Next Article in Journal
Role of the PPARGC1A Gene and Its rs8192678 Polymorphism on Sport Performance, Aerobic Capacity, Muscle Adaptation and Metabolic Diseases: A Narrative Review
Previous Article in Journal
Comparative Transcriptome Analysis Reveals Mechanisms of Differential Salinity Tolerance Between Suaeda glauca and Suaeda salsa
Previous Article in Special Issue
Polymorphic Loci of Adaptively Significant Genes Selection for Determining Nucleotide Polymorphism of Pinus sylvestris L. Populations in the Urals
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Genes
Volume 15
Issue 12
10.3390/genes15121629
genes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Polymorphism of Genes Potentially Affecting Growth and Body Size Suggests Genetic Divergence in Wild and Domestic Reindeer (Rangifer tarandus) Populations

by
Anna A. Krutikova
1,2,
Natalia V. Dementieva
1,*,
Yuri S. Shcherbakov
1,
Vasiliy V. Goncharov
3,
Darren K. Griffin
4,5 and
Michael N. Romanov
4,5,6,*
1
Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin 196601, Russia
2
Department of Genetic and Reproductive Biotechnologies, Saint Petersburg State University of Veterinary Medicine, Saint Petersburg 196084, Russia
3
Research Institute of Agriculture and Ecology of the Arctic—Branch of the Federal Research Center “Krasnoyarsk Science Center”, Norilsk 663302, Russia
4
School of Natural Sciences, University of Kent, Canterbury CT2 7NJ, UK
5
Animal Genomics and Bioresource Research Unit (AGB Research Unit), Faculty of Science, Kasetsart University, Chatuchak, Bangkok 10900, Thailand
6
L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Russia
*
Authors to whom correspondence should be addressed.
Genes 2024, 15(12), 1629; https://doi.org/10.3390/genes15121629
Submission received: 29 November 2024 / Revised: 11 December 2024 / Accepted: 12 December 2024 / Published: 20 December 2024
(This article belongs to the Special Issue Wildlife Genetic Diversity and Genomics)
Browse Figures
Versions Notes

Abstract

:
Background/Objectives: A combination of increased human presence in the Arctic zone alongside climate change has led to a decrease in the number of wild reindeer (Rangifer tarandus). Studying the genetic potential of this species will aid in conservation efforts, while simultaneously promoting improved meat productivity in domestic reindeer. Alongside reducing feed costs, increasing disease resistance, etc., acquiring genetic variation information is a crucial task for domestic reindeer husbandry. This study thus identified highly informative molecular genetic markers usable for assessing genetic diversity and breeding purposes in reindeer. Methods: We analyzed gene polymorphism that may potentially affect animal growth and development in populations of wild (Taimyr Peninsula) and domestic reindeer, including Nenets and Evenk breeds. We screened these populations for polymorphisms by sequencing the GH, GHR, LCORL and BMP2 genes. Results: Following generation of gene sequences, we compared the alleles frequency in the surveyed populations and their genetic divergence. Some loci lacked polymorphism in wild reindeer, unlike domestic breeds. This could suggest a selection-driven microevolutionary divergence in domestic reindeer populations. An isolated domestic population from Kolguyev Island appeared to be genetically remote from continental reindeer. Conclusions: Molecular genetic markers associated with economically important traits in reindeer can be further developed using the data obtained. Monitoring wild reindeer populations and better utilizing the genetic potential of domestic animals will depend on a panel of these marker genes. By using this marker panel, the amount of time spent on selection efforts will be greatly reduced to enhance meat performance during reindeer breeding.

1. Introduction

The wild reindeer (R. tarandus L. 1758) population in Eurasia is estimated to be over one million, but is declining [1] due to various factors. These include increased human presence (e.g., due to tourism) in the Arctic zone alongside climate changes that lead to a habitat deterioration, particularly in the quality of pasture lands [2,3,4]. In addition, overhunting, disease spread [5], the expansion of mining operations and the usage of land for breeding domestic reindeer [6,7] all contribute to this decline. To the best of our knowledge, reindeer is the only species in which the exchange of genetic material between wild and domesticated forms is not restricted [8,9]. The largest population of wild reindeer in Russia is localized on the Taimyr Peninsula, which has not undergone long periods of sharp decline [10].
Russia is home to two-thirds of the world’s domestic reindeer population [11]. In 1985, four breeds of reindeer were approved and entered into the State Register. These are the Nenets [12,13], Chukchi, Even and Evenk breeds. The most numerous of these is the Nenets breed that number over one million individuals. In the western territory of its distribution, the Nenets breed has contact with the wild and Sámi reindeer, in the north and south the breed has virtually no contact with wild reindeer and other domestic breeds. In the east, its contacts have been recorded with the Taimyr wild reindeer population and the Evenk breed [12]. Phenotypic differences between both wild and domestic reindeer are mostly due to habitat conditions. Reindeer grazing in the tundra (e.g., the Nenets breed) are significantly smaller in size than those living in the forest-tundra, taiga, or mountainous regions (e.g., the Evenk breed) [14,15]. The size of an animal is of great importance for survival in the harsh Arctic conditions, where there are many predatory animals. In addition, hunters prefer larger individuals, which leads to a decrease in the survival of wild populations.
Research by Pokharel et al. [16] demonstrated that genes, which differentiate reindeer populations, are associated with evolutionary processes. This may indicate genetic diversity across all populations in genes associated with animal growth and size. Recently, studies on reindeer have been focused on the generation of a complete genome assembly, which will significantly advance our knowledge of the variability of populations belonging to the ruminant species most adapted to extreme habitat conditions [16,17,18,19]. As a result of whole genome sequencing, a large set of R. tarandus scaffolds and whole chromosome sequences is available in the NCBI databases [20]; this makes it possible to compare sequenced regions of individual genes (e.g., growth hormone receptor (GHR) gene [21,22]) with information contained within whole genome sequence databases.
In our previous studies [23,24,25], we preliminarily evaluated the variability of the GH (growth hormone), LCORL (ligand dependent nuclear receptor corepressor like) and BMP2 (bone morphogenetic protein 2) gene regions that are, most likely, important for the formation of reindeer body size. The current investigation provides a further information on the partial sequencing and, for the first time, polymorphism of the GHR gene region, supplemented by a comparative analysis of polymorphic variants of the above studied genes, including a novel LCORL indel.

2. Materials and Methods

2.1. Sample Collection and Genomic DNA Extraction

The experiments were conducted in the Laboratory of Molecular Genetics, Russian Research Institute of Farm Animal Genetics and Breeding (RRIFAGB). The material for the studies was DNA isolated from samples of biological tissues of wild and domestic reindeer collected at five sites in the Far North of Russia (Figure 1).
Blood samples taken from the jugular vein; ear notches as well as parts of muscle tissue of shot wild reindeer were used to isolate DNA. DNA extraction was carried out using the conventional phenol method. For the GHR and GH [23] gene analyses, the following samples were obtained (Figure 1): from the tissues of wild reindeer from the Taimyr Peninsula (TaiWild; n = 10; Figure 2c), as well as domestic breeds, including the Nenets breed (Figure 2a) from the village of Nosok (NoNen; n = 10), vicinity of the Naryan-Mar city (NarNen; n = 11) and Kolguyev Island (KgNen; n = 11) and the Evenk breed (Figure 2b) from the village of Surinda (SurEv; n = 6). For the LCORL [24] and BMP2 [25] gene analyses, a different set of samples was employed, including the wild population of the Taimyr Peninsula (n = 20), the Nenets breed (n = 20) and the Evenk breed (n = 20).

2.2. PCR, Gene Sequencing and Computational Analyses

Initial lab work was performed to optimize the PCR amplification conditions and select annealing temperatures for each primer pairs specific for certain regions of the GHR, GH, LCORL and BMP2 genes used in the comparative analysis within the framework of this study (Table 1). The PCR primers were synthesized by Syntol LLC (Moscow, Russia).
Purification of PCR products for further sample preparation before sequencing was performed using the commercial ExoSAP-IT Express enzymatic purification kit for PCR products (Affymetrix, Santa Clara, CA, USA).
Sanger sequencing of the generated amplicons was performed using an Applied Biosystems 3500 Genetic Analyzer using the commercial BigDye® Terminator v3.1 Sequencing Standard Kit (Applied Biosystems, Waltham, MA, USA) according to the manufacturer’s protocol. The obtained partial gene sequences were aligned and analyzed using Mega 6 software [26,27,28] and deposited in GenBank. Supplementary Information S1 contains the raw genotyping data.
Further analysis of gene sequences was carried out within the bioinformatic environment of the NCBI genetic databases [29]. Allele frequencies were calculated at each locus and in each population (Supplementary Information S1) and used for hierarchical clustering of the populations/breeds studied. The latter was performed using the Phantasus web application [30]. Accordingly, Euclidean distances were computed for columns of the allele frequency matrices (with the average option selected for the clustering method) and hierarchical clustering trees were subsequently generated. As the genetic diversity statistics at SNP loci in the GHR and GH genes, we computed observed heterozygosity (HO), expected heterozygosity (HE), unbiased expected heterozygosity (UHE) [31] and rarefied allelic richness (AR) [32] using the R library diveRsity package [33] in the five studied populations, i.e., TaiWild, SurEv, NoNen, NarNen and KgNen. Additionally, we ranked these populations in a simplified form by the diversity indicator values from 1 (the lowest one) to 5 (the highest one) and calculated the corresponding mean rank values. Similar genetic diversity computations and ranking were performed for SNP loci in the LCORL and BMP2 genes in one wild population and two domestic breeds, Nenets and Evenk.

3. Results and Discussion

3.1. GHR and GH Gene Polymorphisms

In this study, we investigated the GHR gene polymorphism in wild and domestic reindeer; to the best of our knowledge, it is the first time that this has been achieved (Table 2, Supplementary Information S1). This is one of the key genes responsible for growth formation in animals [22]. The obtained data on the frequency of occurrence of three GHR gene polymorphic variants in wild and domestic reindeer differed slightly (Table 2), except the Evenk breed of domestic reindeer (SurEv) that distinguishes from other populations by its greater height and a much lower frequency of the single nucleotide polymorphism (SNP) GHR3 allele C (0.08). Another exception was the wild reindeer population (Tai) that had a greater frequency of the SNP GHR1 allele A (0.80). The data we obtained as a result of sequencing the GHR gene had a few discrepancies with the previously deposited sequence of exon 10 of this gene available for the R. tarandus [21,22]. Data on the detected genetic differences at the nucleotide alignment level are provided in Supplementary Information S2a. The importance of identifying GHR gene polymorphism is due to the fact that its functioning deficiency can cause smaller height phenotypes [34].
In our previous studies [23], we also sequenced regions of exons 2 and 3 in the GH gene. Supplementary Information S2b contains information on the genetic changes identified at the nucleotide alignment level. This was carried out for a total of 48 reindeer from the same five populations spread in northern Russian Eurasia and showed the presence of four SNPs, i.e., C12T, C72T, A122G and A235G (Figure 3, Supplementary Information S1). It should be noted that in mammals, the structure of pituitary GH is generally strictly conserved [35,36]. However, in primates and artiodactyls, the rate of evolution in this gene has increased dramatically (25–50-fold), so that the GH sequences of humans and ruminants differ significantly from the sequences of other mammals [35,36]. At the same time, the GH gene sequence in red deer (Cervus elaphus) differs significantly from that of other ruminants [37]. Wild reindeer from the Taimyr Peninsula in our studies [23] had a higher level of polymorphism for all four SNPs (Figure 3). Unlike wild reindeer, domestic breeds had similar homozygotes with a low minor allele frequency for two of the four polymorphisms.
When analyzing the genetic diversity indicators for a total of seven SNP loci in GHR and GH genes (Table 3), we noted that the SurEv population tended to have the lowest HE, UHE and AR values, while the wild population (TaiWild) seemed to have the highest values. However, because of the overall mixed diversity pattern for the five populations and for the four indices, we also estimated the data in a simplified form using the population ranking (Table 3). Herewith, the SurEv population was least variable (M = 1.5) and the NarNen and TaiWild populations demonstrated the highest mean diversity rank (M = 4).
A very similar genetic diversity difference pattern was observed when implementing the hierarchical clustering of the studied populations (Figure 4a) using the same set of diversity values (Table 3).

3.2. LCORL and BMP2 Gene Polymorphisms

One more important gene putatively influencing the formation of the skeletal size of animals is the LCORL gene [38,39,40]. In our studies [24], we sequenced exon 7 of the LCORL gene, where seven single-nucleotide substitution variants and one insertion/deletion polymorphism were identified (Figure 5, Supplementary Information S1; [24]). In particular, there was one previously undescribed 36-bp deletion detected, namely, in region 5 in exon 7 of the LCORL gene; this was found only in domestic reindeer.
The length of a novel deletion identified by us in exon 7 of the LCORL gene allows to detect its presence even by electrophoresis in an agarose gel. Analysis of the frequency of this deletion showed that such a mutation does not occur in the surveyed sampling of wild reindeer; accordingly, the frequency of the genotype for the alternative allele In/In in the wild population was 1.00. A lower frequency of the minor allele Del was observed in the analyzed sample of domestic reindeer of the Nenets breed and was 0.11. In reindeer of the Evenk breed, the frequency of the minor allele Del was slightly higher and was 0.15 (Figure 5).
The BMP2 gene is another gene associated with animal growth and antler formation in deer [41]. In our earlier studies [25], 11 polymorphic variants were found and studied in wild and domestic reindeer (Figure 6, Supplementary Information S1). However, few clear-cut differences were found between wild and domestic reindeer at first glance. It should be noted that there were slight differences in the allele frequencies in the Evenk breed, which is the largest in size among reindeer.
Using genotyping information for a total of 19 SNP loci in the LCORL and BMP2 genes to analyze genetic diversity indices (Table 4), we established that the Nenets breed was inclined to show the lowest values of all the four statistics calculated. The Evenk breed and wild reindeer were prone to be more variable. This diversity pattern seemed to be similar using the simplified ranking form (Table 4) and hierarchical clustering (Figure 4b) procedures.

3.3. Divergence Estimation and Other General Considerations

Based on the allele frequencies at the analyzed SNP loci in the GHR, GH, LCORL and BMP2 genes, we reconstructed the respective hierarchical clustering trees (Figure 7). Their topology suggests the genetic divergence between the wild and domestic reindeer populations/breeds. The wild reindeer was maximally distant from the domestics and the domestic populations/breeds formed one large cluster.
According to the occurrence frequencies of a total of seven SNP alleles in the GHR and GH genes (Figure 7a), the NoNen population of the Nenets breed was most closely related to the SurEv population of the Evenk breed, while the isolated KgNen population of the Nenets breed from Kolguyev Island was genetically most remote from the continental populations of two domestic breeds. In this context, the KgNen population was established in the 19th century (Figure 2c), originating from domestic reindeer brought to the island from the mainland about 200 years ago. In the 20th century, the number of domestic reindeer here reached around 20,000. Until 2012, the reindeer population remained at a relatively high level (~12,000), but then there was a mass mortality of animals. By 2015, 153 reindeer remained on the island [42,43]. Presently, the population is recovering (~2000 in 2021) [43]. Our findings were derived from the sampling before the mass mortality and do not reflect the current genetic diversity of the KgNen population (Table 3, Figure 4a). A systematic genetic monitoring of this population would provide crucial information for further preservation and exploitation of KgNen reindeer whose herding is the basis of local economy.
We also attempted to estimate genetic diversity and establish its varied pattern across the populations/breeds studied depending on the genes used for genotyping (Table 3 and Table 4, Figure 4). Wild reindeer was, most likely, characterized by a higher overall diversity, although, in contrast to domestic breeds, certain loci in wild reindeer lacked polymorphism. However, taking into account a rather limited number of sequenced animal samples per population, we would cautiously consider these diversity assessment patterns as preliminary, in that they require further investigation using larger population sampling sizes and more SNP markers.
The process of domestication of wild animals, including reindeer, inevitably leads to significant changes in their genome [44,45,46,47]. The longer the exposure of animal species, the more significant changes are fixed in their genes. The most significant changes occur in the genes of interest, i.e., genes involved in metabolic pathways in the process of formation of productive traits [18,48,49] that lead to increased growth, more meat, higher yield and quality of wool, increased milk production, etc. [50,51]. Mutations that spontaneously arise in both wild and domestic animals and lead to hypertrophy of quantitative traits have different ways of implementation in wild and domestic populations of the same species [52,53,54,55,56]. In domestic animals, such a mutation will be fixed due to artificial selection carried out by humans and further breeding work [57,58,59,60]. In a wild population, such mutations are more susceptible to elimination due to natural selection. The realization of the genetic potential of a mutation leading to hypertrophy of quantitative traits was associated, first of all, with increased feed consumption, and secondly, with its balance [61], which is not always feasible in natural conditions, as in the case of wild reindeer.
The current interest in the genetic study of reindeer is due to the fact that it is one of the few currently existing animals that are well-represented both in the wild and domesticated state. In addition, the reindeer is one of the most recently domesticated animals [62,63,64,65]. The main and practically the only type of productivity in reindeer is meat performance [66,67]. In Russia, when breeding reindeer, meat productivity is the main indicator; strength of constitution, growth, endurance to climatic conditions and draft work, and resistance to diseases are secondary [7]. In this regard, further study of the genetic characteristics of reindeer is required to understand the hereditary factors underlying the specific phenotypic and adaptive characteristics of this animal common in cold climates.

4. Conclusions

When introducing molecular genetic methods to study the characteristics of wild species populations and to the selection process in agricultural species, genes of interest responsible for adaptability, as well as dairy, meat and other productivity traits need to be thoroughly investigated [68,69]. From a whole range of genes playing a significant role in growth and muscle mass formation, potential candidates are GHR, GH, LCORL and BMP2. Here, we completed a preliminary comparative study of polymorphic regions of these genes in wild and domestic reindeer of Russia. Several SNPs and indels were identified, as was their occurrence in the genome of wild and domestic reindeer from different regions. The analysis of genes potentially associated with animal growth revealed features of the frequencies of polymorphic sequence variants that distinguish wild reindeer of the Taimyr Peninsula [70] from domestic reindeer breeds. Wild reindeer had no or fewer polymorphisms for a number of polymorphic variants, which may indicate microevolutionarily formed and selection-driven differences underlying the genetic divergence between wild and domestic reindeer populations. Domestic reindeer of the Far North of Russia had different levels of polymorphism for all identified SNPs, which is apparently the result of the selection process in populations. Herewith, the isolated population of Kolguyev Island is likely to be genetically more distant from continental domestic populations.
The obtained data can serve as a starting point for further developing molecular genetic markers associated with economically important traits in reindeer. A panel of such marker genes will be critical in monitoring wild reindeer populations and using the genetic potential of domestic animals more effectively. Application of this marker panel will significantly reduce the time spent on the selection process to improve meat performance in the course of reindeer breeding. The results reported here will be developed further to clarify the localization of polymorphisms in the reindeer genome and their use for the purpose of effective restoration of wild reindeer populations. Subsequent selection for the purposes of domestic breeding can then ensue.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes15121629/s1, Supplementary Information S1: Raw genotyping data, calculation of allele frequencies, and construction of frequency diagrams; Supplementary Information S2: Sequence alignments for the GHR (a) and GH (b) genes.

Author Contributions

Conceptualization: N.V.D.; M.N.R.; data curation: A.A.K.; V.V.G.; formal analysis: Y.S.S.; M.N.R.; funding acquisition: N.V.D.; investigation: N.V.D.; methodology: A.A.K.; Y.S.S.; M.N.R.; project administration: M.N.R.; resources: A.A.K.; software: Y.S.S.; M.N.R.; supervision: D.K.G.; validation: Y.S.S.; visualization: A.A.K.; Y.S.S.; N.V.D.; V.V.G.; M.N.R.; writing–original draft: N.V.D.; M.N.R.; writing–review & editing: M.N.R.; D.K.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Ministry of Science and Higher Education of the Russian Federation (State Assignment Program No. 124020200114-7).

Institutional Review Board Statement

The principles and requirements of laboratory animal care were followed and all appropriate procedures were observed according to the ethical guidelines of the L. K. Ernst Federal Research Center for Animal Husbandry. The ethical review protocol was approved by the Commission on the Ethics of Animal Experiments of the L.K. Ernst Federal Research Center for Animal Husbandry (Protocol No, 2020/2) in compliance with the Law of the Russian Federation on Veterinary Medicine No. 4979-1 (dated 14 May 1993).

Informed Consent Statement

Not applicable.

Data Availability Statement

The data contributions presented in this study are included in the article and Supplementary Materials. The raw sequencing data presented in the study is openly available in GenBank at: https://www.ncbi.nlm.nih.gov/genbank/ (accessed on 27 November 2024).

Acknowledgments

We are grateful to Elena V. Nikitkina for assistance in obtaining reindeer samples.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Gunn, A.; Russell, D. Update on the global status of wild reindeer and caribou. Deer Spec. Group Newsl. 2022, 33, 14–29. Available online: https://www.deerspecialistgroup.org/wp-content/uploads/2022/04/DSGNews33.pdf (accessed on 27 November 2024).
  2. Tryland, M.; Ravolainen, V.; Pedersen, Å.Ø. Climate change: Potential impacts on pasture resources, health and diseases of reindeer and caribou. In Reindeer and Caribou; Tryland, M., Kutz, S., Eds.; CRC Press: Boca Raton, FL, USA, 2018; pp. 493–514. [Google Scholar] [CrossRef]
  3. Dance, M. Genetic Legacies of Past Climate Change on Arctic Species: How Past Responses Shape Future Impacts. Ph.D. Dissertation, University of Oxford, Oxford, UK, 2023. Available online: https://ora.ox.ac.uk/objects/uuid:7e2e2273-73d8-4b2e-bc5a-72430830ebf6 (accessed on 27 November 2024).
  4. Mallory, C.D.; Boyce, M.S. Observed and predicted effects of climate change on Arctic caribou and reindeer. Environ. Rev. 2018, 26, 13–25. [Google Scholar] [CrossRef]
  5. Tahmin, K.K. Parasitic Infection Risk for the Svalbard Reindeer (Rangifer tarandus platyrhynchus) in Relation to Temperature, Host Density, and Grazing Behaviors. Master’s Thesis, Norwegian University of Life Sciences, Ås, Norway, 2023. Available online: https://nmbu.brage.unit.no/nmbu-xmlui/handle/11250/3148260 (accessed on 27 November 2024).
  6. Mustonen, T. Wild reindeer as a keystone cultural and ecological species in the Eurasian North. Glob. Change Biol. 2022, 28, 4225–4228. [Google Scholar] [CrossRef] [PubMed]
  7. Holand, Ø.; Mizin, I.; Weladji, R.B. Reindeer Rangifer tarandus (Linnaeus, 1758). In Handbook of the Mammals of Europe; Hackländer, K., Zachos, F.E., Eds.; Springer Nature: Cham, Switzerland, 2022; pp. 1–30. [Google Scholar] [CrossRef]
  8. Mitrofanova, O.V.; Dementieva, N.V.; Tyshchenko, V.I.; Krutikova, A.A.; Goncharov, V.V. Assessment of genetic polymorphisms of several populations reindeer (Rangifer tarandus). Genet. I Razved. Zivotn. [Anim. Genet. Breed.] 2017, 1, 49–52. Available online: https://www.vniigenjournal.ru/jour/article/view/61/46 (accessed on 27 November 2024). (In Russian with English summary).
  9. Kharzinova, V.R.; Dotsev, A.V.; Deniskova, T.E.; Solovieva, A.D.; Fedorov, V.I.; Layshev, K.A.; Romanenko, T.M.; Okhlopkov, I.M.; Wimmers, K.; Reyer, H.; et al. Genetic diversity and population structure of domestic and wild reindeer (Rangifer tarandus L. 1758): A novel approach using BovineHD BeadChip. PLoS ONE 2018, 13, e0207944. [Google Scholar] [CrossRef] [PubMed]
  10. Kholodova, M.V.; Kolpashchikov, L.A.; Kuznetsova, M.V.; Baranova, A.I. Genetic diversity of wild reindeer (Rangifer tarandus) of Taimyr: Analysis of polymorphism of the control region of mitochondrial DNA. Biol. Bull. 2011, 38, 42–49. [Google Scholar] [CrossRef]
  11. Klokov, K. Reindeer husbandry in Russia. Int. J. Entrep. Small Bus. 2007, 4, 726–784. [Google Scholar] [CrossRef]
  12. Yuzhakov, A.A.; Romanenko, T.M.; Layshev, K.A. Phenogeographic variability of the Nenets reindeer breed. Izv. St. Peterbg. Gos. Agrar. Univ. [Izv. St. Petersburg State Agrar. Univ.] 2017, 47, 115–122. Available online: http://archive.today/2024.12.14-141815/https://elibrary.ru/item.asp?id=29757902 (accessed on 11 December 2024). (In Russian).
  13. Røed, K.H.; Kvie, K.S.; Losey, R.J.; Kosintsev, P.A.; Hufthammer, A.K.; Dwyer, M.J.; Goncharov, V.; Klokov, K.B.; Arzyutov, D.V.; Plekhanov, A.; et al. Temporal and structural genetic variation in reindeer (Rangifer tarandus) associated with the pastoral transition in Northwestern Siberia. Ecol. Evol. 2020, 10, 9060–9072. [Google Scholar] [CrossRef]
  14. Davydov, A.V.; Morgunov, N.A.; Chugreev, M.K.; Tkacheva, I.S. Reindeer of the taiga zone of Western Siberia. Vestn. APK Verhn. [Her. Agroindustrial Complex Up. Volga Reg.] 2022, 3, 10–21, (In Russian with English summary). [Google Scholar] [CrossRef]
  15. Davydov, A.V.; Morgunov, N.A.; Chugreev, M.K.; Tkacheva, I.S. Reindeer of the taiga zone of Eastern Siberia. Vestn. APK Verhn. [Her. Agroindustrial Complex Up. Volga Reg.] 2022, 4, 74–87, (In Russian with English summary). [Google Scholar] [CrossRef]
  16. Pokharel, K.; Weldenegodguad, M.; Dudeck, S.; Honkatukia, M.; Lindeberg, H.; Mazzullo, N.; Paasivaara, A.; Peippo, J.; Soppela, P.; Stammler, F.; et al. Whole-genome sequencing provides novel insights into the evolutionary history and genetic adaptation of reindeer populations in northern Eurasia. Sci. Rep. 2023, 13, 23019. [Google Scholar] [CrossRef] [PubMed]
  17. Li, Z.; Lin, Z.; Ba, H.; Chen, L.; Yang, Y.; Wang, K.; Qiu, Q.; Wang, W.; Li, G. Draft genome of the reindeer (Rangifer tarandus). Gigascience 2017, 6, gix102. [Google Scholar] [CrossRef] [PubMed]
  18. Ponomareva, E.S.; Yildirim, E.A.; Filippova, V.A.; Ilina, L.A.; Dubrowin, A.V.; Laptev, G.Y.; Kalitkina, K.A.; Dunyashev, T.P.; Tiurina, D.G. Comparison of the composition and metabolic potential of the reindeer’s rumen microbiome in the Yamal-Nenets and Nenets autonomous district of the Russian Arctic. Acta Biomed. Sci. 2022, 7, 30–37, (In Russian with English summary). [Google Scholar] [CrossRef]
  19. Hold, K.; Lord, E.; Brealey, J.C.; Le Moullec, M.; Bieker, V.C.; Ellegaard, M.R.; Rasmussen, J.A.; Kellner, F.L.; Guschanski, K.; Yannic, G.; et al. Ancient reindeer mitogenomes reveal island-hopping colonisation of the Arctic archipelagos. Sci. Rep. 2024, 14, 4143. [Google Scholar] [CrossRef]
  20. NCBI. Genome Assembly mRanTar1.h1.1. Sequence ID: GCA_949782905.1.; National Center for Biotechnology Information, National Library of Medicine: Bethesda, MD, USA, 2023. Available online: https://ncbi.nlm.nih.gov/datasets/genome/GCA_949782905.1/ (accessed on 27 November 2024).
  21. NCBI. Rangifer tarandus Growth Hormone Receptor (GHR) Gene, Exon 10 and Partial cds. Sequence ID: DQ062724.1; National Center for Biotechnology Information, National Library of Medicine: Bethesda, MD, USA, 2016. Available online: https://www.ncbi.nlm.nih.gov/nuccore/DQ062724.1 (accessed on 27 November 2024).
  22. Varvio, S.L.; Iso-Touru, T.; Kantanen, J.; Viitala, S.; Tapio, I.; Mäki-Tanila, A.; Zerabruk, M.; Vilkki, J. Molecular anatomy of the cytoplasmic domain of bovine growth hormone receptor, a quantitative trait locus. Proc. R. Soc. B Biol. Sci. 2008, 275, 1525–1534. [Google Scholar] [CrossRef]
  23. Krutikova, A.; Dementieva, N.; Mitrofanova, O.; Nikitkina, E. Polymorphic variants of the locus of the growth hormone gene and linkage disequilibrium in the populations of wild and domestic reindeer. Genet. I Razved. Zivotn. [Anim. Genet. Breed.] 2018, 1, 11–16, (In Russian with English summary). [Google Scholar] [CrossRef]
  24. Krutikova, A.; Barkova, O. Analysis of the ligand-dependent nuclear receptor gene of corepressor type polymorphism in reindeer. Meždunarodnyj Vestn. Vet. [Int. Bull. Vet. Med.] 2020, 4, 111–115, (In Russian with English summary). [Google Scholar] [CrossRef]
  25. Krutikova, A.A.; Peglivanyan, G.K. Analysis of BMP2 gene polymorphism of bone morphogenetic protein-2 in reindeer. Meždunarodnyj Vestn. Vet. [Int. Bull. Vet. Med.] 2023, 2, 161–170, (In Russian with English summary). [Google Scholar] [CrossRef]
  26. Tamura, K.; Stecher, G.; Peterson, D.; Filipski, A.; Kumar, S. MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol. Biol. Evol. 2013, 30, 2725–2729. [Google Scholar] [CrossRef]
  27. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Mol. Biol. Evol. 2018, 35, 1547–1549. [Google Scholar] [CrossRef] [PubMed]
  28. MEGA: Molecular Evolutionary Genetics Analysis. Available online: https://www.megasoftware.net/ (accessed on 27 November 2024).
  29. NCBI. Rangifer tarandus. Available online: https://www.ncbi.nlm.nih.gov/search/all/?term=Rangifer%20tarandus%20 (accessed on 27 November 2024).
  30. Zenkova, D.; Kamenev, V.; Sablina, R.; Artyomov, M.; Sergushichev, A. Phantasus: Visual and Interactive Gene Expression Analysis, Bioconductor version 3.20; Fred Hutchinson Cancer Center: Seattle, WA, USA, 2018. [Google Scholar] [CrossRef]
  31. Nei, M. Estimation of average heterozygosity and genetic distance from small number of individuals. Genetics 1978, 89, 583–590. [Google Scholar] [CrossRef] [PubMed]
  32. Kalinowski, S.T. Counting alleles with rarefaction: Private alleles and hierarchical sampling designs. Conserv. Genet. 2004, 5, 539–543. [Google Scholar] [CrossRef]
  33. Keenan, K.; McGinnity, P.; Cross, T.F.; Crozier, W.W.; Prodohl, P.A. diveRsity: An R package for the estimation of population genetics parameters and their associated errors. Methods Ecol. Evol. 2013, 4, 782–788. [Google Scholar] [CrossRef]
  34. Tanihara, F.; Hirata, M.; Namula, Z.; Wittayarat, M.; Do, L.T.K.; Lin, Q.; Takebayashi, K.; Hara, H.; Nagahara, M.; Otoi, T. GHR-mutant pig derived from domestic pig and microminipig hybrid zygotes using CRISPR/Cas9 system. Mol. Biol. Rep. 2023, 50, 5049–5057. [Google Scholar] [CrossRef]
  35. Wallis, M. Mammalian genome projects reveal new growth hormone (GH) sequences: Characterization of the GH-encoding genes of armadillo (Dasypus novemcinctus), hedgehog (Erinaceus europaeus), bat (Myotis lucifugus), hyrax (Procavia capensis), shrew (Sorex araneus), ground squirrel (Spermophilus tridecemlineatus), elephant (Loxodonta africana), cat (Felis catus) and opossum (Monodelphis domestica). Gen. Comp. Endocrinol. 2008, 155, 271–279. [Google Scholar] [CrossRef]
  36. Menzies, B.R.; Pask, A.J.; Renfree, M.B. Placental expression of pituitary hormones is an ancestral feature of therian mammals. EvoDevo 2011, 2, 16. [Google Scholar] [CrossRef]
  37. Lioupis, A.; Wallis, O.C.; Wallis, M. Cloning and characterisation of the gene encoding red deer (Cervus elaphus) growth hormone: Implications for the molecular evolution of growth hormone in artiodactyls. J. Mol. Endocrinol. 1997, 19, 259–266. [Google Scholar] [CrossRef]
  38. Majeres, L.E.; Dilger, A.C.; Shike, D.W.; McCann, J.C.; Beever, J.E. Defining a haplotype encompassing the LCORL-NCAPG Locus associated with increased lean growth in beef cattle. Genes 2024, 15, 576. [Google Scholar] [CrossRef]
  39. Larkina, T.A.; Barkova, O.Y.; Peglivanyan, G.K.; Mitrofanova, O.V.; Dementieva, N.V.; Stanishevskaya, O.I.; Vakhrameev, A.B.; Makarova, A.V.; Shcherbakov, Y.S.; Pozovnikova, M.V.; et al. Evolutionary subdivision of domestic chickens: Implications for local breeds as assessed by phenotype and genotype in comparison to commercial and fancy breeds. Agriculture 2021, 11, 914. [Google Scholar] [CrossRef]
  40. Larkina, T.A.; Romanov, M.N.; Barkova, O.Y.; Peglivanyan, G.K.; Mitrofanova, O.V.; Dementieva, N.V.; Stanishevskaya, O.I.; Vakhrameev, A.B.; Makarova, A.V.; Shcherbakov, Y.S.; et al. Genetic Variation of the NCAPG-LCORL Locus in Chickens of Local Breeds Based on SNP Genotyping Data. In Molecular Genetic Technologies for Analysis of Gene Expression Related to Animal Productivity and Disease Resistance, Materials of the 3rd International Scientific and Practical Conference, Moscow, Russia, September 30, 2021; Pozyabin, S.V., Kochish, I.I., Romanov, M.N., Eds.; Ministry of Agriculture of the Russian Federation; Federal State Budgetary Educational Institution of Higher Education “Moscow State Academy of Veterinary Medicine and Biotechnology—MVA named after K.I. Scriabin”; Sel’skokhozyaistvennye Tekhnologii: Moscow, Russia, 2021; pp. 133–146, (In Russian with English summary). [Google Scholar] [CrossRef]
  41. Feng, J.Q.; Chen, D.; Ghosh-Choudhury, N.; Esparza, J.; Mundy, G.R.; Harris, S.E. Bone morphogenetic protein 2 transcripts in rapidly developing deer antler tissue contain an extended 5’ non-coding region arising from a distal promoter. Biochim. Biophys. Acta 1997, 1350, 47–52. [Google Scholar] [CrossRef] [PubMed]
  42. Davydov, A.V.; Mizin, I.A.; Sipko, T.P.; Gruzdev, A.R. Reindeer of the Arctic islands of Russia. Vestn. Ohotovedeniâ [Bull. Game Sci.] 2017, 14, 253–271. Available online: http://archive.today/2024.12.14-142914/https://elibrary.ru/item.asp?id=32501476 (accessed on 11 December 2024). (In Russian).
  43. Glazov, P.M.; Loshchagina, Y.A.; Shmatova, A.G.; Gnedenko, A.E.; Tishkov, A.A. Kolguev Island as an object for monitoring the biota of the western sector of the Russian Arctic. Arktika Èkologiâ I Èkonomika [Arctic Ecol. Econ.] 2024, 14, 261–273, (In Russian with English summary). [Google Scholar] [CrossRef]
  44. Wiener, P.; Wilkinson, S. Deciphering the genetic basis of animal domestication. Proc. R. Soc. B Biol. Sci. 2011, 278, 3161–3170. [Google Scholar] [CrossRef]
  45. Wang, G.D.; Xie, H.B.; Peng, M.S.; Irwin, D.; Zhang, Y.P. Domestication genomics: Evidence from animals. Annu. Rev. Anim. Biosci. 2014, 2, 65–84. [Google Scholar] [CrossRef]
  46. Frantz, L.A.; Bradley, D.G.; Larson, G.; Orlando, L. Animal domestication in the era of ancient genomics. Nat. Rev. Genet. 2020, 21, 449–460. [Google Scholar] [CrossRef]
  47. Romanov, M.N.; Sölkner, J.; Zinovieva, N.A.; Wimmers, K.; Weigend, S. Editorial: Traditional and up-to-date genomic insights into domestic animal diversity. Front. Genet. 2023, 13, 1117708. [Google Scholar] [CrossRef]
  48. Seebacher, F. The evolution of metabolic regulation in animals. Comp. Biochem. Physiol. B Biochem. Mol. Biol. 2018, 224, 195–203. [Google Scholar] [CrossRef]
  49. Thompson, S.; Romanov, M.N.; Griffin, D.K. Study of animal myosins in a comparative genomic aspect. In Molecular Genetic Technologies for Analysis of Gene Expression Related to Animal Productivity and Disease Resistance, Materials of the 3rd International Scientific and Practical Conference, Moscow, Russia, September 30, 2021; Pozyabin, S.V., Kochish, I.I., Romanov, M.N., Eds.; Ministry of Agriculture of the Russian Federation; Federal State Budgetary Educational Institution of Higher Education “Moscow State Academy of Veterinary Medicine and Biotechnology—MVA named after K.I. Scriabin”; Sel’skokhozyaistvennye tekhnologii: Moscow, Russia, 2021; pp. 444–449, (In Russian with English summary). [Google Scholar] [CrossRef]
  50. Rejduch, B. Genes associated with production and health in farm animals. J. Cent. Eur. Agric. 2008, 9, 829–835. Available online: https://jcea.agr.hr/en/issues/article/682 (accessed on 27 November 2024).
  51. Pritchard, T.; Coffey, M.; Mrode, R.; Wall, E. Genetic parameters for production, health, fertility and longevity traits in dairy cows. Animal 2013, 7, 34–46. [Google Scholar] [CrossRef]
  52. Laville, E.; Bouix, J.; Sayd, T.; Bibé, B.; Elsen, J.M.; Larzul, C.; Eychenne, F.; Marcq, F.; Georges, M. Effects of a quantitative trait locus for muscle hypertrophy from Belgian Texel sheep on carcass conformation and muscularity. J. Anim. Sci. 2004, 82, 3128–3137. [Google Scholar] [CrossRef] [PubMed]
  53. Cockett, N.E.; Smit, M.A.; Bidwell, C.A.; Segers, K.; Hadfield, T.L.; Snowder, G.D.; Georges, M.; Charlier, C. The callipyge mutation and other genes that affect muscle hypertrophy in sheep. Genet. Sel. Evol. 2005, 37 (Suppl. 1), S65. [Google Scholar] [CrossRef] [PubMed]
  54. Stinckens, A.; Van den Maagdenberg, K.; Luyten, T.; Georges, M.; De Smet, S.; Buys, N. The RYR1 g.1843C>T mutation is associated with the effect of the IGF2 intron3-g.3072G>A mutation on muscle hypertrophy. Anim. Genet. 2007, 38, 67–71. [Google Scholar] [CrossRef] [PubMed]
  55. Freeman, L.M.; Rush, J.E.; Stern, J.A.; Huggins, G.S.; Maron, M.S. Feline hypertrophic cardiomyopathy: A spontaneous large animal model of human HCM. Cardiovasc. Res. 2017, 8, 139–142. [Google Scholar] [CrossRef]
  56. Aiello, D.; Patel, K.; Lasagna, E. The myostatin gene: An overview of mechanisms of action and its relevance to livestock animals. Anim. Genet. 2018, 49, 505–519. [Google Scholar] [CrossRef]
  57. Moiseyeva, I.G.; Nikiforov, A.A.; Romanov, M.N.; Balanovsky, O.P. Dynamics of domestic animal diversity as influenced by anthropogenic factor. In Integration of Archaeological and Ethnographic Studies: Collection of Scientific Papers; Korusenko, M.A., Tikhonov, S.S., Tomilov, N.A., Eds.; Nauka-Omsk: Omsk, Russia, 2003; pp. 284–287. Available online: https://kar.kent.ac.uk/46429/ (accessed on 27 November 2024).
  58. Druet, T.; Ahariz, N.; Cambisano, N.; Tamma, N.; Michaux, C.; Coppieters, W.; Charlier, C.; Georges, M. Selection in action: Dissecting the molecular underpinnings of the increasing muscle mass of Belgian Blue Cattle. BMC Genom. 2014, 15, 796. [Google Scholar] [CrossRef]
  59. Kristensen, T.N.; Hoffmann, A.A.; Pertoldi, C.; Stronen, A.V. What can livestock breeders learn from conservation genetics and vice versa? Front. Genet. 2015, 6, 38. [Google Scholar] [CrossRef]
  60. Georges, M.; Charlier, C.; Hayes, B. Harnessing genomic information for livestock improvement. Nat. Rev. Genet. 2019, 20, 135–156. [Google Scholar] [CrossRef]
  61. Romanov, M.N.; Kochish, I.I.; Sharafetdinov, G.R.; Myasnikova, O.V.; Nikonov, I.N.; Selina, M.V.; Surai, P.F. Towards Advanced Biotechnological Developments to Realize the Genetic Potential of Egg-type Poultry. In Molecular Genetic Technologies for Analysis of Gene Expression Related to Animal Productivity and Disease Resistance, Materials of the 3rd International Scientific and Practical Conference, Moscow, 29 September 2021; Sel’skokhozyaistvennye tekhnologii: Moscow, Russia, 2021; pp. 40–51, (In Russian with English summary). [Google Scholar] [CrossRef]
  62. Røed, K.H.; Flagstad, Ø.; Nieminen, M.; Holand, Ø.; Dwyer, M.J.; Røv, N.; Vilà, C. Genetic analyses reveal independent domestication origins of Eurasian reindeer. Proc. R. Soc. B Biol. Sci. 2008, 275, 1849–1855. [Google Scholar] [CrossRef]
  63. Røed, K.H.; Flagstad, Ø.; Bjørnstad, G.; Hufthammer, A.K. Elucidating the ancestry of domestic reindeer from ancient DNA approaches. Quat. Int. 2011, 238, 83–88. [Google Scholar] [CrossRef]
  64. Røed, K.H.; Bjørklund, I.; Olsen, B.J. From wild to domestic reindeer—Genetic evidence of a non-native origin of reindeer pastoralism in northern Fennoscandia. J. Archaeol. Sci. Rep. 2018, 19, 279–286. [Google Scholar] [CrossRef]
  65. Røed, K.H.; Kvie, K.S.; Bårdsen, B.J. Genetic structure and origin of semi-domesticated reindeer. In Reindeer Husbandry and Global Environmental Change: Pastoralism in Fennoscandia; Horstkotte, T., Holand, Ø., Kumpula, J., Moen, J., Eds.; Routledge: London, UK, 2022; pp. 48–60. [Google Scholar] [CrossRef]
  66. Sampels, S.; Pickova, J.; Wiklund, E. Influence of production system, age an sex on carcass parameters and some biochemical meat quality characteristics of reindeer (Rangifer tarandus tarandus L.). Rangifer 2005, 25, 85–96. [Google Scholar] [CrossRef]
  67. Wiklund, E.; Farouk, M.; Finstad, G. Venison: Meat from red deer (Cervus elaphus) and reindeer (Rangifer tarandus tarandus). Anim. Front. 2014, 4, 55–61. [Google Scholar] [CrossRef]
  68. Plemyashov, K.V.; Smaragdov, M.G.; Romanov, M.N. Molecular Genetic Polymorphism in Animal Populations and Its Application in Intensive Breeding of Dairy Cattle—A Review. In Molecular Genetic Technologies for Analysis of Gene Expression Related to Animal Productivity and Disease Resistance, Materials of the 3rd International Scientific and Practical Conference, Moscow, Russia, September 30, 2021; Pozyabin, S.V., Kochish, I.I., Romanov, M.N., Eds.; Ministry of Agriculture of the Russian Federation; Federal State Budgetary Educational Institution of Higher Education “Moscow State Academy of Veterinary Medicine and Biotechnology—MVA named after K.I. Scriabin”; Sel’skokhozyaistvennye tekhnologii: Moscow, Russia, 2021; pp. 368–378, (In Russian with English summary). [Google Scholar] [CrossRef]
  69. Konorov, E.A.; Kurbakov, K.A.; Semina, M.T.; Stolpovsky, Y.A.; Layshev, K.A. Analysis of the calpastatin (CAST) and androgen receptor (AR) gene polymorphisms as biomarkers for meat quality traits in reindeer Rangifer tarandus. Russ. J. Genet. 2024, 60, 1040–1045. [Google Scholar] [CrossRef]
  70. Davydov, A.V.; Morgunov, N.A.; Chugreev, M.K.; Tkacheva, I.S. Reindeer of Taimyr. Vestn. APK Verhn. [Her. Agroindustrial Complex Up. Volga Reg.] 2023, 3, 5–20, (In Russian with English summary). [Google Scholar] [CrossRef]
Genes 15 01629 g001
Figure 1. Sampling sites of the reindeer (Rangifer tarandus) in the Far North of Russia. Populations/breeds designation: KgNen, Nenets breed, Kolguyev Island; NarNen, Nenets breed, Naryan-Mar; NoNen, Nenets breed, Nosok; TaiWild, wild reindeer, Taimyr Peninsula; SurEv, Evenk breed, Surinda.
Figure 1. Sampling sites of the reindeer (Rangifer tarandus) in the Far North of Russia. Populations/breeds designation: KgNen, Nenets breed, Kolguyev Island; NarNen, Nenets breed, Naryan-Mar; NoNen, Nenets breed, Nosok; TaiWild, wild reindeer, Taimyr Peninsula; SurEv, Evenk breed, Surinda.
Genes 15 01629 g001
Genes 15 01629 g002aGenes 15 01629 g002b
Figure 2. Reindeer (Rangifer tarandus) in the Far North of Russia: (a) Nenets breed that has a smaller body size, (b) a larger Evenk breed, (c) Nenets breed on Kolguyev Island and (d) reindeer in the Taimyr Peninsula. Credit: (a,b,d) own authors’ photographs; (c) https://commons.wikimedia.org/wiki/File:Ice-bound_on_Kolguev_-_a_chapter_in_the_exploration_of_Arctic_Europe_to_which_is_added_a_record_of_the_natural_history_of_the_island_(1895)_(14779560514).jpg (accessed on 27 November 2024) (by J.T. Nettleship, 1895; no known copyright).
Figure 2. Reindeer (Rangifer tarandus) in the Far North of Russia: (a) Nenets breed that has a smaller body size, (b) a larger Evenk breed, (c) Nenets breed on Kolguyev Island and (d) reindeer in the Taimyr Peninsula. Credit: (a,b,d) own authors’ photographs; (c) https://commons.wikimedia.org/wiki/File:Ice-bound_on_Kolguev_-_a_chapter_in_the_exploration_of_Arctic_Europe_to_which_is_added_a_record_of_the_natural_history_of_the_island_(1895)_(14779560514).jpg (accessed on 27 November 2024) (by J.T. Nettleship, 1895; no known copyright).
Genes 15 01629 g002aGenes 15 01629 g002b
Genes 15 01629 g003
Figure 3. Occurrence frequencies of four SNP alleles found in the GH gene [23]. Populations/breeds designation: TaiWild, wild reindeer, Taimyr Peninsula; SurEv, Evenk breed, Surinda; NoNen, Nenets breed, Nosok; NarNen, Nenets breed, Naryan-Mar; KgNen, Nenets breed, Kolguyev Island.
Figure 3. Occurrence frequencies of four SNP alleles found in the GH gene [23]. Populations/breeds designation: TaiWild, wild reindeer, Taimyr Peninsula; SurEv, Evenk breed, Surinda; NoNen, Nenets breed, Nosok; NarNen, Nenets breed, Naryan-Mar; KgNen, Nenets breed, Kolguyev Island.
Genes 15 01629 g003
Genes 15 01629 g004
Figure 4. Hierarchical clustering dendrograms showing the genetic diversity differences between the studied reindeer populations/breeds. Hierarchical clustering trees were built using SNP genotyping data (a) at GHR (present study) and GH [23] loci, and (b) at LCORL (present study and [24]) and BMP2 [25] loci. Populations/breeds designation: (a) SurEv, Evenk breed, Surinda; NoNen, Nenets breed, Nosok; KgNen, Nenets breed, Kolguyev Island; NarNen, Nenets breed, Naryan-Mar; TaiWild, wild reindeer, Taimyr Peninsula; (b) Nenets, Nenets breed; Wild, wild reindeer, Taimyr Peninsula; Evenk, Evenk breed.
Figure 4. Hierarchical clustering dendrograms showing the genetic diversity differences between the studied reindeer populations/breeds. Hierarchical clustering trees were built using SNP genotyping data (a) at GHR (present study) and GH [23] loci, and (b) at LCORL (present study and [24]) and BMP2 [25] loci. Populations/breeds designation: (a) SurEv, Evenk breed, Surinda; NoNen, Nenets breed, Nosok; KgNen, Nenets breed, Kolguyev Island; NarNen, Nenets breed, Naryan-Mar; TaiWild, wild reindeer, Taimyr Peninsula; (b) Nenets, Nenets breed; Wild, wild reindeer, Taimyr Peninsula; Evenk, Evenk breed.
Genes 15 01629 g004
Genes 15 01629 g005
Figure 5. Occurrence frequencies of eight SNP alleles observed in the LCORL gene in domestics (of the Evenk and Nenets breeds) and the wild reindeer (present study and [24]).
Figure 5. Occurrence frequencies of eight SNP alleles observed in the LCORL gene in domestics (of the Evenk and Nenets breeds) and the wild reindeer (present study and [24]).
Genes 15 01629 g005
Genes 15 01629 g006
Figure 6. Occurrence frequency of 11 SNP alleles identified in the BMP2 gene in domestics (of the Evenk and Nenets breeds) and the wild reindeer [25].
Figure 6. Occurrence frequency of 11 SNP alleles identified in the BMP2 gene in domestics (of the Evenk and Nenets breeds) and the wild reindeer [25].
Genes 15 01629 g006
Genes 15 01629 g007
Figure 7. Genetic divergence plots based on occurrence frequencies of SNP alleles. Hierarchical clustering trees were built using SNP allele frequencies identified (a) at GHR (present study) and GH [23] loci, and (b) at LCORL (present study and [24]) and BMP2 [25] loci. Populations/breeds designation: (a) KgNen, Nenets breed, Kolguyev Island; NarNen, Nenets breed, Naryan-Mar; NoNen, Nenets breed, Nosok; SurEv, Evenk breed, Surinda; TaiWild, wild reindeer, Taimyr Peninsula; (b) Wild, wild reindeer, Taimyr Peninsula; Nenets, Nenets breed; Evenk, Evenk breed.
Figure 7. Genetic divergence plots based on occurrence frequencies of SNP alleles. Hierarchical clustering trees were built using SNP allele frequencies identified (a) at GHR (present study) and GH [23] loci, and (b) at LCORL (present study and [24]) and BMP2 [25] loci. Populations/breeds designation: (a) KgNen, Nenets breed, Kolguyev Island; NarNen, Nenets breed, Naryan-Mar; NoNen, Nenets breed, Nosok; SurEv, Evenk breed, Surinda; TaiWild, wild reindeer, Taimyr Peninsula; (b) Wild, wild reindeer, Taimyr Peninsula; Nenets, Nenets breed; Evenk, Evenk breed.
Genes 15 01629 g007
Table 1. PCR primers for analyzing the GHR, GH, LCORL and BMP2 gene fragments.
Table 1. PCR primers for analyzing the GHR, GH, LCORL and BMP2 gene fragments.
Gene/LocusPrimers (F, Forward; R, Reverse)Fragment Size, bp
GHRExon 10
F: TTTGTTAAATCAATTGTTGTGAG
R: GTCGCATTGAGTACAAGGC
844
GHExons 2 and 3
F: GGAGAAGCAGAAGGCAACC
R: CTCTGCCTGCCCTGGACT
382
LCORLExon 7 regions
LCORL-5F: CATCCAAGAAATTGATAGAA
R: TTTCACAACCTGGGGACCTA		682, 646
LCORL-9F: TTTTGAGTAAGACTGAGGGA
R: GTGGTCTTCCATGGTGGTCT		657
LCORL-10F: TCTTAGCAAACTGAACAAAA
R: GCCAAGAAATTAGATTGTCCA		640
BMP2Regions of exons 1 and 2
BMP2-1 (exon 1)F: TCGCGGATTACTAGGGACTCA
R: GCGCAAGTTATTCTCCCTGC		705
BMP2-1 (exon 2)F: GCGCTGTGTGTTTGGGTTAG
R: AAAGCCAGGTTCGGAAAGGT		872
Table 2. Occurrence frequencies of SNP alleles identified in the GHR gene (present study).
Table 2. Occurrence frequencies of SNP alleles identified in the GHR gene (present study).
SNPs and AllelesPopulations 1
KgNenNarNenNoNenSurEvTaiWild
GHR1
A0.550.590.650.580.80
G0.450.410.350.420.20
GHR2
C0.640.550.850.830.70
T0.360.450.150.170.30
GHR3
C0.410.410.200.080.30
T0.590.590.800.920.70
1 Populations/breeds designation: TaiWild, wild reindeer, Taimyr Peninsula; SurEv, Evenk breed, Surinda; NoNen, Nenets breed, Nosok; NarNen, Nenets breed, Naryan-Mar; KgNen, Nenets breed, Kolguyev Island.
Table 3. Summary of genetic diversity statistics 1 (M ± SE) calculated in the studied reindeer populations based on SNP genotypes identified in the GHR (present study) and GH [23] genes.
Table 3. Summary of genetic diversity statistics 1 (M ± SE) calculated in the studied reindeer populations based on SNP genotypes identified in the GHR (present study) and GH [23] genes.
PopulationsHOHEUHEAR
KgNen0.26 ± 0.050.31 ± 0.070.32 ± 0.071.77 ± 0.09
NarNen0.44 ± 0.160.35 ± 0.090.37 ± 0.091.71 ± 0.18
NoNen0.37 ± 0.170.29 ± 0.080.30 ± 0.091.65 ± 0.17
SurEv0.28 ± 0.140.27 ± 0.080.29 ± 0.091.60 ± 0.17
TaiWild0.23 ± 0.020.41 ± 0.020.44 ± 0.031.95 ± 0.01
RanksM
SurEv31111.5
NoNen42222.5
KgNen23343
NarNen54434
TaiWild15554
1 M, mean value; SE, standard error; HO, observed heterozygosity; HE, expected heterozygosity; UHE, unbiased expected heterozygosity; AR, rarefied allelic richness.
Table 4. Summary of genetic diversity statistics 1 (M ± SE) computed for the studied wild reindeer and domestic breeds based on SNP genotypes identified in the LCORL (present study and [24]) and BMP2 [25] genes.
Table 4. Summary of genetic diversity statistics 1 (M ± SE) computed for the studied wild reindeer and domestic breeds based on SNP genotypes identified in the LCORL (present study and [24]) and BMP2 [25] genes.
PopulationsHOHEUHEAR
Wild0.32 ± 0.090.19 ± 0.050.19 ± 0.051.47 ± 0.12
Nenets0.16 ± 0.080.11 ± 0.050.11 ± 0.051.29 ± 0.11
Evenk0.28 ± 0.080.24 ± 0.050.24 ± 0.051.64 ± 0.12
RanksM
Wild32222.25
Nenets11111
Evenk23332.75
1 M, mean value; SE, standard error; HO, observed heterozygosity; HE, expected heterozygosity; UHE, unbiased expected heterozygosity; AR, rarefied allelic richness.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Krutikova, A.A.; Dementieva, N.V.; Shcherbakov, Y.S.; Goncharov, V.V.; Griffin, D.K.; Romanov, M.N. Polymorphism of Genes Potentially Affecting Growth and Body Size Suggests Genetic Divergence in Wild and Domestic Reindeer (Rangifer tarandus) Populations. Genes 2024, 15, 1629. https://doi.org/10.3390/genes15121629

AMA Style

Krutikova AA, Dementieva NV, Shcherbakov YS, Goncharov VV, Griffin DK, Romanov MN. Polymorphism of Genes Potentially Affecting Growth and Body Size Suggests Genetic Divergence in Wild and Domestic Reindeer (Rangifer tarandus) Populations. Genes. 2024; 15(12):1629. https://doi.org/10.3390/genes15121629

Chicago/Turabian Style

Krutikova, Anna A., Natalia V. Dementieva, Yuri S. Shcherbakov, Vasiliy V. Goncharov, Darren K. Griffin, and Michael N. Romanov. 2024. "Polymorphism of Genes Potentially Affecting Growth and Body Size Suggests Genetic Divergence in Wild and Domestic Reindeer (Rangifer tarandus) Populations" Genes 15, no. 12: 1629. https://doi.org/10.3390/genes15121629

APA Style

Krutikova, A. A., Dementieva, N. V., Shcherbakov, Y. S., Goncharov, V. V., Griffin, D. K., & Romanov, M. N. (2024). Polymorphism of Genes Potentially Affecting Growth and Body Size Suggests Genetic Divergence in Wild and Domestic Reindeer (Rangifer tarandus) Populations. Genes, 15(12), 1629. https://doi.org/10.3390/genes15121629

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop