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Yang J, Wang DF, Huang JH, Zhu QH, Luo LY, Lu R, Xie XL, Salehian-Dehkordi H, Esmailizadeh A, Liu GE, Li MH. Structural variant landscapes reveal convergent signatures of evolution in sheep and goats. Genome Biol 2024; 25:148. [PMID: 38845023 PMCID: PMC11155191 DOI: 10.1186/s13059-024-03288-6] [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: 01/17/2023] [Accepted: 05/21/2024] [Indexed: 06/10/2024] Open
Abstract
BACKGROUND Sheep and goats have undergone domestication and improvement to produce similar phenotypes, which have been greatly impacted by structural variants (SVs). Here, we report a high-quality chromosome-level reference genome of Asiatic mouflon, and implement a comprehensive analysis of SVs in 897 genomes of worldwide wild and domestic populations of sheep and goats to reveal genetic signatures underlying convergent evolution. RESULTS We characterize the SV landscapes in terms of genetic diversity, chromosomal distribution and their links with genes, QTLs and transposable elements, and examine their impacts on regulatory elements. We identify several novel SVs and annotate corresponding genes (e.g., BMPR1B, BMPR2, RALYL, COL21A1, and LRP1B) associated with important production traits such as fertility, meat and milk production, and wool/hair fineness. We detect signatures of selection involving the parallel evolution of orthologous SV-associated genes during domestication, local environmental adaptation, and improvement. In particular, we find that fecundity traits experienced convergent selection targeting the gene BMPR1B, with the DEL00067921 deletion explaining ~10.4% of the phenotypic variation observed in goats. CONCLUSIONS Our results provide new insights into the convergent evolution of SVs and serve as a rich resource for the future improvement of sheep, goats, and related livestock.
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Affiliation(s)
- Ji Yang
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Dong-Feng Wang
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Jia-Hui Huang
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Qiang-Hui Zhu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Ling-Yun Luo
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Ran Lu
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xing-Long Xie
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Hosein Salehian-Dehkordi
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, 76169-133, Iran
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Meng-Hua Li
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China.
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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Liu X, Chen W, Huang B, Wang X, Peng Y, Zhang X, Chai W, Khan MZ, Wang C. Advancements in copy number variation screening in herbivorous livestock genomes and their association with phenotypic traits. Front Vet Sci 2024; 10:1334434. [PMID: 38274664 PMCID: PMC10808162 DOI: 10.3389/fvets.2023.1334434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/27/2023] [Indexed: 01/27/2024] Open
Abstract
Copy number variations (CNVs) have garnered increasing attention within the realm of genetics due to their prevalence in human, animal, and plant genomes. These structural genetic variations have demonstrated associations with a broad spectrum of phenotypic diversity, economic traits, environmental adaptations, epidemics, and other essential aspects of both plants and animals. Furthermore, CNVs exhibit extensive sequence variability and encompass a wide array of genomes. The advancement and maturity of microarray and sequencing technologies have catalyzed a surge in research endeavors pertaining to CNVs. This is particularly prominent in the context of livestock breeding, where molecular markers have gained prominence as a valuable tool in comparison to traditional breeding methods. In light of these developments, a contemporary and comprehensive review of existing studies on CNVs becomes imperative. This review serves the purpose of providing a brief elucidation of the fundamental concepts underlying CNVs, their mutational mechanisms, and the diverse array of detection methods employed to identify these structural variations within genomes. Furthermore, it seeks to systematically analyze the recent advancements and findings within the field of CNV research, specifically within the genomes of herbivorous livestock species, including cattle, sheep, horses, and donkeys. The review also highlighted the role of CNVs in shaping various phenotypic traits including growth traits, reproductive traits, pigmentation and disease resistance etc., in herbivorous livestock. The main goal of this review is to furnish readers with an up-to-date compilation of knowledge regarding CNVs in herbivorous livestock genomes. By integrating the latest research findings and insights, it is anticipated that this review will not only offer pertinent information but also stimulate future investigations into the realm of CNVs in livestock. In doing so, it endeavors to contribute to the enhancement of breeding strategies, genomic selection, and the overall improvement of herbivorous livestock production and resistance to diseases.
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Affiliation(s)
| | | | | | | | | | | | | | - Muhammad Zahoor Khan
- Liaocheng Research Institute of Donkey High-Efficiency Breeding, Liaocheng University, Liaocheng, China
| | - Changfa Wang
- Liaocheng Research Institute of Donkey High-Efficiency Breeding, Liaocheng University, Liaocheng, China
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Xu J, Zhang W, Zhang P, Sun W, Han Y, Li L. A comprehensive analysis of copy number variations in diverse apple populations. BMC Genomics 2023; 24:256. [PMID: 37170226 PMCID: PMC10176694 DOI: 10.1186/s12864-023-09347-9] [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: 03/30/2022] [Accepted: 08/16/2022] [Indexed: 05/13/2023] Open
Abstract
BACKGROUND As an important source of genetic variation, copy number variation (CNV) can alter the dosage of DNA segments, which in turn may affect gene expression level and phenotype. However, our knowledge of CNV in apple is still limited. Here, we obtained high-confidence CNVs and investigated their functional impact based on genome resequencing data of two apple populations, cultivars and wild relatives. RESULTS In this study, we identified 914,610 CNVs comprising 14,839 CNV regions (CNVRs) from 346 apple accessions, including 289 cultivars and 57 wild relatives. CNVRs summed to 71.19 Mb, accounting for 10.03% of the apple genome. Under the low linkage disequilibrium (LD) with nearby SNPs, they could also accurately reflect the population structure of apple independent of SNPs. Furthermore, A total of 3,621 genes were covered by CNVRs and functionally involved in biological processes such as defense response, reproduction and metabolic processes. In addition, the population differentiation index ([Formula: see text]) analysis between cultivars and wild relatives revealed 127 CN-differentiated genes, which may contribute to trait differences in these two populations. CONCLUSIONS This study was based on identification of CNVs from 346 diverse apple accessions, which to our knowledge was the largest dataset for CNV analysis in apple. Our work presented the first comprehensive CNV map and provided valuable resources for understanding genomic variations in apple.
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Affiliation(s)
- Jinsheng Xu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Weihan Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Ping Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Weicheng Sun
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Yuepeng Han
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Wuhan, 430074, China.
- Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
| | - Li Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China.
- Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
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Davoudi P, Do DN, Rathgeber B, Colombo SM, Sargolzaei M, Plastow G, Wang Z, Karimi K, Hu G, Valipour S, Miar Y. Genome-wide detection of copy number variation in American mink using whole-genome sequencing. BMC Genomics 2022; 23:649. [PMID: 36096727 PMCID: PMC9468235 DOI: 10.1186/s12864-022-08874-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 09/05/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Copy number variations (CNVs) represent a major source of genetic diversity and contribute to the phenotypic variation of economically important traits in livestock species. In this study, we report the first genome-wide CNV analysis of American mink using whole-genome sequence data from 100 individuals. The analyses were performed by three complementary software programs including CNVpytor, DELLY and Manta. RESULTS A total of 164,733 CNVs (144,517 deletions and 20,216 duplications) were identified representing 5378 CNV regions (CNVR) after merging overlapping CNVs, covering 47.3 Mb (1.9%) of the mink autosomal genome. Gene Ontology and KEGG pathway enrichment analyses of 1391 genes that overlapped CNVR revealed potential role of CNVs in a wide range of biological, molecular and cellular functions, e.g., pathways related to growth (regulation of actin cytoskeleton, and cAMP signaling pathways), behavior (axon guidance, circadian entrainment, and glutamatergic synapse), lipid metabolism (phospholipid binding, sphingolipid metabolism and regulation of lipolysis in adipocytes), and immune response (Wnt signaling, Fc receptor signaling, and GTPase regulator activity pathways). Furthermore, several CNVR-harbored genes associated with fur characteristics and development (MYO5A, RAB27B, FGF12, SLC7A11, EXOC2), and immune system processes (SWAP70, FYN, ORAI1, TRPM2, and FOXO3). CONCLUSIONS This study presents the first genome-wide CNV map of American mink. We identified 5378 CNVR in the mink genome and investigated genes that overlapped with CNVR. The results suggest potential links with mink behaviour as well as their possible impact on fur quality and immune response. Overall, the results provide new resources for mink genome analysis, serving as a guideline for future investigations in which genomic structural variations are present.
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Affiliation(s)
- Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Bruce Rathgeber
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Stefanie M Colombo
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Mehdi Sargolzaei
- Department of Pathobiology, University of Guelph, Guelph, ON, Canada
- Select Sires Inc., Plain City, OH, USA
| | - Graham Plastow
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Zhiquan Wang
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Karim Karimi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Guoyu Hu
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Shafagh Valipour
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada.
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Zhang S, Yao Z, Li X, Zhang Z, Liu X, Yang P, Chen N, Xia X, Lyu S, Shi Q, Wang E, Ru B, Jiang Y, Lei C, Chen H, Huang Y. Assessing genomic diversity and signatures of selection in Pinan cattle using whole-genome sequencing data. BMC Genomics 2022; 23:460. [PMID: 35729510 PMCID: PMC9215082 DOI: 10.1186/s12864-022-08645-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 05/10/2022] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Crossbreeding is an important way to improve production beef cattle performance. Pinan cattle is a new hybrid cattle obtained from crossing Piedmontese bulls with Nanyang cows. After more than 30 years of cross-breeding, Pinan cattle show a variety of excellent characteristics, including fast growth, early onset of puberty, and good meat quality. In this study, we analyzed the genetic diversity, population structure, and genomic region under the selection of Pinan cattle based on whole-genome sequencing data of 30 Pinan cattle and 169 published cattle genomic data worldwide. RESULTS: Estimating ancestry composition analysis showed that the composition proportions for our Pinan cattle were mainly Piedmontese and a small amount of Nanyang cattle. The analyses of nucleotide diversity and linkage disequilibrium decay indicated that the genomic diversity of Pinan cattle was higher than that of European cattle and lower than that of Chinese indigenous cattle. De-correlated composite of multiple selection signals, which combines four different statistics including θπ, CLR, FST, and XP-EHH, was computed to detect the signatures of selection in the Pinan cattle genome. A total of 83 genes were identified, affecting many economically important traits. Functional annotation revealed that these selected genes were related to immune (BOLA-DQA2, BOLA-DQB, LSM14A, SEC13, and NAALADL2), growth traits (CYP4A11, RPL26, and MYH10), embryo development (REV3L, NT5E, CDX2, KDM6B, and ADAMTS9), hornless traits (C1H21orf62), and climate adaptation (ANTXR2). CONCLUSION In this paper, we elucidated the genomic characteristics, ancestry composition, and selective signals related to important economic traits in Pinan cattle. These results will provide the basis for further genetic improvement of Pinan cattle and reference for other hybrid cattle related studies.
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Affiliation(s)
- Shunjin Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, No. 22 Xinong Road, Yangling Shaanxi, 712100, China
| | - Zhi Yao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, No. 22 Xinong Road, Yangling Shaanxi, 712100, China
| | - Xinmiao Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, No. 22 Xinong Road, Yangling Shaanxi, 712100, China
| | - Zijing Zhang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou Henan, 450002, China
| | - Xian Liu
- Henan Provincial Animal Husbandry General Station, Zhengzhou Henan, 450008, China
| | - Peng Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, No. 22 Xinong Road, 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, No. 22 Xinong Road, Yangling Shaanxi, 712100, China
| | - Xiaoting Xia
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, No. 22 Xinong Road, Yangling Shaanxi, 712100, China
| | - Shijie Lyu
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou Henan, 450002, China
| | - Qiaoting Shi
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou Henan, 450002, China
| | - Eryao Wang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou Henan, 450002, China
| | - Baorui Ru
- Henan Provincial Animal Husbandry General Station, Zhengzhou Henan, 450008, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, No. 22 Xinong Road, 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, No. 22 Xinong Road, 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, No. 22 Xinong Road, Yangling Shaanxi, 712100, China
| | - Yongzhen Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, No. 22 Xinong Road, Yangling Shaanxi, 712100, China.
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