Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (6)

Search Parameters:
Keywords = Fst and θπ Ratio and XP-EHH

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
20 pages, 3398 KB  
Article
Whole-Genome Sequencing Reveals Population Structure, Genetic Diversity, and Selection Signatures in Kazakh Dromedary and Bactrian Camels
by Zhannur Niyazbekova, Cai-Yue Gao, Nursultan Makhanbetuly, Kuanysh Kassen, Yuan Xu, Bekzat Baimirzayev, Huanhuan Zhang, Zhadyra Muslimova, Kanat Orynkhanov, Yessengali Ussenbekov, Fengting Bai, Junyan Wang, Hasan Baneh, Yelaman Serikov, Pilong Liu and Yu Jiang
Animals 2026, 16(17), 2793; https://doi.org/10.3390/ani16172793 (registering DOI) - 5 Sep 2026
Abstract
Understanding the genomic basis of environmental adaptation is essential for the conservation and genetic improvement of domestic camels. In this study, we investigated the population structure, genetic diversity, and genomic variation potentially associated with environmental adaptation of Kazakh dromedary and Bactrian camels using [...] Read more.
Understanding the genomic basis of environmental adaptation is essential for the conservation and genetic improvement of domestic camels. In this study, we investigated the population structure, genetic diversity, and genomic variation potentially associated with environmental adaptation of Kazakh dromedary and Bactrian camels using whole-genome sequencing. Whole-genome sequencing data were generated for Kazakh camels (15 dromedaries and 16 Bactrian camels) and integrated with 131 publicly available genomes representing camel populations from the Arabian Peninsula, Iran, Xinjiang, Inner Mongolia, and Mongolian wild camels. Population structure, genetic diversity, and genome-wide selection were evaluated using principal component analysis, ADMIXTURE, nucleotide diversity, linkage disequilibrium, runs of homozygosity, genomic inbreeding (FROH), and selection scans based on FST, θπ ratio, and XP-EHH. Population genomic analyses revealed clear differentiation between dromedary and Bactrian camels, whereas Kazakh camel populations exhibited higher nucleotide diversity (θπ = 1.307–1.551 × 10−3), and lower genomic inbreeding (median FROH: 0.037–0.056) than Arabian populations. Genome-wide selection analyses identified MC4R as the prominent candidate gene in Kazakh dromedaries and RYR1 as a prominent candidate gene in Kazakh Bactrian camels. Functional enrichment analyses highlighted pathways related to energy metabolism, thermogenesis, calcium signaling, skeletal muscle function, mitochondrial activity, and oxidative stress response. These findings provide new insights into genomic variation potentially associated with environmental adaptation in Kazakh camels and offer valuable genomic resources for future conservation, breeding, and evolutionary studies. Full article
(This article belongs to the Special Issue Genomics for Camelid Biodiversity Management and Conservation)
Show Figures

Figure 1

28 pages, 16152 KB  
Article
Integrated SNP and SV Analyses Reveal Genetic Mechanisms Underlying High-Altitude Adaptation in Goats
by Wenze Li, Yixin Su, Can Liu, Xiaokun Lin, Shanhui Xue, Bouabid Badaoui, Xiaochun Yan, Qi Lv and Rui Su
Animals 2026, 16(14), 2177; https://doi.org/10.3390/ani16142177 - 13 Jul 2026
Viewed by 505
Abstract
High-altitude environments, characterized by hypoxia, intense ultraviolet radiation, and low temperatures, pose major challenges to livestock survival. In recent years, researchers have gradually uncovered adaptive mechanisms in livestock across different altitudes using whole-genome resequencing. Previous studies of goat altitude adaptation have been limited [...] Read more.
High-altitude environments, characterized by hypoxia, intense ultraviolet radiation, and low temperatures, pose major challenges to livestock survival. In recent years, researchers have gradually uncovered adaptive mechanisms in livestock across different altitudes using whole-genome resequencing. Previous studies of goat altitude adaptation have been limited by small breed numbers and low sequencing depth, hindering comprehensive exploration of adaptive mechanisms across different altitudes. This study analyzed whole-genome resequencing data from 151 individuals across 17 goat breeds representing three distinct altitude gradients (high, middle, and low). Using both SNPs and structural variations (SVs), we characterized population relationships, gene flow, and the SV landscape, including QTL–SV associations and transposable element interactions. Selective sweep analyses using FST, θπ ratio, XP-CLR, XP-EHH, and LFMM identified several candidate genes associated with altitude adaptation, including ABCC4, RPS6, DSG4, and LY9, which were significantly enriched in pathways related to hypoxia response, oxidative stress, energy metabolism, angiogenesis, and nervous system regulation. Notably, ABCC4 showed ABCC4 showed recurrent candidate selection signals in both SNP and SV analyses, suggesting its potential involvement in altitude adaptation. These findings provide multi-level genomic evidence for goat adaptation to high-altitude stress and provide important insights into the adaptive evolution of goats. Full article
(This article belongs to the Section Animal Genetics and Genomics)
Show Figures

Figure 1

24 pages, 5116 KB  
Article
Whole Genome Resequencing Reveals Selection Signals Related to Wool Color in Sheep
by Wentao Zhang, Meilin Jin, Zengkui Lu, Taotao Li, Huihua Wang, Zehu Yuan and Caihong Wei
Animals 2023, 13(20), 3265; https://doi.org/10.3390/ani13203265 - 19 Oct 2023
Cited by 23 | Viewed by 4625
Abstract
Wool color is controlled by a variety of genes. Although the gene regulation of some wool colors has been studied in relative depth, there may still be unknown genetic variants and control genes for some colors or different breeds of wool that need [...] Read more.
Wool color is controlled by a variety of genes. Although the gene regulation of some wool colors has been studied in relative depth, there may still be unknown genetic variants and control genes for some colors or different breeds of wool that need to be identified and recognized by whole genome resequencing. Therefore, we used whole genome resequencing data to compare and analyze sheep populations of different breeds by population differentiation index and nucleotide diversity ratios (Fst and θπ ratio) as well as extended haplotype purity between populations (XP-EHH) to reveal selection signals related to wool coloration in sheep. Screening in the non-white wool color group (G1 vs. G2) yielded 365 candidate genes, among which PDE4B, GMDS, GATA1, RCOR1, MAPK4, SLC36A1, and PPP3CA were associated with the formation of non-white wool; an enrichment analysis of the candidate genes yielded 21 significant GO terms and 49 significant KEGG pathways (p < 0.05), among which 17 GO terms and 21 KEGG pathways were associated with the formation of non-white wool. Screening in the white wool color group (G2 vs. G1) yielded 214 candidate genes, including ABCD4, VSX2, ITCH, NNT, POLA1, IGF1R, HOXA10, and DAO, which were associated with the formation of white wool; an enrichment analysis of the candidate genes revealed 9 significant GO-enriched pathways and 19 significant KEGG pathways (p < 0.05), including 5 GO terms and 12 KEGG pathways associated with the formation of white wool. In addition to furthering our understanding of wool color genetics, this research is important for breeding purposes. Full article
(This article belongs to the Special Issue Genetics of Coat Color in Animals)
Show Figures

Figure 1

20 pages, 9438 KB  
Article
Whole-Genome Resequencing Reveals Selection Signal Related to Sheep Wool Fineness
by Wentao Zhang, Meilin Jin, Taotao Li, Zengkui Lu, Huihua Wang, Zehu Yuan and Caihong Wei
Animals 2023, 13(18), 2944; https://doi.org/10.3390/ani13182944 - 16 Sep 2023
Cited by 31 | Viewed by 4319
Abstract
Wool fineness affects the quality of wool, and some studies have identified about forty candidate genes that affect sheep wool fineness, but these genes often reveal only a certain proportion of the variation in wool thickness. We further explore additional genes associated with [...] Read more.
Wool fineness affects the quality of wool, and some studies have identified about forty candidate genes that affect sheep wool fineness, but these genes often reveal only a certain proportion of the variation in wool thickness. We further explore additional genes associated with the fineness of sheep wool. Whole-genome resequencing of eight sheep breeds was performed to reveal selection signals associated with wool fineness, including four coarse wool and four fine/semi-fine wool sheep breeds. Multiple methods to reveal selection signals (Fst and θπ Ratio and XP-EHH) were applied for sheep wool fineness traits. In total, 269 and 319 genes were annotated in the fine wool (F vs. C) group and the coarse wool (C vs. F) group, such as LGR4, PIK3CA, and SEMA3C and NFIB, OPHN1, and THADA. In F vs. C, 269 genes were enriched in 15 significant GO Terms (p < 0.05) and 38 significant KEGG Pathways (p < 0.05), such as protein localization to plasma membrane (GO: 0072659) and Inositol phosphate metabolism (oas 00562). In C vs. F, 319 genes were enriched in 21 GO Terms (p < 0.05) and 16 KEGG Pathways (p < 0.05), such as negative regulation of focal adhesion assembly (GO: 0051895) and Axon guidance (oas 04360). Our study has uncovered genomic information pertaining to significant traits in sheep and has identified valuable candidate genes. This will pave the way for subsequent investigations into related traits. Full article
(This article belongs to the Collection Small Ruminant Genetics and Breeding)
Show Figures

Figure 1

13 pages, 2416 KB  
Article
Assessing Genomic Diversity and Selective Pressures in Bohai Black Cattle Using Whole-Genome Sequencing Data
by Xiaohui Ma, Haijian Cheng, Yangkai Liu, Luyang Sun, Ningbo Chen, Fugui Jiang, Wei You, Zhangang Yang, Baoheng Zhang, Enliang Song and Chuzhao Lei
Animals 2022, 12(5), 665; https://doi.org/10.3390/ani12050665 - 7 Mar 2022
Cited by 24 | Viewed by 5360
Abstract
Bohai Black cattle are one of the well-known cattle breeds with black coat color in China, which are cultivated for beef. However, no study has conducted a comprehensive analysis of genomic diversity and selective pressures in Bohai Black cattle. Here, we performed a [...] Read more.
Bohai Black cattle are one of the well-known cattle breeds with black coat color in China, which are cultivated for beef. However, no study has conducted a comprehensive analysis of genomic diversity and selective pressures in Bohai Black cattle. Here, we performed a comprehensive analysis of genomic variation in 10 Bohai Black cattle (five newly sequenced and five published) and the published whole-genome sequencing (WGS) data of 50 cattle representing five “core” cattle populations. The population structure analysis revealed that Bohai Black cattle harbored the ancestry with European taurine, Northeast Asian taurine, and Chinese indicine. The Bohai Black cattle demonstrated relatively high genomic diversity from the other cattle breeds, as indicated by the nucleotide diversity (pi), the expected heterozygosity (HE) and the observed heterozygosity (HO), the linkage disequilibrium (LD) decay, and runs of homozygosity (ROH). We identified 65 genes containing more than five non-synonymous SNPs (nsSNPs), and an enrichment analysis revealed the “ECM-receptor interaction” pathways associated with meat quality in Bohai Black cattle. Five methods (CLR, θπ, FST, θπ ratio, and XP-EHH) were used to find several pathways and genes carried selection signatures in Bohai Black cattle, including black coat color (MC1R), muscle development (ITGA9, ENAH, CAPG, ABI2, and ISLR), fat deposition (TBC1D1, CYB5R4, TUSC3, and EPS8), reproduction traits (SPIRE2, KHDRBS2, and FANCA), and immune system response (CD84, SLAMF1, SLAMF6, and CDK10). Taken together, our results provide a valuable resource for characterizing the uniqueness of Bohai Black cattle. Full article
(This article belongs to the Special Issue Evolution of Genetic Diversity in Domestic Animals)
Show Figures

Figure 1

12 pages, 1427 KB  
Article
Genome-Wide Selective Signatures Reveal Candidate Genes Associated with Hair Follicle Development and Wool Shedding in Sheep
by Zhihui Lei, Weibo Sun, Tingting Guo, Jianye Li, Shaohua Zhu, Zengkui Lu, Guoyan Qiao, Mei Han, Hongchang Zhao, Bohui Yang, Liping Zhang, Jianbin Liu, Chao Yuan and Yaojing Yue
Genes 2021, 12(12), 1924; https://doi.org/10.3390/genes12121924 - 29 Nov 2021
Cited by 27 | Viewed by 4550
Abstract
Hair follicle development and wool shedding in sheep are poorly understood. This study investigated the population structures and genetic differences between sheep with different wool types to identify candidate genes related to these traits. We used Illumina ovine SNP 50K chip genotyping data [...] Read more.
Hair follicle development and wool shedding in sheep are poorly understood. This study investigated the population structures and genetic differences between sheep with different wool types to identify candidate genes related to these traits. We used Illumina ovine SNP 50K chip genotyping data of 795 sheep populations comprising 27 breeds with two wool types, measuring the population differentiation index (Fst), nucleotide diversity (θπ ratio), and extended haplotype homozygosity among populations (XP-EHH) to detect the selective signatures of hair sheep and fine-wool sheep. The top 5% of the Fst and θπ ratio values, and values of XP-EHH < −2 were considered strongly selected SNP sites. Annotation showed that the PRX, SOX18, TGM3, and TCF3 genes related to hair follicle development and wool shedding were strongly selected. Our results indicated that these methods identified important genes related to hair follicle formation, epidermal differentiation, and hair follicle stem cell development, and provide a meaningful reference for further study on the molecular mechanisms of economically important traits in sheep. Full article
(This article belongs to the Section Animal Genetics and Genomics)
Show Figures

Figure 1

Back to TopTop