Bombina bombina) provide an unexpected experimental set‐up to test the genetic consequences of an intraspecific introgression from central population individuals into populations at the species range margin. Here, we utilize complete mitochondrial genomes and transcriptome nuclear data to reveal the full genetic extent of this translocation and the consequences it may have for these populations. We uncover signs of introgression in four out of the five northern populations investigated, including a number of introgressed alleles ubiquitous in all recipient populations, suggesting a possible adaptive advantage. Introgressed alleles dominate at the MTCH2 locus, associated with obesity/fat tissue in humans, and the DSP locus, essential for the proper development of epidermal skin in amphibians. Furthermore, we found loci where local alleles were retained in the introgressed populations, suggesting their relevance for local adaptation. Finally, comparisons of genetic diversity between introgressed and nonintrogressed northern German populations revealed an increase in genetic diversity in all German individuals belonging to introgressed populations, supporting the idea of a beneficial transfer of genetic variation from Austria into North Germany.Due to their isolated and often fragmented nature, range margin populations are especially vulnerable to rapid environmental change. To maintain genetic diversity and adaptive potential, gene flow from disjunct populations might therefore be crucial to their survival. Translocations are often proposed as a mitigation strategy to increase genetic diversity in threatened populations. However, this also includes the risk of losing locally adapted alleles through genetic swamping. Human‐mediated translocations of southern lineage specimens into northern German populations of the endangered European fire‐bellied toad ( It mostly inhabits permanent, fish‐free freshwater bodies, like shallow stagnant lakes, ponds and swamps  genotypes into northern lineage populations. This was likely the result of occasional  translocations of toads of southern origin into northern populations  in 2016 under permit MA22‐984143‐2015‐5 issued by the Municipality of Vienna and 25 from Germany  in 2017 under permits from Landesumweltamt Schleswig‐Holstein Figure . German 2.2We extracted RNA from the tail muscle of the fins, using a modified Trizol isolation protocol in combination with a column‐based commercial kit (QIAGEN RNeasy Mini Kit) based on the manufacturer's protocol. Only skin and muscle tissue of the tadpole's fins were used in order to prevent contamination from gut bacteria during sequencing as much as possible. To further increase RNA yield, we transferred the frozen tadpole tails into a 1 ml Trizol solution and performed a homogenization with a Tissue Lyzer . We implemented the column‐based clean‐up procedure from the QIAGEN Rneasy Mini Kit as described in the manufacturer's manual. We assessed the quality and quantity of the extracted total RNA on an Agilent Bioanalyzer 2100. We only selected samples with a high RIN number (>8) as well as a high RNA concentration (c > 50 ng/µl) for library preparation. We then performed an mRNA enrichment on these samples with poly(A) beads using the Bio Scientific NEXTflex Kit following the manufacturer's protocol. To assess the quantity of successfully enriched mRNA, we ran a Qubit High Sensitivity RNA Assay. We built cDNA libraries from the enriched mRNA samples with the NEXTflex Rapid Directional RNA‐Seq Kit (Bio Scientific) following the manufacturer's protocol. During the strand‐specific library preparation, we single indexed each sample and ran a PCR amplification with 15 cycles and an annealing temperature of 65°C. We performed a final quantity check on the built libraries with a dsDNA High Sensitivity Assay on the Qubit and a quality check on the Bioanalyzer. The cDNA library concentrations ranged from 2.94 to 17.4 ng/µl. We sent the libraries to be sequenced at Novogene in Hong Kong, China, where samples were additionally assessed for sufficient quantity and quality and PE 150 bp shotgun sequenced on three lanes on an Illumina HiSeq.2.3B. bombina from NCBI (GenBank accession: HADQ00000000.1) for population genomics analyses, and a transcriptome from B. orientalis (GenBank accession: HADT00000000.1) for use in downstream admixture analyses to avoid ascertainment bias that can be caused by mapping to an ingroup reference . The resultant mapping files were then converted to BAM files and sorted using SAMtools v1.6.1  , B. variegata (GenBank accession: AY971143.1)) using MAFFT v7.392  and a minimum mapping quality (‐minMapQ) parameter of 25; we required 20 individuals as the minimum number for a site to be considered for analysis (‐minInd 20), only included reads mapping uniquely to one location (‐uniqueonly), specified a minimum minor allele frequency of 0.05 (‐minFreq 0.05), called genotype likelihoods using the GATK method (‐GL 2), only included contigs over 1000 bp in size, required each site to have at least five reads mapping (‐mininddepth 5) and only considered SNPs with a p‐value lower than 1e‐6 . The output genotype likelihoods were then converted from a beagle file into a covariance matrix using PCangsd. The same genotype likelihoods were also used to perform an admixture proportions analysis in PCangsd (‐admix). The most probable K value was chosen by the software based on the eigenvalues of the PCA.We performed two independent principal component analyses with the software ANGSD v0.921 and PC2.6D‐statistics in ANGSD to look for the relative degree of gene flow in our samples. D‐statistics works based on a predefined species tree which uses three ingroup and one outgroup taxon. This topology can be written as ,H3),O) where H1 and H2 are more closely related to one another than either are to H3. D‐statistics then scans across the genome to find regions that break the known species tree, either due to incomplete lineage sorting or admixture between H3 and either H1 or H2. The occurrence of ,H2),O) being equal to ,H1),O), is interpreted as incomplete lineage sorting . Sites at which H2 and H3 share a derived allele, while H1 and the outgroup share the ancestral allele, are called ABBA sites, while BABA represents sites at which H1 and H3 share the derived state and H2 and the outgroup share the ancestral allele. Any deviations from the expected 1:1 ratio are considered as differential levels of gene flow between the ingroup species analysed and are represented by the D value (null expectation of the test: D = 0). This value quantifies the deviation from the expected ratio, which is calculated by the differences in the sum of ABBA and BABA site patterns across the genome, divided by their sum:We ran B. variegata is known to occasionally hybridize with B. bombina in our sampling area in north‐eastern Austria  were considered as statistically significant, which corresponds to a p‐value <0.0013 , considered only transcripts greater than 1000 bp in length and used the following filters: ‐minMapQ 25 ‐minQ 25 ‐uniqueOnly 1. As the sister species 2.7B. variegata, and B. orientalis). The output haploid file was converted to PLINK format using haplotoplink from the ANGSD toolsuite. We used plink v1.90b3.42 . We first ran treemix specifying no migration edges and B. orientalis as root to produce a consensus tree. We then used this tree as a prior when specifying multiple migration edges (‐m 1–4) while running treemix. The tree and residues were produced in R using the plotting_funcs.R script available with treemix . While running the popgenWindows.py, we specified the window size as 20 kb so that the window size encompasses complete contigs/genes, and a minimum number of sites per window as 100. The significance of differences between populations was calculated using a Wilcoxon–Mann–Whitney test while implementing a Bonferroni correction  resulting in independent Fst values for each contig/transcript. From this output, we found contigs that were highly differentiated between the German and Austrian populations, in an attempt to uncover German/Austrian‐specific genes. We took the contigs showing the highest Fst values (top 5%) for each pairwise comparison of a German population against the Austrian population. This resulted in five pairwise comparisons . We extracted the contigs that were found to be in the top 5% of all pairwise comparisons and cross‐referenced the sequences using BLAST to identify names and functions of these genes  Classification System v14.1  and 2017 . A summary table of the mapping results is provided as Table We obtained 30 complete mitochondrial genomes of 3.2B. bombina, we obtained an average read depth of 99.9  and an average number of uniquely mapped reads of 40,467,551. When specifying B. orientalis as reference, the mapping resulted in an average read depth of 112.3  and an average number of uniquely mapped reads of 37,805,633. Three samples, Ho_KQ001, Ho_KQ02 and Te_KQ01, were removed due to insufficient coverage (read depth <25). For more details, see Table When mapping our data to the reference transcriptome of 3.3To examine whether the pattern found in the mitochondrial genomes is also reflected in the coding regions of the nuclear genome, the same cDNA libraries that we sequenced and used to reconstruct mitochondrial trees were also used to build transcriptomes for each individual. We ran a transcriptome‐wide principal component analysis (PCA) with the software ANGSD to identify population structure. For the analysis, we used a genotype‐likelihood (GL) approach . The resultant PCA groups all Austrian individuals into a single cluster and German individuals from Testorf, Eutin, Dannau and Fehmarn into a second cluster, in agreement with their geographical origin Figure . Interes3.4K = 2 shows a high level of shared alleles between all German Högsdorf individuals and Austrian toads; that is, approximately half of the genetic information coming from transcriptome‐wide SNPs are shared with the Austrian individuals  and northern (Germany) European fire‐bellied toads, we performed an admixture structure analysis using PCangsd  were removed from further analyses. As previous analyses indicated toads from Fehmarn not to carry Austrian alleles, we considered the Fehmarn population to represent the autochthonous (nonintrogressed) condition. Consequently, we plotted all significant D values for the remaining four German sampling locations, while constraining Fehmarn to the H1 branch and Austria to the H3  and German (northern lineage) populations, we carried out an ABBA‐BABA or 3 Figure . A positD values indicating higher levels of admixture between the Austrian population and the German populations from Testorf, Högsdorf, Eutin and Dannau compared to Fehmarn, ranging from 0.048 to 0.288. The German Högsdorf population had the highest D values from 0.157 to 0.288, followed by Dannau with 0.144 to 0.194. The Testorf and Eutin populations show similar positive, low D values (around 0.05), indicating a smaller degree of admixture with Austrian toads in these populations.For all four German populations, we found positive m = 0, we uncover migration between Austria and Högsdorf , we were able to identify loci that were highly differentiated (top 5%) between the German and Austrian populations. We uncovered 23 contigs found to be highly differentiated in all pairwise comparisons between the German and Austrian populations. We cross‐referenced these contigs via BLAST and identified gene names for 17 of the 23 genes of interest  relative to Fehmarn  in the remaining German populations  DNA in the northern populations as was previously found using toads collected in 2006  stood out as it encodes for a peptide known as Drosomycin‐Like Defensin (DLD). Studies on humans and The presence of introgressed potentially beneficial alleles at some genes, but local alleles at other genes in the recipient northern German populations could constitute the result of natural selection, leading to mosaic genotypes with favourable alleles at multiple loci, be they introgressed or autochthonous. We further found that the introduction of allochthonous individuals led to an increase in genetic diversity of the recipient populations Figure . This in5B. bombina, we were able to assess the genetic consequences of a human‐mediated translocation of individuals from the more genetically robust central Austrian population into endangered range margin populations in northern Germany. Although conservationists may be reluctant to translocating individuals from different evolutionary lineages as means of genetic rescue (Kock et al., Through the production of mitochondrial genomes and transcriptomic data from six populations of The authors declare that they have no conflict of interest.Supplementary MaterialClick here for additional data file.


Northwest Pakistan has served as a point of entry to South Asia for different populations since ancient times. However, relatively little is known about the population genetic history of the people residing within this region. To better understand human dispersal in the region within the broader history of the subcontinent, we analyzed mtDNA diversity in 659 and Y-chromosome diversity in 678 individuals, respectively, from five ethnic groups , from Swabi and Buner Districts, Khyber Pakhtunkhwa Province, Pakistan. The mtDNAs of all individuals were subject to control region sequencing and SNP genotyping, while Y-chromosomes were analyzed using 54 SNPs and 19 STR loci. The majority of the mtDNAs belonged to West Eurasian haplogroups, with the rest belonging to either South or East Asian lineages. Four of the five Pakistani populations  possessed strong maternal genetic affinities with other Pakistani and Central Asian populations, whereas one (Tanolis) did not. Four haplogroups  among the 11 Y-chromosome lineages observed among these five ethnic groups contributed substantially to their paternal genetic makeup. Gujars, Syeds and Yousafzais showed strong paternal genetic affinities with other Pakistani and Central Asian populations, whereas Jadoons and Tanolis had close affinities with Turkmen populations from Central Asia and ethnic groups from northeast India. We evaluate these genetic data in the context of historical and archeological evidence to test different hypotheses concerning their origins and biological relationships. Archeological and anthropological evidence suggests the initial settlement of the region by AMH populations occurred 60–70 thousand years ago (kya)13, presumably via a coastal route16. From this region, modern humans likely dispersed into East Asia, Southeast Asia, and Sahul17. Although Paleolithic and Mesolithic peoples left their mark in the area10, major prehistoric and historic events with possible genetic consequences also occurred during the Neolithic period and later19.South Asia is thought to be one of the first major geographic regions to be inhabited by anatomically modern humans (AMHs) as they dispersed out of Africa27. These include more than 2200 major population groups28, over 450 tribal communities29 and some 30 hunter-gatherer populations31. Ethnic groups claiming to have arrived and settled in South Asia include but are not limited to Afghans, Arabs, Armenians, Aryans, Chinese, Greeks, Huns, Iranians, Mongols, Persians, Scythians, Syrians, Tajiks, Turks, and Uzbeks32. The overwhelming majority of the current ethnic groups are reportedly endogamous33, and speak an array of languages from various language families, including Indo-European, Dravidian, Tibeto-Burman, Austro-Asiatic, and Sino-Tibetan, each being differentially distributed throughout South Asia36.Today, South Asia is home to more than one billion people who belong to thousands of distinct socio-culturally, ethnically, and genetically diverse populations8 kya41. From there, farming and sedentary lifeways spread further east, laying the foundation for the later Indus Valley (including the cities of Harappa and Mohenjo-Daro) and the Gangetic Valley civilizations, which arose between 4.6–3.9 and 3.5–2.5 kya, respectively41. Sometime around 3.5 kya, Indo-European-speaking nomadic pastoralists from the southern steppes, often called ‘Aryans’, crossed the Hindu Kush Mountains and expanded into the subcontinent46. Later, in the eighth century CE, an Arab-Muslim army invaded Sindh in the extreme western periphery and occupied the subcontinent for a brief period of time. At the beginning of the eleventh century CE, Turkic populations bearing Islamic culture entered South Asia from Afghanistan and began spreading Islamic culture from west to east57. Outside of northern Pakistan, this series of population expansions effectively generated the gene pool from which subsequent South Asia populations developed. Yet, in northern Pakistan, appreciable movement of Islamic populations whose ultimate origins are found in the Kandahar region of southern Afghanistan did not occur until the sixteenth century58.This differential distribution has been attributed to the impact of external influences on South Asian populations. The earliest evidence of farming-based economies in South Asia has been traced to the introduction of West Asian cultigens such as wheat and barley at Mehrgarh, Pakistan, dating to 60. Other studies have further revealed contributions from Middle and Late Bronze Age steppe populations in South Asia, together with a Chalcolithic or Bronze Age Central Asian admixture scenario62. The various invasions and subsequent migrations are assumed to have resulted in major demographic expansions in the region, adding new languages and cultures to the mix of peoples already residing within the subcontinent. As a result of these processes, the majority of present-day Pakistani and Northwest Indian populations have relatively close affinities with West Eurasian populations71.Recent genetic studies suggest that the major West Eurasian genetic contribution to South Asia derives from Neolithic Iranian and early Bronze Age steppe populations33. These languages have been connected to the so-called “Indo-Aryan invasion” from Central Asia that occurred approximately 3.5 kya and the subsequent establishment of the caste system. The actual extent of immigration by “Aryan” populations remains controversial31, although at least some Indo-Iranian languages were likely introduced by immigrant Islamic groups from Afghanistan during the medieval period76. The speakers of these languages are further divided into different castes, sub-castes and tribes, reflecting the complex social organization of the region today80. Moreover, the region is home to followers of many religions, the major ones being Islam, Hinduism, Buddhism and Sikhism, with sizeable Christian and Jewish minorities also being present. All have likely contributed to the genetic and cultural diversity found in this region of South Asia.Like South Asia as a whole, the population of Pakistan encompasses a diverse array of cultures with different communities distributed into different ethnic groups. Indo-European languages are spoken by more than 70% of Pakistani ethnic groups87. Thus, in this study, we conducted an extensive analysis of diversity in the mitochondrial DNA (mtDNA) and the non-recombining portion of the Y-chromosome (NRY) among members of the five major ethnic groups of Buner and Swabi Districts of KPP to elucidate their genetic history. The data generated were also compared with previously published information for geographically and ethnically diverse global populations to explore the maternal and paternal history of South Asian populations. The resulting data provide, for the first time, deep phylogeographic information about Pakistani population genetic diversity.While several studies have focused on Pakistan, genetic research on the ethnic groups in the Khyber Pakhtunkhwa Province (KPP) remains rather limitedThe maternal genetic ancestry of 659 individuals from the five KPP ethnic groups was characterized through coding region single nucleotide polymorphism (SNP) genotyping and control region (CR) sequencing Tables  and S2. The majority (50.8%) of the identified haplogroups were of West Eurasian (WE) derivation. The most prevalent WE haplogroup was H, followed by U7, J1, W and HV. The relative proportion of these haplogroups was greatest among Gujar individuals (62.3%).South Asian (SA) lineages were mainly represented by haplogroups deriving from macrohaplogroup M, which comprised approximately 39% of the individuals within the study populations. The most frequently occurring SA lineages were U2, followed by M3 and R5. The highest frequency of SA lineages occurred among Tanolis (47.8%).All five ethnic groups also had a number of East Eurasian (EE) haplogroups, which together accounted for 10.2% of their mtDNAs. Haplogroup D was the most prevalent EE lineage, with A, C, F, M7, M9, M10 and Z also occurring at low frequencies. The frequency of such EE lineages was highest among Jadoons (15.2%), whereas they were far less common among Tanolis (5.2%) and Gujars (4.1%).Certain haplogroups were confined to particular ethnic groups. For instance, J2 was present only among Gujars, while haplogroup M1 appeared only in Jadoons. Similarly, haplogroups M27, M76, R30 were only observed among Syeds, while M21, M33, M52, V and Z were nearly exclusive to Yousafzais. In addition, the more frequent haplogroups, such as D, HV, M5, M18, M30, N3, U2, U7 and W, differed considerably in their distribution among the five ethnic groups from KPP.We further observed a high degree of CR sequence diversity among members of the five KPP ethnic groups Table . NotablyThese patterns of diversity were mirrored in the median-joining (MJ) networks generated from HVS1 haplotypes present in the five ethnic groups  and South Asia (MSA) showed foci in those regions. Likewise, haplogroups having European  and Near East  origins were concentrated in those areas, although clearly having been spread into South Asia since evolving. The other lineages  were somewhat less concentrated in any one region. While providing insights into the distribution of these haplogroups across Eurasia, this analysis may have been affected by the sample sizes, hence, the relative haplogroup frequencies, used for the comparative populations.To further understand the maternal genetic background of KPP ethnic groups, we compared their mtDNA haplogroup frequency data with those from 77 Old World populations representing South Asia, Central Asia, East Asia, Middle East, Europe and the Caucasus Table . We usedSummary statistics describing genetic diversity in the five KPP ethnic groups and other Pakistani populations are shown in Table ST values based on their HVS1 sequences  was conducting using FThe analysis of NRY variation in 678 male individuals from the same ethnic groups yielded 11 distinct haplogroups defined by 54 SNP and 19 Y-STR markers Tables  and S6. West Eurasian Lineages. The most common paternal haplogroup in the study populations was R1a1a-M17. It appeared at high frequencies among individuals of three of the five ethnic groups . R1a1a-M17 is also one of the most common haplogroups in Eurasia, with high frequencies occurring in Eastern Europe, Central Asia, and South Asia94. In neighboring Afghanistan, R1a1a-M17 is frequent among Pashtuns (51.02%) and Tajiks (30.36%) but less so in Uzbeks (17.65%) and Hazaras (6.7%)95. In addition, it has been observed at high frequency (~ 80%) among Yousafzais of Swat Pakistan82, a finding consistent with our data.99, but also appears in South Asian populations at modest frequencies100.The second most common haplogroup was R1b1a-M297. It occurred in the Tanolis at a very high frequency but appeared at very low frequencies in the Jadoons, Yousafzais and Syeds, while being completely absent in the Gujars. Haplogroup R1b is the most frequent Y-chromosome lineage in Western Europe (> 70%)101, and may be associated with the Neolithic expansion throughout the region94. G2a has also been observed throughout the Near East102 and Mediterranean region103, and occurs in South Asia in appreciable frequencies104. By contrast, I2-P215 may have arisen in the Balkans and central Europe105, since it is commonly observed in Slavic speaking populations of southern Europe106.The other West Eurasian haplogroups appeared non-uniformly in the study populations. G2a-P15 and I2-P215 occurred at low frequency in only the Yousafzais. G2a is thought to have arisen in Anatolia and the Caucasus109. Both J2a-M410 and J2b-M12 (0–8%) also appear at low frequencies in populations inhabiting different parts of India110. In general, the presence of J2a-M410 and J2b-M12 in Pakistan and India has been considered indicative of gene flow from western Asia44.Gujars, Jadoons and Yousafzais exhibited haplogroup J2a-M410 at low frequencies, while J2b-M12 occurred at low frequency in the Gujars and Yousafzais. Previous studies have demonstrated that J2a-M410 and J2b-M12 are associated with the demic diffusion of Neolithic farmers in North Africa and Eurasia from Mesopotamia (Iraq and Syria)South Asian Lineages. Haplogroup H-M69, which is commonly observed in South Asia112, occurred in all five ethnic groups at modest frequencies. The Gujars also had a moderate frequency of haplogroup L-M20, with this paternal lineage being present at low frequency among Syeds, Yousafzais, and Jadoons and completely absent in Tanolis. Haplogroup L commonly occurs in populations from Pakistan, India and Afghanistan, and has spread into the Near East and Iran113. In addition, South Asian-specific haplogroup R2-M124 occurred at low frequencies among all KPP populations. Haplogroup R2-M124 has mainly been found in Indian, Iranian, Pakistani and Central Asian populations, and postulated to have a Central Asian origin118.East Eurasian Lineages. East Eurasian haplogroup O3-M122 occurred nearly exclusively in Jadoons, and otherwise appeared at very low frequency in Yousafzais, Gujars and Tanolis while being absent in Syeds. O3-M122 is the most common haplogroup among Han Chinese populations, occurring at frequencies of 50–60% in them121. It also occurs at very low frequencies in India and Pakistan, mostly likely due to the westward expansion of Tibeto-Burman speakers into South Asia44.122. Among the Pashtuns of Afghanistan, the frequency of haplogroup Q-M242 is about 18.4%95.By contrast, all five KPP populations possessed Q-MEH2 Y-chromosomes at low frequencies. The MEH2 marker occurs downstream of the M242 marker that helps to define this paternal lineage. Haplogroup Q-M242 probably originated in Central Asia and has been distributed widely in Northeast Asia, while also appearing at low frequencies in Europe and the Middle East, mostly likely to due to the influence of Mongolic and Turkic speaking populationsThese patterns of diversity were mirrored in the median-joining (MJ) networks generated from Y-STR haplotypes present in the five ethnic groups  while having relatively few EA mtDNAs. Based on this pattern of diversity, they show strong genetic affinities with the Yousafzais, Kashmiri and other Pakistani populations.Gujar maternal ancestry is largely congruent with their paternal genetic ancestry. Their mtDNAs are largely of WE origin, although some derive from SA and EA155. By contrast, Gujars of Jammu and Kashmir show mtDNA affinities with populations from Uttar Pradesh and Arunachal Pradesh to the east156. Thus, our data suggest a more complex origin for KPP Gujars. One scenario could involve an indigenous population with genetic affinities to geographically proximate Jats and Rajputs mixing with Indo-Iranian or Turkic speaking Muslim populations, and then migrating into the region from the steppes of Central Asia157.With respect to their origins, one hypothesis proposes that Gujars expanded into India from Central Asia, while another suggests they came from Georgia via Afghanistan in the fifth century CE. Based on our data, Gujars generally resemble Iranians who mixed with local populations rather than populations from the Caucasus44, Q-M242 appears at modest frequencies in them. In the NRY NJ tree, the Jadoons occupy an outlier position relative to other KPP populations, but exhibit affinities with Turkmen from Central Asia. In this regard, Mongol expansions into Central-South Asia probably brought NRY haplogroups C3, O3, and Q to Pakistan during the medieval period, and NRY diversity in Kazakh populations from Central Asia was probably similarly influenced during this time159. The rest of their Y-chromosomes belong to either WE or SA haplogroups, and appear similar to types present in other KPP populations, suggesting some degree of gene flow between them.Unlike other KPP ethnic groups, the Jadoons exhibit a strongly East Asian paternal ancestry, with NRY haplogroups O3-M122 and Q-MEH2 representing 82.5% of their Y-chromosomes. Although O3-M122 is very rare among South Asian populations162. Viewed as a whole, genetic diversity among Jadoons appears to reflect a scenario in which male-mediated gene flow into the region was followed by these immigrant males subsequently marrying indigenous females thereby yielding a maternal gene pool similar to those possessed by members of other Pakistani and Central Asian ethnic groups.Jadoons mtDNA shows greatest similarity to groups from WE followed by SA with less affinity to EA groups. As such, Jadoons exhibit a pattern of extra-regional affinities that are generally like those observed among Gujars, Syeds and Yousafzais. The neighbor-joining tree also identifies affinities to European Roma populations and to other South-Central Asian groups. As such, these results corroborate previous studies that identify a genetic affinity of Roma populations to South Asian groups, especially those residing in the northwestern region of the subcontinent132, they are distinct through their hgh frequencies of haplogroup U2, T2, M9, X and R30 mtDNAs.Most Syeds possess NRY haplogroup R1a1a-M17, along with a unique array of Y-STR haplotypes of this patrilineage that is coupled with low prevalence of Y-chromosomal variations common to South and East Asians. This combination aligns Syeds with other Pakistani and Central Asian ethnic groups while distancing them from ethnic groups of the rest of the subcontinent and East Asia. Matrilineal genetics yield a similar pattern. Syeds are marked by high frequencies of WE lineages coupled with low frequencies of lineages common to South and East Asians. While this pattern aligns Syeds with other Pakistani and some Indian Samples163. Moreover, the topography of northern Pakistan with its formidable mountains and narrow, steep-sided valleys may have fostered the establishment of localized endogamous social groups that, over time, developed into largely reproductively isolated distinct ethnic groups.Although Syeds are hypothesized to have come from the Near East and entered South and Central Asia during the Mongol invasions of the thirteenth and fourteenth centuries, mtDNA and NRY data instead support a scenario in which Syeds have an ultimate origin in Afghanistan coupled with long-standing gene flow with Central Asian populations132. In which populations residing west of the Indus Valley possess mtDNA lineages largely of West Eurasian derivation with limited contributions from South Asia and East Eurasia, while those found to the south and to the east are characterized by mtDNA profiles that feature higher frequencies of deep-rooted lineages indigenous to South Asia63. Likewise ethnic groups from KPP are marked by generally show close affinities to one another, but share only distant affinities to populations from Iran, Uzbekistan and Kazakhstan85. Sharma et al.134 further noted the mtDNA divergence between ethnic groups of Jammu and Kashmir in northern India to be greater than within Pakistani groups or populations from Europe and the Caucasus. Such results not only document the limited impact of the medieval incursion of different Pashtun ethnic groups from Afghanistan and the Iranian Plateau into the northwestern periphery of South Asia, but also suggest that such introgressive events involved non-local individuals of both sexes, rather than being limited to males164.This explanation corroborates results obtained in other mtDNA studies from South Asia168. For this reason, the Tanolis are relatively dissimilar to other KPP and comparative populations. From a mtDNA perspective, Tanolis have a high frequency of haplogroup N3, which arose in Western Eurasia, as well as higher frequencies of SA haplogroups such as M2-M6 than other populations. As a result, Tanolis show genetic similarities with Siddi169 and other populations from India.Tanolis, whose communities are restricted to hilly area of Swabi District along the border with Buner and Haripur Districts of KPP, have predominantly R1b1a-P297 Y-chromosomes, along with a low frequency of SA and EA haplotypes. Based on several studies, haplogroup R1b is thought to have spread with pastoralism and Indo-European speakers into South AsiaGiven this genetic profile, Tanolis may be an outlier within the Indo-Pakistani subcontinent. While suggested to have Turkic roots, and also claiming Pashtun ancestry tracing to the fifteenth century CE, the Tanolis appear to have a different genetic origin than the other four KPP ethnic groups. It is possible that they have experienced significant genetic drift, perhaps due to founder effects, which would affect the frequencies of their paternal lineages. Yet, the latter scenario is not consistent with the high proportion (47.8%) of South Asian mtDNA lineages observed in Tanolis relative to other KPP ethnic groups.171. They also exhibit genetic affinities with other Yousafzais populations83. The Yousafzais also exhibit considerable mtDNA diversity. Their maternal lineages are largely of WE derivation, with moderate frequencies of SA and low frequency of EA haplotypes also being present. Based on these data, the Yousafzais show genetic similarities to Central Asian and other Pakistani populations.Yousafzais are the most genetic diverse KPP population in this study. While exhibiting a high frequency of R1a1a Y-chromosomes, they also have a mixture of other NRY haplogroups, including West Eurasian G2, I2, J1 J2, South Asian H, L, R2 and East Asian O3, Q. Four of these haplogroups  are likely associated with male-mediated migrations related to Neolithic farming80, and also integrated local females into their population, either as spouses and daughters of local non-Pathan converts or through hypergamous unions with Yousafzai men80. Both avenues of gene flow are well-documented throughout South Asia175, including regions of northern Pakistan such as Gilgit-Baltistan147, most likely reflect endogamous practices that involved the assimilation of foreign females into the populations.Overall, Yousafzais are marked by affinities to local non-Pathan groups both paternally and maternally. Such findings suggest that Yousafzais absorbed a number of local males, perhaps through religious conversion of the most successful landholdersAs described above, the patterns of mtDNA and NRY diversity amongst the KPP ethnic groups are fairly different, suggesting contrasting paternal and maternal genetic histories for them. We have attempted to situate these data in the context of archaeological, ethnographic, historical, genetic, and linguistic evidence to better explain the complex pattern of ethnic diversity in Pakistan and the KPP region. Yet, as shown in this genetic analysis, there are many uncertainties in the population histories of these ethnic groups. Future analysis of mitogenome and whole genome sequences will greatly facilitate the testing of the hypothesized origins and biological relationships of KPP populations outlined in this study.Ethnographic fieldwork and sample collection were undertaken in 13 villages located within Buner and Swabi Districts of KPP in 2014–15  defining the major branches (haplogroups) of the human mtDNA phylogeny with custom TaqMan assays179. All variable positions were determined relative to the revised Cambridge Reference Sequence (rCRS)181. The CR sequence data defined maternal haplotypes in these individuals, and all haplogroups were ascertained relative to existing mtDNA databases, such as Phylotree version 17183. A single PCR–RFLP test was also used to screen mtDNA samples for the 14,766 SNP that characterizes haplogroup HV.Samples were then surveyed for sequence variation through control region (CR) sequencing using published methods186. The SNP genotyping involved 47 custom TaqMan assays that were read using the ABI 7900HT Fast Real-Time PCR System179. They were then additionally surveyed for variation at 17 Y-STR loci using the ABI Y-filer Kit, as previously described179. Two other STR loci, along with six insertion–deletion (indel) SNPs, were genotyped in a separate custom multiplex assay179. The multiplex PCRs were read on an ABI 3130xl Genetic Analyzer with POP-4 polymer using GeneScan™-500 LIZ™ size standards. The resulting data were analyzed using GeneMapper1 ID Software v3.2. STR allele sizes were identified based on previous recommendations187. Quality control procedures included checking SNP genotypes for phylogenetic consistency and comparing the data with haplogroups predicted from STR profiles (http://www.hprg.com/hapest5/index.html). The paternal haplotype for each sample was designated by its full 19-STR locus profile.Paternal genetic ancestry was elucidated through analysis of NRY variation in male participants. The DNAs of 678 individuals were screened for phylogenetically informative SNPs in a hierarchical fashion according to published information and previously published methods184 and detailed in PhylotreeY188. All of the Y-STR haplotypes were further checked for their haplogroup status using Athey’s (http://www.hprg.com/hapest5/) and the Nevgen Y-DNA (http://www.nevgen.org/) haplogroup predictors. The SNPs and STR alleles defined the haplogroups and haplotypes, respectively, for each male individual.Y chromosome lineages (haplogroups) were defined as the unique combinations of SNP and STR data present in the samples. DYS389b was calculated by subtracting DYS389I from DYS389II, which was used for all statistical network analyses. Each male sample was assigned a SNP haplogroup following the conventions outlined by the Y-chromosome ConsortiumWe compared the mtDNA and NRY data obtained from the five Pakistani ethnic groups to those from populations in South Asia, Central Asia, East Asia, Middle East and Europe in an effort to place the genetic histories of these five Pakistani ethnic groups within a broader framework. For the mtDNA analysis, we examined a total of 11,411 mtDNA HVS1 sequences, including 659 from this study and the rest from comparative populations in South, Central and East Asia, Europe, Caucasus, and the Near East Table . In addi189. Descriptive statistical indices, as well as Tajima’s D190 and Fu’s FS191 neutrality tests, were calculated using the same software. Pairwise FST and RST distances values between populations were calculated from HVS-1 sequences and Y-STR haplotypes using the same software. FST values were estimated with the Tamura and Nei (1993) model of sequence evolution. The resulting matrices were visualized in Neighbor-joining trees using MEGA version X192. For both the mtDNA and NRY data sets, the genetic structure of Pakistani and comparative populations was examined through analysis of molecular variance (AMOVA) in Arlequin v. 3.5.2.1189.Haplotype diversity (h), nucleotide diversity (p) and pairwise differences were calculated for mtDNA HVS-1 sequences  and Y-STR haplotypes using Arlequin v. 3.5.2.1193 were constructed for both mtDNA HVS-1 sequences and Y-STR haplotypes using Network version 5.0.1.1194 to explore the phylogenetic history of the genetic lineages encompassed within the five sampled ethnic groups. For mtDNA HVS-1 sequences, the mutation-weighting scheme was based on that described by Bandelt and coworkers195, in which fast-evolving sites were given lower weights relative to less mutable sites. All variants known to result from homopolymeric C expansions  or to occur at mutational hotspots in the mtDNA CR  were excluded from the haplotypes used in this analysis.Median-joining networks196 by applying a fivefold weighting scheme with higher weights given to slowly evolving markers and lower weights to faster evolving markers. The multicopy marker DYS385 was not used in the analysis because the differentiation between its alleles was not possible to ascertain using the Y-Filer kit187.The NRY haplotypes used to generate the networks for specific haplogroups consisted of 17 Y-STR loci. Y-STR loci were weighted according to their individual mutation rates198. This interpolation does not take into account natural land boundaries, water boundaries, or cultural boundaries that would affect the falloff of influence from neighboring sample points, since it is solely based on geographic distance.The GPS coordinates for the KPP and comparative populations were determined and used to create geospatial maps of haplogroup frequencies with QGIS Desktop v.3.20.0 using the EPSG 4326 coordinate system. The resulting maps were exported at a scale of 1:48,000,000. Continent and country boundary vector data were procured from free-use, publicly available World Health Organization assets. The data points were organized by latitude/longitude coordinates from Tables Supplementary Information 1.Supplementary Information 2.


Drosophila suzukii, or spotted-wing drosophila, is now an established pest in many parts of the world, causing significant damage to numerous fruit crop industries. Native to East Asia, D. suzukii infestations started in the United States a decade ago, occupying a wide range of climates. To better understand invasion ecology of this pest, knowledge of past migration events, population structure, and genetic diversity is needed. In this study, we sequenced whole genomes of 237 individual flies collected across the continental United States, as well as several sites in Europe, Brazil, and Asia, to identify and analyze hundreds of thousands of genetic markers. We observed strong population structure between Western and Eastern US populations, but no evidence of any population structure between different latitudes within the continental United States, suggesting that there are no broad-scale adaptations occurring in response to differences in winter climates. We detect admixture from Hawaii to the Western United States and from the Eastern United States to Europe, in agreement with previously identified introduction routes inferred from microsatellite analysis. We also detect potential signals of admixture from the Western United States back to Asia, which could have important implications for shipping and quarantine policies for exported agriculture. We anticipate this large genomic dataset will spur future research into the genomic adaptations underlying D. suzukii pest activity and development of novel control methods for this agricultural pest. Drosophila suzukii (Matsumura), also known as the spotted-wing drosophila or the Asian vinegar fly, has become an incredibly invasive pest species and a threat to soft-skinned fruit agricultural production worldwide  used six X-linked gene fragments from flies collected across the world, and detected signals of differentiation between European, Asian, and US populations. However, they found no evidence of differentiation within the 12 US populations sampled, possibly due to the limited power provided from a small number of markers. A follow-up study using 25 microsatellite loci of samples collected between 2013 and 2015 greatly improved estimations of migration patterns worldwide; the authors found evidence for multiple invasion events from Asia into Europe and the United States as well as an East–West differentiation in the seven populations sampled in the continental United States . Hawaiian samples were taken from a small laboratory population maintained in vials that was established in 2009 from wild-caught samples in Oahu, Hawaii. All other samples were field-collected. Ethanol-preserved samples were re-hydrated in 100-μL water prior to DNA extraction. Flies were individually disrupted using a 3-mm diameter steel bead in a TissueLyser  for 30 s at 30 Hz in 100 μL of 2 mg/mL Proteinase K in PK buffer  before being spun down in a centrifuge for 1 min at 10,000 rpm and incubated for 2 h at 56°C. 100 μL of MagMAX DNA lysis buffer was added to each sample, followed by a 10-min incubation, before proceeding to DNA purification using a BioSprint DNA Blood Kit on a BioSprint 96 Workstation (Qiagen), using protocol “BS96 DNA Tissue” as per manufacturer’s instructions. Supplementary Table S1 contains all sample names, collection locations, and time of collection.We received either flash-frozen or ethanol-preserved samples of Illumina WGS libraries were prepared with either the Kappa HyperPlus Kit  (lanes 2-4) or Qiaseq FX DNA Library Kit (Qiagen) (lanes 5–8) using 50 ng of input DNA following the manufacturer’s instructions with few exceptions. With the Kappa HyperPlus Kit, DNA was fragmented at 30°C for 20 min and incubated with adapters for 1 h. A 0.6× and 0.7× size selection with AmPure XP beads  was added after five cycles of PCR amplification with an Eppendorf Master Cycler Pro (ThermoFisher Scientific). With the Qiagen FX kit, DNA was fragmented at 30°C for 15 min and amplified with seven cycles of PCR. In both cases, DNA library concentration and fragment size were quantified on a Qubit 2.0 fluorometer with the Qubit dsDNA HS assay kit (ThermoFisher Scientific) and a Bioanalyzer High-Sensitivity DNA chip . Paired-end 150 base-pair sequencing was performed by Novogene, Inc.  on the Illumina HiSeq 4000 platform.D. suzukii reference genome obtained from Dr. Benjamin Prud'homme (now available at GenBank accession GCA_013340165.1) , and trimmed for low-quality bases and adapter sequences using Trimmomatic version 0.35 (40165.1) , sorted D. suzukii mitogenome sequence and ten D. pulchrella COX2 sequences were downloaded from NCBI. The Drosophila subpulchrella mitogenome was identified by running BLAST with the D. suzukii mitogenome against the D. subpulchrella genome assembly (GCA_014743375.2), and annotated using MITOS2 , filtering out any read pairs where one of the reads was unmapped (samtools view –f 2 –F 4). Variants were called with Freebayes version 1.1.0 in haploid mode .The oid mode , and fasG, parameter = 0.1066).All COX2 sequences were aligned with the ClustalOmega web portal  were estimated from aligned reads with ANGSD version 0.935  and D. subpulchrella (SRA accession SRX8970519). GLs and SNPs were called with ANGSD as described above and pruned by only keeping SNPs found originally in the 1-kb pruned dataset used for PCA and admixture analysis. As X-linked and autosomal SNPs may have different phylogenetic signals, X-linked SNPs were excluded. As Treemix requires genotypes to be called, PCAngsd was used to call genotypes from the GLs with a 95% posterior probability cutoff using estimated inbreeding coefficients as a prior. When looking at the distribution of fraction of missing genotypes per site, we observed a peak at 10%, and decided to exclude any sites with greater than 20% missing data across samples, consistent with cutoffs in other studies  was excluded as it unexpectedly clustered with the Western US populations. To root the population trees, two sister species of Z-scores. The F3 statistic tests if population A’s allele frequencies are a result of mixture of allele frequencies from populations B and C. A significantly negative value of F3 supports admixture of B or C into A. The F4 statistic measures correlations in allele frequencies between populations A and B versus populations C and D. F4 is expected to be zero under no admixture. Assuming the tree ,) exists, a significantly positive value suggests gene flow between A and C or B and D, while a significantly negative value suggests gene flow between B and C or A and D. By setting one of these populations to be an outgroup where no admixture is expected, it is possible to infer which population pair experienced admixture. We used a Z-score cutoff of 2 or −2 to determine if a value was significantly positive or negative.Treemix version 1.13  was usedSite allele frequencies were estimated for each cluster from the largest 20 contigs of the genome assembly with ANGSD version 0.933 using the samtools GL model, filtering for a minimum mapping quality = 20 and minimum base quality = 20. The subprogram real SFS from ANGSD was used to estimate a two-dimensional folded SFS for all pairs of clusters and to calculate the global weighted Fst for each cluster pair. RealSFS was also used to estimate one-dimensional folded SFS for each cluster in order to calculate nucleotide diversity and Tajima’s D per site. The command ANGSD/thetaStat do_stat was used to bin these summary statistics in 20-kb windows across the genome.D. suzukii living in recently invaded locations, we sequenced wild-caught individual D. suzukii flies collected from the continental United States, Brazil, Ireland, Italy, South Korea, and China, as well as a laboratory strain from Hawaii and Japan . As several sister species to k = 2 in admixture plotting. We also observe that samples from Asia partition into Japan and South Korea, which is unsurprising as the Japanese samples originate from a laboratory population.As sampling was heavily concentrated in the United States, we first conducted PCA and admixture proportion estimation on each broad geographical region separately before analyzing all populations together . Among the Eastern US samples, PCA did not separate samples by state or latitude, and no distinct populations emerged in admixture plotting at multiple clustering values (k). Among the Western US samples, both the first principal component and varying values of k for admixture proportions separates Hawaii from the other sample sites; however, higher values of k and principal components do not further partition the remaining Western US samples. Thus, it appears there is likely no strong population structure in a north to south cline in the United States. Using a similar approach, we see that in the European samples, collections from Ireland and Italy partition as separate clusters in the first PC and when We then used PCA to analyze all samples together to examine how differentiated invasive populations were from each other and from the ancestral Asian samples . As subtk = 3, we observe Japanese and Hawaiian samples form their own clusters, while all the wild collections form a third cluster. As k is increased up to 7, we see the appearance of Europe, Brazil, Eastern United States, and South Korea samples as their own clusters, before samples from Europe are split into Ireland and Italy at k = 8. We notice increased variability in cluster assignment in the US populations, particularly when subsampling, which likely reflects the large sample size and high within-population diversity . However, analysis using all individuals still clearly supports Eastern and Western US samples as distinct genetic populations . In addition, we also see that the AR Georgia population again clusters with the Western United States. As we were unsure if this could be the result of a very recent migration or mislabeled samples, we decided to exclude this population from further analyses.The observations made from PCA are largely recapitulated when using subsampled data to estimate admixture at varying levels of k . At k = To further quantify the amount of differentiation present between regions, we estimated Fst values between regions using the 20 largest contigs, spanning all 4 chromosomes and covering 54% (145 Mb) of the reference genome . Three gP < 0.05), and was also observed in most models  (Supplementary Table S5). To formally test for admixture, we used the F3 admixture statistic in the form F3 where popX represents any third population, and found significantly negative values for all populations (Z-score < −2), strongly supporting admixture of Hawaii into the Western United States (Supplementary Table S3). We also used the F4 statistic, using the form F4 such that a negative value supports “B” and “C” admixture, whereas a positive value supports “A” and “C” admixture, assuming no migration occurred between the outgroup and either A or B. Using either D. biarmipes or D. subpulchrella as the outgroup, the tests F4 and F4 were significantly positive (Z score > 2), again supporting this admixture (Supplementary Table S4). Thus, the Western US population sampled is composed of nearly equal ancestry from a Hawaiian ancestor and the common ancestor of the US/Brazil populations. As Treemix assigns the edge with smaller weight to be the “migrant” edge by default, it may be unidentifiable whether the Hawaiian ancestor or the US/Brazil common ancestor should be called the migration source.While PCA and admixture proportion estimates were able to identify population clusters, they are unable to provide more detailed depictions of population history or migration events. To estimate the population history of these invasive populations, we used Treemix to generate a population admixture graph with inferred migration events based on co-variance of allele frequencies between clusters, testing models allowing between 0 and 10 migrations (m) . We found that the model using six migrations captured the most variance of the data (99.6%) . ResiduaP < 0.05), although at varying values of “m” the source of this admixture fluctuates between the Eastern United States, Brazil, or the Eastern US/Brazil ancestor. However, in all cases, the admixture strength and significance remain consistent (Supplementary Table S5). While no F3 statistic support was found, the F4 statistics  and  were significantly negative, supporting Ireland’s Eastern US/Brazilian and European ancestry. As the US/Brazilian admixture weight is much less than the European admixture weight, this was likely due to a migration event from the Americas into Irish populations.We also observed two countries with US admixture in the m = 6 model. Ireland had an Eastern US admixture of 25.3% , was seen when m = 6, 8, and 10. F3 statistics  all have significantly negative values, and the F4 statistics  and  are significantly positive, supporting a Western US/South Korea admixture. However, using nine migration edges Treemix reported the reverse direction; as F3 and F4 statistics cannot easily infer directionality, more heavily sampling of the Asian populations or alternate methods may be needed to determine whether flow is occurring in both directions.The other out-of-US admixture event, from the Western United States to South Korea  found a significant difference in mean pairwise nucleotide diversity between clusters. We then used pairwise Games-Howell tests and found each cluster to be significantly different (P < 0.05), except for the Eastern United States, Brazil, and Italy when compared with each other. As Asia is the ancestral home of D. suzukii, it is no surprise that South Korean wild populations exhibit the highest diversity levels , and pairwise Games-Howell tests found all clusters to be statistically different (P < 0.05) except for Western US against Brazilian flies. Strains from Hawaii and Japan both had high genome-wide levels of Tajima’s D, indicative of a loss of rare alleles that can occur during a population shrinkage  can indicate a loss of rare alleles, which can occur during a population shrinkage, whereas extremely negative values (<−2) can indicate a recent bottleneck followed by rapid expansion . A Welchhrinkage . The remhrinkage .D. suzukii exhibit population structure based on region and invasion history. In the New World populations, we find that Eastern and Western US samples appear to be distinct populations. While this could be the result of continuous population variation from East through Central to the West coast, it is more likely the case that the two populations experience little gene flow due to strong geographical barriers such as the Sierra Nevada or Rocky Mountain ranges, and the fact that key target fruit crops such as cherries, raspberries, blueberries, and strawberries are primarily grown in states that we sampled  to be only moderately below that of the wild South Korean population, a trend also observed in D. suzukii have been experimentally tested on multiple lines to ensure the miRNAs are broadly effective , prior knowledge of allelic variation will allow researchers to design targeting oligonucleotides more precisely to avoid loci with variability. Most recently, our dataset has been used to study sensory receptor evolution in D. suzukii, giving insights into its evolution toward becoming a major agricultural pest , such as for the purpose of creating gene drives to control invasive species. Gene drive mechanisms to eliminate https://doi.org/10.25387/g3.16655185. Scripts used to run all analyses can be found at www.github.com/ClockLabX/Dsuz-popgen.Raw Illumina reads have been deposited to the NCBI Sequence Read Archive (SRA) and can be found under BioProject accession number PRJNA705744. Supplementary Table S2 contains GenBank accessions of COX2 sequences used. Supplementary Tables S3 and S4 contain F3 and F4 statistics for all populations calculated by Treemix. Supplementary Table S5 contains all migrations inferred from Treemix at all migration values tested. Supplemental figures and tables have been uploaded to GSA figshare portal:


Indigenous cattle breeds are important to their native environment as they confer significant and often unique adaptability traits. The Nguni is one such breeds that is indigenous to the Southern African region. This breed confers resistance to thermal stress and diseases, amongst other factors. The bovine major histocompatibility complex is an important region, which codes for alleles that have been associated with a plethora of diseases. In the current study, the genetic diversity within this region was assessed in Nguni crossbred cattle. This was done to detect the gene pool of the Nguni breed, and to identify genes that might be important within this breed. The populations displayed a high degree of genetic diversity, and some alleles were common throughout the populations and accounted for a significant portion of the total alleles. This high genetic diversity could account for the great adaptability of the Nguni breed to Southern Africa. BoLA-DRB3) gene is an important region that codes for glycoproteins responsible for the initiation of an immune response. BoLA-DRB3 alleles have been demonstrated to be associated with disease resistance/tolerance. Therefore, great genetic diversity is correlated with better adaptation, fitness, and robustness. The current study was conducted to assess the population genetic structure of the BoLA-DRB3 gene in Nguni crossbred cattle using polymerase chain reaction-sequence based typing (PCR-SBT). High genetic diversity was detected, with 30 alleles, 11 of which are novel to the study. Alleles DRB3*0201, DRB3*0701, DRB*0901, and DRB*1601 were present in all populations and accounted for nearly around 50% of all observed alleles. A mean genetic diversity (HE) of 0.93 was detected. The high overall genetic diversity is possibly associated with pathogen-assisted selection and heterozygote advantage. Such high diversity might explain the hardiness of the Nguni crossbred cattle to the Southern African region. Low population genetic structure was identified (FST = 0.01), suggesting possible gene flow between populations and retention of similar alleles. The study was undertaken to bridge the dearth of such studies in South African breeds and it is imperative for effective sustainability of indigenous breeds and the implementation of effective breeding strategies. The bovine lymphocyte antigen ( The major histocompatibility complex (MHC) is one of the most important genetic regions in living organisms as it is ultimately responsible for the resistance or susceptibility to diseases . GeneralBoLA) and is located on chromosome 23 [DRB loci have been identified, namely, DRB1, DRB2, and DRB3, these genes encode the β-chain of the DR molecule [DRB1 gene is a pseudogene comprised of multiple stops codons and low genetic diversity [DRB2 is a monomorphic region with very low expression levels [DRB1, the DRB2 gene is yet to be elucidated further. The most functional and highly expressed is the DRB3 gene [BoLA-DRB3 is characterized with increased genetic variation and an even distribution of alleles [BoLA-DRB3 region. It is therefore ideal for populations to encompass significant variation in the MHC given that the greater the genetic diversity the greater the spectrum of pathogens that can be identified. Furthermore, this diversity is retained in populations due to various selective mechanisms such as pathogen-mediated selection. As a host’s immune system develops defensive mechanisms against a pathogen, the pathogen in turn develops defense systems and it is this arms race that will require the host to accumulate and retain genetic diversity [In cattle this component is termed the bovine lymphocyte antigen . The field sampling protocols, samples collected from animals, and the research were conducted in full compliance with Section 20 of the Animal Diseases Act of 1984 (Act No 35 of 1984) and were approved by the South African Department of Agriculture, Forestry and Fisheries DAFF . Blood samples of 139 Nguni crossbreds were collected from six different populations. The different populations were defined based on their common shared geographical area, therefore, all individuals from the same population shared the same communal grazing area and they were allowed to interbreed. Furthermore, these populations were collected in two different districts, which are connected by a common road (R56). The sampled populations were Bhongweni = 22; Kromhoek = 24; Mbotho = 21; Shayamoya = 24; Thembeni = 24; and Weza = 24, which are within the province of KwaZulu-Natal, South Africa . Of the Animals shared communal grazing land and were devoid of defined breeding systems. Some animals were herded on a daily basis due to high levels of theft in certain areas, however the majority were allowed to graze without any herdsmen. The majority of the animals in the sampled populations were Nguni crossbreds, and some were non-descript crossbreds. However, most people preferred the Nguni crossbred, and this was evident from the number of these crossbreds. The majority of breeds that were crossed with the Nguni were Angus, Brahman, and Bonsmara. However, due to lack of animal recording and defined breeding strategies, the exact contributing breeds resulting in the sampled composite could not be ascertained. Blood samples were collected from the tail of individuals at dipping facilities under the supervision of representatives of the Department of Agriculture in KwaZulu-Natal. Approximately 3 mL of blood was collected from the tail vein of each individual. The blood samples were stored in VACUETTE tubes coated with EDTA  with immediate storage on ice. Genomic DNA was extracted from each sample using the Quick-gDNA Blood Miniprep  following the manufacturer’s instructions. Sampling was done with the aid of local herdsmen to avoid sampling related individuals within the same herd; hence all study individuals were presumed to be unrelated.BoLA-DRB3 locus was amplified as described by van Eijk et al. [The second exon of the k et al. , with soThe second amplification round was also conducted in total volume of 25 µL containing 1× DreamTaq Green PCR Mastermix , 0.5 µM of each of the two primers; HLO30 5′-ATCCTCTCTCTGCAGCACATTTCC-3′ and HLO32 5′-TCGCCGCTGCACAGTGAAACTCTC-3′, and 2 µL of the PCR products of the first round. Thermal cycling was employed using the following conditions; 40 repeats of 94 °C for 1 min and 65 °C for 30 s and a final extension step of 72 °C for 5 min. The PCR amplicons were then separated by gel electrophoresis in a 1% agarose gel and viewed under ultraviolet illumination after staining with ethidium bromide. Thereafter, the PCR products were cleaned by mixing 10 µL of the PCR product with 2.5 µL of Exo/SAP mix; exonuclease 1 (NEB M0293) 20 U/µL; Shrimp alkaline phosphatase (NEB M0371) 1 U/µL. The mixture was incubated at 37 °C for 30 min then the reaction was stopped by heating the mixture at 95 °C for 5 min. DNA sequencing was then conducted using the ABI V3.1 Big dye kit  in accordance with the manufacturer’s instructions on an ABI 377 automated sequencer . The Zymo Seq clean-up kit  was used to clean the labelled products thereafter, the products were injected in the ABI 3500XL Genetic Analyzer  using POP7. A representation of the sequences that emanated from the South African crossbred Nguni cattle from our study were deposited in GenBank with accession numbers MN721876 to MN721885.Number of alleles (NA) and allele frequencies were obtained through direct counting, the formula employed by Das et al.  was utilGenetic partitioning among and within populations was detected by means of analysis of molecular variance (AMOVA) utilizing 1000 permutations in ARLEQUIN 3.5. Genetic differentiation was evaluated using exact tests  employinDRB3*0201, DRB3*0701, DRB*0901, and DRB*1601 were present in all populations and accounted for nearly around 50% of all observed alleles in the populations. DRB3*0901 was the most frequent in the study with a frequency of 0.144, and DRB3*03021 was only detected in the Shayamoya population with moderate frequency (>0.5). A total of 30 alleles were identified in the studied population . Of thosDRB3*1 and DRB3*8, were identified with a frequency greater than 0.5 in the Bhongweni and Thembeni populations, respectively. Expected heterozygosity ranged from 0.882 for Mbotho to 0.941 for Bhongweni  to 19  to 3.3% (between Bhongweni and Shayamoya), and Slatkins FST indices ranged from 0 to 4.7% for the same population pairs. The genetic diversity was partitioned into two sources of variation, viz. variation among populations and variation within populations, in an AMOVA. It was revealed that the majority (99%) of the genetic variation can be explained by genetic diversity within individuals in the populations and only 1% of the variation can be explained by genetic differences amongst populations . Limitedof 0.011 A and Slaof 0.014 B. Of allBoLA-DRB3 gene is highly important and plays a crucial role in the response of T-cells to pathogens [https://www.ebi.ac.uk/ipd/mhc/group/BoLA/, accessed on 3 March 2021). Hence, substantial genetic variation in this region could account for the association between efficient immune response and disease resistance [BoLA-DRB3 region. Exon 2 of the athogens . To datesistance ,38. The DRB3*0201, DRB3*0701, DRB*0901, and DRB*1601 were found to be present in all the studied populations. Several studies have been conducted to assess possible associations between DRB3 alleles and disease resistance, they have been shown to be significantly correlated with CD4, CD8, and CD12 cells [0201, *0901 [*0901 allele has demonstrated an association with resistance to bovine leukemia virus (BLV) in different regions [*0201 amongst others in Hereford steers [*1601 has shown a response to FMD vaccines [*0201 and *0901 have been illustrated to be associated with several diseases in different species of cattle. This suggests that these alleles play an important role in disease resistance. All populations in the current study possessed high frequencies of both alleles. Further validation studies across the spectrum of African cattle breeds across different countries need to be conducted and possible marker assisted selection to improve disease resistance in cattle. The Nguni is a breed that is very common in South Africa. It was introduced into southern Africa by way of three migrations by pastoralists . It is w1, *0901 ,49. Furt regions ,50. The d steers  and allevaccines . The twoThere was favorable genetic distribution within populations as this was evident from the high levels of observed heterozygosity. Three of the six populations  display an excess of heterozygotes and partial outbreeding. However, no population displayed significant heterozygote excess or deficiency and did not violate HWE. Heterozygote advantage (overdominance) or recent bottleneck events that results in reduced effective population sizes  could beST indices depicted very limited genetic difference between populations, these estimates ranged from 0 (between Thembeni and Weza) to 3.3% (between Bhongweni and Shayamoya). They were comparable to genetic differentiation (FST = 0.009) identified in Holstein cattle [The BoLA-DRB3.2 locus is defined by a low population structure in South African Nguni cattle. Pairwise Fn cattle , albeit n cattle ,61. The n cattle . Furthern cattle , which in cattle , which sThe use of adaptive/non-neutral markers, such as the BoLA-DRB3 gene in this study, is vital in studying the population genetics and the extent of local adaptations in species . NonetheAn analysis of molecular variance depicted that the majority of genetic variance (99%) was partitioned within populations and only 1% of the genetic variance was between populations. This depicts an even allele distribution between populations. The low population genetic differentiation returned can be explained by environmental and pathogen-mediated selection , whereby similar alleles will be maintained in populations due to their relative fitness, and since these populations belong to the same province environmental conditions and other stressors are expected to be somewhat constant across populations hence possibly enabling the retention of similar alleles. Gene flow may also be shaping the genetic structure of the current populations, it is common for farmers to exchange cattle between different regions given the accessibility of the study areas. BoLA is amply illuminated association studies of immunological traits can be assessed and sustainable breeding systems can be put into place.Great genetic diversity was detected with 11 novel alleles identified. This high genetic diversity could possibly be maintained by a heterozygote advantage (overdominance). Low population differentiation was returned, which points to the retention of similar alleles between populations. Such information is crucial for defining the gene pool of indigenous breeds and outlining the genetic basis of their adaptation to local environments. When the genetic architecture of the


Wolbachia is among the most widespread symbionts in insects. Wolbachia typically spreads within host species by conferring direct fitness benefits, and/or by manipulating its host reproduction to favour infected over uninfected females. Under sufficient selective advantage, the mitochondrial haplotype associated with the favoured maternally-inherited symbiotic strains will spread (i.e. hitchhike), resulting in low mitochondrial genetic variation across the host species range.Evolutionary processes can cause strong spatial genetic signatures, such as local loss of genetic diversity, or conflicting histories from mitochondrial versus nuclear markers. Investigating these genetic patterns is important, as they may reveal obscured processes and players. The maternally inherited bacterium Ischnura elegans: van der Linden, 1820) has recently emerged as a model organism for genetics and genomic signatures of range expansion during climate change. Although there is accumulating data on the consequences of such expansion on the genetics of I. elegans, no study has screened for Wolbachia in the damselfly genus Ischnura. Here, we present the biogeographic variation in Wolbachia prevalence and penetrance across Europe and Japan (including samples from 17 populations), and from close relatives in the Mediterranean area .The common bluetail damselfly  potential transfer of the symbiont through hybridization, (c) higher infection rates at higher latitudes, and (d) reduced mitochondrial diversity in the north-west populations, indicative of hitchhiking associated with the selective sweep of the most common strain. We found low mitochondrial haplotype diversity in the Wolbachia-infected north-western European populations  of I. elegans, and, conversely, higher mitochondrial diversity in populations with low penetrance of Wolbachia . The timing of the selective sweep associated with infected lineages was estimated between 20,000 and 44,000 years before present, which is consistent with the end of the last glacial period about 20,000 years.Our data reveal (a) multiple Our findings provide an example of how endosymbiont infections can shape spatial variation in their host evolutionary genetics during postglacial expansion. These results also challenge population genetic studies that do not consider the prevalence of symbionts in many insects, which we show can impact geographic patterns of mitochondrial genetic diversity. Range expansion studies have uncovered waves of demographic expansion in many species by comparing the genetic diversity of the initial source to that of the edge populations. Often, but not always (e.g. ), range Wolbachia can be found in up to half of all arthropod species  & [IK]) carry Wolbachia strains that are divergent from wEle1, and which may have altered the genetics of those populations in ways that are impossible to fully test due to our small sample size for these populations. Therefore, we did not include these sequences in further analyses. The final sample size was 31 sequences, including 23 Wolbachia-uninfected specimens and 8 Wolbachia-infected specimens from five populations  and Fu and Li’s F , Greece [GR], Cyprus [CY], Finland Åland [ÅL], Ukraine  and Central Japan [RK] were Wolbachia-free. Note that the infection screening of the Japanese samples was done using leg tissues, which do not always host Wolbachia cells. Although all samples from [IK] were found infected, the Wolbachia-free status of [RK] could still be an underestimation of the true infection rate in this population. Additionally, all 13 I. pumilio specimens from Sweden were infected. The I. genei specimen from Corsica Island [CO] was infected, while the other two from Sicily [SI] and Sardinia [SD] were not. The single I. saharensis specimen from Morocco was also uninfected.There were geographical variations in ns Table ; Fig. 1.Wolbachia strains from the B-supergroup Wolbachia commonly found in insects, were identified in I. elegans  and Ukraine [VC] , and wEle3 was found in mainland Finland [FL] and Japan [IK]. The I. genei specimen from Corsica was also infected with the strain wEle1; while I. pumilio was found to carry two divergent strains, denoted wPum1 and wPum2, with eight specimens (out of 13) potentially carrying the two strains simultaneously. Note that we characterized these strains using only two markers, which combination should allow the differentiation of most strains, but possibly not of all strain variants ), and absent from a few other populations , Åland [ÅL]). We showed that the few uninfected individuals found in the Western European populations carry the same mitochondrial haplotypes as their wEle1-infected conspecifics (Haplo1 and Haplo3), contrasting with the uninfected specimens from Eastern Europe that show a wide diversity of divergent mitochondrial haplotypes. This may suggest that the maternal transmission of the strain is not perfect and that few offspring from infected mothers can hatch uninfected in these populations. Additionally, two hypotheses could explain differences between populations: (I) wEle1 has spread across the western populations but did not yet invade the remaining populations, or (II) wEle1 has spread across the whole Europe in the past, but the infection was consequently lost in Eastern populations. For the first hypothesis, Wolbachia-infected population would show reduced mitochondrial haplotype diversity, while uninfected populations would have high mitochondrial diversity [Although we found iversity , 91. In iversity , 88. TheWolbachia-uninfected. The Cyprus population is located at the southern range limit of I. elegans in Europe. There, the strong divergence of the mitochondrial haplotypes to those associated to the infection in Western Europe suggests that the population has remained uninfected potentially due to its geographic isolation. The population differ phenotypically in several aspects from other continental populations, particularly in terms of smaller average body size and deviant colour morph frequencies [wEle1 in Sweden, and is identical to the haplotype associated with wEle3 in mainland Finland . These results better support the second hypothesis described above, in which the Åland population may have lost its infection recently. However, the I. elegans specimens collected in Åland all came from a single collection site in the southern part of the main island (i.e. Nåtö). Thus, these specimens might not be representative of the true average infection status of the entire Åland populations, and more mitochondrial genetic data will be needed to infer whether I. elegans colonized the Åland islands (I) after the sweep of wEle1 in Sweden, or (II) after a sweep of wEle3 in Finland and subsequently lost the infection and diverged at the mitochondrial level. Similarly, the uninfected individuals from Greece and Ukraine carry similar, to identical, mitochondrial haplotypes to the wElel1-infected samples, which is also consistent with recent infection loss and divergence from an original population.The two populations originating from the Cyprus island in the Mediterranean Sea and from the Åland islands in the Baltic Sea, were both quencies . In contWolbachia is frequently lost [Wolbachia titers in some Drosophila species [Hyposoter horticola (Hymenoptera) [Wolbachia penetrance across local populations  , which son rate, ). InfectI. elegans damselflies carry two closely related mitochondria (Haplo1 and Haplo6), found in association with two closely related Wolbachia strains . Both mitotypes and Wolbachia strains may have diverged after isolation in geographically separated refugia on the Italian peninsula during the last glacial maximum [wEle3, the third strain characterized in all I. elegans specimens collected from Japan, and from mainland Finland, is highly divergent from both wEle1 and wEle2. The strain wEle3 is found in association with two mitochondrial haplotypes (Haplo9 and Haplo24), suggesting either haplotype diversity across the large range of this particular infection, or yet undetected bacterial diversity across the large geographical distance separating Japan from Finland. Additional sampling, screening and genotyping efforts are likely to uncover a higher strain diversity in the genus Ischnura than already suggested here and by previous studies .Wolbachia has been shown to also transfer horizontally between species. Examples include, but are not restricted to, the horizontal transfer of Wolbachia between damselfly species of the genera Nesobasis and Melanesobasis in Fiji Islands in the Pacific Ocean [Wolbachia can be horizontally transmitted via different means, including hybridization between host species [Wolbachia among Ischnura species remains unknown. In contrast, evidences of frequent hybridization and introgression have been shown in some odonate species due to latitudinal range expansion and the increasing sympatric interactions between closely related species [Ischnura [I. elegans and I. genei could suggest that horizontal transfer of the strain wEle1 between the two species occurred through hybridization.Although a maternally inherited symbiont, ic Ocean . Wolbach species , shared  species ), or sha species  or paras species ). Damsel species , 102, ho species , includiIschnura –36, 104.Wolbachia in the damselfly genus Ischnura revealed a wide diversity of previously hidden inherited symbiotic Wolbachia strains in the three species investigated. Furthermore, we detected a recent selective sweep of the Wolbachia strain wEle1 across the Western European populations of I. elegans, and we discuss the potential horizontal transfer of the strain through hybridization. The biogeographical pattern of the infection and the estimated timing of the sweep suggested that wEle1 might have spread across I. elegans populations during its host’s northern expansion after the last glacial maximum. Consequently, the mitochondrial haplotype diversity in this range expanding species has been highly reduced but started to recover from the successful spread of the symbiont. We found the symbiont in specimens of all colour morphs and both sexes, and thus the costs and benefits from the infections remain to be investigated. We clearly highlight the loss of host genetic diversity resulting from symbiotic associations and call for greater consideration of symbiotic infections in future research on the population genetics and ability of range expanding species in the context of climate change.The present biogeographic study of Additional file 1: Table S1. Pairwise genetic distance between strains using MEGA X [Table S2. List of the primers used in this study, and associated details. Table S3. GenBank accession numbers from additional sequences of the mitochondrial COI gene from diverse Ischnura species from different countries. Figure S1. The phylogeny of (A) ftsz gene and (B) wsp gene, separatelyg MEGA X . Table SAdditional file 2. The wEle1 draft genome assembly  as a fasta file.


Determining the impacts of human activities on natural populations is important for biodiversity conservation. In this paper, we study the past and more recent effects of urbanization and livestock activity on the genetic diversity and population structure of endemic guanaco populations of the arid Monte and Patagonian Steppe of central Argentina. Our results reveal that urbanization, the installation of fences, and the competition from sheep grazing coincided with the isolation of several guanaco populations, especially in areas with the highest intensity of livestock activity. However, our genetic analyses suggest that a more recent increase in connectivity among groups is occurring. Our results highlight the importance of implementing conservation management plans for natural populations in arid and human-intervened environments.Lama guanicoe) of the Monte and Patagonian Steppe of central Argentina, which have been reduced and displaced by sheep ranching and other impacts of human activities. Analyses of genetic variation of microsatellite loci and d-loop revealed high levels of genetic variation and latitudinal segregation of mitochondrial haplotypes. There were indications of at least two historical populations in the Monte and the Patagonian Steppe based on shared haplotypes and shared demographic history among localities. Currently, guanacos are structured into three groups that were probably reconnected relatively recently, possibly facilitated by a reduction of sheep and livestock in recent decades and a recovery of the guanaco populations. These results provide evidence of the genetic effects of livestock activity and urbanization on wild herbivore populations, which were possibly exacerbated by an arid environment with limited productive areas. The results highlight the importance of enacting conservation management plans to ensure the persistence of ancestral and ecologically functional populations of guanacos.Extensive livestock production and urbanization entail modifications of natural landscapes, including installation of fences, development of agriculture, urbanization of natural areas, and construction of roads and infrastructure that, together, impact native fauna. Here, we evaluate the diversity and genetic structure of endemic guanacos ( Understanding the factors and processes linked with the genetic diversity and structure of natural populations is a fundamental goal of evolutionary and conservation biology. Both population diversity and structure are the results of demographic factors, historical biogeography, and life history characteristics , and botLama guanicoe), which is well-adapted to arid and semiarid environments [L. g. cacsilensis is distributed mainly from northern Peru to northern Chile and L. g. guanicoe from the Bolivian Chaco to the Fuegian archipelago [The arid northern and central regions of Argentine Patagonia are a transition zone between the Monte and Patagonian Steppe phytogeographical provinces . The mosronments . The disronments ,12,13,14ronments . There ahipelago  since thhipelago . Today, In Argentinean Patagonia, livestock and agricultural activity began around 150 years ago along the Chubut river, following the arrival of Welsh settlers to the coastal plains near Puerto Madryn. Through the 1890s, domestic sheep were introduced, and their numbers increased rapidly, reaching a peak of 22 million individuals during the 1950s .L. g. guanicoe subspecies, including the Monte desert populations of northern Patagonia in Argentina [Effective management and conservation of livestock and guanaco populations in Patagonia require knowledge of both historical and more-recent population structure and genetic diversity of the guanacos in the region. Previous genetic studies of broad geographic and evolutionary patterns demonstrated that guanaco populations of the Patagonian steppe and Tierra del Fuego  were of rgentina , and fourgentina .To more precisely assess the impact of human activities and sheep production in the region on the genetic structure of the guanacos in northern Patagonia, we evaluate patterns of genetic variation of 15 variable microsatellite markers and one mitochondrial gene in guanacos from several locations of the arid Monte and northern Patagonian Steppe . These nGuanaco skin from dead animals and fecal samples were collected at seven localities, representing a large part of their distribution in the southern Monte and northern Patagonian Steppe of Argentina . GPS cooFourteen frequently used autosomal dinucleotide microsatellite loci , and expected heterozygosity (EH). The inbreeding coefficient ISF was estimated following [We identified samples that came from the same individual by searching for matching microsatellite genotypes using the Excel Microsatellite Toolkit  and elimollowing  and usinollowing .®®, Carlsbad, CA, USA). All PCR amplifications were performed in a PE9700 (Perkin Elmer Applied Biosystems) thermal cycler, with cycling conditions as follows: initial denaturation at 95 °C for 10 min, followed by 30–35 cycles of 94 °C for 45 s, 62 °C for 45 s, 72 °C for 60 s, and a final extension of 72 °C for 5 min. PCR products were purified using the GeneClean Turbo for PCR Kit (Bio101), following the manufacturer’s instructions. Sequence reactions were visualized using an ABI-3100 sequencer (Perkin Elmer Applied Biosystems). Products were sequenced in forward and reverse directions using BigDye chemistry on an ABI Prism 3100 semiautomated DNA analyzer, and consensus sequences were generated and aligned using Geneious v.9.1.5 . The final alignment was trimmed to 514 bp, beginning at the 5′ left domain of the d-loop.The left domain of the mitochondrial control region (514 bp) was amplified using the camelid and guanaco specific primers LthrArtio (5′-GGTCCTGTAAGCCGAAAAAGGA-3′), H15998V (5′-CCAGCTTCAATTGATTTGACTGCG-3′), and HLoop550G: 5′-ATGGACTGAATAGCACCTTATG-3′ . AmplifiThe number of segregating sites (S), haplotypes (nh), haplotype diversity (h), nucleotide diversity (π), and the average number of nucleotide differences between pairs of sequences (k) were estimated using ARLEQUIN 3.5.1.2 . A statiWe used the Bayesian clustering algorithm implemented in STRUCTURE v.2.3.3  to groupA Bayesian analysis of population structure that accounts for the geographical distribution of guanaco was performed with the R package Geneland 1.0.7 , with 1,To correlate genetic variation with geography, we estimated effective migration surfaces (EEMSs) for the microsatellite datasets . EEMS idRecent migration rates among sampling locations were assessed using BAYESASS v.1.3 , an apprWe ran a test of isolation by distance (IBD) by comparing the individual pairwise matrix of genetic distances against the corresponding geographical distance matrix using the Mantel test, with 1000 permutations in ARLEQUIN 3.5.2.2  for alte−2.5 and 10−4.5 [To identify demographic scenarios that are most consistent with current diversity patterns, we used the coalescent-based framework implemented in MSVAR v1.3 , using td 10−4.5 ,45,46,47d 10−4.5  was usedd 10−4.5  in R [50p-value > 0.05). We found consistently high levels of genetic diversity (mean expected heterozygosity ranged from 0.7083 to 0.7625) and high values for allelic richness (mean AR ranged from 1.708 to 1.762)  were present in Loma Blanca (LB). Deviation from H-W equilibrium due to an excess of heterozygotes was found in Loma Blanca (LB), Meseta Somuncura (MS), and Península Valdés (PV), as well as for the LCA22, LCA5, LCA19, and YWLL40 microsatellite markers. Additionally, a significant excess of homozygotes was found in Bajada del Diablo (BD), Las Plumas (LP), and Ameghino (AM) localities and for LCA85, LCA82, YWLL08, and YWLL38 markers. As estimates of genetic diversity excluding these loci were not significantly different from those estimated with all loci, we used all markers in further analyses (Welch-corrected t-test o 1.762) .h) and nucleotide diversity (p) estimates are detailed in Twelve variable positions (2.3%), 11 transitions, and one transversion from 514 nucleotides and 15 haplotypes were identified in 82 sequences of the 5′ end of the control region of mitochondrial DNA. Haplotype  LomThe pairwise FST values ranged from 0.032 between Meseta Somuncura and Loma Blanca to 0.124 between Loma Blanca and Las Plumas. Significant genetic differences were also observed among the three groups identified in the STRUCTURE analysis. Specifically, Group 1 included only Loma Blanca guanacos, Group 2 encompassed individuals from Meseta Somuncura, Telsen, and Península Valdés, and Group 3 consisted of Bajada del Diablo, Las Plumas, and Ameghino individuals . SimilarL. guanicoe suggested that there were higher levels of effective migration than would be expected under a model of isolation-by-distance (IBD) between Meseta Somuncura–Telsen–Peninsula-Valdez and Las Plumas–Ameghino and reduced, fine-scale migration between Meseta Somuncura–Telson–Península Valdés and Las Plumas–Ameghino–Meseta Somuncura , there was no specific locality with elevated levels of genetic diversity  = 0.40, p > 0.05 in ARLEQUIN 3.5.2.2, and r = 0.23, p < 0.001 in ALLELES IN SPACE; Estimates of effective migration surfaces for omuncura C. Estimas Plumas D. This ds Plumas . Howeveriversity D. This pThe posterior probabilities  of recenThe results of the demographic analyses of the microsatellite data using MSVAR under the three demographic models were relatively consistent. The three independent runs for each sampling locality, of (1) no demographic change (Nt~N0), (2) bottleneck (Nt > N0), and (3) population expansion (Nt < N0), resulted in Gelman and Rubin’s statistics convergence analyses of less than 1.2. In all cases, MSVAR detected evidence of major effective-population size declines at each of the localities, which would be consistent with current or recent population sizes based on census estimates . Each ofOur results provide an insight into how human activities, in particular extensive sheep ranching and the development of human settlements, could have influenced the population structure of endemic wild species such as the guanaco. Here, we found that the guanacos in the region are genetically diverse, with low levels of inbreeding. However, there is also evidence of a recent genetic structure that is associated with human activities and likely reflects direct and indirect impacts on guanaco populations and their habitat.STRUCTURE and Geneland analyses of the microsatellite data identified three populations (K = 3). The most northwestern cluster, Loma Blanca, located at the northern limit of the arid Patagonian Steppe, had the highest estimates of genetic variation, evidence of a larger and more diverse population . The secThe individuals from all of the localities appear to share a common evolutionary origin, based on their shared ancestral mitochondrial haplotype  estimates for each of the three genetic groups of (i) LB: 76.6 (95% CI: 44.4–223.6), (ii) MS-TE-PV: 440 (95% CI: 198.9–Inf), and (iii) BD-LP-AM: 92.2 (95% CI: 65.2–150.6), in spite of their past bottleneck events. The Ne values of these Argentine populations are all larger than the estimated guanaco population of the Torres del Paine National Park in Southern Chile  of 34.3–43.1 . Our resHere, we show through nuclear and mitochondrial analyses that the guanaco populations of the southern Monte and northern Patagonian Steppe of Argentina have high levels of genetic diversity and allele-richness and a low level of inbreeding . These oMan-made barriers and human-related activities have likely been the primary cause of the fragmentation and genetic structure currently observed in the guanaco populations in northern Patagonia. Similar processes have been documented in other species ,58. HereSheep ranching first started during the 1890s in Eastern Patagonia and spread rapidly along the coast and central plateaus . The estThe Las Plumas and Ameghino localities seem to be separated by the more ubiquitous and continuous presence of human settlements along the Chubut river. The river played a key role in the establishment of agriculture and the colonization of inland regions, providing water for irrigation of the fertile land and facilitating the arrivals of settlers and the foundation of Rawson city. The basin of the river Chubut and the railroad between Puerto Madryn and Trelew city became an important agrocommercial route, facilitating the development of the surrounding areas. This urbanization and increased human activity appear to have formed a significant barrier to the dispersal of guanacos, which would otherwise have been able to cross the river readily .Physical barriers have often been linked with reduced connectivity between populations and/or disruption of historical movement/migration of animals at the local level ,65,66. POur genetic analyses suggest that the populations of Argentina’s northern Patagonia guanaco populations are not under threat. Our results suggest that in northern Argentinian Patagonia, there is currently gene flow among localities and increasing densities of guanaco and that there has been at least a partial recovery of local populations, increased connectivity, and increased interbreeding. There are several examples of where local interbreeding between two clusters is likely, as the animals in those areas have composite genotypes at intermediate allele frequencies relative to those observed in more northern or southern guanaco clusters. Gene flow among localities, although asymmetric, combined with recent increases in population size, suggest that the guanaco populations in northern Patagonia are slowly recovering from historically low population sizes. For example, here, we documented directional migrants from Península Valdés in the localities of Telsen and Meseta Somuncura, and from Las Plumas in Bajada del Diablo and Ameghino . PhysiolHowever, prolonged drought, overgrazing by livestock, declining productivity, and demand for wool have caused ranches to reduce activity or close ,67, whicAlthough our findings are consistent with the premise that livestock, agricultural activities, and associated urbanization have contributed to the current structure and fragmentation of guanaco populations, it appears that reductions in livestock numbers and related activity in central and southern Patagonia in the last 20 years have benefited guanaco populations by increasing connectivity and facilitating gene flow among previously isolated localities. Further conservation initiatives that reinforce these trends are continuing. For example, during the last decade, groups of sheep-wool producers in Península Valdés and goat herders in Neuquén (northwest of Argentinean Patagonia) are promoting the nonlethal management of native predators, reductions in livestock densities, and the coexistence of native herbivores through certification programs . HoweveOur results suggest that although guanacos may have been non randomly distributed into recognizable populations prior to the arrival of Europeans, the impacts of extensive sheep ranching and the development of human settlements, has continued to influence guanaco population structure. Protection of core areas that are linked biogeographically would help sustain large guanaco populations and would provide a promising model for the long-term persistence of the species across the managed landscapes of Patagonia. Although urbanization and fencing has likely structured natural populations, increased livestock activity has also contributed to decreased connectivity among guanaco populations. However, the implementation of broad regional management and conservation plans of wild populations, especially across the Monte and northern Patagonian Steppe, which are under threat of increasing urbanization and aridity, would help ensure long-term sustainability of functional ecosystems and human livelihoods in the region.