Akebia trifoliata (Thunb.) Koidz is an important medicinal, fruit and oil crop, particularly in China. In this study, 28 simple sequence repeat (SSR) markers were used to assess the genetic diversity and genetic structure of 955 A. trifoliata germplasms, determine their molecular identity and extract a core collection. The genetic diversity of the 955 germplasms was moderately polymorphic. The average number of alleles (Na), observed heterozygosity (HO), expected heterozygosity (HE), Shannon’s information index (I∗), and polymorphic information content (PIC) were 3.71, 0.24, 0.46, 0.81, and 0.41, respectively. Four subpopulations were identified, indicating a weak genetic structure. A 955 germplasms could be completely distinguished by the characters of s28, s25, s74, s89, s68, s30, s13, s100, s72, s77, and s3. And each germplasm’s molecular identity was made up of eleven characters. The core collection was composed of 164 germplasms  and diversity parameters differed significantly from those of a random core collection. These results have implications for germplasm conservation. At the same time, based on the results, the 955 germplasm could be better used and managed.Understand genetic diversity and genetic structure of germplasm is premise of germplasm conservation and utilization. And core collection can reduce the cost and difficulty of germplasm conservation.  Akebia trifoliata (Thunb.) Koidz belongs to the family Lardizabalaceae and genus Akebia Decne and is mainly distributed throughout China, Japan, North Korea, and Russia. In China, this species is mainly distributed in the Yangtze and Yellow River Basins, and Shaanxi-Sichuan area  to evaluate the overall genetic diversity and genetic structure (2) to establish molecular identity to distinguish 955 germplasms and (3) to construct a core collection to facilitate later management. Genetic diversity and genetic structure will be valuable to guide the available collection and application of A. trifoliata in China. Molecular identity and core collection will be beneficial to the A. trifoliata germplasm management and breeding.In the present study, 28 pairs of SSR markers were used to analyze the variation of 955 A. trifoliata germplasms, for which the collection location was unclear, were cultivated in the Taojiang experimental field of the Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences in 2012. Fresh tender leaves from each germplasm were placed in a liquid nitrogen tank, transported to the laboratory, and frozen at −80°C until genomic DNA extraction. Genomic DNA was extracted using a Rapid DNA Extraction Kit . The purity and quality of extracted DNA were evaluated by 1% agarose gel electrophoresis and determined using a NanoDrop 2000 spectrophotometer.The 955 From the SSR primers developed by 1, 2, 3, 4 and A, B, C, D, E, F was used to instead of A/A, B/B, C/C, and D/D and A/B, A/C, A/D, B/C, B/D, and C/D genotype, respectively, and 0 represented no band. The character of the SSR marker which has the highest PIC was first to be used distinguish 955 germplasms. Then, the second, the third was added until all germplasm were completely distinguished. Finally, the molecular identity of each germplasm consisted of characters corresponding to the SSR markers.The stepwise clustering method can effectively preserve the genetic diversity of the original germplasm . AccordiNe), Shannon–Weaver diversity index (I∗), genetic distance (Nei’s genetic distance), observed heterozygosity (HO), and expected heterozygosity (HE) (Na)  ; PowerMaHE) (Na) . Based oHE) (Na) . PopulatHE) (Na) . The varHE) (Na) .Na per locus ranged from 2 to 5 . Seventeen primer pairs amplified four alleles, and five primer pairs amplified two alleles, only one amplified five alleles. NE ranged from 1.2018 to 2.8556 , HO from 0 to 0.83 , HE from 0.1681 to 0.6521 , Nei’s distance from 0.1679 to 0.6535 , I∗ from 0.3083 to 1.1866 , and PIC from 0.1538 to 0.5936 . The PIC indicated that the 28 SSR markers were moderately polymorphic (0.25 < PIC < 0.5). The most polymorphic SSR marker had 3.86 times higher variance than that of the least polymorphic marker. Seven microsatellites exhibited high polymorphism (PIC > 0.5), and four microsatellites exhibited low polymorphism (PIC < 0.25). The heterozygosity of A. trifoliata was relatively low based on HO and HE .A total of 104 alleles were detected using 28 SSR markers. As summarized in A. trifoliata accessions, and a dendrogram based on genetic distances and the unweighted pair group method with arithmetic mean is shown in A cluster analysis was performed to analyze the genetic relationships among the 955 K-values (population number) of 1 to 10 for a STRUCTURE analysis. The most significant change in likelihood occurred when the K-value increased from 2 to 4, and the highest ΔK value was observed between K = 2, 4, and 6 (LnP(K) increased when the K-value ranged from 1 to 10  decreased. Therefore, the optimal K-value in the present study was 4 with the division of the natural population into four subgroups  could distinguish the 955 germplasms. The molecular identity of each germplasm consisted of 11 characters ; for exaNa, Nei’s distance, HO, and PIC over the 28 SSR markers as indicators. The core collection consisted of 164 genetic individuals  of three false core collections were analyzed , thereby verifying that the species is moderately polymorphic (0.25 < PIC < 0.5). Additionally, 10 pairs each of ISSR and SRAP markers have been used to evaluate polymorphisms in 242 individuals from 11 natural populations , the germplasm was only from the Qinba mountain area of China, and the results had certain limitations (sesame (S. indicum) (28/277) (maize (Z. mays) (951/13521) (soyabean (G. max) (rubber tree (Hevea brasiliensis) (128/505) (ramie (Boehmeria nivea L.) (22/105)  (247/707)  , maize (1/13521) , and soy(G. max) . In cont128/505) , ramie ((22/105) , and Gym247/707) . HoweverA. trifoliata, even with some missing geographic information. The use of modern technology to distinguish these germplasms is a key possibility. SSR molecular marker technology is not affected by geographical origin and can result in high polymorphism, stable results, and good repeatability (Abundant crop germplasm resources are the basis of crop breeding, but germplasm collections is time demanding and laborious. Collection of the 955 germplasm resources from China took about 10 years, and the germplasms were cultivated in the Taojiang experimental field of the Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences. However, due to early management and staff turnover, the geographic origin of each germplasm was unclear, which limits our understanding and utilization of the germplasm resources. Although the geographic origin of germplasms is important for genetic diversity research, the 955 germplasms in our collection are still important for the breeding of tability . TherefoA. trifoliata germplasms to date. This results showed moderate genetic diversity and weak genetic structure in the natural population of A. trifoliata, based on 28 SSR markers. Eleven pairs of primers could distinguish the 955 germplasms, and the molecular identity of each germplasm consisted of 11 characters. A core germplasm collection consisting of 164 germplasms was generated, accounting for 17.2% of the original germplasm. Further, estimated of genetic diversity and genetic structure could provide a foundation for future A. trifoliata breeding. The core collection and molecular identity could reduce the management cost and improve the protection of germplasm resources.To the best of our knowledge, this study used the largest number of The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.ML and JaC conceived and designed the project. YZ, YW, ZS, JN, YS, KH, and JnC collected the plant materials. YZ, YW, ZS, JN, YS, and JnC performed molecular labwork and scored the markers. YZ and YW analyzed the data and wrote the manuscript with assistance from all other authors. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Introduction: The National Comprehensive Cancer Network (NCCN) has outlined guidelines for criteria regarding genetic testing for high-penetrance breast and/or ovarian cancer susceptibility genes. Due to the lack of availability of genetic counseling services in Northern Michigan prior to COVID-19, the utilization of genetic testing falls well below recommended guidelines.Methods: Patients diagnosed with breast cancer in 2019 were randomly selected from Ascension Michigan's Northern Ministries Tumor Registry. A retrospective chart review was conducted. For patients who met NCCN criteria, their medical records were used to determine if genetic testing was recommended and if genetic testing was completed. Univariate (Crosstabs and t-tests) and multivariate tests with logistic regression were used to identify significant associations between the variables of interest.Results: One hundred and two (102) patient charts were reviewed in this group; 55 (52.4%) were eligible by the NCCN guidelines for genetic testing. From this eligible subset of patients, only 29 were offered genetic testing, and only 21 were tested. The mean age of the patients offered genetic counseling was 56.2 years compared and 67.6 years in the group not offered counseling (p < 0.001). The patient's insurance type was an independent factor for obtaining genetic testing, specifically, the subgroup who had Medicare . Patients insured through Medicare were less likely to obtain genetic testing after referral to a genetic counselor (p = 0.01).Conclusion: Genetic counseling for high-risk breast cancer patients is below average in Northern Michigan, likely related to lack of physician referral, poor availability of counseling services, low socioeconomic status as well as a lower level of concern in older ages. Breast cancer is the leading cause of cancer diagnoses among women worldwide (excluding skin cancer) . ApproxiGenetic counseling has become more robust since it first became available. The first major utilization of genetic counseling was for classifying a patient’s BRCA status ,6. GenetThe value that genetic counseling provides is undeniable, and the need for this counseling has heightened as genetic testing has advanced. One way in which genetic counseling services have catered to this need is through the implementation of virtual genetic counseling. Virtual genetic counseling is particularly useful in rural communities, as in-person services are most often located in academic and urban settings . One stuSeveral factors contribute to the lack of referral to a genetic counselor in patients who meet NCCN criteria. The purpose of this study is to identify barriers to genetic counseling for patients in the Northern Michigan region to begin recognizing ways to overcome genetic counseling discrepancies.Study designAfter approval from the Ascension St. Mary’s Institutional Review Board (IRB) was obtained, a retrospective analytical study based on the hospital records of patients diagnosed with breast cancer in the Northern Michigan area was conducted.Patients diagnosed with breast cancer in 2019 were selected from the Ascension Michigan’s Northern Ministries Tumor Registry. Using the NCCN guidelines (NCCN version 1.2020), patients eligible for genetic testing were identified based on their individual risk factors. Of those who met NCCN criteria, two subsequent groups were made: patients who were recommended to have a genetic counseling referral and patients who were not. The proportions of patients who underwent testing and those who did not obtain testing following a recommendation by a genetic counselor were also evaluated. Several demographic variables were also obtained through chart review to assess potential contributing factors to a patient’s decision to undergo genetic testing. Inclusion and Exclusion CriteriaPatients who were diagnosed with breast cancer within 2019 were included. A subgroup of 55 patients was obtained after including only the patients eligible for genetic counseling and testing per the NCCN guidelines. The excluded patients were those with incomplete documentation in their medical records that would inhibit accurate evaluation of the fulfillment of NCCN criteria or those with equivocal data regarding genetic counseling.Statistical analysisThe statistical analyses were run using the IBM SPSS Statistics for Windows software . Frequency tables were used for univariate analysis of the demographic data. To adjust for covariates, a simple logistic regression model was used. All the statistical tests were two-sided, and p < 0.05 indicated a statistically significant difference.Population demographicsAt the conclusion of the retrospective review, 105 patients from the Northern Michigan area Ascension Tumor Registry were identified. Of those, 102 were selected as they had fully documented medical records. In this group, 55 (52.4%) were eligible for genetic counseling referral by the 2020 NCCN guidelines (Table Genetic testing offered Of the 55 (52.4%) patients eligible by NCCN criteria for genetic counseling, only 29 were offered a referral to a genetic counselor. However, only 21 (72.4%) of the patients offered referral to a genetic counselor went on to obtain genetic testing. No significant difference was found based on race (p = 0.9) among those who were offered genetic counseling and those who were not. The mean age of patients offered genetic counseling was 56.2 years compared to 67.6 years in the group that was not offered a referral (p < 0.001). When comparing if genetic counseling was offered based on a patient’s insurance and their permanent residence , there was no significant difference based on insurance type and geographic location . On the multivariate logistic regression, there was no significant variable associated with decreased or increased offering of genetic counseling in breast cancer patients. Genetic testing obtainedThe subset of patients in whom genetic counseling was offered was further divided into patients who went on to obtain genetic testing and those who did not. Again, age was a significant factor in the univariate analysis for obtaining genetic testing (p < 0.001), with younger patients more likely to utilize genetic testing resources. When comparing race or residence , once again, no significant difference between the two groups was identified . The only significant variable on multivariable analysis that was associated with decreased genetic testing performed was the insurance type . Specifically, being insured through Medicare was seen more frequently among those who did not obtain testing after being offered (p = 0.01). Genetic counseling and testing have revolutionized the treatment and management of breast cancer in the late 1990s and have continued to advance in the following years. As technology has advanced and the number of genetic variations that testing is capable of identifying has improved, a greater proportion of the patient population has been able to utilize these resources ,15. NCCNSeveral studies have attempted to identify barriers to obtaining genetic counseling. One study in Dallas, Texas, reported 69% of patients who were eligible by NCCN criteria for breast cancer genetic testing obtained it. The most significant barrier to genetic testing in that study was the lack of a timely referral from a physician to a genetic counselor . SeveralIn another study, only 43.5% of patients with a clinical indication for genetic testing received a referral to a genetic counselor . Across The patient's age had a significant influence on being offered genetic counseling in this study. Younger patients more commonly had discussions with their physicians regarding genetic counseling than older patients with newly diagnosed breast cancer. It can be inferred that the younger the patient, the more likely the patient is to be offered counseling because, classically, breast cancer associated with genetic mutations occurs at a younger age . Older pAlthough not demonstrated in this study, race has been identified as a barrier to genetic counseling in previous studies . FurtherPatient demographics and variables that predicted a patient's likelihood of obtaining testing after being offered counseling were also identified. The urban versus rural delineations did not influence whether a patient obtained testing. This clearly demonstrates the underutilization of breast cancer genetic counseling services for the entire Northern Michigan area. Patients insured through Medicaid were less likely to get genetic testing. Insurance coverage should not be a limitation for patients who meet NCCN criteria because under the Affordable Care Act, genetic counseling, and specifically BRCA testing, are recommended preventative services for women found to be at increased risk for hereditary breast and ovarian cancer . TherefoGenetic counseling should be offered to all patients who fulfill NCCN criteria regardless of their socioeconomic status, race, and geographic location. Virtual genetic counseling services paired with at-home genetic testing kits have increased accessibility to testing and the means to educate patients on the clinical relevance of the results. Continuing to advocate for widespread genetic counseling services for all newly diagnosed breast cancer patients who meet NCCN criteria is crucial.With the incorporation of virtual genetic counseling, it may be anticipated that the discrepancy in genetic counseling utilization will lessen in the coming years. Future comparative analysis may look at the proportion of patients who meet NCCN criteria for referral to a genetic counselor pre- and post-COVID-19. The major limitation of this study is that it employed a retrospective chart review which relies on the assumption that the patient documentation was complete at the time of review. The sample size is also a limitation and should be continued with a larger patient population to fully address discrepancies in genetic counseling referral.


By virtue of their cultural, linguistic and genetic legacies, many populations from Sudan have deep histories in the region and retain high genetic diversities. Sudan’s location in north east Africa, a unique spot believed to act as a climatic refuge during periods of climate extremes, might have dictated that fate. Among the marked consequences of this diversity is the potential to provide information on the origin and structure of human populations within and outside the continent, as well as migration patterns towards various parts of the African continent, and out of Africa. The diverse Sudanese gene pool further has the potential to inform on genetic adaptations driven by culture and the environment resulting in unique and interesting traits, some of which are yet to be investigated. In addition, these genomes could offer clues to complex issues of causation amidst the challenge of new paradigms in biology underpinned by the genomic revolution. Populations from Sudan contribute to inferences about the deep history of humans within Africa. Humans were new comers to a 5 billion years old world, which was already endowed with the gift of life for at least 3.5 billion years. The estimated naissance of our sub-species is in the mere range of 100–300 thousand years ago (kya) . Severalbc is distinguished by an increasingly dry climate. The origins and groupings of the population are difficult to reconstruct, since few well-preserved skeletal remains have been discovered  is estimated to be between 1000 and 10 000 individuals—this number is believed to have fluctuated over time, often suffering severe bottlenecks (Genomes of east Africans, and Sudanese in particular, are crucial to consider for the following reason: mounting evidence exists that many human adaptive traits were acquired in Africa, where the modern human species evolved. Many of those adaptive traits like skin color and other physical and physiological traits are products of a deeper African evolutionary history, including natural selection . They astlenecks ,40.eN, an expression of the amount of unique variations or number of mutations in a particular group, is quite pertinent to the practice of genomics in Africa. The significance of population size being a measure of genetic diversity and fitness is multiple, pertinent to most of the challenges we face as a species, our health and social being, and our relationship with the environment. The larger the effective size of a species, the better its chances of confronting adversities and survival.There is no better example to justify understanding the repercussion of a high genetic diversity and high effective population size than cancer biology. Cancer as a disease is the ultimate embodiment of a complex phenomenon. Conventionally, cancer genetics has focused on mutational events that have their primary effects on the cell. Recently, however, that focus has widened, with evidence for the importance of epigenetic occurrences and cellular interactions in cancer development. Differential methylation analysis corroborated these results revealing the epigenetic dysregulation of major developmental pathways including the Hippo signaling pathway . In SudaThe predicament of variant interpretation is accentuated further as conventional variant calling methods of pathogenic alleles in exome and genome sequencing requires the presence of the non-pathogenic alleles as genome references alleles. African data have illustrated that some reference alleles may be pathogenic and should be treated with caution. Under conditions of heterogeneity of allele frequency, it was proven problematic leading to the possible miss-interpretation and oversight of homozygous disease variants .In brief, without understanding the intricacies of the regulation of biological networks and how genes/proteins interact, neither the genetic differences nor the effects of selection will be fully understood and properly elucidated . Africa,It is apparent that detailed analysis and understanding of human population origins and diversity as reflected in extant populations may provide useful insights pertinent to human health and the challenges outlined above, rendering systematic and coordinated analysis of these genomic legacies both relevant and imperative.


Brazilian cassava diversity was characterized through population genetics and clustering approaches, highlighting contrasted genetic groups and spatial genetic differentiation.Manihot esculenta Crantz) is a major staple root crop of the tropics, originating from the Amazonian region. In this study, 3354 cassava landraces and modern breeding lines from the Embrapa Cassava Germplasm Bank (CGB) were characterized. All individuals were subjected to genotyping-by-sequencing (GBS), identifying 27,045 single-nucleotide polymorphisms (SNPs). Identity-by-state and population structure analyses revealed a unique set of 1536 individuals and 10 distinct genetic groups with heterogeneous linkage disequilibrium (LD). On this basis, a density of 1300–4700 SNP markers were selected for large-effect quantitative trait loci (QTL) detection. Identified genetic groups were further characterized for population genetics parameters including minor allele frequency (MAF), observed heterozygosity M. glaziovii were detected. Spatial population structure analysis revealed five ancestral populations related to distinct Brazilian ecoregions. Estimation of historical relationships among identified populations suggests an early population split from Amazonian to Atlantic forest and Caatinga ecoregions and active gene flows. This study provides a thorough genetic characterization of ex situ germplasm resources from cassava’s center of origin, South America, with results shedding light on Brazilian cassava characteristics and its biogeographical landscape. These findings support and facilitate the use of genetic resources in modern breeding programs including implementation of association mapping and genomic selection strategies.Cassava (The online version of this article (10.1007/s00122-021-03775-5) contains supplementary material, which is available to authorized users. Manihot esculenta ssp. esculenta) domestication resulted from human-mediated selection in the Amazonian region and adjacent areas of northern Bolivia  and genomic selection (GS). In general, the success of GWAS relies on linkage disequilibrium (LD) that refers to allelic association and linkage of genetic markers in the genome. Evaluating and assessing the diversity and population genetic parameters, such as LD, of cassava germplasm in Brazil could help to address significant germplasm management challenges. Average LD decay defines the required number of SNP markers and mapping resolution in association studies  of Brazilian Agricultural Research Corporation, Embrapa Mandioca e Fruticultura, located in Cruz das Almas, Bahia, Brazil  were used for this study Fig. . The yeaThe initial 3354 germplasm set (annotated GA panel) was subjected to Identity-By-State analysis on genotyping data (see details in “Population structure and genome-wide relatedness” section) and a unique core set of 1536 germplasm was constructed (annotated GU panel). To further guide GA and GU panels germplasm characterization, 62 known South American cassava landraces and wild relatives from the cassava HapMap  at 65 °C for 2 h and thereafter visualized on agarose gel.DNA extraction was performed following the protocol described by Albuquerque et al. .Genotyping was performed by preparing pooled libraries using Genotyping-By-Sequencing (GBS) . All filtering was performed using PLINK v1.9  using the GATK CombineVariants and SelectVariants functions , MAF (–maf: 0.05) filtering and linkage disequilibrium marker pruning using –indep-pairwise 50 5 0.8 .Germplasm duplicate identification was performed using a set of 9686 SNPs filtered on the basis of genome-wide average proportion of alleles shared between individuals using the IBS estimation approach available in PLINK  estimation was carried out using PLINK as previously described by . The ten genetic groups were identified using DAPC and validated using Admixture as indicated in the population structure section above. Genetic groups (3 and 4) with sample size n < 100 were not considered in subsequent downstream analysis.Average polymorphism information content (PIC) for the identified genetic groups was computed on 27,045 SNPs using R  with a MAF  of 5% on each chromosome was computed using PLINK. In addition, genome-wide LD decay was computed for each identified genetic group. To limit individual group-size incidence on LD estimates, 120 individuals were randomly sampled from each group, identified as a result of Admixture, PCA and DAPC analysis. Population genetics parameters were estimated on aforementioned groups and LD decay curves were fitted using nonlinear regression as previously described  and wild germplasm , introgression detection analysis for M. esculenta ssp. flabellifolia and M. glaziovii was carried out using the method earlier described by Bredeson and colleagues  and a genome-wide scan using TESS3 . These 419 germplasms are a subset of 702 germplasms in our population collected before the year 2000, excluding contemporary breeding lines, located within different ecoregions, excluding those at the boundary of two ecoregions. We constructed a consensus population graph tree using a SNP window size of 50, five migration events with sample correction disabled, and 1000 bootstrap replications to improve tree robustness. The TreeMix maximum likelihood method -based duplicate analysis. This analysis  . Clustering approaches  and metadata on the GUH dataset supported their group identification  and lowest (0.133) MAF, respectively  falling to background levels (r2 < 0.1) at approximately 107 kb  less than 0.1 at genome-wide scale (Supplementary Table 7). Higher chromosomal LD extent was observed on chromosomes 5 and 17 with r2 values of 0.026 and 0.06, respectively, together with the slowest decay . See Supplementary Note 2 for additional LD details.Average genome-wide LD was 0.021  to 603 (NE-LandRaces) SNP markers, based on group average LD threshold (Supplementary Table 7).The estimated number of SNP markers required to detect QTL with large effect size in association studies showed variation across chromosomes and genetic groups, from 1296 (NE-Admix-Group) to 4713 SNP (genome-wide) markers with M. esculenta subsp. esculenta compared to both wild M. esculenta subsp. flabellifolia and M. glaziovii samples identified 294 (Supplementary Table 8) and 1,795,898 biallelic, ancestry-informative SNP markers (Supplementary Table 9), respectively. These SNP markers are distributed across chromosomes and represent fixed, or nearly fixed, differences between cultivated and wild Manihot . Of the M. glaziovii-specific SNPs, 3238 were represented within the GBS marker set , which were used to infer ancestral segments in the identified genetic groups. Introgression of M. glaziovii in the Brazilian germplasm collections was found on two chromosomes. The largest introgressed segment  was found in chromosome 17, and predominately in the Bitter-Group  presented strong geospatial overlap with the six Brazilian ecoregions  .Using 702 landraces (excluding breeding lines), collected before the year 2000, distributed across the five ecoregions of Brazil, the genetic groups show strong overlap with the ecoregions . The average percentage of accessions grouped in the same groups between GUH panel DAPC and spatial analysis GAHg panel was 85% and ranged from 96 to 53% with only two groups having less than 86% (Bitter-Group: 77% and SWEET-Group: 53%), given that GAHg panel contains 1036 individuals in common with GUH panel (Supplementary Table 14).A genome-wide scan for selection, based on population differentiation in the inferred ancestral populations from spatial analysis, detected 24 loci above the Bonferroni-adjusted threshold  method, we identified and characterized genetic groups of the Embrapa Brazilian cassava germplasm collection and inferred the parameters describing genetic diversity, population structure and linkage disequilibrium.Accession mislabelling has been reported to reduce the genetic gain of cassava by up to 40% in Africa  and lead to improved population inference. Admixture models, however, are more interpretable when using spatial information  and Cerrado—Pampa  ecoregions may represent the second phase of cassava domestication from initially “sweet” domesticated cassava to “sweet and bitter” cassava  in some groups  and a higher amount of rare (< 5%) alleles in others , suggesting semi-isolated groups. The Amazonas-Group showed the highest diversity (PIC = 0.190) and rare alleles richness (MAF = 0.144) captured in our dataset, consistent with the origin of cassava in Amazonian ecoregion Allem . GeneticOverall, the MAF identified in the germplasm included in this study provides sufficient power for association studies in a panel that includes a broad range of genetic diversity. The average MAF of 0.14 (14%) indicates that most loci (SNPs) in this study have required allele frequency (> 0.05) for association (and other related trait mapping) studies. MAF highlights informative markers, rare variants and alleles conservation in a population. Our result falls within the range reported for other clonal crops like banana  was higher than previously estimated in Brazilian cassava (r2 < 0.2)  datasets        for all genetic pools shows a similar trend with average genetic pool’s LD decay having higher genetic distances across groups . Given the allogamous nature of cassava, the pattern of LD may reduce prediction accuracy, since LD is crucial for genomic selection (GS) breeding , 1300–4700 SNP markers would be needed to detect large QTL association, while the SNP density of 27,045 was used in this study with 19,085 bp average distance between two SNPs, a much higher marker density will be required to detect small effects QTL association (Supplementary Table 7).Genomic variation across the genome and within groups  reveals that on average, based on the LD decay , was an introgressed segment. Earlier studies reported that Latin American samples from CIAT showed almost no evidence of M. glaziovii introgression on both chromosomes 1 and 4  were too few and too sparse to assign segments of M. esculenta subsp. flabellifolia ancestry across the genome, leading to the speculation that the observation may be incongruent with the evolutionary hypothesis that M. esculenta comes from M. flabellifolia, indicating that the two species may be too close to identify long, contrasted introgression segments. Following the evolutionary history example of another South American crop, tomato (autogamous), cassava does not present such a strong domestication. Therefore, lower differentiation and subsequent contrast between its wild ancestor and contemporary cultivated lines may limit the prevalence of private alleles between M. flabellifolia and M. esculenta groups. Identification of structural variants  would help in that regard.Based on the observed genome-wide LD landscape, we speculated that the extended LD observed in chromosome 17, influencing the LD decay for most population groups except Amazonas-Group M. glaziovii to M. esculenta Brazilian germplasm, we identified a large set of differentiating markers, in contrast with the few differentiating markers earlier reported for CIAT germplasm , and another individual (“UFB_002”) that appears to be from a “pure” M. esculenta × M. glaziovii hybrid backcrossed to another M. glaziovii , supporting the hypothesis put forward by Bredeson et al. . We could confirm this finding, with these accessions clustering within the Bitter-Group. Explaining the ancestral segments in Fig. 5, with blue and green segments highlighting the presence of M. glaziovii introgressions, specifically in individuals identified as hybrid including “Manipeba,” clones showing feral characteristics form of cassava from Northeast Brazil, hypothesized as a transitional link between wild ancestor and cultivated cassava  the counter selection of homozygote M. glaziovii introgressions under natural/anthropic selection pressure and (iii) M. glaziovii hybridization events in Brazilian germplasm might be older than in African germplasm.On the other hand, comparing n et al. . Accessilleagues  found anoup Fig. . Wolfe aoup Fig.  reportedva Allem . Subsequfe et al  observed Nichols , let us , indicating beneficial allele and directional selection in the genome , with 24 differentiating loci identified across the genomeWolfgang .suggesting the likely connections between the Amazonian ecoregion and the Amazon basin, leading to potential routes of seeds/cuttings migration or dispersion by animals or other elements. Given that Northern Bolivia and Amazonian  the identification of M. glaziovii introgressions (and a possible third species sampled by UFB_002) in Brazil may indicate that interspecific hybridization is a more widespread phenomenon than previously suspected, and an effort to sequence and assemble the complete genomes of related Manihot species would enable a more comprehensive survey for sources of desirable alleles/traits and (9) finally, we suggest that cassava may have been propagated to the coastal region of Brazil independently of its migration from the Amazonian ecoregion. In a context where Amazonia’s in situ genetic resources are facing increasing conservation challenges, current findings present significant progress in characterizing ex situ cassava germplasm collections. Results include the identification of crop cultivars for efficient germplasm management, SNP density requirement for the development of simple PCR amplicon assay for genotyping. This study provides important information on the genome-wide assessments of the genetic landscape of cassava in Brazil as future resources for breeding activities, such as genomic selection, association studies and marker-assisted selection to increase genetic gain in cassava breeding programs in Brazil.In this study, we characterized genetic diversity and investigated population structure, performed duplicate analysis, estimated linkage disequilibrium, population differentiation and effective population size among the identified genetics groups in Brazilian cassava. Accurate identification of crop cultivars is crucial in assessing the impact of crop improvement program outputs. It also highlights the magnitude of genetic drift among identified genetic pools and its impact on survival, reproduction and the rate at which a population enters the extinction vortex. Minimizing loss of genetic variation via genetic drift should be an important objective of the cassava breeding program in Brazil. Based on our datasets, we suggest that: (1) there are 1536 IBS-selected unique accessions that represent the diversity within Brazilian germplasm collections, (2) there are 5 major ancestral populations and 10 genetic groups in the Brazilian germplasm collection studied, (3) selection based on traits  of interest by breeders and farmers could have led to the observed population structure in the collected germplasm across Brazil, (4) spatial analysis showed with consistency the Southwestern Amazonia as the center of domestication of cassava, highlighting the cassava diversity landscape of Brazil, including impact of breeding activities, (5) LD decay across the genome indicates that interval of 1300–4700 SNP markers is required to detect with reasonable power, association of large quantitative trait loci (QTL) effect, based on our GBS dataset, (6) in addition, this defines the SNP density for development of PCR amplicon sequencing for genotyping and also suggests that GBS can be done at higher DNA multiplexing, thereby reducing the costs of variety fingerprinting, (7) we found evidence for Supplementary file1 (XLSX 1889 kb)Supplementary file2 (DOCX 1271 kb)Below is the link to the electronic supplementary material.


Urva edwardsii) in Iran, as the most western part of the species range. Using mtDNA, we confirmed the presence of two highly differentiated clades. Then, we incorporated ensemble of small models (ESMs) using climatic and nonclimatic variables with genetic data to assess whether genetic differentiation among clades was coupled with their ecological niche. Climate niche divergence was also examined based on a principal component analysis on climatic factors only. The relative habitat suitability values predicted by the ESMs for both clades revealed their niche separation. Between‐clade climate only niche comparison revealed that climate space occupied by clades is similar to some extent, but the niches that they utilize differ between the distribution ranges of clades. We found that in the absence of evidence for recent genetic exchanges, distribution models suggest the species occurs in different niches and that there are apparent areas of disconnection across the species range. The estimated divergence time between the two Iranian clades (4.9 Mya) coincides with the uplifting of the Zagros Mountains during the Early Pliocene. The Zagros mountain‐building event seems to have prevented the distribution of U. edwardsii populations between the western and eastern parts of the mountains as a result of vicariance events. Our findings indicated that the two U. edwardsii genetic clades in Iran can be considered as two conservation units and can be utilized to develop habitat‐specific and climate change‐integrated management strategies.Combining genetic data with ecological niche models is an effective approach for exploring climatic and nonclimatic environmental variables affecting spatial patterns of intraspecific genetic variation. Here, we adopted this combined approach to evaluate genetic structure and ecological niche of the Indian gray mongoose ( H. edwardsii significantly correlated with different climate features. Niche‐based distribution models revealed that the two molecular clades occupy distinct environmental spaces, which are not similar, and equivalent.Combining genetic data with ecological niche modeling is an effective approach for defining conservation units and exploring environmental variables that affect spatial patterns of genetic variation. We found two distinct genetic clades within  Southern Iran consists of the southern mountain ranges of Zagros, Central Iranian Range, Khuzestan Plain, and the northern coasts of Persian Gulf.Here, we employed an integrative approach to explore genetic and ecological differentiations within the Indian gray mongoose  provide insights into intraspecific genetic diversity and niche differentiations among U. edwardsii populations in Iran and (ii) assess whether the Zagros Mountain may have acted as a physical barrier between the Indian gray mongoose populations.Smaller carnivores such as mongooses lack the attraction and attention that managers and conservationists seek in mega‐carnivores as suitable flagship species and conservation tools. Thus scientific information on small carnivores such as the Indian gray mongoose is still scarce in many countries including Iran. Small carnivores, however, show stronger specialization and resource selectivity compared to large carnivores  only reported from Sistan and Baluchestan Province (Sistan region), Hormozgan Province, and few localities in Khuzestan Province , following the manufacturers’ instructions. Polymerase chain reactions (PCRs) were performed for the amplification of a 691 base pairs (bp) fragment of the mitochondrial control region using HERP–DL‐93‐L  and U. auropunctata (3 sequences), and sequences from GenBank, including eight sequences of U. edwardsii, six sequences of U. auropunctata as well as three sequences of Urva javanica, were aligned using the Clustal W algorithm  was used as the outgroup. The HKY+ G was selected as the best‐fitting model of DNA substitution, using Bayesian information criterion (BIC) implemented in jModelTest . Fixation index (FST) was calculated using ARLEQUIN  the Poisson tree process model , PTP (https://species.h‐its.org/ptp/), and GMYC (https://species.h‐its.org/gmyc/) with the default parameters.Bayesian phylogenetic analyses were carried out in MrBayes v.3.2  and another leading to the remaining of Asian mongoose   as the calibration point . To account for lineage‐specific rate heterogeneity, a lognormal relaxed clock model was used and a Yule model of speciation was used for the tree prior. Two independent Markov chains were run for 3 x107 generations, sampling every 1,000 generations was employed to construct a maximum clade credibility tree. The log parameters and tree files from each run were combined, using the LOGCOMBINER v.1.8. , and nucleotide diversity (π) for each clade separately and the whole samples in Iran. A median‐joining (MJ) network was constructed for U. edwardsii using PopART v.1.7  within an ensemble modeling framework. Climatic data were obtained from 19 bioclimatic variables  with spatial resolution of a 30 arc‐second. To account for multi‐collinearity among bioclimatic variables and avoid overparameterization of the models, we calculated Pearson's correlation tests among all pairs of variables and also variance inflation factor (VIF) for each variable in R package sudm (Naimi r > 0.80), we removed those with higher VIF (>3) from further analysis. This reduction of variables resulted in the inclusion of eight climate predictors in the final ENM including temperature annual range, mean temperature of wettest quarter, mean temperature of warmest quarter, precipitation of wettest month, precipitation seasonality, precipitation of warmest quarter, and precipitation of coldest quarter. Four land use and land cover types were extracted from the Global Land Cover by National Mapping Organization (GLCNMO) .We excluded the Indian gray mongoose occurrence localities in the contact zone of the two identified clades in the process of ecological niche modeling of clades as we did not have genetic samples from their regions, and therefore, their genetic clades were unknown. However, these localities were included in the ENM using all occupied localities clades together. Spatial autocorrelation in presence localities was assessed by Moran's I index for each variable separately in R package ue Table  and to adm Naimi . From eaecospat  . Since niche equivalency test disregards surrounding space, we also performed niche similarity (background similarity) test between clades. Niche similarity test uses randomization to determine whether climate difference detected between clades can be explained by difference in the environmental background they occurred. In niche similarity test, random models are generated by using randomly generated occurrence points. The niche similarity test was carried out in both directions. The mean of overlap metrics obtained by 100 pseudoreplicates was compared to real overlap metric by empirical models. The null hypothesis of niche similarity test is rejected when the observed niche overlap value is significantly lower than the values generated by pseudoreplicates. Significant niche identity and background similarity indicates differences in the predicted climate niches of both clads is due to differences in the overall environment between regions. On the other hand, significant niche identity and insignificant background similarity indicate that the differences in the climate niches of clades are not due to underlying environmental differences and this difference is due to differences in the niche utilized by each clade in each region  collected across the species range in Iran. The Bayesian inference consensus tree with posterior probabilities (PP) showed that the Indian gray mongoose in Iran has divided into two clades corresponding to the haplotypes of the species range in south and southeast, hereafter Clade 1  was 0.57. Pairwise FST between clades 2 and 3 was 0.45. All estimates were significant at p < .05 based on 10,000 permutations with Bonferroni corrections  was averaged at about 4.9 Mya with 95% highest posterior density (HPD) intervals of 3.3–6.5. The divergence time of clade 3  and the lineage leading to Iranian clades  was estimated at about 6.0 Mya (95% HPD: 5.2–7).U. edwardsii and was found within 10 individuals in Clade 1 in four provinces of Fars, Kerman, Yazd, and Bushehr. Haplotype network showed divergence between the Indian gray mongooses in Iran. In line with the results obtained from the phylogeny tree .The haplotype network provided further information regarding the haplotypes Figure . Haplotye Figure , the hapU. auropunctata, but nine unique haplotypes were detected among the sequences generated for CR of U. edwardsii with an overall haplotype and the nucleotide diversity h = 0.804 and π = 0.00627, respectively (Table h = 0.864 and π = 0.00272) than Clade 1 (h = 0.318 and π = 0.00065) indicating a high level of genetic variation in Clade 1 compared to Clade 2.Only one unique haplotype was detected among three sequences of 3.2U. edwardsii. The ESMs produced fairly high AUC and Boyce index values for predicting the ecological niche of Clade 1  and Clade 2 . The results of ESMs showed that the five most important variables for predicting habitat suitability of U. edwardsii in Clade 1 were precipitation seasonality, human footprint, sparse herbaceous, consolidated land, and herbaceous with sparse density of tree and shrub. On the other hand, the EMS predicted that suitable habitats of U. edwardsii in Clade 2 were related to mean temperature of warmest quarter, precipitation of coldest quarter, herbaceous with sparse density of tree and shrub, human footprint, and elevation  explained 40.30% and 29.80% of the variation in climatic variables, respectively. PC1 was mostly correlated with temperature‐related factors , while PC2 was highly correlated with precipitation‐related factors . The relatively low niche overlap suggested that two genetic clades of U. edwardsii occupy considerably distinct climate niches. Considering niche position of both clades on climatic axes  confirming that the niches of the identified clades of U. edwardsii are significantly distinct. The background test comparing the clade in southwestern Iran (Clade 2) occurrences with the background space of the clade in south and southeast (Clade 1) revealed that the observed value of niche similarity is lower than expected under the null hypothesis. However, when comparing in the opposite direction, the observed overlap is higher , yet not significant. Randomization tests  showed that environmental space occupied by clades is similar to some extent, but the niches that they utilize (identity test) differ between the distribution ranges of clades.The comparison of climatic niches of both clades along the PC1 and PC2 showed low climate niche overlap D = 0.25. The rel4U. edwardsii populations in Iran, one in southwest and the other in south and southeast. Second, a genetic clades‐specific combination of environmental variables among the clades was found, indicating the niches that each U. edwardsii clade utilizes differ between the distribution ranges of clades.The present study was the first to employ a combination of genetic data and ecological niche models to evaluate intraspecific genetic and ecological variation within a less studied carnivore, the Indian gray mongoose. Our findings provide evidence in supporting the idea that incorporating ecological niche models into phylogeographic analyses would improve the accuracy of intraspecific genetic information and predictive ability to population boundaries. The adopted methodology has great implications for conservation unit assessment for the species and can provide valuable information regarding the feasibility of this approach to many species around the world. We showed two main results, which are elaborated in the sections below. First, phylogenetic analysis suggested the existence of two genetic clades within the 4.1U. edwardsii is separated from U. auropunctata, which is in line with the results of Veron and Jennings (U. edwardsii in Iran. Based on the phylogenetic tree (1995 bp) from a combined dataset of Cytb + ND2 + FGB  coincides with the uplifting of the Zagros Mountains during the Early Pliocene. The uplifting of Zagros Mountains began as a result of the Arabian plate impinging on Eurasia in the Late Miocene Salah, . The sepU. edwardsii populations between the western and eastern parts of the mountains as a result of vicariance events. The Clade 2 is mainly located in the Khuzestan Plain, which is a relatively flat region of Iran, isolated from the Clade 1 by the southern Zagros Mountains. Khuzestan comprises a southeastern extension of the Mesopotamian plain and includes part of the forested Zagros Mountains. The Zagros mountain‐building event, as a barrier to gene flow, has been also reported in some taxonomic groups, in particular, for small mammals  and western parts (related to the southern part of Zagros mountain range) of its distribution in Iran can be considered as two conservation units according to the genetic and ecological concept. Further investigation is needed into the possible presence of a cryptic subspecies.The two genetic clades of 4.2U. edwardsii and explore the hypothesis that adaptation to different environmental condition are contributing to genetic structuring in Indian gray mongoose. In accordance to genetic findings, our ecological niche models showed little geographic overlap between two genetic clades of U. edwardsii, indicating that clades differ in their niches and occupy a part of the geographic range in south of Iran where environmental conditions are suitable  is relatively more than south and southeast of Iran, and U. edwardsii in south and southeast of Iran inhabits areas with dry summers. Thus, our results highlighted the importance of precipitation and temperature in providing climatically suitable niche for Indian gray mongoose in Iran.Although the distribution of both clade appears to be highly dependent on the herbaceous with sparse density of tree and shrub Table , climatiU. edwardsii occupy distinct ecological niches that are similar, but undoubtedly not equivalent. The results of the niche identity test suggested a lack of ecological exchangeability confirming previous researches that morphological similarity does not necessarily equate to ecological equivalence  coincides with the uplifting of the Zagros Mountains during the Early Pliocene. The Zagros mountain‐building event seems to have prevented the distribution of U. edwardsii populations between the western and eastern parts of the mountains as a result of vicariance events.In conclusion, our results showed that two genetic clades of Indian gray mongoose occupy distinct environmental spaces that are similar, but not equivalent, relatively small niche overlap between these clades. These findings show that two clades of 5.1U. edwardsii, thus, a conservation status assessment should be conducted for both clades separately and may result in a subsequent definition of cryptic subspecies and conservation efforts. Also, it is important that conservation actions be taken in the immediate future to conserve the genetic variation of population in each region before it declines. Despite that the impact on native fauna of introduced Indian gray mongooses is not known, further introductions of any mongoose species to act as a biological control outside their native range are not recommended.Our predicted ecological niche maps broadly estimate the most important ecological requirements that the species may need to establish a habitat. Also, the obtaining distribution data are informative to establish conservation priority and conservation efforts. As our genetic data confirmed the genetic structure among the populations of The authors declare that they have no competing interests.Razieh Oboudi: Conceptualization ; Data curation ; Methodology ; Resources . Mansoureh Malekian: Conceptualization (lead); Formal analysis ; Supervision (lead); Writing‐original draft ; Writing‐review & editing . Rasoul Khosravi: Formal analysis ; Methodology ; Software ; Validation ; Writing‐original draft ; Writing‐review & editing . Davoud Fadakar: Formal analysis ; Methodology ; Software . Mohammad Ali Adibi: Data curation .Table S1Click here for additional data file.


Small and isolated populations have low genetic variation due to founding bottlenecks and genetic drift. Few empirical studies demonstrate visible phenotypic change associated with drift using genetic data in endangered species. We used genomic analyses of a captive tiger pedigree to identify the genetic basis for a rare trait, pseudomelanism, in tigers. Genome sequencing and extensive genotyping of noninvasive samples across tiger range revealed unique spatial presence of this allele in the Similipal Tiger Reserve, India. Population genetic analyses confirmed that Similipal is a small and isolated population. Simulations suggest that intense founding bottlenecks could result in the observed patterns, implicating drift. Our study highlights ongoing phenotypic evolution, potentially from human-induced fragmentation, in endangered large carnivore populations. Panthera tigris) in the Similipal Tiger Reserve (in eastern India) are pseudomelanistic, characterized by wide, merged stripes. Camera trap data across the tiger range revealed the presence of pseudomelanistic tigers only in Similipal. We investigated the genetic basis for pseudomelanism and examined the role of drift in driving this phenotype's frequency. Whole-genome data and pedigree-based association analyses from captive tigers revealed that pseudomelanism cosegregates with a conserved and functionally important coding alteration in Transmembrane Aminopeptidase Q (Taqpep), a gene responsible for similar traits in other felid species. Noninvasive sampling of tigers revealed a high frequency of the Taqpep p.H454Y mutation in Similipal  and absence from all other tiger populations . Population genetic analyses confirmed few  tigers in Similipal, and its genetic isolation, with poor geneflow. Pairwise FST (0.33) at the mutation site was high but not an outlier. Similipal tigers had low diversity at 81 single nucleotide polymorphisms . Simulations were consistent with founding events and drift as possible drivers for the observed stark difference of allele frequency. Our results highlight the role of stochastic processes in the evolution of rare phenotypes. We highlight an unusual evolutionary trajectory in a small and isolated population of an endangered species.Most endangered species exist today in small populations, many of which are isolated. Evolution in such populations is largely governed by genetic drift. Empirical evidence for drift affecting striking phenotypes based on substantial genetic data are rare. Approximately 37% of tigers ( Panthera tigris) in which four subspecies have become extinct in the last century , but the melanistic appearance is a consequence of expanded pattern elements rather than a uniformly darkened color, also referred to as pseudomelanism , a 2,750-km2 protected area in eastern India. In addition to this wild population, pseudomelanistic tigers are present in three captive populations in India: Nandankanan Biological Park, Bhubaneswar (NKB), Arignar Anna Zoological Park, Chennai (AAC), and Bhagwan Birsa Biological Park, Ranchi, where they were born in captivity.Tigers have a distinctive dark stripe pattern on a light background, which can appear in several color shades—white, golden, and snow white. Segregation of these color variants in captive tiger populations has permitted their genetic and molecular characterization , 33. A rmelanism  and a teTaqpep mutations in the domestic cat (Felis catus) and the cheetah (Acinonyx jubatus)   alter pan tigers .Taqpep missense mutational variant as the genetic basis for a rare pseudomelanistic phenotype in tigers using whole-genome sequence data and known pedigrees of captive tigers that included pseudomelanistic individuals. We confirm the presence of this mutation only in Simlipal, where it occurred at a high frequency in a sample of wild tigers from across their global range. Finally, we used population genetics analyses to investigate whether genetic drift may be responsible for the observed discordant frequency within and outside Similipal by 1) investigating whether Similipal is a small and isolated population and 2) conducting population genetic simulations to explore how founding bottlenecks and genetic drift may change allele frequencies.In this paper, we confirmed a Taqpep gene. The Taqpep gene in tigers has 25 exons, with the total coding sequence length being 3,093 base pairs [Assembly PanTig1.0(GCF_000464555.1)]. We observed a single base substitution in exon nine from C to T at position 1360 (Taqpep c.1360C > T), which translates into a missense mutation at position 454 (histidine to tyrosine) in the primary sequence  of the protein (Taqpep p.H454Y)  from AAC  at the Taqpep c.1360C > T variant site and observed complete concordance of Taqpep p.H454Y with pseudomelanism [log likelihood test (LOD) = 2.5]. Loss-of-function mutations in Taqpep in other felid species (different positions) result in similar pattern variants  C. His454 binding C. We obsvariants , providi+/+, 6+/m, and 4m/m) , resulting in a Taqpep p.H454Y allele frequency of 0.58 in Similipal.We observed the presence of the Taqpep p.H454Y allele in Similipal . Among tTaqpep c.1360C > T variant site. We genotyped 85 tigers using whole-genome data for four subspecies n = 5 to 22) populations in a principal component . Simlipal tigers form a separate genetic cluster at K = 3 (best K = 5). On average, Northwest India showed the highest differentiation from Similipal, followed by South India and then populations in Central India .Eight out of 12 tigers from Similipal were genotyped on 85 loci  protected areas close to Similipal (100 to 700 km) where tiger presence was detected recently (as per forest department records). We conducted ground surveys in all five of these protected areas to collect noninvasive samples of tigers . Only two fecal samples collected from these regions had tiger DNA , but neither yielded SNP genotype data.There are five small  but only at shorter geographic distances. A Mantel correlogram  of genetic distance with geographic distance shows that isolation by distance breaks somewhere between 100 and 350 km.We found significant support for isolation by distance . In other words, if tigers can disperse 1,000 km, then Similipal will be connected to multiple nodes; if they can disperse 500 km, then one node. Similipal will be disconnected at a dispersal threshold of 200 km.Our least-cost resistance kernel analysis with dispersal thresholds of 200, 500, and 1,000 km suggests that the strength of the connectivity between Simlipal and the closest source populations was strong only at 1,000 km, weak at 500 km, and zero at 200 km dispersal threshold  was 0.33 . Pairwise FST based on 81 loci (ST), 15 in Similipal—South India, and 23 in Similipal—Northwest India] had higher levels of genetic differentiation than the Taqpep c.1360C > T variant .The pairwise Wright’s F variant B, suggesP value = 1, SI Appendix, Table S6).We cannot infer the absence of selection and selective advantage of the mutant allele because of the small number of loci in our data. However, there is no indication of deviation from HWE at this site in Simlipal based on Fisher's exact test (o = 0.28) is reduced to similar levels as Northwest India (mean Ho = 0.22) as opposed to Central India (mean Ho = 0.36) and South India (mean Ho = 0.32) , suggesting also that Similipal tigers are inbred. Mean relatedness between Similipal individuals was 0.38, close to the mean relatedness in another isolated and inbred population, ]. For example, an isolated population recovering over 44 generations from a severe bottleneck (n = 2) results in the value of P(pH454Y ≥ 0.5) = 0.28, assuming one heterozygote exists in the founding bottlenecked population (pH454Y ≥ 0.5) among several cases [P(pH454Y ≥ 0.5) = 0 to 0.28] of bottleneck size  and time allowed for drift (10 to 50 generations). In other words, the timing of the bottleneck did not substantially affect the probability of achieving a high frequency of Taqpep p.H454Y . Intense bottlenecks were required for any appreciable value of P(pH454Y ≥ 0.5) ). Corresponding simulations (same bottleneck size and time) had a lower value of P(pH454Y ≥ 0.5) when we did not force the founders to include at least one Taqpep p.H454Y allele , implicating founding events.Our noninvasive samples and the resulting low number of markers do not allow us to estimate the demographic history of Similipal tigers. Instead, we used simulations to investigate possible past trajectories and future evolutionary outcomes of  hunting  and the  hunting ] and asspulation D. This wSI Appendix, Fig. S7C). However, with logistic growth of the population  precludes us from making robust inferences from outlier tests or other tests of selection. However, future studies incorporating whole genomes or genome-wide data from Similipal should help confirm the role of genetic drift versus selection. Presently, genetic drift appears to be the most parsimonious explanation for the observed frequency of the variant in Similipal.Contrastingly, the nature of the mutation  suggests that it could be deleterious. Moreover, while pseudomelanistic tigers occur at a high frequency in Similipal, they have disappeared from across India, where populations may be larger (and hence selection more effective). This lends support to the possible deleterious effects of Taqpep p.H454Y.SI Appendix, Fig. S5C). Regardless of how the frequency of this mutation changes in the future, genetic rescue should benefit the population by increasing heterozygosity and decreasing the probability of inbreeding depression  to identify the causal genetic variant for the pseudomelanistic phenotype and targeted Sanger sequencing of individuals from NKB (n = 7) and AAC (n = 5) for genetic linkage analysis . We collected feces, shed hair, saliva, and blood samples from 22 captive tigers for this purpose. We collected the shed hair and fecal samples of the captive individuals from their cage before the scheduled early morning cleaning. To collect saliva samples from the captive tigers, we gave the isolated animal a clean PVC pipe to chew and then collected the salivary fluid from the pipe with a sterile swab (HiMedia). The blood samples of captive tigers used in this study were collected by the zoo hospital and Odisha University of Agricultural Technology for medical and research purposes. We stored the fecal and saliva samples in Longmire's buffer  and AAC (two pseudomelanistic tigers). We used whole-genome sequence data from captive pseudomelanistic tigers and their relatives of NKB . Since our objective was to maximize the sample size, we also collected some opportunistic samples (n = 27) based on the information from the forest guards on sighting a tiger's feces. Within Similipal, we walked 346 km (21 tracks) twice and 124 km (14 tracks) once over 45 d in sampling season one and 20 d in sampling season two. We covered 164 km in SNBD (14 tracks), 261 km in DEB (17 tracks), 212 km in SATK (15 tracks), 41 km in HADG (4 tracks), and 56 km in KULD (4 tracks). We also collected two skin samples that were confiscated and stored at room temperature by OSFD. One skin sample was from a pseudomelanistic tiger that died in 1992 and the second from a normal tiger that died in 2015. The skin samples were collected dry and stored at room temperature on the field site. We stored all the samples at room temperature at the field site for 15 to 30 d until transferred to a −20 °C freezer in the laboratory. The sampling was conducted with prior permission from the NTCA and OSFD following forest department guidelines.To determine the frequency of the mutant allele in the wild, we collected noninvasive samples from six protected areas (PAs) in the state of Odisha, Similipal Tiger Reserve, Satkosia Tiger Reserve (SATK), Sunabeda Wildlife Sanctuary (SNBD), Debrigarh Wildlife Sanctuary (DEB), Hadgarh Wildlife Sanctuary (HADG), and Kuldiha Wildlife Sanctuary (KULD). We sampled Similipal over two seasons spaced 1 y apart (February to March 2018 and March 2019) and other PAs for one season (February to April 2019). Within each PA, we determined several 10- to 20-km sampling tracks based on the information provided by the forest staff. We walked along the tracks and collected fecal samples by swabbing over the surface with a sterile polyester swab (HiMedia) and storing the swab in Longmire's buffer . We alsoAdmixture  and assessed its integrity based on the Bioanalyzer profile. The DNA extracts obtained from blood and saliva samples with high DNA integrity and concentration were selected for paired-end sequencing  on the Illumina HiSeq 2500 platform. In total, we sequenced genomes from nine captive tigers: three pseudomelanistic individuals (siblings), their two parents, their grandmother, their two siblings, and one wild-caught, unrelated individual.TrimGalore  and called variants using Freebayes , we assumed the pseudomelanistic tigers from NKB and AAC to be in two separate families.We trimmed the whole-genome sequences using imGalore  for a qu of the 16S ribosomal RNA gene  and sequencing the obtained products on a Sanger sequencing platform followed by an NCBI nucleotide BLAST of the sequences. To identify recaptures within the collected tiger samples from the wild, we performed SNP typing using multiplex PCR and MiSeq as described in Natesh et al. . We did an exact test for the HWE at these 85 loci by subsetting the data into individual populations (according to protected area boundaries) in Adegenet   in VCFtools  and plotted population-wise F by categorizing individuals into subpopulations. We estimated global and pairwise Weir and Cockerham's FST using the Pegas (GenALEx (Plink (genome function)   for thisAdegenet (Structure (version 2.3.4) program    analysisn 1.3.0) , Khan etn 1.3.0) , and Khan 1.3.0) ]. This wAdegenet  , and thep0 = 1/2N0, where N0 is the starting population size). To build the next generation, a random number was generated between 0 and 1 using the runif function in R, and if the chosen random number was more than p0, the wild-type allele was picked; otherwise, the mutant allele was picked. This was done N0 × 2 times to build the whole population. This process of random sampling was repeated for each generation. The last generation's allele frequency was stored in a matrix, and the whole simulation was repeated 1,000 times for each value of bottleneck size and time to drift. We calculated the probability of Taqpep p.H454Y allele frequency reaching 0.5 and above  by counting the number of times allele frequency crossed the 0.5 mark and dividing that by 1,000 and plotted this probability matrix as a heat map.A founding population keeping only one heterozygote was assigned at the start of the simulation, and the allele frequency was calculated (r = 0.15 per generation) .Future projection simulations to estimate time to fixation under two conditions—1) complete isolation of Similipal and 2) one wild-type homozygous individual is introduced into Similipal every generation (5 y)—were also done using a similar growth model (eration)  till oneeration)  (multiplSupplementary File


Triticum aestivum, Aegilops cylindrica, and Aegilops crassa species using 30 CAAT box–derived polymorphism (CBDP) and start codon targeted (SCoT) markers.Evaluation of genetic diversity and relationships among crop wild relatives is an important task in crop improvement. The main objective of the current study was to estimate molecular variability within the set of 91 samples from Ae. cylindrica species.Fifteen SCoT and Fifteen CBDP primers produced 262 and 298 fragments which all of them were polymorphic, respectively. The number of polymorphic bands (NPB), polymorphic information content (PIC), resolving power (Rp), and marker index (MI) for SCoT primers ranged from 14 to 23, 0.31 to 0.39, 2.55 to 7.49, and 7.56 to 14.46 with an average of 17.47, 0.34, 10.44, and 5.69, respectively, whereas these values for CBDP primers were 15 to 26, 0.28 to 0.36, 3.82 to 6.94, and 4.74 to 7.96 with a mean of 19.87, 0.31, 5.35, and 6.24, respectively. Based on both marker systems, analysis of molecular variance (AMOVA) indicated that the portion of genetic diversity within species was more than among them. In both analyses, the highest values of the number of observed (Na) and effective alleles (Ne), Nei’s gene diversity (He), and Shannon’s information index (I) were estimated for The results of cluster analysis and population structure showed that SCoT and CBDP markers grouped all samples based on their genomic constitutions. In conclusion, the used markers are very effective techniques for the evaluation of the genetic diversity in wild relatives of wheat. Aegilops as the most important wheat gene pool can contribute to obtaining favorable traits in breeding programs. This genus includes 22 species at the three di-, tetra-, and hexaploid levels as well as with various genetic structures such as the U, M, S, B, D, N, X, and T genomes [Aegilops species can be introducing desirable agronomic properties and breeding potential which induce resistance to various biotic and abiotic stresses [Based on the International Grains Council’s report 2019) [9 [1], th genomes . Numeroustresses –19. One Investigation of genetic diversity in wheat and its wild relatives has been done through agro-morphological characters, properties, and molecular markers techniques. Despite the botanical characters and agro-morphological traits being usually used to dissect genetic diversity, they are not completely successful due to environmental influences. In contrast, molecular markers as the genetic tools provide important information regarding the genetic structure and phylogenetic relationships among different plant species. These molecular tools expose genetic differences or similarities in better information without interference from environmental factors .Aegilops species using SCoT and CBDP markers.Various molecular marker techniques such as AFLP (amplified fragment length polymorphism), RAPD (randomly amplified polymorphic DNA), SSR (simple sequence repeat), ISSR (inter simple sequence repeats), DArT (diversity arrays technology), etc. are currently available for the evaluation of genetic population analysis, association analysis, and QTL mapping studies. CAAT box–derived polymorphisms (CBDP) and start codon targeted (SCoT) polymorphisms are two new reproducible markers that are based on the short conserved region in plant genes , 23. TheAe. cylindrica, Ae. crassa, and T. aestivum L. species. The genetic resources of wild species were collected from the natural habitats in Iran. and the seeds of all accessions were deposited in the Ilam University Gene bank with specific voucher numbers. The genetic composition and gene bank codes are presented in Table The plant materials consisted of 91 accessions belonging to 2O. The amplification conditions included an initial denaturation step of 5 min at 94 °C, followed by 45 cycles of 45 s at 94 °C, 1 min at 45 °C, and 3 min at 72 °C with a final extension at 72 °C for 7 min. Produced fragments were separated by gel electrophoresis in 1.5% agarose. In CBDP analysis, 15 primers were designed based on [A total of 15 SCoT primersTable  were selbased on , (Table Na) and effective alleles (Ne), Shannon’s information index (I), Nei’s gene diversity (He), and percentage of polymorphic loci (PPL) were calculated for comparing the level of genetic diversity among different species. All genetic parameters were calculated using GenAlEx software [Aegilops accessions using DARwin software ver. 6.0.13 [K) using the STRUCTURE HARVESTER software [All the observed bands in SCoT and CBDP profiles were scored as 1 and 0 on the basis of the attendance presence and absence of the amplified fragments, respectively. To determination of efficiency the selected primers, five informativeness indices, such as the number of polymorphic bands (NPB), polymorphism information content (PIC), resolving power (Rp), and marker index (MI), were estimated. Partitioning the genetic diversity among and within species was done through analysis of molecular variance (AMOVA). Genetic variation parameters including the number of observed  and minimum (15) numbers of polymorphic fragments. Rp index ranged from 3.82 and 6.94 with an average of 5.35 per primer. CBDP-8 and CBDP-11 showed the highest and lowest values for this index than other primers. The MI index varied between 4.74 and 7.96 with an average of 6.24 per primer, and the highest and lowest values were estimated for CBDP-7 and CBDP-10 primers, respectively. The mean of PIC index was 0.31 and it ranged from 0.28 (CBDP-2 and CBDP-11) to 0.36  (Table GST) among the studied populations (Table Nm) parameter for SCoT and CBDP markers were less than 1, showing a genetic isolation among different species. A summary of the estimated genetic variation parameters based on SCoT and CBDP markers is presented in Table Na, Ne, I, He, and PPL were 1.73, 1.35, 0.35, 0.22, and 86.01, respectively. The highest values for Na and PPL were observed for T. aestivum species, while the highest values for Na, Ne, I, and He were recorded for Ae. cylindrica species. On the other hand, the results based on CBDP data indicated that the average values of all genetic parameters were lower than SCoT data . The highest values of all parameters were recorded for Ae. cylindrica species.The results of the AMOVA analysis are shown in Fig. ns Table . BesidesAe. crassa and 9 accessions from Ae. cylindrica, while sub-II consisted of 9 and 22 accessions from Ae. cylindrica and Ae. crassa, respectively. All T. aestivum accessions (except no. 1) were placed in the second cluster (GII). Three samples from Ae. cylindrica  along with one sample of T. aestivum (no. 1) created the third cluster (GIII)  embraced all bread wheat accessions. The second cluster (GII) consisted of 22 samples from Ae. cylindrica along with 21 samples from Ae. crassa species. The remaining samples from Ae. cylindrica and Ae. crassa were grouped in the third cluster (GIII)  based on the SCoT data sets clustered all investigated samples into three main groups. The first, second, and third clusters consisted of 58, 29, and 4 samples, respectively (pairwise genetic distance coefficients are not shown). The first cluster (GI) was further divided into two sub-clusters (sub-I and sub-II). Sub-I included 21 accessions from K = 3, with accessions falling into three subpopulations  and all Ae. cylindrica were the third subpopulation. One sample (accession no. 2 from T. aestivum) was categorized into an admixed group  fell into subpopulation II, and three samples  along with one sample from Ae. crassa species (no. 59) were placed in the admixed group, respectively. All samples from Ae. crassa were separated from other samples and created subpopulation II. However, one sample from Ae. cylindrica was categorized in this subpopulation. Finally, the remaining Ae. cylindrica (30 samples) were assigned to subpopulation III . Nowak et al. [Aegilops species  using REMP and ISSR markers. The authors indicated that the used markers were efficient systems for evaluating the genetic diversity and also reported that the Aegilops species have a high level of genome variability which can serve as an ideal gene pool for discovering useful genes.Increasing the crop adaptability to climate change and ensuring food security for the next century are two critical scenarios which reveal the importance of genetic diversity in crop wild relatives. Among cereal crops, wheat has a rich gene pool, including many wild relatives with various genomic constructions. This feature has enabled wheat breeders to use them as a main source of important agronomic characters and ideal genes which are involved in tolerance to different biotic and abiotic stresses . Therefoes Table . Pour-Abh et al.  and Etmih et al.  and thesh et al. . PIC deph et al. . Averagera Table . Likewisk et al.  analyzedAegilops species through different DNA markers [Ae. cylindrica species using both marker systems. The higher level of diversity in this species might be referred to as the frequency of allelic variation of this species being affected by different climatic conditions [Ae. cylindrica as novel sources of tolerance to abiotic stresses for further wheat breeding programs [Ae. cylindrica has the highest level of genetic diversity among the evaluated Aegilops species, whereas the lower level of diversity belonged to Ae. crassa, which was in accordance with our findings in this study. However, this result disagrees with Etminan et al. [T. aestivum and Ae. crassa then Ae. cylindrica using CBDP markers. These contradictions could be referred to the primer’s sequences, the geographical origins, or sample size of the tested accessions. Khodaee et al. [Ae. triuncialis accessions using ISSR, CBDP, and SCoT molecular markers and confirmed that all the three marker systems can provide a comprehensive pattern of the genetic diversity in Ae. triuncialis germplasm.The result of AMOVA revealed that genetic diversity observed within species (SCoT = 78% and CBDP = 80%) is more to that found among them (SCoT = 22% and CBDP = 80%), suggesting all accessions in each species have a wide genetic differentiation Fig. . This fi markers , 44–48. programs . Pour-Abprograms  reportedn et al. , so these et al.  also repAegilops and Triticum species by Pour-Aboughadareh et al. [In SCoT and CBDP analyses, clustering patterns were consistent with the results of population structure analysis. In both analyses, all investigated accessions were clustered based on their genomic structure with a minor admixture Figs. , and 4. h et al.  and Etmih et al. . These aTriticum and Aegilops species. The molecular analysis of genetic diversity in the tested species showed a high level of genome variability in Ae. cylindrica species. Based on the results of AMOVA, genetic diversity observed within species was more than that found among them suggesting all accessions in each species have a wide genetic differentiation. In addition, based on obtained results, SCoT and CBDP markers were very effective techniques for the evaluation of the genetic diversity and phylogenetic studies in wheat germplasm. These results revealed that these two different gene-targeted molecular markers can be used as reliable techniques for detecting the levels of DNA polymorphism and genetic relationship.Preservation of the highest possible level of genetic diversity is one of the main goals of genetic resource conservation programs and assessment of genetic diversity using reliable methods provides useful information for the management of genetic resources and crop improvement programs. Our results revealed high polymorphism in the investigated Iranian wheat germplasm from different


Odocoileus virginianus) from eastern North America, which subsequently served to catalyze wildlife management as a national priority. An extensive stock‐replenishment effort soon followed, with deer broadly translocated among states as a means of re‐establishment. However, an unintended consequence was that natural patterns of gene flow became obscured and pretranslocation signatures of population structure were replaced. We applied cutting‐edge molecular and biogeographic tools to disentangle genetic signatures of historical management from those reflecting spatially heterogeneous dispersal by evaluating 35,099 single nucleotide polymorphisms (SNPs) derived via reduced‐representation genomic sequencing from 1143 deer sampled statewide in Arkansas. We then employed Simpson's diversity index to summarize ancestry assignments and visualize spatial genetic transitions. Using sub‐sampled transects across these transitions, we tested clinal patterns across loci against theoretical expectations of their response under scenarios of re‐colonization and restricted dispersal. Two salient results emerged: (A) Genetic signatures from historic translocations are demonstrably apparent; and (B) Geographic filters  now act as inflection points for the distribution of this contemporary ancestry. These results yielded a statewide assessment of contemporary population structure in deer as driven by historic translocations as well as ongoing processes. In addition, the analytical framework employed herein to effectively decipher extant/historic drivers of deer distribution in Arkansas is also applicable for other biodiversity elements with similarly complex demographic histories.Approximately 100 years ago, unregulated harvest nearly eliminated white‐tailed deer ( Quantifying dispersal and connectivity among populations has traditionally been done using direct methods such as radio‐ and satellite‐tracking , which now represents a panzootic  and reduced this to a single index  and those more extrinsic  that drive population structure.Given these predictions, we summarized locus‐wise patterns using two clinal parameters: 22.1During 2016–2019, 1720 tissues were collected by the Arkansas Game and Fish Commission (AGFC), representing all 75 Arkansas counties. We employed a combination of targeted sampling, road‐kill surveys, and a voluntary statewide CWD testing program , following enzyme and size‐selection optimization using in silico digests , Capreolus capreolus (GCA_000751575.1) and Capra hircus (GCF_001704415.1).We homogenized tongue or ear tissue (stored at −20°C) and extracted genomic DNA using QIAamp Fast Tissue kits , with verification via gel electrophoresis (2% agarose). Samples with sufficient yields of high molecular weight DNA (>200 ng) were then enzymatically fragmented via incubation at 37°C, using high‐fidelity N = 48) prior to automated size selection at 300–450 bp using a Pippin Prep (Sage Sciences). Adapter extension was performed over 12 PCR cycles using TruSeq‐compatible indexed primers  and Phusion high‐fidelity taq polymerase . Additional quality controls  were performed on final libraries prior to 1 × 100 single‐end sequencing on the Illumina HiSeq 4000 , with a total of N = 96 samples pooled per lane.Digests were purified using Ampure XP beads  and standardized to 100 ng per sample. Unique inline barcodes . To mitigate issues of independence among sites, we additionally sub‐sampled the dataset to one SNP per locus.Raw reads were demultiplexed using the pyRAD pipeline Eaton, , and tho2.2SD = 2%). We then inferred population structure  followed a cross‐validation approach with results aggregated from 20 independent replicates . Probability surfaces were then summarized as evenness and diversity of ancestries in each cell using Simpson's index . Our use of the diversity index was based on a straightforward prediction: Areas representing spatial transitions between populations will have a correspondingly low certainty of assignment to a given subpopulation ancestry . Likewise, those with low inter‐population exchange will comprise genetically similar individuals assigned with high probability to the endemic ancestry . Thus, genetic edges represent a marked transition from one population to another, as identified by site‐wise diversity in assignment probabilities (i.e. “ancestry diversity”). By lowering the resolution of the genetic diversity surface, we effectively decreased the noise introduced by translocation.Individual‐level ADMIXTURE results were summarized as a “surface” with spatial discontinuities represented as interpolated assignment probabilities. Here, we constructed statewide rasters, as representing per‐pixel probabilities or “ancestry proportions,” using Empirical Bayesian Kriging . Patterns based on Simpson's diversity were contrasted with those inferred using a form of 2D‐stepping stone model  is a product of gene flow averaged over many generations. Of note is the fact that the method only examines local ancestry probabilities and consequently will not be dominated by translocation‐related artifacts (as are methods based on interpolated pairwise genetic distances or 2.3x¯=55.38). Individuals were chosen to represent each subpopulation using a probability threshold applied to ADMIXTURE results. Loci were filtered to remove all SNPs with missing data in >50% of individuals, and computational time was further restricted by retaining only those loci with a sufficient allele frequency differential among clinal extremes .Interestingly, all our Odocoileus hemionus) as driven by pheromonal differences  . Large datasets (as herein) may allow a subset of highly consistent, maximally informative markers to be extracted that are broadly applicable across states and regions. An added benefit of our ddRAD dataset is that it provides a broad geographic database from future studies that can guide assay design (e.g., Chafin et al., post hoc method (such as that of Campbell et al., For white‐tailed deer, our approach provides a broad geographic reference database, followed by assay design for a Although dense spatial and genomic sampling may offer a composite resolution (e.g., Chafin et al., None declared.All authors contributed to study design and conceptualization. MCG, CRM, and JRB coordinated sample collection and curation of samples; TKC, BTM, ZDZ, and MRD contributed to molecular work; TKC, ZDZ, MRD, and MED planned the analysis approach; TKC and BTM wrote code for analysis and contributed exploratory analyses; TKC performed bioinformatic work, assembled data, and performed analyses; TKC and ZDZ prepared figures; TKC and ZDZ drafted the manuscript, and all authors revised the manuscript and contributed to the final version.Supplementary MaterialClick here for additional data file.


Crotalus horridus) populations. Previous work identified the genetic basis of this phenotypic difference, enabling us to characterize the roles geography, history, ecology, selection, and chance play in determining when and why new species emerge or are absorbed. We identified significant genetic, proteomic, morphological, and ecological/environmental differences at smaller spatial scales, suggestive of incipient ecological speciation between type A and type B C. horridus. Range-wide analyses, however, rejected the reciprocal monophyly of venom type, indicative of varying intensities of introgression and a lack of reproductive isolation across the range. Given that we have now established the phenotypic distributions and ecological niche models of type A and B populations, genome-wide data are needed and capable of determining whether type A and type B C. horridus represent distinct, reproductively isolated lineages due to incipient ecological speciation or differentiated populations within a single species.Ecologically divergent selection can lead to the evolution of reproductive isolation through the process of ecological speciation, but the balance of responsible evolutionary forces is often obscured by an inadequate assessment of demographic history and the genetics of traits under selection. Snake venoms have emerged as a system for studying the genetic basis of adaptation because of their genetic tractability and contributions to fitness, and speciation in venomous snakes can be associated with ecological diversification such as dietary shifts and corresponding venom changes. Here, we explored the neurotoxic (type A)–hemotoxic (type B) venom dichotomy and the potential for ecological speciation among Timber Rattlesnake ( Natural selection can promote local adaptation and determine the geographical distributions of phenotypes within species ,2. EcoloSnake venoms have emerged as a system for studying adaptive diversification because of their genetic tractability ,15, contl et al. ,30 showeMost of the >30 rattlesnake species have type B venoms, but type A venoms are known from at least ten species . Nine ofCrotalus horridus) occurs in the eastern half of North America from southern Ontario, southward to northern Florida, and westward to Texas and Minnesota [C. horridus from Florida  and one type B C. horridus from Georgia  [C. horridus possessed six PLAC. horridus possessed 13 SVMP paralogs; type A C. horridus possessed nearly all of the same loci, indicating that, in this region, the differential gene regulation accounts for the divergent phenotypes, consistent with other type A species [The Timber Rattlesnake  and conC. horridus across Florida  was performed on a Beckman System Gold HPLC  as previously described ,42 for tGenomic DNA was extracted from whole blood samples drawn from the caudal vein or muscle/liver/scale tissue from 258 specimens using the Omega bio-tek E.Z.N.A Tissue DNA Kit according to the manufacturer’s protocol; scale extraction procedures were modified  as previously described . All ext minutes ,44. Evidcytochrome b (see below) was used to confirm the presence of amplifiable DNA for type B individuals. We do note, however, that this assay could not distinguish between type A and type A+B hybrid venoms, which we discuss below.Because these subunits have been shown to be present in type A individuals but absent in type B individuals , we wereC. horridus specimens  from the natural-log-transformed SVL . Note th package  in R to  package .C. horridus and 19 bioclimatic variables as well as elevation at 30 arc second resolution [To determine if differences in venom type distributions were correlated with differences in abiotic environmental variables, we followed the approach of Strickland et al.  and conssolution . All presolution . To addrsolution . The twoD, Warren’s I, and Spearman’s rank correlation, and compared these measures across both geographic and environmental space. For each statistic, null distributions were generated using 99 permutation replicates where the occurrence points of type A and type B individuals were randomly reassigned to one of the two models. The test statistic calculated using the original, unpermuted data was then compared with the null distribution to test for significance using a one-tailed test.To test niche equivalency across venom types, we used the niche identity test  implemenC. horridus, a 1079 bp fragment of cytochrome b was amplified in 25 μL PCR runs using the H16064 and L14910 primers and thermal cycling protocol previously described [DNA was extracted and quality checked as described above. For 56 escribed . PCR proC. adamanteus  a ONF , to be ces from ). We conI NALMA; ). We conI NALMA; . The thrTo characterize A–B divergence at the microgeographic scale, we used proteomic, genetic, and morphological data to compare the ONF and JC populations, which were only ∼225 km apart. We used RP-HPLC to show that each population was monomorphic for their respective venom phenotype A, with acytochrome b sequence for 17 ONF (type A) and 9 JC (type B) individuals  and performed Kruskal–Wallis rank sum tests on each morphological character by venom type as previously described [p < 0.001) than type B individuals  depth of injection may not matter for type A venoms (or at least may be less important relative to type B venoms) and (2) narrower heads may be a consequence of prey differences and/or a reduction in the volume of venom needed given the increased toxicity of type A venoms. Interestingly, similar work in type A and type B Mojave Rattlesnakes (C. scutulatus) did not find significant differences in HW, HL, IF, or FL between type A and type B individuals, although trends did exist for type A individuals to have longer fangs and potentially wider heads [C. horridus and C. scutulatus individuals suggests that these morphological differences may be prey specific rather than venom-type specific.To determine whether venom expression differences were integrated with morphological characters also associated with feeding, we measured HL, HW, IF, FL and SVL for 33 preserved escribed . Type A ividuals A. AlthouB snakes B, indica ecology ,39. Marg ecology  previousC. horridus may represent independently evolving lineages, perhaps due to incipient ecological speciation. Alternatively, these differences could reflect incipient allopatric speciation as these populations occur on either side of the Suwannee River, a known biogeographic barrier for continental and peninsular Florida organisms [Crotalus horridus, however, has a very large geographic range, and ecological speciation comes with explicit predictions. Isolation by environment (IBE) should be much greater than isolation by distance (IBD) if ecological differences are leading to reproductive isolation [Overall, we identified fixed venom differences, a deep phylogenetic split dating back >1 Ma  and disrganisms , includirganisms ,38. The rganisms . Althougrganisms . With ousolation . To deteC. horridus and detected 86 type A individuals and 172 type B individuals  and environmental  space  space . For thes) space A, the meC. horridus. Type A habitat suitability was positively correlated with mean temperature of the wettest quarter and minimum temperature of the coldest month, the two most informative variables in the model, whereas these variables had relatively low contributions in the type B model (<10%) and were negatively associated with type B habitat suitability. Previous work showed that the distributions of A–B venoms in Mojave Rattlesnakes  was correlated with minimum temperature of the coldest quarter and mean temperature of wettest quarter [Temperature appeared to be a key factor in determining the distributions of type A and B venoms in  quarter , consist quarter ,28. In tC. oreganus) found that biotic information about local prey species explained more variation in venom expression than abiotic environmental data [C. horridus across their range to compare prey items in regions where C. horridus was monomorphic for type B to regions where C. horridus was monomorphic for type A (regions where C. horridus was polymorphic in venom type were excluded). We found 130 type B records but only 10 type A records  were ∼33% of all prey items recorded for type B animals and were notably absent from the type A records. Type B venoms, therefore, may be locally adapted for Cricetid rodents, and perhaps type A venoms are locally adapted to a different prey species and/or abiotic conditions. Toxicity and digestive assays quantifying these differences in natural prey items are needed to test these hypotheses; although interesting and ultimately necessary to characterize the source of ecological divergence (if present), such work was beyond the scope of the present study.Type A and B venoms, however, could also be locally adapted for different prey species or genetically distinct populations of the same species, and the relationship with temperature may simply correlate with local prey community composition. For example, previous work in Pacific Rattlesnakes  or if reproductive isolation between venom types broke down at larger geographic scales.The identified significant differences in niche space, accompanied with differences in multiple, putatively adaptive phenotypes in venom and head morphology, again suggested incipient ecological speciation. Assessing the degree of reproductive isolation is required when investigating putative species boundaries in wide-ranging taxa, especially along contact zones ,91. Thercytochrome b for 30 type A and 26 type B individuals across the range and constructed a Bayesian phylogeny  could aed above , nuclearC. horridus may represent distinct, reproductively isolated lineages due to incipient ecological speciation or differentiated populations within a single species. Although we found significant genetic, proteomic, morphological, and environmental differences between type A and type B C. horridus at microgeographic scales , the lack of reciprocal monophyly among venom types range-wide suggested varying intensities of gene flow and an overall lack of reproductive isolation across the range. Speciation is a continuous process [C. horridus.We used a combination of genetic, proteomic, morphological, and environmental data to test whether type A and type B  process , and spe process , but res process . To addr process  recently