1
|
Xu S, Akhatayeva Z, Liu J, Feng X, Yu Y, Badaoui B, Esmailizadeh A, Kantanen J, Amills M, Lenstra JA, Johansson AM, Coltman DW, Liu GE, Curik I, Orozco-terWengel P, Paiva SR, Zinovieva NA, Zhang L, Yang J, Liu Z, Wang Y, Yu Y, Li M. Genetic advancements and future directions in ruminant livestock breeding: from reference genomes to multiomics innovations. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-024-2744-4. [PMID: 39609363 DOI: 10.1007/s11427-024-2744-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Accepted: 09/24/2024] [Indexed: 11/30/2024]
Abstract
Ruminant livestock provide a rich source of products, such as meat, milk, and wool, and play a critical role in global food security and nutrition. Over the past few decades, genomic studies of ruminant livestock have provided valuable insights into their domestication and the genetic basis of economically important traits, facilitating the breeding of elite varieties. In this review, we summarize the main advancements for domestic ruminants in reference genome assemblies, population genomics, and the identification of functional genes or variants for phenotypic traits. These traits include meat and carcass quality, reproduction, milk production, feed efficiency, wool and cashmere yield, horn development, tail type, coat color, environmental adaptation, and disease resistance. Functional genomic research is entering a new era with the advancements of graphical pangenomics and telomere-to-telomere (T2T) gap-free genome assembly. These advancements promise to improve our understanding of domestication and the molecular mechanisms underlying economically important traits in ruminant livestock. Finally, we provide new perspectives and future directions for genomic research on ruminant genomes. We suggest how ever-increasing multiomics datasets will facilitate future studies and molecular breeding in livestock, including the potential to uncover novel genetic mechanisms underlying phenotypic traits, to enable more accurate genomic prediction models, and to accelerate genetic improvement programs.
Collapse
Affiliation(s)
- Songsong Xu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Zhanerke Akhatayeva
- Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot, 010010, China
| | - Jiaxin Liu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xueyan Feng
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yi Yu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Bouabid Badaoui
- Laboratory of Biodiversity, Ecology and Genome, Department of Biology, Faculty of Sciences Rabat, Mohammed V University, Rabat, 10106, Morocco
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, 76169-133, Iran
| | - Juha Kantanen
- Production Systems, Natural Resources Institute Finland (Luke), Jokioinen, FI-31600, Finland
| | - Marcel Amills
- Department of Animal Genetics, Center for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus de la Universitat Autónoma de Barcelona, Bellaterra, 08193, Spain
- Departament de Ciència Animal i dels Aliments, Universitat Autónoma de Barcelona, Bellaterra, 08193, Spain
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, 3584, The Netherlands
| | - Anna M Johansson
- Department of Animal Breeding and Genetics, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Uppsala, 75007, Sweden
| | - David W Coltman
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada
- Department of Biology, Western University, London, Ontario, N6A 5B7, Canada
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Ino Curik
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Zagreb, 10000, Croatia
- Institute of Animal Sciences, Hungarian University of Agriculture and Life Sciences (MATE), Kaposvár, 7400, Hungary
| | | | - Samuel R Paiva
- Embrapa Genetic Resources and Biotechnology, Laboratory of Animal Genetics, Brasília, Federal District, 70770917, Brazil
| | - Natalia A Zinovieva
- L.K. Ernst Federal Science Center for Animal Husbandry, Moscow Region, Podolsk, 142132, Russian Federation
| | - Linwei Zhang
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Ji Yang
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Zhihong Liu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Yachun Wang
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Ying Yu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Menghua Li
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
- Sanya Institute of China Agricultural University, Sanya, 572024, China.
| |
Collapse
|
2
|
Fang B, Edwards SV. Fitness consequences of structural variation inferred from a House Finch pangenome. Proc Natl Acad Sci U S A 2024; 121:e2409943121. [PMID: 39531493 PMCID: PMC11588099 DOI: 10.1073/pnas.2409943121] [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: 05/17/2024] [Accepted: 10/03/2024] [Indexed: 11/16/2024] Open
Abstract
Genomic structural variants (SVs) play a crucial role in adaptive evolution, yet their average fitness effects and characterization with pangenome tools are understudied in wild animal populations. We constructed a pangenome for House Finches (Haemorhous mexicanus), a model for studies of host-pathogen coevolution, using long-read sequence data on 16 individuals (32 de novo-assembled haplotypes) and one outgroup. We identified 887,118 SVs larger than 50 base pairs, mostly (60%) involving repetitive elements, with reduced SV diversity in the eastern US as a result of its introduction by humans. The distribution of fitness effects of genome-wide SVs was estimated using maximum likelihood approaches and revealed that SVs in both coding and noncoding regions were on average more deleterious than smaller indels or single nucleotide polymorphisms. The reference-free pangenome facilitated identification of a > 10-My-old, 11-megabase-long pericentric inversion on chromosome 1. We found that the genotype frequencies of the inversion, estimated from 135 birds widely sampled temporally and geographically, increased steadily over the 25 y since House Finches were first exposed to the bacterial pathogen Mycoplasma gallisepticum and showed signatures of balancing selection, capturing genes related to immunity and telomerase activity. We also observed shorter telomeres in populations with a greater number of years exposure to Mycoplasma. Our study illustrates the utility of long-read sequencing and pangenome methods for understanding wild animal populations, estimating fitness effects of genome-wide SVs, and advancing our understanding of adaptive evolution through structural variation.
Collapse
Affiliation(s)
- Bohao Fang
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA02138
- Museum of Comparative Zoology, Harvard University, Cambridge, MA02138
| | - Scott V. Edwards
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA02138
- Museum of Comparative Zoology, Harvard University, Cambridge, MA02138
| |
Collapse
|
3
|
Chen Y, Khan MZ, Wang X, Liang H, Ren W, Kou X, Liu X, Chen W, Peng Y, Wang C. Structural variations in livestock genomes and their associations with phenotypic traits: a review. Front Vet Sci 2024; 11:1416220. [PMID: 39600883 PMCID: PMC11588642 DOI: 10.3389/fvets.2024.1416220] [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: 04/12/2024] [Accepted: 10/29/2024] [Indexed: 11/29/2024] Open
Abstract
Genomic structural variation (SV) refers to differences in gene sequences between individuals on a genomic scale. It is widely distributed in the genome, primarily in the form of insertions, deletions, duplications, inversions, and translocations. Due to its characterization by long segments and large coverage, SVs significantly impact the genetic characteristics and production performance of livestock, playing a crucial role in studying breed diversity, biological evolution, and disease correlation. Research on SVs contributes to an enhanced understanding of chromosome function and genetic characteristics and is important for understanding hereditary diseases mechanisms. In this article, we review the concept, classification, main formation mechanisms, detection methods, and advancement of research on SVs in the genomes of cattle, buffalo, equine, sheep, and goats, aiming to reveal the genetic basis of differences in phenotypic traits and adaptive genetic mechanisms through genomic research, which will provide a theoretical basis for better understanding and utilizing the genetic resources of herbivorous livestock.
Collapse
Affiliation(s)
| | - Muhammad Zahoor Khan
- College of Agronomy and Agricultural Engineering Liaocheng University, Liaocheng, China
| | | | | | | | | | | | | | - Yongdong Peng
- College of Agronomy and Agricultural Engineering Liaocheng University, Liaocheng, China
| | - Changfa Wang
- College of Agronomy and Agricultural Engineering Liaocheng University, Liaocheng, China
| |
Collapse
|
4
|
Heumos S, Heuer ML, Hanssen F, Heumos L, Guarracino A, Heringer P, Ehmele P, Prins P, Garrison E, Nahnsen S. Cluster-efficient pangenome graph construction with nf-core/pangenome. Bioinformatics 2024; 40:btae609. [PMID: 39400346 PMCID: PMC11568064 DOI: 10.1093/bioinformatics/btae609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 09/16/2024] [Accepted: 10/10/2024] [Indexed: 10/15/2024] Open
Abstract
MOTIVATION Pangenome graphs offer a comprehensive way of capturing genomic variability across multiple genomes. However, current construction methods often introduce biases, excluding complex sequences or relying on references. The PanGenome Graph Builder (PGGB) addresses these issues. To date, though, there is no state-of-the-art pipeline allowing for easy deployment, efficient and dynamic use of available resources, and scalable usage at the same time. RESULTS To overcome these limitations, we present nf-core/pangenome, a reference-unbiased approach implemented in Nextflow following nf-core's best practices. Leveraging biocontainers ensures portability and seamless deployment in High-Performance Computing (HPC) environments. Unlike PGGB, nf-core/pangenome distributes alignments across cluster nodes, enabling scalability. Demonstrating its efficiency, we constructed pangenome graphs for 1000 human chromosome 19 haplotypes and 2146 Escherichia coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions. AVAILABILITY AND IMPLEMENTATION nf-core/pangenome is released under the MIT open-source license, available on GitHub and Zenodo, with documentation accessible at https://nf-co.re/pangenome/docs/usage.
Collapse
Affiliation(s)
- Simon Heumos
- Quantitative Biology Center (QBiC) Tübingen, University of Tübingen, Tübingen, 72076, Germany
- Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen, 72076, Germany
- M3 Research Center, University Hospital Tübingen, Tübingen, 72076, Germany
- Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard-Karls University of Tübingen, Tübingen, 72076, Germany
| | - Michael L Heuer
- University of California, Berkeley, Berkeley, CA 94720, United States
| | - Friederike Hanssen
- Quantitative Biology Center (QBiC) Tübingen, University of Tübingen, Tübingen, 72076, Germany
- Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen, 72076, Germany
- M3 Research Center, University Hospital Tübingen, Tübingen, 72076, Germany
- Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard-Karls University of Tübingen, Tübingen, 72076, Germany
| | - Lukas Heumos
- Department of Computational Health, Institute of Computational Biology, Helmholtz Munich, Munich, 85764, Germany
- Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Zentrum Munich, Member of the German Center for Lung Research (DZL), Munich, 81377, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, 81377, Germany
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, United States
- Human Technopole, Milan 20157, Italy
| | - Peter Heringer
- Quantitative Biology Center (QBiC) Tübingen, University of Tübingen, Tübingen, 72076, Germany
- Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen, 72076, Germany
- M3 Research Center, University Hospital Tübingen, Tübingen, 72076, Germany
- Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard-Karls University of Tübingen, Tübingen, 72076, Germany
| | - Philipp Ehmele
- Department of Computational Health, Institute of Computational Biology, Helmholtz Munich, Munich, 85764, Germany
| | - Pjotr Prins
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, United States
| | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, United States
| | - Sven Nahnsen
- Quantitative Biology Center (QBiC) Tübingen, University of Tübingen, Tübingen, 72076, Germany
- Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen, 72076, Germany
- M3 Research Center, University Hospital Tübingen, Tübingen, 72076, Germany
- Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard-Karls University of Tübingen, Tübingen, 72076, Germany
| |
Collapse
|
5
|
Grant JR, Herman EK, Barlow LD, Miglior F, Schenkel FS, Baes CF, Stothard P. A large structural variant collection in Holstein cattle and associated database for variant discovery, characterization, and application. BMC Genomics 2024; 25:903. [PMID: 39350025 PMCID: PMC11440700 DOI: 10.1186/s12864-024-10812-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Accepted: 09/19/2024] [Indexed: 10/04/2024] Open
Abstract
BACKGROUND Structural variants (SVs) such as deletions, duplications, and insertions are known to contribute to phenotypic variation but remain challenging to identify and genotype. A more complete, accessible, and assessable collection of SVs will assist efforts to study SV function in cattle and to incorporate SV genotyping into animal evaluation. RESULTS In this work we produced a large and deeply characterized collection of SVs in Holstein cattle using two popular SV callers (Manta and Smoove) and publicly available Illumina whole-genome sequence (WGS) read sets from 310 samples (290 male, 20 female, mean 20X coverage). Manta and Smoove identified 31 K and 68 K SVs, respectively. In total the SVs cover 5% (Manta) and 6% (Smoove) of the reference genome, in contrast to the 1% impacted by SNPs and indels. SV genotypes from each caller were confirmed to accurately recapitulate animal relationships estimated using WGS SNP genotypes from the same dataset, with Manta genotypes outperforming Smoove, and deletions outperforming duplications. To support efforts to link the SVs to phenotypic variation, overlapping and tag SNPs were identified for each SV, using genotype sets extracted from the WGS results corresponding to two bovine SNP chips (BovineSNP50 and BovineHD). 9% (Manta) and 11% (Smoove) of the SVs were found to have overlapping BovineHD panel SNPs, while 21% (Manta) and 9% (Smoove) have BovineHD panel tag SNPs. A custom interactive database ( https://svdb-dc.pslab.ca ) containing the identified sequence variants with extensive annotations, gene feature information, and BAM file content for all SVs was created to enable the evaluation and prioritization of SVs for further study. Illustrative examples involving the genes POPDC3, ORM1, G2E3, FANCI, TFB1M, FOXC2, N4BP2, GSTA3, and COPA show how this resource can be used to find well-supported genic SVs, determine SV breakpoints, design genotyping approaches, and identify processed pseudogenes masquerading as deletions. CONCLUSIONS The resources developed through this study can be used to explore sequence variation in Holstein cattle and to develop strategies for studying SVs of interest. The lack of overlapping and tag SNPs from commonly used SNP chips for most of the SVs suggests that other genotyping approaches will be needed (for example direct genotyping) to understand their potential contributions to phenotype. The included SV genotype assessments point to challenges in characterizing SVs, especially duplications, using short-read data and support ongoing efforts to better characterize cattle genomes through long-read sequencing. Lastly, the identification of previously known functional SVs and additional CDS-overlapping SVs supports the phenotypic relevance of this dataset.
Collapse
Affiliation(s)
- Jason R Grant
- Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Emily K Herman
- Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Lael D Barlow
- Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Filippo Miglior
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
- , Lactanet, Guelph, ON, Canada
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Christine F Baes
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Paul Stothard
- Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| |
Collapse
|
6
|
Ghavi Hossein-Zadeh N. An overview of recent technological developments in bovine genomics. Vet Anim Sci 2024; 25:100382. [PMID: 39166173 PMCID: PMC11334705 DOI: 10.1016/j.vas.2024.100382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/22/2024] Open
Abstract
Cattle are regarded as highly valuable animals because of their milk, beef, dung, fur, and ability to draft. The scientific community has tried a number of strategies to improve the genetic makeup of bovine germplasm. To ensure higher returns for the dairy and beef industries, researchers face their greatest challenge in improving commercially important traits. One of the biggest developments in the last few decades in the creation of instruments for cattle genetic improvement is the discovery of the genome. Breeding livestock is being revolutionized by genomic selection made possible by the availability of medium- and high-density single nucleotide polymorphism (SNP) arrays coupled with sophisticated statistical techniques. It is becoming easier to access high-dimensional genomic data in cattle. Continuously declining genotyping costs and an increase in services that use genomic data to increase return on investment have both made a significant contribution to this. The field of genomics has come a long way thanks to groundbreaking discoveries such as radiation-hybrid mapping, in situ hybridization, synteny analysis, somatic cell genetics, cytogenetic maps, molecular markers, association studies for quantitative trait loci, high-throughput SNP genotyping, whole-genome shotgun sequencing to whole-genome mapping, and genome editing. These advancements have had a significant positive impact on the field of cattle genomics. This manuscript aimed to review recent advances in genomic technologies for cattle breeding and future prospects in this field.
Collapse
Affiliation(s)
- Navid Ghavi Hossein-Zadeh
- Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, 41635-1314, Iran
| |
Collapse
|
7
|
Blommaert J, Sandoval-Castillo J, Beheregaray LB, Wellenreuther M. Peering into the gaps: Long-read sequencing illuminates structural variants and genomic evolution in the Australasian snapper. Genomics 2024; 116:110929. [PMID: 39216708 DOI: 10.1016/j.ygeno.2024.110929] [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: 05/05/2024] [Revised: 08/25/2024] [Accepted: 08/26/2024] [Indexed: 09/04/2024]
Abstract
Even before genome sequencing, genetic resources have supported species management and breeding programs. Current technologies, such as long-read sequencing, resolve complex genomic regions, like those rich in repeats or high in GC content. Improved genome contiguity enhances accuracy in identifying structural variants (SVs) and transposable elements (TEs). We present an improved genome assembly and SV catalogue for the Australasian snapper (Chrysophrys auratus). The new assembly is more contiguous, allowing for putative identification of 14 centromeres and transfer of 26,115 gene annotations from yellowfin seabream. Compared to the previous assembly, 35,000 additional SVs, including larger and more complex rearrangements, were annotated. SVs and TEs exhibit a distribution pattern skewed towards chromosome ends, likely influenced by recombination. Some SVs overlap with growth-related genes, underscoring their significance. This upgraded genome serves as a foundation for studying natural and artificial selection, offers a reference for related species, and sheds light on genome dynamics shaped by evolution.
Collapse
Affiliation(s)
- Julie Blommaert
- The New Zealand Institute for Plant and Food Research, Nelson, New Zealand.
| | - Jonathan Sandoval-Castillo
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Luciano B Beheregaray
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Maren Wellenreuther
- The New Zealand Institute for Plant and Food Research, Nelson, New Zealand; School of Biological Sciences, The University of Auckland, Auckland, New Zealand
| |
Collapse
|
8
|
Gao Z, Lu Y, Li M, Chong Y, Hong J, Wu J, Wu D, Xi D, Deng W. Application of Pan-Omics Technologies in Research on Important Economic Traits for Ruminants. Int J Mol Sci 2024; 25:9271. [PMID: 39273219 PMCID: PMC11394796 DOI: 10.3390/ijms25179271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Revised: 08/23/2024] [Accepted: 08/26/2024] [Indexed: 09/15/2024] Open
Abstract
The economic significance of ruminants in agriculture underscores the need for advanced research methodologies to enhance their traits. This review aims to elucidate the transformative role of pan-omics technologies in ruminant research, focusing on their application in uncovering the genetic mechanisms underlying complex traits such as growth, reproduction, production performance, and rumen function. Pan-omics analysis not only helps in identifying key genes and their regulatory networks associated with important economic traits but also reveals the impact of environmental factors on trait expression. By integrating genomics, epigenomics, transcriptomics, metabolomics, and microbiomics, pan-omics enables a comprehensive analysis of the interplay between genetics and environmental factors, offering a holistic understanding of trait expression. We explore specific examples of economic traits where these technologies have been pivotal, highlighting key genes and regulatory networks identified through pan-omics approaches. Additionally, we trace the historical evolution of each omics field, detailing their progression from foundational discoveries to high-throughput platforms. This review provides a critical synthesis of recent advancements, offering new insights and practical recommendations for the application of pan-omics in the ruminant industry. The broader implications for modern animal husbandry are discussed, emphasizing the potential for these technologies to drive sustainable improvements in ruminant production systems.
Collapse
Affiliation(s)
- Zhendong Gao
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, Kunming 650201, China
| | - Ying Lu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Mengfei Li
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Yuqing Chong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Jieyun Hong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Jiao Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dongwang Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dongmei Xi
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Weidong Deng
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, Kunming 650201, China
| |
Collapse
|
9
|
Ben-Jemaa S, Boussaha M, Mandonnet N, Bardou P, Naves M. Uncovering structural variants in Creole cattle from Guadeloupe and their impact on environmental adaptation through whole genome sequencing. PLoS One 2024; 19:e0309411. [PMID: 39186744 PMCID: PMC11346954 DOI: 10.1371/journal.pone.0309411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 08/12/2024] [Indexed: 08/28/2024] Open
Abstract
Structural variants play an important role in evolutionary processes. Besides, they constitute a large source of inter individual genetic variation that might represent a major factor in the aetiology of complex, multifactorial traits. Their importance in adaptation is becoming increasingly evident in literature. Yet, the characterization of the genomic landscape of structural variants in local breeds remains scarce to date. Herein, we investigate patterns and gene annotation of structural variants in the Creole cattle from Guadeloupe breed using whole genome sequences from 23 bulls representative of the population. In total, we detected 32821 ascertained SV defining 15258 regions, representing ~ 17% of the Creole cattle genome. Among these, 6639 regions have not been previously reported in the Database of Genomic Variants archive. Average number of structural variants detected per individual in the studied population is in the same order of magnitude of that observed in indicine populations and higher than that reported in taurine breeds. We observe an important within-individual variability where approximately half of the detected structural variants have low frequency (MAF < 0.25). Most of the detected structural variants (55%) occurred in intergenic regions. Genic structural variants overlapped with 7793 genes and the predicted effect of most of them is ranked as "modifier". Among the structural variants that were predicted to have a high functional impact on the protein, a 5.5 Kb in length, highly frequent deletion on chromosome 2, affects ALPI, a gene associated with the interaction between gut microbiota and host immune system. The 6639 newly identified structural variants regions include three deletions and three duplications shared by more than 80% of individuals that are significantly enriched for genes related to tRNA threonylcarbamoyladenosine metabolic process, important for temperature adaptation in thermophilic organisms, therefore suggesting a potential role in the thermotolerance of Creole cattle from Guadeloupe cattle to tropical climate. Overall, highly frequent structural variants that are specific to the Creole cattle population encompass olfactory receptor and immunity genes as well as genes involved in muscle tone, muscle development and contraction. Beyond mapping and characterizing structural variants in the Creole cattle from Guadeloupe breed, this study provides valuable information for a better understanding of the potential role of chromosomal rearrangements in adaptive traits in cattle.
Collapse
Affiliation(s)
- Slim Ben-Jemaa
- INRAE, ASSET, 97170, Petit-Bourg, France
- Institut National de la Recherche Agronomique de Tunisie, Laboratoire des Productions Animales et Fourragères, Université de Carthage, 2049, Ariana, Tunisia
| | - Mekki Boussaha
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | | | - Philippe Bardou
- GenPhySE, Université de Toulouse, INRA, Ecole Nationale Vétérinaire de Toulouse (ENVT), 31320, Castanet-Tolosan, France
- Sigenae, INRAE, 31320, Castanet-Tolosan, France
| | | |
Collapse
|
10
|
Cheng H, Lyu Y, Liu Z, Li C, Qu K, Li S, Ahmed Z, Ma W, Qi X, Chen N, Lei C. A Whole-Genome Scan Revealed Genomic Features and Selection Footprints of Mengshan Cattle. Genes (Basel) 2024; 15:1113. [PMID: 39336704 PMCID: PMC11431585 DOI: 10.3390/genes15091113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 08/21/2024] [Accepted: 08/21/2024] [Indexed: 09/30/2024] Open
Abstract
(1) Background: Mengshan cattle from the Yimeng mountainous region in China stand out as a unique genetic resource, known for their adaptive traits and environmental resilience. However, these cattle are currently endangered and comprehensive genomic characterization remains largely unexplored. This study aims to address this gap by investigating the genomic features and selection signals in Mengshan cattle. (2) Methods: Utilizing whole-genome resequencing data from 122 cattle, including 37 newly sequenced Mengshan cattle, we investigated population structure, genetic diversity, and selection signals. (3) Results: Our analyses revealed that current Mengshan cattle primarily exhibit European taurine cattle ancestry, with distinct genetic characteristics indicative of adaptive traits. We identified candidate genes associated with immune response, growth traits, meat quality, and neurodevelopment, shedding light on the genomic features underlying the unique attributes of Mengshan cattle. Enrichment analysis highlighted pathways related to insulin secretion, calcium signaling, and dopamine synapse, further elucidating the genetic basis of their phenotypic traits. (4) Conclusions: Our results provide valuable insights for further research and conservation efforts aimed at preserving this endangered genetic resource. This study enhances the understanding of population genetics and underscores the importance of genomic research in informing genetic resources and conservation initiatives for indigenous cattle breeds.
Collapse
Affiliation(s)
- Haijian Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (H.C.); (Y.L.); (Z.L.); (C.L.); (S.L.); (N.C.)
- Shandong Key Lab of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan 250100, China
| | - Yang Lyu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (H.C.); (Y.L.); (Z.L.); (C.L.); (S.L.); (N.C.)
| | - Ziao Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (H.C.); (Y.L.); (Z.L.); (C.L.); (S.L.); (N.C.)
| | - Chuanqing Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (H.C.); (Y.L.); (Z.L.); (C.L.); (S.L.); (N.C.)
| | - Kaixing Qu
- Academy of Science and Technology, Chuxiong Normal University, Chuxiong 675099, China;
| | - Shuang Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (H.C.); (Y.L.); (Z.L.); (C.L.); (S.L.); (N.C.)
| | - Zulfiqar Ahmed
- Department of Livestock and Poultry Production, Faculty of Veterinary and Animal Sciences, University of Poonch Rawalakot, Rawalakot 12350, Pakistan;
| | - Weidong Ma
- Shaanxi Province Agriculture & Husbandry Breeding Farm, Baoji 722203, China;
| | - Xingshan Qi
- Animal Husbandry Bureau in Biyang County, Zhumadian 463700, China;
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (H.C.); (Y.L.); (Z.L.); (C.L.); (S.L.); (N.C.)
| | - Chuzhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (H.C.); (Y.L.); (Z.L.); (C.L.); (S.L.); (N.C.)
| |
Collapse
|
11
|
Boschiero C, Neupane M, Yang L, Schroeder SG, Tuo W, Ma L, Baldwin RL, Van Tassell CP, Liu GE. A Pilot Detection and Associate Study of Gene Presence-Absence Variation in Holstein Cattle. Animals (Basel) 2024; 14:1921. [PMID: 38998033 PMCID: PMC11240624 DOI: 10.3390/ani14131921] [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: 05/20/2024] [Revised: 06/18/2024] [Accepted: 06/26/2024] [Indexed: 07/14/2024] Open
Abstract
Presence-absence variations (PAVs) are important structural variations, wherein a genomic segment containing one or more genes is present in some individuals but absent in others. While PAVs have been extensively studied in plants, research in cattle remains limited. This study identified PAVs in 173 Holstein bulls using whole-genome sequencing data and assessed their associations with 46 economically important traits. Out of 28,772 cattle genes (from the longest transcripts), a total of 26,979 (93.77%) core genes were identified (present in all individuals), while variable genes included 928 softcore (present in 95-99% of individuals), 494 shell (present in 5-94%), and 371 cloud genes (present in <5%). Cloud genes were enriched in functions associated with hormonal and antimicrobial activities, while shell genes were enriched in immune functions. PAV-based genome-wide association studies identified associations between gene PAVs and 16 traits including milk, fat, and protein yields, as well as traits related to health and reproduction. Associations were found on multiple chromosomes, illustrating important associations on cattle chromosomes 7 and 15, involving olfactory receptor and immune-related genes, respectively. By examining the PAVs at the population level, the results of this research provided crucial insights into the genetic structures underlying the complex traits of Holstein cattle.
Collapse
Affiliation(s)
- Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
- Department of Veterinary Medicine, University of Maryland, College Park, MD 20742, USA
| | - Mahesh Neupane
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Liu Yang
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Wenbin Tuo
- Animal Parasitic Diseases Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Ransom L Baldwin
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| |
Collapse
|
12
|
Gao Z, Lu Y, Chong Y, Li M, Hong J, Wu J, Wu D, Xi D, Deng W. Beef Cattle Genome Project: Advances in Genome Sequencing, Assembly, and Functional Genes Discovery. Int J Mol Sci 2024; 25:7147. [PMID: 39000250 PMCID: PMC11240973 DOI: 10.3390/ijms25137147] [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: 06/03/2024] [Revised: 06/23/2024] [Accepted: 06/26/2024] [Indexed: 07/16/2024] Open
Abstract
Beef is a major global source of protein, playing an essential role in the human diet. The worldwide production and consumption of beef continue to rise, reflecting a significant trend. However, despite the critical importance of beef cattle resources in agriculture, the diversity of cattle breeds faces severe challenges, with many breeds at risk of extinction. The initiation of the Beef Cattle Genome Project is crucial. By constructing a high-precision functional annotation map of their genome, it becomes possible to analyze the genetic mechanisms underlying important traits in beef cattle, laying a solid foundation for breeding more efficient and productive cattle breeds. This review details advances in genome sequencing and assembly technologies, iterative upgrades of the beef cattle reference genome, and its application in pan-genome research. Additionally, it summarizes relevant studies on the discovery of functional genes associated with key traits in beef cattle, such as growth, meat quality, reproduction, polled traits, disease resistance, and environmental adaptability. Finally, the review explores the potential of telomere-to-telomere (T2T) genome assembly, structural variations (SVs), and multi-omics techniques in future beef cattle genetic breeding. These advancements collectively offer promising avenues for enhancing beef cattle breeding and improving genetic traits.
Collapse
Affiliation(s)
- Zhendong Gao
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Ying Lu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Yuqing Chong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Mengfei Li
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Jieyun Hong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Jiao Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dongwang Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dongmei Xi
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Weidong Deng
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, Kunming 650201, China
| |
Collapse
|
13
|
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.
Collapse
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.
| |
Collapse
|
14
|
Kalleberg J, Rissman J, Schnabel RD. Overcoming Limitations to Deep Learning in Domesticated Animals with TrioTrain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.15.589602. [PMID: 38659907 PMCID: PMC11042298 DOI: 10.1101/2024.04.15.589602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Variant calling across diverse species remains challenging as most bioinformatics tools default to assumptions based on human genomes. DeepVariant (DV) excels without joint genotyping while offering fewer implementation barriers. However, the growing appeal of a "universal" algorithm has magnified the unknown impacts when used with non-human genomes. Here, we use bovine genomes to assess the limits of human-genome-trained models in other species. We introduce the first multi-species DV model that achieves a lower Mendelian Inheritance Error (MIE) rate during single-sample genotyping. Our novel approach, TrioTrain, automates extending DV for species without Genome In A Bottle (GIAB) resources and uses region shuffling to mitigate barriers for SLURM-based clusters. To offset imperfect truth labels for animal genomes, we remove Mendelian discordant variants before training, where models are tuned to genotype the offspring correctly. With TrioTrain, we use cattle, yak, and bison trios to build 30 model iterations across five phases. We observe remarkable performance across phases when testing the GIAB human trios with a mean SNP F1 score >0.990. In HG002, our phase 4 bovine model identifies more variants at a lower MIE rate than DeepTrio. In bovine F1-hybrid genomes, our model substantially reduces inheritance errors with a mean MIE rate of 0.03 percent. Although constrained by imperfect labels, we find that multi-species, trio-based training produces a robust variant calling model. Our research demonstrates that exclusively training with human genomes restricts the application of deep-learning approaches for comparative genomics.
Collapse
Affiliation(s)
- Jenna Kalleberg
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
| | - Jacob Rissman
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
| | - Robert D Schnabel
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
- University of Missouri, Genetics Area Program, Columbia, MO, 65201 USA
| |
Collapse
|
15
|
Du X, Sun Y, Fu T, Gao T, Zhang T. Research Progress and Applications of Bovine Genome in the Tribe Bovini. Genes (Basel) 2024; 15:509. [PMID: 38674443 PMCID: PMC11050176 DOI: 10.3390/genes15040509] [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: 03/22/2024] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Various bovine species have been domesticated and bred for thousands of years, and they provide adequate animal-derived products, including meat, milk, and leather, to meet human requirements. Despite the review studies on economic traits in cattle, the genetic basis of traits has only been partially explained by phenotype and pedigree breeding methods, due to the complexity of genomic regulation during animal development and growth. With the advent of next-generation sequencing technology, genomics projects, such as the 1000 Bull Genomes Project, Functional Annotation of Animal Genomes project, and Bovine Pangenome Consortium, have advanced bovine genomic research. These large-scale genomics projects gave us a comprehensive concept, technology, and public resources. In this review, we summarize the genomics research progress of the main bovine species during the past decade, including cattle (Bos taurus), yak (Bos grunniens), water buffalo (Bubalus bubalis), zebu (Bos indicus), and gayal (Bos frontalis). We mainly discuss the development of genome sequencing and functional annotation, focusing on how genomic analysis reveals genetic variation and its impact on phenotypes in several bovine species.
Collapse
Affiliation(s)
- Xingjie Du
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Yu Sun
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tong Fu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tengyun Gao
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tianliu Zhang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| |
Collapse
|
16
|
Benfica LF, Brito LF, do Bem RD, de Oliveira LF, Mulim HA, Braga LG, Cyrillo JNSG, Bonilha SFM, Mercadante MEZ. Detection and characterization of copy number variation in three differentially-selected Nellore cattle populations. Front Genet 2024; 15:1377130. [PMID: 38694873 PMCID: PMC11061390 DOI: 10.3389/fgene.2024.1377130] [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: 01/26/2024] [Accepted: 04/05/2024] [Indexed: 05/04/2024] Open
Abstract
Introduction: Nellore cattle (Bos taurus indicus) is the main beef cattle breed raised in Brazil. This breed is well adapted to tropical conditions and, more recently, has experienced intensive genetic selection for multiple performance traits. Over the past 43 years, an experimental breeding program has been developed in the Institute of Animal Science (IZ, Sertaozinho, SP, Brazil), which resulted in three differentially-selected lines known as Nellore Control (NeC), Nellore Selection (NeS), and Nellore Traditional (NeT). The primary goal of this selection experiment was to determine the response to selection for yearling weight (YW) and residual feed intake (RFI) on Nellore cattle. The main objectives of this study were to: 1) identify copy number variation (CNVs) in Nellore cattle from three selection lines; 2) identify and characterize CNV regions (CNVR) on these three lines; and 3) perform functional enrichment analyses of the CNVR identified. Results: A total of 14,914 unique CNVs and 1,884 CNVRs were identified when considering all lines as a single population. The CNVRs were non-uniformly distributed across the chromosomes of the three selection lines included in the study. The NeT line had the highest number of CNVRs (n = 1,493), followed by the NeS (n = 823) and NeC (n = 482) lines. The CNVRs covered 23,449,890 bp (0.94%), 40,175,556 bp (1.61%), and 63,212,273 bp (2.54%) of the genome of the NeC, NeS, and NeT lines, respectively. Two CNVRs were commonly identified between the three lines, and six, two, and four exclusive regions were identified for NeC, NeS, and NeT, respectively. All the exclusive regions overlap with important genes, such as SMARCD3, SLC15A1, and MAPK1. Key biological processes associated with the candidate genes were identified, including pathways related to growth and metabolism. Conclusion: This study revealed large variability in CNVs and CNVRs across three Nellore lines differentially selected for YW and RFI. Gene annotation and gene ontology analyses of the exclusive CNVRs to each line revealed specific genes and biological processes involved in the expression of growth and feed efficiency traits. These findings contribute to the understanding of the genetic mechanisms underlying the phenotypic differences among the three Nellore selection lines.
Collapse
Affiliation(s)
- Lorena F. Benfica
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
- Department of Animal Science, Faculty of Agricultural and Veterinary Sciences, Sao Paulo State University, Jaboticabal, São Paulo, Brazil
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Ricardo D. do Bem
- Department of Animal Science, Faculty of Agricultural and Veterinary Sciences, Sao Paulo State University, Jaboticabal, São Paulo, Brazil
| | | | - Henrique A. Mulim
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Larissa G. Braga
- Department of Animal Science, Faculty of Agricultural and Veterinary Sciences, Sao Paulo State University, Jaboticabal, São Paulo, Brazil
- Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | | | - Sarah F. M. Bonilha
- Beef Cattle Research Center, Institute of Animal Science, Sertaozinho, São Paulo, Brazil
| | - Maria Eugenia Z. Mercadante
- Department of Animal Science, Faculty of Agricultural and Veterinary Sciences, Sao Paulo State University, Jaboticabal, São Paulo, Brazil
- Beef Cattle Research Center, Institute of Animal Science, Sertaozinho, São Paulo, Brazil
| |
Collapse
|
17
|
Leonard AS, Mapel XM, Pausch H. Pangenome-genotyped structural variation improves molecular phenotype mapping in cattle. Genome Res 2024; 34:300-309. [PMID: 38355307 PMCID: PMC10984387 DOI: 10.1101/gr.278267.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024]
Abstract
Expression and splicing quantitative trait loci (e/sQTL) are large contributors to phenotypic variability. Achieving sufficient statistical power for e/sQTL mapping requires large cohorts with both genotypes and molecular phenotypes, and so, the genomic variation is often called from short-read alignments, which are unable to comprehensively resolve structural variation. Here we build a pangenome from 16 HiFi haplotype-resolved cattle assemblies to identify small and structural variation and genotype them with PanGenie in 307 short-read samples. We find high (>90%) concordance of PanGenie-genotyped and DeepVariant-called small variation and confidently genotype close to 21 million small and 43,000 structural variants in the larger population. We validate 85% of these structural variants (with MAF > 0.1) directly with a subset of 25 short-read samples that also have medium coverage HiFi reads. We then conduct e/sQTL mapping with this comprehensive variant set in a subset of 117 cattle that have testis transcriptome data, and find 92 structural variants as causal candidates for eQTL and 73 for sQTL. We find that roughly half of the top associated structural variants affecting expression or splicing are transposable elements, such as SV-eQTL for STN1 and MYH7 and SV-sQTL for CEP89 and ASAH2 Extensive linkage disequilibrium between small and structural variation results in only 28 additional eQTL and 17 sQTL discovered when including SVs, although many top associated SVs are compelling candidates.
Collapse
Affiliation(s)
| | - Xena M Mapel
- Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland
| |
Collapse
|
18
|
Miao J, Wei X, Cao C, Sun J, Xu Y, Zhang Z, Wang Q, Pan Y, Wang Z. Pig pangenome graph reveals functional features of non-reference sequences. J Anim Sci Biotechnol 2024; 15:32. [PMID: 38389084 PMCID: PMC10882747 DOI: 10.1186/s40104-023-00984-4] [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: 08/29/2023] [Accepted: 12/22/2023] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND The reliance on a solitary linear reference genome has imposed a significant constraint on our comprehensive understanding of genetic variation in animals. This constraint is particularly pronounced for non-reference sequences (NRSs), which have not been extensively studied. RESULTS In this study, we constructed a pig pangenome graph using 21 pig assemblies and identified 23,831 NRSs with a total length of 105 Mb. Our findings revealed that NRSs were more prevalent in breeds exhibiting greater genetic divergence from the reference genome. Furthermore, we observed that NRSs were rarely found within coding sequences, while NRS insertions were enriched in immune-related Gene Ontology terms. Notably, our investigation also unveiled a close association between novel genes and the immune capacity of pigs. We observed substantial differences in terms of frequencies of NRSs between Eastern and Western pigs, and the heat-resistant pigs exhibited a substantial number of NRS insertions in an 11.6 Mb interval on chromosome X. Additionally, we discovered a 665 bp insertion in the fourth intron of the TNFRSF19 gene that may be associated with the ability of heat tolerance in Southern Chinese pigs. CONCLUSIONS Our findings demonstrate the potential of a graph genome approach to reveal important functional features of NRSs in pig populations.
Collapse
Affiliation(s)
- Jian Miao
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Xingyu Wei
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Caiyun Cao
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Jiabao Sun
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Yuejin Xu
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Zhe Zhang
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Qishan Wang
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
- Yazhou Bay Science and Technology City, Hainan Institute of Zhejiang University, Yazhou District, Building 11, Yongyou Industrial Park, Sanya, 572025, Hainan, China
| | - Yuchun Pan
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
- Yazhou Bay Science and Technology City, Hainan Institute of Zhejiang University, Yazhou District, Building 11, Yongyou Industrial Park, Sanya, 572025, Hainan, China.
| | - Zhen Wang
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
| |
Collapse
|
19
|
Liu X, Zheng J, Ding J, Wu J, Zuo F, Zhang G. When Livestock Genomes Meet Third-Generation Sequencing Technology: From Opportunities to Applications. Genes (Basel) 2024; 15:245. [PMID: 38397234 PMCID: PMC10888458 DOI: 10.3390/genes15020245] [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: 12/23/2023] [Revised: 01/30/2024] [Accepted: 02/10/2024] [Indexed: 02/25/2024] Open
Abstract
Third-generation sequencing technology has found widespread application in the genomic, transcriptomic, and epigenetic research of both human and livestock genetics. This technology offers significant advantages in the sequencing of complex genomic regions, the identification of intricate structural variations, and the production of high-quality genomes. Its attributes, including long sequencing reads, obviation of PCR amplification, and direct determination of DNA/RNA, contribute to its efficacy. This review presents a comprehensive overview of third-generation sequencing technologies, exemplified by single-molecule real-time sequencing (SMRT) and Oxford Nanopore Technology (ONT). Emphasizing the research advancements in livestock genomics, the review delves into genome assembly, structural variation detection, transcriptome sequencing, and epigenetic investigations enabled by third-generation sequencing. A comprehensive analysis is conducted on the application and potential challenges of third-generation sequencing technology for genome detection in livestock. Beyond providing valuable insights into genome structure analysis and the identification of rare genes in livestock, the review ventures into an exploration of the genetic mechanisms underpinning exemplary traits. This review not only contributes to our understanding of the genomic landscape in livestock but also provides fresh perspectives for the advancement of research in this domain.
Collapse
Affiliation(s)
- Xinyue Liu
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Junyuan Zheng
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Jialan Ding
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Jiaxin Wu
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Fuyuan Zuo
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
- Beef Cattle Engineering and Technology Research Center of Chongqing, Southwest University, Rongchang, Chongqing 402460, China
| | - Gongwei Zhang
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
- Beef Cattle Engineering and Technology Research Center of Chongqing, Southwest University, Rongchang, Chongqing 402460, China
| |
Collapse
|
20
|
Wang K, Hua G, Li J, Yang Y, Zhang C, Yang L, Hu X, Scheben A, Wu Y, Gong P, Zhang S, Fan Y, Zeng T, Lu L, Gong Y, Jiang R, Sun G, Tian Y, Kang X, Hu H, Li W. Duck pan-genome reveals two transposon insertions caused bodyweight enlarging and white plumage phenotype formation during evolution. IMETA 2024; 3:e154. [PMID: 38868520 PMCID: PMC10989122 DOI: 10.1002/imt2.154] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 11/07/2023] [Indexed: 06/14/2024]
Abstract
Structural variations (SVs) are a major source of domestication and improvement traits. We present the first duck pan-genome constructed using five genome assemblies capturing ∼40.98 Mb new sequences. This pan-genome together with high-depth sequencing data (∼46.5×) identified 101,041 SVs, of which substantial proportions were derived from transposable element (TE) activity. Many TE-derived SVs anchoring in a gene body or regulatory region are linked to duck's domestication and improvement. By combining quantitative genetics with molecular experiments, we, for the first time, unraveled a 6945 bp Gypsy insertion as a functional mutation of the major gene IGF2BP1 associated with duck bodyweight. This Gypsy insertion, to our knowledge, explains the largest effect on bodyweight among avian species (27.61% of phenotypic variation). In addition, we also examined another 6634 bp Gypsy insertion in MITF intron, which triggers a novel transcript of MITF, thereby contributing to the development of white plumage. Our findings highlight the importance of using a pan-genome as a reference in genomics studies and illuminate the impact of transposons in trait formation and livestock breeding.
Collapse
Affiliation(s)
- Kejun Wang
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| | - Guoying Hua
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenChina
| | - Jingyi Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Intelligent Husbandry Department, College of Animal Science and TechnologyHuazhong Agricultural UniversityWuhanChina
| | - Yu Yang
- Wuhan Academy of Agricultural ScienceWuhanChina
| | - Chenxi Zhang
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| | - Lan Yang
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| | - Xiaoyu Hu
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| | - Armin Scheben
- Simons Center for Quantitative BiologyCold Spring Harbor LaboratoryCold Spring HarborNew YorkUSA
| | - Yanan Wu
- Department of preventive veterinary medicine, College of Veterinary MedicineHenan Agricultural UniversityZhengzhouChina
- International Joint Research Center for National Animal ImmunologyZhengzhouHenanChina
| | - Ping Gong
- Wuhan Academy of Agricultural ScienceWuhanChina
| | - Shuangjie Zhang
- Quality Safety and Processing LaboratoryJiangsu Institute of Poultry SciencesYangzhouChina
| | - Yanfeng Fan
- Quality Safety and Processing LaboratoryJiangsu Institute of Poultry SciencesYangzhouChina
| | - Tao Zeng
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro‐Products, Institute of Animal Husbandry and Veterinary ScienceZhejiang Academy of Agricultural SciencesHangzhouChina
| | - Lizhi Lu
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro‐Products, Institute of Animal Husbandry and Veterinary ScienceZhejiang Academy of Agricultural SciencesHangzhouChina
| | - Yanzhang Gong
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Intelligent Husbandry Department, College of Animal Science and TechnologyHuazhong Agricultural UniversityWuhanChina
| | - Ruirui Jiang
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| | - Guirong Sun
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| | - Yadong Tian
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| | - Xiangtao Kang
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| | - Haifei Hu
- Rice Research Institute, Guangdong Key Laboratory of New Technology in Rice Breeding and Guangdong Rice Engineering LaboratoryGuangdong Academy of Agricultural SciencesGuangzhouChina
| | - Wenting Li
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Department of Animal Genetic and Breeding, College of Animal Science and TechnologyHenan Agricultural UniversityZhengzhouChina
- The Shennong LaboratoryZhengzhouChina
| |
Collapse
|
21
|
Gao G, Zhang H, Ni J, Zhao X, Zhang K, Wang J, Kong X, Wang Q. Insights into genetic diversity and phenotypic variations in domestic geese through comprehensive population and pan-genome analysis. J Anim Sci Biotechnol 2023; 14:150. [PMID: 38001525 PMCID: PMC10675864 DOI: 10.1186/s40104-023-00944-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 10/06/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND Domestic goose breeds are descended from either the Swan goose (Anser cygnoides) or the Greylag goose (Anser anser), exhibiting variations in body size, reproductive performance, egg production, feather color, and other phenotypic traits. Constructing a pan-genome facilitates a thorough identification of genetic variations, thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability. RESULTS To comprehensively facilitate population genomic and pan-genomic analyses in geese, we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples. By constructing the pan-genome for geese, we generated non-reference contigs totaling 612 Mb, unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes, 1,324 softcore genes, 2,734 shell genes, and 878 cloud genes in goose genomes. Furthermore, we detected an 81.97 Mb genomic region showing signs of genome selection, encompassing the TGFBR2 gene correlated with variations in body weight among geese. Genome-wide association studies utilizing single nucleotide polymorphisms (SNPs) and presence-absence variation revealed significant genomic associations with various goose meat quality, reproductive, and body composition traits. For instance, a gene encoding the SVEP1 protein was linked to carcass oblique length, and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length. Notably, the pan-genome analysis revealed enrichment of variable genes in the "hair follicle maturation" Gene Ontology term, potentially linked to the selection of feather-related traits in geese. A gene presence-absence variation analysis suggested a reduced frequency of genes associated with "regulation of heart contraction" in domesticated geese compared to their wild counterparts. Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation. CONCLUSION This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits, thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese. Moreover, assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome, establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.
Collapse
Affiliation(s)
- Guangliang Gao
- Chongqing Academy of Animal Science, Rongchang District, Chongqing, 402460, China
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Rongchang District, Chongqing, 402460, China
| | - Hongmei Zhang
- Department of Cardiovascular Ultrasound and Non-Invasive Cardiology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital,University of Electronic Science and Technology of China, Chengdu, 611731, China
- Ultrasound in Cardiac Electrophysiology and Biomechanics Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Jiangping Ni
- JiguangGene Biotechnology Co., Ltd., Nanjing, 210032, China
| | - Xianzhi Zhao
- Chongqing Academy of Animal Science, Rongchang District, Chongqing, 402460, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Rongchang District, Chongqing, 402460, China
| | - Keshan Zhang
- Chongqing Academy of Animal Science, Rongchang District, Chongqing, 402460, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Rongchang District, Chongqing, 402460, China
| | - Jian Wang
- Jiangsu Agri-Animal Vocational College, Taizhou, 225300, China
| | - Xiangdong Kong
- JiguangGene Biotechnology Co., Ltd., Nanjing, 210032, China.
| | - Qigui Wang
- Chongqing Academy of Animal Science, Rongchang District, Chongqing, 402460, China.
- Chongqing Engineering Research Center of Goose Genetic Improvement, Rongchang District, Chongqing, 402460, China.
- Present Address: Poultry Science Institute, Chongqing Academy of Animal Science, No. 51 Changzhou Avenue, Rongchang District, Chongqing, 402460, P. R. China.
| |
Collapse
|
22
|
Rice ES, Alberdi A, Alfieri J, Athrey G, Balacco JR, Bardou P, Blackmon H, Charles M, Cheng HH, Fedrigo O, Fiddaman SR, Formenti G, Frantz LAF, Gilbert MTP, Hearn CJ, Jarvis ED, Klopp C, Marcos S, Mason AS, Velez-Irizarry D, Xu L, Warren WC. A pangenome graph reference of 30 chicken genomes allows genotyping of large and complex structural variants. BMC Biol 2023; 21:267. [PMID: 37993882 PMCID: PMC10664547 DOI: 10.1186/s12915-023-01758-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/02/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND The red junglefowl, the wild outgroup of domestic chickens, has historically served as a reference for genomic studies of domestic chickens. These studies have provided insight into the etiology of traits of commercial importance. However, the use of a single reference genome does not capture diversity present among modern breeds, many of which have accumulated molecular changes due to drift and selection. While reference-based resequencing is well-suited to cataloging simple variants such as single-nucleotide changes and short insertions and deletions, it is mostly inadequate to discover more complex structural variation in the genome. METHODS We present a pangenome for the domestic chicken consisting of thirty assemblies of chickens from different breeds and research lines. RESULTS We demonstrate how this pangenome can be used to catalog structural variants present in modern breeds and untangle complex nested variation. We show that alignment of short reads from 100 diverse wild and domestic chickens to this pangenome reduces reference bias by 38%, which affects downstream genotyping results. This approach also allows for the accurate genotyping of a large and complex pair of structural variants at the K feathering locus using short reads, which would not be possible using a linear reference. CONCLUSIONS We expect that this new paradigm of genomic reference will allow better pinpointing of exact mutations responsible for specific phenotypes, which will in turn be necessary for breeding chickens that meet new sustainability criteria and are resilient to quickly evolving pathogen threats.
Collapse
Affiliation(s)
- Edward S Rice
- Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
- Faculty of Veterinary Medicine, Ludwig-Maximilians-Universität, Munich, Germany
| | - Antton Alberdi
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - James Alfieri
- Department of Ecology & Evolutionary Biology, Texas A&M University, College Station, TX, USA
| | - Giridhar Athrey
- Department of Poultry Science, Texas A&M University, College Station, TX, USA
| | - Jennifer R Balacco
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Philippe Bardou
- Sigenae, GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, 31326, France
| | - Heath Blackmon
- Department of Biology, Texas A&M University, College Station, TX, USA
| | - Mathieu Charles
- University Paris-Saclay, INRAE, AgroParisTech, GABI, Sigenae, Jouy-en-Josas, France
| | - Hans H Cheng
- Avian Disease and Oncology Laboratory, USDA, ARS, USNPRC, East Lansing, MI, USA
| | - Olivier Fedrigo
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | | | - Giulio Formenti
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Laurent A F Frantz
- Faculty of Veterinary Medicine, Ludwig-Maximilians-Universität, Munich, Germany
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4DQ, UK
| | - M Thomas P Gilbert
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - Cari J Hearn
- Avian Disease and Oncology Laboratory, USDA, ARS, USNPRC, East Lansing, MI, USA
| | - Erich D Jarvis
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
- The Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Christophe Klopp
- Sigenae, Genotoul Bioinfo, MIAT UR875, INRAE, Castanet Tolosan, France
| | - Sofia Marcos
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen (UCPH), Copenhagen, Denmark
- Applied Genomics and Bioinformatics, University of the Basque Country (UPV/EHU), Leioa, Bilbao, Spain
| | | | | | - Luohao Xu
- Key Laboratory of Freshwater Fish Reproduction and Development (Ministry of Education), Key Laboratory of Aquatic Science of Chongqing, School of Life Sciences, Southwest University, Chongqing, 400715, China
| | - Wesley C Warren
- Department of Animal Sciences, University of Missouri, Columbia, MO, USA.
| |
Collapse
|
23
|
Neumann GB, Korkuć P, Reißmann M, Wolf MJ, May K, König S, Brockmann GA. Unmapped short reads from whole-genome sequencing indicate potential infectious pathogens in german black Pied cattle. Vet Res 2023; 54:95. [PMID: 37853447 PMCID: PMC10585868 DOI: 10.1186/s13567-023-01227-0] [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: 03/02/2023] [Accepted: 09/27/2023] [Indexed: 10/20/2023] Open
Abstract
When resequencing animal genomes, some short reads cannot be mapped to the reference genome and are usually discarded. In this study, unmapped reads from 302 German Black Pied cattle were analyzed to identify potential pathogenic DNA. These unmapped reads were assembled and blasted against NCBI's database to identify bacterial and viral sequences. The results provided evidence for the presence of pathogens. We found sequences of Bovine parvovirus 3 and Mycoplasma species. These findings emphasize the information content of unmapped reads for gaining insight into bacterial and viral infections, which is important for veterinarians and epidemiologists.
Collapse
Affiliation(s)
- Guilherme B Neumann
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Paula Korkuć
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Monika Reißmann
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Manuel J Wolf
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Giessen, Germany
| | - Katharina May
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Giessen, Germany
| | - Sven König
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Giessen, Germany
| | - Gudrun A Brockmann
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany.
| |
Collapse
|
24
|
Dai X, Bian P, Hu D, Luo F, Huang Y, Jiao S, Wang X, Gong M, Li R, Cai Y, Wen J, Yang Q, Deng W, Nanaei HA, Wang Y, Wang F, Zhang Z, Rosen BD, Heller R, Jiang Y. A Chinese indicine pangenome reveals a wealth of novel structural variants introgressed from other Bos species. Genome Res 2023; 33:1284-1298. [PMID: 37714713 PMCID: PMC10547261 DOI: 10.1101/gr.277481.122] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 06/30/2023] [Indexed: 09/17/2023]
Abstract
Chinese indicine cattle harbor a much higher genetic diversity compared with other domestic cattle, but their genome architecture remains uninvestigated. Using PacBio HiFi sequencing data from 10 Chinese indicine cattle across southern China, we assembled 20 high-quality partially phased genomes and integrated them into a multiassembly graph containing 148.5 Mb (5.6%) of novel sequence. We identified 156,009 high-confidence nonredundant structural variants (SVs) and 206 SV hotspots spanning ∼195 Mb of gene-rich sequence. We detected 34,249 archaic introgressed fragments in Chinese indicine cattle covering 1.93 Gb (73.3%) of the genome. We inferred an average of 3.8%, 3.2%, 1.4%, and 0.5% of introgressed sequence originating, respectively, from banteng-like, kouprey-like, gayal-like, and gaur-like Bos species, as well as 0.6% of unknown origin. Introgression from multiple donors might have contributed to the genetic diversity of Chinese indicine cattle. Altogether, this study highlights the contribution of interspecies introgression to the genomic architecture of an important livestock population and shows how exotic genomic elements can contribute to the genetic variation available for selection.
Collapse
Affiliation(s)
- Xuelei Dai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Peipei Bian
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Dexiang Hu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Funong Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yongzhen Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Shaohua Jiao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mian Gong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jiayue Wen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Qimeng Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Weidong Deng
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Hojjat Asadollahpour Nanaei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Reproductive Biotechnology Research Center, Avicenna Research Institute, ACECR, Tehran 1983969412, Iran
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Fei Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zijing Zhang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Rasmus Heller
- Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark;
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China;
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| |
Collapse
|
25
|
Gong Y, Li Y, Liu X, Ma Y, Jiang L. A review of the pangenome: how it affects our understanding of genomic variation, selection and breeding in domestic animals? J Anim Sci Biotechnol 2023; 14:73. [PMID: 37143156 PMCID: PMC10161434 DOI: 10.1186/s40104-023-00860-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 03/01/2023] [Indexed: 05/06/2023] Open
Abstract
As large-scale genomic studies have progressed, it has been revealed that a single reference genome pattern cannot represent genetic diversity at the species level. While domestic animals tend to have complex routes of origin and migration, suggesting a possible omission of some population-specific sequences in the current reference genome. Conversely, the pangenome is a collection of all DNA sequences of a species that contains sequences shared by all individuals (core genome) and is also able to display sequence information unique to each individual (variable genome). The progress of pangenome research in humans, plants and domestic animals has proved that the missing genetic components and the identification of large structural variants (SVs) can be explored through pangenomic studies. Many individual specific sequences have been shown to be related to biological adaptability, phenotype and important economic traits. The maturity of technologies and methods such as third-generation sequencing, Telomere-to-telomere genomes, graphic genomes, and reference-free assembly will further promote the development of pangenome. In the future, pangenome combined with long-read data and multi-omics will help to resolve large SVs and their relationship with the main economic traits of interest in domesticated animals, providing better insights into animal domestication, evolution and breeding. In this review, we mainly discuss how pangenome analysis reveals genetic variations in domestic animals (sheep, cattle, pigs, chickens) and their impacts on phenotypes and how this can contribute to the understanding of species diversity. Additionally, we also go through potential issues and the future perspectives of pangenome research in livestock and poultry.
Collapse
Affiliation(s)
- Ying Gong
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China
| | - Yefang Li
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China
| | - Xuexue Liu
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China
- Centre d'Anthropobiologie et de Génomique de Toulouse, Université Paul Sabatier, 37 allées Jules Guesde, Toulouse, 31000, France
| | - Yuehui Ma
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China.
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China.
| | - Lin Jiang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China.
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China.
| |
Collapse
|
26
|
Xia X, Qu K, Wang Y, Sinding MHS, Wang F, Hanif Q, Ahmed Z, Lenstra JA, Han J, Lei C, Chen N. Global dispersal and adaptive evolution of domestic cattle: a genomic perspective. STRESS BIOLOGY 2023; 3:8. [PMID: 37676580 PMCID: PMC10441868 DOI: 10.1007/s44154-023-00085-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 03/26/2023] [Indexed: 09/08/2023]
Abstract
Domestic cattle have spread across the globe and inhabit variable and unpredictable environments. They have been exposed to a plethora of selective pressures and have adapted to a variety of local ecological and management conditions, including UV exposure, diseases, and stall-feeding systems. These selective pressures have resulted in unique and important phenotypic and genetic differences among modern cattle breeds/populations. Ongoing efforts to sequence the genomes of local and commercial cattle breeds/populations, along with the growing availability of ancient bovid DNA data, have significantly advanced our understanding of the genomic architecture, recent evolution of complex traits, common diseases, and local adaptation in cattle. Here, we review the origin and spread of domestic cattle and illustrate the environmental adaptations of local cattle breeds/populations.
Collapse
Affiliation(s)
- Xiaoting Xia
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Kaixing Qu
- Academy of Science and Technology, Chuxiong Normal University, Chuxiong, 675000, China
| | - Yan Wang
- Qingdao Municipal Bureau of Agriculture and Rural Affairs, Qingdao, 266000, China
| | - Mikkel-Holger S Sinding
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, 1350, Denmark
| | - Fuwen Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Quratulain Hanif
- National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan
| | - Zulfiqar Ahmed
- Faculty of Veterinary and Animal Sciences, University of Poonch Rawalakot, Azad Jammu and Kashmir, 12350, Pakistan
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Jianlin Han
- Livestock Genetic Program, International Livestock Research Institute (ILRI), Nairobi, 00100, Kenya
- CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, 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, 712100, China.
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China.
| |
Collapse
|
27
|
Deng T, Wu J, Abdel-Shafy H, Wang X, Lv H, Shaukat A, Zhou X, Zhou Y, Sun H, Wei P, Sun N, Huang Q, Xu L, Liu M, Lin Y, Yang L, Hua G. Comparative Genomic Analysis of the Thiolase Family and Functional Characterization of the Acetyl-Coenzyme A Acyltransferase-1 Gene for Milk Biosynthesis and Production of Buffalo and Cattle. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:3325-3337. [PMID: 36780201 DOI: 10.1021/acs.jafc.2c07763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Cattle and buffalo served as the first and second largest dairy animals, respectively, providing 96% milk products worldwide. Understanding the mechanisms underlying milk synthesis is critical to develop the technique to improve milk production. Thiolases, also known as acetyl-coenzyme A acetyltransferases (ACAT), are an enzyme family that plays vital roles in lipid metabolism, including ACAT1, ACAT2, ACAA1, ACAA2, and HADHB. Our present study showed that these five members were orthologous in six livestock species including buffalo and cattle. Transcriptomic data analyses derived from different lactations stages showed that ACAA1 displayed different expression patterns between buffalo and cattle. Immunohistochemistry staining revealed that ACAA1 were dominantly located in the mammary epithelial cells of these two dairy animals. Knockdown of ACAA1 inhibited mammary epithelial cell proliferation and triglyceride and β-casein secretion by regulating related gene expressions in cattle and buffalo. In contrast, ACAA1 overexpression promoted cell proliferation and triglyceride secretion. Finally, three novel SNPs (g.-681A>T, g.-23117C>T, and g.-24348G>T) were detected and showed significant association with milk production traits of Mediterranean buffaloes. In addition, g.-681A>T mutation located in the promoter region changed transcriptional activity significantly. Our findings suggested that ACAA1 play a key role in regulating buffalo and cattle milk synthesis and provided basic information to further understand the dairy animal lactation physiology.
Collapse
Affiliation(s)
- Tingxian Deng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- Guangxi Key Laboratory of Buffalo Genetic, Breeding and Reproduction, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - Jiyun Wu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Shenzhen 518038, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Hamdy Abdel-Shafy
- Department of Animal Production, Faculty of Agriculture, Cairo University, Giza 12613, Egypt
| | - Xiaojie Wang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Haimiao Lv
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Aftab Shaukat
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- Department of Animal Production, Faculty of Agriculture, Cairo University, Giza 12613, Egypt
| | - Xiang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Hui Sun
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Shenzhen 518038, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Pengfei Wei
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Nan Sun
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Qianzhi Huang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Linghua Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Miaoyu Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yuxin Lin
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- National Center for International Research on Animal Genetics, Breeding and Reproduction, Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan 430070, China
| | - Guohua Hua
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Shenzhen 518038, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
- National Center for International Research on Animal Genetics, Breeding and Reproduction, Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan 430070, China
| |
Collapse
|
28
|
Nguyen TV, Vander Jagt CJ, Wang J, Daetwyler HD, Xiang R, Goddard ME, Nguyen LT, Ross EM, Hayes BJ, Chamberlain AJ, MacLeod IM. In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants. Genet Sel Evol 2023; 55:9. [PMID: 36721111 PMCID: PMC9887926 DOI: 10.1186/s12711-023-00783-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 01/23/2023] [Indexed: 02/02/2023] Open
Abstract
Studies have demonstrated that structural variants (SV) play a substantial role in the evolution of species and have an impact on Mendelian traits in the genome. However, unlike small variants (< 50 bp), it has been challenging to accurately identify and genotype SV at the population scale using short-read sequencing. Long-read sequencing technologies are becoming competitively priced and can address several of the disadvantages of short-read sequencing for the discovery and genotyping of SV. In livestock species, analysis of SV at the population scale still faces challenges due to the lack of resources, high costs, technological barriers, and computational limitations. In this review, we summarize recent progress in the characterization of SV in the major livestock species, the obstacles that still need to be overcome, as well as the future directions in this growing field. It seems timely that research communities pool resources to build global population-scale long-read sequencing consortiums for the major livestock species for which the application of genomic tools has become cost-effective.
Collapse
Affiliation(s)
- Tuan V. Nguyen
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
| | | | - Jianghui Wang
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
| | - Hans D. Daetwyler
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083 Australia
| | - Ruidong Xiang
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
- Faculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, VIC 3052 Australia
| | - Michael E. Goddard
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
- Faculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, VIC 3052 Australia
| | - Loan T. Nguyen
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD 4072 Australia
| | - Elizabeth M. Ross
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD 4072 Australia
| | - Ben J. Hayes
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD 4072 Australia
| | - Amanda J. Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083 Australia
| | - Iona M. MacLeod
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
| |
Collapse
|
29
|
Reference-Guided Draft Genome Assembly, Annotation and SSR Mining Data of the Peruvian Creole Cattle (Bos taurus). DATA 2022. [DOI: 10.3390/data7110155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The Peruvian creole cattle (PCC) is a neglected breed and an essential livestock resource in the Andean region of Peru. To develop a modern breeding program and conservation strategies for the PCC, a better understanding of the genetics of this breed is needed. We sequenced the whole genome of the PCC using a de novo assembly approach with a paired-end 150 strategy on the Illumina HiSeq 2500 platform, obtaining 320 GB of sequencing data. A reference scaffolding was used to improve the draft genome. The obtained genome size of the PCC was 2.81 Gb with a contig N50 of 108 Mb and 92.59% complete BUSCOs. This genome size is similar to the genome references of Bos taurus and B. indicus. In addition, we identified 40.22% of repetitive DNA of the genome assembly, of which retroelements occupy 32.39% of the total genome. A total of 19,803 protein-coding genes were annotated in the PCC genome. For SSR data mining, we detected similar statistics in comparison with other breeds. The PCC genome will contribute to a better understanding of the genetics of this species and its adaptation to tough conditions in the Andean ecosystem.
Collapse
|
30
|
Kalds P, Zhou S, Gao Y, Cai B, Huang S, Chen Y, Wang X. Genetics of the phenotypic evolution in sheep: a molecular look at diversity-driving genes. Genet Sel Evol 2022; 54:61. [PMID: 36085023 PMCID: PMC9463822 DOI: 10.1186/s12711-022-00753-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 08/29/2022] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND After domestication, the evolution of phenotypically-varied sheep breeds has generated rich biodiversity. This wide phenotypic variation arises as a result of hidden genomic changes that range from a single nucleotide to several thousands of nucleotides. Thus, it is of interest and significance to reveal and understand the genomic changes underlying the phenotypic variation of sheep breeds in order to drive selection towards economically important traits. REVIEW Various traits contribute to the emergence of variation in sheep phenotypic characteristics, including coat color, horns, tail, wool, ears, udder, vertebrae, among others. The genes that determine most of these phenotypic traits have been investigated, which has generated knowledge regarding the genetic determinism of several agriculturally-relevant traits in sheep. In this review, we discuss the genomic knowledge that has emerged in the past few decades regarding the phenotypic traits in sheep, and our ultimate aim is to encourage its practical application in sheep breeding. In addition, in order to expand the current understanding of the sheep genome, we shed light on research gaps that require further investigation. CONCLUSIONS Although significant research efforts have been conducted in the past few decades, several aspects of the sheep genome remain unexplored. For the full utilization of the current knowledge of the sheep genome, a wide practical application is still required in order to boost sheep productive performance and contribute to the generation of improved sheep breeds. The accumulated knowledge on the sheep genome will help advance and strengthen sheep breeding programs to face future challenges in the sector, such as climate change, global human population growth, and the increasing demand for products of animal origin.
Collapse
Affiliation(s)
- Peter Kalds
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100 China
- Department of Animal and Poultry Production, Faculty of Environmental Agricultural Sciences, Arish University, El-Arish, 45511 Egypt
| | - Shiwei Zhou
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100 China
- College of Veterinary Medicine, Northwest A&F University, Yangling, 712100 China
| | - Yawei Gao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100 China
| | - Bei Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100 China
| | - Shuhong Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100 China
| | - Yulin Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100 China
- International Joint Agriculture Research Center for Animal Bio-Breeding, Ministry of Agriculture and Rural Affairs, Yangling, 712100 China
| | - Xiaolong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100 China
- International Joint Agriculture Research Center for Animal Bio-Breeding, Ministry of Agriculture and Rural Affairs, Yangling, 712100 China
| |
Collapse
|