lower over long-distance races, a result consistent with several other studies of finishing times (Oki et al.  da Mota . Biologi da Mota . Indeed,In summary, we show here that speed in thoroughbred horses is heritable across categories of race distance. We also show that genetic improvement attributable to selection is contributing to previously demonstrated weak - but non-zero - rates of phenotypic improvement. However, our analyses also show that selection responses are of a limited magnitude, particularly for long-distance race performance. Low heritabilities and among-distance genetic correlation structure contribute to this pattern but weaker selection than previously assumed also seems possible. Accuracy of selection may be low across all distance categories, particularly given that modern genetic tools are rarely applied in thoroughbred breeding. This obviously contrasts with most livestock species in which much more rapid selection responses are regularly achieved.Supplementary material


Mental imagery refers to the representation of stimuli that are not physically present and has long been a subject of interest in psychology. However, most research on mental imagery has been limited to visual images, with other types of imagery, such as sound and smell, receiving little attention. A possible reason for this is the lack of appropriate scales to measure the vividness of multisensory imagery. The Plymouth Sensory Imagery Scale (Psi-Q) has been developed to address this issue and has been used in several studies to measure the vividness of seven imageries: vision, sound, smell, taste, touch, body, and feeling. In this study of 400 participants in Japan, the Psi-Q was translated into Japanese and tested for reliability and validity. The results showed good internal reliability and retest reliability and moderate to high correlations with other measures of construct validity, including mindfulness, Big Five, and life satisfaction. Additionally, there is no significant difference in total Psi-Q scores between the Japanese and British samples, although some differences are found in individual sensory imagery abilities. This study provides valuable insights into multisensory mental imagery, and it is expected that research dealing simultaneously with the responses of multisensory modalities will further accumulate. This has demonstrated construct validity ; α = 0.93–0.96 for the Psi-Q; α = 0.80–0.97 for the subscales), and retest reliability (r = 0.43–0.84). Since then, the Psi-Q has been translated worldwide, including a Spanish version  and correlation with the QMI (r = 0.40–0.56), confirming its construct validity. The Dutch version showed a seven-factor structure, similar to the original version, with adequate to good internal consistency  and test–retest reliability , and construct validity (r = 0.32 with SUIS) using two surveys of students and a general sample. Translating and developing the Psi-Q in Japan will ensure the measurement of multisensory imagery ability simultaneously and confirm that the same factor structure can be found across cultures.Mental imagery is defined as “an internal representation of stimuli that are not physically present , p. 175” version  and a Du version , and hasr = 0.23–0.47, ps < 0.01), while only bodily and feeling imagery was not correlated with “Act with awareness” , suggesting that there were differences across sensory organs. In addition, the Psi-Q has been used in behavioral experiments; for example, B = 0.34, p < 001), while bodily imagery ability predicted relaxation most successfully . Thus, it is important to simultaneously measure individual differences in multisensory imagery ability and identify commonalities and differences among sensory organs. In this study, in addition to mindfulness, we further aim to deepen our understanding of multisensory mental imagery by examining its relevance to other scales, such as the Big Five and Satisfaction with Life Scale, because these measures have not yet been examined in relation to multisensory imagery abilities but have been shown to be associated with single modalities such as visual imagery . All data and scripts are available online.2.1.M = 40.72, SD = 10.73; 155 men, 234 women) were analyzed, excluding those with extremely short response times and those who missed the attention check. To examine retest reliability, the same participants were invited to respond again 1 week later. Data from 344 participants , whose ID matched their first completed questionnaire, were used for the retest reliability analysis.Four hundred people were recruited through the Japanese crowdsourcing platform CrowdWorks.2.2.2.2.1.After obtaining permission from the original authors, the first author, a fluent and native Japanese speaker, translated the Psi-Q into Japanese . All ite2.2.2.The VOIQ is a 14-item scale measuring olfactory imagery ability . The res2.2.3.The AIQ is a 12-item scale measuring auditory imagery ability , using a2.2.4.This shortened version of the Big Five Scale is a 29-item scale measuring the Big Five of extraversion, agreeableness, neuroticism, openness, and conscientiousness . The res2.2.5.The shortened version of the Five Facet Mindfulness Questionnaire is a 24-item scale consisting of five factors  measuring trait mindfulness . A 5-poi2.2.6.The Satisfaction With Life Scale is a one-factor, five-item scale measuring life satisfaction . A 7-poi2.3.The participants, recruited through Crowdworks, completed a web-based questionnaire created by Qualtrics. The participants were briefed on the survey and signed an informed consent form. They then began with responding to the Psi-Q, followed by the other five scales, which were presented in a randomized order. The items were also presented in a randomized order. The survey took approximately 10 min to complete. One week later, the same participants responded to the Psi-Q as described above.2.4.fa function of the psych package (cfa function from the lavaan package (2), goodness of fit index (GFI), adjusted GFI (AGFI), normed fit index (NFI), comparative fit index (CFI), root mean square error of approximation (RMSEA), and Akaike’s information criterion (AIC). To examine internal reliability, we used the alpha function from the psych package, and retest reliability was confirmed by calculating correlations with data obtained from the same sample 1 week later. For the British sample, we used data from Study 2 of t.test function and the mes function from the compute.es package , when retests were conducted 1 week apart.As a result of the factor analysis, a six-factor Psi-Q structure was employed, and its descriptive statistics and internal reliability for the entire scale and each factor were calculated . The res3.3.To examine construct validity, correlations with other measures were calculated .r = 0.68, p = 0.00), which measures auditory imagery ability, and the VOIQ , which measures olfactory imagery ability. There are also positive correlations with the Big Five factors of extraversion , openness , and agreeableness , and a negative correlation with neuroticism . In addition to the positive correlation between the total FFMQ scores and the Psi-Q , the Observe factor and each subfactor of the Psi-Q shows moderate correlations . Life satisfaction and total scores on the Psi-Q and each subscale are positively correlated . Age  and gender  also correlated positively with the Psi-Q. This indicates that older participants and female participants have higher imagery ability. These correlations indicating construct validity were significant, but the effect sizes were week to moderate.The results show moderate to high correlations and validity with existing measures of imagery ability, with total Psi-Q scores correlating with the AIQ  = 1.06, p = 0.30, η2 = 0.001], a significant main effect of modality , and a significant interaction . Multiple comparison showed significant differences of sound , smell , taste , and touch  between cultures. For sound and taste, Japanese scores were higher than British scores. For smell and taste, British scores were higher than Japanese scores. The culture differences for overall Psi-Q score , vision , and body  were non-significant.Finally, we compare the Psi-Q scores of the Japanese sample in this study with the British sample in the original study . ANOVA r4.4.1.In this study, we developed a Japanese version of the Psi-Q , which m4.2.To examine construct validity, we used scales that have already been shown to be related to existing imagery ability scales and the Psi-Q, as well as scales that are newly examined in the present study. First, the validity of the Japanese version of the Psi-Q was confirmed by its moderate to high positive correlations with olfactory imagery ability  and audi4.3.dashi  can be found in the article/The studies involving human participants were reviewed and approved by Ethics Committee of Kyoto University. The patients/participants provided their written informed consent to participate in this study.JH: conceptualization, methodology, software, formal analysis, writing – original draft, and visualization. MN: conceptualization, methodology, writing – review and editing, and supervision. All authors contributed to the article and approved the submitted version.This research was supported by Grants-In-Aid for Scientific Research .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Lipid accumulation causes diseases such as obesity and abnormal lipid metabolism, thus impairing human health. Tea polysaccharide is one of the natural, active substances that can lower lipid levels. In this paper, an oleic-acid-induced HepG2 cell model was established. The lipid-lowering effects of a novel group of Fuzhuan brick tea polysaccharides (FTPs)—obtained from Fuzhuan brick tea—were examined in vitro. The monosaccharide composition of FTP3 was Glc, Gal, Ara, Man, Rha, GalAc, GlcAc, and Xyl with a molar ratio of 23.5:13.2:9.0:5.5:5.4:2.7:1.3:1.0, respectively. A molecular weight of 335.68 kDa was identified for FTP3. HepG2 cells treated with FTP3 achieved a prominent lipid-lowering effect compared with cells treated with oleic acid. Images of the Oil Red O staining treatment showed that FTP3-treated groups had significantly fewer red fat droplets. TC and TG levels were lower in FTP3-treated groups. FTP3 alleviated lipid accumulation in HepG2 cells, activated AMPK, and decreased the SREBP-1C and FAS protein expressions associated with fatty acid synthesis. FTP3 holds promising potential for its lipid-lowering effects. At present, with increasing consumption levels, poor living habits such as staying up late, lack of exercise, and irregular diet are on the rise, which often results in increased lipid levels in the human body. Excessive lipid accumulation in the body causes lipid metabolism disorders, which then lead to obesity, nonalcoholic steatohepatitis, and other metabolic diseases . ExcessiCamellia sinensis) that has undergone fungal fermentation [Natural chemical compounds derived from plants are called phytochemicals, which have recently received increasing attention because of their substantial pharmacological activities and few side effects ,5. Fuzhuentation . FBT is entation . FBT conentation . In partentation . Chen etentation . Relatedentation ,12. FBT entation . Moreoveentation . Xiao etentation . HoweverFBT was purchased from Shaanxi Jingwei Fuzhuan Brick Tea Co., Ltd. . DEAE-cellulose DEAE-52 , cellulase, papain, α-glucosidase , acarbos (95%), PNPD, α-amylase (50 U/mg), Sephadex G-200 (Φ20 × 600 mm), and microporous membranes were obtained from Shanghai Yuanye Biotechnology Co., Ltd. . DMEM high-glucose medium, penicillin–streptomycin, and trypsin-EDTA were obtained from Bioengineering Co., Ltd. . Oil Red O staining solution and blue cell viability dye were obtained from Suolaibao Biotechnology Co., Ltd. . Anti-β-actin, anti-SREBP-lc, anti-FAS, anti-AMPK, and anti-P-AMPK were obtained from Cell Signaling Technology . All other reagents were of analytical grade and were obtained from Tianli Chemical Reagent Co., Ltd. .w/w) at a concentration of 2% was added to 50 g of FBT powder and extracted for 60 min at pH 5.0 and 55 °C. The supernatant of the extract was filtered and concentrated. Protein was removed with Sevage reagent (n-butanol:chloroform = 1:4). The polysaccharide was refrigerated at 4 °C for 12 h and then centrifuged, fully dissolved in water, and freeze-dried. The obtained polysaccharide powder was then dissolved in distilled water, and the DEAE-cellulose DEAE-52 column chromatography method was used for purification. Purification was followed by an elution using NaCl . The section was collected and then purified with distilled water through Sephadex G-200 columns. The major peaks were collected, lyophilized, and named FTP3 [A mixture of papain and cellulase  [UV spectral analysis was conducted according to a previously published method , with slGermany) .In brief, using a capillary tube, FTP3 powder was immersed in conductive gel and mounted on a sample holder. After gold sputtering, SEM  was conducted to examine and image the surface structure of the polysaccharide sample .In accordance with the above-mentioned method, high-performance size-exclusion chromatography coupled with multi-angle laser light scattering and a refractive index detector  was used to determine the Mw of FTP3 . FTP3 seFTP3 (20 mg) was dissolved in heavy water. Then, the sample was filtered through a microporous filter membrane (0.22 μm) and subsequently transferred to an NMR tube for 1H-NMR and 13C-NMR analysis  .For the following series of experiments, the FTP3 solution was prepared at a mass concentration of 0.5 mg/mL; Congo red solution was prepared at a concentration of 50 μM; and NaOH solution was prepared at a concentration of 0–0.50 M. Congo red maximum absorption wavelengths were measured at 200–600 nm in different concentrations of NaOH solution.With continuous stirring at 25 °C for 4 h, FTP3 (10 μg) was dissolved in ultrapure water (1 mL). Samples were dropped onto a mica carrier, dried at 70 °C under ambient pressure, and analyzed [2). The DPPH solution was replaced by absolute ethanol, and the mixture was vortexed (A1). Absolute ethanol was used instead of the sample solution, and the mixture was vortexed (A0). After the solution was in the dark at 25 °C for 30 min, the absorbance was determined at 517 nm. The clearance rate of DPPH· in the sample was calculated according to Equation (1) [FTP3 and vitamin C (Vc) were dissolved in distilled water to obtain solutions with concentrations of 0.025, 0.05, 0.1, 0.2, 0.4, and 0.8 mg/mL. Vc was used as a positive control. To each of the above concentration gradients (2 mL), DPPH solution (0.05 mg/mL) was added, and the mixtures were vortexed (Ation (1) :(1)%DPPH2O2, 9 mmol/L FeSO4, 9 mmol/L salicylic acid absolute ethanol solution, and distilled water were mixed, and the mixture was vortexed and incubated at 37 °C for 35 min. The absorbance value at 510 nm was measured (A2). The H2O2 solution was replaced with distilled water (A1), and the sample was replaced with distilled water (A0). The clearance rate of ·OH in the sample was calculated according to Equation (2) [A total of 1 mL of each concentration of FTP3 and 1 mL each of 9 mmol/L Htion (2) :(2)%OH·r2 represents the absorbance of FTP3 measured at 320 nm. A1 and A0 represent the absorbance of distilled water instead of the pyrogallic acid solution and distilled water instead of the sample solution in the blank group at 320 nm, respectively. The clearance rate of O2−· in the sample was calculated according to Equation (3) [To 1 mL of the test solution, 3 mL Tris-HCl (pH 8.2) was added, and the mixture was incubated at 30 °C for 20 min. Then, 3 mL of 5 mmol/L pyrogallic acid was added at 25 °C, mixed, and left to settle for 3 min; then, the reaction was terminated by the addition of 1 mL of HCL. Ation (3) :(3)%O2−rThe inhibitory activity of FTP3 on α-glucosidase was measured based on the method of Li et al.  and Ren 1, and the cholesterol solubility of the blank group is C0. The cholesterol binding rate was calculated as (1 − C1/C0) × 100%.Cholesterol micelle solution was prepared  at 15 mmol/L at a pH of 7.4). FTP3 (10 mg) was added to micelle solutions, and micelle solution without a sample was used as a blank control. Samples were centrifuged after shaking at 37 °C, the supernatant was obtained, and the cholesterol level was measured with a kit . The cholesterol solubility of the sample group is C1, and the concentration in the blank solution is C0. The bile acid binding rate was calculated as (1 − C1/C0) × 100% [Mother liquor of sodium taurocholate, sodium glycocholate, and sodium cholate solution (0.3 mmol/L) was prepared with 0.1 mol/L of PBS at pH 7.6. Seven tubes with plugs were filled with 0, 0.1, 0.5, 1.0, 1.5, 2.0, and 2.5 mL of the above mother liquor. Then, PBS was added to bring the total amount to 2.5 mL, and 7.5 mL of sulfuric acid solution (60%) was also added. After 20 min of incubation in a water bath at 70 ℃, the solution was cooled in ice water for 5 min and measured at 387 nm. After this, FTP3 was put into these test tubes; then, hydrochloric acid solution  was added, and the mixture was shaken and digested at 37 °C for 2 h. The pH was adjusted to 7.6, 4 mL of cholate solution was added, and the mixture was oscillated at 37 °C for 2 h. The absorbance of FTP3 was measured, and the bile acid salt concentration was obtained based on the standard curve. The concentration of bile acid salt in the sample solution is C) × 100% .v/v) heat-inactivated fetal bovine serum (FBS), and a penicillin–streptomycin mixture was used to incubate cells in 5% CO2 at 37 °C. All experiments used cells at the logarithmic stage [To examine the mechanisms by which FTP3 improves lipid metabolism, an in vitro cell model of the human hepatoma cell line (HepG2) was used to study the disruption of lipid metabolism. HepG2 cells were obtained from Cell Bank, Chinese Academy of Sciences. The cells were grown in DMEM containing 2%  solutions (prepared with medium containing 2% FBS) at concentrations of 0, 100, 200, 300, 400, and 500 μM for both 24 and 48 h. After incubation, 100 μL of 5% MTT solution was added to each well in the dark. After 4 h of incubation in 5% CO2 at 37 °C, the supernatant was aspirated out, and 100 μL of DMSO was added to each well. The viability of cells was calculated by shaking the 96-well plate for 10 min and measuring the absorbance at 490 nm.Cells were washed with PBS and digested with trypsin. The appropriate complete medium was added, and the cell suspension was centrifuged at 1000 rpm for 3 min. Then, the supernatant was discarded, and a complete medium was added. Cell suspension was added to a 96-well plate, and the concentration of cells was maintained at 1 × 10The preparation method of the stock solution is described in the following: OA was dissolved in 0.1 mol/L NaOH and heated in a water bath at 70 °C to obtain a 100 mmol/L stock solution. The solution was slowly added to BSA solution with a mass fraction of 10% in a water bath (55 °C) to prepare OA solution at a concentration of 10 mmol/L; this solution was then filtered through a 0.22 μm filter membrane to remove bacteria, and the filtrate was frozen at −20 °C. Before use, the cells were bathed in water at 55 °C for 15 min, cooled down to 25 °C, and diluted to the desired concentration with DMEM high-glucose medium containing 2% FBS. Intracellular lipid droplets were detected using Oil Red O staining with a concentration of 400 μM. Following this staining step, the unbound dye was removed by rinsing the cells with water. Stained lipid droplets were visualized within cells using a digital camera attached to a light microscope at a 200-fold magnification. Microplate readers at 490 nm were used to measure cholesterol accumulation .Cells were lysed using lysis buffer and centrifuged at 4 °C for 15 min at 4000 rpm. In the cell supernatant, the levels of TC, TG, and malondialdehyde (MDA) were measured. The activities of alanine transaminase (ALT), aspartate aminotransferase (AST), superoxide dismutase (SOD), glutathione peroxidase (GPX), and reactive oxygen species (ROS) were assessed using commercial kits  according to the instructions of the manufacturer .Following the instructions of the manufacturer, total RNA was extracted using a high-purity total RNA rapid extraction kit , and the absorbances of the RNA extracted from the sample were measured at 260–280 nm . Using AWestern blot was performed following a previously reported method . As primp < 0.05.Data obtained from triplicate experiments were calculated as means ± SD. and differences between groups were assessed via one-way analysis of variance. The statistical analyses were conducted using SPSS version 17.0. Differences were considered statistically significant at The polysaccharide content of FTP3 was 77.72 ± 0.83%, the content of protein was 0.28 ± 0.15%, the total phenol content was 1.63 ± 0.22%, and the uronic acid content was 20.09 ± 0.62% (identifying FTP3 as an acidic polysaccharide).In a scanning range of 200–400 nm, there was no absorption peak in FTP3 after DEAE-cellulose and Sephadex G-200 column chromatography. This lack of absorption peak indicated that the method successfully removed proteins from samples and thus obtained protein-free FTP3 A.−1, and C-H stretching vibrations were found at 2956 cm−1. The broad bands at 1650–1900 cm−1 were attributed to C=O stretching vibrations. The signals at 1597 cm−1 and 1412 cm−1 were attributed to uronic acid stretching vibrations, which identified FTP3 as an acidic polysaccharide [−1 and 1200 cm−1. The absorption of FTP3 was around 873 cm−1, caused by a linkage of β-glycosides. As shown by the absorption band at 818 cm−1, FTP3 had a linkage of α-glycosides in its molecular structure.The FT-IR spectrum of FTP3 is shown in ccharide . The preAs shown in 1H-NMR, presented above. The δ > 170 ppm carbon signal indicates that FTP3 contains uronic acid. The chemical shift of FTP3 demonstrated signal peaks at 175.80 ppm and 182.55 ppm, indicating that FTP3 may contain uronic acid, which is an acidic polysaccharide.As shown in SEM images provide visual evidence of FTP3 morphology. As shown in The plan view and the cubic spectrum of the AFM of FTP3 are shown in Concentration-dependent DPPH radical scavenging activity was verified in 0.025–0.8 mg/mL FTP3. The highest scavenging activity was 84.82% of 0.8 mg/mL FTP3 A. With iAs a result of the use of α-glycosidase and α-amylase inhibitors, glucose levels from carbohydrates decreased in response to the inhibition of enzyme activities, thus delaying the absorption of carbohydrates by the human body. As shown in The in vitro binding capacity of FTP3 to bile acid salts was 53.86% F, which The effect of FTP3 on cell viability was detected using an MTT assay. As shown in Six groups of HepG2 cells were tested: a negative control (NC) group, an oleic acid (OA) group (400 μM OA), a low-dose (LD) group (400 μM OA + 25 μg/mL FTP3), a medium-dose (MD) group (400 μM OA + 50 μg/mL FTP3), a high-dose (HD) group (400 μM OA + 100 μg/mL FTP3), and a positive control (PC) group (100 μg/mL simvastatin). As demonstrated in TG and TC concentrations in HepG2 cells were determined to evaluate the role of FTP3 in lipid accumulation. TG and TC levels were decreased progressively following FTP3 treatment for 24 h over a sample range of 25, 50, and 100 μg/mL. The low, medium, and high doses of TG levels following FTP3 treatment were 1.66, 1.48, and 1.34 mmol/gprot, respectively A, and TCThe AST and ALT activities of hepatocytes are important liver injury indicators. In the experiments, following the OA treatment of HepG2 cells, the AST activity reached 11.34 U/gprot, and a noticeable difference was found between the group treated with OA and the control group in terms of ALT activity (59.12 U/gprot). The treatment of cells with different concentrations of FTP3 significantly reduced AST and ALT activities compared with the OA group. These results indicated that FTP3 could attenuate damage caused by the OA treatment in HepG2 cells C,D.SOD and GPX can effectively scavenge free radicals and prevent oxidative damage. As depicted in MDA levels provide an indication of oxidative damage in cells, as this indirectly reflects the severity of free radical attacks. As shown in As depicted in FTP3 affected the expression of AMPK, p-AMPK, SREBP-1c, and FAS in HepG2 cells. As indicated in 2−· [2−·, which may be due to the presence of uronic acid.In this study, the novel polysaccharide FTP3 was obtained via isolation and purification from FBT. FTP3, which has a molecular weight of 335.68 kDa, is composed of Rha, Ara, Gal, Glc, Xyl, Man, GalAc, and GlcAc, identifying it as an acidic polysaccharide. Excessive levels of free radicals can lead to increased oxidative stress (OS) in vivo. OS is associated with the occurrence and development of a variety of diseases arising from disorders of lipid metabolism . Plant p2−· , and the2−· . The in 2−· , showingZhu et al.  demonstrSchisandra polysaccharides adjust AMPK expression in a strict dose-dependent relationship. FTP3 may reduce lipid levels and promote fatty acid oxidation by activating AMPK. These results illustrated that the mRNA expressions of SREBP-1c and FAS were noticeably upregulated after OA-induced lipid deposition in HepG2 cells, which was in accordance with the observed increased lipid deposition in HepG2 cells. Compared with the OA group, both SREBP-1c and FAS were downregulated in the mRNA expression after FTP3 treatment, indicating that FTP3 can reduce lipid levels by inhibiting fatty acid synthesis. In the present study, the upregulation of P-AMPK protein expression and the downregulation of both SREBP-1c and FAS protein expressions induced by FTP3 indicated that, in HepG2 cells, OA-induced lipid accumulation was alleviated. FTP3 may exert lipid-lowering effects by regulating AMPK, SREBP-1c, and FAS protein expressions (By activating the AMPK pathway, cells can adjust lipid metabolism by influencing genes and protein expressions associated with lipid deposition . The SREressions .The polysaccharide structure is closely related to activity ,55. The FTP3 is an acidic polysaccharide that has a powerful effect on decreasing TG, TC, ROS, and MDA contents and the activities of ALT and AST while also increasing the activities of SOD and GPX in HepG2 cells induced by OA. In Oil Red O-stained FTP3 samples, significantly fewer red fat droplets were observed. Moreover, FTP3 stimulated both the gene expression and protein expression of AMPK, SREBP-1C, and FAS. The current research used in vitro cell experiments and showed that FTP3 has a lipid-lowering effect. This is a preliminary study of FTP3. In the future, a high-fat animal model will be established, and the lipid-lowering effect and dosage of FTP3 will be determined in vivo. In addition, a simulated digestion method will be constructed in vitro to analyze the degree and rate of FTP3 digestion. This study provides a basis for the application of FTP3 to functional foods with the ability to regulate lipid accumulation.