1
|
Bastos MS, Solar Diaz IDP, Alves JS, de Oliveira LSM, de Araújo de Oliveira CA, de Godói FN, de Camargo GMF, Costa RB. Genomic association using principal components of morphometric traits in horses: identification of genes related to bone growth. Anim Biotechnol 2023; 34:4921-4926. [PMID: 37184429 DOI: 10.1080/10495398.2023.2209795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
The measurement of morphometric traits in horses is important for determining breed qualification and is one of the main selection criteria for the species. The development of an index (HPC) that consists of principal components weighted by additive genetic values allows to explore the most relevant relationships using a reduced number of variables that explain the greatest amount of variation in the data. Genome-wide association studies (GWAS) using HPC are a relatively new approach that permits to identify regions related to a set of traits. The aim of this study was to perform GWAS using HPC for 15 linear measurements as the explanatory variable in order to identify associated genomic regions and to elucidate the biological mechanisms linked to this index in Campolina horses. For GWAS, weighted single-step GBLUP was applied to HPC. The eight genomic windows that explained the highest proportion of additive genetic variance were identified. The sum of the additive variance explained by the eight windows was 95.89%. Genes involved in bone and cartilage development were identified (SPRY2, COL9A2, MIR30C, HEYL, BMP8B, LTBP1, FAM98A, and CRIM1). They represent potential positional candidates for the HPC of the linear measurements evaluated. The HPC is an efficient alternative to reduce the 15 usually measured traits in Campolina horses. Moreover, candidate genes inserted in region that explained high additive variance of the HPC were identified and might be fine-mapped for searching putative mutation/markers.
Collapse
Affiliation(s)
- Marisa Silva Bastos
- Escola de Medicina Veterinária e Zootecnia, Universidade Federal da Bahia (UFBA), Salvador, Brazil
| | | | - Jackeline Santos Alves
- Escola de Medicina Veterinária e Zootecnia, Universidade Federal da Bahia (UFBA), Salvador, Brazil
| | | | | | | | | | - Raphael Bermal Costa
- Escola de Medicina Veterinária e Zootecnia, Universidade Federal da Bahia (UFBA), Salvador, Brazil
| |
Collapse
|
2
|
Tong X, Chen D, Hu J, Lin S, Ling Z, Ai H, Zhang Z, Huang L. Accurate haplotype construction and detection of selection signatures enabled by high quality pig genome sequences. Nat Commun 2023; 14:5126. [PMID: 37612277 PMCID: PMC10447580 DOI: 10.1038/s41467-023-40434-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 07/27/2023] [Indexed: 08/25/2023] Open
Abstract
High-quality whole-genome resequencing in large-scale pig populations with pedigree structure and multiple breeds would enable accurate construction of haplotype and robust selection-signature detection. Here, we sequence 740 pigs, combine with 149 of our previously published resequencing data, retrieve 207 resequencing datasets, and form a panel of worldwide distributed wild boars, aboriginal and highly selected pigs with pedigree structures, amounting to 1096 genomes from 43 breeds. Combining with their haplotype-informative reads and pedigree structure, we accurately construct a panel of 1874 haploid genomes with 41,964,356 genetic variants. We further demonstrate its valuable applications in GWAS by identifying five novel loci for intramuscular fat content, and in genomic selection by increasing the accuracy of estimated breeding value by 36.7%. In evolutionary selection, we detect MUC13 gene under a long-term balancing selection, as well as NPR3 gene under positive selection for pig stature. Our study provides abundant genomic variations for robust selection-signature detection and accurate haplotypes for deciphering complex traits in pigs.
Collapse
Affiliation(s)
- Xinkai Tong
- National Key Laboratory for Swine genetic improvement and production technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, NanChang, Jiangxi Province, PR China
- College of Life Sciences, Jiangxi Normal University, NanChang, Jiangxi Province, PR China
| | - Dong Chen
- National Key Laboratory for Swine genetic improvement and production technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, NanChang, Jiangxi Province, PR China
| | - Jianchao Hu
- National Key Laboratory for Swine genetic improvement and production technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, NanChang, Jiangxi Province, PR China
| | - Shiyao Lin
- National Key Laboratory for Swine genetic improvement and production technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, NanChang, Jiangxi Province, PR China
| | - Ziqi Ling
- National Key Laboratory for Swine genetic improvement and production technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, NanChang, Jiangxi Province, PR China
| | - Huashui Ai
- National Key Laboratory for Swine genetic improvement and production technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, NanChang, Jiangxi Province, PR China
| | - Zhiyan Zhang
- National Key Laboratory for Swine genetic improvement and production technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, NanChang, Jiangxi Province, PR China.
| | - Lusheng Huang
- National Key Laboratory for Swine genetic improvement and production technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, NanChang, Jiangxi Province, PR China.
| |
Collapse
|
3
|
Salek Ardestani S, Zandi MB, Vahedi SM, Janssens S. Population structure and genomic footprints of selection in five major Iranian horse breeds. Anim Genet 2022; 53:627-639. [PMID: 35919961 DOI: 10.1111/age.13243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 06/08/2022] [Accepted: 07/04/2022] [Indexed: 11/28/2022]
Abstract
The genetic structure and characteristics of Iranian native breeds are yet to be comprehensibly investigated and studied. Therefore, we employed genomic information of 364 Iranian native horses representing the Asil (n = 109), Caspian (n = 40), Dareshuri (n = 44), Kurdish (n = 95), and Turkoman (n = 76) breeds to reveal the genetic structure and characteristics. For these and 19 other horse breeds, principal component analysis, Bayesian model-based, Neighbor-Net, and bootstrap-based TreeMix approaches were applied to investigate and compare their genetic structure. Additionally, three haplotype-based methods including haplotype homozygosity pooled, integrated haplotype score, and number of segregating sites by length were applied to trace genomic footprints of selection of Asil, Caspian, Dareshuri, Kurdish, and Turkoman groups. Then, the Mahalanobis distance based on the negative-log10 rank-based P-values was estimated based on the haplotype homozygosity pooled, integrated haplotype score, and number of segregating sites by length values. Asil, Caspian, Dareshuri, Kurdish, and Turkoman can be categorized into five different genetic clusters. Based on the top 1% of Mahalanobis distance based on the negative-log10 rank-based P-values of SNPs, we identified 24 SNPs formerly reported to be associated with different traits and >100 genes undergoing selection pressures in Asil, Caspian, Dareshuri, Kurdish, and Turkoman. The detected QTL undergoing selection pressures were associated with withers height, equine metabolic syndrome, overall body size, insect bite hypersensitivity, guttural pouch tympany, white markings, Rhodococcus equi infection, jumping test score, alternate gaits, and body weight traits. Our findings will aid to have a better perspective of the genetic characteristics and population structure of Asil, Caspian, Dareshuri, Kurdish, and Turkoman horses as Iranian native horse breeds.
Collapse
Affiliation(s)
| | | | - Seyed Milad Vahedi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, Nova Scotia, Canada
| | - Steven Janssens
- Department Biosystems, Center Animal Breeding and Genetics, KU Leuven, Leuven, Belgium
| |
Collapse
|
4
|
Shen J, Yu J, Dai X, Li M, Wang G, Chen N, Chen H, Lei C, Dang R. Genomic analyses reveal distinct genetic architectures and selective pressures in Chinese donkeys. J Genet Genomics 2021; 48:737-745. [PMID: 34373218 DOI: 10.1016/j.jgg.2021.05.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 05/09/2021] [Accepted: 05/10/2021] [Indexed: 12/28/2022]
Abstract
Donkey (Equus asinus) is an important livestock animal in China because of its draft and medicinal value. After a long period of natural and artificial selection, the variety and phenotype of donkeys have become abundant. We clarified the genetic and demographic characteristics of Chinese domestic donkeys and the selection pressures by analyzing 78 whole genomes from 12 breeds. According to population structure, most Chinese domestic donkeys showed a dominant ancestral type. However, the Chinese donkeys still represented a significant geographical distribution trend. In the selective sweep, gene annotation, functional enrichment, and differential expression analyses between large and small donkey groups, we identified selective signals, including NCAPG and LCORL, which are related to rapid growth and large body size. Our findings elucidate the evolutionary history and formation of different donkey breeds and provide theoretical insights into the genetic mechanism underlying breed characteristics and molecular breeding programs of donkey clades.
Collapse
Affiliation(s)
- Jiafei Shen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jie Yu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xuelei Dai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mei Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Gang Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Hong Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chuzhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ruihua Dang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.
| |
Collapse
|