Geomys arenarius, a subterranean rodent endemic to the northern Chihuahuan Desert. G. arenarius is restricted to sandy soils and are considered to have a disjunct distribution. Two subspecies are recognized: G. a. arenarius and G. a. brevirostris. We used multilocus nuclear (amplified fragment length polymorphisms) and mitochondrial DNA (ND2) sequence data to uncover patterns of genetic diversity within and among populations of G. arenarius. We evaluated correspondence of genetic patterns to traditionally accepted subspecies boundaries, mapped the distribution of potentially suitable soils to identify barriers or corridors to dispersal and to guide future survey efforts, provided evidence that could be used to recognize distinct population segments, and quantified genetic diversity within populations. Both datasets were largely concordant and demonstrated hierarchical patterns of genetic divergence. The greatest divergence was consistent with the two recognized subspecies. Mapping of potentially habitable soils revealed likely barriers to dispersal contributing to the allopatric pattern of geographic distribution and areas, which may be occupied by G. arenarius but not yet documented. Because G. arenarius is restricted to soils with high sand content, and these habitable soils are disjunct within the region occupied by this species, historical factors that impacted soil deposition and deflation likely contributed to the observed patterns of genetic divergence. Genetic diversity was higher within populations of the southern subspecies (G. a. arenarius) compared to G. a. brevirostris. This may be due to a greater availability of continuous suitable soils within the range of G. a. arenarius or higher density due to greater food availability —both of which could allow for a higher effective population size.The biogeographic history of the Chihuahuan Desert is complex, driven by numerous physiographic events and climatic changes. This dynamic history would have influenced the flora and fauna of the region including the desert pocket gopher,  Geomys arenarius, is a burrowing mammal endemic to the biogeographically complex Chihuahuan Desert. Multilocus nuclear and mitochondrial DNA sequence data revealed concordant population structure within this species. Distribution of likely habitable soils is consistent with population structure, and the population structure is consistent with current subspecific taxonomy.The desert pocket gopher,  Considered to be among the world's most biologically diverse deserts  feed mostly from their underground tunnels and are generalist herbivores. Geomys arenarius in Mexico was documented to consume both monocots and dicots in 10 plant families  consumed mostly grasses  along with the cactus Opuntia  compared to those from further south. Later, Williams and Genoways  as belonging to G. bursarius showing that morphological characteristics are not always reliable in defining taxonomic boundaries in this genus. Hafner and Geluso  evaluate the correspondence of genetic patterns to the traditionally accepted subspecies boundaries, (2) map the distribution of potentially suitable soils to identify barriers or corridors to dispersal and to guide future survey efforts, and (3) to inform conservation priorities by providing evidence that could be used to recognize distinct population segments  and by quantifying the relative degree of genetic diversity within populations.The goal of our study was to document the geographic patterns of population genetic diversity of 22.1G. arenarius were obtained representing almost all of the known populations of both subspecies .Samples were obtained by trapping using Macabee and Victor gopher traps and from tissue loans from the New Mexico Museum of Natural History and Science (specimens have since been transferred to the Southwestern Museum of Biology). Tissues from specimens collected near the Samalayuca dunes were imported into the United States by approval from the USFWS #2021ME2698399). Trapping was conducted following the American Society of Mammalogists guidelines , those from near the U.S./Mexico border (which apparently have not been documented since 1959), and those from western Doña Ana Co., NM .2.2AseI (New England Biolabs), 20 units of EcoRI (New England Biolabs), and 1× restriction enzyme buffer. Ligations were performed by adding 75 pmoles each of two double‐stranded adapters EcoRI (5′‐AATTGGTACGCAGTCTAC‐3′/5′‐CTCGTAGACTGCGTACC‐3′) and AseI (5′‐TACTCAGGACTCAT‐3′/5′‐AGTCCTGAGTAGCAG‐3′), 4 μL of 10× ligation buffer, 3 units T4 DNA ligase (New England Biolabs), and 12 μL of H2O to restriction digestion products and incubating for 16 h at 160°C. Ligation products were diluted by adding 160 μL of 10 mM Tris (pH 8.5). A subset of ligated fragments was amplified by polymerase chain reaction (PCR) using preselective primers . Amplifications were carried out in 50‐μL reaction volumes containing 10 μL of diluted ligation product, 0.15 μM of both preselective primers, 1× buffer, 1.5 mM MgCl2, 0.8 mM deoxynucleotide triphosphates, and 2.5 units of GoTaq® DNA polymerase (Promega). Amplification conditions included an initial step of 72°C for 60 s followed by 20 cycles of 94°C for 50 s, 56°C for 60 s, and 72°C for 120 s. Five microliters of the preselective PCR products were diluted in 90 μL of 10 mM Tris (pH 8.5) and used as the template for the selective PCRs. A total of 25 selective primer pairs  were tested on a subset of individuals prior to selecting eight pairs for use with all individuals. These included EcoRI‐CAC paired with AseI‐TAT, TCA, TCC, TCT, TGA, TGG, TGT, and TTC. The following criteria were used in the selection of these eight primer pairs: the production of clearly discernable 70–400 bp fragments with a distribution of approximately 1–5 fragments for every 20 bp (to minimize the chance of homoplasy) and an absence of over‐amplified fragments which tend to minimize the amplification of other fragments. Selective PCR amplifications were carried out in 25 μL reaction volumes containing 5 μL of diluted preselective product, 0.15 μM both selective primers, 1× buffer, 1.5 mM MgCl2, 0.8 mM deoxynucleotide triphosphates, and 1.25 units of Taq DNA polymerase. The thermal profile for selective reactions was as follows: 24 cycles of 94°C for 50 s, 65–56.6°C (0.70°C reduction for 2nd through 13th cycle) for 60 s, and 72°C for 120 s followed by 23 cycles of 94°C for 50 s, 56°C for 60 s, and 72°C for 120 s. The EcoRI primer used in the selective reactions was fluorescently labeled. Selective PCR products were visualized  using a Beckman‐Coulter CEQ8000 Automated Genetic Analysis System . Only AFLP fragments that could be unambiguously scored as present or absent were included in the data set.The AFLP protocol was modified from Vos et al. . Fifty nPopulation structure was assessed using principal coordinate analysis (PCoA) in GenAlEx 6.51 .The software package SNAPP  were calculated in GenAlEx 6.51 ]) and geographic distance. Genetic diversity within populations was measured using unbiased expected heterozygosity  and proportion of polymorphic loci (%P) calculated using GenAlEx 6.51.Pairwise Φ2.32, 0.16 mM each dNTP, 0.1 μM each primer, and 0.05 U Taq DNA polymerase (Qiagen). PCR reactions were performed as follows: initial denaturation at 95°C for 5 min followed by 40 cycles of 95°C for 1 min, 50°C for 30 s, 72°C for 1 min 30 s and a 72°C final extension for 10 min. PCR products were cleaned using ExoSAP‐IT (Affymetrics) and sequenced bi‐directionally, using Beckman‐Coulter chemistry, with the same forward and reverse primers as used for PCR. Sequencing products were cleaned by ethanol precipitation and visualized using a Beckman‐Coulter CEQ 8000 Genetic Analysis System. Sequences were aligned to a reference and visually inspected for errors and low‐quality base calls using Beckman‐Coulter software.A portion of the mitochondrial ND2 gene was amplified by PCR using the primers H6313 . Genetic distances (uncorrected p‐distance and Kimura 2‐parameter) between subspecies and between G. arenarius and its sister species G. knoxjonesi were computed using the program MEGA‐X  using QGIS  were identified and mapped using QGIS.Soil classification maps were created from the Soil Survey Geographic Database  were included in the final dataset of 74 individuals from eight sampled locations representing both subspecies. Of the 275 putative loci, 119 (43.3%) were polymorphic across the 74 individuals.G. a. brevirostris showed two clusters corresponding to specimens from White Sands and Socorro Co.  along axis 1 and specimens from Doña Ana and El Paso counties separated on axis 2 . Unbiased expected heterozygosity ranged from 0.027 (White Sands) to 0.083 (Doña Ana Co.) and the proportion of polymorphic loci ranged from 8.4% (White Sands) to 28.7% . GenBank numbers (MW558503–MW558567) are provided for each specimen in Appendix G. arenarius, there were 21 haplotypes with 69 polymorphic sites, 57 transitions, and 12 transversions. Diversity measures for subspecies, populations within subspecies , and overall, are given in Table G. a. brevirostris relative to G. a. arenarius. Compared to all other populations, the Samalayuca, MX population had the highest nucleotide diversity, greatest number of polymorphic sites, and second highest haplotype diversity (El Paso Co. had a slightly higher haplotype diversity). The White Sands population contained the fewest number of haplotypes, lowest haplotype diversity, lowest number of polymorphic sites, and lowest nucleotide diversity compared to all other populations.ND2 sequences (trimmed to omit missing data at each end) were 828 bp long and obtained from 64 of the 74 individuals of s MW55850–MW558567The median‐joining network of ND2 haplotypes Figure  showed tG. a. brevirostris formed highly supported reciprocally monophyletic clades. Genetic distance between subspecies (both uncorrected p‐distance and K2P distances) was 5%. For comparison, genetic distance between G. arenarius and its sister species G. knoxjonesi was 9%.The ND2 phylogenetic tree showed individuals representative of subspecies forming highly supported reciprocally monophyletic clades Figure . The twop > .05; Table G. a. arenarius appeared multimodal  from the distribution expected under population expansion (Table p > .05). For G. a. brevirostris, the mismatch distribution was clearly multimodal, but both Rg and SSD were nonsignificant (p > .05) indicating a good fit to the model of population expansion. For these two indices (Rg and SSD), calculations were not performed at the level of sampling localities because sample sizes were insufficient for most populations.Tajima and Fu's statistics were not significantly negative  inhabited soils included the Lark‐Transformer and Astrobee‐Lark association . In Doña Ana Co., NM, inhabited soils included Brazito loamy fine sand, Brazito very fine sandy loam, Anthony‐Vinton fine sandy loams, one occurrence in Glendale loam, and one occurrence in Agua clay loam (but immediately adjacent to Brazito very fine sandy loam). In El Paso Co., TX, inhabited soils included Gila fine sandy loam, Harkey loam , Made Land , and Saneli silty clay (adjacent to Vinton fine sandy loam and Brazito loamy fine sand). In addition to the locations in El Paso Co., TX which had accurate coordinates, locations southeast of Fabens had recorded coordinates that were inaccurate—however, we know these specimens were collected adjacent to an irrigation ditch that parallels Texas Highway 20. Soils in this area are classified as Glendale silty clay loam, Tigua silty clay, Glendale loam, or Harkey silty clay loam. The soils classified as clay loam included smaller areas of Glendale loam, Harkey loam, and Gila loam . In contrast, potentially suitable soils appeared to be relatively continuous within the distribution of G. a. arenarius for which soils data were available.Based on USDA soil surveys and SSURGO data, soils that we identified as potentially habitable by a Figure . Unsuita44.1G. arenarius, providing support for the geographic boundaries of the recognized subspecies and revealing further genetic subdivision within each subspecies. These patterns were reflected in both the nuclear AFLP and mitochondrial ND2 datasets. Additionally, the three approaches toward analyzing the AFLP data , each based on differing algorithms and assumptions, consistently identified the same patterns of hierarchical clustering. The greatest genetic divergence was between populations of Socorro Co. and White Sands to the north (representing G. a. brevirostris) and populations of Doña Ana and El Paso counties and Samalayuca, MX to the south (representing G. a. arenarius)—this pattern was consistent with currently recognized subspecies boundaries.Our study documents the phylogeographic and population genetic structure among most known populations of Determining an appropriate taxonomic level at which to recognize genetically distinct, allopatric populations is largely subjective because of the nature of evolutionary divergence and subsequent lack of universally accepted definitions or concepts for these entities. Genetic and phenotypic divergence among populations often occurs along a continuum, parts of which can be recognized as distinct population segments and, more formally, species (or subspecies) which can be supported by various lines of evidence  but were distinct from the Samalayuca, MX samples. Although both AFLP and mtDNA data revealed five genetically distinct populations, the patterns differed between the two subspecies. Within G. a. brevirostris, the two AFLP‐defined populations were reciprocally monophyletic in the mtDNA phylogeny. Within G. a. arenarius, the three AFLP‐defined populations were not reciprocally monophyletic in the mtDNA tree but were nonetheless genetically distinct based on a complete lack of shared mtDNA haplotypes.Both nuclear and mitochondrial datasets showed further subdivision within each subspecies. Within G. arenarius as evidence of clinal variation from northern‐most to southernmost locations, suggestive of gene flow between nearby G. knoxjonesi and G. arenarius. However, this interpretation appears to conflict with their reported genetic similarity coefficients which show the G. knoxjonesi population at Fort Sumner to be least similar to the adjacent Socorro Co. population of G. arenarius. We view their allozyme data as being compatible with genetic drift acting on shared ancestral polymorphisms rather than evidence of clinal variation which would require ongoing gene flow among populations that appear to be disjunct. Our data indicated that the White Sands and Socorro Co. populations are allopatric and most closely related to one another relative to other populations. This pattern of relationship is consistent with figure 3 of Hafner and Geluso  would be needed in order to distinguish between isolation by distance and reduced of gene flow due to the potential barrier itself.Within the Rio Grande river valley there exists an almost continuous distribution of soils with high sand content, and sampled populations within this region  is unknown, but it cannot be ruled out that the White Sands and Socorro Co. populations were once connected along the ancestral Rio Grande River valley west of the Oscura and San Andres mountains. Given the 5% mitochondrial divergence between the subspecies of G. arenarius, it is likely that at least some of these changes occurred during a time in which G. arenarius inhabited the region. We did not date the divergence between subspecies using mitochondrial DNA sequences given the uncertainty in mutational rate of geomyid rodents  is challenging to explain. The Rio Grande river of New Mexico did not drain into the Gulf of Mexico until approximately 800,000 years ago when it joined the Pecos River. Prior to this, the Rio Grande emptied into closed basins  which were formed by the opening of the Rio Grande rift 35 million years ago. Over time, the ancestral Rio Grande progressively integrated basins from north to south, eventually reaching Texas around 2 million years ago, at which time the river bifurcated and began flowing to the east side of the Franklin mountains—spilling through Fillmore Gap between the Organ and Franklin Mountains  despite the terrain. Given the apparent ability of G. arenarius to remain genetically connected over the terrain in this area, we cannot dismiss connectivity between the White Sands and Socorro Co. populations east of the Oscura Mountains during a time when soils within this area may have been somewhat more conducive to gene flow. The lack of data on the historical distribution soils precludes further evaluation of these alternate hypotheses.Alternatively, the connection between White Sands and Socorro Co. populations may have been to the east of the Oscura Mountains. Within this area, these populations are separated by rugged terrain with unsuitable soils and a lava flow  which occurred only 5200 years ago Dunbar, , likely G. arenarius are difficult to access and have not been surveyed, so it is unknown whether the apparent lack of occupancy in these potentially habitable areas is due to unsuitable soils or merely the lack of collecting efforts. Given the complexities of soil classification, the coarseness by which soils are mapped in certain areas, the uncertainty regarding which soil characteristics best define habitability by G. arenarius, and the potential for gophers to occupy unsurveyed areas, the resulting map of likely habitable soils should be interpreted with caution, but could be used to guide future distributional surveys.Many of the areas with soils potentially suitable for 4.3G. arenarius—a rarely documented phylogeographic pattern. If these subspecies had experienced recent population expansion, the haplotype network would not show such geographically restricted haplotypes. Overall, there was no strong support for population expansion within either subspecies; however, many sources of error and low statistical power can make the inference of demographic histories from genetic data challenging , including those in the southwestern United States and northern Mexico  were lower within populations of  Kimura, . Given tG. arenarius has only been reported from the immediate vicinity of the Samalayuca dune field. The relatively high amount of genetic diversity of the Samalayuca, MX population suggests that G. arenarius may occupy (or have recently occupied) a much larger geographical area within Mexico than has been documented, perhaps within the Strauss sand sheet northwest of Samalayuca.Genetic diversity of the Samalayuca, MX population was higher than all other populations except Doña Ana Co., NM. This was unexpected given that 5G. arenarius, reflecting the dynamic geomorphological history of the northern Chihuahuan Desert, particularly those processes resulting in deposition and deflation of soils with high sand content required by this species. The deepest pattern of genetic divergence coincided with the geographic boundaries of the recognized subspecies—G. a. arenarius and G. a. brevirostris. Genetic diversity varied considerably among populations due to differences in population size or unique demographic histories. Although most populations of G. arenarius do not appear to be threatened significantly by urbanization or agriculture, some populations may be negatively impacted by continued loss of desert grasslands due to grazing, conversion for agricultural use, or climate change. Of particular interest is the Samalayuca, MX population which is known only from the vicinity of the Samalayuca dune fields ; formal analysis (lead); investigation (lead); methodology (lead); project administration (lead); resources ; writing – original draft (lead). Ana B. Gatica‐Colima: Resources (supporting); writing – review and editing (supporting). Philip S. Sudman: Conceptualization (lead); investigation ; methodology (supporting); project administration (supporting); resources ; writing – original draft (supporting); writing – review and editing (supporting). Ashley N. Kozora: Investigation ; methodology (supporting); writing – original draft (supporting); writing – review and editing (supporting).This work was supported by Tarleton State University.Figures S1 and S2.Click here for additional data file.Appendix S1.Click here for additional data file.Table S1.Click here for additional data file.


The demographic history of East-Central Europe after the Neolithic period remains poorly explored, despite this region being on the confluence of various ecological zones and cultural entities. Here, the descendants of societies associated with steppe pastoralists form Early Bronze Age were followed by Middle Bronze Age populations displaying unique characteristics. Particularly, the predominance of collective burials, the scale of which, was previously seen only in the Neolithic. The extent to which this re-emergence of older traditions is a result of genetic shift or social changes in the MBA is a subject of debate. Here by analysing 91 newly generated genomes from Bronze Age individuals from present Poland and Ukraine, we discovered that Middle Bronze Age populations were formed by an additional admixture event involving a population with relatively high proportions of genetic component associated with European hunter-gatherers and that their social structure was based on, primarily patrilocal, multigenerational kin-groups. By analysing 91 Bronze Age genomes from East-Central Europe, the authors discovered that Middle Bronze Age populations were formed by an admixture event involving hunter-gatherers and that the social structure of resulting population was primarily patrilocal. However, there is still extensive debate surrounding the scale and exact nature of these demographic events and how they affected the genetic makeup of different regions across Europe7.Currently, it is well established that the European gene pool has been shaped by several major demographic events, including the postglacial spread of hunter-gatherers8. Descendants of steppe pastoralists are thought to have replaced and admixed with the late Neolithic populations, which were characterised by large amounts of Anatolian farmer ancestry with additional low to medium levels of hunter-gatherer ancestry10. However, the Funnel Beaker Culture (FBC) and Globular Amphora Culture (GAC), major entities predating the arrival of steppe pastoralists associated with the later Neolithic in the region, are thought to have been long lasting, with some of their local variants continuing well into the Early Bronze Age 11. As no ancient DNA (aDNA) data are available from individuals associated with later populations, their genetic makeup can only be inferred from their 3rd millennium-BC counterparts. The northern and eastern parts of East-Central Europe followed slightly different trajectories, with populations associated with the sub-Neolithic forest zone13, characterised by high levels of hunter-gatherer ancestry  throughout the Neolithic. In these regions, Anatolian farmer ancestry was introduced along with steppe ancestry during the onset of the Bronze Age15. Similar patterns have been observed in other regions surrounding the Baltic Sea, such as southern Scandinavia and Gotland, where hunter-gatherer individuals (both in terms of lifestyle and genetic composition) of the Pitted Ware Culture (PWC) coexisted in close proximity (but without significant gene flow) with the FBC in the 4th millennium BCE and the Battle Axe Culture (BAC), the Scandinavian variant of the CWC, in the first half of the 3rd millennium BCE17.East-Central Europe, in particular, is a region often on the frontier of these events, resulting in a mosaic of genetically distinct populations associated with a variety of cultural entities. By the turn of the Bronze Age, this region was dominated by populations associated with the Corded Ware Culture (CWC) and Bell Beaker Culture (BBC) and characterised by high levels of steppe ancestry20, are largely seen as continuations of groups associated with the CWC and BBC23. In addition, steppe25 or the northern forest zone26 cultures have been suggested to have influenced, to some extent, the SC.The cultural landscape of Early Bronze Age (EBA) in East-Central Europe (2400–1800 BCE) is widely believed to be a direct continuation of processes that started during the onset of the epoch. For example, the cultural entities present in the region, such as those associated with the Mierzanowice, Iwno and Strzyżów archaeological cultures 27. This study focuses on MBA individuals associated with two of these variants  in the region (1800–1200 BCE) was in turn dominated by the Trzciniec Cultural Circle (TCC). This cultural phenomenon extended from the Oder River drainage basin to the Desna and Seym River basins (ca. 1200 km) and from the Baltic seashore to the Prut basin (ca. 750 km), exhibiting several territorial variantsnts Fig. : the TrzThis study, explores genetic affinities between individuals from various EBA and MBA cultures and their genetic relations to populations of preceding cultural complexes as well as possible kinship structures within MBA societies. To achieve this we conducted population genetic analyses using 91 newly generated genomes from Bronze Age individuals associated with EBA and MBA cultures from modern-day southern and south-eastern Poland and western Ukraine.n = 3), MC (n = 15), SC (n = 6), TC (n = 62) and KC (n = 5) cultures.Out of the 175 Bronze Age individuals screened, 92 produced enough data (>0.018 genome coverage) to be retained for further analysis and/or deeper sequencing. An additional 100 libraries, including 37 uracil-DNA-glycosylase (UDG)-treated libraries, were created and sequenced for the selected individuals. With the exception of two libraries from two different individuals, all libraries displayed characteristic post-mortem damage at the 5′ and 3′ ends of aDNA fragments and low contamination levels, as estimated by mitochondrial sequences and X chromosome sequences in males, where sufficient coverage was obtained  exhibited closer affinity with individuals associated with various CWC groups rather than the BBC populations according to the f3 and D statistics  associated with the MC, IC and SC are genetically similar to their direct cultural predecessors (such as the BBC and CWC), as indicated by the principal component analysis (PCA) plot Fig. . The resf3 statistics indicate that the population sharing the most genetic drift with this individual was the GAC, followed closely by the FBC , it might indicate that such isolated populations lasted far longer than previously reported. This hypothesis is supported by the archaeological record, which shows that some Neolithic cultures, most notably the GAC, lasted well into the Bronze Age21.One IC-associated male from Łojewo (poz502) deviated from the general pattern, as he was genetically closest to the Middle and Late Neolithic populations, which occupied the same space on the PCA plot and displayed similar admixture proportions. The results of 26. Therefore, the definition and associations of the SC with any genetically distinct population warrants further exploration targeting a broader selection of individuals attributed to this culture.Similar to poz502, two of the SC-associated males (poz794 and poz758) differed genetically from other EBA individuals. These two males were closer to the hunter-gatherer space in the PCA plot Fig.  and showf3 and D statistics, which indicate that when analysed separately, KC and TC individuals do not, in majority of cases, display any statistically significant closer genetic affinity to either of the two populations  obtained for pair consisting of IC and Neolithic Baltic hunter-gatherers (NBL). Similarly high pvalues were found for other pairs including IC and other hunter-gatherer populations: Western Hunter Gatherers (WHG), PWC hunter-gatherers from Gotland, hunter-gatherer buried in BKG context (BKGout) and hunter-gatherer populations predating the NBL (HGBL) . These results are in accordance with the archaeological hypothesis that the IC greatly contributed to the emergence of the TC27. However, this finding should be interpreted with caution, as only one individual associated with the IC had sufficient coverage for inclusion in qpAdm. High fit values were also obtained for pair of populations, containing individuals from modern day Estonia associated with the CWC, as the EBA predecessor and PWC, as the source of hunter-gatherer ancestry (p = 0.11).Interestingly compared to EBA populations, the MBA individuals were closer in the PCA space to various hunter-gatherer populations from Europe Fig. , somethiers Fig. . This suers Fig. . When users Fig.  with thep > 0.9) including CWCes in addition to various hunter-gatherer and Neolithic populations  associated with the SC, that displayed closer genetic affinity to the MBA populations both came from the south-eastern part of modern-day Poland (Supplementary Text); of these two, the individual with a direct date (poz794) predated the MBA samples analysed here. This observation suggests that the contact zone described above is not the only place where admixture took place and/or that the process was more geographically diffused. Either is plausible, given the range and duration of exchange networks seen in the EBA25. However, the genetic shift toward an increase in WHG ancestry cannot be explained by additional migration from the steppe, a notion that we previously proposed based solely on mitochondrial data28. This idea is not supported by any indication of increase of steppe ancestry as calculated by three-way qpAdm modelling including WHG, AN and YAM as best proxies of major ancestries in European gene pool  and admixture proportions  show that the proportion of hunter-gatherer ancestry decreased slightly over time , was found to belong to the same mitochondrial haplogroup as the two children28 and thus could potentially be their mother or an additional sibling. The MBA population associated with the TC appeared to be slightly less diverse than its EBA predecessors, according to within-group pairwise f3 statistics used for diversity estimation. This result was not driven by sites with multiple related individuals, as a similar f3 distances distribution was found in pairs of individuals from different sites , which further supports the notion of patrilocality. In some cases, such as Pielgrzymowice grave no. 9, the burial pit/chamber was used for an extended period35. The prevalence of collective kin-based burials was interrupted by the arrival of steppe pastoralists in the turn of the Neolithic and Bronze Age, leading to the development of more individualised societies, such as those associated with the BBC and CWC. The practice of collective burials never disappeared completely as collective burials occurred throughout the EBA30; these graves have been shown to contain the remains of kin groups44. We identified one such example at the Hrebenne cemetery and another possibly at the Zubowice site ; both of these collective graves were associated with the MC. The scale of this phenomenon in the TC is, however, much more similar to what was present in Neolithic societies and could be interpreted as a proof of the re-emergence of older traditions.The idea that collective burials represent patrilineal kin groups is in accordance with previous observations of earlier Neolithic populations in Europe46. Hunter-gatherer societies, on the other hand, are commonly thought to have been much more fluid in their postmarital residence preferences, with the majority of modern and historic hunter-gatherer groups displaying bilateral practices47. Due to the scarcity of samples, we could not assess the postmarital residence preferred by ancient European hunter-gatherers. On the other hand, recent data obtained on Middle Neolithic farmers from Western and Central Europe show that collective burials in these populations usually comprised related individuals of patrilocal descent48, supporting the notion that those populations or their descendants also played a role in the events that resulted in the genetic shift in the MBA.Patrilocal social structure and male-dominated migrations have been linked with populations and events associated with steppe pastoralists and their descendantsThe results presented here indicate that EBA people in East-Central Europe buried in the MC, IC and SC contexts were most likely the direct descendants of preceding populations associated with the CWC. In addition, the MBA populations were dominated by patrilocal lineages of apparent hunter-gatherer origin, practising burial customs that, while displaying some elements associated with steppe pastoralists, were most analogous to those practised in the Middle and Late Neolithic cultures, predating the arrival of steppe pastoralists into Central Europe. We conclude that after the introduction of steppe ancestry into European populations, hunter-gatherers and farmers remained genetically distinct in some regions and influenced later demographic and cultural processes, as seen in the genetic composition of MBA populations.49. They included TC-, KC-, MC- and IC-associated individuals (Supplementary Data n = 62), KC (n = 5), MC (n = 15), SC (n = 6) and IC (n = 3)  Table . DetaileSample preparation, DNA extraction and genomic library preparation were conducted in a dedicated aDNA laboratory at Adam Mickiewicz University in Poznan, Poland. The laboratory followed established guidelines for aDNA facilities and utilised UV lamps (254 nm), positive air pressure, and high efficiency particulate air (HEPA)-filtered laminar flow hoods. The laboratories, equipment and nonbiological reagents were regularly decontaminated using bleach and/or DNA-away (ThermoScientific) and UV irradiation.50 but with the sodium dodecyl sulfate (SDS) in the extraction buffer exchanged for 1 M urea51. The final elution was performed in 100 µl of elution buffer (EB) (Qiagen).Prior to DNA extraction, bones and teeth were cleaned with 5% NaOCl, rinsed with sterile water and finally decontaminated with UV irradiation  for 60 min on each side in a cross-linker. A Dremel® drill with diamond cutting wheels was used to slice the petrous parts of the temporal bone in half, exposing the structures of the otic capsule. We then drilled these structures and tooth roots to obtain 50–150 mg of bone powder for DNA extraction. DNA was extracted using a silica-spin column protocol53, omitting the initial nebulization step due to the fragmented nature of aDNA. In addition, for the selected samples (see Dataset S1 for the library types per sample), UDG-treated libraries were also prepared using UDG and endonuclease VIII (endo VIII) treatment to cut postmortem deaminated sites54. From each DNA extract, 1–5 genomic libraries were prepared, and one negative library control was processed for every 8–12 aDNA libraries. Each library was then amplified using five to seven polymerase chain reactions (PCRs) for 12–16 cycles. The amplifications were used to introduce single indices and performed in 25 µl containing a mix of 3 µl of the DNA library template with 12.5 µl of 1 × AmpliTaq Gold® 360 Master Mix (Life Technologies), 0.5 µl of PCR primer IS4 (10 mM) and 0.5 µl of indexing primer (10 µM)55. Negative controls were included in both the library preparation and PCR steps. All five to seven PCRs per individual were pooled and purified with AMPure® XP Reagents (Agencourt-Beckman Coulter) according to the manufacturer’s protocol. Pooled libraries were then quantified using the High Sensitivity D1 000 Screen Tape assay on a 2200 TapeStation system (Agilent). The genomic libraries were sequenced at the SciLifeLab SNP & SEQ Technology platform in Uppsala or at the National Genomics Infrastructure (NGI) in Stockholm using (in both locations) the Illumina HiSeq 2500 with v2 paired-end, 125 bp chemistry or HiSeq X Ten with v2.5 paired-end, 150 bp chemistry. The processed negative controls did not yield any DNA and were not sequenced.Twenty microlitres of DNA extract was converted into single-indexed blunt-end Illumina genomic libraries using P5 and P7 adapterswww.mycroarray.com). The capture utilised a subset of probes targeting 15,000 SNPs with the highest average per-sample coverage from the 1240k panel used in56. Prior to hybridisation, the DNA libraries (each ≈100 ng) were concentrated to dryness using a Speedvak concentrator (Savant) and resuspended in 6.8 µl of double-distilled water (ddH2O). Two rounds of enrichment were conducted according to the manufacturer’s protocol (v2.3.1) with minor changes57. Primers and IS5 and IS6 from53 as well as PISI and AIS4 from57, were used in the post-capture amplification of the libraries. The second pair was used to allow sequencing of one blunt-end Illumina library on an Ion Torrent Personal Genome Machine (Ion PGM) system . The library was then sequenced with the Ion PGM system at the Molecular Biology Techniques Laboratory, Faculty of Biology, Adam Mickiewicz University, using the Ion Torrent One Touch System II and the Ion One Touch 200 template kit v2 DL according to the manufacturer’s recommendations. Sequencing was performed on the Ion 318TM Chip Kit v2 using 520 flows and the Ion PGM Hi-Q sequencing kit v2.Seven genomic libraries (see Dataset S1 for the library types per sample) underwent an enrichment procedure by hybridisation capture using biotinylated probes supplied by MYcroarray  and the adapters were removed using AdapterRemoval v2.1.760 with the following nondefault parameter settings: -l 16500 -n 0.01 -o 261. Duplicate reads were detected and collapsed using a modified version of FilterUniqueSAMCons.py59. In addition, reads with reference identity <90% or read length shorter than 35 bp were removed.Finally, trimmed and merged reads were mapped to the hs37d5 version of the human reference genome using Burrows-Wheeler Aligner v0.7.17-r118852. The ratio of reads that mapped to sex chromosomes was used to determine the genetic sex of each individual62. For samples that underwent multiple rounds of sequencing, the mapped bam files from each library were merged with the use of the merge option in samtools v1.563. The merged bam files underwent duplicate read removal and basic statistic calculations were performed as in the case of single libraries.The number of reads, the proportion of reads that mapped to the human genome, average read length, clonality, and mean depth of coverage were calculated to assess each library’s quality64 and the read length distribution were calculated using MapDamage v2.0.865.To assess the authenticity of the data, several methods were applied both for the individual and merged bam files. The signature of deamination at the 5′ and 3′ read ends66 was used with default parameters to calculate the posterior probability of mtDNA contamination using a Bayesian approach. For this purpose, the reads were remapped against the rcrs mitochondrial sequence67, following the same procedure as in the case of the whole human genome, and consensus mtDNA sequences were called with the use of the doFasta tool of the ANGSD v0.910 package68; reads were accepted only if they had a mapping score of 30, a minimum base quality of 20, and positions with a minimum coverage of 3.ContamMix v1.0.10 contamination R script included in ANGSD package. Any individual libraries and merged datasets for which contamination estimates exceeded 0.2 and/or the frequency of postmortem damage fell below 25% at the 5′- and 3′-ends were excluded from further analyses.For samples determined to derive from males, X-chromosome-based contamination estimation was performed using the 69 online tool based on the PhyloTree phylogenetic tree build 1770.Consensus mtDNA sequences were called as described above for mtDNA contamination estimates. The obtained fasta files were used to assign mtDNA haplogroups utilising the Haplogrephttps://isogg.org/). The genotypes were called based on the genotype likelihood calculated with the use of the aDNA_GenoCaller.py script71, which takes into account the post-mortem damage estimated with MapDamage. The genotypes in low-quality  transition sites were used only when C or G alleles were found. When a T or A allele was found in transversion sites that did not have those alleles according to the reference dataset, they were assumed to be a result of post-mortem deamination and labelled C and G, respectively. In addition, where damage-repaired libraries were available, the transitions were also called with aDNA_GenoCaller.py script and merged with the genotype data.For the individuals determined to be genetic males, the most likely Y-chromosome haplogroups (Y-DNA) were assigned based on the genotype calls from 69 391 no-indel branch determining SNPs obtained from the International Society of Genetic Genealogy collection :616 938 autosomal SNP sites from the Affymetrix Human Origins/The Human Origins SNP Array complete dataset containing genotypes for 2583 individuals representing 214 populations worldwide73 whole genome set matching 1,240,000 capture data available for a large portion of comparative ancient samples.Simons Genome Diversity Project (SGDP): 1,001,613 autosomal nonfunctional SNPs with minor allele frequency (MAF) < 0.005 from the Simons Genome Diversity Project741k: 6,864,699 autosomal SNPs from the 1000 Genomes Project74, of which the minor allele frequency in the Yoruba (YRI) population was at least 0.155.1k_trv_YRI: 1,622,524 autosomal transversions from the 1000 Genomes Project74.1k_X:3,357,504 SNP from outside the pseudoautosomal region of the X chromosome from the 1000 Genomes Project75 and NgsRelate76 were used to estimate relatedness between pairs of individuals.Both READ71.The genotype likelihoods for the SNPs from the 1k and 1k_X panels for NgsRelate analysis were calculated with the use of aDNA_GenoCaller.py for transversions in the merged bam files and aDNA_GenoCaller.py script for transitions if damage-repaired libraries were present77 (0.1.16)-thin 2500 option. Then, NgsRelate was used on each pair after annotating the vcf file with allele frequencies from the West Eurasia populations from the reference panel (Supplementary Data To maximise the number of overlapping SNPs while filtering them for linkage disequilibrium (LD), all possible combinations of individual pairs were merged and thinned separately with the vcftoolsThe genotypes for the SNPs from the 1k panel for READ analysis were acquired from genotype likelihoods obtained as above and filtered similar to the Y chromosome genotypes. Then, READ was used on the haploidized final dataset after filtering out SNPs with a minimal allele frequency below 0.1  overlapping SNPs were considered. Age at death; genetic sex; R0, R1 and R2 values for autosomal data; the difference between θ values for autosomal and X-chromosome data; and mitochondrial and Y-DNA haplogroups were used to determine the exact kin relation where possible. In case of conflicting reconstructed degree of kinship between the two used methods the results of NGSrelate were found to be more reliable. The parent-offspring and sibling pairs were first distinguished with the uniparental markers and age at death . Then, where available, the degrees of kinship to other related individuals were compared. For example, if an individual was found to share 1st-degree kinship with one individual from a pair of known siblings and 2nd-degree with the other, the individual in question was determined to be child of the first sibling and niece/nephew of the second. Similarly, if 2nd-degree kinship was detected with only one individual from a pair of known siblings, it was interpreted as a grandchild of this individual, as the grandparent, uncle or aunt, and niece or nephew would all be equally related to both siblings. Finally, to verify assumptions based on the abovementioned factors, or in the case of their absence, X chromosomal θ and autosomal k1 were used The summary of all the pairs of individuals found to be related can be found in Supplementary Data smartpca program in the EIGENSOFT package78 was used to estimate eigenvectors in the HO dataset. The ancient samples that overlapped with at least 98% of the reference panel SNPs were projected onto the first two principal components inferred from modern samples with the following nondefault settings: altnormstyle: NO, numoutlieriter: 0, numoutlierevec: 0, lsqproject: YES, shrinkmode: YES.The PCA was carried out as an initial assessment of the genetic affinities of the analysed populations. The To assess, whatever the use of capture data in the five cases where it was merged with shotgun data could cause any bias, in three cases where sufficient amount of both types of data were present, they were analysed both separately and combined (see results in Supplementary Information text).79 on the same set of individuals as included in the PCA. Prior to the analysis, the dataset was first limited to transversions and then pruned for LD with the use of the–indep-pairwise 200 25 0.4 option from PLINK toolset (v1.90b5)80. Finally, clustering was performed on samples that overlapped with at least 85% of the final set of 70 149 SNPs for K = 3 to K = 14 in 10 replicate runs with different random seeds for each K. The results were visualised with the use of pong v1.4.981 to bundle together the membership coefficient matrices (Q) from different replicates and the different numbers of clusters. The K values with the smallest standard error of the cross-validation error estimate for the selected set of individuals  were then selected and discussed in detail; the results for all K values of all samples can be found in the Supplementary Materials (Supplementary Data Unsupervised model-based clustering was performed with the use of ADMIXTURE (v1.3) softwaref3- and D-statistics, implemented with the qp3pop and qpDstat tools from ADMIXTOOLS82 software, respectively. All analyses were performed on data genotyped to the 1k_trv_YRI reference dataset, using the African Yoruba population as an outgroup.Various analyses were performed to quantify shared drift between individuals and/or populations as their divergence from an outgroup population with the use of outgroup Individuals determined to be genetic outliers, based on their position on PCA space and admixture analysis results, were not included in the determination of populations based on individuals’ association with archaeological cultures or horizons. In addition, only one individual (with the highest genome coverage) was selected from each group of individuals determined to share direct genetic kinship.qp3pop with default settings was used to test individuals’ assignment to populations in the form of f3 and f3. Then, shared drift between pairs of individuals, except for 1st- and 2nd-degree relatives, was measured in each population to assess within-group genetic diversity83 in the form of f3. The results  to track the temporal changes, and f3 for direct comparison on population level 15. The temporal changes were displayed on graphs for which trend lines were obtained with geom smooth tool from ggplot2 package in R. The conditional means were calculated both for all the individuals and after removing outliers and displayed with 95% confidence intervals.To determine if sex bias was present in the gene flow from the putative source of hunter-gatherer ancestry during the formation of the TC, the data was also genotyped to the 1k_X dataset, which represented the X chromosome of the 1 000 Genome Project and was filtered similar to the autosomal data. Then, qpDstat with default settings was applied to verify various demographic scenarios by testing the analysed individuals against pairs of potential ancestry sources in the form of D. This analysis was used to determine which ancient population out of all the analysed populations was the best proxy for the source of hunter-gather ancestry in the TC and post-CWC populations , and the results were plotted separately for each sex (Supplementary Data f3 and D statistic results, various demographic scenarios of TC origin were tested with the use of qpAdm tool from the ADMIXTOOLS82 package with the following nondefault parameters: details: YES, summary: YES, allsnps: YES, and maxrank: 7. The SGDP reference dataset was used, and additional ancient individuals were included as outgroups. The right file with the outgroup population comprised the Onge, Papuan, Han, Mixe, Karitiana, Natufian, and Chukchi populations from the dataset and 25 ancient individuals from 13 hunter-gatherer populations worldwide with addition of Neolithic Anatolians (Supplementary Data 37. The models in which the source populations were comprised of only single individuals or had a nested p value > 0.05 were reported however approached with caution and not considered plausible (Supplementary Data p value > 0.05. A separate analysis was performed for the corresponding two-way model. When the nested model did not include WHG, the ancestry was set to 0 (Supplementary Data f3 values.Based on the Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Datasets 1-21Reporting Summary


Conservation genetic management is becoming increasingly important for safeguarding and restoring wildlife populations. Understanding how the intensity of intervention influences genomic components of fitness is therefore essential for supporting species viability. We investigate the impact of contrasting management strategies on the genomic landscape of inbreeding and mutation load in captive populations of the scimitar-horned oryx. We reveal how several decades of management have prevented the formation of long runs of homozygosity and masked the expression of deleterious mutations. Our findings highlight the dynamics between inbreeding, mutation load, and population size and have direct implications for future management of threatened species. Oryx dammah), an iconic antelope that has been subject to contrasting management strategies since it was declared extinct in the wild. We show that unmanaged populations are enriched for long runs of homozygosity (ROH) and have significantly higher inbreeding coefficients than managed populations. Additionally, despite the total number of deleterious alleles being similar across management strategies, the burden of homozygous deleterious genotypes was consistently higher in unmanaged groups. These findings emphasize the risks associated with deleterious mutations through multiple generations of inbreeding. As wildlife management strategies continue to diversify, our study reinforces the importance of maintaining genome-wide variation in vulnerable populations and has direct implications for one of the largest reintroduction attempts in the world.In an age of habitat loss and overexploitation, small populations, both captive and wild, are increasingly facing the effects of isolation and inbreeding. Genetic management has therefore become a vital tool for ensuring population viability. However, little is known about how the type and intensity of intervention shape the genomic landscape of inbreeding and mutation load. We address this using whole-genome sequence data of the scimitar-horned oryx ( Captive populations have become an essential insurance against extinctions in the wild . However212Alongside this, recent debate on the significance of neutral genetic variation in conservation biology has raised practical considerations for sourcing populations for restorations –20. For 2127303440th century, hunting and land-use competition led to their rapid population decline and eventual extinction from the wild  and the USA (n = 17), represent captive populations where genetic management practices are in place. The EEP population comprised individuals from zoological institutions across Europe. The USA population comprised individuals from both privately owned ranches and institutions within the AZA Species Survival Plan® (SSP). The remaining populations from the Environment Agency – Abu Dhabi originate from two genetically unmanaged collections in the United Arab Emirates (EAD A: n = 9 and EAD B: n = 15). Census sizes for the EEP and SSP population are approximately 619 and 223, respectively, while those for EAD A and EAD B are approximately 3,000 and 70. For further details on population origins, management strategies and sampling approach, please refer to SI Appendix, Supplementary Methods.We generated whole-genome sequence data for 49 scimitar-horned oryx from four ex situ populations. Two of these, the EAZA Ex Situ Programmes . Sequencing reads were mapped to the scimitar-horned oryx reference genome . Analysis of population structure using NGSadmix and PCAngsd detected differentiation between the four sampling groups . Individual admixture proportions highlighted two major ancestral source populations , with further hierarchical structure being resolved up to values of K = 4 , corresponding to the four ex situ groups. PCA distinguished EEP and USA populations as discrete clusters along PC2 and PC3, while EAD A and EAD B clustered separately along PC1 .High-coverage sequencing (~15×) was performed for 20 of the individuals and the remaining 29 were sequenced at a lower depth . Oryx from managed populations had significantly lower inbreeding coefficients (ROHF) than oryx from unmanaged populations .To investigate how genomic patterns of inbreeding vary with management strategy, we examined the ROH landscape across individuals . The aveWe also observed variation in the fraction of the genome in ROH of different length classes. There was a steep decrease in the genome fraction in ROH above lengths of around 6.25 Mb C. ROH loeN) . These patterns were reflected in estimates of mean pairwise nucleotide diversity which were also higher in managed  than unmanaged populations .As ROH lengths decrease, their underlying haplotypes are expected to have originated from ancestors further back in time . The genNe) , 48. In  classes D. Ne decSI Appendix, Fig. S7), results using annotations from SnpEff are presented here. We first estimated two components of mutation load; heterozygous and homozygous mutation loads for both weakly (missense) and highly (loss-of-function) deleterious mutations. The heterozygous mutation load was calculated as the absolute number of missense and LoF heterozygotes per individual. The homozygous mutation load was calculated as the absolute number of derived missense and LoF homozygotes per individual. Based on the assumption that most deleterious mutations are (at least) partially recessive . In direct contrast, the homozygous mutation load for both missense and LoF mutations was lower in managed than in unmanaged populations .To account for a scenario where deleterious mutations are approximately additive, we also calculated the total number of derived deleterious alleles per individual . Here, nThe scimitar-horned oryx was declared extinct in the wild in 2000, yet the species has persisted ex situ. Understanding how management shapes the genomic landscape of inbreeding and mutation load is essential for supporting species viability. We used whole-genome resequencing data to characterize ROH and putatively deleterious mutations in scimitar-horned oryx populations undergoing contrasting management strategies. Our study highlights the dynamics between inbreeding, mutation load, and population size and has broad-reaching implications for practical conservation management.eN. Interestingly, assuming a generation time of around seven years  when ROH are inferred using physical positions , the expen years , this di founded , 43. We The overall pattern of ROH lengths was qualitatively similar across populations, yet the absolute proportion of the genome in ROH was considerably lower in managed than unmanaged populations for all length classes. Long ROH are indicative of recent shared ancestry of the underlying haplotypes because recombination has had little opportunity to break them up –57. The eN, but also by genetic drift driving deleterious mutations to fixation in small populations. In line with this, we show that managed populations of oryx have higher nucleotide diversity and effective population sizes than unmanaged collections.We next shed light on the relationship between inbreeding, diversity, and deleterious mutations by exploring how mutation load compares across management strategies. At an individual level, we show that animals from collections employing genetic management practices have a higher heterozygous mutation load for both missense and LoF mutations than animals from unmanaged populations. Indeed, with lower levels of inbreeding—as observed in managed SHO populations—a greater number of heterozygotes are expected. Furthermore, theory and simulations predict that large populations will have higher frequencies of segregating deleterious mutations , 59, 60.The presence of segregating deleterious alleles within insurance populations may be considered a concern for conservation management. Indeed, there has been recent debate surrounding the risks associated with sourcing individuals for restoration from large, genetically diverse populations, given the higher expected levels of strongly deleterious variation , 19. How6164Rxy analysis. Instead, we find an increase in the homozygous mutation load for LoF mutations in unmanaged collections. This suggests that while the total number of alleles has remained unchanged, inbreeding has increased the homozygosity of highly deleterious variants. Consequently, unmanaged populations of oryx may carry a higher fitness cost associated with a greater burden of homozygous genotypes. In line with this, there is some anecdotal evidence of high disease prevalence and low juvenile survival in individuals originating from EAD B.In addition to the heterozygous mutation load, we also considered how both the homozygous mutation load and the total number of derived deleterious alleles varied across populations. Several recent studies have demonstrated reductions in the relative number of highly deleterious mutations in small versus large 21, 26, 37 SI Appendix, Supplementary Methods). Missense mutations are more likely to be weakly deleterious with higher starting allele frequencies than LoF mutations, and therefore are predicted to be more susceptible to accumulation by drift when population size is reduced , USA (n = 17), EAD A (n = 9), and EAD B (n = 15). The EEP and USA are captive collections undergoing genetic management practices, while EAD A and EAD B represent collections in the United Arab Emirates with no genetic management in place . Total genomic DNA was extracted between one and five times per sample using the DNeasy Blood and Tissue Kit . Elutions were pooled and concentrated in an Eppendorf Concentrator plus at 45 °C and 1,400 rpm until roughly 50 µL remained. Library construction was carried out using the Illumina TruSeq Nano DNA library preparation kit (Illumina). Twenty samples from across all four populations were 150 bp paired-end sequenced on an Illumina HiSeq X Ten platform at a target depth of coverage of 15×. The remaining 29 samples from three of the populations were 150 bp paired-end sequenced on an Illumina NovaSeq 6000 instrument at a target depth of coverage of 7× .Blood (in EDTA) and tissue (in 100% ethanol) samples were collected for whole-genome resequencing from 49 scimitar-horned oryx representing four ex situ populations: the EEP  using BWA MEM v0.7.17 . The resulting SNP dataset contained over 10 million polymorphic sites with a genotyping rate of 98%.Haplotype Caller and GenotypeGVCFs in GATK v3.8  were usee-6) with data in at least 60% of individuals (-minInd 30). We restricted this analysis to the 28 chromosome-length autosomes and included only regions with Phred quality and mapping scores over 30. Admixture proportions for the individuals in our dataset were calculated using NGSadmix. We performed admixture runs for ancestry clusters ranging from K = 1 to 6, with 10 runs for each K. The runs with the highest likelihood were plotted. The optimal K was identified based on the maximum value of the mean estimated ln probability of the data . We then performed a principal components analysis (PCA) using PCAngsd with the default parameters. Eigenvectors were computed from the covariance matrix using R v4.2.2.We characterized population structure using genotype likelihood-based approaches in NGSadmix  and PCAnthe data  and the the data . Two indFROH). ROH were called with a minimum length of 500 kb and a minimum of 50 SNPs using the --homozyg function in PLINK v1.9 . To ensure that our inbreeding estimates were not confounded by coverage, we compared FROH with the mean sequencing depth for each individual . Next, we ran linear models to explore the effect of management on inbreeding coefficients with FROH as the response variables and management strategy as the predictor variable. We also calculated FROH based on ROH inferred using bcftools roh and the following parameters: --AF-dflt 0.16 , -G 30, and -M 1.2 [cattle recombination rate, Mouresan et al. (r = 0.99) with our PLINK-based estimates .We used the filtered SNP genotypes to estimate inbreeding as the proportion of the genome in runs of homozygosoty  were calculated using the formula L = 100/(2 × g) (g) ago, respectively. These generations were chosen to capture the time-period during which the wild population of oryx went extinct and captive populations were established. As there is no linkage map for the oryx, we assumed a genome-wide, homogenous, mean recombination rate of 1 cM/Mb and used physical map lengths as opposed to genetic map lengths. For each time-period and for each individual, FROH was calculated as the sum of the ROH expected to coalesce in that time-period over the total autosomal assembly length (2.44 Gb). We then used measures of FROH to infer recent changes in effective population size across each population. For each time-period described above (t), we first calculated the average FROH for each population. We then estimated eN given the following expression where t is the maximum number of generations in that time-period:To assess recent changes in oryx population size, we characterized the fraction of the genome in ROH of seven different length classes ( /(2 × g) , and refeN. In addition to this identity-by-descent (IBD)-based approach, we implemented an LD-based method for estimating eN using the software GONe . As expected, historical estimates of eN were larger using the LD-based approach; however, the general pattern of population size change was the same across both methods .To calculate 95% bootstrap CIs around our estimates, we resampled individuals within each population with replacement 100 times, and recalculated are GONe . This isNucleotide diversity estimates were calculated for each population using ANGSD. We first estimated the unfolded site-frequency spectrum (SFS) using the -doSaf and -realSFS commands while restricting the analysis to regions with Phred quality and mapping scores over 30 within the 28 chromosome-length autosomes. Per-site pairwise nucleotide diversity estimates were then calculated using the -thetaStat command.Connochaetes taurinus), topi , and hartebeest (Alcelaphus buselaphus) as outgroup species. Short read sequencing data from wildebeest (SRR6902709), topi (SRR6913384), and hartebeest (SRR6922939 and SRR6922940) were downloaded from NCBI and mapped to the scimitar-horned oryx reference genome using BWA MEM with the default parameters. The alignments were then merged using SAMtools. A consensus was generated by selecting the most common base from the alignment using the doFasta 2 and doCounts 1 options in ANGSD. We then used PLINK v2.0 to polarize the oryx SNPs in our VCF based on the alleles in the consensus. First, we removed SNPs from our VCF whose positions were not present in the consensus sequence. Second, we removed SNPs where the ancestral allele in the consensus matched neither allele in the VCF file. Finally, we rotated alleles so that the reference allele in our VCF matched the ancestral allele in the consensus.As most deleterious mutations are likely to be derived alleles, we first polarized our SNP genotypes as ancestral or derived using the blue wildebeest . Finally, we used the Rxy statistic to estimate the relative frequency of LoF and missense mutations in one population over another Click here for additional data file.


Bipolaris maydis is the pathogenic microorganism of southern corn leaf blight, a persistent biotic constraint responsible for substantial yield losses of corn worldwide. In the present study, 96 isolates from six representative fields growing single and multiple sweet corn cultivars in Pingnan, Fuqing, and Jian’ou in Fujian Province, which are characterized by different geographical characteristics and cropping patterns, were genetically analyzed using inter-simple sequence repeat (ISSR) markers to assess the impact of geographical origins and corn cultivars on B. maydis population differentiation. B. maydis isolates originated from diverse regions possessed higher genetic variety than those from single and multiple sweet corn cultivars. Phylogenetic analysis showed that the isolates from single and multiple sweet corn cultivars were randomly grouped into different clusters, with those from the same location tending to form clusters. A greater genetic differentiation among different geographical populations than between those from single and multiple sweet corn cultivars was observed by pairwise comparison. Hierarchical analysis indicated that among-population variation was higher when comparatively analyzed B. maydis populations from different locations than in those from single and multiple sweet corn cultivars. In conclusion, these results suggest that geographical origin acts a more considerable role in genetic differentiation of B. maydis than corn cultivar. Two divided genetic clusters were detected in the B. maydis populations from single and multiple sweet corn cultivars at the three locations in Fujian Province, with major genetic variation being derived within populations. The high haplotypic diversity and expected mating type ratio of 1:1 in combination with significant linkage disequilibrium suggested that a mixed reproductive strategy occurs in the B. maydis population in Fujian Province. This study will enrich the information on the role that geographical origins and corn cultivars play in the population structure of the pathogen as well as the reproductive strategies in B. maydis population in Fujian Province. Bipolaris maydis (Nisikado et Miyake) Shoem  Drechsler), the causative microorganism of southern corn leaf blight (SCLB), is one of the most important biotic restrictive factors, and contributes to substantial yield losses worldwide on corn (Zea mays L.), which is a crucial source of human food, industrial ingredient, and animal feed  gene locus, which has two alternative allelic forms, named MAT1-1 and MAT1-2  having not been discovered under natural conditions, they can be easily formed using nutritive substances with suitable inductive materials and proper environmental conditions in a laboratory , the west and central mountainous regions (double-cropping in a year), and the north and south mountainous regions (triplex-cropping in a year). The east high altitude and mountainous region has many high mountain ranges, with an average elevation being more than 800 m and large difference in temperature between day and night. This temperature condition supports for only single cropping. The west and central mountainous regions characterize by abundant light and has an annual average temperature of 17 to 20°C, which satisfy double cropping. The north and south mountainous regions have an annual mean temperature of 18 to 21°C, which allows for triplex-cropping sweet corn. These geographical and meteorological features and cropping patterns impact on the growth of sweet corn and also influence the occurrence of SCLB.2 for each field) located in Pingnan , Fuqing , and Jian’ou , were selected for sampling collection. PN, FQ and JO situate in east, central and north Fujian, respectively. The three locations were selected for sampling due to the prolonged period of sweet corn planting and the history of frequent occurrence of SCLB. The linear distance between any two sampling sites ranges from 65 to 180 km. In each location, the both two fields were divided into 14 to 16 plots  according to the tested number of sweet corn cultivars (B. maydis was randomly isolated from each leaf by surface disinfecting the lesions (5 × 5 mm) in 75% (v/v) alcohol for 2 min and in 0.1% (w/v) corrosive sublimate for 90 s, with three subsequent washes in sterile water. The sterile lesions were put onto potato dextrose agar (PDA) and cultured at 28°C under darkness for five days  on PDA for long time storage at -20°C . Genomic DNA of each isolate was extracted from mycelia using a mini CTAB extraction method  and photoed using an Imaging System . Image Lab v5.2  software was used for scanning DNA fingerprints on the whole piece of gel. DNA bands for each primer on gels were transformed as 0 (absence band) and 1 (presence band) for analysis.Thirteen highly polymorphic ISSR-PCR primers (B. maydis populations were divided into different groups: (1) isolates from single and multiple sweet corn cultivars in PN, FQ, and JO ; (2) isolates from PN, FQ, and JO ; and (3) isolates from single (labeled S) and multiple (labeled M) sweet corn cultivars (two populations: S and M). Nei’s genetic distances among isolates or different groups were calculated using POPGENE v1.32 software according to bootstrap analysis with 1,000 replicates (LP), number of multilocus haplotypes (NM), number of different loci (NL), number of private loci (NP), Nei’s unbiased gene diversity (HU), and Shannon’s information indices (I) were inferred using GenALEx v6.5 with 999 permutations (SH) was used for indicating variety of multilocus haplotypes, which was estimated as SH = [–Σ(iPlniP)]/ln(n), where iP represents the ith haplotype’s frequency and n represents population size  with corresponding P values were calculated using GenALEx 6.5  was calculated as Nm = 0.5(1 – PTΦ)/PTΦ  using the covariance-standardized method in GenAlEx 6.5 (http://taylor0.biology.ucla.edu/structureHarvester/).To conduct genetic differentiation and population structure analyses for above-mentioned groups, phiPT values (ALEx 6.5 . RandomiT)/ΦPT . AnalysiT)/ΦPT . Nei’s gAlEx 6.5 . PopulatAlEx 6.5 . Two sucAlEx 6.5  by StrucB. maydis isolates from single and multiple sweet corn cultivars in the three regions in Fujian, including multilocus haplotypic diversity, the ratios of mating types, and analysis of linkage disequilibrium. The mating type of each isolate was identified by multiple PCR with two specific primer pairs (ChMAT01-3 and ChMAT02-2), which was established previously by -1 ethidium bromide (Shanghai Sangon Biotech), and the fragment sizes were estimated using a 2-kb DNA marker . The two mating type ratios were subjected to Pearson Chi-square tests to compare with an expected ratio of 1:1, which is expected to occur in a population characterized by sexual reproduction. Pearson Chi-square tests were performed in DPS v7.05 software  at a confidence interval of 95%. Two parameters of linkage disequilibrium (index of association (AI) and In the present study, three measures were used for investigating the potential reproduction strategy in izations .B. maydis using 13 ISSR markers, with 100% loci being polymorphic  and a low level of clonal fraction (CF = 0) was detected in all datasets  revealed that the geographical origin has a more important influence on B. maydis population than that of corn cultivars. Similar results were also obtained from the phylogenetic clustering of the individual B. maydis isolates from single and multiple sweet corn cultivars at the three sampling locations in Fujian Province, which shows that the isolates from single and multiple sweet corn cultivars were randomly grouped into different clusters, while those from the same location tended to cluster together  was observed between the compared populations from single and multiple sweet corn cultivars in different locations  (ranging from 0.108 to 0.168) were significantly higher than those from the single and multiple sweet corn cultivars (regardless of sampling location) (PTΦ = 0.038)  and 0.038 (P<0.001), respectively  and numerous isolates from FQ-M at the left of the vertical axis and the majority of isolates from JO (JO-S and JO-M) and FQ-S at the right of the vertical axis Figure 3K  for all six populations and populations from sampling location were K = 2  in all datasets (B. maydis populations from single and multiple sweet corn cultivars in Fujian Province. The detected indices of linkage disequilibrium (IA and dr̄) for the B. maydis populations from single and multiple sweet corn cultivars in Fujian Province were significantly different in all the datasets, thus rejecting the hypothesis of random mating  was detected between the B. maydis isolates from the three sampling locations, which was higher than that when isolates were grouped by corn cultivar . In addition, the genetic variation among populations was higher when isolates were grouped based on location (13.0%), compared to that when isolates were grouped according to corn cultivar (4.0%). The results obtained in the present study show that low genetic similarity and higher genetic differentiation being detected among B. maydis isolates from different sampling locations but not different corn cultivars implies that the geographical factor played a more important role in the population differentiation of B. maydis isolates than corn cultivars. The main reason for lack of genetic differentiation in B. maydis populations from single and multiple sweet corn cultivars may be due to high level of gene exchange (Nm > 12) within population. The findings in this study were consistent with analogical investigations revealing genetic differentiation of B. maydis on corn from north and south China and Villosiclava virens on rice in the Hubei Province of China, where both geographical origins and cultivars had an impact on the differentiation of B. maydis and V. virens populations, but the geographical origins played a more important role in the selection of B. maydis and V. virens isolates when compared with that of cultivars  and fruits , respectively, where among-population differentiation was higher when isolates were grouped based on host rather than geographical location   .B. maydis populations from single and diverse sweet corn cultivars at three sampling locations in the Fujian Province, which was consistent with the findings reported by Magnaporthe oryzae, from East Africa with high gene flow between subpopulations. Nevertheless, our results are in contrast with those from a similar population genetic study of E. turcicum in South Africa, where numerous private alleles were observed in E. turcicum populations from corn and sorghum with limited gene flow between the two hosts  was detected between the populations from the single and multiple corn cultivars in Fujian Province. In addition, high levels of haplotypic diversity (SH=1.0) were detected from B. maydis populations in all situations, suggesting that multiple infection sources occur on individual sampling fields. Meanwhile, no shared multilocus haplotypes were detected from the single and multiple corn cultivars at the three locations in Fujian Province, indicating that large scale migration of B. maydis isolates did not occur in Fujian Province. Furthermore, disease severities in the three sampling fields growing multiple sweet corn cultivars were lower than that growing single sweet corn cultivar  from single and multiple sweet corn cultivars in Fujian Province. These high levels of haplotypic diversity were not related to a strictly clonal population, which afford proof for sexual reproduction. The haplotypic diversity values of the B. maydis isolates were consistent with those of high-haplotypic diversity populations of Cercospora sojina (0.41–0.69) (Mycosphaerella musicola (0.55–0.89) (Bipolaris oryzae (0.51–1.00) (Setosphaeria turcica (0.81–0.91) (Dothistroma septosporum (0.94–1.00)  (P < 0.01) were detected between populations in all datasets; therefore, we gained no forceful proof in favor of random mating in the Fujian B. maydis populations. Previous studies suggested that many factors  could result in linkage disequilibrium analysis deviation from random mating, despite linkage disequilibrium is a crucial measurement for random mating  , Mycosph55–0.89) , Bipolar51–1.00) , Setosph81–0.91) , and Dot94–1.00)  which weelection  and provm mating . As the m mating . This isB. maydis lifecycle in Fujian Province despite evident proof of linkage disequilibrium. In similar previous investigations of other Cercospora, Dothistroma, and Exserohilum fungi, although linkage disequilibrium analysis did not support sexual reproduction in all datasets tested, high haplotypic diversities and near equal mating type ratios suggested that these populations experience both sexual and frequent clonal reproduction (B. maydis populations from single and multiple sweet corn cultivars in Fujian Province. This reproductive strategy was beneficial to B. maydis adaptability. Because wide new genotypes generating in sexual reproduction could help the pathogen to obtain more adaptive characteristics, such as overcoming host resistance or developing fungicides resistance (B. maydis survival in the adverse environment. In addition, asexual reproduction is beneficial to rapid growth and expansion. This challenge warrants the utilization of management strategies to prolong the service life period of these control methods (B. maydis populations. The main reason may be that the reproductive strategy of B. maydis is not only influenced by environmental factors, but by other factors, such as mating type distribution, alternative hosts.Contradicting results were obtained from the analyses of haplotypic diversity, ratios of the two mating types, and linkage disequilibrium. The high levels of haplotypic diversity and equal ratios of mating type supported that sexual reproduction is considerable in the oduction . Thus, tsistance . The per methods . FurtherB. maydis population from single and multiple sweet corn cultivars in Fujian Province. Intriguingly, B. maydis populations from single and multiple sweet corn cultivars at FQ exhibited obvious cultivar-specific differences, although the isolates of B. maydis were collected from the two neighboring fields. A reasonable interpretation of this situation is that there are two different proveniences of the pathogen that undergo mixing through sexual reproduction. A mixed reproduction strategy might explain the consolidation of two genetic groups at a comparatively slow speed (Collectively, the results of STRUCTURE analysis showed that two genetic clusters occur in the ow speed . The mecB. maydis populations in Fujian Province, given the more important role of the geographical origin in this pathogen differentiation. Our results showed high haplotypic diversity, an equal ratio of mating type, and remarkable linkage disequilibrium, and therefore are indicative of a mixed reproductive strategy among the B. maydis isolates from single and multiple sweet corn cultivars in Fujian Province. Sexual reproduction mostly took place on senescent phytodetritus at the later stage of crops or alternative hosts. Therefore, the existence of perithecia or ascospores on corn debris or alternative hosts needs to be further investigated to clarify the full lifecycle of B. maydis. The wide variation of gene recombination in sexual reproduction can increase the adaptability of offspring to natural selection and also promote the spread of advantaged mutations in the population. However, asexual reproduction can enable offspring to maintain the parental excellent characteristics, which can accelerate growth and achieve rapid population expansion. Hence, further evaluation of B. maydis is necessary to carefully assess the relative importance of both sexual and asexual stages in the lifecycle of B. maydis. In addition, a further temporal investigation of B. maydis isolates collected from the same site over continuous years will be beneficial to clarifying the influence of sampling time on genetic diversity and population structure.In conclusion, we comparatively studied the influence of geographical origin and corn cultivars on the differentiation of The original contributions presented in the study are included in the article/YD, XY, and WL: design the experiment. YD, LG, and CL: methodology and technology. YD, LG, CL, XL, and XY: samples and isolates collection. YD, LG, and CL: investigation and data analysis. YD: writing the draft manuscript. YD and WL: further review and editing. WL and XY: project supporting. All authors contributed to the article and approved the submitted version.


IFNL4 gene, its variants have been investigated and associated with several viral diseases, with an emphasis on hepatitis C. However, the impacts of these variants on mixed-race and native populations in the northern region of Brazil are scarce. We investigated three variants of the IFNL4 gene in populations from this location, which were among the 14 most frequent variants in worldwide populations, and compared the frequencies obtained to populational data from the 1000 Genomes Project, gnomAD and ABraOM databases. Our results demonstrate that mixed-race and native populations from the northern region of Brazil present frequencies like those of European and Asian groups for the rs74597329 and rs11322783 variants, and like all populations presented for the rs4803221 variant. These data reinforce the role of world populations in shaping the genetic profile of Brazilian populations, indicate patterns of illness according to the expressed genotype, and infer an individual predisposition to certain diseases.Since the discovery of the polymorphic nature of the  The study of genetic variants has acquired significant importance in recent years, as it provides explanations for different clinical conditions and a profile for responses to therapeutic treatments among individuals . In infeIFNL)—are considered specialists in antiviral action, blocking stages of the viral replicative cycle, increasing antigenic presentation, and triggering antiproliferative properties [IFNL1), lambda 2 (IFNL2) and lambda 3 (IFNL3). After 10 years of studies, a fourth type was identified, called IFN lambda 4 (IFNL4) [Type III interferons—the family of lambda interferons , with effects on therapies against this infection [Studies on type III interferons emphasize how these cytokines have potential in vitro and in vivo against many viruses, such as dengue virus (DENV), cytomegalovirus (CMV), human immunodeficiency virus (HIV), and Epstein–Barr virus (EBV) ,7. Howevnfection ,9.Despite the time that has passed since the discovery and description of this gene until today, there are still few studies on the impact of its variants on world populations. Proof of this are clinical data from banks such as ClinVar—National Center for Biotechnology Information; BraVE, LovD, Beacon—Brazilian Initiative on Precision Medicine—that need to be updated .The study of the distribution and prevalence of genetic variants of certain genes in mixed populations is particularly important. They can indicate patterns of illness according to the expressed genotype and infer an individual’s predisposition to certain diseases ,12,13. IIFNL4, especially in infections by hepatitis B (HBV) and C (HCV) viruses [IFNL4 gene [We add here, as a factor in this variability, the heterogeneous genotype distribution of genes such as  viruses ,17,18. TNL4 gene ,20,21.This variability is often caused by a single allele, which can condition a better or worse resolution of viral infections and therapeutic responses ,23,24. AIn this sense, it is understood that investigations of genetic variants such as single nucleotide polymorphisms (SNPs) and insertion or deletion (INDEL) allow the discovery and characterization of new molecular markers, with clinical applications functioning in prognosis or even in therapeutic decisions for some population groups.IFNL4 gene in a mixed and native population from the Brazilian Amazon and compare these findings with data from the general Brazilian population described in the Online Archive of Brazilian Mutations (ABraOM), and world populations available in the 1000 Genomes Project and Genome Aggregation Database (gnomAD).Therefore, our study aimed to characterize the molecular profile of the https://www.ensembl.org/index.html, accessed on 21 April 2023) database, which uses data from the 1000 Genomes Project, and GnomAD . In these databases, we admitted the Minor Allele Frequency (MAF) on the most frequent variants (MAF > 0.05) of the IFNL4 gene and these were investigated in world populations that could serve as a reference for Brazilian populations, especially Native Americans and mixed-race people from the Northern region of Brazil.The first stage of this research was an exploratory search in the EnsEMBL .For comparisons between the database samples and the study-elected populations, we are only considering the exon variants of this gene since we aim to investigate exome data from mixed-race and native Amazonian populations. For specifics about the Brazilian population, the source database was ABraOM  Aiming for an accurate investigation and comparison of variants that were found in Amazonian populations, the data acquisition phase was designed to include Minor Allele Frequencies (MAF) 5%; (II) using the search query “IFNL4” and selecting the matching result (gene symbol report and Hugo Gene Nomenclature Committee (HGNC) ID: 44480); (III) choosing “variant table” and adjusting the MAF upwards, so the results would depict the percentages from highest to lowest; (IV) organizing a primary table on Google Docs with columns detailing populations in order of: variant (rs), all , AFR (African Population), AMR (American Population), EAS (East Asian Population), EUR (European Population), SAS (South Asian Population); (V) from the data generated, a second organization was made on Google Spreadsheets detailing the following: chromosome, position, reference nucleotide, variant nucleotide, amino acid and protein changes, variant kind and allelic information—number, count, frequency, homozygous or heterozygous. The study condensed these and added information from our native population as well.When considering ABraOM, we had a more local approach since this data bank only considers data generated from Brazilian populations . For this database, the steps were: (I) opening the website, selecting SA-BE-WGS-1171 (hg38) and searching for “IFNL4”; (II) selecting the highest frequency option for the variant order display; (III) exporting the data to a Google spreadsheet considering: chromosome, position, reference and variant nucleotides, category, consequence predictor  rs ID and their population frequencies , homozygous and heterozygous numbers, allele number, count and frequency were sorted highest to lowest. All data were collected and organized between April and July 2023.This study uses population data described by Cohen-Paes and collaborators in 2022 , which iFor our comparative analysis, the Indigenous groups were called Native American Population (NAT). Furthermore, this study includes 89 mixed-race individuals from the metropolitan region of Belém (PA), which includes the cities of Belém, Ananindeua, Marituba, Benevides, Santa Barbara, Santa Izabel, Castanhal and Barcarena; referred in this work by the acronym MISC.The study was approved by the National Research Ethics Committee and the Research Ethics Committee of the Tropical Medicine Center of the Federal University of Pará (CAE: 20654313.6.0000.5172). The participation of all individuals was conditioned on acceptance and signing of the informed consent form (ICF).http://www.1000genomes.org, accessed on 19 April 2023) and GnomAD , which are organized by presenting five continental populations including African (AFR), East Asian (EAS), South Asian (SAS), European (EUR), and American (AMR) individuals. Comparisons to the Brazilian population were obtained from the ABraOM database .The data were compared to samples present in the databases 1000 Genomes  and SureSelect Human All Exon V6 , following the manufacturer’s recommendations. Sequencing took place on the NextSeq 500® platform  with use of the NextSeq 500 High-output v2 300-cycle Kit Kit .DNA extraction occurred using the phenol-chloroform method . DNA quahttp://www.bioinformatics.babraham.ac.uk/projects/fastqc/, accessed on 25 June 2023) and low-quality reads were eliminated . The sequences were aligned with the reference genome (GRCh38) using the BWA v.0.7 tool .The resulting reads in FASTQ format were analyzed . Markers in the IFNL4 gene were selected from the generated coverage (fastx_tools v.0.13-http://hannonlab.cshl.edu/fastx_toolkit (accessed on 25 June 2023)).Allelic variants were noted in ViVaIFNL4 gene variants, similar to those observed in Continental and Brazilian populational groups. For that, we used the Fisher’s exact test. The results were considered statistically significant when the p value was less than 0.05 (p ≤ 0.05). The Benjamini-Hochberg False Discovery Rate (FDR) [The allelic frequencies were compared to verify if the mixed-race (MISC) and native (NAT) Amazonian populations present some sort of Allelic Distribution of the te (FDR)  test wasThe LD Link tool  was emplIn exploratory research, we identified 10 variants in which the altered allele was frequent in at least 10% of the populations described by the 1000 Genomes Project (MAF > 10%) and another four variants with a frequency of 5% (MAF > 5%). Among them, two variants identified in mixed-race and native populations in the northern region of Brazil had a frequency greater than 10%, and one had a frequency greater than 5%. Exome analysis of samples from mixed-race and native Amazonians showed three of these variants being 2 SNVs (single nucleotide variant) and 1 INDEL (Insertion-Deletion). The SNV variants were rs74597329-G/T, rs4803221-C/G and are classified as moderate impact and the INDEL type variant –rs11322783-ΔT/TT–of high impact as it is a frameshift mutation.IFNL4 gene variants in each of the five population groups described by GnomAD v3.1.2—Africa, Americas, East Asia, Europe, and South Asia, while p-value: <0.0001), AMR , and São Paulo—AbraOm  in rs74597329 and rs11322783 variants. In the rs4803221 variant, NAT was also different from AFR  and AMR  groups. The mixed group (MISC) presented differences when compared to AFR  and EAS  for rs74597329 and rs11322783 variants. value: 0.0031) groups. The mixed group (MISC) presented differences when compared to AFR  and EAS  for rs74597329 and rs11322783 variants.We observed subtle differences between data from GnomAD and the 1000 Genomes Project . Pairwisp-value: 0.016 and 0.003). Moreover, examining the mixed population, we saw that either AFR  and EAS  differs from it for rs74597329 and rs11322783 variants. The differences can also be noticed in the plot of 2 = 0.990; D’ = 1) in all populations already observed and, therefore, they can be analyzed as a haplotype [aplotype .Modern-day Latin American people are the result of a complex process of mixing different genetic profiles . The stuIFNL4 gene, whose variants may regulate IFN-λ4 expression and functionality. Interferon lambda proteins can activate the JAK-STAT pathway, leading to a positive expression of genes with antiviral properties aiming to eliminate pathogens, such as hepatitis C virus. This gene presents interesting characteristics due to a polymorphism that regulates IFN-λ4 expression; it is composed of the rs74597329 (IFNL4-G/T) and rs11322783 (IFNL4-∆/T) variants, which are in complete connection imbalance and, due to this, are analyzed together [This can be clearly exemplified by the together ,28.Those variants behave as a dinucleotide variation, named rs368234815 (ΔG/TT). In practical terms, this means that individuals will always have the IFNL4-ΔG (rs11322783∆/rs74597329G) and IFNL4-TT (rs11322783T/rs74597329T) haplotypes . IFNL4-ΔOur study shows that the IFNL4-TT haplotype is predominant in Amazonian natives as well as in mixed and Asian populations, reaching values between 74% and 93%. The mixed group presents a profile similar to American (AMR), European (EUR), Southern Asian (SAS) and São Paulo (ABraOm) groups. It was an expected aspect since the mixed population of the study was formed by founding groups such as Europeans and Asians .The differences observed when comparing the frequencies of African people to our populations of study happen because the AFR group has a differing prevalence of the ∆G haplotype when compared to all the other populations. Some authors discuss how this strong selective pressure for the IFNL4-TT haplotype may have arisen before the migration of human populations out of Africa. Due to other factors still unknown, IFNL4-TT became stronger in European and Asian groups but not in the original population. In other words, the downregulation of this protein is beneficial in many populations. ,45A proposal to justify different results in American populations is given by . He propThe variant rs4803221 has controversial results. While  show G, In our study, the rs4803221 variant did not show any statistically differing results on the comparison between the NAT and MISC samples and the database-checked populations. Low frequencies of minor allele (G) were observed on the NAT and EAS samples, which is expected when we evaluate the formation process of American populations, which considers American ancestry to have come from the migration of Asians by the Bering Strait . HoweverIFNL4 gene are shown in worldwide populations (GnomAd and 1000 Genomes) and in southeastern Brazil (ABraOm), but they are not present in the samples of our study. They are missense-type SNVs, and their absence in the sample of mixed-race and native Amazonians is explained by their minor frequencies of MAF in most continental populations, except for the AFR population, in which the frequencies of the lowest allele are slightly larger.The SNPs rs73555604 and rs117648444 collected in the exome of the A better understanding of the genetic profile of our population is important to validate the existing hypotheses of distinct patterns in disease responses, infections, and treatments in different people. The importance of characterizing the genetics of native populations and people who have suffered intense processes of ethnic mixing is justified by essentially helping to understand illness processes that are, sometimes, unclear.Other studies follow ours to elucidate (1) the distribution of these variants in patients with hepatitis C and (2) the direct consequences of these polymorphisms on both the HCV clearance and the efficiency of drug treatment in populations from the north of Brazil. This information will contribute knowledge and base the development of public policies aiming for health improvement in many groups across the country.IFNL4 gene evaluated in mixed-race and native populations from the northern region of Brazil have frequencies resembling those in world populations, especially Asian and European ones. In practical terms, these results suggest that world populations played a significant role in the formation of the Brazilian population. Therefore, this study aid further future public policies associated with the treatment of viral infections in these populational groups.The results indicate that the variants rs74597329, rs11322783 and rs4803221 of the