Crotalus scutulatus) and the prairie rattlesnake . Specifically, we leveraged established field methods to quantify the hunting behaviors of animals, their prey communities, and the diet of individuals across the hybrid zone in southwestern New Mexico, USA. We found that, even though hybrids had significantly lower body condition indices than snakes from either parental group, hybrids were generally similar to non‐hybrids in hunting behavior, prey encounter rates, and predatory attack and success. We also found that, compared to C. scutulatus, C. viridis was significantly more active while hunting at night and abandoned ambush sites earlier in the morning, and hybrids tended to be more viridis‐like in this respect. Prey availability was similar across the study sites, including within the hybrid zone, with kangaroo rats (Dipodomys spp.) as the most common small mammal, both in habitat surveys and the frequency of encounters with hunting rattlesnakes. Analysis of prey remains in stomachs and feces also showed broad similarity in diets, with all snakes preying primarily on small mammals and secondarily on lizards. Taken together, our results suggest that the significantly lower body condition of hybrids does not appear to be driven by differences in their hunting behavior or diet and may instead relate to metabolic efficiency or other physiological traits we have not yet identified.Predators must contend with numerous challenges to successfully find and subjugate prey. Complex traits related to hunting are partially controlled by a large number of co‐evolved genes, which may be disrupted in hybrids. Accordingly, research on the feeding ecology of animals in hybrid zones has shown that hybrids sometimes exhibit transgressive or novel behaviors, yet for many taxa, empirical studies of predation and diet across hybrid zones are lacking. We undertook the first such field study for a hybrid zone between two snake species, the Mojave rattlesnake  and prairie rattlesnakes . Generally, even though hybrids were in poorer body condition than snakes from either parental lineage, all snakes displayed similar hunting behaviors, diet, and rates of predatory success.Complex traits, such as predatory behaviors, are partially controlled by many co‐evolved gene complexes, which can be disrupted by interspecific hybridization. We quantified the hunting behavior, prey resource base, and diet of snakes dispersed across a hybrid zone between Mojave rattlesnakes ( For predators, their success in acquiring energy depends directly on their ability to locate, subdue, and consume other animals. Anatomical, physiological, and behavioral traits related to these processes are consistent targets of natural selection due to their impacts on a predator's growth, development, and fecundity  had significantly more fish in their diet than parental individuals  represents a unique opportunity to explore the relationship between feeding ecology and hybridization dynamics in snakes Bailey, , 2019. TMost pitvipers are sit‐and‐wait ambush hunters that use chemosensory cues to locate appropriate ambush sites, where they wait for prolonged periods of time in an attempt to strike and envenomate potential prey  and prairie rattlesnakes  are known to hybridize in southwestern New Mexico  zone is located within the Cochise Filter Barrier (CFB), a transitional region between the Chihuahuan and Sonoran deserts frequently implicated in lineage divergence due to climatic and vegetation community shifts induced by glacial cycling  site  was southwest of the hybrid zone and is characterized as a lowland scrub desert macrohabitat. The prairie rattlesnake site  was northeast of the hybrid zone and is dominated by short grass prairie habitat with similar plant species to C. scutulatus habitat, except that Mesquite (Prosopis glandulosa) is less common and is restricted to a riparian corridor bisecting the site. Within the hybrid zone , in the middle of the valley, the macrohabitat transitions from a Creosote (Larrea tridentata)‐dominated lowland desert to an arid short‐grass prairie, similar to the prairie rattlesnake habitat, across a southwest/northeast gradient. Across all three active seasons of data collection, 2019–2021, the average temperature was 28.0°C, ranged from 4.67 to 48.5°C, and had an average total accumulated rainfall between 12.0 and 20.5 cm . For a more detailed description of the study sites, see Maag  to each individual based on species‐typical physical features . These putative designations were later verified/quantified using genetic approaches. At the end of each night, snakes were transported back to a field station in Rodeo, NM. After processing, we released each snake at its exact capture site. Each snake was anesthetized (isoflurane) for processing. While anesthetized, individuals were measured to the nearest mm in snout–vent length (SVL) and body mass to the nearest 0.1 g. Additionally, all snakes were permanently marked with a passive integrated transponder (PIT) tag, sampled for tissue and venom, and measured and photographed for additional data on morphometrics, coloration, and scalation.We collected and sampled all rattlesnakes encountered via surveys within and adjacent to the hybrid zone. Upon capture, we recorded GPS coordinates (precision: ±5 m) and assigned a putative species or hybrid status  radio transmitters  so they could be radio‐tracked in situ for the collection of hunting behavior data. While these snakes were anesthetized, we followed a standard surgical procedure  approach, which was prepared and sequenced by the University of Minnesota Genome Core. For ddRADseq, the restriction enzymes PstI and MspI were used and sequenced on a total of two NextSeq P2 1 × 100 bp runs. In addition to ddRADseq samples, an additional set of 83 samples was prepared for whole‐genome shotgun sequencing using the Illumina Nextera Flex Library Prep kit and sequenced using an Illumina NovaSeq 6000 (with 150 bp paired‐end reads), targeting a per‐sample coverage of ~20×. We used Trimmomatic v0.39  scores for each individual.To generate sequence variant files (VCFs) across individuals, we used GATK v4.1.9.0 with the best practices workflow  as a separate sample when calculating the SMIs. To analyze the relationship between body condition and genetic group, we used a linear model (LM), after verifying normality, with SMI as the dependent variable, and genetic group (determined by its hybrid index) and sex as independent variables. We used these same procedures within the hybrid group  to examine potential relationships between an individual's HI, and its body condition and sex. We also generated scatterplots of HI and SMI to determine if any non‐linear relationships between these variables were present within the hybrid group.Using the mass and SVL data from adult male and non‐pregnant female snakes, we calculated the body condition of adult snakes using the scaled mass index (SMI), as this has been shown to be a more precise indicator of body condition when comparing individuals across different body sizes , we analyzed them independently because they are thought to serve different functions and could potentially be differentially impacted by hybridization. Reviewer scores were averaged to obtain final values; however, when reviewer scores differed in the number or occurrence of snake hunting behaviors, outcomes of prey encounters, or abandonment times, a third individual independently reviewed the video footage. If a mistake was found, then the third reviewer's score was used; otherwise, we averaged the behavioral scores of the third reviewer and the reviewer who had the next closest score to create a final score.To gather data on the hunting behavior and diet of individuals, we used a modified version of the fixed‐field videography approach described in Clark . We locas Figure . Camerass Figure . Chemoses Figure . Mouth gs Figure . AlthougC to select which of the three models best fit the data. We included SMI to account for differences in hunting behaviors based on the body condition of the snakes . When more than one model was within 2 ΔAICC of the top model, we chose only to analyze the simplest model (the model with the fewest number of independent variables). Last, we used either a Bartlett's test, if the data conformed to normality or could be transformed to normality, or a Levene's test (if the data had a non‐Gaussian distribution), to assess whether the variation between the three groups was equal.To analyze the relationship between hunting behavior and genetic group, we used LM when the data could be transformed to conform to a normal distribution and showed no signs of having differences in variances across the genetic linages. When either of these assumptions could not be met, we used a generalized linear model (GLM) framework. The individual's genetic group  was used as the independent variable for all models. For each dependent variable , we created three models with the following fixed factors: genetic group, genetic group + SMI, and genetic group × SMI. We used AICDue to the limited sample of individuals, we did not incorporate sex as a factor in the analysis. Past studies of crotaline hunting behavior indicate that the sexes do not differ in the metrics we calculated .To determine if all snakes encountered the same types of prey, we only used the prey encounter frequencies from known prey items. We then grouped together all known prey types encountered by snakes while hunting into the following five categories: (1) non‐predatory birds; (2) kangaroo rats; (3) all other rodents; (4) lizards; and (5) toads. Due to the nature of the data, we created four GLMs using the beta distribution with a zero‐inflation transformation . Each small mammal captured was identified to at least the genus level, marked with unique ear tags, and measured for mass, body length, hindfoot length, and tail length.We used trapping surveys to characterize the abundance of small mammals, which are the most important class of available prey .We calculated an index of small mammal abundance for each trap night and line (number of unique captures/hours of trapping) for each collection site. The data could not be transformed to conform to normality, so we created three GLMs with the index of abundance as the dependent variable and the following combinations of independent variables: site , site + prey (kangaroo rat or not), and site × prey. We used AICWe conducted visual encounter surveys for herpetofauna (presence and absence of toad and lizard prey species) at all three sites. These surveys were ad hoc, and the effort was broadly similar across the sites. Thus, even though the sampling effort was equivalent between the three collection sites, we consider these comparisons to be tentative.2.7While fixed‐field videography for quantifying feeding ecology works well to eliminate bias due to differential digestion of prey  as a proxy of the HI and considered individuals with a HI between 5% and 95% (rounded to the nearest percent) as hybrids Figures . Based o Figures .3.2C. scutulatus, C. viridis, and hybrids) differed significantly . Overall, individuals of C. scutulatus were in better condition (> SMI) than C. viridis or hybrids , and C. viridis were in better condition (> SMI) than hybrids . Within the hybrid group, the model containing only HI and HI + sex as the predictor variables were the best models to explain the relationship between HI and SMI; therefore, we proceeded with the model containing HI as the sole predictor variable. HI and SMI show no significant relationship to each other within hybrids , and visual inspection of the scatterplot between them indicates no non‐linear patterns are present  of adult snakes in the three genetic groups .Out of the 51 snakes we radio‐tracked, we obtained hunting data through fixed‐field videography on 40 individuals: 16 F = 2.64; df = 2,50; p = .081) and also did not differ in the variance of hunting effort . C. scutulatus exhibited 0.107 ± 0.009 probes per min or one probe every 9.37 min. This was significantly more frequent than probes of C. viridis, which probed at a rate of 0.059 ± 0.006 probes per min or one probe every 16.9 min . The probe rate of hybrid snakes (0.080 ± 0.015 probes per min or one probe every 12.5 min) was intermediate and not significantly different from either C. scutulatus  or C. viridis  than C. viridis , which gaped 0.012 ± 0.002 times per min (once every 87 min). Hybrid snakes gaped 0.017 ± 0.003 times per min or once every 60 min and were not statistically different than the other two groups . We found no difference in the variance of both nocturnal probing and gaping rates between the groups . Daytime probing and mouth gaping rates for all snakes were extremely low compared to nighttime rates , strike rates , or successful strike rates . We also found no differences in the variances of these hunting metrics between genetic groups . Strike success rates were best explained by models containing genetic group or genetic group + SMI. For all three metrics, we report the results from models with genetic group as their sole predictor variable. The three groups were not statistically different in prey encounter rates , but were only significantly different from C. viridis (post‐hoc Tukey: t‐ratio = −3.45 p = .004). C. viridis and hybrids left ambush sites a couple of hours later . However, hybrids were not statistically different in their abandonment time than either C. scutulatus or C. viridis . Variances of abandonment times between the groups were different , but we were not able to differentiate the genetic groups after post‐hoc multiple comparisons and a Holm's adjustment .Individuals of different genetic groups abandoned their hunting sites (ambush coils) at different times during the morning. Because the most informative models for ambush coil abandonment times contained the genetic group and genetic group + SMI of the snakes as the predictor variables, we reported the results of the model containing genetic group as the only predictor variable. The three groups differed in the time of day they abandoned ambush sites to seek thermal refuge , except for birds . All other prey were encountered similarly . Even though birds were frequently recorded with our camera traps, snakes were never observed striking at them, and they were not present in their fecal or gut contents (see below). Accordingly, we do not consider birds to be important prey for the three genetic groups studied at these sites, even though other populations have found birds to be a minor component of the diet of C. viridis  at different rates . Reflecting the predatory encounter rates, kangaroo rats were captured 1.8 times more often than all other rodent species . We did find a significant interaction between the relative abundance of kangaroo rats and the trapping site , while the other two sites exhibited 2–4 times more kangaroo rats than all other rodent species combined .The most informative model of small mammal abundance included collection site, prey category (kangaroo rat species or other rodent species), and their interaction as predictor variables. Small mammal trapping yielded similar abundance of rodent species across the three sites  and 20 juveniles  or lizards . Juveniles fed equally on lizards and mammals as prey , whereas adults shifted to a diet primarily of small mammals .We collected and analyzed fecal samples from a total of 33 adult rattlesnakes (4C. scutulatus), prairie rattlesnakes (C. viridis), and hybrids were remarkably similar, with only minor differences among them. Snakes at the three study sites exhibited comparable rates of hunting behaviors, encountered and successfully subjugated prey at similar rates, and had broadly overlapping diets. However, we found that the body condition index of hybrids was significantly lower than that of individuals of either parental species. This pattern indicates that factors other than differences in hunting behavior or diet may underlie the relatively poorer body condition of hybrid snakes.Overall, the hunting behavior, prey availability, and diet of Mojave rattlesnakes  does vary among taxa. The anatomy of the facial pits affects their sensory fields and causes small differences between species in the spatial resolution of the system  that influence their relative frequency of investigation while in ambush. Although increased movements associated with chemosensory probing might be expected to make individuals less cryptic, we found no evidence of a functional tradeoff associated with higher rates of chemosensory behaviors: active C. scutulatus exhibited similar encounter rates and outcomes with potential prey  attacking kangaroo rats  might reflect an increased reliance on lizards as prey items. The preliminary data from dietary analyses support this pattern  were found to have diets that were more dependent on habitat than ancestry  in different metrics of foraging ecology. Comparable patterns have been reported in other hybrid systems, with hybrids exhibiting similar or intermediate hunting or foraging behaviors when compared to parental individuals ; data curation (lead); formal analysis (lead); funding acquisition ; investigation (lead); methodology (lead); project administration ; resources (lead); software (lead); supervision ; validation (lead); visualization (lead); writing – original draft (lead); writing – review and editing . Yannick Z. Francioli: Data curation (supporting); writing – original draft (supporting); writing – review and editing (supporting). Noelle Shaw: Data curation (supporting); investigation (supporting); writing – review and editing (supporting). Ashana Y. Soni: Data curation (supporting); investigation (supporting); writing – review and editing (supporting). Todd A. Castoe: Writing – original draft (supporting); writing – review and editing (supporting). Gordon W. Schuett: Conceptualization (supporting); methodology (supporting); project administration (supporting); writing – review and editing (supporting). Rulon W. Clark: Conceptualization (supporting); funding acquisition ; investigation (supporting); methodology (supporting); project administration ; supervision ; visualization (supporting); writing – original draft (supporting); writing – review and editing .The authors declare no conflicts of interest.


Depression is associated with frontal alpha asymmetry (FAA) and Psychological Resilience (PR), although in different ways. Only cursory attention has been given to how these three constructs interact despite the possible clinical and research implications of those associations. One limitation of recent research into these associations has been conceptualising PR as a unitary construct, whereas it has been shown to be multi-component. This study investigated the underlying components of PR, their correlations with FAA, and the effect that participants’ depressive status had upon those correlations in a community sample of 54 males and 46 females aged between 18 yr and 75 years. Results confirmed the overall inverse association between total PR and depression for four of the original five PR components and for one of the two components found in this sample. Similarly, there were differences between the ways that FAA and PR components were associated, depending upon the depressive status of participants. Source localisation data indicated that the PR components were not uniformly correlated with alpha activity in the same brain regions. These findings of content, efficacy, and neurophysiological differences between the five components of PR and their associations with FAA argue against consideration of PR as a unitary construct. Depression is a major and widespread disorder  for whicIt has been suggested that PR functions by reducing autonomic responses to stressors , which increases attention towards aversive events, processes potential threats, and prepares the individual for robust withdrawal responses to those threats, and the Behavioural Activation System (BAS), which activates responses to cues of reward and initiates approach-related behaviour . AlthougAlthough these models of brain-behaviour correlates are valuable in understanding how PR interreacts with FAA and depression, previous studies of PR-related variables and functioning have defined PR as a global psychological construct that is measured (i) on the basis of a single score from a self-report inventory, (ii) the presence/absence of a stress-related disorder, or (iii) a dichotomous classification of resilience on some other basis. Although they are common approaches to the definition of an independent variable, these methods suffer from two major limitations in terms of their ability to produce research findings of interest.First, the dichotomisation of a variable such as PR reduces the actual variability in participants’ responses to a simple yes/no or high/low dichotomy, with attendant limitations upon the available statistical procedures that may be used to analyse such data . Simply Second, when treated as a unitary construct , the multifactorial nature of PR-related behaviours is ignored. For example, one of the most commonly used scales to measure PR is the 25-item Connor–Davidson Resilience Scale (CDRISC) . The CDRThus, examination of PR at the factor/component/behaviour level is important because the five factors described by the CDRISC authors represent quite different strategies for dealing with stressful events. That is, trusting one’s own instincts is diametrically opposed to spiritual influences, and having a sense of control over events is a different strategy to positively accepting change. These different underlying components of the CDRISC may represent different neurophysiological pathways to PR-related behaviour, perhaps also linked with the BAS or BIS; coalescing them all into a single PR total score prevents more precise consideration of the nature of PR, PR-related behaviour, and their associations with neurophysiological variables.Therefore, to further investigate the neurophysiological substrates of PR and to test the relevance of the FAA model of approach/withdrawal behaviour  to PR, this study examined the association between PR and FAA at the global PR level , and also for the components of PR . These components of PR were defined in two ways: first, by the five factors reported by the CDRISC authors , and secM age = 32.53 yr, SD = 14.13 yr) recruited from the New England region of New South Wales, Australia, via an advertisement for participants for “a study into how you think”. There were 54 males and 46 females aged between 18 and 75 years, with the age range breakdown of 18–30 yr: 54.5% males, 62.5% females; 35–50 yr: 29.6% males, 25.0% females; and 51 yr and over: 15.8% males, 12.5% females. None of these participants had a previous medical history of severe physical brain injury, brain surgery, or history of epilepsy, seizure disorder, or claustrophobia . Because 61% to 70% of left-handed people also have left hemispheric dominance [The sample was drawn from volunteers aged 18 years or more  , which cParticipants’ depressive status was measured by the Zung Self-Rating Depression Scale (SDS) , composeQuik-Cap, with a focus on five pairs of frontal sites , using the average of the twin mastoids (A1 + A2) as the recording reference. A Nuamps digital EEG amplifier  was used to collect continuous EEG measurements during 3-min Eyes Opened and 3-min Eyes Closed resting conditions. EOG data were recorded using electrodes at VEOR and HEOL below the right eye, and all dropdown electrode sites were cleaned with an alcohol swab and Nuprep gel so that all electrode impedances were < 5 KΩ. Participants were seated in an experimental booth while their EEG data were collected. EEG signals were recorded using the Curry 7 software at a sampling rate of 1 KHz, with a bandpass of DC to 250 Hz.EEG data were collected from a 40-channel Data were re-referenced to a common average, then processed using a low filter (high pass), frequency of 1 Hz and a slope of 2 Hz; a high filter (low pass) with frequency of 30 Hz and a slope of 8 Hz; a notch filter of 50 Hz  with a slope of 1.5 Hz; and a band stop filter of frequency of 50 Hz (Harmonics) with a width of 10 Hz and slope of 5 Hz. A Hann window with a 10% width to prevent data loss was used to filter the data, which were then visually examined to identify artefacts , all of which were removed from the data record. Bad block and eye blink detection (using the magnitude of eye blink deflections as a set threshold criterion to detect artefacts) was undertaken by three automated methods  to produce clean EEG data.eLORETA [Back-to-back epochs of 2 s duration were then created from the cleaned EEG data. Most participants had over 90% usable artefact-free epochs for both Eyes Opened and Eyes Closed conditions. Spectral analysis was performed on the generated epochs (for both conditions for each participant) with a Fast Fourier Transformation (FFT) to calculate the power spectra. The power values obtained from FFT were averaged across the 2-s EEG epochs. From this process, the total FAA power within the alpha (8–13 Hz) frequency range was obtained for each participant by subtracting the left hemisphere site alpha values from the right hemisphere site alpha values  to produce five sets of FAA data. These data were extracted and transferred to MATLAB, EEGLAB, and SPSS to calculate the correlations between CDRISC total score, factor scores, and FAA. Data from EEG sites were analysed using source localisation with eLORETA ,52, whicThere is some discussion in the EEG literature regarding the relative value of alpha wave data from eyes open versus eyes closed conditions, with evidence of differing topography and power values across these two conditions ,54, prinParticipants read an Explanatory Statement and signed a Consent Form a background questionnaire  and completed the CDRISC and SDS. Participants’ scalps were then prepared, and the electrode cap was fitted. Headphones were placed on participants so as to minimise the effect of external stimuli when instructions were given. Following 15 min of sitting still (adaptation), the audio-recorded experimental protocol  was presented via headphones to ensure consistency across participants. Ethics approval was received from the Human Research Ethics Committee of the University of New England, Australia .Mean, standard deviation, standard error, and normality data were produced for the CDRISC and SDS. Internal consistency for the CDRISC and SDS were determined via Cronbach’s alpha. EEG data were tested for normality and found to be skewed. Although this has sometimes been dealt with by log transformation, there are inherent drawbacks to applying that process because it can hinder the interpretation of data, resulting in the recommendation that researchers should instead use the untransformed data with statistical procedures that are robust to non-normality ; in thiseLORET [Factor analysis was undertaken to identify the components of the CDRISC in this sample. The five original CDRISC factors were calculated from the raw scores on relevant items as stipulated by the CDRISC authors , and theeLORET  in orderp-value” before undertaking significance testing [p < .05 criterion or were of sufficient strength to qualify under Cohen’s [There is some disagreement regarding the need to make automatic corrections to alpha values when undertaking multiple tests of association , princip testing  (p. 1).  Cohen’s  definiti Cohen’s .ρ = .091, p = .366, or SDS total score ρ = .022, p = .829, or between the age of participants and CDRISC ρ = .060, p = .553 or SDS ρ = .055, p = .584, allowing the data to be analysed without this potential confound.ρ = −.744, p < .001 (a large effect size) [F = .447, p = .506, but the clinically depressed sample had significantly higher SDS scores  and significantly lower CDRISC  scores than the non-clinically depressed participants  = 273,729, p < .001, ηp2 = .736; CDRISC M = 99.343, SD = 10.409: F = 64.336, p < .001, ηp2 = .396), both of which were large effect sizes [As expected, CDRISC total score was significantly inversely correlated with SDS total score ct size) . By applct size)  (p. 335)p < .001). By reference to eigenvalues > 1.0, the scree plot, and confirmed by parallel analysis, a two-factor solution was obtained. It should be noted that Connor and Davidson [General resilience, was very large, including all CDRISC items except items 3, 9, and 20, and accounting for 44.925% of the variance; Factor 2  was named Reliance on others and accounted for a further 7.915% of the variance. These factors were only moderately correlated (r = .218), suggestive of orthogonality, and allowing either Varimax or Oblimin rotation to be used; both of these procedures produced identical simple solutions. The means (SD) for these two factors are shown in the lowest two rows of representing Spiritual influences, and the current sample factor 2 Reliance on others.The sample means (SD) of the five factors of the CDRISC described by the scale The sample means (SD) of the five factors of the CDRISC described by the scale authors  are showDavidson  reportedDavidson . From thp < .05 or r ≥ .3), four of the five original CDRISC factors and one of the two factors found in the current study had significant inverse associations with total SDS for both the depressed and non-depressed subgroups. The fifth original CDRISC factor (not significantly associated with SDS score) contained two CDRISC items . These two CDRISC items were also included in the second factor from the current study, plus item 20 (I have to act on a hunch). These PR-related behaviours do not appear to assist in reducing the likelihood of developing depression.These results are relevant to the total sample but do not provide any insights into the scores of the clinically depressed versus not-clinically depressed subgroups, which may assist in understanding the associations between CDRISC factors, depression, and FAA. As a first step in that analysis, direct correlation coefficients between the CDRISC scores and their FAA data, but those participants whose SDS scores did not reach the level of severity stipulated by Zung [inverse correlation coefficients between their CDRISC scores and FAA data on that component of the CDRISC that measured participants’ control.The results of the data analysis aimed at understanding the associations between FAA data and the total CDRISC and its factors are presented in  by Zung  had unifTo understand the meaning behind these inverse vs. direct correlations, because the CDRISC scores are always positive, an inverse correlation could only occur if the FAA value was negative. The FAA values were obtained by subtracting the left hemisphere site alpha values from the right hemisphere site alpha values  so that a negative value indicated that the left hemisphere had higher alpha activity than the right hemisphere, represented using the statement: Lα > Rα. When submitted to Spearman correlational analysis, this kind of relative brain site alpha activity produced inverse correlation coefficients between FAA and the CDRISC scores, as was found for the not clinically depressed subgroup. By contrast, the clinically depressed subgroup  had higher alpha activity in their right hemisphere than in their left hemisphere Rα > Lα.Four of the five FAA pairs  showed meaningful correlations with some of the CDRISC factors. Although four of the five original CDRISC factors were found to have at least some meaningful correlations with some FAA data, whether from eyes-open or eyes-closed conditions for either or both of the not-depressed and depressed subgroups, those associations were not uniformly spread across the entire frontal region, but were indicative of specific frontal regional activity being associated with specific aspects of PR. This specificity is reflected in the different directions of the correlations for not-depressed versus depressed subgroups described above.For the two-factor solution found in the current sample, factor 2 (Reliance on others) appears to be very similar to the original factor 5, both in terms of the absence of any significant correlations with the SDS scores  and alsoFinally, when considering these data at the FAA level, there were 10 meaningful correlations under the eyes open condition, but only two under the eyes closed condition, suggesting that the eyes open/closed variable does have some effect on the associations between FAA and CDRISC factors. That effect is no doubt due to the alpha wave activity generated rather than the CDRISC factors and will be discussed in more detail below.eLORETA [p < .05), the results showed broadly consistent results indicating stronger alpha power in the frontal right hemisphere. To avoid needless repetition, only the relevant results from analyses with significant Spearman correlations for original factor scores in the eyes-open condition from These data regarding FAA are informative at a gross scalp region level but do not provide insights into the specific areas of the brain that were associated with CDRISC factor scores. To examine those associations, the regression analyses on the relationship between CDRISC scores and alpha band power (8–13 Hz) were performed using source localisation data via eLORETA . Whilst CDRISC Original Factor 1: While the frontal right hemisphere showed broadly consistent increases in alpha power as the factor score increased, the frontal left hemisphere showed comparatively lower increases in alpha power, with a small decrease observed in the left medial frontal gyrus (Brodmann area (BA) 9); see CDRISC Original Factor 2: Similar to the results regarding factor 1, the frontal right hemisphere showed broadly consistent increases in alpha power as the factor score increased, while a localised fall in alpha power was observed in the left medial frontal gyrus (BA 9); see CDRISC Original Factor 4: Consistent rises and falls in regression coefficients were found across each frontal hemisphere, with the exception of a 4 cm strip of grey matter along the middle frontal gyrus (BA 11) and inferior frontal gyrus (BA 47), which produced a negative regression coefficient in the left hemisphere and a positive coefficient in the right hemisphere; see CDRISC Original Factor 5: This analysis showed a consistent negative relationship between factor 5 and alpha band power across both frontal hemispheres, with a localised positive regression coefficient in the left anterior cingulate (BA 32); see By applying a non-dichotomous metric of total PR score from the CDRISC, plus an examination of the underlying components of that construct and instrument, several confirmatory and extending behavioural findings emerged from this study of the neurophysiological correlates of PR. First, the hypothesis that global PR would be inversely associated with depression was supported. Second, the finding that only Factors 1 to 4 of the CDRISC, and Factor 1 from the current sample, had significant inverse correlations with SDS score suggests that the CDRISC contains some items that are not, on the basis of these data, robust protectors against depression . Generally speaking, when participants sought to rely on others to cope with stressful events, that strategy was not as effective in avoiding depression compared to taking some more active- and self-belief-based path to deal with stress. This lack of internal consistency in terms of PR’s effectiveness in helping participants avoid or reduce depression suggests that PR ought not to be considered a unitary construct but rather a set of (sometimes conflicting) components, at least in the CDRISC.The neurophysiological aspects of PR were the major focus of this investigation, and the results reported above extend those previously found, such as Bae et al.  and Ma eFor Factor 5 D, the coThese initial findings are limited in scope but do provide a firm basis for considering the PR construct as composed of different components that are not all equally strongly inversely associated with depression. In fact, CDRISC Factor 5 does not fulfil this task significantly and may be questioned as to its justification within the overall PR construct. Secondly, the heterogeneity of the PR construct, as measured via the five components of the CDRISC, received initial support from the different neurocognitive manifestations shown in Limitations in this study included the focus on frontal alpha wave activity. Although this was justified because the present study was aimed at testing the FAA-PR hypothesis on the basis of the previous literature regarding FAA depression, an extension of the data to include other brain regions and brain wave frequencies would enhance understanding of the neurobiological underpinnings of PR. The participants were all volunteers and, despite there being a reasonable proportion of participants who met the criteria for clinically significant depression, did not include a clinically diagnosed subsample, thus limiting the generalisation of these data to that subgroup. Data were cross-sectional, and no account can be given of fluctuations in the associations between FAA and CDRISC factors over time or under stressful conditions--these are promising fields for future research. Although not a limitation per se, the difference in results between eyes open and eyes closed conditions suggests the need to further investigate the effects of environmental visual stimulation upon alpha wave data in experiments such as this. As noted in the Methods, there is other evidence of differing power values and topography across these two conditions ,54,55, acorpus and extend it by providing a new understanding of the specific components of PR and how these may be associated with particular brain region activity. The major outcome of this study  holds major implications for research and clinical settings where PR is usually assumed to be homogeneous.Although PR was originally defined in psychological and behavioural terms, recent research has focussed on using EEG and MRI to define and describe the neurobiological processes that underlie resilient behaviour ,75,76. T


Plasmodium spp., low haemoglobin levels or low vitamin D levels. None of these hypotheses have been tested genetically. Here, I calculated different genetic scores to test each hypothesis. Additionally, I calculated a genetic score of bone mineral density as it is a phenotype that seems to be selected in ancient Europeans. I apply these genetic scores on 80 ancient samples, 33 with diagnosed PH. The results seem to suggest anaemia and low bone mineral density as the main cause for this disease. Additionally, Neolithic individuals show the lowest genetic risk score for bone mineral density of all other periods tested here, which may explain the highest prevalence of the porotic hyperostosis during this age.Porotic hyperostosis (PH) is a disease that had high prevalence during the Neolithic. Several hypotheses have been suggested to explain the origin of the disease, such as an iron deficiency diet, low B12 intake, malaria caused by  Due to the nature of ancient remains, bone disorders, such as bone cancer, rickets or bone traumatism, are the most studied in paleopathology. One of the best claimed diseases affecting past populations is Porotic hyperostosis (PH), a skeletal disorder characterised by bony lesions on the bones of the skull due to an expansion of the cranial diploë3  levels during the last thousand years19, which may lead to particularly thin bones in some individuals.Paleopathology is the study of disease in ancient organisms. Unsurprisingly, the majority of studies focus on past pathologies affecting ancient humansoë3 Fig. . This coHomo species21, connections among ancient and modern individuals22 and the selective pressures of particular human traits23. While numerous studies focused on the implication of breeding with Neanderthals and Denisovans on the development of different diseases in modern individuals24, the contribution of ancient DNA to paleopathology has mainly focused on infectious diseases, such as confirming Yersinia pestis as the pathogenic agent of ancient plagues25, comparing the genes related to pathogenic resistance in ancient populations26, determining the oral and microbiome of ancient individuals27, and studying the prevalence of malaria in ancient times28. Yet, ancient DNA still has a huge potential to elucidate the genetic architecture of diseases affecting ancient populations29. With this idea in mind, I calculated different genetic scores using hundreds of SNPs related to specific phenotypes and applied it to 80 ancient genomes for which we can differentiate if they were affected or not by PH. These genetic scores were then used to test for the different hypothesis proposed for the origin of PH  is the amount of minerals  deposited in the bones. Many factors influence the levels of BMD. It can be influenced by environmental cues like the levels of diary activity or the diet, but also by genetic factors32. While the main evolutionary cause for this phenomenon remains obscure, low melanin production has been related to increased levels of vitamin D in blood. Vitamin D is synthesised by the influence of UV-radiation from the sun, and skin tones with higher melanin block more of this UV-radiation32. Vitamin D is needed to absorb calcium in the gut and is fundamental for the development of healthy immune and skeletal systems, including normal levels of mineral deposition in the bones32.Europeans evolved low levels of melanin in the skin cells. Ancient DNA studies suggest that this selection increased after the Agricultural Revolution32, early farmers may have had lower vitamin D levels than recent populations  leading to a lower capacity to synthesise vitamin D. This may explain why the prevalence of PH was higher during the Neolithic than during recent times. To assess this, I used a broad dataset of SNPs related to skin pigmentation (that has previously applied to ancient DNA studies32) to generate a genetic score of skin pigmentation in the ancient samples. 173 of 175 SNPs related to skin pigmentation were recovered in the dataset used here . It also can explain why PH was more common in the Neolithic than in more recent times  as the number of domesticated animal species increased and were included in the diet. This could have triggered changes in vitamin B12 metabolism. Here, I used a genetic score with four SNPs37 related to vitamin B12 metabolism that can be recovered in the database of ancient samples used here 41. Five SNPs could be recovered in the ancient dataset, one of them affecting the gene for the β globin  high bone mineral density, (2) darker skin pigmentation, (3) high iron levels, (4) vitamin B12 levels and (4) high haemoglobin levels  and all markers with a MAF higher than 0.05 were removed. Finally, 772,964 SNPs were left for the PCA analyses.A Principal Component Analysis (PCA) has been generated with PLINK48. Wilcoxon Mann Whitney test was used to analyse differences in individuals with and without porotic hyperostosis among the different genetic scores. Pearson correlations were used to study differences among the genetic scores of BMD levels through time.All statistical analyses were conducted in R Studio49 and the credits correspond to Paula Roig Ferrando. Other figures were conducted in RStudio48.Figure When comparing the individuals with and without PH, I detected significant statistical differences for the genetic risk scores of BMD see Fig.  and Haem52. A possible explanation for this is that anaemia caused by low haemoglobin levels may correlate with a genetically porous bone to allow for an expansion of the diplöe.These results do not support the hypothesis that PH was caused by low vitamin D levels in darker individuals or changes in the iron or in the vitamin B12 metabolism. Instead, the results support the hypothesis that anaemia caused by low haemoglobin levels could be responsible for PH, together with a genetic architecture for low bone mineral density. Interestingly, low BMD correlates with low haemoglobin levelsThere is the possibility that PH and unaffected individuals belong to two different populations, thus sharing different alleles (including those related to BMD and haemoglobin levels). To discard this possibility I conducted a Principal Component Analysis see Fig. ”. The reTo understand what could have caused such prevalence of PH in the Neolithic, I calculate the mean of the genetic risk scores by time periods  Table . The mea11.This last result is confirmed by studying the genetic risk scores of 308 ancient samples  see “” through19. As selection for light skin increased drastically after the Neolithic in Europeans, low BMD levels may have been an adaptation to low UV-radiation in the European latitudes. In this line, I observed a statistical correlation among the genetic risk scores for skin pigmentation and BMD in ancient Mesolithic and Palaeolithic individuals . Selection for light skin was stronger after the Neolithic, so Palaeolothic and Mesolithic individuals had darker skin pigmentation. A still answered question is how these ancient Europeans maintained a healthy skeletal system in the high latitudes of Europe with low UV-radiation if they had high melanin production. Here I suggest that the observed decrease in the BMD genetic score through Palaeolithic and Mesolithic times may be an adaptation to this low vitamin D production.Porotic hyperostosis had a higher prevalence in ancient times than nowadays, specifically during the NeolithicSupplementary Tables.


Camellia sinensis) to the United States since the 1850s have resulted in US tea germplasm that are currently poorly characterized. To resolve questions concerning the relatedness and regional adaptability of US tea germplasm, 32 domestic individuals were evaluated using 10 InDel markers, and compared with a background population of 30 named and registered Chinese varieties of tea. The marker data were analyzed via a neighbor-joining cladistic tree derived from Nei’s genetic distance, STRUCTURE, and Discriminant Analysis of Principal Components, which revealed four genetic groups. Nineteen individuals selected from the four groups were assessed for seven leaf traits, two floral descriptors, and leaf yield, to identify plants best adapted to Florida field conditions. Our analyses compared with available historical records led us to estimate the most likely provenance of some of the US individuals, to precisely identify tea plant material and to choose most diverse accessions for breeding tea improved for adaptability, yield and quality.Multiple introductions of tea ( Its popularity is due to both cultural precedent and documented health benefits  and Assam-type, Camellia sinensis var. assamica (CSA). However, cross pollination followed by continuous selection has resulted in many varieties exhibiting varying levels of admixture between the two. Generally, CSS is characterized by small leaves and a spreading habit, while CSA has larger leaves and a semi-arboreal habit  and quantified using NanoDrop . Concentration of genomic DNA was adjusted to 10 ng.µl2.5Fst) for 10 InDels were calculated in GenAlEx (k was determined using the Evanno method (via Structure Harvester (Expected heterozygosity (He), observed heterozygosity (Ho) and fixation index  to 158.5 g/plant/year (‘Miwa’s Garden’) Table 1.3.2Multiple morphological traits varied between named groups and some varied among the individual plants within a named group Figure 13.3Timelapse photography revealed that tea flowers largely began anthesis in the early- to mid-morning, typically commencing between 5:00 and 11:00 am Figure 23.4Fst) was measured between the US individuals as one population (n=32) and the Chinese individuals as a second population (n=30). At all loci, Fst was <0.05, indicating that there is not sufficient genetic structure to consider the US and Chinese individuals as separate populations.Analysis of 10 InDel markers across 62 individuals revealed a total of 96 unique alleles Table 4.3.53.5.1The NJ tree revealed four distinct clusters Figure 33.5.2k indicated k=4. Proximity between individuals seen in the NJ tree are supported by this analysis. ‘Big Leaf’ and ‘Large Leaf’ derive most of their ancestry from a single source, Group 1. ‘Small Leaf 3’ and ‘MS Oolong’ appear to share most of their ancestry from a second source, Group 2. Among the Chinese background population, ‘Tieguanyin’ and ‘Zimudan,’ both from Fujian province, show the highest proportion of ancestry from this group.STRUCTURE analysis indicated 4 ancestral populations Figure 4Seed lot-derived named groups ‘Fairhope,’ and ‘Georgian’ vary in their ancestral proportions more than ‘Small Leaf,’ also a seed lot-derived named group. ‘Baihaozhao,’ ‘Echa 1,’ ‘Fudingdabai,’ ‘Chuanmu 28,’ ‘Zhenong,’ ‘Anjibaicha,’ ‘Fuzao 2,’ and ‘Bedou,’ which appear together in one node on the NJ tree, are shown in series on the Q-plot with continuous decrease in ancestry from cluster 3 and increasing ancestry from cluster 4 Figure 43.5.3Principal components analysis anterior to DAPC indicated 4 groups based on the Bayesian information criterion (BIC) Figure 53.5.4Clusters identified by the Neighbor-joining method Figure 34The plants included in this study are derived from clonal propagation, selected cuttings from seed-derived plants, or from seed lots . Levels Though it is a woody perennial crop, tea is not cultivated for a mast of fruit or nuts, but rather for vegetative growth. For this crop, yield and biomass accumulation are closely related parameters , with hiThe 19 field-grown individuals used in this study were selected based on yield, and all three analyses were able to distinguish at least some high- versus low-yielding genotypes. Cluster analysis of these field-grown accessions may indicate genetic variations related to adaptability in Florida conditions. Among the low-performing named groups, ‘Georgian’ and ‘China Seed,’ occurrence of a few high-yielding individuals may indicate genetic attributes that enable them to perform well despite the majority of the named group showing poor adaptability to the region. They warrant further investigation to preserve advantageous genetic traits that may be present in these individuals and missing from others in the named group. All four individuals representing ‘Big Leaf’ and ‘Large Leaf’ grouped together, which is unsurprising given the other results presented in this study. Since individuals within these named groups show low genetic diversity, poor performance from low yielding ‘Big Leaf’ and ‘Large Leaf’ individuals can possibly be explained by competition, micro-environmental conditions, or patchy distribution of pests and diseases within the field. In the NJ tree of the full 62-member population, the high- and median-yielding ‘Fairhope’ and ‘Miwa’s Garden’ individuals clustered together. The low-yielding individuals from ‘Fairhope’ and ‘Miwa’s Garden’ appeared in a distant cluster from the other individuals in their named group. This division was preserved for ‘Fairhope’ in the population structure analysis, and for ‘Miwa’s Garden’ in the DAPC.Seed lot-derived named groups ‘Fairhope,’ ‘Small Leaf,’ and ‘Miwa’s Garden’ showed higher genetic diversity within the groups, as well as higher variance in yields. As a self-incompatible species with long-term allogamy, the tea genome shows high heterozygosity and diversity . Even wiThe cluster analysis using the NJ tree may be used to direct choices in breeding, especially of controlled crosses. In an outcrossing organism, inbreeding depression is mitigated by self-incompatibility. Individuals that are closely related may fail to produce viable offspring, or, if offspring survive past the juvenile stage, they may be weak and underperforming. Seed lot-derived individuals from ‘China Seed’ do not show the high variance of yield seen in other seed lot-derived named groups ‘Fairhope’ and ‘Small Leaf.’ Both individuals from ‘China Seed’ clustered nearby each other on the cladistic analysis of genetic distance, indicating low genetic distance, or high genetic similarity, between those individuals. This suggests that ‘China Seed’ has lower genetic variability compared to ‘Fairhope’ and ‘Small Leaf.’ ‘Fairhope,’ ‘Small Leaf,’ ‘Miwa’s Garden,’ and ‘Georgian,’ all seed lot-derived named groups, showed more genetic dissimilarity between individuals included in the study, suggesting these named groups will show more diversity in field production settings and could be useful to identify and select superior performers.Fst scores for each InDel locus between US individuals and the Chinese background population . ‘Red Leaf,’ is distinguished morphologically by the red color of new shoots and pink flowers . Kitamurth century, about 50 years after the establishment of Pinehurst tea plantation. Japanese tea varieties from the Shizuoka and Uji regions, the two main sites of tea’s introduction into Japan from China around the 13th century, were likely sourced from distinct populations within China . There is a stark division in ancestry between ‘MS Oolong’ and ‘Small Leaf 3’ compared to ‘Small Leaf 1’ and Small Leaf 2,’ the latter of which share more ancestry with individuals from northeast China Figure 3in China . Additioin China . Howeverk. While PCA helps to interpret total genetic variation, DAPC is more suited for analyzing variance among groups, while minimizing within-group variation. (DAPC, by minimizing variation within groups, can be useful for balancing breeding decisions based on NJ or similar algorithms, which are designed to show genetic distance. DAPC is used in this study instead of another commonly used measure of genetic variation, the PCA. DAPC does in fact begin by transforming the data using PCA, which allows for an informed selection of the number of groups using the BIC to determine the best riation. . DAPC isriation. Figure 6The investigation into timing and duration of anthesis presents opportunities to cross pairs that would otherwise be temporally isolated. Finally, it should be noted that the breeding recommendations presented here are based on yield and do not take into account questions of quality. Further studies examining the tea produced from named groups and individuals under Florida field conditions are required to investigate horticultural and genetic effects on quality of Florida-grown tea.As an allogamous plant with a highly heterozygous genome and broad geographic range of cultivation, the potential for tea germplasm to possess adaptations to specific environmental conditions is high. Inferring regional suitability may be possible using genetic analysis and observations of regional viability. ‘Chestnut Hill’ was selected from Morris Arboretum near Philadelphia, which is USDA Plant Hardiness Zone 7a and experiences winter low temperatures from -17.8 to -15°C . This spThe poor yield performance of ‘Assamica’ in Florida field conditions is worth noting, especially because this named group was predicted to be one of the better performers for this area due to CSA being mostly cultivated in the relatively warmer tea growing regions . KnowingBased on yield, ‘Fairhope’ individuals perform well in Florida conditions, as do ‘Miwa’s Garden,’ ‘Big Leaf’ and ‘Small Leaf.’ The polyploidy of ‘Big Leaf’ and ‘Large Leaf’ is consistent with broader environmental adaptability . One of The original contributions presented in the study are included in the article/BR and BSR designed the outline of this study and collected the resources needed. CC completed the experimental research, computational data analyses and prepared the manuscript. All authors contributed to the article and approved the submitted version.


Durum wheat is one of the most important crops, especially in the Mediterranean region. Insight into the genetic diversity of germplasm can improve the breeding program management in various traits. This study was done using single nucleotide polymorphisms (SNP) markers to characterize the genetic distinctiveness and differentiation of tetraploid wheat landraces collected from nine European and Asian countries. A sum of 23,334 polymorphic SNPs was detected in 126 tetraploid wheat landraces in relation to the reference genome.K = 2). Evaluating the principal coordinate analysis (PCoA) and weighted pair-group method using arithmetic averages (WPGMA) clustering results demonstrated that landraces (99.2%) are categorized into one of the two chief subpopulations. Therefore, the grouping pattern did not clearly show the presence of a clear pattern of relationships between genetic diversity and their geographical derivation. Part of this result could be due to the historical exchange between different germplasms. Although the result did not separate landraces based on their region of origin, the landraces collected from Iran were classified into the same group and cluster. Analysis of molecular variance (AMOVA) also confirmed the results of population structure. Finally, Durum wheat landraces in some countries, including Turkey, Russia, Ukraine, and Afghanistan, were highly diverse, while others, including Iran and China, were low-diversity.The number of identified SNPs was 11,613 and 11,721 in A and B genomes, respectively. The highest and lowest diversity was on 6B and 6 A chromosomes, respectively. Structure analysis classified the landraces into two distinct subpopulations (The recent study concluded that the 126 tetraploid wheat genotypes and their GBS-SNP markers are very appropriate for quantitative trait loci (QTLs) mapping and genome-wide association studies (GWAS). The core collection comprises two distinct subpopulations. Subpopulation II genotypes are the most diverse genotypes, and if they possess desired traits, they may be used in future breeding programs. The degree of diversity in the landraces of countries can provide the ground for the improvement of new cultivars with international cooperation. linkage disequilibrium (LD) hotspot distribution across the genome was investigated, which provides useful information about the genomic regions that contain intriguing genes.The online version contains supplementary material available at 10.1186/s12864-023-09768-6. Triticum timopheevii, T. araraticum, T. dicoccoides, T. militinae, T. dicoccum, T. carthlicum, T. polonicum, T. ispahanicum, T. turgidum, T. karamyschevii, T. turanicum, T. aethiopicum, and T. durum  were utilized to assess the structure of the tetraploid wheat diversity and classify subgroups (K). The evaluated log-likelihood [LnP(D)] showed a gradually increasing value corresponding to the increase of K Fig. a and theCluster analysis was also performed using WPGMA to construct a dendrogram from a pairwise similarity matrix Fig. . The WPGThe results of PCoA were adopted with WPGMA-based clustering results which divided the 126 landraces into two groups Fig. . The firThe AMOVA was performed based on both different origins and identified two subpopulations in structure analysis Table . The AMOa) and effective (Ne) allele values were 1.755 and 1.599, respectively (Table a (1.093) and Ne (1.071) were observed in the Iranian group. The Shannon’s diversity index (I), which varied from 0.06 (Iran group) to 0.53 (Ukraine group). A comparable and close arrangement was seen for expected heterozygosity  that ranged from 0.041 (Iran group) to 0.368 (Ukraine group). The highest local inbreeding coefficient (F) was found in Ukraine (0.928) and Afghanistan groups (0.925), while the Iran group showed the lowest value of F (-0.362). The percentage of polymorphic loci (PPL) per group varied from 9.66% (Iran group) to 99.96% (Turkey group). Genetic diversity analysis based on the result of structure analysis illustrated that structure group I has a lower value of Na, Ne, I, He, F, and PPL in comparison to structure group II.Investigated genetic variation within a population based on country grouping demonstrated that average observed . The membership coefficient of 97% (122 out of 126) of samples was higher than 0.7. The multivariate methods including WPGMA clustering, PCoA, and Bayesian model-based clustering approach realized in STRUCTURE software were successful to assign landraces (99.2%) to one of these two primary subpopulations. However, as in the studies of Marzang et al.  and SalsIn clustering based on countries of origin, it was observed that Iran is completely different from the others and showed lower gene flow and higher genetic differentiation from other countries. Baloch et al.  also revAMOVA revealed that the two subpopulations had highly significant genetic diversity. Due to the selective breeding of specific traits that wheat breeders have done in different countries, subpopulations can show high levels of genetic diversity. Additionally, each subpopulation possessed wheat genotypes from different countries. A low genetic diversity in the populations might be attributed to the spread of wheat germplasm between different regions. As a result, selecting genotypes as parents, for the purpose of improving target traits, from the same subpopulation may be more effective than selecting genotypes from different subpopulations. The incorporation of haplotypes from different founder populations may require crosses between genotypes from different subpopulations. Both winter wheat and synthetic wheat genotypes had high genetic diversity within subpopulations but low genetic diversity among subpopulations , 54. TheIt is essential to determine the magnitude and decay of LDs as they affect the SNP markers and the resolution of association mapping necessary to conduct association studies . There iEstimation of genetic heterogeneity plays a vital role in plant breeding programs. The current study provides a detailed research-based report of the genetic diversity of tetraploid wheat landraces gathered from various countries. The results indicated that there is a lower association between the geographical origins of tetraploid wheat landraces and their genetic differentiation. Therefore, determined genetic diversity and differentiation of durum wheat materials obtained from diverse regions could provide valuable information for expanding the necessary genetic variation of breeding materials, facilitating and more efficient application of examined wheat resources as selected parental to introduce high-yielding durum wheat genotypes via breeding programs, and associated mapping investigations.A 126 tetraploid wheat landraces set (Supplementary 3) including accessions from Turkey (n = 59), Russia (n = 37), Azerbaijan (n = 7), Kazakhstan (n = 5), Ukraine (n = 5), Armenia (n = 5), Afghanistan (n = 3), China (n = 3), and Iran (n = 2) were used in current study. These samples were kindly provided by the Dryland Agricultural Research Sub-Institute (DARSI), Agricultural Research, Education and Extension Organization (AREEO), Kermanshah, Iran.Genomic DNA of samples were extracted using modified CTAB procedure  from 2-wThe polymorphic information content (PIC), minor allele frequency (MAF), percentage of heterozygosity, and gene diversity of all 23,334 SNP markers were calculated using PowerMarker software V 3.25 . To calcij and Pik are the frequencies of jth and kth alleles for marker i, respectively.Where PSTRUCTURE version 2.3.4 was also used for analyzing the structure of the population based on Bayesian cluster analysis  while alGenetic variation assessment was carried out with DARwin version 6.010 software  based on2). In addition, LD decay was calculated for each chromosome and sub-genome based on the theoretical expectation of r2  using the full matrix option. Due to its less sensitivity to marginal allele frequencies, the pairwise LD was calculated using the squared correlation coefficient of alleles (r r2 (see  for detaThe number of haplotype blocks in each genome was determined using Haploview 4.2 software on the chromosome with the highest significant LD percentage . This waBelow is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Supplementary Material 3Supplementary Material 4


Rhodiola rosea L. is a vulnerable species in the Altai Republic (AR) and Russia in general. For the first time on the territory of AR, studies of the adaptive capabilities of the species and genetic differentiation using ISSR markers were carried out in seven cenopopulations (CP) of R. rosea in 2018 and 2020. The research was founded on the notion of conducting a comparative analysis of the morphogenetic structure of Rhodiola rosea populations in various ecological and geographical conditions of AR. The aim of this work is to evaluate the variability of morphometric traits of sexually mature living female R. rosea plants and to conduct a comparative analysis of genetic variability in cenopopulations (CP) both under undisturbed conditions and under stressful conditions of anthropogenic impact (grazing). Of the 8 primers used, HB12 turned out to be the most informative. The percentage of polymorphic loci in the populations between 0 and 88%. Two populations, located in favorable conditions at relatively low absolute altitudes (2000 m above sea level) (masl) in the undisturbed habitats of the Katun and Altai reserves of AR, were characterized by higher polymorphism. The share of polymorphic loci reached 80%. According to the analysis of statistical data, the highest values of morphometric parameters of the aerial parts of R. rosea plants and the highest potential seed productivity were also recorded in these habitats. Representatives of two high-mountain CPs (2400–2500 masl) in the Sailyugemsky National Park (SNP) were characterized by the lowest genetic polymorphism. Their genetic structure is the most homogeneous, since we have not found polymorphic loci. Due to spatial isolation, these individuals are reliably genetically differentiated. In addition, individuals of one type were subjected to stressful anthropogenic impact (grazing). Therefore, the smallest sizes and lowest potential seed productivity were recorded. Our research shows that alpine populations of R. rosea in AR, under conditions of anthropogenic stress, need protection for their gene pool. Rhodiola rosea L. (Crassulaceae) is an herbaceous polycarpic plant belonging to long-shoot hemicryptophytes. It is a dioecious species with separate female and male plants. The flowers are collected in a cymose inflorescence; the carpels of the ovary are free and isomeric [R. rosea is common in Iceland, the British Isles, the European Alpine system, and Scandinavia. Also, the species is common in western and eastern North America, up to the eastern coastal regions. It has a narrow area of arcto-alpine habitats [isomeric ,2. In thisomeric  and of tisomeric , the speisomeric . The spehabitats .R. rosea in southern Siberia (Russia) is distributed in mountainous regions: Tuva, eastern and western Sayans, Kuznetsk Alatau, and Mountain Altai. According to the published data, the main features of the morphostructure of the aboveground part of the shoots of R. rosea have a wide variability that depends on environmental conditions, including the length of the shoots, the size of the leaves, and the number of flowers. This species is a valuable medicinal plant since the rhizomes of R. rosea are traditionally used for medicinal purposes [purposes ,6. The bpurposes ,8.R. rosea in its natural habitat has occurred over the past few years due to excessive harvesting of rhizomes. This is one of the evident examples of the negative impact of the anthropogenic factor on the environment and the overall state of a particular species, which is rare at present due to excessive exploitation of natural resources [A sharp decline in the abundance of esources .R. rosea, it is necessary to study the state of the species’ coenopopulations within its natural range. Assessment of the biological features, ontogenetic, ecological, and phytocenotic structure of R. rosea populations has previously been conducted in the southern Urals and in the highlands of eastern Kazakhstan (EK) [In relation to the conservation issue of tan (EK) ,11. HoweR. rosea has been studied in the populations of this species in northern Europe [Rhodiola have been discussed for the territories of western Europe and eastern Asia [Rhodiola in eastern Kazakhstan [R. rosea populations in undisturbed habitats and under stressful conditions of anthropogenic impact (grazing).Molecular markers have a wide potential for the detection of intra- and interpopulation genetic variability in different species  ,13,14. Tn Europe . The issern Asia ,17,18,19zakhstan . Up to dRhodiola rosea in natural cenopopulations in various ecological and geographical conditions of the Altai Republic.The purpose of the study is to characterize the variability of morphometric traits and to perform a comparative analysis of the genetic variability of R. rosea did not differ in different growing conditions, maintaining stable values in the whole sample. We attributed the leaf width and the ratio of the number of generative to vegetative shoots to such features. The most robust individuals of this species developed under natural conditions in the KNR (in CP 1 and CP 2). The indicators of shoot length, diameter of the aerial part, and number of shoots in an individual were characterized by the highest values in the representatives of these CPs that grew under natural undisturbed conditions .Some biometric parameters in nditions . Represether CPs  , were characterized by the smallest values of the diameter of the aerial part, leaf length, number of shoots (including vegetative ones), and low leaf area index compared with the plants from other CPs  was found in individuals from CP 5 (found in Seminsky Pass). In general, climatic conditions in the habitat of CP 5 are favorable. The relatively low altitude of AR is combined here with the growth of individuals of this species on the banks of streams formed by melting snowfields, that is, in close proximity to running water during the entire growing season. However, growth near popular hiking trails makes unregulated harvesting of rhizomes possible. Also, farm animals occasionally graze in this habitat in the summer. Such an environment could have contributed to the removal of the most productive individuals of R. rosea in different CPs . Representatives from this CP are also characterized by the smallest size of several other morphometric characteristics, as mentioned above. The same low PSP was observed in the specimens of this species from Seminsky Pass (CP 5), which also grew under conditions of certain anthropogenic impact , the size of the inflorescence (r = 0.5), the number of leaves (r = 0.7), and the total number of shoots per individual (r = 0.5), including vegetative ones (r = 0.5). The number of shoots in an individual is mainly determined by the number of vegetative shoots (r = 0.9). The number of generative shoots affects the total number of shoots (r = 0.6) and the ratio of generative to vegetative shoots in individuals (r = 0.6). Wider leaf blades are negatively associated with the leaf index (r = −0.5). PSP is determined by the diameter and number of inflorescences with fruits .The study of correlations between the traits of R. rosea CPs studied, we found that the variability of a number of morphometric characteristics depends on three factors. These are abiotic conditions, which are (1) the absolute altitude of growth and (2) the year of research with its specific growing conditions, and the biotic factor, (3) anthropogenic impact. The parameters of variability of shoot and leaf length, foliage, leaf index, number of generative and vegetative shoots and their sum, number of flowers in inflorescence with fruits, and PSP depended significantly on the absolute altitude of growth . Higher values of these parameters were recorded for  in 2018 .The parameters of variability in the length of shoots, the diameter of the aerial parts of plants, the length and number of leaves, the number of shoots (both vegetative and generative), and potential seed productivity depended on the factor of anthropogenic impact. Significantly lower values of the length of the shoots, the diameter of the aerial part, and the length and number of leaves were recorded in the highlands of the SNP (CP 6) in the presence of anthropogenic impact a–e. UndeR. rosea in our regions of research with the parameters of this species in other regions. It showed that in AR, individuals of this species were characterized by lower vigor compared to those studied in eastern Kazakhstan (EK) and in the south of the Ural Mountains (SU).We compared the morphometric parameters of R. rosea. Populations of this species migrate to areas free from turf vegetation or fall out of phytocenosis. In such habitats, the death of young plants of this species and low seed renewal is observed [According to published data, in EK, the conditions on the floodplain meadows were optimal for the species . This isobserved .R. rosea was subjected to severe stress associated with anthropogenic impact (unregulated harvesting of rhizomes) [A decrease in the morphometric parameters of shoots was observed in SU as the absolute growth altitude of this species increased. The length of generative shoots ranged, on average, from 4.5 to 54.0 cm, and the number of generative shoots ranged from 1 to 38 pieces . These indicators turned out to be somewhat lower than in the individuals in AR . In thishizomes) .R. rosea than that found in our study was found in the Murmansk region (European part of Russia) [A wider range of variation in the morphometric characteristics of  Russia) . This coR. rosea specimens in CP 1 and CP 2 turned out to be the most vigorous and productive, growing under favorable conditions in the subalpine meadows of the Katunsky Reserve. They also exhibited the highest potential seed productivity compared to plants in other ecological and geographical conditions of AR.In the AR, R. rosea in this CP could be adversely affected by grazing cattle (yaks). According to the SNP records, in CP 6, grazing continues during the growing season, and the cattle summer camp is also located here. In the highlands of the Kosh–Agach region, this method of animal husbandry is common [R. rosea plants in CP 6 is associated not so much with high mountain conditions as with the impact of grazing.In the high-mountain conditions of the Kosh–Agach region , individuals of this species were characterized by the smallest values of several morphometric features of the aerial part. In alpine locations, plants are affected by extreme weather conditions that contribute to the development of dwarfism even in species that are not elements of the alpine flora. In addition to the climatic factor, the productivity of s common . The negs common . We assuThis is confirmed by the fact that representatives from the highest mountain CP 3 (SNP) were mainly characterized by intermediate size of the organs of the aerial part of the shoot, and only the length of the shoots and volume of foliage had the smallest values. There is no cattle grazing in this habitat.R. rosea plants are quite favorable. This is due to their growth in open areas with constant soil moisture from running water from melting snowfields. The morphometric parameters of the above-ground part of the shoots were mostly of intermediate values. However, in the presence of anthropogenic impact on CP 5, as well as in CP 6 in the SNP during grazing, R. rosea showed the lowest values of potential seed productivity.At relatively low altitudes in CP 4 and CP 5, the conditions for In representatives from the ANR (CP 7) under natural conditions, we recorded the smallest length of shoots, as well as in the representatives from two other high-mountain CPs (3 and 6). The small length of shoots and the associated decrease in the photosynthetic surface was compensated by a significantly higher number of shoots due to an increase in the number of generative shoots in an individual. The latter reached the same high values as those of representatives from CP 1 and CP 2, located in protected areas in the KNR.Hedysarum austrosibiricum Ledeb. and also in the species Astragalus mongholicus Bunge (Fabaceae), which has a wide altitudinal range in the highlands of the AR. In those species, the size of leaflets of a compound leaf decreased with an increase in the absolute altitude of growth. Such a decrease in photosynthetic surface in high-mountain CPs in representatives of H. austrosibiricum was compensated by the formation of a higher number of generative shoots and in vegetative shoots in individuals of A. mongholicus [Similar transformations were observed by us in the subalpine species gholicus ,25.Rhaponticum carthamoides (Willd.) Iljin. (Asteraceae), under conditions of grazing and harvesting of the underground parts of plants, we also observed a decrease in the thickness of the renewal zone and a reduction in the photosynthetic surface. However, these processes were accompanied by the preservation of a stable productivity of generative organs, which is comparable to their development in undisturbed habitats. Thus, R. carthamoides retained its reproductive potential under anthropogenic impact [R. rosea under conditions of grazing on high mountains in CP 6, only an uncompensated decrease in the parameters of the photosynthetic surface and potential seed productivity was observed, which may indicate the loss of resistance of individuals of this species under such extreme conditions for survival.In c impact . HoweverR. rosea individuals in the ANR in terms of the number of shoots (CP 7).In addition, a significantly greater number of shoots in individuals from the ANR (in 2018) could have been caused by weather conditions. According to published weather data, 2018 was characterized by an early and prolonged spring, with a predominance of anomalous heat at the beginning of the season and an excess of moisture at the beginning and end of the season. The summer of 2018 was abnormally hot and dry . The sprR. rosea. These basic parameters determine the size of the photosynthetic surface of plants of a given species and their reproductive potential. Under conditions of a dry beginning of the growing season and in the presence of anthropogenic impact (grazing and trampling), the productivity and sustainability of R. rosea significantly decreases.Therefore, the complex of growth conditions at a certain absolute altitude, the meteorological conditions of the year of observation, and anthropogenic impact had a significant effect on the variability of the main indicators of productivity in Rhodiola rosea in the AR, individuals from the studied CPs were characterized by different levels of intrapopulation diversity. Based on the analysis of DNA fragments obtained via amplification with the selected ISSR primer, we observed the absence of genetic intrapopulation diversity in representatives of CP 3 and CP 6 (SNP). Representatives from these CPs also had the lowest number of effective alleles and a low Shannon index, which are the parameters that show the complexity of the population structure and allow for assessing the richness of the studied population   .Samples from CPs no. 1, 4, 5, 6, and 7 formed the first cluster. Samples from four CPs formed the second cluster: CP 1, CP 2, CP 4, and CP 5. Notably, individuals from CP 6 (SNP) on the dendrogram are assigned only to the first cluster, where they formed a separate clade. Even more genetically isolated than the representatives from CP 6 are representatives from CP 3 (SNP). Its individuals formed a separate cluster .R. rosea was approximately equal to the proportion of intraspecific genetic variability  were characterized by the smallest genetic distance. They grew in close proximity to each other, and they had almost complete similarity in the distribution of ISSR markers . Also, pRepresentatives from CP 3 and CP 6 are located relatively close geographically in the SNP, and the distance between them is a little more than 10 km, while representatives from CP 3 and CP 2 are more than 150 km apart from each other see .R. rosea. In northern Europe, the average percentage of band polymorphism for ISSR markers was reported as follows: for Sweden—83.8%, Greenland—94.6%, and Faroe Islands—48.7% [R. rosea in this habitat. The high genetic diversity of individuals from CP 4 may be due to favorable climatic conditions in this habitat and the absence of anthropogenic impact.According to the literature, no gender-specific or population-specific primers were found in ds—48.7% . When cods—48.7% . IndividUPGMA dendrograms clearly demonstrate significant genetic differentiation of CP 3, which grows in SNP. It is the highest of all the studied populations in AR. It is possible that the highest absolute altitude of this CP influenced a certain genetic isolation of its individuals. The lowest number of effective alleles in the two high-mountain populations (CP 3 and CP 6) and the absence of polymorphic loci can be explained by their growth in high-mountain conditions (more than 2400 masl). These conditions can affect the genetic heterogeneity of populations, since they are far from the ecological optimum for this species and are located close to the limits of the altitudinal range of its growth. Also, in the highlands, only adapted individuals can survive. Therefore, the genetic heterogeneity of populations here can be reduced. The existence of geographically relatively close to each other populations of a species with high genetic isolation in the SNP (CP 3 and CP 6) indicates the presence of certain barriers to the exchange of genetic information among representatives from high-mountain populations.R. rosea is characterized by obligate xenogamy. In central Russia, the pollinators of R. rosea under cultivated conditions are hover flies (Syrphidae Latreille) [Syrphinae), closely associated with tundra and alpine biocenoses, lives in the high mountains of Altai. This group of insects does not occur in lower biocenoses and is considered a “typical high mountain species” [R. rosea in high mountains is quite possible. Harsh climatic conditions in the highlands are not an obstacle to the survival of pollinating insects adapted to them. The lack of opportunity for gene exchange between such populations  can be due to the small number of their individuals in each population, since in each of them there were no more than 10–15 mature generative plants subjected to pollination. In this regard, they are isolated in space. In addition, in high-mountain habitats, the species occurs in single populations, which may also be associated with anthropogenic impact , since regulated economic activity is allowed for the local population in the SNP.According to published data, treille) . Accordispecies” . Due to R. rosea plants in the fruiting phase were studied in AR [Live mature female ed in AR . The clied in AR . Six cenn = 15–21  individuals. Potential seed productivity was studied in 78 individuals. According to our assumptions, the variability of quantitative traits of plants could be significantly influenced by abiotic factors: growth at different absolute altitudes (factor A) and weather conditions in different years of research (2018 and 2020) (factor B); as well as a biotic factor—anthropogenic impact (C).In each CP, the sample for morphometric studies was R. rosea were studied at six altitudes: 1850, 2000, 2070, 2260, 2400, and 2500 m above sea level . In the Ongudaysky district, on the Seminsky Pass (CP 5), individuals grew near the hiking trails. Due to easy accessibility, the rhizomes of R. rosea were harvested there in unregulated fashion for several years (gradation 2). The SNP (CP 6) is the location of a summer camp for the large herbivores (yaks), where regular grazing throughout the growing season is allowed by the regulating nature management authorities for representatives of the local population. This is ARea of the strongest anthropogenic impact (gradation 3).Anthropogenic impact (C) was allotted to three gradations. In the Katunsky State Natural Biosphere Reserve , in Sailyugemsky National Park , the Ust-Koksinsky District  and in the Altai Nature Reserve , individuals of Ten metric and allometric features of the aerial part of the shoot were assessed: the length of the shoots; diameter of the above-ground part of the plant; length and width of the leaf in the middle part of the generative shoot; diameter of inflorescence with fruits; number of leaves; total number of generative and vegetative shoots and their ratio; and leaf index (the ratio of the maximum to the minimum size). The parameters for the study of potential seed productivity (PSP) included: the diameter of inflorescence with fruits; number of flowers in inflorescence; number of carpels in the ovary; and potential seed productivity per generative shoot .The names of taxa are given according to the original source . Figure Variability and analysis of pairwise correlations (according to Spearman) were performed using Microsoft Excel software package 6.0. The mean value of the feature (M), standard error of mean (m), coefficient of variation , and correlation coefficient (r) were calculated. To reduce differences in dimension for correlation analysis, feature values are normalized according to the following equation: (Mi—M)/σ, where “Mi” is the feature value and “σ” is the standard deviation.n < 25). Only the features with statistically significant differences (p < 0.05) in mean values are included in the discussion.The variation was considered very low and low at values of the coefficients of variation (Cv) < 21% on the scale of C.A. Mamaev . VariatiR. rosea was studied in 7 CPs. The DNA from leaves dried under field and laboratory conditions  (without taking into account the gender of plants) was isolated via standard methods [The genetic polymorphism of  methods . Eight pThe results of statistical analysis and their visualization were analyzed with the TREECON software package 1.3b and the specialized macro GenAlEx6 for MS-Excel.R. rosea cenopopulations under different ecological and geographical conditions of the AR showed a higher vigor in individuals in undisturbed habitats in the middle mountains in the subalpine meadows of the KNR and the high mountains of the ANR. Here, individuals have the highest values of morphometric indicators of the aerial part, potential seed productivity, and high genetic heterogeneity, which reaches from 50 to 80%. In the undisturbed conditions of high mountains, R. rosea plants have adapted by increasing the number of generative shoots on average, 2.9 times. The most oppressed individuals of the species R. rosea, characterized by genetic homogeneity (lack of genetic polymorphism), grew in high-altitude conditions in the SNP under the constant summer grazing. Perhaps the combination of these two factors—growth in the highlands and constant grazing—is an extreme condition for the growth and development of R. rosea. Grazing is associated with negative impact: soil compaction on summer camp sites and concomitant damage to the above-ground parts of plants of this species. The impact of these unfavorable conditions on R. rosea plants can serve as a limiting factor for plant adaptation. Conservation of genetic diversity is a key factor for the survival of R. rosea. In the AR, the widespread unauthorized extermination of this species through harvesting of the underground part of plants is common. Therefore, in future research it is necessary to monitor the state of genetic diversity of as many natural populations of R. rosea as possible. First, their verification (certification) is necessary, and second, it is expedient to reintroduce them into natural conditions in order to preserve their genotypes in the territory of the AR. High—mountain populations, having a homogeneous genetic structure, are more vulnerable and need preservation. The study of various aspects of the variability of natural populations of R. rosea will enable the development of a sound program for conservation, restoration, and rational use of this rare species.Comparison of the developmental features in seven


Dear Editor,We would like to extend our gratitude to Dr. Ruiz et al.We concur that proper management of patients with hereditary cerebral small vessel disease, specifically CADASIL, should take precedence over predictive genetic testing of family members.Regrettably, there are no effective pharmacological treatments available to delay or halt the progression of this disease, as well as many other late-onset neurodegenerative diseases, even with early diagnosis. Nevertheless, potential benefits of performing genetic testing on asymptomatic family members include enhanced psychosocial well-being and increased control over life decisions, such as the option for reproductive testing.For ethical considerations, both genetic counseling and presymptomatic tests ought to be conducted in accordance with specific guidelines and programs to mitigate negative outcomes—what are often referred to as “catastrophic events”—such as suicide attempts or psychiatric hospitalizations.Unfortunately, these guidelines are not consistently applied in practice, leading to variations in genetic counseling and testing procedures among healthcare providers. These variations can include differing roles for healthcare team members, the number and type of appointments, and specific requirements for neurological or psychiatric/psychological assessments.The literature on genetic counseling for CADASIL and other cerebrovascular diseases is limited. Thus, we recommend adhering to protocols developed for conditions like Huntington's disease.In Brazil, guidelines for genetic counseling in late-onset hereditary neurological disorders are scarce and only available in a few specialized services. Additionally, there remains a need for more research concerning the influence of cultural background on the acceptance of presymptomatic tests in low- and middle-income countries.Our study was conducted at an international neurological rehabilitation center, which primarily serves symptomatic patients to minimize disability and enhancing functionality.In the context of the Brazilian Public Health System (SUS), genetic counseling is primarily offered in university hospitals. Despite advances in medical genetic care, the current public services and specialized personnel in medical and human genetics fall substantially short of the country's needs. It is worth noting that molecular diagnostic technologies were not added to the list of procedures for the SUS until 2014, and even then, only rare diseases were included.In conclusion, we acknowledge the importance of genetic counseling and advocate for increased efforts to broaden access to genetic tests for family members, while rigorously adhering to ethical guidelines.