doi: 10.15389/agrobiology.2020.2.285eng
UDC: 636.393.9:575.174.5:577.21
During the research, the equipment of the Center for Biological Resources and Bioengineering of Agricultural Animals (Ernst Federal Science Center for Animal Husbandry) was used.
Supported financially by the Russian Foundation for Basic Research, project No. 18-316-20006
THE GENOMIC ARCHITECTURE OF THE RUSSIAN POPULATION OF SAANEN GOATS IN COMPARISON WITH WORLDWIDE SAANENGENE POOL FROM FIVE COUNTRIES
Т.Е. Deniskova1, А.V. Dotsev1, М.S. Fornara1, A.A. Sermyagin1, H. Reyer2, К. Wimmers2, G. Brem1, 3, N.А. Zinovieva1
1Ernst Federal Science Center for Animal Husbandry,60, pos. Dubrovitsy, Podolsk District, Moscow Province, 142132 Russia, e-mail horarka@yandex.ru (✉ corresponding author), asnd@mail.ru, margaretfornara@gmail.com, alex_sermyagin85@mail.ru, n_zinovieva@mail.ru;
2Institute of Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Mecklenburg-Vorpommern, 18196 Dummerstorf, Germany, e-mail reyer@fbn-dummerstorf.de, wimmers@fbn-dummerstorf.de;
3Institut für Tierzucht und Genetik, University of Veterinary Medicine (VMU), Veterinärplatz, A-1210, Vienna, Austria, e-mail gottfried.brem@agrobiogen.de
ORCID:
Deniskova T.E. orcid.org/0000-0002-5809-1262
Reyer H. orcid.org/0000-0001-6470-0434
Dotsev A.V. orcid.org/0000-0003-3418-2511
Wimmers K. orcid.org/0000-0002-9523-6790
Fornara M.S. orcid.org/0000-0002-8844-177X
Brem G. orcid.org/0000-0002-7522-0708
Sermyagin A.A. orcid.org/0000-0002-1799-601
Zinovieva N.A. orcid.org/0000-0003-4017-6863
Received February 26, 2020
The Saanen goat breed is valued for its high milk productivity and good adaptive qualities, which contributed to its worldwide distribution outside Switzerland. In Russia, the Saanen is a popular breed that had been officially recommended for breeding and had a pedigree status. Breeding in local environments as well as regional specifics of the used breeding strategies can lead to a significant change in the allele pool of breeds, and therefore, it is relevant to conduct genomic studies of national populations of world breeds to establish their current genetic status. Here, for the first time we presented the results of whole-genome analysis of the Russian population of goats of the Saanen breed in comparative aspect with the original (Switzerland) and the world gene pool of the Saanen breed, represented by four countries. The aim of our work was to assess genetic diversity and to study population structure of the Saanen goats of Russian selection in comparison with representatives of this breed from five different countries (Switzerland, Italy, France, Argentina and Tanzania) whose whole-genome SNP-profiles were obtained from the database of the AdaptMap project. The studies were conducted on 21 goats of the Saanen breed (RUS), bred in one of the Russian breeding farms, in 2019-2020. DNA was extracted from the selected ear fragments using DNA Extran-2 kits (Syntol CJSC, Russia). Genotyping was performed using a GoatSNP50 BeadChip DNA chip (Illumina, Inc., USA) containing 53347 SNPs and providing coverage of the average interval between SNPs in 40 kb. To assess the genetic diversity and to perform comparative analysis of the Russian goat population with the representatives goats of this breed from five different countries, we used SNP-profiles of the Saanen goats bred in Switzerland (SWI, n = 38), Italy (ITA, n = 22), France (FRA, n = 55), Argentina (ARG, n = 11) and Tanzania (TNZ, n = 8), which were downloaded from the publicly available digital data repository Dryad and generated in within the AdaptMap project. The Swiss population of the Saanen breed was assumed as a sample of the original gene pool. Bioinformatic processing and visualization of whole-genome genotyping data was performed in the PLINK 1.90, Admixture 1.3, SplitsTree 4.14.5 software, in R packages “diveRsity” and “pophelper”. The observed heterozygosity varied from 0.381 in SWI to 0.423 in FRA and was high in RUS (Ho = 0.418). In SWI, ITA, FRA populations the values of the inbreeding coefficient were close to zero level; RUS, ARG, and TNZ showed heterozygote deficiencies, which were 1.5%, 8.9, and 6.0%, respectively. Allelic richness was maximal in ARG, RUS, and FRA (Ar ≥ 1.979) and minimal in SWI (Ar = 1.934). The Principal component analysis and the phylogenetic tree showed a clear differentiation between the national and original populations of the Saanen breed. Analysis of population structure demonstrated the presence of the genetic component of the SWI cluster in goats from the RUS group. RUS had the smallest genetic distances with FRA (FST = 0.02; RST = 0.189) and ITA (FST = 0.023; RST = 0.215); and RUS was highly differentiated from TNZ (FST = 0.054; RST = 0.311) and SWI (FST = 0.06; RST = 0.276). Thus, different selection strategies resulted in genetic differences between the national goat populations of the Saanen breed. However, genomic components of the original gene pool are still present in the Russian goat population of the Saanen breed.
Keywords: Saanen breed, domestic goats, SNP markers, DNA chips, genetic diversity, AdaptMap.
REFERENCES
- Novopashina S.I., Sannikov M.Yu., Kizilova E.I. Sbornik nauchnukh trudov Vserossiiskogo nauchno-issledovatel'skogo instituta ovtsevodstva i kozovodstva,2017, 1(10): 225-229 (in Russ.).
- Spravochnik porod i tipov sel'skokhozyaistvennykh zhivotnykh, razvodimykh v Rossiiskoi Federatsii /Pod redaktsiei I.M. Dunina, A.G. Dankverta [Directory of breeds and types of farm animals bred in the Russian Federation. I.M. Dunin, A.G. Dankvert (eds.)]. Moscow, 2013 (in Russ.).
- Devendra S., Haenlein G.F.W. Animals that produce dairy foods | Goat breeds. In: Encyclopedia of dairy sciences (second edition). J.W. Fuquay (ed.). Academic Press, Amsterdam, 2011: 310-324 CrossRef
- Novopashina S.I., Sannikov M.Yu., Khatataev S.A., Kuz'mina T.N., Khmelevskaya G.N., Stepanova N.G., Tikhomirov A.I., Marinchenko T.E. Sostoyanie i perspektivnye napravleniya uluchsheniya geneticheskogo potentsiala melkogo rogatogo skota: nauchnyi analiticheskii obzor [Status and perspective ways for improving genetic potential of small cattle: a scientific analytical review]. Moscow, 2019 (in Russ.).
- Brito L.F., Jafarikia M., Grossi D.A., Kijas J.W., Porto-Neto L.R., Ventura R.V., Salgorzaei M., Schenkel F.S. Characterization of linkage disequilibrium, consistency of gametic phase and admixture in Australian and Canadian goats. BMC Genetics, 2015, 16: 67 CrossRef
- da Silva T.G.F., Santos G.C.L., Duarte A.M.C., Turco S.H.N., da Cruz Neto J.F., da Rosa Ferraz Jardim A.M., dos Santos T.S. Black globe temperature from meteorological data and a bioclimatic analysis of the Brazilian northeast for Saanen goats. Journal of Thermal Biology,2019, 85: 102408 CrossRef
- Zamuner F., DiGiacomo K., Cameron A.W.N., Leury B.J. Effects of month of kidding, parity number, and litter size on milk yield of commercial dairy goats in Australia. Journal of Dairy Science, 2020, 103(1): 954-964 CrossRef
- Sun Y., Wang C., Sun X., Guo M. Proteomic analysis of whey proteins in the colostrum and mature milk of Xinong Saanen goats. Journal of Dairy Science, 2020, 103(2): 1164-1174 CrossRef
- Makete G., Aiyegoro O.A., Thantsha M.S. Isolation, identification and screening of potential probiotic bacteria in milk from South African Saanen goats. Probiotics and Antimicrobial Proteins, 2017, 9(3): 246-254 CrossRef
- Gosudarstvennyi reestr selektsionnykh dostizhenii, dopushchennykh k ispol'zovaniyu. Tom 2 «Porody zhivotnykh» (ofitsial'noe izdanie) [The State register of selection achievements allowed for use. Volume 2 «Breeds of animals» (official publication)]. Moscow, 2019 (in Russ.).
- Ezhegodnik po plemennoi rabote v ovtsevodstve i kozovodstve v khozyaistvakh Rossiiskoi Federatsii (2018 god) /Pod redaktsiei T.A. Moroz [Yearbook on pedigree work in sheep and goat husbandry on the farms of the Russian Federation (2018). T.A. Moroz (ed.)]. Moscow, 2019 (in Russ.).
- Toshchev V.K., Mustafina G.N. Agrarnaya nauka, 2012, 5: 27-28 (in Russ.).
- Ajmone-Marsan P., Colli L., Han J.L., Achilli A., Lancioni H., Joost S., Crepaldi P., Pilla F., Stella A., Taberlet P., Boettcher P., Negrini R., Lenstra J.A., Italian Goat Consortium, Econogene Consortium, Globaldiv Consortium. The characterization of goat genetic diversity: towards a genomic approach. Small Ruminant Research, 2014, 121(1): 58-72 CrossRef
- Tosser-Klopp G., Bardou P., Bouchez O., Cabau C., Crooijmans R., Dong Y., Donnadieu-Tonon C., Eggen A., Heuven H.C.M., Jamli S., Jiken A.J., Klopp C., Lawley C.T., McEwan J., Martin P., Moreno C.R., Mulsant P., Nabihoudine I., Pailhoux E., Palhiere E., Rupp R., Sarry J., Sayre B.L., Tircazes A., Wang J., Wang W., Zhang W., the International Goat Genome Consortium. Design and characterization of a 52k SNP chip for goats. PLoS ONE, 2014, 9(1): e86227 CrossRef
- Nicoloso L., Bomba L., Colli L., Negrini R., Milanesi M., Mazza R., Sechi T., Frattini S., Talenti A., Coizet B., Chessa S., Marletta D., D'Andrea M., Bordonaro S., Ptak G., Carta A., Pagnacco G., Valentini A., Pilla F., Ajmone-Marsan P., Crepaldi P., the Italian Goat Consortium. Genetic diversity of Italian goat breeds assessed with a medium-density SNP chip. Genetics Selection Evolution, 2015, 47(1): 62 CrossRef
- Mdladla K., Dzomba E.F., Huson H.J., Muchadeyi F.C. Population genomic structure and linkage disequilibrium analysis of South African goat breeds using genome-wide SNP data. Animal Genetics, 2016, 47(4): 471-482 CrossRef
- Rahmatalla S.A., Arends D., Reissmann M., Ahmed A.S., Wimmers K., Reyer H., Brockmann G.A. Whole genome population genetics analysis of Sudanese goats identifies regions harboring genes associated with major traits. BMC Genetics, 2017, 18: 92 CrossRef
- Brito L.F., Kijas J.W., Ventura R.V., Sargolzaei M., Porto-Neto L.R., Cánovas A., Feng Z., Jafarikia M., Schenkel F.S. Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers. BMC Genomics, 2017, 18: 229 CrossRef
- Stella A., Nicolazzi E.L., Van Tassell C.P., Rothschild M.F., Colli L., Rosen B.D., Sonstegard T.S., Crepaldi P., Tosser-Klopp G., Joost S., the AdaptMap Consortium. AdaptMap: exploring goat diversity and adaptation. Genetics Selection Evolution, 2018, 50(1): 61 CrossRef
- Bertolini F., Cardoso T.F., Marras G., Nicolazzi E.L., Rothschild M.F., Amills M., AdaptMap consortium. Genome-wide patterns of homozygosity provide clues about the population history and adaptation of goats. Genetics Selection Evolution, 2018, 50(1): 59 CrossRef
- Colli L., Milanesi M., Talenti A., Bertolini F., Chen M., Crisà A., Daly K.G., Del Corvo M., Guldbrandtsen B., Lenstra J.A., Rosen B.D., Vajana E., Catillo G., Joost S., Nicolazzi E.L., Rochat E., Rothschild M.F., Servin B., Sonstegard T.S., Steri R., Van Tassell C.P., Ajmone-Marsan P., Crepaldi P., Stella A., the AdaptMap Consortium. Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes. Genetics Selection Evolution, 2018, 50(1): 58 CrossRef
- Bertolini F., Servin B., Talenti A., Rochat E., Kim E.S., Oget C., Palhière I., Crisà A., Catillo G., Steri R., Amills M., Colli L., Marras G., Milanesi M., Nicolazzi E., Rosen B.D., Van Tassell C.P., Guldbrandtsen B., Sonstegard T.S., Tosser-Klopp G., Stella A., Rothschild M.F., Joost S., Crepaldi P., the AdaptMap consortium. Signatures of selection and environmental adaptation across the goat genome post-domestication. Genetics Selection Evolution, 2018, 50(1): 57 CrossRef
- Fan J.-B., Oliphant A., Shen R., Kermani B.G., Garcia F., Gunderson K.L., Hansen M., Steemers F., Butler S.L., Deloukas P., Galver L., Hunt S., Mcbride C., Bibikova M., Rubano T., Chen J., Wickham E., Doucet D., Chang W., Campbell D., Zhang B., Kruglyak S., Bentley D., Haas J., Rigault P., Zhou L., Stuelpnagel J., Chee M.S. Highly parallel SNP genotyping. Cold Spring Harb. Symp. Quant. Biol., 2003, 68: 69-78 CrossRef
- Chang C.C., Chow C.C., Tellier L.C., Vattikuti S., Purcell S.M., Lee J.J. Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience, 2015, 4: s13742-015-0047-8 CrossRef
- Colli L., Milanesi M., Talenti A., Bertolini F., Chen M., Crisà A., Daly K., Del Corvo M., Guldbrandtsen B., Lenstra J.A., Rosen B.D., Vajana E., Catillo G., Joost S., Nicolazzi E.L., Rochat E., Rothschild M.F., Servin B., Sonstegard T.S., Steri R., Van Tassell C.P., Ajmone-Marsan P., Crepaldi P., Stella A., AdaptMap Consortium. Data from: Signatures of selection and environmental adaptation across the goat genome post-domestication, Dryad, Dataset, 2018 CrossRef
- Weir B.S., Cockerham C.C. Estimating F-statistics for the analysis of population structure. Evolution, 1984, 38(6): 1358-1370 CrossRef
- Reynolds J., Weir B.S., Cockerham C.C. Estimation of the coancestry coefficient: basis for a short-term genetic distance. Genetics, 1983, 105(3): 767-779.
- Keenan K., McGinnity P., Cross T.F., Crozier W.W., Prodöhl P.A. diveRsity: an R package for the estimation of population genetics parameters and their associated errors. Methods in Ecology and Evolution, 2013, 4(8): 782-788 CrossRef
- Wickham H. ggplot2: elegant graphics for data analysis. Springer-Verlag, NY, 2009.
- Huson D.H., Bryant D. Application of phylogenetic networks in evolutionary studies. Molecular Biology and Evolution, 2006, 23(2): 254-267 CrossRef
- Alexander D.H., Novembre J., Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Research, 2009, 19(9): 1655-1664 CrossRef
- Francis R.M. pophelper: An R package and web app to analyse and visualise population structure. Molecular Ecology Resources, 2017, 17(1): 27-32 CrossRef
- R Core Team (2018). R: a language and environment for statistical computing. R foundation for statistical computing, Vienna, Austria. Available: https://www.R-project.org/. No date.
- Mészáros G., Fornara M.S., Reyer H., Wimmers K., Sölkner J., Brem G., Sermyagin A.A., Zinovieva N.A. Elevated haplotypes frequencies reveal similarities for selection signatures in Western and Russian Simmental populations. Journal of Central European Agriculture, 2019, 20(1): 1-11 CrossRef
- Lashmar S.F., Visser C., Van Marle-Köster E. Validation of the 50k Illumina goat SNP chip in the South African Angora goat (short communication). South African Journal of Animal Science, 2015, 45(1): 56-59 CrossRef
- Burren A., Neuditschko M., Signer-Hasler H., Frischknecht M., Reber I., Menzi F., Drögemüller C., Flury C. Genetic diversity analyses reveal first insights into breed-specific selection signatures within Swiss goat breeds. Animal Genetics, 2016, 47(6): 727-739 CrossRef
- Visser C., Lashmar S.F., Van Marle-Köster E., Poli M.A., Allain D. Genetic diversity and population structure in South African, French and Argentinian Angora goats from genome-wide SNP data. PLoS ONE, 2016, 11(5): e0154353 CrossRef
- Laval G., SanCristobal M., Chevalet C. Measuring genetic distances between breeds: use of some distances in various short term evolution models. Genetics Selection Evolution,2002,34(4): 481-507 CrossRef