While there are a growing number of human pluripotent stem cell repositories, genetic diversity remains limited in most collections and studies. Here, we discuss the importance of incorporating diverse ancestries in these models to improve equity and accelerate biological discovery. Despite these advances, a well-documented issue in existing genomic data is the inadequate representation of samples with non-European ancestries2. For instance, in genome wide association studies (GWAS), commonly used to discover connections between disease risk and genomic variants, most participants are of European ancestry (95.76%)3. Participants of Asian ancestry collectively represent 2.9%, while participants of African ancestry and participants of Hispanic/Latin American ancestries make up less than 1%  registry, 93% are derived from donors of European ancestry8. Similarly, samples from donors of reported European ancestry on average contribute to more than 67% of iPSC lines across multiple larger repositories compared to cell lines derived from donors of reported African ancestry, Asian ancestry, or Hispanic or Latino ethnicities , including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), can be used to generate such systems as they can be obtained from individuals of diverse genetic backgrounds, differentiated into disease-relevant cell types, and engineered to harbor one or more genetic variants of interest. Recognizing the utility of such cellular models, several large-scale stem cell repositories have emerged worldwide to ensure standardized collection, reprogramming methods, storage, and distribution of thousands of hPSC lines Fig. . While hies Fig. . By compion Fig. . While t9. These advances, however, also underscore the importance of expanding the genetic diversity of stem cell models to ensure equitable, timely, and broadly applicable scientific insights and medical benefits. Genetically diverse cellular models can be important drivers of scientific and therapeutic discovery for several reasons. First, including cell lines from diverse genetic backgrounds in functional studies can facilitate the identification of genetic variants underlying specific traits and disorders. Populations of African ancestry for instance have more genetic variation compared with the rest of the world. African genomes have shorter haploblocks and exhibit less linkage disequilibrium (LD) which allows causal alleles for a particular trait or disorder to be mapped at higher spatial resolution11. Indeed, despite a relatively small sample size, the H3Africa study5 discussed above successfully identified several novel disease-associated variants, a higher number than what is typically discovered in similar studies based on participants of European ancestry. Second, certain disease-associated risk variants may be more or less prevalent in individuals from specific ancestries. For example, a genetic variant that doubles the risk of respiratory failure from COVID-19 occurs in 60% of individuals of South Asian ancestry compared to 15% of individuals of European ancestry12. Studying the functional impacts of such variants would therefore benefit from greater access to cell lines generated from donors of South Asian ancestry. As efforts to increase the diversity in genomic studies come to fruition, such examples will only increase. Third, the growing number of iPSC-based clinical trials13 highlights their potential in cell replacement therapy. Since autologous transplantation is neither time nor cost effective, efforts have focused instead on the matching of HLA haplotypes to reduce immune rejection. In this approach, iPSC lines are derived from donors homozygous for a few HLA haplotypes common in a given population. For example, a selection of 10 iPSC lines with the most common HLA types in the United Kingdom (UK) would provide a beneficial match for two-thirds of the UK population14. As the most common HLA types vary across ancestries, it is critical to ensure that similar efforts include HLA haplotypes representative of additional global populations through either cell collection efforts or gene editing15, such as the efforts of the CiRA Foundation in Japan discussed above. Finally, non-genetic modifiers, such as co-infection, microbiomes, diet, and socio-cultural factors may also contribute to phenotypic differences across populations. Some of these effects can be tested in hPSC-based models to disentangle genetic versus non-genetic contributors.In recent years, the use of hPSC-based models has rapidly expanded beyond basic research and has begun to revolutionize the pharmaceutical industry, with applications in drug discovery and toxicity7. Another study of 110 iPSC lines identified rare deleterious non-synonymous single nucleotide variants (nsSNVs) that were associated with outlier cellular phenotypes, which deviated significantly from modal phenotypic values16. Of note, the iPSC lines utilized in both studies were predominantly from donors of European ancestry. Increasing the number of cell lines from donors of additional ancestries are thus needed to enable similarly scaled analyses across populations. In that regard, one study using 72 dermal fibroblast-iPSC pairs from donors of African American ancestry and donors of European ancestry identified ancestry-dependent transcriptional profiles that were associated with reprogramming efficiency17. Additionally, a study of iPSC-derived hepatocytes from 28 individuals revealed that donor genetic background was sufficient to drive differences in hepatocyte differentiation propensity across cell lines18, highlighting the potential for inter-individual genetic variation to impact cell type-relevant preclinical toxicity measurements. Together, these reports suggest that some genetic differences across individuals from diverse ancestries have the potential to manifest as measurable differences in cellular phenotypes in iPSC-based in vitro models.While the extent to which different ancestral backgrounds might impact phenotypes in iPSC-based in vitro models is not well understood, studies suggest that inter-individual genetic changes, including common genetic variation, can result in quantifiable differences in cellular phenotypes. One study of iPSC lines derived from 301 donors found that genetic differences between individual donors affected most cellular traits in iPSCs, including differentiation capacity and cellular morphology19. For example, as discussed above, treatment response to Warfarin shows greater variation in individuals of North Asian ancestry as compared to individuals of European ancestry6. This presents a challenge for scientific and pharmaceutical industries, as experimental validation and patient recruitment for clinical trials are predominantly performed in the United States and Europe13. While establishing clinical trials across the globe would be costly and time-consuming, iPSCs can be readily generated using samples from ancestrally and geographically diverse donors, which could pave the way for the investigation of pharmacogenetic effects on iPSC-derived cell types to optimize drug treatments. Given the importance of HLA haplotypes discussed above, one study screened HLA haplotypes from 1000 participants in Taiwan, identifying 13 homozygous HLA haplotypes, and subsequently generating iPSC lines from all of them. Cardiomyocytes and neurons derived from the 13 lines were then used in toxicity screens, illustrating the utility of a population-based hPSC approach to assess cytotoxicity20. Second, introducing protective or pathogenic variants by gene editing on multiple genetic backgrounds is also critical. Given the potential for modifier alleles to influence phenotypes, evaluating the effects of variants across multiple human genetic backgrounds, rather than a single isogenic background, may generate novel insights. Third, studying the effect of natural genetic variation on cellular phenotypes such as expression quantitative trait loci is important. The availability of large-scale hPSC repositories . Self-reported race or ethnicity reflects identity categories that can change over time, while genetically inferred ancestry  reflects aspects of underlying biology which remain static for a given individual. Both types of data provide relevant information, but reliance upon self-reported race or ethnicity alone presents several specific limitations. The 2020 United States Census provides a timely example of how shifting social, political and cultural factors can influence self-reporting29. Here, the allelic variant does not segregate within the population terms used in any hPSC banks. While different studies will require varying levels of granularity in the populations under investigation, current estimates put the number of subcontinental ancestries at a minimum of 21, with 97.3% of individuals harboring ancestral heterogeneity30. In other words, while many hPSC collections were launched prior to or simultaneous with large-scale genomic initiatives , laboratories within Brazil have derived iPSC lines and performed ancestry analyses to establish cellular resources that better reflect the Brazilian population, linked with clinical phenotyping data32. Alternatively, as groups like TOPMed33 and 1000 Genomes34 are expanding their reference populations, and cell banks like the California Institute for Regenerative Medicine are utilizing SNP microarrays to assay genomic integrity, these data could be combined to ascertain more refined ancestry predictions as opposed to relying solely on self-reported race or ethnicity. These more diverse reference panels will also further enable analyses of experimental models from underrepresented populations. At a minimum, standardized and more accurate descriptions of race, ethnicity, and ancestry should be used in future hPSC collections. Here, frameworks developed for reporting data in genomic studies could be leveraged to provide greater harmonization across disciplines 35.In a best-case scenario, for participants who have consented to iPSC derivation, material for iPSC reprogramming and banking would be collected alongside material for genomic and/or phenotypic studies, thus providing a direct link between these data and available cellular resources Fig. . NotablyMoving forward, increasing genetic diversity in hPSC collections and experimental paradigms has the potential to both accelerate basic biological discovery and facilitate more equitable distribution of scientific benefit. Beyond the discrete points discussed above, this will require a deliberate shift in the mentality investigators use to structure experiments and address the pressing scientific questions in their respective fields.Further information on research design is available in the Reporting Summary


Metopolophium dirhodum  were evaluated on parental and first filial generations. The results showed that sub-lethal concentrations of imidacloprid significantly reduced the fecundity, adult longevity, and reproductive period of M. dirhodum in parental generation (F0). However, the imidacloprid-induced hormetic effects on development and reproduction were detected in the F1 generation. These hormetic effects were indicated by significantly higher adult longevity, fecundity, survival rate, intrinsic and finite rates of increase, and net reproductive rate of first filial generation (F1) of M. dirhodum. Our finding indicated that the application of sub-lethal concentrations of imidacloprid inhibited parental generation (F0), but it significantly stimulated the population growth of filial generation (F1) in the M. dirhodum. The results support the inclusion of insecticides in integrated pest management programs for managing wheat aphids.Field populations of insect pests are affected by sub-lethal doses of insecticides, leading to hormesis. Imidacloprid is a neonicotinoid insecticide widely used to control various sucking insect pests, including aphids. In this study, the effects of sub-lethal concentrations of imidacloprid on the life table traits of the rose-grain aphid  Myzus persicae  is characterized by low-dose stimulations and high-dose inhibitions . HormetiMetopolophium dirhodum Walker (Hemiptera: Aphididae) is a major wheat aphid species that substantially lowers the productivity of cultivated winter cereals (Luteovirus)  .M. persicae, Bemisia tabaci and Nilaparvata lugens  competitive modulators) and blocks the nicotinic acetylcholine receptors in the central and peripheral nervous systems of insects . Becausea lugens . It has a lugens . Imidaclpersicae  and A. ggossypii . HoweverM. dirhodum population used in this research was sampled in 2016 from wheat fields located at the Pest Sciences Observation and Testing station in Haidian district, Beijing, China. After field collection, the aphids were maintained on young winter wheat (Triticum aestivum Linnaeus) plants in a growth chamber set at 18°C ± 1°C and 60% ± 10% relative humidity, with a 16-h light/8-h dark photoperiod. The aphids were not exposed to any insecticides prior to this study.The M. dirhodum mortality.Imidacloprid (Gaucho® 600FS)  was obtained from Bayer Crop Science . A stock solution was prepared in acetone  and diluted with water containing 0.05% (w/v) Triton X-100  to concentrations appropriate for generating dose-response curves between 0% and 100% M. dirhodum adults. The treated and control insects were incubated in a plant growth chamber maintained at 18°C ± 1 °C and 60% ± 10% relative humidity, with a 16-h light/8-h dark photoperiod. Insect mortality was recorded after 24 h. If no more than two legs moved in response to a slight touch with a soft brush, the individual was considered dead. The imidacloprid treatments along with the control treatment were replicated ten times.A wheat seedling dipping method was used in this study . BrieflyM. dirhodum (F0) fecundity and survival were determined. The number of new born nymphs was recorded and the offspring were removed daily until death. The long-term  sub-lethal effects of imidacloprid on M. dirhodum (F1) life table parameters were also examined, including the developmental period, life span, survival rate and fecundity. Accordingly, the life table data of the filial generation were recorded. For each treated female, one or two new born nymphs produced overnight were transferred to a new wheat plant, i.e., 100–120 newborn nymphs (≤24-h old) were observed individually in each group. The number of new-born nymphs was recorded and the offspring were removed daily until death. In each experiment, the aphids were transferred to new plants every 3–4 days.A life table study was completed with 50, 100, and 200 mg/L imidacloprid solutions (prepared in distilled water) and water containing 0.05% (w/v) Triton X-100 as the control. Wheat seedlings were dipped in the imidacloprid or control solutions for 10 s. A cohort of 90 third instar nymphs was treated with imidacloprid as described in bioassay section. After 24 h, the surviving aphids were individually transferred to pots (10 × 10 × 10 cm) containing young winter wheat plants. The short-term  sub-lethal effects of imidacloprid on the treated 15, LC25, LC35, were calculated with 95% confidence interval (95% CI), and slope were calculated by a probit analysis using the DPS software (version 7.05). The raw life history data for the M. dirhodum F0 and F1 were evaluated with the TWOSEX-MSChart program (M. dirhodum population (50 newborn nymphs) was projected to 60 days based on the above data with the TIMING-MSChart program , 114.734 mg/L (95% CI: 59.716–182.705 mg/L), 209.699 mg/L (95% CI: 124.736–317.737 mg/L), and 380 mg/L (95% CI: 274–852 mg/L), respectively. Finally, 50, 100, and 200 mg/L imidacloprid were used as the sub-lethal concentrations  in subsequent experiments. The effects of these concentrations on third instar nymphs were evaluated. At 24 h after the 50, 100, and 200 mg/L imidacloprid treatments, the aphid mortality rates were 15% ± 0.925%, 24% ± 0.845%, and 35% ± 1.352%, respectively.The toxicity of imidacloprid to the M. dirhodum third instar nymphs were treated with three sub-lethal concentrations of imidacloprid . The effects of different sub-lethal doses of imidacloprid on adult longevity, reproductive period and fecundity of M. dirhodum F0 are shown in M. dirhodum F0, which showed a trend of significant decrease with the increase of the concentrations of imidacloprid.The M. dirhodum F1 whose parents were treated with three sub-lethal concentrations of imidacloprid are presented in M. dirhodum aphids (first to fourth instars) developed rapidly following all treatments. Moreover, except for the third instar nymphs, the development was significantly negatively (first instars nymphs) and positively (second and fourth instar nymphs) affected by the three sub-lethal concentrations of imidacloprid. The pre-adult stage duration of F1 individuals tended to decrease, which was in contrast to the increase in the average adult stage duration following the imidacloprid treatments (relative to the effects of the control solution). The adult and total longevity of the F1 individuals was highest in response to the 50 mg/L imidacloprid treatment (LC15). The adult pre-reproductive period (APRP) and total pre-reproductive period (TPRP) was significantly reduced by the imidacloprid treatments, but the reproductive period was not significantly different between imidacloprid and the control treatments. Also, the fecundity of the F1 individuals was highest in response to the 100 mg/L imidacloprid treatment (LC25).The developmental duration, longevity and fecundity for the sxj) reflect the high age-stage-specific survival rates for the females following all treatments, however, the imidacloprid-treated M. dirhodum F1 generation had a higher survival rate than that of the control in later stages (lx), the age-specific fecundity (mx), and the age-specific maternity (lxmx) reflected the effects of the increasing imidacloprid concentrations on the M. dirhodum population over time, which indicate that these parameters were higher in different doses of imidacloprid treated groups of aphids middle and later stage  refers to the predicted survival time of an individual at age x and stage j. Compared with control, the F1 individuals produced by F0 imidacloprid-treated had a higher life expectancy  following each imidacloprid treatment revealed that it was highest for LC35 (day 10) than for the control (day 12), as well as for LC15 and LC25 (day 11)  .M. dirhodum F1 generation are listed in T) of M. dirhodum F1 generation. However, increases in imidacloprid concentrations significantly increased the net reproductive rate (R0), intrinsic rate of increase (r) and finite rate of increase (λ), indicated that all imidacloprid treatments induced a rapid M. dirhodum population growth.Population life-table parameters of the control and imidacloprid-treated 1 (15), 100 (LC25), and 200 (LC35) mg/L imidacloprid treatments on day 60 were predicted to result in 4.72, 7.81, and 7.80 million aphids, respectively. Forty days later, the M. dirhodum population growth curves calculated on a logarithmic scale were nearly linear, implying that M. dirhodum populations were approaching the stable age-stage distribution. Such linear population increases are indicated by the slopes of the regression lines, which are equal to log(λ) for each cohort. These results suggest that an exposure to sub-lethal concentrations of imidacloprid induced M. dirhodum population growth.The projected population was analysed based on the age-stage, two-sex life table and the data for F1 . The conM. dirhodum population.Imidacloprid is a typical neonicotinoid insecticide widely used to control various sucking pests, including aphids  Target aM. persicae treated with low imidacloprid concentrations  effects were not observed in F0 individuals treated with low concentrations of imidacloprid. This is consistent with the reported lack of hormetic effects in the F0 generations of A. gossypii exposed to a sub-lethal concentration of afidopyropen and sulfoxaflor  treated with sub-lethal doses of imidacloprid  significantly stimulated the population growth of the F1 generation, the analysed life table parameters , fecundity, longevity, and survival of the F1 generation were positively affected by the sub-lethal concentrations of imidacloprid treatments. Additionally, the population prediction results show that an exposure to sub-lethal concentrations of imidacloprid induced M. dirhodum population growth. Similar effects on population growth were observed in an earlier study on sweetpotato whitefly B. tabaci, which proved that imidacloprid increases the gross reproduction rate, but does not significantly affect the mean generation time (Amblyseius victoriensis (Womersley) significantly increase in response to systemic spray treatments of imidacloprid , but has stimulatory effects on the first filial generation (F1). Considering all of the arthropod biological processes affected by pesticides, it is possible that hormetic responses are induced in arthropods exposed to these chemicals (In conclusion, our findings indicated that the application of sub-lethal concentrations of imidacloprid has inhibitory effects on the parental generation (Fhemicals . Future


Coyotes are ubiquitous on the North American landscape as a result of their recent expansion across the continent. They have been documented in the heart of some of the most urbanized cities, such as Chicago, Los Angeles, and New York City. Here, we explored the genomic composition of 16 coyotes in the New York metropolitan area to investigate genomic demography and admixture for urban-dwelling canids in Queens County, New York. We identified moderate-to-high estimates of relatedness among coyotes living in Queens (r = 0.0–0.5) and adjacent neighborhoods, suggestive of a relatively small population. Although we found low background levels of domestic-dog ancestry across most coyotes in our sample (5%), we identified a male suspected to be a first-generation coyote–dog hybrid with 46% dog ancestry, as well as his two putative backcrossed offspring that carried approximately 25% dog ancestry. The male coyote–dog hybrid and one backcrossed offspring each carried two transposable element insertions that are associated with human-directed hypersociability in dogs and gray wolves. An additional, unrelated coyote with little dog ancestry also carried two of these insertions. These genetic patterns suggest that gene flow from domestic dogs may become an increasingly important consideration as coyotes continue to inhabit metropolitan regions. Canis latrans) are synanthropes [C. lycaon), red wolves (C. rufus), gray wolves (C. lupus), and domestic dogs (C. familiaris) [Coyotes  ,12,13,14iliaris) ,7,15,16.iliaris) ,18, inclNYC is the most densely populated city in the United States with over 8.8 million people and approximately 27,000 people per square mile (United States Census Bureau 2020). The first documented evidence of a coyote in the NYC metropolitan area occurred in 1994 in the Bronx .Canis species, coyotes have a history of being characterized as generalists and opportunistic predators with highly variable diets [Urban areas present a unique ecosystem with many ecological opportunities for coyotes. Among the le diets ,23,24,25le diets ,28,29,30le diets ). Despitle diets . Here, wWe obtained 16 blood or tissue samples from coyote individuals in NYC and surrounding areas , includiWe prepared genomic DNA for restriction-site-associated DNA sequencing  and digWe processed the sequence data by retaining the read (and its pair) that contained the unique barcode and the remnant SbfI recognition motif using a custom perl script. We then further processed these reads in STACKS v2 ,34. We fp = 0.01. All SNPs discovered per locus were reported for downstream filtering. We used VCFtools v0.1.17 [We merged the target 16 coyotes with public RADseq data from 40 reference samples representing domestic dogs, western coyotes, eastern wolves, and gray wolves prepared following the same methods , and peWe included the Y chromosome  with thC. familiaris) collected from North America given the possibility of recent interbreeding with dogs in an urban community. Moreover, we included both the eastern and gray wolves given their different known demographic histories [To infer ancestry proportions for the queried New York coyote samples, we selected a set of reference populations based on previous genome-wide studies that identified populations of little to no admixture, as well as incorporating pre-expansion demographics ,46,47. Tistories . The firBecause of these reports, we genotyped three transposable element insertions that increase human-directed hypersociability behavior in canines: Cfa6.6, Cfa6.7, and Cfa6.66 located on canine chromosome 6 . The alWe explored the ancestry structure across chromosome 6, which houses the TE alleles associated with human-directed canine hypersociability. Ancestry blocks were defined by a minimum of three contiguous SNPs of the same locally inferred ancestry identity. We annotated the genes contained within each ancestry block using the UCSC Genome Browser’s Table Browser function for dog reference genome CanFam3.1 . We usedWe sequenced 16 target coyotes represented by 17 samples (MEW009 was duplicated) collected from the New York City metropolitan area and discovered SNPs with the inclusion of 40 additional reference genomes for ancestry analysis. We established a catalog of 2,620,950 loci with an effective per-sample sequence coverage of 8.7-fold. Four samples were excluded from all downstream ancestry inferences due to missing data (two target coyotes and two gray wolves). After filtering SNPs for MAF and missingness, we retained 53 canids (38 references and 15 target) and 26,763 SNP loci for ancestry inference. An initial check of samples was completed using PCA with 16,355 loci after excluding SNPs that significantly deviated from HWE and were highly correlated with other loci.p = 5.18 × 10−9)  . Of the  × 10−9) . We thenThe PCA revealed that the target coyotes likely contained admixed genomic contributions from both coyotes and domestic dogs . We thenr = 0.05) with substantial variation (s.d. = 0.14) and 76 of these comparisons were unrelated (r = 0) . There was one unrelated dyad  with all other intra-group estimates indicative of siblings/parent–offspring or half-siblings (r = 0.35–0.5) . We found that most notable relatedness pairs were spatially adjacent . A single long-distance dyad was found between male MEW004 and male SH001, collected on opposite ends of Long Island (r = 0.13)  of these adult animals with two Elmjack pups (NY04 and NY05). Each pup notably carried 25% dog genetic ancestry, the expected proportion for offspring of a cross between a coyote–dog F1 hybrid (NY01) and a non-admixed coyote (T211). Together with direct observations, we conclude that NY01 and T211 were a breeding pair and NY04 and NY05 were their offspring. We analyzed genome-wide SNP genotype data and found that NYC area coyotes carry, on average, low levels (5–10%) of domestic dog genetic ancestry. Moreover, we provide the first documented evidence of first- and second-generation coyote–dog hybrids in NYC. The F1 coyote–dog hybrid is an adult male (NY01) of the Elmjack pack and was mated with an unrelated female mate (T211) who carried only background levels of dog introgression. We further documented close genetic relationships . Our overall findings support Henger et al.  who concStudies across multiple species show that animals with frequent human encounters often exhibit reduced fear of, and habituation to, humans over time ,57,58,59Coyotes thus seem to be pulled in two directions regarding human activity, and how an individual coyote behaves depends greatly on what they experience. Schell et al.  observedA potentially key component of this interplay may occur at a genetic level. There is evidence that domesticated and derived traits can be transferred back into wild relatives, and possibly confer an adaptive advantage. For instance, the melanistic K locus mutation causes melanism in coat color in North American wolves and derives from past hybridization with domestic dogs. This mutation is found at a high frequency in forested habitats and exhibits a molecular signature of positive selection, indicating it confers an adaptive advantage . SimilarHere, we examined three candidate alleles that are known to influence human-directed social behavior in canines . These aObserving two heterozygous genotypes per coyote significantly increases the probability that they would show social behavior towards humans . In factOur genetic evidence of recent coyote–dog hybrids, the small population size, and the relatively high frequency of hypersocial alleles suggest that genetic monitoring will be critical to understanding how to coexist with coyotes in the NYC area. Rapid genetic changes through occasional coyote–dog hybridization could lead to changes in genetic background and behavioral traits associated with urbanization . The ratWe describe low levels of dog ancestry in the majority of the 16 coyotes analyzed from the New York Metropolitan area. However, the Elmjack pack had a documented history of increased human proximity and interactions. We discovered that the adult male suspected to be a first-generation coyote–dog hybrid carried 46% dog ancestry with two genetically-confirmed back-crossed offspring that carried approximately 25% dog ancestry. These coyotes also carried transposable element insertions that are associated with human-directed canine hypersociability, likely influencing their tolerance for human activity and interactions. These genetic patterns suggest that gene flow from domestic dogs may become an increasingly important consideration as coyotes continue to inhabit metropolitan regions.


Following foliar spraying with both fertilizers, the content of Zn in leaves of the Castelão and Moscatel varieties showed higher values in all treatments relative to the control. Moreover, in grapes this tendency occurred only in Castelão. Concerning Cu, Fe, Ca, K, S and P, some significant differences also happened in leaves and grapes among treatments. At harvest, the indexes of Zn enrichment in grapes increased between 2.14- and 8.38-fold and between 1.02- and 1.44-fold in Castelão and Moscatel varieties, respectively. Zinc in the dried skin of Castelão only increased with ZnO and ZnSO4 sprayed at 900 g ha−1 , but in Moscatel a clear accumulation trend could not be found. The dry weight of grapes ranged (in %) between 16 and 23 (but did not vary significantly among treatments of each variety or in each treatment between varieties), and total soluble solids  and color parameters showed some significant variations. Through winemaking, the contents of Zn increased in both varieties  and in all treatments, although non-significantly in Castelão. It is concluded that, to increase the contents of Zn in grapes without reaching the threshold of toxicity, ZnO or ZnSO4 can be used for foliar spraying of Castelão and Moscatel varieties until 900 g ha−1 and that winemaking augments the level of this nutrient.Grapes and wine are widely consumed in the world, yet their mineral content can be influenced by many factors such as the mineral composition of soils, viticulture practices and environmental conditions. In this context, considering the importance of Zn in the human physiology, the enrichment of Moscatel and Castelão grapes  with this nutrient prompted this study; further assessment of tissue deposition and some implications for wine production. Using two foliar fertilizers (ZnO or ZnSO In this context, at cellular and tissue levels, zinc’s multiple functions include catalytic, structural and regulatory roles. Thus, Zn binding sites exist in a large number of proteins, membrane lipids and nucleic acid molecules. The largest class of Zn-binding proteins in organisms is the Zn finger domain containing proteins, which can regulate transcription directly through effects on DNA/RNA-binding, and also through site-specific modifications, regulation of the chromatin structure, RNA metabolism and protein–protein interactions [Zinc, the 23rd most abundant element on earth, is a transition metal with the atomic number 30 and is redox-stable under physiological conditions because of a complete d-shell of electrons ,2. Its dractions ,5. Typicractions .Besides the structural and metabolic relevance of Zn at a cellular level, from a nutritional point of view, Zn is a fundamental trace element and one of the most abundant in the human body  ,8. ConsiTo surpass nutrient deficiency in the human diet, the application of agronomic workflows to increase the amount of a nutrient in the edible part of food crops, by application of fertilizers through soil or foliar spraying, is receiving increasing attention ,18,19,20Through leaves, plants can also absorb different nutrients and export them within the stem via phloem or xylem ,31, whicArabidopsis thaliana as a reference biological system, 2367 proteins (implicating 181 gene families) were identified as Zn-related, which is the largest group assigned to transcription regulator activity and binding functional subcategories [Although Zn enrichment occurs when its contents exceed the level of sufficiency within a crop plant, oversupply can have negative metabolic and structural consequences at cellular and tissue levels . Indeed,tegories . On the tegories  and can tegories . At metategories ,39. Accotegories ,42,43,444 and ZnO in vineyards of two contrasting varieties (Castelão and Moscatel) of Vitis vinifera L. for the enrichment of grapes with Zn prompted this study; furthermore, this study assessed its tissue deposition in grapes and the implications on winemaking.Considering the importance of grapes and winemaking , the efficiency of foliar fertilization with ZnSOThe vineyards of both varieties were almost flat with a very slight inclination, revealing a maximum variation of 0.80 m in Lagameças and about 1.10 m in Lau Novo . As the Comparatively to the vineyard of Lau Novo, the average values of pH, electrical conductivity and organic matter in the soils were found to be significantly higher in the vineyard of Lagameças , indicatThe irrigation water of Lau Novo  was from4. It was found that after three leaf sprayings (1 August), the Pn of Castelão treated with ZnO did not vary significantly among treatments, but pulverization with ZnSO4 (450 and 900 g ha−1) revealed about a 20% decrease  due to variations of gs . The combination of Pn and E results led to an iWUE reduction between 10% and 22% on the 2nd assessment , improves electron transport through the photosystem II and increases the photosynthetic rates and chlorophyll content, which determines an increase in fruit yield and quality as observed for kinnow mandarins, sweet oranges and grapes . Based odecrease A. After ns of gs B. Indeedsessment C.−1) of ZnSO4 and ZnO, respectively .After the second foliar application with ZnO or ZnSOl showed  some sig−1 of ZnO and ZnSO4, respectively . In the grapes of Castelão, the concentrations of K did not vary significantly, but in Moscatel the highest value was found in the control and the lowest after application of ZnSO4 (150 g ha−1).The levels of Cu and K in the leaves of Castelão revealed minimum values with the highest treatment of ZnO, but a clear trend could not be found through the application of both foliar fertilizers . In the 4 (150g ha−1)  .−1), respectively (4 (150g ha−1) and the highest with ZnO . Concerning the grapes of Moscatel, the lowest and highest contents of S were found with 900 g ha−1 ZnO and 450 g ha−1 ZnSO4, whereas in Castelão they were found with 900 g ha−1 ZnSO4 and 150 g ha−1 ZnO  and ZnSO4 (450 g ha−1 and 900 g ha−1), whereas the opposite occurred with the lowest treatment with ZnSO4, and significant differences could not be found with the application of ZnO at 450 g ha−1. The amount of Cu remained significantly lower for all treatments of Castelão. The amount of Fe did not vary significantly with ZnO (150 g ha−1 and 900 g ha−1) and ZnSO4 (450 g ha−1 and 900 g ha−1), but opposite trends were found between both varieties with ZnO (450 g ha−1) and ZnSO4 (150 g ha−1). The contents of Ca significantly prevailed in Moscatel for all treatments (except with foliar spraying of ZnO at 900 g ha−1). Relative to the amounts of K among the treatments of each variety, significant differences were found in Castelão and Moscatel (excepting 900 g ha−1 ZnO and 450 g ha−1 ZnSO4). Concerning S, between each treatment of both varieties, significantly higher values were found for Castelão through the application of the different concentrations of both fertilizers . The levels of P did not vary significantly between each treatment of both varieties after foliar spraying with the different concentrations of fertilizers .Between the controls of both varieties, the leaves of Castelão showed significantly higher values of Zn, Fe, S and P, but the opposite occurred with Cu and Ca and significant differences could not be found for K . Moreove−1) and ZnSO4 (150 and 450 g ha−1), but in the other treatments significant differences were not detected. Concerning Ca, similar treatments of both varieties did not reveal significant differences (except Castelão that showed lower contents after the ZnSO4 application with 900 g ha−1). Relative to the amounts of K in the same treatments of each variety, higher values were consistently found in Castelão . Between both varieties, each similar treatment revealed higher contents of S in Castelão . Relative to P, between each similar treatment of both varieties, higher contents were found after application of ZnO at 150 g ha−1 in Castelão, but the opposite occurred through foliar spraying with ZnSO4 at 900 g ha−1, and significant differences could not be found for the remaining concentrations of both fertilizers.Concerning the variations in each treatment of grapes from Castelão and Moscatel, heterogeneous trends were also found after foliar spraying with different concentrations of both fertilizers . The con−1) and ZnSO4 after foliar spraying with 900 g ha−1  (−1), a significantly higher value was found, whereas in Moscatel a ca. 1.45- and 2.10-fold increase was found in the two highest concentrations of spray with ZnSO4   ; Table 3ctively) ; Table 3ctively) ; Table 3−1 of ZnSO4) (−1) and ZnSO4 (at 150 and 900 g ha−1) treatments having systematically lower values in Moscatel  between about 16 and 23, but did not vary among treatments of each variety or in each treatment between varieties . Moreovef ZnSO4) . BetweenMoscatel .−1 and ZnSO4 at 450 and 900 g ha−1). Parameters a * and b * did not vary among treatments in each variety (except a * with ZnSO4 at 450 g ha−1 in Moscatel). Relative to Castelão, in the grapes of each treatment of Moscatel, a * revealed significantly lower values (except ZnO at 150 g ha−1), but the opposite occurred in all treatments with b* , although non-significantly in Castelão (4 (at 900 g ha−1) in Moscatel, but in Castelão the highest increase was detected  with ZnO at 900 g ha−1 , as well as for Mn, Fe and Ca [Mineral and organic components of soils, as well as their chemical and biological processes, interfere with plant productivity, but the bioavailability of nutrients throughout the entire pathway, from soils to plants, also depends on the relief and type of land use. In fact, the slope and slope length of soils are important factors that control the intensity and frequency of surface runoff and, therefore, sediment/fertilizer losses. In this context, the slope of both vineyards , having  similar e and Ca ,50. Comp4 and ZnO, comparatively to the control, both varieties revealed an absence of significant variations of Pn and gs, indicating that at this point the mobilization of photoassimilates was not affected (2 into chloroplasts) [3 and K+ uptake by the guard cells [4 and ZnO (2+ uptake) [2 to the carboxylation sites in the chloroplast [After three leaf sprayings with ZnSOaffected . In factoplasts) . Furtherrd cells . Neverth and ZnO , which s uptake) . Besides uptake) . Moreove uptake) , since a uptake) . Indeed, uptake) , which ioroplast .−1), clearly further pointing to a synergistic accumulation behavior that also does not prevail in grapes  [4 [Although grapes are highly sensitive to Zn deficiency , despite tissues ,82,83,84 tissues . However tissues ,87, ZnSOoxicity) , whereascity) [4 ,90,91,924, in general, accentuated the total soluble solid content in Moscatel, which is a favorable aspect for wine production  [At harvest, the absence of significant variations in biomass among the different Zn-treated grapes and between both varieties  further oduction . Neverth.5 °Brix , which e.5 °Brix . Still, .5 °Brix  that, in mg·L−1) . The enr mg·L−1) .Vitis vinifera varieties, Castelão and Moscatel, were produced in the vineyards of Lagameças and Lau Novo, located in Setubal, Portugal .4  were performed with 14–21 day intervals. Control vines were sprayed with water. Harvest was performed by 24 and 25 September for Castelão and Moscatel, respectively. Between 16 June and 25 September, maximum and minimum mean temperatures ranged between 28 and 16.6 °C.After flowering (on 16 June), three leaf spraying applications with ZnO or ZnSOOn 1 August 2018, for each plot  of both vineyards, data was collected using a drone (DJI Phantom Pro V2.0), with high-definition and multi-sector RGB  and Parrot Sequoia  cameras that were used to produce orthophotomaps. Calibration of the multispectral Parrot Sequoia camera further considered the environmental brightness conditions. Images were processed in a workstation , to produce the final mapping. To assess the general morphology and surface water drainage areas of the experimental fields, Agisoft PhotoScan Professional  was used. The evaluation of the drainage areas of surface water was carried out according to . The higThe content of organic matter in the soils of the vineyards was determined in 28 samples (about 100 g were collect from the surface to a 30 cm depth). Samples were sieved  and the weight recorded after drying  for quantification of the dry mass and percentage of moisture.To determine the content of organic matter, samples were heated to 550 °C for 4 h  and, after removal from the muffle (at 100 °C), desiccated until room temperature was reached (approximately 1 h). Samples were then weighed to determine the percentage of organic matter.soil mL−1 water milli-q) and stirring for 1 h (at 25 °C for 30 min) in a thermal bath, determinations were carried out after decantation of the supernatant [Using a potentiometer, pH and electrical conductivity of soil samples were determined. After mixing at a ratio of 1:2.5  under a helium atmosphere , according to .Water quality was analyzed considering physical  and chemical  parameters. Electrical conductivity (EC) and pH were determined using a Consort Multiparameter analyzer (C 6030) and SP21 (pH) and SK20T (CE) electrodes. Calcium, Na, K and Mg ions were quantified using a Metrohm (Model 761 Compact IC) chromatograph, equipped with a column and pre-column  using an eluent mixture (4 mM tartaric acid/1 mM dipicolinic acid) at a flow rate of 1.00 mL/min and a sample injection of 10.0 μL. Alkalinity/bicarbonate was determined by titration in 100 mL of water samples, using 0.1 N hydrochloric acid as the titrant in the presence of 0.1% methyl orange .Chloride, sulphate, nitrate and phosphate ions were quantified by photometry  using specific kits . Water classification considered dominant ions and followed . A sodiu2 (ca. 400 ppm) and PPFD ranging between 1200–1400 µmol m−2 s−1. Leaf instantaneous water use efficiency (iWUE) was calculated as the Pn-to-E ratio, representing the units of assimilated CO2 per unit of water lost through transpiration.Leaf gas exchange parameters were determined using 4–6 randomized leaves per treatment on 1 August (1st assessment) and 13 September (2nd assessment), following . Leaf raAfter the 2nd foliar application, nutrient contents were quantified in randomized leaves and grapes  according to , using a3−:HClO4 (4:1), according to [After harvest, randomized grapes were washed, dried at 60 °C until a constant weight and ground in an agate mortar. Thereafter, an acid digestion procedure was performed with a mixture of HNOrding to , followe2 sensitive area and energy resolution of 142 eV for Mn Kα. Measurements were carried out under 20 mbar vacuum conditions. These point spectra were acquired for a duration of 200 s.The location of Zn in the skin and seeds of grapes, collected at harvest, was determined with the µ-EDXRF system , according to . The X-rDry weight was measured by considering three randomized grapes per treatment.Total soluble solids were measured in the grapes’ juice, using a digital refractometer from Atago ; the obtained values were expressed as °Brix.65, the system of the Commission Internationale d’Éclaire (CIE) was applied. The parameter L * represented the brightness of the sample, translating the variation of the tonality between dark and light, with a range between 0 (black) and 100 (white). Parameters a * and b * indicated color variations between red (+60) and green (−60), and between yellow (+60) and blue (−60), respectively. The approximation of these coordinates to the null value are consider neutral colors such as white, gray and black. Measurements were carried out at harvest, considered in triplicates of three independent series.Colorimetric parameters, using a fixed wavelength, adopted the methodology described by . Brightn3; DAP—Diammonium phosphate (12 g) was applied at the peak of fermentation (density between 1030–1040 g/cm3) and when the density reached 1000 g/cm3; sulfur dioxide (3 mL) was applied when the density reached 990 g/cm3. The wine was then filtered, followed by bottling.After destemming (50 kg) and pressing the grapes, sulfur dioxide was added to the must (18 mL) and, after 24 h of rest at 6 °C, Springarom (18 g) was added to the vat. The yeast was hydrated with water at 37 °C (1:10), and after 20 min it was added to the wort in the vat, followed by homogenization of the mixture. The temperature and density of the mixture were then regularly checked and PVPP/Polyvinylpolypyrrolidone—Divergan F (12 g) was applied when the density reached 1060 g/cmData were statistically analyzed using a one-way or two-way ANOVA to assess differences between treatments and experimental periods, followed by a Tukey’s test for mean comparison. A 95% confidence level was adopted for all tests.4 at concentrations of 900 g ha−1 on Castelão and Moscatel grapes, but although the synthesis of photoassimilates was not affected in the mid-term of the grapes’ development, by the end of the productive cycle inhibitory effects on Pn and gs limited the water use efficiency. Independently of Zn fertilization through foliar spraying, the higher pH, electric conductivity and level of organic matter in the soils of the vineyard of Castelão, coupled with significantly higher levels of Ca and Fe, determined higher energy expenditure for root uptake of Castelão, determining  significantly lower levels of Zn accumulation in grapes. Moreover, during fruit development, the increased accumulation of Zn in the leaves of Castelão and Moscatel sprayed with both fertilizers was found to be more effective  and did not limit Fe and Cu contents, further inducing a synergistic accumulation between Ca and Zn . In addition, a combined uptake of Zn from soils, at different rates in both varieties, and foliar spraying determined nutrient movement/absorption across the cuticle and/or through the stomatal cavity, increasing the efficiency of Zn accumulation in grapes at harvest. Still, the higher accumulation of Zn in the skin of Castelão in the highest treatments pointed to a lower rate of Zn binding to light organic compounds that are linked to its mobility in the pulp and a higher deposition in the seeds. To a different extent, the glucometric degree of grapes can become accentuated by both Zn fertilizers, which favors winemaking. Besides, the accumulation of Zn in wine from both varieties, as follows the contents of this nutrient in grapes , allowed the development of a new functional food product.The threshold of toxicity was not reached through foliar application of ZnO or ZnSO


Analysis was completed for two interest outcomes—overall interest in genetic testing and interest in genetic testing if the test were free or low cost. Many demographic and SES variables were predictors for interest in genetic testing, including education, income, and MacArthur Subjective Social Scale (SSS). After controlling for the healthcare system, age, and gender, having a higher education level and a higher household income were associated with greater general interest. Lower SSS was associated with greater interest in genetic testing if the test was free or low cost. If genetic testing is the future of preventative medicine, more work needs to be performed to make this option accessible to low-SES groups and to ensure that those services are used by the most underserved populations.Cancer is a significant burden, particularly to individuals of low socioeconomic status (SES). Genetic testing can provide information about an individual’s risk of developing cancer and guide future screening and preventative services. However, there are significant financial barriers, particularly for individuals of low SES. This study used the Early Detection of Genetic Risk (EDGE) Study’s patient baseline survey ( Cancer is a significant health burden to both individuals and the United States (U.S.) health care system. This disproportionately affects individuals in low-SES income groups ,2,3,4, wThese high rates of cancer largely reflect social determinants of health, health behaviors that are influenced by those determinants, healthcare accessibility, and access to what Phelan and Link describe as ‘flexible resources’ ,5,10,11.Genetic testing for germline hereditary cancers in a primary care setting is the future of preventative medicine . GeneticHaving information about an individual’s risk of developing cancer can guide future screening and preventative services, improve the quality of care a patient will receive, and reduce the incidence of cancer . AdditioThis study aims to evaluate a possible mechanism for why cancer genetic testing is underutilized by individuals of low-SES. To do so, we examine the relationship between SES and interest in pursuing genetic testing using data from the Early Detection of GEnetic Risk (EDGE) . PreviouDescribe the demographic characteristics of the EDGE Study population;Test whether individuals of low-SES are more or less interested in pursuing genetic testing in general than individuals of high-SES;Test whether individuals of low-SES are more or less interested in pursuing genetic testing than individuals of high-SES when the test is free or low cost.Given perceived and real financial barriers low-SES individuals face when accessing genetic testing, we hypothesize that individuals of low-SES may be less interested in pursuing genetic testing generally than individuals of high-SES. We also hypothesize that when the test is offered for free or at low cost, there will be no differences in interest between individuals of low-SES and individuals of high-SES’s interest in genetic testing. The overarching study aims are as follows:This study uses data from the Early Detection of Genetic Risk (EDGE) Study. The larger goal of the EDGE Study is to reduce the overall burden of hereditary cancers by implementing cancer risk genomic testing for high-risk individuals in the primary care setting . EDGE isThe patient baseline survey was distributed to patients in participating clinics starting in January 2021, before the implementation of the EDGE program. SES measures such as total household income, education level, and health insurance were collected in this survey. However, SES is meant to capture an array of resources that an individual has available to them; not just limited to money but also including resources such as access to knowledge, power, and social connections . For thiOther SES and demographic variables measured in the patient baseline survey were age, gender, race, ethnicity, and household size. Age was a free response question, although patients were required to be over the age of 25 to participate. For gender, participants were given the options ‘Male’, ‘Female’, ‘Other’, or ‘Prefer not to answer’. If they selected ‘Other’, they were given a free-response option to specify their response. Participants could select as many race options as were applicable, including White, Black or African American, Asian, Native Hawaiian or Pacific Islander, Native American/American Indian/Alaskan Native, or Multiracial. Like gender, participants were also given an ‘Other’ option which if they selected, they could give a free response to specify. To measure ethnicity, participants were asked if they considered themselves Hispanic and/or Latino. For education, participants were given response options ranging from ‘Less than high school’ to ‘Graduate or professional degree’. Participants were given five response options for insurance, including ‘Commercial’, ‘Government/military insurance’, ‘Medicare’, ‘Medicaid’, or ‘No insurance’. They could select multiple responses here if applicable. For household size, participants could select one option ranging from one to ten or more. Lastly, for income, participants were given the option to select one of seven responses ranging from ‘Less than $15,000′ to ‘More than $150,000′. They were also given the option of ‘Prefer not to answer’. To measure interest, we developed a module  based onPatients from the two healthcare systems were asked to participate in the patient baseline survey. We reached out to a total of 6588 patients across all twelve clinics—549 from each clinic. Our original intent was to be able to recruit at least 200 from each clinic. A total of 2329 patients responded, an average of 194 per clinic. Patients who did not have an email or did not want to complete the survey electronically were mailed a copy of the survey to complete and mail back. Participants were compensated with a $10 Tango gift card for completing the survey. Data from the patient baseline survey was analyzed in SPSS. Demographic variables were checked for outliers and data was cleaned when necessary. We removed three outliers in age that were likely due to mistakes in data entry. Missing values were not replaced. We used descriptive statistics to describe income, education level, health insurance, the MacArthur scale, and race and ethnicity for our population of interest. n = 3) were excluded from analysis because there were so few. For the same reason, race and ethnicity were combined into one variable, so that White, non-Hispanic participants represented one group (n = 2011) and non-White and/or Hispanic participants represented the second (n = 217). Race and ethnicity were also analyzed as individual variables such that each possible race and ethnicity response was its own independent variable. This did not change the results of the analysis.Analyses were run using two outcomes: overall interest in pursuing genetic testing and interest in pursuing genetic testing if the test were free or low cost. Because both outcome variables had irregular distributions, we split them into binary variables where people who responded four or higher were ‘high interest’ and those who responded less than four were ‘low interest’. We also recoded all demographic and SES variables into binary variables. ‘Prefer not to answer’ responses were excluded from analysis. If a case did not include one of the variables included in analysis, the case was excluded. For gender, ‘Other’ gender responses (n = 1431) and those who had received some post-high school training or less (n = 784). Insurance was split between those who had commercial insurance (n = 1378) and those who only had Government/military insurance, Medicare, Medicaid, or no insurance (n = 836). No insurance was grouped with other non-commercial insurance because there remain disparities in insurance coverage of cancer genetic testing for underserved populations [n = 1515) and individuals reporting three or more were grouped (n = 571). For household income, individuals making less than $74,999 were grouped (n = 957) and individuals making at least $75,000 were grouped together (n = 1243). Lastly, MacArthur Scale of Subjective Social Status responses were split so that individuals scoring six or higher were grouped together (n = 1453) and those scoring five or below were grouped (n = 728). Education groups were split at those who had received at least an associate degree or higher . Results show a relatively even distribution for household income, with the minority of participants making less than $25,000 a year (n = 294). While 61% of participants indicated that they had commercial/private insurance (n = 1411), nearly half of participants reported having Medicare or Medicare supplement (n = 1073). An additional 20% had either government/military insurance, Medicaid, or no insurance (n = 455). Lastly, for the MacArthur Scale of Subjective Social Status, most participants considered themselves between a five or seven (n = 1338). A smaller amount rated themselves as eight or higher (n = 562) and an even smaller amount rated themselves four or below (n = 359).Most participants were at least high school graduates, with only 3% of our study population falling below this education line. Twenty percent of participants had received a graduate or professional degree. Most participants had a household size between one and two individuals (Odds ratios (OR) for most SES and demographic variables were similar for both clinic systems, with slight variation in education and household size. All three demographics variables—age, gender, and race and ethnicity—were significantly associated with general interest in genetic testing . Unexpecp = 0.13 and p = 0.14, respectively. Out of the remaining four SES variables, two were significantly associated with general interest in genetic testing. Individuals from both healthcare systems who received an associate’s degree or higher had greater odds of reporting interest in genetic testing . Additionally, participants who reported a household income of less than $75,000 had 1.48 greater odds of indicating low general interest in genetic testing (95% CI: 1.24–1.78). While the remaining two variables, insurance and subjective social status, were not significantly associated with general interest, they were near significant where n = 2277), 31.7% indicated low general interest in genetic testing in general and high interest in genetic testing if the cost were free or low cost.As one would expect, individuals were much more likely to report high interest in genetic testing if the test was free or low cost. For general interest in genetic testing, the percentage of individuals who reported high interest within in each demographic and SES variable ranged from 45.8% to 65% . HoweverFewer demographic and SES variables were significant predictors of interest in genetic testing if the test were free or low cost . The ORsMost associations between general interest in genetic testing and SES/demographic variables remained the same after controlling for healthcare system . After cThis project aimed to examine the relationship between SES and interest in pursuing genetic testing for hereditary cancers. This was accomplished through collecting and analyzing data in our patient baseline survey. We hypothesized that individuals of low-SES may be less interested in pursuing genetic testing than individuals of high-SES. My analysis showed that for most variables, there were differences in general interest in genetic testing. However, for some indicators individuals of low SES were more likely to be interested in genetic testing and for other indicators individuals of high SES were more likely to be interested in genetic testing. For example, individuals who rated themselves lower on the MacArthur Scale of Subjective Social Status were more interested in pursuing genetic testing but individuals who reported a household income lower than $75,000 were less interested in genetic testing compared to individuals from high-income households. Individuals of high SES were more interested in genetic testing in general when compared to individuals of low SES. Given the results of this analysis, it may be possible that individuals who make higher income or have higher education levels may be more interested in cancer genetic testing because they perceive fewer barriers to genetic testing. Overall, all individuals were much more interested in genetic testing if the test was free or low cost. This finding aligns with previous work that indicates that individuals perceive cost as a barrier to genetic testing. More importantly, it highlights the need for implementation of accessible genetic testing interventions.While genetic testing can be a successful tool for preventing cancer incidence, there remain significant financial barriers. Healthcare inequalities between the wealthiest and poorest individuals in the United States have continued to rise over the last seventy years . The NatThere is limited research on understanding the financial barriers of genetic counseling and genetic testing . HoweverOne major limitation to this project was the racial and ethnic diversity of the study population. Eighty-nine percent of our study population identified as white and 88% identified as non-Hispanic or Latino. According to the 2020 U.S. Census Bureau data for the distinct regions where these clinics are located, 58.9–94.2% of the population identify as white and 50.5–92.2% as non-Hispanic or Latino . AlthougOther limitations include a low response rate to our survey  and the geographical focus. As previously mentioned, we attempted to control for geographical differences in our analysis but only used clinics from two geographically distinct areas. Additionally, although this survey used MacArthur Scale of Subjective Status to help capture a full picture of SES, it showed opposite results compared to other SES variables. SES remains a difficult concept to measure; although indicators such as income, education, and subjective social status are clearly related, no single variable paints a full picture of SES. Of note, 6.7% of individuals who completed the survey reported already having had genetic testing for hereditary cancer while 3.7% were uncertain if they have had genetic testing for hereditary cancer and 88.6% reported not having had genetic testing. Additionally, 22.6% of individuals who had taken the survey had already been diagnosed with cancer at some point in their life. Research has found that individuals who have had cancer are interested in pursuing genetic testing to find out more about their family members’ risk of developing cancer or finding out if they should procure additional preventative screenings . It is pLastly, understanding interest in genetic testing is significant because it could ultimately influence whether an individual will decide to pursue genetic testing. In Ajzen’s theory of planned behavior , an attiIf genetic testing for hereditary cancers is to become the future of preventative medicine, it is necessary that it first becomes more accessible to individuals of low-SES. This is particularly paramount given that individuals of low-SES have higher cancer incidence and mortality. Future work investigating this relationship should look at SES and uptake in genetic testing when it is offered as a free service. Additional work could investigate the relationship between interest in pursuing genetic testing and uptake. This is a largely understudied area, and although there are theoretical models that support this relationship, research has shown mixed results. Altogether, major financial barriers exist that perpetuate poor health outcomes between the poorest and the richest individuals in the U.S. More work needs to be performed to provide preventative health service to low-SES groups and to ensure that those services are used by the most vulnerable, relevant groups.


Species range contractions both contribute to, and result from, biological annihilation, yet do not receive the same attention as extinctions. Range contractions can lead to marked impacts on populations but are usually characterized only by reduction in extent of range. For effective conservation, it is critical to recognize that not all range contractions are the same. We propose three distinct patterns of range contraction: shrinkage, amputation, and fragmentation. We tested the impact of these patterns on populations of a generalist species using forward-time simulations. All three patterns caused 86–88% reduction in population abundance and significantly increased average relatedness, with differing patterns in declines of nucleotide diversity relative to the contraction pattern. The fragmentation pattern resulted in the strongest effects on post-contraction genetic diversity and structure. Defining and quantifying range contraction patterns and their consequences for Earth’s biodiversity would provide useful and necessary information to combat biological annihilation.  Focusing attention solely on extinctions underestimates the severity of the biodiversity crisis2. Findings on range contraction for mammals by Ceballos et al.1 are alarming: nearly all of the 177 species examined have lost 40% or more of their geographic range, with almost half losing more than 80%. In a separate analysis, Ceballos et al.3 found that for 48 mammal and 29 bird species on the brink of extinction, there was an estimated reduction of 95% and 94% in their ranges since 1900, respectively. While the gravity of species extinctions is a compelling narrative within the biodiversity crisis, extinction accounts for only a small portion of overall biodiversity decline4.Widespread impoverishment of biodiversity, referred to as “biological annihilation”3. However, range contractions can take various patterns beyond the spatial extent of loss and each of these patterns can have different consequences for species’ populations. Range contractions in general are large-scale disturbances that deplete populations and reduce genetic diversity by altering spatial configuration and amount of suitable habitat8. Effects of specific patterns of range contraction on population demography and genetics are understudied. The spatial impact of different patterns of range contraction will vary according to the contraction pattern, and these impacts may be observed well into the future. Indeed, Branco et al.8 found that Paleolithic range contraction influenced the modern-day spatial gradient of human genetic diversity. Different patterns may necessitate different conservation strategies, such as conserving disjunct populations, prioritizing conservation corridors, reintroduction planning, or restoring habitat within a species’ historic range.Range contraction is typically described as the amount of range lost13, but local, regional and historical factors can create exceptions15.Two general patterns are discussed in the literature on range contractions—contraction to the range core and contraction to the range periphery. Evidence suggests that ranges most often contract toward their peripheries16. Declining populations of many threatened or endangered species have been shown to suffer from a complex synergy of genetic and demographic consequences ultimately resulting from demographic depletion, consequent inbreeding and overall reduced fitness19. The influence of anthropogenic disturbance on genetic and demographic components of populations has been addressed by examining disruptions in parameters such as nucleotide diversity20, relatedness18, age structure22, number of offspring23, and reproductive fitness19 as these parameters have been found to be crucial factors in determining the persistence of populations18.Genetic and demographic factors are key determinants of population viability and species survival26. This is due to two key principles of genetic diversity. Firstly, neutral diversity for a diploid species is a product of the effective population size and the mutation rate (θ = 4Neμ); therefore, given some constant mutation rate, we can straightforwardly interpret neutral diversity as informative about the effective population size. Secondly, adaptive and deleterious diversity do not have as obvious a relationship; instead, these variants rely on the inequality 1 ≤|4Nes|, where s is the selection coefficient27. When |4Nes| is greater than 1, selection is expected to dictate the frequency of a given allele; when less than 1, drift is the dominant force. Since selection can take on a myriad of forms and is often context dependent, it is not easy to interpret results from simulations studies that incorporate selective variation due to the reliance on arbitrary values of s. Furthermore, the distribution of fitness effects (DFE) observed in most natural systems demonstrates that adaptive variation represents a small fraction of the standing variation, with most being neutral or nearly neutral28). Therefore, measures of neutral genetic diversity represent the most straightforward technique for assessing population sizes in most natural systems. However, to our knowledge, the potential consequences of distinct patterns of range contraction on genetic diversity of species’ populations have not been explored so far, particularly, how different conformations of range contractions may decouple the expected relationship between genetic diversity and population size27.Genetic diversity has emerged as an important baseline measure of population health and viability in the field of conservation genetics31 have expanded our ability to assess how range contractions impact populations. We consider here three patterns of range contraction: shrinkage, amputation, and fragmentation . Amputation occurs when reduction of geographic range begins at a point in the periphery of the species’ range and spreads across the range until the last remaining populations occur in areas that are furthest from the initial population extinctions. In short, portions of the species’ range are amputated with the advancing extinction front. Shrinkage describes the scenario where a species’ range contracts from its periphery to its core. This pattern has also been referred to as a “melting range”32 or “range collapse”33. Fragmentation at the scale of species’ ranges occurs through land cover changes that create disjunct populations because of loss of continuity in the range. Range fragmentation constrains dispersal, which may impact genetic diversity. Range fragmentation and habitat fragmentation are distinct but not mutually exclusive. Habitat fragmentation affects the spatial configuration of habitat used by a species at local scales and can occur whether or not the species’ range is reduced. The genetic consequences of habitat fragmentation have been well-documented in the literature. Consequences can include reductions in heterozygosity and allelic diversity and richness34, altered distribution of genetic diversity7, increased genetic isolation35, and increased inbreeding36. In this study, we seek to improve our understanding of fragmentation at the scale of the range and thus consider range fragmentation a form of range contraction. Range fragmentation results in a smaller total area available to be occupied by a species, though the geographic extent of the range is similar to its historical baseline. Fragmentation of species’ ranges occur due to conversion of land cover types at the range-scale. These three patterns of range contraction can be deduced when contractions are recent and historical range data exists. These patterns of range contractions have been observed in a wide variety of taxa worldwide and have been attributed to a number of different drivers  or very far .Our goal was to gain insights into the interplay between range contraction and its consequences for genetic diversity and demography, according to the three patterns of range contraction defined above. In addition to tracking nucleotide diversity, we also mapped spatial ancestry, which has been shown to be impacted by range contractionsFinally, we examined how sampling individuals from different parts of the range can alter interpretation of the impacts of range contraction. Our models allow us to make generalizable predictions about the magnitude and timing of effects of range contraction on genetic diversity and demography, and how the spatial distribution of ancestry and genetic diversity influence the interpretation of these effects. These insights can serve to inform the development of conservation interventions aimed at confronting the challenge of biological annihilation.p < 0.001 in all cases; r2 ranged from 0.33 to 0.65; Fig. p < 0.001; Fig. Simulated range contraction models resulted in population declines of 86–88%, Fig. . All mod12) between sampled groups that were similar those in the other contraction scenarios, despite having lower FST . Spatial ancestry in the amputation model was strongly biased towards the extinction front, with very few ancestors from the upper half of the range living 50 timesteps before the contraction.The amputation model was intermediate between shrinkage and fragmentation with respect to its impact on average nucleotide diversity, losing ~ 25% of its diversity prior to pre-contraction conditions Fig. D. As witThe fragmentation scenario produced the largest loss in average nucleotide diversity relative to pre-contraction conditions, suffering a > 50% decline in diversity Fig. D. Few inOur results demonstrated how range contractions can contribute to biological annihilation not only through loss of area inhabited by a generalist species, but also due to impacts on demography and loss of genetic diversity. Our simulations revealed that the extent and magnitude of effects differed depending on the pattern of range contraction. The unique outcomes resulting from amputation, shrinkage, and fragmentation underscore the importance of documenting how range contractions occur in real-world ecosystems. Range contraction can take many forms. Our models are an important step towards a general understanding of what impacts are likely to manifest under different range contraction patterns. This is crucial when considering conservation strategies for preservation or recovery of populations.39, particularly whether it responds to population reductions within the timescale of relevance to anthropogenic causes of range contractions. Concordant with previous studies41, we found that average relatedness responded much more rapidly to reductions in absolute population sizes than nucleotide diversity for our simulated generalist species. This occurred in all three range contraction patterns. In the most extreme case, shrinkage, we found that a decline in nucleotide diversity may not be detectable until > 400 timesteps after range contraction despite a > 85% loss in range area  tended to be resilient to declines in nucleotide diversity. Because population density was highest in the core of the range, the loss of peripheral individuals did not remove the bulk of standing diversity49. This is partially due to the metrics of gene flow (such as FST) being derived for discrete populations. Furthermore, incomplete sampling across the range may skew the interpretation of the impact of a contraction on measures of diversity. In our simulations, we found that samples taken from the center of the range consistently had higher nucleotide diversity and lower differentiation than those from the edges  than to their cores . As such, our generalizations for the amputation pattern will likely be the most broadly applicable in natural systems. Though amputation may be the more common pattern of range contraction in natural systems, our findings reveal that individuals on the periphery of the range will be differentially impacted depending on the way an extinction factor spreads. Given that the importance of the range periphery relative to range core for species persistence has been contested in the literature51, we can expect that impacts on species experiencing range contraction to the periphery will likely vary according to how extinction factors spread across the range14. It is also important to consider that the “abundant center” hypothesis, or the assumption that population density is higher in the center of their range and decreases towards the range edges54 has had equivocal support in the literature55. Similarly, it has been suggested that the distribution of genetic diversity in a species’ range prior to contraction may also be non-random and vary considerably between species’ ranges due to factors such as historic demographic processes56. If for example, the genetic diversity of a temperate species is concentrated at range edge due to post-glacial expansion, a pattern such as amputation could have a catastrophic impact on this species’ diversity if the highly diverse range edge is eliminated. The pre-contraction distribution of both individuals and genetic diversity throughout a species’ range therefore present critically important implications for the anticipated impacts of different range contraction patterns on species’ populations and deserve careful consideration when evaluating contraction effects.Channell and Lomolino12. These patterns have been shown to be influenced by local and regional factors, especially history of anthropogenic land use57. It is important to consider patterns of historical range loss when examining effects of range contractions. We are unaware of any published examples of two range contraction patterns occurring concurrently, but it is plausible that different forms of range contraction can take place across a species’ range over time. For example, a range could undergo amputation, then shrinkage. Though we did not simulate successive patterns of range contraction, our results lend insights into how histories of range contraction may affect demography and genetic diversity. We showed that genetic diversity was maintained near pre-contraction levels after shrinkage; however, pre-contraction diversity may not remain in a range that had historically been amputated prior to shrinking. Indeed, Donald and Greenwood14 hypothesized that this exact contraction scenario occurred in the British range of the Corncrake (Crex crex). Vandergast et al.35 found that both past and present fragmentation contributed to population genetic structure of Jerusalem crickets (Stenopelmatus ‘mahogani’).We chose range contraction patterns that reflect predominant hypotheses in range theory58, yet, despite the large literature on habitat fragmentation, it has not been adequately addressed in the range contraction literature. Our simulations of range contraction by fragmentation resulted in more drastic effects on genetic diversity and post-contraction population genetic structure than the other patterns. This is perhaps unsurprising due to the well-documented effects of habitat fragmentation on genetic diversity and structure59. Range fragmentation can occur naturally over geologic time scales yet is also caused by human land use over rapid time scales46. Range fragmentation has also been shown to cause striking demographic disruption61 that in some instances has directly led to population extinction62. The majority of fragmentation research is directed at understanding effects of habitat fragmentation on populations64. Habitat fragmentation may or may not accompany range contraction, especially for a generalist species like we modeled. Including fragmentation in geographic range theory with the other commonly studied patterns  is especially relevant considering that land use is a driver of range contraction15. We suggest that fragmentation merits further consideration as an important pattern of range contraction across the globe.Fragmentation is a ubiquitous and challenging form of range contraction and biological annihilationFST > 0.49 for all comparisons), which resulted in increased pedigree relatedness within isolated groups and decreased genetic diversity relative to other patterns. In natural systems, it may be a priority to develop corridors between fragments to restore gene flow or employ reciprocal introductions to mitigate loss of diversity among remnant populations65. Reintroductions may be an important strategy for the amputation scenario, in which connectivity remained high in the remaining range but genetic diversity was low due to the persistence of historically less diverse lineages. Undoubtedly, a complex synergy of unique factors including life history, phylogeny, social group structure, behavioral flexibility, ecological niche, or local and regional factors68 should be considered when developing strategies to combat biological annihilation. While our simulations provide important conservation implications for addressing the impacts of range contraction on species’ populations, we acknowledge that the conservation measures we suggest based on our findings may be costly and difficult to implement in practice.The principal implication of our results is that a “one size fits all” conservation approach will not be effective in identifying and ameliorating the consequences of range contraction. We showed fragmentation caused strong genetic differentiation among disjunct range fragments  to be identical, but in nature these may differ dramatically. For example, individuals may choose mates from a relatively small area, but then disperse exceptionally far from their place of birth. While varying these parameters can generate stronger or weaker trends, we contend the benefit of our models is in their generality. They create a baseline expectation for how patterns of contraction will differentially impact species.13, while most reports of range contractions for single species focus on the amount and extent of range lost70. Our results show an important next step will be to investigate consequences of contraction patterns in real ecological systems. Understanding range contraction patterns and their consequences for the planet’s biodiversity is crucial to further combat biological annihilation in the Anthropocene.Empirical studies that explicitly address range contraction patterns are of increasing value to conservation, especially if genetic and demographic correlates are also measured. Patterns of range contraction have typically only been considered in multi-species analyses and reviews31 . To ensure we could conclude that differences observed in reduction of nucleotide diversity were due to the pattern of range contraction and not a result of population decline, we constructed simulations such that population decline was equal among scenarios and co-occurred with a similar amount of range reduction . If population decline were the driver of reductions in nucleotide diversity, then each scenario would result in equivalent levels of genetic diversity. To ensure that our fragmentation model was not influenced by our specific configuration choice, we also ran a model in which the landscape contracts at random. Simulations continued for another 400 timesteps after the final contraction and were performed ten times per contraction scenario, representing ten completely replicated populations for each scenario.Range contraction patterns were modelled using individual-based simulations in SLiM v3.349 for our model runs. Battey et al.49 evaluated the influence of a wide range of parameter values in SliM onWright’s neighborhood size, estimation of genetic diversity, and other summary statistics pertaining to population genetic analysis. We simulated a species with overlapping generations, density-dependent competition, no habitat selection within its range, and spatially explicit mating. For both mate choice and intra-specific competition, distances between individuals were converted into interaction strengths and defined by a Gaussian kernel with a maximum (m) of 1 / 2 π σ2, where π is the mathematical constant (rather than nucleotide diversity) and σ is the dispersal distance. The interaction strength had a maximum distance of 3σ, beyond which spatial competition and probability of mating are both effectively zero. Each cell of the landscape had a carrying-capacity (K) of 5 individuals. For simplicity, individuals were modelled as hermaphroditic but self-incompatible. The number of offspring from each mating pair were chosen based on a random draw from a Poisson distribution with λ = 1/L, where L (= 4) is the mean age (in timesteps) of individuals within the population at any given generation. Following classical spatial population genetic models72, offspring dispersed according to a random draw from a normal distribution with a mean of zero and standard deviation σ. Range boundaries are absorbing such that any individuals that disperse outside the range die. Preliminary simulations showed little difference between absorbing and reflecting boundaries; the former decreases fitness by reducing offspring number, the latter reduces fitness by increasing spatial competition. Individual fitness (W) of individual i can ultimately be defined as a combination of competition and site-specific effects (h):K] and represents the spatial competition constant49.Our simulations apply to an ecological generalist species with broad habitat requirements. The simulated species does not represent a particular taxon; rather, we chose traits that would make our simulations robust to a wide range of life history strategies. In addition, the specific suite of parameter values we chose guaranteed (1) spatial structure and patterns of isolation-by-distance; (2) dispersal distances that allowed a lineage to traverse the range in at least 40 timesteps (~ 10 generations); and (3) population sizes could be equivalent across contraction scenarios, regardless of final range conformation. In some cases, altering dispersal distance or carrying-capacity resulted in population sizes being unequal following contraction, which would make these scenarios cease to be comparable. Thus, we settled on single parameter values for dispersal, carrying-capacity, and interaction distances. We followed the overall design and concept of Battey et al.https://petrelharp.github.io/circle_rectangle_intersection/circle_rectangle_intersection.html).To address the effects of range edges on individual fitness, we corrected the area of the interaction circle for individuals near the edge by recalculating it to represent actual occupiable space . Next, we adjusted the strength of spatial competition to the number of individuals occupying the recalculated interaction area. For the full details on this procedure for correcting for edge effects, see Ralph  with a haploid genome size of 1000 Mb, a recombination rate of 10–9, and mutation rate 10–8. These rates ensure ~ 1 recombination event on average per gamete and ~ 10 new mutations per gamete. During the simulation, SLiM tracked the local ancestry of each recombination breakpoint interval for all individuals via tree sequence recording31. In addition, we utilized SLiM’s ability to store the full pedigree of all individuals, allowing us to estimate an average of Wright’s coefficient of relatedness73. We did so by randomly sampling 50 individuals each generation, estimating their pedigree relatedness, and then estimating average sampled relatedness as: Fr = (r – n)/n where r is the sum of all values in the relatedness matrix and n is the sample size. Finally, we recorded mean and max age (in timesteps) of the population for each timestep, as well as recorded the number of offspring and fitness of individuals, throughout the simulation. Specific SLiM recipes for each contraction model are available at https://github.com/hancockzb.Each simulated individual was diploid .Tree-sequences produced from SLiM were imported into Python. Haplotypes with multiple ancestors  were “recapitated” using 12) between each group, as well as nucleotide diversity within groups. In addition, we calculated pairwise FST for each group as1 and π2 is the nucleotide diversity within group 1 and 2, respectively.To determine how spatial sampling schemes impacted our interpretation of the consequences of range contractions, we sampled 50 individuals each from 4–5 groups alive in the final generation from specific locations in the remaining range  and compared them to random samples of 50 individuals from the population prior to the contraction (“ancient”). The fragmentation scenario had 5 groups  because there were no individuals in the center of the range post-contraction. We computed pairwise nucleotide divergence . We then compare the spatial distribution of ancestors in our sampled timestep to a time-slice 50 timesteps prior to the initial contraction. Again, we calculated the genomic contribution to our four post-contraction sampled individuals from all ancestors living during the pre-contraction time-slice and plot their locations in space.Supplementary Information.