Between the lines: mitochondrial lineages in the heavily managed red deer population of Belarus

Between the lines: mitochondrial lineages in the heavily managed red deer population of Belarus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Between the lines: mitochondrial lineages in the heavily managed red deer population of Belarus Arseni Andreyevich Valnisty, Kanstantsin V Homel, Ekaterina E Kheidorova, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2967492/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Feb, 2024 Read the published version in Mammalian Biology → Version 1 posted You are reading this latest preprint version Abstract Here we report the first thorough genetic characterization of the long understudied red deer population of Belarus in regards to its ancestry according to mtDNA sequence analysis. Employing a 328 base pair segment of the mitochondrial control region (d-loop) from 30 deer specimens of either sex recently harvested across the country, we have discovered 6 haplotypes belonging to 2 of the widely described European red deer lineages, or haplogroups: Iberian (A) and Maraloid (E), clarifying the range limits of both lineages in the region. Combining this data with a comparative analysis of genetic diversity and historical records, we conclude that the Belarusian population of red deer has an artificially mixed origin, though it remains unclear how desirable such a state of the local population is, in terms of sustainable management, use and conservation. Inquiries into ancient DNA are required in order to recognize the lineages closest to the now lost autochthonous population of Belarus. Mitochondrial DNA Ungulates Control Region Genetic lineage Phylogeography Cervus elaphus Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The red deer ( Cervus elaphus Linnaeus, 1758) is one of the key game species in Europe, with significant ecological role and a complicated history (Mattioli et al. 2022). The origins of most contemporary European populations of this species are largely defined by two factors: firstly, isolation of their ancestral populations in one of the few glacial refugia during the period of the Last Glacial Maximum (LGM), before they emerged to re-colonize most of the continent (Ludt et al. 2004; Skog et al. 2009; Niedziałkowska et al. 2021; Doan et al. 2021). Secondly, severe shrinking of populations and fragmentation of their range due to excess hunting, followed by artificial reintroduction efforts to rebuild local populations. (Nussey et al. 2006; Dellicour et al. 2011; Niedziałkowska et al. 2012; Pérez-González et al. 2012; Queiros et al. 2014; Frantz et al. 2017). Those factors have shaped the modern deer population of Europe, including the distribution of its five main genetic lineages, or haplogroups, as they are delineated according to the most recent phylogenetic data (Meiri et al. 2018; Doan et al. 2021; Mackiewicz et al. 2022): Lineage «A», sometimes called «Iberian», «Western European» or «Central European», which originates from the ancestral population of the Iberian glacial refugium. This group includes most populations of the Western and Central Europe, from Iberian Peninsula, through France and the whole North European Plain, roughly limited by East European Plain, Alps in the South and Carpathians in the Southeast. It also includes populations of British Isles, Southern Scandinavia, Crimea, and several artificial populations on other continents. This lineage is occasionally described as a subspecies of its own - Cervus elaphus elaphus, and had additional subspecies described within it: namely Cervus elaphus hippelaphus , scoticus, hispanicus (Queirós et al. 2019) and atlanticus (Mattioli et al. 2022); Lineage «B», which includes populations of Sardinia, Corsica, and the Barbary Coast. Sometimes named “Tyrrhenian”, this line is associated with the Calabrian glacial refugium of Italy, and occasionally described as the subspecies Cervus elaphus corsicanus or Cervus elaphus barbarous (Hmwe et al. 2006; Doan et al. 2017); Lineage «C», also known as the “Eastern”, “South-Eastern” or “Balkan” lineage, or the subspecies Cervus elaphus pannoniensis «восточной», «юго-восточной» или «балканской гаплогруппой», prevalent on the Balkan peninsula, Carpathians, Southern Alps and partso f the Central Europe (Banwell and Bruce. 2002). Lineage «D», also named «Mesola group», or separated into its own subspecies Cervus elaphus italicus (Zachos et al. 2014), present in large numbers only in the Natural Mesola Forest Reserve in Italy. Lineage «E», widespread in Iran, Turkey, Caucasus region and Russia, known as the «Maraloid» or “Middle Eastern“ lineage, or subspecies Cervus elaphus maral . The Eastern European part of the species’ range, which includes the probable borders between the ranges of «A», «C «and «E» lineages (figure 1), is particularly lacking in research – of the earlier studies of red deer population genetics, only a few included samples from those populations, and even then only sporadically and in very limited amounts (Niedziałkowska et al. 2011, 2012; Meiri et al. 2013). The issue is exacerbated by the complexities of the phylogenetic history of the species (Sommer et al. 2008; Jowers et al. 2019; Doan et al. 2021; Mackiewicz et al. 2022), and the ongoing discourse on its precise taxonomic makeup (in regards to which, we refer to the lineages as they are listed by Mattioli et al together with any synonyms that we know of). Continued reintroduction efforts conducted with limited oversight and no measures of genetic monitoring involved serve to make origins of populations more blurry as well (Wilson and Reeder 2005). The red deer population in Belarus has an especially troubled history, including practically total loss of the population by early XXth century, followed by decades of poorly documented reintroductions from various sources, which succeeded in bolstering numbers of animals and expanding their range (Romanov 2000; Shakun 2011; Shakun and Veligurov 2018). However, this practice can have complex, unpredictable consequences for the long-term stability of the population. Detailed analysis of red deer lineages in Belarus serves to not only uncover the traces of complicated cross-country resettlements, but also examine the effects of massive resettlements on population genetics of ungulate species in general, as well as complete the phylogeographic map of this species’ movements and migrations across the continent. In this paper, we report the first thorough study of genetic makeup and ancestry of Belarusian red deer using mtDNA control region. Materials and methods Analysis outline For this study, we obtained sequences of mtDNA control region from a sample of 30 deer harvested across Belarus by extracting DNA from soft tissue or horn samples, amplifying a fragment of the CR locus in a PCR, and Sanger dideoxy sequencing the amplicons. Then we aligned the obtained sequences between themselves, as well as with a large set of homologous sequences obtained from earlier studies, and characterized the local haplotypes statistically and comparatively. Sampling We used a sample of 30 wild red deer specimens, harvested in 23 locations across Belarus during legal hunts between 2016 and 2022 (figure 2). The sample’s coverage includes all major wild populations of deer in Belarus, across five oblasts (regions) and 21 raion (district), while the studied population totals approximately 38 000 animals, according to most recent surveys using indirect counting methods. The analysed sample includes animals of either sex, aged between 1 and 8 years, according to descriptions. The full list of all specimens used in this study, along with Genbank accession numbers for obtained sequences, is given in Online Resource 1. Molecular methods We used two methods for DNA isolation: one for cryogenically preserved soft tissue samples using «Animal & Fungi DNA Preparation - Solution Kit» (Jena Bioscience, Germany) following the manufacturer’s protocol, and an original method for horn tissue samples. The utilized DNA isolation protocol for horn tissue samples was based on demineralization of powdered horn in a solution containing EDTA and sodium lauryl sulphate (SLS), followed by lysis in presence of proteinase K (ArtBioTech, Belarus) and DNA precipitation via iced ammonia acetate and chlorophorm. The latter method was developed based on a similar method described by Hoffman and Griebeler (2013). We conducted all DNA isolation procedures with sterilized tools, in a clean laboratory environment spatially separated from DNA amplification and post-amplification areas, with extraction procedures themselves including negative and positive controls, all in order to avoid DNA isolate contamination. We then measured concentration and purity of the obtained isolate solutions with a nanospectrophotometer (330P Implen, Germany) and banked them for storage at -20 °С until further use. For the analysis itself, we used a hypervariable fragment of mitochondrial DNA control region (also called «D-loop») as the marker of choice. (Wolstenholme 1992; Boore 1999). This neutral, haploid, non-recombining locus was widely used in earlier research into genetics of European ungulates, and population history of red deer specifically, providing us with certainty in its suitability for the task, as well as a wealth of data for comparative analysis. For PCR amplification of the marker we used classical primers LD5 (AAGCCATAGCCCCACTATCAA) and HD8 (TTGACTTAATGCGCTATGTA) by Nagata et al (Nagata et al. 1998), flanking a region approximately 350 base pairs in length, with oligonucleotide synthesis and purification performed by Primetech (Belarus). Amplification was carried out in individual 25µl reactions. Each reaction contained ammonia sulfate PCR buffer (Primetech, Belarus) in standard concentration; 0.2 mM of dNTPs (ArtBioTech, Belarus); 2,5 mM MgCl 2 ; 1 U of Taq DNA polymerase (ArtBioTech, Belarus) and 15-20 ng of sample DNA (Lorenz 2012). All reaction preparation procedures were conducted with positive and negative controls, on coolant trays, in a preemptively decontaminated laminar flow box located in an area spatially separated from sample processing and post-PCR analysis areas in order to prevent reaction contamination. We used a C1000 Touch Thermal Cycler (Bio-rad, USA) to carry out the amplification protocol, given in table 1. Table 1 – PCR thermal cycling protocol used for CR amplification. t – sample temperature for the stage; N – number of stage repeats. t, ℃ Time, sec. N 95 180 1X 95 30 30X 60 30 72 65 72 480 1X The obtained amplicons were checked for size and undesirable by-products with an electrophoretic separation of 1-2 µl of reaction volume in 1% agarose gel with UV-transillumination. We used a 20 cm horizontal electrophoresis chamber with sodium borate buffer, DNA size marker “100+ bp DNA Ladder” (Evrogen, Russia) for size reference, and the Gel Doc™ XR+ (Bio-rad, USA) gel documentation system. Amplicons that showed sufficient quantity and purity of the expected product were sequenced using the Sanger dideoxy method by the Institute of Bioorganic Chemistry of the NAS of Belarus. Amplicons were once again separated by electrophoresis in 0.8% agarose gel, target fragments were cut out from the gel and purified with NucleoSpin Gel and PCR Clean‑up (Macherey Nagel, Germany) following the manufacturer’s protocol. The purified DNA fragments then underwent bidirectional sequencing reaction using BrilliantDye3.1 kit (Nimagen, Netherlands). Products were purified using ethanol/EDTA precipitation and separated with ABI3130 Genetic Analyzer (Thermo Fisher Scientific, USA). We then analysed the produced sequenograms using UGENE v39 (Okonechnikov et al. 2012) software package – readings were aligned against a reference red deer mitochondrial genome (Genbank accession number NC_007704). The CR fragment nucleotide sequences for individual specimens were determined according to consensus reading of two bidirectional reads of the same specimen, aligned against the reference genome and additionally checked by hand. For further multiple alignments we used the MAFFT 7.490 (Katoh and Standley 2013) multiple alignment algorithm implemented in UGENE. Haplotype analysis To determine genetic lineages of studied specimens, we assembled a selection of 615 European and Asian red deer mitochondrial control region sequences, obtained from NCBI Genbank database (Randi et al. 2001; Polziehn and Strobeck 2002; Nussey et al. 2006; Pérez-Espona et al. 2009; McDevitt et al. 2009; Haanes et al. 2010; Fickel et al. 2012; Olivieri et al. 2014; Krojerová-Prokešová et al. 2015; Lorenzini and Garofalo 2015; Borowski et al. 2016; Frank et al. 2017; Schnitzler et al. 2018; Meiri et al. 2018). The selection includes both individual specimen sequences and haplotypes. Every sequence in the selection was then assigned a lineage according to data provided in corresponding publications. In cases where the same sequences had conflicting assignments in different papers, we gave preference to the latest publication. In a few cases where sequences were not assigned a lineage in original research, we assigned it inductively during the ad hoc analysis. The full list of sequences used in analysis, including individual listing of sources, geographic origins, haplotypes and assigned lineages is given in Online Resource 2. Aligned sequences were condensed into haplotypes within the utilized alignment length using FaBox online software tools (Villesen 2007). The haplotypes were numbered in consecutive order, with a naming scheme that refers only only to this study. We then assigned lineages to haplotypes according to the lineages previously assigned to sequences included into said haplotypes, which served to assign a lineage to every original sequence produced in this study through simple grouping. To estimate genetic diversity coefficients we used DNASP 6.12.03 software package. Haplotype networks were designed using NETWORK 10.2.0.0 (Bandelt et al. 1999; Polzin and Daneshmand 2003), where we used Median Joining algorithm, with ε paramenter equaling 0, with no site weighting or external network rooting, followed by MP Calculation post-processing to determine the shortest tree within the network. To create cladograms, we used MEGA 11.0.10 software (Tamura et al. 2021), following maximum parsimony method with partial deletion treatment of gap sites, with threshold of 95% taxa in the sample, and estimated clade bootstrap support with 1000 replicates of bootstrap. Illustrative maps in this paper were made using QGIS 3.24.2. Results We obtained control region sequences for 30 Belarusian specimens (Genbank accession numbers OQ968556- OQ968585), with sequence length ranging between 253 and 359 b.p., and discovered 6 haplotypes among them, segregated by 10 polymorphic sites. Genetic diversity characteristics for the studied population and a number of other European populations (for comparison) are given in Table 2 . Table 2 – Genetic diversity parameters for the Belarusian red deer population according to mtDNA control region sequence analysis, in comparison with a selection of other European populations. The data acquired in this study are given in bold. Src. – source of data; Population – the name or geographic location of the population according to source; b.p. – the length of control region sequence used in the; N – sample size; H – number of haplotypes in the sample; Ĥ – haplotype diversity; SD (Ĥ) – standard deviation of haplotype diversity; n – nucleotide diversity; SD (n) – standard deviation of haplotype diversity. ππ Source Population b.p. N H Ĥ SD (Ĥ) π n SD (π n ) This study Belarus 328 30 6 0.55 0 .101 0.001 0.0021 Niedziałkowska et al ( 2011 ) Eastern Belarus 249 13 4 0.6 - 0.02 - Lithuania 12 3 0.32 - 0.009 - Bialowieza Forest (Poland) 117 7 0.76 - 0.008 - Ukraine 11 1 - - - - Masuria (Poland) 54 4 0.48 - 0.005 - North-Eastern Poland 91 5 0.8 - 0.008 - Skog et al (2009) Serbia 332 54 2 0.04 0.04 0 0 Hungary 32 3 0.23 0.09 0.002 0.002 Scotland (UK) 10 3 0.71 0.09 0.01 0.006 Western Norway 38 3 0.63 0.05 0.006 0.004 Northern Germany 52 4 0.22 0.07 0.002 0.002 Upper Marne (France) 10 3 0.6 0.13 0.013 0.008 Romania 40 5 0.46 0.09 0.009 0.005 Giovannelli et al (2022) Italy 26 5 0.50 - 0.004 - Meiri et al ( 2013 ) Western and Central Europe 763 13 6 0.83 0.082 0.003 0.0021 Obtained genetic diversity parameter values for the studied population indicate a level of genetic diversity similar to most heavily managed, mixed populations of red deer in the region. Due to very limited sequence length and low number of polymorphic sites, we used several different alignments for further analysis. Namely: alignment I (230 b.p.), which included 26 of the best quality sequences that we obtained and a set of 615 Genbank sequences; alignment II (328 b.p.), made up entirely from the 30 obtained in this study; and alignment III (302 b.p.), which included Belarusian sequences assigned to the lineage «E» and a number of lineage «E» sequences obtained from Genbank (Table 3 ). A fourth alignment, meant for a similar clarification of ancestry in Belarusian part of lineage A, was excluded from the work, as it was not any more informative than alignment I. Table 3 – a listing of mtDNA CR alignments used in this study. “Sequences” and “Haplotypes” columns list the numbers of sequences or haplotypes obtained in this study (Bel), plus the number of Genbank sequences, included in the corresponding alignment. Alignment b.p.. Sequences (Bel + GB) Haplotypes (Bel + GB) I 230 26 + 615 3 + 114 II 328 30 6 III 302 6 + 12 3 + 7 Haplotype analysis utilizing alignment I allowed us to assign 20 Belarusian red deer specimens to CR mtDNA lineage «A» (Iberian haplogroup), and 6 specimens – to the maraloid lineage «E». A corresponding haplotype network is given in Fig. 3 . Of the remaining 4 specimens, we had 3 individuals assigned «A» and 1 assigned «E» in the post hoc analysis. What draws immediate attention is the complete absence of Balkan lineage «C» in the studied sample. It’s worth pointing out that the haplotype network shows all European red deer lineages as clearly defined, except for Mesolan lineage «D». We suggest that the length of the utilized alignment was insufficient to manifest lineage «D», but this does not compromise the analysis, as we are not aware of any premises that could make presence of lineage «D» in Belarus likely, be it close range borders of that group or any known translocations of animals from the Mesola preserve to Belarus. Another curious finding is that none of the Belarusian specimens which we assigned lineage «E» had shown prominent maraloid morphology, according to descriptions given to us by the hunters involved in harvesting, while simultaneously multiple individuals described as possessing maraloid appearance were assigned lineage «A» in our analysis. Alignment II was used to build a cladogram of Belarusian specimens obtained in this study (Fig. 4 a), which also shows a clear partition of those individuals into 2 clades, corresponding to genetic lineages «A» and «E». 3 of the 6 haplotypes found in the samples belong to haplogroup «A», the other 3 belong to the haplogroup «E». The cladogram of maraloid specimens (Fig. 4 b) in turn shows that Belarusian «E» lineage haplogroups are divided into 2 subclades – one of which is grouped with Voronezh maral (Russia) haplotype discovered by Meiri et al ( 2013 ), while the other one is grouped with a Turkish maral haplotype. Geographic distribution of red deer genetic lineages over the territory of Belarus (Fig. 5 ) has shown a wide distribution of lineage «A» across the sampled territory, while lineage «E» appears to be present only in a small region in the North-Eastern part of the country, located between Beresinsky Reserve, Orsha and Berezino townships. Discussion Our findings on red deer genetic lineages in Belarus partially diverge from the earlier data – the studied sample shows no presence of Balkan lineage «C», which was reported as present in the country based on analysis of a limited sample by Niedziałkowska et al ( 2011 ). At the same time, our results agree with those for a small Belarusian sample used by Meiri et al ( 2013 ). We interpret the disagreement as a product of differences in reference data for lineage assignment – the study by Niedziałkowska et al was the first inquiry into genetics of Eastern European red deer, preceding any similar research into maral populations, and thus delineation of lineage «E» itself. Thorough inquiries into genetics and ancestry of maral populations are extremely recent (Golosova et al. 2022 ). According to our own analysis (unpublished data), specimens belonging to the latter can be easily misclassified as belonging to lineage «C» when the reference sequences are in limited supply, especially when using short reads. The selection of haplotypes that we observe in the Belarusian population suggests that the core of the local population originates from Central European stock, with a presence of maral admixture. This is supported by the historical management data for the local population, which ascribes most of the current red deer range in the country to reintroduction during Soviet and post-Soviet periods from Bialowieza Forest stock, which itself has origins in Silesian, Lodzian and Bohemian red deer populations (Romanov 2000 ). There is also information on several significant resettlements of deer from the Voronezh Nature Reserve, reporting at least 313 specimens moved to Belarus between 1956 and 1972. This includes 85 individual animals released specifically in the areas that we defined here as the contemporary lineage «E» range, plus several other similar releases in the same area, but involving an unknown number of animals (Shakun 2011 ). The genetic diversity values for the Belarusian population also suggest a mixed character. The findings on the lineage ranges within the country lead us to the conclusion that the contemporary distribution of both discovered lineages in Belarus was determined largely through human involvement in the form of reintroductions from diverse sources. This is indicated by fragmented nature of the range and concentration of specimens assigned to the lineage E around the artificial population of Berezinsky Biosphere Reserve, and supported by historical reintroduction data. The Voronezh preserve population of red deer, described as predominantly maraloid in ancestry by earlier studies (Meiri et al. 2018 ; Doan et al. 2021 ), appears to be the most likely source of maral admixture in the contemporary Belarusian population, as indicated by the clade analysis of maraloid sequences. Unfortunately, short lengths of the obtained sequence reads coupled together with low haplotype diversity in the probable ancestral populations for Belarusian lineage «A» stock prevent us from pinpointing it’s ancestry with precision higher than just «Central Europe». Our sample is also poorly suited for determining the haplotype frequency of lineages in the studied area, as the absolute majority of the specimens assigned to lineage «E» (5 individuals) come from the same locality (Berezinsky Biosphere Reserve), which also happens the be the locality with the highest representation in the sample. This would serve as a source of significant statistical bias. Meanwhile collapsing every locality down to a single data point would make the sample too small for a representative haplotype frequency analysis. What we can deduce from lineage «E» being present in three localities out 23 sampled is that animals belonging to the lineage «E» had had significant success in adapting to the new range after release, and achieved sufficient presence in the population to consider it a part of the local population core. Mitochondrial analysis being limited to pure matrilineal ancestry and the lineage not corresponding clearly with morphological appearance leave an open possibility of much greater scale, undetected presence of maral ancestry in the Belarusian red deer population. Our findings clarify the contemporary distribution of red deer lineages across Eastern Europe. The range of lineage «A» expands further east, at least until the eastern border of Belarus, and possibly beyond. The range of lineage «E» appears to reach further north-west than previously assumed. We cannot conclusively state that Balkan lineage «C» ancestry is absent from the Belarusian red deer population, but its presence appears to be elusively rare at most, with no significant contribution to the gene pool, while the northernmost limits of the lineage’s range seems to be located in Ukraine. In all cases for the Belarusian population, the role of anthropogenic factor in shaping the population’s genetic makeup and distribution range is higher than ever before. Maraloid admixture, artificially introduced from the Voronezh population, contributes a significant portion of the population’s genetic diversity, but most likely serves to distance genetic makeup of population further away from the lost autochthonous deer population that inhabited Belarus before the XVIII century. Additional research into genetics of ancient deer in the region can serve to steer management of the contemporary population closer towards the optimal path of reconstruction and sustainable conservation of autochthonous deer varieties in natural conditions (Apollonio et al. 2017 ) as the contemporary population in Belarus experiences growth stabilization after reintroduction, facing threats of habitat fragmentation and increasing anthropogenic pressure. Declarations Conflict of interest Authors declare no conflict of interest. Acknowledgements We want to thank G.V. Sergeev for his assistance with DNA sequencing. We also thank Alexandra Larchenko, Georgiy Yanuta, Pavel Veligurov, Yuri Bogutsky, Lyudmila Akimova, Gennadiy Puzankevich, Vadim Sidorovich, A.A. Pruchkovskiy, A.N. Sasimovich, P.K. Gorodko, A.A. Pruchkovsky, O.E. Degitrov, V.V. Nosevich, V.N. Alshevskiy, N.V. Makengir, S.N. Kolesnik, Y.N. Yurnezh, A.I. Prasnich, S.N. Moshienko, V.V. Stolyarchuk, V.V. Pushilo, G.N. Klyuka, V.S. Genr, V.V. Kovalenok, A.A. Kravchenko, G.V. Zinevich, A. Mitrinkov, and all anonymous hunters and foresters for their help in the sampling process. Funding This study was conducted as a part of A.A. Valnisty’s research for his PhD thesis «Genetic structure of the red deer population in Belarus under reintroduction conditions» and as such was funded by the graduate student fund of the National Academy of Sciences. Parts of this study were financed by the Belarusian State Scientific Research Program "Nature management and environmental risks" for 2016-2020 (subprogram 01 "Rational use of natural resources and innovative technologies for deep processing of natural resources"), grant 5.1 "Genetic passportization of red deer populations as a basis for forming and maintaining a high degree of diversity and reproduction rates", as well as Belarusian State Scientific Research Program "Natural Resources and Environment" for 2021-2025 (subprogram 10.2 "Biodiversity, Bioresources, Ecology", task 5 "Creating a scientific basis for management of target traits in populations of rare and economically significant animal and plant species based on studies of structural and functional organization of their genomes"), grant 2: "Assessment of molecular genetic effects and associated risks in population disturbances in problem resource, biocenotically significant and rare animal species". Data availability All the sequences obtained in this work were uploaded to the NCBI Genbank Nucleotide open access database (accession numbers OQ968556- OQ968585). All the tissue samples used in this work were banked in the cryocollection of the Genetic Bank of Wildlife of SNPO "SPC of the National Academy of Sciences of Belarus for Bioresources" (Akademicheskaya st., 27, 220072, Minsk, Republic of Belarus) for long-term storage, and can be provided on demand for data verification. References Apollonio M, Belkin VV, Borkowski J et al (2017) Challenges and science-based implications for modern management and conservation of European ungulate populations. Mamm Res 62:209–217. https://doi.org/10.1007/s13364-017-0321-5 Bandelt HJ, Forster P, Rohl A (1999) Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol 16:37–48. https://doi.org/10.1093/oxfordjournals.molbev.a026036 Banwell D, Bruce (2002) In defence of the Pannonian Cervus elaphus pannoniensis. 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Heredity 97:56–65. https://doi.org/10.1038/sj.hdy.6800838 Okonechnikov K, Golosova O, Fursov M (2012) Unipro UGENE: a unified bioinformatics toolkit. Bioinformatics 28:1166–1167. https://doi.org/10.1093/bioinformatics/bts091 Olivieri C, Marota I, Rizzi E et al (2014) Positioning the red deer (Cervus elaphus) hunted by the Tyrolean Iceman into a mitochondrial DNA phylogeny. PLoS ONE 9:e100136. https://doi.org/10.1371/journal.pone.0100136 Pérez-Espona S, Pérez-Barbería FJ, Goodall-Copestake WP et al (2009) Genetic diversity and population structure of Scottish Highland red deer (Cervus elaphus) populations: a mitochondrial survey. Heredity (Edinb) 102:199–210. https://doi.org/10.1038/hdy.2008.111 Pérez-González J, Frantz AC, Torres-Porras J et al (2012) Population structure, habitat features and genetic structure of managed red deer populations. Eur J Wildl Res 58:933–943. https://doi.org/10.1007/s10344-012-0636-0 Polziehn RO, Strobeck C (2002) A phylogenetic comparison of red deer and wapiti using mitochondrial DNA. Mol Phylogenet Evol 22:342–356. https://doi.org/10.1006/mpev.2001.1065 Polzin T, Daneshmand SV (2003) On Steiner trees and minimum spanning trees in hypergraphs. Oper Res Lett 31:12–20. https://doi.org/10.1016/S0167-6377(02)00185-2 Queirós J, Acevedo P, Santos JPV et al (2019) Red deer in Iberia: Molecular ecological studies in a southern refugium and inferences on European postglacial colonization history. PLoS ONE 14:e0210282. https://doi.org/10.1371/journal.pone.0210282 Queiros J, Vicente J, Boadella M et al (2014) The impact of management practices and past demographic history on the genetic diversity of red deer ( Cervus elaphus ): an assessment of population and individual fitness: Genetic diversity of red deer. Biol J Linn Soc Lond 111:209–223. https://doi.org/10.1111/bij.12183 Randi E, Mucci N, Claro-Hergueta F et al (2001) A mitochondrial DNA control region phylogeny of the Cervinae: speciation in Cervus and implications for conservation. Anim Conserv 4:1–11. https://doi.org/10.1017/S1367943001001019 Romanov VS (2000) История охотничьего хозяйства Беларуси [Istoriya okhotnich’yego khozyaystva Belarusi]. Trudy BGTU 57–64 Schnitzler A, Granado J, Putelat O et al (2018) Genetic diversity, genetic structure and diet of ancient and contemporary red deer (Cervus elaphus L.) from north-eastern France. PLoS ONE 13:e0189278. https://doi.org/10.1371/journal.pone.0189278 Shakun VV (2011) Biological and ecological features of thered deer (Cervus elaphus Linnaeus, 1758), reacclimatized on the territory of Belarus. Doctoral dissertation, Scientific and Practical Centre for Bioresources of the National Academy of Sciences of Belarus, Minsk, 1–161. [In Russian] Shakun VV, Veligurov PA. Reintroduction of the reddeer in Belarus. Presented at Proceedings of the 82 Confer-ence on the Forest Industry, Minsk A, Zachos FE, Rueness EK et al (2018) (2009) Phylogeography of red deer ( Cervus elaphus ) in Europe. Journal of Biogeography 36:66–77. https://doi.org/10.1111/j.1365-699.2008.01986.x Sommer RS, Zachos FE, Street M et al (2008) Late Quaternary distribution dynamics and phylogeography of the red deer (Cervus elaphus) in Europe. Q Sci Rev 27:714–733. https://doi.org/10.1016/j.quascirev.2007.11.016 Tamura K, Stecher G, Kumar S (2021) Mol Biol Evol 38:3022–3027. https://doi.org/10.1093/molbev/msab120 . MEGA11: Molecular Evolutionary Genetics Analysis Version 11 Villesen P (2007) FaBox: an online toolbox for fasta sequences. Mol Ecol Notes 7:965–968. https://doi.org/10.1111/j.1471-8286.2007.01821.x Wilson DE, Reeder DM (eds) (2005) Mammal species of the world: a taxonomic and geographic reference, 3rd edn. Johns Hopkins University Press, Baltimore Wolstenholme DR (1992) Animal mitochondrial DNA: structure and evolution. Int Rev Cytol 141:173–216. https://doi.org/10.1016/s0074-7696(08)62066-5 Zachos FE, Mattioli S, Ferretti F, Lorenzini R (2014) The unique Mesola red deer of Italy: taxonomic recognition ( Cervus elaphus italicus nova ssp., Cervidae) would endorse conservation # . Italian J Zool 81:136–143. https://doi.org/10.1080/11250003.2014.895060 Supplementary Files Supplementary1.xlsx Supplementary2.xlsx Cite Share Download PDF Status: Published Journal Publication published 02 Feb, 2024 Read the published version in Mammalian Biology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2967492","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":205867953,"identity":"e70899e3-92de-43a0-83d8-103e2e60c23a","order_by":0,"name":"Arseni Andreyevich Valnisty","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYFAC5gaGBAiL8QGIaCCshRGkxQCs2YB4LQwQLWwSRGkxON7Y9uDBnz+JDeyHn1Xz1NyR7ZdIYPvMg0/LmYPtBoltBokNPGlmt3mOPTOe2XOAeTY+LZIzEtskEhuAWhgSgFrYDiduON7AzExQS8IfoBb+59+Kef4dTtx/mAG/Fn4JkBY2oBaJHDNm3jagLewEbOHnOQh0WJuxcZvEm2LJuX2HjWecOdjMOAePFjb25mOSP/7Iyfbzp2/88ObbYdn+GcmHGd7g0QIDjm1AggniHmJiEwjswWp/EKV2FIyCUTAKRhoAAMjLTg17d0n3AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-3612-1467","institution":"State Research and Production Association \"Scientific and Practical Center of the National Academy of Sciences of Belarus for bioresources\"","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Arseni","middleName":"Andreyevich","lastName":"Valnisty","suffix":""},{"id":205867954,"identity":"39509cc3-0b5e-40fd-ad1a-f105cf848fe5","order_by":1,"name":"Kanstantsin V Homel","email":"","orcid":"","institution":"State Research and Production Association \"Scientific and Practical Center of the National Academy of Sciences of Belarus for bioresources\"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kanstantsin","middleName":"V","lastName":"Homel","suffix":""},{"id":205867955,"identity":"0672a17b-b04a-45f5-9a6d-5d42e92e26bf","order_by":2,"name":"Ekaterina E Kheidorova","email":"","orcid":"","institution":"SNPO \"SPC of the NAS of Belarus for Bioresources\"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ekaterina","middleName":"E","lastName":"Kheidorova","suffix":""},{"id":205867956,"identity":"6d93d570-da74-4308-ad73-182fbcdb5e55","order_by":3,"name":"Vladislav O Molchan","email":"","orcid":"","institution":"SNPO \"SPC of the NAS of Belarus for Bioresources\"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Vladislav","middleName":"O","lastName":"Molchan","suffix":""},{"id":205867957,"identity":"0641d81c-87fe-4a78-9090-98d69d7c5d9a","order_by":4,"name":"Mikhail Y Nikiforov","email":"","orcid":"","institution":"SNPO \"SPC of the NAS of Belarus for Bioresources\"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mikhail","middleName":"Y","lastName":"Nikiforov","suffix":""}],"badges":[],"createdAt":"2023-05-22 15:47:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2967492/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2967492/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s42991-023-00397-w","type":"published","date":"2024-02-02T10:11:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":38027244,"identity":"ba2bf7d7-52ba-4a51-8705-d5d53d1bd824","added_by":"auto","created_at":"2023-06-05 14:33:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":131746,"visible":true,"origin":"","legend":"\u003cp\u003eapproximate distribution of red deer mtDNA lineages in contemporary Europe.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2967492/v1/ac300d8f4af724bf7a7b621f.png"},{"id":38029067,"identity":"5fcaf25e-88c3-4f17-998a-e3eb23afd23e","added_by":"auto","created_at":"2023-06-05 14:41:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":55241,"visible":true,"origin":"","legend":"\u003cp\u003egeographic distribution of samples used in this study. Purple dots represent sample harvesting locations. Orange shapes show the territory of three national parks or reserves that served as sample sources in our sample.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2967492/v1/5eb9c4fd68cf9fbafbefed26.png"},{"id":38027246,"identity":"61ada4af-ad18-4252-97c4-6c620bfe420f","added_by":"auto","created_at":"2023-06-05 14:33:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":217076,"visible":true,"origin":"","legend":"\u003cp\u003emedian-joining network of European red deer mitochondrial DNA control region haplotypes, built using alignment I (table 3). Genetic lineages are outlined in black and labeled. Circles represent haplotypes, with numbers corresponding to those in supplementary 2. Coloration of circles represents their genetic lineage assignment, with lineages A, B, C, D, E, and Y being represented by green, pink, orange, red, cyan and blue filling respectively. Haplotypes that were observed in our sample of Belarusian specimens are singled out with purple halo.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2967492/v1/4f472f7dc7407d04b4a46f2a.png"},{"id":38027242,"identity":"89c28b67-da0b-4bd9-bbef-9970db0d0505","added_by":"auto","created_at":"2023-06-05 14:33:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":83327,"visible":true,"origin":"","legend":"\u003cp\u003emaximum parsimony cladograms of red red deer mitochondrial DNA control region by specimens. Bold values above nodes indicate bootstrap support (n = 1000). Clades with support \u0026lt;30 are collapsed. (a) Belarusian specimens obtained in this study, built from alignment II. Curly brackets connect specimens by lineages («A» or «E») (b) Belarusian specimens from this study assigned to lineage E and a selection of maral sequences of various geographic origin obtained from Genbank database (alignment III). Curly brackets show common geographic origin. For simplicity’s sake, original specimens are given in cladograms as their shortened Belarusian genetic bank of wildlife voucher IDs, while Genbank specimens are given as their accession numbers.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2967492/v1/5aefada2fdbb15f1be0abe42.png"},{"id":38027241,"identity":"d1a1229b-f8b7-41fb-b791-0b6213831a4d","added_by":"auto","created_at":"2023-06-05 14:33:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":73422,"visible":true,"origin":"","legend":"\u003cp\u003edistribution of red deer genetic lineages in Belarus. Colored dots represent harvesting locations for red deer specimens used in this study, with fill color corresponding the specimens’ assignment to genetic lineages – green for «A» and cyan for «E». Correspondingly, colored shapes represent estimated ranges.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-2967492/v1/c40f3f3d235642cb8627a818.png"},{"id":52750289,"identity":"4cfe8daf-870a-4b90-a9d9-e61ce3334ecc","added_by":"auto","created_at":"2024-03-15 10:11:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":797353,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2967492/v1/84bc456b-f457-4eda-84f1-25d314aed245.pdf"},{"id":38027245,"identity":"96c53f9b-d54e-4c72-8aad-407eeb21f35f","added_by":"auto","created_at":"2023-06-05 14:33:53","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":18105,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2967492/v1/94d7737dd309ae5210dfa390.xlsx"},{"id":38029068,"identity":"94b6eabf-81ac-4ceb-a89b-aa269f0f7bc0","added_by":"auto","created_at":"2023-06-05 14:41:53","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":37993,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2967492/v1/6c3bcc3ab3cee0a4cfda2572.xlsx"}],"financialInterests":"","formattedTitle":"Between the lines: mitochondrial lineages in the heavily managed red deer population of Belarus","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe red deer (\u003cem\u003eCervus elaphus\u0026nbsp;\u003c/em\u003eLinnaeus, 1758) is one of the key game species in Europe, with significant ecological role and a complicated history\u0026nbsp;(Mattioli et al. 2022). The origins of most contemporary European populations of this species are largely defined by two factors: firstly, isolation of their ancestral populations in one of the few glacial refugia during the period of the Last Glacial Maximum (LGM), before they emerged to re-colonize most of the continent\u0026nbsp;(Ludt et al. 2004; Skog et al. 2009; Niedziałkowska et al. 2021; Doan et al. 2021). Secondly, severe shrinking of populations and fragmentation of their range due to excess hunting, followed by artificial reintroduction efforts to rebuild local populations.\u0026nbsp;(Nussey et al. 2006; Dellicour et al. 2011; Niedziałkowska et al. 2012; P\u0026eacute;rez-Gonz\u0026aacute;lez et al. 2012; Queiros et al. 2014; Frantz et al. 2017). Those factors have shaped the modern deer population of Europe, including the distribution of its five main genetic lineages, or haplogroups, as they are delineated according to the most recent phylogenetic data\u0026nbsp;(Meiri et al. 2018; Doan et al. 2021; Mackiewicz et al. 2022):\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eLineage \u0026laquo;A\u0026raquo;, sometimes called \u0026laquo;Iberian\u0026raquo;, \u0026laquo;Western European\u0026raquo; or \u0026laquo;Central European\u0026raquo;, which originates from the ancestral population of the Iberian glacial refugium. This group includes most populations of the Western and Central Europe, from Iberian Peninsula, through France and the whole North European Plain, roughly limited by East European Plain, Alps in the South and Carpathians in the Southeast. It also includes populations of British Isles, Southern Scandinavia, Crimea, and several artificial populations on other continents. This lineage is occasionally described as a subspecies of its own - \u003cem\u003eCervus\u003c/em\u003e \u003cem\u003eelaphus elaphus,\u0026nbsp;\u003c/em\u003eand had additional subspecies described within it: namely \u003cem\u003eCervus elaphus\u003c/em\u003e \u003cem\u003ehippelaphus\u003c/em\u003e,\u003cem\u003e\u0026nbsp;scoticus, hispanicus\u0026nbsp;\u003c/em\u003e(Queir\u0026oacute;s et al. 2019)\u003cem\u003e\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;atlanticus\u0026nbsp;\u003c/em\u003e(Mattioli et al. 2022);\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLineage \u0026laquo;B\u0026raquo;, which includes populations of Sardinia, Corsica, and the Barbary Coast. Sometimes named \u0026ldquo;Tyrrhenian\u0026rdquo;, this line is associated with the Calabrian glacial refugium of Italy, and occasionally described as the subspecies \u003cem\u003eCervus elaphus corsicanus\u0026nbsp;\u003c/em\u003eor\u003cem\u003e\u0026nbsp;Cervus elaphus barbarous\u0026nbsp;\u003c/em\u003e(Hmwe et al. 2006; Doan et al. 2017);\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLineage \u0026laquo;C\u0026raquo;, also known as the \u0026ldquo;Eastern\u0026rdquo;, \u0026ldquo;South-Eastern\u0026rdquo; or \u0026ldquo;Balkan\u0026rdquo; lineage, or the subspecies \u0026nbsp;\u003cem\u003eCervus elaphus pannoniensis\u003c/em\u003e \u0026laquo;восточной\u0026raquo;, \u0026laquo;юго-восточной\u0026raquo; или \u0026laquo;балканской гаплогруппой\u0026raquo;, prevalent on the Balkan peninsula, Carpathians, Southern Alps and partso f the Central Europe (Banwell and Bruce. 2002).\u003c/li\u003e\n \u003cli\u003eLineage \u0026laquo;D\u0026raquo;, also named \u0026laquo;Mesola group\u0026raquo;, or separated into its own subspecies \u003cem\u003eCervus elaphus italicus\u0026nbsp;\u003c/em\u003e(Zachos et al. 2014), present in large numbers only in the Natural Mesola Forest Reserve in Italy.\u003c/li\u003e\n \u003cli\u003eLineage \u0026laquo;E\u0026raquo;, widespread in Iran, Turkey, Caucasus region and Russia, known as the \u0026laquo;Maraloid\u0026raquo; or \u0026ldquo;Middle Eastern\u0026ldquo; lineage, or subspecies \u003cem\u003eCervus elaphus maral\u003c/em\u003e.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe Eastern European part of the species\u0026rsquo; range, which includes the probable borders between the ranges of \u0026laquo;A\u0026raquo;, \u0026laquo;C \u0026laquo;and \u0026laquo;E\u0026raquo; lineages (figure 1), is particularly lacking in research \u0026ndash; of the earlier studies of red deer population genetics, only a few included samples from those populations, and even then only sporadically and in very limited amounts (Niedziałkowska et al. 2011, 2012; Meiri et al. 2013). The issue is exacerbated by the complexities of the phylogenetic history of the species (Sommer et al. 2008; Jowers et al. 2019; Doan et al. 2021; Mackiewicz et al. 2022), and the ongoing discourse on its precise taxonomic makeup (in regards to which, we refer to the lineages as they are listed by Mattioli et al together with any synonyms that we know of). Continued reintroduction efforts conducted with limited oversight and no measures of genetic monitoring involved serve to make origins of populations more blurry as well (Wilson and Reeder 2005). The red deer population in Belarus has an especially troubled history, including practically total loss of the population by early XXth century, followed by decades of poorly documented reintroductions from various sources, which succeeded in bolstering numbers of animals and expanding their range (Romanov 2000; Shakun 2011; Shakun and Veligurov 2018). However, this practice can have complex, unpredictable consequences for the long-term stability of the population. Detailed analysis of red deer lineages in Belarus serves to not only uncover the traces of complicated cross-country resettlements, but also examine the effects of massive resettlements on population genetics of ungulate species in general, as well as complete the phylogeographic map of this species\u0026rsquo; movements and migrations across the continent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this paper, we report the first thorough study of genetic makeup and ancestry of Belarusian red deer using mtDNA control region.\u0026nbsp;\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003ch3\u003eAnalysis outline\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eFor this study, we obtained sequences of mtDNA control region from a sample of 30 deer harvested across Belarus by extracting DNA from soft tissue or horn samples, amplifying a fragment of the CR locus in a PCR, and Sanger dideoxy sequencing the amplicons. Then we aligned the obtained sequences between themselves, as well as with a large set of homologous sequences obtained from earlier studies, and characterized the local haplotypes statistically and comparatively.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eSampling\u003c/h3\u003e\n\u003cp\u003eWe used a sample of 30 wild red deer specimens, harvested in 23 locations across Belarus during legal hunts between 2016 and 2022 (figure 2). The sample\u0026rsquo;s coverage includes all major wild populations of deer in Belarus, across five oblasts (regions) and 21 raion (district), while the studied population totals approximately 38 000 animals, according to most recent surveys using indirect counting methods. The analysed sample includes animals of either sex, aged between 1 and 8 years, according to descriptions. The full list of all specimens used in this study, along with Genbank accession numbers for obtained sequences, is given in Online Resource 1.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eMolecular methods\u003c/h3\u003e\n\u003cp\u003eWe used two methods for DNA isolation: one for cryogenically preserved soft tissue samples using \u0026laquo;Animal \u0026amp; Fungi DNA Preparation - Solution Kit\u0026raquo; (Jena Bioscience, Germany) following the manufacturer\u0026rsquo;s protocol, and an original method for horn tissue samples.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe utilized DNA isolation protocol for horn tissue samples was based on demineralization of powdered horn in a solution containing EDTA and sodium lauryl sulphate (SLS), followed by lysis in presence of proteinase K (ArtBioTech, Belarus) and DNA precipitation via iced ammonia acetate and chlorophorm. The latter method was developed based on a similar method described by Hoffman and Griebeler\u0026nbsp;(2013). We conducted all DNA isolation procedures with sterilized tools, in a clean laboratory environment spatially separated from DNA amplification and post-amplification areas, with extraction procedures themselves including negative and positive controls, all in order to avoid DNA isolate contamination. We then measured concentration and purity of the obtained isolate solutions with a nanospectrophotometer (330P Implen, Germany) and banked them for storage at -20\u0026nbsp;\u0026deg;С\u0026nbsp;until further use.\u003c/p\u003e\n\u003cp\u003eFor the analysis itself, we used a hypervariable fragment of mitochondrial DNA control region (also called \u0026laquo;D-loop\u0026raquo;) as the marker of choice.\u0026nbsp;(Wolstenholme 1992; Boore 1999). This neutral, haploid, non-recombining locus was widely used in earlier research into genetics of European ungulates, and population history of red deer specifically, providing us with certainty in its suitability for the task, as well as a wealth of data for comparative analysis. For PCR amplification of the marker we used classical primers LD5 (AAGCCATAGCCCCACTATCAA) and HD8 (TTGACTTAATGCGCTATGTA) by Nagata \u003cem\u003eet al\u0026nbsp;\u003c/em\u003e(Nagata et al. 1998), flanking a region approximately 350 base pairs in length, with oligonucleotide synthesis and purification performed by Primetech (Belarus). Amplification was carried out in individual 25\u0026micro;l reactions. Each reaction contained ammonia sulfate PCR buffer (Primetech, Belarus) in standard concentration; 0.2 mM of dNTPs (ArtBioTech, Belarus); 2,5 mM MgCl\u003csub\u003e2\u003c/sub\u003e; 1 U of Taq DNA polymerase (ArtBioTech, Belarus) and 15-20 ng of sample DNA\u0026nbsp;(Lorenz 2012). All reaction preparation procedures were conducted with positive and negative controls, on coolant trays, in a preemptively decontaminated laminar flow box located in an area spatially separated from sample processing and post-PCR analysis areas in order to prevent reaction contamination. We used a C1000 Touch Thermal Cycler (Bio-rad, USA) to carry out the amplification protocol, given in table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 1 \u0026ndash; PCR thermal cycling protocol used for CR amplification. t \u0026ndash; sample temperature for the stage; N \u0026ndash; number of stage repeats.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.358974358974358%\" valign=\"top\" style=\"width: 31.6456%;\"\u003e\u003cbr\u003e\u0026nbsp; t, ℃\u003c/td\u003e\n \u003ctd width=\"28.205128205128204%\" valign=\"top\" style=\"width: 42.4051%;\"\u003e\n \u003cp\u003eTime, sec.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.102564102564102%\" valign=\"top\" style=\"width: 25.9494%;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.53846153846154%\" valign=\"top\" style=\"width: 31.6456%;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.30769230769231%\" valign=\"top\" style=\"width: 42.4051%;\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\" style=\"width: 25.9494%;\"\u003e\n \u003cp\u003e1X\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.53846153846154%\" valign=\"top\" style=\"width: 31.6456%;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.30769230769231%\" valign=\"top\" style=\"width: 42.4051%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" rowspan=\"3\" style=\"width: 25.9494%;\"\u003e\n \u003cp\u003e30X\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.34146341463415%\" valign=\"top\" style=\"width: 31.6456%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"53.65853658536585%\" valign=\"top\" style=\"width: 42.4051%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.34146341463415%\" valign=\"top\" style=\"width: 31.6456%;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"53.65853658536585%\" valign=\"top\" style=\"width: 42.4051%;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.53846153846154%\" valign=\"top\" style=\"width: 31.6456%;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.30769230769231%\" valign=\"top\" style=\"width: 42.4051%;\"\u003e\n \u003cp\u003e480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\" style=\"width: 25.9494%;\"\u003e\n \u003cp\u003e1X\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe obtained amplicons were checked for size and undesirable by-products with an electrophoretic separation of 1-2 \u0026micro;l of reaction volume in 1% agarose gel with UV-transillumination. We used a 20 cm horizontal electrophoresis chamber \u0026nbsp;with sodium borate buffer, DNA size marker \u0026ldquo;100+ bp DNA Ladder\u0026rdquo; (Evrogen, Russia) for size reference, and the Gel Doc\u0026trade; XR+ (Bio-rad, USA) gel documentation system.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmplicons that showed sufficient quantity and purity of the expected product were sequenced using the Sanger dideoxy method by the Institute of Bioorganic Chemistry of the NAS of Belarus. Amplicons were once again separated by electrophoresis in 0.8% agarose gel, target fragments were cut out from the gel and purified with NucleoSpin Gel and PCR Clean‑up (Macherey Nagel, Germany) following the manufacturer\u0026rsquo;s protocol. The purified DNA fragments then underwent bidirectional sequencing reaction using BrilliantDye3.1 kit (Nimagen, Netherlands). Products were purified using ethanol/EDTA precipitation and separated with ABI3130 Genetic Analyzer (Thermo Fisher Scientific, USA). We then analysed the produced sequenograms using UGENE v39 (Okonechnikov et al. 2012) software package \u0026ndash; readings were aligned against a reference red deer mitochondrial genome (Genbank accession number NC_007704). The CR fragment nucleotide sequences for individual specimens were determined according to consensus reading of two bidirectional reads of the same specimen, aligned against the reference genome and additionally checked by hand. For further multiple alignments we used the MAFFT 7.490 (Katoh and Standley 2013) multiple alignment algorithm implemented in UGENE.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eHaplotype analysis\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eTo determine genetic lineages of studied specimens, we assembled a selection of 615 European and Asian red deer mitochondrial control region sequences, obtained from NCBI Genbank database\u0026nbsp;(Randi et al. 2001; Polziehn and Strobeck 2002; Nussey et al. 2006; P\u0026eacute;rez-Espona et al. 2009; McDevitt et al. 2009; Haanes et al. 2010; Fickel et al. 2012; Olivieri et al. 2014; Krojerov\u0026aacute;-Proke\u0026scaron;ov\u0026aacute; et al. 2015; Lorenzini and Garofalo 2015; Borowski et al. 2016; Frank et al. 2017; Schnitzler et al. 2018; Meiri et al. 2018). The selection includes both individual specimen sequences and haplotypes. Every sequence in the selection was then assigned a lineage according to data provided in corresponding publications. In cases where the same sequences had conflicting assignments in different papers, we gave preference to the latest publication. In a few cases where sequences were not assigned a lineage in original research, we assigned it inductively during the \u003cem\u003ead hoc\u003c/em\u003e analysis. The full list of sequences used in analysis, including individual listing of sources, geographic origins, haplotypes and assigned lineages is given in Online Resource 2. Aligned sequences were condensed into haplotypes within the utilized alignment length using FaBox online software tools\u0026nbsp;(Villesen 2007). The haplotypes were numbered in consecutive order, with a naming scheme that refers only only to this study. We then assigned lineages to haplotypes according to the lineages previously assigned to sequences included into said haplotypes, which served to assign a lineage to every original sequence produced in this study through simple grouping.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo estimate genetic diversity coefficients we used DNASP 6.12.03 software package. Haplotype networks were designed using NETWORK 10.2.0.0\u0026nbsp;(Bandelt et al. 1999; Polzin and Daneshmand 2003), where we used Median Joining algorithm, with \u0026epsilon; paramenter equaling 0, with no site weighting or external network rooting, followed by MP Calculation post-processing to determine the shortest tree within the network. To create cladograms, we used MEGA 11.0.10 software\u0026nbsp;(Tamura et al. 2021), following maximum parsimony method with partial deletion treatment of gap sites, with threshold of 95% taxa in the sample, and estimated clade bootstrap support with 1000 replicates of bootstrap.\u003c/p\u003e\n\u003cp\u003eIllustrative maps in this paper were made using QGIS 3.24.2.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe obtained control region sequences for 30 Belarusian specimens (Genbank accession numbers OQ968556- OQ968585), with sequence length ranging between 253 and 359 b.p., and discovered 6 haplotypes among them, segregated by 10 polymorphic sites. Genetic diversity characteristics for the studied population and a number of other European populations (for comparison) are given in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Genetic diversity parameters for the Belarusian red deer population according to mtDNA control region sequence analysis, in comparison with a selection of other European populations. The data acquired in this study are given in bold. Src. \u0026ndash; source of data; Population \u0026ndash; the name or geographic location of the population according to source; b.p. \u0026ndash; the length of control region sequence used in the; N \u0026ndash; sample size; H \u0026ndash; number of haplotypes in the sample; Ĥ \u0026ndash; haplotype diversity; SD (Ĥ) \u0026ndash; standard deviation of haplotype diversity; n \u0026ndash; nucleotide diversity; SD (n) \u0026ndash; standard deviation of haplotype diversity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"18\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"18\" nameend=\"c18\" namest=\"c1\"\u003e \u003cp\u003eππ\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eb.p.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eĤ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eSD (Ĥ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eπ\u003csub\u003en\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003eSD (π\u003csub\u003en\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThis study\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eBelarus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003e328\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003e30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.55\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0 .101\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.0021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"5\" nameend=\"c2\" namest=\"c1\" rowspan=\"6\"\u003e \u003cp\u003eNiedziałkowska et al (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Belarus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"5\" nameend=\"c5\" namest=\"c4\" rowspan=\"6\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLithuania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBialowieza Forest (Poland)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUkraine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMasuria (Poland)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorth-Eastern Poland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"6\" nameend=\"c2\" namest=\"c1\" rowspan=\"7\"\u003e \u003cp\u003eSkog \u003cem\u003eet al\u003c/em\u003e (2009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSerbia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"6\" nameend=\"c5\" namest=\"c4\" rowspan=\"7\"\u003e \u003cp\u003e332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHungary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eScotland (UK)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWestern Norway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorthern Germany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUpper Marne (France)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRomania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGiovannelli \u003cem\u003eet al\u003c/em\u003e (2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMeiri et al (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWestern and Central Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0.0021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eObtained genetic diversity parameter values for the studied population indicate a level of genetic diversity similar to most heavily managed, mixed populations of red deer in the region.\u003c/p\u003e \u003cp\u003eDue to very limited sequence length and low number of polymorphic sites, we used several different alignments for further analysis. Namely: alignment I (230 b.p.), which included 26 of the best quality sequences that we obtained and a set of 615 Genbank sequences; alignment II (328 b.p.), made up entirely from the 30 obtained in this study; and alignment III (302 b.p.), which included Belarusian sequences assigned to the lineage \u0026laquo;E\u0026raquo; and a number of lineage \u0026laquo;E\u0026raquo; sequences obtained from Genbank (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A fourth alignment, meant for a similar clarification of ancestry in Belarusian part of lineage A, was excluded from the work, as it was not any more informative than alignment I.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; a listing of mtDNA CR alignments used in this study. \u0026ldquo;Sequences\u0026rdquo; and \u0026ldquo;Haplotypes\u0026rdquo; columns list the numbers of sequences or haplotypes obtained in this study (Bel), plus the number of Genbank sequences, included in the corresponding alignment.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlignment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb.p..\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequences (Bel\u0026thinsp;+\u0026thinsp;GB)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHaplotypes (Bel\u0026thinsp;+\u0026thinsp;GB)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u0026thinsp;+\u0026thinsp;615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u0026thinsp;+\u0026thinsp;114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u0026thinsp;+\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u0026thinsp;+\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHaplotype analysis utilizing alignment I allowed us to assign 20 Belarusian red deer specimens to CR mtDNA lineage \u0026laquo;A\u0026raquo; (Iberian haplogroup), and 6 specimens \u0026ndash; to the maraloid lineage \u0026laquo;E\u0026raquo;. A corresponding haplotype network is given in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Of the remaining 4 specimens, we had 3 individuals assigned \u0026laquo;A\u0026raquo; and 1 assigned \u0026laquo;E\u0026raquo; in the post hoc analysis. What draws immediate attention is the complete absence of Balkan lineage \u0026laquo;C\u0026raquo; in the studied sample. It\u0026rsquo;s worth pointing out that the haplotype network shows all European red deer lineages as clearly defined, except for Mesolan lineage \u0026laquo;D\u0026raquo;. We suggest that the length of the utilized alignment was insufficient to manifest lineage \u0026laquo;D\u0026raquo;, but this does not compromise the analysis, as we are not aware of any premises that could make presence of lineage \u0026laquo;D\u0026raquo; in Belarus likely, be it close range borders of that group or any known translocations of animals from the Mesola preserve to Belarus. Another curious finding is that none of the Belarusian specimens which we assigned lineage \u0026laquo;E\u0026raquo; had shown prominent maraloid morphology, according to descriptions given to us by the hunters involved in harvesting, while simultaneously multiple individuals described as possessing maraloid appearance were assigned lineage \u0026laquo;A\u0026raquo; in our analysis.\u003c/p\u003e \u003cp\u003eAlignment II was used to build a cladogram of Belarusian specimens obtained in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), which also shows a clear partition of those individuals into 2 clades, corresponding to genetic lineages \u0026laquo;A\u0026raquo; and \u0026laquo;E\u0026raquo;. 3 of the 6 haplotypes found in the samples belong to haplogroup \u0026laquo;A\u0026raquo;, the other 3 belong to the haplogroup \u0026laquo;E\u0026raquo;. The cladogram of maraloid specimens (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb) in turn shows that Belarusian \u0026laquo;E\u0026raquo; lineage haplogroups are divided into 2 subclades \u0026ndash; one of which is grouped with Voronezh maral (Russia) haplotype discovered by Meiri et al (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), while the other one is grouped with a Turkish maral haplotype.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGeographic distribution of red deer genetic lineages over the territory of Belarus (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) has shown a wide distribution of lineage \u0026laquo;A\u0026raquo; across the sampled territory, while lineage \u0026laquo;E\u0026raquo; appears to be present only in a small region in the North-Eastern part of the country, located between Beresinsky Reserve, Orsha and Berezino townships.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings on red deer genetic lineages in Belarus partially diverge from the earlier data \u0026ndash; the studied sample shows no presence of Balkan lineage \u0026laquo;C\u0026raquo;, which was reported as present in the country based on analysis of a limited sample by Niedziałkowska et al (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). At the same time, our results agree with those for a small Belarusian sample used by Meiri et al (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). We interpret the disagreement as a product of differences in reference data for lineage assignment \u0026ndash; the study by Niedziałkowska \u003cem\u003eet al\u003c/em\u003e was the first inquiry into genetics of Eastern European red deer, preceding any similar research into maral populations, and thus delineation of lineage \u0026laquo;E\u0026raquo; itself. Thorough inquiries into genetics and ancestry of maral populations are extremely recent (Golosova et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). According to our own analysis (unpublished data), specimens belonging to the latter can be easily misclassified as belonging to lineage \u0026laquo;C\u0026raquo; when the reference sequences are in limited supply, especially when using short reads.\u003c/p\u003e \u003cp\u003eThe selection of haplotypes that we observe in the Belarusian population suggests that the core of the local population originates from Central European stock, with a presence of maral admixture. This is supported by the historical management data for the local population, which ascribes most of the current red deer range in the country to reintroduction during Soviet and post-Soviet periods from Bialowieza Forest stock, which itself has origins in Silesian, Lodzian and Bohemian red deer populations (Romanov \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). There is also information on several significant resettlements of deer from the Voronezh Nature Reserve, reporting at least 313 specimens moved to Belarus between 1956 and 1972. This includes 85 individual animals released specifically in the areas that we defined here as the contemporary lineage \u0026laquo;E\u0026raquo; range, plus several other similar releases in the same area, but involving an unknown number of animals (Shakun \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The genetic diversity values for the Belarusian population also suggest a mixed character.\u003c/p\u003e \u003cp\u003eThe findings on the lineage ranges within the country lead us to the conclusion that the contemporary distribution of both discovered lineages in Belarus was determined largely through human involvement in the form of reintroductions from diverse sources. This is indicated by fragmented nature of the range and concentration of specimens assigned to the lineage E around the artificial population of Berezinsky Biosphere Reserve, and supported by historical reintroduction data. The Voronezh preserve population of red deer, described as predominantly maraloid in ancestry by earlier studies (Meiri et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Doan et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), appears to be the most likely source of maral admixture in the contemporary Belarusian population, as indicated by the clade analysis of maraloid sequences. Unfortunately, short lengths of the obtained sequence reads coupled together with low haplotype diversity in the probable ancestral populations for Belarusian lineage \u0026laquo;A\u0026raquo; stock prevent us from pinpointing it\u0026rsquo;s ancestry with precision higher than just \u0026laquo;Central Europe\u0026raquo;.\u003c/p\u003e \u003cp\u003eOur sample is also poorly suited for determining the haplotype frequency of lineages in the studied area, as the absolute majority of the specimens assigned to lineage \u0026laquo;E\u0026raquo; (5 individuals) come from the same locality (Berezinsky Biosphere Reserve), which also happens the be the locality with the highest representation in the sample. This would serve as a source of significant statistical bias. Meanwhile collapsing every locality down to a single data point would make the sample too small for a representative haplotype frequency analysis. What we can deduce from lineage \u0026laquo;E\u0026raquo; being present in three localities out 23 sampled is that animals belonging to the lineage \u0026laquo;E\u0026raquo; had had significant success in adapting to the new range after release, and achieved sufficient presence in the population to consider it a part of the local population core. Mitochondrial analysis being limited to pure matrilineal ancestry and the lineage not corresponding clearly with morphological appearance leave an open possibility of much greater scale, undetected presence of maral ancestry in the Belarusian red deer population.\u003c/p\u003e \u003cp\u003eOur findings clarify the contemporary distribution of red deer lineages across Eastern Europe. The range of lineage \u0026laquo;A\u0026raquo; expands further east, at least until the eastern border of Belarus, and possibly beyond. The range of lineage \u0026laquo;E\u0026raquo; appears to reach further north-west than previously assumed. We cannot conclusively state that Balkan lineage \u0026laquo;C\u0026raquo; ancestry is absent from the Belarusian red deer population, but its presence appears to be elusively rare at most, with no significant contribution to the gene pool, while the northernmost limits of the lineage\u0026rsquo;s range seems to be located in Ukraine. In all cases for the Belarusian population, the role of anthropogenic factor in shaping the population\u0026rsquo;s genetic makeup and distribution range is higher than ever before. Maraloid admixture, artificially introduced from the Voronezh population, contributes a significant portion of the population\u0026rsquo;s genetic diversity, but most likely serves to distance genetic makeup of population further away from the lost autochthonous deer population that inhabited Belarus before the XVIII century. Additional research into genetics of ancient deer in the region can serve to steer management of the contemporary population closer towards the optimal path of reconstruction and sustainable conservation of autochthonous deer varieties in natural conditions (Apollonio et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) as the contemporary population in Belarus experiences growth stabilization after reintroduction, facing threats of habitat fragmentation and increasing anthropogenic pressure.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of interest\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAuthors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe want to thank G.V. Sergeev for his assistance with DNA sequencing. We also thank Alexandra Larchenko, Georgiy Yanuta, Pavel Veligurov, Yuri Bogutsky, Lyudmila Akimova, Gennadiy Puzankevich, Vadim Sidorovich, A.A. Pruchkovskiy, A.N. Sasimovich, P.K. Gorodko, A.A. Pruchkovsky, O.E. Degitrov, V.V. Nosevich, V.N. Alshevskiy, N.V. Makengir, S.N. Kolesnik, Y.N. Yurnezh, A.I. Prasnich, S.N. Moshienko, V.V. Stolyarchuk, V.V. Pushilo, G.N. Klyuka, V.S. Genr, V.V. Kovalenok, A.A. Kravchenko, G.V. Zinevich, A. Mitrinkov, and all anonymous hunters and foresters for their help in the sampling process.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was conducted as a part of A.A. Valnisty\u0026rsquo;s research for his PhD thesis \u0026laquo;Genetic structure of the red deer population in Belarus under reintroduction conditions\u0026raquo; and as such was funded by the graduate student fund of the National Academy of Sciences.\u003c/p\u003e\n\u003cp\u003eParts of this study were financed by the Belarusian State Scientific Research Program \u0026quot;Nature management and environmental risks\u0026quot; for 2016-2020 (subprogram 01 \u0026quot;Rational use of natural resources and innovative technologies for deep processing of natural resources\u0026quot;), grant 5.1 \u0026quot;Genetic passportization of red deer populations as a basis for forming and maintaining a high degree of diversity and reproduction rates\u0026quot;, as well as Belarusian State Scientific Research Program \u0026quot;Natural Resources and Environment\u0026quot; for 2021-2025 (subprogram 10.2 \u0026quot;Biodiversity, Bioresources, Ecology\u0026quot;, task 5 \u0026quot;Creating a scientific basis for management of target traits in populations of rare and economically significant animal and plant species based on studies of structural and functional organization of their genomes\u0026quot;), grant 2: \u0026quot;Assessment of molecular genetic effects and associated risks in population disturbances in problem resource, biocenotically significant and rare animal species\u0026quot;.\u003c/p\u003e\n\u003ch2\u003eData availability\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAll the sequences obtained in this work were uploaded to the NCBI Genbank Nucleotide open access database (accession numbers OQ968556- OQ968585). All the tissue samples used in this work were banked in the cryocollection of the Genetic Bank of Wildlife of SNPO \u0026quot;SPC of the National Academy of Sciences of Belarus for Bioresources\u0026quot; (Akademicheskaya st., 27, 220072, Minsk, Republic of Belarus) for long-term storage, and can be provided on demand for data verification.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eApollonio M, Belkin VV, Borkowski J et al (2017) Challenges and science-based implications for modern management and conservation of European ungulate populations. Mamm Res 62:209\u0026ndash;217. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s13364-017-0321-5\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eBandelt HJ, Forster P, Rohl A (1999) Median-joining networks for inferring intraspecific phylogenies. 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Italian J Zool 81:136\u0026ndash;143. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/11250003.2014.895060\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mitochondrial DNA, Ungulates, Control Region, Genetic lineage, Phylogeography, Cervus elaphus","lastPublishedDoi":"10.21203/rs.3.rs-2967492/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2967492/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHere we report the first thorough genetic characterization of the long understudied red deer population of Belarus in regards to its ancestry according to mtDNA sequence analysis. Employing a 328 base pair segment of the mitochondrial control region (d-loop) from 30 deer specimens of either sex recently harvested across the country, we have discovered 6 haplotypes belonging to 2 of the widely described European red deer lineages, or haplogroups: Iberian (A) and Maraloid (E), clarifying the range limits of both lineages in the region. Combining this data with a comparative analysis of genetic diversity and historical records, we conclude that the Belarusian population of red deer has an artificially mixed origin, though it remains unclear how desirable such a state of the local population is, in terms of sustainable management, use and conservation. Inquiries into ancient DNA are required in order to recognize the lineages closest to the now lost autochthonous population of Belarus.\u003c/p\u003e","manuscriptTitle":"Between the lines: mitochondrial lineages in the heavily managed red deer population of Belarus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-06-05 14:33:48","doi":"10.21203/rs.3.rs-2967492/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6ebaa851-7e84-4a3a-8e3a-663a89cc03b6","owner":[],"postedDate":"June 5th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-03-15T10:11:48+00:00","versionOfRecord":{"articleIdentity":"rs-2967492","link":"https://doi.org/10.1007/s42991-023-00397-w","journal":{"identity":"mammalian-biology","isVorOnly":false,"title":"Mammalian Biology"},"publishedOn":"2024-02-02 10:11:48","publishedOnDateReadable":"February 2nd, 2024"},"versionCreatedAt":"2023-06-05 14:33:48","video":"","vorDoi":"10.1007/s42991-023-00397-w","vorDoiUrl":"https://doi.org/10.1007/s42991-023-00397-w","workflowStages":[]},"version":"v1","identity":"rs-2967492","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2967492","identity":"rs-2967492","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}