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Abdelmanova AA, Deniskova TE, Kharzinova VR, Chinarov RY, Boronetskaya OI, Sölkner J, Brem G, Ai H, Huang L, Trukhachev VI, Zinovieva NA. Tracing the Dynamical Genetic Diversity Changes of Russian Livni Pigs during the Last 50 Years with the Museum, Old, and Modern Samples. Animals (Basel) 2024; 14:1629. [PMID: 38891676 PMCID: PMC11171240 DOI: 10.3390/ani14111629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 05/27/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024] Open
Abstract
The pig industry is usually considered an intensive livestock industry, mainly supported by hybrid breeding between commercial pig breeds. However, people's pursuit of a more natural environment and higher meat quality has led to an increasing demand for eco-friendly and diverse pig feeding systems. Therefore, the importance of rearing and conserving local pig breeds is increasing. The Livni pig is a local breed with good adaptability to the environmental and fodder conditions in central Russia. In this study, we aimed to analyze the genetic diversity and population structure of Livni pigs using whole-genome single nucleotide polymorphism (SNP) data. We utilized the Porcine GGP HD BeadChip on genotype samples from old (n = 32, 2004) and modern (n = 32, 2019) populations of Livni pigs. For the museum samples of Livni pigs (n = 3), we extracted DNA from their teeth, performed genomic sequencing, and obtained SNP genotypes from the whole-genome sequences. SNP genotypes of Landrace (n = 32) and Large White (n = 32) pigs were included for comparative analysis. We observed that the allelic richness of Livni pigs was higher than those of Landrace and Large White pigs (AR = 1.775-1.798 vs. 1.703 and 1.668, respectively). The effective population size estimates (NE5 = 108 for Livni pigs, NE5 = 59 for Landrace and Large White pigs) confirmed their genetic diversity tendency. This was further supported by the length and number of runs of homozygosity, as well as the genomic inbreeding coefficient (almost twofold lower in Livni pigs compared to Landrace and Large White pigs). These findings suggest that the Livni pig population exhibits higher genetic diversity and experiences lower selection pressure compared to commercial pig populations. Furthermore, both principal component and network tree analyses demonstrated a clear differentiation between Livni pigs and transboundary commercial pigs. The TreeMix results indicated gene flow from Landrace ancestors to Livni pigs (2019) and from Large White ancestors to Livni pigs (2004), which was consistent with their respective historical breeding backgrounds. The comparative analysis of museum, old, and modern Livni pigs indicated that the modern Livni pig populations have preserved their historical genomic components, suggesting their potential suitability for future design selection programs.
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Affiliation(s)
- Alexandra A. Abdelmanova
- L.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk Municipal District, Moscow Region, Podolsk 142132, Russia; (A.A.A.); (V.R.K.); (R.Y.C.)
| | - Tatiana E. Deniskova
- L.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk Municipal District, Moscow Region, Podolsk 142132, Russia; (A.A.A.); (V.R.K.); (R.Y.C.)
| | - Veronika R. Kharzinova
- L.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk Municipal District, Moscow Region, Podolsk 142132, Russia; (A.A.A.); (V.R.K.); (R.Y.C.)
| | - Roman Yu Chinarov
- L.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk Municipal District, Moscow Region, Podolsk 142132, Russia; (A.A.A.); (V.R.K.); (R.Y.C.)
| | - Oksana I. Boronetskaya
- Museum of Livestock, Timiryazev Russian State Agrarian University—Moscow Agrarian Academy, 49, ul. Timiryazevskaya, Moscow 127550, Russia; (O.I.B.); (V.I.T.)
| | - Johann Sölkner
- Division of Livestock Sciences, University of Natural Resources and Life Sciences, 1180 Vienna, Austria;
| | - Gottfried Brem
- Institute of Animal Breeding and Genetics, University of Veterinary Medicine (VMU), Veterinärplatz, 1210 Vienna, Austria;
| | - Huashui Ai
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang 330045, China; (H.A.); (L.H.)
| | - Lusheng Huang
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang 330045, China; (H.A.); (L.H.)
| | - Vladimir I. Trukhachev
- Museum of Livestock, Timiryazev Russian State Agrarian University—Moscow Agrarian Academy, 49, ul. Timiryazevskaya, Moscow 127550, Russia; (O.I.B.); (V.I.T.)
| | - Natalia A. Zinovieva
- L.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk Municipal District, Moscow Region, Podolsk 142132, Russia; (A.A.A.); (V.R.K.); (R.Y.C.)
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Ma KY, Song JJ, Li DP, Wu Y, Wang CH, Liu ZL, Li TT, Ma YJ. Genomic structure analysis and construction of DNA fingerprint for four sheep populations. Animal 2024; 18:101116. [PMID: 38484632 DOI: 10.1016/j.animal.2024.101116] [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] [Received: 10/19/2023] [Revised: 02/16/2024] [Accepted: 02/16/2024] [Indexed: 04/20/2024] Open
Abstract
The Yongdeng Qishan sheep (QS) is a sheep population found locally in China. To gain in-depth knowledge of its population characteristics, three control groups were chosen, comprising the Lanzhou fat-tailed sheep (LFT), TAN sheep (TAN), and Minxian black fur sheep (MBF), inhabiting the nearby environments. This study genotyped a total of 120 individuals from four sheep populations: QS, LFT, TAN, and MBF. Using Specific-Locus Amplified Fragment Sequencing, we conducted genetic diversity, population structure, and selective sweep analysis, and constructed the fingerprint of each population. In total, there were 782 535 single nucleotide polymorphism (SNP) variations identified, with most being situated within regions that are intergenic or intronic. The genetic diversity analysis revealed that the QS population exhibited lower genetic diversity compared to the other three populations. Consistent results were obtained from the principal component, phylogenetic tree, and population structure analysis, indicating significant genetic differences between QS and the other three populations. However, a certain degree of differentiation was observed within the QS population. The linkage disequilibrium (LD) patterns among the four populations showed clear distinctions, with the QS group demonstrating the most rapid LD decline. Kinship analysis supported the findings of population structure, dividing the 90 QS individuals into two subgroups consisting of 23 and 67 individuals. Selective sweep analysis identified a range of genes associated with reproduction, immunity, and adaptation to high-altitude hypoxia. These genes hold potential as candidate genes for marker-assisted selection breeding. Additionally, a total of 86 523 runs of homozygosity (ROHs) were detected, showing non-uniform distribution across chromosomes, with chromosome 1 having the highest coverage percentage and chromosome 26 the lowest. In the high-frequency ROH islands, 79 candidate genes were associated with biological processes such as reproduction and fat digestion and absorption. Furthermore, a DNA fingerprint was constructed for the four populations using 349 highly polymorphic SNPs. In summary, our research delves into the genetic diversity and population structure of QS population. The construction of DNA fingerprint profiles for each population can provide valuable references for the identification of sheep breeds both domestically and internationally.
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Affiliation(s)
- Ke-Yan Ma
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Juan-Juan Song
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Deng-Pan Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Yi Wu
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Chun-Hui Wang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Zi-Long Liu
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Tao-Tao Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - You-Ji Ma
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China.
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Huang C, Zhao Q, Chen Q, Su Y, Ma Y, Ye S, Zhao Q. Runs of Homozygosity Detection and Selection Signature Analysis for Local Goat Breeds in Yunnan, China. Genes (Basel) 2024; 15:313. [PMID: 38540373 PMCID: PMC10970279 DOI: 10.3390/genes15030313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 02/25/2024] [Accepted: 02/25/2024] [Indexed: 06/14/2024] Open
Abstract
Runs of Homozygosity (ROH) are continuous homozygous DNA segments in diploid genomes, which have been used to estimate the genetic diversity, inbreeding levels, and genes associated with specific traits in livestock. In this study, we analyzed the resequencing data from 10 local goat breeds in Yunnan province of China and five additional goat populations obtained from a public database. The ROH analysis revealed 21,029 ROH segments across the 15 populations, with an average length of 1.27 Mb, a pattern of ROH, and the assessment of the inbreeding coefficient indicating genetic diversity and varying levels of inbreeding. iHS (integrated haplotype score) was used to analyze high-frequency Single-Nucleotide Polymorphisms (SNPs) in ROH regions, specific genes related to economic traits such as coat color and weight variation. These candidate genes include OCA2 (OCA2 melanosomal transmembrane protein) and MLPH (melanophilin) associated with coat color, EPHA6 (EPH receptor A6) involved in litter size, CDKAL1 (CDK5 regulatory subunit associated protein 1 like 1) and POMC (proopiomelanocortin) linked to weight variation and some putative genes associated with high-altitude adaptability and immune. This study uncovers genetic diversity and inbreeding levels within local goat breeds in Yunnan province, China. The identification of specific genes associated with economic traits and adaptability provides actionable insights for utilization and conservation efforts.
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Affiliation(s)
- Chang Huang
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (C.H.); (Q.Z.)
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (Q.C.); (Y.S.); (Y.M.)
| | - Qian Zhao
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (C.H.); (Q.Z.)
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (Q.C.); (Y.S.); (Y.M.)
| | - Qian Chen
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (Q.C.); (Y.S.); (Y.M.)
| | - Yinxiao Su
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (Q.C.); (Y.S.); (Y.M.)
| | - Yuehui Ma
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (Q.C.); (Y.S.); (Y.M.)
| | - Shaohui Ye
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (C.H.); (Q.Z.)
| | - Qianjun Zhao
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (Q.C.); (Y.S.); (Y.M.)
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Li W, Wu X, Xiang D, Zhang W, Wu L, Meng X, Huo J, Yin Z, Fu G, Zhao G. Genome-Wide Detection for Runs of Homozygosity in Baoshan Pigs Using Whole Genome Resequencing. Genes (Basel) 2024; 15:233. [PMID: 38397222 PMCID: PMC10887577 DOI: 10.3390/genes15020233] [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: 01/16/2024] [Revised: 02/08/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024] Open
Abstract
Baoshan pigs (BS) are a local breed in Yunnan Province that may face inbreeding owing to its limited population size. To accurately evaluate the inbreeding level of the BS pig population, we used whole-genome resequencing to identify runs of homozygosity (ROH) regions in BS pigs, calculated the inbreeding coefficient based on pedigree and ROH, and screened candidate genes with important economic traits from ROH islands. A total of 22,633,391 SNPS were obtained from the whole genome of BS pigs, and 201 ROHs were detected from 532,450 SNPS after quality control. The number of medium-length ROH (1-5 Mb) was the highest (98.43%), the number of long ROH (>5 Mb) was the lowest (1.57%), and the inbreeding of BS pigs mainly occurred in distant generations. The inbreeding coefficient FROH, calculated based on ROH, was 0.018 ± 0.016, and the FPED, calculated based on the pedigree, was 0.027 ± 0.028, which were positively correlated. Forty ROH islands were identified, containing 507 genes and 891 QTLs. Several genes were associated with growth and development (IGFALS, PTN, DLX5, DKK1, WNT2), meat quality traits (MC3R, ACSM3, ECI1, CD36, ROCK1, CACNA2D1), and reproductive traits (NPW, TSHR, BMP7). This study provides a reference for the protection and utilization of BS pigs.
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Affiliation(s)
- Wenjun Li
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (W.L.); (L.W.); (X.M.); (J.H.); (G.F.)
| | - Xudong Wu
- Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230036, China; (X.W.); (W.Z.)
| | - Decai Xiang
- Institute of Pig and Animal Research, Yunnan Academy of Animal Husbandry and Veterinary Science, Kunming 650201, China;
| | - Wei Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230036, China; (X.W.); (W.Z.)
| | - Lingxiang Wu
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (W.L.); (L.W.); (X.M.); (J.H.); (G.F.)
| | - Xintong Meng
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (W.L.); (L.W.); (X.M.); (J.H.); (G.F.)
| | - Jinlong Huo
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (W.L.); (L.W.); (X.M.); (J.H.); (G.F.)
| | - Zongjun Yin
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China;
| | - Guowen Fu
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (W.L.); (L.W.); (X.M.); (J.H.); (G.F.)
| | - Guiying Zhao
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (W.L.); (L.W.); (X.M.); (J.H.); (G.F.)
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Elavarasan K, Kumar S, Agarwal S, Vani A, Sharma R, Kumar S, Chauhan A, Sahoo NR, Verma MR, Gaur GK. Estimation of microsatellite-based autozygosity and its correlation with pedigree inbreeding coefficient in crossbred cattle. Anim Biotechnol 2023; 34:3564-3577. [PMID: 36811467 DOI: 10.1080/10495398.2023.2176318] [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: 02/24/2023]
Abstract
In countries where farming is largely subsistence, no pedigree records of farm animals are maintained at farmers' herd and scientific mating plans are not observed which leads to the accumulation of inbreeding and loss of production potential. Microsatellites have been widely used as reliable molecular markers to measure inbreeding. We attempted to correlate autozygosity estimated from microsatellite data with the inbreeding coefficient (F) calculated from pedigree data in Vrindavani crossbred cattle developed in India. The inbreeding coefficient was calculated from the pedigree of ninety-six Vrindavani cattle. Animals were further grouped into three groups viz. acceptable/low (F: 0-5%), moderate (F: 5-10%) and high (F: ≥10%), based on their inbreeding coefficients. The overall mean of the inbreeding coefficient was found to be 0.070 ± 0.007. A panel of twenty-five bovine-specific loci were chosen for the study according to ISAG/FAO. The mean FIS, FST, and FIT values were 0.0548 ± 0.025, 0.012 ± 0.001 and 0.0417 ± 0.025, respectively. There was no significant correlation between the FIS values obtained and the pedigree F values. The locus-wise individual autozygosity was estimated using the method-of-moments estimator (MME) formula for locus-specific autozygosity. The autozygosities ascribing to CSSM66 and TGLA53 were found to be significantly (p < .01 and p < .05, respectively) correlated with pedigree F values.
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Affiliation(s)
- K Elavarasan
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Subodh Kumar
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Swati Agarwal
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - A Vani
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Rekha Sharma
- National Bureau of Animal Genetic Resources, Karnal, India
| | - Sanjeev Kumar
- Avian Genetics, ICAR - Central Avian Research Institute, Izatnagar, India
| | - Anuj Chauhan
- Division of Livestock Production and Management, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Nihar Ranjan Sahoo
- ICAR-International Centre for Foot and Mouth Disease (DFMD), Bhubaneswar, India
| | - Med Ram Verma
- Division of Livestock Economics, Statistics and Information Technology, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Gyanendra Kumar Gaur
- Division of Livestock Production and Management, ICAR-Indian Veterinary Research Institute, Izatnagar, India
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Khalak VI, Gutyj BV. Feeding and meat qualities of young pigs of different genotypes according to melanocortin 4 receptor (Mc4r) gene and interbreed differentiation according to the coefficient of decrease in growth intensity in early ontogenesis. UKRAINIAN JOURNAL OF VETERINARY AND AGRICULTURAL SCIENCES 2022. [DOI: 10.32718/ujvas5-3.01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
The paper presents the results of studies of fattening and meat qualities of young large white pigs of different genotypes for the melanocortin receptor 4 (Mc4r) gene and the decline in growth intensity in early ontogeny. The research was carried out in the agricultural formations of the Dnipropetrovsk region, the Jazz meat processing plant, the laboratory of the genetics of the Institute of Pig Breeding and APV of the National Academy of Sciences, and the laboratory of animal husbandry of the State Institution “Institute of Grain Crops of the National Academy of Sciences”. The work was carried out following the scientific research program of the National Academy of Sciences No. 30, “Innovative technologies of breeding, industrial and organic production of pig farming products” (“Pig farming”). Assessment of animals for fattening and meat quality was carried out taking into account the following characteristics: average daily gain of live weight during the period of control fattening, g; the age of reaching 100 kg live weight, days, length of the chilled carcass, cm; length of the bacon half of the cooled carcass, cm; thickness of lard at the level of 6–7 thoracic vertebrae, mm. The coefficient of decline in growth intensity was calculated according to the method of Yu. K. Sviechin. Biometric research results were processed using generally accepted methods. It was established that according to live weight at 4 and 6 months of age, fattening and meat qualities (age of reaching a live weight of 100 kg, days; lard thickness at the level of 6–7 thoracic vertebrae, mm; length of the chilled carcass, cm) young pigs the controlled population belongs to the I class and the elite class. The coefficient of growth decline in animals of the controlled population ranges from 108.57 to 142.51 points. The data analysis shows that according to the live weight at 4 and 6 months of age, the age of reaching the live weight of 100 kg, the fat thickness at the level of 6–7 thoracic vertebrae, and the length of the chilled carcass, the young pigs of the controlled population belong to the I class and the elite class. Animals of the Mc4r АГ genotype prevail over peers of the Mc4r AA genotype in terms of fattening and meat qualities by an average of 5.90 %. The interbreed differentiation of young pigs by the coefficient of the intensity of growth decline (∆K) shows that the difference between the animals of the experimental groups in terms of the average daily gain in live weight is 23.3 g (td = 2.62), the age of reaching 100 kg live weight is 2.7 days (td = 1.59), the length of the cooled carcass is 1.4 mm (td = 2.12). The number of reliable correlations between fattening and meat qualities, coefficient of the intensity of growth decline (∆K), and Tyler B. index is 75.0 %, which indicates the possibility of their use in selection and breeding work. The use of young pigs of the Mc4r АG genotype and animals of the I group, in which the coefficient of the intensity of growth decline (∆K) ranges from 115.61 to 123.27 points, provides additional production at the level of +3.68 – +1.75 % respectively.
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Addo S, Jung L. An insight into the runs of homozygosity distribution and breed differentiation in Mangalitsa pigs. Front Genet 2022; 13:909986. [DOI: 10.3389/fgene.2022.909986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 09/30/2022] [Indexed: 11/13/2022] Open
Abstract
Mangalitsa pigs exhibit three distinct coat color patterns based on which they are described as Red, Blond, and Swallow-bellied. The current study investigated genome-wide diversity and selection signatures in the three breeds using fixation index, runs of homozygosity and population structure analyses. The analyses were originally based on quality-controlled data on 77 Mangalitsa animals from Germany, including 23 Blond, 30 Swallow-bellied and 24 Red Mangalitsa genotyped with a customized version of the ProcineSNP60 v2 Genotyping Bead Chip. Also, 20 Hungarian Mangalitsa genotypes were included as outgroup data for comparison. Estimates of observed heterozygosity were 0.27, 0.28, and 0.29, and inbreeding coefficients estimated based on runs of homozygosity were 24.11%, 20.82%, and 16.34% for Blond, Swallow-bellied and Red Mangalitsa, respectively. ROH islands were detected in all breeds, however, none of these were shared amongst them. The KIF16B gene previously reported to play a role in synaptic signaling was found in a ROH island (SSC17: 16–26) in Swallow-bellied Mangalitsa. The same gene was found to harbor a significantly differentiated SNP (MARC0032380) while contrasting either Blond or Red to Swallow-belied Mangalitsa. In the Red Mangalitsa, some ROH islands were associated with genes that play a role in meat quality traits, i.e., ABCA12, VIL1, PLSCR5, and USP37. Our population structure analysis highlighted a separation of the three breeds, but also showed the closest relatedness between Red and Blond Mangalitsa pigs. Findings of this study improve our understanding of the diversity in the three breeds of Mangalitsa pigs.
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Abondio P, Cilli E, Luiselli D. Inferring Signatures of Positive Selection in Whole-Genome Sequencing Data: An Overview of Haplotype-Based Methods. Genes (Basel) 2022; 13:genes13050926. [PMID: 35627311 PMCID: PMC9141518 DOI: 10.3390/genes13050926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 05/19/2022] [Accepted: 05/20/2022] [Indexed: 11/16/2022] Open
Abstract
Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change throughout the evolution of a population. New sources of food, climate conditions, and exposure to pathogens are only some of the possible sources of selective pressure, and the rise of advantageous genetic variants is a crucial determinant of survival and reproduction. In this context, the ability to detect these signatures of selection may pinpoint genetic variants that are responsible for a significant change in gene regulation, gene expression, or protein synthesis, structure, and function. This review focuses on statistical methods that take advantage of linkage disequilibrium and haplotype determination to reveal signatures of positive selection in whole-genome sequencing data, showing that they emerge from different descriptions of the same underlying event. Moreover, considerations are provided around the application of these statistics to different species, their suitability for ancient DNA, and the usefulness of discovering variants under selection for biomedicine and public health in an evolutionary medicine framework.
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Affiliation(s)
- Paolo Abondio
- Department of Cultural Heritage, University of Bologna, Via Degli Ariani 1, 48121 Ravenna, Italy; (E.C.); (D.L.)
- Laboratory of Molecular Anthropology and Center for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Via Selmi 3, 40126 Bologna, Italy
- Correspondence:
| | - Elisabetta Cilli
- Department of Cultural Heritage, University of Bologna, Via Degli Ariani 1, 48121 Ravenna, Italy; (E.C.); (D.L.)
| | - Donata Luiselli
- Department of Cultural Heritage, University of Bologna, Via Degli Ariani 1, 48121 Ravenna, Italy; (E.C.); (D.L.)
- Fano Marine Center, The Inter-Institute Center for Research on Marine Biodiversity, Resources and Biotechnologies (FMC), Viale Adriatico 1/N, 61032 Fano, Italy
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