Analyze Diet
Critical reviews in biotechnology2018; 38(8); 1157-1175; doi: 10.1080/07388551.2018.1451819

Transformation of animal genomics by next-generation sequencing technologies: a decade of challenges and their impact on genetic architecture.

Abstract: For more than a quarter of a century, sequencing technologies from Sanger's method to next-generation high-throughput techniques have provided fascinating opportunities in the life sciences. The continuing upward trajectory of sequencing technologies will improve livestock research and expedite the development of various new genomic and technological studies with farm animals. The use of high-throughput technologies in livestock research has increased interest in metagenomics, epigenetics, genome-wide association studies, and identification of single nucleotide polymorphisms and copy number variations. Such studies are beginning to provide revolutionary insights into biological and evolutionary processes. Farm animals, such as cattle, swine, and horses, have played a dual role as economically and agriculturally important animals as well as biomedical research models. The first part of this study explores the current state of sequencing methods, many of which are already used in animal genomic studies, and the second part summarizes the state of cattle, swine, horse, and chicken genome sequencing and illustrates its achievements during the last few years. Finally, we describe several high-throughput sequencing approaches for the improved detection of known, unknown, and emerging infectious agents, leading to better diagnosis of infectious diseases. The insights from viral metagenomics and the advancement of next-generation sequencing will strongly support specific and efficient vaccine development and provide strategies for controlling infectious disease transmission among animal populations and/or between animals and humans. However, prospective sequencing technologies will require further research and in-field testing before reaching the marketplace.
Publication Date: 2018-04-10 PubMed ID: 29631431DOI: 10.1080/07388551.2018.1451819Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
  • Journal Article
  • Review

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research article discusses the transformation of animal genomics due to the advancement of next-generation sequencing technologies over the past decade, emphasizing on the impact these technologies have had on genetic understanding, improvements in livestock research, and developments in genomic and technological studies with farm animals.

Transformation of Animal Genomics

  • The research centers upon the fascinating opportunities made possible by sequencing technologies, which range from Sanger’s method to next-generation high-throughput techniques. These technologies have seen steady improvement and have proven pivotal in enriching the life sciences.
  • High-throughput sequencing technologies have sparked considerable interest in various aspects of animal genomics including metagenomics, epigenetics, genome-wide association studies, and the identification of single nucleotide polymorphisms and copy number variations.

Role of Farm Animals

  • The article highlights the dual role of farm animals such as cattle, swine, horses, and chickens. These animals are of economic and agricultural significance and simultaneously serve as biomedical research models. This dual role contributes to the exploration of biological and evolutionary processes.
  • The first part of the study delves into the existing state of sequencing methods, many of which have already found utility in animal genomic studies.
  • The second part provides a summary of cattle, swine, horse, and chicken genome sequencing and its accomplishments in recent years.

Improved Detection of Infectious Agents

  • Several high-throughput sequencing approaches are described in the research for the improved detection of both known and emerging infectious agents. This contributes to a more accurate diagnosis of infectious diseases.
  • Findings obtained from viral metagenomics, along with the progress of next-generation sequencing technologies, strongly support the development of specific and efficient vaccines. These can provide potential strategies for controlling the transmission of infectious diseases among animal populations and/or between animals and humans.
  • Despite the promising advancements, the authors note that prospective sequencing technologies will require additional research and in-field testing before they can reach the marketplace and be accepted for widespread use.

Cite This Article

APA
Ghosh M, Sharma N, Singh AK, Gera M, Pulicherla KK, Jeong DK. (2018). Transformation of animal genomics by next-generation sequencing technologies: a decade of challenges and their impact on genetic architecture. Crit Rev Biotechnol, 38(8), 1157-1175. https://doi.org/10.1080/07388551.2018.1451819

Publication

ISSN: 1549-7801
NlmUniqueID: 8505177
Country: England
Language: English
Volume: 38
Issue: 8
Pages: 1157-1175

Researcher Affiliations

Ghosh, Mrinmoy
  • a Department of Animal Biotechnology , Jeju National University , Jeju-Do , Republic of Korea.
Sharma, Neelesh
  • b Department of Veterinary Science and Animal Husbandry , Sher-e-Kashmir University of Agricultural Sciences and Technology , R.S. Pura , India.
Singh, Amit Kumar
  • a Department of Animal Biotechnology , Jeju National University , Jeju-Do , Republic of Korea.
Gera, Meeta
  • a Department of Animal Biotechnology , Jeju National University , Jeju-Do , Republic of Korea.
Pulicherla, Krishna Kanth
  • c Department of Science and Technology , Technology Development Transfer , New Delhi , India.
Jeong, Dong Kee
  • a Department of Animal Biotechnology , Jeju National University , Jeju-Do , Republic of Korea.

MeSH Terms

  • Animal Diseases / genetics
  • Animals
  • Genomics
  • Sequence Analysis / methods

Citations

This article has been cited 18 times.
  1. Das S, Biswas NK, Basu A. Mapinsights: deep exploration of quality issues and error profiles in high-throughput sequence data. Nucleic Acids Res 2023 Aug 11;51(14):e75.
    doi: 10.1093/nar/gkad539pubmed: 37378434google scholar: lookup
  2. Ogun OJ, Soremekun OS, Thaller G, Becker D. An In Silico Functional Analysis of Non-Synonymous Single-Nucleotide Polymorphisms of Bovine CMAH Gene and Potential Implication in Pathogenesis. Pathogens 2023 Apr 13;12(4).
    doi: 10.3390/pathogens12040591pubmed: 37111477google scholar: lookup
  3. Gaspar D, Usié A, Leão C, Guimarães S, Pires AE, Matos C, Ramos AM, Ginja C. Genome-wide assessment of the population structure and genetic diversity of four Portuguese native sheep breeds. Front Genet 2023;14:1109490.
    doi: 10.3389/fgene.2023.1109490pubmed: 36713074google scholar: lookup
  4. Cardinali I, Giontella A, Tommasi A, Silvestrelli M, Lancioni H. Unlocking Horse Y Chromosome Diversity. Genes (Basel) 2022 Dec 2;13(12).
    doi: 10.3390/genes13122272pubmed: 36553539google scholar: lookup
  5. Suminda GGD, Ghosh M, Son YO. The Innovative Informatics Approaches of High-Throughput Technologies in Livestock: Spearheading the Sustainability and Resiliency of Agrigenomics Research. Life (Basel) 2022 Nov 15;12(11).
    doi: 10.3390/life12111893pubmed: 36431028google scholar: lookup
  6. Amin MR, Pednekar DD, Azgomi HF, van Wietmarschen H, Aschbacher K, Faghih RT. Sparse System Identification of Leptin Dynamics in Women With Obesity. Front Endocrinol (Lausanne) 2022;13:769951.
    doi: 10.3389/fendo.2022.769951pubmed: 35480480google scholar: lookup
  7. Peng S, Bellone R, Petersen JL, Kalbfleisch TS, Finno CJ. Successful ATAC-Seq From Snap-Frozen Equine Tissues. Front Genet 2021;12:641788.
    doi: 10.3389/fgene.2021.641788pubmed: 34220931google scholar: lookup
  8. Li L, Liu H, Wen W, Huang C, Li X, Xiao S, Wu M, Shi J, Xu D. Full Transcriptome Analysis of Callus Suspension Culture System of Bletilla striata. Front Genet 2020;11:995.
    doi: 10.3389/fgene.2020.00995pubmed: 33193583google scholar: lookup
  9. Ghosh M, Gera M, Singh J, Prasad R, Pulicherla KK. A Comprehensive Investigation of Potential Novel Marine Psychrotolerant Actinomycetes sp. Isolated from the Bay-of-Bengal. Curr Genomics 2020 May;21(4):271-282.
  10. Arora I, Tollefsbol TO. Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications. Methods 2021 Mar;187:92-103.
    doi: 10.1016/j.ymeth.2020.09.008pubmed: 32941995google scholar: lookup
  11. Lustgarten JL, Zehnder A, Shipman W, Gancher E, Webb TL. Veterinary informatics: forging the future between veterinary medicine, human medicine, and One Health initiatives-a joint paper by the Association for Veterinary Informatics (AVI) and the CTSA One Health Alliance (COHA). JAMIA Open 2020 Jul;3(2):306-317.
    doi: 10.1093/jamiaopen/ooaa005pubmed: 32734172google scholar: lookup
  12. Wang H, Shen Z, Zhou X, Yang S, Yan F, He K, Zhao A. Identification of Differentially Expressed Genes in Different Types of Broiler Skeletal Muscle Fibers Using the RNA-seq Technique. Biomed Res Int 2020;2020:9478949.
    doi: 10.1155/2020/9478949pubmed: 32695825google scholar: lookup
  13. Raudsepp T, Finno CJ, Bellone RR, Petersen JL. Ten years of the horse reference genome: insights into equine biology, domestication and population dynamics in the post-genome era. Anim Genet 2019 Dec;50(6):569-597.
    doi: 10.1111/age.12857pubmed: 31568563google scholar: lookup
  14. Panigrahi M, Rajawat D, Nayak SS, Bose A, Bharia N, Singh S, Sharma A, Dutt T. Advancements in Animal Breeding: From Mendelian Genetics to Machine Learning. Int J Mol Sci 2025 Nov 24;26(23).
    doi: 10.3390/ijms262311352pubmed: 41373512google scholar: lookup
  15. Huang X, Xu C, Li S, Tan Y, Huang Y, Yin Z. Transcriptome and proteome profile analysis of the regulation of chicken ovarian development. Poult Sci 2025 Aug;104(8):105384.
    doi: 10.1016/j.psj.2025.105384pubmed: 40466268google scholar: lookup
  16. Han G (韩郭皓), Yang P (杨朋), Zhang Y (张永进), Li Q (李巧伟), Fan X (范新浩), Chen R (陈锐朴), Yan C (闫超), Zeng M (曾木), Yang Y (杨亚岚), Tang Z (唐中林). PIGOME: An Integrated and Comprehensive Multi-omics Database for Pig Functional Genomics Studies. Genomics Proteomics Bioinformatics 2025 May 10;23(1).
    doi: 10.1093/gpbjnl/qzaf016pubmed: 40036767google scholar: lookup
  17. Wu H, Cao H, Gao X, Shi C, Wang L, Gao B. The role of metagenomic next-generation sequencing in diagnosing and managing post-kidney transplantation infections. Front Cell Infect Microbiol 2024;14:1473068.
    doi: 10.3389/fcimb.2024.1473068pubmed: 39839264google scholar: lookup
  18. Lei L, Pan W, Shou X, Shao Y, Ye S, Zhang J, Kolliputi N, Shi L. Nanomaterials-assisted gene editing and synthetic biology for optimizing the treatment of pulmonary diseases. J Nanobiotechnology 2024 Jun 18;22(1):343.
    doi: 10.1186/s12951-024-02627-wpubmed: 38890749google scholar: lookup