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Sermyagin A.A., Deniskova Т.Е., Gusev I.V. Petrov S.N., Rodionov A.N., Dotsev A.V., Zinovieva N.А. Identification of SNPs associated with growth and development traits of goats (Capra hircus Linnaeus, 1758) from the resource population in age dynamics. Sel'skokhozyaistvennaya Biologiya [Agricultural Biology], 2024, Vol. 59, № 4, p. 633-648.
(how to cite this article)

doi: 10.15389/agrobiology.2024.4.633eng

UDC: 636.39:575.162

Acknowledgements:
The equipment of the Center for Biological Resources and Bioengineering of Agricultural Animals (Ernst Federal Research Center for Animal Husbandry) was used.
Funded by RSF, project number 21-66-00007

 

IDENTIFICATION OF SNPs ASSOCIATED WITH GROWTH AND DEVELOPMENT TRAITS OF GOATS (Capra hircus Linnaeus, 1758) FROM THE RESOURCE POPULATION IN AGE DY-NAMICS

A.A. Sermyagin ✉, Т.Е. Deniskova, I.V. Gusev, S.N. Petrov,
TA.N. Rodionov, A.V. Dotsev, N.А. Zinovieva

Ernst Federal Research Center for Animal Husbandry, 60, pos. Dubrovitsy, Podolsk District, Moscow Province, 142132 Russia, e-mail alex_sermyagin85@mail.ru (✉ corresponding author), horarka@yandex.ru, citelekle@gmail.com, rodiand@yandex.ru, asnd@mail.ru,
n_zinovieva@mail.ru

ORCID:
Sermyagin A.A. orcid.org/0000-0002-1799-6014
Rodionov A.N. orcid.org/0000-0002-2808-4053
Deniskova T.E. orcid.org/0000-0002-5809-1262
Dotsev A.V. orcid.org/0000-0003-3418-2511
Gusev I.V. orcid.org/0000-0002-2346-4313
Zinovieva N.A. orcid.org/0000-0003-4017-6863
Petrov S.N. orcid.org/0000-0001-5130-677X

Final revision received June 10, 2024

Accepted July 15, 2024

 

The search for genetic variants that affect the growth and development of goats is relevant for creating a specialized meat breed and for increasing animal productivity. In this work, 34 potential QTLs associated with genes for linear measurements of growth and development traits, body weight, meat production and reproductive features, adaptability, hair follicle development, milk production and domestication in goats from a group of recurrent crosses in the resource population obtained by crossing local Karachaev goats hybrid by the wild aurochs with Kalahari breed sires were identified for the first time. We aimed to identify candidate genes associated with economically useful traits in the goat (Capra hircus) resource population. The studies were carry out in 2021-2023 at the Ernst Federal Research Center for Animal Husbandry. The object was crosses of individuals from a specially created resource population of goats (n = 237), including 109 male and 128 female goats. The crosses obtained by crossing Karachaev local goats with a genotype share for 25 % genes of wild goat (3/4 Karachaev dam ½ 1/4 wild Caucasian tur) and Kalahari buck with the red coat. We created a database of phenotypes corresponded to the parameters of growth and development of young goats at an average age of 10, 110, 190 and 390 days. The following parameters were recorded: body weight, height at the withers, height at the back, height at the sacrum, height at the hips, height at the ischial tubewirosities, oblique length of the body, chest girth, metacarpus girth, chest width at the shoulders, chest depth, width at the iliac tubercle, width at the ischial tuberosities, and length of the head. Goat genotyping was performed using the Caprine SNP 50K BeadChip DNA chip (59727 SNP; Illumina, Inc., USA). GWAS analysis was performed using a standard linear regression model by Plink 1.9 program taking into account the population structure of the studied goat dataset. Gene annotation was carried out using the NCBI international genome assembly database ARS1.2 Capra hircus (goat). A total of 1036 genes were identified with SNPs included in or located near them ±0.2 Mb in goats’ genome associated with variability in phenotypic measurements for exterior and live weight traits for young goats from the resource population. Of these, 341 polymorphisms were identified directly in 326 genes on chromosomes 1-29. A detailed gene ontology-based analysis on biological functions of the genes we revealed by GWAS was performed using the international genetic information database DAVID. In the animals aged 10 days, the largest number of associations with significance levels from p < 0.0001 to p < 0.00000001 were identified for height at the withers (35 SNPs), oblique body length (52 SNPs), chest girth (19 SNPs), pastern girth (20 SNPs), chest width (18 SNPs), chest depth (19 SNPs), and body weight (12 SNPs). At the age of 390 days, there also were associations for width at the iliac tubercle and width at the ischial tuberosities (6 SNPs), chest width (8 SNPs), height at the ischial tuberosities and chest girth (10 SNPs), and head length (12 SNPs). We identified genes associated with immune function (ADAM10, DNM1L), reproductive traits (ADAMTS12, ACACB, and PTCH1), growth (osteogenesis and myogenesis) and development (ARL8B, AKT3, CDK5RAP2, RBFOX2, CDH5, EFNA5, FMN1, TGFBR3), embryogenesis (ABCA1), feed efficiency (BANK1), meat productivity and reproductive qualities (LRP2, MYCBP2, OXSR1), adaptation (UVRAG, ANO6, CACNA1C, FLT1, RRM2B, STAT1, SOCS2, TRIM71), hair follicle development and pigmentation (WNT3A, YAP1, EDNRA, ITGB8, MAP3K7), milk production (AGO2, PDE4B) and domestication (ZFPM2). These genes can be used as targets in marker-assisted selection.  

Keywords: Capra hircus, goats, GWAS, SNP, QTL, candidate genes, resource population.

 

REFERENCES

  1. 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. Nauchnyy analiticheskiy obzor [The state and prospective improvement of genetic potentia in small ruminants. Analytical review]. Moscow, 2019 (in Russ.).
  2. Zhang L., Wang F., Gao G., Yan X., Liu H., Liu Z., Wang Z., He L., Lv Q., Wang Z., Wang R., Zhang Y., Li J., Su R. Genome-wide association study of body weight traits in Inner Mongolia cashmere goats. Frontiers in Veterinary Science, 2021, 8: 752746 CrossRef
  3. Selionova M., Aibazov M., Sermyagin A., Belous A., Deniskova T., Mamontova T., Zharkova E., Zinovieva N. Genome-wide association and pathway analysis of carcass and meat quality traits in Karachai young goats. Animals, 2023,13(20):3237 CrossRef
  4. Selionova M., Trukhachev V., Aibazov M., Sermyagin A., Belous A., Gladkikh M., Zinovieva N. Genome-wide association study of milk composition in Karachai goats. Animals, 2024, 14(2): 327 CrossRef
  5. Sun X., Niu Q., Jiang J., Wang G., Zhou P., Li J., Chen C., Liu L., Xu L., Ren H. Identifying candidate genes for litter size and three morphological traits in Youzhou Dark goats based on genome-wide SNP markers. Genes, 2023, 14(6): 1183 CrossRef
  6. Deniskova T.E., Petrov S.N., Sermyagin A.A., Dosev A.V., Fornara M.S., Reyer H., Wimmers K., Bagirov V.A., Brem G., Zinovieva N.A. A search for genomic variants associated with body weight in sheep based on high density SNP genotypes analysis. Sel'skokhozyaistvennaya biologiya [Agricultural Biology], 2021, 56(2): 279-291 CrossRef
  7. Deniskova T.E., Koshkina O.A., Petrov S.N., Sermyagin A.A., Zinov’eva N.A. Agrarnaya nauka Evro-Severo-Vostoka, 2024, 25(2): 236-250 CrossRef (in Russ.).
  8. Sherman B.T., Hao M., Qiu J., Jiao X., Baseler M.W., Lane H.C., Imamichi T., Chang W. DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Research, 2022, 50(W1): W216-W221 CrossRef
  9. 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
  10. Tao L., He X., Jiang Y., Liu Y., Ouyang Y., Shen Y., Hong Q., Chu M. Genome-wide analyses reveal genetic convergence of prolificacy between goats and sheep. Genes, 2021, 12(4): 480 CrossRef
  11. Guan D., Martínez A., Castelló A., Landi V., Luigi-Sierra M.G., Fernández-Álvarez J., Cabrera B., Delgado J.V., Such X., Jordana J., Amills M. A genome-wide analysis of copy number variation in Murciano-Granadina goats. Genetics, Selection, Evolution: GSE, 2020, 52(1): 44 CrossRef
  12. Gu B., Sun R., Fang X., Zhang J., Zhao Z., Huang D., Zhao Y., Zhao Y. Genome-wide association study of body conformation traits by whole genome sequencing in Dazu Black goats. Animals, 2022, 12(5): 548 CrossRef
  13. Saif R., Mahmood T., Zia S., Henkel J., Ejaz A. Genomic selection pressure discovery using site-frequency spectrum and reduced local variability statistics in Pakistani Dera-Din-Panah goat. Tropical Animal Health and Production, 2023, 55(5): 331 CrossRef
  14. Yuan Y., Zhang W., Liu C., He Y., Zhang H., Xu L., Yang B., Zhao Y., Ma Y., Chu M., Zhao Z., Huang Y., Han Y., Zeng Y., Ren H., Wang G., E G. Genome-wide selective analysis of Boer goat to investigate the dynamic heredity evolution under different stages. Animals, 2022, 12(11): 1356 CrossRef
  15. Moaeen-Ud-Din M., Danish Muner R., Khan M.S. Genome wide association study identifies novel candidate genes for growth and body conformation traits in goats. Scientific Reports, 2022, 12(1): 9891 CrossRef
  16. Bhat B., Yaseen M., Singh A., Ahmad S.M., Ganai N.A. Identification of potential key genes and pathways associated with the Pashmina fiber initiation using RNA-Seq and integrated bioinformatics analysis. Scientific Reports, 2021, 11(1): 1766 CrossRef
  17. Li C., Feng C., Ma G., Fu S., Chen M., Zhang W., Li J. Time-course RNA-seq analysis reveals stage-specific and melatonin-triggered gene expression patterns during the hair follicle growth cycle in Capra hircus. BMC Genomics, 2022, 23(1): 140 CrossRef
  18. Wu C., Ma S., Zhao B., Qin C., Wu Y., Di J., Suo L., Fu X. Drivers of plateau adaptability in cashmere goats revealed by genomic and transcriptomic analyses. BMC Genomics, 2023, 24(1): 428 CrossRef
  19. Wang W., Li Z., Xie G., Li X., Wu Z., Li M., Liu A., Xiong Y., Wang Y. Convergent genomic signatures of cashmere traits: evidence for natural and artificial selection. International Journal of Molecular Sciences, 2023, 24(2): 1165 CrossRef
  20. Geng R., Yuan C., Chen Y. Exploring differentially expressed genes by RNA-Seq in cashmere goat (Capra hircus) skin during hair follicle development and cycling. PloS ONE, 2013, 8(4): e62704 CrossRef
  21. Waineina R.W., Okeno T.O., Ilatsia E.D., Ngeno K. Selection signature analyses revealed genes associated with adaptation, production, and reproduction in selected goat breeds in Kenya. Frontiers in Genetics, 2022, 13: 858923 CrossRef
  22. Massender E., Oliveira H.R., Brito L.F., Maignel L., Jafarikia M., Baes C.F., Sullivan B., Schenkel F.S. Genome-wide association study for milk production and conformation traits in Canadian Alpine and Saanen dairy goats. Journal of Dairy Science, 2023, 106(2): 1168-1189 CrossRef
  23. Sun Z., Zhang Z., Liu Y., Ren C., He X., Jiang Y., Ouyang Y., Hong Q., Chu M. Integrated analysis of mRNAs and long non-coding RNAs expression of oviduct that provides novel insights into the prolificacy mechanism of goat (Capra hircus). Genes, 2022, 13(6): 1031 CrossRef
  24. Ren C., Chen Y., Tang J., Wang P., Zhang Y., Li C., Zhang Z., Cheng X. TMT-based comparative proteomic analysis of the spermatozoa of buck (Capra hircus) and ram (Ovis aries). Genes, 2023, 14(5): 973 CrossRef
  25. Luo N., Cheng W., Zhou Y., Gu B., Zhao Z., Zhao Y. Screening candidate genes regulating placental development from trophoblast transcriptome at early pregnancy in Dazu Black goats (Capra hircus). Animals, 2021, 11(7): 2132 CrossRef
  26. Reber I., Keller I., Becker D., Flury C., Welle M., Drögemüller C. Wattles in goats are associated with the FMN1/GREM1 region on chromosome 10. Animal Genetics, 2015, 46(3): 316-320 CrossRef
  27. Menzi F., Keller I., Reber I., Beck J., Brenig B., Schütz E., Leeb T., Drögemüller C. Genomic amplification of the caprine EDNRA locus might lead to a dose dependent loss of pigmentation. Scientific Reports, 2016, 6: 28438 CrossRef
  28. Wani S.A., Sahu A.R., Khan R.I.N., Pandey A., Saxena S., Hosamani N., Malla W.A., Chaudhary D., Kanchan S., Sah V., Rajak K.K., Muthuchelvan D., Mishra B., Tiwari A.K., Sahoo A.P., Sajjanar B., Singh Y.P., Gandham R.K., Mishra B.P., Singh R.K. Contrasting gene expression profiles of monocytes and lymphocytes from peste-des-petits-ruminants virus infected goats. Frontiers in Immunology, 2019, 10: 1463 CrossRef
  29. Guo J., Zhong J., Li L., Zhong T., Wang L., Song T., Zhang H. Comparative genome analyses reveal the unique genetic composition and selection signals underlying the phenotypic characteristics of three Chinese domestic goat breeds. Genetics, Selection, Evolution: GSE, 2019 51(1): 70 CrossRef
  30. Signer-Hasler H., Henkel J., Bangerter E., Bulut Z., VarGoats Consortium, Drögemüller C., Leeb T., Flury C. Runs of homozygosity in Swiss goats reveal genetic changes associated with domestication and modern selection. Genetics, Selection, Evolution: GSE, 2022, 54(1): 6 CrossRef
  31. Dong Y., Zhang X., Xie M., Arefnezhad B., Wang Z., Wang W., Feng S., Huang G., Guan R., Shen W., Bunch R., McCulloch R., Li Q., Li B., Zhang G., Xu X., Kijas J. W., Salekdeh G.H., Wang W., Jiang Y. Reference genome of wild goat (Capra aegagrus) and sequencing of goat breeds provide insight into genic basis of goat domestication. BMC Genomics, 2015, 16(1): 431 CrossRef
  32. Ncube K.T., Dzomba E.F., Rosen B.D., Schroeder S.G., Van Tassell C.P., Muchadeyi F.C. Differential gene expression and identification of growth-related genes in the pituitary gland of South African goats. Frontiers in Genetics, 2022, 13: 811193 CrossRef
  33. Wang X., Liu J., Zhou G., Guo J., Yan H., Niu Y., Li Y., Yuan C., Geng R., Lan X., An X., Tian X., Zhou H., Song J., Jiang Y., Chen Y. Whole-genome sequencing of eight goat populations for the detection of selection signatures underlying production and adaptive traits. Scientific Reports, 2016, 6: 38932 CrossRef
  34. Tahir M.S., Porto-Neto L.R., Gondro C., Shittu O.B., Wockner K., Tan A.W.L., Smith H.R., Gouveia G.C., Kour J., Fortes M.R.S. Meta-analysis of heifer traits identified reproductive pathways in Bos indicus cattle. Genes, 2021, 12(5): 768 CrossRef
  35. Chen Q., Qu K., Ma, Z., Zhan J., Zhang F., Shen J., Ning Q., Jia P., Zhang J., Chen N., Chen H., Huang B., Lei C. Genome-wide association study identifies genomic loci associated with neurotransmitter concentration in cattle. Frontiers in Genetics, 2020, 11: 139 CrossRef
  36. Wang Y., Zhang C., Wang N., Li Z., Heller R., Liu R., Zhao Y., Han J., Pan X., Zheng Z., Dai X., Chen C., Dou M., Peng S., Chen X., Liu J., Li M., Wang K., Liu C., Lin Z., Chen L., Hao F., Zhu W., Song C., Zhao C., Zheng C., Wang J., Hu S., Li C., Yang H., Jiang L., Li G., Liu M., Sonstegard T.S., Zhang G., Jiang Y., Wang W., Qiu Q. Genetic basis of ruminant headgear and rapid antler regeneration. Science, 2019, 364(6446): eaav6335 CrossRef
  37. Stronen A.V., Pertoldi C., Iacolina L., Kadarmideen H.N., Kristensen T.N. Genomic analyses suggest adaptive differentiation of northern European native cattle breeds. Evolutionary Applications, 2019, 12(6): 1096-1113 CrossRef
  38. Zeng X., Wang W., Zhang D., Li X., Zhang Y., Zhao Y., Zhao L., Wang J., Xu D., Cheng J., Li W., Zhou B., Lin C., Yang X., Zhai R., Ma Z., Liu J., Cui P., Weng X., Wu W., Zhang X., Zheng W. Expression of the ovine gene and the relationship between its polymorphism and feed efficiency traits. DNA and Cell Biology, 2023, 42(4): 194-202 CrossRef
  39. Berton M.P., de Oliveira Silva R.M., Peripolli E., Stafuzza N.B., Martin J.F., Álvarez M.S., Gavinã B.V., Toro M.A., Banchero G., Oliveira P.S., Eler J.P., Baldi F., Ferraz J.B.S. Genomic regions and pathways associated with gastrointestinal parasites resistance in Santa Inês breed adapted to tropical climate. Journal of Animal Science and Biotechnology, 2017, 8: 73 CrossRef
  40. Pławińska-Czarnak J., Majewska A., Zarzyńska J., Bogdan J., Kaba J., Anusz K., Bagnicka E. Gene expression profile in peripheral blood nuclear cells of small ruminant lentivirus-seropositive and seronegative dairy goats in their first lactation. Animals, 2021, 11(4): 940 CrossRef
  41. Namous H., Peñagaricano F., Del Corvo M., Capra E., Thomas D. L., Stella A., Williams J.L., Marsan P.A., Khatib H. Integrative analysis of methylomic and transcriptomic data in fetal sheep muscle tissues in response to maternal diet during pregnancy. BMC Genomics, 2018, 19(1): 123 CrossRef
  42. Zhang H., Yang P., Liu C., Ma Y., Han Y., Zeng Y., Huang Y., Zhao Y., Zhao Z., He X., E G. Novel heredity basis of the four-horn phenotype in sheep using genome-wide sequence data. Animals, 2023, 13(20): 3166 CrossRef
  43. Zhang X., Zhang S., Tang Q., Jiang E., Wang K., Lan X., Pan C. Goat sperm associated antigen 17 protein gene (SPAG17): small and large fragment genetic variation detection, association analysis, and mRNA expression in gonads. Genomics, 2020, 112(6): 5115-5121 CrossRef
  44. Trigila A.P., Pisciottano F., Franchini L.F. Hearing loss genes reveal patterns of adaptive evolution at the coding and non-coding levels in mammals. BMC Biology, 2021, 19(1): 244 CrossRef
  45. Chebii V. Genome scan for signatures of adaptive evolution in wild African goat (Capra nubiana). PhD Theses and Dissertations. Arusha, Tanzania, 2021
  46. Naldurtiker A., Batchu P., Kouakou B., Terrill T.H., Shaik A., Kannan G. RNA-Seq exploration of the influence of stress on meat quality in Spanish goats. Scientific Reports, 2022, 12(1): 20573 CrossRef

 

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