Characterization of heterozygosity-rich regions in Italian and worldwide goat breeds.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
02 Jan 2024
02 Jan 2024
Historique:
received:
19
09
2023
accepted:
04
12
2023
medline:
4
1
2024
pubmed:
4
1
2024
entrez:
3
1
2024
Statut:
epublish
Résumé
Heterozygosity-rich regions (HRR) are genomic regions of high heterozygosity, which may harbor loci related to key functional traits such as immune response, survival rate, fertility, and other fitness traits. This study considered 30 Italian and 19 worldwide goat breeds genotyped with the Illumina GoatSNP50k BeadChip. The aim of the work was to study inter-breed relationships and HRR patterns using Sliding Window (SW) and Consecutive Runs (CR) detection methods. Genetic relationships highlighted a clear separation between non-European and European breeds, as well as the north-south geographic cline within the latter. The Pearson correlation coefficients between the descriptive HRR parameters obtained with the SW and CR methods were higher than 0.9. A total of 166 HRR islands were detected. CHI1, CHI11, CHI12 and CHI18 were the chromosomes harboring the highest number of HRR islands. The genes annotated in the islands were linked to various factors such as productive, reproductive, immune, and environmental adaptation mechanisms. Notably, the Montecristo feral goat showed the highest number of HRR islands despite the high level of inbreeding, underlining potential balancing selection events characterizing its evolutionary history. Identifying a species-specific HRR pattern could provide a clearer view of the mechanisms regulating the genome modelling following anthropogenic selection combined with environmental interaction.
Identifiants
pubmed: 38168531
doi: 10.1038/s41598-023-49125-x
pii: 10.1038/s41598-023-49125-x
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
3Informations de copyright
© 2024. The Author(s).
Références
Renaud, G., Hanghoj, K., Korneliussen, T. S., Willerslev, E. & Orlando, L. Joint estimates of heterozygosity and runs of homozygosity for modern and ancient samples. Genetics 212, 587–614 (2019).
pubmed: 31088861
pmcid: 6614887
doi: 10.1534/genetics.119.302057
Ferenčaković, M. et al. Mapping of heterozygosity rich regions in Austrian pinzgauer cattle. Acta Agric. Slov. 5, S41-44 (2016).
Santos, W. B. et al. Fine-scale estimation of inbreeding rates, runs of homozygosity and genome-wide heterozygosity levels in the Mangalarga Marchador horse breed. J. Anim. Breed. Genet. 138, 161–173 (2021).
doi: 10.1111/jbg.12508
Williams, J. L. et al. Inbreeding and purging at the genomic Level: the Chillingham cattle reveal extensive, non-random SNP heterozygosity. Anim. Genet. 47, 19–27 (2016).
pubmed: 26559490
doi: 10.1111/age.12376
Samuels, D. C. et al. Heterozygosity ratio, a robust global genomic measure of autozygosity and its association with height and disease risk. Genetics 204, 893–904 (2016).
pubmed: 27585849
pmcid: 5105867
doi: 10.1534/genetics.116.189936
Biscarini, F., Mastrangelo, S., Catillo, G., Senczuk, G. & Ciampolini, R. Insights into genetic diversity, runs of homozygosity and heterozygosity-rich regions in Maremmana semi-feral cattle using pedigree and genomic data. Animals (Basel) 10, 2285 (2020).
Mulim, H. A. et al. Characterization of runs of homozygosity, heterozygosity-enriched regions, and population structure in cattle populations selected for different breeding goals. BMC Genomics 23, 209 (2022).
pubmed: 35291953
pmcid: 8925140
doi: 10.1186/s12864-022-08384-0
Selli, A. et al. Detection and visualization of heterozygosity-rich regions and runs of homozygosity in worldwide sheep populations. Animals (Basel) 11, 2696 (2021).
Ruan, D. et al. Assessment of heterozygosity and genome-wide analysis of heterozygosity regions in two Duroc pig populations. Front. Genet. 12, 812456 (2022).
pubmed: 35154256
pmcid: 8830653
doi: 10.3389/fgene.2021.812456
VanRaden, P. M., Olson, K. M., Null, D. J. & Hutchison, J. L. Harmful recessive effects on fertility detected by absence of homozygous haplotypes. J. Dairy Sci. 94, 6153–6161 (2011).
pubmed: 22118103
doi: 10.3168/jds.2011-4624
Biscarini, F. et al. Use of SNP genotypes to identify carriers of harmful recessive mutations in cattle populations. BMC Genomics 17, 857 (2016).
pubmed: 27809787
pmcid: 5093950
doi: 10.1186/s12864-016-3218-9
Tsartsianidou, V. et al. A comprehensive genome-wide scan detects genomic regions related to local adaptation and climate resilience in Mediterranean domestic sheep. Genet. Sel. Evol. 53, 90 (2021).
pubmed: 34856922
pmcid: 8641236
doi: 10.1186/s12711-021-00682-7
Chen, Z. et al. Heterozygosity and homozygosity regions affect reproductive success and the loss of reproduction: A case study with litter traits in pigs. Comput. Struct. Biotechnol. J. 20, 4060–4071 (2022).
pubmed: 35983229
pmcid: 9364102
doi: 10.1016/j.csbj.2022.07.039
Bordonaro, S. et al. Genome-wide population structure, homozygosity, and heterozygosity patterns of Nero Siciliano pig in the framework of Italian and cosmopolitan breeds. Anim. Genet. 00, 1–15 (2023).
Li, G. et al. Genome-wide estimates of runs of homozygosity, heterozygosity, and genetic load in two chinese indigenous goat breeds. Front. Genet. 13, 774196 (2022).
pubmed: 35559012
pmcid: 9086400
doi: 10.3389/fgene.2022.774196
Naderi, S. et al. The goat domestication process inferred from large-scale mitochondrial DNA analysis of wild and domestic individuals. Proc. Natl. Acad. Sci. USA 105, 17659–17664 (2008).
pubmed: 19004765
pmcid: 2584717
doi: 10.1073/pnas.0804782105
Denoyelle, L. et al. VarGoats project: A dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity. Genet. Sel. Evol. 53, 86 (2021).
pubmed: 34749642
pmcid: 8573910
doi: 10.1186/s12711-021-00659-6
Stella, A. et al. AdaptMap: Exploring goat diversity and adaptation. Genet. Sel. Evol. 50, 61 (2018).
pubmed: 30453882
pmcid: 6240945
doi: 10.1186/s12711-018-0427-5
Colli, L. et al. Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes. Genet. Sel. Evol. 50, 58 (2018).
pubmed: 30449284
pmcid: 6240949
doi: 10.1186/s12711-018-0422-x
Cortellari, M. et al. The climatic and genetic heritage of Italian goat breeds with genomic SNP data. Sci. Rep. 11, 10986 (2021).
pubmed: 34040003
pmcid: 8154919
doi: 10.1038/s41598-021-89900-2
Miller, M. A. & Zachery, J. F. Pathologic basis of veterinary disease. 6th edn St Louis (Elsevier, 2017).
Serranito, B. et al. Local adaptations of Mediterranean sheep and goats through an integrative approach. Sci. Rep. 11, 21363 (2021).
pubmed: 34725398
pmcid: 8560853
doi: 10.1038/s41598-021-00682-z
Cortellari, M. et al. Runs of homozygosity in the Italian goat breeds: Impact of management practices in low-input systems. Genet. Sel. Evol. 53, 92 (2021).
pubmed: 34895134
pmcid: 8666052
doi: 10.1186/s12711-021-00685-4
Tosser-Klopp, G. et al. Design and characterization of a 52K SNP chip for goats. PLoS One 9, e86227 (2014).
pubmed: 24465974
pmcid: 3899236
doi: 10.1371/journal.pone.0086227
Mastrangelo, S. et al. Genome-wide patterns of homozygosity reveal the conservation status in five Italian goat populations. Animals (Basel) 11, 1510 (2021).
Somenzi, E. et al. The SNP-based profiling of Montecristo feral goat populations reveals a history of isolation, bottlenecks, and the effects of management. Genes (Basel) 13, 213 (2022).
Peñaloza, C. et al. Development and testing of a combined species SNP array for the European seabass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata). Genomics 113, 2096–2107 (2021).
pubmed: 33933591
doi: 10.1016/j.ygeno.2021.04.038
Pereira, F. et al. Tracing the history of goat pastoralism: new clues from mitochondrial and Y chromosome DNA in North Africa. Mol. Biol. Evol. 26, 2765–2773 (2009).
pubmed: 19729424
doi: 10.1093/molbev/msp200
Missohou, A., Talaki, E. & Laminou, I. M. Diversity and genetic relationships among seven west African goat breeds. Asian-Australas. J. Anim. Sci. 19, 1245–1251 (2006).
doi: 10.5713/ajas.2006.1245
Gifford-Gonzalez, D. & Hanotte, O. Domesticating animals in Africa: Implications of genetic and archaeological findings. J. World Prehist. 24, 1–23 (2011).
doi: 10.1007/s10963-010-9042-2
Naderi, S. et al. Large-scale mitochondrial DNA analysis of the domestic goat reveals six haplogroups with high diversity. PLoS One 2, e1012 (2007).
pubmed: 17925860
pmcid: 1995761
doi: 10.1371/journal.pone.0001012
Dixit, S. P. et al. Genome-wide runs of homozygosity revealed selection signatures in Bos indicus. Front. Genet. 11, 92 (2020).
pubmed: 32153647
pmcid: 7046685
doi: 10.3389/fgene.2020.00092
Biscarini, F., Cozzi, P., Gaspa, G. & Marras, G. detectRUNS: An R package to detect runs of homozygosity and heterozygosity in diploid genomes. https://orca.cardiff.ac.uk/108906/ . Accessed 28 August 2023 (2018).
Biscarini, F., Cozzi, P., Ramirez-Díaz, J., Stella, A. & Manunza, A. in Proceedings of 25th Congress on Animal Production Science: innovations and sustainability for future generations (ASPA) (2023).
Marras, G. et al. in Proceedings of the 11th World Congress of Genetics Applied to Livestock Production (WCGALP) (2018).
Bertolini, F. et al. Genome-wide patterns of homozygosity provide clues about the population history and adaptation of goats. Genet. Sel. Evol. 50, 59 (2018).
pubmed: 30449279
pmcid: 6241033
doi: 10.1186/s12711-018-0424-8
Bertolini, F. et al. Signatures of selection and environmental adaptation across the goat genome post-domestication. Genet. Sel. Evol. 50, 57 (2018).
pubmed: 30449276
pmcid: 6240954
doi: 10.1186/s12711-018-0421-y
Mota, L. F. M. et al. Meta-analysis across Nellore cattle populations identifies common metabolic mechanisms that regulate feed efficiency-related traits. BMC Genomics 23, 424 (2022).
pubmed: 35672696
pmcid: 9172108
doi: 10.1186/s12864-022-08671-w
Zhao, B. et al. Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep. Genet. Sel. Evol. 53, 56 (2021).
pubmed: 34193030
pmcid: 8247193
doi: 10.1186/s12711-021-00649-8
Seto, E., Yoshida-Sugitani, R., Kobayashi, T. & Toyama-Sorimachi, N. The assembly of EDC4 and Dcp1a into processing bodies is critical for the translational regulation of IL-6. PLoS One 10, e0123223 (2015).
pubmed: 25970328
pmcid: 4430274
doi: 10.1371/journal.pone.0123223
Zhang, X. et al. Novel nucleotide variations, haplotypes structure and associations with growth related traits of goat AT Motif-Binding Factor (ATBF1) gene. Asian-Australas. J. Anim. Sci. 28, 1394–1406 (2015).
pubmed: 26323396
pmcid: 4554846
doi: 10.5713/ajas.14.0860
Wei, Z. et al. Detection of insertion/deletions (indels) of the ATBF1 gene and their effects on growth-related traits in three indigenous goat breeds. Arch. Anim. Breed. 61, 311–319 (2018).
doi: 10.5194/aab-61-311-2018
Lamartine, L. et al. Mutations in GJB6 cause hidrotic ectodermal dysplasia. Nat. Genet. 26, 142–144 (2000).
pubmed: 11017065
doi: 10.1038/79851
Pandya, A. et al. Frequency and distribution of GJB2 (connexin 26) and GJB6 (connexin 30) mutations in a large North American repository of deaf probands. Genet. Med. 5, 295–303 (2003).
pubmed: 12865758
doi: 10.1097/01.GIM.0000078026.01140.68
Feng, Y., Peng, X., Li, S. & Gong, Y. Isolation and characterization of sexual dimorphism genes expressed in chicken embryonic gonads. Acta Biochim. Biophys. Sin. (Shanghai) 41, 285–294 (2009).
pubmed: 19352543
doi: 10.1093/abbs/gmp012
Abied, A. et al. Genome-wide analysis revealed homozygosity and demographic history of five chinese sheep breeds adapted to different environments. Genes (Basel) 11, 1480 (2020).
Onzima, R. B. et al. Genome-wide characterization of selection signatures and runs of homozygosity in Ugandan goat breeds. Front. Genet. 9, 318 (2018).
pubmed: 30154830
pmcid: 6102322
doi: 10.3389/fgene.2018.00318
Kim, E. S. et al. Multiple genomic signatures of selection in goats and sheep indigenous to a hot arid environment. Heredity (Edinb) 116, 255–264 (2016).
pubmed: 26555032
doi: 10.1038/hdy.2015.94
Lee, Y., Clinton, J., Yao, C. & Chang, S. H. Interleukin-17D promotes pathogenicity during infection by suppressing CD8 T cell activity. Front. Immunol. 10, 1172 (2019).
pubmed: 31244826
pmcid: 6562898
doi: 10.3389/fimmu.2019.01172
Huang, J. et al. Interleukin-17D regulates group 3 innate lymphoid cell function through its receptor CD93. Immunity 54, 673–686 e674 (2021).
Biscarini, F., Manunza, A., Cozzi, P. & Stella, A. in Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP) (2022).
Taye, M. et al. Exploring evidence of positive selection signatures in cattle breeds selected for different traits. Mamm. Genome 28, 528–541 (2017).
pubmed: 28905131
doi: 10.1007/s00335-017-9715-6
Berihulay, H. et al. Whole genome resequencing reveals selection signatures associated with important traits in Ethiopian indigenous goat populations. Front. Genet. 10, 1190 (2019).
pubmed: 31850061
pmcid: 6892828
doi: 10.3389/fgene.2019.01190
Arora, R. et al. Transcriptome profiling of longissimus thoracis muscles identifies highly connected differentially expressed genes in meat type sheep of India. PLoS One 14, e0217461 (2019).
pubmed: 31170190
pmcid: 6553717
doi: 10.1371/journal.pone.0217461
Zhang, L. et al. Quantitative genomics of 30 complex phenotypes in Wagyu x Angus F1 progeny. Int. J. Biol. Sci. 8, 838–858 (2012).
pubmed: 22745575
pmcid: 3385007
doi: 10.7150/ijbs.4403
de Lima, A. O. et al. Potential biomarkers for feed efficiency-related traits in Nelore cattle identified by co-expression network and integrative genomics analyses. Front. Genet. 11, 189 (2020).
pubmed: 32194642
pmcid: 7064723
doi: 10.3389/fgene.2020.00189
Wragg, D. et al. A locus conferring tolerance to Theileria infection in African cattle. PLoS Genet. 18, e1010099 (2022).
pubmed: 35446841
pmcid: 9022807
doi: 10.1371/journal.pgen.1010099
Wang, J. J. et al. Genome-wide detection of selective signals for fecundity traits in goats (Capra hircus). Gene 818, 146221 (2022).
pubmed: 35092859
doi: 10.1016/j.gene.2022.146221
Cui, L. X. et al. Knockdown of ASH1L methyltransferase induced apoptosis inhibiting proliferation and H3K36 methylation in bovine cumulus cells. Theriogenology 161, 65–73 (2021).
pubmed: 33296745
doi: 10.1016/j.theriogenology.2020.11.007
Giesecke, K. et al. Evaluation of SPATA1-associated markers for stallion fertility. Anim. Genet. 40, 359–365 (2009).
pubmed: 19220231
doi: 10.1111/j.1365-2052.2008.01844.x
Waineina, R. W., Okeno, T. O., Ilatsia, E. D. & Ngeno, K. In Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP) (2022).
Zang, X. W. et al. Heritable and nonheritable rumen bacteria are associated with different characters of lactation performance of dairy cows. mSystems 7, e00422 (2022).
Liu, L. et al. Study of the integrated immune response induced by an inactivated EV71 vaccine. PLoS One 8, e54451 (2013).
pubmed: 23372725
pmcid: 3553120
doi: 10.1371/journal.pone.0054451
Berton, M. P. et al. Genomic regions and pathways associated with gastrointestinal parasites resistance in Santa Ines breed adapted to tropical climate. J. Anim. Sci. Biotechnol. 8, 73 (2017).
pubmed: 28878894
pmcid: 5584554
doi: 10.1186/s40104-017-0190-4
Mousel, M. R. et al. Genes involved in immune, gene translation and chromatin organization pathways associated with Mycoplasma ovipneumoniae presence in nasal secretions of domestic sheep. PLoS One 16, e0247209 (2021).
pubmed: 34252097
pmcid: 8274911
doi: 10.1371/journal.pone.0247209
Li, G. S. et al. Genome-wide association study of bone quality and feed efficiency-related traits in Pekin ducks. Genomics 112, 5021–5028 (2020).
pubmed: 32927007
doi: 10.1016/j.ygeno.2020.09.023
He, Y. et al. Interleukin-31 receptor alpha is required for basal-like breast cancer progression. Front. Oncol. 10, 816 (2020).
pubmed: 32528891
pmcid: 7266966
doi: 10.3389/fonc.2020.00816
Fu, L. et al. Effect of heat stress on bovine mammary cellular metabolites and gene transcription related to amino acid metabolism, amino acid transportation and mammalian target of rapamycin (mTOR) signaling. Animals (Basel) 11, 3153 (2021).
de Klerk, B. et al. A genome-wide association study for natural antibodies measured in blood of Canadian Holstein cows. BMC Genomics 19, 694 (2018).
pubmed: 30241501
pmcid: 6150957
doi: 10.1186/s12864-018-5062-6
Milanesi, M. et al. BITE: An R package for biodiversity analyses. https://doi.org/10.1101/181610 . Accessed 28 August 2023. (2017).
Chang, C. C. et al. Second-generation PLINK: Rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).
pubmed: 25722852
pmcid: 4342193
doi: 10.1186/s13742-015-0047-8
Excoffier, L. & Lischer, H. E. Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Resour. 10, 564–567 (2010).
Huson, D. H. & Bryant, D. Application of phylogenetic networks in evolutionary studies. Mol. Biol. Evol. 23, 254–267 (2006).
pubmed: 16221896
doi: 10.1093/molbev/msj030
Bjelland, D. W., Weigel, K. A., Vukasinovic, N. & Nkrumah, J. D. Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding. J. Dairy Sci. 96, 4697–4706 (2013).
pubmed: 23684028
doi: 10.3168/jds.2012-6435
Marras, G. et al. Analysis of runs of homozygosity and their relationship with inbreeding in five cattle breeds farmed in Italy. Anim. Genet. 46, 110–121 (2015).
pubmed: 25530322
doi: 10.1111/age.12259
Criscione, A. et al. Genome-wide survey on three local horse populations with a focus on runs of homozygosity pattern. J. Anim. Breed. Genet. 139, 540–555 (2022).
pubmed: 35445758
pmcid: 9541879
doi: 10.1111/jbg.12680
Gorssen, W., Meyermans, R., Janssens, S. & Buys, N. A publicly available repository of ROH islands reveals signatures of selection in different livestock and pet species. Genet. Sel. Evol. 53, 2 (2021).
pubmed: 33397285
pmcid: 7784028
doi: 10.1186/s12711-020-00599-7
Huang, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2008).
doi: 10.1038/nprot.2008.211