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Saini T, Chauhan A, Ahmad SF, Kumar A, Vaishnav S, Singh S, Mehrotra A, Bhushan B, Gaur GK, Dutt T. Elucidation of population stratifying markers and selective sweeps in crossbred Landlly pig population using genome-wide SNP data. Mamm Genome 2024; 35:170-185. [PMID: 38485788 DOI: 10.1007/s00335-024-10029-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/23/2024] [Indexed: 05/29/2024]
Abstract
The present study was aimed at the identification of population stratifying markers from the commercial porcine SNP 60K array and elucidate the genome-wide selective sweeps in the crossbred Landlly pig population. Original genotyping data, generated on Landlly pigs, was merged in various combinations with global suid breeds that were grouped as exotic (global pig breeds excluding Indian and Chinese), Chinese (Chinese pig breeds only), and outgroup pig populations. Post quality control, the genome-wide SNPs were ranked for their stratifying power within each dataset in TRES (using three different criteria) and FIFS programs and top-ranked SNPs (0.5K, 1K, 2K, 3K, and 4K densities) were selected. PCA plots were used to assess the stratification power of low-density panels. Selective sweeps were elucidated in the Landlly population using intra- and inter-population haplotype statistics. Additionally, Tajima's D-statistics were calculated to determine the status of balancing selection in the Landlly population. PCA plots showed 0.5K marker density to effectively stratify Landlly from other pig populations. The A-score in DAPC program revealed the Delta statistic of marker selection to outperform other methods (informativeness and FST methods) and that 3000-marker density was suitable for stratification of Landlly animals from exotic pig populations. The results from selective sweep analysis revealed the Landlly population to be under selection for mammary (NAV2), reproductive efficiency (JMY, SERGEF, and MAP3K20), body conformation (FHIT, WNT2, ASRB, DMGDH, and BHMT), feed efficiency (CSRNP1 and ADRA1A), and immunity (U6, MYO3B, RBMS3, and FAM78B) traits. More than two methods suggested sweeps for immunity and feed efficiency traits, thus giving a strong indication for selection in this direction. The study is the first of its kind in Indian pig breeds with a comparison against global breeds. In conclusion, 500 markers were able to effectively stratify the breeds. Different traits under selective sweeps (natural or artificial selection) can be exploited for further improvement.
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Affiliation(s)
- Tapendra Saini
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, 243122, India
| | - Anuj Chauhan
- Swine Production Farm, LPM Section, ICAR-Indian Veterinary Research Institute, Izatnagar, 243122, India.
| | - Sheikh Firdous Ahmad
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, 243122, India
| | - Amit Kumar
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, 243122, India
| | - Sakshi Vaishnav
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, 243122, India
| | - Shivani Singh
- Swine Production Farm, LPM Section, ICAR-Indian Veterinary Research Institute, Izatnagar, 243122, India
| | | | - Bharat Bhushan
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, 243122, India
| | - G K Gaur
- Swine Production Farm, LPM Section, ICAR-Indian Veterinary Research Institute, Izatnagar, 243122, India
- ADG Animal Production & Breeding, ICAR, New Delhi, 110001, India
| | - Triveni Dutt
- Indian Veterinary Research Institute, Izatnagar, 243122, India
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Li C, Wang X, Li H, Ahmed Z, Luo Y, Qin M, Yang Q, Long Z, Lei C, Yi K. Whole-genome resequencing reveals diversity and selective signals in the Wuxue goat. Anim Genet 2024. [PMID: 38806279 DOI: 10.1111/age.13437] [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: 10/10/2023] [Revised: 04/14/2024] [Accepted: 04/17/2024] [Indexed: 05/30/2024]
Abstract
Animal genetic resources are crucial for ensuring global food security. However, in recent years, a noticeable decline in the genetic diversity of livestock has occurred worldwide. This decline is pronounced in developing countries, where the management of these resources is insufficient. In the current study, we performed whole genome sequencing for 20 Wuxue (WX) and five Guizhou White (GW) goats. Additionally, we utilized the published genomes of 131 samples representing five different goat breeds from various regions in China. We investigated and compared the genetic diversity and selection signatures of WX goats. Whole genome sequencing analysis of the WX and GW populations yielded 120 425 063 SNPs, which resided primarily in intergenic and intron regions. Population genetic structure revealed that WX exhibited genetic resemblance to GW, Chengdu Brown, and Jintang Black and significant differentiation from the other goat breeds. In addition, three methods (nucleotide diversity, linkage disequilibrium decay, and runs of homozygosity) showed moderate genetic diversity in WX goats. We used nucleotide diversity and composite likelihood ratio methods to identify within-breed signatures of positive selection in WX goats. A total of 369 genes were identified using both detection methods, including genes related to reproduction (GRID2, ZNF276, TCF25, and SPIRE2), growth (HMGA2 and GJA3), and immunity (IRF3 and SRSF3). Overall, this study explored the adaptability of WX goats, shedding light on their genetic richness and potential to thrive in challenges posed by climatic changes and diseases. Further investigations are warranted to harness these insights to enhance more efficient and sustainable goat breeding initiatives.
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Affiliation(s)
- Chuanqing Li
- Hunan Institute of Animal and Veterinary Science, Changsha, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Xianglin Wang
- Animal Husbandry and Aquatic Products Affairs Center of Xiangxi Autonomous Prefecture, Jishou, China
| | - Haobang Li
- Hunan Institute of Animal and Veterinary Science, Changsha, China
| | - Zulfiqar Ahmed
- Faculty of Veterinary and Animal Sciences, University of Poonch Rawalakot, Rawalakot, Pakistan
| | - Yang Luo
- Hunan Institute of Animal and Veterinary Science, Changsha, China
| | - Mao Qin
- Animal Husbandry and Aquatic Products Affairs Center of Xiangxi Autonomous Prefecture, Jishou, China
| | - Qiong Yang
- Animal Husbandry and Aquatic Products Affairs Center of Xiangxi Autonomous Prefecture, Jishou, China
| | - Zhangcheng Long
- Animal Husbandry and Aquatic Products Affairs Center of Xiangxi Autonomous Prefecture, Jishou, 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, China
| | - Kangle Yi
- Hunan Institute of Animal and Veterinary Science, Changsha, China
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Jogi HR, Smaraki N, Nayak SS, Rajawat D, Kamothi DJ, Panigrahi M. Single cell RNA-seq: a novel tool to unravel virus-host interplay. Virusdisease 2024; 35:41-54. [PMID: 38817399 PMCID: PMC11133279 DOI: 10.1007/s13337-024-00859-w] [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: 12/07/2023] [Accepted: 02/12/2024] [Indexed: 06/01/2024] Open
Abstract
Over the last decade, single cell RNA sequencing (scRNA-seq) technology has caught the momentum of being a vital revolutionary tool to unfold cellular heterogeneity by high resolution assessment. It evades the inadequacies of conventional sequencing technology which was able to detect only average expression level among cell populations. In the era of twenty-first century, several epidemic and pandemic viruses have emerged. Being an intracellular entity, viruses totally rely on host. Complex virus-host dynamics result when the virus tend to obtain factors from host cell required for its replication and establishment of infection. As a prevailing tool, scRNA-seq is able to understand virus-host interplay by comprehensive transcriptome profiling. Because of technological and methodological advancement, this technology is capable to recognize viral genome and host cell response heterogeneity. Further development in analytical methods with multiomics approach and increased availability of accessible scRNA-seq datasets will improve the understanding of viral pathogenesis that can be helpful for development of novel antiviral therapeutic strategies.
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Affiliation(s)
- Harsh Rajeshbhai Jogi
- Division of Veterinary Microbiology, Indian Veterinary Research Institute, Izatnagar, Bareilly, UP 243122 India
| | - Nabaneeta Smaraki
- Division of Veterinary Microbiology, Indian Veterinary Research Institute, Izatnagar, Bareilly, UP 243122 India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP 243122 India
| | - Divya Rajawat
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP 243122 India
| | - Dhaval J. Kamothi
- Division of Pharmacology and Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP 243122 India
| | - Manjit Panigrahi
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP 243122 India
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Nayak SS, Panigrahi M, Rajawat D, Ghildiyal K, Sharma A, Jain K, Bhushan B, Dutt T. Deciphering climate resilience in Indian cattle breeds by selection signature analyses. Trop Anim Health Prod 2024; 56:46. [PMID: 38233536 DOI: 10.1007/s11250-023-03879-8] [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: 08/11/2023] [Accepted: 12/07/2023] [Indexed: 01/19/2024]
Abstract
The signature of selection is a crucial concept in evolutionary biology that refers to the pattern of genetic variation which arises in a population due to natural selection. In the context of climate adaptation, the signature of selection can reveal the genetic basis of adaptive traits that enable organisms to survive and thrive in changing environmental conditions. Breeds living in diverse agroecological zones exhibit genetic "footprints" within their genomes that mirror the influence of climate-induced selective pressures, subsequently impacting phenotypic variance. It is assumed that the genomes of animals residing in these regions have been altered through selection for various climatic adaptations. These regions are known as signatures of selection and can be identified using various summary statistics. We examined genotypic data from eight different cattle breeds (Gir, Hariana, Kankrej, Nelore, Ongole, Red Sindhi, Sahiwal, and Tharparkar) that are adapted to diverse regional climates. To identify selection signature regions in this investigation, we used four intra-population statistics: Tajima's D, CLR, iHS, and ROH. In this study, we utilized Bovine 50 K chip data and four genome scan techniques to assess the genetic regions of positive selection for high-temperature adaptation. We have also performed a genome-wide investigation of genetic diversity, inbreeding, and effective population size in our target dataset. We identified potential regions for selection that are likely to be caused by adverse climatic conditions. We observed many adaptation genes in several potential selection signature areas. These include genes like HSPB2, HSPB3, HSP20, HSP90AB1, HSF4, HSPA1B, CLPB, GAP43, MITF, and MCHR1 which have been reported in the cattle populations that live in varied climatic regions. The findings demonstrated that genes involved in disease resistance and thermotolerance were subjected to intense selection. The findings have implications for marker-assisted breeding, understanding the genetic landscape of climate-induced adaptation, putting breeding and conservation programs into action.
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Affiliation(s)
- Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India.
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Karan Jain
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
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Panigrahi M, Rajawat D, Nayak SS, Ghildiyal K, Sharma A, Jain K, Lei C, Bhushan B, Mishra BP, Dutt T. Landmarks in the history of selective sweeps. Anim Genet 2023; 54:667-688. [PMID: 37710403 DOI: 10.1111/age.13355] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 08/28/2023] [Indexed: 09/16/2023]
Abstract
Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next-generation sequencing, high-density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large-scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data.
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Affiliation(s)
- Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | | | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Karan Jain
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Bishnu Prasad Mishra
- Division of Animal Biotechnology, ICAR-National Bureau of Animal Genetic Resources, Karnal, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Bareilly, India
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Saravanan KA, Rajawat D, Kumar H, Nayak SS, Bhushan B, Dutt T, Panigrahi M. Signatures of selection in riverine buffalo populations revealed by genome-wide SNP data. Anim Biotechnol 2023; 34:3343-3354. [PMID: 36384399 DOI: 10.1080/10495398.2022.2145292] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The detection of selection signatures assists in understanding domestication, evolution, and the identification of genomic regions related to adaptation and production traits in buffaloes. The emergence of high-throughput technologies like Next Generation Sequencing and SNP genotyping had expanded our ability to detect these signatures of selection. In this study, we sought to identify signatures of selection in five buffalo populations (Brazilian Murrah, Bulgarian Murrah, Indian Murrah, Nili-Ravi, and Kundi) using Axiom Buffalo 90 K Genotyping Array data. Using seven different methodologies (Tajima's D, CLR, ROH, iHS, FST, FLK and hapFLK), we identified selection signatures in 374 genomic regions, spanning a total of 381 genes and 350 quantitative trait loci (QTLs). Among these, several candidate genes were associated with QTLs for milk production, reproduction, growth and carcass traits. The genes and QTLs reported in this study provide insight into selection signals shaping the genome of buffalo breeds. Our findings can aid in further genomic association studies, genomic prediction, and the implementation of breeding programmes in Indian buffaloes.
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Affiliation(s)
- K A Saravanan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
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Rajawat D, Panigrahi M, Nayak SS, Ghildiyal K, Sharma A, Kumar H, Parida S, Bhushan B, Gaur GK, Mishra BP, Dutt T. Uncovering genes underlying coat color variation in indigenous cattle breeds through genome-wide positive selection. Anim Biotechnol 2023; 34:3920-3933. [PMID: 37493405 DOI: 10.1080/10495398.2023.2240387] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
The identification of candidate genes related to pigmentation and under selective sweep provides insights into the genetic basis of pigmentation and the evolutionary forces that have shaped this variation. The selective sweep events in the genes responsible for normal coat color in Indian cattle groups are still unknown. To find coat color genes displaying signs of selective sweeps in the indigenous cattle, we compiled a list of candidate genes previously investigated for their association with coat color and pigmentation. After that, we performed a genome-wide scan of positive selection signatures using the BovineSNP50K Bead Chip in 187 individuals of seven indigenous breeds. We applied a wide range of methods to find evidence of selection, such as Tajima's D, CLR, iHS, varLD, ROH, and FST. We found a total of sixteen genes under selective sweep, that were involved in coat color and pigmentation physiology. These genes are CRIM1 in Gir, MC1R in Sahiwal, MYO5A, PMEL and POMC in Tharparkar, TYRP1, ERBB2, and ASIP in Red Sindhi, MITF, LOC789175, PAX3 and TYR in Ongole, and IRF2, SDR165 and, KIT in Nelore, ADAMTS19 in Hariana. These genes are related to melanin synthesis, the biology of melanocytes and melanosomes, and the migration and survival of melanocytes during development.
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Affiliation(s)
- Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Subhashree Parida
- Pharmacology and Toxicology Division, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - G K Gaur
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - B P Mishra
- Animal Biotechnology Division, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, Bareilly, India
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Saravanan KA, Panigrahi M, Kumar H, Nayak SS, Rajawat D, Bhushan B, Dutt T. Progress and future perspectives of livestock genomics in India: a mini review. Anim Biotechnol 2023; 34:1979-1987. [PMID: 35369840 DOI: 10.1080/10495398.2022.2056046] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
The field of genetics has evolved a lot after the emergence of molecular and advanced genomic technologies. The advent of Next Generation Sequencing, SNP genotyping platforms and simultaneous reduction in the cost of sequencing had opened the door to genomic research in farm animals. There are various applications of genomics in livestock, such as the use of genomic data: (i) to investigate genetic diversity and breed composition/population structure (ii) to identify genetic variants and QTLs related to economically important and ecological traits, genome-wide association studies (GWAS) and genomic signatures of selection; (iii) to enhance breeding programs by genomic selection. Compared to traditional methods, genomic selection is expected to improve selection response by increasing selection accuracy and reducing the generation interval due to early selection. Genomic selection (GS) in developed countries has led to rapid genetic gains, especially in dairy cattle, due to a well-established genetic evaluation system. Indian livestock system is still lagging behind developed nations in adopting these technologies. This review discusses the current status, challenges, and future perspectives of livestock genomics in India.
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Affiliation(s)
- K A Saravanan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Bareilly, UP, India
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Ryan CA, Berry DP, O’Brien A, Pabiou T, Purfield DC. Evaluating the use of statistical and machine learning methods for estimating breed composition of purebred and crossbred animals in thirteen cattle breeds using genomic information. Front Genet 2023; 14:1120312. [PMID: 37274789 PMCID: PMC10237237 DOI: 10.3389/fgene.2023.1120312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 05/03/2023] [Indexed: 06/07/2023] Open
Abstract
Introduction: The ability to accurately predict breed composition using genomic information has many potential uses including increasing the accuracy of genetic evaluations, optimising mating plans and as a parameter for genotype quality control. The objective of the present study was to use a database of genotyped purebred and crossbred cattle to compare breed composition predictions using a freely available software, Admixture, with those from a single nucleotide polymorphism Best Linear Unbiased Prediction (SNP-BLUP) approach; a supplementary objective was to determine the accuracy and general robustness of low-density genotype panels for predicting breed composition. Methods: All animals had genotype information on 49,213 autosomal single nucleotide polymorphism (SNPs). Thirteen breeds were included in the analysis and 500 purebred animals per breed were used to establish the breed training populations. Accuracy of breed composition prediction was determined using a separate validation population of 3,146 verified purebred and 4,330 two and three-way crossbred cattle. Results: When all 49,213 autosomal SNPs were used for breed prediction, a minimal absolute mean difference of 0.04 between Admixture vs. SNP-BLUP breed predictions was evident. For crossbreds, the average absolute difference in breed prediction estimates generated using SNP-BLUP and Admixture was 0.068 with a root mean square error of 0.08. Breed predictions from low-density SNP panels were generated using both SNP-BLUP and Admixture and compared to breed prediction estimates using all 49,213 SNPs (representing the gold standard). Breed composition estimates of crossbreds required more SNPs than predicting the breed composition of purebreds. SNP-BLUP required ≥3,000 SNPs to predict crossbred breed composition, but only 2,000 SNPs were required to predict purebred breed status. The absolute mean (standard deviation) difference across all panels <2,000 SNPs was 0.091 (0.054) and 0.315 (0.316) when predicting the breed composition of all animals using Admixture and SNP-BLUP, respectively compared to the gold standard prediction. Discussion: Nevertheless, a negligible absolute mean (standard deviation) difference of 0.009 (0.123) in breed prediction existed between SNP-BLUP and Admixture once ≥3,000 SNPs were considered, indicating that the prediction of breed composition could be readily integrated into SNP-BLUP pipelines used for genomic evaluations thereby avoiding the necessity for a stand-alone software.
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Affiliation(s)
- C. A. Ryan
- Teagasc, Co. Cork, Ireland
- Munster Technological University, Cork, Ireland
| | | | | | - T. Pabiou
- Irish Cattle Breeding Federation, Cork, Ireland
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Panigrahi M, Kumar H, Saravanan KA, Rajawat D, Sonejita Nayak S, Ghildiyal K, Kaisa K, Parida S, Bhushan B, Dutt T. Trajectory of livestock genomics in South Asia: A comprehensive review. Gene 2022; 843:146808. [PMID: 35973570 DOI: 10.1016/j.gene.2022.146808] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 08/08/2022] [Accepted: 08/10/2022] [Indexed: 02/07/2023]
Abstract
Livestock plays a central role in sustaining human livelihood in South Asia. There are numerous and distinct livestock species in South Asian countries. Several of them have experienced genetic development in recent years due to the application of genomic technologies and effective breeding programs. This review discusses genomic studies on cattle, buffalo, sheep, goat, pig, horse, camel, yak, mithun, and poultry. The frontiers covered in this review are genetic diversity, admixture studies, selection signature research, QTL discovery, genome-wide association studies (GWAS), and genomic selection. The review concludes with recommendations for South Asian livestock systems to increasingly leverage genomic technologies, based on the lessons learned from the numerous case studies. This paper aims to present a comprehensive analysis of the dichotomy in the South Asian livestock sector and argues that a realistic approach to genomics in livestock can ensure long-term genetic advancements.
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Affiliation(s)
- Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - K A Saravanan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Kaiho Kaisa
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Subhashree Parida
- Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
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Pal D, Panigrahi M, Chhotaray S, Kumar H, Nayak SS, Rajawat D, Parida S, Gaur GK, Dutt T, Bhushan B. Unraveling genetic admixture in the Indian crossbred cattle by different approaches using Bovine 50K BeadChip. Trop Anim Health Prod 2022; 54:135. [PMID: 35292868 DOI: 10.1007/s11250-022-03133-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 02/24/2022] [Indexed: 11/25/2022]
Abstract
With the upsurge of crossbreeding in India, the admixture levels are highly unpredictable in the composite breeds. Hence, in the present study, 72 Vrindavani animals were assessed for the level of admixture from their known ancestors that are Holstein-Friesian, Jersey, Brown Swiss, and Hariana, through three different software, namely, STRUCTURE, ADMIXTURE, and frappe. The genotype data for ancestral breeds were obtained from a public repository, i.e., DRYAD. The Frieswal crossbred cattle along with ancestral breeds like Holstein-Friesian and Sahiwal were also investigated for the level of admixture with the help of the above-mentioned software. The Frieswal population was found to comprise an average of 62.49, 61.12, and 61.21% of Holstein-Friesian and 37.50, 38.88, and 38.80% of Sahiwal estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. The Vrindavani population was found to consist of on average 39.5, 42.4, and 42.3% of Holstein-Friesian; 22.9, 22.3, and 21.7% of Jersey; 10.7, 10.6, and 11.9% of Brown Swiss; and 26.9, 24.7, and 24.1% of Hariana blood estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. A greater degree of variation was noted in the results from STRUCTURE vs. frappe, STRUCTURE vs. ADMIXTURE than in ADMIXTURE vs. frappe. From this study, we conclude that the admixture analysis based on a single software should be validated through the use of many different approaches for better prediction of admixture levels.
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Affiliation(s)
- Dhan Pal
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243122, India
| | - Manjit Panigrahi
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243122, India.
| | - Supriya Chhotaray
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243122, India
| | - Harshit Kumar
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243122, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243122, India
| | - Divya Rajawat
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243122, India
| | - Subhashree Parida
- Division of Veterinary Pharmacology & Toxicology, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - G K Gaur
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243122, India
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Panigrahi M, Kumar H, Nayak SS, Rajawat D, Parida S, Bhushan B, Sharma A, Dutt T. Molecular characterization of CRBR2 fragment of TLR4 gene in association with mastitis in Vrindavani cattle. Microb Pathog 2022; 165:105483. [DOI: 10.1016/j.micpath.2022.105483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 02/24/2022] [Accepted: 03/10/2022] [Indexed: 01/02/2023]
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Kumar H, Panigrahi M, Saravanan KA, Parida S, Bhushan B, Gaur GK, Dutt T, Mishra BP, Singh RK. SNPs with intermediate minor allele frequencies facilitate accurate breed assignment of Indian Tharparkar cattle. Gene 2021; 777:145473. [PMID: 33549713 DOI: 10.1016/j.gene.2021.145473] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 01/23/2021] [Accepted: 01/28/2021] [Indexed: 10/22/2022]
Abstract
Tharparkar cattle breed is widely known for its superior milch quality and hardiness attributes. This study aimed to develop an ultra-low density breed-specific single nucleotide polymorphism (SNP) genotype panel to accurately quantify Tharparkar populations in biological samples. In this study, we selected and genotyped 72 Tharparkar animals randomly from Cattle & Buffalo Farm of IVRI, India. This Bovine SNP50 BeadChip genotypic datum was merged with the online data from six indigenous cattle breeds and five taurine breeds. Here, we used a combination of pre-selection statistics and the MAF-LD method developed in our laboratory to analyze the genotypic data obtained from 317 individuals of 12 distinct breeds to identify breed-informative SNPs for the selection of Tharparkar cattle. This methodology identified 63 unique Tharparkar-specific SNPs near intermediate gene frequencies. We report several informative SNPs in genes/QTL regions affecting phenotypes or production traits that might differentiate the Tharparkar breed.
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Affiliation(s)
- Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
| | - K A Saravanan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Subhashree Parida
- Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - G K Gaur
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - B P Mishra
- Division of Animal Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - R K Singh
- Division of Animal Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
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Saravanan KA, Panigrahi M, Kumar H, Parida S, Bhushan B, Gaur GK, Kumar P, Dutt T, Mishra BP, Singh RK. Genome-wide assessment of genetic diversity, linkage disequilibrium and haplotype block structure in Tharparkar cattle breed of India. Anim Biotechnol 2020; 33:297-311. [PMID: 32730141 DOI: 10.1080/10495398.2020.1796696] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Knowledge about genetic diversity is very essential for the management and sustainable utilization of livestock genetic resources. In this study, we presented a comprehensive genome-wide analysis of genetic diversity, ROH, inbreeding, linkage disequilibrium, effective population size and haplotype block structure in Tharparkar cattle of India. A total of 24 Tharparkar animals used in this study were genotyped with Illumina BovineSNP50 array. After quality control, 22,825 biallelic SNPs were retained, which were in HWE, MAF > 0.05 and genotyping rate >90%. The overall mean observed (HO) and expected heterozygosity (HE) were 0.339 ± 0.156 and 0.325 ± 0.129, respectively. The average minor allele frequency was 0.234 with a standard deviation of ± 0.131. We identified a total of 1832 ROH segments and the highest autosomal coverage of 13.87% was observed on chromosome 23. The genomic inbreeding coefficients estimates by FROH, FHOM, FGRM and FUNI were 0.0589, 0.0215, 0.0532 and 0.0160 respectively. The overall mean linkage disequilibrium (LD) for a total of 133,532 pairwise SNPs measured by D' and r2 was 0.6452 and 0.1339, respectively. In addition, we observed a gradual decline in effective population size over the past generations.
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Affiliation(s)
- K A Saravanan
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Manjit Panigrahi
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Harshit Kumar
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Subhashree Parida
- Division of Pharmacology and Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Bharat Bhushan
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - G K Gaur
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Pushpendra Kumar
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - B P Mishra
- Division of Animal Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - R K Singh
- Division of Animal Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
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