We also tested for changes in genetic diversity using the up to 750-year-old mitochondrial genomes from pre-European archaeological sites to assess the potential impacts of human exploitation. Nucleotide diversity and haplotype diversity was high . There was no significant change in nucleotide diversity over the last 750 years (p = 0.343), with no detectable loss of diversity as a result of indigenous and industrial-scale fishing activity. While there was no evidence for contemporary population structure , phylogeographic analyses identified two distinct mitochondrial clades that diverged approximately 650,000 years ago during the mid-Pleistocene, suggesting the species experienced barriers to gene flow when sea levels dropped over 120 m during previous glacial maxima. An exponential population increase was also observed around 8000 years ago consistent with a post-glacial expansion, which was likely facilitated by increased ocean temperatures and rising sea levels. This study demonstrates that glacial cycles likely played an important role in the demographic history of C. auratus and adds to our growing understanding of how dynamic climatic changes have influenced the evolution of coastal marine species.Glacial cycles play important roles in determining the phylogeographic structure of terrestrial species, however, relatively little is known about their impacts on the distribution of marine biota. This study utilised modern ( Phylogeographic studies have provided key insights into past demographic changes such as population expansion, contraction and fragmentation. Geological processes such as continental drift, mountain formation, climatic changes, shifting sea currents, and Pleistocene glacial-interglacial cycles have been shown to play important roles in the evolution and phylogeographic structuring of biodiversity  is a common coastal fish species in the waters around the North Island, and the northern South Island of New Zealand , and its distribution is primarily determined by water temperature  deposits   has contributed to large reductions in population size of New Zealand C. auratus throughout New Zealand. Specifically, the following questions are addressed: (1) is there evidence of phylogeographic structure and demographic change associated with Pleistocene glacial cycles; and (2) can past changes in abundance be detected in patterns of genetic diversity, including a potential loss of genetic diversity caused by high fishing pressure since humans colonized New Zealand?Recent studies have shown great potential for the retrieval of ancient DNA from fish bones . Portions of the tooth-row were removed in a sterile extraction hood using a Dremel cutting disk (whilst preserving morphometric landmarks) and powdered using a sterile mortar and pestle. Ancient DNA was extracted following Boessenkool et al. , in accoC. auratus . Double-stranded, double-indexed sequencing libraries were constructed from USER-treated DNA template Kircher . QualitySequenced reads from modern and ancient samples were processed using the bam_pipeline in PALEOMIX v1.2.13.3  files were generated from the BAM files. This was done using GATK’s HaplotypeCaller, using the mitochondrial genome of e Ashton , settingPagrus major) from Japan were used as the outgroup sequences .Ten whole-genome-sequences from wild-caught red seabream (https://www.geneious.com). The annotated mitochondrial genome of C. auratus was compared for consistency to the annotation of the red seabream, obtained from the Mitochondrial Genome Database of Fish, MitoFish  were grouped as if the 3rd codon was the first. PartitionFinder2 identified four distinct partitions that followed different substitution models , haplotype diversity (h), genetic diversity (θ), were estimated using the R-package pegas , and 3.28e−9 site−1/year−1, respectively , and P. major mitogenomes had an average coverage of 270× . We generated and skim-sequenced 62 libraries out of the 90 successfully extracted ancient specimens. For these libraries levels of endogenous DNA ranged between 0.003% and 58%  and ranged between 0.932 and 0.989 among populations. High haplotype diversity was also observed in the rarefaction curve  and genetic diversity (θ = 54.47–64.35) of modern sequences was consistent across populations (Table p = 0.343).In total, 472 polymorphic sites resulted in 233 unique haplotypes Table . The overve Fig. . Nucleotns Table . We did ns Table . Tajima’ns Table . Diversins Table , with noDA) of 0.84%. Eight minor clades were subsequently identified . There was also no significant mitochondrial structure observed between two genetic clusters identified using whole-genome data obtained from the high-throughput sequences used for this study (p = 0.104)   during the mid-Pleistocene  diverged around 727,000 years ago , which was not significantly different from when the major clades observed in C. auratus diverged. Nodes T2 and T3 were estimated at ~150,000 years ago. A large radiation of new lineages was observed in all models between 7,000 and 35,000 years ago (T4) . The Extended Bayesian Skyline Plot analysis also showed that C. auratus experienced an exponential population increase approximately 8,000 years ago  Fig. . A populC. auratus. Below, we discuss how glacial cycles had a major impact on the phylogeographic structure and population abundance of C. auratus. Finally, we will discuss the effect of historic structure on the contemporary estimates of genetic diversity, and the potential effect of exploitation on genetic diversity.We used contemporary and ancient mitochondrial genomes to investigate the phylogeographic and demographic history of C. auratus individuals in New Zealand . This two-clade phylogeographic structure typically arises when populations have a significant level of genetic divergence after been in isolation for long periods of time, and have subsequently mixed when barriers to gene flow disappeared , after which distinct mitochondrial lineages intermixed during secondary contact , a species with limited dispersal capabilities around New Zealand  do not show evidence of phylogeographic structuring  and the rarefaction curve show that our sample size was unable to capture most of the mitochondrial diversity present in the population (Table Gadus morhua (π = 0.002) , their 650,000-year-old lineages are influencing contemporary diversity estimates. Summary statistics such as nucleotide diversity, genetic diversity and Tajima’s D are estimated using the number of segregating sites. The number of segregating sites is relatively high in C. auratus because of the presence of the two highly diverged clades which do not necessarily reflect current day demographics. This may imply that diversity estimates do not correlate well with long-term effective population size  implies that the population is much smaller than that of C. auratus (π = 0.005) , which is consistent with the expansion observed in the Extended Bayesian Skyline Plot  in es Table . Here, sp = 0.723), suggesting there was no recent selective advantage for specific mitochondrial haplotypes. Second, nucleotide diversity has not significantly changed (p = 0.349), suggesting no detectable loss of genetic variation since the onset of fishing in New Zealand. This is despite lower temperatures during the Little Ice Age (which could have influenced population abundance) , Atlantic bluefin tuna (Thunnus thynnus), and Pacific herring , which showed that exploitation has not yet led to detectable losses of genetic diversity .Supplementary informationSupplementary table S4


Differences in vaccination coverage can perpetuate coronavirus disease 2019 (COVID-19) disparities. We explored the association between neighborhood-level social vulnerability and COVID-19 vaccination coverage in 16 large US cities from the beginning of the vaccination campaign in December 2020 through September 2021. We calculated the proportion of fully vaccinated adults in 866 zip code tabulation areas (ZCTAs) of 16 large US cities: Long Beach, Los Angeles, Oakland, San Diego, San Francisco, and San Jose, all in California; Chicago, Illinois; Indianapolis, Indiana; Minneapolis, Minnesota; New York, New York; Philadelphia, Pennsylvania; and Austin, Dallas, Fort Worth, Houston, and San Antonio, all in Texas. We computed absolute and relative total and Social Vulnerability Index–related inequities by city. COVID-19 vaccination coverage was 0.75 times  or 16 percentage points  lower in neighborhoods with the highest social vulnerability as compared with those with the lowest. These inequities were heterogeneous, with cities in the West generally displaying narrower inequities in both the absolute and relative scales. The Social Vulnerability Index domains of socioeconomic status andof household composition and disability showed the strongest associations with vaccination coverage. Inequities in COVID-19 vaccinations hamper efforts to achieve health equity, as they mirror and could lead to even wider inequities in other COVID-19 outcomes. CIconfidence intervalCOVID-19coronavirus disease 2019RIIrelative index of inequalitySARS-CoV-2severe acute respiratory syndrome coronavirus 2SESsocioeconomic statusSIIslope index of inequalitySVISocial Vulnerability IndexZCTAzip code tabulation areaThrough December 2021, the coronavirus disease 2019 (COVID-19) pandemic has taken the lives of over 800,000 people in the United States. The burden of COVID-19 has been disproportionate among minoritized populations and persons of lower socioeconomic position. We previously reported higher positivity ratios, incidence rates, and mortality rates in areas of high social vulnerability .In December 2020, the first 2 vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection were authorized by the Food and Drug Administration. A vaccination roll-out started nationwide, with different prioritization schedules by jurisdiction, but generally focusing first on older adults, health-care workers, and long-term care facility residents and staff . By ApriIn the context of higher incidence and mortality rates among low–socioeconomic status (SES) and minoritized populations, calls for prioritizing these populations emerged –11. EarlCharacterizing social and spatial inequities in cities is critical to developing appropriate interventions and policies to increase COVID-19 vaccination among underserved populations, helping control the pandemic, and reducing health disparities. This is especially important in large cities, where social inequalities are more prevalent  and whoshttps://doi.org/10.1093/aje/kwac076) details the specific data sources for each city, also available in the online dashboard (https://www.covid-inequities.info/).We obtained data from the Big Cities Health Coalition (BCHC) COVID-19 Health Inequities in Cities Dashboard , which cThe main outcome was the proportion of the total population that was fully vaccinated in each neighborhood. Full vaccination was defined by health departments as an individual having received 2 doses of mRNA-based vaccines  or Moderna  vaccines) or 1 dose of the Janssen  vaccine.The main neighborhood-level predictor examined was the 2018 Centers for Disease Control and Prevention’s Social Vulnerability Index (SVI)  at the nWe described basic neighborhood- and city-level characteristics and graphically examined the relationship between the SVI and vaccination coverage using scatterplots with smoothed, locally weighted scatterplot smoothing (lowess) lines and by computing vaccination coverage by quintile of the SVI. We then computed indicators of total relative and absolute inequities by estimating the ratio and difference between the top (defined as neighborhoods at the 90th percentile of vaccination) vs. bottom neighborhoods (10th percentile).To describe relative and absolute SVI-related inequities we estimated the relative index of inequality (RII) and the slope index of inequality (SII). These indices represent the ratio or difference in vaccination coverage between the top (most vulnerable) and bottom (least vulnerable) parts of the SVI distribution, while accounting for the distribution across the full range of social vulnerability. We estimated the indices using a linear model at the neighborhood level, stratified by city, with log(vaccination coverage) (for the RII) or vaccination coverage (for the SII) as the outcomes, and the SVI as the main exposure. The SVI coefficient (exponentiated in the case of the RII) and associated 95% confidence intervals (CIs) represent the RII or SII for the city. We adjusted these models by the % of the population of each neighborhood aged (in years) 18–44, 45–64, and 65 or older, but we also show results not adjusted for age. We also fitted these models using the 4 SVI domains instead of the summary SVI. To address potential differences in the distribution of the SVI across cities we refitted the same models using the SVI scaled to the whole sample instead to each city separately.To examine heterogeneity in the RII and SII, we used a multilevel linear model of neighborhoods nested in cities, with a random intercept for city, and introduced the SVI as both a fixed and random coefficient. To test whether there was variability in these inequities we compared models with and without the SVI random slope using the likelihood ratio test. To assess whether there were geographical differences in these inequities, and how much of the variability in inequities was explained by geography, we added a term for the interaction between the SVI and Census region .All analyses were conducted using R, version 4.1 . This analysis was approved by the Drexel University Institutional Review Board under proposal number 2102008373.https://www.covid-inequities.info/) contains maps for the SVI and vaccination coverage for the cities included in this study.We included a total of 866 neighborhoods (ZCTAs) in 16 cities, representing 32.2 million residents . The numWe found wide heterogeneity in the levels of vaccination between neighborhoods within cities . Top/botP values were 0.038 and 0.046, respectively, for the RII and SII; see Web Tables 2 and 3). The correlation between random intercepts and random SVI slopes in multilevel models was very low for the RII  and Philadelphia, Pennsylvania. RIIs in these cities varied from 0.93  in San Diego to 1.13  in Oakland. Outside of these 5 cities, we observed wider relative inequities, with RIIs ranging from 0.61  in Fort Worth, Texas, to 0.83  in San Jose, California. These patterns generally held for absolute inequities, as measured by the SII . Specifically, we observed narrower or inverted absolute inequities in the same 5 cities, varying from −4.3%  in San Diego to 6.6%  in Oakland.Results were relatively similar in models that did not adjust for age , with generally narrower inequities after age adjustment. Models using the city-specific rescaled SVI vs. the whole sample–rescaled SVI showed virtually unchanged results . We also tested whether there were regional differences in coverage, and found that, compared with the Southern United States, cities in the West had a 27% narrower RII  and an SII that was 12.7% percentage units closer to the null . Adding region and an interaction with the SVI explained 92% and 73% of the variability in inequities (Web Table 2).We documented wide spatial inequities in COVID-19 vaccination through September 2021 in 16 large US cities. We found negative and heterogeneous associations between social vulnerability and vaccination coverage for all cities. Overall, coverage in areas of the highest social vulnerability was 0.75 times lower than the coverage in areas of the lowest social vulnerability, or 16% percentage points lower. However, these disparities were regionally heterogeneous, as cities in the West region tended to have narrower inequities compared with cities in other regions. We also observed that the social vulnerability domains of SES and household composition and disability were more strongly associated with vaccination coverage, as compared with the domains of minority status and language and housing type and transportation.Findings from this study mirror other reports examining inequities in COVID-19 positivity, incidence, and/or mortality by neighborhood . This isWhile we cannot test what specific mechanisms are driving these inequities, we propose a few potential explanations that may have contributed to the large differences in vaccination coverage by social vulnerability across all cities. First, the eligibility schedule, which initially focused on health-care workers and older adults: Both health-care workers  and oldSecond, there are specific barriers to access for low-SES and minoritized populations. These include the location of vaccination sites , as spatThe second key finding of our study was the wide heterogeneity in spatial inequities across cities. Specifically, we found narrower disparities in cities in the Western region of the United States, all located in California . California has implemented an extensive COVID-19 equity plan , 37, incOver time, cities varied and expanded the location of vaccination sites, including implementing pop-up sites in easily accessible locations, expanding mobile vaccination clinics, targeted vaccinations by zip code, allowing walk-in and same-day appointments, in-home vaccinations for the homebound and their families and home health aides, and leveraging primary care clinics where people are already getting care , 41. NotA limitation of our study is that we rely on aggregated surveillance data, which may not be complete. While we used data on neighborhood of residence, the data for Philadelphia, Chicago, and New York City do not, to our knowledge, include residents who were vaccinated outside of their respective cities, while residents vaccinated outside their states of residence are not captured as vaccinated in the data we used. While we have no data on who was vaccinated outside their cities or states, considering the barriers outlined above, we speculate that individuals of high SES may be more likely to be vaccinated outside their cities, so this would bias our estimates of inequities towards the null. ZCTAs are very imperfect proxies for neighborhoods, but they represent a practical way to collect data during a public health emergency. Heterogeneity in the SVI (and its components) within zip codes may have led to underestimation of inequities. We also lacked longitudinal data for some of the cities included in our study, so we could not assess trends in these inequities; this type of data may be useful to evaluate some of the interventions outlined above. Last, given the cross-sectional, descriptive, and ecological nature of our study, caution should be used in drawing causal inferences or conclusions at the individual level. For example, our adjustment for age was crude and indirect, adjusting for the age distribution of each neighborhood, as we had no data on vaccination by neighborhood and age. We also lacked data on coverage by neighborhood and race/ethnicity, so we could not explicitly examine disparities by population subgroup.In summary, we found wide but heterogeneous spatial inequities in COVID-19 vaccination in 16 US cities, with areas of high social vulnerability having the lowest vaccination coverage. While we cannot infer a causal relationship between social vulnerability and vaccination coverage, the combination of these patterns with disproportionate impact of COVID-19 in these same neighborhoods , continuWeb_Material_kwac076Click here for additional data file.


This paper considers a host of definitions and labels attached to the concept of smart cities to identify four dimensions that ground a review of ethical concerns emerging from the current debate. These are: (1) network infrastructure, with the corresponding concerns of control, surveillance, and data privacy and ownership; (2) post-political governance, embodied in the tensions between public and private decision-making and cities as post-political entities; (3) social inclusion, expressed in the aspects of citizen participation and inclusion, and inequality and discrimination; and (4) sustainability, with a specific focus on the environment as an element to protect but also as a strategic element for the future. Given the persisting disagreements around the definition of a smart city, the article identifies in these four dimensions a more stable reference framework within which ethical concerns can be clustered and discussed. Identifying these dimensions makes possible a review of the ethical implications of smart cities that is transversal to their different types and resilient towards the unsettled debate over their definition. Most of the world’s population lives in cities. Cities are the sites where most consumption and production occur and where most of the negative environmental externalities originate  network infrastructure, (b) post-political governance, (c) social inclusion, and (d) sustainability as the four dimensions of the conceptual framework that best accommodates the review of a series of ethical concerns identified by a systematic search . While one can admit that techniques, such as data collection, often target now, as then, groups marked as “moral outsiders” , wherein information and communication technologies record, transmit and process data, with human societies crucially relying on ICTs and on information as an essential resource Floridi . In thisThe centralisation of data in smart cities gives considerable power to those who control it. There are different kinds of control in play here. One is the control of architecture, on what can be done physically within the boundaries of a space. This kind of control in cities is not new and falls under the category of urban planning typically discussed in traditional cities. The other kind of control is that of data and knowledge. This refers to a network rather than an urban infrastructure.As cities become “smarter” and increasingly connected with sensors and reliant on algorithms being fed large quantities of real-time data, the power centred in the administration of city services moves from the mayor’s office and city council chambers to the control rooms, from officials who are responsive to democratic will to those processing the data. Control rooms in cities are not new. However, as Kitchin notes , they arAlthough smart city technologies can increase the control of the government over people, they can also shift that control to private entities. Fisher  brings tThe degree of control afforded to officials in smart cities exceeds that of any previous era. Those in, or otherwise responsible for, control rooms can monitor and affect city activities and systems with extraordinary detail and pervasiveness. Such power can be used well, but also misused or even underused , and in each case there is a pertinent moral dimension to be considered and addressed, possibly leading to regulations.A major ethical implication of smart cities concerns the surveillance of their citizens. Surveillance as a consideration for urban planning is not new. In a related sense, for example, Georges-Eugene Haussmann, the architect of the great boulevards of Paris, acknowledged the military value of having broader and straighter streets to dispatch riots quickly, allegedly using this justification to attain more funding for his projects Andrews . The samYigitcanlar et al. , b reporIn cases like this, smart cities may run the risk of becoming a tool or even a catalyst for unwarranted surveillance as well as exacerbating existing inequities in policing systems in the name of increased security. Additionally, some smart cities may install surveillance tools specifically for policing, raising additional ethical questions. In the city of Chicago, “Shot Spotter” gun-shot-detection boxes placed at streetlights around the city are meant to use AI to detect the sound of gunshots to prevent crimes from going unreported and speed-up responses. Work has since shown that Shot Spotter is unlikely to have a significant impact on firearm-related homicides or arrests  enhancement framework can support potential mitigation strategies , the decision-making processes of black-box predictive algorithms are often un-interpretable to even the developers themselves. Guidelines and internal documentation can explain decisions made by humans, but the use of non-transparent technology in smart cities may complicate public oversight. When private companies develop these technologies for public use, transparency becomes even more problematic.Calo and Citron  write abThe lack of readiness of the government to harness innovation provides opportunities for private companies to take over and re-shape the rules of previously public services. Platforms like Airbnb and Uber offer good examples of the case in point. Their increased use impacts urban settings (e.g. changes traffic flows) and the balance of responsibilities between the public and the private sectors [e.g. see Uber Files for examples on Uber’s role in lobbying government and defying the law  citizens receive and who receives those benefits. In this context, we identify citizen participation and inclusion as well as inequality and discrimination as key points of relevance. Overall, which citizens get to participate in the shaping of a smart city, to what extent and on which issues are key issues in matters of social inclusion.The input and participation of urban residents are essential for the fair and effective deployment of smart city technologies. Therefore, some retain that cities can be defined as “smart” only when they successfully integrate the democratic participation of their multiple stakeholders, among which citizens, within a city’s management (Fernandez-Anez et al. Nevertheless, several authors are critical of these initiatives. Some argue that digital solutions like e-democracy platforms and fablabs are designed with tech-savvy people in mind, as they require good data literacy levels or programming skills Trencher . FurtherThe benefits of smart city technologies may not reach all city residents equally, and their deployment may exacerbate longstanding inequalities. Cities are sources of great prosperity and GDP output, but they also feature sharp divides between the rich and the poor and other social, digital divides, often with devastating effects. In Chicago, there is a 30-year gap in life expectancy between rich and poor neighbourhoods (City Health Dashboard Many people lack the digital literacy skills, the technologies, or sufficient internet connection to use smart city technologies. According to Pew Research Center, about 75 per cent of Americans in urban areas have broadband at home, which is 12 percentage points higher than those in rural areas Vogels . AnotherThe use of the technologies themselves, regardless of the population’s connectivity, may also entrench inequalities. Much has been written about the problems of fairness in the use of algorithms. City officials and other customers of smart city technologies like to point to the outcomes of algorithmic predictions and decisions as objective and unburdened by value judgments. However, these algorithms are trained with data from the “real world,” which invariably reflects ethical and political choices and historical trends that may be open to criticism. Algorithms that help decide who should get a bank loan, the economic impact of routing a new highway through poor neighbourhoods, or where police should send more patrols, are informed by, and reinforce economic and racial disparities (Yigitcanlar et al. The benefits of smart cities depend on what the cities envision as smart citizens, those who are in the position to exploit, or have access to, the means and the knowledge required to use the available resources in the best way (Gran et al. Sustainability should not be understood one-dimensionally, merely in relation to the environment. Bibri , b, for As an element to protect, smart cities can help mitigate the adverse effects that traditional cities had and keep on having on the environment. Some authors argue that urbanisation has had profoundly adverse effects on the environment due to excessive urban growth Dodman . These eSeveral initiatives show how smart cities can relate to the environment as a strategic element for the future. For example, Bibri and Krogstie  list smaBoth as solutions to traditional city problems and as new opportunities for the present, smart cities come with their own risks and challenges, which call for ethical scrutiny. As solutions to traditional city problems, smart city projects are often conceived as an increase in efficiency over previous approaches. This feeds into a conceptualisation of smart cities mostly in terms of technology and optimisation potential which, as stated in the beginning, might eclipse the complex character of urban life and its multidimensional challenges. When unquestioningly introduced, these technological solutions might incur the danger of exacerbating pre-existing problematic aspects of old solutions as well as generating new ones. As we have seen in the section on surveillance, technologies that entail predictive analytics, motion detection and autonomous or semi-autonomous devices such as drones are often introduced in the name of increased protection and improvement of a city’s traditional services and its social and economic status. However, they can pose a threat to the autonomy and privacy of citizens. Additionally, as shown by the example of San Diego, even when introduced for seemingly beneficial purposes—such as “smart streetlight” cameras to understand traffic patterns—these initiatives can serve controversial purposes, such as increased policing, which can, in turn, exacerbate existing inequities and introduce new forms of bias and discrimination. It is paramount that smart city projects, when presented as new solutions, are informed by the problems that made previous solutions problematic or redundant. Additionally, when conceiving smart cities as solutions to current social, environmental, and economic problems, it is crucial to assess their potential for direct and indirect social, environmental, and economic impact.Some of these impacts are intuitive, and easily discoverable. It is clear that policies of increased technological surveillance in policing, potential downtime of vital city services because of private company outages and shifts from public accountability to privately led projects deserve consistent ethical scrutiny and rectification. However, smart cities bring other, often inter-linked, potential ethical issues, which may be less visible. Increased surveillance from traffic sensors shifts the responsibility of safety and neighbourhood management from city officials to traffic control rooms. In the name of increased accessibility, the digitisation of government forms may do the opposite and translate inequities in digital access to inequities in government services. The optimisation of city services through technology may result in social service austerity, leaving behind groups whose needs are not easily quantifiable in models. Due to their ease of scale, even small changes in smart city technologies—from the location of sensors to the way buttons are placed on city websites—can significantly impact the lives of residents.As new opportunities for the present, the information revolution which powers smart cities has led to redesigning the environment surrounding us to make it more digitally friendly Floridi . These tThe four dimensions identified here provide the groundwork for an ethical analysis of a fast-changing field that can offer many solutions and opportunities, as well as for tracking the multiple aspects in which smart cities reinforce old, and introduce new, ethical challenges.


Substantial progress has been made in the understanding of anorexia nervosa (AN) and eating disorder (ED) genetics through the efforts of large-scale collaborative consortia, yielding the first genome-wide significant loci, AN-associated genes, and insights into metabo-psychiatric underpinnings of the disorders. However, the translatability, generalizability, and reach of these insights are hampered by an overly narrow focus in our research. In particular, stereotypes, myths, assumptions and misconceptions have resulted in incomplete or incorrect understandings of ED presentations and trajectories, and exclusion of certain patient groups from our studies. In this review, we aim to counteract these historical imbalances. Taking as our starting point the Academy for Eating Disorders (AED) Truth #5 “Eating disorders affect people of all genders, ages, races, ethnicities, body shapes and weights, sexual orientations, and socioeconomic statuses”, we discuss what we do and do not know about the genetic underpinnings of EDs among people in each of these groups, and suggest strategies to design more inclusive studies. In the second half of our review, we outline broad strategic goals whereby ED researchers can expand the diversity, insights, and clinical translatability of their studies. Over the past decade, substantial progress has been made in understanding the genetic etiology of anorexia nervosa (AN) and related eating disorders (EDs). Global collaborative efforts have yielded large-scale linkage, and later, genome-wide associations studies –4, reveaTo contextualize ED genetic research, we take as a starting point an aspirational document prepared and disseminated (available in 34 languages) by the Academy for Eating Disorders (AED), titled the Nine Truths About Eating Disorders . OngoingAED Truth #5 directly counters many of the stereotypes that have hindered ED science. Dissecting this truth illustrates the importance of broad representation to prevent biased or distorted understanding of the causes and impact of EDs. The failure to acknowledge the diversity of individuals affected by EDs has led to narrow definitions of disease and diagnostic criteria, and consequently incomplete assessments of disease characteristics, risk factors, and etiology. Accordingly, individuals who fall outside of these parameters  have been excluded from research and even from treatment. Stereotypes propagated by the media as well as the medical profession have contributed to under-detection and under-treatment of individuals with EDs who do not conform to these expectations. Under-detection, under-diagnosis, and under-referral for specialist treatment have been documented in men , 9, in pExpansion of genetic studies to include diverse presentations of EDs, and to capture the full spectrum of symptoms, behaviors, and outcomes that characterize EDs will yield increased power for discovery overall, but, more importantly, may also yield insights into specific genetic underpinnings of different facets of the disorders. Analytical approaches that can identify symptom-specific associations and account for potential biases can help reshape the understanding of EDs in the minds of researchers, clinicians, and the general public. In the Section “Background”, we outline what is known about EDs across the various groups referenced in AED Truth #5, and highlight existing genetic studies in these groups. In the Section “Large-scale approaches to address diversity in ED genetics”, we propose strategies for enhancing genetic research to advance the science of EDs.ED research, diagnoses, treatment guidelines, and public attention have overwhelmingly focused on women and girls. Although men might be included in studies, numbers are often too small to warrant analysis or to generate confident conclusions Fig. . AlthougAccording to a recent large meta-analysis, the gender ratio for AN is estimated to be 7:1 , for bulLGBTQIA+ individuals report increased prevalence of psychiatric disorders, including all EDs –18, due SNP-h2 showed that BF%female was significantly enriched for CNS tissue while BF%male was enriched for adipose tissue [Genetic studies have identified both shared and distinct genetic risk factors across sexes. For example, female relatives of men with AN have an elevated crude relative risk of AN (20.3) , implyine tissue .No explicit research exists on the genetic risk of EDs among LGBTQIA+ individuals, though we can reasonably assume that many of the same genetic influences on EDs are acting on these individuals as cisgender and heterosexual individuals, although environmental risk factors may differ. What is essential for ED genetic studies is that these individuals are included and unique risk factors that contribute to their experience of EDs are considered and assessed.It is overly simplistic to conclude that AN and anthropometric traits have different genetic risk factors between men and women. Such an interpretation ignores the historical bias in ED research. Because diagnostic guidelines were developed and tailored to the presentation of EDs in women and girls, assessment instruments likely have differential accuracy and sensitivity according to sex and gender . MoreoveThe limited available data from population-based studies report few racial or ethnic differences in the prevalence of EDs among adults, although results are inconsistent. Nationally representative studies in the US report no significant racial or ethnic differences in the prevalence of AN, BN, or BED , althougFurthermore, studies have reported differing prevalence of component symptoms of binge eating, purging, body dissatisfaction, and fear of weight gain across races and ethnicities. For example, Asian men and women with EDs tend to exhibit lower fear of fatness –45, a keDifferences in prevalence estimates may reflect that people of color are less likely to be diagnosed with an ED, to seek treatment, and to be referred for specialist treatment , 13, 14.It is widely known that complex trait genetics has focused overwhelmingly on individuals of European ancestry , 48, incEDs affect people of all ages , althougDisordered eating behaviors occur in young children, but can differ in clinical presentation. For example, “avoidant/restrictive food intake disorder (ARFID)”  occurs iEDs that occur in midlife and beyond can represent persistent cases, relapsing cases in individuals with initial onset in childhood or adolescence, or most uncommonly, new onset cases . The reqLittle is known about the genetic risk factors underlying ED onset at different ages. A recent GWAS examined genetic etiology of AN age-of-onset, and compared early onset (defined as <13 years of age) to typical-onset AN . DistincEDs affect individuals at all socioeconomic status (SES) levels. However, individuals with lower SES are less likely to receive screening or treatment for EDs and thus remain underrepresented among clinical samples , particuOther factors related to lower SES may be associated with increased risk for EDs. Some studies in U.S. samples have found evidence that food insecurity or insufficiency is associated with BED and BN , 89, whiIndicators of SES, including education, social deprivation, and household income, have heritable components , and stuDisproportionate attention to AN has obscured the fact that EDs occur in individuals of all body shapes and sizes. Although low BMI is required for a diagnosis of AN, BN can occur in individuals across the BMI spectrum, and BED occurs in individuals with typical and higher weight bodies. The DSM-5 now recognizes atypical AN (AAN) in which individuals meet all diagnostic criteria for AN including weight loss but do not present with low weight , 96. AANr = −0.36), fat mass (r = −0.33), BMI (r = −0.32), waist to hip ratio (r = −0.2), hip circumference (r = −0.2) and waist circumference (r = −0.24) [Genetic research has addressed body shape and weight in three ways. First, GWAS have highlighted shared genetic factors between AN and body shape and weight, including negative genetic correlations between AN and body fat percentage (= −0.24) , suggest= −0.24) . Further= −0.24) . Althoug= −0.24) . Third, = −0.24) .In addition, genetic research has the potential to shed light on the extent to which restrictive EDs in individuals with larger bodies  are genetically similar to AN. Comparing GWAS of AN and AAN could inform nosology and shed light on whether it is actually appropriate (from a genetic perspective) to label this presentation as a form of AN. Divergent results could inform whether AN and AAN share the same underlying genetics and only differ in BMI or represent genetically distinct syndromes.In the Section “Background”, we outlined ways in which stereotypes and misconceptions have biased our understanding of and research on EDs. Here, we suggest five overarching foci to improve the applicability of genetic research on EDs to the full spectrum of afflicted individuals Fig. .Fig. 2PrAs there is no guarantee that the same genetic and environmental factors influence risk for EDs across demographic groups, innovative practices are essential to ensure representation of individuals of diverse ancestry, gender and sexual orientation, age, SES, and body sizes. Strategies to recruit and retain diverse participants have been discussed in detail elsewhere , but sevThe ED research workforce is overwhelmingly white, which is also true for the ED genetics workforce. Building capacity to diversify the workforce has to start early in the educational trajectory. Recruiting interested individuals into science, technology, engineering and mathematics (STEM) as early as middle school (~ages 11–14) and engaging them in research related to eating, body composition, nutrition, psychology, psychiatry, and EDs will ensure a more diverse workforce in the future. Moving away from a purely sociocultural theory of ED etiology will engage more individuals interested in science (including genetics) and encourage more research on the biology of EDs.A recurring theme in Part 1 was the extent to which the narrow focus on young white thin females with AN in both research and in lay circles has shaped and biased the diagnostic schema, instruments, and research conclusions in the ED field. This restricted perspective has considerable downstream implications—from individuals outside of this stereotype who are neither detected nor referred for treatment, to who volunteers to participate in studies, to the conclusions that are drawn from samples that are mostly of European ancestry. The bias is compounding because any findings from these samples only serve to reinforce existing stereotypes about disease prevalence and presentation. Failure to include people of color and of size, other genders, and children and older people in our research studies severely limits our understanding. Moving the field forward will require a careful reconsideration of disease nosology and treatment guidelines. Guidelines should be restructured to consider differing presentations, behaviors, environmental risk factors, and psychological drivers, bearing in mind that many of the marginalized identities discussed in this review are intersectional, meaning that diagnostic criteria need to be flexible and applicable simultaneously to many different groups and presentations.Researchers should also attend to nomenclature used outside of the DSM and ICD that often emerges from traditional and social media to describe dysfunctional eating behavior. Popular terms like disordered eating, body dysmorphia, food addiction, orthorexia, and relative energy deficiency in sport  often capture trends in the population that describe what people are actually experiencing. The breadth in naming and lack of parallel to current treatment guidelines presents a variety of challenges. First, by using the above terms in the medical literature without defined criteria, we exacerbate challenges in clinical translation, as findings related to disordered eating might not easily be applied to a patient with AN or BN presenting to clinic. Second, we may unknowingly exclude historically marginalized groups who might find one of the above terms to be more representative of their lived experience. For example, if an individual identifies with a diagnosis of body dysmorphia, but researchers only recruit patients with atypical AN, we may miss including that participant and others like them. Lastly, the ED field suffers from chronic underfunding due in part to a dilution of recognition of the true prevalence of the disorders and resulting public health impact . By addrSuccess in this area will require a multi-pronged approach. First, the creation and deployment of more broadly useful screening tools and questionnaires should include opportunities to describe symptoms and behaviors falling outside stereotyped expectations for each condition; should not include BMI stratification or BMI-based inclusion/exclusion criteria; and should be appropriate cross-culturally.Researchers should also explore alternative or additional phenotyping approaches that rely on observed behaviors, specific symptoms, and digital phenotyping. Other examples include electronic-health record-based phenotype inference –110 or aResearchers should leverage insights from genetic studies to reshape disease nosology. Novel analytical approaches such as pathway-based PRS, transcriptomic imputations, and incorporating electronic and longitudinal health records afford researchers an unprecedented opportunity to study disease on an individual rather than population level. Such analyses might allow researchers to infer molecular subtypes of disease, identifying for example clinically-relevant subgroups associated with specific molecular signatures. Alternatively, these analyses might reveal that clinically distinct presentations are not rooted in genetic differences, rather stemming from societal or environmental exposures. Any assessment of environmental risk factors or correlates must account for the broad range of experiences that individuals with EDs from diverse backgrounds might have. Beyond the historical focus on the societal thin ideal, space must be made for assessing main effects of group-specific or shared factors  as well as gene x environment interplay. Understanding these disparate presentations, behaviors and symptoms will also represent a significant step towards personalizing treatment options, effectively identifying interventions and therapies that match specific symptoms and behaviors.Although there are substantial insights to be gained from larger, more inclusive GWAS of AN, it is imperative that we expand our analytical approaches, adopting cutting edge statistical techniques in order to more fully elucidate the genetic architecture of EDs. Elegant and intentional study design may increase our power to understand disease as much as increasing sample size.Substantial attention should be paid to approaches that can identify shared and distinct associations between ED diagnoses, or within disorders between subtypes. Explicit comparison of cases between psychiatric disorders has previously been shown to elucidate disorder-specific genic associations . As suchResearchers should also investigate the role of potentially clinically relevant endophenotypes. For example, comparing genetic risk factors across the lifespan may elucidate relationships with specific biological pathways and mechanisms. Studies of younger cohorts may reveal the role of metabolic and hunger/satiety dysregulation in AN, whilst examining ED onset in older cohorts may elucidate specifically the role of psychiatric pathways. Investigating these groups may also yield insights into the role of hormones associated with menarche and menopause to ED pathology through BMI and/or body dissatisfaction . A seconResearchers should also undertake approaches that can identify clinical consequences of genetic associations. For example, phenome-wide association studies (PheWAS) test for associations between genetic risk factors and the full patient phenome, including diagnostic records, reactions to medications, substance use/abuse, and longitudinal trajectories. These approaches might be particularly useful in disentangling whether specific comorbidities occur due to genetic pleiotropy , healthcare pleiotropy , or due to diagnostically meaningful overlap.Approaches that rely on genotype alone will ultimately be limited in the potential for translational and clinical insights. A full dissection of potential functional genomics approaches and integrative analyses is outside the scope of this review, and indeed has been explored in detail elsewhere –122. HowWe should be wary of over-interpreting differential heritability, correlations, or relative lack of genome-wide associations between two groups. For example, it might be tempting to interpret differential heritability between sexes as explaining sex differences in ED diagnoses. However, genetic associations are only as good as the phenotypes we provide; researchers should consider that phenotyping instruments might have differential power; diagnostic contamination might occur at different rates; disease severity might be substantially different between groups; and study participation rates may differ dramatically. If indeed researchers identify true sex-specific effects  that are not confounded by diagnostic differences, it is important not to default to assumptions of genetic essentialism . InsteadConsideration of the impact of societal factors is also essential. These may include exposure to stress and early life adversity; access to therapy and/or healthcare; access to healthy foods and opportunities for exercise; and support networks of family and friends. On the surface these factors are not genetic; however, it is likely that they correlate with genetic factors, as evidenced for example by recent GWAS of SES , 123 andFinally, we note that expanding inclusion within our studies is vital to equity in research and clinical care. The ability to participate in studies and research, and access to the findings and benefits of that research, should be equally available to all. Increasing diversity will inarguably increase our insight and understanding of ED biology, and indeed of psychiatric disease genetics more broadly; however, the goal of inclusion and equity alone is a sufficient motivator. Research conclusions that emerge from the study of a narrow and privileged subset of individuals with EDs and the treatment approaches they generate overestimate our actual understanding of disease and further perpetuate already damaging health disparities. This work is both hard and expensive, but must be a priority to replace myths with facts and to sharpen our understanding of EDs.


Cedrus atlantica is a large, long‐lived conifer native to the mountains of North Africa, threatened by extinction. The relevant genetic units for conservation were selected using Bayesian analysis. The relative contribution of the populations to the genetic pool that maximized the species' genetic diversity was calculated to design an optimal seed bank. Finally, the relationship between the genetic composition and bioclimatic variables was estimated and projected throughout the study area under current and future climatic conditions. Three relevant genetic units were found for C. atlantica conservation that maximizes genetic diversity in a spatial context. Bioclimatic variables with the highest influence on genetic composition were closely related to climate warming and decreased soil water availability. We identified the role of genetic markers in designing a reliable conservation strategy for forest trees considering climate change, increased deforestation, and aridity. Projections of genetic composition due to the climate in the study region of North Africa provide spatially explicit guidance for optimizing the selection and preservation of seed banks.Preserving the genetic diversity of forest species is critical for maintaining their adaptive potential and allowing for generation turnover in forest ecosystems. Considering an uncertain future, it is necessary to establish reliable genetic conservation strategies to optimize the genetic variation preserved within populations in a spatially explicit context to assist decision‐makers. Hence, we aimed to incorporate genetic information into spatially designed conservation actions.  Cedrus atlantica populations and the bioclimatic conditions of the areas where it inhabits. The proposal includes the most appropriate areas to consider in order to preserve the values of genetic diversity and rarity, three seed banks to be designed looking to maximize the genetic diversity of reinforcements and the climatic areas in which the different seed banks should be used.This paper aims to establish a reliable conservation proposal, both ex situ and in situ, regarding the genetic pattern of  However, the total area of occupancy (1300–1500 km2) is estimated to be a small fraction of its extent of occurrence .Previous studies have examined the genetic characteristics, diversity, and structure of b et al. . A populC. atlantica natural populations from climatic and anthropic pressures, it appears necessary to establish robust conservation measures for the species. This must be based on the genetic composition and structure of the remaining populations and on spatial models to investigate the potential relationship between genetic structure and climate, allowing the estimation of the most suitable areas for different genetic groups. These advances are necessary to set in situ and ex situ conservation measures: prioritizing the populations to conserve, guiding the creation of seed banks adequately representing the species' genetic diversity, and using these seed banks to ensure a correct match between genetic diversity and climatic suitability.Given the great threat to C. atlantica in a spatial context assisting decision‐makers, we aimed to: (a) select the genetic populations for an optimal in situ management plan, (b) calculate the genetic contribution of populations to generate a seed bank that optimizes diversity values for ex situ conservation, and (c) model genetic structure as a function of environmental conditions to guide in situ and ex situ actions (defined in the previous objectives), providing spatially explicit guidance for conservation and management plans.To establish a reliable conservation strategy for 2C. atlantica, selecting relevant genetic units for conservation (RGUCs) that maximized genetic diversity through its extant populations (in situ conservation). Based on this data, we designed a seed sampling strategy to optimize the selection and preservation of its genetic diversity (ex situ conservation). In addition, we studied the relationship between the genetic structure of the populations and climatic variables. Relating the complete genetic composition at the population level with multiple climatic variables simultaneously, we made genetic composition projections due to the climate in the study region.We analyzed current population genetic data for 2.1C. atlantica from Terrab et al. (The amplified fragment length polymorphism (AFLP) data set of b et al.  was usedb et al. . Genomicb et al. . The AFLb et al. . The finb et al. . Details2.2y, which quantifies the average genetic distance between pairs of individuals that fall into different distance classes  pattern was explored. Mantel's test Mantel,  was perf Miller, . A total Miller, . Subsequ Miller, , we deten) that should be preserved to represent a known proportion of genetic diversity (P), we solved the equation P = 1 − FSTn  for C. atlantica populations was set at 99% of the total genetic diversity.Relevant genetic units for conservation selection relies on population structure and the probability of rare allele loss N2  and the number of populations in which the rare band is present (N)  were calculated using the method described by Pérez‐Collazos et al.  captured by sampling only one population  for each rare band. We took into account the percentage of the population in which a rare band was present within the genetic clusters and the number of individuals within the clusters in which a rare band was present. The optimal proportion of the populations sampled in each cluster was calculated based on the PSA percentages and dex Nei,  as calcudex Nei, . Moreovedex Nei,  implemendex Nei,  to displ2.3Dmax). The expected contributions were calculated for BAPS genetic clusters using all populations as a whole. This was done by maximizing the function Dmax=1−∑ij=1nfijcicj, where fij is the average coancestry between populations i and j and ci is the contribution of subpopulation i to the pool  between populations to interpret the importance of the populations in the seed bank. To evaluate the efficiency of selection, the software calculated the genetic diversity of a randomly selected seed bank using the same parameters.To design an optimal seed bank, we calculated the relative contribution of the populations to the genetic pool that maximized the species' genetic diversity using the software Metapop2 v2.2.1 : Annual Mean Temperature (Bio1), Mean Diurnal Range (Bio2), Isothermality (Bio3), Temperature Seasonality (Bio4), Maximum Temperature of Warmest Month (Bio5), Minimum Temperature of Coldest Month (Bio6), Temperature Annual Range (Bio7), Annual Precipitation (Bio12), Precipitation of Wettest Month (Bio13), Precipitation of Driest Month (Bio14), and Precipitation Seasonality (Bio15). We used these variables since they describe different aspects of temperature and precipitation regimes, discarding quarterly variables . These quarterly variables were discarded because they correlated with monthly variables in the study area or because they combined temperature and precipitation regimes, hampered the interpretation of the results, and created meaningless patterns in regions with high seasonality in temperature and precipitation. We downloaded the data at a 2.5 arcmin resolution (~5 km2 at the equator), which were cropped to the study area defined by a bounding box from −9° W to 7° E and from 30° N to 38° N. To avoid multicollinearity problems, the initial 11 bioclimatic variables were analyzed using a variance inflation factor analysis, using 0.7 as the R2 threshold , we obtained 11 out of the 19 bioclimatic variables from the WorldClim dataset v2.1 , as implemented in the gradientForest package v0.1–32 for C. atlantica population were analyzed using hierarchical cluster analysis. To test whether climate can explain the observed genetic structure, we expected to observe three groups in the genetic importance variables. Next, to plot the results, we analyzed their values with principal component analysis (PCA), in which eigenvalues were used to rotate the genetic importance values for the remaining study area. The first three axes of the rotated variables were plotted as biplots and maps, illustrating their positions in the environmental and geographic spaces. This procedure was performed with current and future climate projections from 24 climate models in the worst‐case scenario (RCP8.5) available in the WorldClim database, whose results were then averaged  of each environmental gradient. Therefore, it performs biologically informed transformations of bioclimatic variables into genetic importance values  with a similar value (40.43%) estimated when considering the entire range of the species. Considering the PSA distribution and the R‐values of the different clusters, the optimal proportions of the populations to be sampled for each cluster were 0.38 (Cluster 1), 0.28 (Cluster 2), and 0.34 (Cluster 3). Given the FST calculated value of 0.247 and a target of 99.9% of the diversity, the optimal number of populations to be sampled was 4.94. Applying this method to the different genetic clusters, the optimal number of populations to be sampled for all three clusters was two: Cluster 1 (1.88), Cluster 2 (1.37), and Cluster 3 (1.67). Values were rounded up to avoid underestimating the conservation goals.From 203 AFLP bands, 60 met the rarity requirements  to 0.203 in population 6 (Cluster 2). The diversity values presented a general pattern of low genetic diversity. Populations 6 and 8 from the Middle Atlas and population 9 from the Tell Atlas had relatively higher levels of genetic diversity  McBride , all of which had low levels of genetic diversity, should be performed with the seed bank of the first genetic cluster. Populations 4–5, although they belong to genetic Cluster 1, are grouped with populations from genetic Cluster 2 (except for population 9) by the GF model. This could be because populations 4 and 5 have lost most of their original genetic diversity after reforestation programs or that these populations have survived in conditions for which they were not adapted , isothermality (Bio3), and mean annual temperature (Bio 1). Notably, these variables are consistent with several previous studies suggesting that climatic warming ; formal analysis ; investigation ; methodology ; software ; visualization ; writing – original draft . Diego Nieto Lugilde: Conceptualization ; formal analysis ; investigation ; methodology ; software ; visualization ; writing – original draft . Anass Terrab: Conceptualization ; supervision ; writing – review and editing . Francisco Balao: Conceptualization ; supervision ; writing – review and editing . Julio Peñas: Conceptualization ; formal analysis ; funding acquisition ; investigation ; project administration ; supervision ; writing – original draft .The authors declare that they have no conflict of interest.Appendix S1Click here for additional data file.


Frontiers in Genetics Research Topic  expanding the gene bank’s Research Topic of genetic diversity; 2) tracing the evolution of the genetic diversity from living populations; and 3) enhancing the genetic diversity and performance of existing populations. These three possibilities for the use of gene bank sires in the genomic era have been detailed in many studies demonstrating the immense significance of a gene bank as a library of genetic variation.One of conventional ways to preserve the domestic animal diversity is the use of semen cryo-conserved in gene banks that also opens plentiful opportunities for genomics studies as reviewed by For conservation and preservation measures, the identification and evaluation of important genetic resources is necessary. This requires a comprehensive characterization of populations at risk of loss. This includes recording the phenotypes and especially those traits for which superiority and potential usefulness of the populations is anticipated. Characterization also includes the determination of genetic variability and distance. Genetic markers are used for this purpose. Advances in genome sequencing, the availability of genotyping tools and techniques such as SNP microarrays and genotyping-by-sequencing make such analyses simple, fast and informative. Ongoing progress in genome annotation increasingly enables the assessment of the functional significance of polymorphisms. The use of holistic “omics” techniques, especially next-generation sequencing, also enables a comprehensive characterization of genetic resources along the genotype–phenotype map at the genome, epigenome, transcriptome, proteome and metabolome levels. Such analyses not only contribute to the comprehensive characterization of genetic resources, but also allow the use of selected populations with specific traits, e.g., adaptation to environmental and climatic stresses or pathogens, to facilitate the understanding of the expression of functional traits and adaptation mechanisms to abiotic and biotic stressors, as shown in several studies in this Research Topic. Old, local, site-adapted breeds can thus serve as valuable models. A number of good research publications as overviewed below by species have been provided within the present Research Topic that address conventional methodologies, in addition to genotypic and genomic data, and more recent developments in the study and conservation of domestic animal diversity.Kunene et al. used high-density single nucleotide polymorphism (SNP) genotypes to explore the genetics of base coat color variations and coat color patterns in South African Nguni cattle. The Nguni breed of cattle, which is similar to the Sanga, has mixed B. taurus and B. indicus lineage and has been shown to be resistant to ticks, illnesses, and other challenging environmental factors found in Africa. The leather business has developed a specialty market for the multicolored Nguni coats, which has prompted breeding goals for the propagation of such diversity. Limited research has been done on the genetic architecture that underlies coat color and pattern, which is a barrier to future breeding and development of that characteristic. Using Illumina Bovine HD (770K) genotypes and coat color phenotyped Nguni cattle, the authors examined genes underlying the base coat color, color-sidedness, and white forehead stripe in this cattle. Four indicative SNPs were identified on BTA18 as a result of the genome-wide association studies (GWAS) for base coat color (eumelanin vs. pheomelanin). A well-known gene, MC1R, was found to be located within 1 MB of the indicative SNPs, and it was discovered to be involved in both the mitogen-activated protein kinase (MAPK) signaling pathway and melanogenesis, the core pathway for the production of melanin. Four suggestive SNPs were discovered by GWAS for the color-sidedness gene, although none of them were located near the KIT candidate gene, which is linked to color-sidedness. Seventeen suggestive SNPs were found on BTA6 as a result of GWAS for the white forehead stripe. Four genes, including MAPK10, EFNA5, PPP2R3C, and PAK1, were discovered to be connected to the white forehead stripe and to the MAPK, adrenergic, and Wnt signaling pathways, which are mutually connected to melanin formation. These findings supported past theories about the function of MC1R in base coat colors in cattle and proposed a separate genetic mechanism for the phenotypes of Nguni cattle with forehead stripes.Jaafar et al. evaluated the effects of employing several ancestral reference populations on the population admixture and performance of crossbred cattle. Animals from several breeds are bred together during the process of crossbreeding. The offspring show a combination of genetic improvements from the parental breeds that boost heterozygosity and counteract inbreeding depression, both additive and non-additive. However, because the advantages of heterosis rely on the type of crossbreeding systems utilized and the heritability of the traits, crossbreeding may also disrupt the special and frequently advantageous gene combinations in parental breeds, thus lowering performance potential. Regarding three-breed crossbreeding systems, it is yet unclear how crossbreeding affects the genomic architecture in particular. In order to compare genomic ancestry estimates to pedigree-based estimates, this study connected breed composition with important production and health parameters among two rotational crossbred populations, ProCROSS and Grazecross. Rotational crossbreeding of the Viking Red , Holstein, and Montbeliarde led to the creation of ProCROSS. In contrast, Grazecross was made up of VKR, Normande, and Jersey. Both breeding initiatives attempted to maximize heterosis’ beneficial effects. All genomic estimations considered, choosing the most appropriate and useful animals to use as the reference animals in admixture analysis is important when interpreting relationship and population structure results, but there is some uncertainty when determining how breed composition relates to phenotypic performance.Liu et al. on a genome-wide scale in the longissimus dorsi skeletal muscle of Shandong Black and Luxi cattle. LncRNAs may play a regulatory role, which is becoming increasingly clear. The regulation of cell differentiation, fat synthesis, and embryonic development have been the main Research Topic of studies on cattle. However, there has not been much research on the potential function of lncRNAs in the skeletal muscle of domestic animals. Here, bioinformatics analysis was employed to build a network of lncRNAs, miRNAs, and mRNA interactions connected to muscle using the transcriptome numbers of distinct beef cattle, Shandong Black and Luxi. This can be utilized to advance animal husbandry, increase animal husbandry output, and elucidate the molecular basis of the growth of bovine muscle. A total of 1,415 transcripts (of which 480 were lncRNAs) were differently expressed in the two breeds. Furthermore, 1,164 protein-coding genes  were the targets of the most differentially expressed lncRNAs, which were located on chromosome 9. A probable trans-regulatory link between the differentially expressed lncRNAs and 43,844 mRNAs was also shown. The detected co-expressed mRNAs  are enriched in calcium and AMPK signaling, muscle cell and striated muscle tissue development, and strained muscle cell differentiation. A network of lncRNAs, miRNAs, and mRNA interactions was built as the putative foundation for biological control in the skeletal muscle of cattle based on this. The reported findings will theoretically support future research on lncRNA regulation and activity in various cattle breeds.Long non-coding RNAs (lncRNAs) were identified and described by Bao et al. used resequencing to examine the signals of selective scanning leading to potential genetic variations for hair length features in Tianzhu white yaks with long and normal hair. The Tianzhu white yak is a unique native yak breed in China that has an all-white coat. Breeders have recently identified long-haired individuals of the Tianzhu white yak, which are distinguished by long hair on the forehead. The length and density of the hair on these two sections of the body are also higher than that of the typical Tianzhu white yak. The authors re-sequenced the whole genomes of long-haired and normal Tianzhu White yaks to clarify the genetic basis of hair length in Tianzhu white yaks. Two hotspots were discovered on chromosome 6 that contain two (FGF5 and CFAP299) and four  genes, respectively. Ras, MAPK, PI3K-Akt and Rap1 signaling pathways were found to be involved in the process of hair length variation by function enrichment analysis of genes in two hotspots. In addition, four more genes  were discovered as connected to the growth of hair follicles.Yuan et al. investigated the genetic diversity and population dynamics of Tongcheng (TC) pigs. Indigenous to China, TC pigs are known for their high meat quality. Due to the introduction of global pig breeds and the African swine fever pathogen, the genetic resources of TC pigs are now seriously threatened. The current study used multiple SNP markers to analyze the genetic diversity and population structure of TC pigs in order to support their management and conservation. With an average linkage disequilibrium (LD) value of .15, LD and neutrality testing both showed a low selection of TC pigs. Estimates of minor allele frequency, observed heterozygosity (Ho), expected heterozygosity, and nucleotide diversity values pointed to the TC pigs’ astonishingly great genetic diversity. Additionally, runs of homozygosity (ROHs) segments were examined in the whole genome of TC pigs. Based on ROHs, the average genomic inbreeding coefficient FROH was .04%. On nine separate autosomes, 14 ROH islands with 240 genes were discovered. Some of them, including FFAR2, FFAR4, MAPK8, NPY5R, and KISS1, overlapped with genes involved in immunological response, reproduction, muscle development, and fat deposition. These genes may be linked to qualities like meat quality and disease resistance in TC pigs. Genetic diversity and population structure data together revealed that the TC pig was a valuable genetic resource. To provide sufficient genetic diversity and prevent inbreeding depression, the TC pig breed conservation program needs to be further developed, and this research gives management and conservation methods for TC pigs a theoretical foundation.Using a whole-genome SNP chip, Addo and Jung. Mangalitsa pigs have three different color patterns on their coats, according to which they can be classified as Red, Blond, or Swallow-bellied. The current work used studies of population structure, ROHs, and fixation index to examine genome-wide diversity and selection fingerprints in the three breeds genotyped using a modified ProcineSNP60 v2 Genotyping Bead Chip. Also provided as comparison outgroup data were 20 genotypes of the Hungarian Mangalitsa. For the Blond, Swallow-bellied, and Red Mangalitsa, respectively, estimates of observed heterozygosity were .27, .28, and .29, and estimates of inbreeding coefficients based on ROHs were 24.11%, 20.82%, and 16.34%. All breeds had ROH islands, but none of them were shared by any of the breeds. In a ROH island in the Swallow-bellied Mangalitsa, the KIF16B gene—previously known to be involved in synaptic signaling—was discovered. The same gene was discovered to contain a significantly different SNP (MARC0032380) when comparing Swallow-belied Mangalitsa to either Red or Blond. Some ROH islands in the Red Mangalitsa were connected to genes like ABCA12, VIL1, PLSCR5, and USP37 that affect meat quality attributes. This research revealed that the variation and population structure of the three breeds were distinct, with the Red and Blond Mangalitsa pigs being the most closely related.Insights on the ROH distribution and breed differentiation in Mangalitsa pigs were provided by Feng et al. discovered a putative miRNA-mRNA regulation network and the important miRNAs in intramuscular and subcutaneous adipose. Intramuscular fat (IMF) is a key metric for assessing the quality of meat. Breeds with high IMF content frequently also have high subcutaneous fat, which negatively impacts pigs’ ability to produce meat. Important ramifications for pig breeding result from research into the processes of miRNAs involved in lipogenesis and lipid metabolism. Here, the patterns of lipogenesis in the Chinese breed of pig known as Laiwu were analyzed by creating two small RNA libraries from intramuscular and subcutaneous fat. Two types of adipose tissue were used to identify a total of 286 differentially expressed miRNAs (DEmiRNAs), comprising 193 known miRNA and 93 novel miRNA. Gene ontology (GO) and KEGG enrichment analysis for DEmiRNAs revealed that their target genes were involved in numerous biological processes and signaling pathways related to adipogenesis and lipid metabolism, including the Wnt, MAPK, Hippo and PI3K-Akt signaling pathways, melanogenesis, and signaling pathways controlling stem cell pluripotency, among others. After that, a network of interactions between miRNA and mRNA was built to determine which miRNAs were crucial for regulating the Wnt signaling pathway. MiR-331-3p, miR-339-5p, miR-874, and novel346 mature target PPARD, WNT10B, RSPO3, and WNT2B in this pathway. This research offers a theoretical foundation for future research into the post-transcriptional control mechanism of meat quality generation as well as disease diagnosis and management related to ectopic fat.In a Chinese pig breed, Yang et al. with respect to the lncRNA-associated ceRNA regulation network. Understanding the regulatory mechanisms governing responses to hypoxia may help in alleviating harm brought on by hypoxia. ATII cells’ ability to function is significantly hindered by oxygen deprivation. In this study, ATII cells were cultivated from Tibetan and Landrace pigs in hypoxic and normoxic conditions to search for differentially expressed (DE) lncRNAs and DEmiRNAs as well as build their related ceRNA regulation networks in response to hypoxia. Target genes of Tibetan and Landrace pig DElncRNAs were significantly enriched in the proteoglycans in cancer, renal cell carcinoma, and erbB signaling pathways between the normoxic and hypoxic groups, whereas DEmiRNAs’ target genes were significantly enriched in the axon guidance, focal adhesion, and MAPK signaling pathways. Through the activation of the focal adhesion/PI3K-Akt/glycolysis pathway, hypoxia induction has been demonstrated to potentially encourage apoptosis. By controlling ATII cell autophagy in normoxic and hypoxic conditions, the ssc-miR-20b/MSTRG.57127.1/ssc-miR-7-5p axis may have significantly reduced hypoxia injury. The most impacted axis, MSTRG.14861.4-miR-11971-z-CCDC12, controlled a number of RNAs and may thus control the proliferation of ATII cells in Tibetan pigs under hypoxic settings. In Landrace pigs, the ACTA1/ssc-miR-30c-3p/MSTRG.23871.1 axis plays a critical role in reducing ATII cell damage and enhancing dysfunction and fibrosis brought on by oxidative stress. These findings give a better knowledge of how Tibetan pigs regulate their lncRNA, miRNA, and mRNA in hypoxic environments.An integrative analysis of the alveolar type II epithelial (ATII) cells of Tibetan pigs and their response to hypoxia was conducted by Li et al. discovered SSTR5 gene polymorphisms and their correlation with growth traits. This investigation sought to identify SSTR5 polymorphisms and assess their relationship to growth parameters in Hulun Buir sheep. Seven SNPs were found as a result of Sanger sequencing, showed moderate polymorphism (.25 < PIC <.5), and were then subject to association analysis in relation to the growth traits. At 9 months of age, cannon circumference was substantially related with SNP4 (rs605867745) and SNP3 (rs413380618). There was linkage disequilibrium among the five haplotypes and seven SNPs. These haplotypes were not connected to distinct ages of growth features, nevertheless. SNP1, SNP3, SNP4, and SNP7 may all function as molecular markers for the growth features of Hulun Buir sheep, to sum up.In Hulun Buir sheep, Dzomba et al. Merino sheep are a preferred breed that are widely raised for their wool and mutton worth. Using the Illumina Ovine50K BeadChip, this study assessed genetic diversity, population structure, and breed divergence in the South African Merino (SAM), eight Merino-based sheep breeds, as well as non-Merino founding breeds . The Meatmaster, SAM and Dohne Merino (DM) showed the highest genetic diversity levels, with Ho values of .37–.39. The degree of inbreeding varied from zero (DM) to .27 points (Nguni). High within population variance (80 + per cent) was observed across all population categories. Selection sweeps for the Afrino (12 sweeps), Meatmaster (four sweeps), and DM (29 sweeps) were identified. Such genes as FGF12, the metabolic genes ICA1, NXPH1, and GPR171, as well as the immune response genes IL22, IL26, IFNAR1, and IL10RB, have all been linked to hair and wool features. The DM vs. Merino, Meatmaster vs. Merino and Meatmaster vs. Nguni shared a selection sweep on chromosome 10 harboring the RXFP2 gene for the polledness. Additionally, the DM vs. Merino and the Meatmaster vs. Merino shared a Rsb-based selection sweep on chromosome 1 connected to the CAPN7 gene for calpain. Collectively, the analysis showed some genetic divergence caused by breed-specific selection objectives and some genetic similarity between the Merino and Merino-derived breeds originating from shared founder populations.A genome-wide divergence and selection signature investigation of South African Merino-derived breeds from their ancestors was carried out by Drzaic et al. Using 50K SNP profiles, this comprehensive genomic research has revealed that the regional Balkan sheep populations share a great deal of genetic variation with neighboring breeds, but they are also very distinct from them. Using the Ovine Infinium® HD SNP BeadChip, eight Croatian sheep breeds and mouflon were genotyped. Also, various Mediterranean sheep breeds and Balkan Pramenka, which are readily accessible, were added to the analysis. This research uncovered the intricate demographic structure of Croatian sheep breeds, as well as information on their geographic origins (island vs. mainland). The historical establishment of breeds and the routes of gene flow were confirmed by migration patterns. Between sheep populations, FROH>2 Mb coefficients ranged from .025 to .070, with Dalmatian Pramenka and Pag Island Sheep having lower inbreeding coefficients and Dubrovnik sheep having higher inbreeding. For the Krk Island Sheep and Dalmatian Pramenka, the estimated effective population size (Ne) varied from 61 to 1039, respectively. In order to retain genetic variation in particular breeds, there is a need for greater conservation management due to higher inbreeding rates and a smaller Ne. These findings will aid in breeding and developing conservation plans for Croatia’s indigenous sheep breeds.High-density genomic characterization of native Croatian sheep breeds was performed by Liu et al. revealed that the lipid metabolism pathway is a key characteristic of adipose tissue from various sheep. Important non-coding RNAs known as miRNAs can take part in the control of biological processes. MiRNAs have been extensively explored in recent years, not just in humans and mice but also in animal husbandry. However, the investigation of miRNA in subcutaneous adipose tissue of sheep is not thorough compared to other livestock and poultry breeds. Using RNA-Seq technology, the transcriptomes of miRNAs in the subcutaneous adipose tissue of Duolang sheep and Small Tail Han sheep were analyzed to identify those that were expressed differently in these two breeds. As a result, 38 miRNAs were discovered that were differently expressed (nine novel miRNAs and 29 known miRNAs). Additionally, 854 target genes were predicted in total. The deposition of subcutaneous adipose tissue in Duolang and Small Tail Han sheep has been linked to the regulation of lipolysis in adipocytes. The genes involved in controlling lipolysis in adipocytes may be controlled by the miRNAs, which in turn may control fat accumulation. In particular, NC_ 040278.1 37602, oar-mir-493-3p, NC_ 040278.1 37521, and NC_ 040255.1 11627 may each target PTGS2, AKT2, AKT3, and PIK3CA, thus playing a crucial regulatory role. Overall, the findings establish the groundwork for further elucidating the mechanism underlying the deposition of subcutaneous adipose tissue in sheep, enhancing the performance of their ability to produce meat, and advancing the field of animal husbandry.A genome-wide investigation of miRNAs by Chokoe et al. clarified the conservation status and historical relatedness of communal indigenous goat populations in South Africa. Due to their tolerance to various production situations and support for communal farming, indigenous goats, which make up the bulk of populations in smallholder, low input, low output production systems, are regarded as an important genetic resource. In order to assist breeding strategies to utilize and conserve genetic resources, Ne, inbreeding rates, and ROHs are useful tools for examining genetic diversity and comprehending the demographic history. The historical Ne across populations indicates that the ancestor Ne has decreased in Free State (FS), North West (NW), Limpopo (LP), and Gauteng (GP), respectively, over the last 971 generations. The current Ne of GP was the lowest across populations. The Eastern Cape (EC) had the lowest levels of FROH>5 Mb, and FS had the greatest levels. The FS, GP and NW populations had 871 ROH island areas that contain crucial environmental adaptation and thermo-tolerance genes such IL10RB, IL23A, FGF9, IGF1, EGR1, and MAPK3. Despite having a similar ancestor, the genomes of KZN and LP exhibit significant mixing from the EC and NW populations. Using genome-wide SNP markers, the results showed that the presence of high Ne and autozygosity differed significantly across communal indigenous goat populations at recent and ancient events. The migration of communal indigenous goat populations from the northern section (LP) of South Africa to the eastern regions (KZN) showed their historical kinship and coincided with the Bantu nation’s migratory phases.Using the genome-wide Illumina goat SNP50K BeadChip, Zhang et al. demonstrated. An essential metric for assessing cashmere quality is cashmere fineness. Although the Liaoning Cashmere Goat (LCG) breed studied produces a lot of cashmere and has long cashmere fiber, its fineness may be better. Thus, it is crucial to identify genes related to cashmere fineness that might be applied in next attempts to enhance this phenotype. Through high-throughput sequencing and genome-wide association analysis, the regulation of cashmere fineness has achieved unprecedented strides due to the ongoing improvement of technology. Translatomics has been demonstrated to be able to pinpoint genes linked to phenotypic features. The authors performed translatomic analysis after having sequenced the skin tissue of LCG sample groups with various cashmere fineness ranges by Ribo-seq. Differently expressed genes were found between the sample groups using these data. From these, 186 genes were downregulated and 343 genes were upregulated in the fine LCG group as compared to the coarse LCG group. The biological functions of differential genes were explored by GO enrichment analysis, with functional genes related to the extracellular area being predominant. The enrichment of the human papillomavirus infection pathway was particularly prominent in the KEGG enrichment study. The authors suggested that the COL6A5 gene might impact the fineness of cashmere.Translatomics can be used to select functional genes for cashmere fineness, as Iqbal et al. investigated how multi-omics can disclose different strategies in the immune and metabolic systems. Due to their high egg production and outstanding commercial applicability, Lohmann Brown (LB) and Lohmann Selected Leghorn (LSL) are two major laying hen strains for the poultry industry. To further understand how the genetic makeup of the two strains effects their biological pathways, the genotype-phenotype map of the current study incorporated multiple data sets. The harvested data sets in the two strains were intestinal miRNA and mRNA transcriptome data, immune cells, inositol phosphate metabolites, minerals, and hormones from various organs. These were analyzed using the R package mixOmics. Among the most distinctive characteristics between the two strains, there were 20 miRNAs, 20 mRNAs, 16 immune cells, 10 microorganisms, 11 behavioral properties, and 16 metabolites. The enrichment of immune pathways in the LSL strain was correlated with the expression of particular miRNAs and the quantity of different immune cell types. On the other hand, more microbial taxa that were unique to the LB strain were discovered, and the prevalence of several bacteria showed a high correlation with transcripts enriched in immunological and metabolic pathways in the host gut. According to this research, both strains use unique innate mechanisms to develop and keep their immune and metabolic systems functioning well. The study also adds to our understanding of the role of host–gut interactions, including immune phenotype, microbiota, gut transcriptome, and metabolome, by offering a fresh perspective on the functional biodiversity that emerges during strain selection.In highly productive lines of laying hens, Ediriweera et al. The chicken MHC-B region plays a vital role in the development of the immune systems and is extremely variable across breeds, lines, and populations. It is crucial to examine this chromosomal region, particularly the class I and II genes, to ascertain the variation and diversity that eventually alter antigen presentation because it determines the resistance/susceptibility to a variety of infectious illnesses. Using NGS data, Geneious Prime-based assembly and variant calling with the Genome Analysis Toolkit (GATK) best practices pipeline, this study examined five KNC lines and the Ogye breed. For each line or breed of chicken, the consensus MHC-B (BG1–BF2) sequences were collected, and their variations were examined. Each of the KNC lines had an excessive number of mutations, including a sizable number of high-impact variants that revealed important details about altered MHC molecules. The study verified that MHC variations can be successfully detected using NGS techniques, and the KNC lines had a very diverse MHC-B region, indicating a significant divergence from the red junglefowl, the progenitor of domestic fowls.The utility of next-generation sequencing (NGS) for the high-resolution typing of major histocompatibility complex-B (MHC-B) in Korean native chickens (KNC) was proven by Eimeria species, as demonstrated by Kim et al. The coccidiosis disease brought on by the Eimeria species is quite harmful for the poultry production. RNA sequencing was employed to track the temporally-dependent host responses of chickens infected with Eimeria in order to investigate the genes and biological processes linked to parasite immunity. Four, seven, and 21 days post infection (dpi) were the times at which transcriptome analysis was carried out. Three categories of genes with differential expression were identified based on alterations in gene expression patterns. As a result, endoplasmic reticulum stress was document during the early stages of Eimeria infection. Furthermore, innate immune responses to the parasite were engaged at the time of the initial exposure and gradually returned to normal. Despite being considerably active at 4 dpi, the cytokine-cytokine receptor interaction pathway was downregulated, which had an anti-inflammatory effect. After Eimeria infection, the creation of gene co-expression networks also made it possible to identify key pattern recognition receptors and immunoregulation hub genes. These findings give a thorough insight of how chickens and Eimeria interact as hosts and pathogens. The gene clusters identified in this work can be used to enhance the coccidiosis resistance of chickens.Time-series transcriptome analysis revealed differently expressed genes in broiler chicken infected with mixed In conclusion, the evaluation of breeds by comprehensive phenotyping and the effective study of breed genetic diversity using appropriate polymorphic markers or genome-wide SNP genotyping are both possible today thanks to the combination of traditional techniques and approaches with cutting-edge genetic and genomic methods. In this way, the genotype/genomic content is important and gains from the comparison or combination of conventional and genomic metrics. The papers in this Research Topic serve as excellent illustrations for how to create and contrast “portraits” of breeds at the level of complete genomic sequences and transcriptomes, as well as how to identify potential candidate genes for key features in particular breeds. The history of domestication and the development of breeds can be clarified using genomic data, and genomic regions with signs of artificial selection can be found. The formulation of breed conservation measures, their sustainable use, and marker-assisted breeding are all made possible with the help of comprehensive breed assessment using genetic, genomic and multi-omic approaches.


Genetic diversity provides the long-term capacity of species, communities, and the biosphere to persist under change. It is a fundamental element of biodiversity that is globally declining, mainly in habitats that are more affected by humans . The monSus scrofa) and two deer species  are the most widely distributed ungulates [C. pygargus) is distributed throughout this continent [Populations of large herbivores, such as ungulates, are generally declining, mostly in developing countries . In addingulates . The wilngulates . This spngulates , where ingulates . Roe deeontinent . The ranontinent . Wild boontinent . The stuThe present Special Issue discusses the genetic diversity of wild boar and deer. Three questions were proposed to approach this topic: What is the pattern of genetic diversity of wild boar and deer species? What are the factors affecting their genetic diversity? What are the consequences of genetic diversity of wild boar and deer species? Five papers have been published in the Special Issue addressing some aspects related to these questions. The papers focused on wild boar and the deer species with wider presence in Eurasia (roe deer and red deer). Two research articles addressed the genetic diversity patterns of wild boar/wild pigs in China  and NortHu et al.  analyzedDelgado-Acevedo et al.  addresseBarros et al.  used thePérez-González et al.  performeThe four papers described above offer divergent contexts for wild boar and the two deer species. The lack of genetic structure in Chinese wild boar , supportMC1R and NR6A1 polymorphisms.Genetic markers and genetic structure analyses at nuclear markers were similar in the three research articles in the Special Issue ,17,18. GThe importance of monitoring the genetic diversity of wild boar and deer for conservation and public health purposes deserves additional consideration. Recently, Teixeira and Huber  reopenedTraditional genetic tools, such as microsatellite markers and mitochondrial sequences, have been broadly used to estimate the genetic diversity of wild boar. The development of genome-wide approaches, such as those using thousands of single nucleotide polymorphisms (SNPs), opens new possibilities in conservation genetics. Large SNP datasets have been shown to offer similar results to those obtained with traditional tools, but these new technologies present higher precision and repeatability ,32. Ther